process_output_4cases.ipynb

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    "import xarray as xr\n",
    "import cftime \n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "import re\n",
    "import os\n",
    "import time\n",
    "import logging\n",
    "import cartopy.crs as ccrs\n",
    "import metpy  # accessor needed to parse crs\n",
    "import calendar\n",
    "import argparse\n",
    "import seaborn as sns\n",
    "from shapely.geometry import Point\n",
    "import geopandas\n",
    "from geodatasets import get_path\n",
    "import glob\n",
    "\n",
    "import metpy.calc as mpcalc\n",
    "from metpy.units import units\n",
    "import xarray as xr\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "import xarray as xr\n",
    "import matplotlib.pyplot as plt\n",
    "from matplotlib.animation import FuncAnimation\n",
    "import numpy as np\n",
    "\n"
   ]
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       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt;\n",
       "Dimensions:   (time: 250)\n",
       "Coordinates:\n",
       "  * time      (time) float32 60.0 120.0 180.0 ... 1.488e+04 1.494e+04 1.5e+04\n",
       "Data variables: (12/33)\n",
       "    cfrac     (time) float32 nan nan nan nan nan nan ... nan nan nan nan nan nan\n",
       "    zb        (time) float32 nan nan nan nan nan nan ... nan nan nan nan nan nan\n",
       "    zc_av     (time) float32 nan nan nan nan nan nan ... nan nan nan nan nan nan\n",
       "    zc_max    (time) float32 nan nan nan nan nan nan ... nan nan nan nan nan nan\n",
       "    zi        (time) float32 0.0 0.0 0.0 0.0 0.0 ... 67.27 69.41 50.27 56.42\n",
       "    we        (time) float32 0.0 0.0 0.0 0.0 ... 0.1124 0.03568 -0.3189 0.1024\n",
       "    ...        ...\n",
       "    rs        (time) float32 -4.078e-15 -4.928e-15 -5.388e-15 ... 116.2 116.1\n",
       "    ra        (time) float32 53.24 63.66 70.16 74.79 ... 89.15 88.88 88.73 88.56\n",
       "    cliq      (time) float32 0.001953 0.004173 0.006289 ... 0.00559 0.005451\n",
       "    Wl        (time) float32 7.836e-07 1.671e-06 ... 2.236e-06 2.18e-06\n",
       "    rssoil    (time) float32 0.0 0.0 0.0 0.0 0.0 ... 99.04 99.08 99.12 99.15\n",
       "    rsveg     (time) float32 0.0 0.0 0.0 0.0 0.0 ... 120.3 119.8 119.8 119.7\n",
       "Attributes:\n",
       "    title:    tmser.001.nc\n",
       "    history:  Created on 20230610 at 150901.905\n",
       "    Source:   DALES 4.4 git: v4.4\n",
       "    Author:   </pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-e82e121f-743c-4e88-8ff1-edc2aa7ef850' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-e82e121f-743c-4e88-8ff1-edc2aa7ef850' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>time</span>: 250</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-874f2cc9-b5d9-45db-9fe7-15b7d3ab0b9d' class='xr-section-summary-in' type='checkbox'  checked><label for='section-874f2cc9-b5d9-45db-9fe7-15b7d3ab0b9d' class='xr-section-summary' >Coordinates: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>60.0 120.0 ... 1.494e+04 1.5e+04</div><input id='attrs-10caeaaa-9818-4b42-9223-5e518c1c5e92' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-10caeaaa-9818-4b42-9223-5e518c1c5e92' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f4e1a966-3be4-46e3-aa73-9783a68fa1a4' class='xr-var-data-in' type='checkbox'><label for='data-f4e1a966-3be4-46e3-aa73-9783a68fa1a4' 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>longname :</span></dt><dd>Time</dd><dt><span>units :</span></dt><dd>s</dd></dl></div><div class='xr-var-data'><pre>array([   60.,   120.,   180., ..., 14880., 14940., 15000.], dtype=float32)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-45dea817-1c34-473e-ab20-f7d11d04ffa4' class='xr-section-summary-in' type='checkbox'  ><label for='section-45dea817-1c34-473e-ab20-f7d11d04ffa4' class='xr-section-summary' >Data variables: <span>(33)</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>cfrac</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-7d4b6bc0-334e-4da4-a988-ef854058574a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-7d4b6bc0-334e-4da4-a988-ef854058574a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9fe4858c-d1b6-4ef0-b62a-d8e9264ebf38' class='xr-var-data-in' type='checkbox'><label for='data-9fe4858c-d1b6-4ef0-b62a-d8e9264ebf38' 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>longname :</span></dt><dd>Cloud fraction</dd><dt><span>units :</span></dt><dd>-</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>zb</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-28e81201-d1b1-4179-8b7b-c94df46563cc' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-28e81201-d1b1-4179-8b7b-c94df46563cc' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d6f6ebe0-34f4-4f19-89b4-db53a1b5ed06' class='xr-var-data-in' type='checkbox'><label for='data-d6f6ebe0-34f4-4f19-89b4-db53a1b5ed06' 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>longname :</span></dt><dd>Cloud-base height</dd><dt><span>units :</span></dt><dd>m</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>zc_av</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-c36885ed-ddeb-4618-be82-5d7384bc862a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-c36885ed-ddeb-4618-be82-5d7384bc862a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-28ecc86a-3346-43de-a56f-67b311461d21' class='xr-var-data-in' type='checkbox'><label for='data-28ecc86a-3346-43de-a56f-67b311461d21' 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>longname :</span></dt><dd>Average Cloud-top height</dd><dt><span>units :</span></dt><dd>m</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>zc_max</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-3c9a1d82-097f-4eeb-b0d8-2e0d69b0fb1b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3c9a1d82-097f-4eeb-b0d8-2e0d69b0fb1b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0ad42ec8-b3ba-4bfe-9b1b-d941880f1d92' class='xr-var-data-in' type='checkbox'><label for='data-0ad42ec8-b3ba-4bfe-9b1b-d941880f1d92' 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>longname :</span></dt><dd>Maximum Cloud-top height</dd><dt><span>units :</span></dt><dd>m</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, ..., nan, nan, nan], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>zi</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-a8d7dcd4-a447-4a3b-b51b-5943d82214cb' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a8d7dcd4-a447-4a3b-b51b-5943d82214cb' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5869147f-57cf-4751-aa19-106c7e1278fe' class='xr-var-data-in' type='checkbox'><label for='data-5869147f-57cf-4751-aa19-106c7e1278fe' 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>longname :</span></dt><dd>Boundary layer height</dd><dt><span>units :</span></dt><dd>m</dd></dl></div><div class='xr-var-data'><pre>array([ 0.      ,  0.      ,  0.      , ..., 69.409325, 50.273457, 56.418705],\n",
       "      dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>we</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-506333f8-5cce-430c-b1a7-41797874bc80' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-506333f8-5cce-430c-b1a7-41797874bc80' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c2f1e03e-d022-4b65-8921-76ce3c3c0721' class='xr-var-data-in' type='checkbox'><label for='data-c2f1e03e-d022-4b65-8921-76ce3c3c0721' 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>longname :</span></dt><dd>Entrainment velocity</dd><dt><span>units :</span></dt><dd>m/s</dd></dl></div><div class='xr-var-data'><pre>array([ 0.      ,  0.      ,  0.      , ...,  0.035682, -0.318931,  0.102421],\n",
       "      dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lwp_bar</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-1bb54591-3f92-464d-9b93-ec737fcb0b0f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-1bb54591-3f92-464d-9b93-ec737fcb0b0f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-936a49c8-10cc-40e9-82fe-33aed70d0487' class='xr-var-data-in' type='checkbox'><label for='data-936a49c8-10cc-40e9-82fe-33aed70d0487' 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>longname :</span></dt><dd>Liquid-water path</dd><dt><span>units :</span></dt><dd>kg/m^2</dd></dl></div><div class='xr-var-data'><pre>array([0., 0., 0., ..., 0., 0., 0.], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lwp_max</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-e04a9116-4da9-4f84-b9eb-a2f2be248f4e' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e04a9116-4da9-4f84-b9eb-a2f2be248f4e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-576a2db4-306d-4315-94c5-ab853e8c9706' class='xr-var-data-in' type='checkbox'><label for='data-576a2db4-306d-4315-94c5-ab853e8c9706' 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>longname :</span></dt><dd>Maximum Liquid-water path</dd><dt><span>units :</span></dt><dd>kg/m^2</dd></dl></div><div class='xr-var-data'><pre>array([0., 0., 0., ..., 0., 0., 0.], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>wmax</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-386aa24d-491d-4bf4-9bc4-5e8ee2c41e4e' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-386aa24d-491d-4bf4-9bc4-5e8ee2c41e4e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7b1c51a0-ead9-40d5-8edf-4a02ca3ddf13' class='xr-var-data-in' type='checkbox'><label for='data-7b1c51a0-ead9-40d5-8edf-4a02ca3ddf13' 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>longname :</span></dt><dd>Maximum vertical velocity</dd><dt><span>units :</span></dt><dd>m/s</dd></dl></div><div class='xr-var-data'><pre>array([0.022053, 0.020673, 0.016922, ..., 2.738279, 2.685218, 2.597439],\n",
       "      dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>vtke</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-9b695638-e1cf-45e6-8e96-611150677d38' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-9b695638-e1cf-45e6-8e96-611150677d38' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f0b4d15d-9e85-47d0-85c0-c469a9ae641c' class='xr-var-data-in' type='checkbox'><label for='data-f0b4d15d-9e85-47d0-85c0-c469a9ae641c' 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>longname :</span></dt><dd>Vertical integral of total TKE</dd><dt><span>units :</span></dt><dd>kg/s</dd></dl></div><div class='xr-var-data'><pre>array([ 7.177012,  3.378411,  2.737716, ..., 95.713875, 94.67615 , 93.45589 ],\n",
       "      dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lmax</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-4e050128-2461-4668-bbde-500c655364c2' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-4e050128-2461-4668-bbde-500c655364c2' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-21584abc-77d4-47ce-869a-4c3273e8ee47' class='xr-var-data-in' type='checkbox'><label for='data-21584abc-77d4-47ce-869a-4c3273e8ee47' 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>longname :</span></dt><dd>Maximum liquid water specific humidity</dd><dt><span>units :</span></dt><dd>kg/kg</dd></dl></div><div class='xr-var-data'><pre>array([0., 0., 0., ..., 0., 0., 0.], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>ustar</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-63f4d14b-f682-4416-8ae9-90e5413302db' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-63f4d14b-f682-4416-8ae9-90e5413302db' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f1210615-5f34-4a12-ad33-11766ddcf49b' class='xr-var-data-in' type='checkbox'><label for='data-f1210615-5f34-4a12-ad33-11766ddcf49b' 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>longname :</span></dt><dd>Surface friction velocity</dd><dt><span>units :</span></dt><dd>m/s</dd></dl></div><div class='xr-var-data'><pre>array([0.346927, 0.291946, 0.266101, ..., 0.159469, 0.159868, 0.16026 ],\n",
       "      dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>tstr</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-7287118a-bdb3-4cbe-aee7-b17ae655797a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-7287118a-bdb3-4cbe-aee7-b17ae655797a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-23362cf2-109d-432d-98b5-a6fe2a48535c' class='xr-var-data-in' type='checkbox'><label for='data-23362cf2-109d-432d-98b5-a6fe2a48535c' 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>longname :</span></dt><dd>Turbulent temperature scale</dd><dt><span>units :</span></dt><dd>K</dd></dl></div><div class='xr-var-data'><pre>array([ 0.057223,  0.066411,  0.071216, ..., -0.641932, -0.641173, -0.641378],\n",
       "      dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>qtstr</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-c27259e5-78c7-44c6-a1db-9ef55459c810' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-c27259e5-78c7-44c6-a1db-9ef55459c810' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e2ab138d-c489-4023-852e-4a88c5197c6a' class='xr-var-data-in' type='checkbox'><label for='data-e2ab138d-c489-4023-852e-4a88c5197c6a' 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>longname :</span></dt><dd>Turbulent humidity scale</dd><dt><span>units :</span></dt><dd>K</dd></dl></div><div class='xr-var-data'><pre>array([ 3.671666e-05,  4.112571e-05,  4.318295e-05, ..., -4.259372e-04,\n",
       "       -4.256587e-04, -4.258993e-04], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>obukh</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-8b870ba9-aed8-40d9-9dc0-f660f9eda12e' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-8b870ba9-aed8-40d9-9dc0-f660f9eda12e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d5659104-99a7-4b39-86fc-97016a1b13a0' class='xr-var-data-in' type='checkbox'><label for='data-d5659104-99a7-4b39-86fc-97016a1b13a0' 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>longname :</span></dt><dd>Obukhov Length</dd><dt><span>units :</span></dt><dd>m</dd></dl></div><div class='xr-var-data'><pre>array([138.04855 ,  84.412964,  65.47966 , ...,  -2.734139,  -2.750987,\n",
       "        -2.763988], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>thlskin</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-8160a7ee-ea3f-42e8-ad60-803b0a0f3dd3' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-8160a7ee-ea3f-42e8-ad60-803b0a0f3dd3' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2a77a507-6a57-400a-ace7-944ecf96a572' class='xr-var-data-in' type='checkbox'><label for='data-2a77a507-6a57-400a-ace7-944ecf96a572' 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>longname :</span></dt><dd>Surface liquid water potential temperature</dd><dt><span>units :</span></dt><dd>K</dd></dl></div><div class='xr-var-data'><pre>array([286.12796, 285.7876 , 285.5728 , ..., 302.5354 , 302.5438 , 302.5893 ],\n",
       "      dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>z0</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-f3cc6517-fc76-4e9e-b391-8e5934867153' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f3cc6517-fc76-4e9e-b391-8e5934867153' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d9594301-cec1-4041-8164-49e9af5755ed' class='xr-var-data-in' type='checkbox'><label for='data-d9594301-cec1-4041-8164-49e9af5755ed' 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>longname :</span></dt><dd>Roughness height</dd><dt><span>units :</span></dt><dd>m</dd></dl></div><div class='xr-var-data'><pre>array([0.01, 0.01, 0.01, ..., 0.01, 0.01, 0.01], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>wtheta</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-ad64c572-924b-4a02-b783-75dc3851635d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ad64c572-924b-4a02-b783-75dc3851635d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a8df9fc9-9f38-44dd-b06e-c083f973cf93' class='xr-var-data-in' type='checkbox'><label for='data-a8df9fc9-9f38-44dd-b06e-c083f973cf93' 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>longname :</span></dt><dd>Surface kinematic temperature flux</dd><dt><span>units :</span></dt><dd>K m/s</dd></dl></div><div class='xr-var-data'><pre>array([-0.019852, -0.019388, -0.018951, ...,  0.102368,  0.102503,  0.102787],\n",
       "      dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>wthetav</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-65fca2f6-e551-4d63-aa78-7c87acc8d62f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-65fca2f6-e551-4d63-aa78-7c87acc8d62f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-842d67a2-ce38-43c2-bbfe-2e2faf611717' class='xr-var-data-in' type='checkbox'><label for='data-842d67a2-ce38-43c2-bbfe-2e2faf611717' 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>longname :</span></dt><dd>Surface kinematic virtual temperature flux</dd><dt><span>units :</span></dt><dd>K m/s</dd></dl></div><div class='xr-var-data'><pre>array([-0.022179, -0.021581, -0.021048, ...,  0.115964,  0.116124,  0.116453],\n",
       "      dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>wq</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-009cb55a-07ed-4b34-a860-218a5aa30bab' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-009cb55a-07ed-4b34-a860-218a5aa30bab' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5cd2937b-5bc4-43cb-8c20-bb6d4a147abb' class='xr-var-data-in' type='checkbox'><label for='data-5cd2937b-5bc4-43cb-8c20-bb6d4a147abb' 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>longname :</span></dt><dd>Surface kinematic moisture flux</dd><dt><span>units :</span></dt><dd>kg/kg m/s</dd></dl></div><div class='xr-var-data'><pre>array([-1.273800e-05, -1.200650e-05, -1.149102e-05, ...,  6.792381e-05,\n",
       "        6.804922e-05,  6.825479e-05], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>twp_bar</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-d7289e54-6831-4da8-b5a2-78e9ff0c6980' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d7289e54-6831-4da8-b5a2-78e9ff0c6980' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4dd0af30-d695-4df9-a8e5-13240e723ef5' class='xr-var-data-in' type='checkbox'><label for='data-4dd0af30-d695-4df9-a8e5-13240e723ef5' 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>longname :</span></dt><dd>Total water path</dd><dt><span>units :</span></dt><dd>kg/m^2</dd></dl></div><div class='xr-var-data'><pre>array([3.03254 , 3.031674, 3.030852, ..., 3.392494, 3.396984, 3.401509],\n",
       "      dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>rwp_bar</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-9601c8dc-f4a6-46d6-abaa-e76646f91569' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-9601c8dc-f4a6-46d6-abaa-e76646f91569' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d8895ac8-2830-4fc5-bf4f-6bd3a5704369' class='xr-var-data-in' type='checkbox'><label for='data-d8895ac8-2830-4fc5-bf4f-6bd3a5704369' 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>longname :</span></dt><dd>Rain water path</dd><dt><span>units :</span></dt><dd>kg/m^2</dd></dl></div><div class='xr-var-data'><pre>array([1428.8915 , 1392.8132 , 1360.6578 , ...,  215.64893,  218.74994,\n",
       "        220.78128], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Qnet</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-32c5e372-9bb5-4c8a-98c7-8472688c42e7' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-32c5e372-9bb5-4c8a-98c7-8472688c42e7' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-dc65882a-a60c-4f21-ad13-de5c10b5dd53' class='xr-var-data-in' type='checkbox'><label for='data-dc65882a-a60c-4f21-ad13-de5c10b5dd53' 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>longname :</span></dt><dd>Net radiation</dd><dt><span>units :</span></dt><dd>W/m^2</dd></dl></div><div class='xr-var-data'><pre>array([-67.48574 , -66.884834, -66.1477  , ..., 399.1959  , 399.62485 ,\n",
       "       400.66266 ], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>H</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-8a9d0069-aa75-4985-bef9-008ee321e4d4' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-8a9d0069-aa75-4985-bef9-008ee321e4d4' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-74aa8a63-caf5-4e11-bfc8-32ebe7356fc5' class='xr-var-data-in' type='checkbox'><label for='data-74aa8a63-caf5-4e11-bfc8-32ebe7356fc5' 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>longname :</span></dt><dd>Sensible heat flux</dd><dt><span>units :</span></dt><dd>W/m^2</dd></dl></div><div class='xr-var-data'><pre>array([-23.587427, -23.113144, -22.627838, ..., 121.39699 , 121.551346,\n",
       "       121.87099 ], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>LE</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-087b5395-9df9-49a9-9da1-7d5c5c49300a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-087b5395-9df9-49a9-9da1-7d5c5c49300a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2d66f2cd-52d6-4698-9174-8ac921f13fef' class='xr-var-data-in' type='checkbox'><label for='data-2d66f2cd-52d6-4698-9174-8ac921f13fef' 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>longname :</span></dt><dd>Latent heat flux</dd><dt><span>units :</span></dt><dd>W/m^2</dd></dl></div><div class='xr-var-data'><pre>array([-38.654953, -36.483246, -34.943596, ..., 202.62144 , 202.98668 ,\n",
       "       203.57368 ], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>G0</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-554b16dd-6be5-4323-b417-793861740cfc' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-554b16dd-6be5-4323-b417-793861740cfc' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-50fbf551-9731-4214-bb1a-25fdf95d4ba3' class='xr-var-data-in' type='checkbox'><label for='data-50fbf551-9731-4214-bb1a-25fdf95d4ba3' 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>longname :</span></dt><dd>Ground heat flux</dd><dt><span>units :</span></dt><dd>W/m^2</dd></dl></div><div class='xr-var-data'><pre>array([-5.243363, -7.288444, -8.576266, ..., 75.17745 , 75.086815, 75.217995],\n",
       "      dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>tendskin</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-945ea9e1-d8bc-4527-a1d3-61caceb2ae98' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-945ea9e1-d8bc-4527-a1d3-61caceb2ae98' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-08efab30-92bf-4222-add3-21b6f775d048' class='xr-var-data-in' type='checkbox'><label for='data-08efab30-92bf-4222-add3-21b6f775d048' 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>longname :</span></dt><dd>Skin tendency</dd><dt><span>units :</span></dt><dd>W/m^2</dd></dl></div><div class='xr-var-data'><pre>array([0., 0., 0., ..., 0., 0., 0.], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>rs</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-2db7cd84-a881-4106-b586-c25b71f01abc' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-2db7cd84-a881-4106-b586-c25b71f01abc' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f1f862f8-4db1-4928-a300-0e0b48ff223e' class='xr-var-data-in' type='checkbox'><label for='data-f1f862f8-4db1-4928-a300-0e0b48ff223e' 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>longname :</span></dt><dd>Surface resistance</dd><dt><span>units :</span></dt><dd>s/m</dd></dl></div><div class='xr-var-data'><pre>array([-4.078335e-15, -4.928349e-15, -5.388051e-15, ...,  1.160793e+02,\n",
       "        1.161608e+02,  1.160883e+02], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>ra</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-003d6c05-6b89-4bec-8958-346c83eb4e70' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-003d6c05-6b89-4bec-8958-346c83eb4e70' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-09baafee-e5ed-435e-9a69-46f7f5d61627' class='xr-var-data-in' type='checkbox'><label for='data-09baafee-e5ed-435e-9a69-46f7f5d61627' 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>longname :</span></dt><dd>Aerodynamic resistance</dd><dt><span>units :</span></dt><dd>s/m</dd></dl></div><div class='xr-var-data'><pre>array([53.238724, 63.656776, 70.1589  , ..., 88.87916 , 88.72605 , 88.56137 ],\n",
       "      dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>cliq</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-96477280-da7d-4eac-9e84-3694c491f259' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-96477280-da7d-4eac-9e84-3694c491f259' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ca192ffb-66fe-403e-8645-a82f01ad5b39' class='xr-var-data-in' type='checkbox'><label for='data-ca192ffb-66fe-403e-8645-a82f01ad5b39' 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>longname :</span></dt><dd>Fraction of vegetated surface covered with liquid water</dd><dt><span>units :</span></dt><dd>-</dd></dl></div><div class='xr-var-data'><pre>array([0.001953, 0.004173, 0.006289, ..., 0.005731, 0.00559 , 0.005451],\n",
       "      dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Wl</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-ab0da09b-b325-4105-bcec-6fc742105dce' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ab0da09b-b325-4105-bcec-6fc742105dce' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2c615f15-7de3-4459-92e1-35b2f7c3cc9e' class='xr-var-data-in' type='checkbox'><label for='data-2c615f15-7de3-4459-92e1-35b2f7c3cc9e' 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>longname :</span></dt><dd>Liquid water reservoir</dd><dt><span>units :</span></dt><dd>m</dd></dl></div><div class='xr-var-data'><pre>array([7.835611e-07, 1.670590e-06, 2.516847e-06, ..., 2.291913e-06,\n",
       "       2.235508e-06, 2.180021e-06], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>rssoil</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-a6d4a7b9-9865-4e7a-aa57-61082bcd4c6f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a6d4a7b9-9865-4e7a-aa57-61082bcd4c6f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-42d716e9-55d9-4a19-abf8-c04a28b23bc7' class='xr-var-data-in' type='checkbox'><label for='data-42d716e9-55d9-4a19-abf8-c04a28b23bc7' 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>longname :</span></dt><dd>Soil evaporation resistance</dd><dt><span>units :</span></dt><dd>s/m</dd></dl></div><div class='xr-var-data'><pre>array([ 0.      ,  0.      ,  0.      , ..., 99.078705, 99.11542 , 99.15251 ],\n",
       "      dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>rsveg</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-1ce88198-fc51-44d4-8231-3df61a2685d5' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-1ce88198-fc51-44d4-8231-3df61a2685d5' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0f2d23a0-625c-470a-a0b3-cb20b132d13d' class='xr-var-data-in' type='checkbox'><label for='data-0f2d23a0-625c-470a-a0b3-cb20b132d13d' 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>longname :</span></dt><dd>Vegitation resistance</dd><dt><span>units :</span></dt><dd>s/m</dd></dl></div><div class='xr-var-data'><pre>array([  0.      ,   0.      ,   0.      , ..., 119.777214, 119.828995,\n",
       "       119.7012  ], dtype=float32)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-d0a28c9d-91f3-479a-8885-b78f8085b878' class='xr-section-summary-in' type='checkbox'  checked><label for='section-d0a28c9d-91f3-479a-8885-b78f8085b878' class='xr-section-summary' >Attributes: <span>(4)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>title :</span></dt><dd>tmser.001.nc</dd><dt><span>history :</span></dt><dd>Created on 20230610 at 150901.905</dd><dt><span>Source :</span></dt><dd>DALES 4.4 git: v4.4</dd><dt><span>Author :</span></dt><dd></dd></dl></div></li></ul></div></div>"
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       "    zc_av     (time) float32 ...\n",
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       "    ...        ...\n",
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       "    title:    tmser.001.nc\n",
       "    history:  Created on 20230610 at 150901.905\n",
       "    Source:   DALES 4.4 git: v4.4\n",
       "    Author:   "
      ]
     },
     "execution_count": 120,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "path = '~/dales/build/stable_runs/high_shear_output'\n",
    "# case = 'stable_low_shear'\n",
    "# path = '/home/smmrrr/dales/build/case4'\n",
    "# case = 'case4'\n",
    "# cross=xr.open_dataset(path+case+'/crossxz.x000y000.001.nc')\n",
    "\n",
    "profile = xr.open_dataset(path +'/profiles.001.nc')\n",
    "tmser = xr.open_dataset(path +'/tmser.001.nc')\n",
    "\n",
    "tmser"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "id": "9d6a373d-a056-4dca-bb04-6e740deaff48",
   "metadata": {},
   "outputs": [
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       "    title:    tmser.001.nc\n",
       "    history:  Created on 20230610 at 131956.291\n",
       "    Source:   DALES 4.4 git: v4.4\n",
       "    Author:   </pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-b27bbd3b-8b67-410c-a0e2-f87e6e4e878e' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-b27bbd3b-8b67-410c-a0e2-f87e6e4e878e' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>time</span>: 60</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-ca4df1d4-07b0-4386-9ae9-a584317cd64e' class='xr-section-summary-in' type='checkbox'  checked><label for='section-ca4df1d4-07b0-4386-9ae9-a584317cd64e' class='xr-section-summary' >Coordinates: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>60.0 120.0 ... 3.54e+03 3.6e+03</div><input id='attrs-4d3adc01-13ec-43c3-86b0-1d5069d0d9e4' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-4d3adc01-13ec-43c3-86b0-1d5069d0d9e4' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9c59964b-1454-470d-9916-7c071a8797f3' class='xr-var-data-in' type='checkbox'><label for='data-9c59964b-1454-470d-9916-7c071a8797f3' 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>longname :</span></dt><dd>Time</dd><dt><span>units :</span></dt><dd>s</dd></dl></div><div class='xr-var-data'><pre>array([  60.,  120.,  180.,  240.,  300.,  360.,  420.,  480.,  540.,  600.,\n",
       "        660.,  720.,  780.,  840.,  900.,  960., 1020., 1080., 1140., 1200.,\n",
       "       1260., 1320., 1380., 1440., 1500., 1560., 1620., 1680., 1740., 1800.,\n",
       "       1860., 1920., 1980., 2040., 2100., 2160., 2220., 2280., 2340., 2400.,\n",
       "       2460., 2520., 2580., 2640., 2700., 2760., 2820., 2880., 2940., 3000.,\n",
       "       3060., 3120., 3180., 3240., 3300., 3360., 3420., 3480., 3540., 3600.],\n",
       "      dtype=float32)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-8d2e7231-e4d7-4deb-ad5d-1c04410425d1' class='xr-section-summary-in' type='checkbox'  ><label for='section-8d2e7231-e4d7-4deb-ad5d-1c04410425d1' class='xr-section-summary' >Data variables: <span>(33)</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>cfrac</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-cd945cec-09f0-4ef1-8f40-c15a88e80ba4' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-cd945cec-09f0-4ef1-8f40-c15a88e80ba4' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-36d1c4d6-a54a-4181-b6c0-8dc5c2b146ab' class='xr-var-data-in' type='checkbox'><label for='data-36d1c4d6-a54a-4181-b6c0-8dc5c2b146ab' 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>longname :</span></dt><dd>Cloud fraction</dd><dt><span>units :</span></dt><dd>-</dd></dl></div><div class='xr-var-data'><pre>array([3.076172e-02, 2.929688e-03, 4.882812e-04,          nan,          nan,\n",
       "                nan,          nan,          nan,          nan,          nan,\n",
       "                nan,          nan,          nan,          nan,          nan,\n",
       "                nan, 2.441406e-04, 1.464844e-03, 3.417969e-03, 4.150391e-03,\n",
       "       5.859375e-03, 1.147461e-02, 2.172852e-02, 4.492188e-02, 1.013184e-01,\n",
       "       1.809082e-01, 2.766113e-01, 4.216309e-01, 5.727539e-01, 7.368164e-01,\n",
       "       8.698730e-01, 9.570312e-01, 9.870605e-01, 9.995117e-01, 1.000000e+00,\n",
       "       1.000000e+00, 1.000000e+00, 1.000000e+00, 1.000000e+00, 1.000000e+00,\n",
       "       1.000000e+00, 1.000000e+00, 1.000000e+00, 1.000000e+00, 1.000000e+00,\n",
       "       1.000000e+00, 1.000000e+00, 1.000000e+00, 1.000000e+00, 1.000000e+00,\n",
       "       1.000000e+00, 1.000000e+00, 1.000000e+00, 1.000000e+00, 1.000000e+00,\n",
       "       1.000000e+00, 1.000000e+00, 1.000000e+00, 1.000000e+00, 1.000000e+00],\n",
       "      dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>zb</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-0b59879b-3b6b-4fba-8243-30bd29ce0c96' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-0b59879b-3b6b-4fba-8243-30bd29ce0c96' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-17e0c770-01d9-4374-b231-90078f247c60' class='xr-var-data-in' type='checkbox'><label for='data-17e0c770-01d9-4374-b231-90078f247c60' 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>longname :</span></dt><dd>Cloud-base height</dd><dt><span>units :</span></dt><dd>m</dd></dl></div><div class='xr-var-data'><pre>array([ 2.,  2.,  2., nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan,\n",
       "       nan, nan,  2.,  2.,  2.,  2.,  2.,  2.,  2.,  2.,  2.,  2.,  2.,  2.,\n",
       "        2.,  2.,  2.,  2.,  2.,  2.,  2.,  2.,  2.,  2.,  2.,  2.,  2.,  2.,\n",
       "        2.,  2.,  2.,  2.,  2.,  2.,  2.,  2.,  2.,  2.,  2.,  2.,  2.,  2.,\n",
       "        2.,  2.,  2.,  2.], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>zc_av</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-775d1d5f-1be3-4122-843c-68031a8c5541' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-775d1d5f-1be3-4122-843c-68031a8c5541' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1c04cddc-7039-4930-a3ea-55742c3c339c' class='xr-var-data-in' type='checkbox'><label for='data-1c04cddc-7039-4930-a3ea-55742c3c339c' 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>longname :</span></dt><dd>Average Cloud-top height</dd><dt><span>units :</span></dt><dd>m</dd></dl></div><div class='xr-var-data'><pre>array([2.      , 2.      , 2.      ,      nan,      nan,      nan,      nan,\n",
       "            nan,      nan,      nan,      nan,      nan,      nan,      nan,\n",
       "            nan,      nan, 2.      , 2.      , 2.      , 2.      , 2.      ,\n",
       "       2.      , 2.      , 2.      , 2.      , 2.      , 2.      , 2.      ,\n",
       "       2.      , 2.      , 2.      , 2.      , 2.      , 2.      , 2.082031,\n",
       "       2.550781, 2.644531, 2.757812, 2.861328, 3.005859, 3.244141, 3.655273,\n",
       "       4.025391, 4.504883, 5.014648, 5.445312, 5.766602, 5.90625 , 5.975586,\n",
       "       5.999023, 6.      , 6.001953, 6.02832 , 6.067383, 6.084961, 6.228516,\n",
       "       6.518555, 7.100586, 7.728516, 8.519531], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>zc_max</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-f4e70212-41c0-408d-9c11-f85a12bad516' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f4e70212-41c0-408d-9c11-f85a12bad516' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-bc4219c2-f36a-4d86-9754-0bbb020c56a8' class='xr-var-data-in' type='checkbox'><label for='data-bc4219c2-f36a-4d86-9754-0bbb020c56a8' 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>longname :</span></dt><dd>Maximum Cloud-top height</dd><dt><span>units :</span></dt><dd>m</dd></dl></div><div class='xr-var-data'><pre>array([ 2.,  2.,  2., nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan,\n",
       "       nan, nan,  2.,  2.,  2.,  2.,  2.,  2.,  2.,  2.,  2.,  2.,  2.,  2.,\n",
       "        2.,  2.,  2.,  2.,  2.,  2.,  6.,  6.,  6.,  6.,  6., 10.,  6.,  6.,\n",
       "        6.,  6.,  6., 10.,  6., 10., 10.,  6., 10., 10., 10., 10., 10., 10.,\n",
       "       10., 14., 14., 14.], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>zi</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-c7093f98-e3b9-42a1-b6ef-5b80a3d8d884' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-c7093f98-e3b9-42a1-b6ef-5b80a3d8d884' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2a52c0d7-fc9c-4862-b4e8-a05f3ee1a7b9' class='xr-var-data-in' type='checkbox'><label for='data-2a52c0d7-fc9c-4862-b4e8-a05f3ee1a7b9' 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>longname :</span></dt><dd>Boundary layer height</dd><dt><span>units :</span></dt><dd>m</dd></dl></div><div class='xr-var-data'><pre>array([ 29.70034 ,  34.400875, 121.70446 , 233.89204 , 244.9354  , 244.96472 ,\n",
       "       244.98642 , 245.00241 , 245.01308 , 245.02193 , 245.02994 , 245.03558 ,\n",
       "       245.04102 , 245.04538 , 245.04858 , 245.04776 , 245.04549 , 245.03828 ,\n",
       "       245.02457 , 245.014   , 245.0117  , 245.01703 , 245.0239  , 245.02826 ,\n",
       "       245.03261 , 245.03683 , 245.03986 , 245.04399 , 245.04753 , 245.04964 ,\n",
       "       245.05322 , 239.31227 , 151.9691  ,  28.719316,   0.      ,   0.      ,\n",
       "         0.      ,   0.      ,   0.      ,   0.      ,   0.      ,   0.      ,\n",
       "         0.      ,   0.      ,   0.      ,   0.      ,   0.      ,   0.      ,\n",
       "         0.      ,   0.      ,   0.      ,   0.      ,   0.      ,   0.      ,\n",
       "         0.      ,   0.      ,   0.      ,   0.      ,   0.      ,   0.      ],\n",
       "      dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>we</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-f2bb5a66-b65c-45e1-b90d-f54145f6b2f5' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f2bb5a66-b65c-45e1-b90d-f54145f6b2f5' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ceb5d435-24f0-4a8d-b7ae-ce8792ef0a00' class='xr-var-data-in' type='checkbox'><label for='data-ceb5d435-24f0-4a8d-b7ae-ce8792ef0a00' 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>longname :</span></dt><dd>Entrainment velocity</dd><dt><span>units :</span></dt><dd>m/s</dd></dl></div><div class='xr-var-data'><pre>array([ 0.000000e+00,  7.834225e-02,  1.455060e+00,  1.869793e+00,\n",
       "        1.840558e-01,  4.889644e-04,  3.616054e-04,  2.664200e-04,\n",
       "        1.778031e-04,  1.475179e-04,  1.333852e-04,  9.431364e-05,\n",
       "        9.039735e-05,  7.280070e-05,  5.336151e-05, -1.369919e-05,\n",
       "       -3.793517e-05, -1.201086e-04, -2.285604e-04, -1.758850e-04,\n",
       "       -3.852702e-05,  8.879053e-05,  1.145066e-04,  7.267743e-05,\n",
       "        7.243601e-05,  7.050021e-05,  5.037964e-05,  6.894715e-05,\n",
       "        5.891694e-05,  3.502539e-05,  5.988506e-05, -9.568264e-02,\n",
       "       -1.455719e+00, -2.054163e+00, -4.786552e-01,  0.000000e+00,\n",
       "        0.000000e+00,  0.000000e+00,  0.000000e+00,  0.000000e+00,\n",
       "        0.000000e+00,  0.000000e+00,  0.000000e+00,  0.000000e+00,\n",
       "        0.000000e+00,  0.000000e+00,  0.000000e+00,  0.000000e+00,\n",
       "        0.000000e+00,  0.000000e+00,  0.000000e+00,  0.000000e+00,\n",
       "        0.000000e+00,  0.000000e+00,  0.000000e+00,  0.000000e+00,\n",
       "        0.000000e+00,  0.000000e+00,  0.000000e+00,  0.000000e+00],\n",
       "      dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lwp_bar</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-c48559b3-2a47-4963-a56e-f8d32a606fb2' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-c48559b3-2a47-4963-a56e-f8d32a606fb2' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-afe051b1-2ed8-4960-be6a-964e78acc564' class='xr-var-data-in' type='checkbox'><label for='data-afe051b1-2ed8-4960-be6a-964e78acc564' 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>longname :</span></dt><dd>Liquid-water path</dd><dt><span>units :</span></dt><dd>kg/m^2</dd></dl></div><div class='xr-var-data'><pre>array([3.942768e-07, 1.628522e-08, 8.150598e-09, 0.000000e+00, 0.000000e+00,\n",
       "       0.000000e+00, 0.000000e+00, 0.000000e+00, 0.000000e+00, 0.000000e+00,\n",
       "       0.000000e+00, 0.000000e+00, 0.000000e+00, 0.000000e+00, 0.000000e+00,\n",
       "       0.000000e+00, 8.585803e-10, 3.937283e-09, 1.086039e-08, 1.533870e-08,\n",
       "       1.276117e-08, 2.438971e-08, 8.583079e-08, 2.219244e-07, 5.894744e-07,\n",
       "       1.555929e-06, 3.355081e-06, 7.640668e-06, 1.546882e-05, 3.149634e-05,\n",
       "       6.444046e-05, 1.369038e-04, 2.764965e-04, 5.255962e-04, 9.245426e-04,\n",
       "       1.329555e-03, 1.590564e-03, 1.713525e-03, 1.772692e-03, 1.790792e-03,\n",
       "       1.770732e-03, 1.788069e-03, 1.788027e-03, 1.760333e-03, 1.764382e-03,\n",
       "       1.770886e-03, 1.761334e-03, 1.759544e-03, 1.769590e-03, 1.775182e-03,\n",
       "       1.774862e-03, 1.770328e-03, 1.778457e-03, 1.780574e-03, 1.779224e-03,\n",
       "       1.772810e-03, 1.786559e-03, 1.785089e-03, 1.794590e-03, 1.799676e-03],\n",
       "      dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lwp_max</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-4e954219-18e4-4057-b8fa-2c58291e9a14' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-4e954219-18e4-4057-b8fa-2c58291e9a14' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-bec53a19-3000-48b9-b4b2-0820fa2d5b2b' class='xr-var-data-in' type='checkbox'><label for='data-bec53a19-3000-48b9-b4b2-0820fa2d5b2b' 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>longname :</span></dt><dd>Maximum Liquid-water path</dd><dt><span>units :</span></dt><dd>kg/m^2</dd></dl></div><div class='xr-var-data'><pre>array([5.215616e-05, 1.566328e-05, 1.765179e-05, 0.000000e+00, 0.000000e+00,\n",
       "       0.000000e+00, 0.000000e+00, 0.000000e+00, 0.000000e+00, 0.000000e+00,\n",
       "       0.000000e+00, 0.000000e+00, 0.000000e+00, 0.000000e+00, 0.000000e+00,\n",
       "       0.000000e+00, 3.516745e-06, 9.689464e-06, 6.975590e-06, 1.285445e-05,\n",
       "       7.770734e-06, 9.592937e-06, 2.404942e-05, 2.995019e-05, 5.197689e-05,\n",
       "       5.771576e-05, 8.187679e-05, 1.392690e-04, 1.834069e-04, 2.844871e-04,\n",
       "       4.845206e-04, 7.408731e-04, 9.634197e-04, 1.438341e-03, 1.646863e-03,\n",
       "       2.057721e-03, 2.160775e-03, 2.329560e-03, 2.423528e-03, 2.439111e-03,\n",
       "       2.439290e-03, 2.505852e-03, 2.467438e-03, 2.427582e-03, 2.302528e-03,\n",
       "       2.463254e-03, 2.471047e-03, 2.481876e-03, 2.391154e-03, 2.407769e-03,\n",
       "       2.417459e-03, 2.395042e-03, 2.376995e-03, 2.407953e-03, 2.400130e-03,\n",
       "       2.575683e-03, 2.343345e-03, 2.433891e-03, 2.455047e-03, 2.439112e-03],\n",
       "      dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>wmax</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-8620369e-9a08-4e54-addd-574bbb1446d6' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-8620369e-9a08-4e54-addd-574bbb1446d6' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-94056e3e-2193-4ff6-a257-89d787a22d99' class='xr-var-data-in' type='checkbox'><label for='data-94056e3e-2193-4ff6-a257-89d787a22d99' 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>longname :</span></dt><dd>Maximum vertical velocity</dd><dt><span>units :</span></dt><dd>m/s</dd></dl></div><div class='xr-var-data'><pre>array([0.054144, 0.045856, 0.036239, 0.041622, 0.035514, 0.028614, 0.029914,\n",
       "       0.024542, 0.019758, 0.024897, 0.032675, 0.040291, 0.041538, 0.052368,\n",
       "       0.059915, 0.073665, 0.079231, 0.088725, 0.095771, 0.097862, 0.095695,\n",
       "       0.086055, 0.084315, 0.083852, 0.075994, 0.072233, 0.071192, 0.070661,\n",
       "       0.073698, 0.072916, 0.0745  , 0.078095, 0.073597, 0.11426 , 0.186267,\n",
       "       0.279357, 0.344806, 0.27754 , 0.206809, 0.171483, 0.156408, 0.175718,\n",
       "       0.117338, 0.108074, 0.103983, 0.116209, 0.094719, 0.091242, 0.093182,\n",
       "       0.094664, 0.077016, 0.070049, 0.086283, 0.083052, 0.07238 , 0.069173,\n",
       "       0.070329, 0.068127, 0.069072, 0.069919], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>vtke</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-343459b2-a80c-4c44-b60f-3d23834ea285' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-343459b2-a80c-4c44-b60f-3d23834ea285' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-613d9666-9a18-4d12-866f-5ffda5d29a23' class='xr-var-data-in' type='checkbox'><label for='data-613d9666-9a18-4d12-866f-5ffda5d29a23' 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>longname :</span></dt><dd>Vertical integral of total TKE</dd><dt><span>units :</span></dt><dd>kg/s</dd></dl></div><div class='xr-var-data'><pre>array([5.665051, 1.351268, 0.512567, 0.238503, 0.124475, 0.070982, 0.042619,\n",
       "       0.027635, 0.018025, 0.013216, 0.009812, 0.008121, 0.006853, 0.006326,\n",
       "       0.006313, 0.006569, 0.007486, 0.008566, 0.009652, 0.01009 , 0.00996 ,\n",
       "       0.009402, 0.008716, 0.007935, 0.007472, 0.007049, 0.006854, 0.006687,\n",
       "       0.006699, 0.006973, 0.007515, 0.008765, 0.010765, 0.014435, 0.020687,\n",
       "       0.03027 , 0.03996 , 0.045147, 0.046359, 0.046419, 0.046366, 0.046115,\n",
       "       0.045722, 0.045032, 0.04459 , 0.045098, 0.045116, 0.044743, 0.044734,\n",
       "       0.043993, 0.043871, 0.043574, 0.044027, 0.043345, 0.043841, 0.04367 ,\n",
       "       0.043993, 0.044219, 0.044205, 0.044321], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lmax</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-1552e90a-683a-4f57-807b-7673b81744d4' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-1552e90a-683a-4f57-807b-7673b81744d4' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f3f00dce-f6a8-4f8f-8d9b-8f128e44b862' class='xr-var-data-in' type='checkbox'><label for='data-f3f00dce-f6a8-4f8f-8d9b-8f128e44b862' 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>longname :</span></dt><dd>Maximum liquid water specific humidity</dd><dt><span>units :</span></dt><dd>kg/kg</dd></dl></div><div class='xr-var-data'><pre>array([1.082370e-05, 3.250479e-06, 3.663093e-06, 0.000000e+00, 0.000000e+00,\n",
       "       0.000000e+00, 0.000000e+00, 0.000000e+00, 0.000000e+00, 0.000000e+00,\n",
       "       0.000000e+00, 0.000000e+00, 0.000000e+00, 0.000000e+00, 0.000000e+00,\n",
       "       0.000000e+00, 7.296261e-07, 2.010250e-06, 1.447178e-06, 2.666764e-06,\n",
       "       1.612066e-06, 1.990041e-06, 4.988888e-06, 6.212797e-06, 1.078166e-05,\n",
       "       1.197172e-05, 1.698279e-05, 2.888595e-05, 3.803903e-05, 5.900003e-05,\n",
       "       1.004769e-04, 1.536152e-04, 1.997063e-04, 2.980108e-04, 3.409337e-04,\n",
       "       4.255117e-04, 4.393699e-04, 4.760762e-04, 4.998075e-04, 5.026360e-04,\n",
       "       4.933428e-04, 4.929930e-04, 4.677232e-04, 4.706565e-04, 4.684849e-04,\n",
       "       4.936742e-04, 4.771319e-04, 4.822472e-04, 4.661164e-04, 4.593985e-04,\n",
       "       4.581471e-04, 4.389824e-04, 4.262275e-04, 4.432552e-04, 4.438111e-04,\n",
       "       4.630134e-04, 4.186835e-04, 4.277499e-04, 4.338669e-04, 4.241689e-04],\n",
       "      dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>ustar</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-ec27bdfc-54ca-405b-a29a-6329c6e3ca4b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ec27bdfc-54ca-405b-a29a-6329c6e3ca4b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-bd2853e1-7500-4432-935c-3cd1342a2c3c' class='xr-var-data-in' type='checkbox'><label for='data-bd2853e1-7500-4432-935c-3cd1342a2c3c' 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>longname :</span></dt><dd>Surface friction velocity</dd><dt><span>units :</span></dt><dd>m/s</dd></dl></div><div class='xr-var-data'><pre>array([0.010549, 0.008107, 0.006324, 0.005779, 0.00583 , 0.005871, 0.005902,\n",
       "       0.006002, 0.006064, 0.00614 , 0.006269, 0.006397, 0.006496, 0.00665 ,\n",
       "       0.006852, 0.007099, 0.007206, 0.007381, 0.007569, 0.007807, 0.008036,\n",
       "       0.008322, 0.008561, 0.008863, 0.009193, 0.009427, 0.009768, 0.010064,\n",
       "       0.010477, 0.010949, 0.011348, 0.011714, 0.012529, 0.014387, 0.022404,\n",
       "       0.066951, 0.067277, 0.065052, 0.062148, 0.059316, 0.056747, 0.054568,\n",
       "       0.052555, 0.050726, 0.049137, 0.047736, 0.046473, 0.045314, 0.044347,\n",
       "       0.043455, 0.042674, 0.041948, 0.041326, 0.040775, 0.040294, 0.039865,\n",
       "       0.03952 , 0.03917 , 0.038912, 0.038689], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>tstr</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-a94fb48b-5b71-44f9-b269-d9fb16dc3b8e' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a94fb48b-5b71-44f9-b269-d9fb16dc3b8e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-cca18ea4-96a6-4d7d-b119-22c57a867adb' class='xr-var-data-in' type='checkbox'><label for='data-cca18ea4-96a6-4d7d-b119-22c57a867adb' 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>longname :</span></dt><dd>Turbulent temperature scale</dd><dt><span>units :</span></dt><dd>K</dd></dl></div><div class='xr-var-data'><pre>array([ 0.040972,  0.04163 ,  0.038206,  0.03655 ,  0.036836,  0.037084,\n",
       "        0.037316,  0.037804,  0.03818 ,  0.038621,  0.039272,  0.039929,\n",
       "        0.040511,  0.041281,  0.042213,  0.04326 ,  0.043926,  0.044793,\n",
       "        0.04571 ,  0.046746,  0.047751,  0.048853,  0.049879,  0.050982,\n",
       "        0.05209 ,  0.053063,  0.054121,  0.055106,  0.056106,  0.057021,\n",
       "        0.057858,  0.058646,  0.058928,  0.056799,  0.0452  , -0.047179,\n",
       "       -0.110595, -0.151663, -0.174304, -0.189394, -0.201677, -0.217747,\n",
       "       -0.231318, -0.242906, -0.256284, -0.269979, -0.282941, -0.294678,\n",
       "       -0.309212, -0.322811, -0.335713, -0.346542, -0.358216, -0.370187,\n",
       "       -0.38082 , -0.391836, -0.404275, -0.413131, -0.424836, -0.436399],\n",
       "      dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>qtstr</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-6083fa70-5e9b-4c0e-a049-f594f43cae24' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-6083fa70-5e9b-4c0e-a049-f594f43cae24' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d83e73f5-446a-4e5d-a8ef-0fb69355b0cf' class='xr-var-data-in' type='checkbox'><label for='data-d83e73f5-446a-4e5d-a8ef-0fb69355b0cf' 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>longname :</span></dt><dd>Turbulent humidity scale</dd><dt><span>units :</span></dt><dd>K</dd></dl></div><div class='xr-var-data'><pre>array([ 2.376235e-05,  2.217483e-05,  1.853457e-05,  1.706167e-05,\n",
       "        1.722035e-05,  1.735514e-05,  1.745688e-05,  1.775944e-05,\n",
       "        1.794748e-05,  1.818777e-05,  1.856687e-05,  1.895154e-05,\n",
       "        1.927655e-05,  1.972254e-05,  2.029499e-05,  2.097571e-05,\n",
       "        2.131703e-05,  2.181617e-05,  2.230924e-05,  2.293834e-05,\n",
       "        2.356789e-05,  2.434217e-05,  2.494591e-05,  2.565634e-05,\n",
       "        2.641026e-05,  2.696415e-05,  2.771855e-05,  2.839032e-05,\n",
       "        2.920470e-05,  3.003203e-05,  3.075202e-05,  3.161502e-05,\n",
       "        3.291114e-05,  3.478749e-05,  3.769409e-05,  1.884125e-05,\n",
       "       -7.920031e-07, -7.129810e-06, -9.659745e-06, -1.147993e-05,\n",
       "       -1.344716e-05, -1.559708e-05, -1.760100e-05, -1.966983e-05,\n",
       "       -2.165493e-05, -2.376934e-05, -2.606721e-05, -2.805190e-05,\n",
       "       -3.051309e-05, -3.287945e-05, -3.527131e-05, -3.732922e-05,\n",
       "       -3.932892e-05, -4.157713e-05, -4.367205e-05, -4.608182e-05,\n",
       "       -4.838043e-05, -5.013987e-05, -5.240197e-05, -5.496689e-05],\n",
       "      dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>obukh</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-bd151cb5-e319-45cf-8e9e-41d786ea818b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-bd151cb5-e319-45cf-8e9e-41d786ea818b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e77677f2-c73f-4051-a3b8-de6261ab18f2' class='xr-var-data-in' type='checkbox'><label for='data-e77677f2-c73f-4051-a3b8-de6261ab18f2' 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>longname :</span></dt><dd>Obukhov Length</dd><dt><span>units :</span></dt><dd>m</dd></dl></div><div class='xr-var-data'><pre>array([ 0.178087,  0.103235,  0.068119,  0.059331,  0.059923,  0.060369,\n",
       "        0.060628,  0.061896,  0.062564,  0.063416,  0.065033,  0.066606,\n",
       "        0.067713,  0.069647,  0.072353,  0.075824,  0.076935,  0.079173,\n",
       "        0.081624,  0.084953,  0.088137,  0.092401,  0.095815,  0.100504,\n",
       "        0.105884,  0.109323,  0.115131,  0.120036,  0.127825,  0.137409,\n",
       "        0.145486,  0.152829,  0.173806,  0.236773,  0.701391, -7.45125 ,\n",
       "       -2.989779, -2.025956, -1.606583, -1.345378, -1.154881, -0.988074,\n",
       "       -0.861891, -0.76384 , -0.678749, -0.607611, -0.549026, -0.500834,\n",
       "       -0.45683 , -0.419867, -0.389105, -0.36402 , -0.341637, -0.321672,\n",
       "       -0.305205, -0.290189, -0.27631 , -0.265531, -0.254746, -0.245054],\n",
       "      dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>thlskin</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-6285c288-8ef7-4e9e-bb52-58179a59f460' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-6285c288-8ef7-4e9e-bb52-58179a59f460' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a800721a-4e8e-4ee9-9207-734b080dbe09' class='xr-var-data-in' type='checkbox'><label for='data-a800721a-4e8e-4ee9-9207-734b080dbe09' 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>longname :</span></dt><dd>Surface liquid water potential temperature</dd><dt><span>units :</span></dt><dd>K</dd></dl></div><div class='xr-var-data'><pre>array([283.2304 , 280.33014, 276.9546 , 275.53983, 275.59146, 275.6182 ,\n",
       "       275.6042 , 275.75098, 275.7871 , 275.84396, 276.0048 , 276.14462,\n",
       "       276.20374, 276.36942, 276.62088, 276.94675, 276.9612 , 277.10086,\n",
       "       277.24948, 277.47818, 277.67175, 277.95102, 278.12228, 278.3865 ,\n",
       "       278.6767 , 278.7962 , 279.0661 , 279.24896, 279.57773, 279.94855,\n",
       "       280.18326, 280.3225 , 280.86563, 282.0706 , 284.28372, 286.58276,\n",
       "       287.04147, 287.24118, 287.23425, 287.16177, 287.09183, 287.02948,\n",
       "       286.95764, 286.89227, 286.8231 , 286.761  , 286.71228, 286.65225,\n",
       "       286.6133 , 286.5751 , 286.5423 , 286.50366, 286.46732, 286.44293,\n",
       "       286.4179 , 286.407  , 286.39682, 286.3762 , 286.3763 , 286.38574],\n",
       "      dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>z0</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-dd5fd8df-a07a-4a18-a7d9-7dc338d06c18' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-dd5fd8df-a07a-4a18-a7d9-7dc338d06c18' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-84a21453-92f8-4110-b1f2-c74dfa7b9c81' class='xr-var-data-in' type='checkbox'><label for='data-84a21453-92f8-4110-b1f2-c74dfa7b9c81' 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>longname :</span></dt><dd>Roughness height</dd><dt><span>units :</span></dt><dd>m</dd></dl></div><div class='xr-var-data'><pre>array([0.01, 0.01, 0.01, 0.01, 0.01, 0.01, 0.01, 0.01, 0.01, 0.01, 0.01, 0.01,\n",
       "       0.01, 0.01, 0.01, 0.01, 0.01, 0.01, 0.01, 0.01, 0.01, 0.01, 0.01, 0.01,\n",
       "       0.01, 0.01, 0.01, 0.01, 0.01, 0.01, 0.01, 0.01, 0.01, 0.01, 0.01, 0.01,\n",
       "       0.01, 0.01, 0.01, 0.01, 0.01, 0.01, 0.01, 0.01, 0.01, 0.01, 0.01, 0.01,\n",
       "       0.01, 0.01, 0.01, 0.01, 0.01, 0.01, 0.01, 0.01, 0.01, 0.01, 0.01, 0.01],\n",
       "      dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>wtheta</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-e674c73d-21fc-4cb8-a85a-b8e417aa1ee2' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e674c73d-21fc-4cb8-a85a-b8e417aa1ee2' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-acf13120-aadf-4b57-92a9-c6c19a182d2c' class='xr-var-data-in' type='checkbox'><label for='data-acf13120-aadf-4b57-92a9-c6c19a182d2c' 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>longname :</span></dt><dd>Surface kinematic temperature flux</dd><dt><span>units :</span></dt><dd>K m/s</dd></dl></div><div class='xr-var-data'><pre>array([-0.000432, -0.000338, -0.000242, -0.000211, -0.000215, -0.000218,\n",
       "       -0.00022 , -0.000227, -0.000232, -0.000237, -0.000246, -0.000255,\n",
       "       -0.000263, -0.000275, -0.000289, -0.000307, -0.000317, -0.000331,\n",
       "       -0.000346, -0.000365, -0.000384, -0.000407, -0.000427, -0.000452,\n",
       "       -0.000479, -0.0005  , -0.000529, -0.000555, -0.000588, -0.000624,\n",
       "       -0.000657, -0.000687, -0.000738, -0.000817, -0.001013,  0.003159,\n",
       "        0.007441,  0.009866,  0.010833,  0.011234,  0.011444,  0.011882,\n",
       "        0.012157,  0.012322,  0.012593,  0.012888,  0.013149,  0.013353,\n",
       "        0.013713,  0.014028,  0.014326,  0.014537,  0.014804,  0.015094,\n",
       "        0.015345,  0.01562 ,  0.015977,  0.016182,  0.016531,  0.016884],\n",
       "      dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>wthetav</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-881f3f0b-4dc3-4ca6-a3ee-314299e78458' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-881f3f0b-4dc3-4ca6-a3ee-314299e78458' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-17defd38-e84f-4e18-a082-2d722c8cbd10' class='xr-var-data-in' type='checkbox'><label for='data-17defd38-e84f-4e18-a082-2d722c8cbd10' 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>longname :</span></dt><dd>Surface kinematic virtual temperature flux</dd><dt><span>units :</span></dt><dd>K m/s</dd></dl></div><div class='xr-var-data'><pre>array([-0.000477, -0.000369, -0.000262, -0.000228, -0.000232, -0.000235,\n",
       "       -0.000238, -0.000245, -0.00025 , -0.000257, -0.000266, -0.000276,\n",
       "       -0.000285, -0.000297, -0.000314, -0.000333, -0.000343, -0.000359,\n",
       "       -0.000376, -0.000396, -0.000417, -0.000442, -0.000465, -0.000492,\n",
       "       -0.000522, -0.000545, -0.000576, -0.000605, -0.000642, -0.000683,\n",
       "       -0.000719, -0.000753, -0.000812, -0.000907, -0.001164,  0.002957,\n",
       "        0.007494,  0.010005,  0.011001,  0.011418,  0.011644,  0.012098,\n",
       "        0.012387,  0.012565,  0.012849,  0.013157,  0.013432,  0.013647,\n",
       "        0.014022,  0.014352,  0.014665,  0.014886,  0.015165,  0.015469,\n",
       "        0.015731,  0.016022,  0.016393,  0.016608,  0.016971,  0.017341],\n",
       "      dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>wq</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-6a6f2cb3-512a-4fe6-8ad7-6541da524c22' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-6a6f2cb3-512a-4fe6-8ad7-6541da524c22' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ec2b85e2-1787-4dce-a3a7-82d0002155a1' class='xr-var-data-in' type='checkbox'><label for='data-ec2b85e2-1787-4dce-a3a7-82d0002155a1' 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>longname :</span></dt><dd>Surface kinematic moisture flux</dd><dt><span>units :</span></dt><dd>kg/kg m/s</dd></dl></div><div class='xr-var-data'><pre>array([-2.506609e-07, -1.797823e-07, -1.172056e-07, -9.859424e-08,\n",
       "       -1.003927e-07, -1.018962e-07, -1.030341e-07, -1.065886e-07,\n",
       "       -1.088293e-07, -1.116703e-07, -1.163946e-07, -1.212236e-07,\n",
       "       -1.252233e-07, -1.311477e-07, -1.390656e-07, -1.489114e-07,\n",
       "       -1.536092e-07, -1.610238e-07, -1.688634e-07, -1.790881e-07,\n",
       "       -1.894013e-07, -2.025737e-07, -2.135707e-07, -2.273859e-07,\n",
       "       -2.427935e-07, -2.541874e-07, -2.707661e-07, -2.857142e-07,\n",
       "       -3.059838e-07, -3.288244e-07, -3.489810e-07, -3.703392e-07,\n",
       "       -4.123443e-07, -5.004797e-07, -8.444867e-07, -1.261447e-06,\n",
       "        5.328373e-08,  4.638115e-07,  6.003351e-07,  6.809448e-07,\n",
       "        7.630800e-07,  8.511012e-07,  9.250275e-07,  9.977751e-07,\n",
       "        1.064055e-06,  1.134649e-06,  1.211409e-06,  1.271133e-06,\n",
       "        1.353174e-06,  1.428761e-06,  1.505163e-06,  1.565884e-06,\n",
       "        1.625317e-06,  1.695317e-06,  1.759716e-06,  1.837044e-06,\n",
       "        1.911986e-06,  1.963984e-06,  2.039091e-06,  2.126601e-06],\n",
       "      dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>twp_bar</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-89cdea5d-e59a-4933-a132-55f29e1c3570' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-89cdea5d-e59a-4933-a132-55f29e1c3570' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-420b0f33-872e-4c47-a070-12a3b63de2d5' class='xr-var-data-in' type='checkbox'><label for='data-420b0f33-872e-4c47-a070-12a3b63de2d5' 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>longname :</span></dt><dd>Total water path</dd><dt><span>units :</span></dt><dd>kg/m^2</dd></dl></div><div class='xr-var-data'><pre>array([3.033262, 3.033217, 3.03318 , 3.033145, 3.033112, 3.033078, 3.033045,\n",
       "       3.03301 , 3.032977, 3.032943, 3.032908, 3.032873, 3.032838, 3.032803,\n",
       "       3.032767, 3.03273 , 3.032695, 3.032658, 3.03262 , 3.032583, 3.032544,\n",
       "       3.032504, 3.032465, 3.032423, 3.032382, 3.03234 , 3.032295, 3.032251,\n",
       "       3.032205, 3.032157, 3.032108, 3.032055, 3.031989, 3.031889, 3.031703,\n",
       "       3.031298, 3.030815, 3.030286, 3.029725, 3.029145, 3.028571, 3.028013,\n",
       "       3.027459, 3.026918, 3.026396, 3.025883, 3.025384, 3.024903, 3.024436,\n",
       "       3.023984, 3.023547, 3.023128, 3.022726, 3.022331, 3.021949, 3.021585,\n",
       "       3.021235, 3.020893, 3.020563, 3.020243], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>rwp_bar</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-ad9d2ac3-1e8e-45f4-ad2a-92eff8c441da' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ad9d2ac3-1e8e-45f4-ad2a-92eff8c441da' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-49053cea-d4ee-4958-a9b1-7e2502e4d3a7' class='xr-var-data-in' type='checkbox'><label for='data-49053cea-d4ee-4958-a9b1-7e2502e4d3a7' 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>longname :</span></dt><dd>Rain water path</dd><dt><span>units :</span></dt><dd>kg/m^2</dd></dl></div><div class='xr-var-data'><pre>array([nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan,\n",
       "       nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan,\n",
       "       nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan,\n",
       "       nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan,\n",
       "       nan, nan, nan, nan], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Qnet</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-3bad904e-ed71-476c-8eaa-31082428796b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3bad904e-ed71-476c-8eaa-31082428796b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-31630eeb-12f5-4018-a34f-1c6c81f57c31' class='xr-var-data-in' type='checkbox'><label for='data-31630eeb-12f5-4018-a34f-1c6c81f57c31' 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>longname :</span></dt><dd>Net radiation</dd><dt><span>units :</span></dt><dd>W/m^2</dd></dl></div><div class='xr-var-data'><pre>array([-23.887827, -40.906036, -60.75328 , -69.01117 , -68.57066 , -68.27848 ,\n",
       "       -68.23023 , -67.233986, -66.89382 , -66.43662 , -65.363914, -64.4234  ,\n",
       "       -63.965397, -62.879528, -61.290356, -59.271576, -59.098137, -58.189323,\n",
       "       -57.23193 , -55.80865 , -54.59941 , -52.89383 , -51.827732, -50.22357 ,\n",
       "       -48.47507 , -47.734894, -46.120255, -45.023167, -43.080254, -40.90215 ,\n",
       "       -39.53344 , -38.74493 , -35.63331 , -28.761232, -16.975103,  -2.539013,\n",
       "         8.263309,  13.178705,  14.586146,  14.914343,  15.150922,  15.584197,\n",
       "        15.78826 ,  15.96535 ,  16.130749,  16.381552,  16.735468,  16.881468,\n",
       "        17.366714,  17.796011,  18.250086,  18.526955,  18.838644,  19.295797,\n",
       "        19.689812,  20.244507,  20.836582,  21.155703,  21.81206 ,  22.579964],\n",
       "      dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>H</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-3144dac7-73e2-4f23-aef2-915227428383' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3144dac7-73e2-4f23-aef2-915227428383' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d945c740-d83e-4e5a-b4a3-7bd0a48d4bfe' class='xr-var-data-in' type='checkbox'><label for='data-d945c740-d83e-4e5a-b4a3-7bd0a48d4bfe' 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>longname :</span></dt><dd>Sensible heat flux</dd><dt><span>units :</span></dt><dd>W/m^2</dd></dl></div><div class='xr-var-data'><pre>array([-0.520317, -0.407098, -0.291673, -0.255047, -0.259322, -0.262927,\n",
       "       -0.265966, -0.27399 , -0.279573, -0.286358, -0.297302, -0.308428,\n",
       "       -0.317796, -0.33149 , -0.349293, -0.370844, -0.382219, -0.399229,\n",
       "       -0.417791, -0.440685, -0.463361, -0.490881, -0.515599, -0.545538,\n",
       "       -0.578161, -0.603962, -0.638376, -0.669827, -0.710342, -0.755295,\n",
       "       -0.796326, -0.838013, -0.912299, -1.044146, -1.507023,  0.393353,\n",
       "        4.469875,  6.977488,  8.044865,  8.596531,  9.034985,  9.604859,\n",
       "       10.044365, 10.420406, 10.826245, 11.260322, 11.696946, 12.045032,\n",
       "       12.535887, 12.985472, 13.424229, 13.768668, 14.137153, 14.546199,\n",
       "       14.912648, 15.314692, 15.756682, 16.059254, 16.502596, 16.963013],\n",
       "      dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>LE</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-f18baf94-1f08-4322-a359-e9bd6c1d44ff' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f18baf94-1f08-4322-a359-e9bd6c1d44ff' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0218287e-525a-4cbd-9c83-6284954c71f3' class='xr-var-data-in' type='checkbox'><label for='data-0218287e-525a-4cbd-9c83-6284954c71f3' 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>longname :</span></dt><dd>Latent heat flux</dd><dt><span>units :</span></dt><dd>W/m^2</dd></dl></div><div class='xr-var-data'><pre>array([-0.763482, -0.547748, -0.357151, -0.300468, -0.305946, -0.310533,\n",
       "       -0.314007, -0.324845, -0.331676, -0.340335, -0.354743, -0.369457,\n",
       "       -0.381655, -0.399725, -0.42386 , -0.453864, -0.468199, -0.490811,\n",
       "       -0.514708, -0.545885, -0.577337, -0.617505, -0.651032, -0.693167,\n",
       "       -0.740132, -0.774887, -0.825444, -0.871051, -0.932859, -1.002524,\n",
       "       -1.064014, -1.129275, -1.257571, -1.52676 , -2.576509, -3.815863,\n",
       "        0.190099,  1.436698,  1.856138,  2.104695,  2.358232,  2.630443,\n",
       "        2.859524,  3.085085,  3.29109 ,  3.510616,  3.749254,  3.935481,\n",
       "        4.190905,  4.426513,  4.664709,  4.854417,  5.040289,  5.258922,\n",
       "        5.460211,  5.701519,  5.935669,  6.09853 ,  6.333165,  6.606215],\n",
       "      dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>G0</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-2be7e907-cebe-4f86-881f-5606cd5327b8' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-2be7e907-cebe-4f86-881f-5606cd5327b8' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4cdd75f5-297a-40c0-a0b2-359e76024843' class='xr-var-data-in' type='checkbox'><label for='data-4cdd75f5-297a-40c0-a0b2-359e76024843' 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>longname :</span></dt><dd>Ground heat flux</dd><dt><span>units :</span></dt><dd>W/m^2</dd></dl></div><div class='xr-var-data'><pre>array([-22.604029, -39.95119 , -60.104454, -68.45566 , -68.005394, -67.70502 ,\n",
       "       -67.65026 , -66.635155, -66.28257 , -65.80993 , -64.71187 , -63.745518,\n",
       "       -63.265945, -62.14831 , -60.5172  , -58.44687 , -58.24772 , -57.299282,\n",
       "       -56.29943 , -54.82208 , -53.558712, -51.785442, -50.661102, -48.984867,\n",
       "       -47.15678 , -46.35605 , -44.656437, -43.48229 , -41.437054, -39.14433 ,\n",
       "       -37.6731  , -36.77764 , -33.46344 , -26.190327, -12.891572,   0.883497,\n",
       "         3.603335,   4.764519,   4.685143,   4.213117,   3.757706,   3.348895,\n",
       "         2.884372,   2.459859,   2.013412,   1.610615,   1.289268,   0.900956,\n",
       "         0.639922,   0.384026,   0.161148,  -0.096131,  -0.338798,  -0.509324,\n",
       "        -0.683047,  -0.771704,  -0.855768,  -1.002081,  -1.023701,  -0.989264],\n",
       "      dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>tendskin</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-bb3370a5-5aa4-40a9-9d26-38567c02d6f7' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-bb3370a5-5aa4-40a9-9d26-38567c02d6f7' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3fcee403-fe71-4d0b-b078-0851f29ea37c' class='xr-var-data-in' type='checkbox'><label for='data-3fcee403-fe71-4d0b-b078-0851f29ea37c' 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>longname :</span></dt><dd>Skin tendency</dd><dt><span>units :</span></dt><dd>W/m^2</dd></dl></div><div class='xr-var-data'><pre>array([0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
       "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
       "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
       "       0., 0., 0., 0., 0., 0.], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>rs</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-759ea64c-9e2a-4a1d-96d3-9bfd0d0eeeff' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-759ea64c-9e2a-4a1d-96d3-9bfd0d0eeeff' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9e98a6ce-1cab-4f4b-ad86-0d692bbe85aa' class='xr-var-data-in' type='checkbox'><label for='data-9e98a6ce-1cab-4f4b-ad86-0d692bbe85aa' 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>longname :</span></dt><dd>Surface resistance</dd><dt><span>units :</span></dt><dd>s/m</dd></dl></div><div class='xr-var-data'><pre>array([-7.647216e-13,  6.989964e-13, -1.472600e-12,  1.364242e-12,\n",
       "       -2.113865e-12, -1.614708e-12, -1.776357e-13,  2.698286e-12,\n",
       "        7.460699e-14, -3.026912e-12,  1.174172e-12, -1.312728e-12,\n",
       "        3.431921e-12,  3.979039e-12, -7.638334e-13, -3.131717e-12,\n",
       "       -1.482370e-12,  5.142553e-13,  1.051603e-12,  1.170619e-12,\n",
       "        1.254108e-12, -1.636913e-12, -8.206769e-13, -4.725109e-13,\n",
       "       -1.509903e-12,  2.327027e-13,  4.020606e-01,  7.709389e-13,\n",
       "        7.496226e-13,  3.081672e-01,  3.922886e-01,  5.081936e-01,\n",
       "        5.223105e-01,  3.578089e-01,  5.523364e+00,  4.152845e+01,\n",
       "        3.479125e+02,  5.367751e+02,  5.497596e+02,  5.567996e+02,\n",
       "        5.594652e+02,  5.562712e+02,  5.548987e+02,  5.536280e+02,\n",
       "        5.521895e+02,  5.497976e+02,  5.463997e+02,  5.458854e+02,\n",
       "        5.392361e+02,  5.331830e+02,  5.276897e+02,  5.242739e+02,\n",
       "        5.204828e+02,  5.147108e+02,  5.096973e+02,  5.029444e+02,\n",
       "        4.960263e+02,  4.932068e+02,  4.864054e+02,  4.788136e+02],\n",
       "      dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>ra</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-1ee8893f-9d5f-467d-b53b-b59e8aa3dd9e' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-1ee8893f-9d5f-467d-b53b-b59e8aa3dd9e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9b12a35d-1928-4aa9-854a-36aa5437239a' class='xr-var-data-in' type='checkbox'><label for='data-9b12a35d-1928-4aa9-854a-36aa5437239a' 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>longname :</span></dt><dd>Aerodynamic resistance</dd><dt><span>units :</span></dt><dd>s/m</dd></dl></div><div class='xr-var-data'><pre>array([ 9595.276  , 20872.31   , 43116.277  , 56002.914  , 54822.07   ,\n",
       "       53930.145  , 53359.695  , 51132.164  , 49936.74   , 48495.645  ,\n",
       "       46038.816  , 43812.574  , 42278.688  , 39910.766  , 36989.113  ,\n",
       "       33760.84   , 32693.516  , 30861.041  , 29043.633  , 26890.703  ,\n",
       "       25053.443  , 22945.283  , 21427.408  , 19650.367  , 17919.096  ,\n",
       "       16898.691  , 15460.805  , 14388.065  , 12989.798  , 11601.28   ,\n",
       "       10617.952  ,  9841.238  ,  8241.51   ,  5679.761  ,  2004.2732 ,\n",
       "         235.8054 ,   213.03073,   209.4266 ,   212.09474,   216.36404,\n",
       "         220.79457,   223.81766,   227.05153,   230.29974,   232.71799,\n",
       "         234.65718,   236.4059 ,   238.12683,   238.87189,   239.60356,\n",
       "         240.14001,   240.85995,   241.15613,   241.2099 ,   241.25764,\n",
       "         241.10136,   240.5066 ,   240.44113,   239.71094,   238.91165],\n",
       "      dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>cliq</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-be48bfec-985e-4515-b1d7-7a911f8828bf' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-be48bfec-985e-4515-b1d7-7a911f8828bf' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d2c017b7-3a0e-4da7-9082-553d110bf856' class='xr-var-data-in' type='checkbox'><label for='data-d2c017b7-3a0e-4da7-9082-553d110bf856' 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>longname :</span></dt><dd>Fraction of vegetated surface covered with liquid water</dd><dt><span>units :</span></dt><dd>-</dd></dl></div><div class='xr-var-data'><pre>array([5.400837e-05, 9.216608e-05, 1.193374e-04, 1.375521e-04, 1.555872e-04,\n",
       "       1.738946e-04, 1.926109e-04, 2.113595e-04, 2.311333e-04, 2.509386e-04,\n",
       "       2.718185e-04, 2.931737e-04, 3.154573e-04, 3.385092e-04, 3.634447e-04,\n",
       "       3.894271e-04, 4.167493e-04, 4.452566e-04, 4.750258e-04, 5.064432e-04,\n",
       "       5.398204e-04, 5.753402e-04, 6.136175e-04, 6.535591e-04, 6.959166e-04,\n",
       "       7.407908e-04, 7.883468e-04, 8.385876e-04, 8.921186e-04, 9.494086e-04,\n",
       "       1.010651e-03, 1.075734e-03, 1.146292e-03, 1.227863e-03, 1.338282e-03,\n",
       "       1.629781e-03, 1.736831e-03, 1.741522e-03, 1.741046e-03, 1.740396e-03,\n",
       "       1.739670e-03, 1.738874e-03, 1.738004e-03, 1.737073e-03, 1.736085e-03,\n",
       "       1.735038e-03, 1.733935e-03, 1.732776e-03, 1.731563e-03, 1.730290e-03,\n",
       "       1.728953e-03, 1.727569e-03, 1.726139e-03, 1.724664e-03, 1.723141e-03,\n",
       "       1.721567e-03, 1.719943e-03, 1.718279e-03, 1.716564e-03, 1.714797e-03],\n",
       "      dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Wl</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-fe6e9749-88f2-455e-b408-d0dae7c8ee49' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-fe6e9749-88f2-455e-b408-d0dae7c8ee49' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5f2aa71f-6cb5-49f2-84cf-f9a64fb87e09' class='xr-var-data-in' type='checkbox'><label for='data-5f2aa71f-6cb5-49f2-84cf-f9a64fb87e09' 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>longname :</span></dt><dd>Liquid water reservoir</dd><dt><span>units :</span></dt><dd>m</dd></dl></div><div class='xr-var-data'><pre>array([2.183277e-08, 3.722323e-08, 4.780122e-08, 5.511261e-08, 6.232062e-08,\n",
       "       6.961670e-08, 7.705227e-08, 8.466629e-08, 9.248746e-08, 1.004959e-07,\n",
       "       1.087346e-07, 1.173429e-07, 1.263123e-07, 1.355870e-07, 1.453961e-07,\n",
       "       1.558374e-07, 1.668110e-07, 1.782502e-07, 1.902054e-07, 2.028159e-07,\n",
       "       2.161866e-07, 2.304320e-07, 2.454540e-07, 2.614405e-07, 2.784027e-07,\n",
       "       2.963597e-07, 3.153778e-07, 3.354846e-07, 3.568993e-07, 3.798323e-07,\n",
       "       4.043551e-07, 4.303874e-07, 4.586335e-07, 4.913172e-07, 5.355903e-07,\n",
       "       6.523458e-07, 6.947765e-07, 6.966082e-07, 6.964171e-07, 6.961569e-07,\n",
       "       6.958665e-07, 6.955477e-07, 6.951998e-07, 6.948270e-07, 6.944319e-07,\n",
       "       6.940131e-07, 6.935718e-07, 6.931081e-07, 6.926227e-07, 6.921134e-07,\n",
       "       6.915788e-07, 6.910252e-07, 6.904528e-07, 6.898624e-07, 6.892533e-07,\n",
       "       6.886233e-07, 6.879738e-07, 6.873079e-07, 6.866218e-07, 6.859147e-07],\n",
       "      dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>rssoil</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-2685415c-a6bb-4854-a1ff-f8089ed792d2' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-2685415c-a6bb-4854-a1ff-f8089ed792d2' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4508f785-bee9-4760-af0e-fae7cf458a8f' class='xr-var-data-in' type='checkbox'><label for='data-4508f785-bee9-4760-af0e-fae7cf458a8f' 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>longname :</span></dt><dd>Soil evaporation resistance</dd><dt><span>units :</span></dt><dd>s/m</dd></dl></div><div class='xr-var-data'><pre>array([0.000000e+00, 0.000000e+00, 0.000000e+00, 0.000000e+00, 0.000000e+00,\n",
       "       0.000000e+00, 0.000000e+00, 0.000000e+00, 0.000000e+00, 0.000000e+00,\n",
       "       0.000000e+00, 0.000000e+00, 0.000000e+00, 0.000000e+00, 0.000000e+00,\n",
       "       0.000000e+00, 0.000000e+00, 0.000000e+00, 0.000000e+00, 0.000000e+00,\n",
       "       0.000000e+00, 0.000000e+00, 0.000000e+00, 0.000000e+00, 0.000000e+00,\n",
       "       0.000000e+00, 9.394659e-02, 0.000000e+00, 0.000000e+00, 7.045993e-02,\n",
       "       9.394645e-02, 1.174325e-01, 1.174325e-01, 7.045933e-02, 1.080378e+00,\n",
       "       8.384621e+00, 6.545595e+01, 9.572961e+01, 9.619972e+01, 9.620018e+01,\n",
       "       9.620068e+01, 9.620125e+01, 9.620186e+01, 9.620252e+01, 9.620322e+01,\n",
       "       9.620397e+01, 9.620476e+01, 9.620559e+01, 9.620647e+01, 9.620739e+01,\n",
       "       9.620837e+01, 9.620937e+01, 9.621043e+01, 9.621152e+01, 9.621265e+01,\n",
       "       9.621381e+01, 9.621503e+01, 9.621629e+01, 9.621758e+01, 9.621893e+01],\n",
       "      dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>rsveg</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-c91cb158-6a77-4bab-b46a-f3c2b85025a2' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-c91cb158-6a77-4bab-b46a-f3c2b85025a2' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-067b870d-975f-4772-ab61-99095ace2c0d' class='xr-var-data-in' type='checkbox'><label for='data-067b870d-975f-4772-ab61-99095ace2c0d' 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>longname :</span></dt><dd>Vegitation resistance</dd><dt><span>units :</span></dt><dd>s/m</dd></dl></div><div class='xr-var-data'><pre>array([0.000000e+00, 0.000000e+00, 0.000000e+00, 0.000000e+00, 0.000000e+00,\n",
       "       0.000000e+00, 0.000000e+00, 0.000000e+00, 0.000000e+00, 0.000000e+00,\n",
       "       0.000000e+00, 0.000000e+00, 0.000000e+00, 0.000000e+00, 0.000000e+00,\n",
       "       0.000000e+00, 0.000000e+00, 0.000000e+00, 0.000000e+00, 0.000000e+00,\n",
       "       0.000000e+00, 0.000000e+00, 0.000000e+00, 0.000000e+00, 0.000000e+00,\n",
       "       0.000000e+00, 4.374322e-01, 0.000000e+00, 0.000000e+00, 3.356942e-01,\n",
       "       4.268996e-01, 5.538170e-01, 5.699624e-01, 3.926844e-01, 6.133468e+00,\n",
       "       5.088342e+01, 4.378602e+02, 6.864207e+02, 7.053456e+02, 7.149653e+02,\n",
       "       7.176921e+02, 7.113180e+02, 7.078185e+02, 7.045406e+02, 7.014438e+02,\n",
       "       6.970372e+02, 6.910421e+02, 6.898928e+02, 6.793422e+02, 6.696572e+02,\n",
       "       6.610788e+02, 6.556261e+02, 6.497707e+02, 6.409072e+02, 6.333116e+02,\n",
       "       6.232822e+02, 6.130686e+02, 6.089600e+02, 5.988644e+02, 5.879045e+02],\n",
       "      dtype=float32)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-a19daf41-34b9-4e04-a646-f2bee0bc2628' class='xr-section-summary-in' type='checkbox'  checked><label for='section-a19daf41-34b9-4e04-a646-f2bee0bc2628' class='xr-section-summary' >Attributes: <span>(4)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>title :</span></dt><dd>tmser.001.nc</dd><dt><span>history :</span></dt><dd>Created on 20230610 at 131956.291</dd><dt><span>Source :</span></dt><dd>DALES 4.4 git: v4.4</dd><dt><span>Author :</span></dt><dd></dd></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.Dataset>\n",
       "Dimensions:   (time: 60)\n",
       "Coordinates:\n",
       "  * time      (time) float32 60.0 120.0 180.0 ... 3.48e+03 3.54e+03 3.6e+03\n",
       "Data variables: (12/33)\n",
       "    cfrac     (time) float32 ...\n",
       "    zb        (time) float32 ...\n",
       "    zc_av     (time) float32 ...\n",
       "    zc_max    (time) float32 ...\n",
       "    zi        (time) float32 ...\n",
       "    we        (time) float32 ...\n",
       "    ...        ...\n",
       "    rs        (time) float32 ...\n",
       "    ra        (time) float32 ...\n",
       "    cliq      (time) float32 ...\n",
       "    Wl        (time) float32 ...\n",
       "    rssoil    (time) float32 ...\n",
       "    rsveg     (time) float32 ...\n",
       "Attributes:\n",
       "    title:    tmser.001.nc\n",
       "    history:  Created on 20230610 at 131956.291\n",
       "    Source:   DALES 4.4 git: v4.4\n",
       "    Author:   "
      ]
     },
     "execution_count": 59,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tmser = xr.open_dataset('~/tmser.001.nc')\n",
    "\n",
    "tmser"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "340a9789-02e9-4fbd-a0ba-5601f6a1c7b2",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "\n",
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       ".xr-attrs {\n",
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       "\n",
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       "\n",
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       "\n",
       ".xr-attrs dt,\n",
       ".xr-attrs dd {\n",
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       "\n",
       ".xr-attrs dt {\n",
       "  font-weight: normal;\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-attrs dt:hover span {\n",
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       "\n",
       ".xr-attrs dd {\n",
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       "\n",
       ".xr-icon-database,\n",
       ".xr-icon-file-text2 {\n",
       "  display: inline-block;\n",
       "  vertical-align: middle;\n",
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       "  stroke: currentColor;\n",
       "  fill: currentColor;\n",
       "}\n",
       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt;\n",
       "Dimensions:  (xt: 64, xm: 64, yt: 16, ym: 16, time: 0)\n",
       "Coordinates:\n",
       "  * xt       (xt) float32 3.125 9.375 15.62 21.88 ... 378.1 384.4 390.6 396.9\n",
       "  * xm       (xm) float32 0.0 6.25 12.5 18.75 25.0 ... 375.0 381.2 387.5 393.8\n",
       "  * yt       (yt) float32 203.1 209.4 215.6 221.9 ... 278.1 284.4 290.6 296.9\n",
       "  * ym       (ym) float32 200.0 206.2 212.5 218.8 ... 275.0 281.2 287.5 293.8\n",
       "  * time     (time) float32 \n",
       "Data variables:\n",
       "    uxy      (time, yt, xm) float32 \n",
       "    vxy      (time, ym, xt) float32 \n",
       "    wxy      (time, yt, xt) float32 \n",
       "    thlxy    (time, yt, xt) float32 \n",
       "    thvxy    (time, yt, xt) float32 \n",
       "    qtxy     (time, yt, xt) float32 \n",
       "    qlxy     (time, yt, xt) float32 \n",
       "    buoyxy   (time, yt, xt) float32 \n",
       "    qrxy     (time, yt, xt) float32 \n",
       "    nrxy     (time, yt, xt) float32 \n",
       "    e120xy   (time, yt, xt) float32 \n",
       "Attributes:\n",
       "    title:    crossxy.0002.x000y002.001.nc\n",
       "    history:  Created on 20230609 at 191437.628\n",
       "    Source:   DALES 4.4 git: v4.4\n",
       "    Author:   </pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-c6d1da33-2ef3-4234-8202-b2c2a035232e' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-c6d1da33-2ef3-4234-8202-b2c2a035232e' 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'>xt</span>: 64</li><li><span class='xr-has-index'>xm</span>: 64</li><li><span class='xr-has-index'>yt</span>: 16</li><li><span class='xr-has-index'>ym</span>: 16</li><li><span class='xr-has-index'>time</span>: 0</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-e2552ba3-1fdf-434d-9aae-ed563ff889a0' class='xr-section-summary-in' type='checkbox'  checked><label for='section-e2552ba3-1fdf-434d-9aae-ed563ff889a0' class='xr-section-summary' >Coordinates: <span>(5)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>xt</span></div><div class='xr-var-dims'>(xt)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>3.125 9.375 15.62 ... 390.6 396.9</div><input id='attrs-21422c62-b051-443c-952c-dda13aaf7dbb' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-21422c62-b051-443c-952c-dda13aaf7dbb' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b43b1ea3-c968-4ceb-8fd6-c2d39c3063f3' class='xr-var-data-in' type='checkbox'><label for='data-b43b1ea3-c968-4ceb-8fd6-c2d39c3063f3' 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>longname :</span></dt><dd>West-East displacement of cell centers</dd><dt><span>units :</span></dt><dd>m</dd></dl></div><div class='xr-var-data'><pre>array([  3.125,   9.375,  15.625,  21.875,  28.125,  34.375,  40.625,  46.875,\n",
       "        53.125,  59.375,  65.625,  71.875,  78.125,  84.375,  90.625,  96.875,\n",
       "       103.125, 109.375, 115.625, 121.875, 128.125, 134.375, 140.625, 146.875,\n",
       "       153.125, 159.375, 165.625, 171.875, 178.125, 184.375, 190.625, 196.875,\n",
       "       203.125, 209.375, 215.625, 221.875, 228.125, 234.375, 240.625, 246.875,\n",
       "       253.125, 259.375, 265.625, 271.875, 278.125, 284.375, 290.625, 296.875,\n",
       "       303.125, 309.375, 315.625, 321.875, 328.125, 334.375, 340.625, 346.875,\n",
       "       353.125, 359.375, 365.625, 371.875, 378.125, 384.375, 390.625, 396.875],\n",
       "      dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>xm</span></div><div class='xr-var-dims'>(xm)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.0 6.25 12.5 ... 381.2 387.5 393.8</div><input id='attrs-b010c400-9456-4f8b-8451-cb79db53ac3f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b010c400-9456-4f8b-8451-cb79db53ac3f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9f8560ec-4e94-46b1-865b-1d9dabc44b08' class='xr-var-data-in' type='checkbox'><label for='data-9f8560ec-4e94-46b1-865b-1d9dabc44b08' 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>longname :</span></dt><dd>West-East displacement of cell edges</dd><dt><span>units :</span></dt><dd>m</dd></dl></div><div class='xr-var-data'><pre>array([  0.  ,   6.25,  12.5 ,  18.75,  25.  ,  31.25,  37.5 ,  43.75,  50.  ,\n",
       "        56.25,  62.5 ,  68.75,  75.  ,  81.25,  87.5 ,  93.75, 100.  , 106.25,\n",
       "       112.5 , 118.75, 125.  , 131.25, 137.5 , 143.75, 150.  , 156.25, 162.5 ,\n",
       "       168.75, 175.  , 181.25, 187.5 , 193.75, 200.  , 206.25, 212.5 , 218.75,\n",
       "       225.  , 231.25, 237.5 , 243.75, 250.  , 256.25, 262.5 , 268.75, 275.  ,\n",
       "       281.25, 287.5 , 293.75, 300.  , 306.25, 312.5 , 318.75, 325.  , 331.25,\n",
       "       337.5 , 343.75, 350.  , 356.25, 362.5 , 368.75, 375.  , 381.25, 387.5 ,\n",
       "       393.75], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>yt</span></div><div class='xr-var-dims'>(yt)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>203.1 209.4 215.6 ... 290.6 296.9</div><input id='attrs-e90a29c5-b553-49bb-9272-7cfe5b4070f8' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e90a29c5-b553-49bb-9272-7cfe5b4070f8' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c269d98e-5ad3-405a-b5bd-9964deddc9a6' class='xr-var-data-in' type='checkbox'><label for='data-c269d98e-5ad3-405a-b5bd-9964deddc9a6' 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>longname :</span></dt><dd>South-North displacement of cell centers</dd><dt><span>units :</span></dt><dd>m</dd></dl></div><div class='xr-var-data'><pre>array([203.125, 209.375, 215.625, 221.875, 228.125, 234.375, 240.625, 246.875,\n",
       "       253.125, 259.375, 265.625, 271.875, 278.125, 284.375, 290.625, 296.875],\n",
       "      dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>ym</span></div><div class='xr-var-dims'>(ym)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>200.0 206.2 212.5 ... 287.5 293.8</div><input id='attrs-154c25af-8575-4d0a-ac47-c8331b40838d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-154c25af-8575-4d0a-ac47-c8331b40838d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a355ed81-4022-48c3-aa26-f9fb4f5658e3' class='xr-var-data-in' type='checkbox'><label for='data-a355ed81-4022-48c3-aa26-f9fb4f5658e3' 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>longname :</span></dt><dd>South-North displacement of cell edges</dd><dt><span>units :</span></dt><dd>m</dd></dl></div><div class='xr-var-data'><pre>array([200.  , 206.25, 212.5 , 218.75, 225.  , 231.25, 237.5 , 243.75, 250.  ,\n",
       "       256.25, 262.5 , 268.75, 275.  , 281.25, 287.5 , 293.75], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'></div><input id='attrs-eac29e52-d741-4d62-971d-e0c3eeca4097' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-eac29e52-d741-4d62-971d-e0c3eeca4097' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-70a29ba8-934d-4a24-a603-3d14e5fe10af' class='xr-var-data-in' type='checkbox'><label for='data-70a29ba8-934d-4a24-a603-3d14e5fe10af' 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>longname :</span></dt><dd>Time</dd><dt><span>units :</span></dt><dd>s</dd></dl></div><div class='xr-var-data'><pre>array([], dtype=float32)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-3050f89f-05ef-4ac4-90af-af3e216aca32' class='xr-section-summary-in' type='checkbox'  checked><label for='section-3050f89f-05ef-4ac4-90af-af3e216aca32' class='xr-section-summary' >Data variables: <span>(11)</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>uxy</span></div><div class='xr-var-dims'>(time, yt, xm)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-17b7c679-8041-4107-93ef-772e6c149049' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-17b7c679-8041-4107-93ef-772e6c149049' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-379c8186-0b3b-426d-9535-e7bf7e641c55' class='xr-var-data-in' type='checkbox'><label for='data-379c8186-0b3b-426d-9535-e7bf7e641c55' 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>longname :</span></dt><dd>xy crosssections of the West-East velocity</dd><dt><span>units :</span></dt><dd>m/s</dd></dl></div><div class='xr-var-data'><pre>array([], shape=(0, 16, 64), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>vxy</span></div><div class='xr-var-dims'>(time, ym, xt)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-f63d98f9-46af-44da-8ec1-99f12b94f586' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f63d98f9-46af-44da-8ec1-99f12b94f586' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d5f352c8-f00b-4bf5-8cd4-8687e905e92f' class='xr-var-data-in' type='checkbox'><label for='data-d5f352c8-f00b-4bf5-8cd4-8687e905e92f' 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>longname :</span></dt><dd>xy crosssections of the South-North velocity</dd><dt><span>units :</span></dt><dd>m/s</dd></dl></div><div class='xr-var-data'><pre>array([], shape=(0, 16, 64), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>wxy</span></div><div class='xr-var-dims'>(time, yt, xt)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-25213ae9-8026-4769-b5eb-94f3e37eea83' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-25213ae9-8026-4769-b5eb-94f3e37eea83' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ab277fce-a3ed-4108-9555-b726f913f069' class='xr-var-data-in' type='checkbox'><label for='data-ab277fce-a3ed-4108-9555-b726f913f069' 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>longname :</span></dt><dd>xy crosssections of the Vertical velocity</dd><dt><span>units :</span></dt><dd>m/s</dd></dl></div><div class='xr-var-data'><pre>array([], shape=(0, 16, 64), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>thlxy</span></div><div class='xr-var-dims'>(time, yt, xt)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-8bddf145-4766-4592-9f30-4dda9d1dab02' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-8bddf145-4766-4592-9f30-4dda9d1dab02' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3737fc63-3cb5-4c6d-9198-65fe1cbe633e' class='xr-var-data-in' type='checkbox'><label for='data-3737fc63-3cb5-4c6d-9198-65fe1cbe633e' 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>longname :</span></dt><dd>xy crosssections of the Liquid water potential temperature</dd><dt><span>units :</span></dt><dd>K</dd></dl></div><div class='xr-var-data'><pre>array([], shape=(0, 16, 64), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>thvxy</span></div><div class='xr-var-dims'>(time, yt, xt)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-0e69d3b6-54a6-4493-97b5-902c9d3ede1d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-0e69d3b6-54a6-4493-97b5-902c9d3ede1d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-919b04ba-6db5-4f41-bbb2-27a3c7a8038d' class='xr-var-data-in' type='checkbox'><label for='data-919b04ba-6db5-4f41-bbb2-27a3c7a8038d' 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>longname :</span></dt><dd>xy crosssections of the Virtual potential temperature</dd><dt><span>units :</span></dt><dd>K</dd></dl></div><div class='xr-var-data'><pre>array([], shape=(0, 16, 64), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>qtxy</span></div><div class='xr-var-dims'>(time, yt, xt)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-448bc75f-9e0b-471b-9083-6ed391468235' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-448bc75f-9e0b-471b-9083-6ed391468235' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-70d66123-a83b-42e2-994c-6d4e160951e3' class='xr-var-data-in' type='checkbox'><label for='data-70d66123-a83b-42e2-994c-6d4e160951e3' 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>longname :</span></dt><dd>xy crosssections of the Total water specific humidity</dd><dt><span>units :</span></dt><dd>kg/kg</dd></dl></div><div class='xr-var-data'><pre>array([], shape=(0, 16, 64), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>qlxy</span></div><div class='xr-var-dims'>(time, yt, xt)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-498ad806-a993-4554-864c-2d42c703dcbb' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-498ad806-a993-4554-864c-2d42c703dcbb' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-fba328ae-b132-498f-8873-50efb9dac7d2' class='xr-var-data-in' type='checkbox'><label for='data-fba328ae-b132-498f-8873-50efb9dac7d2' 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>longname :</span></dt><dd>xy crosssections of the Liquid water specific humidity</dd><dt><span>units :</span></dt><dd>kg/kg</dd></dl></div><div class='xr-var-data'><pre>array([], shape=(0, 16, 64), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>buoyxy</span></div><div class='xr-var-dims'>(time, yt, xt)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-4b9b9b00-6367-45b4-86d1-a8486bd84204' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-4b9b9b00-6367-45b4-86d1-a8486bd84204' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2f79fcf3-d348-446c-9864-90a23e5ffb4e' class='xr-var-data-in' type='checkbox'><label for='data-2f79fcf3-d348-446c-9864-90a23e5ffb4e' 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>longname :</span></dt><dd>xy crosssection of the Buoyancy</dd><dt><span>units :</span></dt><dd>K</dd></dl></div><div class='xr-var-data'><pre>array([], shape=(0, 16, 64), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>qrxy</span></div><div class='xr-var-dims'>(time, yt, xt)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-a602b665-665b-4c1a-a35c-7fce7c11bb73' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a602b665-665b-4c1a-a35c-7fce7c11bb73' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ec26a535-00ab-453e-a0db-47d3f61016ce' class='xr-var-data-in' type='checkbox'><label for='data-ec26a535-00ab-453e-a0db-47d3f61016ce' 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>longname :</span></dt><dd>xy crosssection of the Rain water specific humidity</dd><dt><span>units :</span></dt><dd>kg/kg</dd></dl></div><div class='xr-var-data'><pre>array([], shape=(0, 16, 64), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>nrxy</span></div><div class='xr-var-dims'>(time, yt, xt)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-a2797873-9ab4-4eb1-ab8c-c1782d6346e1' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a2797873-9ab4-4eb1-ab8c-c1782d6346e1' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-195e9c1a-7c13-4d99-97cb-9956214041b6' class='xr-var-data-in' type='checkbox'><label for='data-195e9c1a-7c13-4d99-97cb-9956214041b6' 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>longname :</span></dt><dd>xy crosssection of the rain droplet number concentration</dd><dt><span>units :</span></dt><dd>-</dd></dl></div><div class='xr-var-data'><pre>array([], shape=(0, 16, 64), dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>e120xy</span></div><div class='xr-var-dims'>(time, yt, xt)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-4edd95d1-0a2d-4c65-b722-176dc0417683' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-4edd95d1-0a2d-4c65-b722-176dc0417683' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f01e3d91-a1f6-4120-b8db-0c0496078c1d' class='xr-var-data-in' type='checkbox'><label for='data-f01e3d91-a1f6-4120-b8db-0c0496078c1d' 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>longname :</span></dt><dd>xy crosssection of sqrt(turbulent kinetic energy)</dd><dt><span>units :</span></dt><dd>m^2/s^2</dd></dl></div><div class='xr-var-data'><pre>array([], shape=(0, 16, 64), dtype=float32)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-200c9abc-7407-4991-a39a-8d6989f66c41' class='xr-section-summary-in' type='checkbox'  checked><label for='section-200c9abc-7407-4991-a39a-8d6989f66c41' class='xr-section-summary' >Attributes: <span>(4)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>title :</span></dt><dd>crossxy.0002.x000y002.001.nc</dd><dt><span>history :</span></dt><dd>Created on 20230609 at 191437.628</dd><dt><span>Source :</span></dt><dd>DALES 4.4 git: v4.4</dd><dt><span>Author :</span></dt><dd></dd></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.Dataset>\n",
       "Dimensions:  (xt: 64, xm: 64, yt: 16, ym: 16, time: 0)\n",
       "Coordinates:\n",
       "  * xt       (xt) float32 3.125 9.375 15.62 21.88 ... 378.1 384.4 390.6 396.9\n",
       "  * xm       (xm) float32 0.0 6.25 12.5 18.75 25.0 ... 375.0 381.2 387.5 393.8\n",
       "  * yt       (yt) float32 203.1 209.4 215.6 221.9 ... 278.1 284.4 290.6 296.9\n",
       "  * ym       (ym) float32 200.0 206.2 212.5 218.8 ... 275.0 281.2 287.5 293.8\n",
       "  * time     (time) float32 \n",
       "Data variables:\n",
       "    uxy      (time, yt, xm) float32 ...\n",
       "    vxy      (time, ym, xt) float32 ...\n",
       "    wxy      (time, yt, xt) float32 ...\n",
       "    thlxy    (time, yt, xt) float32 ...\n",
       "    thvxy    (time, yt, xt) float32 ...\n",
       "    qtxy     (time, yt, xt) float32 ...\n",
       "    qlxy     (time, yt, xt) float32 ...\n",
       "    buoyxy   (time, yt, xt) float32 ...\n",
       "    qrxy     (time, yt, xt) float32 ...\n",
       "    nrxy     (time, yt, xt) float32 ...\n",
       "    e120xy   (time, yt, xt) float32 ...\n",
       "Attributes:\n",
       "    title:    crossxy.0002.x000y002.001.nc\n",
       "    history:  Created on 20230609 at 191437.628\n",
       "    Source:   DALES 4.4 git: v4.4\n",
       "    Author:   "
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "path = '/home/smmrrr/dales/build/stable_runs/'\n",
    "case = 'stable_low_shear'\n",
    "\n",
    "sec = 'crossxy.0002.x000y002.001.nc'\n",
    "\n",
    "\n",
    "cross=xr.open_dataset(path+case+'/'+sec)\n",
    "\n",
    "cross"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "4d907caa-c688-42b3-bd58-7f4386888133",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "d39b2888-95ff-42e7-a940-a96df0bd9f65",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 648x648 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, axs = plt.subplots(nrows=2, figsize = (9, 9))\n",
    "plot1 = profile.mean(dim = ['zt']).thv.plot(ax=axs[0])\n",
    "plot2 = profile.mean(dim = ['time']).thv.plot(ax=axs[1])\n",
    "plt.tight_layout()\n",
    "axs[0].set_title('Virtual Potential Temperature Over Time ' +case)\n",
    "axs[1].set_title('Virtual Potential Temperature Profile Averaged Over Time '+case)\n",
    "plt.tight_layout()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "c7d209e6-009a-4e1f-81e9-c5fe3d85e831",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 1.0, 'Wind Speed (u) at Differnt Times stable_high_shear')"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "profile.sel(time=[time_step]).u.plot.pcolormesh(\n",
    "        # ax=axes[i, 0],\n",
    "        # vmin=-30,\n",
    "        # vmax=2.5,\n",
    "        cmap=\"Spectral_r\",\n",
    "        add_colorbar=True\n",
    "        # extend=\"both\",\n",
    "    \n",
    ", x='time'\n",
    "    ,y='zt'\n",
    ")\n",
    "\n",
    "axs.set_title('Wind Speed (u) at Differnt Times '+case)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "55bd5596-abda-41c4-a5fd-1add2b87bb28",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 1.0, 'Wind Speed (u) at Differnt Times stable_high_shear')"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "profile.u.plot.pcolormesh(\n",
    "        # ax=axes[i, 0],\n",
    "        vmin=-.5,\n",
    "        vmax=2.5,\n",
    "        cmap=\"Spectral_r\",\n",
    "        add_colorbar=True\n",
    "        # extend=\"both\",\n",
    "    \n",
    ", x='time'\n",
    "    ,y='zt'\n",
    ")\n",
    "\n",
    "axs.set_title('Wind Speed (u) at Differnt Times '+case)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "3dbe85b2-5425-4950-824e-4252d8c23ef0",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 1.0, 'Wind Speed (u) at Differnt Times stable_low_shear')"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "profile.u.plot.pcolormesh(\n",
    "        # ax=axes[i, 0],\n",
    "        # vmin=-30,\n",
    "        # vmax=30,\n",
    "            vmax=3,\n",
    "\n",
    "        cmap=\"Spectral_r\",\n",
    "        add_colorbar=True\n",
    "        # extend=\"both\",\n",
    "    , x='time'\n",
    "    ,y='zt'\n",
    "    )\n",
    "\n",
    "axs.set_title('Wind Speed (u) at Differnt Times '+case)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 88,
   "id": "24cadda9-4fa4-409e-a4bd-0fc1cc3402b7",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 648x432 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "time_steps = [300, 15000]  # Example time steps\n",
    "\n",
    "# Create subplots\n",
    "fig, axs = plt.subplots(nrows=1, figsize=(9, 6))\n",
    "\n",
    "# Plot each time step with labels\n",
    "for time_step in time_steps:\n",
    "    profile.sel(time=[time_step]).thv.plot(ax=axs, label=f'Time {time_step}s')\n",
    "\n",
    "# Add any necessary customizations\n",
    "plt.tight_layout()\n",
    "axs.set_title('Virtual Potential Temperature at Differnt Times')\n",
    "axs.legend()\n",
    "\n",
    "# Show the plot\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 123,
   "id": "834138da-3028-4ef6-b2db-795f38589711",
   "metadata": {},
   "outputs": [],
   "source": [
    "Rd = 287 #J/kgK\n",
    "cp = 1005 #J/kgK\n",
    "\n",
    "# pres = fog_profiles.variables['presh'].data\n",
    "profile['pressure'] = profile['presh']/100\n",
    "profile['virt_T'] = profile['thv']/((1000/profile['pressure'])**(Rd/cp))\n",
    "# virt_T = virt_theta/((1000/pressure)**(Rd/cp))\n",
    "# thl= fog_profiles.variables['thl'].data\n",
    "\n",
    "# totalwater_q = fog_profiles.variables['qt'].data\n",
    "# liquid_q = fog_profiles.variables['ql'].data\n",
    "profile['spec_hum'] = profile['qt']-profile['ql']\n",
    "\n",
    "profile['temp'] = profile['virt_T']/(1+0.61*profile['spec_hum'])\n",
    "\n",
    "profile['pres'] = profile['pressure']*units.hPa\n",
    "profile['temp'] = profile['temp']*units.K\n",
    "\n",
    "profile['RH'] = mpcalc.relative_humidity_from_specific_humidity(profile['pres'] , profile['temp'], profile['spec_hum'])*100\n",
    "# height = fog_profiles.variables['zt'].data\n",
    "# time = fog_vars.variables['time'].data\n",
    "mask = profile['RH'] < 100.00001\n",
    "\n",
    "# Set the values to NaN where the mask is True\n",
    "profile['supersat'] = xr.where(mask, np.nan, profile['RH'])\n",
    "\n",
    "# profile['supersat'] = profile['RH'].copy()\n",
    "# profile[profile['supersat']<100] = np.nan\n",
    "# supersat = np.copy(RH)\n",
    "# supersat[supersat<100] = np.nan\n",
    "# avg_S = np.nanmean(supersat, axis=1)\n",
    "# time_prof = fog_profiles.variables['time'].data\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 121,
   "id": "837fa473-5a23-4c81-bae9-58aaf2b2a244",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 648x648 with 4 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "tmser['lwp_bar_m'] = tmser['lwp_bar']*1000\n",
    "\n",
    "fig, axs = plt.subplots(nrows=2, figsize = (9, 9))\n",
    "\n",
    "ax1 = axs[0]   # Line plot axis\n",
    "ax2 = ax1.twinx()  # Bar plot axis\n",
    "\n",
    "tmser.zc_av.plot(ax=ax1, color = 'purple')\n",
    "tmser.cfrac.plot(ax=ax2, alpha=0.01)\n",
    "ax2.fill_between(tmser['time'], tmser.cfrac, color='cyan', alpha=0.1, label='Shaded Area')\n",
    "\n",
    "\n",
    "\n",
    "ax3 = axs[1]   # Line plot axis\n",
    "ax4 = ax3.twinx()  # Bar plot axis\n",
    "\n",
    "tmser.lwp_bar_m.plot(ax=ax3, color = 'purple')\n",
    "tmser.cfrac.plot(ax=ax4, alpha=0.1)\n",
    "ax4.fill_between(tmser['time'], tmser.cfrac, color='cyan', alpha=0.1, label='Shaded Area')\n",
    "\n",
    "# ax5 = axs[2]   # Line plot axis\n",
    "# ax6 = ax5.twinx()  # Bar plot axis\n",
    "\n",
    "# tmser.cliq.plot(ax=ax5, color = 'purple')\n",
    "# tmser.cfrac.plot(ax=ax6, alpha=0.01)\n",
    "# ax6.fill_between(tmser['time'], tmser.cfrac, color='cyan', alpha=0.1, label='Shaded Area')\n",
    "\n",
    "# # Add a legend for each variable\n",
    "ax1.legend(['Cloud Top Height'], loc='lower right', fontsize=14)\n",
    "# ax2.legend(['Cloud Fraction of Grid'], loc='upper right', fontsize=16)\n",
    "ax1.tick_params(axis='both', labelsize=16)\n",
    "ax2.tick_params(axis='both', labelsize=16)\n",
    "# # Set common x-label for the entire subplot\n",
    "ax1.set_xlabel('Time (seconds)', fontsize=18)\n",
    "ax1.set_ylabel('Cloud Top Height (meters)', fontsize=18)\n",
    "ax2.set_ylabel('Cloud Fraction', fontsize=18)\n",
    "ax1.set_title('Cloud Top Height Over Time', fontsize=18, fontweight='bold')\n",
    "\n",
    "# # Add a legend for each variable\n",
    "ax3.legend(['Liquid Water Path'], loc='upper right', fontsize=14)\n",
    "# ax2.legend(['Cloud Fraction of Grid'], loc='upper right', fontsize=16)\n",
    "ax3.tick_params(axis='both', labelsize=16)\n",
    "ax4.tick_params(axis='both', labelsize=16)\n",
    "# # Set common x-label for the entire subplot\n",
    "ax3.set_xlabel('Time (seconds)', fontsize=18)\n",
    "ax3.set_ylabel('Liquid Water Path (grams/meter^2)', fontsize=18)\n",
    "ax4.set_ylabel('Cloud Fraction', fontsize=18)\n",
    "ax3.set_title('Liquid Water Path Over Time', fontsize=18, fontweight='bold')\n",
    "\n",
    "# Adjust subplot spacing\n",
    "plt.tight_layout()\n",
    "\n",
    "# Display the plot\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 124,
   "id": "3ba2cb2b-0f4a-44ac-b5c7-c7907f2f2856",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1008x432 with 3 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, axs = plt.subplots(nrows=1, figsize = (14, 6))\n",
    "ax5 = axs  # Line plot axis\n",
    "# ax6 = ax5.twinx()  # Bar plot axis\n",
    "\n",
    "plot1 = profile.RH.plot.pcolormesh(\n",
    "    ax = ax5,\n",
    "        # ax=axes[i, 0],\n",
    "        # vmin=-30,\n",
    "        # vmax=30,\n",
    "            # vmax=3,\n",
    "        cmap=\"Spectral_r\",\n",
    "        add_colorbar=True\n",
    "        # extend=\"both\",\n",
    "    , x='time'\n",
    "    ,y='zt'\n",
    "    )\n",
    "\n",
    "plot1 = profile.supersat.plot.contour(\n",
    "    ax = ax5,\n",
    "        # ax=axes[i, 0],\n",
    "        # vmin=-30,\n",
    "        # vmax=30,\n",
    "            # vmax=3,\n",
    "        cmap=\"Purples\",\n",
    "        add_colorbar=True\n",
    "        # extend=\"both\",\n",
    "    , x='time'\n",
    "    ,y='zt'\n",
    "    )\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 142,
   "id": "bfd8730e-c6f5-45d2-95c9-47ad5bf2358c",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  grid-column: 1 / -1;\n",
       "  margin-bottom: 5px;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked ~ .xr-section-details {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-array-wrap {\n",
       "  grid-column: 1 / -1;\n",
       "  display: grid;\n",
       "  grid-template-columns: 20px auto;\n",
       "}\n",
       "\n",
       ".xr-array-wrap > label {\n",
       "  grid-column: 1;\n",
       "  vertical-align: top;\n",
       "}\n",
       "\n",
       ".xr-preview {\n",
       "  color: var(--xr-font-color3);\n",
       "}\n",
       "\n",
       ".xr-array-preview,\n",
       ".xr-array-data {\n",
       "  padding: 0 5px !important;\n",
       "  grid-column: 2;\n",
       "}\n",
       "\n",
       ".xr-array-data,\n",
       ".xr-array-in:checked ~ .xr-array-preview {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-array-in:checked ~ .xr-array-data,\n",
       ".xr-array-preview {\n",
       "  display: inline-block;\n",
       "}\n",
       "\n",
       ".xr-dim-list {\n",
       "  display: inline-block !important;\n",
       "  list-style: none;\n",
       "  padding: 0 !important;\n",
       "  margin: 0;\n",
       "}\n",
       "\n",
       ".xr-dim-list li {\n",
       "  display: inline-block;\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "}\n",
       "\n",
       ".xr-dim-list:before {\n",
       "  content: '(';\n",
       "}\n",
       "\n",
       ".xr-dim-list:after {\n",
       "  content: ')';\n",
       "}\n",
       "\n",
       ".xr-dim-list li:not(:last-child):after {\n",
       "  content: ',';\n",
       "  padding-right: 5px;\n",
       "}\n",
       "\n",
       ".xr-has-index {\n",
       "  font-weight: bold;\n",
       "}\n",
       "\n",
       ".xr-var-list,\n",
       ".xr-var-item {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-var-item > div,\n",
       ".xr-var-item label,\n",
       ".xr-var-item > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-even);\n",
       "  margin-bottom: 0;\n",
       "}\n",
       "\n",
       ".xr-var-item > .xr-var-name:hover span {\n",
       "  padding-right: 5px;\n",
       "}\n",
       "\n",
       ".xr-var-list > li:nth-child(odd) > div,\n",
       ".xr-var-list > li:nth-child(odd) > label,\n",
       ".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-odd);\n",
       "}\n",
       "\n",
       ".xr-var-name {\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-var-dims {\n",
       "  grid-column: 2;\n",
       "}\n",
       "\n",
       ".xr-var-dtype {\n",
       "  grid-column: 3;\n",
       "  text-align: right;\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-var-preview {\n",
       "  grid-column: 4;\n",
       "}\n",
       "\n",
       ".xr-var-name,\n",
       ".xr-var-dims,\n",
       ".xr-var-dtype,\n",
       ".xr-preview,\n",
       ".xr-attrs dt {\n",
       "  white-space: nowrap;\n",
       "  overflow: hidden;\n",
       "  text-overflow: ellipsis;\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-var-name:hover,\n",
       ".xr-var-dims:hover,\n",
       ".xr-var-dtype:hover,\n",
       ".xr-attrs dt:hover {\n",
       "  overflow: visible;\n",
       "  width: auto;\n",
       "  z-index: 1;\n",
       "}\n",
       "\n",
       ".xr-var-attrs,\n",
       ".xr-var-data {\n",
       "  display: none;\n",
       "  background-color: var(--xr-background-color) !important;\n",
       "  padding-bottom: 5px !important;\n",
       "}\n",
       "\n",
       ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
       ".xr-var-data-in:checked ~ .xr-var-data {\n",
       "  display: block;\n",
       "}\n",
       "\n",
       ".xr-var-data > table {\n",
       "  float: right;\n",
       "}\n",
       "\n",
       ".xr-var-name span,\n",
       ".xr-var-data,\n",
       ".xr-attrs {\n",
       "  padding-left: 25px !important;\n",
       "}\n",
       "\n",
       ".xr-attrs,\n",
       ".xr-var-attrs,\n",
       ".xr-var-data {\n",
       "  grid-column: 1 / -1;\n",
       "}\n",
       "\n",
       "dl.xr-attrs {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  display: grid;\n",
       "  grid-template-columns: 125px auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt,\n",
       ".xr-attrs dd {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  float: left;\n",
       "  padding-right: 10px;\n",
       "  width: auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt {\n",
       "  font-weight: normal;\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-attrs dt:hover span {\n",
       "  display: inline-block;\n",
       "  background: var(--xr-background-color);\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-attrs dd {\n",
       "  grid-column: 2;\n",
       "  white-space: pre-wrap;\n",
       "  word-break: break-all;\n",
       "}\n",
       "\n",
       ".xr-icon-database,\n",
       ".xr-icon-file-text2 {\n",
       "  display: inline-block;\n",
       "  vertical-align: middle;\n",
       "  width: 1em;\n",
       "  height: 1.5em !important;\n",
       "  stroke-width: 0;\n",
       "  stroke: currentColor;\n",
       "  fill: currentColor;\n",
       "}\n",
       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt;\n",
       "Dimensions:  (yt: 16, ym: 16, zt: 64, zm: 64, time: 250)\n",
       "Coordinates:\n",
       "  * yt       (yt) float32 103.1 109.4 115.6 121.9 ... 178.1 184.4 190.6 196.9\n",
       "  * ym       (ym) float32 100.0 106.2 112.5 118.8 ... 175.0 181.2 187.5 193.8\n",
       "  * zt       (zt) float32 2.0 6.0 10.0 14.0 18.0 ... 242.0 246.0 250.0 254.0\n",
       "  * zm       (zm) float32 0.0 4.0 8.0 12.0 16.0 ... 240.0 244.0 248.0 252.0\n",
       "  * time     (time) float32 60.0 120.0 180.0 ... 1.488e+04 1.494e+04 1.5e+04\n",
       "Data variables:\n",
       "    uyz      (time, zt, yt) float32 ...\n",
       "    vyz      (time, zt, ym) float32 ...\n",
       "    wyz      (time, zm, yt) float32 ...\n",
       "    thlyz    (time, zt, yt) float32 ...\n",
       "    thvyz    (time, zt, yt) float32 ...\n",
       "    qtyz     (time, zt, yt) float32 ...\n",
       "    qlyz     (time, zt, yt) float32 ...\n",
       "    buoyyz   (time, zt, yt) float32 ...\n",
       "    qryz     (time, zt, yt) float32 ...\n",
       "    nryz     (time, zt, yt) float32 ...\n",
       "    e120yz   (time, zt, yt) float32 ...\n",
       "Attributes:\n",
       "    title:    crossyz.x000y001.001.nc\n",
       "    history:  Created on 20230610 at 150901.948\n",
       "    Source:   DALES 4.4 git: v4.4\n",
       "    Author:   </pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-1bf6ae64-5e2b-4f32-8e98-4e25b9f32ad4' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-1bf6ae64-5e2b-4f32-8e98-4e25b9f32ad4' 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'>yt</span>: 16</li><li><span class='xr-has-index'>ym</span>: 16</li><li><span class='xr-has-index'>zt</span>: 64</li><li><span class='xr-has-index'>zm</span>: 64</li><li><span class='xr-has-index'>time</span>: 250</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-a1f6a74c-3dda-48c2-a382-097c8eacf8b6' class='xr-section-summary-in' type='checkbox'  checked><label for='section-a1f6a74c-3dda-48c2-a382-097c8eacf8b6' class='xr-section-summary' >Coordinates: <span>(5)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>yt</span></div><div class='xr-var-dims'>(yt)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>103.1 109.4 115.6 ... 190.6 196.9</div><input id='attrs-c04793c3-114f-43a4-8484-2c11ff8d15a1' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-c04793c3-114f-43a4-8484-2c11ff8d15a1' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6a8a43ca-f974-482b-a067-b45ceecc117e' class='xr-var-data-in' type='checkbox'><label for='data-6a8a43ca-f974-482b-a067-b45ceecc117e' 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>longname :</span></dt><dd>South-North displacement of cell centers</dd><dt><span>units :</span></dt><dd>m</dd></dl></div><div class='xr-var-data'><pre>array([103.125, 109.375, 115.625, 121.875, 128.125, 134.375, 140.625, 146.875,\n",
       "       153.125, 159.375, 165.625, 171.875, 178.125, 184.375, 190.625, 196.875],\n",
       "      dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>ym</span></div><div class='xr-var-dims'>(ym)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>100.0 106.2 112.5 ... 187.5 193.8</div><input id='attrs-721ad86f-57b2-414e-8a00-e0e38d9893c2' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-721ad86f-57b2-414e-8a00-e0e38d9893c2' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ef98812f-0aab-4028-a9b0-8fec1140095a' class='xr-var-data-in' type='checkbox'><label for='data-ef98812f-0aab-4028-a9b0-8fec1140095a' 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>longname :</span></dt><dd>South-North displacement of cell edges</dd><dt><span>units :</span></dt><dd>m</dd></dl></div><div class='xr-var-data'><pre>array([100.  , 106.25, 112.5 , 118.75, 125.  , 131.25, 137.5 , 143.75, 150.  ,\n",
       "       156.25, 162.5 , 168.75, 175.  , 181.25, 187.5 , 193.75], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>zt</span></div><div class='xr-var-dims'>(zt)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>2.0 6.0 10.0 ... 246.0 250.0 254.0</div><input id='attrs-a28a0acc-b00e-4c83-a2e1-041fe755e09d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a28a0acc-b00e-4c83-a2e1-041fe755e09d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f968aacf-008a-418a-8b27-5107cb64b134' class='xr-var-data-in' type='checkbox'><label for='data-f968aacf-008a-418a-8b27-5107cb64b134' 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>longname :</span></dt><dd>Vertical displacement of cell centers</dd><dt><span>units :</span></dt><dd>m</dd></dl></div><div class='xr-var-data'><pre>array([  2.,   6.,  10.,  14.,  18.,  22.,  26.,  30.,  34.,  38.,  42.,  46.,\n",
       "        50.,  54.,  58.,  62.,  66.,  70.,  74.,  78.,  82.,  86.,  90.,  94.,\n",
       "        98., 102., 106., 110., 114., 118., 122., 126., 130., 134., 138., 142.,\n",
       "       146., 150., 154., 158., 162., 166., 170., 174., 178., 182., 186., 190.,\n",
       "       194., 198., 202., 206., 210., 214., 218., 222., 226., 230., 234., 238.,\n",
       "       242., 246., 250., 254.], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>zm</span></div><div class='xr-var-dims'>(zm)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.0 4.0 8.0 ... 244.0 248.0 252.0</div><input id='attrs-3d878493-d7fa-41e8-8e99-02bacd552be6' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3d878493-d7fa-41e8-8e99-02bacd552be6' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e38c3523-67ed-4c3f-a132-e794eda385e0' class='xr-var-data-in' type='checkbox'><label for='data-e38c3523-67ed-4c3f-a132-e794eda385e0' 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>longname :</span></dt><dd>Vertical displacement of cell edges</dd><dt><span>units :</span></dt><dd>m</dd></dl></div><div class='xr-var-data'><pre>array([  0.,   4.,   8.,  12.,  16.,  20.,  24.,  28.,  32.,  36.,  40.,  44.,\n",
       "        48.,  52.,  56.,  60.,  64.,  68.,  72.,  76.,  80.,  84.,  88.,  92.,\n",
       "        96., 100., 104., 108., 112., 116., 120., 124., 128., 132., 136., 140.,\n",
       "       144., 148., 152., 156., 160., 164., 168., 172., 176., 180., 184., 188.,\n",
       "       192., 196., 200., 204., 208., 212., 216., 220., 224., 228., 232., 236.,\n",
       "       240., 244., 248., 252.], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>60.0 120.0 ... 1.494e+04 1.5e+04</div><input id='attrs-d2c916e3-e4fa-4004-ac25-c95e1c639b9d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d2c916e3-e4fa-4004-ac25-c95e1c639b9d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-32faa5d2-66cb-4877-a10c-ea1d34c1f01b' class='xr-var-data-in' type='checkbox'><label for='data-32faa5d2-66cb-4877-a10c-ea1d34c1f01b' 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>longname :</span></dt><dd>Time</dd><dt><span>units :</span></dt><dd>s</dd></dl></div><div class='xr-var-data'><pre>array([   60.,   120.,   180., ..., 14880., 14940., 15000.], dtype=float32)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-a85b7cc5-f931-467c-a1bf-2799e32e3a1d' class='xr-section-summary-in' type='checkbox'  checked><label for='section-a85b7cc5-f931-467c-a1bf-2799e32e3a1d' class='xr-section-summary' >Data variables: <span>(11)</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>uyz</span></div><div class='xr-var-dims'>(time, zt, yt)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-e1eb442b-98ef-4297-8b1f-58bd75902a27' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e1eb442b-98ef-4297-8b1f-58bd75902a27' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-addc6474-9693-40ad-b0e7-75df2da236ad' class='xr-var-data-in' type='checkbox'><label for='data-addc6474-9693-40ad-b0e7-75df2da236ad' 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>longname :</span></dt><dd>yz crosssection of the West-East velocity</dd><dt><span>units :</span></dt><dd>m/s</dd></dl></div><div class='xr-var-data'><pre>[256000 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>vyz</span></div><div class='xr-var-dims'>(time, zt, ym)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-216f5d99-e1dd-4772-bd31-205664846687' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-216f5d99-e1dd-4772-bd31-205664846687' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6277426f-0710-4d50-8d17-0cce10ffcbf9' class='xr-var-data-in' type='checkbox'><label for='data-6277426f-0710-4d50-8d17-0cce10ffcbf9' 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>longname :</span></dt><dd>yz crosssection of the South-North velocity</dd><dt><span>units :</span></dt><dd>m/s</dd></dl></div><div class='xr-var-data'><pre>[256000 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>wyz</span></div><div class='xr-var-dims'>(time, zm, yt)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-52ff6d1c-64d4-4cee-a524-6f6025a8f9d4' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-52ff6d1c-64d4-4cee-a524-6f6025a8f9d4' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5515d85b-306a-4a25-bbf4-4a940796055c' class='xr-var-data-in' type='checkbox'><label for='data-5515d85b-306a-4a25-bbf4-4a940796055c' 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>longname :</span></dt><dd>yz crosssection of the Vertical velocity</dd><dt><span>units :</span></dt><dd>m/s</dd></dl></div><div class='xr-var-data'><pre>[256000 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>thlyz</span></div><div class='xr-var-dims'>(time, zt, yt)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-34b458f8-576d-4618-9a2e-ecdc357a5b29' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-34b458f8-576d-4618-9a2e-ecdc357a5b29' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e8dc2355-d0ca-4231-abd5-952400e34f69' class='xr-var-data-in' type='checkbox'><label for='data-e8dc2355-d0ca-4231-abd5-952400e34f69' 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>longname :</span></dt><dd>yz crosssection of the Liquid water potential temperature</dd><dt><span>units :</span></dt><dd>K</dd></dl></div><div class='xr-var-data'><pre>[256000 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>thvyz</span></div><div class='xr-var-dims'>(time, zt, yt)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-5bd6abde-79af-47ea-bc2d-1db8eadecbd0' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-5bd6abde-79af-47ea-bc2d-1db8eadecbd0' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-02d29ad2-ade8-44bf-9b55-446ac9b6a135' class='xr-var-data-in' type='checkbox'><label for='data-02d29ad2-ade8-44bf-9b55-446ac9b6a135' 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>longname :</span></dt><dd>yz crosssection of the Virtual potential temperature</dd><dt><span>units :</span></dt><dd>K</dd></dl></div><div class='xr-var-data'><pre>[256000 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>qtyz</span></div><div class='xr-var-dims'>(time, zt, yt)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-0a711969-dae2-4433-baab-aadcce331144' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-0a711969-dae2-4433-baab-aadcce331144' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-33a141e0-2e24-43d9-a5c8-33aa44fbcf76' class='xr-var-data-in' type='checkbox'><label for='data-33a141e0-2e24-43d9-a5c8-33aa44fbcf76' 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>longname :</span></dt><dd>yz crosssection of the Total water specific humidity</dd><dt><span>units :</span></dt><dd>kg/kg</dd></dl></div><div class='xr-var-data'><pre>[256000 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>qlyz</span></div><div class='xr-var-dims'>(time, zt, yt)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-52cd7392-2687-4abb-8ea6-31b96724c966' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-52cd7392-2687-4abb-8ea6-31b96724c966' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4b31c9ed-8349-4221-ad90-c3fd8d5c0f4e' class='xr-var-data-in' type='checkbox'><label for='data-4b31c9ed-8349-4221-ad90-c3fd8d5c0f4e' 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>longname :</span></dt><dd>yz crosssection of the Liquid water specific humidity</dd><dt><span>units :</span></dt><dd>kg/kg</dd></dl></div><div class='xr-var-data'><pre>[256000 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>buoyyz</span></div><div class='xr-var-dims'>(time, zt, yt)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-11579c0f-35cc-48b1-b15e-e827cc346603' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-11579c0f-35cc-48b1-b15e-e827cc346603' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ef3d03f5-466c-4b46-9226-4b55ef0b7fb5' class='xr-var-data-in' type='checkbox'><label for='data-ef3d03f5-466c-4b46-9226-4b55ef0b7fb5' 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>longname :</span></dt><dd>yz crosssection of the Buoyancy</dd><dt><span>units :</span></dt><dd>K</dd></dl></div><div class='xr-var-data'><pre>[256000 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>qryz</span></div><div class='xr-var-dims'>(time, zt, yt)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-b3edc05b-cf5d-4e73-9cc6-a6b9b545222c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b3edc05b-cf5d-4e73-9cc6-a6b9b545222c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4dd0cfa0-2357-4912-8c6f-9237f639cc93' class='xr-var-data-in' type='checkbox'><label for='data-4dd0cfa0-2357-4912-8c6f-9237f639cc93' 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>longname :</span></dt><dd>yz crosssection of the Rain water specific humidity</dd><dt><span>units :</span></dt><dd>kg/kg</dd></dl></div><div class='xr-var-data'><pre>[256000 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>nryz</span></div><div class='xr-var-dims'>(time, zt, yt)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-bc0a7c8d-ad3e-47f2-91f3-46f1bc5177c4' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-bc0a7c8d-ad3e-47f2-91f3-46f1bc5177c4' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-182171e2-5ff9-4ef1-86d4-2fe61986fec9' class='xr-var-data-in' type='checkbox'><label for='data-182171e2-5ff9-4ef1-86d4-2fe61986fec9' 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>longname :</span></dt><dd>yz crosssection of the Number concentration</dd><dt><span>units :</span></dt><dd>-</dd></dl></div><div class='xr-var-data'><pre>[256000 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>e120yz</span></div><div class='xr-var-dims'>(time, zt, yt)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-ad545ef8-5962-4cff-971c-3df6c37561fd' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ad545ef8-5962-4cff-971c-3df6c37561fd' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8372c0dd-c849-4dd4-b03d-78d06a0e0e9f' class='xr-var-data-in' type='checkbox'><label for='data-8372c0dd-c849-4dd4-b03d-78d06a0e0e9f' 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>longname :</span></dt><dd>yz crosssection of sqrt(turbulent kinetic energy)</dd><dt><span>units :</span></dt><dd>m^2/s^2</dd></dl></div><div class='xr-var-data'><pre>[256000 values with dtype=float32]</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-03bbf2d7-c59d-4cdf-baa6-2e909feb8688' class='xr-section-summary-in' type='checkbox'  checked><label for='section-03bbf2d7-c59d-4cdf-baa6-2e909feb8688' class='xr-section-summary' >Attributes: <span>(4)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>title :</span></dt><dd>crossyz.x000y001.001.nc</dd><dt><span>history :</span></dt><dd>Created on 20230610 at 150901.948</dd><dt><span>Source :</span></dt><dd>DALES 4.4 git: v4.4</dd><dt><span>Author :</span></dt><dd></dd></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.Dataset>\n",
       "Dimensions:  (yt: 16, ym: 16, zt: 64, zm: 64, time: 250)\n",
       "Coordinates:\n",
       "  * yt       (yt) float32 103.1 109.4 115.6 121.9 ... 178.1 184.4 190.6 196.9\n",
       "  * ym       (ym) float32 100.0 106.2 112.5 118.8 ... 175.0 181.2 187.5 193.8\n",
       "  * zt       (zt) float32 2.0 6.0 10.0 14.0 18.0 ... 242.0 246.0 250.0 254.0\n",
       "  * zm       (zm) float32 0.0 4.0 8.0 12.0 16.0 ... 240.0 244.0 248.0 252.0\n",
       "  * time     (time) float32 60.0 120.0 180.0 ... 1.488e+04 1.494e+04 1.5e+04\n",
       "Data variables:\n",
       "    uyz      (time, zt, yt) float32 ...\n",
       "    vyz      (time, zt, ym) float32 ...\n",
       "    wyz      (time, zm, yt) float32 ...\n",
       "    thlyz    (time, zt, yt) float32 ...\n",
       "    thvyz    (time, zt, yt) float32 ...\n",
       "    qtyz     (time, zt, yt) float32 ...\n",
       "    qlyz     (time, zt, yt) float32 ...\n",
       "    buoyyz   (time, zt, yt) float32 ...\n",
       "    qryz     (time, zt, yt) float32 ...\n",
       "    nryz     (time, zt, yt) float32 ...\n",
       "    e120yz   (time, zt, yt) float32 ...\n",
       "Attributes:\n",
       "    title:    crossyz.x000y001.001.nc\n",
       "    history:  Created on 20230610 at 150901.948\n",
       "    Source:   DALES 4.4 git: v4.4\n",
       "    Author:   "
      ]
     },
     "execution_count": 142,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "path = '~/dales/build/stable_runs/high_shear_output/'\n",
    "file = 'crossyz.x000y001.001.nc'\n",
    "cross = xr.open_dataset(path + file)\n",
    "cross"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 157,
   "id": "e434a99f-64ca-4c2a-bb1b-1e8cb7b6b6d3",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.collections.QuadMesh at 0x14daedc902e0>"
      ]
     },
     "execution_count": 157,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "cross.sel(time = [1000], method=\"nearest\").buoyyz.plot()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 154,
   "id": "6ca7b549-b113-41e1-aaad-282aecd05c0b",
   "metadata": {},
   "outputs": [
    {
     "ename": "TypeError",
     "evalue": "'Axes' object is not iterable",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mTypeError\u001b[0m                                 Traceback (most recent call last)",
      "\u001b[0;32m/tmp/ipykernel_1146863/1533178383.py\u001b[0m in \u001b[0;36m<cell line: 20>\u001b[0;34m()\u001b[0m\n\u001b[1;32m     18\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     19\u001b[0m \u001b[0;31m# Create the animation\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 20\u001b[0;31m \u001b[0manim\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mFuncAnimation\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mfig\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mupdate\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mframes\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mcross\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mtime\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0msize\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0minit_func\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0minit\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mblit\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mTrue\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m     21\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     22\u001b[0m \u001b[0;31m# Display the animation\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/miniconda3/envs/condaforge/lib/python3.10/site-packages/matplotlib/animation.py\u001b[0m in \u001b[0;36m__init__\u001b[0;34m(self, fig, func, frames, init_func, fargs, save_count, cache_frame_data, **kwargs)\u001b[0m\n\u001b[1;32m   1692\u001b[0m         \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_save_seq\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m[\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1693\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1694\u001b[0;31m         \u001b[0msuper\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m__init__\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mfig\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   1695\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1696\u001b[0m         \u001b[0;31m# Need to reset the saved seq, since right now it will contain data\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/miniconda3/envs/condaforge/lib/python3.10/site-packages/matplotlib/animation.py\u001b[0m in \u001b[0;36m__init__\u001b[0;34m(self, fig, interval, repeat_delay, repeat, event_source, *args, **kwargs)\u001b[0m\n\u001b[1;32m   1414\u001b[0m         \u001b[0;32mif\u001b[0m \u001b[0mevent_source\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1415\u001b[0m             \u001b[0mevent_source\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mfig\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcanvas\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mnew_timer\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0minterval\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_interval\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1416\u001b[0;31m         \u001b[0msuper\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m__init__\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mfig\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mevent_source\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0mevent_source\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m*\u001b[0m\u001b[0margs\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   1417\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1418\u001b[0m     \u001b[0;32mdef\u001b[0m \u001b[0m_step\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m*\u001b[0m\u001b[0margs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/miniconda3/envs/condaforge/lib/python3.10/site-packages/matplotlib/animation.py\u001b[0m in \u001b[0;36m__init__\u001b[0;34m(self, fig, event_source, blit)\u001b[0m\n\u001b[1;32m    878\u001b[0m                                                       self._stop)\n\u001b[1;32m    879\u001b[0m         \u001b[0;32mif\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_blit\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 880\u001b[0;31m             \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_setup_blit\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    881\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    882\u001b[0m     \u001b[0;32mdef\u001b[0m \u001b[0m__del__\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/miniconda3/envs/condaforge/lib/python3.10/site-packages/matplotlib/animation.py\u001b[0m in \u001b[0;36m_setup_blit\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m   1207\u001b[0m         \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_drawn_artists\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m[\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1208\u001b[0m         \u001b[0;31m# _post_draw needs to be called first to initialize the renderer\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1209\u001b[0;31m         \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_post_draw\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;32mNone\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_blit\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   1210\u001b[0m         \u001b[0;31m# Then we need to clear the Frame for the initial draw\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1211\u001b[0m         \u001b[0;31m# This is typically handled in _on_resize because QT and Tk\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/miniconda3/envs/condaforge/lib/python3.10/site-packages/matplotlib/animation.py\u001b[0m in \u001b[0;36m_post_draw\u001b[0;34m(self, framedata, blit)\u001b[0m\n\u001b[1;32m   1162\u001b[0m             \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_blit_draw\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_drawn_artists\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1163\u001b[0m         \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1164\u001b[0;31m             \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_fig\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcanvas\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mdraw_idle\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   1165\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1166\u001b[0m     \u001b[0;31m# The rest of the code in this class is to facilitate easy blitting\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/miniconda3/envs/condaforge/lib/python3.10/site-packages/matplotlib/backend_bases.py\u001b[0m in \u001b[0;36mdraw_idle\u001b[0;34m(self, *args, **kwargs)\u001b[0m\n\u001b[1;32m   2080\u001b[0m         \u001b[0;32mif\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_is_idle_drawing\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   2081\u001b[0m             \u001b[0;32mwith\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_idle_draw_cntx\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 2082\u001b[0;31m                 \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mdraw\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m*\u001b[0m\u001b[0margs\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   2083\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   2084\u001b[0m     \u001b[0;34m@\u001b[0m\u001b[0mproperty\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/miniconda3/envs/condaforge/lib/python3.10/site-packages/matplotlib/backends/backend_agg.py\u001b[0m in \u001b[0;36mdraw\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m    398\u001b[0m              (self.toolbar._wait_cursor_for_draw_cm() if self.toolbar\n\u001b[1;32m    399\u001b[0m               else nullcontext()):\n\u001b[0;32m--> 400\u001b[0;31m             \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mfigure\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mdraw\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mrenderer\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    401\u001b[0m             \u001b[0;31m# A GUI class may be need to update a window using this draw, so\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    402\u001b[0m             \u001b[0;31m# don't forget to call the superclass.\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/miniconda3/envs/condaforge/lib/python3.10/site-packages/matplotlib/artist.py\u001b[0m in \u001b[0;36mdraw_wrapper\u001b[0;34m(artist, renderer, *args, **kwargs)\u001b[0m\n\u001b[1;32m     93\u001b[0m     \u001b[0;34m@\u001b[0m\u001b[0mwraps\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mdraw\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     94\u001b[0m     \u001b[0;32mdef\u001b[0m \u001b[0mdraw_wrapper\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0martist\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mrenderer\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m*\u001b[0m\u001b[0margs\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 95\u001b[0;31m         \u001b[0mresult\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mdraw\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0martist\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mrenderer\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m*\u001b[0m\u001b[0margs\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m     96\u001b[0m         \u001b[0;32mif\u001b[0m \u001b[0mrenderer\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_rasterizing\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     97\u001b[0m             \u001b[0mrenderer\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mstop_rasterizing\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/miniconda3/envs/condaforge/lib/python3.10/site-packages/matplotlib/artist.py\u001b[0m in \u001b[0;36mdraw_wrapper\u001b[0;34m(artist, renderer)\u001b[0m\n\u001b[1;32m     70\u001b[0m                 \u001b[0mrenderer\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mstart_filter\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     71\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 72\u001b[0;31m             \u001b[0;32mreturn\u001b[0m \u001b[0mdraw\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0martist\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mrenderer\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m     73\u001b[0m         \u001b[0;32mfinally\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     74\u001b[0m             \u001b[0;32mif\u001b[0m \u001b[0martist\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mget_agg_filter\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/miniconda3/envs/condaforge/lib/python3.10/site-packages/matplotlib/figure.py\u001b[0m in \u001b[0;36mdraw\u001b[0;34m(self, renderer)\u001b[0m\n\u001b[1;32m   3148\u001b[0m             \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mstale\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;32mFalse\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   3149\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 3150\u001b[0;31m         \u001b[0mDrawEvent\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\"draw_event\"\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcanvas\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mrenderer\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_process\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   3151\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   3152\u001b[0m     \u001b[0;32mdef\u001b[0m \u001b[0mdraw_without_rendering\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/miniconda3/envs/condaforge/lib/python3.10/site-packages/matplotlib/backend_bases.py\u001b[0m in \u001b[0;36m_process\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m   1261\u001b[0m     \u001b[0;32mdef\u001b[0m \u001b[0m_process\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1262\u001b[0m         \u001b[0;34m\"\"\"Generate an event with name ``self.name`` on ``self.canvas``.\"\"\"\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1263\u001b[0;31m         \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcanvas\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mcallbacks\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mprocess\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mname\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   1264\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1265\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/miniconda3/envs/condaforge/lib/python3.10/site-packages/matplotlib/cbook/__init__.py\u001b[0m in \u001b[0;36mprocess\u001b[0;34m(self, s, *args, **kwargs)\u001b[0m\n\u001b[1;32m    307\u001b[0m                 \u001b[0;32mexcept\u001b[0m \u001b[0mException\u001b[0m \u001b[0;32mas\u001b[0m \u001b[0mexc\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    308\u001b[0m                     \u001b[0;32mif\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mexception_handler\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 309\u001b[0;31m                         \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mexception_handler\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mexc\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    310\u001b[0m                     \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    311\u001b[0m                         \u001b[0;32mraise\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/miniconda3/envs/condaforge/lib/python3.10/site-packages/matplotlib/cbook/__init__.py\u001b[0m in \u001b[0;36m_exception_printer\u001b[0;34m(exc)\u001b[0m\n\u001b[1;32m     94\u001b[0m \u001b[0;32mdef\u001b[0m \u001b[0m_exception_printer\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mexc\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     95\u001b[0m     \u001b[0;32mif\u001b[0m \u001b[0m_get_running_interactive_framework\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;32min\u001b[0m \u001b[0;34m[\u001b[0m\u001b[0;34m\"headless\"\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 96\u001b[0;31m         \u001b[0;32mraise\u001b[0m \u001b[0mexc\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m     97\u001b[0m     \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     98\u001b[0m         \u001b[0mtraceback\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mprint_exc\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/miniconda3/envs/condaforge/lib/python3.10/site-packages/matplotlib/cbook/__init__.py\u001b[0m in \u001b[0;36mprocess\u001b[0;34m(self, s, *args, **kwargs)\u001b[0m\n\u001b[1;32m    302\u001b[0m             \u001b[0;32mif\u001b[0m \u001b[0mfunc\u001b[0m \u001b[0;32mis\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0;32mNone\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    303\u001b[0m                 \u001b[0;32mtry\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 304\u001b[0;31m                     \u001b[0mfunc\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m*\u001b[0m\u001b[0margs\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    305\u001b[0m                 \u001b[0;31m# this does not capture KeyboardInterrupt, SystemExit,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    306\u001b[0m                 \u001b[0;31m# and GeneratorExit\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/miniconda3/envs/condaforge/lib/python3.10/site-packages/matplotlib/animation.py\u001b[0m in \u001b[0;36m_start\u001b[0;34m(self, *args)\u001b[0m\n\u001b[1;32m    902\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    903\u001b[0m         \u001b[0;31m# Now do any initial draw\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 904\u001b[0;31m         \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_init_draw\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    905\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    906\u001b[0m         \u001b[0;31m# Add our callback for stepping the animation and\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/miniconda3/envs/condaforge/lib/python3.10/site-packages/matplotlib/animation.py\u001b[0m in \u001b[0;36m_init_draw\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m   1753\u001b[0m                     raise RuntimeError('The init_func must return a '\n\u001b[1;32m   1754\u001b[0m                                        'sequence of Artist objects.')\n\u001b[0;32m-> 1755\u001b[0;31m                 \u001b[0;32mfor\u001b[0m \u001b[0ma\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_drawn_artists\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   1756\u001b[0m                     \u001b[0ma\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mset_animated\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_blit\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1757\u001b[0m         \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_save_seq\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m[\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;31mTypeError\u001b[0m: 'Axes' object is not iterable"
     ]
    },
    {
     "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": [
    "fig, ax = plt.subplots()\n",
    "# Define the initialization function\n",
    "def init():\n",
    "    ax.set_xlabel('y(m)')\n",
    "    ax.set_ylabel('z(m)')\n",
    "    ax.set_title('Animated Plot')\n",
    "    return ax\n",
    "\n",
    "# Define the update function\n",
    "def update(frame):\n",
    "    ax.cla()  # Clear the axis for the new frame\n",
    "    cross.buoyyz[frame].plot(ax=ax, cmap='viridis', add_colorbar=False)\n",
    "    plt.colorbar(mappable=ax.images[-1], ax=ax)\n",
    "    ax.set_xlabel('y(m)')\n",
    "    ax.set_ylabel('z(m)')\n",
    "    ax.set_title(f'Time = {data.time[frame]}')\n",
    "    return ax\n",
    "\n",
    "# Create the animation\n",
    "anim = FuncAnimation(fig, update, frames=cross.time.size, init_func=init, blit=True)\n",
    "\n",
    "# Display the animation\n",
    "plt.show()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 146,
   "id": "79ff5db7-e3e2-4375-bae2-4ba807cb97cb",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.collections.QuadMesh at 0x14daee6edc30>"
      ]
     },
     "execution_count": 146,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "cross.sel(time = [1000], method=\"nearest\").qtyz.plot()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 145,
   "id": "8f7a6a9a-3b73-454f-a90f-fa3af0ffd692",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.collections.QuadMesh at 0x14daed148d90>"
      ]
     },
     "execution_count": 145,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "cross.sel(time = [3500], method=\"nearest\").qlyz.plot()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 140,
   "id": "5920a02b-4d4a-4d59-b6a1-74a8d9035690",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.collections.QuadMesh at 0x14daed30c2e0>"
      ]
     },
     "execution_count": 140,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "cross.sel(time = [1000], method=\"nearest\").vxy.plot()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 137,
   "id": "e865f77a-be1d-4ad5-9ab2-fef7f2ef1a2d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.collections.QuadMesh at 0x14daed67ebf0>"
      ]
     },
     "execution_count": 137,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "cross.sel(time = [3000], method=\"nearest\").wxy.plot()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 138,
   "id": "be9c3b2b-91d4-42ec-a206-b6ca42ef3839",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.collections.QuadMesh at 0x14daed57a200>"
      ]
     },
     "execution_count": 138,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "cross.sel(time = [2000], method=\"nearest\").wxy.plot()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "id": "d926c42e-0ce8-491e-8433-13bba282ea57",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 648x864 with 3 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, axs = plt.subplots(nrows=3, figsize = (9, 12))\n",
    "plot1 = tmser.cfrac.plot(ax=axs[0])\n",
    "plot2 = tmser.zc_av.plot(ax=axs[1])\n",
    "plot3 = tmser.lwp_bar.plot(ax=axs[2])\n",
    "\n",
    "plt.tight_layout()\n",
    "axs[0].set_title('Cloud Fraction Over Time ')\n",
    "axs[1].set_title('Cloud Top Height Over Time ')\n",
    "axs[2].set_title('Liquid Water Path Over Time ')\n",
    "# axs[3].set_title('Liquid Water Path Over Time ')\n",
    "plt.tight_layout()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "58c9b153-f764-42f2-bce3-7ab937b4022c",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  color: var(--xr-font-color2);\n",
       "  font-weight: 500;\n",
       "}\n",
       "\n",
       ".xr-section-summary > span {\n",
       "  display: inline-block;\n",
       "  padding-left: 0.5em;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:disabled + label {\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-section-summary-in + label:before {\n",
       "  display: inline-block;\n",
       "  content: '►';\n",
       "  font-size: 11px;\n",
       "  width: 15px;\n",
       "  text-align: center;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:disabled + label:before {\n",
       "  color: var(--xr-disabled-color);\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked + label:before {\n",
       "  content: '▼';\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked + label > span {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-section-summary,\n",
       ".xr-section-inline-details {\n",
       "  padding-top: 4px;\n",
       "  padding-bottom: 4px;\n",
       "}\n",
       "\n",
       ".xr-section-inline-details {\n",
       "  grid-column: 2 / -1;\n",
       "}\n",
       "\n",
       ".xr-section-details {\n",
       "  display: none;\n",
       "  grid-column: 1 / -1;\n",
       "  margin-bottom: 5px;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked ~ .xr-section-details {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-array-wrap {\n",
       "  grid-column: 1 / -1;\n",
       "  display: grid;\n",
       "  grid-template-columns: 20px auto;\n",
       "}\n",
       "\n",
       ".xr-array-wrap > label {\n",
       "  grid-column: 1;\n",
       "  vertical-align: top;\n",
       "}\n",
       "\n",
       ".xr-preview {\n",
       "  color: var(--xr-font-color3);\n",
       "}\n",
       "\n",
       ".xr-array-preview,\n",
       ".xr-array-data {\n",
       "  padding: 0 5px !important;\n",
       "  grid-column: 2;\n",
       "}\n",
       "\n",
       ".xr-array-data,\n",
       ".xr-array-in:checked ~ .xr-array-preview {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-array-in:checked ~ .xr-array-data,\n",
       ".xr-array-preview {\n",
       "  display: inline-block;\n",
       "}\n",
       "\n",
       ".xr-dim-list {\n",
       "  display: inline-block !important;\n",
       "  list-style: none;\n",
       "  padding: 0 !important;\n",
       "  margin: 0;\n",
       "}\n",
       "\n",
       ".xr-dim-list li {\n",
       "  display: inline-block;\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "}\n",
       "\n",
       ".xr-dim-list:before {\n",
       "  content: '(';\n",
       "}\n",
       "\n",
       ".xr-dim-list:after {\n",
       "  content: ')';\n",
       "}\n",
       "\n",
       ".xr-dim-list li:not(:last-child):after {\n",
       "  content: ',';\n",
       "  padding-right: 5px;\n",
       "}\n",
       "\n",
       ".xr-has-index {\n",
       "  font-weight: bold;\n",
       "}\n",
       "\n",
       ".xr-var-list,\n",
       ".xr-var-item {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-var-item > div,\n",
       ".xr-var-item label,\n",
       ".xr-var-item > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-even);\n",
       "  margin-bottom: 0;\n",
       "}\n",
       "\n",
       ".xr-var-item > .xr-var-name:hover span {\n",
       "  padding-right: 5px;\n",
       "}\n",
       "\n",
       ".xr-var-list > li:nth-child(odd) > div,\n",
       ".xr-var-list > li:nth-child(odd) > label,\n",
       ".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-odd);\n",
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       "\n",
       ".xr-var-name {\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-var-dims {\n",
       "  grid-column: 2;\n",
       "}\n",
       "\n",
       ".xr-var-dtype {\n",
       "  grid-column: 3;\n",
       "  text-align: right;\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-var-preview {\n",
       "  grid-column: 4;\n",
       "}\n",
       "\n",
       ".xr-var-name,\n",
       ".xr-var-dims,\n",
       ".xr-var-dtype,\n",
       ".xr-preview,\n",
       ".xr-attrs dt {\n",
       "  white-space: nowrap;\n",
       "  overflow: hidden;\n",
       "  text-overflow: ellipsis;\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-var-name:hover,\n",
       ".xr-var-dims:hover,\n",
       ".xr-var-dtype:hover,\n",
       ".xr-attrs dt:hover {\n",
       "  overflow: visible;\n",
       "  width: auto;\n",
       "  z-index: 1;\n",
       "}\n",
       "\n",
       ".xr-var-attrs,\n",
       ".xr-var-data {\n",
       "  display: none;\n",
       "  background-color: var(--xr-background-color) !important;\n",
       "  padding-bottom: 5px !important;\n",
       "}\n",
       "\n",
       ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
       ".xr-var-data-in:checked ~ .xr-var-data {\n",
       "  display: block;\n",
       "}\n",
       "\n",
       ".xr-var-data > table {\n",
       "  float: right;\n",
       "}\n",
       "\n",
       ".xr-var-name span,\n",
       ".xr-var-data,\n",
       ".xr-attrs {\n",
       "  padding-left: 25px !important;\n",
       "}\n",
       "\n",
       ".xr-attrs,\n",
       ".xr-var-attrs,\n",
       ".xr-var-data {\n",
       "  grid-column: 1 / -1;\n",
       "}\n",
       "\n",
       "dl.xr-attrs {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  display: grid;\n",
       "  grid-template-columns: 125px auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt,\n",
       ".xr-attrs dd {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  float: left;\n",
       "  padding-right: 10px;\n",
       "  width: auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt {\n",
       "  font-weight: normal;\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-attrs dt:hover span {\n",
       "  display: inline-block;\n",
       "  background: var(--xr-background-color);\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-attrs dd {\n",
       "  grid-column: 2;\n",
       "  white-space: pre-wrap;\n",
       "  word-break: break-all;\n",
       "}\n",
       "\n",
       ".xr-icon-database,\n",
       ".xr-icon-file-text2 {\n",
       "  display: inline-block;\n",
       "  vertical-align: middle;\n",
       "  width: 1em;\n",
       "  height: 1.5em !important;\n",
       "  stroke-width: 0;\n",
       "  stroke: currentColor;\n",
       "  fill: currentColor;\n",
       "}\n",
       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.DataArray &#x27;cfrac&#x27; (time: 600)&gt;\n",
       "array([0.030762, 0.00293 , 0.000488, ...,      nan,      nan,      nan],\n",
       "      dtype=float32)\n",
       "Coordinates:\n",
       "  * time     (time) float32 60.0 120.0 180.0 ... 3.588e+04 3.594e+04 3.6e+04\n",
       "Attributes:\n",
       "    longname:  Cloud fraction\n",
       "    units:     -</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'>'cfrac'</div><ul class='xr-dim-list'><li><span class='xr-has-index'>time</span>: 600</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-cba6d8be-9897-4683-828a-b156e16251bb' class='xr-array-in' type='checkbox' checked><label for='section-cba6d8be-9897-4683-828a-b156e16251bb' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>0.03076 0.00293 0.0004883 nan nan nan nan ... nan nan nan nan nan nan</span></div><div class='xr-array-data'><pre>array([0.030762, 0.00293 , 0.000488, ...,      nan,      nan,      nan],\n",
       "      dtype=float32)</pre></div></div></li><li class='xr-section-item'><input id='section-48fdaa9e-32a9-4f1f-a60a-03fcfc64b246' class='xr-section-summary-in' type='checkbox'  checked><label for='section-48fdaa9e-32a9-4f1f-a60a-03fcfc64b246' class='xr-section-summary' >Coordinates: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>60.0 120.0 ... 3.594e+04 3.6e+04</div><input id='attrs-d3661c2a-de43-4e7f-bdd9-9496c92d9f59' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d3661c2a-de43-4e7f-bdd9-9496c92d9f59' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-834d9bf9-6fc8-4ef1-904e-39e15dadf8b6' class='xr-var-data-in' type='checkbox'><label for='data-834d9bf9-6fc8-4ef1-904e-39e15dadf8b6' 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>longname :</span></dt><dd>Time</dd><dt><span>units :</span></dt><dd>s</dd></dl></div><div class='xr-var-data'><pre>array([   60.,   120.,   180., ..., 35880., 35940., 36000.], dtype=float32)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-028f9a69-a27a-49ae-8254-2e06616b9e24' class='xr-section-summary-in' type='checkbox'  checked><label for='section-028f9a69-a27a-49ae-8254-2e06616b9e24' class='xr-section-summary' >Attributes: <span>(2)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>longname :</span></dt><dd>Cloud fraction</dd><dt><span>units :</span></dt><dd>-</dd></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.DataArray 'cfrac' (time: 600)>\n",
       "array([0.030762, 0.00293 , 0.000488, ...,      nan,      nan,      nan],\n",
       "      dtype=float32)\n",
       "Coordinates:\n",
       "  * time     (time) float32 60.0 120.0 180.0 ... 3.588e+04 3.594e+04 3.6e+04\n",
       "Attributes:\n",
       "    longname:  Cloud fraction\n",
       "    units:     -"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
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   "source": []
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