Using the ERA5 O3 data in the WRF initial condition

era5_to_wrf.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Because of the COVID-19, [CAM-chem](https://www.acom.ucar.edu/cam-chem/cam-chem.shtml) output files aren't available after June 2019.\n",
    "\n",
    "I compared the [WACCM](https://www.acom.ucar.edu/waccm/download.shtml) output file and [ERA5 reanalysis](https://cds.climate.copernicus.eu/cdsapp#!/dataset/reanalysis-era5-pressure-levels?tab=overview) pressure level data and found that the upper tropospheric ozone is better for the ERA5 data.\n",
    "\n",
    "As a result, I decided to directly replace the O3 variable in `wrfinput*` files by that of the ERA5 data.\n",
    "\n",
    "Here're the steps:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import xarray as xr\n",
    "import proplot as plot\n",
    "from netCDF4 import Dataset\n",
    "from wrf import getvar, ll_to_xy\n",
    "import scipy.interpolate as interp"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Read data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "# read wrfinput file\n",
    "ncfile = Dataset('./wrfinput/20200901/mozbc/wrfinput_d01', 'r+') # for modification\n",
    "ds_wrf = xr.open_dataset('./wrfinput/20200901/mozbc/wrfinput_d01') # for reading data\n",
    "# calculate the pressure levels (hPa)\n",
    "p_wrf = (ds_wrf['P']+ds_wrf['PB']).isel(Time=0)/1e2\n",
    "p_wrf.attrs['units'] = 'hPa'\n",
    "# convert to ppbv\n",
    "o3 = ds_wrf['o3']*1e3\n",
    "\n",
    "# read era5 data\n",
    "ds_era5 = xr.open_dataset('./era5/era5_20200901.nc')\n",
    "era5_o3 = ds_era5['o3']*28.9644/47.9982*1e9"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Correct the ERA5 data manually (optional)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "I correct the ERA5 data based on the ozonesonde data:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "# correct the ERA5 data manually\n",
    "era5_o3 = xr.where((era5_o3.level<=500) & (era5_o3.level>=100) & (era5_o3-20>10), era5_o3-20, era5_o3)\n",
    "era5_o3 = xr.where((era5_o3.level<=700) & (era5_o3.level>500) & (era5_o3-10>10), era5_o3-10, era5_o3)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Interpolation"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Interpolating era5 data to wrf grids (lon/lat)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "era5_o3_interp = era5_o3.interp(longitude=o3.XLONG.isel(Time=0), latitude=o3.XLAT.isel(Time=0))\n",
    "\n",
    "## expand 1d to 3d\n",
    "p_era5 = era5_o3_interp.level.expand_dims(['south_north', 'west_east'])\n",
    "p_era5 = np.repeat(p_era5, repeats=o3.sizes['south_north'], axis=0)\n",
    "p_era5 = np.repeat(p_era5, repeats=o3.sizes['west_east'], axis=1)\n",
    "p_era5.attrs['units'] = 'hPa'"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Check the result of interpolation:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 808.333x316.528 with 6 Axes>"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 318,
       "width": 742
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "f, axs = plot.subplots(ncols=2, share=0)\n",
    "\n",
    "ax = axs[0]\n",
    "m = ax.pcolormesh(era5_o3.longitude,\n",
    "                  era5_o3.latitude,\n",
    "                  era5_o3.isel(time=0, level=-1),\n",
    "                  cmap='viridis')\n",
    "ax.colorbar(m, label='O$_3$ (ppbv)', loc='r')\n",
    "ax.format(title='Original')\n",
    "\n",
    "ax = axs[1]\n",
    "m = ax.pcolormesh(era5_o3_interp.longitude,\n",
    "                  era5_o3_interp.latitude,\n",
    "                  era5_o3_interp.isel(time=0, level=-1),\n",
    "                  cmap='viridis')\n",
    "ax.format(title='Interpolated')\n",
    "ax.colorbar(m, label='O$_3$ (ppbv)', loc='r')\n",
    "\n",
    "axs.format(xlim=(o3.XLONG.min(), o3.XLONG.max()),\n",
    "           ylim=(o3.XLAT.min(), o3.XLAT.max()),\n",
    "           xlabel='longitude',\n",
    "           ylabel='latitude',)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Interpolating to WRF pressure levels"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Define the interpolation function used by `xr.apply_ufunc`:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "def interp1d_np(data, x, xi):\n",
    "    from scipy import interpolate\n",
    "    f = interpolate.interp1d(x, data, fill_value='extrapolate')\n",
    "    return f(xi)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Display the structue of each DataArray:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
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       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.DataArray (level: 37, time: 72, latitude: 201, longitude: 281)&gt;\n",
       "array([[[[2436.0215  , 2437.7124  , 2438.7883  , ..., 2450.778   ,\n",
       "          2450.9316  , 2451.239   ],\n",
       "         [2441.5552  , 2442.631   , 2443.246   , ..., 2456.158   ,\n",
       "          2456.4653  , 2456.7725  ],\n",
       "         [2446.0127  , 2447.0886  , 2447.0886  , ..., 2461.845   ,\n",
       "          2462.1526  , 2462.4602  ],\n",
       "         ...,\n",
       "         [3067.625   , 3057.7874  , 3049.026   , ..., 3244.2405  ,\n",
       "          3248.083   , 3255.9224  ],\n",
       "         [3072.2366  , 3061.4768  , 3051.7925  , ..., 3257.9207  ,\n",
       "          3262.9932  , 3269.449   ],\n",
       "         [3075.7715  , 3064.397   , 3053.176   , ..., 3273.599   ,\n",
       "          3278.3643  , 3284.8203  ]],\n",
       "\n",
       "        [[2427.26    , 2429.2583  , 2431.2563  , ..., 2447.8574  ,\n",
       "          2447.8574  , 2448.0112  ],\n",
       "         [2431.8713  , 2433.716   , 2435.5603  , ..., 2451.3926  ,\n",
       "          2451.3926  , 2451.3926  ],\n",
       "         [2436.9438  , 2438.9421  , 2440.6328  , ..., 2454.7744  ,\n",
       "          2454.467   , 2454.3132  ],\n",
       "...\n",
       "         [  26.428476,   26.428476,   26.428476, ...,   26.890043,\n",
       "            26.890043,   26.736372],\n",
       "         [  26.428476,   26.428476,   26.274803, ...,   27.043716,\n",
       "            27.043716,   27.043716],\n",
       "         [  26.428476,   26.428476,   26.274803, ...,   27.19739 ,\n",
       "            27.19739 ,   27.19739 ]],\n",
       "\n",
       "        [[  35.34426 ,   35.34426 ,   35.34426 , ...,   44.720516,\n",
       "            44.720516,   44.720516],\n",
       "         [  35.49793 ,   35.651604,   35.651604, ...,   44.720516,\n",
       "            44.720516,   44.566837],\n",
       "         [  35.80528 ,   35.95895 ,   35.80528 , ...,   44.720516,\n",
       "            44.566837,   44.25949 ],\n",
       "         ...,\n",
       "         [  26.428476,   26.428476,   26.428476, ...,   26.736372,\n",
       "            26.582697,   26.428476],\n",
       "         [  26.428476,   26.428476,   26.274803, ...,   26.890043,\n",
       "            26.890043,   26.890043],\n",
       "         [  26.428476,   26.428476,   26.274803, ...,   27.043716,\n",
       "            27.043716,   27.043716]]]], dtype=float32)\n",
       "Coordinates:\n",
       "  * level      (level) int32 1 2 3 5 7 10 20 30 ... 850 875 900 925 950 975 1000\n",
       "  * longitude  (longitude) float32 90.0 90.25 90.5 90.75 ... 159.5 159.75 160.0\n",
       "  * latitude   (latitude) float32 60.0 59.75 59.5 59.25 ... 10.5 10.25 10.0\n",
       "  * time       (time) datetime64[ns] 2020-08-01 ... 2020-09-01T23:00:00</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'>level</span>: 37</li><li><span class='xr-has-index'>time</span>: 72</li><li><span class='xr-has-index'>latitude</span>: 201</li><li><span class='xr-has-index'>longitude</span>: 281</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-720b4fc7-4be9-4553-b11f-df593c18099b' class='xr-array-in' type='checkbox' checked><label for='section-720b4fc7-4be9-4553-b11f-df593c18099b' 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>2436.0215 2437.7124 2438.7883 ... 27.043716 27.043716 27.043716</span></div><div class='xr-array-data'><pre>array([[[[2436.0215  , 2437.7124  , 2438.7883  , ..., 2450.778   ,\n",
       "          2450.9316  , 2451.239   ],\n",
       "         [2441.5552  , 2442.631   , 2443.246   , ..., 2456.158   ,\n",
       "          2456.4653  , 2456.7725  ],\n",
       "         [2446.0127  , 2447.0886  , 2447.0886  , ..., 2461.845   ,\n",
       "          2462.1526  , 2462.4602  ],\n",
       "         ...,\n",
       "         [3067.625   , 3057.7874  , 3049.026   , ..., 3244.2405  ,\n",
       "          3248.083   , 3255.9224  ],\n",
       "         [3072.2366  , 3061.4768  , 3051.7925  , ..., 3257.9207  ,\n",
       "          3262.9932  , 3269.449   ],\n",
       "         [3075.7715  , 3064.397   , 3053.176   , ..., 3273.599   ,\n",
       "          3278.3643  , 3284.8203  ]],\n",
       "\n",
       "        [[2427.26    , 2429.2583  , 2431.2563  , ..., 2447.8574  ,\n",
       "          2447.8574  , 2448.0112  ],\n",
       "         [2431.8713  , 2433.716   , 2435.5603  , ..., 2451.3926  ,\n",
       "          2451.3926  , 2451.3926  ],\n",
       "         [2436.9438  , 2438.9421  , 2440.6328  , ..., 2454.7744  ,\n",
       "          2454.467   , 2454.3132  ],\n",
       "...\n",
       "         [  26.428476,   26.428476,   26.428476, ...,   26.890043,\n",
       "            26.890043,   26.736372],\n",
       "         [  26.428476,   26.428476,   26.274803, ...,   27.043716,\n",
       "            27.043716,   27.043716],\n",
       "         [  26.428476,   26.428476,   26.274803, ...,   27.19739 ,\n",
       "            27.19739 ,   27.19739 ]],\n",
       "\n",
       "        [[  35.34426 ,   35.34426 ,   35.34426 , ...,   44.720516,\n",
       "            44.720516,   44.720516],\n",
       "         [  35.49793 ,   35.651604,   35.651604, ...,   44.720516,\n",
       "            44.720516,   44.566837],\n",
       "         [  35.80528 ,   35.95895 ,   35.80528 , ...,   44.720516,\n",
       "            44.566837,   44.25949 ],\n",
       "         ...,\n",
       "         [  26.428476,   26.428476,   26.428476, ...,   26.736372,\n",
       "            26.582697,   26.428476],\n",
       "         [  26.428476,   26.428476,   26.274803, ...,   26.890043,\n",
       "            26.890043,   26.890043],\n",
       "         [  26.428476,   26.428476,   26.274803, ...,   27.043716,\n",
       "            27.043716,   27.043716]]]], dtype=float32)</pre></div></div></li><li class='xr-section-item'><input id='section-9cb4bc94-0f16-4f68-bfa9-441289071662' class='xr-section-summary-in' type='checkbox'  checked><label for='section-9cb4bc94-0f16-4f68-bfa9-441289071662' 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'>level</span></div><div class='xr-var-dims'>(level)</div><div class='xr-var-dtype'>int32</div><div class='xr-var-preview xr-preview'>1 2 3 5 7 ... 900 925 950 975 1000</div><input id='attrs-b5ab0ded-6f6f-427f-8174-9f358060f7e4' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b5ab0ded-6f6f-427f-8174-9f358060f7e4' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-393e4d38-b5ed-4ea5-8734-8d7f161f7958' class='xr-var-data-in' type='checkbox'><label for='data-393e4d38-b5ed-4ea5-8734-8d7f161f7958' 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>millibars</dd><dt><span>long_name :</span></dt><dd>pressure_level</dd></dl></div><div class='xr-var-data'><pre>array([   1,    2,    3,    5,    7,   10,   20,   30,   50,   70,  100,  125,\n",
       "        150,  175,  200,  225,  250,  300,  350,  400,  450,  500,  550,  600,\n",
       "        650,  700,  750,  775,  800,  825,  850,  875,  900,  925,  950,  975,\n",
       "       1000], dtype=int32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>longitude</span></div><div class='xr-var-dims'>(longitude)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>90.0 90.25 90.5 ... 159.75 160.0</div><input id='attrs-377b82e6-07d0-4a36-8395-c01eee3ce5f4' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-377b82e6-07d0-4a36-8395-c01eee3ce5f4' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-98b65de9-f196-4165-932a-4c6279ae6beb' class='xr-var-data-in' type='checkbox'><label for='data-98b65de9-f196-4165-932a-4c6279ae6beb' 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>degrees_east</dd><dt><span>long_name :</span></dt><dd>longitude</dd></dl></div><div class='xr-var-data'><pre>array([ 90.  ,  90.25,  90.5 , ..., 159.5 , 159.75, 160.  ], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>latitude</span></div><div class='xr-var-dims'>(latitude)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>60.0 59.75 59.5 ... 10.5 10.25 10.0</div><input id='attrs-68618649-6582-4e64-8b36-0c9864fcfae3' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-68618649-6582-4e64-8b36-0c9864fcfae3' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f9bfacc1-e012-4126-9b4a-09b89847ecea' class='xr-var-data-in' type='checkbox'><label for='data-f9bfacc1-e012-4126-9b4a-09b89847ecea' 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>degrees_north</dd><dt><span>long_name :</span></dt><dd>latitude</dd></dl></div><div class='xr-var-data'><pre>array([60.  , 59.75, 59.5 , ..., 10.5 , 10.25, 10.  ], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2020-08-01 ... 2020-09-01T23:00:00</div><input id='attrs-433e7c6c-75c5-4c78-816f-6b3f3ec9ff1a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-433e7c6c-75c5-4c78-816f-6b3f3ec9ff1a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-150c09d5-77da-48f2-bff4-fe0d1a07cae9' class='xr-var-data-in' type='checkbox'><label for='data-150c09d5-77da-48f2-bff4-fe0d1a07cae9' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>time</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;2020-08-01T00:00:00.000000000&#x27;, &#x27;2020-08-01T01:00:00.000000000&#x27;,\n",
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       "       &#x27;2020-08-01T14:00:00.000000000&#x27;, &#x27;2020-08-01T15:00:00.000000000&#x27;,\n",
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       "       &#x27;2020-08-31T16:00:00.000000000&#x27;, &#x27;2020-08-31T17:00:00.000000000&#x27;,\n",
       "       &#x27;2020-08-31T18:00:00.000000000&#x27;, &#x27;2020-08-31T19:00:00.000000000&#x27;,\n",
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       "       &#x27;2020-09-01T18:00:00.000000000&#x27;, &#x27;2020-09-01T19:00:00.000000000&#x27;,\n",
       "       &#x27;2020-09-01T20:00:00.000000000&#x27;, &#x27;2020-09-01T21:00:00.000000000&#x27;,\n",
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       "      dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-16b1a21e-f7c1-45d3-bbcc-39ebdd29a03f' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-16b1a21e-f7c1-45d3-bbcc-39ebdd29a03f' 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>"
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       "\n",
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       "\n",
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       ".xr-var-dtype:hover,\n",
       ".xr-attrs dt:hover {\n",
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       "\n",
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       "\n",
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       "\n",
       ".xr-attrs dt {\n",
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       "\n",
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       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.DataArray &#x27;level&#x27; (south_north: 119, west_east: 119, level: 37)&gt;\n",
       "array([[[   1,    2,    3, ...,  950,  975, 1000],\n",
       "        [   1,    2,    3, ...,  950,  975, 1000],\n",
       "        [   1,    2,    3, ...,  950,  975, 1000],\n",
       "        ...,\n",
       "        [   1,    2,    3, ...,  950,  975, 1000],\n",
       "        [   1,    2,    3, ...,  950,  975, 1000],\n",
       "        [   1,    2,    3, ...,  950,  975, 1000]],\n",
       "\n",
       "       [[   1,    2,    3, ...,  950,  975, 1000],\n",
       "        [   1,    2,    3, ...,  950,  975, 1000],\n",
       "        [   1,    2,    3, ...,  950,  975, 1000],\n",
       "        ...,\n",
       "        [   1,    2,    3, ...,  950,  975, 1000],\n",
       "        [   1,    2,    3, ...,  950,  975, 1000],\n",
       "        [   1,    2,    3, ...,  950,  975, 1000]],\n",
       "\n",
       "       [[   1,    2,    3, ...,  950,  975, 1000],\n",
       "        [   1,    2,    3, ...,  950,  975, 1000],\n",
       "        [   1,    2,    3, ...,  950,  975, 1000],\n",
       "        ...,\n",
       "...\n",
       "        ...,\n",
       "        [   1,    2,    3, ...,  950,  975, 1000],\n",
       "        [   1,    2,    3, ...,  950,  975, 1000],\n",
       "        [   1,    2,    3, ...,  950,  975, 1000]],\n",
       "\n",
       "       [[   1,    2,    3, ...,  950,  975, 1000],\n",
       "        [   1,    2,    3, ...,  950,  975, 1000],\n",
       "        [   1,    2,    3, ...,  950,  975, 1000],\n",
       "        ...,\n",
       "        [   1,    2,    3, ...,  950,  975, 1000],\n",
       "        [   1,    2,    3, ...,  950,  975, 1000],\n",
       "        [   1,    2,    3, ...,  950,  975, 1000]],\n",
       "\n",
       "       [[   1,    2,    3, ...,  950,  975, 1000],\n",
       "        [   1,    2,    3, ...,  950,  975, 1000],\n",
       "        [   1,    2,    3, ...,  950,  975, 1000],\n",
       "        ...,\n",
       "        [   1,    2,    3, ...,  950,  975, 1000],\n",
       "        [   1,    2,    3, ...,  950,  975, 1000],\n",
       "        [   1,    2,    3, ...,  950,  975, 1000]]], dtype=int32)\n",
       "Coordinates:\n",
       "  * level    (level) int32 1 2 3 5 7 10 20 30 ... 850 875 900 925 950 975 1000\n",
       "Dimensions without coordinates: south_north, west_east\n",
       "Attributes:\n",
       "    units:    hPa</pre><div class='xr-wrap' hidden><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'>'level'</div><ul class='xr-dim-list'><li><span>south_north</span>: 119</li><li><span>west_east</span>: 119</li><li><span class='xr-has-index'>level</span>: 37</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-bc5ccd20-6320-411f-99e6-c1b2a90db2bb' class='xr-array-in' type='checkbox' checked><label for='section-bc5ccd20-6320-411f-99e6-c1b2a90db2bb' 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>1 2 3 5 7 10 20 30 50 70 ... 775 800 825 850 875 900 925 950 975 1000</span></div><div class='xr-array-data'><pre>array([[[   1,    2,    3, ...,  950,  975, 1000],\n",
       "        [   1,    2,    3, ...,  950,  975, 1000],\n",
       "        [   1,    2,    3, ...,  950,  975, 1000],\n",
       "        ...,\n",
       "        [   1,    2,    3, ...,  950,  975, 1000],\n",
       "        [   1,    2,    3, ...,  950,  975, 1000],\n",
       "        [   1,    2,    3, ...,  950,  975, 1000]],\n",
       "\n",
       "       [[   1,    2,    3, ...,  950,  975, 1000],\n",
       "        [   1,    2,    3, ...,  950,  975, 1000],\n",
       "        [   1,    2,    3, ...,  950,  975, 1000],\n",
       "        ...,\n",
       "        [   1,    2,    3, ...,  950,  975, 1000],\n",
       "        [   1,    2,    3, ...,  950,  975, 1000],\n",
       "        [   1,    2,    3, ...,  950,  975, 1000]],\n",
       "\n",
       "       [[   1,    2,    3, ...,  950,  975, 1000],\n",
       "        [   1,    2,    3, ...,  950,  975, 1000],\n",
       "        [   1,    2,    3, ...,  950,  975, 1000],\n",
       "        ...,\n",
       "...\n",
       "        ...,\n",
       "        [   1,    2,    3, ...,  950,  975, 1000],\n",
       "        [   1,    2,    3, ...,  950,  975, 1000],\n",
       "        [   1,    2,    3, ...,  950,  975, 1000]],\n",
       "\n",
       "       [[   1,    2,    3, ...,  950,  975, 1000],\n",
       "        [   1,    2,    3, ...,  950,  975, 1000],\n",
       "        [   1,    2,    3, ...,  950,  975, 1000],\n",
       "        ...,\n",
       "        [   1,    2,    3, ...,  950,  975, 1000],\n",
       "        [   1,    2,    3, ...,  950,  975, 1000],\n",
       "        [   1,    2,    3, ...,  950,  975, 1000]],\n",
       "\n",
       "       [[   1,    2,    3, ...,  950,  975, 1000],\n",
       "        [   1,    2,    3, ...,  950,  975, 1000],\n",
       "        [   1,    2,    3, ...,  950,  975, 1000],\n",
       "        ...,\n",
       "        [   1,    2,    3, ...,  950,  975, 1000],\n",
       "        [   1,    2,    3, ...,  950,  975, 1000],\n",
       "        [   1,    2,    3, ...,  950,  975, 1000]]], dtype=int32)</pre></div></div></li><li class='xr-section-item'><input id='section-16efa49a-06a2-417b-bd6d-191e23a67e60' class='xr-section-summary-in' type='checkbox'  checked><label for='section-16efa49a-06a2-417b-bd6d-191e23a67e60' class='xr-section-summary' >Coordinates: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>level</span></div><div class='xr-var-dims'>(level)</div><div class='xr-var-dtype'>int32</div><div class='xr-var-preview xr-preview'>1 2 3 5 7 ... 900 925 950 975 1000</div><input id='attrs-7e1cd1d0-3f1a-47d4-8945-084a561cc686' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-7e1cd1d0-3f1a-47d4-8945-084a561cc686' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-65d9d8aa-0e9d-4e23-bfb9-0b93ca4242b1' class='xr-var-data-in' type='checkbox'><label for='data-65d9d8aa-0e9d-4e23-bfb9-0b93ca4242b1' 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>millibars</dd><dt><span>long_name :</span></dt><dd>pressure_level</dd></dl></div><div class='xr-var-data'><pre>array([   1,    2,    3,    5,    7,   10,   20,   30,   50,   70,  100,  125,\n",
       "        150,  175,  200,  225,  250,  300,  350,  400,  450,  500,  550,  600,\n",
       "        650,  700,  750,  775,  800,  825,  850,  875,  900,  925,  950,  975,\n",
       "       1000], dtype=int32)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-bfcf0acb-8de9-4a8d-bfc5-e48d51cd8e6d' class='xr-section-summary-in' type='checkbox'  checked><label for='section-bfcf0acb-8de9-4a8d-bfc5-e48d51cd8e6d' class='xr-section-summary' >Attributes: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>hPa</dd></dl></div></li></ul></div></div>"
      ],
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       "        ...,\n",
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       "        [   1,    2,    3, ...,  950,  975, 1000],\n",
       "        [   1,    2,    3, ...,  950,  975, 1000]],\n",
       "\n",
       "       [[   1,    2,    3, ...,  950,  975, 1000],\n",
       "        [   1,    2,    3, ...,  950,  975, 1000],\n",
       "        [   1,    2,    3, ...,  950,  975, 1000],\n",
       "        ...,\n",
       "        [   1,    2,    3, ...,  950,  975, 1000],\n",
       "        [   1,    2,    3, ...,  950,  975, 1000],\n",
       "        [   1,    2,    3, ...,  950,  975, 1000]],\n",
       "\n",
       "       [[   1,    2,    3, ...,  950,  975, 1000],\n",
       "        [   1,    2,    3, ...,  950,  975, 1000],\n",
       "        [   1,    2,    3, ...,  950,  975, 1000],\n",
       "        ...,\n",
       "...\n",
       "        ...,\n",
       "        [   1,    2,    3, ...,  950,  975, 1000],\n",
       "        [   1,    2,    3, ...,  950,  975, 1000],\n",
       "        [   1,    2,    3, ...,  950,  975, 1000]],\n",
       "\n",
       "       [[   1,    2,    3, ...,  950,  975, 1000],\n",
       "        [   1,    2,    3, ...,  950,  975, 1000],\n",
       "        [   1,    2,    3, ...,  950,  975, 1000],\n",
       "        ...,\n",
       "        [   1,    2,    3, ...,  950,  975, 1000],\n",
       "        [   1,    2,    3, ...,  950,  975, 1000],\n",
       "        [   1,    2,    3, ...,  950,  975, 1000]],\n",
       "\n",
       "       [[   1,    2,    3, ...,  950,  975, 1000],\n",
       "        [   1,    2,    3, ...,  950,  975, 1000],\n",
       "        [   1,    2,    3, ...,  950,  975, 1000],\n",
       "        ...,\n",
       "        [   1,    2,    3, ...,  950,  975, 1000],\n",
       "        [   1,    2,    3, ...,  950,  975, 1000],\n",
       "        [   1,    2,    3, ...,  950,  975, 1000]]], dtype=int32)\n",
       "Coordinates:\n",
       "  * level    (level) int32 1 2 3 5 7 10 20 30 ... 850 875 900 925 950 975 1000\n",
       "Dimensions without coordinates: south_north, west_east\n",
       "Attributes:\n",
       "    units:    hPa"
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       "  --xr-background-color: var(--jp-layout-color0, white);\n",
       "  --xr-background-color-row-even: var(--jp-layout-color1, white);\n",
       "  --xr-background-color-row-odd: var(--jp-layout-color2, #eeeeee);\n",
       "}\n",
       "\n",
       "html[theme=dark],\n",
       "body.vscode-dark {\n",
       "  --xr-font-color0: rgba(255, 255, 255, 1);\n",
       "  --xr-font-color2: rgba(255, 255, 255, 0.54);\n",
       "  --xr-font-color3: rgba(255, 255, 255, 0.38);\n",
       "  --xr-border-color: #1F1F1F;\n",
       "  --xr-disabled-color: #515151;\n",
       "  --xr-background-color: #111111;\n",
       "  --xr-background-color-row-even: #111111;\n",
       "  --xr-background-color-row-odd: #313131;\n",
       "}\n",
       "\n",
       ".xr-wrap {\n",
       "  display: block;\n",
       "  min-width: 300px;\n",
       "  max-width: 700px;\n",
       "}\n",
       "\n",
       ".xr-text-repr-fallback {\n",
       "  /* fallback to plain text repr when CSS is not injected (untrusted notebook) */\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-header {\n",
       "  padding-top: 6px;\n",
       "  padding-bottom: 6px;\n",
       "  margin-bottom: 4px;\n",
       "  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, 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 (bottom_top: 74, south_north: 119, west_east: 119)&gt;\n",
       "array([[[ 977.6088   ,  973.8247   ,  980.0365   , ..., 1005.25305  ,\n",
       "         1005.3736   , 1005.49805  ],\n",
       "        [ 972.2685   ,  972.64575  ,  980.2555   , ..., 1005.1616   ,\n",
       "         1005.28357  , 1005.40784  ],\n",
       "        [ 973.7658   ,  979.50134  ,  983.94495  , ..., 1005.05743  ,\n",
       "         1005.1929   , 1005.32166  ],\n",
       "        ...,\n",
       "        [ 910.8054   ,  898.6346   ,  894.9356   , ..., 1013.1167   ,\n",
       "         1012.9816   , 1012.9492   ],\n",
       "        [ 903.1422   ,  885.46564  ,  880.11725  , ..., 1013.20825  ,\n",
       "         1013.1019   , 1012.9691   ],\n",
       "        [ 868.00275  ,  854.2058   ,  859.6906   , ..., 1009.3077   ,\n",
       "         1013.17224  , 1013.0759   ]],\n",
       "\n",
       "       [[ 970.978    ,  967.2171   ,  973.3924   , ...,  998.4201   ,\n",
       "          998.54095  ,  998.6655   ],\n",
       "        [ 965.6708   ,  966.0465   ,  973.6117   , ...,  998.33044  ,\n",
       "          998.4526   ,  998.5758   ],\n",
       "        [ 967.15784  ,  972.86304  ,  977.2757   , ...,  998.2269   ,\n",
       "          998.3619   ,  998.4895   ],\n",
       "...\n",
       "        [  11.009878 ,   10.996195 ,   10.992074 , ...,   11.122887 ,\n",
       "           11.122656 ,   11.1225195],\n",
       "        [  11.0012455,   10.981459 ,   10.975507 , ...,   11.123066 ,\n",
       "           11.122817 ,   11.1225195],\n",
       "        [  10.961985 ,   10.946582 ,   10.95274  , ...,   11.118411 ,\n",
       "           11.122959 ,   11.122741 ]],\n",
       "\n",
       "       [[  10.351611 ,   10.350232 ,   10.352553 , ...,   10.362022 ,\n",
       "           10.362007 ,   10.361997 ],\n",
       "        [  10.349756 ,   10.349896 ,   10.352734 , ...,   10.361921 ,\n",
       "           10.362008 ,   10.362052 ],\n",
       "        [  10.350339 ,   10.352377 ,   10.3541   , ...,   10.361861 ,\n",
       "           10.361966 ,   10.361929 ],\n",
       "        ...,\n",
       "        [  10.328756 ,   10.324332 ,   10.322899 , ...,   10.3655405,\n",
       "           10.365465 ,   10.36542  ],\n",
       "        [  10.325963 ,   10.319494 ,   10.317566 , ...,   10.3655205,\n",
       "           10.3654995,   10.365434 ],\n",
       "        [  10.313118 ,   10.308083 ,   10.31015  , ...,   10.364057 ,\n",
       "           10.365552 ,   10.365443 ]]], dtype=float32)\n",
       "Coordinates:\n",
       "    XLAT     (south_north, west_east) float32 16.568985 16.612839 ... 45.305634\n",
       "    XLONG    (south_north, west_east) float32 104.098694 104.3277 ... 138.15619\n",
       "Dimensions without coordinates: bottom_top, south_north, west_east\n",
       "Attributes:\n",
       "    units:    hPa</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>bottom_top</span>: 74</li><li><span>south_north</span>: 119</li><li><span>west_east</span>: 119</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-c339c545-37c4-490d-b7ad-065a079dde04' class='xr-array-in' type='checkbox' checked><label for='section-c339c545-37c4-490d-b7ad-065a079dde04' 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>977.6088 973.8247 980.0365 985.46826 ... 10.364057 10.365552 10.365443</span></div><div class='xr-array-data'><pre>array([[[ 977.6088   ,  973.8247   ,  980.0365   , ..., 1005.25305  ,\n",
       "         1005.3736   , 1005.49805  ],\n",
       "        [ 972.2685   ,  972.64575  ,  980.2555   , ..., 1005.1616   ,\n",
       "         1005.28357  , 1005.40784  ],\n",
       "        [ 973.7658   ,  979.50134  ,  983.94495  , ..., 1005.05743  ,\n",
       "         1005.1929   , 1005.32166  ],\n",
       "        ...,\n",
       "        [ 910.8054   ,  898.6346   ,  894.9356   , ..., 1013.1167   ,\n",
       "         1012.9816   , 1012.9492   ],\n",
       "        [ 903.1422   ,  885.46564  ,  880.11725  , ..., 1013.20825  ,\n",
       "         1013.1019   , 1012.9691   ],\n",
       "        [ 868.00275  ,  854.2058   ,  859.6906   , ..., 1009.3077   ,\n",
       "         1013.17224  , 1013.0759   ]],\n",
       "\n",
       "       [[ 970.978    ,  967.2171   ,  973.3924   , ...,  998.4201   ,\n",
       "          998.54095  ,  998.6655   ],\n",
       "        [ 965.6708   ,  966.0465   ,  973.6117   , ...,  998.33044  ,\n",
       "          998.4526   ,  998.5758   ],\n",
       "        [ 967.15784  ,  972.86304  ,  977.2757   , ...,  998.2269   ,\n",
       "          998.3619   ,  998.4895   ],\n",
       "...\n",
       "        [  11.009878 ,   10.996195 ,   10.992074 , ...,   11.122887 ,\n",
       "           11.122656 ,   11.1225195],\n",
       "        [  11.0012455,   10.981459 ,   10.975507 , ...,   11.123066 ,\n",
       "           11.122817 ,   11.1225195],\n",
       "        [  10.961985 ,   10.946582 ,   10.95274  , ...,   11.118411 ,\n",
       "           11.122959 ,   11.122741 ]],\n",
       "\n",
       "       [[  10.351611 ,   10.350232 ,   10.352553 , ...,   10.362022 ,\n",
       "           10.362007 ,   10.361997 ],\n",
       "        [  10.349756 ,   10.349896 ,   10.352734 , ...,   10.361921 ,\n",
       "           10.362008 ,   10.362052 ],\n",
       "        [  10.350339 ,   10.352377 ,   10.3541   , ...,   10.361861 ,\n",
       "           10.361966 ,   10.361929 ],\n",
       "        ...,\n",
       "        [  10.328756 ,   10.324332 ,   10.322899 , ...,   10.3655405,\n",
       "           10.365465 ,   10.36542  ],\n",
       "        [  10.325963 ,   10.319494 ,   10.317566 , ...,   10.3655205,\n",
       "           10.3654995,   10.365434 ],\n",
       "        [  10.313118 ,   10.308083 ,   10.31015  , ...,   10.364057 ,\n",
       "           10.365552 ,   10.365443 ]]], dtype=float32)</pre></div></div></li><li class='xr-section-item'><input id='section-a664d938-3432-42fd-8bf2-823f1a8377a7' class='xr-section-summary-in' type='checkbox'  checked><label for='section-a664d938-3432-42fd-8bf2-823f1a8377a7' class='xr-section-summary' >Coordinates: <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>XLAT</span></div><div class='xr-var-dims'>(south_north, west_east)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>16.568985 16.612839 ... 45.305634</div><input id='attrs-e54793ab-c887-4620-9aec-bb6e3688e464' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e54793ab-c887-4620-9aec-bb6e3688e464' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a9af8f7e-6c04-4d19-93fd-ffe96b2516ba' class='xr-var-data-in' type='checkbox'><label for='data-a9af8f7e-6c04-4d19-93fd-ffe96b2516ba' 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>FieldType :</span></dt><dd>104</dd><dt><span>MemoryOrder :</span></dt><dd>XY </dd><dt><span>description :</span></dt><dd>LATITUDE, SOUTH IS NEGATIVE</dd><dt><span>units :</span></dt><dd>degree_north</dd><dt><span>stagger :</span></dt><dd></dd></dl></div><div class='xr-var-data'><pre>array([[16.568985, 16.612839, 16.656075, ..., 17.305672, 17.273308,\n",
       "        17.240318],\n",
       "       [16.788559, 16.832611, 16.87603 , ..., 17.52864 , 17.496117,\n",
       "        17.462982],\n",
       "       [17.008484, 17.052727, 17.09636 , ..., 17.751953, 17.719307,\n",
       "        17.68602 ],\n",
       "       ...,\n",
       "       [43.68952 , 43.762844, 43.835167, ..., 44.925404, 44.870953,\n",
       "        44.815437],\n",
       "       [43.929745, 44.003387, 44.076023, ..., 45.171005, 45.116314,\n",
       "        45.06056 ],\n",
       "       [44.16991 , 44.243866, 44.316814, ..., 45.416573, 45.361637,\n",
       "        45.305634]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>XLONG</span></div><div class='xr-var-dims'>(south_north, west_east)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>104.098694 104.3277 ... 138.15619</div><input id='attrs-2a3d3d69-5a30-49d5-a5dc-190213a85314' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-2a3d3d69-5a30-49d5-a5dc-190213a85314' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ce91913e-049a-4d85-a202-b83b6e5ae5ad' class='xr-var-data-in' type='checkbox'><label for='data-ce91913e-049a-4d85-a202-b83b6e5ae5ad' 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>FieldType :</span></dt><dd>104</dd><dt><span>MemoryOrder :</span></dt><dd>XY </dd><dt><span>description :</span></dt><dd>LONGITUDE, WEST IS NEGATIVE</dd><dt><span>units :</span></dt><dd>degree_east</dd><dt><span>stagger :</span></dt><dd></dd></dl></div><div class='xr-var-data'><pre>array([[104.098694, 104.3277  , 104.55701 , ..., 131.43512 , 131.66837 ,\n",
       "        131.90143 ],\n",
       "       [104.05249 , 104.282135, 104.512054, ..., 131.46875 , 131.7027  ,\n",
       "        131.9364  ],\n",
       "       [104.00604 , 104.23633 , 104.46686 , ..., 131.50262 , 131.73718 ,\n",
       "        131.97156 ],\n",
       "       ...,\n",
       "       [ 96.13068 ,  96.46338 ,  96.796875, ..., 137.30432 , 137.65088 ,\n",
       "        137.9968  ],\n",
       "       [ 96.02817 ,  96.36212 ,  96.6969  , ..., 137.3808  , 137.72882 ,\n",
       "        138.07614 ],\n",
       "       [ 95.924805,  96.26001 ,  96.59607 , ..., 137.45795 , 137.80743 ,\n",
       "        138.15619 ]], dtype=float32)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-6df035ab-53c1-4bf2-9954-8badf25b640a' class='xr-section-summary-in' type='checkbox'  checked><label for='section-6df035ab-53c1-4bf2-9954-8badf25b640a' class='xr-section-summary' >Attributes: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>hPa</dd></dl></div></li></ul></div></div>"
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       "<xarray.DataArray (bottom_top: 74, south_north: 119, west_east: 119)>\n",
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       "...\n",
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       "\n",
       "       [[  10.351611 ,   10.350232 ,   10.352553 , ...,   10.362022 ,\n",
       "           10.362007 ,   10.361997 ],\n",
       "        [  10.349756 ,   10.349896 ,   10.352734 , ...,   10.361921 ,\n",
       "           10.362008 ,   10.362052 ],\n",
       "        [  10.350339 ,   10.352377 ,   10.3541   , ...,   10.361861 ,\n",
       "           10.361966 ,   10.361929 ],\n",
       "        ...,\n",
       "        [  10.328756 ,   10.324332 ,   10.322899 , ...,   10.3655405,\n",
       "           10.365465 ,   10.36542  ],\n",
       "        [  10.325963 ,   10.319494 ,   10.317566 , ...,   10.3655205,\n",
       "           10.3654995,   10.365434 ],\n",
       "        [  10.313118 ,   10.308083 ,   10.31015  , ...,   10.364057 ,\n",
       "           10.365552 ,   10.365443 ]]], dtype=float32)\n",
       "Coordinates:\n",
       "    XLAT     (south_north, west_east) float32 16.568985 16.612839 ... 45.305634\n",
       "    XLONG    (south_north, west_east) float32 104.098694 104.3277 ... 138.15619\n",
       "Dimensions without coordinates: bottom_top, south_north, west_east\n",
       "Attributes:\n",
       "    units:    hPa"
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     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "display(era5_o3, p_era5, p_wrf)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "It's time to run the interpolation:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Explanations are given in https://github.com/pydata/xarray/issues/3931\n",
    "interped = xr.apply_ufunc(\n",
    "    interp1d_np,\n",
    "    era5_o3_interp,\n",
    "    p_era5,\n",
    "    p_wrf,\n",
    "    input_core_dims=[['level'], ['level'], [\"bottom_top\"]],\n",
    "    output_core_dims=[['bottom_top']],\n",
    "    exclude_dims=set((\"bottom_top\",)),\n",
    "    vectorize=True,\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Reorgnizie interpolated data to WRF variable dimension:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
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       "          9585.6528903 , 9590.35306113, 9595.75774179],\n",
       "         [9686.9817295 , 9685.91018815, 9682.07826455, ...,\n",
       "          9576.20928858, 9580.64839163, 9585.35674978],\n",
       "         [9678.86203706, 9677.71921539, 9674.5757891 , ...,\n",
       "          9566.05929144, 9569.49277165, 9574.19528187],\n",
       "         ...,\n",
       "         [7659.76051491, 7642.8204401 , 7622.65272498, ...,\n",
       "          7648.34201255, 7683.81940009, 7730.1049812 ],\n",
       "         [7626.72798026, 7609.10646871, 7591.36561556, ...,\n",
       "          7622.32897339, 7635.5818719 , 7659.58415364],\n",
       "         [7585.96803727, 7569.48853948, 7558.64050131, ...,\n",
       "          7612.8093532 , 7611.19161405, 7612.15335775]]]])\n",
       "Coordinates:\n",
       "    XLAT     (south_north, west_east) float32 16.568985 16.612839 ... 45.305634\n",
       "    XLONG    (south_north, west_east) float32 104.098694 104.3277 ... 138.15619\n",
       "Dimensions without coordinates: Time, bottom_top, south_north, west_east</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>Time</span>: 1</li><li><span>bottom_top</span>: 74</li><li><span>south_north</span>: 119</li><li><span>west_east</span>: 119</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-e96934e6-6098-484e-977e-d73018305195' class='xr-array-in' type='checkbox' checked><label for='section-e96934e6-6098-484e-977e-d73018305195' 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>26.86 26.89 26.89 26.89 ... 7.62e+03 7.613e+03 7.611e+03 7.612e+03</span></div><div class='xr-array-data'><pre>array([[[[  26.85544708,   26.89004326,   26.89004326, ...,\n",
       "            27.85048673,   27.96454546,   27.97777195],\n",
       "         [  26.79858192,   26.89004517,   26.90632874, ...,\n",
       "            27.86999883,   28.03319995,   28.00973581],\n",
       "         [  26.89004326,   26.91651859,   26.96341212, ...,\n",
       "            27.75184335,   27.91883112,   28.01447156],\n",
       "         ...,\n",
       "         [  42.88559052,   42.90171678,   42.84873043, ...,\n",
       "            43.76431619,   42.66415577,   42.48096888],\n",
       "         [  43.05763403,   43.23619572,   42.85495261, ...,\n",
       "            43.87452885,   42.7925106 ,   42.38859107],\n",
       "         [  43.60155035,   43.34088363,   43.06596098, ...,\n",
       "            44.04397503,   43.13010603,   42.49644742]],\n",
       "\n",
       "        [[  26.86850858,   26.89004326,   26.89004326, ...,\n",
       "            27.74865668,   27.90227851,   27.96283885],\n",
       "         [  26.82568012,   26.89004517,   26.89004326, ...,\n",
       "            27.74462751,   27.90841153,   27.95417291],\n",
       "         [  26.89004326,   26.89004326,   26.90871055, ...,\n",
       "            27.62621128,   27.79286227,   27.9352251 ],\n",
       "...\n",
       "         [7541.28326442, 7527.26233612, 7509.01665573, ...,\n",
       "          7506.93546421, 7541.55757499, 7586.09060089],\n",
       "         [7511.94835776, 7497.8423389 , 7482.09586978, ...,\n",
       "          7479.4326681 , 7493.47807596, 7517.35630734],\n",
       "         [7479.79887861, 7466.09814386, 7455.23409676, ...,\n",
       "          7466.90025385, 7466.7015107 , 7469.38325193]],\n",
       "\n",
       "        [[9694.82835713, 9693.7357371 , 9689.58353861, ...,\n",
       "          9585.6528903 , 9590.35306113, 9595.75774179],\n",
       "         [9686.9817295 , 9685.91018815, 9682.07826455, ...,\n",
       "          9576.20928858, 9580.64839163, 9585.35674978],\n",
       "         [9678.86203706, 9677.71921539, 9674.5757891 , ...,\n",
       "          9566.05929144, 9569.49277165, 9574.19528187],\n",
       "         ...,\n",
       "         [7659.76051491, 7642.8204401 , 7622.65272498, ...,\n",
       "          7648.34201255, 7683.81940009, 7730.1049812 ],\n",
       "         [7626.72798026, 7609.10646871, 7591.36561556, ...,\n",
       "          7622.32897339, 7635.5818719 , 7659.58415364],\n",
       "         [7585.96803727, 7569.48853948, 7558.64050131, ...,\n",
       "          7612.8093532 , 7611.19161405, 7612.15335775]]]])</pre></div></div></li><li class='xr-section-item'><input id='section-1266f87e-7b2b-45be-8fed-921e34b29f0a' class='xr-section-summary-in' type='checkbox'  checked><label for='section-1266f87e-7b2b-45be-8fed-921e34b29f0a' class='xr-section-summary' >Coordinates: <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>XLAT</span></div><div class='xr-var-dims'>(south_north, west_east)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>16.568985 16.612839 ... 45.305634</div><input id='attrs-7fad8ee5-c1cd-47a4-b296-ba9b80abd28d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-7fad8ee5-c1cd-47a4-b296-ba9b80abd28d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-24ce1929-2633-4261-b3b0-b84c44a1c644' class='xr-var-data-in' type='checkbox'><label for='data-24ce1929-2633-4261-b3b0-b84c44a1c644' 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>FieldType :</span></dt><dd>104</dd><dt><span>MemoryOrder :</span></dt><dd>XY </dd><dt><span>description :</span></dt><dd>LATITUDE, SOUTH IS NEGATIVE</dd><dt><span>units :</span></dt><dd>degree_north</dd><dt><span>stagger :</span></dt><dd></dd></dl></div><div class='xr-var-data'><pre>array([[16.568985, 16.612839, 16.656075, ..., 17.305672, 17.273308,\n",
       "        17.240318],\n",
       "       [16.788559, 16.832611, 16.87603 , ..., 17.52864 , 17.496117,\n",
       "        17.462982],\n",
       "       [17.008484, 17.052727, 17.09636 , ..., 17.751953, 17.719307,\n",
       "        17.68602 ],\n",
       "       ...,\n",
       "       [43.68952 , 43.762844, 43.835167, ..., 44.925404, 44.870953,\n",
       "        44.815437],\n",
       "       [43.929745, 44.003387, 44.076023, ..., 45.171005, 45.116314,\n",
       "        45.06056 ],\n",
       "       [44.16991 , 44.243866, 44.316814, ..., 45.416573, 45.361637,\n",
       "        45.305634]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>XLONG</span></div><div class='xr-var-dims'>(south_north, west_east)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>104.098694 104.3277 ... 138.15619</div><input id='attrs-df8341b6-3ca2-46cc-90e4-4b11684c41a6' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-df8341b6-3ca2-46cc-90e4-4b11684c41a6' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f6c1bb7b-75da-4b6f-8f26-c54f346300d0' class='xr-var-data-in' type='checkbox'><label for='data-f6c1bb7b-75da-4b6f-8f26-c54f346300d0' 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>FieldType :</span></dt><dd>104</dd><dt><span>MemoryOrder :</span></dt><dd>XY </dd><dt><span>description :</span></dt><dd>LONGITUDE, WEST IS NEGATIVE</dd><dt><span>units :</span></dt><dd>degree_east</dd><dt><span>stagger :</span></dt><dd></dd></dl></div><div class='xr-var-data'><pre>array([[104.098694, 104.3277  , 104.55701 , ..., 131.43512 , 131.66837 ,\n",
       "        131.90143 ],\n",
       "       [104.05249 , 104.282135, 104.512054, ..., 131.46875 , 131.7027  ,\n",
       "        131.9364  ],\n",
       "       [104.00604 , 104.23633 , 104.46686 , ..., 131.50262 , 131.73718 ,\n",
       "        131.97156 ],\n",
       "       ...,\n",
       "       [ 96.13068 ,  96.46338 ,  96.796875, ..., 137.30432 , 137.65088 ,\n",
       "        137.9968  ],\n",
       "       [ 96.02817 ,  96.36212 ,  96.6969  , ..., 137.3808  , 137.72882 ,\n",
       "        138.07614 ],\n",
       "       [ 95.924805,  96.26001 ,  96.59607 , ..., 137.45795 , 137.80743 ,\n",
       "        138.15619 ]], dtype=float32)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-14d88b3a-a8b4-4d4b-9abd-e5286c63fd95' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-14d88b3a-a8b4-4d4b-9abd-e5286c63fd95' 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: 1, bottom_top: 74, south_north: 119, west_east: 119)>\n",
       "array([[[[  26.85544708,   26.89004326,   26.89004326, ...,\n",
       "            27.85048673,   27.96454546,   27.97777195],\n",
       "         [  26.79858192,   26.89004517,   26.90632874, ...,\n",
       "            27.86999883,   28.03319995,   28.00973581],\n",
       "         [  26.89004326,   26.91651859,   26.96341212, ...,\n",
       "            27.75184335,   27.91883112,   28.01447156],\n",
       "         ...,\n",
       "         [  42.88559052,   42.90171678,   42.84873043, ...,\n",
       "            43.76431619,   42.66415577,   42.48096888],\n",
       "         [  43.05763403,   43.23619572,   42.85495261, ...,\n",
       "            43.87452885,   42.7925106 ,   42.38859107],\n",
       "         [  43.60155035,   43.34088363,   43.06596098, ...,\n",
       "            44.04397503,   43.13010603,   42.49644742]],\n",
       "\n",
       "        [[  26.86850858,   26.89004326,   26.89004326, ...,\n",
       "            27.74865668,   27.90227851,   27.96283885],\n",
       "         [  26.82568012,   26.89004517,   26.89004326, ...,\n",
       "            27.74462751,   27.90841153,   27.95417291],\n",
       "         [  26.89004326,   26.89004326,   26.90871055, ...,\n",
       "            27.62621128,   27.79286227,   27.9352251 ],\n",
       "...\n",
       "         [7541.28326442, 7527.26233612, 7509.01665573, ...,\n",
       "          7506.93546421, 7541.55757499, 7586.09060089],\n",
       "         [7511.94835776, 7497.8423389 , 7482.09586978, ...,\n",
       "          7479.4326681 , 7493.47807596, 7517.35630734],\n",
       "         [7479.79887861, 7466.09814386, 7455.23409676, ...,\n",
       "          7466.90025385, 7466.7015107 , 7469.38325193]],\n",
       "\n",
       "        [[9694.82835713, 9693.7357371 , 9689.58353861, ...,\n",
       "          9585.6528903 , 9590.35306113, 9595.75774179],\n",
       "         [9686.9817295 , 9685.91018815, 9682.07826455, ...,\n",
       "          9576.20928858, 9580.64839163, 9585.35674978],\n",
       "         [9678.86203706, 9677.71921539, 9674.5757891 , ...,\n",
       "          9566.05929144, 9569.49277165, 9574.19528187],\n",
       "         ...,\n",
       "         [7659.76051491, 7642.8204401 , 7622.65272498, ...,\n",
       "          7648.34201255, 7683.81940009, 7730.1049812 ],\n",
       "         [7626.72798026, 7609.10646871, 7591.36561556, ...,\n",
       "          7622.32897339, 7635.5818719 , 7659.58415364],\n",
       "         [7585.96803727, 7569.48853948, 7558.64050131, ...,\n",
       "          7612.8093532 , 7611.19161405, 7612.15335775]]]])\n",
       "Coordinates:\n",
       "    XLAT     (south_north, west_east) float32 16.568985 16.612839 ... 45.305634\n",
       "    XLONG    (south_north, west_east) float32 104.098694 104.3277 ... 138.15619\n",
       "Dimensions without coordinates: Time, bottom_top, south_north, west_east"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# sort the dims and delete useless coordinates\n",
    "interped_o3 = interped.sel(time='2020-09-01 00:00').transpose('bottom_top', ...).expand_dims('Time').drop_vars(['time', 'longitude', 'latitude'])\n",
    "display(interped_o3)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Check the surface O3 again:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 808.333x316.528 with 6 Axes>"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 318,
       "width": 742
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "f, axs = plot.subplots(ncols=2, share=0)\n",
    "\n",
    "ax = axs[0]\n",
    "m = ax.pcolormesh(era5_o3.longitude,\n",
    "                  era5_o3.latitude,\n",
    "                  era5_o3.isel(time=0, level=-1),\n",
    "                  cmap='viridis',\n",
    "                  vmin=20,\n",
    "                  vmax=65)\n",
    "ax.colorbar(m, label='O$_3$ (ppbv)', loc='r')\n",
    "ax.format(title='Original')\n",
    "\n",
    "ax = axs[1]\n",
    "m = ax.pcolormesh(interped_o3.XLONG,\n",
    "                  interped_o3.XLAT,\n",
    "                  interped_o3.isel(Time=0, bottom_top=0),\n",
    "                  cmap='viridis',\n",
    "                  vmin=20,\n",
    "                  vmax=65)\n",
    "ax.format(title='Interpolated')\n",
    "ax.colorbar(m, label='O$_3$ (ppbv)', loc='r')\n",
    "\n",
    "axs.format(xlim=(o3.XLONG.min(), o3.XLONG.max()),\n",
    "           ylim=(o3.XLAT.min(), o3.XLAT.max()),\n",
    "           xlabel='longitude',\n",
    "           ylabel='latitude',)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We can get the index of specific location and use it to pick the interpolated O3 profile."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "# convert to index in wrf grid\n",
    "x_y = ll_to_xy(ncfile, 32, 119)\n",
    "x, y = x_y[0].values, x_y[1].values"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Saving and exporting data"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Original surface ozone:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.collections.QuadMesh at 0x7f82849716d0>"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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i3XfffTrttNM61NfevXs1ceJEbdiwQZs3b1ZRUftr509+8pNatWqVt59bbrlF06d7rvE76KKLLlJxcbE+97nP6dxzz9WkSZO4kw8fChOA7zNx4kRNnDix9b9/9KMfSdoXbw4AAAAAADJ3++23a+HChYpEIvr+97+vs88+WzU1Nbrrrrt01113ac6cOfqnf/qnNn+X+1x++eWqrKxUWVmZfvKTn2jSpEl67bXXNGfOHD333HOaPn26Xn75ZZWUlOy3r1mzZmnDhg3e17z++usdGldXKCwsVE1NjRYsWKB7771XgwcP1rnnnqtzzz1XH/3oR3tsHMgdTAB6LFq0iBl2AAAAAEB29IIU4K7S1NSkm2++WZJ0zTXX6PLLL2+tmzt3rqqqqvTQQw/ppptu6tAE4OrVq/Xoo48qGo1qwYIFmjBhgqR9N/bce++9mjx5stavX6/58+drxowZ3r7+9Kc/6e677/a+pqqqStXV1crPz9eWLVu6PQB0w4YNevLJJ7Vw4UI9/vjj2rx5s37605/qpz/9qSoqKnTeeefp85//vIYNG9at40DuMH6/AEk644wz9NnPflbbt2/P9lAAAAAAADhgLVu2TFu3blVBQYEuu+yydvVXXrnv8UHPPPOMdu3atd/+HnroIUnShAkTWif/WpSUlOiSSy6RJD388MPefqqqqvTNb35zv8truftv9OjR3T75J0mJREJnnHGG7rrrLq1fv16/+93v9KUvfUklJSV69dVXdd111+nYY4/VmWeeqQULFmjPHvuxJYDEBKDXEUccoTAMtW7dumwPBQAAAABwsAmz/K8LLVmyRJI0adIkFRS0f27rmDFjNGjQIKVSKS1btmy//T333HOSpNNPP91ZP2XKFEnSyy+/rN27/3/27jw6iiptA/hTvScBEkICIgQECQoiiyJBEGRccBsd0NHBDUYUFxRFQJYoIzoOoqMgEgdFRRhBx3EQRAQVFYggICKMAuEjQFhlzb51d7q7vj9iMsbc95I0nXRInt85nDNz375Vt6urquPtqnpyxeU89thjOH78OO69917t+somADt1kp9XX1PsdjuuueYazJ49G3v27MHixYsxbNgwNG3aFKmpqXjkkUeQmJiIYcOG1frY6MzBCUCNJ598EgDw4osvhnkkRERERERERGeusgm0Xr16KeuGYaB79+4VXqtTFvwhLa9jx46IioqCaZrYs2eP8jULFy7E0qVL0bt3bzz66KPa9ZUto02bNpg6dSr69OmDli1bonfv3rj//vuxffv2U445FKxWK6644grMnDkT6enpeO655xAREQG3233Kqx2pYeMzADUGDx6M4uJijB07FoMGDcLDDz+MLl26ID4+vlYu+W0IHIYPHSKPVWqPtRbU2hgusEfW2rrqo0u23CrW7IXqdkMOvROT94K1ZVL1k4OD1Xvig8p2i+b9SsnBAOBzqZ9BqktWjPhOnfQLyGmNrv+TYxx3/NhRrJnCabA4TuwCq0d+v42OqNP85tx/s9jHli/HLlqy1eeRiEz5qm5NYDPVEIviCoDyWnPNzuRWx3EGcuTbXwIFtffdUltMr3wMGH45VVNM9wwy9VNanqmJbjU1qbhevzoBtdgnx8QW+OSTo9uvPmG5fZqkXyHpHIAci6t5dLRpkzduwKHu6GskL6+kiVzzNlWvy54rD9CqSbiV3pep20S6ywyE5en+BggmtVf394ZVsy5pW+i+w3Q16e+AiKNykr3FK383B5PWrUuUlpan+xvF4tOcX4R+hq6PJgXYKFF/Oxt+zbc2U4DrpAMHDgAAzj77bPE1sbGxFV4rKSoqQmZmZpWWV1hYiIMHD+Kiiy6qNJ4JEyYgKioKr7/+OqxWOX0b+N+k5IwZMxAI/G+f3bFjB3bs2IHFixdj6tSpGDFihHY5p8vn8yE1NRXLly/HihUrcPjwYZi/pHk3bdq0RtdNZzbOYmmUPUcgIiICq1evxurVq0/ZxzAMZGdn1/DIiIiIiIiIqN4zDf0Mbk2vG6XhmNJVdr/13XffibWioiIAQOPGjcXXlE1gFRYKVxL8ZlkA0KiR/GtJ06ZNcfDgQRT85kfAQCCABx98EHl5eZg5cybat29/yknHsglAh8OBiRMn4tprr0WrVq2wbds2PPvss1i/fj2eeOIJ9OrVC926ddMuq7ry8vLwxRdf4NNPP8WXX36J/Pz88km/Zs2a4cYbb8Qf/vAHXH755SFdL9UvnADUCOYS3rKDkCo6ceIETp48WaHN4/HAz+1FRERERERU77ndbgDQXmkXFVV6N0txsXyF7K+XFezyXnvtNaxduxZXX3017rnnHv3Af+FwONC5c2c8/fTTuO6668rb+/bti+XLl+P666/H+vXrMWnSJCxfvrxKy9Q5dOgQli9fjk8//RTr1q2Dz+crn29o3rw5brzxRgwaNAiXXXYZLBY+3Y1OjROAGtu2bQv3EOqNN998E9OmTavUHtVUvpWHiIiIiIiIwuv666/HnDlzTns5Llfpre26tNqSktL7851OzTNvfrUsAMjPz0d0dLTydd5fHpXx69fv2LEDzz77LJo2bYrXXnutaoMHtHcEWq1WTJ48uXwS0OPxnPI9nEqXLl0A/O8io7PPPrt80u/SSy+FYYTpylA6Y3ECUCMhISHcQ6g3RowYgcGDB1doGzJkCArMys//IyIiIiIiIsA0S/+Fa92hFBlZ+uz1nJwc8TX5+fkA/nfl3qmWVba81q1bV2l5Xq8XI0aMgMfjweuvv46zzjqryuM/lZ49e8IwDPj9fuzZswedO3c+reWZpomEhATcdNNN+MMf/oCkpKQQjZQaKk4AUq2Ij49HfHx8hTan04niEv5qQUREREREVN+1adMGP/zwA7KyssTXHDlyBMCpL8aJjIxEs2bNkJmZqV3e0aNHAaB8gnDmzJn46aefcMstt+CWW26p7lvQcrlciIuLw4kTJ0KSC/D111/j4osvDsHIiEpxArCKVqxYgf/85z/Yt28f9u/fD6/Xi/bt26N9+/a4+eab8fvf/z7cQzwjxVpLMCpG/7BVqtvMJXJKZ6SUKqdJZjM0gW5Sym6wz0U+/8Edyva/tvpU7PN2dm+xJqX86VP0xBJM4XEmUpovAHjVdz8AAEoaCeOwasbnlp8nIqUkumPlMdiK5A/LJqzLkSP3MYrkBFQzU/2Hlz8vX+xDtS+gecaPkSt/VoEC9cPBTV+Io8TruIAmBdia5xZrjjx1+nJJpCYBUXMlSEDo5oiUxxcZIdeiHOqa0yqfNC2aaFSLMHiHVf7Ssdvlmt+prmlO9/BrzrUBh/r85/Npzn+6hHmh5ovSJM9rEodFumRezdil1F5dErFFU7MKu5JVPgRgc8vbwl6krlk98hu2ujU1j3p/sebK5z+HTT4WpYTvgF3+zjat1X8+mC5J3KJL7RXSfqU0XwCAJtHX8Ao1XZ/6lAJsQnv+rfF1h1BiYiIAYNOmTeJryh7DVfZanY4dO2L9+vXYtGkT+vfvX6m+f//+8tuNO3ToAADYu3cvAGDRokVYtGiRuOyWLVsCAH7/+9/jvffeQ3p6Ovbv34/mzZuja9euyj4lJSXlk5FVGf+pcPKPQo0TgKewZ88ePPDAA/j+++8rBXxs2bIFW7ZswUcffYRLLrkEb7zxBtq3bx+mkRIRERERERHVTf3798ff//53rFu3DkVFRRVu4wWA9PR0HDhwAFarFX369Dnl8vr164f169dj5cqVGDt2bKX6V199BQDo1q1bebpwsLZv346hQ4fi7LPPxo4dO5ShGz/++CP8fj9iYmLQvHnz01pfmUAggJUrVyI9Pf2UychlJkyYEJJ1U/3DCUANj8eDoUOHYtu2bXA4HLjtttvQv39/tGnTBhaLBfv378eaNWvwwQcfYNOmTfjzn/+Mr776CnY7gy2IiIiIiIiIylx66aVo0aIFjh07hpSUFIwfP768Zpomnn32WQDAgAEDEBuruaXkF4MHD8aLL76IjRs3Yu3atbjsssvKa9nZ2Zg5c2b568rMnj0bs2fPVi7vwIED5cEbR44cqfAcwquvvhoulws///wz5s+fXyk52DRNPPfccwBKn3UfCseOHcOgQYOQlpZWpdebpgnDMDgBSCJOAGq88sor2LZtG+Lj4/H555/j3HPPrVBPSkrCbbfdhtGjR2PgwIH48ccfMXPmTIwbNy5MIyYiIiIiIqJ6wzSCf95NKNYdQg6HA2PHjsX48eMxdepUREZGYvDgwcjOzsbbb7+Njz/+GBaLpdIEVs+ePQEAN954I55++uny9gsuuAA33XQTli5dimHDhuHll19Gv379kJaWhqlTpyIjIwNxcXG49957T3vsUVFRGDlyJKZPn44JEyYgNzcXt956K5o0aYIdO3Zg6tSpWLVqFZo1a4ZJkyad9voAYMqUKdixo/SRReeeey66du1a6apJourgBKDG+vXrYRgGXnzxxUqTf7+WmJiIF198Effddx/Wrl3LCUAiIiIiIiKi33jggQewYcMGfPTRR0hOTkZycnKF+pQpU9C7d8Vnbu/atQvA/wI9fm3mzJnYuXMndu3ahaFDh1aoRUZGYt68eYiO1jwkuxomT56MLVu2YNWqVfjLX/6Cv/zlLxXqCQkJePvtt0/7duMya9euhWEYeOCBBzBt2jQYBgM06fRwAlCj7AGk/fr1O+VrBwwYAAD46aefanJIRERERERE1EAYZum/cK075Ms0DLzzzjvo378/5s+fj127dsFut6N79+545JFHMHDgwGotr1mzZli1ahVefvllLFmyBIcPH0Z0dDQuv/xyjB8/Huedd17Ixm61WrFkyRJ88MEHmD9/Pvbu3YvCwkJceOGFuOSSSzBmzBjExMSEbH3Hjx8HAIwbN46TfxQSnADUsNlKN4/Ho4kd+4X3lxQ+h8NRo2MiOl1dX35IrEUeV3/LRx6XowYbS1F+AGAJ4otKl9omLM/UBNvp7lzYN+18ZftdFnU7AARs8gILE9Q16+/UabQA4HovRqz5XOrl+dThnQA0Sb8Azu1xUNn++fly6rHOT151euF92+8W++R/Fy/WfDnVH4NRJCco+nJzq7/AIFgbNxZr/nwmDp8Of05OuIdwRjNy8sSaM1sd+eqJlk+oRkBzQrWrUz8bRcp/QzVxyhGtTpv6e8elSwHWxFXaLOrx2TUpwE67vC6fv/qJqgFhGwGAGSF8v+m+xOpCyKlHkzpbrEuxFd6XJlVYSvoFAHuhemNIab4A4MiXV2bLV/9to02+1dSsBcK+7pH/hrIUa96w1MevSfG2ajauQJfaKyX9AgCEfkaJJrrap0kI9gn9SjR/g5rVf79UewzDwPDhwzF8+PAqvb4syVfSuHFjTJkyBVOmTDmtcbVp0+aU6zIMA0OGDAnZc/50WrdujT179sAnHQNE1VT9v14akLJ475UrV57ytWWvufDCC2t0TERERERERERUv919990wTRPvvvtuuIdC9QQnADUGDBgA0zTx5JNPYt26deLrvv32WyQnJ8MwDPzud7+rxRESERERERFRvWWG+R+FzaOPPorrrrsO06ZNw/PPP4/cWrq7heov3gKs8dBDD2H58uX45ptvcMMNN+Dyyy/H5ZdfjoSEBBiGgQMHDmDNmjVYs2YNTNNEv3798NBD8u2VRERERERERESnYrFY8Mgjj+Crr77CCy+8gBdeeAFnnXWW9rFjhmHgv//9by2Oks4knADUKHtA6fjx47F48WKsXr0aa9asqfAa0zRhGAYGDx6MF198MUwjJSIiIiIiIgo9t9uNtLS0Su1xcXGIj5ef70yn56uvvsJtt90Gv98P0yy9HPPIkSPaPgwLIR1OAJ5CfHw83nnnHTz++OP46KOPkJGRgYyMDJimiXbt2qFdu3YYPHgwunfvHu6hEhERERERUX1iGvpUu5peN4D09HQkJSVVKk+cOBHJycm1PaoG429/+xt8Ph9iYmLw6KOPomvXroiMjAz3sOgMxgnAKuratWt5KAgRERERERFRQ5CYmIi5c+dWao+LiwvDaBqOHTt2wDAMzJkzB9dcc024h0P1ACcAieqh9l/cK9ZaHgqItajDbmW7/WSh2Me0yVlCptWqLlg1v2JqLls3hX6mVTcGzfIs6lrAKYwbgC9SrqF/jrL5h4s/kPtcLJeCscdXINauSX1E2d7h5z+LfXZfMU+sXeiIULZv7PEfsc8tTa4Wa/sXdFAXdHFVJT5NsfoMaZ8FYOmcqGz3/7QzpGMgCpVAVo5Ys2fFKNttZ2meKxTQnLvt6ifFN40oErvEOovFmsUI7ZPnpeXZLX6xj8Mq1/yOEmW7VzNuQ1tTt+u2g8Uif59LTM1VRLqa16c+N3oMeX8xPfLJ2/Cr12VT/xkCALAXyNvCXiR8voXyNrIWyZ+v1aOuGT7NNg9U//OATf7OMUrk8Uk7jOEPcWKDZgyG7vu3RH18aL+zfXLNlGpeYT0AzEA9Sq8IZxjHL+t1uVzo1KlTmAbRcEVGRsLtduOyyy4L91ConuAEYBWsXbsWW7duRWGhPAnyaxMmTKjhERERERERERFRfdW/f38sWbIEO3fuxMUXh/iqAWqQOAGo4Xa7cdddd+HLL7+s0uvLAkE4AUhEREREREREwXrmmWewZs0ajBs3DkuXLkXjxo3DPSQ6w3ECUCMlJQUrV64EALRt2xYXXXQRH7pJREREREREtaMO3AJM4ZGTk4MXX3wRY8eORffu3XH77bcjMTERDof8+AUAuP3222tphHSm4QSgxuLFi2EYBgYPHow5c+bAbreHe0hEREREREREVM/1798fhmHANEtnYlNSUqrUjxOAJOEEoMbevXsBAJMnTz5jJ/927tyJV199FatXr0ZmZibOPfdc/O53v8PEiROVlxB7vV6kpKTg3//+NzIyMhAVFYWePXti9OjR6NOnTxjeAREREREREVHDctlll8HQBCQSVRcnADWaNGmC4uJixMfHh3soQfnkk09w3333obj4fyl727Ztw7Zt27B48WKsWrUKLVq0KK+53W7cdNNN2LBhQ3lbcXExPvvsM6xcuRIpKSm48847a/U9UHDa/EdO3nOelFMXbUdz1IV8OVlW95VkCCm7uqRf2DSnJelyd02KnmnXLE9ICPY3UafbAkDAIW/bqA+aqAu95CGE2rm2RmLNYlMnFH7R5zXNEkP7rJFF564Uaz2c6hRgXfKyM0rzWAZDFx+slnOn/GHlnqveX9qXqNOBAcC3M73aYyAKlYBHjlS1ncxRttuLhPMYAMOvOaas6vvE4lxyCnBzZ75Y8wTU5+4SUx6DL6BJaRc0snvFmi6B1yF8V5U4qj+GYOlSe4tL1OPzCO0AUOKWawGPumYUyO/XkSN/Vo5cqV3e5q4cTaJvsbpmc8spthZNzXCrU2cNvyaZ15THbtrU20L7N5QucTgYmvFBSswNJukXALzq48rUpfbqliekAJu6zyOYVOa6ircAN1iffvppuIdA9Uz1/+uoARkwYAAAYNOmTeEdSBB27dqFESNGoLi4GLfffjtWrlyJw4cP46OPPkK7du1w6NAhjBw5skKfKVOmYMOGDYiIiEBKSgrS09OxatUqDBo0CH6/H6NHj8aePXvC9I6IiIiIiIiIiCgYvAJQY9KkSfjyyy8xbtw4fP3114iJiQn3kKrsueeeQ1FREf70pz/h9ddfL790+KqrrsIHH3yASy+9FCtXrkRGRgbatWuHEydOYO7cuQBKny1w6623AgBatGiBt956C0eOHMHGjRsxa9YsvPLKK+F6W0RERERERA2HaZT+C9e6qU4oKirCV199hX379mHfvn3wer1o164d2rVrhyuuuALR0dHhHiKdATgBqHHOOefgs88+w7333osePXrg4YcfxiWXXIKEhARt8k7r1q1rcZSVnThxAkuXLoXFYsEzzzxT6bkB559/Pm6//Xb8+OOP+Omnn9CuXTusWLECbrcbbdu2LZ/8K+NwODBq1Chs3LgRH3/8MWbMmMFnERARERERERHVIK/Xi9deew2zZs1CVlYWAJSHgpT9N3l0dDQee+wxPPzww3A6nWEbK9V9nADUiIuLA1B6gPn9fjz33HOn7GMYBrKzs2t6aFpffPEFAoEALr/8cpx99tnK1/zjH/+o8P9TU1MBAAMHDlS+fsCAAbDb7cjMzMT27dvRpUuX0A6aiIiIiIiIiMqNHDkS//nPf2CaJqKjo3HppZeiTZs2sNvtyMjIwIYNG5CVlYVnn30WO3bswFtvvRXuIVMdxglAjRLdw2gFpu4Bu7Vk69atAIBLLrmkyn3S00sfVN+rl/oB+E2aNEGHDh2QlpaG3bt3cwKQiIiIiIiohhlm6b9wrZvCZ/78+fjwww9hGAbGjx+Pxx57DI0aVQz8KyoqwiuvvIIXXngB//nPf3D55Zfj7rvvDtOIqa7jBKBGbq4QUVbH7d69GwDQvHlzHDp0CFOmTMGaNWtQUFCA888/H0lJSZgwYQKaNm1a3ufgwYMAgFatWonLjY2NrfDaUAgggIJA5ZTCYwE5dUyXclofXX37PWLNWqyepI7MzxH7GLly6mLgZKa6XUhzq20W4dZ7I1JOgjUiXPICHXZhPfKp0fCp+wCAKaQK93j+IbHPlkmzxVqo7er/T6ES2qTfYG2ZqN4Wlz32gNgnoElstjWPUxc0P9Q0+2y3vK7fq1OKTc3+Yo1tKtakdEVTSDsEAFOTyGj6qv+jFTVcviNHle2uY/FiH3sbzbnCU/1cOadV3p9tFk26pyCgeVZVialOq9UlB0tJxADgE9KIdcvzampuv3pdbp88Brfm+8jnV6+rREjzBQB/kbw8q5D2a8+Tt7kjRyzBmac+D+uSfp3Z8jnO4lHvLxavJunXK+9/Ys0f4mTZYB+pI32P+TTHjea7BVKari61V/O3ofQ9xu+wM5fb7UZaWlql9ri4OMTHy98bdHqWL18OwzDw0EMP4cknn1S+JjIyEsnJycjLy8Ps2bPxySefcAKQREwBrmF/+MMfQjphVhWZmaWTOEeOHMGVV16Jf//73zh27BgKCwuxefNm/OMf/0Dv3r3x3XfflfcpKioCgEq/KPxa2YRhQUFBDY6eiIiIiIiIAABmmP+h9G6xpKSkSv/efPPNGn7zDdvmzZsBAEOHDj3la//85z9X6EOkwisAa9jatWvLJ9dqS9kE3YwZMxATE4OZM2fiqquuQqNGjbB582ZMnDgRu3btwv33348NGzbA5XLB7S69Cs9qlX+djoqKAgAUFxdr1y/dRvxbe/fuRftzqvRSIiIiIiIiCoPExETMnTu3UnvZM/OpZvh+uZr2rLPOOuVry16ju6CHiFcA1kOBQOntCVarFUuXLsU999yDhIQENG3aFFdddRW++OILxMTEYO/eveUncper9DbJ/Hz59tCyZyIyWYiIiIiIiKhhcLlc6NSpU6V/vP23ZpU903/dunWnfG3Z3X09e/as0THRmY1XANZDkb88D+3GG29E9+7dK9VjY2MxbNgwzJw5s/wS4cjISBQVFSEnJ0dcbl5eHoBT/6rw61uLdXr16gUE5OdtERERERERETVE48aNw9dff40xY8bgggsuQLt27ZSvO3HiBMaNGweLxYJ77pGfH0/ECcB6qOxSbF1S7/nnnw8A2LlzJwAgISEBJ0+eRFZWltjn6NHSB4a3bt06VEMlIiIiIiIiot9ISkrCW2+9hYcffhi9e/fG7bffjquuugpt2rSBw+HAgQMHsG7dOsydOxf5+fl4/PHHcc455+DQoUPK5fG/44kTgPXQueeei9WrV2ufPWj+kh4WHR0NAOjYsSO2bNmCTZs24a677qr0eq/Xi127dgEofQZEqFhgQSNL5ZTWRg3s5vSBtw0Ta/Zte+WOQspawO0Ru5zJKWtiGrEmic7ilROCLY3VV7MaPjnlz/DLCbKWEnXN4pNT/rrMkhOCS4TAzZLGmhTCxvLnu3dg5We3nAlKIuXt52ukToYGAHtsjLLd0KQA68SvO1H9Ts1i5ZowDu34gkmgNINMrQwmZdIjH4sB4fmxpkdzvpKSKanGWI9mizVHvnwHgCGkAOuSeSMs1U+YtxrB7c8WqPfnAOTx+YWk32DllMjfR1lCLQdy0nmJJlU4EFC/r0CJ3MdaJL9fKe3XKe8ucObK5zJnrvpz1CX92rM0z6AuUZ8rDE3qrPZcFhBqoU4B1p3vtd8F6vHpUuSl5HldP6b2EoVX2YSd1+tFSUkJ5s2bh3nz5omvnzFjBmbMmKGsGYaB7GzNSZsahAY2zdIw9O7dGwDw/fffi6/ZunUrAKBTp04AgP79+wMAVq5cqXx9amoqvF4vYmNjtVcWEhERERERUWgYZnj/Ufjk5+cjPz+//Fn8pmkG/a8sJ4AaNl4BWA8NHDgQERERSE1NxRdffIGBAwdWqO/fvx/vvvsuAOCKK64AAFx33XVwuVw4dOgQ/vWvf2HIkCHlr/d6vXj++ecBAIMGDYLFwnljIiIiIiIiopqSm5sb7iFQPcOZnHqoadOmeOih0tsK77rrLrz22ms4cOAAMjMzsXjxYgwcOBDFxcW48sorccMNNwAofW7gfffdBwAYPXo0FixYgBMnTuD777/Hvffei02bNiEiIgKPPfZY2N4XERERERFRg2Ia4f1HRPUGrwCsp5588kls2bIFq1atwqRJkzBp0qQK9UsuuQQpKSkV2p5++mls3rwZ69evx8iRIyvUbDYbZs2aJSYPEREREREREVHoHT58GIsXL8a+ffuwf/9+eL1etGvXDu3atcONN96I9u3bh3uIdAbgBGA9Zbfb8dFHH+Htt9/Ge++9h927d8Nut6Nr1664+uqr8dBDD8FqrfggaKfTiWXLlmHWrFn44IMPsG/fPkRGRiIpKQmPP/44kpKSwvRuiIiIiIiIiBqW3NxcTJkyBQsXLoTX6y0P8wSA1atXwzAM/PWvf8Vdd92Fp59+Gk2bNg3jaKmu4wRgPWa1WnH//ffj/vvvr3Ifu92OMWPGYMyYMTU4svqt05tyqmvsDvXDV2N+Pir28efnizXDZle2M5ntfwKaNGzD5VQXhDRBALB4NTUhXdHQhPJZNB+V1M+iCy4Ukh/PBOvc6uMjYNOkdLo0iZZNKieMA8DJbnKSadxW+XgTGfL4TE1NDB/V9dEwrep+GfIpCf5sOUW5/X/UO6ChScG0FWgSuQuFtN8CTWJ9QaFY8/O5ODXCd/BnsebMbSXWLF4hBViTsuvSnADthvpEJ7WX1uSTrUV4kr1D10dIDgbkNGLd+H62xYg1m0X9H2w+TdJvYYl8/JrSbXtCWjMA2ArkmiNH3e7KlreRI08+Vzhy1dvdli+fQ4wiOTEcXqGfLrVXl5grJARrk8l1qb3Sw/c1fUzdA/uFsQd0qcfBJsJT+Jm//AvXuilsAoEAhg4dijVr1sA0TZx77rm48sor0bZtW9hsNmRkZGD16tXYuXMn5s2bh4yMDCxZsgRGkH9LUv3HCUAiIiIiIiIiojokJSUFq1evhs1mw6uvvoo77rij0uSeaZp47733MGrUKKxZswYpKSkYNWpUmEZMdR1DQIiIiIiIiIiI6pCvv/4ahmFg0qRJuPPOO5VX9hmGgTvvvBOTJk2CaZr48ssvwzBSOlPwCkAiIiIiIiKiuqgO3ALsdruRlpZWqRwXF4f4+PhaHlTDsWXLFgDAzTfffMrX3nLLLXjuueewdevWGh4Vnck4AVjDPvnkE7Rt2zbcwyAiIiIiIiKqtvT0dGUg5MSJE5GcnByGETUMdnvp896bNGlyytdGR0cDAFq0aFGjY6IzGycAq2DNmjX46aefUFgoP4z81yZMmFD+v/v06VNTwyIiIiIiIqJ6zAAg5BjVyroBIDExEXPnzq1Uj4uLq90BNTCXXXYZlixZgi+++AJ33HGH9rWrV68GAPTs2bMWRkZnKk4AahQWFuL2229HampqlV5vmiYMw6gwAUhERERERER0pnK5XOjUqVO4h9HgTJw4EZ9//jnGjx+P9u3bo3fv3srXpaWlYdy4cXA4HHjooYdqeZR0JuEEoMb06dOxZs0aAEDbtm1x0UUXITIyMsyjorqg47sPirUmh+V+UYfdyvbAoZ/FPqbfH1SNqsBbomw2SnxiF0tJQK751D/PSu2ltcoP8y2vSR+vX+5j+uRspy4b1L8cbuv9ntinNt311f3K9viAvP1MTZSVqXhQMgBk9ZCPm2Y/yQu0HctVF3TH4S+3bqiYTvVXsGmTv5pNu1WsZV7UWNmePmC22EdrsLr5vHfkPyzPXiuP3Z6v3hY2h9zHsGo+4Lx8dbspH6NUBZrtZy/QnBu9TmV7wJTPV5EWr7wuQ70ul0V93i7tIx+LLkPuJ7EY1d+XApqTkicgnw9Oehop2w8VRIt9jmWrj3kA8GW5lO2OTPkc4swSS3Blq8/Drix5m9vz5f3FVqD+7C0F6r+TAADFmppXvTxT830On1yT+pk+eT8yNd9VPC8RUTBatGiBN998EyNHjsS1116LAQMG4Oqrr0bbtm1ht9tx8OBBrF27FkuXLkUgEMAjjzyC/Px8fPvtt8rl8e5E4gSgxrJly2AYBm6++WbMmTMHNs1/lBERERERERGFVB0IAaHwaNeuXfn/Nk0Tq1evLr/V99fK7kRMSUlBSkqKclmGYSA7O7umhkpnCM5oaezfvx8AMHnyZE7+EREREREREVGtSEhIgCHc0UIUDM5qaTRp0gRutxuxsbHhHgoRERERERE1NLwCsMH66aefwj0Eqmc0D9ehq666CgCwfv36MI+EiIiIiIiIiIgoOJwA1Hj66afRvHlzjBkzBocPa5IdiIiIiIiIiIiCEB0djaZNm55xy6YzC28B/oWUlDNlyhSMHz8eF110EW6//XZccsklaN26NeyaZEem69R/u+5+XazpEoJbfKF+8KpPSK+j02dY5cRDo7E6dVFKZwUA0yb/bmIIt0lYNCGEHs138b+HTVe2X+iIkDvVcc9ndhRrTdKk86omBdiqeS6KUDr/VfkByEaukCwLIJCjTgEOaJIpLS51MioAGE51zeKQv1/gcIilxgfUqZ+h9n/3aFKF75FLV/z5XmW7xS2/X6vmu9YaFals9xcUyIOg06MLMg3iNjEp6ReQ036dmjRfhyYFWFqXX/NbeIkpfxe4hUTfElP+zjnqkRN9DxbEKNt1Sb/+4/J3gStT/b4cOWIXuLLkDzFCSPt1ntSc/4rkv22MIo+6oDmfmkXFcs2jXp4uBViX6EtUlxim/Ddmbaybao9p1twGr8ll05mDE4C/uO6667QP2DRNE/PmzcO8efO0y2G6DhERERERERFV1wsvvBDuIVA9xgnAX7Rp04YJO0RERERERERU60zTxPPPPx/uYVA9xgnAXzBhh4iIiIiIiOoUE4AZpgtVeNdorbnzzjvDPQRqADgBSEREREREREQUJv/4xz/CPQRqADgBqHHjjTfCMAwsXbq0Sq8fPHgwmjdvjjfeeKOGR0ZERERERET1nonwXYn3y3rdbjfS0tIqlePi4hAfH1/LgyKiYHECUCM1NbXKzwUsKSnB+vXrYbNxkzZ0uoTgREOdENx+/P6g1mW5uIu6fd8RsY8vMzOodZ2prM3lP0rMZupERl9TdbooAHhj5FTS1W+8WfWBVYk64XFnSaHY43x7VIjHUH0XbrxDrPm3yCmYDiFhVJdAp00BFhgeOZkykJ0j14rlBMqg+gSxPBhyYmmkU50QPDP7HLHPY033VX8MQfJHqNNRAy45NdVql79TjUj18WFotqvpl1NiqfbZtam96pou6VdKDi5dnjoNtjAgJ3XrEn2LAurjLT8gp3Gf9Mrn58xCdc2XLS/PdVI+H0QcF/rkyFHOziw5MdeRpU7ZtWbJyelwC0m/AEy3Ou3X1PXxyp8vE32JalZ6ejqSkpIqtU+cOBHJyclhGBERBYOzVb+yfPlyfPrpp5XaH374YW0/0zSxc+dOFBcXo2nTpjU1PCIiIiIiIqJalZiYiLlz51Zqj4uLC8NoiChYnAD8lR9//BELFiwo//9lV//9uu1U/vCHP4R8XPXBiRMncPLkyQptHo8HdgufLEtERERERKRimPq7IWp63QDgcrnQqVOn8AyCiEKGE4C/0q9fvwr///nnn4dhGJg0aVKV+rdt2xa33XZbTQztjPfmm29i2rRpldrjm8m31xARERERERER0enjBOCv9O3bF3379i3//88//zyA0mcb0OkZMWIEBg8eXKFtyJAhsFsOhWlEREREREREREQNAycANZYvXx7uIdQb8fHxlRKinE4nLIHqP8CfiIiIiIioQagDKcBEVD9wAlDj11cDEoVC+l3qhODr37lV7GPkygl75i51erC/qKh6AzvDWWPl8B0p6RcASmLVab+6pN/PZqdoRiKnSQZjg0edyNjFXrdvnX/0/FVibfp/B4k1U/g9IKBJ+g3YgvgRQZMkGUzSb60y5QRP5Bcom5c9NEDs8ti/5p3eeH6jx9SHxFpEpHrs9gJ5fzY1+7oRqT5+LT45yTSQmyeviwnBp2SYof0vQV0KsMtQH6e6pF+XISd8u4QUYDfk870+BVh9vs/1ySnyWR65VligXp4tRx6D66RYQqMjQopyrrz9bHlyAq8lV/i7Qvc3ikeT6Fui/jx0ab48RonqD9M08c4772D+/PlIT0+HzWZD165dMXLkSFx//fXVXl5+fj6mT5+OJUuW4PDhw4iJiUHfvn0xbtw4XHDBBSEf/+7du/HSSy9h1apVyMrKQsuWLXHDDTfgiSeeQGxsbMjXRxQqnADUeOGFF6rdxzAMjB8/vgZGQ0RERERERA1JXQgBCSXTNDFs2DAsWbKkQntqaipSU1Px5JNPYsKECVVeXmZmJgYOHIj09PTytqNHj2LRokVYvnw53n//fVxxxRVVWlZBQQH69u2LjIwMHDlyBFFRUZVes3HjRtx8883Iz//fDyD79u3Da6+9hqVLl2LlypU4++yzqzz+YHz99df46aefUFJSgs6dO6N79+41vk6qHzgBqDF16tTyJOCqME2TE4BERERERERECrNnz8aSJUtgsVjw17/+FYMGDUJ+fj7eeustvPXWW5g6dSouu+yyKt+NN2rUKKSnpyMuLg4vv/wy+vfvj507d2Lq1Kn45ptvMHz4cGzduhUxMTGnXFZycjIyMjLEelFREYYNG4b8/Hz06tULkydPRpcuXfDtt99i/PjxOHjwIB588EEsXbq0qpujkuXLl2Pu3LlIS0tDbm4uOnfujMcffxzXXXcdcnJycMstt2Dz5s0V+thsNowePRoTJkyA3S5f2U7ECUCNO+64Q5wALCkpwaFDh5CWlobs7GycddZZePTRR+FwOGp5lERERERERER1m9frxYwZMwAAkydPxqhRo8pr06dPR2ZmJhYvXoyXXnqpShOA27Ztw7Jly2C1WrFgwQL06dMHQOmjvBYuXIgBAwZg7969mDt3LsaMGaNd1meffYZ58+ZpXzN//nz8/PPPaNWqFd5///3yZ9zfeOONaN26NQYOHIjVq1fju+++Q69evU45/t8aN24c3nrrLZi/euTGxo0bcccdd+Cdd97BsmXL8P3338PpdOLiiy9GfHw8du3ahbS0NLz00ktIT0/H/Pnzq71eajg4Aagxe/bsU77G4/Fg7ty5mDx5MlatWoUPP/ywFkZGRERERERE9V49CgH59ttvcezYMURERGDkyJGV6o8//jgWL16M1atXIycn55RX7S1evBgA0KdPn/LJvzIxMTG47777kJycjI8//lg7AZiZmYlHHnnklOMvu2156NChlQIue/TogSuuuAIrVqzAxx9/XO0JwNWrV+PNN9+EYRi4++67MWjQIDRp0gQbN27Ec889h7FjxyI7OxsJCQlYtGgRzjvvvPK+X3zxBYYPH46PP/4YX3zxBQYOHFitdVPDYQn3AM50TqcTDz30EKZOnYovv/wSr732WriHRERERERERFSnpKamAgD69++PiIiISvVu3bqhRYsW8Pv9+Pbbb0+5vG+++QYAcM011yjrZRNhW7duRW5urricxx57DMePH8e9994rvsbtdmPTpk1VWl/Z+6yO2bNnwzAMPProo0hJScFVV12FXr16YdSoURg3bhxOnjyJQCCAyZMnV5j8K1tvcnIyTNPEggULqr1uajh4BWCI3HHHHZgwYQIWLlxYpV8PiH4t7wI5LcqV3Vis2bPUiaVWKa0PEJNCASBQUKhuryPJqNZGjZTtRjN5+3njKj+8t7wWrX5Gxj0vLBH7rHXLy0uwqf+w+OPmEWKfRi45tfLv5/9H3cdSt0/dI6KPiLWXNQHGAeFtmZq3G9A85sS0Cb9xWYJIDj4T2NQbyrTKv/V1TB0q1izpwr6u2XxOzVMw/E51R1+EvFPYIuUFWoREWkPz+VqFbVS6MmH7FWrOpwlniSXDp0499u1MV7afETRXghhCQLXXH1xquV/4jdovxYUD8Bvyvu4VEn1z/PI5/ZBX/m455Fanzx8ukpPn92XKyzMz1SnAzmyxC5y58gfiyFGn6doK5O8cS6Gc2otit7JZm/TrldcVEFKAtUnnRA1VPboCcPfu3QAgXh1nGAa6d++Ozz//vPy1OmXBH9LyOnbsiKioKBQWFmLPnj246KKLKr1m4cKFWLp0KXr37o1HH30Ub7/9tnJZGRkZ8Pl8cDgc6N69u/I1PXr0AIAqjf23du3aBQC45557KtVuuukmPPfccwCAyy67TNn/hhtuwKRJk5CWllbtdVPDwSsAQ6RRo0aIiorCvn37wj0UIiIiIiIiojrlwIEDAKBNrI2Nja3wWklRUREyMzOrvLyDBw8qxzNhwgRERUXh9ddfh9Uq/2hVNp6WLVvCYlFPo5Stq7CwsHxsVXX06FEAwFlnVf5xsXnz5uX/u1WrVsr+Za85dOhQtdZLDUvdvozkDPLdd98hPz+f8dtERERERERUbyxfvrzKz7T77rvvxFpRUelV9Y0by3c4NW1aeoV1YaH6zqTfLgsovRhHt7yDBw+ioKDiXVCBQAAPPvgg8vLyMHPmTLRv31476Vi2vlOtq0xhYSGaNWumfQ+/1r59e2zfvh27d+/GhRdeWKEWExODhx56SAwoBVB+IVLr1q2rvE5qeDgBqFGV2XOPx4MffvgBU6ZMgWEY6Nq1ay2MjIiIiIiIiOo7wyz9F651h5LbXfo4Ad2VdlFRpY9mKD7FI4jKlhXs8l577TWsXbsWV199tfK2W2l9unX9enLwVOP/rfPPPx/btm3D3/72N7z//vsVJvsMw8C0adO0/V9//XUAQGJiYrXWSw0LJwA1unTpUuXXmqYJm82GiRMn1uCIiIiIiIiIiGrP9ddfjzlz5pz2clwuFwAgLy9PfE1JSekzTJ1O9bNRf7ssAMjPz0d0tPoZrN5fnkf669fv2LEDzz77LJo2bVrlEM+qjN37q2efnmr8vzVhwgR88skn+Oyzz5CUlITbb78dCQkJ+OMf/yj2MU0Tu3btwqxZs/Duu+/CMAzmEZAWnwGoYZpmlf5FRUWhT58++PTTT8sf/ElEREREREREpSIjIwEAOTk54mvy8/MB/O/KvVMtq7rL83q9GDFiBDweD6ZPn6585p5ufVVZF6C/VVilY8eOeOWVV9C4cWP83//9H6ZMmYL77rtP26d9+/ZISkoqT/59+OGH0adPn2qtlxoWXgGooYsKJyIiIiIiIqKqadOmDX744QdkZWWJrzly5AgAICEhQbusyMhINGvWDJmZmdrllYVrlD0bb+bMmfjpp59wyy234JZbbqnW2IHSKwD9fr/yVuCysUdERFTr+X9l7rjjDlxzzTV44403sHPnzlMGjHo8HjgcDnTr1g1PPvkkBgwYUO11UsPCCUCiOiD11dliLWnyw2ItspH6EHadcIh9rBFyzRIbo273lIh9oHm+hVlYpGw3IlzKdgBAs6ZiqSRe/Uuau5n8ntxN5Qudo+9SP+fzmbU3iX2i9tjFmi9S3e6PkB+gUuyQa0vOukjZ3u+sH8Q+dUEAAbmm+dYxhZpf3uTw2+WHIZtWoWaRn91yRhOOq4BDPgaarJJ/XS8I4hnSAc2m9TvVn0dJlDw+S4l8+0zTl44q24t88g7zfxltxZrjZ/V5xC7f6YPI4/LxG7dyv9zxTGXK79cQDnvd55HrF06aANym+nvHZcjLcwl9AMBu+JTth7yxYp89hfFibW+e+j/sjufID7YvOSF/90WcUB8HLvm/aeHKUr8nALBnq7+bjSKPvMAizfe5UDN/dbvbbwU0NSJqmMqeT7dp0ybxNdu2bavwWp2OHTti/fr12LRpE/r371+pvn///vJbdjt06AAA2Lt3LwBg0aJFWLRokbjsli1bAgB+//vf47333kO7du1gs9ng8/nw/fffIykpSRx7hw4dtIEdOs2aNUNycnKVXrtq1Sp06NBB+1xCol/jLcDV5Ha7sWvXLmzbtu2UyUREREREREREQTPD/C+Eyibp1q1bVyHFt0x6ejoOHDgAq9VapVtZ+/XrBwBYuXKlsv7VV18BALp161YhoTcYLperPAlZWt+XX34JAMrJyJpw3nnncfKPqoUTgFWQmZmJJ598Eueddx7OOuss9OrVC5dddhlatWqFjh07YsKECcjMzAz3MImIiIiIiIjqpEsvvRQtWrSAx+NBSkpKhZppmnj22WcBAAMGDEBsrHyFdpnBgwcDADZu3Ii1a9dWqGVnZ2PmzJkVXgcAs2fPRl5envJf2RV8QOntvHl5eXjvvffK2wYNGgQAePfdd3HixIkK69u8eTOWLVtW4XWhdOLECcybNw9TpkzBn//8Z9x5552YPHky3nnnnfJbj4lOhROAp/D555+jW7dueO2113D06NHytF+HwwHTNHHs2DG88cYb6N69e/mMPxERERERERH9j8PhwNixYwEAU6dORUpKCg4fPoxt27ZhzJgx+Pjjj2GxWDBhwoQK/Xr27ImePXvimWeeqdB+wQUX4KabboLf78ewYcOwZMkSZGZmYu3atbjzzjuRkZGBuLg43HvvvSEZ/9ChQ9GqVSscOXIEd9xxB7755htkZmZi6dKluOOOO+DxeHDFFVcobw8OVmFhIZ555hl069YNo0ePxiuvvILFixdj2bJlmDVrFh5//HH06NEDzz77rPKqSqJf4zMANY4cOYIHH3wQ+fn5OP/88zF69GhcfvnlaNmyJQzDwJEjR7B69WpMnz4du3btwgMPPIBvv/0WLVq0CPfQiYiIiIiI6AxnmKX/wrXuUHvggQewYcMGfPTRR0hOTq70vLspU6agd+/eFdp27doF4H+BHr82c+ZM7Ny5E7t27cLQoUMr1CIjIzFv3jxER0eHZOxly7v55puxceNG3HDDDRXq55xzDt54442QrKvMww8/jCVLlsA0TbRv3x6XXXYZEhISYLVasX//fqxduxZ79uzB9OnTsW/fPsydOzek66f6hROAGi+99BKysrLQo0cPfPbZZ3C5Kj68uWXLlrj99tsxaNAgDBw4ED/99BNefvllvPjii2EaMREREREREVHdZBgG3nnnHfTv3x/z58/Hrl27YLfb0b17dzzyyCMYOHBgtZbXrFkzrFq1Ci+//DKWLFmCw4cPIzo6GpdffjnGjx+P8847L6TjT0pKQmpqKl588UWsWrUK2dnZaNmyJW688UY88cQTiImJCdm63n//fSxevBh2ux2zZs3CkCFDKoWLmKaJhQsX4tFHH8VHH32Ea6+9FrfddlvIxkD1CycANX788UcYhoHnnnuu0uTfr0VEROC5557DTTfdhC1bttTiCOm3pme3U7aPaZpRyyOpHovmbvzCVnI/0yY99FVOzrQ7NQ+KlYYhh7rCCMg/DVpK1B1LhPRiAPBGyzVPtHqAZ9+9V+yT75W3xd7t6o3rzJM/D2+M/H7NNuqURH+unFIMU04I++pgR2X7u1EHxD7Pbv69WEsfME8eRwjde+BysWba5O0XEBJ9pXRgADA1u7OcAhxcKltdYHHK30WmkPAdcMjvV5faiyA2k+6z8guHYkmUvCJPEznx9eBB9fFr7I8Q+0T/LJZQeLa63a8JLXfky/uz77BmZWco3ZUgQsguikvk81++ZuOWCAd3iSbF221qEoINdULwUW8Tsc/+AvmB8Uez1P0Cx6uf9FtaU7dHnvCLfZxZcqKvkSXEV3vkPmaxW6wF3Op+pk9OXiYikhiGgeHDh2P48OFVen1Zkq+kcePGmDJlCqZMmXJa42rTps0p1wUA5557bsiv9FP59NNPYRgGnnrqKdx+++3K1xiGgbvuugtHjx7FX//6VyxdupQTgCTiMwA1du7cCaA0NehUevToUaEPERERERER0WmpRynAVD0//fQTAOCmm2465WvLgk5+/PHHGh0Tndk4AajRvHlzAMChQ4dO+dqy5B0+/4+IiIiIiIiITkd2djYAoGlT+Yr0MmWpybm5uTU6JjqzcQJQo2vXrgCAhQsXnvK17777LgCgS5cuNTomIiIiIiIiaiB4BWCDVTa38N13353ytZs2barQh0iFE4Aaf/rTn2CaJlJSUvDCCy+goKCg0msKCwvxwgsvYNasWTAMA0OGDAnDSImIiIiIiIhCz+12Iy0trdK/EyeEB5hSSFx88cUwTRMTJkwovxpQJTs7G0888QQMw8DFF19ciyOkMw1DQDSuvfZaPPDAA3jjjTfw/PPP47XXXsPFF1+MNm3awDAM7N+/Hz/88EP5ZbYjRozAtddeG+ZRExEREREREYVGeno6kpKSKrVPnDgRycnJYRhRwzBu3DgsWbIE+/btw8UXX4yRI0eif//+FeYjUlNTMXv2bJw8eRJt2rTB2LFjwz1sqsM4AXgKzz//PM4//3y8+OKLOHLkCL7++utKr2nRogXGjx+Pe+65JwwjbHjm5snPWZRSA89k3lg5gtcIqC/iNQ15O9ibVP/CX1PTJWCrflRoSSO55ouSa96uhcr2TYmfV3sMAPB6a3WK6CvbrhD7GAH5/e7q909le7tlI+RBWOTPNy9LvTGe3iA/CNiwyPdqfFWs3i+ujJBTJoOx5vtOYs3ulbefVQiglNoBwOqR36/hF2oWeYc2rPKxY/pDu52Mnhcq20/2aCz2afGVnCzrdwkpwJpjVHdsByOgSwGWwmAj5fHZ1MHaAADXVnXab9QReZ+IPC5E1QJofEi9MfyaFOXGX6aJtdDuLaFn7XKest2/7f/kTqYm9V14w8Ul8k5RIEVDA/AIO5PTIif92i3y5+sx1P0yPfIX0sl8+QvJn6Uee8Rx+aCKPCqWEHlSvQFdJ+TUXmtm5TtTypg56mdAmSXyNgp4vWINpvxdRUQ1yzD1Kew1vW4ASExMxNy5cyvV4+LianlEDUt0dDTmzZuHYcOG4eDBg3juueeUrzNNE61bt8Y777yD6OjoWh4lnUk4AXgKVqsVw4cPxx133IG1a9ciIyMDGRkZME0T7dq1Q7t27XDZZZchIkL9HyJEREREREREZyqXy4VOneQfeKnmXHzxxfjhhx/w1ltvYdGiRcjIyEBmZiaA0uCPdu3a4ZZbbsGIESPgcEi/thKV4gRgFblcLlx11VUV2g4fPowNGzZg7dq1uOSSSxATExOewZ0BTpw4gZMnT1Zo83g8sGuuViIiIiIiImrQwhnGwf9UqxMcDgdGjhyJkSNHAgDy8/NhmiaaNGkS5pHRmYYTgKeQm5uLv//97/jhhx+wYMGC8njtJUuW4MEHH4TbXXpvWlRUFN566y1cd9114RxunfXmm29i2rRpldrjm9W/W3aJiIiIiIiIakLjxvLjYoh0OAGokZ2djX79+uHQoUMAgECg9PknWVlZePTRR1FcXIw2bdoAAA4cOIC77roL33//Pdq1axe2MddVI0aMwODBgyu0DRkyBHbLoTCNiIiIiIiIiIioYQjx47/rlxkzZuDgwYNo0aIF/v73v5c/UHPp0qXIzc1Fz549sXXrVvz000+45ZZb4PP5kJKSEuZR103x8fHo1KlThX9OpxM2a/UDJIiIiIiIiBqCshCQcP0jovqDVwBqfP311zAMA7Nnz8YVV/wvFfTTTz+FYRi45557YP0lMXLcuHFYtGgRvvvuu3ANt8HI8UeGewghN/boRWLNjJVT+Yqt6ge9+h3y3L69UJ50tQhhg5pgRe0fBr+7d6Oy3alZYHpBc7H2Yfsv5ZUF4cHow+r2vu+KfbZ6NZG0cClbDYcuDzSISXDNNndElIi1c+zqVEhAE8uscd3/Xa9st/g0Sb9yoKWY+OrIl9+wM0+Tki2kAJsuOUXU2jxerPmOqCM8LZoQqLNXy485eDthgViTzB0rp6DPn/AHZbu3UXC/9Vk1CbwS7blC+qh0KePyR4Woo+rP1+aW9xe/U943nZnqc63jSJ7YR5uaWktsieeKteOXy/tLkVBq3aS72EdM1gZgCJ+92yt/iFklcsquRTjRWcQdCbBovpCswvIOFchpiUV58rFtz1Ef284csQtcOfLY7XnqDWgp1OxjbvmEKqX9mj75O4JJv0RERPUbrwDU2LdvHwCgd+/e5W2maWLjxtJJjQEDBpS3n3tu6R/g+/fvr7XxERERERERERERnQonADUifrmqw+P53y+sP/74I3Jzc9GmTRu0bt26vL2kRPOLKhEREREREVF1mWH+R0T1BicANcrCPFJTU8vb/vOf/wAArrnmmgqvLbsq8NeTgkREREREREREROHGZwBq3Hrrrdi4cSNGjx6NkydPori4GG+88QYMwyhPtC0pKcGaNWswevRoGIaBpKSkMI+aiIiIiIiI6oVwXonHKwCJ6hVOAGr8+c9/xsKFC7FlyxaMHTsWQOkzAK+//nr06dMHAPDGG2/gqaeegmmaiIiIwJgxY8I5ZCIiIiIiIiIiogo4Aahht9vx+eef4+9//zvWrl2L4uJi9OvXD8nJyRVe53Q6cdFFF2H69OlISEgI02iJiIiIiIiIiIgq4wTgKTidTjz11FNi/d5778XDDz8MwzBqcVQNW64vUqxZjUAtjiR0duU1F2vxcfliLTfSpWz3NHKKfXw5drFmz1Pvx7ZCsQtsbrn28lk/yEWJvClE32jG0MMhFxtZ1NtPZ19JM7HW3aHeUBa7vF+aAfncYfrVtWsv2C72ebj5KrGWE3Ao2zMD8gecXiLvS/+X0VLZbvXK78mq+azsher7TJy5frGPLV8OYDL86uUFXOrtAACWuBh5XZERyva8bvJOO6PVTLEGqJenM7zJMbk2e46y/eK/PiT20Z0yHXlCQXM7kKG7VUio6cZgyB+9PA7d+DTrCjis6sVFaPaXxo3k5RUXyysLoZN95P2vRB4eIBymnlj5/bqOy+/J4hXG4Jb/1Mz0RIm1gKkeoNQOAD5TfrS1L6CunciVN5KRK4/dkatud+bKO6AzRz5f2fM8ynZLoeak6VH3AQDTp16X6dcdVERUFxnmKb5fa3jdAOB2u5GWllapHhcXh/j4+FoeFREFixOAp6ksKZiIiIiIiIiovklPT1c+637ixImV7o4jorqLE4BEREREREREpJSYmIi5c+dWao+LiwvDaIgoWJwAJCIiIiIiIqqL6kAKsMvlQqdOncI0CCIKFflhKURERERERERERHTG4xWARERERERERHVRHbgCkIjqB04AUp302M+XiDWbRU6ws4YrIus0PZrwpVh778SlYi2vsTrF9mijxmKfEZeuFWu73Gcp25cs6iv20aUAd39RnT66dfxsuVMQ+mnDfOWix1SnJKaVyPvYIDm0UqQLCTc1u6w9wqdsX7H1QrHPCrNrVYdV7un+H4u1Pzc5LtbOa3dE2Z5xuK3YR7e/OPLVG8ORI8SLArAWq7cRAASc6q84f5SchO2LlhNQTUOdFprXRp0eCwC/33G7WEvtskSshZJPk1Vl1yR82/PUn4cmhBWaEFaxZlrkBRoB+QART/e68VnlYsCurvkj5X3CpkkBthapE3P9BQViHx3bue2U7bpt7hA+QwBwZarbo7YeFvsEWjQVaxbhUPRrUoCz3fLO6fGr+/n88hv2+uVjscSnrnly5O8IV468LqeQAuzKlr8/7FmaFOV84eSYL+8vgcIisca0XyIiIvot3gJMRERERERERERUj/EKQCIiIiIiIqI6yDA1V73XwrqJqP7gFYBERERERERERET1GK8AJCIiIiIiIqqLGAJCRCHCKwCJiIiIiIiIiIjqMV4BSGF1qCQSd+4bUKndoUn6tWtqDiGGUJcqbDECYm1Gy81iLZSuFtJeAeDqNt/UyhgA4NwvBivbHXKwIiBvPm06ZW3ZWSLHnN7+3+HK9i09PwjpGNIHzBNr69zyBrzrq/uV7UaJZsNqPg9J34i9mqqccrrivOXK9mvMG8Q+Of9MEGuOXPVxYMuUky6NgPyGTas6YdSM0CSFNpK/Fkui1Nv90ju2in1eb71erIXauV/eo2yP0KRkO3N0KbHqz8O0yUm6foe8bwaE8GW/HMqsTfSVrkrQnXcCmrFLv4kGXPL+Emgkp9haPNHqdk06a6BYToktuCBe2a5LUXYUyMdHzPfHlO2+Q3IKsKWZ+j0BgFUI6zbc8geS55F3TrdXSAEW0nwBwOfVfFYl6potR+7jyBFLcOaot60jyyP2sWTmyQssVqcAm0I7AAQ0NSIiIqLf4gQgERERERERUR3EEBAiCpU6cH0OERERERERERER1RReAUhERERERERESm63G2lpaZXa4+LiEB+vfkQFEdU9nAAkIiIiIiIiqovqQApweno6kpKSKpUnTpyI5OTkWh4UEQWLE4BEREREREREpJSYmIi5c+dWao+LiwvDaIgoWJwApLAKmBbkeCunKLqsciquy1oi1u44S524+d7JS8U+lrD9pFb37PnjG9Xu03vig2LN00SdTtn5jYfkPrFyaqWrdYGy/dmuS8U+8w5fK9YMXSBoCBWbcirk3WtGijXDp35Mq8WrGbipq6mbE+1y0m8wPj//U7k4VS4lJav3pYit2XInm/w1ZnGq42WNSDl2Vrf5AsKqQp30q0uuvv7Tx8WaI1OdZmqVQ5TF5FYAsJSodxhd0LRh1ZxPtQm8arrPQ3qKsTbpV/M0cylNd88f5f3FWuwUa20+j1S2u36UN7rRoa1Yy2+t3gH9DrELdI96NrNzdB2VDE2CsbS/WDzyGArd8uBLPOr3G9Ak/UKzLkOo2Qvl/cUmhzLD5pber/z3CzzyZ2+WCKnbmm1ORA1ImP9zxeVyoVOnTuEdBBGdNoaAEBERERERERER1WO8ApBqxYkTJ3Dy5MkKbR6PBwG/7loSIiIiIiIiIiI6XZwApFrx5ptvYtq0aZXa7TGVb/8lIiIiIiIiwPjlX7jWTUT1BycAqVaMGDECgwcPrtA2ZMgQHPNpnu1FRERERERERESnjROAVCvi4+MRHx9foc3pdMJi8jGUREREREREREQ1iROAFFb+gIEcd+XbgO1WOfXOqUkInnFwoLLdoVmew6JJ7BN4TDmJ2GnIiZH1kTNXfo6jz6VOazQ0m9wIyDcbuAvViZHTdslJv1EOOXWxXUyWPJAgfFrkUrY//v1QuZMu1c2n3haGJgVYt/2MED9y84AvX9nextY4qOXFbTipbPcdPyH2sTaW12U0jlIXAurPqbSTXJJSgDv8S07Cdh2XF2gKy/Npnozg1Bw79jyhXQ4VhlVIMtUS0nIBQPebjlTT9tEEvkr9NEG/MK2asf9Jvf8ZWfI+5tec7z1N1R+wpXOC2Ce7o7xvBoRVWeWvI1i98sbwZ1X/CnzDJ59EpERpW7G8zb3F8vYLeITvD7e8w+gSh61u9ThsmuPDXiRvP2ux+u8KwysfpKYuBdgr1HQpwCafo3xKRpA/NHPbUl1iInwpwGFOHyai0OLlV0RERERERERERPUYrwAkIiIiIiIiqoMMU391e02vm4jqD14BSEREREREREREVI9xApCIiIiIiIiIiKge4y3ARERERERERHURQ0CIKEQ4AUhERERERERESm63G2lpaZXa4+LiEB8fH4YREVEwOAFIYRUwLcgrdlVqt1n9Yh+HpmazBpTtdk2f1Rd8rBmhmtOwV7tPfXX4d4ZYa/qTut3UnHlMi/xT43WdtyvbhzVbJ/bp6pDXFerP8cntg5TtFs17glVTc6j350BAfnqDxSsvbtfQ1+ViEAZ8OVrZ7sqQN3rb5XlizTh6qNpj8BcUijWbp0S9noC8zU2LvD9LtZidYheYVrkWEI4Dm/yWYPHJNVuxut1eJL9fa0n1f9o35U0EGNXfftptZNWtLMRM9XFl0Ryjfk3t+MXqN+bIrfydV8au+eylWtymHLFP4L875AUGwyd/l1o96m1h8cifYcAtf/iWYnXN4paXZyuWa1a30KdI7AKb7thxq7eF4VafdwAg4PHIK/Orlxco0Rz0DY0hf/cZmnN3MEzN96ymU0jHQFSuDlwBmJ6ejqSkpErliRMnIjk5uZYHRUTB4gQgERERERERESklJiZi7ty5ldrj4uLCMBoiChYnAImIiIiIiIhIyeVyoVOnTuEeBhGdJk4AEhEREREREdVBhln6L1zrJqL6I4gHXBAREREREREREdGZghOARERERERERFQrTNPE3Llzcfnll+Pss89GmzZt8Pvf/x7Lly8Pann5+fl45pln0KNHDzRv3hwdO3bEPffcg+3b1QGCZT777DP86U9/Qrdu3dCyZUv06dMHDzzwAHbv3h3UOIjqOt4CTGEVCBhwF1dODLUIab4A4NbUrBZ1bVvv96o/OCrXZcMdYu3CizLE2uLbvqiJ4SjUXirzV0IyJQAYwn0SuhRgq13en/1C3KqpuR0j/dY35WKItUk4qWzP+fFsuVNAk5Koe2MCi13zNWZTf1amVf7tK6DZlYSQWLS9W/4jMbHRcbG2aualworkMVjlgFFYvOqOuqRfi1fzeUihmpqwTWkb6WpZXeQ+o65ZIdbe399T2e5dFi8vUDf2z5op233d5I1uaCKRpXRZQ7PJpWRoAGh8UD2OkCf96uhSgIX9TErfBeSkXwCwCom+UjtwikRfISXbUSAfH/ZCzfstEtJ53XLSr6lJ9DV9moO7IQk26Vfop+tjahLhDeHvSR1tcjATgul01IEU4JAu0jQxbNgwLFmypEJ7amoqUlNT8eSTT2LChAlVXl5mZiYGDhyI9PT08rajR49i0aJFWL58Od5//31cccUVlfo9/vjjePvttyu0bdu2Ddu2bcOiRYuQkpKCIUOGVOp35ZVXYtOmTdoxvfLKKxg+fHiV3wNRbeEVgERERERERERU42bPno0lS5bAYrHgb3/7G7Zv344NGzbgvvvuAwBMnToV69atq/LyRo0ahfT0dMTFxWH+/PnIyMjAihUr0K9fPxQXF2P48OHIycmp0Oerr77C22+/DYvFgtGjR2Pz5s04cuQIUlNTcfXVV8Pr9WLcuHE4dOhQpfXx6kA6k3ECkIiIiIiIiKgOKgsBCde/UPJ6vZgxYwYAYPLkyRg1ahQSEhLQuXNnTJ8+HYMHD4ZpmnjppZeqtLxt27Zh2bJlsFqtWLBgAQYPHoxmzZqhb9++WLhwIdq3b4+srCzMnTu3Qr+y5d9999149tlnkZiYiKioKHTv3h3vv/8+OnbsiLy8PHz44YcV+mVmZiI7OxsOhwNZWVnIy8tT/uPVf1RXcQKQiIiIiIiIiGrUt99+i2PHjiEiIgIjR46sVH/88ccBAKtXr6501Z7K4sWLAQB9+vRBnz59KtRiYmLKryr8+OOPK9TS0tIAAHfddVelZTocDtxwww0AgB07Kj5mo+zqv44dO8Jm49PU6MzDCUAiIiIiIiIiqlGpqakAgP79+yMiIqJSvVu3bmjRogX8fj++/fbbUy7vm2++AQBcc801yvrAgQMBAFu3bkVubi4AIC8vD1lZWQCANm3aKPs1adIEAMr7lCmbAOzUqdMpx0ZUF3ECkCrwer2YPn06evfujRYtWqB9+/a47bbbqnQCJiIiIiIiohAyw/wvhMom0Hr16qWsG4aB7t27V3itTlnwh7S8jh07IioqCqZpYs+ePQBKJ/fKbtVt2bKlst/GjRsBAJ07d67QXraMNm3aYOrUqejTpw9atmyJ3r174/777z9l6jBRuPG61QbmL3/5C1555RW89NJLuP/++yvU3G43brrpJmzYsKG8rbi4GJ999hlWrlyJlJQU3HnnnaEdkAn4iyvvhn5NaupVF6SJtTmtOVFZE87kFOWxRy8Say+f9UO1l3dlhJwKeVu7Lcr293ar00oBwHTIqZASf4j/GNvqlWM6/7TwcbFmJBYo222R8rqMEA/eiJRXZrrUkb5+p/zbl98uJ0YOH/2Jsn1kTOUHRJeZfFyOuJVScQ15F4MmdFZMuNUm81rlBUoBmaYuVVP3s6I0vng5NXXm95VT+8o03eCs1npKVyaXxNBjhyZ5Pkf+M8oqvC3dZxiQQ3HhOqI+3jS7S+hpPnvp2NYmV3vk5VndQgqwJlVY2uaAnAJs9WhSsjUJ2kaJsOW1SedMgj0twSQEW+WDytA93Ew4UE1/rR5xRPXOgQMHAABnn322+JrY2NgKr5UUFRUhMzOzSssrLCzEwYMHcdFF6v8uKCkpQXZ2NjIyMvDuu+/is88+Q0xMTKVn+ZVNSs6YMQOBX53vd+zYgR07dmDx4sWYOnUqRowYoR07UbjwCsAGZP369Xj11VfF+pQpU7BhwwZEREQgJSUF6enpWLVqFQYNGgS/34/Ro0eX/+pBREREREREVFVFRUUAgMaNG4uvadq0KQCgsLCwSssCgEaNGp1yeQUF6h/SAOB3v/sdOnTogKuvvhr//Oc/ceGFF+KTTz6pdItw2QSgw+Eo/2/ngwcPYsWKFbj00kvh8XjwxBNP4L///a927EThwisAG4j8/Hw88MADFX6p+LUTJ06UpyOlpKTg1ltvBQC0aNECb731Fo4cOYKNGzdi1qxZeOWVV2pr2ERERERERA1WTaTxVmfdALB8+XLxNtvf+u6778Sa2116GbdVc3VuVFQUgNI70XTKlhWq5f1aRkYGPv30U3Tt2hWG8b8rgh0OBzp37oynn34a1113XXl73759sXz5clx//fVYv349Jk2ahOXLl1d5fUS1hVcANhCTJk3Cvn37xPqKFSvgdrvRtm3b8sm/Mg6HA6NGjQJQmqBkmmH6BiIiIiIiIqIzksvlAlAaxCEpKSl9doTTKTzq4zfLAkovdpF4vd5Kr/+ttWvX4uTJk9i8eTOefPJJBAIBTJs2DZMnT67wutWrV2PDhg0VJv/KWK3W8tevX78eHo/muRREYcIrABuA5cuX45///Ce6dOmCyMhI5a8yZYlMZUlJvzVgwADY7XZkZmZi+/bt6NJFfq4VERERERERhUANhHFUa90Arr/+esyZM+e0Fxf5y7Obc3JyxNeUTeaVXbl3qmWVLa9169antTyHw4HExERMmDABLVu2xCOPPII5c+Zg3LhxiImJ0fYt07NnTxiGAb/fjz179lQKESEKN14BWM+dPHkSo0aNgsPhwJw5c8RfUk6VoNSkSRN06NABQNUSmYiIiIiIiIjKlD1TLysrS3zNkSNHAAAJCQnaZUVGRqJZs2anXN7Ro0cBQJwgVBkyZAhsNhvcbnf5fydXhcvlQlxcHAAgOzu7yv2IaguvAKznRo0ahRMnTuDZZ5/VXrV38OBBAECrVq3E15QlMpW9NiQCBowCxTMbNCmJX36nufqwgaUALypUP0B3WWZ3sc87bb6podGEjy5pNZik32B9n9NW2W7RPLjFZpVTIS1OdXyms3HVn2Hya723/lHZnrc+Xuzji5fHd2vij8r2jfM1z4jRPULA0MW3Cl0i5Ns5Ak51CnDAIf/2FVB3ASCn/f4jR/6DcsU/+ok16e1qkyk1m8gUHn9jBnSpvZp12dT9dEm12hRgQewa+TMMZnnV34vKVqZutrvkpG4z4BBrvgh1u9WrGYIusTmI4yPkdImqwvazaFKApaRfQE701aUA27QJweoB2tyaFGCvnPhq+IT9gimxp0VM8z1FTUwI1h03uvNLQFqeJhnaIn9fmtLymAxNDUxiYiIAYNOmTeJrtm3bVuG1Oh07dsT69euxadMm9O/fv1J9//795bcbl13MMnfuXDz11FPo27cvPvzwQ+VyHQ4HmjRpgqysLPh+Od+np6dj//79aN68Obp27arsV1JSUj4ZWZXxE9U2XgFYj7377rv49NNP0bt3bzz66KPa15alKJ1ughIRERERERGFiBnmfyFUNkm3bt26Cim+ZdLT03HgwAFYrVb06dPnlMvr16/0h9aVK1cq61999RUAoFu3buX/LdupUycUFBTghx9+EJ9tn5mZWT6R16lTJwDA9u3bcfPNN+O2224TgzV//PFH+P1+xMTEoHnz5qccP1Ft4wRgPbV//35MnDgRUVFReP3112Gx6D/qUCYy9erVq0r/9u7dW813RURERERERGeiSy+9FC1atIDH40FKSkqFmmmaePbZZwGUPn++7O4zncGDBwMANm7ciLVr11aoZWdnY+bMmRVeBwBdunSBw+HAiRMn8P777yuXW9YvMTGx/Pl/V199NVwuF37++WfMnz+/Uh/TNPHcc88BKL2FmKgu4gRgPRQIBPDAAw8gPz8fU6dORfv27U/ZpywVSZegVNVEJiIiIiIiIjp9hhnef6HkcDgwduxYAMDUqVORkpKCw4cPY9u2bRgzZgw+/vhjWCwWTJgwoUK/nj17omfPnnjmmWcqtF9wwQW46aab4Pf7MWzYMCxZsgSZmZlYu3Yt7rzzTmRkZCAuLg733ntveZ/GjRuX3x03ZswYvPrqq8jIyEBRURF27NiBsWPH4tVXXwUAvPjii+X9oqKiMHLkSADAhAkT8Morr+Dw4cPIz8/Hxo0bMWjQIHz11Vdo1qwZJk2aFNoNRxQifAZgPfTqq6/i22+/xVVXXYV77rmnSn0iIyNRVFSkTWQqe36C7jZhAMqUYZVevXphTw4fjkpERERERNQQPPDAA9iwYQM++ugjJCcnIzk5uUJ9ypQp6N27d4W2Xbt2AfhfoMevzZw5Ezt37sSuXbswdOjQCrXIyEjMmzcP0dHRFdrHjx+PtWvXYsOGDXjqqafw1FNPVajb7XY89dRTuPLKKyu0T548GVu2bMGqVavwl7/8BX/5y18q1BMSEvD222+X325MVNdwArCeycjIwHPPPYemTZviH//4R5X7JSQk4OTJkyFPUCIiIiIiIiICAMMw8M4776B///6YP38+du3aBbvdju7du+ORRx7BwIEDq7W8Zs2aYdWqVXj55ZexZMkSHD58GNHR0bj88ssxfvx4nHfeeZX6uFwufP755/jnP/+JRYsWYc+ePcjKykJiYiI6d+6M0aNH4/zzz6/Uz2q1YsmSJfjggw8wf/587N27F4WFhbjwwgtxySWXYMyYMeW3DBPVRZwArGcOHz4Mr9cLr9eLjh07iq8bN24cxo0bB6A01bdjx47YsmULNm3ahLvuuqvS671eb/kvL6FMNDICgK1QcSe65nJz0xbia9HPYBOX3KlstxXKqXcXFsmJuR8+/JKy/Xx7VPUGVssGNtkW7iEAANKOtVC2BzQprLqalBqYmjRHMwr5s5qYuELZPqh7oWZ5skufeFDZHlGiif3UJDIawjNIDZsmmlfzSIKAU/0V53doPg+7XDt/3d3K9shV8lXRutBKKa7W1CX96mrCynRJv6ZVlxBcvfUA0H6+urHLnTSrEsIzDV3StG55Qi3g16RGR8gLDDjVtYDqO+8XNs0jdg3hgeMWpyYJ26OJxRVYHHKysenQREAH1O9XmwIsJP0CctqvTdtHk7herK5Z3XIKq9WjSwEW+gmfEwCYwjaiEBDOS8YpnoEtMYUTjPY0pjvJSScYTR/zTE6UllKZdZiILKuBMI5qrbsGGIaB4cOHY/jw4VV6fdmdaJLGjRtjypQpmDJlSrXGMGzYMAwbNqzKfcr6DRkyhM/5ozMSnwFIAP6XyCQlKKWmpsLr9SI2NhZdusgTSEREREREREREVLdwArCeueyyy5CXlyf+K4tKf+mll8rboqOjcd1118HlcuHQoUP417/+VWGZXq8Xzz//PABg0KBBp0wUJiIiIiIiIiKiuoMzOQQAiIuLw3333QcAGD16NBYsWIATJ07g+++/x7333otNmzYhIiICjz32WJhHSkRERERE1DCUpvGaYfoX7ndPRKHEZwBSuaeffhqbN2/G+vXryyPOy9hsNsyaNQvt2rUL0+iIiIiIiIiIiCgYnACkck6nE8uWLcOsWbPwwQcfYN++fYiMjERSUhIef/xxJCUlhXuIREREREREDUcdCAFxu91IS0urVI6Li0N8fHwtD4qIgsUJwAbm008/1dbtdjvGjBmDMWPG1NKIiIiIiIiIqK5KT09XXgwyceJEJCcnh2FERBQMTgBSeAUAe4G6XeziNGpsOGea9DtfV7af//ZDYp+AXV7en2aOU7Z3vXWH2Kdb40NibVzsHnllIbTd00qs9XMdrpUxAMDvz92ubP9oezexT8AvP4p179VzhUpUdYZVblBUYbX7fFbsEGsB4RvEF2kV+5TEuMSa3d9M2W6NaSL28TdtJK+rkXqAfs05JCAPHTv7vqts39DTJ/Z55PlR8gKFX/MNzfkvGKbmPQVMeVtIz/3RLU+zOOS3VRejNIeo7tlDFr+6qNt+utqxy/zKds3bhWmTB2ha1DV7rnzM67afkZ2vbm+kOR9YNPt6cXG1l2faqv9no6VE3kYWjzw+i1fdbnXLy7Npa+oP3+pWf+4AYHjlYxs+oV+AD8yqMYbm0eWGsC9ZdUewbnHq5Wk/Xd35VDiZmfLupz8BmiH+oggxQ3PukcmflSkdV3V8O9QniYmJmDu38t+lcXFxYRgNEQWLE4BEREREREREdVBpCEj41g0ALpcLnTp1Cs8giChkmAJMRERERERERERUj3ECkIiIiIiIiIiIqB7jLcBEREREREREdVEdSAEmovqBVwASERERERERERHVY7wCkMLKMAGrIojQKqT/AcAPj86u9no2eUrE2iVOTSzuGSqhz0GxdnBdgtxRCG07Xiwnrc5dMVCsze7gVrb/87K3xT59XdX/XWJexqVi7cUTcoKsIaR0WqyaZE9dQrVPGHtATsMzpT51xKRX7hVrNuHQ8UXK78nQxFCb1sbqPn55o/sj5K+xkij1OAJ2+fPI6apJ/RT0dspjsHo1CajCacnik/sElXBrBrc86Xxg+DXpjpq/KpxZ0hg020iTkCmly1o9muVptm2zhBxle05epDyICHmAjbapE7Rbf3ZS7GO45e8qMdHXIR9ThimnbluFdFQjUn6/AbsmUVUYn/4z1NSEQzHYlGeJqUsrtQSTOqs5/2kSaU0f00xPhyF9VtLnBGhTsqV+2mxbzbnWFHbOYLJygTN4f9ElOWu7qd+vGdAsrx5duVYXQkCIqH6o2//lSURERERERERERKeFE4BERERERERERET1GG8BJiIiIiIiIqqLGAJCRCHCKwCJiIiIiIiIiIjqMV4BSERERERERFQHMQSEiEKFE4AUdqpQ0JRR1U/6BYC5eS2U7auyzxf7vNt2TVDrqsvuT/hGrCVH3C7WTKs6j27/2jZyHzlkEpZjTmX70GUPiX32/PENeYGC29t+L9YuOn+fWOsnjL3dshFiH+0fQlLaryasz6JLVA2x13NbKdv/8fZNYh9hlwAA+NUhp8iRDzfE/iSnYErpwYYmRTSg+RaT0n79mhTgvTe9KS8wCLpEcymt1lIS2nTHYP94N6UUYF2opiZEOUJIAdZ9hroUZVuRejtJ7YB8jgOAzH1Nle2OeEVU/S90h6+9SN1u5AsFANAkXosJo5oPxHCqz8EAAKkWIZ/UTbt844i0v+huH9MlBEvHfdD/MSqNTxciqjsBSmm/mqRffQqwJhKZTk06DjRJv7rPQ9rRtLufLnFdGJ9ueYapOZdJabqaPrXJFNLdDc0mD4ahS3KuG5uCiKhO4QQgERERERERESm53W6kpaVVao+Li0N8fHwYRkREweAEIBEREREREVFdVAdCQNLT05GUlFSpPHHiRCQnJ9fyoIgoWJwAJCIiIiIiIiKlxMREzJ07t1J7XFxcGEZDRMHiBCARERERERERKblcLnTq1CncwyCi08QJQCIiIiIiIqI6iCnARBQqnACksLI3LkH7G/ZWau/sKNT0ihIrF7n2K9v/mLBPs7wITe3MtOBIb7Hmd8nf5KZdqEnptqdiUS8vMiE/uOUJDnhixdpjTfdVe3kZv5eTYD2mnNTYZeEoZbv2jycxOhM4f93dyvbr2u8Q+3y+pJdYswhDt+qCRzUfvalI8AaARgfkTt4m8vJKhP3M0CX5abattN0dg45rFhhaVrc8eJuUAuzVJT9qVialTGr7aGpCAqouuVW3vIDwgRiaKF1dArR2vxAc6SPstACid6rb8xrLfypFpQlR2ADOWpSubDd9clSyISV7AoBNiM+0af6Us2tqQj8zQn5PAYcmxVYYuu78J52TAPnzDfZ8IB0HpiZF1LRoUo+FmqHpY+g+D2/dTnWtE3SJr9LnoUv61XxW0o6rO2WawXxWft0JtR7SbSPd+U9XIyKiKuMEIBEREREREVFdZJql/8K1biKqNzgBSLXixIkTOHnyZIU2j8cD089ftomIiIiIiIiIahInAKlWvPnmm5g2bVqldkeMKwyjISIiIiIiIiJqODgBSLVixIgRGDx4cIW2IUOG4LgvO0wjIiIiIiIiqtsYAkJEocIJQKoV8fHxiI+Pr9DmdDphSE8NJyIiIiIiIiKikOAEIIVVpNWLPs32VGpvZpGTfnVcQmTkJ4UJYp87G2cFtS7Ju/lxYu1vP16nbL+41UGxz+w2K8RaE4s6wdinmVg1I+TEuYCQxjnrynfFPqO/GyLWerY9oGx3+0N76lm8tYdYS21xrljb1OPDaq/rmN8t1uz5Qj5gsCmsPzVSNn+xVZP0qwkUHHG3el/SJSV3f/EheYECbeqsrp8Q1mjIoamwaGpSguyHXeZpRtFYU1Pr9Ka8jZrrEl9L1M9AtQjtAGAKSb+lHdU/02tTTrWRlkK7po82tVcYu18TxH5MDjSHvblH3W6Xt7nTKifMi2+3QH5URavVBWLNd/yEenmaVFLDISfwWiIj1QVtCrCceiyl/fojNSnAdl1KZ/VTvHXHr8UvpLCG+NHBQadk24RtIaU1A9rPyiIkBJsB+fIbU5cgW9fTg4VUV8Mm77OGbl+3Cp+HLulXt7xA9bef7vxnSqnCuqRpTfKtIZzXzboSKizuf5rjI4iEYGk7lBaD/GOEiKge4wQgERERERERUV1kQv6VqjbWTUT1Bu+/JCIiIiIiIiIiqsd4BSARERERERFRXRQI/eMPqrNuIqo/OAFIREREREREREputxtpaWmV2uPi4ioFPRJR3cUJQCIiIiIiIiJSSk9PR1JSUqX2iRMnIjk5OQwjIqJgcAKQiIiIiIiIqK4KcxhHYmIi5s6dW6k9Li4uDKMhomBxApDCqsS0Yn9xs0rt7+bniH3+deQSsZaWlqAuuPxin9sGviHW7Eb1D5ELnYfEWkJstrL9+dafiH2aWBpXewyHc6PFmmGXH+ax9/rKX+yncsOAedXu88jPvcTa+GM9xFqExatsd2U4xD7uNPkPk9fbt1K2Pxh9WOzzh7+PF2t2q1DQxC0FpD4AYAjtmj8Cdc+IeazpPmV7+5XDxT7avU8an9QOwNTUpH5WzXvSvd+/Tnpb2d7KWv1jSqf5D/L5xdB8VqZdvWP4LJqNZJVrprCf6ba5qVmXNHYjIL+pY7e7xVrJSZe6YJGXF9G8UKxZhH5+v3zAFXrs1V5ewC1/DwTs8th1u7rYx6b5zrEK78umOYloaqZFWF4wAwcAU70tdPuLIR86Yk27PF1NKhmaY0p3vNnU289wyN9HRmSEWBP7+OWNZPp8cq1EXTN9JdUeQ+lAhPerO18JfXT9DLvuGJD3Z/HY0R1TumNH3rQy4RgorQnbSbP/1Uem7hjV7UsUdi6XC506dQr3MIjoNHECkIiIiIiIiKgOMkz9D4o1vW4iqj8016UQERERERERERHRmY4TgERERERERERERPUYbwEmIiIiIiIiqotMU/+MyZpeNxHVG7wCkIiIiIiIiIiIqB7jFYAUVgVFLnyxrnul9r/c8pXY5+m0m8WaKSTcGpon2AaT9KvT3SEkXQJY2WmZUAkulfSTokhlu7dEfk82ZzDRdqHVxCYnhS7f31ms5R1qomxvnC+vy14k1+b/7UZ1u+bHTqt6k5dyqpsDml1M9yuMLuE2GFen/V7Z3mSLMHBoA4fR6JpjyvZ1XT8S+xz3F4i1K/7xhLLdogmt1KWIPrzuTmV7s1Xy+/W7NKm4N2Qq2xv75K0kJfMCQMCmXpfp0CX9BpECrAm61C3P4lW/r8KW8gLbN5cTtAti1Nv9xMazxD72s+UP2Cek/fp88kY3/fL79ear01s7zcwR+/i37xJrEsMp739GhPz9ASldVpNyagaTMKpLGffLRYuU2qv5yrFoatL5T5scHOILVbTHm5BIazrlz8Pwaz57qaBJ+oVXPjka0vi8mvcUTEKrJulXTK4GYEgp1Jr9WZsQLPXTjEGXKizS/QklvSfICdXaXbahpeLq9iUiIgoJTgASERERERER1UFMASaiUOFPLURERERERERERPUYrwAkIiIiIiIiqotMnOJ+8RpeNxHVG7wCkIiIiIiIiIiIqB7jBCAREREREREREVE9xluAKbwsJgIxlSPVzrI2ErtMGvCJWNvjbq5sn9biv9Uf2xngxkh1xO3TTjkZ0A27WEtc/Wdle/qAedUZ1ilZIcfb3tNhg1h7K9BH2e74IVrs48yT12XPV8dJBjQprL4I+bTpi1C3l6jDi0v7NJbHZ5Sox2ErksdnlQOWcfzTBGW7RZc2rPmZ6Lqzd2g6qvX+6jGx5hI27dYJs6u9HgC4/KH7le2ObHkj2QrlYyc3p6my3SiRYyEDLnkD+u3qz1G3/+lShcUU4CD6AIBNyCX1yocbLJqnhTdyeNTt/faLfXLdwkEFILdInZjrc8vHaPOvhCRdALE/qFOeg0n61TGkNF8A0KUASymnNk2SqbX6KaKGqUmC1dQgJARbdMnBuhRgoZs2HV13q5pQM3WbSJcCbFMfPKZd83k45c/ekBKbSzRJv5qUZynBWLtH+HURy8LyNMm32pRdaXnBJP0CcgKvRTMG3dilRGTdDqhbHoRtq+2jISbmaj5DOmPVhRAQt9uNtLS0SvW4uDjEx8fX8qiIKFicACQiIiIiIiIipfT0dCQlJVVqnzhxIpKTk8MwIiIKBicAiYiIiIiIiEgpMTERc+fOrdQeFxcXhtEQUbA4AUhERERERERUF5lm6b9wrRuAy+VCp06dwjMGIgoZhoAQERERERERERHVY7wCkIiIiIiIiKgOqgshIERUP3ACkMLPXzkJrv3n94ov33vN2/Kyoo+EYkRnvNU95om1ft8PF2t+v/qi4PafyZ8HCuXTiBmhTqPr2F7+nD4//1Ox1uHCo8r2Zz75s9jHlSUnKNqzipXt3rhIsY8uNdUnhFd7m8tRl5HxMN6JawAAdRxJREFUhWLNXaROjPRmOcU+9lx5gIYwDJt6MwDQv9+Fu3oq29s6T4p9otI0Cai6dM8gWHxCKmmJZkWB6g/C1CStBmxyze9S1/xyULeY7FlaEwq6oEtdQKaw/WJ3yCmTvivklUXa1MdipM0r9iks0ewvgrhUuU/0u+vFWm1lZxqaJFi45GPblNJCdUm/QSSMBuxyn4CQfAsAhpCaamhTgDVjF0NYNSnFuloQ/xFr6lJ2hWPb1B1UQZzjdEm/2n7CZ6/bDIY/iNReXdKv5nwl7pva5ekSh6UU4OC2n9hPtzzdSSSYcWg+e0NYHudq6ExhmibeeecdzJ8/H+np6bDZbOjatStGjhyJ66+/vtrLy8/Px/Tp07FkyRIcPnwYMTEx6Nu3L8aNG4cLLrhA7PfZZ5/hnXfewc6dO3H8+HG0a9cOF154IZ544gl06NBB7Ld792689NJLWLVqFbKystCyZUvccMMNeOKJJxAbG1vt8RPVFk4AEhEREREREVGNM00Tw4YNw5IlSyq0p6amIjU1FU8++SQmTJhQ5eVlZmZi4MCBSE9PL287evQoFi1ahOXLl+P999/HFVdcUanf448/jrffrnhhybZt27Bt2zYsWrQIKSkpGDJkSKV+GzduxM0334z8/Pzytn379uG1117D0qVLsXLlSpx99tlVHj9RbeIzAKlWnDhxAmlpaRX+eTwemEFcbUNERERERNQgmGH+F2KzZ8/GkiVLYLFY8Le//Q3bt2/Hhg0bcN999wEApk6dinXr1lV5eaNGjUJ6ejri4uIwf/58ZGRkYMWKFejXrx+Ki4sxfPhw5OTkVOjz1Vdf4e2334bFYsHo0aOxefNmHDlyBKmpqbj66qvh9Xoxbtw4HDp0qEK/oqIiDBs2DPn5+ejVqxc++eQTZGRkYOHChWjVqhUOHjyIBx988LS3EVFN4QQg1Yo333wTSUlJFf5lZGQgUKi595CIiIiIiIjqBa/XixkzZgAAJk+ejFGjRiEhIQGdO3fG9OnTMXjwYJimiZdeeqlKy9u2bRuWLVsGq9WKBQsWYPDgwWjWrBn69u2LhQsXon379sjKysLcuXMr9Ctb/t13341nn30WiYmJiIqKQvfu3fH++++jY8eOyMvLw4cfflih3/z58/Hzzz+jVatWeP/993H55ZejWbNmuPHGG/Hee+/B6XRi9erV+O6770KwtYhCjxOAVCtGjBiBjRs3VvjXrl07WKIiwj00IiIiIiKiOqksBCRc/0Lp22+/xbFjxxAREYGRI0dWqj/++OMAgNWrV1e6ak9l8eLFAIA+ffqgT58+FWoxMTHlVxV+/PHHFWppaWkAgLvuuqvSMh0OB2644QYAwI4dOyrUym5bHjp0KOLj4yvUevToUX6r8W/XR1RXcAKQakV8fDw6depU4Z/T6RQfUk1ERERERET1R2pqKgCgf//+iIiofCFIt27d0KJFC/j9fnz77benXN4333wDALjmmmuU9YEDBwIAtm7ditzcXABAXl4esrKyAABt2rRR9mvSpAkAlPcBALfbjU2bNlVpfWXvk6iu4ewLEREREREREdWo3bt3AwB69eqlrBuGge7du1d4rU5Z8Ie0vI4dOyIqKgqmaWLPnj0ASif38vLykJeXh5YtWyr7bdy4EQDQuXPn8raMjAz4fD44HI7yMf5Wjx49qjx2onBgCjCFlwEYdr+yXbLJUyLWLnHaQzCoM18Ti3xr9X97vS/Wzl97d7XXpbs1wHZC/XnsP6r+tQ0A7o64XKx9/0VnZbu3mxwmY96SL9YaOzzK9uJ50WKfgGYXK4lWj6PJWfIYLmu1V6ylnK1+fki3724X+xTtlsduL1AfWBb5kIKp+ZnI51V/hdzd+KTYJ+GB18Xa8JX3Kdvbrxwu9mkenyfWIvzVv2/FtFrFWl5b9cYovs4r9jEy5a/ZmB3qz8OUhwBDk5sk1YwSeTtY5KHDXqju58z2iX2aRxSItYCpfr8bNp0n9mmyW94BI4VHyDade+orBsJKd+W7IX/5GabwOfrkz9fUnKB98VHqPlZ5fKZVHp/VrfguB2DRHIcWr+YYlVal6xLMrWrSdj0V4bMyNZ+vYdOsSzjwdaMT9wldH13Rr/4MSzsKPYPcn8V+Fl0fzclR6hfs+KRaMH10gumjXZ7m/ZoM3jtjBWrgXtzqrDuEDhw4AADalNzY2NgKr5UUFRUhMzOzSssrLCzEwYMHcdFFFylfU1JSguzsbGRkZODdd9/FZ599hpiYGAwf/r+/QcvG07JlS1iEc0vZ2AsLC5GZmYlmzZpp3wNRbeMEIBEREREREREpLV++XLzK7rd0ARhFRUUAgMaNG4uvadq0KYDSSTSdsmUBQKNGjbTLO3jwIAoK5B8pf/e73+HHH38s//8XXngh/vGPf1S4RbhsfadaV5nCwkJOAFKdw1uAiYiIiIiIiKhGud1uAIBVc8dFVFTpFerFxcKl/r9ZVqiW92sZGRn49NNPYf7qSuuqjP3Xk4PVWR9RbeEVgERERERERER1kQn98wBqet0Arr/+esyZM+e0F+dyuQCUBnFISkpKn03jdDqrtCwAyM/PR3S0+jE4Xq+30ut/a+3atfB6vdi/fz8++ugjzJgxA9OmTUNRURGee+65Ko+9bF1VGT9ROPAKQCIiIiIiIiKqUZGRkQCAnJwc8TX5+aXPzi67cu9UywrV8hwOBxITEzFhwgS8+OKLAIA5c+aUL7s6Ywf0twoThQsnAImIiIiIiIjqIMMM779QKnumXlZWlviaI0eOAAASEhK0y4qMjCx/xp5ueUePHgUAtG7dusrjHDJkCGw2G9xud3nScNnY8/Ly4BdCk8rGHhERwef/UZ3EW4AprBKjcvDTVe9Uas8MyA99nXzkCrF25x51mqTFIn977bzsXc0IG5ZgtsW5Hz4g1qRUUluRuh0AfvxAnfQLAM0Oqxf48w1yjG2xR47tbTKjibK9kdetbAcAT4ycsBwQEh5bNJZTgKWkX53mmuXtcarfUykhBViXIqr5mSh6lXpbBAbISYMDXPICH+/3ubL9vanXi33shbFizQhoEi0Fpl0en1XYLZrGyuerXE3qp2+fvC+JY1AHVwOQP0ddyrNVk8JqK1JvP0OTCNjcKe+bhT71rTAdHtsg9jmTGTbh3KNL/fRrUjqlxFdNEqy/hZwK7th3Ql3QfL6+hDixZvGo06F1qbhWh/wcJSlx2NSlxGpKQS1PQwi11n68uhRl6WSrS/o1IX+/GcGk2PqDSNnVpuJqvkCCWl6IE3h1n730AeuEeHyG5tgJ192gRKcrMTERALBp0ybxNdu2bavwWp2OHTti/fr12LRpE/r371+pvn///vJbdjt06AAAmDt3Lp566in07dsXH374oXK5DocDTZo0QVZWFny+0u+3du3awWazwefz4fvvv0dSUpI49g4dOsjnYaIw4hWARERERERERFSjyibp1q1bVyHFt0x6ejoOHDgAq9WKPn36nHJ5/fr1AwCsXLlSWf/qq68AAN26dStP6O3UqRMKCgrwww8/VAj5+LXMzMzyqwo7deoEoPQZgGVJyNL6vvzyywrvk6iu4QQgERERERERUV1kmuH9F0KXXnopWrRoAY/Hg5SUlN+8TRPPPvssAGDAgAGIjZXv8igzePBgAMDGjRuxdu3aCrXs7GzMnDmzwusAoEuXLnA4HDhx4gTef/995XLL+iUmJiImJqa8fdCgQQCAd999FydOVLySfvPmzVi2bFmF1xHVNZwAJCIiIiIiIqIa5XA4MHbsWADA1KlTkZKSgsOHD2Pbtm0YM2YMPv74Y1gsFkyYMKFCv549e6Jnz5545plnKrRfcMEFuOmmm+D3+zFs2DAsWbIEmZmZWLt2Le68805kZGQgLi4O9957b3mfxo0b49FHHwUAjBkzBq+++ioyMjJQVFSEHTt2YOzYsXj11VcBoDwMpMzQoUPRqlUrHDlyBHfccQe++eYbZGZmYunSpbjjjjvg8XhwxRVXKG8PJqoL+AxAIiIiIiIiIqpxDzzwADZs2ICPPvoIycnJSE5OrlCfMmUKevfuXaFt165dAP4X6PFrM2fOxM6dO7Fr1y4MHTq0Qi0yMhLz5s1DdHTFZ+KOHz8ea9euxYYNG/DUU0/hqaeeqlC32+146qmncOWVVyqXd/PNN2Pjxo244YYbKtTPOeccvPHGG1XYCkThwSsAiYiIiIiIiOqg+pQCDJSGFL3zzjt45ZVX0KNHD0RFRSEmJgYDBgzAf/7zH4wePbpay2vWrBlWrVqFMWPGoH379nA6nWjevDluvfVWrFmzRvk8PpfLhc8//xyzZs3CgAEDkJCQgKioKHTv3h133HEH1q1bh3HjxinXl5SUhNTUVNx+++0466yz4HQ6cc4552DUqFFITU1FixYtgtksRLWCVwBSnfTkz1eJtaubbhNrX0KdAmxoUoA7f3uXWNvRZ4FYC0af/96ibP9rxyVinysjqp9kWpuu6bNVrH392UXKdkMdFgkAsMuBqjD8wudYLJ/K3DaHWHP+sEfZ7rvgHLGPLoXVlq9OUDyQ1VTsU2LKG2PAT7cp249lykm/Fs3uIoUa+u1ySpkuIVhKkO0zcaTYJ+8ceV03Df5WvR6PPAZxn4Dmj1ZNKlvAJtc8zdTtBXvlz7fxXvl3Nr9L3W5oPkOL5tiRUrd1Sb/2Ijl1VkoBPviIPIirHHli7aipTqQN9O8h9rGkbhFrdZ1hD+JPrIAmBVhKCPZpdgoduzpB1nTJybLWfDkh3SgSTo6a7WDadSnA6pq2jybFOyDVNH2CoU361f3uHkxKrKaPfPrTpQBrTj7BpArrasGkANcm8f3q9pcg/l7TpTzrzgdEZzjDMDB8+HAMHz68Sq8vS/KVNG7cGFOmTMGUKVOqNYZhw4Zh2LBhVe5T5txzz+WVfnRG4gQgERERERERUV1kQp7Vr411E1G9wVuAiYiIiIiIiIiI6jFOABIREREREREREdVjvAWYiIiIiIiIqA4yTBOG5nmRNb1uAHC73UhLS6tUj4uLQ3x8fG0Pi4iCxAlAIiIiIiIiIlJKT09HUlJSpfaJEyciOTk5DCMiomBwApDCKj2/Kdp/fH/lglNOUnv92vVi7Zb+/1S237lvgNhn65FWYi0YR/0FYq24RH3Ijdv+R7HPs50/EWs3RhZVfWA15B+tNsrFe9W15ONdxS5fzuwj1qRE2sR/ytG8e2+OFGuGkIJp+OTkPXuR/AusI1edGlh0Qh5D1/V/FmveYiGls1A+dVt9moRbIdzTJw8PtiJ5eTa3elvYiuVtFL9VPrbXbav8hyUAuHJLxD4Wj7w8i1tds3jk5R3/XaxYCzjU76v5Rk1ycIxYkre7LvhRcwGAmAKsSVG2Fssra/LcIWX7ojYfi322uluLtQ/3qVPB/d0ixD7NU8VSnWfYgvgTS0r6BYASYb/VpABb3PK+LqWPGl75mPLHRok167FMYRDy02Z028hwqhPcTaEdAEyXbpurT4B+a5BPwxFSbLXX6GgTeEN7dY+0JlMXRKz5/pA7BZfaa9aVtF+BIaUUS+2nEszVW9qE4HqYzGBqzn/a9OUGIAD5oK6NdQNITEzE3LlzK5Xj4uJqeUBEdDo4AUhERERERERESi6XC506dQr3MIjoNDXwn1OIiIiIiIiIiIjqN14BSERERERERFQH1YUQECKqH3gFIBERERERERERUT3GCUAiIiIiIiIiIqJ6jLcAU3iZAFSBg2Zoo64WnrNarF1w5E6x1unbu0I6jmDcECmnCtfWHH6xKafsWjRjcBrq1EWrJubUIgdQiimnhiY5s+PbJ+UFCumUFk0Kpr1Arrmy1adUv8sq9inxyKma0lFgBOTjw9Bsv4AQnul3yX2s8keP7N+rU6h7tdkv9tmdIj9AOiYtT9lulMhvyvDKCaiQ0n69XrHL2Z/LyyuJb6ReTTOn2MfvkI8Pv139Od7w53Vin9tivhNrs45dqWxftaWz2MeWIyeqHjsRr2z/fdpjYp+EFfK+2WKbcCx6Doh9EC+nC5rFbmW7v1CTjq5LmQyCYROitXU0qb1BJaoKaeYAYNrlc4+YzuvRnO8L5OWZcUKCtk0+BnTjk2oBu7y8gGZ5AeF4MzXLgyZpVf4+kvtYNAnz0p89Ft3fQ5ptK6Y8a2KAdQnBolD/GaI7BkJ9K6LudFBbKcUBzSD8mi906VwW4nNcrdIk/YqpzA2FiVNEjNfwuomo3uAVgERERERERERERPUYrwCkWnHixAmcPFnx6g+PxwNT98snERERERFRQ2aaob8CtjrrJqJ6gxOAVCvefPNNTJs2rVK7pZF8+yMREREREREREZ0+TgBSrRgxYgQGDx5coW3IkCE4WKh7vh0REREREREREZ0uTgBSrYiPj0d8fMUHyjudThjFmoe1ExERERERNWCGWfovXOsmovqDISBERERERERERET1GK8ApLAzAkalNlPzc1PimmFiLf3y+dVe//ZLF4q189ferWz3+zVz52bl91Nekt5WiH9dW1IoP1vx1X1XirUDx2OV7cbPLrGPrVB+v75I9RtrkiH3cQQ0G0PoFnBYxS5yBUCTRurl2eVelhJ5fPZCdc2VKb9fq1velwJOod0udkHALo/P71LXLD55fMiTS64N6v0sfVknsU+z70/ICywQrgguKRG7mD6fvDyvul/A7RG7WP1+sWZzqjd8wCnvLz6X/GH5nertPrX5j2IfQD4W305Yp2z/3bOdxT62Are8qhXCDgjNNtc8LNzbsomy3dAc89Z8r1izFKrHbiuUryw3CwrFWqBI3c+was4iupqwLUyP/J4MvyYYK0L92fsS4sQutuPyARxoEqEeg88h9ilpFikvz6Y+l5lWzXeiTa4FhE1rWjTnK01J6qf5ytbumxafcD6VT1eAIZ/vLSXqz94UtmtpUbMu7ZefmhHMw/4NzQYMNd26ghm7Re5jKv42LR2CbocJYltoxm3q/h4iqmVutxtpaWmV2uPi4ird5UVEdRcnAImIiIiIiIjqojqQApyeno6kpKRK5YkTJyI5Obm2R0VEQeIEIBEREREREREpJSYmYu7cuZXa4+Lkq9CJqO7hBCARERERERFRHWQEavdu+9+uGwBcLhc6dZIf8UJEZwaGgBAREREREREREdVjnAAkIiIiIiIiIiKqx3gLMIVVRIQHvXv+X6X2EWetEfuM/OFOsbbVq06F7O6QkzN1BpyzW9m+KiNR7OMv0aQa+oRYPr/cp9+PfxRr67p+pGzfXNhO7LPv/84Sa1IirbVYk2IrB6rCmS2k6MlBq1oBIU1Sl8Lqb6T57IWfQPxR8qkx4JB/N5HSJHXv1yoHgsITq37gsz9aXmCn8w6JtUM5Mcr2ks3qdgD6lEnh/UYel1NidYmW/p+PCp00yaghFsjOEWsWlzoV1+aS9xeHS943f76ydt7X/uvl4/fcf8v9pH1ddwwEdKmuQs3U/BRpbySnKNsL1Gm1tjwpvRgwnHLNKny+Zokm9ViTGm1KNd3y7PLyjCh1aq83Wk7tteZpIsMt6g3vbikn/bqbyfu6lPYrpfmW9tHUhPvdtEm1uhB5oWZoDkNdQrrplRaoO2lqViYcCBbd+U9zvElfcLrtp/s8pH7S51QTtJ+9NI5ggxOkhOBw3Yf5G2dqQrChS/HWdwztQM40dSAEhIjqhwZ+NiUiIiIiIiIiIqrfeAUgERERERERUV1kQn9HRk2vm4jqDV4BSEREREREREREVI9xApCIiIiIiIiIiKge4y3ARERERERERHWQAVMfglPD6yai+oMTgBRWHp8dPx47u1L7gHPkLxuXs0SsTd43SNn+ScfPqj02AHi99Xple/cjbcU+Xqt8WHmFxNyAJnrvyP5mYu1Pja5Uts9s+7HYZ8U5ncVawRb1unRJv9qakHAbdAqwkHjo1yStGn45BVNKrdQtT5dyKrFoQj9NTQqwRUiUfvJy+fP9c5PjVR1WuZUXyvvsA1/eI9auvehHZfv6dy8S+5y9Wz5+rU2jle3+7FyxT6gTggNe+QOxFBSp25tEyX08cursoIu3Ktvbf3y/2Ofsr+X9L+ohdQK0PU6djg4AAYd8fPid6psEfBHyzQMlkfL4fBFCSqwmqNahWZ7TpR6Hwy4fv3bhmAcAi1VITS2Wt5/plmvwqQ/8gEfuoztfSe/KL2yH0pXJJcOjPhYzOzeR++gCeIVhaJN+NTVxDJpkXovmu8UQzsO687NVSvoFYBH2Jd17suqSTMVzmdxHG6gqfFi6M6ahS7itA0mgpjYBWqgF5PdkBGovYV5MD64jqcIhF0Rqb9AJwUREVGW8BZiIiIiIiIiIiKge4xWARERERERERHWRaYbvKtw6cPUvEYUOJwCJiIiIiIiISMntdiMtLa1Se1xcHOLj48MwIiIKBicAiYiIiIiIiOqiWnxcpbTu9PR0JCUlVSpPnDgRycnJtTwoIgoWJwCJiIiIiIiISCkxMRFz586t1B4XFxeG0RBRsDgBSBV4vV6kpKTg3//+NzIyMhAVFYWePXti9OjR6NOnT8jXF/BZUPhzo0rtR/0FYp/zYk+INYtROz+Rbb3kX2Ltki23irWAkEbnLdHEBmoS7DZ/30HZ/rA5WOwzs7M89n2J6i/xJlY5tfLGSHUyarCeO3m+WFv20gBluyHFTwIwLfJpzhQ2rZQODAABzVlTSsi0+HTPT9Gkuh5Wtz+3+Xqxz59/N0+zLrWrI+QYzE+unSnWLrBHKtvP63ue2Mf/beXjvYxVSE21FBaLfXSJqqFmeqQYb13UqlzaMOMSZXtMtNwpt728vMxv2ijbA5Hy/rfv95p9Uzo+tMmjmm0hHaaaIdhz5HOjQ6g5NX1c2XLKrjNHvT9b3fLxYS2SU62NYnXNVqyLTtckLLdUp2Tntpffr8UXIy8vSr2u4hZiF+3+LJ0ANadn/fKEXUlKRy+tyYuTUuktmiR2v2ZdVul0oPmO0G8LddEskQ8QU7ctfOoNqAud1YWw1tZjwIxgkn4BGH6ppjkn6U5m0rqC3YANjJjoG0Q6MNUNLpcLnTp1CvcwiOg0cQKwHsvNzcWLL76I7777Dunp6bDZbLjgggtw9dVX48EHH4TNVvHjd7vduOmmm7Bhw4bytuLiYnz22WdYuXIlUlJScOedd9b22yAiIiIiImqQDNPUT47X8LqJqP7gzzD11A8//IBLLrkEs2bNwsaNG5GVlYXjx49j1apVSE5ORr9+/XDgwIEKfaZMmYINGzYgIiICKSkpSE9Px6pVqzBo0CD4/X6MHj0ae/bsCdM7IiIiIiIiIiKiYHACsB4yTROPP/44jh49ihYtWmD+/PnYs2cPdu/ejTlz5qBFixbYvn07HnzwQZi//Kpz4sSJ8uc6pKSkYOjQoWjRogUuvvhivPXWW0hKSoLH48GsWbPC+daIiIiIiIiIiKiaOAFYDy1btgxbtmyBYRj48MMPMXjwYMTHx6N58+YYMmQIPvnkE7hcLqxduxaff/45AGDFihVwu91o27Ytbr214jPsHA4HRo0aBQD4+OOPyycNiYiIiIiIqAaZZnj/EVG9wQnAeujHH38EAAwYMADdu3evVD///PNxzTXXACi9VRgAUlNTAQADBw5ULnPAgAGw2+3IzMzE9u3ba2DURERERERERERUExgCUg/t27cPANC1a1fxNW3btgWA8ucApqenAwB69eqlfH2TJk3QoUMHpKWlYffu3ejSpUtIxprYOBs/DZ6jqMhJoe+3+1qsPfKzevy1KcIuxxAWWpzVX6BPk/LnUde2r1KnAwPAiM5yxOOOPguqPq4a8lTcTrH2z06/U7ZbdNvIK//OYRfCpm1y6CysXvmXUIsQFiq1A4ARqP7yYtZEyAtUb6KgLcq9WKxdEJembPcfUqepAoA3Vj4+XMXq92XYNV9VmkDVUAu41SuziumT+pBJvxBI624m93GfLe9MTVrmK9svij8q9unS+GexlutTfx55PpfYp9jvEGtu4Q3nlcjnxf1ZTcVaQZZ6P/NkyvuLJ0s+Hzhy1WO3ueXkYKtH3ha2YvV+YXVrUkk1CeRF8eq034K28vI8sfK28Db1K9uNJppk7SAuBDG1sdEafnU/v0eTeix8J5b2U9es7uon/QKAKQxDlyKvT1EWxmfRnF8s8mdvWtT7ukWXYqup6b6r5EFUv4+p2Uhy0i/EFGpD8/1rahLcDWlb1JWkX1NzHqktTPStPeG8Eo9XABLVK5wArIeGDh2Ka6+9VjsBWHaVYJs2bQAABw8eBAC0atVK7BMbG1vhtUREREREREREVPdxArAe6tevn7b++eefY/Xq1TAMAzfddBMAoKioCADQqJF85V3TpqVXYhQUCJdN/UK6ivC39u7diw7nVOmlREREREREREQUJF673cAsWLAAw4YNAwAMGTKk/FZet7v0lh+rVb61JioqCgBQXKy5P5KIiIiIiIhCIxDmf0RUb/AKwAZi69atmDRpEtatWwegNNTj1VdfLa+7XC4UFRUhP1/9DCkAKCkpfXaX06l/jt13331XpTH16tULCOyt0muJiIiIiIiIiCg4nACs5woLC/HUU0/hnXfeQSAQgMPhwIQJEzBmzJgKV/tFRkaiqKgIOTk54rLy8vIA6G8TJiIiIiIiotAwTBNGmMI4wrVeIqoZnACsxzZs2ID777+/PBV48ODBmDJlCtq1a1fptQkJCTh58iSysrLE5R09Wpok2bp16xoZLxEREREREdUtbrcbaWlpldrj4uIQHx8fhhERUTA4AVhPbdq0CYMGDUJRURHOPfdczJ49G7179xZf37FjR2zZsgWbNm3CXXfdVanu9Xqxa9cuAEBiYmKNjft0pZxdtduPa1JqlyVircuGO9QFzY9rFr9cs7oNZbvhk/v4djcWa8eT1AEvza21d9XnBevvFGuRnbOV7RaLvAG9JfJzLfNPRCnbbVnyqdGZo97mAGAX7qC3ueXxlUTJy/MLd9tL7QDQ+Y2HxNq2B15Ttv89q6PYZ9G8AWLt/Wh1rakmKNwTq9m2mQ5lu6F5NmltMn0l6oJf84AcQ/f5qmueOHl5rdufEGt3J2xUto+IPiL2CbWCgFusHfGrT0x7fLFin3Ux8r75Q2yCsj0jppnYpzA6Qqx5stX7ptUrf4bSObi0JrR75f3Z1DyZ2SNsJjPGK/aJScwTay0bqWtFPrvYxxeQB1gSUL8vv6aPzy/XPD7151HsVp8nAKCkWD6/BIRawCGPIVAsf74BYVW6zxCQlyf/ISD3MS3yykzpe1HzfakbnuGr/lVAQV05pOtiaIo+4bxpld+UoXu2mV9YV6COXA1lCJ+9qfs+4qPfKXjp6elISkqq1D5x4kQkJyeHYUREFAxOANZDmZmZuPXWW1FUVIRrr70W8+bNQ2RkpLZP//798cEHH2DlypXKempqKrxeL2JjY8uDQ4iIiIiIiKgGmWbpv3CtG6UXgMydO7dSOS4urrZHRESngROA9dD8+fORlZWF8847DwsWLIDDIf9aXua6666Dy+XCoUOH8K9//QtDhgwpr3m9Xjz//PMAgEGDBsGi+cWZiIiIiIiI6g+Xy4VOnTqFexhEdJo4k1MPLVy4EABw//33V2nyDyj99ea+++4DAIwePRoLFizAiRMn8P333+Pee+/Fpk2bEBERgccee6zGxk1ERERERERERKHHKwDrGZ/Ph7179wIAxo4di7Fjx2pfP3LkSEybNg0A8PTTT2Pz5s1Yv349Ro4cWeF1NpsNs2bNUgaIEBERERERUQ2oA7cAE1H9wCsA65mDBw/C79ekRmg4nU4sW7YMU6ZMQadOnRAREYFmzZrh+uuvx4oVK3DbbbeFeLRERERERERERFTTeAVgPdOuXTvk5cmpf6dit9sxZswYjBkzJoSjojJRTnVao8clpy76izWJkULJ1CT5BRzyL3mNLfI4gjEz+xxl+3e56nYAuKH9DrF2liNH2R5vE+J3AZzwyanHK6IvULbv/Tle7OOxyBG8lhIhlVnzgXibiCV4Y9Sflb+xPMlvaSQk1QLovG6YenmapGR/N49YM0vUvyF54uXflqyFcq3wLPXGaNLmfLFPo925Yi2wI13Zbgb5I4mtdStluz9WnSYNACVRmgRUIZDWiJW3+e9aqN8TULtpv5JGFpdYSxQ2RaJdTrG9xKlONgaAryPVcdNrGp0n9tnSqLVYOx6tPld4PJo/ldzy52t41DWLR3OC1vws649VH9uRjeXk5XbRWWLtLJf62GnlzBH75Pvlz7c4oH7kSIFPfhRJoU8+n+aVqNeV6ZZDzXKdcspzkUO9Lp9d/nxNi+b7V0xhFbtoU2cNv/D9oUmdNTUp48HR7M9SerDm6iDdd5+0nbTJweog8dJ+od4W0jh04wtxQrBh0SRAS19jtZj0qxufNA5tn2CEenl1VT28AtA0TbzzzjuYP38+0tPTYbPZ0LVrV4wcORLXX399tZeXn5+P6dOnY8mSJTh8+DBiYmLQt29fjBs3DhdcoP57n6gh4hWARERERERERFTjTNPEsGHDMHr0aGzZsgUFBQXIyclBamoqhgwZghdeeKFay8vMzMSAAQPw8ssvY8+ePXC73Th69CgWLVqEK664Al9//bXYd/PmzRg6dCiSkpJw1llnoWfPnhg2bBjWr18v9rnyyivRpEkT7T9VYjJRXcAJQCIiIiIiIiKqcbNnz8aSJUtgsVjwt7/9Ddu3b8eGDRvKAymnTp2KdevWVXl5o0aNQnp6OuLi4jB//nxkZGRgxYoV6NevH4qLizF8+HDk5ORU6jdt2jRceeWVWLJkCdLS0lBUVIRdu3Zh8eLFuPbaazFu3Djl+nbv3h3U+yaqCzgBSERERERERFQXBcL8L4S8Xi9mzJgBAJg8eTJGjRqFhIQEdO7cGdOnT8fgwYNhmiZeeumlKi1v27ZtWLZsGaxWKxYsWIDBgwejWbNm6Nu3LxYuXIj27dsjKyur0hV5//3vfzFt2jQEAgFcddVVWLNmDX7++Wds2rQJDz74IAzDwJw5c7BgwYIK/TIzM5GdnQ2Hw4GsrCzk5eUp/w0fPjw0G4woxDgBSEREREREREQ16ttvv8WxY8cQERGBkSNHVqo//vjjAIDVq1crr9r7rcWLFwMA+vTpgz59+lSoxcTElF9V+PHHH1eoPf/88wgEAujatSsWLVqEHj16oFGjRjjvvPPw4osv4oknngBQOkn5a2VX/3Xs2BE2G+MU6MzDCUAiIiIiIiIiqlGpqakAgP79+yMionJwU7du3dCiRQv4/X58++23p1zeN998AwC45pprlPWBAwcCALZu3Yrc3P+FX/30008ASm8fVoUIPfroozAMA5mZmdi/f395e9kEYKdOnU45NqK6iNPWRLVoY4//KNt7fP8nsU9+QJMgCyFd0SWnnEZEy4mR1+24TdneKkpOWk2IyBZrbZyZyvY/t1gr9jnPrlmeTU70lZ0UK40t6m2xMNBL7HOgqLlY8+cIp1RNgJqU9AsAgRbqNNiz4uWk7/OaHhdrLYXUT09A/ioo9svJ0FI/t6bP8eJGYm1fqzhle0GCnDwaeW6sWGvU5RJluytTjpIMODQpxS51zRepOUYbybUSIQHaapfvt5GSVgEgL1CsbG9ikZNR67pmFjlhOdFxTNmeGSXvY7r92WlV7xf5Xjmptsgtfx5ej3pdfo+cLKs7VzgaqdOSI5xy8neOVz52XFZ1v4ApHwN5Pnl5RULab5FP3uaFJZqEYK+QKuyWPw9Psbwuv1t9vjKK5c/D4pWPX4uw2XVJvzrSadhv16Wc6iKH1f00Hy+gC3UVNpMu6Ve7Lfzqsev66IZuCn8rSenKpySNI6AZoC4tNVwJrlUU8nTe2hLi5OW6yjBNfUJ2Da87lMom0Hr1Uv+tbRgGunfvjs8//7xKz9pLT0/XLq9jx46IiopCYWEh9uzZg4suugherxeHDx8GUDrhqNK4cWPExsYiMzMTBw4cQNu2bQEAe/bsAQC0adMGU6dOxbJly5CRkYG2bduia9eueOyxx5g6THUaJwCJiIiIiIiIqEYdOHAAAHD22WeLr4mNja3wWklRUREyMzOrtLzCwkIcPHgQF110Efx+P95++20AwLnnnqvsc+jQofJlt2nTpry9bFJyxowZCPzqB4EdO3Zgx44dWLx4MaZOnYoRI0Zox04ULpwAJCIiIiIiIqqLTDN8V5H+st7ly5eLV9n91nfffSfWioqKAJReYSdp2rQpAKCwsFC7nrJlAUCjRvLV/02bNsXBgwdRUFAAAIiIiMAtt9wivt40TTz11FMAgO7du5df/Qf8bwLQ4XBg4sSJuPbaa9GqVSts27YNzz77LNavX48nnngCvXr1Eq8uJAonPgOQiIiIiIiIiGqU2136+B2rVX78QlRU6eM/iovVjzb57bJCtTwAyM3NxfDhw/HRRx/BarViypQpFeoOhwOdO3fG/PnzMWbMGHTu3BnR0dHo27cvli9fjksvvRSBQACTJk065bqIwoFXABIRERERERGR0vXXX485c+ac9nJcrtJnyeblyc+zLikpfciq0yk/8/XXywKA/Px8REdHK1/n9Xorvf63/H4//vnPf+L/27vzMKeqw//jnySzDwzbwAgIAgqCKEKLsgkCtrhgrbRfBatf+bliaVVErYDa4oaKFFFxgxbFpXZRGVwrLiD7sBREKJQBkWHvMCyzb0l+f/BNNM49BwiZSci8X8/D8+g995x7bu5JJjk5uZ9HH31U+fn5crvdmjp1qgYPHhyy34IFC4xteDwePfjgg7rsssu0bNkyVVRUHPUcgLrGBCAAAAAAALHI55c19KfWjx05aWlpkqRDhw4Z9ykqKpL03cq9o7UVaO/UU08Nq71169bp17/+dTAZuH379nr55ZfVu3dv6/Gd9OzZUy6XS16vV1u3btVZZ5113G0AtYkJQCAGtGhQbCxL8JgT54oSndN+WzQuMtY5u8keY1mPBs432+2eYr4J79lJ5v6lusL51iucpN/wDEzLddy+ulE7Y52d6U2MZb4E55dUv+X9i7epOZG2bcsDjtsHZ2021hma8ZWxrGOC83jxWt5UVvnN19dUUmm5T82OavODsSyro+P2lW3bGev8p6C5sWxPvvP9YBIOmpNCramfhktlTbq0vG+uSncuTLQ854sNSauSlFvt/POXH5urnNSaGmJY2yQ6p49LUnG6+dv/RMOFPFiZ5rhdkg6kmBOWC8udj1VSYb4g1V7zT5g8buf+VVaZ38rll5jviXSg1Pm8DOGxR45l6V9llXOZ7Zy81eY70fiqnMt8leb2XBXm9jxVhpRYy3PeY3s9cH45tb4eWAJzjTfl8VveqXstsb1+l/Pri99ygW0JwW7T42eZHDA9RpLkMh3L/CfR+DfnSHuG1GPL+douhzH51DYZYrtHWwyk1UY86dd4EQGztm3b6l//+pcOHHB+jytJe/Yc+azSpk0ba1tpaWlq1qyZCgoKrO3t3btXkmpMEPr9fj311FN68sknVVVVpcaNG+uee+7RqFGjwl65l5KSoszMTOXn5+vgwYNhtQHUJl65AQAAAACIRYEQkGj9i6COHY982bty5UrjPuvXrw/Z16ZTp07W9rZv3x78ufEZZ5wRUvbAAw/o0UcfVVVVlYYPH641a9bojjvuME7+5ebm6rPPPtO6deuM/amqqgpORh5L/4G6xgQgAAAAAACoVQMGDJAkLVmyJCTFNyA3N1d5eXnyeDzq27fvUdvr37+/JOnTTz91LP/8888lSeeee24wXViS3njjDT333HPyeDx64YUXNHPmTDVr1sx6rA0bNugXv/iFrr76avl8zmuS161bJ6/Xq8aNG6tFixZH7T9Q15gABAAAAAAAtapPnz7KyspSRUWFpk+fHlLm9/v18MMPS5IGDhyopk2bHrW9YcOGSZJycnK0ePHikLKDBw/qmWeeCdkvYNq0aZKk8ePH67rrrjumvv/0pz9VSkqKdu/erdmzZ9co9/v9evTRRyVJI0aMOKY2gbrGBCAAAAAAALEojn4CnJSUpLvvvluSNGnSJE2fPl27du3S+vXrNXbsWM2dO1dut1v33XdfSL2ePXuqZ8+eeuihh0K2d+3aVVdccYW8Xq9Gjhyp7OxsFRQUaPHixbr22mu1bds2ZWZm6qabbgrWWbFihTZv3qyEhASNGjXqmPuenp6u0aNHS5Luu+8+TZs2Tbt27VJRUZFycnJ05ZVX6vPPP1ezZs00fvz4cB8ioFYRAgIAAAAAAGrdqFGjtHz5cr377ruaMGGCJkyYEFI+ceLEGgm8mzcfCcALBHp83zPPPKNNmzZp8+bNuv7660PK0tLS9Oqrr6pRo0bBbbm5R0IAq6urjxo0Ih35ufI555wjSXrwwQe1Zs0azZ8/X7///e/1+9//PmTfNm3a6M9//nPIz42BWMIKQAAAAAAAUOtcLpdeeeUVTZs2TT169FB6eroaN26sgQMH6u2339aYMWOOq71mzZpp/vz5Gjt2rDp06KDk5GS1aNFCV111lb788svgfQcDtm3bFnbfPR6PsrOzNWPGDPXr108tW7ZURkaG+vXrpzFjxmjJkiU1Ji+BWMIKQKAO/W5fD8ftpzUwx8RnJFUYywpTnVOq+mV+Y6wzpOHXxrLeyaaXhERjnZNZx8QGjttbpRwy1klI9pobNHylUp1kruJJrTaWNU8tcdzeKaXmt58BP06yHCwGtLX81emXstVxe3HjDcY6a1qlGMtWlrV33P5Vofnb3m8KzTeAzj/sPF4qipyfh5LkKvYYy/wJzj+rSXY731hakoqqzee7qeIUx+1nJuw21mngNrcX65q6nV+X2iUeCKu9Bp5yx+17Khsb6+QnO48JSSowlB2oSDXWKaowX4/yKucnT6VhuySVlplfD7yVhrFZbf5u2O91GctcpjLLS6axjqUswfySKXe1rT3DdvPTTS7bsUztWc7Xxmd62C1/fl3m0zUXusw/5/O7zQ36Df0zPQ6S5A/n8bOck9v2S0TbY2FiufZG/nAqSbI8tkau41+n4QrnOBHuQ630o76rhZ/iHtexa4HL5dKNN96oG2+88Zj2DyT5mjRs2FATJ07UxIkTj9rWAw88oAceeOCYjuvE5XJpxIgR3OcPJyUmAFEn8vPztX///pBtFRUVSrS+mwMAAAAAAMCJYgIQdWLmzJl64oknamxv3sy8OgYAAAAA6jWfX1KUFk34WKwBxBMmAFEnbrnllhrx6yNGjFCie2eUegQAAAAAAFA/MAGIOtG8eXM1b948ZFtycrLcPu4RAgAAAACxqry8XBs3bqyxPTMzs8ZnPACxiwlAAAAAAABikd8ffgBNJI4tKTc3V7169apRPG7cOE2YMKGuewUgTEwAAnXolKRDjtszPGXGOplJxcayFHeV4/arG60y1umcmG4swxEtEw8Zy5ITzbGGlYawPG+a+f4pycnO11CSMhKdx0Vjj3M68Mmgwm8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      "text/plain": [
       "<Figure size 640x480 with 2 Axes>"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 480,
       "width": 640
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "ds_wrf['o3'].isel(Time=0, bottom_top=0).plot(vmin=20*1e-3, vmax=65*1e-3)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Replace the era5 surface ozone:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.collections.QuadMesh at 0x7f8284e1c4f0>"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 640x480 with 2 Axes>"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 480,
       "width": 640
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "ds_wrf['o3'] = interped_o3*1e-3 # back to ppmv\n",
    "ds_wrf['o3'].isel(Time=0, bottom_top=0).plot(vmin=20*1e-3, vmax=65*1e-3)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Because the coordinates in the attributes of variables are important for WRF, we should use `netCDF4` instead of `xarray` to change the O3 value.\n",
    "\n",
    "To make sure the structure and attributes of the new wrfinput is correct, it's better to compare the head info using `ncdump -h`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "# ds_wrf.to_netcdf(path='./wrfinput/20200901/era5/wrfinput_d01',\n",
    "#                  mode='w',\n",
    "#                  engine='netcdf4')\n",
    "\n",
    "# back up the original wrfinput file, please change the path by yourself\n",
    "!cp ./wrfinput/20200901/mozbc/wrfinput_d01 ./wrfinput/20200901/mozbc/wrfinput_d01_bak\n",
    "\n",
    "ncfile['o3'][:] = interped_o3*1e-3 # back to ppmv\n",
    "ncfile.close()\n",
    "\n",
    "# move the edited one to anywhere you like\n",
    "!mv ./wrfinput/20200901/mozbc/wrfinput_d01 ./wrfinput/20200901/era5/wrfinput_d01"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Comparison of O3 profiles"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 554.167x466.528 with 2 Axes>"
      ]
     },
     "metadata": {
      "image/png": {
       "height": 454,
       "width": 690
      }
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# check the O3 profile at one pixel\n",
    "f, axs = plot.subplots(axwidth=4)\n",
    "\n",
    "# o3_profile = era5_o3.sel(longitude=119, latitude=32, time='2020-09-01 00:00')\n",
    "# legend_1 = axs.plot(o3_profile, o3_profile.level, label='Original')\n",
    "\n",
    "interped_o3_profile = interped_o3.sel(west_east=x, south_north=y).isel(Time=0)\n",
    "p_profile = p_wrf.sel(west_east=x, south_north=y)\n",
    "legend_1 = axs.plot(interped_o3_profile,\n",
    "                    p_profile,\n",
    "                    label='interpolated ERA5 O3 profile',\n",
    "                    linewidth=3)\n",
    "\n",
    "wrf_o3_profile = o3.sel(west_east=x, south_north=y).isel(Time=0)\n",
    "legend_2 = axs.plot(wrf_o3_profile, p_profile, label='orginal wrfinput')\n",
    "\n",
    "new_wrf_o3_profile = ds_wrf['o3'].sel(west_east=x, south_north=y).isel(Time=0)*1e3 # ppbv\n",
    "legend_3 = axs.plot(new_wrf_o3_profile,\n",
    "                    p_profile,\n",
    "                    label='updated wrfinput',\n",
    "                    linewidth=1,\n",
    "                    color='yellow5')\n",
    "\n",
    "axs.legend([legend_1, legend_2, legend_3], loc='r', ncols=1)\n",
    "axs.format(xlim=(0, 200),\n",
    "           ylim=(1000, 100),\n",
    "           xlabel='Pressure (hPa)',\n",
    "           ylabel='O$_3$ (ppbv)',)"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.8.5"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}