Case_Studies_V2.ipynb

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   "cell_type": "code",
   "execution_count": 1,
   "id": "5af1e1b0",
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import xarray as xr\n",
    "import matplotlib.pyplot as plt\n",
    "from matplotlib.lines import Line2D\n",
    "import cartopy\n",
    "import cartopy.crs as ccrs\n",
    "import lightningutil"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "e5b39428",
   "metadata": {},
   "outputs": [],
   "source": [
    "#files \n",
    "\n",
    "\"\"\"\n",
    "metfields\n",
    "\n",
    "/aosc/eos20/djallen/lightning/geos/twod/201907            cmap\n",
    "\n",
    "GEOS_cape_hrly.UT.t201907.r180W-30W_50S-50N.nc       *    YlOrRd\n",
    "GEOS_cldht_hrly.UT.t201907.r180W-30W_50S-50N.nc      *    copper  \n",
    "GEOS_l_cbase_hrly.UT.t201907.r180W-30W_50S-50N.nc    *    \n",
    "GEOS_mf_cbase_hrly.UT.t201907.r180W-30W_50S-50N.nc   *    ocean_r\n",
    "GEOS_pblh_hrly.UT.t201907.r180W-30W_50S-50N.nc       *    tab20b , BuPu\n",
    "GEOS_p_cbase_hrly.UT.t201907.r180W-30W_50S-50N.nc    *    PuRd_r\n",
    "GEOS_p_ctop_hrly.UT.t201907.r180W-30W_50S-50N.nc     *    binary , plasma_r *cant have white\n",
    "GEOS_precon_hrly.UT.t201907.r180W-30W_50S-50N.nc     *    cool\n",
    "GEOS_pretot_hrly.UT.t201907.r180W-30W_50S-50N.nc     *    summer\n",
    "GEOS_t_sfc_hrly.UT.t201907.r180W-30W_50S-50N.nc      *    turbo\n",
    "GEOS_z_cbase_hrly.UT.t201907.r180W-30W_50S-50N.nc    *    pink\n",
    "\n",
    "/aosc/eos20/djallen/lightning/geos/twod_440/201907\n",
    "\n",
    "GEOS_cldfrac_conv_440_hrly.UT.t201907.r180W-30W_50S-50N.nc   *   viridis\n",
    "GEOS_cldfrac_ls_440_hrly.UT.t201907.r180W-30W_50S-50N.nc     *   viridis\n",
    "GEOS_cnv_mfc_440_hrly.UT.t201907.r180W-30W_50S-50N.nc        *   ocean_r\n",
    "GEOS_iwc_440_hrly.UT.t201907.r180W-30W_50S-50N.nc            *   winter\n",
    "\n",
    "lightning\n",
    "\n",
    "/aosc/eos20/djallen/data/lightning/glm/2019\n",
    "\n",
    "GLMmax_hrly_count_f.nominalq.UT.t201907.r180W-30W_50S-50N.nc    *\n",
    "GLMmax_hrly_count_g.nominalq.UT.t201907.r180W-30W_50S-50N.nc    *\n",
    "GLMmax_hrly_energy_f.nominalq.UT.t201907.r180W-30W_50S-50N.nc   *\n",
    "GLMmax_hrly_energy_g.nominalq.UT.t201907.r180W-30W_50S-50N.nc   *\n",
    "\"\"\"\n",
    "print()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a037e33a",
   "metadata": {},
   "source": [
    "# Counts "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "abbb2463",
   "metadata": {},
   "outputs": [],
   "source": [
    "directory = '/aosc/eos20/djallen/lightning/geos/twod/201907/'\n",
    "filename = 'GEOS_z_cbase_hrly.UT.t201907.r180W-30W_50S-50N.nc'\n",
    "ds_tmp = lightningutil.open_and_preprocess(directory+filename, lightningutil.variables)\n",
    "\n",
    "directory = '/aosc/eos20/djallen/data/lightning/glm/2019/'\n",
    "filename = 'GLMmax_hrly_count_g.nominalq.UT.t201907.r180W-30W_50S-50N.nc'\n",
    "CS1_tmp = lightningutil.open_and_preprocess(directory+filename, lightningutil.variables)\n",
    "\n",
    "filename = 'GLMmax_hrly_count_f.nominalq.UT.t201907.r180W-30W_50S-50N.nc'\n",
    "CS2_tmp = lightningutil.open_and_preprocess(directory+filename, lightningutil.variables)"
   ]
  },
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   "cell_type": "code",
   "execution_count": 9,
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       "Attributes:\n",
       "    long_name:      Group count\n",
       "    units:          Count 0.5x0.5 box-1 60min-1\n",
       "    var_desc:       Count of GLM Groups\n",
       "    missing_value:  nan</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'>'groups'</div><ul class='xr-dim-list'><li><span class='xr-has-index'>Latitudes</span>: 200</li><li><span class='xr-has-index'>Longitudes</span>: 300</li><li><span class='xr-has-index'>Datetime</span>: 744</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-3869ba62-19c3-4e4a-ab43-84cc71d2bebe' class='xr-array-in' type='checkbox' checked><label for='section-3869ba62-19c3-4e4a-ab43-84cc71d2bebe' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 ... 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0</span></div><div class='xr-array-data'><pre>array([[[  0.,   0.,   0., ...,   0.,   0.,   0.],\n",
       "        [  0.,   0.,   0., ...,   0.,   0.,   0.],\n",
       "        [  0.,   0.,   0., ...,   0.,   0.,   0.],\n",
       "        ...,\n",
       "        [  0.,   0.,   0., ...,   0.,   0.,   0.],\n",
       "        [  0.,   0.,   0., ...,   0.,   0.,   0.],\n",
       "        [  0.,   0.,   0., ...,   0.,   0.,   0.]],\n",
       "\n",
       "       [[  0.,   0.,   0., ...,   0.,   0.,   0.],\n",
       "        [  0.,   0.,   0., ...,   0.,   0.,   0.],\n",
       "        [  0.,   0.,   0., ...,   0.,   0.,   0.],\n",
       "        ...,\n",
       "        [  0.,   0.,   0., ...,   0.,   0.,   0.],\n",
       "        [  0.,   0.,   0., ...,   0.,   0.,   0.],\n",
       "        [  0.,   0.,   0., ...,   0.,   0.,   0.]],\n",
       "\n",
       "       [[  0.,   0.,   0., ...,   0.,   0.,   0.],\n",
       "        [  0.,   0.,   0., ...,   0.,   0.,   0.],\n",
       "        [  0.,   0.,   0., ...,   0.,   0.,   0.],\n",
       "        ...,\n",
       "...\n",
       "        ...,\n",
       "        [  0.,   0.,   0., ...,   0.,  94.,  66.],\n",
       "        [  0.,   0.,   0., ...,   0.,   0.,  78.],\n",
       "        [  0.,   0.,   0., ...,   0.,   0.,  24.]],\n",
       "\n",
       "       [[  0.,   0.,   0., ...,   0.,   0.,   0.],\n",
       "        [  0.,   0.,   0., ...,   0.,   0.,   0.],\n",
       "        [  0.,   0.,   0., ...,   0.,   0.,   0.],\n",
       "        ...,\n",
       "        [  0.,   0.,   0., ...,   0.,  12.,   0.],\n",
       "        [  0.,   0.,   0., ...,   0.,   0.,  15.],\n",
       "        [  0.,   0.,   0., ...,   0.,   0., 103.]],\n",
       "\n",
       "       [[  0.,   0.,   0., ...,   0.,   0.,   0.],\n",
       "        [  0.,   0.,   0., ...,   0.,   0.,   0.],\n",
       "        [  0.,   0.,   0., ...,   0.,   0.,   0.],\n",
       "        ...,\n",
       "        [  0.,   0.,   0., ...,   0.,   0.,   0.],\n",
       "        [  0.,   0.,   0., ...,   0.,   0.,   0.],\n",
       "        [  0.,   0.,   0., ...,   0.,   0.,   0.]]], dtype=float32)</pre></div></div></li><li class='xr-section-item'><input id='section-b530b9c4-49aa-4598-9c3e-909dac3f1ccd' class='xr-section-summary-in' type='checkbox'  checked><label for='section-b530b9c4-49aa-4598-9c3e-909dac3f1ccd' class='xr-section-summary' >Coordinates: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>Longitudes</span></div><div class='xr-var-dims'>(Longitudes)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-179.8 -179.2 ... -30.75 -30.25</div><input id='attrs-07e403c1-4d3f-4d12-9af9-e3c8d2e38086' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-07e403c1-4d3f-4d12-9af9-e3c8d2e38086' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4e22175d-3ce8-4b84-b142-8086827e55e3' class='xr-var-data-in' type='checkbox'><label for='data-4e22175d-3ce8-4b84-b142-8086827e55e3' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>longitude</dd><dt><span>units :</span></dt><dd>Degrees</dd><dt><span>var_desc :</span></dt><dd>Longitude</dd></dl></div><div class='xr-var-data'><pre>array([-179.75, -179.25, -178.75, ...,  -31.25,  -30.75,  -30.25],\n",
       "      dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>Latitudes</span></div><div class='xr-var-dims'>(Latitudes)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-49.75 -49.25 ... 49.25 49.75</div><input id='attrs-2e70b5df-1eb6-4709-9c7d-2c68faf25cff' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-2e70b5df-1eb6-4709-9c7d-2c68faf25cff' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d9484495-16a1-4172-9074-ff3c21d774ba' class='xr-var-data-in' type='checkbox'><label for='data-d9484495-16a1-4172-9074-ff3c21d774ba' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>latitude</dd><dt><span>units :</span></dt><dd>Degrees</dd><dt><span>var_desc :</span></dt><dd>Latitude</dd></dl></div><div class='xr-var-data'><pre>array([-49.75, -49.25, -48.75, -48.25, -47.75, -47.25, -46.75, -46.25, -45.75,\n",
       "       -45.25, -44.75, -44.25, -43.75, -43.25, -42.75, -42.25, -41.75, -41.25,\n",
       "       -40.75, -40.25, -39.75, -39.25, -38.75, -38.25, -37.75, -37.25, -36.75,\n",
       "       -36.25, -35.75, -35.25, -34.75, -34.25, -33.75, -33.25, -32.75, -32.25,\n",
       "       -31.75, -31.25, -30.75, -30.25, -29.75, -29.25, -28.75, -28.25, -27.75,\n",
       "       -27.25, -26.75, -26.25, -25.75, -25.25, -24.75, -24.25, -23.75, -23.25,\n",
       "       -22.75, -22.25, -21.75, -21.25, -20.75, -20.25, -19.75, -19.25, -18.75,\n",
       "       -18.25, -17.75, -17.25, -16.75, -16.25, -15.75, -15.25, -14.75, -14.25,\n",
       "       -13.75, -13.25, -12.75, -12.25, -11.75, -11.25, -10.75, -10.25,  -9.75,\n",
       "        -9.25,  -8.75,  -8.25,  -7.75,  -7.25,  -6.75,  -6.25,  -5.75,  -5.25,\n",
       "        -4.75,  -4.25,  -3.75,  -3.25,  -2.75,  -2.25,  -1.75,  -1.25,  -0.75,\n",
       "        -0.25,   0.25,   0.75,   1.25,   1.75,   2.25,   2.75,   3.25,   3.75,\n",
       "         4.25,   4.75,   5.25,   5.75,   6.25,   6.75,   7.25,   7.75,   8.25,\n",
       "         8.75,   9.25,   9.75,  10.25,  10.75,  11.25,  11.75,  12.25,  12.75,\n",
       "        13.25,  13.75,  14.25,  14.75,  15.25,  15.75,  16.25,  16.75,  17.25,\n",
       "        17.75,  18.25,  18.75,  19.25,  19.75,  20.25,  20.75,  21.25,  21.75,\n",
       "        22.25,  22.75,  23.25,  23.75,  24.25,  24.75,  25.25,  25.75,  26.25,\n",
       "        26.75,  27.25,  27.75,  28.25,  28.75,  29.25,  29.75,  30.25,  30.75,\n",
       "        31.25,  31.75,  32.25,  32.75,  33.25,  33.75,  34.25,  34.75,  35.25,\n",
       "        35.75,  36.25,  36.75,  37.25,  37.75,  38.25,  38.75,  39.25,  39.75,\n",
       "        40.25,  40.75,  41.25,  41.75,  42.25,  42.75,  43.25,  43.75,  44.25,\n",
       "        44.75,  45.25,  45.75,  46.25,  46.75,  47.25,  47.75,  48.25,  48.75,\n",
       "        49.25,  49.75], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>Datetime</span></div><div class='xr-var-dims'>(Datetime)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2019-07-01T01:00:00 ... 2019-08-01</div><input id='attrs-f1b171b4-8661-4b85-af0d-0527afc2d238' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-f1b171b4-8661-4b85-af0d-0527afc2d238' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a63616b0-46ed-432d-8972-c5c95f0403d3' class='xr-var-data-in' type='checkbox'><label for='data-a63616b0-46ed-432d-8972-c5c95f0403d3' 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'></dl></div><div class='xr-var-data'><pre>array([&#x27;2019-07-01T01:00:00.000000000&#x27;, &#x27;2019-07-01T02:00:00.000000000&#x27;,\n",
       "       &#x27;2019-07-01T03:00:00.000000000&#x27;, ..., &#x27;2019-07-31T22:00:00.000000000&#x27;,\n",
       "       &#x27;2019-07-31T23:00:00.000000000&#x27;, &#x27;2019-08-01T00:00:00.000000000&#x27;],\n",
       "      dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-fd2cf8b5-e619-4716-b407-a5731e962f54' class='xr-section-summary-in' type='checkbox'  ><label for='section-fd2cf8b5-e619-4716-b407-a5731e962f54' class='xr-section-summary' >Indexes: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>Longitudes</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-1c392b6a-48a9-44d4-be5c-35905354e1af' class='xr-index-data-in' type='checkbox'/><label for='index-1c392b6a-48a9-44d4-be5c-35905354e1af' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([-179.75, -179.25, -178.75, -178.25, -177.75, -177.25, -176.75, -176.25,\n",
       "       -175.75, -175.25,\n",
       "       ...\n",
       "        -34.75,  -34.25,  -33.75,  -33.25,  -32.75,  -32.25,  -31.75,  -31.25,\n",
       "        -30.75,  -30.25],\n",
       "      dtype=&#x27;float32&#x27;, name=&#x27;Longitudes&#x27;, length=300))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>Latitudes</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-3f857a6e-deba-41c6-af33-6f31d07d9b10' class='xr-index-data-in' type='checkbox'/><label for='index-3f857a6e-deba-41c6-af33-6f31d07d9b10' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([-49.75, -49.25, -48.75, -48.25, -47.75, -47.25, -46.75, -46.25, -45.75,\n",
       "       -45.25,\n",
       "       ...\n",
       "        45.25,  45.75,  46.25,  46.75,  47.25,  47.75,  48.25,  48.75,  49.25,\n",
       "        49.75],\n",
       "      dtype=&#x27;float32&#x27;, name=&#x27;Latitudes&#x27;, length=200))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>Datetime</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-39715a04-13f9-4e4f-ac5a-ad550586a161' class='xr-index-data-in' type='checkbox'/><label for='index-39715a04-13f9-4e4f-ac5a-ad550586a161' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(DatetimeIndex([&#x27;2019-07-01 01:00:00&#x27;, &#x27;2019-07-01 02:00:00&#x27;,\n",
       "               &#x27;2019-07-01 03:00:00&#x27;, &#x27;2019-07-01 04:00:00&#x27;,\n",
       "               &#x27;2019-07-01 05:00:00&#x27;, &#x27;2019-07-01 06:00:00&#x27;,\n",
       "               &#x27;2019-07-01 07:00:00&#x27;, &#x27;2019-07-01 08:00:00&#x27;,\n",
       "               &#x27;2019-07-01 09:00:00&#x27;, &#x27;2019-07-01 10:00:00&#x27;,\n",
       "               ...\n",
       "               &#x27;2019-07-31 15:00:00&#x27;, &#x27;2019-07-31 16:00:00&#x27;,\n",
       "               &#x27;2019-07-31 17:00:00&#x27;, &#x27;2019-07-31 18:00:00&#x27;,\n",
       "               &#x27;2019-07-31 19:00:00&#x27;, &#x27;2019-07-31 20:00:00&#x27;,\n",
       "               &#x27;2019-07-31 21:00:00&#x27;, &#x27;2019-07-31 22:00:00&#x27;,\n",
       "               &#x27;2019-07-31 23:00:00&#x27;, &#x27;2019-08-01 00:00:00&#x27;],\n",
       "              dtype=&#x27;datetime64[ns]&#x27;, name=&#x27;Datetime&#x27;, length=744, freq=&#x27;H&#x27;))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-238b137b-7096-4eb6-b711-b41677798372' class='xr-section-summary-in' type='checkbox'  checked><label for='section-238b137b-7096-4eb6-b711-b41677798372' 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>long_name :</span></dt><dd>Group count</dd><dt><span>units :</span></dt><dd>Count 0.5x0.5 box-1 60min-1</dd><dt><span>var_desc :</span></dt><dd>Count of GLM Groups</dd><dt><span>missing_value :</span></dt><dd>nan</dd></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.DataArray 'groups' (Latitudes: 200, Longitudes: 300, Datetime: 744)>\n",
       "array([[[  0.,   0.,   0., ...,   0.,   0.,   0.],\n",
       "        [  0.,   0.,   0., ...,   0.,   0.,   0.],\n",
       "        [  0.,   0.,   0., ...,   0.,   0.,   0.],\n",
       "        ...,\n",
       "        [  0.,   0.,   0., ...,   0.,   0.,   0.],\n",
       "        [  0.,   0.,   0., ...,   0.,   0.,   0.],\n",
       "        [  0.,   0.,   0., ...,   0.,   0.,   0.]],\n",
       "\n",
       "       [[  0.,   0.,   0., ...,   0.,   0.,   0.],\n",
       "        [  0.,   0.,   0., ...,   0.,   0.,   0.],\n",
       "        [  0.,   0.,   0., ...,   0.,   0.,   0.],\n",
       "        ...,\n",
       "        [  0.,   0.,   0., ...,   0.,   0.,   0.],\n",
       "        [  0.,   0.,   0., ...,   0.,   0.,   0.],\n",
       "        [  0.,   0.,   0., ...,   0.,   0.,   0.]],\n",
       "\n",
       "       [[  0.,   0.,   0., ...,   0.,   0.,   0.],\n",
       "        [  0.,   0.,   0., ...,   0.,   0.,   0.],\n",
       "        [  0.,   0.,   0., ...,   0.,   0.,   0.],\n",
       "        ...,\n",
       "...\n",
       "        ...,\n",
       "        [  0.,   0.,   0., ...,   0.,  94.,  66.],\n",
       "        [  0.,   0.,   0., ...,   0.,   0.,  78.],\n",
       "        [  0.,   0.,   0., ...,   0.,   0.,  24.]],\n",
       "\n",
       "       [[  0.,   0.,   0., ...,   0.,   0.,   0.],\n",
       "        [  0.,   0.,   0., ...,   0.,   0.,   0.],\n",
       "        [  0.,   0.,   0., ...,   0.,   0.,   0.],\n",
       "        ...,\n",
       "        [  0.,   0.,   0., ...,   0.,  12.,   0.],\n",
       "        [  0.,   0.,   0., ...,   0.,   0.,  15.],\n",
       "        [  0.,   0.,   0., ...,   0.,   0., 103.]],\n",
       "\n",
       "       [[  0.,   0.,   0., ...,   0.,   0.,   0.],\n",
       "        [  0.,   0.,   0., ...,   0.,   0.,   0.],\n",
       "        [  0.,   0.,   0., ...,   0.,   0.,   0.],\n",
       "        ...,\n",
       "        [  0.,   0.,   0., ...,   0.,   0.,   0.],\n",
       "        [  0.,   0.,   0., ...,   0.,   0.,   0.],\n",
       "        [  0.,   0.,   0., ...,   0.,   0.,   0.]]], dtype=float32)\n",
       "Coordinates:\n",
       "  * Longitudes  (Longitudes) float32 -179.8 -179.2 -178.8 ... -30.75 -30.25\n",
       "  * Latitudes   (Latitudes) float32 -49.75 -49.25 -48.75 ... 48.75 49.25 49.75\n",
       "  * Datetime    (Datetime) datetime64[ns] 2019-07-01T01:00:00 ... 2019-08-01\n",
       "Attributes:\n",
       "    long_name:      Group count\n",
       "    units:          Count 0.5x0.5 box-1 60min-1\n",
       "    var_desc:       Count of GLM Groups\n",
       "    missing_value:  nan"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "CS1_tmp"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "124ec043",
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "lightningutil.case_study_plotting(\n",
    "    ds_tmp,\n",
    "    CS1_tmp,\n",
    "    CS2_tmp,\n",
    "    lon_range=slice(-88,-82),\n",
    "    lat_range=slice(27,31),  \n",
    "    date_time='2019-07-06T18:00:00.000000000',\n",
    "    vmin=0.05,\n",
    "    vmax=2.25,\n",
    "    cmap='plasma',\n",
    "    cnt_levels_1=[8000,12000,16000,20000,24000,28000,32000,36000],  \n",
    "    # 20,40,60,80,100 (15z), 250,500,750,1000,1500 (16z), 2000,4000,6000,8000,12000 (17z) \n",
    "    # 4000,8000,12000,16000,20000,24000 (18z), 4000,8000,12000,16000,20000,24000,28000,32000,36000 (19z) remove 4000 for 20/21\n",
    "    color_1='green',\n",
    "    legend_label_1=\"Groups\",\n",
    "    cnt_levels_2=[600,1000,1400,1800,2400,3000], \n",
    "    # 2,4,6,8,10 (15z), 10,50,100,150,200 (16z), 400,600,800,1000,1200 (17z), 600,1000,1400,1800,2200 (18z),\n",
    "    # 600,1000,1400,1800,2400,3000(19-21z)\n",
    "    color_2='white',\n",
    "    legend_label_2=\"Flashes\",\n",
    "    cbar_label=\"z_cbase [km]\",\n",
    "    legend_facecolor='grey',\n",
    "    fig_title='Lightning & Cld Base Height: 2019-07-13 21Z',\n",
    "    #save_string= \"/aosc/eos20/eevans15/p_cbase_plots/23zp_cbase.png\"\n",
    "                   )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "6215ab46",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.collections.QuadMesh at 0x7fd4714203d0>"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "ds_tmp.sel(\n",
    "     Latitudes=slice(27,31),\n",
    "    Longitudes=slice(-88,-82),\n",
    "    Datetime='2019-07-06T18:00:00.000000000',\n",
    "    ).plot()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "5feb3948",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "6e37e680",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "46461ed1",
   "metadata": {},
   "source": [
    "# Energy"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "72980946",
   "metadata": {},
   "outputs": [],
   "source": [
    "directory = '/aosc/eos20/djallen/lightning/geos/twod/201907/'\n",
    "filename = 'GEOS_t_sfc_hrly.UT.t201907.r180W-30W_50S-50N.nc'\n",
    "ds_tmp = lightningutil.open_and_preprocess(directory+filename, lightningutil.variables)\n",
    "\n",
    "directory = '/aosc/eos20/djallen/data/lightning/glm/2019/'\n",
    "filename = 'GLMmax_hrly_energy_g.nominalq.UT.t201907.r180W-30W_50S-50N.nc'\n",
    "CS1_tmp = lightningutil.open_and_preprocess(directory+filename, lightningutil.variables)\n",
    "\n",
    "filename = 'GLMmax_hrly_energy_f.nominalq.UT.t201907.r180W-30W_50S-50N.nc'\n",
    "CS2_tmp = lightningutil.open_and_preprocess(directory+filename, lightningutil.variables)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "8cefdb4b",
   "metadata": {},
   "outputs": [],
   "source": [
    "lightningutil.case_study_plotting(\n",
    "    ds_tmp,\n",
    "    CS1_tmp,\n",
    "    CS2_tmp,\n",
    "    lon_range=slice(-96,-86),\n",
    "    lat_range=slice(30,37),  \n",
    "    date_time='2019-07-16T12:00:00.000000000',\n",
    "    vmin=290,\n",
    "    vmax=315,\n",
    "    cmap='turbo',\n",
    "    cnt_levels_1=[10000,20000,30000,40000,50000,60000],  #(16z) add 1000,5000\n",
    "    color_1='white',\n",
    "    legend_label_1=\"Groups\",\n",
    "    cnt_levels_2=[10000,20000,30000,40000,50000,60000], \n",
    "    color_2='purple',\n",
    "    legend_label_2=\"Flashes\",\n",
    "    cbar_label=\"t_sfc [K]\",\n",
    "    legend_facecolor='grey',\n",
    "    fig_title='Energy and Sfc Temp: 2019-07-16 12Z',\n",
    "    )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "fa270ba5",
   "metadata": {},
   "outputs": [],
   "source": []
  }
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