code/uref_ration_validation.ipynb

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    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "from hn2016_falwa.oopinterface import QGField\n",
    "import xarray as xr\n",
    "import os\n",
    "import glob\n",
    "import cartopy.crs as ccrs\n",
    "from dask.distributed import Client, LocalCluster\n",
    "import pandas as pd\n",
    "from itertools import product\n",
    "from cftime import DatetimeNoLeap\n",
    "import seaborn as sns\n"
   ]
  },
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    "cluster = LocalCluster(host='195.113.23.121')#, n_workers=4\n",
    "client = Client(cluster) # "
   ]
  },
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       "<h3 style=\"text-align: left;\">Client</h3>\n",
       "<ul style=\"text-align: left; list-style: none; margin: 0; padding: 0;\">\n",
       "  <li><b>Scheduler: </b>tcp://195.113.23.121:33285</li>\n",
       "  <li><b>Dashboard: </b><a href='http://195.113.23.121:8787/status' target='_blank'>http://195.113.23.121:8787/status</a></li>\n",
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       "<h3 style=\"text-align: left;\">Cluster</h3>\n",
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       "  <li><b>Workers: </b>8</li>\n",
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     "text": [
      "/mnt/data02/model/CMAM/0A.daily/QGFields_6hrlogH_CMAM_CMAM30-SD_r1i1p1_19790101-20101231.zarr\n"
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   "source": [
    "inpath = '/mnt/data02/model/CMAM/0A.daily/'\n",
    "\n",
    "infile = os.path.join(inpath, \n",
    "                       f\"QGFields_6hrlogH_CMAM_CMAM30-SD_r1i1p1_19790101-20101231.zarr\")\n",
    "print(infile)\n",
    "#uref_xa.to_dataset().to_zarr(outfile, mode = \"w-\", consolidated=True)#.to_netcdf(outfile)"
   ]
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       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt;\n",
       "Dimensions:  (height: 39, lat: 48, lon: 96, time: 46720)\n",
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       "  * lat      (lat) float64 -87.16 -83.48 -79.78 -76.07 ... 79.78 83.48 87.16\n",
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       "  * time     (time) object 1979-01-01 00:00:00 ... 2010-12-31 18:00:00\n",
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       "    lwa      (time, height, lat, lon) float32 dask.array&lt;chunksize=(1460, 39, 48, 96), meta=np.ndarray&gt;\n",
       "    ua_int   (time, height, lat, lon) float32 dask.array&lt;chunksize=(1460, 39, 48, 96), meta=np.ndarray&gt;\n",
       "    uref     (time, height, lat) float32 dask.array&lt;chunksize=(1460, 39, 48), meta=np.ndarray&gt;</pre><div class='xr-wrap' hidden><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-5ce63851-5eae-4edf-af3f-52e8b4999552' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-5ce63851-5eae-4edf-af3f-52e8b4999552' 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'>height</span>: 39</li><li><span class='xr-has-index'>lat</span>: 48</li><li><span class='xr-has-index'>lon</span>: 96</li><li><span class='xr-has-index'>time</span>: 46720</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-61255664-c016-4d64-82bd-7ef7f9de519d' class='xr-section-summary-in' type='checkbox'  checked><label for='section-61255664-c016-4d64-82bd-7ef7f9de519d' class='xr-section-summary' >Coordinates: <span>(4)</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'>height</span></div><div class='xr-var-dims'>(height)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>10000 11000 12000 ... 47000 48000</div><input id='attrs-2528def8-f0c4-42d6-ade8-7d36086ffbda' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-2528def8-f0c4-42d6-ade8-7d36086ffbda' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-855a5bfc-65a3-42d8-915f-706d00e080c5' class='xr-var-data-in' type='checkbox'><label for='data-855a5bfc-65a3-42d8-915f-706d00e080c5' 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([10000, 11000, 12000, 13000, 14000, 15000, 16000, 17000, 18000, 19000,\n",
       "       20000, 21000, 22000, 23000, 24000, 25000, 26000, 27000, 28000, 29000,\n",
       "       30000, 31000, 32000, 33000, 34000, 35000, 36000, 37000, 38000, 39000,\n",
       "       40000, 41000, 42000, 43000, 44000, 45000, 46000, 47000, 48000])</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'>-87.16 -83.48 ... 83.48 87.16</div><input id='attrs-bdf6917b-e3f6-49c6-9c7f-6d081691573a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-bdf6917b-e3f6-49c6-9c7f-6d081691573a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f767a5c2-e5df-47ab-9fa2-816fd50db65f' class='xr-var-data-in' type='checkbox'><label for='data-f767a5c2-e5df-47ab-9fa2-816fd50db65f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>axis :</span></dt><dd>Y</dd><dt><span>bounds :</span></dt><dd>lat_bnds</dd><dt><span>long_name :</span></dt><dd>latitude</dd><dt><span>standard_name :</span></dt><dd>latitude</dd><dt><span>units :</span></dt><dd>degrees_north</dd></dl></div><div class='xr-var-data'><pre>array([-87.159094, -83.478937, -79.777046, -76.070244, -72.361581, -68.652017,\n",
       "       -64.941949, -61.231573, -57.520994, -53.810274, -50.099453, -46.388558,\n",
       "       -42.677606, -38.96661 , -35.25558 , -31.544523, -27.833444, -24.122348,\n",
       "       -20.411238, -16.700118, -12.988988,  -9.277853,  -5.566714,  -1.855571,\n",
       "         1.855571,   5.566714,   9.277853,  12.988988,  16.700118,  20.411238,\n",
       "        24.122348,  27.833444,  31.544523,  35.25558 ,  38.96661 ,  42.677606,\n",
       "        46.388558,  50.099453,  53.810274,  57.520994,  61.231573,  64.941949,\n",
       "        68.652017,  72.361581,  76.070244,  79.777046,  83.478937,  87.159094])</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'>0.0 3.75 7.5 ... 348.8 352.5 356.2</div><input id='attrs-07f90582-c5e0-480c-8e47-fe8cbd70f163' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-07f90582-c5e0-480c-8e47-fe8cbd70f163' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-712e247e-c322-4a4a-9915-413e2f1b162f' class='xr-var-data-in' type='checkbox'><label for='data-712e247e-c322-4a4a-9915-413e2f1b162f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>axis :</span></dt><dd>X</dd><dt><span>bounds :</span></dt><dd>lon_bnds</dd><dt><span>long_name :</span></dt><dd>longitude</dd><dt><span>standard_name :</span></dt><dd>longitude</dd><dt><span>units :</span></dt><dd>degrees_east</dd></dl></div><div class='xr-var-data'><pre>array([  0.  ,   3.75,   7.5 ,  11.25,  15.  ,  18.75,  22.5 ,  26.25,  30.  ,\n",
       "        33.75,  37.5 ,  41.25,  45.  ,  48.75,  52.5 ,  56.25,  60.  ,  63.75,\n",
       "        67.5 ,  71.25,  75.  ,  78.75,  82.5 ,  86.25,  90.  ,  93.75,  97.5 ,\n",
       "       101.25, 105.  , 108.75, 112.5 , 116.25, 120.  , 123.75, 127.5 , 131.25,\n",
       "       135.  , 138.75, 142.5 , 146.25, 150.  , 153.75, 157.5 , 161.25, 165.  ,\n",
       "       168.75, 172.5 , 176.25, 180.  , 183.75, 187.5 , 191.25, 195.  , 198.75,\n",
       "       202.5 , 206.25, 210.  , 213.75, 217.5 , 221.25, 225.  , 228.75, 232.5 ,\n",
       "       236.25, 240.  , 243.75, 247.5 , 251.25, 255.  , 258.75, 262.5 , 266.25,\n",
       "       270.  , 273.75, 277.5 , 281.25, 285.  , 288.75, 292.5 , 296.25, 300.  ,\n",
       "       303.75, 307.5 , 311.25, 315.  , 318.75, 322.5 , 326.25, 330.  , 333.75,\n",
       "       337.5 , 341.25, 345.  , 348.75, 352.5 , 356.25])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>1979-01-01 00:00:00 ... 2010-12-...</div><input id='attrs-9e5b9f93-4265-49c2-8dc8-1015395827da' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-9e5b9f93-4265-49c2-8dc8-1015395827da' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-cbbc06da-2f82-438d-945c-1d09cf6b7708' class='xr-var-data-in' type='checkbox'><label for='data-cbbc06da-2f82-438d-945c-1d09cf6b7708' 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>bounds :</span></dt><dd>time_bnds</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([cftime.DatetimeNoLeap(1979, 1, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "       cftime.DatetimeNoLeap(1979, 1, 1, 6, 0, 0, 0, has_year_zero=True),\n",
       "       cftime.DatetimeNoLeap(1979, 1, 1, 12, 0, 0, 0, has_year_zero=True), ...,\n",
       "       cftime.DatetimeNoLeap(2010, 12, 31, 6, 0, 0, 0, has_year_zero=True),\n",
       "       cftime.DatetimeNoLeap(2010, 12, 31, 12, 0, 0, 0, has_year_zero=True),\n",
       "       cftime.DatetimeNoLeap(2010, 12, 31, 18, 0, 0, 0, has_year_zero=True)],\n",
       "      dtype=object)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-55e6f8ba-255c-4a72-888a-1934fe63d522' class='xr-section-summary-in' type='checkbox'  checked><label for='section-55e6f8ba-255c-4a72-888a-1934fe63d522' 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>lwa</span></div><div class='xr-var-dims'>(time, height, lat, lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1460, 39, 48, 96), meta=np.ndarray&gt;</div><input id='attrs-cbb08f46-d978-41a1-a9c4-3a8cbd0b9f0d' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-cbb08f46-d978-41a1-a9c4-3a8cbd0b9f0d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-034f81a6-4c23-4f98-a439-66e20be121ad' class='xr-var-data-in' type='checkbox'><label for='data-034f81a6-4c23-4f98-a439-66e20be121ad' 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'><table>\n",
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       "    <tr><td> </td><th> Array </th><th> Chunk </th></tr>\n",
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       "  <tbody>\n",
       "    <tr><th> Bytes </th><td> 31.28 GiB </td> <td> 0.98 GiB </td></tr>\n",
       "    <tr><th> Shape </th><td> (46720, 39, 48, 96) </td> <td> (1460, 39, 48, 96) </td></tr>\n",
       "    <tr><th> Count </th><td> 33 Tasks </td><td> 32 Chunks </td></tr>\n",
       "    <tr><th> Type </th><td> float32 </td><td> numpy.ndarray </td></tr>\n",
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       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>ua_int</span></div><div class='xr-var-dims'>(time, height, lat, lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1460, 39, 48, 96), meta=np.ndarray&gt;</div><input id='attrs-43652bd3-fcff-4a49-971b-c1ce41b47d6e' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-43652bd3-fcff-4a49-971b-c1ce41b47d6e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-942d9e0b-0ce7-4dfc-bb93-560b1e91ae6a' class='xr-var-data-in' type='checkbox'><label for='data-942d9e0b-0ce7-4dfc-bb93-560b1e91ae6a' 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'><table>\n",
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       "    <tr><th> Count </th><td> 33 Tasks </td><td> 32 Chunks </td></tr>\n",
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      "text/plain": [
       "<xarray.Dataset>\n",
       "Dimensions:  (height: 39, lat: 48, lon: 96, time: 46720)\n",
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       "    uref     (time, height, lat) float32 dask.array<chunksize=(1460, 39, 48), meta=np.ndarray>"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ds = xr.open_zarr(infile, consolidated=True)\n",
    "ds"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "07c3249a-8541-4eed-ba2f-f87ccb6528fa",
   "metadata": {},
   "source": [
    "list of weak-vortex winters from [Nakamura et al 2020](https://journals.ametsoc.org/view/journals/atsc/77/3/jas-d-19-0249.1.xml)"
   ]
  },
  {
   "cell_type": "code",
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   "id": "0e9b8a0f-7c59-413b-a423-3326eec1d82d",
   "metadata": {
    "execution": {
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     "shell.execute_reply.started": "2021-06-15T21:50:12.769220Z"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "month_ls = ds.time.dt.month\n",
    "year_ls = ds.time.dt.year\n",
    "weak_vortex_winter_ls = [1985, 1987, 1999, 2001, 2002, 2004, 2006, 2009, 2010, 2012, 2013]\n",
    "mask = np.isin(month_ls, [1,2,3,4]) & np.isin(year_ls, weak_vortex_winter_ls)"
   ]
  },
  {
   "cell_type": "code",
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   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([ True,  True,  True,  True,  True,  True,  True,  True,  True,\n",
       "        True,  True,  True])"
      ]
     },
     "execution_count": 15,
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   ],
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    "np.isin(month_ls, [1,2,3,4])[:12]"
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    {
     "data": {
      "text/plain": [
       "4320"
      ]
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     "execution_count": 7,
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    "np.count_nonzero(mask)"
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    {
     "data": {
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       "<xarray.plot.facetgrid.FacetGrid at 0x7f2c63ba2850>"
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     "execution_count": 93,
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\n",
      "text/plain": [
       "<Figure size 1152x216 with 6 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "ds['uref'].sel(lat = slice(0,None)).groupby('time.month').mean('time').sel(month = [11,12,1,2,3]).plot(col = 'month',\n",
    "                                                                                                       x = 'lat', robust = True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "d24f4481-77be-4745-9a8c-99885b3e9780",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2021-06-15T21:50:18.020776Z",
     "iopub.status.busy": "2021-06-15T21:50:18.020235Z",
     "iopub.status.idle": "2021-06-15T21:50:18.041326Z",
     "shell.execute_reply": "2021-06-15T21:50:18.040315Z",
     "shell.execute_reply.started": "2021-06-15T21:50:18.020713Z"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "ds_sel = ds.sel(time = mask)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "c3ee33b0-5167-4354-baa7-f62a4175f9a6",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2021-06-15T21:50:20.002083Z",
     "iopub.status.busy": "2021-06-15T21:50:20.001498Z",
     "iopub.status.idle": "2021-06-15T21:50:20.136544Z",
     "shell.execute_reply": "2021-06-15T21:50:20.136006Z",
     "shell.execute_reply.started": "2021-06-15T21:50:20.002014Z"
    },
    "tags": []
   },
   "outputs": [
    {
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       ".xr-section-item input {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-section-item input + label {\n",
       "  color: var(--xr-disabled-color);\n",
       "}\n",
       "\n",
       ".xr-section-item input:enabled + label {\n",
       "  cursor: pointer;\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-section-item input:enabled + label:hover {\n",
       "  color: var(--xr-font-color0);\n",
       "}\n",
       "\n",
       ".xr-section-summary {\n",
       "  grid-column: 1;\n",
       "  color: var(--xr-font-color2);\n",
       "  font-weight: 500;\n",
       "}\n",
       "\n",
       ".xr-section-summary > span {\n",
       "  display: inline-block;\n",
       "  padding-left: 0.5em;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:disabled + label {\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-section-summary-in + label:before {\n",
       "  display: inline-block;\n",
       "  content: '►';\n",
       "  font-size: 11px;\n",
       "  width: 15px;\n",
       "  text-align: center;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:disabled + label:before {\n",
       "  color: var(--xr-disabled-color);\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked + label:before {\n",
       "  content: '▼';\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked + label > span {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-section-summary,\n",
       ".xr-section-inline-details {\n",
       "  padding-top: 4px;\n",
       "  padding-bottom: 4px;\n",
       "}\n",
       "\n",
       ".xr-section-inline-details {\n",
       "  grid-column: 2 / -1;\n",
       "}\n",
       "\n",
       ".xr-section-details {\n",
       "  display: none;\n",
       "  grid-column: 1 / -1;\n",
       "  margin-bottom: 5px;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked ~ .xr-section-details {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-array-wrap {\n",
       "  grid-column: 1 / -1;\n",
       "  display: grid;\n",
       "  grid-template-columns: 20px auto;\n",
       "}\n",
       "\n",
       ".xr-array-wrap > label {\n",
       "  grid-column: 1;\n",
       "  vertical-align: top;\n",
       "}\n",
       "\n",
       ".xr-preview {\n",
       "  color: var(--xr-font-color3);\n",
       "}\n",
       "\n",
       ".xr-array-preview,\n",
       ".xr-array-data {\n",
       "  padding: 0 5px !important;\n",
       "  grid-column: 2;\n",
       "}\n",
       "\n",
       ".xr-array-data,\n",
       ".xr-array-in:checked ~ .xr-array-preview {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-array-in:checked ~ .xr-array-data,\n",
       ".xr-array-preview {\n",
       "  display: inline-block;\n",
       "}\n",
       "\n",
       ".xr-dim-list {\n",
       "  display: inline-block !important;\n",
       "  list-style: none;\n",
       "  padding: 0 !important;\n",
       "  margin: 0;\n",
       "}\n",
       "\n",
       ".xr-dim-list li {\n",
       "  display: inline-block;\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "}\n",
       "\n",
       ".xr-dim-list:before {\n",
       "  content: '(';\n",
       "}\n",
       "\n",
       ".xr-dim-list:after {\n",
       "  content: ')';\n",
       "}\n",
       "\n",
       ".xr-dim-list li:not(:last-child):after {\n",
       "  content: ',';\n",
       "  padding-right: 5px;\n",
       "}\n",
       "\n",
       ".xr-has-index {\n",
       "  font-weight: bold;\n",
       "}\n",
       "\n",
       ".xr-var-list,\n",
       ".xr-var-item {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-var-item > div,\n",
       ".xr-var-item label,\n",
       ".xr-var-item > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-even);\n",
       "  margin-bottom: 0;\n",
       "}\n",
       "\n",
       ".xr-var-item > .xr-var-name:hover span {\n",
       "  padding-right: 5px;\n",
       "}\n",
       "\n",
       ".xr-var-list > li:nth-child(odd) > div,\n",
       ".xr-var-list > li:nth-child(odd) > label,\n",
       ".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-odd);\n",
       "}\n",
       "\n",
       ".xr-var-name {\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-var-dims {\n",
       "  grid-column: 2;\n",
       "}\n",
       "\n",
       ".xr-var-dtype {\n",
       "  grid-column: 3;\n",
       "  text-align: right;\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-var-preview {\n",
       "  grid-column: 4;\n",
       "}\n",
       "\n",
       ".xr-var-name,\n",
       ".xr-var-dims,\n",
       ".xr-var-dtype,\n",
       ".xr-preview,\n",
       ".xr-attrs dt {\n",
       "  white-space: nowrap;\n",
       "  overflow: hidden;\n",
       "  text-overflow: ellipsis;\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-var-name:hover,\n",
       ".xr-var-dims:hover,\n",
       ".xr-var-dtype:hover,\n",
       ".xr-attrs dt:hover {\n",
       "  overflow: visible;\n",
       "  width: auto;\n",
       "  z-index: 1;\n",
       "}\n",
       "\n",
       ".xr-var-attrs,\n",
       ".xr-var-data {\n",
       "  display: none;\n",
       "  background-color: var(--xr-background-color) !important;\n",
       "  padding-bottom: 5px !important;\n",
       "}\n",
       "\n",
       ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
       ".xr-var-data-in:checked ~ .xr-var-data {\n",
       "  display: block;\n",
       "}\n",
       "\n",
       ".xr-var-data > table {\n",
       "  float: right;\n",
       "}\n",
       "\n",
       ".xr-var-name span,\n",
       ".xr-var-data,\n",
       ".xr-attrs {\n",
       "  padding-left: 25px !important;\n",
       "}\n",
       "\n",
       ".xr-attrs,\n",
       ".xr-var-attrs,\n",
       ".xr-var-data {\n",
       "  grid-column: 1 / -1;\n",
       "}\n",
       "\n",
       "dl.xr-attrs {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  display: grid;\n",
       "  grid-template-columns: 125px auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt,\n",
       ".xr-attrs dd {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  float: left;\n",
       "  padding-right: 10px;\n",
       "  width: auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt {\n",
       "  font-weight: normal;\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-attrs dt:hover span {\n",
       "  display: inline-block;\n",
       "  background: var(--xr-background-color);\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-attrs dd {\n",
       "  grid-column: 2;\n",
       "  white-space: pre-wrap;\n",
       "  word-break: break-all;\n",
       "}\n",
       "\n",
       ".xr-icon-database,\n",
       ".xr-icon-file-text2 {\n",
       "  display: inline-block;\n",
       "  vertical-align: middle;\n",
       "  width: 1em;\n",
       "  height: 1.5em !important;\n",
       "  stroke-width: 0;\n",
       "  stroke: currentColor;\n",
       "  fill: currentColor;\n",
       "}\n",
       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.DataArray (time: 4320, height: 39)&gt;\n",
       "dask.array&lt;truediv, shape=(4320, 39), dtype=float32, chunksize=(480, 39), chunktype=numpy.ndarray&gt;\n",
       "Coordinates:\n",
       "  * height   (height) int64 10000 11000 12000 13000 ... 45000 46000 47000 48000\n",
       "    lat      float64 61.23\n",
       "  * time     (time) object 1985-01-01 00:00:00 ... 2010-04-30 18:00:00</pre><div class='xr-wrap' hidden><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'></div><ul class='xr-dim-list'><li><span class='xr-has-index'>time</span>: 4320</li><li><span class='xr-has-index'>height</span>: 39</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-5b71f6de-199e-4a5b-9f56-284520466b41' class='xr-array-in' type='checkbox' checked><label for='section-5b71f6de-199e-4a5b-9f56-284520466b41' 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>dask.array&lt;chunksize=(480, 39), meta=np.ndarray&gt;</span></div><div class='xr-array-data'><table>\n",
       "<tr>\n",
       "<td>\n",
       "<table>\n",
       "  <thead>\n",
       "    <tr><td> </td><th> Array </th><th> Chunk </th></tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr><th> Bytes </th><td> 658.12 kiB </td> <td> 73.12 kiB </td></tr>\n",
       "    <tr><th> Shape </th><td> (4320, 39) </td> <td> (480, 39) </td></tr>\n",
       "    <tr><th> Count </th><td> 129 Tasks </td><td> 9 Chunks </td></tr>\n",
       "    <tr><th> Type </th><td> float32 </td><td> numpy.ndarray </td></tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</td>\n",
       "<td>\n",
       "<svg width=\"75\" height=\"170\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
       "\n",
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       "\n",
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       "  <polygon points=\"0.0,0.0 25.412616514582485,0.0 25.412616514582485,120.0 0.0,120.0\" style=\"fill:#ECB172A0;stroke-width:0\"/>\n",
       "\n",
       "  <!-- Text -->\n",
       "  <text x=\"12.706308\" y=\"140.000000\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >39</text>\n",
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       "</svg>\n",
       "</td>\n",
       "</tr>\n",
       "</table></div></div></li><li class='xr-section-item'><input id='section-a68fd82b-528e-4f4c-b80c-3875023ed620' class='xr-section-summary-in' type='checkbox'  checked><label for='section-a68fd82b-528e-4f4c-b80c-3875023ed620' 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'>height</span></div><div class='xr-var-dims'>(height)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>10000 11000 12000 ... 47000 48000</div><input id='attrs-4b1f3f7c-b313-498a-b3eb-7802f7ac79a5' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-4b1f3f7c-b313-498a-b3eb-7802f7ac79a5' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e9a948b8-5ae2-4e2a-b6fb-e19b55f83439' class='xr-var-data-in' type='checkbox'><label for='data-e9a948b8-5ae2-4e2a-b6fb-e19b55f83439' 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([10000, 11000, 12000, 13000, 14000, 15000, 16000, 17000, 18000, 19000,\n",
       "       20000, 21000, 22000, 23000, 24000, 25000, 26000, 27000, 28000, 29000,\n",
       "       30000, 31000, 32000, 33000, 34000, 35000, 36000, 37000, 38000, 39000,\n",
       "       40000, 41000, 42000, 43000, 44000, 45000, 46000, 47000, 48000])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lat</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>61.23</div><input id='attrs-c45e568c-cc2d-4012-8980-c4de62e2c0a1' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-c45e568c-cc2d-4012-8980-c4de62e2c0a1' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3edd3d4f-1b93-47be-b12d-9d8552ec3891' class='xr-var-data-in' type='checkbox'><label for='data-3edd3d4f-1b93-47be-b12d-9d8552ec3891' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>axis :</span></dt><dd>Y</dd><dt><span>bounds :</span></dt><dd>lat_bnds</dd><dt><span>long_name :</span></dt><dd>latitude</dd><dt><span>standard_name :</span></dt><dd>latitude</dd><dt><span>units :</span></dt><dd>degrees_north</dd></dl></div><div class='xr-var-data'><pre>array(61.23157309)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>1985-01-01 00:00:00 ... 2010-04-...</div><input id='attrs-94517123-1d4c-490b-86ec-bc976f179745' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-94517123-1d4c-490b-86ec-bc976f179745' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6376472a-3eec-438c-abaf-48cceece8192' class='xr-var-data-in' type='checkbox'><label for='data-6376472a-3eec-438c-abaf-48cceece8192' 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>bounds :</span></dt><dd>time_bnds</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([cftime.DatetimeNoLeap(1985, 1, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "       cftime.DatetimeNoLeap(1985, 1, 1, 6, 0, 0, 0, has_year_zero=True),\n",
       "       cftime.DatetimeNoLeap(1985, 1, 1, 12, 0, 0, 0, has_year_zero=True), ...,\n",
       "       cftime.DatetimeNoLeap(2010, 4, 30, 6, 0, 0, 0, has_year_zero=True),\n",
       "       cftime.DatetimeNoLeap(2010, 4, 30, 12, 0, 0, 0, has_year_zero=True),\n",
       "       cftime.DatetimeNoLeap(2010, 4, 30, 18, 0, 0, 0, has_year_zero=True)],\n",
       "      dtype=object)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-d5d761be-b6ca-47a1-a068-efd13d194368' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-d5d761be-b6ca-47a1-a068-efd13d194368' class='xr-section-summary'  title='Expand/collapse section'>Attributes: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.DataArray (time: 4320, height: 39)>\n",
       "dask.array<truediv, shape=(4320, 39), dtype=float32, chunksize=(480, 39), chunktype=numpy.ndarray>\n",
       "Coordinates:\n",
       "  * height   (height) int64 10000 11000 12000 13000 ... 45000 46000 47000 48000\n",
       "    lat      float64 61.23\n",
       "  * time     (time) object 1985-01-01 00:00:00 ... 2010-04-30 18:00:00"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sel_dict = dict(lat = 60, method = 'nearest')\n",
    "uref_60 = ds_sel['uref'].sel(**sel_dict)\n",
    "ratio = ds_sel['ua_int'].sel(**sel_dict).mean('lon')/uref_60\n",
    "ratio"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "8f6140b7-d335-4341-a8f7-45615c6ac1a9",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2021-06-15T21:56:16.365250Z",
     "iopub.status.busy": "2021-06-15T21:56:16.364576Z",
     "iopub.status.idle": "2021-06-15T21:56:21.186759Z",
     "shell.execute_reply": "2021-06-15T21:56:21.179476Z",
     "shell.execute_reply.started": "2021-06-15T21:56:16.365178Z"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "ration_tm = ratio.groupby('time.dayofyear').mean('time').load()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "fe3419c6-52d7-465a-9592-135aa63e48e1",
   "metadata": {
    "execution": {
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     "shell.execute_reply": "2021-06-15T21:58:29.199461Z",
     "shell.execute_reply.started": "2021-06-15T21:58:28.996300Z"
    },
    "tags": []
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/kuchar/.conda/envs/moje/lib/python3.9/site-packages/xarray/plot/plot.py:932: UserWarning: The following kwargs were not used by contour: 'lw'\n",
      "  primitive = ax.contour(x, y, z, **kwargs)\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<matplotlib.contour.QuadContourSet at 0x7f2c6a658e50>"
      ]
     },
     "execution_count": 27,
     "metadata": {},
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    },
    {
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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "ration_tm.plot.contour(y = 'height', \n",
    "                       levels = [0.3], \n",
    "                       lw = 3 )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "9204a12e-4dca-4719-8b17-33f90dc3abfa",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2021-06-15T22:00:08.057294Z",
     "iopub.status.busy": "2021-06-15T22:00:08.056704Z",
     "iopub.status.idle": "2021-06-15T22:00:12.987497Z",
     "shell.execute_reply": "2021-06-15T22:00:12.986656Z",
     "shell.execute_reply.started": "2021-06-15T22:00:08.057223Z"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x7f2ca827e250>]"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "ratio.sel(height = 32_000).groupby('time.dayofyear').mean('time').plot()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "d38e7fea-851e-40c5-b594-a838a6ab51d9",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2021-06-15T21:57:46.842897Z",
     "iopub.status.busy": "2021-06-15T21:57:46.841957Z",
     "iopub.status.idle": "2021-06-15T21:57:51.222198Z",
     "shell.execute_reply": "2021-06-15T21:57:51.221310Z",
     "shell.execute_reply.started": "2021-06-15T21:57:46.842822Z"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.collections.QuadMesh at 0x7f2c6af7b910>"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "uref_60.groupby('time.dayofyear').mean('time').plot(y = 'height',\n",
    "                                                   vmin = 0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "9bd5734d-be10-460c-8c3f-ff688a26c2ba",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2021-06-15T21:55:45.323655Z",
     "iopub.status.busy": "2021-06-15T21:55:45.322786Z",
     "iopub.status.idle": "2021-06-15T21:55:47.600878Z",
     "shell.execute_reply": "2021-06-15T21:55:47.599603Z",
     "shell.execute_reply.started": "2021-06-15T21:55:45.323585Z"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "ration_tm = ratio.groupby('time.month').mean('time').load()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "1f9888e8-16a2-4382-9374-4895c7ecbd4f",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2021-06-15T21:55:47.603865Z",
     "iopub.status.busy": "2021-06-15T21:55:47.603196Z",
     "iopub.status.idle": "2021-06-15T21:55:47.809586Z",
     "shell.execute_reply": "2021-06-15T21:55:47.808787Z",
     "shell.execute_reply.started": "2021-06-15T21:55:47.603803Z"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.contour.QuadContourSet at 0x7f2c706a34c0>"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "ration_tm.plot.contour(y = 'height', \n",
    "                       levels = [0.2,0.3,0.4], \n",
    "                       colors = 'k')"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5aa85f0c-5b88-4d73-ab9a-fa6c3191b278",
   "metadata": {},
   "source": [
    "# SSWs"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "id": "499caa33-19e4-4abc-9d56-ca395a7a8d50",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2021-06-15T22:17:10.548243Z",
     "iopub.status.busy": "2021-06-15T22:17:10.547451Z",
     "iopub.status.idle": "2021-06-15T22:17:10.561979Z",
     "shell.execute_reply": "2021-06-15T22:17:10.560479Z",
     "shell.execute_reply.started": "2021-06-15T22:17:10.548162Z"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "dates = ['1980-02-29', '1981-03-04',\n",
    "         '1981-12-04', '1985-01-01',\n",
    "         '1987-01-23', '1987-12-08',\n",
    "         '1998-12-16', '2000-03-20',\n",
    "         '2001-02-11', '2001-12-31',\n",
    "         '2003-01-18', '2004-01-06',\n",
    "         '2006-01-21', '2007-02-24',\n",
    "         '2008-02-22', '2009-01-24',\n",
    "         '2010-02-09']\n",
    "dates = pd.to_datetime(dates)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 82,
   "id": "a76cbd4a-0ead-4a27-9cad-c154a2df5e65",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2021-06-15T22:43:27.838374Z",
     "iopub.status.busy": "2021-06-15T22:43:27.837854Z",
     "iopub.status.idle": "2021-06-15T22:43:33.597754Z",
     "shell.execute_reply": "2021-06-15T22:43:33.592514Z",
     "shell.execute_reply.started": "2021-06-15T22:43:27.838312Z"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
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       "</symbol>\n",
       "</defs>\n",
       "</svg>\n",
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       " */\n",
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       "\n",
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       "\n",
       ".xr-section-summary-in:checked + label > span {\n",
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       "\n",
       ".xr-section-summary,\n",
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       "\n",
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       "\n",
       ".xr-section-details {\n",
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       "\n",
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       ".xr-array-wrap {\n",
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       "\n",
       ".xr-array-wrap > label {\n",
       "  grid-column: 1;\n",
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       "\n",
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       "\n",
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       "\n",
       ".xr-array-data,\n",
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       "  display: none;\n",
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       "\n",
       ".xr-array-in:checked ~ .xr-array-data,\n",
       ".xr-array-preview {\n",
       "  display: inline-block;\n",
       "}\n",
       "\n",
       ".xr-dim-list {\n",
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       "}\n",
       "\n",
       ".xr-dim-list li {\n",
       "  display: inline-block;\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
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       "\n",
       ".xr-dim-list:before {\n",
       "  content: '(';\n",
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       "\n",
       ".xr-dim-list:after {\n",
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       "\n",
       ".xr-dim-list li:not(:last-child):after {\n",
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       "  padding-right: 5px;\n",
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       "\n",
       ".xr-has-index {\n",
       "  font-weight: bold;\n",
       "}\n",
       "\n",
       ".xr-var-list,\n",
       ".xr-var-item {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-var-item > div,\n",
       ".xr-var-item label,\n",
       ".xr-var-item > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-even);\n",
       "  margin-bottom: 0;\n",
       "}\n",
       "\n",
       ".xr-var-item > .xr-var-name:hover span {\n",
       "  padding-right: 5px;\n",
       "}\n",
       "\n",
       ".xr-var-list > li:nth-child(odd) > div,\n",
       ".xr-var-list > li:nth-child(odd) > label,\n",
       ".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-odd);\n",
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       "\n",
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       "\n",
       ".xr-var-dims {\n",
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       "\n",
       ".xr-var-dtype {\n",
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       "\n",
       ".xr-var-preview {\n",
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       "\n",
       ".xr-var-name,\n",
       ".xr-var-dims,\n",
       ".xr-var-dtype,\n",
       ".xr-preview,\n",
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       "\n",
       ".xr-var-name:hover,\n",
       ".xr-var-dims:hover,\n",
       ".xr-var-dtype:hover,\n",
       ".xr-attrs dt:hover {\n",
       "  overflow: visible;\n",
       "  width: auto;\n",
       "  z-index: 1;\n",
       "}\n",
       "\n",
       ".xr-var-attrs,\n",
       ".xr-var-data {\n",
       "  display: none;\n",
       "  background-color: var(--xr-background-color) !important;\n",
       "  padding-bottom: 5px !important;\n",
       "}\n",
       "\n",
       ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
       ".xr-var-data-in:checked ~ .xr-var-data {\n",
       "  display: block;\n",
       "}\n",
       "\n",
       ".xr-var-data > table {\n",
       "  float: right;\n",
       "}\n",
       "\n",
       ".xr-var-name span,\n",
       ".xr-var-data,\n",
       ".xr-attrs {\n",
       "  padding-left: 25px !important;\n",
       "}\n",
       "\n",
       ".xr-attrs,\n",
       ".xr-var-attrs,\n",
       ".xr-var-data {\n",
       "  grid-column: 1 / -1;\n",
       "}\n",
       "\n",
       "dl.xr-attrs {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  display: grid;\n",
       "  grid-template-columns: 125px auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt,\n",
       ".xr-attrs dd {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  float: left;\n",
       "  padding-right: 10px;\n",
       "  width: auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt {\n",
       "  font-weight: normal;\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-attrs dt:hover span {\n",
       "  display: inline-block;\n",
       "  background: var(--xr-background-color);\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-attrs dd {\n",
       "  grid-column: 2;\n",
       "  white-space: pre-wrap;\n",
       "  word-break: break-all;\n",
       "}\n",
       "\n",
       ".xr-icon-database,\n",
       ".xr-icon-file-text2 {\n",
       "  display: inline-block;\n",
       "  vertical-align: middle;\n",
       "  width: 1em;\n",
       "  height: 1.5em !important;\n",
       "  stroke-width: 0;\n",
       "  stroke: currentColor;\n",
       "  fill: currentColor;\n",
       "}\n",
       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt;\n",
       "Dimensions:  (lag: 61)\n",
       "Coordinates:\n",
       "    height   int64 32000\n",
       "    lat      float64 61.23\n",
       "  * lag      (lag) int64 -30 -29 -28 -27 -26 -25 -24 ... 24 25 26 27 28 29 30\n",
       "Data variables:\n",
       "    cmean    (lag) float32 0.71 0.7191 0.7051 0.6947 ... 1.044 0.8553 0.8289\n",
       "    cstd     (lag) float32 0.238 0.2428 0.2395 0.2398 ... 1.804 1.532 2.01 1.942</pre><div class='xr-wrap' hidden><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-8e09551f-f590-43cc-90f1-e46093bb1819' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-8e09551f-f590-43cc-90f1-e46093bb1819' 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'>lag</span>: 61</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-79a68c3f-2b32-49a3-bf49-edd3dbb2c3c3' class='xr-section-summary-in' type='checkbox'  checked><label for='section-79a68c3f-2b32-49a3-bf49-edd3dbb2c3c3' 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>height</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>32000</div><input id='attrs-1eed5bf4-c0b8-400b-9777-972422aec8c1' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-1eed5bf4-c0b8-400b-9777-972422aec8c1' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-419b1bdc-0dcf-44da-8bc6-8f98e5dae5bc' class='xr-var-data-in' type='checkbox'><label for='data-419b1bdc-0dcf-44da-8bc6-8f98e5dae5bc' 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(32000)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lat</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>61.23</div><input id='attrs-49df2dfa-ebff-4221-be3e-32e3ac78f7a4' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-49df2dfa-ebff-4221-be3e-32e3ac78f7a4' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a267b236-7619-4398-91e8-58a7927e9cbb' class='xr-var-data-in' type='checkbox'><label for='data-a267b236-7619-4398-91e8-58a7927e9cbb' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>axis :</span></dt><dd>Y</dd><dt><span>bounds :</span></dt><dd>lat_bnds</dd><dt><span>long_name :</span></dt><dd>latitude</dd><dt><span>standard_name :</span></dt><dd>latitude</dd><dt><span>units :</span></dt><dd>degrees_north</dd></dl></div><div class='xr-var-data'><pre>array(61.23157309)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lag</span></div><div class='xr-var-dims'>(lag)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>-30 -29 -28 -27 -26 ... 27 28 29 30</div><input id='attrs-a1774f4a-3937-4920-b723-165797a998d4' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a1774f4a-3937-4920-b723-165797a998d4' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-51e296f8-4aab-4cbf-8b94-83c4ec47f4e8' class='xr-var-data-in' type='checkbox'><label for='data-51e296f8-4aab-4cbf-8b94-83c4ec47f4e8' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>day</dd></dl></div><div class='xr-var-data'><pre>array([-30, -29, -28, -27, -26, -25, -24, -23, -22, -21, -20, -19, -18, -17,\n",
       "       -16, -15, -14, -13, -12, -11, -10,  -9,  -8,  -7,  -6,  -5,  -4,  -3,\n",
       "        -2,  -1,   0,   1,   2,   3,   4,   5,   6,   7,   8,   9,  10,  11,\n",
       "        12,  13,  14,  15,  16,  17,  18,  19,  20,  21,  22,  23,  24,  25,\n",
       "        26,  27,  28,  29,  30])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-d1f3f093-5da4-46e8-8905-dce763738e96' class='xr-section-summary-in' type='checkbox'  checked><label for='section-d1f3f093-5da4-46e8-8905-dce763738e96' class='xr-section-summary' >Data variables: <span>(2)</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>cmean</span></div><div class='xr-var-dims'>(lag)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.71 0.7191 ... 0.8553 0.8289</div><input id='attrs-11c6072a-b7c8-4ae2-800d-61068f4a8fd6' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-11c6072a-b7c8-4ae2-800d-61068f4a8fd6' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1a47466a-893f-46a1-8905-0cb0d6070388' class='xr-var-data-in' type='checkbox'><label for='data-1a47466a-893f-46a1-8905-0cb0d6070388' 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([ 7.0995337e-01,  7.1910501e-01,  7.0511103e-01,  6.9467300e-01,\n",
       "        7.0692259e-01,  7.3583758e-01,  7.5704241e-01,  7.7166855e-01,\n",
       "        7.5388467e-01,  7.0886648e-01,  6.6320252e-01,  6.2181646e-01,\n",
       "        5.9228170e-01,  5.7782114e-01,  5.8175558e-01,  5.8898014e-01,\n",
       "        6.1001468e-01,  6.1552542e-01,  6.2553626e-01,  6.1678994e-01,\n",
       "        6.0333711e-01,  5.7125694e-01,  5.3177786e-01,  5.1410961e-01,\n",
       "        4.9485326e-01,  4.2747533e-01,  3.3877873e-01,  2.6462913e-01,\n",
       "        1.6290365e-01,  2.6997976e-02, -1.4198589e-01, -2.4357618e-01,\n",
       "       -2.6700991e-01, -2.3303023e-01, -1.7976663e-01, -8.4208690e-02,\n",
       "       -3.0706756e-02, -3.2993183e-03,  7.5519972e-02,  2.1921632e-01,\n",
       "        3.1952214e-01,  3.5557675e-01,  3.2069647e-01,  3.6393830e-01,\n",
       "        3.3080974e-01,  3.6153087e-01,  7.4148870e+00,  1.3137280e+00,\n",
       "        6.0400057e-01,  3.8597474e-01,  3.2349744e-01,  4.9203935e-01,\n",
       "        7.8124458e-01,  1.3703171e+00,  1.5099348e+00,  1.1504778e+00,\n",
       "        1.1135242e+00,  1.2018242e+00,  1.0439584e+00,  8.5533458e-01,\n",
       "        8.2889140e-01], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>cstd</span></div><div class='xr-var-dims'>(lag)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.238 0.2428 0.2395 ... 2.01 1.942</div><input id='attrs-d81dc87b-8d6d-4d5a-be27-499838f24cc1' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-d81dc87b-8d6d-4d5a-be27-499838f24cc1' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f63f9e8c-c1aa-4385-baf8-5e24ed2aebfe' class='xr-var-data-in' type='checkbox'><label for='data-f63f9e8c-c1aa-4385-baf8-5e24ed2aebfe' 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([ 0.23804784,  0.24280426,  0.23951572,  0.23983987,  0.2400325 ,\n",
       "        0.20641777,  0.16050988,  0.1458116 ,  0.14127137,  0.1405619 ,\n",
       "        0.15181263,  0.17445906,  0.16646877,  0.18095256,  0.19523402,\n",
       "        0.22326577,  0.277067  ,  0.28305545,  0.30189753,  0.31371596,\n",
       "        0.3751784 ,  0.3752477 ,  0.3275754 ,  0.31989416,  0.32112536,\n",
       "        0.2793494 ,  0.20734595,  0.13602723,  0.10961089,  0.09462401,\n",
       "        0.1077937 ,  0.20060277,  0.33220536,  0.46409792,  0.59899175,\n",
       "        0.67663217,  0.731963  ,  0.837248  ,  0.9624133 ,  1.2320377 ,\n",
       "        1.2348099 ,  1.3852435 ,  1.5508169 ,  1.5191613 ,  1.5394974 ,\n",
       "        1.6653221 , 63.177326  ,  5.8208427 ,  2.506508  ,  2.694347  ,\n",
       "        2.3024075 ,  2.2270093 ,  2.46927   ,  9.478687  ,  3.2365658 ,\n",
       "        2.0408337 ,  1.7314339 ,  1.8038225 ,  1.5318587 ,  2.010172  ,\n",
       "        1.9424769 ], dtype=float32)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-d57b1540-e94f-47ff-b0ed-d288c240022e' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-d57b1540-e94f-47ff-b0ed-d288c240022e' class='xr-section-summary'  title='Expand/collapse section'>Attributes: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.Dataset>\n",
       "Dimensions:  (lag: 61)\n",
       "Coordinates:\n",
       "    height   int64 32000\n",
       "    lat      float64 61.23\n",
       "  * lag      (lag) int64 -30 -29 -28 -27 -26 -25 -24 ... 24 25 26 27 28 29 30\n",
       "Data variables:\n",
       "    cmean    (lag) float32 0.71 0.7191 0.7051 0.6947 ... 1.044 0.8553 0.8289\n",
       "    cstd     (lag) float32 0.238 0.2428 0.2395 0.2398 ... 1.804 1.532 2.01 1.942"
      ]
     },
     "execution_count": 82,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sel_dict = dict(lat = 60, height = 32_000, method = 'nearest')\n",
    "uref_60 = ds['uref'].sel(**sel_dict)\n",
    "ratio = ds['ua_int'].sel(**sel_dict).mean('lon')/uref_60\n",
    "\n",
    "max_lag = 30\n",
    "lag_arr = range(-max_lag,max_lag+1)\n",
    "ds_ls = []\n",
    "for il, lag in enumerate(lag_arr):\n",
    "    #print(lag)\n",
    "    sel_dates = dates+pd.Timedelta(str(lag)+' days')\n",
    "    sel_dates = sel_dates[~((sel_dates.month == 2) & (sel_dates.day == 29))]\n",
    "    sel_dates = sel_dates[(sel_dates.year != 2011) & (sel_dates.year != 1978)]\n",
    "    \n",
    "    hourly_index_temp = [DatetimeNoLeap(*x, hour) for x, hour in product(zip(sel_dates.year, sel_dates.month, sel_dates.day), range(0,24,6))]\n",
    "    comp_m = ratio.sel(time = hourly_index_temp).mean('time')\n",
    "    comp_m.name = 'cmean'\n",
    "    comp_s = ratio.sel(time = hourly_index_temp).std('time')\n",
    "    comp_s.name = 'cstd'\n",
    "    ds_ls.append(xr.merge([comp_m, comp_s]))\n",
    "    \n",
    "da_comp = xr.concat(ds_ls, dim = 'lag').load()\n",
    "da_comp['lag'] = lag_arr\n",
    "da_comp['lag'].attrs['units'] = 'day'\n",
    "da_comp"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "41fc7fbb-0cc5-4d7c-8368-8eeb52337595",
   "metadata": {},
   "source": [
    "Given that the threshold is reached on average 4–5 days prior to an SSW event (Fig. 11 or below),  should provide a\n",
    "forecast skill of SSW with a few days of lead time without a need for running a numerical weather prediction\n",
    "model."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 112,
   "id": "b9937f1f-7bca-4f78-999d-0d9423825f6d",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2021-06-16T13:18:18.457171Z",
     "iopub.status.busy": "2021-06-16T13:18:18.456541Z",
     "iopub.status.idle": "2021-06-16T13:18:18.467005Z",
     "shell.execute_reply": "2021-06-16T13:18:18.465733Z",
     "shell.execute_reply.started": "2021-06-16T13:18:18.457094Z"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "sns.set_style('whitegrid')\n",
    "plt.rcParams.update({'font.size': 22})\n",
    "plt.rc('text', usetex=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 113,
   "id": "66c2cb3d-064e-4305-8284-44195240d39d",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2021-06-16T13:18:19.615733Z",
     "iopub.status.busy": "2021-06-16T13:18:19.615469Z",
     "iopub.status.idle": "2021-06-16T13:18:19.854130Z",
     "shell.execute_reply": "2021-06-16T13:18:19.853327Z",
     "shell.execute_reply.started": "2021-06-16T13:18:19.615702Z"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 1.0, 'SSW composite at 32 km; 60°N in CMAM30')"
      ]
     },
     "execution_count": 113,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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A0LZtW4ERwPn5+SX+uOCLiopCTk4OgMLaC1GK7hOWLCxbtgyqqqo4duwY+vXrh169esHZ2Rny8vLs41SSJk2asP1ET58+LbQ1oLL4+/tj+PDhOHv2LD59+oS8vDwkJSXh1q1bGDduXLm/327fvg2gsHZm8ODBEou3adOmMDc3F+iHVNSdO3eQnp6Ohg0bwtLSUuxy79y5g7S0NAD/n7zw/8/KyhI6qEOULl26QF9fX6AfUlFXrlwBj8eDhYWFyIFVZXHjxg32b2GfQ/w+0sbGxiJ/HCgpKcHY2Fjg+NKUmii1aNGC/bC5d+8e1q1bh/fv34tVOF/Xrl3Z5jYXFxf8888/ZX7D1K1bF61btwYABAQEFNvPT374ozDESZS0tbXRsmXLMsUBFH6BOjo6IiwsDPLy8pgwYQLOnTsHX19fPHnyBKdOncIvv/wi9EP60KFDOH78OBuju7s7fH19cfv2bSxZsgTKysqIj4/HjBkz8OPHD5Ex+Pv7w9XVFYMHD8aFCxfg5+eHK1eusL+cLly4gNu3b8PJyQlqampwdXXF48eP8fDhQ/z+++9QVFTE169fsWvXrhLv66FDh+Dv7w9HR0dcvXoVz549g4eHB3r06AGg8IUrqiZm8eLF7HM1evRoXLp0CX5+frh06RJGjRoFAHj27JnQERNubm4IDg6GvLw8fvnlF1y+fBlPnz6Fj48Pzp07h40bN6Jz585ij56aM2cOgoKC2NeFvb09goKCBP4VHQWRn5+POXPm4NmzZ1BRUYGTkxO8vLzg7++Pu3fvYt26ddDS0sKbN2/w66+/ltgEIYqqqioGDhwIZ2dn/Pvvv/Dx8cHTp0/h6emJ+fPnQ1NTE8HBwdiwYYPAeZ06dRKI18DAoNh9cXNzK3M8P8vPz0d8fDy8vLzg4OCAHz9+CFRdl1XRD+CKThPwszt37mDmzJlIT0+HtbU13N3dhXZOBirvvVNe+fn5bNJiamqKrKws7NmzB/3794epqSnatWsHW1tbbNu2TaDGrKjo6Gj278aNG4u8loGBAfseEva53rZtW5w5cwa9evWCqqoqVFRU0L17d3h4eIhdGz9v3jwoKioiMzNTIq/L8khLS8OCBQtgYGCAvXv34vHjx3jy5Al27NiBunXrsqOyhTU/liQ7O5t9rkxMTIp1O6kofgIjrGmLv83e3r5Mo0j5LQF6enqwsrICUPiZwk/IxWkp4JOTk4O9vX2pMVakNok/2Gv37t3YtGkTgML3Bb8WjI/H4yEmJgYASk3K+O+JmJgYsX54lDrqjcPhYNmyZfjtt98AAOfOncO5c+dgYGAAU1NTmJiYoFOnTujQoYPI3vItWrTAmDFjcP78eWRnZ2Pnzp1wdnZGq1atYGJiAlNTU3Tp0qXUpKVz586IiIhAWFgYMjIy2GY8Ho+HFy9eAPj/BMnCwgIcDgcRERFIS0tj22AZhmGP7dSpU4n9pUTZvXs3Pn78CA6Hg7/++qtY3wxdXV107twZCxYsENj+7ds3trnE0tIS//zzD5v16ujoYM6cOWjTpg1mz56NhIQE7N+/H6tWrRIaw6dPnzB+/Hi2bRwoHLnk6uqKQYMG4ePHj1i0aBHq16+Ps2fPClQHOzo6IikpCQcPHsStW7ewceNGkb/wP336hMWLF+OXX35ht3Xs2BGHDx/GzJkz8fTpUxw5cgQTJkxA/fr12WPu3r2Lx48fAyhMUooO+9TS0sLWrVuhpaWFf/75Bw8ePMDdu3fZ+Y+A//9FPWnSJCxevFggJn19fZiZmQkdpi6KkpISlJSU2NeogoJCic3AJ0+exIsXL6CgoAA3NzeBLwVNTU1MnDgRnTt3xujRoxEQEID//vuv2Bu3NIsWLRK6vV69emjXrh0GDBiAESNG4Pr161i0aBE7h5G8vDzU1NTYpjAOh1PuJm1hunTpgpSUlGLbW7dujY0bN5arRikmJgbnzp0DUFiLIWo4enlcuHAB69evR0FBAYYMGYLt27ezj40wlfXeKa/k5GS2NkhZWRmjR48uVsMcGxsLd3d3XLp0Cfv27SuWtBTt7lCvXj2R11JUVETdunWRkpIi9DkHgDZt2uDw4cPlvDeFydjo0aNx5swZeHh4YPr06dDT0yt3eeWRmpqKtm3bwsPDA6qqquz24cOHQ1VVFQsWLMDnz5/x9OnTYiM6S5KQkMA2v7do0ULicdvZ2WHLli149+4d3rx5AxMTEwCFtbNPnjwBULYk5Nu3b2zNmb29Pft5yOFwMHToUBw4cAABAQGIj48XOV/hz4YNGwY3Nzc8efIE3759g66uLoDCPkRv376FkpKSwDxP4rh//77Adw6fgoIChgwZgo0bNxZLDjMyMtjnoqTXfNH9ubm5yMjIKPU9LFYaOnToULi4uAi8uOPj43Hr1i3s3r0bDg4O6N27N9zc3IT2qQCADRs2YO7cuWz/Bh6Ph8jISHh6emLjxo2ws7PDsGHD2GpMYfjNZAUFBQL9f/jJUN26dcHlcgEUfvC1aNECPB5PoE9TVFQU+4FQnma39PR0XLp0CUDhC6SkDqxF21OBwuya/0T+/vvvQqsGe/Xqxf6y9fT0FNmspaKigmXLlhXbrqSkxMaUn5+PefPmCW0z51cR5+XlISwsTOR9aNCggdAmRHl5eaxevZot4+eq4QsXLgAo/NUiag6VRYsWsS9Y/vF8/F92pXWKlBb+ZGjjxo0T+cuZy+ViyJAhACC0aryijIyMYGxsDIZhyt1kLSn169fHlClT2L5/ZZGdnY3FixcjNzcXCgoK+P333yUW16FDh7BmzRoUFBRg8uTJcHZ2LjFJAqT/3unSpQsiIiIQERFR7MeSOPjNIkBhh+y3b9+ib9++uHz5Ml6/fo1Hjx5hxYoVUFJSwo8fP+Dk5FSsZonfBxMovU8Zf39mZmaZYxXX3LlzoaSkhOzsbBw6dEhq1ykJvxnxZ/369WO7mPAHBImraK2/NKY/0NTUhI2NDQDBGhtvb2/k5+ejXbt2pU72WBT/PKB4gsW/zQiZOqAkrVu3Rrt27VBQUCAw/yE/Xhsbm1IHgYmrW7ducHBwEJrYFH39imp24yv6nhDndS92fZ2dnR3u3r0LFxcXDBs2rFjV1tevX+Hs7IypU6cKvEn55OXlsWjRIjx48ABr165Fnz59inUEDA8Ph5OTEztn08+KJjZFm9/4TWnm5uYCWaaw5reif5enI/fz58/ZZFDUHE0lnQsUzjVT0sRe/JqJ1NRUREVFCT2mQ4cObC3Zz4o+Nz179hR6TNEZloVNjsZnY2NTLOHja926NTtqo2gyyjAMe7tPnz4lthXzPwR+7qDPb0M+cuQI7t27JzJhlIaYmBh25llLS0u2X5awf/zEXNgIDHGkpKTg8OHDmDx5Mrp16wYTExOBTtn8D+6iTSnSdv/+fQQFBSEgIABXr17F8uXLkZOTgzVr1mDChAll6ojNMAxWrVrFNk/8+uuvaN++fYVj5Pf1+/PPP9ly16xZI1YNcWW9d8qraFNAXl4eevXqhX379qFt27ZQUlJC/fr1MX36dOzYsQNA4Wvo5yatomWU9piI0/RQUQ0aNMC4ceMAAOfPnxfZZCgtSkpKImfpl5OTY59TYaOkZY2fwFy7do1NcsrbpMVvVuNyucW+g5o3b44OHToIHCcu/gg9foKVn5+Pa9euCewrC2tra7YbwdOnT3Hy5EkMHToUDx8+xMSJE9l5kkQpT0tRSco0PW6dOnVgZ2eHnTt34s6dO/D398f+/fthZ2fHJijPnz/H7t27RZaho6ODSZMm4cCBA/D19cW9e/ewdetWmJubs8e4u7sLrVnS09Njv5iLjtDgJz8/1xAJS5T456mrq5drFtK4uDj277I2H/BHLpT2C4DfFwuAwFTxRRVt5vpZ0XZyUVXcRY/hV/MLU1p1Mr+5tOiojPT0dLYDcmnNqfz7+uPHD4FO3U5OTqhbty6Sk5Mxd+5cWFlZYe7cuThy5EiZf/WVVdGk5Ndff2VH+gn7x0/qy9NJNTg4GIMGDcLu3bvh7++PpKQkkaPoitYySJuqqirU1NTYfoEzZszAhQsXoKmpiZCQkDJNFrllyxZcv34dADB+/HjMnj1bIjHu3bsXx48fh5ycHDZt2oR58+aJfW5lvXfK6+daDycnJ6Ef/HZ2dmyifvfuXZFlCBuNVBT/h5+w2hZJmj17NpSVlZGTk4ODBw9K9Vo/09HRKbGmkT+0vrTH6mdFa0qkNejC2toaWlpaSEpKwuPHjxEVFYXQ0FC2GUpcERERCA8PByA6weJvj46OZqfQEceQIUOgoKCAkJAQREVF4fHjx0hKSoKWllapM4sLw+9eoKamhnr16sHS0hK7du1iRzYePHiwWJ+ooq/f0t6XRfeL87qv0DoCmpqa6Nu3L1xcXPD333+zb+YLFy6IbIL7WaNGjTBq1CicPXtWYBjsqVOnhB7PT4ZevnzJXoOf/PzcQZSfKL1+/Zp9YIrWPok7A2lRRb/My9ovhD/sv7Qnpmi5oqYKEDd2cY4r6RdlabHy9xeNs+jf5b2vjRs3hqenJ0aMGAFVVVX8+PED9+7dw65duzB69Gj079+/TNXDZVGepETc1ztfeno65s+fz65BtHTpUpw7dw4PHz5EYGAg+2uK/5quzBo1YZo1a8ZOOeDr6yvWgI49e/awTZhDhgzB+vXrJRYPv8lDTk5OZKdtUSrrvVNeWlpa7GepsrIy2y9FGP7nYXx8vMD7p2iTYUmjMvPy8tgv+LI+jmVVv359ODg4ACj8jhA25F1axH3Oy/p86uvrswlYWQc5iUtJSYmdQdrLy4ut7enRo0epfXGKKlpL1KpVK4SFhRX716JFC/a1V5ZaJV1dXXTv3r1YjIMHDy61Kbwspk6dynbE5s8Txle032ZpI5H5+5WUlMT6HpfYgkv8oaNAYVZenhfN0qVL2XZeUfNa8JvLcnJy8ObNG8TGxiIxMRFKSkrFqvSbNGmC+vXrsxNMfvz4kR3SW975k8RJYko7t7Q20aL7JdlJtzzEjbVonEX/Lu38oo/hz/e1SZMm2L59O/z8/HDmzBmsWLEC1tbWUFRURFxcHH777Td2BKEkFU3url69yvY3Ke1fWdy8eRPfvn2DnJwcTpw4gdmzZ8PMzAwNGjSAhoYG+2uqrK8xaSr6/irt/h47dgz79u0DUNj8umPHDomu77Z06VJ2UeslS5aUaUhzVaeqqoqGDRsCKJxrp6THrWi/mKI/4oouuPrx40eR58fHx7MjNqXRGflns2bNgqqqKvLy8nDgwAGpX0/alJWV2W4Cb968KXONlLj4NT337t0rV7NbQUGBQD/KOXPmYPjw4cX+TZ06lU0Wr127VqZ54vjxXL58mZ2fSBJzJxXF4XDYwSQ/fwbJycmxLU4fPnwosRz+e8LQ0FCsZjqJrkxZtElJWD+l0igqKrJ3VNT5RZvXAgMD2RoiU1NToX1h+L/IAwICJDJ/UrNmzdi/S+oELQx/+GVpcyQV7ZdUdA4VWSgt4X337h0ACIyQUFdXZ6uk+ftF4T8WWlpaIkceKCkpwcLCAtOnT4ebmxvu3LnDvk72799frqH5JSnaT6UiE9GVhF8FbmRkJNDUWlRubi473LUqKFqrVdKHy4ULF9gFcrt27QpXV1eR/dzKS0VFBYcPHxZIlv777z+JXkOW+F8GqampJb6+i45UK5o0tW7dmu2w+vOCuEUVHRTD/8KXpnr16mHChAkACid9Le0LrTrgz5qemZnJ9suRNDMzMxgaGiI7OxuJiYlQV1dnB/2I48mTJ2XuT5eSkgIfHx+xj+/bty/U1dWRmJiInJwcGBoasn2eJIn/OSTsM4g/2CQ0NFRkkpeXl8d+ros7OEWiiVLRCdhK6gdQEn4nP1HnN27cmP21VTRR4jez/Yy//fnz52wTXZ06dco9aV7Hjh3ZD6CydnjjxxITE1PiL3L+r+Oio/hk5cGDByLnFomKimK/yIs2e3I4HPb2vXv3RL5gc3Nz2ZlUi/ZRK42+vj5bhZ+SklKmDpj8L+ySmrK4XC7bP0WcRT/Lg99UV1IcN2/eLLGtXZz7IklFB1AU7dBc1LVr19iJCM3MzLB///5SR6CUl6qqqkCytHjx4hqTLPGnysjJySkx0eE/J4aGhgJLWCgrK7Nz5Ny9e1dk0zB/EXJNTU2Rn6GSNnPmTKipqSEvL49dRLY6Gz9+PPsjz8XFReylWtLS0srUqb1op+iBAweWac4mfi2UkpISnj9/XmLN+Js3b9hm2LIsaaKsrIwBAwawtyVdmwQUdhLnT+8jbK4k/uCg7OxskUnegwcP2Jo/cZPNUhOluLg4uLi4iJxjgy8sLIztgG1oaChQE3L79m1cuHCh1Gq8M2fOsC8cfnunMPw3NH9kTtFtJR3Ln8W5Q4cO5f7wVldXZ0e7Xb58WehspHw/JxhDhw5l21C3bNkiNAF5+PAhW+aoUaMk2lxRHgkJCThy5Eix7QUFBWxHZkVFRXbSMT7+mjyJiYlsE8zP/v77bzbJGTt2rMC+0mqi+J3q5eXlRY5gEob/AVDSyC0Oh4OpU6cCKJwQ093dvcQyc3NzRXa6F4Xfzv7+/XuhI9q+fPkCZ2fnEsvg35fk5OQyT5RXVHJycqnv79DQUJw9exZAYezCBjL4+PhgxYoV4PF4MDIywuHDh6XedFxTk6UBAwawU2O4uroKTYYvXbrEvk+Ederl19wkJyfj2LFjxfY/f/6cXetq7NixEq/1E0VbW5vt7+bl5VXm905Vo6GhgbVr1wIo/LybMWNGqSNDg4ODMXr06DLVGE+bNg3Xr1/H9evXsWLFCrHPS09PZzv79+7du9Q5gxQVFdlpMu7fv1/qZ0NRK1euZGPkf4aKKzo6utQ+Ynv27GFrxoRNzdOnTx+2IsXV1bXYD4Tc3Fzs2bMHQGEriKhlTn5W6rdwdnY2Dh48CGtrayxZsgSXL1/G27dv8f37dyQnJ+P169dwdXXFxIkT2V+/P0+k9+XLF6xZswbW1tbYvHkz7ty5gw8fPiA1NRVfv36Fr68vVq1axU4Ap6qqWuLoGH7/orS0NHz48EGgBuNnbdq0gZqaGjIzM9kXZUUXwl2yZAkaN24MhmHw66+/YvPmzXj58iW+f/+OpKQkBAUF4e+//8bw4cMFztPV1WXnFPLz88O0adPw7NkzfP/+HR8+fMDhw4fZWY8bNGiAuXPnVihOSWjUqBH++usvbN26FW/fvkVKSgqCgoIwe/ZsdsKzmTNnFqsB7Nu3Lzt794EDB7Bu3TqEhYUhJSUF4eHhWLNmDTuJXdG5o/gGDx6MqVOn4vTp03jz5g2SkpKQnJyMkJAQ7Nixg+3I17dv3zItBsmvan3+/Dlu3LiBlJQU5OfnIz8/X6CJY8qUKezrZNu2bXBycsLDhw/x9etXpKam4sOHD7h//z42b96M3r17s7/MxTVgwADIy8uzM4Dfvn0bX79+RUJCAjw9PTF27FikpqaW2PTKvy/8N/+XL1+Ql5eH/Pz8MtUyRUVFoW/fvli3bh3u3LmDuLg4/PjxA0lJSXjx4gWcnZ3h4OCAzMxMyMnJYe3atcWqvQMDA7Fw4ULk5eWhUaNG2Lt3L7vGl7B/Ze38XpKfkyVZN8NJYgkTZWVldoSPr68vZs2ahefPnyMlJQWxsbHYu3cv++XcpEkToV9KvXr1YidP/Ouvv+Di4oIPHz4gMTERly5dwty5c8Hj8UTOlSZN06dPh4aGBgoKCqp9ogQUTlzJ/84KCQnBgAEDsGPHDvj7+yMhIQEpKSl49+4dLl++jDlz5mDcuHFlblZXVVVFy5Yt0bJlyzLN2XTz5k22K4u4o+T4x+Xl5bGjVsVRt25dNsayjqI8dOgQ7O3tcfjwYQQGBuLLly9IS0tDfHw8O/M+fw6upk2bCl0DUUlJiR2VGxkZienTpyMoKAjJyckICgrC9OnTERkZCQD47bffxK4wKfUnhJKSEhQVFZGTk4Nr166V2AarrKyMFStWFJuFU01NDRwOB8nJyTh58iQ7EkaYBg0a4M8//yxxCvKfO2K3bt1a5AtHXl4eZmZm7Je6sPPLSlNTE8ePH8fcuXMRGRkp8j7VqVMHy5Ytw5s3b9ip0v/66y84OjrixIkT8Pf3F7pWmYGBAdzc3IRO0sWvgfH29satW7fQvHlzjBo1Cg4ODlKpfZozZw6uXr2K48ePC+04PWjQIKGT6nE4HLi4uGDevHkICAhgZ3T/WZcuXdi5cIriT7JY0kSLbdu2LfNIqmHDhuHw4cP48eNHsYTeycmJvS+Kioo4dOgQli9fjrt37+L27dslToZa1hrKZs2aYcmSJdi1axdiY2OLTcpZp04d7Nq1C6dOnRL5RdK+fXuYm5vjxYsXOHTokMBEfpaWliW+z36Wnp4u8jni09TUxMaNG4X+Cvv333/Z6uxPnz6Vutr9iBEj2H5MksBPlmbPno2AgAAsWbIELi4upcZRldnZ2SEhIQHOzs548uSJwGcYX7NmzXDo0CGRtap//vknZsyYgZcvX+LgwYPFhuXr6enh0KFDUh/x9jNNTU1MmTKFXamgJli6dClatGiBXbt2ISkpCUePHsXRo0eFHsvhcGBvbw8jIyOpx8VvPlNXVxe7BqVz585o0KABvnz5Ai8vL7Z2Utr4S5WUxNzcHC4uLiJrq+3s7BAXFwdXV1cEBASw3TT45OTksGjRInYkoThKTZQMDQ3x7NkzPHz4EP7+/ggLC0NcXBzS0tLA4XBQt25dtGjRAl27dsXIkSPZaq+iRowYga5du8LHxweBgYGIjIxEfHw8MjMzoaSkBB0dHXC5XPTu3Rv29valVte3bNkSOjo67Nw1pbWtW1hYsB8yCgoKJS4SKa7GjRvj0qVLuHTpEm7evImwsDCkpqaibt260NfXB4/HQ1hYWLEZmzkcDn7//XcMGDAAHh4eeP78OZKSkqCsrIzmzZujf//+mDhxotDHYOPGjWzn6nr16sHU1BS+vr7YtGkTfH194erqWq4pD0qiqKiIo0eP4sSJE/D29kZsbCyAwk7I48aNK3HSzbp16+LEiRO4cuUKvL29ERoayj5GxsbGGDp0KIYOHSq0U56npyd8fX3h5+eHuLg4fPv2DTk5OdDU1ESbNm0wcOBADB8+vMxDT/X09HD27FkcPHgQgYGB7EK3wqirq2P//v3w9fWFl5cXnj9/jm/fviEvLw8aGhowNDSElZUVbG1tyzUn18yZM9GyZUu4u7vjzZs3yM3NhZ6eHrp27YqpU6eCy+WKnCaDz83NDQcOHICPjw8+ffpUrkEUHTp0wIEDB+Dn54fg4GB8/fqVHT6rpaWF1q1bo2fPnhg2bJjYK6PLws/J0uLFi2WSLH3+/Jn9uyx974SZPn06LC0tcerUKfj7+yMxMRF16tRBy5YtMWDAADg4OJRYo6qhoQEPDw+cPXsWV65cQXR0NPLy8mBgYIC+ffti2rRpxSb+rSxTp07FyZMnS1zTsroZMWIEBgwYAG9vbzx8+BDh4eHsYuCamppo2bIlOnfujGHDhons5ydJ8fHxbPeU/v37lzpLO5+cnBzs7Oxw7NgxBAcHIyYmhh1AIy0LFy6EhYUF/Pz8EBkZiW/fviE1NRXKysqoX78+TExMYGdnh169epVaKfDLL7+gU6dOOHnyJIKCgvD9+3doa2vDwsICkydPLnOrEoepjGlZa6ELFy4gOjoaJiYmMDExwe+//84uxlnWNcGAwg7eCxcuhJ6eHk6dOsW+aL99+wZHR0e8e/cOq1evxpQpUyQSP/+XzrZt2zBy5EiJlElIbbB8+XJ4eXmhe/fuImsUCCHVR+X03quFxowZI9Hy+M0qy5YtE8jsdXV1sWHDBkyePBlubm6YPHmyzDuAE1KbPX36FHJycuxC4oSQ6o2+UauBhIQEhISEQFFRUWhtlKWlJRo0aIDExESBeVEIIZUrIiICiYmJsLe3L/MSR4SQqolqlKoB/uRYrVu3Fjl3hqmpKb58+YKwsDCRIwAJIdJlZGRU5lnaCSFVG9UoVQP86daLzn79M34n+pKWKyCEEEJI2VCNUjXAXy+tpNEt/FFy4q4NFhQUJNYaN7GxsexMqDURj8ejPl1VTFV9TgoKChAeHg5dXV12MkhZe/v2LTstQ8uWLUudUywiIoId5cnlcss0rYW4z0t4eDg7AWpZr1FeOTk57NJP8vLyaNOmjVifb+XB4XAkMnKaVB+UKFUD/IGJknzjq6iolNiHorY0H4SFhVFfkiqmqj4n9+7dw+TJk3H9+vUKD/uXlClTpuD169cACtd0+3lh8J9NnToVr169AlA46WpZ7oc4zwvDMOjSpQubjGVkZJR54sHyYBgGw4cPZ1d2CA4Olso6Y0DZ1/gk1V/V+9lGiuHXFvFrloTh1yRJe8kIUnWlpKRU2rpvtVGvXr0QHBzMznZdFRSdTV6c2p6i82CJuyZZWaSlpbFJkqqqaqUkSUDhj8iiz0tZFnMlpDSUKFUD/GUs4uPjRR7DX5C4pCUvpCU2NlZgkj1Sefbu3YstW7aAYRiMHz8e1tbWePv2razDqpHk5eXRoUOHKvVjpGiiJE6Ns7QTpaIr1Ovq6kq8/JIUnXWaEiUiSZQoVQPGxsYACqd35/dH+Bm/+r0ymizy8/Px+PFjrFy5Eu3atYOhoSECAwMBFC7AmZqaKvUYCHD48GEsWLAAgYGB4PF4mDx5MkJCQtChQwccPHiw1AUmifh4PB4WLVoEPz8/WYcioOhzXBVqlPhLLAGFs+BXpl69erF/+/j4CCSRhFQEJUrVQMOGDdGuXTvk5eUJXXyVv/Cinp6e1PtOxMbGokGDBujZsyd2794NfX19ODs7s8tEuLi4QF9fHxMnToSXlxfbZ+BnPB4PwcHBcHZ2ZtckYxgG3t7eCAwMZJfQIMK5u7tjzpw5sLOzw9mzZyEvL4+JEyfizZs36N69O+bOnYtBgwYhPT1d1qHWCKGhoXB1dUV4eLisQxFQkaa3sqwKL66iiVJl1ygZGxuz10xKSmKnVSGkoihRqkJ2796NgQMHCl0UkL8ytbOzM7veGlD4gbBx40YAwKxZs6Q+Wqhp06ZwcHDA+fPn8e3bN9y9exdLly5l53caMWIEpk6dihs3bmD48OHQ19dn1+JjGAZHjx6Fg4MD9PX1YW5ujt9++w1xcXEACmujhg4dis6dO0NfXx/z5s2jJj0hPDw8MH36dPTr1w8XL14UWL+pcePGuHXrFv7++298/fq1RqzMXhXw14rs3r27jCMRVNamt6KL30q7RqmyEyXqp0SkhUa9SUlISAibwABg+424uLgIrP90/vx59u/ExERER0cLtPPzDRw4EA4ODjhz5gzs7e3RrVs3KCgowNfXF+np6ejXrx8mTZokxXtUiMPhlLjit4WFBfbv3w8XFxcEBATAz8+PbS7kcDhwdXVFYmIiBg4ciH79+qFv375svyoNDQ34+/sjPj4et27dgpubG9zd3XH79u0q9wVVGV6/fo1z584hOTkZ379/x6RJkzB48GDk5OTAxsYGXl5eQicg5XA4cHJywvz586U2RLq2efr0KerXr4+WLVvKOhQBVa3prehnV2U3vQGF/ZQ8PT0BAA8ePMD8+fMrPQZS81CiJCXp6el4+fJlse0xMTHlLnPDhg3o2LEjTp8+DX9/f/B4PLRo0QKjRo2Cg4NDlZp7pk6dOujRowd69OghsP3OnTvQ1dUV+gWupKSEzp07AwCGDRuGpUuXwtXVlV3p+fHjx+ycTvzz1dTUMHXq1BqVEOTm5uL333+Hi4sLgMIvN21tbQwYMAAAMG3aNEyZMqXU55vD4eD79+94+PAhhg0bJvW4a7KnT5+iW7duVe51VtVGvcmyRgkQ7Kf08OFDMAxT5Z4zUv1QoiQlXbp0KfNcRNu3b8f27dtLPMbe3h729vYVCU2myvIrs2XLltizZw8AIC8vDxMmTMCHDx8Ejhk0aBCmTZsGoHCKhKo0Iqm8FBUVERQUhOnTp2P79u3Q0dEpdoy4SfHGjRuxb98+hIeHV7nakOoiPT0dubm5VbJWkxIlQSYmJtDR0UFycjK+fv2K8PDwKjknF6leqk4VBCElUFRUxOvXr/Ht2zckJiay//hNl9HR0WjYsCEWLlzI9nmqLvLy8vDs2TM4ODjg48eP4HA4uHnzJg4fPiw0SSqLFStWQElJCWvXrpVQtLWPuro6YmNjsXjxYlmHUkzRpreqNj2ALJre5OTkBPopPXjwoNJjIDUPJUqk2tDU1ES9evWgq6vL/lNXVwcAKCgoYPTo0Thw4ABatWqFU6dOyTjakqWkpGDLli2wtbWFtrY2rKyscOXKFTx//hxAYWIoCQ0bNsSiRYtw5syZGr0UTWWQl5eXdQjF0Ki34n6eJoCQiqJEidQITZo0wdGjR/Hu3Tv06NEDjo6OcHd3l3VYIikqKmLTpk1ISEjAtGnTcOHCBcTFxUmlL9Hy5cuho6ODVatWSbzs2mDMmDECAzOqkrImSjV51Bvfz4kSzSdGKor6KJEapWnTprh69SpGjBhRoY7z0hIcHIzmzZtDU1MTiYmJqFu3rtSvqampidWrV+Phw4fIysoqdeFU8v+ys7Nx5coVNG/eXNahCFXRmbkl3dlZlhNO8rVv3x6ampr48eMHEhISEBUVBS6XK5NYSM1ANUqkxlFVVcXVq1exfv16AIXzM1UFaWlpsLe3x9ixYwGgUpIkviVLlsDLy4uSpDJ6/vx5le3IDZR9eoA6deqwr4GCggKJTkian5/Pvtc4HI5AUlaZ5OXlqZ8SkShKlEiNpKioCA6Hw/6adHV1lXVIWL9+PT5+/IgNGzZU+rX5tQavXr3C8OHDaQV0MT19+hQAYGVlJeNIhCtr0xsgvQ7dRX+QaGtrQ0FBdg0WRZvfNmzYgJMnT9KSJqTcKFEiNVqzZs3Qq1cvLFq0CEuXLkVubq5M4njx4gVcXV0xZ84cmX7pRkRE4P79+zAxMcGsWbNKXGiZFM7I3bp1a9SvX1/WoQhV1qY3QHqJUlXon8Q3cOBA9u/Pnz/D0dERXbt2ZWdYJ6QsKFEiNZqSkhLOnj2L+fPn488//0SPHj3w/v37So2hoKAAs2fPhp6eHrZt21ap1/7ZmDFj8O7dOyxYsADHjx9Hq1atsHnzZpnGVJWZmppi4sSJsg5DpLI2vQGCHbolOfJN1lMDFNWuXTucOnUKDRo0YLcFBASgR48eGDt2bJVpjifVAyVKpMZTVFTE3r178e+//yIyMlLoWnrSlJqainr16uGvv/6SWb+NonR1dfHXX38hPDwcw4cPZ5eYKSgowK1bt5Cfny/jCKuOP/74g+3rVhVVpaa3qlSjBAATJ05EVFQUVq1aJbAe4oULF7Bo0SLZBUaqHRr1RmqNUaNGoWPHjuyv3ejoaIl2ZhVFW1sbN27ckPp1yqpFixbw8PBgayXu3r2LgQMHolGjRpgyZQpWrlwJDQ0NGUcpO2/fvoWhoaFM+9qUhhKlkmloaGDr1q2YPXs2VqxYwU5QK2yNREJEoRolUqsYGhpCTU0N+fn5GDJkCHr16oWZM2ciICBA4vOtfP78GYsXL0ZMTAw4HE6VXXOKH1fv3r1x8eJFdOjQAdu2bcPq1atlHJns8Hg89O3bF5MnT5Z1KCUq68zcQOUkSrJuevuZoaEhzp07h6CgIHh4eJS4sDchP6NEidRKCgoKOHnyJOzs7HDmzBlYWlqiY8eO8PLykkj59+7dg7m5OQ4dOoSAgACJlCltSkpKGDlyJK5du4ZJkybB3d0dqampsg5LJp4+fYq4uDgMGTJE1qGUqCrVKBXto1RVapR+Zm5uDgcHBygpKck6FFKNUKJEai0LCwv88ccfiI+Px/79+8Hj8ZCUlFShMgsKCvDHH3+gf//+0NHRQUBAAMaMGSOhiCvPwoUL0atXr1rb6dXDwwMqKipSmSldkiqaKEmyM3dVbHojRBIoUSLVVkJCAh4/flzhD3tNTU3MnTsXL168wNSpUwEAx44dw927d8tc1ubNm7Fu3TpMnDgR/v7+aNeuXYVik5VOnTrh6tWrMDQ0lHUolS4vLw/nz5/HsGHD2LUEq6ryTA8grWVMqnLTGyEVQYkSqVYiIyOxc+dOdOvWDQYGBujZsyf09fUxYcIE3L59u0KTynE4HMjJySE/Px979uyBra0tXFxcSuy7xDAMHj16BF9fXwCAk5MTjh8/juPHj1f5L1lxREdHIzQ0VNZhVKo7d+4gKSkJEyZMkHUopSrP9ADSanorumSQvr6+xMolROYYUiuFhobKOgSxJScnM9u2bWOMjY0ZACX+a9q0KbNu3Trmy5cvYpUt6nFITU1lRo4cyQBgJk6cyISHh7P74uLimJcvXzI7d+5kuFwuA4AZPHiwRO5rVZKfn880atSIGTRoUKVeV9avzfz8fObu3btMTk6OTOMQh4KCAvvaz83NFeuchw8fsudYWVmJfa2SnpecnBxGXl6eLTc9PV3scqsbWb8+SeWjGiVSZcXExGDRokVo0qQJVq1aVaxmQ15eHi1atBDYFhcXh02bNsHMzKxCy3RoaGjgwoUL2Lx5Mzw8PNCjRw9238KFC9GhQwcsX74cenp6OHbsGM6dO1fua1VV8vLymDVrFm7cuIGoqChZh1Np5OXl0adPn2rR4beqdOaOiopCQUEBgMLZ8NXU1CRSLiFVASVKpMp59eoVHBwc0KpVK7i6uiIjI4Pdp6KiguHDh8Pd3R1fvnzBu3fvEBwcjF9//RX16tVjj/v8+TN69eqFly9fljsOOTk5/P777wgICICbmxu7fdmyZTh37hxCQ0Px+PFjTJ06tcZ+McyZM4edsLM2uHr1KpYuXVop82tJAlNFpgco+qOkbdu2EimTkCpD1lVaRDaqYvVxamoq8+uvvzJycnLFmtRMTEyYY8eOMRkZGSLPz87OZk6fPs2oq6uz52lrazMBAQEiz6mKj0NVM3HiREZDQ4NJTU2tlOvJ8jmxt7dnGjVqxBQUFMgsBnHxeDyB9wiPxxPrvIyMDPacOnXqiH29kp6XTZs2sWUuWbJE7DKrI/rMqH2oRomUC8MwePfuHS5cuIDff/8d69evx5MnT9jq97KWdfHiRbRt2xaurq4CzQl9+/bFjRs38OrVK0ydOhWqqqoiy6lTpw4mTJiA//77D5qamgAKfzH37duXXQWelN2CBQuQnZ3NdlivqZKSknDjxg04ODiI3YwlS8xPtUni1iipqKhAUVERAJCTk4OsrKwKx0I1SqQmq7pz85Mqhz8azNvbGy9evMCPHz8E9m/atAm6urqws7ODvb09bG1tUbduXZHlMQyDiIgILFu2DNeuXRPY169fP+zYsQMWFhZljtPKygr37t1D//79kZycjNTUVNja2sLb2xs2NjZlLq+269KlCz59+lTjh3z/+++/yM/Prxaj3YDyNbvxj9XW1sbXr18BFP6YUFFRqVAsRfsPUqJEahpKlIjYTp48iaVLl5Z4zLdv33DixAmcOHEC8vLyaN++PaysrNh/6urquHfvHu7evYs7d+4gNjZW4Pz69evDxcUFDg4OFVryw8LCAg8ePEC/fv3w9etXZGRkwM7ODl5eXrC1tS13ubUVP0nKzs6usetkeXh4oE2bNjAzM5N1KGIpT0duvp8TJQMDg3LHUVBQgIiICPY2JUqkpqFEiYitfv36Arfr1asHCwsLWFhYICkpCVevXkVCQgK7v6CgAC9evMCLFy+wf//+EsvmcDiYM2cOtm7dKtDZtCJMTU3x8OFD9O3bF58+fUJ2djaGDh0KT09P2NnZSeQatcmoUaOgrq6O48ePyzoUiSsoKEDz5s0xbNiwKrsm388qmijxVbRDd2xsLLKzswEADRo0gI6OToXKI6SqoUSJiG3w4MHw8/NDQkICzMzM0KRJE4EvFR6Ph6CgIHh7e+Pq1at48eJFqQvNqqmpwcbGBqtXr4aVlZXEYzYyMoKPjw/69OmDuLg45OTkYMSIEbhw4QKGDh0q8evVZCoqKrhx4wZ4PF616MNTFvLy8nB3d5d1GGVS3qY3QLKJEjW7kZqOEiVSJpaWliL3ycnJoVOnTujUqRM2btyIHz9+wN/fH76+vnj69CmePXuGzMxMdO3aFX379kXfvn1haWkp9flqWrZsCR8fH9jY2CAmJga5ubkYNWoUzp49C2NjY6leuyaxs7PD6dOnERgYWOLroLrJyspCaGgoOnbsKOtQyqQiNUpFlzGp6BJARTty0/uJ1ESUKBGp0dTURP/+/dG/f38Ahb+AGYaRSW2EoaEhHj58CBsbG7x79w75+fkYN24cdu7cSb+CxTRgwABwOBxcv369RiVKZ86cwYwZM+Dv74/OnTvLOhyxVZWmNxrxRmq6mlV/Tqo0/lpqstKkSRP4+PiAy+UCKOyXsmzZMuzbt09mMVUn9erVQ9euXYuNUKzOGIbBnj17YGpqik6dOsk6nDKpKokSNb2Rmo4SJVKrNGrUCD4+PuwHOsMwcHJywsqVKyu0oG5tsWjRIkyfPr3UvmfVxaNHj/Dy5UssXLiw2nTi5qsKfZQYhqEaJVLjUaJEah19fX34+PigS5cu7LYdO3bA0dERubm5Moys6hs7dizmzp1b7ZIKUf7++29oa2tXm7mTiqoKNUqfP39GamoqgMKm9oYNG5a7LEKqKkqUSK2kp6eHe/fuCUxAefr0adjZ2RWbSFMWvn79Cm9vbxw9ehRPnz6tUmuPJSQk4P79+7IOo8LS09Nx7949zJo1q8QZ36uqqpAo/dzsVlMSaEKKos7cpNp68OAB/vnnH/Tt2xdTp04t8/mqqqpwdXXFvn37cOjQIQDA3bt30a1bN7i7u1dKx97MzEx8+PABcXFxePPmDfz8/ODn54eYmBiB4zgcDlq1agUzMzOYm5ujf//+sLCwkEmfrzVr1uDff/9FYmIiuxRGdaSuro7Y2Fjk5eXJOpRyqUjTm6RGvVGzG6kNqEaJVDtJSUmYPn06bGxs4OXlhefPnwMo7Jy9cOFCeHl5id3fSEFBAQcOHMDmzZvZbaGhoejatSsWLVqEtLQ0icYeEhKCuXPnolOnTtDT04OamhratGkDW1tbLFmyBOfOnSuWJAGFX4pRUVG4cOECVq9ejc6dO6Nhw4aYMmUKzp07J7FV4MUxePBg/Pjxo1qv/Zafnw+GYaCuri6xCU4rW1WoUaKpAUitUOnL8JIqobqugH3r1i1GV1eXUVBQYFauXMlkZGQweXl5DMMwTGRkJKOhocEAYCZNmsRuL0nRx+H48eOMioqKwIrsTZo0Yby9vSsUM4/HY+7evcsMGjRIoOyS/ikrKzPdunVjxo4dy7Rr146Rl5cv8Xh5eXlm3rx5THp6eoViFcePHz8YRUVFZvny5VIpvzJem0eOHGGMjY2ZhIQEqV9LWj5//sw+/w0aNCjTuTExMey5jRo1EuscYc9Lr1692HKuXr1aphiqq+r62UnKjxKlWqq6vtlDQ0OZXr16Ma9evRK6Pzc3l/njjz8YAMyIESOY7OzsUssr6v3794ytrW2xRGTQoEHM8ePHmW/fvpUaI4/HY75+/co8evSI2bdvH2NmZiYywVFQUGCaN2/O9OrVi5k2bRqzf/9+JjAwkMnNzRUoMzMzkwkICGAOHz7MODo6Mnp6ekLLa9myJfPkyZNSY6yoPn36MCYmJlIpW9qvTR6Px3To0IExNTVleDyeVK8lTfHx8ezz3rBhwzKdm5aWxp6rqKhY6vuEYYQ/L/Xr12fLeffuXZliqK6q62cnKT9KlGqp6vRm5/F4zJkzZ5j8/Hyxz3F1dWUAMLNnzy7xOGGPA4/HY06dOiU0GZGXl2d69erF/Pnnn4yXlxdz5MgRZtu2bczixYuZiRMnMlZWVoyOjo7IxIjD4TDDhw9nbt26xXz8+LFM96mogoICxt/fn9mwYQPTsWNHgWvIyckxq1atYnJycspVtjicnZ0ZAMynT58kXra0X5u+vr4MAObw4cNSvY60ffz4kX3ODQwMynx+y5Yt2fOfPXtW6vE/Py9JSUkCNaDlfS1XN9Xps5NIBiVKtVR1erPv37+fAcCcO3euTOedOnWKiYmJKfGYkh6Hb9++MdOmTRO7uaykfyoqKszcuXOZyMjIMt0HcfB4POb48eNM3bp1Ba7ZoUMH5vXr1xK/HsMwTGJiIhMbGyuVsqX92ly/fj0jJyfHJCcnS/U60hYXF8c+140bNy7z+RMmTGDPd3V1LfX4n5+Xx48fs+ebmZmV+frVVXX67CSSQZ25SZUWGRmJpUuXYsCAARgzZkyZzp04cSKaNWsGHo+HzZs3l7nTar169XD06FFERERg+/bt6Nq1q9iji9TU1GBhYYEJEybA2dkZcXFx2L9/P1q3bl2mGMTB4XDg6OiI169fo0+fPuz2ly9fomvXrvD29pb4NXV1ddG0aVOJl1sZbt++jU6dOlXbTtx8FenMDUBgHjF/f/8yn08zcpPagqYHIFVWXl4eJk2aBBUVFRw9erTcc7S8efMGf/zxBx48eICbN29CQaFsL3sul4sVK1ZgxYoVSEhIgLe3N27evInMzEzUr1+f/aenp4fGjRujTZs2aNSoUaXPKdO0aVPcvn0be/fuxYoVK5CdnY2MjAwMGzYMu3fvxqJFiyQa09OnT+Hq6orjx49DWVlZYuVK24IFC6r1tAZ8TAWmBwAEEyU/P78yn09TA5DaghIlKfP29saZM2cQEREBHo+H5s2bY9SoUXBwcCjTr8CVK1fi0qVLIvc3b94cN2/elETIVcbWrVsREBCACxcuwMDAoNzltG/fHocPH8bUqVOxdOlSuLq6lrssfX19zJo1C7NmzSp3GdIkJyeHhQsXok+fPrC3t0dMTAwYhsGSJUsQHh6OvXv3SixJSElJwfnz5zF9+nQMGDBAImVWhvHjx8s6BImoaI2SmZkZFBUVkZeXh7dv3yIpKQn16tUT+3yaGoDUFpQoSdHGjRvh4eGBOnXqwMrKCgoKCvD19cWmTZvg6+sLV1dXyMvLl6lMCwsLNGvWrNh2PT09SYVdZdja2iInJwejR4+ucFlTpkzBq1ev8Oeff8LU1BQzZ86UQIRVl4mJCfz8/DB8+HB2vqPDhw/j/fv3OH/+vESanWxsbKCiooKrV69Wm0TpwYMHaNiwIYyMjGQdSoVVNFGqU6cOzMzMEBAQAKCw+W3QoEFin09Nb6TWkHUnqZrq5s2bDJfLZbp3785ER0ez2xMTE5lBgwYxXC6XcXd3F7u8FStWMFwul7l48aJE4qvKHRKlNWQ7Ly+PGTBgAFO3bl22I29VfhwkISsrS6DTLgBGQ0ODmTlzJvPkyZMKP9bDhg1jGjduLNHnTJrPSevWrRk7OzuplV+ZIiMj2ee0VatW5SrDycmJLWPDhg0lHlv0eSk6vYC8vLxUR1hWNTX9M4MUR525pYS/JMayZctgaGjIbtfV1cWGDRsAAG5ubrRivRC//PILFi9eLPEV6hUUFHD27Fncv3+/2nfkFZeysjJOnTqFjRs3stvS0tJw5MgRdO/eHW3btsX27dvx+fPncpU/cuRIfPz4EYGBgZIKWWpiY2MRFRWF/v37yzoUiahojRJQ/n5KERER7N+tW7eGkpJSua5PSHVAiZIUJCQkICQkBIqKihg4cGCx/ZaWlmjQoAESExMRHBxc+QFWYR4eHjh8+DCUlZWl0hlaS0sLFhYWAABPT09kZmZK/BpVDYfDwbp163Dx4kVwuVyBfREREVi1ahWaNm2KsWPH4sGDB2VKUIcMGQJzc/MqsZBwaW7fvg0AlCgV8fPIN3Gfe2p2I7UJJUpSwP8Qad26tcjRQKampgAEO0SKw8/PD9u2bcPatWvx119/4dGjRzWmVioyMhJz5sxB9+7d8ccff0j1WuHh4RgzZozAGm813ciRIxEeHo4nT55g5syZ0NDQYPfl5+fjwoULsLGxQbt27fD3338jNTW11DJ1dHQQFBSEfv36STN0ibh9+zYMDAxqTMfjoklNeROlVq1asbWrSUlJePfunVjn0Yg3UptQoiQFHz9+BIASR2o1bNhQ4FhxXb58Ge7u7jh//jwOHDiAmTNnwt7eXqAqvDrKzs7G2LFjUadOHZw5c6bMQ/jLqk2bNvj9999x+fJlnD59WqrXqko4HA66desGNzc3fP78GSdOnEDPnj0FjgkLC8PChQthYWGBxMREscrNzs6u0rVKDMPgwYMH6NevX6VP2yAtRX8glfc+cTgcWFpasrfFbX6jRInUJjTqTQr4zTkqKioij1FTUwMAZGRkiFVmmzZtsGbNGlhZWcHAwADp6ekIDQ2Fi4sLwsPDMW3aNFy6dAkNGjQQq7ycnJwy12ZJU1BQECIjI/Hnn38iPT29UmIbM2YMvL29MWfOnGo9gWJFdOrUCZ06dUJUVBTOnj2LK1eusK/Jd+/eYcKECXB1dS3xizgjIwM2NjaYOnUq5s2bV+GYsrOzpfL8e3l5ITMzs0q97ivi7du37N95eXnlvl8tWrRg/7558ybbNP0z/vPCMIxAQqWsrFxjHlNChKFESQr4VeKS/OU6depUgduqqqqoX78+unXrhsmTJyM4OBiHDh3CunXrxCqvTp065f4lmJWVhS9fviAhIYH917ZtW/Tq1atc5QGFv0r79++P+vXrl7uM8nB2dsaYMWOwZs0aPHv2rMzTNdQUbdu2xdChQ5GWlobDhw9j2bJlAIA7d+4gICAAU6ZMKfH8Dh064NGjR/j7778rHEtYWBjVUoghJyeH/VtFRaXcj9mQIUNw4MABAEBUVJTIcvjPS2RkJNv5X11dHcOGDasRE3iKi5LC2oea3qSAX1tUUkdh/q92/rHlpaSkhNmzZwMAfHx8KlSWOJKTk6GqqormzZvDysoKI0aMwNy5c9lRT1++fMHIkSOxe/duPHv2DLm5uSLLyszMxOXLl3H8+HEAqPQkCShsHnV3d8eyZctqbZJUlIaGBpYuXYpffvmF3bZgwQLExsaWeN7IkSPx8uVLsfu4VLYVK1bgxIkTsg5DopgKzszN17lzZ/bvFy9eCCRgwty6dYv9u0+fPrUqSSK1EyVKUtCoUSMAQHx8vMhjEhISBI6tCH7V+ZcvXypcVmm0tbWxdetWHD16FNevX0dQUBA+ffqE+fPnAwA+fPiAV69eYdmyZbCysoKmpiasra0RFBQE4P+XE7GxsYG2tjZGjBiB5cuX49u3b1KPXZShQ4di3LhxAFDql0Rt4ezsjFatWgEonE5gypQpJQ4aGDlyJIDCkYRVTVZWFlxdXfHy5UtZhyJRkhj1BhROVsv/DMnNzS31cSqaKFWXiUYJqQhKlKSAP6omKioK2dnZQo95/fo1AMl0hExJSQFQ8dopcXA4HKxatQrTpk3DoEGDYG5uDgMDA3Z0X6dOnfD27Vt8/vwZFy9exLx585Cbm4u6desCAG7cuIH169cjNTUVCxcuxPXr1/Hu3Tvo6upKPfbSnDlzBlwut8wd7GsiNTU1nDx5kv0C9vHxgYuLi8jjDQ0NYWFhUSUTpUePHiEnJ6fGTAvAJ6lECRB/gdycnBzcv3+fvU2JEqkNKFGSgoYNG6Jdu3bIy8sTuv6av78/EhISoKenB3Nz8wpf78aNGwAKl62oKvT19QWa4Pi1EzNmzMC3b9/w/Plz7Nq1C4MGDYK6urqMoy1kamqKxMREcLlcODk54f3797IOSaa6du2K1atXs7dXr16NN2/eiDze2dlZIn2UJO327dtQUlIqNrqvupPE9AB84k48+eTJE7ZLQcuWLdGyZcsKXZeQ6oASJSnh9xtydnYW6N+RlJTEzpI8a9YsgQ+43bt3Y+DAgdi9e7dAWWFhYbh//z4KCgoEtufn5+PYsWM4efIkgOIdvqsiHR0d6OjoyDoMoUxMTPDixQs4ODjg8OHDaN26NdavXy/rsGRq3bp17Cio3NxcTJo0SWS/MxsbG3Tq1KkywxPL7du30a1bt0qpca1MkpgegE/cKQKo2Y3URjTqTUoGDhwIBwcHnDlzBvb29ujWrRu7KG56ejr69euHSZMmCZyTmJiI6OjoYnPX8PsAaWlpwdDQEA0aNEBGRgYiIyPx9etXyMnJYdmyZTXuF7MsGBkZ4Z9//sEff/wBV1dXdOzYEUBhx/Pk5GQ0btxYxhFWLkVFRZw8eRIdO3ZEdnY2Xr58iSNHjoicBuDp06fw8/PD4sWLKzlS4XJzc6GtrY3BgwfLOhSJk2TTm7m5ORQVFZGXl4eoqCgkJycL/UFDiRKpjahGSYo2bNgAZ2dnGBsbw9/fH48fP0azZs2wbt06/P3332KPsjIyMoKjoyOaN2+O+Ph43L9/HwEBAVBRUcHIkSNx4cIFzJo1S8r3pnYxMDDAjh07MHToUADAli1b0LZtW/z111/Iz8+XcXSVy9jYmF2fEAD++OMPkSM6r1+/jt9++w1JSUmVFF3JlJSUcP/+fXa6g5pEkk1vysrK6NChA3tbWD+lxMREtqO3goICevfuXaFrElJtyGo1XiJbtAJ2IXEfh/fv3zN2dnYMAMbc3Jzx8/OTcmRVS2ZmJmNgYMCuGL99+3ahxz1//pwBwBw9erTc15LkazMvL09iZVU1Dx8+ZJ+PHj16VLi8+fPns+Vt3Lix2P7t27ez+62trSt8veqKPjtrH2p6I2Xm7u4u6xAkJjMzU+xlG0aPHg1DQ0N4eHiga9eumD59Onr06IH8/Hzk5eWVOBN7TdCvXz92LqI//vgDGhoaUFVVFTiGYRjo6urCxcWl3P1myvKclGbNmjUwMTHB+PHjJVJeVRIeHs7+nZiYWOH3ZdGpMS5evFhspvqLFy+yf+vp6VXbz4Hq0JeTVC3U9EaImDgcDjp37oytW7di4MCB7ASZUVFRmD9/PtauXYsLFy4gOTlZxpFKR8+ePdn7nJGRwY62LIrD4aBLly4ICQmR+dpvKSkp+PTpEzQ1NWUaR2WQxCoARZcyefv2rUDzKo/HE5iRuiqNsCVE6mRdpUVkg6qPC0nicXj79i2zfv16pl+/foycnByjoKDATJw4kfn27ZsEIqxaPDw82OYXNTU1JiEhodgxoaGhTIMGDZgHDx6U6xqSem2ePXuWAcD4+/tLpLyq5u7du+xzYWNjU+HyCgoKBJpXR4wYwfB4PIZh/r9JFQCjp6fHFBQUVPh61RV9dtY+VKNESAW1bNkSGzZswO3bt/H27Vs4OTkhODiYrcmQdc2KJI0bNw7t27cHUFirtGXLlmLHtG3bFp8+farQ2n+S8ODBA2hoaEhkrjJJyc/PL3GGcwCIiIiAlZUV2rZtK9Dc9TNJjnrjl7Fnzx729qVLl7B3714AgqPd+vfvL5HrEVJd0KudEAlq3rw5XFxc8OrVKygoKCA5ORkmJiZwcnIqce2/6kJOTk4gOTp48KDQdeDk5eXB4/HYNQ1lwcfHBz169ICCQtXoinnixAk0bNgQhoaGuHbtmtBjnj9/jh49euDZs2cIDw/H6NGjMWPGDKSnpwsc9+jRI8ydO5e9Lal1CkeNGsUuRwQAy5Ytw/PnzwUSJVtbW4lci5BqQ9ZVWkQ2qPq4kLQfh6ysLGbx4sUMAKZNmzbM8+fPpXq9ysDj8Zhu3bqxTTFTp04tdkx2djbTvHlzZsWKFWUuXxLPCY/HY3bv3s1cvHixwmVVVFZWFjNnzhz28eL/++2335jc3Fz2uPv37zMaGhrFjgPAtGrVivHz82PS0tKYBQsWMBwOR2D/jh07JBqvubk5W3bz5s0ZRUVF9nZ8fLzErlUd0Wdn7UOJUi1Fb/ZClfU43L59mzEwMGAUFBSYrVu3Mvn5+ZVyXWnx8fFhvzjl5OSYV69eFTvGzs6Oady4cZn7s9Sk12Z0dDTTqVMnockPAMbKyoqJjY1lvLy8mDp16rDbtbW1mWHDhgkcKy8vzzRq1EhgW926dRk3Nze2L5GkREVFCU3a2rdvL9HrVEc16fVJxENNb4RUgn79+uH169cYMWIEHj58CDk5OeTm5qJNmzYwNjaGqakpunfvjnnz5uHevXuyDrdU1tbW7MzMPB4Pv/zyS7G+N5MnT8bHjx/x4MGDSo8vODgYX79+rfTrFnXz5k107NgRgYGB7LZx48bBzs6Ove3r64sOHTpg5MiR7PB8AwMDPHr0CJcuXcLJkyehoaEBACgoKMCnT5/Yc+3s7BASEoKZM2dKZNRbUa1atYKbm1ux7TQbN6mVZJ2pEdmgX0WFKvtx4PF4TGZmJsMwDJOTk8OMGzeOGT16NDNy5EimZ8+eTN26dZmdO3cyDMMwnz59Yjp16sQcOXKEycrKqtQ4xRESEiLQJHPgwAGB/ZmZmUzdunWFNs2VRBLPiYmJCWNra1vhcsrr4sWLAs1jCgoKzJ49exgej8cUFBQwO3bsYOTl5YvV2LRs2ZJ5//69QFnv379nunfvLlDbdOLECYnXIgnzyy+/CMR3584dqV+zqqPPztqHEqVait7shara41BQUMBkZ2czDMMwkZGRTPv27dkh2evWrRM6HF+W1qxZw36JampqFuu/Mn36dEZdXZ3JyMgQu8yKPieJiYkMAGbr1q0VKqe88vPzmVatWrGPS6NGjZinT58WO+7x48dM48aNBZq1Pn/+LLTMvLw8xs3NjVm3bl2l9hHKyspiOnbsyABgDA0N2ddmbVbVPjOI9HEYpsiCQaTWCAsLQ9u2bct3cg1a4ykjMxNqP80uXZUwDIP7KSlw+fgRV5OToSwnh9guXVBfSUnWoQEAsnk8tA8MRFRWFgBgjJ4ezhsbs/tfp6fjQ04ObHV0oCBm81BFnxPPxESMCg3FUzMzWMlgsskLiYkYGxoKANBSUEB4585oIOL5SsrLw64PH8AAWNW0KbSqyAi9orJ5PNxKToaJggJaamnJOpyKq2BTcIU+O0m1VPXelYQQFofDQR9tbfTR1kZkZiZuf/9eZZIkAFCWk8PB1q3R99UrAIVJwrWkJAyuVw8AYKquDlN19UqN6cGPH1CVk0On//XtqUwMw2BHXBx7e76BgcgkCQDqKSpie5EZsasiZTk5DNPVRUYNmN6CkPKgRImUnQw650pLXDX6dcj93z8AuH37NrhcLpo1aybLkAAAfQBMnTaNXftrXmoqQnx9of6/BCk+Ph779u3DggULoK+vX2p5FX1OfDp0QHdjYyj+91+5yyive3fv4nm/fgAAZWVlLAwIAP637Et1V53eK4RIEo16I6SaSUpKwogRI+Dk5ISq0nLu7OwMXV1dAEBcXBzWr1/P7ktNTcXWrVtx5syZSonl4sWL2LlzZ6Vc62c7duxg/542bRq7Nh4hpPqiRImQaqZevXrYuHEjrl69ikuXLsk6HACFMf3555/s7b/++gsvX74EALRp0wadOnWCh4dHpcTSqlUrmJmZVcq1igoKCsLt27cBFM5gvmzZskqPgRAieZQoEVIN/frrr+jQoQMWLlyI1NRUWYcDAJg0aRL69u0LoHBupW3btrH7Ro4cicDAQIF5gKTh9OnTOHXqlFSvIUrRWqwxY8agRRXve0QIEQ8lSoRUQwoKCjh06BDi4+Oxdu1aWYcDoLDjubOzM3v7woULiI6OBgAMGzYMAHDlyhWpxuDs7Mz2lapM7969w4ULF9jbK1asqPQYCCHSQYkSIdVUly5dsHLlSpiYmMg6FJaZmRn69+8PoLBWid8c17ZtW5iZmSEpKUlq105OTsbLly/Rq1cvqV1DlN27d7Mzk9va2sLc3LzSYyCESAeNeiOkGtu6dSv7d05ODurUqSPDaAr99ttvbF+df/75B+vXr4euri6CgoIkvtRGUY8ePQLDMJWeKH358gXHjh1jb1NtEiE1C9UoEVIDnDlzBqampvDz85N1KOjXrx/bmTorKwv79+8HADZJys3Nlcp1b9++DVVVVXTp0kUq5Yuyb98+ZGdnAwA6deoEGxubSr0+IUS6KFEipAYwMDBATk4OunXrhrVr10otGREHh8PBb7/9xt7eu3cvsv43c7etrS2mTZsmlevGxcWhT58+lVqrxjCMQOfx5cuXS7XWjBBS+ShRIqQG6NWrF169eoXJkydj8+bNsLKyQkhICAAgICAAq1evhr29PYyNjTFs2DBs3boVaWlpUotnzJgxaNq0KQAgMTERx48fBwA0btwY165dQ15ensSveeXKFfz7778SL7ckL168YDusa2pqYujQoZV6fUKI9FGiREgNoampCXd3d3h6eiIuLg5hYWEAChOlXbt2ISYmBq1atUJ4eDg2bdoEpf8treHi4oKtW7dKtKO1oqIilixZwt52dnZGQUEBhg0bhh8/fsDHx0di1yqqsvtoXbx4kf3b3t6+SvQRI4RIFiVKhNQwI0aMwNu3bzF69GgAwNSpU5GRkYHXr1/jypUriIiIQGJiIvul/v79e/z+++9o0qQJ5syZwyZYFTVjxgxoa2sDKBw+f/nyZfTv3x8qKirw8vKSyDX4HBwcsGDBAomWWRqGYQQSpVGjRlXq9QkhlYMSJUJqIE1NTfZvVVVVtvaIT6PIgrF///03Xr9+jYkTJ+L48eMwNjbGunXrKhyDuro65s6dy97euXMnVFRUYGtrCy8vL4ktv5KdnS31+ZmECQ0NRUREBABATU0NAwYMqPQYCCHSR4kSIQQmJiZwc3PDhw8fsHnzZnbk1rdv3xAZGVnuchcsWMDWXPn7++PRo0dYsGABNmzYgIKCAonE/vjxY2RmZmLgwIESKU9cRWuT7OzsoKKiUqnXJ4RUDkqUCCEsPT09/P7772yitGXLFhgbG2P+/Pn4+vVrmcvT19eHo6Mje/vYsWPo27cvpk+fDgUFyUzjdvPmTSgpKaF3794SKU9c1OxGSO1AiRIhRKSVK1dizpw5OHToEFq2bIlff/0VQUFBZSpj1qxZ7N+enp7IycnBp0+fJLZI7s2bN2FtbQ01NTWJlCeOqKgovHr1CgCgrKwMOzu7Srs2IaRyUaJECBGpQYMG2LdvH0JCQjB48GAcPHiQnUCSYRjExMSUWkanTp3YBWJTU1Nx8+ZNnDlzBhMnThTr/JIUFBRg+PDhUpubSZSitUkDBgwQ6PNFCKlZKFEihJTKyMgIZ8+eRUJCAjZu3AgACAoKQvPmzVGvXj20bNkSFhYW6NOnDx4/fixwLofDwfjx49nbZ8+eldgiufLy8ti8eTMmTJhQoXLKiprdCKk9KFEihIhNW1sbjRo1AgA0adIEzs7OGD9+PKysrGBgYIC8vDyhM1MXTZSuXLkCAwMDGBsbV3iagFevXrHLh1SW2NhYBAYGAiicL8re3r5Sr08IqVy0KC4hpFzq16+PpUuXCt338uVLXLp0CRs2bABQOKrO2NgYoaGhyMzMxLVr1zB06FA4Ozvjx48fAtMZiCsvLw89e/bE+PHjcejQoYrclTLx9PRk/+7bty+0tLQq7dqEkMpHNUqEEIm7du0aNm7ciOvXrwMobH4bN24cu//s2bOwt7dHQUEBnj17Vq5r+Pn5ITU1Fba2thKJWVzU7EZI7UKJEiFE4pYtW4a2bdti/vz5yMzMBACBROn69eto06YNPn/+XO6JGm/evAl5eXn07dtXIjGLIz4+Hk+fPgVQ2D9q+PDhlXZtQohsUKJECJE4JSUlHDx4EDExMfjjjz8AFHYINzc3BwDk5OTg6tWraNCgQbmvcePGDVhZWVVq09elS5fYGcV79eoFXV3dSrs2IUQ2KFEihEiFtbU1pk6dCmdnZ4SEhABAsdFv79+/h52dHVtLI64vX74gKCioUmfjLigowJEjR9jb1OxGSO1AnbkJIVKza9cutGjRgp1HaezYsVixYgUA4Pbt2+BwOLhz5w5MTEzQrVs3scvV1dXFs2fPYGBgIJW4hfnnn38QHBwMoHCSSUqUCKkdqEZJyry9vTFhwgR07NgR5ubmGDlyJE6fPg0ej1clyiNEmnR1dbF27Vp2HTRDQ0NYWVkBAPLz83H79m306tULV69eLVO58vLy6NKlC5o0aSLxmIVJTk7G6tWr2dsrV66sULMhIaT6oERJijZu3Ihly5bhzZs36NSpE7p164aYmBhs2rQJCxcuLPOioJIuj5DK4u3tjWHDhoHH4xVrfhsyZAjCwsLw7t07scp6+fIlZsyYgc+fP0sr3GLWrl2LpKQkAIXJ3vLlyyvt2oQQ2aJESUpu3boFDw8P6Onp4cqVKzh06BD27duH//77Dy1btsTt27dx6tQpmZVHSGVKT0/HlStXcO/ePYwZM4adlPLBgwewtLQEALFrlVxdXXH27Fm2lkragoODcfDgQfa2i4tLpV2bECJ7lChJCX8CvGXLlsHQ0JDdrqury07C5+bmJnaTmaTLI6QyjRgxAtra2jh69CgaNmyI3r17AyhcLy4gIADjx4+Hnp5eqeUkJibCw8MDU6ZMqZTRbgzDwMnJiX1f2drassuvEEJqB0qUpCAhIQEhISFQVFQUOirH0tISDRo0QGJiIts5tDLLI6SyKSsrY+LEifD09MT3798xduxYdt/169dx5swZsdZrO3z4MHJycrBgwQJphss6ffo0njx5AqBwuZI9e/YIXaKFEFJzUaIkBaGhoQCA1q1bQ1lZWegxpqamAICwsLBKL48QWZg+fTpycnJw+vRpDBo0iN3u4+ODrKwsZGRkID4+XuT5eXl52L9/P2xtbdG2bVupx5uamorffvuNvb148WIYGRlJ/bqEkKqFEiUp+PjxIwCUOHS5YcOGAsdWZnmEyIK5uTlmzJiBZs2aoVmzZmzSkZ2djUePHsHIyAgrV64UeX5mZiZGjRqFZcuWST3Wz58/Y/LkyUhISABQ+P5as2aN1K9LCKl6aB4lKeAv2VBSh081NTUAQEZGRqWXBxTOjEy1T4Vf0vQ4VB7+IrphYWHo3LkzIiIiAABnzpyBhYUFvL29sXDhQpHPydy5c9nzpSE3NxcnT57EgQMH2PcdUFibVNt/hNB7hdRWlChJAX+JA0n1ZZB0eQBQp06dSmm+qOrCwsLocahk3759w+vXr+Hg4MCO1AwMDMTatWvh7e2NiIgITJw4UeCcsLAwfPnyBb169ZJaH6GbN2/i119/RWRkpMD2mTNnYtmyZbW+bxK9VwpRslj7UNObFPBrd4r+Iv0Zv+aHf2xllkeILC1atAgjR46EpaUllJSUAABv3rxB+/btoaCggAcPHhQ7Z8uWLRg6dCjS09MlHg/DMJg/fz4GDRokkCS1bdsWt2/fhpubW61PkgipzShRkoJGjRoBQIkdU/l9H/jHVmZ5hMjStGnTkJKSgv/++w89evRgtz979gzW1tYICgpit3l5ecHX1xfnz5/HtGnToKGhIfF4Nm/ejP3797O369atCxcXF7x8+RL9+vWT+PUIIdULNb1JgbGxMQAgKioK2dnZQkeqvX79GgDEqsqWdHmEyJKNjQ2aN2+Of/75BwMGDMC9e/cAFE6qumPHDvj5+QEAkpKSMHz4cACFzc7SmBLgxIkTWLduHXt7xIgROHjwIOrXry/xaxFCqieqUZKChg0bol27dsjLy8PNmzeL7ff390dCQgL09PRgbm5e6eURIktycnKYNm0a7t27x/4IAAoXybWwsECfPn0AAJqamggKCsLRo0dx9uxZtGrVSqJx3Lt3DzNmzGBv9+vXD+fOnaMkiRAigBIlKZk9ezYAwNnZGbGxsez2pKQkbNy4EQAwa9YsyMn9/1Owe/duDBw4ELt375ZIeYRUVVOnToW8vDzi4+PZxWWTkpIEmt0UFBRgbm6OadOmCUxQKQkhISEYOXIk8vPzARTOQ/bvv/9CUVFRotchhFR/1PQmJQMHDoSDgwPOnDkDe3t7dOvWDQoKCvD19UV6ejr69euHSZMmCZyTmJiI6OhoJCYmSqQ8QqqqJk2a4OPHj9DX18fjx49x8uRJAIXNbyNHjpTqtePj4zFo0CD8+PEDQOH8ZNevX4empqZUr0sIqZ4oUZKiDRs2oGPHjjh9+jT8/f3B4/HQokULjBo1Cg4ODmWu/ZF0eYTIkr6+PoDC9dP4idJ///0n1USJYRiMHj0aHz58AACoq6vj2rVraNy4sdSuSQip3jgMf5IeUqvQnCiF6HGQneTkZEyePBnDhw9nm5YVFBTw9OlTdO7cWSrX9Pb2xtChQwEA8vLyuHbtGgYMGCCVa9U09F4pRI9D7UNVEIQQmdDS0oKfnx+ePHnCDkLIz89nR71JGsMw+OOPP9jbCxcupCSJEFIqSpQIITIhJyeH3r174/79++jfvz+7/enTp1K53n///YeAgAAAhTPTF13wlhBCRKFEiRAiM3369EFcXBxMTU3ZbY8fP5b4dX6uTZo1axa7kDQhhJSEEiVCiMzw50xKTU1ll9/58OED3r17J9HrPHjwAE+ePAEAKCoqYvny5RItnxBSc1GiRAiRGSMjI9jb20NPTw+9e/dmt9+6dUui1ylamzRt2jQ0adJEouUTQmouSpQIITLD4XBw5coVjBkzRqBj9YkTJyCpAblPnjzB/fv3ARSOdFu5cqVEyiWE1A6UKBFCZC4zMxN2dnZQUlICAPj5+Umsr1LR2qRJkyahefPmEimXEFI7UKJECJGpz58/Q0tLCzdv3oSjoyO7fefOnRUu29/fn23Gk5OTw+rVqytcJiGkdqFEiRAiU/r6+mjYsCHu37+PpUuXstuvXr2K0NDQcpfLMAw2bdrE3h43bhy4XG6FYiWE1D6UKBFCZIrD4aBPnz64f/8+uFwuOxIOKFwEurx27dqFa9eusbd///33CsVJCKmdKFEihMhcnz59kJycjFevXmHGjBns9lOnTuHTp09lLu/s2bNYsWIFe3v69Olo166dRGIlhNQulCgRQmTOxsYGAHD//n2Ym5ujW7duAIC8vDzs2bOnTGU9fPgQU6ZMYW9bW1tj//79kguWEFKrUKJECJG5xo0bY//+/Rg0aBAACEwIefDgQaSmpopVTlhYGIYNG4bc3FwAQNu2bXH58mXUqVNH8kETQmoFSpQIIVXC3Llz0aZNGwCAvb09jIyMABTO2n348OFSz09ISMCgQYOQkpICAGjQoAGuX78ObW1tqcVMCKn5KFEihFQJmZmZuHTpEj58+AA5OTksW7aM3efi4sLWEgkTFRUFW1tbxMbGAgDU1NRw7do1GBoaSjtsQkgNR4kSIaRKSEtLw8iRI9l5jyZNmgR9fX0AQHx8PFauXIm0tLRi5508eRIWFhZ4/fo1gML5ks6fP4+OHTtWXvCEkBqLEiVCSJXQoEEDtGvXDn5+fgAAZWVlLFy4kN3v4uKC5s2bY/v27UhPT0daWhomT54MR0dHpKenAyhc8Pbo0aOws7OTyX0ghNQ8lCgRQqoMGxsbBAUFIS8vDwDg5OSEzp07s/uTkpKwatUqNG/eHB06dMCpU6fYfVwuF8+ePRMY8UYIIRVFiRIhpMqwtrZGVlYWXrx4AQDQ0NDAkydPcOTIEYH+Rt++fUN0dDR7e9q0aXj+/DksLCwqO2RCSA1HiRIhpMro2bMnAODZs2fsNkVFRcyYMQMRERFwc3NDs2bN2H0aGhrw8PDA0aNHoa6uXunxEkJqPgVZB0AIIXz6+vq4efMmbG1ti+1TUlLCzJkz4ejoiDNnziAiIgKzZs1C8+bNZRApIaS2oESJEFKlNG3aFBwOR+R+JSUl6odECKk01PRGCKlSYmNjMW3aNERERMg6FEIIoUSJEFK1yMnJwd3dHffu3ZN1KIQQQokSIaRqady4MQwMDPDw4UNZh0IIIZQoEUKqFg6HA2trazx69AgMw8g6HEJILUeJEiGkyunZsyc+ffqEmJgYWYdCCKnlKFEihFQ51tbW4HK5+Pz5s6xDIYTUcjQ9ACGkyjExMaFRb4SQKoFqlAghVRb1USKEyBolSoSQKunSpUvQ09NDQkKCrEMhhNRilCgRQqokAwMDJCUl4dGjR7IOhRBSi1GiRAipkiwsLKCqqkqJEiFEpihRIoRUSYqKirCysqKJJwkhMkWJEiGkyrK2tsarV6+QkpIi61AIIbUUTQ9ACKmyBg8ejLS0NOTm5so6FEJILUWJEiGkyurYsSM6duwo6zAIIbUYJUpS9P79e+zfvx/Pnj1DSkoK9PT0YG1tjfnz56N+/fplKsvPzw+Ojo4lHnPu3DmYmZlVIGJCqp6cnByEh4ejQ4cOsg6FEFILUaIkJf7+/pg1axays7PRrl07dO7cGeHh4Th79iz+++8/eHh4oHnz5mUuV1dXFz179hS6T0dHp6JhE1LlbNy4Ebt27UJSUhLq1q0r63AIIbUMJUpSkJmZiSVLliA7Oxtr167FpEmT2H07duzA0aNHsXTpUly8eBEcDqdMZbdo0QLbt2+XdMiEVFmDBg3Ctm3bcOvWLYwZM0bW4RBCahka9SYFnp6eSExMhKWlpUCSBADLli1D06ZNERISQsOeCRGDlZUVdHR04O3tLetQCCG1ECVKUnDnzh0AwNChQ4vtk5eXh52dncBxhBDRFBQUYGdnh+vXr6OgoEDW4RBCahlqepOCsLAwAICpqanQ/fztoaGhZS7727dv2Lt3L758+QIVFRVwuVz07dsX2tra5Q+YkCrO3t4ep06dgq+vL3r06CHrcEgV4+/vj5cvX2LWrFmyDoXUQJQoSVh6ejo7OV6jRo2EHmNgYAAA+PjxY5nLf//+Pf7++2+BbZs3b8bSpUsxefLkMpdHSHUwaNAg+Pj4oGvXrrIOhVRB1tbWyMnJoUSJSAUlShKWkZHB/q2ioiL0GFVV1WLHlkZDQwNTp05F//79YWhoCBUVFcTGxsLDwwMXL17E5s2bUadOHYwdO1as8nJyctiar9osOzubHocqRtRzoqenh6ioKBlERICq/V6ZM2cO9uzZg5cvX0JJSUnW4ZAahhKln+zcuRP37t0r83nHjx9HgwYNpBBRIWNjYxgbGxfbtnnzZhgZGWHz5s3YvXs3hg8fLtYHRZ06ddC2bVtphVtthIWF0eNQxYh6TuLi4uDi4oIFCxagRYsWMoisdquq75WUlBQYGRkBAPT19aX6OQygyiaLRHooUfrJ169fER0dXebz8vLyAABqamrstqysLGhoaBQ7NjMzs9ixFTFx4kTs27cP379/x8uXL9G5c2eJlEtIVZKfn4+//voLTZs2xeLFi2UdDqkCUlJS0KRJE7bfZ3JystQTJVL7UKL0E2dnZzg7O5f7fHV1dWhpaSElJQWfPn1CmzZtih3z+fNnAKL7MJWVnJwcDA0N8f37d3z58kUiZRJS1bRo0QLGxsbw9vamRIkAAE6cOIH09HSMHj0aCQkJyMnJkXVIpAai6QGkgF89/fr1a6H7X716BQDFmtIq4vv37wD+v/8TITXR0KFD8ejRI3bABKm9GIbBwYMHYWlpiSVLluD9+/e0hBORCkqUpKBv374AIHSCvIKCAly/fh0A0L9/f4lcLzw8HDExMeBwODAxMZFImYRURfb29sjPz8fNmzdlHQqRsYcPHyIsLAy//PKLrEMhNRwlSlIwcuRI6Onpwc/PD6dPnxbY5+zsjLi4OBgbG8Pa2lpg36tXrzBw4EAMHDiwWJknTpxga42KevHiBRYuXAgAsLOzK/Niu4RUJ126dIGRkRGSk5NlHQqRsUOHDkFLSwvjxo1DVlYWbG1t4eHhIeuwSA1EfZSkQE1NDX/++SdmzZqFTZs24eLFizA0NER4eDjevXsHbW1t7N69u9g6b1lZWSI7ku/Zswc7duxAixYt0LBhQygrKyM2NhYRERFgGAYWFhbYtGlTZdw9QmRGXl4eYWFhZV4jkdQ8f/75J6ZNmwZVVVXweDzcvXsXXbp0kXVYpAaiRElKLC0tcenSJezbtw/Pnj1DZGQkdHV1MW7cODg5OZW55ueXX35BYGAg3r59i+fPnyM7Oxuampro3r07Bg8ejGHDhkFeXl5K94aQqoPD4YBhGOTm5qJOnTqyDofIiL6+PvT19QEUDmjR0tISWutOSEVRoiRFLVq0wO7du8U+vkuXLoiIiBC6b+bMmZg5c6akQiOk2iooKECHDh0wcODACo1QJdVTQUEBJk2ahNmzZ8PGxobdrqOjQ02yRCqojxIhpFqRl5dHo0aN4O3tDYZhZB0OqWQ3btzA2bNn8e3bN4HtlCgRaaFEiRBS7YwaNQqRkZF49OiRrEMhlSAjIwPHjh3DwIEDMXz4cBgYGGD48OECx5iZmaFJkyayCZDUaJQoEUKqncmTJ6N+/frYunWrrEMhlSAnJwezZ89GZGQkli9fjkePHkFRUVHgmEOHDsHNzU1GEZKajPooEUKqHRUVFSxevBirVq3CixcvYG5uLuuQiBQcOXIEXC4X1tbWCAkJQevWrWnEI6l0VKNECKmW5s6di3PnzqF9+/ayDoVIAcMwWLJkCS5cuAAA4HK5JSZJR48ehampKQoKCiorRFJLUKJECKmWNDU1MXbsWJoWo4b68OED0tLSxF5tIC0tDW/evMGPHz+kHBmpbShRIoRUa7t378aSJUtkHQaRsDdv3gCA2ImSjo4OANDINyJxlCgRQqq1Dx8+YM+ePYiJiZF1KESC+IlSu3btxDqeEiUiLZQoEUKqtWXLlkFOTo4mn6xhwsPD0ahRI2hpaYl1PCVKRFooUSKEVGuNGzfGlClTcOTIESQkJMg6HCIhR44cQWBgoNjHN2zYEH379oW6uroUoyK1ESVKhJBqb/ny5cjLy8Nff/0l61CIhMjJybFruYnD0NAQd+7cQY8ePaQYFamNKFEihFR7rVu3xvbt22Fvby/rUIgExMbGYvbs2QgNDZV1KIRQokQIqRl+++03dO/eXdZhEAkICgqCm5sbMjIyynSeubk51qxZI6WoSG1FiRIhpMZISkrCrFmzEBISIutQSAXwR7wZGxuX6bzv37/jw4cP0giJ1GK0hAkhpMZgGAb//vsv4uLicPPmTVruopp68+YNWrRoATU1tTKdp6OjQ6PeiMRRjRIhpMbQ1dXF+vXr8d9//+H69euyDoeU05s3b8SeaLIoSpSINFCiRAipUebPnw8jIyMsWbIEeXl5sg6HlBGPxwOPxyvXGn6UKBFpoKY3QkiNoqioiN27d2PIkCHYv38/fv31V1mHRMpATk4OYWFhYBimzOdaW1ujfv36UoiK1GZUo0QIqXHs7OywY8cOjBw5kt3GMAwePXqEadOmsR1+r1y5AmNjY3Tq1AmDBg1CVFSUrEImPylP/zInJyfs3btXCtGQ2owSJUJIjcPhcLB8+XI0adIE8fHx2L59O4yMjGBtbY2LFy/i5cuXAABNTU2YmJhAX18fT58+xaxZs8pVk0Ekx8XFBcOGDaPngVQZlCgRQmqsmJgYdO3aFatWrULDhg1x/PhxfP78GUOGDAEA9OrVC+fPn8fVq1exc+dO+Pj4wNPTU8ZR124+Pj6IiooqV43SmTNnoKqqitjYWClERmor6qNECKmxdHR0sHz5cgwYMACtW7cu8diZM2cCAAYPHlwZoRERQkJCYG5uXq5zlZWVkZWVhe/fv6NZs2YSjozUVlSjRAipserWrQsnJ6dSkyQAkJeXx5w5c6CsrIyCgoJKiI78LDMzE+/evSvX1ABAYWIMgEa+EYmiRIkQQooIDAwEl8uldcZkgD/ajRIlUpVQokQIIUUYGhri+/fvcHJyog7FlSwvLw/W1tblmkMJoESJSAclSoQQUoSuri62bNmC+/fv49y5c7IOp1bp2rUrfHx80KpVq3KdX69ePcycOVOsplZCxEWJEiGE/GT27NmwsLDA0qVLkZaWJutwao2K1uApKyvDzc0NNjY2EoqIEEqUCCGkGHl5eezfvx+fP3/GqVOnZB1OrdG6dWusXr26QmUwDIPs7GwJRUQITQ9ACCFCdenSBY8ePUK3bt1kHUqtkJKSgnfv3qFu3boVKsfMzAwtW7ak+bCIxFCNEiGEiNC9e3dwOBy8ffsWU6dORVZWlqxDqrFCQkIAoNwj3vi0tLSoMzeRKEqUCCGkFIGBgThx4gSGDh2KzMxMWYdTI7158wZAxRMlbW1tfP/+XRIhEQKAEiVCCCnV+PHj4e7ujrt371KyJCUhISFQV1dH06ZNK1SOjo4O1SgRiaI+SoQQIgZHR0fIycnB0dER27Ztwx9//CHrkGqUrl27QlNTE3JyFfv9TokSkTRKlAghREyTJk3C6dOn8fr1a1mHUuNMmDBBIuXY2tpCTU0NPB6vwkkXIQAlSoQQUib//vsv1NTUZB1GjfPjxw+oq6tDXl6+QuXY2trC1tZWQlERQn2UCCGkTPhJUl5enowjqVmaNGmCpUuXVric/Px8fPnyBTk5ORKIihBKlAghpMz++ecfNGrUCOnp6UL3e3h4YOfOnQgKCqL+MmLg8XhIS0uDpqZmhct68OAB9PX14e/vL4HICKFEiRBCyqxNmzZITEzExYsXi+3Lz8/HmjVrsGvXLnTs2BFHjx6VQYTVCz/hrOhkkwAtjEskjxIlKcjMzMSVK1ewZcsWjB8/Hh06dICRkRHmzJlT4bLfv3+PZcuWoUePHjAxMYGNjQ3Wr1+Pr1+/SiByQog4unXrhpYtW+L48ePF9p09exbR0dH4559/0KNHDxw6dAg8Hk8GUVYfP378AECJEqmaKFGSgtjYWPz22284ceIEXrx4IbF1h/z9/TFixAh4e3ujfv366N+/P5SVlXH27FkMGzYM0dHRErkOIaRkHA4Hjo6OuH//PmJjY9ntPB4P27Ztg6mpKYYMGYK5c+fi7du3uHfvngyjrfpSU1MBQCJNb5QoEUmjREkK1NTUMGrUKKxfvx4XLlzAxo0bK1xmZmYmlixZguzsbKxduxaenp5wcXHBjRs3MH36dCQnJ2Pp0qUVXn2bECIeR0dHAMDJkyfZbV5eXggNDcWqVasgJyeHUaNGQVdXFwcOHJBVmNWCjo4ONmzYAFNT0wqXpaGhAXl5eZqdm0gMTQ8gBU2bNsXWrVvZ22/fvq1wmZ6enkhMTISlpSUmTZoksG/ZsmW4c+cOQkJC8PDhQ/Tq1avC1yOElMzQ0BD79++HjY0Nu83AwACOjo4YO3YsAKBOnTqYNm0a3NzckJ6eDnV1dVmFW6U1bNgQ69evl0hZHA4Hu3btQqdOnSRSHiFUo1RN3LlzBwAwdOjQYvvk5eVhZ2cncBwhRPrmzp2LNm3asLe7dOmC48ePC8wFtHLlSsTGxlKSVIK0tDTEx8ejoKBAIuUtXrwYPXv2lEhZhFCiVE2EhYUBgMiqaf720NDQSouJEALcu3cPx44dw549e/Dx48di+3V0dFC3bl0wDENN4yKcO3cOjRo1Qnx8vETK+/z5s0Rq8gkBKFGqFtLT05GSkgIAaNSokdBjDAwMAEDoBzUhRHqOHTuGuXPn4tdff8W///4r9JjY2FiYm5vjypUrlRxd9cDvzC2JUW8AMHPmTIwbN04iZRHCYegnjtR5enpi1apV6N27Nw4dOlTm8798+QJra2sAhStsKygU71oWExODAQMGQFFREW/evCm1zODgYNSpU6fMsRBCSG2Wk5MDMzMzWYdBKhF15v7Jzp07yzWU9/jx42jQoIEUIpIOeqMTQgghpaNE6Sdfv34t13xE0lz3qegCnFlZWdDQ0Ch2TGZmZrFjCSGEEFIxlCj9xNnZGc7OzrIOQ4C6ujq0tLSQkpKCT58+CYyy4fv8+TMA0X2YCCGEEFJ21Jm7mmjbti0A4PXr10L3v3r1CgBgbGxcaTERQgghNR0lStVE3759AQDe3t7F9hUUFOD69esAgP79+1dqXIQQQkhNRolSFfLq1SsMHDgQAwcOLLZv5MiR0NPTg5+fH06fPi2wz9nZGXFxcTA2NmZHxxFCCCGk4mh6ACmZP38+EhMTARQuzvjhwwfUrVsXzZs3Z4+ZN28eevfuzd728/Nj14+KiIgoVqa/vz9mzZqF7OxstGvXDoaGhggPD8e7d++gra0NDw8PtGjRQrp3jBBCCKlFqDO3lISFheHTp08C21JTU/Hy5Uv2dllXt7a0tMSlS5ewb98+PHv2DJGRkdDV1cW4cePg5OSE+vXrSyT2muz9+/d4+PAhHj9+jNjYWCQkJEBJSQmtWrXCoEGDMGHCBCgpKZV4/v79+/Hs2TOkpKRAT08P1tbWmD9/Pj3+FeTt7Y0zZ84gIiICPB4PzZs3x6hRo+Dg4AA5Oar8lqS8vDwEBgbCx8cHQUFBiI+PR0pKCrS1tWFubo6JEyeiS5cuIs+n54rUJlSjRGoVa2trfPnyBXXq1IGJiQn09fXx7ds3BAcHIycnB8bGxjh27Bi0tLSKnftzjV6zZs0QHh6O9+/fQ0dHBx4eHgI1hkR8GzduhIeHB+rUqQMrKysoKCjA19cXGRkZ6N+/P1xdXQXWTyMV8/TpU0ybNg0AoKenh3bt2kFFRQXv3r1DZGQkgMIa719//bXYufRckVqHIaQWcXR0ZC5cuMCkp6cLbP/w4QMzePBghsvlMsuXLy92XkZGBtO9e3eGy+UyJ0+eFNi3fft2hsvlMiNGjGB4PJ5U46+Jbt68yXC5XKZ79+5MdHQ0uz0xMZEZNGgQw+VyGXd3d9kFWAM9ffqUWbBgARMQEFBs37Vr15i2bdsyXC6X8fX1FdhHzxWpjShRIuR/AgICGC6Xy5iamjI5OTkC+06ePMlwuVxm0qRJxc7Lz89n+vXrx3C5XObBgweVFW6NMWLECIbL5TKXLl0qts/Pz4/9Yi4oKKj84Gqp1atXM1wul1m1apXAdnquSG1EjcmE/A9/DqqcnBx2EWK+O3fuAACGDh1a7Dx5eXnY2dkJHEfEk5CQgJCQECgqKgod7WlpaYkGDRogMTERwcHBlR9gLcV/L3z58oXdRs8Vqa0oUSLkf2JjYwEAioqKxfoohYWFAQBMTU2FnsvfHhoaKr0AayD+49W6dWsoKysLPYb/2PKfAyJ9MTExAAr7L/HRc0VqK0qUCPmfw4cPAwBsbGwERr6lp6ezNUyilogxMDAAAHz8+FG6QdYw/MeL//gJ07BhQ4FjiXQlJibi0qVLAABbW1t2Oz1XpLaiRIkQAJ6enrh+/TpUVFSwePFigX0ZGRns3yoqKkLPV1VVLXYsKR1/MWdRjyvw/ws902Mrffn5+fjtt9+QlpYGKysr9OnTh91HzxWprWgeJVJt7Ny5E/fu3SvzecePH0eDBg1E7vf19cW6devA4XCwceNGmrSzEjH/m52Ew+HIOBICAOvXr4evry8aNmyIXbt2Ceyj54rUVpQokWrj69eviI6OLvN5eXl5IvcFBgZi3rx5yMvLw5o1azBs2LBix/B/JQNAVlYWNDQ0ih3D/7Vd9FhSOv7jxX/8hOHXTtBjK12bN2/Gv//+Cz09Pbi7uwv0TwLouSK1FyVKpNpwdnaGs7OzxMoLCgrC7NmzkZmZiWXLlmHy5MlCj1NXV4eWlhZSUlLw6dMntGnTptgxnz9/BiC6DxMRjv94xcfHizwmISFB4Fgiedu3b8fJkyeho6MDd3d3GBoaFjuGnitSW1EfJVIrBQcHY9asWcjIyMCiRYswa9asEo9v27YtAOD169dC97969QrA/w+rJuLhP15RUVHIzs4Wegz/Mec/B0Sydu7cyc5Gf+zYMbRq1UrocfRckdqKEiVS67x69QozZsxAeno6FixYgLlz55Z6Tt++fQEUrnH1s4KCAly/fh0A0L9/f8kGW8M1bNgQ7dq1Q15eHm7evFlsv7+/PxISEqCnpwdzc3MZRFizOTs7459//oGmpiaOHTsmtLaUj54rUltRokRqlTdv3mD69OlIT0/HvHnz4OTkJNZ5I0eOhJ6eHvz8/HD69GmBfc7OzoiLi4OxsTGsra2lEXaNNnv2bACFjyN/LisASEpKwsaNGwEAs2bNosVWJeyvv/6Cm5sb6tati6NHj4pVG0rPFamNaFFcUqtYWlrix48fqFu3LltLJMzy5cuho6MjsO3nRXENDQ0RHh6Od+/eQVtbGx4eHjRirpw2bNiAM2fOoE6dOujWrRu70Gp6ejr69euHPXv20EKrEnT37l3MmzcPAGBiYoLWrVsLPa5FixZscsRHzxWpbShRIrWKkZGRWMfdvXsXjRs3Lrb9/fv32LdvH549e4YfP35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      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "m = da_comp['cmean']\n",
    "s = da_comp['cstd']\n",
    "upper = m+s\n",
    "lower = m-s\n",
    "m.plot(lw = 3, color = 'k')\n",
    "upper.plot(ls = 'dashed', color = 'k')\n",
    "lower.plot(ls = 'dashed', color = 'k')\n",
    "plt.ylim(-1,1)\n",
    "plt.hlines(0.4,-max_lag, max_lag, color = 'gray')\n",
    "plt.hlines(0.3,-max_lag, max_lag, color = 'red')\n",
    "#plt.vlines(0,-1, 1, color = 'gray')\n",
    "#plt.ylabel(r'$\\bar{u}/u_{\\mathrm{REF}}$')\n",
    "#plt.grid(axis = 'x')\n",
    "plt.title('SSW composite at 32 km; 60°N in CMAM30')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 98,
   "id": "af820e97-8b38-4e23-9712-ce3b6a0d0a0c",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2021-06-16T12:18:44.164059Z",
     "iopub.status.busy": "2021-06-16T12:18:44.163460Z",
     "iopub.status.idle": "2021-06-16T12:18:44.226139Z",
     "shell.execute_reply": "2021-06-16T12:18:44.225376Z",
     "shell.execute_reply.started": "2021-06-16T12:18:44.163989Z"
    },
    "tags": []
   },
   "outputs": [
    {
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       "  border-bottom: solid 1px var(--xr-border-color);\n",
       "}\n",
       "\n",
       ".xr-header > div,\n",
       ".xr-header > ul {\n",
       "  display: inline;\n",
       "  margin-top: 0;\n",
       "  margin-bottom: 0;\n",
       "}\n",
       "\n",
       ".xr-obj-type,\n",
       ".xr-array-name {\n",
       "  margin-left: 2px;\n",
       "  margin-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-obj-type {\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-sections {\n",
       "  padding-left: 0 !important;\n",
       "  display: grid;\n",
       "  grid-template-columns: 150px auto auto 1fr 20px 20px;\n",
       "}\n",
       "\n",
       ".xr-section-item {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-section-item input {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-section-item input + label {\n",
       "  color: var(--xr-disabled-color);\n",
       "}\n",
       "\n",
       ".xr-section-item input:enabled + label {\n",
       "  cursor: pointer;\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-section-item input:enabled + label:hover {\n",
       "  color: var(--xr-font-color0);\n",
       "}\n",
       "\n",
       ".xr-section-summary {\n",
       "  grid-column: 1;\n",
       "  color: var(--xr-font-color2);\n",
       "  font-weight: 500;\n",
       "}\n",
       "\n",
       ".xr-section-summary > span {\n",
       "  display: inline-block;\n",
       "  padding-left: 0.5em;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:disabled + label {\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-section-summary-in + label:before {\n",
       "  display: inline-block;\n",
       "  content: '►';\n",
       "  font-size: 11px;\n",
       "  width: 15px;\n",
       "  text-align: center;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:disabled + label:before {\n",
       "  color: var(--xr-disabled-color);\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked + label:before {\n",
       "  content: '▼';\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked + label > span {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-section-summary,\n",
       ".xr-section-inline-details {\n",
       "  padding-top: 4px;\n",
       "  padding-bottom: 4px;\n",
       "}\n",
       "\n",
       ".xr-section-inline-details {\n",
       "  grid-column: 2 / -1;\n",
       "}\n",
       "\n",
       ".xr-section-details {\n",
       "  display: none;\n",
       "  grid-column: 1 / -1;\n",
       "  margin-bottom: 5px;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked ~ .xr-section-details {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-array-wrap {\n",
       "  grid-column: 1 / -1;\n",
       "  display: grid;\n",
       "  grid-template-columns: 20px auto;\n",
       "}\n",
       "\n",
       ".xr-array-wrap > label {\n",
       "  grid-column: 1;\n",
       "  vertical-align: top;\n",
       "}\n",
       "\n",
       ".xr-preview {\n",
       "  color: var(--xr-font-color3);\n",
       "}\n",
       "\n",
       ".xr-array-preview,\n",
       ".xr-array-data {\n",
       "  padding: 0 5px !important;\n",
       "  grid-column: 2;\n",
       "}\n",
       "\n",
       ".xr-array-data,\n",
       ".xr-array-in:checked ~ .xr-array-preview {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-array-in:checked ~ .xr-array-data,\n",
       ".xr-array-preview {\n",
       "  display: inline-block;\n",
       "}\n",
       "\n",
       ".xr-dim-list {\n",
       "  display: inline-block !important;\n",
       "  list-style: none;\n",
       "  padding: 0 !important;\n",
       "  margin: 0;\n",
       "}\n",
       "\n",
       ".xr-dim-list li {\n",
       "  display: inline-block;\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "}\n",
       "\n",
       ".xr-dim-list:before {\n",
       "  content: '(';\n",
       "}\n",
       "\n",
       ".xr-dim-list:after {\n",
       "  content: ')';\n",
       "}\n",
       "\n",
       ".xr-dim-list li:not(:last-child):after {\n",
       "  content: ',';\n",
       "  padding-right: 5px;\n",
       "}\n",
       "\n",
       ".xr-has-index {\n",
       "  font-weight: bold;\n",
       "}\n",
       "\n",
       ".xr-var-list,\n",
       ".xr-var-item {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-var-item > div,\n",
       ".xr-var-item label,\n",
       ".xr-var-item > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-even);\n",
       "  margin-bottom: 0;\n",
       "}\n",
       "\n",
       ".xr-var-item > .xr-var-name:hover span {\n",
       "  padding-right: 5px;\n",
       "}\n",
       "\n",
       ".xr-var-list > li:nth-child(odd) > div,\n",
       ".xr-var-list > li:nth-child(odd) > label,\n",
       ".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-odd);\n",
       "}\n",
       "\n",
       ".xr-var-name {\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-var-dims {\n",
       "  grid-column: 2;\n",
       "}\n",
       "\n",
       ".xr-var-dtype {\n",
       "  grid-column: 3;\n",
       "  text-align: right;\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-var-preview {\n",
       "  grid-column: 4;\n",
       "}\n",
       "\n",
       ".xr-var-name,\n",
       ".xr-var-dims,\n",
       ".xr-var-dtype,\n",
       ".xr-preview,\n",
       ".xr-attrs dt {\n",
       "  white-space: nowrap;\n",
       "  overflow: hidden;\n",
       "  text-overflow: ellipsis;\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-var-name:hover,\n",
       ".xr-var-dims:hover,\n",
       ".xr-var-dtype:hover,\n",
       ".xr-attrs dt:hover {\n",
       "  overflow: visible;\n",
       "  width: auto;\n",
       "  z-index: 1;\n",
       "}\n",
       "\n",
       ".xr-var-attrs,\n",
       ".xr-var-data {\n",
       "  display: none;\n",
       "  background-color: var(--xr-background-color) !important;\n",
       "  padding-bottom: 5px !important;\n",
       "}\n",
       "\n",
       ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
       ".xr-var-data-in:checked ~ .xr-var-data {\n",
       "  display: block;\n",
       "}\n",
       "\n",
       ".xr-var-data > table {\n",
       "  float: right;\n",
       "}\n",
       "\n",
       ".xr-var-name span,\n",
       ".xr-var-data,\n",
       ".xr-attrs {\n",
       "  padding-left: 25px !important;\n",
       "}\n",
       "\n",
       ".xr-attrs,\n",
       ".xr-var-attrs,\n",
       ".xr-var-data {\n",
       "  grid-column: 1 / -1;\n",
       "}\n",
       "\n",
       "dl.xr-attrs {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  display: grid;\n",
       "  grid-template-columns: 125px auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt,\n",
       ".xr-attrs dd {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  float: left;\n",
       "  padding-right: 10px;\n",
       "  width: auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt {\n",
       "  font-weight: normal;\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-attrs dt:hover span {\n",
       "  display: inline-block;\n",
       "  background: var(--xr-background-color);\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-attrs dd {\n",
       "  grid-column: 2;\n",
       "  white-space: pre-wrap;\n",
       "  word-break: break-all;\n",
       "}\n",
       "\n",
       ".xr-icon-database,\n",
       ".xr-icon-file-text2 {\n",
       "  display: inline-block;\n",
       "  vertical-align: middle;\n",
       "  width: 1em;\n",
       "  height: 1.5em !important;\n",
       "  stroke-width: 0;\n",
       "  stroke: currentColor;\n",
       "  fill: currentColor;\n",
       "}\n",
       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.DataArray &#x27;ratio&#x27; (time: 46720, height: 39)&gt;\n",
       "dask.array&lt;truediv, shape=(46720, 39), dtype=float32, chunksize=(1460, 39), chunktype=numpy.ndarray&gt;\n",
       "Coordinates:\n",
       "  * height   (height) int64 10000 11000 12000 13000 ... 45000 46000 47000 48000\n",
       "    lat      float64 61.23\n",
       "  * time     (time) object 1979-01-01 00:00:00 ... 2010-12-31 18:00:00</pre><div class='xr-wrap' hidden><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'>'ratio'</div><ul class='xr-dim-list'><li><span class='xr-has-index'>time</span>: 46720</li><li><span class='xr-has-index'>height</span>: 39</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-e2723d8b-397c-45c8-b9db-ba4901717b2f' class='xr-array-in' type='checkbox' checked><label for='section-e2723d8b-397c-45c8-b9db-ba4901717b2f' 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>dask.array&lt;chunksize=(1460, 39), meta=np.ndarray&gt;</span></div><div class='xr-array-data'><table>\n",
       "<tr>\n",
       "<td>\n",
       "<table>\n",
       "  <thead>\n",
       "    <tr><td> </td><th> Array </th><th> Chunk </th></tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr><th> Bytes </th><td> 6.95 MiB </td> <td> 222.42 kiB </td></tr>\n",
       "    <tr><th> Shape </th><td> (46720, 39) </td> <td> (1460, 39) </td></tr>\n",
       "    <tr><th> Count </th><td> 226 Tasks </td><td> 32 Chunks </td></tr>\n",
       "    <tr><th> Type </th><td> float32 </td><td> numpy.ndarray </td></tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</td>\n",
       "<td>\n",
       "<svg width=\"75\" height=\"170\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
       "\n",
       "  <!-- Horizontal lines -->\n",
       "  <line x1=\"0\" y1=\"0\" x2=\"25\" y2=\"0\" style=\"stroke-width:2\" />\n",
       "  <line x1=\"0\" y1=\"3\" x2=\"25\" y2=\"3\" />\n",
       "  <line x1=\"0\" y1=\"11\" x2=\"25\" y2=\"11\" />\n",
       "  <line x1=\"0\" y1=\"18\" x2=\"25\" y2=\"18\" />\n",
       "  <line x1=\"0\" y1=\"22\" x2=\"25\" y2=\"22\" />\n",
       "  <line x1=\"0\" y1=\"30\" x2=\"25\" y2=\"30\" />\n",
       "  <line x1=\"0\" y1=\"37\" x2=\"25\" y2=\"37\" />\n",
       "  <line x1=\"0\" y1=\"41\" x2=\"25\" y2=\"41\" />\n",
       "  <line x1=\"0\" y1=\"48\" x2=\"25\" y2=\"48\" />\n",
       "  <line x1=\"0\" y1=\"56\" x2=\"25\" y2=\"56\" />\n",
       "  <line x1=\"0\" y1=\"60\" x2=\"25\" y2=\"60\" />\n",
       "  <line x1=\"0\" y1=\"67\" x2=\"25\" y2=\"67\" />\n",
       "  <line x1=\"0\" y1=\"75\" x2=\"25\" y2=\"75\" />\n",
       "  <line x1=\"0\" y1=\"78\" x2=\"25\" y2=\"78\" />\n",
       "  <line x1=\"0\" y1=\"86\" x2=\"25\" y2=\"86\" />\n",
       "  <line x1=\"0\" y1=\"93\" x2=\"25\" y2=\"93\" />\n",
       "  <line x1=\"0\" y1=\"97\" x2=\"25\" y2=\"97\" />\n",
       "  <line x1=\"0\" y1=\"105\" x2=\"25\" y2=\"105\" />\n",
       "  <line x1=\"0\" y1=\"112\" x2=\"25\" y2=\"112\" />\n",
       "  <line x1=\"0\" y1=\"120\" x2=\"25\" y2=\"120\" style=\"stroke-width:2\" />\n",
       "\n",
       "  <!-- Vertical lines -->\n",
       "  <line x1=\"0\" y1=\"0\" x2=\"0\" y2=\"120\" style=\"stroke-width:2\" />\n",
       "  <line x1=\"25\" y1=\"0\" x2=\"25\" y2=\"120\" style=\"stroke-width:2\" />\n",
       "\n",
       "  <!-- Colored Rectangle -->\n",
       "  <polygon points=\"0.0,0.0 25.412616514582485,0.0 25.412616514582485,120.0 0.0,120.0\" style=\"fill:#8B4903A0;stroke-width:0\"/>\n",
       "\n",
       "  <!-- Text -->\n",
       "  <text x=\"12.706308\" y=\"140.000000\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >39</text>\n",
       "  <text x=\"45.412617\" y=\"60.000000\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(-90,45.412617,60.000000)\">46720</text>\n",
       "</svg>\n",
       "</td>\n",
       "</tr>\n",
       "</table></div></div></li><li class='xr-section-item'><input id='section-f5ee68d7-5b9e-4dbb-9de4-d6077c6a38ba' class='xr-section-summary-in' type='checkbox'  checked><label for='section-f5ee68d7-5b9e-4dbb-9de4-d6077c6a38ba' 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'>height</span></div><div class='xr-var-dims'>(height)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>10000 11000 12000 ... 47000 48000</div><input id='attrs-3e053df3-4a9b-49eb-b688-9a18eb29ca84' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-3e053df3-4a9b-49eb-b688-9a18eb29ca84' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-db955278-c615-42c6-bf2b-ac62ca960733' class='xr-var-data-in' type='checkbox'><label for='data-db955278-c615-42c6-bf2b-ac62ca960733' 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([10000, 11000, 12000, 13000, 14000, 15000, 16000, 17000, 18000, 19000,\n",
       "       20000, 21000, 22000, 23000, 24000, 25000, 26000, 27000, 28000, 29000,\n",
       "       30000, 31000, 32000, 33000, 34000, 35000, 36000, 37000, 38000, 39000,\n",
       "       40000, 41000, 42000, 43000, 44000, 45000, 46000, 47000, 48000])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lat</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>61.23</div><input id='attrs-298673ac-a46e-4092-998a-a92134e3d984' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-298673ac-a46e-4092-998a-a92134e3d984' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-43413f4a-2eb6-4bc4-bd6d-4b8f4c0a6607' class='xr-var-data-in' type='checkbox'><label for='data-43413f4a-2eb6-4bc4-bd6d-4b8f4c0a6607' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>axis :</span></dt><dd>Y</dd><dt><span>bounds :</span></dt><dd>lat_bnds</dd><dt><span>long_name :</span></dt><dd>latitude</dd><dt><span>standard_name :</span></dt><dd>latitude</dd><dt><span>units :</span></dt><dd>degrees_north</dd></dl></div><div class='xr-var-data'><pre>array(61.23157309)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>1979-01-01 00:00:00 ... 2010-12-...</div><input id='attrs-5e72d0c3-d44c-486f-9107-8e3c87569678' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-5e72d0c3-d44c-486f-9107-8e3c87569678' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3fce950a-e436-4f21-93ac-6819703d3c69' class='xr-var-data-in' type='checkbox'><label for='data-3fce950a-e436-4f21-93ac-6819703d3c69' 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>bounds :</span></dt><dd>time_bnds</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([cftime.DatetimeNoLeap(1979, 1, 1, 0, 0, 0, 0, has_year_zero=True),\n",
       "       cftime.DatetimeNoLeap(1979, 1, 1, 6, 0, 0, 0, has_year_zero=True),\n",
       "       cftime.DatetimeNoLeap(1979, 1, 1, 12, 0, 0, 0, has_year_zero=True), ...,\n",
       "       cftime.DatetimeNoLeap(2010, 12, 31, 6, 0, 0, 0, has_year_zero=True),\n",
       "       cftime.DatetimeNoLeap(2010, 12, 31, 12, 0, 0, 0, has_year_zero=True),\n",
       "       cftime.DatetimeNoLeap(2010, 12, 31, 18, 0, 0, 0, has_year_zero=True)],\n",
       "      dtype=object)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-e22cc1af-027f-4c6b-ae8e-63fe2b06fda6' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-e22cc1af-027f-4c6b-ae8e-63fe2b06fda6' class='xr-section-summary'  title='Expand/collapse section'>Attributes: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.DataArray 'ratio' (time: 46720, height: 39)>\n",
       "dask.array<truediv, shape=(46720, 39), dtype=float32, chunksize=(1460, 39), chunktype=numpy.ndarray>\n",
       "Coordinates:\n",
       "  * height   (height) int64 10000 11000 12000 13000 ... 45000 46000 47000 48000\n",
       "    lat      float64 61.23\n",
       "  * time     (time) object 1979-01-01 00:00:00 ... 2010-12-31 18:00:00"
      ]
     },
     "execution_count": 98,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sel_dict = dict(lat = 60, method = 'nearest')\n",
    "uref_60 = ds['uref'].sel(**sel_dict)\n",
    "ratio = ds['ua_int'].sel(**sel_dict).mean('lon')/uref_60\n",
    "ratio.name = 'ratio'\n",
    "ratio"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 99,
   "id": "d37634e0-c1c1-4ff9-94b0-e3fa7a928105",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2021-06-16T12:18:46.156182Z",
     "iopub.status.busy": "2021-06-16T12:18:46.155416Z",
     "iopub.status.idle": "2021-06-16T12:18:46.167538Z",
     "shell.execute_reply": "2021-06-16T12:18:46.166184Z",
     "shell.execute_reply.started": "2021-06-16T12:18:46.156111Z"
    },
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "7.28832"
      ]
     },
     "execution_count": 99,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ratio.nbytes/1e6"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 100,
   "id": "16aeb7bc-2229-4efe-a029-b1b320a861a1",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2021-06-16T12:19:34.258632Z",
     "iopub.status.busy": "2021-06-16T12:19:34.257726Z",
     "iopub.status.idle": "2021-06-16T12:19:40.626602Z",
     "shell.execute_reply": "2021-06-16T12:19:40.625278Z",
     "shell.execute_reply.started": "2021-06-16T12:19:34.258544Z"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "inpath = '/mnt/data02/model/CMAM/0A.daily/'\n",
    "outfile = os.path.join(inpath, \n",
    "                       f\"ratio_6hrlogH_CMAM_CMAM30-SD_r1i1p1_19790101-20101231.nc\")\n",
    "ratio.to_netcdf(outfile)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 102,
   "id": "0687a9a2-eeeb-4463-91cc-954abfba25cd",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2021-06-16T12:26:48.759145Z",
     "iopub.status.busy": "2021-06-16T12:26:48.758409Z",
     "iopub.status.idle": "2021-06-16T12:29:09.789517Z",
     "shell.execute_reply": "2021-06-16T12:29:09.787960Z",
     "shell.execute_reply.started": "2021-06-16T12:26:48.759070Z"
    },
    "tags": []
   },
   "outputs": [],
   "source": [
    "inpath = '/mnt/data02/model/CMAM/0A.daily/'\n",
    "outfile = os.path.join(inpath, \n",
    "                       f\"ratio_DailylogH_CMAM_CMAM30-SD_r1i1p1_19790101-20101231.nc\")\n",
    "ratio.resample(time = '1D').mean().to_netcdf(outfile)"
   ]
  }
 ],
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