{
 "cells": [
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Met Éireann Reanalysis - create input data for ModVege"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import glob\n",
    "import os\n",
    "from datetime import datetime, timezone\n",
    "import cartopy.crs as ccrs\n",
    "import matplotlib.pyplot as plt\n",
    "import pandas as pd\n",
    "import xarray as xr\n",
    "import climag.climag as cplt\n",
    "from climag import climag_plot"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "# directory of processed MÉRA netCDF files\n",
    "DATA_DIR = os.path.join(\"/run/media/nms/MyPassport\", \"MERA\", \"netcdf_day\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "# list of netCDF variable files\n",
    "var_list = [\n",
    "    \"11_105_2_0\",  # 2 m temperature\n",
    "    \"61_105_0_4\",  # total precipitation\n",
    "    \"117_105_0_4\",  # global irradiance\n",
    "    \"PET\",  # evapotranspiration\n",
    "]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "# dictionary to store Xarray datasets\n",
    "ds = {}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "for var in var_list:\n",
    "    ds[var] = xr.open_mfdataset(\n",
    "        glob.glob(os.path.join(DATA_DIR, f\"MERA_{var}_day.nc\")),\n",
    "        chunks=\"auto\",\n",
    "        decode_coords=\"all\",\n",
    "    )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "# obtain CRS info\n",
    "data_crs = ds[\"11_105_2_0\"].rio.crs"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "CRS.from_wkt('PROJCS[\"undefined\",GEOGCS[\"undefined\",DATUM[\"undefined\",SPHEROID[\"undefined\",6367470,0]],PRIMEM[\"Greenwich\",0,AUTHORITY[\"EPSG\",\"8901\"]],UNIT[\"degree\",0.0174532925199433]],PROJECTION[\"Lambert_Conformal_Conic_1SP\"],PARAMETER[\"latitude_of_origin\",53.5],PARAMETER[\"central_meridian\",5],PARAMETER[\"scale_factor\",1],PARAMETER[\"false_easting\",1481641.67696368],PARAMETER[\"false_northing\",537326.063885016],UNIT[\"metre\",1,AUTHORITY[\"EPSG\",\"9001\"]],AXIS[\"Easting\",EAST],AXIS[\"Northing\",NORTH]]')"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data_crs"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "# drop the height dimension from the datasets\n",
    "for v in var_list[:-1]:\n",
    "    ds[v] = ds[v].isel(height=0)"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## View datasets"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
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       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt;\n",
       "Dimensions:            (x: 158, y: 166, time: 9131)\n",
       "Coordinates:\n",
       "  * x                  (x) float64 4.15e+05 4.175e+05 ... 8.05e+05 8.075e+05\n",
       "  * y                  (y) float64 4.075e+05 4.1e+05 ... 8.175e+05 8.2e+05\n",
       "    height             float64 2.0\n",
       "    Lambert_Conformal  int64 ...\n",
       "  * time               (time) datetime64[ns] 1981-01-01 ... 2005-12-31\n",
       "    spatial_ref        int64 ...\n",
       "Data variables:\n",
       "    t                  (time, y, x) float32 dask.array&lt;chunksize=(4871, 85, 81), meta=np.ndarray&gt;\n",
       "Attributes:\n",
       "    CDI:          Climate Data Interface version 2.0.5 (https://mpimet.mpg.de...\n",
       "    Conventions:  CF-1.6\n",
       "    history:      Wed Mar 22 19:51:04 2023: cdo -s -f nc4c -shifttime,-3hour ...\n",
       "    CDO:          Climate Data Operators version 2.0.5 (https://mpimet.mpg.de...</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-3f384b65-e3d1-426f-bb52-2cdece310c3c' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-3f384b65-e3d1-426f-bb52-2cdece310c3c' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>x</span>: 158</li><li><span class='xr-has-index'>y</span>: 166</li><li><span class='xr-has-index'>time</span>: 9131</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-8e9fef55-2e68-4728-acf6-f8412c28fc80' class='xr-section-summary-in' type='checkbox'  checked><label for='section-8e9fef55-2e68-4728-acf6-f8412c28fc80' class='xr-section-summary' >Coordinates: <span>(6)</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'>x</span></div><div class='xr-var-dims'>(x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>4.15e+05 4.175e+05 ... 8.075e+05</div><input id='attrs-8e965943-fe5f-4a80-add8-38ccedd5b74f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-8e965943-fe5f-4a80-add8-38ccedd5b74f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8896c4a1-bbb0-4abb-9e1b-cb8cf61c1d03' class='xr-var-data-in' type='checkbox'><label for='data-8896c4a1-bbb0-4abb-9e1b-cb8cf61c1d03' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>projection_x_coordinate</dd><dt><span>units :</span></dt><dd>metre</dd><dt><span>axis :</span></dt><dd>X</dd><dt><span>long_name :</span></dt><dd>x coordinate of projection</dd></dl></div><div class='xr-var-data'><pre>array([415000., 417500., 420000., 422500., 425000., 427500., 430000., 432500.,\n",
       "       435000., 437500., 440000., 442500., 445000., 447500., 450000., 452500.,\n",
       "       455000., 457500., 460000., 462500., 465000., 467500., 470000., 472500.,\n",
       "       475000., 477500., 480000., 482500., 485000., 487500., 490000., 492500.,\n",
       "       495000., 497500., 500000., 502500., 505000., 507500., 510000., 512500.,\n",
       "       515000., 517500., 520000., 522500., 525000., 527500., 530000., 532500.,\n",
       "       535000., 537500., 540000., 542500., 545000., 547500., 550000., 552500.,\n",
       "       555000., 557500., 560000., 562500., 565000., 567500., 570000., 572500.,\n",
       "       575000., 577500., 580000., 582500., 585000., 587500., 590000., 592500.,\n",
       "       595000., 597500., 600000., 602500., 605000., 607500., 610000., 612500.,\n",
       "       615000., 617500., 620000., 622500., 625000., 627500., 630000., 632500.,\n",
       "       635000., 637500., 640000., 642500., 645000., 647500., 650000., 652500.,\n",
       "       655000., 657500., 660000., 662500., 665000., 667500., 670000., 672500.,\n",
       "       675000., 677500., 680000., 682500., 685000., 687500., 690000., 692500.,\n",
       "       695000., 697500., 700000., 702500., 705000., 707500., 710000., 712500.,\n",
       "       715000., 717500., 720000., 722500., 725000., 727500., 730000., 732500.,\n",
       "       735000., 737500., 740000., 742500., 745000., 747500., 750000., 752500.,\n",
       "       755000., 757500., 760000., 762500., 765000., 767500., 770000., 772500.,\n",
       "       775000., 777500., 780000., 782500., 785000., 787500., 790000., 792500.,\n",
       "       795000., 797500., 800000., 802500., 805000., 807500.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>y</span></div><div class='xr-var-dims'>(y)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>4.075e+05 4.1e+05 ... 8.2e+05</div><input id='attrs-d864ee02-95c4-4700-a383-c0b4810156ec' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d864ee02-95c4-4700-a383-c0b4810156ec' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c0eb4fe8-f062-4401-86c1-47fee22893c4' class='xr-var-data-in' type='checkbox'><label for='data-c0eb4fe8-f062-4401-86c1-47fee22893c4' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>projection_y_coordinate</dd><dt><span>units :</span></dt><dd>metre</dd><dt><span>axis :</span></dt><dd>Y</dd><dt><span>long_name :</span></dt><dd>y coordinate of projection</dd></dl></div><div class='xr-var-data'><pre>array([407500., 410000., 412500., 415000., 417500., 420000., 422500., 425000.,\n",
       "       427500., 430000., 432500., 435000., 437500., 440000., 442500., 445000.,\n",
       "       447500., 450000., 452500., 455000., 457500., 460000., 462500., 465000.,\n",
       "       467500., 470000., 472500., 475000., 477500., 480000., 482500., 485000.,\n",
       "       487500., 490000., 492500., 495000., 497500., 500000., 502500., 505000.,\n",
       "       507500., 510000., 512500., 515000., 517500., 520000., 522500., 525000.,\n",
       "       527500., 530000., 532500., 535000., 537500., 540000., 542500., 545000.,\n",
       "       547500., 550000., 552500., 555000., 557500., 560000., 562500., 565000.,\n",
       "       567500., 570000., 572500., 575000., 577500., 580000., 582500., 585000.,\n",
       "       587500., 590000., 592500., 595000., 597500., 600000., 602500., 605000.,\n",
       "       607500., 610000., 612500., 615000., 617500., 620000., 622500., 625000.,\n",
       "       627500., 630000., 632500., 635000., 637500., 640000., 642500., 645000.,\n",
       "       647500., 650000., 652500., 655000., 657500., 660000., 662500., 665000.,\n",
       "       667500., 670000., 672500., 675000., 677500., 680000., 682500., 685000.,\n",
       "       687500., 690000., 692500., 695000., 697500., 700000., 702500., 705000.,\n",
       "       707500., 710000., 712500., 715000., 717500., 720000., 722500., 725000.,\n",
       "       727500., 730000., 732500., 735000., 737500., 740000., 742500., 745000.,\n",
       "       747500., 750000., 752500., 755000., 757500., 760000., 762500., 765000.,\n",
       "       767500., 770000., 772500., 775000., 777500., 780000., 782500., 785000.,\n",
       "       787500., 790000., 792500., 795000., 797500., 800000., 802500., 805000.,\n",
       "       807500., 810000., 812500., 815000., 817500., 820000.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>height</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>2.0</div><input id='attrs-e63783e1-2c5a-4986-a9c4-e848f09df26d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e63783e1-2c5a-4986-a9c4-e848f09df26d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-be15ccf5-9213-4f0d-9552-db5b3054305c' class='xr-var-data-in' type='checkbox'><label for='data-be15ccf5-9213-4f0d-9552-db5b3054305c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>height</dd><dt><span>long_name :</span></dt><dd>height</dd><dt><span>units :</span></dt><dd>m</dd><dt><span>positive :</span></dt><dd>up</dd><dt><span>axis :</span></dt><dd>Z</dd></dl></div><div class='xr-var-data'><pre>array(2.)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Lambert_Conformal</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-4ffc1f51-a005-48a2-a57c-a1f984170140' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-4ffc1f51-a005-48a2-a57c-a1f984170140' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e8a7de61-82af-43a1-84d3-dbecbbc4930d' class='xr-var-data-in' type='checkbox'><label for='data-e8a7de61-82af-43a1-84d3-dbecbbc4930d' 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>crs_wkt :</span></dt><dd>PROJCS[&quot;undefined&quot;,GEOGCS[&quot;undefined&quot;,DATUM[&quot;undefined&quot;,SPHEROID[&quot;undefined&quot;,6367470,0]],PRIMEM[&quot;Greenwich&quot;,0,AUTHORITY[&quot;EPSG&quot;,&quot;8901&quot;]],UNIT[&quot;degree&quot;,0.0174532925199433]],PROJECTION[&quot;Lambert_Conformal_Conic_1SP&quot;],PARAMETER[&quot;latitude_of_origin&quot;,53.5],PARAMETER[&quot;central_meridian&quot;,5],PARAMETER[&quot;scale_factor&quot;,1],PARAMETER[&quot;false_easting&quot;,1481641.67696368],PARAMETER[&quot;false_northing&quot;,537326.063885016],UNIT[&quot;metre&quot;,1,AUTHORITY[&quot;EPSG&quot;,&quot;9001&quot;]],AXIS[&quot;Easting&quot;,EAST],AXIS[&quot;Northing&quot;,NORTH]]</dd><dt><span>semi_major_axis :</span></dt><dd>6367470.0</dd><dt><span>semi_minor_axis :</span></dt><dd>6367470.0</dd><dt><span>inverse_flattening :</span></dt><dd>0.0</dd><dt><span>reference_ellipsoid_name :</span></dt><dd>undefined</dd><dt><span>longitude_of_prime_meridian :</span></dt><dd>0.0</dd><dt><span>prime_meridian_name :</span></dt><dd>Greenwich</dd><dt><span>geographic_crs_name :</span></dt><dd>undefined</dd><dt><span>horizontal_datum_name :</span></dt><dd>undefined</dd><dt><span>projected_crs_name :</span></dt><dd>undefined</dd><dt><span>grid_mapping_name :</span></dt><dd>lambert_conformal_conic</dd><dt><span>standard_parallel :</span></dt><dd>53.5</dd><dt><span>longitude_of_central_meridian :</span></dt><dd>5.0</dd><dt><span>false_easting :</span></dt><dd>1481641.67696368</dd><dt><span>false_northing :</span></dt><dd>537326.063885016</dd><dt><span>spatial_ref :</span></dt><dd>PROJCS[&quot;undefined&quot;,GEOGCS[&quot;undefined&quot;,DATUM[&quot;undefined&quot;,SPHEROID[&quot;undefined&quot;,6367470,0]],PRIMEM[&quot;Greenwich&quot;,0,AUTHORITY[&quot;EPSG&quot;,&quot;8901&quot;]],UNIT[&quot;degree&quot;,0.0174532925199433]],PROJECTION[&quot;Lambert_Conformal_Conic_1SP&quot;],PARAMETER[&quot;latitude_of_origin&quot;,53.5],PARAMETER[&quot;central_meridian&quot;,5],PARAMETER[&quot;scale_factor&quot;,1],PARAMETER[&quot;false_easting&quot;,1481641.67696368],PARAMETER[&quot;false_northing&quot;,537326.063885016],UNIT[&quot;metre&quot;,1,AUTHORITY[&quot;EPSG&quot;,&quot;9001&quot;]],AXIS[&quot;Easting&quot;,EAST],AXIS[&quot;Northing&quot;,NORTH]]</dd><dt><span>GeoTransform :</span></dt><dd>413750.0 2500.0 0.0 406250.0 0.0 2500.0</dd></dl></div><div class='xr-var-data'><pre>[1 values with dtype=int64]</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'>1981-01-01 ... 2005-12-31</div><input id='attrs-fa1fee25-0508-4d98-afd2-bc4d20ceca1c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-fa1fee25-0508-4d98-afd2-bc4d20ceca1c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e2003d43-aaa6-43d5-8fa6-7121c2dad38b' class='xr-var-data-in' type='checkbox'><label for='data-e2003d43-aaa6-43d5-8fa6-7121c2dad38b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>time</dd><dt><span>axis :</span></dt><dd>T</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;1981-01-01T00:00:00.000000000&#x27;, &#x27;1981-01-02T00:00:00.000000000&#x27;,\n",
       "       &#x27;1981-01-03T00:00:00.000000000&#x27;, ..., &#x27;2005-12-29T00:00:00.000000000&#x27;,\n",
       "       &#x27;2005-12-30T00:00:00.000000000&#x27;, &#x27;2005-12-31T00:00:00.000000000&#x27;],\n",
       "      dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>spatial_ref</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-12722068-7571-4b10-a36c-7c132c5dcc2f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-12722068-7571-4b10-a36c-7c132c5dcc2f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-340b4695-118a-45d1-adbd-76aa19ca11ea' class='xr-var-data-in' type='checkbox'><label for='data-340b4695-118a-45d1-adbd-76aa19ca11ea' 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>crs_wkt :</span></dt><dd>PROJCS[&quot;undefined&quot;,GEOGCS[&quot;undefined&quot;,DATUM[&quot;undefined&quot;,SPHEROID[&quot;undefined&quot;,6367470,0]],PRIMEM[&quot;Greenwich&quot;,0,AUTHORITY[&quot;EPSG&quot;,&quot;8901&quot;]],UNIT[&quot;degree&quot;,0.0174532925199433]],PROJECTION[&quot;Lambert_Conformal_Conic_1SP&quot;],PARAMETER[&quot;latitude_of_origin&quot;,53.5],PARAMETER[&quot;central_meridian&quot;,5],PARAMETER[&quot;scale_factor&quot;,1],PARAMETER[&quot;false_easting&quot;,1481641.67696368],PARAMETER[&quot;false_northing&quot;,537326.063885016],UNIT[&quot;metre&quot;,1,AUTHORITY[&quot;EPSG&quot;,&quot;9001&quot;]],AXIS[&quot;Easting&quot;,EAST],AXIS[&quot;Northing&quot;,NORTH]]</dd><dt><span>semi_major_axis :</span></dt><dd>6367470.0</dd><dt><span>semi_minor_axis :</span></dt><dd>6367470.0</dd><dt><span>inverse_flattening :</span></dt><dd>0.0</dd><dt><span>reference_ellipsoid_name :</span></dt><dd>undefined</dd><dt><span>longitude_of_prime_meridian :</span></dt><dd>0.0</dd><dt><span>prime_meridian_name :</span></dt><dd>Greenwich</dd><dt><span>geographic_crs_name :</span></dt><dd>undefined</dd><dt><span>horizontal_datum_name :</span></dt><dd>undefined</dd><dt><span>projected_crs_name :</span></dt><dd>undefined</dd><dt><span>grid_mapping_name :</span></dt><dd>lambert_conformal_conic</dd><dt><span>standard_parallel :</span></dt><dd>53.5</dd><dt><span>longitude_of_central_meridian :</span></dt><dd>5.0</dd><dt><span>false_easting :</span></dt><dd>1481641.67696368</dd><dt><span>false_northing :</span></dt><dd>537326.063885016</dd><dt><span>spatial_ref :</span></dt><dd>PROJCS[&quot;undefined&quot;,GEOGCS[&quot;undefined&quot;,DATUM[&quot;undefined&quot;,SPHEROID[&quot;undefined&quot;,6367470,0]],PRIMEM[&quot;Greenwich&quot;,0,AUTHORITY[&quot;EPSG&quot;,&quot;8901&quot;]],UNIT[&quot;degree&quot;,0.0174532925199433]],PROJECTION[&quot;Lambert_Conformal_Conic_1SP&quot;],PARAMETER[&quot;latitude_of_origin&quot;,53.5],PARAMETER[&quot;central_meridian&quot;,5],PARAMETER[&quot;scale_factor&quot;,1],PARAMETER[&quot;false_easting&quot;,1481641.67696368],PARAMETER[&quot;false_northing&quot;,537326.063885016],UNIT[&quot;metre&quot;,1,AUTHORITY[&quot;EPSG&quot;,&quot;9001&quot;]],AXIS[&quot;Easting&quot;,EAST],AXIS[&quot;Northing&quot;,NORTH]]</dd><dt><span>GeoTransform :</span></dt><dd>413750.0 2500.0 0.0 406250.0 0.0 2500.0</dd></dl></div><div class='xr-var-data'><pre>[1 values with dtype=int64]</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-4e8350c5-7d21-4481-8027-31ecb6918cb0' class='xr-section-summary-in' type='checkbox'  checked><label for='section-4e8350c5-7d21-4481-8027-31ecb6918cb0' class='xr-section-summary' >Data variables: <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>t</span></div><div class='xr-var-dims'>(time, y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(4871, 85, 81), meta=np.ndarray&gt;</div><input id='attrs-aa81bcc8-32d7-4196-b34f-322ac668cddb' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-aa81bcc8-32d7-4196-b34f-322ac668cddb' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ab04647d-dbf1-4aba-92fe-8c603e4c2b42' class='xr-var-data-in' type='checkbox'><label for='data-ab04647d-dbf1-4aba-92fe-8c603e4c2b42' 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>GRIB_paramId :</span></dt><dd>233253011</dd><dt><span>GRIB_numberOfPoints :</span></dt><dd>258681</dd><dt><span>GRIB_typeOfLevel :</span></dt><dd>heightAboveGround</dd><dt><span>GRIB_stepUnits :</span></dt><dd>1</dd><dt><span>GRIB_stepType :</span></dt><dd>instant</dd><dt><span>GRIB_gridType :</span></dt><dd>lambert</dd><dt><span>GRIB_DxInMetres :</span></dt><dd>2500</dd><dt><span>GRIB_DyInMetres :</span></dt><dd>2500</dd><dt><span>GRIB_LaDInDegrees :</span></dt><dd>53.5</dd><dt><span>GRIB_Latin1InDegrees :</span></dt><dd>53.5</dd><dt><span>GRIB_Latin2InDegrees :</span></dt><dd>53.5</dd><dt><span>GRIB_LoVInDegrees :</span></dt><dd>5.0</dd><dt><span>GRIB_NV :</span></dt><dd>132</dd><dt><span>GRIB_Nx :</span></dt><dd>529</dd><dt><span>GRIB_Ny :</span></dt><dd>489</dd><dt><span>GRIB_cfName :</span></dt><dd>unknown</dd><dt><span>GRIB_cfVarName :</span></dt><dd>unknown</dd><dt><span>GRIB_gridDefinitionDescription :</span></dt><dd>Lambert Conformal</dd><dt><span>GRIB_iScansNegatively :</span></dt><dd>0</dd><dt><span>GRIB_jPointsAreConsecutive :</span></dt><dd>0</dd><dt><span>GRIB_jScansPositively :</span></dt><dd>1</dd><dt><span>GRIB_latitudeOfFirstGridPointInDegrees :</span></dt><dd>46.834</dd><dt><span>GRIB_latitudeOfSouthernPoleInDegrees :</span></dt><dd>0.0</dd><dt><span>GRIB_longitudeOfFirstGridPointInDegrees :</span></dt><dd>-14.609</dd><dt><span>GRIB_longitudeOfSouthernPoleInDegrees :</span></dt><dd>0.0</dd><dt><span>GRIB_missingValue :</span></dt><dd>3.4028234663852886e+38</dd><dt><span>GRIB_name :</span></dt><dd>Temperature</dd><dt><span>GRIB_shortName :</span></dt><dd>t</dd><dt><span>GRIB_units :</span></dt><dd>K</dd><dt><span>long_name :</span></dt><dd>Temperature</dd><dt><span>units :</span></dt><dd>°C</dd><dt><span>standard_name :</span></dt><dd>unknown</dd></dl></div><div class='xr-var-data'><table>\n",
       "    <tr>\n",
       "        <td>\n",
       "            <table style=\"border-collapse: collapse;\">\n",
       "                <thead>\n",
       "                    <tr>\n",
       "                        <td> </td>\n",
       "                        <th> Array </th>\n",
       "                        <th> Chunk </th>\n",
       "                    </tr>\n",
       "                </thead>\n",
       "                <tbody>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 913.57 MiB </td>\n",
       "                        <td> 127.93 MiB </td>\n",
       "                    </tr>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> (9131, 166, 158) </td>\n",
       "                        <td> (4871, 85, 81) </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Dask graph </th>\n",
       "                        <td colspan=\"2\"> 8 chunks in 3 graph layers </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Data type </th>\n",
       "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
       "                    </tr>\n",
       "                </tbody>\n",
       "            </table>\n",
       "        </td>\n",
       "        <td>\n",
       "        <svg width=\"158\" height=\"149\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
       "\n",
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       "\n",
       "  <!-- Colored Rectangle -->\n",
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       "  <!-- Text -->\n",
       "  <text x=\"94.701824\" y=\"119.086827\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >158</text>\n",
       "  <text x=\"128.815413\" y=\"84.837531\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(-90,128.815413,84.837531)\">166</text>\n",
       "  <text x=\"35.294118\" y=\"83.792709\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(45,35.294118,83.792709)\">9131</text>\n",
       "</svg>\n",
       "        </td>\n",
       "    </tr>\n",
       "</table></div></li></ul></div></li><li class='xr-section-item'><input id='section-0fbeaad0-af3e-41a1-b045-90813f4f3510' class='xr-section-summary-in' type='checkbox'  ><label for='section-0fbeaad0-af3e-41a1-b045-90813f4f3510' class='xr-section-summary' >Indexes: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>x</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-e7774cf9-ced4-481f-adbd-bb64abf66473' class='xr-index-data-in' type='checkbox'/><label for='index-e7774cf9-ced4-481f-adbd-bb64abf66473' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Float64Index([415000.0, 417500.0, 420000.0, 422500.0, 425000.0, 427500.0,\n",
       "              430000.0, 432500.0, 435000.0, 437500.0,\n",
       "              ...\n",
       "              785000.0, 787500.0, 790000.0, 792500.0, 795000.0, 797500.0,\n",
       "              800000.0, 802500.0, 805000.0, 807500.0],\n",
       "             dtype=&#x27;float64&#x27;, name=&#x27;x&#x27;, length=158))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>y</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-cd3da3f6-bf35-428a-bafb-c5fbdbf966ed' class='xr-index-data-in' type='checkbox'/><label for='index-cd3da3f6-bf35-428a-bafb-c5fbdbf966ed' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Float64Index([407500.0, 410000.0, 412500.0, 415000.0, 417500.0, 420000.0,\n",
       "              422500.0, 425000.0, 427500.0, 430000.0,\n",
       "              ...\n",
       "              797500.0, 800000.0, 802500.0, 805000.0, 807500.0, 810000.0,\n",
       "              812500.0, 815000.0, 817500.0, 820000.0],\n",
       "             dtype=&#x27;float64&#x27;, name=&#x27;y&#x27;, length=166))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>time</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-fed46a41-8989-4c1e-b4c2-5cb4e285f28c' class='xr-index-data-in' type='checkbox'/><label for='index-fed46a41-8989-4c1e-b4c2-5cb4e285f28c' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(DatetimeIndex([&#x27;1981-01-01&#x27;, &#x27;1981-01-02&#x27;, &#x27;1981-01-03&#x27;, &#x27;1981-01-04&#x27;,\n",
       "               &#x27;1981-01-05&#x27;, &#x27;1981-01-06&#x27;, &#x27;1981-01-07&#x27;, &#x27;1981-01-08&#x27;,\n",
       "               &#x27;1981-01-09&#x27;, &#x27;1981-01-10&#x27;,\n",
       "               ...\n",
       "               &#x27;2005-12-22&#x27;, &#x27;2005-12-23&#x27;, &#x27;2005-12-24&#x27;, &#x27;2005-12-25&#x27;,\n",
       "               &#x27;2005-12-26&#x27;, &#x27;2005-12-27&#x27;, &#x27;2005-12-28&#x27;, &#x27;2005-12-29&#x27;,\n",
       "               &#x27;2005-12-30&#x27;, &#x27;2005-12-31&#x27;],\n",
       "              dtype=&#x27;datetime64[ns]&#x27;, name=&#x27;time&#x27;, length=9131, freq=None))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-8f9bd78e-7bb1-49e3-ae76-c4b0c61e77a5' class='xr-section-summary-in' type='checkbox'  checked><label for='section-8f9bd78e-7bb1-49e3-ae76-c4b0c61e77a5' class='xr-section-summary' >Attributes: <span>(4)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>CDI :</span></dt><dd>Climate Data Interface version 2.0.5 (https://mpimet.mpg.de/cdi)</dd><dt><span>Conventions :</span></dt><dd>CF-1.6</dd><dt><span>history :</span></dt><dd>Wed Mar 22 19:51:04 2023: cdo -s -f nc4c -shifttime,-3hour -copy -seltimestep,3/744/3 /run/media/nms/Elements/MERA/grib/11_105_2_0_FC3hr/temp/MERA_PRODYEAR_1981_01_11_105_2_0_FC3hr /run/media/nms/Elements/MERA/grib/11_105_2_0_FC3hr/temp/MERA_PRODYEAR_1981_01_11_105_2_0_FC3hr.nc</dd><dt><span>CDO :</span></dt><dd>Climate Data Operators version 2.0.5 (https://mpimet.mpg.de/cdo)</dd></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.Dataset>\n",
       "Dimensions:            (x: 158, y: 166, time: 9131)\n",
       "Coordinates:\n",
       "  * x                  (x) float64 4.15e+05 4.175e+05 ... 8.05e+05 8.075e+05\n",
       "  * y                  (y) float64 4.075e+05 4.1e+05 ... 8.175e+05 8.2e+05\n",
       "    height             float64 2.0\n",
       "    Lambert_Conformal  int64 ...\n",
       "  * time               (time) datetime64[ns] 1981-01-01 ... 2005-12-31\n",
       "    spatial_ref        int64 ...\n",
       "Data variables:\n",
       "    t                  (time, y, x) float32 dask.array<chunksize=(4871, 85, 81), meta=np.ndarray>\n",
       "Attributes:\n",
       "    CDI:          Climate Data Interface version 2.0.5 (https://mpimet.mpg.de...\n",
       "    Conventions:  CF-1.6\n",
       "    history:      Wed Mar 22 19:51:04 2023: cdo -s -f nc4c -shifttime,-3hour ...\n",
       "    CDO:          Climate Data Operators version 2.0.5 (https://mpimet.mpg.de..."
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ds[\"11_105_2_0\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
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       "  fill: currentColor;\n",
       "}\n",
       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt;\n",
       "Dimensions:            (x: 158, y: 166, time: 9131)\n",
       "Coordinates:\n",
       "  * x                  (x) float64 4.15e+05 4.175e+05 ... 8.05e+05 8.075e+05\n",
       "  * y                  (y) float64 4.075e+05 4.1e+05 ... 8.175e+05 8.2e+05\n",
       "    height             float64 0.0\n",
       "    Lambert_Conformal  int64 ...\n",
       "  * time               (time) datetime64[ns] 1981-01-01 ... 2005-12-31\n",
       "    spatial_ref        int64 ...\n",
       "Data variables:\n",
       "    tp                 (time, y, x) float32 dask.array&lt;chunksize=(4871, 85, 81), meta=np.ndarray&gt;\n",
       "Attributes:\n",
       "    CDI:          Climate Data Interface version 2.0.5 (https://mpimet.mpg.de...\n",
       "    Conventions:  CF-1.6\n",
       "    history:      Wed Mar 22 16:41:24 2023: cdo -s -f nc4c -shifttime,-3hour ...\n",
       "    CDO:          Climate Data Operators version 2.0.5 (https://mpimet.mpg.de...</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-ac2df076-ed27-4bd0-94e9-9daa1f26a74c' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-ac2df076-ed27-4bd0-94e9-9daa1f26a74c' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>x</span>: 158</li><li><span class='xr-has-index'>y</span>: 166</li><li><span class='xr-has-index'>time</span>: 9131</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-eb1a7267-4c71-4e70-928d-e1fed35357e8' class='xr-section-summary-in' type='checkbox'  checked><label for='section-eb1a7267-4c71-4e70-928d-e1fed35357e8' class='xr-section-summary' >Coordinates: <span>(6)</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'>x</span></div><div class='xr-var-dims'>(x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>4.15e+05 4.175e+05 ... 8.075e+05</div><input id='attrs-46b0dd82-e7e5-4235-8472-35cb7ce57cf5' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-46b0dd82-e7e5-4235-8472-35cb7ce57cf5' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5d25d75e-6d63-4da7-a682-4bc420077751' class='xr-var-data-in' type='checkbox'><label for='data-5d25d75e-6d63-4da7-a682-4bc420077751' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>projection_x_coordinate</dd><dt><span>units :</span></dt><dd>metre</dd><dt><span>axis :</span></dt><dd>X</dd><dt><span>long_name :</span></dt><dd>x coordinate of projection</dd></dl></div><div class='xr-var-data'><pre>array([415000., 417500., 420000., 422500., 425000., 427500., 430000., 432500.,\n",
       "       435000., 437500., 440000., 442500., 445000., 447500., 450000., 452500.,\n",
       "       455000., 457500., 460000., 462500., 465000., 467500., 470000., 472500.,\n",
       "       475000., 477500., 480000., 482500., 485000., 487500., 490000., 492500.,\n",
       "       495000., 497500., 500000., 502500., 505000., 507500., 510000., 512500.,\n",
       "       515000., 517500., 520000., 522500., 525000., 527500., 530000., 532500.,\n",
       "       535000., 537500., 540000., 542500., 545000., 547500., 550000., 552500.,\n",
       "       555000., 557500., 560000., 562500., 565000., 567500., 570000., 572500.,\n",
       "       575000., 577500., 580000., 582500., 585000., 587500., 590000., 592500.,\n",
       "       595000., 597500., 600000., 602500., 605000., 607500., 610000., 612500.,\n",
       "       615000., 617500., 620000., 622500., 625000., 627500., 630000., 632500.,\n",
       "       635000., 637500., 640000., 642500., 645000., 647500., 650000., 652500.,\n",
       "       655000., 657500., 660000., 662500., 665000., 667500., 670000., 672500.,\n",
       "       675000., 677500., 680000., 682500., 685000., 687500., 690000., 692500.,\n",
       "       695000., 697500., 700000., 702500., 705000., 707500., 710000., 712500.,\n",
       "       715000., 717500., 720000., 722500., 725000., 727500., 730000., 732500.,\n",
       "       735000., 737500., 740000., 742500., 745000., 747500., 750000., 752500.,\n",
       "       755000., 757500., 760000., 762500., 765000., 767500., 770000., 772500.,\n",
       "       775000., 777500., 780000., 782500., 785000., 787500., 790000., 792500.,\n",
       "       795000., 797500., 800000., 802500., 805000., 807500.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>y</span></div><div class='xr-var-dims'>(y)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>4.075e+05 4.1e+05 ... 8.2e+05</div><input id='attrs-88b07867-052d-43fd-97cc-27e6ae542115' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-88b07867-052d-43fd-97cc-27e6ae542115' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-cefd0bc2-f940-4e59-b496-08e6c17ce55d' class='xr-var-data-in' type='checkbox'><label for='data-cefd0bc2-f940-4e59-b496-08e6c17ce55d' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>projection_y_coordinate</dd><dt><span>units :</span></dt><dd>metre</dd><dt><span>axis :</span></dt><dd>Y</dd><dt><span>long_name :</span></dt><dd>y coordinate of projection</dd></dl></div><div class='xr-var-data'><pre>array([407500., 410000., 412500., 415000., 417500., 420000., 422500., 425000.,\n",
       "       427500., 430000., 432500., 435000., 437500., 440000., 442500., 445000.,\n",
       "       447500., 450000., 452500., 455000., 457500., 460000., 462500., 465000.,\n",
       "       467500., 470000., 472500., 475000., 477500., 480000., 482500., 485000.,\n",
       "       487500., 490000., 492500., 495000., 497500., 500000., 502500., 505000.,\n",
       "       507500., 510000., 512500., 515000., 517500., 520000., 522500., 525000.,\n",
       "       527500., 530000., 532500., 535000., 537500., 540000., 542500., 545000.,\n",
       "       547500., 550000., 552500., 555000., 557500., 560000., 562500., 565000.,\n",
       "       567500., 570000., 572500., 575000., 577500., 580000., 582500., 585000.,\n",
       "       587500., 590000., 592500., 595000., 597500., 600000., 602500., 605000.,\n",
       "       607500., 610000., 612500., 615000., 617500., 620000., 622500., 625000.,\n",
       "       627500., 630000., 632500., 635000., 637500., 640000., 642500., 645000.,\n",
       "       647500., 650000., 652500., 655000., 657500., 660000., 662500., 665000.,\n",
       "       667500., 670000., 672500., 675000., 677500., 680000., 682500., 685000.,\n",
       "       687500., 690000., 692500., 695000., 697500., 700000., 702500., 705000.,\n",
       "       707500., 710000., 712500., 715000., 717500., 720000., 722500., 725000.,\n",
       "       727500., 730000., 732500., 735000., 737500., 740000., 742500., 745000.,\n",
       "       747500., 750000., 752500., 755000., 757500., 760000., 762500., 765000.,\n",
       "       767500., 770000., 772500., 775000., 777500., 780000., 782500., 785000.,\n",
       "       787500., 790000., 792500., 795000., 797500., 800000., 802500., 805000.,\n",
       "       807500., 810000., 812500., 815000., 817500., 820000.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>height</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0</div><input id='attrs-c7799104-bd4b-4852-bf5b-d1582f2b874f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-c7799104-bd4b-4852-bf5b-d1582f2b874f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d36506d2-37ed-4990-9afe-0a0d42ddb132' class='xr-var-data-in' type='checkbox'><label for='data-d36506d2-37ed-4990-9afe-0a0d42ddb132' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>height</dd><dt><span>long_name :</span></dt><dd>height</dd><dt><span>units :</span></dt><dd>m</dd><dt><span>positive :</span></dt><dd>up</dd><dt><span>axis :</span></dt><dd>Z</dd></dl></div><div class='xr-var-data'><pre>array(0.)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Lambert_Conformal</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-8e08fb9d-4d51-4c19-85f2-46716a30ff4c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-8e08fb9d-4d51-4c19-85f2-46716a30ff4c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9add3662-5030-497a-83f5-1ae3601730b2' class='xr-var-data-in' type='checkbox'><label for='data-9add3662-5030-497a-83f5-1ae3601730b2' 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>crs_wkt :</span></dt><dd>PROJCS[&quot;undefined&quot;,GEOGCS[&quot;undefined&quot;,DATUM[&quot;undefined&quot;,SPHEROID[&quot;undefined&quot;,6367470,0]],PRIMEM[&quot;Greenwich&quot;,0,AUTHORITY[&quot;EPSG&quot;,&quot;8901&quot;]],UNIT[&quot;degree&quot;,0.0174532925199433]],PROJECTION[&quot;Lambert_Conformal_Conic_1SP&quot;],PARAMETER[&quot;latitude_of_origin&quot;,53.5],PARAMETER[&quot;central_meridian&quot;,5],PARAMETER[&quot;scale_factor&quot;,1],PARAMETER[&quot;false_easting&quot;,1481641.67696368],PARAMETER[&quot;false_northing&quot;,537326.063885016],UNIT[&quot;metre&quot;,1,AUTHORITY[&quot;EPSG&quot;,&quot;9001&quot;]],AXIS[&quot;Easting&quot;,EAST],AXIS[&quot;Northing&quot;,NORTH]]</dd><dt><span>semi_major_axis :</span></dt><dd>6367470.0</dd><dt><span>semi_minor_axis :</span></dt><dd>6367470.0</dd><dt><span>inverse_flattening :</span></dt><dd>0.0</dd><dt><span>reference_ellipsoid_name :</span></dt><dd>undefined</dd><dt><span>longitude_of_prime_meridian :</span></dt><dd>0.0</dd><dt><span>prime_meridian_name :</span></dt><dd>Greenwich</dd><dt><span>geographic_crs_name :</span></dt><dd>undefined</dd><dt><span>horizontal_datum_name :</span></dt><dd>undefined</dd><dt><span>projected_crs_name :</span></dt><dd>undefined</dd><dt><span>grid_mapping_name :</span></dt><dd>lambert_conformal_conic</dd><dt><span>standard_parallel :</span></dt><dd>53.5</dd><dt><span>longitude_of_central_meridian :</span></dt><dd>5.0</dd><dt><span>false_easting :</span></dt><dd>1481641.67696368</dd><dt><span>false_northing :</span></dt><dd>537326.063885016</dd><dt><span>spatial_ref :</span></dt><dd>PROJCS[&quot;undefined&quot;,GEOGCS[&quot;undefined&quot;,DATUM[&quot;undefined&quot;,SPHEROID[&quot;undefined&quot;,6367470,0]],PRIMEM[&quot;Greenwich&quot;,0,AUTHORITY[&quot;EPSG&quot;,&quot;8901&quot;]],UNIT[&quot;degree&quot;,0.0174532925199433]],PROJECTION[&quot;Lambert_Conformal_Conic_1SP&quot;],PARAMETER[&quot;latitude_of_origin&quot;,53.5],PARAMETER[&quot;central_meridian&quot;,5],PARAMETER[&quot;scale_factor&quot;,1],PARAMETER[&quot;false_easting&quot;,1481641.67696368],PARAMETER[&quot;false_northing&quot;,537326.063885016],UNIT[&quot;metre&quot;,1,AUTHORITY[&quot;EPSG&quot;,&quot;9001&quot;]],AXIS[&quot;Easting&quot;,EAST],AXIS[&quot;Northing&quot;,NORTH]]</dd><dt><span>GeoTransform :</span></dt><dd>413750.0 2500.0 0.0 406250.0 0.0 2500.0</dd></dl></div><div class='xr-var-data'><pre>[1 values with dtype=int64]</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'>1981-01-01 ... 2005-12-31</div><input id='attrs-07ea1331-f869-4f8f-a304-bc6c31126603' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-07ea1331-f869-4f8f-a304-bc6c31126603' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-99ca5ccc-0621-45ab-b017-f12af73290dd' class='xr-var-data-in' type='checkbox'><label for='data-99ca5ccc-0621-45ab-b017-f12af73290dd' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>time</dd><dt><span>axis :</span></dt><dd>T</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;1981-01-01T00:00:00.000000000&#x27;, &#x27;1981-01-02T00:00:00.000000000&#x27;,\n",
       "       &#x27;1981-01-03T00:00:00.000000000&#x27;, ..., &#x27;2005-12-29T00:00:00.000000000&#x27;,\n",
       "       &#x27;2005-12-30T00:00:00.000000000&#x27;, &#x27;2005-12-31T00:00:00.000000000&#x27;],\n",
       "      dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>spatial_ref</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-01775f53-f88d-433c-89e2-ad5741a54136' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-01775f53-f88d-433c-89e2-ad5741a54136' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-df55c225-d73e-45e5-9c31-0a4d53fbdfe1' class='xr-var-data-in' type='checkbox'><label for='data-df55c225-d73e-45e5-9c31-0a4d53fbdfe1' 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>crs_wkt :</span></dt><dd>PROJCS[&quot;undefined&quot;,GEOGCS[&quot;undefined&quot;,DATUM[&quot;undefined&quot;,SPHEROID[&quot;undefined&quot;,6367470,0]],PRIMEM[&quot;Greenwich&quot;,0,AUTHORITY[&quot;EPSG&quot;,&quot;8901&quot;]],UNIT[&quot;degree&quot;,0.0174532925199433]],PROJECTION[&quot;Lambert_Conformal_Conic_1SP&quot;],PARAMETER[&quot;latitude_of_origin&quot;,53.5],PARAMETER[&quot;central_meridian&quot;,5],PARAMETER[&quot;scale_factor&quot;,1],PARAMETER[&quot;false_easting&quot;,1481641.67696368],PARAMETER[&quot;false_northing&quot;,537326.063885016],UNIT[&quot;metre&quot;,1,AUTHORITY[&quot;EPSG&quot;,&quot;9001&quot;]],AXIS[&quot;Easting&quot;,EAST],AXIS[&quot;Northing&quot;,NORTH]]</dd><dt><span>semi_major_axis :</span></dt><dd>6367470.0</dd><dt><span>semi_minor_axis :</span></dt><dd>6367470.0</dd><dt><span>inverse_flattening :</span></dt><dd>0.0</dd><dt><span>reference_ellipsoid_name :</span></dt><dd>undefined</dd><dt><span>longitude_of_prime_meridian :</span></dt><dd>0.0</dd><dt><span>prime_meridian_name :</span></dt><dd>Greenwich</dd><dt><span>geographic_crs_name :</span></dt><dd>undefined</dd><dt><span>horizontal_datum_name :</span></dt><dd>undefined</dd><dt><span>projected_crs_name :</span></dt><dd>undefined</dd><dt><span>grid_mapping_name :</span></dt><dd>lambert_conformal_conic</dd><dt><span>standard_parallel :</span></dt><dd>53.5</dd><dt><span>longitude_of_central_meridian :</span></dt><dd>5.0</dd><dt><span>false_easting :</span></dt><dd>1481641.67696368</dd><dt><span>false_northing :</span></dt><dd>537326.063885016</dd><dt><span>spatial_ref :</span></dt><dd>PROJCS[&quot;undefined&quot;,GEOGCS[&quot;undefined&quot;,DATUM[&quot;undefined&quot;,SPHEROID[&quot;undefined&quot;,6367470,0]],PRIMEM[&quot;Greenwich&quot;,0,AUTHORITY[&quot;EPSG&quot;,&quot;8901&quot;]],UNIT[&quot;degree&quot;,0.0174532925199433]],PROJECTION[&quot;Lambert_Conformal_Conic_1SP&quot;],PARAMETER[&quot;latitude_of_origin&quot;,53.5],PARAMETER[&quot;central_meridian&quot;,5],PARAMETER[&quot;scale_factor&quot;,1],PARAMETER[&quot;false_easting&quot;,1481641.67696368],PARAMETER[&quot;false_northing&quot;,537326.063885016],UNIT[&quot;metre&quot;,1,AUTHORITY[&quot;EPSG&quot;,&quot;9001&quot;]],AXIS[&quot;Easting&quot;,EAST],AXIS[&quot;Northing&quot;,NORTH]]</dd><dt><span>GeoTransform :</span></dt><dd>413750.0 2500.0 0.0 406250.0 0.0 2500.0</dd></dl></div><div class='xr-var-data'><pre>[1 values with dtype=int64]</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-cadeeed7-018f-49ee-8e43-f7de0f81b2ac' class='xr-section-summary-in' type='checkbox'  checked><label for='section-cadeeed7-018f-49ee-8e43-f7de0f81b2ac' class='xr-section-summary' >Data variables: <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>tp</span></div><div class='xr-var-dims'>(time, y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(4871, 85, 81), meta=np.ndarray&gt;</div><input id='attrs-1f2cdc5f-c3aa-4ad5-bc35-9bad66c1e6e7' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-1f2cdc5f-c3aa-4ad5-bc35-9bad66c1e6e7' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2c10ba5c-2bf3-4fe5-82c0-a48e69a03020' class='xr-var-data-in' type='checkbox'><label for='data-2c10ba5c-2bf3-4fe5-82c0-a48e69a03020' 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>GRIB_paramId :</span></dt><dd>233253061</dd><dt><span>GRIB_numberOfPoints :</span></dt><dd>258681</dd><dt><span>GRIB_typeOfLevel :</span></dt><dd>heightAboveGround</dd><dt><span>GRIB_stepUnits :</span></dt><dd>1</dd><dt><span>GRIB_stepType :</span></dt><dd>accum</dd><dt><span>GRIB_gridType :</span></dt><dd>lambert</dd><dt><span>GRIB_DxInMetres :</span></dt><dd>2500</dd><dt><span>GRIB_DyInMetres :</span></dt><dd>2500</dd><dt><span>GRIB_LaDInDegrees :</span></dt><dd>53.5</dd><dt><span>GRIB_Latin1InDegrees :</span></dt><dd>53.5</dd><dt><span>GRIB_Latin2InDegrees :</span></dt><dd>53.5</dd><dt><span>GRIB_LoVInDegrees :</span></dt><dd>5.0</dd><dt><span>GRIB_NV :</span></dt><dd>132</dd><dt><span>GRIB_Nx :</span></dt><dd>529</dd><dt><span>GRIB_Ny :</span></dt><dd>489</dd><dt><span>GRIB_cfName :</span></dt><dd>unknown</dd><dt><span>GRIB_cfVarName :</span></dt><dd>unknown</dd><dt><span>GRIB_gridDefinitionDescription :</span></dt><dd>Lambert Conformal</dd><dt><span>GRIB_iScansNegatively :</span></dt><dd>0</dd><dt><span>GRIB_jPointsAreConsecutive :</span></dt><dd>0</dd><dt><span>GRIB_jScansPositively :</span></dt><dd>1</dd><dt><span>GRIB_latitudeOfFirstGridPointInDegrees :</span></dt><dd>46.834</dd><dt><span>GRIB_latitudeOfSouthernPoleInDegrees :</span></dt><dd>0.0</dd><dt><span>GRIB_longitudeOfFirstGridPointInDegrees :</span></dt><dd>-14.609</dd><dt><span>GRIB_longitudeOfSouthernPoleInDegrees :</span></dt><dd>0.0</dd><dt><span>GRIB_missingValue :</span></dt><dd>3.4028234663852886e+38</dd><dt><span>GRIB_name :</span></dt><dd>Total precipitation</dd><dt><span>GRIB_shortName :</span></dt><dd>tp</dd><dt><span>GRIB_units :</span></dt><dd>kg m**-2</dd><dt><span>long_name :</span></dt><dd>Total precipitation</dd><dt><span>units :</span></dt><dd>mm day⁻¹</dd><dt><span>standard_name :</span></dt><dd>unknown</dd></dl></div><div 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       "                        <td> 127.93 MiB </td>\n",
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       "                        <th> Dask graph </th>\n",
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       "              430000.0, 432500.0, 435000.0, 437500.0,\n",
       "              ...\n",
       "              785000.0, 787500.0, 790000.0, 792500.0, 795000.0, 797500.0,\n",
       "              800000.0, 802500.0, 805000.0, 807500.0],\n",
       "             dtype=&#x27;float64&#x27;, name=&#x27;x&#x27;, length=158))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>y</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-adda7932-e8d3-4059-b3fd-392a2b788dea' class='xr-index-data-in' type='checkbox'/><label for='index-adda7932-e8d3-4059-b3fd-392a2b788dea' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Float64Index([407500.0, 410000.0, 412500.0, 415000.0, 417500.0, 420000.0,\n",
       "              422500.0, 425000.0, 427500.0, 430000.0,\n",
       "              ...\n",
       "              797500.0, 800000.0, 802500.0, 805000.0, 807500.0, 810000.0,\n",
       "              812500.0, 815000.0, 817500.0, 820000.0],\n",
       "             dtype=&#x27;float64&#x27;, name=&#x27;y&#x27;, length=166))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>time</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-e45c989b-7e36-4419-b008-b5733688f009' class='xr-index-data-in' type='checkbox'/><label for='index-e45c989b-7e36-4419-b008-b5733688f009' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(DatetimeIndex([&#x27;1981-01-01&#x27;, &#x27;1981-01-02&#x27;, &#x27;1981-01-03&#x27;, &#x27;1981-01-04&#x27;,\n",
       "               &#x27;1981-01-05&#x27;, &#x27;1981-01-06&#x27;, &#x27;1981-01-07&#x27;, &#x27;1981-01-08&#x27;,\n",
       "               &#x27;1981-01-09&#x27;, &#x27;1981-01-10&#x27;,\n",
       "               ...\n",
       "               &#x27;2005-12-22&#x27;, &#x27;2005-12-23&#x27;, &#x27;2005-12-24&#x27;, &#x27;2005-12-25&#x27;,\n",
       "               &#x27;2005-12-26&#x27;, &#x27;2005-12-27&#x27;, &#x27;2005-12-28&#x27;, &#x27;2005-12-29&#x27;,\n",
       "               &#x27;2005-12-30&#x27;, &#x27;2005-12-31&#x27;],\n",
       "              dtype=&#x27;datetime64[ns]&#x27;, name=&#x27;time&#x27;, length=9131, freq=None))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-95fd29d7-730d-42ec-83b3-18de9e05ddfc' class='xr-section-summary-in' type='checkbox'  checked><label for='section-95fd29d7-730d-42ec-83b3-18de9e05ddfc' class='xr-section-summary' >Attributes: <span>(4)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>CDI :</span></dt><dd>Climate Data Interface version 2.0.5 (https://mpimet.mpg.de/cdi)</dd><dt><span>Conventions :</span></dt><dd>CF-1.6</dd><dt><span>history :</span></dt><dd>Wed Mar 22 16:41:24 2023: cdo -s -f nc4c -shifttime,-3hour -copy -seltimestep,3/744/3 /run/media/nms/Elements/MERA/grib/61_105_0_4_FC3hr/temp/MERA_PRODYEAR_1981_01_61_105_0_4_FC3hr /run/media/nms/Elements/MERA/grib/61_105_0_4_FC3hr/temp/MERA_PRODYEAR_1981_01_61_105_0_4_FC3hr.nc</dd><dt><span>CDO :</span></dt><dd>Climate Data Operators version 2.0.5 (https://mpimet.mpg.de/cdo)</dd></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.Dataset>\n",
       "Dimensions:            (x: 158, y: 166, time: 9131)\n",
       "Coordinates:\n",
       "  * x                  (x) float64 4.15e+05 4.175e+05 ... 8.05e+05 8.075e+05\n",
       "  * y                  (y) float64 4.075e+05 4.1e+05 ... 8.175e+05 8.2e+05\n",
       "    height             float64 0.0\n",
       "    Lambert_Conformal  int64 ...\n",
       "  * time               (time) datetime64[ns] 1981-01-01 ... 2005-12-31\n",
       "    spatial_ref        int64 ...\n",
       "Data variables:\n",
       "    tp                 (time, y, x) float32 dask.array<chunksize=(4871, 85, 81), meta=np.ndarray>\n",
       "Attributes:\n",
       "    CDI:          Climate Data Interface version 2.0.5 (https://mpimet.mpg.de...\n",
       "    Conventions:  CF-1.6\n",
       "    history:      Wed Mar 22 16:41:24 2023: cdo -s -f nc4c -shifttime,-3hour ...\n",
       "    CDO:          Climate Data Operators version 2.0.5 (https://mpimet.mpg.de..."
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ds[\"61_105_0_4\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
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       "  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-index-preview {\n",
       "  grid-column: 2 / 5;\n",
       "  color: var(--xr-font-color2);\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",
       ".xr-index-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",
       ".xr-index-data-in:checked ~ .xr-index-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-index-name div,\n",
       ".xr-index-data,\n",
       ".xr-attrs {\n",
       "  padding-left: 25px !important;\n",
       "}\n",
       "\n",
       ".xr-attrs,\n",
       ".xr-var-attrs,\n",
       ".xr-var-data,\n",
       ".xr-index-data {\n",
       "  grid-column: 1 / -1;\n",
       "}\n",
       "\n",
       "dl.xr-attrs {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  display: grid;\n",
       "  grid-template-columns: 125px auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt,\n",
       ".xr-attrs dd {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  float: left;\n",
       "  padding-right: 10px;\n",
       "  width: auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt {\n",
       "  font-weight: normal;\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-attrs dt:hover span {\n",
       "  display: inline-block;\n",
       "  background: var(--xr-background-color);\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-attrs dd {\n",
       "  grid-column: 2;\n",
       "  white-space: pre-wrap;\n",
       "  word-break: break-all;\n",
       "}\n",
       "\n",
       ".xr-icon-database,\n",
       ".xr-icon-file-text2,\n",
       ".xr-no-icon {\n",
       "  display: inline-block;\n",
       "  vertical-align: middle;\n",
       "  width: 1em;\n",
       "  height: 1.5em !important;\n",
       "  stroke-width: 0;\n",
       "  stroke: currentColor;\n",
       "  fill: currentColor;\n",
       "}\n",
       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt;\n",
       "Dimensions:            (x: 158, y: 166, time: 9131)\n",
       "Coordinates:\n",
       "  * x                  (x) float64 4.15e+05 4.175e+05 ... 8.05e+05 8.075e+05\n",
       "  * y                  (y) float64 4.075e+05 4.1e+05 ... 8.175e+05 8.2e+05\n",
       "    height             float64 0.0\n",
       "    Lambert_Conformal  int64 ...\n",
       "  * time               (time) datetime64[ns] 1981-01-01 ... 2005-12-31\n",
       "    spatial_ref        int64 ...\n",
       "Data variables:\n",
       "    grad               (time, y, x) float32 dask.array&lt;chunksize=(4871, 85, 81), meta=np.ndarray&gt;\n",
       "Attributes:\n",
       "    CDI:          Climate Data Interface version 2.0.5 (https://mpimet.mpg.de...\n",
       "    Conventions:  CF-1.6\n",
       "    history:      Wed Mar 22 21:11:40 2023: cdo -s -f nc4c -shifttime,-3hour ...\n",
       "    CDO:          Climate Data Operators version 2.0.5 (https://mpimet.mpg.de...</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-d3e86da8-d130-455d-b82d-c2a479105f00' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-d3e86da8-d130-455d-b82d-c2a479105f00' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>x</span>: 158</li><li><span class='xr-has-index'>y</span>: 166</li><li><span class='xr-has-index'>time</span>: 9131</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-567fdf82-1e51-4f17-981b-428af49fb5c0' class='xr-section-summary-in' type='checkbox'  checked><label for='section-567fdf82-1e51-4f17-981b-428af49fb5c0' class='xr-section-summary' >Coordinates: <span>(6)</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'>x</span></div><div class='xr-var-dims'>(x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>4.15e+05 4.175e+05 ... 8.075e+05</div><input id='attrs-3a581eb0-011f-4e29-99a3-628d60783100' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3a581eb0-011f-4e29-99a3-628d60783100' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-bf21acd0-daa3-4ffb-8739-4d29be44e6a9' class='xr-var-data-in' type='checkbox'><label for='data-bf21acd0-daa3-4ffb-8739-4d29be44e6a9' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>projection_x_coordinate</dd><dt><span>units :</span></dt><dd>metre</dd><dt><span>axis :</span></dt><dd>X</dd><dt><span>long_name :</span></dt><dd>x coordinate of projection</dd></dl></div><div class='xr-var-data'><pre>array([415000., 417500., 420000., 422500., 425000., 427500., 430000., 432500.,\n",
       "       435000., 437500., 440000., 442500., 445000., 447500., 450000., 452500.,\n",
       "       455000., 457500., 460000., 462500., 465000., 467500., 470000., 472500.,\n",
       "       475000., 477500., 480000., 482500., 485000., 487500., 490000., 492500.,\n",
       "       495000., 497500., 500000., 502500., 505000., 507500., 510000., 512500.,\n",
       "       515000., 517500., 520000., 522500., 525000., 527500., 530000., 532500.,\n",
       "       535000., 537500., 540000., 542500., 545000., 547500., 550000., 552500.,\n",
       "       555000., 557500., 560000., 562500., 565000., 567500., 570000., 572500.,\n",
       "       575000., 577500., 580000., 582500., 585000., 587500., 590000., 592500.,\n",
       "       595000., 597500., 600000., 602500., 605000., 607500., 610000., 612500.,\n",
       "       615000., 617500., 620000., 622500., 625000., 627500., 630000., 632500.,\n",
       "       635000., 637500., 640000., 642500., 645000., 647500., 650000., 652500.,\n",
       "       655000., 657500., 660000., 662500., 665000., 667500., 670000., 672500.,\n",
       "       675000., 677500., 680000., 682500., 685000., 687500., 690000., 692500.,\n",
       "       695000., 697500., 700000., 702500., 705000., 707500., 710000., 712500.,\n",
       "       715000., 717500., 720000., 722500., 725000., 727500., 730000., 732500.,\n",
       "       735000., 737500., 740000., 742500., 745000., 747500., 750000., 752500.,\n",
       "       755000., 757500., 760000., 762500., 765000., 767500., 770000., 772500.,\n",
       "       775000., 777500., 780000., 782500., 785000., 787500., 790000., 792500.,\n",
       "       795000., 797500., 800000., 802500., 805000., 807500.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>y</span></div><div class='xr-var-dims'>(y)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>4.075e+05 4.1e+05 ... 8.2e+05</div><input id='attrs-4acc982a-59ba-49cb-ba14-ca97bd06c5c2' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-4acc982a-59ba-49cb-ba14-ca97bd06c5c2' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e6b80215-d491-44a8-b656-e378b1204512' class='xr-var-data-in' type='checkbox'><label for='data-e6b80215-d491-44a8-b656-e378b1204512' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>projection_y_coordinate</dd><dt><span>units :</span></dt><dd>metre</dd><dt><span>axis :</span></dt><dd>Y</dd><dt><span>long_name :</span></dt><dd>y coordinate of projection</dd></dl></div><div class='xr-var-data'><pre>array([407500., 410000., 412500., 415000., 417500., 420000., 422500., 425000.,\n",
       "       427500., 430000., 432500., 435000., 437500., 440000., 442500., 445000.,\n",
       "       447500., 450000., 452500., 455000., 457500., 460000., 462500., 465000.,\n",
       "       467500., 470000., 472500., 475000., 477500., 480000., 482500., 485000.,\n",
       "       487500., 490000., 492500., 495000., 497500., 500000., 502500., 505000.,\n",
       "       507500., 510000., 512500., 515000., 517500., 520000., 522500., 525000.,\n",
       "       527500., 530000., 532500., 535000., 537500., 540000., 542500., 545000.,\n",
       "       547500., 550000., 552500., 555000., 557500., 560000., 562500., 565000.,\n",
       "       567500., 570000., 572500., 575000., 577500., 580000., 582500., 585000.,\n",
       "       587500., 590000., 592500., 595000., 597500., 600000., 602500., 605000.,\n",
       "       607500., 610000., 612500., 615000., 617500., 620000., 622500., 625000.,\n",
       "       627500., 630000., 632500., 635000., 637500., 640000., 642500., 645000.,\n",
       "       647500., 650000., 652500., 655000., 657500., 660000., 662500., 665000.,\n",
       "       667500., 670000., 672500., 675000., 677500., 680000., 682500., 685000.,\n",
       "       687500., 690000., 692500., 695000., 697500., 700000., 702500., 705000.,\n",
       "       707500., 710000., 712500., 715000., 717500., 720000., 722500., 725000.,\n",
       "       727500., 730000., 732500., 735000., 737500., 740000., 742500., 745000.,\n",
       "       747500., 750000., 752500., 755000., 757500., 760000., 762500., 765000.,\n",
       "       767500., 770000., 772500., 775000., 777500., 780000., 782500., 785000.,\n",
       "       787500., 790000., 792500., 795000., 797500., 800000., 802500., 805000.,\n",
       "       807500., 810000., 812500., 815000., 817500., 820000.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>height</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0</div><input id='attrs-0cb9be98-f70b-443f-87d6-11bf1722f61a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-0cb9be98-f70b-443f-87d6-11bf1722f61a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2ae1fbd4-f0bf-495d-b647-f54b1583f278' class='xr-var-data-in' type='checkbox'><label for='data-2ae1fbd4-f0bf-495d-b647-f54b1583f278' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>height</dd><dt><span>long_name :</span></dt><dd>height</dd><dt><span>units :</span></dt><dd>m</dd><dt><span>positive :</span></dt><dd>up</dd><dt><span>axis :</span></dt><dd>Z</dd></dl></div><div class='xr-var-data'><pre>array(0.)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Lambert_Conformal</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-be5cd524-5ecc-45e4-b014-b78b70305013' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-be5cd524-5ecc-45e4-b014-b78b70305013' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8289e3eb-6b26-4e49-8dd0-6a24823873b5' class='xr-var-data-in' type='checkbox'><label for='data-8289e3eb-6b26-4e49-8dd0-6a24823873b5' 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>crs_wkt :</span></dt><dd>PROJCS[&quot;undefined&quot;,GEOGCS[&quot;undefined&quot;,DATUM[&quot;undefined&quot;,SPHEROID[&quot;undefined&quot;,6367470,0]],PRIMEM[&quot;Greenwich&quot;,0,AUTHORITY[&quot;EPSG&quot;,&quot;8901&quot;]],UNIT[&quot;degree&quot;,0.0174532925199433]],PROJECTION[&quot;Lambert_Conformal_Conic_1SP&quot;],PARAMETER[&quot;latitude_of_origin&quot;,53.5],PARAMETER[&quot;central_meridian&quot;,5],PARAMETER[&quot;scale_factor&quot;,1],PARAMETER[&quot;false_easting&quot;,1481641.67696368],PARAMETER[&quot;false_northing&quot;,537326.063885016],UNIT[&quot;metre&quot;,1,AUTHORITY[&quot;EPSG&quot;,&quot;9001&quot;]],AXIS[&quot;Easting&quot;,EAST],AXIS[&quot;Northing&quot;,NORTH]]</dd><dt><span>semi_major_axis :</span></dt><dd>6367470.0</dd><dt><span>semi_minor_axis :</span></dt><dd>6367470.0</dd><dt><span>inverse_flattening :</span></dt><dd>0.0</dd><dt><span>reference_ellipsoid_name :</span></dt><dd>undefined</dd><dt><span>longitude_of_prime_meridian :</span></dt><dd>0.0</dd><dt><span>prime_meridian_name :</span></dt><dd>Greenwich</dd><dt><span>geographic_crs_name :</span></dt><dd>undefined</dd><dt><span>horizontal_datum_name :</span></dt><dd>undefined</dd><dt><span>projected_crs_name :</span></dt><dd>undefined</dd><dt><span>grid_mapping_name :</span></dt><dd>lambert_conformal_conic</dd><dt><span>standard_parallel :</span></dt><dd>53.5</dd><dt><span>longitude_of_central_meridian :</span></dt><dd>5.0</dd><dt><span>false_easting :</span></dt><dd>1481641.67696368</dd><dt><span>false_northing :</span></dt><dd>537326.063885016</dd><dt><span>spatial_ref :</span></dt><dd>PROJCS[&quot;undefined&quot;,GEOGCS[&quot;undefined&quot;,DATUM[&quot;undefined&quot;,SPHEROID[&quot;undefined&quot;,6367470,0]],PRIMEM[&quot;Greenwich&quot;,0,AUTHORITY[&quot;EPSG&quot;,&quot;8901&quot;]],UNIT[&quot;degree&quot;,0.0174532925199433]],PROJECTION[&quot;Lambert_Conformal_Conic_1SP&quot;],PARAMETER[&quot;latitude_of_origin&quot;,53.5],PARAMETER[&quot;central_meridian&quot;,5],PARAMETER[&quot;scale_factor&quot;,1],PARAMETER[&quot;false_easting&quot;,1481641.67696368],PARAMETER[&quot;false_northing&quot;,537326.063885016],UNIT[&quot;metre&quot;,1,AUTHORITY[&quot;EPSG&quot;,&quot;9001&quot;]],AXIS[&quot;Easting&quot;,EAST],AXIS[&quot;Northing&quot;,NORTH]]</dd><dt><span>GeoTransform :</span></dt><dd>413750.0 2500.0 0.0 406250.0 0.0 2500.0</dd></dl></div><div class='xr-var-data'><pre>[1 values with dtype=int64]</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'>1981-01-01 ... 2005-12-31</div><input id='attrs-02931485-1175-401a-be5d-5518472a13c7' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-02931485-1175-401a-be5d-5518472a13c7' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-aaedfbbd-666d-4914-b67e-97f7e7643403' class='xr-var-data-in' type='checkbox'><label for='data-aaedfbbd-666d-4914-b67e-97f7e7643403' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>time</dd><dt><span>axis :</span></dt><dd>T</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;1981-01-01T00:00:00.000000000&#x27;, &#x27;1981-01-02T00:00:00.000000000&#x27;,\n",
       "       &#x27;1981-01-03T00:00:00.000000000&#x27;, ..., &#x27;2005-12-29T00:00:00.000000000&#x27;,\n",
       "       &#x27;2005-12-30T00:00:00.000000000&#x27;, &#x27;2005-12-31T00:00:00.000000000&#x27;],\n",
       "      dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>spatial_ref</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-8a777d36-bce3-4d6b-b457-2367dba2c9ea' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-8a777d36-bce3-4d6b-b457-2367dba2c9ea' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-81333750-7375-4b92-ae88-81e987bd2ac5' class='xr-var-data-in' type='checkbox'><label for='data-81333750-7375-4b92-ae88-81e987bd2ac5' 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>crs_wkt :</span></dt><dd>PROJCS[&quot;undefined&quot;,GEOGCS[&quot;undefined&quot;,DATUM[&quot;undefined&quot;,SPHEROID[&quot;undefined&quot;,6367470,0]],PRIMEM[&quot;Greenwich&quot;,0,AUTHORITY[&quot;EPSG&quot;,&quot;8901&quot;]],UNIT[&quot;degree&quot;,0.0174532925199433]],PROJECTION[&quot;Lambert_Conformal_Conic_1SP&quot;],PARAMETER[&quot;latitude_of_origin&quot;,53.5],PARAMETER[&quot;central_meridian&quot;,5],PARAMETER[&quot;scale_factor&quot;,1],PARAMETER[&quot;false_easting&quot;,1481641.67696368],PARAMETER[&quot;false_northing&quot;,537326.063885016],UNIT[&quot;metre&quot;,1,AUTHORITY[&quot;EPSG&quot;,&quot;9001&quot;]],AXIS[&quot;Easting&quot;,EAST],AXIS[&quot;Northing&quot;,NORTH]]</dd><dt><span>semi_major_axis :</span></dt><dd>6367470.0</dd><dt><span>semi_minor_axis :</span></dt><dd>6367470.0</dd><dt><span>inverse_flattening :</span></dt><dd>0.0</dd><dt><span>reference_ellipsoid_name :</span></dt><dd>undefined</dd><dt><span>longitude_of_prime_meridian :</span></dt><dd>0.0</dd><dt><span>prime_meridian_name :</span></dt><dd>Greenwich</dd><dt><span>geographic_crs_name :</span></dt><dd>undefined</dd><dt><span>horizontal_datum_name :</span></dt><dd>undefined</dd><dt><span>projected_crs_name :</span></dt><dd>undefined</dd><dt><span>grid_mapping_name :</span></dt><dd>lambert_conformal_conic</dd><dt><span>standard_parallel :</span></dt><dd>53.5</dd><dt><span>longitude_of_central_meridian :</span></dt><dd>5.0</dd><dt><span>false_easting :</span></dt><dd>1481641.67696368</dd><dt><span>false_northing :</span></dt><dd>537326.063885016</dd><dt><span>spatial_ref :</span></dt><dd>PROJCS[&quot;undefined&quot;,GEOGCS[&quot;undefined&quot;,DATUM[&quot;undefined&quot;,SPHEROID[&quot;undefined&quot;,6367470,0]],PRIMEM[&quot;Greenwich&quot;,0,AUTHORITY[&quot;EPSG&quot;,&quot;8901&quot;]],UNIT[&quot;degree&quot;,0.0174532925199433]],PROJECTION[&quot;Lambert_Conformal_Conic_1SP&quot;],PARAMETER[&quot;latitude_of_origin&quot;,53.5],PARAMETER[&quot;central_meridian&quot;,5],PARAMETER[&quot;scale_factor&quot;,1],PARAMETER[&quot;false_easting&quot;,1481641.67696368],PARAMETER[&quot;false_northing&quot;,537326.063885016],UNIT[&quot;metre&quot;,1,AUTHORITY[&quot;EPSG&quot;,&quot;9001&quot;]],AXIS[&quot;Easting&quot;,EAST],AXIS[&quot;Northing&quot;,NORTH]]</dd><dt><span>GeoTransform :</span></dt><dd>413750.0 2500.0 0.0 406250.0 0.0 2500.0</dd></dl></div><div class='xr-var-data'><pre>[1 values with dtype=int64]</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-4cd7fded-6c57-439f-b75f-94c62591fcbf' class='xr-section-summary-in' type='checkbox'  checked><label for='section-4cd7fded-6c57-439f-b75f-94c62591fcbf' class='xr-section-summary' >Data variables: <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>grad</span></div><div class='xr-var-dims'>(time, y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(4871, 85, 81), meta=np.ndarray&gt;</div><input id='attrs-50075a85-ca6f-4344-b817-1e01deddac12' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-50075a85-ca6f-4344-b817-1e01deddac12' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-903225db-95bb-49a6-9fcf-47b9c0e82368' class='xr-var-data-in' type='checkbox'><label for='data-903225db-95bb-49a6-9fcf-47b9c0e82368' 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>GRIB_paramId :</span></dt><dd>233253117</dd><dt><span>GRIB_numberOfPoints :</span></dt><dd>258681</dd><dt><span>GRIB_typeOfLevel :</span></dt><dd>heightAboveGround</dd><dt><span>GRIB_stepUnits :</span></dt><dd>1</dd><dt><span>GRIB_stepType :</span></dt><dd>accum</dd><dt><span>GRIB_gridType :</span></dt><dd>lambert</dd><dt><span>GRIB_DxInMetres :</span></dt><dd>2500</dd><dt><span>GRIB_DyInMetres :</span></dt><dd>2500</dd><dt><span>GRIB_LaDInDegrees :</span></dt><dd>53.5</dd><dt><span>GRIB_Latin1InDegrees :</span></dt><dd>53.5</dd><dt><span>GRIB_Latin2InDegrees :</span></dt><dd>53.5</dd><dt><span>GRIB_LoVInDegrees :</span></dt><dd>5.0</dd><dt><span>GRIB_NV :</span></dt><dd>132</dd><dt><span>GRIB_Nx :</span></dt><dd>529</dd><dt><span>GRIB_Ny :</span></dt><dd>489</dd><dt><span>GRIB_cfName :</span></dt><dd>unknown</dd><dt><span>GRIB_cfVarName :</span></dt><dd>unknown</dd><dt><span>GRIB_gridDefinitionDescription :</span></dt><dd>Lambert Conformal</dd><dt><span>GRIB_iScansNegatively :</span></dt><dd>0</dd><dt><span>GRIB_jPointsAreConsecutive :</span></dt><dd>0</dd><dt><span>GRIB_jScansPositively :</span></dt><dd>1</dd><dt><span>GRIB_latitudeOfFirstGridPointInDegrees :</span></dt><dd>46.834</dd><dt><span>GRIB_latitudeOfSouthernPoleInDegrees :</span></dt><dd>0.0</dd><dt><span>GRIB_longitudeOfFirstGridPointInDegrees :</span></dt><dd>-14.609</dd><dt><span>GRIB_longitudeOfSouthernPoleInDegrees :</span></dt><dd>0.0</dd><dt><span>GRIB_missingValue :</span></dt><dd>3.4028234663852886e+38</dd><dt><span>GRIB_name :</span></dt><dd>Global radiation flux</dd><dt><span>GRIB_shortName :</span></dt><dd>grad</dd><dt><span>GRIB_units :</span></dt><dd>W m**-2</dd><dt><span>long_name :</span></dt><dd>Global radiation flux</dd><dt><span>units :</span></dt><dd>MJ m⁻² day⁻¹</dd><dt><span>standard_name :</span></dt><dd>unknown</dd></dl></div><div 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       "                        <th> Bytes </th>\n",
       "                        <td> 913.57 MiB </td>\n",
       "                        <td> 127.93 MiB </td>\n",
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       "                        <th> Shape </th>\n",
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       "                        <td> (4871, 85, 81) </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Dask graph </th>\n",
       "                        <td colspan=\"2\"> 8 chunks in 3 graph layers </td>\n",
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       "                        <th> Data type </th>\n",
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       "</table></div></li></ul></div></li><li class='xr-section-item'><input id='section-dfc1e8b6-c937-4ba6-a2f6-24a3dfee86da' class='xr-section-summary-in' type='checkbox'  ><label for='section-dfc1e8b6-c937-4ba6-a2f6-24a3dfee86da' class='xr-section-summary' >Indexes: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>x</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-a9a91e48-bd5a-4715-b66a-a2520824c033' class='xr-index-data-in' type='checkbox'/><label for='index-a9a91e48-bd5a-4715-b66a-a2520824c033' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Float64Index([415000.0, 417500.0, 420000.0, 422500.0, 425000.0, 427500.0,\n",
       "              430000.0, 432500.0, 435000.0, 437500.0,\n",
       "              ...\n",
       "              785000.0, 787500.0, 790000.0, 792500.0, 795000.0, 797500.0,\n",
       "              800000.0, 802500.0, 805000.0, 807500.0],\n",
       "             dtype=&#x27;float64&#x27;, name=&#x27;x&#x27;, length=158))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>y</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-7680e04e-fbfc-4e25-b154-e58496599894' class='xr-index-data-in' type='checkbox'/><label for='index-7680e04e-fbfc-4e25-b154-e58496599894' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Float64Index([407500.0, 410000.0, 412500.0, 415000.0, 417500.0, 420000.0,\n",
       "              422500.0, 425000.0, 427500.0, 430000.0,\n",
       "              ...\n",
       "              797500.0, 800000.0, 802500.0, 805000.0, 807500.0, 810000.0,\n",
       "              812500.0, 815000.0, 817500.0, 820000.0],\n",
       "             dtype=&#x27;float64&#x27;, name=&#x27;y&#x27;, length=166))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>time</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-e7f08ae7-c818-49c7-9179-03310aaebae1' class='xr-index-data-in' type='checkbox'/><label for='index-e7f08ae7-c818-49c7-9179-03310aaebae1' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(DatetimeIndex([&#x27;1981-01-01&#x27;, &#x27;1981-01-02&#x27;, &#x27;1981-01-03&#x27;, &#x27;1981-01-04&#x27;,\n",
       "               &#x27;1981-01-05&#x27;, &#x27;1981-01-06&#x27;, &#x27;1981-01-07&#x27;, &#x27;1981-01-08&#x27;,\n",
       "               &#x27;1981-01-09&#x27;, &#x27;1981-01-10&#x27;,\n",
       "               ...\n",
       "               &#x27;2005-12-22&#x27;, &#x27;2005-12-23&#x27;, &#x27;2005-12-24&#x27;, &#x27;2005-12-25&#x27;,\n",
       "               &#x27;2005-12-26&#x27;, &#x27;2005-12-27&#x27;, &#x27;2005-12-28&#x27;, &#x27;2005-12-29&#x27;,\n",
       "               &#x27;2005-12-30&#x27;, &#x27;2005-12-31&#x27;],\n",
       "              dtype=&#x27;datetime64[ns]&#x27;, name=&#x27;time&#x27;, length=9131, freq=None))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-933b00c3-4e1f-48bf-8608-164f8d9ae912' class='xr-section-summary-in' type='checkbox'  checked><label for='section-933b00c3-4e1f-48bf-8608-164f8d9ae912' class='xr-section-summary' >Attributes: <span>(4)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>CDI :</span></dt><dd>Climate Data Interface version 2.0.5 (https://mpimet.mpg.de/cdi)</dd><dt><span>Conventions :</span></dt><dd>CF-1.6</dd><dt><span>history :</span></dt><dd>Wed Mar 22 21:11:40 2023: cdo -s -f nc4c -shifttime,-3hour -copy -seltimestep,3/744/3 /run/media/nms/Elements/MERA/grib/117_105_0_4_FC3hr/temp/MERA_PRODYEAR_1981_01_117_105_0_4_FC3hr /run/media/nms/Elements/MERA/grib/117_105_0_4_FC3hr/temp/MERA_PRODYEAR_1981_01_117_105_0_4_FC3hr.nc</dd><dt><span>CDO :</span></dt><dd>Climate Data Operators version 2.0.5 (https://mpimet.mpg.de/cdo)</dd></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.Dataset>\n",
       "Dimensions:            (x: 158, y: 166, time: 9131)\n",
       "Coordinates:\n",
       "  * x                  (x) float64 4.15e+05 4.175e+05 ... 8.05e+05 8.075e+05\n",
       "  * y                  (y) float64 4.075e+05 4.1e+05 ... 8.175e+05 8.2e+05\n",
       "    height             float64 0.0\n",
       "    Lambert_Conformal  int64 ...\n",
       "  * time               (time) datetime64[ns] 1981-01-01 ... 2005-12-31\n",
       "    spatial_ref        int64 ...\n",
       "Data variables:\n",
       "    grad               (time, y, x) float32 dask.array<chunksize=(4871, 85, 81), meta=np.ndarray>\n",
       "Attributes:\n",
       "    CDI:          Climate Data Interface version 2.0.5 (https://mpimet.mpg.de...\n",
       "    Conventions:  CF-1.6\n",
       "    history:      Wed Mar 22 21:11:40 2023: cdo -s -f nc4c -shifttime,-3hour ...\n",
       "    CDO:          Climate Data Operators version 2.0.5 (https://mpimet.mpg.de..."
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ds[\"117_105_0_4\"]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
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       "  --xr-border-color: var(--jp-border-color2, #e0e0e0);\n",
       "  --xr-disabled-color: var(--jp-layout-color3, #bdbdbd);\n",
       "  --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[data-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 !important;\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-index-preview {\n",
       "  grid-column: 2 / 5;\n",
       "  color: var(--xr-font-color2);\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",
       ".xr-index-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",
       ".xr-index-data-in:checked ~ .xr-index-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-index-name div,\n",
       ".xr-index-data,\n",
       ".xr-attrs {\n",
       "  padding-left: 25px !important;\n",
       "}\n",
       "\n",
       ".xr-attrs,\n",
       ".xr-var-attrs,\n",
       ".xr-var-data,\n",
       ".xr-index-data {\n",
       "  grid-column: 1 / -1;\n",
       "}\n",
       "\n",
       "dl.xr-attrs {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  display: grid;\n",
       "  grid-template-columns: 125px auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt,\n",
       ".xr-attrs dd {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  float: left;\n",
       "  padding-right: 10px;\n",
       "  width: auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt {\n",
       "  font-weight: normal;\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-attrs dt:hover span {\n",
       "  display: inline-block;\n",
       "  background: var(--xr-background-color);\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-attrs dd {\n",
       "  grid-column: 2;\n",
       "  white-space: pre-wrap;\n",
       "  word-break: break-all;\n",
       "}\n",
       "\n",
       ".xr-icon-database,\n",
       ".xr-icon-file-text2,\n",
       ".xr-no-icon {\n",
       "  display: inline-block;\n",
       "  vertical-align: middle;\n",
       "  width: 1em;\n",
       "  height: 1.5em !important;\n",
       "  stroke-width: 0;\n",
       "  stroke: currentColor;\n",
       "  fill: currentColor;\n",
       "}\n",
       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt;\n",
       "Dimensions:            (x: 158, y: 166, time: 9131)\n",
       "Coordinates:\n",
       "  * x                  (x) float64 4.15e+05 4.175e+05 ... 8.05e+05 8.075e+05\n",
       "  * y                  (y) float64 4.075e+05 4.1e+05 ... 8.175e+05 8.2e+05\n",
       "    height             float64 ...\n",
       "    Lambert_Conformal  int64 ...\n",
       "  * time               (time) datetime64[ns] 1981-01-01 ... 2005-12-31\n",
       "    spatial_ref        int64 ...\n",
       "Data variables:\n",
       "    PET                (time, y, x) float32 dask.array&lt;chunksize=(4756, 86, 82), meta=np.ndarray&gt;\n",
       "Attributes:\n",
       "    CDI:          Climate Data Interface version 2.0.5 (https://mpimet.mpg.de...\n",
       "    Conventions:  CF-1.6\n",
       "    CDO:          Climate Data Operators version 2.0.5 (https://mpimet.mpg.de...</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-ca85bdcc-a3b8-44c8-9b9d-8094dd6e1f5f' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-ca85bdcc-a3b8-44c8-9b9d-8094dd6e1f5f' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>x</span>: 158</li><li><span class='xr-has-index'>y</span>: 166</li><li><span class='xr-has-index'>time</span>: 9131</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-54b96b5e-49a9-49c5-8a6e-a3e2d809e87d' class='xr-section-summary-in' type='checkbox'  checked><label for='section-54b96b5e-49a9-49c5-8a6e-a3e2d809e87d' class='xr-section-summary' >Coordinates: <span>(6)</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'>x</span></div><div class='xr-var-dims'>(x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>4.15e+05 4.175e+05 ... 8.075e+05</div><input id='attrs-3d14b10d-102a-4f24-a256-e2e6b29baae1' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3d14b10d-102a-4f24-a256-e2e6b29baae1' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c7d01edf-b5b6-4f74-a3a3-444f23dd2a10' class='xr-var-data-in' type='checkbox'><label for='data-c7d01edf-b5b6-4f74-a3a3-444f23dd2a10' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>projection_x_coordinate</dd><dt><span>units :</span></dt><dd>metre</dd><dt><span>axis :</span></dt><dd>X</dd><dt><span>long_name :</span></dt><dd>x coordinate of projection</dd></dl></div><div class='xr-var-data'><pre>array([415000., 417500., 420000., 422500., 425000., 427500., 430000., 432500.,\n",
       "       435000., 437500., 440000., 442500., 445000., 447500., 450000., 452500.,\n",
       "       455000., 457500., 460000., 462500., 465000., 467500., 470000., 472500.,\n",
       "       475000., 477500., 480000., 482500., 485000., 487500., 490000., 492500.,\n",
       "       495000., 497500., 500000., 502500., 505000., 507500., 510000., 512500.,\n",
       "       515000., 517500., 520000., 522500., 525000., 527500., 530000., 532500.,\n",
       "       535000., 537500., 540000., 542500., 545000., 547500., 550000., 552500.,\n",
       "       555000., 557500., 560000., 562500., 565000., 567500., 570000., 572500.,\n",
       "       575000., 577500., 580000., 582500., 585000., 587500., 590000., 592500.,\n",
       "       595000., 597500., 600000., 602500., 605000., 607500., 610000., 612500.,\n",
       "       615000., 617500., 620000., 622500., 625000., 627500., 630000., 632500.,\n",
       "       635000., 637500., 640000., 642500., 645000., 647500., 650000., 652500.,\n",
       "       655000., 657500., 660000., 662500., 665000., 667500., 670000., 672500.,\n",
       "       675000., 677500., 680000., 682500., 685000., 687500., 690000., 692500.,\n",
       "       695000., 697500., 700000., 702500., 705000., 707500., 710000., 712500.,\n",
       "       715000., 717500., 720000., 722500., 725000., 727500., 730000., 732500.,\n",
       "       735000., 737500., 740000., 742500., 745000., 747500., 750000., 752500.,\n",
       "       755000., 757500., 760000., 762500., 765000., 767500., 770000., 772500.,\n",
       "       775000., 777500., 780000., 782500., 785000., 787500., 790000., 792500.,\n",
       "       795000., 797500., 800000., 802500., 805000., 807500.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>y</span></div><div class='xr-var-dims'>(y)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>4.075e+05 4.1e+05 ... 8.2e+05</div><input id='attrs-59eb6c1f-5996-494a-88fe-eed4e965f7cb' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-59eb6c1f-5996-494a-88fe-eed4e965f7cb' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-443eb2e5-76f5-48ba-a92a-781d965b0a8d' class='xr-var-data-in' type='checkbox'><label for='data-443eb2e5-76f5-48ba-a92a-781d965b0a8d' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>projection_y_coordinate</dd><dt><span>units :</span></dt><dd>metre</dd><dt><span>axis :</span></dt><dd>Y</dd><dt><span>long_name :</span></dt><dd>y coordinate of projection</dd></dl></div><div class='xr-var-data'><pre>array([407500., 410000., 412500., 415000., 417500., 420000., 422500., 425000.,\n",
       "       427500., 430000., 432500., 435000., 437500., 440000., 442500., 445000.,\n",
       "       447500., 450000., 452500., 455000., 457500., 460000., 462500., 465000.,\n",
       "       467500., 470000., 472500., 475000., 477500., 480000., 482500., 485000.,\n",
       "       487500., 490000., 492500., 495000., 497500., 500000., 502500., 505000.,\n",
       "       507500., 510000., 512500., 515000., 517500., 520000., 522500., 525000.,\n",
       "       527500., 530000., 532500., 535000., 537500., 540000., 542500., 545000.,\n",
       "       547500., 550000., 552500., 555000., 557500., 560000., 562500., 565000.,\n",
       "       567500., 570000., 572500., 575000., 577500., 580000., 582500., 585000.,\n",
       "       587500., 590000., 592500., 595000., 597500., 600000., 602500., 605000.,\n",
       "       607500., 610000., 612500., 615000., 617500., 620000., 622500., 625000.,\n",
       "       627500., 630000., 632500., 635000., 637500., 640000., 642500., 645000.,\n",
       "       647500., 650000., 652500., 655000., 657500., 660000., 662500., 665000.,\n",
       "       667500., 670000., 672500., 675000., 677500., 680000., 682500., 685000.,\n",
       "       687500., 690000., 692500., 695000., 697500., 700000., 702500., 705000.,\n",
       "       707500., 710000., 712500., 715000., 717500., 720000., 722500., 725000.,\n",
       "       727500., 730000., 732500., 735000., 737500., 740000., 742500., 745000.,\n",
       "       747500., 750000., 752500., 755000., 757500., 760000., 762500., 765000.,\n",
       "       767500., 770000., 772500., 775000., 777500., 780000., 782500., 785000.,\n",
       "       787500., 790000., 792500., 795000., 797500., 800000., 802500., 805000.,\n",
       "       807500., 810000., 812500., 815000., 817500., 820000.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>height</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-d7c6b356-373d-43b7-8370-910d43300942' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d7c6b356-373d-43b7-8370-910d43300942' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-56d4b8c3-c8eb-4f25-986b-55bdd6398f65' class='xr-var-data-in' type='checkbox'><label for='data-56d4b8c3-c8eb-4f25-986b-55bdd6398f65' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>height</dd><dt><span>long_name :</span></dt><dd>height</dd><dt><span>units :</span></dt><dd>m</dd><dt><span>positive :</span></dt><dd>up</dd><dt><span>axis :</span></dt><dd>Z</dd></dl></div><div class='xr-var-data'><pre>[1 values with dtype=float64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Lambert_Conformal</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-705f34ad-58f8-4251-8602-2de3809d3631' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-705f34ad-58f8-4251-8602-2de3809d3631' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2d3518fc-8fe1-46e6-9a96-f6509cb089a6' class='xr-var-data-in' type='checkbox'><label for='data-2d3518fc-8fe1-46e6-9a96-f6509cb089a6' 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>crs_wkt :</span></dt><dd>PROJCS[&quot;undefined&quot;,GEOGCS[&quot;undefined&quot;,DATUM[&quot;undefined&quot;,SPHEROID[&quot;undefined&quot;,6367470,0]],PRIMEM[&quot;Greenwich&quot;,0,AUTHORITY[&quot;EPSG&quot;,&quot;8901&quot;]],UNIT[&quot;degree&quot;,0.0174532925199433]],PROJECTION[&quot;Lambert_Conformal_Conic_1SP&quot;],PARAMETER[&quot;latitude_of_origin&quot;,53.5],PARAMETER[&quot;central_meridian&quot;,5],PARAMETER[&quot;scale_factor&quot;,1],PARAMETER[&quot;false_easting&quot;,1481641.67696368],PARAMETER[&quot;false_northing&quot;,537326.063885016],UNIT[&quot;metre&quot;,1,AUTHORITY[&quot;EPSG&quot;,&quot;9001&quot;]],AXIS[&quot;Easting&quot;,EAST],AXIS[&quot;Northing&quot;,NORTH]]</dd><dt><span>semi_major_axis :</span></dt><dd>6367470.0</dd><dt><span>semi_minor_axis :</span></dt><dd>6367470.0</dd><dt><span>inverse_flattening :</span></dt><dd>0.0</dd><dt><span>reference_ellipsoid_name :</span></dt><dd>undefined</dd><dt><span>longitude_of_prime_meridian :</span></dt><dd>0.0</dd><dt><span>prime_meridian_name :</span></dt><dd>Greenwich</dd><dt><span>geographic_crs_name :</span></dt><dd>undefined</dd><dt><span>horizontal_datum_name :</span></dt><dd>undefined</dd><dt><span>projected_crs_name :</span></dt><dd>undefined</dd><dt><span>grid_mapping_name :</span></dt><dd>lambert_conformal_conic</dd><dt><span>standard_parallel :</span></dt><dd>53.5</dd><dt><span>longitude_of_central_meridian :</span></dt><dd>5.0</dd><dt><span>false_easting :</span></dt><dd>1481641.67696368</dd><dt><span>false_northing :</span></dt><dd>537326.063885016</dd><dt><span>spatial_ref :</span></dt><dd>PROJCS[&quot;undefined&quot;,GEOGCS[&quot;undefined&quot;,DATUM[&quot;undefined&quot;,SPHEROID[&quot;undefined&quot;,6367470,0]],PRIMEM[&quot;Greenwich&quot;,0,AUTHORITY[&quot;EPSG&quot;,&quot;8901&quot;]],UNIT[&quot;degree&quot;,0.0174532925199433]],PROJECTION[&quot;Lambert_Conformal_Conic_1SP&quot;],PARAMETER[&quot;latitude_of_origin&quot;,53.5],PARAMETER[&quot;central_meridian&quot;,5],PARAMETER[&quot;scale_factor&quot;,1],PARAMETER[&quot;false_easting&quot;,1481641.67696368],PARAMETER[&quot;false_northing&quot;,537326.063885016],UNIT[&quot;metre&quot;,1,AUTHORITY[&quot;EPSG&quot;,&quot;9001&quot;]],AXIS[&quot;Easting&quot;,EAST],AXIS[&quot;Northing&quot;,NORTH]]</dd><dt><span>GeoTransform :</span></dt><dd>413750.0 2500.0 0.0 406250.0 0.0 2500.0</dd></dl></div><div class='xr-var-data'><pre>[1 values with dtype=int64]</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'>1981-01-01 ... 2005-12-31</div><input id='attrs-6aff4d22-3964-4de1-b440-ceb108b3822a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-6aff4d22-3964-4de1-b440-ceb108b3822a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-82ea9900-b302-4a13-8266-f6198a8a00f5' class='xr-var-data-in' type='checkbox'><label for='data-82ea9900-b302-4a13-8266-f6198a8a00f5' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>time</dd><dt><span>axis :</span></dt><dd>T</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;1981-01-01T00:00:00.000000000&#x27;, &#x27;1981-01-02T00:00:00.000000000&#x27;,\n",
       "       &#x27;1981-01-03T00:00:00.000000000&#x27;, ..., &#x27;2005-12-29T00:00:00.000000000&#x27;,\n",
       "       &#x27;2005-12-30T00:00:00.000000000&#x27;, &#x27;2005-12-31T00:00:00.000000000&#x27;],\n",
       "      dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>spatial_ref</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-41dada48-861a-477a-880d-b3674c6e1663' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-41dada48-861a-477a-880d-b3674c6e1663' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a7cb6038-6a86-4321-8347-e08295f23607' class='xr-var-data-in' type='checkbox'><label for='data-a7cb6038-6a86-4321-8347-e08295f23607' 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>crs_wkt :</span></dt><dd>PROJCS[&quot;undefined&quot;,GEOGCS[&quot;undefined&quot;,DATUM[&quot;undefined&quot;,SPHEROID[&quot;undefined&quot;,6367470,0]],PRIMEM[&quot;Greenwich&quot;,0,AUTHORITY[&quot;EPSG&quot;,&quot;8901&quot;]],UNIT[&quot;degree&quot;,0.0174532925199433]],PROJECTION[&quot;Lambert_Conformal_Conic_1SP&quot;],PARAMETER[&quot;latitude_of_origin&quot;,53.5],PARAMETER[&quot;central_meridian&quot;,5],PARAMETER[&quot;scale_factor&quot;,1],PARAMETER[&quot;false_easting&quot;,1481641.67696368],PARAMETER[&quot;false_northing&quot;,537326.063885016],UNIT[&quot;metre&quot;,1,AUTHORITY[&quot;EPSG&quot;,&quot;9001&quot;]],AXIS[&quot;Easting&quot;,EAST],AXIS[&quot;Northing&quot;,NORTH]]</dd><dt><span>semi_major_axis :</span></dt><dd>6367470.0</dd><dt><span>semi_minor_axis :</span></dt><dd>6367470.0</dd><dt><span>inverse_flattening :</span></dt><dd>0.0</dd><dt><span>reference_ellipsoid_name :</span></dt><dd>undefined</dd><dt><span>longitude_of_prime_meridian :</span></dt><dd>0.0</dd><dt><span>prime_meridian_name :</span></dt><dd>Greenwich</dd><dt><span>geographic_crs_name :</span></dt><dd>undefined</dd><dt><span>horizontal_datum_name :</span></dt><dd>undefined</dd><dt><span>projected_crs_name :</span></dt><dd>undefined</dd><dt><span>grid_mapping_name :</span></dt><dd>lambert_conformal_conic</dd><dt><span>standard_parallel :</span></dt><dd>53.5</dd><dt><span>longitude_of_central_meridian :</span></dt><dd>5.0</dd><dt><span>false_easting :</span></dt><dd>1481641.67696368</dd><dt><span>false_northing :</span></dt><dd>537326.063885016</dd><dt><span>spatial_ref :</span></dt><dd>PROJCS[&quot;undefined&quot;,GEOGCS[&quot;undefined&quot;,DATUM[&quot;undefined&quot;,SPHEROID[&quot;undefined&quot;,6367470,0]],PRIMEM[&quot;Greenwich&quot;,0,AUTHORITY[&quot;EPSG&quot;,&quot;8901&quot;]],UNIT[&quot;degree&quot;,0.0174532925199433]],PROJECTION[&quot;Lambert_Conformal_Conic_1SP&quot;],PARAMETER[&quot;latitude_of_origin&quot;,53.5],PARAMETER[&quot;central_meridian&quot;,5],PARAMETER[&quot;scale_factor&quot;,1],PARAMETER[&quot;false_easting&quot;,1481641.67696368],PARAMETER[&quot;false_northing&quot;,537326.063885016],UNIT[&quot;metre&quot;,1,AUTHORITY[&quot;EPSG&quot;,&quot;9001&quot;]],AXIS[&quot;Easting&quot;,EAST],AXIS[&quot;Northing&quot;,NORTH]]</dd><dt><span>GeoTransform :</span></dt><dd>413750.0 2500.0 0.0 406250.0 0.0 2500.0</dd></dl></div><div class='xr-var-data'><pre>[1 values with dtype=int64]</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-68403084-258b-4931-ac18-0000771b621b' class='xr-section-summary-in' type='checkbox'  checked><label for='section-68403084-258b-4931-ac18-0000771b621b' class='xr-section-summary' >Data variables: <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>PET</span></div><div class='xr-var-dims'>(time, y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(4756, 86, 82), meta=np.ndarray&gt;</div><input id='attrs-223e77a9-046d-4637-be63-eeb33960977b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-223e77a9-046d-4637-be63-eeb33960977b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5f4226fa-2256-4d89-8f31-3ed93b94b0e0' class='xr-var-data-in' type='checkbox'><label for='data-5f4226fa-2256-4d89-8f31-3ed93b94b0e0' 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>mm day⁻¹</dd><dt><span>long_name :</span></dt><dd>Reference evapotranspiration</dd></dl></div><div class='xr-var-data'><table>\n",
       "    <tr>\n",
       "        <td>\n",
       "            <table style=\"border-collapse: collapse;\">\n",
       "                <thead>\n",
       "                    <tr>\n",
       "                        <td> </td>\n",
       "                        <th> Array </th>\n",
       "                        <th> Chunk </th>\n",
       "                    </tr>\n",
       "                </thead>\n",
       "                <tbody>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 913.57 MiB </td>\n",
       "                        <td> 127.94 MiB </td>\n",
       "                    </tr>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> (9131, 166, 158) </td>\n",
       "                        <td> (4756, 86, 82) </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Dask graph </th>\n",
       "                        <td colspan=\"2\"> 8 chunks in 2 graph layers </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Data type </th>\n",
       "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
       "                    </tr>\n",
       "                </tbody>\n",
       "            </table>\n",
       "        </td>\n",
       "        <td>\n",
       "        <svg width=\"158\" height=\"149\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
       "\n",
       "  <!-- Horizontal lines -->\n",
       "  <line x1=\"10\" y1=\"0\" x2=\"80\" y2=\"70\" style=\"stroke-width:2\" />\n",
       "  <line x1=\"10\" y1=\"14\" x2=\"80\" y2=\"85\" />\n",
       "  <line x1=\"10\" y1=\"28\" x2=\"80\" y2=\"99\" style=\"stroke-width:2\" />\n",
       "\n",
       "  <!-- Vertical lines -->\n",
       "  <line x1=\"10\" y1=\"0\" x2=\"10\" y2=\"28\" style=\"stroke-width:2\" />\n",
       "  <line x1=\"46\" y1=\"36\" x2=\"46\" y2=\"65\" />\n",
       "  <line x1=\"80\" y1=\"70\" x2=\"80\" y2=\"99\" style=\"stroke-width:2\" />\n",
       "\n",
       "  <!-- Colored Rectangle -->\n",
       "  <polygon points=\"10.0,0.0 80.58823529411765,70.58823529411765 80.58823529411765,99.08682694645151 10.0,28.498591652333857\" style=\"fill:#ECB172A0;stroke-width:0\"/>\n",
       "\n",
       "  <!-- Horizontal lines -->\n",
       "  <line x1=\"10\" y1=\"0\" x2=\"38\" y2=\"0\" style=\"stroke-width:2\" />\n",
       "  <line x1=\"46\" y1=\"36\" x2=\"74\" y2=\"36\" />\n",
       "  <line x1=\"80\" y1=\"70\" x2=\"108\" y2=\"70\" style=\"stroke-width:2\" />\n",
       "\n",
       "  <!-- Vertical lines -->\n",
       "  <line x1=\"10\" y1=\"0\" x2=\"80\" y2=\"70\" style=\"stroke-width:2\" />\n",
       "  <line x1=\"24\" y1=\"0\" x2=\"95\" y2=\"70\" />\n",
       "  <line x1=\"38\" y1=\"0\" x2=\"108\" y2=\"70\" style=\"stroke-width:2\" />\n",
       "\n",
       "  <!-- Colored Rectangle -->\n",
       "  <polygon points=\"10.0,0.0 38.22717743315806,0.0 108.81541272727571,70.58823529411765 80.58823529411765,70.58823529411765\" style=\"fill:#ECB172A0;stroke-width:0\"/>\n",
       "\n",
       "  <!-- Horizontal lines -->\n",
       "  <line x1=\"80\" y1=\"70\" x2=\"108\" y2=\"70\" style=\"stroke-width:2\" />\n",
       "  <line x1=\"80\" y1=\"85\" x2=\"108\" y2=\"85\" />\n",
       "  <line x1=\"80\" y1=\"99\" x2=\"108\" y2=\"99\" style=\"stroke-width:2\" />\n",
       "\n",
       "  <!-- Vertical lines -->\n",
       "  <line x1=\"80\" y1=\"70\" x2=\"80\" y2=\"99\" style=\"stroke-width:2\" />\n",
       "  <line x1=\"95\" y1=\"70\" x2=\"95\" y2=\"99\" />\n",
       "  <line x1=\"108\" y1=\"70\" x2=\"108\" y2=\"99\" style=\"stroke-width:2\" />\n",
       "\n",
       "  <!-- Colored Rectangle -->\n",
       "  <polygon points=\"80.58823529411765,70.58823529411765 108.81541272727571,70.58823529411765 108.81541272727571,99.08682694645151 80.58823529411765,99.08682694645151\" style=\"fill:#ECB172A0;stroke-width:0\"/>\n",
       "\n",
       "  <!-- Text -->\n",
       "  <text x=\"94.701824\" y=\"119.086827\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >158</text>\n",
       "  <text x=\"128.815413\" y=\"84.837531\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(-90,128.815413,84.837531)\">166</text>\n",
       "  <text x=\"35.294118\" y=\"83.792709\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(45,35.294118,83.792709)\">9131</text>\n",
       "</svg>\n",
       "        </td>\n",
       "    </tr>\n",
       "</table></div></li></ul></div></li><li class='xr-section-item'><input id='section-6b1c5478-8fd8-44c6-840a-0e8d12a7e480' class='xr-section-summary-in' type='checkbox'  ><label for='section-6b1c5478-8fd8-44c6-840a-0e8d12a7e480' class='xr-section-summary' >Indexes: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>x</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-1a2bfaae-6866-40b4-ab63-c67ae17eb9c2' class='xr-index-data-in' type='checkbox'/><label for='index-1a2bfaae-6866-40b4-ab63-c67ae17eb9c2' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Float64Index([415000.0, 417500.0, 420000.0, 422500.0, 425000.0, 427500.0,\n",
       "              430000.0, 432500.0, 435000.0, 437500.0,\n",
       "              ...\n",
       "              785000.0, 787500.0, 790000.0, 792500.0, 795000.0, 797500.0,\n",
       "              800000.0, 802500.0, 805000.0, 807500.0],\n",
       "             dtype=&#x27;float64&#x27;, name=&#x27;x&#x27;, length=158))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>y</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-8dd885a5-7784-4458-b098-58a07bb41d68' class='xr-index-data-in' type='checkbox'/><label for='index-8dd885a5-7784-4458-b098-58a07bb41d68' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Float64Index([407500.0, 410000.0, 412500.0, 415000.0, 417500.0, 420000.0,\n",
       "              422500.0, 425000.0, 427500.0, 430000.0,\n",
       "              ...\n",
       "              797500.0, 800000.0, 802500.0, 805000.0, 807500.0, 810000.0,\n",
       "              812500.0, 815000.0, 817500.0, 820000.0],\n",
       "             dtype=&#x27;float64&#x27;, name=&#x27;y&#x27;, length=166))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>time</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-c82d1efa-3e27-4be3-ace3-ec4bc2557846' class='xr-index-data-in' type='checkbox'/><label for='index-c82d1efa-3e27-4be3-ace3-ec4bc2557846' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(DatetimeIndex([&#x27;1981-01-01&#x27;, &#x27;1981-01-02&#x27;, &#x27;1981-01-03&#x27;, &#x27;1981-01-04&#x27;,\n",
       "               &#x27;1981-01-05&#x27;, &#x27;1981-01-06&#x27;, &#x27;1981-01-07&#x27;, &#x27;1981-01-08&#x27;,\n",
       "               &#x27;1981-01-09&#x27;, &#x27;1981-01-10&#x27;,\n",
       "               ...\n",
       "               &#x27;2005-12-22&#x27;, &#x27;2005-12-23&#x27;, &#x27;2005-12-24&#x27;, &#x27;2005-12-25&#x27;,\n",
       "               &#x27;2005-12-26&#x27;, &#x27;2005-12-27&#x27;, &#x27;2005-12-28&#x27;, &#x27;2005-12-29&#x27;,\n",
       "               &#x27;2005-12-30&#x27;, &#x27;2005-12-31&#x27;],\n",
       "              dtype=&#x27;datetime64[ns]&#x27;, name=&#x27;time&#x27;, length=9131, freq=None))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-b71bcd4b-2444-4241-84a1-203240c9f0c8' class='xr-section-summary-in' type='checkbox'  checked><label for='section-b71bcd4b-2444-4241-84a1-203240c9f0c8' class='xr-section-summary' >Attributes: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>CDI :</span></dt><dd>Climate Data Interface version 2.0.5 (https://mpimet.mpg.de/cdi)</dd><dt><span>Conventions :</span></dt><dd>CF-1.6</dd><dt><span>CDO :</span></dt><dd>Climate Data Operators version 2.0.5 (https://mpimet.mpg.de/cdo)</dd></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.Dataset>\n",
       "Dimensions:            (x: 158, y: 166, time: 9131)\n",
       "Coordinates:\n",
       "  * x                  (x) float64 4.15e+05 4.175e+05 ... 8.05e+05 8.075e+05\n",
       "  * y                  (y) float64 4.075e+05 4.1e+05 ... 8.175e+05 8.2e+05\n",
       "    height             float64 ...\n",
       "    Lambert_Conformal  int64 ...\n",
       "  * time               (time) datetime64[ns] 1981-01-01 ... 2005-12-31\n",
       "    spatial_ref        int64 ...\n",
       "Data variables:\n",
       "    PET                (time, y, x) float32 dask.array<chunksize=(4756, 86, 82), meta=np.ndarray>\n",
       "Attributes:\n",
       "    CDI:          Climate Data Interface version 2.0.5 (https://mpimet.mpg.de...\n",
       "    Conventions:  CF-1.6\n",
       "    CDO:          Climate Data Operators version 2.0.5 (https://mpimet.mpg.de..."
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ds[\"PET\"]"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Calculate photosynthetically active radiation (PAR)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Papaioannou et al. (1993) - irradiance ratio\n",
    "ds[\"117_105_0_4\"] = ds[\"117_105_0_4\"].assign(\n",
    "    PAR=ds[\"117_105_0_4\"][\"grad\"] * 0.473\n",
    ")\n",
    "ds[\"117_105_0_4\"][\"PAR\"].attrs[\n",
    "    \"long_name\"\n",
    "] = \"Surface Photosynthetically Active Radiation\"\n",
    "ds[\"117_105_0_4\"][\"PAR\"].attrs[\"units\"] = \"MJ m⁻² day⁻¹\""
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Merge datasets"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "# merge datasets\n",
    "ds = xr.combine_by_coords(\n",
    "    [ds[\"11_105_2_0\"], ds[\"61_105_0_4\"], ds[\"117_105_0_4\"], ds[\"PET\"]],\n",
    "    combine_attrs=\"drop_conflicts\",\n",
    "    compat=\"override\",\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "# drop global radiation\n",
    "ds = ds.drop_vars([\"grad\"])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "# rename other variables\n",
    "ds = ds.rename({\"t\": \"T\", \"tp\": \"PP\"})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "# assign dataset name\n",
    "ds.attrs[\"dataset\"] = \"IE_MERA_FC3hr_3_day\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
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       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt;\n",
       "Dimensions:            (x: 158, y: 166, time: 9131)\n",
       "Coordinates:\n",
       "  * x                  (x) float64 4.15e+05 4.175e+05 ... 8.05e+05 8.075e+05\n",
       "  * y                  (y) float64 4.075e+05 4.1e+05 ... 8.175e+05 8.2e+05\n",
       "    height             float64 0.0\n",
       "    Lambert_Conformal  int64 ...\n",
       "  * time               (time) datetime64[ns] 1981-01-01 ... 2005-12-31\n",
       "    spatial_ref        int64 0\n",
       "Data variables:\n",
       "    PAR                (time, y, x) float32 dask.array&lt;chunksize=(4871, 85, 81), meta=np.ndarray&gt;\n",
       "    PET                (time, y, x) float32 dask.array&lt;chunksize=(4756, 86, 82), meta=np.ndarray&gt;\n",
       "    T                  (time, y, x) float32 dask.array&lt;chunksize=(4871, 85, 81), meta=np.ndarray&gt;\n",
       "    PP                 (time, y, x) float32 dask.array&lt;chunksize=(4871, 85, 81), meta=np.ndarray&gt;\n",
       "Attributes:\n",
       "    CDI:          Climate Data Interface version 2.0.5 (https://mpimet.mpg.de...\n",
       "    Conventions:  CF-1.6\n",
       "    CDO:          Climate Data Operators version 2.0.5 (https://mpimet.mpg.de...\n",
       "    dataset:      IE_MERA_FC3hr_3_day</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-ddd5f085-6b16-4a53-9037-b389b8594963' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-ddd5f085-6b16-4a53-9037-b389b8594963' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>x</span>: 158</li><li><span class='xr-has-index'>y</span>: 166</li><li><span class='xr-has-index'>time</span>: 9131</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-c7ee2b01-bc13-4d57-959a-878e42b526e2' class='xr-section-summary-in' type='checkbox'  checked><label for='section-c7ee2b01-bc13-4d57-959a-878e42b526e2' class='xr-section-summary' >Coordinates: <span>(6)</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'>x</span></div><div class='xr-var-dims'>(x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>4.15e+05 4.175e+05 ... 8.075e+05</div><input id='attrs-331d4f75-c005-4795-bde7-0229da2ef954' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-331d4f75-c005-4795-bde7-0229da2ef954' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-af6acc58-fec4-4242-80f1-353fbca42147' class='xr-var-data-in' type='checkbox'><label for='data-af6acc58-fec4-4242-80f1-353fbca42147' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>projection_x_coordinate</dd><dt><span>units :</span></dt><dd>metre</dd><dt><span>axis :</span></dt><dd>X</dd><dt><span>long_name :</span></dt><dd>x coordinate of projection</dd></dl></div><div class='xr-var-data'><pre>array([415000., 417500., 420000., 422500., 425000., 427500., 430000., 432500.,\n",
       "       435000., 437500., 440000., 442500., 445000., 447500., 450000., 452500.,\n",
       "       455000., 457500., 460000., 462500., 465000., 467500., 470000., 472500.,\n",
       "       475000., 477500., 480000., 482500., 485000., 487500., 490000., 492500.,\n",
       "       495000., 497500., 500000., 502500., 505000., 507500., 510000., 512500.,\n",
       "       515000., 517500., 520000., 522500., 525000., 527500., 530000., 532500.,\n",
       "       535000., 537500., 540000., 542500., 545000., 547500., 550000., 552500.,\n",
       "       555000., 557500., 560000., 562500., 565000., 567500., 570000., 572500.,\n",
       "       575000., 577500., 580000., 582500., 585000., 587500., 590000., 592500.,\n",
       "       595000., 597500., 600000., 602500., 605000., 607500., 610000., 612500.,\n",
       "       615000., 617500., 620000., 622500., 625000., 627500., 630000., 632500.,\n",
       "       635000., 637500., 640000., 642500., 645000., 647500., 650000., 652500.,\n",
       "       655000., 657500., 660000., 662500., 665000., 667500., 670000., 672500.,\n",
       "       675000., 677500., 680000., 682500., 685000., 687500., 690000., 692500.,\n",
       "       695000., 697500., 700000., 702500., 705000., 707500., 710000., 712500.,\n",
       "       715000., 717500., 720000., 722500., 725000., 727500., 730000., 732500.,\n",
       "       735000., 737500., 740000., 742500., 745000., 747500., 750000., 752500.,\n",
       "       755000., 757500., 760000., 762500., 765000., 767500., 770000., 772500.,\n",
       "       775000., 777500., 780000., 782500., 785000., 787500., 790000., 792500.,\n",
       "       795000., 797500., 800000., 802500., 805000., 807500.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>y</span></div><div class='xr-var-dims'>(y)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>4.075e+05 4.1e+05 ... 8.2e+05</div><input id='attrs-13b0b28b-fdd5-4ce1-abb6-8d2ce04cd977' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-13b0b28b-fdd5-4ce1-abb6-8d2ce04cd977' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f4ec810d-85b9-476c-be02-bdd7a8039842' class='xr-var-data-in' type='checkbox'><label for='data-f4ec810d-85b9-476c-be02-bdd7a8039842' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>projection_y_coordinate</dd><dt><span>units :</span></dt><dd>metre</dd><dt><span>axis :</span></dt><dd>Y</dd><dt><span>long_name :</span></dt><dd>y coordinate of projection</dd></dl></div><div class='xr-var-data'><pre>array([407500., 410000., 412500., 415000., 417500., 420000., 422500., 425000.,\n",
       "       427500., 430000., 432500., 435000., 437500., 440000., 442500., 445000.,\n",
       "       447500., 450000., 452500., 455000., 457500., 460000., 462500., 465000.,\n",
       "       467500., 470000., 472500., 475000., 477500., 480000., 482500., 485000.,\n",
       "       487500., 490000., 492500., 495000., 497500., 500000., 502500., 505000.,\n",
       "       507500., 510000., 512500., 515000., 517500., 520000., 522500., 525000.,\n",
       "       527500., 530000., 532500., 535000., 537500., 540000., 542500., 545000.,\n",
       "       547500., 550000., 552500., 555000., 557500., 560000., 562500., 565000.,\n",
       "       567500., 570000., 572500., 575000., 577500., 580000., 582500., 585000.,\n",
       "       587500., 590000., 592500., 595000., 597500., 600000., 602500., 605000.,\n",
       "       607500., 610000., 612500., 615000., 617500., 620000., 622500., 625000.,\n",
       "       627500., 630000., 632500., 635000., 637500., 640000., 642500., 645000.,\n",
       "       647500., 650000., 652500., 655000., 657500., 660000., 662500., 665000.,\n",
       "       667500., 670000., 672500., 675000., 677500., 680000., 682500., 685000.,\n",
       "       687500., 690000., 692500., 695000., 697500., 700000., 702500., 705000.,\n",
       "       707500., 710000., 712500., 715000., 717500., 720000., 722500., 725000.,\n",
       "       727500., 730000., 732500., 735000., 737500., 740000., 742500., 745000.,\n",
       "       747500., 750000., 752500., 755000., 757500., 760000., 762500., 765000.,\n",
       "       767500., 770000., 772500., 775000., 777500., 780000., 782500., 785000.,\n",
       "       787500., 790000., 792500., 795000., 797500., 800000., 802500., 805000.,\n",
       "       807500., 810000., 812500., 815000., 817500., 820000.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>height</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0</div><input id='attrs-bda0f745-adff-4fc2-be44-d27cc81c998d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-bda0f745-adff-4fc2-be44-d27cc81c998d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c151f211-e75b-4443-bf6f-bf3f0362a5a8' class='xr-var-data-in' type='checkbox'><label for='data-c151f211-e75b-4443-bf6f-bf3f0362a5a8' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>height</dd><dt><span>long_name :</span></dt><dd>height</dd><dt><span>units :</span></dt><dd>m</dd><dt><span>positive :</span></dt><dd>up</dd><dt><span>axis :</span></dt><dd>Z</dd></dl></div><div class='xr-var-data'><pre>array(0.)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Lambert_Conformal</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-0595a616-2951-43cc-9db0-7ae092a4730a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-0595a616-2951-43cc-9db0-7ae092a4730a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9d41d470-3910-47ca-b18b-06535c5b6ebb' class='xr-var-data-in' type='checkbox'><label for='data-9d41d470-3910-47ca-b18b-06535c5b6ebb' 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>crs_wkt :</span></dt><dd>PROJCS[&quot;undefined&quot;,GEOGCS[&quot;undefined&quot;,DATUM[&quot;undefined&quot;,SPHEROID[&quot;undefined&quot;,6367470,0]],PRIMEM[&quot;Greenwich&quot;,0,AUTHORITY[&quot;EPSG&quot;,&quot;8901&quot;]],UNIT[&quot;degree&quot;,0.0174532925199433]],PROJECTION[&quot;Lambert_Conformal_Conic_1SP&quot;],PARAMETER[&quot;latitude_of_origin&quot;,53.5],PARAMETER[&quot;central_meridian&quot;,5],PARAMETER[&quot;scale_factor&quot;,1],PARAMETER[&quot;false_easting&quot;,1481641.67696368],PARAMETER[&quot;false_northing&quot;,537326.063885016],UNIT[&quot;metre&quot;,1,AUTHORITY[&quot;EPSG&quot;,&quot;9001&quot;]],AXIS[&quot;Easting&quot;,EAST],AXIS[&quot;Northing&quot;,NORTH]]</dd><dt><span>semi_major_axis :</span></dt><dd>6367470.0</dd><dt><span>semi_minor_axis :</span></dt><dd>6367470.0</dd><dt><span>inverse_flattening :</span></dt><dd>0.0</dd><dt><span>reference_ellipsoid_name :</span></dt><dd>undefined</dd><dt><span>longitude_of_prime_meridian :</span></dt><dd>0.0</dd><dt><span>prime_meridian_name :</span></dt><dd>Greenwich</dd><dt><span>geographic_crs_name :</span></dt><dd>undefined</dd><dt><span>horizontal_datum_name :</span></dt><dd>undefined</dd><dt><span>projected_crs_name :</span></dt><dd>undefined</dd><dt><span>grid_mapping_name :</span></dt><dd>lambert_conformal_conic</dd><dt><span>standard_parallel :</span></dt><dd>53.5</dd><dt><span>longitude_of_central_meridian :</span></dt><dd>5.0</dd><dt><span>false_easting :</span></dt><dd>1481641.67696368</dd><dt><span>false_northing :</span></dt><dd>537326.063885016</dd><dt><span>spatial_ref :</span></dt><dd>PROJCS[&quot;undefined&quot;,GEOGCS[&quot;undefined&quot;,DATUM[&quot;undefined&quot;,SPHEROID[&quot;undefined&quot;,6367470,0]],PRIMEM[&quot;Greenwich&quot;,0,AUTHORITY[&quot;EPSG&quot;,&quot;8901&quot;]],UNIT[&quot;degree&quot;,0.0174532925199433]],PROJECTION[&quot;Lambert_Conformal_Conic_1SP&quot;],PARAMETER[&quot;latitude_of_origin&quot;,53.5],PARAMETER[&quot;central_meridian&quot;,5],PARAMETER[&quot;scale_factor&quot;,1],PARAMETER[&quot;false_easting&quot;,1481641.67696368],PARAMETER[&quot;false_northing&quot;,537326.063885016],UNIT[&quot;metre&quot;,1,AUTHORITY[&quot;EPSG&quot;,&quot;9001&quot;]],AXIS[&quot;Easting&quot;,EAST],AXIS[&quot;Northing&quot;,NORTH]]</dd><dt><span>GeoTransform :</span></dt><dd>413750.0 2500.0 0.0 406250.0 0.0 2500.0</dd></dl></div><div class='xr-var-data'><pre>[1 values with dtype=int64]</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'>1981-01-01 ... 2005-12-31</div><input id='attrs-8bf3a31f-f09a-42a3-bacc-879314d6dd58' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-8bf3a31f-f09a-42a3-bacc-879314d6dd58' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ad0a7119-eb71-4d5d-981a-c5aba9482f7e' class='xr-var-data-in' type='checkbox'><label for='data-ad0a7119-eb71-4d5d-981a-c5aba9482f7e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>time</dd><dt><span>axis :</span></dt><dd>T</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;1981-01-01T00:00:00.000000000&#x27;, &#x27;1981-01-02T00:00:00.000000000&#x27;,\n",
       "       &#x27;1981-01-03T00:00:00.000000000&#x27;, ..., &#x27;2005-12-29T00:00:00.000000000&#x27;,\n",
       "       &#x27;2005-12-30T00:00:00.000000000&#x27;, &#x27;2005-12-31T00:00:00.000000000&#x27;],\n",
       "      dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>spatial_ref</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>0</div><input id='attrs-3e1451a8-e46f-4874-8743-250a352e5895' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3e1451a8-e46f-4874-8743-250a352e5895' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d97e2556-601e-48eb-a5d6-d39a6d7fe23f' class='xr-var-data-in' type='checkbox'><label for='data-d97e2556-601e-48eb-a5d6-d39a6d7fe23f' 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>crs_wkt :</span></dt><dd>PROJCS[&quot;undefined&quot;,GEOGCS[&quot;undefined&quot;,DATUM[&quot;undefined&quot;,SPHEROID[&quot;undefined&quot;,6367470,0]],PRIMEM[&quot;Greenwich&quot;,0,AUTHORITY[&quot;EPSG&quot;,&quot;8901&quot;]],UNIT[&quot;degree&quot;,0.0174532925199433]],PROJECTION[&quot;Lambert_Conformal_Conic_1SP&quot;],PARAMETER[&quot;latitude_of_origin&quot;,53.5],PARAMETER[&quot;central_meridian&quot;,5],PARAMETER[&quot;scale_factor&quot;,1],PARAMETER[&quot;false_easting&quot;,1481641.67696368],PARAMETER[&quot;false_northing&quot;,537326.063885016],UNIT[&quot;metre&quot;,1,AUTHORITY[&quot;EPSG&quot;,&quot;9001&quot;]],AXIS[&quot;Easting&quot;,EAST],AXIS[&quot;Northing&quot;,NORTH]]</dd><dt><span>semi_major_axis :</span></dt><dd>6367470.0</dd><dt><span>semi_minor_axis :</span></dt><dd>6367470.0</dd><dt><span>inverse_flattening :</span></dt><dd>0.0</dd><dt><span>reference_ellipsoid_name :</span></dt><dd>undefined</dd><dt><span>longitude_of_prime_meridian :</span></dt><dd>0.0</dd><dt><span>prime_meridian_name :</span></dt><dd>Greenwich</dd><dt><span>geographic_crs_name :</span></dt><dd>undefined</dd><dt><span>horizontal_datum_name :</span></dt><dd>undefined</dd><dt><span>projected_crs_name :</span></dt><dd>undefined</dd><dt><span>grid_mapping_name :</span></dt><dd>lambert_conformal_conic</dd><dt><span>standard_parallel :</span></dt><dd>53.5</dd><dt><span>longitude_of_central_meridian :</span></dt><dd>5.0</dd><dt><span>false_easting :</span></dt><dd>1481641.67696368</dd><dt><span>false_northing :</span></dt><dd>537326.063885016</dd><dt><span>spatial_ref :</span></dt><dd>PROJCS[&quot;undefined&quot;,GEOGCS[&quot;undefined&quot;,DATUM[&quot;undefined&quot;,SPHEROID[&quot;undefined&quot;,6367470,0]],PRIMEM[&quot;Greenwich&quot;,0,AUTHORITY[&quot;EPSG&quot;,&quot;8901&quot;]],UNIT[&quot;degree&quot;,0.0174532925199433]],PROJECTION[&quot;Lambert_Conformal_Conic_1SP&quot;],PARAMETER[&quot;latitude_of_origin&quot;,53.5],PARAMETER[&quot;central_meridian&quot;,5],PARAMETER[&quot;scale_factor&quot;,1],PARAMETER[&quot;false_easting&quot;,1481641.67696368],PARAMETER[&quot;false_northing&quot;,537326.063885016],UNIT[&quot;metre&quot;,1,AUTHORITY[&quot;EPSG&quot;,&quot;9001&quot;]],AXIS[&quot;Easting&quot;,EAST],AXIS[&quot;Northing&quot;,NORTH]]</dd><dt><span>GeoTransform :</span></dt><dd>413750.0 2500.0 0.0 406250.0 0.0 2500.0</dd></dl></div><div class='xr-var-data'><pre>array(0)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-c642ed9b-7fde-43a8-95d1-423e6a48afa9' class='xr-section-summary-in' type='checkbox'  checked><label for='section-c642ed9b-7fde-43a8-95d1-423e6a48afa9' class='xr-section-summary' >Data variables: <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>PAR</span></div><div class='xr-var-dims'>(time, y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(4871, 85, 81), meta=np.ndarray&gt;</div><input id='attrs-74b53c1d-394e-43e9-850a-3827f7ff1b2a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-74b53c1d-394e-43e9-850a-3827f7ff1b2a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8a736bb2-5185-4675-8c3f-e9ba2fb4fd30' class='xr-var-data-in' type='checkbox'><label for='data-8a736bb2-5185-4675-8c3f-e9ba2fb4fd30' 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>Surface Photosynthetically Active Radiation</dd><dt><span>units :</span></dt><dd>MJ m⁻² day⁻¹</dd></dl></div><div class='xr-var-data'><table>\n",
       "    <tr>\n",
       "        <td>\n",
       "            <table style=\"border-collapse: collapse;\">\n",
       "                <thead>\n",
       "                    <tr>\n",
       "                        <td> </td>\n",
       "                        <th> Array </th>\n",
       "                        <th> Chunk </th>\n",
       "                    </tr>\n",
       "                </thead>\n",
       "                <tbody>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 913.57 MiB </td>\n",
       "                        <td> 127.93 MiB </td>\n",
       "                    </tr>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> (9131, 166, 158) </td>\n",
       "                        <td> (4871, 85, 81) </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Dask graph </th>\n",
       "                        <td colspan=\"2\"> 8 chunks in 4 graph layers </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Data type </th>\n",
       "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
       "                    </tr>\n",
       "                </tbody>\n",
       "            </table>\n",
       "        </td>\n",
       "        <td>\n",
       "        <svg width=\"158\" height=\"149\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
       "\n",
       "  <!-- Horizontal lines -->\n",
       "  <line x1=\"10\" y1=\"0\" x2=\"80\" y2=\"70\" style=\"stroke-width:2\" />\n",
       "  <line x1=\"10\" y1=\"14\" x2=\"80\" y2=\"85\" />\n",
       "  <line x1=\"10\" y1=\"28\" x2=\"80\" y2=\"99\" style=\"stroke-width:2\" />\n",
       "\n",
       "  <!-- Vertical lines -->\n",
       "  <line x1=\"10\" y1=\"0\" x2=\"10\" y2=\"28\" style=\"stroke-width:2\" />\n",
       "  <line x1=\"47\" y1=\"37\" x2=\"47\" y2=\"66\" />\n",
       "  <line x1=\"80\" y1=\"70\" x2=\"80\" y2=\"99\" style=\"stroke-width:2\" />\n",
       "\n",
       "  <!-- Colored Rectangle -->\n",
       "  <polygon points=\"10.0,0.0 80.58823529411765,70.58823529411765 80.58823529411765,99.08682694645151 10.0,28.498591652333857\" style=\"fill:#ECB172A0;stroke-width:0\"/>\n",
       "\n",
       "  <!-- Horizontal lines -->\n",
       "  <line x1=\"10\" y1=\"0\" x2=\"38\" y2=\"0\" style=\"stroke-width:2\" />\n",
       "  <line x1=\"47\" y1=\"37\" x2=\"75\" y2=\"37\" />\n",
       "  <line x1=\"80\" y1=\"70\" x2=\"108\" y2=\"70\" style=\"stroke-width:2\" />\n",
       "\n",
       "  <!-- Vertical lines -->\n",
       "  <line x1=\"10\" y1=\"0\" x2=\"80\" y2=\"70\" style=\"stroke-width:2\" />\n",
       "  <line x1=\"24\" y1=\"0\" x2=\"95\" y2=\"70\" />\n",
       "  <line x1=\"38\" y1=\"0\" x2=\"108\" y2=\"70\" style=\"stroke-width:2\" />\n",
       "\n",
       "  <!-- Colored Rectangle -->\n",
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       "\n",
       "  <!-- Horizontal lines -->\n",
       "  <line x1=\"80\" y1=\"70\" x2=\"108\" y2=\"70\" style=\"stroke-width:2\" />\n",
       "  <line x1=\"80\" y1=\"85\" x2=\"108\" y2=\"85\" />\n",
       "  <line x1=\"80\" y1=\"99\" x2=\"108\" y2=\"99\" style=\"stroke-width:2\" />\n",
       "\n",
       "  <!-- Vertical lines -->\n",
       "  <line x1=\"80\" y1=\"70\" x2=\"80\" y2=\"99\" style=\"stroke-width:2\" />\n",
       "  <line x1=\"95\" y1=\"70\" x2=\"95\" y2=\"99\" />\n",
       "  <line x1=\"108\" y1=\"70\" x2=\"108\" y2=\"99\" style=\"stroke-width:2\" />\n",
       "\n",
       "  <!-- Colored Rectangle -->\n",
       "  <polygon points=\"80.58823529411765,70.58823529411765 108.81541272727571,70.58823529411765 108.81541272727571,99.08682694645151 80.58823529411765,99.08682694645151\" style=\"fill:#ECB172A0;stroke-width:0\"/>\n",
       "\n",
       "  <!-- Text -->\n",
       "  <text x=\"94.701824\" y=\"119.086827\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >158</text>\n",
       "  <text x=\"128.815413\" y=\"84.837531\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(-90,128.815413,84.837531)\">166</text>\n",
       "  <text x=\"35.294118\" y=\"83.792709\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(45,35.294118,83.792709)\">9131</text>\n",
       "</svg>\n",
       "        </td>\n",
       "    </tr>\n",
       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>PET</span></div><div class='xr-var-dims'>(time, y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(4756, 86, 82), meta=np.ndarray&gt;</div><input id='attrs-88ca33a4-7085-4fea-9df8-3a5b5f491a08' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-88ca33a4-7085-4fea-9df8-3a5b5f491a08' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-cdc69ef0-16e8-4ddb-9251-8058d3b5a906' class='xr-var-data-in' type='checkbox'><label for='data-cdc69ef0-16e8-4ddb-9251-8058d3b5a906' 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>mm day⁻¹</dd><dt><span>long_name :</span></dt><dd>Reference evapotranspiration</dd></dl></div><div class='xr-var-data'><table>\n",
       "    <tr>\n",
       "        <td>\n",
       "            <table style=\"border-collapse: collapse;\">\n",
       "                <thead>\n",
       "                    <tr>\n",
       "                        <td> </td>\n",
       "                        <th> Array </th>\n",
       "                        <th> Chunk </th>\n",
       "                    </tr>\n",
       "                </thead>\n",
       "                <tbody>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 913.57 MiB </td>\n",
       "                        <td> 127.94 MiB </td>\n",
       "                    </tr>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> (9131, 166, 158) </td>\n",
       "                        <td> (4756, 86, 82) </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Dask graph </th>\n",
       "                        <td colspan=\"2\"> 8 chunks in 2 graph layers </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Data type </th>\n",
       "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
       "                    </tr>\n",
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       "            </table>\n",
       "        </td>\n",
       "        <td>\n",
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       "    </tr>\n",
       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>T</span></div><div class='xr-var-dims'>(time, y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(4871, 85, 81), meta=np.ndarray&gt;</div><input id='attrs-b771a014-c52d-428a-91b9-0d7f0fbcfc22' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b771a014-c52d-428a-91b9-0d7f0fbcfc22' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ef84491c-ce07-4478-8070-e589ab3b8d5e' class='xr-var-data-in' type='checkbox'><label for='data-ef84491c-ce07-4478-8070-e589ab3b8d5e' 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>GRIB_paramId :</span></dt><dd>233253011</dd><dt><span>GRIB_numberOfPoints :</span></dt><dd>258681</dd><dt><span>GRIB_typeOfLevel :</span></dt><dd>heightAboveGround</dd><dt><span>GRIB_stepUnits :</span></dt><dd>1</dd><dt><span>GRIB_stepType :</span></dt><dd>instant</dd><dt><span>GRIB_gridType :</span></dt><dd>lambert</dd><dt><span>GRIB_DxInMetres :</span></dt><dd>2500</dd><dt><span>GRIB_DyInMetres :</span></dt><dd>2500</dd><dt><span>GRIB_LaDInDegrees :</span></dt><dd>53.5</dd><dt><span>GRIB_Latin1InDegrees :</span></dt><dd>53.5</dd><dt><span>GRIB_Latin2InDegrees :</span></dt><dd>53.5</dd><dt><span>GRIB_LoVInDegrees :</span></dt><dd>5.0</dd><dt><span>GRIB_NV :</span></dt><dd>132</dd><dt><span>GRIB_Nx :</span></dt><dd>529</dd><dt><span>GRIB_Ny :</span></dt><dd>489</dd><dt><span>GRIB_cfName :</span></dt><dd>unknown</dd><dt><span>GRIB_cfVarName :</span></dt><dd>unknown</dd><dt><span>GRIB_gridDefinitionDescription :</span></dt><dd>Lambert Conformal</dd><dt><span>GRIB_iScansNegatively :</span></dt><dd>0</dd><dt><span>GRIB_jPointsAreConsecutive :</span></dt><dd>0</dd><dt><span>GRIB_jScansPositively :</span></dt><dd>1</dd><dt><span>GRIB_latitudeOfFirstGridPointInDegrees :</span></dt><dd>46.834</dd><dt><span>GRIB_latitudeOfSouthernPoleInDegrees :</span></dt><dd>0.0</dd><dt><span>GRIB_longitudeOfFirstGridPointInDegrees :</span></dt><dd>-14.609</dd><dt><span>GRIB_longitudeOfSouthernPoleInDegrees :</span></dt><dd>0.0</dd><dt><span>GRIB_missingValue :</span></dt><dd>3.4028234663852886e+38</dd><dt><span>GRIB_name :</span></dt><dd>Temperature</dd><dt><span>GRIB_shortName :</span></dt><dd>t</dd><dt><span>GRIB_units :</span></dt><dd>K</dd><dt><span>long_name :</span></dt><dd>Temperature</dd><dt><span>units :</span></dt><dd>°C</dd><dt><span>standard_name :</span></dt><dd>unknown</dd></dl></div><div class='xr-var-data'><table>\n",
       "    <tr>\n",
       "        <td>\n",
       "            <table style=\"border-collapse: collapse;\">\n",
       "                <thead>\n",
       "                    <tr>\n",
       "                        <td> </td>\n",
       "                        <th> Array </th>\n",
       "                        <th> Chunk </th>\n",
       "                    </tr>\n",
       "                </thead>\n",
       "                <tbody>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 913.57 MiB </td>\n",
       "                        <td> 127.93 MiB </td>\n",
       "                    </tr>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> (9131, 166, 158) </td>\n",
       "                        <td> (4871, 85, 81) </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Dask graph </th>\n",
       "                        <td colspan=\"2\"> 8 chunks in 3 graph layers </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Data type </th>\n",
       "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
       "                    </tr>\n",
       "                </tbody>\n",
       "            </table>\n",
       "        </td>\n",
       "        <td>\n",
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       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>PP</span></div><div class='xr-var-dims'>(time, y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(4871, 85, 81), meta=np.ndarray&gt;</div><input id='attrs-1831c2f0-b113-473e-ae39-46b86534fbc4' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-1831c2f0-b113-473e-ae39-46b86534fbc4' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6d50b2a3-62c6-4012-ad72-2b5e23d87475' class='xr-var-data-in' type='checkbox'><label for='data-6d50b2a3-62c6-4012-ad72-2b5e23d87475' 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>GRIB_paramId :</span></dt><dd>233253061</dd><dt><span>GRIB_numberOfPoints :</span></dt><dd>258681</dd><dt><span>GRIB_typeOfLevel :</span></dt><dd>heightAboveGround</dd><dt><span>GRIB_stepUnits :</span></dt><dd>1</dd><dt><span>GRIB_stepType :</span></dt><dd>accum</dd><dt><span>GRIB_gridType :</span></dt><dd>lambert</dd><dt><span>GRIB_DxInMetres :</span></dt><dd>2500</dd><dt><span>GRIB_DyInMetres :</span></dt><dd>2500</dd><dt><span>GRIB_LaDInDegrees :</span></dt><dd>53.5</dd><dt><span>GRIB_Latin1InDegrees :</span></dt><dd>53.5</dd><dt><span>GRIB_Latin2InDegrees :</span></dt><dd>53.5</dd><dt><span>GRIB_LoVInDegrees :</span></dt><dd>5.0</dd><dt><span>GRIB_NV :</span></dt><dd>132</dd><dt><span>GRIB_Nx :</span></dt><dd>529</dd><dt><span>GRIB_Ny :</span></dt><dd>489</dd><dt><span>GRIB_cfName :</span></dt><dd>unknown</dd><dt><span>GRIB_cfVarName :</span></dt><dd>unknown</dd><dt><span>GRIB_gridDefinitionDescription :</span></dt><dd>Lambert Conformal</dd><dt><span>GRIB_iScansNegatively :</span></dt><dd>0</dd><dt><span>GRIB_jPointsAreConsecutive :</span></dt><dd>0</dd><dt><span>GRIB_jScansPositively :</span></dt><dd>1</dd><dt><span>GRIB_latitudeOfFirstGridPointInDegrees :</span></dt><dd>46.834</dd><dt><span>GRIB_latitudeOfSouthernPoleInDegrees :</span></dt><dd>0.0</dd><dt><span>GRIB_longitudeOfFirstGridPointInDegrees :</span></dt><dd>-14.609</dd><dt><span>GRIB_longitudeOfSouthernPoleInDegrees :</span></dt><dd>0.0</dd><dt><span>GRIB_missingValue :</span></dt><dd>3.4028234663852886e+38</dd><dt><span>GRIB_name :</span></dt><dd>Total precipitation</dd><dt><span>GRIB_shortName :</span></dt><dd>tp</dd><dt><span>GRIB_units :</span></dt><dd>kg m**-2</dd><dt><span>long_name :</span></dt><dd>Total precipitation</dd><dt><span>units :</span></dt><dd>mm day⁻¹</dd><dt><span>standard_name :</span></dt><dd>unknown</dd></dl></div><div class='xr-var-data'><table>\n",
       "    <tr>\n",
       "        <td>\n",
       "            <table style=\"border-collapse: collapse;\">\n",
       "                <thead>\n",
       "                    <tr>\n",
       "                        <td> </td>\n",
       "                        <th> Array </th>\n",
       "                        <th> Chunk </th>\n",
       "                    </tr>\n",
       "                </thead>\n",
       "                <tbody>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 913.57 MiB </td>\n",
       "                        <td> 127.93 MiB </td>\n",
       "                    </tr>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> (9131, 166, 158) </td>\n",
       "                        <td> (4871, 85, 81) </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Dask graph </th>\n",
       "                        <td colspan=\"2\"> 8 chunks in 3 graph layers </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Data type </th>\n",
       "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
       "                    </tr>\n",
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       "            </table>\n",
       "        </td>\n",
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       "</table></div></li></ul></div></li><li class='xr-section-item'><input id='section-ec39ec0b-4342-4af8-9e96-4af8c6329ac8' class='xr-section-summary-in' type='checkbox'  ><label for='section-ec39ec0b-4342-4af8-9e96-4af8c6329ac8' class='xr-section-summary' >Indexes: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>x</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-bb49ee31-6fa3-49a1-a553-fd96ba16abd4' class='xr-index-data-in' type='checkbox'/><label for='index-bb49ee31-6fa3-49a1-a553-fd96ba16abd4' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Float64Index([415000.0, 417500.0, 420000.0, 422500.0, 425000.0, 427500.0,\n",
       "              430000.0, 432500.0, 435000.0, 437500.0,\n",
       "              ...\n",
       "              785000.0, 787500.0, 790000.0, 792500.0, 795000.0, 797500.0,\n",
       "              800000.0, 802500.0, 805000.0, 807500.0],\n",
       "             dtype=&#x27;float64&#x27;, name=&#x27;x&#x27;, length=158))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>y</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-0f2b19af-ebbd-407a-a14f-7395e4f82b93' class='xr-index-data-in' type='checkbox'/><label for='index-0f2b19af-ebbd-407a-a14f-7395e4f82b93' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Float64Index([407500.0, 410000.0, 412500.0, 415000.0, 417500.0, 420000.0,\n",
       "              422500.0, 425000.0, 427500.0, 430000.0,\n",
       "              ...\n",
       "              797500.0, 800000.0, 802500.0, 805000.0, 807500.0, 810000.0,\n",
       "              812500.0, 815000.0, 817500.0, 820000.0],\n",
       "             dtype=&#x27;float64&#x27;, name=&#x27;y&#x27;, length=166))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>time</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-c2cc4f86-7113-4503-ae24-573cd6944c9f' class='xr-index-data-in' type='checkbox'/><label for='index-c2cc4f86-7113-4503-ae24-573cd6944c9f' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(DatetimeIndex([&#x27;1981-01-01&#x27;, &#x27;1981-01-02&#x27;, &#x27;1981-01-03&#x27;, &#x27;1981-01-04&#x27;,\n",
       "               &#x27;1981-01-05&#x27;, &#x27;1981-01-06&#x27;, &#x27;1981-01-07&#x27;, &#x27;1981-01-08&#x27;,\n",
       "               &#x27;1981-01-09&#x27;, &#x27;1981-01-10&#x27;,\n",
       "               ...\n",
       "               &#x27;2005-12-22&#x27;, &#x27;2005-12-23&#x27;, &#x27;2005-12-24&#x27;, &#x27;2005-12-25&#x27;,\n",
       "               &#x27;2005-12-26&#x27;, &#x27;2005-12-27&#x27;, &#x27;2005-12-28&#x27;, &#x27;2005-12-29&#x27;,\n",
       "               &#x27;2005-12-30&#x27;, &#x27;2005-12-31&#x27;],\n",
       "              dtype=&#x27;datetime64[ns]&#x27;, name=&#x27;time&#x27;, length=9131, freq=None))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-1100e852-fa33-4f42-a6a4-4f71a7fe5196' class='xr-section-summary-in' type='checkbox'  checked><label for='section-1100e852-fa33-4f42-a6a4-4f71a7fe5196' class='xr-section-summary' >Attributes: <span>(4)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>CDI :</span></dt><dd>Climate Data Interface version 2.0.5 (https://mpimet.mpg.de/cdi)</dd><dt><span>Conventions :</span></dt><dd>CF-1.6</dd><dt><span>CDO :</span></dt><dd>Climate Data Operators version 2.0.5 (https://mpimet.mpg.de/cdo)</dd><dt><span>dataset :</span></dt><dd>IE_MERA_FC3hr_3_day</dd></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.Dataset>\n",
       "Dimensions:            (x: 158, y: 166, time: 9131)\n",
       "Coordinates:\n",
       "  * x                  (x) float64 4.15e+05 4.175e+05 ... 8.05e+05 8.075e+05\n",
       "  * y                  (y) float64 4.075e+05 4.1e+05 ... 8.175e+05 8.2e+05\n",
       "    height             float64 0.0\n",
       "    Lambert_Conformal  int64 ...\n",
       "  * time               (time) datetime64[ns] 1981-01-01 ... 2005-12-31\n",
       "    spatial_ref        int64 0\n",
       "Data variables:\n",
       "    PAR                (time, y, x) float32 dask.array<chunksize=(4871, 85, 81), meta=np.ndarray>\n",
       "    PET                (time, y, x) float32 dask.array<chunksize=(4756, 86, 82), meta=np.ndarray>\n",
       "    T                  (time, y, x) float32 dask.array<chunksize=(4871, 85, 81), meta=np.ndarray>\n",
       "    PP                 (time, y, x) float32 dask.array<chunksize=(4871, 85, 81), meta=np.ndarray>\n",
       "Attributes:\n",
       "    CDI:          Climate Data Interface version 2.0.5 (https://mpimet.mpg.de...\n",
       "    Conventions:  CF-1.6\n",
       "    CDO:          Climate Data Operators version 2.0.5 (https://mpimet.mpg.de...\n",
       "    dataset:      IE_MERA_FC3hr_3_day"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# reassign CRS\n",
    "ds.rio.write_crs(data_crs, inplace=True)"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Visualise"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Moorepark, Fermoy met station coords\n",
    "LON, LAT = -8.26389, 52.16389"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [],
   "source": [
    "# transform coordinates from lon/lat to Lambert Conformal Conic\n",
    "XLON, YLAT = cplt.projection_lambert_conformal.transform_point(\n",
    "    x=LON, y=LAT, src_crs=ccrs.PlateCarree()\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [],
   "source": [
    "def plot_map(data, var, cmap=\"Spectral_r\"):\n",
    "    \"\"\"\n",
    "    Helper function for plotting maps\n",
    "    \"\"\"\n",
    "\n",
    "    plt.figure(figsize=(9, 7))\n",
    "    ax = plt.axes(projection=cplt.projection_lambert_conformal)\n",
    "    data.isel(time=120)[var].plot.contourf(\n",
    "        ax=ax,\n",
    "        robust=True,\n",
    "        x=\"x\",\n",
    "        y=\"y\",\n",
    "        levels=10,\n",
    "        transform=cplt.projection_lambert_conformal,\n",
    "        cmap=cmap,\n",
    "        cbar_kwargs={\n",
    "            \"label\": (\n",
    "                data[var].attrs[\"long_name\"]\n",
    "                + \" [\"\n",
    "                + data[var].attrs[\"units\"]\n",
    "                + \"]\"\n",
    "            )\n",
    "        },\n",
    "    )\n",
    "    ax.gridlines(\n",
    "        draw_labels=dict(bottom=\"x\", left=\"y\"),\n",
    "        color=\"lightslategrey\",\n",
    "        linewidth=0.5,\n",
    "        x_inline=False,\n",
    "        y_inline=False,\n",
    "    )\n",
    "    ax.coastlines(resolution=\"10m\", color=\"darkslategrey\", linewidth=0.75)\n",
    "    ax.set_title(str(data.isel(time=90)[\"time\"].values))\n",
    "    plt.tight_layout()\n",
    "    plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [],
   "source": [
    "def plot_ts(data, var):\n",
    "    \"\"\"\n",
    "    Helper function for plotting time series\n",
    "    \"\"\"\n",
    "\n",
    "    plt.figure(figsize=(12, 4))\n",
    "    data_ts = data.sel({\"x\": XLON, \"y\": YLAT}, method=\"nearest\")\n",
    "    data_ts = data_ts.sel(time=slice(\"1989\", \"1991\"))\n",
    "    plt.plot(data_ts[\"time\"], data_ts[var])\n",
    "    plt.title(\n",
    "        data[var].attrs[\"long_name\"] + \" [\" + data[var].attrs[\"units\"] + \"]\"\n",
    "    )\n",
    "    plt.tight_layout()\n",
    "    plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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lRv+46Sbmz5jR7WPn8/u54re/ZduePW2mTn739NO58XvfA8KWiMd897tomsYVZ5/d4nHfneMGcOfDD/P0G2+0mUQ5ecwYHr399payjot/+Uu27t7N1HHjWppWnXV1XHrjjZRWVraZTvmLK67g4iaPcYD31qzhxnvuQdO0ljjSkpN57M9/prip3CqSxzuSxzbSx7G7x0wikUhiiawpl0gIC8r2tdXNdmsNLhfjRozg/t/+lqffeINte/cysqiIY+fM4ZoLLkDfylVl0ezZPHzbbTz03HPs/vZbhBBMHz+e7597bpvR4O3rxeHQcKFmT/SuuHjZMowGAy+vWkWVw8H8GTO44corI9q0NmPCBP72+9/z7+eeY8e+fcydMoXvn3tuG0HUnOlsjcvjOaxBryfcfcMN3Pef/7B6/XoAFs2Zw3XtLB2LCwp48NZb+b8nnmDLrl1MHTeOi5ctayMQmy0RNU1rsUSE7h07k9HIv26+mbsefpjPv/ySpIQETlqwgB+0qs9vtkRcs3lziyVid48bwC+vvJKUxETe/fRTGlwuTjrmGG648soWIQlw9kknUVVdzVlNmV4INyb++49/5J5HH2Xjtm0My89nxYkntgypaubE+fMRv/gFT772GvvLylgwaxY/vfjiNoI8ksc7ksc20sexu8dMIpFIYonMlEskEolEIpFIJDFG1pRLJBKJRCKRSCQxRpavSCQSiUQikUjiglAoxNovv+Tt1at555NPuP266zi51UTsjdu28d/XX2fjtm2kJSez4sQTuejMM1HVzvPMoVCI+x9/nPfWrMFgMLB88WKuaGXSEC9IUS6RSCQSiUQiiQtq6uu5/cEHCYVChDStzX0ff/EFN95zD8uWLOGP117L13v28H9PPIFOp+PCM87odM27HnmEdz/9lOsuvxyP18t9K1ei0+m4tMl4IF6QolwikUgkEolEEhdkpqXx1kMPUW6ztUyZbmZkURG3X3cdJzRZmS6aMwd7TQ0v/O9/nYryuoYGXn7vPf7085+3NKe7vV6efPVVLjrjDHStzBpijawpl0gkEolEIpHEPUV5eS2CvJlxI0ZQ1eRe1hGrN2xAURQWzprVctuSo4/GXlPDVzt39lusvWFAZcptTif1jY2xDkMikUgkEonkiKQnJ5OemhrrMLokVtoqOTGR7PT0Pq+zt6SEkUVFnd5fabeTk5nZMjQNoDA3F71OR0UXYj4WDBhRbnM6OetHP+qT/7FEIpFIJBJJNPngscfiVpjbnE5Ov/hy/AYl6vtOsFh4+YEH+iTM6xoaeH/tWi7qYgiYo7aWlMTEw25PTkzE0TSPJF4YMKK8vrERl8fDX379a4ry8mIdTsxxe7xUVFVTbnNQU+9CryrUNbg4asZEhhXktBloI+k/3v5oHUuOmYXBMGDeSgOa0nIbjppaZkwaG+tQhgQ79uzHYNAzenhhrEMZ/AjB6++v5YwlXU/zlfQdoWm89eE6li4++sgb94HbH3yQTdu24ayvj1tRXt/YiN+gcPoXHlJd2pEfECFqE1TemBvef19E+f898QTGpsnbnaEAHY3kEYCqRP9kpCsGnJIoystj9LBhsQ4jLpg67tD/A8Egjzz7FiaDhU1bviEYCpGRmkJxQQ7FBTkkJVpjF+ggJiVxJxNGjYx1GEOG8ooa5kyZzPDC3FiHMiTYtbecuVMnkp6aHOtQBj01dQ2MLh4mv9+igLO2njHDi/v1WPv8fnbu29dv60eaVJdGRkP0RHkkePOjj3j1/ff55803tylNaU9GWhp17cpzhBDUNzSQmZbW32H2iAEnyiUdEwgEyUhL5tijpgHhF1x1bT0lZVWs+mwjDS43ZpORYfk5DCvIITczrUtPT8mRaXR7SLCYYx3GkKLcVs1RMybGOowhQ01dA2kpSbEOY0hQ5aghN7Pv9bWSI2OvriUzPbVf91Hf2CivWPcjW3bt4pYHHuCnl1zCnClTutw2PyuLKocDj9eLxRz+zj5QUUFI08jLzo5GuN1GivJBwoFyG8X5OS2/K4pCZloKmWkpzJocvtTv9fk5UG5j2+5vef+zjQDkZqZTXJBDUX42FnPnZ5qSwzlYYacoP77e0IMdfyCIyWiIdRhDAiEEAoESZ5d3BytVDicjivJjHcaQwOaspSivfz+701JSENrAyjwPFPYeOMBPbruNZYsXc/GyZR1u0+BykZSQAIRtExVF4eP16zll4UIAVq1ZQ05GBlPHxlcppBTlg4SSskqmTxjd5TZmk5GxIwoZOyJcH6ppGlWOGkrKqvhyxzd4fX4SrWaGNZW8ZKalyC/kLigttzF53IhYhzFk8Pr8mE1SkEeLhkY3ybLsLWpUOWqYN11eBYoG9upaZvZzX4pep2Pe9Om8t2ZNv+5nMFJSXo6zrq6lCfPbgwfZvGMH6SkpqIrCD2+6iWF5eZy1ZAmbd+xoeVxeZia5WVk8/cYb3PXII9z3q19x/FFHkZSQwDknn8wdDz2EPxDA4/Xy0HPPce3FF8ddxYAU5YMEW3UtWZk9q41SVZW87AzysjOY11QS0OjyUFJWxYYtu7A769CpKvk5GQwryKEoNwujzFK2YKuuISdzZqzDGDKUVTnIz86MdRhDhgpbNXlZGbEOo1/weL28+v77rNuyhVMWLmTx0UfHvNTA5w9gMhljGsNQweXxkmDt/9LDjDht7ox3HnnhBV774IOW3//1zDP865lnOPOEE1AUBXtNDfaaGi64/vo2j7v6/PO5+vzzSU9NJTM1tY3jyi8uvxy9Tsc/n34ag8HA1eef32VzaKyQonwQEAppqIoSkS7ixAQLk8YOZ9LY4QAEQyEqqqopKa9i/Vc7CQSDJCdaKS7IZVh+NmkpSUMymy6EQBMi7s6yBzPllQ4K87JiHcaQocLuZFTx4Cyn+Mt//sNXO3dS+PIO/vr2Gh5PV/i1EiJFgaKX3ox6PJqmoTD0PkcHM5qm8dEXX8Q6jAHJrddey63XXtvp/bf85CddPv7kBQs4ecGCNrepqsrPL7uMn192WSRC7DekKB8ElNsc5GX3T0ZLr9NRlJ/dpna6rr6RknIbazZuw1nXgF6nUpCbRXFBDgU5mUPCHtBRU0dmWkqswxhSlNuqmTt9QqzDGDJU2p0cM2tyrMPoF844/ng+XLeORZVBJh0IUHamlRuEnt8ThBVLoy7MnbUNpKfKhtpo4PZ4o9I/tXrDBhKssvxL0jMGv3oaApSUVVEcRYu4lOREpiYnMnV82AowEAxSXumgpNzG2k3bCARDpCYntDi9pCUnDrps+sEKu8zaRhl/ICCbPKNIIBgctCfYU8aO5cwTTuCNvc9y5jo3ha+5OXeZhV8LPd9F45SzljL85egJ8ypHDTnSeSUq2J11ZPWz8wrAk6+9xhnHHcdfH3+83/clGTwMzk/cIcbBCjtzp46P2f4Nej3FhbktJwZCCOoaXBwoq+KzDVuprQ9bQ+XnZA6abPqBchvHNdlPSvofn8+P0SAFeTMr1cVtfr9cez+i6wcCQQz6gf0ePRLXfPe7bLzzKZ5fYGXZ5x5WKIJRBPm30PE2er531ulMVw4NHOnP7Hmlw8n4kdKfPBrYnbVkpffvVc5d335LaUUF82bMACnKJT1gcH/qDgGEEPgDgbhqwFQUhdTkRFKTE5k6YRRwKJt+oNzG55u34w8ED2XTB2Btel2Di5Tkw8f2SvqHMls1+TmDs+kwEqxUF0dUmFc6nORmDe7MrU6n49htPjb4jLw+10LyK26WLDfzJ0J8jsIDQkexEFyhhMhXoLQfy1rs1bUsnDO1X9aWtMVeXcucfk5ibdm1i/kzZ8a8eVgy8JCifIBTW99IanL81yK2z6ZDOPYD7WrT83MyGZafTWEcO70EgyH0OtngGU3KKu0U5MpyoWYu194/LFseSWFeUVVN3iAX5c0UOoLsyT/0VagocDSC2QR5DZXrhZ5jhcYJikCctZRh/VDWEggGMQ7wq4cDBWdtA2n9XL9vq67u0+h4ydBFfgoMcErKqhhekHPkDeOQlmx6U216MBiivCqcTf/iq534A2Gnl6L8bIblZ8eNb3q5rZr8HGnNF03Kq6pjWqIVj/SnMK+wVzN+1NAop2iwqCR5wkNeVr3iZcnysFWeQYGz0TgBjdeFyh1Cx0QEPz5rKaMjKMxDIQ2ddHGKGpro/+NtczqZOm5cv+5DMjiRonyAU1JWyXFHTY91GBFBr9cxrCDcHNpMfaOb0nIbG7bswlFTh6oo5GSlMyw/h6K8rJhMIS0tt/X7NDhJW/wB6eHcEf0lzOsb3SQNkcFBDRaFJI/o9P40BS5RNM4VGn8TOn4p9Pz2rKVsedXbsk1fjrejpo4M6eQUFaJ1AlRdW0um9CiX9AIpygc4dQ3uQV3bnJxobeObHtI0quxODpTb+Gr7Xrx+PxaTiaL8LIryc8jJTOv3D92DlXZmT4mv0byDGdnk2TWRbvLURFigxsNVqWigD0GdNfyZ0Zwl7wizAtcT4lVUfuLRcUaqSm5t38eoh51Xejb4TdI7nLX1pKcm9/t+vD4fFnP/DyeSDD6kKB/A+Hx+TMah9ScMTxjNJD8ns2UKqdvjpbTCzrbd3/Lhmk1oQpCZltJU9pIT8VHhMmsbXcpt1eT3kw+/5HBq6hpIS4n/PpVIMbE0wPoxRgqXWYDOM+YQrjdfjkbVliBvzLFw3idukrxdP+ZIVNmdTGkq4ZP0LzZnbVTsEP2BAAaZSJD0gqGl6AYZpRV2WUYBWC1mxo0sYtzIIiCc6at21nGg3MYHazZR3+jGoNdRkJvFsPzsPlkyuqI0eEJyiLJKBwW5soY/WlTYqvttGFlXtC/Dgd5fBaiurSU9pXs9KHoN5u3y8dgME38mxJEesuoVL6OAinQdG8YYOX6rr1cxNuOoqSOzny36JGHs1bWMGtb/U2oDgQAmKcolvUCK8gHM/rJKJowqjnUYcYeqKGRlpJKVkcqspjITfyBIWaWdA2VVLQOOkhOtFOWFm0gz0lNQu/EFfrDCTpEcGhRVym0OZk+VTVPRosJWzaSxI6K6z2ZBLqBPw+ab17n/zCSuOPtsrr344g638/p8/HD2WRxcZKXRorDCLNghFNajMPcI2fJmpu/z8+RxCczf0TdRHgyFpHVelLBX17ZcYe1PquvqSElKwuPr22tDMvSQonwAU2lzcvzRM2IdxoDAaNAzoiiPEUV5LbfVN7g4UGFjw9ZwE6mCQnZmWtiSMS+LRKvlsHVKy21MHCNPhKKJzx/ALMuFooa9upbsjNSIrCWEOGK2eqW6mPJ0HWvGG6lK1VFsC3Ls175ulYXYnU4u+MUvmDV5Mul/fIfWp8uPvvgisydPZv6Mtp+RByoquOKCq0g3KZywxcuiY408IHS4gL8LHXcQJL8bZwaJXkGxLcj2Yb3PiAaCQSnIo4jX7+/3z5IGl4sGl4u8rCz2HTzYr/uSDD6kD9MARRMCgZBWWn0gOSmByWNHcOpxR3HxWSdxwbLFTB0/kvpGN++uXs8TL7/Ls298wKfrt1JSVkUgGKTK4SRniPg3xwM+f0D6N0eZkKb1WSg6a2uZf/75PPTcc0D4cv47n3xCbX19m+3+blnC/2aYeXuWmcklAS5f5SLVpfHGXEu38tUpSUnUNDTQ8OAqXj7awodTTHwxJiy6jt3q5Re/uYn3165t2f6Dzz/nvCt+wOSSAKds8pJbqzFMgVuUED5gmaJxs9BT180y8enf+vlqhJFQKNS9B7QjWiPfJeETxGiwv6yMEQUFqPK7WdIL5LfdAMXmqCEnQ3bsRxJVVcnNSic3K52508Ke2D6fn4NVDr4treCzDV+z/2AVr69aE24izet+2Yukd4Trm2U9eU/orSXiSnUxIZMB2xkzWHn2nUDvarrvTjmR1+da0AMv/PNJjN99iJIsHW/NDl95KnQEKbaHqE1Q2XGclUkHAlz8gRdjk649Zoefx/INFC87/EpVe4wGA2nVPgodQcYfDPD1MAMNFoULP3SR2aCR7wzxpzvv4M5aDYtf4ExUOXODh9xarcVpJSDABExAkItgARp/FDpuI4T5CG/t3BoNk19wc+Gp/LHi3R4fK5ujhpws+TkeDVxub4dXPyPNax98ID3KJb1GivIBSklZZZvpmJL+wWQyMmpYPqOG5VNdU8/nm7ezYM4USluVvQBkZ6RRlJ9NUV4WSQlDw985Gsgmz57RUbNkTygbm06ZzsXW6WbyakI9Evg+v58bx5/JuvkWFm3zkTrTiBOFhcvMPFmnsnCbjzHlAb7J03MwQ0+qS+PcT92kudpmMBVgbFmAdWP1HOnZrFQXo1tgJaBTSPRqzNvtb3N/dp3Gv5QgB9IUVq0PMMwexBJoa334I6GnAoU0BF8JhR8qGvcJHfcIHb8mhK4LYa5wKFvem5OhSruTmZOlvWo0sDlryYpQWVZnvLJqFZ9/+SVP3Xtvv+5HMniRonyAUlJmY+r4UbEOY0hRWmGjKD+blKQEUpJGMLmpGU7TNOzVtRyosLHq0400uDxht5ecTIqa3F6MRtmJ3xvKqxwtzbqSrumrIHeZFLbOzqRgTw0p1UG+GBt2GSpdsZSilzqfYCmE4OVVq7jvnr+Rma3nDnOInFl6vi9U7lGCPCJUJiYr/HSGDmWmjlWveJlYGuwylmGOEJ+PNRLowlpupboYvw6qk1XyajovH7EoMA7BuLl6Vr0SPMyL/E4lyGVCTzGCMxQNRYFrCXGz0PGwULkKrY0jy5LlZla9cmhw0JjyIJ9ONFGdqPZYmFfX1JOR1v++2ZJwr0R/lQoJIXj4+ed56b33eOAPfyApIaFf9iMZ/MiipwGK1+eX1nxR5kC5jWH5h1tQqqpKTlY6c6aO56yTF3LJipM4+9RjGVaQw8FKOy/97xOeePldXnx7NV98uYNyWzUhre9DR4YC0WjMGgz0VZALIXh3hpkiEpmyycHE0iDL17pZN87I50KhdMXSDh+naRp3PfII/7j9/1i63sPf8gUjFXgDlVkIvkVhMyo/Ug5ZDXY1oKeZS48xkIXgmbff7vD+5udbnqEjuzaEvptvp472nabAw0oQD/CQ0PGNCH8xnq9ovIXKhg78YFqvo9dgckmATaMMbWLrDtEY+S4JE8kG5tYEgkFufeABPvj8cx6/805GFhVFfB+SoYPMlA9AGlxuEq1yWli0qa1vJCWpexkQo0HP8MJchrcqMXK5vRyssLUMOQppgvSUJIrysijMzyY9JWnITFHsDn5/AINefkQdiY5EYE8ztn/IPxnXBBPpAT06d7gEJNUtmGKG3UJhniJahHnrLPHacUZKs/Scvc6NORC+zSPgdaHycyXEX4SOPyghEppe1q0f2xWqAseisWXnTjjzzE632zbMwMiqrrPuzfvs6mQgS4E7CfECKvcIPQ7AClyhaEzrpOW0eb1Vr3iZsc/PU8cmsCcvxJiK4GF/k47+Fn7ZxBxVausbIz79utHt5oa77kKv1/PIn/6E1dL/NeuSwY38RBiAlJRVUVwg68mjSdhLWO2TaE6wmhk3ahjjRg0DwtnJmroGSivsfL5pO866ehQUcjLTKMzLonCI16fHaohNPOIPhE9QOnr9Xa693ydh/ohuMZ8da+WYHT6U/LAArbco2E+0UIrC9UrnpSH2FB2z9/haBPmqV7zUL7MyGcH/hMoyRWOsIlruAwiqUJahY5g91KUnuQ2FvKzOZwIczNBRlarj5E3dE/pHEuc6Bc5D4zxFwy3AABi68XZvLmdZut7Dq/Ms1CaozNrrb3MZuqO/ha26lmzZrB81BCJiTflCCD74/HPufuQRjps7l+uvvFJaW0oighTlA5ADZVXMnT4h1mEMKfpDICqKQnpqMumpyUybEO4PCDXVp5eW23jvkw00ur0Y9DryczIozMumMCcT0xAp5zhYJZs8Abbv3cv3f/97QqEQJy1YwPVXXEFyYtuMX2+EeSAY5L7MU/l4voVUl0a+ZqWqvpF3ZpopK9SzBI3blSCmLnSMpoDSKpEcVOFZj8LvLBp/Ejp+RljQNwtiAbw33cz+HD2jKoKc9GXngnqrULhi0qQO76u1Knw4xcSC7b5ul670BGsvtFtOncb5q928N8PMtzkWTt7sJcV96OC0/1tUOWrIyZSiPBpE0g++vrGR3/zlL5TbbNz2s58xe/LkiKwrkYAU5QMSR009GamyOSialJbbKIzCJE9dK1vGOU22jIFAkHJbddjxZcsufP4AFpMxnE3PzSIvOwO9fvBlacorHcycNCbWYcSEZoHtNcB/j03g2G0+ihxB1ux6h9PeWMWJX3q5ydbWgq8rYd5MSIFv8vRsLTZQka4jcbaFqfv9TN8X4NNlBdhSPHgbVUYgWIPKQgTpTeUbbgE17dYW7UT5jiIDuTUhtqzzYzr28Ks8bpNCSbaey1c18uiJiRz7NZjaVZ8sWW6mUcAeFGa2E+WapvHj8UvZtNDKnL1+xpR3XbrSEate8Xarrr03JHsEK9Z42DzSwLMLrRy1y8/E0gCGposNrYV5lcPJUdP7f7qkJNxQm5meEpG13vjoI/Q6Hc/ed1+nTcgSSW+RonyAET7j71sZhaTnHKx0xMy6zGDQU1yQQ3FBTsttbq+Psgo7e0vK+GT9FoIhjaQEC4V5WRTlZZOdkTrgh1d4/UOzmbm1iN44ykixPciYirD4PGGrj5LKIO/NMPPNtNN4cN1LWMxmhBDs+OYb1ow3UpmmI6TCyZu8JHvCirnOqvD1MAPbhxlIb9CYUhLgzC88LWLRawBXURr1laVMSFaYr2j4UbhH6DhaaFSisBUFA3ARtJSdpDdoHMzUMdweXujbHD1jywPk1GkchcavhZ6LCCGaHuMyKSR5NMwByKkNUZmmo9h+eHnMWhSmIai9+FySWjm//DH3FLZPNfPd1e6W5xZvKMDMfQGKbSE+mWRi7XgTI6uCjC8NUOQ4ZDNZU9dAWmpSrMMdEtiqa8mOkPPKh+vWceEZZ0hBLukXpCgfYIR9m/s/Yytpi9cXXy4gVrOJMSMKGTOisOW2+kY3BytsbNnxDVXVNQgB6SlJLfXpGanJA+Zkzh8IDskmz9aC3G1U+Hq4ke9+7GqzTbE9xIUfufh4spkTzzyX0bMmUWGz4SuxM0qBZLdGRZoOq09Qmary+TgTVakqEw4GOXuNh/TGw+s9TAEY7TJxS6COxKZzOU0IEhRBFQpHo/E9BLcKPeXpOgqcYSE9/Vs/zyy0Mne3H2MIUlwaddbwAt9XND5B8B+hw3JmAse95cJrVDAHwmLa6hN4jW1fjy3Nk0316Kte8UKTiF2pLsYxykCxLdgnQd4fWfL2NokAGY0ay9d5cJkUdufrWT3ZRIJXcMIWLyvVxehfvFEOHosS9upaxo8e1ud1auvr2fHNN8ybNi0CUUkkhzP0vvUGOCVllQyXTZ5Rxe31YYkjQd4ZyYlWJo4ZzsQxw4FDjaQHK+x88eUOqmvDI86z0lNbSl9SkhLiUqiHa/jTYx1GVGlferJxtJGxZYEOBag5ACdv9mJPVvFv2shUn0aqS2BLUXl1noXln3soT9fxziwz83f4OX19oMvaawUYnqmS2Ko+RVVgEQJauY8cJTS+yTkkylPcgpkmCJ5uxfiqm7HlAd6abSHFrfEfoccNrCCcaa88zYpptRd/0zQenQahVhdzmsVyUMBOFP6IYHW7YxNUFQzB+MyQd0aCTzDj2wDT9gfYNMrIMwutXJigI+Gz1XDWSbEOb0jgqKklK31qn9fZU1LCmOJizKahdwVPEh2kKB9glFU6mD9LNpZEk4MVdoo68CePd1o3kk5taiTVhMBRXcvBSjurv/iKugYXqqKQnZlGUV42BbmZceH4UlZppyBn6FwRai/IXSaFbcMMXPShq5NHhMmqP6S0NQXemWXhuK0+PEaF/800s3S9t0VAd8aS5WY8eiOfB/xdbgdQi4LFJ3AbFZxJKssXGEhC4w2h8sembPHsPX62DTNwnRJiGIK7hA4j8AUqtx1rYrUIK3GfHowdlITrFcgUUNKBN4shKHCZB2ZZlipg9l4/oyoCfHxcHpnuRuaftZS1r7bNsPd0KqjkyAQCoYjYT9qdTrIzpCOUpP+QonwAIYQgGNKG5GX9WFJabmP8qL5f+owHmgV4dmZaS418KKRR5XBSVulg1acbaXR70KkqedkZFORmUZibidUSXV/8sioH04dIk2d7QW5PVvnfTDNT9vtJ9HU/K1yWrsMYFBgDgv/NNHP6ei/53RDkAA5rCpnuui639Qn4HyqFOXq+GGsiYIRhhEjk0BfJkuVmlgCts+u3EOKPQocbhVeESjVwwjIzr1YqrTdr04B5fpPH+SlGBav/0EbpjRo7Cw0tNeq9oT8bPbtDmktwTJWZ7YFarnMpHJuiUpauI8WtMbIq1GOPeUnXCBG5Kyv2mhqy0ofWFTxJdJHqbgBRXVNPphzJHHUq7dUcN296rMPoN3Q6lfycTPJzMlscX4LBEJV2Jwcr7WzZ+Q0erw+DXk9edgaFuVkU5Gb2a4291+fHOgSaPNsL8qAKr821cNRuP5MOBHq0lsui0GhWeHemmdO/8JBf03m9SntR6rAmk9vY3lulLTWABcGCLIUcJcR/hY6FCP4idC1e5B1hVuD3hPihUFjd5N7tBrJrQ9hSVUZXHtq2uS77xOVmqoTG08daOWXjoWx/kT1EcDLsKtAzvqznzivxgj83hdmf7MI9XOOtWRay60JsGWFkRJULBShdsZSiVg2uQwFN0/qlOb2+wUVyN4e+HYnq2loyUlMjspZE0hFSlA8g5NCg6COEIKQJdLqBecm8t+j1upYG0Wb8gSAVtmoOVtrZ+PVufH4/RoOe/OxMCvKyKMjOiIiHeiAQOU/heKYj+8KSbD2pLo3JPRTkAKMqgrhMCpMOBFqG+bSnswxxtTWZSbaSLtdPBI5DowSFt4XKzUqQHSjsQuFaus7ImxX4I0FuFHpuU4IkKnDceB0vlXUs5le94iUXOCFbx1uzzZz4pZfhthAqcMpGLy8fbSGtUSOnrh9MyqNAINmCoc7Nkq8AfAhg5ZIEqpNUMhvCz2koCHOXx8NTb7zBmx99xP6yMkxGI0dPn87xRx3FsXPmkJrc9ySUzVlLdkZq34MFQqHQkPhsksQOKcoHECVllZy4cHaswxhS1NQ1kJ4ibcsAjB1YM/r8AcqrHJRVOlj/1U58/gAmo4GCnEwK88Ie6iZjz6zDKuzOQT/JsyNBDuAxKr12FjGEYNY3h6vx7pRqBHR6jFrXmeftKLyPykQE9yhBTMDdQsf3lBDmbtSSFCowVwi2ojICjUIEzsSOT3ab3UxG2EIUOUK4W00wyqrXWPyVjzfmWrj4AxfGrs8HOiTSJSztnVeOiNK2/EYBCh0hyjJ0LaJ8sAvynfv28f2rf0ZuTYh5e/2cUafhN8D+zz/m8Vc/40+ZenJqQ8z4xs8IW6jXJT326lpyMiNTcqIoSkTLYSSS9khRPoBodHvjoglvKFFabhuQTZ7RwmQ0MKIojxFFeS23eX1+yqscHCi38fnm7fgDQcwmIwU5mRTkZpKfnYGxC6FeVmkf1JM8OxPkAH49GAPR/dIPKSqqOHLGeRSCs9AoReE6oUcPnILGPLof7zRFY61QOVOBdMDdjabNeqtKsrvtPkZVBtlZqGdHkYFp+9ueiLTYKvZUKPeSnu4nZDGicx/eVFudrLaULA12QQ7Q6HaT4BUcyNLTaFExBAUJXkGRI8jxW3wYg172Z+t5f7qZUzb2/m9pd9YxeeyIiMSsQA9e7RJJz5GifIDg8friyid7qFBaYWf+rI5HfUs6xmwyMnJYPiOH5bfc5vX5Kat0cKCsqpVQN5Cfk0lhblYboV5W5WBak1vMYKMrQQ4QUhV0WnS/9p2WRNI9DUfcLkOBi5SweK8WUA+M6GG3ZTGC55pyxFbCJyFHatpM8Gq4TIdvMfXbAB9PMTF1f6DDx0dbnHcXX04yRlt9m9s8BqhNUMmt6X1GeKAxe/JkzvvUTaNJoS5BJaiDugSVfbl6Pplk4uw1HsZUhE++fIbe27bWN7pISoxMMktRVZkpl/QrUpQPEA6UVVFcIDO20aamvoE0Wb7SZ8wmI6OK8xlVfEioe7w+yquqW4R6IBjEZDRQXuWgylFDfk5mj0tf4oEjCe+u0GmCUJQnsVZbU8hw1x95w1ZkKNCbAqMioArwCvABqtqxKG8tpNMaNaqTVShvu01hdQihQFmGjsLqXtSwxAhfTgqmyrDTjQAq0nVsGmmgoDrE90JDQ5A30/oEZKW6GOwhpu4PsLNAz2tzLXznUzeOZB2JniPbdXZFpGYxKETWzUUiaY8U5QOEkrKqFq9pSXQIhTRURY3L4TqDAYvZdJhQb3C5eea1DyitsPPFVzvw+cNCPT8nbM+Yn50xqK4YCcCZpJLeoKEAeg1CUe4jc1hTmFr5TVT2pVcgS4SF+XNCx/j9AY50ClJsC/H+NBNH7/QfVoc99dsAW4YbWkR5R3XiHU3bjBQ9WbfBrFCWqcM9MZ3qXQ78aWaqk8LPftKBABN70dw7mGie2gowvizInnw9LyywkuDtfUOvz+eP6Im9rCmX9DdSlA8QqqpryM5Mi3UYQ4pKu5PcLOlJG01q6xoZM6KQRXMPTd/z+vyU26opr3SwYUu4mdRo0JOXnUlBTib5ORlYBqh94gdTTXxdbOCUTV7GlQXRhQRBNbIngUdqamwwWUjyeyK6z67wA282+ZUfu813xO3znSGEorAvV8+oyrbNqOMPBlg73kSjSenS0729MI+WT7nHAF8XG9lWbMCvh/zqECMMJooOuNCFINGrkVuj9dpzPRo4a2v5YN061mzeDEBKUhI//O53ye4Hv+5mYR5SYF+eAYTg+C29z5Lba+rISk+NWHxmk4kGV9cDvSSSviBF+QAgpGkoKKgyYxtVSitkk2e0KatykJ/TtsnTbDIysiiPka2aSX3+AJW2ag5WOdi0bTdenx+9ThceeJSTSX5uJglRHnjUU3YW6inL0HHil152FBkYVxYkqFPajJ7vb5plbLQ+WaoEOIBPUVn+gRtDN6pOFODEL728McdMklsju9UUU1MQxpYH2DDGyLFfH1ngQ3QEucuk8Pk4I3vyDYysDHLqBg/ZTdne8nEaBQfDJxeVqSq78/Vk14VIc0U3A9ucle6ohn2lupigCuvHGPlqhJFie5ARlUF0GhxIVbnwvXc56UN3i1NMV/S0Rv5y7X3+nH4iAFNKAhTbe1+aZK+uJTM9pdePb8+86dO57R//4KeXXNLh/UIIdn37Lf5AgAmj5JVtSc+RonwAUGGrHvQWcfFIablNlgxFmbJKB1PGjTzidiajgeLCXIoLD/n2BwJBKuxOyqscbNm5D7fXi05VyclKDzu/5GRGrOGrM7pbT15nVVg9ycRZaz1UpeqwegUVaSrrxhk5bUPkSy06y5a7jGYS/NFrhPwYFYHCIkKkN3a/JCHfGWLR1z7emWXmgo/d6Fs9dM5uP/89LoEfjOr61CLSYryz0pVvcvV8MNXEhNIAF3/o4seeVS33/Tv5NPSN4ZOHgA5ePcpCYXWIj6eYOHWDN2rTPFu/Ttv7oZeuWEq9ReHVoyykuTQu+tDV5irEmAowjNXxwHwLJ2/ythHN9RaFzaOMVCepTC4JMKoi2KvnZLrvQnjlFR5a9zIWU++vgtmddUwdf+TPk+4ydexYXB4P9z76KJeffTbpKWHBL4Tgkw0b+Pt//4vH68ViNhMIBrnmggsitm/J0ECK8gFAeGhQzpE3lEQUzxCZKhlPuL1eEqy9E08Gg55h+dkMa3V1IxgMUeWooazSzs5vDtDgcqMqClkZaS2lL6nJiT3uGwiGQoRCIUzGQ/XtRxLkQRVqElVMAcE7My3M2eMnq15jb56eZI/GVyOMzNnt77emxY6EucOaQqa7LuLrdsZTInwZIP+dnpfLjC8L8vFkEz6Dgr6VSEzwCkJq7xpPI0lAB6snmTiQpWfp+vBE1fZi9Pgt/+a1C24FYEehgQJniKUbvBzMaBqStLn/hXnpiqUt/2/+uzUL89IVS6kS8OaJCZytaFg+8ra5inLo7yzYv97L27PN5NaEGF8aZE+BngOZOiYdCDCpJMDW4QY+m2DitA2eHj+nH11wAT+64II276/eUF1TR2Za5DLlqqry5N1388B//8vpP/gBCVYrwwsKsDud6HU6fnThhRw3dy6KovDmxx/zxwceiNi+JUMDKcoHAKXlNmZPGRfrMIYUXp8fs2ngOX8MZALByE/y1Ot1FORmtvE9D2ka9upayqocfLp+K7UNjQBkpCa3lL5kpKV0Wi72+Vdf8ev77gPgP3fcwbC8vCNbHSrwxPEJKIQHBE06EGD6vnBjX4NFJdWlsT9bz3FbO697jkSzYnsB7bCmMKy2qk/rdbRuR5QKCKHwfSWE1d/zUo2QAn6DgqVd7XhdgoLVJ7DGoP9XABVpKnvyDewp0DPMHuKCj12Ygh2XbVQ5alj+zE18PPxidhXqmb0nXC9dWB3ijC88vD7XwvFbfP0izG1OJ29eeQmbhQ7/mQmkIqjSIFWBVASpZ53OTlReEioXKBpLFQ26+JsWOENctsrF18UGNo02Mro8wAlfeTE1lf2PKw+yJ0/Pq/MsLPq6Z8+pr2K8mWAohF4f2c+UjNRU/vCjH/H7a66hwm5nf1kZ6SkpjCkuRtfq82vpsceSn5XF5b/5TUT3LxncSFE+APAHAgPSGm4gU1phozA368gbSiJGtBprdapKblY6uVnpzJo8FgBNCJw19ZRVOdiwZReOmjqEgNTkBPJzMtHdeTNpngZ0QvDnCoVRdSEsAcH3zr+K5Z+7sRxhn9/k6UnyaJyzxnOYBWBBdZAPppmZsj+AucmAozMXkWYi5SbitCQxvWJvRNY6kjAvQ8GIwPKqu1fr1yWoJHjFYW4tjmQdmfUhiJJz6RqhsFao7D7GQm2CitkvGFMe5Kw1HjKaSnI6E59VDifTJ47mfM9b/OPscylodVUkr0bjrLUeXp1noTxdx/yzljLu5Z4NEWp9chhSoDxdR0m2jpJsPd4UlemozFQ0rEAtCnUCSgR8hUotkAncoQQp6uaFI70G078NMP3bjp1jxlQESWvUeGOuBVuqDk23mCujZPuoaVq/9mEpikJ+djb52Z33HSUlJvbb/iWDEynK45za+kZSkuQbO9ocrLAzenhBrMMYUpRVOijIic0kT1VRyExPITM9pWVwkRCCugYXZVUOdqblYcsfywFFJXF4gKQ9TkZtddBY5+HpYxM4a627TaOe1wAVaTpS3IL0Ro0vxh7K/LWXCRNLgyR5PBQ6Orf1a09PbP66Wi+kqui7Mc2zO3EcKe55iuCHrzb2el87C/WMqmjrvqIBG0cbmbLfDwX9+3UWEHC/0LEXhRVKiPSdflLcGske0e0MsMsTLs+6JfskMsebMLarVMqq17jwIzffnmLlQqFgOelMRs+aRG5WFnlZWeRmZob/3/RvUkJCy2NXqouptSqUZOspyQ43Eac1ahTbgpywxcsFi4zo2rz4RFQ6fDMbNM5f7eLtWRZemWfBZ1rMNb7+F+a19Y1yxoRkwCFFeZwj68ljQ4WtmoWtbPkk/U9ZpYPJ4yIzDjsSKIpCanIiqcmJJJft4mWhUiEU5nwaQp+Rgnd4FqPzUslK1rNtgmDClw7M5TXUeup5a7KO9AYNZ5LK+INB3CaF+Ts6tnZTgGFdCPLeWvkdaduAqkOv9b1+PRpuJkEVtg8zcNaatrXoX440YAgKJpYGYVb/fZ35BfxZ6DAC9ytBTAqsaspyd1eQN/tbr1QXc3C8kUJHsMPtzjjNBIT4oYDX1vho2LyRGc/9mgqHg9379/Px+vVUOhxU2GwoikJuVhbB9fuoPSGBgD7s6z7uYIATv/RiaSoTilaTa2eYA7BsnYfPJph4dlECjakn8sva9yIaU3vs1bURtUOUSKKBFOVxTklZVRvPZkn/I4QgGNIiXt8s6RqXx0ui9UiFILHjoFAYgyDF6QWnl4Q94VrsfODJJUkMd5pRs1OomjSC+TojafVBcDbw+TQ303ZVM+mAq8sM95EEeevflyw3d7pWdwVYtTW5x5M8o029RaEqVceWEQaK7KGW8hAAvy5s2Xfup+5+Tfj6BfxJ6LACv1BC6Jt2tmS5uY1ryZGoa3BR9ti75AAHM3TM23X4SVrrv51BgRS3IMUdwr74NvRAQdMPhOvZ/XqotzposCgkegRZ9Yd7nkfLk/1IqAIWbveRVRfi5aMt1BaczJiKjk9MOqKnNfY2Zy1FedLSVjKwkKI8zgmXryQceUNJxKhrcJGaLEuGokkwGEKvi+54+Z6yAYU/KiF2d3BfhjNAY52Hwm12dtQcoMaoMHFbAF9WMscVpBLIH0lwcSJvA8nXuqlcHc6qGx0NnHhmbBx+HNbkPjuv9BcC2DDayKZR4fHzw2whZu1tK2LLM3QkeQSp/ejv7RNwm9CRDNz34st9OlGvctRgqqwjoANHio68mrZXKXra2KsQ9mnPqtfI6uDcKl7EeHvGlwVJb9R4Y064dn72Xj8JPoEAHMkqBzN1HMzQYU/REdSB1ScYWxakLnEJP2tcdcT1m7FX1zJj0pj+eyISST8gRXkc42+aXCjHvEeXA+W2NrZ6kv6n0uEkJ46np2pN5bclKC1ip7VoCupA35T0m/GNn8dPSGDmN37SKmsxV9ayZHkl7AmLzXqTldwZKdgXjKTWnMjbioI54CfLXUemu44Mdz2GbpSVdCbaulvjXW1NYURN5ZGffJQJ6OC96WYaLSrfXe0m2dOx6C50hBAKvD/NxPFbujc4qCd4mwR5KnBvHwU5QJXdiamqjvJ0HVl1ocMGJ7VulO1rI29/CvJINBln12mcv9rN2vFG/rM4nHTSFEjyCAodQcaWBVm4zYcxGLYR3VWg59mFVv638HT+8p//Y/zII3uPuz2+uL7yJpF0hBTlcUxppZ3CPOkAEm1Ky20cNWNCrMMYUpRVOiiMUZNnd1AVuIkgvxd6vhCCKYpGYJkVm4AqFMr9CtOaHCgsAZixL8Dn40zcO6ztOgqQ4nOT4nMzqqai5Xa33ki1NYXypAy25owg2FTv7VzkxFxRi6mipmXoTHc5khuK22AiIRB5MdtbFi4z8+CmIJtGGcmq01ixpu2QoPboNfjOp25eOdqKcqaFQ/NJ+06oqYY8HbjnxZfbWN31lipHDYG6Bj6cZWbuno6PeyQEb7wL8masfsHiLT6O/dqHpoTfGx1NeLU6QxQ4Qxz7tY9dhXou/9HPuPH6n7J8cfcGdUkkAwkpyuOYkoOVjB1RFOswhhzVtfVkpCbHOowhRVmlnUljhsc6jC4ZocBfCbIBha1CxYIgS4GRaCw3wZhjDOiUsHXpMQJ+IPTsE0FGduNClzXox1pvp6je3nJbQNXxzj4TvrxUGicWEEw0gQBjdQMv7avFlFWL0dGIIjoXo50J8/a2jLGk3qJQf6KFK4XK6Bk6jvncy3BbqFvxGUOQVRfCl6EjkqL8CaESAu6OkCAH2PLiB6yebWBSSSDcmBphIinGO7raEklB3pquTrxaoxNhp6LsWo0777mfqlNub3GvaV9v7vb6MJtjYFwvkfQRKcrjmAqbk2OPmh7rMIYUoSZvW1kyFF1cHi+JCfF7qbm5oa8ImNF0W+vJiO2xKPAdNP4jdNxMiN68nAxaiDNmu1n1irPlNqEoBDIS8ealUj9jOP7MJFAUdC4fpoqacFa9sg7VHxZ9nQm1epOVZK+r50FFEK8BtpyawNcoHI/GXUqQfAVW2XrmCJM9Qo8aQUH+mVD4BJX7lMgNs/prwhLKf7iQ+e/6GFse34I83sls0BhTHuTlo62c85kbXQd/eod0XpEMUKQoj1M0IdCEhi7Om98GG1V2JzlZabEOY0gRDIXQqQPvdd48lrwzTkHjf+j5EIUTeiEam7PcrV1WFCEwOhowOhpga2nLtsEEE778VDzFmdTOG01msRGdprHB00BmU616gv/QyHSHNSUmziutxeNqofC1UDgRDSPwvlDRBOjOtJL8jqdbUz8DOliHwvn03doRoFHAv4SO3yohUiJ0Xv6oupjPjsugsLKxXwR5f9KdSa2x4LitPl47ysLG0Ubm7jncxcbmrCUrIzX6gUkkfWTgfRMOEezVtWTLD5WoU1phY5i00YoqVfaauG7y7IquLPEMClynBHlE6LD1UJO3Hl8PR86E6l0+EvZUkf7JLi72f8Wpe9Zzwr7NDKuz4TaY2JQ3hnfGzOHtMXP4dNgkdmYWodNChGJ4RWgUglPQMBCu2TcqYFWgHnh6kZWqlCN/Pe0qMDAOQU6EnsbjQuVoNMYrkcm8r1QXsy9XTygrmaJdNRFZsz39LZr7q2ylLyjA8Vu8bB5pwJl4+OvEXl1LtsyUSwYgMlMep5QcrKS4IDfWYQw5SsvtTD7+yJ39kshRVmmP2STPSGIX8KZQGakIFjWJupFNZSw3Cj0/IsTsPoi9nkzxBNALjWxXLdmu2pbbBNBgsvLeyJlUW5P5JiMfTVExhIJkuOvJdNeT6a7DEux40FEkKVDgEqWDgmIF9jlhT4GBnLrOG1HtySobppv4nRKZLPk+AWtR+adyKJtdumJpj7zIW9M88n7DaCMzPBbMVZF3uonHLHa0SPYI5u3ys2q6mVR1MVe2qiuvqWsgLVVO85QMPKQoj1NKyqtYevy8WIcx5HB7vSRYhu4XXSwoq3IwYUxxrMPoM78ReqYieEyoGAhxdJMAX65ojEBwt9CxQGhcrfZ+rP2ROJJIU4Bknxtr0MdRZbtabvfr9FRbknFYk9mbno/XEG6SS/G6Wmwa0zyNEa3d7oxX3/ax//gELvqobc17g1nBZVbwGhUq0nRsG2bgGiUUsaz200LHOYpGYruse2+EebMgr0hTcZsUEi1JmKp2HeFR8Us8ZssBpu4PsLtAz9bhBlaqi1saPjVNDMiSOIlEivI4xeP1Y5XiMKp4fX5MRkOswxhyNLo9JCVYYx1Gn8lCcIyicTxhOz0HGrkIKlBYLRRMQHEvyixa1/X2dCJoR3h1BkzBQJvbjKEgeY1O8hoPNZVqQL05ISzUMwqoMSciFAVjMECmp74ps16Hud1afWXjaCPjDwZI9IYHyqwdb2RXgYGAPuxjbfYLsupCnLrRy6JFkXm/fitgNwrXd1Kb3hNh3izIAbYXGZhSEkDk6lADkcnotyZea76jhQIcs93Hqulmpu4PsFJdzCWB91BV2agvGZhIUR6HNLo9JFqH7gdtrDhYaacwV9aTR5OB2uTZESMQfIvC2YrGrQR5UejYgEIOgnMUjTkIdBHQCs3CvLdirNqa3K0mTxVI9bpI9boY7Tzkqe7T6am2puCwJrMnowCv3hj2X/e6yGjKqqd6G9F1YdXYEUEBz6Oyu0Dh/I/dhBTYUWRgX66eM9d5SG88fIQ89E6U55+T0eb3v65xM+2gn29RsAuwNf3rR2GqojEP0dLU23xS1NHY99aCHMCZpDKmPICi9f8VhqFKXo1GUKdQnaSS2aDxcN4Kip//TazDkkh6hRTlcUhJWRXDCnJiHcaQ42CFnZHD8mMdxpCiylFDdubgcLsZqQg2CBUUGKXAL/tQ63wkwd2X7KjDmkKmu67XjzeFguQ3VJPfUN1yW5usenoBtZZENEXB2FSrHv6pw9pBrbpfwCpUXhQqhQjO/9jNgWwdn0wyYwgKzvjCQ0bj4SU/vTkG7cV4M3Oz9bzvFzwWFKQ6g2QhyFdARfChUHkOhV8RZFirs4LW5RLNvzcT0MHmkUYcyTqSjQYCzsYexyrpPkEdmALhEx9fVpJ0XpEMWKQoj0NKDlYyZ9r4WIcx5CivcnDM7MmxDmNIUVbpoDB3cEytnYbgERRCgohkxPuLamsy4xylR96wB7TJqtMuq25JxmlN5pv0PDwGExCua0921bPD3cBbbjcjRYgblBA5CG6aZqbBorBijZus+sjV33cmyAHOGW3knNGHhs2Uv3DohON0Bd4TCr8Wer7frrylWZi3FuQeo8IrR1lI9micv9qFbng+alX07Sd7S7zWj3eGyxx+syV6w6Lcn5UsnVckAxYpyuMQR009mWkpsQ5jSCGEIBgKYdDLt0Q0Kau0M/6YWbEOIyJkKpApYBcKE6PQENlbfHoD5lBk68A7wxQKkt/oJL9VrboA1hsT+LclleGpuZyZn4BFVdmoaWxxN5LnquGkjQ5MXQjynmbJuxLk3eFERTCaIH8WeiafmUDWRx4y68PlNK0Feb1F4ZV5FkZXBDl6px8FcOSkkLijvE/7l3SOLUUlq+5QaZM/K1lmyiUDFqlA4oxgMIRep8qJklGmvsFFSlJirMMYcjS4PCQnDvwmz2Zmo7FeKExs5wjylVAIAJMRmGP41tZQUHpY6x1ptgiF+70+fukrZ1qdoK5pYE+JqmPuTgNJCcnUzx9LINUKKOgbvRgrw5NKTZV1nHxqZKZs9pQRCvyFIM8LlTfmWFCA4VVBTAGBToOAHrYNMzB7j5+Z+w6d9PizkjGu3nnE9Xs70n6oN3vaU3Rk1x26gqGZ9ZhNxi4eIZHEL1KUxxllVQ7yB4Fn80DjQIWNorzBUUYxUAiFNHSDwCWh9WTP4xWNXws9ZwqNtKantkEo3C90FCC4C4XvoHE2GrF46jWWRNK8satv3iwU7hE6fqWEmKII1gmFfwgdi9D4mfDzyc56oLrNY4KJJny5qXiLMqibPZK3R5pQhAg3lja5wHTWWNqbDHnr0pX2JChwmaJR8L4Xe4pKaaaOgE4hoAMEnPNZuCG1NUKvogZ7VobTLLK7K86HsjC3p6iMLQt7ywtg+IpFsQ1IIukDUpTHGeGhQbLJM9qUlttkHX+UqaoePE2ezcK8SIEThcbDQscNTY2e/xMqlykhFisCm4CbhJ5iRTA3BiUuYeeV3jd59oVNQuE+oeM3SohiBH/RdOxA4ZdKiEmK6FSA6ht96PdWkbC3CggLVg2FOnMC1e0aS/VaiHR3A2NmCnINboTw0dlFR3XJArRVn/boOTTHqADZdRrZdV2LbaFTUUJH/jt3Jqg7ssDsyRCp7k6EHcjYUnQs2B4eMnVuwxus+mxjjCOSSHqPFOVxxsFKO0fPnBTrMIYc1bWyjj/alFXaKRgkTZ5wSJifp2j8ROi5W9MxWRF8jso1TQ2C2QrMFRolKDER5Q5rChNtJVHdp1fAE0LlY1R+o4RwAz8Reuaicb8SwtKLKwYqgjRvI2neRkZzqF7br+rQLS2kKpDAZ95U6kImBJCgBsg1uMkxuMgxuLHqgp0v3gG9bX70ZyZhdDR0uU1vnHa6I8wj2bDZ08x9tPAYwGdQSHEJLtfeZ19pBVmyyVMSYTZt29anx08YPRqLydStbaUojyNamg0N8s8STTRNQ0GRdfxRpqzSwQlHz4h1GBGlWZjfSZD1KGwRKgvQaP1xXKQIvmqyTuwurcswuiqvOBJ15gRSfK4jbxhBPkTlU1ROVzQeFipuFK5VQszoxSTOrgTsoWPUSJGpbYlOY8hAVcBKeSCRL1On4vaB8oyDNP1wcprEerbegyHC01Z92ckYqzq/MjGYM9jRwJ6iI6suxBVN1pT26lqy0mVyZaATCoVY++WXvL16Ne988gm3X3cdJy9Y0Ob++x9/nPfWrMFgMLB88WKuOPvsLtf8xR138P7nn7e5LTMtjVUrVx4xnit/9zsy09IwGno2F0EIQaXDwVP33MP4kSO79Rip/uIIZ20D6anJsQ5jyGGrrh00ZRQDiQaXm+SkhFiHEXGKXnoTVizlZATHE+IxofJdoWeMECxRNEYA/0GhUkBuDM4Do73LBASFCKqEwncUjaMQvaqn754g75hEXYBEXR1jTp/SclvwvZ3UhkxUBhLY7U3js0ABDQeDqKOHk+ppJMPTQLq7nlRv709i/LkpJG3p2H6yr4K8J2UsfVm3dZz9tc/ecjBTR07toRMpe3UtY0cUxjAiSSSoqa/n9gcfJBQKEdIOP1G+65FHePfTT7nu8svxeL3ct3IlOp2OS5cv73TNepeLJUcfzYVnntlym17X/abxe375S6aN71mJaygUYvY55/ToMVKUxxElZbKePBYcKLcxLF9O8owmIU1DHcRXJpoz5o8LlQoUHleC7EbhPaHyGAo+4Dmh49puDBjqq51fMy6DCUvAF5G1esIiRbCoG8+zK8HXF0HejLpkQdvfFUjX+0jX+5hoCVs2ln9YTUhRqDUn4rQkszuzkDpzIpUXaqiBEMaqekxVdRir6jDUujhSsr+z8pVIZcj7Ot21L/uMNSEFtg8zcNZaT8ttdQ2NpCRLF62BTmZaGm899BDlNhunXXVVm/vqGhp4+b33+NPPf86J8+cD4PZ6efLVV7nojDPQdSK06xoamDN5MjMmTOj3+JvpzdV3KcrjiJKyKhYPEs/mgcTBChsnLZoT6zCGFDZHDdkZA/PqxJtnnc77QuXqdvXQRS+92Wa7opfeZPvyM7lS0UhRYA6COUqIBgFeINrPvtqaTKY7fofY9EaQd5f2gryrBk+dEGR4GsjwNDDGeSg2zaDDl5OCPzuZ2nmjCaQlgAI6TwCjrQ5TVdiyUdfgbbkaIVQVJdQ20xdpAR2LEph4qDH/Jk9Piksjo+HQ8RWCQX2yL4HVGzagKAoLZx3SSkuOPpq//uc/fLVzJzMnddyTV9/YSHpqaq/2ueaZZzAbe26zqapqjx8rRXkc0eByDyrP5oFCo9tLotUS6zCGFGWVDgpyB5b1pxCCu1ecyXtCRz6ClULlGuWQIChdsbSNMN931lJK0DOqXUNnkgJJPdhv+QvVLdngvtSTO6wp5Df0/vH9SW/F3ZGy5O3FeG9ojk0NhLAcdGI56Gxzf8hsCIv1nBQaxxcQTA4LVp3bTyDVintEFkZbPXqXb8DVkHenCTUWwjyowpoJJo7f4uXypnryQDCIXh8bD3tJ9Ki028nJzMTcqnGyMDcXvU5HhcPR6ePqGxt57YMPuP/xx1EUhXnTpnH9lVeSnZ5+xH12t0kzEo+VojxO8Pr8mHpxJibpGz5/AJNRvg2iTVmVnePmxXeTpxCCXd9+i8VkQhOCf/z4Gvagcq8SxEDYQeRJDY5WNJqLn7aftZTCJ57FcfF5qEA6sAOFGX10WumLGG+m2prM5Kpv+7xOpOkPQd6VGO+pDeKR0HkDWEscWEvCgqBZqLpGZiNUBV9uKvXThhFKMPF2vo4Ev5f0pnr1dE9Dn6erdmR72FehHC8lKp3x5Ugj6Q0aN1e923JbdU09GWmyJ6u3zDvBSHEULzKUCHiyFx+LjtpaUhIPL1FKTkzEUVPT6eMmjh7NtPHj+clFF/HtwYM88NRT/OxPf+LJu+9GVdWeB9JPSDUSJxwoq5L15DGgrNJOQc7gseUbKNQ3xv9VoXtWnMm7QkUh3Bx5FII/KyESm764bibI/4TK3UJPHRyS3RddiBE931NCXKmEeFDouJ0g6TG+qh5UdRi1I9d2R4u+iL7eCvJoEky2kLiznKRtZUBY6Io94DKYcVqTsCWmsjNrGD592NEh0ecJi3VPWKybQj2zbYw03c3qR1vAu40KG0cZeO7RB9vcbquuJVvaIQ56FMIJk/YIui5devi221r+P2fKFFKSkrjxnnvYuG0bc6ZMOWz74y+9tMum+A/+858eRN19pCiPE0rKqpg0bkSswxhylFbYGV6YG+swhhTNTZ7xbEEZCAZ5Tah8V9E4CQ1TB6EWK3CVogGHuwPsFAp/FzqyEExE8FOh51JCLEJgjMHTDioqug5cDOKdnpZ7dCbIu5Mdj8TVCDh0suHPSSFl47429ylAYsBLYp2XYXX2ltsF0Gi04LQkUZmYzvasYvx6Q3h7n7tJrDeQFgdiPdb4DKDTYFXBRS1WiBB2XpkwelgMI5NEg4y0NOoa21qeCiGob2ggM637nTpHT58OwP6ysg5F+ZQxY3B5PFxzwQV9irenSFEeJ1Q6nCw+ZmaswxhylFc5mC+HNUUVe3UtWXHe5KlTVc5XNNYIhWfRcwtBRvVATI9XBH8hyEuovCpUZiF4T6g8gsLvCE+wjCZOSxLpnq6H2EST7mRWOxPkPXGj6W6pSqQEeWv8GYkYqrtnp6gASX4PSX4PxXW2ltsF0GC04LQmU56Uwbbs4fh1+jZi3TOsmpPm+GCIiPU0l8DiF7w038LGsaey9N+/YnRxMXZnLQvTDhdXksFFflYWVQ4HHq8Xizn8GXGgooKQppGX3X0XNX8gXDaWaO34iu3Fy5bx/tq1zOqkcbS/kKI8Dmj24YynuqahghzWFH0OVtrjvslTVVXOVDTOVGCNULhF6PkzQQp6IMwNCpyHxjFo/Evo2Bt1h/BDOBJSyHR3PsQm3ohEQ2Ska8d7jAJKB5fZe7gEyX4PyX4Pw2urWm5vEeuWJAqW5vGpORF/UxlMks9D7RwnRlvYvlHn7VvNejxy7qduDmTpKcvQ8dj1d+GaWcjI/DFMGJPfYy9pycBi0Zw5KIrCx+vXc8rChQCsWrOGnIwMpo4d27Jdg8tFUkJ4Dsa6r76iMDeXgpxDJcKr1qxBURQmjh7d4X7mTJnSYQa9v5FqJA6otDvJy4qMF7Gk+9Q3uklKiO+65sFIWaWD446aFuswuqR0xdKW/89XBC5C/EHouYMgWT3U1oUK3KaE8Ao4CIyKbKjdotqaTFHF3hjsuedEwpO8J4K8P7LkmlGP6u+/+v02Yr1dZr3RaKG6zoS3KIP6WSMIWQxtG0ybymAsQX+/xdffGEIwqjLIqMogS5abefffe9lzZS5X//yXnLLRy022d4+8iCRuKSkvx1lX19K4+e3Bg2zesYP0lBSK8/M55+STueOhh/AHAni8Xh567jmuvfjilsTm02+8wV2PPMJ9v/oVxx91FG+vXs3qDRs4+6STmDJuHLv27ePfzz/Pd045heL8/Fg+1cOQojwOkE2esaG03EaRHBoUdeoaXHE9ybO1IG/mREXgQuOXQs8VhFiAoKcl8WYFOs7J9D+NRguJ/vh104DIZccj3ejZm0ZGX3YyRtuhKxPRskJsLoNJ2F1Dwu7KltsXLzfjMpipsSRhT0hhV0YhXkPY7csa8JHWJNTTPQ1YA74YXtPpHaFkC6lVLk7d4OXt2WZ+Ewhg6OFIdEn88MgLL/DaBx+0/P6vZ57hX888w5knnMCt117LLy6/HL1Oxz+ffhqDwcDV55/PhWec0bJ9emoqmampLS4tN/34xzz39tt8vH49z779NmnJyVx9/vldTgBtz5xzzmH9Cy9E7Dl2hhTlccCB8ipmTBoT6zCGHKUVNmZOHnvkDSURI96bPFsL8hoBX6FQj0I+gjloDFcEjwodbyL4ASFGxOfTaENzAUU8hdrVKPfOiNRk02jgz0nBVBU/g5paGkwDXorq2zaYevQmaiyJOC1JfJuWh9sY/lsYg4EWoZ7maSDJ74mr11Br/FnJGO315FSHSHYLNu/YwdypU2MdlqSX3Hrttdx67bWd3q+qKj+/7DJ+ftllHd5/8oIFnLzg0Mm5oiicd9ppnHfaab2OKVpdQFKUxwE+fwCzSXqURxu7s5bM9JRYhzGkCDd5pkZ1n+0z3x4BJShYEBQRHrfeEb8TeowIxiLYiEoFCg5gNIKRCH4r9NxDkPx2jz+SeOyPcomuaDBaSPR5jrxhjIi0II916QqALyeF1LV7+mXtSKIA1qAPa4OPgnaDpbw6AzWWRGosSZSmZNFosiIAQyhEqrexRbAn+7rXzNqf+LOSMNnCJ0EWv6DR7Y5xRJLBRrROSKUojzF1DS6SE+P3Uv5gRdM0FBQ5kjnKRHuSZ7Mg9wj4Hyr/Eyo2oAhwA/XAGCEYh2C8Ev43qeklcYES4gmh4wol1GKJGBTwMiobhcK5isb9QsfthCj6TvdFY2uBGQ2BXm2NzybPgTbdsivaP5d3xiRxsjGEwsB9juZQgLzGGvIa2w5k8as6as1hsb4zs4h6cwKVF2ooIYGhugGTvQGjrR6jvR410P+++Kte8eI/I5mkbQcRQGWajslj5RVQycBEivIYUyLryWNCLDK2kvAkz0Vzo9PkWbpiKXUC3hAqb6EyBcFPlRBjEOiaRHadgF0o7BIKLwuVPSikC1pEeg6C64Ses5s8xvUKLBcar6JnLiE+R8fHUxO5qJcxNgv0/hTnDmtyG+eOgUZ/la1E6ph3dHIhiG25UH8O9DFqIbLddWS3OtFb9YoXoVPxZyTiz0rGNS4P54KxCEN47L2h1t0i1I22evTuyDaZBpPM6Bq81CSq6EOiW6PTJZKeIMtXhgglZZUcM1t6q0abAxWyyTMW1Na7SIlCk+fGs5byslD5CJVjENytHF5mApCiwFwEc5t8w0MCDhAW6tuaRPoIBO8IlSdQWE54mNAJaLwuVH6qhLhhh59j8vSMSNb1Ot7+KHlpXrNmcxIzB4jzSnviWZB3lun36fQYg4PPhrAzmsW/EtIw2erDZSTbDt0vFAimWPFnJ+MtSKd+xnBCVhMg0Ln9LULdaG/AUOuitxb+CvB1sYEx5UPDr10SXaLlVy5FeYypqWskLTkx1mEMOQ5W2FmyYFaswxhSaP3U5Nm6Ztwm4EmhYwN6TkTj70qQjB7sTqfACGAEglOUEOUCHhM6vkFhARrbhcJz6DkajVWoXH1aCldXBLn5Cy+PnGBF31mBeh/JPyfjiEKyMwFrLDJTNCMt6rXs8Up/CnIApyU5rgY19ZZVr3iPWGLUnWy8IsKZckOtu40jDEDQasSflYw/Kxn36FwCqdawv3tQw+hoaBHrRkcDarDjUhjNqEcNBPHpYXuRgQs/in2Nu2Tw8eAtt7T8/4PPP2fhrFn94vAjRXkM8QeCGPS6uHWiGMw0uDzSozzK2J11ZGVEtrG2tSD/WijcKXScgsZDSojECLyt8hX4jRLia6HwiFDxozASwYeoFAM/frOBv56WxAt7/Ty1288l40292k8khGL7NfLPycCn6TAoWp/XlhziSELVaUkiwxM/ziu9ob9KX9qjd/vRlziwljja3K7pdfgzw6UwjZMK8GckIvRNpTB17kNi3V5PIMWK0d7A1uFGhtuCJHmjOy1XMvT4xZ13kmi1csK8eZy6aBFzp0yJ2PBHKcpjyMEKG4V5WbEOY8jhDwQxyimeUaes0k5BTuRe7+1dVR4TKlcpIRb2wwj7yYrgXkLh+vOmuvNLlRAfo3L2Ww2MRKDf6qf868Y2j+ssex2NrHX5C9UEzhhOrsE1YLPk5S9Ux5UVYneaU6utyRTXDdwa/u7Sn8JdDYYwV9ZhrmzboCwUCCZb8Wcn4ctPpX7aMEyT02lwarimpjFxZw0NE+qwVdeSkZqMTienZEsiz0t/+xur1q7lw88/57UPPiA9JYUT58/n1EWL+jxRViqTGFJSVsWo4oJYhzHkCIvD+B7zPhgpq3SwYE5k+ifaC/ISARUoHN2P7TiqAhMQTEC0dPGdhcaZaC2No+2JtRjetQ5Gzh26l/NjcfxdRjMJcTCoqT+bPWOFIsKZckOdm4Q94ROfpMLpfPFZCTUpQeZ+a8CflcSmr3fjrK1vmougkpaSSFZGKlnpqWRlpJJgGbiuOJLYM6KwkO9/5zt8/zvfodxm4/3PP+ejdet44be/JTsjg1MWLuSUhQsZO3x4j9eWojyGlFc5WDhXDjiINqUVdobJJs+oU9vQSGqE+idKBXyLggI0ovCCULlcCaGPQSVYZ4I8HnBYkxn5zs5Yh9EnmoV1rDPmPbFwjOOXRI/oTl15rKkzJ7A7wc+kvT4sFQ1YDjqpOP7XXK69D4QHltXWNWJ31nKg3Mamr3fj8oRPVswmI9kZqWSmhwW7zK5Lekp+djYXn3kmF595Jlt37+bWBx5g5Usv8djLLzN5zBh+dsklzOxBk6gU5TFCE4KQJtDreu/YIOkd5VUO5s2YGOswhhTNvvCR6J8ot9m4QeiZhkAl/CH2AyXU4qAST7QXktHO3HoMJqzByNrPxYqujl1Hgr2j7bvTMNsR3RWmHr0RcyA+jvdgy5J3RkhVMflCbBhjpNGsMKY8SKJPsFJdzOXa++hUlYy0ZDLSkhk/alibx3q8PuzOOuzOWjZv242ztoFQSENRFFKTE8lKTyEzI5Ws9BQSrRbZ/yU5jOraWt5evZq3Vq9m5759TBg1it9fcw1FubmsfOklrvrDH7jrhhs4Yd68bq0nRXmMcFTXki19smOCrCmPPg5nXcSmp+7ev5+RCH6t9v9gkt7SWVa3t6KwN2gMnoztkYiX2vPB0OTZnnjOlgtFQRGCPxfBY2t97Mk3sH6skfk7/Ew6EGgR5p1hMZsYlp992JVTTdOorW/E7qyjvMrBlh3f0OgKT8U1GPRkpqW0CPbMtBT5fTLE8Pn9fPD557zx0Ues27IFs9HIqYsW8YdrrmH8yJEt282ZMoX7Vq7kgaeekqI83ikpq2KYHBoUdRpcbpISLLEOY8hRVhW5SZ5zpkzh9yhsEAqz4yw73h1hGC1hXm9OIMU7dOvJY0G1NXJ2iLG6ytLdDHs81KzPPTeNr31uDAqMsIUYYQvhTFR5a7aZ0kwdJ23uXXyqqpKemkx6ajLjRha1uc/vD2CvqcNRXcv2PfuprqnDHwh7oyclWMlMTyErLSzYhSadjwYjJ1x6KR6fj0mjR/O7q6/m5IULsZg6dt6aN306L777brfXlqI8RpSUVXHqcUfFOowhR2m5jaI8WU8ebQ5W2iM2JMt54Tn8WlG4Teh4hiDxdEW5OxnbaIkrhzWFDHfdkTccJLQ+9p0d4/4+9k5LEqOryyK+bqwbhqNBb0R+jTmRNG9bx6P0Ro3zV7t5Y46FTyea+F4kgwSMRgMFOZmHmQUIIWh0eVoE+zcHytmzvyTCe5fEA6cffzxnn3RStxo5Z0+ezAM33dTttWVHQ4xwe70kWOPzkuBgprTCRpG0oYw6tfWRGZLV7LryhVAYjogrQX4kyl+ojqq4cliTyXQPrlKKIxFr8TqYavijSW/LY2otiaR6Gg9bQ6/BKZs8fJur53+ffhqRGI+EoigkJVoZWZTH3OkTOO34eSxdfHRU9i2JLr++6qpuO6sYDQam98AmUWbKY4DL7cVqloI8Ftiqa8mStfxRRRPhEpO+Nkk1C/I1QmENKvcr8TlOO9bCsJla8yHBMpSI1fGPp0KqaJSV9Mc+epItX7LczIfmJMY5DnZ4vzkAp633cMdDD3HMzJkkWuWwOEnkOFhZyf8+/ZRKh4NAIHDY/Tf/5Ce9WleK8hhQUl5FsawnjzrN4jBSk7ck3cPhrCMrPbVPa7T2JX9fqNhQuEPo+B4hhg+gbHlXtC57iYSwFIqCGldScXDjNkTWnzxeTu76m740kXoNRixdXJnIrteYN306z7/zDpevWNHr/UgkrflkwwZ+fscdhEIhFEXBoNej1+kIhULodLo+DRCSojwGHCirYuakMbEOY8gRCXEo6TlllXby+zisqeilN1v+/xDg9nh48oJz+a3Qc7LQOE/RMA1gcd6+Dr2vAt2rM2AKHp69kfQfTktSxJo8+0K0mi8j0ejZkSBvvq2rtXsi5K9YsYIf3nIL3126FHMnzXgSSU944KmnmDVpEjdceSXPvf02+dnZXHbWWdQ1NHDB9ddzw5VX9nptmTKMAbbqWjJlCUXUkU2esSGSzivNWC0Wrnr5df6mBClH4SdCz5ciPlV5/jkZfbLra358T9ZwJKSQOYSaPOOBamsS6TGwQ1z1irflpz+IlR3ikuXmw/bd+raOTjw7inXM8OGMGjaMzzZt6r9gJUOK0ooKLjzjDEYPG8bIoiL2HjgAQEpSEhecfjr/eOqpXq8tRXmUCYZC6FQVdSB1qA0SSitsFMlJnlGnpq6B9JSkfll72stv8is1xPeVEH8TOu7VdNTFacVGX8V56zWOtM5QbPKMNU5LMunu2GbKY21R2BO6K/abhXj77WstiaR148rESnUxU8eOZdf+/b0JUyI5jIKcHOobwq+9cSNGsHbzZrQm+8ui3Fw2bd/e67WlKI8yFVXV5OfEfsjFUKS+0U1yomz2iSaRavLsiqKX3mSOIvi7EiQVwY+FnrVxkjXvSDy3F9W9FepdifPqIWaHGA/49AbMIVky1B0ikX3vyA6xM/b+/gmctbV93qdEAjB5zBg+27wZgBkTJmAyGrnvscfYs38/L/zvf32a1C5ryqPM/rJK2eQZAwKBIAZ9798okt5RXVNHZlpkJnl2RdFLb1K6YilXKhoLhOAWoWM0QbIioM37a1JkpNbtaBiRX6fHFIpPd5rBSCwvzrQXuPGeLY9UOUytJYk8W/d8wC0+webH3oAf/jAi+5YMbS5etow//N//oWkaqqrys0sv5df33stTb7yBEIKfXnJJr9eWojzKHKywc9T0ibEOY8hRXuXoc7OhpOeUVTooyI2OL3yzMDcgejxePh5GtEeKkKKgijit4RmkNBgtJPk8sQ4DiI9Jm50Ryfr0OpOVZJ+7W9umN2rYUnQ8qi7mCu39iMUgGZqMKCzkibvuavn9pGOOoTAnh03btzO6uJh506b1em0pyqOIEIJAMIjRIA97tDkg68ljQlmlg3kzo3cSWvTSmzy8/AyGI0jv4P7BJL47I+xPHnsXkKFE2Hklfmr441mYR4qeWH6mN2joQ4L92fJqqaR/mDh6NBNHj+7zOrKmPIrU1DeS1k8Nb5KuKat0HDYWWdL/OOvq+63JszN+/ewL6IEbhI7HNJVPhEK5AE0MDe/nsPNK/AjEoYDTmtxjO8TBKJq7yoRHMksevhqkdXt7BThhi49V082UlJdHLA6JJNLIlG0UKTlYSXFBbqzDGJL4A0FMRkOswxhSRKPJsyPMJhMPPv8ib5x7Ft+gsFqorETBDYwUglHP1XD+ScmMSQ1nzdwBwQZ7kMaAIM+qYtYrvF0SYEdNiO+OMXJC4aHXzWZ7kBvXekgzKfx9kZUsS8d5DXXJgja/a6uiM+obwGFNYXLVt1HbnwRqLElMtu2PdRg9ovmkoC9iOVYZ+XpTAine7pWuNFNYHWLeLj8/v/12nr7vPkxGYz9FJxlszDjrrB5/j2166aVe7UuK8ihSUlbFCUfPiHUYQ45Gl4dEa2y8docyzpp6MlKTY7Jvg8HAWS+/EZ4E2vRZWifgGxR2CoUfrXbzwCIro1JUfvGZG58GuVaFCpegMSBYkKfnhAI9D2/3tYjyL6qC/OZzD7+caebmLzwkGtp+SLcX4u3v644w7+52XdHQg1pbSWTw6/QY46yxNtqCOZp+5jWWRNK8PS/RmlwSQMvP5+k33+Sys87qh8gkg5HzTj21jShvcLt5++OPOXXRInStnFbsTidbdu3i+iuu6PW+pCiPIvWNbpKTEmIdxpCjtEIODYoFZZX2qDV5dkbrSaBFwGRgGTDtk0/48aOPMm/aNLxpFTx6++3hMclPHeqaf+1bP8VJ4Ux4g1/wq7Ue7jnGQr1fMC1Dx966ECadwtjUjutUnQ0+Pvvajtcf4kzvAQy6rjMtzaK++d/eiHPR9BMfhpBDAw1QetFYG6uhPP1BtJ9LrTmRgnpHjx+nAPl3fch/z9rDhWecgUEvJZDkyPzqqqva/H73I49w9skn85sf/OCwbX906614fb5e70vWlEcJr88vyydiRGm5bPKMBf0xyTNSnLJwIXffcAOBYJA//exnLb6yugseb9mmKFHl23oNIQQv7fMzP1fPzCw9n1UE2eQI8ZPVbn77uYegFhZkrUX0xt1Ozrn5Ez76sooPVu3ksg9cLeU8HdFRll1dsoAtjiCv7vN3+Vxa18m7DSasgd5/IUh6Tr0pIW6vTHQ0dKc/9hFtaixJpHbTo7w9WfUaum8cfLFlS4SjkgwVPly3joWzZnV43/IlS3j1/d47/EhRHiVKK2wMk8IwJtiqa8nOSI11GEOO6trYla90hxkTJ3Ln9ddTlJfX5vZmYT41Q4cnJFhbFeKp3X4uHR+uQZ2RpePkIgPPn5JIgkHhs4pDZQvaqk95d+WH3PC3ddw2Q8/dYzz8fZEVXwi2OUPdjq263sc9z23n8g/c3LrBS4O/e5lYhzWFTJccGhRNnNakHjd59pSh4BrUE/rqwz+6IsC/Lv9dBCOSDCV8fj/2mpoO7wsEApTZbL1eW167iRIlB6uYMKY41mEMOTQhEAhUVZ5/RhMRoybPSKG74HF46hJ+OtXMzz5xs7hQ39IYelqxkdOa3sqpRiVcMiIEO2s13jsQ4O0DAR5YZGVcWnh7RVEIaAJTU/lKhUvjoW0+vqkPoVcUdCrot6xDr1PQqQo1DX72V7lYPDOXBxZZ+e06D0eofGnBYU2hsN4e6cMh6QKnJZlhtVX9tn6zIO9oSFQkWPWKtyXbPRAcYbo6Pe1u/Nm1Gvty9axUF3O59C2X9JDZkyfzz6efZsaECYwoLGy53VlbyyMvvsi4ESN6vbYU5VGi0u7k+PmyyTPaRGuipKQt8Z4l7w66Cx7nhKcu4b4FMC3j8I/Ker/gQKPGeluIOzZ5seoV5ufqeez+B8lZdX3Ldv/e5sOsU8i1qtz/lZdXvw3wndEGVowyE9QgJCAkPGjTJhHSNKwmPVP2b8egq+eXa/xcNdGE1dA9Ve60JjG1al/EjoHkyNRYEplW+U2/72eg2Hn2d4OpR2/C0scSrVSXRm1COFHzb/1iJn5xN0dNm9an8eiSocMNV17J+dddx3d+9jNmTphAXnY21bW1bPj6azRN49Zrr+312lKURwFN0xAIdDJbG3VKy2WTZywoHyS+8LoLHmdBq+bP0kaN5/b4sXk0NthD1PoE3lCAu+dbmJKhP1STfsHjhJ66hM32IA/v8HFykYEVbzeyKF/PsycndGil6C7diaKARa+ATsHu0VhvC3LTHEun8bUXakFVh0HrfpmMpO/09zEvf6E64uUrAyEj3hm1lkTSPL2rJ29GKKA2pdw/nmxi5W9uJqUohwvOOINzTj4Zi8kUgUglg5XMtDRe+tvf+OfTT7Ph66/Zsns3WWlpHDtnDt8/91xGDxvW67WlKI8CVY4acjI7mi8o6W9KK2wcN09eoYg2ZVUO5kwdH+swIoLugscJ/PdiHtrm47m9Ac4ZZWBSuo5PKoIcm6/n5rkWko1KmybR5sc13PNdRiWr5FoV/n28lRHJnWfiHt3h44OyIA8eF/Y/f3lfgBOLDCR0M0seVFR0UpBHlfAQm547r/SU/s6Sty5h6Q8iuXaNuXd2iK0J6hT0IdhVoOdgpp5L33fhTNrPi18/xAt3PMSZ6zxcGZJlLZLOSU5M5Mbvfz/i60pRHgVKyqoYXpAT6zCGJHUNblKkDWXUqa6pJz1tYJevNFP/n4v53ToPjQHBsycnsKdW4+b1Hn540aVcunx5l3Xzx1//NMe3+r215WJ7ylwaJh38cYOXe4+x8Mo+P39daO12nNXWZDL6ueFQ0pY6UwIpXlesw4g7+rOEpcaSSFFd7xvpAHSaIKTC6kkmTtrsxRiC3FqNM77w8OpRFj6ZaOLKCMUrkfQEWU8RBQ6UVzFMivKoEwgGMehljWC0Ec3NtQO0ybM1tkcv4vIPXGSaFX7i8PKX1+v44wYPd//+Ni7rxZS39tn01lS6BT+fZqbBL7h0lYscq9qpB3ozrcsaqq3JZEjnlagSdl6pj3UYQ4pGo4Ukv6dPa5j9Ap9BYdKBAF+NMLY0j6oCTt3ooSRbx4vvvtv3YCWSHiIz5VHA6wtgNsmRvtGmoqqavGxpJRZtnHUNpKcM/Cx56YqlvCMUnEJHWV2QH6NnCRov/PsJkhMTe72urqnevDVCCCrcGkWJKv881sp7BwMMT+pezqRZmG+oyWHY6q1tbmvPQGkWHCg4LcmMdFbEOoy4pDlbHvGyGEXp83AsYxACOpizx8/zC6xsL9IzqTRssWgOwBlfeLj/8cc5cf78Pr3XJZKeIjPl/UxDo5ukhM4btST9R2mFXTZ5xoCyyvgdGtRTJiNYrmgco2g8rAS55ZXXI/Il3Tpj/m19iKs+cpNvVcmyKJj1CmcMNzKlA8eXrmgIGRlzZkKXTYHS7zqy1JoTSevlEJt4o6Nyk74K6kgJ8ubXbVBRUSPQN6EApiAEdAonbfLy2UQTddZDUj/NJSjYXsOzb7/d531JJD1BivJ+pqSsimJZuhITDlbaKRwk4nAgUVZpHxTOK0UvvcnRL7/JT19+nUtefoMJL78Z0fUDZ/+bf2z18r0P3SwpNPDv463o1d7lAIUIC41BUDE0oAipKjqhxTqMNgxkZ5XOaL7CU2dOILWTGv6ePu+cmhCrJ5tIdWnM2uvnvenmNh7oM7/xs/KRJ/D5u56oKxnc1DUc3qfz7+ef77f9SVHez+wvq6S4IDfWYQxJfH4/Jlk2FHUcNXVkpEtv+K5Yv3Ur3/npTylp0HjmpATOG2NE10tBDlATMpGq65t3s6RnhBQVNU4F+apXvC0/g4kaS1Kf7RCbWbrBQ1AHr8yzMLYsiFBg80hDy/2ZDRrGIPw9c2lE9icZWKzfupUTr7iC4y+9lBMuvZT/vv56y30PPftsv+1XivJ+xlnbQHpqUqzDGHK4PF6slv6z+JJ0TPMkz8HQ5Nmf/OYvf+Gnl1zCT8s9BN6sofyF6j7Ve1f6E8gzSheQI9GVSO2pgK0x990vOxr0pSwl3kR9jTmR1D7aITZjCMFp670UVId46lgrmfUa68aZqG7VyxFuCIWV6uKI7FMycPjzQw9x8oIFvP7Pf/LHn/6Ul997j+vvuguvz9flVNm+Ihs9+5FAIIhepw7YUeMDmYNyaFBMqKlrIC1ZnoR2RSAQoKa+ntF3/4n2HWvthXl3a8ArAglMtDi73EY2eUaWsPPKwLSgjDex3V1qLYmkVkbu5FMFjt7lZ/zBAB9PMeM3KHw4xcQ5a8LuLqaAwNvNOQGSwUVNfT1XnH026SkpFOTkMHPSJH59771c/utfh+sF+wmZKe9HyqocFOZmxTqMIcmBChtFefLYR5vB1OTZX9icTlKDAXTd+K5vzqAfSVDbA1ayDO4u15F0TU+bEp2WZNLd8WOH2B9Cuz8HCvWGUBfTU/sSa5pLcMY6D1avRlmmnkZT+M1pDgh8RinKhyLHz53bpnbcYjJx369+RXFBAZoU5QOT/QcrKS6U9eSxwOaoISdLTlGNNmVVDgrkiWinrP3yS370g6uY1osLoF2J8xAKeqXjNaUg7x9qzQmk+GTJULTo77mpOgGz9oabOr/NDRcRmP0yUz5UufH73yc7Pb2lJBNAVVVu//nPue6yy/ptv7J8pR8pr3KwYPaUWIcx5BBCoAmBTo3cOWezr3RXw18k4HDWkSmbPNtQumIppQIeFTrKULhMCXF0HyRGs8huLm3xajpMSkiK7ygjFAVdP2bM4oG++oxH0qfcZTSTcIShQX2dJDq5JMAnk82sHW9kSkkAv15BF1+9vJIoYTIauXzFisNuV1WVi848s9/2KzPl/YQQgmBIQy8nSkad6tr6iA6vaT3opasx6UOdwTTJM1LU1NfzL03lV0LPNEXwgBJkviIiYl3YnDn/+t0g1h32vi84BIiUQAyoOvQR8MuOBu2fc09Fa2+2b+38EqmymhpzEqn93FhrDMHiL72MrggPEqpKU8mtCXG59n6/7lcS/8w555yo7EdmyvsJR00dmWkDf6rhQORghZ2i/Mg0eXYkwkNPXSIz5h1QU99IarKcfteaH/zhD+Si8A8lSEo/natUJ6SQ4a7rn8UlHTJQnFf6k56I7b5mzPPPyWDLJ4lRaaydfCAAB8CnhwaLys8dcoCQpP/Lp5qRoryfKDlYJevJY8SBchuL5k7t1WP3lZZSXVuLy+OhftV9NAbAFRCMT9dxdI6uxUlHCvPDKau0y8bmdpy8YAEb9++jP0/PHdZkRleX9eMeJO1xWpNJ98RPk2d/E4lsd1+Fea05kVHO8iNu19cSlmZsqTomTZmIQS9lkuQwo6x+Q77a+omSsipOXjQn1mEMOdZ+dDvffJPE0uOP6tb2wvZQy/+/2Onghr9/wahkHYkGpekHrAaFv37p5V96uGWuhRHJ4ZIkKczbUlbpYOakMbEOI65Y9N+VvIGeO4WOpWiMRWCK8Ke7V2/EEpRTB6OJ05LERFtJrMMYUmgjkrGWRG9Alvn2c5lhlMPnJNFF1pT3Ey6Pl8QES6zDGFJ88v5t3PKfrew5WMfrH37Yrcco2Ve1/H/1VzYuOW0sD5+QwF8XWrltnoVfzbJw7VQzz5ycwLIRRq7+yM3eukO1pLLG/BCyybMtpSuWYlbgHiXIMASPCZULhZ5fajoaI3QtVAOUQd5sGI/UmxNIjjPnlY6y0PFmadgbWnv1RytbWWdVePPjj7nwjDOitEdJvBOtT1kpyvsBt8eLxSzPsKOFx+vl3bdu4fantnHNWdMYmadjX2lptx/fLMwVVcGgV1GXLDhsG1VROHuUkeumm7nmYze7aqQwb01Lk2cEHW9igdvj4Ya77sJZW9undUpXHBrNXQdYFZiF4EQ09qBE7BJlnTmRFG98icOhgCD+vzzjTZD3JR6fpsOoRK+x9rMJJi48/XQy09Kitk9JfDNr0qSo7EeWr/QDB8ptFOfnxDqMQUfrUhOPL8gnW+28t6GCz7c7mDwilZ+fM54ESzqIUqxie4/WVrKvwqT/BW5vsNNt1CULOBXQP/YhP17t5mfTTJwyzIBOVY4ozAd7mUttfSOpSQO7ybN0xVI+FQrvCT2WNZ/wfVWj6KU3u/W4jtgr4BWhYyMKxyBIQ5CuwM8JYe5hyi//nIwOLQ8d1hQyZZNnVPHr9BhDnX9OxJLmeup4E+S9pTlL7giayTB0bYcYKXbl66lI13HxsmVR2Z9kYPDgLbdEZT9SlPcDJWWVTJ8wOtZhDFreWFvGX1/cwdjCZJbMyuM3F04mLSl8ZeL5T6AwE1ZvqUWrehA15wfdWlPYHmLGmHT++dpurj5zLOqSBWirPu0wa37iZceTtbCG+1/Yyb+313FcgZ75uXpmZOowdDKmcbDXnw+WSZ5rhcoxaHzTdKG8dMXSFmHuDwT4audO6hsb0YRA0zQc996BhoIgnD3VgAAKq4VCJQpnKBpXEyKxExHekdhufbm+o9tbb+9ISGa8vftXhSR9x2lJIi0KLiC9ZbAI8tY4Alay9Z5OT07b05tmTwGsG2dke5GBM9Z5sJgH33GURA5/IMCOb77B7nR2OOHzpGOO6dW6UpT3A7bqWrIy5WWv/mDDrmr+7+Wd/O0nc5hQfHj9ss8P31mUz+trD/CPV3dzzbIjC/PmDPxREzK47UkfNz+2hYtPGsGoDgR5M9NHpfHoL+exbX8dn7y6gb9v9VLSoDE7W88xuXrm5+nJtba9wD2YhXlZlZ3pEwd2k6cmYBMKtyghbhY6NAFB4NGzTufLWfPYuG0bIwoLyc7IQFUUPGs/Q0VFIVzKoDT9qMDJisYCBPouxHhH/+8OrcV5uHxlaFvzRRunJYl099BxXokVrd8X9qCFqVZ7y+2RHJTlMinszdOzq9AAwHmfuPmxZ1XE1pcMPjZt28YNd99NTX19m4mfzSiKIkV5vBAKaaiKIgeo9AP+QIib/7OF3180pUNB7vGB2QQmg46/XDOLnz2wkQM2N5efcjf+xDP4bNMmrj7//DZ1z61LYvQ6lad/t4DnPz7AD+5bx8TiFC45aSSzxqa3WCG2RlEUJo9IZfLPlvCDVZ9S49VYWxXks4ogf9/qI9OitAj06RnhLPpgFeb26jqyBniTZxmQCIxEEAJ+KXTYURiB4PiNn3Prf54iNTlsbli6YmmPi4p7Kr67s57JYaRwWmRFiqRrnJZkiurksKZoUh20kK4/lPnuqTAXQL1VoTZBpTZBpS5Bpc6qUJuo4jKpDLcFmbnXz4iqIN8LyUFBkq658+GHMZtM/PbqqynMyUEfQdvMXq+04euvMRmNTB4zpkPBMlSpsFWTlx3ZL19JWDy/tqaM4bmJLJza8WCgUgcUNVVQZKWaeeSGeTz69jfc8K/NKMpmPP4Qx4wsZerIw69ieP0hzEYdqYlGvr90NCfPyePnD2zk+/euY3R+Io/9aj4J5s7fLuqSBWQAp636lNOKjYQ0wfaaEJ9VBPnblnAWfU52uMzlmIcvIsfauaIbaKJ9MDR5lq5Yyk4Uxjdlt48SAhtwsxJkRNPHW8Nl36U3RQuRFuPNuEJ6rGp81jYPZhpNFhKPMO59sBMpL/DuEhIKeqVn/hdLlpt56X8+dhYa2FWox2dQSG/QSHFppLo08qsFKW6NtEYNvRZ+jJzcKekOFXY7N//4x5wwb17E1+6VKA+FQtz+4INU19YSCoXITEvj0uXLWbZ4MaqqIoQYskJ9f1klxQVyaFAkEbaHcDb4eOStvfz5qhmdbldqhwlFh343G3Vcs2ws1ywbC8DKd77hby/t4qgJmeyvbOS2K6fzTXkD/3h1N6u/sjF3QgY/OWsc44el8MAruynKtjJpeAqvry1jwbXv8sU/TsGg71p4Ntei61SFKRl6pmTouXoyOL0aayuDfFZ5KIt+dI6edLPC3jqNHTUhVODS8UaWDrBsel2Di5QB3OTZ3Ki5WahMafriv06NjNNDbwR5R30MANqqT9v8XhFIIM/gklnyKCOInjWfJFxW1tPjHRLwKipPL7IypjzI4i+95NVoXCFFtyQCzJ48GbvT2S9r90qUb9u7l6z0dF7629/wBwJs+PprgJZMmRCCfzz1FAtnz2bquHEArPvqK1RVZdr48RgNhgiFH38crLAzd+r4WIcxaLj9r9ey80A9DZ4gS+cVMH1U57X6VTVwXBeDPC8+cQQN7gCb9jhZu93BMZOzuPf5HVx68kh+f/EU3t1QwTX3r+eWy6ZiMqj4Axq/uXAyN5w3kZc/LaW755nNwrw16WaVpcONLB0ezqJvc4b4whai2iuYmaXj4nFGXAHBL9d4GJOqY+wAEuYDuclz+1lL2YzCfqHwJQrXEDnbtZ4K8s7EeGdU+hMpNMVvw+FgxKszYAoGYh3GkKI2ZCJV3/2sfIWAe4UOI3D+J25S3OETbZkFl0SKH55/PjfcfTfHHXUUORmRvRLaK1G+ZvNmGt1u7E4nWenpzJ9xKHvprK3l6Tff5OEXXkBRFKaOG8fGbdt4/cMPEUKwaft2fnDeeRF7AvGEEAJ/IIDROHhPOqKJ0/ckowuSWLejmh8tG8uSWZ1fgRACNA1URbBxdw2zxqYfto1ep3LtivE8/3EJa7c7uOXxrdz+vemcMCO87rnHFTN+WDI//ftG/nLNTJ79qIRf/HMjf792DpecNLJHsXckzJvRqQpTM/VMzTz87ffDySb+uN7DP49LILEP/ufRFPRllXamTRgVtf31hM7sCisFvCpUPkTPZATDENypBDt1SelveirIASoDVgrf75n1p6RvOK1JZHhkk2c0sQesZOq7Vy5UKuD3Qs9yReNMND6QglzSD4wZPpwJo0Zx/s9/TlrK4b1UiqLw4v/9X6/W7lURqE5VyUpL46d/+hPnX3cdO/ftA8JlLY+8+CIbt23jpGOOYdyIEQDs3LeP4486ip9cdBEHyssB+HDdOh589lk0TetV4PFIXYOL1OSBexk/nnD6ngRg4SljMVgMvL3VzpptDho9HWepahohNQm+2FnN9+75nPc2VnS43YZd1fzrtT2MKUjix8vHtQjyZqaOTOOmS6Zww4ObufqMMdhqvKzb0bvyAHXJgpaf7rJ8pIHJGTpOf6OBP6zzsK4qSEjrvJaypCHEj1e7WP5WI0/v9rVYM0VzoJHdWUtWRmrU9tddOhLku4XCHZqO64QeE/CAEuR3aohLVI2iGNYkdHYC1xV+oYtbv+zBitOSTLpbXp2IZj25PWghqxse5QcE/E7ouVgJsVzR+ODV6MUoGVrc/cgjvPPJJxgNBlISE8lITW3zk96BUO8uvcqUL1uyhCvOPhudTsfP//xnXnz3XX579dXc9q9/kWS1cvrxx7Nz3z6y0sPZyqSEBJ564w3ysrOZPXkyEC5nefbttznhqKMYM3w4EG4edbndHDt3bq+fUCzZf1DWk0eCZkEOYDLquP+W43j+jd38e9W37PpXDcuOKeRX3207XavUDsMy4bF3Sli+oJA7ntrG9FFpZKUe8potqXLxq39v5vtLR/PvN/dy9qJhHe7/uOk5OBt8XHT7GqwmPV/tq2HexL6VZ7QW5l0JMFVRuHGmhSsnmHi3NMD/bfFS7RWcMszAacUGxqbqAAhogrf2B/j7Vh+XTzAyNUPPvV96WVsV4ta5ZlJNalScXoQQhLT4a/JsLcg1AetReFmo2FBYpmhcSwhrnBUGd+aL3xFBoeA7KEVHtHFakhhR0/EJv6R/cAQszLDautzGJeCPQs9Pf3ItyxYvPuyEfKW6+LBseUl5OZ9t2kSi1crSY49Fp9NFPHbJ4OSDzz/nwjPO4Porroj42r0S5dnp6WiahhCCY+fM4YGnnmLciBGU22z85Ve/4uP163G53YwsCnfdHX/UUfj8fswmE0uOPhoAj8+HyWCgpLy8RZT/65lnSEtOHrCivKSsiuOOmhbrMAY0rQV5MxaznkvOmcix8wq57taPmbOguOW+mhQr+w7Usa/WzMhRITbsruadO04gM8XMTx/YwEVLRjBpeApPf1DCO1+Uc+2K8Rj0CpOGp2Axdf4hvGLhMI6blsPra8sYkZcQ0efYVWlLM5kWlQvGmrhgrIl9dSHeKgnw80/dJBoUChJUvnSEGJOq8pcFViZnhJ/HQ8dbeWCrjwvec/HneRamZer7XZjXN7hISYrs8ekrzV/IfgEfovCy0GEGVighjkHQyXynuKC7wtwWsJLmkf7k0cZlNGMN+GIdxpDCrRlI0HV+RUgIuF/oWHTqaSxbvBggPPBLXdxmu2ZhvuHrr7n/8ceptNs5ZuZMSsrLefbtt/nHH/5ASlJSvz4XyeDAYjIxd8qUflm7R6K8rqGBtz7+mIWzZ1OYm0swFCKkaThqanjspZe4+Sc/wWqx4PJ4KMjJIdFqBcKZ8u+cckrLOnankz0lJVx5zjms27KFY2bOxGI2U1JezrmnnhrZZxhF6hpcpMjylX7hjff38cjTX/PDS6Yxc3I2NUAwqPHPlV/yzkf7mTVhFpnZZhITTTz3UQmXnzyS4TkJvPNFOXc+vZ1lxxTy0i2LSE820eAOcNcz23E2+EhPMnW6z/RkE5ee3LNa8u7SHWHezMgUHT+equOaKSa+coRw+gQ3zDCTl9A2O21QFX42zczMLB3Xf+ZhYb6e66abSexHYX6wKvZNns2lOs0uJHUC3kblTaEyGsGPlBCTEd1u1I0U5S9U98p9pSNh3v61UhlIINNd06f4JD2juYgsjs/phgytHYdeJ3wF7P52WcvLtfdZ2UqYO5JUlh99Os5ElaN3+ji+LIjynwMMAz6daOI7X1zAvF0+8p0h9CEQCmhK+N/w/5U2t2kqKAKS3eKw14SsYe8bgWCQfz79NG99/DGaECz4f/bOO7yt8uz/n3O0l2V5j3hkOXsnZLHSJOxdCm1ZhQ4obWnp7tv10kHL20F/3YOWUqBQyibshBkIhEDI3sN2vG1JHtrSOb8/FDkesi3JWrbP57p8JT46es6jY0nn+9znvr/34sV849OfHrbL6hvvvcff/vtf6pqaWDpnDt/9/OdHlUYyHOefeSbPv/kmZy5blvSx4xLlVouFbpeLfz7xBBevWcMHe/fy6rvvcuW559LjdvPdu+/GHwig0WiYOXkyPW43Rr0eURQJhUKIooggCBw8fhyNWs3Fa9bwia99je/ecgvdLhcdTidzp4/NroA+fwCtRunFlAr+++xBnnn5KL/+wVlMrjz1IXvoqQPsPdjBv39/Pg8/6uKOuzdz+2eX8OSLh7nnuSMsqcnj61fPprLoVCTX3uXjN4/tJxiSOdLQQ97MoUV5qokIr1jFuSgILCoc+T12ZpmGh85R8asPvfx1j4+vLtSnLGLe0NzO/JmpWbjEQvDB6/iwPcSLdQGaiw00NflpQmAVMj8VglSOUQUVEeZDvTea/SamuI6nd1ITHI9ah0GJkqcVj6RCP8CLv68gPygLPCKL/EII0nL1ZeEI+Un+Ia6lLUfkaKmaIyVq3DqBpYf8XPheoNeXHMKLrNP3+vhwsoYPpmp5bqmKkAiiHBbdp/6VB/wOPjUsORJg6WF/qk/FhOJX//gHz7/5Jl+5/nqMBgN/e+QRbvnf/+W+n/886v4f7t/P1+66i6svuIAbr7iCfzz2GLf88Ic89KtfpSQt6aI1a/jCHXfwm/vuY/a0aVH3SVtHzwvOOosnNm7kR3/8I+VFRXzp2mtZ1ieMv/n99/nnE08giiL7jhxh2bx5SJLU78Ts2L+fqRUVlBQWMmvqVN7btYtgKIQtJ4fSwsKEXkimqW9qpaIselMbhdjJ013bL4Wls8vHvx7dxz2/WE9xgbHfvquWlPL0y0fo7BSZN9vCrNmL+fP9O/jzz9eR1+3hqbdO8Km7tvC/N8zjzPnFtDg8fP7urayeV8QzPz2bAmvmBHlf4omax0qBQeSiag0PHzp1sUiFMG/ryFyRZ/d91/GjbR72OyQun6JhRYlI4Rwd6k1OLGNUjPdluPeEM6TDMsEb2KQbu9FCnmdsF3mms0CzL+suGzrCORxtASOFfZxX+grybhnuklXcKoQoPfl5r7/iQioef5YDl1/IM6cZ6LCITG0OcvYuH6WOEOIQNfMCsOhYgEXH4rO77DCLPLnSwJLDfuUOSpJwezz894UX+P6tt3LZunUALJkzhwtvvpk3t23jjKVLBz3ngaefZsXChb053vNqajjvM59hy4cfcvqSJUmf4wWf+xwAxxoaoj4uCEL6RPmkkhK+dO21fOnaa3ubBEmShCTLqFUqgqEQOWYzv/zmN3uLvwYWge05fLg3t1yv07H/2DG6e3qYV1MzZpsO1Z5oYcbUipF3VOiH3fcAebpr+23rK8zffK+BZQuKewV5fWM3FrOW3BwdkyutaNQiH+7uZt4sK5OrJrHnQAd3/m4rf7plEdeun8yCqTa+/IdtXLbawdNvn+C69VNSlpIyGmIt8ItHvBvVAq4BqZjJFOayLCPJEqoMFHmG/n09v9nhRZbhP+ea0PVNFP9YOGVkvDbVkWWlgU0m6DDkUODuzPQ0EiZTgjxRGh/t4FCBkbLlnt7f+/JnWcUiZFYN6PR59PIL+amsYmoJXPiMC1V8jUDjIr9HQhuQabKJlDnGj5NcJjne0EBIkph3sscNQIHNxsqFC3n57bcHifJAMMjrW7fyvc9/vndbYV4eC2bOZOPbb6dElN/zk58kfcwIo8q3iAhoURR7vRWXzp1Lbk7OkG4MPW43TW1tnDY/3OVlzfLlHKmr4/X33uO6Sy8dzXQySlNrB2evWJjpaYwpohV1RogI89e3nOCidadE9P2P7ePNrQ2sWlJKc5ubgjwDKsFEaXH4/fbZT87jaz9+nd+/Usdt66qYNyWXX92ymAc2HuP3ty1jZmVqcszSRawuLgAmjUC3/9QV6e3mIMuLVCTrZl5Xj5scs3HkHVOAPySzoTbA8xdZ+gvyPpRdmZ9RYR4tnzzRPPO+dIW05Kiy53Z5ps9zurAbLNR0nMj0NBJirAnyCE6DhdKNtTT6XIMeWyRI3C+r6JHp7S8gy/AnWYUB+KIQ4tUUCvII848HeGmRgXU7vEzqSF7zsYlKpNi2w+FgasWpQKdBr6eprW3Q/nank0AwSFV5eb/tVWVlNEbZPxksmTNn5J0SJOlJ0GajkYUzh+5oebyhAUdnJ+XFxQCsX7WK3z/wACFJYsEwz4uw6a336e72UTWpBFuOOSsi65IsIyOjUmWXLVw2M5wgj3D4uJPjJ7pYsbi0d9u8mQXYnV4WzSuitNDE7Jp8Xng5hF4ffh+o1SLf//IKPv8/m5g1PY+l84upXmrke0snAeAAbJ3ulLymdDNS2stki4gvJLP+qW6CskyXH+5ZY2Twzb/EaGhuo6w4M0WebR6ZXK2AVTf85z8igLNJNI5WmDcFTJRqBosUhdTi1WgxBLNnMTQR6NQZyfFF/75eJ8i8IMvUITD7ZBnuo4gcQeDnQjBtLksLjgcw+mSeXWbgys1u8nvGZsS86Jxcyqzps4X0dIbgxcHfY6WFhVSVlfG7Bx7gx1/+Mjqtln8/8wxvbttGfm7uoP3bnU4ArOb+JhtWi4WdBw+mYuopJe0qcu706dx31139ts2aOpVulyumdqUrF81BrVbx1rZd3P/ESzz8zCu89f5uGlraCWWoEVFru4Pi/KHbvyv0JxZBLkkSf3lwJ1ddXINaJbBjbxsvv1mLNUfHrgPtXLBmMkvmFyOgQqeFQFDi4hufosPhoSDPwOXnTePRZw9FHdthNeKwZibCm2yGS3vRqAT+e56Zh8818fh5Zj46RcMBZ2KfkdqGBt547z127N9PbWMjgUCAhuZ2yksyUwNi0wkIAty0ycVdH3h46qif/Y4QgVD00FjZlfm9P5kiWQuD5oCJEq0ro69lopGGgOu4JdF8cgBZEBCHOfsGwAMEZPi9JPKSLPIDIYghzbG66U1Bip0hOk2ZDxKOdURR5Ke3306H08llX/gCl956KzJhxxOdVjto/8gZl+X+7xNZlhGzIGgbLxmxC6ksLe3NR9frdHz/1ls5cOxYr4XicBiNeqZVVjJvRjilwecPUN/Uyr7Dtbz69nZkZEoL86meVEJFWRG6NLS8r21ooaq8OOXHGQ9EE+TR8sr/+N8f4PWG8PtDXHnzBgrzjVSVWzhc20lZsRlRDH/YmlskSkpENGoRlzvAx255lqsuruGF147zs28Pn6cdEeZjPXI+XMRcpxJ60zvsPpmF2vi/pBpaWrjpa19kRq5Ilx8cPglvCM6eu5hFhw8RGqJeNpX+6EaNwCPnmtnnCHHAEWJbW4gHD/o54ZKotojMtKmYkatipk1kbp4KlXjqdQ8Us6MVy9HSN0YSzKOJlrcEjKw2Nyb0XIXEcGn1mPxjMwVkrKauhAQBUR4+iNADmIEHZZEWBP6fEMxYUzC3VsDoU5ZvyWDu9Ols+POfaWxtJc9qxWgw8NWf/7y3IWVf8m3hgGhnT/++DZ3d3RTYxl6wNGMefn3TTvJzc1m1aFFC4+i0GqZVlTOtKpxPFJIkmtvsHD/RzLZdB/AHAuTmWKguL6ZqUklKGp3UNbQwf+3KpI873rj/4INcWBX9sb7C/NXtd/PYc4f488/W8sXvv8oXP7WQtaeHu2/KskwgIPXu+2H7B8yYPAl4iXt+sZ7PfONlvN4gdw+wTxyOoaLmY0msj2SveMgZYltrkO8tjS9q5fF6uf1bn+dTM7V8suaU+j7kDPHPVoErnu/igiot19RoKTOJ7OoIYtUKVFpUKW9cZNIILC1Ss7To1NeYJyhzuDPEAYfEAWeIx476CUrwmdlazq/URE13iyXFZSQBnYjA7ivM+x57pLGCsohGHJu3yMcqdoOFPE9XpqcRN2NVkAN06UzkeIf/Dp6JzA9lFQXAj6MI8nWX6dN2DiQR1EpKedIQRZFJJeEO6aFQiF0HD/LRc84ZtF9+bi46rZbjJ06waNas3u3HGhr65aSPFcadsbZKFCkvLqC8uACWhEWcs6uH4yeaeXXLdrp6XOi0WqrKi6kqL6a4wDbqFuEenx+DPjvs9bKV+w8+CMCztQIXVkWPJth9D2B3evnp77byrVuXUZhv5JZr5/Obez5gzox8SgpNCIJAieWG3uc0tdo5c/kC1KprofIBLl43BZ1WFbMgH46xGEkfKmr+o/c83L5AT64uvvf63+64nskWkU9M73/bsNhi4DQpxG3nmHnokJ9rX3ZRZhJocEmoBIF/rzdRZBRTLswHYlALzMtXMy8/XAyqFmFba4i7d3jZ0R7iW4v1Q97SzEQ6SLxRer8kohGyR5BPlBSaDkMOJT1Ks6Z04jCYsXmH71p7syjxUVnCAoxQXpJyVBIE05eSPa7x+nzodac01YubN9PZ3c2V554LgMvjwaDTIYoiapWKNcuX8/Lbb3P5+vUAtLS3s/vgQW75+MczMv/RMO5E+UAEQcBmtWCzWlg0J9yYyOP1UdfYyq79R9nY4UBAoLQ4n+ryEipKC9HGkfLS4/JgNiaeMzcRiAjyCM/Whr89o4nzX/31fc49q4rTFoZXyGtWVbDprTr2H3ZQUmjql+YiyzIhKYT6pAd+nu5aPnZRN1/8/qtceu5UyoqT0111LIrzgTj9Ml0BeVDe3XD4H7iODccD/O5M46AIc6PfRLm2h2KjyFcW6Pn0LB37nSHm2FQ8esTPza+5+eNZRkpN6RfmEH5v3PKam6As85PlBv62xsTtm938cruXby42pHUuEWJ1KRkutaUlYKREKfJMO3aDhdlttZmexoTCqTdT1jXy52X+x7LD/cfklXHpRSB7Fs1jlVvvuIOK0lLWrljB4bo6/vzww1x/2WUU2Gx0OJ1cePPNrF60iF99+9sAXHPxxXz6u9/lrnvuYdncudzz6KPMmDyZ5Sdd/pLBFV/60rCP67VaKsvKuPqCC/pF7ONlQtqFGPQ6Zkyp4Jwzl3Hd5efwiUvWUjN5Ek2tHTz2whv86/EXeWbj2+zcf5Su7uEvgOF88pI0zXx8cF3NNVxXc82gPPLtu1s5Xt/FdR/t/4bu7PJji9Lox9nVQ26Opff3Vrud67/yIpIks2HTsaTPO1Igmu1FotGKP/90lokX6gL8ZkdsHQlD/76e99tC2HQC06JU5Df4zZRpT0WxLFqBZUVqjBqB62fquGqahhs2uXjmuD+8ePr39Ym/oAR4symIJyRzboWGL7/pQZLh/1Ya2FAbIChlf97nUCKjKWDqFeXZIEQaH+3IinmkGr9agy4UHHlHhX6MpsjTYbBg846dZk0mr0SPfuwVFmYjX77+ehpbW/mfu+/mxc2b+fpNN/HFa64BQKvRUJiXR0mfRpPzamr49be/ze6DB7njD3+grLCQP/zwh6POguhLntVKfm7ukD+iKLL5/ff59He/yxvbtiV8nHEfKY8FlUqkorSIitJwR05ZlnF09VB7oplXtmynq8eNTquhsqyIqkkllPRJealtaOa0BYmviiYa19Vc0+/3vo2CNmw8yscvmYFWc0oEdvf4aWzpoaxkcNS7vrGVyj5dVD3ykwAEgxIPP3WAz35iblZYZmaCgWksJUaBM0vVHO0aOYoTEdAbjge4qDr6XaPWgJGzc4b2bP5EjY75BWrueM9DbZfEF+frkxoxV33yX8MK/eNdEsuK1FwzQ0ezW+Zrb7mx6QRkGRw+mcJ02zMkiSa/mZlWe6anMaFQGjVlBr9KPeqFUDpz6i0eWRHlSWLBzJn87cc/jvqYxWTimT/9adD205csSUmjoAixNAzyeL185c47+dsjj3BmlM6jsaCI8igIgkCe1UJen5QXr89PXWMrew4eY9Nb7wNQUpjH8RMtrFmZWJHqRGOgII+Qp7uW+w8+yK5jXXz80nAXr9e21PPYc4c5WteJ0aAmP1fPs7UC19Wcel59UxsrFs0GwvnoJqOG3Bwdv/z+mRw44kipIHdYjVmfzhIR5vscIb72lptyk8hXFwwfuYoI3YPOEJubgnx5QfTCaAkBlTB8xHlOnoq/nG3kc6+60ap83DRLC8MIc1mWaWlv7xcBGY7hhHlNrooHtnpo90qUGkU0IqwoVvP9pQYsCTjQZIJoEei26VPpfqWZ4TNtFZJJt9aAeQiv7GwnnYWOySTWhVA21TSYvBINBYqkmsgY9HouOOssfvH3vyc8hvIOihG9TkvN5EnUTA43oQlJEiea2th3uJanN76Nz+8nx2yiqryYyvJi8qyWCRuljcZQgjzCJ6Z+nP/X/hiV5TkA1DV009zm4uE/XIDFPNibFKDD2UVerqU30i6KApeeM5VHnjnIt7+wLLkvYIwirjudQ397hQX5Kn62Mpx2M1TEOiJwu/0y33jbzTcX68nXD7791x3SYBYDMR3fphP541lGvrPFw9PH/KwqUTPzyMeZZVMx1SqiVQlIssz2thC/3+Vjjz3E/60ycHZ5OEI/UmR9KGG+okTNH840cqhT4lhXiAaXxJPH/CwqVGHRnroTMzDVZ6QuqaNlNN0vw0JFVqK2acZuzCHPM3bSKAYyFoW5R63FEIgt1S5bMHtlupVI+YTnRHMzU0bh+qKI8gRRiSLIMgtmTeWs5QsB6Op2UdvQwpb392Dv7EKjVlNeUkhVeTHlxQWo1ROzNHskQQ7wz933I4gCL54QuWQKXPfRWRw+7mTDpqN84tKZJ6Pkp8YJhSREQcDh719EesX507j1u6/wzMtHuXj9lKS/lrHIlLWL+Mtv36HbL/dGiQcK84iwDUoyP9jq4fRSDedVRk9dGZhPPhKFBpF7PmJinyPEh21BPmwP8fBhPyd6JHK0Ag6fTKlR5HNztHzVrOMrmz3k68MuKiOlvPQV5O5AuJi1xBheSEzPVTE9VwVouHWujseOBPjMq25+stzAyhJ11Nz7dIv0eOjSGcnxKkWe6cZusMRUcKiQPJwGC7me4b9jktmt97W5OjpyRIqcEmX2EFOag3Evfgu6JNqsKkKKLp+wbN+3j39v2MBnr7oq4TEUUT4Kjg8o8syxmJg3cwrzZobFYCAQpKGlneMnmnhr2y5CkkR+bg6VJ+0YLabsLhhMF/cffBCdQUNeUQ51h1t5VlUCCNx41Ry+dMcbWObP5PqZ/YV9S7sda94JoL9wtJi1/Pw7p/PlH75GQZ6elUvK0vdCspT5U2yceVoFP9nWyM9XGnrv4EQEb0TYHu0M8cOtHvL0Il+ZP7TFZ6PfzExD/HnNs2wqZtlOLUw9QRmnTyZfL6Dt0xP7h8v0fPlND5PM4Rxw6eUrkHOrkGWZApuN795yC+XFxf0E+fa2IN9420NIlvn8HD0fm6ZBkuHdlhDekMwZpWqunKZlWq7I19/y8Ndvn860GOY8XGOmWIgIhmTcZm83Wilwjz2v7LGO3ZDD3JbkF46ni7EWJQdw6M3kDmOHGOvnKda7BHWFKhYcC+DTCLwzQ8uBcjXrPvSijcN33OSTsfVINORPzOCbAhh0Oq655BI+dfnlCY+hiPJR0NDcxqolc4Z8XKNRUz2phOpJYeEuyzIdji5qG1vYuPl9ul0e9DoNlWXhlJeSJHimjwUGWiRGWP6RWTz/8LssPXMGU2eX8VoIvG4/180YHGnfX/cMIclFXYNIRZkFWYZul5/OLh92p5dZ0/L46e+28sQ9l6BRJ/+cZns++UC++rFZXPczB08cDXDF1FPpQI33XMu21iC7OkK8VB/kC/N0XDElepOdCK0BI2cOU+QZKwa1gEE9+Dhnlmn459pw91BBCFtECUIrArC1tYnrbruF/z1Nz+rS8IKstjvEt7Z4+PFyA5NMIt/a4ubVhgCeEAQkGZNa4Gfve7mwWsPlUzTcNl/H9/+xg39/b3VMKWaJCvO+EbxkiPN2o5Vp9oaEn6+QGAGVCq00NrvCjEVBDmGP8orO1qiP9f0MJcv5x9YjoQvILDgeYPERP6/O1/PIGUYu2+LBHEeXzpqGAJvn6Ghqa6M0xtoYhfHDzClTmDlldHfoFVGeILIsEwyF0KhjP4WCIFCQZ6Ugz8qSueGKRa/PT/3JAtJX3voAGZnifBtV5cVUlBdjHGdNiYYS5ADT55Zz7eKreOjZZ3np/u3odTouX7c+qnBqapF46a3dHDzWDoA/EMJk0JBj0WK16Jg/q4AbPjYbjVrkWF0n72xvoqXNTY87wJJ5RZx3dvWEyvnXaVTc9dlF3PSLd1hQEGLqSZvDH2z1oBLCRZAPrDdRZhp5ARNCQD1CkedoqbREjzbNsKmYm6fiq2+5uX+diqAkc8vrbr4wV8fKkvBn8b61Jp6vC9Dtl/lkjRZBEKjtDvHk0QCfecVNVWUuR5s6eWNnK2ctKI5pPqONmPcl0bxyh2H46KHC6Bn4t5EAIQ5vf4Xk0KM1YPF7oj6WCgvOHLdM18m0N7UE6z708s4MLc8tM/DRt9yoYnwLLDwWQBLhpv/5Hzb8+c9Jn6fC+EcR5QnS4ewiP3f0XSP1Oi3TJ09i+skCUkmSaO1wUtvQws5XtuDx+jEadFSdjKYX5ucO2ZFwrBPJGf/hF74w4r5SoILpU/azbEEBl5wzBYNejUoVXVA+suEgnd0+ls4vwaBX8+8n9yPLcMFHJic0z7EWJY8wudTM7VfO5NsvHuVfK2UMagGNCJ+Yru2NOo9ET0iDKcYiz1SxqFDN/Hw1B50hDndKzLapOLPs1FeZRiVwyeT+xcFVFhW3f+0svhiUeG1HC0+8Wc+2g/aYRXk2IAsCKkUgpoxodzG6dCasY9R5ZUwjCGkraA6KcLREzQXbTi0CbpI28SlJ4opVl7B5to6z9sRWdCoAS44EaLvIzI79+8mxWEZ8jsLY4KKbb455X0EQeCbBRZkiyhOktqGFqknJv6CLokhJYR4lhXksXxj2P3d5vNQ3tvLh3kO0djgRECgpyqOqrJiKsiL0uujuJGOJWIpBI3h9fnRaDctmXcpTrz3IJy+fGXW/tg43r7/TwN5Ddj73yXnUTMnlH//Zg9sTGNLRZbxz8cpyXvuwhac0eXxcbkAjCvjiuDPf4DdTHkeRZ6qwagVcQZnZeSIftge54oUeLqjScvMcHTkDLA/7Fm9q1CLrl5Syfklp3MfMZLTcp1KjDWZ2MTQRsRtzyFPy+NNKUBAR05QuJAmwaYGeYmeIos5wD4cbpU1A+Fr8r40Pc9Hln6TMHmJ6U+ye6WVFRTi6uhRRPo5oaG1FJYrMmT6d+TU1+INBvL7kOwQpojxBak80s/6MxMzh48Vk0DNzaiUzp1YCYTvG5jY7dQ0tbN97CK8vgNmo781NL8yzjqnUjHgEOUBDczvlJYVMrSzm539zI8ty1Nf7wmu13P/YXq69YhY2q45Pf+NlLlk/hft+cx5mY2yR4YGM1Sh5BEEQ+OTaan7+0B4+8cMz2Pv0C3x1Yexd9xr9ZmoSKPJMNt6QjF4lcHqphtNLNXR4Jf64y8dnX3Xxp7OM5OnFqO4qoyFeQT6S8I4WmR1q/3ajlQKPIg5TSbRzbzdYqHK2ZGA2o2es5pN36k3kpsll6IXFeo6WqLn2NRcCpwR5hByzmb/8+W5u+uLt5HdL5PWM3HwNoMftxmxUjBzGE7/73vd49vXXeW3rVo43NHD2aadx0dlns2zevKQeRxHlCdLj9mbMPUUlipQXF1BeXMBKwoWmPS4PdY0tfLD7IG12J6IgUFKYT2V5uFNptkTT4xXg0ahvamVqZRklhYXotVqOHlrI1Jod/fYJhSReeP04wZDMtVfM4pW36gkEJK69YhZ63cR+2y+pycPR7eet3W1oTXoqzLEXwrYEjJyRhCLP0WLTCbR7Tl0g8/Ui31uq5+4dPn6708f/nmZA2rh51MI8Gc4rydi33WglX4nYph27wczCpsOZnsaEwmGwYBvBDjFZzK0NoAvIPL7SyJVvublXXDtImL8z/XOsqtTw7FI9V7/pjsmRpcflwmyK3nhNYWwS6Rjq8XrZuGULz73+Orf88IcUFxRw8Zo1XLxmDZNKSkYeaAQmtjpJEI/XlzUiN4LZZGD29GpmT68GwqK0uc1OXWML2/eciqZXlBVRVVZMwRjOTW9saef0peHV6fc+/3n+5+67+eOdK8m3GQDo6vHzo7vfoaLUzO9+tIYf/Optmlpc3HT1HDQaxa5KEARK8w08uPE4axYVI66bHbP4lNJQ5BkL8/JV/GOfn/kFaubkhf+mgiBw5VQNt7w+ursZ6fImj0e0dxhzmNFen8LZKEQjJKpQy7FFRxUGs/FJL+sui/1OHITtEKvTdHeisj1EZXuI96dKPLfUwBVv9xfm94prAZhTF6ApT8WmBXrO+8A7Yr57JFIeCMae8qIwNjDo9b0ivNVu58XNm3n1nXf4+2OPsWDGDK46/3zOPT3xYJAiyhOgrrGVyrKiTE9jWFQqkfKSAspLokTT9xyizX4yN70wj8qyIirKijCMAaeXsOuN1NuIafXixXzs3HP5n7ueZ+n8cI7/G+82sGpJKZ+7dj4f7GzhRGMPf/vF+pRYI45V8nN0vLGzlS9dMSPm57hCaowZLvKMcGGVBpUgcPtmNxdVa/jSPB2CIDDJLOL0ybgCMiaNEHO0PJuaBEXDp9agD2XHuZ8ohAQBUSmsTTtOg5nc5iNpPebiIwGcJpG/n2Om2Bliy6zzqW4NEqk8EYA1O7385wwju6s0zKsd/rPY43ZjMRqxdyl3t8YzRXl5XHvxxcycPJn/PPccm955h0AwqIjydFPb0ML8mWOvW+SgaLok0dJmp66xlR37juDx+THqdeFoenkxRfm5Weeb3tXtIjen/23Bz3zsYxz0HcCk9QNwy7XzWb0s3DRoSpWVkCRzz0O7+Px1C9I+32zlnb1hK8lZlTlAbEWM8XbyTCWCIHB+lYYVxSq+8IabSSaRK6ZqEQWBaVaRx474uX5meJGZjYI7nii5hKDY8mUA5wgNbLKZbMonjzdaHhRVaNLsCy8Aa3f6WLXPR1OeiiabimdOM7B+u5fJreG5qCU4Z7uXp5cbmFMXQBziIykD3W43ZpNJEeXjmL2HD7Phtdd4cfNmOnt6WLVwIT//2tdYs3z5qMZVRHkCtLTbKSpYkulpjBqVKFJWXEBZcQErFs0Gwk4vJxpb2bn/KC3t4YK+ovxcKsqKqSwtwmwyZHLK1DW1UlHa/y6FKIr88vofYPc90LvNHwjxzgdNHKvrwuUOsHB2ahs5OKzGMVME6vWH8Acl1i0uiasguCFgpkbvSOHM4semF/nRcgM3v+bmwmoNOpXAXSuNfOENN4c6JW6dq6M0Bu/1dJGIx7JT8SfPCHaDRXFeSTOZXHq6dAIbF+rpNAoE1AIhUaDZpmJya4gbpU3cK66lsEvC7JE5XqRiSsvQC4dgMBhXDxOFsUFDSwvPvfEGz772GrWNjdRUV/OpK67gwjPPJC83NynHUN41cRKSJASEMZuPPRImg54ZUyuZcdLpRZJl2tod1DW18tKb79Hj9qLTqplUWkRlWRGlRfmoVSPnaT//xhuctWwZRsPoRH19YyunLZgV9bE83bXYfQ/g8Qb59NdforTYxIwpNn7+ndOpmWIb1XHHE0ebwgJv2cz4uku2BkycYcm+jpLTrCpm5opsOhHggiotpSaRf60z8cABH9e87OL2hTourk5vDUgyG5y0G3MoUMRh2rEbcsZkB9VsipJHiDVa7tLqMQ/RNCjVHC9S0ZCvYv12L8XOEGaPjMgpR5aIMJ9X62d3lZYpLdHnKQAatVrJJx9n3Pid77DjwAEmT5rEeWecwfrVq5laUZH04yiiPE6aW+2UFiXeKnusIQoCxYV5FBfmsWx+2A/c5/NT39zG4eMNvLl1JyFJwma1UFlaRGV5MVaLqV8E9ifP/ppH//YGp62ZyfS55bz5/C7+79ZvD2pHG+n2KcsyAX8IrU49yK2lw9lFvi2H+w8+GNXJJU93Lfdv+jFTqqz85Burk306ouKwji3rq6llZu789AJWze1/92CkFJagnB1FnhAWvX0tBT86Vct9+/2c6JH5sD2IJMMsm4rrZ2j56TYvq0vU5OmzJ2IeD+1GK7NbazM9jQmH02BK6x2KaBaZEVLRxTIbcejT57wykDn1QQS8vDpfx9m7fNR4goOcWG6UNvFb4zrenjV8/ZXNaqWusRHGafBuIvLh/v3oNBr8fj+Pvfgi9z/1FJ5hfMo/ePzxhI6jiPI4qW1opqp87HQBTAU6nZZpVeVMqyoHwiLa0dlNfWMrb27dibO7pzc1Zo9vO68++SFrLlnI3vdrObCjnqLyXL7z1//jiZ+f6nh1/8EHsbd2s/PdoxzZ20iX00VuvpmNU97nE6svZ8mcOeTl5iIg8MChf/c+Z6Awv//ggzz7ylFuuHJ2+k7IGEOnUXH+8vJB24cT5OEiz+yJ/AwUMGeWqfn9Lh/1PRLX1oQvmHvsIba2Bqkwi+Tqxu7FsUtvwupLj2+zwikkQYy5g2q8zaAGPlchjMNgJs/TndQx112mj/nuwez6ILoAvDlHR01jcJBF4r3iWkyARysQFMN55tGY/FYjD27YwDUXX5yEV6CQDfzottvSchxFlMdJfVMrS+bF7lgxERAEgbzcHPJyc1gwexoAwWCIv7xzP7vermdG5WwK1IV85MxKDDYRrRUe/NOL3Pn83Xx62XXc+8GDfLD5EPVH2pi/fAoXXbuCwhIrbU2dnDjaxt+ef4g7/9JFSX4RBSX55PpFKqcVYbLo+wnzSKS99kQ3c2cUpOS1Dswd7xslH0t55fHSmCWdPIdCLQo8fr6537ZVpWog/Y5CyY5qypC2luMKYYKCiCrGYsPRiOpkC/JsTF2JB6fezFR7U0bn0JSnYmqf7p0RYR6xRxQBk1fGpRewuqMv2hYcD3Dfsy9x4VlnpWPKCmng4jVr0nIcRZTHic8fRKdNrBvkeEWWZb73m9+g1+mYXl2NUa/nlaOvs+OdIxSW5bL28sUYTTqCPhmPPURPk8TqJas49LqTL710N5LgpmxGAed+bBnaPo19iifZKJ5kY8mZNciSTN3OLhwdnRzcdYJXn97O2RcvZPbiql4xDuHFQDAoYTSk7q09XLrKWBXmIzqvBMxM0zvTMxmFXtxqHYZA8ls5KwyPw2BOeRqFEiEfjFurxxjI7MKivkDF2bv6zyEiyCOYvTI9ehGrO/rCzeCXqWkI8JtrvwlprmdRSD4PbdjA+tWrKbDFX5v20IYNnHfmmdhycmLaXxHlcdDZ1YPVonTpGki7w8Gzr79ORUkJ+44cAWsQnUHDmRcuYNqcst791DoBS6map49bIacQLDK6UBCTP0B5bg/N24OIqiD6XBUGm4ghV0RUh2OEgiiglvTMPT2HhbpK2pqcPHXf22h1aqbN6ZOKIQOiwJOHJC6viV6A+mxt/7jjhVXJzZMea8I8FsvAloCJ1VlY5JltJDtK3m5Sijwzgd2Qk/Q0ir4ogjw62XBXyGkSye0ZvmFUQAXa4PDXjUVH/fznjLFVb6QQnV/84x/MnjYtblEuSRK/+Mc/WDR7tiLKU0FtQ8uEzyePRp7Vys+/9jXe37OHdz78EFEls/rcOeTYoi9grlnZGWXrSU/poIzHKeFxSDiOBZBCoNYLGGwifpeE6mTQobA0l/krplB/pK2fKFdrVJRW5nNsfxPP6gZXRl9YJXNhldxPmEf+n0xxPhaEeTz+3UFZQJMlRZ7ZSjRBHhFfiYr1dqOVsu6xV+TXV3SOxSJFu9HCrLa6pIwVLd98YKHycIzF85cIflGNJpT5uhWDX8alFzEETgnzvukrAB6dgME//PehzSVT1hHiWOnYLDBXOIUsyxw4doxQKD7//JAkIcfZY0IR5XFwvKGFM5bNy/Q0sg6VSsV5Z5zBeWecQSAY5PZ7/pcHfruRVevnsGDFVAQx9tiHqBYwFagwFaiAcJpQwCvhag8R8snUb/WBDDqLSKG1iON7dw8aY8HKqWx/6zAzFgxtVzRQmENYnE8UYR6PIHeH1BiyqMgzGxlJOCVaCGg35DC35Vii00o74yUC3KkzkeMdfXHteDkfoyUWO0SnPr1uN0Mx40SAp5cbOP99D6UOaZAloky40FM/giiXAfcYLjBXOEVpYSH3PflkQs8tKypCHYdnvSLK48DZ1UNujnnkHScwGrWa5R+ZxbQ55bz46DYO7Khn9XnzKK/Oj6tRTb8x9SIanYytWkP+NA2yLOPvllG1mchRFVK7xYOoFjBYRQw2FUUlNuytXbSccJCbb0ZnCIv7ZKepxEI2CvN4O1w2BLK7yDOTjCS0+0ZE+wrzWCPoAZUKbZq7GybKeBKgsiAQS3xzPL3mTOMwZM4OsS8rDvipLVLj0oncKL3c77EbpU38WbsWlTS080oEnwY6ckbu4aGQ/Tz317+m7ViKKI8Rvz+ARq1KWFhOJK6ruQZq4EurQvz3xRd55Jnn2BzYy6pFi1CJIvscB5AlGVmWkeXwrSG1RsXi06eTV2iJOqbHEcKYH/6CEwSBgweOs++DWprr7cw/r4iSSXl4T6a9eBwqls05jf2vOGh3Hmbl+dMpnWrtFwkfGCWPkOxoOWSnMI+HRr+ZKTpnpqeRVcQa9R4o2ob7feCYYQeQEa78WUTf+Y9lseoXVWjivE2dKiZK6gqEO9dO68h83cqxYhUBNUxuiW6J2JUjYvKOfI3QBDPboVRhbKKI8hipb24b1N5dYXhUKhUfv+ACrj7/fPYfPcr2ffsQgOpJk3ivbRuCEBbYgijQ7XTz0B9eYdlZMzhtzcxBY3k6JfKmnnK9aWt0kpNrpGp6MZZcI6JKwJivOincNUxaVkLQJ7PlOT8tR9yE7HpkGf6+U8CQFy4k1RiFqIus8S7MR2oSNJDmgIlVSpEnEJ9IGq0wDUcOU1dsmEriyZnONsbyeR/LdOpM5CYhZSga8XiVA6hDoDp5CRhoiXi4VM3klpHT+RxmEVGG7FjeKYwVFFEeI7Unmpk+eVKmpzEmEQSBWVOnMmvq1N5tH+eCflaGAPNPm8J9v36ROUurMVn65yDKIRBVpwS0va2bBSumMn3u4CY4EdQ6gYamJlaszaVihj7cKdQt43FI2I8G8LtkBAF0OWLY7cWmQn0yB1AR5qdQijzDDCfIUyFA243WMe28MlaFedh5JTnnfTTnIJEoebziM5sIiSIqOXV3hmI9N6IEoQG5SxFB7tXAvgoNF77nGXYMrwaeW6pnyWEf78waOZ9eQSGCIspjpKm1g7OWL8z0NMYV19Vc00+Ym60GqmpKOLqviXmnTe7dHvBIqPWnBLmzo4eWEw4qpvZvEx8Nvy+AwRx2dhEEAa1JQGsSsU4Kv/VlScbXLeNxhGjd6yfokxFVoLeKPNKu4rJ5Alpt8lKWskmYx0I8RZ7iutNj2i/enPZsIBNpBO3GHBY2H0n7cZPJWEy/sBstzG1pj+s5w73OdJ+DgUWVY0GkS4AQp0tFIowkzGVg6wwdyw75Bz3m1go8sdLAtKYgRZ1DLx6CImxYZqC6NcS05hDvzErGzBUmCooojwFJlpFkGZVKsTZKNgOFudfjx2ju34XR45Aw5oXPfTAQ4vF/bGblutnoDSM3ZdAZtPg8gSEfF0QBvVVAbxWxVYe3SUEZb6fEZCHEy69K+P2g10FJsUhJiUhRgYhKlbhQzxZhHhHRw4nkxoCZMs3Qt5RjFeJjmVicVVJxjB6dAbN/+IicQvLp1hnJ8Y38+UxlJ8+xuJgZDd06I5YYznkyGE6Yn8hX4dEKTG/oH4jo0Qs8vtLA9MYgKw74h/VSf3W+Hr1f5ow9Ps48fi8PpKk9u8L4QBHlMdDW4aQoPzfT0xi3RIS5x+2nuc5O2ScL+j3usUvkVoXfqu3NnTjaunnvtf1sfmEXc5ZW85FLFw1ZgKszaPB5hxbl0RDV4fz0pVWnFmFer0xzi8TxWomt24JIEpjNAqXFIiXFIvl50fPTAWyd7kFdQCO/Z5M4h8ECvcFvZrJusK/8RBDjsZCq9IxIzFApK08/2dDAZqLh1JuxZYEd4tYaLcsO+QY577wxR8fU5iArDwyOoPfFbhY5Vqzixo0ubpI2cbguOV73CtmHLMs0tLTQ5nAgRynIXzxnTkLjKqI8BmpPNFNVXpLpaYxrrqu5hq/d9yOqZ5RgMPaPgPt6JLTm8GWypCKPS29YRWFpLhqtikf+8jrPPbwVURTw+4L4vQH8viAFJTl85NJF6PQadm89xpvP7WTh6mksXj09ofnp9QLVVSqqq05ZXHX3SDQ3S+zdH8TuCDvJ2HIFSopFSotFcnIE8rrCkc6+4ruvQM+WqHmEgbnmzQETq8yNg/ZJ5jGymXTkkUeNkmuVKHkm8KnUaDPcwGa8Rclj8Sh3GMwU9zgHfaZSdS6iRcsbbSJdRpEZJ/r//TssIg35KtZ/OHIa0K5qDfOOB/hcYNOI+yqMXfYcPsx3fv1rTjQ3D3pMlmUEQeCDxx9PaGxFlMdAbWMLF65ZkelpjHsO72lg/vIp/bbJsgwnXVoiRDp4SiEJQRDYv72OletnU1hiRaPToNWp2f7WIZ7+19tUTCvized2MXNhJe+/cZD8ohyqpienK6vFLGKZJjJ92qm5OpzhiPq2D4N0dcnoglCUC5MKwj/B0sFtl7NZmAdkEY0oJTUyPlYEOQzd9CdVKSsR2o05FLjGbpHnWMVusJAXQ3FtqjqWjjdBHisOvYWZ7fU0PhrfXc3RMFCYb63RsfSwv9d1JUKrVaSiPYQmBhsVSQCjTymKH+/89M9/xu3x8IVPfpJJJSWoVcnzo1dEeQx4vD6MBqWCOpV4vF4aj3dwyXWr+m33dcvoLNFz+V95ajtGsw6tXo3JrGf6vFPuOCWTbDz1r7epPdgCQEuDg9PPm8fWV/fHLMojXubRXFiiubMIgkCeTSDPJjL7pKujJMkEaj2caIfn9qlxbfMhilBUGE57KSkSMRiErBTmbh8Y3wPx9IkpyCMkO0UlFuHVYbRS5WxJ6nEVRibsvJJ6O8RoriwTVZADeDVa9MH0CfKBtFhFOnJELnpv8BwCagF1KDahbfTJuPRK8tN4p66xke/feivnJvHaGEER5SPQ4/ZgMhgyPY1xj8/vR6UW0er6vyU99hBG22BR3t7cyaHdDVxz21oe+H8bqarpL7RFlchF16zg+f9sRW/Ucvp5c5kyq5TXN+ygud5OSUVezHMbTaMhURQoyQPdZCMRQ8hgUKatI5z6sv9gEK8X1GooKtRQYw5Qlg/6kWtYU05jB5TFfppGZCwK8mQTq/CyGywsbDqc4tkoDMRutFDZmbzFUCydW1MtxjNpkxhL6kqmkYF3ZupYctgftUtnbo/EwbLYpJIgQ0hURPl4Z8706fj8w9cXJIoiykegtqGFqvLkpDsoDI3JaEStFnni3s2YLHrKqwuYsaACj0OiaNZghfruK/tZfEYNrQ1Oistt5OabB+2j0aq55LpVHN7TyMbH36d6ejELVkxlxztH4hLlwxGLMB9Y5KlWC5QWqygtPnXLyx+QaW2TONKiYds7AXwB0GmgPB/KC8LiWKsZOHJqaeiA6iS99RVBHp/4Coki6hR6NitEJ5zLnx4BO94j47EKcq9Kgy5DUfJ1l+n5zQchug0Cc2ujz6HYGaLNqsKnBt0I5QZ1hSqWHE6NWFPIHq656CL++sgjnHfGGWg1yb0wK6J8BOoaWlg6b0ampzHu0ajVPP+nv/OzDb/F5/Gz671j1B1pZU7V/H4e5QBet5+j+xtZd8ViDu06gdEy/Jf/tDllvPDIVkKSzLEDTVE7ho6GZDQa0moEJpWpmFSmwjYlfHHw+sPR6rpWeGc/BIJg0IWF+qQCKLGBJoWf4CY7rEyCx64iyOMTYH5RnTVt3ici4zHOmc1NhZwGc0Y6qLbK8A9Zxa7pKi7e6kEtgUsncLxIRZdRpNMULvzUBGWqWoO8P03Lqv1DC26XTqA1V8WkDuWzO95xeTy4vV4+/7//y9TKykGPC4LAdz73uYTGVkT5CLTZOynIs2Z6GhMCi8nEnVd/h/sPPsicpdX8+3evUJnrAvqL7qP7mpg0uZC3X9rD3vePc+aFC4YdN+APEgpKyJKEva2bKbPKkj73ZHYAjeSX67UwpTT8E8HtCwv1I02weQ8EQ2DSn4qol9hAnaSak0AQtKP4hlDEeGJ0GC1J6yipEDsetRZ9cOQo51jsUppu4klbcejN5KbRDtEvw2OIPCOLXCxILHjNTUuuiueW6KktUlPdGsTWI1HZFsTqkvlwigZJhENlGgSZqLaIXQaBp5cbWHrIH1NBqMLY5n/uvhuAY8AHe/cOelwR5SkiGAyhEsUh/acVUkPEt3zthct5f+NRJq8292sodGRvI+YcA7v2dJJ71pXsDJmYx2Av7QjdnR7MOQa6HG6sNhNiinL+kinMh8Kog2ll4Z8ILm841eRQA7yxC0ISmPVhkT6pIOz+Eq9Q9/gght5MUVHEeH/iTVPoMFopcA/9flZIDWHnleRFbGPJJ1cAp8HCrNbatBwrJMOdsooA8FkhRDsCD51pRJRh3vEAa3d4B6Wo5HWHePBsE4uP+NlbqRkkyg+VqnllfrgL6KKjmStWVUgf2594ImVjK6J8GBpb2ikvKRh5R4Wkc13NNVy38WFyyxvZ9sYBzrxgfu9jnQ4XPV0ejFPmojKYRhwr4A8SDIZoON5ObsHg3PNsJB43FpMeasrDPxG6PdDQDvvq4bWdhJsdGcJCvTwfim0wXIPaxg4oUwKCoyYRQdZuzGGKvSkFs1EYDrtBuUORDOIt7uyMsYNqMngckfcR0SDjlUVqkFm7w0eZPTRk2pIhAGt3eHlpkR6/RujXXMqvgtfm6bj0XQ8lznANyI2S4lGukDiKKB+G40qRZ0YxBALMO6OSB3+/kSVn1GCy6AkGQrh7fHjdfm75TB7//SC874NbrFyzMnp0sbjcxvS55byzcS/nfGxZSuec7DSWvsRjmWgxwMyK8E+Ebnc4oh6LUG/ogKqiZLyKiUuiEVKPRocx6EvybBRGwm7MYWoKFkNDed0rhJEFAZH0eHuvQmKBIDMZGc1JZb3RPnK+yeTWsGiXBejRC1i84flKIkiigMEf/l0R5BOLg8ePs233buqbmphUUsLSuXOZMXnyqMZURPkwNDS3sXLR7ExPY8IiyjLPHipjyRk1/OdPr7L8I7N4Z9Ne9AYNZZV5aHVqrlnZyYNbwjn/QwnzB7dYoehsrOfKbO0W2LqFIQV8MuhroZjMdJaISE/Uz9xihJnGEYS6HE59aeyAquJwzvpIqS+RdJVkNhga6yQqwiTGZ6HhWMCt0WGIczGkiO3RERIExDS6DJULwCgWAPldEm1WEYs3LOR1AZjcHOSdGToefv/Z5ExSYUzw63vv5d8bNhCSJFSiSEiSEAWBay6+mK/eeGPC4yqifAhkWSYQDKJJpb2FwpB097gJiuGw7Yq1s9AbNOx45wi2AgvNJxysvXxx1Of1FeYRsR4hUhsgyxL3v2nkujNSf8t0oMd5MkT6wAh6LAwl5KMKdQ88sAkON8Jbe8IRdZO+f0Q9mlAfKM4nam75aIRal95Ejtc1quMrkdn4iXwqk7UgGlgMmum/SbY6r3TpTFi92dM0bSRKHSGa8lRMaQkhA88u02M3i9z+3dszPTWFNPLkxo08+Mwz3Hz11Vy+fj2FeXm0Oxw8/tJL/OU//2FqZSWXrl2b0NiK4hwCe2c3edacTE9jwlLf1MotZy/je9sPhcW1sIRrvjiNp/71NgtWTKG8Onquf98IeN8ouhwK4W9rxNt4HF9TLVIwwH3vmSipyKe0Mo/Syjzyi60pKwKNkI5i0GjEk6OuUUGBFdYuPLWtxxOOqB9sgDd2n3J9KcuHUp+ZEo0b3Tn9u7GK606fsMI8UdpHWeQZEYOZFoFjDbdGhzEQf8rQWDjP6RTk8eaTOwxmbN702yEmSmVriDfm6lh6yM++Cg09epFrXnNzyaaPZHpqCmnkvy++yHWXXsrnrr66d1uBzcbnrr4at9fLIy+8oIjyZFPX0ELVJCWfPFPUN7WycPZ0Xpg/g/Pu2wCEI9+h8tM58eYTzFlazbMHy/s9Z2BKit8XZJlpD4d2n+DAnhbUFhu3XXoBH1nxVW567l3WV9XRVNdBw/F2tr1xEFeXh6JyW1ikV+RRUpmPxTrxurlG6+RpNsCMSeGfCD3e8L7HKhayxQHBTaDXhZ9bng+leRPvC2a0Aq3dmENNR0PG5zHRsBtyyHePXOQ5kh1ittklZrMgB3DqzZR3tadgNrERz/kR5HCkfHJLkHvXmRFkmas3u1GlP8aikGGOnzjBrZ/4RNTHls2bx6Mvvpjw2BPtmhkzx080s3b1kkxPY8LS2uGk8KQ//As3XNQrzFVGC+rJC3jgn7vJXVnWm5ISEeQet5+jexs5tLuB+iOtlFblM31uOWdfvJBblny6d/wXb7yE+w8+SPEkGwtPbvO6/TTX22mqs7PrvWO89Nj7qDWqkwI9jykzSykoGb1nfbZHyxs6oKJw5PHMUVxfPD5otENtK7xzAALtM9EKIUq1Lso0PZRqXejF8Wnkmwwh7NSbyfUk5tmcbYJwLGE3Wih09V/UxxoFj/W8j4WoerpxGCzMaT2e6WnEhHzyJurZu3wsPeRHH5AVT/IJSnlxMfuOHGH14sFptPuOHKGsKHGXBEWUD0G3y0OOOf7cXYXRI8lhwSqKpzz7+gpz07S5dNQdouPVJ08+IcTf3wgSCkn4PH4qpxdTM28S5121DL0xbLZ9Xc01g44T8UOPoDdqqZ5RQvWMEiBcV9Bpd9FUZ6eproP//vV1Zi2qYsW6WdQebMHV42X+8imok9WtJ0totMNpCTaxNehgamn4B0DauB+fpKIpYKLRb+Z9VzE+WYVakCjVuCjTuijV9GBSjdC/eoIwlBPFSJ7XfYWhIvzix26wMKO9ftD2ZC50xuvfJZEIeQS/So0ulP2f/XaLiCCD3i8jQK/7isLE5Pwzz+QvDz9McUEBF551FqIoIssyz772Gvc8+ig390lriRdFlEfB6/Oj12kyPY0JS3uHk8K83EHbX7jhot7/Oz66hvqmJjRqde+PWq0mLzcXg0436LmJIAgCuflmcvPNzFpUyYq1s3l9ww7+/KNnyCvOoa3RyZzF1QmJ8kxEy2PNKQ8EIFlvf3Hd6eg2bqZa10W17lR6gF8SaQkYaQyY2eUuwCVpUCNRpHH3RtVzVH4mUt8ur0qDLniq+Ug8EdhUMVEa4HjVWvRBpfFLrIxGiEfo6/edCeJJXdlVrWFubSBqqopigzjxuP7SS9l54AA/+O1v+cmf/kSBzUaHw4E/GOSsZcu44bLLEh5bEeVRqGtspbJMySfPFHVNrVSUDn/7x5aTgy0nvYW4RrOO8z9+GqefN5cDO0/QmG9CZ0hcvUacWdIhzmMV5F4/aJO8Ho1W8KkVJSp0PVToTqVqBGWB1oCRRr+Z172T6A5pEYACtYdSbQ9lWhd5Ku+4FertJmtvXvNQQnukFIhkiueJkg4T7dM3Xl57X/Ecjwgd6nnJEOMRPGothgSKa5NBPOfCr4ID5RqufW2wK5IiyCcmKpWKu7/zHV5991227tpFQ3MzZy5dymnz57Nm+fJRja2I8ijUnmhmzozRGcArJE59YytrVy/hvPs29IuOZwt+f5Ctr+7jqpvPTsp4qY6ax+Nr3mgPF2lmArUgU6YNp7REkGRoDxpo8pvZ2lOCI6hHQsCm8vamvhRq3KjGgVDvMOZQ4OqMSxCmI21lvEfJe7QGzD5PSo+RDecwIqhHEqQDhXcyhXhfnAZLwvUToyHe4td9FRoq2oOYB6SsKIJcYc3y5aMW4QNRRHkUmtvtrF0d3QdbIfV0uzxc9dgrAFknzI/ua+KFR7Zy1oULklL0mW00tMdW5JkuRAGKNB6KNB4W0AaALIMzpKPRb2a3p4C2LgMSAiYx0Jv6UqJxoxHT15QkGaLLPauIubYeYPjqsb7R8sZHO1JSQDheIsWxYDdYyPeM7LwyXlh3mT6qME2V+B4Khz777RAdJoGtNVoufK//ok0R5BOLUCiEIAj96txShSLKBxCSJATSc/IVBhMIBHmrvgVybb3bUinMBxZ7joTRrEMQBCRZJhSSUKmS8z7JlCPLQJpGUeQ5FMn2KhcEsKl92NQ+5nBKjPaENDT5TRz15fJ2TxlBWUR7sqC0VNtDqcaFMUsLSsuuzMfbrsKQgDNNKqOw2RDhTTUdxhzKuk+9zmQvSLLxHPYV5ukW4xEcBjMVna1pP+5Qi5KBdOsFnlhpZNU+H2WOUwt8RZBPPD7xta9h0Ou57+c/B2DFVVcxXB6lIAhsefjhhI6liPIBtLTZKSnMG3lHhZTw8X8+hVEzOKk5W4R5SUUeq9bP4aX/bsPd42P5mplJm0cqun/Gk7oC4A8mr8gz3ZhVAaYbnEw3OHu3RZxfmvwmdrgL8UhqVMgU9haUurCqfBnNUy+7Mp+QPNh1JVPNlyZSlBzCtnxzx4gtXzLJlBiP0KMzYvGnNm0oUTwaeHKlgQXH/MypP7WQVwT5xGReTQ1arbb393NOP73XjjnZKKJ8ALUNLVSWK0We6SJicxihMBDAHUWUR/bNpDBvbXSy+flddLR2cd7Vy5i1qColc4mQ7ui5LwDacfaNoBNDg5xfIgWlzQETm7vL6QyFv2zz1N6TUXUXBer05KlHBHBbwECh5pRAEded3vtvuoV5NkZ2k0W0HHy/So32pC3fRIiSZwvR3FcGnv9MnD+HSeDZZQYmNwdZcuSUI48iyCcu37/11n6//+i221J2rHF2CR49dY2tLJozPdPTmLAYAgE6DNnnD7/z3aO89eJulq+dxSU3rBoz3uSxNgyCk508kxwkzUSkdyT6FpQuNoVvn0syOEJ6mvwmdroLaA8YkQCjGKT0ZNOjEo0LXRLz1PsKkOaAiVJNuMA1IsiHQhF6yaHsynwkGQwdWsoWJP/ugPJ3GpqgIKKSRk7VirVeQpahDfABhpM/eoi6sB4udeVwqZpX5utYccDPvOOKIFeIzoZXX2X1kiVRHeCOnTjB+3v2cOW55yY0tiLKB+DzB9DrtCPvqJASRFlGyrJ8/obj7Wx5eQ8f//wabIWWTE8nbuLp5Jkp55VMIwqQr/aSr/Yyt0+euiukpilgps6Xw9aeUvyyiFqQKNG4KTmZq24R4/e3HhgRbAqYOM3cPOrXoRAfjpAemzr5regVQT48nXoTud7BFoPR6CvMAzIcQ8AJeIFaWeAwAocQ0BAW456Tj3mBUhnmIDNHkJiDzECjXUmAt2bpMPokevQiR0rVXPKuhxKnkkOuMDQ/+N3vuPfOO6OK8paODv7x2GOKKE8GXd0upYtnBlGHQgSzTJADhIISufnmjAjydKawNHbAspq0HGrMYFIFmaZyMk3v7N0WONn4qClg4kBXRdhP/WzQHnFQ4O4k392FzdMzbGfOgTiCemwq76AoeTbeaRhPtASMFGviq7sYCUWQj4zDYMEWhx1i2ZX53P1fB4/KIiVAATI6YBIyFwgS05DJHxAVD8lQB+xGZKssci8CQbfMsmoN809GwesLVBwuVVNuD4EMn3jdhaHPGlsR5ArRkGU5ak65JEm8uW0bHm/iC31FlPehtqGFKiWfPK30zRHfd7iWHpeHZQvCxZMD880j29JpkdjlcPPh24fR6vvnuT+4JWyHeM3KzrTNZTTEEi33J7GT53hGI0pM0vUwqU/jI0mG/Vu8tJtyOJxfjkNvRhYEdMEABe5OZp4GJRoX0ewOZRkkBNTrRxbkiuBLLq0BY78Fl0J6cOjNVDsH3xmKvL8HLl4dPoknZZE/CEGKBKh4/NmYjlMNTL7iQi4Wwp+zh7f6eWKlgSJniBKnxIFJGhYe9bPoWEAR4ArDcuHNN/ergfjaXXehG1D/5ujqwuPzcdHZZyd8HEWU9+F4QzOrl8zN9DQmLPWNrcyfNbX39xduuCijwvzQ7gae/tfbzDttMrOXRC/qfHCLNeXCPFmdPx3W8F2gaOLcF4Ah6mtHRSTyO94jvqIAsy/WA34aH93fKyrcITVNARMNfhPbeorxymrUSGH3l5NFpSISOar+nQ0VQZ4eWgNGVpkbkzae8jeKDafBTG7z0OkrA/33n5VFliLEJcgjVDz+LPVXXIggwCc+ouXo3gCHyzQYfX6OFqtZvdenCHKFEbli/Xq6XS46e3po3LSJ8uJirGZzv30Mej1zpk/nYwmmroAiyvvh6OzGZh17OcPjhZYOB0X5uf22jUaYHzp+nByLheL8xBKlJ00uoKwqny6nm/ziU42CIlHyvr+nI2KerFSWaFHzxg4oS6ETaKbs/TJB3yifURVkqqqTqfpT74+gLNB2Mv1lS3cZ9X4zAbOVp9+B0jwoPvwhxWqxX/MjReylhoAsok1S8a7yN4qdkKhCM0KhZ9/z2STDZEGOW5BHiAhzgBJHiOeWGthdqWHpYT9f9GxMaEyFicWnr7yy9/9PbtzI7TfcwIKZybNEjqCI8pMEAkE0anXKvCcVhkeSw2IzWtOmvsI85HUjedygUrHuDw8CAiFXF8FuJ5Lfi6jVI6g1BDqa8bU2gCxhW3Uem778qbjnZDDpuPqWs3nj+V08+NuNXHzdSorLbVyzsnPMC/OBNHRAeUHSh+3HRBLmw6EWZEq14Sg5Jni9axKTVcewzVtIwyt7OBzI5e1AuPmRWpAo1rjRWlUUuLswBryDbOQSJRWdQMcSIZmoef/xMpHPYSIkcsZbEVj1tW+O6rgRYf7p1RqKnu1BG4TPhJQIuUL8bH/iiZSNrYjyk9Q3tzGpJIv6i08wOuydFNiGblv/wg0XceaPfk33rndQGS3IUgikEMgyKlMOaksuok5PyNWFFAygNlkoWHcl/tYGHG+/wEeCAV752meHHP+8+zZwzcrB20WVyNkXLaC43MZj97xJySQbl9ywKqO55MkQ5gNTWRo7YGkanEAVYT6YloCRleZGtFs2M9MAMw2O3sf8J4tK92sN1OYW49KGG75YfG4K3F3ku7vI83SjkuOP9k40MTkwT9keNJA/SueViXYOk4FLq8fki69pUBtQVjTQOyV+IpH2W0fYT0EhVjqcTgKBwQ5cJYWJ6UlFlJ+krqGFKZVlmZ7GhKWuqZWK0uG/dEPdTkzT52OesTDmcfXlkxHUapxbX2HRlS+RazSg0WjQqtVoNBo0ajXHOl0givxuswpBVFFRKKFSiajU4sl/VahUIrMXV7LjnaNZcTclmaksAP6AG32anEAVYd6f4VIotKJEha4HVdsp8ScD3VoD7SYrx23FbC+dRkgUUUsh8k8K9WRH1ccjo3VeUQR5Yjj0Fmze2J1XANoQKClI8a08haxg2+7dfOZ734v6WFlREc/99a+Dtr++dStfvvPOQdv/+MMfsmrRoqTP0eXx8H/33MMLb75JIBiMus8Hjz+e0NiKKD9JQ3M7py+bl+lpjAsSKcQ80dTK2SuG//CIWj2hOCMsALriCgrP+wRyKIgshZBDIbyShFcKIUshLJIEJ/8vSxLtofC/SCFOm+QiGAohBSVCIYl1VyxGpcoO28ZkCXN/QEY2qojmDJIqJkoB6EgEJBGNEF+UWwBy/B5y/B6mOE45WPhFFXZDDh3GHI7bSnBrdABYfB7y3Z0UuLuwebpRJxBVH4+0BIzMNtgTeq4iyBPHYTCT5+mOeX+fDG4gPzc3ZXNSyB5mTpnCvT/7Wb9tgUCAr//f/3HZ2rVRn9PlcqHXavnTHXf02z61oiIlc/zFPffw4ptvcsbSpZxobqasqIhFs2bR7nDw1KZN3P2d7yQ8tiLKCXtOhiQJtWpsdGkcC8QrzDu73VgtpuF3UqmQA/6E5iOIIoIYfyh4lwzXrM5e28NkCPPWNomiQhGHVRdz989kMdGj5i1BI0UjRGtjFYBaKUSJy0GJyxG+38+pqHqHMYfa3FNRdZUUIs/T3ZsCY/Z7JlxUvT1ooCDJHuUKI+PUm5lqj93xpgkoInq9kcL4w2w0smjWrH7b7n38cfJzc7nxiiuiPqezu5sCm23Q81LFWx98wJeuu45rLr6YPz/8MG6vl+suvRSAVrud3YcPs2j27ITGVt7lQLu9k8K8ofOZFRIjmmtKNALBIOoRos+yLOOpO4SuJDUr3+F4cIt1UGFnNhGxTEyUlhaJkqLw+Y+ks6STkdrKj2ea/KaT/uWpIRJVn+xsYWnjQc458j7nH3qPNcd2UNnZhluj48OSqbwwfRnPT1/GG1Xz2FNYRbPZhl8c30GKkCyiEdLTmEvhFC6tHmPAN/KOJ9mLyMwkFOQqjE3aHQ7+9sgjfPMzn0EzhG9vV08PeWm8kyLJMlVl4XTnyZMmsefQod7H1q9axfNvvJHw2EqknLA/udI0KDXEEjFvaumgrHj4fMEtH34IoSC60uh+4ekgXQ4riTCaiHlLq8Tc2ae+CobzM1dILs0BEzV6x5CPpypNQiOFKHI5KXI5e7fJgFujp92YQ6Mln91FkwmoVIiyTK6nh3xPJ/nubqzenjEfzQnKAipFkGeMeMIIe2SBhXGmeCmMHx5/6SVKCgpYuXDhkPt09fTQZrdz+Re/SENLC1MqKvjCJz/JGUuXpmRO06uqOHj8OKcvWcKyefP4/v/7fxytr2dKRQX2zk5qGxoSHlsR5YQ7eZ5/1vJMT2PcMjBiPlCk1zW1UlE2dJGnx+vlS7+8G8u85RkvshyPwtznB51u8HlNpzifqGks3SEtOarEUrKSjQCYAl5MnV6qOlt7t4cEAafeTIcxh/2FFXTqTMiCgDYYIN/TRb67m3x3F8Zg7NHPTBBpSAPQHjCQr46/PmU8s/FJL+su06f0GH5RjSYUvTAuGiEZdiFwnRIpTzniysWIZenr0yI2dsOLbw67jyRJPLFxI9dcfPGw+02pqKCuqYmrzj8fURC478kn+cqdd/LAL37BrKlTh31uIqxbtYp/Pv44n7r8cvKsVs5atozP/eAHLJgxg7e2b2d+TU3CYyuiHHB7fJiMqf0ymkgM1fBnKBqa21g2b8aQj6/97o/R5BWhz2CUvC/jSZj7A/KInTyjNRtKBRNNmJ+05me4dWY2eImrZJl8Tzf5nm7oOBUB8qnUdBhz6DDkcCSvFE+fwtI8zym7xpGaxGSC1qCR4gTThjL99xjLOPUmcuNwXtmHgA1Y9kRiTYMUxjY7Dhygqa2NNcuHD5pedf75XHX++b2/L507lwtvuYV/b9jAj7/85aTP69K1aynKy+utc/jhF7/Id+++m3d37mTmlCl8/9bETTcnvCh3ebwY9bpMT2PcMZQwj5bK4vMH0emiF2Gu/9NDeOoOU3jOx5I+x9EwXoR5W5tEYcHIyQiKME8+zpCOXFV2R5eHQxcKUtZtp6z7lINJ38LSE9ZCdpZMISiqEGXpZApM18kUGFdSGvfESyRa3hIwssDYltDzFRLHYbBg88QuyjfLAhdee10KZ6SQzezYvx+rxUJ5cXzpxUaDgQUzZnB8FGkkw6FRqzlz2bLe381GI//vu99NytgTXpTXNbRQqeSTp4SBwjyaIHe5vRgN0RdF5923AXftQQwVUxG12XcnI9uFOTCiOG9ulSgpji1DWMk1Ty5NflO4q+c4oq9d42RnS+/2IVNgQkFsnu5ef3VTmrzVOwLxNw4a74J88ywtr0kqPiOEqE7RH8FpMDO9IzahFJDhndx8bl69OjWTUch6duzfz6wpUxJ6rj8QwGxMv3HBaJnwory2oYXFc9LQynCCMlKRZ/0wTYNkWcJTexDbynNSMbWkkM3CHEaOmre2SsyZGd/XQKqj5hMlWt4UMMXkk50NKSyjZagUGL9Kjd1gocOQ069jqTHgC6e/uLvI93ShiyMPORYk4iv0HOvnfyTaZHh/uo5rhRDfk9VMlmVmCzJzCf8kq5SnU2fC6o1tIbrvK99k2qZNVJaWJufgCmOO+qYm5kXJz3Z5PBh0OkRRpMft5u3t2zmnz+Kt3eHgw337RsxFj5W/P/ooGrWa6y+7DIA7//KXYfcXBIHvfO5zCR1rwovy1g4nBfm5mZ7GhKW+qZU5NZOjPhZwtCOqtWis+VEfzxYidonZKs6Hi5p7faDXx3/FVYT56GkLGCnMOZHpaWQUbShISY+Dkp5TDjRhFxgddkMOreZc9hdW4lNrEACL10W+p5s8dxc2b09C+eoBSUQdh5vHeBfkAIUCnCNLnJAF/iIE2YPAXlngL6jQI/MZJGYmwa1GEkVUMTavevjZZ7npox8d9TEVxi4dnZ3k5uT03+Z0cuHNN7N60SJ+9e1vs/vQIb73m9/w2tatnL54MYIg8LdHHsFkNPZ6h4+Wx156CYNe3yvK//vCC8Pur4jyBAmGQqhEATEL2qZPVFraHHxk1eKoj8nBAKIu+9JWhmKsRc0DARn1KL4BFGE+OiQE1DEKnfEQLY+VsAuMD1OgjYquU3nfMtClM2I35FCXW8QOw9ST+eoyud4e8k4WluZ6e1DJ0c9r2ZX5NPgNFCrOK4P4rBDia7KaLQisE2ROE2SulyVeQ+BnsorPE2LFKIS5BKeqm0eg+SwrHXucnJkiSzuF7CcUCtHZ3Y3V0t8RRqvRUJiXR0lhIQArFizgH3feycPPPsufHnqIbpeLZfPm8fWbbiLHbE7KXP79y1/2c37b/sQTSRk3GhNalMfijz2RicVBJZ6unQORZRlJllEN1alNlmCMdXEbS1HzSCfP0ZAOYQ6MO3HulVRohfiivBNJmEdDAKw+N1afm8nO5t7tIUGgU2+mw2DhcF45ToMJSYh0Le0hz9NFnrubmReFF/itAVPMzisT6XzrBfgmQf5HVlNDkEoBRAE+gowTiR2yMCpR3q0zYvGN/F0RkuGX273c9unPo1K6bE9YVCoVHzz++KDtFpOJZ/70p37b5k6fzk++8pWUzWVgtD6VTGhRrjQNGppYLQ1jaQ40FB3OLgpsQ7/ZZUlCGGOiPMJYEOeljlOdPEdDOpxZxlvUvCVgpERp8Z4UVLJMnqebPE83cKp9e0BU9RaX7i2qYkeHDRloCxio0TtQCTJFGje5Kl/UnOnxKMhH8iKvEuBThLhLVvMrgkQy2zo3+ziyenR3LR16M7YY7BA3ICI6g5x7+sTt9KswcZnQovxEUxvLF87O9DSyjng8xiP7JyLM6xuHLvIEQJIgS1p9R8R1RGzHSjantGw7KnP9zOQsetIlzGF8RM2b/CZKtLFbwynEj0YKUejupNDdebJpUNgN5oG2Wcw2tNMWNHHEm4szFHZ/0otBijRuitVu5JcbMBFf58lsZ+OT3t5/hxPm65DZicxfZRW3CSE2PumlSA0bAgI/16i4TEgsv9xpMFPc4xx2n8dlkQ2yyE+EYMYbxSkoRFh0+eVxvx+jRfljYcKKclmW8QeCaDUT9hREJV5B3vd58Qrz+qZWzjxtwZCPy5KEIGRXpDwRcZ6twjwUkNnUIibUBTQa6bJMHA/ivClgZp6xPdPTmBBEunhGEASZKn0PVfRfFB19ogu7wcIxowV76XTcJ51gdEE/ee7u3mi8MU22jckiIsajbYsmzgUBPk+I22U1G+XwK9UF4dpXXejPNfBzWcUcWeZ6IURxHCfCobcws71+0HavDNsQeF0WaUDgLiFI4Vg6wQrjnqvPP7+fKO92u3n+9dc5/8wz+6VYtdnt7DxwgK/fdFPCx5qwitTR1UOeNX0tZRUG4+xyYbWYht5BCmVtTnm84jzbhLkUkntvQsTbBXQk0tloCMamOPdIakyq5Nr8KYyMT1KhjeK80vhoB3qgrMdOWU9/m0qPWovdYMFhsHDMVtJr26gP+HuFep6nC2PAl3ViPZogH/h4NGFuFOA7BLlDVlM5W8fpe31YvDLrBIk1SDyByO2ymnNliY8JEsYYXrhXo0UfDPT+vkMWeF4W2Y5ADTIXLjFy3lf/jsU0zDVBQSEDfHuAk8ov/v53PnruufzPzTcP2vcLP/oRXl/iTeGyU/GkgbqGFiWfPInEGyUPBkOoVeKwt4S+fsYiQu4eZCl2+7J0Mxqh/eAWa9zpMMnC2ymhs576+EcKQJNFJGqeDiLifKwgyYmnRQyM+ioMz8Dz1RowxFzkGcEQ9FPe3cHc1uOcWbuL8w+9x/mH3mPFiX0UuDtxGsxsK5/BC9OX8fz0ZbxavYAdxVOozynEpdGltW/pxie9/X5ifU40qgX4f0KQZpvI1ppTHZf1AnzziWf4nRDEgcAtsprnZZFQjC80JMMDkshvZBWLBImnL7Xw96ty+dj3H1YEucKY4NV33+WMJUuiPnbZunU8tWlTwmNP2Ej58RPNrFmxMNPTGBckkk/e1NpBadHwAmP9qlW8uHkz723dRO6yjyBksBJ/uEj3UFHzgftnSoBHw+uUMOSm9nymK2IOYytq3hE0kKdY8qWcaAuYloCJogEFtokWdEbEenl3/+dHIut2Y07/yHrwZGTd3Y3N05307qWxivChnhstYp4jwPcLZL5m0rD0kB+AisefBWDhE8/SfvlFNMkif5RVfIDAd4dwFPKqNOiCAbpk+JWsIgD8Wggy52Phv5Hqk/9KeO4KCunG5/fT5nBEfSwQCNDQ2prw2BNWlHf1uLDmJMfDciIzkiAfKke9wNWDV63hroMNQ46h1+m4+9vf5ju//jVvvPMStuXrEUZjrD1KRkpBuWZlZ1YJ7+HwOCVyyvufy2SnsUB6hTmMDXHeFDBRqo0vWtuXiW6NGAtD3VFoDRiZqnf2/p6K8zicWHcYLOG89T5iXRcMYDuZBmPzdGPxe+IW66MR5H3HiCbM9z/lJW+VAcMlBioeP/V97vP7+Z7WxJV+N58jQPkwY9v1ZhyeHr4iqzkDiesFiQpFkCuMUZbOncufHnqIRbNmMXnSpN7tdqeTvz/2GDMmR2+IGAsTUpT7fH50Wk2mp5GVjMZ3fCDDFY0aAwHsBmPvfkMdV6PRsKtoFuKJNuxvv4Bt5TmIGm3UfdNBtuWGJ0rIL6PWDb70D9f9M1HSLcwhu8V5s9/EIlPikRSFkWl8tCOqMHeGdFhVvowsagxBP4buDsoGiHWvStMr1uusRfToDABoQkFsnp5esZ7jc8Wdb9pqFWm1qpjcEsTkG/kzPZS4X3bQz+8teo784Q+sXryYs087DUmSMPq8FAsyU4dZReyQBR7T5xByu7jzxz9h2bx5cb4KBYXs4huf/jQf/+pX+dhXvsLiWbMoLSqiw+lk2+7dSJLEj267LeGxJ6Qor2sawYpPYdT0FeTBni6Cne3IsnzS5lBEMOQg9SniHEqYn3ffBgRRxLrkLLo+fAvHW89jW3UeolaXltcRjaE8yEeKkkeLpGdC4EshGSHNmUDpcmYZSDb6m3cEDeSPMn1FiZbHT+OjHXim+2l+LbvOmz4UoLTHTumAAlO/So1Db8ZusLC3qIounRFZEFBJIWyeHmzebvI8Pbz/SMeQkfWd1RpaclVsnq0j1yUxuSXIlOYgBV1SXNH4yvYQV77lofbgM9x3ZR3/3rCBb+39kB8J8ANZzQ5ZZqkgkQvkIGMGjiDwjCzSalaxxmDi+p/fSWF+bkLnSEEhmyiw2Xj8d7/jTw89xLbdu9l58CCFNhtnLVvGZ6+6immVlQmPPSFFeW1DC7OmVmV6GuOWgRFyT+0BPHWH0OYXgyCikmVcxhw69ryDvqwaXWk1apNlkDCPjBPs6cRbfwRBpUby+7Bvfhbb6vNRnYwopYNoeeNjJVVlIN5OCX3O8DG3VKSyQOai5tkkzCXCnRIVUkvfaHnjox29ec1jBW0oSLHLSbHL2W97UBBxGMw4DBYO5ZfT9LFpyCoBISSjsfega+1C29qFtq0Lq0um1QrXv+KiPUfkWLGaZ04zUNAlsWanF4s39s94Xo9EXo+E/IttPLdUz1PlIh8XJH5DkNcQeUUW6Qa6EOgGypE5W5C54Vwzj1nOJW+YRnEKCmONHLOZb332s0kfd0KK8qbWDtasXJTpaYwbRvI2N1TPxH1sPzmLzkDUaLH4vEiBAOaCYryNx3Ad2IFoMKEvq2bt/2sHQUAO+Al2d+KpO0TI1Yl+0lREvREEgWCnHfsbG8g9bS0aa16aXmVyyIbUl3CR58g3whVhnnxcITVGUbFCTBd97ybYDZaTXT/HNmpZotDdRaG7C4DukyknsijgzzfjL8rBVVOC4/QainVqvEUq7Lld5DR2sayti5Vvd7F9Ejx0lpHlB/zMPx6IK2ouAKv2+fhvvpHL9GAT4HIkLh9iEP119yM98RKqLLW3VVDIJiacKJdO2uspXxDJISLIQx4XolaHoBr8llKbLOhKKunavhnrsrMxBgJ06fTozBXoSiqQJYmAvQVv43Gc215DEAQEjRaVwYSpZj664gqEk38v4+RZ2N/cgBwIYN/8HMYpszDXLEy5M8twUfFoaSzZIL6HIlzkGVtefiqFOaQ3nSUbhHlzwERpnJZ8Q9E3CqwwMnajhTxPV6ankTIESUbX1o2urRtoQAaeXarH+r5McaMKX1EO8//zXTbf9SCTjFqK1AKNk4O82tPD7J128ms7UXe6YxLoNpdMeUeI33WE+MaC/t+9EXeWCKGQpFxvFcYd7+/Zw3Ovv05zezuBwOA7cH/98Y8TGnfCifKWdgfFBWMrupoteHw+Oru6KCksBPpHyNteeAgAja0ITX4R2rxidCUVvSLdumg1ji0v0fnBm1RPmUeL6ZTzjSCKaAtK0RaUjjgHUaPFtuo87G8+i6jR4tq/HW/9ESzzV6DJsSHqTb0CPlNksyCHoYs8hyJVwhwy584CmSkCbQqYmKTtGXnHOFDEeWw59nZDDtWOljTNKPO8P01Lj0HkvA/cqCX4nP0ZAM54bD73imuRgUkmHfvm23hvsY3KBWUYNXq0AdD6gidTYLrRtnWh7ehBCPXvF5HjlvFqhX7FoTdKg/2Z7c4u8pXUFYVxxJObNnHH73+PShTRajSYTSasZjMujweXx8P6VasSHnvCifLahhaqlaZBQxItFUWWJTy1h+jZ9z5yKISg1qArqcA8YyEqQ7jZgwYjU1hN0OHD5eigh510Gd7BPGMhhqoaBJWa3BXrcbz9IqHODuRcW8IevSq9kYK1H8XXVIv72D78bY04t7wUflAQEfVGVEZz74+xegYqo9K9FRIv8ky1MIfMFIFCesV5s9/EUlNqhOFEFeexNlRyafWYAqO3DhwLdOsFtk3Tcs1rLtTSYLF8o7SJe8W1aFw+5m9pZvL2Ft6epaNHL9BpErnyXT9aSzgVpmtBJYF8SzhvXZLR2F0I9i4aKwOseb2t35jRaLU7KcjLTeXLVVBIK/c/9RTnnn463/v85/nzww9jtVj47Mc+htfn45Nf/zoXr1mT8NgTTpTXNbawcPa0TE9jTOHY8hKy30fu8nVobIWEerrw1B6gfdPjGCfPpOxgPm0EUaFFTw5mCilmJm6PneYP92L/cDslzMJ/2UKKT1uL6+g+unduwTJ/5bAdPYdDEEX05ZPRl08m2NOJ+9h+fE21SAE/KpMZtSUXtclKyOOi47WnyV2+LlxoOsHxdY1c5DkUqRTmkJlcc0hvWotfVqEXozdYUUg9462+digLw91VGmaeCGDxykOK5YHbLeJaAN6bpuWpJRoue8dJTmP/BimyKOAsMbN5dQFTyEU6s4wGg4aqK87giRffpDA/l6K8XArzc7HmmBEFgbYOJ1Mry5LwahUUsoPmtja++qlPYTYamTxpElt37gTCvVU+edFF3PPoo/zue99LaOwJJ8q9vgB6XeZ8rrOdF264aFC0XFdYjvvYXtxHdiMHA0h+PypzDvlnX4r72F7qeI8QfoQBLrpG8pjC6bhop45tlD2pRX/eFEIV0/Bve4Xu3VvJmbd81HNWm63hceYtJ9jThb/1BL6WE/TUH0FtyUU0GHEf25cyUZ7KHPJkj+2JschzKMarME8HQVlATEPT9YlmlxjLa3WrtRgCvjTMJvNIAuyp0nD5lvhsNyPR82WH/agkmUfOMHLxVg9FnafSVtrNAk/PkVj4wQkWHwkXiN4obUKWZVxuL612J20dTg4eO4GzqwcZmcaWDjxeH3ZnF4X5uRTk5aLVTDjpoTCOqCovp7Uj/L0zZ9o0fnPffQQCATQaDXlWKzsPHEh47An1yejucWMxpc9Gb6wyUJgbp81FnZuP5HUjqDWIGh3de9/D395IzrwVFB+eQYgAKqI3ZDJRQDGzsFPL/H0FHJ2uBymEr6kWefbSpBZpqs05qM2zMU6ZjRwK4be34G85gbYotZGaobzLkzFmMoW51ymRUza6RWk6hDmMvyLQtoCRQs34XHBkO3ZjzrhwXomFllwRvV8mv1saeecBRIT54qMBLB6ZJ1cYmNIcZE5dgJZcFVtrtKzZ6WN6U7B3fwBBEDCbDJhNBqZU9K8Nuu+xF1g4expt9k72Ha6jzb6TQDD8fKvFROHJyHphXi45ZmPCd08VFNLFolmzePXdd7l8/XpmTplCYV4e3/3Nb7jwrLO478knsRiNCY89oUR5bUMLVUo+eUz0FeaCIKAr7C9qDVUz8Lc2YKyeCTCkII+QQykNfIig89O2cROGefMxTp2T0i9gQaVCV1g2aO6pJFVR82SNG/TFV+Q5FKkW5pCZItBUCvNkOq+MxESLlo/EeLFDjIW6QjVVrYmnSEWE+fSmIBXtQbZN17FpgZ6iTolL3vVQ4pR69xsJWZYRRZHSonxKi/IHPdbV7aLN3klbh5O9h47T1R3+vGs0KgpsuRTmWSnIz6XAZlWi6wpZw/WXXsov/v53JElCFEX+5+ab+eKPfsTLb7+NKAjc8aUvJTz2hHqX1za0sGLR7ExPY8wQLZUlgiY3H9ehcB5Vy+U2ip9w9P4/QmQbgBotZiGfbrmVYmaSv6uclmnjMyKSLAEdrQPoaEh2J09FmMdHk9/ESktjSsZWGB67wcL0joZMTyMt1BWqOO2gH4hNOEcj0ecNpMftwWKKHjUUBAFrjhlrjplp1eX9HvMHgrQ7Ton1DkcngUB4oWExGynMs/ZG2HMsJkQluq6QRooLCvjlt77V+/vSuXN55s9/ZtfBg0ypqKC6vHyYZw/PhBLlHc4u8nIVF454GEqYizoDsu9UkVFfMd53W19hPs24HL1bJp9w+kQ0IT9eyEav8tEUeQ7FeBTmqcIZ0pGrSl9esxItP4VHo8MQ9Gd6GinHp4Y2q4oyeyhpwno0tHU4KciLP7Cg1agpK8qnLEp0vbvHHY6u253sP1pHV7cLWQaVSiTfZg1H10+KdqV+TCFdFObl8ZEVK0Y9zoQR5YFgEI1apeSrJUA0YS6oNUih+FpW68wCgZ7BorD4CYcizNOAxymhH0WR51CkS5hDevLMUxEtl0+ennR//Qy0C8ykSO87l3TOI/WltZlj3WX6fg4sTTYVxc4QnwtkXpADtNmdFCXRDlEQBHIsJnIsJqZW9U9LDAZDdDg6aXN0cqS2kXc+2IvXH16IGfX6fmI9LzcHlUppaKQQH0fr63lq0yaONzRQUljIR885h5rq6n77HK6r40d/+AP/uuuuhI4xYUR5Q3M75SWFmZ7GmGWgMJeDAQRBRA4Fo3bxjIbGLOFpj557Pl6F+WhIZuoKJKfIcyjSIcwhfVHzZAvzrpAWi2r8R2qHI1MLApdGj8k/MfzJ26wqCjvjL/BMFW0dndRMrkjLsdRqFcWFeRQXDm4O6PJ4aT8ZXX9/90Hszi5CkoSAQG6OmYI+gl0pNlWIxv6jR/n0d7+LLxCgKC+Pt7Zv57GXXuJ33/seKxcuJBAI8NdHHuGfTzyBxWRK+DgTRpTXNjRTPWnkjpEKsaHSG9EWluE+uhfT9PkxPUdUy8ihifVll6grS7IFOSSvyHMoxpswTybNARMlaSryHIp0i+JsaWZkN1rI83RldA7pot0qUt0SzPQ0enF29WDNMY+8Y4oxGfSYyvWDjB4kWaazqycs2Duc7D1US1d3+HOqUonk5+acFOy5FORZMep1mZi+Qhbwj8ceo6SwkL/96Efk5ebS2d3N7T/7Gb/8xz/49mc/y0///Gfqm5q4fP16brvuuoSPM2FEeUNzO6uXzMv0NMYVljnL6HhjA4bK6Yi64a0mBZWMFBxeEPbNPx9vUfNYU1lSIcYBJElGSMPd2mdrw3/j8ZBnnsxoeXPAxFS9MyljZTuxdthMF3ZDDkU9jpF3HKP0TWFx6QTM3uxJ2JGRs7oIUxQEbFYLNquF6ZMn9XssGAzR4eyi3d7JsfpGtu7Yh9frR0ZGp9VSmGcl3xaOsBfk5qDVDu9ApjC22XXwIJ+96irycnMBsFosfOWGG7jh29/m5h/+kJlTpnDfXXcxd/r0UR1nQohyWZYJhiTU6iRaTyigtuRimjKb9teeInfJWWgLhr4ToTFLUfPJh2I8FoGOJMxTJcgBfJ0SuiQXeQ7HeCkATZYwbwkYWWUev84r2SbE+2I3WJjZVpfpaaQFdQiCWZIqHQgE0ajHrsRQq1UUF9goLhh8DfL6/LQ7Oumwd/a6w/gD4TsUJoOeApuV/DwrLndPuqetkCLaHA4qSkr6bZteVQXArZ/4BJ++8sqkpD2N3U9MHHQ4uiiw5WR6GuMS86zFqHMLcG59BUNVDeZZSxDEwVcFrVnC64x/UTQec80HprTEKsZHUzg62k6eiaAI81MEZRGNmD25vskgFiGe6dQVAJ9agz7OovSxijokE1AL3Cuuzbj7Srujk/xxet3V67RMKilk0oA6NVmWcXt8tDs6abd3su/IxFgMTgRCoRBaTf+7ITptuEbr9CVLklaHkCVr6tRyvKGZqkklI++oMCwv3HBR1O0qkwUEAdfBHbQ+ez+ugzuR/L7+PuVGmaA7e29jppO+Yjze6Hii0XSvU8KQm/47RZF0llQScWZJJeK60xN+rl8SUQuKIM8E2ZPIkVrWXaYHoNQR4nBpONZ2r7g2k1Oizd6ZVOeVsYAgCJiM4dz1JfNqWL10bqanpJBEjtbXs/vQod6fXQcPAnC4trbf9t2HDiV8jAkRKa9raOGcM5ZlehrjghduuIgbLru/X/RaEATkUBD9pKl4TxzBdXgXPQd34KcILSaslGITTSArojwZJBIxD/pk1Prxe/6zOWLeEjBmvMgTkuNbns1pKtHo1hqw+MZWUfBomH88wD/XamnLESnskjIaMW/rcDJrWmVGjq2gkAp+/Kc/Rd3+g9/9rvf/siwjCAIfPP54QseYEKK8x+3FbBq+EFEhPvpGwSUkHED1iWm0nD6Dzm2voS0sQ9Oopo2DGHVmgt7MV+CPJwZGzIcT6ekq8hyK8eTKkogwb8oC55UIoxHm8QjybIiSA9iNOeR5ujM9jbShCcGSw362zNRx8VYPAmRMmLfZnZyRF5szl4JCtvOj225Ly3HGvSh3e30YlK5eSeOGy+4ftE1EpJBp1PEekzYvopQ1tDUews5xLBRRZC4noNS7AKkr5hwueu7rSm+RZzTGmysLELM4bw6YmGmwp3JKcRGvVWG80fFsEeQQLvIs68qe+aSSiAvL/OMBDpdpeGq5gXO3ezH45YwI80AwiFYz7iWGwgTh4jVr0nKccZ9TXtfQQuUAb1KF+AkEAlx62c9o4xB2avHRX2UXMZMcyjjEq0gEKWMes7mQalaiNctxOa8MpG9UXiF+vBko8hyK8ZJjDrHnmfeEtFjE7Cs0LLsyv/cnnseGI5sEOYTtECdSpBxALcFH33JT0BXi32cZOV6oQiK9OeayPFGy+RUUksu4X8bWNrSwYNbUTE9jTBKJirtxcoy30GHGQC5BHDSyExMFFDIdE+ELtwY9Iiq0hEWReHLNp9YHCPnG/Vst4wwVLfc4JQpnZo+H7nhxZYGRo+bSyZeZxVbNQHJyxbNNkAMEVCq0UvY000kXKhlO3+dnUkeIzXN0uHUC1S0hDpefS2VrEG0ovF+qoudd3S6sFiVlUUEhXsa9UmrtcFAUxWdUYXgigtxHD8d4i3IWkkt57+MhgjiopZ5tgIAKNTISUzkLoe8NGEEmHDTJclUyTogmzINeGY0+OyLlEdKRzpLOzp9D5Zo7Qzps6vHf4j0bBbmE8q1T3RqiutVNl0HgaImaXVUaXlqkp8weYnJzkK6eHnLMyRfPrXYnhXmp67ugoDBeya4rdZIJhSREQcjqjmLZSESQy8jU8wFFTO8nyAFUqClgKjM5l2qWU8Z8pvMRDPT/IlYbZILu0b/NlBSW2Ombty5nuMhzJFKdzpKuVBaIns7S5DdnTZHnRKNLZyLHq5x7gByPzMJjAS5/x8OnX+phTm2AndUaXtycnI61A2nrcFKUrwTDFBTiZVxHyptaOygpGlsWXukmWuFmhE4aCOGngGl46UYiiJH+X7QCAgZyhxxDa5Hwd2exKswgQxVmJqMYNBIx93ZJ6CzZff7T5c6SDgZGzJsCJuYa2jM4o9STjVFyCDuv5Hu6Mj2NrEMXhKnNQbbM1DLtZEfCZNNmdzJ3xpSUjK2gkC3sPXyYg8eP4+jq4tK1a8mzWpFlGUmSUKkS6wuS3VfrUVLb0EJ1udI0KFE6aSCAm8O8zmFe4zhbCBFffqbGLBFwJedtpkTL4+PBLdasKvIcjlRGzNMZLYf+EfP2gIECjSetx1cIYzdYyHNPrCLPWNlbocHok1k4c2ZKxu/qcWNRbIgVxiken49b77iDa77xDX5177387oEHaO0IByfu+P3veeyllxIeO/uv1qOgvqmVitLCkXdUiMqrT/yOGtZRylxmcS4m8qlnGy7akWPslSeqZeSgkj6UKTxOCf0YEOUQFuapEueZEuYSAmphfNwFSAWJurzEgt1gxjbBnFcinT2HI6CCd2ZoOWOPL2mtwaORyrEVFDLJr++9l4aWFh65+25e+9e/+rkNza2p4elXXkl47LFxtU4QfyCAVps9rhNjifuevA5BEHjoyZsxU4gKLeUsRE8OJ9jObp5iDxvYx/Ps5yVqeRc//fM3BZWMNEEF+TUrOwf9DCRVnuV95xD0ymgM0T/mqT5+oowXYe6RVOiEUFqPOZYYKMSTLcxDogq1LCV1zPFAY54Kq1uiuDM158bn86NTrrsK45jN77/PrZ/8JNOrqwctPitKSjje0JDw2OM2p9zZ1UNujmLJlAj3PXndoN9vuOx+1OgoYTYlzCZEAIkQEkFkJJyc4DCvM4vzEU56HmhMw6eudNFMC/swkU8pcxEQ6aaVRnYAMJnVvfaKEYqfcNByeXYXEA2VKz5c181UIEtyVCu+vmJ8uKZDmWQ85Jm3zl9JyZajmZ5GVjKUAB9Nx9G+hAQBUfHKjkqbVUWRM3WLlTZHJ4V5uSkbX0Eh0/j8frSa6AvPVrsdi8mU8NjjVpTXnmimSsknH5GBAjye/foWiZYwm04acdGBmQIgnE/u74pe7OCig3q2UcYCHNRynC3oyKGDI6jRo8WEhui3YrNdmPcVvRHBG9kWiwC+ZmVnUqLYj282cUbhqaY1Q405kYR5Om0Sm+xQtnwK7G1My/HGCqlIVRlIp96M1au0EY5Ge45IRVvqvNvbOpwUKHaICuOYxbNn868nn2TlwoX9xLnP7+ffzzzDglHUaozb9JXaxhaqlE6eKWWgUDeRj4dTxZgak0zAFT0VoYNjFFKDjQqqWYmRfNo4iEQIAzaqWN7f73wAxU84xkTh54NbrAkJ7KFSXuLBGAjwbrMl4TlkA6lIZUlXGkuTHUrywvnlsXb/HIvEI7JH2jdZTi52g4X8CVjkufHJkT3xjT4Zty51l37FDlFhvHP7pz7FwePH+ehtt/Gb++5DEAQef/llrv3GN6hrauK262ILdkZj3IpyZ5dLSV9JA32FuYkCumg6+ZuMIMogRxdVPrp7O4GKqNBgQI+VWZxP9UlB3sYhDrKJ3TzDEd7Az+AIZ0ScjwWBnojIHo0wNwT9eIa4xTaQbBbtY1WYe3xg6nOzZ7wL85EEdzoi5BE6DBbyFDvEqJQ4QrTYUnfp73B2kZ+bk7LxFRQyTXlxMf/+5S+ZVFLCQ88+iyzLPP7yy1gtFh74xS8oKypKeOxxmb7i8wfQasblS8tKIjnnuZTTxC6cNJCnLSXkG1pMhfCj4pRgdHKCImagxYiTBhrYjol8CpmOHw+t7ENm+DzIiDDP5tSWdKIJSQTE8bHuHmupLCGJqE2bel1ZonT/HA8MlROeTkEO4fSVXCV9JSplHSFem6ejMUXCPBSSUKsT82hWUBgrVJWX85c77iAQDNLc1kZJQQGaGINgwzE+rtgDqG9qpaIs8ZWKQvzc9+R1CIhUs5IGPqTLfJjOnm6C+Hr3kZEJEcBHN348aDlVDKFGi58eAnhoZT9lLKCMBZxgOx4clLMILSZaLrf1+xlLJBKNTjiCHSlyi8OWLJuj5ZC6iHkqoubtXVAwTLBwvEfNM01IFFEphZ5RMftkzvnAy4bTDByuq0vq2JIkxfOVo6AwJvnF3//OviNHANCo1VSUliZFkMM4FeW1DS1UlSn55Onmvievw4iNGawnx5xDY89h9vEie3mOw7zOHjac/P8bFFGDyKloio0qOmlkPy9BVRG+i2fTvEpGVgv4JulxzlPTsHbwt/1AYT7WhPpwjEYk64NBvOr47xZluzBPFckW5k12KMsbfh9FmKeGoCCikhQrxOEo6JbQBuCN995L6riOrh5sVktSx1RQyDaee/11rvnGN7jsC1/gb//9Lyeam5M29rjM8Whu7eDs5QszPY0JSSSVxaq3IXmLKQP8uPDjQk8OGsJd3lout9HS75k2rMxAluVe309tUTl5Z11MwNGOr/E4nvrDFKy5bNAxWy63Zb0jS4RYXVhGK46NgQDuBFfu2erGAqm1SkxmOkuzHZZMH3k/cd3p4zqVJRM4DUrqynC05og8s9zA/GMBbrziiqSOHXZeyU3qmAoK2camf/6Trbt28dLmzfz7mWf400MPMa+mhgvPOotzVq8mNyfxmopxFymXZBlJllGpxt1LGzP84/FrTvb7FBAQ0GHGQnGvIB+Ovkb8giCgNucCEHC0YZg0ddjnjoVizwjDie5kRKsNwQAejXbU42QjqWouBMmLmHd0Q36MAcPxHDGPh2Q5r3QYcsh3K0WeQ/H2bB3LDvlZdtif9K6bbXYnRfm5SR1TQSHbEEWRFQsW8IMvfIGN997L77//faZWVPDXRx5h/U038eWf/jThscddpLy13aHYMWWY1nYHF12ykAd+uW/IfUaKbIfcPYgvfkgHx9FhZior6J4+WJQPFOIDf8/m6Hk83uXxogmFRlXkGW1hkE3R82yPwZixVwAA/gBJREFUmMsSxHP6x3PEPBaSJcghbIc4s70+aeONJ4JiuKPn+ds83ChtSvr4bR1OFs+tSfq4CgrZikqlYtWiRaxatIgd+/fzm/vu48333094vHEnymsbWqhW/MkzSn1jKxWlRdz35NJ+DYYGUvyEg8ZzNbiP7UMOhVCZLMjBIAF7C8HmZnKpYCpnoCd8K8gYRyTcjYMOjlL2xHzaL8/uot++4jxa6kjckfMEijzHItkqzHs8/a0QY2WiCvNkCnKATr0Jq9eV1DHHCusu0w/rVd6Qr6KgM8Qt/uQLcgC3x4fJkMCbX0FhjLJj/35eeustNr79Nm0OBzXV1dz+qU8lPN64E+V1DS3MW7sy09OY0NQ3tXFezeQR9wsRxPHis2inTUPUGwh2OxDVGoqaC7GyCFWCb08H9TSyAxE1zexFTXaL8gjJKrJMtMhzLJJqYQ7ELc6b7FCaYDr1RBXmyUQWBEQU55Vo1BapufyLiTc2UVBQgF0HD/LS5s28/PbbtNrtFNpsXHDWWVx49tlMq6wc1djj7srt8fkw6nWZnsaExuXxYjLqh42SA9g5hol8qg/PSMpxHdTRwTH8uJnCGYio2a96mWL5LAKONnyNx0EQUBlMaAtKUVlyk55TmWwSEerhfPLk2DONBVIpzCF+cd5kh6pRrAMVYZ44AVGFWgplehpZS7NNxaLZs1MyttvjxaBcexUmANd/61uYDAY+smIFF519NsvmzUualhhXorzH5cFsHLmYUCF1+PwBdFr1iIIcwEkDxcxMynHt1NLMHiaxGBP5qNBQu7wL9QEbPfs+wFN3EENVDYIoEnC003PgQ5BlDJXTsMxdnpQ5JItoueaR1JZYMAYCtJpMI+84jogUf6ZanMcizJsdsHyUb2tFmCeGw2DB5unO9DSyFpdOoKSgICVjt9k7KcybmJaqChOLO2+/nTXLl6PXJX8ROq4sSmobWqhU8skzyonmNl7bUDvifh468ePCnITUEh89NLKTKZxODiWo0NB8iYXu3e9gmb0EjdWG2pSDeeZi1GYrUsCHHAygsRWgyS8Z9fFTRSS/PCLOYy20DBd5TsyOeql0ZokVfwB0SbhRMZFdWcquzE/IUrHDYCHfrYjyaMiASy9QkDeCgX6CtHU4KVCcVxQmAOefeWZKBDmMs0h5bUMzpy2YlelpTGjqG1v5zvcv6Lc4Ghg1l5FpYT+FTEMc5bpQRqae9yliRm9BKIDr8C7UOXnoiiuQpRCdH7yJ/fVnkKUQpmlzsS4+E1Gb/bda43ZomSBFnsORyqj5SNHyYAhUSVwPTYSIedmV+UMWew73WDTsBgtzW48naWbjC58GVBIYUiQm2uxOllUk586ngkI28YUf/QiDTscvv/UtAK740peG3V8QBB777W8TOta4ipS3O7rItyVu2q4wehpb2ikt7h/huu/J/oVFPbTSRRN5jFwMOuLx2ImAQCGnOrU0X2rFfWQvltlLwxsEETkYIOBoJWfBKgyV08eEIO/Lg1usQ6av9I2mT6Qiz5FIVdR8OC/zFgcU5abksBOGgRHyeCLm3XoTOb7kNIAab7h0IiZv6jqd2p3dSjdPhXGJJEmE+nQJzrNayc/NHfInz5p4Gte4uXoHgyHUKjHrC/fGO8GQhCaKKIx0+gQwUYiZAmp5Fx0mZGRkJARESpmLmtgEcxuH6aaFaZyNQPjv3nK5DX/LCVRGM+qcsEe57PchaLTkzF9J14ebyT/7MoRkhjMzQLTI+TUrO3nuFc2EKvIciVRFzYeKmDc5oDTJ2QETKVo+lACPbB8pai4DyhUgOi69gMmXupoLSZZQjaI3goJCtvKn//3ffr/f85OfpOxY4+YT1NDSTnlJagpYFGKjs9uF1TJ0FDESMRcRqWIFuZSjx4qRPMwUISNTx3vIMdiZddJIKweYzGrU9O9c6W04hq60uvd3X0s96pw89BXTUJly6Nn/QWIvcAxgDARwp0iUJ8uyMROkImoeLWLeZE++KIewMB/vOeaxRMSHyzX3q9RoQ8FkT2vc4NYLGL2pEeWhkCLIFSYOH+zZg9vjifpYS3s7r23dmvDY4+ZTVHuimary7C3amwjUN7YyqTS2wk0VavKZQgFTyWcyeVRRwWJCBGnj4LDP7aKJet5nMivRccplJNK9U1tUhvfEYWRJQgr46d7zHpY5yxAEgZyFq/HUHiDgaEv8hWYpD26xTugiz5FIlTDvK847eyA3hcY3412Yx0o0YW5XnFeAcAOhaLh0qYuUdziV1FGFicNnvv99DtVGN7Q4Ul/Pb+67L+Gxx40oVyLlmae+qZXKGEV5NAREKllKKwcJ4uv3mIyMHzct7KeeD5jMKoycCklGBDmAvnwKot5Ex6tP0vbSf9CXVaPNDxeelj3vo8BXRc/BnQnPM9vozTdXijwzhsNqTNvpV4R5mIHC3G6wkO/uytBssh+XPnU55W0dTgrzclMytoJCtiHL8pCp0vuOHKHD6Ux47HGRUy7LMoFgKGous0L6aHd0kj9Kn1odZnRTpnHI9SGGiulIXhd+eysBeytIEpqCEqY3rkHLqehkX0EO4crn3GVrCDjaELU6vI3HaXv5v+QsWImHIB0cY0rjasZDTK1vSokuFMSnfAaGJZWNhupEPVbT0C3Ok8lEyDOPhb7uLB2GHCo6x98dsERYd5mejU/2fy+6dAJFztS899vsTqZWlqVkbAWFbOCz3/9+v3qVn//1r5iN/VMY2xwOahsbOWvZsoSPMy6u4HZnN/m5yq2zTCJJEgIC4ghhwoFOLNGaDJlnL8V9dA/exmOo9Eb0ZdVY5p6GymhBEAS0Tzh69x0oyCOIWh0aWyFtL/0HQ8U0zDUL6HrrFboRKGMeRvIwnhxnqDGymWj53anMJx9PpEqYt7ZL5EzSAv6kjx0NRZiHiUTMQ+1WapYZaXoseq7nRCeVhZ5tHU5WLEpNp1CFiYk/EOA3993Hm9u24fZ6WTp3Ll+/6SYKh/DZf+O99/jbf/9LXVMTS+fM4buf//yoXFAGUlVWRldPD109PQiCQFdPD4Fg/xoWi8nE1RdcwOeuuirh44wLUX68oZkqpWlQRmntcFKUQOOIvq4sEUo3uGi5fNGQz2m53EbxE45hxXTxEw48OOlCz/SjYe96H2toWS3gLyyHJ5399h2LwnwghkCAduPE6uSZKKkQ5q1tMlOq05vPrwjzU8iEU4fi9TafKPg0ArpAakS51+9Hr9OOvKOCQgxIksTNP/gBTW1tfO7qqzEbjTzw9NP85/nn+eI11wza/8P9+/naXXdx9QUXcOMVV/CPxx7jlh/+kId+9StUSXJa+97nP9/7/0WXX85Pb7+dBTOT78s/LnLKw0WeiijPJPWNrVSUJZZPPjB6DmGhPBwjCXKAAF7UnCp6cl5ega5oEoIgDHr+SMcbC2hDIfxj3OoxnSS78LPDLlGQLwzrY54KlBxzcIfUGMVTUatEO4KOFwamrgCoQxBKwRVfllNns6gwMXn13XfZdegQ9/zkJ1yxfj3nrF7N3378Y275+Mej7v/A00+zYuFCvn7TTXxkxQru/s53OFJXx5YPP0zJ/J7761+ZPW1aSsYeF6K8x+3BYk7vhVChP/VNrVSMosgzEWEejb7PCeJFc1KUxxIJH9PCXCnyTIhkCvNgENTq8HiKME8vLQEjxZrBvvETWZgPRB2SCaiS//3Q4/ZgMSnXX4Xk8e8NGzh72TImlZxy1NNptaijBJ0CwSCvb93KupUre7cV5uWxYOZMNr79dkrm5/F6eemtt6I+9oPf/pbahoaExx7zotzj9Sm3zbKAHrcXs8kwqjGGEubRxLIsy/jtrfjaGpF80YvrBkbKY2GsCnOlyDNxkiHM/X6ZTKfzTwQv86FoCRgp0rgyPY2sIZototEn49YlX5QrzisKyUSSJPYcOsTiOXNi2t/udBIIBqkqL++3vaqsjKb29lRMkbvvu4/3dkZ3cNPrdPz2/sG1crEy5q/idY2tVJYpqSuZxO8PoNUk560ULccc+ud9B7udON97BTkUQtQZCHbZMc9ajGnq3H7PCeJFi+nU87ocyMiozbkIwzS6KB6DBaBKkefoGG2OeVu7RGFB//fUUF0/U81EzDNvDRqZY1TyyPsy0IHF7JXpNiQ/Dtdmd1I4StcthczTadan9Q5fZ1cg6vZulwuv34/VYuHX//wnz73+OgDnnn46t113HTpt/yBs+0n7QavZ3G+71WJh58Hhe54kyu6DB7njttuiPnb64sX8+I9/THjsMR8pr21oUfLJM8yJlnbKi5PnER8tYh4h5O7B/tbzGCfPpmDdleSfeRH5ay6nZ98HBF39TQ4DeHEtC88r5HHR8cYGnFtexvnuxpjmMZai5oZAAI869aJ8LHf1HInRRMxb2yWKCrLn63SiRcx7QlrMYvSL/ESmb8Tc1iPRkZMCUd7RSUECRf4KCtHwB8Kf4z/++99IksRPv/IVbrj8ch598UX++sgjg/aPfGsPrG2QZXlEN7hE0et0dHVHN1Xu6ukZ1djZcxVJkJZ2O8UFYyeiOR4ZTZHnUAyVyqJ5cS+6onKMk2f2mverTRYMVTMQX9rRu69ECA+dqAxhN5KefR9grJ5B3pkXEXC0xjyPodJnso10FHles7KTa1Z2pvQYmebZWiEhcd7WJlNUOPjrNN255X2ZKOkssnzKeUVhMBFhXt4R5ES+ir9q1iZ1fGdXD7k55pF3VFCIgTyrFZUoctX55/P1m25i+YIFXHfJJXz0nHOi5nHn28L6r3OAGO7s7qbAlhptOK+mhn8+8QQeX/8mhz6/nweeeWZURaBjOn0lJIW7k4nDpCIopJ7GlnZWLY4t/2u0iGjQ1zopru0vlC0UUsu7lBD2yq3jPYzYmPSGhsZ1TnxNtRSs/xgBeyuyJFH0hB2I/Sqe1baJKSjyHO/ieyTiTWdxuWVMpujnP1NpLBEiwny8prT0SJpho+SKRWJYmMsyvFsfYuNCPSrVWj4d2pSUsWVSF5FUmHioVCqK8vMHpalUl5fzxMbBd7nzc3PRabUcP3GCRbNm9W4/1tDA1IqKlMzxtuuu48ovf5nLbr2Vy9evp6yoiJb2dp7ctIk2u50fD5HaEgsJq9ktH37Ih/v3EwyFEj74aGlutVNapFTXZ5pAMIQmSTnlI6HDhJ/BAsdALiDgwUETuwnio4Il4YZGG3eR76/E9OwRure8xtTAKoQ4BHmEbI2Y60KhpBZ5TnRBHiHWiHm45fLw+2QyYh5hvEbOW4dwXumL4sISXrP/pAJ8aoHnlur5m3r0EfNAIKh00lZIOutXrerNJY+w78gRJp8s5nR5PEgng7JqlYo1y5fzch+nlZb2dnYfPMj61atTMr9JJSX86667yLfZ+Mt//sMPf/c7/vjQQ+h1Ov5yxx1Mr65OeOyEPk0er5c7//IXXG43Pr+fvNxcbrriCi5btw6XxzOo9WiqqFWaBmWcrh43llG6rsRDCD8qBudOCwjkUk4bh3Bhp4aPIKJCRsZJPSXMpZatTOEMTETvCBYL2RgxNwT8SSvyVAR5f2KJmDucMrnWkQV8piPmEcZbIWhLwESpZuQ8zogwn8hRc70Ad5fIfLMBXlys57OjHK/d0UmBbfzWmShkhmsuuYSnX3mFb//qV1xw1lnsP3KEZ159lZ/efjsdTicX3nwzqxct4lff/nZ4/4sv5tPf/S533XMPy+bO5Z5HH2XG5Mksnz8/ZXOsqa7m37/8Jd0uF/VNTZQWFWHLGX1n+YQi5bsOHqS6vJxX7ruPNx54gB9/+cuUFBby7s6dfOXOO1l/003c8Yc/4Ozq6n3O82+8wYubN+P2JK8Fcn1TK5Wj8MZWGD31TcnPJx8OCQmJwXdnfLhwUI+AiJkC1OgAcONAQMRKGWp0hJLQAj3bIubGJBZ5judCzlTR1i5FzSePhsNqVKLmSSZshxj7YmeiR801Avy8HGqL1KO+HrfZOylUijwVkkxxfj7/+r//o9vl4rt3380Lb77J92+9lXNPPx2tRkNhXh4lhYW9+8+rqeHX3/522BXlD3+grLCQP/zwh2lJbbaYTMyeNg1bTg6BQIBX3nmHb/7iFwmPl1Ck/O3t2+l2uWhua6OksJCFM2fi8nh4fetWvnbjjWg0Gv7vb3/jiY0bufGKK9j8/vu8t2sXep2O4w0N3Hz11QlPuC8+fwCd4lGeUeobW1k0Z3rajmellCZ200M7ZsLOKj5cHOENiqghhxIO8gr/n73zjo+jvNr2NbO9SFppV11y7zYYN2ywDZjQS2I6ISFOIAmkJ28SEnhJ+NI74U1PICFgCEkIgQAmJPRqwBgb3LtlyepbtFpt35nvj5Vk9bLarufiZ6SdnX3mWc3uzD1nzrlPlBASMg1sxcFs2i5zYD6+ioaDO7GfOb/fmBNpUpQNUfNkF3k+uLlIRMz7MFq0vLVNYf7c8R1KsylqDrmdb+5XtFg00dFXFPRikGC2VmX73r2cvmRJwuO0OT3Mnz01iTMTCOJMqazk19/85qDlBRYLT/z2t4OWr1m2jDXLlqVjav2IxWK8+d57PP3KKzz/xhsTzhZJSJQb9HpKi4v50g9+gAp85/OfZ/a0aVx05pnd+ZUSlWVlbN+zB4DD9fWctXIl1eXlPPCvfwHw6DPPsPfIEW658UY0CQiKDq+PQqslkekLkkiby5PWSImMlkoWUccbaNATJYhCDOviVcRmLMAN6LfPZJ/7DVBVdCVVRBcvRQIMFbV0vPMySiiIbDhhFdZyWXHC0e+Mp7OkqJNnT8RciPM4Iwlzl1ulpHj8f/9sEeaQu+JcVcdTrn0CUfwJi1DZumvXhER5u9uDozh1KQICQbayddcunn7lFZ7dvJmOzk4qHA4uPftszlqxgmWLFo0+wDAkJMqvOP98ykrieblf/P73efg//+ErN9xALBZDlmXqGhvZtmcPH/nABwCwFRbym7/8hdqKit7E+50HDvDPZ57hsnPOYd6MGQA89dJL+INBrjz//FHnUHe8hWk1FaOuJ0gdSrcgTFXl/XB+5aqqsuvgQYx6PfbiYoqs1n63qQLXnMPr27ahqipnrVzJJQ/8GwBJo8VQOQ3/0T1Y5/Y/EfUI62xLTRkNfZKLPAcixPkJhhPmigKynNh3oCeVRYjzxOiI6SnUTDwlbTKySFL50z8e5qZrrkGfYE1KOBJNWuM4gSDb2XngAP955RX+89prtLlcTK+p4fJzz+Xef/6TO7/+9V4tOxES+jaVlZSgKAqyLLNm2TLu/ec/ue2mm3hrzx5uuuMOiqxWvv7JT3LB2rVAvBOT1WxGq9Fw2imnEI3F8AeDFFgsNLa29r6Rvzz5JHOnTx/THOqOt7BmxUmJTF+QJDLVXlmSJBbNHj5lxmQ08r7TTut9/PSGS7jgvicBsM45Gecrm9DbK9A7Kge9dmDUOxYKEG5rRAn60ZislL6losOEFgMSUsbTV5KZTy4YP4GginFwR/Nxk01Rc8idYtCWiIVyXVemp5GTnIxKFSo3XXUFv/nbw5gMhnG9XlHHbhkqEOQ6l958M01tbSyaM4frLrmEdaeeytTqamKxGH965JGkbWdcWfAdnZ385cknOd7SgizLxGIxPF4vld0J96eefDIv3HcfF555Jk6Pp9eyxqDXc/aqVZyxYgU6nY42l4sjDQ18+oMf5NnNmwmF45GOhuZm1q1cOaa5uEXDgoyT7iLPifD0hksA0BYWY1t+Jp63nsf73hsEm4+hhPoXOymhIL4979D+/D9pf+ZhgvWHiHV1Eqg/yJGid9nHM+zgMfbyH1yvPkXHOy/j2/MO/rr9hNoaifo6UNNkFWpOovOKYHQG2iS2tSWvk2c2FID2JRcKQVvHWeQpOIFGglukGMXAjddchau7XflY8XZ2YSsQ52DB5KChpYXF8+ZxzYUXcvm55zK1255RSnKmwLgi5UUFBfi6urjnH//g4jPP5K0dO9i5fz/V5eW0OJ04bDZshYUsnjuXvz31FBeuXUuJzQaAoihIkoQkSew9fBiLycS6Vau4++GHMej1OD0eOru6xhQp77llluw/hmB8NDS18b7Tl2Z6GmOmJ2JuKK/FftYH8B/Zg//gTjo87cg6PbLRghoNEwt0YayeTuHi1eiKS5GGqOB2PNpG8/u0xAI+Yv4uYgEf4bZGYn4fSsBHLOBH1hvQmK1ozFZkkxWN2YLGFH+sMVmR9IYJf4bT0clTMDytbQplZcmr8BcR8/HRGjGzwtqc0GtFXnlcmH+BGA+qMld8dAOflWKcKp2IgNf+c9Owr21zpreeSCDIJPf/6Ec8/cor3PnnP/ONX/yCJfPnc9app3LmihVJ3c6401cuPuss/vX88/z4nnuoLi/nMx/6EEcbGnjwiSe49KyzmFZTw79ffpnioiK6AgFKbDZUVe2X8/vevn3MmjqVcrudBbNm8crbb6MoCqUlJZSWjO4h3dDUSk1F6ajrCVKL1+enwJpd0b3R6ImY90VRFI41NeHyeCi0Wimz2ym0jhIB2jDy0+f/+XGUYICY39ct3H3EOjsItx7vFfEoCnK3QNeYLb1ivVfEmyxIsowSCRNxtRJ2tRDzdYAkozFZMFZNB+S09BcXjiwn6Jtb3tausGhBcnNqhTAfO0FVg1HOXAO7fECW4HpJYamqcqeq4V1V4UZJYbQyiTaXh3JH4j0fBIJc4qQ5czhpzhy+csMNvL1zJ/959VXuefhhfnbvvUiSxL9ffhmjwcC07gh6ooz7bFJdXs6nP/hBPv3BD/YumzVlCnWNjXzuu98lpijMmzGDj61fT21lPGd3YDRw96FDXHrWWUA8teXo8eO0ud0snjdvTHOoO97CrGkTe+OCiRHv5JYfEVpZlplWXT3hL1Nf/vPR93PBfU+iMVmAoRtcKZFwr2BX/D5igS5CLQ29Ql4JBpD1BtRYFK3Njr6kHEPFFFBVop0egttfxeOoxtdah7FmJlrLxBsXjIQQ5oMJhcFoTP5FkRDmo6Mk6LzSFxEtP8FCSeUXRPmWquE3qoZPD9EPoi9tLg+L5k68sE0gyCUkSWLFSSex4qST+PonP8nmbdv4z2uv8ch//8vGxx9nSmUl61au5Asf+UhC4yclxGPQ6/n0ddfx6euuw9XRgSxJ2IbpbOT1+Whpb2d5t2XMRWecwZYdO3j57bf7Cf2RaGxxcsapi5MxdUGCHG9pp7rckelpZDV9C0yHQtbpkXUl6AqHjjapioISCiAbTEOm0BTNWEjU14HSeATXi4+jsRRirJ2JsWYGGkNquqwKYR5nU53EBTVKSm9SZKMzSzYJc0/MQLE2OOFxRKfPE1gk+H/E+F9Vw4tII94QTHc3Z4Eg29BqNKxdvpy1y5cTjkR4ecsWnn71Vf761FMJi/KktzsqKSoaVpBDvJjTHwz2dmNau3w5z73xBsFQiAWzZo06/u4DRwmGQglbkAmSQ31jYkWeG9ZvZMP6jSmYUXYyVLrMWJFkuTeFZSjM0Qjh4lIKF59O6YXXYZ2/hHDrcdyv/yfhbQrGzmO7oaQk9cehbOkCCtlV/Bl3XkneBctk7/TZg1mC9ZLCK+ro8kDUdQkEcfQ6Heecfjo/veUWnrv33oTHSbvB6IJZs/j7z3/e+1hVVU475RT+88orlNtHPyiGQmECoTAPPPYMWo2G6opSplaXU13uQJsn6RS5wPGWdlaeMn/0FYdhw/qNw/qQ5xsTEeZ9GRh1N0RjBMJBgkcOEwsGUIJ+Ih1ODBW1SdnecIhoeZygR6GsIvVtnHvIlpSWbImYt0bMzDR4kjqmSGeJczIqvx8hOSgUCmPQC9cngWAozKbE7yCl74zSh76RdL1Ox+2f+hQP/OQnY3ojOp2Oc1Yv4/rLzuPKC89kSlUZRxua+PumF7j/n//lqRfeYNf+o3R2Zf7klc+EI1H0Ezwob1i/EVVV2fTSS/z75Zc5XF+PKrxvh6WfuFdV1EiY9hceJerzojGYMJTXUHL6BRQuXp3yufQ0FZrMBDsUdofTGwgQEfMTpMoOUUTMwQYogNvrHfL5NndHRnpUCAT5Tla04tJptcyaOnVM6za1tHPumriXuU6nZVpNRW9nT1VVcbq91B1v4ZlX3sbnD2I06JlSVcbU6nLKHcX9XGAEieHrCmA1J6FjCnDuZV/FRysGCvDjwkoZtSxD6o7STJZo+ljpyVPXx2L4QwEkWYMky8gmM8aaGUiS+Hyni4hfQWdJ/+17ETGPE1Fl9LKSkrEne8RckqBQjfcmKR4iHTVTjeMEgnwn587ggXAEi2loQShJEo6SIpadNIfLLziDj1x+Hpe+7zSKiwrYue8ID/7rWTY++l+eefVt9h9pIBgS7ZkT4VhTK7WViTUN6iuyVVS8NFHMVKaxirmcRxAvLezuXWcy5Z+PRqvLxfNvvEGgbj9yw2E6Q3405gJCzfV0vP0iaiS9n+fJHi1XiR9zBjYUSgeTPWIeU0FC3FVLJX6gwGIZ8jnhUS6YzPz4nnvYsX9/SsbOikj5eDAZxpcyYTIamDujlrkz4nm2iqLQ3O7m2PEWtu8+SDAUxmo2MqW6nKnV5TiKi0Txyig0NLZy8vyZCb/+vseuZ8P6jUhIzGANB3kJPWZs1DCd0znIiwTwoMeKhMT562/jN7/8FDNrU5srna34AwFuvfNOtu3ZQ8hajKQzYLGV0RIJYyirJhaMR01lfXLuXoyHyZpfHgkqaA0njhN9vcvTxWSOmLuiJuxJcF4ZickcLfepEGB4Ue70eLHbUmvBKhBkK/997TX++tRTVJWWcsEZZ3DBmjVjzvYYjZwT5ZUTtOGTZZmqMjtVZXZWLVkAQGeXn2PHW3n7vX20uTrQyDJV5XamVJdTW1E64dzpfKPV6aFsglGSHmFuwMoMVnOYV5HRUEglszmbTlqIEAAgSpBrPvdVVpwyj9s/9Smqy4f2/c5XdDodGo0Gv8aAyVGJzl5BgaTBaSvBmgUXkJNRmIc6FIxF/W80TnZhDqRNnKcqn3wgk1WYP4XMGlT0uqHPfdFYTBgrCCYtz/zpT2zfu5fnN2/m3y+/zJ8eeYQZNTVcsHYtF55xxoQ0Ss6J8uqy5HtjF1jMLJwzjYVzpgHxA05Ti5O6xha2vLuXSDRKgcXM1OpyplSXU1JUMGmj6YqqoqImJTe/R5ibsDGN06jjTYpxUsECiukfFa9kEUe3H+D9N32OKk6ihGm9Y+Q7Oq2Wn33ta6z7wa8ItzcRqH+NUMU0nDs2o7eXo7dXoCspQ9YbMjbHySbMgx0KZsdgUTKZhTmkL2reEjEz3+RK+XYmI60qPKHKfFeKDvm8oijIk/T8JxBAPG1xyfz5LJk/ny/fcAN7Dx/m+Tff5LnNm/ntQw+xcPZsLly7lovPOmv07uADyDlRXlw0vjeYCFqNhtqqsn4+3B2dXRw73sLmd3bh7ujsjqY7mFJdTk1FKXpdzv0pE8Lp6sBRnLxc4r6i2uXx8P6P3sIhXmYKp6LnRN6shEwZcymggkO8hI0aZLSTxlpRkiSM1dMxVk9HH42Cz4vVXkrY2ULXgfeIeNrRmK3oSspAVQm3NxPr8mIor6X49PPTMsfJJMyDXoWSGUNHETMlzCE7Gg2lQ5i3RU2sTUOkHCZXtNynwrdULVdKCmse3TTkOm6vj+KigjTPTCDIXubNmEFVWRmVDgcPPvEEO/bvZ/+RI/zigQe48YoruPHKK8ccyM09JZmhK/SiAgsnzZvBSfPibYWj0RiNLe3UNbbw5rbdRKJRigqs8Wh6VRnFeRpNP9aUWNOgsVBis/HyP3/HRZd/kwM8Ty3LKKSy3zpR4nmkMSLI3R/fySLMe5xXTNEIAYMRg60EQ3kNEO/+Ge1wEmppwH94N0oogL60Cuv8pRmedX6ixEDWDv/9zoQwh+wR56kW5jFVRieJQs9koqjwY1XDySh85p+PD7uecF4RCOJEIhFe2rKFJ198kde3bcNqNnPpunX87Otfp9xu5y9PPsk9Dz+Moih88pprxjRm7onyLEGr1TClO52lB4/Xx7HGVl7fugu3Nz+j6fWNraw7bUnKxpdlmacf+y5Xrv85dWzBRhsVLELuNgpqYDtTOBUd/T3tMy3MBzb2SVbDoIE8veESPvarv+Ay9XffkGQZJRrBf2QPhopaLHMWo7VObneUVKHEVMaSvZUpYQ7ZIc5TJcyjqoQmzYJ8MkTLX0SiC/jWI4+NGFBqc3pSFpgRCHKBbXv28OQLL/DM66/j8/tZsWgR3/nCFzh71Sp02hM674YrrsBiMvHnRx8VojwT2Aqt2AqtnDxENP2t7XuIRKMUWs1MqSpnSlU5Jbbci6Z7fX6KCoauyE8m/3jsS3xo/T3Us5VDvMgUVmLAggYtPlopoLzXy7yHTAvzvlxw35MpE+aGaJSQpn8+s//IXnx7tlK0/CwMZdUp2e5YmAwpLCGvgqFwbDUVmRTm0N86MRMCPRXC3BkxYdcGkjrmZEdV4XFVw+du+180mpELONtcHpaeNCdNMxMIso8bbruNkqIirjjvPC4/91xqKyuHXXf21KlEokPXZwyFEOUpZKhoek9u+hvbduP0eHudXmqryqitKMVg0GdwxiMTiUbRpbHi/sHHPs5H1utp5yAHeYFqljCDNRzlTfbwb6ayEgv9u+9lSphHOz0EG+uIdrSjLbJjmbM4KcK8xenEbDT2WpNd8Ocn4iWufS7mwu3N+Pa8TckZl4roeBoIdigYxyjKIfPCvIdsiJ4ng5aomfI05ZP3JZ+j5c93BzhWLx093a0rEBy2V4hAMBn48Ve/yrqVK9GOcgELsHThQp76wx/GPLYQ5WlmUG56LEZTq5Njx1vZumMfoXA07pteFc9Nd9htWVPp3tjipKo8vS2o73/sI2xYvxELdup4kwIqqWYxDWylk+ZBohzSL8wP19fjemUTxpoZGCqm4D+8m1iXl8JT1owqzB9++mn2HDqELMtIkoQkSciShK2wkA9deinf/vWvOVxfz/e/9CVu3XIYbcBPV4cTz6EdWGYtQmMpwLPleYqWnSkEeZoIdig4ZueuTWqui/OWiJnF5raMbDsfhblHhT+qGr4nRfvdeh+OgXcoBYLJxrmnnz7scy6Ph3+/8gofuvTS3mXDWYsOhRDlGUar0VBbWdavQ2Znl59jja1s3bmfdncHEhLlpcVMqSqntrIUc4aiFPVNrdQk2MlzIvRYJ87hfTSwnaO8gQ4jxSTHrH8iNLW1ceUtX6dg0amYpswGwFA1Dc+bz+F993WKlqwZ9iLhgvuepPWpBzHPWIBsMIKqoqrxiGrUc4A//OsJ1FgM2WDkxm99G72jEltMwVvsIOJuJdRSj3nmQtRYDG1hSVrf90jkewpLJKCiNY1PmGRLtLwv6bJSTHYKSzx9JbWNg0YiV4X5cRVeReaoGpfVqyWF01F5QJVZh8L0MXyk/YEgJmPmrFcFgkzw/d//fszrHjp2jL2HD/cT5eNBiPIspMBiZuHsaSycPQ2AmKLQ0u6mvrGFHXsP4w+GMBn08ZSXyjIqSkvQaCbuGz4ax5vbWHHyvJRvZyh6hPlUTs3I9ociEo1y6Ve+hmXmwl5BDiBrddhOPRvn849ifHQXUDVImPcUhhqrpuE/vBvr/GWYps1F6lNBGKjbj/e9zaCqaG0OdCXllFqL6SiyEdv7TlzMa3XoS6sItzdhqp2Vtvc+GvkqzHsumnKtFmQ4ssnjfKwopL/QcyC5JMxVFf6oyjyPzNkorJQUQsC9qoY6FN5E5rdSlNp/Dm2B2Jc2VwelJeKOnGBy8fDTT4953crSUj5+1VUJb0uI8hxA06cL6cpT4sv8wRANTW3sOVTHi29sI6aoOIoLqa0qY0plGUWFyfdzD4WjGDLY3bRHmGcL6775Q2SjGfOskwY9J+v0TPMvpY43MVOCDmOvMO/r1FJ4ympM0+bSueNN/Id2UbD4NAylVQCYps4h4nURcbchyRqCjUcxLyynzWhGV1JOqPkYptpZaAuKiHV50/a+x0o+CvNIQEVnzg9B3kM6hHmyouURRUYrKUmY0cTJFWGuAq1IlADnSgpTuz++HSj8RZW5VYoxfxhP8oG0uTyUTrCbs0CQa2x79NG0bSv14VVBSjAbDcyZXsM5q5fxofXncv1l53Lq4vlEIlFefHM79//zvzz0+HO89Oa7HK5vIhyOTGh7Xf4gZlPmb1tmi7vKOb96kK6DOyg6ZfWwUVMrDkqYSj1bUYlH9jas30j5o+5+6+lsDorXXIR14XI8bz1H1HdCyBYsPBVJo0WNxVACPmL+TpAkChYsp3PHm8SCfmSdHiUSTt2bnQAPbi7iwc35E1kLehSMRYkdNjfVZa+Y7+vSkirkc9ZMeIy2qAlHFjmvVF2Z3hqbRJAluFWK8QEpxm2qlkdVGUWF81H4vhTjykefHH2QbtqcQpQLBKlERMrzBEmScJQU4SgpYumiuF1VJBKlsaWdY02tvLV9D+FIlAKLKZ7DXlVG6TiKSOubWpmSgXzyoRhKmA+MoKey2PO8Pz5Kx9YXsc5dgsY8uLNdX9FdzgIO8gJODuNg5qB1Wi4rBro7dlZOJTZnMZ073qT4tPPiy2UZ28pzCNYfhDYdEX28nkDvqMA8axHOlx7H4KjMWFOtsdIjzHM9ch70KhRUpM+BKJ3kQsS8JZIZ55WRyIWIuSTBuaicRJSfqxreQsOXpBjnj0OQA7g7OkU3T4FgBA7V1/Pbv/yFn37tawm9XojyPEan0zK1poKpNRW9yzp9fo41tbJt1wHaXB4AyuzFvWkvVotpyLHqG1tZNHd6OqadEEOltqRCmJ9/7+N43noOTYEN88yFg54fGAWXkZnCCg7yEiBhZzoSEiG6cHGUjkePE9aHUWNRCk9ahWwwDRLYslaHefp8iiqnEVZP5NJauxsE+fZsRVdcmtT3mSpyPaUl5J2Y80o2Fnz2JduFeWvEzDJLS5JnNHFyQZgDVEjwfWI8hsyXVC137drF0oWDj2PDEVMUNGPpnCUQ5BGXf+5zY17X6fEgT+A7IkT5JKPA2r+IVFEU2pwejjW18t9XttAVCKLTaqkud1BbVUZ1uQOdTktLu5uzV2d3y/ZUC/Pz/vgo3ndeRkKiaMnafmkrA8V4X4wUMoszOcYWnBwmRgSFKMVMYQrL6TinCiUcxr35P6jRCAULVww5jikSwW3qf9FkrJqGoTLzLjTjIZeFuaqArJnYXYmeNJZsFefZLMxdURMlGXReyQc0ElyBQhh49Z13xizKYzFlTL7MAkG+UVJUNObi/kWzZ3PpunUJb0uI8kmOLMuUl5ZQXlrS66wSDkdoaGmn7ngLm9/ZRSQapanVxfZdB6mtLM0q7/SBJFOY9x2nYV0Mz5YX0BWXYTv1zH4uKSMJ8h6MFDKbdfhoR48ZPZZev99OgwnZYKLkzEvp3PEmhsopQ48RjRLSDP7K5qITSC4K81hERdYm72+d7VHzVJOIMFeJ50hnI7kSLe/BgcrORx6G68d2bHR6vJTYROqKYPJxz3e/m7ZtCVEuGIRer2NGbSUzauOtY9tdHbyy5T2MBj3v9Et7sfV6rBdYU18olim8NOF+7R0KTl7Vz3ZwLGK8LxIyBQyfl68xmLAtP2voJ3vSVnJQgA9HrgnzkDfxIs/hyNaoeTZ6mIcUGV2WOK8MRy4JcyMQBuovv3iMdogeSktsqZ6WQDCpEaJcMCr1Ta3MmlrNwjnTWDhnGtCd9uLqoL6plWdf20pnVwCdVkNVuYPaylKqK0ozap+YLIJ4qWcrttPOR19yQlCPV5APR0+h52jolBgRces4owQ7ki/Ke5jsUfOx0BoxU67ryvQ0RqXHkSXbxbkJaCN+vT8WYd7m9DBzalVa5iYQZDuKorBj/36a29uJRAa7212SYAqLEOWCUalvauWMUxf3WybLMuWOYsodxSw/aS7Q3+1ly3t7CYWjmE2G7mh6KeWO9DQ5ShZRwhxhM5UsIpJBQQ5gjkTwj6NVryD5BDsUCqtTd8jMtqh5tkXLWyIWyrLMeWUksl2cn4LKD5DYh8Q8VOovv7jf8wNFepvTw6olC9I5RYEgK6k7fpzPfe97NDQ39y7r21hOp9UKUS5IHR5vF0UFllHXG8rtpSsQpKGpjd0H63hhc7zJUXGRtTftpcRWkPSc6GQUdn5k/X3U8SaFVFDCNEiSEO9L+aPuMQtzUySCxzi0M44gPURDKlpD6tOHsilqnk3CvDViZqbRk/K5JJtsFeevIWEHqhn6szYweh4KRzAa9GmanUCQvfzgD38gGo1yy8c/zuZt25hSWclFZ55Ju9vNt3/zGx75xS8SHluIcsGIRKMxtBo5YeFsMRmZO6OWuTNqgfjVpNvro6GxlTe27cbV4UVCosxRTG1lKTWVpRRYMpufvmH9RprYCUAVg7t1JpPhhPnA5cZolKA2/76uuZJXrqpqWtP5sy1qng5GE+aemIEiTSiNM0ou2ZRv7lThp6qWb0lRCsbwuVZVtbcBmkAw2dl18CD/e/PNXLB2LcFQiMbWVubPjPchuXTdOn73179yy8c/ntDY+XeWFySVplYnlWXJ61onSRIlRQWUFBVw8vz4hzimKLS2u2loauOZV97G5w9256fbqakso6bcgSFNEZoN6zfioo4OGpnN2UhpaHo7sJHQoPSYPCzyzDXCPhW9Nf2pV9kgztMVLYcTXT+HE+fZ6rwyVjIZNY+p0AK8h8Q7avyz/ANVw9mqwjxJZS4qlQx9mPH5AxkPlggE2YKtoAB9dzrpzNpaHn/++d7nTpk/n5/+6U/ckuDYQpQLRuRYUyu1Vant5KmRZSrL7FSW2VmxuNuWMRKlqaWd+qY23n5vH6FwBJNBT013NL2y1I5Wm9zCxw3rN9KFi0beYxZnoiW9t2oHivGeaLlOUUSRZ4ZJZZHnWOgR5z3kewR9YNQ8oGgwyLEMzii5pDtq/o4q8SdVQxewAJVVkkJMBQWolOBNVeb+bovWW4kxR+r/+WpzCucVgaCHOdOmsX3PHs5etYqVixfT5nLx7Ouvc87pp7N15046OjsTHluIcsGINDS1sWzRnLRvVz9Efro/GOJ4UxsHjx7nlbfeIxpTKLSaqakopbaylFK7LeFOWhvWbyRCgDreoJZlGClM1luZMKZImIA2f4s8cyGFJdihYKvNnsNluvPO0xkt76GvMG+JWHLCeWU8pEOYH1XhXlVDMxIflWKs4kQa1snE+Lyq5SZirO8+bL6pSnxL1fC/xFjQR5i3uTyU2m0pnatAkCtccf753PHLX/LFDRvQ63Rce9FFfPUnP8FWUECHz8clZ52V8NjZc5YRZCXZVNxjNhqYPb2G2dNrepd5O7uob25j+55DtDk9qKiUFBX2RtRLikYvJN2wfiMKCkfZjJ0ZFJE9tl/lj7qRztGIIs8ME/Yp6K3ZlTsxGYR5D60RM+Xa3HFeGSupSmdxqvCgqmELEldLChcQQzfg4+uQ4EMo3Kpq+Wq3CF+KigUYmLnf5uxg7oyhm5oJBJON05cs4aGf/aw3CPiZD32IQquVrbt2MWvqVD5+5ZUJjy1EuWBY/IEgJmN2CPLhKCywsLDAwsLZ04B4QZLL00lDUytvvHOikLTUbosL9YrSfk4yPV07FSIE8DKDtZl4GyNSdMxP84L87qSX7dFyVQUpCxOa812Y90TLWyJm5hpdadtuukmmOH9dlfiVquFcFH4rxRjpWvJiSaEcle+pGr5DlJ3IVKKyZED6isfro3AMDlwCwWTBUdzfoOH6D3yA6z/wgQmPK0S5YFjqm9qorUxtPnmykSQJe3Eh9uJCFi+Id99UFIU2p4eG5nZefGMbXp8fWZJ5/ZljGGwyQV+MxugOJCQiBNCQTaki3bebJ0GRZ7YK82hIRaPP3r9/JoQ5kFZx7o3pKdSE07a9TNEjziFxgf5PVeaLUoxTpbF9JpZLKjcT46uqFgn4mRQF+vuUq6jIk+AYJBCMhRank2ONjaw4abA722/+8heuuuACSktKEhpbiHLBsNQ3tTJ/1tRMT2PCyLJMeWkJ5aUlLDspnh+/4bL70Zo1aCxhmNLEbG0tRnUR0S4NEV+MSJeMGsv8SUjWQywsjcvTPJfJRmEe9Ga2yHMsZMLbPJ0e5tJzMEaNmTf0FegwNpEeVeEAEicNY184XNfO64ArwmHCkQgFlv4R8Ugkii4P7VgFgkS58957iSnKkKK8vrmZX2zcyHe+8IWExs7uM40go7S0uahwJHa1l81sWL8RVIlQl8LO1tdpPtxFcH8ZHYcMhL0atGaVwmkRiueEKJoVxlIZRVcQQ5LTrwp0FoWIL/41TVYn0Wznwc1FmZ5CP4Ke7BflmaInap5KfAGwGE/YJU5Wqq60DxLqA9FKMBuVXQwOKAwnyHsw6PWDBDlAu7sDR3F2fScFgkzyzq5dXHzmmUM+d+7pp/P2zp0Jjy3ONIIhUVWVmKKi0eTXR6Qnh1xFoY43MFJEBQuRkECRiPhk/M1aOg7pce834D2sI+KT0FtVCmd0C/WZYcwVUXTWGKRYqOssCpGuE/tgsgjzbCKUA5FyGGybmC5SLcxbPFDWfZNosgtzGF2cXyYp3KNqCPY5NI0myEcibocoRLlA0IOiqoQjkSGfi8ZiBEOJNznL/jONICO4OjopseVXceEJQa5Sz1YkJGpYEhfkw6AqEuFODV1NWjoOdgv1ozqifgl9oYKtr1Avj6KzKkm9z641qUT9/ec3GYR5NkXLYxEVzUDriiwlH4V5ixsqbCceC2EeZzhxvlpSmYnKfd0NgiYiyAHaXB3CDlEg6MOCWbP421NPoSjKoOf+8fTTzJk+PeGxhSgXDEl9Y2vOFXmORF9B3si7hOhiKisT6tipxiTCXg1djTo8PUK9Tkc0KKEvjGGbFaF4boiiGWHMZVF0lsSFuiSpMMRFw2QR5pkW54qiIomjZEbpGykXjI2bpRivI7NfnfhFWpvLg0M0DhIIevnMddfx3r59fPiWW3j8+ed5e+dONr34Ih/52tfYumsXN119dcJji+oNwZDUN7ayesXgIoZcpEeQx4hQz1aihJjO6chJ/PirUYlwh4Zwx4nOm7JWRWtRMNhiWKpUJEklFo2nyES65HgEfISTpqxTiUWGf14Uf6aecKeCoUCo8rGQqsLPrgBYjUkfNq8pkOAKFB5RZd43wbEi0Sh6nZAKAkEP82bM4K7bbuPbv/kNd/zyl0iShKqq2AoL+d6XvsTShQsTHlt80wRD4vb6KC60ZnoaScNLMw1so5ByprACmdS3rVeGEeo6q4LRFkM7ilDvW+Q5HEKYp5ZgR27kk/eQbgeWgSRbmKvdb0e48Q3NSI4s56LwN7S8ednFrHw0sRQWVZ1kljcCwRhZs2wZm37/ew7X11Pf1ERlWRmzpkzBoJ9YbxchygWDiMZiaDXyqJ0wc4FgKEQ9W+mklVqWUkB5RuejRCVCHg0hz8hCXYlKyDqVQLsmnvoyQkRdCPPUEexQKJmRTb71g8m0EB9IMoV5ZwAKhkhX72kqJBgekwQXqgp/VjVUXnYxUxIQ5h2dXRQV5E9wRiBIJjqtlrnTpzN3AjnkAxGiXDCI5lYXFaX5YYXo9Hjw0oyVUkzYMj2dIRlOqNvmhNEaVWyzIr1CPdIlx6PqA1JfJoswTzdhv4rOnJ0Xp9kmxvuSLGHe7IYK8bEekrH4ll8tKdymaviVquGqyy5mxTiFeZvLQ5ko8hRMct567z00Gg3LutNS/vvaa6O+5rzVqxPalhDlgkHUN7VSW5UfRZ7V5eXM4zya2cUe/oORAgxYMQz4mY50lvGgRCWUKPiOn4jSSloVnUVBXxTPUUdSUWMnUl/K/+Wi5QP5cTE1HOmMlquqCipZeccomwV5D8kQ5q0eqB7G/U9Ey0dHL8E3iPEPVeZ/VC1z17+f7/3xXsrtI/ud99Dm9FCeh70qBILx8L933YXJaOTx3/wGgK/99Ke9eeRDIUmSEOWC5NHQ1MYp3S3q84EHHrsBALfXy9GGBuoaGzl6/Dh1jY28/uabhOlCixEb1ZQzDw0TywlLBrJORRlQ5DlUMWmvUC+MYalQKd7VjL/agF+nI6DTEdDqUOTcyYkeC+kS5tGgis4kBPlEmKgwb3HD0vw5FCWFsUTI+1IkwY2SwodVhYdVmY/feAPf/v4PWLJgwaivbXN5WDR3RqJTFQjygu984Qto+pxH7/nud1O2LSHKBYMIhsOYjIZMTyPpFBcWUrxgwaCT0UfW30eILlrZy16eYQEXjehdng4GNg0ajiGF+iGV4Pk6zJEIdr8fWVVRJKlXpAd0OmJ5JtRTQa4VeeYjgTCYRzgUTaZo+XjF+EAMEnwIhUpUvnLbrXz0hhu5/v3vH/E1Xp+fAotpQtsVCHKdVYsX93u8bALuKqMhzjiCfgSCIYyGzEeK08n9j23ASAEa9BRSkXFBDqCzju68MhxqTMLylJ82i5VjtmKOFpfQUFiEX6fDGI1Q1dnBNLeLqR43Zb5OCkJBNEosye8g98lFUZ6p5kEjkWhjobEaf0yGZkITFeQ9SBK8T1L5iBTjrT/dM8bXZN9nSiDIJJ/8xjc4VF8/5HOvb9vG5yYQSc+tM44g5TQ0teVV06Cxcvtda/FQTyWLMj0VoLuTZ2BiJ8O+DYYUWaZLb6DdYqW+KC7UjxXZ6DQY0MdiVHZ2dgt1FxWdXgqDQXSx2NiVUR4S8ioYCrPrEDlc6sqmOqlXkOeLMPd0gc2SgslMclQVnldlTpYGdyPsSygUxqDPbuchgSATbNm5E19X15DPRSIR3t27N+GxRfqKoB/HmlqZO6M209NIKy+8+Sa3/OAuKliIluxI25FGsUEcKyO5sqiSRECnJ6Drc2dEVTFGo5gjEcq6fHFhDoS0WgJaHX6djrBGMymMo5UYyJrseJ8j5ZFnowgfivHml7e4oXyMziuTKY1loryKhBuJcxn5grvN1UGp6OQpEADwzq5d/R7vO3KEWKz/HeY2t5sHHn+cooKChLcjRLmgH82tLs5aeUqmp5EWWl0ufnz33byyeQdTWIGV0kxPCRi9k+d4GZddoiQR1OkI6vpEyFQVQyyGKRLGHujCEI0fiCIaTbygVKsjqNWmTaino8hTiarIWWLIM1ph58VT1UHCfFOdlFMFoUPR4oHp42grkM/CvOrKE24pE01leV2VuUKKMW0Ue8Q2l4dSYYcoEABw4+2396ZySZLED+++e9A6qqqi02q547OfTXg7QpQLelFVlZiioNFk1y37ZLJh/UZUVFwcoYld2JnBHM7JKkvEsRZ5jocJ+ZhLEiGtlpBWi6dnmaqiU2KYIxFswQDGaBSAqCz3KSjVokrJfR/pskMMZknqSq4L64GMJ1re6oGVc8c3fj4L8x56BHqi4vwIEl+869ejrtfm9LA4j1y4BIKJ8Myf/oTX56PD5+OG227j09ddx4yamn7rmIxG5k6fjt1mS3g7QpQLenF3dFJclL/d2zas30gQLw1sQ0VhJmdgoijT0xqEzqIQ9CT/IiGpDYYkiYhGS4dGS4fxhDuDpluoW8MhHP6unHV+yaUiz4FR8mwX8mMV5qEIGBOoOZ8Mwhzi4ny8wjyggtNgZNoAMTEUTo8Xu60w0ekJBHmFo7gYR3H8/Pn+s8/mgjVrqK2sTPp2hCgX9FLf1MaUPC3y3LB+I26OcZx3qWA+dmZmhcvKUGjNKtHG1Mwt1Z0/Y7KGToOGToOxd5msKJiiEUyRKMXBABpFQZUgqNUR0GoJ6HRE5OTkqT+4OX6RNdGIesirUFCR+SK38aahZLsg72E0Ya4oE/s4TCZhDmOPmh8HplRWotWMftEfjcXQarPnDqJAkC1863Of6/09GovR0dlJSVFRUpyKciMUJEgL9Y3508mzLxvWbwSgjQNMZSUOZmWtIIfkFXkOR19XlpHWGct6Y+GE84uF+iJbt/NLMR0GIxpVpayri2keN9PcLqq8HRQH/BgjkUHOLyMJ7Qc3F/UK8p7HEyESUNEas+MzMlIhZ9/nckWQ9zCSI4vLByUTvGknn7NmUtglQv+c85HwII3p1rqiKMhJTj0TCBLhlbff5pT16/nmL34x7DovvfUWp6xfP+jf69u2pWxeT7/yCld+/vOsuvpqzrvhBvYdOQLAY88+y479+xMeV0TKBb24OjopLkq8ajibiRAkTBdWHJmeyojIWpVYNPVicKwR81RF1tU+BaXunuwXVUUfi2GK9s9Tj8kyfp0OvzOGoUhGo+3/9xlOgCfa+VNVVZCy3585EUHe85psF/DjcV4RxBlLOosPKLSOfrXj7vDldSqjIDeIRKP87N57+3XTHApvVxdGvZ7ffutb/ZbPrE2Nk9ymF1/k//3qV1x70UV86oMf5Cs//nHvc8dbWnhpyxZ+fuutCY0tRLkAgFhMQSNLWS9EEkFFxc0xzNiRsvzm0ESaBo2X4QR3siLk40aSCGu1hLWD89RNkSh+VwDXkShKTEWWwVAos7mpAK02RlSWk+b+EvGr6M3Z9T1Ihu1hNlon9kTLB6aytHpgTnVytjFZUlnGggnwB4OjriecVwTZwF+feopINMpJc0eu+O7o7MRRXMyS+fPTMq8HHn+cT159NZ+4+moUpb/f/8lz5/L4888nPHZ2KxRB2mhuc1FROrZboLlGOwdwcZQK0vOFnQipcF4ZiZ40lb7/hlonk8RkDT6Dgf+0O6hZbmDKSiNVSw1YyzToYjHKuzp7018qO73YAn4M0Xj6SyJpLLlU5Jko2SbQB6aytHqg1Ja88UUaSxwrcQEzGm1OD2XCo1yQQVwdHfz+r3/lE1dfPWoNhNfno2QCjifjpb65mYWzZw/5nKqqY7rwHY78PvMIxkx9Uyu1ldnh051MvD4fLexjOqdhpiTT0xkVrVkl6s8uwZRN9IhsWSNhKtbgMls4XhjPUz9qK8ZpMqNKEsWBAFM74kL9padVXIcj+J0xYpHR0zbiolwUuKWbvsI8EgV9ku/jThZhPhLTUTlcX4/L4xlxvTaXB4eIlAsyyK8ffJDaigrev27dqOt6fT7aXC4u++xnOfWqq7j2f/6HV95+O2Vzm15Tw1vvvTfkcy9t2cKsKVMSHlukrwiAuCg/ed6MTE8j6Vzx4W9TSCUGciNXPtVFnomSateWRBgUBR8h/cVzLMrq6s54+ktURepOfzEVyRiKZHSmE6lboU4FfUH27YPhSDQ/PFsbDMUUSJVrZl9hnq8pLSPllpslWOn38c9nnuHjV1017BhdgSAWk3HY5wX5x8uNEruV9B332puH39bew4d57Nlnued730Mew8FgRm0tx5qauPrCC5Elifsee4wvfv/7PPCTnzB/5sxkThuAD7///dx2550AXHTmmUA8sn/33//Ov557jh9/9asJjy1EuQCAQDCMOc8OwlesvxM3dczhnExPZUxIWhUlDUWeiZItwny8BZzx9BcN/2k3AHEXFyWmEupUCHoUfAcjRPxxcaozS4R9CiGvgqFARtZk7/4Yj6AeLl0l24S5u8hMpM6PPQ322JM11/xKKcYtDz7A+nPO6fVdHkg2u1MJ8p+f/PGPXLB27ZhzxK++8EKuvvDC3sfLFy3i4ptv5i9PPsl3vvCFpM/v/DVraGhu5vd/+xv3/+tfAHz2O99BI8vcdM01nL1qVcJjC1EuIBgKYzRk3pM5mVy5/i7qeJMpnIqO3LjY0FnSV+SZKNkkzCf62g+d1oHJdiJNRVXjQj3UodDZHKP9QAQ1BrIWjIUyxiIZY5EmK6wSx+u2Mto62STMD4X0lBeH07KtfBXmI0XLayQ4TVX5yw0f4fOPPjHoeX8whDGRrk0CQRL472uvsfvQIX7w5S8nPIbZZGLx3LkcPX48iTPrz41XXskFa9eyZedOjjc3U11eztKFC5kywYZCQpQLaGhqo6Yit/PJe7zIVVQ8NHCc7UxhOQXkju+6zqoQTkEnz2TTU/iZDeJ8IgyMuEuSRCwM1kotjlknLlJjUZVQh0LQq+BtChMNxi0T9eYeoS5jKJCQ5PSI9WQK8r7rZoswb3cqzJllBBIvlhoP+SrMR2KWpHJgmDS5NqeHMntuf7cFucsj//kPgWCQ8264YdBzjz//PE/94Q9UlY1+Xg9HIljNw/dCSAbV5eVUl5cndUwhygXUN7Uya1qS/McySAeNODlMGD8zWIOZ3Dqx6MwqXSnq5JkK8kGcDxTmQzmvaLQSZrsGs71/VD3SpRLsUPA2Rgl1KqgKaHQShsITYl1rSO/+zDZXlURwuVVKiiXoSt82e3LN80mcjxQtb1fBxNAXYW1OD6UlE2u+JRAkyu2f+tQg95Jv/frXlJWU8KkPfpDSkhK6AgFMBgOyLOPz+3l92zbOW726d/12t5vte/bwoUsvTdk8VVXleEsLbW436gBbRIClCxcmNK4Q5QKaWp2sXXFypqcxYZrYSRFVTOM0ZLI/4jyQbC3yzHf6prMEOxSKakY/LEqShN4qobfKFPa5no1FVEJeJS7Wj0eJhlUkQGfpFuqFMvoCCTnJUfV8EOM9KApotRLuIvMg//JUMxkKQaMqPIPMd6XokM+3uTxMq52X5lkJBHFqh0j/MBuNFFqtzJ0+HafHw8U33cTqJUv42de/zs4DB7j9rrt48a23WLN0KZIkcfff/47FbOb6D3wgJXPceeAAt955J8dbWgY9p6oqkiTxzj//mdDYQpRPclRVJRpT0GpzT8QOxEwxWgy5KcizvMizbzQ8077lqeLBzUVMc7uoXpr4ftDoho6qh7viKTB9o+qyVsJYKMXTX7qj6mNp3tU31SSfxDhANKrS15I4E8K8h3xNa9mGRBkqU4b56LjzuLOzIPfR63SUlpRQURpPuV21eDF/+v73+eumTfz2oYfo7OpixUkn8ZUbbhhT99pE+P7vfkcgGOQz111HTUXFqD7q40GI8klOR2cXtkJLpqcxYUJ04uYYlSzK9FQSIt1Ng5LJQJGes+ksalzo9o2cJwNJkjBYJQzDRdW9Ct6mCNFQtwOMSeqNqhsKh3eASaYgz5Z8cpdbpdjW/30JYZ5cqlFpQsI/zC5XFHXUtuYCQTq557vf7f29wGLhid/+tt/zi2bP5rtf/GLa5nOsqYlvfPrTnL8m+b0PhCif5NQ3tlJbmTvFkMOhogISWgyZnkpC6CwKYW/2RvjHEx3P1VxzQyxKUHvikDhe68XxMlxUPRKIR9V9LTGcByMoMZA1cV91Q2FcrD95VGIMQfWco92pUOoYLAiFME8eVRKcoqr8F5mBzctjMQWNRghygWAkFs6eTSicGoco8e2b5NQ3tVJblduiXFVV6tlKFYuQcvQjrbOoRLryS2WVP+rOqVQXUyRKUNvfGnQi1ouJIEkSerNMQaWW0nl6alYYmbLKSNVSA9ZyDbGwiutQhPq3Qhx7I0jj9hCuwxG62sfWrTTbaXcqOOzZ9x3O1W6gVVfah1x+nqTw6hD1K06PlxKbSF0RCEbiQ5dcwt/+/W/CkUjSxxaR8kmO0+PFbktDp44E6LE57Mt9j10/aNlVl91FjDAOZqdjWikhn4s8s8XbfDRM0QguU2ottBJF1kiYbJp+vuoA0aBK0KsQcCt46qLEIiqSBHrriaj6aIWl2ZK6AuD2DE5f6X0ug9FyyN2IeY8w7+vEsgCVBiScHg92m613edx5xYZAIDjBXffdN2hZu8vFp/7f/2PmlCmDnpMkiVs/+cmEtiVE+SQmpihIjK24LN0MJch7lvcV5hvWb6Sdw5QwPWe70GV7kedkwRCNEhqiYCfVaSwTQWuUsBo1WMsGFJb64mLdezxKyKegqt0pMAXdvuqFMjpT9n33VZWkO9Mkk1wV5tDfIlHXncLyytatrH/f+3rXaXN5mDm1KlNTFAiykvsee2zI5a0uF+/s3j1ouRDlgoRoaXdTXpp9EcwN6zfShQs3RwniRUKmkCpsVKPDxEfW38+P7r6Qz33iQYJ48dFKDUsyPe2EyeUiz7xjGJGazcJ8IJIkYSiQMBTI0KewVInGhXrIq+BrjRAJqKDCfw5KlDokSu0ypQ4ZY4Y6lkYiKtpRzkiZjpZD/tgmrpAUXtmypb8od3pYtWRBBmclEGQf2x59NG3bEqJ8EtPQ2MqULCryjEQiXH7Vj/DQQJAOHMzERi0xInRwnBZ2o8VAjCiXfmITeixoMTCVVWjQjb6BLCXbizxHoyc1JZfyxweiUWJE89xxQtZKmEs0mEv6f9bWOBTanAotrQo790QJBuPXJkVFcaHucMjYSyR02tSKdadLxV6SW/sg15oO9Y2WL0flnvfeIxyJoNfFj5+hcASjQZ/JKQoEOU0sFqO5vT3hTp9ClE9i6pvaWDh3eqan0csHr/o1TeyggoVMY1U/v/EiqlCIEaYLGQ06zDmbrjIQnVmlqzk/3stQ5EQ+eSRKQDfyhV0uRcvHg8UiYbFomDalfwqMp0OlvV3h8JEYW7YqRKOg0UBJsUSpQ8Zhlym2Ja8RUrzIc/SxsiFaPpBcTGspkmBGbS1v79zJ6UuWoKrZU1sgEGQzSy+/nHu//30WzxvcZOulLVv44yOP8OBPfpLQ2EKUT2L8wSAWkzHT0wDiKSsSGrQYsTP0hYKMBiPZWZQ6IWQVlNwV5bkcIe/BFI3QpZt8EcLhijwlSaLYJlFsk5k968TyaFTF5VZpdyrs3B3F06GiKKDXg8MeF+qldomCgvHnq7c7FRafJE5JqaZvtPyM5ct5ecsWTl+yBJ8/gNViyvDsBILsZ6QLWJ/fz9GGhoTHFkfASUooFO69ZZlpNqzfSIwobupQUTI9nbQiaVTUWO4K8nzBFIngHIPzSr5Gy8eKVitRVipRVto/zSQUVnE6FdqdKkfrYnT64icto5HeFBiHXcZiHv6z7ulQsRWJ70K6UFV4d98+KhwOQDivCAQj8Ye//a3f48eee443332337I2t5sX3nyTaTU1CW9HiPJJSkNLOzUVpZmeBhvWb8RLM8fZhhk7Mzkj01NKKzqLQsSXW3m0+Yisqih5nlM+kGRaIRr0ElWVGqoq+y/3B+JR9Xanwr79MfwBFVWFAquEwy71RteNRglVZczR9WxMYcklqq60c/BhJ6+8/TavP/QQEHdeKbXbMjsxgSBLeerll/H6fHR2dSFJEo89++yQ682eOpVvfOpTCW9HiPJJSn1jKzNqK0dfMYVct/5uGnkXP25qWEoBiRVG5DI6q0LYO7nEYLYhqeq4LOIne7R8PJhNElNqNEyp6Z+v7utSaXeqNLUo7Ngdxe9XaWtXeP6lcLdQl7DbZQx6ETlPBY3/cKIBDHo9ZlM8ZaXV6WHujMGeywKBAB779a97f19y2WX88vbbOWnOnH7rmIzGCWcgCFE+SWlqdbJ6+aKMbFtRFN5/+XdoZjclTKOW5f2KOicT8SJPmQhBOmkhQpAu2rAznaK+fnY5zFibB2WqyZAxOriTpyB1SJJEgVWiwArTp8a/98cbY9QfjzF/jpZ2l0p9g8K296KEw3EnGFtRPKput0vYS2T0uuwT67lS7NmTT64SPxb34O3sorDAkqFZCQS5w7c//3kWzp5NUUHyu98KUT5JicZi6EYzBU4BB+vq+MgXvg2ozGAtJtLbxjybiBEhJHdyQNlBCC9WyogQxI+TYiZXxKqnWLTnZzrFuSkSITDO74KIlieXdpdKqUNDUZFMURHMnH7iIl1R4k4wTqfC0TqFrduiRCJgiIG9AMpsUG6L/9SJM9qYaQCmVp1oFKSoKnKWNZMSCLKRS9etS9nY4hA2Ceno7KLQmp524j2dORVitLAHJ0eoYCH2HO7AOVFUVDpopFWzi/mxhZQzDyulRAlxgBeYzmoKqcj0NJPKSFHwodxb0hk1N0YjtJtFhDCTtLcrTJsy9OlIliVKiiVKimVm91le6Pbj6oQWN+xtgFd2QTQKsgz2whNivbRIiPWhOIzEvBkzAIhEohkJ0ggEuYiiKGx66SXefPdd2txuVKW/QYUkSfz+299OaGzxLZyE1De2UpuGpkE9gryTFhrYholi5nIOOia37dZxtuGjndmW5dx43fv4w3e2ESXMEV6nlFl5J8izHX0sRlgz/vQpES1PHt5OlcKC8V2ka+S44C4tgr6JeDEFnF5o9cCeenh5J0RjIEtCrMMJS8TDqsS86XH72XZ3B47iyXvXUiAYD3f++c88+MQTmI1Gyux2tAmcP4ZjEh6SBPVNrSw/aW5Kt7Fh/UYiBGliBz7aqeEUCslsYWk2ECOCm3oWcBGf+Mwyasod3PfY9Zyz/isoRIf1aM8HBka/R/M3T0sqS4/frLhtn3HG62s+HBo5LrzLbIPFem9kvR5e2QmRbrFe0icNptQG+jw/M1ZdaWff3z1cPituQh+3QxSiXCAYC/9++WUuO+ccbr3ppqTfYcrzQ49gKNrdHdiTfADuiYpDPD3DRR3N7KSYKczlXDTj/KgdZztBOjFRhJEirDjQk/spBm6OYcHBA4/dwF+feJ7Tli4E4LG/fJuLr/sqTeykhqUZnmXqSKTRUCrFuU5RiCQxyiEYP4GgijENPcz6Rtb70iPWWz2w/zi8thsiUUCCEusJgV9mA0Oe1AO3+hXa9BpOnhsPzrS6PCyYPS2zkxIIcgSz0cjZq1alJOVLiPJJhqIoSEhJLejpK8iDeGlgGwoxZrAGE7aExuygiQLK0WCgkxaa2MFszkZPenLhU4EfF83sZhZnAhCJRtF33z//zHWPYKWUICIdYjhSkWeeSJFnX0QKy8RpdyqU2jNnC9pXrC+cemK5ooDbFxfrh5rgjb0QjsSfK7L0F+tmQ/rnPRFeaYpyeoW2V1S0u0T6ikAwVlYvXcrbO3eyZtmypI8tRPkko9XpoSyJDSL6FnK2so92DlHOfBzMnFAhZy3LOMZbTGMV5cyljjfxUE8ZqU27SRURghzlDWpZipFCPnrF/Vx0Q9xhpedvGMSbF3cDkkGP+B4YWU+2MDdFI3gNOaaoksSmOimpDYQSpb1dwZFBUT4cPQWj9kKY38cMSVHB2wUtHqhvg60HIBACta2dAs0MyrQBSnV+ynR+rHIkKzOjXjoe5ZLpJ8L+fQMEAoFgZD774Q/zkVtuYfmiRSzoTgEbSElRYhe54ls4yahvbKWmKjlFnj1i0kcrDWzDSCFzeF9SotkFlFHJIlrYy1RW0UkrFWTGV32iKMQ4yhuUMK3Xe1xnUXjhiSNsuru+dz0frUxlZaammZW0XFacUMrLWDFGo7RarCkbP9vZVBdXjJkU5+0ulVkzs1C5DoMsgc0a/ze3u5u28uyrqHboVHS0Rcy0Rszs9DvoUnSogEmO9hPrRZoQcobe8hFvjN3uGD88LV5wr6iZvzATCHKJ677yFVra2/n897437Drv/POfCY0tRPkko76plfPWrhj36/qmqPQQJUQjO/DRSjWnUETVEK9MnEIqOc67dNKCASuGHIwiq6gcZztaDJQzv3e5zqIQ9vWPDirE0KBP9xSzjnR6lMe7eeaOIEwVmYyad3WpWC25vw8kCQo1EQo1Hcw09k9p8se0tEVNtEbMHAra8MTid2d0koKjj1i3a4NopNTuh7t3hfjQHD3m7gZM3s4ubAWT98JUIBgvF51xRtIK0wciRPkkw+cPYrWMz5JwoCBXUXFzjCZ2YKO2u5Bz4hVQKgp+PHTRRhftdOFEjwUrDo6znU5aKKB8wttJJ+0cpAsns1nXL51HZ1Hxtwy8ZS+hojDZSZdHuawoKEKQ99ITNYf0Rc5VVUVVk+e8kq2YNVGmajqZaujstzysyLRFTbRFzLzrL8UZMaEgIaNSog1SqvNTqgtQqvVjkCd+bHAFFV5rjnL78hPngDanh9IkpjQKBPnOzddem7KxhSifRITDkXHlDTo9HjZ89P+IEiZGBIUoClFC+FBRmM5qzIxdPEUJE8QLKKi9/ykE6KCLNvy4e0V4MVOpYRk64rYMtSzlGG+jw0gxtdiY0vtcNqKi0sIe3BxjBmsHXbRIsoqqxIVIlDCNvIuEJHLKRyGZYt0YjRIUDVOGJF2Rc78fLObEBLm7yExxhz/JM0ovelmhWt9Ftb6r3/KYKuGKGmmLmDgUtPFGpJKwGncJKtSE42K9O8I+nrz1F4/HCzzNOgnNdfcD0ObyUO4oSer7EgjymR/fcw8XnnEGJ82Zk/SxxRlpEtHQ0k51uWPY53si4gE6aOcgHRyngAr0mNGgQ4cJDTps1FBAORJjK87y0kQjO4gQwEghEnJ31FhCQsJIEaXMxoJ92PSNQipZwEX4aMPFUVzUMYdzsrIraE/Kih8Xszhr0MWDpFFRYifm7eIoUcJZ+37yFVM0QkA38Ts8woElcdpdCg6H+MwPRCOp8Qi5LgC4eperKnhjetqiJloiZnYG7Phi8WOmQY5Rqj0RWS/WBtEM+NO+3hzlzGptryCHuChfNHdGOt6WQJAX/Pe11/jrU09RVVrKBWecwQVr1jBr6tTRXzgGhCifRNQ3tjK1euj0j+vW300X7Tg5QhAvDmYwj/PRMjFniiCd1LOVWpZTQNmoQv6+x67v/X1g2oyERAFlWCllP8/RRRtWUt+ZdDwoxDjGFmKEmckZQ6b16CwKka4Tfwc9ZkJ0EsGPhsJ0Tjdr6UlhSWWRpykSocOQnLstQpgnRnu7QqkjceeVfIiWjwdJgiJtmCJtmFkD8taDioa2iIm2qJmtXeW4okYUJDR9UmFqijs40NE/Ku/1+SkYZ0qjQDCZeeZPf2L73r08v3kz/375Zf70yCPMqKnhgrVrufCMM6guTzzNVojySURjSzundzer6csF62+jjQOYKaGYKdioQSbxhio9edESMo28Rxlze1vH94juoQpH+wrynsdDrSchYaOWdg5jwTHmiH2qiRHhCJvRomc6q4f9Gw4s8rRRQ5Qgh3gZHWa0GJDRIKPt/hn/vYAyzNgnTTR9KEGezHxzraIQTWLjoAc3xy2whDgfO+1Olflzs+P7m+sY5Ri1Bh+1Bl+/5VFVwt2dClNrd/BscxX3/+L7SLXLKbCYcbq9HDx6nFK7jcICS1J7WAgE+YgkSSyZP58l8+fz5RtuYO/hwzz/5ps8t3kzv33oIRbOns2Fa9dy8VlnUWgdXxG1EOWTiEg0hm5ATvmG9Rvx40FFJYQPJ4fwUI8GPRp0aNF3/x5/rEHfZ5mun/CMEsbJIdo5hAY9tSynC2evzV9f0T1QcA8U5MOt14Od6RyjjYO8RBUnY6Zk3GJVRaULJ27qgLg3eqJECHKYV7Fgp5pTRpyLdogiTwezsDODLpzdufuxPj9jxIhwjK3IaHAwk2KmImfJxUhOkkIbuB5xPhxCtJ8gEFQxJ5hTni0oz76a6SmMiLZPKsx8k8rD27soKzFwjn8vnjN/gdPdgdPjZe+hY3R0dqGiotNqcRQXUWq3UVpShKPEJnzMBYJhmDdjBlVlZVQ6HDz4xBPs2L+f/UeO8IsHHuDGK67gxiuvHHMxu/iWTRJGukU5jVXECBMjTJRIn9/jBZ5h/MTw9D7u+7yM3CvaI/gppIqZnEEnrRzkRRzMQIN2WNENwwvyvs8PFOY90WgnRzjGlt5IspFCjBRioBBN98c7RpQoAcIEiPT510kLEjJ6zMgT+CqE8HGYVylmKuXMG/XiQNacKPLsi4SMldJhX1fBAny00sp+2jlILcswM/kKtJIRLdfHYoS0yYuSC8aPmqQLI3fR4L4IkymlZTxIksTXlxn5+uYAq8q1BMMRZkypYtWSBf3Wi0SitLs7aHN62HPwGO3u94hEYgAUFpgpLbF1/yuisMCS9+45AsFQRCIRXtqyhSdffJHXt23DajZz6bp1/OzrX6fcbucvTz7JPQ8/jKIofPKaa8Y0phDlk4T6plZqh2gaNJogHglVVQkEg3T4fHR0dmK32SgtiYvEDes39uvquWH9xmHzxQc+N5ChIuUQT2NxMAM707ttFF100kobBwnhQ4u+N9qsw9Tvn4ECSpiKgULqeBMTtoT+Bn48HOE1KpiPndGLpQYWeY6HeE59OVbK8NDAEV6nmClUsGBCFxW5SE9qS6Li3BSNENROvMgzEUT+eRyfT8VqTY2Ym2y55uPhFIeWM6q0/PK9IJes8FBaYhu0jk6npbLMTmWZvd9yVVXx+vy0uTy0uzrYfbCOTl8XqgparSYeXS8pwmG3UVpchF6fme+YQJBKtu3Zw5MvvMAzr7+Oz+9nxaJFfOcLX+DsVavQ9XH0uuGKK7CYTPz50UeFKBf0p76xlaULZyd1TEmSMJtMmE0mKkv7R3iHim5vWL+R3/31Kq6/9neoKLRxgBhh7MzkI+vv5/7HPjJoG8MJ8n7zQMJKWb+iTxWFMIHulBvdoOi1ioqXJup4CwsOHMwcz1sHoJNWjvEW1SzB1t2pczR0FoVo18TSTiQkiqmlgDKO8y77eJZalo0YZc9XEo2amyIRPEZR3DYSqe722eZUcdhFClYm+NxJRq76j4+p+w5y/hmrxvw6SZIoKrBQVGBh1tT+x7ze6Lqrg72HjvGqq4NIJAqA1WLCUVLUG123FVqRZbHvBbnJDbfdRklREVecdx6Xn3sutZWVw647e+pUItHomMcWonyS0O7qwJHmBhEDhXkIH+uu/SRBvOgwU8ECNOhoZS+t7OUD6xspoiophYwS8pAdQBVitHOQdg6hw0QVJ/d2IlWIdr9y9LQGDw0cZztTWTkuMayzKER8MioqTo7gpq63k6e2O2dfM8zPvs9LyGgxMJVT6aCRY2zBSikmiihm6oRdc3KJoQpCRxPqhpjwKB9Ij/ju20So7+Nki/N2p0JVZX4LM/mcNVmZc16gl/jqEiOPbd/BlReuS8qYI0XXff4Aba4O2p0eDh49jsfrQ1VVZFmixFYYF+zF8Qi7xZS9/ScEAoAff/WrrFu5Eu0YjAKWLlzIU3/4w5jHFmelSYDSnbuZiar6HmHeSQvH2EI58yiiBg363kLFQirppJlmdnOc7ZgpxkwxJooxU4I2Sa3nu2jnGFswUcw0TsfcJ2XFTT3H2YZCrFfw9v9nRIsBFYVOmgnhYwZrhk17iRAkgJtC+l9B9xR5tnMQJ0eoZjEaDN15+ify9WNEiODvk+Pf92cEGU0fwa7r7bLqJn5Z4WBWUv5mucpo6S2SCmPuuJICRAoLOJ0KJy/Mv1OQfM6aQY+zUZifXa3l6aN6Xn57CxesXZuy7UiSRIHFTIHFzIza/sfDWEzB1eGlzdVBXWMrW3fupysQBMCg13cXmcYj7HZb4SCjAoEgE5y9ciWe7pTdHl566y227NzJqSefzBnLl/dbXz+OfhjiEz4JiLdRHtkRIpUE6aSOt5jGqiGjyhIShVRSQAVh/ARw48dFK/sI4EGLoVuo27EzvTeSHRfILYA0JvEeF7RRHMzsJ8jbOUQr+5jJmRgpRCFKlFD3v2Dv72F8qKg4mIWVMjRoUYj1Fo6G8RMhQBAvnTSjEGMBF/ebl6xR6VI8tLKP2axLqINnvA9qpFewK0TQYECPpbe4VTA8GkUhJovCtIEMjJCnmmAIjMbc3w8DRfhw62STMFdVlYcOhAnEQni83ozNQ6ORe4tGBxIMhWl3d9Du6mDHvsM43d7eNIBCqxlHsQ1Ht2gvFukwgjRy/7/+xdZdu/jVN74BwAtvvsn//PCHGA0G/vLkk3zn85/n4rPOSmhscQafBNQ3tlJbmbkmOy6OYGfGqGkeEhIGLBiwYKMGoNuqsRM/bjo4jocGZrIWhSiHeRUJDTIyftzosWDFgYVSrDgGpXAUUskUlnOMLeixYKaYIJ2E6GQmZ/amu/REnw1YUVDw4+wupJSIEMDFUVrYQxg/ClF0GNFh7i0iteKgmlOo4w1cHKGU2fEuprJKNBajjreo4uSEBHnP36nH8YYEx5gsDJVzbopECGSoyLMvuRYt31QnJS2FRVXVlN+oyLZizx7xng3i/IH9YZ5v0rL27Hlcft55mZ7OkBgNemoqSqmp6H/eUFUVX1eAtm7Bfqgung6jKPF0GFuhFUdxXKw7iososJqFO4wgqTz9yitcc9FFvY//+I9/cOOVV3LztdfyzV/8go2PPy5EuWB46ptaOWd14h7cEyVCsLd50HiRkHptDouZQj1vs5/nugtEp1POAiQkFBQCuOmiHRdHqWcrOoxYcVBEDRECqChYsDOP8+mkhRCd2CjERu2gPPJ4IepB2jjQ7dZiQYcZAwUUUNYrwrUYhs2Br2QRjeygjQNo0FNosWLtMlPCVIqZktDfQzBxjBl0XhlIrgnzZNHhVSksnJxCKdNRc19E5b69Yb65pgzr/LnjurWeDUiSRIHVTIF1cDqMoii4vT6crg6a2lzs2HeETp8fFRWtRtObv94j2kX+uiARjjU1UdbtNLd9714OHjvGb+64A61Gw/mrV3PrnXcmPLYQ5ZMAnz9AgXWwl286iMViBPAk5G4yEAmJWpbjoxUdJox9WtLLyFiwY8FOGXNRUQnQgY8WGnkXAwXIaGhlHzHCmCnBgh0dJiIEesdRUQjipY0DyGi688YTS/0xU8IsziRMFwoxiiwalC4jkQl0SxWMn4HRclM0ituUme/DUExGYd7uVChNg/NKtkXLe8ikMP/7gTAryzXIegulaS7+TzWyLGO3FWK3FTKH2n7PRaMxXB4vbe4O6hqa2bpjH/5ACBUVvU6HvbgwLta7BbvRkJxaJkH+UW6389KWLaxZtoz7H3uMS9et6+3c6fP7KbPbRxlheIQoz3PCkWg/38x0oigKn//e99BjTlqTmx6v7rGsZ8aGGRtlzO33XIQgfpx04aKZPUT7iHKQMVJAMVOxMz0pTjA9aSpGSxhvm8h7zAR9hXk8pzy79kOuCPNkpbC0O1Wm1mbXPkg3mRDmbzRHefBAmD+uM/Pu1ItYnmeifCS0Wg1ljmLKHIOLv8PhCO0eL05XBweONrD5nV2EwhFUVIx6PY6SIuzFRTiKC7EXF2EQ/uuTmivOO487//xnnnrpJaKxGP/85S97n3tl61ZOnjt3hFePjBDleU5jSztV5Y6MbLuusZHD9fVMZ01SxG2y0GGkiGqKxugtnixkjYqaYOMgwcQpf9RNy3pbpqcxLLkizJOB06WwdLE4/YyUZ55s0f73g2Hu2R3ix6eZmHnzg7z+6H9F+kY3er2OqjI7VWWDI5w9BadOVwd7Dh7D6ekgHI6iomIyGLoFe1ysO2yFomHSJOD6D3yA4sJC9hw+zPlr1lBdHg8UhiMRDtbV8etvfjPhscVRMc851thKbWVmmsoUWq20tnmwE0PD5I6KSbKKoghBnmmq/+MiuDp7T5qTRZhHIqDXi+9DDz0CfCg7RZh4cegRb4zf7Qyx8RwLUz75wITGmmwMV3AK4A+GcLo7cLq97N5/FKfHSzgSAcBkNBCJhtI9XUGauGTdOi5Z19/jX6/T8fe77pqQE5AQ5XlOY0s7q06Zn5Ftf+mjjyOjI9LdWXMyo7UoRLuECMk0WouC9p0w5a7EOoGmg3wX5oqSeueVXGQka8WJRM0VVeV7bwf55EID1da4WPAHgpiMk6fBWKowGw2YK8uGdDfzB0O8s2tPBmYlSBcuj4f39u+nvqmJmooKTp47t593eSIIUZ7nhCPRjNxO27B+I03sJIK/205wcqOzqES6JvfdgmxAZ1bxt8b3w2gNhjLJg5vjxcXZKM4nmlfu6VCxFaVPlWdrsed4SVSY/+tIhLCictXME+eBNlcHZUN4gwuSh9looKI0ObVUguzjr5s28YuNGwmETtwNMRoMfOH667n24osTHleopTyms8uP1Zz6nMEN6zf2e6yidtsURtBjYT/PYcVBDcuS1p0z19BZFAJtk/tuQTagMSrEgv0Pe0N5mWcL2SrOBzYaGo9Ib3cqONLgvJKPjFeYO4MKv94R4jdnmtH0aZgVbyhnS8EMBYL856W33uJH99zDB84+m8vOPZcKh4MWp5N//ve//PiPf6SqvHxQV8+xIkR5HlPf1EZtVWqbBvUIchUVJ4dxc4wAHswUY8HBdFajw0Qj73KcbUxlZUrnk63IWlHkmQ3E0yZybz9ke0rLeKLn7U6VmdPTZwuaD1HyRPnZ9iDvn6Zjji3+99Zcdz8AbS4P02rmZXJqAkHOcu+jj7L+nHO44zOf6V1W7nBw8ty5SLLMnx55JGFRLsIVeUx9YytTUtjJs68gr2crbuopZz4LuJhy4nnsB3mR42yjlNl4OI6KkrL5ZCuSLAR5NiDrVGLhofdDTypLNtMTNc9WBkbPh8PpUrCXiO9DooyUe96X15ui7HTG+MTCeO54jyAHcHd0UmwrSMn8BIJ852BdHWevHDrAePbKlRysq0t4bBEpz2Nane6U3aLsEeQRghxnOzHCzGANmu6PVAHlFFBOGXNp5yCHeBlQycUo5UTRWhQi/sn3vrMNrVkh6hdxiFQyloh5LAZabeq/D5M5Qg7w421BvrbUiEkr9RPkADFFQZNlXv0CQa5QVlJCQ3PzkM81NDf3dvtMBCHK8xRFjZ8YB1rzDMz/7uG+x64fcby+UfEgXrpopwsnnbRQzBSmsGJQq3oADTrKmY+VUlrYm1V+5elCZ1GJ+MQJMNPoLAphb253U832NJbRiMVUUq0FJ7sY76FQDzGVwYI8JgS5QDARzlixgt/97W/MmT6dZQsX9i7fumsXv//b37j8vPMSHluI8jyl3dWBo3jo290xwoToIkYYPRb0mNmwfuOQwjwQCvHha37dK8K7cKHDgAUHVsqoZBF6Rm9ZbsHBDMZ22zXfEEWe2YHWrOJvzv2LwmwX5iNFy90eleLi3N8HmWakgs+YorJxX5jGLhXzEHcknB4v9uLCVE9RIMhbbr72Wt7asYNPfOMbVJeX9xZ6NjQ3M3/mTG665pqExxaiPE+pb2wdVOQZDIVo5D2cHEGPBQ16InQRIYgOE2vXv8rFFy2juqKC1vZ2tu3Zw+4DhzFShAU7dqZTy3J0iC5w40EUeWYHkqyiigZOGaWtXcFRkroo7WSPkjf4FO54K4BGgo3nWKi0DP5btzk9lAo7RIEgYYwGAxt/9CP++tRTbNmxg4bmZqZXV3PNhRdy7UUXodEkfkdWiPI8pb6plbNPW9Jv2W0//zkBOpjPBWg50ThCIUaYLsJ08fJTDYTYiw4TFipZyMIh01IEY0MUeWYJkgpq/uyHbI+WD0e7S2H+HHHaSTaqqvL4kQi/2BHiY/P0XDdHjzxMh6Y2l4eZU6vSPEOBIL/QaDR86NJL+dCllyZ1XJFYlqd0dvkpLLD0W3bmihUoRNEM8AqX0WCkkEIqKWU2NSyhnHlYKRWCfIJozaLIMxvQmlWiebYfstmNZTgnFrdbpdiWX/sh06iqys/fDfHg/jC/P8vMhm/9Dd2HNqK57v5B+eQgIuUCwUT55De+waH6+iGfe33bNj733e8mPLYQ5XlIJBJFO8Ttk0vXrQNU2jmQ/klNUnRWUeSZDejMyqgdVXPBFnEg2SzMh0JRQKMRojyZ/H5XiO3tUe4528LcTz046vrBcBijYXI2cRMIksGWnTvxdXUN+VwkEuHdvXsTHlvcR8xDGludVJXbBy2XZZkprOAImwnSSTWniEh4ihFFntmBzqLgaxz9cJfN3T2HI1dSWSJRlQmkWgqGYJcrxiOHIjx0noXijw7trNUXVR1751WBQHCCd3bt6vd435EjxGKxfsva3G4eePxxigoS7wEgRHkeUt/YSu0wTYMMFDCbddSzlQM8TylzsFEjxHmKEEWe2YFGr6IM0zhoID0R81wS57kgzF0uFXsKizwnGzFF5VtbAnx5iZHyGx8Y02t8/gAFltHdsgQCQX9uvP12pO46DUmS+OHddw9aR1VVdFotd3z2swlvR4jyPKShuY0Vi4duodxje6iqH+OlLVv421NPsWX7vylhGnamo8cy5OsECSDcPrKEnujg+PZFrkXNs02YD7RGbHcqOOyp/T64i8yTxoHl+eNRzFqJ82vHfhoX+eQCQWI886c/4fX56PD5uOG22/j0ddcxo6am3zomo5G506djt9kS3o4Q5XlIOBLFoB85ZUKSJM469VTOOvVU6o4f58bP/Jz9PE8JU6ni5DTNNL/RmVUiXUKUZxqNXiUaSmw/5FrUPNuEeV/anQonLRSnnGSgqip/3B3i0ycZeqN3Y6HN5aG0JLfqEASCbMBRXIyjOH4eeP/ZZ3PBmjXUVlYmfTviXmKe4fMHsJrH5yM+tbqaZx/7KfO5gA6O42Xo9rGC8aGzjF5cKEg9WotK1D+x/VD+qDtnCkGztfjT06FiK0r9Raq7KPnpGe4ic++/kZali5ffa0WSYG3l+C5yWp0eHHZbaiYlEEwSvvW5z6VEkIOIlOcdDU1t1AyTTz4aDzx2A+vXt9LMLgqpSPLMJh86q0LAKYo8M43OohB0JadmIlci59kYMVdVkOXcuXM0nNgeank602ZUVeWPTx3ixvnji5IDdHi7sBVaUzQzgWDy4A8E+N1f/8pbO3ZQ39RETUUFK08+mZuvvRazyZTwuCKMl2cca2yltrI04dcrKOhI/AMlOIGsVVGjuSNC8hWtSSUaSO5+yIWoeTZEzDfVSWyqk3j8EOjSeH060eh1JqLfY+XNPU58wSjnbDgLYEgv8uFQUYdtKiQQCMaG1+fjyi98gb9s2kRxYSHnrV6N3WbjoU2buPqLX8Tr8yU8toiU5xmt7W7KVy9N+PVdtGElcVEv6EYUeWYNUoq6eeZaIWgmCXcq+CQRA0oGf3zqIDdcMBNZlpDGIcgjkSg6rTjlCwQT5ZcPPICqqjz2q19RU3Eiq6ChuZlPfOMb/PKBB/jfm29OaGzxDc1RNqwf7En750c/HI+EyImf/Hy0YWfGRKYmQBR5ZguSrKJMYkvKbEljCXoVjIXyIEcWwfjYddRDkyvABadWIpV9clyvbXd34CjO/N0TgSDXeWP7dm665pp+ghygpqKCT159NX965JGExxahizyi3d2B3VaY8OtbXS6ihDEiDtwTRRR5Zgdas0LUnzpRLtJYxkbIq2AojH8fNtWl5yIp0RSUbE5dafWEmFVdgFYz/mNLm9NDqSjyFOQAbS4Xd/zyl1z0yU9yxoc/zGe/8x0OHD064mte3rKF62+5hTOvv54v//CHuDpSF4zwdnVhKxxaaxUXFeEdptvnWBCqIQdxejwE6EBF6be8oamN2qrEijwBtuzYgQUH0jj9nAWD0VmFKM8GdBaVyASdV0YjF4R5pon4VXTmE8eVbBfm2botiXjBbCK0CjtEQQ4QjcW48fbbaXe7+eyHPsRnP/QhGltb+fS3voXPP3Qx9fa9e/nyj37E4nnzuOMzn6HF6eTmO+4Y1HEzWcybPp3Hn39+yOcef/555s1IPNtApK+kgaFSTQaiovaK4Z4GP8Px+PPPs5/nkJAxUkAhlZQzj2ONrZy5cnHC83x7506RT54kRJFndqC1KATT4ICT7fnlmU5jUWGQU0iPMM+mdJZsjpIDyHLcfSUR2l0dOETjIEGWo9Vo+O0dd1BdXt67bO706Wz4+tfZsX8/p51yyqDXPPD446w65RS+csMNAJw0Zw4XfPzjbN6+nTXLliV9jjdfey033n47n/zGN1h/zjmUOxy0tLfzr+ee4+2dO/nj97+f8NhClKeQprY2bv7EH4kRJkaYaPfPvr/3/JSQmMEZWCgZddz3n302v7r/IWZzNlFCNLIDhRgdnZUUFSTekXPTM68zjdMSfr2gG0kUeWYLGq2KkqaLo2wX5pkiFlbRaIffByLPfOzsPebFZtUn9NpINIpeJ075guynryAHCEciAJiNg3uwRKJRXnrrLW7/1Kd6l5WWlLB43jyeff31lIjyJQsW8NNbbuEHv/89/3vXXUiShKqq2G02fnLLLZwyb+iO6mNBfENTQDQW49u//jWbnn8VC3a0GNCgR4seA9be3zXo0aBDi4FOmqnjTeZyzqjj2202bNTgoo4KFqAQwSrZ0WrkcfvW9rBh/UZihNFiSOj1ghPEUyaEKM88KumWekKYDybUeSKffDhSJczT5R2eDo61dvHQc0d58H9Xj/u1SqI5LwJBhlBVFVdHB7sOHOBn997LOaefzuIhxK7L4yESjTK1urrf8qlVVTS2taVsfmevWsXaZcs4VF9PQ3Mz1eXlzJwyBf0EvV+FKE8ysViMb/zf//Hqy/tYwIXIY/wTWykjRgSF6JjWtzOTQ7yMnelECVFiKaeyzJ7QnHvSa4wUEaQDHePrCCroj86iEPGJfPJMozGqxIJiP/SQqRSWoFfBUJj9F6nZnLqiqio/eHAXH7twJlWO8c/T29mFrUA0DRLkDlt37eLjt98OwBnLl/ODL31pyPXaPR4Aiqz9P99FBQW8t39/Sueo0+mYN2PGhHLIByJEeYIMlSeuolLPViL4mc5qZMbeRdDNMQooG3Pjnk5asFKKioKMBr1VHVOR58B5+2hDRkOILhRiBPFSQPkwrxaMBZ1FdPLMBjJlSymi5f0JdSoUVIz+fRBpLMPz77cacXWG+ODZ0xJ6vXBeEYzGk+8WoDuSvkLgiFcZ8fn5M2fy629+k0PHjvHQpk1suPVW7v7Od7AM6JbZc4QfWGuhqqltlOUPBNh54ABtbjeqMvi9XLJuXULjClGeABvWbyREJwG8WChBi4EoIY6znSghprNmXIJcRaWdg9SwtHf8kYo9P7z+XtrYzwzWohBDQoPOolBTMbYiTRUFF3UUUMYRXkOPFQMWCiingIrRBxCMiCjyzA60FoVg+9i/h8lECPMTRAIqWmP6vw/pTF1J5bZa3UHufHgPd31mOTpt/M7PeD3KW10eKhyj1ysJBNmCxWRi9dKlrF66lPPXruUDn/40f3niCT5x9dX91rMXx4+zHQO6aHZ0duIoTs0x+NWtW7n1zjvpCgSGLLyWJEmI8nSxYf1GWthHOwcwYaOBd4gRQULGwUymcOq4BDnEo94SGiw4+m1nKGH+kfX30UTcutBEER4aMFKArFUxGsZWABSmiwbeoZQ5SGgwYKGWZWhIrIBI0AdJRU1B90jB+NEaVaIBsS+ygURrXXKBVArySFThK79/hw+ePY1F023A+AU5xCPlJ80VTeEEuUm53c6Mmhr2HTky6Dm7zYZBr+doQwNL5s/vXX7k+HFm1tamZD53/vnPOIqLue2mm6ipqECrSV7wR4jycbBh/UaCeGljP3N4H3qSk4PYziEczBrkDz5QmF+7/rccYwsyWqawAoAAHiza4nE5TCjd/uYujlLFSbRzmIO8zGzORhbW9RNCZ1ZT2qxGMA4kFTLouS+i5RANqWj1+RklT8c2fvr33TgKDXzsgplAYoIcoLPLT4FlbKmRAkEm6ezq4vVt2zh/zZreZV2BAPXNzaxcvLj3sclgQJZltBoN61au5JnXX+eyc88FoKW9nZ3793PztdemZI7tbjff+fznOfPUU5M+thDlwzCct3gzu7FSmjRBHiGAHxfTWDXsPCIE8VBPC3spZ14/AR8lRIm1mEinPGraC8Q90K9bfzcadEzlVNo4gAYdBZSJlkFJQHTyzA4kkUKUFfTt5JntFHf4s6rY8/HXG3hrj5ONt52OLEsJC/Ie8vluhSB/2HngALffdRcvvvUWa5Ytw6jXs/Hxx1EUhcvPPRenx8PFN93E6iVL+NnXvw7Ahy69lBv/93/50T33sGLRIu75xz+YO306K08+OSVzPGXePFpdrpSMnRtHyzTzkfX3E8CDkyO0sg8/J/74ZcyhkxaCeJOyrR7HlUO8xCFe4ShvUM9WGnmPJnZxkJfYy3/x42YGaylldr+IuoqK0aol3O32MZZGRX957BNoMaIQw0oZNqq7hb74OEwUnVU4r2QDOrOS8k6egtEJjsEOsYdkFnmmQ1y7i8wp286eug7uemQvP/3UUqwm3YQEeSgUxqAXheeC3OC0U07hj9/7HpIk8Zu//IVv/frXWEwm/vi971FbWYlep6O0pISK0hM1dCfNmcOdX/86O/fv51u//jVVpaX8+o47kOXUnANuvPJKHtq0ic6urqSPLSLlfVAUhYsv/ybtHEYCLDjwUE8tyzFT0l2QeRg9FjQk5yBnoIC5nNPdRCgu0GN9fi9lNgWUD5unXkwtkjlAW0MDNmqQGFvE/JtfvJH/vev/sFFDjAit7GcGqzFQkJT3NVmRdelrViMYHp1FJewT+2Eg6bZFDHkViqoyc5pxF5nTkmKS7O24O8N8+XfvcNt1C5lZVTDhCHmbq4NS0clTkEOcPHcuJ8+dO+RzBRYLT/z2t4OWr1m2LCWNggBu+clPBi3r6Ozk+ltuoaZisDmGJEn8stvOcbwIUd6HdZd/jghBpnM6RgrxUE8IHzbixQJhuuikhXmcjyZJfzoJCQMFCbfsKaAMi+RjP+/QxE5qWUYB5aMK84vPOoszTz2Vz1z3CABOjnCQl5jGaVhIzO980iM6eWYNWrOCv1VEB4cincI8GlLR5FA/skRTWJIlzGOKyq33bOP8FZWcs6xywoIcoM0l7BAFgomw88CBQelfRoOBSDTKkYaGQetPRAUIUd7NhvUbCdNFOfMwEffq1GIkQoAoIXQYu3+akibIk4HGoELQyCzOxEcrdWzBzjTKWTCqMP/MdY+gEKOD44TxU8XJHOF1SpmNFQcmisftJDOZ0Yoiz6xB1qioMbEvMkmPVVgmc5nTFS3v2RZMrAD0nqcOAvCZD8xJiiCHuPPKKQtmJWUsgWAy8tQf/pC2bYmkS07kYZcwDQ/He5cXUEYJU6njTRRiRAllXd61rkAh0hmfk5Uy5vA+unBygBfwcJyPrL9/yNdtWL+RKCEO8TLtHKaVvdTzNjNZS5Qgx3mXXTzBUd4ghG/IMQT9EUWeWYKwpcwKoiEVXQb8yXOVmKLy8It13HrdInSVNydtXKfHS0lxYdLGEwgEqSN7Qr4ZYsP6jaiodNBIK/spZ16/58tZQIgt7OO/xIhSw5IMzXRo9FaFrsYTu1GHkRmspYNG2thPEzu4cP1+fvzjjzBvxgx0Wm2vteMRXsPGFAxY8eNiJmdgwkY1pwDxItR2DnGQl5jLuWiFj/mI6KwKvnqRMpFptCbhT54NhLwqhoLcu0idqAtLotH5d/a7KLMZmXbS0O3EEyUaiyXVR1kgmKzs2L+fv//73xw9fpypVVVccd55LFmwIKnbmPSivJNWmtiJSqw7H7t/q3oJiamcio92dBgxYM3QTIdGY1CJhfsLEAkJG9UUUYUfJ26O8YlbvkuYLkwUIyHhx0M1iylhKioqAdzU8RYGCtCiR9P9T4sOLXqa2dnbcVQwNBqtihIRYjDTZKvzSvmjboBJ410e8ioYbdm3H7KV57Y1c84Z70/qmIqiIEtiHwgEE2XH/v184vbb0el0TKmq4tWtW/nPq6/y81tvTWqBqRDlNGOmmGoWj5iaYu3TbTNr6C0sHFoISkhYcPR2Co0RoQsnKjGslPfmxktIVLGYEqYRIUiMSLcDTJgwAUzYkMVHZWREykTWoLWo+JuzQ4j0CPGByzItzNNR7Bn0KhRNEceNsVLX3MUZa5PbddPt9VFclF2BJIEgF3nwiSeYUVvLH77zHaxmM6FwmK/++Mf88oEHhChPJjJaZDRZlys+FsbbPVKDjkIG2/dAXJibsCF6viWG1iSKPLMFjUEhFsruQ1s2CPNUE4uMr5vnprr4usn0K88lWtwByh3JDf60OYXzikCQDN7bt49PXHUVVnM8tc2g13Pztdfy4Vtuwef39y6fKLmnRMfABfc9yQX3PTmmdTVoiRFN8YxSg86q9DYNEmQWnVUUeWYHavd9o+y/QBoqip5OHtxclLKxe5xXEqFHnCeLdHfpTNR9JRRRMOqTW7fT5vRQJjzKBYIJ4/R4qCrrn948rboaVVVpbm9P2nbyWkWMJsx7ijylHDiBD4XoHpk9COeV7EDWQSxH8voHRsozIdJTJcwjARWdKfH9kGxhPh7SLeJ7KDDr8PmTa9/Y5vLgEJFygWDChCMRjIb+TRd6HkejyQvsZvc93iRwwX1P8vSGSwYt77FBDOHDTG7eRpa1wos5W5B1osgzG8iVi6OhUlcylc6SivzykFfBWJg9+2GsjigTFeTj2cbAdQtM2qS37e4KBLGYjEkdUyCYrLz13nu0OJ29jxVFQZIkNm/fzrGmpn7rnrd6dULbyHtRDoOF+QX3PQmXFVP+qJsQnRQzZdQxsi2iLmlEO/esQVJBFHlmBVqzQtgr7N/GS7KFecirYHbkzn5IV3S873YGbtNQaEy6KBcIBMnjNw89NOTyX2zc2O+xJEmTR5Tf9K+X0BWeiCgNFQUfiqFSWVouK0Z6VEZFGfG1UcLsZhN6LFiwU8psjBSiolDHWwTxEiWIioqNWmpYknIBL1JXsgfhi5096Mwq/maxLxKhJ5UlGeI81KlSPH1ix6dNdVJSiz5TKbyTEYU3JzlS7g8EMRtFlDyjTKC2QpBd3PPd76ZlOwmL8pe3bMFsMnHSnDkYklycMh6GjIKPAx1mumjHStmQQlpFIUgHGvRMYTmdtHGQl7AznSJq6OA4NmqpZCESGo6yGRdHsJNca6uB6K0KQU/uRKLyGXGBlD1Ico9NqCCTxKIqGl1q9kOyxfpESbSwcyCRqDIoZ3UitLk6KC1JXTGvYHQCoXCmpyBIEssWLkzLdhJSEm6vlx/efTdf/9nPOHvDBi6+6SYee/ZZAFwdqfW+/f0Hzhy0rEeIj0WQP73hkn4iXn7fcjpo5Aiv00krftx00kIzuznEy+zkCY6wmShBjvIG5cxlLucQpos6NuNgFqByhNdRiFHDUprYRYQALexlH8/Qwr6kvf8etOO0QxSkjlzJY8575Nzxis+088pwJCNKrqpq0u4TDiz4zGQB6FAkS5AD+AORpEa2hR1i5uno8GV6CoIcI6FI+bt797Jg5kx++rWvAbDvyBHaXC42vfgij/z3vxw5fpxzTjuNL23YgNlkIhKJ8NCmTUiyzPvXraOooGBCk356wyWDBPhYBfnAMXSFxRR94Aqkf71FC3tQiCKj7U1TMWNHg44oQZRu60QdJqayEi/NHGc7WoxIaDjGFmZzFnams49n0WOmmlOo4y0KKEtiQamKJPKYswaNKPLMCnQmlUgOXagOFOb54lse6VLRWZJ3kdoTGc82QZ5sWtr8lNntSRuvzeVhWu28pI0nGD+eTiHKBeMjIVH++rZteH0+jre0UF1eztzp0ym0Wnl282Z+8OUv4+7o4Hu/+x1PvPAC11x0ES9u2UKL00mBxcJfn3qKm665JtnvYxBjyTXvt87HPpDQdiLRKK+8/TYPP/0002pq+NrHryccifDBq36JGTsyMg5m4eTIsKJcRUUhhkoMpfvfUL9LyFgpRW/QEA3l9wkqZxCdPLMGrUUhmsN3LPKloVDQq2AsSO53ItcF+Wj55IFglJZ2PzNqa5O2TZenk+KiiQXABBPD7RWiXDA+EhLlhVYrJTYbX/nRjwD4zhe/yKwpU7j+/e8nGotRbrdjt9nYc+gQAMcaG1m7fDkmg4FNL70EwB//8Q/2Hz3K9770JbSa5OZGj7X4MxnotFrOXrWKs1et6l2m1+l45LH/6bVdLKaW/TxHCdPw48JDPWH8vYJbRenuKqrp91Pu83jladPp9PvZ8u5T1FpnEPTZ0VCBjEyYLhrYhh4LBqwYKMBIATrMWeUYk4+IIs/sQWdW8Hl0mZ7GpCfUqWAtE/Uu4+HQUQ9TawrRaZPnvaCoCho5dy9S84EOESkXjJOEjgDXXHghpSUlAHzhe9/j7//+N1/+2MfQ63S9AvtgXR0fWb8egNKSEn7w+98zvaaGqy+8EICG5mb++9prbFi/ngWzZgHwp0ceIRaL8Ymrr074DaVTkI/GfY9dz4b1G9Fjppz5HOZlCqminPmYKOojwuURxfN9j13f+3sgGOQLX/sDh5sP4GUH01iFjIYunBRSQZBOvDQTopMoYQxYMFDQK9Tjv1vRIMRLMhD55NmDRq+i5HhdVT5Ey0OdCvaZ+X98GWs++VhcX/YfcTNnRvL2eywmBHk2EI3EMj0FQYpQVZXnNm9m/9GjuL1ePn7VVZTb7QSCQSRJSrhoOyFRXlpS0muafvqSJTzw+OMYbroJiJup//GRR7BaLFx69tkAXLpuHVOqqgA4afZsQuEwnV1dlJWU0Nze3ivKn37lFVYvXZrQG4HsEuQ99AjzUmbhYAbSOGtr+wpyAJPRyJoz5xG634aZeg7zCrM5GxWVYqb2E9sxooTwEaKTEJ14aSLIfsL4kNF1C3Vrr2g3UIBeRNfHhc6q4GvIfwGS/fS4cYjPbioYj12iEgNZK/YDjN2Gcf9hD4vmJS+f3OnxYi8uTNp4AoHgBG6vlxtvu43G1lamVldzoK6OK847j3K7ne/89rfMrK3lxiuvTGjscYlyt9fLUy+9xFmnnkp1eTnRWAxXR0dvcUpLezuPPfccz23ezE+++lVMBkO8El+SOGXeiYKT462tHGtq4nMf/jCPPfssZ6xYgVajoaG5ecyiPBsF+HAMFNYTIR4BkbjvsY+wYf1GgnhpYS9GCgjRiZkSYkRxchgHszBjw4yt3xgqKhECvWK9J7rux4mKShHVTOXUpM05nxFFntmBxqCKOoskMFQToR5BPhZURUUSu2HcHDji5vILZyVtvDanh9ISW9LGE4wffzCEwSACNvnIj+6+G4vZzFN3302R1cryPgJ81eLFPPjEEwmL8nGFbYsLC/H5/dzz8MO88e67/Pahh3j1nXe48coraWxt5Wf33suRhgZ+fuutTK2uJhqLIXUfoRXlRIOePYcOUVJUxMrFi9l35AgaWeZ4SwvhaJRZU0bvrjmZaW5zUVEavwi677HrsVJKAA8RgkjEU4dcHKGF3Rzl9V7HmL5ISOgxU0A5DmZhwUGUEDI6HMyiggVpfU+5i0r2uCVPbrRmNaeLPHvIhtSV8YjwgYS7VPRJdF7JZcYaJXd5gjS1djGtNnmR7TaXsEPMNE53B7ZCUWibj7y9cycfu/xySoqKejVuD+V2Ow3NzQmPPe6j5yVnnUVFaSn/d999HGlo4If/8z+8u3cvl9x8M2V2Oz/88pepLi8H6FfAKffJb9uxfz8zp0yhtKSE+TNn8uzmzew5dIhKhwNbobjlNhL1Ta3UVpX1Pv7at84lgJtCKjBRhIpCGweZwVq0GDjEq0QIjjimi6PIaFjAhVRxEgasqX4beUHcK14IkGxAZ1GI5Pi+yAZBPpDxCvSgV8FQmNv7IZ2oqsrP736HKy6ajV6XvOLYVhEpzzhOtxdboTiX5iNajYZIdHDAE6C+uRl7ceLH8nHnlFeXl3PTNdf0szWcWlXFB973Pl7dupXHn38eh83G1RdeyBXnnz9kNfnew4e56oILADCbTDS1ttLQ0sIp8+cn/EYmC/WNrZw8f2bv43KHAy1GqjgJAA/H0WPGgh0zJTSxk738Bz0WCijDSCEa9GjRd/80UMMpHOBFYkTQkryOcvmOKPLMHnLdBSfbBHmi0fKQV6GwKnkOIrnKWKPkz71aT2OLj298cWVStx8KhzEaMtdpW9Ajyi2ZnoYgBZx68snc/fe/s3zRIor7BJLdXi/3/+tfrFi0KOGxk3L0vOjMM7nozHinTZ/fz/Y9ewiGQkMK8o7OTlqcTpYuiKdIXHbOOTz54ots3r6dr9xwQzKmk9cEQmHMxhPC+Y7PPM9CLgbiyRRt7Kec+MWNhEQVJ1HJwu5Opa34aCNKmBjh3p8xIoBKM7upYUkm3lZOorMo+BpFzmA2kMvNtLJNkI/EUDnnfQn5FPTW1O+HnoZCmcRdZJ5QR89DdR5+c/+7/PDWNeh1GkoMH07KvFRVJNVlA05PB1XlIh03H/nSRz/K1V/8Ih/49KdZtXgxkiTxh7//nR379oEk8bkPJ/5dTnpIw2o2s2bZsmGfb2prQ5akXkvFpQsW8M1f/IJINMrc6dNHHf/AkQZKi+0UFUy+K9BgKIyxu3DkSEMDn/3s3RQzDU33bvTRhkKMQir7vU5CxoIdC0NX96uoxAgjJ//jkNfkgwVfPiBpVJSYEOTZgBoDWZOb+yJZjCVK7vIEuf0nr/PZj57CnBnFSRPkAD5/gALL2CL1gtQRDkfR6UXQJh8pLizkH//3f9x1//28sX07qqqy++BBTluyhC9u2DChNOy0q7B5M2bwyC9/2ftYUVXOW72aR/773zG1GI7FYrz4xjY6Ov3odVpqKkqZUl1OVbk96U2Iso36plZqKkoJhcNc+9lbu91W7L2dQtvYTymzx21pKCGJtJVx01PkObkFSDagNStE/fm/H7Ldw1yJqUj5fQgelbEI8lA4xjd+8joXnDmNs1fXJlWQg3BeEQjSQVFBAXd85jMARGOxpOnPjIRG+05ep9XypY9+lI9dfjmmMZitz5s1tdehJRyOUN/cxqG647y65T2iMYUSWwFTq8qZUl2ed9H0+sZWZk+v4ZKrb0ePmQh+jMSvyAJ0EMDDNE7L8CwnB/EcZpFPng3oLOqkyO3PFkE+nGd52KdisKZvP2RbCstYBLmiqPz4N1uoLLfwkSvnJ12Qg3BeyQaCoTAGESXPW7w+H+1uNzNqa4H+mvbRZ57h3NWrsZoTu1uVNfkKiYT79XodM6dUMXNKvDGRqqq4PJ0ca2zpF02vrnAwpaqc6nIHWm3uhnKaWl389iev4KaOak4hShi52waxjQM4mNn7WJBadFaFiC//hWAuoDMrBNrFCTDdDBTnoUnsvDLWws77/7GblnY/d37zTOzG5PWv6Eur08PcGSKXOZM43aJ5Uz5z13330eZ288vbbx/03LObN7O/ro6vffzjCY2dNaI8GUiShL24EHtxIUsWzgYgHInS0NzG0YYmXnt7B9GYQnGRlSlV5UztjqYP9JnMRlRV5a3NR6hXt1LFyZgpJkwXMcJIyHRwnPlckOlpThriRZ559fXJWWStihrN/u9wvtJT/Bn0Kthq0/udyJZo+Vh49pVj/PflOn713bOpKNiQsvl4vD4K8+wuca7hdHdgL07c71+Q3bzx7rt8ccPQ3+FL163jNw89lPDYea8q9DotM2ormVEbL35UVRW318ex4y288tZ7uL0+tBr5RDS9ohS9Lrv+LLFYjA9+8P8wVQXQY8FGLRISxUxhL89QSIXIC08z8SJPIQQzT243cMr2PPGx8uDmIs7QtKTFeWUg2SDMR2PnvnZ+c/+7/OwbZzCrPLEI2niQcyDQlM84PV5mT68hGA5keiqCFOAPBIbNIdfrdLg7hneoGo3sUp9pQJIkSooKKCkq4JQF8bbGkWiUxhYnx4638Ma23USiUQqtFqZUlTGlqhx7cWFSo+nNbW00tbePul6X389LW7bw6NMvUFlSg8Znp5blvYWc1SzGznS8NFPK3KTNTzAaosgzW9CaVGIitz8rONauo1YW34mBNLV28f/ufIOvfXo5y2Z/JqXbikSiQ1oRC9JLu7uD05YupKFFiPJ8ZM60aTzxwgucvWrVoOeeevnlCXWmF99e4sWmU6vj6Sw9dHR2Ud/Yylvv7sHp8SJLEuWlJUypKqe2shSTcWxRaUVROFxfz7Y9e+L/du8mGA5TW1ExqtDXabU07IRZnIWjwIC/RUNsQBNWI4W9xZ6C9CCKPLMHrVkhkuPOK/kQLZdUBUWSRvUxTxXZGi13eYLc9qPXuG79PC5c9dWUb6/d3YFDpE1knFAoIpo35TEfv+oqbrrjDv7nhz/kuksuoaqsjJb2dv761FM8/8Yb/PSWWxIeW4jyYSgqsFA0dzqL5sa902MxheZ2F8eOt7B990GCoTAmo54pVWX84O19BLVa6BbZpY868dKIm2N00Y4GPRYcWLBTyBJKsSJ1jC4kIkDPZYLWECIWFLsrGxCdPLMHnUXF3yqKmzONMRol1B2hFcI8Tn1jJ1//4auct3YqN37gjrRss80pnFcEglRz6skn878338zP//xnXnzrrd7lOq2Wz334w0NG0MeKUHljRKORqS53UF3u6DUd7PIHuP4Pf8Ps8+JQ48kM4TY/rSUNBDtj2CI11LAEHaYJbl2kS2QTOqso8swWNEYlLy5We6Ll5Y+6+y3PlQi6MRqNByYyzKa6+DFyLOI8VSL+eLOP/7x0lE3PHeHGaxfx4Qu/kfRtDEery8OC2dPStj3BYMLhCLosq0sTJJ8rzz+fs1euZPvevTQ0N1NZVsbJc+ZQ7nBMaFzxyZkAZ376cyihIIayKmSjGeu+IEajgSrrAsw1BjQ6FVWRiHRFCPvkeHRVGb+w1ppVon4Rmc0WRJFn9iD1+X+uM1CQ9yzLBWFujEZxmuIuJJmIkg+kR5yPdb1kifPtu1r51s/f4NwzpvKT289geYpzyAfiFOkrGafdI+wQJwslNtuEouJDIUR5glxw35Oo0Qglp5+PtrBPhCsI0SB4e+o4ZRWdRUFvVbCUx5A0KrGwRMQnE+6UiQUlRhMVwhM7mxB3LbIFWauiTAIrxFwQ5oZolHAOd1RORtR8x952vn3Xm9zxpVWcsrAsJY2BRiMSiWWde9hkQ1wYTR7aXC6a29uJRCKDnlu6cGFCY4pv7xi54L4ne39XVRUl4EOSZGLBLqqfG+GFikSkU0Ok88QJS9ap6KwK5rIYWqOCCkQDMhGfTKRTHiQ09FYF7zHRHCUbEG4f2YN2EuX254IwJ8dt+CYizJvbuvh/d27m1s+uyJggV9XsyaefzDjd3t6GhoL8pN3t5tY772Trrl3DrvPOP/+Z0NhClI+BC+57kkiHE/+hXURcrUT9nchaHfqyarQFxUB4XOMpEYmQW0PI3SPUVbQmFV2BQsGUCLJORY1JRLpkwp0Ssk4RzVGyBFHkmT3ozArhSXQHKVuFuazEnVd6yFShZ6YIR2J86+dvcPWlc1ixuCIjghzijmFFomlQxnG6vZy6eF6mpyFIIT/4/e85cPQoH37/+9l14AC1FRWsXb6cdreb3/3tb2z80Y8SHluI8lHoiZB73nwOY9U0ilasQ2MuQNadsDtqucwyZD7o2JGIBiSiAZlAa/cSOR5N1xcpaM1QPDfUm/YS8clEA6OnvQiSj9ai4G8SX5tsQGtW8bdOHlEO2SnMs6XIMxkkEi3/9X3vUmY3c/UlczImyEE4r2QLgWAIs8mY6WkIUsg7u3fzxQ0bWH/OOdzz8MO4Ojp432lxC5BD9fU8/sILfPqDH0xo7Pw4kiaJvikqA9HZHPiP7gWNhoL5y1I+F1WRCHvjkfSumIS/Wdub9mIqjaExKkjE017C3UJdiQiRnmq0hnhNgCDzyJr4HaXJRrYJc2M0QkDXP71uskTLn3+tnm07W/nt99+H3Xh9RufS6vJQUVqS0TkIBJMBg15PSVG8bmBGbS3Pv/lm73Orlyzhlw88kLAon1xhphEYSZAD2E49G8f7rsB/cCdKKNi7vPxR9wSj5CPTt8izJ+2l85gOz34D7v16Au0aZK2KtSZC8dwQttlhLFUR9IUxJFnkGCYXUeSZNUgqqjo590M2CXLIr0g5jN25JRCM8tuN7/L1T6+gtvhjKZ7V6LS7PJSV2DI9jUlNJBJFq83dgmfB2Jg9bRo7DxwAYOXixfEGkbt3A3Dk+HGax9CxfTjy50g6AXoEuaqqhJrq8B/ahbaoBEPFFGpfM/W2tQcIU47+qd3YmZ6WueksKl1Nw50k+qS9tHUvklV0ZgWdVcVUFkGWVZRYt9uLTybql2CSipmJojGqxILiOjYbiHdVnVyf42wT4z3oYzEi8mAhMjBa/uDmE44U+RBF/9sT+1i8oJQFc+yZngoAXp8fq2WiPTEEE8Hp8WK3CTvEfOeSs87iZ/fey83XXovFZOKSs87i09/+NtOqqth39ChnrliR8NiTXpRfcN+TKKEggWMH8B/diyTLWOaeQqzLh/+1V2mknEoWIRM/6RRQRhftaRPlkqyOT0QrEhGfhoivzxjauC2jsTiGtkpFklWiwe789K6x2TIKhDVlNpHvBbfZKsCHZRjnlb5CfKjl2SbOve4uDu9tpq3JwUdXjSyuXni9gW98YWWaZjY2pBx3wMl1nG7hUT4ZOG/1aqZVVyPL8XPQ1z7xCXRaLVt37eKCtWv5yscSv3M2KUX5Bfc9iaqqRJwt+I/uJdR8DEPFFIqWrEVnL0eSJMofdROhlMO8ym6eooqTKWEqVkppYid+3JhJ7YlT1icnf1mNSoQ7NIQ7Tri9aPQqOquKuTyG1jDAllHkpw+JzqLgb56UX5msQ2sW+yIb0CgKMTnxi6NsEeddnUFeeHw7dQdaCPrDnHPZUjZVFg1b9BkIRmlt9zOtJjsEWCgUxqAXtrmZxunuYGpNRaanIUgym156iRUnnURZSbxmQ5Ik5k4/EZjVabV87ROfSMq28jfUNAJKKIDrlU10bHsFXZGd0nOvxrb8LPSOil5BDqDDxFzOpZz5dNIMgAErtSzjCK8RHacV4njRWxUinanYRRKxsEzQpaGzTod7vwHPfj3BkfLTNSI/XWv4/+29d3wc93Xu/Z3tHYvFohcSBEGCvVOURImiei+WbTm2Fdpy4hLfOI6d+MZviuPcxE7cbq4T27EdF1mW4y7KVrcaRVGk2MXeK+r2Xqe8fywAEgRYQJRdAL8vP/iAmJ2dOYvBzj5z5pznaChZcbFSCky1YzHWvStXi0XOj0o9+ZObyy6aVR9rVEXlyf94mTKPnUc/fRtmi5HZixsv+ZxT7TEa65wYDLqiOq704Q9FqRT15EUnKKZ5Tkq+8aMfcez06f6f7/3Yxzh4/PiY7GvKpZrOdHUR3PB7LPXNOOYuv+TtPoU8Yc7g4xBNrOxfXkYd3ewnTwoDpos+f6QYHSop33g1jQxRny5pGO19ji95dPre+vRkb0Y9OZXq00WTZ+nQd4E4eY9Fn8PKhUL8/J9LocRltJs8i+HakknnSSey1DSUc+ZoDzaHmVxWxmI1XdQisduXpK7aXhKCHMAfEnaIpUAylcEu7BAnHTpJ4g9vvcX81lZcDgcdPh95WR6TfU05Uf7F//xPbNPbsM9aSC7Yg5rLoLc60FvtIEE+5KeL06QIkiKCkyrqWYyERIR2LLiQySGTxYxzTGM1WFSUTBEPkSaRT0gD6qglfaE+3eRSsNcW6tP7/dOTvY2kk1AsiSbP0kFnYkrYUl4uMz6UNeJ42yVa5DxR8+iKkPEW5jaHmQc/vJpXntpJ25ImWhc08MS//wFPpROr3cyLdhPza024nGYqPVZuWFlPMJyh3rt43GK8HP5ghMVzZxY7DAGirn8ycteaNTzx9NM8/UphfLskSXzo85+/6PoSsENM9LwyNE0j3X6UTNdp5EQEncmCJudR8znQNPRWG8beqh49RmJ0kSSIGTsGzKSJoqFSx6L+5s8xirQkM7OaUvBP7/NQB/r90y0VCoaGXv/07ORqJDXaRZNnqWC0qeRT4ljA0MJ9PIW5UVaQR1BTXipMa63m4T+5kZ/95ys89OHVLL9xFkFfnHQySzqZpT2VozaaYedeH08+dYgFbV6m1xT/TkUfwUgMjyibKCqyrAg7xEnKZz70Iea3trL/6FGyuRy/eP55blm1ikrP6M8FmHKi/Guf+xxnu7v5i6dfI7L5RTBZMFXVo+UyaJKOsi4TJuznfdnGWHwPjcGmIacnxoddn396NnxeI6m5UPpiqyoMOgJQ0gWRnktIqLmJJdSNDo1U98Q4HpMdo10lGxEffpdiXIS5ppHpOk0y1IV95vyx3dc4UOaxs+qWuWx7/TD3PXotDc3m/scenfUBAELZn/Jv397G718+wXf+8Y+LFeogFEXFoBfviWISisTwlI3t3XNB8bj9+uu5/frrAdi4Ywcfefe7mdPSMur7mXIqw+N2s6itjdf/9ycK1oeJKPYZ82jrXsmcruXUsRAvLbiowYKzKIIceu33xqTJczyQULK9jaS9g44iR0yk/HoknYajTqZ8Vg53aw5HQx6zW0FnKO1GUr1ZnVKNhaWMwaaRn2Ie5VfDWDeGGlSVXD5HfO8WNG1037/Favqct2waZ471kIyfGxDXJ8gBPOYP8t57ZwGwaPbscY9vKFRVFSUTJUAgEqOivDh/t4Lx5Z6bbsLtGps7U1MuU34+ZYc1VNzUv1564tfkUImfmUwWVxJKRiKd0ZHuG3YlaRishdIXR2MevbEwpTGfPNdMWhpj1Cd/Y+FEQpI0UMWxuBLGMmNukWVSah4AJR7B4Brd/VwozMejztxkMVJVX46vI0xzW+0AQd7HstZP8tvvW7BZS2NQTziaoLzMUewwpjzBcJTG2qpihyEYB37z4ossnTuX2srKUd926anRcWLdg0+QwIcJ+4CJnaWCzqihyqUX16iiScgpHWmfgdhJU8Ga8ZiRXEyPwaLhmp6nfFYW98wc9triWTOKJs/SQdJpaEKQlwQWOU8inUJndaCkk8UOZ9TwVLkIdMcAeOLIk0OuM6PyI+MZ0iURziulQTAcwysy5VOCm1et4qU33xyTbU9JpXHn48/Q81A5JuwYKY1sx/lIOq1EMsRFQCs0iKZ6DESPF4R69ISRXEKHwVYQ6u5ZWcpacthqZIxOpTD1dAwpTI+cosejxDDYNPIpcSyGw1iVsVhkmXgqgcHuHBdRPh4lLfmczPEDHdRNr+hfdr4wD0WjbHnnnTGPYzj4gxGqhEd50Umm0thtwg5xKvC5j3wEXyjE57/xDXYdPMi+o0cHfV0tU7Z8xfnUCY5zijbuKHYogzA6JvcI8eGiqRL5uJ58/NwySddrzehQsVUr6HTne6hLBXeOUcqoFpo8RRNVKWC0qcjCeaUkMKgK2VQMW00DSjpR7HBGBX9XlHQiy/7tp9DrddQ0FtwVnjjyJI80v5eb160DYPf69UWMciD+UISlC2YVO4wpj6YJO8SpwvXvf3+/T/mLF2TMNU1DkiR2CkvE4aFDjwUXh/kDJuzYcONlJhaKbytldKjkYkJ4XApNlcjF9eTi58TyOQ91FXtNodRFlc9ZM+ZT0lUJ9UKT55R9q5QUBrtKJjyZei3Gh1GvLde0/lYLg91JPhK49PqjxFh7mNdNq+BPPn8P+7ad5Pc/3cycJU2svnMBmqbx//3f/wvAl/7yL8ds/1dDMi0G1hQbWVHQ68Vn9lTh7z7xiTG7AJuySiP60DRmPuXkaz+8lz977CfE6eEorzGPe9AV+dditGskhf3esBnKQ10yDB52pOZ7M+rJK5lKqvV2HIgMSCmgMxaOn2D49JWxjIY4N6oqeYMBg6MMTVXI+jpQcxl0ptERh33ZpqEYa2Fud1q45uY5zF02nZ9840WW3TibPW+f4M239rL2mmu4e82aMdu3YGISjsYpF3aIU4b7b755zLY9pZXfT9b/MVUeD79e/2lqmIseIzLZSz4nQjuH+QMneHPAuqOZhZJ0wl1itNBkiVxUT7LTSOSoifBhM7EzRuSMhMml4J6Zp3x2b416tYzRoYJ0rkZdb9GQs1P6bVJClLZt5kSh+qnwiOvMLXKejMGAuW4aSjqFpa6Z8OaXUDKpEceXPLaXyNZXLrnOeNSXO8usVNWX8/JvdvDm83sx6PV88c//fMz3OxxS6QxWi/nyKwrGlGA4RoUY3iQYBaZspvyFdfcO+PnHT32QlQ89j4py0ef4OUqAYzSwlDg+jvAq07iGxEMFA/meh8pH/GGnM2pTYoR4MekT6rnoJTLqUp/7jYaclUBcKBUdvUVDERdIo8aF56rhJBYsskzKaMRSO43I1lfx3vYeEvu3Etn2Kp7V91zVrV1N00ge2UPiwDZsMxdcdv2xzpgDVFS7OHvcx6pb5uBIuXE5Sst60B+MUFVROpNFpyqBcJS6qorLryiYFPzjf/zH5de5ygv4KSnKLxTkAA899BX0GDEz9C0oH0cIcoIW1mDChpNq7Hg4xVvYTuaxNbeNSmxGhxjnXgwuJtTLmnPoDOBuyReEutJXoz66zaSCy2O0acjCBWfMGE7duUXOE7LaMJRVoCTjgIZj3gqCrz9NpuME1oZLT7pLnTpE+vRRXIuvw+DyoCRjxN7ZjJbPobe7MFXUXDaG8fAtv+GuBUiSRD4n85OvvkwyncZeIv7kAL5QhEqPsOErNsFwjIWzZxQ7DME48dKmTUMmHrK5HJUeD9Pr669621NSlF/IHz/4E3o4SA1zBnmWa2j4OEKIk7RwIyZsADy+/lEA3vfgdzi052WsTTOR9CP/dZqcKimfcPooBTRZAgnip4301ZRf2ExKr31lX326nNQJH+0xwmBXyQTEe6MU0Ksaik6Hls+BTgJVQ9LrcbQtI3FoB5b6GRfNlivZNPG9b+NoW0LozeeR9HpQVazNbeitDlLH9mKuvvoPtdHEaCqc0w1GPYvnzGHD1q0lVVPuD0ZobqwtdhhTnngihdNhK3YYgnHirZ//fOjlu3bx9R/9iC9/5jNXve0JK8rvfPyZQcuGyoBfyXYsdKGh4aKuf3mWBFE6CHMGCR0zWdPvad4nyAF+vv4TLP/jrcjxCEa3d8QlLAaLipKZsIdlkjG4yXPIZlL9EPaMakGg900nnbK+86OIwaIhZ8TvcSy5omy5dq62P3lsL5b6loKwBsw1jcT3bEaOBjG6vUM+Xc2k0Nsc2FsXYmmciSbn0dtdZLvOEN21Ec/quy6b4BiPLPmF3Ll6Nc9u2FBSorwwzVM0GJYCwg5RcN2SJWzbu5d/f/xxUb4yEjrKj1EXLmTJFWR8HCLISdw0UsdCHFT1Z9DPF+R93L5kIW9GQxf9ELpytN5WNvHmLgX05itr8hxSqOs0DHYVo13DWpkvTCJVJfKpc84v2mSf2DraSNplnHIEo8HlhLlJUcjp9ajZDKkTB6i46YH+xyRJwlw7jWxP+0XPh5qioGTSxPZswdo0k3w0RHbfVuRoiPJVt2IsqyiK6L4cvsozdPT08FwJCXNVU9HrRLljMVEUFZ1OnJdGE0VR2Lx7N8+/8QYvbNzIlz7zGe5Yvfqi62/YupW/+NKXBi3/9he+wHVLloxlqIOYO3MmX/3BD676+ZNGlF9NlrwPJZ3ERjlROuhgD3YqmM2tg6Z9DiXIAWZNn87rb24HRjY9z2DVkNPiBFsqFOr7r+5kO9TAI3QaRlshq26tyKMzFkbGy+cJdWH3NzSSfgpPuS0xLLJMxmAkeXQPlrpmDPaBrhN6uxMlcXFRnTqxHy2XIXV8H0o6gRwLY5+5gLJla3j0xjRQeoIcCqUsq989h6/+4Acsamujvrq6qPHIiiIEeQkQjgk7xNEmHIvxpe9+F0VRUFT1suvHkkksJhPf+eIXByxvaWwcqxCHpCcQ4LcvvTSi9+WkEOUjEeQAksHIYcsGTBkDjSzDSdWgdS4myAGcdjtKOjVi5xXR5FlaGO3a6Nb3q1Jh2uj5x1jSMPQKdUd5Hr2xcLdETuvIJ3TISanXjWdqC1KjTUy5HU8ulS23yHkSJjOZ7jO4l9806HGd2Uou0H3RbTvmLMfRtpTga+sxVzWQ83chx8MssR3kwE4JnU5C0knodDp0OgmdXkfdtArMluIPjaquL2fhDdP5/De+wQ+/9CUM+uL1OITCMTxuYcNXbILhGBXiOIwq3vJynvve9+j0+bj7ox+97PrReBxveTlL5swZh+hg1XvfCxeUK/VdQGiaxqcevbhevBwTXpSPVJADuBasQme2UP+6flCjJ1xakGuaxle//SR1zBtxHEaHSqK9eB88GhoyWbLEyZNBjxEDJvT9X8Yhfz+TFf141PdrEnJvg2j63EIM1oJQt9Uq6M2FoiYlc65GXclMLaFusGvIqanzeseTLvYRpRMTNsqZRvbBBZesj7XIMgGbHTSNxOHdGN2VWBrOZcz1FitqNn3R5xvsTpLH92OqqMHW3Ia5up4WeQ9nj/tQFQ2194NNVTU0VSOXlQn2RFm6upUl17VithZXnC+7YRa/ObKRP//O33Pd7YXz/qOzPjDucfhDUaoq3OO+X8FAguEo1V5PscOY0sQSCTxu97jt7/bVqwedI3WSREV5OasWLWL5/PlXve0JK8pHQ4wP2s6nh//8dz30VQCcXN7C63LoTeMzrVBDI0eSLHEyxM/7HgMkzDgxYkUlj0wOhSwyOVQU9BixUc4MLl7fNTko5iRPCTktFUqZ+qeXa+gtvUK9SkFvUZEAJXeu9EVOX2466cTFaFNJ+4ufKZ1MKOTxP+glvCGMua4Nnc1B59G96Da1U7b0BvS2oW/J6zQNVafDvfIW8mEfqRMHkHQShtaFhcdNlkuK8lygi/iezZQtvREAvc3J9dfOv6SwPdnezt/+8Kv84CvPsfi6mSxd3YrFahrBq796JJ3EnY+s4Il//wNNrdU0NI+0l+jq8IcitEyru/yKgjElGI4xr3V6scOY0sQSCfyhEA/9r/9FR08PMxob+eT7388Ny5ePyf7+6VOfGpPtwgQW5cUiFI1yuqODQCTCv3/lJYKcoIq2kWeQddqYWempKMToIkonGWJkSWDAhBknFlxYKaecJsw4MWAe8Fo0NLLESRMhS4IkQRRyYxJnKVFo8iwlgSuhZCSUjI5MsG+Zhs4ERruKxaNgsGpIusKFXb9FY2pyWDRKhtKvKVdR0HHl5QwqCnG6idBBkgANDRU47XZOHo6ix4geE4be7/qLfPc/6L0i14fzS+uyJDjJJrK6NPo/2LDUNZPtOk3Fmvux1DUT3PA74vu24l55y+ANaedPu7WSDPSgZjOYqhv6l+sukylX0kkAUicPYp02C7h8prm5oYGf/cP/45ub/ou3XzvED/7teRZf28LSG2ZhtY2/OHe4rNx4z0Je/91uPvgXt477/gF8wQirlswtyr4F54glkjid9mKHMWK8r8SwjOP+MsQIXn61K2JGYyNnurp47113oZMkHl+/nk9/6Uv89KtfZU7LpWcmjAaZbJZTHR3UVVWNeMCYEOXD5F++8x1e2bIFJ9WYsFPONNw0XP6Jl8Fov/KmQhWZEKcBcFHb750+FBE6aGcnVspw04D+pqW4nG50hkLWcag6eA2NNGGidBKlAxUFOxUYsVFG3ZA195MNo12bADXMEmoOsjk92fBQ00lVbDXnWTROWOeX0nVdSRGim4MkCaAi08IaHFw8c3q+EI/RjRU3bur5yXf+P3L5PPFEglgiwde+9BIKeWJtetR8FjWXRstnUfNZtFyusCyfhac1dEYTksnc/93o8mBtnoPBfi7T3WfVqqJwkk2YFy3E3TynYEO4/TU0RUbN50gc3AGahmvR9UPGb1YUsgYDSiZFaOOzmKsb8N76bnTGc8JYMprRZBlNkYe0Nsz5uwCwNBSGrQznruenrv84T1Q+SSSY4O1XD/Gjrz7Pbe9aRuuCkZ+Dh8vxA500zymeR3g2l8NiLs7dAsE5NK1QuiAoHu+96y7ee9dd/T8vnz+fez7+cX72zDP8n7/4i1HZR16W+caPf8ynHn0Uq9ncv/ytXbv4/De+QTxZSDZ88P77+cyHPnTV+xGifBise/AJFKopp4k0EepZdNEJoMPF5FDJXUGTZ54MJ9iICTtZEuRIUsdCQpwmyEkUclgpw4YHDZUAx5nBamyU0/NQOUr3GRJH9mCwOzHXNNH9QBXep33IZMmRIk43UTrRoaeMeppYiRX3lKolh0J9/0Qd4jTkdFKdhsHWa9FYkUdn0NA0CTlTEOpyUkLJlmadusFaev7kGhrt7CROD1XMpokV+DhEiiAOvGioxCm8r1RkFGQyRInTjaVXiNexkJ+t/9Mht79m/UrWPfgE6pxLe4ZrilIQ6vkcaq7wPevvIPjaekzeGmwt8zB5qkCnJ0WEHg5iwY11RiHDaqmbhvH295LtOkN8zxbkeATP6rvRmcxD7s8i50mpCqGNL2Jtmolj9hB2Y5o6qAkKQEnFSZ06TLbnLNZps7DPXHBVZYiPzvoATxx5kjves5zuszP4/U83Ew4mWHnT6ExVvhJOHe7G1xHhrvddM277PB/tvDsWguKhqqrwJy9BbFYri2bP5lRHx6ht86e/+x0vbtzIJ973vn5Rnkqn+eJ//idmk4lPvv/9BMJhfvzUU7ROm8Z9a9de1X6EKB8Gj69/lHUPPkEjywlykmNsoJ4luBn59DmjQyPZc06UZ4jh5yhZCp56OoyARoowlcykitkc4Hk8TAcgTQQjFhpYTJooKUJkSTCD1Vhw0fNQOZnuM8R2bsQxb0VhrPWet5CjIQIYMWDBiAUHlcxgNWacU06In8+4NHmOI5oqkU/oySfOWyj1NpTaChl1vblQRy9n+wYf9dapF/nvwGBTkUvsroWPw6SJMpvb0feeRk3YSRNFQ+M0b5Mjzdo1C7FbrdgsFhpra1l7zTVUXGFD0qUazC9HKp3m96+9xlMvv8zJrS9jNBiw1Ll5aOVKPvmBD2AynqvPv/PxZ1BSceRkjPLr7xyQ9b4QUzrF2X1bsE6bhWPWoiHXSZ85hsHuQtIb0FSVbM9Z0icPkQv7eN/tt/Hu//WREVuV9QnzmkYPf/TJmwv13S1V1DReuuFO0zRkWSWfzXN0Xwc7Nh5FVVRufmAJMy7Iep8+2sORPe00tlTStripf7ksK7z69C5ufmAJRqO+KE2eiWQah816+RUFY0oklsDtGlm5gmBsyOXzOGyjN2V14/bt/NE99wwoT/nx+vX4w2G+/YUvsGpR4XyoqCq/euEFIcrHiz5h7mUGNso5zRaSBKhjARJXJhxUVNJEsHPuA0TSFYbLZIjRw0ES+PEyk3IKHwbBVYVqr3KXG+wuznScRNmp0Dk3Qfr0TqRomlrmYcWNFTcepg3YZy7kI7rjDcqvvb2QOQNmHm5BQ73iuKcOxWzyHEe0QkmLnLqgodSsYbBrWCoKdepIGprcW/qSKgj28axTL1hTls7faI4kfo4ym1v7BTmAg0p6OMgpMuTJsOFX3xsgfscTm9XKI3ffzSN3300+nyeeSuEpKxty3cfvWcUdT/8I55xlZDpPYbA70dtd6Cy2/iygpqqkzxxFl0qh1TTi6G3qPJ9csIfk0T3IsTCuhdeSOLST1KnD6C12rM1tvP7Nrw247TtS+oS5w2XlpvsW8+KvtvGBT92KwVC4Q6RpGh0nA+zdepIzx33ksnnyWRmdXofRZKC2yUP9dC8nD3XxzJNbePTTt1HuLXzgHt3bzstP7WTZjbN4/hdbaWqtxmYvxL59w2E81S5mzKktiiCHQpNnVcVlJq8KxpxgOEZFubBDHG+S6TRWsxmdTkcileKtXbu4/fpzJXeBcJjdBw/ygfvuG7V9Hj19mg+/6139PyuKwlN/+AOLZs/uF+QAy+bN41cvvHDV+xGi/CroE+Y2ymnlFs6wjWO8wXSuGTRw6EIyxDjDNrIkqGAGtcxHZ1TJ5nKcZjcJ/FTSSgPLBnzgJ2sHnoDleARNzpMP+XDOX4mpso6cJNFz3jqapqJbvxWf4yza23nKFl/fL8j7asmFIB9M6TV5jieFMhYlC9nQBXXqNhWTQ8VWXahT1zSpX6QXBh8Vnj/alNpdC5kcRiwkCAAaNiowY8eCi2msIkucn/30M0UT5BdiNBovKsgB/OEwqxbMZ3cwCJKO9OnDKIkYqpxDb3WAqqLmMhjKKjDPXoa1emBGWVNkYrvfIuvvxDFrIeaqeiI7XsdSP4Pya2/HWFYxam5ZF9InzNsWN3J4z1me//lWFqxsxtcZYd/Wk+j0OuavaOba2+ZisZkwmgzo9efOec88uYVkPAPA3q0nmNZazf7tp+g4FeChD6+m80yQmgYP1l6nl2goyY6NR/ngp24tmiCHgiivFHaIRScYER7lY8Hpzk5C0SiBcEGnnGxvZ9fBg3jKynDYbNzzsY9x/ZIlfP1v/oZ9R4/yd//+77y+dSurly5FkiS+/8tfYrfZePSBBy6zpyvHYbNxtvvc/IXn3niDYCTCZz/84QHrReNxbJarb5ktnU+6CcS6B5/o/78BE81ch4/DHOFVmlgxZCOkgkyAY/g5Si3zKaOOU2whUrcFVdbhMbhZ98c388hdd2GzDi3s73z8mf7/O9qW4Gi7+PhYJZsmuu01jORpTizFRjnSVgkY2YCjqYDRrpVcuUSx0WSJXExPLnZenb1Ow2jVMFww+KjPT11OjWb5S+lcJKkoZIgR4DhGrHTwDi5qqGUBDrw48I64A388md/ayn9dMAkPCiUwXYEAJoMBh92O02bnl8++xvsfuHXAuSh+YAdqNo33lneR83UQ27sFz+p7MJYV7gSOlSDvo08cP/A3D/CL555j05u7aK6v59//6gMsnD37kjW/qQcyzFnSRMgfJ+SLs/kPB6iodvGhz97B2eN+Nv/hAH/0Zzcj6SQ0VeOV9TtZdsMsyjzFddvwBSPMntF0+RUFY0ogHGXWjPGdGjkV+MGvf83vXn21/+f/+vnP+a+f/5z7b76Zv/7IR6j0eKiprARg1aJF/PBLX+Lnzz7Ld/7nf4gnk6xYsIC/euyxUT0PL2pr45nXXuPuG28knkzy7Z/9jOl1ddx63XUD1tt39Cizm5uvej9ClA+T8wV5HxIS1bRhw8NJ3qKVtVgpZKYUZEKcxMdhHFTSylrMFP5QXv/Vd9h//Dhn2oNcs2gO1ZWXrod8Yd29Az4Mh0LTNHKBLqI7NmBtnEmLf4bIhg8To10lHZiYTZ7jiir1DzM6f/CR3qJhtGlYvQp6a8FPXZWvzqZRZxwf7/7hYMZBHQvw0oqEhEK+96L8ZepZPCpuTKWAzWodUPvdEwjjLS+c1/rORflIkPTJg3jveAQ5HiG6exOe6+4cN0F+PmVOJx995BE++sgjV/ycjy39CE84nuRC07R0Mstz//M2Dz22Gk+VE03VePmpneSyMsvXzBrdwK+CaCyJaxLY8E10orEkbnEcRp1/+tSnLukF/vvvfGfAz/NbW/nnT396TGP6s/e/n3V/8zfc3OusotPp+N4Xvzhgqm+nz8f6l1/mL4X7yvgwlCA/HwkJPYVb1hHaidBOnB6cVDGDG/qFOpxr4lrc1sbegy9d8a3ISwlzJZ0kvPkltHwW16LrmbZldJxhphp6q4qcFm+Nq6PPTx0y55W/6AyFjLrJec6mUeutac+nCmJdzQ3OqhtsaqHmvYQwYqGSc8JMj5Fa5uOijjNsI8wZAuF78ZZPrprfHn+Iau+51/TCunu5/fu/weCuILLlDyiJGGVLb8BY7u1/fCLQVwJzPjqdDrPVSE97mDKPndd+t5tENM3DH7mhv2a9mGhowoavBNA0DZ2utM5PgrGhqbaW//na1/jdq6+SymS4/frrmTtz5oB1du7fT+v06bz7jjuuej9CeYwiEdpRyXOKLZixU0Y9DSzFQKEeseehwgfa+R9Waq+11dW8sXMhHzqjCYPTXfjZ14Gk01Fx23upeTo6wlczVZkiTZ7jjDqETSOShsFWqFV31CnoTYX3gpwtZNPzSR1GuzKwZKaEseNhNrdwgk28sX0777rttmKHNKr0BMIsaJsxYNlLf/owd+gNJI/tw9o4o38K6EQR5H1cKMzNViPv/pMbef6X23jzhX3MXzGdux5ZicFY/L/FfF7GaBAf3cVG1bShnD8Fk5iayspL3om7d+3aQeUsw0W8s4fB5SzKNO2Dw/YsDYSiVHrcl9muhizLZPN5Hv7Fy0i9Aj6z4U1yJJnOddjxIOPiNJB8+vdkWTJqHupTCb1JQ8mJM+24oEnIyUKjaNrfvxC9qdf9xaNgrVQxOTVUWenPqstJHWqJDj/qqze/bvHiYocy6vhDEbyewQ2jLz72ADB6DVXFYlDj5qzCsKJSIxCOCsePEiAWFyVEgsFYRugwJUT5KHI1QwTOdvporB3YGJrL59l75Ajb9u5l29697Dt6FFmWUVQVW8s8XAuvpeKpbnzEqGcxp3kbAybseHHTQIxujvAaC7h/tF7alMHo0MhfwRAnwVghoeQklBxkw3oMNpXIETOSvnf4kU3DUpFHbzivqbTXAaaYnuoaGnG66eYAbhr7m5AmE4qqDqifFBQHf1DYIZYCgXBUOK8IRh0hyovMj3+4kUS7ETW/EYU8QU7g5yi4nZgrazF5Gyi7fRlqNkNww9PYWxdS9VSIDg7gpAYP0yiniSR+UkRIEiRH6pKjvgUXRzR5lhCSBlqvT7YikY/rycfPX+FcU6nFq2CwaEiShqr0TintzaxrY5xVj9FNN/vRUKlmDmWjMEys1MjLcskK8gvrwWGIrPckwheKMLd1erHDmPIEw7H+xmeBYLQQoryIrHvwCcpna8h5DT+H8HMMJ9WFptBIGT1ry6l+KoxKjIO8QBmVWF84zinOIpOlmYJZvoSEgyocQ1gxCoaHaPIsHQw2DTl1KUF9rqmU8z3V9YU6dYNdw+rNIxkKtepjYdWoInOat2lkOWXUTdopuP5QtCR9saeaIIdCyaMQg8UnGI4yc9rkuwAXFBehPorEugefAJ2GqsJZtiGTo5WbBtSB9w34yZNCJkOGGCoyDqrxMH3AcCHBaNDXuDM5hdVEw2hTyV+F84qmSOTienJDZdXtaiGr3mfVOMKsepIgVspwn5cdv1zvyUTkQueVUmAqCnIAWVYwGcW5v9hEYgncZRNnHoFgYiDe2UWgz1rRYFMJJrvJk2EGq9Ex9O1hM04W8fB4hjgl0Zk0lCk7ybP0MNpVEp1Xd4qK48OB9zyP/r6sug6C59brr1XvzarrLqxV78uqa0P/XRT2c+4O1WQU5FBwXlk6v/j+3H1MVUHe59YlKD6qqqEXdoiCUUaI8nFmgNe5M0Zn4gR6zIQ4iQ0PVtxi2E+REE2epYXepPV6lw+PBAFOsBEnNTRz3SVLSi5bq+5RMFh7a9XVgq96n12jmocEfupYAExeQQ6F+tlSdvyYCoIcCo4fZS7h+FFsNHFxJBgjhCgfRy4cPmS326jqWUqSEClC9HCYSmZSxewiRXhp4vRgxokJW7FDGROMdpWMaPIsEfo+9IYvymN0UU0bAU4gk8GIdZhbuEituq7gq26wqTjceSSTQhszsOdcrPvwCs52+qj2lmMyGYcdc6mjampJZQWnigi/EH8wclkLXcHYE0ukcDkn5+egoLgIUT5ODDUNVKcDi1qGhcJXAj8WSjcb1cleciRoYsWkdJgwiCbPkkE3Ar/4FGGqmIWRTmSyVyzKNTQyxIjRjYaMkxpsePoz7ZoqkU9IRBMRUoSI48OAmWmmJpwOG8fPdPLWzn3k8jJ6nY7KCjc1lR5qKj1UuF0TdvJfLpcXNcwlgi8UocbrKXYYU55gOIpH2CEKxgBxph0DhhLgF6IzaKiyhEKeLvYRpZM6FuKkZhwivHrqWEQ7u9BjHmC72PNQeX9j6sRkajR55skQpYMkQXToMWDBTgV2vAMahzU0siTIkUBFxUU1unE8XRjtGvnkVTR5opEmjA0PKvKwYj7DNpIEcVGLHgPt7EQmi5NqXNSioRHiFFniuKjFRjkVzEDN6WhraaKtpal/W7Ki4A9G6PaH2L7nMKFIDFXTsJhN/UK9ptKD01762baeYFj4YpcIgVCEhbNnXH5FwZgi7BAFY4UQ5WOAQo40UUDCgAkzzkF1rQaHQjQR4zBbcVLNbG7DgKk4AV8BGip5UriowYiFs2yn/IFH+qeLwsQW5lOhyTNFmKO81ismm9FQyZHGx2HSbMFCGWac/U4/ABbKkMkSp5tGlo1brEabSiYy/FKiNBGMWDBgwoSdDt6hnMZeoX3xspI4PlIEaeP2/obrl9b/G50+Hxu3b+eN7dvRNI0/u/lR1l5zDWbTpd+rBr2e2qoKaqsqBixPZbJ0+0P0+EPsPXSCRCoDQHmZo1+oV3s9JZWZ7gmEqa4U2dlSIJ5I47APtxxLMNoEIzGmN5Z2Ak0wMSmdM/8kIRiJcJTX0WNAQkeOFBI6XNTiohYjFtJEcDpluoKdNLFyQgz6ab8xj7THRWhtHZpSTe6Zt0FTYZI0pV5tZnYiYcVNA4vp5gBpotQwt1+oqsgkCZEjiRELZhyYcCAhkSHGMV6nnEbMODFgGXM/boNNQ+4c3j40NAIcw00jANNYRYxOwpylnV048FJGPS7qBl0Ad3OAWhb0C/K+ps26qioeuftuHrn77lF4VWCzmJnRWMuMxtpzcWsakViCbn+IY6c6eGvHuRIYr+e8EphyV1Hqunv8YVYtnTvu+xUMzdVMjhaMLuFonPIy5+VXFAiGiRDlo4iiKHzsH/4BCYkmVmDG2VunGiVGF13sQyGHFTd11lnoUk3jWhIwEuRYBIOrkC3LBbowuiuQ9INjn6jZcqNDJROc3E2eEhIVzMBFHV3s4wDP46IGNw04qcF5keFTBsyUUU83B8kSR0XpL90oDMzRkSOJBpgZHWcI6bxpnleKn6OkiVDPot64TXiYjofpKOSJ0UWUDjp4Bxse3P0C3UyGCE6qgfF3UZEkifIyJ+VlTubMnNa/XFYUAqEo3f4QO/cdIRiOoWoqZpORaq+HGm85NZUeXE77mAo1IUBKg2w2NymbiCciiqKW7IRbwcRmYijCCYIkSXzw/vv5ynOvcrh9AzW5VqqYjRU3VtxUM6d3TQ0LOdIT5Nff81A5en8a+cQBAHL+ToyeajRNG1IMTERhbrCqyKmJcTxGihELTSzvry/3c5Sz7KCaOVQyc9D6BswDSlcUcsTx4ecYfo5SRh0+jgAwi1tG7M4j6Qr2g1dKX4Y8wDFmchP6IcrA9Bgpp4lymlCQidNNlA462YcBMzYq0GMsKVtDg17fnyU/n0w2hy8Qptsf4vDJdqLxBAAOm7VQ/lJZEOw2q2VU4tDQ0InsbNHxh6JUekQdc7ERdoiCsWRqqJBxQqfT8eCtt/JfHRnssxbhe+HXeGgedKtcb9GQMxOjVCJDjNieQyipBHIshJyIYfRUEd25ETkWpvza2wfUlffR81ChMWxiiPOp0eR5IUYseGnBSwtZEhxnI3oMeJh+yefpMeGmgTLq6WA3QU7SylrOsJ00kRGLcoNNRU5dwlu81y5RQuqtdj9IhhgzWYMJ27CEdTaXY8/hw8yfNQur2TyiuMcLi9lEU301TfXVA5Ynkmm6/SE6ewLs2neUVKa3Xt3lpLqynBqvhypvOeZhZFsz2RyWy9TPC8YHf0jYIZYCiZSo6xeMHUKUjxE6kxnVpEfJ5QeJcpNDLfkhNQp5OtlLxNyF1TAHa+NMbC3z0NsdGBwuzLVNRDb/gdiet3Atuh41mybbeYp8LIxzzlJ05sJJayKIc52Jq7bfmyyYcTCD6znOG5iwDZhSeTEkJBpYgorMSd5CQ8XMyMdOX66+/zRb+u0IVWTKmUYDS9FjGHam22wysWLBgpGGXBI47FZm2uuZOf2cXWlfvXpPINxr2bifXD6PTtJRUe6i2ltOdaWHKo8bg2Hw7fgef4hqr3BeKQV8wQhL5g6+kyUYX4LhGBXCDlEwRghRfpXc+fgzvLDu3os+nmk/gc5kxpwbXGNrdKokOkq3NjBBgLNsw0EV3tvei844OFMmSTrKVqwltOF3+J9/Ek1VMVc3oDOaCb7+NN5b3z2g5ryUS1qM9tK/SBoPzDgxYiNPdljPC3AcCR2trB2VBlCDTSUTuvj7o4rZxPFRzyIcVKPrbTYupdKTUuH8evXzLRsVVSUUjtEdCLH/yEk2hKLIinLOX93rodpbTqcvJJxXSoRQJIanhKeqThUC4SgVooxIMEYIUX4V3Pn4M/3fLxTmfY+h06EkomioSBc4lFzp+HANjRxJUoTIk0GPET2mAd8NGNFhvKgYUpDJECFPBgMWjL1fFzaYamgkCRLiFHF6aGAJZdTRM4Qg70NnNOFZcz9qLove5kCSJPKRAOkzR5lIpSBGu0omJJp2QpxGQsJNwxU/RyFHD4eoY+GoObLojRpq/uLbsuGhhrl0c5CZ52X01z34hBDmV0if+K6scLPgPN9rWVbwhyL0BMLsOnCUPYdOUOEuY9f+o1RVuKn2eqiuLMdT5pyww5AmKqK5sDQIhmM01V7+TqJAcDUIUT5M7nz8GTRNJdt5GjkR5fq/3srdLXXEk0leO3IKNZ9FzWWREhmqmTtIkCNpaJdoYlPI9wpjHylC6NBjw4MRKxliKOR7v3L931UU9BjQY0J1W9AZzUh6A3IiipJOYHR50FlsqNk0aiaFkkmjV3UYsGDAjEKePGkMmPEwjToWYMDM4+sfPXeRcRF0RlN/Jl3JpAhvfgnX0huQLvjwKNUsOYDBql2yhnkqoJCjm/00c92Q4rpP7F44GEvCQA1z6OEQCnmqmDXCSPoqxi+Nl5kkCHCKLTSytH9qpxDmI8NgGOiv7gtG+OCDt5GXFXzBMD2BMFt3HyQUiaOhYTIaCyUwvV/uMqdoCh0DVFUVVoglQigSE9M8BWOGEOXDoE+gxvdtIxfoxFxZj2Q08WJXDMlowto8B53RhHdjBgvOwYKcvnrZoU+uMbo5y3YcVFLONGqYi4qMhA4Ttov6Q3c/UIaWz6Hms4XvuSyanEfvcGFwlg9qxNQ0DS2fRcmkULOZgrC22Kh9PtO//T5h88K6ey8rzPuIbH0V24y5WBtaBiwvZUEOvfZ7EyizPxZ0cxAXNdgYXD98vsh9fP2jA4S5Dh2VzMKAlTNsxU09phHYIuotGsoVNEFLSDSyjEO8SJizAy4GhDAfXSRJwmQ00FBTSUNN5YDHstkcPcEIPYEQx3d2Eokm0NCwmExUnS/WXQ4hKkdAOJqgvGzk/RqCkaMo6pD9FwLBaCBE+QVcToBqikz61CEqb39vfzPjhVi5uAg1XqLJs4eD1PV6LHezH5V8r8DRyJFGNUNFthEP07Fw7kpd0umQzBZ05iuzQJMkCclkQWcauL7voYJrxoUlOVcizJVMCjkWwrN64JCVUhfkOqOGcolSiamAikqQkxgxc5w3MGDBjgcPzTyx/kMXfV5feVWA40Q4SzPXjUiQAxhtGvnz7lqoKORIoqKgoqChIJMjRYg43biopZLWEe1TMDTJVAab5dLnFLPZRFNdFU11A2/nZ7I5egKFzPrRU+1EY0k0NKxmc0GsV7iprvRQNsYe65MFfyhCZYW72GFMeYQdomCsEaL8ElwoRjVFJn5gO8aKauR4hNyJg+TCPrR8Hp3Zgs5sRWe2kFpsp3F3OQYGW6wZHSopn6G/ZKTvK0UYmQwaKj4O0cCSQcNcstk4QU5xnI0YsWLCShkNMER281JNqBdyoeC+sFb+soI8lSB14gDmqvoBWflSF+Rw6YukqYIOHXO5mzxpZDLkydDFXvJkBmWd1z34BD6OEOQ4Su9dnHIamcUt/SUkI0FvlwkFYoTw0ThPz4Hjx6n0eLBZLNhMJiwmEw6bjfmzrmPxnDksmj1b1DaPET2BENWVV+e8YjGbmFZfzbQLbBvTmSy+XrF+5DyxbjGbqK4oZNWrRGZ9EP5ghMY6UcdcbFLpLHbb6Pj/CwRDIUT5RegTpecL81ygi/Spw+gdLqI7N2Kpb8Y2fQ46kwk1mynUbGcz5ALdHDBuxzl3GdPfqen1U07i4xAGfRV71R2A1Nt0ae0V2HZmchPt7MJLy5DTFc04qWMBtcwjSZAEPs6wjarcbHQm86DYh/NaLybMCzX0WuEipPss+VgQTVFAVdAUBTkRBUXBWFFNU1cLtgkgxM9HNHkWMGDqte4sI44PmWz/3Zg+Yd5XtqKQw0UdVczGgHlUGjwV8pxlO82WGs6mz/C+d9/E0rlzWdTWhsM2Mt9zwdXREwiPuh2i1WJmWkMN0xpqBizvF+vBCEdPdRCNJ1C1gWUwVRXuKVuz7g9FWLpgpP0agpESCEdFPblgTBGifAguVr5hrKgBnQ5zZT2OOUuHHDPfhxyPEN2xgYOeY+gdZWS7z+CaMQ+81XhbPzCkzWAI0HXm6Nz1JsnFXsx10wtCP51ESSWwbfWTJ02OFHnSZIjRwBLkEQjyC19j6sQBsj3t6EwWrtv7NpqcJ9vTDhKYqxsxVdYj6Q2Ub0sjocOMHRMOpK6J+UFpsGrI6YkZ+1ghk+kdQ3/OhWXdg0+goRLmLEFOUkYdRkYnYyST5QSbsFJGmVTLpvX/MCrbFYyMnkCY+bOax2VfFxPrmWwOX1/N+ulOIrE4qqZhNhmpqigI9Srv5HeDSaWz2EdpQqvg6gmGo3jLhR2iYOwQovwCLiZq+5arH37gik/+efl9vPb223T09PCu2/6Bbl+YSDzBNYvnXvJ5+4/dyV9/5SsEdr2B3Wql2uulxuul5u4Gqr1eaisrqfZ6aWlsxOUYveaf5LF9pE7sxzlvBWo+j5rLIFlt2FvmoXe6+28nF8pSJsdAEUnSQBOiHAo14kFOEqWDFCF8HKaaOf2PnWQzCnnqWIAd76jtN0Y3KjKNhiXccNP0UduuYGTEk6miTy60XKRmPZvL4w9G6AmG2fbOoYIbjKZhMOip9Lip8rqpriinorwMvX7ii/Ur8yQSjDXBcIwFbTMuv6JAcJUIUT5MhpONMRoM3H799f0/b3vnCHNbp132efNmzuTpb30LWVXHdPS3pmkcP3uWjdu3898/eZY8aWZxI6atQzXrRcYsjmIhmjwHopCng10ASOjIkUJFRYeOON3IZHoHBI2uyCmnER+HydsC1FYtG9VtC66Ovoa2Uq3rNpuMNNRW0lA70A0mn5fxhyL4ghF2HThGMBxFUQv+3hVuF1W9ZTCVHjdG48T4+EumL99wKxgfghExzVMwtkyMs9IkoScQYu11S65oXaPRyFjM/Mzl8+zYv583tm3jje3bURSFfMBFFW04qETH1KmvNtrVS45zn2oYMLGIh5HJcYotZIj314tL6MmTpoN3MOPESRVmnMOuJy9k/DRUVLTeLxUZG+XkbH5qq8T0yFIgkUzjtE+8Wn6j0UBdtZe66oF3cmRFIRiO4QuGOXjsDG+E9iDLCpIE5WXOAaUwFvPFB6YVg0BQOK+UCrKsTJiLOcHERPx1jROapqFqGvpxrntc9+ATdN5tIdt9lmz3GXL+TgwONxXhSlwswIJr1CYxTjSMDtHkORR+jqKSp4Ub+v82nFTRzGqS+MkQxc9RAGwUXIb6BlH1fYFGmkj/V45UvwgvuIzrkNCh6/3uoIoqe2P/0BpBcekOhEa9ybOYGPT6fs90Zp9brqoq4WgCXzDMyfYu3t59kEwuB4DLYesV6wXB7rBbi3LnwBeKUCVEuUAwJRCifJwIReJ4ysbntpemaRw9fZpPffr7xOgi81wcJ1VUUYOTeRjD4lYoiCbPoYjRRYR2WrkJPQMzhr9a/+f9/9c0jfc99G0yxMiTQSZLmghy7/8BrLix4+XbX/8LGmpqMBmNGPR69BcZFf7EUy9htYxduZbgyukJhAdlmycjOp2OinIXFeUu5sw8V1qoaRqxRApfMEx3IMTewyeIJ1MAWM1mKivchcx6RTnlZY4xbTL1ByM0N9aO2fYFV0YqnRHnJ8GYI0T5OHG2yzdmPrMHjx/n+Tfe4Gx3N+3d3bT39KBkdLiopYa52PFeUVlKjhR6DIPE2KRFNHkOIkMcF9WDPPYvnJApSRK/WP/JAdM9h+JKJ2sqiopOEqVEpUKPP8ySeVN3KJMkSZQ57ZQ57bRObxjwWCqTxR+MFLLrZ7sIRwuOMAa9Hq+njCqPm0pvOZXlZaNS6lCY5ukc8XYEIyMYjlFRLurJBWOLEOXjxJlOHzesWDDq2z1y6hSf/Kd/4pG77+buNWtorKnhnz/zOvorqEhXyJPARxwfcXpQkVFRsOFBt2gm5rrp6C22CTEEaLjojBqqaPIchA03XXQMWHYpYX2+f/lQj10pYmJhaZHKZIQF30WwWcxDDkbKy3Khbj0Q5sDRUwRCUfKyjE6ScLuc/dn1So97WANoVE0d97JHwWCCESHKBWOPEOXjRCSWwO0aHfvCvkE/ai5D4LX1OOet4KmMneqvHAeOX1SQa6ikCBOnhzg+MkSx4cFJNdNZhYUyVBTidNNx6jCxd97C3raEaiafBZRo8hwamfyAn69EWA8lzIcjyAG6fEHqRD15SSBGiV8dRoOBmkoPNZUDm5VVTSMSS+APRjjb5WPnviMk0xkAbBbLALF+YSmMrChCkJcIgXCUua3Tix2GYJIjRPk4ICsKBr1uVJqE7nz8GeR4lJy/g9TJg1jqpmNtaBkym62hkSPZL8IT+DFhw0k1NczpL2vR0MgSJ8QpkgRJEkSKqlQzl4pDk7OW0WhXyUREk+f5pAjRyTs0sBQYnrAergi/kC5f8LL+/YLxIRpPUuYcvfkHUx2dJOEpc+IpczJ7RuOAx5LpDIFgBF8owokznf2lMHqdDm95GWaTEZPRQDaXx2waCz8uwZUSDAs7RMHYI0T5ONDlC47YVSKdzXLnv32L1KnDKMkYpqp6HHNXYK5pHCDIZXL9JSkJelBRcVKNm3oaWELooYLITgFJTSPbdZrs29uRyWLHi50KKpmJhbJJ7cpisGnInZP39Q2HwtCgE/RwkAaW4KJmxCJ7uAQjMcrdom62FOjxh6iZRM4rpYzdasE+xCRTWVYIhqPs2HeETC7P03/YRPY8V5hKTyGzXlnhxuW0oytRP/nJRD4viwsjwZgjRPk40N7lHzTk4kq48/FnULMZ4gd3kDl7DL3NiaNtCebaaUi9tzQrnwqSINgvwjPEsVOBk2oqmYkZJ76HPOSA0HnbVjIpottfR81lcVyzHFftNCRJwjsJ68eHQkzyLKAg085OMsSYyU2YcYy7INc0DU1DCIsSoTsQZvoFIlEwvhgMeqorPdisFha0zaCxtmASoGka8WQafyiCPxjh0IkzxOJJVE3DaDBQUe7qF+uV5WWYhIgUCCYUQpSPA2e7/FftZKApeTQ5j6HMg5KME9n+GnqrA73NATodProx4+CPHr6Faxd/gEVtbZiMxku6YmT9nUS3v4512mwcc5Yg9bpeTMaGzqHQGTQUeeIIQBWFLvZhxo4VD1bKBrjppAgR6/07cNN4xXc4FPIc5w0slNHKWnTox12QA8STaVyOiTeoZrLSEwhzzeI5xQ5DAPiCEVYtOVfWJUkSLocNl8NGS1PdgHXzeZlAOIo/FOXQ8TO8GYqQy8tAIbvu7cuue8oocznERfAwyGRzIksuGBeEKB8HsrncVU+J09ucuJff1P+zpsgoqQRKKo6mKNT3LObJ9X8y6HlDNd9pmkbyyDukju+nbNkazNUNg543FTA6VPKJidM8lSFKiNO4qSfEaTLEMeOgmjm4qSdJkB4OYcZOiNM0c90lLTA1VBL46eYAdiqoYxESUlEEOfSVd4lJnqXCSM5XgtFlOMfCaDRQW1UxqFSyP7sejOAPRTh84gzRWBKNgo1jhdtFZYUbr6eMSo9bHPshCISjeD1lxQ5DMAUQonyMSWWyo3qSk/QGDE43BqcbgCfX33vRdc8X5mo2Q2TH62hynoq1D6K32gesO1Wy5DDxmjwtuLDhJkUYN/U00UCQE5xmCylaqWUBSYJYcJEhShf7qGcRGhoxusgSR0FGJY9Mlji+/qy6l5aiCnIoiPIZF2T9BMVB1bRJ3UsykRgtF5wB2fVpA99nsqwQjMTwhyIcP93Jlp0HyORySEjYrGa8nj6xXoanzIVeP3GSGaOJaPIUjBdClI8x7V3+/nrAYqCikDy6h+TRPVibZuGYu7y/Hr2PqSTIYeI1eeowMIPVJAgQo5NjvIau1/bSz1E8NOOgkgxRGljGIV6gjHo62IWEHgeV6DFgwIGVcmpZgIlz5SLFFOQA3f4Q1y2dV9QYBAXCkbgYVFMiJJJpnPaxLesyGPRUe8upHqKxN5nOEAhF8Yci7NjbQygSQ1FVdJJEmctBZZ9gLy/D6bCNirtYqRIMR5nd0lTsMARTACHKx5iznT7arvLN/MK6wVnwPo/y839+Yd29BCMRznR2Ek8miadSBMNh/vvHL5IggGNfJa3cgOWoC45GryqWycREbPKU0OGkCidVVDMHFYUTbCRLAhUZhYIzgwETZlyc5E3qWIiHZn6y/o+LHP2lycuyaEgrEXoCoSEFmmD88RV5oJbdasFebxk0JElVVSLxJIFghG5/iH2HTxJPpNDobTZ1u/B6yiZVOUwgHOM6kSkXjANClI8x3f4QN61aPGrbe2HdvQOEeT7sZ9Un/xJjxMeMxkacdjsOm43tGzspp4lGlg0amT6V0Rk01AnU5HkhGWL0cIgEPspoQI+JJAECHGcGNwDgoQk9M3HTUPQs+OXI52UM+olTSjTZ6QmEmTm9vthhCAB/MEKlx13sMAah0+n6fddnMdB3PZ+XB5bD7DpANlsYSGaxmKj0lOEtd+Mtd+Epd2E0TAwJIvosBOPFxHhHTFA0TUNR1VGvw3th3b3c8YP1xA9sJ9N+HPvsxViX3ADPJIkDcaCesS2ZyZKgh0NkiOKilgqaMWId032OBmPd5KmQ5xSbsVOBizqsuEetRldD5QzbcFLdb194gk0EOUkNc7FSaESq6J3AWuqCHAoi8MIJiILi4QuGuX7Z/GKHIQD8ocigYUOljtE49FRTKPRXBUNRAuEoew6dIBiJIcsKGhouh42K8kIpjNfjxl3mGNdJppqmcfT0aULRKHarlVnTp2M2CREuGH+EKB9DwtE4njGoz7z5698nunMjxvJKvLc8jM5s6X0kedHnaIxuA1eGKClCNLCYCB0c4RWaWIGT6ss/uYgY7SrZMWzy1PW+pcK0E6EDhTwuanBRi5Oq/sevBj9H0WOihnn9zZmy8n70utGZFlsMRmOwlmD0yOVFKVGpEI0lKXNNnsmqNosZW10VjXUDE0Z97jCBcJRAMMLxM51EYolz9etOR6EcprxQEjPaw5KCkQh//ZWv0B0I0FBdTTSR4HRHBzOamrj/5pu5d81NQqALxg0hyseQs52+QSegkXC6o4P3feX/ke1px7X4eqZtcUF7Gkhf8nkyOY7xOuU0UcXsEYtzlUJ2QyaDnUocVOGmkVNsZiZrsFC6tXcGm0ZiDJs8JSTqWcwxNlBJKy5qSODDz1HOsA0HlbioxUXNsO4sFDxTjtDKzQPcUiZ66UenL8hNzVPTmrPUKIigqemuUYpoaFPCS/x8d5gZjbUDHlNVlWg82d9wevD46X47R71OR3mZk4ryMrzlLrxX2XD63IYNVLjdfP///B/0vefTTDbLnsOH+dFvf8sLb2zigbV3XPT5B44do8vv57qlS7GaRamoYGQIUT6GnOnyjehWsKZpfPcXv6C9u5tOn4/dx05gbW7De8vD1D6buqJtZIhxlp3YqSBCO6nFbmzNgweD9Dmw5EjRw8F+4Q0qWu8/0FCQyRDBggsvM/uf78CLmwaidBB9aNqAbZYSkm7smzwtuJjFzXSyhx4OYcKGjXLKqMOAmRhddLEXEw5c1AASMlkUssjkUMhjw00507FTuA3cxT6qmIUZ+4QoS7lSYokkLqf98isKxpxQOEZFeeleUE8lcnl5wtRbjyW6XuFdXuak9YKLd0VRCcfiBENRunwh9vY2nALo9YXn9WXXK9wuHHbrkIK9pamJnzz9NP5QiJrKwuRti9nMyoULWbFgAd9+8lf89Pfrsdl13LF69aDnv7x5M7996SVkReGRu+/msYcfxm4t/VJOQWki3vVjSDiaGJG92J2PP4Pvuaewty7E6G6i8o6VSAbDFYldhTw9HCTEaappw0sL7Tfkie7aiHV626CTU89D5VQ/FaadXZiw46KSQt5X6s2sS0jo0KHHihs9A29xa2hEHEHKltxAqd7okwwayXoLHB4d/99LYcLOdK5FRSVLjCgdBDjGHO6inKbeAT4BEvgACTN2DHgwYEaHgSQBTrKJGazGgosY3TSyYlIJ8j4f5olaejPZ6BbOKyVDIBzFWy6G1VwKvV5XEN3lZcy+4DFZUQhH4gTCUc52+dh94BiJZLp/YJLH7aTCXYa7zMHOAwcpczh4a/du3nXbbQO2I0kSc1taWTB7Jl/9wffYtncvf/XYY1jOy4jXV1ezavFi/nLdOv7jpz/lwU9+kk9+4APcv3btOPwWBJMNIcrHCEVR0eukEQkOSZIwV9ahyTKmqvr+bfUJ6KHQ0Ahzhi724aSa2dzGz9b/KesefAJjRTWoCnIsjLGskIGVk3GSh3cj6fVkVtaQ3BpgGisHie7Lcfa6FOyVCvu4gDwZ2tmFEQsNLBnmb+HiDLdO3mhXMexXyF3Fn/3V1uTr0JElSYATVNLav7zP4vC36z87YP2+YU92KjBh5wzbaOZajFj56foPD3v/pUw4lqDcJTyxS4WeQJi5M6cVOwwBEAgW1w5xomPQ66mscA/5O5RlhVC0INh3HTjMrn3HaZs2j0Agzf/87pXekhhXb1lMGYFQlHtvuZafff3r/PN3vsN7Pv1pls6di9VsZueBA3T6fPzRPfdQ7fXyz5/+NHuPHOGrP/gBP/zNb1gyZ/BdaYHgUghRPkZ0+YPUVI68gc0xbwXhTS+gtzuxTZvVv3woYZ4iQge70VCYzirsVPRnVh9f/yh3Pv4MmiKjpBNIBiOZ9uMkj+3FPmMe6PWkTh7CPn8pgdbh1cFrikzslT/gXHBN/4WDKucJc4YwZ0gSwoKDGJ3UsgD9KP3ZnWAjGhr1LO53HrkURrtKLjb8GuwonZxhO5XMxMM00kRxUYPEldXfKuSRkAbFOFTW+/wprGXU085OsiSGfZE0EejqEU2epYQ/GKHymkXFDkNAwaN8buv0YocxKTEY9FRVuKmqcLPn8D6mNXj4h09+DOjNsEfjBMMxOnsC7D10gqOn2vn18xvQ63TctPwGVsxfRjwZQ1Fl/vbjH2dea+uA3p4Fs2bx+L/+K/uPHeOpP/yhWC9TMEERonyMGK0mT52p4Kyitw3uwr9QmJ/iLcqZRg1zhxyd/sK6e7l+31YS+7ej5jKYvDVU3PQABntvHemsq/tAznScRG93YaktZNnUfI7gq09hw4aTaqy4CXGKSlrRMXqNiWmiOKjiBBt7L0K8l1zfaNdIdg0v2x3kFN3sZxor8HMMH4cw4yLAMWqYh43yy4rzchqJcJZ2djGHmsuOte8T5hISNjwkCQ0r5olCly/I3FaRmS0VZEURdcwlQiAkylfGgz1HjrBi/rm+L4NeT6XHPcAfPp5I8cGHbivUsEfjBCMxguEowXCMfYfOsvfgWSRJosxp78+wV7hdzGlpwWI285uXXirCKxNMVMQZeIxo7/KzaO7My694GVInD2Is92KurAMg29NO+vQRbDPnY/JU0fNQOd6n/KQIoqLg4xA1zOHxi0xx3PTVf7rk/i6cGHolZH2dmGsKfrpyPEpk6yuYvLUYzmTo4SBl1DODG64omz0cGllGO7toZDkn2Uwt83HTCGj47nGhqSpoGuUv+OmcG2G2ycbxuWlsM+aiMwydeT7/IidLgi720spNmHHym9/+FeFYjDKnk/sf/iJn2UGeFBZcWHFTQcuQr7GdnejQM4tbLivI++gT5nYqiNJ1xVn5iYQvGB7VwVqCq0dWlHH1hRZcmrwsYzKKj+exJJZIsOvAAR57+OGLrpPL5TEaC4kkvV7XP6mUC4Ym9U05DYVjBCMxjp1qJxJL4AsGxvIlCCYh4l0/RqSzOWyWkdsjJfZvQ293ISfjxPduQY6FUZIx9DYH2c5T5ALd9OhD2JQyKpiBAy8/Wb/uqvd34cTQK8FUUU2m4wRqOknq9GFszXPIdJ7CTgVt3IlhjFo/U4Sx4ib90BzckSp63nmLjugekCR4SYekk0DSYaktQ5etQLW7kYMdBF99Cs+N96K32AZts+/ug4ZGB7t7HU+c/UK6wu0G4Ln1/8S6B59AIU+aKEn8nGQTs7ltQKlJlgRxepjDnegwDLtR08N0/BzDzuQr81BUFYNhYls6ThYCoWhJTo+ciqja6M6UEAzmtbff5kvf/S63rFrFjIaLW7KGonEq3JdPJp0/5XQm5ybiHjtzhh//7uejErNgaiBE+RiQyY7OSF5NVQBQUgmCr6/HPnM+rsXXE3j51+TDfozeGhzzlmPyVCHpC4fyt+vuHfF+hyvMrU0zSRzZjd5qx3vzu4ju2IClrpn6wzNGFEeQE2RJ4GH6AO9zDY0eDhLmNO67HgLA6K6gYs19Q74WgKMn2/nHFzbhbphO4tAuwm+9iOeGe9AZBx+nnofKMTy1gzwZKmm9qJDuy2Y78OLAS5ooIU7hoBITdvQYSRHCjveqBDmAESvTWUWezLCfW8pksjkxkKOE6PGHqBaTVUuCWDxJmbAJHXVkReHY6dP86Le/5eCJE/zrZz/LsnnzLvmcQCgqbEIF44oQ5WPA2S4fjbWVI96OpNNTdc8HyUeCGBwu9LaCU0XVPY8O6erywigI8vO3daXCXNIbqLz9ESRJInXqMGoui9FTyTv8hmau7/XiPoeGRpIAWeL9I+GHopuDlFHHcd7AjhcbHmSyROnAhA33nQ8Ome0+/zX00dET4MsPrOWjf9iKffZi1FyG0BvPULH2QSSdDk1TUdMp5GQMJR4hYTpIa+7Gy951OL8xs5o5HON19BhRyOOkCj2mKy5ZuRgORv63VGp0+0NDjuIWFIeeQHhUyu0EI8cvnFeuGkVR2HngAGe7u9E0DU3T6OjpYc/hwxw8fpwar5e1q1bxj3/+51c06CcYidLcWDcOkQsEBYQoHwPOdvoGDTq4GkZTZI81fRcJWj6LHA0R2VxobkncNQ3X89nCY2j4OUKQk4CEQnZIUd59vxM1n0N5WUV/23V49HrSp49w6/RKrFYra1Z8lLktLcOym+zyBbl+2fz+iw3nglWFOw6RANmu0ySP7UNnMqO3O9HbnJStvJlf/NVHr2jb5wvunuAf4XW7SabTvPb227y0aRPT6+sv8ewr2+5ko8sXpLZKiPJSQfhilw6+UERcsF4Fe48c4fNf/zp2m422GTMK01AliSqPh4+8+93Mb23F5RhsmHApguEYyxe2jVHEAsFghCgfA7r9IW6cotZitpkL0DvdxHa+gWvpjegtNnoeslH+VAcZYoQ4xTRWYqWcfTxN1732ASUkajZD6PXfoaTiSEYTksmMJEls/Kf/PaK4ZEXB2Ns41SfMbc1txPdsRknGqbrzj9CZLf3rX+0FUXVFofbb5XDwwC238MAtt4wo7slKly/IgraRlTcJRg9FVdHrRaNnKRAIRVg4W7w3rhRN0/jVCy/wnZ//nL//xCe4edWqUdt2Mp0Zld4wgeBKEaJ8lNE0DVlRB/iWThVygS4i214DTaVs2U2YqxvIx8LE92ymxxiAvEwDS7H1jo7XjAaSx/ZiqZ+B0VWYJBh7ZxOmylqcCx4CTUOSpBHfMUilM4NuVb6w7l7u+KGCkkpgaWodFUEuuHKS6QwOmxhFXQrkxUj3kiKeSOOwi/fGhWSyWXL5PA6bDZ1Oh6ZpnOnq4vu//CWHT57kx1/+MtPqRrfURGJkAwAFguEizsSjTCSWwO0a3i2yUuRqrBFzQR9qJgVAfO8WYns01FwGx5xlbPrONzHo9eeGC6kqf/r3hzgQTxDe+CzW6bPR8jnysTDeZWsK642CIIdCPXl9zWAP8xcfewB4YMTbFwwPVVWFu0QJ4RM1zCWHEIID2XXgAJ/76ldJZ7OkMxnstkIvkd1qZc2KFfzkK1+5ohrx4ZCXZeEOJRh3hCgfZc52+WkahaFBxeRqBHmhJAQcsxehKQpyIgKSDoPNyYsfeXDQ+jqdjh/8y78AcOu3/4fUsb0gSVTceF+/k8xoZaw7ugM0N9aOyrYEIycQjvV6/QpKgZ5AiBqvqGEuBbLZHCbT5JveO1L+59lnef999/Hhd70LWVFIJJOoqoqn16J2LAhF4njcwnlFML6IIsJR5mynj4ZRcF4pFhcT5NVPhQcM1jmfPvHc913S6zGWVWB0lQ8pyC/k5T/7I1yLrsO16Dp0JvOAbY0GhabCyefzPVERx6O06AmEqfaWFzsMAeAPRakUF6yDmNPSQiBc+Pwx6PW4Xa4xFeRQaH4WdojF441t23j0c59jzaOP8tl//VdC0eiorl+qCFE+ygQjMSom2dX1+WL8QmF+oXg+/+fhCOurfd6VkJcVMR2vhBCivLQIRWJ43M5ihyEA/CFRSjQUdVVVdPT0jOs+g+EY3kn2WT5R2H3oEJ/9t39jUVsbX/jkJ+kJBvn4F76Aoiijsn4pI5TKKKKoKnrd5GkM6RfHwxwQerWieiwaLFOZLNZRGOQkGD2C4ShekYEqGVRNQ6cT+ZlSwBeMsET4xQ/guQ0b+PL3vsen1139pOqrIRiOsnRe67juU1Dgp7/7HasWL+avHnsMgAWzZnHnn/wJm3fvZvWyZSNev5QRZ+JRpMcfonqS1GZOFgeSzu4AdUM0eQqKhxCBpUM2m8MsaphLhmA4ikdcsA7g9a1b+V8f+AAP3377uO43kUpjt1kuv6JgVMnLMhu2buXWa6/tX1bp8bCorY2X33prxOuXOhMuU362q6vYIVyUvYdO4LRbOXbmTLFDuWrysTDffWDNhH4N57N93yHqq72T5vVMdNKZLIlUQhyPEqHbF0JR8+J4lAg9wQCnOjqKHUZJUenxsOfIEZbNnz+u+w2EQxw/e3ZE2yhlvXIhWRIlsb9QJEJelpl2wdC9aXV1dPr9I16/1JkwotzlcGC3WvnLL3+52KFMet79ym+KHYJgkvPdX/2k2CEIBCXJ47/7ebFDKEmeff31cd/naBwLu9U67Emi40mftjqV3jzu+x7qdxOIRAAou2B5mdPJniNHBm1juOuXOhNGlFd5PDz1rW8RS4zv1ZxAIBAIBALB1eByOKjylG5ZazG11VC/m76OPE3TBizXNA3dEP16w12/1JkwohwKfzyl/MctEAgEAoFAMJEoJW1VUV6wZ41ecJEQjcfxlg+2bh3u+qWO6LYSCAQCgUAgEBSdCrcbs8nEqfb2ActPdnRQWzl4Bsxw1y91hCgXCAQCgUAgEBQdg17P2muu4Q/nOaf0BALsO3KE266/HoBkOo2qqle8/kRCiHKBQCAQCAQCQUnwgfvuY/u+ffzbf/83r27Zwl/+678yu7mZaxYuJBiJcMuHPsRff+UrV7T+REOIcoFAIBAIBAJBSbBg1iy+8Td/w74jR/jit75FXWUl3/rCF9DpdJiMRio9HmrOK0251PoTDUm7sGVVIBAIBJMWTdMmzdThiY44FqVBnwwSx0JQbCbeZUSROdvVxZ7Dh8nn8wCoqoqiKEWOamrzb9//Ppt37yadyfQv0zRtkEWSYHzo8vv50W9/S/cFgxtUVRXHpAhs37ePzbt3I/eep/qER19NpmB82fLOOwTCYWCgCBTHY3xRFIVjp08DhePQdyzEZ4egmEwoS8RSYOeBA7ywcSM3rVzJTddcQ3VFRbFDmtJkczm6/H7+88knaaiu5tolS1i9dOmEtEKaLATCYX71wgu89vbbzJs5kxuWL2fFggUYDeJ0Uwzefucd/ufZZ1kwaxYrFy7kuiVLmN3cPCFv7U4GvvL975NMp1k2fz7XL1nCioULqfJ4xPEYZ9q7u3nPpz/NnJYWrlm4kGsXL2bh7NlYzOZihyaYwojylWHS3t3Nmzt38uaOHew7coTZM2Zw9403smLBAuqqqood3pTlVEcHm3buZNvevcQSCea3tnL76tXMnj4do9FY7PCmJNv27mXTzp0cPnkSSZK4dskSbly+nMaaGiFAxplQJMKmXbvYvm8f3YEAnrIyblq5kmXz5okL2CJw4NgxNu/ezcETJ0hnMsxoaODGFSuY3dxc0tMfJxuZbJZNO3ey88ABOnp6MBgMLJw1i2sWLaKprg6rEOiCcUaI8hHQ0dPDhm3bONvVhdPhYF5LC2tWrix2WFOG8+sx+/6fz+fZe+QIv3npJU53dtLc0MB777qLBbNmFTnaqcFQNbKRWIw3d+zg+Y0bSaXTzGlpYd2DD1Lt9RYpyqlLXpbp6OnhpTffZNOuXVjNZpbPn8+6Bx8UF69FIJZIcPjkSZ7bsIEjp0/jdbu59brruG/t2mKHNqXI5fP4gkG279/PK5s3E4nFqK+u5r133snSefOKHZ5gCiHuJw+DZDrNgWPHKHe5cLtcpNJpKj0e4skknT4fr23Zwjd+/GOe/va3ix3qlECSJB5fv550JkOF282Zzk5OdXZS7nIxc9o09Ho9v3/tNVqamoQoHyckSeKJ3/0Op91OLpfjxNmz9ASDNNbUsGzePHYdPMj/PPss77rtNiHKx4FYIsGbO3ZgtVjo8vs51dFBKpNhWl0dqxYtYsO2bfz3r37Fn7znPcUOdUrQ5ffT5fORzmY50d5OR3c3kk5HS1MTTrud3736KulMRojycaAnECCTzdLh83H87Fn8wSAOm43rlyzh0IkTPP3qq7TNmCFEuWBcEZnyYfDyW2/x99/8JgDe8nIWzZ6N2+UiFI1y8uxZDAYDbTNm8Lcf/3iRI506fPpLX+KtXbu4ZtEibr/+emq8Xtq7uwnHYnjLy2msraWlsVHcEh4nYokED//5n5POZrl7zRpWLFiAyWDgTFcXiqpSX11NY00NbTNmFDvUKcH2ffv407//exqqq7n/lluY0dBAMp2m0+fDbrMxva6OptpaptXXFzvUKcF//fznfPcXv2DZvHnceu21lJeV4QuFiMbjVHk8tDQ10VRbS2WJjDyfzPzJ3/0dO/bv556bbmJxWxs6nY5Onw9VVWmqraV1+nSm19djt1qLHapgCiFE+TA4fPIkv3npJeLJJNUVFbROn86qRYuocLuBwq1hWZaxWizFDXQKcbari7d27WL9yy+Tl2XuWL2aB269lSrxoVYU8rLM/mPHePmtt3hl82aqvV4euvVW7rzhBswmU7HDm3LEEgk2797Ncxs2sP/YMRa3tfGeO+/kmkWLih3alOR0ZyevbtnC82+8QTyZ5OZVq3jX7bfT0thY7NCmHG+/8w4vb97M61u34ikr4/6bb+buNWsod7mKHZpgCiNE+VXQ0dPDS5s2sffIEWwWC7dedx1L584V2dgis/fIEd7csYN4Msms3gum8wcMCMafV7ds4Z1Dh5AkiQWzZrF03jzxoTdOXFjf7wuFeGPbNk62t+NyOFgyZw7zWltFJrBI7D1yhK179hCMRKitqmLp3Lm0NDYK949xJhqPs33fPvYfO4Ysy8xobGTJnDnUVVWJPgvBuCNE+TBIZzLEkkmcNhs2q5VgJMLTr7zC9n37qKuq4o7Vq1k+f74YQDBO7Dt6lEMnTlBZXk59TQ2SJHH4xAne2r2bt3buJJXJ8NkPf5j33HlnsUOdMuw6eJBILEaN14u3vJxoIsHugwd5c8cOtu/bh9Fg4F8/+1mRqR0n9h45giRJ1FZWYjWbOdPVxdt79vDGtm3sO3qUaq+Xb//DP9BQU1PsUKcEx86cwWmzUe31ks/n2Xf0KG/t2sWGbds40d7Owlmz+M4//qO4qzTG5GWZaDyO2+XCoNeTy+fZtncvG7dvZ9POnXQFAtx5ww3881/8RbFDFUwxRKPnFbLrwAG+/L3vMbelhXQ2SyAcRq/T0dbSwrT6ejZs3corW7bw2uOPFzvUKcPm3bs5ePw4nT4fpzs78brdzGttpbayktuuv54XN24kmU4XO8wpxXMbNtDl93Ps9GmCkQjNDQ3MaWlhRmMjZU4nL23aJOwQxwlZUfjJ+vWEYzEOnTiBrCjMbWnpb3wuLytj865d2G22Yoc6JfCFQvz7448TjsU4fuYMVouF+a2tNNbUsGrRIsrLymjv7haCfBw4cuoU//HEEwQjEbr8fjxuN3NbWqjyeFi9fDk79+/HHwwWO0zBFERkyq+QUDTKsxs2YNDpMBgMuByOftcVSZJwO53UVVVxy7XXFjvUKcOvX3wRg8HAHddfj9ViIZZI4AsGkRWFCrebSo9HjLEeZ37w61/T3NDAyoULsVksdAcCRGIxdDod1V6vKF0ZR7K5HN/9xS9YsWABs6ZPR6/T0R0IkM5msVks1FdX4xCCfNzo9Pn4xXPPccPy5VRXVKCqKsFIBEVVcTudTKuvxyTKJcaFnfv3s3HHDlYtWoTdZiMvyySSSYxGI5UeDzMaGsTnhqAoiEz5FbDv6FE27dxJucvFLdde29/YKSgOiqLw+W98g2Xz5pFMpznT1dU/dOP8un4hyMePdDbLfzzxBE21tfiCQbK5HA6bjbqqKjFUqwiEYzHWv/wynrIyguEwrvnzMRoMuMVFUVHoCQR4+5138LjdZHM5GmtrAYTrTRHo6OnBFwrhcjgoczqHdIISuUpBsRD3ka+Af/yP/2DezJmYjEb+5b/+i0QqBYCqqiiKIt7A40wwGqXD5+ORu+8G4Os//CFQEOvnIwT5+HHi7FlOd3byvnvu4diZM/zXz38OIN4fRWL7vn0cP3uW+9au5ZUtW/jl888D4ngUi9+/9hpnurq4cflyHn/qKd7csQMQx6MYfO+Xv6TL72d+ayvf+NGPOHbmDDDwWIjPDkGxEJnyy6CqKtPr6+n0+XDa7ew/erT/lq+ojS0ODquVJXPm8M0nnkBVVW5YvhwoHCtJksRxKQIVZWXUV1fzzGuvodfraZ02DQCNwnEB0Ov1RYxwauF1u2mur6fL70dWFKoqKoCC2BCCY/ypcLuxW60Y9HoS6XT/Hb2+94ZOpxPHZZywmM3M6vUgb+/pwdHrPqRqGqiqOBaCoiJqyq+AnkCA17duJZfP93uT52UZvU4nBGCRiMbjvPb22yTTaa5dvJgZwue3qGiaxtHTp/nBr3/NorY2HrjlFmG1V2Tu+8QnsJrN/N0nPsG8mTPFRVERSWcy/L+f/ITuQIAP3Hcfy+bNE58dRaLb7+eL3/oWdpuNh2+/nWsXLy52SAJBPyJTfgVUe708cvfdxJPJ/ttbRoP41RWTM11dnDh7Fk3T+NxXvwrAzGnTuG7JEu6/+eYiRzf1kCSJA8eOIUkSew4fxmm3c9/atbywcSO7Dh7kmoULuWnlSiFExom8LNPe3c2HHnoIu83WL8gVRenPlots4DgiSdRWVfHoAw9QX13N2a4ufvjb3xKLx5nX2spNK1eKxMI40tLUxF899hhQcMX52e9/TyKVYn5rK6uXLcNbXl7kCAVTFaEsr4BTHR08/tRTZHI5ZFnub9RZNm8eq5ctEx3z40woEuHL3/0uj9x9NysXLsRqtVJXWUkun2fLO+/QEwjwoXe9S1w4jSNnurr45hNP8JkPfYjmxkZe3LiRT/3zP2MyGqmtrOS/f/UrKj0eFsyaVexQpwSHT56kuqKCxW1t/M3Xvsa6Bx/k3rVrRba8SOw6cICnX3mFdQ8+yNFTp/iX736X2c3NzGpu5p1DhzjZ3s5nPvxh4U40Dmzft4+te/YAhffJ//vJT4gmEjTV1vLUyy9z+ORJPvvYYxjEe0VQBETa6gr4h29+E5vVyqK2Nm5csYLrly4F4MU33+QHv/416UymyBFOLfYeOYKqaTxwyy3UVlZy7eLFvL51K++96y7uvOEGXt+2jV0HDhQ7zCnF4ZMnqaqo4N61a5k3cyZrVq4km8/zuT/9Uz772GOsWbmSH/7mN8UOc8pw4NgxZjc3s2blSv7505/muTfe4L6Pf5yv//CHbNy+nVMdHWSy2WKHOWUI9w7UgoKbV5nDwec/+lE+9sgjfO1zn8NiNvPfv/pVkaOcGpxob+/vedm4fTt6vZ5v/f3f8+XPfIbPf/SjHDl1ivUvv1zkKAVTFZFKvAzHTp8mFInw1x/5SP+yPn/ZvUeO9GcA333HHUWMcmpR6fFgMhp58ve/Z+Hs2ax/+WUcdjsANy5fTrffzy+ff56VCxcWOdKpw6xp0yhzOPjGj37Egtmz+fWLL7J07lyqPB4AbFYreVkucpRTh+379tHUa7s3u7mZb/7d3/HWrl1s3r2bZzdsIJlOc+9NN3HH6tVFjnRqsHzePN7auZOfP/ssc1pa6A4ESKXT2KxWjEYjkiSJ98c40RMIkEynSabTpDIZblq5ErfLRV6WaZsxg5amJjp9vmKHKZiiCFF+GdwuFzMaG/naD3/Iu++4gxqvF4vZTKXHw82rVuGw2fj3xx8XonwcmTtzJo/cfTebdu7k1S1bcNrt/Ml73gNATzDI1j17mNHUVOQopxbT6ut55O67+cXzz9MTDPLHDzzA8xs38qPf/haATTt3cveaNUWOcuowvb6ea5csAQp15Aa9nhuXL2duSwsn29vZd/So8I8fR6q9Xh6+/Xb+9fvfJ/373xOOxdh54ACzpk+no6cHgA+9611FjnJqcN3SpTz/xht8+POf5+jp03zwvvv6L5CCkQgdPT08fPvtxQ5TMEUR7itXwPZ9+3jy97+nzOGgqa6O6ooKDAYD/lCI/ceO4SkrG5BJF4wP/lCITDZLQ01Nf9ParoMH2bRzJ/etXcu0uroiRzi1OXLqFM+/8QYn29tZvWwZ96xZg9ViKXZYU4JcPo9BrxeNtSXC+YPMjp46xY4DB/AFg4QiEWxWK3/8wAPUVFYWOcqpRyKVIpvL4XY60ev1/PA3vyGRSvHB++/HU1ZW7PAEUxAhyq+QwydPsnH7dg4cP05elrFZLERiMdZecw33rl0rxlULBEOQzmaRKHgDC0oDMSClNFB7PbEFpcOx06eZ0dgojougaAhRfgk0TSMajw8aTR2JxQhEIsxsaqLL76dWZDgEAoFAIBAIBCNAiPJLsOvAAR77279lTksLMxoaWDpvHova2pheV4deryeRSnHPxz7GhieeKHaoAoFAIBAIBIIJjGj0vATRRIIV8+ezsK2NTp+P7//yl/QEg1jNZtpmzMBkNPY7HAgEAoFAIBAIBFeLEOWXoKWxkQ8+8AA3Ll8+YPmugwc5euoU//fxx3n0/vuLFJ1AIBAIBAKBYLIgRPklaKytpaGmBlVV+5fpdDqWzJnDkjlz+PWLLzK7ubmIEQoEAoFAIBAIJgNClF8GSZIu6lLw0K23cs2iReMckUAgEAgEAoFgsiEaPQUCgUAgEAgEgiIjzDgFAoFAIBAIBIIiI0S5QCAQCAQCgUBQZIQoFwgEAoFAIBAIiowQ5QKBQCAQCAQCQZERolwgEAgEAoFAICgyQpQLBAKBQCAQCARFRohygUAgEAgEAoGgyAhRLhAIBAKBQCAQFJn/Hyyk0PcUI6UEAAAAAElFTkSuQmCC",
      "text/plain": [
       "<Figure size 864x672 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 864x672 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 864x672 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 864x672 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "for var in ds.data_vars:\n",
    "    plot_map(ds, var, climag_plot.colormap_configs(var))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1152x384 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1152x384 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1152x384 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1152x384 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "for var in ds.data_vars:\n",
    "    plot_ts(ds, var)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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k0YFFK1ZQUVVFzy5dyM3KijyGsHrDBi67/XYKiopIcDiodLn4z+uv061TJw7v2pX01FQy0tIoLi3FarFExpbY/iJ+2xNPUFBURJLTSUVVFW/87390Ouggzu7XDwgmWC69/XYKi4tJcDgwm0x8MX06v69ezQfPPYfFYqnz+5JeI4Gyvfq+Hz6/n8vuuIOCoiKsFguJTidrN25k9JtvkmC3N6ibbm52Nn179ODnhQuZ9ssv/P200yLfmblLlmCzWjmhd+861/X7/cycOxeH3U73zp05sls3vvzxR2bOm8dZJ50UWW7dpk1cfvfdlJaXYzKZSElK4peFC/m4RQuuvvDCBh2fU44+mk+nTmX2ggW1EjuzFywAiPzuA4EANzz8MHMWL8ZqsZCUmMjPCxdy5T338O7TTze4i295ZSUQ7G0CwXN08a23Uu3xYLfZsNtsrPjzT+5/7jnSUlIix6y4rIxBd9xBYXExZrMZn9/PI2PHRrXPaPaRkpREs4wMCkLdbMMJIUcdv/Wwj7/9lkdeeAHDMEhOTGTtpk2s2biRnxcuZPyTT2LbbiyJO558kmVr1kSuEd///DOpyck8uJtTanZu144lK1fy3U8/RRI73/30EyaTiS7t2zdKYmf72JMTEyO/36LSUr6dNQuD4ACpS1auZMSoUXz+0ku7rMQBvPTuu6wPDZb879deA3beFdrj9XLF3XezZsMGAFKTk3l+woQ6t3v9ww+zdOVKzGYzqUlJbNy6lTf+9z8CgQAjrrySww45hINatmT95s3MXbKEo0ONyK2Fhaxev55mGRn07NJldw+TyH4pfN02mUyRa/fultnha8P/jRnD59OmRX6r85Yu5cZHHuHFhx6iT48etfY/9p13+HTqVNJTUiLv/bF2LVfdey+VLhfJiYkUuFy8N2UKf27cyMuPPFJr/XlLl3LZHXdQ7XZjNpkoLi3l3tGj6dmly1/J/12Ur+HEzgvvvsu4994DICM1lSUrV3L300/j9/sjdZntzV6wgFseewyvz0dqcjLrt2xh3PvvU1BUxIM33cRJffpgtVj4fdUqisvKIjeFwnWyrp06kZudHXVZGTbq5ZcpKS8nOTGRSpeLGXPn8vuqVUweOzZSp4ymDMvOyCA1OZmyigocdjtZdTwyu339vl2rVg2Od+Jnn7Fy3TqcDgfVbjeLV6zgtief5NMXXsBkMlFSVsb1Dz1EcVkZNqsVv9/PlOnTyd+2rVayZP2WLVx0661UVVfjdDhYs2EDT7/xBl6fj6suuKDOc1TTR99+y5Tp00lOTKRrx46YzWaee/NN3go9hpuekkJpRQXfzJrFpvz8SDKuZU4ORSUlVHs8pCQlkZKURHZGxk73E02boKZovsMNUVBUxBV3382fGzdit9spKC7moeefZ8Hvv/Ph119HyvqpP/+M0+HgsREjasezZAnf//QTPr8fn8/HLwsXcueWLXRs04Yf586NrP/mxx/TtmVLzg/Vibc3Z/Firn/4YXw+Hw67neWrV3PXf/6zw3LRtAvP7d+fj775hu9/+ok7hw6N3JwN12tPjcGjcBKf9qvBkwefey7JiYkUl5UxYtQoLrr1ViZ/9x3ePeyWvm7zZraVlPDpiy8y7e23Ofukk5gybhztWrYEYMSVVzJl3Dhys7Lo2KYNwy66iDdGjWL2u+8yY8IEjujalUAgwHtffhnZ5n/eeCPYI6V1az554QWmjx/Pe6NH82iocVBUUsLTb7yByWTi6bvuYtrbb/PFyy+TmpzMW5MnU+lyRR3/5vx8xr3/PkCd4+s4bDY+HDOGGRMn8o8zzgDg+59/jrw/7r33WLtxIx0POoivX32VGRMncvPgwfgDAZ589VXKKiro0bkzU8aNwxm6aD1x++1MGTcu2DMBePr119lWUkLv7t354e23mTFxIheeeSZuj4eRL72Ez+8HYGpovzcNGsSPEyYw8513eOzWWzn35JNJcDg47dhjg/HVGItjdug5+P5HH13rcxWXlnJwu3Z8/+abTHv7bTqH7p6EP9ttV17JfddeCwQHaZsyblzkPNaUk5nJl+PG8eOECRx3xBE7HJ+n33iDwuJizjzhBKaPH8+MiRM54/jjWbtxI1/9+CO5oW1v/325rUZSYnv1fT+sFgvDhwzhyTvuYNa77/LjhAlcef75AEyaMmWn292Zc0N3oWoe1wW//46rupqjDjuM5MTEOtdbuHw5JeXl9OjcGbvNFukRMj3UiyfskRdeoLS8nF6HHsq3r7/OjxMm8Mbjj3P7P//Z4ONzdK9eJCYksHLdOrZu2xZ5/adwYic0lsz/vv2WOYsX06F1a7585RWmjx/P3ddcg6u6mjf/97+oj01JWRmTvvgiMt5CuHKenprKTYMHM/aBB5j17rvMmDgxUqGpeQ7GvfcehcXFtG3Zkikvv8zMd97hhQcfjBTwuxLNPgadey7P3XdfZJ3w93hnY2ltC11bDMPg7mHDmDFxIl+8/DJtmjdn+Zo1kUpgTVu2beP1xx5jxsSJDB8yBKj9G2ioJKeTTgcdxC8LF1JeWYnH62XmvHkc0r59ncnnPbF12zbGP/UUM995h1ND149Pvv+ei886i+njxzPxP//BZDKRV1DA0lWr6t3egzfdxG+TJ9f6b2fPt78XujuekZbGB88+y48TJjDh3/+mWR2V5msvvpj7r7+emRMn8sP48dwbujZ98NVX+EPXx3NDDbBa17/w9/7oo6PuqTegf39+mzx5r463JhJLXp+P5WvW8NSrrwLBuk/4mru7ZXZuVhazFyzg82nTyEpP53/PP88P48cz5r778Pn9vBKqZ9X02bRpPHTzzfwwfnwkEf74yy9T6XJx+XnnMX38eKaPH88RXbvyy6JFzF+6tNb6m7Zu5dRjjuGHt9/mm9dfJzsjg0BoLLuwXZWvEGxYvv7hhyQ4HLz5xBNMe/ttJj3zDGazmZcmTcLYrvcogNvj4bGXXsLr83Hn0KH8OGEC37/xBm1btuTTqVPZtHUraSkpHNm9O4Zh8PNvv0XW3b4sjrasDAsYBs/eey8zJk7ksxdfpFlmJttKSiKzK0Zbhj1x++1c/Y9/RM5/uGysafv6fZ8ePRoc76p167j32muZPmFCpEfWhrw8Vq5bBwR7dRSXldG5XTt+nDCB2ZMm8fLDD/PAjTfW2o7P5+Poww5j6ptvMmPiRIaGYn978mSqo5gA5vNp07j24ouZPn585PGpS84+m6H/+AffvP46P4wfzwfPPYfJZGLpypUsXrECCNYZ+vbsCQTrE1PGjeOJ22/f6X6iaRPUFM13uCE8Xi9JTiffvP46373xBi1zcvD6fHw6dSpP3nEHMyZO5K5Qr5fvfvpph+/3xq1b+duJJzJ9/HjeffppTCYTm7ZuZeW6dXzw7LPMmDgxkkj5dvbsOmMwDIN/v/YaPp+P/kcfzY8TJjDr3Xcj9aOaomkX9jrkENo0b87WbdtqTZ6xs/bNrrw6ciQf//e/US8v+5f9KrHTpkULPnjuuUjDa8Wff/LQf//LkLvuYu3GjXu07XuGDduhG+jOXH/ppZHucpvy82ndvDlA5C6vz+/nm5kzAbj7mmtoG6o8dGnfPtI1cub8+ZRXVtK3R4/IoGUtmjXjuCOOoKKqilWhAmNnPps2jbOGDePkK67grGHD+H3VKtJTUmr1cAi7ecgQOh10EAAnhu5E5NdoMH81Y0bwc11yCc0yMzGbzfzz73+nZU4OxaWl9c624/X5aiVTkhMTsVmtjLjiCpwJCazZsIGVocdbmmVmArBy3Tqq3W6cCQmc3a9fpMES7gZb82I7K1SJqOvC9/DNN5OemordZovc4a752aJx97BhNG/WDLPZzAlHHllrGz6/n+9CjawRV1yBw27HYrFEeiEsWLasQfsKb7O+7wcEkzFnHH88Drudrdu2RRJSG7ZsafCA0P2PPprEhAR+WbQoUiiHj+spuyhQwgVzuMdVOLEza/78SEJ1S0EB80KV1UeGD4/cCTq8a9eokhvbc9jtHB86Dz+FKpMVVVUs+uMPMtLSIo+ihL+3V194YeR7NaB/f2xWa1Tn5bI77qDXwIH0u/xynnjlFQzD4OyTTqr1qOTgAQM47ogjsFosbM7Pj9x9Wl9j+uvwd//6Sy+leajb9bGHH05alI8xRbOPhpg5bx4VVVV0OuggLjnrLEwmEy1zchh64YUAfB367tV0xcCBkXMcvkaUVVTs9myDLrebk/r2xevzMXPePOYsXkxFVRX9jzmGqihmcGqIywcOjCQwwt+bFs2accvll2O32ejSvj3NQ7NabSksbNR9h8/9kAEDIt3yux98cKRMqOnE3r35xxlnkOh0UlRSEnluvqq6OjLo4VknnYTJZGLqzz9HfuPR/E5FDhQ/zp1Lr4ED6fOPf3DJbbex6I8/SE5M5O5rrgH2vMwOlyuXnn12pNfniX36kJOVxW/Ll+/QiDzt2GMZeMopkX9vzs9n4fLlJCYkcFPoMY8EhyPSa2b7/Sc4HDxw440kOp2kJifTK1S+hesg0ZSv386ahc/v56wTT4ys36V9e3p07syGLVvqHFR18YoVbNq6lTYtWkRu0KWlpHDqscfiDwQivSrD153wdajm3zV7zTekHDv28MPp17cvJpOJ1s2bc37o3Mz//Xdg98qwXamrft+QeI85/HD+ccYZWC0WenbpQnro0Z/wOQrXPwqKiiJlzFGHHRbpdV7TTYMHk56aitls5uoLL8Rht1NSXs7qUK/PXel+8MFce/HFtRL8LZo14+bBg8nJzKTK5aLK5YrEs7t1iIa2Cer7Du+Of119NVnp6SQ5nZG6yenHH88Zxx+PyWTixD59gGCCsjg0VlbNeO677jocdjsHt2sXKf+vveQSDm7XDpPJxPGhes7O6gQbtmxhxZ9/YjabI0NXWCyWyM3n7dXXLoQd2zfllZUsXrGC3KysXT4eLlLTfvUoFgQvYq88+ihzFi+OzGKzfM0ahvzrX3z20ku1xg9piO4HHxz1sqvWr+ftyZP5ZtasWln28Kjz6zdvxuP1YjKZ6LWT5yVXr18PwM8LF+4whTEELzaH7fDqXypdLipdLuw2G+1ataJvz54MveACcuuYltdcoxAIz/YTjttVXR25sB3aseNf65jNHNKhA5vz81m9fv0uR8xfn5eHz+fDbDbTucbYJolOJ21btmT5mjWsXr8++IzuxRezfM0avp45k9kLFnDp2Wdz+cCBkR4jR3TtSsucHH5ftYrN+fkkOBwsW72azu3a1VlI7uqzRWtX21i3eTO+0ECvZ9R4LjZsdxqK0Xw/IPiIzzuffcbH331Xq2Lm8/koq6jY5aNe23MmJHDKMcfw2bRp/PDrrwzo35/Z8+djMZs5aRezKYXH1+kTSui0bdmSnKws8rdtY+7SpRzTqxerQt/lZpmZdZ6j3XHKMcfwzaxZ/LRgAQNPOYVfFy3C5/fTr0+fyNhH4YrQvaNHc+/o0bXWj+a8NMvIwGazsaWwkEAgwG1XXlnrWXeAvIIC3v7kEz6fNi3S5R/++q1XuVyRysvuFsz17aOhwo8FHVLj9wzQNfTvPzdtwuf31xrDpa7fAIDb7Y700msIj9fLGccfz2sffshPv/0WSXKdfuyxvPbRRw3e3q7UjD3J6QTYoWdLYuj1hl4b6vNn6IZCNOfeVV3NpClT+Ojrr9m4dWut97aVlJCbnU2r3FyO6NqVeUuXMv/33zn80EP5ZeHCyJ1zkQNdeFasSpeL0vJy2rZsybhHHonUffa0zA6XK/+dOJH/Tpy4w/tFpaW1HvnZvu4YrttVVVfTN5SI2NX+zdtdq7avg0RTvob3+b9vv+V/335b5z7Djf3t19mQl7fTOigEkzejxo3jpwULMAyDkvJylq1eTevc3Frjju1JORb+XHmhx+x3pwzblbrq9w2Jt65zVFJeHjlH3Q8+mGsuvJA3/vc//n7zzZzYuzc3XHZZvWP9OR0OmmVksHHrVvLy8+stR3bWTgmPrbR4xYpaicfdqUPsTpugvu/w7qirXK/5WrhMr2s/28eTWMf6SfXUCcJle7OMDHK2++3Upb52IcDZJ53ES5Mm8f1PP3HblVfyy8KF+Px++h9zjAZvl6jtd4mdsD49etCnRw/mLlnCTY8+SkVVFdNrDNQJsGPn0z33x9q1DL3vvuDd56OP5qQ+fdiwZQuvfvBBZJnwnVaTybTTH2s4tvC05dur67Waag4M3RDbx1NXF91o3tvdbWSmp/P2k0/y9cyZvPbhh4x7/30++OorXn3sMTq2aYPJZOKcfv0Y9/77/DhnDhlpaRiGEdVUjI1xYdzZ8TGZTJFB8Gqq67X6RPP9qKiqYtj//R8r162ja6dOXHXBBWSmpXH30083eH9h5558Mp9Nm8aPc+Zw3BFHsGr9evr06LHTEffXbtwYudtwzf/93w7vT//1V47p1avW52ksxx95JHabjZ8XLsQwjMjjKLWm9A6dm3CCpqadPVpWU3hWrLuffpqvZszg99Wra32GLQUFXHn33Wzdto2+PXpw+vHH4/F6I13/gcgjhrDj2E3RiGYfDbWzX2O0v+fGOo+d27WjfevW/LRgAempqXRp3562UY57FH40qaGx7GzpvVVl8oe++/Wde5/fz62PP84vixbRrlUrbrn8crp27Mi1Dz64w7Lnnnwy85Yu5cc5c3DY7ZRXVnLeKadomnIR/poVa/WGDVx4yy1s3LKFCpeLcH+MPS2zw+tnpKXVmdSuL9EdvspardY6G4T1NRK3v+ZFU76G95manFxn2VfXa+F1womy7YXrBc0yM+nZpQsLly9nxZ9/snbjRgKBQK3eOntajoVnfAw3wPe0DKvPnsZb17m4cdAgzu7Xj5cmTeK72bP5ce5chg8Zwj///vddbmv7z95Q4bGV0lNSuPy88zi8a1fGvfcev69evVvba4w2QWMnKeraWkP2sDvrh+t20dTromkXArRu3pzDDz2U+b//zqp16/glNLC7xteRhtivEjtVLhc2my0yQB4EHw3p1qkT85YujYxLEx5UtOY4NQ0Zs2ZXPvz6ayqqqhg8YAB3XHUVQGTmpbC2LVtiMZvxBwL8tmxZ5NnWmjqEZoo6pEMHXnvssUaJbXckOp00z84mr6CAZatXR7qrBgIB/gjNsNUx9BgXEOktUXO63bYtW2K1WvH5fKxYuzYymF+Vy8X6vLwdtgFwRqhL5QvvvMO499/nrY8/joxjcXYosTNz/vxIJWx3H0OoK96GaNuiBVaLBZ/fz7hHHqnzEYuG7iua78es+fMjSZ3xTz6JJdRdeE/07t6d5tnZ/LxwIT8vXAhE9xhWekpKrZ5gVS4XG7ZsYfqcOdw9bBjtW7cGgt2QN+Tl0WYndxUbci6SnE6OPuwwfpw7lz/WruXXxYtJcDhqzUrSoU2b4KCWgwfX6grfUMMuuohvZs3i65kzufy88yLf3y9nzGDrtm30P/ponrn7boDIDBxhqcnJkQGHV61f3+CBAqPZB1BrhjaP14t9u0RWTeFZ6JZvV7FbtmYNAO1atdpnSYLTjzuOl997j4LiYm4ePHiny1VUVdVqfOQXFQFEBjxvqlrm5PDH2rWRGTp2Ztnq1fyyaBE5WVm8+8wzu2wcnnrssTwxbhwz588nI9S40mNYIrV1bNOG0487jq9mzGDM229HxiFrSJldlw5t2vD7qlVceOaZ3HDppbsVFwTHyftozJhaPSB3RzTla7g+eWKfPoy85ZYGxZmZns4XL7+8y8b4KUcfzcLly5mzeHGkN03NxE605djO/B4a+yz8WHpDyrDdqePtabw7065VK564/XbWXHQRF48YwYvvvsvgc8/d4cZT2NbCwkiPjvBnbwi/38/4Tz4BYNyjj0bGmZzw6ac7LBvtcWpom2B/Ff7c+UVFdc4CW1M07cKwc04+mfm//87M+fOZt2QJGWlpkUfXRKKx34yxEwgEuOvppxl0xx2R6bS9Ph+zFyyIZKbDM4aE74j8umgRhcXFbMjLq3Mk891REGpwuKqrMQyD/KIiPps2rdYyNpst8vznE6+8wsYtW4Bg99LwmCHHHX44SU4n85Yu5ZUPPsAb6jq8aevWWtMt7wunH3ccAC9OmkRhcTGBQIDXP/qIzfn5ZKSm1poFIvx8dzgxAMFZhMKD6D3z5ptUVFXh9fkY/dZbuKqrad+6daTL7isffMDXM2fi9fnw+/2RrLirxrgbbVu2pGeXLsxdvJifFiygTYsWO51quD7heAuLiyNdmhvCZrNFeon833PPsTXURdXt8UR6kWy/r18XLdrlGDjRfD/CDVu3x4M/EKDa7WbiZ5/tsK1w5aZm4tIaSnx6fL5aA4ubzWbOOumk4MxBH32EyWTa5cxy4QGSr7/0Ut4bPTry31tPPonZbCavoIA/1q6ldfPmHNqhA4Zh8NB//0tRaSkAi/74IzJ4X0OOT1j/0F2Mz0NTcB97+OG1xuwJP+v8/PjxkfEADMPgp99+a1Alr0OogWAYBqPfeivyeq1z4PdTVlHBB199tcP64WTTy++9R1lFBX6/n0lTptQ5rsH2ot1HzRksav726nLcEUeQnJjIqvXrmfTFFxiGweb8fF4L3T0K/973hdOPPz7y92k72e/Un3/mzKuv5v0vv6S8spLZCxZEBhjtul1X/KYmfO4nfPIJW0IzBn47ezbLtmuQhMsNj8eDz+fD6/Pxdh2DWEPw7nq/o45izYYNfP7DDyQmJHB0r15782OIxKVhF12E2Wxm+pw5kXFoGlJm1+X0ULky/pNP+HHu3Mjri/74I1K27UrLnBy6HXww1W439z/7LCWh8T8qqqrqHa+wLtGUr6ccfTQWs5kvp09n8vffR3pWrFq/PlK/2F73zp1p0awZm/PzGTVuXKQOVlRSssOsheEe03OXLOHX0DTdh9VojEZbjoUtX7MmkiCat3QpU6ZPB/4q0xtShoXLxj/Wrt1hrJWdaWi89VmyciXPvPFG5Nz4/X4Mw8Dn9+MJ1e3DwuMhuT0e/v3aaxiGQddOnXZr9qhKlyty3sJ1wJnz5tXZhggfp3lLl9Y74UxD2gT7qw6tW5OTlYXP5+P5CRPw+/24qqsjE9XUFE27MOy0Y4/FYbfz2bRprNm4kZP79t2t3t5y4NpveuyUVVTgdrtZ8eefXPN//4fVasVmtUYuauedckpkAM3+xxzD2HfeIX/bNk4NzRrQuV07WjRrFpleenf17dmTH379lY+++YavZ86k0uUiu45urHdcdRULfv+dNRs2cM5115GWkkJpeTnZGRlMGTeOZpmZjLjySh576SXGTpzIqx98QGJCAsVlZXRp3573thszZG+67pJLmD5nDqvXr+f0oUNxhqYON5vN/Ovqq2tlqk/q04c/N23i7cmT+WrGDM7r358bBw3ijqFDmbd0KXOXLKHf5ZdjtViodrtx2O3cd9112KxWSsvLeffzzykqLcVqtZJgt1NRVQXA3048sVZM5558Mo/98Qcbt26ttyvrrhzasWNkTJhLbruN9JQUXhs5MupHQgDuHDqU+b//zoJlyzjzmmvITEujtLwcfyDAu08/zSEdOkSOzewFC/hm1izm//47R/fqtdO7Z/V9P/p0747ZbGb1+vWcOHgwfr8fh92OMyGhdhIs9DnyCgq4d/RoHh8xgjbNm2Mxm/H5fFzzwAO8GZrFAeCcfv14/aOPWLV+PT06d65zTCYIjiMQrtxtP/VnZloa3Q8+mEV//MH0X3+lS/v23HvddVzzf//HvKVLOfWf/yQ5MZGyigoO7dCBd595psHHB6Bfnz5YzGbeC81SsX0S6sIzz+TrmTNZsGwZl991F+kpKVS73VR7PNw5dGhkQMhoXHvxxXwzaxZzFi9m5rx5HH/kkRzVsyfvfv45s+bP54RBg3B7PKSnpu5wZ/OaCy9kxty5LF25kv5XXIHdZsPldpOanExpefku9xvtPrIzMuh28MEsXbmSWx57jJzMTB686aZaAz3XXHbElVcy8sUXeeKVV/jvxIlUulwYhkGX9u25IjS72r7QsU0bTurTB4vFstPxIdJC5+3xl1/m8Zdfjrx++KGH1uqh1RRdft55TP7uOzZu3cpZ115LYkICFVVVwe9iqIs9/DVjT0l5Of2vuCLSYy/8u9/euSefzFczZrB6/XrOOP74XfbQEjlQdWjThjOOP54vf/yR0W++yYTQ9M7Rltl1ObFPH8484QS+mjGD4SNHkpyYiGEYVLpcDDr3XO4cOnSXMZlMJu6/7jqG3ncf3//8Mz/8+ivpqakUl5Vht1r57KWXdhjvpr7t1Ve+hq/rr3/0EQ89/zxPvfIKFouF8spKTj7qKEbfc88O23U6HNxz7bXc9sQTvP/ll/zv229JTUqiuKyMrPR0Pn/ppciNlFa5uXRp3z44aYLPx3mnnFKrMRptORb256ZN/P3mm2td/47p1Styw6shZdjRhx1Ggt1OtcfD3665huTERD578cVdHtOGxlufj775ho+//Za3P/mk1mc6+aijImO5hI195x1e++gjDMPA7fFgs1q57cord2vfqcnJHNKhA8vXrOGqe+8lyemkoqqqzlkZT+rThw+//pqFy5dz+tChHNy2LeMefbTO7TakTbC/stlsDLvoIka++CIffPUVn//wA16fD0foqRFvjYRdtO1CgJSkJPr17RsZADyaYSZEatpveuykp6by8iOP8NBNN9Gvb1+y09MjI9Q/eOONPBSaZhKCjYmHbrqJ1rm5NMvIYOApp/DqyJGRGQ72xEV/+xuDBwwgIy2N1ORkLjvnHN4PTS9YU6vcXD4cM4ZzTj6Z1rm5BAIBjjrsMJ6+665IJf0fZ5zBuEce4aiePXE6HFgtFk7s3Xu3xs7ZE86EBN75z3+49OyzaZWbi9ls5qiePXlt5MgdEi7XXXIJ551yChlpaVjMZkyh7p25WVl8+NxznHPyyTTLyMCZkMCJvXsz8T//iTyikJaSwvvPPsv5p55Ky5ycyJ2KJ++4Y4cZr844/vhIb5Q9ufDZrFZG33MP3Q8+GLvVSrOMDIqivKsTlpudzYdjxnD+aafRpkULXNXVdG7fnjuHDo10GQa44IwzuPy888jJysIwjFqPDG6vvu/HIR068NBNN9EqNxenw0G/vn15b/RoDt6u51K3Tp24+KyzSE5MpDB01yArPZ0bLruMtJQUtm3Xa6RDmzYcGqrU7uq4zpg7l0AgQOd27eq8kxSeOSn8uFaPzp15b/RoTjn6aJplZGCxWOjXty+PjRixW8cHgr/5I7t1w+vzYakxY1mYxWJh3KOPcuNll3FIhw64vV5a5uQweMCAHb639WnfunVkutNn33qLQCBAv759GT5kCDlZWSQ5nZxz8sl88NxztQbOhODsI6899hi9u3cnweGgU9u2PHfvvfwttL1diXYfAE/cdht9e/QgMSGB5KSkXQ5MeMHpp/PCgw9yZGg2iXatWnHFwIG89cQT+zxJ8Nx990W6u9flyG7d+O8DD9CzSxcSHA7atGjBRX/7Gy/UMf5MU5OdkcGEf/87coe5VW4uD918M/+84IJayzXLzOQ///oXHdq0IcHhoHePHox/6imO2UlPnKMPOywyxoUqfiI7d+3FF2Mxm1myciXfzJoFRF9m78yo227jnmHD6H7wwQQCATLT0jj/1FOjvllwaMeOfPDcc5xx/PHkZGXh9njo2aUL919/fZ3X9vpEU74OHzKEp+68k8MPPRSz2UxyYiJnHH88N1522U63e2Lv3kx46ilO7N2bjJQUAoEAfbp354EbbthhRstTjj460pjtt92ECw0pxwDOPOEErrrgAhx2Oy2aNWPIgAGMCT1KFxZtGZaemsoz99zDwW3bYjGbaZmTE+mRszMNjbc+D9xwA3cOHcphhxyC1+uldW4uQwYM4NE6blw9deeddO3YEZvVyhFdu/LKyJG7fIy3Pk/efju9u3cnMSGBDm3a8OQdd3DtJZfssNwJvXtzy+WX0yo3l4Bh4HA4djpmTkPaBPuzf5xxBo8MH84hHTpgtVg4tlcvJv7nPzs8NhdtuzDsrNAxTE5MrHMoBpFdMRmNNdqYyD60Pi+PAddfT6vcXD5/6SWNGN9IfH4/5153HVsKC/n8pZd2mAJUJBpzlyzh6vvv55HhwxnQv3+sw9nvlFdWcvrQoZiA7954Y7cH1qzLWcOG0TInh1dHjmy0bYqI1OelSZN4adIkBvTvHxlT8UARnnlsyrhxu/XY1f7m6vvvZ3N+PlPGjYt1KPvc/779lkfGjm3034HqZQeG/abHjhw4yisrefr114FgxlxJncbh8/t5/cMPySso4NjDD1dSR6QJqna7eTY0PtnZ/fo1alJHREREYmPT1q28Ehqn58Izz4xxNBKP9psxduTA8OgLL/DF9OlUu920adGCS84+O9Yh7Rcmf/89o998k9LycmxWKyOuuCLWIcl+4KH//pdHxo7l7mHD+McZZ8Q6nLg37r33ePuTT6ioqiItJYVrL7640bZ9+tChFJWU4PP7dcdYRERianN+Pr0vuIDM9HS+ee21WIez1110662sWr+eQCDA3048MTIu7J6avWABw0eOjHo6eolvSuxIXFmzYQNWi4UTevfmnmHDdjktsERv/ebNeL1eunbqxIgrrtjtWcZEALodfDAfjhkT+XdOAwYDlZ1bu2kTgUCAI7t1465rrqk1G9qeGvfII5FZCHVdFRGRWHn45ptxhcYJtB4As0IVFBVRVFpKZloapxxzDLc24s3VXoccwqQaE+6oPrZ/0xg7IiIiIiIiIiJxSmPsiIiIiIiIiIjEqagexSqrqGDe0qU0z87Gto+nwhURERHZntfrZUthIUd260ZqcvIeb091HREREWlqoq3vRJXYmbd0KSNGjWq04EREREQaw+h77uHko47a4+2oriMiIiJNVX31nagSO7nZ2ZGNtWnRonEiExEREdlNG/LyGDFqVKSOsqdU1xEREZGmJtr6TlSJHXuoS3KbFi3odNBBex6diIiISCOwN9JjU6rriIiISFNVX31HgyeLiIiIiIiIiMQpJXZEREREREREROKUEjsiIiIiIiIiInFKiR0RERERERERkTilxI6IiIiIiIiISJxSYkdEREREREREJE4psSMiIiIiIiIiEqeU2BERERERERERiVNK7IiIiIiIiIiIxCkldkRERERERERE4pQSOyIiIiIiIiIicUqJHRERERERERGROKXEjoiIiIiIiIhInFJiR0REREREREQkTimxIyIiIiIiIiISp5TYERERERERERGJU0rsiIiIiIiIiIjEKSV2RERERERERETilBI7IiIiIiIiIiJxSokdEREREREREZE4pcSOiIiIiIiIiEicUmJHRERERERERCROKbEjIiIiIiIiIhKnlNgREREREREREYlTSuyIiIiIiIiIiMQpJXZEREREREREROKUEjsiIiIiIiIiInFKiR0RERERERERkTilxI6IiIiIiIiISJxSYkdEREREREREJE4psSMiIiIiIiIiEqeU2BERERERERERiVNK7IiIiIiIiIiIxCkldkRERERERERE4pQSOyIiIiIiIiIicUqJHRERERERERGROKXEjoiIiIiIiIhInFJiR0REREREREQkTimxIyIiIiIiIiISp5TYERERERERERGJU0rsiIiIiIiIiIjEKSV2RERERERERETilBI7IiIiIiIiIiJxSokdEREREREREZE4pcSOiIiIiIiIiEicUmJHRERERERERCROKbEjIiIiIiIiIhKnlNgREREREREREYlTSuyIiIiIiIiIiMQpa6wD2N/lFxVRVlER6zDiU3kVpCTGOgqJodTkZHIyM2MdhoiI7CNxV29SXaXBVLaLiDQ+JXb2ovyiIgbeeCNVLlesQ4k7mW4/L8wr4YYj0ylyWGIdjsRIotPJ5LFjVQEUETkAxFu9SXWV3aOyXUSk8SmxsxeVVVRQ5XLxwHX/omWz5rEOJ65Y/tyIbe59PHn1nfjbtY51OBIDmwu28MhLT1FWUaHKn4jIASDe6k2qqzScynYRkb1DiZ19oGWz5rRt2SbWYcSVQJWPaqBlTnPMOnYiIiIHjHipN6muIiIiTYUGTxYRERERERERiVNNKrFTXlkZ6xBEAFiychnDR93FkpXLYh2KiEhcUpleNx0XqY/qICLxR9d2ibUmk9jZWljIyVdcwdbCwliHIsL4z99j5fo1jP/8vViHIiISd1Sm103HRaKhOohIfAlf29dvycfl9lBS4aa0wkVJpZvSimpcbg9Vbi+uai8ut4dt5S6Kylx4vD4A/P4Abq8fvz8Q+XdFlZuSCndkme1tv0407+1qnYYss7Nlw//2eH24qr1Uub27FUND97snn2FP7ct91afJjLFTXlWFz+ejvKqK3FgHIwe0RSuWsmjFUgaffRETvnifRSuW0rNzt1iHJSISN1Sm103HReqjOohIfPF4/azeVIjP52PmonWkp1YRMAwCAcAUXMYMmM0mMAz8RvA1kwmsFjNJCVbSkh3YrRYC/gDVXj9lVV48Xj+YwGo2k5nqoFOrNJKddjxePwWlLiqqvBihXSQn2miW5gSo8720JDullZ4617HbLJHPsbPthpep+ZlrLhvwB/AbBgZQVe2jqtqHgYHNasFpt5CT4SQrNaHeGKI51ruKsSGfYU/ty31Fq8kkdkSaiolffEDPzt0YdM6FLFq5NPJvERERkb1JdRCR+OHx+lm3tZxKlxeAgN/AZjXj9vqxWsDARCBgYDKb8IYyOjYLOGxW7DYzVdU+yiq9+AIGhx6UwebCSvJLXFgtZjq0SMWZYCW/2EVRuZuFq7bRtV0GhaXVWC1mmmcl4rBZcHv9FJW5WbO5FEwmHDZLrffyi12s31pBdlrCDuus21pO29wUANZtLa9zu+FlaiaAai5rMsG6LeVUuX1Ue/xYzCYyUhxYLCb8AQOrxcTmwio25leSk+Gsd/v1HeudxdgiK5G8bVVRfYbGOu/7Yl8N0WQexRJpCsJ3ygadfSEAg86+MPKaiIiIyN6iOohIfCkoDSZhvKHHcFKT7CTYLeSkJ5KbkUiq00ay04rFbMJsAqvFRMvsZNq1SMVkMpGd7iQrPQG/z2BtXhlVbh8ZKQ7aNU/BmWClVXYyh3XM5qCcFPwBg+Xri7FazLTNTSEtyUGC3UpakoO2uSm4PH5cbt8O7zntVqwWMwkOyw7rWC1mCkpdkc9R13bDy2z/mcPLlld5SXbag0keTCQ6rBzWMZvu7bJIT3KQkZSAw2bBHzB2GUO0x3pnMa7NK4v6MzTWed8X+2qIJtdjZ0NeXqxDaDT702c5UITvjIXvjoX/1h2z2NHvSCT+6He7azo+dTvQj8uBVAc50M+1xL+AP8D6/ArSku38uXEzEHwcJ2BAi8xECsurCRiQm+FkTV45ZpOJ5AQrFS4vzbOS8PsNLCYTOVlJrKgqobTSg8NmoX2LVJKdNrZsq8LvD2CxmGmWnkBRmYuSCg8Ht7YGH+uqwTCM0KNewb/Dz4D5/QEqq720zE6kosob2R4EHw3LTHWwubASDGjZLGmH7YaXCccCUFHlpXlWImazKTQWkJecdCdbiqtw2i1YLGYMw8BiMUe2bzKB02GhotKLP3PHGGp+1rqE9xPe7/YxpiXb2VxYSevs5Ho/w872Ea36YmnMfTVUk0nsVLmCma0Ro0bFOJLG56qOTdZOGmbrtnwWrVjKbZffWOv1U4/uxzNvj2Xrtnxys3JiFN2BJ/y72R+vCSIHinDZLkH7c12nMR2I9aYDpQ6isl32Z65qF2lpkOCwYi4PjqNjt1kxDDCZDRw2Cx5fACMQwGQCk8lEgsOCyWwi4DUwDINkpw2HzYIB+AIGFgs4bH8lTCID99TgCxhYQkmG8Drhvw0g2WmjvMpb6z0g0pMm/HddasYCYNRYNrx9i8WMP2Bgs5mxmE214vYHDMwmsFnN+A2jzhhqfta6hPezsxitZhMGxk4TKdHsI1r1xdKY+2qoJpPYSXQGB3wafc89tGnRIsbRNI4NeXmMGDUKZ4Iz1qFIFHKzcujZuRvf/fwDpx3TL/L6dz//QM/O3faLClU8Cf9u9qdrgsiBIlz+hct2Cdof6zqN6UCuNx0odRCV7bK/qNljZ86S1Yx792WcCU4MoNrtIwAYBni8PkwmwDDh9vqxWMyYzGaMUO+aarcfIxDscWMymagIjddjIpiwACKzLpmCG9ohFqs5OJ4Nxl/rhF83ARUub63thbm9wTFxMIJ/J9h3TA24vf5a65r4a9nw9v3+ABazCVd1MMaacVvMJrw+8PkDOKyWOmOoK7btP1/N/W7PFzAwYdrpzFTR7CNa9cXSmPtqcGz7fI/1aNOiBZ0OOijWYcgBatDZF3LX6Icis1CEn21/csRDsQ7tgKVrgojsb3Rdk7ocSHUQ/QZkf5CUUoHHG6Bd62BPNAMwmyCvqAqLOfj31uLQODy+ABXVPlplJ1Hp8gYHFzYMNm2rxDAgLcmOP2CwsaCCrNQEkhNtWCxmAgGDgpJqqj0BUhJtlFf5yEwxaj0GZDIFB2kO/x1msZhJSrCxubCK5lnOWj1aAgGDojI3qUl2AIrK3KQ47bW2G14mHAsEZ34KL2uxmElOtFFS6SHRaaWgpBqLxRSJJ7ycy+3C5fbTPCuxzhhqbr8u4f3sLMbSCg+pScE40pId9X6GPVFfLI25r4ZqcokdkVja/nn27Z93FxEREdkbVAcRiS/N0pys21qOLdSIL6v04Ez0U1rpIdgRJpjgMJtNBIzgrFmbCysis2IVlrjw+Q0SnVbat0iNzIpVXuWlXW4KmworyC92UVzhxmG1cMhBwVmx1m0tJzPVUWs2JqfdAibTDu+5PD58/gDVbj+lle5a6/j8AVplJwHBWbHq2m7NZWp+5vCyKYm2yKxYBgZVbh8LVxfWmhUr3HOnvhiiOdY7i7F9i1TytlVF9Rka67zvi301RJNJ7KQkJmK1WklJTIx1KHKAC98xm/j5B/vtnTIRkb1JZXrddFykPqqDiMQPu81C29wUqqpSsVgsJCU68fqCjwP5/IApNC5NwMBmMYFh4A9AlduHywNWi5nUJBtpyQ5KKjwk2CzkpDspq/KyJq8MTGA1Bwch7tQqjWSnnaQEGwWlLrZsqyI84k5yoo1W2WkAdb7XIyuT0kpPHeskRablbpubspPtJtWaujv8mWsuazEFZ8NyOqxUVfsoLndjYGCzWnDaLbTMTiQrNaHeGKI51ruKsW2uJarPsKeiiSUWmkxiJzc7m2lvvUVKUmwyXCJh4btjE754X3fKRER2g8r0uum4SH1UBxGJL3abhcM6t+X7N97E6UwkEPDj9hqYCGCYzJgMA7vNjIEpmOcxGVR5/JiM4KDGdpsVvz+AL2BgNZuCAxH7A7jcXnwBSHRYsNustfbXKjt5h3XCdvZestO+03Wi2W40y4b/bcLA7zcwTOCwWqKOIZpjvasYG/IZ9tS+3Fe0mkxiB1BFR5qMIedczLgP32TIORfHOhQRkbikMr1uOi5SH9VBROJPempK6C8LTseul93+fYvFXGsGpeA4LrveyPbrRPPertZpyDI7W7bWv217vv1o97s39tFYsexLTSqxI9JUdD/4UMbc82SswxAREZEDjOogIiLSUErs7AObC7bEOoS4Y8nfQiawOX8L/kR9TQ9E+t2IiByY4uX6r7pKw8XLuRURiTcqhfai1ORkEp1OHnnpqViHEncy3X5eMMFdr/6bIkcT6d8m+1yi00lqcnKswxARkX0g3upNqqvsHpXtIiKNT4mdvSgnM5PJY8dSVlER61DiU3kV41I0c8iBLDU5mZzMzFiHISIi+0Bc1ptUV2kwle0iIo1PiZ29LCczU4WXiIiISBRUbxIREWm42M7JJSIiIiIiIiIiu02JHRERERERERGROKXEjoiIiIiIiIhInFJiR0REREREREQkTimxIyIiIiIiIiISp5TYERERERERERGJU0rsiIiIiIiIiIjEKSV2RERERERERETilBI7IiIiIiIiIiJxSokdEREREREREZE4pcSOiIiIiIiIiEicUmJHRERERERERCROKbEjIiIiIiIiIhKnlNgREREREREREYlTSuyIiIiIiIiIiMQpJXZEREREREREROKUEjsiIiIiIiIiInFKiR0RERERERERkTilxI6IiIiIiIiISJxSYkdEREREREREJE4psSMiIiIiIiIiEqeU2BERERERERERiVNK7IiIiIiIiIiIxCkldkRERERERERE4pQSOyIiIiIiIiIicUqJHRERERERERGROKXEjoiIiIiIiIhInFJiR0REREREREQkTimxIyIiIiIiIiISp5TYERERERERERGJU0rsiIiIiIiIiIjEKSV2RERERERERETilBI7IiIiIiIiIiJxSokdEREREREREZE4pcSOiIiIiIiIiEicUmJHRERERERERCROKbEjIiIiIiIiIhKnlNgREREREREREYlTSuyIiIiIiIiIiMQpJXZEREREREREROKUEjsiIiIiIiIiInFKiR0RERERERERkTilxI6IiIiIiIiISJxSYkdEREREREREJE4psSMiIiIiIiIiEqeU2BERERERERERiVNK7IiIiIiIiIiIxCkldkRERERERERE4pQSOyIiIiIiIiIiccoazUIerxeADXl5ezUYERERkWiE6yThOsqeUl1HREREmppo6ztRJXa2FhYCMGLUqD0MS0RERKTxbC0spGvHjo2yHVBdR0RERJqe+uo7JsMwjPo2UlZRwbylS2menY3NZmvUAEVEREQayuv1sqWwkCO7dSM1OXmPt6e6joiIiDQ10dZ3okrsiIiIiIiIiIhI06PBk0VERERERERE4pQSOyIiIiIiIiIicUqJHRERERERERGROBXVrFh7049z5vDKBx+wPi+P3t26cd/115OZlhbrsGKmrKKCF955h59++42yykr69ujBHVddRbPMzFiHFnMz5s7l5pEjGdC/P48MHx7rcGLK4/Xy7FtvMWPuXKqqq+ndvfsB/z35+NtvefuTT9haWEintm0ZccUVHN61a6zD2if8fj8//fYbX/74I1/NmMHjt93GGccfX+v9595+m29nz8ZmszHwlFO46oILYhjx3lXf8Zi3dCkTP/uMeUuXkpGayt9PO43BAwZgNu+/9zrqOyY13fnUU3w7ezavjhxJ7+7d93GkEiuqj0WnIb8lUb22IQqKivjvxInMWbyYiqoqenbpwi1DhnBwu3axDq1JU/ugftN//ZVbHn98h9dfePBBjj388BhE1PTFY1srprXY35Yv5/Ynn+SwQw7hwRtvZOu2bVz34IP4/f5YhhUzJWVlXHXvvSxfu5ZrLryQO/75T5auXMktjz1GIBCIdXgx5fX5ePqNN7Dsxw2vaAUCAa594AGm/vwz/7zgAu665hryCgp478svYx1azEz9+WceHjuWfn378tSdd9I8O5ubHn2Urdu2xTq0faK4rIzHX36ZuUuW4K/jWvHUa6/x2bRp3HDZZQw+91zGvfceb02evO8D3Ud2dTym//orNz78MM0yM3l0+HBOP+44xowfz7tffBGjaPeN+r4jYfOWLmXqzz/vw8ikKVB9LHrR/pZE9dqG8Pn9DL3/fgqLi7lp0CBuGjSIzfn53PDww1RUVcU6vCZL7YPolFVWkmC388aoUbX+637wwbEOrUmK17ZWTHvsTPj0U47u1Ys7rroKgB6dO3Pm1Vfz02+/cfyRR8YytJhITU7mH2ecwQVnnIHNGjw1LXNz+ec997B01Sp6dO4c4whjZ9KUKXh9Pnp06RLrUGJu2i+/sHjlSib/97+0bt4cgJP69MFiscQ4stj5euZM2rZsyS2XXw7A4V270v+KK5g1fz5/P+20GEe392VnZDBl3Dg25+dz1rBhtd4rLS/n42+/5bERIzjt2GMBqKquZsInnzD43HP3y+/Nro5HhzZtePy22+h/9NEAnNinDwXFxXz49dcMOvfcWIS7T+zqmIQFAgGeevVV/nbiiXz+ww/7NkCJKdXHohfNb0mCVK+NntVi4cUHH6RVbm7ktS7t23PF3XezeMUKjunVK3bBNWFqH0SntLyc7IwMDj/00FiHEhfita0Vs/Sm1+dj+q+/cuoxx0Rea5aZyWGHHMJ3s2fHKqyYMpvNXHL22ZHCD+CQ9u0B2FpYGKuwYq6otJSXJ03imosuwtrEf1D7wjuff06/Pn0iFxoAh91+QB+b1OTkWscjyemkTfPmuN3uGEbVNPw4dy4mk4kTajTOTj3mGAqKi1m4fHkMI4uNNi1aRJI6YV3atz+gr7FhH3/3HZu2bmXwgAGxDkX2IdXHZG9RvbZhaiZ1IPgoCEBiQkIswmny1D6IXllFBZnp6bEOI27Ea1srZomdopISvD4fbVu1qvV625YtydPFPmLlunVA8C7zgWrsxIm0ad6cASefHOtQYi4QCLB05UqO6NYt1qE0KWf368e8JUsij5Bszs9nU34+/Y46KsaRxd6WggJys7NJcDgir7Vu3hyrxaJrbciqdesO6GssQHllJf+dOJHrL72U1OTkWIcj+5DqY7IvqV67a4ZhsK2khB/nzGHkiy9y6rHHctghh8Q6rCZJ7YPolVVUUFBUxPk33UTfCy/kkttuY8bcubEOq0mK57ZWzB7FKiwpASBtuwpkWkoKi1asiEFETdP/vvmGDq1b0267CteBYvmaNUz+7jtefeyx/Xpg02iVV1ZS7fGQlpLCM2++yZTp0wE44/jjGT5kCA67PcYRxkavQw5hxJVXctsTT3D0YYdRVlHByFtuoUWzZrEOLeYKS0p2uM5CsJdTYXFxDCJqWkrLy/n+p58O+F4q4957j4zUVC4+6yzyD5CxqSRI9THZlw70em195i1dytX33w/Aib17M2rEiBhH1DSpfdAwHdq0YX1eHhf97W+YTSbemjyZWx9/nAn//jeHduwY6/CalHhua8Xsl2AK/d8wjFqvG4aB2WTacYUD0G/Ll/PJ1KnccvnlB+xF69+vvcaZJ5ygZ0JDwt1yX3jnHQKBAI/deitXnH8+H379NePefz/G0cXO76tWMfHzz3lsxAha5eayct06ZsydGzleBzITO15nAQzQtRYYM348dpttvx5fpz5/btrEu1Om8K+rr27y3Yyl8ak+JvuK6rX1O7RjR8Y+8AC3XXklK9et44p77qHS5Yp1WE2O2gcNc9Hf/sYLDz5Iv759ObFPH56//35SU1J45/PPYx1akxPPba2YXVWzMjIAKK2oqPV6eHCnA11hcTF3/fvfnNe/Pyf17RvrcGLim1mz+H31am654opYh9JkZKalYTGbuehvf+OOq67iqMMOY8iAAVxw+ul8M2tWrMOLCa/Xy21PPMFVF1zA2SedxP/dcAOTx47ll0WLeGLcuFiHF3NZGRk7XGcNw6BM11q++OEHPvn+e0beemutR9UONP95/XVO7N2bow87LNahSAyoPib7guq10UlyOjnuiCO4fOBA3nziCdZs2MA7n30W67CaFLUP9lyi08lhXbrw56ZNsQ6lyYnntlbMHsXKSk/HYbfz58aNtbKtazdtouMB/tyt2+NhxKhRZGVkcO9118U6nJj56OuvcVVXc3polo6aPp06lSnjxtEyJycGkcWOxWIhJytrh26A7Vq14uPvvotRVLG1esMGthQW0q9Pn8hrrXJzuehvf+PNjz/mgRtvjGF0sdeyWTO2Fhbiqq7GGRqAcX1eHv5AgBYH2O+npkV//MHDY8dyy+WX06dHj1iHEzNbCwuZOW8eAL0GDqz13tX330/v7t15deTIGEQm+4rqY7K3qV67e3KzsujQujV/rF0b61CaFLUPGofH6yU5MTHWYTQ58dzWillix2qxcPJRR/Ht7NmcH5qOeGthIUtWrOC6Sy6JVVgx5/X5uOOppygqLeWtJ57AbrPFOqSYuf/666mqrq712sNjx5KTmcn1l15Ks8zMGEUWW6cdeyxTpk/nkrPOiry2bPVq2h+gz6tnpKUBsOLPP+nbs2fk9YKiIpKczliF1WSc2KcPJpOJ6XPmcOYJJwDw3ezZ5GZl0fMAnWp21fr13DxyJOedcgpDzjsv1uHEVGZ6Ou+NHl3rtYKiIm569FEevPFGenfvHqPIZF9RfUz2JtVro1NeWcnsBQs44/jjI69Vulxs2LKFo9Sbsha1DxqmoqqK2QsWcPpxx0VeKywu5rdlyw7ox9B3JV7bWjFL7AAMOvdcht53H0+++ip9unfn1Q8/pEv79hxVo3F2IAkEAvzfc88xZ9EiHr/tNjZt3cqGLVsAsNtsdOvUKcYR7lttWrTY4bXEhARSk5PpEpou80A0aMAAPp06lbuffpqzTjqJ5atX89m0aTx2gA6wl5uVxWnHHstdTz/NNRdeSLtWrfht2TLe//JLbho8ONbh7RPrNm+mqLQ0Mhjy2o0bWbBsGZlpabRt2ZJ/nHEGT4wbh8frxVVdzbj332f4kCH77RgHuzoeZpOJ6x98kINatOD8U09lwbJlkfVaZGfTfD8dcHtXx2T762lKUhIQvAbXdR2W/Y/qY9Gr73orf1G9NnpLVq7k/mef5Ydff+X4I48kwW5n/KefEggE+Hso4SpBah80TK3v1hFHYDKZeOX990lKTDzgb27tTLy2tUxGXaNq7kMz583j5ffeY31eHn26d+e+668nIzU1liHFzLylSxl63311vtcyJ4cpGi+Eq++/n5Y5OTwyfHisQ4mp9Xl5PPnKKyz64w+aZWRwxfnnc94pp8Q6rJipdrt5/X//46sZM8jfto02zZtz8VlnccHpp2M6AAb/fGDMGD6dOnWH1wf0788jw4cTCAR47u23+WbWLGw2G+efeir//PvfYxDpvrGr42Eymfjk++/rXO+6Sy7Zb3so1PcdqWlzfj5nDRvGqyNHqsfOAUT1seg05Ld0oFO9tmEW/fEHk6ZMYeHy5ZRXVtKjc2duHjyYQzp0iHVoTZ7aB7u2ZOVKJn3xReS71adHD+646ipys7NjHVqTFY9trZgndkREREREREREZPfsn/3wRUREREREREQOAErsiIiIiIiIiIjEKSV2RERERERERETilBI7IiIiIiIiIiJxSokdEREREREREZE4pcSOiIiIiIiIiEicUmJHRERERERERCROKbEjIiIiIiIiIhKnlNgREREREREREYlTSuyIiIiIiIiIiMQpJXZEREREREREROKUEjsiIiIiIiIiInFKiR0RERERERERkTilxI6IiIiIiIiISJxSYkdEREREREREJE4psSMiIiIiIiIiEqeU2BERERERERERiVNK7IiIiIiIiMgBz+V288X06Zx/000cddFFsQ5HJGrWWAcgIiIiIiIiEmt/rF3LI2PH4vP5sFrVVJb4oR47IiJ16DVwYOS/u59+utG2O2b8+Frb3pyf32jbFhER2V1nDRtGr4ED+W727FiHEpX5S5dy5tVX8+xbbzV4Xb/fz9D77uOiW2+ltLx8L0RX25+bNnHu9dc3an0iGg+MGVOrzuHxevfp/vdE7wsuiEk9qdchh/DL++9zdr9+tV7/c9OmWsfypUmT9mlcIvVRGlJkL3pp0qR6L/y9u3fn1ZEj91FETdNZw4axOT+f3yZPjnUotfQ/+miGDxlCotMJQGl5OY++8AI//fYbLZo1419XX03fnj1rrVNUWsq4995j4fLlbNiyhYPbtuX4I4/kivPPx2qxMHjAAAb078+kL75g0pQpsfhYIiISQ3urbhDe7iPDhzOgf/89CTEu/Dh3LlsKC/ls2jRuveKKBq27bvNm5i1dCsCSlSs57ogjgD0/hnOXLOHq++9nQP/+PDJ8eOT1XxctYkNeHpu2buXBG2/EmZDQ4G3vicljxwJgUw8UDMOg2u3e4XWz2YzDbt/peq1ycpg8diz527Yx7IEH9maIIrtFv26RvSglKYmWOTmRf4fvOjTLyMBmswGQnZERk9iakqKSkliHUKfkxETatWoV+fczb75JflER7z/7LFOmT+e2J57g69deIymU+Jm/dCn/+s9/KCwuBiA1OZkFy5axYNkyfl+1iqfvvpvMtDQy09JIT02NyWcSEZHY2lt1g21NtCzdW845+WSWr1nDKccc0+B1O7Rpwz/OOIOyigqO6NYt8vqeHsOdrd/vqKOYOW8eh3bsuM+TOkCtusyBLq+ggLOGDdvh9fqSqTabjXatWmEP/UZFmholdkT2okHnnsugc8+N/LvXwIEAPHfffXTt1ClGUTUtVS4X1R5PrMOIytKVKznn5JNplZvLBWecwdh33mH95s0c2rEjrupq7nr6aQqLiznuiCP4v+uvp3mzZuQXFfHcW28xeMCAWIcvIiJNwN6qGxSXlu5paHGl00EH8dLDD+/2+vdff/0Or+3pMdzZ+jmZmYy5//492rY0juyMDN4YNWqH11MSE2MQjUjjUWJHpAnx+ny88sEHfDd7NoXFxXTt2JERV15Jl/btI8ucNWwYWwsLmfXuu7w0aRLfzJpFgt3O+aefzpABA5izeDGvf/QRS1aupGvHjjx4002RO4Ob8/M5a9gwjjviCG65/HLGTpzIgmXLaJWTw+ABA3Z4nriopIRn3nqLXxctAqBP9+786+qrSUtJqbW9o3r25Ik77uCJceP46bffuHnwYC4880zWbd7MhE8/ZdEff7AhL4/WzZtz+Xnncc7JJwM7dkcPV25fHTmS3t27R/79zn/+E6nsvj15Ms+8+WatOyvh7Tx2662kpaTw8nvvsT4vj8ljx5KRmkqVy8XzEyYwc948KlwuDuvShX9dfXWtO6bR6NqpE9N++YXTjzuOKdOnk5yYyEEtWwLw+kcfUVBURNuWLXnuvvuwWixAsDL32IgRDdqPiIhImNfn47UPP+S72bPZUljIwW3bcsX559Ovb1/gr7I47IExY3hgzJjI40CGYTDtl1/4dOpU/li7lkqXix6dO3P3NdfQpkWLBsXSa+BAOrRuzX8feIAx48fzy6JFZKSmcv6ppzLkvPMiyzVWubx01SpemjSJ31etwmKx0Kd7d2775z/JSk/fZX3gyTvuoLyykv998w2b8vPp2aULd19zDa1ycwEoKSuj3+WXAzBl3DiAPT6G4cfKAT6dOpVPp06lZU4OU8aN47vZs7njqaci/4723NY8v727d+epO+/k+fHjmb1gARaLhcvOOWe3bhw1Rl2yT48ePDZiBM+88Qa/LFpE25YtGXbRRRx7+OF88NVXfPztt+QVFHBSnz7cPWwYCQ7HTuNZs2ED/3n9dRavWEHr3FyuveSSOperr1752ocf8vyECfTr25dn7703sl5RaSmnXHkliQkJTHv7bQ4/9NAGHzORpk6JHZEmIhAIcMPDDzNn8WKsFgtJiYn8vHAhV95zD+8+/XStbrT+QIB/3nMPy9euJcnpZHNVFU+//jrrN2/m4+++w2Gz4XK7+WXRIu4bPXqHOxMLfv+dQXfcgQFYLRaWrVnDfc8+i8Vi4cwTTgCgoKiIS2+/ncLiYhIcDswmE19Mn87vq1fzwXPPRRIXAFsKC7nlscdYunIlqcnJtGvVipKyMi6+9VaqPR7sNht2m40Vf/7J/c89R1pKCif07k1KUhLNMjIoCD26FK407OoZ5135ce5cpv/6K1arlWaZmWSkpuJyuxl8552s2bgxEscPv/7Kwj/+4JOxY0lNTo56+7ddeSWPvvAC/xg+nBY5OTx9112Rx7BmzpsHwJDzzqt1bERERHZXIBDg+oceYu6SJUDwEeHwI763XnEFV55/PhaLhZY5OeQXFeHz+chITcWZkBB55Pf9L79kVCiZkJqcTGVVFbPmz2fo/ffzxUsvRR7/itb6LVu46NZbqaquxulwsGbDBp5+4w28Ph9XXXBBrWX3pFz+asYM7n/2WXx+PzarFZvVyhfTp3NC796RusrOjHr5ZUrKy0lOTKTS5WLG3Ln8vmoVk8eOJSUpaYflG+MY5mZlUVpeTqXLRWJo3dysrJ3GGM25rWn1hg1cdvvtFBQVkeBwUOly8Z/XX6dbp04c3rVrPWdtR3tal1y9fj2D77yTkrIyAH5btoy7/vMfTurTh89/+IGUpCTKKyuZ/P33NMvM5MZBg+qMY82GDQz517+odLmwWq2sz8vj1scf32G5aOqVZ590EmPfeYeffvuNKpcrMkbiT7/9hmEYnNC7tx6lkv2WZsUSaSL+9+23zFm8mA6tW/PlK68wffx47r7mGlzV1bz5v//tsHxldTWTx45l2ttv07NLFwA++uYbbr/ySn6cMIHRd98NwIJlyyJjvoRVVVdzwemnM2PCBGa+8w7nhHrqjHv//cgyT7/xBoXFxZx5wglMHz+eGRMncsbxx7N240a++vHHWttbt3kz20pK+PTFF5n29tv06dGD9NRUbho8mLEPPMCsd99lxsSJkYpYeNDgQeeey3P33RfZzpRx45gybhw9OnferWP49cyZnHXSSUx76y0+/u9/AXjl/fdZs3EjR3brxndvvMHMd97h8oEDKS4tZdIXXzRo++mpqTx9993MnjSJj8aM4ajDDgOCA/H9uXkzAId06LBbsYuIiGzvo2++Ye6SJTTLzGTy2LHMfOedSC/QF999lw15eeRmZTFl3DjahXqQjrjySqaMG8dtV14JwLknn8yQAQP49MUX+XHCBL569VWSExPJ37aNqb/80uCYfD4fRx92GFPffJMZEycy9B//AII9arcflHZ3y+XisjKeGDcOn9/PxWedxax332XmO+/w8sMP15vUAQgYBs/eey8zJk7ksxdfpFlmJttKSvjw66/rXL4xjuEbo0ZxbqjnyKnHHsuUcePqfOQnLJpzW1NxaSkHt2vH92++ybS336Zzu3YAfP/zz/Uej53Zk7pkUWkpXTt2ZOpbbzFl3DgSExIor6zkx7lzeeXRR5kxcSJDQr2Jvt3FTGvPvf02lS4Xhx1yCFPffJOZ77zD43X0dI6mXtm8WTP6dO+O2+NhRuiGG8Ds+fOB4KQY0Xpk+HB+qVEvFmnqlNgRaSK+mjEDgKsvvJBmmZkADOjfH5vVyoJly3ZY/qZBg2jbsiU2q5Wje/UC4PBDD+XSc87BYrFw/JFHYjYHf+JbCgt3WP+2f/4TZ0ICVouF60JdXtds2EBxWRk+v5/vfvoJgBFXXIHDbsdisTDw1FMB6oznnmHDIl2cwwYPGMBxRxyB1WJhc35+pEfO+lASpLHlZmVxz7Bhte4+ho/rzUOGRO4CXnD66Tv9HLujuLQUV3U1QOTciYiI7KlwGTZkwIBIz92zTzqJI7t1w+3x8MOvv9a7jUSnk9uvuoqDWrTA7fFQWFxM6+bNgd0vj28aPJj01FTMZjNXX3ghDrudkvJyVm/YUGu53S2XZ82bR0l5OS1zcrhz6FDsNhtmszlyQ6U+xx5+OP369sVkMtG6eXPOD9Vf5v/++2593r1xDHfn3D58882kp6Zit9k4OnQs8rdt2639w57XJR+48UaSExPJzsjg0I4dAbjk7LPp06MHACf26bPTdQE8Xm8kAXP7P/9JanIyJpOJM44/vs7lo6lXhh/LCieTDMNg9m+/4bDbOT40+5nI/kiPYok0EeHK0L2jR3Pv6NG13qurQDSbTJG/w48DmWq8ZrFYcNjtuKqr65zWsaZWublYLRZ8fj95+fkUORz4fD4Azrj66h2Wryue7gcfvMNreQUFvP3JJ3w+bRrllZWR1/fWzB1d2revVXl0VVeTV1AAwJWhu0417ayi0VDpqak47HbcHg/biot32fVaREQkWms2bgSINJrDDu3YkXlLl7J6/fqotjNr/nzGf/IJcxYvxh8IRF5vjPLY6XDQLCODjVu3kpefT7caA0Dvbrm8KvS5DjvkkEZ5vPmg0Dg4eaExcHZHYx/D3Tm3Net+4dm16qvj7cqe1iVrrh9+7Kmu13YW4/rNmwkEApjNZg6NosdzNPXKU44+msdffpmZ8+bhcrtZu2EDxaWl9OvbNxKPyP5IiR2RpsIwgNrTnYYl1zNSv6mBr2/P4/VGKilJTidevz+4vslEi2bNdli+rte2t6WggCvvvput27bRt0cPTj/+eDxeL0+9+mqUUf3FaPAaofWMv9Zsnp0duesUFr7btqfMZjMHtWjBynXrWPHnn5rxTERE9qqa5Vt9Jn//PQ89/zzOhAQuOOMM+vTowWdTp/Lj3LmNFk94dsv6Gs7RlsuBUJ2kZpJhX8S3M/viGIZFe24b69hEttfA16NZrr51feH6JuzwXdhetPXKRKeTU44+ms9/+IE5ixZFbpyecswxUX4SkfikxI5IE9GhTRvmLV3KjYMHM/CUU/bpvpetWYNhGFgtFlrm5kLob5/fz7hHHtmtBMiXM2awdds2+h99NM+E7sqFBwisqWZB7vF6aw1ql2C3U+3xUOVyRV6rrPF3fRKdTppnZ5NXUMCjt9wS6Rq8N/Tu0YOV69Yx4dNPGdC/f70VFBERkfp0aN2aeaWlLFu9ulYZtnzNGgA6HnRQ5LVwuePxemtt462PPwZg1G23RWZbmtGICYmthYWRHhNtQ2PU7Ey05XL71q0BWLh8OX6/H8se9tr5fdWqqOLb02O4s/Xr0pBzu78KP8LvDwRYu2kTnXbxmaOtV0LwcazPf/iBmfPns2nrVqwWCyeFHgsT2V+p5SHSRJx27LEAPD9+PIv++AMI3rX56bffoqogNNRXM2ZgGAZlFRU8+9ZbAPTr2zc484TNFqm4/N9zz7E11DXa7fEwe8GCqLafX1QUWcfv91NWUcEHX321w3LZGRmRv39euLDWe+Hxar6aMQO3x8PUn3/mzVDlKlrh4/r4yy+zJnTXxu/3R2axaizXXnQRqcnJrFq/nhGjRkWO2baSEh58/nmee/vtRt2fiIjs/04/7jgAxn/6KX9u2gTAFz/8wLylS7HbbJxUY1rscHn666JFkR4vEJzlEv66MbJ4xQrmLF68w76sVmut5Xbl21mz8Pn9uD0e/v3aaxiGQddOnXaYrrwu0ZTLxx5xBM6EBDZt3RqcccvrJRAIMGX6dMoqKurdx/I1ayLbnrd0KVOmT6+1753Z02MYXn/RH39Ext7bmYac2/1VSlJSpJfz8+PH4/Z48Hq9vPDuuzssG229EqBvjx7kZGUxY+5cFi5fTu/u3Rs0C6pIPFKPHZEm4sIzz+TrmTNZsGwZl991F+kpKVS73VR7PNw5dCiDzj23Uff3wJgxPPnKK7i9Xnw+H8mJidw0eHDk/TuHDmX+77+zYNkyzrzmGjLT0igtL8cfCPDu00/XO/vTUT178u7nnzNr/nxOGDQIt8dDemrqDl2HszMy6HbwwSxduZJbHnuMnMxMHrzpJo49/HBOOeYY3vz4Yz765hv+9+23GIZBv759oxosMuy6Sy5h+pw5rN24kb/ffDMZaWlUVFbi9fkYfc89nHzUUQ07cDuRnprKo8OHc9+zzzJ9zhymz5lDanJypAJ6ZLduO/RIEhER2ZULzzyTb2bNYt7SpQwMDVRbUVUFwPWXXhoZOwbgpD59mL1gAd/MmsX833/n6F69GHnLLfTt2ZOpP//MfaNHM+rll6moqqJZjZsqYW1btmT95s2MevllunbsyMGhWZfqMvadd3jto48wDAO3x4PNauW2K6+M6vGgaMrl3Kwshg8ezJOvvso7n3/Oh19/jcViwVVdzeABA7jjqqt2uY8/N23i7zffTFpKCqXl5QAc06tXZDDfndnTY3hinz48P2ECm/PzOX3oULLS05k8dmyd+2rIud2f3XDppQx/7DGmz5nDCYMGYTaZ8AUCtY4HRF+vhGDPqbNPOok3QrPK6jEsORCox45IE2GxWBj36KPceNllHNKhA26vl5Y5OQweMIC/nXhio+9v7AMP0LZlS5wOB8cefjjjn3oqMisDQG52Nh+OGcP5p51GmxYtcFVX07l9e+4cOpSObdrUu/1+ffsyfMgQcrKySHI6Oefkk/nguefISk/fYdknbruNvj16kJiQQHJSUmSQvWsvvpizTjqJ1ORkurRvzz3DhnHfddc16HMmOp1MeuYZhgwYQMeDDqLa7aZ969Zcd8klHNWzZ4O2VZ+T+vblg+ee47xTTqHTQQfh9/vpdeih3DhoEC8/8oiSOiIi0iBms5mXHn6YYRdfTMeDDsIwDHodeijP3H03//z732ste8EZZ3D5eeeRk5WFYRjYQj1w7r32Wvr17UtyYiKtcnO5e9gwHrr55h32deNll9G+dWssFgtb65lp6ak776Rrx47YrFaO6NqVV0aOpHf37lF9pmjL5UvPOYexDzxA7+7dSXA4yEpL48Izz2TYRRfVu48zTziBqy64AIfdTotmzRgyYABj7ruv3vX29Bh2OuggHhk+nHatWmEYBlnp6TvtYdSQc7s/O/7II3nu3nvp2aULdpuNHl268Ppjj3FE1661lmtIvRLgrFDd2Ww2N9pNPJGmzGQ0ZPQ1EYlrm/PzOWvYMAB+mzw5tsE0cb0GDmRA//48Mnz4Xtn+S5Mm8dKkSUwZNy6qrusiIiKx1mvgQIAmW3aFy9a9WX7HkwfGjOHTqVMPyDrfzwsXct2DD9K7e3deHTmy0bYbrktfd8klXHfJJY22XZE9pR47IiIiIiIisl/YVlLC8xMmAMFH3kQOBBpjR0RkJz6bNo0p06dz2nHHMeq22xplm89PmMBbH39MQJ0lRUREZB/ofcEFAMyeNGm/fyz85pEj+em33/D5fBx+6KH1DpgdrT83beIfw4dHPR29yL6mxI6ISB0+HDMm8ndKYmKjbfeyc86pNWZSeOYvERERkcZ046BBXB56fA6IjBm0v/L5/azdsIFkp5NjDj+cu66+OjIF/Z5qlZPDpNGjI//OTEtrlO2KNBaNsSMiIiIiIiIiEqc0xo6IiIiIiIiISJxSYkdEREREREREJE5F9aBlWUUF85YupXl2Nrb9fMAtERERafq8Xi9bCgs5sls3UpOT93h7quuIiIhIUxNtfSeqxM68pUsZMWpUowUnIiIi0hhG33MPJx911B5vR3UdERERaarqq+9EldjJzc6ObKxNixaNE5mIiIjIbtqQl8eIUaMidZQ9pbqOiIiINDXR1neiSuzYQ12S27RoQaeDDtrz6EREREQagb2RHptSXUdERESaqvrqOxo8WUREREREREQkTimxIyIiIiIiIiISp5TYERERERERERGJU0rsiIiIiIiIiIjEKSV2RERERERERETilBI7IiIiIiIiIiJxSokdEREREREREZE4pcSOiIiIiIiIiEicUmJHRERERERERCROKbEjIiIiIiIiIhKnlNgREREREREREYlTSuyIiIiIiIiIiMQpJXZEREREREREROKUEjsiIiIiIiIiInFKiR0RERERERERkTilxI6IiIiIiIiISJxSYkdEREREREREJE4psSMiIiIiIiIiEqeU2BERERERERERiVNK7IiIiIiIiIiIxCkldkRERERERERE4pQSOyIiIiIiIiIicUqJHRERERERERGROKXEjoiIiIiIiIhInFJiR0REREREREQkTimxIyIiIiIiIiISp5TYERERERERERGJU0rsiIiIiIiIiIjEKSV2RERERERERETilBI7IiIiIiIiIiJxSokdEREREREREZE4pcSOiIiIiIiIiEicUmJHRERERERERCROKbEjIiIiIiIiIhKnlNgREREREREREYlTSuyIiIiIiIiIiMQpJXZEREREREREROKUEjsiIiIiIiIiInFKiR0RERERERERkTilxI6IiIiIiIiISJxSYkdEREREREREJE4psSMiIiIiIiIiEqeU2BERERERERERiVNK7IiIiIiIiIiIxCkldkRERERERERE4pQSOyIiIiIiIiIicUqJHRERERERERGROKXEjoiIiIiIiIhInFJiR0REREREREQkTlljHYCINK78oiLKKipiHcbeVV4FKYmxjmKvS01OJiczM9ZhiEgj2+E6vRevabqOiIiI7P+U2BHZj+QXFTHwxhupcrliHcpek+n288K8Em44Mp0ihyXW4exViU4nk8eOVaNMZD+y/XV6b1/TdB0RERHZ/ymxI7IfKauooMrl4oHr/kXLZs1jHc5eYflzI7a59/Hk1Xfib9c61uHsNZsLtvDIS09RVlGhBpnIfmT76/TevKbpOiIiInJgUGJHZD/Usllz2rZsE+sw9opAlY9qoGVOc8z76WcUkf1f+Dqta5qIiIjsKQ2eLCJxYcnKZQwfdRdLNq6NdSgiIk1S5Dq5clmsQxEREZF9qMn02PF4fbi9ARw2M3Zb3WH5/QF8AQMTBgYmrGYTFou5zmW2f6+u12tuzxcwMBlgtwWfb3f7/JF/h5cvr6wkJSlpb3x8EanH+M/fY+X6NUwwvuahWAcjcgDZnbJvZ2WxQOVeHAMtfJ0c//l7PDniob22n8bicnv4Zck6Sqt3rPeZAGMn65mBQB2vWwFfjX87rYAFbIAnAD7vdu/bwGQE9+MPgDfw1z5tgN0BWalOEuw2Kqo8+AlgMZvw+w18AR+G3wQm8Pn8eP2QmAAJDidur49qtxcCYDGD2WLB6bSQYLUCJhwWK5jAEwiQaLfg9hqUu9z4DT+mgAm7w4rdbMEb8OMLBCAAhsnAFPrcZjNYTRaMgIHH78fr82Ix2UhOtJOSZMfr9uHxB7CaLZitZmwmA4vVitkEJosJ/AHcPkiwm0hJcuCwmiP1YEwGJZU+3B4PDrudRIcZl9tPIBDAZDbj9/vx+cFuM2OzmLFYTLjcfvx+PwkJNhLtFlxuH74AJDosGAZ4fX4qXT7cngAWE1htZlKT7WAYVFb7SXTacFiD27FbzdhtZtxeg4AR3JfHEyAQ8GNz2HBYwGK2YLaYqPb48HoDJDmt2C0WDBM4rMF6e806vt9vUOX14/P6cDiC+/L5wWQKvmeYTJgMA59hYDWZQzEE2wN1tTv8/gBun5+A3wAMzBZzZL9hDbkGhpcNBPy4vQGsZjMWC7i9BlYzOB02ADxeP4YJrOHvoBE8ZxazqVZ7pa79b3886jpWNWOt2S6zmM07bUPt6vPtrO1Vs40VPsZWswmou/1Vn+23ubPPFK26thfNZwurq01bXzz7sszc02NTX1t8d+IJf7d39Z3cmxrjmDSF+k7MEzsVLg9r88ooq/SGviImUpNstG+RSrLTDgQvZAWlLkrL3VS4gxdxm81MUoKN9GQ7zdKcABSUuqio8mIQrBAkJ9pIS7JTWump9XqCwwIGVFT7KK/yUFXtwyB4oQwW6AZmsxmzCRw2CznpTsxUc/5NN/DFSy+Rm50di0MlcsBatGIpi1YsZfDZFzHhi/dZkmqld6yDEjkAbC0s5Ozrrou67AuX19uXxc3SnJFK/IFsa2EhQ++9d69se/vr5KIVS0lLTt0r+9pTxeXV/Lgoj9LyEp4bN5Jbht1PWkp6rWV2ltSBupM6UDtpA+DyBV/cWSrN5d35PryA1w2VBS52voU6tlde17J+iiv9gCeq7US/XO11Csp2Zz0wm8BuNeH1Gfh3deD3EVPo/w0JxQwkJdpIclhx2C2YzSaqqn2UV7qp9gYwACO0QZPpr30EauzEFHrPaoEEm40EhwWTKZhEsdnMJNgtBAIGrmoflW4fXl/wm2izmkl22miRlUhWasIO7Y6dXQPD18ttZdUUlVUHE2iGgWEYGEbwvFgsZixmE1azGZMFfD4Dnz8QXCaU/rRbzaQ47TTPTCQrrfb+/QGDQCCYsax0+0JtHgO71YLNGvxMdosZs8WMCbBaTZRXeal0+fAbAXw+A6vFRHqyA4fNEmlDVXv8O/18dZUDCXYLvkCAojI3bm+AgBGMyWGz4HRYcXl8uD1+MJlqtb9aZCXttOzweP3kFVWSX+zC7Q0ABjarGYet9meKtgyqa3vbx7GrMs7j8+/Qpk1yWklx2vD5jTqP174sM/dkX9G0xRsar8frJ29bJfklLtxeP2DCajHt8J3cm3WIxjgmTam+E9PEToXLw+I1RVgtZtq1SCHZaaPC5WVzYRWL1xTRo0MmdquFdVvLAfAbBunJdpISbMHMvzd4gVpTVQaGgcNupXlWIg6bBbfXT36xi/VbK8hOS4i8XuHysnpzGYFAALvNimFARooDE1Bc4cbrD2A2mchwBrdVWuFhS3EVZWWF+Hw+yquqyI3lQRM5AE384gN6du7GoHMuZOGiubxf+ocSOyL7QHlVVdRln8frZ93WcqwWc62yuKjMzbqt5bTNTTngkzvlVVX4/P69su2a18lFK5cy8YsPuOHioXtlX3sinNQBcLtd+AN+3G4XbJfYkX0nYEC1twlkdNh1T626mAGTOdh/oNLlBQwqqn2YQzfO3T4DTGAzBz9nIBD8f7ghZjYFEz5G6G+r1Yw/YFDl9uHxBUhy2mjTLIkqt4/8Yhdef4BAwMBut5CWbMdkQJUnmOTZWFDJxvxKcjKc9V4Dw9dLvz9AcbkbfwBSE22UV3nwGcFkEQaYzSa8Pj9eAjhsFixm8PvBb0CCPZhQcnv8uH1+NhVWsrGwkpz04P7NmPhzaxlV1X6qvT6sFhMZKQ4sFhNeb4Aqt48qt4/MFAcdcpOpdPn4fV0xZhMclJNMlduHz2/gcvsoq/LSNtfB5m1VgEHHlmnBfW/3+YAdyoEKl5eVG0uocvvJSXfSMttBfokLV7UPt89PtcePyWzCajXjdFjJSXdG2l8uj58OLVLrTIqt2VxKaZWXlEQbbZsn4PMFWJNXTlW1m4zQZzIMoiqD6toeQGFJdSSO1s2SyNtWVWcZt3JjMSWVXuxWS6RNW1LuZk1eGdvKqunaNpOMFEet49UiK3Gn22vsMnNPyufwurDztvi66obF6/H6WZNXRmmlmxSnnbbNU/D5DNbklVJU/td3MtrzF6tj0tTqOzHtL7Q2rwyrxczhnbJplZ1MWpKDVtnJHN4pG6vFzNq8MgpKXVgtZpx2K8lOO51aptMqO5lOrdJIdtpJcAS7fLo8ftrmppCW5CDBbg3+32GJrBt+3e310ywtAYfNgsvtJTfDyWEds8lKT8BiNpOVmkDb5imYQ10CDzkog+w0J27P9veBRGRfCN+FHnT2hQBcdsxpLE2zsWjD6hhHJiI1hcvr7cvitrkpWC1mCkr33iNIB7rtr5ODzr6QRSuW8sefq2Ic2Y6Wry+OdQhC8BExU+j/NSUnmElKsGAKJUNqMvNXT5eaar62q6ZMckLdzQ6LCTKSgo8bBXvQ//WewwJWiwm71YTN8teezIDdasZhN9Mi00luphOTyYTH6yc92Y7fZ+D2+LDbLHRunUaK00Gy005akg2LKZjEMZnAYQtuIyPFQU6GE6vFRLLTis1qwmI2keiwYLWaSU60YTKZQstbSXXaOPLgHI7onEOr7GSSEqwYhoE/YJDgsNR7DQxfLz3+ACZMtM1NJiXRhjPBRk66k0MOysCZYCUQMMjJSCQxwYbXH8BmsZCd7qRZmpOMZActs5No3SyZ5AQb/kAAv9+ItHvKXB6SnXZaZCViwoTTbuWwjtl0b5eF2WwiKcHKQTkpGAaUV3kpLHWRmmijdSipk+y0c1jHbPoekovDZmFjQQXN0hKC7SKvv87PV1c54Pb6cdgspCbaSE8JPo2RnuSg7yG5JCfY8PoCJCfY6Nsll/QkB/BX+8vl9tVZdhSUunB5gm26Q9pkkJOeiAG0zEqkdU5y5DNFWwbVtb2c9MRacYTbrXWVccUVHvx+o1ab1mo10yYnmZREO4Wlrh2O166219hl5p6Uz9G0xRsab0GpC5fbR3Za8LsePH8GLbKSan0n92YdojGOSVOr78Ssx47H66Os0ku7FilYrbUv9FarmZbZiazNK8NsMtEiO4mCYlcw+xxKuJjNJjJTHWwuqAx2nTSbMIxw/j34vFuVy0fL7EQqqrz4/cHukhVV3mAmuCr4A8xIdmAYBhWVXpyhL2ZWagJVLh9llR6aZySSnZaAyRTc7rqNm/bZMRJpqA15ebEOodGF70L37NwNgJ5tOtKt1Ms7P31Lr5NPjXF0e9/+eE4lfkT7/fP7A1RUeWuV02Hh8nrLtir8/kDMn0HfH+1wnQz9/cWPXwNN5zri9nhZsmpr5N/bigtjGM2BywQYgWBiw2IOji8U5rRbKa3yYjaZMEwGNosJb+j5rACQkWKjuPyvZ9jMpr8eZ7KYwWYx4/fW/bCcw2alotqDxfRXrxkI/u3xB7BaTPj8Bv7AXz13AiZTaNweP2aLCfyhB5BMYDICWCw2MJuwEkz8eHwB/AE/mAy8PoPMZAuZqU62FLlw2ILjBdltFvyBQOhzGSQl2PEHDJqlOSmu8JBkteDz/dVvqKTCHXxsyB5cP9FuxmIxYxgGFouZ7LQEyio9+PwBEh02Kiq9+DP/utZtfw2EYHskKzWBTQUVOB0W0pPtbNlWRaLDSsvsJMoqPThsZqqqAZMJp81MlTt4nJLMJppnJlJYWk1FpZfmmYmRdk2iw0K5y4PH66OiykuzDCdbi6pw2i2RmIPnLZjdykpxUFntpaismtJKD+1bpOJ0WFn2ZzGts5Mxm02YzSaaZzpZvr6Eg1vbsFktta7nkTZZYSUY0LJZUqQc8PsDlFV4sFjM5GYmUFbhARO0zE4KPhIX2n440RY+TkaGQXZaAhVV3lB7LFBrnJ6yCg9ms4mstATMZlOtMgio0Y4LrrerMqiu7UW+32YT2WkJlFd6KK3w0KpZ8g5lnM/vxx8wSLRbCTUXa8XjdFj5M68cj9eH3WbFbDaRlmxnc2Fl5BjX1Nhl5p6Uz+F1m2U4d9oW37Ktipx0J/klrqji9fsDlFV6MJuCx7au81dZ7aWsIrrzF6tj0hTrOzFL7Li9AQwMkp22Ot9PdtoIBILPkYbHvnFs16XJYbPgN4JdLC1mE76AgSW0iC8QfJYx2WmjvMqLLxAePSf4vKqZUIFmCQ4I5jeCz2UGn2M1YbGY8AeCgyo7bBa8XjcAtz/15N45ICKNyFW9f9wZ37otn0UrlnLb5TfWev3krW7+m7aGrdvyyc3KiVF0e1f4HI4YNSrGkYhAVT0D/obL3O3L6TCHzYIRWs5yAD+NVfM4NtZ1emfXyVOP7sczb48Fmv51xO1xxzqEA0rNR51MtdslBAwThhEcWDj4KFDt9xNsFoIjEAVZzeAJPV0YHqOmpnCCxkRwvBcAiwUM/19j3hhAIGAE6/I1xiIBMAwDm9VCtdsXzOYQ7OHjM8BkDo2XYwSXCzeyfP6/PqTNZsYUGo3GbAp+NrM59PiVEdyk3Wqm2hNKHIWCCt7QDcbi8wcXDg7wa2AJtRfC1zOHzULorWD7wTB2uNbVvAZGzoEJAqH2B5gifyc7bRSXuzGbTaEknIHJbAoOWGsYmCGyjD+UXDKHthduv7hD4wpZzcF/22x/xRw8B6FjGRrDx+P1EwgE22XhT16zUZrgsERuoNd1PXfYLJHzW7McCLexLGZTJObw2Dq+QPCzmENdwcJtrvC2HTZLrfZYzTZeeJvhfW1fBm2/3q7KoLq2V5PDZomcK+t2DXkItmlNoe9aePvbx2MQPCf2ULPXGnp8cGcN/8YsM/ekfA6vu6u2eLhtHW28vkCwZ5vFsovzZ679O2rsOkRjHJOmWN+JWWLHYTNjwkSFK9jNansVLi9mswlrKPFigki3vzC314/FZMJnBAuLmj82a+hiWOHyBgcDC71nIphpCxC8dvv9AaxmKxaTCZcvgMkUvOj5/QZ2mxmr2URFtQ+bLRjj0/+6i7atW+29AyOyBzbk5TFi1CicCc5Yh9IocrNy6Nm5G9/9/AOnHdMv8vq0XAc92nTYb5M6QOQcjr7nHtq0aBHjaORAFb6mJDp3fU0Jl7nbl9Nhbq+/Vll8oKp5HBvrOr2z6+R3P/9A57YdWbFudZO5jrg9XmYvrd1jZ9Lk13HYd6wHyt5jombipPZ7ZpOByQSBgAmTyag1uDBAtbf2GFG+Gp1zag5QXPO18P8tkV4ctZczERpLJtTTp+ZVwmQKjjFjYPqrN4QRTOgYgb+SMyaTiUAoWKvlr414vQGCc/gEG+YmEwT8wV5C4aSQxxdMggTCG4ZIzxYTwUfBMEyhz27C7wvgt5j/msnJ6w8eJxP4/QYWu2mHa93210BT6KCYTabQIMxG5O8KlxeLOfh5DIK9WgKhz2EymQgQbN/4Awb20AxCgdD2/P5wgiI48KwvlDBzVQfbONbIOTBC8QaCiR9rsOdNhcuL02HFhCnSuwig2u2PJLvqup67vf7g+TVqlwNWswmLyYTHH/pcoZGr3V4/yQk2AgTHPcIg0uYKb7ui2lerPRZWc5vhfdUsg8Kfr+Z6uyqD6tre9ucufK582/8gCLZpjdB3Lbz9mvEE26LBcxIWbNvWPsa7+r7siT0pn8Pr7qotHm5bRxuv1WwKJRN3cf5C3+1ozt/uaIxj0hTrOzFL7NhtVlKTbGwurCI3PbHW41g+X4DNhVWkJdlJT3FQWuEhKcFGUVlwgCVz6GJXVOYmOclGdYk/mM2ucZvAYjGT6LSyubCKFpmJkYxocqKN4go3RihTWFzhJi3ZQXKSjYLSasxmE9vKqgkYBqlJdkwmE4Wl1ZELfNvWreh00EH79mCJHMAGnX0hd41+iEUrltKzczcWbVjN0jQbo445Ldah7RNtWrTQNUeaPIslOAZFzXI6LFJeJ9r0GNZessN1MjTmzoghN7Bi/AtN6jpS5k4kv6Q61mEc0AyCvSQCgdqPYQG4PD5sVjNetx8r4K3RkDUDJeW1pxILGH/1yvFHWul1c3uD41VuP/OW2QR2i5nK6mCjzmL+K2FkNgyq3P7gI1/+v3q7mA0wTMHp1wkY+DDw+o3Q2DgWMHzYrCYqPX6KylxYTCbc3gAWM1R6/5rRCUxUVntxOmwUlLqwmMHj8+MPBDCbgter9GQHAcNgW5kbixlc3gBWayCSTAq3E6yWYM+fFtmJta51dV0DkxNtlLu8pCbbKSn3UFLhITXJRnGFh00FFeRkJJJf4grmmQwDlzcQOU6BgMGmgsrgeECpjlrtmmpvgJZOO3ableREW6QNVVBSjcViirSVAoaBETDYVu4mEDDIzggmmjcXVpKe4iA1yUZJpYe0ZAeBgMGWIhfJTmtoxidvrc8S/nypScHxc2qWAxZLcGr7rUVVbC6sDD6+YjJRVOYmyWHDCBgEAsEEYnig3PB4RoWlf7XHah7P8Dbzi11sK60mxWmPlEHbSqvxG0at9eorg+raXrgMi5xfIC3ZTmmFh/QkR60yzmqxBJNnHn8kYRmOp6DERVG5m9QkW2Tq80DAoDR0vsPHeG+WmXtSPofX3VVbPNFppaTSE3W8FouZ1KTg8S7c7vwFf0vBuFLTojt/sTomTbG+E9NZsdq3SGXxmiIWrCqkZXZirVmxfP4A7VukR2bF8vkDVHt8rNpcUmsk7gS7FafDCobBuq3lZKY6IiNTV7v9+PwBXB4fpZVuHDZLaPCvSgKBAE6Hja3FLkorPaEuogG2lVVTXO4mIzl492j5+mLKXR4cdWTkRGTvC48VER5D4p2fvqVbqZeebTrGOjQRqaFZmpN1W8t3KIuLytz4/AFaZSfFOsT91vbXyfD/u7TrFOvQdnDIQRnklzSNMX8OZOGEzvaJnYrqv17YfqKsnaVsai62qznfam67ViwGFFcGE0bB3gF/vef2b7+Hv2Lx+AKYgbwiV/ChKSN447ikwoPFasKClUqXjxUbS7FuNytWeF9ubwDDgGqPG4spOM6n2+sL9iCxBJNKPl9wBinDMPD4AqGeNAbzVuZHZsUyERwrxmIO9m4Jtzt2dg0MXy/tFjMGBuu2VpBgM+Oq9lJe5aEo9MiS2WIiv7iK8CNQXr+fypLgEBMJdgtefyA0TThYzcGeI+F2T6rTzp9lwVmxDAxcHh8LVxdisQQb5VVuHyWVHjJTHKQk2jCbTPy+rpgKl5eDcpKpcHlYuLoQl9tHwIC2ucm1ZsWq9vjq/HzblwPh41Dl9pNg95CZ6qCk0k3etkp8gQA2q5mKai+//rE1MitWuP2VluSgWdqOvRubpTkpr/RQUFpNtdcfHA8V2LytCq/PT0boM5VWuqMqg+raHgR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      "text/plain": [
       "<Figure size 1152x384 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# box plots\n",
    "ds_box = ds.sel({\"x\": XLON, \"y\": YLAT}, method=\"nearest\").sel(\n",
    "    time=slice(\"1981\", \"2005\")\n",
    ")\n",
    "\n",
    "ds_df = pd.DataFrame({\"time\": ds_box[\"time\"]})\n",
    "for var in ds_box.data_vars:\n",
    "    ds_df[var] = ds_box[var]\n",
    "ds_df.set_index(\"time\", inplace=True)\n",
    "\n",
    "fig, axs = plt.subplots(2, 2, figsize=(12, 4))\n",
    "for ax, var in zip(axs.flat, ds_box.data_vars):\n",
    "    ds_df.plot.box(\n",
    "        column=var,\n",
    "        vert=False,\n",
    "        showmeans=True,\n",
    "        ax=ax,\n",
    "        patch_artist=True,\n",
    "        color={\n",
    "            \"medians\": \"Crimson\",\n",
    "            \"whiskers\": \"DarkSlateGrey\",\n",
    "            \"caps\": \"DarkSlateGrey\",\n",
    "        },\n",
    "        boxprops={\"facecolor\": \"Lavender\", \"color\": \"DarkSlateGrey\"},\n",
    "        meanprops={\n",
    "            \"markeredgecolor\": \"DarkSlateGrey\",\n",
    "            \"marker\": \"d\",\n",
    "            \"markerfacecolor\": (1, 1, 0, 0),  # transparent\n",
    "        },\n",
    "        flierprops={\n",
    "            \"alpha\": 0.5,\n",
    "            \"markeredgecolor\": \"LightSteelBlue\",\n",
    "            \"zorder\": 1,\n",
    "        },\n",
    "    )\n",
    "    ax.set_title(\n",
    "        f\"{ds_box[var].attrs['long_name']} [{ds_box[var].attrs['units']}]\"\n",
    "    )\n",
    "    ax.set(yticklabels=[])\n",
    "plt.tight_layout()\n",
    "plt.show()"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Extend data to spin-up year"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [],
   "source": [
    "# copy 1981 data to 1980\n",
    "ds_interp = ds.interp(\n",
    "    time=pd.date_range(\"1980-01-01\", \"1980-12-31\", freq=\"D\"),\n",
    "    kwargs={\"fill_value\": None},\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
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       "}\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-index-preview {\n",
       "  grid-column: 2 / 5;\n",
       "  color: var(--xr-font-color2);\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",
       ".xr-index-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",
       ".xr-index-data-in:checked ~ .xr-index-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-index-name div,\n",
       ".xr-index-data,\n",
       ".xr-attrs {\n",
       "  padding-left: 25px !important;\n",
       "}\n",
       "\n",
       ".xr-attrs,\n",
       ".xr-var-attrs,\n",
       ".xr-var-data,\n",
       ".xr-index-data {\n",
       "  grid-column: 1 / -1;\n",
       "}\n",
       "\n",
       "dl.xr-attrs {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  display: grid;\n",
       "  grid-template-columns: 125px auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt,\n",
       ".xr-attrs dd {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  float: left;\n",
       "  padding-right: 10px;\n",
       "  width: auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt {\n",
       "  font-weight: normal;\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-attrs dt:hover span {\n",
       "  display: inline-block;\n",
       "  background: var(--xr-background-color);\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-attrs dd {\n",
       "  grid-column: 2;\n",
       "  white-space: pre-wrap;\n",
       "  word-break: break-all;\n",
       "}\n",
       "\n",
       ".xr-icon-database,\n",
       ".xr-icon-file-text2,\n",
       ".xr-no-icon {\n",
       "  display: inline-block;\n",
       "  vertical-align: middle;\n",
       "  width: 1em;\n",
       "  height: 1.5em !important;\n",
       "  stroke-width: 0;\n",
       "  stroke: currentColor;\n",
       "  fill: currentColor;\n",
       "}\n",
       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt;\n",
       "Dimensions:            (x: 158, y: 166, time: 366)\n",
       "Coordinates:\n",
       "  * x                  (x) float64 4.15e+05 4.175e+05 ... 8.05e+05 8.075e+05\n",
       "  * y                  (y) float64 4.075e+05 4.1e+05 ... 8.175e+05 8.2e+05\n",
       "    height             float64 0.0\n",
       "    Lambert_Conformal  int64 ...\n",
       "  * time               (time) datetime64[ns] 1980-01-01 ... 1980-12-31\n",
       "    spatial_ref        int64 0\n",
       "Data variables:\n",
       "    PAR                (time, y, x) float32 dask.array&lt;chunksize=(366, 85, 81), meta=np.ndarray&gt;\n",
       "    PET                (time, y, x) float32 dask.array&lt;chunksize=(366, 86, 82), meta=np.ndarray&gt;\n",
       "    T                  (time, y, x) float32 dask.array&lt;chunksize=(366, 85, 81), meta=np.ndarray&gt;\n",
       "    PP                 (time, y, x) float32 dask.array&lt;chunksize=(366, 85, 81), meta=np.ndarray&gt;\n",
       "Attributes:\n",
       "    CDI:          Climate Data Interface version 2.0.5 (https://mpimet.mpg.de...\n",
       "    Conventions:  CF-1.6\n",
       "    CDO:          Climate Data Operators version 2.0.5 (https://mpimet.mpg.de...\n",
       "    dataset:      IE_MERA_FC3hr_3_day</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-d89d418b-7eeb-4f76-9a3c-6c33dc9bc69b' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-d89d418b-7eeb-4f76-9a3c-6c33dc9bc69b' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>x</span>: 158</li><li><span class='xr-has-index'>y</span>: 166</li><li><span class='xr-has-index'>time</span>: 366</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-b4b6811b-fae0-4c78-8683-bd7305ae80db' class='xr-section-summary-in' type='checkbox'  checked><label for='section-b4b6811b-fae0-4c78-8683-bd7305ae80db' class='xr-section-summary' >Coordinates: <span>(6)</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'>x</span></div><div class='xr-var-dims'>(x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>4.15e+05 4.175e+05 ... 8.075e+05</div><input id='attrs-5a9ca744-393f-4f44-81c0-71c41b6003e2' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-5a9ca744-393f-4f44-81c0-71c41b6003e2' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c407ff0b-175c-478c-9829-203f3425baaa' class='xr-var-data-in' type='checkbox'><label for='data-c407ff0b-175c-478c-9829-203f3425baaa' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>projection_x_coordinate</dd><dt><span>units :</span></dt><dd>metre</dd><dt><span>axis :</span></dt><dd>X</dd><dt><span>long_name :</span></dt><dd>x coordinate of projection</dd></dl></div><div class='xr-var-data'><pre>array([415000., 417500., 420000., 422500., 425000., 427500., 430000., 432500.,\n",
       "       435000., 437500., 440000., 442500., 445000., 447500., 450000., 452500.,\n",
       "       455000., 457500., 460000., 462500., 465000., 467500., 470000., 472500.,\n",
       "       475000., 477500., 480000., 482500., 485000., 487500., 490000., 492500.,\n",
       "       495000., 497500., 500000., 502500., 505000., 507500., 510000., 512500.,\n",
       "       515000., 517500., 520000., 522500., 525000., 527500., 530000., 532500.,\n",
       "       535000., 537500., 540000., 542500., 545000., 547500., 550000., 552500.,\n",
       "       555000., 557500., 560000., 562500., 565000., 567500., 570000., 572500.,\n",
       "       575000., 577500., 580000., 582500., 585000., 587500., 590000., 592500.,\n",
       "       595000., 597500., 600000., 602500., 605000., 607500., 610000., 612500.,\n",
       "       615000., 617500., 620000., 622500., 625000., 627500., 630000., 632500.,\n",
       "       635000., 637500., 640000., 642500., 645000., 647500., 650000., 652500.,\n",
       "       655000., 657500., 660000., 662500., 665000., 667500., 670000., 672500.,\n",
       "       675000., 677500., 680000., 682500., 685000., 687500., 690000., 692500.,\n",
       "       695000., 697500., 700000., 702500., 705000., 707500., 710000., 712500.,\n",
       "       715000., 717500., 720000., 722500., 725000., 727500., 730000., 732500.,\n",
       "       735000., 737500., 740000., 742500., 745000., 747500., 750000., 752500.,\n",
       "       755000., 757500., 760000., 762500., 765000., 767500., 770000., 772500.,\n",
       "       775000., 777500., 780000., 782500., 785000., 787500., 790000., 792500.,\n",
       "       795000., 797500., 800000., 802500., 805000., 807500.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>y</span></div><div class='xr-var-dims'>(y)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>4.075e+05 4.1e+05 ... 8.2e+05</div><input id='attrs-8c94b73f-9ffc-4f95-9bfa-c10064df4e07' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-8c94b73f-9ffc-4f95-9bfa-c10064df4e07' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5aa77f0d-159e-4abc-b6e1-9eb776c370bc' class='xr-var-data-in' type='checkbox'><label for='data-5aa77f0d-159e-4abc-b6e1-9eb776c370bc' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>projection_y_coordinate</dd><dt><span>units :</span></dt><dd>metre</dd><dt><span>axis :</span></dt><dd>Y</dd><dt><span>long_name :</span></dt><dd>y coordinate of projection</dd></dl></div><div class='xr-var-data'><pre>array([407500., 410000., 412500., 415000., 417500., 420000., 422500., 425000.,\n",
       "       427500., 430000., 432500., 435000., 437500., 440000., 442500., 445000.,\n",
       "       447500., 450000., 452500., 455000., 457500., 460000., 462500., 465000.,\n",
       "       467500., 470000., 472500., 475000., 477500., 480000., 482500., 485000.,\n",
       "       487500., 490000., 492500., 495000., 497500., 500000., 502500., 505000.,\n",
       "       507500., 510000., 512500., 515000., 517500., 520000., 522500., 525000.,\n",
       "       527500., 530000., 532500., 535000., 537500., 540000., 542500., 545000.,\n",
       "       547500., 550000., 552500., 555000., 557500., 560000., 562500., 565000.,\n",
       "       567500., 570000., 572500., 575000., 577500., 580000., 582500., 585000.,\n",
       "       587500., 590000., 592500., 595000., 597500., 600000., 602500., 605000.,\n",
       "       607500., 610000., 612500., 615000., 617500., 620000., 622500., 625000.,\n",
       "       627500., 630000., 632500., 635000., 637500., 640000., 642500., 645000.,\n",
       "       647500., 650000., 652500., 655000., 657500., 660000., 662500., 665000.,\n",
       "       667500., 670000., 672500., 675000., 677500., 680000., 682500., 685000.,\n",
       "       687500., 690000., 692500., 695000., 697500., 700000., 702500., 705000.,\n",
       "       707500., 710000., 712500., 715000., 717500., 720000., 722500., 725000.,\n",
       "       727500., 730000., 732500., 735000., 737500., 740000., 742500., 745000.,\n",
       "       747500., 750000., 752500., 755000., 757500., 760000., 762500., 765000.,\n",
       "       767500., 770000., 772500., 775000., 777500., 780000., 782500., 785000.,\n",
       "       787500., 790000., 792500., 795000., 797500., 800000., 802500., 805000.,\n",
       "       807500., 810000., 812500., 815000., 817500., 820000.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>height</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0</div><input id='attrs-9fd62e20-f0bb-431c-9f85-c2b0c5d51791' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-9fd62e20-f0bb-431c-9f85-c2b0c5d51791' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-56896a05-84c1-447c-abde-81586c420ddb' class='xr-var-data-in' type='checkbox'><label for='data-56896a05-84c1-447c-abde-81586c420ddb' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>height</dd><dt><span>long_name :</span></dt><dd>height</dd><dt><span>units :</span></dt><dd>m</dd><dt><span>positive :</span></dt><dd>up</dd><dt><span>axis :</span></dt><dd>Z</dd></dl></div><div class='xr-var-data'><pre>array(0.)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Lambert_Conformal</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-ef57e3cc-ca94-4a6d-be12-8c296c236d82' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ef57e3cc-ca94-4a6d-be12-8c296c236d82' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-bd678fdf-9def-4ce4-96c7-be4e605cd5dc' class='xr-var-data-in' type='checkbox'><label for='data-bd678fdf-9def-4ce4-96c7-be4e605cd5dc' 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>crs_wkt :</span></dt><dd>PROJCS[&quot;undefined&quot;,GEOGCS[&quot;undefined&quot;,DATUM[&quot;undefined&quot;,SPHEROID[&quot;undefined&quot;,6367470,0]],PRIMEM[&quot;Greenwich&quot;,0,AUTHORITY[&quot;EPSG&quot;,&quot;8901&quot;]],UNIT[&quot;degree&quot;,0.0174532925199433]],PROJECTION[&quot;Lambert_Conformal_Conic_1SP&quot;],PARAMETER[&quot;latitude_of_origin&quot;,53.5],PARAMETER[&quot;central_meridian&quot;,5],PARAMETER[&quot;scale_factor&quot;,1],PARAMETER[&quot;false_easting&quot;,1481641.67696368],PARAMETER[&quot;false_northing&quot;,537326.063885016],UNIT[&quot;metre&quot;,1,AUTHORITY[&quot;EPSG&quot;,&quot;9001&quot;]],AXIS[&quot;Easting&quot;,EAST],AXIS[&quot;Northing&quot;,NORTH]]</dd><dt><span>semi_major_axis :</span></dt><dd>6367470.0</dd><dt><span>semi_minor_axis :</span></dt><dd>6367470.0</dd><dt><span>inverse_flattening :</span></dt><dd>0.0</dd><dt><span>reference_ellipsoid_name :</span></dt><dd>undefined</dd><dt><span>longitude_of_prime_meridian :</span></dt><dd>0.0</dd><dt><span>prime_meridian_name :</span></dt><dd>Greenwich</dd><dt><span>geographic_crs_name :</span></dt><dd>undefined</dd><dt><span>horizontal_datum_name :</span></dt><dd>undefined</dd><dt><span>projected_crs_name :</span></dt><dd>undefined</dd><dt><span>grid_mapping_name :</span></dt><dd>lambert_conformal_conic</dd><dt><span>standard_parallel :</span></dt><dd>53.5</dd><dt><span>longitude_of_central_meridian :</span></dt><dd>5.0</dd><dt><span>false_easting :</span></dt><dd>1481641.67696368</dd><dt><span>false_northing :</span></dt><dd>537326.063885016</dd><dt><span>spatial_ref :</span></dt><dd>PROJCS[&quot;undefined&quot;,GEOGCS[&quot;undefined&quot;,DATUM[&quot;undefined&quot;,SPHEROID[&quot;undefined&quot;,6367470,0]],PRIMEM[&quot;Greenwich&quot;,0,AUTHORITY[&quot;EPSG&quot;,&quot;8901&quot;]],UNIT[&quot;degree&quot;,0.0174532925199433]],PROJECTION[&quot;Lambert_Conformal_Conic_1SP&quot;],PARAMETER[&quot;latitude_of_origin&quot;,53.5],PARAMETER[&quot;central_meridian&quot;,5],PARAMETER[&quot;scale_factor&quot;,1],PARAMETER[&quot;false_easting&quot;,1481641.67696368],PARAMETER[&quot;false_northing&quot;,537326.063885016],UNIT[&quot;metre&quot;,1,AUTHORITY[&quot;EPSG&quot;,&quot;9001&quot;]],AXIS[&quot;Easting&quot;,EAST],AXIS[&quot;Northing&quot;,NORTH]]</dd><dt><span>GeoTransform :</span></dt><dd>413750.0 2500.0 0.0 406250.0 0.0 2500.0</dd></dl></div><div class='xr-var-data'><pre>[1 values with dtype=int64]</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'>1980-01-01 ... 1980-12-31</div><input id='attrs-211e3946-56e3-4550-9b88-539ddd221f02' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-211e3946-56e3-4550-9b88-539ddd221f02' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f3313946-e6ff-4c39-952c-081571fd00ee' class='xr-var-data-in' type='checkbox'><label for='data-f3313946-e6ff-4c39-952c-081571fd00ee' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>time</dd><dt><span>axis :</span></dt><dd>T</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;1980-01-01T00:00:00.000000000&#x27;, &#x27;1980-01-02T00:00:00.000000000&#x27;,\n",
       "       &#x27;1980-01-03T00:00:00.000000000&#x27;, ..., &#x27;1980-12-29T00:00:00.000000000&#x27;,\n",
       "       &#x27;1980-12-30T00:00:00.000000000&#x27;, &#x27;1980-12-31T00:00:00.000000000&#x27;],\n",
       "      dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>spatial_ref</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>0</div><input id='attrs-b15c0940-396d-483a-bf55-0275450f1550' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b15c0940-396d-483a-bf55-0275450f1550' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5ecd2b58-8257-452c-9f04-4d058989e770' class='xr-var-data-in' type='checkbox'><label for='data-5ecd2b58-8257-452c-9f04-4d058989e770' 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>crs_wkt :</span></dt><dd>PROJCS[&quot;undefined&quot;,GEOGCS[&quot;undefined&quot;,DATUM[&quot;undefined&quot;,SPHEROID[&quot;undefined&quot;,6367470,0]],PRIMEM[&quot;Greenwich&quot;,0,AUTHORITY[&quot;EPSG&quot;,&quot;8901&quot;]],UNIT[&quot;degree&quot;,0.0174532925199433]],PROJECTION[&quot;Lambert_Conformal_Conic_1SP&quot;],PARAMETER[&quot;latitude_of_origin&quot;,53.5],PARAMETER[&quot;central_meridian&quot;,5],PARAMETER[&quot;scale_factor&quot;,1],PARAMETER[&quot;false_easting&quot;,1481641.67696368],PARAMETER[&quot;false_northing&quot;,537326.063885016],UNIT[&quot;metre&quot;,1,AUTHORITY[&quot;EPSG&quot;,&quot;9001&quot;]],AXIS[&quot;Easting&quot;,EAST],AXIS[&quot;Northing&quot;,NORTH]]</dd><dt><span>semi_major_axis :</span></dt><dd>6367470.0</dd><dt><span>semi_minor_axis :</span></dt><dd>6367470.0</dd><dt><span>inverse_flattening :</span></dt><dd>0.0</dd><dt><span>reference_ellipsoid_name :</span></dt><dd>undefined</dd><dt><span>longitude_of_prime_meridian :</span></dt><dd>0.0</dd><dt><span>prime_meridian_name :</span></dt><dd>Greenwich</dd><dt><span>geographic_crs_name :</span></dt><dd>undefined</dd><dt><span>horizontal_datum_name :</span></dt><dd>undefined</dd><dt><span>projected_crs_name :</span></dt><dd>undefined</dd><dt><span>grid_mapping_name :</span></dt><dd>lambert_conformal_conic</dd><dt><span>standard_parallel :</span></dt><dd>53.5</dd><dt><span>longitude_of_central_meridian :</span></dt><dd>5.0</dd><dt><span>false_easting :</span></dt><dd>1481641.67696368</dd><dt><span>false_northing :</span></dt><dd>537326.063885016</dd><dt><span>spatial_ref :</span></dt><dd>PROJCS[&quot;undefined&quot;,GEOGCS[&quot;undefined&quot;,DATUM[&quot;undefined&quot;,SPHEROID[&quot;undefined&quot;,6367470,0]],PRIMEM[&quot;Greenwich&quot;,0,AUTHORITY[&quot;EPSG&quot;,&quot;8901&quot;]],UNIT[&quot;degree&quot;,0.0174532925199433]],PROJECTION[&quot;Lambert_Conformal_Conic_1SP&quot;],PARAMETER[&quot;latitude_of_origin&quot;,53.5],PARAMETER[&quot;central_meridian&quot;,5],PARAMETER[&quot;scale_factor&quot;,1],PARAMETER[&quot;false_easting&quot;,1481641.67696368],PARAMETER[&quot;false_northing&quot;,537326.063885016],UNIT[&quot;metre&quot;,1,AUTHORITY[&quot;EPSG&quot;,&quot;9001&quot;]],AXIS[&quot;Easting&quot;,EAST],AXIS[&quot;Northing&quot;,NORTH]]</dd><dt><span>GeoTransform :</span></dt><dd>413750.0 2500.0 0.0 406250.0 0.0 2500.0</dd></dl></div><div class='xr-var-data'><pre>array(0)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-dce7ecb0-c0a5-4d70-a487-706b718ee641' class='xr-section-summary-in' type='checkbox'  checked><label for='section-dce7ecb0-c0a5-4d70-a487-706b718ee641' class='xr-section-summary' >Data variables: <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>PAR</span></div><div class='xr-var-dims'>(time, y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(366, 85, 81), meta=np.ndarray&gt;</div><input id='attrs-86a193ef-7ee5-4b61-acec-4a3a0f2814f1' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-86a193ef-7ee5-4b61-acec-4a3a0f2814f1' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b7b01f0a-00ae-4544-9132-81e3dfc80914' class='xr-var-data-in' type='checkbox'><label for='data-b7b01f0a-00ae-4544-9132-81e3dfc80914' 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>Surface Photosynthetically Active Radiation</dd><dt><span>units :</span></dt><dd>MJ m⁻² day⁻¹</dd></dl></div><div class='xr-var-data'><table>\n",
       "    <tr>\n",
       "        <td>\n",
       "            <table style=\"border-collapse: collapse;\">\n",
       "                <thead>\n",
       "                    <tr>\n",
       "                        <td> </td>\n",
       "                        <th> Array </th>\n",
       "                        <th> Chunk </th>\n",
       "                    </tr>\n",
       "                </thead>\n",
       "                <tbody>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 36.62 MiB </td>\n",
       "                        <td> 9.61 MiB </td>\n",
       "                    </tr>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> (366, 166, 158) </td>\n",
       "                        <td> (366, 85, 81) </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Dask graph </th>\n",
       "                        <td colspan=\"2\"> 4 chunks in 12 graph layers </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Data type </th>\n",
       "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
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       "                </tbody>\n",
       "            </table>\n",
       "        </td>\n",
       "        <td>\n",
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       "    </tr>\n",
       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>PET</span></div><div class='xr-var-dims'>(time, y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(366, 86, 82), meta=np.ndarray&gt;</div><input id='attrs-3175914d-c513-4471-a11f-640591429137' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3175914d-c513-4471-a11f-640591429137' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c1999e66-7b5e-433d-b6ec-ef2cc736f5ba' class='xr-var-data-in' type='checkbox'><label for='data-c1999e66-7b5e-433d-b6ec-ef2cc736f5ba' 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>mm day⁻¹</dd><dt><span>long_name :</span></dt><dd>Reference evapotranspiration</dd></dl></div><div class='xr-var-data'><table>\n",
       "    <tr>\n",
       "        <td>\n",
       "            <table style=\"border-collapse: collapse;\">\n",
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       "                    <tr>\n",
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       "                </thead>\n",
       "                <tbody>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 36.62 MiB </td>\n",
       "                        <td> 9.85 MiB </td>\n",
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       "                    <tr>\n",
       "                        <th> Shape </th>\n",
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       "                        <td> (366, 86, 82) </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Dask graph </th>\n",
       "                        <td colspan=\"2\"> 4 chunks in 10 graph layers </td>\n",
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       "                    <tr>\n",
       "                        <th> Data type </th>\n",
       "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
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       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>T</span></div><div class='xr-var-dims'>(time, y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(366, 85, 81), meta=np.ndarray&gt;</div><input id='attrs-964a7bea-7a73-4c55-ae4a-cfef8cfc87bc' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-964a7bea-7a73-4c55-ae4a-cfef8cfc87bc' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-54972508-7ab1-47c0-8459-3a4bba6c5a92' class='xr-var-data-in' type='checkbox'><label for='data-54972508-7ab1-47c0-8459-3a4bba6c5a92' 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>GRIB_paramId :</span></dt><dd>233253011</dd><dt><span>GRIB_numberOfPoints :</span></dt><dd>258681</dd><dt><span>GRIB_typeOfLevel :</span></dt><dd>heightAboveGround</dd><dt><span>GRIB_stepUnits :</span></dt><dd>1</dd><dt><span>GRIB_stepType :</span></dt><dd>instant</dd><dt><span>GRIB_gridType :</span></dt><dd>lambert</dd><dt><span>GRIB_DxInMetres :</span></dt><dd>2500</dd><dt><span>GRIB_DyInMetres :</span></dt><dd>2500</dd><dt><span>GRIB_LaDInDegrees :</span></dt><dd>53.5</dd><dt><span>GRIB_Latin1InDegrees :</span></dt><dd>53.5</dd><dt><span>GRIB_Latin2InDegrees :</span></dt><dd>53.5</dd><dt><span>GRIB_LoVInDegrees :</span></dt><dd>5.0</dd><dt><span>GRIB_NV :</span></dt><dd>132</dd><dt><span>GRIB_Nx :</span></dt><dd>529</dd><dt><span>GRIB_Ny :</span></dt><dd>489</dd><dt><span>GRIB_cfName :</span></dt><dd>unknown</dd><dt><span>GRIB_cfVarName :</span></dt><dd>unknown</dd><dt><span>GRIB_gridDefinitionDescription :</span></dt><dd>Lambert Conformal</dd><dt><span>GRIB_iScansNegatively :</span></dt><dd>0</dd><dt><span>GRIB_jPointsAreConsecutive :</span></dt><dd>0</dd><dt><span>GRIB_jScansPositively :</span></dt><dd>1</dd><dt><span>GRIB_latitudeOfFirstGridPointInDegrees :</span></dt><dd>46.834</dd><dt><span>GRIB_latitudeOfSouthernPoleInDegrees :</span></dt><dd>0.0</dd><dt><span>GRIB_longitudeOfFirstGridPointInDegrees :</span></dt><dd>-14.609</dd><dt><span>GRIB_longitudeOfSouthernPoleInDegrees :</span></dt><dd>0.0</dd><dt><span>GRIB_missingValue :</span></dt><dd>3.4028234663852886e+38</dd><dt><span>GRIB_name :</span></dt><dd>Temperature</dd><dt><span>GRIB_shortName :</span></dt><dd>t</dd><dt><span>GRIB_units :</span></dt><dd>K</dd><dt><span>long_name :</span></dt><dd>Temperature</dd><dt><span>units :</span></dt><dd>°C</dd><dt><span>standard_name :</span></dt><dd>unknown</dd></dl></div><div class='xr-var-data'><table>\n",
       "    <tr>\n",
       "        <td>\n",
       "            <table style=\"border-collapse: collapse;\">\n",
       "                <thead>\n",
       "                    <tr>\n",
       "                        <td> </td>\n",
       "                        <th> Array </th>\n",
       "                        <th> Chunk </th>\n",
       "                    </tr>\n",
       "                </thead>\n",
       "                <tbody>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 36.62 MiB </td>\n",
       "                        <td> 9.61 MiB </td>\n",
       "                    </tr>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> (366, 166, 158) </td>\n",
       "                        <td> (366, 85, 81) </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Dask graph </th>\n",
       "                        <td colspan=\"2\"> 4 chunks in 11 graph layers </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Data type </th>\n",
       "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
       "                    </tr>\n",
       "                </tbody>\n",
       "            </table>\n",
       "        </td>\n",
       "        <td>\n",
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       "</svg>\n",
       "        </td>\n",
       "    </tr>\n",
       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>PP</span></div><div class='xr-var-dims'>(time, y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(366, 85, 81), meta=np.ndarray&gt;</div><input id='attrs-ec0245b5-8fd6-455e-8a3c-44a8592ae035' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ec0245b5-8fd6-455e-8a3c-44a8592ae035' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-53c7c484-1f35-406f-b8d9-8da9937e1a36' class='xr-var-data-in' type='checkbox'><label for='data-53c7c484-1f35-406f-b8d9-8da9937e1a36' 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>GRIB_paramId :</span></dt><dd>233253061</dd><dt><span>GRIB_numberOfPoints :</span></dt><dd>258681</dd><dt><span>GRIB_typeOfLevel :</span></dt><dd>heightAboveGround</dd><dt><span>GRIB_stepUnits :</span></dt><dd>1</dd><dt><span>GRIB_stepType :</span></dt><dd>accum</dd><dt><span>GRIB_gridType :</span></dt><dd>lambert</dd><dt><span>GRIB_DxInMetres :</span></dt><dd>2500</dd><dt><span>GRIB_DyInMetres :</span></dt><dd>2500</dd><dt><span>GRIB_LaDInDegrees :</span></dt><dd>53.5</dd><dt><span>GRIB_Latin1InDegrees :</span></dt><dd>53.5</dd><dt><span>GRIB_Latin2InDegrees :</span></dt><dd>53.5</dd><dt><span>GRIB_LoVInDegrees :</span></dt><dd>5.0</dd><dt><span>GRIB_NV :</span></dt><dd>132</dd><dt><span>GRIB_Nx :</span></dt><dd>529</dd><dt><span>GRIB_Ny :</span></dt><dd>489</dd><dt><span>GRIB_cfName :</span></dt><dd>unknown</dd><dt><span>GRIB_cfVarName :</span></dt><dd>unknown</dd><dt><span>GRIB_gridDefinitionDescription :</span></dt><dd>Lambert Conformal</dd><dt><span>GRIB_iScansNegatively :</span></dt><dd>0</dd><dt><span>GRIB_jPointsAreConsecutive :</span></dt><dd>0</dd><dt><span>GRIB_jScansPositively :</span></dt><dd>1</dd><dt><span>GRIB_latitudeOfFirstGridPointInDegrees :</span></dt><dd>46.834</dd><dt><span>GRIB_latitudeOfSouthernPoleInDegrees :</span></dt><dd>0.0</dd><dt><span>GRIB_longitudeOfFirstGridPointInDegrees :</span></dt><dd>-14.609</dd><dt><span>GRIB_longitudeOfSouthernPoleInDegrees :</span></dt><dd>0.0</dd><dt><span>GRIB_missingValue :</span></dt><dd>3.4028234663852886e+38</dd><dt><span>GRIB_name :</span></dt><dd>Total precipitation</dd><dt><span>GRIB_shortName :</span></dt><dd>tp</dd><dt><span>GRIB_units :</span></dt><dd>kg m**-2</dd><dt><span>long_name :</span></dt><dd>Total precipitation</dd><dt><span>units :</span></dt><dd>mm day⁻¹</dd><dt><span>standard_name :</span></dt><dd>unknown</dd></dl></div><div class='xr-var-data'><table>\n",
       "    <tr>\n",
       "        <td>\n",
       "            <table style=\"border-collapse: collapse;\">\n",
       "                <thead>\n",
       "                    <tr>\n",
       "                        <td> </td>\n",
       "                        <th> Array </th>\n",
       "                        <th> Chunk </th>\n",
       "                    </tr>\n",
       "                </thead>\n",
       "                <tbody>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 36.62 MiB </td>\n",
       "                        <td> 9.61 MiB </td>\n",
       "                    </tr>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> (366, 166, 158) </td>\n",
       "                        <td> (366, 85, 81) </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Dask graph </th>\n",
       "                        <td colspan=\"2\"> 4 chunks in 11 graph layers </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Data type </th>\n",
       "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
       "                    </tr>\n",
       "                </tbody>\n",
       "            </table>\n",
       "        </td>\n",
       "        <td>\n",
       "        <svg width=\"182\" height=\"175\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
       "\n",
       "  <!-- Horizontal lines -->\n",
       "  <line x1=\"10\" y1=\"0\" x2=\"80\" y2=\"70\" style=\"stroke-width:2\" />\n",
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       "\n",
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       "\n",
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       "  <text x=\"106.489875\" y=\"145.014465\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >158</text>\n",
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       "</svg>\n",
       "        </td>\n",
       "    </tr>\n",
       "</table></div></li></ul></div></li><li class='xr-section-item'><input id='section-4e7831d1-c4a6-4cc1-9d25-0d78d64a71ee' class='xr-section-summary-in' type='checkbox'  ><label for='section-4e7831d1-c4a6-4cc1-9d25-0d78d64a71ee' class='xr-section-summary' >Indexes: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>x</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-be3bbdea-b1d8-45a2-8647-ef50cd593fe9' class='xr-index-data-in' type='checkbox'/><label for='index-be3bbdea-b1d8-45a2-8647-ef50cd593fe9' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Float64Index([415000.0, 417500.0, 420000.0, 422500.0, 425000.0, 427500.0,\n",
       "              430000.0, 432500.0, 435000.0, 437500.0,\n",
       "              ...\n",
       "              785000.0, 787500.0, 790000.0, 792500.0, 795000.0, 797500.0,\n",
       "              800000.0, 802500.0, 805000.0, 807500.0],\n",
       "             dtype=&#x27;float64&#x27;, name=&#x27;x&#x27;, length=158))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>y</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-3df79230-3923-4bdd-8a8e-01e1815bd2c0' class='xr-index-data-in' type='checkbox'/><label for='index-3df79230-3923-4bdd-8a8e-01e1815bd2c0' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Float64Index([407500.0, 410000.0, 412500.0, 415000.0, 417500.0, 420000.0,\n",
       "              422500.0, 425000.0, 427500.0, 430000.0,\n",
       "              ...\n",
       "              797500.0, 800000.0, 802500.0, 805000.0, 807500.0, 810000.0,\n",
       "              812500.0, 815000.0, 817500.0, 820000.0],\n",
       "             dtype=&#x27;float64&#x27;, name=&#x27;y&#x27;, length=166))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>time</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-42bc75ec-0aa8-4edd-a89d-381c10d5e96c' class='xr-index-data-in' type='checkbox'/><label for='index-42bc75ec-0aa8-4edd-a89d-381c10d5e96c' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(DatetimeIndex([&#x27;1980-01-01&#x27;, &#x27;1980-01-02&#x27;, &#x27;1980-01-03&#x27;, &#x27;1980-01-04&#x27;,\n",
       "               &#x27;1980-01-05&#x27;, &#x27;1980-01-06&#x27;, &#x27;1980-01-07&#x27;, &#x27;1980-01-08&#x27;,\n",
       "               &#x27;1980-01-09&#x27;, &#x27;1980-01-10&#x27;,\n",
       "               ...\n",
       "               &#x27;1980-12-22&#x27;, &#x27;1980-12-23&#x27;, &#x27;1980-12-24&#x27;, &#x27;1980-12-25&#x27;,\n",
       "               &#x27;1980-12-26&#x27;, &#x27;1980-12-27&#x27;, &#x27;1980-12-28&#x27;, &#x27;1980-12-29&#x27;,\n",
       "               &#x27;1980-12-30&#x27;, &#x27;1980-12-31&#x27;],\n",
       "              dtype=&#x27;datetime64[ns]&#x27;, name=&#x27;time&#x27;, length=366, freq=None))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-b28e484b-ddc2-4b18-a887-ba55464ac6cb' class='xr-section-summary-in' type='checkbox'  checked><label for='section-b28e484b-ddc2-4b18-a887-ba55464ac6cb' class='xr-section-summary' >Attributes: <span>(4)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>CDI :</span></dt><dd>Climate Data Interface version 2.0.5 (https://mpimet.mpg.de/cdi)</dd><dt><span>Conventions :</span></dt><dd>CF-1.6</dd><dt><span>CDO :</span></dt><dd>Climate Data Operators version 2.0.5 (https://mpimet.mpg.de/cdo)</dd><dt><span>dataset :</span></dt><dd>IE_MERA_FC3hr_3_day</dd></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.Dataset>\n",
       "Dimensions:            (x: 158, y: 166, time: 366)\n",
       "Coordinates:\n",
       "  * x                  (x) float64 4.15e+05 4.175e+05 ... 8.05e+05 8.075e+05\n",
       "  * y                  (y) float64 4.075e+05 4.1e+05 ... 8.175e+05 8.2e+05\n",
       "    height             float64 0.0\n",
       "    Lambert_Conformal  int64 ...\n",
       "  * time               (time) datetime64[ns] 1980-01-01 ... 1980-12-31\n",
       "    spatial_ref        int64 0\n",
       "Data variables:\n",
       "    PAR                (time, y, x) float32 dask.array<chunksize=(366, 85, 81), meta=np.ndarray>\n",
       "    PET                (time, y, x) float32 dask.array<chunksize=(366, 86, 82), meta=np.ndarray>\n",
       "    T                  (time, y, x) float32 dask.array<chunksize=(366, 85, 81), meta=np.ndarray>\n",
       "    PP                 (time, y, x) float32 dask.array<chunksize=(366, 85, 81), meta=np.ndarray>\n",
       "Attributes:\n",
       "    CDI:          Climate Data Interface version 2.0.5 (https://mpimet.mpg.de...\n",
       "    Conventions:  CF-1.6\n",
       "    CDO:          Climate Data Operators version 2.0.5 (https://mpimet.mpg.de...\n",
       "    dataset:      IE_MERA_FC3hr_3_day"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ds_interp.rio.write_crs(data_crs, inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [],
   "source": [
    "# merge spin-up year with first two years of the main data\n",
    "ds_interp = xr.combine_by_coords(\n",
    "    [ds_interp, ds.sel(time=slice(\"1981\", \"1982\"))]\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
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       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt;\n",
       "Dimensions:            (x: 158, y: 166, time: 1096)\n",
       "Coordinates:\n",
       "  * x                  (x) float64 4.15e+05 4.175e+05 ... 8.05e+05 8.075e+05\n",
       "  * y                  (y) float64 4.075e+05 4.1e+05 ... 8.175e+05 8.2e+05\n",
       "    height             float64 0.0\n",
       "    Lambert_Conformal  int64 0\n",
       "  * time               (time) datetime64[ns] 1980-01-01 ... 1982-12-31\n",
       "    spatial_ref        int64 0\n",
       "Data variables:\n",
       "    PAR                (time, y, x) float32 dask.array&lt;chunksize=(366, 85, 81), meta=np.ndarray&gt;\n",
       "    PET                (time, y, x) float32 dask.array&lt;chunksize=(366, 86, 82), meta=np.ndarray&gt;\n",
       "    T                  (time, y, x) float32 dask.array&lt;chunksize=(366, 85, 81), meta=np.ndarray&gt;\n",
       "    PP                 (time, y, x) float32 dask.array&lt;chunksize=(366, 85, 81), meta=np.ndarray&gt;\n",
       "Attributes:\n",
       "    CDI:          Climate Data Interface version 2.0.5 (https://mpimet.mpg.de...\n",
       "    Conventions:  CF-1.6\n",
       "    CDO:          Climate Data Operators version 2.0.5 (https://mpimet.mpg.de...\n",
       "    dataset:      IE_MERA_FC3hr_3_day</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-f2369ff2-7d70-4dfd-8ca0-367d0b460f1c' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-f2369ff2-7d70-4dfd-8ca0-367d0b460f1c' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>x</span>: 158</li><li><span class='xr-has-index'>y</span>: 166</li><li><span class='xr-has-index'>time</span>: 1096</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-d763d2c5-d693-44a5-95b9-70bb408439af' class='xr-section-summary-in' type='checkbox'  checked><label for='section-d763d2c5-d693-44a5-95b9-70bb408439af' class='xr-section-summary' >Coordinates: <span>(6)</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'>x</span></div><div class='xr-var-dims'>(x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>4.15e+05 4.175e+05 ... 8.075e+05</div><input id='attrs-2133b980-5d09-4e16-aed9-7d72a3f2fc2f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-2133b980-5d09-4e16-aed9-7d72a3f2fc2f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3e471f53-2c00-4997-a83c-43d674ca434b' class='xr-var-data-in' type='checkbox'><label for='data-3e471f53-2c00-4997-a83c-43d674ca434b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>projection_x_coordinate</dd><dt><span>units :</span></dt><dd>metre</dd><dt><span>axis :</span></dt><dd>X</dd><dt><span>long_name :</span></dt><dd>x coordinate of projection</dd></dl></div><div class='xr-var-data'><pre>array([415000., 417500., 420000., 422500., 425000., 427500., 430000., 432500.,\n",
       "       435000., 437500., 440000., 442500., 445000., 447500., 450000., 452500.,\n",
       "       455000., 457500., 460000., 462500., 465000., 467500., 470000., 472500.,\n",
       "       475000., 477500., 480000., 482500., 485000., 487500., 490000., 492500.,\n",
       "       495000., 497500., 500000., 502500., 505000., 507500., 510000., 512500.,\n",
       "       515000., 517500., 520000., 522500., 525000., 527500., 530000., 532500.,\n",
       "       535000., 537500., 540000., 542500., 545000., 547500., 550000., 552500.,\n",
       "       555000., 557500., 560000., 562500., 565000., 567500., 570000., 572500.,\n",
       "       575000., 577500., 580000., 582500., 585000., 587500., 590000., 592500.,\n",
       "       595000., 597500., 600000., 602500., 605000., 607500., 610000., 612500.,\n",
       "       615000., 617500., 620000., 622500., 625000., 627500., 630000., 632500.,\n",
       "       635000., 637500., 640000., 642500., 645000., 647500., 650000., 652500.,\n",
       "       655000., 657500., 660000., 662500., 665000., 667500., 670000., 672500.,\n",
       "       675000., 677500., 680000., 682500., 685000., 687500., 690000., 692500.,\n",
       "       695000., 697500., 700000., 702500., 705000., 707500., 710000., 712500.,\n",
       "       715000., 717500., 720000., 722500., 725000., 727500., 730000., 732500.,\n",
       "       735000., 737500., 740000., 742500., 745000., 747500., 750000., 752500.,\n",
       "       755000., 757500., 760000., 762500., 765000., 767500., 770000., 772500.,\n",
       "       775000., 777500., 780000., 782500., 785000., 787500., 790000., 792500.,\n",
       "       795000., 797500., 800000., 802500., 805000., 807500.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>y</span></div><div class='xr-var-dims'>(y)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>4.075e+05 4.1e+05 ... 8.2e+05</div><input id='attrs-569c0721-45d1-48ac-a149-5eaeced78318' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-569c0721-45d1-48ac-a149-5eaeced78318' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-285c1c2b-ccf2-4f46-9f61-956761e4467f' class='xr-var-data-in' type='checkbox'><label for='data-285c1c2b-ccf2-4f46-9f61-956761e4467f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>projection_y_coordinate</dd><dt><span>units :</span></dt><dd>metre</dd><dt><span>axis :</span></dt><dd>Y</dd><dt><span>long_name :</span></dt><dd>y coordinate of projection</dd></dl></div><div class='xr-var-data'><pre>array([407500., 410000., 412500., 415000., 417500., 420000., 422500., 425000.,\n",
       "       427500., 430000., 432500., 435000., 437500., 440000., 442500., 445000.,\n",
       "       447500., 450000., 452500., 455000., 457500., 460000., 462500., 465000.,\n",
       "       467500., 470000., 472500., 475000., 477500., 480000., 482500., 485000.,\n",
       "       487500., 490000., 492500., 495000., 497500., 500000., 502500., 505000.,\n",
       "       507500., 510000., 512500., 515000., 517500., 520000., 522500., 525000.,\n",
       "       527500., 530000., 532500., 535000., 537500., 540000., 542500., 545000.,\n",
       "       547500., 550000., 552500., 555000., 557500., 560000., 562500., 565000.,\n",
       "       567500., 570000., 572500., 575000., 577500., 580000., 582500., 585000.,\n",
       "       587500., 590000., 592500., 595000., 597500., 600000., 602500., 605000.,\n",
       "       607500., 610000., 612500., 615000., 617500., 620000., 622500., 625000.,\n",
       "       627500., 630000., 632500., 635000., 637500., 640000., 642500., 645000.,\n",
       "       647500., 650000., 652500., 655000., 657500., 660000., 662500., 665000.,\n",
       "       667500., 670000., 672500., 675000., 677500., 680000., 682500., 685000.,\n",
       "       687500., 690000., 692500., 695000., 697500., 700000., 702500., 705000.,\n",
       "       707500., 710000., 712500., 715000., 717500., 720000., 722500., 725000.,\n",
       "       727500., 730000., 732500., 735000., 737500., 740000., 742500., 745000.,\n",
       "       747500., 750000., 752500., 755000., 757500., 760000., 762500., 765000.,\n",
       "       767500., 770000., 772500., 775000., 777500., 780000., 782500., 785000.,\n",
       "       787500., 790000., 792500., 795000., 797500., 800000., 802500., 805000.,\n",
       "       807500., 810000., 812500., 815000., 817500., 820000.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>height</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0</div><input id='attrs-2ba65662-860a-45bc-bdb9-3eb0e45b5c73' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-2ba65662-860a-45bc-bdb9-3eb0e45b5c73' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-fe413a19-3a21-4ee4-ae86-72997679d8d6' class='xr-var-data-in' type='checkbox'><label for='data-fe413a19-3a21-4ee4-ae86-72997679d8d6' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>height</dd><dt><span>long_name :</span></dt><dd>height</dd><dt><span>units :</span></dt><dd>m</dd><dt><span>positive :</span></dt><dd>up</dd><dt><span>axis :</span></dt><dd>Z</dd></dl></div><div class='xr-var-data'><pre>array(0.)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Lambert_Conformal</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>0</div><input id='attrs-1a600853-5006-412e-bacc-764bc41e0c83' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-1a600853-5006-412e-bacc-764bc41e0c83' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9bb67d0f-8471-4c06-8f4b-72944b8ec98e' class='xr-var-data-in' type='checkbox'><label for='data-9bb67d0f-8471-4c06-8f4b-72944b8ec98e' 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>crs_wkt :</span></dt><dd>PROJCS[&quot;undefined&quot;,GEOGCS[&quot;undefined&quot;,DATUM[&quot;undefined&quot;,SPHEROID[&quot;undefined&quot;,6367470,0]],PRIMEM[&quot;Greenwich&quot;,0,AUTHORITY[&quot;EPSG&quot;,&quot;8901&quot;]],UNIT[&quot;degree&quot;,0.0174532925199433]],PROJECTION[&quot;Lambert_Conformal_Conic_1SP&quot;],PARAMETER[&quot;latitude_of_origin&quot;,53.5],PARAMETER[&quot;central_meridian&quot;,5],PARAMETER[&quot;scale_factor&quot;,1],PARAMETER[&quot;false_easting&quot;,1481641.67696368],PARAMETER[&quot;false_northing&quot;,537326.063885016],UNIT[&quot;metre&quot;,1,AUTHORITY[&quot;EPSG&quot;,&quot;9001&quot;]],AXIS[&quot;Easting&quot;,EAST],AXIS[&quot;Northing&quot;,NORTH]]</dd><dt><span>semi_major_axis :</span></dt><dd>6367470.0</dd><dt><span>semi_minor_axis :</span></dt><dd>6367470.0</dd><dt><span>inverse_flattening :</span></dt><dd>0.0</dd><dt><span>reference_ellipsoid_name :</span></dt><dd>undefined</dd><dt><span>longitude_of_prime_meridian :</span></dt><dd>0.0</dd><dt><span>prime_meridian_name :</span></dt><dd>Greenwich</dd><dt><span>geographic_crs_name :</span></dt><dd>undefined</dd><dt><span>horizontal_datum_name :</span></dt><dd>undefined</dd><dt><span>projected_crs_name :</span></dt><dd>undefined</dd><dt><span>grid_mapping_name :</span></dt><dd>lambert_conformal_conic</dd><dt><span>standard_parallel :</span></dt><dd>53.5</dd><dt><span>longitude_of_central_meridian :</span></dt><dd>5.0</dd><dt><span>false_easting :</span></dt><dd>1481641.67696368</dd><dt><span>false_northing :</span></dt><dd>537326.063885016</dd><dt><span>spatial_ref :</span></dt><dd>PROJCS[&quot;undefined&quot;,GEOGCS[&quot;undefined&quot;,DATUM[&quot;undefined&quot;,SPHEROID[&quot;undefined&quot;,6367470,0]],PRIMEM[&quot;Greenwich&quot;,0,AUTHORITY[&quot;EPSG&quot;,&quot;8901&quot;]],UNIT[&quot;degree&quot;,0.0174532925199433]],PROJECTION[&quot;Lambert_Conformal_Conic_1SP&quot;],PARAMETER[&quot;latitude_of_origin&quot;,53.5],PARAMETER[&quot;central_meridian&quot;,5],PARAMETER[&quot;scale_factor&quot;,1],PARAMETER[&quot;false_easting&quot;,1481641.67696368],PARAMETER[&quot;false_northing&quot;,537326.063885016],UNIT[&quot;metre&quot;,1,AUTHORITY[&quot;EPSG&quot;,&quot;9001&quot;]],AXIS[&quot;Easting&quot;,EAST],AXIS[&quot;Northing&quot;,NORTH]]</dd><dt><span>GeoTransform :</span></dt><dd>413750.0 2500.0 0.0 406250.0 0.0 2500.0</dd></dl></div><div class='xr-var-data'><pre>array(0)</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'>1980-01-01 ... 1982-12-31</div><input id='attrs-65561734-7af3-4121-a85e-faa62dc4f48d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-65561734-7af3-4121-a85e-faa62dc4f48d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2e468847-5d92-4230-8206-25ce924da00e' class='xr-var-data-in' type='checkbox'><label for='data-2e468847-5d92-4230-8206-25ce924da00e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>time</dd><dt><span>axis :</span></dt><dd>T</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;1980-01-01T00:00:00.000000000&#x27;, &#x27;1980-01-02T00:00:00.000000000&#x27;,\n",
       "       &#x27;1980-01-03T00:00:00.000000000&#x27;, ..., &#x27;1982-12-29T00:00:00.000000000&#x27;,\n",
       "       &#x27;1982-12-30T00:00:00.000000000&#x27;, &#x27;1982-12-31T00:00:00.000000000&#x27;],\n",
       "      dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>spatial_ref</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>0</div><input id='attrs-09811453-c4c8-4bc5-8c1b-947c8d54abb6' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-09811453-c4c8-4bc5-8c1b-947c8d54abb6' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-50c6cfb6-e399-4406-81f3-e0e66c76a134' class='xr-var-data-in' type='checkbox'><label for='data-50c6cfb6-e399-4406-81f3-e0e66c76a134' 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>crs_wkt :</span></dt><dd>PROJCS[&quot;undefined&quot;,GEOGCS[&quot;undefined&quot;,DATUM[&quot;undefined&quot;,SPHEROID[&quot;undefined&quot;,6367470,0]],PRIMEM[&quot;Greenwich&quot;,0,AUTHORITY[&quot;EPSG&quot;,&quot;8901&quot;]],UNIT[&quot;degree&quot;,0.0174532925199433]],PROJECTION[&quot;Lambert_Conformal_Conic_1SP&quot;],PARAMETER[&quot;latitude_of_origin&quot;,53.5],PARAMETER[&quot;central_meridian&quot;,5],PARAMETER[&quot;scale_factor&quot;,1],PARAMETER[&quot;false_easting&quot;,1481641.67696368],PARAMETER[&quot;false_northing&quot;,537326.063885016],UNIT[&quot;metre&quot;,1,AUTHORITY[&quot;EPSG&quot;,&quot;9001&quot;]],AXIS[&quot;Easting&quot;,EAST],AXIS[&quot;Northing&quot;,NORTH]]</dd><dt><span>semi_major_axis :</span></dt><dd>6367470.0</dd><dt><span>semi_minor_axis :</span></dt><dd>6367470.0</dd><dt><span>inverse_flattening :</span></dt><dd>0.0</dd><dt><span>reference_ellipsoid_name :</span></dt><dd>undefined</dd><dt><span>longitude_of_prime_meridian :</span></dt><dd>0.0</dd><dt><span>prime_meridian_name :</span></dt><dd>Greenwich</dd><dt><span>geographic_crs_name :</span></dt><dd>undefined</dd><dt><span>horizontal_datum_name :</span></dt><dd>undefined</dd><dt><span>projected_crs_name :</span></dt><dd>undefined</dd><dt><span>grid_mapping_name :</span></dt><dd>lambert_conformal_conic</dd><dt><span>standard_parallel :</span></dt><dd>53.5</dd><dt><span>longitude_of_central_meridian :</span></dt><dd>5.0</dd><dt><span>false_easting :</span></dt><dd>1481641.67696368</dd><dt><span>false_northing :</span></dt><dd>537326.063885016</dd><dt><span>spatial_ref :</span></dt><dd>PROJCS[&quot;undefined&quot;,GEOGCS[&quot;undefined&quot;,DATUM[&quot;undefined&quot;,SPHEROID[&quot;undefined&quot;,6367470,0]],PRIMEM[&quot;Greenwich&quot;,0,AUTHORITY[&quot;EPSG&quot;,&quot;8901&quot;]],UNIT[&quot;degree&quot;,0.0174532925199433]],PROJECTION[&quot;Lambert_Conformal_Conic_1SP&quot;],PARAMETER[&quot;latitude_of_origin&quot;,53.5],PARAMETER[&quot;central_meridian&quot;,5],PARAMETER[&quot;scale_factor&quot;,1],PARAMETER[&quot;false_easting&quot;,1481641.67696368],PARAMETER[&quot;false_northing&quot;,537326.063885016],UNIT[&quot;metre&quot;,1,AUTHORITY[&quot;EPSG&quot;,&quot;9001&quot;]],AXIS[&quot;Easting&quot;,EAST],AXIS[&quot;Northing&quot;,NORTH]]</dd><dt><span>GeoTransform :</span></dt><dd>413750.0 2500.0 0.0 406250.0 0.0 2500.0</dd></dl></div><div class='xr-var-data'><pre>array(0)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-d8755417-cd90-4517-912d-f5dbaca9f335' class='xr-section-summary-in' type='checkbox'  checked><label for='section-d8755417-cd90-4517-912d-f5dbaca9f335' class='xr-section-summary' >Data variables: <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>PAR</span></div><div class='xr-var-dims'>(time, y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(366, 85, 81), meta=np.ndarray&gt;</div><input id='attrs-83ac84ea-493c-428b-83b7-7cedfd480311' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-83ac84ea-493c-428b-83b7-7cedfd480311' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-bde9308b-8ba8-459d-8cce-5e5a6b2035ee' class='xr-var-data-in' type='checkbox'><label for='data-bde9308b-8ba8-459d-8cce-5e5a6b2035ee' 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>Surface Photosynthetically Active Radiation</dd><dt><span>units :</span></dt><dd>MJ m⁻² day⁻¹</dd></dl></div><div class='xr-var-data'><table>\n",
       "    <tr>\n",
       "        <td>\n",
       "            <table style=\"border-collapse: collapse;\">\n",
       "                <thead>\n",
       "                    <tr>\n",
       "                        <td> </td>\n",
       "                        <th> Array </th>\n",
       "                        <th> Chunk </th>\n",
       "                    </tr>\n",
       "                </thead>\n",
       "                <tbody>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 109.66 MiB </td>\n",
       "                        <td> 19.17 MiB </td>\n",
       "                    </tr>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> (1096, 166, 158) </td>\n",
       "                        <td> (730, 85, 81) </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Dask graph </th>\n",
       "                        <td colspan=\"2\"> 8 chunks in 14 graph layers </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Data type </th>\n",
       "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
       "                    </tr>\n",
       "                </tbody>\n",
       "            </table>\n",
       "        </td>\n",
       "        <td>\n",
       "        <svg width=\"171\" height=\"161\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
       "\n",
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       "  <text x=\"35.294118\" y=\"96.047155\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(45,35.294118,96.047155)\">1096</text>\n",
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       "        </td>\n",
       "    </tr>\n",
       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>PET</span></div><div class='xr-var-dims'>(time, y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(366, 86, 82), meta=np.ndarray&gt;</div><input id='attrs-f2e24884-849e-4a67-a0fd-e3fbc97184c2' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f2e24884-849e-4a67-a0fd-e3fbc97184c2' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-91510a74-ebe9-4a65-ae34-adb1b257589b' class='xr-var-data-in' type='checkbox'><label for='data-91510a74-ebe9-4a65-ae34-adb1b257589b' 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>mm day⁻¹</dd><dt><span>long_name :</span></dt><dd>Reference evapotranspiration</dd></dl></div><div class='xr-var-data'><table>\n",
       "    <tr>\n",
       "        <td>\n",
       "            <table style=\"border-collapse: collapse;\">\n",
       "                <thead>\n",
       "                    <tr>\n",
       "                        <td> </td>\n",
       "                        <th> Array </th>\n",
       "                        <th> Chunk </th>\n",
       "                    </tr>\n",
       "                </thead>\n",
       "                <tbody>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 109.66 MiB </td>\n",
       "                        <td> 19.64 MiB </td>\n",
       "                    </tr>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> (1096, 166, 158) </td>\n",
       "                        <td> (730, 86, 82) </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Dask graph </th>\n",
       "                        <td colspan=\"2\"> 8 chunks in 12 graph layers </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Data type </th>\n",
       "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
       "                    </tr>\n",
       "                </tbody>\n",
       "            </table>\n",
       "        </td>\n",
       "        <td>\n",
       "        <svg width=\"171\" height=\"161\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
       "\n",
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       "</svg>\n",
       "        </td>\n",
       "    </tr>\n",
       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>T</span></div><div class='xr-var-dims'>(time, y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(366, 85, 81), meta=np.ndarray&gt;</div><input id='attrs-14a8401f-b980-4952-9d20-cf0c06443243' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-14a8401f-b980-4952-9d20-cf0c06443243' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-787160e5-74b8-4c48-a564-1161b52be27b' class='xr-var-data-in' type='checkbox'><label for='data-787160e5-74b8-4c48-a564-1161b52be27b' 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>GRIB_paramId :</span></dt><dd>233253011</dd><dt><span>GRIB_numberOfPoints :</span></dt><dd>258681</dd><dt><span>GRIB_typeOfLevel :</span></dt><dd>heightAboveGround</dd><dt><span>GRIB_stepUnits :</span></dt><dd>1</dd><dt><span>GRIB_stepType :</span></dt><dd>instant</dd><dt><span>GRIB_gridType :</span></dt><dd>lambert</dd><dt><span>GRIB_DxInMetres :</span></dt><dd>2500</dd><dt><span>GRIB_DyInMetres :</span></dt><dd>2500</dd><dt><span>GRIB_LaDInDegrees :</span></dt><dd>53.5</dd><dt><span>GRIB_Latin1InDegrees :</span></dt><dd>53.5</dd><dt><span>GRIB_Latin2InDegrees :</span></dt><dd>53.5</dd><dt><span>GRIB_LoVInDegrees :</span></dt><dd>5.0</dd><dt><span>GRIB_NV :</span></dt><dd>132</dd><dt><span>GRIB_Nx :</span></dt><dd>529</dd><dt><span>GRIB_Ny :</span></dt><dd>489</dd><dt><span>GRIB_cfName :</span></dt><dd>unknown</dd><dt><span>GRIB_cfVarName :</span></dt><dd>unknown</dd><dt><span>GRIB_gridDefinitionDescription :</span></dt><dd>Lambert Conformal</dd><dt><span>GRIB_iScansNegatively :</span></dt><dd>0</dd><dt><span>GRIB_jPointsAreConsecutive :</span></dt><dd>0</dd><dt><span>GRIB_jScansPositively :</span></dt><dd>1</dd><dt><span>GRIB_latitudeOfFirstGridPointInDegrees :</span></dt><dd>46.834</dd><dt><span>GRIB_latitudeOfSouthernPoleInDegrees :</span></dt><dd>0.0</dd><dt><span>GRIB_longitudeOfFirstGridPointInDegrees :</span></dt><dd>-14.609</dd><dt><span>GRIB_longitudeOfSouthernPoleInDegrees :</span></dt><dd>0.0</dd><dt><span>GRIB_missingValue :</span></dt><dd>3.4028234663852886e+38</dd><dt><span>GRIB_name :</span></dt><dd>Temperature</dd><dt><span>GRIB_shortName :</span></dt><dd>t</dd><dt><span>GRIB_units :</span></dt><dd>K</dd><dt><span>long_name :</span></dt><dd>Temperature</dd><dt><span>units :</span></dt><dd>°C</dd><dt><span>standard_name :</span></dt><dd>unknown</dd></dl></div><div class='xr-var-data'><table>\n",
       "    <tr>\n",
       "        <td>\n",
       "            <table style=\"border-collapse: collapse;\">\n",
       "                <thead>\n",
       "                    <tr>\n",
       "                        <td> </td>\n",
       "                        <th> Array </th>\n",
       "                        <th> Chunk </th>\n",
       "                    </tr>\n",
       "                </thead>\n",
       "                <tbody>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 109.66 MiB </td>\n",
       "                        <td> 19.17 MiB </td>\n",
       "                    </tr>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> (1096, 166, 158) </td>\n",
       "                        <td> (730, 85, 81) </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Dask graph </th>\n",
       "                        <td colspan=\"2\"> 8 chunks in 13 graph layers </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Data type </th>\n",
       "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
       "                    </tr>\n",
       "                </tbody>\n",
       "            </table>\n",
       "        </td>\n",
       "        <td>\n",
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       "        </td>\n",
       "    </tr>\n",
       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>PP</span></div><div class='xr-var-dims'>(time, y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(366, 85, 81), meta=np.ndarray&gt;</div><input id='attrs-f9a06725-139c-448e-bbf6-9f0013592383' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f9a06725-139c-448e-bbf6-9f0013592383' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-fcd35e0a-04ff-4279-87d3-57f6408f0f8c' class='xr-var-data-in' type='checkbox'><label for='data-fcd35e0a-04ff-4279-87d3-57f6408f0f8c' 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>GRIB_paramId :</span></dt><dd>233253061</dd><dt><span>GRIB_numberOfPoints :</span></dt><dd>258681</dd><dt><span>GRIB_typeOfLevel :</span></dt><dd>heightAboveGround</dd><dt><span>GRIB_stepUnits :</span></dt><dd>1</dd><dt><span>GRIB_stepType :</span></dt><dd>accum</dd><dt><span>GRIB_gridType :</span></dt><dd>lambert</dd><dt><span>GRIB_DxInMetres :</span></dt><dd>2500</dd><dt><span>GRIB_DyInMetres :</span></dt><dd>2500</dd><dt><span>GRIB_LaDInDegrees :</span></dt><dd>53.5</dd><dt><span>GRIB_Latin1InDegrees :</span></dt><dd>53.5</dd><dt><span>GRIB_Latin2InDegrees :</span></dt><dd>53.5</dd><dt><span>GRIB_LoVInDegrees :</span></dt><dd>5.0</dd><dt><span>GRIB_NV :</span></dt><dd>132</dd><dt><span>GRIB_Nx :</span></dt><dd>529</dd><dt><span>GRIB_Ny :</span></dt><dd>489</dd><dt><span>GRIB_cfName :</span></dt><dd>unknown</dd><dt><span>GRIB_cfVarName :</span></dt><dd>unknown</dd><dt><span>GRIB_gridDefinitionDescription :</span></dt><dd>Lambert Conformal</dd><dt><span>GRIB_iScansNegatively :</span></dt><dd>0</dd><dt><span>GRIB_jPointsAreConsecutive :</span></dt><dd>0</dd><dt><span>GRIB_jScansPositively :</span></dt><dd>1</dd><dt><span>GRIB_latitudeOfFirstGridPointInDegrees :</span></dt><dd>46.834</dd><dt><span>GRIB_latitudeOfSouthernPoleInDegrees :</span></dt><dd>0.0</dd><dt><span>GRIB_longitudeOfFirstGridPointInDegrees :</span></dt><dd>-14.609</dd><dt><span>GRIB_longitudeOfSouthernPoleInDegrees :</span></dt><dd>0.0</dd><dt><span>GRIB_missingValue :</span></dt><dd>3.4028234663852886e+38</dd><dt><span>GRIB_name :</span></dt><dd>Total precipitation</dd><dt><span>GRIB_shortName :</span></dt><dd>tp</dd><dt><span>GRIB_units :</span></dt><dd>kg m**-2</dd><dt><span>long_name :</span></dt><dd>Total precipitation</dd><dt><span>units :</span></dt><dd>mm day⁻¹</dd><dt><span>standard_name :</span></dt><dd>unknown</dd></dl></div><div class='xr-var-data'><table>\n",
       "    <tr>\n",
       "        <td>\n",
       "            <table style=\"border-collapse: collapse;\">\n",
       "                <thead>\n",
       "                    <tr>\n",
       "                        <td> </td>\n",
       "                        <th> Array </th>\n",
       "                        <th> Chunk </th>\n",
       "                    </tr>\n",
       "                </thead>\n",
       "                <tbody>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 109.66 MiB </td>\n",
       "                        <td> 19.17 MiB </td>\n",
       "                    </tr>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> (1096, 166, 158) </td>\n",
       "                        <td> (730, 85, 81) </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Dask graph </th>\n",
       "                        <td colspan=\"2\"> 8 chunks in 13 graph layers </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Data type </th>\n",
       "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
       "                    </tr>\n",
       "                </tbody>\n",
       "            </table>\n",
       "        </td>\n",
       "        <td>\n",
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       "</svg>\n",
       "        </td>\n",
       "    </tr>\n",
       "</table></div></li></ul></div></li><li class='xr-section-item'><input id='section-eb8189ee-71d4-4fea-aba4-215dba48857e' class='xr-section-summary-in' type='checkbox'  ><label for='section-eb8189ee-71d4-4fea-aba4-215dba48857e' class='xr-section-summary' >Indexes: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>x</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-14708b6b-8cb8-4fa5-8d28-8d78efff3060' class='xr-index-data-in' type='checkbox'/><label for='index-14708b6b-8cb8-4fa5-8d28-8d78efff3060' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Float64Index([415000.0, 417500.0, 420000.0, 422500.0, 425000.0, 427500.0,\n",
       "              430000.0, 432500.0, 435000.0, 437500.0,\n",
       "              ...\n",
       "              785000.0, 787500.0, 790000.0, 792500.0, 795000.0, 797500.0,\n",
       "              800000.0, 802500.0, 805000.0, 807500.0],\n",
       "             dtype=&#x27;float64&#x27;, name=&#x27;x&#x27;, length=158))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>y</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-8f271866-8bdf-4dda-af7e-c1889c1d9a7d' class='xr-index-data-in' type='checkbox'/><label for='index-8f271866-8bdf-4dda-af7e-c1889c1d9a7d' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Float64Index([407500.0, 410000.0, 412500.0, 415000.0, 417500.0, 420000.0,\n",
       "              422500.0, 425000.0, 427500.0, 430000.0,\n",
       "              ...\n",
       "              797500.0, 800000.0, 802500.0, 805000.0, 807500.0, 810000.0,\n",
       "              812500.0, 815000.0, 817500.0, 820000.0],\n",
       "             dtype=&#x27;float64&#x27;, name=&#x27;y&#x27;, length=166))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>time</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-c8907f8a-7b36-4428-a240-03c099498bad' class='xr-index-data-in' type='checkbox'/><label for='index-c8907f8a-7b36-4428-a240-03c099498bad' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(DatetimeIndex([&#x27;1980-01-01&#x27;, &#x27;1980-01-02&#x27;, &#x27;1980-01-03&#x27;, &#x27;1980-01-04&#x27;,\n",
       "               &#x27;1980-01-05&#x27;, &#x27;1980-01-06&#x27;, &#x27;1980-01-07&#x27;, &#x27;1980-01-08&#x27;,\n",
       "               &#x27;1980-01-09&#x27;, &#x27;1980-01-10&#x27;,\n",
       "               ...\n",
       "               &#x27;1982-12-22&#x27;, &#x27;1982-12-23&#x27;, &#x27;1982-12-24&#x27;, &#x27;1982-12-25&#x27;,\n",
       "               &#x27;1982-12-26&#x27;, &#x27;1982-12-27&#x27;, &#x27;1982-12-28&#x27;, &#x27;1982-12-29&#x27;,\n",
       "               &#x27;1982-12-30&#x27;, &#x27;1982-12-31&#x27;],\n",
       "              dtype=&#x27;datetime64[ns]&#x27;, name=&#x27;time&#x27;, length=1096, freq=None))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-ac3478ca-15c7-44ce-8b2c-bd7d0f0e3a45' class='xr-section-summary-in' type='checkbox'  checked><label for='section-ac3478ca-15c7-44ce-8b2c-bd7d0f0e3a45' class='xr-section-summary' >Attributes: <span>(4)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>CDI :</span></dt><dd>Climate Data Interface version 2.0.5 (https://mpimet.mpg.de/cdi)</dd><dt><span>Conventions :</span></dt><dd>CF-1.6</dd><dt><span>CDO :</span></dt><dd>Climate Data Operators version 2.0.5 (https://mpimet.mpg.de/cdo)</dd><dt><span>dataset :</span></dt><dd>IE_MERA_FC3hr_3_day</dd></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.Dataset>\n",
       "Dimensions:            (x: 158, y: 166, time: 1096)\n",
       "Coordinates:\n",
       "  * x                  (x) float64 4.15e+05 4.175e+05 ... 8.05e+05 8.075e+05\n",
       "  * y                  (y) float64 4.075e+05 4.1e+05 ... 8.175e+05 8.2e+05\n",
       "    height             float64 0.0\n",
       "    Lambert_Conformal  int64 0\n",
       "  * time               (time) datetime64[ns] 1980-01-01 ... 1982-12-31\n",
       "    spatial_ref        int64 0\n",
       "Data variables:\n",
       "    PAR                (time, y, x) float32 dask.array<chunksize=(366, 85, 81), meta=np.ndarray>\n",
       "    PET                (time, y, x) float32 dask.array<chunksize=(366, 86, 82), meta=np.ndarray>\n",
       "    T                  (time, y, x) float32 dask.array<chunksize=(366, 85, 81), meta=np.ndarray>\n",
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       "Attributes:\n",
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       "    Conventions:  CF-1.6\n",
       "    CDO:          Climate Data Operators version 2.0.5 (https://mpimet.mpg.de...\n",
       "    dataset:      IE_MERA_FC3hr_3_day"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ds_interp"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(6.8350525, dtype=float32)"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# check value for the first day of the first year\n",
    "ds.sel({\"x\": XLON, \"y\": YLAT}, method=\"nearest\").isel(time=0)[\"T\"].values"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(nan)"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# check first value of spin-up year - should be nan\n",
    "ds_interp.sel({\"x\": XLON, \"y\": YLAT}, method=\"nearest\").isel(time=0)[\n",
    "    \"T\"\n",
    "].values"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [],
   "source": [
    "# shift first year of the main data to the spin-up year\n",
    "ds_interp = ds_interp.shift(time=-ds_interp.sel(time=\"1980\").dims[\"time\"])"
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  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(6.8350525, dtype=float32)"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# check value for the first day of the first year\n",
    "ds_interp.sel({\"x\": XLON, \"y\": YLAT}, method=\"nearest\").isel(time=0)[\n",
    "    \"T\"\n",
    "].values"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [],
   "source": [
    "# keep only spin-up year\n",
    "ds_interp = ds_interp.sel(time=\"1980\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [],
   "source": [
    "# merge with main dataset\n",
    "ds = xr.combine_by_coords([ds, ds_interp])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
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       "    spatial_ref        int64 0\n",
       "Data variables:\n",
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       "    Conventions:  CF-1.6\n",
       "    CDO:          Climate Data Operators version 2.0.5 (https://mpimet.mpg.de...\n",
       "    dataset:      IE_MERA_FC3hr_3_day</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-1942294c-78a7-4ddd-aecc-ff1ca4fe9252' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-1942294c-78a7-4ddd-aecc-ff1ca4fe9252' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>x</span>: 158</li><li><span class='xr-has-index'>y</span>: 166</li><li><span class='xr-has-index'>time</span>: 9497</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-c1ef1d53-2bed-48f9-b8e2-ee30c1e1d31b' class='xr-section-summary-in' type='checkbox'  checked><label for='section-c1ef1d53-2bed-48f9-b8e2-ee30c1e1d31b' class='xr-section-summary' >Coordinates: <span>(6)</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'>x</span></div><div class='xr-var-dims'>(x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>4.15e+05 4.175e+05 ... 8.075e+05</div><input id='attrs-c0c0e206-6c2c-4a20-9c4c-b1c437bf9cb4' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-c0c0e206-6c2c-4a20-9c4c-b1c437bf9cb4' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-cbcacf0d-e3cc-4bd1-9c33-1c3b8d79fea0' class='xr-var-data-in' type='checkbox'><label for='data-cbcacf0d-e3cc-4bd1-9c33-1c3b8d79fea0' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>projection_x_coordinate</dd><dt><span>units :</span></dt><dd>metre</dd><dt><span>axis :</span></dt><dd>X</dd><dt><span>long_name :</span></dt><dd>x coordinate of projection</dd></dl></div><div class='xr-var-data'><pre>array([415000., 417500., 420000., 422500., 425000., 427500., 430000., 432500.,\n",
       "       435000., 437500., 440000., 442500., 445000., 447500., 450000., 452500.,\n",
       "       455000., 457500., 460000., 462500., 465000., 467500., 470000., 472500.,\n",
       "       475000., 477500., 480000., 482500., 485000., 487500., 490000., 492500.,\n",
       "       495000., 497500., 500000., 502500., 505000., 507500., 510000., 512500.,\n",
       "       515000., 517500., 520000., 522500., 525000., 527500., 530000., 532500.,\n",
       "       535000., 537500., 540000., 542500., 545000., 547500., 550000., 552500.,\n",
       "       555000., 557500., 560000., 562500., 565000., 567500., 570000., 572500.,\n",
       "       575000., 577500., 580000., 582500., 585000., 587500., 590000., 592500.,\n",
       "       595000., 597500., 600000., 602500., 605000., 607500., 610000., 612500.,\n",
       "       615000., 617500., 620000., 622500., 625000., 627500., 630000., 632500.,\n",
       "       635000., 637500., 640000., 642500., 645000., 647500., 650000., 652500.,\n",
       "       655000., 657500., 660000., 662500., 665000., 667500., 670000., 672500.,\n",
       "       675000., 677500., 680000., 682500., 685000., 687500., 690000., 692500.,\n",
       "       695000., 697500., 700000., 702500., 705000., 707500., 710000., 712500.,\n",
       "       715000., 717500., 720000., 722500., 725000., 727500., 730000., 732500.,\n",
       "       735000., 737500., 740000., 742500., 745000., 747500., 750000., 752500.,\n",
       "       755000., 757500., 760000., 762500., 765000., 767500., 770000., 772500.,\n",
       "       775000., 777500., 780000., 782500., 785000., 787500., 790000., 792500.,\n",
       "       795000., 797500., 800000., 802500., 805000., 807500.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>y</span></div><div class='xr-var-dims'>(y)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>4.075e+05 4.1e+05 ... 8.2e+05</div><input id='attrs-d36dd1f5-0256-455f-83c2-721745516f95' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d36dd1f5-0256-455f-83c2-721745516f95' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0218a2eb-0c76-450d-8253-267ddd713cae' class='xr-var-data-in' type='checkbox'><label for='data-0218a2eb-0c76-450d-8253-267ddd713cae' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>projection_y_coordinate</dd><dt><span>units :</span></dt><dd>metre</dd><dt><span>axis :</span></dt><dd>Y</dd><dt><span>long_name :</span></dt><dd>y coordinate of projection</dd></dl></div><div class='xr-var-data'><pre>array([407500., 410000., 412500., 415000., 417500., 420000., 422500., 425000.,\n",
       "       427500., 430000., 432500., 435000., 437500., 440000., 442500., 445000.,\n",
       "       447500., 450000., 452500., 455000., 457500., 460000., 462500., 465000.,\n",
       "       467500., 470000., 472500., 475000., 477500., 480000., 482500., 485000.,\n",
       "       487500., 490000., 492500., 495000., 497500., 500000., 502500., 505000.,\n",
       "       507500., 510000., 512500., 515000., 517500., 520000., 522500., 525000.,\n",
       "       527500., 530000., 532500., 535000., 537500., 540000., 542500., 545000.,\n",
       "       547500., 550000., 552500., 555000., 557500., 560000., 562500., 565000.,\n",
       "       567500., 570000., 572500., 575000., 577500., 580000., 582500., 585000.,\n",
       "       587500., 590000., 592500., 595000., 597500., 600000., 602500., 605000.,\n",
       "       607500., 610000., 612500., 615000., 617500., 620000., 622500., 625000.,\n",
       "       627500., 630000., 632500., 635000., 637500., 640000., 642500., 645000.,\n",
       "       647500., 650000., 652500., 655000., 657500., 660000., 662500., 665000.,\n",
       "       667500., 670000., 672500., 675000., 677500., 680000., 682500., 685000.,\n",
       "       687500., 690000., 692500., 695000., 697500., 700000., 702500., 705000.,\n",
       "       707500., 710000., 712500., 715000., 717500., 720000., 722500., 725000.,\n",
       "       727500., 730000., 732500., 735000., 737500., 740000., 742500., 745000.,\n",
       "       747500., 750000., 752500., 755000., 757500., 760000., 762500., 765000.,\n",
       "       767500., 770000., 772500., 775000., 777500., 780000., 782500., 785000.,\n",
       "       787500., 790000., 792500., 795000., 797500., 800000., 802500., 805000.,\n",
       "       807500., 810000., 812500., 815000., 817500., 820000.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>height</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0</div><input id='attrs-424aae85-3e80-4bbc-90d6-287553e950cc' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-424aae85-3e80-4bbc-90d6-287553e950cc' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f9b50a97-9a79-4985-8122-c1c9983afd64' class='xr-var-data-in' type='checkbox'><label for='data-f9b50a97-9a79-4985-8122-c1c9983afd64' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>height</dd><dt><span>long_name :</span></dt><dd>height</dd><dt><span>units :</span></dt><dd>m</dd><dt><span>positive :</span></dt><dd>up</dd><dt><span>axis :</span></dt><dd>Z</dd></dl></div><div class='xr-var-data'><pre>array(0.)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>Lambert_Conformal</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>0</div><input id='attrs-7a391542-ef8a-4fa3-b32a-db3e143e3eeb' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-7a391542-ef8a-4fa3-b32a-db3e143e3eeb' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-86c7dfcb-8539-494b-ab6a-624f2f4eca7a' class='xr-var-data-in' type='checkbox'><label for='data-86c7dfcb-8539-494b-ab6a-624f2f4eca7a' 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>crs_wkt :</span></dt><dd>PROJCS[&quot;undefined&quot;,GEOGCS[&quot;undefined&quot;,DATUM[&quot;undefined&quot;,SPHEROID[&quot;undefined&quot;,6367470,0]],PRIMEM[&quot;Greenwich&quot;,0,AUTHORITY[&quot;EPSG&quot;,&quot;8901&quot;]],UNIT[&quot;degree&quot;,0.0174532925199433]],PROJECTION[&quot;Lambert_Conformal_Conic_1SP&quot;],PARAMETER[&quot;latitude_of_origin&quot;,53.5],PARAMETER[&quot;central_meridian&quot;,5],PARAMETER[&quot;scale_factor&quot;,1],PARAMETER[&quot;false_easting&quot;,1481641.67696368],PARAMETER[&quot;false_northing&quot;,537326.063885016],UNIT[&quot;metre&quot;,1,AUTHORITY[&quot;EPSG&quot;,&quot;9001&quot;]],AXIS[&quot;Easting&quot;,EAST],AXIS[&quot;Northing&quot;,NORTH]]</dd><dt><span>semi_major_axis :</span></dt><dd>6367470.0</dd><dt><span>semi_minor_axis :</span></dt><dd>6367470.0</dd><dt><span>inverse_flattening :</span></dt><dd>0.0</dd><dt><span>reference_ellipsoid_name :</span></dt><dd>undefined</dd><dt><span>longitude_of_prime_meridian :</span></dt><dd>0.0</dd><dt><span>prime_meridian_name :</span></dt><dd>Greenwich</dd><dt><span>geographic_crs_name :</span></dt><dd>undefined</dd><dt><span>horizontal_datum_name :</span></dt><dd>undefined</dd><dt><span>projected_crs_name :</span></dt><dd>undefined</dd><dt><span>grid_mapping_name :</span></dt><dd>lambert_conformal_conic</dd><dt><span>standard_parallel :</span></dt><dd>53.5</dd><dt><span>longitude_of_central_meridian :</span></dt><dd>5.0</dd><dt><span>false_easting :</span></dt><dd>1481641.67696368</dd><dt><span>false_northing :</span></dt><dd>537326.063885016</dd><dt><span>spatial_ref :</span></dt><dd>PROJCS[&quot;undefined&quot;,GEOGCS[&quot;undefined&quot;,DATUM[&quot;undefined&quot;,SPHEROID[&quot;undefined&quot;,6367470,0]],PRIMEM[&quot;Greenwich&quot;,0,AUTHORITY[&quot;EPSG&quot;,&quot;8901&quot;]],UNIT[&quot;degree&quot;,0.0174532925199433]],PROJECTION[&quot;Lambert_Conformal_Conic_1SP&quot;],PARAMETER[&quot;latitude_of_origin&quot;,53.5],PARAMETER[&quot;central_meridian&quot;,5],PARAMETER[&quot;scale_factor&quot;,1],PARAMETER[&quot;false_easting&quot;,1481641.67696368],PARAMETER[&quot;false_northing&quot;,537326.063885016],UNIT[&quot;metre&quot;,1,AUTHORITY[&quot;EPSG&quot;,&quot;9001&quot;]],AXIS[&quot;Easting&quot;,EAST],AXIS[&quot;Northing&quot;,NORTH]]</dd><dt><span>GeoTransform :</span></dt><dd>413750.0 2500.0 0.0 406250.0 0.0 2500.0</dd></dl></div><div class='xr-var-data'><pre>array(0)</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'>1980-01-01 ... 2005-12-31</div><input id='attrs-f1aee729-79b4-44c3-ba3f-ca9ac878cd39' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f1aee729-79b4-44c3-ba3f-ca9ac878cd39' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6afc953e-b7ef-46c5-b27c-153686845df4' class='xr-var-data-in' type='checkbox'><label for='data-6afc953e-b7ef-46c5-b27c-153686845df4' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>time</dd><dt><span>axis :</span></dt><dd>T</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;1980-01-01T00:00:00.000000000&#x27;, &#x27;1980-01-02T00:00:00.000000000&#x27;,\n",
       "       &#x27;1980-01-03T00:00:00.000000000&#x27;, ..., &#x27;2005-12-29T00:00:00.000000000&#x27;,\n",
       "       &#x27;2005-12-30T00:00:00.000000000&#x27;, &#x27;2005-12-31T00:00:00.000000000&#x27;],\n",
       "      dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>spatial_ref</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>0</div><input id='attrs-eafcd5b0-f509-4057-b88e-df36599b9a6a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-eafcd5b0-f509-4057-b88e-df36599b9a6a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6d0479d2-23cb-46cc-a921-b63ae11509f8' class='xr-var-data-in' type='checkbox'><label for='data-6d0479d2-23cb-46cc-a921-b63ae11509f8' 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>crs_wkt :</span></dt><dd>PROJCS[&quot;undefined&quot;,GEOGCS[&quot;undefined&quot;,DATUM[&quot;undefined&quot;,SPHEROID[&quot;undefined&quot;,6367470,0]],PRIMEM[&quot;Greenwich&quot;,0,AUTHORITY[&quot;EPSG&quot;,&quot;8901&quot;]],UNIT[&quot;degree&quot;,0.0174532925199433]],PROJECTION[&quot;Lambert_Conformal_Conic_1SP&quot;],PARAMETER[&quot;latitude_of_origin&quot;,53.5],PARAMETER[&quot;central_meridian&quot;,5],PARAMETER[&quot;scale_factor&quot;,1],PARAMETER[&quot;false_easting&quot;,1481641.67696368],PARAMETER[&quot;false_northing&quot;,537326.063885016],UNIT[&quot;metre&quot;,1,AUTHORITY[&quot;EPSG&quot;,&quot;9001&quot;]],AXIS[&quot;Easting&quot;,EAST],AXIS[&quot;Northing&quot;,NORTH]]</dd><dt><span>semi_major_axis :</span></dt><dd>6367470.0</dd><dt><span>semi_minor_axis :</span></dt><dd>6367470.0</dd><dt><span>inverse_flattening :</span></dt><dd>0.0</dd><dt><span>reference_ellipsoid_name :</span></dt><dd>undefined</dd><dt><span>longitude_of_prime_meridian :</span></dt><dd>0.0</dd><dt><span>prime_meridian_name :</span></dt><dd>Greenwich</dd><dt><span>geographic_crs_name :</span></dt><dd>undefined</dd><dt><span>horizontal_datum_name :</span></dt><dd>undefined</dd><dt><span>projected_crs_name :</span></dt><dd>undefined</dd><dt><span>grid_mapping_name :</span></dt><dd>lambert_conformal_conic</dd><dt><span>standard_parallel :</span></dt><dd>53.5</dd><dt><span>longitude_of_central_meridian :</span></dt><dd>5.0</dd><dt><span>false_easting :</span></dt><dd>1481641.67696368</dd><dt><span>false_northing :</span></dt><dd>537326.063885016</dd><dt><span>spatial_ref :</span></dt><dd>PROJCS[&quot;undefined&quot;,GEOGCS[&quot;undefined&quot;,DATUM[&quot;undefined&quot;,SPHEROID[&quot;undefined&quot;,6367470,0]],PRIMEM[&quot;Greenwich&quot;,0,AUTHORITY[&quot;EPSG&quot;,&quot;8901&quot;]],UNIT[&quot;degree&quot;,0.0174532925199433]],PROJECTION[&quot;Lambert_Conformal_Conic_1SP&quot;],PARAMETER[&quot;latitude_of_origin&quot;,53.5],PARAMETER[&quot;central_meridian&quot;,5],PARAMETER[&quot;scale_factor&quot;,1],PARAMETER[&quot;false_easting&quot;,1481641.67696368],PARAMETER[&quot;false_northing&quot;,537326.063885016],UNIT[&quot;metre&quot;,1,AUTHORITY[&quot;EPSG&quot;,&quot;9001&quot;]],AXIS[&quot;Easting&quot;,EAST],AXIS[&quot;Northing&quot;,NORTH]]</dd><dt><span>GeoTransform :</span></dt><dd>413750.0 2500.0 0.0 406250.0 0.0 2500.0</dd></dl></div><div class='xr-var-data'><pre>array(0)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-a4c08411-24e2-4024-8fe9-2300fa9c83d8' class='xr-section-summary-in' type='checkbox'  checked><label for='section-a4c08411-24e2-4024-8fe9-2300fa9c83d8' class='xr-section-summary' >Data variables: <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>PAR</span></div><div class='xr-var-dims'>(time, y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(366, 85, 81), meta=np.ndarray&gt;</div><input id='attrs-f00cc45e-c365-40a4-9298-5aea90168f3c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f00cc45e-c365-40a4-9298-5aea90168f3c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d972e11b-df6a-4daa-8a05-d64ba284e59f' class='xr-var-data-in' type='checkbox'><label for='data-d972e11b-df6a-4daa-8a05-d64ba284e59f' 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>Surface Photosynthetically Active Radiation</dd><dt><span>units :</span></dt><dd>MJ m⁻² day⁻¹</dd></dl></div><div class='xr-var-data'><table>\n",
       "    <tr>\n",
       "        <td>\n",
       "            <table style=\"border-collapse: collapse;\">\n",
       "                <thead>\n",
       "                    <tr>\n",
       "                        <td> </td>\n",
       "                        <th> Array </th>\n",
       "                        <th> Chunk </th>\n",
       "                    </tr>\n",
       "                </thead>\n",
       "                <tbody>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 0.93 GiB </td>\n",
       "                        <td> 127.93 MiB </td>\n",
       "                    </tr>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> (9497, 166, 158) </td>\n",
       "                        <td> (4871, 85, 81) </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Dask graph </th>\n",
       "                        <td colspan=\"2\"> 12 chunks in 21 graph layers </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Data type </th>\n",
       "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
       "                    </tr>\n",
       "                </tbody>\n",
       "            </table>\n",
       "        </td>\n",
       "        <td>\n",
       "        <svg width=\"158\" height=\"148\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
       "\n",
       "  <!-- Horizontal lines -->\n",
       "  <line x1=\"10\" y1=\"0\" x2=\"80\" y2=\"70\" style=\"stroke-width:2\" />\n",
       "  <line x1=\"10\" y1=\"14\" x2=\"80\" y2=\"85\" />\n",
       "  <line x1=\"10\" y1=\"28\" x2=\"80\" y2=\"98\" style=\"stroke-width:2\" />\n",
       "\n",
       "  <!-- Vertical lines -->\n",
       "  <line x1=\"10\" y1=\"0\" x2=\"10\" y2=\"28\" style=\"stroke-width:2\" />\n",
       "  <line x1=\"12\" y1=\"2\" x2=\"12\" y2=\"31\" />\n",
       "  <line x1=\"48\" y1=\"38\" x2=\"48\" y2=\"67\" />\n",
       "  <line x1=\"80\" y1=\"70\" x2=\"80\" y2=\"98\" style=\"stroke-width:2\" />\n",
       "\n",
       "  <!-- Colored Rectangle -->\n",
       "  <polygon points=\"10.0,0.0 80.58823529411765,70.58823529411765 80.58823529411765,98.87064223992012 10.0,28.28240694580246\" style=\"fill:#ECB172A0;stroke-width:0\"/>\n",
       "\n",
       "  <!-- Horizontal lines -->\n",
       "  <line x1=\"10\" y1=\"0\" x2=\"38\" y2=\"0\" style=\"stroke-width:2\" />\n",
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       "        </td>\n",
       "    </tr>\n",
       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>PET</span></div><div class='xr-var-dims'>(time, y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(366, 86, 82), meta=np.ndarray&gt;</div><input id='attrs-d30d14f5-0443-4ced-b0a9-247e8f8717e6' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d30d14f5-0443-4ced-b0a9-247e8f8717e6' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-999bcbc0-b985-43f7-8ba7-040caa10bff1' class='xr-var-data-in' type='checkbox'><label for='data-999bcbc0-b985-43f7-8ba7-040caa10bff1' 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>mm day⁻¹</dd><dt><span>long_name :</span></dt><dd>Reference evapotranspiration</dd></dl></div><div class='xr-var-data'><table>\n",
       "    <tr>\n",
       "        <td>\n",
       "            <table style=\"border-collapse: collapse;\">\n",
       "                <thead>\n",
       "                    <tr>\n",
       "                        <td> </td>\n",
       "                        <th> Array </th>\n",
       "                        <th> Chunk </th>\n",
       "                    </tr>\n",
       "                </thead>\n",
       "                <tbody>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 0.93 GiB </td>\n",
       "                        <td> 127.94 MiB </td>\n",
       "                    </tr>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> (9497, 166, 158) </td>\n",
       "                        <td> (4756, 86, 82) </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Dask graph </th>\n",
       "                        <td colspan=\"2\"> 12 chunks in 19 graph layers </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Data type </th>\n",
       "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
       "                    </tr>\n",
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       "    </tr>\n",
       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>T</span></div><div class='xr-var-dims'>(time, y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(366, 85, 81), meta=np.ndarray&gt;</div><input id='attrs-69097717-61a0-4a56-8be2-8e83b4647427' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-69097717-61a0-4a56-8be2-8e83b4647427' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6d5c570d-d40c-47c6-887a-05d66d33a14d' class='xr-var-data-in' type='checkbox'><label for='data-6d5c570d-d40c-47c6-887a-05d66d33a14d' 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>GRIB_paramId :</span></dt><dd>233253011</dd><dt><span>GRIB_numberOfPoints :</span></dt><dd>258681</dd><dt><span>GRIB_typeOfLevel :</span></dt><dd>heightAboveGround</dd><dt><span>GRIB_stepUnits :</span></dt><dd>1</dd><dt><span>GRIB_stepType :</span></dt><dd>instant</dd><dt><span>GRIB_gridType :</span></dt><dd>lambert</dd><dt><span>GRIB_DxInMetres :</span></dt><dd>2500</dd><dt><span>GRIB_DyInMetres :</span></dt><dd>2500</dd><dt><span>GRIB_LaDInDegrees :</span></dt><dd>53.5</dd><dt><span>GRIB_Latin1InDegrees :</span></dt><dd>53.5</dd><dt><span>GRIB_Latin2InDegrees :</span></dt><dd>53.5</dd><dt><span>GRIB_LoVInDegrees :</span></dt><dd>5.0</dd><dt><span>GRIB_NV :</span></dt><dd>132</dd><dt><span>GRIB_Nx :</span></dt><dd>529</dd><dt><span>GRIB_Ny :</span></dt><dd>489</dd><dt><span>GRIB_cfName :</span></dt><dd>unknown</dd><dt><span>GRIB_cfVarName :</span></dt><dd>unknown</dd><dt><span>GRIB_gridDefinitionDescription :</span></dt><dd>Lambert Conformal</dd><dt><span>GRIB_iScansNegatively :</span></dt><dd>0</dd><dt><span>GRIB_jPointsAreConsecutive :</span></dt><dd>0</dd><dt><span>GRIB_jScansPositively :</span></dt><dd>1</dd><dt><span>GRIB_latitudeOfFirstGridPointInDegrees :</span></dt><dd>46.834</dd><dt><span>GRIB_latitudeOfSouthernPoleInDegrees :</span></dt><dd>0.0</dd><dt><span>GRIB_longitudeOfFirstGridPointInDegrees :</span></dt><dd>-14.609</dd><dt><span>GRIB_longitudeOfSouthernPoleInDegrees :</span></dt><dd>0.0</dd><dt><span>GRIB_missingValue :</span></dt><dd>3.4028234663852886e+38</dd><dt><span>GRIB_name :</span></dt><dd>Temperature</dd><dt><span>GRIB_shortName :</span></dt><dd>t</dd><dt><span>GRIB_units :</span></dt><dd>K</dd><dt><span>long_name :</span></dt><dd>Temperature</dd><dt><span>units :</span></dt><dd>°C</dd><dt><span>standard_name :</span></dt><dd>unknown</dd></dl></div><div class='xr-var-data'><table>\n",
       "    <tr>\n",
       "        <td>\n",
       "            <table style=\"border-collapse: collapse;\">\n",
       "                <thead>\n",
       "                    <tr>\n",
       "                        <td> </td>\n",
       "                        <th> Array </th>\n",
       "                        <th> Chunk </th>\n",
       "                    </tr>\n",
       "                </thead>\n",
       "                <tbody>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 0.93 GiB </td>\n",
       "                        <td> 127.93 MiB </td>\n",
       "                    </tr>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> (9497, 166, 158) </td>\n",
       "                        <td> (4871, 85, 81) </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Dask graph </th>\n",
       "                        <td colspan=\"2\"> 12 chunks in 20 graph layers </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Data type </th>\n",
       "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
       "                    </tr>\n",
       "                </tbody>\n",
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       "        </td>\n",
       "        <td>\n",
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       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>PP</span></div><div class='xr-var-dims'>(time, y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(366, 85, 81), meta=np.ndarray&gt;</div><input id='attrs-ea1987b5-c701-485a-ba34-ca6e1e8edba7' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ea1987b5-c701-485a-ba34-ca6e1e8edba7' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8b4d973f-9f2b-4bf7-91d1-ca83023ffbea' class='xr-var-data-in' type='checkbox'><label for='data-8b4d973f-9f2b-4bf7-91d1-ca83023ffbea' 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>GRIB_paramId :</span></dt><dd>233253061</dd><dt><span>GRIB_numberOfPoints :</span></dt><dd>258681</dd><dt><span>GRIB_typeOfLevel :</span></dt><dd>heightAboveGround</dd><dt><span>GRIB_stepUnits :</span></dt><dd>1</dd><dt><span>GRIB_stepType :</span></dt><dd>accum</dd><dt><span>GRIB_gridType :</span></dt><dd>lambert</dd><dt><span>GRIB_DxInMetres :</span></dt><dd>2500</dd><dt><span>GRIB_DyInMetres :</span></dt><dd>2500</dd><dt><span>GRIB_LaDInDegrees :</span></dt><dd>53.5</dd><dt><span>GRIB_Latin1InDegrees :</span></dt><dd>53.5</dd><dt><span>GRIB_Latin2InDegrees :</span></dt><dd>53.5</dd><dt><span>GRIB_LoVInDegrees :</span></dt><dd>5.0</dd><dt><span>GRIB_NV :</span></dt><dd>132</dd><dt><span>GRIB_Nx :</span></dt><dd>529</dd><dt><span>GRIB_Ny :</span></dt><dd>489</dd><dt><span>GRIB_cfName :</span></dt><dd>unknown</dd><dt><span>GRIB_cfVarName :</span></dt><dd>unknown</dd><dt><span>GRIB_gridDefinitionDescription :</span></dt><dd>Lambert Conformal</dd><dt><span>GRIB_iScansNegatively :</span></dt><dd>0</dd><dt><span>GRIB_jPointsAreConsecutive :</span></dt><dd>0</dd><dt><span>GRIB_jScansPositively :</span></dt><dd>1</dd><dt><span>GRIB_latitudeOfFirstGridPointInDegrees :</span></dt><dd>46.834</dd><dt><span>GRIB_latitudeOfSouthernPoleInDegrees :</span></dt><dd>0.0</dd><dt><span>GRIB_longitudeOfFirstGridPointInDegrees :</span></dt><dd>-14.609</dd><dt><span>GRIB_longitudeOfSouthernPoleInDegrees :</span></dt><dd>0.0</dd><dt><span>GRIB_missingValue :</span></dt><dd>3.4028234663852886e+38</dd><dt><span>GRIB_name :</span></dt><dd>Total precipitation</dd><dt><span>GRIB_shortName :</span></dt><dd>tp</dd><dt><span>GRIB_units :</span></dt><dd>kg m**-2</dd><dt><span>long_name :</span></dt><dd>Total precipitation</dd><dt><span>units :</span></dt><dd>mm day⁻¹</dd><dt><span>standard_name :</span></dt><dd>unknown</dd></dl></div><div class='xr-var-data'><table>\n",
       "    <tr>\n",
       "        <td>\n",
       "            <table style=\"border-collapse: collapse;\">\n",
       "                <thead>\n",
       "                    <tr>\n",
       "                        <td> </td>\n",
       "                        <th> Array </th>\n",
       "                        <th> Chunk </th>\n",
       "                    </tr>\n",
       "                </thead>\n",
       "                <tbody>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Bytes </th>\n",
       "                        <td> 0.93 GiB </td>\n",
       "                        <td> 127.93 MiB </td>\n",
       "                    </tr>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> (9497, 166, 158) </td>\n",
       "                        <td> (4871, 85, 81) </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Dask graph </th>\n",
       "                        <td colspan=\"2\"> 12 chunks in 20 graph layers </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Data type </th>\n",
       "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
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       "                </tbody>\n",
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       "        </td>\n",
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       "  <line x1=\"48\" y1=\"38\" x2=\"48\" y2=\"67\" />\n",
       "  <line x1=\"80\" y1=\"70\" x2=\"80\" y2=\"98\" style=\"stroke-width:2\" />\n",
       "\n",
       "  <!-- Colored Rectangle -->\n",
       "  <polygon points=\"10.0,0.0 80.58823529411765,70.58823529411765 80.58823529411765,98.87064223992012 10.0,28.28240694580246\" style=\"fill:#ECB172A0;stroke-width:0\"/>\n",
       "\n",
       "  <!-- Horizontal lines -->\n",
       "  <line x1=\"10\" y1=\"0\" x2=\"38\" y2=\"0\" style=\"stroke-width:2\" />\n",
       "  <line x1=\"12\" y1=\"2\" x2=\"40\" y2=\"2\" />\n",
       "  <line x1=\"48\" y1=\"38\" x2=\"76\" y2=\"38\" />\n",
       "  <line x1=\"80\" y1=\"70\" x2=\"108\" y2=\"70\" style=\"stroke-width:2\" />\n",
       "\n",
       "  <!-- Vertical lines -->\n",
       "  <line x1=\"10\" y1=\"0\" x2=\"80\" y2=\"70\" style=\"stroke-width:2\" />\n",
       "  <line x1=\"24\" y1=\"0\" x2=\"94\" y2=\"70\" />\n",
       "  <line x1=\"38\" y1=\"0\" x2=\"108\" y2=\"70\" style=\"stroke-width:2\" />\n",
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       "  <line x1=\"80\" y1=\"98\" x2=\"108\" y2=\"98\" style=\"stroke-width:2\" />\n",
       "\n",
       "  <!-- Vertical lines -->\n",
       "  <line x1=\"80\" y1=\"70\" x2=\"80\" y2=\"98\" style=\"stroke-width:2\" />\n",
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       "  <line x1=\"108\" y1=\"70\" x2=\"108\" y2=\"98\" style=\"stroke-width:2\" />\n",
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       "\n",
       "  <!-- Text -->\n",
       "  <text x=\"94.594847\" y=\"118.870642\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >158</text>\n",
       "  <text x=\"128.601458\" y=\"84.729439\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(-90,128.601458,84.729439)\">166</text>\n",
       "  <text x=\"35.294118\" y=\"83.576525\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(45,35.294118,83.576525)\">9497</text>\n",
       "</svg>\n",
       "        </td>\n",
       "    </tr>\n",
       "</table></div></li></ul></div></li><li class='xr-section-item'><input id='section-dfff1da8-3ae1-492b-be01-b88bcd052b02' class='xr-section-summary-in' type='checkbox'  ><label for='section-dfff1da8-3ae1-492b-be01-b88bcd052b02' class='xr-section-summary' >Indexes: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>x</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-b5468b87-e13f-45f9-a5e0-21d6741bc4af' class='xr-index-data-in' type='checkbox'/><label for='index-b5468b87-e13f-45f9-a5e0-21d6741bc4af' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Float64Index([415000.0, 417500.0, 420000.0, 422500.0, 425000.0, 427500.0,\n",
       "              430000.0, 432500.0, 435000.0, 437500.0,\n",
       "              ...\n",
       "              785000.0, 787500.0, 790000.0, 792500.0, 795000.0, 797500.0,\n",
       "              800000.0, 802500.0, 805000.0, 807500.0],\n",
       "             dtype=&#x27;float64&#x27;, name=&#x27;x&#x27;, length=158))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>y</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-9ea4e43c-fce0-4082-9380-b2b280bcee59' class='xr-index-data-in' type='checkbox'/><label for='index-9ea4e43c-fce0-4082-9380-b2b280bcee59' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Float64Index([407500.0, 410000.0, 412500.0, 415000.0, 417500.0, 420000.0,\n",
       "              422500.0, 425000.0, 427500.0, 430000.0,\n",
       "              ...\n",
       "              797500.0, 800000.0, 802500.0, 805000.0, 807500.0, 810000.0,\n",
       "              812500.0, 815000.0, 817500.0, 820000.0],\n",
       "             dtype=&#x27;float64&#x27;, name=&#x27;y&#x27;, length=166))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>time</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-81760b1b-a7b6-4758-8e6b-6dd7ab032699' class='xr-index-data-in' type='checkbox'/><label for='index-81760b1b-a7b6-4758-8e6b-6dd7ab032699' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(DatetimeIndex([&#x27;1980-01-01&#x27;, &#x27;1980-01-02&#x27;, &#x27;1980-01-03&#x27;, &#x27;1980-01-04&#x27;,\n",
       "               &#x27;1980-01-05&#x27;, &#x27;1980-01-06&#x27;, &#x27;1980-01-07&#x27;, &#x27;1980-01-08&#x27;,\n",
       "               &#x27;1980-01-09&#x27;, &#x27;1980-01-10&#x27;,\n",
       "               ...\n",
       "               &#x27;2005-12-22&#x27;, &#x27;2005-12-23&#x27;, &#x27;2005-12-24&#x27;, &#x27;2005-12-25&#x27;,\n",
       "               &#x27;2005-12-26&#x27;, &#x27;2005-12-27&#x27;, &#x27;2005-12-28&#x27;, &#x27;2005-12-29&#x27;,\n",
       "               &#x27;2005-12-30&#x27;, &#x27;2005-12-31&#x27;],\n",
       "              dtype=&#x27;datetime64[ns]&#x27;, name=&#x27;time&#x27;, length=9497, freq=None))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-35733bb8-66fe-43ae-b231-dd1a027b1859' class='xr-section-summary-in' type='checkbox'  checked><label for='section-35733bb8-66fe-43ae-b231-dd1a027b1859' class='xr-section-summary' >Attributes: <span>(4)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>CDI :</span></dt><dd>Climate Data Interface version 2.0.5 (https://mpimet.mpg.de/cdi)</dd><dt><span>Conventions :</span></dt><dd>CF-1.6</dd><dt><span>CDO :</span></dt><dd>Climate Data Operators version 2.0.5 (https://mpimet.mpg.de/cdo)</dd><dt><span>dataset :</span></dt><dd>IE_MERA_FC3hr_3_day</dd></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.Dataset>\n",
       "Dimensions:            (x: 158, y: 166, time: 9497)\n",
       "Coordinates:\n",
       "  * x                  (x) float64 4.15e+05 4.175e+05 ... 8.05e+05 8.075e+05\n",
       "  * y                  (y) float64 4.075e+05 4.1e+05 ... 8.175e+05 8.2e+05\n",
       "    height             float64 0.0\n",
       "    Lambert_Conformal  int64 0\n",
       "  * time               (time) datetime64[ns] 1980-01-01 ... 2005-12-31\n",
       "    spatial_ref        int64 0\n",
       "Data variables:\n",
       "    PAR                (time, y, x) float32 dask.array<chunksize=(366, 85, 81), meta=np.ndarray>\n",
       "    PET                (time, y, x) float32 dask.array<chunksize=(366, 86, 82), meta=np.ndarray>\n",
       "    T                  (time, y, x) float32 dask.array<chunksize=(366, 85, 81), meta=np.ndarray>\n",
       "    PP                 (time, y, x) float32 dask.array<chunksize=(366, 85, 81), meta=np.ndarray>\n",
       "Attributes:\n",
       "    CDI:          Climate Data Interface version 2.0.5 (https://mpimet.mpg.de...\n",
       "    Conventions:  CF-1.6\n",
       "    CDO:          Climate Data Operators version 2.0.5 (https://mpimet.mpg.de...\n",
       "    dataset:      IE_MERA_FC3hr_3_day"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ds.rio.write_crs(data_crs, inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1152x384 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# visualise\n",
    "# spin-up year and first year should be identical\n",
    "ds_interp = ds.sel({\"x\": XLON, \"y\": YLAT}, method=\"nearest\").sel(\n",
    "    time=slice(\"1980\", \"1982\")\n",
    ")\n",
    "plt.figure(figsize=(12, 4))\n",
    "plt.plot(ds_interp[\"time\"], ds_interp[\"T\"])\n",
    "plt.title(f\"{ds['T'].attrs['long_name']} [{ds['T'].attrs['units']}]\")\n",
    "plt.tight_layout()\n",
    "plt.show()"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "ClimAg",
   "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": "3.10.6"
  },
  "vscode": {
   "interpreter": {
    "hash": "c4e659d1bedfc73d1fd31d7c0e2c79d7cc7aac22204994016c65a9e44686eb91"
   }
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}