LLC_90_Sciserver_tutorial.ipynb

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  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Working with LLC90 data on SciServer (using OceanSpy)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<font size=\"3\">This notebook is meant to demonstrate the workflow to use the data on the LLC90 grid (ECCOv4r4) on the Johns Hopkins University's [SciServer](https://www.sciserver.org/) Portal. It serves as a precurser to the LLC4320 tutorial by introducing basic Oceanspy and SciServer essentials to the user and explore the ECCOv4r4 dataset as a test case for data analysis. Here, we will simply try and show model-data comparison between some [WOCE](http://woceatlas.ucsd.edu/) sections in the Atlantic and the ECCOv4r4 data. "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "&nbsp;&nbsp;&nbsp;&nbsp;<img src=\"img/oceanspy_logo_blue.png\" style=\"width: 200px;\"/>   &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp; &nbsp; &nbsp;&nbsp; &nbsp; <img src=\"img/sciserver.png\" style=\"width: 150px;\"/> ; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp;&nbsp; &nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;<img src=\"img/poseidon_white.png\" style=\"width: 150px;\"/> &nbsp; &nbsp; &nbsp; &nbsp;&nbsp; &nbsp;<img src=\"img/pangeo_logo.png\" style=\"width: 250px;\"/> &nbsp; &nbsp; &nbsp; &nbsp;&nbsp; &nbsp;<img src=\"img/NSF_logo.png\" style=\"width: 150px;\"/> "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Let's get started !"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "#Importing oceanspy and some other packages\n",
    "\n",
    "import oceanspy as ospy\n",
    "import xarray as xr\n",
    "import matplotlib.pyplot as plt \n",
    "import cmocean\n",
    "import cartopy.crs as ccrs\n",
    "import numpy as np\n",
    "import matplotlib.pylab as pylab"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Setting plotting parameters\n",
    "params = {'figure.figsize':'20,8',\n",
    "          'legend.fontsize': 'x-large',\n",
    "          'axes.labelsize': 'x-large',\n",
    "          'axes.titlesize':'x-large',\n",
    "          'xtick.labelsize':'x-large',\n",
    "          'ytick.labelsize':'x-large',\n",
    "          'text.usetex':True}\n",
    "pylab.rcParams.update(params)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "# This is to suppress warnings \n",
    "import warnings\n",
    "warnings.filterwarnings('ignore')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
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   "outputs": [
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       "                            <strong>Nanny: </strong> tcp://127.0.0.1:35931\n",
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      "text/plain": [
       "<Client: 'tcp://127.0.0.1:43082' processes=4 threads=4, memory=100.00 GiB>"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Creating a dask client\n",
    "from dask.distributed import Client\n",
    "client = Client()\n",
    "client"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Loading the ECCOv4r4 dataset\n",
    "\n",
    "<font size=\"3\">This is where we initiate the oceanspy object and import the ECCOv4r4 data stored on SciServer. The SciServer catalog contains multiple publicly available datasets. A detailed description of the available datasets can be found here. https://oceanspy.readthedocs.io/en/latest/datasets.html. For more information on the ECCO dataset, please refer to ECCO Version 4 Release 4 Synopsis (https://doi.org/10.5281/zenodo.4533349)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Opening ECCO.\n",
      "ECCO v4r4 3D dataset, ocean simulations on LLC90 grid\n",
      "CPU times: user 2.65 s, sys: 759 ms, total: 3.41 s\n",
      "Wall time: 9.03 s\n"
     ]
    }
   ],
   "source": [
    "%%time\n",
    "od = ospy.open_oceandataset.from_catalog('ECCO')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "145.518932476 GB\n"
     ]
    }
   ],
   "source": [
    "# Let's see how big the dataset is !\n",
    "print (str(od.dataset.nbytes * 1.0e-9) + ' GB')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "# some bookkeeping\n",
    "_ds = od._ds.drop({'k', 'k_p1','k_l','k_u'})\n",
    "od._ds = _ds"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# LLC90 as OceanSpy object"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<font size=\"3\">This is what the oceanspy object looks like when we import the LLC_90 data in it's native grid, without any transformations into an interpolated lat-lon grid. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
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       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt;\n",
       "Dimensions:     (time: 312, Zl: 50, face: 13, Y: 90, X: 90, Z: 50, Xp1: 90,\n",
       "                 Yp1: 90, time_midp: 311, Zp1: 51, Zu: 50, nv: 2)\n",
       "Coordinates: (12/38)\n",
       "    CS          (face, Y, X) float32 dask.array&lt;chunksize=(13, 90, 90), meta=np.ndarray&gt;\n",
       "    Depth       (face, Y, X) float32 dask.array&lt;chunksize=(13, 90, 90), meta=np.ndarray&gt;\n",
       "    PHrefC      (Z) float32 dask.array&lt;chunksize=(50,), meta=np.ndarray&gt;\n",
       "    PHrefF      (Zp1) float32 dask.array&lt;chunksize=(51,), meta=np.ndarray&gt;\n",
       "    SN          (face, Y, X) float32 dask.array&lt;chunksize=(13, 90, 90), meta=np.ndarray&gt;\n",
       "    XC          (face, Y, X) float32 dask.array&lt;chunksize=(13, 90, 90), meta=np.ndarray&gt;\n",
       "    ...          ...\n",
       "    rAw         (face, Y, Xp1) float32 dask.array&lt;chunksize=(13, 90, 90), meta=np.ndarray&gt;\n",
       "    rAz         (face, Yp1, Xp1) float32 dask.array&lt;chunksize=(13, 90, 90), meta=np.ndarray&gt;\n",
       "  * time        (time) datetime64[ns] 1992-01-16T12:00:00 ... 2017-12-16\n",
       "    time_bnds   (time, nv) datetime64[ns] dask.array&lt;chunksize=(1, 2), meta=np.ndarray&gt;\n",
       "  * time_midp   (time_midp) datetime64[ns] 1992-01-31T12:00:00 ... 2017-12-01\n",
       "    timestep    (time) int64 dask.array&lt;chunksize=(1,), meta=np.ndarray&gt;\n",
       "Dimensions without coordinates: nv\n",
       "Data variables: (12/30)\n",
       "    ADVr_SLT    (time, Zl, face, Y, X) float32 dask.array&lt;chunksize=(1, 50, 13, 90, 90), meta=np.ndarray&gt;\n",
       "    ADVr_TH     (time, Zl, face, Y, X) float32 dask.array&lt;chunksize=(1, 50, 13, 90, 90), meta=np.ndarray&gt;\n",
       "    ADVx_SLT    (time, Z, face, Y, Xp1) float32 dask.array&lt;chunksize=(1, 50, 13, 90, 90), meta=np.ndarray&gt;\n",
       "    ADVx_TH     (time, Z, face, Y, Xp1) float32 dask.array&lt;chunksize=(1, 50, 13, 90, 90), meta=np.ndarray&gt;\n",
       "    ADVy_SLT    (time, Z, face, Yp1, X) float32 dask.array&lt;chunksize=(1, 50, 13, 90, 90), meta=np.ndarray&gt;\n",
       "    ADVy_TH     (time, Z, face, Yp1, X) float32 dask.array&lt;chunksize=(1, 50, 13, 90, 90), meta=np.ndarray&gt;\n",
       "    ...          ...\n",
       "    UVELMASS    (time, Z, face, Y, Xp1) float32 dask.array&lt;chunksize=(1, 50, 13, 90, 90), meta=np.ndarray&gt;\n",
       "    VVELMASS    (time, Z, face, Yp1, X) float32 dask.array&lt;chunksize=(1, 50, 13, 90, 90), meta=np.ndarray&gt;\n",
       "    WVELMASS    (time, Zl, face, Y, X) float32 dask.array&lt;chunksize=(1, 50, 13, 90, 90), meta=np.ndarray&gt;\n",
       "    oceFWflx    (time, face, Y, X) float32 dask.array&lt;chunksize=(1, 13, 90, 90), meta=np.ndarray&gt;\n",
       "    oceQsw      (time, face, Y, X) float32 dask.array&lt;chunksize=(1, 13, 90, 90), meta=np.ndarray&gt;\n",
       "    oceSPtnd    (time, Z, face, Y, X) float32 dask.array&lt;chunksize=(1, 50, 13, 90, 90), meta=np.ndarray&gt;\n",
       "Attributes: (12/16)\n",
       "    date_created:               Mon Dec 30 11:13:26 2019\n",
       "    geospatial_lat_max:         90.0\n",
       "    geospatial_lat_min:         -90.0\n",
       "    geospatial_lon_max:         180.0\n",
       "    geospatial_lon_min:         -179.9991912841797\n",
       "    geospatial_vertical_max:    -5.0\n",
       "    ...                         ...\n",
       "    title:                      ECCOv4 MITgcm grid information\n",
       "    OceanSpy_parameters:        {&#x27;rSphere&#x27;: 6371.0, &#x27;eq_state&#x27;: &#x27;jmd95&#x27;, &#x27;rho...\n",
       "    OceanSpy_name:              ECCO_v4r4\n",
       "    OceanSpy_description:       ECCO v4r4 3D dataset, ocean simulations on LL...\n",
       "    OceanSpy_grid_coords:       {&#x27;Y&#x27;: {&#x27;Y&#x27;: None, &#x27;Yp1&#x27;: 0.5}, &#x27;X&#x27;: {&#x27;X&#x27;: Non...\n",
       "    OceanSpy_face_connections:  {&#x27;face&#x27;: {0: {&#x27;X&#x27;: ((12, &#x27;Y&#x27;, False), (3, &#x27;X&#x27;...</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-989c8cd1-130d-4e9f-98da-ca76d5b6d11e' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-989c8cd1-130d-4e9f-98da-ca76d5b6d11e' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>time</span>: 312</li><li><span class='xr-has-index'>Zl</span>: 50</li><li><span class='xr-has-index'>face</span>: 13</li><li><span class='xr-has-index'>Y</span>: 90</li><li><span class='xr-has-index'>X</span>: 90</li><li><span class='xr-has-index'>Z</span>: 50</li><li><span class='xr-has-index'>Xp1</span>: 90</li><li><span class='xr-has-index'>Yp1</span>: 90</li><li><span class='xr-has-index'>time_midp</span>: 311</li><li><span class='xr-has-index'>Zp1</span>: 51</li><li><span class='xr-has-index'>Zu</span>: 50</li><li><span>nv</span>: 2</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-91411cde-4a12-409e-9f75-c74057058fea' class='xr-section-summary-in' type='checkbox'  ><label for='section-91411cde-4a12-409e-9f75-c74057058fea' class='xr-section-summary' >Coordinates: <span>(38)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>CS</span></div><div class='xr-var-dims'>(face, Y, X)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(13, 90, 90), meta=np.ndarray&gt;</div><input id='attrs-d3dddba3-0c4d-4911-b4d9-5b56d9ad0f88' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d3dddba3-0c4d-4911-b4d9-5b56d9ad0f88' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4ee24e08-7e6e-48b5-a634-82d97637b1b3' class='xr-var-data-in' type='checkbox'><label for='data-4ee24e08-7e6e-48b5-a634-82d97637b1b3' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>coordinate :</span></dt><dd>YC XC</dd><dt><span>long_name :</span></dt><dd>AngleCS</dd><dt><span>units :</span></dt><dd> </dd></dl></div><div class='xr-var-data'><table>\n",
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       "                    </tr>\n",
       "                </thead>\n",
       "                <tbody>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 411.33 kiB </td>\n",
       "                        <td> 411.33 kiB </td>\n",
       "                    </tr>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> (13, 90, 90) </td>\n",
       "                        <td> (13, 90, 90) </td>\n",
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       "                    <tr>\n",
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       "                        <td> 2 Tasks </td>\n",
       "                        <td> 1 Chunks </td>\n",
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       "                    <th> Type </th>\n",
       "                    <td> float32 </td>\n",
       "                    <td> numpy.ndarray </td>\n",
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       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Depth</span></div><div class='xr-var-dims'>(face, Y, X)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(13, 90, 90), meta=np.ndarray&gt;</div><input id='attrs-5f746170-f180-48f8-b095-fd9f5e2ba13f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-5f746170-f180-48f8-b095-fd9f5e2ba13f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7780a6d6-210d-434f-bd00-0f351450c2a9' class='xr-var-data-in' type='checkbox'><label for='data-7780a6d6-210d-434f-bd00-0f351450c2a9' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>coordinate :</span></dt><dd>XC YC</dd><dt><span>long_name :</span></dt><dd>ocean depth</dd><dt><span>units :</span></dt><dd>m</dd><dt><span>standard_name :</span></dt><dd>ocean_depth</dd></dl></div><div class='xr-var-data'><table>\n",
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       "                    <tr>\n",
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       "                        <td> 411.33 kiB </td>\n",
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       "                        <td> (13, 90, 90) </td>\n",
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       "                        <td> 1 Chunks </td>\n",
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       "                    <tr>\n",
       "                    <th> Type </th>\n",
       "                    <td> float32 </td>\n",
       "                    <td> numpy.ndarray </td>\n",
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       "    <tr>\n",
       "        <td>\n",
       "            <table>\n",
       "                <thead>\n",
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       "                    </tr>\n",
       "                </thead>\n",
       "                <tbody>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 200 B </td>\n",
       "                        <td> 200 B </td>\n",
       "                    </tr>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> (50,) </td>\n",
       "                        <td> (50,) </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Count </th>\n",
       "                        <td> 2 Tasks </td>\n",
       "                        <td> 1 Chunks </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                    <th> Type </th>\n",
       "                    <td> float32 </td>\n",
       "                    <td> numpy.ndarray </td>\n",
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       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>PHrefF</span></div><div class='xr-var-dims'>(Zp1)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(51,), meta=np.ndarray&gt;</div><input id='attrs-78787dd3-7385-4fc2-a647-841fb9a147f4' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-78787dd3-7385-4fc2-a647-841fb9a147f4' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f9b3fd19-d64e-477b-86b3-70593a6d7d9f' class='xr-var-data-in' type='checkbox'><label for='data-f9b3fd19-d64e-477b-86b3-70593a6d7d9f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>Reference Hydrostatic Pressure</dd><dt><span>units :</span></dt><dd>m2 s-2</dd><dt><span>standard_name :</span></dt><dd>cell_reference_pressure</dd></dl></div><div class='xr-var-data'><table>\n",
       "    <tr>\n",
       "        <td>\n",
       "            <table>\n",
       "                <thead>\n",
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       "                <tbody>\n",
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       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 204 B </td>\n",
       "                        <td> 204 B </td>\n",
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       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
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       "                        <td> (51,) </td>\n",
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       "                        <td> 2 Tasks </td>\n",
       "                        <td> 1 Chunks </td>\n",
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       "                    <tr>\n",
       "                    <th> Type </th>\n",
       "                    <td> float32 </td>\n",
       "                    <td> numpy.ndarray </td>\n",
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       "            </table>\n",
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       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>SN</span></div><div class='xr-var-dims'>(face, Y, X)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(13, 90, 90), meta=np.ndarray&gt;</div><input id='attrs-35347909-3d6c-41b5-a6ab-71c44ac41312' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-35347909-3d6c-41b5-a6ab-71c44ac41312' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-33eccbb9-fccb-4742-b8ab-717da3bc5328' class='xr-var-data-in' type='checkbox'><label for='data-33eccbb9-fccb-4742-b8ab-717da3bc5328' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>coordinate :</span></dt><dd>YC XC</dd><dt><span>long_name :</span></dt><dd>AngleSN</dd><dt><span>units :</span></dt><dd> </dd></dl></div><div class='xr-var-data'><table>\n",
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       "        <td>\n",
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       "                        <td> (13, 90, 90) </td>\n",
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       "                    <tr>\n",
       "                        <th> Count </th>\n",
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       "                    <tr>\n",
       "                    <th> Type </th>\n",
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       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>XG</span></div><div class='xr-var-dims'>(face, Yp1, Xp1)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(13, 90, 90), meta=np.ndarray&gt;</div><input id='attrs-9494caff-4472-4564-b4f6-dd3dd0eaf768' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-9494caff-4472-4564-b4f6-dd3dd0eaf768' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e67059c2-ce9c-44d6-8103-d4871417201e' class='xr-var-data-in' type='checkbox'><label for='data-e67059c2-ce9c-44d6-8103-d4871417201e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>coordinate :</span></dt><dd>YG XG</dd><dt><span>long_name :</span></dt><dd>longitude</dd><dt><span>units :</span></dt><dd>degrees_east</dd></dl></div><div class='xr-var-data'><table>\n",
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       "        <td>\n",
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       "                </thead>\n",
       "                <tbody>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 411.33 kiB </td>\n",
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       "                        <td> (13, 90, 90) </td>\n",
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       "                        <th> Count </th>\n",
       "                        <td> 2 Tasks </td>\n",
       "                        <td> 1 Chunks </td>\n",
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       "                    <tr>\n",
       "                    <th> Type </th>\n",
       "                    <td> float32 </td>\n",
       "                    <td> numpy.ndarray </td>\n",
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       "    </tr>\n",
       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>YC</span></div><div class='xr-var-dims'>(face, Y, X)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(13, 90, 90), meta=np.ndarray&gt;</div><input id='attrs-82ed83a6-4caa-457f-8109-10a46a5e81ae' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-82ed83a6-4caa-457f-8109-10a46a5e81ae' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e79ba5d7-9769-47af-bf90-7b001271bd6c' class='xr-var-data-in' type='checkbox'><label for='data-e79ba5d7-9769-47af-bf90-7b001271bd6c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>coordinate :</span></dt><dd>YC XC</dd><dt><span>long_name :</span></dt><dd>latitude</dd><dt><span>units :</span></dt><dd>degrees_north</dd></dl></div><div class='xr-var-data'><table>\n",
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       "        <td>\n",
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       "                </thead>\n",
       "                <tbody>\n",
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       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 411.33 kiB </td>\n",
       "                        <td> 411.33 kiB </td>\n",
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       "                        <td> (13, 90, 90) </td>\n",
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       "                    <tr>\n",
       "                        <th> Count </th>\n",
       "                        <td> 2 Tasks </td>\n",
       "                        <td> 1 Chunks </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                    <th> Type </th>\n",
       "                    <td> float32 </td>\n",
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       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>YG</span></div><div class='xr-var-dims'>(face, Yp1, Xp1)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(13, 90, 90), meta=np.ndarray&gt;</div><input id='attrs-c5d97be5-f338-41dc-8fee-59831da488a5' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-c5d97be5-f338-41dc-8fee-59831da488a5' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-68e5e93c-2065-4d29-a03a-a45dfe7d6fc3' class='xr-var-data-in' type='checkbox'><label for='data-68e5e93c-2065-4d29-a03a-a45dfe7d6fc3' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>latitude</dd><dt><span>units :</span></dt><dd>degrees_north</dd></dl></div><div class='xr-var-data'><table>\n",
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       "                        <td> 411.33 kiB </td>\n",
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       "    </tr>\n",
       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>Z</span></div><div class='xr-var-dims'>(Z)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-5.0 -15.0 ... -5.906e+03</div><input id='attrs-189a73fd-84f9-4731-8b24-af216956da2f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-189a73fd-84f9-4731-8b24-af216956da2f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c7ca2664-c5e8-48a4-897e-72f29624cc22' class='xr-var-data-in' type='checkbox'><label for='data-c7ca2664-c5e8-48a4-897e-72f29624cc22' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>vertical coordinate of cell center</dd><dt><span>positive :</span></dt><dd>down</dd><dt><span>units :</span></dt><dd>m</dd><dt><span>standard_name :</span></dt><dd>depth</dd></dl></div><div class='xr-var-data'><pre>array([-5.000000e+00, -1.500000e+01, -2.500000e+01, -3.500000e+01,\n",
       "       -4.500000e+01, -5.500000e+01, -6.500000e+01, -7.500500e+01,\n",
       "       -8.502500e+01, -9.509500e+01, -1.053100e+02, -1.158700e+02,\n",
       "       -1.271500e+02, -1.397400e+02, -1.544700e+02, -1.724000e+02,\n",
       "       -1.947350e+02, -2.227100e+02, -2.574700e+02, -2.999300e+02,\n",
       "       -3.506800e+02, -4.099300e+02, -4.774700e+02, -5.527100e+02,\n",
       "       -6.347350e+02, -7.224000e+02, -8.144700e+02, -9.097400e+02,\n",
       "       -1.007155e+03, -1.105905e+03, -1.205535e+03, -1.306205e+03,\n",
       "       -1.409150e+03, -1.517095e+03, -1.634175e+03, -1.765135e+03,\n",
       "       -1.914150e+03, -2.084035e+03, -2.276225e+03, -2.491250e+03,\n",
       "       -2.729250e+03, -2.990250e+03, -3.274250e+03, -3.581250e+03,\n",
       "       -3.911250e+03, -4.264250e+03, -4.640250e+03, -5.039250e+03,\n",
       "       -5.461250e+03, -5.906250e+03], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>Zl</span></div><div class='xr-var-dims'>(Zl)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.0 -10.0 ... -5.244e+03 -5.678e+03</div><input id='attrs-6f2de52a-01b7-41fd-aa94-cbfda954db7c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-6f2de52a-01b7-41fd-aa94-cbfda954db7c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-cb81fc68-5afa-4a18-b319-92fbcf938011' class='xr-var-data-in' type='checkbox'><label for='data-cb81fc68-5afa-4a18-b319-92fbcf938011' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>vertical coordinate of upper cell interface</dd><dt><span>positive :</span></dt><dd>down</dd><dt><span>units :</span></dt><dd>m</dd><dt><span>standard_name :</span></dt><dd>depth_at_lower_w_location</dd></dl></div><div class='xr-var-data'><pre>array([    0.  ,   -10.  ,   -20.  ,   -30.  ,   -40.  ,   -50.  ,   -60.  ,\n",
       "         -70.  ,   -80.01,   -90.04,  -100.15,  -110.47,  -121.27,  -133.03,\n",
       "        -146.45,  -162.49,  -182.31,  -207.16,  -238.26,  -276.68,  -323.18,\n",
       "        -378.18,  -441.68,  -513.26,  -592.16,  -677.31,  -767.49,  -861.45,\n",
       "        -958.03, -1056.28, -1155.53, -1255.54, -1356.87, -1461.43, -1572.76,\n",
       "       -1695.59, -1834.68, -1993.62, -2174.45, -2378.  , -2604.5 , -2854.  ,\n",
       "       -3126.5 , -3422.  , -3740.5 , -4082.  , -4446.5 , -4834.  , -5244.5 ,\n",
       "       -5678.  ], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>Zp1</span></div><div class='xr-var-dims'>(Zp1)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.0 -10.0 ... -5.678e+03 -6.134e+03</div><input id='attrs-3644e830-c024-4f3f-b6df-24621485b2c0' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3644e830-c024-4f3f-b6df-24621485b2c0' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-914a0fe9-98f9-41a0-8cf2-a038f2a2f42d' class='xr-var-data-in' type='checkbox'><label for='data-914a0fe9-98f9-41a0-8cf2-a038f2a2f42d' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>vertical coordinate of cell interface</dd><dt><span>positive :</span></dt><dd>down</dd><dt><span>units :</span></dt><dd>m</dd><dt><span>standard_name :</span></dt><dd>depth_at_w_location</dd></dl></div><div class='xr-var-data'><pre>array([    0.  ,   -10.  ,   -20.  ,   -30.  ,   -40.  ,   -50.  ,   -60.  ,\n",
       "         -70.  ,   -80.01,   -90.04,  -100.15,  -110.47,  -121.27,  -133.03,\n",
       "        -146.45,  -162.49,  -182.31,  -207.16,  -238.26,  -276.68,  -323.18,\n",
       "        -378.18,  -441.68,  -513.26,  -592.16,  -677.31,  -767.49,  -861.45,\n",
       "        -958.03, -1056.28, -1155.53, -1255.54, -1356.87, -1461.43, -1572.76,\n",
       "       -1695.59, -1834.68, -1993.62, -2174.45, -2378.  , -2604.5 , -2854.  ,\n",
       "       -3126.5 , -3422.  , -3740.5 , -4082.  , -4446.5 , -4834.  , -5244.5 ,\n",
       "       -5678.  , -6134.5 ], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>Zu</span></div><div class='xr-var-dims'>(Zu)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-10.0 -20.0 ... -6.134e+03</div><input id='attrs-49d97b8f-8537-4404-9b6d-d0f1e55e90d3' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-49d97b8f-8537-4404-9b6d-d0f1e55e90d3' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b6c378b3-239f-4d35-b913-71b1dc6b60db' class='xr-var-data-in' type='checkbox'><label for='data-b6c378b3-239f-4d35-b913-71b1dc6b60db' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>vertical coordinate of lower cell interface</dd><dt><span>positive :</span></dt><dd>down</dd><dt><span>units :</span></dt><dd>m</dd><dt><span>standard_name :</span></dt><dd>depth_at_upper_w_location</dd></dl></div><div class='xr-var-data'><pre>array([  -10.  ,   -20.  ,   -30.  ,   -40.  ,   -50.  ,   -60.  ,   -70.  ,\n",
       "         -80.01,   -90.04,  -100.15,  -110.47,  -121.27,  -133.03,  -146.45,\n",
       "        -162.49,  -182.31,  -207.16,  -238.26,  -276.68,  -323.18,  -378.18,\n",
       "        -441.68,  -513.26,  -592.16,  -677.31,  -767.49,  -861.45,  -958.03,\n",
       "       -1056.28, -1155.53, -1255.54, -1356.87, -1461.43, -1572.76, -1695.59,\n",
       "       -1834.68, -1993.62, -2174.45, -2378.  , -2604.5 , -2854.  , -3126.5 ,\n",
       "       -3422.  , -3740.5 , -4082.  , -4446.5 , -4834.  , -5244.5 , -5678.  ,\n",
       "       -6134.5 ], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>drC</span></div><div class='xr-var-dims'>(Zp1)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(51,), meta=np.ndarray&gt;</div><input id='attrs-edd80d84-d37b-4491-a72a-368617dc0bfe' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-edd80d84-d37b-4491-a72a-368617dc0bfe' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2c4895d1-7728-40de-8eb8-083d6fddbbcf' class='xr-var-data-in' type='checkbox'><label for='data-2c4895d1-7728-40de-8eb8-083d6fddbbcf' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>cell z size</dd><dt><span>units :</span></dt><dd>m</dd><dt><span>standard_name :</span></dt><dd>cell_z_size_at_w_location</dd></dl></div><div class='xr-var-data'><table>\n",
       "    <tr>\n",
       "        <td>\n",
       "            <table>\n",
       "                <thead>\n",
       "                    <tr>\n",
       "                        <td> </td>\n",
       "                        <th> Array </th>\n",
       "                        <th> Chunk </th>\n",
       "                    </tr>\n",
       "                </thead>\n",
       "                <tbody>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 204 B </td>\n",
       "                        <td> 204 B </td>\n",
       "                    </tr>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> (51,) </td>\n",
       "                        <td> (51,) </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Count </th>\n",
       "                        <td> 2 Tasks </td>\n",
       "                        <td> 1 Chunks </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                    <th> Type </th>\n",
       "                    <td> float32 </td>\n",
       "                    <td> numpy.ndarray </td>\n",
       "                    </tr>\n",
       "                </tbody>\n",
       "            </table>\n",
       "        </td>\n",
       "        <td>\n",
       "        <svg width=\"170\" height=\"78\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
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       "        </td>\n",
       "    </tr>\n",
       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>drF</span></div><div class='xr-var-dims'>(Z)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(50,), meta=np.ndarray&gt;</div><input id='attrs-54c4a137-f9e3-42ee-b242-59a6bf7bf87f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-54c4a137-f9e3-42ee-b242-59a6bf7bf87f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5da0d918-1815-4c81-9cd7-105f4c507ab9' class='xr-var-data-in' type='checkbox'><label for='data-5da0d918-1815-4c81-9cd7-105f4c507ab9' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>cell z size</dd><dt><span>units :</span></dt><dd>m</dd><dt><span>standard_name :</span></dt><dd>cell_z_size</dd></dl></div><div class='xr-var-data'><table>\n",
       "    <tr>\n",
       "        <td>\n",
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       "                </thead>\n",
       "                <tbody>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 200 B </td>\n",
       "                        <td> 200 B </td>\n",
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       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
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       "                        <td> (50,) </td>\n",
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       "                        <td> 2 Tasks </td>\n",
       "                        <td> 1 Chunks </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                    <th> Type </th>\n",
       "                    <td> float32 </td>\n",
       "                    <td> numpy.ndarray </td>\n",
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       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>dxC</span></div><div class='xr-var-dims'>(face, Y, Xp1)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(13, 90, 90), meta=np.ndarray&gt;</div><input id='attrs-65bd9ef1-e1ad-4ee4-95cd-30ed4ae83430' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-65bd9ef1-e1ad-4ee4-95cd-30ed4ae83430' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8fd0b6ac-5d59-432c-9fa4-37ad9f170114' class='xr-var-data-in' type='checkbox'><label for='data-8fd0b6ac-5d59-432c-9fa4-37ad9f170114' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>coordinate :</span></dt><dd>YC XG</dd><dt><span>long_name :</span></dt><dd>cell x size</dd><dt><span>units :</span></dt><dd>m</dd><dt><span>standard_name :</span></dt><dd>cell_x_size_at_u_location</dd></dl></div><div class='xr-var-data'><table>\n",
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       "                        <th> Count </th>\n",
       "                        <td> 2 Tasks </td>\n",
       "                        <td> 1 Chunks </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                    <th> Type </th>\n",
       "                    <td> float32 </td>\n",
       "                    <td> numpy.ndarray </td>\n",
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       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>face</span></div><div class='xr-var-dims'>(face)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>0 1 2 3 4 5 6 7 8 9 10 11 12</div><input id='attrs-68ae8e77-c3de-4c0f-b292-8c663a58c82a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-68ae8e77-c3de-4c0f-b292-8c663a58c82a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8b3335ba-3664-4eb3-b6a0-3e87172ad09e' class='xr-var-data-in' type='checkbox'><label for='data-8b3335ba-3664-4eb3-b6a0-3e87172ad09e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>index of llc grid tile</dd></dl></div><div class='xr-var-data'><pre>array([ 0,  1,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11, 12])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>HFacC</span></div><div class='xr-var-dims'>(Z, face, Y, X)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(50, 13, 90, 90), meta=np.ndarray&gt;</div><input id='attrs-04a4b29b-d4b7-4a13-a4ed-2b53ed3439ce' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-04a4b29b-d4b7-4a13-a4ed-2b53ed3439ce' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3d495e00-92c3-48bf-9df7-f290d9e72134' class='xr-var-data-in' type='checkbox'><label for='data-3d495e00-92c3-48bf-9df7-f290d9e72134' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>vertical fraction of open cell</dd><dt><span>standard_name :</span></dt><dd>cell_vertical_fraction</dd><dt><span>units :</span></dt><dd> </dd></dl></div><div class='xr-var-data'><table>\n",
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       "        </td>\n",
       "    </tr>\n",
       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>HFacS</span></div><div class='xr-var-dims'>(Z, face, Yp1, X)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(50, 13, 90, 90), meta=np.ndarray&gt;</div><input id='attrs-0d969e26-bb0b-46a4-92b2-d19820562c15' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-0d969e26-bb0b-46a4-92b2-d19820562c15' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7c110a17-5b3e-44e6-b37b-2fe4bb8c909f' class='xr-var-data-in' type='checkbox'><label for='data-7c110a17-5b3e-44e6-b37b-2fe4bb8c909f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>vertical fraction of open cell</dd><dt><span>standard_name :</span></dt><dd>cell_vertical_fraction_at_v_location</dd><dt><span>units :</span></dt><dd> </dd></dl></div><div class='xr-var-data'><table>\n",
       "    <tr>\n",
       "        <td>\n",
       "            <table>\n",
       "                <thead>\n",
       "                    <tr>\n",
       "                        <td> </td>\n",
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       "                </thead>\n",
       "                <tbody>\n",
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       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 20.08 MiB </td>\n",
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       "                    <tr>\n",
       "                        <th> Shape </th>\n",
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       "                        <td> (50, 13, 90, 90) </td>\n",
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       "                    <tr>\n",
       "                        <th> Count </th>\n",
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       "                        <td> 1 Chunks </td>\n",
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       "                    <tr>\n",
       "                    <th> Type </th>\n",
       "                    <td> float32 </td>\n",
       "                    <td> numpy.ndarray </td>\n",
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       "    </tr>\n",
       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>HFacW</span></div><div class='xr-var-dims'>(Z, face, Y, Xp1)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(50, 13, 90, 90), meta=np.ndarray&gt;</div><input id='attrs-078a31ce-223e-4707-9d45-b2b2b99d8ef8' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-078a31ce-223e-4707-9d45-b2b2b99d8ef8' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-bbad13c6-c0be-4fa2-bf91-ab4c82c94405' class='xr-var-data-in' type='checkbox'><label for='data-bbad13c6-c0be-4fa2-bf91-ab4c82c94405' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>vertical fraction of open cell</dd><dt><span>standard_name :</span></dt><dd>cell_vertical_fraction_at_u_location</dd><dt><span>units :</span></dt><dd> </dd></dl></div><div class='xr-var-data'><table>\n",
       "    <tr>\n",
       "        <td>\n",
       "            <table>\n",
       "                <thead>\n",
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       "                </thead>\n",
       "                <tbody>\n",
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       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 20.08 MiB </td>\n",
       "                        <td> 20.08 MiB </td>\n",
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       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> (50, 13, 90, 90) </td>\n",
       "                        <td> (50, 13, 90, 90) </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Count </th>\n",
       "                        <td> 2 Tasks </td>\n",
       "                        <td> 1 Chunks </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                    <th> Type </th>\n",
       "                    <td> float32 </td>\n",
       "                    <td> numpy.ndarray </td>\n",
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       "    </tr>\n",
       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>X</span></div><div class='xr-var-dims'>(X)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>0 1 2 3 4 5 6 ... 84 85 86 87 88 89</div><input id='attrs-4975efe0-2558-4c23-9b34-f9faa5ca77df' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-4975efe0-2558-4c23-9b34-f9faa5ca77df' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-286ff8ef-a867-4525-aa1b-7663b9810dbb' class='xr-var-data-in' type='checkbox'><label for='data-286ff8ef-a867-4525-aa1b-7663b9810dbb' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>axis :</span></dt><dd>X</dd><dt><span>long_name :</span></dt><dd>x-dimension of the t grid</dd><dt><span>swap_dim :</span></dt><dd>XC</dd></dl></div><div class='xr-var-data'><pre>array([ 0,  1,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11, 12, 13, 14, 15, 16, 17,\n",
       "       18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35,\n",
       "       36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53,\n",
       "       54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71,\n",
       "       72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>Xp1</span></div><div class='xr-var-dims'>(Xp1)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>0 1 2 3 4 5 6 ... 84 85 86 87 88 89</div><input id='attrs-3528b104-648f-45dc-ae4c-6d81546993d8' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3528b104-648f-45dc-ae4c-6d81546993d8' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-78b9cb1b-dec0-430a-a7b1-df088473be6c' class='xr-var-data-in' type='checkbox'><label for='data-78b9cb1b-dec0-430a-a7b1-df088473be6c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>axis :</span></dt><dd>X</dd><dt><span>c_grid_axis_shift :</span></dt><dd>-0.5</dd><dt><span>long_name :</span></dt><dd>x-dimension of the u grid</dd><dt><span>swap_dim :</span></dt><dd>XG</dd></dl></div><div class='xr-var-data'><pre>array([ 0,  1,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11, 12, 13, 14, 15, 16, 17,\n",
       "       18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35,\n",
       "       36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53,\n",
       "       54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71,\n",
       "       72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>Y</span></div><div class='xr-var-dims'>(Y)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>0 1 2 3 4 5 6 ... 84 85 86 87 88 89</div><input id='attrs-f6f8880e-0abe-4ad4-bbb9-3999b389f6ed' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f6f8880e-0abe-4ad4-bbb9-3999b389f6ed' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-11abf9fd-5ac6-4cbb-8c4b-e0ce67541117' class='xr-var-data-in' type='checkbox'><label for='data-11abf9fd-5ac6-4cbb-8c4b-e0ce67541117' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>axis :</span></dt><dd>Y</dd><dt><span>long_name :</span></dt><dd>y-dimension of the t grid</dd><dt><span>swap_dim :</span></dt><dd>YC</dd></dl></div><div class='xr-var-data'><pre>array([ 0,  1,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11, 12, 13, 14, 15, 16, 17,\n",
       "       18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35,\n",
       "       36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53,\n",
       "       54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71,\n",
       "       72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>Yp1</span></div><div class='xr-var-dims'>(Yp1)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>0 1 2 3 4 5 6 ... 84 85 86 87 88 89</div><input id='attrs-6ffdc7aa-39c6-44f6-8684-e8aeb9dcff04' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-6ffdc7aa-39c6-44f6-8684-e8aeb9dcff04' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f482b89f-9a2d-4cff-83bb-60f7c7d333ba' class='xr-var-data-in' type='checkbox'><label for='data-f482b89f-9a2d-4cff-83bb-60f7c7d333ba' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>axis :</span></dt><dd>Y</dd><dt><span>c_grid_axis_shift :</span></dt><dd>-0.5</dd><dt><span>long_name :</span></dt><dd>y-dimension of the v grid</dd><dt><span>swap_dim :</span></dt><dd>YG</dd></dl></div><div class='xr-var-data'><pre>array([ 0,  1,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11, 12, 13, 14, 15, 16, 17,\n",
       "       18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35,\n",
       "       36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53,\n",
       "       54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 71,\n",
       "       72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>maskC</span></div><div class='xr-var-dims'>(Z, face, Y, X)</div><div class='xr-var-dtype'>int8</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(50, 13, 90, 90), meta=np.ndarray&gt;</div><input id='attrs-631da140-f51c-4d41-a26d-0020eb2b9e96' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-631da140-f51c-4d41-a26d-0020eb2b9e96' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d54c4b70-b1ea-4085-a790-e7b7d83793cd' class='xr-var-data-in' type='checkbox'><label for='data-d54c4b70-b1ea-4085-a790-e7b7d83793cd' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>mask denoting wet point at center</dd><dt><span>standard_name :</span></dt><dd>sea_binary_mask_at_t_location</dd></dl></div><div class='xr-var-data'><table>\n",
       "    <tr>\n",
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       "                <tbody>\n",
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       "                    <tr>\n",
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       "                        <td> (50, 13, 90, 90) </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Count </th>\n",
       "                        <td> 2 Tasks </td>\n",
       "                        <td> 1 Chunks </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                    <th> Type </th>\n",
       "                    <td> int8 </td>\n",
       "                    <td> numpy.ndarray </td>\n",
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       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>maskS</span></div><div class='xr-var-dims'>(Z, face, Yp1, X)</div><div class='xr-var-dtype'>int8</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(50, 13, 90, 90), meta=np.ndarray&gt;</div><input id='attrs-3a13af54-e52c-42ce-a94c-88100c110ed0' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3a13af54-e52c-42ce-a94c-88100c110ed0' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5fb395f8-a699-47f3-9720-708acca8b282' class='xr-var-data-in' type='checkbox'><label for='data-5fb395f8-a699-47f3-9720-708acca8b282' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>mask denoting wet point at interface</dd><dt><span>standard_name :</span></dt><dd>cell_vertical_fraction_at_v_location</dd></dl></div><div class='xr-var-data'><table>\n",
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       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>maskW</span></div><div class='xr-var-dims'>(Z, face, Y, Xp1)</div><div class='xr-var-dtype'>int8</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(50, 13, 90, 90), meta=np.ndarray&gt;</div><input id='attrs-e0ffb7ac-03f4-485b-89e8-4b06259dd117' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e0ffb7ac-03f4-485b-89e8-4b06259dd117' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-031356e9-0e47-4a35-bcba-2b2b21d34fb8' class='xr-var-data-in' type='checkbox'><label for='data-031356e9-0e47-4a35-bcba-2b2b21d34fb8' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>mask denoting wet point at interface</dd><dt><span>standard_name :</span></dt><dd>cell_vertical_fraction_at_u_location</dd></dl></div><div class='xr-var-data'><table>\n",
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       "       &#x27;1992-03-16T12:00:00.000000000&#x27;, ..., &#x27;2017-10-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;2017-11-16T00:00:00.000000000&#x27;, &#x27;2017-12-16T00:00:00.000000000&#x27;],\n",
       "      dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>time_bnds</span></div><div class='xr-var-dims'>(time, nv)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 2), meta=np.ndarray&gt;</div><input id='attrs-01e19128-cb84-4253-8b44-750659a5d538' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-01e19128-cb84-4253-8b44-750659a5d538' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0d221270-2443-487e-ba51-72ea31eb2d20' class='xr-var-data-in' type='checkbox'><label for='data-0d221270-2443-487e-ba51-72ea31eb2d20' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>time bounds of averaging period</dd></dl></div><div class='xr-var-data'><table>\n",
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       "                        <td> (1, 2) </td>\n",
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       "                        <td> 626 Tasks </td>\n",
       "                        <td> 312 Chunks </td>\n",
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       "                    <tr>\n",
       "                    <th> Type </th>\n",
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       "       &#x27;1992-03-31T18:00:00.000000000&#x27;, ..., &#x27;2017-10-01T06:00:00.000000000&#x27;,\n",
       "       &#x27;2017-10-31T18:00:00.000000000&#x27;, &#x27;2017-12-01T00:00:00.000000000&#x27;],\n",
       "      dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>timestep</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1,), meta=np.ndarray&gt;</div><input id='attrs-55b62eda-b8b8-4d13-8715-8c30dd50e5b0' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-55b62eda-b8b8-4d13-8715-8c30dd50e5b0' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f84d428a-ca33-47de-bb7e-9585af3c434e' class='xr-var-data-in' type='checkbox'><label for='data-f84d428a-ca33-47de-bb7e-9585af3c434e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>model timestep number</dd></dl></div><div class='xr-var-data'><table>\n",
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       "                    <tr>\n",
       "                    <th> Type </th>\n",
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       "                    <tr>\n",
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       "                        <td> 6.12 GiB </td>\n",
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       "                    <tr>\n",
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       "                    <th> Type </th>\n",
       "                    <td> float32 </td>\n",
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       "                    <tr>\n",
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       "                    <tr>\n",
       "                    <th> Type </th>\n",
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       "                        <td> 124.92 MiB </td>\n",
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       "                <tbody>\n",
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       "                    <tr>\n",
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       "                        <td> 6.12 GiB </td>\n",
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       "                    <tr>\n",
       "                        <th> Count </th>\n",
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       "                        <td> 312 Chunks </td>\n",
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       "                    <tr>\n",
       "                    <th> Type </th>\n",
       "                    <td> float32 </td>\n",
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       "    ADVr_TH     (time, Zl, face, Y, X) float32 dask.array<chunksize=(1, 50, 13, 90, 90), meta=np.ndarray>\n",
       "    ADVx_SLT    (time, Z, face, Y, Xp1) float32 dask.array<chunksize=(1, 50, 13, 90, 90), meta=np.ndarray>\n",
       "    ADVx_TH     (time, Z, face, Y, Xp1) float32 dask.array<chunksize=(1, 50, 13, 90, 90), meta=np.ndarray>\n",
       "    ADVy_SLT    (time, Z, face, Yp1, X) float32 dask.array<chunksize=(1, 50, 13, 90, 90), meta=np.ndarray>\n",
       "    ADVy_TH     (time, Z, face, Yp1, X) float32 dask.array<chunksize=(1, 50, 13, 90, 90), meta=np.ndarray>\n",
       "    ...          ...\n",
       "    UVELMASS    (time, Z, face, Y, Xp1) float32 dask.array<chunksize=(1, 50, 13, 90, 90), meta=np.ndarray>\n",
       "    VVELMASS    (time, Z, face, Yp1, X) float32 dask.array<chunksize=(1, 50, 13, 90, 90), meta=np.ndarray>\n",
       "    WVELMASS    (time, Zl, face, Y, X) float32 dask.array<chunksize=(1, 50, 13, 90, 90), meta=np.ndarray>\n",
       "    oceFWflx    (time, face, Y, X) float32 dask.array<chunksize=(1, 13, 90, 90), meta=np.ndarray>\n",
       "    oceQsw      (time, face, Y, X) float32 dask.array<chunksize=(1, 13, 90, 90), meta=np.ndarray>\n",
       "    oceSPtnd    (time, Z, face, Y, X) float32 dask.array<chunksize=(1, 50, 13, 90, 90), meta=np.ndarray>\n",
       "Attributes: (12/16)\n",
       "    date_created:               Mon Dec 30 11:13:26 2019\n",
       "    geospatial_lat_max:         90.0\n",
       "    geospatial_lat_min:         -90.0\n",
       "    geospatial_lon_max:         180.0\n",
       "    geospatial_lon_min:         -179.9991912841797\n",
       "    geospatial_vertical_max:    -5.0\n",
       "    ...                         ...\n",
       "    title:                      ECCOv4 MITgcm grid information\n",
       "    OceanSpy_parameters:        {'rSphere': 6371.0, 'eq_state': 'jmd95', 'rho...\n",
       "    OceanSpy_name:              ECCO_v4r4\n",
       "    OceanSpy_description:       ECCO v4r4 3D dataset, ocean simulations on LL...\n",
       "    OceanSpy_grid_coords:       {'Y': {'Y': None, 'Yp1': 0.5}, 'X': {'X': Non...\n",
       "    OceanSpy_face_connections:  {'face': {0: {'X': ((12, 'Y', False), (3, 'X'..."
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "od.dataset"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Using the `ospy.cutout` function to transform the data. \n",
    "\n",
    "<font size=\"3\">Since the dataset is in its native LLC grid distributed across 13 tiles/faces, we need to transform the data into a regular lat-lon grid to be able to use it with OceanSpy. For now, the `ospy.cutout` function helps us achieve that. Note that the ECCO data is also available as interpolated monthly fields on regular lat-lon grids, however, we take the example of the LLC_90 to demonstrate this transformation because as we move towards higher resolution datasets, such as the LLC2160 and LLC4320, we will have to transform it from the native grid, since those are not available as interpolated datasets. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "%%time\n",
    "## Parameters\n",
    "\n",
    "\n",
    "varList = ['THETA', 'SALT', 'Depth']\n",
    "YRange = [20,80] # degrees latitude\n",
    "XRange = [-90, 20] # longitude\n",
    "add_Hbdr = False\n",
    "mask_outside = True\n",
    "ZRange = None\n",
    "add_Vbdr = False\n",
    "timeRange = ['1992', '2017']\n",
    "timeFreq= None\n",
    "sampMethod = 'snapshot'\n",
    "dropAxes = False\n",
    "\n",
    "# Transformation parameters\n",
    "centered= 'Atlantic'\n",
    "transformation = 'arctic_crown'\n",
    "\n",
    "## Carrying out the cutout\n",
    "cut_od = ospy.subsample.cutout(od,varList,YRange,XRange,add_Hbdr,mask_outside,\n",
    "                               ZRange,add_Vbdr,timeRange,timeFreq,sampMethod,dropAxes, \n",
    "                               centered=centered, transformation=transformation)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Let's see how big the cutout is\n",
    "print (str(cut_od.dataset.nbytes * 1.0e-9) + ' GB')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# How does is look ?\n",
    "cut_od._ds"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Observational data (WOCE sections)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<font size=\"3\">As a test case, we will simply take the A01 section in the North Atlantic and plot the salinity and potential temperature vertical sections. We will then use this to validate the model data. This section needs expansion with information about the campaigns and how to fetch data.<br>\n",
    "\n",
    "![WOCE Atlantic section](img/woce_stations_final.jpg \"WOCE image\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# opening files from CCHDO https://cchdo.ucsd.edu/\n",
    "ds_a1 = xr.open_dataset('test_data/06MT30_3_ctd.nc')\n",
    "ds_a5 = xr.open_dataset('test_data/29HE06_1_ctd.nc')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Creating the A01 section for ECCO using OceanSpy"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Masking the depth\n",
    "cut_od._ds['Depth_masked'] = cut_od._ds['Depth']\n",
    "depth_masked = cut_od._ds['Depth_masked']\n",
    "depth_masked = depth_masked.where(depth_masked>0)\n",
    "cut_od._ds['Depth_masked'] = depth_masked"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Making a survey using OceanSpy !\n",
    "\n",
    "<font size=\"3\">We simply provide the lat-lon information to the `ospy.subsample.survey_stations` function along with any other relavant information required, such as depth levels and the variables that need to be included in the analysis. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "time_range_A01 = ['1994-11', '1994-12']\n",
    "time_range_A05 = ['1992-07', '1992-08']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "%%time\n",
    "## ecco A01 and A05 information \n",
    "\n",
    "lat_a1 = ds_a1.latitude\n",
    "lon_a1 = ds_a1.longitude\n",
    "depth_a1 = [-ds_a1.btm_depth.min(), -ds_a1.btm_depth.max()]\n",
    "\n",
    "\n",
    "lat_a5 = ds_a5.latitude\n",
    "lon_a5 = ds_a5.longitude\n",
    "depth_a5 = [ds_a5.btm_depth.min(), -ds_a5.btm_depth.max()]\n",
    "\n",
    "# Extract ship survey and fields used by this notebook\n",
    "od_surv_a1 = cut_od.subsample.survey_stations(Xsurv=lon_a1,\n",
    "                                              Ysurv=lat_a1,\n",
    "                                              ZRange=depth_a1,\n",
    "                                              timeRange = time_range_A01,\n",
    "                                              varList=[\"THETA\", 'SALT'])\n",
    "\n",
    "od_surv_a5 = cut_od.subsample.survey_stations(Xsurv=lon_a5,\n",
    "                                              Ysurv=lat_a5,\n",
    "                                              ZRange=depth_a5,\n",
    "                                              timeRange = time_range_A05,\n",
    "                                              varList=[\"THETA\", 'SALT'])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Visualizing the sections\n",
    "\n",
    "<font size=\"3\">We can now visualize the section A01 and compare the observations with the model data !"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Here we can set projections for the visuals\n",
    "cut_od = cut_od.set_projection('Orthographic', central_longitude=-40)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "%%time\n",
    "# Plot map of survey locations\n",
    "\n",
    "fig= plt.figure(frameon=True)\n",
    "ax = cut_od.plot.horizontal_section(varName=\"Depth_masked\", \n",
    "                                    plotType='contourf',\n",
    "                                    levels=np.linspace(0,6000,50),\n",
    "                                    cmap = cmocean.cm.deep,\n",
    "                                    use_coords=True)\n",
    "\n",
    "XC_a1 = od_surv_a1.dataset[\"XC\"].squeeze()\n",
    "YC_a1 = od_surv_a1.dataset[\"YC\"].squeeze()\n",
    "\n",
    "XC_a5 = od_surv_a5.dataset[\"XC\"].squeeze()\n",
    "YC_a5 = od_surv_a5.dataset[\"YC\"].squeeze()\n",
    "\n",
    "ax.set_extent([-85, 15, 20, 80], crs=ccrs.PlateCarree())\n",
    "\n",
    "a1_line = ax.plot(XC_a1, YC_a1, 's', markersize=5, markerfacecolor='r',\n",
    "             markeredgewidth=0.5, markeredgecolor='w', transform=ccrs.PlateCarree())\n",
    "a5_line = ax.plot(XC_a5, YC_a5, 's', markersize=5, markerfacecolor='r',\n",
    "             markeredgewidth=0.5, markeredgecolor='w', transform=ccrs.PlateCarree())\n",
    "\n",
    "plt.figtext(0.44,0.60, 'A01', fontsize=24, color='white')\n",
    "plt.figtext(0.44,0.29, 'A05', fontsize=24, color='white')\n",
    "\n",
    "ax.patch.set_facecolor('black')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Visualizing the vertical sections"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<font size=\"3\">A01 section in ECCO and observations "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "od_surv_a1._ds = od_surv_a1._ds.where(od_surv_a1._ds.SALT>34)\n",
    "od_surv_a5._ds = od_surv_a5._ds.where(od_surv_a5._ds.SALT>34)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Salinity"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "%%time\n",
    "import numpy as np\n",
    "from cartopy.crs import PlateCarree\n",
    "import matplotlib.pyplot as plt\n",
    "from matplotlib.colors import LinearSegmentedColormap\n",
    "\n",
    "# To toggle between the A1 and A5 sections, simply uncomment the commented lines and make sure you comment out the lines for the current case.\n",
    "\n",
    "# Create subplots\n",
    "fig = plt.figure()\n",
    "ax1 = plt.subplot2grid((2,1), (0,0), rowspan=1, colspan=1)\n",
    "ax2 = plt.subplot2grid((2,1), (1,0), rowspan=1, colspan=1)\n",
    "\n",
    "levels_salt_a5 = np.linspace(34,ds_a5.ctd_salinity.max(),50)\n",
    "levels_salt_a1 = np.linspace(34,ds_a1.ctd_salinity.max(),50)\n",
    "\n",
    "c0=ax1.contourf(ds_a5.ctd_salinity.transpose(), levels_salt_a5, cmap=cmocean.cm.haline, extend='both' )\n",
    "#c0=ax1.contourf(ds_a1.ctd_salinity.transpose(), levels_salt_a1, cmap=cmocean.cm.haline, extend='both' )\n",
    "\n",
    "ax1.invert_yaxis()\n",
    "\n",
    "ax1.set_xticks([])\n",
    "ax1.set_yticklabels(['0','-1000','-2000', '-3000', '-4000', '-5000', '-6000'])\n",
    "#ax1.set_yticklabels(['0','-1000','-2000', '-3000', '-4000'])\n",
    "ax1.set_facecolor('black')\n",
    "#ax1.set_title('A01 in observations (winter 1994)')\n",
    "ax1.set_title('A05 in observations (winter 1992)')\n",
    "\n",
    "\n",
    "ax2 = od_surv_a5.plot.vertical_section(\n",
    "    varName=\"SALT\",\n",
    "    robust=True,\n",
    "    subsamp_kwargs={'time':time_range_A05[0]},\n",
    "    levels=levels_salt_a5,\n",
    "    meanAxes='time',\n",
    "    cmap=cmocean.cm.haline,\n",
    "    add_colorbar=False,\n",
    "    ax=ax2)\n",
    "    \n",
    "ax2.patch.set_facecolor('black')\n",
    "#ax2.set_title('A01 in ECCOv4r4 (winter 1994)')\n",
    "ax2.set_title('A05 in ECCOv4r4 (winter 1992)')\n",
    "\n",
    "plt.figtext(0.84,0.83, '$psu$', fontsize=24)\n",
    "\n",
    "fig.subplots_adjust(right=0.8)\n",
    "cbar_ax = fig.add_axes([0.82, 0.15, 0.01, 0.7])\n",
    "fig.colorbar(c0, cax=cbar_ax)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Temperature"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "%%time\n",
    "# To toggle between the A1 and A5 sections, simply uncomment the commented lines and make sure you comment out the lines for the current case.\n",
    "\n",
    "fig = plt.figure()\n",
    "ax1 = plt.subplot2grid((2,1), (0,0), rowspan=1, colspan=1)\n",
    "ax2 = plt.subplot2grid((2,1), (1,0), rowspan=1, colspan=1)\n",
    "\n",
    "levels_temp_a5 = np.linspace(0,ds_a5.ctd_temperature.max(),50)\n",
    "#levels_temp_a1 = np.linspace(0,ds_a5.ctd_temperature.max(),50)\n",
    "\n",
    "c0=ax1.contourf(ds_a5.ctd_temperature.transpose(), levels_temp_a5, cmap=cmocean.cm.thermal, extend='both' )\n",
    "#c0=ax1.contourf(ds_a1.ctd_temperature_unk.transpose(), levels_temp_a1, cmap=cmocean.cm.thermal, extend='both' )\n",
    "\n",
    "ax1.invert_yaxis()\n",
    "\n",
    "ax1.set_xticks([])\n",
    "ax1.set_yticklabels(['0','-1000','-2000', '-3000', '-4000', '-5000', '-6000'])\n",
    "#ax1.set_yticklabels(['0','-1000','-2000', '-3000', '-4000'])\n",
    "ax1.set_facecolor('black')\n",
    "#ax1.set_title('A01 in observations (winter 1994)')\n",
    "ax1.set_title('A05 in observations (winter 1992)')\n",
    "\n",
    "\n",
    "# Change the dataset when toggling between A1 and A5\n",
    "ax2 = od_surv_a5.plot.vertical_section(\n",
    "    varName=\"THETA\",\n",
    "    robust=True,\n",
    "    subsamp_kwargs={'time':time_range_A05[0]},\n",
    "    levels=levels_temp_a5,\n",
    "    meanAxes='time',\n",
    "    cmap=cmocean.cm.thermal,\n",
    "    add_colorbar=False,\n",
    "    ax=ax2)\n",
    "    \n",
    "ax2.patch.set_facecolor('black')\n",
    "#ax2.set_title('A01 in ECCOv4r4 (winter 1994)')\n",
    "ax2.set_title('A05 in ECCOv4r4 (winter 1994)')\n",
    "\n",
    "\n",
    "plt.figtext(0.84,0.83, '$^{\\circ}C$', fontsize=18)\n",
    "\n",
    "fig.subplots_adjust(right=0.8)\n",
    "cbar_ax = fig.add_axes([0.82, 0.15, 0.01, 0.7])\n",
    "fig.colorbar(c0, cax=cbar_ax)"
   ]
  }
 ],
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