Examples/annual_maximum_ozone.ipynb

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    "# Maximum Ozone Hole Extent\n",
    "Welcome to the **Maximum Ozone Hole Extent** notebook! In this notebook, we will provide a more complex example of how to plot data onto a 3D model of the Earth using the **accessvis** package. \n",
    "\n",
    "In this notebook we will plot both the historical and predicted ozone hole size.\n",
    "* Animate the ozone hole every day for one year.\n",
    "* Calculate the size of the ozone hole.\n",
    "  * This includes calculating the area of each grid cell.\n",
    "* Finding the day of the year where the ozone hole is largest.\n",
    "* Animating this hole over time.\n",
    "\n",
    "The data used is available in project p73 on gadi and takes about 5 minutes to run."
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    "## Initial Setup"
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    "import accessvis\n",
    "import os\n",
    "import glob\n",
    "from tqdm.notebook import tqdm\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import xarray as xr"
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    "Finding and pre-loading data to speed up the rest of the notebook (~5GB)."
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      "/g/data/p73/archive/non-CMIP/CMORised/CCMI2022/CSIRO-ARCCSS/ACCESS-CM2-Chem/refD2/r1i1p1f1/Aday/toz/gn/v20220822/toz_Aday_ACCESS-CM2-Chem_refD2_r1i1p1f1_gn_19600101-20091231.nc\n",
      "/g/data/p73/archive/non-CMIP/CMORised/CCMI2022/CSIRO-ARCCSS/ACCESS-CM2-Chem/refD2/r1i1p1f1/Aday/toz/gn/v20220822/toz_Aday_ACCESS-CM2-Chem_refD2_r1i1p1f1_gn_20100101-20591231.nc\n",
      "/g/data/p73/archive/non-CMIP/CMORised/CCMI2022/CSIRO-ARCCSS/ACCESS-CM2-Chem/refD2/r1i1p1f1/Aday/toz/gn/v20220822/toz_Aday_ACCESS-CM2-Chem_refD2_r1i1p1f1_gn_20600101-21001231.nc\n"
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       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt; Size: 6GB\n",
       "Dimensions:   (time: 51500, lat: 144, bnds: 2, lon: 192)\n",
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       "  * lon       (lon) float64 2kB 0.9375 2.812 4.688 6.562 ... 355.3 357.2 359.1\n",
       "Dimensions without coordinates: bnds\n",
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       "    lon_bnds  (time, lon, bnds) float64 158MB 0.0 1.875 1.875 ... 358.1 360.0\n",
       "    toz       (time, lat, lon) float32 6GB 0.003163 0.003164 ... 0.005004\n",
       "Attributes: (12/45)\n",
       "    Conventions:             CF-1.7\n",
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       "    branch_time_in_child:    0.0\n",
       "    branch_time_in_parent:   0.0\n",
       "    ...                      ...\n",
       "    variable_id:             toz\n",
       "    variant_label:           r1i1p1f1\n",
       "    version:                 v20220822\n",
       "    license:                 CCMI2022 model data produced by CSIRO is license...\n",
       "    cmor_version:            3.4.0\n",
       "    tracking_id:             hdl:21.14100/c172e59b-9c50-44be-836c-6c44dd9a8e40</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-d32c5d2c-ed66-4941-ba0f-a039fa8a5fed' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-d32c5d2c-ed66-4941-ba0f-a039fa8a5fed' 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>: 51500</li><li><span class='xr-has-index'>lat</span>: 144</li><li><span>bnds</span>: 2</li><li><span class='xr-has-index'>lon</span>: 192</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-5da57520-f135-4908-88fd-6928bf6bffd7' class='xr-section-summary-in' type='checkbox'  checked><label for='section-5da57520-f135-4908-88fd-6928bf6bffd7' class='xr-section-summary' >Coordinates: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>1960-01-01T12:00:00 ... 2100-12-...</div><input id='attrs-f60b965a-a75b-4f8c-9f5c-718289e8456d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f60b965a-a75b-4f8c-9f5c-718289e8456d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a4e070aa-54c5-462a-9835-bb7abf508033' class='xr-var-data-in' type='checkbox'><label for='data-a4e070aa-54c5-462a-9835-bb7abf508033' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>axis :</span></dt><dd>T</dd><dt><span>long_name :</span></dt><dd>time</dd><dt><span>standard_name :</span></dt><dd>time</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;1960-01-01T12:00:00.000000000&#x27;, &#x27;1960-01-02T12:00:00.000000000&#x27;,\n",
       "       &#x27;1960-01-03T12:00:00.000000000&#x27;, ..., &#x27;2100-12-29T12:00:00.000000000&#x27;,\n",
       "       &#x27;2100-12-30T12:00:00.000000000&#x27;, &#x27;2100-12-31T12:00:00.000000000&#x27;],\n",
       "      dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lat</span></div><div class='xr-var-dims'>(lat)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-89.38 -88.12 ... 88.12 89.38</div><input id='attrs-7ce0da47-26a3-4715-aadb-0a3f27e28f09' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-7ce0da47-26a3-4715-aadb-0a3f27e28f09' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-dc34e09c-60cc-43a1-8598-f9334311db97' class='xr-var-data-in' type='checkbox'><label for='data-dc34e09c-60cc-43a1-8598-f9334311db97' 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>bounds :</span></dt><dd>lat_bnds</dd><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>axis :</span></dt><dd>Y</dd><dt><span>long_name :</span></dt><dd>Latitude</dd><dt><span>standard_name :</span></dt><dd>latitude</dd></dl></div><div class='xr-var-data'><pre>array([-89.375, -88.125, -86.875, -85.625, -84.375, -83.125, -81.875, -80.625,\n",
       "       -79.375, -78.125, -76.875, -75.625, -74.375, -73.125, -71.875, -70.625,\n",
       "       -69.375, -68.125, -66.875, -65.625, -64.375, -63.125, -61.875, -60.625,\n",
       "       -59.375, -58.125, -56.875, -55.625, -54.375, -53.125, -51.875, -50.625,\n",
       "       -49.375, -48.125, -46.875, -45.625, -44.375, -43.125, -41.875, -40.625,\n",
       "       -39.375, -38.125, -36.875, -35.625, -34.375, -33.125, -31.875, -30.625,\n",
       "       -29.375, -28.125, -26.875, -25.625, -24.375, -23.125, -21.875, -20.625,\n",
       "       -19.375, -18.125, -16.875, -15.625, -14.375, -13.125, -11.875, -10.625,\n",
       "        -9.375,  -8.125,  -6.875,  -5.625,  -4.375,  -3.125,  -1.875,  -0.625,\n",
       "         0.625,   1.875,   3.125,   4.375,   5.625,   6.875,   8.125,   9.375,\n",
       "        10.625,  11.875,  13.125,  14.375,  15.625,  16.875,  18.125,  19.375,\n",
       "        20.625,  21.875,  23.125,  24.375,  25.625,  26.875,  28.125,  29.375,\n",
       "        30.625,  31.875,  33.125,  34.375,  35.625,  36.875,  38.125,  39.375,\n",
       "        40.625,  41.875,  43.125,  44.375,  45.625,  46.875,  48.125,  49.375,\n",
       "        50.625,  51.875,  53.125,  54.375,  55.625,  56.875,  58.125,  59.375,\n",
       "        60.625,  61.875,  63.125,  64.375,  65.625,  66.875,  68.125,  69.375,\n",
       "        70.625,  71.875,  73.125,  74.375,  75.625,  76.875,  78.125,  79.375,\n",
       "        80.625,  81.875,  83.125,  84.375,  85.625,  86.875,  88.125,  89.375])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lon</span></div><div class='xr-var-dims'>(lon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.9375 2.812 4.688 ... 357.2 359.1</div><input id='attrs-cecd0618-64d2-4315-a9fc-37e9c8f568d8' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-cecd0618-64d2-4315-a9fc-37e9c8f568d8' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d9115fcd-668f-4439-868d-83d1af1e08e8' class='xr-var-data-in' type='checkbox'><label for='data-d9115fcd-668f-4439-868d-83d1af1e08e8' 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>bounds :</span></dt><dd>lon_bnds</dd><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>axis :</span></dt><dd>X</dd><dt><span>long_name :</span></dt><dd>Longitude</dd><dt><span>standard_name :</span></dt><dd>longitude</dd></dl></div><div class='xr-var-data'><pre>array([  0.9375,   2.8125,   4.6875,   6.5625,   8.4375,  10.3125,  12.1875,\n",
       "        14.0625,  15.9375,  17.8125,  19.6875,  21.5625,  23.4375,  25.3125,\n",
       "        27.1875,  29.0625,  30.9375,  32.8125,  34.6875,  36.5625,  38.4375,\n",
       "        40.3125,  42.1875,  44.0625,  45.9375,  47.8125,  49.6875,  51.5625,\n",
       "        53.4375,  55.3125,  57.1875,  59.0625,  60.9375,  62.8125,  64.6875,\n",
       "        66.5625,  68.4375,  70.3125,  72.1875,  74.0625,  75.9375,  77.8125,\n",
       "        79.6875,  81.5625,  83.4375,  85.3125,  87.1875,  89.0625,  90.9375,\n",
       "        92.8125,  94.6875,  96.5625,  98.4375, 100.3125, 102.1875, 104.0625,\n",
       "       105.9375, 107.8125, 109.6875, 111.5625, 113.4375, 115.3125, 117.1875,\n",
       "       119.0625, 120.9375, 122.8125, 124.6875, 126.5625, 128.4375, 130.3125,\n",
       "       132.1875, 134.0625, 135.9375, 137.8125, 139.6875, 141.5625, 143.4375,\n",
       "       145.3125, 147.1875, 149.0625, 150.9375, 152.8125, 154.6875, 156.5625,\n",
       "       158.4375, 160.3125, 162.1875, 164.0625, 165.9375, 167.8125, 169.6875,\n",
       "       171.5625, 173.4375, 175.3125, 177.1875, 179.0625, 180.9375, 182.8125,\n",
       "       184.6875, 186.5625, 188.4375, 190.3125, 192.1875, 194.0625, 195.9375,\n",
       "       197.8125, 199.6875, 201.5625, 203.4375, 205.3125, 207.1875, 209.0625,\n",
       "       210.9375, 212.8125, 214.6875, 216.5625, 218.4375, 220.3125, 222.1875,\n",
       "       224.0625, 225.9375, 227.8125, 229.6875, 231.5625, 233.4375, 235.3125,\n",
       "       237.1875, 239.0625, 240.9375, 242.8125, 244.6875, 246.5625, 248.4375,\n",
       "       250.3125, 252.1875, 254.0625, 255.9375, 257.8125, 259.6875, 261.5625,\n",
       "       263.4375, 265.3125, 267.1875, 269.0625, 270.9375, 272.8125, 274.6875,\n",
       "       276.5625, 278.4375, 280.3125, 282.1875, 284.0625, 285.9375, 287.8125,\n",
       "       289.6875, 291.5625, 293.4375, 295.3125, 297.1875, 299.0625, 300.9375,\n",
       "       302.8125, 304.6875, 306.5625, 308.4375, 310.3125, 312.1875, 314.0625,\n",
       "       315.9375, 317.8125, 319.6875, 321.5625, 323.4375, 325.3125, 327.1875,\n",
       "       329.0625, 330.9375, 332.8125, 334.6875, 336.5625, 338.4375, 340.3125,\n",
       "       342.1875, 344.0625, 345.9375, 347.8125, 349.6875, 351.5625, 353.4375,\n",
       "       355.3125, 357.1875, 359.0625])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-3d52bf81-bda3-4a5f-b864-0ef15cd1f15e' class='xr-section-summary-in' type='checkbox'  checked><label for='section-3d52bf81-bda3-4a5f-b864-0ef15cd1f15e' class='xr-section-summary' >Data variables: <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>lat_bnds</span></div><div class='xr-var-dims'>(time, lat, bnds)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-90.0 -88.75 -88.75 ... 88.75 90.0</div><input id='attrs-6cd9b4da-f85f-4e47-8c6c-e897108846a6' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-6cd9b4da-f85f-4e47-8c6c-e897108846a6' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a3e25f1e-79a4-4195-bf87-149df32a093b' class='xr-var-data-in' type='checkbox'><label for='data-a3e25f1e-79a4-4195-bf87-149df32a093b' 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([[[-90.  , -88.75],\n",
       "        [-88.75, -87.5 ],\n",
       "        [-87.5 , -86.25],\n",
       "        ...,\n",
       "        [ 86.25,  87.5 ],\n",
       "        [ 87.5 ,  88.75],\n",
       "        [ 88.75,  90.  ]],\n",
       "\n",
       "       [[-90.  , -88.75],\n",
       "        [-88.75, -87.5 ],\n",
       "        [-87.5 , -86.25],\n",
       "        ...,\n",
       "        [ 86.25,  87.5 ],\n",
       "        [ 87.5 ,  88.75],\n",
       "        [ 88.75,  90.  ]],\n",
       "\n",
       "       [[-90.  , -88.75],\n",
       "        [-88.75, -87.5 ],\n",
       "        [-87.5 , -86.25],\n",
       "        ...,\n",
       "...\n",
       "        ...,\n",
       "        [ 86.25,  87.5 ],\n",
       "        [ 87.5 ,  88.75],\n",
       "        [ 88.75,  90.  ]],\n",
       "\n",
       "       [[-90.  , -88.75],\n",
       "        [-88.75, -87.5 ],\n",
       "        [-87.5 , -86.25],\n",
       "        ...,\n",
       "        [ 86.25,  87.5 ],\n",
       "        [ 87.5 ,  88.75],\n",
       "        [ 88.75,  90.  ]],\n",
       "\n",
       "       [[-90.  , -88.75],\n",
       "        [-88.75, -87.5 ],\n",
       "        [-87.5 , -86.25],\n",
       "        ...,\n",
       "        [ 86.25,  87.5 ],\n",
       "        [ 87.5 ,  88.75],\n",
       "        [ 88.75,  90.  ]]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lon_bnds</span></div><div class='xr-var-dims'>(time, lon, bnds)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0 1.875 1.875 ... 358.1 360.0</div><input id='attrs-5f229227-a575-426f-a982-16b765df2df9' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-5f229227-a575-426f-a982-16b765df2df9' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-950266c7-013c-4b24-9ea2-52921687b519' class='xr-var-data-in' type='checkbox'><label for='data-950266c7-013c-4b24-9ea2-52921687b519' 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([[[  0.   ,   1.875],\n",
       "        [  1.875,   3.75 ],\n",
       "        [  3.75 ,   5.625],\n",
       "        ...,\n",
       "        [354.375, 356.25 ],\n",
       "        [356.25 , 358.125],\n",
       "        [358.125, 360.   ]],\n",
       "\n",
       "       [[  0.   ,   1.875],\n",
       "        [  1.875,   3.75 ],\n",
       "        [  3.75 ,   5.625],\n",
       "        ...,\n",
       "        [354.375, 356.25 ],\n",
       "        [356.25 , 358.125],\n",
       "        [358.125, 360.   ]],\n",
       "\n",
       "       [[  0.   ,   1.875],\n",
       "        [  1.875,   3.75 ],\n",
       "        [  3.75 ,   5.625],\n",
       "        ...,\n",
       "...\n",
       "        ...,\n",
       "        [354.375, 356.25 ],\n",
       "        [356.25 , 358.125],\n",
       "        [358.125, 360.   ]],\n",
       "\n",
       "       [[  0.   ,   1.875],\n",
       "        [  1.875,   3.75 ],\n",
       "        [  3.75 ,   5.625],\n",
       "        ...,\n",
       "        [354.375, 356.25 ],\n",
       "        [356.25 , 358.125],\n",
       "        [358.125, 360.   ]],\n",
       "\n",
       "       [[  0.   ,   1.875],\n",
       "        [  1.875,   3.75 ],\n",
       "        [  3.75 ,   5.625],\n",
       "        ...,\n",
       "        [354.375, 356.25 ],\n",
       "        [356.25 , 358.125],\n",
       "        [358.125, 360.   ]]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>toz</span></div><div class='xr-var-dims'>(time, lat, lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.003163 0.003164 ... 0.005004</div><input id='attrs-e3c80c55-fbd5-4fb2-a429-62eaed0e02f2' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e3c80c55-fbd5-4fb2-a429-62eaed0e02f2' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-038b4d7f-f0b8-4cc6-9b6b-e97c7c8c3d88' class='xr-var-data-in' type='checkbox'><label for='data-038b4d7f-f0b8-4cc6-9b6b-e97c7c8c3d88' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>equivalent_thickness_at_stp_of_atmosphere_ozone_content</dd><dt><span>long_name :</span></dt><dd>Total Column Ozone</dd><dt><span>comment :</span></dt><dd>Total ozone column calculated at 0 degrees C and 1 bar, such that 1m = 1e5 DU.</dd><dt><span>units :</span></dt><dd>m</dd><dt><span>cell_methods :</span></dt><dd>area: mean time: point</dd><dt><span>cell_measures :</span></dt><dd>area: areacella</dd></dl></div><div class='xr-var-data'><pre>array([[[0.00316332, 0.00316365, 0.00316396, ..., 0.00316269,\n",
       "         0.00316302, 0.00316364],\n",
       "        [0.00316808, 0.00317046, 0.00317293, ..., 0.00316129,\n",
       "         0.00316333, 0.00316543],\n",
       "        [0.00315113, 0.00315621, 0.00316143, ..., 0.00313711,\n",
       "         0.00314148, 0.00314617],\n",
       "        ...,\n",
       "        [0.00358528, 0.00358041, 0.00357533, ..., 0.00359891,\n",
       "         0.00359455, 0.00358999],\n",
       "        [0.00354198, 0.00353898, 0.00353597, ..., 0.00355093,\n",
       "         0.00354796, 0.00354498],\n",
       "        [0.00351405, 0.00351343, 0.00351282, ..., 0.00351602,\n",
       "         0.00351535, 0.0035147 ]],\n",
       "\n",
       "       [[0.00330269, 0.00330401, 0.00330531, ..., 0.003299  ,\n",
       "         0.00330029, 0.00330192],\n",
       "        [0.00333318, 0.00333704, 0.00334086, ..., 0.0033213 ,\n",
       "         0.00332521, 0.00332899],\n",
       "        [0.00335125, 0.00335816, 0.00336488, ..., 0.00332995,\n",
       "         0.00333707, 0.00334417],\n",
       "...\n",
       "        [0.00477266, 0.00476822, 0.00476423, ..., 0.00478875,\n",
       "         0.00478264, 0.00477741],\n",
       "        [0.00490935, 0.00490557, 0.00490195, ..., 0.0049219 ,\n",
       "         0.00491727, 0.00491313],\n",
       "        [0.0050242 , 0.00502201, 0.00501989, ..., 0.00503152,\n",
       "         0.00502908, 0.00502666]],\n",
       "\n",
       "       [[0.00357622, 0.00357691, 0.00357744, ..., 0.00357595,\n",
       "         0.00357613, 0.00357651],\n",
       "        [0.00360329, 0.00360407, 0.00360509, ..., 0.00360079,\n",
       "         0.00360126, 0.0036021 ],\n",
       "        [0.00358293, 0.00358338, 0.00358359, ..., 0.00358084,\n",
       "         0.00358163, 0.00358229],\n",
       "        ...,\n",
       "        [0.00473665, 0.00473222, 0.0047291 , ..., 0.0047591 ,\n",
       "         0.00475017, 0.00474259],\n",
       "        [0.00488281, 0.00488024, 0.00487746, ..., 0.00488768,\n",
       "         0.00488648, 0.00488492],\n",
       "        [0.00500315, 0.00500255, 0.00500207, ..., 0.00500531,\n",
       "         0.00500452, 0.0050038 ]]], dtype=float32)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-1b28d781-a035-443a-9fb9-c6f9c8f2a2a0' class='xr-section-summary-in' type='checkbox'  ><label for='section-1b28d781-a035-443a-9fb9-c6f9c8f2a2a0' 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>time</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-e575ac42-cae1-436c-b118-0b15b16ace66' class='xr-index-data-in' type='checkbox'/><label for='index-e575ac42-cae1-436c-b118-0b15b16ace66' 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;1960-01-01 12:00:00&#x27;, &#x27;1960-01-02 12:00:00&#x27;,\n",
       "               &#x27;1960-01-03 12:00:00&#x27;, &#x27;1960-01-04 12:00:00&#x27;,\n",
       "               &#x27;1960-01-05 12:00:00&#x27;, &#x27;1960-01-06 12:00:00&#x27;,\n",
       "               &#x27;1960-01-07 12:00:00&#x27;, &#x27;1960-01-08 12:00:00&#x27;,\n",
       "               &#x27;1960-01-09 12:00:00&#x27;, &#x27;1960-01-10 12:00:00&#x27;,\n",
       "               ...\n",
       "               &#x27;2100-12-22 12:00:00&#x27;, &#x27;2100-12-23 12:00:00&#x27;,\n",
       "               &#x27;2100-12-24 12:00:00&#x27;, &#x27;2100-12-25 12:00:00&#x27;,\n",
       "               &#x27;2100-12-26 12:00:00&#x27;, &#x27;2100-12-27 12:00:00&#x27;,\n",
       "               &#x27;2100-12-28 12:00:00&#x27;, &#x27;2100-12-29 12:00:00&#x27;,\n",
       "               &#x27;2100-12-30 12:00:00&#x27;, &#x27;2100-12-31 12:00:00&#x27;],\n",
       "              dtype=&#x27;datetime64[ns]&#x27;, name=&#x27;time&#x27;, length=51500, freq=None))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>lat</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-a9f130be-771f-4596-a616-abe72a727be4' class='xr-index-data-in' type='checkbox'/><label for='index-a9f130be-771f-4596-a616-abe72a727be4' 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([-89.375, -88.125, -86.875, -85.625, -84.375, -83.125, -81.875, -80.625,\n",
       "       -79.375, -78.125,\n",
       "       ...\n",
       "        78.125,  79.375,  80.625,  81.875,  83.125,  84.375,  85.625,  86.875,\n",
       "        88.125,  89.375],\n",
       "      dtype=&#x27;float64&#x27;, name=&#x27;lat&#x27;, length=144))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>lon</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-0eccff79-f1b9-43a6-8689-8bc2472c2993' class='xr-index-data-in' type='checkbox'/><label for='index-0eccff79-f1b9-43a6-8689-8bc2472c2993' 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([  0.9375,   2.8125,   4.6875,   6.5625,   8.4375,  10.3125,  12.1875,\n",
       "        14.0625,  15.9375,  17.8125,\n",
       "       ...\n",
       "       342.1875, 344.0625, 345.9375, 347.8125, 349.6875, 351.5625, 353.4375,\n",
       "       355.3125, 357.1875, 359.0625],\n",
       "      dtype=&#x27;float64&#x27;, name=&#x27;lon&#x27;, length=192))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-79512208-f8b7-4704-8ebb-b9d4d7a32f53' class='xr-section-summary-in' type='checkbox'  ><label for='section-79512208-f8b7-4704-8ebb-b9d4d7a32f53' class='xr-section-summary' >Attributes: <span>(45)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>Conventions :</span></dt><dd>CF-1.7</dd><dt><span>activity_id :</span></dt><dd>CCMI2022</dd><dt><span>activity_participation :</span></dt><dd>CCMI2022</dd><dt><span>branch_method :</span></dt><dd>standard</dd><dt><span>branch_time_in_child :</span></dt><dd>0.0</dd><dt><span>branch_time_in_parent :</span></dt><dd>0.0</dd><dt><span>cohort :</span></dt><dd>Registered</dd><dt><span>contact :</span></dt><dd>access_csiro@csiro.au</dd><dt><span>creation_date :</span></dt><dd>2022-08-22T02:45:30Z</dd><dt><span>data_specs_version :</span></dt><dd>01.00.00</dd><dt><span>experiment :</span></dt><dd>Baseline projection using CMIP6 SSP2-45 GHGs and precursor emissions with WMO-2018 ODSs</dd><dt><span>experiment_id :</span></dt><dd>refD2</dd><dt><span>external_variables :</span></dt><dd>areacella</dd><dt><span>forcing_index :</span></dt><dd>1</dd><dt><span>frequency :</span></dt><dd>dayPt</dd><dt><span>further_info_url :</span></dt><dd>https://furtherinfo.es-doc.org/CMIP6.CSIRO-ARCCSS.ACCESS-CM2-Chem.refD2.none.r1i1p1f1</dd><dt><span>grid :</span></dt><dd>native atmosphere N96 grid (144x192 latxlon)</dd><dt><span>grid_label :</span></dt><dd>gn</dd><dt><span>history :</span></dt><dd>2022-08-22T02:45:30Z ; CMOR rewrote data to be consistent with CMIP6, CF-1.7 and CF standards.</dd><dt><span>initialization_index :</span></dt><dd>1</dd><dt><span>institution :</span></dt><dd>CSIRO (Commonwealth Scientific and Industrial Research Organisation, Aspendale, Victoria 3195, Australia), ARCCSS (Australian Research Council Centre of Excellence for Climate System Science)</dd><dt><span>institution_id :</span></dt><dd>CSIRO-ARCCSS</dd><dt><span>mip_era :</span></dt><dd>CMIP6</dd><dt><span>nominal_resolution :</span></dt><dd>250 km</dd><dt><span>notes :</span></dt><dd>Local exp ID: ch097; Variable: toz ([&#x27;fld_s50i219&#x27;])</dd><dt><span>parent_experiment_id :</span></dt><dd>no parent</dd><dt><span>physics_index :</span></dt><dd>1</dd><dt><span>product :</span></dt><dd>model-output</dd><dt><span>realization_index :</span></dt><dd>1</dd><dt><span>realm :</span></dt><dd>atmos</dd><dt><span>run_variant :</span></dt><dd>forcing: GHG, Oz, SA, Sl, Vl, BC, OC, (GHG = CO2, N2O, CH4, CFC11, CFC12, CFC113, HCFC22, HFC125, HFC134a)</dd><dt><span>source :</span></dt><dd>ACCESS-CM2-Chem (2020): aerosol: UKCA-GLOMAP-mode atmos: MetUM-HadGEM3-GA7.1 (N96; 192 x 144 longitude/latitude; 85 levels; top level 85 km) atmosChem: UKCA CheST land: CABLE2.5 landIce: none ocean: ACCESS-OM2 (GFDL-MOM5, tripolar primarily 1deg; 360 x 300 longitude/latitude; 50 levels; top grid cell 0-10 m) ocnBgchem: none seaIce: CICE5.1.2 (same grid as ocean)</dd><dt><span>source_id :</span></dt><dd>ACCESS-CM2-Chem</dd><dt><span>source_type :</span></dt><dd>AOGCM CHEM</dd><dt><span>sub_experiment :</span></dt><dd>none</dd><dt><span>sub_experiment_id :</span></dt><dd>none</dd><dt><span>table_id :</span></dt><dd>Aday</dd><dt><span>table_info :</span></dt><dd>Creation Date:(March 26, 2021) MD5:2acf5e4a6a5bd657d18f8ebe0b0d05c4</dd><dt><span>title :</span></dt><dd>ACCESS-CM2-Chem output prepared for CMIP6</dd><dt><span>variable_id :</span></dt><dd>toz</dd><dt><span>variant_label :</span></dt><dd>r1i1p1f1</dd><dt><span>version :</span></dt><dd>v20220822</dd><dt><span>license :</span></dt><dd>CCMI2022 model data produced by CSIRO is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License (https://creativecommons.org/licenses). Consult http://blogs.reading.ac.uk/ccmi/ for terms of use governing CCMI output, including citation requirements and proper acknowledgment. The data producers and data providers make no warranty, either express or implied, including, but not limited to, warranties of merchantability and fitness for a particular purpose. All liabilities arising from the supply of the information (including any liability arising in negligence) are excluded to the fullest extent permitted by law.</dd><dt><span>cmor_version :</span></dt><dd>3.4.0</dd><dt><span>tracking_id :</span></dt><dd>hdl:21.14100/c172e59b-9c50-44be-836c-6c44dd9a8e40</dd></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.Dataset> Size: 6GB\n",
       "Dimensions:   (time: 51500, lat: 144, bnds: 2, lon: 192)\n",
       "Coordinates:\n",
       "  * time      (time) datetime64[ns] 412kB 1960-01-01T12:00:00 ... 2100-12-31T...\n",
       "  * lat       (lat) float64 1kB -89.38 -88.12 -86.88 ... 86.88 88.12 89.38\n",
       "  * lon       (lon) float64 2kB 0.9375 2.812 4.688 6.562 ... 355.3 357.2 359.1\n",
       "Dimensions without coordinates: bnds\n",
       "Data variables:\n",
       "    lat_bnds  (time, lat, bnds) float64 119MB -90.0 -88.75 -88.75 ... 88.75 90.0\n",
       "    lon_bnds  (time, lon, bnds) float64 158MB 0.0 1.875 1.875 ... 358.1 360.0\n",
       "    toz       (time, lat, lon) float32 6GB 0.003163 0.003164 ... 0.005004\n",
       "Attributes: (12/45)\n",
       "    Conventions:             CF-1.7\n",
       "    activity_id:             CCMI2022\n",
       "    activity_participation:  CCMI2022\n",
       "    branch_method:           standard\n",
       "    branch_time_in_child:    0.0\n",
       "    branch_time_in_parent:   0.0\n",
       "    ...                      ...\n",
       "    variable_id:             toz\n",
       "    variant_label:           r1i1p1f1\n",
       "    version:                 v20220822\n",
       "    license:                 CCMI2022 model data produced by CSIRO is license...\n",
       "    cmor_version:            3.4.0\n",
       "    tracking_id:             hdl:21.14100/c172e59b-9c50-44be-836c-6c44dd9a8e40"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "datadir = '/g/data/p73/archive/non-CMIP/CMORised/CCMI2022/CSIRO-ARCCSS/ACCESS-CM2-Chem/refD2/r1i1p1f1/Aday/toz/gn/v20220822/'\n",
    "files = sorted(glob.glob(datadir + \"*.nc\"))\n",
    "ds = xr.open_mfdataset(files, combine='nested', concat_dim=\"time\")\n",
    "for f in files:\n",
    "    print(f)\n",
    "ds.load()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b46514f1-976a-4d04-bb49-ab6fe4f5e250",
   "metadata": {},
   "source": [
    "## Plot One Year\n",
    "Below we are making a quick animation of the ozone hole throughout 2015.\n",
    "\n",
    "You can clearly see the ozone hole change with the seasons."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "2629cb13-19a1-4bb6-9c66-4b1ad2f56e93",
   "metadata": {},
   "outputs": [],
   "source": [
    "lv = accessvis.plot_earth(texture='bluemarble', waves=True, background='black', vertical_exaggeration=30)\n",
    "lv.set_properties(diffuse=0.6, ambient=0.85, specular=0.25, shininess=0.03, light=[1,1,0.98,1], lightpos=[0,0,10000,1])\n",
    "\n",
    "threshold = 220 * 1e-5 #220 DU threshold converted to M\n",
    "\n",
    "colourmap='plasma'\n",
    "cmap = lv.colourmap(colourmap, range=(220, 550))\n",
    "cb = lv.colourbar()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "49b85c3a-e695-48ea-b222-7e2fcd7cb25f",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Output #0, mp4, to 'ozone_one_year.mp4':\n",
      "  Stream #0:0: Unknown: none\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "62fc4766a0e748919e469274b51bf4db",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "  0%|          | 0/365 [00:00<?, ?it/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<video src=\"ozone_one_year.mp4\" id='video_26ee8ba1' autoplay  width=\"600\"  height=\"600\">\n",
       "      Your browser does not support the <code>video</code> element.\n",
       "    </video>"
      ],
      "text/plain": [
       "<IPython.core.display.Video object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<a id=\"link_video_26ee8ba1\" href=\"ozone_one_year.mp4\" download>Download Video</a>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/javascript": [
       "\n",
       "        let el = document.getElementById('video_26ee8ba1');\n",
       "        let url = el.src;\n",
       "        fetch(url, {method: 'HEAD'}).then(response=>{\n",
       "          if(response.status == 404) {\n",
       "            console.log(\"Bad video url: \" + url);\n",
       "            let toppath = \"/files/home/\"\n",
       "            let baseurl = url.substring(0, url.indexOf(toppath)+toppath.length);\n",
       "            let endurl = url.substring(url.indexOf(\"ozone_one_year.mp4\"));\n",
       "            let fixed = baseurl + endurl;\n",
       "            console.log(\"Replaced video url: \" + fixed);\n",
       "            el.src = fixed;\n",
       "            //Also fix download link\n",
       "            document.getElementById('link_video_26ee8ba1').href = fixed;\n",
       "          }\n",
       "        });\n",
       "        "
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "filename = 'ozone_one_year.mp4'\n",
    "\n",
    "with lv.video(filename=filename, quality=4, resolution=(600,600), width=600, height=600, params=\"autoplay\") as v:\n",
    "    for i in tqdm(range(365)):\n",
    "        date = np.datetime64('2015-01-01T12:00:00') + np.timedelta64(i, 'D')\n",
    "        timepoint = ds['toz'].sel(time=date, method='nearest') # finding the corrosponding data for that day.\n",
    "        timepoint = np.roll(timepoint, timepoint.shape[1] // 2, axis=1) * 1e5 # rotating the data so it lines up with the earth correctly.\n",
    "        colours = accessvis.array_to_rgba(timepoint, colourmap=colourmap, minimum=220,maximum=550, flip=True, opacity=0.8) # converting to colours\n",
    "        accessvis.update_earth_values(lv, dataMode=0, data=colours) # Overlaying the data onto the earth\n",
    "\n",
    "        # A static earth is a little bit boring. Lets move it as well.\n",
    "        lv.reset()\n",
    "        lv.rotate('y', i)\n",
    "        lv.rotate('x',-80)\n",
    "        \n",
    "        lv.title(f'Ozone - {date}')\n",
    "        lv.render()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d99ca74c-18ff-4fd2-a070-f48f6d5d9ab6",
   "metadata": {},
   "source": [
    "## Calculating Grid Cell Area\n",
    "Below we are getting an approximate area of each grid cell."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "0333609e-f03f-441e-8405-f37ff0fa0438",
   "metadata": {},
   "outputs": [],
   "source": [
    "def calculate_area(lat_start, lat_delta, lon_delta):\n",
    "    # Area based on https://en.wikipedia.org/wiki/Spherical_segment where h=R(sin(lat1)-sin(lat2))\n",
    "    R = 6371009  # radius earth meters\n",
    "    area = 2 * np.pi * (R ** 2) * (\n",
    "                np.sin(np.deg2rad(lat_start)) - np.sin(np.deg2rad(lat_start + lat_delta))) * lon_delta / 360\n",
    "    return np.abs(area)\n",
    "\n",
    "\n",
    "def make_grid_area(ds, lat_name='lat', lon_name='lon'):\n",
    "    lat = ds[lat_name]\n",
    "    min_lat = float(lat.min())\n",
    "    max_lat = float(lat.max())\n",
    "    delta_lat = abs(float(lat[0] - lat[1]))\n",
    "\n",
    "    lon = ds[lon_name]\n",
    "    min_lon = float(lon.min())\n",
    "    max_lon = float(lon.max())\n",
    "    delta_lon = abs(float(lon[0] - lon[1]))\n",
    "\n",
    "    lon_grid, lat_grid = np.meshgrid(\n",
    "        np.arange(min_lon, max_lon + 0.0000001, delta_lon),\n",
    "        np.arange(min_lat, max_lat + 0.0000001, delta_lat)\n",
    "    )\n",
    "\n",
    "    grid = calculate_area(lat_grid, lat_delta=delta_lat, lon_delta=delta_lon)\n",
    "\n",
    "    grid_nc = xr.DataArray(grid, coords={'lat': lat_grid[:, 1], 'lon': lon_grid[1, :]}, dims=['lat', 'lon'])\n",
    "    return grid_nc\n",
    "\n",
    "grid_nc = make_grid_area(ds)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3d94a4e2-b5c4-4673-ad6c-3c9084884299",
   "metadata": {},
   "source": [
    "Sanity check: grid squares should be smaller near the poles"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "df5ebafe-3b2d-4cab-b459-d3274876b728",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots()\n",
    "c = ax.pcolormesh(grid_nc['lon'], grid_nc['lat'], grid_nc)\n",
    "fig.colorbar(c, ax=ax)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "53ba1802-76a9-4df9-857b-1597bc1c9265",
   "metadata": {},
   "source": [
    "Sanity check: Earth's surface area: 510.1 million km²"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "20801e2a-38db-46c3-b4f2-17a6e42f0bda",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "510035566625638.0 m\n",
      "510035566.62563795 km²\n",
      "510.0355666256379 million km²\n",
      "Error 0.01%\n"
     ]
    }
   ],
   "source": [
    "earth_sa = 510.1\n",
    "m2 = np.array(grid_nc).sum()\n",
    "km2 = 1e-6 * m2\n",
    "Mkm2 = 1e-6 * km2\n",
    "error = abs(earth_sa - Mkm2)\n",
    "print(f\"{m2} m\\n{km2} km²\\n{Mkm2} million km²\\nError {round(error / Mkm2 * 100, 2)}%\")\n",
    "#Check within ~1% tolerance\n",
    "assert(error < (earth_sa * 0.01))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "66104d05-ff28-4ce3-808b-8ef214896285",
   "metadata": {},
   "source": [
    "## Daily Ozone Hole Area\n",
    "* We make a mask of the ozone hole - A cell is a part of the ozone hole when it is at 220 Dobson units or lower.\n",
    "* We multiply this by the area of each cell and sum to get the total area of the hole.\n",
    "* We adjust units for readability."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "00bb87d9-df4f-4394-8427-2a8d7bcefff8",
   "metadata": {},
   "outputs": [],
   "source": [
    "def get_hole_all_time(threshold=220*1e-5):\n",
    "    below = ds['toz'] < threshold # Finding cells in of the ozone hole \n",
    "    hole_area = grid_nc * below\n",
    "    m2 = hole_area.sum(dim=('lat', 'lon')) # Total Area\n",
    "    km2 = 1e-6 * m2\n",
    "    Mkm2 = 1e-6 * km2\n",
    "\n",
    "    return Mkm2\n",
    "\n",
    "hole_size_daily = get_hole_all_time()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f85d6d36-d567-4e42-aa1e-ad4708dfdaa5",
   "metadata": {},
   "source": [
    "## Annual Maximum Ozone Hole Area\n",
    "Below we calculate the maximum hole area each year and plot this"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "41a964c9-94ab-4771-afcf-5a61a7249252",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.collections.PathCollection at 0x14c03c648f10>"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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UGLAQhTF/ZjfW22SMRKQtDFiIwpwvLSdaqxBMRPrDgIUozPnScuJYoC0jJRad2kUiIyUWq2cPwtje8RxwS0Sy46BbIh+ptQZJMGwtJ66l7d3NbswCbUQUSgxYiHyg1xok3krbuzs2FmgjolBhHRaiVoRDDRI9th4RkTb4ev/mFYmoFf5k0mhVqFtOXAftKjGINxSfSUSBY5cQ6YLcLQSsQSKfUHS36bWLj0jPtP9oSGHPdvOZmrMf6Y9sx9Sc/Sg8chJS9nayBok8/Clcp+XPJKLgMWAhTZPq5uOte4A1SOQTiu62cOjiI9Ij/mWSpklx82mthYY1SOQViu42dvERaQ/HsJDmBXPzcZcBZGuhccwAYg0S+aQmRKOkqrbl6zJ2t4XiM4koOHw0JM0LZnyJPy00oc6k0aNQdLexi49Im3jFJU2T4ubD7oHQCUV3G7v4iLSJXUKkaf5WanWH3QOhFYruNnbxEWkPAxYKuWBrqARz8/FnLh2STyi629jFR6QtDFgopKQq4BXozUeKFhoiIpIf5xKikFHTHD2cS4eIKDQ4lxCpnpoKeLF7gOTCOYuIpMEuIQopZujIiy1HocU5i4ikwysXyaq1p0vO0SMN1/Pa3GxVZI4l8oxzFhFJiwELyaa1GyYLeEnD9TxPf3E//tvEm2WoqanLk0gP+BdDsvDl6VJPBbxCNU7B3Xlu1yYCl0W14c1SBdjlSSQdjmEhWbT2dGmrmaKHAl6hHKfgep6z+pjw5NS+AHizVAMWJSSSDh+zSHLN1kutC77eMLWcoaOGcQq285zVx4SXZmag8sdzADg+KNTY5UkkLe3cGUgThBAo/emJMhxumGoYp5CaEI0IA7B0Uhp2l9VgxqoiVJ0+jwWZ6r5Z6j3dV09dnkRqwC4hkoytENz814ux58FMLMjsgbtf13/J+1B2vdie4l/54Bskx3XE/etK0GwFntj2FV6amYFVswbhpT3qq+AbLum+eujyJFILBiwkGVtrgxI3TDXVFwl0nIIUx2B7ik+IaQ/g5+Bpx2Ez7n3zUyydlIaNC0Y6fUaob5buKhzbutGUrnCsBC13eRKpCQMWkpQSN0w1PZ0HOnmilMdgMBiQ9lNw5Bg87ThsRt6XZgzpHochV8Vh8fhUVdwsfR2QTUTkyO+r1969ezF58mQkJSXBYDBg8+bNTu/fcccdMBgMTj/Dhg1rdbsbNmxAeno6oqKikJ6ejk2bNvm7a6QCjuNWdhw2Y/TfCnDbqiKs2FkOILiny6ZmqyoGuToKZJyCHMcQGRnhdpCnVQAHK0+jf3KsqsaIMIOJiPzl993j3Llz6N+/P1544QWPy0yYMAHV1dX2n/fee8/rNouKijBjxgzMmjULn332GWbNmoVbb70VBw8e9Hf3KITkvGEKIfDZ97WqGOTqyjZOYeOCkTj85wnYuGAkRvfq7LGlRK5j0NIgz3AYkE1E0vK7S2jixImYOHGi12WioqJgMpl83uZzzz2HG2+8EUuWLAEALFmyBIWFhXjuueewbt06t+s0NDSgoaHB/rvFYvH580gejjfMnALpxq3Yxjxs/ewHXNstTpVP5/6OU5DrGLQwyDPQbjTbumoZu0REypLlL33Pnj2Ij49Hr169MG/ePNTU1HhdvqioCOPHj3d6LSsrCwcOHPC4TnZ2NoxGo/0nOTlZkn2n4Pjb2uALW4tEjeUCAH08nct5DGof5BloSxDnRiIKb5JfySZOnIg333wT+fn5eOaZZ/Dxxx9j7NixTq0hrsxmMxISnAfaJSQkwGw2e1xnyZIlqKurs/9UVVVJdgwUHDlumOUn6vFR5WlN1BdpDQuK+R/Yqm3sEhEpT/KAZcaMGZg0aRL69u2LyZMn4/3338eRI0ewbds2r+u5XqiEEF6fyqOiohATE+P0Q/qVmhANq7iULj2udzxWzVL/OA1PtDTWRE7+BLZqHLtERMqSPa05MTER3bp1w9GjRz0uYzKZWrSm1NTUtGh1ofDkOOZBzfVF/KGFsSZqo8axS0SkHNkfS06dOoWqqiokJiZ6XGb48OHIy8tzem3nzp0YMWKE3LtHGuDaIrHv6En87q0SfPLdafv4BS0+Yat9rIna6GHsEhEFzu8WlrNnz6KiosL+e2VlJUpLSxEXF4e4uDgsW7YM06dPR2JiIr799ls8/PDDuPLKKzF16lT7OrNnz0aXLl2QnZ0NAPjtb3+LUaNGYfny5bj55puxZcsW7Nq1C/v27ZPgEEkP2CIR3oLJLCIiffD7L7y4uBgDBw7EwIEDAQCLFy/GwIED8cgjjyAyMhKHDh3CzTffjF69emHOnDno1asXioqKEB3981PQsWPHUF1dbf99xIgRWL9+PdasWYNf/OIXWLt2Ld566y0MHTpUgkMkvWCLRPjiuB8iMgid5ARaLBYYjUbU1dVxAC6RTrEOC5H++Hr/5l86EWkGW9mIwhf/2omIiEj1GLAQERGR6jFgISJy4Vo5l5V0iUJP9sJxRERaYpuzKCe/AuUn6pFmisbDk9KQkXI50+iJQogBCxHRT2wzg8/7qd5LVh8Tlk5KQ3JcR/syzc1WRHKwL5Hi+FdHRGGjta4exzmLsvqY8NLMDJSZ6zE1Zz/uX1cCc90Fp2CFXUVEymELCxE50WutE9euntSEaCwa2wNje8c7dfWUn6hHhAFYOikNu8tqcPfrxRifbsJzMwZgd1kN7n3jE6/rE5E8tH8VIiLJ2G7qU3P2I/2R7Ziasx+FR05C6/Ulm5qt2F1Wg3m5xSipqsX5xmaUVNVibm4x8stqnFpKUhOiMaR7HJLjOuLFggoY4By8tLY+EcmDAQsRAfDvpq41jl09joQAcgoq7C1ItjmL4mPaA7jU2uIYvLS2PhHJh11CRASg9Zu648STWlR+ot796+afX7fNWRTbsS2AS60t8dHtfV6fiOTDxwIistPzTTk1Idr96ybn1w0GA/p3jbW3ttTUX/BrfSKSBwMWIrLT0k3Zn+JutuDDdWyswQAszOzhNlvI1toy7/qrYa67gAWZvq9PRNJjwEIkMa1WSfX3ph5K/g4OtgUfq2cPQkZKLDq1i0RGSixWzx6Esb3jPY5BMRgMGN2rM0zG9rghzf/1iUg6BqH14f8/8XV6aiI5CSGwu6ym1dRZtRJCIL+sBjkFFSg31yPVFI2Fmeraf9fibjYGA7B69iCM7tXZYwARbMq2XlO+iULJ1/s3AxYiiQRzI1UTLdyUp+bsR0lVbYvXM1JisXHBSOV3iIgC5uv9W11XIQobWu028cbX1Fm1c91PNe63VgcH6/F7T6QUpjWT4nytOKpFWr2Rak1qQrTbFhY1Dg62keN7r4XWMCKp8JtNitJzcTJAW1k2WqWlwcE2cnzv9VqVmMgTBiykKL10m7ijxRupFgWa8RNKUn/v9R74E7nDLiFSTLPVisiICN12mzjeSNWcZaMHtnRjx+q7Tc1WVZ9j1+99hAGXyv5f3tHvbem9KjGROwxYSBFCCJRW1eLabnGaHH/gKy3eSLVKysHBSowFcfzeZ/UxYemkNCTH/Rys+PuZeg38iTxRX9sp6Y6t+frWfxSh6vR53VcM1UKWDf1MibEgjt2FWX1MeGlmBsrM9UF9JsdLUbhhHRZShK1uhu1ivbusBi/tYbcJhZaStXNsRfn6JBlx6Hgd7n498M9sarai8MhJzJVpv6VscWImE7WGheNIVdIf2Y7zjc0ApGkOJ5KKkkXomputiIyMkOQz5apKLGW1Zq1XfiZl+Hr/5hgWUoRj//2Ow2bkfWnGkO5xGHJVHBaPT2WwQiEj1VgQX1oSIn/6PdDPdNymwWDAKInHS7lrcbJlH/nbciPltogAjmEhBbhL97UK4GDlafRPjtXFuBXSLinGgvg7DiaQz3T3GXtdPiPYAEDK9Gs9lzCg0OA3hmSnxboZFB6kqJ3jb02UQD5TyborUmYfMZOJpMQuIVIE031JjaSoneNvTZRAPlPJuitSlh3QcwkDUh4DFlIM031JjaQIpv1tSQjkM5VorbC1/rjLPrK1/vgzhkWqbakVM6CU5feZ3bt3LyZPnoykpCQYDAZs3rzZ/t7Fixfxhz/8Af369UOnTp2QlJSE2bNn44cffvC6zbVr18JgMLT4uXDhgt8HRETkr2CD6UDGpHj7THddPErUXZGy+1bvXcGcy0l5frewnDt3Dv3798edd96J6dOnO713/vx5fPrpp/jTn/6E/v3748yZM3jggQfwq1/9CsXFxV63GxMTg/LycqfX2rdv7+/uEREpSuqWBMdZnZPjOuLhm9Jw5WXtFGutkLL7Vq9dwcyACg2/A5aJEydi4sSJbt8zGo3Iy8tzeu3555/HkCFDcOzYMaSkpHjcrsFggMlk8nd3iIhCSso5pBxvhOPTTXhuxgDsLqvBp9+dxu+zemPVrEGKFFyUsvtWj13BnMspNGQfw1JXVweDwYDY2Fivy509exbdunVDc3MzBgwYgMcffxwDBw70uHxDQwMaGhrsv1ssFql2mYjIL1K1JNhuhAYASyelYXdZjb0i7jc/nsfSSWlOheX00FqhVcyAUp6soe6FCxfwxz/+Eb/+9a+9Vq/r3bs31q5di61bt2LdunVo3749Ro4ciaNHj3pcJzs7G0aj0f6TnJwsxyEQEflEqpaE8hP1l2ZxjuuIFwt+forfcdiM0X8rwG2rirBiZ3lQn0HB41xOypPt237x4kXcdtttsFqtePHFF70uO2zYMPzmN79B//79cf311+Ptt99Gr1698Pzzz3tcZ8mSJairq7P/VFVVSX0IRESKS02IRnz0pfF7rk/xVgF8+M1pvLqvMhS7Rj+Ron4P+U+WgOXixYu49dZbUVlZiby8PL/n9omIiMDgwYO9trBERUUhJibG6YeIyJW7wm1qZbsR1tRfypDkU7w66T0DSq0kH8NiC1aOHj2KgoICXHHFFX5vQwiB0tJS9OvXT+rdI6Iw4phxo4XJ92w3QgAw113Agswebmd11ksdEy3TawaUmvkdsJw9exYVFRX23ysrK1FaWoq4uDgkJSXhf/7nf/Dpp5/i3XffRXNzM8xmMwAgLi4O7dq1AwDMnj0bXbp0QXZ2NgDgsccew7Bhw9CzZ09YLBasXLkSpaWlyMnJkeIYiSgMhTL1NJiCYrYbYZvICCTERAWdfcTiZvLRYwaUmvkdsBQXFyMzM9P+++LFiwEAc+bMwbJly7B161YAwIABA5zWKygowJgxYwAAx44dQ0TEz/+xtbW1uPvuu2E2m2E0GjFw4EDs3bsXQ4YM8Xf3iIgAhC71VIpWHccZmX19incNRJqbrYiIMGiqhYnIG4PQSVk+i8UCo9GIuro6jmfRET4dUjDSH9mO843NLV7v1C4Sh/88QfLPc9eqA1zqxpGzVUcIgd1lNfbAJM0UjdfuGooPvzml+L4Q+cvX+ze/raRaLH1NwVJ60GprrTpyBAjuZnJu2yYCl0W1UXxfiOTEbyypkruLsG38QX5ZjaozPUgdQpV6qnRBMXdBkqe0aLn3hUhODFhIlULxpEr6InfqqWvA0/zT76FIRXYNTJgWTXoke2l+okDx6ZCCJVfqqaeBtaN7dVZskkJHqQnRKKmqtf/+UeVpVJ0+z7Ro0hV+W0m1pHg61FLRMJKH1Kmn3rorv6y2KF5QzF3Xl1UAf3nvK9yQ5vu+8G+F1I5ZQqRKTc1WFB456fZJ1dcMB9fMCaZ0klSm5ux3atGwyUiJxcYFIxXPbhNCIL+sxm29lmaraHVf+LfSEjMUlePr/ZsBC6mWt4twaxfRUKWXUniQI1062BtkoOvzb6UlBnDK8vX+zTEspFrBjD8IVdEwCg+uY0bsrwc4mFXKYnOefve2ntR/K4EET0q1aLT2OaGskEze8ayTqgUz/oCDdkkOUqdLqyGFX8q/lUDqJylVc8mXz2GGonrxzJNuMaWT5CB1urQabpBS/a0EEnwpFbD58zl82FEnBiykS6EqGkbhwdZduXHBSBz+8wRsXDASo3t1Dnh8QyhvkFL+rQQSfCkVsPnzOXzYUScGLKRLchcNI5IyXTqUN0ip/1YCCb6UCth8+Rw+7KgXB92SbslVNIxISrYbpNLF5hxJ+bcSyIBkqQcxB/M5jgFcIBmKJB8+ZpKuSV00jEhqamkNlOJvJZDWCaVaNPz5HKm7/EgarMNCRKQCeilUFkj9pGBqLsm9byQ/Fo4jxejlQktE0vB2TfDl3+5+V2LfKDRYOI4UIUXBKyLSF0/dS7brxSffnsbvs3qjoPwkXiy4dO1IM0Xj4UlpyEi5HAaDwe8gwtdAhN3E2sUWFgoYS3oTka9s14v5rxdjz4OZKDPXu51JOpBrB0vpa5uv92/eTShgaih4RUTaYLteDL4qDslxHfFigTTXDjVUCiZl8I5CQWFFSCLtcL15K30zLz9Rj/jo9vZ/u13Gz2sHH5zCB/8nKSisCEmkDXLM1+NvAJSaEI2a+gv2f7sze0Q3v7fLB6fwwICFAsaKkETaIEe3ib8BkO168fG3p1F1+jwWZLa8dkzoa8JDWb2dtrv8/a9wocl7AMMHp/DAgIUCppaCV0TkndTdJoEEQLbrxapZg/Cvj77DuJ/+bbt2DOoWi6dv6e+03et7dsbvs3qj6OtTbgOjpmYrH5zCCNOaKSgsf0+kPu5SeqXsNmktAHK8HjhyvV5kpnbGjenOy9q2G2EAlk5Kw+6yGqdsopKqWrzzyfcY2zveKUV61axBeGkPC8LpGQMW8pmnOgesa0CkHq61kaYN7IInpvaTbL6eZqsVkRERAQdAjtcHd9cK23aHdL+UTXT/uhKnwCjCAPzfTWnY9dXPgcw3P57H0klp2LhgpH05PjjpD+8s5BM5Bux5EupMBiKtctdV86+PjqHq9HksdDNmJDIC+L9JaWi2+vY3JoRA6U9Bj1zjRmzb9ZRNZAtkHNOidxw2Y/TfCnDbqiKs2FkOgA9OesT/UWqVknUOlAyMiPTGXVeNVQBPbPsKY9Ocx5vdO+ZqfPZoFq7tFofIiJ/L43tiuw7c+o8ij4Nmgx034jgexVM2kadAxiqAD785jVf3VQb02aR+DFioVUrVOWABKKLgueuq2XHYjN+tL3WagfihrN748Bv3g1ndsV0Hmq2XAiDXQbNSDLh3HMjf1GzF92daBkatpUX708LD1lxt4RgW8okSdQ4CHchHRD/zNFal6sx5p4kGXafVsD0ceCuNb7sO7Dhsxr1vfirLuBHXgbldYjtg9exB9hmWm5qtONvQhEVje2Cum2lBbC08rQVNrmN9XOcyIvVhwEI+kWrAXmtYAIoocLYuldZu5IE+HDheB3YcNiPvSzOGdI/DkKvisHh8qmStrY7bcZeJ2NxstbfE2AIZfzKDXAO2rD4mLJ2UhuS4jk7L+DtFAGeBlhcDFmqVrxdBKSgVGBHpkWOXSms3cn8fDtxdB6wCOFh5GvOuv1rWG7TrdiN/+j3QkgqOAVtWHxNempmB3WU1uH9dSUCTJ3LWemX4/e3au3cvJk+ejKSkJBgMBmzevNnpfSEEli1bhqSkJHTo0AFjxozB4cOHW93uhg0bkJ6ejqioKKSnp2PTpk3+7hrJRKkCcSwApQ8cFxBathYJ21iVjQtGYnSvzi1unP6OAVFLoUjH71ObyAg0u/zuq/IT9S1qvQQydo5j75TjdwvLuXPn0L9/f9x5552YPn16i/f/+te/YsWKFVi7di169eqFJ554AjfeeCPKy8sRHe3+D6GoqAgzZszA448/jqlTp2LTpk249dZbsW/fPgwdOtT/oyLJKVEgzp+nQ1InPmmqQ2u1kQJtNQ11oUgpv1+pCdGIahvhttbLpc/ybewcx94pxyCCyBc1GAzYtGkTpkyZAuDSlykpKQkPPPAA/vCHPwAAGhoakJCQgOXLl2P+/PlutzNjxgxYLBa8//779tcmTJiAyy+/HOvWrXO7TkNDAxoaGuy/WywWJCcno66uDjExMYEeEqkA+4K1yd1ATuDSTdDbQE4KDSEE8stqNPNwIOX3q6nZisIjJ7Hlsx+w8raBSH9kO843NrdYrlO7SBz+84RWtxfs+uHOYrHAaDS2ev+W9OpRWVkJs9mM8ePH21+LiorC6NGjceDAAY/rFRUVOa0DAFlZWV7Xyc7OhtFotP8kJycHfwCkCqycq01Kpb+TNHztOlILKb9fttbcOcO7AQg+RZqTLypD0iuI2WwGACQkODeBJSQk2N/ztJ6/6yxZsgR1dXX2n6qqqiD2nIikwCwvbdHaw4GU3y+DwYD+XWODHjvHsXfKkeXb6RqhCyFajdr9XScqKgoxMTFOP0QUWnzSJDlJ/f2ypXgHM5hYicHIUg5k1/KgeEnTmk0mE4BLLSaJiYn212tqalq0oLiu59qa0to6RKQuSqa/U/iR8/sV7GBiOQcjSznQWOuD4iW9enTv3h0mkwl5eXn21xobG1FYWIgRI0Z4XG/48OFO6wDAzp07va5DROqilrRX0ie5v1/Bdo/J0b0mZcq0HtKv/W5hOXv2LCoqKuy/V1ZWorS0FHFxcUhJScEDDzyAJ598Ej179kTPnj3x5JNPomPHjvj1r39tX2f27Nno0qULsrOzAQC//e1vMWrUKCxfvhw333wztmzZgl27dmHfvn0SHCIRKSXUaa+kb+H2/ZIyZVoP6dd+ByzFxcXIzMy0/7548WIAwJw5c7B27Vo89NBD+O9//4sFCxbgzJkzGDp0KHbu3OlUg+XYsWOIiPg5+hwxYgTWr1+PpUuX4k9/+hOuueYavPXWW6zBQqRBWhvISdoSyPdLy6USpBxorPVB8UHVYVETX/O4iYgofAghsLusRrPjNqbm7Hc7XUlGSqzTxJNKb0tKIanDQkREpBZyjNtQMstGypRpPaRfM2AhIiJdkrqYoS3LZmrOfqQ/sh1Tc/aj8MhJyNVRIeVAYz0MimeXEBER6ZZUZfNDOfWElGNw1Dieh11CREQU9qQqNhfKqSekHMiu5UHx2tlTIiIiP0g9bkPrWTZax4CFiIh0SepxG+E69YRayvlLWpqfiIhITaQqNheuU0+oqZw/B90SERH5QAiB/LIa5BRUoNxcj1RTNBZmur95q3Fwq7+UGmjs6/2bLSxEREQ+8LW1Rk2tEsFQWzl/bYV7REREIdRalo0eJhl0pKaBxgxYiIiIJBLK9Gc5qGmgsbbOHBERkcq5tkpEGIBhV8fhms6XBb1trU4NIAWOYSEiIpJQakK0fZLBrD4mLJ2UhuS4jvb3Ax2Aq/TYGMe0cF8GGsuNWUJERBQ0PWTFSKGp2YrCIycxN7cY49NNeGlmBnaX1eDFguCCDL1MDeCOr/dvBixhRO/zURBRaAghsLusRvNZMVKxpT/3STLi0PE63P26NEHG1Jz99pYbRxkpsdi4YKQEex4aTGsmJ1I2JeolZY+Igufuyd+WFSP3k79aGQwGjOnVGZGREbj3jU8kSwtWU8ZOKITXtyhMSZlmp7eUPSIKjt6yYqQS+dNxSxlkqCljJxTC85sUZqS8oPDiRESuwv3J3xupggy1ZeyEAu8uYULKCwovTkTkKNyf/D2RMsiQeiJHLeIYljDhmGbn9HoAFxQpt0VE2haukwL6Quq0YH8mctRjYgSzhMKAY5pdsCPVpdwWEemDP5MChiOlgwetZW0xrZmcSHlB4cWJiFzp8Ylei0JZryVQDFioBdZhISLSP63Va/H1/s07TBhpbZbRUG2LiIiko9fECN5liIiIdESvWVsMWIiIyCMlZwcOB3KfTz3Xa2FaMxERucVpOKSlxPlU2wzLUuKgWyIiakGL2SZqpvT51FJiBAfdEhFRwDgNh7SUPp96TIzQ/hEQEZEs9JptEio8n8GRPGC56qqrYDAYWvwsXLjQ7fJ79uxxu3xZWZnUu0ZERH7Qa7ZJqPB8BkfygOXjjz9GdXW1/ScvLw8AcMstt3hdr7y83Gm9nj17Sr1rYYkj/IkoEHrONgkFns/gSZ4l1LlzZ6ffn3rqKVxzzTUYPXq01/Xi4+MRGxsr9e6ENY7wJ6JA6TnbJBR4PoMna1pzY2Mj3njjDSxevLjV/4yBAwfiwoULSE9Px9KlS5GZmel1+YaGBjQ0NNh/t1gskuyzXrgbkV5SVYu5ucUc4U9EPvFndmBqndrPp9ozi2Tdk82bN6O2thZ33HGHx2USExOxatUqbNiwARs3bkRqairGjRuHvXv3et12dnY2jEaj/Sc5OVnivdc2jvAnIinoMdsklLydz1B24dta5Kfm7Ef6I9sxNWc/Co+chJoqn8hahyUrKwvt2rXDf/7zH7/Wmzx5MgwGA7Zu3epxGXctLMnJyazD4iD9ke0439jc4vVO7SJx+M8TQrBHRETkjhACu8tqQtKFH+qaOyGvw/Ldd99h165dmDt3rt/rDhs2DEePHvW6TFRUFGJiYpx+yJmvI9I5MJeIKHSamq3YXVaDebnFKKmqxfnGZnsXfn5ZjezXZK20yMu2F2vWrEF8fDwmTZrk97olJSVITEyUYa/Ch68j0rXQDEhEpGdqCBi0UCNGlrNgtVqxZs0azJkzB23aOI/rXbJkCWbPnm3//bnnnsPmzZtx9OhRHD58GEuWLMGGDRuwaNEiOXZN9aRq7XAckZ6REotO7SKRkRKL1bMHYWzveLSJjAh5VE9ERJeEOmDQQo0YWbKEdu3ahWPHjuF///d/W7xXXV2NY8eO2X9vbGzEgw8+iOPHj6NDhw7o06cPtm3bhptuukmOXVM11zTkNFM0Hp6UhoyUywPqw/Q2Ir35p9Hf3qJ6x/WIiEg+qQnRKKmqbfm6AgGDrUV+rpsxLLYWeTV0C3HyQ5VwHfSU1ceEpZPSkBzX0WkZKb40Qgh88YMF/boYOTCXiCjEmpqtKDxy0m3A4G3Qq5RpyEII5JfVhKRGjK/3b1nrsJDvHFs7svqY8NLMDOwuq8H960okHTFuC4xWf/AN1t89PKRRPRERBVZUTurCoGqvEQOwhUVV0h/ZjgsXm1H4+0yUmetx9+vypJhNzdmPz76vlf1ziIjId762mIQ6DVlqIU9rJv+lJkRjSPc4JMd1xIsFvo8Y93egbvmJelgF8MS2rzCudzxWzfI8MJeIiJTha5E+NWQVhQK7hFTCNuhpy2c/APB9xHggzYK2bqAdh824981PsXRSGjYuGOm0L2pqBiQiImf+ZBWpveS+r7S3xzpl68OcM7wbAN9SzAJJS3atz7LjsBmj/1aA21YV4YvjdfbsISIiUi9394gIAzAto4vTa3qqtcU7k4oYDAb07xrrc9G3QJoF3dVnGZAci3nXX40+STGIZLBCRBqn9+rd7u4RWX1MKPx9Jh6f0s/+2kWd1dpil5DK2IIMX0eMB1JsSAujwYmIAiF19owauWYVJV/eEc/eNgD5X/2cWTptYBc8MbWfrmptMWBRKV+DikDTkjkDKxHpjbvsGVuLghazZ7xxvEc0NVuRX1aDeQ4Zn5YLTQBCX0FXSvr4n9Op1oIKX7uOiIjCgVzZM2rtYrIdj7vjrqm/AEAbJfd9xYDFC7V+SW18mS+IiCicSN2ioJVBq67H/VHlaVSdPo8Fmfp5qGWXkAda6QfleBQiop9JWb1bS11Mrsdtq7X10m8y/Kqgq2asdOuG3qoIEhGFg0Dn5PFmas5+twFQRkqsU/2qUPJ23FsWjkRaYgzaqrgOCyvdBiFcqwgSEWmZHN3kWhi06u24+3UxOgUrtuW1iF1CHmjhSyoHvVREJKLwJHU3uZwTxEp5vQ2H4QG8E3mgp5HVvtLK4DIiIm+kKtsgZyamHNdbvZer0NfRSCQc04UDKfNPRKRncmVi8nobGHYJueFaRVDrI6t90dq4Ha1VRCQikoIcXS283gaGAYsH4dAf6Cpcx+0QEXkjR1cLr7f+Y5eQF3rvD3QVjuN2iIhCgddb/+n7Dkw+C8dxO0REocDrbWAYsChIzaX+WeafiEgZvN4GhpVuFSKEwO6yGslK/ctVL4V1WIiIlMHr7SW+3r8ZsChA6lL/Ugc/REREocLS/CoiZal/5u8TEVE4YsCiEKlS2DjPERERhSPe3RQiZQob8/eJiEgKak4GccWARQFSp7Axf5+IiIKltfnjGLBIzF20KmUKG/P3iYgoWFocD8ksIQm1lr0jVQqbEAL5ZTVhM88RERFJb2rOfpRU1bZ4PSMlFhsXjFRsP3y9f3MuIYm4S122RaueUpcDHSAbjvMcERGRtLQ2HlLyLqFly5bBYDA4/ZhMJq/rFBYW4tprr0X79u1x9dVX4+WXX5Z6tyTn2lymdPZOuM1zRERE0tLaeEhZ7nJ9+vRBdXW1/efQoUMel62srMRNN92E66+/HiUlJXj44Ydx//33Y8OGDXLsmiRcByo9s7McgPaiVSIiCk9aHA8pS5dQmzZtWm1VsXn55ZeRkpKC5557DgCQlpaG4uJiPP3005g+fbocuxcUd10/H397GsClaNVdf6Bao1UiIgpPjskgWhkPKUvAcvToUSQlJSEqKgpDhw7Fk08+iauvvtrtskVFRRg/frzTa1lZWXj11Vdx8eJFtG3b1u16DQ0NaGhosP9usVikOwAv3HX9fFR5GlWnz2NBZg/c/XrL8vu2aJXdNkREpBZaGw8p+R106NChyM3NxY4dO/DKK6/AbDZjxIgROHXqlNvlzWYzEhISnF5LSEhAU1MTfvzxR4+fk52dDaPRaP9JTk6W9Di8ce36sQrgiW1fYRxn3yQiIg3R0nhIyVtYJk6caP93v379MHz4cFxzzTV47bXXsHjxYrfruEZztkxrb1HekiVLnLZnsVgUC1rcdf3sOGzG33aW4f/dmKqZaJWIiEgrZA+lOnXqhH79+uHo0aNu3zeZTDCbzU6v1dTUoE2bNrjiiis8bjcqKgoxMTFOP3KyDUDyNlBpULe4FuupOVolIiLSCtnvpg0NDfjqq6+QmJjo9v3hw4cjLy/P6bWdO3di0KBBHsevKM0xK2jx258hs3c8Xpn1c9fPoG6x+Pc9w9n1Q0REJBPJu4QefPBBTJ48GSkpKaipqcETTzwBi8WCOXPmALjUlXP8+HHk5uYCAO655x688MILWLx4MebNm4eioiK8+uqrWLdundS7FhDXrKCSqlo0NFmxdFKavRKgVBVsiYiIyD3JA5bvv/8et99+O3788Ud07twZw4YNw4cffohu3boBAKqrq3Hs2DH78t27d8d7772H3/3ud8jJyUFSUhJWrlypmpRmd1lBOw6bkfelGX+Z0he3DUnBniMnPZbjJyIiouBxLiEfpD+yHecbm51eizAAex/KRJm53qkmC3BpPIuncvxERET0M1/v37yb+sBd+eIh3ePQ9fKOipbjJyIiCle8o7bCU1ZQfEx7ACzHT0RE+uNaml8NpfoZsLTCsXyxY0G4OcMvjcnR2uRRRERE3rjOlzc1Zz8Kj5xEqEeQcAyLj9xlAgFA4ZGTmMsxLEREpAPu5ssD5L2vcQyLxNyVL/bU+sJy/EREpEXuMmMBdYzNlGXyw3CitcmjiIiIvFHr2Ew2AUhAS5NHEREReaPWsZm8sxIREREA7/PlLczsEdJsIQYsOqPGVDQiItIGNY/N5BgWHbGlonGaACIiCpRax2ayhUUnmpqt2F1Wg3m5xSipqsX5xmaUVNVibm4x8stq2NJCREQ+U+PYzNDvAUlCzaloREREweJdTEfUmopGREQULAYsOqLWVDQiIqJgMWDRCTWnohEREQWLAYtOqDkVjYiIKFhMa9YRtaaiERERBYuP3TqjxlQ0IiKiYPFuRkRERKrHgIWIiIhUjwELERERqR4DFiIiIlI9BixERESkegxYiIiISPUYsBAREZHqMWCRkWs5fJbHJyIiCgwr3cpECIE9R04iJ78C5SfqkZoQjUVje2Bs73hWniUiIvITW1hk0NRsxe6yGszLLUZJVS3ONzajpKoWc3OLkV9Ww5YWIiIiPzFgkUGbyAjk5FdACOfXhQByCipYLp+IiMhPvHPKpPxEvfvXze5fJyIiIs8YsMgkNSHa/esm96+rFQcOExGRGkgesGRnZ2Pw4MGIjo5GfHw8pkyZgvLycq/r7NmzBwaDocVPWVmZ1LuniKZmKxaN7QHXsbUGA7Aws4dmbvq2gcNTc/Yj/ZHtmJqzH4VHTkK49nURERHJTPKApbCwEAsXLsSHH36IvLw8NDU1Yfz48Th37lyr65aXl6O6utr+07NnT6l3TxFtIiMwtnc8Vs8ehIyUWHRqF4mMlFisnj0IY3vHo01khOpbLjhwmIiI1ETytObt27c7/b5mzRrEx8fjk08+wahRo7yuGx8fj9jYWJ8+p6GhAQ0NDfbfLRaL3/sqJ4PBgNG9OmNcWoL9taZmKwwGgyZSnlsbOOx4XERERHKTfQxLXV0dACAuLq7VZQcOHIjExESMGzcOBQUFXpfNzs6G0Wi0/yQnJ0uyv1JyzQaytaxopeWCA4eJiEgtZA1YhBBYvHgxrrvuOvTt29fjcomJiVi1ahU2bNiAjRs3IjU1FePGjcPevXs9rrNkyRLU1dXZf6qqquQ4BMlpKeVZLwOHiYhI+2StdLto0SJ8/vnn2Ldvn9flUlNTkZqaav99+PDhqKqqwtNPP+2xGykqKgpRUVGS7q9StNByYRs4PDe32Cm4chw4rKbgioiI9E22O859992HrVu3oqCgAF27dvV7/WHDhuHo0aMy7FnoaaHlwpeBw0REREqRvIVFCIH77rsPmzZtwp49e9C9e/eAtlNSUoLExESJ9y70tNRy4W3gMBERkZIkD1gWLlyIf/3rX9iyZQuio6NhNpsBAEajER06dABwafzJ8ePHkZubCwB47rnncNVVV6FPnz5obGzEG2+8gQ0bNmDDhg1S717IObZc5BRUoNxcj1RTNBZmqitLyMbdwGEiIiKlSR6wvPTSSwCAMWPGOL2+Zs0a3HHHHQCA6upqHDt2zP5eY2MjHnzwQRw/fhwdOnRAnz59sG3bNtx0001S754qsOWCiIjIPwahk7KlFosFRqMRdXV1iImJCfXuEBERkQ98vX+zfZ+IiEhl1F4NPRRkTWsmIiIi/2ihGnoosIVFBRhJExERwHncvGELS4gxkiYiIhvO4+YZW1hCiJE0ERG50kI19FBgwBJCWppXiIiIlKGFauihwDtiiDGSJiIiG1s1dNcRAY7V0MMVA5YQYyRNREQ2nMfNMw66DSEtzStERETKYDV093g3DCFG0kRE5A7ncWuJLSwhxkiaiIiodQzZVICRNBERkXe8M2oIK+ISEVG4YpeQRrAiLhERhTO2sGgAK+ISEVG4Y8CiAayIS0RE4Y53Oo1gRVwiIgpnDFg0ghVxiYgonDFg0QDOLUFEROGOAYsGsCIuERGFO6Y1awQr4hIRUTjjo7mGsCIuERGFK97xiIiISPUYsBAREZHqMWAhIiIi1WPAQkRERKrHgIWIiIhUjwELERERqR4DFiIiIlI9BixERESkegxYiIiISPUYsBAREZHq6WYuISEEAMBisYR4T4iIiMhXtvu27T7uiW4Clvr6egBAcnJyiPeEiIiI/FVfXw+j0ejxfYNoLaTRCKvVih9++AHR0dGSzmBssViQnJyMqqoqxMTESLZdLQn3cxDuxw/wHPD4w/v4AZ4DOY9fCIH6+nokJSUhIsLzSBXdtLBERESga9eusm0/JiYmLL+kjsL9HIT78QM8Bzz+8D5+gOdAruP31rJiw0G3REREpHoMWIiIiEj1GLC0IioqCo8++iiioqJCvSshE+7nINyPH+A54PGH9/EDPAdqOH7dDLolIiIi/WILCxEREakeAxYiIiJSPQYsREREpHoMWIiIiEj1wiJg2bt3LyZPnoykpCQYDAZs3rzZ6f0TJ07gjjvuQFJSEjp27IgJEybg6NGjLbZTVFSEsWPHolOnToiNjcWYMWPw3//+1/7+mTNnMGvWLBiNRhiNRsyaNQu1tbUyH13rpDh+s9mMWbNmwWQyoVOnTsjIyMC///1vp2XUevzZ2dkYPHgwoqOjER8fjylTpqC8vNxpGSEEli1bhqSkJHTo0AFjxozB4cOHnZZpaGjAfffdhyuvvBKdOnXCr371K3z//fdOy+j5HJw+fRr33XcfUlNT0bFjR6SkpOD+++9HXV2d03bUeA6k+g44Ljtx4kS3f09qPH5A2nOgxWuhVMev1WuhL8e/ceNGZGVl4corr4TBYEBpaWmL7YT0OijCwHvvvSf+7//+T2zYsEEAEJs2bbK/Z7VaxbBhw8T1118vPvroI1FWVibuvvtukZKSIs6ePWtf7sCBAyImJkZkZ2eLL774Qhw5ckS888474sKFC/ZlJkyYIPr27SsOHDggDhw4IPr27St++ctfKnmobklx/DfccIMYPHiwOHjwoPj666/F448/LiIiIsSnn35qX0atx5+VlSXWrFkjvvjiC1FaWiomTZrU4vieeuopER0dLTZs2CAOHTokZsyYIRITE4XFYrEvc88994guXbqIvLw88emnn4rMzEzRv39/0dTUZF9Gz+fg0KFDYtq0aWLr1q2ioqJC7N69W/Ts2VNMnz7d6bPUeA6k+g7YrFixQkycOLHF35MQ6jx+IaQ7B1q9Fkp1/Fq9Fvpy/Lm5ueKxxx4Tr7zyigAgSkpKWmwnlNfBsAhYHLleYMrLywUA8cUXX9hfa2pqEnFxceKVV16xvzZ06FCxdOlSj9v98ssvBQDx4Ycf2l8rKioSAERZWZm0BxGEQI+/U6dOIjc312lbcXFxYvXq1UII7Ry/EELU1NQIAKKwsFAIcSloM5lM4qmnnrIvc+HCBWE0GsXLL78shBCitrZWtG3bVqxfv96+zPHjx0VERITYvn27EEL/58Cdt99+W7Rr105cvHhRCKGdcxDM8ZeWloquXbuK6urqFn9PWjl+IQI/B3q5FgZ6/Hq5Froev6PKykq3AUuor4Nh0SXkTUNDAwCgffv29tciIyPRrl077Nu3DwBQU1ODgwcPIj4+HiNGjEBCQgJGjx5tfx+41ERqNBoxdOhQ+2vDhg2D0WjEgQMHFDoa//ly/ABw3XXX4a233sLp06dhtVqxfv16NDQ0YMyYMQC0dfy2Loy4uDgAQGVlJcxmM8aPH29fJioqCqNHj7bv+yeffIKLFy86LZOUlIS+ffval9H7OfC0nZiYGLRpc2laMq2cg0CP//z587j99tvxwgsvwGQytdiuVo4fCOwc6OlaGOh3QC/XQtfj90Wor4NhH7D07t0b3bp1w5IlS3DmzBk0NjbiqaeegtlsRnV1NQDgm2++AQAsW7YM8+bNw/bt25GRkYFx48bZx3qYzWbEx8e32H58fDzMZrNyB+QnX44fAN566y00NTXhiiuuQFRUFObPn49NmzbhmmuuAaCd4xdCYPHixbjuuuvQt29fALDvX0JCgtOyCQkJ9vfMZjPatWuHyy+/3Osyej4Hrk6dOoXHH38c8+fPt7+mhXMQzPH/7ne/w4gRI3DzzTe73bYWjh8I/Bzo5VoYzHdAD9dCd8fvi1BfB3UzW3Og2rZtiw0bNuCuu+5CXFwcIiMjccMNN2DixIn2ZaxWKwBg/vz5uPPOOwEAAwcOxO7du/HPf/4T2dnZAACDwdBi+0IIt6+rhS/HDwBLly7FmTNnsGvXLlx55ZXYvHkzbrnlFnzwwQfo168fAG0c/6JFi/D55587PRHauO6nL/vuuky4nAOLxYJJkyYhPT0djz76qNdteNtOKAR6/Fu3bkV+fj5KSkq8bl/txw8Efg70ci0M5m9AD9dCb8cfCKWug2HfwgIA1157LUpLS1FbW4vq6mps374dp06dQvfu3QEAiYmJAID09HSn9dLS0nDs2DEAgMlkwokTJ1ps++TJky0idrVp7fi//vprvPDCC/jnP/+JcePGoX///nj00UcxaNAg5OTkANDG8d93333YunUrCgoK0LVrV/vrtqZ91+i/pqbGvu8mkwmNjY04c+aM12X0fA5s6uvrMWHCBFx22WXYtGkT2rZt67QdNZ+DYI4/Pz8fX3/9NWJjY9GmTRt7N9j06dPt3QFqP34guHOgh2thMMevh2uhp+P3RaivgwxYHBiNRnTu3BlHjx5FcXGxvdn3qquuQlJSUosUsCNHjqBbt24AgOHDh6Ourg4fffSR/f2DBw+irq4OI0aMUO4gguDp+M+fPw8AiIhw/rpERkban7jUfPxCCCxatAgbN25Efn6+PRCz6d69O0wmE/Ly8uyvNTY2orCw0L7v1157Ldq2beu0THV1Nb744gv7Mno/B8CllpXx48ejXbt22Lp1q9PYJ0C950CK4//jH/+Izz//HKWlpfYfAHj22WexZs0aAOo9fkCac6Dla6EUx6/la2Frx++LkF8HgxqyqxH19fWipKRElJSUCABixYoVoqSkRHz33XdCiEuZDgUFBeLrr78WmzdvFt26dRPTpk1z2sazzz4rYmJixDvvvCOOHj0qli5dKtq3by8qKirsy0yYMEH84he/EEVFRaKoqEj069cv5KlsQgR//I2NjaJHjx7i+uuvFwcPHhQVFRXi6aefFgaDQWzbts2+nFqP/9577xVGo1Hs2bNHVFdX23/Onz9vX+app54SRqNRbNy4URw6dEjcfvvtbtOau3btKnbt2iU+/fRTMXbsWLfpfHo9BxaLRQwdOlT069dPVFRUOG1H7edAqu+AK3hIa1bb8Qsh3TnQ6rVQiuPX8rXQl+M/deqUKCkpEdu2bRMAxPr160VJSYmorq62LxPK62BYBCwFBQUCQIufOXPmCCGE+Pvf/y66du0q2rZtK1JSUsTSpUtFQ0NDi+1kZ2eLrl27io4dO4rhw4eLDz74wOn9U6dOiZkzZ4ro6GgRHR0tZs6cKc6cOaPAEXonxfEfOXJETJs2TcTHx4uOHTuKX/ziFy1S+9R6/O6OHYBYs2aNfRmr1SoeffRRYTKZRFRUlBg1apQ4dOiQ03b++9//ikWLFom4uDjRoUMH8ctf/lIcO3bMaRk9nwNP3yMAorKy0r6cGs+BVN8Bd9t1DVjUePxCSHsOtHgtlOr4tXot9OX416xZ43aZRx991L5MKK+Dhp8OhIiIiEi1OIaFiIiIVI8BCxEREakeAxYiIiJSPQYsREREpHoMWIiIiEj1GLAQERGR6jFgISIiItVjwEJERESqx4CFiIiIVI8BCxEREakeAxYi0rXm5mb7TLpEpF0MWIhIMbm5ubjiiivQ0NDg9Pr06dMxe/ZsAMB//vMfXHvttWjfvj2uvvpqPPbYY2hqarIvu2LFCvTr1w+dOnVCcnIyFixYgLNnz9rfX7t2LWJjY/Huu+8iPT0dUVFR+O6775Q5QCKSDQMWIlLMLbfcgubmZmzdutX+2o8//oh3330Xd955J3bs2IHf/OY3uP/++/Hll1/iH//4B9auXYu//OUv9uUjIiKwcuVKfPHFF3jttdeQn5+Phx56yOlzzp8/j+zsbKxevRqHDx9GfHy8YsdIRPLgbM1EpKgFCxbg22+/xXvvvQcA+Pvf/46VK1eioqICo0ePxsSJE7FkyRL78m+88QYeeugh/PDDD26398477+Dee+/Fjz/+COBSC8udd96J0tJS9O/fX/4DIiJFMGAhIkWVlJRg8ODB+O6779ClSxcMGDAA06dPx5/+9Cd06tQJVqsVkZGR9uWbm5tx4cIFnDt3Dh07dkRBQQGefPJJfPnll7BYLGhqasKFCxdw9uxZdOrUCWvXrsX8+fNx4cIFGAyGEB4pEUmpTah3gIjCy8CBA9G/f3/k5uYiKysLhw4dwn/+8x8AgNVqxWOPPYZp06a1WK99+/b47rvvcNNNN+Gee+7B448/jri4OOzbtw933XUXLl68aF+2Q4cODFaIdIYBCxEpbu7cuXj22Wdx/Phx3HDDDUhOTgYAZGRkoLy8HD169HC7XnFxMZqamvDMM88gIuLSELy3335bsf0motBhwEJEips5cyYefPBBvPLKK8jNzbW//sgjj+CXv/wlkpOTccsttyAiIgKff/45Dh06hCeeeALXXHMNmpqa8Pzzz2Py5MnYv38/Xn755RAeCREphVlCRKS4mJgYTJ8+HZdddhmmTJlifz0rKwvvvvsu8vLyMHjwYAwbNgwrVqxAt27dAAADBgzAihUrsHz5cvTt2xdvvvkmsrOzQ3QURKQkDrolopC48cYbkZaWhpUrV4Z6V4hIAxiwEJGiTp8+jZ07d2LmzJn48ssvkZqaGupdIiIN4BgWIlJURkYGzpw5g+XLlzNYISKfsYWFiIiIVI+DbomIiEj1GLAQERGR6jFgISIiItVjwEJERESqx4CFiIiIVI8BCxEREakeAxYiIiJSPQYsREREpHr/H21yBksen/AjAAAAAElFTkSuQmCC",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "max_hole_size = hole_size_daily.groupby('time.year').max()\n",
    "max_hole_size.plot.scatter()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3e218d98-cfa9-4b79-9934-2a86fee6b23a",
   "metadata": {},
   "source": [
    "## Calculating the Specific Date When Annual Maximum Occurs"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "56d9482a-24c3-4e74-afd2-a163164f63b5",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "2c627826703e46d8a63c7afa311ac7ed",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "  0%|          | 0/141 [00:00<?, ?it/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "max_hole_size_date = {}\n",
    "\n",
    "for i in tqdm(max_hole_size):\n",
    "    filter_by_year = hole_size_daily.sel(time=hole_size_daily.time.time.dt.year == i.year)\n",
    "    diffs = np.abs(filter_by_year.values - np.array(i))\n",
    "    nearest_index = diffs.argmin()\n",
    "    max_date = filter_by_year.time[nearest_index].values\n",
    "\n",
    "    max_hole_size_date[int(i.year)] = max_date"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "38b013de-f59d-4311-8d6a-6aff35e1e18f",
   "metadata": {},
   "source": [
    "## Animation of the Annual Maximum Ozone Hole\n",
    "We iterate through all years, plotting the largest ozone hole for that year."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8d8656c8-3510-423a-9901-615b1ae63ec5",
   "metadata": {},
   "source": [
    "#### Plotting the hole itself"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "d070215f-398d-42a4-84dd-c022a4a065e3",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "max_ozone_hole.mp4\n"
     ]
    }
   ],
   "source": [
    "lv = accessvis.plot_earth(texture='bluemarble', waves=True, background='black', vertical_exaggeration=20)\n",
    "lv.set_properties(diffuse=0.6, ambient=0.85, specular=0.25, shininess=0.03, light=[1,1,0.98,1], lightpos=[0,0,10000,1])\n",
    "\n",
    "threshold = 220e-5 #220 DU threshold converted to M\n",
    "\n",
    "filename = 'max_ozone_hole.mp4'\n",
    "print(filename)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "09872b29-254d-4fb5-8f06-e5c25e10bf52",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "602b6739ed254890964b20862d0db078",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "  0%|          | 0/141 [00:00<?, ?it/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<video src=\"max_ozone_hole.mp4\" id='video_bad0bf60' autoplay  width=\"600\"  height=\"600\">\n",
       "      Your browser does not support the <code>video</code> element.\n",
       "    </video>"
      ],
      "text/plain": [
       "<IPython.core.display.Video object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<a id=\"link_video_bad0bf60\" href=\"max_ozone_hole.mp4\" download>Download Video</a>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/javascript": [
       "\n",
       "        let el = document.getElementById('video_bad0bf60');\n",
       "        let url = el.src;\n",
       "        fetch(url, {method: 'HEAD'}).then(response=>{\n",
       "          if(response.status == 404) {\n",
       "            console.log(\"Bad video url: \" + url);\n",
       "            let toppath = \"/files/home/\"\n",
       "            let baseurl = url.substring(0, url.indexOf(toppath)+toppath.length);\n",
       "            let endurl = url.substring(url.indexOf(\"max_ozone_hole.mp4\"));\n",
       "            let fixed = baseurl + endurl;\n",
       "            console.log(\"Replaced video url: \" + fixed);\n",
       "            el.src = fixed;\n",
       "            //Also fix download link\n",
       "            document.getElementById('link_video_bad0bf60').href = fixed;\n",
       "          }\n",
       "        });\n",
       "        "
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "with lv.video(filename=filename, quality=4, resolution=(600,600), width=600, height=600, params=\"autoplay\") as v:\n",
    "    for year, date in tqdm(sorted(max_hole_size_date.items())):\n",
    "        timepoint = ds['toz'].sel(time=date, method='nearest')\n",
    "        timepoint = np.roll(timepoint, timepoint.shape[1] // 2, axis=1)\n",
    "        hole_mask =  (0.9*(timepoint<threshold))\n",
    "        \n",
    "        colours = accessvis.array_to_rgba(hole_mask, colourmap='coolwarm', flip=True, opacitymap=hole_mask)\n",
    "        accessvis.update_earth_values(lv, dataMode=0, data=colours)\n",
    "        \n",
    "        lv.reset()\n",
    "        lv.rotate('y', year % 360)\n",
    "        lv.rotate('x',-80)\n",
    "        \n",
    "        lv.title(f'Largest Ozone Hole - {year}')\n",
    "        lv.render()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "50e5e74f-297f-4c2d-beb3-b8733f5b3713",
   "metadata": {},
   "source": [
    "#### Plotting the Ozone Concentration"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "1b78a558-e833-467f-ba05-568972b83035",
   "metadata": {},
   "outputs": [],
   "source": [
    "lv = accessvis.plot_earth(texture='bluemarble', waves=True, background='black', vertical_exaggeration=30)\n",
    "lv.set_properties(diffuse=0.6, ambient=0.85, specular=0.25, shininess=0.03, light=[1,1,0.98,1], lightpos=[0,0,10000,1])\n",
    "\n",
    "threshold = 220 * 1e-5 #220 DU threshold converted to M\n",
    "\n",
    "colourmap='plasma'\n",
    "cmap = lv.colourmap(colourmap, range=(220, 550))\n",
    "cb = lv.colourbar()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "f4d886d5-9b07-4cb5-835e-6d25db6c23b9",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "max_ozone_level.mp4\n"
     ]
    },
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "fdde3f7b9247474dbee80471edaa09d5",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "  0%|          | 0/141 [00:00<?, ?it/s]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<video src=\"max_ozone_level.mp4\" id='video_a95aa751' autoplay  width=\"600\"  height=\"600\">\n",
       "      Your browser does not support the <code>video</code> element.\n",
       "    </video>"
      ],
      "text/plain": [
       "<IPython.core.display.Video object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<a id=\"link_video_a95aa751\" href=\"max_ozone_level.mp4\" download>Download Video</a>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "application/javascript": [
       "\n",
       "        let el = document.getElementById('video_a95aa751');\n",
       "        let url = el.src;\n",
       "        fetch(url, {method: 'HEAD'}).then(response=>{\n",
       "          if(response.status == 404) {\n",
       "            console.log(\"Bad video url: \" + url);\n",
       "            let toppath = \"/files/home/\"\n",
       "            let baseurl = url.substring(0, url.indexOf(toppath)+toppath.length);\n",
       "            let endurl = url.substring(url.indexOf(\"max_ozone_level.mp4\"));\n",
       "            let fixed = baseurl + endurl;\n",
       "            console.log(\"Replaced video url: \" + fixed);\n",
       "            el.src = fixed;\n",
       "            //Also fix download link\n",
       "            document.getElementById('link_video_a95aa751').href = fixed;\n",
       "          }\n",
       "        });\n",
       "        "
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "filename = 'max_ozone_level.mp4'\n",
    "print(filename)\n",
    "\n",
    "with lv.video(filename=filename, quality=4, resolution=(600,600), width=600, height=600, params=\"autoplay\") as v:\n",
    "    for year, date in tqdm(sorted(max_hole_size_date.items())):\n",
    "        timepoint = ds['toz'].sel(time=date, method='nearest')\n",
    "        timepoint = np.roll(timepoint, timepoint.shape[1] // 2, axis=1) * 1e5\n",
    "        colours = accessvis.array_to_rgba(timepoint, colourmap=colourmap, minimum=220,maximum=550, flip=True, opacity=0.8)\n",
    "        accessvis.update_earth_values(lv, dataMode=0, data=colours)\n",
    "\n",
    "        lv.reset()\n",
    "        lv.rotate('y', year % 360)\n",
    "        lv.rotate('x',-80)\n",
    "        \n",
    "        lv.title(f'Ozone Maximum - {year}')\n",
    "        lv.render()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "d51b7a8e-7de6-4c5a-9f69-fea5acb2eb7b",
   "metadata": {},
   "outputs": [],
   "source": []
  }
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