docs/examples/two-layer.ipynb

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    "# Two-Layer QG Model Example"
   ]
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    "Here is a quick overview of how to use the two-layer model. See the\n",
    ":py:class:`pyqg.QGModel` api documentation for further details.\n",
    "\n",
    "First import numpy, matplotlib, and pyqg:"
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   "source": [
    "import numpy as np\n",
    "from matplotlib import pyplot as plt\n",
    "%matplotlib inline\n",
    "\n",
    "import pyqg\n",
    "from pyqg import diagnostic_tools as tools"
   ]
  },
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   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Initialize and Run the Model ##\n",
    "\n",
    "Here we set up a model which will run for 10 years and start averaging\n",
    "after 5 years. There are lots of parameters that can be specified as\n",
    "keyword arguments but we are just using the defaults."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
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     "text": [
      "INFO:  Logger initialized\n",
      "INFO: Step: 10000, Time: 7.20e+07, KE: 4.14e-04, CFL: 0.090\n",
      "INFO: Step: 20000, Time: 1.44e+08, KE: 4.58e-04, CFL: 0.084\n",
      "INFO: Step: 30000, Time: 2.16e+08, KE: 4.35e-04, CFL: 0.109\n",
      "INFO: Step: 40000, Time: 2.88e+08, KE: 4.85e-04, CFL: 0.080\n"
     ]
    }
   ],
   "source": [
    "year = 24*60*60*360.\n",
    "m = pyqg.QGModel(tmax=10*year, twrite=10000, tavestart=5*year)\n",
    "m.run()"
   ]
  },
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   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Convert Model Outpt to an xarray Dataset ##\n",
    "\n",
    "Model variables, coordinates, attributes, and metadata can be stored conveniently as an xarray Dataset. (Notice that this feature requires xarray to be installed on your machine. See here for installation instructions: http://xarray.pydata.org/en/stable/getting-started-guide/installing.html#instructions)"
   ]
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  {
   "cell_type": "code",
   "execution_count": 3,
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       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt;\n",
       "Dimensions:            (lev: 2, y: 64, x: 64, l: 64, k: 33, lev_mid: 1)\n",
       "Coordinates:\n",
       "    time               float64 3.11e+08\n",
       "  * lev                (lev) int64 1 2\n",
       "  * lev_mid            (lev_mid) float64 1.5\n",
       "  * x                  (x) float64 7.812e+03 2.344e+04 ... 9.766e+05 9.922e+05\n",
       "  * y                  (y) float64 7.812e+03 2.344e+04 ... 9.766e+05 9.922e+05\n",
       "  * l                  (l) float64 0.0 6.283e-06 ... -1.257e-05 -6.283e-06\n",
       "  * k                  (k) float64 0.0 6.283e-06 ... 0.0001948 0.0002011\n",
       "Data variables: (12/32)\n",
       "    q                  (lev, y, x) float64 -1.822e-06 -1.356e-06 ... -1.087e-06\n",
       "    u                  (lev, y, x) float64 -0.05977 -0.04566 ... -0.001317\n",
       "    v                  (lev, y, x) float64 0.04194 0.0462 ... 0.00118 0.009001\n",
       "    ufull              (lev, y, x) float64 -0.03477 -0.02066 ... -0.001317\n",
       "    vfull              (lev, y, x) float64 0.04194 0.0462 ... 0.00118 0.009001\n",
       "    qh                 (lev, l, k) complex128 (0.002324483338567505+0j) ... (...\n",
       "    ...                 ...\n",
       "    ENSgenspec         (l, k) float64 0.0 -3.458e-24 ... 7.51e-52 -3.186e-61\n",
       "    ENSfrictionspec    (l, k) float64 0.0 -7.479e-24 ... -2.395e-50 -7.94e-60\n",
       "    APEgenspec         (l, k) float64 0.0 -7.781e-16 ... 1.69e-43 -7.168e-53\n",
       "    APEflux            (l, k) float64 -0.0 -7.048e-16 ... 1.097e-28 2.951e-33\n",
       "    KEflux             (l, k) float64 0.0 -4.226e-15 ... 5.188e-27 9.932e-32\n",
       "    APEgen             float64 6.336e-11\n",
       "Attributes: (12/23)\n",
       "    pyqg:beta:       1.5e-11\n",
       "    pyqg:delta:      0.25\n",
       "    pyqg:del2:       0.8\n",
       "    pyqg:dt:         7200.0\n",
       "    pyqg:filterfac:  23.6\n",
       "    pyqg:L:          1000000.0\n",
       "    ...              ...\n",
       "    pyqg:tc:         43200\n",
       "    pyqg:tmax:       311040000.0\n",
       "    pyqg:twrite:     10000\n",
       "    pyqg:W:          1000000.0\n",
       "    title:           pyqg: Python Quasigeostrophic Model\n",
       "    reference:       https://pyqg.readthedocs.io/en/latest/index.html</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-946a919c-fce8-4f1f-ade6-51e7c4bd851c' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-946a919c-fce8-4f1f-ade6-51e7c4bd851c' 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'>lev</span>: 2</li><li><span class='xr-has-index'>y</span>: 64</li><li><span class='xr-has-index'>x</span>: 64</li><li><span class='xr-has-index'>l</span>: 64</li><li><span class='xr-has-index'>k</span>: 33</li><li><span class='xr-has-index'>lev_mid</span>: 1</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-ae83c69c-972e-4f40-a800-3ddb3f2747bb' class='xr-section-summary-in' type='checkbox'  checked><label for='section-ae83c69c-972e-4f40-a800-3ddb3f2747bb' class='xr-section-summary' >Coordinates: <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>time</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>3.11e+08</div><input id='attrs-3dabc38b-37ea-4789-9bb5-5df7c0764a42' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3dabc38b-37ea-4789-9bb5-5df7c0764a42' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0ab0b888-4f99-48b6-8c6e-2a81f0e8962a' class='xr-var-data-in' type='checkbox'><label for='data-0ab0b888-4f99-48b6-8c6e-2a81f0e8962a' 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 time</dd><dt><span>units :</span></dt><dd>s</dd></dl></div><div class='xr-var-data'><pre>array(3.1104e+08)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lev</span></div><div class='xr-var-dims'>(lev)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>1 2</div><input id='attrs-e17030e4-9217-4e4c-a6ee-b03dcaf513df' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e17030e4-9217-4e4c-a6ee-b03dcaf513df' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-60e3ae73-2b23-47e7-a396-71148a225e12' class='xr-var-data-in' type='checkbox'><label for='data-60e3ae73-2b23-47e7-a396-71148a225e12' 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 levels</dd></dl></div><div class='xr-var-data'><pre>array([1, 2])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lev_mid</span></div><div class='xr-var-dims'>(lev_mid)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>1.5</div><input id='attrs-f10e01d9-a4d9-455a-9568-43215ce80574' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f10e01d9-a4d9-455a-9568-43215ce80574' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-fd65831a-9bcf-4d2c-b7d7-1384c3bd4068' class='xr-var-data-in' type='checkbox'><label for='data-fd65831a-9bcf-4d2c-b7d7-1384c3bd4068' 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 level interface</dd></dl></div><div class='xr-var-data'><pre>array([1.5])</pre></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'>float64</div><div class='xr-var-preview xr-preview'>7.812e+03 2.344e+04 ... 9.922e+05</div><input id='attrs-2ecf2279-b7d5-4d8d-9a85-1085d7888e99' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-2ecf2279-b7d5-4d8d-9a85-1085d7888e99' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-75c764a1-55cd-4afc-b9d5-a5ef50749edc' class='xr-var-data-in' type='checkbox'><label for='data-75c764a1-55cd-4afc-b9d5-a5ef50749edc' 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>real space grid points in the x direction</dd><dt><span>units :</span></dt><dd>grid point</dd></dl></div><div class='xr-var-data'><pre>array([  7812.5,  23437.5,  39062.5,  54687.5,  70312.5,  85937.5, 101562.5,\n",
       "       117187.5, 132812.5, 148437.5, 164062.5, 179687.5, 195312.5, 210937.5,\n",
       "       226562.5, 242187.5, 257812.5, 273437.5, 289062.5, 304687.5, 320312.5,\n",
       "       335937.5, 351562.5, 367187.5, 382812.5, 398437.5, 414062.5, 429687.5,\n",
       "       445312.5, 460937.5, 476562.5, 492187.5, 507812.5, 523437.5, 539062.5,\n",
       "       554687.5, 570312.5, 585937.5, 601562.5, 617187.5, 632812.5, 648437.5,\n",
       "       664062.5, 679687.5, 695312.5, 710937.5, 726562.5, 742187.5, 757812.5,\n",
       "       773437.5, 789062.5, 804687.5, 820312.5, 835937.5, 851562.5, 867187.5,\n",
       "       882812.5, 898437.5, 914062.5, 929687.5, 945312.5, 960937.5, 976562.5,\n",
       "       992187.5])</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'>float64</div><div class='xr-var-preview xr-preview'>7.812e+03 2.344e+04 ... 9.922e+05</div><input id='attrs-8abcde99-11c0-4d47-b785-8e95b07c9232' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-8abcde99-11c0-4d47-b785-8e95b07c9232' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-85bd24b7-6519-4958-8c68-0a6e13adcc5d' class='xr-var-data-in' type='checkbox'><label for='data-85bd24b7-6519-4958-8c68-0a6e13adcc5d' 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>real space grid points in the y direction</dd><dt><span>units :</span></dt><dd>grid point</dd></dl></div><div class='xr-var-data'><pre>array([  7812.5,  23437.5,  39062.5,  54687.5,  70312.5,  85937.5, 101562.5,\n",
       "       117187.5, 132812.5, 148437.5, 164062.5, 179687.5, 195312.5, 210937.5,\n",
       "       226562.5, 242187.5, 257812.5, 273437.5, 289062.5, 304687.5, 320312.5,\n",
       "       335937.5, 351562.5, 367187.5, 382812.5, 398437.5, 414062.5, 429687.5,\n",
       "       445312.5, 460937.5, 476562.5, 492187.5, 507812.5, 523437.5, 539062.5,\n",
       "       554687.5, 570312.5, 585937.5, 601562.5, 617187.5, 632812.5, 648437.5,\n",
       "       664062.5, 679687.5, 695312.5, 710937.5, 726562.5, 742187.5, 757812.5,\n",
       "       773437.5, 789062.5, 804687.5, 820312.5, 835937.5, 851562.5, 867187.5,\n",
       "       882812.5, 898437.5, 914062.5, 929687.5, 945312.5, 960937.5, 976562.5,\n",
       "       992187.5])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>l</span></div><div class='xr-var-dims'>(l)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0 6.283e-06 ... -6.283e-06</div><input id='attrs-38eff27c-25f3-4bbf-b38e-f903b3e4efa9' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-38eff27c-25f3-4bbf-b38e-f903b3e4efa9' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d637b4a7-6059-4a6f-a800-6e5ab1a4ec48' class='xr-var-data-in' type='checkbox'><label for='data-d637b4a7-6059-4a6f-a800-6e5ab1a4ec48' 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>spectal space grid points in the l direction</dd><dt><span>units :</span></dt><dd>meridional wavenumber</dd></dl></div><div class='xr-var-data'><pre>array([ 0.000000e+00,  6.283185e-06,  1.256637e-05,  1.884956e-05,\n",
       "        2.513274e-05,  3.141593e-05,  3.769911e-05,  4.398230e-05,\n",
       "        5.026548e-05,  5.654867e-05,  6.283185e-05,  6.911504e-05,\n",
       "        7.539822e-05,  8.168141e-05,  8.796459e-05,  9.424778e-05,\n",
       "        1.005310e-04,  1.068142e-04,  1.130973e-04,  1.193805e-04,\n",
       "        1.256637e-04,  1.319469e-04,  1.382301e-04,  1.445133e-04,\n",
       "        1.507964e-04,  1.570796e-04,  1.633628e-04,  1.696460e-04,\n",
       "        1.759292e-04,  1.822124e-04,  1.884956e-04,  1.947787e-04,\n",
       "       -2.010619e-04, -1.947787e-04, -1.884956e-04, -1.822124e-04,\n",
       "       -1.759292e-04, -1.696460e-04, -1.633628e-04, -1.570796e-04,\n",
       "       -1.507964e-04, -1.445133e-04, -1.382301e-04, -1.319469e-04,\n",
       "       -1.256637e-04, -1.193805e-04, -1.130973e-04, -1.068142e-04,\n",
       "       -1.005310e-04, -9.424778e-05, -8.796459e-05, -8.168141e-05,\n",
       "       -7.539822e-05, -6.911504e-05, -6.283185e-05, -5.654867e-05,\n",
       "       -5.026548e-05, -4.398230e-05, -3.769911e-05, -3.141593e-05,\n",
       "       -2.513274e-05, -1.884956e-05, -1.256637e-05, -6.283185e-06])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>k</span></div><div class='xr-var-dims'>(k)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0 6.283e-06 ... 0.0002011</div><input id='attrs-80278309-6ea4-430f-b7b5-90c434f86dac' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-80278309-6ea4-430f-b7b5-90c434f86dac' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b31e7460-61e6-44f6-b9fd-8d23fe8949f4' class='xr-var-data-in' type='checkbox'><label for='data-b31e7460-61e6-44f6-b9fd-8d23fe8949f4' 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>spectal space grid points in the k direction</dd><dt><span>units :</span></dt><dd>zonal wavenumber</dd></dl></div><div class='xr-var-data'><pre>array([0.000000e+00, 6.283185e-06, 1.256637e-05, 1.884956e-05, 2.513274e-05,\n",
       "       3.141593e-05, 3.769911e-05, 4.398230e-05, 5.026548e-05, 5.654867e-05,\n",
       "       6.283185e-05, 6.911504e-05, 7.539822e-05, 8.168141e-05, 8.796459e-05,\n",
       "       9.424778e-05, 1.005310e-04, 1.068142e-04, 1.130973e-04, 1.193805e-04,\n",
       "       1.256637e-04, 1.319469e-04, 1.382301e-04, 1.445133e-04, 1.507964e-04,\n",
       "       1.570796e-04, 1.633628e-04, 1.696460e-04, 1.759292e-04, 1.822124e-04,\n",
       "       1.884956e-04, 1.947787e-04, 2.010619e-04])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-af4a5c06-d38f-4387-9603-42523918da5d' class='xr-section-summary-in' type='checkbox'  ><label for='section-af4a5c06-d38f-4387-9603-42523918da5d' class='xr-section-summary' >Data variables: <span>(32)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>q</span></div><div class='xr-var-dims'>(lev, y, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-1.822e-06 ... -1.087e-06</div><input id='attrs-c498b994-4dcf-4b26-a6dc-160364720767' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-c498b994-4dcf-4b26-a6dc-160364720767' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7b10ad17-db21-49e9-82e5-88ac1f986ae9' class='xr-var-data-in' type='checkbox'><label for='data-7b10ad17-db21-49e9-82e5-88ac1f986ae9' 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>units :</span></dt><dd>s^-1</dd><dt><span>long_name :</span></dt><dd>potential vorticity in real space</dd></dl></div><div class='xr-var-data'><pre>array([[[-1.82155607e-06, -1.35614850e-06, -2.73898371e-06, ...,\n",
       "         -6.85958828e-06, -3.88652325e-06, -7.07170613e-07],\n",
       "        [-2.24241759e-06, -6.30783618e-06, -9.64180522e-06, ...,\n",
       "          8.28700407e-07, -3.62581851e-06, -2.18831772e-06],\n",
       "        [-3.21053920e-06, -1.23838527e-05, -1.70457033e-05, ...,\n",
       "          5.90566987e-06, -4.37522563e-06, -3.90119075e-06],\n",
       "        ...,\n",
       "        [ 1.74383701e-05,  4.74421973e-06, -3.97541428e-06, ...,\n",
       "          1.39955471e-05,  2.88647068e-05,  2.92223526e-05],\n",
       "        [ 1.63871061e-05,  4.98120523e-06, -3.30331793e-06, ...,\n",
       "          7.80011160e-06,  2.43203864e-05,  2.74599319e-05],\n",
       "        [ 4.29350266e-06, -1.76233514e-07, -4.52788793e-06, ...,\n",
       "         -4.09975671e-06,  6.90339664e-06,  1.07226221e-05]],\n",
       "\n",
       "       [[-3.33208786e-08,  3.96628369e-07,  7.16963768e-07, ...,\n",
       "          5.78802928e-07,  3.48351068e-07, -1.59284286e-07],\n",
       "        [ 8.82458643e-07,  1.40627384e-06,  1.61550730e-06, ...,\n",
       "          6.19656450e-07,  8.79536706e-07,  6.72872557e-07],\n",
       "        [ 1.72684105e-06,  2.07050296e-06,  1.79271303e-06, ...,\n",
       "          3.44060815e-07,  1.19072781e-06,  1.45201173e-06],\n",
       "        ...,\n",
       "        [-1.96770868e-06, -6.02974769e-07, -1.93654523e-07, ...,\n",
       "         -1.71781896e-06, -2.97724536e-06, -3.21060907e-06],\n",
       "        [-1.53072205e-06, -4.76886961e-07, -1.02493765e-07, ...,\n",
       "         -9.52231342e-07, -1.92618338e-06, -2.37473090e-06],\n",
       "        [-6.82081661e-07, -1.07404161e-07,  1.63025070e-07, ...,\n",
       "         -1.65139673e-07, -6.49227654e-07, -1.08681543e-06]]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>u</span></div><div class='xr-var-dims'>(lev, y, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-0.05977 -0.04566 ... -0.001317</div><input id='attrs-845cb9d5-c4c3-4ef2-a6ab-92966223720e' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-845cb9d5-c4c3-4ef2-a6ab-92966223720e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-85187866-23bc-474f-a351-10b4187f9d44' class='xr-var-data-in' type='checkbox'><label for='data-85187866-23bc-474f-a351-10b4187f9d44' 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>units :</span></dt><dd>m s^-1</dd><dt><span>long_name :</span></dt><dd>zonal velocity anomaly</dd></dl></div><div class='xr-var-data'><pre>array([[[-0.05977365, -0.04566044, -0.0300013 , ...,  0.00313956,\n",
       "         -0.05354602, -0.07361268],\n",
       "        [-0.03410872, -0.04832014, -0.0436795 , ...,  0.03619708,\n",
       "         -0.00852563, -0.0302402 ],\n",
       "        [-0.01284595, -0.0007373 ,  0.01982649, ...,  0.00808109,\n",
       "         -0.01780913, -0.02519738],\n",
       "        ...,\n",
       "        [ 0.03291048,  0.01935363,  0.00108856, ..., -0.01936507,\n",
       "          0.01178554,  0.03422701],\n",
       "        [-0.06464542, -0.03662093, -0.02514983, ..., -0.07523594,\n",
       "         -0.09564462, -0.08762571],\n",
       "        [-0.09744367, -0.05272586, -0.02502093, ..., -0.06773183,\n",
       "         -0.12211898, -0.13019829]],\n",
       "\n",
       "       [[ 0.00018518,  0.00178978,  0.00374121, ...,  0.00738511,\n",
       "          0.0028788 ,  0.00019862],\n",
       "        [ 0.0026525 ,  0.00251875,  0.00221745, ...,  0.00521121,\n",
       "          0.00308351,  0.00242911],\n",
       "        [-0.00196729, -0.00190097, -0.00146095, ...,  0.00088748,\n",
       "         -0.00132439, -0.00201614],\n",
       "        ...,\n",
       "        [ 0.00593403,  0.00365724,  0.0017545 , ...,  0.01161436,\n",
       "          0.0113088 ,  0.00879691],\n",
       "        [ 0.00172549,  0.00071104,  0.00080111, ...,  0.00678718,\n",
       "          0.00541306,  0.00367907],\n",
       "        [-0.00198774, -0.00057552,  0.00172088, ...,  0.00614775,\n",
       "          0.00158964, -0.00131667]]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>v</span></div><div class='xr-var-dims'>(lev, y, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.04194 0.0462 ... 0.00118 0.009001</div><input id='attrs-f53a9e15-592f-48fa-bfe9-4e91fc0c39bc' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f53a9e15-592f-48fa-bfe9-4e91fc0c39bc' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-df8ac727-82b9-4ff7-b086-fa9d5eb67554' class='xr-var-data-in' type='checkbox'><label for='data-df8ac727-82b9-4ff7-b086-fa9d5eb67554' 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>units :</span></dt><dd>m s^-1</dd><dt><span>long_name :</span></dt><dd>meridional velocity anomaly</dd></dl></div><div class='xr-var-data'><pre>array([[[ 0.04193728,  0.04619567,  0.04606487, ...,  0.00914963,\n",
       "         -0.01375966,  0.01612357],\n",
       "        [ 0.04114261,  0.04963187,  0.02388613, ...,  0.05653599,\n",
       "          0.029679  ,  0.01889034],\n",
       "        [ 0.04238221,  0.05254364, -0.00317824, ...,  0.08718173,\n",
       "          0.06116157,  0.0193422 ],\n",
       "        ...,\n",
       "        [ 0.12361364,  0.11601851,  0.05419519, ..., -0.11855288,\n",
       "         -0.06021382,  0.05868665],\n",
       "        [ 0.11444405,  0.11155098,  0.06699201, ..., -0.11226167,\n",
       "         -0.07512554,  0.04453635],\n",
       "        [ 0.07533527,  0.07553595,  0.06256184, ..., -0.05571866,\n",
       "         -0.05462336,  0.02682797]],\n",
       "\n",
       "       [[ 0.01243645,  0.01307927,  0.01055738, ..., -0.00193764,\n",
       "          0.00550631,  0.01063706],\n",
       "        [ 0.011838  ,  0.01226643,  0.0098713 , ...,  0.00129449,\n",
       "          0.00826311,  0.01119273],\n",
       "        [ 0.01187803,  0.01273346,  0.00989068, ...,  0.00367322,\n",
       "          0.00943853,  0.01105163],\n",
       "        ...,\n",
       "        [ 0.01046388,  0.01504644,  0.01335022, ..., -0.01056941,\n",
       "         -0.0026157 ,  0.00459572],\n",
       "        [ 0.01279311,  0.01647135,  0.01391478, ..., -0.01038098,\n",
       "         -0.0014363 ,  0.00714923],\n",
       "        [ 0.01334085,  0.01548231,  0.01263995, ..., -0.00688463,\n",
       "          0.00118041,  0.00900085]]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>ufull</span></div><div class='xr-var-dims'>(lev, y, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-0.03477 -0.02066 ... -0.001317</div><input id='attrs-e1e4dcda-94dd-4f6c-a55e-b2d056b0d142' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e1e4dcda-94dd-4f6c-a55e-b2d056b0d142' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-51bfe2fd-86b5-42c2-b1fc-4b3198e28f20' class='xr-var-data-in' type='checkbox'><label for='data-51bfe2fd-86b5-42c2-b1fc-4b3198e28f20' 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>units :</span></dt><dd>m s^-1</dd><dt><span>long_name :</span></dt><dd>zonal full velocities in real space</dd></dl></div><div class='xr-var-data'><pre>array([[[-3.47736519e-02, -2.06604356e-02, -5.00130117e-03, ...,\n",
       "          2.81395648e-02, -2.85460236e-02, -4.86126789e-02],\n",
       "        [-9.10872099e-03, -2.33201399e-02, -1.86794994e-02, ...,\n",
       "          6.11970801e-02,  1.64743670e-02, -5.24020014e-03],\n",
       "        [ 1.21540536e-02,  2.42627049e-02,  4.48264878e-02, ...,\n",
       "          3.30810948e-02,  7.19086952e-03, -1.97384631e-04],\n",
       "        ...,\n",
       "        [ 5.79104757e-02,  4.43536257e-02,  2.60885571e-02, ...,\n",
       "          5.63492850e-03,  3.67855361e-02,  5.92270089e-02],\n",
       "        [-3.96454245e-02, -1.16209314e-02, -1.49831987e-04, ...,\n",
       "         -5.02359400e-02, -7.06446179e-02, -6.26257108e-02],\n",
       "        [-7.24436689e-02, -2.77258637e-02, -2.09251419e-05, ...,\n",
       "         -4.27318328e-02, -9.71189759e-02, -1.05198294e-01]],\n",
       "\n",
       "       [[ 1.85178683e-04,  1.78978348e-03,  3.74121000e-03, ...,\n",
       "          7.38511443e-03,  2.87879559e-03,  1.98623349e-04],\n",
       "        [ 2.65249705e-03,  2.51874738e-03,  2.21744836e-03, ...,\n",
       "          5.21121011e-03,  3.08350991e-03,  2.42910507e-03],\n",
       "        [-1.96729014e-03, -1.90096873e-03, -1.46095285e-03, ...,\n",
       "          8.87477936e-04, -1.32439200e-03, -2.01613867e-03],\n",
       "        ...,\n",
       "        [ 5.93402695e-03,  3.65723784e-03,  1.75449644e-03, ...,\n",
       "          1.16143622e-02,  1.13088014e-02,  8.79691414e-03],\n",
       "        [ 1.72549331e-03,  7.11035015e-04,  8.01114513e-04, ...,\n",
       "          6.78717670e-03,  5.41306198e-03,  3.67906691e-03],\n",
       "        [-1.98774402e-03, -5.75520802e-04,  1.72088364e-03, ...,\n",
       "          6.14775491e-03,  1.58963584e-03, -1.31666776e-03]]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>vfull</span></div><div class='xr-var-dims'>(lev, y, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.04194 0.0462 ... 0.00118 0.009001</div><input id='attrs-fc3a0c7a-3fb9-48b0-a8c9-73f1b1cfbf89' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-fc3a0c7a-3fb9-48b0-a8c9-73f1b1cfbf89' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f0ba8384-5efe-4698-9c9a-a6700ea9dc96' class='xr-var-data-in' type='checkbox'><label for='data-f0ba8384-5efe-4698-9c9a-a6700ea9dc96' 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>units :</span></dt><dd>m s^-1</dd><dt><span>long_name :</span></dt><dd>meridional full velocities in real space</dd></dl></div><div class='xr-var-data'><pre>array([[[ 0.04193728,  0.04619567,  0.04606487, ...,  0.00914963,\n",
       "         -0.01375966,  0.01612357],\n",
       "        [ 0.04114261,  0.04963187,  0.02388613, ...,  0.05653599,\n",
       "          0.029679  ,  0.01889034],\n",
       "        [ 0.04238221,  0.05254364, -0.00317824, ...,  0.08718173,\n",
       "          0.06116157,  0.0193422 ],\n",
       "        ...,\n",
       "        [ 0.12361364,  0.11601851,  0.05419519, ..., -0.11855288,\n",
       "         -0.06021382,  0.05868665],\n",
       "        [ 0.11444405,  0.11155098,  0.06699201, ..., -0.11226167,\n",
       "         -0.07512554,  0.04453635],\n",
       "        [ 0.07533527,  0.07553595,  0.06256184, ..., -0.05571866,\n",
       "         -0.05462336,  0.02682797]],\n",
       "\n",
       "       [[ 0.01243645,  0.01307927,  0.01055738, ..., -0.00193764,\n",
       "          0.00550631,  0.01063706],\n",
       "        [ 0.011838  ,  0.01226643,  0.0098713 , ...,  0.00129449,\n",
       "          0.00826311,  0.01119273],\n",
       "        [ 0.01187803,  0.01273346,  0.00989068, ...,  0.00367322,\n",
       "          0.00943853,  0.01105163],\n",
       "        ...,\n",
       "        [ 0.01046388,  0.01504644,  0.01335022, ..., -0.01056941,\n",
       "         -0.0026157 ,  0.00459572],\n",
       "        [ 0.01279311,  0.01647135,  0.01391478, ..., -0.01038098,\n",
       "         -0.0014363 ,  0.00714923],\n",
       "        [ 0.01334085,  0.01548231,  0.01263995, ..., -0.00688463,\n",
       "          0.00118041,  0.00900085]]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>qh</span></div><div class='xr-var-dims'>(lev, l, k)</div><div class='xr-var-dtype'>complex128</div><div class='xr-var-preview xr-preview'>(0.002324483338567505+0j) ... (1...</div><input id='attrs-ff19dde3-7708-4d41-9daa-9c64a873124e' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ff19dde3-7708-4d41-9daa-9c64a873124e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-62be2d82-9902-418c-b6a3-81d51646dfa6' class='xr-var-data-in' type='checkbox'><label for='data-62be2d82-9902-418c-b6a3-81d51646dfa6' 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>units :</span></dt><dd>s^-1</dd><dt><span>long_name :</span></dt><dd>potential vorticity in spectral space</dd></dl></div><div class='xr-var-data'><pre>array([[[ 2.32448334e-03+0.00000000e+00j,\n",
       "         -2.01080652e-04-4.39246062e-04j,\n",
       "          1.53507095e-06-4.20067097e-04j, ...,\n",
       "         -1.88224155e-13-2.96311988e-14j,\n",
       "          4.81504240e-19+7.99759315e-17j,\n",
       "         -2.99366079e-39+8.39283127e-22j],\n",
       "        [-2.92698757e-05+6.03290076e-04j,\n",
       "          3.54793590e-04-2.18449154e-04j,\n",
       "          2.52214672e-04-6.59930446e-04j, ...,\n",
       "          1.53815216e-13+1.37469143e-13j,\n",
       "         -4.35998761e-18+5.83709453e-17j,\n",
       "          2.99540575e-22-2.85357222e-21j],\n",
       "        [ 1.61731739e-04-4.20079560e-04j,\n",
       "         -3.52313525e-04-1.40295854e-03j,\n",
       "         -1.63231762e-04+1.19696946e-04j, ...,\n",
       "          1.57661809e-13+1.02150932e-14j,\n",
       "         -8.23400906e-18+1.95994567e-17j,\n",
       "         -1.00792612e-22+3.41673650e-23j],\n",
       "        ...,\n",
       "        [-5.07721866e-04+7.06202015e-04j,\n",
       "...\n",
       "          5.61805921e-25-3.75140125e-24j],\n",
       "        ...,\n",
       "        [ 1.25318320e-04-1.13117572e-04j,\n",
       "         -4.13985393e-05-2.14296869e-04j,\n",
       "         -6.92306404e-05-3.21572049e-04j, ...,\n",
       "         -3.21334959e-16+2.00064599e-15j,\n",
       "         -2.82240831e-19+1.75246158e-19j,\n",
       "         -4.59744663e-26+2.41891379e-24j],\n",
       "        [-3.94528728e-05-6.97557545e-05j,\n",
       "         -8.26298616e-05-1.49572101e-04j,\n",
       "         -1.51381577e-06+1.02187434e-04j, ...,\n",
       "         -2.25358031e-15+4.69900069e-16j,\n",
       "         -6.06306978e-19-5.99679682e-20j,\n",
       "          2.29114870e-24-1.20154019e-23j],\n",
       "        [ 1.61796735e-05+1.51818655e-04j,\n",
       "         -1.80918831e-04+1.26499881e-04j,\n",
       "          3.47977208e-05+1.33735499e-05j, ...,\n",
       "         -3.73818518e-15-2.34062717e-15j,\n",
       "          4.19934011e-19+1.72112874e-19j,\n",
       "          1.10348835e-23-1.56631921e-23j]]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>uh</span></div><div class='xr-var-dims'>(lev, l, k)</div><div class='xr-var-dtype'>complex128</div><div class='xr-var-preview xr-preview'>(-39.060809062416254+0j) ... (-3...</div><input id='attrs-2c101275-445f-46e7-b6e7-6d917e70d798' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-2c101275-445f-46e7-b6e7-6d917e70d798' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f71d68a7-31fe-45ed-bd6c-09a3326862eb' class='xr-var-data-in' type='checkbox'><label for='data-f71d68a7-31fe-45ed-bd6c-09a3326862eb' 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>units :</span></dt><dd>m s^-1</dd><dt><span>long_name :</span></dt><dd>zonal velocity anomaly in spectral space</dd></dl></div><div class='xr-var-data'><pre>array([[[-3.90608091e+01+0.00000000e+00j,\n",
       "         -2.06762906e+01+1.73508184e+00j,\n",
       "          4.33688640e-01-2.14771838e-01j, ...,\n",
       "          1.20237434e-10+1.22581925e-10j,\n",
       "          2.28539517e-15+2.73638235e-15j,\n",
       "         -6.45781388e-20+8.86671913e-21j],\n",
       "        [-5.36504824e+01+0.00000000e+00j,\n",
       "          4.42635776e+01+1.23506486e+01j,\n",
       "          1.59365016e+00-3.68557154e+01j, ...,\n",
       "          1.38348463e-10+5.36994501e-11j,\n",
       "         -3.52695867e-15+9.06979097e-15j,\n",
       "         -4.58348613e-20-2.80942762e-20j],\n",
       "        [-2.43280935e+01+0.00000000e+00j,\n",
       "          6.05477733e+01+2.63166040e+01j,\n",
       "          1.99101198e+01-5.03374383e+01j, ...,\n",
       "          1.39460656e-10-1.27539634e-11j,\n",
       "         -8.67019583e-15+1.28067803e-14j,\n",
       "         -6.33284742e-21-3.18590336e-20j],\n",
       "        ...,\n",
       "        [ 2.16311873e+01+0.00000000e+00j,\n",
       "...\n",
       "         -1.18888656e-21-5.59150242e-21j],\n",
       "        ...,\n",
       "        [ 1.17224678e+01+0.00000000e+00j,\n",
       "          2.64593929e+00+1.04069626e+00j,\n",
       "          1.11685906e+00+1.07864755e+01j, ...,\n",
       "         -5.52563727e-13+8.68411985e-12j,\n",
       "          3.11153601e-16-4.04157995e-17j,\n",
       "         -3.37784983e-21-2.88531117e-21j],\n",
       "        [ 1.05227718e+01+0.00000000e+00j,\n",
       "          1.75781290e+00+3.76923449e+00j,\n",
       "         -2.50040215e+00+1.37087074e+01j, ...,\n",
       "          8.35615361e-13+8.02149223e-12j,\n",
       "          2.73193112e-16+8.86981249e-17j,\n",
       "         -3.92037924e-21-4.41225480e-21j],\n",
       "        [ 7.45468949e+00+0.00000000e+00j,\n",
       "          2.81806951e+00+2.53775347e+00j,\n",
       "         -6.03130177e+00+1.19614280e+01j, ...,\n",
       "          2.23652133e-12+6.73751338e-12j,\n",
       "          2.17448314e-16+2.39055914e-16j,\n",
       "         -3.99705064e-21-5.87229612e-21j]]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>vh</span></div><div class='xr-var-dims'>(lev, l, k)</div><div class='xr-var-dtype'>complex128</div><div class='xr-var-preview xr-preview'>0j ... (-6.292253685240078e-19+2...</div><input id='attrs-7c0abbb4-a3f0-42c6-b540-60e889de04bc' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-7c0abbb4-a3f0-42c6-b540-60e889de04bc' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-cefcfcb6-edc5-43b9-a584-44973f88565e' class='xr-var-data-in' type='checkbox'><label for='data-cefcfcb6-edc5-43b9-a584-44973f88565e' 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>units :</span></dt><dd>m s^-1</dd><dt><span>long_name :</span></dt><dd>meridional velocity anomaly in spectral space</dd></dl></div><div class='xr-var-data'><pre>array([[[ 0.00000000e+00+0.00000000e+00j,\n",
       "         -6.66629764e+00+5.79419093e+00j,\n",
       "          1.64939478e+01+1.14129578e+01j, ...,\n",
       "          3.43813642e-09+2.67534196e-10j,\n",
       "          8.36021263e-13-2.69732499e-13j,\n",
       "         -1.57814876e-17+1.90007327e-18j],\n",
       "        [ 0.00000000e+00+0.00000000e+00j,\n",
       "         -6.10275592e+00+4.51854646e+00j,\n",
       "          1.24385903e+01+1.09167008e+01j, ...,\n",
       "          3.69830502e-09-1.17137135e-10j,\n",
       "          8.54494298e-13-2.67735299e-13j,\n",
       "         -1.58190468e-17+2.07918491e-18j],\n",
       "        [ 0.00000000e+00+0.00000000e+00j,\n",
       "         -4.17163618e+00-1.20822021e+00j,\n",
       "          3.44705889e+00+9.42864910e+00j, ...,\n",
       "          3.75688547e-09-5.30597908e-10j,\n",
       "          8.88579094e-13-2.48947942e-13j,\n",
       "         -1.59230525e-17+2.16621624e-18j],\n",
       "        ...,\n",
       "        [ 0.00000000e+00+0.00000000e+00j,\n",
       "...\n",
       "         -6.90713823e-19+5.15410688e-20j],\n",
       "        ...,\n",
       "        [ 0.00000000e+00+0.00000000e+00j,\n",
       "         -1.50221707e+00-6.33378379e-02j,\n",
       "         -6.88126379e-01-3.38280925e+00j, ...,\n",
       "          3.05134435e-11+4.92047404e-11j,\n",
       "          2.19881105e-14-3.81314386e-15j,\n",
       "         -6.01572655e-19-4.29386170e-22j],\n",
       "        [ 0.00000000e+00+0.00000000e+00j,\n",
       "         -1.23586877e+00-2.74358125e-01j,\n",
       "          1.76314072e+00-3.29207121e+00j, ...,\n",
       "          5.52800561e-11+4.88205516e-11j,\n",
       "          2.20529085e-14-4.70788341e-15j,\n",
       "         -6.12989209e-19+1.11449488e-20j],\n",
       "        [ 0.00000000e+00+0.00000000e+00j,\n",
       "         -8.99957764e-01-4.75333696e-01j,\n",
       "          4.38081381e+00-2.41531668e+00j, ...,\n",
       "          7.71509683e-11+4.42692766e-11j,\n",
       "          2.25497652e-14-5.45793111e-15j,\n",
       "         -6.29225369e-19+2.37134782e-20j]]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>ph</span></div><div class='xr-var-dims'>(lev, l, k)</div><div class='xr-var-dtype'>complex128</div><div class='xr-var-preview xr-preview'>0j ... (-9.114747217910704e-17+1...</div><input id='attrs-a6022ec6-3c86-47c2-bea7-de57a7e83aff' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a6022ec6-3c86-47c2-bea7-de57a7e83aff' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c305860b-2c37-479f-9297-146cace85983' class='xr-var-data-in' type='checkbox'><label for='data-c305860b-2c37-479f-9297-146cace85983' 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>units :</span></dt><dd>m^2 s^-1</dd><dt><span>long_name :</span></dt><dd>streamfunction in spectral space</dd></dl></div><div class='xr-var-data'><pre>array([[[ 0.00000000e+00+0.00000000e+00j,\n",
       "          8.39975810e+04+1.00692609e+05j,\n",
       "         -2.25032933e+04+7.30426384e+03j, ...,\n",
       "          4.78122204e-06+7.81118780e-07j,\n",
       "         -2.69136901e-11-1.92528717e-09j,\n",
       "          6.83339794e-32-1.91152085e-14j],\n",
       "        [-1.71543723e+05-1.14820851e+05j,\n",
       "         -1.15392094e+05+9.46613399e+04j,\n",
       "         -1.49294292e+05+2.04864604e+05j, ...,\n",
       "         -3.81431846e-06-3.67850126e-06j,\n",
       "          1.56187433e-10-1.35359732e-09j,\n",
       "         -7.06969307e-15+6.48995002e-14j],\n",
       "        [-3.95191801e+04+2.63444806e+05j,\n",
       "         -2.28589604e+04+4.77298129e+05j,\n",
       "          2.05192125e+04-1.66583547e+04j, ...,\n",
       "         -4.03558234e-06-3.65470935e-07j,\n",
       "          2.07110353e-10-4.32175766e-10j,\n",
       "          1.07638255e-15-1.10020492e-15j],\n",
       "        ...,\n",
       "        [ 1.09370696e+05-2.79500412e+05j,\n",
       "...\n",
       "          1.09978828e-17+6.16270605e-17j],\n",
       "        ...,\n",
       "        [-2.25961145e+04-1.08660256e+05j,\n",
       "         -6.11750802e+02-1.54582008e+05j,\n",
       "         -5.41566103e+04-8.65925364e+04j, ...,\n",
       "          8.01713256e-08-6.67041565e-08j,\n",
       "         -1.56242319e-12+4.46067683e-12j,\n",
       "         -9.12967879e-17-6.35761311e-17j],\n",
       "        [ 3.90714535e+03-1.57168781e+05j,\n",
       "          7.63897180e+04+3.48593962e+04j,\n",
       "          1.47666318e+05+8.44959665e+03j, ...,\n",
       "          5.95741166e-08-1.54408134e-07j,\n",
       "          1.64482508e-11-4.77368441e-12j,\n",
       "          1.86708714e-16+1.38160987e-16j],\n",
       "        [-1.81675230e+05-5.36556727e+04j,\n",
       "         -9.11610787e+04+2.74125502e+04j,\n",
       "         -1.36354890e+05-2.71384385e+02j, ...,\n",
       "          8.79005445e-08-5.65019610e-08j,\n",
       "         -2.77429959e-11-4.36824600e-11j,\n",
       "         -9.11474722e-17+1.52245960e-15j]]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>dqhdt</span></div><div class='xr-var-dims'>(lev, l, k)</div><div class='xr-var-dtype'>complex128</div><div class='xr-var-preview xr-preview'>(-0-0j) ... (1.7617742214702241e...</div><input id='attrs-ce530949-38d3-4003-85be-a37b642217de' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ce530949-38d3-4003-85be-a37b642217de' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5a507eb2-b0fe-4fd9-bd4e-63cd03fc28f5' class='xr-var-data-in' type='checkbox'><label for='data-5a507eb2-b0fe-4fd9-bd4e-63cd03fc28f5' 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>units :</span></dt><dd>s^-2</dd><dt><span>long_name :</span></dt><dd>previous partial derivative of potential vorticity wrt. time in spectral space</dd></dl></div><div class='xr-var-data'><pre>array([[[-0.00000000e+00-0.00000000e+00j,\n",
       "         -3.86764655e-11-7.68358643e-12j,\n",
       "         -1.40536833e-10+1.50126986e-10j, ...,\n",
       "         -1.72320643e-10-2.75723086e-11j,\n",
       "          2.24516032e-12+2.24370494e-10j,\n",
       "         -3.99280395e-28+1.11941857e-10j],\n",
       "        [-2.75534890e-12-3.76298518e-11j,\n",
       "         -3.73486844e-11-4.22377984e-11j,\n",
       "          3.37755096e-11+8.10649340e-11j, ...,\n",
       "          1.56137258e-10+1.44752900e-10j,\n",
       "         -1.77896313e-11+1.86998273e-10j,\n",
       "          4.93537691e-11-4.60848056e-10j],\n",
       "        [ 1.50982658e-10-8.47125976e-11j,\n",
       "          1.54275188e-10+1.65761530e-10j,\n",
       "         -2.80712916e-11-7.36408243e-11j, ...,\n",
       "          2.29786125e-10+1.78063142e-11j,\n",
       "         -4.34630303e-11+9.68319595e-11j,\n",
       "         -2.14306548e-11+1.20467462e-11j],\n",
       "        ...,\n",
       "        [ 4.88094845e-11-7.46402415e-11j,\n",
       "...\n",
       "          1.53944643e-13-1.05406334e-12j],\n",
       "        ...,\n",
       "        [-1.91300325e-12+1.84361759e-11j,\n",
       "         -4.69792647e-11-5.49828626e-12j,\n",
       "          5.84761435e-12-2.43811081e-11j, ...,\n",
       "         -8.46643650e-13+5.23244563e-12j,\n",
       "         -3.13536764e-12+1.94549683e-12j,\n",
       "         -4.08659085e-14+1.85082940e-12j],\n",
       "        [-3.25807491e-11-1.49158466e-11j,\n",
       "         -1.60679566e-11+3.31564556e-11j,\n",
       "          1.51118326e-11+5.38873773e-12j, ...,\n",
       "         -3.27891862e-12+6.86330006e-13j,\n",
       "         -3.10204959e-12-3.04848569e-13j,\n",
       "          6.71792676e-13-3.45260401e-12j],\n",
       "        [ 2.42821648e-13-7.85083198e-12j,\n",
       "         -2.31744952e-11-1.49179172e-11j,\n",
       "         -2.90741823e-11-1.99008647e-11j, ...,\n",
       "         -3.85216251e-12-2.43477494e-12j,\n",
       "          1.36240518e-12+5.80086651e-13j,\n",
       "          1.76177422e-12-2.50264620e-12j]]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Ubg</span></div><div class='xr-var-dims'>(lev)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.025 0.0</div><input id='attrs-ff27cd93-3b36-4ca8-9116-7e4308cee98b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ff27cd93-3b36-4ca8-9116-7e4308cee98b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-52987ebe-1db0-4d55-9f4f-db0837d6f57d' class='xr-var-data-in' type='checkbox'><label for='data-52987ebe-1db0-4d55-9f4f-db0837d6f57d' 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>units :</span></dt><dd>m s^-1</dd><dt><span>long_name :</span></dt><dd>background zonal velocity</dd></dl></div><div class='xr-var-data'><pre>array([0.025, 0.   ])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Qy</span></div><div class='xr-var-dims'>(lev)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>1.039e-10 -7.222e-12</div><input id='attrs-82a25591-ac71-48b3-8279-7243701b87b5' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-82a25591-ac71-48b3-8279-7243701b87b5' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-013c1c3b-96df-40d7-8cd7-4d20d6146d0a' class='xr-var-data-in' type='checkbox'><label for='data-013c1c3b-96df-40d7-8cd7-4d20d6146d0a' 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>units :</span></dt><dd>m^-1 s^-1</dd><dt><span>long_name :</span></dt><dd>background potential vorticity gradient</dd></dl></div><div class='xr-var-data'><pre>array([ 1.03888889e-10, -7.22222222e-12])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>dqdt</span></div><div class='xr-var-dims'>(lev, y, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-7.465e-12 ... -8.823e-13</div><input id='attrs-f6c34af3-b8f7-43b5-bc43-84d222830537' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f6c34af3-b8f7-43b5-bc43-84d222830537' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a660e546-5f5f-4570-8255-d6ac90dc237d' class='xr-var-data-in' type='checkbox'><label for='data-a660e546-5f5f-4570-8255-d6ac90dc237d' 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>units :</span></dt><dd>s^-2</dd><dt><span>long_name :</span></dt><dd>previous partial derivative of potential vorticity wrt. time in real space</dd></dl></div><div class='xr-var-data'><pre>array([[[-7.46480121e-12, -7.05301364e-12, -2.50852789e-12, ...,\n",
       "          8.10469953e-12, -3.17683647e-12,  2.73974577e-12],\n",
       "        [-2.76997848e-12,  2.17936883e-11,  9.59576924e-12, ...,\n",
       "         -1.13352671e-11,  1.63170042e-12,  4.22105886e-12],\n",
       "        [-4.82795936e-13,  1.12061876e-11, -5.79556648e-12, ...,\n",
       "          9.42784264e-12,  7.15595642e-12, -4.68795757e-12],\n",
       "        ...,\n",
       "        [-1.06603635e-11, -5.81864791e-12, -7.50220858e-12, ...,\n",
       "         -1.27884657e-11,  1.43449582e-11, -5.26804162e-12],\n",
       "        [ 2.11718134e-11,  4.52763323e-12,  1.22028997e-12, ...,\n",
       "         -1.43204608e-11, -7.71830287e-12, -6.75550187e-13],\n",
       "        [ 1.81453295e-11,  1.18766938e-11, -1.23646569e-11, ...,\n",
       "         -1.06645633e-11,  1.67536304e-11,  8.48204329e-12]],\n",
       "\n",
       "       [[-3.27685950e-13, -4.08228921e-13, -3.16244516e-13, ...,\n",
       "         -3.05938150e-13, -2.98492814e-13, -4.37900110e-13],\n",
       "        [-8.92131814e-13, -9.65029971e-13, -3.94851240e-13, ...,\n",
       "         -6.34837154e-13, -3.82828419e-13, -6.20347624e-13],\n",
       "        [-4.29263534e-13, -2.22594932e-14,  4.68287952e-13, ...,\n",
       "         -4.44701468e-13, -3.74553750e-13, -5.39096719e-13],\n",
       "        ...,\n",
       "        [-7.91955099e-13, -2.01448024e-13,  3.18076661e-13, ...,\n",
       "          1.10272854e-12,  3.83546108e-13, -6.88516473e-13],\n",
       "        [-1.08710988e-12, -3.62382375e-13,  1.50900153e-13, ...,\n",
       "          3.73534447e-13, -1.83579735e-13, -1.06252388e-12],\n",
       "        [-6.32057816e-13, -2.68329613e-13,  6.63375808e-14, ...,\n",
       "          2.36160060e-13, -3.85837772e-13, -8.82316262e-13]]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>p</span></div><div class='xr-var-dims'>(lev, y, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-247.4 450.7 ... -705.3 -621.2</div><input id='attrs-37736ac3-6dee-4e98-96db-1e49ea594c9c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-37736ac3-6dee-4e98-96db-1e49ea594c9c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9470ae08-e370-44cc-b21e-eb85606a3f9f' class='xr-var-data-in' type='checkbox'><label for='data-9470ae08-e370-44cc-b21e-eb85606a3f9f' 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>units :</span></dt><dd>m^2 s^-1</dd><dt><span>long_name :</span></dt><dd>streamfunction in real space</dd></dl></div><div class='xr-var-data'><pre>array([[[-2.47381527e+02,  4.50686452e+02,  1.18462755e+03, ...,\n",
       "         -6.13686454e+02, -7.16347205e+02, -7.40135279e+02],\n",
       "        [ 4.55907305e+02,  1.21151360e+03,  1.81812317e+03, ...,\n",
       "         -1.01901104e+03, -3.20375578e+02,  4.26449504e+00],\n",
       "        [ 8.34947519e+02,  1.66696358e+03,  2.10119915e+03, ...,\n",
       "         -1.40717066e+03, -1.47115787e+02,  4.16884061e+02],\n",
       "        ...,\n",
       "        [-3.15532332e+03, -1.20408874e+03,  1.85240148e+02, ...,\n",
       "         -3.14075295e+03, -4.68167353e+03, -4.68662633e+03],\n",
       "        [-2.90503063e+03, -1.07218303e+03,  3.69820356e+02, ...,\n",
       "         -2.37614482e+03, -4.00664292e+03, -4.26189567e+03],\n",
       "        [-1.50142416e+03, -2.95536991e+02,  8.05719400e+02, ...,\n",
       "         -1.13731174e+03, -2.13932315e+03, -2.38926491e+03]],\n",
       "\n",
       "       [[-4.22566434e+02, -2.21382990e+02, -3.06375994e+01, ...,\n",
       "         -7.64257789e+02, -7.36823014e+02, -6.05208458e+02],\n",
       "        [-4.51020676e+02, -2.61408427e+02, -8.28712847e+01, ...,\n",
       "         -8.67400820e+02, -7.88825602e+02, -6.31425892e+02],\n",
       "        [-4.65884218e+02, -2.71415905e+02, -8.80387724e+01, ...,\n",
       "         -9.15972952e+02, -8.07781808e+02, -6.43859705e+02],\n",
       "        ...,\n",
       "        [-3.87079982e+02, -1.83538037e+02,  4.94190574e+01, ...,\n",
       "         -4.18870074e+02, -5.23407333e+02, -5.05290616e+02],\n",
       "        [-4.51463465e+02, -2.18551413e+02,  2.99736632e+01, ...,\n",
       "         -5.61994310e+02, -6.58579830e+02, -6.09695633e+02],\n",
       "        [-4.43276966e+02, -2.14427844e+02,  1.40496066e+01, ...,\n",
       "         -6.56006738e+02, -7.05254610e+02, -6.21180587e+02]]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Ensspec</span></div><div class='xr-var-dims'>(lev, l, k)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>3.221e-13 3.714e-14 ... 2.195e-53</div><input id='attrs-58571b84-35f4-4809-8297-e2f2c364639a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-58571b84-35f4-4809-8297-e2f2c364639a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b796f0d1-366f-4e71-8b0b-41a11a761908' class='xr-var-data-in' type='checkbox'><label for='data-b796f0d1-366f-4e71-8b0b-41a11a761908' 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>enstrophy spectrum</dd><dt><span>units :</span></dt><dd>s^-2</dd></dl></div><div class='xr-var-data'><pre>array([[[3.22057175e-13, 3.71403542e-14, 2.16930481e-14, ...,\n",
       "         5.71871690e-33, 4.36189560e-40, 1.46392698e-49],\n",
       "        [1.79426521e-14, 2.93879362e-14, 2.75107173e-14, ...,\n",
       "         4.44877708e-33, 3.10819945e-40, 1.47960701e-49],\n",
       "        [3.87727581e-14, 2.83845192e-14, 3.34693556e-14, ...,\n",
       "         2.55274957e-33, 2.03372844e-40, 7.35682386e-50],\n",
       "        ...,\n",
       "        [9.62502459e-14, 8.53490518e-14, 1.06223689e-13, ...,\n",
       "         1.04755599e-33, 6.30340981e-41, 1.56764288e-50],\n",
       "        [3.87727581e-14, 3.65703075e-14, 3.49163776e-14, ...,\n",
       "         2.98042516e-33, 1.97337790e-40, 7.79488065e-50],\n",
       "        [1.79426521e-14, 2.10737124e-14, 1.77783346e-14, ...,\n",
       "         4.07652941e-33, 3.45020117e-40, 1.46220667e-49]],\n",
       "\n",
       "       [[0.00000000e+00, 2.31037571e-15, 1.24686096e-15, ...,\n",
       "         9.69650234e-37, 7.77313383e-44, 2.75778178e-53],\n",
       "        [1.08733063e-15, 1.80265152e-15, 1.47732661e-15, ...,\n",
       "         8.31423477e-37, 5.82516248e-44, 2.33262027e-53],\n",
       "        [2.07080859e-15, 1.45642460e-15, 1.56012498e-15, ...,\n",
       "         4.10478878e-37, 2.87790905e-44, 8.22526289e-54],\n",
       "        ...,\n",
       "        [4.21663754e-15, 3.11157315e-15, 4.00824057e-15, ...,\n",
       "         1.50166582e-37, 7.04172900e-45, 1.52247195e-54],\n",
       "        [2.07080859e-15, 1.92848905e-15, 1.48922901e-15, ...,\n",
       "         4.05469347e-37, 2.90864034e-44, 8.71432147e-54],\n",
       "        [1.08733063e-15, 1.26457034e-15, 9.66235126e-16, ...,\n",
       "         9.34703284e-37, 6.26169709e-44, 2.19453275e-53]]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>KEspec</span></div><div class='xr-var-dims'>(lev, l, k)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0 8.622e-08 ... 1.725e-45</div><input id='attrs-f41d2169-734e-42b4-a7bb-70dad35f0a70' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f41d2169-734e-42b4-a7bb-70dad35f0a70' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1340ce8f-0917-48b7-b99a-0efd9c2ea210' class='xr-var-data-in' type='checkbox'><label for='data-1340ce8f-0917-48b7-b99a-0efd9c2ea210' 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>kinetic energy spectrum</dd><dt><span>units :</span></dt><dd>m^2 s^-2</dd></dl></div><div class='xr-var-data'><pre>array([[[0.00000000e+00, 8.62165368e-08, 3.11562419e-07, ...,\n",
       "         1.33563127e-25, 9.64652925e-33, 3.06975796e-42],\n",
       "        [1.17490940e-07, 1.82906861e-07, 5.69717366e-07, ...,\n",
       "         1.03818586e-25, 6.86955544e-33, 3.09942269e-42],\n",
       "        [7.91357529e-07, 7.41483970e-07, 1.15445554e-06, ...,\n",
       "         5.93960597e-26, 4.48171261e-33, 1.53749040e-42],\n",
       "        ...,\n",
       "        [3.22695389e-06, 3.79626070e-06, 4.63974930e-06, ...,\n",
       "         2.42662005e-26, 1.38315605e-33, 3.26244688e-43],\n",
       "        [7.91357529e-07, 7.96539073e-07, 1.33668827e-06, ...,\n",
       "         6.93511898e-26, 4.34917658e-33, 1.62897212e-42],\n",
       "        [1.17490940e-07, 1.69667966e-07, 4.12790311e-07, ...,\n",
       "         9.51322177e-26, 7.62383975e-33, 3.06316983e-42]],\n",
       "\n",
       "       [[0.00000000e+00, 8.01302815e-09, 5.90111062e-08, ...,\n",
       "         9.74026612e-29, 6.33055858e-36, 1.98539033e-45],\n",
       "        [5.24011894e-08, 4.40332956e-08, 1.09956400e-07, ...,\n",
       "         8.05275074e-29, 5.00104097e-36, 1.71949441e-45],\n",
       "        [1.91841201e-07, 1.95695441e-07, 2.22918844e-07, ...,\n",
       "         4.07156653e-29, 2.63519601e-36, 8.25966581e-46],\n",
       "        ...,\n",
       "        [2.83931580e-07, 4.90116555e-07, 3.55646425e-07, ...,\n",
       "         1.68504259e-29, 7.78720614e-37, 1.59739577e-46],\n",
       "        [1.91841201e-07, 1.53728699e-07, 2.45466546e-07, ...,\n",
       "         4.66898159e-29, 2.70850041e-36, 8.57292827e-46],\n",
       "        [5.24011894e-08, 4.44092019e-08, 1.18183997e-07, ...,\n",
       "         7.85764035e-29, 5.07577067e-36, 1.72538781e-45]]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>EKEdiss</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>5.262e-11</div><input id='attrs-3c124d67-bb98-4a21-8b31-c9576b24bf34' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3c124d67-bb98-4a21-8b31-c9576b24bf34' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-34703f72-d027-4585-b788-097b301ff890' class='xr-var-data-in' type='checkbox'><label for='data-34703f72-d027-4585-b788-097b301ff890' 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>total energy dissipation by bottom drag</dd><dt><span>units :</span></dt><dd>m^2 s^-3</dd></dl></div><div class='xr-var-data'><pre>array(5.2620925e-11)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>KEfrictionspec</span></div><div class='xr-var-dims'>(l, k)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-0.0 -3.71e-15 ... -7.988e-52</div><input id='attrs-bcb1fde1-6422-4ed5-9681-7bd06198b41b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-bcb1fde1-6422-4ed5-9681-7bd06198b41b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1b539e61-1ab1-4ea4-8ffe-0992f95edf80' class='xr-var-data-in' type='checkbox'><label for='data-1b539e61-1ab1-4ea4-8ffe-0992f95edf80' 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>total energy dissipation spectrum by bottom drag</dd><dt><span>units :</span></dt><dd>m^2 s^-3</dd></dl></div><div class='xr-var-data'><pre>array([[-0.00000000e+00, -3.70971151e-15, -2.73197817e-14, ...,\n",
       "        -4.50935360e-35, -2.93079540e-42, -9.19156307e-52],\n",
       "       [-2.42596547e-14, -2.03856545e-14, -5.09054149e-14, ...,\n",
       "        -3.72810148e-35, -2.31528193e-42, -7.96057134e-52],\n",
       "       [-8.88148024e-14, -9.05991611e-14, -1.03202508e-13, ...,\n",
       "        -1.88497244e-35, -1.21999034e-42, -3.82389489e-52],\n",
       "       ...,\n",
       "       [-1.31448964e-13, -2.26904360e-13, -1.64650069e-13, ...,\n",
       "        -7.80107316e-36, -3.60516495e-43, -7.39530344e-53],\n",
       "       [-8.88148024e-14, -7.11702383e-14, -1.13641192e-13, ...,\n",
       "        -2.16155172e-35, -1.25392735e-42, -3.96892287e-52],\n",
       "       [-2.42596547e-14, -2.05596841e-14, -5.47144633e-14, ...,\n",
       "        -3.63777318e-35, -2.34987879e-42, -7.98785540e-52]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>EKE</span></div><div class='xr-var-dims'>(lev)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.002105 5.683e-05</div><input id='attrs-756b449f-a7c2-4e94-91bf-a1f4d62425da' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-756b449f-a7c2-4e94-91bf-a1f4d62425da' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2784b267-4989-4838-981d-e253914827bf' class='xr-var-data-in' type='checkbox'><label for='data-2784b267-4989-4838-981d-e253914827bf' 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>mean eddy kinetic energy</dd><dt><span>units :</span></dt><dd>m^2 s^-2</dd></dl></div><div class='xr-var-data'><pre>array([2.10465295e-03, 5.68309627e-05])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Dissspec</span></div><div class='xr-var-dims'>(l, k)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-0.0 -0.0 ... -5.44e-27 -1.075e-31</div><input id='attrs-91214108-1fe8-4c6c-bcc2-29bfb378d262' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-91214108-1fe8-4c6c-bcc2-29bfb378d262' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b89484cb-6f31-4c4e-b51b-5b6ef374c9f5' class='xr-var-data-in' type='checkbox'><label for='data-b89484cb-6f31-4c4e-b51b-5b6ef374c9f5' 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>Spectral contribution of filter dissipation to total energy</dd><dt><span>units :</span></dt><dd>m^2 s^-3</dd></dl></div><div class='xr-var-data'><pre>array([[-0.00000000e+00, -0.00000000e+00, -0.00000000e+00, ...,\n",
       "        -2.69775429e-23, -5.92222478e-27, -8.88727114e-32],\n",
       "       [-0.00000000e+00, -0.00000000e+00, -0.00000000e+00, ...,\n",
       "        -2.35027121e-23, -4.90135766e-27, -1.08815499e-31],\n",
       "       [-0.00000000e+00, -0.00000000e+00, -0.00000000e+00, ...,\n",
       "        -1.89904693e-23, -5.03809118e-27, -9.66362169e-32],\n",
       "       ...,\n",
       "       [-0.00000000e+00, -0.00000000e+00, -0.00000000e+00, ...,\n",
       "        -1.39497309e-23, -3.36051678e-27, -5.49266578e-32],\n",
       "       [-0.00000000e+00, -0.00000000e+00, -0.00000000e+00, ...,\n",
       "        -2.21700749e-23, -4.88937886e-27, -1.02374670e-31],\n",
       "       [-0.00000000e+00, -0.00000000e+00, -0.00000000e+00, ...,\n",
       "        -2.15408317e-23, -5.43969706e-27, -1.07527907e-31]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>ENSDissspec</span></div><div class='xr-var-dims'>(l, k)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0 0.0 ... -2.255e-34 -4.726e-39</div><input id='attrs-7bb88999-6f8c-4d69-a608-4e564d66d3ca' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-7bb88999-6f8c-4d69-a608-4e564d66d3ca' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2f22b296-2820-4e71-98d0-374d787b7c24' class='xr-var-data-in' type='checkbox'><label for='data-2f22b296-2820-4e71-98d0-374d787b7c24' 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>Spectral contribution of filter dissipation to barotropic enstrophy</dd><dt><span>units :</span></dt><dd>s^-3</dd></dl></div><div class='xr-var-data'><pre>array([[ 0.00000000e+00,  0.00000000e+00,  0.00000000e+00, ...,\n",
       "        -1.05229705e-30, -2.45310248e-34, -3.90219837e-39],\n",
       "       [ 0.00000000e+00,  0.00000000e+00,  0.00000000e+00, ...,\n",
       "        -9.17586872e-31, -2.03169873e-34, -4.78319490e-39],\n",
       "       [ 0.00000000e+00,  0.00000000e+00,  0.00000000e+00, ...,\n",
       "        -7.43837659e-31, -2.09504579e-34, -4.25875740e-39],\n",
       "       ...,\n",
       "       [ 0.00000000e+00,  0.00000000e+00,  0.00000000e+00, ...,\n",
       "        -5.49088088e-31, -1.40402683e-34, -2.43173373e-39],\n",
       "       [ 0.00000000e+00,  0.00000000e+00,  0.00000000e+00, ...,\n",
       "        -8.68333159e-31, -2.03298790e-34, -4.51183698e-39],\n",
       "       [ 0.00000000e+00,  0.00000000e+00,  0.00000000e+00, ...,\n",
       "        -8.40976585e-31, -2.25532253e-34, -4.72630221e-39]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>paramspec</span></div><div class='xr-var-dims'>(l, k)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-0.0 -0.0 -0.0 ... -0.0 -0.0 -0.0</div><input id='attrs-0cc3cd4a-f71e-4ce8-9040-a6e172a351b0' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-0cc3cd4a-f71e-4ce8-9040-a6e172a351b0' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-bade3ead-0a15-4f38-8d38-ca7f1ac04a01' class='xr-var-data-in' type='checkbox'><label for='data-bade3ead-0a15-4f38-8d38-ca7f1ac04a01' 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>Spectral contribution of subgrid parameterization (if present)</dd><dt><span>units :</span></dt><dd>m^2 s^-3</dd></dl></div><div class='xr-var-data'><pre>array([[-0., -0., -0., ..., -0., -0., -0.],\n",
       "       [-0., -0., -0., ..., -0., -0., -0.],\n",
       "       [-0., -0., -0., ..., -0., -0., -0.],\n",
       "       ...,\n",
       "       [-0., -0., -0., ..., -0., -0., -0.],\n",
       "       [-0., -0., -0., ..., -0., -0., -0.],\n",
       "       [-0., -0., -0., ..., -0., -0., -0.]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>entspec</span></div><div class='xr-var-dims'>(l, k)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>1.288e-14 2.147e-19 ... 5.792e-51</div><input id='attrs-94913434-a5bd-4744-ae88-e0f917590095' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-94913434-a5bd-4744-ae88-e0f917590095' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-750fa450-d5c6-4558-9434-7aa36a8a716d' class='xr-var-data-in' type='checkbox'><label for='data-750fa450-d5c6-4558-9434-7aa36a8a716d' 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>barotropic enstrophy spectrum</dd><dt><span>units :</span></dt><dd>m s^-2</dd></dl></div><div class='xr-var-data'><pre>array([[1.28822870e-14, 2.14741640e-19, 1.10258362e-17, ...,\n",
       "        2.27206968e-34, 1.72932417e-41, 5.84298924e-51],\n",
       "       [2.23721116e-18, 3.44058548e-18, 2.78185191e-17, ...,\n",
       "        1.77556061e-34, 1.24516247e-41, 5.84432213e-51],\n",
       "       [3.81940910e-17, 4.78894668e-17, 9.47022603e-17, ...,\n",
       "        1.00956523e-34, 8.02829297e-42, 2.92275872e-51],\n",
       "       ...,\n",
       "       [1.87069991e-16, 3.26534785e-16, 3.64131721e-16, ...,\n",
       "        4.16435241e-35, 2.49288871e-42, 6.19689067e-52],\n",
       "       [3.81940910e-17, 3.97777065e-17, 1.10957315e-16, ...,\n",
       "        1.18120900e-34, 7.82723106e-42, 3.09080594e-51],\n",
       "       [2.23721116e-18, 3.89320480e-18, 2.71806541e-17, ...,\n",
       "        1.62846797e-34, 1.36948155e-41, 5.79236715e-51]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>paramspec_APEflux</span></div><div class='xr-var-dims'>(l, k)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-0.0 -0.0 -0.0 ... -0.0 -0.0 -0.0</div><input id='attrs-61b28ccd-1fdd-40e2-99cb-b896a6e6dd20' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-61b28ccd-1fdd-40e2-99cb-b896a6e6dd20' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e1ffcb79-dfac-4850-9e04-eae896978966' class='xr-var-data-in' type='checkbox'><label for='data-e1ffcb79-dfac-4850-9e04-eae896978966' 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>total additional APE flux due to subgrid parameterization</dd><dt><span>units :</span></dt><dd>m^2 s^-3</dd></dl></div><div class='xr-var-data'><pre>array([[-0., -0., -0., ..., -0., -0., -0.],\n",
       "       [-0., -0., -0., ..., -0., -0., -0.],\n",
       "       [-0., -0., -0., ..., -0., -0., -0.],\n",
       "       ...,\n",
       "       [-0., -0., -0., ..., -0., -0., -0.],\n",
       "       [-0., -0., -0., ..., -0., -0., -0.],\n",
       "       [-0., -0., -0., ..., -0., -0., -0.]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>paramspec_KEflux</span></div><div class='xr-var-dims'>(l, k)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0 0.0 0.0 0.0 ... 0.0 0.0 0.0 0.0</div><input id='attrs-64750f16-f413-444a-9570-5707108937b1' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-64750f16-f413-444a-9570-5707108937b1' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9b015680-f26d-4e63-8f4c-819bde66bffb' class='xr-var-data-in' type='checkbox'><label for='data-9b015680-f26d-4e63-8f4c-819bde66bffb' 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>total additional KE flux due to subgrid parameterization</dd><dt><span>units :</span></dt><dd>m^2 s^-3</dd></dl></div><div class='xr-var-data'><pre>array([[0., 0., 0., ..., 0., 0., 0.],\n",
       "       [0., 0., 0., ..., 0., 0., 0.],\n",
       "       [0., 0., 0., ..., 0., 0., 0.],\n",
       "       ...,\n",
       "       [0., 0., 0., ..., 0., 0., 0.],\n",
       "       [0., 0., 0., ..., 0., 0., 0.],\n",
       "       [0., 0., 0., ..., 0., 0., 0.]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>ENSflux</span></div><div class='xr-var-dims'>(l, k)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0 -3.132e-23 ... 4.728e-39</div><input id='attrs-67199475-395f-4930-9c07-016852b809a1' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-67199475-395f-4930-9c07-016852b809a1' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3ace674a-aa62-4683-8d64-8519260ebead' class='xr-var-data-in' type='checkbox'><label for='data-3ace674a-aa62-4683-8d64-8519260ebead' 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>barotropic enstrophy flux</dd><dt><span>units :</span></dt><dd>s^-3</dd></dl></div><div class='xr-var-data'><pre>array([[ 0.00000000e+00, -3.13209704e-23,  3.37332581e-23, ...,\n",
       "         1.05256536e-30,  2.45367529e-34,  3.90337644e-39],\n",
       "       [ 9.87953585e-24,  8.24561526e-23, -1.56179572e-23, ...,\n",
       "         9.17841977e-31,  2.03226045e-34,  4.78418792e-39],\n",
       "       [-1.55140389e-23, -4.87651205e-23, -1.23032936e-23, ...,\n",
       "         7.44037847e-31,  2.09564190e-34,  4.25983062e-39],\n",
       "       ...,\n",
       "       [-1.14215311e-22, -1.02671958e-22, -4.64890589e-22, ...,\n",
       "         5.49249493e-31,  1.40442956e-34,  2.43246172e-39],\n",
       "       [-1.55140389e-23,  2.68806531e-23,  1.04498927e-23, ...,\n",
       "         8.68580273e-31,  2.03352779e-34,  4.51325623e-39],\n",
       "       [ 9.87953585e-24,  6.94577514e-23,  2.07970865e-23, ...,\n",
       "         8.41193863e-31,  2.25588383e-34,  4.72753524e-39]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>ENSgenspec</span></div><div class='xr-var-dims'>(l, k)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0 -3.458e-24 ... -3.186e-61</div><input id='attrs-b729e761-da87-4e30-8151-ddba2e807f29' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b729e761-da87-4e30-8151-ddba2e807f29' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-552489db-67d9-4fd3-8d0e-7e76d92671b7' class='xr-var-data-in' type='checkbox'><label for='data-552489db-67d9-4fd3-8d0e-7e76d92671b7' 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>the spectrum of the rate of generation of barotropic enstrophy</dd><dt><span>units :</span></dt><dd>s^-3</dd></dl></div><div class='xr-var-data'><pre>array([[ 0.00000000e+00, -3.45832152e-24, -4.95562005e-23, ...,\n",
       "        -1.97760373e-44, -1.40678308e-51,  3.70687839e-78],\n",
       "       [ 0.00000000e+00, -7.26192151e-23, -1.99370821e-23, ...,\n",
       "        -2.77248548e-44,  5.98402401e-52,  6.46395597e-61],\n",
       "       [ 0.00000000e+00, -1.13796110e-24, -4.17650396e-23, ...,\n",
       "        -5.56183933e-45, -7.97734649e-52, -2.85804147e-62],\n",
       "       ...,\n",
       "       [ 0.00000000e+00, -1.14866262e-22,  4.13637960e-22, ...,\n",
       "        -4.73517778e-45, -2.60546639e-52, -1.74309872e-61],\n",
       "       [ 0.00000000e+00, -5.40902919e-23, -5.06432107e-23, ...,\n",
       "        -5.39127568e-45, -2.78324380e-52, -6.04781828e-61],\n",
       "       [ 0.00000000e+00, -3.96757935e-23, -2.21005566e-23, ...,\n",
       "        -1.89308452e-44,  7.51043675e-52, -3.18580925e-61]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>ENSfrictionspec</span></div><div class='xr-var-dims'>(l, k)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0 -7.479e-24 ... -7.94e-60</div><input id='attrs-e3c4b919-7f28-4fc4-b8d8-c5644f29b521' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e3c4b919-7f28-4fc4-b8d8-c5644f29b521' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9cd216c5-b328-43c7-9f4d-707fbcff3721' class='xr-var-data-in' type='checkbox'><label for='data-9cd216c5-b328-43c7-9f4d-707fbcff3721' 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>the spectrum of the rate of dissipation of barotropic enstrophy due to bottom friction</dd><dt><span>units :</span></dt><dd>s^-3</dd></dl></div><div class='xr-var-data'><pre>array([[ 0.00000000e+00, -7.47883873e-24, -3.40269577e-24, ...,\n",
       "        -3.69366418e-43, -2.90392626e-50, -1.16441306e-59],\n",
       "       [ 1.18273872e-24, -9.34193701e-24,  6.13395879e-24, ...,\n",
       "        -3.46568700e-43, -2.58436859e-50, -8.03583212e-60],\n",
       "       [ 1.94688660e-23,  1.43743267e-23,  1.84268772e-23, ...,\n",
       "        -1.40447345e-43, -9.26528514e-51, -3.01208838e-60],\n",
       "       ...,\n",
       "       [ 1.13854810e-22,  1.73743048e-22,  1.50186186e-22, ...,\n",
       "        -5.66747650e-44, -2.19981093e-51, -4.53770567e-61],\n",
       "       [ 1.94688660e-23,  1.43401385e-23,  4.41075781e-23, ...,\n",
       "        -1.40120031e-43, -1.06181092e-50, -3.02016304e-60],\n",
       "       [ 1.18273872e-24, -1.76676500e-24, -8.58711443e-25, ...,\n",
       "        -3.97002188e-43, -2.39539566e-50, -7.93980913e-60]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>APEgenspec</span></div><div class='xr-var-dims'>(l, k)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0 -7.781e-16 ... -7.168e-53</div><input id='attrs-46f65b09-003a-45ae-a864-8b4765e8a63c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-46f65b09-003a-45ae-a864-8b4765e8a63c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-884e2486-155a-488c-ad6a-a52400ed206c' class='xr-var-data-in' type='checkbox'><label for='data-884e2486-155a-488c-ad6a-a52400ed206c' 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>the spectrum of the rate of generation of available potential energy</dd><dt><span>units :</span></dt><dd>m^2 s^-3</dd></dl></div><div class='xr-var-data'><pre>array([[ 0.00000000e+00, -7.78122342e-16, -1.11501451e-14, ...,\n",
       "        -4.44960839e-36, -3.16526194e-43,  8.34047637e-70],\n",
       "       [ 0.00000000e+00, -1.63393234e-14, -4.48584347e-15, ...,\n",
       "        -6.23809234e-36,  1.34640540e-43,  1.45439009e-52],\n",
       "       [ 0.00000000e+00, -2.56041247e-16, -9.39713391e-15, ...,\n",
       "        -1.25141385e-36, -1.79490296e-43, -6.43059330e-54],\n",
       "       ...,\n",
       "       [ 0.00000000e+00, -2.58449090e-14,  9.30685410e-14, ...,\n",
       "        -1.06541500e-36, -5.86229938e-44, -3.92197212e-53],\n",
       "       [ 0.00000000e+00, -1.21703157e-14, -1.13947224e-14, ...,\n",
       "        -1.21303703e-36, -6.26229855e-44, -1.36075911e-52],\n",
       "       [ 0.00000000e+00, -8.92705355e-15, -4.97262523e-15, ...,\n",
       "        -4.25944018e-36,  1.68984827e-43, -7.16807080e-53]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>APEflux</span></div><div class='xr-var-dims'>(l, k)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-0.0 -7.048e-16 ... 2.951e-33</div><input id='attrs-9d6a3284-49e2-4a8f-b86a-43532f4227ab' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-9d6a3284-49e2-4a8f-b86a-43532f4227ab' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-21d34e84-c3d3-43f7-89b4-df2863eb723f' class='xr-var-data-in' type='checkbox'><label for='data-21d34e84-c3d3-43f7-89b4-df2863eb723f' 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>spectral flux of available potential energy</dd><dt><span>units :</span></dt><dd>m^2 s^-3</dd></dl></div><div class='xr-var-data'><pre>array([[-0.00000000e+00, -7.04819510e-16,  8.38720913e-15, ...,\n",
       "         3.83929794e-25,  9.98642618e-29,  1.45610163e-33],\n",
       "       [ 1.54985334e-15,  1.79456797e-14, -8.79617227e-15, ...,\n",
       "         4.27320654e-25,  1.08029713e-28,  2.82920104e-33],\n",
       "       [-1.93390457e-14, -2.55156027e-14, -2.03121096e-14, ...,\n",
       "         5.03477783e-25,  1.68333626e-28,  3.86869722e-33],\n",
       "       ...,\n",
       "       [-1.24517562e-13, -2.26947417e-13, -1.87937326e-13, ...,\n",
       "         4.70297165e-25,  1.37416346e-28,  2.70280182e-33],\n",
       "       [-1.93390457e-14, -1.16103445e-14, -4.45253636e-14, ...,\n",
       "         6.05818242e-25,  1.77693471e-28,  4.23644959e-33],\n",
       "       [ 1.54985334e-15,  1.27931866e-14,  1.22129644e-14, ...,\n",
       "         4.23808494e-25,  1.09705240e-28,  2.95062136e-33]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>KEflux</span></div><div class='xr-var-dims'>(l, k)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0 -4.226e-15 ... 9.932e-32</div><input id='attrs-c34c1b70-7b7b-4a0b-b82b-31efdf552014' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-c34c1b70-7b7b-4a0b-b82b-31efdf552014' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-eaf43e56-c78f-4680-b064-24c41032e57b' class='xr-var-data-in' type='checkbox'><label for='data-eaf43e56-c78f-4680-b064-24c41032e57b' 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>spectral flux of kinetic energy</dd><dt><span>units :</span></dt><dd>m^2 s^-3</dd></dl></div><div class='xr-var-data'><pre>array([[ 0.00000000e+00, -4.22556346e-15,  2.56123875e-14, ...,\n",
       "         2.66004923e-23,  5.82374352e-27,  8.74434443e-32],\n",
       "       [ 2.53347400e-14,  1.89053541e-14,  5.82195701e-14, ...,\n",
       "         2.26896836e-23,  4.62604099e-27,  1.00407639e-31],\n",
       "       [ 1.09295429e-13,  1.10290246e-13,  1.24074283e-13, ...,\n",
       "         1.74592944e-23,  4.46484911e-27,  8.22600488e-32],\n",
       "       ...,\n",
       "       [ 2.54567096e-13,  4.69520343e-13,  2.82401712e-13, ...,\n",
       "         1.23597090e-23,  2.82711256e-27,  4.41211777e-32],\n",
       "       [ 1.09295429e-13,  9.22336745e-14,  1.71571757e-13, ...,\n",
       "         2.04980858e-23,  4.28353341e-27,  8.66670778e-32],\n",
       "       [ 2.53347400e-14,  2.31357171e-14,  4.71942459e-14, ...,\n",
       "         2.07326609e-23,  5.18832880e-27,  9.93163056e-32]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>APEgen</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>6.336e-11</div><input id='attrs-f96893a5-da3c-455c-b19b-eb8f7f5b1f36' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f96893a5-da3c-455c-b19b-eb8f7f5b1f36' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f237bf0c-f45b-461b-be4d-1153b8693f19' class='xr-var-data-in' type='checkbox'><label for='data-f237bf0c-f45b-461b-be4d-1153b8693f19' 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>total available potential energy generation</dd><dt><span>units :</span></dt><dd>m^2 s^-3</dd></dl></div><div class='xr-var-data'><pre>array(6.33648561e-11)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-3aabcecf-0f0d-41df-ac27-73d27ae80367' class='xr-section-summary-in' type='checkbox'  ><label for='section-3aabcecf-0f0d-41df-ac27-73d27ae80367' class='xr-section-summary' >Attributes: <span>(23)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>pyqg:beta :</span></dt><dd>1.5e-11</dd><dt><span>pyqg:delta :</span></dt><dd>0.25</dd><dt><span>pyqg:del2 :</span></dt><dd>0.8</dd><dt><span>pyqg:dt :</span></dt><dd>7200.0</dd><dt><span>pyqg:filterfac :</span></dt><dd>23.6</dd><dt><span>pyqg:L :</span></dt><dd>1000000.0</dd><dt><span>pyqg:M :</span></dt><dd>4096</dd><dt><span>pyqg:nk :</span></dt><dd>33</dd><dt><span>pyqg:nl :</span></dt><dd>64</dd><dt><span>pyqg:ntd :</span></dt><dd>1</dd><dt><span>pyqg:nx :</span></dt><dd>64</dd><dt><span>pyqg:ny :</span></dt><dd>64</dd><dt><span>pyqg:nz :</span></dt><dd>2</dd><dt><span>pyqg:rd :</span></dt><dd>15000.0</dd><dt><span>pyqg:rek :</span></dt><dd>5.787e-07</dd><dt><span>pyqg:taveint :</span></dt><dd>86400.0</dd><dt><span>pyqg:tavestart :</span></dt><dd>155520000.0</dd><dt><span>pyqg:tc :</span></dt><dd>43200</dd><dt><span>pyqg:tmax :</span></dt><dd>311040000.0</dd><dt><span>pyqg:twrite :</span></dt><dd>10000</dd><dt><span>pyqg:W :</span></dt><dd>1000000.0</dd><dt><span>title :</span></dt><dd>pyqg: Python Quasigeostrophic Model</dd><dt><span>reference :</span></dt><dd>https://pyqg.readthedocs.io/en/latest/index.html</dd></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.Dataset>\n",
       "Dimensions:            (lev: 2, y: 64, x: 64, l: 64, k: 33, lev_mid: 1)\n",
       "Coordinates:\n",
       "    time               float64 3.11e+08\n",
       "  * lev                (lev) int64 1 2\n",
       "  * lev_mid            (lev_mid) float64 1.5\n",
       "  * x                  (x) float64 7.812e+03 2.344e+04 ... 9.766e+05 9.922e+05\n",
       "  * y                  (y) float64 7.812e+03 2.344e+04 ... 9.766e+05 9.922e+05\n",
       "  * l                  (l) float64 0.0 6.283e-06 ... -1.257e-05 -6.283e-06\n",
       "  * k                  (k) float64 0.0 6.283e-06 ... 0.0001948 0.0002011\n",
       "Data variables: (12/32)\n",
       "    q                  (lev, y, x) float64 -1.822e-06 -1.356e-06 ... -1.087e-06\n",
       "    u                  (lev, y, x) float64 -0.05977 -0.04566 ... -0.001317\n",
       "    v                  (lev, y, x) float64 0.04194 0.0462 ... 0.00118 0.009001\n",
       "    ufull              (lev, y, x) float64 -0.03477 -0.02066 ... -0.001317\n",
       "    vfull              (lev, y, x) float64 0.04194 0.0462 ... 0.00118 0.009001\n",
       "    qh                 (lev, l, k) complex128 (0.002324483338567505+0j) ... (...\n",
       "    ...                 ...\n",
       "    ENSgenspec         (l, k) float64 0.0 -3.458e-24 ... 7.51e-52 -3.186e-61\n",
       "    ENSfrictionspec    (l, k) float64 0.0 -7.479e-24 ... -2.395e-50 -7.94e-60\n",
       "    APEgenspec         (l, k) float64 0.0 -7.781e-16 ... 1.69e-43 -7.168e-53\n",
       "    APEflux            (l, k) float64 -0.0 -7.048e-16 ... 1.097e-28 2.951e-33\n",
       "    KEflux             (l, k) float64 0.0 -4.226e-15 ... 5.188e-27 9.932e-32\n",
       "    APEgen             float64 6.336e-11\n",
       "Attributes: (12/23)\n",
       "    pyqg:beta:       1.5e-11\n",
       "    pyqg:delta:      0.25\n",
       "    pyqg:del2:       0.8\n",
       "    pyqg:dt:         7200.0\n",
       "    pyqg:filterfac:  23.6\n",
       "    pyqg:L:          1000000.0\n",
       "    ...              ...\n",
       "    pyqg:tc:         43200\n",
       "    pyqg:tmax:       311040000.0\n",
       "    pyqg:twrite:     10000\n",
       "    pyqg:W:          1000000.0\n",
       "    title:           pyqg: Python Quasigeostrophic Model\n",
       "    reference:       https://pyqg.readthedocs.io/en/latest/index.html"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "m_ds = m.to_dataset().isel(time=-1)\n",
    "m_ds"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Visualize Output ##\n",
    "\n",
    "Let's assign a new data variable, ``q_upper``, as the **upper layer PV anomaly**. We access the PV values in the Dataset as ``m_ds.q``, which has two levels and a corresponding background PV gradient, ``m_ds.Qy``."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "m_ds['q_upper'] = m_ds.q.isel(lev=0) + m_ds.Qy.isel(lev=0)*m_ds.y\n",
    "m_ds['q_upper'].attrs = {'long_name': 'upper layer PV anomaly'}\n",
    "m_ds.q_upper.plot.contourf(levels=18, cmap='RdBu_r');"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Plot Diagnostics ##\n",
    "\n",
    "The model automatically accumulates averages of certain diagnostics. We can \n",
    "find out what diagnostics are available by calling"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "NAME               | DESCRIPTION\n",
      "--------------------------------------------------------------------------------\n",
      "APEflux    | spectral flux of available potential energy           \n",
      "APEgen     | total available potential energy generation           \n",
      "APEgenspec | the spectrum of the rate of generation of available potential energy\n",
      "Dissspec   | Spectral contribution of filter dissipation to total energy\n",
      "EKE        | mean eddy kinetic energy                              \n",
      "EKEdiss    | total energy dissipation by bottom drag               \n",
      "ENSDissspec | Spectral contribution of filter dissipation to barotropic enstrophy\n",
      "ENSflux    | barotropic enstrophy flux                             \n",
      "ENSfrictionspec | the spectrum of the rate of dissipation of barotropic enstrophy due to bottom friction\n",
      "ENSgenspec | the spectrum of the rate of generation of barotropic enstrophy\n",
      "Ensspec    | enstrophy spectrum                                    \n",
      "KEflux     | spectral flux of kinetic energy                       \n",
      "KEfrictionspec | total energy dissipation spectrum by bottom drag      \n",
      "KEspec     | kinetic energy spectrum                               \n",
      "entspec    | barotropic enstrophy spectrum                         \n",
      "paramspec  | Spectral contribution of subgrid parameterization (if present)\n",
      "paramspec_APEflux | total additional APE flux due to subgrid parameterization\n",
      "paramspec_KEflux | total additional KE flux due to subgrid parameterization\n"
     ]
    }
   ],
   "source": [
    "m.describe_diagnostics()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "To look at the wavenumber energy spectrum, we plot the `KEspec` diagnostic.\n",
    "(Note that summing along the l-axis, as in this example, does not give us\n",
    "a true *isotropic* wavenumber spectrum.)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "kr, kespec_upper = tools.calc_ispec(m, m_ds.KEspec.isel(lev=0).data)\n",
    "_, kespec_lower = tools.calc_ispec(m, m_ds.KEspec.isel(lev=1).data)\n",
    "\n",
    "plt.loglog(kr, kespec_upper, 'b.-', label='upper layer')\n",
    "plt.loglog(kr, kespec_lower, 'g.-', label='lower layer')\n",
    "plt.legend(loc='lower left')\n",
    "plt.ylim([1e-14,1e-8])\n",
    "plt.xlabel(r'k (m$^{-1}$)'); plt.grid()\n",
    "plt.title('Kinetic Energy Spectrum');"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We can also plot the spectral fluxes of energy and enstrophy. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "kr, APEgenspec = tools.calc_ispec(m, m_ds.APEgenspec.data)\n",
    "_, APEflux     = tools.calc_ispec(m, m_ds.APEflux.data)\n",
    "_, KEflux      = tools.calc_ispec(m, m_ds.KEflux.data)\n",
    "_, KEfrictionspec = tools.calc_ispec(m, m_ds.KEfrictionspec.data)\n",
    "_, Dissspec    = tools.calc_ispec(m, m_ds.Dissspec.data)\n",
    "\n",
    "ebud = [ APEgenspec,\n",
    "         APEflux,\n",
    "         KEflux,\n",
    "         KEfrictionspec,\n",
    "         Dissspec]\n",
    "ebud.append(-np.vstack(ebud).sum(axis=0))\n",
    "ebud_labels = ['APE gen','APE flux','KE flux','Bottom drag','Diss.','Resid.']\n",
    "[plt.semilogx(kr, term) for term in ebud]\n",
    "plt.legend(ebud_labels, loc='upper right')\n",
    "plt.xlabel(r'k (m$^{-1}$)'); plt.grid()\n",
    "plt.title('Spectral Energy Transfer');"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "_, ENSflux    = tools.calc_ispec(m, m_ds.ENSflux.data.squeeze())\n",
    "_, ENSgenspec = tools.calc_ispec(m, m_ds.ENSgenspec.data.squeeze())\n",
    "_, ENSfrictionspec = tools.calc_ispec(m, m_ds.ENSfrictionspec.data.squeeze())\n",
    "_, ENSDissspec = tools.calc_ispec(m, m_ds.ENSDissspec.data.squeeze())\n",
    "\n",
    "ebud = [ ENSgenspec,\n",
    "         ENSflux,\n",
    "         ENSDissspec,\n",
    "         ENSfrictionspec]\n",
    "ebud.append(-np.vstack(ebud).sum(axis=0))\n",
    "ebud_labels = ['ENS gen','ENS flux div.','Dissipation','Friction','Resid.']\n",
    "[plt.semilogx(kr, term) for term in ebud]\n",
    "plt.legend(ebud_labels, loc='best')\n",
    "plt.xlabel(r'k (m$^{-1}$)'); plt.grid()\n",
    "plt.title('Spectral Enstrophy Transfer');"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.9.5"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}