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    "# Met Éireann Reanalysis (MÉRA) - using GRIB files\n",
    "\n",
    "<https://www.met.ie/climate/available-data/mera>\n",
    "\n",
    "Issues:\n",
    "\n",
    "- data uses 0/360 longitude coordinates instead of -180/180\n",
    "  - data spans both negative and positive longitudes\n",
    "- projection information is not parsed when the data is read\n",
    "- lon/lat are multidimensional coordinates (y, x)\n",
    "  - data with two-dimensional coordinates cannot be spatially selected (e.g.\n",
    "    extracting data for a certain point, or clipping with a geometry)\n",
    "  - x and y correspond to the index of the cells and are not coordinates in\n",
    "    Lambert Conformal Conic projection\n",
    "\n",
    "Solution:\n",
    "\n",
    "- use CDO to convert the GRIB file to netCDF first\n",
    "  - projection info is parsed and can be read by Xarray\n",
    "  - one-dimensional coordinates in Lambert Conformal Conic projection\n",
    "  - data can now be indexed or selected both spatially and temporally using\n",
    "    Xarray\n",
    "  - some metadata are lost (e.g. variable name and attributes) but these can\n",
    "    be reassigned manually\n",
    "  - this method combines all three time steps in the example data (data needs\n",
    "    to be split prior to conversion to avoid this)\n",
    "\n",
    "Relevant links:\n",
    "\n",
    "- <https://docs.xarray.dev/en/stable/examples/multidimensional-coords.html>\n",
    "- <https://docs.xarray.dev/en/stable/examples/ERA5-GRIB-example.html>\n",
    "- <https://scitools.org.uk/cartopy/docs/latest/reference/projections.html>\n",
    "- <https://confluence.ecmwf.int/display/OIFS/How+to+convert+GRIB+to+netCDF>\n",
    "\n",
    "Example data used:\n",
    "<https://www.met.ie/downloads/MERA_PRODYEAR_2015_06_11_105_2_0_FC3hr.grb>\n",
    "\n",
    "Requirements:\n",
    "\n",
    "- CDO\n",
    "- Python 3.10\n",
    "  - rioxarray\n",
    "  - geopandas\n",
    "  - dask\n",
    "  - cartopy\n",
    "  - matplotlib\n",
    "  - nc-time-axis\n",
    "  - pooch\n",
    "  - netcdf4\n",
    "  - cfgrib"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import os\n",
    "from datetime import date, datetime, timezone\n",
    "import cartopy.crs as ccrs\n",
    "import geopandas as gpd\n",
    "import matplotlib.dates as mdates\n",
    "import matplotlib.pyplot as plt\n",
    "import matplotlib.units as munits\n",
    "import numpy as np\n",
    "import pooch\n",
    "import xarray as xr"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Moorepark, Fermoy met station coords\n",
    "LON, LAT = -8.26389, 52.16389"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Ireland boundary (derived from NUTS 2021)\n",
    "GPKG_BOUNDARY = os.path.join(\"data\", \"boundaries\", \"boundaries_all.gpkg\")\n",
    "ie = gpd.read_file(GPKG_BOUNDARY, layer=\"NUTS_RG_01M_2021_2157_IE\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "DATA_DIR = os.path.join(\"data\", \"MERA\", \"sample\")\n",
    "os.makedirs(DATA_DIR, exist_ok=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "URL = \"https://www.met.ie/downloads/MERA_PRODYEAR_2015_06_11_105_2_0_FC3hr.grb\"\n",
    "FILE_NAME = \"MERA_PRODYEAR_2015_06_11_105_2_0_FC3hr\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "# download data if necessary\n",
    "# sample GRIB data; 2 m temperature; 3-h forecasts\n",
    "if not os.path.isfile(os.path.join(DATA_DIR, FILE_NAME)):\n",
    "    pooch.retrieve(\n",
    "        url=URL, known_hash=None, fname=f\"{FILE_NAME}.grb\", path=DATA_DIR\n",
    "    )\n",
    "\n",
    "    with open(\n",
    "        os.path.join(DATA_DIR, f\"{FILE_NAME}.txt\"), \"w\", encoding=\"utf-8\"\n",
    "    ) as outfile:\n",
    "        outfile.write(\n",
    "            f\"Data downloaded on: {datetime.now(tz=timezone.utc)}\\n\"\n",
    "            f\"Download URL: {URL}\"\n",
    "        )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "# path to example data file\n",
    "BASE_FILE_NAME = os.path.join(DATA_DIR, FILE_NAME)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Read original GRIB data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "data = xr.open_dataset(\n",
    "    f\"{BASE_FILE_NAME}.grb\",\n",
    "    decode_coords=\"all\",\n",
    "    chunks=\"auto\",\n",
    "    engine=\"cfgrib\",\n",
    ")"
   ]
  },
  {
   "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:            (time: 240, step: 3, y: 489, x: 529)\n",
       "Coordinates:\n",
       "  * time               (time) datetime64[ns] 2015-06-01 ... 2015-06-30T21:00:00\n",
       "  * step               (step) timedelta64[ns] 01:00:00 02:00:00 03:00:00\n",
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       "    longitude          (y, x) float64 dask.array&lt;chunksize=(489, 529), meta=np.ndarray&gt;\n",
       "    valid_time         (time, step) datetime64[ns] dask.array&lt;chunksize=(240, 3), meta=np.ndarray&gt;\n",
       "Dimensions without coordinates: y, x\n",
       "Data variables:\n",
       "    t                  (time, step, y, x) float32 dask.array&lt;chunksize=(194, 1, 398, 432), meta=np.ndarray&gt;\n",
       "Attributes:\n",
       "    GRIB_edition:            1\n",
       "    GRIB_centre:             eidb\n",
       "    GRIB_centreDescription:  Dublin\n",
       "    GRIB_subCentre:          255\n",
       "    Conventions:             CF-1.7\n",
       "    institution:             Dublin\n",
       "    history:                 2023-04-01T21:49 GRIB to CDM+CF via cfgrib-0.9.1...</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-11d70e4d-6ff9-4c11-9594-18ac2b0fd2c4' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-11d70e4d-6ff9-4c11-9594-18ac2b0fd2c4' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>time</span>: 240</li><li><span class='xr-has-index'>step</span>: 3</li><li><span>y</span>: 489</li><li><span>x</span>: 529</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-06b1ddb7-234b-4407-88be-591773628a73' class='xr-section-summary-in' type='checkbox'  checked><label for='section-06b1ddb7-234b-4407-88be-591773628a73' 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'>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'>2015-06-01 ... 2015-06-30T21:00:00</div><input id='attrs-f89a1017-fa1f-4a3f-8898-4fbdc77687ef' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f89a1017-fa1f-4a3f-8898-4fbdc77687ef' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b7cb565b-887e-4305-a1cd-cc83a6e93c9a' class='xr-var-data-in' type='checkbox'><label for='data-b7cb565b-887e-4305-a1cd-cc83a6e93c9a' 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>initial time of forecast</dd><dt><span>standard_name :</span></dt><dd>forecast_reference_time</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;2015-06-01T00:00:00.000000000&#x27;, &#x27;2015-06-01T03:00:00.000000000&#x27;,\n",
       "       &#x27;2015-06-01T06:00:00.000000000&#x27;, ..., &#x27;2015-06-30T15:00:00.000000000&#x27;,\n",
       "       &#x27;2015-06-30T18:00:00.000000000&#x27;, &#x27;2015-06-30T21:00:00.000000000&#x27;],\n",
       "      dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>step</span></div><div class='xr-var-dims'>(step)</div><div class='xr-var-dtype'>timedelta64[ns]</div><div class='xr-var-preview xr-preview'>01:00:00 02:00:00 03:00:00</div><input id='attrs-6f6b24ca-ac2d-4d75-9f09-6d8aadc2bcd0' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-6f6b24ca-ac2d-4d75-9f09-6d8aadc2bcd0' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d70038d9-5309-4fe7-95a6-012c09840873' class='xr-var-data-in' type='checkbox'><label for='data-d70038d9-5309-4fe7-95a6-012c09840873' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>time since forecast_reference_time</dd><dt><span>standard_name :</span></dt><dd>forecast_period</dd></dl></div><div class='xr-var-data'><pre>array([ 3600000000000,  7200000000000, 10800000000000], dtype=&#x27;timedelta64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>heightAboveGround</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-29a892f4-39b3-4d22-908d-6b57d63ca0f7' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-29a892f4-39b3-4d22-908d-6b57d63ca0f7' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c576b6f4-0c1c-4a3b-9896-a8dbf75e9040' class='xr-var-data-in' type='checkbox'><label for='data-c576b6f4-0c1c-4a3b-9896-a8dbf75e9040' 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>height above the surface</dd><dt><span>units :</span></dt><dd>m</dd><dt><span>positive :</span></dt><dd>up</dd><dt><span>standard_name :</span></dt><dd>height</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>latitude</span></div><div class='xr-var-dims'>(y, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(489, 529), meta=np.ndarray&gt;</div><input id='attrs-2f129ac0-b57c-4d08-82db-e4508e22a666' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-2f129ac0-b57c-4d08-82db-e4508e22a666' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7fd44548-5a1b-497e-95e6-202f6c64fc56' class='xr-var-data-in' type='checkbox'><label for='data-7fd44548-5a1b-497e-95e6-202f6c64fc56' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>standard_name :</span></dt><dd>latitude</dd><dt><span>long_name :</span></dt><dd>latitude</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> 1.97 MiB </td>\n",
       "                        <td> 1.97 MiB </td>\n",
       "                    </tr>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> (489, 529) </td>\n",
       "                        <td> (489, 529) </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Dask graph </th>\n",
       "                        <td colspan=\"2\"> 1 chunks in 2 graph layers </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Data type </th>\n",
       "                        <td colspan=\"2\"> float64 numpy.ndarray </td>\n",
       "                    </tr>\n",
       "                </tbody>\n",
       "            </table>\n",
       "        </td>\n",
       "        <td>\n",
       "        <svg width=\"170\" height=\"160\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\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>longitude</span></div><div class='xr-var-dims'>(y, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(489, 529), meta=np.ndarray&gt;</div><input id='attrs-8bd1d497-3b34-4a28-95e3-e29781272e43' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-8bd1d497-3b34-4a28-95e3-e29781272e43' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-44a49019-7427-4400-9c09-2d49879271ca' class='xr-var-data-in' type='checkbox'><label for='data-44a49019-7427-4400-9c09-2d49879271ca' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>standard_name :</span></dt><dd>longitude</dd><dt><span>long_name :</span></dt><dd>longitude</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> 1.97 MiB </td>\n",
       "                        <td> 1.97 MiB </td>\n",
       "                    </tr>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> (489, 529) </td>\n",
       "                        <td> (489, 529) </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Dask graph </th>\n",
       "                        <td colspan=\"2\"> 1 chunks in 2 graph layers </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Data type </th>\n",
       "                        <td colspan=\"2\"> float64 numpy.ndarray </td>\n",
       "                    </tr>\n",
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       "        </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>valid_time</span></div><div class='xr-var-dims'>(time, step)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(240, 3), meta=np.ndarray&gt;</div><input id='attrs-bfaccb53-5a98-4294-891c-8ac877ed34be' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-bfaccb53-5a98-4294-891c-8ac877ed34be' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-597fa6d9-b734-48f1-9d7f-65fb59335bbb' class='xr-var-data-in' type='checkbox'><label for='data-597fa6d9-b734-48f1-9d7f-65fb59335bbb' 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>long_name :</span></dt><dd>time</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> 5.62 kiB </td>\n",
       "                        <td> 5.62 kiB </td>\n",
       "                    </tr>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> (240, 3) </td>\n",
       "                        <td> (240, 3) </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Dask graph </th>\n",
       "                        <td colspan=\"2\"> 1 chunks in 2 graph layers </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Data type </th>\n",
       "                        <td colspan=\"2\"> datetime64[ns] numpy.ndarray </td>\n",
       "                    </tr>\n",
       "                </tbody>\n",
       "            </table>\n",
       "        </td>\n",
       "        <td>\n",
       "        <svg width=\"76\" height=\"170\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
       "\n",
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       "\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-aa9bac5d-8c6a-420b-a0c0-7d0d68ebca9f' class='xr-section-summary-in' type='checkbox'  checked><label for='section-aa9bac5d-8c6a-420b-a0c0-7d0d68ebca9f' 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, step, y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(194, 1, 398, 432), meta=np.ndarray&gt;</div><input id='attrs-2bc47ac0-7c31-4aaf-ba34-c8744925334a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-2bc47ac0-7c31-4aaf-ba34-c8744925334a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d68ac9b5-8eb9-496a-8ba8-a087436b684e' class='xr-var-data-in' type='checkbox'><label for='data-d68ac9b5-8eb9-496a-8ba8-a087436b684e' 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>K</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> 710.49 MiB </td>\n",
       "                        <td> 127.24 MiB </td>\n",
       "                    </tr>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> (240, 3, 489, 529) </td>\n",
       "                        <td> (194, 1, 398, 432) </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Dask graph </th>\n",
       "                        <td colspan=\"2\"> 24 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=\"432\" height=\"175\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
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       "        </td>\n",
       "    </tr>\n",
       "</table></div></li></ul></div></li><li class='xr-section-item'><input id='section-68486462-a8ee-4913-89e7-0c989bf444dd' class='xr-section-summary-in' type='checkbox'  ><label for='section-68486462-a8ee-4913-89e7-0c989bf444dd' class='xr-section-summary' >Indexes: <span>(2)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>time</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-2998f445-a546-4397-908b-972a50417de7' class='xr-index-data-in' type='checkbox'/><label for='index-2998f445-a546-4397-908b-972a50417de7' 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;2015-06-01 00:00:00&#x27;, &#x27;2015-06-01 03:00:00&#x27;,\n",
       "               &#x27;2015-06-01 06:00:00&#x27;, &#x27;2015-06-01 09:00:00&#x27;,\n",
       "               &#x27;2015-06-01 12:00:00&#x27;, &#x27;2015-06-01 15:00:00&#x27;,\n",
       "               &#x27;2015-06-01 18:00:00&#x27;, &#x27;2015-06-01 21:00:00&#x27;,\n",
       "               &#x27;2015-06-02 00:00:00&#x27;, &#x27;2015-06-02 03:00:00&#x27;,\n",
       "               ...\n",
       "               &#x27;2015-06-29 18:00:00&#x27;, &#x27;2015-06-29 21:00:00&#x27;,\n",
       "               &#x27;2015-06-30 00:00:00&#x27;, &#x27;2015-06-30 03:00:00&#x27;,\n",
       "               &#x27;2015-06-30 06:00:00&#x27;, &#x27;2015-06-30 09:00:00&#x27;,\n",
       "               &#x27;2015-06-30 12:00:00&#x27;, &#x27;2015-06-30 15:00:00&#x27;,\n",
       "               &#x27;2015-06-30 18:00:00&#x27;, &#x27;2015-06-30 21:00:00&#x27;],\n",
       "              dtype=&#x27;datetime64[ns]&#x27;, name=&#x27;time&#x27;, length=240, freq=None))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>step</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-8c215ff8-bf02-49e1-8a3e-b908b8ee750b' class='xr-index-data-in' type='checkbox'/><label for='index-8c215ff8-bf02-49e1-8a3e-b908b8ee750b' 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(TimedeltaIndex([&#x27;0 days 01:00:00&#x27;, &#x27;0 days 02:00:00&#x27;, &#x27;0 days 03:00:00&#x27;], dtype=&#x27;timedelta64[ns]&#x27;, name=&#x27;step&#x27;, freq=None))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-977b050c-abeb-4e57-b13e-c74963dc9d38' class='xr-section-summary-in' type='checkbox'  checked><label for='section-977b050c-abeb-4e57-b13e-c74963dc9d38' class='xr-section-summary' >Attributes: <span>(7)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>GRIB_edition :</span></dt><dd>1</dd><dt><span>GRIB_centre :</span></dt><dd>eidb</dd><dt><span>GRIB_centreDescription :</span></dt><dd>Dublin</dd><dt><span>GRIB_subCentre :</span></dt><dd>255</dd><dt><span>Conventions :</span></dt><dd>CF-1.7</dd><dt><span>institution :</span></dt><dd>Dublin</dd><dt><span>history :</span></dt><dd>2023-04-01T21:49 GRIB to CDM+CF via cfgrib-0.9.10.3/ecCodes-2.28.0 with {&quot;source&quot;: &quot;data/MERA/sample/MERA_PRODYEAR_2015_06_11_105_2_0_FC3hr.grb&quot;, &quot;filter_by_keys&quot;: {}, &quot;encode_cf&quot;: [&quot;parameter&quot;, &quot;time&quot;, &quot;geography&quot;, &quot;vertical&quot;]}</dd></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.Dataset>\n",
       "Dimensions:            (time: 240, step: 3, y: 489, x: 529)\n",
       "Coordinates:\n",
       "  * time               (time) datetime64[ns] 2015-06-01 ... 2015-06-30T21:00:00\n",
       "  * step               (step) timedelta64[ns] 01:00:00 02:00:00 03:00:00\n",
       "    heightAboveGround  float64 ...\n",
       "    latitude           (y, x) float64 dask.array<chunksize=(489, 529), meta=np.ndarray>\n",
       "    longitude          (y, x) float64 dask.array<chunksize=(489, 529), meta=np.ndarray>\n",
       "    valid_time         (time, step) datetime64[ns] dask.array<chunksize=(240, 3), meta=np.ndarray>\n",
       "Dimensions without coordinates: y, x\n",
       "Data variables:\n",
       "    t                  (time, step, y, x) float32 dask.array<chunksize=(194, 1, 398, 432), meta=np.ndarray>\n",
       "Attributes:\n",
       "    GRIB_edition:            1\n",
       "    GRIB_centre:             eidb\n",
       "    GRIB_centreDescription:  Dublin\n",
       "    GRIB_subCentre:          255\n",
       "    Conventions:             CF-1.7\n",
       "    institution:             Dublin\n",
       "    history:                 2023-04-01T21:49 GRIB to CDM+CF via cfgrib-0.9.1..."
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "# view CRS\n",
    "data.rio.crs"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [],
   "source": [
    "# save variable attributes\n",
    "t_attrs = data[\"t\"].attrs"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [],
   "source": [
    "# convert 0/360 deg to -180/180 deg lon\n",
    "long_attrs = data.longitude.attrs\n",
    "data = data.assign_coords(longitude=(((data.longitude + 180) % 360) - 180))\n",
    "# reassign attributes\n",
    "data.longitude.attrs = long_attrs"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Plots"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 864x672 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(9, 7))\n",
    "(data.isel(time=0, step=2)[\"t\"] - 273.15).plot.contourf(\n",
    "    robust=True,\n",
    "    cmap=\"Spectral_r\",\n",
    "    levels=11,\n",
    "    cbar_kwargs={\"label\": \"Temperature [°C]\"},\n",
    ")\n",
    "plt.tight_layout()\n",
    "plt.xlabel(None)\n",
    "plt.ylabel(None)\n",
    "plt.title(f\"time={data.isel(time=0, step=2)['t']['time'].values}\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 864x672 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# specifying lon/lat as the x/y axes\n",
    "plt.figure(figsize=(9, 7))\n",
    "(data.isel(time=0, step=2)[\"t\"] - 273.15).plot.contourf(\n",
    "    robust=True,\n",
    "    cmap=\"Spectral_r\",\n",
    "    x=\"longitude\",\n",
    "    y=\"latitude\",\n",
    "    cbar_kwargs={\"label\": \"Temperature [°C]\"},\n",
    "    levels=11,\n",
    ")\n",
    "plt.xlabel(None)\n",
    "plt.ylabel(None)\n",
    "plt.title(f\"time={data.isel(time=0, step=2)['t']['time'].values}\")\n",
    "plt.tight_layout()\n",
    "plt.show()"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Convert GRIB to netCDF using CDO"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# keep only the third forecast step and convert to netCDF\n",
    "os.system(\n",
    "    f\"cdo -s -f nc4c -copy -seltimestep,3/{len(data['time']) * 3}/3 \"\n",
    "    f\"{BASE_FILE_NAME}.grb {BASE_FILE_NAME}.nc\"\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Read data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "data = xr.open_dataset(\n",
    "    f\"{BASE_FILE_NAME}.nc\", decode_coords=\"all\", chunks=\"auto\"\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "\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:            (time: 240, x: 529, y: 489, height: 1)\n",
       "Coordinates:\n",
       "  * time               (time) datetime64[ns] 2015-06-01T03:00:00 ... 2015-07-01\n",
       "  * x                  (x) float64 0.0 2.5e+03 5e+03 ... 1.318e+06 1.32e+06\n",
       "  * y                  (y) float64 0.0 2.5e+03 5e+03 ... 1.218e+06 1.22e+06\n",
       "    Lambert_Conformal  int32 ...\n",
       "  * height             (height) float64 2.0\n",
       "Data variables:\n",
       "    var11              (time, height, y, x) float32 dask.array&lt;chunksize=(194, 1, 399, 432), 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:      Sat Mar 25 22:55:27 2023: cdo -s -f nc4c -copy -seltimestep...\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-d4f41b57-77be-41d2-a72e-01ee35d842be' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-d4f41b57-77be-41d2-a72e-01ee35d842be' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>time</span>: 240</li><li><span class='xr-has-index'>x</span>: 529</li><li><span class='xr-has-index'>y</span>: 489</li><li><span class='xr-has-index'>height</span>: 1</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-aa199171-0d0e-4572-aa93-190a60af5637' class='xr-section-summary-in' type='checkbox'  checked><label for='section-aa199171-0d0e-4572-aa93-190a60af5637' class='xr-section-summary' >Coordinates: <span>(5)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2015-06-01T03:00:00 ... 2015-07-01</div><input id='attrs-3e49ba2c-9ae7-46cc-b03e-69c8f9d5b84b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3e49ba2c-9ae7-46cc-b03e-69c8f9d5b84b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-cfa65507-bcf5-4494-b1ce-c04327c478b1' class='xr-var-data-in' type='checkbox'><label for='data-cfa65507-bcf5-4494-b1ce-c04327c478b1' 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;2015-06-01T03:00:00.000000000&#x27;, &#x27;2015-06-01T06:00:00.000000000&#x27;,\n",
       "       &#x27;2015-06-01T09:00:00.000000000&#x27;, ..., &#x27;2015-06-30T18:00:00.000000000&#x27;,\n",
       "       &#x27;2015-06-30T21:00:00.000000000&#x27;, &#x27;2015-07-01T00:00:00.000000000&#x27;],\n",
       "      dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>x</span></div><div class='xr-var-dims'>(x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0 2.5e+03 ... 1.318e+06 1.32e+06</div><input id='attrs-3dcc53fe-4400-499f-8c32-7eea29348f43' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3dcc53fe-4400-499f-8c32-7eea29348f43' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-cfcafe83-a714-4dfb-86a5-7ce808989503' class='xr-var-data-in' type='checkbox'><label for='data-cfcafe83-a714-4dfb-86a5-7ce808989503' 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>m</dd><dt><span>axis :</span></dt><dd>X</dd></dl></div><div class='xr-var-data'><pre>array([      0.,    2500.,    5000., ..., 1315000., 1317500., 1320000.])</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'>0.0 2.5e+03 ... 1.218e+06 1.22e+06</div><input id='attrs-91c24980-9473-4dd0-b9ec-f710f9cbb1cf' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-91c24980-9473-4dd0-b9ec-f710f9cbb1cf' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ada5439e-9b96-48a3-aefd-f0560b65f8f0' class='xr-var-data-in' type='checkbox'><label for='data-ada5439e-9b96-48a3-aefd-f0560b65f8f0' 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>m</dd><dt><span>axis :</span></dt><dd>Y</dd></dl></div><div class='xr-var-data'><pre>array([      0.,    2500.,    5000., ..., 1215000., 1217500., 1220000.])</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'>int32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-d1f464dc-17ce-4032-8ccd-f4d12044d347' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d1f464dc-17ce-4032-8ccd-f4d12044d347' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-69614d1a-ed5f-4ed2-ba3e-343173b52930' class='xr-var-data-in' type='checkbox'><label for='data-69614d1a-ed5f-4ed2-ba3e-343173b52930' 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>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>latitude_of_projection_origin :</span></dt><dd>53.5</dd><dt><span>earth_radius :</span></dt><dd>6367470.0</dd><dt><span>false_easting :</span></dt><dd>1481641.6769636814</dd><dt><span>false_northing :</span></dt><dd>537326.0638850163</dd><dt><span>longitudeOfFirstGridPointInDegrees :</span></dt><dd>-14.609</dd><dt><span>latitudeOfFirstGridPointInDegrees :</span></dt><dd>46.834</dd></dl></div><div class='xr-var-data'><pre>[1 values with dtype=int32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>height</span></div><div class='xr-var-dims'>(height)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>2.0</div><input id='attrs-4d3c93c9-e5ba-4b56-b49e-4b3c740414a9' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-4d3c93c9-e5ba-4b56-b49e-4b3c740414a9' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0be643c5-540a-45b3-bb0d-ff518a705ce1' class='xr-var-data-in' type='checkbox'><label for='data-0be643c5-540a-45b3-bb0d-ff518a705ce1' 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></ul></div></li><li class='xr-section-item'><input id='section-4519754c-8bfa-449b-a103-2b866986bb94' class='xr-section-summary-in' type='checkbox'  checked><label for='section-4519754c-8bfa-449b-a103-2b866986bb94' 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>var11</span></div><div class='xr-var-dims'>(time, height, y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(194, 1, 399, 432), meta=np.ndarray&gt;</div><input id='attrs-5deb6d0a-1f58-42c5-8c1f-cede4ed1d26d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-5deb6d0a-1f58-42c5-8c1f-cede4ed1d26d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-460eba3a-b1f3-41dc-a8e6-ca8e167b27e8' class='xr-var-data-in' type='checkbox'><label for='data-460eba3a-b1f3-41dc-a8e6-ca8e167b27e8' 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>table :</span></dt><dd>253</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> 236.83 MiB </td>\n",
       "                        <td> 127.56 MiB </td>\n",
       "                    </tr>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> (240, 1, 489, 529) </td>\n",
       "                        <td> (194, 1, 399, 432) </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=\"432\" height=\"175\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
       "\n",
       "  <!-- Horizontal lines -->\n",
       "  <line x1=\"0\" y1=\"0\" x2=\"54\" y2=\"0\" style=\"stroke-width:2\" />\n",
       "  <line x1=\"0\" y1=\"25\" x2=\"54\" y2=\"25\" style=\"stroke-width:2\" />\n",
       "\n",
       "  <!-- Vertical lines -->\n",
       "  <line x1=\"0\" y1=\"0\" x2=\"0\" y2=\"25\" style=\"stroke-width:2\" />\n",
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       "  <line x1=\"54\" y1=\"0\" x2=\"54\" y2=\"25\" style=\"stroke-width:2\" />\n",
       "\n",
       "  <!-- Colored Rectangle -->\n",
       "  <polygon points=\"0.0,0.0 54.44234404536862,0.0 54.44234404536862,25.412616514582485 0.0,25.412616514582485\" style=\"fill:#ECB172A0;stroke-width:0\"/>\n",
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       "               &#x27;2015-06-01 09:00:00&#x27;, &#x27;2015-06-01 12:00:00&#x27;,\n",
       "               &#x27;2015-06-01 15:00:00&#x27;, &#x27;2015-06-01 18:00:00&#x27;,\n",
       "               &#x27;2015-06-01 21:00:00&#x27;, &#x27;2015-06-02 00:00:00&#x27;,\n",
       "               &#x27;2015-06-02 03:00:00&#x27;, &#x27;2015-06-02 06:00:00&#x27;,\n",
       "               ...\n",
       "               &#x27;2015-06-29 21:00:00&#x27;, &#x27;2015-06-30 00:00:00&#x27;,\n",
       "               &#x27;2015-06-30 03:00:00&#x27;, &#x27;2015-06-30 06:00:00&#x27;,\n",
       "               &#x27;2015-06-30 09:00:00&#x27;, &#x27;2015-06-30 12:00:00&#x27;,\n",
       "               &#x27;2015-06-30 15:00:00&#x27;, &#x27;2015-06-30 18:00:00&#x27;,\n",
       "               &#x27;2015-06-30 21:00:00&#x27;, &#x27;2015-07-01 00:00:00&#x27;],\n",
       "              dtype=&#x27;datetime64[ns]&#x27;, name=&#x27;time&#x27;, length=240, freq=None))</pre></div></li><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-fe85b16e-9367-4154-a2f2-a295f7291782' class='xr-index-data-in' type='checkbox'/><label for='index-fe85b16e-9367-4154-a2f2-a295f7291782' 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([      0.0,    2500.0,    5000.0,    7500.0,   10000.0,   12500.0,\n",
       "                15000.0,   17500.0,   20000.0,   22500.0,\n",
       "              ...\n",
       "              1297500.0, 1300000.0, 1302500.0, 1305000.0, 1307500.0, 1310000.0,\n",
       "              1312500.0, 1315000.0, 1317500.0, 1320000.0],\n",
       "             dtype=&#x27;float64&#x27;, name=&#x27;x&#x27;, length=529))</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-d415e910-9ff6-41f8-9be7-f1126a016b11' class='xr-index-data-in' type='checkbox'/><label for='index-d415e910-9ff6-41f8-9be7-f1126a016b11' 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([      0.0,    2500.0,    5000.0,    7500.0,   10000.0,   12500.0,\n",
       "                15000.0,   17500.0,   20000.0,   22500.0,\n",
       "              ...\n",
       "              1197500.0, 1200000.0, 1202500.0, 1205000.0, 1207500.0, 1210000.0,\n",
       "              1212500.0, 1215000.0, 1217500.0, 1220000.0],\n",
       "             dtype=&#x27;float64&#x27;, name=&#x27;y&#x27;, length=489))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>height</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-241ae69b-105e-42af-831e-1b643a2b0518' class='xr-index-data-in' type='checkbox'/><label for='index-241ae69b-105e-42af-831e-1b643a2b0518' 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([2.0], dtype=&#x27;float64&#x27;, name=&#x27;height&#x27;))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-eba1145a-7444-4bbc-999b-7cd560f4edf5' class='xr-section-summary-in' type='checkbox'  checked><label for='section-eba1145a-7444-4bbc-999b-7cd560f4edf5' 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>Sat Mar 25 22:55:27 2023: cdo -s -f nc4c -copy -seltimestep,3/720/3 data/MERA/sample/MERA_PRODYEAR_2015_06_11_105_2_0_FC3hr.grb data/MERA/sample/MERA_PRODYEAR_2015_06_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:            (time: 240, x: 529, y: 489, height: 1)\n",
       "Coordinates:\n",
       "  * time               (time) datetime64[ns] 2015-06-01T03:00:00 ... 2015-07-01\n",
       "  * x                  (x) float64 0.0 2.5e+03 5e+03 ... 1.318e+06 1.32e+06\n",
       "  * y                  (y) float64 0.0 2.5e+03 5e+03 ... 1.218e+06 1.22e+06\n",
       "    Lambert_Conformal  int32 ...\n",
       "  * height             (height) float64 2.0\n",
       "Data variables:\n",
       "    var11              (time, height, y, x) float32 dask.array<chunksize=(194, 1, 399, 432), 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:      Sat Mar 25 22:55:27 2023: cdo -s -f nc4c -copy -seltimestep...\n",
       "    CDO:          Climate Data Operators version 2.0.5 (https://mpimet.mpg.de..."
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "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": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.rio.crs"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [],
   "source": [
    "# reassign attributes and rename variables\n",
    "data[\"var11\"].attrs = t_attrs\n",
    "data = data.rename({\"var11\": \"t\"})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
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       ".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:            (time: 240, x: 529, y: 489, height: 1)\n",
       "Coordinates:\n",
       "  * time               (time) datetime64[ns] 2015-06-01T03:00:00 ... 2015-07-01\n",
       "  * x                  (x) float64 0.0 2.5e+03 5e+03 ... 1.318e+06 1.32e+06\n",
       "  * y                  (y) float64 0.0 2.5e+03 5e+03 ... 1.218e+06 1.22e+06\n",
       "    Lambert_Conformal  int32 ...\n",
       "  * height             (height) float64 2.0\n",
       "Data variables:\n",
       "    t                  (time, height, y, x) float32 dask.array&lt;chunksize=(194, 1, 399, 432), 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:      Sat Mar 25 22:55:27 2023: cdo -s -f nc4c -copy -seltimestep...\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-326786ed-1a76-420f-9ac2-f4783a8ace9a' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-326786ed-1a76-420f-9ac2-f4783a8ace9a' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>time</span>: 240</li><li><span class='xr-has-index'>x</span>: 529</li><li><span class='xr-has-index'>y</span>: 489</li><li><span class='xr-has-index'>height</span>: 1</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-06f0706b-a9b6-446e-8640-c78636f70050' class='xr-section-summary-in' type='checkbox'  checked><label for='section-06f0706b-a9b6-446e-8640-c78636f70050' class='xr-section-summary' >Coordinates: <span>(5)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2015-06-01T03:00:00 ... 2015-07-01</div><input id='attrs-5674282e-228c-4685-b9ab-e2043d9714cb' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-5674282e-228c-4685-b9ab-e2043d9714cb' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a1bb23e8-d085-4184-b452-664afe0830ad' class='xr-var-data-in' type='checkbox'><label for='data-a1bb23e8-d085-4184-b452-664afe0830ad' 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;2015-06-01T03:00:00.000000000&#x27;, &#x27;2015-06-01T06:00:00.000000000&#x27;,\n",
       "       &#x27;2015-06-01T09:00:00.000000000&#x27;, ..., &#x27;2015-06-30T18:00:00.000000000&#x27;,\n",
       "       &#x27;2015-06-30T21:00:00.000000000&#x27;, &#x27;2015-07-01T00:00:00.000000000&#x27;],\n",
       "      dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>x</span></div><div class='xr-var-dims'>(x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0 2.5e+03 ... 1.318e+06 1.32e+06</div><input id='attrs-2e90b40a-33f4-4043-ae6d-20e0f568fae7' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-2e90b40a-33f4-4043-ae6d-20e0f568fae7' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-979c01cd-c3e6-45a8-8f93-72bfd30ff31b' class='xr-var-data-in' type='checkbox'><label for='data-979c01cd-c3e6-45a8-8f93-72bfd30ff31b' 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>m</dd><dt><span>axis :</span></dt><dd>X</dd></dl></div><div class='xr-var-data'><pre>array([      0.,    2500.,    5000., ..., 1315000., 1317500., 1320000.])</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'>0.0 2.5e+03 ... 1.218e+06 1.22e+06</div><input id='attrs-26ed815e-3bac-44b6-8f66-6fc8c75ce356' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-26ed815e-3bac-44b6-8f66-6fc8c75ce356' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d3b99fda-59f5-4689-9c7a-47ae6cc3aa43' class='xr-var-data-in' type='checkbox'><label for='data-d3b99fda-59f5-4689-9c7a-47ae6cc3aa43' 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>m</dd><dt><span>axis :</span></dt><dd>Y</dd></dl></div><div class='xr-var-data'><pre>array([      0.,    2500.,    5000., ..., 1215000., 1217500., 1220000.])</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'>int32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-f0b189b7-8b2b-4e7a-a3f7-4a0ca4bb2e16' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f0b189b7-8b2b-4e7a-a3f7-4a0ca4bb2e16' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e1adff5f-e407-4aab-9348-a44ca9f8dfcd' class='xr-var-data-in' type='checkbox'><label for='data-e1adff5f-e407-4aab-9348-a44ca9f8dfcd' 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>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>latitude_of_projection_origin :</span></dt><dd>53.5</dd><dt><span>earth_radius :</span></dt><dd>6367470.0</dd><dt><span>false_easting :</span></dt><dd>1481641.6769636814</dd><dt><span>false_northing :</span></dt><dd>537326.0638850163</dd><dt><span>longitudeOfFirstGridPointInDegrees :</span></dt><dd>-14.609</dd><dt><span>latitudeOfFirstGridPointInDegrees :</span></dt><dd>46.834</dd></dl></div><div class='xr-var-data'><pre>[1 values with dtype=int32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>height</span></div><div class='xr-var-dims'>(height)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>2.0</div><input id='attrs-a1acbc04-3a75-482f-8f4b-1c74230d6b18' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a1acbc04-3a75-482f-8f4b-1c74230d6b18' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e7b18dd3-d00a-467a-bd79-ca5082874976' class='xr-var-data-in' type='checkbox'><label for='data-e7b18dd3-d00a-467a-bd79-ca5082874976' 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></ul></div></li><li class='xr-section-item'><input id='section-f0122bdd-8d38-432a-8dd1-8fa17f959442' class='xr-section-summary-in' type='checkbox'  checked><label for='section-f0122bdd-8d38-432a-8dd1-8fa17f959442' 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, height, y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(194, 1, 399, 432), meta=np.ndarray&gt;</div><input id='attrs-c15a2b41-5a52-45c9-9845-9f33c3c04e7d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-c15a2b41-5a52-45c9-9845-9f33c3c04e7d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-38bd119c-255e-4ab4-89d9-8fd7eca0b840' class='xr-var-data-in' type='checkbox'><label for='data-38bd119c-255e-4ab4-89d9-8fd7eca0b840' 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>K</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> 236.83 MiB </td>\n",
       "                        <td> 127.56 MiB </td>\n",
       "                    </tr>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> (240, 1, 489, 529) </td>\n",
       "                        <td> (194, 1, 399, 432) </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",
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       "  <line x1=\"138\" y1=\"105\" x2=\"258\" y2=\"105\" />\n",
       "  <line x1=\"138\" y1=\"125\" x2=\"258\" y2=\"125\" style=\"stroke-width:2\" />\n",
       "\n",
       "  <!-- Vertical lines -->\n",
       "  <line x1=\"138\" y1=\"14\" x2=\"138\" y2=\"125\" style=\"stroke-width:2\" />\n",
       "  <line x1=\"236\" y1=\"14\" x2=\"236\" y2=\"125\" />\n",
       "  <line x1=\"258\" y1=\"14\" x2=\"258\" y2=\"125\" style=\"stroke-width:2\" />\n",
       "\n",
       "  <!-- Colored Rectangle -->\n",
       "  <polygon points=\"138.9485979497544,14.948597949754403 258.9485979497544,14.948597949754403 258.9485979497544,125.87487394219296 138.9485979497544,125.87487394219296\" style=\"fill:#ECB172A0;stroke-width:0\"/>\n",
       "\n",
       "  <!-- Text -->\n",
       "  <text x=\"198.948598\" y=\"145.874874\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >529</text>\n",
       "  <text x=\"278.948598\" y=\"70.411736\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(-90,278.948598,70.411736)\">489</text>\n",
       "  <text x=\"121.474299\" y=\"138.400575\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(45,121.474299,138.400575)\">1</text>\n",
       "</svg>\n",
       "        </td>\n",
       "    </tr>\n",
       "</table></div></li></ul></div></li><li class='xr-section-item'><input id='section-c50bd73d-c7c6-46c3-953b-9bc8273385c7' class='xr-section-summary-in' type='checkbox'  ><label for='section-c50bd73d-c7c6-46c3-953b-9bc8273385c7' class='xr-section-summary' >Indexes: <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-index-name'><div>time</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-ed2ab449-d7b2-40c7-a4de-663ee2175b41' class='xr-index-data-in' type='checkbox'/><label for='index-ed2ab449-d7b2-40c7-a4de-663ee2175b41' 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;2015-06-01 03:00:00&#x27;, &#x27;2015-06-01 06:00:00&#x27;,\n",
       "               &#x27;2015-06-01 09:00:00&#x27;, &#x27;2015-06-01 12:00:00&#x27;,\n",
       "               &#x27;2015-06-01 15:00:00&#x27;, &#x27;2015-06-01 18:00:00&#x27;,\n",
       "               &#x27;2015-06-01 21:00:00&#x27;, &#x27;2015-06-02 00:00:00&#x27;,\n",
       "               &#x27;2015-06-02 03:00:00&#x27;, &#x27;2015-06-02 06:00:00&#x27;,\n",
       "               ...\n",
       "               &#x27;2015-06-29 21:00:00&#x27;, &#x27;2015-06-30 00:00:00&#x27;,\n",
       "               &#x27;2015-06-30 03:00:00&#x27;, &#x27;2015-06-30 06:00:00&#x27;,\n",
       "               &#x27;2015-06-30 09:00:00&#x27;, &#x27;2015-06-30 12:00:00&#x27;,\n",
       "               &#x27;2015-06-30 15:00:00&#x27;, &#x27;2015-06-30 18:00:00&#x27;,\n",
       "               &#x27;2015-06-30 21:00:00&#x27;, &#x27;2015-07-01 00:00:00&#x27;],\n",
       "              dtype=&#x27;datetime64[ns]&#x27;, name=&#x27;time&#x27;, length=240, freq=None))</pre></div></li><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-89cc408b-3f47-4289-bd72-fee8b41baddd' class='xr-index-data-in' type='checkbox'/><label for='index-89cc408b-3f47-4289-bd72-fee8b41baddd' 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([      0.0,    2500.0,    5000.0,    7500.0,   10000.0,   12500.0,\n",
       "                15000.0,   17500.0,   20000.0,   22500.0,\n",
       "              ...\n",
       "              1297500.0, 1300000.0, 1302500.0, 1305000.0, 1307500.0, 1310000.0,\n",
       "              1312500.0, 1315000.0, 1317500.0, 1320000.0],\n",
       "             dtype=&#x27;float64&#x27;, name=&#x27;x&#x27;, length=529))</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-75c792c7-c932-44d6-a104-896140eefba7' class='xr-index-data-in' type='checkbox'/><label for='index-75c792c7-c932-44d6-a104-896140eefba7' 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([      0.0,    2500.0,    5000.0,    7500.0,   10000.0,   12500.0,\n",
       "                15000.0,   17500.0,   20000.0,   22500.0,\n",
       "              ...\n",
       "              1197500.0, 1200000.0, 1202500.0, 1205000.0, 1207500.0, 1210000.0,\n",
       "              1212500.0, 1215000.0, 1217500.0, 1220000.0],\n",
       "             dtype=&#x27;float64&#x27;, name=&#x27;y&#x27;, length=489))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>height</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-d3f65c1b-29aa-4457-9ff9-e4d15e18de6e' class='xr-index-data-in' type='checkbox'/><label for='index-d3f65c1b-29aa-4457-9ff9-e4d15e18de6e' 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([2.0], dtype=&#x27;float64&#x27;, name=&#x27;height&#x27;))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-9d7485f4-fb20-4319-ad8c-6572482ea600' class='xr-section-summary-in' type='checkbox'  checked><label for='section-9d7485f4-fb20-4319-ad8c-6572482ea600' 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>Sat Mar 25 22:55:27 2023: cdo -s -f nc4c -copy -seltimestep,3/720/3 data/MERA/sample/MERA_PRODYEAR_2015_06_11_105_2_0_FC3hr.grb data/MERA/sample/MERA_PRODYEAR_2015_06_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:            (time: 240, x: 529, y: 489, height: 1)\n",
       "Coordinates:\n",
       "  * time               (time) datetime64[ns] 2015-06-01T03:00:00 ... 2015-07-01\n",
       "  * x                  (x) float64 0.0 2.5e+03 5e+03 ... 1.318e+06 1.32e+06\n",
       "  * y                  (y) float64 0.0 2.5e+03 5e+03 ... 1.218e+06 1.22e+06\n",
       "    Lambert_Conformal  int32 ...\n",
       "  * height             (height) float64 2.0\n",
       "Data variables:\n",
       "    t                  (time, height, y, x) float32 dask.array<chunksize=(194, 1, 399, 432), 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:      Sat Mar 25 22:55:27 2023: cdo -s -f nc4c -copy -seltimestep...\n",
       "    CDO:          Climate Data Operators version 2.0.5 (https://mpimet.mpg.de..."
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Plots"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 864x672 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(9, 7))\n",
    "(data.isel(time=0, height=0)[\"t\"] - 273.15).plot.contourf(\n",
    "    robust=True,\n",
    "    cmap=\"Spectral_r\",\n",
    "    levels=11,\n",
    "    cbar_kwargs={\"label\": \"Temperature [°C]\"},\n",
    ")\n",
    "plt.xlabel(None)\n",
    "plt.ylabel(None)\n",
    "plt.title(f\"time={data.isel(time=0, height=0)['t']['time'].values}\")\n",
    "plt.tight_layout()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [],
   "source": [
    "# define Lambert Conformal Conic projection for plots and transformations\n",
    "# using metadata\n",
    "lambert_conformal = ccrs.LambertConformal(\n",
    "    false_easting=data[\"Lambert_Conformal\"].attrs[\"false_easting\"],\n",
    "    false_northing=data[\"Lambert_Conformal\"].attrs[\"false_northing\"],\n",
    "    standard_parallels=[data[\"Lambert_Conformal\"].attrs[\"standard_parallel\"]],\n",
    "    central_longitude=(\n",
    "        data[\"Lambert_Conformal\"].attrs[\"longitude_of_central_meridian\"]\n",
    "    ),\n",
    "    central_latitude=(\n",
    "        data[\"Lambert_Conformal\"].attrs[\"latitude_of_projection_origin\"]\n",
    "    ),\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "data": {
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      "text/plain": [
       "<Derived Projected CRS: +proj=lcc +ellps=WGS84 +lon_0=5.0 +lat_0=53.5 +x_0 ...>\n",
       "Name: unknown\n",
       "Axis Info [cartesian]:\n",
       "- E[east]: Easting (metre)\n",
       "- N[north]: Northing (metre)\n",
       "Area of Use:\n",
       "- undefined\n",
       "Coordinate Operation:\n",
       "- name: unknown\n",
       "- method: Lambert Conic Conformal (1SP)\n",
       "Datum: Unknown based on WGS84 ellipsoid\n",
       "- Ellipsoid: WGS 84\n",
       "- Prime Meridian: Greenwich"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "lambert_conformal"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
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      "text/plain": [
       "<Figure size 864x672 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(9, 7))\n",
    "ax = plt.axes(projection=lambert_conformal)\n",
    "(data.isel(time=0, height=0)[\"t\"] - 273.15).plot.contourf(\n",
    "    ax=ax,\n",
    "    robust=True,\n",
    "    cmap=\"Spectral_r\",\n",
    "    x=\"x\",\n",
    "    y=\"y\",\n",
    "    levels=11,\n",
    "    transform=lambert_conformal,\n",
    "    cbar_kwargs={\"label\": \"Temperature [°C]\"},\n",
    ")\n",
    "ax.gridlines(\n",
    "    draw_labels={\"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",
    "plt.title(f\"time={data.isel(time=0, height=0)['t']['time'].values}\")\n",
    "plt.tight_layout()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Clip to boundary of Ireland"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [],
   "source": [
    "data_ie = data.rio.clip(\n",
    "    ie.buffer(1).to_crs(lambert_conformal), all_touched=True\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       ".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:            (time: 240, x: 158, y: 166, height: 1)\n",
       "Coordinates:\n",
       "  * time               (time) datetime64[ns] 2015-06-01T03:00:00 ... 2015-07-01\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             (height) float64 2.0\n",
       "    spatial_ref        int64 0\n",
       "    Lambert_Conformal  int64 0\n",
       "Data variables:\n",
       "    t                  (time, height, y, x) float32 dask.array&lt;chunksize=(194, 1, 166, 158), 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:      Sat Mar 25 22:55:27 2023: cdo -s -f nc4c -copy -seltimestep...\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-3639dc78-1aeb-4af3-9298-4e8e4b912228' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-3639dc78-1aeb-4af3-9298-4e8e4b912228' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>time</span>: 240</li><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'>height</span>: 1</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-2943e38a-e1b7-4fc7-b84b-8984d2278125' class='xr-section-summary-in' type='checkbox'  checked><label for='section-2943e38a-e1b7-4fc7-b84b-8984d2278125' 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'>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'>2015-06-01T03:00:00 ... 2015-07-01</div><input id='attrs-1806e097-4476-48e4-9d12-3ccb9be15c22' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-1806e097-4476-48e4-9d12-3ccb9be15c22' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-07b04ed4-7eed-410a-adf3-b9e957515482' class='xr-var-data-in' type='checkbox'><label for='data-07b04ed4-7eed-410a-adf3-b9e957515482' 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;2015-06-01T03:00:00.000000000&#x27;, &#x27;2015-06-01T06:00:00.000000000&#x27;,\n",
       "       &#x27;2015-06-01T09:00:00.000000000&#x27;, ..., &#x27;2015-06-30T18:00:00.000000000&#x27;,\n",
       "       &#x27;2015-06-30T21:00:00.000000000&#x27;, &#x27;2015-07-01T00:00:00.000000000&#x27;],\n",
       "      dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>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-8998fbd2-3e65-4cf7-bc53-baac4c7a5d33' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-8998fbd2-3e65-4cf7-bc53-baac4c7a5d33' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7e468fd9-77ce-4341-8c01-8aa0954efb59' class='xr-var-data-in' type='checkbox'><label for='data-7e468fd9-77ce-4341-8c01-8aa0954efb59' 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-d3788a19-40ee-451e-948c-7eb18baac938' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d3788a19-40ee-451e-948c-7eb18baac938' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-30542c87-ceea-47aa-8397-579229ca6440' class='xr-var-data-in' type='checkbox'><label for='data-30542c87-ceea-47aa-8397-579229ca6440' 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 class='xr-has-index'>height</span></div><div class='xr-var-dims'>(height)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>2.0</div><input id='attrs-638cf3eb-7805-48b1-a16c-a74f1ff7a6bc' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-638cf3eb-7805-48b1-a16c-a74f1ff7a6bc' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b9d47e19-2e1d-4cdc-950b-53f63c3229df' class='xr-var-data-in' type='checkbox'><label for='data-b9d47e19-2e1d-4cdc-950b-53f63c3229df' 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>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-3f3a210e-be30-47cc-987a-7d0ccc3385a7' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3f3a210e-be30-47cc-987a-7d0ccc3385a7' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1197d057-fe22-43a2-8ea0-2acaf1f5e3d1' class='xr-var-data-in' type='checkbox'><label for='data-1197d057-fe22-43a2-8ea0-2acaf1f5e3d1' 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>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>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-60055f90-be56-40b1-9d70-f5a489aeee91' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-60055f90-be56-40b1-9d70-f5a489aeee91' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-900501c1-c8fc-4eee-9cf0-6506ff978c8f' class='xr-var-data-in' type='checkbox'><label for='data-900501c1-c8fc-4eee-9cf0-6506ff978c8f' 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-78d724cd-d3f5-4a40-9c10-dcd4a3c56350' class='xr-section-summary-in' type='checkbox'  checked><label for='section-78d724cd-d3f5-4a40-9c10-dcd4a3c56350' 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, height, y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(194, 1, 166, 158), meta=np.ndarray&gt;</div><input id='attrs-ededc552-2510-4ebd-a22a-838361d64fde' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ededc552-2510-4ebd-a22a-838361d64fde' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-adc36a0d-57d3-41c7-9c35-dc60f8a90578' class='xr-var-data-in' type='checkbox'><label for='data-adc36a0d-57d3-41c7-9c35-dc60f8a90578' 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>K</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> 24.01 MiB </td>\n",
       "                        <td> 19.41 MiB </td>\n",
       "                    </tr>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> (240, 1, 166, 158) </td>\n",
       "                        <td> (194, 1, 166, 158) </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Dask graph </th>\n",
       "                        <td colspan=\"2\"> 2 chunks in 6 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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       "</table></div></li></ul></div></li><li class='xr-section-item'><input id='section-5e6ecb6d-ece1-4a5b-99a4-462cb8d9c9a6' class='xr-section-summary-in' type='checkbox'  ><label for='section-5e6ecb6d-ece1-4a5b-99a4-462cb8d9c9a6' class='xr-section-summary' >Indexes: <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-index-name'><div>time</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-8d1c41e5-9f21-49c8-a6c0-42aa68585d70' class='xr-index-data-in' type='checkbox'/><label for='index-8d1c41e5-9f21-49c8-a6c0-42aa68585d70' 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;2015-06-01 03:00:00&#x27;, &#x27;2015-06-01 06:00:00&#x27;,\n",
       "               &#x27;2015-06-01 09:00:00&#x27;, &#x27;2015-06-01 12:00:00&#x27;,\n",
       "               &#x27;2015-06-01 15:00:00&#x27;, &#x27;2015-06-01 18:00:00&#x27;,\n",
       "               &#x27;2015-06-01 21:00:00&#x27;, &#x27;2015-06-02 00:00:00&#x27;,\n",
       "               &#x27;2015-06-02 03:00:00&#x27;, &#x27;2015-06-02 06:00:00&#x27;,\n",
       "               ...\n",
       "               &#x27;2015-06-29 21:00:00&#x27;, &#x27;2015-06-30 00:00:00&#x27;,\n",
       "               &#x27;2015-06-30 03:00:00&#x27;, &#x27;2015-06-30 06:00:00&#x27;,\n",
       "               &#x27;2015-06-30 09:00:00&#x27;, &#x27;2015-06-30 12:00:00&#x27;,\n",
       "               &#x27;2015-06-30 15:00:00&#x27;, &#x27;2015-06-30 18:00:00&#x27;,\n",
       "               &#x27;2015-06-30 21:00:00&#x27;, &#x27;2015-07-01 00:00:00&#x27;],\n",
       "              dtype=&#x27;datetime64[ns]&#x27;, name=&#x27;time&#x27;, length=240, freq=None))</pre></div></li><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-fbfb05ee-f789-4817-9720-c8247a3238e1' class='xr-index-data-in' type='checkbox'/><label for='index-fbfb05ee-f789-4817-9720-c8247a3238e1' 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-84ea6b84-f70f-4c0b-816d-fdddc09d1cb8' class='xr-index-data-in' type='checkbox'/><label for='index-84ea6b84-f70f-4c0b-816d-fdddc09d1cb8' 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>height</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-c32bdd79-96ff-47fb-ab75-309e055ff383' class='xr-index-data-in' type='checkbox'/><label for='index-c32bdd79-96ff-47fb-ab75-309e055ff383' 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([2.0], dtype=&#x27;float64&#x27;, name=&#x27;height&#x27;))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-e96ed2f3-e298-4a37-bdd1-e806b19e86f1' class='xr-section-summary-in' type='checkbox'  checked><label for='section-e96ed2f3-e298-4a37-bdd1-e806b19e86f1' 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>Sat Mar 25 22:55:27 2023: cdo -s -f nc4c -copy -seltimestep,3/720/3 data/MERA/sample/MERA_PRODYEAR_2015_06_11_105_2_0_FC3hr.grb data/MERA/sample/MERA_PRODYEAR_2015_06_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:            (time: 240, x: 158, y: 166, height: 1)\n",
       "Coordinates:\n",
       "  * time               (time) datetime64[ns] 2015-06-01T03:00:00 ... 2015-07-01\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             (height) float64 2.0\n",
       "    spatial_ref        int64 0\n",
       "    Lambert_Conformal  int64 0\n",
       "Data variables:\n",
       "    t                  (time, height, y, x) float32 dask.array<chunksize=(194, 1, 166, 158), 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:      Sat Mar 25 22:55:27 2023: cdo -s -f nc4c -copy -seltimestep...\n",
       "    CDO:          Climate Data Operators version 2.0.5 (https://mpimet.mpg.de..."
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data_ie"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 864x672 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# contour plot\n",
    "plt.figure(figsize=(9, 7))\n",
    "ax = plt.axes(projection=ccrs.EuroPP())\n",
    "(data_ie.isel(time=0, height=0)[\"t\"] - 273.15).plot.contourf(\n",
    "    ax=ax,\n",
    "    robust=True,\n",
    "    cmap=\"Spectral_r\",\n",
    "    x=\"x\",\n",
    "    y=\"y\",\n",
    "    levels=8,\n",
    "    transform=lambert_conformal,\n",
    "    cbar_kwargs={\"label\": \"Temperature [°C]\"},\n",
    ")\n",
    "ax.gridlines(\n",
    "    draw_labels={\"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",
    "plt.title(\n",
    "    \"MERA_FC3hr, \"\n",
    "    + f\"time={str(data_ie.isel(time=0, height=0)['t']['time'].values)[:19]}\"\n",
    ")\n",
    "plt.tight_layout()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "14490"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# find number of grid cells with data\n",
    "len(\n",
    "    data_ie.isel(time=0, height=0)[\"t\"].values.flatten()[\n",
    "        np.isfinite(data_ie.isel(time=0, height=0)[\"t\"].values.flatten())\n",
    "    ]\n",
    ")"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Time series for a point (Moorepark)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [],
   "source": [
    "# transform coordinates from lon/lat to Lambert Conformal Conic\n",
    "XLON, YLAT = lambert_conformal.transform_point(\n",
    "    x=LON, y=LAT, src_crs=ccrs.PlateCarree()\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(579021.4574730808, 472854.55040691514)"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "XLON, YLAT"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [],
   "source": [
    "# extract data for the nearest grid cell to the point\n",
    "data_ts = data_ie.sel({\"x\": XLON, \"y\": YLAT}, method=\"nearest\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "\n",
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       "\n",
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       "\n",
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       "\n",
       ".xr-array-in:checked ~ .xr-array-data,\n",
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       "\n",
       ".xr-dim-list {\n",
       "  display: inline-block !important;\n",
       "  list-style: none;\n",
       "  padding: 0 !important;\n",
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       "\n",
       ".xr-dim-list li {\n",
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       "\n",
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       "\n",
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       "\n",
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       "\n",
       ".xr-has-index {\n",
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       "}\n",
       "\n",
       ".xr-var-list,\n",
       ".xr-var-item {\n",
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       "\n",
       ".xr-var-item > div,\n",
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       ".xr-var-item > .xr-var-name span {\n",
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       "\n",
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       "\n",
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       "\n",
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       "\n",
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       "\n",
       ".xr-var-dtype {\n",
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       "\n",
       ".xr-var-preview {\n",
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       "\n",
       ".xr-index-preview {\n",
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       "\n",
       ".xr-var-name,\n",
       ".xr-var-dims,\n",
       ".xr-var-dtype,\n",
       ".xr-preview,\n",
       ".xr-attrs dt {\n",
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       "\n",
       ".xr-var-name:hover,\n",
       ".xr-var-dims:hover,\n",
       ".xr-var-dtype:hover,\n",
       ".xr-attrs dt:hover {\n",
       "  overflow: visible;\n",
       "  width: auto;\n",
       "  z-index: 1;\n",
       "}\n",
       "\n",
       ".xr-var-attrs,\n",
       ".xr-var-data,\n",
       ".xr-index-data {\n",
       "  display: none;\n",
       "  background-color: var(--xr-background-color) !important;\n",
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       "\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",
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       "\n",
       ".xr-var-data > table {\n",
       "  float: right;\n",
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       "\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:            (time: 240, height: 1)\n",
       "Coordinates:\n",
       "  * time               (time) datetime64[ns] 2015-06-01T03:00:00 ... 2015-07-01\n",
       "    x                  float64 5.8e+05\n",
       "    y                  float64 4.725e+05\n",
       "  * height             (height) float64 2.0\n",
       "    spatial_ref        int64 0\n",
       "    Lambert_Conformal  int64 0\n",
       "Data variables:\n",
       "    t                  (time, height) float32 dask.array&lt;chunksize=(194, 1), 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:      Sat Mar 25 22:55:27 2023: cdo -s -f nc4c -copy -seltimestep...\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-d440de78-428d-4b22-bd8c-022dffa56454' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-d440de78-428d-4b22-bd8c-022dffa56454' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>time</span>: 240</li><li><span class='xr-has-index'>height</span>: 1</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-597fbd89-e858-497c-9d9c-b2111ea9378f' class='xr-section-summary-in' type='checkbox'  checked><label for='section-597fbd89-e858-497c-9d9c-b2111ea9378f' 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'>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'>2015-06-01T03:00:00 ... 2015-07-01</div><input id='attrs-26fd540a-5a74-416a-978d-5e4b6c54a8cf' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-26fd540a-5a74-416a-978d-5e4b6c54a8cf' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d0e11bb1-d06a-4768-bb2c-19ed4edb2b15' class='xr-var-data-in' type='checkbox'><label for='data-d0e11bb1-d06a-4768-bb2c-19ed4edb2b15' 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;2015-06-01T03:00:00.000000000&#x27;, &#x27;2015-06-01T06:00:00.000000000&#x27;,\n",
       "       &#x27;2015-06-01T09:00:00.000000000&#x27;, ..., &#x27;2015-06-30T18:00:00.000000000&#x27;,\n",
       "       &#x27;2015-06-30T21:00:00.000000000&#x27;, &#x27;2015-07-01T00:00:00.000000000&#x27;],\n",
       "      dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>x</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>5.8e+05</div><input id='attrs-e2c6628a-623c-4d19-8d1e-e8f2a35ff9e2' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e2c6628a-623c-4d19-8d1e-e8f2a35ff9e2' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b65071a2-cfba-4527-8849-9edcd0fd4d76' class='xr-var-data-in' type='checkbox'><label for='data-b65071a2-cfba-4527-8849-9edcd0fd4d76' 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(580000.)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>y</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>4.725e+05</div><input id='attrs-73faa581-fdc7-4cea-a2dd-7902d3b94db9' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-73faa581-fdc7-4cea-a2dd-7902d3b94db9' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2a1d16fe-fddb-4bf4-932b-dfc4f26c34ae' class='xr-var-data-in' type='checkbox'><label for='data-2a1d16fe-fddb-4bf4-932b-dfc4f26c34ae' 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(472500.)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>height</span></div><div class='xr-var-dims'>(height)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>2.0</div><input id='attrs-3424cbdd-21ed-4f9f-b223-13420f02d151' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3424cbdd-21ed-4f9f-b223-13420f02d151' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-39e87567-39d4-49cd-869b-4aed0dd60ef9' class='xr-var-data-in' type='checkbox'><label for='data-39e87567-39d4-49cd-869b-4aed0dd60ef9' 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>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-540e3cf1-df60-45ce-9d36-ca8a202455cb' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-540e3cf1-df60-45ce-9d36-ca8a202455cb' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1283042b-8a5a-4585-af7b-cdc873cb0ea7' class='xr-var-data-in' type='checkbox'><label for='data-1283042b-8a5a-4585-af7b-cdc873cb0ea7' 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>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>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-7c91c48d-4c12-4f96-9f0e-1a590262098f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-7c91c48d-4c12-4f96-9f0e-1a590262098f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d75d8352-589d-4e15-8508-7bc4bbb715e6' class='xr-var-data-in' type='checkbox'><label for='data-d75d8352-589d-4e15-8508-7bc4bbb715e6' 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-0cf38483-1664-476d-b0af-1205a282472a' class='xr-section-summary-in' type='checkbox'  checked><label for='section-0cf38483-1664-476d-b0af-1205a282472a' 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, height)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(194, 1), meta=np.ndarray&gt;</div><input id='attrs-ac75f3a7-f3f3-46b4-8a85-c127f3ba1b22' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ac75f3a7-f3f3-46b4-8a85-c127f3ba1b22' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4784d476-0319-4894-83a6-4f71cdc466e3' class='xr-var-data-in' type='checkbox'><label for='data-4784d476-0319-4894-83a6-4f71cdc466e3' 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>K</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> 0.94 kiB </td>\n",
       "                        <td> 776 B </td>\n",
       "                    </tr>\n",
       "                    \n",
       "                    <tr>\n",
       "                        <th> Shape </th>\n",
       "                        <td> (240, 1) </td>\n",
       "                        <td> (194, 1) </td>\n",
       "                    </tr>\n",
       "                    <tr>\n",
       "                        <th> Dask graph </th>\n",
       "                        <td colspan=\"2\"> 2 chunks in 7 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=\"75\" height=\"170\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
       "\n",
       "  <!-- Horizontal lines -->\n",
       "  <line x1=\"0\" y1=\"0\" x2=\"25\" y2=\"0\" style=\"stroke-width:2\" />\n",
       "  <line x1=\"0\" y1=\"97\" x2=\"25\" y2=\"97\" />\n",
       "  <line x1=\"0\" y1=\"120\" x2=\"25\" y2=\"120\" style=\"stroke-width:2\" />\n",
       "\n",
       "  <!-- Vertical lines -->\n",
       "  <line x1=\"0\" y1=\"0\" x2=\"0\" y2=\"120\" style=\"stroke-width:2\" />\n",
       "  <line x1=\"25\" y1=\"0\" x2=\"25\" y2=\"120\" style=\"stroke-width:2\" />\n",
       "\n",
       "  <!-- Colored Rectangle -->\n",
       "  <polygon points=\"0.0,0.0 25.412616514582485,0.0 25.412616514582485,120.0 0.0,120.0\" style=\"fill:#ECB172A0;stroke-width:0\"/>\n",
       "\n",
       "  <!-- Text -->\n",
       "  <text x=\"12.706308\" y=\"140.000000\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >1</text>\n",
       "  <text x=\"45.412617\" y=\"60.000000\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(-90,45.412617,60.000000)\">240</text>\n",
       "</svg>\n",
       "        </td>\n",
       "    </tr>\n",
       "</table></div></li></ul></div></li><li class='xr-section-item'><input id='section-2d726a92-81b7-471b-a0c2-51254e87d746' class='xr-section-summary-in' type='checkbox'  ><label for='section-2d726a92-81b7-471b-a0c2-51254e87d746' class='xr-section-summary' >Indexes: <span>(2)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>time</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-c6df8e73-0760-43f5-9930-958f171a53db' class='xr-index-data-in' type='checkbox'/><label for='index-c6df8e73-0760-43f5-9930-958f171a53db' 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;2015-06-01 03:00:00&#x27;, &#x27;2015-06-01 06:00:00&#x27;,\n",
       "               &#x27;2015-06-01 09:00:00&#x27;, &#x27;2015-06-01 12:00:00&#x27;,\n",
       "               &#x27;2015-06-01 15:00:00&#x27;, &#x27;2015-06-01 18:00:00&#x27;,\n",
       "               &#x27;2015-06-01 21:00:00&#x27;, &#x27;2015-06-02 00:00:00&#x27;,\n",
       "               &#x27;2015-06-02 03:00:00&#x27;, &#x27;2015-06-02 06:00:00&#x27;,\n",
       "               ...\n",
       "               &#x27;2015-06-29 21:00:00&#x27;, &#x27;2015-06-30 00:00:00&#x27;,\n",
       "               &#x27;2015-06-30 03:00:00&#x27;, &#x27;2015-06-30 06:00:00&#x27;,\n",
       "               &#x27;2015-06-30 09:00:00&#x27;, &#x27;2015-06-30 12:00:00&#x27;,\n",
       "               &#x27;2015-06-30 15:00:00&#x27;, &#x27;2015-06-30 18:00:00&#x27;,\n",
       "               &#x27;2015-06-30 21:00:00&#x27;, &#x27;2015-07-01 00:00:00&#x27;],\n",
       "              dtype=&#x27;datetime64[ns]&#x27;, name=&#x27;time&#x27;, length=240, freq=None))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>height</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-9691a873-5961-409b-9d2c-d05ca92d27bd' class='xr-index-data-in' type='checkbox'/><label for='index-9691a873-5961-409b-9d2c-d05ca92d27bd' 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([2.0], dtype=&#x27;float64&#x27;, name=&#x27;height&#x27;))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-a6fefad5-67bd-41eb-9023-a0dc6b96f2a0' class='xr-section-summary-in' type='checkbox'  checked><label for='section-a6fefad5-67bd-41eb-9023-a0dc6b96f2a0' 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>Sat Mar 25 22:55:27 2023: cdo -s -f nc4c -copy -seltimestep,3/720/3 data/MERA/sample/MERA_PRODYEAR_2015_06_11_105_2_0_FC3hr.grb data/MERA/sample/MERA_PRODYEAR_2015_06_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:            (time: 240, height: 1)\n",
       "Coordinates:\n",
       "  * time               (time) datetime64[ns] 2015-06-01T03:00:00 ... 2015-07-01\n",
       "    x                  float64 5.8e+05\n",
       "    y                  float64 4.725e+05\n",
       "  * height             (height) float64 2.0\n",
       "    spatial_ref        int64 0\n",
       "    Lambert_Conformal  int64 0\n",
       "Data variables:\n",
       "    t                  (time, height) float32 dask.array<chunksize=(194, 1), 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:      Sat Mar 25 22:55:27 2023: cdo -s -f nc4c -copy -seltimestep...\n",
       "    CDO:          Climate Data Operators version 2.0.5 (https://mpimet.mpg.de..."
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data_ts"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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bIYoi5syYgQduuaXHgOlXV12Fm/74R1z229/i+osvloc4v7vuOvk2Y4qLsWXXLvzn00/x66uvRltHB+5/5hkAQI0Bzx9BEAQxNKC6c4IgCGLYEQgEcMzs2WhoacGmHTvw9erVEEURc488Et3hxVEs2js7UV1fL//X0Nwc83ZPvvwyZs6fjyMvuQQ3PvAAWtraMGnMGFx13nnybVaF83RmTJ4Mu82GMUVFyMvORmNLCzbHaO9RyqW/+Y1cKz1z/nzZqtLS1iYv/PLCu/v94Q8E5KEOICmPYg2+UhwO3HvjjXCmpiLD5cLMsL2jvqmp7/GddZbuoQ4A/LhzJ6rr6+FOT8cNl14Ki8UCd0YGbg1Xr3/2v//1uc85c+di7hFHgOM4HBfOkBFFMe7zqBaX04kL5s1DMBTCfz79FFfceSdsVitOO/ZYVT9n+969WPz113DY7fjpmWfKX2fKr7+8/DIWLV6MYCiEipoaPPv663jpv//t8TNCgiAPdQBJ+RH9XAKSdWdscTH2V1Xht489hlc//BCnH3us3M4EAJeGf/+jL7yA4y+/HKddey0EUQQgqUD0ctyhh+LCefPgTE1Fc2urrCrp9nrlgG+9sNd9Z3c3Nu/ahUAwiL0VFXj0hRfwYq/HLZonX3oJgGSNipXLoxb2/L3+0Ud4btEieP1+1DQ04LUPP8Rj//xnn9u3tLVBDD/W3V6vfH/GzGnTMGPyZNQ3NeGPf/87nnjxRRw9a1YPJRx7/l754AMcc+mlmHvllWgM27l6vx4IgiCI4QsNdgiCIIhhhz8QkO0Q32/YgJVh5czxc+bEDU4GgF9fdRU2vP++/N9bf/lLzNtluFwoys+XQ5BPOeoovPLYYz1yX74K27Ci1QdM0cO+p4W8rCwU5efL/7HWLndGBhx2OwCgSeGC+dADD8Q3r72G1x5/HKccdRQ++fprXHr77fD0Gu7wvdRFzLITawgUrUDRw96KCgCSpSjaGjZtwgQA0qK1tqEh7nFGKx8SqbR68+POnTjjuut6/Pfjzp0AgEWffIKHn38e9914I156+GEcM3s2mlpbccWdd6IuKvckER6fD//3zDMICQJ+dsEFcv4PALjYMXMcPn3hBXzz2mu4Pxys/ObHH/f4OUX5+fj2jTfw9l//ip+cfjq+W78eP7ntNtSHh1jNbW24Mjx4+uT553HzZZchKzMTC99+Gwvfekv+OVdfcAFuvPRSlIwaBQvP49KzzsJt4eGZEcMOj9eLl/77X5x1/fWYe9VV+M1jj8nf09uExcjOzMTz99+P1x5/HF+/+iq+feMNzD/pJADAv955B4Ig9LnPkm++wZcrVyI7M7NPBo5WWL5Pe2cn3n36aXz96qt4/v77wfM8PvjyS7m5i/H9okV4/9lncf3FF2Pr7t249PbbsX3vXgCS4u/6e+9FZW0t3nvmGfz++utRmJeHj5cvlxU5AHDmCSfg7l/+EuNGjwbP8zjj+OPxx1tvBWDM80cQBEEMDciKRRAEQQxLjjrkELicTqxYtw4VNTU4etasuMGqamGtWO8sXYoH//EPbNm9G5aoqmtRFPHN2rUAgOffegvPRy2kASl75+bLLtP0u+O1YvE8j9LCQuwqK8PO/fvjNmf1JsPlwoGTJuHR22/Hph07UNPQgP+tW5fQAmO0jSwWYryvi/G+0z9KwpOL8vP73Mbn96Ojqwt/+fe/MbG0FOedcgoA4JkDDsAjCxfircWL8fpHH/UJOY517Hf/5S/YvncvjjrkEPz8oot6fL8oPx9b9+zBHddei4LcXADAuSedhCdefBHNbW1o7+zsMTx0OZ2YPHYsfn/99di+dy827diBT7/5BlfMn4/XPvwQeysr8eRdd6G4oADXXHghTj/uOJx/881Y+J//4OIzzkBmejqsFgt+Hm5wYnzy9dcApCBlPQRDIdz28MNYtWkTxhYX49YrrsABEybg+vvuU3T/D5ctUxyefPjBB8tft9tsuOXyy/H+l1/C6/Ohsq4OpYWF8vc37diB/3vmGVgtFjz229/KKiK9MDveDZdeigklJfJxTRozBjv27UN5TU0Py1dqSgrGFhfjlz/9Kcqqq/HpihV4/4svcNd11+Gj5cuxfts2/OZnP8O40aMxbvRonHbssfjJbbfh/S+/xGXnnIOJY8YAkBRH0YHM67dtA6D/+SMIgiCGDjTYIQiCIIYldpsNJx5+OD5avhyAlEFiNOfOnYt/vfMOquvr8dbixbj83HMBAJt37UJjSwvsNhvGjR4t314URezcvx+7y8tRWVuL0eGgW6M4dMYM7Corw2sffohz5s6V81Zi0dzW1mNBa7FYkJmejrqmpj6WkIGALYz3lJf3aOliioa01NQeahclKAlPPvTAA7EhnJkUzZbdu+Hz+zEqPHBhHHHwwXhr8WLsUxBU+8SLL+LLlSsxbvRoPHr77X2enzHhhfim7dtlu5soigiGQrDwvKwQ6/3cAZD/zZ67XWVlANDjeIvy8zGmqAg79u1DZV1dn/BpxmfffgsAui112/bswapNm5Cfk4M3n3yyT8ZMNOyx8AcC8teUhifHyqxiocgA4I76O8uqqnDbww/D5/fj99df30NRpxf5+duxA2ccf3zkWMJ/EwtvjvX8ZSl4/jJcLkybMAG1jY3YV1UlD3Z6Y9TzRxAEQQwdyIpFEARBDFvYMMdht5vSRGWz2XDNhRcCkIKX2zs7AQBfr1kDADh+zhy89Ze/yP+9/de/YmJpaY/bGMn1P/kJMlwu7C4vx68eeUS2BzW1tuK+p5/G3155BYBkBZt/441Y+u23cj7Jx8uXy4vJ6QbZqRhvL1mCK++6S27tioU13CjWFbarzJg8GYV5eWjt6MDf33gDoVAIbR0d8t+gZVD30iOPYPHChXH/S6RSKi0sBM/z+G7DBrntrLahAe8sXQoAGBvOPRFFEbc9/DAuuOWWHsqfp197Da9/9BEKcnLw9/vu66G8YVxw6qmwWq145YMPUBYeFL35ySfweL2YPHYs7DYbtu3Zg7Ouvx5vL1kiv95WbtyI79avBxB57saFhwzPvvEG2js7EQyF8MV332FPeTk4jpMVLNX19XjypZfQ2d0NQRDwztKlWLFuHUYXFPRod9LyHLJsI7/fj2AwiEAwiFdiDM2ASGvYyo0b5a+dfNRRCZ8vFob9j0WL8Js//UkOL+72ePDnF18EIFn52GNdVVeH6+69F81tbbju4ovxk9NPj3ksDz33HM66/npsDVeJK+X0Y49FZno63v/iC7l576vVq7G3shJZGRkoLihAbUMD5t94Ixa+9Raaw1a07Xv3YklYJdX7+Xvx3XdR39wMURSx5scfsebHHwFEXm/tnZ14dOFC2da2fNUqvPf553A5nXH/PoIgCGL4QYodgiAIYthyxMyZOGjKFEybMCFm1XFverdiAf03Y5170kl48d13UV1fjxfffRe3XXmlvPCPNUw6bs4c7C4vx9erV2PB2Wer/IsS487IwB9vuQV/+Otf8fWaNfh6zRpkuFzyAGD29OnwBwJobW9Ht9eLO594AlarFSl2uxy0et7JJ2Py2LGGHZMgCPjrv/+Nbq8Xf37pJRwze3bM240pKsKe8nLc9vDDWPLCC8hwufD766/Hrx59FC+/9x7eXrJErucelZuLW8I5MMkiPS0NV5x7Ll5+7z3c+vDDSE9LQ2d3N0RRRGZ6Oi4NP5f7q6rkDKXv1q/HhfPm4c2PP8a/3nkHAGCzWnHrQw/1CLb99VVX4eSjjkJRfj6uOPdcvPjuu5h/001IT0tDe2cnOI7DbeG2MhY4/PDzz+PRF15AelqaHKJ8+MEHy6HRl551Fj5avhz/++EHzL3ySjjsdnngcuX8+XL+yhMvvohlK1fi9Y8+gsNuR7fXC4fdjjuuvVZuk9L6HM6YPBkpDgdaOzow98orYeF5hAQBmenpPYKfAWkIur+qCq+8/z4+XbEC586dixvD7V2JEEUR+ysr8cX33+OL779HeloaPD4fgsEgrBYL7r3hBgDSsOnn99yDuqYmWC0WfL9+PT5dsQLBcOZWQU4OXnrkEXh8Prz72WcQBAFffP+9bGm8+ne/Q11Tk6wo8vh8OCPcTvWn3/wGMyZPhjM1FTctWICHn38eV9x5J9zp6WgN/523XnkleJ5HU1sbrBYL/v7mm/jHokXIdLnk20Tb/M468US88ckn2LpnD0679lo4U1Lk18zJRx2FSeH36MK338aixYvx1pIlSEtNRWd3t9SIds01MYeHBEEQxPCEBjsEQRDEsMVmteKVP/1J8e3bOzvlIQijvwBSm9WKay+6CA88+yze/OQTHDN7NnaVlYHn+ZgL4OPmzMGL776LH7Zu7ZOZYgTHH3YY/vO3v+G5RYuwZdcu1DQ0YOa0aTh61iy5Mnv+ySdj7OjReOHtt7Fl1y74AgFMGTcOF5x6Ks4/9VRDj4fnecw/+WS8/emnCfNtbr/6avzx739Hl8eDusZGZLhcOPbQQ/HKo4/imddfx5bdu5GVmYnDDzoIt15xRVwbkZnccvnlGFtcjLeXLMH+qioU5ORg5rRpuPHSS1EYtoWNLS7G8XPmoKK2VrbCbAvbxwCgsq6uz8+Nbmq75fLLUZiXh/9+9hnKa2pw0JQpuGnBAhx20EEAgGMPPRSvPv44nnvzTfywdSu6ursxobQUpx17LC4/5xzZ0jQqLw+vPvYY/hG+XWtHB6aNH48LTzsN5518svz7HrjlFhTk5GDVxo1obG3F0bNm4ReXXIIZkyfLt9H6HE4aOxZP3HEHnnz5ZTQ0N+PgqVNx04IFePm99/DpihU97vuLSy5Ba0cHvlm7FhaeB5fARhgNx3F47Le/xVGHHIJ3li7FvspKZKSl4cBJk3DTZZfJQ8q2jg752IOhkByI3ZtUhwMXnHoqvlu/HicdeaT89bqmph5/uyiK8r99fr/89YtOOw3ZmZl45YMPsLusDFPHj8fV558vq5+mT5yIN598Es++/jpWbtyI1vZ2jCkqwvFz5uDaiy6S7WoupxMvP/wwnnvrLXy/fj0aWlowsbQUZ55wQo+B8K2XX45UhwPfrF2Lqro6HHrggbjqvPPiDt8IgiCI4Qkn6kkhJAiCIAiCUMDtjz6KnWVl+Ogf/xjoQyE0Qs8hQRAEQQxOSLFDEARBEAPEky+/jC+++y7hbZjNYyizdvNmrFi3Dledd95AHwqhEXoOCYIgCGLwQoMdgiAIghggWtvbE1pbgJ42j6HIph07cN299+KgKVNoKDBEoeeQIAiCIAY3ZMUiCIIgCMI0PD4f3l26FD85/XS5spwYWtBzSBAEQRCDGxrsEARBEARBEARBEARBDFGUVQ4QBEEQBEEQBEEQBEEQgw7K2AnT3tmJdVu2YFRuLmwkMyYIgiAIgiAIgiAIYgAJBAKobWzE7OnTkeFyxb0dDXbCrNuyBb965JGBPgyCIAiCIAiCIAiCIAiZv/zudzjx8MPjfp8GO2EKcnMBSA9YSWHhAB8NQRAEQRAEQRAEQRAjmYqaGvzqkUfkeUU8aLAThrU8lBQWYmJp6QAfDUEQBEEQBEEQBEEQBPptpaTwZIIgCIIgCIIgCIIgiCEKDXYIgiAIgiAIgiAIgiCGKDTYIQiCIAiCIAiCIAiCGKLQYIcgCIIgCIIgCIIgCGKIQoMdgiAIgiAIgiAIgiCIIQoNdgiCIAiCIAiCIAiCIIYoNNghCIIgCIIgCIIgCIIYotBghyAIgiAIgiAIgiAIYohCgx2CIAiCIAiCIAiCIIghinWgD4DR3tmJv7/xBr7fsAHtXV04bMYM/OZnP0NedjYAIBQK4W+vvILPv/sONpsN8086CT+74IKEP1PLfQiCIAiCIAiCIAiCGFz8UNWF7Q1e/PTgbHAcN9CHM6gYFIOd1vZ2XHv33XClpeHnF10EjuPwjzffxK0PPYTXHn8cPM/jsX/9C599+y1+ffXV8Hi9ePKll2CxWHDl/Plxf66W+xAEQRAEQRAEQRAEMbi4c0klylv9GJ/twBGlroE+nEHFoBjsZLhcuHDePFwwbx5sVumQigoKcPXvfoctu3ejtLAQ733+OR761a9wylFHAQC6vV689sEHuOzss2GxWPr8zLaODtX3IQiCIAiCIAiCIAhicFHT7kd5qx8AsGxPOw12ejEoMnZ4nsclZ54pD3UAYOq4cQCAusZGfLN2LTiOw7GzZ8vfP/nII9HQ0oKN27fH/Jla7kMQBEEQBEEQBEEQxOBiTWWX/P/L93RAFMUBPJrBx6AY7MRiV1kZAGB8SQlqGxpQkJuLFIdD/v7oUaNgtVhQ09gY8/5a7kMQBEEQBEEQBEEQxOAierBT3urHnibfAB7N4GPQDnb++9lnGD96NMYWF6OxtRWZrr5SqwyXC40tLTHvr+U+BEEQBEEQBEEQBEEMLtZUdgMAJuVIwo1lezoG8nAGHYNysLNh+3Z8sGwZbr3iCvA8Dw6IKbUSAfBx0rC13IcgCIIgCIIgCIIgiMFDQ1cA+5p9cNp4/PLIfADA8r3tA3xUg4tBN9hpbGnBnY8/jnPnzsXxhx0GAMjJykJbZ2eP24miiPaODuRmZcX8OVruQxAEQRAEQRAEQRDE4GFtWK1zSJETx49Ph83CYX1VN5q7gwN8ZIOHQTXY8fn9+NUjjyAnKwu//8Uv5K8X5eWhrrERHq9X/lp5TQ1CgoDC/PyYP0vLfQiCIAhiIBBFEd6AMNCHQRAEQRAEMehYUyEJNg4dnQaX3YLDS9IgAvh6L9mxGINmsBMIBvGbxx5Dc1sbnvrDH2C32eTvHTdnDjiOw9dr1shf++K771CQk4ODJk+Wv9bR1aX6PgRBEAQx0DzxTS0Oe3Yr9jVTECBBEARBEEQ0LF/nsJI0AMDcCRkAgOV7yI7FsPZ/E/MRBAH3/O1vWLNpEx7+9a9RVVeHitpaAIDdZsP0iRNx4bx5eHThQvgDAXi8Xix8+23ccvnl4HlpNvXmxx/jsX/9C0/edRdOPPxwpKel9XsfgiAIghgMbKjphi8oYvmedozLzhvowyEIgiAIghgUtHiC2Nnohd3CYcaoVADACePT8cCXwIr9nfAHBdittL4fFIOd9du24dMVKwAAv3700R7fK8rPx+KFC3H71VfDarHgH2++CZvNhl9ccgkWnH22fLtstxu5bnePJqz+7kMQBEEQg4Euv2TDWlvVjZ/NGeCDIQiCIAiCGCSsq5LUOjMLnXCEBzjFmXZMzUvB9gYvVlV04dhx6QN5iIOCQTHYmT19Oja8/37C2/A8j19ddRV+ddVVMb8/75hjMO+YY1TdhyAIgiAGA2yws66qC4IoUnsjQRAEQRAEeubrRHPihHRsb/Bi+Z52GuxgEGXsEARBEMRIhQ12Wj0h7G2inB2CIAiCIAigb74Og+XsLNvTAVEUk35cgw0a7BAEQRDEANPlD8n/v7aqK8EtCYJIJhtruvHrj8tR1xkY6EMhCIIYcXT4QthW74GVBw4udPb43oGjUpGXZkVNRwC7GmlTjAY7BEEQBDGABAUR3mBkp2lteGeKIIiB57X1Tfhkexv+/n39QB8KMYD8YWklzn55FzwBYaAPhSBGFD9UdUMQgRmjnHDae44ueI7D1LwUAEB1u38gDm9QQYMdgiAIghhAuv09FwrrKkmxQxCDhebuIADggy0taPeG+rk1MRwRRBGfbGvFzkYvNtd6BvpwCGJEsTZ8TdQ7X4eR5ZQig1s8dH6mwQ5BEARBDCDMhpWXZkWGg0d1R4B2nghikNDikQY7nqCI97a0DPDREANBfWcQnrCqcmejd4CPhiBGFmvCg5058QY7qRYAkXP1SIYGOwRBEAQxgLDg5HSHBbOKpQuXtaTaIYhBQUt3ZBf4jQ1NECigc8SxvyWS3bGDBjsEkVTKwu+/qfkpMb/vTiHFDoMGOwRBEAQxgHSGBztpdh6z2WCninJ2CGIw0BzeBc51WrG/xY9v93cO8BERyaasJaKg3NlAg52BosMXwqc72uAPUs7RSEEQRbSGLbDZqdaYtyHFTgQa7BAEQRDEAMKsWGl2HoeOlhofKGeHIAYeT0CANyjCbuFwxewcAMDr65sG+KiIZBOt2NnV6KVa5QGg0x/ClW/vw60flePdzWSJHCm0eUMQRCDDwcNm4WLeJis88GmlDDQa7BAEQRDEQNIlK3YsOHBUKhxWDrubfLT7RBADDAtOznZacdGMbNgtHL7e24HyVqrVHUmUtUYUO51+AdXtgQE5jpE6UPIHBdz0fhm21EnB1VvrKcB6pBB9Do4HKXYi0GCHIAiCIAaQrigrlt3C4+BRYdUO2bEIYkBhmQ1ZqRZkO604c2omRABvrG8e2AMjkgrL+GALyIEIUF5b2YUDntyM90dYgHdIEHHHkkp8X94Fa3jVureZBqsjhcg5OP5gxx3+XnQe2kiFBjsEQRAEMYDIViyb9JE8m+xYRJjX1zfhb9/WDfRhjFhYvg7LdlhwiGTHendzM7r9lPMxEggJIsrDip2TJmYAGJjBzndlnRBE4KNtrUn/3QOFKIp4aFk1luxoQ5qdx9PnjgEA7Gmiwc5Igalw2FA1FqTYiUCDHYIgCIIYQLoCEcUOABw6mpqxCKDbL+Dh5dX4+8p6VLb5+78DYTi9FxUzRjkxszAV7T4Bn+1qG8hDI5JETUcA/pCIvDQrZhZJQ/eBCFCu65TsXz/WekaMJes/P7bg9Q3NsFk4/H3+GJw4Ph1OG48WT0i26BDDm+ZuJYod6fws5fGMjPdGPGiwQxAEQRADCLNiuRzSxcnMIid4TsoRIFXAyGV9dRdY+Ut5Kw12BoJYNoBTJmUCkBbYxPCH2bDGZNkxJVeqWx4IxU5dhzTYafOGRsz5YPmedgDA704oxBGlLnAch3HZDgBkxxopsOF6oowdu4WHy84jJAIdvpF9zUSDHYIgCIIYQKIzdgDAZbdgWn4qggKwsZZydkYqqysiiq3oVh4iebSEVQFZzogNYHLewC3uieSzP1x1PsbtwMScFHCQhgr+UHIXkHWdEYXKxpqR8blQER5gHRJWSgHAhBwa7IwkmhVYsaTvh3N2RrgdiwY7BEEQBDGA9M7YAYDJudLFaxVZcEYsq6IGO+Ut9DoYCGIpdiZHqTZGiiVmJFMWbkAbm+WA086jxG1HUAD2NSf3PVnfGWni2jQC1GKCKKI8/PlX6rbLXx/PFDuUszMiYFas7ARWLCBix6LBDkEQBEEQA0Z03TmDyY4pR2Bk0u0XsDlq8baf6rUHhN7hyQBQ4LIi3cGj1RNCI70/hz1l4aHq2CxpuDB5AOxY3oCAVm+k8efHEaDYaegMwhcUkZ1qkW3KADAhPNjZ00yKuZFAxIrVn2JH+n6rZ2Q3Y9FghyAIgiAGkM5eViwAyAkPdppo4Tgi2VDTjYAgwhV+TZSRYmdAiNXIwnGcvLjf1Wj+wE0URby+vonC1AeI/XLGjjRQkAc7SQxQru+S1DruFOl1uLXem3QrWLJhSqlotQ5AVqyRRuQcnFixE7Fi0WCHIAiCIIgBQrZixRzsjOyLlJHKqopOAMBZ09wAgIo2P0IC2X6SjWwD6BXcOSmJi/v11d144Mtq3P9Ftem/i+hJUBDlRjo2YBiIjKX6cL7OuGwHxmU74A+J2DEAzVzJhAVEl4YHaowStx0WDqhqC8AbMHe4FQiJ+N2nlXj3x2ZTfw8RnxYFrVjS98mKBdBghyAIgiAGFLJiEb1hwcknjE9HvsuKQEhETUegn3sRRhNLsQMk146zJqzUqWon1VayqWrzIygAo9JtSA1noLH8s2QqdljVeb7LioNHpQIANtUM75wdFpxcmtlTsWO38CjNckAEsM/kUPl1VV347+YWPPVdvam/h4iPHJ7cjxXLTYodADTYIQiCIIgBpXcrFkBWrMHC9nqP6bvCven2C/ixxgOeA2YXp2GMW1pIjpSK48FCSBDlvAZ3r93iiBUrCYOd8JCvyy+g0zeyFy3JJtKIFRkujMlywG7hUN0RQEeSng9WdV7gsuGgQqkh6sdh3phYJit27H2+NyFJlefb6qXhWW0Sn+v+aPeGsKaia0QEt3sCArxBEXYL16NcIhak2JGgwQ5BEARBDCCJrVgj+yJlIHlpbQPOfWU3nlhRm9Tfy/J1puWnIiPFgjHhhQ1VnieXNm8IIoDMFAusPNfjexPDqo3dTT4IJi6wQoKIH6ojC/i6TlJtJRO5ESs7Ygey8hwmhnNekmXHiih2bJgRVuxsHOaKHdmK5e472GHNWHtMbsbaVh95fnc3Dbz1rarNjwte243L3torqzqHM0yxnO20guO4hLdlVi0KTyYIgiAIYkAQRTGmYic7avdpJOzMDTZ+rO3Gn7+pAwD8b39nUn83y9c5vCQNAGTFThkNdpJKPBuW9DUr8tKs6A4IqGozb9iyvcErnx8ASTlAJA+5EavXcCHZAcp14YydApcVU/NTYLNw2NvsGzQqEqMRRRHlLDw509Hn+8kKUO452BnY8+++Zh8WLNorD7yij2240pzgHNwbUuxI0GCHIAiCIAYIX1BESARsFg52S+Qj2W7lke7gERSAdt/wbj8ZbHT6Q7j94woEwmHFe5t9aPcmbwHFrDeHscFOWLFTRlaspMKyGuKFdk5JQohu7yYstsAnkkPvRixGsgOUmWKnwGWD3cLjgHzp92+uHZ6qnVZvCB0+AWl2PmbNdTIUO76ggL1Rleq7kxiW3ZudDV5ctmgvajoCSLVKyhWmJhvOsHNwdj/ByQC1YjFosEMQBEEQAwTbjXfZ+34ckx1rYHjgi2qUtfoxNS9FXkBtSlKehScgYFONBxykfB0garBDledJJZFiBwAm5Zi/uF8XHuzkpUnnArJiJRdZsZMVR7GTrMEOy9hJtwEADhol5exsrBmeOTsVUTasWBYcNtjZ3+IzrS1wd5MPQaHnvweCbfUeXP7WXjR2B3FkaRoeOm00gJGRucasWEoUO25S7ACgwQ5BEAQxyKhu9+MvK2pRPQJaYLoCffN1GNSMlXze39KCD7a2ItXK4cmzSnDoaGm4kqwF1IZqKV/ngIIUZKRIF6rMikCV58klXtU5Y1I4Z8esAGVRFOVGrNOmZAIgK1Yy8YcEVLX7wXNASa9mJlmx0+A13SoriiLqu5gVKzzYKQw3Yw1TxU5ZnEYshsthQYHLCn9INK0tjgUnH1ggPdbJCEqPxZ+/qUWrN4QTxqfj+fPHYmr4tTcSBv0sLycrzjk4GneKdJs2b8jU3LPBTv+PVBIIhUL4fsMGLPnmG3y6YgUe/vWvMe+YYwAA9z71FD5ctizm/X5xySX4xSWXxPze7Y8+ii9XruzxtdysLHzx0kvGHjxBEARhKM+tbMBbm5rx7uYWvHDBWEzLTx3oQzKNTl/fqnMGkx+TYic5VLb5cf8X1QCAP5xUhAk5KZhZ5MQrPzRhY3VyFlAsX+ew0S75a047j3yXFfWdQdR0BDA6zmKHMJaIYif2pTJb3Ju14NvX4kezJ4RcpxWHl6Th1R+aSLGTRCpa/RBEYHSmDXZrz8F7fpoV7hQLWr0h1HUGMSqspDGDFk8IgZCIDAcvV66zZqxNNd0QRbHfYNmhhpyvk9U3X4cxPtuBus4g9jT5UOqOfzutbA9n2Jw6OQO7mryo6wyiwxdCuqN/9YiRsEr3u04ohMPKY3SmHRyAqnY//CGhh4V7uMEydpRYsWwWDukOHh0+Ae3eUJ8mw5HCoPirW9rb8fDzzyMUCiEk9MwSuObCC3HeKaf0+Nq6zZux8O23cfqxx8b9me1dXTj5yCOx4Jxz5K9ZLcl9MxIEQRDq+V9ZBwCgoSuIBYv24ulzSnH02PSk/X5RFPHB1lYUpttweKmr/zvoIFZwMoOsWMnly93t6A4IOGF8Oi48MAsAcHB4AbWxNjkLKNZ0clhpWo+vj3U7UN8ZRFmLjwY7SSKyqIh97TghOwUcpAwmMxZYLF/n0NFpslKjjhQ7SYOpRsbGGC5wHIfRmXa0ej2o6wyYOtiJztdhjHHbkZliQUNXELUdARRmDK9zQkWCRizGhJwUfF/ehb3NPpw4wfhj2BpW7EwvSMX4bAe21Xuxu8mLQ4rS+rmncYQEEXUd0nmoMPwac1h5FKbbUN0RQHV7IObrc7igxool3c6KDp8fLZ6RO9gZFGO+3KwsLF64EC898kif740pKsIh06bJ/x00eTI+XbEC1154IcYUF8f9mW0dHZg8dmyP+86YPNnMP4MgCILQSUWrH5VtAWSmWHDm1Ex0+QVc99/9eH9LS9KO4ePtbbhzSSVu+6jcdJm9XHVui2XFki5myIqVHNgA7eBCpzzAKc6wIddpRasnZHqmgSCKsrWC5eswSgcoQHlHgxcXv7572Ia0JqK/8GSnnUeJ246gAOxvNv55iQx2nHK2CoUnJw/WQjcmznCBWSXNDlbvna8DSIMlVns+HO1Y7DxXkmCwY2aAsiCK2B5uPJual4KJ4Tyt3Y3Jzdlp7A4iIIjIcVqREnWNwD4PhnvOjhyerMCKBQDuFMrZGRSDHTX8Z+lSeHw+XH3++Qlv197ZiWy3OzkHRRAEQRjC9+WSFeWIkjQ8cWYJfnZoLoICcOeSSny9t93031/XGcADX1QBAJo9IVS0mXvh1BWIb8UixU5yYY9zTtRFJMdxcp7FBpNzdpq6gwiERGSlWpCZ0vP1MFCV5+9vacGGGg/e2tSU1N87GGAD1VitPAwWoruryXg7VrRiJ9dphYWTXiP+ILXkJYP94QyT3o1YjHSHtIQyu3KcDfPyXT1VQcM5QJkpduIN1QBgvImV55VtfnT5BeSlWZGbZsPE8O/abcL7PBE17dJQr7CXIox9HpQn+fMg2aipO5duJ312tyaxxXKwMaQGO6Io4vUPP8SF8+bBZksse2zv7MSHy5bh2AULcNxll+GOxx9HfXNzko6UIAiC0MJ3ZeHBzhgXeI7DnScU4vJZOT2+ZxaiKOLupZU96sU31Zi7G0pWrMFDUzigNCet5+7gzCKWZ2Hua4EF48aydQxU5XlleLC5rX7gqn4Hiv4UO0AkQHlng7GPT027H1XtAaQ7eEzOTYGF55AXXtizIF3CXNgQtXcjFiMjnLXS4TN30FYvW7F6vg6nhDOe9pkw2BhIuv0CGrqCsFm4Hvaz3kzIjgx2jFbWsvPdAeF8v4nhAW6ym7FYgURxRs/HgVnUkv15kGzU1J0DkQFQywi+ZhpSg51VmzahprER586d2+9tD5g4EXNmzMCTd92FmxYswKpNm3DbQw9BEGingyAIYjAiiCJWhhU7R42JZNuwiyv2IW8W7/zYgm/2dSIzxYKfHpwNwPyaa9mKlbAVa+TuPiWTiGKn5+4gy9nZUG3ua4FZLkbFWMwMVOU5a5zZ2ehFcIQ1crV0Jw5PBsyrvV5bJb3WZhWlwcJLtkC2sKdmrOQQqTqPp9gJW7FMV+z0zdgBgOJM6d/V7cPr9VDeJg1PSjLt8ms/FnlpVrjsPNq8IcM3P1gj1rR86f09KcfcBrx4sOe2sNdgZ8xIsWLJqkmlgx3pdmZfKw5mhlSy0NJvv8XBU6Yoslj988EH5f+fM2MGMtPTcecTT2Ddli2YM2OGiUdJEARBaGFHgxctnhCK0m09JNhsF6bVxA/rilY/Hl5eAwC47+QiZKZY8ObG5kGh2KGMneQQy4oFAAeOSgUHYHuDB96A0CPrwEhqY2RpMHpXnida8BhJZZt0TL6giP3NPnnneiQgt2IpsGIZPdhZE5WvwxjlsmEjPLKCgzCPQEhEbWcAPAcUxQkmZoOdziQNdnpbsYrDx2VW3fdAoSQ4GZBsshNyHNhY48HeZh9y04wLsGaNWFPDm0qjM+1wWDnUdQbR7g3J+UpmU9PBBjs9HwvWAjacFTtBQUSrNwQO6GNNjgc7V1PGzhBh4/btOGCCtujzI2fOBADsr6oy8IgIgiAIo4i2YUW3D0V2Ycz5sBZFEb9fWonugIDTJmfijCmZOLBAuqDbVu9BIGSeUiEy2EmQsTOCL1KSSXOc3UGX3YJJuSkICpGmFDOoDWdpxLJiscrzQEiUL/bNpsMXQltUVsE2g+1GgxlPQIAnKMJm4WIGmzPGZDlg4zlUtgVk9Z0RrIvK12Hkh18XpNgxn9qOAARRGqbYLLGHqBnhjB3zFTvSeaG3Yicr1YJUKyfXOw8XmFIqUXAyY0K2NFg1OkB5ay/FjoXnImHNzck7DzIrVlGvz4SScDNiZas06DeTNm8I176zD0t3tpn6e/r83vBGXmaqRfFGhjuFMnaGzGCnvbMT+yorMU3jYMcfkD4IXU5nP7ckCIIgBoLvy/rasADAzXzTJil29jb7sLqiC5kpFtx3chE4joM71Yoxbju8QdHUwEQ22HHFUOxkpljAc5JSaaTZYJJNt19ayDussRfyM4ukQZ+ZQaW1CaxYgFR5DiQvQLmyV3D4dhOHWoONlqiq80QV9zYLh3EGt/M0dwexu8kHh5XDgeHmIyDyuqgjxY7pVMXJNonGlWwrVnrPgTPHcSgOL/Crh5Fqp7yt/+BkBhv+GGlHa+4Ooq4zCKeN76EaGohmLPZ39VaNyYN+wfxB//I97VixvxN/+qrG9JbQaCLBycrNRVkmXysOBYbMYKeythaiKKIwLy/m9zu6uuT/X7VxI6rq6np8/4vvvgPHcThg4kRTj5MgCIJQjz8kyC0wR5b2rHqONB2Yo1xpCIeRTs5N6aHWmBFuQzLTjtWZIGPHwnOmq5UICdmGlWqNuZA/SM7ZMVGxwwY7cRaTya48Z4Mde1ixsH0EKXaUBCczJudJg50dBtmxvt7bAQA4pMgJuyVyXqDK8+QRb0EdDbPjdJoYnuwLCmj1hGDl+1pEpeOTXhNVwyhnR6kVC4g01hn5+cjOc1PyUsBHfRawoHQzGvDiwYY2RTE+E+RmLJM/D/aHNxKq2gOmN0NGEz1cVwpdLw2SwU5ZdTXWb9uGLbt3AwD2VVZi/bZtKKuulm/T1NoKAHBnZPS5/5sff4zjLrsMy1etAgAs+eYbXH7HHXj29dfxzdq1eOHtt/Hkyy/jotNOw5iiIvP/IIIgiCHMfze3YNHG5NYbb6z2wBMUMTnX0ccrn+7gYeGk9hEzbFHxao1ZnayZAcqJrFhA5KKGmrHMhe0OxgtpnFnImrEGTrGT7MrzqnC+ztFhBd3WOk9Sd2wHkni2vFhMknfyjVnwfbStFQBwxhR3j6+z1wVZscwnXhtRNBlJUOzUh4d4eWm2HkMGxnDM2WHntxJ37NDqaMwIy+0dnMxgih2jbV/x6PRLVliHlYtZ9y03Y5n8eRA9OPpkW/LsWKw0QmlwMkCKHWCQhCf/65138OGyZfK/n1u0CM8tWoRz5s7FA7fcAgBobpNeTJnp6X3un+12I9ftRqZLuvi476ab8PaSJfh6zRq8tWQJsjIy8ItLLsGV8+eb/8cQBEEMYTr9IfxhaSVEETh7mjvuwMFoWL7Okb1sWADAcxwyUyxo9oTQ6g0iz8CQRCBqEddrd35G2AbxY615Ko1E4clA+KKmyUfNWCYTLziZMSHHAZedR3VHAPWdgT5BpnoRRSmsFeibpcEYm+RmLKbYmVOShrVVXWj2hNDQFTT8bx+MyMHJCnaLJ+REapf1Ut8ZwPflnbDxHOZN7rmRyaw4FJ5sPlUKFDuucMZOh4l5HnVxqs4ZzIpV1TY8Bjv+kICaDim0enSCoRojspA3buOjd9U5Y2KSm7FqWSNWui2mijRZzVjRnzeLd7ThrhMLYU1CeL+aczDDbcLrYagxKAY7D9xyizzAice5J52Ec086Keb35h1zDOYdc4z8b47jcPEZZ+DiM84w9DgJgiCGO1tqPWBxLk3dwaQNdr5nNeelfQc7gLQz1+wJodUTMn6w44m9M3RAfiosnHQh1+0X4IwzfNFDorpzICpAmRQ7ptLfYIfnOMwYlYrvy7uwqaYbJ0/KNPT3t3hCCIREZKZY4r7OBsqKVZJpx7S8VKyu7MK2eu+IGOzI5wQFVqzxBmbsLN7eBkEE5k5Ih7vX7y6IytgRRDGmgoMwBjYoYZXisWCKnQ6/eVaseFXnDKYoGi6V59XtUmh1cYYNdmv/n7fs/dlsoEKDZYlN7aXYSXYzFhsuFscZLpYmwYoliiLKWqXzWl6aFQ1dQaws78QxY/uKLIxGVtGqyNjJDIcnt3tDSW2PHEwMCisWQRAEMTjYFKVOYdkzZtPpC2FTTTesPHBoSVrM25i5ExNvUZ9i4zElLwWCaF4bUn9WLBrsJId4drxoDi4K5+yYkLkkV50nGJr0rjw3GzbYGZ1plxc52xtGRoAyO8+4FewWl7odsPLSotQT0LfI/zBswzp7mrvP9xxWHu5UC4JC5PVKmIOijB1mxTJTsRM+L+THaMoDohQ7w8SKpaYRCzA+U8UbELC32QcLF7FYMiw8hwnhIa6ZhQqMmg7psSiMo1xi4dLlreZZsVo8IXT4BKTZeVx8UDaA5NmxWrqV55wxbBYOGQ4egmh+qPlghQY7BEEQhMyPURkijUka7Kyu7EJIlAJqXXEGHGZ46Rkt3fElvzNMzlZRZMUCLeTMpj/FDgBMD0vzzZDiMxvWqPT4v99p51EQrjw3W34vimKPwc608N/ObArDnRYV+Q42C4cxbgdEAPt02LH2NHmxpc4Dl53HiRNi74hHcnZG1vkgKIh4flU9diYhwFsQRXnQ2rtmOhqnnQcHoDsgmNZa2J9iZ7iFJ1eEhxRjFOTrAFIVNiBVYxsx7N7d5ENIBMZlO5ASox1xYm7ycnZqoqxYsSh1R6xYgknZZ+xzZozbjrPCw+alu9rg1TnAVoJsxUqw2RILM68VhwI02CEIgiBkohU7SRvslLM2rNg2LCAydGk14cOaybhjLerNztkhK9bgoElBWC67YDRjJ1AOTk6wkASAmWHV0JrKroS300uLJwRPUESGg0dGikUOEt2W5MrzoCBiwaI9uOWDsqT+3haVVbssZ2ePjsEOC02eNzkTjjg2lIIRWnn+6Y42PLmiDjd9UGZKgH40DZ1BBAQROU5rzMU9g+c4pIdzdjpNUgew8OR4GTu5TiscVg6tnpD8WTKUYTZTpYodKy/l74kA2gxQTrH31ejM2L9fztlJgmKnuiOxaszlsCA71QJvUESDSU15zIZV6nZgXLYD0wtS0eUX8PW+DlN+XzRq7LDRmJG7NJSgwQ5BEAQBAGjoCsj1mkDyBjv7wxcPU/NS4t7GbWKNZaJFvZnNWCFBhCcoLVKccRYQOeHdqmQrdgIhEX/6qgaf7kheC8ZAwsKpEyl2zFzE1SmwYgHAEeHh58pwJpVZVMoZI9KiYkKOAzaeQ1mLH90mZor0Zm+TD2sru7F0V7tum5MaWuRFhbLd4vFssKNxwSeKojzYOfsAd9zbsQDlkdaMta5KGmSWtfrx380tpv6uSgWNWIx0lrNjUuU5GzTEy7XiOE5WdAyHnB2meGNB8UowciHfX67LRLkBz3zFDmtmi1V1zhiTFW5KNMmOxaxx7Pk4e5qULfdJ+FxlJmqH6wx2rWjGJuBQgAY7BEEQBIC+qpTG7uRcKCrJMzBzFybRxdzEHAecNh6VbQHDhyvd4YWq08bHDUIdKCvWl7vb8eLaRtz6UTme+KbWNKn3YEGJFctl4iJOqWInMtjpMrV6PNqGBQB2C48JOZLdaGeSWmGAntlWFUkKjQYi7zeliwoWoLxXo0VjfXU3KtsCKHBZcdjo2DljQGTwN9KasX6oigzWn/2+zlQriJLPI0ZksGPOIrI/KxYQeY8O9WYsURSxpY5Vjaf2c+sIRlpv+staY5tPqyu6sLrC3OF6jfw6TJC75jY3UD+i2JF+zxlT3OAALN/bYdprnqEk9y4WpNghCIIgCERyZNjuTLIUO0p2prJM2oUJCiJaPSFwiB2UauE5TC8wx47VX74OEG3FSu7u07I97fL/v7C6ATd9UD4spP7xaFYw2DFzERfJ2Ek82BmXZUe+y4qm7iB2mbhrLA92oha3A2HHYgs9wNyQ0N6ozXeYkC09Nlorz5la58yp7oRNLgXpLGNn5Ax2On0h7Gz0wsoDk3MdqOsM4o0NTab9PiWfRww5QNmEc4IoilFWrPjHwlqThnrOTm1HAM2eEDJTLIrUUgwjF/L9DfiLM+24YlYOAoKImz4o16zQ64+QEMl5GpUoUJ/l7LSYM9hhP5cpgwrSbZhTkgZ/SMQXu9oT3VUXoijKViy1ih3K2CEIgiAIRAYXcydkAEjOYKfdK7UupFq5mOHFjEgrlrEf1q1R7TfxFlSRnB1j7VjM0sOUILEYiIydoCDi672Sh/7ek4qQ4eDx5e52XPrmXnnRM5wQRDGi0EiwkHeFB3BdfsFwBRO7iI8XlMngOC6i2jFxx7iyjWVNRI5nal44QDkJAbaMaMVOsmreBVFEazivw52iTrGzv8WvOkg3EBKxOGx5PDeBDQuILPJGUsbOxppuCCJwQH4qfnPcKADA86sbTMu1qWpjNdMKrFgp5g17Wzwh+EMi0h08nAmG/5EA5aF9bmZD3OkFqeDiKFhjYaxip//Q9LtOKMRJEzPQ5g3h5+/uR2OX8e/Fhq4gQqJUMZ6o9t1sKxYLTy6Nyjw6a6obALDERJt2V0BAICQi1cohNUHOVSxIsUMQBEGMeERRlBU7J01M3mAnsjtqT3gxZ9aHtXwhl2BXiA12Nhlcc90VthOkJbhwSbPzsFk4dAeEpGWMrK/qRqs3hLFZdlw6MxtvL5iIsVl2bG/w4p7PqpJyDMmkzRtCSAQyUyywW+I/Fxaeg9PGQ0REbWUEYlQLT0E/gx0AOKJEsuqsLDcvQJktEqNDROXK8yQpdgRR7NHClazBTps3BEEEMhzSe08JTjuPonQbAoKo2jK2tqoLrZ4QJuU4MCVBzhgQHZ48chYtzIY1q9iJ48alY1axE62eEF5a22jK72Ov/eI4AbrRpIcHLmbYM+sV2LCAqMrztqE97NscNdhRg5F25WYFIfoWnsOfzyzBjFGpqGoP4JfvlRn+2VylUDU2JqoZy2haPUG0ekNw2njkpUUejxPGS41966q6DGkii4WWqnMGZewQBEEQI56yVj/afQLy0qzyhVVDd9DUHA8gIh/v7wKG7Zy3GtB8EU2Tp38LzkGFkQBlIx8PJVYsjuPkY0tWzg6zYZ04PgMcx2FctgPPnjsGALC/JXl2mGSh5GKeYUaAcps3BG9QhMvOw2Xv3/rDFDurKzpNu7DuHZ4MRPIldjR4Tfu90ZS3+nsM0MqT9NpT83qIZrzGZiyWyzOzyNmvUmHUCLRira+WBjuHFKWB4zjcfqyk2nlxbaMp50RVGTsp5lmxlOTrAJHPzmSoKTt9IXSaZMndonGwY4YVq78mplQbj+fOG4PiDBs21Xpw99JK3b87mkjVeeLXoJyx0+I3/FotWq0TfV4qSLehOMOGTr+AXSblrUWssOoHO6TYIQiCIEY8TK0zY1QqUm080uw8AiHRtLYPhqzY6Wd31KwP6xYFFpziDBuyUy1o8YQMzTHor+qcwZqxkmXHYoOduRPT5a+xRW5nEhuRkgVTpuUoyFMxowVHab4OozjTjlK3HR0+oYdVySgEUZRf58VRi1t3qhVF6TZ4g2JSBnxbwws9lvllxq50LFo0ZjuwyvO9KnM32BBNScVzuoNHqlVS8JllRRpMhAQRG8KfTYcUSwP2Q0en4bhxLnQHBPxzTYOhv08URfkzSZEVKzyI7TBgw6HLH8L7W1rw73WNWLiqAe/8KLV/9TfYGZ2kjJ2gIOL8V3fj/Fd2q7Yb9ocUnCy9bw5UPdgx0IrlUf5ZkJtmwwsXjIWN57B4R5shdeuMaqUbXqlWZKZY0B0QZPWxUTCF5JgY56VZxZJqdF2VsfZ0hjxcV9hKGA1l7BAEQRAjnk3hfB2mTmHS2wYT/OPRVLcryzPISLGA56QFdSBk3EWlkjYkjuMwg9We1xh3IRNR7CS+eGG7h8lQ7Oxt9mF/ix+ZKRb54g2IypfxCaaruJKN/BpQsJBnj0OHgbvWdQobsaI5otQYO9b66i7c+H5Zj93++s4gAiEROU5rn2wP2Y6VhJydrWEb1imTMmHhpHOFP2j+YDFSs6tuUcEClPeobMZiA6sSBdYfjuNGVIDyrkYvuvwCijNsPQYcPzs0DwCwttJYO2Jzt6Sey3DwCbPPGBkpxp0PXl7XiDuXVOLh5TX484pafBYOp+1v4JfnssLGc2jqDpraFrat3oOyVj/KWv3YXm/s+7+uM4im7iAyUyw9cr2UwN6nej8fRVGULUBK1XoTclJwcFEqBBFYY+BrsaZDOicUKhguRpqxjB22l4WH9yzHJ5pZ4SHrD9Xm2IHl4TopdlRDgx2CIAgCm9lgJ5wnkxse7Jids1MVlbGTCJ7jkBmWvbd5jTsmJRk7AHBQofHNWEqsWEByA5SXh9U6x49PhzUqTNpulfJGAoIIv4GDtcGAGusNW+wZqZao7ei/+aY3kdpzfQHKL6xuxBe72/H8qojyIVJ13vd4WA2x0Qu7WDDFzszCVBRl2CECqEhCpbNWxQ4LUFZrxapQodgBonN2hv9gZ52cr9OzAp4teI1WKajJ1wGiFHxe/QOVylbp+Tx6jAvXzMnFDUfk43cnFOKyQ3IS3o/nOPnxMDNAeVXUEHltlbELepavc0B+iqrgZCBy3tar0OjwCQgIItLsPBwJAot7c0SJMefiaNTYAUtNytlhip3SrFiKnfBgp9IkxY5Hv2KHMnYIgiCIEUkgJMr+9gPDyhQ2TGg0eZigVHIMmCOxlS8g+lnUy4odA5uxlFqxspNYeR7J10nv8z2mVuk02Z6XbNjjmki1xTDFiqVBsXN4OEB5XWUX/CFtxyKKIjaG80s+3tYqB4DK+ToxFhVsEVHdYe6ARRRFbAnbzA4oSMWYJNqxtGbsyFasZp9iVZsoRsKWS919d8ZjMZJydpgi4JAiZ4+vs8+CZoN35dUsqIHI+cCIjB32t1x6SA7uOL4Qtx5TgKsOzUVGSv+L22I5Z8e818TqisgwZ53BSik2xD1ApQ0LME6hoUS9Gws2ZF9lxmBHwWdCfpp0G6M34VimWSwr1qScFLjsPKo7Aqach+SWSg3hyRnyBmAoKVlwgw0a7BAEQYxwdjZ64Q+JGJtll1UxeSZdLPSmOkaWRzzYBZyROzFKF3GsGWtLrcewfAG1ih2zrVgtniB+qOqGjedw7LhYg52wWsWk8MyBoknhcA+IhCcbWW+sNmMHkPIdJuU44AmKmtvaKtsC8uC20y/gs11t4a/3bcRi5IfVIg0mtzLVdATQ6gnBnWJBYbrNtF3pWGi1YmU7rXCnWtDlF1Cv8PFp7g6hOyAgw8HL597+GEnNWOvDip3ZxT0HOxkOHlZeOocaac+rVthGFDkO4+rO9eSKFMk5O+a8P4KC2EOls7ayy1BLrryxpGmwY8yGT5PGx//gwlQ4rBx2NvrQZND1khorVk6aOYreSMZO34GzhefkYesPBqu3gMhzqXa4DgBWXlJ3i4ChuUdDBRrsEARBjHBYbgzL1wGSY8XyBgQ0dQdh5dGjTjMebvkCzkArlkLJb7bTitGZNniCouoMjXgozdiRBzsme8a/3tsBQQQOK0mTd6KjcbFGqGEWoNysYqeWDbeMVOywjB01VixAvx1rY/h9bw9Xer8bDmtltcmxBjvsfVpv8sCX5escUJAKjuPkxUVyBjvaq3YnqLRjlbdJtytRqNYBohQ7w9yKVdcZQFV7AGl2HpNye9bAcxxnioKzSmHmGyPdyMGOigFzb4rDtkmzKs+31nnQ5Rcwxm1HXpoVzZ4Q9qq0HCZCayMWIClJbbwUKO7TMeRr0fj42608Zoetgqsq9Kt2OnwhdPgEpFo5uBUMe3NNUFe3e0No8YSQYuWQ74r9eJgZoKzHigWM7JwdGuwQBEGMcDb1ytcBkjPYqY6yoFj4/n31kQ9r4y7k1dhwDjLYjtWp2opl7kWKbMOa0FetA0QpdoZZG48aCT5byBmpWtJixQL0ByhvCNuwLp+VgxQrh1UVXaho9SfM2GGKnXqThwpbozI3gEj+TFkS2rgirwf1iwpmx9qjsBmrQkVwMqMgvNCqH+ZWLKbWmVnojPn5IIfmGrh4kzN2FFuxpHO3EVYsWaWgYaDIjtesyvNVYRvW4aVp8hDDqAV9XWcADV1BpDt4WZmnBo7j4Dbg2kCrFQuIOhdX6FevRNsBleQN5ZhwrcaCmEvdjrjHIOfsmKDYYapst4b3AjCym7FosEMQBBFFqycoX2yPFH6Mpdhxmt+KVa0wOJnBdq9aDQxPblGRpyEHKGu0vvRGVuzY+hvsGNP6kQh/UMCKfdJu44kTMmLeRs7YGaaKnWxFdefmWbEKVQ525pS4wHPSgKZbw3PCaqSPHZeOeZMzAQDvbm5OaMXKcPCwWzh0+QU5I8oMtvbawR+TRCsWs1ExO6oa1DZjlcv5OioGO+kjIzyZ5evM6mXDYpixeNOasaM3d8wfFNDlF2DlI+cYNRSbXHm+OqxEOazEhUNHS8+HUY1kW+Qhbqrq4GRGlgFq3iaN2VqAsTk7Ne3KbVhAREVp5GCHnZfGxAhOZhw0ygkrLzUkGm3P1ppzxmBD32QUTgw2aLBDEAQRxS/fL8NZL+8cEcGUAOALCtjd5IOFA6bmReTuuSb5tqNRWnXOkC/eDAoRDgoiWr0hcICifAsWoPyjQYodNtjpr1Y3Ga1YG2q60R0QMDk3JeaCHgDSZCtWcnbB/CEhKR55LYodo6xYnb4QuvwCnDZe9YIuM8WCGaNSERBEfBlWWynFGxCwrd4DDlJ+1AUHZgEA/ru5BbWdAXCIPWjiuIg0v8FENR8LTmYtXCVuOzhIioqAya1sjeFhdl4cC0Iixueos2JVqmzEAqJVU8lbtHT7BZQbXKfcH0yx0zs4mZFtQvZYVZu6jJ3o8GQ9mTPNUfY/LcONIhNbsYKCiLXh9qPDStJw6GhJnWLYYKdWuw2LYYSaV23VeTTTC1KRZuexv8Wv+9qRKZmVvgbNuD7YnyA4meG085iWL1W9sxB+I/AEBNSEH4NcjYMdNpitGSHX8dEoesT+7+mndf2S6y+5BIV5ebp+BkEQhNmw8FgA+L6sE+eFFzvDmabuIERIg5zoik+2W23m4k1p1TnDaN90dEiqEivYAfmp4DlgR4MX3oCAlH6UNv2huBWLNcB0S4sHrbuaiWAXQJNy42d9RKxYyVHs3Lm4Eot3tOHECen42aG5mDM6zfC/3R8U0OGTdsqVtM8YXXfOFgEF6TZNf9v5B2ZhY40HizY24expbsX321LvQVAAJuemwGW34LCSNJS67fJO7ah0G+xxKn/zXTZUtgXQ0BnE2Czl2TBKaewKoL4zCKeNl3eMHVYeo9JtqOkIoKbDr7hBSi2BkIhmTwg8p80SwzJ29qpU7KgZ7GRHNUIJogjehPNBb+75THovLr56MsZlm/PYR+MJCNha7wHPAQcXxhnsGGzFaveG0OmXsk2UBmfbLBxSrRw8QRFdAUE+R6pFTwsQIJ0/LJw07PMHhbjvXS1srfOgOyBgbJYdBS4bcp1WuOw8qtqlRiS1FtLeRBo5tQ92jBjy6bFiWXkOc0an4au9HVhZ3on507VfO9a0MwWnsnNCttMKDtL1TEgQFV3L9Ed5C1PsJH6vzyp24sdaD36o6sbRYyULty8o4PFvajHWbceCQ3JUf679b38H/CERBxemKvpMjgXblKgxyZo4mFH0zv9g2TJwPI/C/HxV/xXk5uLD5cvR1tFh9t9BEAShm2jP+GqD6zwHK/EuZqLtP2ZVRqqpOgcifutWg1QczSp36JzhEM+QCGyt12/HUtqKlWLjkWbnERBEQ0N7o1GyW8msWGZacBjdfgGf75ZUKMv3dODyt/bhgtf2YMmONkPbWKJ3ypUskNPDj0GHQY8BG6iN0qAOAYCzprmRZuextrIbOxuU5boAkR1WpobgOA7nRw2yY+XrMCIByiYFtcrBySk9npNSOWfHvIv1SDORVdMCqTDDhlQrh8buoCK1WUWb+owdm0UKVRVEYxsC4xEURCzbIwWrGxmYm4jNtVGDxziKRqMVnMwaXJypLNuEkZ6if+AdCU7WtpC18pw8YDFapSDn65RIdiMLz8n2OCNUO5ujrFhaMWLTR29gL8vZWaUx84yhtpnNyksZQ4Jo3JCzTKFFlOUt/RD+PBFFEfd8VoVXf2jCH5fV4LGva1V/Xn8R/tw/eWJsS7gS2GNXY5I1cTCj+Epi/kkn4eCpU1X98FAohIVvv636oAiCIAaCtVHBd0bJjAc78bzMdgsPd4oFrd4QWj0hOaDPSKIvpJVgtGJHi4/7oFGp2NHgxaZaj9wKoZVIxk7/F5I5Tiu6/H40dQc172IlInJRm2CwIwcHm6/YWVfVhUBIxOTcFMybnIHX1zdhS50Ht31UjrcXTIi7i68Wtbu0RluxtFSdR+OyW3DONDfe3NiMRRubcO/JxYrux4KTDy6MLKbOm56Fp/5XB0EERidQ0ZkdoLw1zkJvTJYdqyq6TM3ZqddhwwIAnuMwLtuBrfVe7G324pCi+OcIb0CqRbfy6vOVsp1WtHpDaOoOas6hUApTbADGZkslgllBEi32sw1uC6xSudHAyHBYUN8ZRLs3pPl9rCc4mVGcYUdVu9Qk1p/SQg0sN+awkshr+dDRafhmXyfWVHbhLBVKwd7Uh4OT0+x8wjyX/jAib0lNO2IsolsK9Shrq9rVZ67lpVnR4gmhqSuoKRusN+wc258ikw34NlR3IyiIePWHRnywtRUpVg4hAXhxbSN8QQF3n1SkaOMkKIhYvkcSg5ykY7DD8omqR6AVS5Fi5+Qjj4Q7PXZLRsIfzvM4+cgjkZ6m7+KXIAgiGayNSvcvb/XLNcTDmUStUHIzlknZLtVtGjN2DNqlVjLM6I2ROTtdAWWKHcD8nJ0mBQHCcnhyEhZ334cXE8ePT8dNRxVg+XVTccxY6cJ5d6NyZUp/aB3sGPUY1EVZsbTy05k5AID3t7YqVlOx4OSZUfklo9Jt8mMcL2cJAPLTzM14YWq43ot6Zr8qMzHrhQWQas12AKJydvqxYzG1TnGGXbU6yIyK43isitrwSFYjnmyTTXA+kgf9Bj0Gaq3BjOicHa1ErFjah/aRynPjBp+BkCgrmXsPdgBgnc4NMDkkPT9Vl6XQiE0fdi2UpfG9PyUvBe4UC6o7AvJ7Wy2iKMqqODWWxxwDzwedPmlg7EhQdc7IS7OhJNOO7oCAF9c04LGvawEAj51RgqfPLYXNwuH1Dc2457MqRcrvH6q60OoNYWyWHeN1WD6Lwja2kajYUTTYefyOOzCmWNkuUDAUObFxHIfH77gDxQUF2o6OIAgiSXT5Q9ha54GFi+xCrDWhxnGwwRYyCQc7JlgugoKIunBIq9JdTlZp2mq4Ykf5xbRRzViiKMqLcJeCwY4ZQaHRRFtQ4iFn7CRBsfN9mTTYOWqMNGhIsfFyBoORzS9qVVsuh7HNYHLVuUv7YGdKXgpmFTvR5Rfwyfa2fm9f0+5HXWcQGQ6+z+LhzuMLcebUTFw4I35GBLvYN82KVcesWL0UO0loxmKZYnk6no/JuVII/dubmhO2lVVoCE5mmH0+iGZN1GCnI0mNeC1RFsl4sAW4UYN+tRsNDBZ6rmfoFbFiaR8oFsnNWNreHyFBxKPLa/Dkilr5s2lrvaTWGpftkJV6ADCjIBV2C4ddTb4ewxRvQMCmmm58u78Dn2xvxevrm/DZzvjnpM11+oOTgej3g7bnQBDFHpl7WuA5Th5+rdRox6rvlCyc7hSLbHlVgpGV57INK9OuaNg2O3y9/OcVktrzhiPyMW9yJk6ckIHnzhuDFCuHd35swd2fVfVry4q2YenJ08tNs8LKS4MuX3B4tXj2h+J0LY/PhweefRYeb/ydsk07duDS22+Hzz/ywooIghjabKjuRkiUWlhOGC8pFKMvaIcrieTHkcpz4xcPdR0BhETJ8mC3KPsoynBYwHNAu08wpBlHS1jixJwUpFg5lLX6dQ2Y/CERQQGw8ZyioEt2kWeWtFi2AiTK2DF4qBGP5u4gttZ7YbdwmBWlKGEqEiN3pNlrQKlCIxIgra8FhyEPdnQGkF5ycDYA4M0NTf0e14bwUPLgQmefC/eJuSl48qxSFCqyYhl/XujwhVDR5ofdwvXZsS0NWzXKTczYaWBWLB3W0/MPzEJRug0bazy46YMy+OMsLOTgZBX5OoxktBYC0mJ/XdQGR7KsWEoW2dEh0kag1hrMyDBAscNygrSGJwORgVRlm7bPiNWVXXhpXSOeX9WAc/+9G2sru+S8mGi1DgDYrbxsh2WFEyvLO3HKv3bgotf34Jp39uPXH1fggS+rcfOH5fh8V9/hjiiK+Ha/NMCfriM4GdBfd97qCUEQpaZBpdcjsdBbe74zrEadnJuiarAhK/iMGOyEbZClCu180Zb0kyZm4Oaj8+V/HzM2HS9cMBapVg7/3dyCNzY0x/05oijii13hwc4k7TYsQMqBKnCZkzk12FH86n3h7bfxw9at4Pn4d5k2YQIsPI/n33rLkIMjCIJIFqzOc85o4+s81VDV5se17+xL2lCpydO/YseMxUOk6lz5RbSF5+R8mTav/mNqVrAr3BubhZOVBGy3UQtKg5MZTAWgJiBXDU0KlCvRQw0zYdaPWcXOHs1jLPel0sCmCyV/dzQ2CyflB4iQc0f0UKczY4dx2uRMuFMt2Fov5T8lYkO19PjOjFMj3R/5aeYNfNl5odRth83Sc2FTmiktNMrb/KYFurOFkZ7BTl6aDS/9ZBxynVb8r6wTt39SgWCM461UGFAaC6YybDKxtRAAttV7ewxyk6HWAyKh0InOzdEB/0agNWPHZUDulhGKHWZVrNBoVVy8vRUAkGrlUNHmx2WL9uLFtQ0AgMNL+kZqzB4tnT9WVXTiL9/W4qq396G+M4hStx1Hj3Hh9CmZOHGCtEn2xy+r0dnLJvru5hasr+6GO9WCY8MWUK3orTs3wgoHRAKUvy/vivme7w822EnUThmL3LA91ohrtfrwOUVpxs9RY1ywWThMznXgsTNG99ksOKzEhYdOGw0AeOSrGmyqiW1j39HgRVV7ALlOqyEZenLl+QizYyke7KzcsAE/PfNMOOzxP4BsVivmn3wyVm/apOogQqEQvl23Dn/4y18w+/zzsfTbb3t8//ZHH8XM+fN7/Hfy1Vf3+zOffOklnP7zn+OcG27Ai+++q+qYCIIYWbAhzqGjnZgxKhUOqyQzTobUPZpXfmjEiv2duPfzKggGtv/EI5EVhV0sGLEL1Jsqlc0PDHahb0QbjJbwZACYEd5d3KTDjtWpsOqcMSVPGuxsN2mwE7Fixb+wZcdq9uKutw2LEcmQMN6KlaPCjhfJ2dH/OMh15zqsP4BUB35BuNXqzQ1NCW+7MUqxo4U8E8OT2c/Mj/F4OO088tKsCIREeSBmNGxYlaszgHRslgP/umgsMhw8PtvVjnuW9j2fa6k6Z+Q6jVvIJWJNpfReTEtivhYQUV64E5yP3CmRlkQjPiu1ZuxkyIMdHYodnY1MAOTw4f0aFG2BkIjPdkpqidd/OgG/PCIPPBcZlMwZ3Xewc2hYqfHvdU14bmUDOA648ch8LPnZZLx40Tj89exSPHvuGMwYlYq6ziCe+l+dfN/6zgD+9FUNAOAPJxbKjZda0avYaU6wwaWG8dkOjM2yo6k7iKUJLGjxYBs3k8Of90oxMnNLzhlTONwucdvx2TWT8Z8FE+XNn96cOdWNBTOzEQiJuO2j8phqZ2bDOmlihq68JYYcoDzCKs8VD3bKqqtRUljY7+1GjxqF/VVVqg6ipb0dDz//PNZu3oyQ0PdCqb2rCycfeSReeuQR+b+//O53CX/mY//6Fz5avhw3XHopLjv7bCx86y38+/33VR0XQRAjA39QwMZwGO6s4jTYLTxmhhc965KYsyOKUq0sINXKfh6WpZpJIjuSmVasSNW5uotovTtz0WhZ1APAQeEA5U06ApS1KnZ2N3k17QQmwh8U0OkXYOWRsHGL7UybXXf+XXiwc2Rpz8HOqHQbeE5SufhDxgyXEmVMxcNlwEIOkPIo2n0CbBZO904xAFx8kGTHWryjLa5N0B8UZKWZ1sFOhoOHw8qhyy8Y/lqQBztxFhVy5blJOTtGKHYYU/NSsZDZELa04MU1jT2+rydjh52zzA5PXh1Wzx07VlJeJM+K1b9ix2bhkOHgIYhQVC2fCFEU5c0CtcHZxoQn67di5aVZ4bTxaPWGVA84vivrRKs3hIk5DkwvSMVtx4zCWwsm4KBRqThzambMQeshRU6wzO8ClxX//sk43HJ0AaxRQeAWnsMDpxSD54BXf5CaDQHgwS+r0e4TcNw4F87W0arFiA5P1mKRZcHJehvmOI7D1YfmAgD+taZB9bHsaopYsdTAMnaMUPA1arCjFmXYe6hrY3HXCYWYMSoVVe0B3LWkss8wNnqwYwRF6WTFSsiY4mLsLivr93Z7ystVhyXnZmVh8cKFeOmRR2J+v62jA5PHjsUh06bJ/82YPDnuz2vr6MB7n3+O3//iFzj7xBPxk9NPxy9++lO89sEHCIWS86FEEMTQYXOdB76giIk5DvmDne1QrUmiHWtPk69HMOhzK+sNyfFIRFOC4YaZ4claFTvuFOMqz5s1VsxGByhrfX4igx1lC/qMFAuK0m3wBUXZA28U0YuoRDtlkVYs8xQ7Fa1+VLT5keHg+wRq2i08Clw2CGJE6aIXLRaI9PDj0KFzqMFUWxkOi66gSMaYLAeOHuOCLyjGDVHe1uBFICRiQrYj4RAvERzHyRf9Rg99mQ0g1kISAMaE7SZm5eywwZIRgx0AOKQoDY+dUQIAeGNDk7yYEUQRleHBTqIGsngkIzxZECONSHMnssFOssKTlVljjHoc/CERIqRhkdqGMhaerGfoFTkPaR/wchyHcdnhwafK98eSHa0AgDOmZspfmzHKif9cNhFPnlUa8z4uhwW3HVOAi2Zk4YMrJ+Gwkth2qgMKUnHFrBwIInDvZ1X4dEcblu5qh9PG4/5Tig059zmsPJw2HkFBm6JUq3o3FvMPyEJ2qgVb6rw9GuX6IySI2B1u0pukcrBj5CZcg4HD7WjsVh5/O7sUmSkWLN/bgb/9r07OSqxs82NbvRdOG48jS41p0o4odmiwE5ODp07FW0uWoKMr/ou0vbMTby9ZgoOmTDHk4KJ/brbbrfj236xdC47jcOzs2fLXTj7ySDS0tGDj9u2GHhsxdBFFsY/nlxiZMBvW7Ci58aElyc/Z+XKPtGNxxpRM5Dqt2FrvxYr92kL4lCCIYsILmrykZOxotGLp3KEFtF/MlWTa4bTxaOwOal7odKm0YgHAlHzpYm+HwXasJjlfIPHjEGnFMu+8uTIcOnl4qSvmAstoOxbbqVWj2Ek3IFMDiCxAlLSiKeX8sB3r/S0tMb+/vrpvzbkW8k2yY7H693g1uyxA2YzKc1EUZQWMUhuCEk6elIHiDBuq2gPyQq++Mwh/SESO0xrXvpCIXANbcOKxs8GLNm8IRek22QqaDCtWUBDR7hPAcxGbUzwiFhx9x+ULSgtMh0X9kIENSLWeD0KCiLbw8eu1JI0NB97uVzH89wcFWR18xhS3qt93/eH5eHDe6H4/O245ugCj0m3YXOfBbz6pAAD8+tgC1YrdROipPJfVuzoff0BqcFxwSA4A9FHpJaKs1Q9fUERRuk3+jFGKkXmIjQbZUWNRnGnHY6dLeTvPrWzAvH/twOvrm7A4vBFx3Lh0RWUSSihkleek2InNLy+5BP5AANffey/Wbt7c5/trfvwRv7jvPnh8Pvzypz819CDbOzvx4bJlOHbBAhx32WW44/HHUd8cP1m7tqEBBbm5SHFEwqdGjxoFq8WCmkblbzJiePPcqgYc8cw2zen1xPAhOjiZMbPQCSsvhUcmS36+LCxFPXNqJq4Ky3mfW1lv2u9r94YQFKSFpSPGh2muqSGp2vIM9Fy8RRMIiWjzhsBziXMcYsFxnBwsqPWiQa0VC4jk7OxoNHawo3S3ONXGgecAb1A0pJUsFvFsWAwjA5RFUVQdngxEtYPpPC8w5RP7eUZw0sQMpNl5bKr1YE9T39fJN3slq6fuwU6aOc1Y/St2zKs87/AJ8AVFOG28YiWdEniOw/zp0sDtv5ulgVt5eDBVkqlt8ZQMxQ4bQs0pSUN6+PFIRt05G3JkpFj6Vc8Y9XngDTeXpWhYVKbrtGa2eUMQIalRrSrVQr1hg519KgY73+zvRKdfwLT8FIzLVhfaq5Q0uwX3zJXiPAKCiEOKnLh0Zo6hv0NP5Xnkc8CY9/2lM3OQYuXw9b4O7FL4ec1upzZfB5D+dg7S+0BvsHyDyowdtZwwIQN/O7sU47IdqGoP4IEvq/HnFbUA9LdhRVNEGTuJyXC58ORdd6HL48F1996LE6+4AlfceSeuuPNOnHjllbj+vvvQ0dWFJ+64A9mZmf3/QBUcMHEi5syYgSfvugs3LViAVZs24baHHoIQI48HABpbW5Hp6ntRmOFyobEl9i4WMfJYXdGFgCDiHyYunInBT3Sd66HFkcVOqo3HjFFOCGKkztNMGroC2Fjjgd3C4agx6fjpzGxkOHisq+o2rSGrqZ/dacmaI+2GGrmQF0QxKmNHpRWL7dBquHiLpjXcquVOsWgK6mMy3xqNFw1qrVgAMCXXHMVOosr7aDiOk9UlZuTsCKIoK3aOHBN7sMOqiCsNqDzv9AsIhKSFfGo/+QDRGKfYYaot44YIqTYep0+RrsHe39La43tb6jz4X1knnDYep+i8gM5zsaGvsbuhkfDkeBk70sJTrdVECUZUncfjvPBg57Odbej0hVAhBydrW0in2XikWDl4gqJpmVfMhnxYSVpUYLj5mxwRG1b/z4OexXw0smLHqv6zgFmx2jWqSOVGJgNsQHKAcrPy98eScBuWWrWOWk6elImzp7nhTrHgwVOLVVve+kOXYseg8GRGttMqqyeVqnZYcLJaGxYAWHkO7lQLBFHfkDMoSCpuDuot6mo4bUomPrlqEp46p1S2XKdaORw/Lt2w3xG9+WZ2pMFgQtVoesbkyXjnqadwx7XX4ujZsxESBIQEAUfPmoU7rrkG7z79NA454ADDD/KfDz6Imy+7DHNmzMBPTj8dv7/+emzdswfrtmyJeXsOiPkkioAhSdvE8IDttH9f3oXt9drbbYihzc5Gqc61OMOGwl7qkWTWnn+1twMipCYgp52Hy27B5bPCqp1V5gwfm/sJDLTwnPzhbuTOcFO3ZENwp1hUL2rZxVurzrrzRKHRSmAXDdUDoNgxuvJcfh0ouJCL2LGM37nf2eBFsyeEUek2jMuKreRi1j0jrFhaXwOyekGvYscEKxYQGSJ8sLWlx+7twlVSdfHFB2XrCmkFTFTsyOHJcRQ74ddFRavP8It1OVsizlBJDyVuOw4bnQZvUMSSHW0oZ8HJGvJ1AGnImmPQUCMWgij2GOykyQNdwfS2xkjmV/+fDfLnk07Fji+s2ImlXO0PuRVL4zmxWWGekBLGhRU7Sq2KnoAgFzawgbCZPH7GaHx/4zRM1DC86A89trz+roW0cPWhueAAfLStVVGLH6s6n6yy6pwhN2PpUFg3dwchQnot2jTYEtVg4TnMm5yJdy+bgDd+Oh6LLp2gOfctFi6HBRkOHr6gaEjZxlBB9RnMZrXikjPOwIO33orXH38crz/+OB689VZccuaZsNuM9+PF4siZMwEgbvtWTlYW2jp72mtEUUR7Rwdys7LMPjxiCCCKImqjdtpfXkcWvZHKGrnmvG9gWzIDlL8M27DmTojspF8+KwdOG49v93fiRx0NTPFQsrCVsxwMHOxoVesAUYodnR/UTPGjdZc0otjRNmBQW3cOSOG4DiuHqvaAofZAeWGhQIYu25BMUAkwG9ZRpa64gZosaLbKAHl1ouDwRLDHQHd4cvg5dKnMU+iP2cVOlGTaUdcZlBVQ+5p9WLqzDTY+0tqiB6aoMTJjJySI/bZSpTsscNp4SakSMHa4KGdLOM25lj0vvIP/3y0tqAwrdko1NGIx2HnbjAy03Y0+tHpCKHBZUZJph4Xn4LTxEBEZSpsFG9orGT4aZ8WShlUpmhQ74cGOZsWOthD/WIxhGTvNygafX+3tQHdAwEGjUjW1s6mF4zjTNtj1vBZkK5aBKpVStwOnTspAQBDx6g9N/d5+pw4rFmDMtZqZ+Trx4DgOs4vTMDU/tf8bq4Rt1o6kAGXFV5RVdXVYtnIlduzbZ+bxKMIfkJ4glzO2R7woLw91jY3weCO7muU1NQgJAgrz85NyjMTgptUbgicowmbhwAH4eFub4SGQxNBgbYLBzqxiqc5zc60HHoMXEdF4AoK8qD1hQkSKmpVqxSUHSxXG//nReBupknwRM5qxqtq05esAUYodnRfyehU7RTqD+WTFjk35ot7Kc5iYY7wdS6kVC4jYhsxoxvo+PIQ4Ykz8VgwjrVhaw7MjthR9j0GXSYodjuMwf7obAPBe2I71zzUNEAHMn+5GQbr+i3Y5PNnA/K1mTxAhUXqPJwrQzAzv6rYZvAsrW7FMUOwAwLzJGXDaePxQ1S3n1+hZTLP3qxmV52wzY05JmjxkNaL9SQlsaO9WsHtvlBXLq0Oxo7fu3IhGLEZmigXZqRZ4gqIiNR2zYZ051a37dw80enKnjLZiMa45LA8A8Pr6poR5nt6AgPJWPywcMD5Lm2Inx4BAdbMasQaKSOX5yMnZUXQGe2fpUlx51134dt06/PrRR/Gnf/7T7OOSWbVxI6rq6np87YvvvgPHcThg4kT5a9FtXcfNmQOO4/D1mjU97lOQk4ODEtSkEyMHVpU71m3HyeGJ+hsb+p+oE8OPjTWSDW92cd9BcbrDgok5KQgIouIAPC18V9YJX1DEQaNSUdArNJQdlxntJ0qaIIys0WToUewY1YIiX0xrlL/Lih2NFwxarFhAVICykYMdFbXvZmbssL9pVlH8wc6odBssXLhVKKhvsKLZiqUzLJXBVE9aWpH649wDJHXI57vasKfJiw+2tILngGvDCw295KcZr9hhC9F4wckMebBjQDNeNGYvatLsFpw2ObPH79I12EkzL0B5dXjwdNjoSNaVUdlS/aG06ly6Dfs80F93DmjL2EmxcrDxHPwhUbZ0qaHFY6xaZGy2sgDlLn8IX+2TbFinJcGGZTZarw2CgohWTwgc1Bcp9MfBhU6cNS0T3QEB17yzHx9sjb1Bt6fZB0EExmU7NLdC5Rqg4GMbeGYFJyebkVh5rujV8/c33sBtV1yBe2+8EX++8068tXhxwlYqtZRVV2P9tm3Ysns3AGBfZSXWb9uGsupqLPnmG1x+xx149vXX8c3atXjh7bfx5Msv46LTTsOYoiIAwJsff4zjLrsMy1etAgCkp6Xhwnnz8OjChfhw2TK8tXgxFr79Nq6YPx88b+zOGDE0Ybvso9JtuGq2JEt/c2OzrMoQRRGfbG/FL/67H/uaja9VJQYHgZCIuo4AeC4Sytkb9gGndTdOCcvCNedzJ/YNNE0zaBEZi0YFVhQzanVZS0GxBsUO28XVeyGvVa3BkIP5NF4waKk7B0wa7Kh4LJhtyOiMnWgbTkF6/OOw8hxG6cw3YrDBgNqK4XTZjqYzPNmEVixGiduOOeFMl1+8V4aAIOK0yZlya45e2PDFyIFvJF8n8fPBBjutpg12zLMhnHegW/5/h5XTNUTKMSBTIx5bw7mDh0S1p8lKNZPCmhmyTTapViztrVgcx0XsmRo+p/Xagnsz1q2s8nxbvRe+oIgD8lPkc+pQRutrgd3endp/C5sWHju9BFfOzkFAEHHH4ko8811dH5ucnuBkRk7YQqrnfNDYT6HGUIOpwrVepw1FFD1zNqsVHp90gmD2JpvVuCf9X++8gw+XLZP//dyiRXhu0SKcM3cu7r/5Zry9ZAm+XrMGby1ZgqyMDPzikktw5fz58u2z3W7kut09mrBuv/pqWC0W/OPNN2Gz2fCLSy7BgrPPNuyYiaENe5MXZtgwu9iJAwtSsbnOgw+2tuDUSZm4/4tqfLqzDQBwUKETNxxJFr7hSENXACKkHdp4QXF6Gy/6IySIWB4OL4zO12GYqZCQFTsJFjJskWOk3L8pfCGrxfKQmWIBB6DdJyAoiJrrYfWGJbIL4dqOAEKCqPqCUKsNZ6o82DEu8F1uZVGwW8mO12grFrPhZKdaYLckfkyKM+2oag+gss2va1DBBvlqczVchoUnm6fYAYBzp7uxprJLrga/7nBj1DqAdF50WDl0+QV0+kOG/A1MsdOfVcxtkB2zN40m1/wCkuV3dKYNlW0BlGTadeWN5OiwniTCHxJQ1eYHh0hYNRD93jd3sBPJ2EmiFSvArFjano8MhwUtnhDafQJy4wsOY2JkeDIAjM2WnrP+muOYomdCjvFBxgOBVsUOe+0YbcNiWHgOvz+xCKMz7Xh4WQ2e/q4eNR0BPHhqsWxzjAQna38u8gzI2GHD7Xjh9UMNufJ8BFmxFL2K7/z5z/HAs89i+apV2LJ7N26+7DJkZRjXNf/ALbfggVtuifv9i884AxefcUbc78875hjMO+aYHl/jeR6/uuoq/Oqqq4w6TGIYURul2OE4KUzy9k8q8NzKBjz9v/oeJ0a97TvE4EVWbiWQ/meYLD/fVNuNpu4gijNsMdsQXCZmmigJjzXCt90bn47dUQvPITPVglZPCG2ekHx8amnWKX93WHnkOq1o7A6isSuoOrdES905ELnw29nogyCKhgRRqskXiLRiGbu4q+tQZsMBgNEZdqxGl+5mLJ8cmKrudSgHSBvUiqVWtaWU0ydn4sEvq+ENijhunAvTDAyn5DgO+Wk2VLT50dAZhCvbiMFO4kYshjtFep0abcViNoT+FEN64DkO503PwtPf1esOqzUrY6eyLYCQKDXQRWfOuJJmxVKupItuxRJFMW7oen9ErFja3ot66uCbDQ7uZcPu/qxYTI0+Ltv80ORkoFWxY/TjH48rZuWiKMOO2z8uxzs/tuDIUhfOmuYGoD84GYhcqzXpUewkYbidTPQqq4ciis5gc484AosXLsRNCxbgvWeewdXnn2/2cRGEqbAFfWE4AHXe5EyMSrehpiOAxu4g5oxOww1HSCodowMaifg0dQVx9ss78eoPyWkpq5NfB/EXEnqDEftjTTjL4Pjx6TEvSo2yfcRCVSuWgYMdT3iwk2rTdhFthB0rEhytfUEasQSp3w1qVKGSiSbbaUW+y4rugGBIgLA/KKDDJ8DCQVHVaGSoYezrsZ4tqhWouIozw5XnOpuxIvYLdYtBo7JG5FYskwY7LocFF87Ihs3C4aajCgz/+Uxx12BQsLrS14BZGTv1SVrUXDk7F5fOzJavMbRiVitWWXgg0FsNl7zwZOXnRqedR4qVgy8owhPQXsOu9VzAkJW9WgY7Hn3q0d6w521/P4od9v1xBtkzBxrNih05vNr8YcbJEzNwz0lSjMijX9XInwF6q86BqLpzQ1qxhsdgR7Zi6bRtDyUUXU28+fHH6PZ6ccDEicjOVBew9ebHH6OlvV3TwRGEWdT2WtDbLBzuOH4UijNsuOuEUXjl4nGYPkra3TT64pGIz4r9HdjZ6MPzqxogKKjq1At7HSRSW7DFrlnycznIO87FlVkKCUBZtkqeCbvCTCmhVfbOLuD0ZGyoaYKKR5HGyvOQIKIiPJTRsms/Jde4nB12EZyValWk/jHr9SirNZQodgxqxmIVxw6VA8Z0ZsXSW3fOFDsG151H8/sTC/H9DdNwcGHsFlE9MGWNkvYdJagNT241cNPFHxLQ6gnBwinLdtFDusOC+04uxkE6nxN5sGNwxs5+ebDT89wUsSAmR7Gj9HnIilLtaEU+F2hU7DBlrxbLdovOIP/ejAl/plS0+hAU4l9HRRQ7w2Oww2zabd5Qwr+7N0Zs8qjh/AOzMLMwFQ1dQTz9XR1aPUHUdwbhtPHyZ5sWjGnFCjcDDpPBTl6aFRZOspjpLVsYKig6gz3+4ot9mqmUIAgCHn/xRdQ1Jmf3nSCUwsJbowPjzpzqxrLrpuLqQ/PAc5ysCjA6oJGID8uCaOgKYnOtcRki8ajtjFjy4pFhsmKH7RLHW8w4rBysvDQM8YeM+2DyhwS0h5UamQmUGjkm1J3rCaoEIhkbehQ7ahcPsYg0Y6l7bGo7AgiEROSlWVVbsQBjA5TV7lammaQgkxf1Crz9LHS7SudgR6slMD3KitU7BFMNXX5zFTuAZF1MN2lwxJQ1RjVjRYZ7iV+L7P1v5KYLG45kO62mBKiagTzYMThraF9YyTGmj2JHetzNyHuLplVl5gxbkOvJGmKLPkecrL3+SGcbQCrPi6IoqgqLVkKKjUdhug1BIf45MiiIqAhfb42JUxwx1GA2bUBd/pbWdkSt8ByH+04uBs8Br/7QhE+2S3meE3McuqzV2alWcJCui0IqBlvRNMiKneGRsWOJKluoNbDBcTCj6FUsiiJ27NuHUEjdyTwkCLouegjCDARRlBcRiSw4NNhJPmVRnvBle9p172j2R217/4MdPRJrJfS3mOE4Di67Ba3eEDp9ArKdxiwCW6LCgxNdTGSmWGDjOXT4BHgDAlI02qei0Rpay9BbeR4IiWjzhsBz+upNi9K1NS6wAWapxowNQwc7Kncr2a59l8HvB6WLeiDaiqXvQs0rZ+yoex3arTzsFqne2BsUkWrT9jqWW7FMCk82GxasblQzVp1CxU7ks9m4gYYcGqoh0H2gcKdawHOScklPkHxvBtKKFQiJaPcJ4BVaQwFjKs+9GvO2GEzFp1ax0+kXEBBEOG28IZ+tjLFZdtR0BLC/xd9nQAdIaseAIKIw3QaniYPlZJOdakWrJ4QWT0jxcKJFZ5GCFg4oSMWlM3Pw2vomPPJVDQB9jViA5Dxwp0oh3i2eoOrhTLdfQJdfgM3CIcOEpsaBojDDhqr2AKrbA3Hbb4cTil7FhXl5+Pf772v6BUX5+bAa2KBFEHpp7AoiIIjISrUk/CCVdwUN3g0j4lPWGtld+nJ3B247ZpSpv0+NYqfDa46Ms0GBUiHNzqPVG0KXX0C2QbOuRoUV1zzHId9llT4YOwIYb4BsW2toLSNLZytOJMNBmf0oHlprt8tapYWT1p3SKXmSTdSIwU6TyuBIuRnHJMWOkhDqApcNVl5ajOsZNjLFjhb7RbrDgqbuIDp8Ic1ZUewxNKPuPBkYqdgJhEQ0dQfBc/3vnGeaEJ4s71Q7h85OtYXnkJVqRVN3EM3dQUU2RiWw7JXeViw5W8qEvDdGW3hYl5liUXxu1jvoByIqUs3hySnhoZdKNZOaRkI1jM1y4PvyLuxv8eF4pPf5/v5hZsNiaAlQVvsZaBS3Hl2Axdtb5YwlPcHJjFynFS2eEBq71Q922OOQ57RqDiEfjEhZqt0jJkBZ0at48cKFZh8HQSSN3vk68ciICmjU07ZAKIcpGewWDjsbvaho9etuDklErYJWLJeJVixBFOUFRSJPs3RBHTA014R9iOcq2KUak+VAVXsA5S0+QwY7+sOT9V3IR1ow9F1MRzJ21FmCZMVOlrbX9vhsB2w8h/JWP7r8IU12Loba4E45PNnojJ0uZY1IgLSgLUy3o6LNj6p2v+a6Xj2BqekOHk3dknpB64La7LpzsylwGZexw6yeOU5rv8oTMzJ2hmpoaI7T2MGOJyCgtiMAKw8UZ/bO2DFfsaPFImuMFUtf7ltkA0jdY9NicHAyY2w2C1CO3Yy1L06O0lBHy5Av2VYsRkaKBXccX4i7Pq0EEMnO00NOmhW7mnzS+SxP3X1Zvs5QOwf2x0irPB+a20QEoYOajv5VGgBgt/Bw2niERHMaiYietHiCaPOG4LTxmDshAwCwfK95wetBQRqqcEgs/Y/UnRt/MdvqCSEgiMhMSaweM6OJSElwMoOFMe5vNeaD0Rdgu6PaLqLZ49Gl8X0ZUUroW1Brzdgpl7MNtF1U2ywcJuQ4IALY1Zi40rY/WjRasQxvxepUZ4Uxwo7lDWhXjkVCpLU9Dv6QAF9QhIXTbkkcaNgwut6A/K3+ssaiMSNjRw4NHUJWLADICb9vjQq3Z2rC0Zn2PgM2l8Oc9340rfJgR/m5OVJ5rl+xo9mKJW8AqXts5Iwzg9Ui48IDm3jNWPuaw41Yw0yxo2XIJ4dXJyk8OZpzp7txwvh0FLismBEubNGDnhbToTrc7o+RVnlOgx1ixFGjULEDRFs+KGfHbNhid2yWHSdNlKTDy3abN9hp6AxAEKUPMVuCwESm3DJDsSPnivTzQeoyqIUnmsguVf8XM2PCF4nlcXb/1CCKIjw6rVip4ft5NLYceHUqhhg5TitsPIcWT0jODVJCWQvL2NF+Uc1ydrY36AsZV7uwiFixjG0kUmrDYRjRjKXPiqVPvdAVNVwcqmrQfAMVO2oyljJ7qWmNQFZOJnnXXi8s3N6oyvOyBBXY6SZucjCibbJKMTJjR+tmQ7o89BocViyWq8MsV72RG7GGSdU5Q49iJ5kZOwye4/CP88bgq+un6t5oAiIKbC3ng4h6fOjYUZVQpHEDbqhCgx1ixBEJzO1/tzzThJBGIjZMMlzqduC4cemwcMCayi5N9aFKUJKvA0Qt4Ew4DqW71PJi2sALajXyY3aRWGaAYscfki6gbRZOc/sMUzf5VAxTotEamtsbnos0Lii9aBBFEeWt7LWuXQZ/YHh3b0N1t+afAQBNKoMj5V17A1WM0TuFSl8TRjRj6XkdRBa5GlVjcnDy0L0MS3fwSLFy6A4Iugd9SqvOAWkQl2rlEBBEdGs8B/RGXtQYlFOTLIyuPGefw2NiWHTSTbJhRsMW5GpC7Q1txdJbd656sGOOFas4ww4rL+W/eWO8R5gVa7gpdtj7oU5h7pc/JKBDQTuomfAcpyvrL5qccEYYKXYiFIbXetWk2CGI4Yms2Mno/wIuemeQMJdyuWLVDneqFbNHpyEoAN/s6zDl99V2SB9i/Q12nDYeFg7wBEUEQsa2/LFd6kT5OgCQZsJiWosVqyyOrFsNTNmSqmOowu6rWbET0Ce7j6ZQZc5OfVcQ3qAU3q609SUWhxanAQDWVekb7DSrDI502iI2OMEgtYSaqnOGIVYsHfYLl8YdegarjNaTjzTQcBwXacbSqdpRql5kZIZfr0apaRuHaL5Ejo4d+lhEgpP7LvjNsmFGwzbRtCl29Fix9A37tSr4tCiUlGCzcLKqsbzXhkynL4SGriDsFk5WMwwX2Ot2XxylUm+iq+aNGq4MJLIVS8P5oLFb2fXoUCM6C3EkNHXTYIcYcdSEA7SUWLHcBl88JkIQRSza2IRv95szyBjslPXKHTkpnLOzbI85dqza8Ougv8EOx3FITzFHgq50lzrdbnzGjhrFzuhMOzgAVe1++EP6jsEnS961f/wwxQ7LSFGL3jyFaIpUKnbkAabOUPDJeSlIs/Mob/XraiVSmy9g4Tl5uNNt0KBRjQ2HYawVS1t4MqD9nDDUG7EYRjVjya1oChUzboM3XZS0Ew5GjB/sxK46ByKv1Q6fcRa43kQW2moUO0ZYsYzJ2FGr4DMz34XZrHoHKEcHJw+HYUY0E3Kkv3mvwsHOQNqwzIANdrQo+JQUeQxFXA4L0h08PEERrSNgk17zFUVVXR0eXbgQP/v973H+TTdhX6WU6r19717UNTYadoAEYTRKw5OB5Cp23tvcgvs+r8Y17+zHi2saTP99g40yWQIufTDPDefsfLOvQ/cwIRZKGrEYZgUoK13QMnVAlykZO/1/iDusPIoybBBEoKpN3wLOiKEKy8bRqtiR69Zt+i9qR2WoC+Zj4aQlOvJ1AMDKczikyAlAn2pHy4VtpBnL6MGO8kX1aEOtWMkPT2ZKn6FsxQIieQwNOq1AciuawuGekZ/NoiiioXto2hCMHuyUxak6B6RCCYeVQ0gEPBqH6v2hLWPHACtWWI1r19qKpTGLzywrFhAZzvUZ7AzTfB1AUmekWDk0dAUV2fhZaPpABCebAcvY0aTYka1YQ2u4rQRmxxoJAcqarii27dmD82++GZt27MDU8eOxv7oaPr/0YfDWkiX45zvvGHqQBGEUgZCIhk6pCUnJzqA7SRk7rZ4gHv+mVv73n76uxaPLawyzOgwF5ArosJKh1O3ApBwHOnwC1lXqs5vEQqkVC4jszhsdoNygMmPHyMESy1ZRGlbLnheWD6OVSNW59qEKW4jHyg5QdAwGWrGKmH9bqWJHZyNWNLOK2WCnS9P9teYLRCwZxrweWdaUUrUGILUX2Swcmj0hTcohQRTlxdyAKnaGsBULMFKxI91frWLHiB3Ydp+AQEiEy87rDlRPNpHBjv7HocMXQlN3EA4rh4I4n4vpJgT5R6MlYyczxQILF3ketaB3wyHNzoODZFENCcqPoVkeZBl/HmA5Sft6WaiZ3W645esAUl4N+7uUqHbWhzPqpuXpb6QaDOToUOwM14wdIGLHqtX5OTUU0HQGe/Lll3HK0UfjjT//GbdffXUPSeZRhxyC1Zs2GXaABGEk9Z0BiOi/CYnhTlIr1l++rUOLJ4TDStLw+BmjYeM5vLSuEb/9pMIUtcpgo9UTRGu46jxaBjp3omTH+tKEdiylVixAf1BqPJRm7OhVB/RGFEXVSg25ZUNnzo4RViw2FNLbiqW1ASUatRk7ciNWjB1xtcwO5+z8oHGw0+LRli8QacYaOCsWz3EozmA5O+pfk76oFhwtrVR6q59ZAO3Qt2IZ04ylJjwZADLlz2b9my4NnUMzXwcwVrEjBye7HXHPB7Jaz6RmrEjGjvJBB89xEdu8xk04vRk7PMdpUjKqzThTw6RcqTlxTUVXj01CWbEzDAc7ADBexWBnTaX02TmnJM3UY0oW7HXU7AmqGjCKohgZ7AwTW1o0Fx+cjSNK0zC9YHgM8BKh6Ypi+969OP3YYwGgzwWRy+lEQ3Oz/iMjCBNgNiylgXGZKdIJzkwr1o+13XhrYzOsPHDvSUU454AsPH/+GDhtPD7e3obffVpp2u/uzbs/NuOWD8tMbb2IRbRaJ/qccvQYFwBgQ40Jip1O5YodufHC4NeB4lYsg60vnX5pZ9NpU75DPcYdO4hRLZHwZB0ZO7JiR9vuLFvUG7E7X6g2Y6c1snjSy8GFTlh5YFu9V9N7tkUe7qnbLY40YxnzfqhTuahn6GnG0p2poVO5EGnFGtqKHXb+1DJcY/iCAlq9Idh4TrFSw23gZzOzYQ21fB2g52BHb+7N/gQ2LEa6CUH+0UQPm9UQsWNpez2wViy7RftngpbrBPb3mmHFOqTIiVHpNlS0+bGmIjL835cgR2k4wAY7e5q8CW/nDQjYWOMBB+DQ0cNjsGOzcMhKtUAQ1WVOtXpDCAii1HQ4xFSLSpg7IQP//sl4VargoYqmZy8vOxsVNTUxv/fjjh0oKSzUdVAEYRa1KvJ1APMzdkKCiPu/qIYI4IpZufIOy9Fj0/HKxeMAAJ/tbE+KJWvhqgb8fmkVlu5sN0Uhkwg5OLnXBSV7nvSEIsYiKIjyLq0SlUC6CRk7gijKTSz9NcHobeDpjZp8HYZced6iz4qlJ7CWoTdjx6Oz2jaa6MFOfwsrURTl17qeqnNGqo3H9IJUCKK22nP2OlC7iHIZHOatRbEDRBZzbRreF8zGp/V1qNeK1RVeGKcN8YydCfIiSvt5gal18tKUK8eM/GweyoqdFBuPNDuPQEjUrSgtU7DgN8MWHI3WlqhopYIWvAbkrrlUXid4AwK6AwJsPGdK1paF53DedDcA4N3NLQCk6479I0Sxs6cfxc7Gmm4EQiKm5KUMWNW5GWjJ2RnO+TojDU1nknnHHIPnFi3Ct+vW9Vhwrt+6Fa9++CHmHXOMYQdIEEYiV50rHOy4DZR7x+KdH1vwY60HBS4rbjwqv8f3ZoxyIjvVAn9I1C1zT4Qoivjrt7X484pIxs+WOo9pvy8WZS2xVQxsF0vrLlw8GruCCInSB6CSHTp5J87Ai9mW7hCCgvQas/czYDDa+hIZ7Ci/mJErz3UrdvSrZaIzdrTsUvtktYZ+K5bLYUGGg4cvKPZbt9viCaHLLyDdwRuWqcDsWFpyqJo17hZHrIEGZezIVdfqLirTdNih9AQnA/rtmREr1tBeUIzLdoCDFAqu1TZcp2Gwl2mgTZotavJUDhYHC7kG2bGi25LiYZYtGYA8nOK5yOBUKVnhz7IWjY+BEaH+7DpB6aBZHmI5LZrsoEq44MBsAMDSnW3o8IVQ3xmEJygiO9UyrIYZ0UzIkTZI+6s8H242LIaWnB35HDgMbVgjDU1nsGsuvBAHTJyIWx56CKf87GcAgF898giuuftuHDBxIq6cP9/IYySGKU0KU+uNpFYe7CjbLTcyoLE3bd4QngwPU+46oTCmJN8olUQ8RFHEo1/V4B8rG2DhgPMPzAIwAIOd1ti5Iy47DxvPoTsgyItxI1Cr3EpPMT48uV6hWgcwPqyW+fpzVCykS9zhyvM2v+aASiA630b7BbTNwsHKAyERCKjwkUeOQd+ivjeFYUtQf3Ys1ohV6nYYdiE/W0eAcrMG5RYApBloDfQEBLT7pF1rtcMuNvDU0hand7inV0UXCU8e2oqdVBuP0Zl2BIVIfpRatLSiGVls0CBnSwzN3epsgwY77Pkbk0ixY7B6NJq28HPpTrGoruFmCp/+huvx8LPMLQXZi/FQm8nYrNF2poYStx2Hl6TBGxTxyfbWYZ+vA7Aad8k27k9w3bg6bE87bJjYsBhs0KumqZC1gw1F1SLRE01XFFaLBX+/7z788dZbccysWZg5dSpmT5+O/7vpJjx///2wWIbnFJgwji5/CGe+vBOXvbVXty9cDdXtygNzAWN9/L35cnc7Wr0hzCp24vQpmTFvU2pQrkk8nv2+Hi+va4KN5/DXs0vxm2NHAQC21nmT2shVznYKeyl2OC6SuaCnyrQ3agc7GTqDUmOhZjFjdMYO251Ro9hxWHkUptsQEvXmaTDFjr7Bhp6cHa+BrVhAlB2rn8dFXjgZYMNizAordpisXA3NshVL20DFiMVdQ1TNtdphl55Qca/OEG/dViy57nzoXy9NzJXO27s12rGUZo1FY2jGTlfECjYUMSJAWRRFOTw5UQ223td9IrTm6wBRViwNj0FIEBEQRHCAolKNeLhle6CyY4gEJ5t7DrhghrRh9+6PLXKg8HAe7Dis0rBZEOMrjP1BQc5uHC75Ogx2HlWa+wcM70askYamZ3Dlxo04eOpUnHn88Tjz+OONPiZiBLC9wYsWTwgtnhC21XtxQJKSymXFjsLw5IwoH78giqp3kRKxbI+UY3PWVHfcBU2pQfaXeHy4tRUA8MSZJTh1sjRcGpVuQ21HAPuafbKk1Wz2x1HsANJuZENXEM2eEAozjPl9rPJQsWLHBCuW3AKjQDVjtPVFbSMWozTLjuqOAMpa/JqDF43Kt0m18ej0C/AEBWRA3YWx10ArFhAZ7PRXeV6e4HWulWynFeOzHdjb7MO2eg8OKnQqvi/Lo9BqxeoyYNCotg2px3HoaOgxLjxZqxUrrNgZ4q1YADAxJwXL93SEw0pjb1IkQkvGkpEZO41DfLeaWS8aNVQcM5q7Q+jwCXDZ+YRh6ukGNzRGE21NUgs7Zi0ZO9GfB3qUlHIzl2LFjrbzr1rmTcrEHx3V2FTrgTM8lB+uwcmMCdkOlLf6safJJ2dXRrOp1gNfUMTEHIfpj3+yYUM7NUr/yHB7aKoWiQiarijuePxxbNy+3ehjIUYQOxoiafVfJDGot0alUsNm4ZBm5yGIxqo1fEEB/9vfCQCYOyE97u0iih3jrVi+oICKNj94rucxsDrAzUmyY7V5Q2j1hJBq5WLakthulpEByrXt0utAaUK+nCtgoHKrvkv5YibFKlmPfEFRc45FNFotOLI1UMfr0WdAlkH0/Zn6Rg2RoExjFtVFcuW5MiuWEY1Y0TA71tpKdXYsll2l9nUQUZDpfz9oDU4G9Cl29FqxHFYONp5DICRqsonKGTvDQbGTI72edzVqVOyoGHIzjMzYaQq/D4bsYEeHWoWxvzUSnJxouOFKgmKHqbHUwBbnWqxYPp3qPYZsD1R4DHIjlolWLED6nDtzqhsAsLJc+owYzoodIPL3xas8l/N1hplaB4hkZO1XYY1lQctDVbVIRNB0Fpt1wAHYsW+f0cdCjCB2DsBgxxsQ0OIJwcpHPKhKcJvQjLWyvAvdAQEH5KfI+RyxYAtpM6xY+1p8EERpeBQd3ju9QNrdSFbODttVKI1zQRkJUDZwsNOpUrllomJHyQcpx3GGqiSaNC7o5cpzjVkaQKTuXK9aht2fDWnUYLQVa5TCynP2uBnRiBWNHKBcpS5AWd4xVt2KZZw1UZdiR0eouN7hHsdxuha5kbrz4aHYAfqvF46HluFe9OeyXjt3xBIzNBc1bCClx4rFmpISBScD0Rk7xit2WmUrlvphZ5aO4ZYRTY1AVMaOQisWC3p2m2zFAoALwvmJjHEGqkYHIxNyWDNW7HMSq38/bJgFJwMRNdY+FYodsmINH7Qpdq69Fp989RXe/eyzpOajEMOHnY2Rk+2OBi8qTLIaRcMW8wUuGyy88g9wtwmKEWbDmjshsbdItmK1+A1/r7F62om97FYHFki7/8ka7LChVbzcEfmCzYCdWYacsaNUsZNi/C6l2sDQNAMrpps1WrGMUewYE1zMFuReDWqJSHiyMVasIhae3E/GjvxaN/iievboSICymvNE5HWgMWPHAMVOncZGLEBfkKvXgMWcnoYg9tgN9bpzIFIvvL9FW7C6lowdh5VHqpVDQBDRrUG1xxBEUZcFaDBgRHgys3v3Z9GJWBDNUOxoqzqX7sOu07ScC4z5TFJrxWIbAclYTM8YlYrJYUuShZNClYcz7JwUqxkrEBKxvlraBBlujViAtFnotPFo9YQUr1uYHZUUO0MfTWexB//xD3i8Xjz03HM4/Cc/wREXX9zjvyMvucTo4ySGEaIoyoMdJoP8co/5qh21NixGpsEByqIoRgY7ExMPdtwpUpVyd0DQ3XjRm91h2Tzb2WAcGLZiba3zIqShcUgtsj0lzgWlfME2CMKT2w0NT1a3mJEXsQZcUMt15yovoMdEDRq1whQ7eurOASA1fBHu0WTFCit2DLJiKcnYafUE0eoNwWnjVSkGlVCSaUdemhUtnhD2qXhuIuHJaq1YxuVs6LNiaVfsGDFg1BMkG8nYGZrDhGicdh7FGTYEBFGTbVhLKxYAZKbq/2xu84YQEoEMBw+7ZWgO2YyoO2eKnf6GzuaGJ2sLcwciQ1YtQ15fyCDFjsoW1Y3h8N7pSciY5DhODlEenWkfsq91pbDBzt4mX58ikK31HnQHBIzNsg/LTBmO4zAuW921Wj0pdoYNmp7BvOxs5GVnY9b06UYfDzECqOkIoMMnIDvVgosPzsaayi58ubsdV83ONfX3slyVQpWDHaOtWFvqvKjvDKLAZcUB+YnDiTmOQ4nbgS11HpS3+pFr4IcQk833HuzkpFnlAOX9LeYHKPfXFKTHOx+LkCDKC4kChYtJebBjoB2vQUXGDhDdRGSAFcuj7UO8lFWet0s781oaRCJ5BjqtWOFWLW0ZO8ZasfJdNvAc0NAZRIcvJC8yopGDk912w6rOGRzHYXZxGj7d2YYLXt0Nu5WDhePgtPF44NRiHDXG1ec+/pBUM85z6q0ARr4W2YBTad5VNGk66s6NeA2kabRHCqIo38dp0HBxoJmYk4Kq9gB2N6n7zOj0h9DlF+CwcshQGSSdmWJBbUcArZ4QijQG62tVLw4mmOJOz2CH2Tb6VeyYaMWSM3Y0KHbYZ7QWJZFRGTtZKtTdzd1B7G/xI9XKYWpecspDzp+ehW/3deDEfpTiwwF3qhU5TiuauoOo7QjIqlogquZ8GKp1GGOzHNhS58X+Fh9mFiUuVPCHBLR6QuA5bWo5YnCh6Rm8/+abDT2IUCiE7zdswJJvvsGnK1bg4V//GvOOOUb+/rotW/D6Rx9h3ZYtyMrIwPmnnILLzjkHPB//JHz7o4/iy5Ure3wtNysLX7z0kqHHTqiH5etMzkvB8ePSYeWl0M8WT9DUk0qN3IilToKaKQfiGaMYibZhKVngjXHb5cEOqzY2gj3Nsa1YgLSDVNsRwOY6j+mDnegFbyzkGlODHv/G7iBCopQvY1d4Iee08+A5oDsgICiIsKqw8sUiJIiqPc3pBil2AiFR/hBnr22lOKw8RqXbUNMRQHW7P67KKhGsFcswxY6GjB2jhksMm4XDrGIn1lZ248kVtbjv5OI+t+nPcqiXM6dm4vNdbegOCOgOC4eaALy5oSnmYCe6Wlht219koGFAeLLKAWc0evI+vAH9r4GIFUvd49AdNdRRYwsezEzMdeDrfR3Y3eTFPBXNWA1RWWNqB55GNGOxAPGhPNgpcNmkgXtbAHUdARSo3Lxq7g5iZ6MPdgsXs0EoGiOVo73Rk7ETbVVW22BqVOYaC31WothhVqAZhU5dFetqyEix4J8XjkvK7xoMTMh2oKk7iD1Nvh6DHZavMxyDkxlqcnaiSxSGy+fRSGZQbBW1tLfj4eefx9rNmxESel6gfb16NW68/37kZWfjj7fcglOPPhpPvfoq3vzkk4Q/s72rCycfeSReeuQR+b+//O53Zv4ZhEKYDWtybgoyUiw4vMQFQQS+3tth6u+t6ZAWVmoVO3L7hkFqDaU2LAarRtZjf+lNICRif/iEPy7G4pzZsZKRs7O/n51CucbUICtWnWzDUn4hz3OcLql3b5o90nApK9WiWBLNVBJ6JfBMdZSRYtH0IS7nPmnMxfIaVHcuZ+xoUOzIdjCDFDsAcM9JRbDywBsbmmO2UzHLYalJNbOnTs7EulumY+WN0/D9DdPwnwUTAEjtH7Fyd1rkwFj1i6hIK5a+XXtRFHWFJ0eql7Xs0utfzKVrfE8Op6pzRiRAWZ0Viw3stdgT1VpfYtGksSFwMOFyWDBvciYCgogXVjeovv/Kcqmhc3axs9+Be+RzyMS6cw0bfBaeg8vOQ4T6Qa8vZMygn10rtntDfew/vWGDnVn9qCkI7YzP6duMFRJErKtiip2+Gx7DBbkZq7n/6zSmHicb1vBA07P48fLl/d7mrBNPVPzzcrOysHjhQlTX1+OM667r8b3xJSV4+Ne/xtwjjgAAHDdnDhpaWvDO0qVYcPbZcX9mW0cH5hx4IA6ZNk3xcRDJYUeUYgcATpqYgf+VdeKL3e2YPz0r0V11EZH8q3vZZ6nYhemP6nY/ttV74bTxOEKhDJRVI5e3GVd5Xt7qQ1AAijNscMYI75yepMFOuzeEFk8IKVYOeXGeF6PDkyNZS+qUE+kOHm3eEDp8Atw6ldNaFrNpBuWasMGKU+OCdmyWA6squqQ2s3Hpqu/P1DKpuq1YTLGj3gbjN+hCPpqpean4+WF5+MfKBtz9WRU+uGJij+FVhcmKHUBSQbGFWVaqBfkuK+o7pR3Lib124tn7SYtSIbI7LjUSabWWdfkFdAcEpFo5Te1QqTYOPCeFn6q1Bnp11p0DUYodle9JNhweDlXnDK2V56067DfMQtimsIUoFlqb4QYbNxyZj093tuGtTc34+eF5qqyN/yuTBjuxlH290apSU0KLDsUOINmxOv0COnwhZKhQo/oM2myw8hzSHTw6fALavaGEr+kfwsOFQ2iwYxosZ2dP1GBnS50HnX4BJZl21XmbQwlW965EsSOrx4fwcJuIoOlZvOepp8BxXJ9dQHZxZ7VYVA12ElFSWIiSwsIeX5sybhyWrliR8H7tnZ3IdrsNOQbCWJhiZ0p4oTF3Qjoe+BL4dl8HvAHBsEDT3rCqahaGrBQj5N6M5XskVdKxY12KbUClBlRM9yZeIxajd4CyWfLMaBtWPOk0u+A2Kjw50oil7nUgXdAGDKk8b5CbgJQfg1G5Jmx30q5xQatXscPUMnovotlgSK1iJ9qGZXTWzQ1H5GPpznbsbfbh7yvr8atjRgEANtd6ZF+/0VXn8eA4DnNGp+GT7W1YXdnVZ7BTFr7g09KCYbfwcFg5+IIiPAERTru2x5E1YhWk2zQ9FxwnDYTafQK6/IkXUr0xIldDVi5pVewMg0YsBtsd39fiU2VX1ROYyz7LlbYQxUJrM9xgY0peCuZNysDSXe345+oG/GFukaL7iaKI7/azwU7/g/oUKwcrD/hDIvxBQfF1jBLYa0HLkA8I28Q6AqqHTka2JLpTrOjw+dGaYLDjDwn4sVbaNOsv/4TQDsuP3Be+3g0JIv70dQ0A4Jixw1etA0QU8GUtvn6tiWywMxyDpEcims6ebzzxRMyvL1+1Cuu3bcPz99+v66D6Y3dZGcaXlCS8TXtnJz5ctgx/e+UVcByHIw4+GL+55hrkZ2ebemxEYvwhAXubfeAA2ctdmGHHgQWp2FznwXflnf1WgGuFXXynqw1oZLuCBihG1NqwgKjBjoGV8LubYjdiMZIVoPxDtbTYTRTY6E61gIM0WDMi30ZtIxYjXW7GMiJXJPxBqmJX1WVQrolf5+4kk/hqHTQaYYEBtCt2zLBhMexWHg/OK8alb+7FP1c34JBCJz7Z0YYPt7YCkBRyB45KTlAmAHmws7ayC5fOzOnxva/C1tfDS7Vd4LrsFviCQXT6QzFVf0qQlWs6LihddgvafQI6/eqUdEaEJ2tVLzDr2HBoxGK47BYUpdtQ3RFARatf3jHuj9aorCe1GLHpMhysWIwbjsrH0l3tkmrnsDxFitD9LX5UdwTgTrXggIL+P+c5joPLYUGrR1Kv5hh0Hg2ERHT6BVg49ddojIwU6X5qP6NlxY4BTVHuVAsq2sKv6zgC9G31XvhDIiZkOzQPsYj+6a3YeWF1A9ZWdiMvzYpbji4YyEMznXSHBblOKxq7g6jrCCTMFm2gRqxhhaaz2LQJE2L+d8OllyLH7cbCt982+jhl2jo68OX33+PEww9PeLsDJk7EnBkz8ORdd+GmBQuwatMm3PbQQxAE433BhHL2NksWoFK3vYeX+6TwoOOLXebVnjNPuNqL6YiPX59ipNMXwqryLvAccJwKC0temhWpVg6t3pBhzVzxGrGiYaqdzSbZsYKCiJfXNgIAzprmjns7C88hM9UCEcYM19hgR23ApNy6YcBzoKXiOd2gXBM5T0BjYGNp2BpYpqHWGIiEHafa9A3o2GCGheAqJSK7N0eFNrs4DZfOzEZQAK5/rwwfbm2FzcLhmjm5eP+KSXLwcDJg4ZCrK3rm7HT7BXwXtl+cOEG9nQ7QVzXOqNNRdS4fh/y+0LZLb0x4slor1vBT7ACRzxP2+aKEiEpD/fvCiIyd4RCezJial4pTJmXAFxTxrzXKsnbYeeDIUpfiwGE92VbxYNdXbg1h7vJxaXw/Ghmm71ZQtiHbsIpJrWMmo9JtcNp4NHUH8b/9HXj6uzoAwCOnjR4W7/f+GBuuPN/fzyacPNymwc6wwPCrihMOOwyff/ed0T9W5qlXX4XdZkuYrwMA/3zwQdx82WWYM2MGfnL66fj99ddj6549WLdli2nHRvTPzl75OoyTw4OdL3e3G9Y+1ZsOOddAfaUqoN+K9WOtBwFBxIxRqao+VDiOkwNXyzUupnuTqBGLYXbOzpIdbahqD2Bsll1+/uORZWAzVm2nttr7DCMVOxqUCkyxozfbQG+eAFOQVbb5ERQ0NFIZZMXSqtjxyoMl8xbVtx87CsUZ0nN75tRMfPqzybjj+EJVuQ9GMCHHgaxUCxq6gj0Uf/8r64A/JOLgwlTN8mutNqRo9AQnM9igTHVgqgGKHZdd22MgK3aGUcYOEPk82aUiQLlFh2InkrFjhBVreCxqbjwyHwCwaGMzGsOhqABiBqgDkXydoxXk6zDYe9/IAOWWbn35OkDU5otqK5YxKlIgYiNLNGxcX0XBycmA5ziMCw83bvmwHEEBuHxWDo7VkA04FFHajEUZO8MLw69sN+3YgebWVqN/LADgk6++wgdffokHb7sNKQ51zSJHzpwJANhfVWXCkRG9EUURz3xXhxX7ejZd7QwHK07plfcwKdeBOaPT0OoN4eHlNYYfjyCK6PJrVewYE57MBgJaFlJjDLRjhQRRbglIpNhhg53NtcYPdkRRxMJV0o7itYfl9Zvhw5p7jGjGqtNqxUoxppUKiFQ8qwnyNqqJSO/uZIqNR4HLiqAA1LQH+r9DL+S6c90ZO9pasYxq5UqEy2HBO5dNxOfXTsaTZ5VidGZycnV6w3J2AGB1VFPXst3SefkkFZbQ3kQqz7W/HvVUnTPYcEWtRXFAw5PDt08bRq1YADAhV/o82a1CscM+V90ahp6ZCtQR/dHUPTzCkxnT8lNx0sQMeIMi7lxSiTsWV+DC13Zj9tNbcd4ru2QrKiCpZleVKw9OZjDFToeBih09yi2GVru0oYod1qIaR10siiJ+CDdiHVI8fOu2Bwvjs6W1RqdfwKQcB35z7KgBPqLkwQY7+/sZ7JBiZ3ih6Vm86Y9/7PO1YDCIqro6VNXX46wTTtB7XH3YtGMH7n/2Wdx6xRWYM2OG6vv7A9IFpMtJE/JksLXei6e/q4fLzmP5dVPlnep4ih2O4/DgvGKc8+9d+GBrK86YkokTDMza6fILEAE4bbzqjJbeFZZaZcLd7GJeg/y+xG1c5XlVux++oIh8l1W+EIoFs2Jtqzc+QPnrvR3Y2ehFvsuKcxPYsBhsN9WIZqxGjZkKsmLHq3+XkikVtGTs6K1bl8OTNVqxAElhUdcZRFN3UH5tKv797CJapxUrJXx/9Yod/Qt6JWQ7rYNCBTCnJA2f7WrH2oouXDQjGyFBxPK94awvHefYiBVLj2KHDXZ0ZOxobIuTrVg6lFuRRZy6wUKnRvXoYGeShspzPRXXLDxZl2LHwz4Pho966sYj8/Hl7nZ8Gw5FZmyt9+KF1Q1yvsimmm50+gWMzbKjWMXw2Qi1Xm/YgE/L64DB7MrtKl8PRrViAZEBZUsc635lWwANXUG4UywYlzUwA/+RBMvZsVk4PHFWiWnlLIORcQorz9k1MSl2hgeansW9FRV9Gix4jkNOVhbOPOEEXHneeYYcHGN3eTlufvBBnHvSSbj83HNj3qajqwvpadL0e9XGjRg9ahSKCyLhWF989x04jsMBEycaemxEbFh2QqdfwGvrm3BDWB68I9yINTm3rwVobJYDtx1dgD99XYt7Pq/CJ8VphlkXZBuWhh1SKy81r0g1moK8S6gWtqOsZbAjV54bYMXqrxGLYWaA8sLVklrn6tm5ilo15GYsnVYsURTlwYJa2bWRNa/1Glqx0gzINAH0hycDkaFYk0oFlSiK8o6xXtk7U+yw51MpXo3P/1CFKXbWhBU766u70eIJodRtlyuqtSAPVHTYMYwJT9bWFuczYMCn9X0gq0eHmRWLKUD3NvsUbwboqbh267RJBwURrZ4QOGhvYhqMTC9IxUPzirGnyYfx2Q6My3ag0xfC9e+V4YXVDThvehZK3HY5X0eNWgfQnmWTCGYHMcKKpfZcYOSwnw2m4il21ldHas6NbmUk+nLqpAy8t6UF1x+eh6l5ySsuGAwoVuyElbPDIUCe0DjYWbxwoaEHUVZdjea2NjS2tAAA9lVWYv22bcjOzATPcfjlffehtLAQ5518MtZv2ybfrzA3F6Py8vDmxx/jsX/9C0/edRdOPPxwLPnmG3yzdi0uOPVUzJgyBTv27sUL//kPLjrtNIwpUlYBSegj+kL33+saceXsHAQFKbg2xcrFrfy9cnYulu5sw4YaDx79qgYPnzbakONhH/TpGi+k3akWdPoFtHmD2gc74QWtU8OOQWmWcVas/hqxojkgPwW1HQHsaPAaNthZW9mFdVXdyHDw+MnBylrqspzGWLEC4UwYG8+pViBp9e/3JiSI8vsjV8WCll1M623FkhUzOhQ7soJK5fMRCIkQIT3+etvN5IwdtVYsgwZLQ4XJuSlId/Coag+gqs0faeabkK5rYWGsYkePFUtbkKsRAz42cG7uDkEURcWPZ6QVa3i9BtMdFhS4rKjrDKKyzY8xCdoOGa06LDiZUeHJah7/6N8thn+33vPRYOPCGX0/W8+alomPt7XhT1/X4Jlzx2jK1wEin0VGhifvC9vDWTi/FvRbsYxpxQISDXbC+ToUnJwUJuam4PNrpwz0YQwIpW47OEh5iP6QAHuM1jd/UEC7T2qj02ODJAYPmq6mftiyBVPHj4czte/0s7ahAdv37cMJhx2m+Of965138OGyZfK/n1u0CM8tWoRz5s4Fx3FoaGlBQ0sLLv3Nb3rc7xeXXIJfXHIJst1u5Lr/v737DpOrLtsHfp9pO7s72zfZbJJNryQhQGiBKBLFUEQQQXgBFQEFpKsogsorSqT5iljAoPKiviDF0OFHMUiH0JuJKZC2advb9Jnz+2Pme2Z2d3bmnDPfM7N75v5cl9clW092Z2fOec7z3E8tanyJF6drLroI9z35JJ5/4w3c++STqKuuxvmnnYavn3iimX8umdAxkLrg6w7G8Pf3OrG4OfFCNqvBO+JFtdOhYOXRk3HiXzbhHx924Zi5NVKCzsQsuNk1mjVeF3b0RNAdiGFKrbljSI1iGX/ylJmxo23E0rGOVrRniw4sGf6Y7NY5Y/8G3Xes67SOnXxXfSfHkEzcmdPavPMs7HT4o4iribsjbgPFFVmBlaFY8Tp2tIvpPMewgLSMHZPhyVaPYo0WToeCAydV4rmP+/DGjgH8c1P+Y1hAekHF/ONR/C2ZLZYD6WMh5jp28vk78LodqHA74I8kujn1dpimtmLZ70R6dqMXe/r7sakjlLOwE4urWreNGKsywut2wOtSEIyq8Efihl9bxUasBht162Tz/U83Y82mPjyzsRdPb+jBezv9cCrAIVOMFXZEUVdG96qQrZtbL7NdtZZsxRphFOvtZHDy/hOZr0PW8rgcmFTjxo6eCHb0RLSxtHTtaeHxZmMmaHQx9Wp27o9/jDtXrsTiefOGve/jHTtwy113GSrsXHvJJbj2kktGfP9PL7446+evWLYMK5Yt0/5bURSceuyxOPXYY3UfA8klLvgOm+rDK1v78ec32nH2QY0AhufrDDWzwYuLD2vCL1/cjWueacWz35yb9xOOlmlgMDhZkLFWdSCPjJ0mnxtup4K2gSgGwrG8VibrHcUCUiMSe/rkbCrb2B7Ecx/3wetS8LUDGnV/nqzw5Hy6VWS1n2v5OgaD6sx2JgwVyqO4JYg8CqOFnYDE7SPiJDxgct15Kc3aHzg5Udi5/4NObOkKo8brxJLJ+V1YyMjZCOTRxagdR94dO/m9tjRUuODvCaPDH9Vf2NG2YtnvMTizoQwvbenH5o5gznDu3lAMcRWoLnMYKnKnq/E6EeyPoido/HWxI2Aub22saqpy44JDx+GXL+7B95/YjpiaGAnKlrWXiYwxzHSqqmJDsrAzN8f5YTbi729UbMXKcBOqPxTDhvYgXA5g4YTSGgui4phWV4YdPYk4hYyFnQFz56M0epl6FsvW8rpu82Z0WLQVi8YOcQF+4oJaLGgqR7s/qm1BGroRK5OzD2pEXbkTrb0R7UI4H+Ji3OgJjCBjraoo7FSYOJl3OhS0JLtntveY79pRVdXQKFZTVeLJXlbHjmj9PnZuraFgWfGx+WbsiG4VPbk+Q4mTxnw7dsxuAvK6FDiVRGEmHDN/Ql3MUaxUl4SEjh23ua1YsjJ+xpKDWxJFnDd3JO4WHzGjKu/Rk3w7dsKxOKJxwOWA6Yt6ILVZynh4spzHgShydhp4buo3uaFxLBA3DDbpCFAWF7/55NvkE6Asnr/qbBScnMtZSxoxtdaDQPJ1wGi+DpDqXpXVsdPuj6I7EENVmcPQpsihRKG012j3XsyKjp3hP5v3dwcQV4F9xpdrr19EVpouVp53Zn4+7jC5TIRGL92/yW/++MdIf8q7ftWqYRum2rq6sHXnThxx0EGyjo/GqPSU9W8fOg4XPrxNe6HL1bEDJAKLp9WVoSvgx7bukOHV1EOJExDzo1j5r1UdiCTDk02+oE+t9eDjzhC2dYVNh8Dt7ovAH4mjrtypq7DSlNxWI4oR+drVmyhKzTAY2qplWeQ7ihWT0LGT59p7s5uAFEVBVZkT3cEYBsJxeMrNPY7CRRzFEt01+a46B1IX5EZHsWS23Y8V88eXayNDAPBZCRsHK/PM2NEeC25Hnlk/yewpo+MXETlFRjNFztQolv0u7pqTr9V7ddwMSG3EMl9YyZVpkk1nCV7UeFwOXHVkM857cCsAs4UdueHJ2rbURm9ezwVmO3akbsXKsinv7dZkcDLzdahAptdnD1DWrtXYsWMbup/Fpk6ciNrqajgciZOw3v5+dPX2DvpfVWUlTj32WPzkwgutPGYaA9JPmJbPqsacxtSFvJ6OHSC14ltGrkxfnpkGNXlu3wDyG8UCUgHKW/P4eWzu1D+GBaQKO7JGsXb2Jk72J1YbK2rUyR7FMnExV20ymHGoNpOjWEDaxXQeJ9QyChupwk7xTqDLxbpzo+HJyWMopTumbqeihXW6nQqWTTd+MTeU6DYZMPlY9CcLQvn+HnwmtsWpqiptO5qZImdqQ6L9OkVS3ZW5nxvEzZ5aE/k6Qj5j0qV6t/ozM6vx9SUNWDGnGvtNNF5kkDUWLGyQkK8DmF9wIHMrVoU7MVYYjKrDuknX7U38O/edwMIOFca0HCvPRR5qqT0H2pnu3+SPLrhA+//7f+lLuO7yyzNm7BABqbnNhspEINf5h47Hdx7bjsYKFxp0XtBOqZFX2OnXwpPNjmIl56alFHbMHUPq52F+5bmRMSwgNS60pz9iauvIUGYLO+JioTtgbvuJIAoLmbYD5OIrc0BB4gJS7yrfTMTjwMxjMXExHcnrhFoLTzbxMxDMjmKJIoyMoorIyAkaXHcekDgONpYcOLkSL23px6EtlVJCe80UVNL5JeTrAGlZPwb+JtK3s5n9OxbMFHZSo1j2Ky5qRXgd3a1d/vw7dlI3XYwX/UV4cl2JhCenu+pI8xtiqyTka6Xb0J44L5mdZ2HHlzYiZuQ8QeZWLEVRUOt1om0giu5gDBPSnt/EGP00HdviiGQQj7VP2LFTMkyvO2+srZV8KGQXsbiq3a0TJ0xHz6nBJ4eFDAXjye3YyW+9rHZXMI9RIHEhY75jJ/EEnc/PQ9uIpbOwU+lxwudxoD8cR3cwlvcJ8K6+ZGGnKvO6+5GUucxtnxkqnMcsvUNR4CtzoC8UR384bnqTTz7ZHj6JHTv5hCeLC7GuQBRxVdUdbh6UOAYlfn6BSNzYSXxETqfGWPNfi+uxszeMM/ZvkPL18r1rL0ax8i7siOMw8Dch83GYKnLq+zmoqqpdEJt9LRjN0jcY5vq7HHqeYEY+3bSdJRaeLIv4m5M9ipVPcDKQuGEjtqQFIioqPHoLO3KL/XXlycJOIKrFCKiqiu3JczdxbktkteZqNzzJxSv94diwmzrs2LEfU7/J5nHjZB8H2UhXIAoViVljEdDpdCi46LAmQ19nigWjWFV5j2LlkbGTvAAyeyEjVp6v3T6AJbd+BBWAqgL7TazAqpOm6Qog3WRgI5bQ5HOjvzOEPf2RvE7Ag5E4OvxRuBzm7g7UVzjh74mjK6B/+8xQqY4dcydw1WVO9IXi6AvFTBd28hmFktECH5YQnuxxOlBd5kBvKI4eAwW/kMQxKJdDgdupIBJTEY6pun+eMjdzjSW15S787POTpX09X54BqrK6t7TVywb+JmRuwTHasROMqoipib9/M52Do12524Fyl4JAVMVAJJ61O0wbxcorY2fkLUS5lOooVr608GQJo1ixuIpNyRtO+XbsAIlO2GA0ir5wTPeiCq3QK+nvMTFaGEJXWrGxKxCDPxJHdZnD9LkDkVEORcG0Og82tIewtSuMBU2D8zlTHTv55ZjS6GHq1Swai+FPDzyAJ55/Hrvb2xGJZggJW70674OjsUnkbjTmebIkCjvb8xg9ElKjWCY7dvIIaBT8eWbsTKrxYHZDGTZ2hAaNP7yytR//924HzlqSe334ti7RCqz/jlFTlRubO0PY2x/FvDxquqJbp8nnNjX+UFfuwo6eCDoDUUw12cqc6tgx9zsQo1D5bAPJ56KyyuQGoHQhCeHJQKJToTcURqc/qruwI3sMqtyVKOwEInHd/56QxDyFUpb/KJakjB0Tq5dlBmgbLeyI1yKzIfpjQV25C4G+CLr8w+8Qp0uFJxcnY0eMktaX0FYsGaokrjvf3hNGMKqiyeeSUvCoKkt0y/QFY1pGYC6yXxMynS+KMazJNezWocKaVleGDe0hbOkKDS/ssGPHdkz9Jm/961/xt0cewbwZMzC+oQFNDQ2YPXUqOrq7sfb99/H9c8+VfZw0hqROlvJ7omiocKHCnegK6A5E81qJqm0hMZmxk89KVWFAG8Uydwwuh4KHvz4bfaEYHIoChwK8uq0fFz28Db95eQ++MK8ma9XdH46j3R+F26noPuEBoK0fzXfluSjsTKo2d2KjbcYyGNibLt9V31qAch6Pg3yCGiu1E2oJP4M8T2IbKlzY0hVGhz+KmTqne8T3lrEVC0jk7PSG4oZydrTQXBtfWBdCVVp4spncK7+kUSzx+f6I/uwrmR07RvOm8n0tGgvqKlzY2RdBVyCadewkNYolI2Mnn8IOL2qMqPAk8ub8kTiicVXrzDZjo6TgZKG6TKw81/94kJmxA2TejKWNYbGwQwU2LcvKc3FDwswyDxqdTD2LPfPyy/jWV76Cu2++GSuWLcPiefPwg29+EzdecQUWzJ6NaExOoBoVzge7/fjCnRvw2rb+vL9W+qrzfCiKIi1nJ7Xu3GR4cp5bsaJxFaGoCoeS310hp0NBbbkL1V4nfGVOHDW7Bp+ZUYX+cBy/fGFP1s9tTa4an1RtrGNmvLYZK7/Czs7k9282GJwsiLuqekI5RyK6VTwmT+Cq8hw/AfI7idTGTvLK2DEfIJ3OzGYsMX4jawyqPC1nR6+g5GMoVWWuxPaXSPK5zaiApPBkp0MZVNzRQyvsuGVk7Bjb2Cc6duy46lzQu8VQXPjmM4pldkw6HIujNxSHUwFHYwwSeXNAahmAWf8Rq87zzNcRzKxiD0ruJBVb3tK7yLSOHebrUIFNHWGjbjiWGKV3Kvk9B9PoYurMwh8MYt+5cwEA0ydPxrrNm7X3fXH5cqx+5hk5R0cF85e3O7CxI4S73mrP+2vJnFvXxrF6ZBV2zJ1MV6cVdmJx4xcxYgyrwu3Ie7PUUFcd2Qy3U8Hqj7rwzs6BET/ObCuw6O7Z25/fqvFdyY1YZgs7WihnHivPRb5MPhk7ANCbR2Elv/DkZJdEXlux5HTsmNmMJTukUnTdiK+rh8zVtqWuykS+jSBzQ5rP4JYemXfo08OC9bw2aBuxbLjqXNC78lxGeLLZjJ307603/J1SUgHK+d3IlbXqXKgyuPJcVVOFaVnFfnbs0GgytTbRsbN1yGYs0f1eX8HnQDsx9Sw2e+pUfLx9OwDggH32wVsffYS9nZ0AgGg0io1btkg7QLJeLK7ihU/6AACvbRtAOJbfHZiOtFXn+WqRtPI835Npl0NBVZkDKsydyIgLcSu2oEytK8M5BybydX72z10jXlyYPbGQNYqlrTo3uBFL0HuxkE2+hYUqryjs5DOKlUd4soyMHUljKGbWPItNSDIu5oFExg6Qyu7RIyi57b6U+UzcHRf8Mgs7Wqi4wY4dCY8Bl0NBbbkTKvQVF0SHQ6UNV50L6Vvzskll7OQRnmyym5ZjWPmRtfJ8Y3LVubTCjsHX6EhMhQrA7VBMZf9lkmmL6o4ebsSi4hipY4f5OvZk6szi8AMOwCNr1gBIbMjab/58nP+Tn+CXf/4zbrnrLkyfLG/zBlnvvV1+7QXIH4nj3Z3+vL6eFR07+RR20tfLmh3FAvKb5Rcn8xUW3aU975DxmFDlxkd7Anjgg66MH7PDZMfOeK1jJ8/CTl/i+0803bFjbOQhEy082eQYkujY6csjYyefwkqVttp5dGTsAMYKO6mWd3kZOwAQjBjJ2JFXUCh1+VzcpXcxSjsOnZ1DMtedA0BDuf6/BfGzsnXHjshDy1Loiquq9loqMuzMqEkLT1ZV/c8DqfMU+/4erOQry/8mRygax9auEBwKMLPB3EKEoaoNduyI5wKPxA5OrYssmKGww44dKrBxlYm80u5AbND1S4c/cU5vZkstjV6mzqhOO/ZYnHTUUdp//+zSS+F0OvG3Rx+Fw+HAD887T9oBkvWe/zjRrSOutV7akl/OTofEO2GpzVjmCzv+SBwxNTF6oWcl+EgyzU0bOQbAuk0oFR4HfnDEBADAr17anbHrarvJO0ZiFGuPpFEss4UdbfQnr4yd/C7oqiWczOaT7yGlYyeW3ziaYGYUSyuqSNuKlczYMdGxw1Gs/BntlEmnZexI6GLUjkNn55CsrjVBK3LqeG4a0LpH7VtYTI2njfzz6A3GEFcTRbl8Xpe9bgfKktvx9GYsAezYyZd4LTz3H1tw2t2b8fM1O/H4+m4tw0yPzR0hxNRE17GsYn8qB0/nc0FMfuba0FGscCyOXX0RKDA/ik5klqIo2rVU+jgWO3bsydQzWbnXi9OOO0777/H19bj/17/G83/9K57605+wYNYsaQdI1vtXsrDz1f0T4zwvbenL6+t1SApPBoApydnQbXmsPBcn+/l06wD5rTxPdexYdzJ/zNwatNR40BWI4ZPO4YWwHd3mOnYaKl1wKInfq9kxvbiqaluxJlSZLOxI2YolwpNNjmIVPTw5/1yDsKSuGXGn21jHTvLfLqnAmerYMbDqOiK3a6iUGc2zSOeX2DlldPV6KkBbTnHPSJFTC0+281YsHd2V4gZJbR7dOqnvZ3xMNz1fgow7dXE9ptZ6EIqqeGenH399uwPfeWw7jly1Hr99ZY+uv4VUvo6cbh0g9Zyk9+aL6PaUWeivTesiAxI3teIq0FzlzntpAZEZmcaxZE5X0Ohh6hnmmz/+MdZ//PGwt1f7fHkfEBXW7r4I1rcFUeF24NtLx8PjVPDRnqCWk2NGp8Qni+ZqN1yORLeIkYu3dOKiI998m1qT2zeA9FXn1r2oK4qCucnNEmKFqKCqqulWYJdD0Vo120x27SSKQipqvU7T697F9plcuQ3ZhLTwZLNbscxnigj55HtUGryAzaSYo1ghrWOneFuxApKPoZTlU+iUtRULACrLROeQ0VEsWR07+ouc2rpzG3fs6MlDk5GvIzQY3EwGpHUW5xHcXMqWz6zG0+fOxesXzsefTp6Gy5Y1YUFTOToDMfzmlb04ctV6/OSZVjy+vhub2oOIZsj+kx2cDBgfl07d7JH391g3JNCbG7Go2MTK8/SOnbbkdR5HsezF1DNZW2cn2pJhyTS2/evjXgDA0qk+VHudOGhyJQDg5a3munZUVdXWncso7LgcCiZWJ14Md5jcjCU2tuTbsVMz5C6MEVaGJ6eblbzztbFjcGGnwx9FIKqixuvUNnwZoW3GGjCXs5PvGBZg7q7sUOE8R7FkhiebuUMo7vLntxUr2bGS551DM6NYAcmdEuL3GDSwblsrbElYdV3qjI5ApRMZOzI7dgYMj2LJ7djRVdgpoXXn2YrwMjZipb6f8eciMdLLu9X5qS13Ydm0Klxw6Hj848yZ+MtXpuMzM6oQjKq4971OfOex7Tjufzdi/19/hFP+tglv7kht7tzQJr+wY7TYLEaTZXbsDN2iyo1YVGxiFGtL1/COHRZ27MXUmcUpRx+NO1evRjiSX5gqFZ8Yw/rMjCoAwLJpia4rszk7A5E4QlEV5S5F2tiRFqBssrAjaxRLBDx2mRgF0jahuK1tv5/dkDhB2tQ+eHQttercXGFFBCjv6TPXLbNTW3Vu/sTG53HA7VDgj8RNd2+F8yxqGA1mHCoWVxGJqVBgLuMmFVZb/I6dGq8TTiWx+l3viJ7MNdNAqiigt2NHVVWpG5FKnc9gaHE6qevOPeY6dmRn7OgbxUp27Nh6FCt3EV50M9RK6NhJ5a/pfxwyPFk+RVFwyBQf/nDSNDx21mx8+9DxWD6zCpOq3QjHVLy/O4CzH/gE/9yUuKGodeyMk1nYMRqeLP/1wOVQUJ3cotobinEjFhVdpo4dkbEjIzaDRg9Tv819587Fq+++iy9fcgm+uHw53K7BX0ZRFHz9xBNlHB9ZKBSN47WtiQLOEdNFYacKNzy/Gy9v6UdcVeFQjF38yVx1LuS78ly8wFflWWhq0SrexvN+xN1pqzt2ZjdmHsXa0ZMorBjN1xHyXXm+S2zEMpmvAySeV+oqnNjbH0VnIIqJbuP/lnyLGlp4ssmtWOnfXzH4twUYv4AdSlVVrWsp3/Bkh6KgvsKFtoEouvwxNFXlfmwHJG+kEifjQZ3hyZGYiriaWG3rkrTatpTllbEjcRTLZ7DgGZK8nS3VvZb755DaimXfwmKN1wkFiY6FaFzN+LcmcxSr3sTGRPGxdbyoscTsRi8uXZYq2PSFYrj5hd34+3uduPjhrfj+Z5qxpz8Kr0uR2smSWnBg7GZDvq+HQ9WWu9AbCqM7EEstrmDHDhWJyNjZliljhx07tmLqt/m1H/xA+/+/v/vuYe9nYWdseH37AAJRFfuM96IpecE9u7EMTT4X9vRH8Z+2IOaPLzf0Na0I48p3M5asO6Szkus4Nw0Zc9JjoECFnel1HjiVxJN3MBLXwmXzbQVObcYyV9hp1Tp28tsIUV/uShR2/DFMrDb++fmexOUbnpzv3UGvS4FTSXQcRGKq4W0y6UUdM4WloURhp8Mf1Z5DskldUEvaipUcp9LbsSN7zXWpyydzSmbGjvGOHbmjWEbypsTrUaWNO3acDgU15U50B2LoDkTRWDn8uUHmKJaZjYmiCMdRrMKoKnPivz83EfXlLvz+tb34xXO7AAAzG7xwSiyyi3Fp3aNYFnVw1nqd2AagOxhlxw4VXWNFcuV5MPGcXFvu0mIz2LFjL6Z+m0+sWiX7OKgI/rU50Q57RHIMC0gU5Q6fVoXVH3bhpS39pgs7MjdNaKNYJjdjaR07Zfm9cM9MFnY+6QwbvqgeiCSOQcZFTDYelwNT68rwcWcImztDWNCU+P2lRrGKU9hJZezkd2KTCuU0NxIm8mXMBiX60i5kzXS05VvYUBQFvjIneoIx9Idjhi+KZI1hCUYDlAPJDSSygou1rVg6M3aCkjuGSp22jSqPjh0po1jaSJjRAp/sjh09687t37EDJIrw3YEYugKxjIUdsQpa6iiWifBkFnYKR1EUXLqsCXUVTly3JlHYmSsxXwcAqgxujswn8y6b9C2q4sba5DzPf4jMUhQFU+s8WLc3iK3dYVR6EoV3hyKnuE6jh6kzi+Zx43L+j0Y3VVXT8nUGtz58SsvZMR6gLHPVudCirTzPcxQrzzuklR4nJte4EYmrg+ZU9UiNYll/l3a2CFBOG8fK946R6MbYa3IrljaKlWfHjrZG12RhJyLCk0127LgcCio9idn5ARObqWRke6Qupo1/f1nByUK9wZXnskdgjG7FCkruGCp1WqHTxN+C3I4dYwUm2eHJhjp2tK1Y9u3YAXKvPJfasVOufxQOSKy790ficDsU2xfYRqOvHdCIm49rwfT6Mnxhfo3Ur13uVuByJF5r9WS/WbEVC0iMYgGJ9dK9oTgq3A7t9ZKoGKbWpnJ2OrVRWJfUjjkqPtOvqKqq4p+vvooNW7agq7cX555yCpoaGhAIBqEoCrxlZTKPkyTb3BFCa28E9eVOLJowuCtn6VQfFABvtfrhD8cNhSBbcRdMjA+19kQQi6uGn4S0E2kJre+zG7zY0RPBxo4QZhm40ySKALICpbOZ3eDFU+jFpo5U8WlHnqNY45MzuHtNduxo4cl5ZOwAqRN4MwHWgJyOleoyJwbCcfQGY4aLhTIKG4nHccTUZiyrOnb03ikXha1ySRupUh07Ogs7EbmhuaUuFeadR8aOhOfESm0Uy1jHjldS51Z1mQMuR+L7h6LxrH/fqdFgez8Gc608F12XtSa2NA7/XsYK/uLj6iucUkZSybjj59fi+Pm10r+uoiioKnOiKxBDfyiO+orsf2chqzp2ko/rD3b7ASS6pflYo2ISOTtbu8KY1cCORbsydWbR1duLL198MX50yy14/o038I+nn0ZXTw8A4Ge33Yb/e/RRqQdJ8j29MTGG9enpVcMKJXXlLiyaUI5ITMXa7ca2Y1kRnlzhcWBcpQuRuIrdfcYLC7LCkwFoxZyh4cS5FCpjBxh+jOFYHLv7I1BgPuNGdOzs6YtAVfWvlgYS3UpdgRjcTiXvtYp1Bk/gh5JRWNFydkwUVmS0fWvdCSa6JGTfnTQ+iiU3z6Dc4LpzbsSSSxt7MPhYVFVV7las5N+k3mJnUHLnmJIMEgdyFzlT687tffc+18rzbks6dvQ9D3EMy96qtADl3M8HVr0m1CQLOx/uDgBgvg4V31SxAKY7hDaxEYvBybZj6pnshjvuQGVFBZ644w7cffPNgy70Dl28GE+//LK0AyT5/OE4/vp2OwDgCyPcMVk2LZG788o2g4UdiwIJW/JYeS4uOvIdxQJSY06bDBZ2xN3pygJke8wZMoq1qzeCuJrolvGYHMHxeRyocDsQiKqGg1LFGFZzldtwJs1QWseO6Yyd/EaxgLSTRhObsWScRPoMZgikC0v496czsg1IVVXpo1hax47BUSyvpI6hUif+Fox27ISiye1kTjnbybTwZIObcGTepU8VOUf+WYRjcYSiKpyK/A6B0UYrtozwXK1txZIwnpKrO2ioTguyAGn0MPIanbrZIffvURQst3SJbun8upWJ8jVVW3keZnHbxkydXb/54Yf4xkknob6mZlhrYVNDA3bs3i3l4Mgaf3+vA52BGPadUI5lyTydofabmBjP+k+bsQKGVU8WU2rMb8YSF8CyRrEAYGOHsYwdcSe5EKNYU2rL4HYoaO1NjOtowcl53DFSFAXjfebGsXb1yRnDAlInS3qzFIYSJ3FGt0ml0y5m8+iYyWcUymhQ7ODvX7zw5EhcRUwFXI78fv7pRIEsoHcUS0LGEaVUmtwSJ3PVOZDexWZ0K5a8x4GevwXRpVLpcdh+LKOufORiS1xV0ZO86K6RMIrl8zjgdirwR+K68rbE6wcLO/ZUbeA1MmTRa8LQUHCuOqdiS1953p7s2BnHjh3bMfVM5nI6EYlmPnnZvns3GurqDH29WCyGl956C1f/6ldYctJJeOqll4a9/3/uvBPHfPOb+OK3v40//+Mfur6m0c8pBYFIHH96I9Gtc+HS8SOeXM7WxnmMFTCsKuxoHTsmCjsyt5DMqC+DQ0mEj4V1XkwCaR07BWi/dzsVTK9PVOY3d4S04GSzG7GE8SY3Y6U2YuVf2DGapTCUFp4sIbzYTMeMjGyPVHeCmYwdueHJRgo7IcmbiIDUGI/ujh3Jo2ClrtLtgENJPK7F35YeMoOTgcEZO3pGRWUUWIfSM4r14ieJhQRiW6GdiQvbrgw/j75QHDE18Vxqtos0naIoqM8R1pxOO0/hNhhbMtKxE5QcpC4MzY7iKBYVm1h53hOM4ePOxE17duzYj6lX1IP33Rd33HcfOrq7B729q7cXf3n4YRy0cKGhr9fV24uVf/gD3vzwQ8Tiw0/Qb/zTn/Doc8/h26efjjOPPx6r7r0Xdz30UNavaeZzSsG973ei3R/FgqbyQWvOh2qucqPS40CHP6rl5uhhWcdOHivPxeiQjFEsr9uBKbUexFTgYwObsQqZsQMM3oy1Pc/gZCG18txYUaW1V4xi5X9iU5/lLrAeMjpWfGXGxj7SydjKlFfHTvLiW1bbuZFsCy1TRWJRRZyMBwxn7Ni7W6JQFEUx3C0DQGq+DpAoZntdCuIqEIjkfixYEaJdr2Nj35P/SWQRHjO3Vtr3Ha2yjUd1pW1kkf399BT9O7RRLHvnHJUqca6n5+aLOCewaiuWkO+NNaJ8KYqCacmunbdaE6HezNixH1O/0cvPOgtfuewynPDtb+PQxYuhKApW3XcfPvjPfwBFwcVnnmno6zXW1eGJVauwc+9eHPutbw16X09fHx585hlcd/nlOOqwwwAA/mAQf3v4YZx5/PFwOoe/MJv5nFIQjMTxx7VtALJ36wCJJ4A5jV68s9OPDR1BLK3MPLKVLhyLoycYg0MZ3oaarynJNX35jGJVSdpCMqvBiy1dYWxqD2HeOH13XrXCTgEydoDEMQI92NQR0gor+d4xakqOYpnu2JEwY17tNZ9vA8hZ9y0uZPPZSiUjY8fIhbQQlpxxo3XsBKJQVTXrc4rsMTDAeMeOFV1Dpa6qzIneUBz9oTjqdDai+CUXdoDE30UwGkV/OJZz5LUYo1jdgShe3dYPpwIcNbta2vcdreqyFLrESJrM8wQjK8+7AszYsbNqA+HJ4pzA6o6dSdUs7FDxTaktw7/3BrXpB3bs2I+ps5q66mo88Otf46jDD8dHmzZBVVX8e9MmLN1/f9z7q1+htlreScsLb74JRVHwqSVLtLd9bulStHV14b3166V9Til44INOtA1Esc94L5bPHLlbR5hjcAOUuDNXX+7KOyR3qClpo1hGtjKpqqp1Vsjo2AGAWaIbpkPfzyWuqlJX++ohApQ3tAexoydRWJmcZ2ElfTOWETuTHz9RQsaOyGPoCUYNb+cC0u7OScjYMRoiDUgKT9ZWTJvv2JEVnlzhcaDcpSAUVTGQo7giu0sDMJ6xIz5O5jGUOp+Bu+OC7IydxHEYz9Uo5CjWs5t6EY0Dh0zxlURBIVt3ZapjR15hR9uYaGQUqwR+D6XIZyD7y6rctfSi5XifK6/xayJZRMeOwI4d+zH9G62pqsI1F14IAIjGYnBZ1AWzu60NTY2N8JaVaW+bPGECXE4ndrW3S/scuwtH41ils1tHmD1ku1IuVqw6F+rKnfB5HOgPx7F3IKqNBeUSiqqIxFW4nYq0u/RzDOYPpV/EyC54jUSsPN/UEdIuqGWNYu01MJoHpDp2miXcsSpzOeB1KQhGE8UyI5lFqqpqW6HyGUUyM3oiiBGQvEax8srYseaCtrU3gk5/NOsKZ9krpgEzGTvy//2lzkzmlOyMHSAtZ6dIK45zdez8P20Mq0ba9xzN6tI2GA7t5uuSuOpcaDA0isXwZDsTnb16br6Eks9F+dzsyaTCnQj0jsRUBifTqCE2YwksbttP3mc17V1d2NLailDY+IiMrq/f3Y0a3/AxoGqfD+1dXdI+x+4e/Kgbe/qjmDvOi+Wz9HVUiQDlDTo3Y1l5F0xRFOw3sQIA8NaOAd2f15e8+K6S2CkzK7kZS+/KczGGJfMiJpeWGg/KXAp290XQE4yh3KXk/XsRW7GMdOzEVRW7JW7FAtK7dowVNkS4q9up5FVg8+XRsROSsu48eSGdx1YumXkCegOURVGpXOKqcVGgCUZVxA2E5jI8WR4zW+Ks6N5KjUga2YRTmHXn6WNYn9P5+jvWlbsVlCW7+fxDCq/dyeKLNaNYuQs7ItC5nuHJtmRsFCv/hQaZKIqijWOxsEOjxZS0SAYFLG7bkenf6P89+ijuXL0anT2Ju1AKgH3nzsUV55yDfWbNknV8UICMIxcqMOLFmZnPsbu3WxPFkNMW1+v+GYjOlA3toZz5GYD1gYQHt1TipS39eG37AI6dV6vrc2QGJwvT6zxwKomxsGAknvOEwF/g4GQAcDoUzKxPzNICieC+fNfrNpnYitU2EEUkrqK+3CntIq7G68Se/ih6gzFMNHCNJGsMSQtPNtOxIyG8VzyO/GYyfiSPYgHZL2jTBSwoqjiU1MVjKKrmLBpZcQylzsjYgzBgySiWvr/LWDzRxakgUeSVJdsolhjDOnxqaYxhAWJTlQu7+iLoCsQGdVda0bGTCk/O/vtXVRUdAY5i2ZmR8VAruveEunIn2gai3IhFo0b6KFZtuRMuR2leE9uZqWeyux97DDf/+c+Y0tyMi888E1eddx6+esIJaN27F9+46iqs//hjaQfYUFeHnv7+QW9TVRW9fX1oHGGtupnPsTsxPmMkmb++woXGChf8kTh29ua+mBeFnUaLTpYOaUl0Ya3drr9jR7Tl+yQWdjwuB6bVlUEFsLkz9ziW1rFTwMIOkBrHAoDJEk4sxlW6oSDxe47G9eXbyBzDEmq8icdXt8GOnZCkUSCtM8BUx07+4b3iAklPZ8JQssOTAX1rngHrumXElq2AjnEsrVNDYtdQqasyMRqY6tiR93vQRiRz/F2mF1fzLXanE90fHf7h+V9iG9bRJTKGJdSNsIJcZOwMDZjNR32W9erpBiJxhKIqvC6l4K/JVBjVBorNMnL3RlKbPFfhRiwaLRoqXNrNwXHM17ElU69qDz7zDI474gj8eeVKfOOkk3DyihW47OtfxyO//z1mT52KX911l7QDnDhuHPa0tyMQTI29bNu1C7F4HM3jx0v7HLsT4zN6s2kEIzk7VgcSLmgqR4XbgU86Q7q7RmRvxBJmGfi5iO1JhezYAYDZDalZWhmtwG5nYpwrrgLtOnN2diY3ck2sljOGBaRGsYxuxpJ1AqeFJ+fVsZNPYUf/yMlQWmHJko6d7I8JcTEve/uI6JgL6ghQtvLubKlK/T2MjlGsXB072t+A5NGLCo8DFW4HwjF10N9mVyCK10psDEsYaeW5KMpb0bGT63moK9lZyG4d+9JGsYJ6iv3WvSZ8bnY1JlW7ceiU3FtliQpBURRMTd7o5XOgPZl6JtvT0YHPL1s27O3esjJ87cQT8e9Nm/I+MOHTBx0ERVHw/BtvaG979pVX0NTQgH3nzNHe1jcwYPhzSokohIiV1XppOTt6CjsD1hZ23E4FSyYlcnbe0Nm1I3IfsoW6mjG7IRVOnIvIF6h0WzOiNpLZ6R07ku4YiZydvToLa+uSo2CTJBZ2qk1m7Ijg5HyDc/V2BmQSlBBerBV2dAYGpwtJ+hmkM5qxI3vVuCgU6enYCVpUXCplZkaxrNgSqDfrx8rinhhDTg/wFWNYS0toDEsQGTpdgcwdOzK3YtXrDE9OjYyX1u+ilGhjmYa2Ysl/Tfj6kkas+dY8TJCUL0gkgwhQtmLRDRWfqTObRXPmYOfevRnfp6oqmseNM/T1tu7ciXfWrcNHyYLQJzt24J1167B1505UVVbi5BUrcP2qVXhkzRrc+8QTWHXfffjaiSfC4Ugc/j2PPYZPn3kmnnv9dQDQ9TmlZCAcQ384jjKXonU76JWes5NLIVaIHpwcx3p9e3+Oj0ywqmNHFE30BCgXbRSrIVXYkTXjLTq+tnXnDkuPxFQ8+FEirPyo2fJGEET7vuFRrJjYfpHvKJb5jB0Z42Ail8RMxk7QgvDkep1rhq1aNS6+nigcZWPVattSlvp70F9o9FsQKC9GFHMVmKy8kMtU5BTbsI6eU1pjWED6yvPBzw3dyQ6eWpkdO1p4cvbfvyj8MDjZvgyFJ1swnkw0momcnfGVLDjakalXtnO+/GX85NZbccLy5Sj3ege9b/Uzz+D044839PX+9MADeGTNGu2/b//733H73/+OLy5fjmsvuQTf/cY34HI6cds998DtduP8007DGWnfo762Fo21tYM2YeX6nFKypz9xItPkcxvOFJgzTqz2NjCKZWEV+NAplQD05+yIrgqZGTtAakRNTyeT1rFT4MLOpBo3yl0KAlEVkyVl3MwfX47nPu7DNc+0oq7cicOnVY34sc9/3Iu2gShm1JdpnVYyVJscxQpLWvUtioT9obiuUPF0csKTUxk7Rr9/2NJtQNkLO1atGhdFmoCBUSyexMuT+nswk7EjMzxZjGJlfxxYeSGXytlJ/Cy2dYfw6tbkGNbs0hrDAtJXng9+bKTCk+W9LleVOeB2KPBH4ghF4yP+fgtxA4qKy1fmgILEc0EsrsKZJSA2JOm8gGisOHlRPXb3RXDyotLMnLU7U69sDz77LLp6e3HihReisiJ1wRaLxbB9927s7ejAXx56SHu7oij4x623jvj1rr3kElx7ySUjvt/hcODys87C5WedlfH9K5Ytw4oho2G5PqeUpMawjFdnZyZzWjZ3hhCNq1kT1AtxwrRPUzkqPQ5s6QpjT18ETTlaXLWOHcmjWFNqy+B2KGjtjWAgPHjjx1DFythxKAouWzYBmzuDWiZQvs47ZBw2dwbx1IZefGv1Fvz3UZNwyqL6jB973/uJbp1TFtVJDSk1u+5c1gmcx+WA26kgElMRjqmGvp6MjhG3U4HHqSAcS2yCMhIErF3U5tm1lK7BYHhyuezwZJGxo2cUS+sa4km8LFUGNtAIlq47z9mxY904XnqQeCgax2WPbkNMBb4wv0ZqnsxYkSk8WVVVS9adK4qC2uQWok5/dMTAfnEsdRZt76TicygKKj0O9IfjGAjHtZtBmTB3jUrN5BoPrj+mpdiHQRYx9Uy2u70d+8yahSkTJ6Khtlb73/iGBixZsACNdXWD3l5fU3otyKNJKjjZ+Imlz+PEpGo3IjEVW7tGHsdSVVVrgbaysONyKDhwUqJrR884lgi4lT2K5XYqmF6fOHHcnCNnZ8CCsQO9zjqwET/7/GTdK+5z8boduOX4KTj3oEZE48CPnmrF/7y4G/EhW2B29Ybx4pY+uB0KTlwg966A6cKOpFEsAKjyGM8VAdK7BfL7fZgNULYiY6fe4LpzyzJ29IxiRTiKJVuqsGNgFEvLHbNi3XmujB1rsp6Awd1r1/9rFz7aE8TkGjeu+ewk6d9rLMgUntwXiiOmJp7DZDwXp2vQ8VzUyY6dkqB3HIsdO0RkJ6Ze2e742c9kHwdZSATdjjfRsQMkcnZaeyPY0B7CzAZvxo/pDcURiavweRyWjzkc3FKJ5z/pw+vbB/DFfbIXDcTFRpXkUSwgkbOzoT2Eje1B7Ns88qiRuPjO1tUzljgUBVcc0YyWWg+ufXYn/vB6GwDgO5+aoH3MPz7sQlwFVsyplh5SmSrs6NvMJWjhyRI2QvnKnOgMJLKrGiv1f56sjJcKtwNdgRj8kTgaDHxeyIKMnbq0HI1sbe/iBFp2t4yRjh0rN6CUKq1TxkDmU1G3YlkYoC2KBQ//uxufdIbgdiq45fgpWTsG7Ezr2EnL2LEiOFnQE6Dcwa1YJaHK6wT6IllvvsTiKiJxFQqsWXdORFRoPLstAVrGjslkfj05O4WcWz/EQM6OyH2QnbEDpMKJN3fm6NgpUsaO1U5b3IDfnzgVTgX4w+tteGJ9N4DEydIDHyTGsE7dN/OYVj6MBCOm09adS7igM7sZS17HjsjZMbkZTOJJrNupoNbrRFzN3kWVWncuu2NHf8aO+Bgj42uUnS+Pjh25hR2xCUdfx46VW7E+Sb4mXHnEBCyaIC9fbKypz5CxsyXZ+WvFuUJ9htGvobRRrBIcjSslVTq29aV368gcFyciKhbTr2zhSATrNm9GW2fnsDEMAPj84YfndWAkTz4ZO0BqA1S2ws727sTJWmMB1ufNH18On8eBbd1h7OoNjzhLD1i3FQtIrf7uyjGCIi6+izGKZbXPzKzGDz7TjJXP7cJV/28HZtSXYU9/FLv6Imip8WhFOJlELkN3wOwYVP6/B+1i1mBhRdZFZaXWnWC0sGRN23lDhQvdwRj+uakXp4xQzNO6ZSzaiqWvY8e6MZxSlU/GjsznxFR4sr6MHStHsYDEFqwz9jfST2c/dRm2Yj26LrEl7NPTRw7eN/39KoZ/v6FENw87duytSrsBNPLrAsP0ichuTL2yvf3RR7jippvQ1dsLNUNRR1EUFnZGkXwydgB9G6Ce2tALADh0im/Ej5HF5VBw0ORKPPdxYhzrxAXZCjvWjWLp7RwRq319NuvYEb52QAPW7Q3gwY+68e2HtmJKcrX6KfvWScv2SWe2Y0d0q8houdYb1DqUrKBG0xk7Fp3Inrq4Hiuf24UfP90KhwJ8OUOgdsCiNdNaxk5Ez7pzawKcS5kv7bEYV1Vdf/OiY6dC4nOi3rXrIQvXnU+vL4NTSYRT/nzFpJLvAqgpd0IB0BOIIRZXEYzG8ezGRGHnhBxj1GboWXme6i4uzfG4UiHOE/qydJGGLcicIyIqJlNX+jf88Y/wlpXh6vPPx+SmJrhcvPMxmuXbsTOjLnGyurUrjGAkPuyOezgaxzPJk7Xj5hUmKPvglvTCzsgniOLurRVFFb1rt7XwZJtk7AylKAp+etQkbOoI4YPdAbT2RuBUgC9JDk0WqsoSFwt9odyrTNOlNkLlfxJnJjAWSOV7lOU5CiRCZ/06ulQGfX8LRrEA4OtLGhGIxPGrl/bgqqdaEY0nij2DvrdFRSWtY0fPuvOIdRf1pcrpUFDhdsAfSWyg0VNEF0U4a7ZixaGq6ohFFSu34Eys9uDhr8/GhCq3JTcTxhqXQ0GN14nuYAw9wRhe+KQPgaiKAyZVoKV25BsyZqWHV2eiqqrWYSs7+41GlyodN4C4EYuI7MbUK9uutjb890UXYfmhh8o+HpIsFlfRPpA4yRlnsmPH43Jgen0ZNnWEsLkzhAVN5YPe/+KWfvSG4pg3zjtiuLJshyQ7g17fln0zlshbsCJjR3fHjk0zdtKVuRz47QlT8eW/bkK7P4ojZ1abDuvOxelQUO11oicYQ28opjsrIXV3TsIols6g1nSqqkocxTKXsWNFeLJw/qHj4XIouOmF3fjJM62IxtVBoyhaYK5VGTs5ilzpQZluBmVK5StLFHb6QzFdBQ1/8nErs7DjcTngdiqIxFSEY+qId+Fl5VyNRIwuU0JteaKw0+mP4uF/dwMATtin1pLvJTKORgpP7ksueagswJIHKi49GTtBiTd7iIhGA1OvbAcuXIi2zk7Zx0IWaPdHEVMToYL5rBbNlrPzeDI0t1DdOgAwb5wX1WUOtPZGsLM3POLHaevOLeiW0ZstoW3FsmHGTroJVW7cftJULJ9ZhUsPb7L0e4mimpGV51LDk3WuVk4XialQAbgciTvZ+TA7ihWOWtOxI5x78DhcdWQzAODaf+4c9HwRtCjfR2/HjjaG5XaU/IiMbOL5VU8HW1xVtbE82UU+PaHmVoYn03CiM2Z9WxCvbu2H26ngmLm1lnwvLdNnhI6dQi55oOKq1nF+FmbmGhHZjKlnswtOOw33PP449nR0yD4ekkzL1zG5EUsQOTvr9gYGvd0fjmPNpkS+zrHzavP6HkY4HYq2Yvz9XYGMHxOOxRGKqnAq8lcsA6lRrFzFBS082cYdO8KiCRW47UvTtE1qVqnROQaXLhQTd+dkdOwYD4wNSjyJrDCbsVOATIGvL2nEijnVAID3dvlT3zutsCKTGKsK5sjYEe9nnoJ82t1xHR1k6eNwesco9Url7OTezsaLucIQxZa/vt0OFcCRM6q052/ZUuvOM//+RWGn3oJV6zS6VHn1hydzSyIR2YWp2xazp03D/Jkzcdrll6OuZniXhqIo+Mett+Z9cJS/vXnm6wgHTEpsN7r/gy6ctaRR20T13Me9CERV7Ndcjsk18mfms1k0oRwvbenHB7v9OHru8Mdhf1pwshV36KvKHFCQ6NrIlvWSGsXiyaQs4sKg20BhR9ydkxKerG3g0V9YkTnPLzp2DGfsFGgLyPzx5XhqQy82tYe0t1m17lwUinKtO2eegnW0DjYdhc6ABavOU8eR++8yxIu5ghJFlHeTN2CsGsNK/14jZeyIbVnM17E/0UWY7TlJu9ki4WYPEdFoYOrZ7KY//Qn/78UX4XG7UePzoaG2dtD/6jMUe6g49vQnTmTyLewc2lKJz82qxkA4jp8806ptQ3t8fTI0eX5tXl/fDNGx88HuzB07opvCZ8GqcwBwKErOCwlVVVPhyTYfxSokMx07MjdgVBm4kBVkbuMRY32GM3YsCk8ealZDosNvU0dqFEv790u+oBZFKr2jWLLXrZOxMHG/BavOBZ+BizkW+AojPQOt1uvEp2fIX3MuVHudcDkSnYzhDM8HHMUqHdpyi6yjWNbmbRERFZqpV7c1r72GM44/Ht87+2zZx0OSiY1Y400GJwuKouCaz03EGzsG8MIn/Xj4391YPrMaL3zSB4cCHD2n8MW8RRMSIc4f7glkXLNr5apzobrMib5QHL3BWMb28mBURVxNdIkwsFUevWNw6WR2q+jJ8hgqKPH7p8KT9X//uKoikizsWP1YnJUMUd/UkdaxY1HHjJaxk6N7KWjhmutSZyRM3G9lx45Hf8cOL+YKoy5t7OnYeTV5Zf3l4lAU1JW70DYQRWcghglVg7+XNorFwo7t6QtPZpGXiOzF1LNZeVkZDl60SPaxkAVkZewAwHifWwtGvW7NTtz9bgciMRUHt1RatgEpm3GVbkyocmMgHMcnnaFh77cyOFnIdVfIL4KTSyBfp5BqtVGszC33mYhuFSmjWDqyPIZKjQLl//3NZOyE08KLrQ4Pbqn1wONUsKsvonVPhCwq7GgZO9EcGTscxbKMkY4dK0exKg1czMkObqbM0osoJ+xTZ/n3Ex1CnRnGsbjqvHRo49oj5C0B6TdbWOQlInswdWZzzKc/jSdffFH2sZAF9kjK2BFO2KcWn57uQ28ojl+9tAcAcFwBQ5OHEl07mcax+i0exQJSFzQjFXYGIsngZI5/SFVtJjxZYsdM6m6g/sJKSGJ4spmMnUKNYQGJrV/T6xPjWJs7Q4jEVETjgFOR3y2kZezk6tiJyCus0WDaSKqBjB0rnhNrvYkL9mydfDI75yi3xsrE72RanQeLm8st/37ZVp5zFKt0jK9MnPPu7Y8irmYu+st8TSYiGg1Mvbp94cgjceFPf4pb7roL+8yalfFjPn/44XkdGMkhK2NHUBQF1x41Ccf970YMhONwOYDPz66W8rXN2HdCOZ7Z2IsPdgdw4oLBdwP7CzSKBQB9I1xIaKvOGZwsVY2JUSyZ4cmpUajidOyk1p0Xp7Clx+yGMvynLYiN7UHMTBZ5rPjeXt0ZO2y7t0qVjtXCwoCFhR09d+llZl1Rbkun+HD+IeNwxIwqyzsFgVTRJlOAMrdilQ6v24H6cic6AzG0D0QzdpWHJL4mExGNBqYKO8d+61sAgE9aWzO+X1EUFnZGiVTHjrw7VM3VHvzwM8340dOtOHJmNWrLi3f3a9EEsfLcP+x92ihWAQo7I3bscBTLErVmCjtSw5PNbMWSV1iodBvP2AlJLGzpMbPBC6AHmztCWtHFivEbvR07hS5slRJtA42Ox6OVo1i15blHNBmiXVhOh4LLPzWhYN+vPnk+Isau0omtWOzYKQ3N1R50BgLY1RfJWNgJsmOHiGzG1KvbH3/+c9nHQRboD8cwEI6jzKVkDPbNxyn71mNWYxlm1nulfl2jFjQlWrvXtQURjsUHBTNqW7EsLKpUexNfe6SRIBZ2rGEqPDmWvLCXEN5ZmbZ9R1VVXXeiZRYWTGXsxArcsdOY6NLZ2B5EIGJdl4TejJ1UQYF3Z2Xz6ci2ESwt7Oh4XmB4sr3VZR3FYsZOKZlY7cZHewLY2RvB4ubh79fOCfhcQEQ2YerVbcmCBbKPgyygBSf73Ja0QO8/sVL61zSq2uvEtDoPtnSFsaEthIUTUjP8YhTLZ2HHTq6MHZGBUsm7w1LVJLM0jGXsyOvYcTsVeF0KglEVgYiKCk/urykz48VUxo7Ef78eM5ObsTZ3hCwLTgYMZOzw7qxlxHOsni1x2rpzC4rdons0e2AqR/LsrH6E8OS4qmodO3VF7DKmwmlOLg3Z1RvO+P5QhM8FRGQveT2b/XvTJjz07LO4c/VqdPb0AABUVUUspv9ii6yzV3K+zmglxrE+2D14HEvcPa6yMDxZdI6MFKIrMlCYsSOXlqVhorAjaxRJyxXRmXOjFRYkFPnSM3bUEYIhh0p1LBWmsDOl1gO3U8HOvgjakxdZXgu6ZTxOBQoSo3ax+Mg/C+YpWEeMYun5WxCbAq0JTzYwisWLOVsS3TidQ4p73YEY4mritUN2gDuNThOrE+e+O5M3OYfSgtT5eCAimzB12yIQCuG711+PV999F76KCgwEAli6336or6nBT3/7W+wzaxa+cswxso+VDLIiX2c02re5HI+u68b7uwP4r7S39xUwPHmk1n8xKmPF3elSVpNjzXwmYhTJI+mCrtLjQNtAYhxLT/FUZmHB43TA7VQQiakIx1RdXThaYatAF7Quh4IZ9YkA5Y/2JLbWWXExrSgKyt0O+CNxBKPxEYuoAWarWKZqlIxi1eno2Cl05xoVlsjPGdqxI/67jsHJJWNClQcAsKs3c2FH2xTJ1wQisglTz2b/c+edaN2zB/f96lf411/+MuiO8cI5c/DImjXSDpDME4WdTKFxdiJWnn84pGOnV8vYsbCw482+DUYbxWJhRyqvS4HbqSAUVbURp1zEVixZd+dEwVBvzo3sERAx3qf3+4ck//v1mNWQyNn5cLd1hZ3E103m7ESydeyw7d4q4m9htIQnd2UdxWLHjp2Jws2wwg6Dk0uO6NjZ1TfCKBafC4jIZkw9m7301lv49umnY/a0acOyW1omTMCWEbZlUWFpGTtV9i7szB9XDpcD2NQR0tr839/lx+vb+qEAmFrnsex7cytWcSiKkgpK1dm1E5K4FQtIhXLr6VIA5Ie2VhoMUC50eDIAzErm7HwoOnYsujOq5exkWXmubebiSbx04m9BhIlnY2XumM/jgFNJfA/xeE+nqio7dmwuNYo1uLAjgpNZ2CkdqYydkUaxCn+zg4jISqbOrELhMDzuzMWCvZ2dqKosfqguAXtKJGPH63ZgdqMXcRX4994AQtE4rnxyB2Iq8LUlDZhWV2bZ99ZyVkYcxUq83Yo8iVKnjcFluTufTva6a5+BLgVAfqeAVtiJGMz4KeAFrejY2daduGNqVb6N+Jlm694S3Ty8oJfP43LA41QQjefeTua3sGNHUVIbIDONY6XnbDksWChAxVfjdcKpJEax04t72igWCzslo7HSBbdDQWcglvG1QfY5ARFRsZl6Njtgn33wl4ceQjAUGvT2UDiMux99FIvnzZNycJSfvSWSsQMA+yYDlN/f5cevX96DzZ0hTKvz4DvLJlj6fWtydI34tY4dzvXLVlNuLGdHdOxIC0/2ZB/DG0r6KJbH2CiYdhIrYd27XrMavYP+26oTaK+Bjh223VtDK3Ln+HuwchQLSG3GypR7FmSAtu05FEXLWhILJIBUYaeBG7FKhkNRMEF07WQIUE6N5/L5gIjswdSZ1eVnnYUNW7bgy5dcglvuuguKomD1M8/gzCuuwLZdu3DJV78q+zjJhFR4sr07doBUzs7qD7vw5zfa4VCAG45psTwoVQsNHaljR6z2ZceOdDVl+jdjqaqKiOTCTmXyd6+3Y0f2KFaF2YydAp7Eis1YQrlF37s8uW0rlKVbJMjwZEvpDVD2W/ycKHJ2snXs8A69ve3TlCgov9U6oL2tQxR2KniTpZQ0V49c2AmyY4eIbMbUrYtJTU24++absXLVKtzz+ONQVRWrn3kG+82bhxuvuAITx4+XepBvfvghzv3RjzK+b+L48Xhi1aphb39+7VpcunLlsLf//pprcNj++0s9vtEoFlfRPpA4kRlXAh07orCzsSPRRXbuQeOw38QKy79vhTuR6RCIqgjH4vAM6YZgxo51tG6pwMirjYVwWlFnaC6YWaJjp193xo7sjh2zGTuFK+y4HAqm15VhQ3sw+b2tCk9OduzoGMXi3Vlr+HR2kInfkVWbArOtPGfXVmk4dIoPL3zSj9e2DeCEfeoApDp26jmKVVImJjt2dvYOD1Bmxw4R2Y3pV7ipkybhDz/9KSLRKHa3tWFCYyPcI+Tu5GvejBm48xe/GPS2SCSC7914I0787Gczfk7vwAC8Hg9u++lPB719ZkuLJcc42rT7o4ipQH25c1ixwY5mNXrhdSkIRlXMbijDJYfJLS6ORFEUVHmd6A7E0BeMo6Fy8M/an8zYYWFHPiOjWFZ0q/hEx07IaMaO3PBk8RjLpVjdCrMbU4Udq8ZvtIwdjmIVjU9nx442imXR76E2y8rzIC/kSsKhU3wAgNe29kNVVShKImcFYGGn1GgdOxkClJmxQ0R2o/sVbtW99+KEz30OTQ0Ng97udrnQ0tws/cDS+SoqsP/8+YPedufq1WiorcU3Tjop4+f09PWhsa5u2OeVilLZiCW4HAo+Pb0KL23px/XHtMBTwBfqmrJEYac3FEND5eA/KXH32qq706Ws2sAoVigmP19GdCj0F6mwomXs6Fz3nh4cW0gzG1Lh5ZaFJydHsbJ17Girbd28qLdCKmMn++NR5I5ZlrHjHXnlOS/kSsP88V7UeJ3Y2RfB9p4wptSWpY1isbBTSpqrEltRd2YdxeJrAhHZg+6zm9vvvRe729qsPBbd2ru6cMd99+H75547YpdQb38/6mtrC3tgo8jeEsrXEf7nC1Pwr/PmYWFyLKtQsoWGplb7cq5fNnEB16unsGNBUSOVKVKcrViGM3aKsO4cAGY3pAKULVt3rnXsjJyxE5A8CkeDaWHiOQqd/miBMnayjWKxuGdrDkXBIS2J7ayvbUvk7GijWAxPLimiY2d3pvDkGF8TiMhedD+bqWr2FaaFtPrppzGhsRFL99tvxI/p7e9HW2cnvnTRRTj4lFNw2ne+gxfffLNwB1lkpbLqPJ3bmVp1W0jV3pFHgpixYx3xc8+0/WYoLWNH4p25SoMdO7LXjRvO2ClCeDIwtGPH4q1YOjp22K1hDTGKNZCj0Gn5ViyvnlEsPgbsThvH2taPaFxFdzAGBanCH5WGrBk7EXbsEJG9GDq7kRU6mo94PI4Hn30WJ33+81k/bkZLC6ZPnoxLv/Y13Pz976OyvByXrVyJdZs3F+hIi0tsxBpfAsHJxSZGgjJ1jrCwY50a78hrjYcKW3BRr13IGtyKJTs8WXfGjgXjaHpMrSvTNmNZNYpVriNjJ5XtUvzXMTvSs+48FlcRiqpQYF3XTKpjh6NYpezQKamOHdGtU1fuhNPBv/9SMiFtK1b6DWpVVdNutvD5gIjswdBV//WrVsFXkXvTkKIo+MO115o+qGze+89/sKutDUceckjWj/vKMcfgK8cco/33gQsX4rjzz8fdjz2Gn116qSXHNppoo1glkrFTTNXexEnB0I6dcCyOSFyFy1H4XJNSUGOgY0e0XJfJHMXy5L6QTSd7DKRS5xYioRjrzoHBm7Gs69jRk7HDk3gr+ZKFxmyjWOndOg6LbhTVas8LmUaxGJ5cKmbUl2G8z4W9/VG8vj0xjsXg5NLj8zhR43WiJxhDVyCmPQZCURUqAJcj8RpFRGQHhl7levv7EYnmXi1spffWr0dNVRUmNTUZ+ryK8nIsnjsXW1pbLTqy0YVBgYVTpXXsDL6o1IKT3Y5R0e1mNzWGMnYSvwuZo1jaVizDhRXJGTujPDwZAD413YctXSHMavTm/mATtI6dyMgjw9yKZS094cl+i8ewgFxbsdixUyoURcGhU3x45N/deGJ9NwAWdkpVc5UbPcEYdvZGtMfAB7sDAIDpdWXZPpWIaEwx9Cp33eWXY/G8eVYdiy7vrV+P+TNmmPrccCSiq+PIDjr9ydWeDAq0XPUIIwipMSzO9FvBUMeOKKpIHEPSM3qSTnZhwWjGTrHCkwHgik9PwEVLmyzbDqdl7IwwipXeds/gXGv4kn8P/Vn+HlIdO9b9DrRRrExbsSLib5CPgVJwaEslHvl3N178pB8Ab3SVquZqN9a3BbGrL6wt13hla+IxsXSqr5iHRkQk1Zi7bbV91y40jxs37O0DgQDi8cRJW7/fj6dffnnQ+9u7uvDuunVYOHt2QY6z2LoCyQ0QFSwqWE0L8R1yQeNnvo6l0kOr4znC3a0IT07fSpXr+wPyx0CMZuwUKzwZSNw9t6qoA6R+FiMV2dK7lawaASp1VTo62ERhp8LCLYF13tRWrKFLHxieXFpEgHIknvi91zM4uSSlApRTm7Fe3cbCDhHZz5i7fdHR04Pa6urBb+vuxnHnnYfD998fv7zySny4cSN+dMst+NfatVh2wAFQFAV33HcfKisq8NUTTijSkRcWV3sWjtaxM6RzZCCS+G+r1vqWOpdDgc/jQH84jv5QXCv0ZKKFpkrs2HE6FFS4HfBH4vCH41rHQiaxuIpILBEaK2sUynDGTpHCkwthYpUHwOAT93SpbikWdayip4NtQCvsWPd78Lgc2t/lwJC/y9QoFh8HpWBSjQdTaj3Y1p3YiMRRrNI0Ifn6IFae94dieH+XH04FOHhyZTEPjYhIKt1n+OefdhomZOiUKaRYLIaevj7UVFUNervH7ca4+nrt+A5dvBh/XrkSDkXBbffcgxvuuAMzp0zB3268EdU++1fnA5E4AlEVbqfCbpEC0DJ22LFTcHrHsUTHjuwLOtGlkGscKz24WFbeUnrHkB7FCk8uhEk1iTuyO3qGr7QF0jo1WGS1jC9H1xRg/apzQTwvdAUyj8ey2F46lk5JnfNxFKs0Tawe3LHzxo4BxFRg3+aKrDdkiIjGGt2vcuedeqqVx6GL0+nE26tXD3t7VWUlHr3ttkFvWzh7Nn5+2WUFOrLRRRvDKncytLcARgrx7U2GiPLEwTo1XidaeyPoCcbQkuXjrAoO9nmc2INozgBlK4J7tYwdo+HJNizsjPe54XIAbQNRhKLxYTlCDE62XipjR8fKeYsLK7XlTuzqi6A7GEULPNrbxYVdc7VnpE8lmzl0SiXufb8TADt2SlWztvI8UfjXxrCm2P9GLxGVFp7l2pAWnMyTmIIQXRtDO3ZE94C4W0TypefsZGNVcHAqVyRXx478ERCflrGjr7ATtvEolsuhYEKGHAWBo1jWqyt3QgHQGYgiEsucOSW2YlmZtwSkrzwf/He5PfmcPLmGz8ml4pAWduyUuqEZO69qwckcwyIie7HfGT6hM8B8nUISxYWha363dYcAAFNruU7TKqJbqjv5mB9J2KqOHR0rngFrQls9LgfcDgWRuIrwCNug0tl5FAsAJiW7MFp7h49jiTXo7NixjsfpwIQqN+Jq6s74UP4CjUKNtPK8VSvssGOnVDRUurBkUgU8TgVT6/h7L0XjfG44lURH587eMDa0h+B1KdivuTS25BJR6eBZrg2J4OQ6boAoiOq0jJ30LSxbuxIXEVNqeTJpFb0ZO6mOHblFDTEOlW3FM5DesSP3KVd0PuQaBRt0DDbs2AESQakA0NozvGMnwFGsgmhJ/g62d2cu7BRsFCtDwbc/FEN3MAavS0EjOzdKyu9OnIpHz5qNcZXs1CpFLoeCJl/id//QR90AgAMnV8LD1wMishk+q9mQyNip48lrQZS5HChzKYjEVK0zA4C2iYN3Ca1T4008xnONYqVWfcsexUrmiuTM2JG76lyoNBCgHLIoQHq0EOM1mTp2diVb8Bsr+ZxopcnJIvaODMU1IDWKVYiMHQDoTiv47kjr1mH2XGmpK3dhWh07Z0uZyNl58KMuAMzXISJ7YmHHhrSMHY5iFUz1kM1YwUgcu/oicCpAcxULO1YRP/ehIxdDWReerK9jx6rwXtEx5NcRoBy2cXgykDaKlWEz1sedibHImQ28uLOS1rEzwnYy0bFTWYRRrO0cwyIqWaKwI264HTaVhR0ish8WdmxIy9ip4ChWoYjOjb7kHWJxd3hSjQduycUEShF35nN27GjBwbLXnevr2LEiPBlI24yVI7w5FlcRiatQALgd9nw8igv21gzhyaKwM6OehR0ria6pkUaxCtaxI9adB1OjWDtY2CEqWek32GrLnZg33lvEoyEisgYLOzYkMnbYsVM4WtZLssCwtZv5OoUgOnZyZ+xYM4rl84jw5FwdO8lRLMkXtBXJ759rFCucNoZl1zGUSck7sjuydOzMYMeOpVpq9XXsFC5jJ30UK1Hwa2Fhh6jkNFel8pUObfHBYdPXQSIqbSzs2FBXgOvOC02svRYdO6mNWLyIsFJNuc7CjkVjSJVl+sKLg5Z37OjtGLLvU/54nxsuR2LzSShtS1g4Fse2rhAUANO4oc5SLTUjj8MBaevOizCKtYOrzolK1sTq1N8915wTkV3Z9yy/hHErVuENzdjRNmIxsNFStTq3Yol14B7JG6Gqkh0zubdiWbNuW2SV5MrYER1LsjOGRhOnQ9Ha7XemjWNt7w4jpgKTatzSO6ZosIYKF8pdCrqDMfRm+JssWMdOhoKvGA/jKBZR6WlOL+wwOJmIbIpnuTbUpWXssGOnULSMnVDiwkWMIrBjx1r6151bsxHKZ7Bjx6rw5FwZO1Zl/Iw2kzJsxmK+TuEoiqIVTjKNxBWsY0eMYiUzdlRV1R4TLOwQlZ4pNWWoL3diQVM5R+SJyLZ45W8zkZiK3lAcTiV10UvWG1pg0Dp2eAJhqbrkyEWnPwpVVUfMj9EyZqwKT86VsROxprCkN2NHdAyVSe5YGm0Sm7EG0Jq2blvbiFXPsMxCmFzrwcaOEHb0hLFPU/mg9xWqY6fa64RDSRTao3EVXYEoglEVteVO+Mr4ukhUaio8Djxx9hy4HfbNmSMisvdZfgkS3Tq15S6GwxVQqmMnhnAsjtbeMBQwqNNq5W4HKtwOhGNq1uKGVRkzYt15n86MG+s6dnQWdkqkYye9W2RzB4OTCynbynN/ssBpdceOQ1FQLYrtgVgqX6eaz8dEpaqu3MXCLhHZGgs7NqOtOme+TkGJi4jeUAw7eyOIq4mwPo+Nw2pHi/qKxM++wx8d8WO08GTJHTs+nRk7qVEsa8KTc2fs2D88GRAdOxzFKiYx6pRp5XmhOnaAweNYzNchIiIiu7P3WX4J6vInLjDruOq8oLSOnWCMY1gF1pDMkhJFzUzCycKG7K1YWsaOzvBk2YUVEZ6cK2MnXCIdO5OHbGVSVZWFnQITK88zZuwkH6cVnsIVdroCMW3VOTdiERERkV2xsGMz4uK2roIdO4WkZeyEYtqqc27EKoz6ZBGzwz9yccOqjJkKtwMOBQhEVUTj6ogfZ1V4sv6MnWTHju0zdkR4cuJCfu9AFAPhOGq9Tm4JLJCRRrG6A1H0huLwOBWt081K2srzYGoUq4XFdiIiIrIpe5/llyCx6ryeHTsFVZXs3OgLxbA12fY/hW3/BSG2v3VmGcUKW7QVS1EULWcnW3ElaFHHjO6MHYv+/aPNeJ8bLgfQNhBFMBJPdes0lDEws0BS43ARxNVUsfPNVj8AYHFzBdySRyIzqdUydqKpjB0+JxMREZFNsbBjM53JrgWuOi+s6uQoVm8wjm3JUaypdbyIKAQ9hR0rO1ZE90FflnEsq8OTc2bsRK0ZRRttnA4FzVWJv7udfRF83MExrEKr8DjQWOFCJKZib3/qb/LN7QMAgIMmVxbkOGrLRcZOjIUdIiIisj0WdmyG4cnFkR6evFWMYtXyYrIQGvSEJ1vYsaLl7GTJubE6PDlXxo7277f5KBaQ2ozV2hNmvk6RiJGn9ADltTuShZ2WQhV2EgXf9oEodvVFoACYWMWMHSIiIrIn+5/ll5guMYrFjp2CSl933poM6uSq88Ko1xOebNFWLADa+tT+kI5RLMnbgCrd+jJ2SiU8GUgLUO5lYadYJg/J2ekPxbBubwAuB7Bfc0VBjkGMYq1vCyKuAhOquKWQiIiI7ItnOTbTFUhuxWJhp6BcDgUVbgfiKhCJqxjvcxVk8wul8qQ6RwhPjqsqIslgYyuyPUTGjr5RrCJl7JRIeDKQlvHSE2Fhp0jE9inRsfNWqx9xFVjYVF6w50URaP/hbn/ymFhoJyIiIvuy/1l+iUmNYrGwU2hiHAsApnIMq2DEuvORRrHSu1WsCNBNbeUauWNIdOxYlbEzkCtjp0TCk4HUKNaG9iB290Xgdiq8qC8w0a24ozdR2HlTG8PyFewY6pJ/l73JTjquOiciIiI7Y2HHZrStWFx3XnAiQBkApnCtbsHkCk9O5ctYU9RoSuZ27OmPjPgxWseM5MKOx6nA5QAiMRXh2MjFnVIJTwZSHTuvb+sHAEyv88DpsP+/ezQZmrHzhijsTC7MGBaQCk8WWNwjIiIiO2Nhx0biqoruYGIcpNbLjp1Cq/am/py4EatwRFB4VyAKNW29sqAVNSwaQ2ryJQs7fXo6duSvW69w5x7HCkVLJzxZXMAHkv/m6RzDKjjxO9jRE4Y/HMcHu/1wKMABkwoTnAykMnaGHhMRERGRHdn/LL+EdAdiiKtAdZnDkiwRyq5qUMcOLyYLxeNyoKrMgWg8NXaRLmRxcLCejp2gRevOAaDSkztAOVxCo1jjKl1wp3XoMF+n8Jp8brgdCtoGonhtez+icWD+eO+g50ir1Q4ZR2Zhh4iIiOyMhR0b6QpwI1Yx1ZSlZ+zwIqKQsuXciBElqzbiNPkS3zvrKFZEjGLJL6yInB1/1o4da0bBRiOnQ0FzdSpPhYWdwnM6FC3r6KEPuwAAB00uXLcOAJS7HYP+3rilkIiIiOxszFQAnl+7FpeuXDns7b+/5hoctv/+GT/nhTfewB33349tu3bhwAULcPUFF6C+psbqQy0asRWojsHJRVHlZcZOsdRXuLC1O4xOf3TYhXzY4oydCcmOnd19mQs7qqqm1p1b0rEjApSzbOWKWbfufTSaVO3GtmS+y4x6b5GPpjRNrvFgS1cYazb3ASh8YQdIjGPt6Y/C41QwzsfXRSIiIrKvMXOm0zswAK/Hg9t++tNBb5/Z0pLx499dvx7fveEGnHrssfjGSSfhz//4B86/5hrc88tfwum0Z7BwJzt2ikqEJ9eXO+Er4MgBZQ9QtnoUq6HCBZcD6ArEEI7Gh3UGRWIqVAAuB+CyIMRXX8ZO6XTsAMCkGg+ARGDv9HoWWYtBjD5F4om/vyVFKOzUeF3Y0x/FpBoPHBZsxCMiIiIaLcZMBaCnrw+NdXXYf/58XR//t0cewaH7EYFSKwAAHm1JREFU7YfvnX02AGDRnDk4+txz8eq772LZkiVWHmrRaBuxyllUKAZR2Jlax9GPQmtIboHLNIpldXiyQ1EwrtKNXX0R7OmPahuBBCu7dQCdGTsWF7dGG7EZq7nKrf18qLDSR5/mNJYVpZNUbMaaXM1V50RERGRvY+b2bW9/P+pra3V9bCQaxfNr1+JzS5dqbxtXX4/F8+bh2VdesegIi48dO8UlQnRnNbCwU2jiMZ+xsFOA4OBsOTtWBicDOjN2LB5HG20mJ/NdmK9TPOkFzmKMYQFAXXI8lsHJREREZHdjpgLQ29+Pts5OfOmii9C6Zw9mtLTgwtNPx6cOPHDYx3Z2dyMSjWLqpEmD3j514kTsbGsr1CEXXFcgkbFRz4ydovjsrCr84ujJ+NR0X7EPpeSIx7z4G0gXLkC+TFOVG9gVyFjYCVm06lzQMnbCWTJ2SmwUa/nMapy0oA4nLqgt9qGUrPRiyoFFKuyIgi8zz4iIiMjuxkwFYEZLC7bt2oWvHHMMHIqCux56CJetXIm/3XQT5s+cOehj27u7AQA1vsEX2DVVVXh/w4ZCHXLBdSW7FeoqOHpQDB6nAyctrCv2YZSkhiwdO+ECFDWafCMHKAct/v5axk4kW8ZOaYUn+8qc+MUxk4t9GCUtfRTroJbiFHbO2L8BcRX44j61Rfn+RERERIUyZgo7XznmGHzlmGO0/z5w4UIcd/75uPuxx/CzSy8d9LHi0kVV1UFvV1XV1gGKnezYoRKlKzzZyo6dZGEn+yiWVR07OjJ2YqXVsUPFV+114uLDxkNRgHGVxcm4md3oxbWfn5T7A4mIiIjGuDFbAagoL8fiuXOxpbV12Psa6hJdEz39/YPeLgKY7UoLT2bGDpWY+mSXWsbCTrKo4bEwY0esPN/Tl20rVxEzdkosPJlGh4sOayr2IRARERGVhDF9+zYcicBXUTHs7Q21tSjzeLBlx45Bb/+ktRXN48YV6vAKTgtP5lYsKjFZR7G04GDrR7GK07GjY915iYUnExERERGVkjFR2On3+/H0yy8Pelt7VxfeXbcOC2fPBgAMBAKIxxMXNi6nE0cecgieSduAtae9HR9u2ICjDj+8cAdeQKqqosufGMUqxlpZomKq9SYe893BGGLxwSOYWr6MlVuxqpJbsTJm7IjwZIszdrKEJ1ud80NERERERMUzJioAH27ciB/dcgv+tXYtlh1wABRFwR333YfKigp89YQT0NHdjePOOw+H778/fnnllQCAM44/HudcfTVu+OMfcdDChfjjAw9g7vTpOGTffYv8r7FGfziOSFxFhdsBr5sXb1Ra3E4FtV4nuoMx9ARjg8YRtY1QBejY2TsQQXxIlpfVG6m0jJ0s4cnhAhS3iIiIiIioOMZEBeDQxYvx55Ur4VAU3HbPPbjhjjswc8oU/O3GG1Ht88HjdmNcfT0mpI1ZLZozB/9z5ZX4cMMG/PR3v8PEcePwu2uugcMxJv7JholskTqOYVGJqhshQFlbd25hUaPM5UBtuRPR+PBxsGDE2lEskS+0t3/4GJpQiOIWEREREREVx5jo2AGAhbNn4+eXXZbxfVWVlXj0ttuGvX3ZkiVYtmSJxUc2Omj5OgxOphLVUOHEJ52JwsqstLenihrWdqs0+dzoDsSwpy86aAuQGMUqs6iTbnpdGQBga3doWLcQAETjKmIq4FAATmIREREREdkPT/NtoourzqnENZRnDlDWwpMtrmpMGCFAOWRxeLKvzIlxlS6Eoip29g7P+El9fwcUhaNYRERERER2w8KOTaRWnXMUi0qTGMUSRU6hEOHJQCpAefeQAGWrw5MBYHp9omvnk87QsPcV6t9PRERERETFwcKOTXRyIxaVuJFWnodihRvFAoC9I3TslFlYWBGFnY8zFHbCXHVORERERGRrLOzYRBczdqjE1SeDw4eNYomOFYuDg5uqMo9iBdNGoawyo27kjp3+UMzy709ERERERMXDM32b0EaxuBWLSpQoanYN7dgR4cVWj2IlO3aGjmLt6En8t5X5V9ooVtfwws6G9iAAYEbyY4iIiIiIyF5Y2LGJmmRBZ844b5GPhKg4tFGswNDwZDEKZXHHjhaenPr+sbiKtdv7AQAHtVRa9r1nZMnY+WhPAAAwf3y5Zd+fiIiIiIiKh3M7NvH9I5px5v4NmFLLu/JUmkTHjsibEkIxMYplbcfOhAyjWP/eG0BvKI7JNW5MrvFY9r0nVrvhcSrY0x9FfzgGnyfVubdub6JjZ0ETi75ERERERHbEjh2bcDkUFnWopDVohZ3ijGJVlzngdSkYCMe1XJvXtg0AAA6d4rP0ezsdCqbVJQpHWzrD2ttVVcVHe9mxQ0RERERkZyzsEJEt1HidUAB0B2OIJLt0ACCcDC+2OjxZUZS0caxE185r2xJjWEstLuwAwPS64Tk7u/si6A7EUOt1YmK12/JjICIiIiKiwmNhh4hswelQUJfMmuoOprp2tHXfFnfsAOmbsaIIx+J4a0eiY+eQKdbl6wjayvOOVGHno+QY1vzxXigK150TEREREdkRCztEZBtagHLaOJbI2CmzOGMHGLwZ6/1dAQSiKmY1lGFcpfXdMpk2Y61LBifv08QxLCIiIiIiu2J4MhHZRl2FC+gIoSstQDkULcxWLABo8iWeUvf0R7CzN5F1Y3W+jpBpM5bI19mH+TpERERERLbFwg4R2UbGjp1oYbZiAWmjWH0RbEqORC0twBgWkOrY2dIVQlxV4VAUbSMWO3aIiIiIiOyLo1hEZBv1yYyd9MJOOJYMTy5Axs6E5CjWlq4Q3t3phwLgoJbCdOxUlTnRWOFCMKpiV28EHQNR7O6LoMLt0DZmERERERGR/bBjh4hso16sPA8kCjtvtQ4gGgfcTgVuR+E6dtZuH0BMBRY0laPG67T8+woz6svQ7o/ik64Q1ORisHnjvXAwOJmIiIiIyLbYsUNEtiFGsTr9UWzvDuPCh7YCAM7Yr74gW6FEeLLYtn5ogcawBG0zVmcI65L5OguYr0NEREREZGvs2CEi2xAdO1u7wrjgwS3oCsSwbJoPVxzRXJDv31jpgkMB4snCztICBScL0+sTI1efdIbQmQyQnj/eW9BjICIiIiKiwmJhh4hsQ3TsvL59AAAws74Mtxw/Ba4CjGEBgMuhoLHShb39UbgcwJJJhe3YSd+MtbM3AiAxDkZERERERPbFUSwisg3RsQMAteVO3H7SVFSVFS7jBkiNYy1urkCFp7BPsWIU6997g9jaHYbbqWBmAzt2iIiIiIjsjIUdIrKN8ZUuuB2JoOTfnTAVU2rLCn4ME5IByocWeAwLACZVe+B2KugJJsaw5jR64S7AmnciIiIiIioejmIRkW34ypy448vTUOlxYN/miqIcwymL6tEViOLkRXUF/95Oh4JptR5s7AgBAPZhvg4RERERke2xsENEtrJ0auE7ZdIdMaMKR8yoKtr3n15flirsMF+HiIiIiMj2OIpFRGQjImcHAPbhqnMiIiIiIttjYYeIyEbEZiyHAswdx1EsIiIiIiK7Y2GHiMhGRDFn7jgvyt18iiciIiIisrsxk7HT29+P3999N1599130Dgzg4EWL8L2zz8a4+vqMH//82rW4dOXKYW///TXX4LD997f6cImIimL++HL86gstXHNORERERFQixkRhp7u3F+f+6EfwVVbim6ecAkVRcNs99+DS667D3266CQ7H8LvSvQMD8Ho8uO2nPx309pktLYU6bCKiojh2Xm2xD4GIiIiIiApkTBR2qn0+nLxiBb68YgXcrsQhT2xqwjd++EN8tGkTFs2ZM+xzevr60FhXh/3nzy/04RIRERERERERFcSYCGBwOBw47bjjtKIOAMybPh0AsKe9PePn9Pb3o762thCHR0RERERERERUFGOiYyeTjVu3AgBmjDBa1dvfj7bOTnzpoovQumcPZrS04MLTT8enDjywkIdJRERERERERGSZMdGxk8nqp5/GjMmTMW3SpIzvn9HSgumTJ+PSr30NN3//+6gsL8dlK1di3ebNBT5SIiIiIiIiIiJrjMmOnXfXr8fDa9bglh/+MGNwMgB85Zhj8JVjjtH++8CFC3Hc+efj7scew88uvbRQh0pEREREREREZJkx17HT3tWFH9x0E05YvhxHHHyw7s+rKC/H4rlzsaW11cKjIyIiIiIiIiIqnDFV2AmFw7j8F79AQ10drjr/fMOfH45E4KuosODIiIiIiIiIiIgKb8wUdiLRKL53443o7OnBrVdfDY/bPej9A4EA4vE4AKDf78fTL7886P3tXV14d906LJw9u2DHTERERERERERkpTGRsROPx/HjX/8ab7z/PlZ+5zto3bMH23fvBgB43G5MaGzEceedh8P33x+/vPJKfLhxI350yy3419q1WHbAAVAUBXfcdx8qKyrw1RNOKPK/hoiIiIiIiIhIjjFR2Hln3Tr8vxdfBAB85/rrB71v4vjxuPdXv8K4+npMGDcOAHDo4sX488qV+Pvjj+O2e+5B38AADlq0CN87+2xU+3wFP34iIiIiIiIiIiuMicLOkgUL8O5DD2X9mEdvu23Qfy+cPRs/v+wy3d8jHIkAALbv2mX08IiIiIiIiIiIpBL1CVGvGMmYKOwUwp72dgDA5b/4RZGPhIiIiIiIiIgoYU97O/aZOXPE9yuqqqoFPJ5Rq7e/H2999BEmNDbCPSSYmYiIiIiIiIiokCKRCHa3t2PJggVZY2VY2CEiIiIiIiIiGqPGzLpzIiIiIiIiIiIajIUdIiIiIiIiIqIxioUdIiIiIiIiIio5x37rW7ju9tuLfRh541asUewnt96KDzZswIO//W2xD4VGgRfeeAN33H8/tu3ahQMXLMDVF1yA+poaAMB3r78e/3zttUEf31hXh2fvvLMYh0oWyvY42LZrF2644w68t349WiZMwH994Qv44vLlRT5ikikWi+HVd9/Fky+8gP/34otY+Z3vYMWyZdr7X3jzTdzz2GP4YMMGVFVWYsWyZTj/tNPgLSsr4lGTbNkeBz+59VY8smZNxs87/7TTcP5ppxXyUMlCvf39+P3dd+PVd99F78AADl60CN87+2yMq68HAHR0d+Nfa9fi3ieewNadO/H6ffcV+YjJCrkeBzxHLA25Hgelco5YytfPLOwQjQHvrl+P795wA0499lh846ST8Od//APnX3MN7vnlL+F0OtE7MIDPLV2KM774Re1zXE5nEY+YrJDtcRAMh3HO1Vdj+qRJuO6yy/Dxjh247vbbEY5EcPKKFcU+dJKkq7cXK//wB8RiMcTi8UHve+ODD3DFjTfiv447DqceeyzeW78e//foo/AHg7jqvPOKdMRkhWyPg3NOPhlfOuqoQW9768MPseq++3DMpz5VyMMkC3X39uLcH/0IvspKfPOUU6AoCm675x5cet11+NtNN8HhcOCZl1/GXx5+GH0DA8U+XLKInscBzxHtL9fjIBAK8RyxBLCwQzQG/O2RR3Dofvvhe2efDQBYNGcOjj73XLz67rtYtmQJevr6cNDChdh//vwiHylZKdvjYOfevfAHAvjllVeiqrISRxx8MNwuF1bddx9OWL4cbre7yEdPMjTW1eGJVauwc+9eHPutbw1630GLFmH1b36DSU1NAIDPHHwwevv78dzrr7OwYzPZHgdTJ07E1IkTtf+OxWK47rbbcO7JJ2PqpEmFPlSySLXPh5NXrMCXV6yA25U4nZ/Y1IRv/PCH+GjTJiyaMwenHXccTjvuONz+97/jztWri3zEZAU9jwOeI9pfrsfBus2beY5YApixM0Y8smYN9jvxRHR0d2tv27l3L/Y78UQ89dJL2tuO/da38NCzz+Kpl17C137wAyw7/XR89/rr0dvfX4SjJhki0SieX7sWn1u6VHvbuPp6LJ43D8++8gqARPtlfW1tkY6QCiHX4+Dj7dsxbfJkVFVWau//4vLl2NvRgff+859iHDIVgSjqCOFIBBVeb5GOhkaD+596CoFQCN846aRiHwpJ5HA4cNpxx2kXcQAwb/p0AMCe9vZiHRYVmJ7HAc8R7S/X46BUzxH1Xj/bBTt2bOjO1atRV1OD07/wBXT29OB/7rwT//vgg7jkq18t9qGRCZ3d3YhEo8PutE6dOBE729oAJF60H1mzBr/+y1+gKAoOXbwY3zvnHIxPztXS2JfrcbB43jx0dndDVVUoiqK9v8Lrxa7k44RKQzgSwd6ODjzzyiv456uv4r8vvrjYh0RFoqoq/u+RR3DyihW8I1sCNm7dCgCY0dJS5COhYhr6OOA5YmlKfxxs2LqV54glgB07NtRQW4tV116Loz/1KZz+hS9gycKFePPDD4t9WGRSe7LKXOPzDXp7TVUV2ru6AAD7zJqFgxYtwv9ceSUuOuMMvP7++7jsuusQH5K9QGNXrsfB0sWLsautDbf//e/o7u3Fe+vX46Kf/QzRWAx7OzqKcMRULD+/7TZ84fzzcetf/4ofXXABPn/44cU+JCqS199/H7va23GCDQMyabjVTz+NGZMnYxpH7kra0McBzxFLU/rjgOeIpYEdOzY0c8oUeNLuzE0cNw5vfPBBEY+I8iHq6qqqDnq7qqpwJKvuf/z5z7W3H7RoEWqqqvCDm2/GWx99hIMWLSrUoZKFcj0O9t9nH1x0xhm4/d578Yd778W4ujpcd/nluOS66+DxeAp/wFQ055x8Mo446CC89t57uOY3v8Gutjacc/LJxT4sKoKnXnoJi+fO5RhGCXh3/Xo8vGYNbvnhD+Fw8L5tqcr0OOA5YukZ+jjgOWJpYGGnBLhcLsSHXAzS2NFQVwcA6BmSk9TT14fG5PuGWrrffgCALa2tfNG2CT2Pg3NPOQVnfPGL2NvRgSnNzRgIBBAMhdhuXWJEeO5nly7F1IkT8av//V8c8+lPY+L48cU+NCqw99avx+H771/swyCLtXd14Qc33YQTli/HEQcfXOzDoSLR+zjgOaK9jfQ44Dmi/bGkP4oFgkGt80Z0ZkSj0WIeEhVBQ20tyjwebNmxY9DbP2ltRfO4cRk/JxyJAAB8FRWWHx8Vht7HQXlZGaZOnAhFUfDOv/8NRVGwcPbsQh8ujRKHLl6MWDyOTclZeyodvf39+GTHDsyfObPYh0IWCoXDuPwXv0BDXR2uOv/8Yh8OFYmRxwHPEe0r1+OgFM4RS/n6mYWdUSIcieDxf/1r0Ns2bt2KlgkTAAB1NTUAEknewstvv12w46PicTmdOPKQQ/BMcgMWkEi4/3DDBhx1+OF4/b330Lpnz6DPefaVV6AoCvaZNavQh0sWyfU4AIBgKKS9T1VV3PP44zjioIOGbUoie3rtvfewY/fuQW9b//HHAICW5uZiHBIV0Y7du6Gq6og3AGjsi0Sj+N6NN6Kzpwe3Xn31oDF8Kh3ZHgc8RywduZ4P7HiOyOvnwTiKNUq0d3Xh5jvvxHNr12LZAQfgzQ8/xJbWVlxxzjkAgIWzZ8NbVoZf3XUXzjj+eLy3fj0+2rQJTs5Rl4Qzjj8e51x9NW744x9x0MKF+OMDD2Du9Ok4ZN99ce3vfocX3nwTX/7857Fo7lz85+OPccf99+OUo4/G1IkTi33oJFG2x8Hm7dtx3k9+gm+cdBImjh+Px557Du+tX48/XXddsQ+bJNq6cyc6e3q04PRPduzAO+vWob6mBk++8AJeePNNnJx8Ltixezdu//vf8akDD8T0yZOLfOQkU7bHgXjeF+tda6uri3WYZKF4PI4f//rXeOP997HyO99B65492J4s7HrcbiyYNQvvrFsHANjd1oZ4PK799+ypU9mtYRO5HgfidYHniPaW63HgLSuz5TmirOvnCY2N+Hj7dnT29KA+WQwaixR1aBInFc0HGzZg1X334d1169DU0ICvnnACTvjsZ7X3P/3yy/j1X/6CUDiMIw46CN87+2wce955uPKb38SKZcsAAMd+61s4/IADcHVa+911t9+Ol99+G0+sWlXwfxPJ89Jbb+EP996Lbbt24aCFC3H1BRegrroaqqriviefxPNvvIEPN25EXXU1TvjsZ/H1E0+E0+ks9mGTZNkeB3euXo3Hn38ebZ2dWDBrFr579tmYNWVKsQ+ZJPrJrbfikTVrhr39i8uX46cXX4x7Hn8cLySfC2qqqvDZpUtx3qmnorK8vAhHS1bJ9ji49pJLAAAP//OfuOY3v8Gau+4a0yeqlNlbH32Ec66+OuP7Jo4fjydWrcJ+J56Y8f1//PnPceDChRYeHRVKrsfB43/4A88RS4Cex4FdzxFlXD+vfuYZ3PynP+GKc87Bl446qlj/lLyxsENERERERERENEZxjoeIiIiIiIiIaIxiYYeIiIiIiIiIaIxiYYeIiIiIiIiIaIxiYYeIiIiIiIiIaIxiYYeIiIiIiIiIaIxiYYeIiIiIiIiIaIxiYYeIiIiIiIiIaIxiYYeIiIiIiIiIaBRYvnw5rrnmGkOfw8IOEREREREREY16vb29+NnPfoYVK1Zg6dKluPzyy7F3717t/bFYDDfccAOOPPJIrFixAqtWrRr2NT744AP88pe/xJIlSzIWUP76179i7ty5w/738ccfGzrWH/7whzjmmGOM/yNNcBXkuxARERERERERmdTV1YWvfe1r8Pl8uOCCC6AoCn7zm9/g/PPPxwMPPACHw4HrrrsOTzzxBK688kr4/X7ccMMNcDqdOOecc7Svc+ONN6K1tRXBYDDj9+np6UFLSwtuuOGGQW+fOHGipf++fLCwQ0RERERERESjWk1NDU499VSceuqpcLvdAIDJkyfj9NNPxwcffICpU6fi/vvvx0033YSjjz4aAOD3+3HnnXfirLPOgtPpBJDoyAESI0+Z9PT0YNKkSViyZEkB/lVycBSLiIiIiIiIiEY1h8OBM888UyvqAMD8+fMBALt378a//vUvKIqCz3zmM9r7V6xYgba2Nrzzzju6v09PTw8aGxulHbfw4IMPYu7cuWhvb9fe1trairlz5+KJJ57I62uzsENEREREREREY86GDRsAALNmzcLOnTvR3NwMr9ervb+lpQUulws7d+7U/TV7e3uxbt06LF++HIsXL8Z//dd/4b333pN+7DJxFIuIiIiIiIiIxpz77rsPM2fOxPTp09He3o6ampphH1NTU4O2tjbdX3P27NmoqKjAiSeeiEAggN/+9rc466yz8OSTT2LChAkyD18aFnaIiIiIiIiIaEx5++23sXr1avz+97+Hw+GAoihQVXXYx6mqCodD/7DSd7/73UH/ve++++Koo47C/fffj4svvhiRSGTQ93G73VAUxfw/RAKOYhERERERERHRmNHW1obLL78cJ510khaC3NjYiJ6enkEfp6oqenp6MG7cONPfq7m5GTNnztTWnZ999tlYtGiR9r833njD/D9EEnbsEBEREREREdGYEAqFcOGFF6KxsRH//d//rb194sSJ2LVrF/x+PyoqKgAAW7duRSwWy3tVeSgUQlVVFQDg2muvxcDAgPa+6dOnZ/wcv9+PsrIy7b9FV080Gs3rWDJhxw4RERERERERjXqRSASXXHIJOjo6cPvtt8Pj8WjvW758ORRFwXPPPae97amnnsKECROw33776fr6ra2tePnllwe9bf369di6dSsWLVoEIFHIWbhwofa/yspKhMNhPPzww4M+7z//+Q+mTJmi/Xd9fT0AYMeOHdrbXnjhBX3/8BzYsUNEREREREREo1o8HscPfvADvPbaa7j55puxY8cObNu2DQDg8XiwaNEinHbaabj22msRDofh9/vxu9/9Dt/97ne1jJ2Ojg5s2bIFABAOh9HW1oa33npL+/y1a9fixz/+Mb785S/jsMMOQ29vL37zm99gzpw5+NKXvjTisbW1teH666/HP//5T3z605/G2rVr8cknn+Cqq67SPmbfffdFeXk5brrpJnz961/HO++8gw8++ABOp3PQ12pubsbmzZvR2dmpFYNyUdRM6UJERERERERERKPEG2+8gTPPPDPj+yZNmoQ1a9YgHo/j5ptvxpNPPgmPx4OTTz4Z3/zmN7WPe/DBB3HllVeO+PkA8NJLL+GBBx7AO++8g1gshs985jO44oorMm7cSvf+++/jd7/7Hd5++21MmDAB3/jGN3DSSScN+pgnn3wSN998M0KhEJYvX44rr7wSn/3sZ/HjH/8Yxx57LADg/vvvx8qVK3HVVVfhlFNO0fWzYWGHiIiIiIiIiGiMYsYOEREREREREdEYxcIOEREREREREdEYxcIOEREREREREdEYxcIOEREREREREdEYxcIOEREREREREdEYxcIOEREREREREdEYxcIOEREREREREdEYxcIOEREREREREdEYxcIOEREREREREdEYxcIOEREREREREdEYxcIOEREREREREdEYxcIOEREREREREdEY9f8BOr4OyzlT68YAAAAASUVORK5CYII=",
      "text/plain": [
       "<Figure size 1152x384 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "converter = mdates.ConciseDateConverter()\n",
    "munits.registry[np.datetime64] = converter\n",
    "munits.registry[date] = converter\n",
    "munits.registry[datetime] = converter\n",
    "\n",
    "plt.figure(figsize=(12, 4))\n",
    "plt.plot(data_ts[\"time\"], (data_ts[\"t\"] - 273.15))\n",
    "plt.ylabel(\"Temperature [°C]\")\n",
    "plt.title(f\"MERA_FC3hr, lon={LON}, lat={LAT}\")\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
}