02_mitgcm.ipynb

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    "# MITgcm Example \n",
    "\n",
    "xgcm is developed in close coordination with the [xmitgcm](http://xmitgcm.readthedocs.io/) package.\n",
    "The metadata in datasets constructed by xmitgcm should always be compatible with xgcm's expectations.\n",
    "xmitgcm is necessary for reading MITgcm's binary MDS file format.\n",
    "However, for this example, the MDS files have already been converted and saved as netCDF.\n",
    "\n",
    "Below are some example of how to make calculations on mitgcm-style datasets using xgcm.\n",
    "\n",
    "First we import xarray and xgcm:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import xarray as xr\n",
    "import numpy as np\n",
    "import xgcm\n",
    "from matplotlib import pyplot as plt\n",
    "%matplotlib inline\n",
    "plt.rcParams['figure.figsize'] = (10,6)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now we open the example dataset which is stored in a [zenodo archive](https://zenodo.org/record/4421428#.X_XP7y1h3x9)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
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       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt;\n",
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       "    drF      (Z) float32 50.0 70.0 100.0 140.0 190.0 ... 540.0 590.0 640.0 690.0\n",
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       "Data variables:\n",
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       "    VVEL     (time, Z, YG, XC) float32 0.0 0.0 0.0 0.0 0.0 ... 0.0 0.0 0.0 0.0\n",
       "    WVEL     (time, Zl, YC, XC) float32 0.0 0.0 0.0 0.0 0.0 ... 0.0 0.0 0.0 0.0\n",
       "    SALT     (time, Z, YC, XC) float32 0.0 0.0 0.0 0.0 0.0 ... 0.0 0.0 0.0 0.0\n",
       "    THETA    (time, Z, YC, XC) float32 0.0 0.0 0.0 0.0 0.0 ... 0.0 0.0 0.0 0.0\n",
       "    PH       (time, Z, YC, XC) float32 -8.3 -8.3 -8.3 ... -470.8 -202.8\n",
       "    Eta      (time, YC, XC) float32 0.0 0.0 0.0 0.0 ... -0.6293 -0.6234 -0.649\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(extra_metadata=None, ll...</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-72a286d4-0053-4829-95e8-15dd43697988' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-72a286d4-0053-4829-95e8-15dd43697988' 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'>XC</span>: 90</li><li><span class='xr-has-index'>XG</span>: 90</li><li><span class='xr-has-index'>YC</span>: 40</li><li><span class='xr-has-index'>YG</span>: 40</li><li><span class='xr-has-index'>Z</span>: 15</li><li><span class='xr-has-index'>Zl</span>: 15</li><li><span class='xr-has-index'>time</span>: 1</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-accfcb77-e81a-4e2e-855d-924eeaa347a0' class='xr-section-summary-in' type='checkbox'  ><label for='section-accfcb77-e81a-4e2e-855d-924eeaa347a0' class='xr-section-summary' >Coordinates: <span>(25)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>timedelta64[ns]</div><div class='xr-var-preview xr-preview'>11:00:00</div><input id='attrs-61229a7d-e8f9-4855-a770-eae1147af6ac' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-61229a7d-e8f9-4855-a770-eae1147af6ac' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e0c0d328-5028-49aa-aa24-dafb2d0fb074' class='xr-var-data-in' type='checkbox'><label for='data-e0c0d328-5028-49aa-aa24-dafb2d0fb074' 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([39600000000000], dtype=&#x27;timedelta64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>maskC</span></div><div class='xr-var-dims'>(Z, YC, XC)</div><div class='xr-var-dtype'>bool</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-ddf06bbc-80d6-46ab-8a58-487b9b6c89a3' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ddf06bbc-80d6-46ab-8a58-487b9b6c89a3' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-982a2422-8343-415a-92ef-879466378501' class='xr-var-data-in' type='checkbox'><label for='data-982a2422-8343-415a-92ef-879466378501' 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>sea_binary_mask_at_t_location</dd><dt><span>long_name :</span></dt><dd>mask denoting wet point at center</dd></dl></div><div class='xr-var-data'><pre>array([[[False, False, ..., False, False],\n",
       "        [False, False, ..., False, False],\n",
       "        ...,\n",
       "        [ True,  True, ...,  True,  True],\n",
       "        [ True,  True, ...,  True,  True]],\n",
       "\n",
       "       [[False, False, ..., False, False],\n",
       "        [False, False, ..., False, False],\n",
       "        ...,\n",
       "        [ True,  True, ...,  True,  True],\n",
       "        [ True,  True, ...,  True,  True]],\n",
       "\n",
       "       ...,\n",
       "\n",
       "       [[False, False, ..., False, False],\n",
       "        [False, False, ..., False, False],\n",
       "        ...,\n",
       "        [False, False, ..., False, False],\n",
       "        [False, False, ..., False, False]],\n",
       "\n",
       "       [[False, False, ..., False, False],\n",
       "        [False, False, ..., False, False],\n",
       "        ...,\n",
       "        [False, False, ..., False, False],\n",
       "        [False, False, ..., False, False]]])</pre></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'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-64e1f845-4714-4681-828a-315073e187ae' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-64e1f845-4714-4681-828a-315073e187ae' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-049507eb-9202-4f52-8597-fc05a6293f0b' class='xr-var-data-in' type='checkbox'><label for='data-049507eb-9202-4f52-8597-fc05a6293f0b' 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'><pre>array([[444709.9, 444709.9, 444709.9, ..., 444709.9, 444709.9, 444709.9],\n",
       "       [444709.9, 444709.9, 444709.9, ..., 444709.9, 444709.9, 444709.9],\n",
       "       [444709.9, 444709.9, 444709.9, ..., 444709.9, 444709.9, 444709.9],\n",
       "       ...,\n",
       "       [444709.9, 444709.9, 444709.9, ..., 444709.9, 444709.9, 444709.9],\n",
       "       [444709.9, 444709.9, 444709.9, ..., 444709.9, 444709.9, 444709.9],\n",
       "       [444709.9, 444709.9, 444709.9, ..., 444709.9, 444709.9, 444709.9]],\n",
       "      dtype=float32)</pre></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'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-c29ef024-503f-4a74-953c-dc39f68ddaa7' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-c29ef024-503f-4a74-953c-dc39f68ddaa7' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9bf62580-39d2-482d-9d03-16d6e88d0f39' class='xr-var-data-in' type='checkbox'><label for='data-9bf62580-39d2-482d-9d03-16d6e88d0f39' 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'><pre>array([[[0., 0., ..., 0., 0.],\n",
       "        [0., 0., ..., 0., 0.],\n",
       "        ...,\n",
       "        [1., 1., ..., 1., 1.],\n",
       "        [1., 1., ..., 1., 1.]],\n",
       "\n",
       "       [[0., 0., ..., 0., 0.],\n",
       "        [0., 0., ..., 0., 0.],\n",
       "        ...,\n",
       "        [1., 1., ..., 1., 1.],\n",
       "        [1., 1., ..., 1., 1.]],\n",
       "\n",
       "       ...,\n",
       "\n",
       "       [[0., 0., ..., 0., 0.],\n",
       "        [0., 0., ..., 0., 0.],\n",
       "        ...,\n",
       "        [0., 0., ..., 0., 0.],\n",
       "        [0., 0., ..., 0., 0.]],\n",
       "\n",
       "       [[0., 0., ..., 0., 0.],\n",
       "        [0., 0., ..., 0., 0.],\n",
       "        ...,\n",
       "        [0., 0., ..., 0., 0.],\n",
       "        [0., 0., ..., 0., 0.]]], 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'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-3b41b33e-6bed-4fa2-9eed-0a5f165c60ad' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3b41b33e-6bed-4fa2-9eed-0a5f165c60ad' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-740589a3-f500-489f-bff2-3d16abc0617f' class='xr-var-data-in' type='checkbox'><label for='data-740589a3-f500-489f-bff2-3d16abc0617f' 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'><pre>array([[4.110970e+10, 4.110970e+10, 4.110970e+10, ..., 4.110970e+10,\n",
       "        4.110970e+10, 4.110970e+10],\n",
       "       [5.450087e+10, 5.450087e+10, 5.450087e+10, ..., 5.450087e+10,\n",
       "        5.450087e+10, 5.450087e+10],\n",
       "       [6.762652e+10, 6.762652e+10, 6.762652e+10, ..., 6.762652e+10,\n",
       "        6.762652e+10, 6.762652e+10],\n",
       "       ...,\n",
       "       [6.762652e+10, 6.762652e+10, 6.762652e+10, ..., 6.762652e+10,\n",
       "        6.762652e+10, 6.762652e+10],\n",
       "       [5.450087e+10, 5.450087e+10, 5.450087e+10, ..., 5.450087e+10,\n",
       "        5.450087e+10, 5.450087e+10],\n",
       "       [4.110970e+10, 4.110970e+10, 4.110970e+10, ..., 4.110970e+10,\n",
       "        4.110970e+10, 4.110970e+10]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>hFacS</span></div><div class='xr-var-dims'>(Z, YG, XC)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-60904eee-a1f2-480f-9e52-a9ecfc3917c0' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-60904eee-a1f2-480f-9e52-a9ecfc3917c0' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-72d19e71-71f0-4d69-9994-45669850d324' class='xr-var-data-in' type='checkbox'><label for='data-72d19e71-71f0-4d69-9994-45669850d324' 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_at_v_location</dd><dt><span>long_name :</span></dt><dd>vertical fraction of open cell</dd></dl></div><div class='xr-var-data'><pre>array([[[0., 0., ..., 0., 0.],\n",
       "        [0., 0., ..., 0., 0.],\n",
       "        ...,\n",
       "        [1., 1., ..., 1., 1.],\n",
       "        [1., 1., ..., 1., 1.]],\n",
       "\n",
       "       [[0., 0., ..., 0., 0.],\n",
       "        [0., 0., ..., 0., 0.],\n",
       "        ...,\n",
       "        [1., 1., ..., 1., 1.],\n",
       "        [1., 1., ..., 1., 1.]],\n",
       "\n",
       "       ...,\n",
       "\n",
       "       [[0., 0., ..., 0., 0.],\n",
       "        [0., 0., ..., 0., 0.],\n",
       "        ...,\n",
       "        [0., 0., ..., 0., 0.],\n",
       "        [0., 0., ..., 0., 0.]],\n",
       "\n",
       "       [[0., 0., ..., 0., 0.],\n",
       "        [0., 0., ..., 0., 0.],\n",
       "        ...,\n",
       "        [0., 0., ..., 0., 0.],\n",
       "        [0., 0., ..., 0., 0.]]], dtype=float32)</pre></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'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-155c9ae0-ddd0-4491-9b05-4b0efc446e2c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-155c9ae0-ddd0-4491-9b05-4b0efc446e2c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0a80dc64-7c8a-49e0-b44b-52f2c7acda31' class='xr-var-data-in' type='checkbox'><label for='data-0a80dc64-7c8a-49e0-b44b-52f2c7acda31' 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'><pre>array([[   0. ,    0. ,    0. , ...,    0. ,    0. ,    0. ],\n",
       "       [   0. ,    0. ,    0. , ...,    0. ,    0. ,    0. ],\n",
       "       [3740. , 3671.5, 1732.5, ..., 3821. , 4047.5, 4047.5],\n",
       "       ...,\n",
       "       [2144. , 2214.5, 2414. , ..., 1586.5, 2703. , 2048.5],\n",
       "       [2995. , 2414. , 2414. , ..., 1183. , 1569.5, 2995. ],\n",
       "       [2995. , 2354.5, 2087. , ...,  187.5, 1917. , 2995. ]], 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'>float32</div><div class='xr-var-preview xr-preview'>-80.0 -76.0 -72.0 ... 72.0 76.0</div><input id='attrs-48402fee-d094-4039-8939-190e934eb5d8' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-48402fee-d094-4039-8939-190e934eb5d8' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-fb32b1c7-3e4b-4adf-bb41-ed214c3ad5eb' class='xr-var-data-in' type='checkbox'><label for='data-fb32b1c7-3e4b-4adf-bb41-ed214c3ad5eb' 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>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([-80., -76., -72., -68., -64., -60., -56., -52., -48., -44., -40., -36.,\n",
       "       -32., -28., -24., -20., -16., -12.,  -8.,  -4.,   0.,   4.,   8.,  12.,\n",
       "        16.,  20.,  24.,  28.,  32.,  36.,  40.,  44.,  48.,  52.,  56.,  60.,\n",
       "        64.,  68.,  72.,  76.], 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'>float32</div><div class='xr-var-preview xr-preview'>-25.0 -85.0 ... -4.855e+03</div><input id='attrs-c73c42a6-f791-4860-b82f-11dc26a54f17' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-c73c42a6-f791-4860-b82f-11dc26a54f17' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f44d9cd4-e10c-4603-b0a9-e328b25fd2c3' class='xr-var-data-in' type='checkbox'><label for='data-f44d9cd4-e10c-4603-b0a9-e328b25fd2c3' 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([  -25.,   -85.,  -170.,  -290.,  -455.,  -670.,  -935., -1250., -1615.,\n",
       "       -2030., -2495., -3010., -3575., -4190., -4855.], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>PHrefC</span></div><div class='xr-var-dims'>(Z)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-f35c0ae2-a36d-44d1-ad26-ca35aafb08bd' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f35c0ae2-a36d-44d1-ad26-ca35aafb08bd' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-41aae8ca-7f0b-49bd-b648-52a43b7967d9' class='xr-var-data-in' type='checkbox'><label for='data-41aae8ca-7f0b-49bd-b648-52a43b7967d9' 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_reference_pressure</dd><dt><span>long_name :</span></dt><dd>Reference Hydrostatic Pressure</dd><dt><span>units :</span></dt><dd>m2 s-2</dd></dl></div><div class='xr-var-data'><pre>array([  245.25,   833.85,  1667.7 ,  2844.9 ,  4463.55,  6572.7 ,  9172.35,\n",
       "       12262.5 , 15843.15, 19914.3 , 24475.95, 29528.1 , 35070.75, 41103.9 ,\n",
       "       47627.55], dtype=float32)</pre></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'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-7a9c201a-38fb-4aa0-a9ee-a3c6fbe082eb' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-7a9c201a-38fb-4aa0-a9ee-a3c6fbe082eb' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-575a080f-a4df-4fd4-8785-c9dbcc8432b0' class='xr-var-data-in' type='checkbox'><label for='data-575a080f-a4df-4fd4-8785-c9dbcc8432b0' 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'><pre>array([[444709.9, 444709.9, 444709.9, ..., 444709.9, 444709.9, 444709.9],\n",
       "       [444709.9, 444709.9, 444709.9, ..., 444709.9, 444709.9, 444709.9],\n",
       "       [444709.9, 444709.9, 444709.9, ..., 444709.9, 444709.9, 444709.9],\n",
       "       ...,\n",
       "       [444709.9, 444709.9, 444709.9, ..., 444709.9, 444709.9, 444709.9],\n",
       "       [444709.9, 444709.9, 444709.9, ..., 444709.9, 444709.9, 444709.9],\n",
       "       [444709.9, 444709.9, 444709.9, ..., 444709.9, 444709.9, 444709.9]],\n",
       "      dtype=float32)</pre></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'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-e30e9b79-ac46-493f-989c-844742c2c848' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e30e9b79-ac46-493f-989c-844742c2c848' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8da2f932-dce2-4b04-8be0-d75c90e9db73' class='xr-var-data-in' type='checkbox'><label for='data-8da2f932-dce2-4b04-8be0-d75c90e9db73' 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'><pre>array([[4.110970e+10, 4.110970e+10, 4.110970e+10, ..., 4.110970e+10,\n",
       "        4.110970e+10, 4.110970e+10],\n",
       "       [5.450087e+10, 5.450087e+10, 5.450087e+10, ..., 5.450087e+10,\n",
       "        5.450087e+10, 5.450087e+10],\n",
       "       [6.762652e+10, 6.762652e+10, 6.762652e+10, ..., 6.762652e+10,\n",
       "        6.762652e+10, 6.762652e+10],\n",
       "       ...,\n",
       "       [6.762652e+10, 6.762652e+10, 6.762652e+10, ..., 6.762652e+10,\n",
       "        6.762652e+10, 6.762652e+10],\n",
       "       [5.450087e+10, 5.450087e+10, 5.450087e+10, ..., 5.450087e+10,\n",
       "        5.450087e+10, 5.450087e+10],\n",
       "       [4.110970e+10, 4.110970e+10, 4.110970e+10, ..., 4.110970e+10,\n",
       "        4.110970e+10, 4.110970e+10]], dtype=float32)</pre></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'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-aa64ee4a-b8db-4ef9-b5c5-d83b3f0c4711' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-aa64ee4a-b8db-4ef9-b5c5-d83b3f0c4711' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b5a06418-1cd1-4754-92ee-eeb336efbf95' class='xr-var-data-in' type='checkbox'><label for='data-b5a06418-1cd1-4754-92ee-eeb336efbf95' 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'><pre>array([ 50.,  70., 100., 140., 190., 240., 290., 340., 390., 440., 490., 540.,\n",
       "       590., 640., 690.], 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'>float32</div><div class='xr-var-preview xr-preview'>-78.0 -74.0 -70.0 ... 74.0 78.0</div><input id='attrs-ce951f13-c593-4ba0-bdcc-39c11f3166e8' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ce951f13-c593-4ba0-bdcc-39c11f3166e8' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-adc0f007-2dd3-4c8b-a59d-2c76dc7248f8' class='xr-var-data-in' type='checkbox'><label for='data-adc0f007-2dd3-4c8b-a59d-2c76dc7248f8' 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([-78., -74., -70., -66., -62., -58., -54., -50., -46., -42., -38., -34.,\n",
       "       -30., -26., -22., -18., -14., -10.,  -6.,  -2.,   2.,   6.,  10.,  14.,\n",
       "        18.,  22.,  26.,  30.,  34.,  38.,  42.,  46.,  50.,  54.,  58.,  62.,\n",
       "        66.,  70.,  74.,  78.], dtype=float32)</pre></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'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-5a39974e-5457-4aee-9ff5-78d13377ac24' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-5a39974e-5457-4aee-9ff5-78d13377ac24' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4d1071c6-81ea-495a-a93b-023cccfdda96' class='xr-var-data-in' type='checkbox'><label for='data-4d1071c6-81ea-495a-a93b-023cccfdda96' 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'><pre>array([[ 77223.06,  77223.06,  77223.06, ...,  77223.06,  77223.06,  77223.06],\n",
       "       [107585.06, 107585.06, 107585.06, ..., 107585.06, 107585.06, 107585.06],\n",
       "       [137422.92, 137422.92, 137422.92, ..., 137422.92, 137422.92, 137422.92],\n",
       "       ...,\n",
       "       [166591.27, 166591.27, 166591.27, ..., 166591.27, 166591.27, 166591.27],\n",
       "       [137422.92, 137422.92, 137422.92, ..., 137422.92, 137422.92, 137422.92],\n",
       "       [107585.06, 107585.06, 107585.06, ..., 107585.06, 107585.06, 107585.06]],\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'>float32</div><div class='xr-var-preview xr-preview'>0.0 4.0 8.0 ... 348.0 352.0 356.0</div><input id='attrs-0236bbbc-4563-4791-a1bd-affdb0a8161b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-0236bbbc-4563-4791-a1bd-affdb0a8161b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-960da1a9-133c-4a71-87f3-576f4e97f939' class='xr-var-data-in' type='checkbox'><label for='data-960da1a9-133c-4a71-87f3-576f4e97f939' 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([  0.,   4.,   8.,  12.,  16.,  20.,  24.,  28.,  32.,  36.,  40.,  44.,\n",
       "        48.,  52.,  56.,  60.,  64.,  68.,  72.,  76.,  80.,  84.,  88.,  92.,\n",
       "        96., 100., 104., 108., 112., 116., 120., 124., 128., 132., 136., 140.,\n",
       "       144., 148., 152., 156., 160., 164., 168., 172., 176., 180., 184., 188.,\n",
       "       192., 196., 200., 204., 208., 212., 216., 220., 224., 228., 232., 236.,\n",
       "       240., 244., 248., 252., 256., 260., 264., 268., 272., 276., 280., 284.,\n",
       "       288., 292., 296., 300., 304., 308., 312., 316., 320., 324., 328., 332.,\n",
       "       336., 340., 344., 348., 352., 356.], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>iter</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-e609efc4-98c2-41ca-96cb-8df291167d1f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e609efc4-98c2-41ca-96cb-8df291167d1f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a127ab83-58f7-4847-ab59-9a0192b81623' class='xr-var-data-in' type='checkbox'><label for='data-a127ab83-58f7-4847-ab59-9a0192b81623' 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'><pre>array([39600])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>maskW</span></div><div class='xr-var-dims'>(Z, YC, XG)</div><div class='xr-var-dtype'>bool</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-d32bdb09-82fe-4acc-b703-7474ef735ef5' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d32bdb09-82fe-4acc-b703-7474ef735ef5' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f2c4a124-d2e2-415f-a3e6-dc3cf55355e3' class='xr-var-data-in' type='checkbox'><label for='data-f2c4a124-d2e2-415f-a3e6-dc3cf55355e3' 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_at_u_location</dd><dt><span>long_name :</span></dt><dd>mask denoting wet point at interface</dd></dl></div><div class='xr-var-data'><pre>array([[[False, False, ..., False, False],\n",
       "        [False, False, ..., False, False],\n",
       "        ...,\n",
       "        [ True,  True, ...,  True,  True],\n",
       "        [ True,  True, ...,  True,  True]],\n",
       "\n",
       "       [[False, False, ..., False, False],\n",
       "        [False, False, ..., False, False],\n",
       "        ...,\n",
       "        [ True,  True, ...,  True,  True],\n",
       "        [ True,  True, ...,  True,  True]],\n",
       "\n",
       "       ...,\n",
       "\n",
       "       [[False, False, ..., False, False],\n",
       "        [False, False, ..., False, False],\n",
       "        ...,\n",
       "        [False, False, ..., False, False],\n",
       "        [False, False, ..., False, False]],\n",
       "\n",
       "       [[False, False, ..., False, False],\n",
       "        [False, False, ..., False, False],\n",
       "        ...,\n",
       "        [False, False, ..., False, False],\n",
       "        [False, False, ..., False, False]]])</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'>float32</div><div class='xr-var-preview xr-preview'>0.0 -50.0 ... -3.87e+03 -4.51e+03</div><input id='attrs-8ecfeae7-32a4-41e4-9c9f-292c32228e87' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-8ecfeae7-32a4-41e4-9c9f-292c32228e87' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-daf171f3-9f91-461c-b66c-06143dcc09cb' class='xr-var-data-in' type='checkbox'><label for='data-daf171f3-9f91-461c-b66c-06143dcc09cb' 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([    0.,   -50.,  -120.,  -220.,  -360.,  -550.,  -790., -1080., -1420.,\n",
       "       -1810., -2250., -2740., -3280., -3870., -4510.], dtype=float32)</pre></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'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-0c93ed7d-4916-4bd9-99a9-e08f532c1de8' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-0c93ed7d-4916-4bd9-99a9-e08f532c1de8' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-61cd9f08-5e6f-4ac5-9999-1ef10f370849' class='xr-var-data-in' type='checkbox'><label for='data-61cd9f08-5e6f-4ac5-9999-1ef10f370849' 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></dl></div><div class='xr-var-data'><pre>array([[3.433489e+10, 3.433489e+10, 3.433489e+10, ..., 3.433489e+10,\n",
       "        3.433489e+10, 3.433489e+10],\n",
       "       [4.783442e+10, 4.783442e+10, 4.783442e+10, ..., 4.783442e+10,\n",
       "        4.783442e+10, 4.783442e+10],\n",
       "       [6.110092e+10, 6.110092e+10, 6.110092e+10, ..., 6.110092e+10,\n",
       "        6.110092e+10, 6.110092e+10],\n",
       "       ...,\n",
       "       [7.406974e+10, 7.406974e+10, 7.406974e+10, ..., 7.406974e+10,\n",
       "        7.406974e+10, 7.406974e+10],\n",
       "       [6.110092e+10, 6.110092e+10, 6.110092e+10, ..., 6.110092e+10,\n",
       "        6.110092e+10, 6.110092e+10],\n",
       "       [4.783442e+10, 4.783442e+10, 4.783442e+10, ..., 4.783442e+10,\n",
       "        4.783442e+10, 4.783442e+10]], dtype=float32)</pre></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'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-007244ec-ae9d-4bf9-b28e-9d25cccf4874' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-007244ec-ae9d-4bf9-b28e-9d25cccf4874' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5d26ec0e-73dc-40e4-aa48-69ce97d91770' class='xr-var-data-in' type='checkbox'><label for='data-5d26ec0e-73dc-40e4-aa48-69ce97d91770' 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'><pre>array([[3.433489e+10, 3.433489e+10, 3.433489e+10, ..., 3.433489e+10,\n",
       "        3.433489e+10, 3.433489e+10],\n",
       "       [4.783442e+10, 4.783442e+10, 4.783442e+10, ..., 4.783442e+10,\n",
       "        4.783442e+10, 4.783442e+10],\n",
       "       [6.110092e+10, 6.110092e+10, 6.110092e+10, ..., 6.110092e+10,\n",
       "        6.110092e+10, 6.110092e+10],\n",
       "       ...,\n",
       "       [7.406974e+10, 7.406974e+10, 7.406974e+10, ..., 7.406974e+10,\n",
       "        7.406974e+10, 7.406974e+10],\n",
       "       [6.110092e+10, 6.110092e+10, 6.110092e+10, ..., 6.110092e+10,\n",
       "        6.110092e+10, 6.110092e+10],\n",
       "       [4.783442e+10, 4.783442e+10, 4.783442e+10, ..., 4.783442e+10,\n",
       "        4.783442e+10, 4.783442e+10]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>maskS</span></div><div class='xr-var-dims'>(Z, YG, XC)</div><div class='xr-var-dtype'>bool</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-f0b977e2-a927-4302-82a3-93e2d0b3a45c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f0b977e2-a927-4302-82a3-93e2d0b3a45c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3476522e-f5eb-4cdc-bbf3-c4cf07a10ae0' class='xr-var-data-in' type='checkbox'><label for='data-3476522e-f5eb-4cdc-bbf3-c4cf07a10ae0' 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_at_v_location</dd><dt><span>long_name :</span></dt><dd>mask denoting wet point at interface</dd></dl></div><div class='xr-var-data'><pre>array([[[False, False, ..., False, False],\n",
       "        [False, False, ..., False, False],\n",
       "        ...,\n",
       "        [ True,  True, ...,  True,  True],\n",
       "        [ True,  True, ...,  True,  True]],\n",
       "\n",
       "       [[False, False, ..., False, False],\n",
       "        [False, False, ..., False, False],\n",
       "        ...,\n",
       "        [ True,  True, ...,  True,  True],\n",
       "        [ True,  True, ...,  True,  True]],\n",
       "\n",
       "       ...,\n",
       "\n",
       "       [[False, False, ..., False, False],\n",
       "        [False, False, ..., False, False],\n",
       "        ...,\n",
       "        [False, False, ..., False, False],\n",
       "        [False, False, ..., False, False]],\n",
       "\n",
       "       [[False, False, ..., False, False],\n",
       "        [False, False, ..., False, False],\n",
       "        ...,\n",
       "        [False, False, ..., False, False],\n",
       "        [False, False, ..., False, False]]])</pre></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'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-1a0113ae-e435-4432-85d2-7f3041e69c5e' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-1a0113ae-e435-4432-85d2-7f3041e69c5e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0c9972a2-48b3-4c61-a115-60ae76292afb' class='xr-var-data-in' type='checkbox'><label for='data-0c9972a2-48b3-4c61-a115-60ae76292afb' 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'><pre>array([[ 92460.38,  92460.38,  92460.38, ...,  92460.38,  92460.38,  92460.38],\n",
       "       [122578.66, 122578.66, 122578.66, ..., 122578.66, 122578.66, 122578.66],\n",
       "       [152099.73, 152099.73, 152099.73, ..., 152099.73, 152099.73, 152099.73],\n",
       "       ...,\n",
       "       [152099.73, 152099.73, 152099.73, ..., 152099.73, 152099.73, 152099.73],\n",
       "       [122578.66, 122578.66, 122578.66, ..., 122578.66, 122578.66, 122578.66],\n",
       "       [ 92460.38,  92460.38,  92460.38, ...,  92460.38,  92460.38,  92460.38]],\n",
       "      dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>hFacW</span></div><div class='xr-var-dims'>(Z, YC, XG)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-96167200-3ab6-45c9-8b0f-a264742a487e' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-96167200-3ab6-45c9-8b0f-a264742a487e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-de6a3698-4ed2-44e6-932a-52fae73d8223' class='xr-var-data-in' type='checkbox'><label for='data-de6a3698-4ed2-44e6-932a-52fae73d8223' 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_at_u_location</dd><dt><span>long_name :</span></dt><dd>vertical fraction of open cell</dd></dl></div><div class='xr-var-data'><pre>array([[[0., 0., ..., 0., 0.],\n",
       "        [0., 0., ..., 0., 0.],\n",
       "        ...,\n",
       "        [1., 1., ..., 1., 1.],\n",
       "        [1., 1., ..., 1., 1.]],\n",
       "\n",
       "       [[0., 0., ..., 0., 0.],\n",
       "        [0., 0., ..., 0., 0.],\n",
       "        ...,\n",
       "        [1., 1., ..., 1., 1.],\n",
       "        [1., 1., ..., 1., 1.]],\n",
       "\n",
       "       ...,\n",
       "\n",
       "       [[0., 0., ..., 0., 0.],\n",
       "        [0., 0., ..., 0., 0.],\n",
       "        ...,\n",
       "        [0., 0., ..., 0., 0.],\n",
       "        [0., 0., ..., 0., 0.]],\n",
       "\n",
       "       [[0., 0., ..., 0., 0.],\n",
       "        [0., 0., ..., 0., 0.],\n",
       "        ...,\n",
       "        [0., 0., ..., 0., 0.],\n",
       "        [0., 0., ..., 0., 0.]]], dtype=float32)</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'>float32</div><div class='xr-var-preview xr-preview'>2.0 6.0 10.0 ... 350.0 354.0 358.0</div><input id='attrs-8e18d524-8bb4-4776-b62a-3160e57c10fe' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-8e18d524-8bb4-4776-b62a-3160e57c10fe' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-29308dab-d3ae-498e-a1ec-53da593c0600' class='xr-var-data-in' type='checkbox'><label for='data-29308dab-d3ae-498e-a1ec-53da593c0600' 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([  2.,   6.,  10.,  14.,  18.,  22.,  26.,  30.,  34.,  38.,  42.,  46.,\n",
       "        50.,  54.,  58.,  62.,  66.,  70.,  74.,  78.,  82.,  86.,  90.,  94.,\n",
       "        98., 102., 106., 110., 114., 118., 122., 126., 130., 134., 138., 142.,\n",
       "       146., 150., 154., 158., 162., 166., 170., 174., 178., 182., 186., 190.,\n",
       "       194., 198., 202., 206., 210., 214., 218., 222., 226., 230., 234., 238.,\n",
       "       242., 246., 250., 254., 258., 262., 266., 270., 274., 278., 282., 286.,\n",
       "       290., 294., 298., 302., 306., 310., 314., 318., 322., 326., 330., 334.,\n",
       "       338., 342., 346., 350., 354., 358.], dtype=float32)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-87b2e04f-0b70-4a64-adf9-c1138177a8f8' class='xr-section-summary-in' type='checkbox'  checked><label for='section-87b2e04f-0b70-4a64-adf9-c1138177a8f8' class='xr-section-summary' >Data variables: <span>(7)</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'>...</div><input id='attrs-ab7bfc99-c2fb-4e22-b3bd-14853482d687' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ab7bfc99-c2fb-4e22-b3bd-14853482d687' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-396e52b9-b422-47a8-af3d-261a6432e15a' class='xr-var-data-in' type='checkbox'><label for='data-396e52b9-b422-47a8-af3d-261a6432e15a' 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'><pre>array([[[[ 0.      , ...,  0.      ],\n",
       "         ...,\n",
       "         [-0.005508, ..., -0.00823 ]],\n",
       "\n",
       "        ...,\n",
       "\n",
       "        [[ 0.      , ...,  0.      ],\n",
       "         ...,\n",
       "         [ 0.      , ...,  0.      ]]]], dtype=float32)</pre></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'>...</div><input id='attrs-e2031086-ff5f-40bd-b5a9-c19ea46a30ff' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e2031086-ff5f-40bd-b5a9-c19ea46a30ff' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e55739ca-758f-44b3-afa6-bfc77bb8b8bc' class='xr-var-data-in' type='checkbox'><label for='data-e55739ca-758f-44b3-afa6-bfc77bb8b8bc' 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'><pre>array([[[[ 0.      , ...,  0.      ],\n",
       "         ...,\n",
       "         [ 0.003407, ..., -0.002983]],\n",
       "\n",
       "        ...,\n",
       "\n",
       "        [[ 0.      , ...,  0.      ],\n",
       "         ...,\n",
       "         [ 0.      , ...,  0.      ]]]], dtype=float32)</pre></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'>...</div><input id='attrs-a0c3041e-3c2a-4b28-b0e4-34cca9117852' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a0c3041e-3c2a-4b28-b0e4-34cca9117852' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-052d47a2-377a-481b-abe0-6ac465d82e2c' class='xr-var-data-in' type='checkbox'><label for='data-052d47a2-377a-481b-abe0-6ac465d82e2c' 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'><pre>array([[[[ 0.000000e+00, ...,  0.000000e+00],\n",
       "         ...,\n",
       "         [ 2.502884e-09, ..., -1.597719e-09]],\n",
       "\n",
       "        ...,\n",
       "\n",
       "        [[ 0.000000e+00, ...,  0.000000e+00],\n",
       "         ...,\n",
       "         [ 0.000000e+00, ...,  0.000000e+00]]]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>SALT</span></div><div class='xr-var-dims'>(time, Z, YC, XC)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-0baf521a-8938-408e-9454-3945345b5241' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-0baf521a-8938-408e-9454-3945345b5241' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ff80b0e1-fd91-415b-87c9-d8e6a8de8d5d' class='xr-var-data-in' type='checkbox'><label for='data-ff80b0e1-fd91-415b-87c9-d8e6a8de8d5d' 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>SALT</dd><dt><span>long_name :</span></dt><dd>Salinity</dd><dt><span>units :</span></dt><dd>psu</dd></dl></div><div class='xr-var-data'><pre>array([[[[ 0.      , ...,  0.      ],\n",
       "         ...,\n",
       "         [34.48869 , ..., 34.226387]],\n",
       "\n",
       "        ...,\n",
       "\n",
       "        [[ 0.      , ...,  0.      ],\n",
       "         ...,\n",
       "         [ 0.      , ...,  0.      ]]]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>THETA</span></div><div class='xr-var-dims'>(time, Z, YC, XC)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-caad1ad6-b209-4e63-8d92-54260c7b3a75' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-caad1ad6-b209-4e63-8d92-54260c7b3a75' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-36f6bae4-648f-409f-ba54-7d23ef360e2e' class='xr-var-data-in' type='checkbox'><label for='data-36f6bae4-648f-409f-ba54-7d23ef360e2e' 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>THETA</dd><dt><span>long_name :</span></dt><dd>Potential Temperature</dd><dt><span>units :</span></dt><dd>degC</dd></dl></div><div class='xr-var-data'><pre>array([[[[ 0.      , ...,  0.      ],\n",
       "         ...,\n",
       "         [ 0.010286, ..., -0.237801]],\n",
       "\n",
       "        ...,\n",
       "\n",
       "        [[ 0.      , ...,  0.      ],\n",
       "         ...,\n",
       "         [ 0.      , ...,  0.      ]]]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>PH</span></div><div class='xr-var-dims'>(time, Z, YC, XC)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-cc94d543-13eb-41a5-a1cf-598430e6cd34' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-cc94d543-13eb-41a5-a1cf-598430e6cd34' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-764d92d5-6c76-4c5d-a0eb-6559e3c9f92e' class='xr-var-data-in' type='checkbox'><label for='data-764d92d5-6c76-4c5d-a0eb-6559e3c9f92e' 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>sea_water_dynamic_pressue</dd><dt><span>long_name :</span></dt><dd>Hydrostatic Pressure Pot.(p/rho) Anomaly</dd><dt><span>units :</span></dt><dd>m2 s-2</dd></dl></div><div class='xr-var-data'><pre>array([[[[   -8.300195, ...,    -8.300195],\n",
       "         ...,\n",
       "         [   -8.130636, ...,    -8.112844]],\n",
       "\n",
       "        ...,\n",
       "\n",
       "        [[-1062.0314  , ..., -1062.0314  ],\n",
       "         ...,\n",
       "         [ -202.76265 , ...,  -202.77208 ]]]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Eta</span></div><div class='xr-var-dims'>(time, YC, XC)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-534ff762-a33e-4292-8b70-75e9554383e0' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-534ff762-a33e-4292-8b70-75e9554383e0' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-206ea36f-899e-42bb-b979-4ce8f149866b' class='xr-var-data-in' type='checkbox'><label for='data-206ea36f-899e-42bb-b979-4ce8f149866b' 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>ETAN</dd><dt><span>long_name :</span></dt><dd>Surface Height Anomaly</dd><dt><span>units :</span></dt><dd>m</dd></dl></div><div class='xr-var-data'><pre>array([[[ 0.      ,  0.      , ...,  0.      ,  0.      ],\n",
       "        [ 0.      ,  0.      , ...,  0.      ,  0.      ],\n",
       "        ...,\n",
       "        [-0.702411, -0.694586, ..., -0.694789, -0.709546],\n",
       "        [-0.656158, -0.659816, ..., -0.623395, -0.649   ]]], dtype=float32)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-fd77a38d-3d65-435a-9f60-996c7793611b' class='xr-section-summary-in' type='checkbox'  checked><label for='section-fd77a38d-3d65-435a-9f60-996c7793611b' class='xr-section-summary' >Attributes: <span>(4)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>Conventions :</span></dt><dd>CF-1.6</dd><dt><span>title :</span></dt><dd>netCDF wrapper of MITgcm MDS binary data</dd><dt><span>source :</span></dt><dd>MITgcm</dd><dt><span>history :</span></dt><dd>Created by calling `open_mdsdataset(extra_metadata=None, llc_method=&#x27;smallchunks&#x27;, nz=None, ny=None, nx=None, default_dtype=None, ignore_unknown_vars=False, chunks=None, endian=&#x27;&gt;&#x27;, swap_dims=None, grid_vars_to_coords=True, geometry=&#x27;sphericalpolar&#x27;, calendar=&#x27;gregorian&#x27;, ref_date=None, delta_t=1, read_grid=True, prefix=None, iters=&#x27;all&#x27;, grid_dir=None, data_dir=&#x27;./global_oce_latlon/&#x27;)`</dd></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.Dataset>\n",
       "Dimensions:  (XC: 90, XG: 90, YC: 40, YG: 40, Z: 15, Zl: 15, time: 1)\n",
       "Coordinates:\n",
       "  * time     (time) timedelta64[ns] 11:00:00\n",
       "    maskC    (Z, YC, XC) bool ...\n",
       "    dyC      (YG, XC) float32 ...\n",
       "    hFacC    (Z, YC, XC) float32 ...\n",
       "    rA       (YC, XC) float32 ...\n",
       "    hFacS    (Z, YG, XC) float32 ...\n",
       "    Depth    (YC, XC) float32 ...\n",
       "  * YG       (YG) float32 -80.0 -76.0 -72.0 -68.0 -64.0 ... 64.0 68.0 72.0 76.0\n",
       "  * Z        (Z) float32 -25.0 -85.0 -170.0 ... -3.575e+03 -4.19e+03 -4.855e+03\n",
       "    PHrefC   (Z) float32 ...\n",
       "    dyG      (YC, XG) float32 ...\n",
       "    rAw      (YC, XG) float32 ...\n",
       "    drF      (Z) float32 ...\n",
       "  * YC       (YC) float32 -78.0 -74.0 -70.0 -66.0 -62.0 ... 66.0 70.0 74.0 78.0\n",
       "    dxG      (YG, XC) float32 ...\n",
       "  * XG       (XG) float32 0.0 4.0 8.0 12.0 16.0 ... 344.0 348.0 352.0 356.0\n",
       "    iter     (time) int64 ...\n",
       "    maskW    (Z, YC, XG) bool ...\n",
       "  * Zl       (Zl) float32 0.0 -50.0 -120.0 ... -3.28e+03 -3.87e+03 -4.51e+03\n",
       "    rAs      (YG, XC) float32 ...\n",
       "    rAz      (YG, XG) float32 ...\n",
       "    maskS    (Z, YG, XC) bool ...\n",
       "    dxC      (YC, XG) float32 ...\n",
       "    hFacW    (Z, YC, XG) float32 ...\n",
       "  * XC       (XC) float32 2.0 6.0 10.0 14.0 18.0 ... 346.0 350.0 354.0 358.0\n",
       "Data variables:\n",
       "    UVEL     (time, Z, YC, XG) float32 ...\n",
       "    VVEL     (time, Z, YG, XC) float32 ...\n",
       "    WVEL     (time, Zl, YC, XC) float32 ...\n",
       "    SALT     (time, Z, YC, XC) float32 ...\n",
       "    THETA    (time, Z, YC, XC) float32 ...\n",
       "    PH       (time, Z, YC, XC) float32 ...\n",
       "    Eta      (time, YC, XC) float32 ...\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(extra_metadata=None, ll..."
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# download the data\n",
    "import urllib.request\n",
    "import shutil\n",
    "\n",
    "url = 'https://zenodo.org/record/4421428/files/'\n",
    "file_name = 'mitgcm_example_dataset_v2.nc'\n",
    "with urllib.request.urlopen(url + file_name) as response, open(file_name, 'wb') as out_file:\n",
    "    shutil.copyfileobj(response, out_file)\n",
    "    \n",
    "# open the data\n",
    "ds = xr.open_dataset(file_name)\n",
    "ds"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Creating the grid object\n",
    "\n",
    "Next we create a `Grid` object from the dataset.\n",
    "We need to tell xgcm that the `X` and `Y` axes are periodic.\n",
    "(The other axes will be assumed to be non-periodic.)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<xgcm.Grid>\n",
       "Z Axis (not periodic, boundary=None):\n",
       "  * center   Z --> left\n",
       "  * left     Zl --> center\n",
       "T Axis (not periodic, boundary=None):\n",
       "  * center   time\n",
       "Y Axis (periodic, boundary=None):\n",
       "  * center   YC --> left\n",
       "  * left     YG --> center\n",
       "X Axis (periodic, boundary=None):\n",
       "  * center   XC --> left\n",
       "  * left     XG --> center"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "grid = xgcm.Grid(ds, periodic=['X', 'Y'])\n",
    "grid"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We see that xgcm identified five different axes: X (longitude), Y (latitude), Z (depth),  T (time), and 1RHO (the axis generated by the output of the LAYERS package).\n",
    "\n",
    "## Velocity Gradients\n",
    "\n",
    "The gradients of the velocity field can be decomposed  as divergence, vorticity, and strain. Below we use xgcm to compute the velocity gradients of the horizontal flow.\n",
    "\n",
    "### Divergence\n",
    "\n",
    "The divergence of the horizontal flow is is expressed as\n",
    "\n",
    "$$ \\frac{\\partial u}{\\partial x} + \\frac{\\partial v}{\\partial y} $$\n",
    "\n",
    "\n",
    "In discrete form, using [MITgcm notation](http://mitgcm.org/public/r2_manual/latest/online_documents/node50.html), the formula for the C-grid is\n",
    "\n",
    "$$ ( \\delta_i \\Delta y_g \\Delta r_f h_w u + \\delta_j \\Delta x_g \\Delta r_f h_s v ) / A_c$$\n",
    "\n",
    "First we calculate the volume transports in each direction:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "u_transport = ds.UVEL * ds.dyG * ds.hFacW * ds.drF\n",
    "v_transport = ds.VVEL * ds.dxG * ds.hFacS * ds.drF"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The `u_transport` DataArray is on the left point of the X axis, while the `v_transport` DataArray is on the left point of the Y axis."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "('time', 'Z', 'YC', 'XG')"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "('time', 'Z', 'YG', 'XC')"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "display(u_transport.dims)\n",
    "display(v_transport.dims)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now comes the xgcm magic: we take the diff along both axes and divide by the cell area element to find the divergence of the horizontal flow. Note how this new variable is at the cell center point."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "('time', 'Z', 'YC', 'XC')"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "div_uv = (grid.diff(u_transport, 'X') + grid.diff(v_transport, 'Y')) / ds.rA\n",
    "div_uv.dims"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We plot this near the surface and observe the expected patern of divergence at the equator and in the subpolar regions, and convergence in the subtropical gyres."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.collections.QuadMesh at 0x7fec29aa8bb0>"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x432 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "div_uv[0, 0].plot()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Vorticity\n",
    "\n",
    "The vertical component of the vorticity is a fundamental quantity of interest in ocean circulation theory. It is defined as\n",
    "\n",
    "$$ \\zeta = - \\frac{\\partial u}{\\partial y} + \\frac{\\partial v}{\\partial x} \\ . $$\n",
    "\n",
    "On the c-grid, a finite-volume representation is given by\n",
    "\n",
    "$$ \\zeta =  (- \\delta_j \\Delta x_c u + \\delta_i \\Delta y_c v ) / A_\\zeta \\ . $$\n",
    "\n",
    "In xgcm, we calculate this quanity as"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  --xr-border-color: var(--jp-border-color2, #e0e0e0);\n",
       "  --xr-disabled-color: var(--jp-layout-color3, #bdbdbd);\n",
       "  --xr-background-color: var(--jp-layout-color0, white);\n",
       "  --xr-background-color-row-even: var(--jp-layout-color1, white);\n",
       "  --xr-background-color-row-odd: var(--jp-layout-color2, #eeeeee);\n",
       "}\n",
       "\n",
       "html[theme=dark],\n",
       "body.vscode-dark {\n",
       "  --xr-font-color0: rgba(255, 255, 255, 1);\n",
       "  --xr-font-color2: rgba(255, 255, 255, 0.54);\n",
       "  --xr-font-color3: rgba(255, 255, 255, 0.38);\n",
       "  --xr-border-color: #1F1F1F;\n",
       "  --xr-disabled-color: #515151;\n",
       "  --xr-background-color: #111111;\n",
       "  --xr-background-color-row-even: #111111;\n",
       "  --xr-background-color-row-odd: #313131;\n",
       "}\n",
       "\n",
       ".xr-wrap {\n",
       "  display: block;\n",
       "  min-width: 300px;\n",
       "  max-width: 700px;\n",
       "}\n",
       "\n",
       ".xr-text-repr-fallback {\n",
       "  /* fallback to plain text repr when CSS is not injected (untrusted notebook) */\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-header {\n",
       "  padding-top: 6px;\n",
       "  padding-bottom: 6px;\n",
       "  margin-bottom: 4px;\n",
       "  border-bottom: solid 1px var(--xr-border-color);\n",
       "}\n",
       "\n",
       ".xr-header > div,\n",
       ".xr-header > ul {\n",
       "  display: inline;\n",
       "  margin-top: 0;\n",
       "  margin-bottom: 0;\n",
       "}\n",
       "\n",
       ".xr-obj-type,\n",
       ".xr-array-name {\n",
       "  margin-left: 2px;\n",
       "  margin-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-obj-type {\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-sections {\n",
       "  padding-left: 0 !important;\n",
       "  display: grid;\n",
       "  grid-template-columns: 150px auto auto 1fr 20px 20px;\n",
       "}\n",
       "\n",
       ".xr-section-item {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-section-item input {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-section-item input + label {\n",
       "  color: var(--xr-disabled-color);\n",
       "}\n",
       "\n",
       ".xr-section-item input:enabled + label {\n",
       "  cursor: pointer;\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-section-item input:enabled + label:hover {\n",
       "  color: var(--xr-font-color0);\n",
       "}\n",
       "\n",
       ".xr-section-summary {\n",
       "  grid-column: 1;\n",
       "  color: var(--xr-font-color2);\n",
       "  font-weight: 500;\n",
       "}\n",
       "\n",
       ".xr-section-summary > span {\n",
       "  display: inline-block;\n",
       "  padding-left: 0.5em;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:disabled + label {\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-section-summary-in + label:before {\n",
       "  display: inline-block;\n",
       "  content: '►';\n",
       "  font-size: 11px;\n",
       "  width: 15px;\n",
       "  text-align: center;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:disabled + label:before {\n",
       "  color: var(--xr-disabled-color);\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked + label:before {\n",
       "  content: '▼';\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked + label > span {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-section-summary,\n",
       ".xr-section-inline-details {\n",
       "  padding-top: 4px;\n",
       "  padding-bottom: 4px;\n",
       "}\n",
       "\n",
       ".xr-section-inline-details {\n",
       "  grid-column: 2 / -1;\n",
       "}\n",
       "\n",
       ".xr-section-details {\n",
       "  display: none;\n",
       "  grid-column: 1 / -1;\n",
       "  margin-bottom: 5px;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked ~ .xr-section-details {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-array-wrap {\n",
       "  grid-column: 1 / -1;\n",
       "  display: grid;\n",
       "  grid-template-columns: 20px auto;\n",
       "}\n",
       "\n",
       ".xr-array-wrap > label {\n",
       "  grid-column: 1;\n",
       "  vertical-align: top;\n",
       "}\n",
       "\n",
       ".xr-preview {\n",
       "  color: var(--xr-font-color3);\n",
       "}\n",
       "\n",
       ".xr-array-preview,\n",
       ".xr-array-data {\n",
       "  padding: 0 5px !important;\n",
       "  grid-column: 2;\n",
       "}\n",
       "\n",
       ".xr-array-data,\n",
       ".xr-array-in:checked ~ .xr-array-preview {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-array-in:checked ~ .xr-array-data,\n",
       ".xr-array-preview {\n",
       "  display: inline-block;\n",
       "}\n",
       "\n",
       ".xr-dim-list {\n",
       "  display: inline-block !important;\n",
       "  list-style: none;\n",
       "  padding: 0 !important;\n",
       "  margin: 0;\n",
       "}\n",
       "\n",
       ".xr-dim-list li {\n",
       "  display: inline-block;\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "}\n",
       "\n",
       ".xr-dim-list:before {\n",
       "  content: '(';\n",
       "}\n",
       "\n",
       ".xr-dim-list:after {\n",
       "  content: ')';\n",
       "}\n",
       "\n",
       ".xr-dim-list li:not(:last-child):after {\n",
       "  content: ',';\n",
       "  padding-right: 5px;\n",
       "}\n",
       "\n",
       ".xr-has-index {\n",
       "  font-weight: bold;\n",
       "}\n",
       "\n",
       ".xr-var-list,\n",
       ".xr-var-item {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-var-item > div,\n",
       ".xr-var-item label,\n",
       ".xr-var-item > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-even);\n",
       "  margin-bottom: 0;\n",
       "}\n",
       "\n",
       ".xr-var-item > .xr-var-name:hover span {\n",
       "  padding-right: 5px;\n",
       "}\n",
       "\n",
       ".xr-var-list > li:nth-child(odd) > div,\n",
       ".xr-var-list > li:nth-child(odd) > label,\n",
       ".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-odd);\n",
       "}\n",
       "\n",
       ".xr-var-name {\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-var-dims {\n",
       "  grid-column: 2;\n",
       "}\n",
       "\n",
       ".xr-var-dtype {\n",
       "  grid-column: 3;\n",
       "  text-align: right;\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-var-preview {\n",
       "  grid-column: 4;\n",
       "}\n",
       "\n",
       ".xr-var-name,\n",
       ".xr-var-dims,\n",
       ".xr-var-dtype,\n",
       ".xr-preview,\n",
       ".xr-attrs dt {\n",
       "  white-space: nowrap;\n",
       "  overflow: hidden;\n",
       "  text-overflow: ellipsis;\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-var-name:hover,\n",
       ".xr-var-dims:hover,\n",
       ".xr-var-dtype:hover,\n",
       ".xr-attrs dt:hover {\n",
       "  overflow: visible;\n",
       "  width: auto;\n",
       "  z-index: 1;\n",
       "}\n",
       "\n",
       ".xr-var-attrs,\n",
       ".xr-var-data {\n",
       "  display: none;\n",
       "  background-color: var(--xr-background-color) !important;\n",
       "  padding-bottom: 5px !important;\n",
       "}\n",
       "\n",
       ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
       ".xr-var-data-in:checked ~ .xr-var-data {\n",
       "  display: block;\n",
       "}\n",
       "\n",
       ".xr-var-data > table {\n",
       "  float: right;\n",
       "}\n",
       "\n",
       ".xr-var-name span,\n",
       ".xr-var-data,\n",
       ".xr-attrs {\n",
       "  padding-left: 25px !important;\n",
       "}\n",
       "\n",
       ".xr-attrs,\n",
       ".xr-var-attrs,\n",
       ".xr-var-data {\n",
       "  grid-column: 1 / -1;\n",
       "}\n",
       "\n",
       "dl.xr-attrs {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  display: grid;\n",
       "  grid-template-columns: 125px auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt,\n",
       ".xr-attrs dd {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  float: left;\n",
       "  padding-right: 10px;\n",
       "  width: auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt {\n",
       "  font-weight: normal;\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-attrs dt:hover span {\n",
       "  display: inline-block;\n",
       "  background: var(--xr-background-color);\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-attrs dd {\n",
       "  grid-column: 2;\n",
       "  white-space: pre-wrap;\n",
       "  word-break: break-all;\n",
       "}\n",
       "\n",
       ".xr-icon-database,\n",
       ".xr-icon-file-text2 {\n",
       "  display: inline-block;\n",
       "  vertical-align: middle;\n",
       "  width: 1em;\n",
       "  height: 1.5em !important;\n",
       "  stroke-width: 0;\n",
       "  stroke: currentColor;\n",
       "  fill: currentColor;\n",
       "}\n",
       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.DataArray (time: 1, Z: 15, YG: 40, XG: 90)&gt;\n",
       "array([[[[-1.48332937e-08, -1.02609041e-08, -6.38644559e-09, ...,\n",
       "          -2.02205257e-08, -2.36162538e-08, -2.21622898e-08],\n",
       "         [ 0.00000000e+00,  0.00000000e+00,  0.00000000e+00, ...,\n",
       "           0.00000000e+00,  0.00000000e+00,  0.00000000e+00],\n",
       "         [ 3.81209766e-08,  3.97684836e-08,  4.13142871e-08, ...,\n",
       "           1.29681979e-07,  3.34656640e-08,  3.61909045e-08],\n",
       "         ...,\n",
       "         [ 4.37701573e-08,  9.16013079e-08, -2.54561030e-08, ...,\n",
       "           1.26603963e-08, -6.90892721e-09,  5.01466104e-08],\n",
       "         [ 6.99142433e-08,  3.79757061e-08,  6.82349199e-09, ...,\n",
       "           6.06992998e-08,  6.45270646e-08,  4.38413430e-08],\n",
       "         [ 5.32967235e-08,  3.35858523e-08,  7.44277244e-08, ...,\n",
       "          -4.63408085e-08,  1.05465695e-07, -3.87492776e-08]],\n",
       "\n",
       "        [[-5.91518168e-09, -5.92747895e-09, -4.68231898e-09, ...,\n",
       "           4.79974616e-10, -5.15723109e-09, -8.35224956e-09],\n",
       "         [ 0.00000000e+00,  0.00000000e+00,  0.00000000e+00, ...,\n",
       "           0.00000000e+00,  0.00000000e+00,  0.00000000e+00],\n",
       "         [ 2.93285876e-08,  2.88299127e-08,  2.76142540e-08, ...,\n",
       "           4.49574458e-08,  2.74702163e-08,  2.87617432e-08],\n",
       "...\n",
       "           0.00000000e+00,  0.00000000e+00,  0.00000000e+00],\n",
       "         [ 0.00000000e+00,  0.00000000e+00,  0.00000000e+00, ...,\n",
       "           0.00000000e+00,  0.00000000e+00,  0.00000000e+00],\n",
       "         [ 0.00000000e+00,  0.00000000e+00,  0.00000000e+00, ...,\n",
       "           0.00000000e+00,  0.00000000e+00,  0.00000000e+00]],\n",
       "\n",
       "        [[ 0.00000000e+00,  0.00000000e+00,  0.00000000e+00, ...,\n",
       "           0.00000000e+00,  0.00000000e+00,  0.00000000e+00],\n",
       "         [ 0.00000000e+00,  0.00000000e+00,  0.00000000e+00, ...,\n",
       "           0.00000000e+00,  0.00000000e+00,  0.00000000e+00],\n",
       "         [ 0.00000000e+00,  0.00000000e+00,  0.00000000e+00, ...,\n",
       "           0.00000000e+00,  0.00000000e+00,  0.00000000e+00],\n",
       "         ...,\n",
       "         [ 0.00000000e+00,  0.00000000e+00,  0.00000000e+00, ...,\n",
       "           0.00000000e+00,  0.00000000e+00,  0.00000000e+00],\n",
       "         [ 0.00000000e+00,  0.00000000e+00,  0.00000000e+00, ...,\n",
       "           0.00000000e+00,  0.00000000e+00,  0.00000000e+00],\n",
       "         [ 0.00000000e+00,  0.00000000e+00,  0.00000000e+00, ...,\n",
       "           0.00000000e+00,  0.00000000e+00,  0.00000000e+00]]]],\n",
       "      dtype=float32)\n",
       "Coordinates:\n",
       "  * time     (time) timedelta64[ns] 11:00:00\n",
       "  * Z        (Z) float32 -25.0 -85.0 -170.0 ... -3.575e+03 -4.19e+03 -4.855e+03\n",
       "  * YG       (YG) float32 -80.0 -76.0 -72.0 -68.0 -64.0 ... 64.0 68.0 72.0 76.0\n",
       "  * XG       (XG) float32 0.0 4.0 8.0 12.0 16.0 ... 344.0 348.0 352.0 356.0\n",
       "    rAz      (YG, XG) float32 3.433e+10 3.433e+10 ... 4.783e+10 4.783e+10</pre><div class='xr-wrap' hidden><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'></div><ul class='xr-dim-list'><li><span class='xr-has-index'>time</span>: 1</li><li><span class='xr-has-index'>Z</span>: 15</li><li><span class='xr-has-index'>YG</span>: 40</li><li><span class='xr-has-index'>XG</span>: 90</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-46e15248-15b8-4da4-a7a2-7d9f4bc898cb' class='xr-array-in' type='checkbox' checked><label for='section-46e15248-15b8-4da4-a7a2-7d9f4bc898cb' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>-1.483e-08 -1.026e-08 -6.386e-09 -1.034e-08 ... 0.0 0.0 0.0 0.0</span></div><div class='xr-array-data'><pre>array([[[[-1.48332937e-08, -1.02609041e-08, -6.38644559e-09, ...,\n",
       "          -2.02205257e-08, -2.36162538e-08, -2.21622898e-08],\n",
       "         [ 0.00000000e+00,  0.00000000e+00,  0.00000000e+00, ...,\n",
       "           0.00000000e+00,  0.00000000e+00,  0.00000000e+00],\n",
       "         [ 3.81209766e-08,  3.97684836e-08,  4.13142871e-08, ...,\n",
       "           1.29681979e-07,  3.34656640e-08,  3.61909045e-08],\n",
       "         ...,\n",
       "         [ 4.37701573e-08,  9.16013079e-08, -2.54561030e-08, ...,\n",
       "           1.26603963e-08, -6.90892721e-09,  5.01466104e-08],\n",
       "         [ 6.99142433e-08,  3.79757061e-08,  6.82349199e-09, ...,\n",
       "           6.06992998e-08,  6.45270646e-08,  4.38413430e-08],\n",
       "         [ 5.32967235e-08,  3.35858523e-08,  7.44277244e-08, ...,\n",
       "          -4.63408085e-08,  1.05465695e-07, -3.87492776e-08]],\n",
       "\n",
       "        [[-5.91518168e-09, -5.92747895e-09, -4.68231898e-09, ...,\n",
       "           4.79974616e-10, -5.15723109e-09, -8.35224956e-09],\n",
       "         [ 0.00000000e+00,  0.00000000e+00,  0.00000000e+00, ...,\n",
       "           0.00000000e+00,  0.00000000e+00,  0.00000000e+00],\n",
       "         [ 2.93285876e-08,  2.88299127e-08,  2.76142540e-08, ...,\n",
       "           4.49574458e-08,  2.74702163e-08,  2.87617432e-08],\n",
       "...\n",
       "           0.00000000e+00,  0.00000000e+00,  0.00000000e+00],\n",
       "         [ 0.00000000e+00,  0.00000000e+00,  0.00000000e+00, ...,\n",
       "           0.00000000e+00,  0.00000000e+00,  0.00000000e+00],\n",
       "         [ 0.00000000e+00,  0.00000000e+00,  0.00000000e+00, ...,\n",
       "           0.00000000e+00,  0.00000000e+00,  0.00000000e+00]],\n",
       "\n",
       "        [[ 0.00000000e+00,  0.00000000e+00,  0.00000000e+00, ...,\n",
       "           0.00000000e+00,  0.00000000e+00,  0.00000000e+00],\n",
       "         [ 0.00000000e+00,  0.00000000e+00,  0.00000000e+00, ...,\n",
       "           0.00000000e+00,  0.00000000e+00,  0.00000000e+00],\n",
       "         [ 0.00000000e+00,  0.00000000e+00,  0.00000000e+00, ...,\n",
       "           0.00000000e+00,  0.00000000e+00,  0.00000000e+00],\n",
       "         ...,\n",
       "         [ 0.00000000e+00,  0.00000000e+00,  0.00000000e+00, ...,\n",
       "           0.00000000e+00,  0.00000000e+00,  0.00000000e+00],\n",
       "         [ 0.00000000e+00,  0.00000000e+00,  0.00000000e+00, ...,\n",
       "           0.00000000e+00,  0.00000000e+00,  0.00000000e+00],\n",
       "         [ 0.00000000e+00,  0.00000000e+00,  0.00000000e+00, ...,\n",
       "           0.00000000e+00,  0.00000000e+00,  0.00000000e+00]]]],\n",
       "      dtype=float32)</pre></div></div></li><li class='xr-section-item'><input id='section-9ca14184-b99b-4eaa-a145-48f1542a6177' class='xr-section-summary-in' type='checkbox'  checked><label for='section-9ca14184-b99b-4eaa-a145-48f1542a6177' class='xr-section-summary' >Coordinates: <span>(5)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>timedelta64[ns]</div><div class='xr-var-preview xr-preview'>11:00:00</div><input id='attrs-d0f979d9-db8e-41da-96e9-ed23f73a455d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d0f979d9-db8e-41da-96e9-ed23f73a455d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4d790ff8-9a2d-4066-9706-2c80c41b6cc4' class='xr-var-data-in' type='checkbox'><label for='data-4d790ff8-9a2d-4066-9706-2c80c41b6cc4' 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([39600000000000], dtype=&#x27;timedelta64[ns]&#x27;)</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'>float32</div><div class='xr-var-preview xr-preview'>-25.0 -85.0 ... -4.855e+03</div><input id='attrs-ddfc808a-54a0-46f1-887f-3847af1e14af' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ddfc808a-54a0-46f1-887f-3847af1e14af' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-269344cf-e602-45fc-ab92-7bded841d7e5' class='xr-var-data-in' type='checkbox'><label for='data-269344cf-e602-45fc-ab92-7bded841d7e5' 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([  -25.,   -85.,  -170.,  -290.,  -455.,  -670.,  -935., -1250., -1615.,\n",
       "       -2030., -2495., -3010., -3575., -4190., -4855.], 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'>float32</div><div class='xr-var-preview xr-preview'>-80.0 -76.0 -72.0 ... 72.0 76.0</div><input id='attrs-189696e6-35d1-4479-95d7-8159207e4a8e' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-189696e6-35d1-4479-95d7-8159207e4a8e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7ecfc756-a4d6-4ef8-a13e-c035a7f5d03c' class='xr-var-data-in' type='checkbox'><label for='data-7ecfc756-a4d6-4ef8-a13e-c035a7f5d03c' 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>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([-80., -76., -72., -68., -64., -60., -56., -52., -48., -44., -40., -36.,\n",
       "       -32., -28., -24., -20., -16., -12.,  -8.,  -4.,   0.,   4.,   8.,  12.,\n",
       "        16.,  20.,  24.,  28.,  32.,  36.,  40.,  44.,  48.,  52.,  56.,  60.,\n",
       "        64.,  68.,  72.,  76.], 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'>float32</div><div class='xr-var-preview xr-preview'>0.0 4.0 8.0 ... 348.0 352.0 356.0</div><input id='attrs-c873af06-140c-4595-a13a-b3ac3c43a194' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-c873af06-140c-4595-a13a-b3ac3c43a194' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e1ad3cb9-e702-48ca-a152-5b2d8e14192c' class='xr-var-data-in' type='checkbox'><label for='data-e1ad3cb9-e702-48ca-a152-5b2d8e14192c' 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([  0.,   4.,   8.,  12.,  16.,  20.,  24.,  28.,  32.,  36.,  40.,  44.,\n",
       "        48.,  52.,  56.,  60.,  64.,  68.,  72.,  76.,  80.,  84.,  88.,  92.,\n",
       "        96., 100., 104., 108., 112., 116., 120., 124., 128., 132., 136., 140.,\n",
       "       144., 148., 152., 156., 160., 164., 168., 172., 176., 180., 184., 188.,\n",
       "       192., 196., 200., 204., 208., 212., 216., 220., 224., 228., 232., 236.,\n",
       "       240., 244., 248., 252., 256., 260., 264., 268., 272., 276., 280., 284.,\n",
       "       288., 292., 296., 300., 304., 308., 312., 316., 320., 324., 328., 332.,\n",
       "       336., 340., 344., 348., 352., 356.], dtype=float32)</pre></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'>float32</div><div class='xr-var-preview xr-preview'>3.433e+10 3.433e+10 ... 4.783e+10</div><input id='attrs-08b324cf-eae5-4314-a4f7-cb3b9f80107d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-08b324cf-eae5-4314-a4f7-cb3b9f80107d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-eace8cee-968e-45b8-9581-8c77043d5373' class='xr-var-data-in' type='checkbox'><label for='data-eace8cee-968e-45b8-9581-8c77043d5373' 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'><pre>array([[3.433489e+10, 3.433489e+10, 3.433489e+10, ..., 3.433489e+10,\n",
       "        3.433489e+10, 3.433489e+10],\n",
       "       [4.783442e+10, 4.783442e+10, 4.783442e+10, ..., 4.783442e+10,\n",
       "        4.783442e+10, 4.783442e+10],\n",
       "       [6.110092e+10, 6.110092e+10, 6.110092e+10, ..., 6.110092e+10,\n",
       "        6.110092e+10, 6.110092e+10],\n",
       "       ...,\n",
       "       [7.406974e+10, 7.406974e+10, 7.406974e+10, ..., 7.406974e+10,\n",
       "        7.406974e+10, 7.406974e+10],\n",
       "       [6.110092e+10, 6.110092e+10, 6.110092e+10, ..., 6.110092e+10,\n",
       "        6.110092e+10, 6.110092e+10],\n",
       "       [4.783442e+10, 4.783442e+10, 4.783442e+10, ..., 4.783442e+10,\n",
       "        4.783442e+10, 4.783442e+10]], dtype=float32)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-5801d354-4f9c-4b25-b34f-f3ff21934f2b' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-5801d354-4f9c-4b25-b34f-f3ff21934f2b' class='xr-section-summary'  title='Expand/collapse section'>Attributes: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.DataArray (time: 1, Z: 15, YG: 40, XG: 90)>\n",
       "array([[[[-1.48332937e-08, -1.02609041e-08, -6.38644559e-09, ...,\n",
       "          -2.02205257e-08, -2.36162538e-08, -2.21622898e-08],\n",
       "         [ 0.00000000e+00,  0.00000000e+00,  0.00000000e+00, ...,\n",
       "           0.00000000e+00,  0.00000000e+00,  0.00000000e+00],\n",
       "         [ 3.81209766e-08,  3.97684836e-08,  4.13142871e-08, ...,\n",
       "           1.29681979e-07,  3.34656640e-08,  3.61909045e-08],\n",
       "         ...,\n",
       "         [ 4.37701573e-08,  9.16013079e-08, -2.54561030e-08, ...,\n",
       "           1.26603963e-08, -6.90892721e-09,  5.01466104e-08],\n",
       "         [ 6.99142433e-08,  3.79757061e-08,  6.82349199e-09, ...,\n",
       "           6.06992998e-08,  6.45270646e-08,  4.38413430e-08],\n",
       "         [ 5.32967235e-08,  3.35858523e-08,  7.44277244e-08, ...,\n",
       "          -4.63408085e-08,  1.05465695e-07, -3.87492776e-08]],\n",
       "\n",
       "        [[-5.91518168e-09, -5.92747895e-09, -4.68231898e-09, ...,\n",
       "           4.79974616e-10, -5.15723109e-09, -8.35224956e-09],\n",
       "         [ 0.00000000e+00,  0.00000000e+00,  0.00000000e+00, ...,\n",
       "           0.00000000e+00,  0.00000000e+00,  0.00000000e+00],\n",
       "         [ 2.93285876e-08,  2.88299127e-08,  2.76142540e-08, ...,\n",
       "           4.49574458e-08,  2.74702163e-08,  2.87617432e-08],\n",
       "...\n",
       "           0.00000000e+00,  0.00000000e+00,  0.00000000e+00],\n",
       "         [ 0.00000000e+00,  0.00000000e+00,  0.00000000e+00, ...,\n",
       "           0.00000000e+00,  0.00000000e+00,  0.00000000e+00],\n",
       "         [ 0.00000000e+00,  0.00000000e+00,  0.00000000e+00, ...,\n",
       "           0.00000000e+00,  0.00000000e+00,  0.00000000e+00]],\n",
       "\n",
       "        [[ 0.00000000e+00,  0.00000000e+00,  0.00000000e+00, ...,\n",
       "           0.00000000e+00,  0.00000000e+00,  0.00000000e+00],\n",
       "         [ 0.00000000e+00,  0.00000000e+00,  0.00000000e+00, ...,\n",
       "           0.00000000e+00,  0.00000000e+00,  0.00000000e+00],\n",
       "         [ 0.00000000e+00,  0.00000000e+00,  0.00000000e+00, ...,\n",
       "           0.00000000e+00,  0.00000000e+00,  0.00000000e+00],\n",
       "         ...,\n",
       "         [ 0.00000000e+00,  0.00000000e+00,  0.00000000e+00, ...,\n",
       "           0.00000000e+00,  0.00000000e+00,  0.00000000e+00],\n",
       "         [ 0.00000000e+00,  0.00000000e+00,  0.00000000e+00, ...,\n",
       "           0.00000000e+00,  0.00000000e+00,  0.00000000e+00],\n",
       "         [ 0.00000000e+00,  0.00000000e+00,  0.00000000e+00, ...,\n",
       "           0.00000000e+00,  0.00000000e+00,  0.00000000e+00]]]],\n",
       "      dtype=float32)\n",
       "Coordinates:\n",
       "  * time     (time) timedelta64[ns] 11:00:00\n",
       "  * Z        (Z) float32 -25.0 -85.0 -170.0 ... -3.575e+03 -4.19e+03 -4.855e+03\n",
       "  * YG       (YG) float32 -80.0 -76.0 -72.0 -68.0 -64.0 ... 64.0 68.0 72.0 76.0\n",
       "  * XG       (XG) float32 0.0 4.0 8.0 12.0 16.0 ... 344.0 348.0 352.0 356.0\n",
       "    rAz      (YG, XG) float32 3.433e+10 3.433e+10 ... 4.783e+10 4.783e+10"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "zeta = (-grid.diff(ds.UVEL * ds.dxC, 'Y') + grid.diff(ds.VVEL * ds.dyC, 'X'))/ds.rAz\n",
    "zeta"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "...which we can see is located at the `YG, XG` horizontal position (also commonly called the vorticity point).\n",
    "\n",
    "We plot the vertical integral of this quantity, i.e. the barotropic vorticity:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.collections.QuadMesh at 0x7fec28f16dc0>"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x432 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "zeta_bt = (zeta * ds.drF).sum(dim='Z')\n",
    "zeta_bt.plot(vmax=2e-4)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "A different way to calculate the barotropic vorticity is to take the curl of the vertically integrated velocity.\n",
    "This formulation also allows us to incorporate the $h$ factors representing partial cell thickness."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.collections.QuadMesh at 0x7fec28ac3970>"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x432 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "u_bt = (ds.UVEL * ds.hFacW * ds.drF).sum(dim='Z')\n",
    "v_bt = (ds.VVEL * ds.hFacS * ds.drF).sum(dim='Z')\n",
    "zeta_bt_alt = (-grid.diff(u_bt * ds.dxC, 'Y') + grid.diff(v_bt * ds.dyC, 'X'))/ds.rAz\n",
    "zeta_bt_alt.plot(vmax=2e-4)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Strain\n",
    "\n",
    "Another interesting quantity is the horizontal strain, defined as\n",
    "\n",
    "$$ s = \\frac{\\partial u}{\\partial x} - \\frac{\\partial v}{\\partial y} \\ . $$\n",
    "\n",
    "On the c-grid, a finite-volume representation is given by\n",
    "\n",
    "$$ s =  (\\delta_i \\Delta y_g u - \\delta_j \\Delta x_g v ) / A_c \\ . $$"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.collections.QuadMesh at 0x7fec28f2d6a0>"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 720x432 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "strain = (grid.diff(ds.UVEL * ds.dyG, 'X') - grid.diff(ds.VVEL * ds.dxG, 'Y')) / ds.rA\n",
    "strain[0,0].plot()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Barotropic Transport Streamfunction\n",
    "\n",
    "We can use the barotropic velocity to calcuate the barotropic transport streamfunction, defined via\n",
    "\n",
    "$$ u_{bt} = - \\frac{\\partial \\Psi}{\\partial y} \\ , \\ \\ v_{bt} = \\frac{\\partial \\Psi}{\\partial x} \\ .$$\n",
    "\n",
    "We calculate this by integrating $u_{bt}$ along the Y axis using the grid object's `cumsum` method:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
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       "  --xr-border-color: #1F1F1F;\n",
       "  --xr-disabled-color: #515151;\n",
       "  --xr-background-color: #111111;\n",
       "  --xr-background-color-row-even: #111111;\n",
       "  --xr-background-color-row-odd: #313131;\n",
       "}\n",
       "\n",
       ".xr-wrap {\n",
       "  display: block;\n",
       "  min-width: 300px;\n",
       "  max-width: 700px;\n",
       "}\n",
       "\n",
       ".xr-text-repr-fallback {\n",
       "  /* fallback to plain text repr when CSS is not injected (untrusted notebook) */\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-header {\n",
       "  padding-top: 6px;\n",
       "  padding-bottom: 6px;\n",
       "  margin-bottom: 4px;\n",
       "  border-bottom: solid 1px var(--xr-border-color);\n",
       "}\n",
       "\n",
       ".xr-header > div,\n",
       ".xr-header > ul {\n",
       "  display: inline;\n",
       "  margin-top: 0;\n",
       "  margin-bottom: 0;\n",
       "}\n",
       "\n",
       ".xr-obj-type,\n",
       ".xr-array-name {\n",
       "  margin-left: 2px;\n",
       "  margin-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-obj-type {\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-sections {\n",
       "  padding-left: 0 !important;\n",
       "  display: grid;\n",
       "  grid-template-columns: 150px auto auto 1fr 20px 20px;\n",
       "}\n",
       "\n",
       ".xr-section-item {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-section-item input {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-section-item input + label {\n",
       "  color: var(--xr-disabled-color);\n",
       "}\n",
       "\n",
       ".xr-section-item input:enabled + label {\n",
       "  cursor: pointer;\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-section-item input:enabled + label:hover {\n",
       "  color: var(--xr-font-color0);\n",
       "}\n",
       "\n",
       ".xr-section-summary {\n",
       "  grid-column: 1;\n",
       "  color: var(--xr-font-color2);\n",
       "  font-weight: 500;\n",
       "}\n",
       "\n",
       ".xr-section-summary > span {\n",
       "  display: inline-block;\n",
       "  padding-left: 0.5em;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:disabled + label {\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-section-summary-in + label:before {\n",
       "  display: inline-block;\n",
       "  content: '►';\n",
       "  font-size: 11px;\n",
       "  width: 15px;\n",
       "  text-align: center;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:disabled + label:before {\n",
       "  color: var(--xr-disabled-color);\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked + label:before {\n",
       "  content: '▼';\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked + label > span {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-section-summary,\n",
       ".xr-section-inline-details {\n",
       "  padding-top: 4px;\n",
       "  padding-bottom: 4px;\n",
       "}\n",
       "\n",
       ".xr-section-inline-details {\n",
       "  grid-column: 2 / -1;\n",
       "}\n",
       "\n",
       ".xr-section-details {\n",
       "  display: none;\n",
       "  grid-column: 1 / -1;\n",
       "  margin-bottom: 5px;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked ~ .xr-section-details {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-array-wrap {\n",
       "  grid-column: 1 / -1;\n",
       "  display: grid;\n",
       "  grid-template-columns: 20px auto;\n",
       "}\n",
       "\n",
       ".xr-array-wrap > label {\n",
       "  grid-column: 1;\n",
       "  vertical-align: top;\n",
       "}\n",
       "\n",
       ".xr-preview {\n",
       "  color: var(--xr-font-color3);\n",
       "}\n",
       "\n",
       ".xr-array-preview,\n",
       ".xr-array-data {\n",
       "  padding: 0 5px !important;\n",
       "  grid-column: 2;\n",
       "}\n",
       "\n",
       ".xr-array-data,\n",
       ".xr-array-in:checked ~ .xr-array-preview {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-array-in:checked ~ .xr-array-data,\n",
       ".xr-array-preview {\n",
       "  display: inline-block;\n",
       "}\n",
       "\n",
       ".xr-dim-list {\n",
       "  display: inline-block !important;\n",
       "  list-style: none;\n",
       "  padding: 0 !important;\n",
       "  margin: 0;\n",
       "}\n",
       "\n",
       ".xr-dim-list li {\n",
       "  display: inline-block;\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "}\n",
       "\n",
       ".xr-dim-list:before {\n",
       "  content: '(';\n",
       "}\n",
       "\n",
       ".xr-dim-list:after {\n",
       "  content: ')';\n",
       "}\n",
       "\n",
       ".xr-dim-list li:not(:last-child):after {\n",
       "  content: ',';\n",
       "  padding-right: 5px;\n",
       "}\n",
       "\n",
       ".xr-has-index {\n",
       "  font-weight: bold;\n",
       "}\n",
       "\n",
       ".xr-var-list,\n",
       ".xr-var-item {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-var-item > div,\n",
       ".xr-var-item label,\n",
       ".xr-var-item > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-even);\n",
       "  margin-bottom: 0;\n",
       "}\n",
       "\n",
       ".xr-var-item > .xr-var-name:hover span {\n",
       "  padding-right: 5px;\n",
       "}\n",
       "\n",
       ".xr-var-list > li:nth-child(odd) > div,\n",
       ".xr-var-list > li:nth-child(odd) > label,\n",
       ".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-odd);\n",
       "}\n",
       "\n",
       ".xr-var-name {\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-var-dims {\n",
       "  grid-column: 2;\n",
       "}\n",
       "\n",
       ".xr-var-dtype {\n",
       "  grid-column: 3;\n",
       "  text-align: right;\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-var-preview {\n",
       "  grid-column: 4;\n",
       "}\n",
       "\n",
       ".xr-var-name,\n",
       ".xr-var-dims,\n",
       ".xr-var-dtype,\n",
       ".xr-preview,\n",
       ".xr-attrs dt {\n",
       "  white-space: nowrap;\n",
       "  overflow: hidden;\n",
       "  text-overflow: ellipsis;\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-var-name:hover,\n",
       ".xr-var-dims:hover,\n",
       ".xr-var-dtype:hover,\n",
       ".xr-attrs dt:hover {\n",
       "  overflow: visible;\n",
       "  width: auto;\n",
       "  z-index: 1;\n",
       "}\n",
       "\n",
       ".xr-var-attrs,\n",
       ".xr-var-data {\n",
       "  display: none;\n",
       "  background-color: var(--xr-background-color) !important;\n",
       "  padding-bottom: 5px !important;\n",
       "}\n",
       "\n",
       ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
       ".xr-var-data-in:checked ~ .xr-var-data {\n",
       "  display: block;\n",
       "}\n",
       "\n",
       ".xr-var-data > table {\n",
       "  float: right;\n",
       "}\n",
       "\n",
       ".xr-var-name span,\n",
       ".xr-var-data,\n",
       ".xr-attrs {\n",
       "  padding-left: 25px !important;\n",
       "}\n",
       "\n",
       ".xr-attrs,\n",
       ".xr-var-attrs,\n",
       ".xr-var-data {\n",
       "  grid-column: 1 / -1;\n",
       "}\n",
       "\n",
       "dl.xr-attrs {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  display: grid;\n",
       "  grid-template-columns: 125px auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt,\n",
       ".xr-attrs dd {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  float: left;\n",
       "  padding-right: 10px;\n",
       "  width: auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt {\n",
       "  font-weight: normal;\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-attrs dt:hover span {\n",
       "  display: inline-block;\n",
       "  background: var(--xr-background-color);\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-attrs dd {\n",
       "  grid-column: 2;\n",
       "  white-space: pre-wrap;\n",
       "  word-break: break-all;\n",
       "}\n",
       "\n",
       ".xr-icon-database,\n",
       ".xr-icon-file-text2 {\n",
       "  display: inline-block;\n",
       "  vertical-align: middle;\n",
       "  width: 1em;\n",
       "  height: 1.5em !important;\n",
       "  stroke-width: 0;\n",
       "  stroke: currentColor;\n",
       "  fill: currentColor;\n",
       "}\n",
       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.DataArray (time: 1, YG: 40, XG: 90)&gt;\n",
       "array([[[ 0.00000000e+00,  0.00000000e+00,  0.00000000e+00, ...,\n",
       "          0.00000000e+00,  0.00000000e+00,  0.00000000e+00],\n",
       "        [-0.00000000e+00, -0.00000000e+00, -0.00000000e+00, ...,\n",
       "         -0.00000000e+00, -0.00000000e+00, -0.00000000e+00],\n",
       "        [-0.00000000e+00, -0.00000000e+00, -0.00000000e+00, ...,\n",
       "         -0.00000000e+00, -0.00000000e+00, -0.00000000e+00],\n",
       "        ...,\n",
       "        [-1.06634920e+08, -1.06666912e+08, -1.05922952e+08, ...,\n",
       "         -1.07724152e+08, -1.07341128e+08, -1.06941400e+08],\n",
       "        [-1.07050680e+08, -1.06612056e+08, -1.06356232e+08, ...,\n",
       "         -1.07048232e+08, -1.07335792e+08, -1.07102304e+08],\n",
       "        [-1.05933672e+08, -1.05922800e+08, -1.05856504e+08, ...,\n",
       "         -1.05376272e+08, -1.05493376e+08, -1.05632128e+08]]],\n",
       "      dtype=float32)\n",
       "Coordinates:\n",
       "  * time     (time) timedelta64[ns] 11:00:00\n",
       "  * YG       (YG) float32 -80.0 -76.0 -72.0 -68.0 -64.0 ... 64.0 68.0 72.0 76.0\n",
       "  * XG       (XG) float32 0.0 4.0 8.0 12.0 16.0 ... 344.0 348.0 352.0 356.0</pre><div class='xr-wrap' hidden><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'></div><ul class='xr-dim-list'><li><span class='xr-has-index'>time</span>: 1</li><li><span class='xr-has-index'>YG</span>: 40</li><li><span class='xr-has-index'>XG</span>: 90</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-88b92b80-2480-48de-855a-f7b6faaf2d98' class='xr-array-in' type='checkbox' checked><label for='section-88b92b80-2480-48de-855a-f7b6faaf2d98' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>0.0 0.0 0.0 0.0 0.0 ... -1.054e+08 -1.054e+08 -1.055e+08 -1.056e+08</span></div><div class='xr-array-data'><pre>array([[[ 0.00000000e+00,  0.00000000e+00,  0.00000000e+00, ...,\n",
       "          0.00000000e+00,  0.00000000e+00,  0.00000000e+00],\n",
       "        [-0.00000000e+00, -0.00000000e+00, -0.00000000e+00, ...,\n",
       "         -0.00000000e+00, -0.00000000e+00, -0.00000000e+00],\n",
       "        [-0.00000000e+00, -0.00000000e+00, -0.00000000e+00, ...,\n",
       "         -0.00000000e+00, -0.00000000e+00, -0.00000000e+00],\n",
       "        ...,\n",
       "        [-1.06634920e+08, -1.06666912e+08, -1.05922952e+08, ...,\n",
       "         -1.07724152e+08, -1.07341128e+08, -1.06941400e+08],\n",
       "        [-1.07050680e+08, -1.06612056e+08, -1.06356232e+08, ...,\n",
       "         -1.07048232e+08, -1.07335792e+08, -1.07102304e+08],\n",
       "        [-1.05933672e+08, -1.05922800e+08, -1.05856504e+08, ...,\n",
       "         -1.05376272e+08, -1.05493376e+08, -1.05632128e+08]]],\n",
       "      dtype=float32)</pre></div></div></li><li class='xr-section-item'><input id='section-d9b8a0ac-99d0-4683-81a3-936289c945b3' class='xr-section-summary-in' type='checkbox'  checked><label for='section-d9b8a0ac-99d0-4683-81a3-936289c945b3' class='xr-section-summary' >Coordinates: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span 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'>11:00:00</div><input id='attrs-34c55d00-f0ad-4e4e-b1f9-10ce32a4c06c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-34c55d00-f0ad-4e4e-b1f9-10ce32a4c06c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-100acb15-ef5e-4156-b95a-7672c44260de' class='xr-var-data-in' type='checkbox'><label for='data-100acb15-ef5e-4156-b95a-7672c44260de' 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([39600000000000], dtype=&#x27;timedelta64[ns]&#x27;)</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'>float32</div><div class='xr-var-preview xr-preview'>-80.0 -76.0 -72.0 ... 72.0 76.0</div><input id='attrs-f673f8a0-3f0d-4602-846b-6b48e7c00130' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f673f8a0-3f0d-4602-846b-6b48e7c00130' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-53d81ed0-7386-47e6-b660-00f4d6bede80' class='xr-var-data-in' type='checkbox'><label for='data-53d81ed0-7386-47e6-b660-00f4d6bede80' 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>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([-80., -76., -72., -68., -64., -60., -56., -52., -48., -44., -40., -36.,\n",
       "       -32., -28., -24., -20., -16., -12.,  -8.,  -4.,   0.,   4.,   8.,  12.,\n",
       "        16.,  20.,  24.,  28.,  32.,  36.,  40.,  44.,  48.,  52.,  56.,  60.,\n",
       "        64.,  68.,  72.,  76.], 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'>float32</div><div class='xr-var-preview xr-preview'>0.0 4.0 8.0 ... 348.0 352.0 356.0</div><input id='attrs-05601d74-0250-47cc-a0ce-e7a8f2bee6a0' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-05601d74-0250-47cc-a0ce-e7a8f2bee6a0' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e9669950-c4aa-489e-afb4-adf36339605e' class='xr-var-data-in' type='checkbox'><label for='data-e9669950-c4aa-489e-afb4-adf36339605e' 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([  0.,   4.,   8.,  12.,  16.,  20.,  24.,  28.,  32.,  36.,  40.,  44.,\n",
       "        48.,  52.,  56.,  60.,  64.,  68.,  72.,  76.,  80.,  84.,  88.,  92.,\n",
       "        96., 100., 104., 108., 112., 116., 120., 124., 128., 132., 136., 140.,\n",
       "       144., 148., 152., 156., 160., 164., 168., 172., 176., 180., 184., 188.,\n",
       "       192., 196., 200., 204., 208., 212., 216., 220., 224., 228., 232., 236.,\n",
       "       240., 244., 248., 252., 256., 260., 264., 268., 272., 276., 280., 284.,\n",
       "       288., 292., 296., 300., 304., 308., 312., 316., 320., 324., 328., 332.,\n",
       "       336., 340., 344., 348., 352., 356.], dtype=float32)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-93488a68-bb04-41f2-b1a9-f5257ec18b8a' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-93488a68-bb04-41f2-b1a9-f5257ec18b8a' class='xr-section-summary'  title='Expand/collapse section'>Attributes: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.DataArray (time: 1, YG: 40, XG: 90)>\n",
       "array([[[ 0.00000000e+00,  0.00000000e+00,  0.00000000e+00, ...,\n",
       "          0.00000000e+00,  0.00000000e+00,  0.00000000e+00],\n",
       "        [-0.00000000e+00, -0.00000000e+00, -0.00000000e+00, ...,\n",
       "         -0.00000000e+00, -0.00000000e+00, -0.00000000e+00],\n",
       "        [-0.00000000e+00, -0.00000000e+00, -0.00000000e+00, ...,\n",
       "         -0.00000000e+00, -0.00000000e+00, -0.00000000e+00],\n",
       "        ...,\n",
       "        [-1.06634920e+08, -1.06666912e+08, -1.05922952e+08, ...,\n",
       "         -1.07724152e+08, -1.07341128e+08, -1.06941400e+08],\n",
       "        [-1.07050680e+08, -1.06612056e+08, -1.06356232e+08, ...,\n",
       "         -1.07048232e+08, -1.07335792e+08, -1.07102304e+08],\n",
       "        [-1.05933672e+08, -1.05922800e+08, -1.05856504e+08, ...,\n",
       "         -1.05376272e+08, -1.05493376e+08, -1.05632128e+08]]],\n",
       "      dtype=float32)\n",
       "Coordinates:\n",
       "  * time     (time) timedelta64[ns] 11:00:00\n",
       "  * YG       (YG) float32 -80.0 -76.0 -72.0 -68.0 -64.0 ... 64.0 68.0 72.0 76.0\n",
       "  * XG       (XG) float32 0.0 4.0 8.0 12.0 16.0 ... 344.0 348.0 352.0 356.0"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "psi = grid.cumsum(-u_bt * ds.dyG, 'Y', boundary='fill')\n",
    "psi"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We see that xgcm automatically shifted the Y-axis position from center (YC) to left (YG) during the cumsum operation.\n",
    "\n",
    "We convert to sverdrups and plot with a contour plot."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.contour.QuadContourSet at 0x7fec294e19a0>"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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GIUZmthy4BPipuz/ezA4C/gk4GvgR8Ax3v7G/FAoxDMpk5qFUzfSHJGhpaalbmEmOuqOKFNV5/sruK0FaLAYhRsDLgCuBtdHnVwOfc/fXm9mro8+v6itxQgyBrMy8rqAMSXCapIl2I2XlSL3T2qfP512CtBj03sbIzI4EfgN4d2LxycD7or/fBzyp42QJMXjUzigcfVfDJSRa1ES7nyafAT1P06Z3MQL+GnglsJRYdqi7XwMQ/X9ID+kSojfmC4u0BqKiPFUKNH3X/dLE99/m3GhtTEYr+qXXqjQzezxwrbt/3cweXmH/U4BTANYefHiziRNiIJSVoi5mAi9LmQKhi3SVrSIrs72q08LIixQ1GdkRzbJsxXLW3GH/vpPRKn23MXoI8EQzexywGlhrZv8I/MzMDnf3a8zscODatJ3dfT2wHuCwY4/3rhItRJuULTCqZv5DLTTy0tWkNLUpRyKdomqzLhtU94Gen3HQa1Wau5/u7ke6+9HAM4F/c/ffBs4Dnhdt9jzgEz0lUYheSWb2WeOtLBLJtiZDrmIRe9KUFM0/A4v4OxDt0nfEKIvXA+eY2QuAHwNP7zk9QnRCsvAokiLRfc+z0G1VnbY7daSoi2ddvc1EksGIkbt/AfhC9Pf1wCP6TI8QXRPaOyeLgyoUIDdMqCCoU7ipmqw9qkpRG0IU0j5Pz4EYjBgJIXaRFi1Ky9SryFBT+w9VqqoKUmihqMKzOZpsM1f2PF2jZ2Y8SIyEGABZb9VNR4iapOz5uxapKoLUpPSoOq39jgRtSZQkZrGRGAkxMIoKjL6FqCoh6W5DntrofabCsx5lpajriI/u72IjMRKiQ8q0t0irQsuSizUry3cw3XL7UvFGHRNfX9OCpIKue8pEQbtsZyREERIjITqiihQlSZOiKkJUZt8hytOYUHVaPosiRFOS8mUrlrP6DmuLNxwxQ5gSRIiFJ0uK4r/npWjNymW1pCiU+DxdnCtJG9WFmrqhf4rkf4xjErUtPRLr7pEYCdEBoY1QQ6WoD/qSpKESWoCHDMOwCDQ1lU0XNCk7dY4lKeoHVaUJ0RN5gzamFRJDEpJkWtqqbjtozUq1NZooRc/6WNCzNE2Gk9MKMVHSIgahUhRSpbTPimWF/9pEUSRRRFFUdKooWtQsZvYmM/uumX3bzM41swMS6043s6vM7Htm9ug651HESIgWmZeioh45WVKUJh5lhCdt21u2NxvpidPYZASpjahRKBrTqDp1RnEPbV/W1nMRes8VLeqFzwKnu/t2M3sDcDrwKjO7B7P5Vo8H7ghcYGbHufuOKifRa54QPRJSOMxLUVNRoLaiS0OPIDUZpZh6xKMJQiNEB61ZWarRfbz9UMf1UrSoedz9M+6+Pfp4EXBk9PfJwNnuvs3dfwhcBZxY9TzDzb2EGDlF0aKsz1lS1EW1WJPnGbIc9YEaYe9i/tlvYmqbLgVJ0aJB8LvAp6O/jwB+kli3IVpWCVWlCdEBeW/NIW2KuhCiptEYSCJJ3aqzLpDwFGPLl7P6DvvXOcQ6M7sk8Xm9u6/feXyzC4DDUvY7w90/EW1zBrAdOCveLWV7r5pAiZEQLVNVivqMuDTd/qgKfbchaYNFaGuUjIx1Ob1N3eelybZFqkbLZaO7n5C10t1PytvZzJ4HPB54hLvH8rMBOCqx2ZHA1VUTOL7XUCFGRBNStIjRor4aXCdR9KA8VSZDHgJDaXC9AFJUCzN7DPAq4Inufmti1XnAM81slZndBTgWuLjqeRQxEqIlQifFLGpoPTaGKkVDEZ1FiBplMcRoUdNSNJTnbKL8LbAK+KyZAVzk7i9098vN7BzgCmZVbKdV7ZEGEiMhOiFtQlgYphT1VY3WZpRIhVX7hAxN0QZdSFEXLKosl8HdfyFn3ZnAmU2cZ3yvo0KMgLQqtDFIUV2qRovajBJVKfzaLjAXqYdam4LUlRS1HS2SFA0LRYyEaJiicVuKGllLisozpDf/RaTsgI5990QbkhSJ4SExEqJB6k4I27cUdV2NNpVqkCpMpa1R3pQ3Q2x03YYU1WEKz8DUkBgJ0TJZhcPQpKgOVaJFVaWo7cJq7MK1KFR5ftqSIj0z00JiJERDlKlCG8qo0E1EiMpK0VCFqMo56qZpKlGjodP1fZ0ytnw5K9au7TsZrSIxEqIBylah9UHT1WRlhGgMVWYqDLvjhi231/pNhD5PXTS812CO00NiJERLhFahQXvVaH3KEIxDiKoy9PRNlZBnqqueiHoGpkmuGJnZeQHHuMHdf6eZ5AgxPsr2QmubvmUIhl1dNqTzgqrTyjAkKRLTpShi9IvA/8hZb8DfNZccIcZLkSBBe22L2uhN1mX3+7EJkQrSbEJ7opWtTit6rroWIj0D06VIjM5w9y/mbWBmr20wPUKMiiYmyaxTjdaUENWdxgO6F6K8fYsKZxVq3XPjltv3uC912xolj93FPk3sK4ZPrhi5+zlFBwjZRogpUncgxzpUEaIm5CeNLoVoqoPtLXJ1WpEcNR0pqvtsjO3ZEuUJanxtZscBfwjcObmPu/96S+kSDbFIUw8MgbYHtCsrRG3JEJQXoqm8oQ8pLVMhS46alCIJkQgltFfah4H/C7wLqDxjrRBiT+ZlJ1m1NiQRgmFVl/XB0NIzdOarz9Kq02Lm5agpKWrinrVx38caIbTly1m+/x36TkarhIrRdnd/R6spEWLibLl9Kag6bUgy1FfvsiEKSJtpGmshWYUiOWryPEM4hhgfRd31D4r+/GczexFwLrDzF+zuN7SYNiFGQR/zQXXZhb4MEiIxT5oI5clR6DGrrKt77KZYJBEeI0URo68DzqxbPszaGcU4cEwbiRJiqsRCU6UhdlcjTZdh6m/lQ07bEKjThrGuHGUds499yyApGj5FvdLuAmBmq919a3Kdma2ue3IzOwp4P3AYsASsd/e3RpGqfwKOBn4EPMPdb6x7PiGaIiRDz+ttk5ScNEnqcoTpskxdhqDb9I21oGyiY0cVOcq6NxqTSjRFaBujfwfuH7CsLNuB/+Xu3zCz/YCvm9lngd8BPufurzezVwOvBl5V81xCDJIuB1IsS1OFRhuFT9Yx26qiEdVpIzo0f/w2t2+CsQrwIlLUxugw4AhgjZndj11VamuBveue3N2vAa6J/t5sZldG5zsZeHi02fuALyAxEiOkqQHskscrSx+FQJcilLddaGEsISpHlWhRlhyVkaYxVJWlISkaF0URo0czi94cCfwVu8RoE/BHTSbEzI4G7gd8FTg0kibc/RozO6TJcwkxJsrI0Nim1mj7uEMXnkUrMJuQo7R966xvm0W7x1OgqI3R+8zsA8Cz3P2sthJhZvsCHwVe7u6bzKxol3i/U4BTANYefHhbyRM9MKWRgJueEyrJ1ESo7WOL9imSnKpylPZctNk7rS5Tyb/2YPkKli36OEbuvmRmvw+0IkZmtpKZFJ3l7h+LFv/MzA6PokWHA9dmpG09sB7gsGOP9zbSJ0QayUw86+8kQxufJT5OyFt6FwVM34VY10y20AxkaG2OmmbR7+/YCW18/VkzewWznmK3xAvrjmNks9DQ3wNXuvubE6vOA54HvD76/xN1ziPGyVijRkPohjz0OcX6Lrj6ZIzPdFlCfgNZ4xuVOUeZ5V2wCPd2EQgVo9+N/j8tsayJcYweAjwH+I6ZXRot+yNmQnSOmb0A+DHw9JrnESNlyHKUFylqcwC7Otv2wdDT1xVDfY7boqoc1T1nHyzavZ06QWIUj2fUNO7+ZXY16J7nEW2cU4i2SJOjNs81NIaYpiGgQjOfJscy6hrd22kSJEZRO6BTgYdFi74AvNPdh/F0ikkz5KjRPG21nWiyIKg7/s9QCqWhM5Zntk3abks0f66u0L3tl6hpz5uAg919Y7TsdOAFzCa6f6m7n1/1+KFVae8AVgJvjz4/J1r2P6qeWIgp0MY8UPExutinyf0XnUUqLK/btC14LKM+qtRCWKT7NSWiGTMeyayZTbzsHsAzgeOBOwIXmNlx7r6jyjlCxeiB7n6fxOd/M7NvVTmhEFUYU9QIqnU9Lnt80R9jehbHQp1ekqG/B923SfAW4JXs3inrZOBsd98G/NDMrgJOBC6scoJQMdphZnd19+8DmNkxzMJVYkA0MXeRKE/euCxNn0d0hwrR5ugjIpRE93JQrDOzSxKf10dD7xRiZk8Efuru35ob7/AI4KLE5w3RskqEitEfAp83sx8wayx9Z+D5VU8qmkdS1C9D6KJfhqyCYpGfIxWe7RI/z6GR1NCXjaLfie5rs9jyFSyvN8DjRnc/IfP4Zhcwm1h+njOY9Vp/VNpuKcsqj20Y2ivtc2Z2LHC3KAHfjUJWYgAscmE2JNqc1qCIpjL/tOOEPF9NFj5dPc8qMOtRpp1RkhBBSm4nFgt3PyltuZndC7gLEEeLjgS+YWYnMosQHZXY/Ejg6qppCI0YATwAODra5z5mhru/v+qJhZgieZl+0xl9VwV71wKRPF9RwSu56ZeqcgThghRyDDF93P07wM55U83sR8AJ7r7RzM4DPmhmb2bW+PpY4OKq5wrtrv8B4K7ApexqW+SAxKhnFC0aJm1k2IsoAYt4zYtGVUEK+Y3p+VkM3P1yMzsHuALYDpxWtUcahEeMTgDu4e6aj0yIjlCmLsZA/JzWfUkrUxWtSJFw96PnPp8JnNnEsUPF6DJmjaGuaeKkohkULRo/fcjPtZvzz3nIfnquRHnqVKvFVGl8nZceIaoQKkbrgCvM7GJg59Pm7k9sJVWiEEnR+Ggjoy6SnCaOKVESoTQVPQJFhUR/hIrRa9pMhBBTZSwyFHo+SZIIIfS51wueGCKh3fW/mLfezC509wc3kyQhxssURCiPazdvkxyJxmii+k10zLLl+Kp9+05Fq5Tprp/H6oaOI8RCMyQJykJyJJpEciSGRlNipN5qQlRgDCKUhuRICDFVmhIjIUQgY5WheSRHzRIaNZlibytFjcSQaEqM0uYpEULMMRUpipEcVaeqCCT3m5IkSY7EUAgd+XofYIu7L5nZccDdgU+7e9yf8jltJVCIsVBUSE1NimIkR2G0UejHx5ySIAnRN6ERoy8BDzWzA4HPAZcAvwk8G8DdL2sneaIuB65ZqfFABkCXUnTtpq3B2x6ytpl+E5KjPeky+jEVQWoyanTw2lWj/z5EP4SKkbn7rWb2AuBv3P2NZvbNNhMm6hOPHBv/L0HqhzalqIwEhezflCgtKn1XBU1BBjQGkuibYDEyswczixC9oOS+YiAoejQN6spQ0bGrytEiRY2GXChPJXpUhNok9YPbMpZWr+07Ga0SKjcvB04Hzo1msT0G+HxrqRK1yZqMUXLUDKGFThvRokPWrm5VjqoyZSkaYwG8CIKUJ0djvO60axnjdYydMiNffzFqhI27/wB4aZsJE9UpmqFacjR+2pAjVaPNGKME5TGF6rU8xhw5Ckn3WK9tzCwL2cjMHmxmVwBXRp/vY2ZvbzVlQgyUKRYyiy5FB69dtfPfFJnqdWUx9N/olJ+1KRBalfbXwKOB8wDc/Vtm9rC2ElWFFcuCHG/yFEWLktspalSeMhlu2z3RykSNYvFRY+tdLFrBNOWqta6iRov2zCwqwQ2o3f0nZruN47ij+eSIOoRKkRg2sbyESEuWHGXtu8giBCrYYDGq1ppGz81iESpGPzGzXwbczPZi1r7oyvaSVY2p/+BFv7QZLUqTm9AeYosuOyGoYNudKeaVTV+PnpnFJbT+6YXAacARwAbgvtHnwaGHORxFmIZBXnXYEHufjQm15chG3002+l4Wm9BeaRuJRrkeA1N8GypCktMubT5PU4j4DK2rvgq2cBYxv8xDz44InSvtOOAdwKHufk8zuzfwRHd/Xaupq8GUxraYZ/7a6kjRmBph95mBlzn3VOdEGwMq1Kox1Ylpy6LnJ4Bly/HV+/WdilYJrUp7F7MBHm8HcPdvA89sK1FtMvYHf+zpr0uf17/o3/3Q0f1pBlWxiUUntPH13u5+8VyvtO0tpKcTphQ6bqIKbUxRo6GziNGiPqvRVIC3x5S79wuRR2jEaKOZ3RVwADN7GnBNa6nqgDFmqE1Woc0zpjZKihotNlMfjHFoLMr3vCjXKYoJFaPTgHcCdzeznzKbO+2FbSUKwMweY2bfM7OrzOzVbZ5LzBiTHA2RRYwWdY0Kr37Q9y6Ggpm9JHKDy83sjYnlp0e+8D0ze3SdcxRWpZnZcuBUdz8pmittmbtvrnPSwHP+HfBIZsMDfM3MznP3K5o8z5iq1NqMFs0fdwzVamNpiC2aQQVz/0z5udfzNQ7M7NeAk4F7u/s2MzskWn4PZu2ejwfuCFxgZse5e6WBqAsjRtGBHxD9fUvbUhRxInCVu//A3W8Dzmb2ZTTOGH4QIWk8cM3KzH9lGUvkaAz3bup00b5I93k46F6InjkVeL27bwNw92uj5ScDZ7v7Nnf/IXAVM4+oRGhV2jfN7Dwze46ZPSX+V/WkARwB/CTxeUO0TFBeXKYsR2LaqCAWbaNnbFQcBzzUzL5qZl80swdGyxt1htBeaQcB1wO/nljmwMeqnrgAS1nme2xkdgpwCsABh96xpaT0S2i0KGSbslVkyeOOoXqtTxaxfVEX0aKuJgcVi4uesZLYMpb22qfOEdaZ2SWJz+vdff3Ow5tdAByWst8ZzJzlQOBBwAOBc8zsGAKdIZTQka+fX/UEFdkAHJX4fCRw9fxG0Ze5HuDIu92r8pcwJvoazFGSJIQQogE2uvsJWSvd/aSsdWZ2KvAxd3fgYjNbAtYR6AyhhI58/baUxTcBl7j7J6qePIevAcea2V2AnzJrVPVbLZxn0LTxFtNE42pJ0uIytKk/hGgCRY1Gw8eZ1Vx9IZqRYy9gI3Ae8EEzezOzxtfHAhdXPUloVdpq4O7Ah6PPTwUuB15gZr/m7i+vmoA03H27mb0YOB9YDrzH3S9v8hxDJ/RHWrX9UFNCI0maHpIfsYhIjkbBe4D3mNllwG3A86Lo0eVmdg5wBbPBp0+r2iMNwsXoF4Bfd/ftAGb2DuAzzLrTf6fqyfNw908Bn2rj2GOl6QEdmxaZsXT1F3siGRJi1yjfEqRhEvVS/+2MdWcCZzZxntBeaUcAydZW+wB3jIxs8Vqdtkyb0aIm9886pnq0jYdD9ls1eCma6tg5Yrhct2mbnrsFJjRi9EbgUjP7ArPW3w8D/k804OMFLaVNdEAsMW1Ej9o4rmiOoQuREEL0QWivtL83s08xGzDJgD9y97jF9x+2lbhFJCta1HYUpq1qMFWvDRNJkRDFqN3RYhLaK82ARwDHuPufmdmdzOxEd6/c6lsMD0mMEEKIPHYAt26f9ug4oW2M3g48GHhW9Hkzs7nMRMNk1Wt3JSxttBFSmyNRF7X3EEJ0RagY/ZK7nwZsBXD3G5mNHyAmimQmGxXS/aDvvX90D8QiECpGt0cz3juAmR0MLLWWqgUnNGrUdhSp6eEBpoAKhn7R998f+u7FohAqRm8DzgUOMbMzgS8D/6e1VInBZELqfj89xt7weii/DbEY6HlbPEJ7pZ1lZl9n1gDbgCe5+5WtpkykcuOW2/cYbboLcWlqKpExN+5WBikWFT37YpHIFSMzOyjx8VrgQ8l17n5DWwkTw+sqqrGJxFAY2m9DCDEdiqrSvg5cEv1/HfAfwH9Gf3+93aQJSH9T67qt0Tx1IlRjrZbTG/Pw0D3pBn3PYtHIFSN3v4u7H8NsMtcnuPs6d78D8HjgY10kUAghRD9IisQiEjolyAPd/YXxB3f/tJn9eUtp6pQx/PDTqg26alvUNH1Vw7V5n6/dPPxnaKqoSq09xpA3doWes10sLcGtt0+7U3por7SNZvbHZna0md3ZzM4Arm8zYWJ3ijKpLoVjbG2MJEW7M8Y056EJP5tH3+ee6DtZHELF6FnAwcy67J8b/f2s3D1GwNge9Pn09tHWqM45uhYqFZiLhe51M+h7zEZ5ymIQ2l3/BuBlLadFVCCt+z4038hZUaI9mVrkZQrE913VHtVQoR+GnrNpkxsxMrPXFB0gZJshMtYMIDTdTYpME8fqUqzGem+7pK7UXbt5W+q/oRC/2etZCEPfVTX0vU2ToojR/zCzTTnrDXgm8JrGUiQKmW8ImNUQu24D7bFFibpkSBLQNXnXPr9uCKNspxVcetPfhQr2+iS/Qz1b46dIjN4F7BewzaiYQkZQRo76ZmrRoqlI0bWbt5USlyrXndxnCJIUI1maRj44RCRJ4ydXjNz9tV0lRIgxMBUpigmRo6aueaiSFNOmKAytgJQUdYMkaZyEjmMkBkho1KhPphYtmiJZctSmBMbHHqIgtUHos9lG4anfxTCYiiQt4dyyfdrjGEmMJkZbvdKqpKErusr4pxYtStLXtS2aIBUhiVkMsu7zmIVpSkiMRk7WiKxdR4/6aMvUZSEyZSkaAmW/X4mUmCLzeZpEqR+CxMjMjgPeARzq7vc0s3sDT3T317WaOhFEnhxlUVeapji1hxgPZRuOCzFGplL9NjZCI0bvAv4QeCeAu3/bzD4ISIxGyhB6q4UwBBFStGiYqBpOLBIaVLI7QsVob3e/2MySy7a3kB5RkbFPcjgEAUpDUhTGtZu2Bm13yNrVzZ+75j2SWIkqZD13bT9PiyxIZnZf4P8Cq5k5yIvc/eJo3enAC4AdwEvd/fyq5wkVo41mdlfAowQ8Dbim6klFO4wl7DpUCZpHUpRNqAjl7deGJFUh7z5LmkQaoYOctvn8jCUfbZg3Aq9190+b2eOizw83s3swG2z6eOCOwAVmdpy776hyklAxOg1YD9zdzH4K/BD47SonFN2Q96PpSprG/MOVFO1OVREKPeZQJGmepp4DCdZ0KPNMqLq3cRxYG/29P3B19PfJwNnuvg34oZldBZwIXFjlJKGTyP4AOMnM9gGWufvmKicTw6BIWKqI05glKMmiCFEbolOH+fQMVZSqoqjUYiNB2o11ZnZJ4vN6d18fuO/LgfPN7C+ZzfX6y9HyI4CLEtttiJZVIleMzOwPMpYD4O5vrnriptm+tBRUOA+5imkoTEVyyjJ1KRqaDOUxhmhSU/TVVkWUp4nJl2PGen+XHLbcXmuAx43ufkLWSjO7ADgsZdUZwCOA/+nuHzWzZwB/D5zEbN7WebxqAosiRvE8aXcDHgicF31+AvClqiftm4PXrlrYwl8sJmOSonnitE9dkOYpKoTHWrCKGVOQpDZw95Oy1pnZ+4GXRR8/DLw7+nsDcFRi0yPZVc1WmqC50szsM8D94yo0M3tNlCgxUKq+2SzqD3TK0aI+pOiWW27LXLfPPntVOuYiRZFCSHtmF/X32wVdTJEDuocFXA38KvAF4NeB/4yWnwd80MzezKzx9bHAxVVPEtr4+k5AMqe7DTi66klFezQZ6m2Lof3wJUX1yROhvG27kKQq38FYxUsFbPekPV91nh+1R8rl94C3mtkKYCtwCoC7X25m5wBXMOvGf1rVHmkQLkYfAC42s3OZ1ds9GXh/1ZMCmNmbmFXJ3QZ8H3i+u/88WtfYeARZTLE6bSwFfEg6u8oUxvKdVaFJKSojPlWOW1WQoP0ec6EMTaZUwDbHfD5R9Hw0Uf2r+7cn7v5l4AEZ684EzmziPKG90s40s08DD40WPd/dv1nz3J8FTnf37Wb2BuB04FVNj0ew6JTJ4IeUsXdRTSApmtGW9JShiShS3+R9533+tlTA9ocEaZyEzpV2J2AjcG5ymbv/uOqJ3f0ziY8XAU+L/m50PIJFIa2QL/vWm7X9UISpKVmashCFMgQZyqKJKNLQaLq6pVIaVMA2QpVoogRpXIRWpX2SXV3f1gB3Ab7HLKrTBL8L/FP0d/B4BGZ2ClEd49qDDy990qlUp5UN85Y+fsXjdZHxz197XqaxKEKUdb+GLENpTFGQkvQ1dpMm4C1Hk/lGU4Kk+9cuoVVp90p+NrP7A79ftF/eeATu/olomzOYNZY6K94tLQkZ6VrPbERuDjv2+KAxC6YgQnnMZ7ZlCsOmC6A+IlCLIj9j4dab05+/vfcNf9amUM0WQpe97lS4VqOpl866gtRn9GjHknPDSCYhr0poxGg33P0bZvbAgO0yxyMAMLPnAY8HHuHusdg0Oh7BIlM2QpC2fRsF0dRHOR4iXUSLsiQob9syggTNSlJXz3sVuviNSI6KSb5ohURiyz4/TQmSaJbQNkbJEbCXAfcHrqtzYjN7DPAq4Ffd/dbEqkbHI1gk2uidU1SgNlGQSJTGQxn5KXO8soIE7cheF897FdqKJkmOwkjLW9OelarVv4s6iOlQCY0Y7Zf4ezuzNkcfrXnuvwVWAZ+Nphi5yN1f2PR4BItK/AMtW5DVeYOfp+4YNcokmqGKQDQtQKHnqyJIXTIEcWpaktqQo3jqpTE3XciKxoT8niRI4yZUjK5w991Gujazp1Nj9Gt3/4WcdY2NRzB10n68dd6k5wvEOgXVfDqqZhKgjKILupahojQMXZLS6Lp6rqnfSJNylJyPchKCVCMSL0EaJ6FidDp7SlDaMtET8Q8pmTEnC5ktm/fMsNfsV/xjbaLxbEyfdfEinSHIUBZjl6SYrhqPD/k3MjZBqhMtyttP+d44yBUjM3ss8DjgCDN7W2LVWmbVXINh+47KE+lOkrhQSROimKqylDz+PKEFWNXCQhlFPqG9ErsSoqznL/Q5i5EkhVP1N9JFe6OxDZGS/D010aatjiApz+uOoojR1cAlwBOBryeWbwb+Z1uJEtWYb1eUJ0VZzO9TpwCDsEKsSmYhQapGm0JU5nmLty37fEH6NYxRltoep6lKYVpXjpLVaGOl6eYJaSjPGza5YuTu3wK+ZWZnufugIkRpLGoPi6I68C03Z7+hrdk3//tqSpTaFCRlFGE0KUVVpDvvOFUEKUlbwteFcLUZRepDjqZCXr7aVBODW265bXTRo+1Lzo2LPI6RmZ3j7s8Avmlme9RVufu9W0tZRcb+ow4ZyTltbI2saFGeFKWtLytKUK6tUhuC1HdGsWg0JUVpx6wrSE3TZGeEEKoUlEUM7fcx5Oq0OG/Nq0JrWsL1Qjg8iqrSXhb9//i2E9IkY5Wj1PnOAgbwqipFaST3KZKknfskCsqigq0tQVJGsSdtjPPThhRlHX9okgTdVOO1UcXWxe9j7NVoIVVoRVJ06823VX4eykpxG+PWiRlFVWnXRH++yN1flVxnZm9gNkCjaIAyI5imvc3kSdG2zT9PPc6q/Q7IPU+bklRWkCRH/dO2FGWdb4iClKStqFKfc8WN9eWyCbKEIzRS1KUciXYI7a7/SPaUoMemLBsMY/phhww7n0YdKUpblydKdSSpCUGSHNWjbvi/aynKO/dYRKlJQWpqhPmh/DaGVp1WFC3qcliLqU+ePAaK2hidCrwIOMbMvp1YtR/wlTYT1gRjkKO+pCiN5PahkgTh7ZKKBClEjkAZxpio0/A/85gjEaUmhxgYuhyNvRotpmg8uFDqRI1iFD3qj6KI0QeBTwN/Abw6sXyzu9/QWqoWhDLth9IIlaKtm/ac1m712oNzzxsqSfPnzSvstmy+rZPo0ZDejKdApWEfAtq3xdtUFaSdx2lorKQ2aSKKpBeDdkhrcN0ETbRHkxz1Q1Ebo5uAm4BnAZjZIcBqYF8z29fdf9x+EusxhqgRpL+p5JElRfNRojQpSlueJ0rxMYsEKZmOrMKuyeiR5Kh9ykpRnQb/dQVpj+MGpL1reWpKkOoUlqG/jbbzziFUp3VdhVbl/kuOuieojZGZPQGIZ7u/FrgzcCVwfHtJmzZlq9DSfqB5UpQlRFkkt8+SpCpRpDxBqhs9UobRPmv22ytYjqpIUdb+TUtS5jl7ijbVrWoZUvRoCtVoaXlwlhQV5V0hlL3/Q7rfi0Bo4+vXAQ8CLnD3+5nZrxFFkYbC7TuWMteNJWoU+qaSzMybkKJ5tm66LriqLUSQqsoRFGcgeXKkqFEzxPeoSJDW7LuqthzF5D03XdBFj7gm2qEMges2baskR0OPFol0dizAAI/LAre73d2vB5aZ2TJ3/zxw3/aStTjMv6ncevNtuW8qZaVo200b2XbTxtLpCpWrbZt/XtjIO6+w7LO3kyhH19VOW27e1phoVU7D3G+uaepW1VQtyDUGzi7KfBd951cSt24IFaOfm9m+wJeAs8zsrQxsEtkiyowT1AdZD3ycMc8LUagUJf9O/gth66brSglSHnXkqKjwyMssVAA0S5EctRHlmbogddkVvCyh+WbZ6M/Qo0VDvieifULF6GRgC7OJY/8V+D7whLYSVZWxFIJZmU2yQXVaRjxfQIRKURplBSmEouhRX3IkmmXNfnv10uNrKII0NMb27PctRUnGFC0S3REkRu5+i7vvcPft7v4+d39bVLU2KoYWNUrriZb240sTojpSVGXbpqJHbcpRFmMR5rHRV3f4vgWpjehRX1VqTTIk4clj7NGiIdzrvjCzp5vZ5Wa2ZGYnzK073cyuMrPvmdmjE8sfYGbfida9zcys6Dy5YmRmm81sU8q/zWa2qfrltcdYC8HUXmcBQlRHipL7tBE9yqItOVrkDGNIdNajbGKC1HWB3EZeWSRHQ5InRYtGyWXAU5g169mJmd0DeCaznvKPAd5uZsuj1e8ATgGOjf49pugkuWLk7vu5+9qUf/u5+9rSlzQAhhY1SosWFQkRNNfIev4YIYRGj9qSoyqMVZiHzhAGURyCIA2Bob8YDEGKqkSLhnJ/kwz9XreFu1/p7t9LWXUycLa7b3P3HwJXASea2eHAWne/0N0deD/wpKLzhLYxGhVjKASTaUz+GEMiREkpaUKIkpQ5VoggtSFHihoNizQ56qOrfSxIfUhSU9GjoVfjhJAUoOs2bdv5b0iUKSPm29Q18TIwhWEaBsYRwE8SnzdEy46I/p5fnkvoOEaiIZqOWK3af10jYrRq/3WV9isa70j0xz777LVTFPfed69ShW5Wxp11jLSBIJsc12gMDCF6NhSGJkJNUPf+NiFDQxjgcXv9cYzWmdklic/r3X19/MHMLgAOS9nvDHf/RMYx09oNec7yXBZSjMYy4OOq/Q7YLeKyeu3BqRGaWGpCBamqBCUJFaKQaUSqkDc4XtagjxrwMZ+QjDveJk2QhiJHfUSrpixFY8kvi+iyGUXTEaEhCFGDbHT3E7JWuvtJFY65ATgq8flI4Opo+ZEpy3NZSDEaMkUFSZYcQTPCU8TYI0SSo3TKZuRZgtS3HI1dilTF0i9lI6tp+zfFxGSobc4DPmhm8dRlxwIXu/uOqLPYg4CvAs8F/qboYJNsYzQWQtrDpEVcupST1WsP3u1flwyx0ePU2HvfvWpl5mn79tXmaOxSJIZBld9D3d9Rkn322UtSlIGZPdnMNgAPBj5pZucDuPvlwDnAFczGWjzN3XdEu50KvJtZg+zvA58uOo8iRiMlL3JU9XhN01Y1WgiaQ21P2opGpL1ldx05khSJqiTb4sWERo4UIeoWdz8XODdj3ZnAmSnLLwHuWeY8CytGfdabN9VrLpaZMoI09qowMUzSqta6kqOpSJGq0YZFnhxJiKbNwopRH4Q2/psvPOYbYc+zqLJTZ3byRY0atc18YdJ3m6M2UKRocWhLViVDw2aSYjTFAq9IjoZGn9VoMXnVaSA5CiXvO0xrJ9elHHUdLWpLihQtmjYSoXExGTFauXxZqUKuSjXawWvD9skaw+OQ/VbNqvDWrubaTVt31m3PZ4pbNt+2W4YfFyBDkI0mCCnMQgqgosIkJDOSHNUjrX0GhMsR5A/0Oc9Uqs1iVCXTLAevXVWY/8Kul+e4WUP83dUZILbJ73/IedL2paVJjlOVZDJiVIY2pSi5bdrDkyVHsKswSWbE85K0c3nFt+0qBUtT1R6h525CisogOcqmTmafJkewZ2/DIkGaSlQoyRCEKPSZH8sYRnG+m8yr5/PgpBwBO/PhmD7kUnnP8Fg4MSr7Iy8jRGn7hph18m1lvhHrfCYdFypdFhaddLUOLIxCCxS9PXdHVtQIwnusQT/RIOi2zZAG/uuWtJfUuAzIih41hYRnvCyEGFV946kjRcljZL21pIVzk9GjJFmi1DVNjy1U5nralCJFjerRlBy1TR+/nzbaD0mIdqcor87Lh3d+nvv9lxGlpvOOkDJraBOiT4nJiNGK5dZoyLcJKcojq757PsPLEqWYtsfaSCvQ5ilbwJUtnLpqmDp2OZrPyIc0oW6XctT3y0Obz2tTQjTm53ye0Lw6JHqUpMvvqErZNZYqzjHSuxiZ2SuANwEHu/vGaNnpwAuAHcBL3f38rtLThhBlVallvbEU1XknC7y2pSHt+CGy1Na582ii0Bi7HPVJXtQIwsc6CqVvAYLupF0RoubIEyRoJhIjaRk3vYqRmR0FPBL4cWLZPYBnAsczm/PkAjM7LjG8d2u0GSXKapCd9oPMKpjne1B0SZaM1ZlXKI2qBU2T30n8PUuQypMV8UwS2ih7nkUSIWjvdz6l57puG1DIz5P7JOvapt4jbAj0HTF6C/BK4BOJZScDZ7v7NuCHZnYVcCJwYVuJaLvabP5ced1J58mrA99j24YL9LzIVVFbqDLUKWzalMQxRY+abjjaFFndoLOq1mJ2djKYcLVYFooO1efANStTl9+45fY9luX1YuuKKr2eRXv0JkZm9kTgp+7+LTNLrjoCuCjxeUO0LO0YpwCnABxw6B1H88CUeRMoensJEaem34CqtIVqgi4LjLEI0VgoOx9VV0LU58CKXQtQlWd6KNGTNNLy0SwhyluflKWQMmQ+nx5LuSPCaVWMzOwC4LCUVWcAfwQ8Km23lGWednx3Xw+sBzjybvdK3aZJin50WaS9paRR9gd23aaw+d6q/nBD20aliVKSkEbAXRUSiyI8TTS8bvqepEWP0todlWHoI0YPIfoztWc+Kz9Ly5/z8uw4Xy4TXco7fx2qli19sH2HT75HXKti5O4npS03s3sBdwHiaNGRwDfM7ERmEaKjEpsfCVxddK4Vy6zw4Uo+6F0+iG2c68Ytt5f6gVZNw4FrVgaLXZIuBk2bWoa/KGRFj2KSkjRU8RmC8BRR9/cxxGhRkRSVyeeKokdjkhXRLL1Upbn7d4BD4s9m9iPgBHffaGbnAR80szcza3x9LHBxE+cdy4MeInhlr6XLa0+O0ZS5TUqbGInOcGi74C8a96gvhi48Xf1GhiZFeS+BWVJUJs8rih6lbdskYymbFoW+G1/vgbtfbmbnAFcA24HTQnqkLc+IGLXxEFelqahNlePU+eGViRqlVe/1PUbI1Gm64XVXclB3fqqhS0wIQ/wd1JWivCmRmiak+uygnLzvhgAhms/7JDHTZxBi5O5Hz30+EziziWOP5SGu0miwDHmZQ+j+N5SUzDhjzMto8+qqG280PvF68ZghDewYMt3CFARnniEKT1tkRXNCp0SqevxknpgWNQrJ87K2uaGlKrW0F8yxlFGLxCDEqAmy2hgNKWKUJOvHUFdgslizclntYxxEeBVfWhuoKr3umiTrXIsiTCG0NUN4W/NRdcWiiE6Xc0nWOX6oFJXJ97bcvrTH/mmUfUFMUkeCqrycimpMRoyyKNMgu680pP0ImxCZJPusqH+8fVYs45bts8zjiJWrdstIksy3gYq/46EOWFYU0aoa8RJ7khSMOpK0KKLSJW28pDQVNcpiXoqSeWlaHpqWD8Z5Wl6eGypNbdPnuReJyYjR8mUWFBadp68wZqgMNSE0MXs3LFsxeZGktIbi8zLa9ltnnYy5qLAIaU+1iISIy6LLTV0RaepZa3uS7apyVKZbPqRLUUj+mbdNiDQBmS+JdQmVNdEskxGjZbbrIZp/YMpYdpuhyqx0zD/8eT/UpuRm7xVpw0Xlc+t233n+W29f2hlBitM/L0hZUtSEjJaJ9BVl4E2+0bbx1l22ACyasyxvvyYYu/AMrUdWFn2mc0iDGs7nJ/P5aZU889aoDAmRprRzdkEf5wS4fcfSaKvEQ5mMGCUJeWCybLvLUGWRENWRoDLis+y2W3LXL+21T8oxd09bLEhbbl/K/A6LpKiM7JSVq7xjdylOVSiKSh2ydvUeGVVZOepKisYiHWKcJPPUfVYs2yMPDckXky+AqesDpCmPpFDFNFkzIOozGTFahgXbPYTbdpPhyqxzFglRlehOkiLxqbL/3pEszQtSzLwg3ZAhRU0PqJYlQGVHt01SZZqANpkfeRzqyVGbvcIWVYTajKj0LepVRujvmmSeOp9/5uWHS3vtk5vfFkkT7BKnkLQV0VbzB5HPdMRo2Z4PUfIBLXoY0ywe2g1XVhGiupJjWzfX2h/AV++3Mx1FggR7ShKEjR+SRpHIlI1I1RGmJCE98JqkjBxBdhf+tnqhlWFI1TJjIO/76luauqSoa/7eK5ftloeG5J1VpenW7btmpJLMjJ/JiNFyZiIR+oDOW31VcSpL2nnyhKjox1xXdJZt3VR6n/ibCBGkZBukmLzqNmimsXyoBJWNMOXtkySt8Oqi0EqTI9hTgLoY6ygtWlRXgpoS2anStqAPWWKzGlwn89Cq+WUyr0uS3swgjN3Kqpq1AouCmT0deA3wi8CJ7n5JtPyRwOuBvYDbgD9093+L1j0AeC+wBvgU8DJ3z51bdTJiFFP0gMUPYxlpgnbqgIsiRPM/xDI/6irCM49tuxlftW/msecFKX6jygs3p4kS1OsOmyZSoQVolbGvinrZZdG0LKVFjSBbjpI0XX02Hy2al6KiArVuNeoiDZJXt+NBkz3EhkacT8fRojgPTeadZfPGpdVr98h7ffV+s2MVRJjyKCqr6tYOTJTLgKcA75xbvhF4grtfbWb3BM4HjojWvQM4BbiImRg9Bvh03kmmI0a+lPkgJR/QOqHQorrjENKOnSdEaTJURXps282l9ynaL76SpbnPcfRoXpDinmxJQrvDxqS1+SoTfQqRmrLikzZmUyh1C646ctQUeVVoadfX1jx/ixI1qirmMaFt5oYoQyHzoc1XocV5aJxvlskLfdW+e+S3aaIEu2QppmmxaaIZxNhx9ysBosnnk8u/mfh4ObDazFYBBwFr3f3CaL/3A09iYcRoacduD07yIa0qTElZgvC641tvXwraNlSI0kSoqugk2XHT9ZX3Xb7/HXamoUiQIL3RYpooJUmrviw7rkdW26aYpkWpjiTFlJWlPDmC7kebzmtwnSU5TUR8+owa9SlldUUpjb6lqMz5D1qzMjVfWHbbLdjWzbvln3GeVZT3Ld//DrttH5MmSpAtS0XE5ZSkp1GeCnzT3beZ2RHAhsS6DeyKJGUyGTEyX9pVxVPwkBaFQUPqjeelKUmeFIU0qM6TorJCVEd+io6bzDziDCP+7pN18vONFvOqM8s0mIfwsURiaUqLLhXNixQ6iWTZySbrVInMi1JSRtIaZUPzgpQWKUqmI05z2VnPmxKcLmWlDykLbR+3KJG0tO75SUKlKGub5MtgTNzUIEuWisgrp5poDtEGS0tet43iOjO7JPF5vbuvjz+Y2QXAYSn7neHun8g7sJkdD7wBeFS8KGWz3PZFMCExSpL1QMUPatbDmCdM8/XFTXehn09T2ltOkraEpwwhcgS7X2tWz46Qtl+7bd/AAGx1ZAnqt1eqU0WUFKUsScoSJGh+Oo40IYL0Oa2StCkUQ5KVNggVoEVrsB63LUpGi9KkaCkwD10W5XHJffMiSjv3a0lsmqgt6JmN7n5C1kp3P6nKQc3sSOBc4Lnu/v1o8QbgyMRmRwJXFx1rOmK0tCP3gckKgUK+MIU0stt5nJzGdln7lxGiIcjQPEVyFJP1PZbt1VGm8XyWNOW1awqVJQgrcJqIGhUJV5YkZQkSVJOkrLZERVGiIjmC7ueAamuE+y5krKlI0Zgm3a7DvBSFClHM/PbL9r/DHnlxliiJbjCzA4BPAqe7+1fi5e5+jZltNrMHAV8Fngv8TdHxJiNGvmN7ZvgT0h/YkDBoUXQpSWhju5AG1cn0pl1X2R/3bueKvpOmyJIjKJbO0O+sTPVmUeP5MhNJhvSWCxGmKsMC5O0b75c171yoIEFYVVtRlCh57rTZzuevM0+E6owdFjoga5si1vYM6KHPV5UqtTZkqe2JZKtS9kUzzuOSeW9aNGl++zoM8WW4T8zsyczE5mDgk2Z2qbs/Gngx8AvAn5jZn0SbP8rdrwVOZVd3/U9T0PAaJiRG7Nge/MBCen0xhNcZN9VYrowQ1ZGhvOOUEaV43/l95uUI8hsqQvF3GNKAHoqlKaRNU9neckXCFBpdgnrDA2Q19q4jSEXkdcWfl6IiIWp6ANWmjldnxPs+pCuk0X/VtkdjarO02xhwWzelRovSyoTtm/KrvVasXZsaJcrLS9uUmqbKgrHh7ucyqy6bX/464HUZ+1wC3LPMeSYjRr5jx26Fc9aDkyVMVSNLMSEN7bL2L6oyS7uW0F4VIaQJZdF2aYIUp6mo/j30ewwVp6I2YWXaNBWJUkzVsZjKjLkUk9eWKU2SQgUJyk9QW1WK0mY+T9LWXFFVB2btImpVhSoS3pYoDU2Q4t9y3L4oJq8KrUiIsrabF6WickeMi8mIUUyeMKQZPuTXGUO+LO08RgNjCxUJUZk3kKqh3aWbrt9DjvJ+7CGCFFPUBgzCvsc6bcKyoktlRQnKyxKUE6aYkIhRiCClVWdkdfVPo4oUZQlRkQiVnVYha4yxJoSrrFy1NY1QyMTXReLd5FATQxKkovsc51Nx3jQvOluvvynoPKvvsP8e+6dFk6CZqrQYVal1y2TEyHfsyLT/FWtnBWnWwxvSuC7eNqbJRnZ5QpT1gyi61qLz5P1ok7IT+gZUphozLQ0h32cTbcJCG38XiRI0J0tQbZDKsoKUFj2C4iq25DYxeY2s56UoT4iamleqzHHKDtRaVq6amj5onrLi3ZUkHbhmZa9ylDqGUVSNtuOm63OlKEuItl6/ex6z+g5r99g+TZIgv7xpitBIl6jGpMQo7aGF9Ico7eHNCoeGtFcqQ9ZxiiJEIT+GrB9pVhpCBKksoVVzIRlHiDwVtWWCPYWpKVHauT6wJxyERRRC2jClRZKKlt245fbMMZHyBmaEPcdSKooSZQlRyOjvdak6zljQsRucPb0MIQOe5j03VTsJlB0EtWh4iarMS/iBa1buvMbkFCBpL0fzUjQvRPMiNE9yfZ4kJc+RxYq1ayU2A2cyYjTP/IOffHBhz1AoZEdUihor13kzCGk/VOdHFO+bJ0hNhnznKTtWyDxFVaNQri1TVmSp6nACdYUpJiTSFFM0CW9MmijVIWugxrS2RGkTeia/oxARanMeqiLaFKvMc1YQrqLnpolOAmUHOG1ryIJ5MYpHvN5nxbI9xi5KRovypKhIiNKI94kFaf6Y82XNPE1IUWjVXxss7XBuvbn9Saj7ZDJitLR9R+oDG5MnSkWSBPmilKSoh1fevmWEKL6eoh/h/LHSBKltOQqhikA10YC+rChBubn3igrRUHEqIlSW6pLVBT9LiIpkqOp8UlX2K5KpJGXFKk+kgs8ZIFzz8lQkS010Eqg6wGnZ6rUyI6LvJkVz11hXirZkSMeaubw2q7zJk5bQ/LroOKJdJiNGSbIe+BDDT5MkCG/MXLb6qUzX0bQfStqyvB/f9k2bOpGjpurX59OU1Xg+65xFslRm3qMyM2qHTidTpZFxqEQdRPOiVNTTLC1CtFsX6sCBTsuQNqZYGk1N6pkmWE1XBUK6bBVNowP1e1RCMwOcVo0chQwCmpSitJGuk/lEiBRlyVDaNlmCBOkv5btv26zsVIl4iWImI0ZL23ew5fqb9nhok2Q9wFnRpLy2SRBe+C/PaMw9T9r5qvyQisK6bcpR0w0OQ6rSmpKlslGl3fZtSJqyKDtlShpNRZWaEKImJ81sYwLOPNkqEqwykak8iqKRO7erOOdgSLu3kOgShEWYypI35lWWFMXRIpj99uelKE0kQqQoa/s8SZqnSJqykPx0z2TEKCbvIU8+xFm9DmbrwqrdYvJ6gkF+4V4mOlSFrCq3rKq1kEbZ81SVviqERvHKyFLVcZdCx1wqM63MHucIlqnqwlQ2slTUqDpLiEJGfG+KkHHF8igjW/MS1VRkKiZknsaysgTVe1VC+DAUkN47LkTQ5889/6yFtCuCbCkKEaKtP9/C6gPWZK7Pk6Q9jiXBGQ2TE6M85n8ITYgSNNt1Mr26LPz4WW8lW6+/qZXoUdnhBPIo+p7zjls0JAOE9zYMaasExYV66AjfkB2hCJ2jL60XXVuNhIsaVOfJUN53VmbIhiLanJl8XrqqRqzqVgGGDmK6c5uKsgTlOwckqSJBaemZf9ZCGlunSVGWEG39+Zbg5WmyFPpSXoey0S1RjcmIke9YynywY+Yf5qZEafftyv0A8o7VVI+J5Lm6qFpro0owi5BqzyzxKTMsQ+gkkVXECepVB6UVKXunVuc0J0plhChv2puydDVJZ56A1R0BP6ZOVArqdwyA4t6UMXnt2spIUx5p58hqvD8vRfPsPlZRvhQVlRtpzO+TF1XKOq8YLpMRoxCKHuYyogRhvd/K0lS4tajHRFrUq6wchTQcL/o+yl5vUQ+QvGrPsqIEYYNVlhmosow4hZDVUDxclrK23sWtty/tUYCGVJclry/re6nbJq2t3pRlBKyNe7pHegInsy6SJageXdq5bQlpKkvIcxZ/F/NzocXRomS7ojwpqiJEWYRGldo8n2iOhRKjeZIPV1FoNC0UGipLhekoIQd58pZ17NDoUZ4cxeQ1JC9TfVZVAPMiebP15YZlgPJDM5Qdx6qNEdML2z+lLMsqvvYlv8Hw3iuW73msitGhLhvnN0megIVMGVSGMhGpEGFqqkNAEx0AssgcyiExXE5SiIDUka3TpKhNIcpjqvKytORs2axxjEbB0vYlbt14a+42e6/bO3NdXUnaeZyGG9gVhWBD0tWEHMWUKYjqtpcKO0d+V9nQ0WlDRQnKj2NVdoTvEIrmnUsdhiDneFWKutDoUOhI711TNOZYkrKTNjchwGly1cQEzKHStPO4NXpThjAvQJDfNi0tSgQ0JkV55UheGSKmw2TEKITkA9+UJMU01bgu6/hl9suKbpWRIyjubZe2T/K4aWnII/S68wQwSV40qagBfciwDHXGsWpy9PR5lmc8isu33Zwdydi6qXRPrrIy1LcIzVM1PVXkt0qVX8iky7ulqwFp2u0cNXpThpCVjrTrSMpQTBkpyhOiohfqvG37FqUyaRfhLJQYJQl9wIskKaZOj4SmG+ZljeeU1+6oTKPsKpQdZTaPUDFtuqdh1tAGeWQViG1JQtYEyLvSk7NvyXMVyVCZUd6HQojAVBn5vs71pqWpTFs2CG/71FSHgDzK9kycl6Hk8qxxikKkqAmpyDpGGWGS3AyPhRWjeUKiSVUb2PXRIyFvsMu06FGeHEF+9Khsg+tkGpsipO1V2Z6GZYdlKGqf1TbL979DTeEq1wsxNCpU9TvIahPWJmUGbU2j7PcfUp1XJRoVWpVXVaCqkJemKhNrJ7vjw55SlJZfdyUhkp1x06sYmdlLgBcD24FPuvsro+WnAy8AdgAvdffzi461tH2JLRvz64/XrAvrJVAmXJr1NtJmj4RQylatZckR7C5IZccoKjPabJkGi2UieGVFabY+PY1F31FZQgr9vGPnjeE0T9EQDEs3XV+q7U1ZEar6HfUxG3mdtnahgtmESNWRua6GP8hLY9Z3UDR3ZJkokURFlKE3MTKzXwNOBu7t7tvM7JBo+T2AZwLHA3cELjCz49x9R91zpolTiCyl/aiKQqVd9kgIGUOjjBxB9cJ/XiZCpKjqd1VGSkOq30Lm2JttFx7pChnXqm6h37Q0lBm/qkkJ6nLSzKbuS5Y8VYmS1a3GS1JHoJqmbJVqyDhoWd3wpyZERS/7oh36jBidCrze3bcBuPu10fKTgbOj5T80s6uAE4EL20hE1oNXJExN1C03RUg7qDJyNFueL0hV6aLrbJ2RakOHZdjt2DlDNAxyhuycyGBMmfZlIQIxtO+hbHrqRAlDv8ey4lIU+RsCZYf2CO20UZSPFAlRU7ULIUhuxkefYnQc8FAzOxPYCrzC3b8GHAFclNhuQ7RsD8zsFOAUgENW7tVo4uKHuewPJP5B9tVbIW9un7zZofOmEoFiQQrJ0KpKUWhvwjzic5UdoTakt2EbE0dWPWfo+ZpoU1Xm2OWP0W7VWdn7UrZaNUmZ77FMW6omRaoudeZLzPpuQ6vgy75chYhKcpuyZYBEaPy0KkZmdgFwWMqqM6JzHwg8CHggcI6ZHQOkDZbhKctw9/XAeoC77b1P6jZ12bJxS6W3hz4FKWTiw7xqpCZG9G5CitLe+m7deGut7zRUkGLKTBKZer6OJ46sI2khshSyT/a23bcTyqJOFHD34zQ3PRC0J1HQbVVa3nVUnQYpVIqarj6bF50169YstPws7Vhiy83b+k5Gq7QqRu5+UtY6MzsV+Ji7O3CxmS0B65hFiI5KbHokcHWb6SyiavQI6hfkVQmdFbpMt/6g85ZoaJ1FUcbWxHdaVpCg/fGr2qaKNFWN/gxJgqrQRBQw9LurWl1dp21ZnV5+TbYdqzO2WV8jSy+yFC0KfValfRz4deALZnYcsBewETgP+KCZvZlZ4+tjgYv7SmSSutEj6DaCFFL4F3XrjymONoSPU9TEYGtNReRCx6nKokj6xiJOVarmqsrPECfULHOfmq46rSKfddv+tdXLL+RamhjoterYRJIaEUKfYvQe4D1mdhmzAeGfF0WPLjezc4ArmHXjP62JHmlNUVWOYvqoYqsTPdp5jAqFYBcFYJPfZ9kZs0MYogRAuAhMSX7yqDNAa5KQ76uJdmdDa8yeRVOj3UN/ESKxePQmRu5+G/DbGevOBM4sc7zZXGl7/nD2brB3QUydqrWYroeWD40exdSNdFQZp6hO24A2onJDHqOqLmUKpPlnoU3p6arwq1uFGtN1u7O2GvPXoc4k2JnHrPAcjL1rfhZp5dqiYmZPB14D/CJwortfMrf+TsyCKq9x97+Mlj0AeC+wBvgU8LIoCJPJ5Ee+jh+qoQpSTJWxkqrQZu+soUQJ2q66LJtpj12kqt7XIb/hF6WtSuP8LJqsTh1L26061WFlCRWioVejSYCCuAx4CvDOjPVvAT49t+wdzHqvX8RMjB6Tss1uTF6MYpIPXdOSVLd6LYs2x0oq27amCelpK1qUR1fCmceQBUGk02S0sO5vZyjt1OpcR1u/gbFGiSRB1XD3KwHM9uy8bmZPAn4A3JJYdjiw1t0vjD6/H3gSEqM9uXXjltHIURpNt1Oq2wC57Dn6pq/G8GJP+izYqtz7qvMl1mEokdgydPF7H6MUSYgAWGdmySqw9dHQO5Uxs32AVwGPBF6RWHUEs57uMZnjIiZZKDFqozotpispapsq3dhDjicWmyEWYk0Jch+yNFT0e88nWQaNVZJ8aQfbNv+8ziE2uvsJWSvzxj90909k7PZa4C3ufvNcNCl4XMQkkxSjNgUojalIUZK6UaSyGeTe6/YeZOEpqjG2e9l0Z4hFk6UxCNHQBmbMKqfGKkxNkTf+YQ6/BDzNzN4IHAAsmdlW4KPMxkKMCRoXcTJitGzFMglRS4wh0xP9MjYRKqLLXo4xYxGnMecHQ5OjNEqXY9e0k44x4e4Pjf82s9cAN7v730afN5vZg4CvAs8F/qboeJMRoy5ZFCESIoupiVAeXbVJG7NwCNEFZvZkZmJzMPBJM7vU3R9dsNup7Oqu/2kKGl6DxCgYyVD7qDptuOi+zOh6/DHRPGOIGol03P1c4NyCbV4z9/kS4J5lziMxykAiJBaNMchPVoHW1+9VojRO4udFgiTSWGgxkvwsNlMvxMYgOvNULajK7tfWb1+iNC4UPRJpLIQYSYDGg6rTyjHm76rPAqmryNMQBhgV+UiOxDyTEaNlK5ZNRoAWPeNc9Osvw5hFUgWSqErTz7yq1sJZ2rGdrZuu6zsZrTIZMZoKkgKxSCRfZvoqlLp+obp14636nQ+U+Weh6WdyKi/vU0diNCCUWYoqjDlqlCSt0GhLllRAjZcun3U9J4uJxEgIMViaiCgNsXBT1KgaU3gBEMNHYjQQlEmKOkwlapTHEAVHCDE9lvWdACFEM0iux8WtG2+dvMw2ib4r0RWKGA0AFWhCLC5dTTkihAhDYiTEhFiEKrUpE3LvmpCnOs9IH/KmZ1p0icSoZ/SGKIQoQ54khOQndSVDg1aKqTMZMVq2Ypl+nEJQv5DS2/k46Sv/U77bDkP9Xn3HdrbdtLHvZLSKGl8LIXZjqBmyaIYx3t8xprkOi3a9Q0NiJIQQI6dsQdpUwdtlAb4osrAo1zlkJEZCiD1Q5jweVIUmRLNIjIQQYgEZo9iMMc1lmPr1jQWJkRAiFWXSw0fRIiGaR2IkhMhEBeC0GeP9HWOaQ5jqdY0RiZEQQoyQvhpQD6EAH0IammRq1zN2JjOOkRCiHZRpT58x3uMxpnkK+I7tbNt8Q9/JaBVFjIQQQgghIiRGQgghhBAREiMhhBBCiIjexMjM7mtmF5nZpWZ2iZmdmFh3upldZWbfM7NH95VGIYQQQgwDM3u6mV1uZktmdsLcunub2YXR+u+Y2epo+QOiz1eZ2dvMzIrO02fE6I3Aa939vsD/jj5jZvcAngkcDzwGeLuZLe8rkUIIIYQYBJcBTwG+lFxoZiuAfwRe6O7HAw8Hbo9WvwM4BTg2+veYopP0KUYOrI3+3h+4Ovr7ZOBsd9/m7j8ErgJOTNlfCCGEEAuCu1/p7t9LWfUo4Nvu/q1ou+vdfYeZHQ6sdfcL3d2B9wNPKjpPn931Xw6cb2Z/yUzQfjlafgRwUWK7DdEyIYQQQoh5jgPczM4HDmYWXHkjM3fYkNguyCdaFSMzuwA4LGXVGcAjgP/p7h81s2cAfw+cBKTV/3nG8U9hFiID2HbfD//rZfVTPUrWARv7TkRPLOq1L+p1g659Ea99Ua8biq/9zl0lBMC3XH/+7Zf+w7oah1htZpckPq939/XxhzxvcPdPZBxzBfArwAOBW4HPmdnXgU0p26b6xPzBWsPdT8paZ2bvB14Wffww8O7o7w3AUYlNj2RXNdv88dcD66PjXeLuJ6RtN3V07Yt37Yt63aBrX8RrX9TrhuFdu7sXttGpefxMb8hhA/BFd98IYGafAu7PrN3RkYntMn0iSZ9tjK4GfjX6+9eB/4z+Pg94ppmtMrO7MGssdXEP6RNCCCHE8DkfuLeZ7R01xP5V4Ap3vwbYbGYPinqjPRfIijrtpM82Rr8HvDW6iK1EVWLufrmZnQNcAWwHTnP3Hf0lUwghhBB9Y2ZPBv6GWTuiT5rZpe7+aHe/0czeDHyNWVXZp9z9k9FupwLvBdYAn47+5dKbGLn7l4EHZKw7Eziz5CHXF28yWXTti8eiXjfo2heRRb1uWOxr3w13Pxc4N2PdPzKrOptffglwzzLnsVkPNiGEEEIIoSlBhBBCCCEiJiFGZvaYaPqQq8zs1X2np03M7EfR8OaXxl0ezewgM/usmf1n9P+BfaezCczsPWZ2rZldlliWea1Tmkom49pfY2Y/je79pWb2uMS6SVy7mR1lZp83syujof1fFi2f/H3PufZFuO+rzexiM/tWdO2vjZZP+r7nXPfk7/mgcfdR/wOWA98HjgH2Ar4F3KPvdLV4vT8C1s0teyPw6ujvVwNv6DudDV3rw5h1ubys6FqBe0T3fhVwl+iZWN73NTR87a8BXpGy7WSuHTgcuH/0937Af0TXN/n7nnPti3DfDdg3+nsl8FXgQVO/7znXPfl7PuR/U4gYnQhc5e4/cPfbgLOZTSuySJwMvC/6+30EDHk+Btz9S8ANc4uzrnVSU8lkXHsWk7l2d7/G3b8R/b0ZuJLZSLWTv+85157FlK7d3f3m6OPK6J8z8fuec91ZTOK6h84UxOgI4CeJz1OfQsSBz5jZ16ORvwEO9dl4DUT/H9Jb6ton61oX5Tl4sZl9O6pqi6sVJnntZnY0cD9mb9ELdd/nrh0W4L6b2XIzuxS4Fvisuy/Efc+4bliAez5UpiBGwVOITISHuPv9gccCp5nZw/pO0EBYhOfgHcBdgfsC1wB/FS2f3LWb2b7AR4GXu3vasP47N01ZNrVrX4j77u473P2+zEYnPtHM8rpYT+baM657Ie75UJmCGAVPITIF3P3q6P9rmY3ncCLwM5vNIkz0/7X9pbB1sq518s+Bu/8sykSXgHexK4Q+qWs3s5XMxOAsd/9YtHgh7nvatS/KfY9x958DXwAew4Lcd9j9uhftng+NKYjR14BjzewuZrYX8Exm04pMDjPbx8z2i/8GHgVcxux6nxdt9jwChjwfMVnXOvmpZOICIuLJzO49TOjazcyYTSh9pbu/ObFq8vc969oX5L4fbGYHRH+vYTah+HeZ+H3Puu5FuOdDps8pQRrB3beb2YuZzZWyHHiPu1/ec7La4lDg3Fn+yQrgg+7+r2b2NeAcM3sB8GPg6T2msTHM7EPAw4F1ZrYB+FPg9aRcq09sKpmMa3+4md2XWej8R8Dvw+Su/SHAc4DvRO0uAP6IxbjvWdf+rAW474cD7zOz5cxe2M9x938xswuZ9n3Puu4PLMA9Hywa+VoIIYQQImIKVWlCCCGEEI0gMRJCCCGEiJAYCSGEEEJESIyEEEIIISIkRkIIIYQQERIjIYQQQogIiZEQDWJmNxdvVfqYTzSzV0d/P8nM7lHhGF8wsxNKbv89M3tiyrqjzeyytP2miJn9UeLvNWZ2qZndZmbr+kyXEKIdJEZCDBx3P8/dXx99fBJQWowq8mx3b3UU+Whgu6GzU4zcfUs0r5WmYRBiokiMhGgBm/EmM7vMzL5jZr8ZLX94FI35iJl918zOiqaCwMweFy37spm9zcz+JVr+O2b2t2b2y8ATgTdFUYu7JiNBZrbOzH4U/b3GzM6OZuf+J2BNIm2PMrMLzewbZvbhaNLSout5gJl9KxqJ+LTE8uXRdX4tOtfvR8uXmdnbzexyM/sXM/uUmT0tWvcjM/vfZvZl4OlZ6YnO+UUz+7qZnW+75sx6qZldEZ3v7Jw072Ozmcm/ZmbfNLOTo+VHm9n/i873jeh7xcwON7MvRd/tZWb2UDN7PRBHic4KuvlCiFEz+ilBhBgoT2E2M/Z9gHXA18zsS9G6+wHHM4s6fAV4iJldArwTeJi7/9BmU4Lshrv/u5mdB/yLu38EIHKqNE4FbnX3e5vZvYFvRNuvA/4YOMndbzGzVwF/APxZwfX8A/ASd/+imb0psfwFwE3u/kAzWwV8xcw+AzwAOBq4F3AIcCXwnsR+W939V6L0fGw+PWb2F8DfACe7+3WRWJ4J/C7wauAu7r7NonmmMjgD+Dd3/91ou4vN7AJmE5E+0t23mtmxwIeAE4DfAs539zOjSNbe7v7/zOzFUZRICLEASIyEaIdfAT4UzWP0MzP7IvBAYBNwsbtvALDZnFhHAzcDP3D3H0b7fwg4pcb5Hwa8DcDdv21m346WP4hZVdxXIqnaC7gw70Bmtj9wgLt/MVr0AeCx0d+PAu4dR4OA/ZlNbPkrwIej2cH/28w+P3fYfypIz92AewKfjZYvB66J9vk2cJaZfRz4eE7SHwU80cxeEX1eDdyJmZD+rc3motoBHBet/xrwHpvNcP9xd78059hCiIkiMRKiHTJDOcC2xN87mP0O87bPYzu7qsRXz61LmwjRgM+6+7NKnMMyjhWve4m7n7/bQrPfKDjmLXnpMbN7AZe7+4NT9v0NZuL3ROBPzOx4d9+ekbanuvv35o79GuBnzKJ5y4CtAO7+JTN7WHT8D5jZm9z9/QXXIYSYGGpjJEQ7fAn4zagNzsHMCvKLc7b/LnCMmR0dff7NjO02A/slPv+IWbUVwNMSy78EPBvAzO4J3DtafhGzqrtfiNbtbWbHkYO7/xy4ycx+JVr07MTq84FToygLZnacme0DfBl4atTW6FDg4RmHz0rP94CDzezB0fKVZna8mS0DjnL3zwOvBA4AstpInQ+8xGxnG677Rcv3B66JolnPYRaNwszuDFzr7u8C/h64f7T97fH1CSGmj8RIiHY4l1mVz7eAfwNe6e7/nbWxu28BXgT8a9Qo+WfATSmbng38YdSY+K7AXzITk39n1pYp5h3AvlEV2iuJpMzdrwN+B/hQtO4i4O4B1/N84O+ixtdbEsvfDVwBfMNmXfjfySwC9lFgAxAv+2ra9WSlx91vYyZ6bzCzbwGXAr/MTGL+0cy+A3wTeEskbmn8ObAS+HaUtj+Plr8deJ6ZXcSsGi2OXj0cuNTMvgk8FXhrtHx9dAw1vhZiATD3rAi5EKJLzGxfd785inD8HfCf7v6WntLyBeAV7n5JjWPE13MHZmL2kDw5HBM26/13grtv7DstQohmUcRIiOHwe1Fj7MuZVfe8s8e03AC811IGeCzBv0TX8/+AP5+CFFk0wCOzSNRSz8kRQrSAIkZCiFFjZs8HXja3+Cvuflra9kIIkYfESAghhBAiQlVpQgghhBAREiMhhBBCiAiJkRBCCCFEhMRICCGEECJCYiSEEEIIEfH/AbQU7tSi7nlOAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 720x432 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "(psi[0] / 1e6).plot.contourf(levels=np.arange(-160, 40, 5))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "This doesn't look nice because it lacks a suitable land mask. The dataset has no mask provided for the vorticity point. But we can build one with xgcm!"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.contour.QuadContourSet at 0x7fec29ce21f0>"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x432 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "maskZ = grid.interp(ds.hFacS, 'X')\n",
    "(psi[0] / 1e6).where(maskZ[0]).plot.contourf(levels=np.arange(-160, 40, 5))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Kinetic Energy\n",
    "\n",
    "Finally, we plot the kinetic energy $1/2 (u^2 + v^2)$ by interpoloting both quantities the cell center point."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.collections.QuadMesh at 0x7fec2911cd90>"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 720x432 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "ke = 0.5*(grid.interp((ds.UVEL*ds.hFacW)**2, 'X') + grid.interp((ds.VVEL*ds.hFacS)**2, 'Y'))\n",
    "ke[0,0].where(ds.maskC[0]).plot()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.8.6"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}