regional_subset_shbaam.ipynb

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    "# Import Dependencies\n",
    "## Required\n",
    "### rioxarray (Will get xarray and other dependencies as needed)\n",
    "### geopandas"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "864fbaf1-3c55-432c-a4e1-0161f855aca3",
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   "source": [
    "import os\n",
    "import glob\n",
    "import time\n",
    "import math\n",
    "\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "import xarray as xr\n",
    "import rioxarray\n",
    "import geopandas as gpd\n",
    "from shapely.geometry import mapping"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4456ccea-1263-4a1e-b677-e0d400c0803b",
   "metadata": {},
   "source": [
    "## Set path to the grace dir here"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "8cb8fcea-2e74-44e6-bb63-de2b6fdc689f",
   "metadata": {},
   "outputs": [],
   "source": [
    "grace_dir = '/home/dev/grace_dir/'"
   ]
  },
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   "cell_type": "code",
   "execution_count": 3,
   "id": "de77177c-ba75-4e78-bac1-b254ec385f6b",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>OBJECTID</th>\n",
       "      <th>Shape_Leng</th>\n",
       "      <th>Shape_Area</th>\n",
       "      <th>geometry</th>\n",
       "    </tr>\n",
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       "      <th>0</th>\n",
       "      <td>1</td>\n",
       "      <td>18.876597</td>\n",
       "      <td>3.089947</td>\n",
       "      <td>MULTIPOLYGON (((88.93296 26.33316, 88.93322 26...</td>\n",
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       "   OBJECTID  Shape_Leng  Shape_Area  \\\n",
       "0         1   18.876597    3.089947   \n",
       "\n",
       "                                            geometry  \n",
       "0  MULTIPOLYGON (((88.93296 26.33316, 88.93322 26...  "
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   "source": [
    "# Reading the NW Bangladesh shapefile\n",
    "gdf = gpd.read_file(os.path.join(grace_dir, 'NorthWestBD.shp'))\n",
    "gdf"
   ]
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  {
   "cell_type": "markdown",
   "id": "116d79bf-7793-43a4-a766-1a90f81fe5ad",
   "metadata": {},
   "source": [
    "# Start GLDAS Processing"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "e8356c7e-dee3-4e13-8383-4957ab37c6c1",
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   "source": [
    "# Load Concatenated GLDAS Model Files\n",
    "gldas_vic_ds = xr.open_dataset(os.path.join(grace_dir, 'vic.nc'))\n",
    "gldas_clsm_ds = xr.open_dataset(os.path.join(grace_dir, 'clsm.nc'))\n",
    "gldas_noah_ds = xr.open_dataset(os.path.join(grace_dir,'noah.nc'))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "8ea99435-68d1-46b4-93e2-927022a0472f",
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   "outputs": [],
   "source": [
    "# Clip GLDAS Model file to given GeoDataFrame\n",
    "def clip_gldas_ds(ds, gdf): \n",
    "    # Looping through the variables and setting a spatial dimension so that they can be clipped\n",
    "    for var in ds.variables:\n",
    "        if var not in ['lat', 'lon', 'time']:\n",
    "            ds[var] = ds[var].rio.write_crs(\"epsg:4326\") \n",
    "    ds.rio.set_spatial_dims(x_dim=\"lon\", y_dim=\"lat\", inplace=True)\n",
    "    clipped_ds = ds.rio.clip(gdf.geometry.apply(mapping), gdf.crs, drop=True)\n",
    "    return clipped_ds"
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   "cell_type": "code",
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    "# Calculate Surface Area of Grid Cell\n",
    "def calculate_surface_area(ds):\n",
    "    # Find the lon size\n",
    "    lon_interval_size = ds.variables['lon'][1] - ds.variables['lon'][0]\n",
    "    # Find the lat size\n",
    "    lat_interval_size = ds.variables['lat'][1] - ds.variables['lat'][0]\n",
    "    surface_area_array = np.array([6371000*math.radians(lat_interval_size)*6371000*math.radians(lon_interval_size)*math.cos(math.radians(lat)) for lat in ds.lat.values])\n",
    "    return surface_area_array"
   ]
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  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "94f2e012-d156-4f15-9c25-3cf7d8c35f9d",
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   "outputs": [],
   "source": [
    "# Unit Factors Dict\n",
    "unit_factors = {\"mm\": 1000, \"kg/m2\": 1000, \"kg/m^2\": 1000, \"cm\": 100, \"dm\": 10, \"m\": 1, \"km\": .001, \"kg m-2\": 1000}"
   ]
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  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "67803759-e6b3-4314-ad3e-07b328ba28f0",
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   "outputs": [],
   "source": [
    "# For a given gldas dataset and surface area data array calculate anomalies for each variable\n",
    "def calculate_gldas_anomalies(ds, surface_area_da):\n",
    "    for var in ds.variables:\n",
    "        if var not in ['lat', 'lon', 'time', 'spatial_ref']:\n",
    "            # Calculate variable mean from 2004 to 2009\n",
    "            var_mean = ds.sel(time=slice('2004-01-01', '2009-12-31')).mean('time')[var]\n",
    "#             ds.sel(time=slice('2004-01-01', '2009-12-31')).mean('time')[var]\n",
    "            var_factor = unit_factors[ds[var].units]\n",
    "            ds[var] = (ds[var] - var_mean)/var_factor * surface_area_da\n",
    "            ds[var] = ds[var]*100/surface_area_da\n",
    "    return ds"
   ]
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   "cell_type": "code",
   "execution_count": 9,
   "id": "bbc40278-39ad-4893-99f5-e3e8619102d6",
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   "outputs": [],
   "source": [
    "# Clipped GLDAS Model Files\n",
    "gldas_vic_ds = clip_gldas_ds(gldas_vic_ds, gdf)\n",
    "gldas_clsm_ds = clip_gldas_ds(gldas_clsm_ds, gdf)\n",
    "gldas_noah_ds = clip_gldas_ds(gldas_noah_ds, gdf)"
   ]
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       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.DataArray &#x27;CanopInt_inst&#x27; (time: 253, lat: 3, lon: 2)&gt;\n",
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       "        [          nan, 4.9741324e-03],\n",
       "        [1.6314936e-03,           nan]],\n",
       "\n",
       "       [[4.6360674e-03, 6.0724551e-03],\n",
       "        [          nan, 2.8319203e-03],\n",
       "        [1.9860514e-03,           nan]],\n",
       "\n",
       "       [[3.9738659e-03, 1.0312374e-02],\n",
       "        [          nan, 6.0620140e-03],\n",
       "        [1.2444491e-03,           nan]],\n",
       "\n",
       "       ...,\n",
       "\n",
       "       [[2.6973630e-03, 5.9376070e-03],\n",
       "        [          nan, 3.8915239e-03],\n",
       "        [3.0699957e-03,           nan]],\n",
       "\n",
       "       [[6.1404699e-04, 3.2297478e-04],\n",
       "        [          nan, 1.3766765e-03],\n",
       "        [6.0483871e-06,           nan]],\n",
       "\n",
       "       [[1.0117865e-03, 9.9555170e-04],\n",
       "        [          nan, 9.1912842e-04],\n",
       "        [0.0000000e+00,           nan]]], dtype=float32)\n",
       "Coordinates:\n",
       "  * lat          (lat) float64 24.5 25.5 26.5\n",
       "  * lon          (lon) float64 88.5 89.5\n",
       "  * time         (time) datetime64[ns] 2000-01-01 2000-02-01 ... 2021-01-01\n",
       "    spatial_ref  int64 0\n",
       "Attributes:\n",
       "    standard_name:  canopy_water_amount\n",
       "    long_name:      Plant canopy surface water\n",
       "    units:          kg m-2\n",
       "    cell_methods:   time: mean\n",
       "    vmin:           0.0\n",
       "    vmax:           0.8526354</pre><div class='xr-wrap' hidden><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'>'CanopInt_inst'</div><ul class='xr-dim-list'><li><span class='xr-has-index'>time</span>: 253</li><li><span class='xr-has-index'>lat</span>: 3</li><li><span class='xr-has-index'>lon</span>: 2</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-1fd34b73-160f-4993-9518-60b5e8b3b9a7' class='xr-array-in' type='checkbox' checked><label for='section-1fd34b73-160f-4993-9518-60b5e8b3b9a7' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>0.00448 0.005843 nan 0.004974 0.001631 ... nan 0.0009191 0.0 nan</span></div><div class='xr-array-data'><pre>array([[[4.4795391e-03, 5.8432859e-03],\n",
       "        [          nan, 4.9741324e-03],\n",
       "        [1.6314936e-03,           nan]],\n",
       "\n",
       "       [[4.6360674e-03, 6.0724551e-03],\n",
       "        [          nan, 2.8319203e-03],\n",
       "        [1.9860514e-03,           nan]],\n",
       "\n",
       "       [[3.9738659e-03, 1.0312374e-02],\n",
       "        [          nan, 6.0620140e-03],\n",
       "        [1.2444491e-03,           nan]],\n",
       "\n",
       "       ...,\n",
       "\n",
       "       [[2.6973630e-03, 5.9376070e-03],\n",
       "        [          nan, 3.8915239e-03],\n",
       "        [3.0699957e-03,           nan]],\n",
       "\n",
       "       [[6.1404699e-04, 3.2297478e-04],\n",
       "        [          nan, 1.3766765e-03],\n",
       "        [6.0483871e-06,           nan]],\n",
       "\n",
       "       [[1.0117865e-03, 9.9555170e-04],\n",
       "        [          nan, 9.1912842e-04],\n",
       "        [0.0000000e+00,           nan]]], dtype=float32)</pre></div></div></li><li class='xr-section-item'><input id='section-a8f3b3d7-9283-439e-981f-31b7b6b933d2' class='xr-section-summary-in' type='checkbox'  checked><label for='section-a8f3b3d7-9283-439e-981f-31b7b6b933d2' class='xr-section-summary' >Coordinates: <span>(4)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lat</span></div><div class='xr-var-dims'>(lat)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>24.5 25.5 26.5</div><input id='attrs-bf4b6055-2b28-4533-a59e-9b966e0b57db' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-bf4b6055-2b28-4533-a59e-9b966e0b57db' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8ea9afb2-a53b-4685-ac02-969e3fee6ce4' class='xr-var-data-in' type='checkbox'><label for='data-8ea9afb2-a53b-4685-ac02-969e3fee6ce4' 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>latitude</dd><dt><span>long_name :</span></dt><dd>latitude</dd><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>axis :</span></dt><dd>Y</dd></dl></div><div class='xr-var-data'><pre>array([24.5, 25.5, 26.5])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lon</span></div><div class='xr-var-dims'>(lon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>88.5 89.5</div><input id='attrs-bf6c5592-2452-4df2-a32e-83f49ca29b96' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-bf6c5592-2452-4df2-a32e-83f49ca29b96' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-934c4e84-72fc-43eb-971f-8e25aa482953' class='xr-var-data-in' type='checkbox'><label for='data-934c4e84-72fc-43eb-971f-8e25aa482953' 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>longitude</dd><dt><span>long_name :</span></dt><dd>longitude</dd><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>axis :</span></dt><dd>X</dd></dl></div><div class='xr-var-data'><pre>array([88.5, 89.5])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2000-01-01 ... 2021-01-01</div><input id='attrs-9f783c09-d24e-4943-af9e-7565caeaffaf' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-9f783c09-d24e-4943-af9e-7565caeaffaf' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0e5d1e94-df02-43e7-a4fd-6e14771e7ec1' class='xr-var-data-in' type='checkbox'><label for='data-0e5d1e94-df02-43e7-a4fd-6e14771e7ec1' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>time</dd><dt><span>bounds :</span></dt><dd>time_bnds</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;2000-01-01T00:00:00.000000000&#x27;, &#x27;2000-02-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;2000-03-01T00:00:00.000000000&#x27;, ..., &#x27;2020-11-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;2020-12-01T00:00:00.000000000&#x27;, &#x27;2021-01-01T00:00:00.000000000&#x27;],\n",
       "      dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>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-93c5c9cb-ee27-4e7f-aaa4-028c9e47445d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-93c5c9cb-ee27-4e7f-aaa4-028c9e47445d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6a83ee27-47ce-4fc4-8e09-0ca2f66fc47d' class='xr-var-data-in' type='checkbox'><label for='data-6a83ee27-47ce-4fc4-8e09-0ca2f66fc47d' 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>GEOGCS[&quot;WGS 84&quot;,DATUM[&quot;WGS_1984&quot;,SPHEROID[&quot;WGS 84&quot;,6378137,298.257223563,AUTHORITY[&quot;EPSG&quot;,&quot;7030&quot;]],AUTHORITY[&quot;EPSG&quot;,&quot;6326&quot;]],PRIMEM[&quot;Greenwich&quot;,0,AUTHORITY[&quot;EPSG&quot;,&quot;8901&quot;]],UNIT[&quot;degree&quot;,0.0174532925199433,AUTHORITY[&quot;EPSG&quot;,&quot;9122&quot;]],AXIS[&quot;Latitude&quot;,NORTH],AXIS[&quot;Longitude&quot;,EAST],AUTHORITY[&quot;EPSG&quot;,&quot;4326&quot;]]</dd><dt><span>semi_major_axis :</span></dt><dd>6378137.0</dd><dt><span>semi_minor_axis :</span></dt><dd>6356752.314245179</dd><dt><span>inverse_flattening :</span></dt><dd>298.257223563</dd><dt><span>reference_ellipsoid_name :</span></dt><dd>WGS 84</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>WGS 84</dd><dt><span>grid_mapping_name :</span></dt><dd>latitude_longitude</dd><dt><span>spatial_ref :</span></dt><dd>GEOGCS[&quot;WGS 84&quot;,DATUM[&quot;WGS_1984&quot;,SPHEROID[&quot;WGS 84&quot;,6378137,298.257223563,AUTHORITY[&quot;EPSG&quot;,&quot;7030&quot;]],AUTHORITY[&quot;EPSG&quot;,&quot;6326&quot;]],PRIMEM[&quot;Greenwich&quot;,0,AUTHORITY[&quot;EPSG&quot;,&quot;8901&quot;]],UNIT[&quot;degree&quot;,0.0174532925199433,AUTHORITY[&quot;EPSG&quot;,&quot;9122&quot;]],AXIS[&quot;Latitude&quot;,NORTH],AXIS[&quot;Longitude&quot;,EAST],AUTHORITY[&quot;EPSG&quot;,&quot;4326&quot;]]</dd><dt><span>GeoTransform :</span></dt><dd>88.0 1.0 0.0 24.0 0.0 1.0</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-2e90e000-33e4-4b6d-9634-10f8df1af9eb' class='xr-section-summary-in' type='checkbox'  checked><label for='section-2e90e000-33e4-4b6d-9634-10f8df1af9eb' class='xr-section-summary' >Attributes: <span>(6)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>canopy_water_amount</dd><dt><span>long_name :</span></dt><dd>Plant canopy surface water</dd><dt><span>units :</span></dt><dd>kg m-2</dd><dt><span>cell_methods :</span></dt><dd>time: mean</dd><dt><span>vmin :</span></dt><dd>0.0</dd><dt><span>vmax :</span></dt><dd>0.8526354</dd></dl></div></li></ul></div></div>"
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       "<xarray.DataArray 'CanopInt_inst' (time: 253, lat: 3, lon: 2)>\n",
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       "\n",
       "       [[4.6360674e-03, 6.0724551e-03],\n",
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       "\n",
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       "        [          nan, 6.0620140e-03],\n",
       "        [1.2444491e-03,           nan]],\n",
       "\n",
       "       ...,\n",
       "\n",
       "       [[2.6973630e-03, 5.9376070e-03],\n",
       "        [          nan, 3.8915239e-03],\n",
       "        [3.0699957e-03,           nan]],\n",
       "\n",
       "       [[6.1404699e-04, 3.2297478e-04],\n",
       "        [          nan, 1.3766765e-03],\n",
       "        [6.0483871e-06,           nan]],\n",
       "\n",
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       "        [          nan, 9.1912842e-04],\n",
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       "Coordinates:\n",
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       "  * lon          (lon) float64 88.5 89.5\n",
       "  * time         (time) datetime64[ns] 2000-01-01 2000-02-01 ... 2021-01-01\n",
       "    spatial_ref  int64 0\n",
       "Attributes:\n",
       "    standard_name:  canopy_water_amount\n",
       "    long_name:      Plant canopy surface water\n",
       "    units:          kg m-2\n",
       "    cell_methods:   time: mean\n",
       "    vmin:           0.0\n",
       "    vmax:           0.8526354"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "gldas_vic_ds.CanopInt_inst"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "ccb7de30-6b6a-4032-88e1-0bd2a1795ac3",
   "metadata": {},
   "outputs": [
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       "  grid-column: 2 / -1;\n",
       "}\n",
       "\n",
       ".xr-section-details {\n",
       "  display: none;\n",
       "  grid-column: 1 / -1;\n",
       "  margin-bottom: 5px;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked ~ .xr-section-details {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-array-wrap {\n",
       "  grid-column: 1 / -1;\n",
       "  display: grid;\n",
       "  grid-template-columns: 20px auto;\n",
       "}\n",
       "\n",
       ".xr-array-wrap > label {\n",
       "  grid-column: 1;\n",
       "  vertical-align: top;\n",
       "}\n",
       "\n",
       ".xr-preview {\n",
       "  color: var(--xr-font-color3);\n",
       "}\n",
       "\n",
       ".xr-array-preview,\n",
       ".xr-array-data {\n",
       "  padding: 0 5px !important;\n",
       "  grid-column: 2;\n",
       "}\n",
       "\n",
       ".xr-array-data,\n",
       ".xr-array-in:checked ~ .xr-array-preview {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-array-in:checked ~ .xr-array-data,\n",
       ".xr-array-preview {\n",
       "  display: inline-block;\n",
       "}\n",
       "\n",
       ".xr-dim-list {\n",
       "  display: inline-block !important;\n",
       "  list-style: none;\n",
       "  padding: 0 !important;\n",
       "  margin: 0;\n",
       "}\n",
       "\n",
       ".xr-dim-list li {\n",
       "  display: inline-block;\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "}\n",
       "\n",
       ".xr-dim-list:before {\n",
       "  content: '(';\n",
       "}\n",
       "\n",
       ".xr-dim-list:after {\n",
       "  content: ')';\n",
       "}\n",
       "\n",
       ".xr-dim-list li:not(:last-child):after {\n",
       "  content: ',';\n",
       "  padding-right: 5px;\n",
       "}\n",
       "\n",
       ".xr-has-index {\n",
       "  font-weight: bold;\n",
       "}\n",
       "\n",
       ".xr-var-list,\n",
       ".xr-var-item {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-var-item > div,\n",
       ".xr-var-item label,\n",
       ".xr-var-item > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-even);\n",
       "  margin-bottom: 0;\n",
       "}\n",
       "\n",
       ".xr-var-item > .xr-var-name:hover span {\n",
       "  padding-right: 5px;\n",
       "}\n",
       "\n",
       ".xr-var-list > li:nth-child(odd) > div,\n",
       ".xr-var-list > li:nth-child(odd) > label,\n",
       ".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-odd);\n",
       "}\n",
       "\n",
       ".xr-var-name {\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-var-dims {\n",
       "  grid-column: 2;\n",
       "}\n",
       "\n",
       ".xr-var-dtype {\n",
       "  grid-column: 3;\n",
       "  text-align: right;\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-var-preview {\n",
       "  grid-column: 4;\n",
       "}\n",
       "\n",
       ".xr-var-name,\n",
       ".xr-var-dims,\n",
       ".xr-var-dtype,\n",
       ".xr-preview,\n",
       ".xr-attrs dt {\n",
       "  white-space: nowrap;\n",
       "  overflow: hidden;\n",
       "  text-overflow: ellipsis;\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-var-name:hover,\n",
       ".xr-var-dims:hover,\n",
       ".xr-var-dtype:hover,\n",
       ".xr-attrs dt:hover {\n",
       "  overflow: visible;\n",
       "  width: auto;\n",
       "  z-index: 1;\n",
       "}\n",
       "\n",
       ".xr-var-attrs,\n",
       ".xr-var-data {\n",
       "  display: none;\n",
       "  background-color: var(--xr-background-color) !important;\n",
       "  padding-bottom: 5px !important;\n",
       "}\n",
       "\n",
       ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
       ".xr-var-data-in:checked ~ .xr-var-data {\n",
       "  display: block;\n",
       "}\n",
       "\n",
       ".xr-var-data > table {\n",
       "  float: right;\n",
       "}\n",
       "\n",
       ".xr-var-name span,\n",
       ".xr-var-data,\n",
       ".xr-attrs {\n",
       "  padding-left: 25px !important;\n",
       "}\n",
       "\n",
       ".xr-attrs,\n",
       ".xr-var-attrs,\n",
       ".xr-var-data {\n",
       "  grid-column: 1 / -1;\n",
       "}\n",
       "\n",
       "dl.xr-attrs {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  display: grid;\n",
       "  grid-template-columns: 125px auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt,\n",
       ".xr-attrs dd {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  float: left;\n",
       "  padding-right: 10px;\n",
       "  width: auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt {\n",
       "  font-weight: normal;\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-attrs dt:hover span {\n",
       "  display: inline-block;\n",
       "  background: var(--xr-background-color);\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-attrs dd {\n",
       "  grid-column: 2;\n",
       "  white-space: pre-wrap;\n",
       "  word-break: break-all;\n",
       "}\n",
       "\n",
       ".xr-icon-database,\n",
       ".xr-icon-file-text2 {\n",
       "  display: inline-block;\n",
       "  vertical-align: middle;\n",
       "  width: 1em;\n",
       "  height: 1.5em !important;\n",
       "  stroke-width: 0;\n",
       "  stroke: currentColor;\n",
       "  fill: currentColor;\n",
       "}\n",
       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt;\n",
       "Dimensions:           (lat: 3, lon: 2, time: 253)\n",
       "Coordinates:\n",
       "  * lat               (lat) float64 24.5 25.5 26.5\n",
       "  * lon               (lon) float64 88.5 89.5\n",
       "  * time              (time) datetime64[ns] 2000-01-01 2000-02-01 ... 2021-01-01\n",
       "    spatial_ref       int64 0\n",
       "Data variables:\n",
       "    SWE_inst          (time, lat, lon) float32 0.0 0.0 nan 0.0 ... 0.0 0.0 nan\n",
       "    CanopInt_inst     (time, lat, lon) float32 0.01136 0.01191 ... 0.0009293 nan\n",
       "    TWS_inst          (time, lat, lon) float32 989.2 1.093e+03 ... 1.121e+03 nan\n",
       "    SoilMoist_P_inst  (time, lat, lon) float32 989.2 1.093e+03 ... 1.121e+03 nan\n",
       "Attributes: (12/19)\n",
       "    CDI:                    Climate Data Interface version 1.9.8 (https://mpi...\n",
       "    Conventions:            CF-1.6\n",
       "    history:                created on date: 2019-09-09T16:18:11.303\n",
       "    source:                 CLSM_F2.5 forced with GDAS-AGRMET-GPCPv13rA1\n",
       "    institution:            NASA GSFC\n",
       "    missing_value:          -9999.0\n",
       "    ...                     ...\n",
       "    MAP_PROJECTION:         EQUIDISTANT CYLINDRICAL\n",
       "    SOUTH_WEST_CORNER_LAT:  -59.5\n",
       "    SOUTH_WEST_CORNER_LON:  -179.5\n",
       "    DX:                     1.0\n",
       "    DY:                     1.0\n",
       "    CDO:                    Climate Data Operators version 1.9.8 (https://mpi...</pre><div class='xr-wrap' hidden><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-9b0906b2-4193-4217-b70d-36853dd72fa3' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-9b0906b2-4193-4217-b70d-36853dd72fa3' 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'>lat</span>: 3</li><li><span class='xr-has-index'>lon</span>: 2</li><li><span class='xr-has-index'>time</span>: 253</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-6eb982b8-1c30-4f56-851b-ff8601930393' class='xr-section-summary-in' type='checkbox'  checked><label for='section-6eb982b8-1c30-4f56-851b-ff8601930393' class='xr-section-summary' >Coordinates: <span>(4)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lat</span></div><div class='xr-var-dims'>(lat)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>24.5 25.5 26.5</div><input id='attrs-25ca2944-f808-433b-b694-84918bab6b08' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-25ca2944-f808-433b-b694-84918bab6b08' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-52a5e408-112f-406b-a50c-a66e07192d60' class='xr-var-data-in' type='checkbox'><label for='data-52a5e408-112f-406b-a50c-a66e07192d60' 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>latitude</dd><dt><span>long_name :</span></dt><dd>latitude</dd><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>axis :</span></dt><dd>Y</dd></dl></div><div class='xr-var-data'><pre>array([24.5, 25.5, 26.5])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lon</span></div><div class='xr-var-dims'>(lon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>88.5 89.5</div><input id='attrs-8bd823f2-b390-40e5-96ad-323e01a5f0c1' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-8bd823f2-b390-40e5-96ad-323e01a5f0c1' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-58f34d50-2e9d-4a55-9535-b0b3546aacb0' class='xr-var-data-in' type='checkbox'><label for='data-58f34d50-2e9d-4a55-9535-b0b3546aacb0' 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>longitude</dd><dt><span>long_name :</span></dt><dd>longitude</dd><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>axis :</span></dt><dd>X</dd></dl></div><div class='xr-var-data'><pre>array([88.5, 89.5])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2000-01-01 ... 2021-01-01</div><input id='attrs-61d6a345-7918-4756-9ce4-36344da77b24' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-61d6a345-7918-4756-9ce4-36344da77b24' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d596e02f-1151-45ab-9513-6576ba0c7960' class='xr-var-data-in' type='checkbox'><label for='data-d596e02f-1151-45ab-9513-6576ba0c7960' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>time</dd><dt><span>bounds :</span></dt><dd>time_bnds</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;2000-01-01T00:00:00.000000000&#x27;, &#x27;2000-02-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;2000-03-01T00:00:00.000000000&#x27;, ..., &#x27;2020-11-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;2020-12-01T00:00:00.000000000&#x27;, &#x27;2021-01-01T00:00:00.000000000&#x27;],\n",
       "      dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>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-dbaff158-d010-43d9-a6fd-772c9ce7f6db' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-dbaff158-d010-43d9-a6fd-772c9ce7f6db' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-fbc625dd-a62c-41aa-91cf-b0ff73e12695' class='xr-var-data-in' type='checkbox'><label for='data-fbc625dd-a62c-41aa-91cf-b0ff73e12695' 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>GEOGCS[&quot;WGS 84&quot;,DATUM[&quot;WGS_1984&quot;,SPHEROID[&quot;WGS 84&quot;,6378137,298.257223563,AUTHORITY[&quot;EPSG&quot;,&quot;7030&quot;]],AUTHORITY[&quot;EPSG&quot;,&quot;6326&quot;]],PRIMEM[&quot;Greenwich&quot;,0,AUTHORITY[&quot;EPSG&quot;,&quot;8901&quot;]],UNIT[&quot;degree&quot;,0.0174532925199433,AUTHORITY[&quot;EPSG&quot;,&quot;9122&quot;]],AXIS[&quot;Latitude&quot;,NORTH],AXIS[&quot;Longitude&quot;,EAST],AUTHORITY[&quot;EPSG&quot;,&quot;4326&quot;]]</dd><dt><span>semi_major_axis :</span></dt><dd>6378137.0</dd><dt><span>semi_minor_axis :</span></dt><dd>6356752.314245179</dd><dt><span>inverse_flattening :</span></dt><dd>298.257223563</dd><dt><span>reference_ellipsoid_name :</span></dt><dd>WGS 84</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>WGS 84</dd><dt><span>grid_mapping_name :</span></dt><dd>latitude_longitude</dd><dt><span>spatial_ref :</span></dt><dd>GEOGCS[&quot;WGS 84&quot;,DATUM[&quot;WGS_1984&quot;,SPHEROID[&quot;WGS 84&quot;,6378137,298.257223563,AUTHORITY[&quot;EPSG&quot;,&quot;7030&quot;]],AUTHORITY[&quot;EPSG&quot;,&quot;6326&quot;]],PRIMEM[&quot;Greenwich&quot;,0,AUTHORITY[&quot;EPSG&quot;,&quot;8901&quot;]],UNIT[&quot;degree&quot;,0.0174532925199433,AUTHORITY[&quot;EPSG&quot;,&quot;9122&quot;]],AXIS[&quot;Latitude&quot;,NORTH],AXIS[&quot;Longitude&quot;,EAST],AUTHORITY[&quot;EPSG&quot;,&quot;4326&quot;]]</dd><dt><span>GeoTransform :</span></dt><dd>88.0 1.0 0.0 24.0 0.0 1.0</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-d78fd0b2-4490-41c9-b5b1-cbf4adbdf2ff' class='xr-section-summary-in' type='checkbox'  checked><label for='section-d78fd0b2-4490-41c9-b5b1-cbf4adbdf2ff' class='xr-section-summary' >Data variables: <span>(4)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>SWE_inst</span></div><div class='xr-var-dims'>(time, lat, lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.0 0.0 nan 0.0 ... nan 0.0 0.0 nan</div><input id='attrs-92087dba-99be-48c1-b461-efe31efa787b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-92087dba-99be-48c1-b461-efe31efa787b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-97caa945-8eff-46ca-9f73-adfcf767a985' class='xr-var-data-in' type='checkbox'><label for='data-97caa945-8eff-46ca-9f73-adfcf767a985' 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>surface_snow_amount</dd><dt><span>long_name :</span></dt><dd>Snow depth water equivalent</dd><dt><span>units :</span></dt><dd>kg m-2</dd><dt><span>cell_methods :</span></dt><dd>time: mean</dd><dt><span>vmin :</span></dt><dd>0.0</dd><dt><span>vmax :</span></dt><dd>1811.7639</dd></dl></div><div class='xr-var-data'><pre>array([[[ 0.,  0.],\n",
       "        [nan,  0.],\n",
       "        [ 0., nan]],\n",
       "\n",
       "       [[ 0.,  0.],\n",
       "        [nan,  0.],\n",
       "        [ 0., nan]],\n",
       "\n",
       "       [[ 0.,  0.],\n",
       "        [nan,  0.],\n",
       "        [ 0., nan]],\n",
       "\n",
       "       ...,\n",
       "\n",
       "       [[ 0.,  0.],\n",
       "        [nan,  0.],\n",
       "        [ 0., nan]],\n",
       "\n",
       "       [[ 0.,  0.],\n",
       "        [nan,  0.],\n",
       "        [ 0., nan]],\n",
       "\n",
       "       [[ 0.,  0.],\n",
       "        [nan,  0.],\n",
       "        [ 0., nan]]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>CanopInt_inst</span></div><div class='xr-var-dims'>(time, lat, lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.01136 0.01191 ... 0.0009293 nan</div><input id='attrs-672421ed-6c7e-4ceb-a14b-03c210954237' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-672421ed-6c7e-4ceb-a14b-03c210954237' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-af49bca6-a709-46c7-9b8c-6585f0cb3f43' class='xr-var-data-in' type='checkbox'><label for='data-af49bca6-a709-46c7-9b8c-6585f0cb3f43' 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>canopy_water_amount</dd><dt><span>long_name :</span></dt><dd>Plant canopy surface water</dd><dt><span>units :</span></dt><dd>kg m-2</dd><dt><span>cell_methods :</span></dt><dd>time: mean</dd><dt><span>vmin :</span></dt><dd>0.0</dd><dt><span>vmax :</span></dt><dd>0.58855873</dd></dl></div><div class='xr-var-data'><pre>array([[[0.01136437, 0.01190688],\n",
       "        [       nan, 0.01260729],\n",
       "        [0.00756275,        nan]],\n",
       "\n",
       "       [[0.008875  , 0.01166379],\n",
       "        [       nan, 0.00538362],\n",
       "        [0.00494828,        nan]],\n",
       "\n",
       "       [[0.0046371 , 0.01433871],\n",
       "        [       nan, 0.00633468],\n",
       "        [0.00091532,        nan]],\n",
       "\n",
       "       ...,\n",
       "\n",
       "       [[0.00639961, 0.00991802],\n",
       "        [       nan, 0.01120315],\n",
       "        [0.01904065,        nan]],\n",
       "\n",
       "       [[0.00222062, 0.00155721],\n",
       "        [       nan, 0.00864407],\n",
       "        [0.00180623,        nan]],\n",
       "\n",
       "       [[0.00178485, 0.00189993],\n",
       "        [       nan, 0.00221678],\n",
       "        [0.00092932,        nan]]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>TWS_inst</span></div><div class='xr-var-dims'>(time, lat, lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>989.2 1.093e+03 ... 1.121e+03 nan</div><input id='attrs-35454b1d-e792-443c-8c20-cb4566ec7cc0' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-35454b1d-e792-443c-8c20-cb4566ec7cc0' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4be6b78c-343c-4601-81a3-dd84b84b256a' class='xr-var-data-in' type='checkbox'><label for='data-4be6b78c-343c-4601-81a3-dd84b84b256a' 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>terrestrial_water_storage</dd><dt><span>long_name :</span></dt><dd>Terrestrial water storage</dd><dt><span>units :</span></dt><dd>mm</dd><dt><span>cell_methods :</span></dt><dd>time: mean</dd><dt><span>vmin :</span></dt><dd>112.555756</dd><dt><span>vmax :</span></dt><dd>3941.7783</dd></dl></div><div class='xr-var-data'><pre>array([[[ 989.159  , 1093.0092 ],\n",
       "        [       nan, 1131.0294 ],\n",
       "        [1056.8068 ,        nan]],\n",
       "\n",
       "       [[ 926.07513, 1009.9631 ],\n",
       "        [       nan, 1046.4502 ],\n",
       "        [ 973.4028 ,        nan]],\n",
       "\n",
       "       [[ 828.48926,  888.4691 ],\n",
       "        [       nan,  918.96106],\n",
       "        [ 845.0135 ,        nan]],\n",
       "\n",
       "       ...,\n",
       "\n",
       "       [[1085.0808 , 1273.626  ],\n",
       "        [       nan, 1290.088  ],\n",
       "        [1269.27   ,        nan]],\n",
       "\n",
       "       [[ 986.1208 , 1177.6255 ],\n",
       "        [       nan, 1201.3169 ],\n",
       "        [1194.0941 ,        nan]],\n",
       "\n",
       "       [[ 902.49713, 1086.4757 ],\n",
       "        [       nan, 1118.3572 ],\n",
       "        [1120.676  ,        nan]]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>SoilMoist_P_inst</span></div><div class='xr-var-dims'>(time, lat, lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>989.2 1.093e+03 ... 1.121e+03 nan</div><input id='attrs-afba78ea-8a40-44b4-bd37-98d8147db3ec' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-afba78ea-8a40-44b4-bd37-98d8147db3ec' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3cf6eb63-d647-4fc6-9916-ae037e74e225' class='xr-var-data-in' type='checkbox'><label for='data-3cf6eb63-d647-4fc6-9916-ae037e74e225' 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>soil_moisture_content</dd><dt><span>long_name :</span></dt><dd>Profile Soil moisture</dd><dt><span>units :</span></dt><dd>kg m-2</dd><dt><span>cell_methods :</span></dt><dd>time: mean</dd><dt><span>vmin :</span></dt><dd>112.568245</dd><dt><span>vmax :</span></dt><dd>3941.6658</dd></dl></div><div class='xr-var-data'><pre>array([[[ 989.16327, 1092.9868 ],\n",
       "        [       nan, 1131.0664 ],\n",
       "        [1056.7959 ,        nan]],\n",
       "\n",
       "       [[ 926.04987, 1009.9538 ],\n",
       "        [       nan, 1046.4363 ],\n",
       "        [ 973.3716 ,        nan]],\n",
       "\n",
       "       [[ 828.48505,  888.45026],\n",
       "        [       nan,  918.9524 ],\n",
       "        [ 844.9844 ,        nan]],\n",
       "\n",
       "       ...,\n",
       "\n",
       "       [[1085.0743 , 1273.6161 ],\n",
       "        [       nan, 1290.0768 ],\n",
       "        [1269.2509 ,        nan]],\n",
       "\n",
       "       [[ 986.1186 , 1177.6239 ],\n",
       "        [       nan, 1201.3082 ],\n",
       "        [1194.0923 ,        nan]],\n",
       "\n",
       "       [[ 902.4953 , 1086.4739 ],\n",
       "        [       nan, 1118.3549 ],\n",
       "        [1120.675  ,        nan]]], dtype=float32)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-9879307b-bfde-4659-9feb-5bebe383ef68' class='xr-section-summary-in' type='checkbox'  ><label for='section-9879307b-bfde-4659-9feb-5bebe383ef68' class='xr-section-summary' >Attributes: <span>(19)</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 1.9.8 (https://mpimet.mpg.de/cdi)</dd><dt><span>Conventions :</span></dt><dd>CF-1.6</dd><dt><span>history :</span></dt><dd>created on date: 2019-09-09T16:18:11.303</dd><dt><span>source :</span></dt><dd>CLSM_F2.5 forced with GDAS-AGRMET-GPCPv13rA1</dd><dt><span>institution :</span></dt><dd>NASA GSFC</dd><dt><span>missing_value :</span></dt><dd>-9999.0</dd><dt><span>tavg definision: :</span></dt><dd>past 3-hour average</dd><dt><span>acc definision: :</span></dt><dd>past 3-hour accumulation</dd><dt><span>inst definision: :</span></dt><dd>instantaneous</dd><dt><span>title :</span></dt><dd>GLDAS2.1 LIS land surface model output monthly mean</dd><dt><span>references :</span></dt><dd>Rodell_etal_BAMS_2004, Kumar_etal_EMS_2006, Peters-Lidard_etal_ISSE_2007</dd><dt><span>conventions :</span></dt><dd>CF-1.6</dd><dt><span>comment :</span></dt><dd>website: https://ldas.gsfc.nasa.gov/gldas, https://lis.gsfc.nasa.gov/</dd><dt><span>MAP_PROJECTION :</span></dt><dd>EQUIDISTANT CYLINDRICAL</dd><dt><span>SOUTH_WEST_CORNER_LAT :</span></dt><dd>-59.5</dd><dt><span>SOUTH_WEST_CORNER_LON :</span></dt><dd>-179.5</dd><dt><span>DX :</span></dt><dd>1.0</dd><dt><span>DY :</span></dt><dd>1.0</dd><dt><span>CDO :</span></dt><dd>Climate Data Operators version 1.9.8 (https://mpimet.mpg.de/cdo)</dd></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.Dataset>\n",
       "Dimensions:           (lat: 3, lon: 2, time: 253)\n",
       "Coordinates:\n",
       "  * lat               (lat) float64 24.5 25.5 26.5\n",
       "  * lon               (lon) float64 88.5 89.5\n",
       "  * time              (time) datetime64[ns] 2000-01-01 2000-02-01 ... 2021-01-01\n",
       "    spatial_ref       int64 0\n",
       "Data variables:\n",
       "    SWE_inst          (time, lat, lon) float32 0.0 0.0 nan 0.0 ... 0.0 0.0 nan\n",
       "    CanopInt_inst     (time, lat, lon) float32 0.01136 0.01191 ... 0.0009293 nan\n",
       "    TWS_inst          (time, lat, lon) float32 989.2 1.093e+03 ... 1.121e+03 nan\n",
       "    SoilMoist_P_inst  (time, lat, lon) float32 989.2 1.093e+03 ... 1.121e+03 nan\n",
       "Attributes: (12/19)\n",
       "    CDI:                    Climate Data Interface version 1.9.8 (https://mpi...\n",
       "    Conventions:            CF-1.6\n",
       "    history:                created on date: 2019-09-09T16:18:11.303\n",
       "    source:                 CLSM_F2.5 forced with GDAS-AGRMET-GPCPv13rA1\n",
       "    institution:            NASA GSFC\n",
       "    missing_value:          -9999.0\n",
       "    ...                     ...\n",
       "    MAP_PROJECTION:         EQUIDISTANT CYLINDRICAL\n",
       "    SOUTH_WEST_CORNER_LAT:  -59.5\n",
       "    SOUTH_WEST_CORNER_LON:  -179.5\n",
       "    DX:                     1.0\n",
       "    DY:                     1.0\n",
       "    CDO:                    Climate Data Operators version 1.9.8 (https://mpi..."
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "gldas_clsm_ds"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "d737c8a2-3bbb-4db3-bd4a-19b62a1c5b01",
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       ".xr-attrs dt:hover span {\n",
       "  display: inline-block;\n",
       "  background: var(--xr-background-color);\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-attrs dd {\n",
       "  grid-column: 2;\n",
       "  white-space: pre-wrap;\n",
       "  word-break: break-all;\n",
       "}\n",
       "\n",
       ".xr-icon-database,\n",
       ".xr-icon-file-text2 {\n",
       "  display: inline-block;\n",
       "  vertical-align: middle;\n",
       "  width: 1em;\n",
       "  height: 1.5em !important;\n",
       "  stroke-width: 0;\n",
       "  stroke: currentColor;\n",
       "  fill: currentColor;\n",
       "}\n",
       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt;\n",
       "Dimensions:                (lat: 3, lon: 2, time: 253)\n",
       "Coordinates:\n",
       "  * lat                    (lat) float64 24.5 25.5 26.5\n",
       "  * lon                    (lon) float64 88.5 89.5\n",
       "  * time                   (time) datetime64[ns] 2000-01-01 ... 2021-01-01\n",
       "    spatial_ref            int64 0\n",
       "Data variables:\n",
       "    SWE_inst               (time, lat, lon) float32 0.0 0.0 nan ... 0.0 0.0 nan\n",
       "    CanopInt_inst          (time, lat, lon) float32 0.01098 0.01813 ... nan\n",
       "    SoilMoi0_10cm_inst     (time, lat, lon) float32 20.06 21.51 ... 19.49 nan\n",
       "    SoilMoi10_40cm_inst    (time, lat, lon) float32 66.19 69.25 nan ... 63.1 nan\n",
       "    SoilMoi40_100cm_inst   (time, lat, lon) float32 145.5 151.0 ... 138.1 nan\n",
       "    SoilMoi100_200cm_inst  (time, lat, lon) float32 273.2 279.0 ... 262.4 nan\n",
       "Attributes: (12/19)\n",
       "    CDI:                    Climate Data Interface version 1.9.8 (https://mpi...\n",
       "    Conventions:            CF-1.6\n",
       "    history:                created on date: 2019-09-09T16:06:53.375\n",
       "    source:                 Noah_v3.6 forced with GDAS-AGRMET-GPCPv13rA1\n",
       "    institution:            NASA GSFC\n",
       "    missing_value:          -9999.0\n",
       "    ...                     ...\n",
       "    MAP_PROJECTION:         EQUIDISTANT CYLINDRICAL\n",
       "    SOUTH_WEST_CORNER_LAT:  -59.5\n",
       "    SOUTH_WEST_CORNER_LON:  -179.5\n",
       "    DX:                     1.0\n",
       "    DY:                     1.0\n",
       "    CDO:                    Climate Data Operators version 1.9.8 (https://mpi...</pre><div class='xr-wrap' hidden><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-0477125d-73c2-4c2e-b052-38e46affb8f9' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-0477125d-73c2-4c2e-b052-38e46affb8f9' 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'>lat</span>: 3</li><li><span class='xr-has-index'>lon</span>: 2</li><li><span class='xr-has-index'>time</span>: 253</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-9a40133f-0b89-49cb-b283-a9ac7af12e73' class='xr-section-summary-in' type='checkbox'  checked><label for='section-9a40133f-0b89-49cb-b283-a9ac7af12e73' class='xr-section-summary' >Coordinates: <span>(4)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lat</span></div><div class='xr-var-dims'>(lat)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>24.5 25.5 26.5</div><input id='attrs-736a9be1-02ff-4c12-95bf-242dbf571767' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-736a9be1-02ff-4c12-95bf-242dbf571767' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-77cef7d2-a176-4811-bdc3-f8904a19dc93' class='xr-var-data-in' type='checkbox'><label for='data-77cef7d2-a176-4811-bdc3-f8904a19dc93' 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>latitude</dd><dt><span>long_name :</span></dt><dd>latitude</dd><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>axis :</span></dt><dd>Y</dd></dl></div><div class='xr-var-data'><pre>array([24.5, 25.5, 26.5])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lon</span></div><div class='xr-var-dims'>(lon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>88.5 89.5</div><input id='attrs-3f8c0d33-5dea-4405-b28c-eab84b51ec11' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3f8c0d33-5dea-4405-b28c-eab84b51ec11' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e9ec5032-6eb7-4346-9058-839d01310047' class='xr-var-data-in' type='checkbox'><label for='data-e9ec5032-6eb7-4346-9058-839d01310047' 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>longitude</dd><dt><span>long_name :</span></dt><dd>longitude</dd><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>axis :</span></dt><dd>X</dd></dl></div><div class='xr-var-data'><pre>array([88.5, 89.5])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2000-01-01 ... 2021-01-01</div><input id='attrs-b9606af2-fb80-4a85-83ac-a0858ea7f9b0' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b9606af2-fb80-4a85-83ac-a0858ea7f9b0' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0754fdec-f8d2-453d-900d-258deb661d03' class='xr-var-data-in' type='checkbox'><label for='data-0754fdec-f8d2-453d-900d-258deb661d03' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>time</dd><dt><span>bounds :</span></dt><dd>time_bnds</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;2000-01-01T00:00:00.000000000&#x27;, &#x27;2000-02-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;2000-03-01T00:00:00.000000000&#x27;, ..., &#x27;2020-11-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;2020-12-01T00:00:00.000000000&#x27;, &#x27;2021-01-01T00:00:00.000000000&#x27;],\n",
       "      dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>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-cc20be18-dfea-46fe-ad00-0f4ed93406af' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-cc20be18-dfea-46fe-ad00-0f4ed93406af' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9ce0fa08-8d0e-4d3d-a395-cfcb19701fe7' class='xr-var-data-in' type='checkbox'><label for='data-9ce0fa08-8d0e-4d3d-a395-cfcb19701fe7' 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>GEOGCS[&quot;WGS 84&quot;,DATUM[&quot;WGS_1984&quot;,SPHEROID[&quot;WGS 84&quot;,6378137,298.257223563,AUTHORITY[&quot;EPSG&quot;,&quot;7030&quot;]],AUTHORITY[&quot;EPSG&quot;,&quot;6326&quot;]],PRIMEM[&quot;Greenwich&quot;,0,AUTHORITY[&quot;EPSG&quot;,&quot;8901&quot;]],UNIT[&quot;degree&quot;,0.0174532925199433,AUTHORITY[&quot;EPSG&quot;,&quot;9122&quot;]],AXIS[&quot;Latitude&quot;,NORTH],AXIS[&quot;Longitude&quot;,EAST],AUTHORITY[&quot;EPSG&quot;,&quot;4326&quot;]]</dd><dt><span>semi_major_axis :</span></dt><dd>6378137.0</dd><dt><span>semi_minor_axis :</span></dt><dd>6356752.314245179</dd><dt><span>inverse_flattening :</span></dt><dd>298.257223563</dd><dt><span>reference_ellipsoid_name :</span></dt><dd>WGS 84</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>WGS 84</dd><dt><span>grid_mapping_name :</span></dt><dd>latitude_longitude</dd><dt><span>spatial_ref :</span></dt><dd>GEOGCS[&quot;WGS 84&quot;,DATUM[&quot;WGS_1984&quot;,SPHEROID[&quot;WGS 84&quot;,6378137,298.257223563,AUTHORITY[&quot;EPSG&quot;,&quot;7030&quot;]],AUTHORITY[&quot;EPSG&quot;,&quot;6326&quot;]],PRIMEM[&quot;Greenwich&quot;,0,AUTHORITY[&quot;EPSG&quot;,&quot;8901&quot;]],UNIT[&quot;degree&quot;,0.0174532925199433,AUTHORITY[&quot;EPSG&quot;,&quot;9122&quot;]],AXIS[&quot;Latitude&quot;,NORTH],AXIS[&quot;Longitude&quot;,EAST],AUTHORITY[&quot;EPSG&quot;,&quot;4326&quot;]]</dd><dt><span>GeoTransform :</span></dt><dd>88.0 1.0 0.0 24.0 0.0 1.0</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-88253581-6355-4929-8512-979c37b2b863' class='xr-section-summary-in' type='checkbox'  checked><label for='section-88253581-6355-4929-8512-979c37b2b863' class='xr-section-summary' >Data variables: <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>SWE_inst</span></div><div class='xr-var-dims'>(time, lat, lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.0 0.0 nan 0.0 ... nan 0.0 0.0 nan</div><input id='attrs-7ba16765-4da3-4713-9bf9-cac85c01d9ef' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-7ba16765-4da3-4713-9bf9-cac85c01d9ef' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-fde04941-16cb-485c-9764-df3b94c1d4fd' class='xr-var-data-in' type='checkbox'><label for='data-fde04941-16cb-485c-9764-df3b94c1d4fd' 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>surface_snow_amount</dd><dt><span>long_name :</span></dt><dd>Snow depth water equivalent</dd><dt><span>units :</span></dt><dd>kg m-2</dd><dt><span>cell_methods :</span></dt><dd>time: mean</dd><dt><span>vmin :</span></dt><dd>0.0</dd><dt><span>vmax :</span></dt><dd>76323.02</dd></dl></div><div class='xr-var-data'><pre>array([[[0.        , 0.        ],\n",
       "        [       nan, 0.        ],\n",
       "        [0.00020243,        nan]],\n",
       "\n",
       "       [[0.        , 0.        ],\n",
       "        [       nan, 0.        ],\n",
       "        [0.        ,        nan]],\n",
       "\n",
       "       [[0.        , 0.        ],\n",
       "        [       nan, 0.        ],\n",
       "        [0.        ,        nan]],\n",
       "\n",
       "       ...,\n",
       "\n",
       "       [[0.        , 0.        ],\n",
       "        [       nan, 0.        ],\n",
       "        [0.        ,        nan]],\n",
       "\n",
       "       [[0.        , 0.        ],\n",
       "        [       nan, 0.        ],\n",
       "        [0.        ,        nan]],\n",
       "\n",
       "       [[0.        , 0.        ],\n",
       "        [       nan, 0.        ],\n",
       "        [0.        ,        nan]]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>CanopInt_inst</span></div><div class='xr-var-dims'>(time, lat, lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.01098 0.01813 ... 0.002044 nan</div><input id='attrs-5cf867a9-b7b4-42f8-b5e9-8ef5f76a466f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-5cf867a9-b7b4-42f8-b5e9-8ef5f76a466f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-db0bb2ef-8bb8-41f6-ad2f-2ea03e603c08' class='xr-var-data-in' type='checkbox'><label for='data-db0bb2ef-8bb8-41f6-ad2f-2ea03e603c08' 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>canopy_water_amount</dd><dt><span>long_name :</span></dt><dd>Plant canopy surface water</dd><dt><span>units :</span></dt><dd>kg m-2</dd><dt><span>cell_methods :</span></dt><dd>time: mean</dd><dt><span>vmin :</span></dt><dd>0.0</dd><dt><span>vmax :</span></dt><dd>0.5</dd></dl></div><div class='xr-var-data'><pre>array([[[0.01097976, 0.0181336 ],\n",
       "        [       nan, 0.00817814],\n",
       "        [0.00451012,        nan]],\n",
       "\n",
       "       [[0.05575431, 0.04634483],\n",
       "        [       nan, 0.05291379],\n",
       "        [0.02784052,        nan]],\n",
       "\n",
       "       [[0.01528226, 0.04850806],\n",
       "        [       nan, 0.03809274],\n",
       "        [0.00517742,        nan]],\n",
       "\n",
       "       ...,\n",
       "\n",
       "       [[0.00351667, 0.016925  ],\n",
       "        [       nan, 0.01774583],\n",
       "        [0.031975  ,        nan]],\n",
       "\n",
       "       [[0.00132661, 0.00029032],\n",
       "        [       nan, 0.00900403],\n",
       "        [0.00327823,        nan]],\n",
       "\n",
       "       [[0.00440726, 0.009375  ],\n",
       "        [       nan, 0.00177419],\n",
       "        [0.00204435,        nan]]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>SoilMoi0_10cm_inst</span></div><div class='xr-var-dims'>(time, lat, lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>20.06 21.51 nan ... 20.44 19.49 nan</div><input id='attrs-85a01a75-1ced-46ff-9421-b2343dd28cdc' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-85a01a75-1ced-46ff-9421-b2343dd28cdc' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-40019b0e-2cf8-48d9-9290-5e7cb2b216b0' class='xr-var-data-in' type='checkbox'><label for='data-40019b0e-2cf8-48d9-9290-5e7cb2b216b0' 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>soil_moisture_content</dd><dt><span>long_name :</span></dt><dd>Soil moisture</dd><dt><span>units :</span></dt><dd>kg m-2</dd><dt><span>cell_methods :</span></dt><dd>time: mean</dd><dt><span>vmin :</span></dt><dd>2.0053928</dd><dt><span>vmax :</span></dt><dd>100.0</dd></dl></div><div class='xr-var-data'><pre>array([[[20.062988 , 21.511745 ],\n",
       "        [       nan, 22.152946 ],\n",
       "        [19.328405 ,        nan]],\n",
       "\n",
       "       [[22.05861  , 21.94084  ],\n",
       "        [       nan, 21.647528 ],\n",
       "        [18.453396 ,        nan]],\n",
       "\n",
       "       [[16.121552 , 18.716549 ],\n",
       "        [       nan, 18.245186 ],\n",
       "        [12.7413025,        nan]],\n",
       "\n",
       "       ...,\n",
       "\n",
       "       [[24.9506   , 27.142637 ],\n",
       "        [       nan, 26.533934 ],\n",
       "        [26.037996 ,        nan]],\n",
       "\n",
       "       [[20.837887 , 23.677572 ],\n",
       "        [       nan, 23.564484 ],\n",
       "        [22.7615   ,        nan]],\n",
       "\n",
       "       [[17.11708  , 20.26438  ],\n",
       "        [       nan, 20.443222 ],\n",
       "        [19.48617  ,        nan]]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>SoilMoi10_40cm_inst</span></div><div class='xr-var-dims'>(time, lat, lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>66.19 69.25 nan ... 66.94 63.1 nan</div><input id='attrs-6c1a1193-50a2-4bdb-92b6-1a9849ca8c2a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-6c1a1193-50a2-4bdb-92b6-1a9849ca8c2a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-224e32a3-0222-4c71-ad66-721226269a1e' class='xr-var-data-in' type='checkbox'><label for='data-224e32a3-0222-4c71-ad66-721226269a1e' 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>soil_moisture_content</dd><dt><span>long_name :</span></dt><dd>Soil moisture</dd><dt><span>units :</span></dt><dd>kg m-2</dd><dt><span>cell_methods :</span></dt><dd>time: mean</dd><dt><span>vmin :</span></dt><dd>6.2155223</dd><dt><span>vmax :</span></dt><dd>300.00003</dd></dl></div><div class='xr-var-data'><pre>array([[[66.187355, 69.25441 ],\n",
       "        [      nan, 71.23046 ],\n",
       "        [64.35099 ,       nan]],\n",
       "\n",
       "       [[67.84036 , 69.15632 ],\n",
       "        [      nan, 70.67176 ],\n",
       "        [62.03372 ,       nan]],\n",
       "\n",
       "       [[55.793095, 57.588135],\n",
       "        [      nan, 61.073086],\n",
       "        [53.15815 ,       nan]],\n",
       "\n",
       "       ...,\n",
       "\n",
       "       [[77.940254, 83.69386 ],\n",
       "        [      nan, 81.59317 ],\n",
       "        [79.68518 ,       nan]],\n",
       "\n",
       "       [[68.19532 , 74.38464 ],\n",
       "        [      nan, 73.442665],\n",
       "        [70.86736 ,       nan]],\n",
       "\n",
       "       [[61.1337  , 66.40489 ],\n",
       "        [      nan, 66.9394  ],\n",
       "        [63.098713,       nan]]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>SoilMoi40_100cm_inst</span></div><div class='xr-var-dims'>(time, lat, lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>145.5 151.0 nan ... 146.0 138.1 nan</div><input id='attrs-914f2cf4-2cbe-4c57-8b3b-2bf9407b25c4' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-914f2cf4-2cbe-4c57-8b3b-2bf9407b25c4' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-cf63dcd1-6bd9-4370-8f35-76b44b1acabb' class='xr-var-data-in' type='checkbox'><label for='data-cf63dcd1-6bd9-4370-8f35-76b44b1acabb' 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>soil_moisture_content</dd><dt><span>long_name :</span></dt><dd>Soil moisture</dd><dt><span>units :</span></dt><dd>kg m-2</dd><dt><span>cell_methods :</span></dt><dd>time: mean</dd><dt><span>vmin :</span></dt><dd>12.000621</dd><dt><span>vmax :</span></dt><dd>600.00006</dd></dl></div><div class='xr-var-data'><pre>array([[[145.53212 , 150.99332 ],\n",
       "        [       nan, 154.96133 ],\n",
       "        [142.15863 ,        nan]],\n",
       "\n",
       "       [[138.4543  , 143.71329 ],\n",
       "        [       nan, 147.92259 ],\n",
       "        [131.5945  ,        nan]],\n",
       "\n",
       "       [[120.01031 , 120.36397 ],\n",
       "        [       nan, 132.47821 ],\n",
       "        [116.386246,        nan]],\n",
       "\n",
       "       ...,\n",
       "\n",
       "       [[166.61328 , 176.42297 ],\n",
       "        [       nan, 171.83383 ],\n",
       "        [167.10345 ,        nan]],\n",
       "\n",
       "       [[149.63658 , 159.01703 ],\n",
       "        [       nan, 156.22787 ],\n",
       "        [150.7247  ,        nan]],\n",
       "\n",
       "       [[136.1801  , 145.71231 ],\n",
       "        [       nan, 145.97069 ],\n",
       "        [138.14584 ,        nan]]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>SoilMoi100_200cm_inst</span></div><div class='xr-var-dims'>(time, lat, lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>273.2 279.0 nan ... 267.6 262.4 nan</div><input id='attrs-c7284a9b-2e90-4828-92ed-c7e4c7b53ba3' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-c7284a9b-2e90-4828-92ed-c7e4c7b53ba3' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ec2b59f6-797c-4655-863a-4c15a29dc613' class='xr-var-data-in' type='checkbox'><label for='data-ec2b59f6-797c-4655-863a-4c15a29dc613' 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>soil_moisture_content</dd><dt><span>long_name :</span></dt><dd>Soil moisture</dd><dt><span>units :</span></dt><dd>kg m-2</dd><dt><span>cell_methods :</span></dt><dd>time: mean</dd><dt><span>vmin :</span></dt><dd>21.051027</dd><dt><span>vmax :</span></dt><dd>999.99994</dd></dl></div><div class='xr-var-data'><pre>array([[[273.22125, 278.95093],\n",
       "        [      nan, 283.21298],\n",
       "        [269.44833,       nan]],\n",
       "\n",
       "       [[258.88895, 263.5894 ],\n",
       "        [      nan, 267.545  ],\n",
       "        [256.05154,       nan]],\n",
       "\n",
       "       [[249.2451 , 253.0533 ],\n",
       "        [      nan, 255.9859 ],\n",
       "        [247.16219,       nan]],\n",
       "\n",
       "       ...,\n",
       "\n",
       "       [[307.68387, 321.46054],\n",
       "        [      nan, 314.7429 ],\n",
       "        [306.83295,       nan]],\n",
       "\n",
       "       [[278.7669 , 289.47925],\n",
       "        [      nan, 284.58356],\n",
       "        [279.3263 ,       nan]],\n",
       "\n",
       "       [[261.93777, 270.1148 ],\n",
       "        [      nan, 267.55893],\n",
       "        [262.42688,       nan]]], dtype=float32)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-06e30ee3-5317-413b-a675-03d9eeab2721' class='xr-section-summary-in' type='checkbox'  ><label for='section-06e30ee3-5317-413b-a675-03d9eeab2721' class='xr-section-summary' >Attributes: <span>(19)</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 1.9.8 (https://mpimet.mpg.de/cdi)</dd><dt><span>Conventions :</span></dt><dd>CF-1.6</dd><dt><span>history :</span></dt><dd>created on date: 2019-09-09T16:06:53.375</dd><dt><span>source :</span></dt><dd>Noah_v3.6 forced with GDAS-AGRMET-GPCPv13rA1</dd><dt><span>institution :</span></dt><dd>NASA GSFC</dd><dt><span>missing_value :</span></dt><dd>-9999.0</dd><dt><span>tavg definision: :</span></dt><dd>past 3-hour average</dd><dt><span>acc definision: :</span></dt><dd>past 3-hour accumulation</dd><dt><span>inst definision: :</span></dt><dd>instantaneous</dd><dt><span>title :</span></dt><dd>GLDAS2.1 LIS land surface model output monthly mean</dd><dt><span>references :</span></dt><dd>Rodell_etal_BAMS_2004, Kumar_etal_EMS_2006, Peters-Lidard_etal_ISSE_2007</dd><dt><span>conventions :</span></dt><dd>CF-1.6</dd><dt><span>comment :</span></dt><dd>website: https://ldas.gsfc.nasa.gov/gldas, https://lis.gsfc.nasa.gov/</dd><dt><span>MAP_PROJECTION :</span></dt><dd>EQUIDISTANT CYLINDRICAL</dd><dt><span>SOUTH_WEST_CORNER_LAT :</span></dt><dd>-59.5</dd><dt><span>SOUTH_WEST_CORNER_LON :</span></dt><dd>-179.5</dd><dt><span>DX :</span></dt><dd>1.0</dd><dt><span>DY :</span></dt><dd>1.0</dd><dt><span>CDO :</span></dt><dd>Climate Data Operators version 1.9.8 (https://mpimet.mpg.de/cdo)</dd></dl></div></li></ul></div></div>"
      ],
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       "<xarray.Dataset>\n",
       "Dimensions:                (lat: 3, lon: 2, time: 253)\n",
       "Coordinates:\n",
       "  * lat                    (lat) float64 24.5 25.5 26.5\n",
       "  * lon                    (lon) float64 88.5 89.5\n",
       "  * time                   (time) datetime64[ns] 2000-01-01 ... 2021-01-01\n",
       "    spatial_ref            int64 0\n",
       "Data variables:\n",
       "    SWE_inst               (time, lat, lon) float32 0.0 0.0 nan ... 0.0 0.0 nan\n",
       "    CanopInt_inst          (time, lat, lon) float32 0.01098 0.01813 ... nan\n",
       "    SoilMoi0_10cm_inst     (time, lat, lon) float32 20.06 21.51 ... 19.49 nan\n",
       "    SoilMoi10_40cm_inst    (time, lat, lon) float32 66.19 69.25 nan ... 63.1 nan\n",
       "    SoilMoi40_100cm_inst   (time, lat, lon) float32 145.5 151.0 ... 138.1 nan\n",
       "    SoilMoi100_200cm_inst  (time, lat, lon) float32 273.2 279.0 ... 262.4 nan\n",
       "Attributes: (12/19)\n",
       "    CDI:                    Climate Data Interface version 1.9.8 (https://mpi...\n",
       "    Conventions:            CF-1.6\n",
       "    history:                created on date: 2019-09-09T16:06:53.375\n",
       "    source:                 Noah_v3.6 forced with GDAS-AGRMET-GPCPv13rA1\n",
       "    institution:            NASA GSFC\n",
       "    missing_value:          -9999.0\n",
       "    ...                     ...\n",
       "    MAP_PROJECTION:         EQUIDISTANT CYLINDRICAL\n",
       "    SOUTH_WEST_CORNER_LAT:  -59.5\n",
       "    SOUTH_WEST_CORNER_LON:  -179.5\n",
       "    DX:                     1.0\n",
       "    DY:                     1.0\n",
       "    CDO:                    Climate Data Operators version 1.9.8 (https://mpi..."
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "gldas_noah_ds"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "2af92588-1020-4055-b472-6dfd560fc26a",
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       "  font-weight: normal;\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-attrs dt:hover span {\n",
       "  display: inline-block;\n",
       "  background: var(--xr-background-color);\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-attrs dd {\n",
       "  grid-column: 2;\n",
       "  white-space: pre-wrap;\n",
       "  word-break: break-all;\n",
       "}\n",
       "\n",
       ".xr-icon-database,\n",
       ".xr-icon-file-text2 {\n",
       "  display: inline-block;\n",
       "  vertical-align: middle;\n",
       "  width: 1em;\n",
       "  height: 1.5em !important;\n",
       "  stroke-width: 0;\n",
       "  stroke: currentColor;\n",
       "  fill: currentColor;\n",
       "}\n",
       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.DataArray (lat: 3, lon: 2)&gt;\n",
       "array([[1.12510448e+10, 1.12510448e+10],\n",
       "       [1.11598458e+10, 1.11598458e+10],\n",
       "       [1.10652474e+10, 1.10652474e+10]])\n",
       "Coordinates:\n",
       "  * lat          (lat) float64 24.5 25.5 26.5\n",
       "    spatial_ref  int64 0\n",
       "  * lon          (lon) float64 88.5 89.5</pre><div class='xr-wrap' hidden><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'></div><ul class='xr-dim-list'><li><span class='xr-has-index'>lat</span>: 3</li><li><span class='xr-has-index'>lon</span>: 2</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-ce764b8b-3973-47c6-afa2-493b897a5c1f' class='xr-array-in' type='checkbox' checked><label for='section-ce764b8b-3973-47c6-afa2-493b897a5c1f' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>1.125e+10 1.125e+10 1.116e+10 1.116e+10 1.107e+10 1.107e+10</span></div><div class='xr-array-data'><pre>array([[1.12510448e+10, 1.12510448e+10],\n",
       "       [1.11598458e+10, 1.11598458e+10],\n",
       "       [1.10652474e+10, 1.10652474e+10]])</pre></div></div></li><li class='xr-section-item'><input id='section-b25acd55-f7cd-467a-a722-5dba89b49685' class='xr-section-summary-in' type='checkbox'  checked><label for='section-b25acd55-f7cd-467a-a722-5dba89b49685' class='xr-section-summary' >Coordinates: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lat</span></div><div class='xr-var-dims'>(lat)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>24.5 25.5 26.5</div><input id='attrs-5a5c92ae-ac66-434e-acd5-2e1704b53427' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-5a5c92ae-ac66-434e-acd5-2e1704b53427' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-dcec1681-c49f-40d1-97ae-dbd6a713df5f' class='xr-var-data-in' type='checkbox'><label for='data-dcec1681-c49f-40d1-97ae-dbd6a713df5f' 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>latitude</dd><dt><span>long_name :</span></dt><dd>latitude</dd><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>axis :</span></dt><dd>Y</dd></dl></div><div class='xr-var-data'><pre>array([24.5, 25.5, 26.5])</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-b299bd76-2b66-4586-aa74-8a10f173e756' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b299bd76-2b66-4586-aa74-8a10f173e756' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-50932f5e-14f9-4f6d-9ca2-6f1ad3aab94b' class='xr-var-data-in' type='checkbox'><label for='data-50932f5e-14f9-4f6d-9ca2-6f1ad3aab94b' 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>GEOGCS[&quot;WGS 84&quot;,DATUM[&quot;WGS_1984&quot;,SPHEROID[&quot;WGS 84&quot;,6378137,298.257223563,AUTHORITY[&quot;EPSG&quot;,&quot;7030&quot;]],AUTHORITY[&quot;EPSG&quot;,&quot;6326&quot;]],PRIMEM[&quot;Greenwich&quot;,0,AUTHORITY[&quot;EPSG&quot;,&quot;8901&quot;]],UNIT[&quot;degree&quot;,0.0174532925199433,AUTHORITY[&quot;EPSG&quot;,&quot;9122&quot;]],AXIS[&quot;Latitude&quot;,NORTH],AXIS[&quot;Longitude&quot;,EAST],AUTHORITY[&quot;EPSG&quot;,&quot;4326&quot;]]</dd><dt><span>semi_major_axis :</span></dt><dd>6378137.0</dd><dt><span>semi_minor_axis :</span></dt><dd>6356752.314245179</dd><dt><span>inverse_flattening :</span></dt><dd>298.257223563</dd><dt><span>reference_ellipsoid_name :</span></dt><dd>WGS 84</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>WGS 84</dd><dt><span>grid_mapping_name :</span></dt><dd>latitude_longitude</dd><dt><span>spatial_ref :</span></dt><dd>GEOGCS[&quot;WGS 84&quot;,DATUM[&quot;WGS_1984&quot;,SPHEROID[&quot;WGS 84&quot;,6378137,298.257223563,AUTHORITY[&quot;EPSG&quot;,&quot;7030&quot;]],AUTHORITY[&quot;EPSG&quot;,&quot;6326&quot;]],PRIMEM[&quot;Greenwich&quot;,0,AUTHORITY[&quot;EPSG&quot;,&quot;8901&quot;]],UNIT[&quot;degree&quot;,0.0174532925199433,AUTHORITY[&quot;EPSG&quot;,&quot;9122&quot;]],AXIS[&quot;Latitude&quot;,NORTH],AXIS[&quot;Longitude&quot;,EAST],AUTHORITY[&quot;EPSG&quot;,&quot;4326&quot;]]</dd><dt><span>GeoTransform :</span></dt><dd>88.0 1.0 0.0 24.0 0.0 1.0</dd></dl></div><div class='xr-var-data'><pre>array(0)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lon</span></div><div class='xr-var-dims'>(lon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>88.5 89.5</div><input id='attrs-17ba890d-b0e5-479a-a738-75ae05b94071' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-17ba890d-b0e5-479a-a738-75ae05b94071' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-baea16da-7f9f-4dfd-a245-ecae618d332c' class='xr-var-data-in' type='checkbox'><label for='data-baea16da-7f9f-4dfd-a245-ecae618d332c' 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>longitude</dd><dt><span>long_name :</span></dt><dd>longitude</dd><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>axis :</span></dt><dd>X</dd></dl></div><div class='xr-var-data'><pre>array([88.5, 89.5])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-e86b9a94-fb31-4bde-a764-1397f49f0409' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-e86b9a94-fb31-4bde-a764-1397f49f0409' class='xr-section-summary'  title='Expand/collapse section'>Attributes: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.DataArray (lat: 3, lon: 2)>\n",
       "array([[1.12510448e+10, 1.12510448e+10],\n",
       "       [1.11598458e+10, 1.11598458e+10],\n",
       "       [1.10652474e+10, 1.10652474e+10]])\n",
       "Coordinates:\n",
       "  * lat          (lat) float64 24.5 25.5 26.5\n",
       "    spatial_ref  int64 0\n",
       "  * lon          (lon) float64 88.5 89.5"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# GLDAS Grid Cell Area\n",
    "areas = calculate_surface_area(gldas_clsm_ds)\n",
    "\n",
    "surface_area_da = (xr.DataArray(areas, dims=['lat'],\n",
    "                                coords={'lat': gldas_clsm_ds.lat})\n",
    "                   .expand_dims(lon=len(gldas_clsm_ds.coords['lon']))\n",
    "                   .assign_coords(lon=gldas_clsm_ds.lon)\n",
    "                   .transpose('lat', 'lon')\n",
    "#                    .drop('spatial_ref')\n",
    "                  )\n",
    "surface_area_da"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "716fecfa-0d0e-41d2-a3f2-bb6a1ffa402e",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Calculate Anomalies for each model\n",
    "gldas_clsm_anomalies = calculate_gldas_anomalies(gldas_clsm_ds, surface_area_da)\n",
    "gldas_noah_anomalies = calculate_gldas_anomalies(gldas_noah_ds, surface_area_da)\n",
    "gldas_vic_anomalies = calculate_gldas_anomalies(gldas_vic_ds, surface_area_da)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "c110e988-93d9-404b-9f33-f4421299b183",
   "metadata": {},
   "outputs": [
    {
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       "  text-overflow: ellipsis;\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-var-name:hover,\n",
       ".xr-var-dims:hover,\n",
       ".xr-var-dtype:hover,\n",
       ".xr-attrs dt:hover {\n",
       "  overflow: visible;\n",
       "  width: auto;\n",
       "  z-index: 1;\n",
       "}\n",
       "\n",
       ".xr-var-attrs,\n",
       ".xr-var-data {\n",
       "  display: none;\n",
       "  background-color: var(--xr-background-color) !important;\n",
       "  padding-bottom: 5px !important;\n",
       "}\n",
       "\n",
       ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
       ".xr-var-data-in:checked ~ .xr-var-data {\n",
       "  display: block;\n",
       "}\n",
       "\n",
       ".xr-var-data > table {\n",
       "  float: right;\n",
       "}\n",
       "\n",
       ".xr-var-name span,\n",
       ".xr-var-data,\n",
       ".xr-attrs {\n",
       "  padding-left: 25px !important;\n",
       "}\n",
       "\n",
       ".xr-attrs,\n",
       ".xr-var-attrs,\n",
       ".xr-var-data {\n",
       "  grid-column: 1 / -1;\n",
       "}\n",
       "\n",
       "dl.xr-attrs {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  display: grid;\n",
       "  grid-template-columns: 125px auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt,\n",
       ".xr-attrs dd {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  float: left;\n",
       "  padding-right: 10px;\n",
       "  width: auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt {\n",
       "  font-weight: normal;\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-attrs dt:hover span {\n",
       "  display: inline-block;\n",
       "  background: var(--xr-background-color);\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-attrs dd {\n",
       "  grid-column: 2;\n",
       "  white-space: pre-wrap;\n",
       "  word-break: break-all;\n",
       "}\n",
       "\n",
       ".xr-icon-database,\n",
       ".xr-icon-file-text2 {\n",
       "  display: inline-block;\n",
       "  vertical-align: middle;\n",
       "  width: 1em;\n",
       "  height: 1.5em !important;\n",
       "  stroke-width: 0;\n",
       "  stroke: currentColor;\n",
       "  fill: currentColor;\n",
       "}\n",
       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt;\n",
       "Dimensions:           (lat: 3, lon: 2, time: 253)\n",
       "Coordinates:\n",
       "  * lat               (lat) float64 24.5 25.5 26.5\n",
       "  * lon               (lon) float64 88.5 89.5\n",
       "  * time              (time) datetime64[ns] 2000-01-01 2000-02-01 ... 2021-01-01\n",
       "    spatial_ref       int64 0\n",
       "Data variables:\n",
       "    SWE_inst          (time, lat, lon) float64 0.0 0.0 nan 0.0 ... 0.0 0.0 nan\n",
       "    CanopInt_inst     (time, lat, lon) float64 -0.0008521 -0.001237 ... nan\n",
       "    TWS_inst          (time, lat, lon) float64 -6.134 1.641 nan ... 4.258 nan\n",
       "    SoilMoist_P_inst  (time, lat, lon) float64 -6.132 1.642 nan ... 4.262 nan\n",
       "Attributes: (12/19)\n",
       "    CDI:                    Climate Data Interface version 1.9.8 (https://mpi...\n",
       "    Conventions:            CF-1.6\n",
       "    history:                created on date: 2019-09-09T16:18:11.303\n",
       "    source:                 CLSM_F2.5 forced with GDAS-AGRMET-GPCPv13rA1\n",
       "    institution:            NASA GSFC\n",
       "    missing_value:          -9999.0\n",
       "    ...                     ...\n",
       "    MAP_PROJECTION:         EQUIDISTANT CYLINDRICAL\n",
       "    SOUTH_WEST_CORNER_LAT:  -59.5\n",
       "    SOUTH_WEST_CORNER_LON:  -179.5\n",
       "    DX:                     1.0\n",
       "    DY:                     1.0\n",
       "    CDO:                    Climate Data Operators version 1.9.8 (https://mpi...</pre><div class='xr-wrap' hidden><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-31275768-1b8e-4dbe-b148-3b662d7e63bc' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-31275768-1b8e-4dbe-b148-3b662d7e63bc' 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'>lat</span>: 3</li><li><span class='xr-has-index'>lon</span>: 2</li><li><span class='xr-has-index'>time</span>: 253</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-d5e61cd3-8c2b-43f7-b816-a48730310ad7' class='xr-section-summary-in' type='checkbox'  checked><label for='section-d5e61cd3-8c2b-43f7-b816-a48730310ad7' class='xr-section-summary' >Coordinates: <span>(4)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lat</span></div><div class='xr-var-dims'>(lat)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>24.5 25.5 26.5</div><input id='attrs-0c7aac0f-3dc9-4ff5-bd87-11f8de7f161d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-0c7aac0f-3dc9-4ff5-bd87-11f8de7f161d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c0351f83-3a9b-4980-9e6c-7093da0d0adc' class='xr-var-data-in' type='checkbox'><label for='data-c0351f83-3a9b-4980-9e6c-7093da0d0adc' 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>latitude</dd><dt><span>long_name :</span></dt><dd>latitude</dd><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>axis :</span></dt><dd>Y</dd></dl></div><div class='xr-var-data'><pre>array([24.5, 25.5, 26.5])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lon</span></div><div class='xr-var-dims'>(lon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>88.5 89.5</div><input id='attrs-cfba8cf0-e072-497e-b53d-55cb1c91ebd3' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-cfba8cf0-e072-497e-b53d-55cb1c91ebd3' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e43ed0a3-4a12-404b-9ad7-e4f878e92355' class='xr-var-data-in' type='checkbox'><label for='data-e43ed0a3-4a12-404b-9ad7-e4f878e92355' 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>longitude</dd><dt><span>long_name :</span></dt><dd>longitude</dd><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>axis :</span></dt><dd>X</dd></dl></div><div class='xr-var-data'><pre>array([88.5, 89.5])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2000-01-01 ... 2021-01-01</div><input id='attrs-9f1fe269-24eb-4d50-bb4b-ffd2cce72b09' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-9f1fe269-24eb-4d50-bb4b-ffd2cce72b09' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9b555553-e62d-4909-895b-16044fc3a670' class='xr-var-data-in' type='checkbox'><label for='data-9b555553-e62d-4909-895b-16044fc3a670' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>time</dd><dt><span>bounds :</span></dt><dd>time_bnds</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;2000-01-01T00:00:00.000000000&#x27;, &#x27;2000-02-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;2000-03-01T00:00:00.000000000&#x27;, ..., &#x27;2020-11-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;2020-12-01T00:00:00.000000000&#x27;, &#x27;2021-01-01T00:00:00.000000000&#x27;],\n",
       "      dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>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-69d791ee-7a7f-4364-874c-108e9daff9fc' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-69d791ee-7a7f-4364-874c-108e9daff9fc' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e24756ca-3268-4a8e-966c-bf44f983d022' class='xr-var-data-in' type='checkbox'><label for='data-e24756ca-3268-4a8e-966c-bf44f983d022' 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>GEOGCS[&quot;WGS 84&quot;,DATUM[&quot;WGS_1984&quot;,SPHEROID[&quot;WGS 84&quot;,6378137,298.257223563,AUTHORITY[&quot;EPSG&quot;,&quot;7030&quot;]],AUTHORITY[&quot;EPSG&quot;,&quot;6326&quot;]],PRIMEM[&quot;Greenwich&quot;,0,AUTHORITY[&quot;EPSG&quot;,&quot;8901&quot;]],UNIT[&quot;degree&quot;,0.0174532925199433,AUTHORITY[&quot;EPSG&quot;,&quot;9122&quot;]],AXIS[&quot;Latitude&quot;,NORTH],AXIS[&quot;Longitude&quot;,EAST],AUTHORITY[&quot;EPSG&quot;,&quot;4326&quot;]]</dd><dt><span>semi_major_axis :</span></dt><dd>6378137.0</dd><dt><span>semi_minor_axis :</span></dt><dd>6356752.314245179</dd><dt><span>inverse_flattening :</span></dt><dd>298.257223563</dd><dt><span>reference_ellipsoid_name :</span></dt><dd>WGS 84</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>WGS 84</dd><dt><span>grid_mapping_name :</span></dt><dd>latitude_longitude</dd><dt><span>spatial_ref :</span></dt><dd>GEOGCS[&quot;WGS 84&quot;,DATUM[&quot;WGS_1984&quot;,SPHEROID[&quot;WGS 84&quot;,6378137,298.257223563,AUTHORITY[&quot;EPSG&quot;,&quot;7030&quot;]],AUTHORITY[&quot;EPSG&quot;,&quot;6326&quot;]],PRIMEM[&quot;Greenwich&quot;,0,AUTHORITY[&quot;EPSG&quot;,&quot;8901&quot;]],UNIT[&quot;degree&quot;,0.0174532925199433,AUTHORITY[&quot;EPSG&quot;,&quot;9122&quot;]],AXIS[&quot;Latitude&quot;,NORTH],AXIS[&quot;Longitude&quot;,EAST],AUTHORITY[&quot;EPSG&quot;,&quot;4326&quot;]]</dd><dt><span>GeoTransform :</span></dt><dd>88.0 1.0 0.0 24.0 0.0 1.0</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-e6a44506-3924-42a4-83a4-f848f607772d' class='xr-section-summary-in' type='checkbox'  checked><label for='section-e6a44506-3924-42a4-83a4-f848f607772d' class='xr-section-summary' >Data variables: <span>(4)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>SWE_inst</span></div><div class='xr-var-dims'>(time, lat, lon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0 0.0 nan 0.0 ... nan 0.0 0.0 nan</div><input id='attrs-1a8857cc-b735-451f-bec2-9ac23305a025' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-1a8857cc-b735-451f-bec2-9ac23305a025' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-73867f61-33bd-4079-be70-2854610dcf5d' class='xr-var-data-in' type='checkbox'><label for='data-73867f61-33bd-4079-be70-2854610dcf5d' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[[ 0.,  0.],\n",
       "        [nan,  0.],\n",
       "        [ 0., nan]],\n",
       "\n",
       "       [[ 0.,  0.],\n",
       "        [nan,  0.],\n",
       "        [ 0., nan]],\n",
       "\n",
       "       [[ 0.,  0.],\n",
       "        [nan,  0.],\n",
       "        [ 0., nan]],\n",
       "\n",
       "       ...,\n",
       "\n",
       "       [[ 0.,  0.],\n",
       "        [nan,  0.],\n",
       "        [ 0., nan]],\n",
       "\n",
       "       [[ 0.,  0.],\n",
       "        [nan,  0.],\n",
       "        [ 0., nan]],\n",
       "\n",
       "       [[ 0.,  0.],\n",
       "        [nan,  0.],\n",
       "        [ 0., nan]]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>CanopInt_inst</span></div><div class='xr-var-dims'>(time, lat, lon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-0.0008521 -0.001237 ... nan</div><input id='attrs-fbce9764-ae1d-4deb-a9a0-6f17e91e84af' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-fbce9764-ae1d-4deb-a9a0-6f17e91e84af' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f515e862-b49f-432b-8a2a-555c3e23b2a3' class='xr-var-data-in' type='checkbox'><label for='data-f515e862-b49f-432b-8a2a-555c3e23b2a3' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[[-0.0008521 , -0.00123749],\n",
       "        [        nan, -0.00213228],\n",
       "        [-0.00340144,         nan]],\n",
       "\n",
       "       [[-0.00110104, -0.0012618 ],\n",
       "        [        nan, -0.00285464],\n",
       "        [-0.00366289,         nan]],\n",
       "\n",
       "       [[-0.00152483, -0.00099431],\n",
       "        [        nan, -0.00275954],\n",
       "        [-0.00406618,         nan]],\n",
       "\n",
       "       ...,\n",
       "\n",
       "       [[-0.00134857, -0.00143637],\n",
       "        [        nan, -0.00227269],\n",
       "        [-0.00225365,         nan]],\n",
       "\n",
       "       [[-0.00176647, -0.00227246],\n",
       "        [        nan, -0.0025286 ],\n",
       "        [-0.00397709,         nan]],\n",
       "\n",
       "       [[-0.00181005, -0.00223818],\n",
       "        [        nan, -0.00317133],\n",
       "        [-0.00406478,         nan]]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>TWS_inst</span></div><div class='xr-var-dims'>(time, lat, lon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-6.134 1.641 nan ... 4.258 nan</div><input id='attrs-927bef7e-1e41-4794-a32f-0f5b967aaee9' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-927bef7e-1e41-4794-a32f-0f5b967aaee9' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ea5382e2-36b9-42de-9e3e-3e0be8413994' class='xr-var-data-in' type='checkbox'><label for='data-ea5382e2-36b9-42de-9e3e-3e0be8413994' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[[ -6.13395385,   1.64146721],\n",
       "        [         nan,   1.3312988 ],\n",
       "        [ -2.12852787,          nan]],\n",
       "\n",
       "       [[-12.44233996,  -6.66314065],\n",
       "        [         nan,  -7.12662339],\n",
       "        [-10.46892703,          nan]],\n",
       "\n",
       "       [[-22.20092714, -18.81253719],\n",
       "        [         nan, -19.87553686],\n",
       "        [-23.30785543,          nan]],\n",
       "\n",
       "       ...,\n",
       "\n",
       "       [[  3.45822759,  19.7031498 ],\n",
       "        [         nan,  17.23715812],\n",
       "        [ 19.11779791,          nan]],\n",
       "\n",
       "       [[ -6.43777475,  10.10310054],\n",
       "        [         nan,   8.36004615],\n",
       "        [ 11.60020754,          nan]],\n",
       "\n",
       "       [[-14.80014026,   0.98812254],\n",
       "        [         nan,   0.06407471],\n",
       "        [  4.25839834,          nan]]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>SoilMoist_P_inst</span></div><div class='xr-var-dims'>(time, lat, lon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-6.132 1.642 nan ... 4.262 nan</div><input id='attrs-9a576191-b075-4bc9-bc12-cc6cc6f36cf4' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-9a576191-b075-4bc9-bc12-cc6cc6f36cf4' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6ac43f99-f2b7-4c97-a4d6-1bddf05e6ad9' class='xr-var-data-in' type='checkbox'><label for='data-6ac43f99-f2b7-4c97-a4d6-1bddf05e6ad9' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[[ -6.13153689,   1.64166261],\n",
       "        [         nan,   1.3384277 ],\n",
       "        [ -2.12543942,          nan]],\n",
       "\n",
       "       [[-12.44287714,  -6.66163936],\n",
       "        [         nan,  -7.12458491],\n",
       "        [-10.46787128,          nan]],\n",
       "\n",
       "       [[-22.19935954, -18.8119933 ],\n",
       "        [         nan, -19.87297386],\n",
       "        [-23.30659181,          nan]],\n",
       "\n",
       "       ...,\n",
       "\n",
       "       [[  3.45957018,  19.70458925],\n",
       "        [         nan,  17.23946482],\n",
       "        [ 19.12005544,          nan]],\n",
       "\n",
       "       [[ -6.43600449,  10.10537073],\n",
       "        [         nan,   8.36260989],\n",
       "        [ 11.60419956,          nan]],\n",
       "\n",
       "       [[-14.79833424,   0.99036861],\n",
       "        [         nan,   0.06727295],\n",
       "        [  4.26247567,          nan]]])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-7cf277aa-9efb-4f04-a39d-52ad4843f587' class='xr-section-summary-in' type='checkbox'  ><label for='section-7cf277aa-9efb-4f04-a39d-52ad4843f587' class='xr-section-summary' >Attributes: <span>(19)</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 1.9.8 (https://mpimet.mpg.de/cdi)</dd><dt><span>Conventions :</span></dt><dd>CF-1.6</dd><dt><span>history :</span></dt><dd>created on date: 2019-09-09T16:18:11.303</dd><dt><span>source :</span></dt><dd>CLSM_F2.5 forced with GDAS-AGRMET-GPCPv13rA1</dd><dt><span>institution :</span></dt><dd>NASA GSFC</dd><dt><span>missing_value :</span></dt><dd>-9999.0</dd><dt><span>tavg definision: :</span></dt><dd>past 3-hour average</dd><dt><span>acc definision: :</span></dt><dd>past 3-hour accumulation</dd><dt><span>inst definision: :</span></dt><dd>instantaneous</dd><dt><span>title :</span></dt><dd>GLDAS2.1 LIS land surface model output monthly mean</dd><dt><span>references :</span></dt><dd>Rodell_etal_BAMS_2004, Kumar_etal_EMS_2006, Peters-Lidard_etal_ISSE_2007</dd><dt><span>conventions :</span></dt><dd>CF-1.6</dd><dt><span>comment :</span></dt><dd>website: https://ldas.gsfc.nasa.gov/gldas, https://lis.gsfc.nasa.gov/</dd><dt><span>MAP_PROJECTION :</span></dt><dd>EQUIDISTANT CYLINDRICAL</dd><dt><span>SOUTH_WEST_CORNER_LAT :</span></dt><dd>-59.5</dd><dt><span>SOUTH_WEST_CORNER_LON :</span></dt><dd>-179.5</dd><dt><span>DX :</span></dt><dd>1.0</dd><dt><span>DY :</span></dt><dd>1.0</dd><dt><span>CDO :</span></dt><dd>Climate Data Operators version 1.9.8 (https://mpimet.mpg.de/cdo)</dd></dl></div></li></ul></div></div>"
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       "    ...                     ...\n",
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       "    DX:                     1.0\n",
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       "Dimensions:                (lat: 3, lon: 2, time: 253)\n",
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       "Attributes: (12/19)\n",
       "    CDI:                    Climate Data Interface version 1.9.8 (https://mpi...\n",
       "    Conventions:            CF-1.6\n",
       "    history:                created on date: 2019-09-09T16:06:53.375\n",
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       "    institution:            NASA GSFC\n",
       "    missing_value:          -9999.0\n",
       "    ...                     ...\n",
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       "    SOUTH_WEST_CORNER_LAT:  -59.5\n",
       "    SOUTH_WEST_CORNER_LON:  -179.5\n",
       "    DX:                     1.0\n",
       "    DY:                     1.0\n",
       "    CDO:                    Climate Data Operators version 1.9.8 (https://mpi...</pre><div class='xr-wrap' hidden><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-e064ffad-6d85-403c-9167-1b37152ba27c' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-e064ffad-6d85-403c-9167-1b37152ba27c' 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'>lat</span>: 3</li><li><span class='xr-has-index'>lon</span>: 2</li><li><span class='xr-has-index'>time</span>: 253</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-82304f90-ef0c-4739-b63d-7093c7dfe3ee' class='xr-section-summary-in' type='checkbox'  checked><label for='section-82304f90-ef0c-4739-b63d-7093c7dfe3ee' class='xr-section-summary' >Coordinates: <span>(4)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lat</span></div><div class='xr-var-dims'>(lat)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>24.5 25.5 26.5</div><input id='attrs-249a34c5-c670-440a-a086-c93ef2bc1b5e' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-249a34c5-c670-440a-a086-c93ef2bc1b5e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9c586c6a-6229-4b84-93b9-40cf3470766f' class='xr-var-data-in' type='checkbox'><label for='data-9c586c6a-6229-4b84-93b9-40cf3470766f' 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>latitude</dd><dt><span>long_name :</span></dt><dd>latitude</dd><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>axis :</span></dt><dd>Y</dd></dl></div><div class='xr-var-data'><pre>array([24.5, 25.5, 26.5])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lon</span></div><div class='xr-var-dims'>(lon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>88.5 89.5</div><input id='attrs-ea2411e6-252b-462c-9fb8-348ce8544003' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ea2411e6-252b-462c-9fb8-348ce8544003' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1bac9a23-b05f-4c7a-abe6-1c5cb0409597' class='xr-var-data-in' type='checkbox'><label for='data-1bac9a23-b05f-4c7a-abe6-1c5cb0409597' 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>longitude</dd><dt><span>long_name :</span></dt><dd>longitude</dd><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>axis :</span></dt><dd>X</dd></dl></div><div class='xr-var-data'><pre>array([88.5, 89.5])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2000-01-01 ... 2021-01-01</div><input id='attrs-4a6ccdeb-69e5-4dda-bdfb-0d1465be623f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-4a6ccdeb-69e5-4dda-bdfb-0d1465be623f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a8f99981-4053-4cc7-841e-dbac16c546be' class='xr-var-data-in' type='checkbox'><label for='data-a8f99981-4053-4cc7-841e-dbac16c546be' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>time</dd><dt><span>bounds :</span></dt><dd>time_bnds</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;2000-01-01T00:00:00.000000000&#x27;, &#x27;2000-02-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;2000-03-01T00:00:00.000000000&#x27;, ..., &#x27;2020-11-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;2020-12-01T00:00:00.000000000&#x27;, &#x27;2021-01-01T00:00:00.000000000&#x27;],\n",
       "      dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>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-66901c2b-db5f-46a7-828d-b5f53926d382' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-66901c2b-db5f-46a7-828d-b5f53926d382' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-08d516c4-e209-4dba-b870-394e21d04b63' class='xr-var-data-in' type='checkbox'><label for='data-08d516c4-e209-4dba-b870-394e21d04b63' 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>GEOGCS[&quot;WGS 84&quot;,DATUM[&quot;WGS_1984&quot;,SPHEROID[&quot;WGS 84&quot;,6378137,298.257223563,AUTHORITY[&quot;EPSG&quot;,&quot;7030&quot;]],AUTHORITY[&quot;EPSG&quot;,&quot;6326&quot;]],PRIMEM[&quot;Greenwich&quot;,0,AUTHORITY[&quot;EPSG&quot;,&quot;8901&quot;]],UNIT[&quot;degree&quot;,0.0174532925199433,AUTHORITY[&quot;EPSG&quot;,&quot;9122&quot;]],AXIS[&quot;Latitude&quot;,NORTH],AXIS[&quot;Longitude&quot;,EAST],AUTHORITY[&quot;EPSG&quot;,&quot;4326&quot;]]</dd><dt><span>semi_major_axis :</span></dt><dd>6378137.0</dd><dt><span>semi_minor_axis :</span></dt><dd>6356752.314245179</dd><dt><span>inverse_flattening :</span></dt><dd>298.257223563</dd><dt><span>reference_ellipsoid_name :</span></dt><dd>WGS 84</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>WGS 84</dd><dt><span>grid_mapping_name :</span></dt><dd>latitude_longitude</dd><dt><span>spatial_ref :</span></dt><dd>GEOGCS[&quot;WGS 84&quot;,DATUM[&quot;WGS_1984&quot;,SPHEROID[&quot;WGS 84&quot;,6378137,298.257223563,AUTHORITY[&quot;EPSG&quot;,&quot;7030&quot;]],AUTHORITY[&quot;EPSG&quot;,&quot;6326&quot;]],PRIMEM[&quot;Greenwich&quot;,0,AUTHORITY[&quot;EPSG&quot;,&quot;8901&quot;]],UNIT[&quot;degree&quot;,0.0174532925199433,AUTHORITY[&quot;EPSG&quot;,&quot;9122&quot;]],AXIS[&quot;Latitude&quot;,NORTH],AXIS[&quot;Longitude&quot;,EAST],AUTHORITY[&quot;EPSG&quot;,&quot;4326&quot;]]</dd><dt><span>GeoTransform :</span></dt><dd>88.0 1.0 0.0 24.0 0.0 1.0</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-417e452c-e7e2-46a0-bd39-c0f9f1caae3d' class='xr-section-summary-in' type='checkbox'  checked><label for='section-417e452c-e7e2-46a0-bd39-c0f9f1caae3d' class='xr-section-summary' >Data variables: <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>SWE_inst</span></div><div class='xr-var-dims'>(time, lat, lon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0 0.0 nan 0.0 ... nan 0.0 0.0 nan</div><input id='attrs-a3d7bc38-b778-4ecd-b22d-834bdc269aa0' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-a3d7bc38-b778-4ecd-b22d-834bdc269aa0' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4a468a4d-35f9-4406-963c-5129213adbbd' class='xr-var-data-in' type='checkbox'><label for='data-4a468a4d-35f9-4406-963c-5129213adbbd' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[[0.00000000e+00, 0.00000000e+00],\n",
       "        [           nan, 0.00000000e+00],\n",
       "        [2.02429149e-05,            nan]],\n",
       "\n",
       "       [[0.00000000e+00, 0.00000000e+00],\n",
       "        [           nan, 0.00000000e+00],\n",
       "        [0.00000000e+00,            nan]],\n",
       "\n",
       "       [[0.00000000e+00, 0.00000000e+00],\n",
       "        [           nan, 0.00000000e+00],\n",
       "        [0.00000000e+00,            nan]],\n",
       "\n",
       "       ...,\n",
       "\n",
       "       [[0.00000000e+00, 0.00000000e+00],\n",
       "        [           nan, 0.00000000e+00],\n",
       "        [0.00000000e+00,            nan]],\n",
       "\n",
       "       [[0.00000000e+00, 0.00000000e+00],\n",
       "        [           nan, 0.00000000e+00],\n",
       "        [0.00000000e+00,            nan]],\n",
       "\n",
       "       [[0.00000000e+00, 0.00000000e+00],\n",
       "        [           nan, 0.00000000e+00],\n",
       "        [0.00000000e+00,            nan]]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>CanopInt_inst</span></div><div class='xr-var-dims'>(time, lat, lon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-0.009269 -0.009541 ... nan</div><input id='attrs-26bab20b-bbb8-4e03-8282-b81b77cbd7c2' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-26bab20b-bbb8-4e03-8282-b81b77cbd7c2' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-702f575a-e9d1-4b0e-9cb5-0a4383ecede8' class='xr-var-data-in' type='checkbox'><label for='data-702f575a-e9d1-4b0e-9cb5-0a4383ecede8' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[[-0.00926931, -0.00954134],\n",
       "        [        nan, -0.01155246],\n",
       "        [-0.0127138 ,         nan]],\n",
       "\n",
       "       [[-0.00479186, -0.00672022],\n",
       "        [        nan, -0.0070789 ],\n",
       "        [-0.01038077,         nan]],\n",
       "\n",
       "       [[-0.00883906, -0.0065039 ],\n",
       "        [        nan, -0.008561  ],\n",
       "        [-0.01264707,         nan]],\n",
       "\n",
       "       ...,\n",
       "\n",
       "       [[-0.01001562, -0.0096622 ],\n",
       "        [        nan, -0.01059569],\n",
       "        [-0.00996732,         nan]],\n",
       "\n",
       "       [[-0.01023463, -0.01132567],\n",
       "        [        nan, -0.01146987],\n",
       "        [-0.01283699,         nan]],\n",
       "\n",
       "       [[-0.00992656, -0.0104172 ],\n",
       "        [        nan, -0.01219286],\n",
       "        [-0.01296038,         nan]]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>SoilMoi0_10cm_inst</span></div><div class='xr-var-dims'>(time, lat, lon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-0.5768 -0.5066 nan ... -0.741 nan</div><input id='attrs-1a0f13c2-2cd9-47d4-a84e-d7f6a1a00095' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-1a0f13c2-2cd9-47d4-a84e-d7f6a1a00095' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4c5b8e43-0539-49d0-8170-19980b3e8de5' class='xr-var-data-in' type='checkbox'><label for='data-4c5b8e43-0539-49d0-8170-19980b3e8de5' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[[-0.57677878, -0.50656088],\n",
       "        [        nan, -0.4981827 ],\n",
       "        [-0.75674895,         nan]],\n",
       "\n",
       "       [[-0.37721654, -0.46365145],\n",
       "        [        nan, -0.54872455],\n",
       "        [-0.84424987,         nan]],\n",
       "\n",
       "       [[-0.9709225 , -0.78608058],\n",
       "        [        nan, -0.88895876],\n",
       "        [-1.41545925,         nan]],\n",
       "\n",
       "       ...,\n",
       "\n",
       "       [[-0.08801766,  0.05652828],\n",
       "        [        nan, -0.06008396],\n",
       "        [-0.08578987,         nan]],\n",
       "\n",
       "       [[-0.49928892, -0.28997823],\n",
       "        [        nan, -0.35702896],\n",
       "        [-0.41343956,         nan]],\n",
       "\n",
       "       [[-0.87136952, -0.63129747],\n",
       "        [        nan, -0.66915513],\n",
       "        [-0.74097253,         nan]]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>SoilMoi10_40cm_inst</span></div><div class='xr-var-dims'>(time, lat, lon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-1.4 -1.278 nan ... -1.97 nan</div><input id='attrs-75355730-811c-41c3-9894-9f3baf3bb427' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-75355730-811c-41c3-9894-9f3baf3bb427' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-909c91f2-5230-4aa9-9030-7333d8b7dafe' class='xr-var-data-in' type='checkbox'><label for='data-909c91f2-5230-4aa9-9030-7333d8b7dafe' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[[-1.39966356, -1.27822878],\n",
       "        [        nan, -1.26705784],\n",
       "        [-1.84440836,         nan]],\n",
       "\n",
       "       [[-1.23436283, -1.28803784],\n",
       "        [        nan, -1.32292788],\n",
       "        [-2.07613558,         nan]],\n",
       "\n",
       "       [[-2.43908949, -2.44485624],\n",
       "        [        nan, -2.28279531],\n",
       "        [-2.96369251,         nan]],\n",
       "\n",
       "       ...,\n",
       "\n",
       "       [[-0.22437363,  0.16571655],\n",
       "        [        nan, -0.2307869 ],\n",
       "        [-0.31098938,         nan]],\n",
       "\n",
       "       [[-1.19886706, -0.76520536],\n",
       "        [        nan, -1.04583744],\n",
       "        [-1.19277118,         nan]],\n",
       "\n",
       "       [[-1.90502889, -1.56318061],\n",
       "        [        nan, -1.69616397],\n",
       "        [-1.96963623,         nan]]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>SoilMoi40_100cm_inst</span></div><div class='xr-var-dims'>(time, lat, lon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-1.889 -1.662 nan ... -3.151 nan</div><input id='attrs-c52cc95e-939f-4302-99bd-6dcf02529659' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-c52cc95e-939f-4302-99bd-6dcf02529659' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-eef7a7e8-4812-4c01-b8c1-3044715992c5' class='xr-var-data-in' type='checkbox'><label for='data-eef7a7e8-4812-4c01-b8c1-3044715992c5' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[[-1.8893417 , -1.66182257],\n",
       "        [        nan, -1.79664008],\n",
       "        [-2.74997409,         nan]],\n",
       "\n",
       "       [[-2.59712376, -2.38982551],\n",
       "        [        nan, -2.50051431],\n",
       "        [-3.80638726,         nan]],\n",
       "\n",
       "       [[-4.44152281, -4.72475737],\n",
       "        [        nan, -4.04495224],\n",
       "        [-5.32721244,         nan]],\n",
       "\n",
       "       ...,\n",
       "\n",
       "       [[ 0.21877442,  0.88114319],\n",
       "        [        nan, -0.10939026],\n",
       "        [-0.25549163,         nan]],\n",
       "\n",
       "       [[-1.47889555, -0.85945129],\n",
       "        [        nan, -1.66998599],\n",
       "        [-1.89336706,         nan]],\n",
       "\n",
       "       [[-2.82454379, -2.18992308],\n",
       "        [        nan, -2.69570462],\n",
       "        [-3.15125287,         nan]]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>SoilMoi100_200cm_inst</span></div><div class='xr-var-dims'>(time, lat, lon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-3.471 -3.365 nan ... -4.929 nan</div><input id='attrs-ba9a7f9c-fc8b-4d42-a3e4-90a5e201905d' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-ba9a7f9c-fc8b-4d42-a3e4-90a5e201905d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9be6f085-116c-4cb6-8399-ef8f72b8f127' class='xr-var-data-in' type='checkbox'><label for='data-9be6f085-116c-4cb6-8399-ef8f72b8f127' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[[-3.47120352, -3.36528011],\n",
       "        [        nan, -3.27937007],\n",
       "        [-4.2271208 ,         nan]],\n",
       "\n",
       "       [[-4.90443408, -4.90143448],\n",
       "        [        nan, -4.84616682],\n",
       "        [-5.56680001,         nan]],\n",
       "\n",
       "       [[-5.86881861, -5.95504306],\n",
       "        [        nan, -6.00207821],\n",
       "        [-6.45573586,         nan]],\n",
       "\n",
       "       ...,\n",
       "\n",
       "       [[-0.02494202,  0.88568116],\n",
       "        [        nan, -0.12637939],\n",
       "        [-0.48865965,         nan]],\n",
       "\n",
       "       [[-2.91663818, -2.31244806],\n",
       "        [        nan, -3.14231254],\n",
       "        [-3.23932506,         nan]],\n",
       "\n",
       "       [[-4.59955148, -4.24889214],\n",
       "        [        nan, -4.84477542],\n",
       "        [-4.9292665 ,         nan]]])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-fb3ebfc1-97dd-47d3-bc30-4e4bf4052c7b' class='xr-section-summary-in' type='checkbox'  ><label for='section-fb3ebfc1-97dd-47d3-bc30-4e4bf4052c7b' class='xr-section-summary' >Attributes: <span>(19)</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 1.9.8 (https://mpimet.mpg.de/cdi)</dd><dt><span>Conventions :</span></dt><dd>CF-1.6</dd><dt><span>history :</span></dt><dd>created on date: 2019-09-09T16:06:53.375</dd><dt><span>source :</span></dt><dd>Noah_v3.6 forced with GDAS-AGRMET-GPCPv13rA1</dd><dt><span>institution :</span></dt><dd>NASA GSFC</dd><dt><span>missing_value :</span></dt><dd>-9999.0</dd><dt><span>tavg definision: :</span></dt><dd>past 3-hour average</dd><dt><span>acc definision: :</span></dt><dd>past 3-hour accumulation</dd><dt><span>inst definision: :</span></dt><dd>instantaneous</dd><dt><span>title :</span></dt><dd>GLDAS2.1 LIS land surface model output monthly mean</dd><dt><span>references :</span></dt><dd>Rodell_etal_BAMS_2004, Kumar_etal_EMS_2006, Peters-Lidard_etal_ISSE_2007</dd><dt><span>conventions :</span></dt><dd>CF-1.6</dd><dt><span>comment :</span></dt><dd>website: https://ldas.gsfc.nasa.gov/gldas, https://lis.gsfc.nasa.gov/</dd><dt><span>MAP_PROJECTION :</span></dt><dd>EQUIDISTANT CYLINDRICAL</dd><dt><span>SOUTH_WEST_CORNER_LAT :</span></dt><dd>-59.5</dd><dt><span>SOUTH_WEST_CORNER_LON :</span></dt><dd>-179.5</dd><dt><span>DX :</span></dt><dd>1.0</dd><dt><span>DY :</span></dt><dd>1.0</dd><dt><span>CDO :</span></dt><dd>Climate Data Operators version 1.9.8 (https://mpimet.mpg.de/cdo)</dd></dl></div></li></ul></div></div>"
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       "    CDI:                    Climate Data Interface version 1.9.8 (https://mpi...\n",
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       "    DX:                     1.0\n",
       "    DY:                     1.0\n",
       "    CDO:                    Climate Data Operators version 1.9.8 (https://mpi...</pre><div class='xr-wrap' hidden><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-80fc3247-0580-4e8c-8568-a3b53c972b89' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-80fc3247-0580-4e8c-8568-a3b53c972b89' 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'>lat</span>: 3</li><li><span class='xr-has-index'>lon</span>: 2</li><li><span class='xr-has-index'>time</span>: 253</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-ca0b91d4-2a52-4c04-b156-9d264b9645f4' class='xr-section-summary-in' type='checkbox'  checked><label for='section-ca0b91d4-2a52-4c04-b156-9d264b9645f4' class='xr-section-summary' >Coordinates: <span>(4)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lat</span></div><div class='xr-var-dims'>(lat)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>24.5 25.5 26.5</div><input id='attrs-75dc8d99-0eb6-4266-a388-375260a1249c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-75dc8d99-0eb6-4266-a388-375260a1249c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8a2be6df-91fa-451e-b717-23f33ec29d93' class='xr-var-data-in' type='checkbox'><label for='data-8a2be6df-91fa-451e-b717-23f33ec29d93' 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>latitude</dd><dt><span>long_name :</span></dt><dd>latitude</dd><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>axis :</span></dt><dd>Y</dd></dl></div><div class='xr-var-data'><pre>array([24.5, 25.5, 26.5])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lon</span></div><div class='xr-var-dims'>(lon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>88.5 89.5</div><input id='attrs-631dff1f-d31a-4ee5-845f-c2d0369b5e60' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-631dff1f-d31a-4ee5-845f-c2d0369b5e60' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-817a12cc-8906-4db8-8313-88d4e956c71b' class='xr-var-data-in' type='checkbox'><label for='data-817a12cc-8906-4db8-8313-88d4e956c71b' 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>longitude</dd><dt><span>long_name :</span></dt><dd>longitude</dd><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>axis :</span></dt><dd>X</dd></dl></div><div class='xr-var-data'><pre>array([88.5, 89.5])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2000-01-01 ... 2021-01-01</div><input id='attrs-44fec9e0-13f9-4df5-a9a1-8d364298b2a7' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-44fec9e0-13f9-4df5-a9a1-8d364298b2a7' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c11af4af-d9b5-4684-9d0d-6c15f4d87f2f' class='xr-var-data-in' type='checkbox'><label for='data-c11af4af-d9b5-4684-9d0d-6c15f4d87f2f' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>time</dd><dt><span>bounds :</span></dt><dd>time_bnds</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;2000-01-01T00:00:00.000000000&#x27;, &#x27;2000-02-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;2000-03-01T00:00:00.000000000&#x27;, ..., &#x27;2020-11-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;2020-12-01T00:00:00.000000000&#x27;, &#x27;2021-01-01T00:00:00.000000000&#x27;],\n",
       "      dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>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-e6333909-e5a2-4609-8e57-5516d583c557' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e6333909-e5a2-4609-8e57-5516d583c557' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e1fbe80a-4466-418b-9d76-7d87fa6eb14d' class='xr-var-data-in' type='checkbox'><label for='data-e1fbe80a-4466-418b-9d76-7d87fa6eb14d' 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>GEOGCS[&quot;WGS 84&quot;,DATUM[&quot;WGS_1984&quot;,SPHEROID[&quot;WGS 84&quot;,6378137,298.257223563,AUTHORITY[&quot;EPSG&quot;,&quot;7030&quot;]],AUTHORITY[&quot;EPSG&quot;,&quot;6326&quot;]],PRIMEM[&quot;Greenwich&quot;,0,AUTHORITY[&quot;EPSG&quot;,&quot;8901&quot;]],UNIT[&quot;degree&quot;,0.0174532925199433,AUTHORITY[&quot;EPSG&quot;,&quot;9122&quot;]],AXIS[&quot;Latitude&quot;,NORTH],AXIS[&quot;Longitude&quot;,EAST],AUTHORITY[&quot;EPSG&quot;,&quot;4326&quot;]]</dd><dt><span>semi_major_axis :</span></dt><dd>6378137.0</dd><dt><span>semi_minor_axis :</span></dt><dd>6356752.314245179</dd><dt><span>inverse_flattening :</span></dt><dd>298.257223563</dd><dt><span>reference_ellipsoid_name :</span></dt><dd>WGS 84</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>WGS 84</dd><dt><span>grid_mapping_name :</span></dt><dd>latitude_longitude</dd><dt><span>spatial_ref :</span></dt><dd>GEOGCS[&quot;WGS 84&quot;,DATUM[&quot;WGS_1984&quot;,SPHEROID[&quot;WGS 84&quot;,6378137,298.257223563,AUTHORITY[&quot;EPSG&quot;,&quot;7030&quot;]],AUTHORITY[&quot;EPSG&quot;,&quot;6326&quot;]],PRIMEM[&quot;Greenwich&quot;,0,AUTHORITY[&quot;EPSG&quot;,&quot;8901&quot;]],UNIT[&quot;degree&quot;,0.0174532925199433,AUTHORITY[&quot;EPSG&quot;,&quot;9122&quot;]],AXIS[&quot;Latitude&quot;,NORTH],AXIS[&quot;Longitude&quot;,EAST],AUTHORITY[&quot;EPSG&quot;,&quot;4326&quot;]]</dd><dt><span>GeoTransform :</span></dt><dd>88.0 1.0 0.0 24.0 0.0 1.0</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-45ea055c-5c33-4dd8-8d53-8b6210e6be09' class='xr-section-summary-in' type='checkbox'  checked><label for='section-45ea055c-5c33-4dd8-8d53-8b6210e6be09' class='xr-section-summary' >Data variables: <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>SWE_inst</span></div><div class='xr-var-dims'>(time, lat, lon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0 0.0 nan 0.0 ... nan 0.0 0.0 nan</div><input id='attrs-994d59b3-9ff8-4367-b9b9-6784bce11706' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-994d59b3-9ff8-4367-b9b9-6784bce11706' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-82e363c3-e192-40ec-ab7f-14dbf5f07ff2' class='xr-var-data-in' type='checkbox'><label for='data-82e363c3-e192-40ec-ab7f-14dbf5f07ff2' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[[0.00000000e+00, 0.00000000e+00],\n",
       "        [           nan, 0.00000000e+00],\n",
       "        [8.58554294e-07,            nan]],\n",
       "\n",
       "       [[0.00000000e+00, 0.00000000e+00],\n",
       "        [           nan, 0.00000000e+00],\n",
       "        [0.00000000e+00,            nan]],\n",
       "\n",
       "       [[0.00000000e+00, 0.00000000e+00],\n",
       "        [           nan, 0.00000000e+00],\n",
       "        [0.00000000e+00,            nan]],\n",
       "\n",
       "       ...,\n",
       "\n",
       "       [[0.00000000e+00, 0.00000000e+00],\n",
       "        [           nan, 0.00000000e+00],\n",
       "        [0.00000000e+00,            nan]],\n",
       "\n",
       "       [[0.00000000e+00, 0.00000000e+00],\n",
       "        [           nan, 0.00000000e+00],\n",
       "        [0.00000000e+00,            nan]],\n",
       "\n",
       "       [[0.00000000e+00, 0.00000000e+00],\n",
       "        [           nan, 0.00000000e+00],\n",
       "        [0.00000000e+00,            nan]]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>CanopInt_inst</span></div><div class='xr-var-dims'>(time, lat, lon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-0.002262 -0.002365 ... nan</div><input id='attrs-d14b0993-dede-40d6-8b42-5f4f9c57402c' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-d14b0993-dede-40d6-8b42-5f4f9c57402c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-eaa2aade-5194-4b75-9b15-f19bde2fa94c' class='xr-var-data-in' type='checkbox'><label for='data-eaa2aade-5194-4b75-9b15-f19bde2fa94c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[[-0.00226235, -0.00236515],\n",
       "        [        nan, -0.00238322],\n",
       "        [-0.00263504,         nan]],\n",
       "\n",
       "       [[-0.00224669, -0.00234223],\n",
       "        [        nan, -0.00259744],\n",
       "        [-0.00259958,         nan]],\n",
       "\n",
       "       [[-0.00231292, -0.00191824],\n",
       "        [        nan, -0.00227443],\n",
       "        [-0.00267374,         nan]],\n",
       "\n",
       "       ...,\n",
       "\n",
       "       [[-0.00244057, -0.00235572],\n",
       "        [        nan, -0.00249148],\n",
       "        [-0.00249119,         nan]],\n",
       "\n",
       "       [[-0.0026489 , -0.00291718],\n",
       "        [        nan, -0.00274296],\n",
       "        [-0.00279758,         nan]],\n",
       "\n",
       "       [[-0.00260912, -0.00284992],\n",
       "        [        nan, -0.00278872],\n",
       "        [-0.00279819,         nan]]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>SoilMoi0_30cm_inst</span></div><div class='xr-var-dims'>(time, lat, lon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-2.197 -2.184 nan ... -2.561 nan</div><input id='attrs-33a5da0c-5ecf-4fb7-85e3-deb805621f63' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-33a5da0c-5ecf-4fb7-85e3-deb805621f63' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-96a910cd-822a-42ce-988c-cc71ebdc448b' class='xr-var-data-in' type='checkbox'><label for='data-96a910cd-822a-42ce-988c-cc71ebdc448b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[[-2.19667163, -2.18428764],\n",
       "        [        nan, -1.98027343],\n",
       "        [-2.27115788,         nan]],\n",
       "\n",
       "       [[-0.3385002 , -0.67779999],\n",
       "        [        nan, -0.96154632],\n",
       "        [-1.64645389,         nan]],\n",
       "\n",
       "       [[-0.81794206, -0.52478868],\n",
       "        [        nan, -1.19853821],\n",
       "        [-2.15890054,         nan]],\n",
       "\n",
       "       ...,\n",
       "\n",
       "       [[-1.57627948, -1.11386487],\n",
       "        [        nan, -1.55924298],\n",
       "        [-2.13029105,         nan]],\n",
       "\n",
       "       [[-2.17050053, -2.02081911],\n",
       "        [        nan, -2.12016534],\n",
       "        [-2.43461765,         nan]],\n",
       "\n",
       "       [[-2.4355026 , -2.39995569],\n",
       "        [        nan, -2.30692364],\n",
       "        [-2.56081857,         nan]]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>SoilMoi_depth2_inst</span></div><div class='xr-var-dims'>(time, lat, lon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-15.17 -5.777 nan ... -12.08 nan</div><input id='attrs-92899785-9ca4-4ad6-a835-013d6a57f4a8' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-92899785-9ca4-4ad6-a835-013d6a57f4a8' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-965aebb3-6890-4741-a926-68d96fc34d00' class='xr-var-data-in' type='checkbox'><label for='data-965aebb3-6890-4741-a926-68d96fc34d00' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[[-15.17135054,  -5.77691644],\n",
       "        [         nan,  -3.14827263],\n",
       "        [ -4.9192138 ,          nan]],\n",
       "\n",
       "       [[-19.05147135, -14.42088038],\n",
       "        [         nan, -10.51082164],\n",
       "        [-12.66152412,          nan]],\n",
       "\n",
       "       [[-21.3782534 , -19.17205155],\n",
       "        [         nan, -14.31640685],\n",
       "        [-16.9612363 ,          nan]],\n",
       "\n",
       "       ...,\n",
       "\n",
       "       [[ 13.41862231,  14.18925226],\n",
       "        [         nan,   8.5446775 ],\n",
       "        [  7.51182288,          nan]],\n",
       "\n",
       "       [[  3.16286013,   3.9600648 ],\n",
       "        [         nan,  -1.93106085],\n",
       "        [ -3.32861952,          nan]],\n",
       "\n",
       "       [[ -6.83358759,  -6.16823137],\n",
       "        [         nan, -10.25506556],\n",
       "        [-12.07865626,          nan]]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>SoilMoi_depth3_inst</span></div><div class='xr-var-dims'>(time, lat, lon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.4509 1.31 nan ... 0.7597 nan</div><input id='attrs-c43ef509-1871-4032-9f49-a7783caddbfa' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-c43ef509-1871-4032-9f49-a7783caddbfa' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6060e82e-a7d2-4033-a2e3-2321c8829f62' class='xr-var-data-in' type='checkbox'><label for='data-6060e82e-a7d2-4033-a2e3-2321c8829f62' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[[ 0.45094681,  1.30980602],\n",
       "        [        nan,  2.11749263],\n",
       "        [ 1.96809694,         nan]],\n",
       "\n",
       "       [[-2.31382567,  0.74854963],\n",
       "        [        nan,  0.66961213],\n",
       "        [ 0.54910658,         nan]],\n",
       "\n",
       "       [[-4.02729213, -1.79825295],\n",
       "        [        nan, -1.95237733],\n",
       "        [-2.22657975,         nan]],\n",
       "\n",
       "       ...,\n",
       "\n",
       "       [[ 1.44812008,  1.30980602],\n",
       "        [        nan,  2.13610772],\n",
       "        [ 1.97877884,         nan]],\n",
       "\n",
       "       [[ 1.44812008,  1.30980602],\n",
       "        [        nan,  2.13339012],\n",
       "        [ 1.97800901,         nan]],\n",
       "\n",
       "       [[ 1.44811403,  1.30978469],\n",
       "        [        nan,  0.82350615],\n",
       "        [ 0.75969314,         nan]]])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-860f8aef-eb83-4c57-8914-0dbfedd4d1af' class='xr-section-summary-in' type='checkbox'  ><label for='section-860f8aef-eb83-4c57-8914-0dbfedd4d1af' class='xr-section-summary' >Attributes: <span>(19)</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 1.9.8 (https://mpimet.mpg.de/cdi)</dd><dt><span>Conventions :</span></dt><dd>CF-1.6</dd><dt><span>history :</span></dt><dd>created on date: 2020-02-03T12:00:52.166</dd><dt><span>source :</span></dt><dd>VIC_v4.1.2 forced with GDAS-AGRMET-GPCPv13rA1</dd><dt><span>institution :</span></dt><dd>NASA GSFC</dd><dt><span>missing_value :</span></dt><dd>-9999.0</dd><dt><span>tavg definision: :</span></dt><dd>past 3-hour average</dd><dt><span>acc definision: :</span></dt><dd>past 3-hour accumulation</dd><dt><span>inst definision: :</span></dt><dd>instantaneous</dd><dt><span>title :</span></dt><dd>GLDAS2.1 LIS land surface model output monthly mean</dd><dt><span>references :</span></dt><dd>Rodell_etal_BAMS_2004, Kumar_etal_EMS_2006, Peters-Lidard_etal_ISSE_2007</dd><dt><span>conventions :</span></dt><dd>CF-1.6</dd><dt><span>comment :</span></dt><dd>website: https://ldas.gsfc.nasa.gov/gldas, https://lis.gsfc.nasa.gov/</dd><dt><span>MAP_PROJECTION :</span></dt><dd>EQUIDISTANT CYLINDRICAL</dd><dt><span>SOUTH_WEST_CORNER_LAT :</span></dt><dd>-59.5</dd><dt><span>SOUTH_WEST_CORNER_LON :</span></dt><dd>-179.5</dd><dt><span>DX :</span></dt><dd>1.0</dd><dt><span>DY :</span></dt><dd>1.0</dd><dt><span>CDO :</span></dt><dd>Climate Data Operators version 1.9.8 (https://mpimet.mpg.de/cdo)</dd></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.Dataset>\n",
       "Dimensions:              (lat: 3, lon: 2, time: 253)\n",
       "Coordinates:\n",
       "  * lat                  (lat) float64 24.5 25.5 26.5\n",
       "  * lon                  (lon) float64 88.5 89.5\n",
       "  * time                 (time) datetime64[ns] 2000-01-01 ... 2021-01-01\n",
       "    spatial_ref          int64 0\n",
       "Data variables:\n",
       "    SWE_inst             (time, lat, lon) float64 0.0 0.0 nan ... 0.0 0.0 nan\n",
       "    CanopInt_inst        (time, lat, lon) float64 -0.002262 -0.002365 ... nan\n",
       "    SoilMoi0_30cm_inst   (time, lat, lon) float64 -2.197 -2.184 ... -2.561 nan\n",
       "    SoilMoi_depth2_inst  (time, lat, lon) float64 -15.17 -5.777 ... -12.08 nan\n",
       "    SoilMoi_depth3_inst  (time, lat, lon) float64 0.4509 1.31 nan ... 0.7597 nan\n",
       "Attributes: (12/19)\n",
       "    CDI:                    Climate Data Interface version 1.9.8 (https://mpi...\n",
       "    Conventions:            CF-1.6\n",
       "    history:                created on date: 2020-02-03T12:00:52.166\n",
       "    source:                 VIC_v4.1.2 forced with GDAS-AGRMET-GPCPv13rA1\n",
       "    institution:            NASA GSFC\n",
       "    missing_value:          -9999.0\n",
       "    ...                     ...\n",
       "    MAP_PROJECTION:         EQUIDISTANT CYLINDRICAL\n",
       "    SOUTH_WEST_CORNER_LAT:  -59.5\n",
       "    SOUTH_WEST_CORNER_LON:  -179.5\n",
       "    DX:                     1.0\n",
       "    DY:                     1.0\n",
       "    CDO:                    Climate Data Operators version 1.9.8 (https://mpi..."
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "gldas_vic_anomalies"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "07a7ef24-32f3-4d14-a5f2-df6fbd91c969",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Declare TWS variables that need to be summed\n",
    "\n",
    "clsm_tws_variables = ['SWE_inst', 'CanopInt_inst', 'SoilMoist_P_inst']\n",
    "\n",
    "noah_tws_variables = ['SWE_inst', 'CanopInt_inst', 'SoilMoi0_10cm_inst',\n",
    "                      'SoilMoi10_40cm_inst', 'SoilMoi40_100cm_inst',\n",
    "                      'SoilMoi100_200cm_inst'\n",
    "                     ]\n",
    "\n",
    "vic_tws_variables = ['SWE_inst', 'CanopInt_inst', \n",
    "                     'SoilMoi0_30cm_inst', 'SoilMoi_depth2_inst',\n",
    "                     'SoilMoi_depth3_inst'\n",
    "                    ]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "d17468c4-81c5-4f9e-b956-50aaae88eb16",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Declare Surface Water Variables\n",
    "clsm_sw_variables = ['SWE_inst', 'CanopInt_inst']\n",
    "\n",
    "noah_sw_variables = ['SWE_inst', 'CanopInt_inst']\n",
    "\n",
    "vic_sw_variables = ['SWE_inst', 'CanopInt_inst']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "a141f506-24f6-4670-8483-d5120a1ce6c7",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Declare Snow Water Equivalent Variables\n",
    "clsm_swe_variables = ['SWE_inst']\n",
    "\n",
    "noah_swe_variables = ['SWE_inst']\n",
    "\n",
    "vic_swe_variables = ['SWE_inst']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "f941f632-a56d-4fd9-9766-820b12e7eb34",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Declare Canopy Variables\n",
    "clsm_canopy_variables = ['CanopInt_inst']\n",
    "\n",
    "noah_canopy_variables = ['CanopInt_inst']\n",
    "\n",
    "vic_canopy_variables = ['CanopInt_inst']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "10f6fd4c-be44-43b5-bf73-460e1ff16f21",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Declare Soil Moisture variables\n",
    "clsm_sm_variables = ['SoilMoist_P_inst']\n",
    "\n",
    "noah_sm_variables = ['SoilMoi0_10cm_inst', 'SoilMoi10_40cm_inst', 'SoilMoi40_100cm_inst',\n",
    "                      'SoilMoi100_200cm_inst']\n",
    "\n",
    "vic_sm_variables = ['SoilMoi0_30cm_inst', 'SoilMoi_depth2_inst', 'SoilMoi_depth3_inst']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "e8aa01e4-3f02-4a67-87a5-355697806b64",
   "metadata": {},
   "outputs": [],
   "source": [
    "def aggregate_gldas_anomalies(clsm_variables, noah_variables, vic_variables, variable_name):\n",
    "    clsm_ds = gldas_clsm_anomalies[clsm_variables].to_array().sum('variable').to_dataset(name=variable_name)\n",
    "    noah_ds = gldas_noah_anomalies[noah_variables].to_array().sum('variable').to_dataset(name=variable_name)\n",
    "    vic_ds = gldas_vic_anomalies[vic_variables].to_array().sum('variable').to_dataset(name=variable_name)\n",
    "    # create a new dataset with all the model tws mean values\n",
    "    # returns a single value at each time step\n",
    "    model_ds = xr.Dataset({\n",
    "        'clsm': clsm_ds[variable_name].mean(['lat', 'lon']),\n",
    "        'noah': noah_ds[variable_name].mean(['lat', 'lon']),\n",
    "        'vic': vic_ds[variable_name].mean(['lat', 'lon'])\n",
    "    })\n",
    "    # calculate the TWS mean and stddev across the three models\n",
    "    model_mean = model_ds.to_array().mean('variable').values\n",
    "    model_std = model_ds.to_array().std('variable').values\n",
    "    \n",
    "    # create a final netcdf array with the mean and std values\n",
    "    final_ds = (xr.Dataset(data_vars={f'mean_{variable_name}': ([\"time\"], model_mean),\n",
    "                                      f'std_{variable_name}': ([\"time\"], model_std)\n",
    "                                     },\n",
    "                           coords={\"time\":vic_ds.coords['time']})\n",
    "                .expand_dims(lat=len(vic_ds.coords['lat']), lon=len(vic_ds.coords['lon']))\n",
    "                .assign_coords(lat=vic_ds.coords['lat'], lon=vic_ds.coords['lon']))\n",
    "    return final_ds"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "5b28633f-a09f-40f3-89e9-07f907f6b9a0",
   "metadata": {},
   "outputs": [],
   "source": [
    "final_tws_ds = aggregate_gldas_anomalies(clsm_tws_variables, noah_tws_variables, vic_tws_variables, 'tws')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "1939c10e-8af0-4c51-8403-01d6268530fd",
   "metadata": {},
   "outputs": [],
   "source": [
    "final_sw_ds = aggregate_gldas_anomalies(clsm_sw_variables, noah_sw_variables, vic_sw_variables, 'sw')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "73428bf1-ed82-49b3-b0f7-2da7d2390692",
   "metadata": {},
   "outputs": [],
   "source": [
    "final_sm_ds = aggregate_gldas_anomalies(clsm_sm_variables, noah_sm_variables, vic_sm_variables, 'sm')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "81ca0d59-6fe5-4dab-b0a6-c7986a8bcb32",
   "metadata": {},
   "outputs": [],
   "source": [
    "final_canopy_ds = aggregate_gldas_anomalies(clsm_canopy_variables, noah_canopy_variables, vic_canopy_variables, 'canopy')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "c035c273-0c36-480d-8c7a-6ec8ab1c34e1",
   "metadata": {},
   "outputs": [],
   "source": [
    "final_swe_ds = aggregate_gldas_anomalies(clsm_swe_variables, noah_swe_variables, vic_swe_variables, 'swe')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "d8223d84-4a5c-476f-ba71-9e85dfe63135",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "    <tr>\n",
       "      <th>249</th>\n",
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       "  </tbody>\n",
       "</table>\n",
       "<p>253 rows × 2 columns</p>\n",
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      "text/plain": [
       "          time   mean_tws\n",
       "0   2000-01-01  -3.761522\n",
       "1   2000-02-01  -7.612675\n",
       "2   2000-03-01 -12.655033\n",
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       "4   2000-05-01  -8.470782\n",
       "..         ...        ...\n",
       "248 2020-09-01  15.017552\n",
       "249 2020-10-01  13.221290\n",
       "250 2020-11-01   5.768155\n",
       "251 2020-12-01   0.015571\n",
       "252 2021-01-01  -4.987467\n",
       "\n",
       "[253 rows x 2 columns]"
      ]
     },
     "execution_count": 29,
     "metadata": {},
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    }
   ],
   "source": [
    "tws_df = final_tws_ds.mean_tws.to_dataframe().reset_index()[['time', 'mean_tws']].drop_duplicates()\n",
    "tws_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "8ab44f8d-a3c0-40be-aefb-a29fdf33f2ce",
   "metadata": {},
   "outputs": [
    {
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       "          time   std_tws\n",
       "0   2000-01-01  2.038648\n",
       "1   2000-02-01  1.773507\n",
       "2   2000-03-01  2.230922\n",
       "3   2000-04-01  4.142180\n",
       "4   2000-05-01  6.261489\n",
       "..         ...       ...\n",
       "248 2020-09-01  2.478384\n",
       "249 2020-10-01  4.363169\n",
       "250 2020-11-01  4.192047\n",
       "251 2020-12-01  3.194324\n",
       "252 2021-01-01  2.409556\n",
       "\n",
       "[253 rows x 2 columns]"
      ]
     },
     "execution_count": 30,
     "metadata": {},
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    }
   ],
   "source": [
    "tws_std_df = final_tws_ds.std_tws.to_dataframe().reset_index()[['time', 'std_tws']].drop_duplicates()\n",
    "tws_std_df"
   ]
  },
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   "execution_count": 31,
   "id": "bcb65bc7-baf5-4cae-9292-191434ff9c01",
   "metadata": {},
   "outputs": [
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       "          time    std_sm\n",
       "0   2000-01-01  2.037270\n",
       "1   2000-02-01  1.774064\n",
       "2   2000-03-01  2.233062\n",
       "3   2000-04-01  4.141858\n",
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       "248 2020-09-01  2.481580\n",
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     "execution_count": 31,
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   ],
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    "sm_std_df = final_sm_ds.std_sm.to_dataframe().reset_index()[['time', 'std_sm']].drop_duplicates()\n",
    "sm_std_df"
   ]
  },
  {
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   "execution_count": 32,
   "id": "43c72671-5c85-4586-bed2-a3590f3f8c61",
   "metadata": {},
   "outputs": [
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       "          time    std_sw\n",
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     "execution_count": 32,
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    "sw_std_df"
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       "          time  std_canopy\n",
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       "2   2000-03-01    0.002144\n",
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  {
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   "id": "83abe4e9-018e-43a9-817f-ed91e1ec00c3",
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   "source": [
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   "execution_count": 35,
   "id": "11aa0ed9-15a2-497d-95a7-0840861cc219",
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    "# Open GRACE netcdf file\n",
    "grace_ds = xr.open_dataset(os.path.join(grace_dir, 'latest_jpl_grace.nc'))[['lwe_thickness', 'uncertainty']]"
   ]
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   "execution_count": 36,
   "id": "4f72263b-8e67-43d5-b20f-072cfa2f6eb5",
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   "source": [
    "# Clipping the grace ds to utah shapefile\n",
    "ds = grace_ds.copy()\n",
    "ds = ds.assign({\"lon\": (((ds.lon + 180) % 360) - 180)}).sortby('lon')\n",
    "ds['lwe_thickness'] = ds['lwe_thickness'].rio.write_crs(\"epsg:4326\")\n",
    "ds['uncertainty'] = ds['uncertainty'].rio.write_crs(\"epsg:4326\")\n",
    "ds.rio.set_spatial_dims(x_dim=\"lon\", y_dim=\"lat\", inplace=True)\n",
    "grace_clipped = ds.rio.clip(gdf.geometry.apply(mapping), gdf.crs, drop=True)"
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   "execution_count": 37,
   "id": "5b33cd34-9443-4e5e-9169-502950b3ebd1",
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       ".xr-var-item > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-even);\n",
       "  margin-bottom: 0;\n",
       "}\n",
       "\n",
       ".xr-var-item > .xr-var-name:hover span {\n",
       "  padding-right: 5px;\n",
       "}\n",
       "\n",
       ".xr-var-list > li:nth-child(odd) > div,\n",
       ".xr-var-list > li:nth-child(odd) > label,\n",
       ".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-odd);\n",
       "}\n",
       "\n",
       ".xr-var-name {\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-var-dims {\n",
       "  grid-column: 2;\n",
       "}\n",
       "\n",
       ".xr-var-dtype {\n",
       "  grid-column: 3;\n",
       "  text-align: right;\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-var-preview {\n",
       "  grid-column: 4;\n",
       "}\n",
       "\n",
       ".xr-var-name,\n",
       ".xr-var-dims,\n",
       ".xr-var-dtype,\n",
       ".xr-preview,\n",
       ".xr-attrs dt {\n",
       "  white-space: nowrap;\n",
       "  overflow: hidden;\n",
       "  text-overflow: ellipsis;\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-var-name:hover,\n",
       ".xr-var-dims:hover,\n",
       ".xr-var-dtype:hover,\n",
       ".xr-attrs dt:hover {\n",
       "  overflow: visible;\n",
       "  width: auto;\n",
       "  z-index: 1;\n",
       "}\n",
       "\n",
       ".xr-var-attrs,\n",
       ".xr-var-data {\n",
       "  display: none;\n",
       "  background-color: var(--xr-background-color) !important;\n",
       "  padding-bottom: 5px !important;\n",
       "}\n",
       "\n",
       ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
       ".xr-var-data-in:checked ~ .xr-var-data {\n",
       "  display: block;\n",
       "}\n",
       "\n",
       ".xr-var-data > table {\n",
       "  float: right;\n",
       "}\n",
       "\n",
       ".xr-var-name span,\n",
       ".xr-var-data,\n",
       ".xr-attrs {\n",
       "  padding-left: 25px !important;\n",
       "}\n",
       "\n",
       ".xr-attrs,\n",
       ".xr-var-attrs,\n",
       ".xr-var-data {\n",
       "  grid-column: 1 / -1;\n",
       "}\n",
       "\n",
       "dl.xr-attrs {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  display: grid;\n",
       "  grid-template-columns: 125px auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt,\n",
       ".xr-attrs dd {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  float: left;\n",
       "  padding-right: 10px;\n",
       "  width: auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt {\n",
       "  font-weight: normal;\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-attrs dt:hover span {\n",
       "  display: inline-block;\n",
       "  background: var(--xr-background-color);\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-attrs dd {\n",
       "  grid-column: 2;\n",
       "  white-space: pre-wrap;\n",
       "  word-break: break-all;\n",
       "}\n",
       "\n",
       ".xr-icon-database,\n",
       ".xr-icon-file-text2 {\n",
       "  display: inline-block;\n",
       "  vertical-align: middle;\n",
       "  width: 1em;\n",
       "  height: 1.5em !important;\n",
       "  stroke-width: 0;\n",
       "  stroke: currentColor;\n",
       "  fill: currentColor;\n",
       "}\n",
       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt;\n",
       "Dimensions:        (lat: 5, lon: 4, time: 195)\n",
       "Coordinates:\n",
       "  * lat            (lat) float64 24.25 24.75 25.25 25.75 26.25\n",
       "  * lon            (lon) float64 88.25 88.75 89.25 89.75\n",
       "  * time           (time) datetime64[ns] 2002-04-17T12:00:00 ... 2021-03-16T1...\n",
       "    WGS84          int64 0\n",
       "Data variables:\n",
       "    lwe_thickness  (time, lat, lon) float64 nan -11.94 -14.36 ... -55.73 nan nan\n",
       "    uncertainty    (time, lat, lon) float64 nan 22.89 22.97 ... 11.68 nan nan\n",
       "Attributes: (12/53)\n",
       "    Conventions:                   CF-1.6, ACDD-1.3, ISO 8601\n",
       "    Metadata_Conventions:          Unidata Dataset Discovery v1.0\n",
       "    standard_name_vocabulary:      NetCDF Climate and Forecast (CF) Metadata ...\n",
       "    title:                         JPL GRACE and GRACE-FO MASCON RL06Mv2 CRI\n",
       "    summary:                       Monthly gravity solutions from GRACE and G...\n",
       "    keywords:                      Solid Earth, Geodetics/Gravity, Gravity, l...\n",
       "    ...                            ...\n",
       "    C_30_substitution:             TN-14; Loomis et al., 2019, Geophys. Res. ...\n",
       "    user_note_1:                   The accelerometer on the GRACE-B spacecraf...\n",
       "    user_note_2:                   The accelerometer on the GRACE-D spacecraf...\n",
       "    journal_reference:             Watkins, M. M., D. N. Wiese, D.-N. Yuan, C...\n",
       "    CRI_filter_journal_reference:  Wiese, D. N., F. W. Landerer, and M. M. Wa...\n",
       "    date_created:                  2021-04-27T21:04:06Z</pre><div class='xr-wrap' hidden><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-6b9a2af3-34c6-45da-9da0-6e8c0af5ad7b' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-6b9a2af3-34c6-45da-9da0-6e8c0af5ad7b' 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'>lat</span>: 5</li><li><span class='xr-has-index'>lon</span>: 4</li><li><span class='xr-has-index'>time</span>: 195</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-a0a7ae61-8d49-4956-8e4b-923501558f2f' class='xr-section-summary-in' type='checkbox'  checked><label for='section-a0a7ae61-8d49-4956-8e4b-923501558f2f' class='xr-section-summary' >Coordinates: <span>(4)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lat</span></div><div class='xr-var-dims'>(lat)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>24.25 24.75 25.25 25.75 26.25</div><input id='attrs-d7a6ac0d-3603-44e3-bb03-5044661533c9' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d7a6ac0d-3603-44e3-bb03-5044661533c9' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2332a80e-6a91-4890-97e7-5b4b27b9209b' class='xr-var-data-in' type='checkbox'><label for='data-2332a80e-6a91-4890-97e7-5b4b27b9209b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>long_name :</span></dt><dd>latitude</dd><dt><span>standard_name :</span></dt><dd>latitude</dd><dt><span>axis :</span></dt><dd>Y</dd><dt><span>valid_min :</span></dt><dd>-89.75</dd><dt><span>valid_max :</span></dt><dd>89.75</dd><dt><span>bounds :</span></dt><dd>lat_bounds</dd></dl></div><div class='xr-var-data'><pre>array([24.25, 24.75, 25.25, 25.75, 26.25])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lon</span></div><div class='xr-var-dims'>(lon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>88.25 88.75 89.25 89.75</div><input id='attrs-0d5124bd-7b5b-4edc-b266-5a8555c00124' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-0d5124bd-7b5b-4edc-b266-5a8555c00124' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b9f30867-941d-4e0d-a631-db1bde36485c' class='xr-var-data-in' type='checkbox'><label for='data-b9f30867-941d-4e0d-a631-db1bde36485c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>axis :</span></dt><dd>X</dd><dt><span>long_name :</span></dt><dd>longitude</dd><dt><span>standard_name :</span></dt><dd>longitude</dd><dt><span>units :</span></dt><dd>degrees_east</dd></dl></div><div class='xr-var-data'><pre>array([88.25, 88.75, 89.25, 89.75])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2002-04-17T12:00:00 ... 2021-03-...</div><input id='attrs-e14c9656-9f4e-4428-8f15-9816e03cfb1f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e14c9656-9f4e-4428-8f15-9816e03cfb1f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-99abc82b-f59c-4a97-9de1-99b145c12a70' class='xr-var-data-in' type='checkbox'><label for='data-99abc82b-f59c-4a97-9de1-99b145c12a70' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>time</dd><dt><span>standard_name :</span></dt><dd>time</dd><dt><span>axis :</span></dt><dd>T</dd><dt><span>bounds :</span></dt><dd>time_bounds</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;2002-04-17T12:00:00.000000000&#x27;, &#x27;2002-05-10T12:00:00.000000000&#x27;,\n",
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       "       &#x27;2002-10-16T12:00:00.000000000&#x27;, &#x27;2002-11-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;2002-12-16T12:00:00.000000000&#x27;, &#x27;2003-01-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;2003-02-15T00:00:00.000000000&#x27;, &#x27;2003-03-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;2003-04-16T00:00:00.000000000&#x27;, &#x27;2003-05-11T12:00:00.000000000&#x27;,\n",
       "       &#x27;2003-07-16T12:00:00.000000000&#x27;, &#x27;2003-08-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;2003-09-16T00:00:00.000000000&#x27;, &#x27;2003-10-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;2003-11-16T00:00:00.000000000&#x27;, &#x27;2003-12-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;2004-01-07T12:00:00.000000000&#x27;, &#x27;2004-02-17T00:00:00.000000000&#x27;,\n",
       "       &#x27;2004-03-16T12:00:00.000000000&#x27;, &#x27;2004-04-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;2004-05-16T12:00:00.000000000&#x27;, &#x27;2004-06-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;2004-07-16T12:00:00.000000000&#x27;, &#x27;2004-08-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;2004-09-16T00:00:00.000000000&#x27;, &#x27;2004-10-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;2004-11-16T00:00:00.000000000&#x27;, &#x27;2004-12-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;2005-01-16T12:00:00.000000000&#x27;, &#x27;2005-02-15T00:00:00.000000000&#x27;,\n",
       "       &#x27;2005-03-16T12:00:00.000000000&#x27;, &#x27;2005-04-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;2005-05-16T12:00:00.000000000&#x27;, &#x27;2005-06-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;2005-07-16T12:00:00.000000000&#x27;, &#x27;2005-08-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;2005-09-16T00:00:00.000000000&#x27;, &#x27;2005-10-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;2005-11-16T00:00:00.000000000&#x27;, &#x27;2005-12-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;2006-01-16T12:00:00.000000000&#x27;, &#x27;2006-02-15T00:00:00.000000000&#x27;,\n",
       "       &#x27;2006-03-16T12:00:00.000000000&#x27;, &#x27;2006-04-16T00:00:00.000000000&#x27;,\n",
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       "       &#x27;2006-07-16T12:00:00.000000000&#x27;, &#x27;2006-08-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;2006-09-16T00:00:00.000000000&#x27;, &#x27;2006-10-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;2006-11-16T00:00:00.000000000&#x27;, &#x27;2006-12-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;2007-01-16T12:00:00.000000000&#x27;, &#x27;2007-02-15T00:00:00.000000000&#x27;,\n",
       "       &#x27;2007-03-16T12:00:00.000000000&#x27;, &#x27;2007-04-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;2007-05-16T12:00:00.000000000&#x27;, &#x27;2007-06-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;2007-07-16T12:00:00.000000000&#x27;, &#x27;2007-08-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;2007-09-16T00:00:00.000000000&#x27;, &#x27;2007-10-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;2007-11-16T00:00:00.000000000&#x27;, &#x27;2007-12-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;2008-01-16T12:00:00.000000000&#x27;, &#x27;2008-02-15T12:00:00.000000000&#x27;,\n",
       "       &#x27;2008-03-16T12:00:00.000000000&#x27;, &#x27;2008-04-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;2008-05-16T12:00:00.000000000&#x27;, &#x27;2008-06-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;2008-07-16T12:00:00.000000000&#x27;, &#x27;2008-08-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;2008-09-16T00:00:00.000000000&#x27;, &#x27;2008-10-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;2008-11-16T00:00:00.000000000&#x27;, &#x27;2008-12-16T12:00:00.000000000&#x27;,\n",
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       "       &#x27;2009-03-16T12:00:00.000000000&#x27;, &#x27;2009-04-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;2009-05-16T12:00:00.000000000&#x27;, &#x27;2009-06-16T00:00:00.000000000&#x27;,\n",
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       "       &#x27;2010-05-16T12:00:00.000000000&#x27;, &#x27;2010-06-16T00:00:00.000000000&#x27;,\n",
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       "       &#x27;2015-08-16T12:00:00.000000000&#x27;, &#x27;2015-09-14T12:00:00.000000000&#x27;,\n",
       "       &#x27;2015-12-23T12:00:00.000000000&#x27;, &#x27;2016-01-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;2016-02-14T00:00:00.000000000&#x27;, &#x27;2016-03-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;2016-05-20T00:00:00.000000000&#x27;, &#x27;2016-06-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;2016-07-15T12:00:00.000000000&#x27;, &#x27;2016-08-21T12:00:00.000000000&#x27;,\n",
       "       &#x27;2016-11-27T12:00:00.000000000&#x27;, &#x27;2016-12-24T12:00:00.000000000&#x27;,\n",
       "       &#x27;2017-01-21T00:00:00.000000000&#x27;, &#x27;2017-03-31T12:00:00.000000000&#x27;,\n",
       "       &#x27;2017-04-24T12:00:00.000000000&#x27;, &#x27;2017-05-12T12:00:00.000000000&#x27;,\n",
       "       &#x27;2017-06-11T00:00:00.000000000&#x27;, &#x27;2018-06-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;2018-07-10T00:00:00.000000000&#x27;, &#x27;2018-10-31T12:00:00.000000000&#x27;,\n",
       "       &#x27;2018-11-16T00:00:00.000000000&#x27;, &#x27;2018-12-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;2019-01-16T12:00:00.000000000&#x27;, &#x27;2019-02-14T00:00:00.000000000&#x27;,\n",
       "       &#x27;2019-03-16T12:00:00.000000000&#x27;, &#x27;2019-04-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;2019-05-16T12:00:00.000000000&#x27;, &#x27;2019-06-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;2019-07-16T12:00:00.000000000&#x27;, &#x27;2019-08-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;2019-09-16T00:00:00.000000000&#x27;, &#x27;2019-10-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;2019-11-16T00:00:00.000000000&#x27;, &#x27;2019-12-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;2020-01-16T12:00:00.000000000&#x27;, &#x27;2020-02-15T12:00:00.000000000&#x27;,\n",
       "       &#x27;2020-03-16T12:00:00.000000000&#x27;, &#x27;2020-04-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;2020-05-16T12:00:00.000000000&#x27;, &#x27;2020-06-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;2020-07-16T12:00:00.000000000&#x27;, &#x27;2020-08-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;2020-09-16T00:00:00.000000000&#x27;, &#x27;2020-10-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;2020-11-16T00:00:00.000000000&#x27;, &#x27;2020-12-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;2021-01-16T12:00:00.000000000&#x27;, &#x27;2021-02-15T00:00:00.000000000&#x27;,\n",
       "       &#x27;2021-03-16T12:00:00.000000000&#x27;], dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>WGS84</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-90387456-c6fe-45b2-983e-7a486becb67f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-90387456-c6fe-45b2-983e-7a486becb67f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e3f993a5-6b4f-4e3c-8046-e31e2d39e038' class='xr-var-data-in' type='checkbox'><label for='data-e3f993a5-6b4f-4e3c-8046-e31e2d39e038' 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>GEOGCS[&quot;WGS 84&quot;,DATUM[&quot;WGS_1984&quot;,SPHEROID[&quot;WGS 84&quot;,6378137,298.257223563,AUTHORITY[&quot;EPSG&quot;,&quot;7030&quot;]],AUTHORITY[&quot;EPSG&quot;,&quot;6326&quot;]],PRIMEM[&quot;Greenwich&quot;,0,AUTHORITY[&quot;EPSG&quot;,&quot;8901&quot;]],UNIT[&quot;degree&quot;,0.0174532925199433,AUTHORITY[&quot;EPSG&quot;,&quot;9122&quot;]],AXIS[&quot;Latitude&quot;,NORTH],AXIS[&quot;Longitude&quot;,EAST],AUTHORITY[&quot;EPSG&quot;,&quot;4326&quot;]]</dd><dt><span>semi_major_axis :</span></dt><dd>6378137.0</dd><dt><span>semi_minor_axis :</span></dt><dd>6356752.314245179</dd><dt><span>inverse_flattening :</span></dt><dd>298.257223563</dd><dt><span>reference_ellipsoid_name :</span></dt><dd>WGS 84</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>WGS 84</dd><dt><span>grid_mapping_name :</span></dt><dd>latitude_longitude</dd><dt><span>spatial_ref :</span></dt><dd>GEOGCS[&quot;WGS 84&quot;,DATUM[&quot;WGS_1984&quot;,SPHEROID[&quot;WGS 84&quot;,6378137,298.257223563,AUTHORITY[&quot;EPSG&quot;,&quot;7030&quot;]],AUTHORITY[&quot;EPSG&quot;,&quot;6326&quot;]],PRIMEM[&quot;Greenwich&quot;,0,AUTHORITY[&quot;EPSG&quot;,&quot;8901&quot;]],UNIT[&quot;degree&quot;,0.0174532925199433,AUTHORITY[&quot;EPSG&quot;,&quot;9122&quot;]],AXIS[&quot;Latitude&quot;,NORTH],AXIS[&quot;Longitude&quot;,EAST],AUTHORITY[&quot;EPSG&quot;,&quot;4326&quot;]]</dd><dt><span>GeoTransform :</span></dt><dd>88.0 0.5 0.0 24.0 0.0 0.5</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-64e06d93-9570-42c8-a037-7cda26e0c7a5' class='xr-section-summary-in' type='checkbox'  checked><label for='section-64e06d93-9570-42c8-a037-7cda26e0c7a5' class='xr-section-summary' >Data variables: <span>(2)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>lwe_thickness</span></div><div class='xr-var-dims'>(time, lat, lon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan -11.94 -14.36 ... nan nan</div><input id='attrs-584e8847-697d-40b2-99cf-019dae6230ea' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-584e8847-697d-40b2-99cf-019dae6230ea' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4b0343d5-b00e-4f99-bde8-68fdb3eb81e3' class='xr-var-data-in' type='checkbox'><label for='data-4b0343d5-b00e-4f99-bde8-68fdb3eb81e3' 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>cm</dd><dt><span>long_name :</span></dt><dd>Liquid_Water_Equivalent_Thickness</dd><dt><span>standard_name :</span></dt><dd>Liquid_Water_Equivalent_Thickness</dd><dt><span>grid_mapping :</span></dt><dd>WGS84</dd><dt><span>valid_min :</span></dt><dd>-1772.1489773088445</dd><dt><span>valid_max :</span></dt><dd>767.7368277116782</dd><dt><span>comment :</span></dt><dd>Coastline Resolution Improvement (CRI) filter is applied</dd></dl></div><div class='xr-var-data'><pre>array([[[         nan, -11.94018736, -14.36499903, -14.36499903],\n",
       "        [-11.94018736, -11.94018736, -14.36499903, -14.36499903],\n",
       "        [         nan,          nan, -14.36499903, -14.36499903],\n",
       "        [         nan,  -4.51591578,  -4.51591578,  -4.51591578],\n",
       "        [         nan,  -4.51591578,          nan,          nan]],\n",
       "\n",
       "       [[         nan,  -9.1974171 ,  -8.73952681,  -8.73952681],\n",
       "        [ -9.1974171 ,  -9.1974171 ,  -8.73952681,  -8.73952681],\n",
       "        [         nan,          nan,  -8.73952681,  -8.73952681],\n",
       "        [         nan,   2.26790787,   2.26790787,   2.26790787],\n",
       "        [         nan,   2.26790787,          nan,          nan]],\n",
       "\n",
       "       [[         nan,  34.96501532,  40.48118844,  40.48118844],\n",
       "        [ 34.96501532,  34.96501532,  40.48118844,  40.48118844],\n",
       "        [         nan,          nan,  40.48118844,  40.48118844],\n",
       "        [         nan,  46.84133128,  46.84133128,  46.84133128],\n",
       "        [         nan,  46.84133128,          nan,          nan]],\n",
       "\n",
       "       ...,\n",
       "\n",
       "       [[         nan,  -9.43841032,  -4.18955521,  -4.18955521],\n",
       "        [ -9.43841032,  -9.43841032,  -4.18955521,  -4.18955521],\n",
       "        [         nan,          nan,  -4.18955521,  -4.18955521],\n",
       "        [         nan, -50.30981117, -50.30981117, -50.30981117],\n",
       "        [         nan, -50.30981117,          nan,          nan]],\n",
       "\n",
       "       [[         nan, -18.35521449, -10.72662746, -10.72662746],\n",
       "        [-18.35521449, -18.35521449, -10.72662746, -10.72662746],\n",
       "        [         nan,          nan, -10.72662746, -10.72662746],\n",
       "        [         nan, -56.0383663 , -56.0383663 , -56.0383663 ],\n",
       "        [         nan, -56.0383663 ,          nan,          nan]],\n",
       "\n",
       "       [[         nan, -27.2759952 , -16.98597545, -16.98597545],\n",
       "        [-27.2759952 , -27.2759952 , -16.98597545, -16.98597545],\n",
       "        [         nan,          nan, -16.98597545, -16.98597545],\n",
       "        [         nan, -55.7299579 , -55.7299579 , -55.7299579 ],\n",
       "        [         nan, -55.7299579 ,          nan,          nan]]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>uncertainty</span></div><div class='xr-var-dims'>(time, lat, lon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>nan 22.89 22.97 ... 11.68 nan nan</div><input id='attrs-a6fbd623-4a78-4237-8303-814d13c7cbda' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a6fbd623-4a78-4237-8303-814d13c7cbda' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ac739eb9-0954-438d-b95e-e5c6dbe470b2' class='xr-var-data-in' type='checkbox'><label for='data-ac739eb9-0954-438d-b95e-e5c6dbe470b2' 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>cm</dd><dt><span>long_name :</span></dt><dd>uncertainty</dd><dt><span>standard_name :</span></dt><dd>uncertainty</dd><dt><span>grid_mapping :</span></dt><dd>WGS84</dd><dt><span>valid_min :</span></dt><dd>0.1586236479248768</dd><dt><span>valid_max :</span></dt><dd>53.34469598560085</dd><dt><span>comment :</span></dt><dd>1-sigma uncertainty: not for each 0.5 degree grid cell, but for each 3-degree mascon estimate</dd></dl></div><div class='xr-var-data'><pre>array([[[        nan, 22.88781746, 22.970621  , 22.970621  ],\n",
       "        [22.88781746, 22.88781746, 22.970621  , 22.970621  ],\n",
       "        [        nan,         nan, 22.970621  , 22.970621  ],\n",
       "        [        nan, 16.11850607, 16.11850607, 16.11850607],\n",
       "        [        nan, 16.11850607,         nan,         nan]],\n",
       "\n",
       "       [[        nan, 11.58461565, 13.84303503, 13.84303503],\n",
       "        [11.58461565, 11.58461565, 13.84303503, 13.84303503],\n",
       "        [        nan,         nan, 13.84303503, 13.84303503],\n",
       "        [        nan,  8.82634613,  8.82634613,  8.82634613],\n",
       "        [        nan,  8.82634613,         nan,         nan]],\n",
       "\n",
       "       [[        nan,  8.5030887 , 10.70921288, 10.70921288],\n",
       "        [ 8.5030887 ,  8.5030887 , 10.70921288, 10.70921288],\n",
       "        [        nan,         nan, 10.70921288, 10.70921288],\n",
       "        [        nan,  6.72845995,  6.72845995,  6.72845995],\n",
       "        [        nan,  6.72845995,         nan,         nan]],\n",
       "\n",
       "       ...,\n",
       "\n",
       "       [[        nan,  9.81802383, 12.12489983, 12.12489983],\n",
       "        [ 9.81802383,  9.81802383, 12.12489983, 12.12489983],\n",
       "        [        nan,         nan, 12.12489983, 12.12489983],\n",
       "        [        nan,  8.08193173,  8.08193173,  8.08193173],\n",
       "        [        nan,  8.08193173,         nan,         nan]],\n",
       "\n",
       "       [[        nan, 12.00826813, 14.92740054, 14.92740054],\n",
       "        [12.00826813, 12.00826813, 14.92740054, 14.92740054],\n",
       "        [        nan,         nan, 14.92740054, 14.92740054],\n",
       "        [        nan,  9.87491097,  9.87491097,  9.87491097],\n",
       "        [        nan,  9.87491097,         nan,         nan]],\n",
       "\n",
       "       [[        nan, 14.23089245, 17.64399448, 17.64399448],\n",
       "        [14.23089245, 14.23089245, 17.64399448, 17.64399448],\n",
       "        [        nan,         nan, 17.64399448, 17.64399448],\n",
       "        [        nan, 11.6800812 , 11.6800812 , 11.6800812 ],\n",
       "        [        nan, 11.6800812 ,         nan,         nan]]])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-d7538664-1a5f-4216-a1e1-39a6b8a97f78' class='xr-section-summary-in' type='checkbox'  ><label for='section-d7538664-1a5f-4216-a1e1-39a6b8a97f78' class='xr-section-summary' >Attributes: <span>(53)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>Conventions :</span></dt><dd>CF-1.6, ACDD-1.3, ISO 8601</dd><dt><span>Metadata_Conventions :</span></dt><dd>Unidata Dataset Discovery v1.0</dd><dt><span>standard_name_vocabulary :</span></dt><dd>NetCDF Climate and Forecast (CF) Metadata Convention-1.6</dd><dt><span>title :</span></dt><dd>JPL GRACE and GRACE-FO MASCON RL06Mv2 CRI</dd><dt><span>summary :</span></dt><dd>Monthly gravity solutions from GRACE and GRACE-FO as determined from the JPL RL06Mv2 mascon solution - with CRI filter applied</dd><dt><span>keywords :</span></dt><dd>Solid Earth, Geodetics/Gravity, Gravity, liquid_water_equivalent_thickness</dd><dt><span>keywords_vocabulary :</span></dt><dd>NASA Global Change Master Directory (GCMD) Science Keywords</dd><dt><span>platform :</span></dt><dd>GRACE and GRACE-FO</dd><dt><span>institution :</span></dt><dd>NASA/JPL</dd><dt><span>creator_name :</span></dt><dd>David Wiese</dd><dt><span>creator_email :</span></dt><dd>grace@podaac.jpl.nasa.gov</dd><dt><span>creator_url :</span></dt><dd>https://grace.jpl.nasa.gov</dd><dt><span>creator_type :</span></dt><dd>group</dd><dt><span>creator_institution :</span></dt><dd>NASA/JPL</dd><dt><span>publisher_name :</span></dt><dd>Physical Oceanography Distributed Active Archive Center</dd><dt><span>publisher_email :</span></dt><dd>podaac@jpl.nasa.gov</dd><dt><span>publisher_url :</span></dt><dd>https://podaac.jpl.nasa.gov</dd><dt><span>publisher_type :</span></dt><dd>group</dd><dt><span>publisher_institution :</span></dt><dd>NASA/JPL</dd><dt><span>project :</span></dt><dd>NASA Gravity Recovery and Climate Experiment (GRACE) and NASA Gravity Recovery and Climate Experiment Follow-On (GRACE-FO)</dd><dt><span>program :</span></dt><dd>NASA Earth Science System Pathfinder and NASA Earth Systematic Missions Program</dd><dt><span>id :</span></dt><dd>10.5067/TEMSC-3JC62</dd><dt><span>naming_authority :</span></dt><dd>org.doi.dx</dd><dt><span>source :</span></dt><dd>GRACE and GRACE-FO JPL RL06Mv2-CRI</dd><dt><span>processing_level :</span></dt><dd>2 and 3</dd><dt><span>acknowledgement :</span></dt><dd>GRACE is a joint mission of NASA (USA) and DLR (Germany).  GRACE-FO is a joint mission of NASA (USA) and the German Research Center for Geosciences (GFZ).  Use the digital object identifier provided in the id attribute when citing this data.  See https://podaac.jpl.nasa.gov/CitingPODAAC</dd><dt><span>license :</span></dt><dd>https://science.nasa.gov/earth-science/earth-science-data/data-information-policy</dd><dt><span>product_version :</span></dt><dd>v2.0</dd><dt><span>time_epoch :</span></dt><dd>2002-01-01T00:00:00Z</dd><dt><span>time_coverage_start :</span></dt><dd>2002-04-16T00:00:00Z</dd><dt><span>time_coverage_end :</span></dt><dd>2021-03-16T23:59:59Z</dd><dt><span>geospatial_lat_min :</span></dt><dd>-89.75</dd><dt><span>geospatial_lat_max :</span></dt><dd>89.75</dd><dt><span>geospatial_lat_units :</span></dt><dd>degrees_north</dd><dt><span>geospatial_lat_resolution :</span></dt><dd>0.5 degree grid; however the native resolution of the data is 3-degree equal-area mascons</dd><dt><span>geospatial_lon_min :</span></dt><dd>0.25</dd><dt><span>geospatial_lon_max :</span></dt><dd>359.75</dd><dt><span>geospatial_lon_units :</span></dt><dd>degrees_east</dd><dt><span>geospatial_lon_resolution :</span></dt><dd>0.5 degree grid; however the native resolution of the data is 3-degree equal-area mascons</dd><dt><span>time_mean_removed :</span></dt><dd>2004.000 to 2009.999</dd><dt><span>months_missing :</span></dt><dd>2002-06;2002-07;2003-06;2011-01;2011-06;2012-05;2012-10;2013-03;2013-08;2013-09;2014-02;2014-07;2014-12;2015-06;2015-10;2015-11;2016-04;2016-09;2016-10;2017-02;2017-07;2017-08;2017-09;2017-10;2017-11;2017-12;2018-01;2018-02;2018-03;2018-04;2018-05;2018-08-2018-09</dd><dt><span>postprocess_1 :</span></dt><dd> OCEAN_ATMOSPHERE_DEALIAS_MODEL (GAD), MONTHLY_AVE, ADDED BACK TO OCEAN PIXELS ONLY</dd><dt><span>postprocess_2 :</span></dt><dd>Water density used to convert to equivalent water height: 1000 kg/m^3</dd><dt><span>postprocess_3 :</span></dt><dd>Coastline Resolution Improvement (CRI) filter has been applied to separate land/ocean mass within mascons that span coastlines</dd><dt><span>GIA_removed :</span></dt><dd>ICE6G-D; Peltier, W. R., D. F. Argus, and R. Drummond (2018) Comment on the paper by Purcell et al. 2016 entitled An assessment of ICE-6G_C (VM5a) glacial isostatic adjustment model, J. Geophys. Res. Solid Earth, 122.</dd><dt><span>geocenter_correction :</span></dt><dd>We use a version of TN-13 based on the JPL mascons</dd><dt><span>C_20_substitution :</span></dt><dd>TN-14; Loomis et al., 2019, Geophys. Res. Lett., doi:10.1029/2019GL082929</dd><dt><span>C_30_substitution :</span></dt><dd>TN-14; Loomis et al., 2019, Geophys. Res. Lett., doi:10.1029/2019GL082929.  This substitution is made for all months after August 2016.</dd><dt><span>user_note_1 :</span></dt><dd>The accelerometer on the GRACE-B spacecraft was turned off after August 2016.  After this date, the accelerometer on GRACE-A was used to derive the non-gravitational accelerations acting on GRACE-B using a transplant procedure.  This has led to a subsequent degradation in the quality of the gravity fields derived.  The uncertainties in this file have been scaled to accomodate this degradation.</dd><dt><span>user_note_2 :</span></dt><dd>The accelerometer on the GRACE-D spacecraft began performing sub-optimally after June 21, 2018.  After this date, the accelerometer on GRACE-C is used to derive the non-gravitational accelerations acting on GRACE-D using a transplant procedure.  The uncertainties in the file have been scaled to accomodate this degradation using the current best state of knowledge.</dd><dt><span>journal_reference :</span></dt><dd>Watkins, M. M., D. N. Wiese, D.-N. Yuan, C. Boening, and F. W. Landerer (2015) Improved methods for observing Earth&#x27;s time variable mass distribution with GRACE using spherical cap mascons, J. Geophys. Res., 120, doi:10.1002/2014JB011547. </dd><dt><span>CRI_filter_journal_reference :</span></dt><dd>Wiese, D. N., F. W. Landerer, and M. M. Watkins (2016) Quantifying and reducing leakage errors in the JPL RL05M GRACE mascon solution, Water Resour. Res., 52, doi:10.1002/2016WR019344. </dd><dt><span>date_created :</span></dt><dd>2021-04-27T21:04:06Z</dd></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.Dataset>\n",
       "Dimensions:        (lat: 5, lon: 4, time: 195)\n",
       "Coordinates:\n",
       "  * lat            (lat) float64 24.25 24.75 25.25 25.75 26.25\n",
       "  * lon            (lon) float64 88.25 88.75 89.25 89.75\n",
       "  * time           (time) datetime64[ns] 2002-04-17T12:00:00 ... 2021-03-16T1...\n",
       "    WGS84          int64 0\n",
       "Data variables:\n",
       "    lwe_thickness  (time, lat, lon) float64 nan -11.94 -14.36 ... -55.73 nan nan\n",
       "    uncertainty    (time, lat, lon) float64 nan 22.89 22.97 ... 11.68 nan nan\n",
       "Attributes: (12/53)\n",
       "    Conventions:                   CF-1.6, ACDD-1.3, ISO 8601\n",
       "    Metadata_Conventions:          Unidata Dataset Discovery v1.0\n",
       "    standard_name_vocabulary:      NetCDF Climate and Forecast (CF) Metadata ...\n",
       "    title:                         JPL GRACE and GRACE-FO MASCON RL06Mv2 CRI\n",
       "    summary:                       Monthly gravity solutions from GRACE and G...\n",
       "    keywords:                      Solid Earth, Geodetics/Gravity, Gravity, l...\n",
       "    ...                            ...\n",
       "    C_30_substitution:             TN-14; Loomis et al., 2019, Geophys. Res. ...\n",
       "    user_note_1:                   The accelerometer on the GRACE-B spacecraf...\n",
       "    user_note_2:                   The accelerometer on the GRACE-D spacecraf...\n",
       "    journal_reference:             Watkins, M. M., D. N. Wiese, D.-N. Yuan, C...\n",
       "    CRI_filter_journal_reference:  Wiese, D. N., F. W. Landerer, and M. M. Wa...\n",
       "    date_created:                  2021-04-27T21:04:06Z"
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "grace_clipped"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "id": "6da00e80-bdf1-4fbf-942e-11bbec78fd0e",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Clipping Scale Factors NetCDF file\n",
    "sf_ds = xr.open_dataset(os.path.join(grace_dir, 'scale_factors.nc'))\n",
    "sf_ds = sf_ds.assign({\"lon\": (((sf_ds.lon + 180) % 360) - 180)}).sortby('lon')\n",
    "sf_ds['scale_factor'] = sf_ds['scale_factor'].rio.write_crs(\"epsg:4326\")\n",
    "sf_ds.rio.set_spatial_dims(x_dim=\"lon\", y_dim=\"lat\", inplace=True)\n",
    "sf_clipped = sf_ds.rio.clip(gdf.geometry.apply(mapping), gdf.crs, drop=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "id": "a88aa907-b733-435e-b017-2501faa33e97",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Calculate GRACE grid cell area\n",
    "grace_areas = calculate_surface_area(sf_clipped)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "id": "17942ceb-c90e-470b-bcd3-059e8595fc5d",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Convert array to xarray dataarray\n",
    "grace_area_da = xr.DataArray(grace_areas, dims=['lat'], coords={'lat': sf_clipped.lat}).expand_dims(lon=len(sf_clipped.coords['lon'])).assign_coords(lon=sf_clipped.lon)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "id": "3e2f25a3-f0bd-48de-89eb-73fdae6df001",
   "metadata": {},
   "outputs": [],
   "source": [
    "sf_clipped['surface_area'] = grace_area_da.transpose('lat', 'lon')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "id": "9a530616-c071-4b53-aa27-0493698d1f48",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Calculate GRACE TWS Anomalies\n",
    "\n",
    "# Calculate grid cell long term mean\n",
    "grid_cell_mean = grace_clipped.mean('time').lwe_thickness\n",
    "# grace_clipped.sel(time=slice('2004-01-01', '2009-12-31')).mean('time').lwe_thickness\n",
    "# Calculate anamolies based on grid cell mean, scale factor and surface area\n",
    "gw_wsa_da = (grace_clipped.lwe_thickness - grid_cell_mean) * sf_clipped.scale_factor\n",
    "final_gw_da = gw_wsa_da.copy()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "id": "0b81ec52-e697-4178-be52-d7aa40f6a761",
   "metadata": {},
   "outputs": [
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       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.DataArray (time: 195, lat: 5, lon: 4)&gt;\n",
       "array([[[         nan,  -7.13845266, -17.26486904, -17.26486904],\n",
       "        [ -7.13845266,  -7.13845266, -17.26486904, -17.26486904],\n",
       "        [         nan,          nan, -16.10406004, -16.10406004],\n",
       "        [         nan,   9.88780363,   9.74180973,   9.74180973],\n",
       "        [         nan,   8.38552132,          nan,          nan]],\n",
       "\n",
       "       [[         nan,  -4.14765822, -10.76105615, -10.76105615],\n",
       "        [ -4.14765822,  -4.14765822, -10.76105615, -10.76105615],\n",
       "        [         nan,          nan, -10.03753309, -10.03753309],\n",
       "        [         nan,  19.8869995 ,  19.59336698,  19.59336698],\n",
       "        [         nan,  16.86551073,          nan,          nan]],\n",
       "\n",
       "       [[         nan,  44.00830982,  46.14480162,  46.14480162],\n",
       "        [ 44.00830982,  44.00830982,  46.14480162,  46.14480162],\n",
       "        [         nan,          nan,  43.04224109,  43.04224109],\n",
       "        [         nan,  85.58717298,  84.3234742 ,  84.3234742 ],\n",
       "        [         nan,  72.58366878,          nan,          nan]],\n",
       "\n",
       "       ...,\n",
       "\n",
       "       [[         nan,  -4.41044406,  -5.50066862,  -5.50066862],\n",
       "        [ -4.41044406,  -4.41044406,  -5.50066862,  -5.50066862],\n",
       "        [         nan,          nan,  -5.1308294 ,  -5.1308294 ],\n",
       "        [         nan, -57.61131673, -56.76068283, -56.76068283],\n",
       "        [         nan, -48.85826445,          nan,          nan]],\n",
       "\n",
       "       [[         nan, -14.13358007, -13.05841543, -13.05841543],\n",
       "        [-14.13358007, -14.13358007, -13.05841543, -13.05841543],\n",
       "        [         nan,          nan, -12.18042869, -12.18042869],\n",
       "        [         nan, -66.05507172, -65.07976537, -65.07976537],\n",
       "        [         nan, -56.01913557,          nan,          nan]],\n",
       "\n",
       "       [[         nan, -23.86105221, -20.29507514, -20.29507514],\n",
       "        [-23.86105221, -23.86105221, -20.29507514, -20.29507514],\n",
       "        [         nan,          nan, -18.93052925, -18.93052925],\n",
       "        [         nan, -65.60048502, -64.63189066, -64.63189066],\n",
       "        [         nan, -55.63361553,          nan,          nan]]])\n",
       "Coordinates:\n",
       "  * lat          (lat) float64 24.25 24.75 25.25 25.75 26.25\n",
       "  * lon          (lon) float64 88.25 88.75 89.25 89.75\n",
       "  * time         (time) datetime64[ns] 2002-04-17T12:00:00 ... 2021-03-16T12:...\n",
       "    WGS84        int64 0\n",
       "    spatial_ref  int64 0</pre><div class='xr-wrap' hidden><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'></div><ul class='xr-dim-list'><li><span class='xr-has-index'>time</span>: 195</li><li><span class='xr-has-index'>lat</span>: 5</li><li><span class='xr-has-index'>lon</span>: 4</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-4c1d55c2-643e-4648-acac-01d311382f36' class='xr-array-in' type='checkbox' checked><label for='section-4c1d55c2-643e-4648-acac-01d311382f36' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>nan -7.138 -17.26 -17.26 -7.138 -7.138 ... -64.63 nan -55.63 nan nan</span></div><div class='xr-array-data'><pre>array([[[         nan,  -7.13845266, -17.26486904, -17.26486904],\n",
       "        [ -7.13845266,  -7.13845266, -17.26486904, -17.26486904],\n",
       "        [         nan,          nan, -16.10406004, -16.10406004],\n",
       "        [         nan,   9.88780363,   9.74180973,   9.74180973],\n",
       "        [         nan,   8.38552132,          nan,          nan]],\n",
       "\n",
       "       [[         nan,  -4.14765822, -10.76105615, -10.76105615],\n",
       "        [ -4.14765822,  -4.14765822, -10.76105615, -10.76105615],\n",
       "        [         nan,          nan, -10.03753309, -10.03753309],\n",
       "        [         nan,  19.8869995 ,  19.59336698,  19.59336698],\n",
       "        [         nan,  16.86551073,          nan,          nan]],\n",
       "\n",
       "       [[         nan,  44.00830982,  46.14480162,  46.14480162],\n",
       "        [ 44.00830982,  44.00830982,  46.14480162,  46.14480162],\n",
       "        [         nan,          nan,  43.04224109,  43.04224109],\n",
       "        [         nan,  85.58717298,  84.3234742 ,  84.3234742 ],\n",
       "        [         nan,  72.58366878,          nan,          nan]],\n",
       "\n",
       "       ...,\n",
       "\n",
       "       [[         nan,  -4.41044406,  -5.50066862,  -5.50066862],\n",
       "        [ -4.41044406,  -4.41044406,  -5.50066862,  -5.50066862],\n",
       "        [         nan,          nan,  -5.1308294 ,  -5.1308294 ],\n",
       "        [         nan, -57.61131673, -56.76068283, -56.76068283],\n",
       "        [         nan, -48.85826445,          nan,          nan]],\n",
       "\n",
       "       [[         nan, -14.13358007, -13.05841543, -13.05841543],\n",
       "        [-14.13358007, -14.13358007, -13.05841543, -13.05841543],\n",
       "        [         nan,          nan, -12.18042869, -12.18042869],\n",
       "        [         nan, -66.05507172, -65.07976537, -65.07976537],\n",
       "        [         nan, -56.01913557,          nan,          nan]],\n",
       "\n",
       "       [[         nan, -23.86105221, -20.29507514, -20.29507514],\n",
       "        [-23.86105221, -23.86105221, -20.29507514, -20.29507514],\n",
       "        [         nan,          nan, -18.93052925, -18.93052925],\n",
       "        [         nan, -65.60048502, -64.63189066, -64.63189066],\n",
       "        [         nan, -55.63361553,          nan,          nan]]])</pre></div></div></li><li class='xr-section-item'><input id='section-d21a757a-26b4-4045-9291-7a4db9909e59' class='xr-section-summary-in' type='checkbox'  checked><label for='section-d21a757a-26b4-4045-9291-7a4db9909e59' 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'>lat</span></div><div class='xr-var-dims'>(lat)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>24.25 24.75 25.25 25.75 26.25</div><input id='attrs-eca4b4f4-e872-49c2-a4d1-c52fb9d4466c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-eca4b4f4-e872-49c2-a4d1-c52fb9d4466c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5c9763d8-e5c6-4058-9ee1-ccd4d9a5a792' class='xr-var-data-in' type='checkbox'><label for='data-5c9763d8-e5c6-4058-9ee1-ccd4d9a5a792' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>long_name :</span></dt><dd>latitude</dd><dt><span>standard_name :</span></dt><dd>latitude</dd><dt><span>axis :</span></dt><dd>Y</dd><dt><span>valid_min :</span></dt><dd>-89.75</dd><dt><span>valid_max :</span></dt><dd>89.75</dd><dt><span>bounds :</span></dt><dd>lat_bounds</dd></dl></div><div class='xr-var-data'><pre>array([24.25, 24.75, 25.25, 25.75, 26.25])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lon</span></div><div class='xr-var-dims'>(lon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>88.25 88.75 89.25 89.75</div><input id='attrs-f538c7bd-de5f-4544-9c2a-f614563acd1f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f538c7bd-de5f-4544-9c2a-f614563acd1f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2e9ebb85-6601-4dd5-92bf-befabeca03a0' class='xr-var-data-in' type='checkbox'><label for='data-2e9ebb85-6601-4dd5-92bf-befabeca03a0' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>axis :</span></dt><dd>X</dd><dt><span>long_name :</span></dt><dd>longitude</dd><dt><span>standard_name :</span></dt><dd>longitude</dd><dt><span>units :</span></dt><dd>degrees_east</dd></dl></div><div class='xr-var-data'><pre>array([88.25, 88.75, 89.25, 89.75])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2002-04-17T12:00:00 ... 2021-03-...</div><input id='attrs-de3e1a99-8899-4d0a-9924-69ea0e7b411e' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-de3e1a99-8899-4d0a-9924-69ea0e7b411e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-41937415-753c-4f64-ae4e-cbafba901ec9' class='xr-var-data-in' type='checkbox'><label for='data-41937415-753c-4f64-ae4e-cbafba901ec9' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>time</dd><dt><span>standard_name :</span></dt><dd>time</dd><dt><span>axis :</span></dt><dd>T</dd><dt><span>bounds :</span></dt><dd>time_bounds</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;2002-04-17T12:00:00.000000000&#x27;, &#x27;2002-05-10T12:00:00.000000000&#x27;,\n",
       "       &#x27;2002-08-16T12:00:00.000000000&#x27;, &#x27;2002-09-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;2002-10-16T12:00:00.000000000&#x27;, &#x27;2002-11-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;2002-12-16T12:00:00.000000000&#x27;, &#x27;2003-01-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;2003-02-15T00:00:00.000000000&#x27;, &#x27;2003-03-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;2003-04-16T00:00:00.000000000&#x27;, &#x27;2003-05-11T12:00:00.000000000&#x27;,\n",
       "       &#x27;2003-07-16T12:00:00.000000000&#x27;, &#x27;2003-08-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;2003-09-16T00:00:00.000000000&#x27;, &#x27;2003-10-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;2003-11-16T00:00:00.000000000&#x27;, &#x27;2003-12-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;2004-01-07T12:00:00.000000000&#x27;, &#x27;2004-02-17T00:00:00.000000000&#x27;,\n",
       "       &#x27;2004-03-16T12:00:00.000000000&#x27;, &#x27;2004-04-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;2004-05-16T12:00:00.000000000&#x27;, &#x27;2004-06-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;2004-07-16T12:00:00.000000000&#x27;, &#x27;2004-08-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;2004-09-16T00:00:00.000000000&#x27;, &#x27;2004-10-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;2004-11-16T00:00:00.000000000&#x27;, &#x27;2004-12-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;2005-01-16T12:00:00.000000000&#x27;, &#x27;2005-02-15T00:00:00.000000000&#x27;,\n",
       "       &#x27;2005-03-16T12:00:00.000000000&#x27;, &#x27;2005-04-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;2005-05-16T12:00:00.000000000&#x27;, &#x27;2005-06-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;2005-07-16T12:00:00.000000000&#x27;, &#x27;2005-08-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;2005-09-16T00:00:00.000000000&#x27;, &#x27;2005-10-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;2005-11-16T00:00:00.000000000&#x27;, &#x27;2005-12-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;2006-01-16T12:00:00.000000000&#x27;, &#x27;2006-02-15T00:00:00.000000000&#x27;,\n",
       "       &#x27;2006-03-16T12:00:00.000000000&#x27;, &#x27;2006-04-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;2006-05-16T12:00:00.000000000&#x27;, &#x27;2006-06-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;2006-07-16T12:00:00.000000000&#x27;, &#x27;2006-08-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;2006-09-16T00:00:00.000000000&#x27;, &#x27;2006-10-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;2006-11-16T00:00:00.000000000&#x27;, &#x27;2006-12-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;2007-01-16T12:00:00.000000000&#x27;, &#x27;2007-02-15T00:00:00.000000000&#x27;,\n",
       "       &#x27;2007-03-16T12:00:00.000000000&#x27;, &#x27;2007-04-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;2007-05-16T12:00:00.000000000&#x27;, &#x27;2007-06-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;2007-07-16T12:00:00.000000000&#x27;, &#x27;2007-08-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;2007-09-16T00:00:00.000000000&#x27;, &#x27;2007-10-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;2007-11-16T00:00:00.000000000&#x27;, &#x27;2007-12-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;2008-01-16T12:00:00.000000000&#x27;, &#x27;2008-02-15T12:00:00.000000000&#x27;,\n",
       "       &#x27;2008-03-16T12:00:00.000000000&#x27;, &#x27;2008-04-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;2008-05-16T12:00:00.000000000&#x27;, &#x27;2008-06-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;2008-07-16T12:00:00.000000000&#x27;, &#x27;2008-08-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;2008-09-16T00:00:00.000000000&#x27;, &#x27;2008-10-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;2008-11-16T00:00:00.000000000&#x27;, &#x27;2008-12-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;2009-01-16T12:00:00.000000000&#x27;, &#x27;2009-02-15T00:00:00.000000000&#x27;,\n",
       "       &#x27;2009-03-16T12:00:00.000000000&#x27;, &#x27;2009-04-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;2009-05-16T12:00:00.000000000&#x27;, &#x27;2009-06-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;2009-07-16T12:00:00.000000000&#x27;, &#x27;2009-08-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;2009-09-16T00:00:00.000000000&#x27;, &#x27;2009-10-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;2009-11-16T00:00:00.000000000&#x27;, &#x27;2009-12-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;2010-01-16T12:00:00.000000000&#x27;, &#x27;2010-02-15T00:00:00.000000000&#x27;,\n",
       "       &#x27;2010-03-16T12:00:00.000000000&#x27;, &#x27;2010-04-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;2010-05-16T12:00:00.000000000&#x27;, &#x27;2010-06-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;2010-07-16T12:00:00.000000000&#x27;, &#x27;2010-08-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;2010-09-16T00:00:00.000000000&#x27;, &#x27;2010-10-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;2010-11-16T00:00:00.000000000&#x27;, &#x27;2010-12-14T12:00:00.000000000&#x27;,\n",
       "       &#x27;2011-02-18T12:00:00.000000000&#x27;, &#x27;2011-03-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;2011-04-16T00:00:00.000000000&#x27;, &#x27;2011-05-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;2011-07-18T12:00:00.000000000&#x27;, &#x27;2011-08-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;2011-09-16T00:00:00.000000000&#x27;, &#x27;2011-10-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;2011-11-01T12:00:00.000000000&#x27;, &#x27;2012-01-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;2012-01-16T12:00:00.000000000&#x27;, &#x27;2012-02-15T12:00:00.000000000&#x27;,\n",
       "       &#x27;2012-03-16T12:00:00.000000000&#x27;, &#x27;2012-04-04T12:00:00.000000000&#x27;,\n",
       "       &#x27;2012-06-16T00:00:00.000000000&#x27;, &#x27;2012-07-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;2012-08-16T12:00:00.000000000&#x27;, &#x27;2012-09-13T00:00:00.000000000&#x27;,\n",
       "       &#x27;2012-11-18T12:00:00.000000000&#x27;, &#x27;2012-12-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;2013-01-16T12:00:00.000000000&#x27;, &#x27;2013-02-14T00:00:00.000000000&#x27;,\n",
       "       &#x27;2013-04-21T00:00:00.000000000&#x27;, &#x27;2013-05-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;2013-06-16T00:00:00.000000000&#x27;, &#x27;2013-07-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;2013-10-16T12:00:00.000000000&#x27;, &#x27;2013-11-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;2013-12-16T12:00:00.000000000&#x27;, &#x27;2014-01-09T12:00:00.000000000&#x27;,\n",
       "       &#x27;2014-03-16T12:00:00.000000000&#x27;, &#x27;2014-04-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;2014-05-16T12:00:00.000000000&#x27;, &#x27;2014-06-13T00:00:00.000000000&#x27;,\n",
       "       &#x27;2014-08-16T12:00:00.000000000&#x27;, &#x27;2014-09-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;2014-10-16T12:00:00.000000000&#x27;, &#x27;2014-11-17T00:00:00.000000000&#x27;,\n",
       "       &#x27;2015-01-22T12:00:00.000000000&#x27;, &#x27;2015-02-15T00:00:00.000000000&#x27;,\n",
       "       &#x27;2015-03-16T12:00:00.000000000&#x27;, &#x27;2015-04-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;2015-04-27T00:00:00.000000000&#x27;, &#x27;2015-07-15T12:00:00.000000000&#x27;,\n",
       "       &#x27;2015-08-16T12:00:00.000000000&#x27;, &#x27;2015-09-14T12:00:00.000000000&#x27;,\n",
       "       &#x27;2015-12-23T12:00:00.000000000&#x27;, &#x27;2016-01-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;2016-02-14T00:00:00.000000000&#x27;, &#x27;2016-03-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;2016-05-20T00:00:00.000000000&#x27;, &#x27;2016-06-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;2016-07-15T12:00:00.000000000&#x27;, &#x27;2016-08-21T12:00:00.000000000&#x27;,\n",
       "       &#x27;2016-11-27T12:00:00.000000000&#x27;, &#x27;2016-12-24T12:00:00.000000000&#x27;,\n",
       "       &#x27;2017-01-21T00:00:00.000000000&#x27;, &#x27;2017-03-31T12:00:00.000000000&#x27;,\n",
       "       &#x27;2017-04-24T12:00:00.000000000&#x27;, &#x27;2017-05-12T12:00:00.000000000&#x27;,\n",
       "       &#x27;2017-06-11T00:00:00.000000000&#x27;, &#x27;2018-06-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;2018-07-10T00:00:00.000000000&#x27;, &#x27;2018-10-31T12:00:00.000000000&#x27;,\n",
       "       &#x27;2018-11-16T00:00:00.000000000&#x27;, &#x27;2018-12-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;2019-01-16T12:00:00.000000000&#x27;, &#x27;2019-02-14T00:00:00.000000000&#x27;,\n",
       "       &#x27;2019-03-16T12:00:00.000000000&#x27;, &#x27;2019-04-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;2019-05-16T12:00:00.000000000&#x27;, &#x27;2019-06-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;2019-07-16T12:00:00.000000000&#x27;, &#x27;2019-08-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;2019-09-16T00:00:00.000000000&#x27;, &#x27;2019-10-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;2019-11-16T00:00:00.000000000&#x27;, &#x27;2019-12-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;2020-01-16T12:00:00.000000000&#x27;, &#x27;2020-02-15T12:00:00.000000000&#x27;,\n",
       "       &#x27;2020-03-16T12:00:00.000000000&#x27;, &#x27;2020-04-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;2020-05-16T12:00:00.000000000&#x27;, &#x27;2020-06-16T00:00:00.000000000&#x27;,\n",
       "       &#x27;2020-07-16T12:00:00.000000000&#x27;, &#x27;2020-08-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;2020-09-16T00:00:00.000000000&#x27;, &#x27;2020-10-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;2020-11-16T00:00:00.000000000&#x27;, &#x27;2020-12-16T12:00:00.000000000&#x27;,\n",
       "       &#x27;2021-01-16T12:00:00.000000000&#x27;, &#x27;2021-02-15T00:00:00.000000000&#x27;,\n",
       "       &#x27;2021-03-16T12:00:00.000000000&#x27;], dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>WGS84</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-cb14e7cf-1953-4cdc-a14a-a0139df55fea' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-cb14e7cf-1953-4cdc-a14a-a0139df55fea' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3f7c6f9f-848e-4401-8984-f88f6ff8aeaf' class='xr-var-data-in' type='checkbox'><label for='data-3f7c6f9f-848e-4401-8984-f88f6ff8aeaf' 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>GEOGCS[&quot;WGS 84&quot;,DATUM[&quot;WGS_1984&quot;,SPHEROID[&quot;WGS 84&quot;,6378137,298.257223563,AUTHORITY[&quot;EPSG&quot;,&quot;7030&quot;]],AUTHORITY[&quot;EPSG&quot;,&quot;6326&quot;]],PRIMEM[&quot;Greenwich&quot;,0,AUTHORITY[&quot;EPSG&quot;,&quot;8901&quot;]],UNIT[&quot;degree&quot;,0.0174532925199433,AUTHORITY[&quot;EPSG&quot;,&quot;9122&quot;]],AXIS[&quot;Latitude&quot;,NORTH],AXIS[&quot;Longitude&quot;,EAST],AUTHORITY[&quot;EPSG&quot;,&quot;4326&quot;]]</dd><dt><span>semi_major_axis :</span></dt><dd>6378137.0</dd><dt><span>semi_minor_axis :</span></dt><dd>6356752.314245179</dd><dt><span>inverse_flattening :</span></dt><dd>298.257223563</dd><dt><span>reference_ellipsoid_name :</span></dt><dd>WGS 84</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>WGS 84</dd><dt><span>grid_mapping_name :</span></dt><dd>latitude_longitude</dd><dt><span>spatial_ref :</span></dt><dd>GEOGCS[&quot;WGS 84&quot;,DATUM[&quot;WGS_1984&quot;,SPHEROID[&quot;WGS 84&quot;,6378137,298.257223563,AUTHORITY[&quot;EPSG&quot;,&quot;7030&quot;]],AUTHORITY[&quot;EPSG&quot;,&quot;6326&quot;]],PRIMEM[&quot;Greenwich&quot;,0,AUTHORITY[&quot;EPSG&quot;,&quot;8901&quot;]],UNIT[&quot;degree&quot;,0.0174532925199433,AUTHORITY[&quot;EPSG&quot;,&quot;9122&quot;]],AXIS[&quot;Latitude&quot;,NORTH],AXIS[&quot;Longitude&quot;,EAST],AUTHORITY[&quot;EPSG&quot;,&quot;4326&quot;]]</dd><dt><span>GeoTransform :</span></dt><dd>88.0 0.5 0.0 24.0 0.0 0.5</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>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-e22d7aec-f6a4-481f-809b-ccf0f20c007d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e22d7aec-f6a4-481f-809b-ccf0f20c007d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-bacec46e-9194-42f7-85f8-20f63d72d7af' class='xr-var-data-in' type='checkbox'><label for='data-bacec46e-9194-42f7-85f8-20f63d72d7af' 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>GEOGCS[&quot;WGS 84&quot;,DATUM[&quot;WGS_1984&quot;,SPHEROID[&quot;WGS 84&quot;,6378137,298.257223563,AUTHORITY[&quot;EPSG&quot;,&quot;7030&quot;]],AUTHORITY[&quot;EPSG&quot;,&quot;6326&quot;]],PRIMEM[&quot;Greenwich&quot;,0,AUTHORITY[&quot;EPSG&quot;,&quot;8901&quot;]],UNIT[&quot;degree&quot;,0.0174532925199433,AUTHORITY[&quot;EPSG&quot;,&quot;9122&quot;]],AXIS[&quot;Latitude&quot;,NORTH],AXIS[&quot;Longitude&quot;,EAST],AUTHORITY[&quot;EPSG&quot;,&quot;4326&quot;]]</dd><dt><span>semi_major_axis :</span></dt><dd>6378137.0</dd><dt><span>semi_minor_axis :</span></dt><dd>6356752.314245179</dd><dt><span>inverse_flattening :</span></dt><dd>298.257223563</dd><dt><span>reference_ellipsoid_name :</span></dt><dd>WGS 84</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>WGS 84</dd><dt><span>grid_mapping_name :</span></dt><dd>latitude_longitude</dd><dt><span>spatial_ref :</span></dt><dd>GEOGCS[&quot;WGS 84&quot;,DATUM[&quot;WGS_1984&quot;,SPHEROID[&quot;WGS 84&quot;,6378137,298.257223563,AUTHORITY[&quot;EPSG&quot;,&quot;7030&quot;]],AUTHORITY[&quot;EPSG&quot;,&quot;6326&quot;]],PRIMEM[&quot;Greenwich&quot;,0,AUTHORITY[&quot;EPSG&quot;,&quot;8901&quot;]],UNIT[&quot;degree&quot;,0.0174532925199433,AUTHORITY[&quot;EPSG&quot;,&quot;9122&quot;]],AXIS[&quot;Latitude&quot;,NORTH],AXIS[&quot;Longitude&quot;,EAST],AUTHORITY[&quot;EPSG&quot;,&quot;4326&quot;]]</dd><dt><span>GeoTransform :</span></dt><dd>88.0 0.5 0.0 24.0 0.0 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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",
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       "\n",
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       "\n",
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       "  padding: 0;\n",
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       "\n",
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       "  font-weight: normal;\n",
       "  grid-column: 1;\n",
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       "\n",
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       "  display: inline-block;\n",
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       "\n",
       ".xr-attrs dd {\n",
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       "\n",
       ".xr-icon-database,\n",
       ".xr-icon-file-text2 {\n",
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       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.DataArray ()&gt;\n",
       "array(2.91504712e-15)\n",
       "Coordinates:\n",
       "    WGS84        int64 0\n",
       "    spatial_ref  int64 0</pre><div class='xr-wrap' hidden><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'></div></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-13428212-afa2-41ea-9831-19f282b406fb' class='xr-array-in' type='checkbox' checked><label for='section-13428212-afa2-41ea-9831-19f282b406fb' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>2.915e-15</span></div><div class='xr-array-data'><pre>array(2.91504712e-15)</pre></div></div></li><li class='xr-section-item'><input id='section-023d9af0-3f6f-4905-ad08-ed94a47469a5' class='xr-section-summary-in' type='checkbox'  checked><label for='section-023d9af0-3f6f-4905-ad08-ed94a47469a5' class='xr-section-summary' >Coordinates: <span>(2)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>WGS84</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-ed09797b-b594-42f0-8ec8-fb29b395cf4e' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ed09797b-b594-42f0-8ec8-fb29b395cf4e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ba765f6c-e973-48a4-949c-0716a43403b9' class='xr-var-data-in' type='checkbox'><label for='data-ba765f6c-e973-48a4-949c-0716a43403b9' 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>GEOGCS[&quot;WGS 84&quot;,DATUM[&quot;WGS_1984&quot;,SPHEROID[&quot;WGS 84&quot;,6378137,298.257223563,AUTHORITY[&quot;EPSG&quot;,&quot;7030&quot;]],AUTHORITY[&quot;EPSG&quot;,&quot;6326&quot;]],PRIMEM[&quot;Greenwich&quot;,0,AUTHORITY[&quot;EPSG&quot;,&quot;8901&quot;]],UNIT[&quot;degree&quot;,0.0174532925199433,AUTHORITY[&quot;EPSG&quot;,&quot;9122&quot;]],AXIS[&quot;Latitude&quot;,NORTH],AXIS[&quot;Longitude&quot;,EAST],AUTHORITY[&quot;EPSG&quot;,&quot;4326&quot;]]</dd><dt><span>semi_major_axis :</span></dt><dd>6378137.0</dd><dt><span>semi_minor_axis :</span></dt><dd>6356752.314245179</dd><dt><span>inverse_flattening :</span></dt><dd>298.257223563</dd><dt><span>reference_ellipsoid_name :</span></dt><dd>WGS 84</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>WGS 84</dd><dt><span>grid_mapping_name :</span></dt><dd>latitude_longitude</dd><dt><span>spatial_ref :</span></dt><dd>GEOGCS[&quot;WGS 84&quot;,DATUM[&quot;WGS_1984&quot;,SPHEROID[&quot;WGS 84&quot;,6378137,298.257223563,AUTHORITY[&quot;EPSG&quot;,&quot;7030&quot;]],AUTHORITY[&quot;EPSG&quot;,&quot;6326&quot;]],PRIMEM[&quot;Greenwich&quot;,0,AUTHORITY[&quot;EPSG&quot;,&quot;8901&quot;]],UNIT[&quot;degree&quot;,0.0174532925199433,AUTHORITY[&quot;EPSG&quot;,&quot;9122&quot;]],AXIS[&quot;Latitude&quot;,NORTH],AXIS[&quot;Longitude&quot;,EAST],AUTHORITY[&quot;EPSG&quot;,&quot;4326&quot;]]</dd><dt><span>GeoTransform :</span></dt><dd>88.0 0.5 0.0 24.0 0.0 0.5</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>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-52b8935b-3c16-4b6e-9a25-792dcb65d730' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-52b8935b-3c16-4b6e-9a25-792dcb65d730' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-396ae849-ab99-4e4d-bd11-9b008f5052a6' class='xr-var-data-in' type='checkbox'><label for='data-396ae849-ab99-4e4d-bd11-9b008f5052a6' 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>GEOGCS[&quot;WGS 84&quot;,DATUM[&quot;WGS_1984&quot;,SPHEROID[&quot;WGS 84&quot;,6378137,298.257223563,AUTHORITY[&quot;EPSG&quot;,&quot;7030&quot;]],AUTHORITY[&quot;EPSG&quot;,&quot;6326&quot;]],PRIMEM[&quot;Greenwich&quot;,0,AUTHORITY[&quot;EPSG&quot;,&quot;8901&quot;]],UNIT[&quot;degree&quot;,0.0174532925199433,AUTHORITY[&quot;EPSG&quot;,&quot;9122&quot;]],AXIS[&quot;Latitude&quot;,NORTH],AXIS[&quot;Longitude&quot;,EAST],AUTHORITY[&quot;EPSG&quot;,&quot;4326&quot;]]</dd><dt><span>semi_major_axis :</span></dt><dd>6378137.0</dd><dt><span>semi_minor_axis :</span></dt><dd>6356752.314245179</dd><dt><span>inverse_flattening :</span></dt><dd>298.257223563</dd><dt><span>reference_ellipsoid_name :</span></dt><dd>WGS 84</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>WGS 84</dd><dt><span>grid_mapping_name :</span></dt><dd>latitude_longitude</dd><dt><span>spatial_ref :</span></dt><dd>GEOGCS[&quot;WGS 84&quot;,DATUM[&quot;WGS_1984&quot;,SPHEROID[&quot;WGS 84&quot;,6378137,298.257223563,AUTHORITY[&quot;EPSG&quot;,&quot;7030&quot;]],AUTHORITY[&quot;EPSG&quot;,&quot;6326&quot;]],PRIMEM[&quot;Greenwich&quot;,0,AUTHORITY[&quot;EPSG&quot;,&quot;8901&quot;]],UNIT[&quot;degree&quot;,0.0174532925199433,AUTHORITY[&quot;EPSG&quot;,&quot;9122&quot;]],AXIS[&quot;Latitude&quot;,NORTH],AXIS[&quot;Longitude&quot;,EAST],AUTHORITY[&quot;EPSG&quot;,&quot;4326&quot;]]</dd><dt><span>GeoTransform :</span></dt><dd>88.0 0.5 0.0 24.0 0.0 0.5</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-30e78743-108c-4af0-8a5d-5dbf37f0ed2f' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-30e78743-108c-4af0-8a5d-5dbf37f0ed2f' class='xr-section-summary'  title='Expand/collapse section'>Attributes: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.DataArray ()>\n",
       "array(2.91504712e-15)\n",
       "Coordinates:\n",
       "    WGS84        int64 0\n",
       "    spatial_ref  int64 0"
      ]
     },
     "execution_count": 45,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "final_gw_da.mean(['lat', 'lon']).mean()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "id": "5cc04c31-5595-4c87-a967-c73b43115eda",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Convert to a dataframe to leverage SHBAAM interpolation code\n",
    "grc_df = final_gw_da.mean(['lat', 'lon']).to_dataframe(name='twsa').reset_index()\n",
    "grc_df.set_index(pd.to_datetime(grc_df.time), inplace=True)\n",
    "grc_df.drop(columns=['time'], inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "id": "bd7115e9-4b81-4be0-8b13-b7b62211ddc7",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Interpolate GRACE TWS anomalies data\n",
    "df_sync_grc = grc_df.resample('M').fillna(method='pad', limit=1)\n",
    "x = np.arange(df_sync_grc.index.size)\n",
    "df_sync_grc['x']=x\n",
    "df_nonans = df_sync_grc.dropna()\n",
    "X = np.array(df_nonans.x)\n",
    "fit = np.polyfit(X, df_nonans.twsa, 1)\n",
    "fit_fn = np.poly1d(fit)\n",
    "df_sync_grc['linear_trend']= fit_fn(x)\n",
    "df_sync_grc['iav']=df_sync_grc.twsa-df_sync_grc.linear_trend\n",
    "df_sync_grc['month_num']=df_sync_grc.index.month\n",
    "month_clim = df_sync_grc.iav.groupby(df_sync_grc.index.month).mean()\n",
    "clim_dict = month_clim.to_dict()\n",
    "df_sync_grc['clim']=df_sync_grc['month_num'].map(clim_dict)\n",
    "df_sync_grc['noclim']=df_sync_grc.twsa-df_sync_grc.clim\n",
    "df_sync_grc['noclim_fill'] = df_sync_grc.noclim.fillna(method='pad', limit=1).interpolate(method='cubic', limit=3)\n",
    "df_sync_grc['twsa_fill'] =df_sync_grc.noclim_fill+df_sync_grc.clim\n",
    "df_sync_grc.reset_index(inplace=True)\n",
    "df_sync_grc['time'] = df_sync_grc['time'].apply(lambda x: x.to_pydatetime().replace(day=1, hour=0))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "id": "d5a03537-488b-4994-919f-53cd847a6144",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th>time</th>\n",
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       "      <td>0</td>\n",
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       "      <td>-17.865543</td>\n",
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       "      <td>-26.872790</td>\n",
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       "      <td>2002-05-01</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.028998</td>\n",
       "      <td>1</td>\n",
       "      <td>11.230229</td>\n",
       "      <td>-11.201230</td>\n",
       "      <td>5</td>\n",
       "      <td>-18.457718</td>\n",
       "      <td>18.486716</td>\n",
       "      <td>18.486716</td>\n",
       "      <td>0.028998</td>\n",
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       "      <th>2</th>\n",
       "      <td>2002-06-01</td>\n",
       "      <td>NaN</td>\n",
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       "      <td>2</td>\n",
       "      <td>11.127684</td>\n",
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       "      <td>6</td>\n",
       "      <td>0.629685</td>\n",
       "      <td>NaN</td>\n",
       "      <td>18.486716</td>\n",
       "      <td>19.116401</td>\n",
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       "      <td>7</td>\n",
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       "      <td>21.769590</td>\n",
       "      <td>51.594553</td>\n",
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       "      <td>0.0</td>\n",
       "      <td>56.115878</td>\n",
       "      <td>4</td>\n",
       "      <td>10.922595</td>\n",
       "      <td>45.193282</td>\n",
       "      <td>8</td>\n",
       "      <td>37.072206</td>\n",
       "      <td>19.043672</td>\n",
       "      <td>19.043672</td>\n",
       "      <td>56.115878</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>223</th>\n",
       "      <td>2020-11-01</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>6.290697</td>\n",
       "      <td>223</td>\n",
       "      <td>-11.534653</td>\n",
       "      <td>17.825350</td>\n",
       "      <td>11</td>\n",
       "      <td>3.694475</td>\n",
       "      <td>2.596222</td>\n",
       "      <td>2.596222</td>\n",
       "      <td>6.290697</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>224</th>\n",
       "      <td>2020-12-01</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-7.802380</td>\n",
       "      <td>224</td>\n",
       "      <td>-11.637198</td>\n",
       "      <td>3.834818</td>\n",
       "      <td>12</td>\n",
       "      <td>-9.619713</td>\n",
       "      <td>1.817333</td>\n",
       "      <td>1.817333</td>\n",
       "      <td>-7.802380</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>225</th>\n",
       "      <td>2021-01-01</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-20.422047</td>\n",
       "      <td>225</td>\n",
       "      <td>-11.739742</td>\n",
       "      <td>-8.682305</td>\n",
       "      <td>1</td>\n",
       "      <td>-17.139543</td>\n",
       "      <td>-3.282504</td>\n",
       "      <td>-3.282504</td>\n",
       "      <td>-20.422047</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>226</th>\n",
       "      <td>2021-02-01</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-28.556077</td>\n",
       "      <td>226</td>\n",
       "      <td>-11.842287</td>\n",
       "      <td>-16.713790</td>\n",
       "      <td>2</td>\n",
       "      <td>-22.603818</td>\n",
       "      <td>-5.952259</td>\n",
       "      <td>-5.952259</td>\n",
       "      <td>-28.556077</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>227</th>\n",
       "      <td>2021-03-01</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-33.932492</td>\n",
       "      <td>227</td>\n",
       "      <td>-11.944831</td>\n",
       "      <td>-21.987661</td>\n",
       "      <td>3</td>\n",
       "      <td>-28.926369</td>\n",
       "      <td>-5.006124</td>\n",
       "      <td>-5.006124</td>\n",
       "      <td>-33.932492</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>228 rows × 12 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "          time  WGS84  spatial_ref       twsa    x  linear_trend        iav  \\\n",
       "0   2002-04-01    0.0          0.0  -6.532770    0     11.332773 -17.865543   \n",
       "1   2002-05-01    0.0          0.0   0.028998    1     11.230229 -11.201230   \n",
       "2   2002-06-01    NaN          NaN        NaN    2     11.127684        NaN   \n",
       "3   2002-07-01    NaN          NaN        NaN    3     11.025140        NaN   \n",
       "4   2002-08-01    0.0          0.0  56.115878    4     10.922595  45.193282   \n",
       "..         ...    ...          ...        ...  ...           ...        ...   \n",
       "223 2020-11-01    0.0          0.0   6.290697  223    -11.534653  17.825350   \n",
       "224 2020-12-01    0.0          0.0  -7.802380  224    -11.637198   3.834818   \n",
       "225 2021-01-01    0.0          0.0 -20.422047  225    -11.739742  -8.682305   \n",
       "226 2021-02-01    0.0          0.0 -28.556077  226    -11.842287 -16.713790   \n",
       "227 2021-03-01    0.0          0.0 -33.932492  227    -11.944831 -21.987661   \n",
       "\n",
       "     month_num       clim     noclim  noclim_fill  twsa_fill  \n",
       "0            4 -26.872790  20.340020    20.340020  -6.532770  \n",
       "1            5 -18.457718  18.486716    18.486716   0.028998  \n",
       "2            6   0.629685        NaN    18.486716  19.116401  \n",
       "3            7  29.824963        NaN    21.769590  51.594553  \n",
       "4            8  37.072206  19.043672    19.043672  56.115878  \n",
       "..         ...        ...        ...          ...        ...  \n",
       "223         11   3.694475   2.596222     2.596222   6.290697  \n",
       "224         12  -9.619713   1.817333     1.817333  -7.802380  \n",
       "225          1 -17.139543  -3.282504    -3.282504 -20.422047  \n",
       "226          2 -22.603818  -5.952259    -5.952259 -28.556077  \n",
       "227          3 -28.926369  -5.006124    -5.006124 -33.932492  \n",
       "\n",
       "[228 rows x 12 columns]"
      ]
     },
     "execution_count": 48,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df_sync_grc"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "id": "8326178d-43ff-4102-bb24-e3a5c66a82ce",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
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       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>time</th>\n",
       "      <th>grace_std</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2002-04-01</td>\n",
       "      <td>11.323719</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2002-05-01</td>\n",
       "      <td>12.902123</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2002-06-01</td>\n",
       "      <td>12.902123</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2002-07-01</td>\n",
       "      <td>12.902123</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2002-08-01</td>\n",
       "      <td>17.343568</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>223</th>\n",
       "      <td>2020-11-01</td>\n",
       "      <td>21.247063</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>224</th>\n",
       "      <td>2020-12-01</td>\n",
       "      <td>21.916328</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>225</th>\n",
       "      <td>2021-01-01</td>\n",
       "      <td>23.138380</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>226</th>\n",
       "      <td>2021-02-01</td>\n",
       "      <td>23.120775</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>227</th>\n",
       "      <td>2021-03-01</td>\n",
       "      <td>19.329218</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>228 rows × 2 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "          time  grace_std\n",
       "0   2002-04-01  11.323719\n",
       "1   2002-05-01  12.902123\n",
       "2   2002-06-01  12.902123\n",
       "3   2002-07-01  12.902123\n",
       "4   2002-08-01  17.343568\n",
       "..         ...        ...\n",
       "223 2020-11-01  21.247063\n",
       "224 2020-12-01  21.916328\n",
       "225 2021-01-01  23.138380\n",
       "226 2021-02-01  23.120775\n",
       "227 2021-03-01  19.329218\n",
       "\n",
       "[228 rows x 2 columns]"
      ]
     },
     "execution_count": 49,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Grace std\n",
    "grace_std_df = grace_clipped['uncertainty'].mean(['lat', 'lon']).to_dataframe().reset_index().drop(columns=['WGS84'])\n",
    "grace_std_df = final_gw_da.std(['lat', 'lon']).to_dataframe('grace_std').reset_index()[['time', 'grace_std']]\n",
    "grace_std_df.set_index(pd.to_datetime(grace_std_df.time), inplace=True)\n",
    "grace_std_df.drop(columns=['time'], inplace=True)\n",
    "grace_std_df.interpolate(method='cubic', inplace=True)\n",
    "grace_std_df = grace_std_df.resample('M').fillna(method='pad')\n",
    "grace_std_df.reset_index(inplace=True)\n",
    "grace_std_df['time'] = grace_std_df['time'].apply(lambda x: x.to_pydatetime().replace(day=1, hour=0))\n",
    "grace_std_df"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3edf7b05-a45d-4ee4-a725-9e2deb60cbb6",
   "metadata": {},
   "source": [
    "# Merge GRACE and GLDAS. Calculate Ground Water Storage."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "id": "ae1f8ec5-98d1-445f-98c8-93d3c87dac70",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Mergin GRACE dataframe and GLDAS dataframe on time\n",
    "merged_df = (tws_df\n",
    "             .merge(df_sync_grc[['time', 'twsa_fill']], on='time')\n",
    "             .merge(grace_std_df, on='time')\n",
    "             .merge(tws_std_df, on='time')\n",
    "             .merge(canopy_std_df, on='time')\n",
    "             .merge(sm_std_df, on='time')\n",
    "             .merge(swe_std_df, on='time'))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "id": "1e400f70-ab68-4147-937c-327d53fd35bb",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Subtracting GRACE TWSa from GLDAS TWS to calculate ground waterstorage\n",
    "merged_df['gw_storage'] = merged_df['twsa_fill'] - merged_df['mean_tws']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "id": "ca018ad2-b9a4-4690-a8f1-0de5483ce6fb",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>time</th>\n",
       "      <th>mean_tws</th>\n",
       "      <th>twsa_fill</th>\n",
       "      <th>grace_std</th>\n",
       "      <th>std_tws</th>\n",
       "      <th>std_canopy</th>\n",
       "      <th>std_sm</th>\n",
       "      <th>std_swe</th>\n",
       "      <th>gw_storage</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2002-04-01</td>\n",
       "      <td>-11.229002</td>\n",
       "      <td>-6.532770</td>\n",
       "      <td>11.323719</td>\n",
       "      <td>2.782853</td>\n",
       "      <td>0.000433</td>\n",
       "      <td>2.782432</td>\n",
       "      <td>0.0</td>\n",
       "      <td>4.696232</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2002-05-01</td>\n",
       "      <td>-6.748051</td>\n",
       "      <td>0.028998</td>\n",
       "      <td>12.902123</td>\n",
       "      <td>3.786122</td>\n",
       "      <td>0.002202</td>\n",
       "      <td>3.784017</td>\n",
       "      <td>0.0</td>\n",
       "      <td>6.777050</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2002-06-01</td>\n",
       "      <td>2.031710</td>\n",
       "      <td>19.116401</td>\n",
       "      <td>12.902123</td>\n",
       "      <td>4.163500</td>\n",
       "      <td>0.004866</td>\n",
       "      <td>4.158756</td>\n",
       "      <td>0.0</td>\n",
       "      <td>17.084691</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2002-07-01</td>\n",
       "      <td>16.156021</td>\n",
       "      <td>51.594553</td>\n",
       "      <td>12.902123</td>\n",
       "      <td>2.256581</td>\n",
       "      <td>0.007013</td>\n",
       "      <td>2.262857</td>\n",
       "      <td>0.0</td>\n",
       "      <td>35.438532</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2002-08-01</td>\n",
       "      <td>17.587461</td>\n",
       "      <td>56.115878</td>\n",
       "      <td>17.343568</td>\n",
       "      <td>5.322464</td>\n",
       "      <td>0.003253</td>\n",
       "      <td>5.325474</td>\n",
       "      <td>0.0</td>\n",
       "      <td>38.528416</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>221</th>\n",
       "      <td>2020-09-01</td>\n",
       "      <td>15.017552</td>\n",
       "      <td>29.498407</td>\n",
       "      <td>9.639095</td>\n",
       "      <td>2.478384</td>\n",
       "      <td>0.003472</td>\n",
       "      <td>2.481580</td>\n",
       "      <td>0.0</td>\n",
       "      <td>14.480855</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>222</th>\n",
       "      <td>2020-10-01</td>\n",
       "      <td>13.221290</td>\n",
       "      <td>32.547862</td>\n",
       "      <td>15.387149</td>\n",
       "      <td>4.363169</td>\n",
       "      <td>0.000799</td>\n",
       "      <td>4.362380</td>\n",
       "      <td>0.0</td>\n",
       "      <td>19.326572</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>223</th>\n",
       "      <td>2020-11-01</td>\n",
       "      <td>5.768155</td>\n",
       "      <td>6.290697</td>\n",
       "      <td>21.247063</td>\n",
       "      <td>4.192047</td>\n",
       "      <td>0.002496</td>\n",
       "      <td>4.189594</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.522541</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>224</th>\n",
       "      <td>2020-12-01</td>\n",
       "      <td>0.015571</td>\n",
       "      <td>-7.802380</td>\n",
       "      <td>21.916328</td>\n",
       "      <td>3.194324</td>\n",
       "      <td>0.002753</td>\n",
       "      <td>3.191927</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-7.817951</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>225</th>\n",
       "      <td>2021-01-01</td>\n",
       "      <td>-4.987467</td>\n",
       "      <td>-20.422047</td>\n",
       "      <td>23.138380</td>\n",
       "      <td>2.409556</td>\n",
       "      <td>0.002697</td>\n",
       "      <td>2.408298</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-15.434580</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>226 rows × 9 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "          time   mean_tws  twsa_fill  grace_std   std_tws  std_canopy  \\\n",
       "0   2002-04-01 -11.229002  -6.532770  11.323719  2.782853    0.000433   \n",
       "1   2002-05-01  -6.748051   0.028998  12.902123  3.786122    0.002202   \n",
       "2   2002-06-01   2.031710  19.116401  12.902123  4.163500    0.004866   \n",
       "3   2002-07-01  16.156021  51.594553  12.902123  2.256581    0.007013   \n",
       "4   2002-08-01  17.587461  56.115878  17.343568  5.322464    0.003253   \n",
       "..         ...        ...        ...        ...       ...         ...   \n",
       "221 2020-09-01  15.017552  29.498407   9.639095  2.478384    0.003472   \n",
       "222 2020-10-01  13.221290  32.547862  15.387149  4.363169    0.000799   \n",
       "223 2020-11-01   5.768155   6.290697  21.247063  4.192047    0.002496   \n",
       "224 2020-12-01   0.015571  -7.802380  21.916328  3.194324    0.002753   \n",
       "225 2021-01-01  -4.987467 -20.422047  23.138380  2.409556    0.002697   \n",
       "\n",
       "       std_sm  std_swe  gw_storage  \n",
       "0    2.782432      0.0    4.696232  \n",
       "1    3.784017      0.0    6.777050  \n",
       "2    4.158756      0.0   17.084691  \n",
       "3    2.262857      0.0   35.438532  \n",
       "4    5.325474      0.0   38.528416  \n",
       "..        ...      ...         ...  \n",
       "221  2.481580      0.0   14.480855  \n",
       "222  4.362380      0.0   19.326572  \n",
       "223  4.189594      0.0    0.522541  \n",
       "224  3.191927      0.0   -7.817951  \n",
       "225  2.408298      0.0  -15.434580  \n",
       "\n",
       "[226 rows x 9 columns]"
      ]
     },
     "execution_count": 52,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "merged_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "id": "eb508cb0-660e-474f-a586-d807295cbc37",
   "metadata": {},
   "outputs": [],
   "source": [
    "merged_df['uncertainty_paper'] = np.sqrt(np.abs(merged_df.grace_std**2 - merged_df.std_sm**2 - merged_df.std_swe**2 - merged_df.std_canopy**2))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "id": "18838cbe-5a80-4351-a9fd-45646f6a4346",
   "metadata": {},
   "outputs": [],
   "source": [
    "merged_df['uncertainty'] = np.sqrt(np.abs(merged_df.grace_std**2 - merged_df.std_tws**2))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "id": "81d9bf19-0444-45af-935b-fef1c5cf6411",
   "metadata": {},
   "outputs": [],
   "source": [
    "pd.set_option(\"display.max_rows\", None, \"display.max_columns\", None)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "id": "a686c372-7d5a-4ece-8c77-1b0b1b1cf684",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>time</th>\n",
       "      <th>mean_tws</th>\n",
       "      <th>twsa_fill</th>\n",
       "      <th>grace_std</th>\n",
       "      <th>std_tws</th>\n",
       "      <th>std_canopy</th>\n",
       "      <th>std_sm</th>\n",
       "      <th>std_swe</th>\n",
       "      <th>gw_storage</th>\n",
       "      <th>uncertainty_paper</th>\n",
       "      <th>uncertainty</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>2002-04-01</td>\n",
       "      <td>-11.229002</td>\n",
       "      <td>-6.532770</td>\n",
       "      <td>11.323719</td>\n",
       "      <td>2.782853</td>\n",
       "      <td>0.000433</td>\n",
       "      <td>2.782432</td>\n",
       "      <td>0.0</td>\n",
       "      <td>4.696232</td>\n",
       "      <td>10.976552</td>\n",
       "      <td>10.976445</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>2002-05-01</td>\n",
       "      <td>-6.748051</td>\n",
       "      <td>0.028998</td>\n",
       "      <td>12.902123</td>\n",
       "      <td>3.786122</td>\n",
       "      <td>0.002202</td>\n",
       "      <td>3.784017</td>\n",
       "      <td>0.0</td>\n",
       "      <td>6.777050</td>\n",
       "      <td>12.334747</td>\n",
       "      <td>12.334101</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2002-06-01</td>\n",
       "      <td>2.031710</td>\n",
       "      <td>19.116401</td>\n",
       "      <td>12.902123</td>\n",
       "      <td>4.163500</td>\n",
       "      <td>0.004866</td>\n",
       "      <td>4.158756</td>\n",
       "      <td>0.0</td>\n",
       "      <td>17.084691</td>\n",
       "      <td>12.213496</td>\n",
       "      <td>12.211881</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>2002-07-01</td>\n",
       "      <td>16.156021</td>\n",
       "      <td>51.594553</td>\n",
       "      <td>12.902123</td>\n",
       "      <td>2.256581</td>\n",
       "      <td>0.007013</td>\n",
       "      <td>2.262857</td>\n",
       "      <td>0.0</td>\n",
       "      <td>35.438532</td>\n",
       "      <td>12.702134</td>\n",
       "      <td>12.703252</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>2002-08-01</td>\n",
       "      <td>17.587461</td>\n",
       "      <td>56.115878</td>\n",
       "      <td>17.343568</td>\n",
       "      <td>5.322464</td>\n",
       "      <td>0.003253</td>\n",
       "      <td>5.325474</td>\n",
       "      <td>0.0</td>\n",
       "      <td>38.528416</td>\n",
       "      <td>16.505716</td>\n",
       "      <td>16.506687</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>2002-09-01</td>\n",
       "      <td>15.443497</td>\n",
       "      <td>43.263017</td>\n",
       "      <td>17.926438</td>\n",
       "      <td>5.213158</td>\n",
       "      <td>0.001283</td>\n",
       "      <td>5.214303</td>\n",
       "      <td>0.0</td>\n",
       "      <td>27.819520</td>\n",
       "      <td>17.151333</td>\n",
       "      <td>17.151681</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>2002-10-01</td>\n",
       "      <td>14.230325</td>\n",
       "      <td>32.766144</td>\n",
       "      <td>10.485881</td>\n",
       "      <td>5.730409</td>\n",
       "      <td>0.001592</td>\n",
       "      <td>5.728845</td>\n",
       "      <td>0.0</td>\n",
       "      <td>18.535820</td>\n",
       "      <td>8.782598</td>\n",
       "      <td>8.781578</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>2002-11-01</td>\n",
       "      <td>7.516800</td>\n",
       "      <td>10.102582</td>\n",
       "      <td>9.234070</td>\n",
       "      <td>5.576715</td>\n",
       "      <td>0.002231</td>\n",
       "      <td>5.574764</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.585782</td>\n",
       "      <td>7.361389</td>\n",
       "      <td>7.359911</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>2002-12-01</td>\n",
       "      <td>2.094432</td>\n",
       "      <td>-1.095195</td>\n",
       "      <td>7.788890</td>\n",
       "      <td>4.919833</td>\n",
       "      <td>0.002713</td>\n",
       "      <td>4.917898</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-3.189627</td>\n",
       "      <td>6.039957</td>\n",
       "      <td>6.038381</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>2003-01-01</td>\n",
       "      <td>-2.489345</td>\n",
       "      <td>-2.082164</td>\n",
       "      <td>10.765632</td>\n",
       "      <td>4.664026</td>\n",
       "      <td>0.002426</td>\n",
       "      <td>4.662937</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.407181</td>\n",
       "      <td>9.703394</td>\n",
       "      <td>9.702870</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>2003-02-01</td>\n",
       "      <td>-6.028713</td>\n",
       "      <td>-12.836875</td>\n",
       "      <td>10.677366</td>\n",
       "      <td>4.342949</td>\n",
       "      <td>0.001781</td>\n",
       "      <td>4.342648</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-6.808162</td>\n",
       "      <td>9.754361</td>\n",
       "      <td>9.754227</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>2003-03-01</td>\n",
       "      <td>-8.011217</td>\n",
       "      <td>-18.238363</td>\n",
       "      <td>12.887024</td>\n",
       "      <td>3.528340</td>\n",
       "      <td>0.001079</td>\n",
       "      <td>3.528575</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-10.227145</td>\n",
       "      <td>12.394537</td>\n",
       "      <td>12.394604</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>2003-04-01</td>\n",
       "      <td>-9.767217</td>\n",
       "      <td>-9.153495</td>\n",
       "      <td>12.141384</td>\n",
       "      <td>3.130991</td>\n",
       "      <td>0.000408</td>\n",
       "      <td>3.131246</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.613722</td>\n",
       "      <td>11.730666</td>\n",
       "      <td>11.730734</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>2003-05-01</td>\n",
       "      <td>-9.338281</td>\n",
       "      <td>-5.839181</td>\n",
       "      <td>11.729268</td>\n",
       "      <td>3.761060</td>\n",
       "      <td>0.000961</td>\n",
       "      <td>3.760173</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3.499101</td>\n",
       "      <td>11.110213</td>\n",
       "      <td>11.109913</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>2003-06-01</td>\n",
       "      <td>-3.469807</td>\n",
       "      <td>13.248222</td>\n",
       "      <td>11.729268</td>\n",
       "      <td>5.126579</td>\n",
       "      <td>0.004736</td>\n",
       "      <td>5.122245</td>\n",
       "      <td>0.0</td>\n",
       "      <td>16.718029</td>\n",
       "      <td>10.551697</td>\n",
       "      <td>10.549593</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>2003-07-01</td>\n",
       "      <td>10.941452</td>\n",
       "      <td>48.122491</td>\n",
       "      <td>19.449624</td>\n",
       "      <td>1.226065</td>\n",
       "      <td>0.003634</td>\n",
       "      <td>1.224863</td>\n",
       "      <td>0.0</td>\n",
       "      <td>37.181040</td>\n",
       "      <td>19.411017</td>\n",
       "      <td>19.410941</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>2003-08-01</td>\n",
       "      <td>13.254915</td>\n",
       "      <td>42.298563</td>\n",
       "      <td>15.783157</td>\n",
       "      <td>2.489112</td>\n",
       "      <td>0.002329</td>\n",
       "      <td>2.491428</td>\n",
       "      <td>0.0</td>\n",
       "      <td>29.043648</td>\n",
       "      <td>15.585276</td>\n",
       "      <td>15.585646</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>2003-09-01</td>\n",
       "      <td>12.810863</td>\n",
       "      <td>42.530672</td>\n",
       "      <td>16.563646</td>\n",
       "      <td>3.135990</td>\n",
       "      <td>0.001856</td>\n",
       "      <td>3.137670</td>\n",
       "      <td>0.0</td>\n",
       "      <td>29.719809</td>\n",
       "      <td>16.263745</td>\n",
       "      <td>16.264069</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>2003-10-01</td>\n",
       "      <td>15.323859</td>\n",
       "      <td>32.059766</td>\n",
       "      <td>9.730202</td>\n",
       "      <td>4.705950</td>\n",
       "      <td>0.000414</td>\n",
       "      <td>4.706036</td>\n",
       "      <td>0.0</td>\n",
       "      <td>16.735906</td>\n",
       "      <td>8.516458</td>\n",
       "      <td>8.516506</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>2003-11-01</td>\n",
       "      <td>9.223135</td>\n",
       "      <td>17.615395</td>\n",
       "      <td>12.080150</td>\n",
       "      <td>5.719372</td>\n",
       "      <td>0.002556</td>\n",
       "      <td>5.717083</td>\n",
       "      <td>0.0</td>\n",
       "      <td>8.392260</td>\n",
       "      <td>10.641663</td>\n",
       "      <td>10.640433</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>2003-12-01</td>\n",
       "      <td>3.334581</td>\n",
       "      <td>2.424833</td>\n",
       "      <td>8.919454</td>\n",
       "      <td>5.184244</td>\n",
       "      <td>0.001803</td>\n",
       "      <td>5.182810</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-0.909747</td>\n",
       "      <td>7.259141</td>\n",
       "      <td>7.258118</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>2004-01-01</td>\n",
       "      <td>-0.982065</td>\n",
       "      <td>-8.009696</td>\n",
       "      <td>10.543709</td>\n",
       "      <td>4.800630</td>\n",
       "      <td>0.002189</td>\n",
       "      <td>4.799495</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-7.027631</td>\n",
       "      <td>9.388005</td>\n",
       "      <td>9.387425</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>2004-02-01</td>\n",
       "      <td>-5.613434</td>\n",
       "      <td>-6.965889</td>\n",
       "      <td>12.049297</td>\n",
       "      <td>4.327398</td>\n",
       "      <td>0.002820</td>\n",
       "      <td>4.326930</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-1.352455</td>\n",
       "      <td>11.245587</td>\n",
       "      <td>11.245407</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>2004-03-01</td>\n",
       "      <td>-10.185071</td>\n",
       "      <td>-21.437331</td>\n",
       "      <td>12.064621</td>\n",
       "      <td>3.021555</td>\n",
       "      <td>0.001876</td>\n",
       "      <td>3.022218</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-11.252260</td>\n",
       "      <td>11.679952</td>\n",
       "      <td>11.680124</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>2004-04-01</td>\n",
       "      <td>-11.324487</td>\n",
       "      <td>-11.132193</td>\n",
       "      <td>14.907668</td>\n",
       "      <td>2.758243</td>\n",
       "      <td>0.000230</td>\n",
       "      <td>2.758018</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.192294</td>\n",
       "      <td>14.650321</td>\n",
       "      <td>14.650278</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>2004-05-01</td>\n",
       "      <td>-9.574932</td>\n",
       "      <td>2.722408</td>\n",
       "      <td>12.772406</td>\n",
       "      <td>4.069171</td>\n",
       "      <td>0.001459</td>\n",
       "      <td>4.067878</td>\n",
       "      <td>0.0</td>\n",
       "      <td>12.297340</td>\n",
       "      <td>12.107300</td>\n",
       "      <td>12.106866</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>2004-06-01</td>\n",
       "      <td>0.818719</td>\n",
       "      <td>14.628752</td>\n",
       "      <td>18.884368</td>\n",
       "      <td>4.914883</td>\n",
       "      <td>0.004938</td>\n",
       "      <td>4.910270</td>\n",
       "      <td>0.0</td>\n",
       "      <td>13.810033</td>\n",
       "      <td>18.234818</td>\n",
       "      <td>18.233575</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>2004-07-01</td>\n",
       "      <td>14.497416</td>\n",
       "      <td>58.404716</td>\n",
       "      <td>25.159448</td>\n",
       "      <td>1.498047</td>\n",
       "      <td>0.004690</td>\n",
       "      <td>1.502733</td>\n",
       "      <td>0.0</td>\n",
       "      <td>43.907300</td>\n",
       "      <td>25.114530</td>\n",
       "      <td>25.114810</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>2004-08-01</td>\n",
       "      <td>13.887342</td>\n",
       "      <td>52.079701</td>\n",
       "      <td>19.168102</td>\n",
       "      <td>4.345226</td>\n",
       "      <td>0.001625</td>\n",
       "      <td>4.346806</td>\n",
       "      <td>0.0</td>\n",
       "      <td>38.192359</td>\n",
       "      <td>18.668728</td>\n",
       "      <td>18.669096</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>2004-09-01</td>\n",
       "      <td>17.315240</td>\n",
       "      <td>50.818241</td>\n",
       "      <td>11.859462</td>\n",
       "      <td>4.568966</td>\n",
       "      <td>0.003375</td>\n",
       "      <td>4.572028</td>\n",
       "      <td>0.0</td>\n",
       "      <td>33.503001</td>\n",
       "      <td>10.942732</td>\n",
       "      <td>10.944011</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>2004-10-01</td>\n",
       "      <td>15.869274</td>\n",
       "      <td>45.318906</td>\n",
       "      <td>6.739501</td>\n",
       "      <td>5.818468</td>\n",
       "      <td>0.000739</td>\n",
       "      <td>5.817771</td>\n",
       "      <td>0.0</td>\n",
       "      <td>29.449632</td>\n",
       "      <td>3.402119</td>\n",
       "      <td>3.400926</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>31</th>\n",
       "      <td>2004-11-01</td>\n",
       "      <td>7.680985</td>\n",
       "      <td>17.903008</td>\n",
       "      <td>11.007083</td>\n",
       "      <td>6.230897</td>\n",
       "      <td>0.002732</td>\n",
       "      <td>6.228481</td>\n",
       "      <td>0.0</td>\n",
       "      <td>10.222023</td>\n",
       "      <td>9.075346</td>\n",
       "      <td>9.073687</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>32</th>\n",
       "      <td>2004-12-01</td>\n",
       "      <td>1.555081</td>\n",
       "      <td>-6.864831</td>\n",
       "      <td>10.095491</td>\n",
       "      <td>5.346214</td>\n",
       "      <td>0.002793</td>\n",
       "      <td>5.344062</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-8.419912</td>\n",
       "      <td>8.565041</td>\n",
       "      <td>8.563698</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>33</th>\n",
       "      <td>2005-01-01</td>\n",
       "      <td>-3.233837</td>\n",
       "      <td>-13.593327</td>\n",
       "      <td>11.199849</td>\n",
       "      <td>4.603600</td>\n",
       "      <td>0.002002</td>\n",
       "      <td>4.602517</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-10.359490</td>\n",
       "      <td>10.210458</td>\n",
       "      <td>10.209970</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>34</th>\n",
       "      <td>2005-02-01</td>\n",
       "      <td>-7.134987</td>\n",
       "      <td>-14.452025</td>\n",
       "      <td>11.415825</td>\n",
       "      <td>3.800555</td>\n",
       "      <td>0.002255</td>\n",
       "      <td>3.800068</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-7.317037</td>\n",
       "      <td>10.764782</td>\n",
       "      <td>10.764610</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>35</th>\n",
       "      <td>2005-03-01</td>\n",
       "      <td>-10.223869</td>\n",
       "      <td>-12.044153</td>\n",
       "      <td>12.825885</td>\n",
       "      <td>2.256807</td>\n",
       "      <td>0.001028</td>\n",
       "      <td>2.257276</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-1.820283</td>\n",
       "      <td>12.625689</td>\n",
       "      <td>12.625773</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>36</th>\n",
       "      <td>2005-04-01</td>\n",
       "      <td>-12.765896</td>\n",
       "      <td>-14.018963</td>\n",
       "      <td>11.763851</td>\n",
       "      <td>2.529005</td>\n",
       "      <td>0.001077</td>\n",
       "      <td>2.530077</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-1.253067</td>\n",
       "      <td>11.488555</td>\n",
       "      <td>11.488791</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>37</th>\n",
       "      <td>2005-05-01</td>\n",
       "      <td>-13.779052</td>\n",
       "      <td>-7.585786</td>\n",
       "      <td>18.515487</td>\n",
       "      <td>4.253897</td>\n",
       "      <td>0.000395</td>\n",
       "      <td>4.253686</td>\n",
       "      <td>0.0</td>\n",
       "      <td>6.193266</td>\n",
       "      <td>18.020250</td>\n",
       "      <td>18.020200</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>38</th>\n",
       "      <td>2005-06-01</td>\n",
       "      <td>-6.053177</td>\n",
       "      <td>2.516844</td>\n",
       "      <td>16.912282</td>\n",
       "      <td>6.371356</td>\n",
       "      <td>0.001859</td>\n",
       "      <td>6.369921</td>\n",
       "      <td>0.0</td>\n",
       "      <td>8.570020</td>\n",
       "      <td>15.666825</td>\n",
       "      <td>15.666241</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>39</th>\n",
       "      <td>2005-07-01</td>\n",
       "      <td>5.048038</td>\n",
       "      <td>29.894489</td>\n",
       "      <td>17.435816</td>\n",
       "      <td>5.329369</td>\n",
       "      <td>0.003641</td>\n",
       "      <td>5.326925</td>\n",
       "      <td>0.0</td>\n",
       "      <td>24.846451</td>\n",
       "      <td>16.602154</td>\n",
       "      <td>16.601371</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>40</th>\n",
       "      <td>2005-08-01</td>\n",
       "      <td>12.969151</td>\n",
       "      <td>39.780794</td>\n",
       "      <td>14.757584</td>\n",
       "      <td>2.436030</td>\n",
       "      <td>0.003871</td>\n",
       "      <td>2.437925</td>\n",
       "      <td>0.0</td>\n",
       "      <td>26.811643</td>\n",
       "      <td>14.554821</td>\n",
       "      <td>14.555138</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>41</th>\n",
       "      <td>2005-09-01</td>\n",
       "      <td>13.881463</td>\n",
       "      <td>37.185736</td>\n",
       "      <td>13.371876</td>\n",
       "      <td>3.486384</td>\n",
       "      <td>0.001113</td>\n",
       "      <td>3.487495</td>\n",
       "      <td>0.0</td>\n",
       "      <td>23.304272</td>\n",
       "      <td>12.909084</td>\n",
       "      <td>12.909384</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>42</th>\n",
       "      <td>2005-10-01</td>\n",
       "      <td>15.328437</td>\n",
       "      <td>29.471504</td>\n",
       "      <td>10.005572</td>\n",
       "      <td>4.069964</td>\n",
       "      <td>0.000226</td>\n",
       "      <td>4.070113</td>\n",
       "      <td>0.0</td>\n",
       "      <td>14.143068</td>\n",
       "      <td>9.140331</td>\n",
       "      <td>9.140397</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>43</th>\n",
       "      <td>2005-11-01</td>\n",
       "      <td>10.693533</td>\n",
       "      <td>10.314751</td>\n",
       "      <td>7.335094</td>\n",
       "      <td>5.271275</td>\n",
       "      <td>0.002623</td>\n",
       "      <td>5.268741</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-0.378782</td>\n",
       "      <td>5.103329</td>\n",
       "      <td>5.100712</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>44</th>\n",
       "      <td>2005-12-01</td>\n",
       "      <td>4.162937</td>\n",
       "      <td>-0.910949</td>\n",
       "      <td>6.972660</td>\n",
       "      <td>4.598862</td>\n",
       "      <td>0.002806</td>\n",
       "      <td>4.596342</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-5.073886</td>\n",
       "      <td>5.243245</td>\n",
       "      <td>5.241036</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>45</th>\n",
       "      <td>2006-01-01</td>\n",
       "      <td>-1.432504</td>\n",
       "      <td>-12.298131</td>\n",
       "      <td>7.277517</td>\n",
       "      <td>3.456537</td>\n",
       "      <td>0.002817</td>\n",
       "      <td>3.454466</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-10.865626</td>\n",
       "      <td>6.405382</td>\n",
       "      <td>6.404264</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>46</th>\n",
       "      <td>2006-02-01</td>\n",
       "      <td>-6.741870</td>\n",
       "      <td>-18.143863</td>\n",
       "      <td>7.321646</td>\n",
       "      <td>2.205315</td>\n",
       "      <td>0.002808</td>\n",
       "      <td>2.204349</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-11.401993</td>\n",
       "      <td>6.981929</td>\n",
       "      <td>6.981624</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>47</th>\n",
       "      <td>2006-03-01</td>\n",
       "      <td>-12.302053</td>\n",
       "      <td>-26.642624</td>\n",
       "      <td>6.416209</td>\n",
       "      <td>1.370398</td>\n",
       "      <td>0.002578</td>\n",
       "      <td>1.372796</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-14.340572</td>\n",
       "      <td>6.267628</td>\n",
       "      <td>6.268153</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>48</th>\n",
       "      <td>2006-04-01</td>\n",
       "      <td>-15.227662</td>\n",
       "      <td>-29.219403</td>\n",
       "      <td>11.720964</td>\n",
       "      <td>3.271488</td>\n",
       "      <td>0.001246</td>\n",
       "      <td>3.272605</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-13.991740</td>\n",
       "      <td>11.254824</td>\n",
       "      <td>11.255148</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>49</th>\n",
       "      <td>2006-05-01</td>\n",
       "      <td>-15.237675</td>\n",
       "      <td>-25.487442</td>\n",
       "      <td>12.453093</td>\n",
       "      <td>5.021224</td>\n",
       "      <td>0.001441</td>\n",
       "      <td>5.020188</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-10.249767</td>\n",
       "      <td>11.396369</td>\n",
       "      <td>11.395913</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50</th>\n",
       "      <td>2006-06-01</td>\n",
       "      <td>-1.448422</td>\n",
       "      <td>11.436324</td>\n",
       "      <td>11.203513</td>\n",
       "      <td>6.820291</td>\n",
       "      <td>0.003816</td>\n",
       "      <td>6.817257</td>\n",
       "      <td>0.0</td>\n",
       "      <td>12.884746</td>\n",
       "      <td>8.890651</td>\n",
       "      <td>8.888325</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>51</th>\n",
       "      <td>2006-07-01</td>\n",
       "      <td>5.209481</td>\n",
       "      <td>27.750855</td>\n",
       "      <td>9.867478</td>\n",
       "      <td>4.582654</td>\n",
       "      <td>0.002047</td>\n",
       "      <td>4.581153</td>\n",
       "      <td>0.0</td>\n",
       "      <td>22.541373</td>\n",
       "      <td>8.739575</td>\n",
       "      <td>8.738788</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>52</th>\n",
       "      <td>2006-08-01</td>\n",
       "      <td>6.352994</td>\n",
       "      <td>24.377789</td>\n",
       "      <td>8.392375</td>\n",
       "      <td>3.497628</td>\n",
       "      <td>0.001556</td>\n",
       "      <td>3.496866</td>\n",
       "      <td>0.0</td>\n",
       "      <td>18.024795</td>\n",
       "      <td>7.629147</td>\n",
       "      <td>7.628798</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>53</th>\n",
       "      <td>2006-09-01</td>\n",
       "      <td>10.399671</td>\n",
       "      <td>28.976714</td>\n",
       "      <td>8.690446</td>\n",
       "      <td>2.141101</td>\n",
       "      <td>0.002388</td>\n",
       "      <td>2.141063</td>\n",
       "      <td>0.0</td>\n",
       "      <td>18.577043</td>\n",
       "      <td>8.422571</td>\n",
       "      <td>8.422562</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>54</th>\n",
       "      <td>2006-10-01</td>\n",
       "      <td>10.040683</td>\n",
       "      <td>24.034197</td>\n",
       "      <td>8.407208</td>\n",
       "      <td>2.588272</td>\n",
       "      <td>0.001185</td>\n",
       "      <td>2.587100</td>\n",
       "      <td>0.0</td>\n",
       "      <td>13.993514</td>\n",
       "      <td>7.999253</td>\n",
       "      <td>7.998874</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>55</th>\n",
       "      <td>2006-11-01</td>\n",
       "      <td>3.269239</td>\n",
       "      <td>2.876260</td>\n",
       "      <td>9.569891</td>\n",
       "      <td>2.125421</td>\n",
       "      <td>0.002165</td>\n",
       "      <td>2.123278</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-0.392979</td>\n",
       "      <td>9.331372</td>\n",
       "      <td>9.330885</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>56</th>\n",
       "      <td>2006-12-01</td>\n",
       "      <td>-2.477746</td>\n",
       "      <td>-3.765012</td>\n",
       "      <td>5.703908</td>\n",
       "      <td>1.412641</td>\n",
       "      <td>0.002689</td>\n",
       "      <td>1.411139</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-1.287266</td>\n",
       "      <td>5.526594</td>\n",
       "      <td>5.526211</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>57</th>\n",
       "      <td>2007-01-01</td>\n",
       "      <td>-7.605655</td>\n",
       "      <td>-19.622432</td>\n",
       "      <td>7.482212</td>\n",
       "      <td>1.787315</td>\n",
       "      <td>0.002831</td>\n",
       "      <td>1.788608</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-12.016777</td>\n",
       "      <td>7.265285</td>\n",
       "      <td>7.265603</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>58</th>\n",
       "      <td>2007-02-01</td>\n",
       "      <td>-10.028605</td>\n",
       "      <td>-18.181312</td>\n",
       "      <td>7.307836</td>\n",
       "      <td>2.628142</td>\n",
       "      <td>0.000550</td>\n",
       "      <td>2.628513</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-8.152707</td>\n",
       "      <td>6.818753</td>\n",
       "      <td>6.818896</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>59</th>\n",
       "      <td>2007-03-01</td>\n",
       "      <td>-12.934819</td>\n",
       "      <td>-23.211356</td>\n",
       "      <td>10.611340</td>\n",
       "      <td>3.218929</td>\n",
       "      <td>0.002474</td>\n",
       "      <td>3.221399</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-10.276537</td>\n",
       "      <td>10.110545</td>\n",
       "      <td>10.111332</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>60</th>\n",
       "      <td>2007-04-01</td>\n",
       "      <td>-16.183223</td>\n",
       "      <td>-20.189578</td>\n",
       "      <td>6.739960</td>\n",
       "      <td>4.502524</td>\n",
       "      <td>0.001625</td>\n",
       "      <td>4.504026</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-4.006355</td>\n",
       "      <td>5.014061</td>\n",
       "      <td>5.015410</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>61</th>\n",
       "      <td>2007-05-01</td>\n",
       "      <td>-16.516297</td>\n",
       "      <td>-17.979053</td>\n",
       "      <td>3.777471</td>\n",
       "      <td>5.657269</td>\n",
       "      <td>0.000628</td>\n",
       "      <td>5.656841</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-1.462756</td>\n",
       "      <td>4.210767</td>\n",
       "      <td>4.211342</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>62</th>\n",
       "      <td>2007-06-01</td>\n",
       "      <td>-2.753546</td>\n",
       "      <td>11.231308</td>\n",
       "      <td>11.846230</td>\n",
       "      <td>6.824715</td>\n",
       "      <td>0.004048</td>\n",
       "      <td>6.821504</td>\n",
       "      <td>0.0</td>\n",
       "      <td>13.984854</td>\n",
       "      <td>9.685052</td>\n",
       "      <td>9.682790</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>63</th>\n",
       "      <td>2007-07-01</td>\n",
       "      <td>7.367433</td>\n",
       "      <td>36.262122</td>\n",
       "      <td>10.423697</td>\n",
       "      <td>4.052601</td>\n",
       "      <td>0.005301</td>\n",
       "      <td>4.049263</td>\n",
       "      <td>0.0</td>\n",
       "      <td>28.894688</td>\n",
       "      <td>9.605046</td>\n",
       "      <td>9.603639</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>64</th>\n",
       "      <td>2007-08-01</td>\n",
       "      <td>15.237857</td>\n",
       "      <td>59.456432</td>\n",
       "      <td>11.004005</td>\n",
       "      <td>3.091184</td>\n",
       "      <td>0.003093</td>\n",
       "      <td>3.094214</td>\n",
       "      <td>0.0</td>\n",
       "      <td>44.218575</td>\n",
       "      <td>10.560017</td>\n",
       "      <td>10.560905</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>65</th>\n",
       "      <td>2007-09-01</td>\n",
       "      <td>17.101064</td>\n",
       "      <td>53.836445</td>\n",
       "      <td>9.324450</td>\n",
       "      <td>4.601147</td>\n",
       "      <td>0.003604</td>\n",
       "      <td>4.604623</td>\n",
       "      <td>0.0</td>\n",
       "      <td>36.735381</td>\n",
       "      <td>8.108193</td>\n",
       "      <td>8.110167</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>66</th>\n",
       "      <td>2007-10-01</td>\n",
       "      <td>14.267415</td>\n",
       "      <td>31.877598</td>\n",
       "      <td>2.374934</td>\n",
       "      <td>5.604014</td>\n",
       "      <td>0.000861</td>\n",
       "      <td>5.603176</td>\n",
       "      <td>0.0</td>\n",
       "      <td>17.610183</td>\n",
       "      <td>5.074965</td>\n",
       "      <td>5.075890</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>67</th>\n",
       "      <td>2007-11-01</td>\n",
       "      <td>8.071233</td>\n",
       "      <td>9.736710</td>\n",
       "      <td>4.327803</td>\n",
       "      <td>5.561957</td>\n",
       "      <td>0.002003</td>\n",
       "      <td>5.560143</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.665477</td>\n",
       "      <td>3.490747</td>\n",
       "      <td>3.493635</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>68</th>\n",
       "      <td>2007-12-01</td>\n",
       "      <td>2.473500</td>\n",
       "      <td>3.641468</td>\n",
       "      <td>1.611227</td>\n",
       "      <td>4.869285</td>\n",
       "      <td>0.002781</td>\n",
       "      <td>4.867257</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.167967</td>\n",
       "      <td>4.592836</td>\n",
       "      <td>4.594985</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>69</th>\n",
       "      <td>2008-01-01</td>\n",
       "      <td>-2.167325</td>\n",
       "      <td>-14.570775</td>\n",
       "      <td>8.354411</td>\n",
       "      <td>4.153670</td>\n",
       "      <td>0.001811</td>\n",
       "      <td>4.152811</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-12.403450</td>\n",
       "      <td>7.249161</td>\n",
       "      <td>7.248669</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>70</th>\n",
       "      <td>2008-02-01</td>\n",
       "      <td>-5.047356</td>\n",
       "      <td>-16.582186</td>\n",
       "      <td>6.967726</td>\n",
       "      <td>3.763908</td>\n",
       "      <td>0.002506</td>\n",
       "      <td>3.763609</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-11.534830</td>\n",
       "      <td>5.863826</td>\n",
       "      <td>5.863634</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>71</th>\n",
       "      <td>2008-03-01</td>\n",
       "      <td>-8.857948</td>\n",
       "      <td>-17.176624</td>\n",
       "      <td>3.700120</td>\n",
       "      <td>2.731230</td>\n",
       "      <td>0.001243</td>\n",
       "      <td>2.731683</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-8.318675</td>\n",
       "      <td>2.495755</td>\n",
       "      <td>2.496252</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>72</th>\n",
       "      <td>2008-04-01</td>\n",
       "      <td>-12.005633</td>\n",
       "      <td>-14.612592</td>\n",
       "      <td>5.450157</td>\n",
       "      <td>2.569548</td>\n",
       "      <td>0.001306</td>\n",
       "      <td>2.570854</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-2.606959</td>\n",
       "      <td>4.805718</td>\n",
       "      <td>4.806416</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>73</th>\n",
       "      <td>2008-05-01</td>\n",
       "      <td>-13.379781</td>\n",
       "      <td>-14.622052</td>\n",
       "      <td>4.257626</td>\n",
       "      <td>4.404862</td>\n",
       "      <td>0.001519</td>\n",
       "      <td>4.403662</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-1.242272</td>\n",
       "      <td>1.124662</td>\n",
       "      <td>1.129352</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>74</th>\n",
       "      <td>2008-06-01</td>\n",
       "      <td>-2.819744</td>\n",
       "      <td>4.560556</td>\n",
       "      <td>9.099045</td>\n",
       "      <td>6.634129</td>\n",
       "      <td>0.002586</td>\n",
       "      <td>6.632092</td>\n",
       "      <td>0.0</td>\n",
       "      <td>7.380300</td>\n",
       "      <td>6.229604</td>\n",
       "      <td>6.227436</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75</th>\n",
       "      <td>2008-07-01</td>\n",
       "      <td>7.163965</td>\n",
       "      <td>38.139954</td>\n",
       "      <td>8.630185</td>\n",
       "      <td>4.909314</td>\n",
       "      <td>0.003969</td>\n",
       "      <td>4.906649</td>\n",
       "      <td>0.0</td>\n",
       "      <td>30.975988</td>\n",
       "      <td>7.099639</td>\n",
       "      <td>7.097797</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>76</th>\n",
       "      <td>2008-08-01</td>\n",
       "      <td>13.168807</td>\n",
       "      <td>47.684170</td>\n",
       "      <td>11.563436</td>\n",
       "      <td>2.417443</td>\n",
       "      <td>0.003981</td>\n",
       "      <td>2.419674</td>\n",
       "      <td>0.0</td>\n",
       "      <td>34.515363</td>\n",
       "      <td>11.307441</td>\n",
       "      <td>11.307919</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>77</th>\n",
       "      <td>2008-09-01</td>\n",
       "      <td>15.047499</td>\n",
       "      <td>48.172022</td>\n",
       "      <td>9.077226</td>\n",
       "      <td>3.811473</td>\n",
       "      <td>0.002331</td>\n",
       "      <td>3.813775</td>\n",
       "      <td>0.0</td>\n",
       "      <td>33.124524</td>\n",
       "      <td>8.237181</td>\n",
       "      <td>8.238247</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>78</th>\n",
       "      <td>2008-10-01</td>\n",
       "      <td>12.463551</td>\n",
       "      <td>27.939612</td>\n",
       "      <td>4.919838</td>\n",
       "      <td>4.375666</td>\n",
       "      <td>0.000115</td>\n",
       "      <td>4.375607</td>\n",
       "      <td>0.0</td>\n",
       "      <td>15.476061</td>\n",
       "      <td>2.249192</td>\n",
       "      <td>2.249078</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>79</th>\n",
       "      <td>2008-11-01</td>\n",
       "      <td>6.960910</td>\n",
       "      <td>0.174751</td>\n",
       "      <td>4.714551</td>\n",
       "      <td>4.230669</td>\n",
       "      <td>0.002425</td>\n",
       "      <td>4.228494</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-6.786159</td>\n",
       "      <td>2.084905</td>\n",
       "      <td>2.080490</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>80</th>\n",
       "      <td>2008-12-01</td>\n",
       "      <td>1.351667</td>\n",
       "      <td>-12.277944</td>\n",
       "      <td>4.934047</td>\n",
       "      <td>3.930062</td>\n",
       "      <td>0.002716</td>\n",
       "      <td>3.928355</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-13.629611</td>\n",
       "      <td>2.985438</td>\n",
       "      <td>2.983191</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>81</th>\n",
       "      <td>2009-01-01</td>\n",
       "      <td>-3.677429</td>\n",
       "      <td>-16.777630</td>\n",
       "      <td>5.882510</td>\n",
       "      <td>3.740274</td>\n",
       "      <td>0.002765</td>\n",
       "      <td>3.739615</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-13.100201</td>\n",
       "      <td>4.540837</td>\n",
       "      <td>4.540295</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>82</th>\n",
       "      <td>2009-02-01</td>\n",
       "      <td>-8.494066</td>\n",
       "      <td>-21.535492</td>\n",
       "      <td>7.306811</td>\n",
       "      <td>3.142305</td>\n",
       "      <td>0.002522</td>\n",
       "      <td>3.142780</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-13.041426</td>\n",
       "      <td>6.596394</td>\n",
       "      <td>6.596621</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>83</th>\n",
       "      <td>2009-03-01</td>\n",
       "      <td>-13.303445</td>\n",
       "      <td>-25.337450</td>\n",
       "      <td>3.457748</td>\n",
       "      <td>2.472357</td>\n",
       "      <td>0.002197</td>\n",
       "      <td>2.474308</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-12.034005</td>\n",
       "      <td>2.415329</td>\n",
       "      <td>2.417327</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>84</th>\n",
       "      <td>2009-04-01</td>\n",
       "      <td>-16.607549</td>\n",
       "      <td>-29.567565</td>\n",
       "      <td>4.661347</td>\n",
       "      <td>3.640013</td>\n",
       "      <td>0.001820</td>\n",
       "      <td>3.641745</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-12.960016</td>\n",
       "      <td>2.909613</td>\n",
       "      <td>2.911780</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>85</th>\n",
       "      <td>2009-05-01</td>\n",
       "      <td>-13.747132</td>\n",
       "      <td>-25.353675</td>\n",
       "      <td>5.991832</td>\n",
       "      <td>5.623733</td>\n",
       "      <td>0.001743</td>\n",
       "      <td>5.622395</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-11.606543</td>\n",
       "      <td>2.071405</td>\n",
       "      <td>2.067770</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>86</th>\n",
       "      <td>2009-06-01</td>\n",
       "      <td>-11.066009</td>\n",
       "      <td>-8.967745</td>\n",
       "      <td>7.651303</td>\n",
       "      <td>7.023500</td>\n",
       "      <td>0.001620</td>\n",
       "      <td>7.022163</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.098265</td>\n",
       "      <td>3.038366</td>\n",
       "      <td>3.035275</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>87</th>\n",
       "      <td>2009-07-01</td>\n",
       "      <td>-2.610020</td>\n",
       "      <td>13.963624</td>\n",
       "      <td>13.918995</td>\n",
       "      <td>7.855471</td>\n",
       "      <td>0.002676</td>\n",
       "      <td>7.853235</td>\n",
       "      <td>0.0</td>\n",
       "      <td>16.573644</td>\n",
       "      <td>11.491959</td>\n",
       "      <td>11.490430</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>88</th>\n",
       "      <td>2009-08-01</td>\n",
       "      <td>9.982275</td>\n",
       "      <td>36.883740</td>\n",
       "      <td>8.940083</td>\n",
       "      <td>4.013251</td>\n",
       "      <td>0.003875</td>\n",
       "      <td>4.011694</td>\n",
       "      <td>0.0</td>\n",
       "      <td>26.901465</td>\n",
       "      <td>7.989455</td>\n",
       "      <td>7.988673</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>89</th>\n",
       "      <td>2009-09-01</td>\n",
       "      <td>11.930132</td>\n",
       "      <td>28.345383</td>\n",
       "      <td>2.093557</td>\n",
       "      <td>2.820072</td>\n",
       "      <td>0.001125</td>\n",
       "      <td>2.820763</td>\n",
       "      <td>0.0</td>\n",
       "      <td>16.415252</td>\n",
       "      <td>1.890429</td>\n",
       "      <td>1.889398</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>90</th>\n",
       "      <td>2009-10-01</td>\n",
       "      <td>10.825113</td>\n",
       "      <td>20.465428</td>\n",
       "      <td>3.047585</td>\n",
       "      <td>2.996949</td>\n",
       "      <td>0.000666</td>\n",
       "      <td>2.996287</td>\n",
       "      <td>0.0</td>\n",
       "      <td>9.640316</td>\n",
       "      <td>0.556810</td>\n",
       "      <td>0.553236</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>91</th>\n",
       "      <td>2009-11-01</td>\n",
       "      <td>4.330891</td>\n",
       "      <td>5.010420</td>\n",
       "      <td>0.791013</td>\n",
       "      <td>2.669655</td>\n",
       "      <td>0.002290</td>\n",
       "      <td>2.667394</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.679529</td>\n",
       "      <td>2.547409</td>\n",
       "      <td>2.549775</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>92</th>\n",
       "      <td>2009-12-01</td>\n",
       "      <td>-1.178747</td>\n",
       "      <td>-12.466815</td>\n",
       "      <td>4.178950</td>\n",
       "      <td>1.537391</td>\n",
       "      <td>0.002715</td>\n",
       "      <td>1.534941</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-11.288068</td>\n",
       "      <td>3.886847</td>\n",
       "      <td>3.885879</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>93</th>\n",
       "      <td>2010-01-01</td>\n",
       "      <td>-6.031552</td>\n",
       "      <td>-14.202218</td>\n",
       "      <td>6.283838</td>\n",
       "      <td>1.361619</td>\n",
       "      <td>0.002775</td>\n",
       "      <td>1.361952</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-8.170666</td>\n",
       "      <td>6.134468</td>\n",
       "      <td>6.134542</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>94</th>\n",
       "      <td>2010-02-01</td>\n",
       "      <td>-10.368890</td>\n",
       "      <td>-22.706006</td>\n",
       "      <td>7.457794</td>\n",
       "      <td>2.017035</td>\n",
       "      <td>0.002405</td>\n",
       "      <td>2.018969</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-12.337117</td>\n",
       "      <td>7.179307</td>\n",
       "      <td>7.179851</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>95</th>\n",
       "      <td>2010-03-01</td>\n",
       "      <td>-14.532393</td>\n",
       "      <td>-35.873630</td>\n",
       "      <td>7.818610</td>\n",
       "      <td>2.971242</td>\n",
       "      <td>0.002297</td>\n",
       "      <td>2.973514</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-21.341237</td>\n",
       "      <td>7.231104</td>\n",
       "      <td>7.232038</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>96</th>\n",
       "      <td>2010-04-01</td>\n",
       "      <td>-16.630136</td>\n",
       "      <td>-25.760638</td>\n",
       "      <td>5.785051</td>\n",
       "      <td>4.700112</td>\n",
       "      <td>0.000609</td>\n",
       "      <td>4.700597</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-9.130502</td>\n",
       "      <td>3.372122</td>\n",
       "      <td>3.372798</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>97</th>\n",
       "      <td>2010-05-01</td>\n",
       "      <td>-12.523227</td>\n",
       "      <td>-12.391820</td>\n",
       "      <td>6.989732</td>\n",
       "      <td>6.511458</td>\n",
       "      <td>0.001030</td>\n",
       "      <td>6.510691</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.131407</td>\n",
       "      <td>2.543081</td>\n",
       "      <td>2.541117</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>98</th>\n",
       "      <td>2010-06-01</td>\n",
       "      <td>-3.665323</td>\n",
       "      <td>5.616780</td>\n",
       "      <td>12.938643</td>\n",
       "      <td>7.954845</td>\n",
       "      <td>0.004152</td>\n",
       "      <td>7.951608</td>\n",
       "      <td>0.0</td>\n",
       "      <td>9.282103</td>\n",
       "      <td>10.206879</td>\n",
       "      <td>10.204358</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>99</th>\n",
       "      <td>2010-07-01</td>\n",
       "      <td>4.451830</td>\n",
       "      <td>30.736937</td>\n",
       "      <td>12.635755</td>\n",
       "      <td>6.324845</td>\n",
       "      <td>0.003088</td>\n",
       "      <td>6.322702</td>\n",
       "      <td>0.0</td>\n",
       "      <td>26.285107</td>\n",
       "      <td>10.940098</td>\n",
       "      <td>10.938859</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>100</th>\n",
       "      <td>2010-08-01</td>\n",
       "      <td>7.717196</td>\n",
       "      <td>29.286877</td>\n",
       "      <td>13.855310</td>\n",
       "      <td>4.062070</td>\n",
       "      <td>0.002850</td>\n",
       "      <td>4.060870</td>\n",
       "      <td>0.0</td>\n",
       "      <td>21.569680</td>\n",
       "      <td>13.246847</td>\n",
       "      <td>13.246479</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>101</th>\n",
       "      <td>2010-09-01</td>\n",
       "      <td>10.614531</td>\n",
       "      <td>33.495004</td>\n",
       "      <td>12.678095</td>\n",
       "      <td>2.431727</td>\n",
       "      <td>0.001053</td>\n",
       "      <td>2.432197</td>\n",
       "      <td>0.0</td>\n",
       "      <td>22.880472</td>\n",
       "      <td>12.442609</td>\n",
       "      <td>12.442701</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>102</th>\n",
       "      <td>2010-10-01</td>\n",
       "      <td>7.531755</td>\n",
       "      <td>24.344580</td>\n",
       "      <td>8.572335</td>\n",
       "      <td>1.998037</td>\n",
       "      <td>0.000733</td>\n",
       "      <td>1.997555</td>\n",
       "      <td>0.0</td>\n",
       "      <td>16.812826</td>\n",
       "      <td>8.336349</td>\n",
       "      <td>8.336233</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>103</th>\n",
       "      <td>2010-11-01</td>\n",
       "      <td>1.593469</td>\n",
       "      <td>3.632127</td>\n",
       "      <td>7.151535</td>\n",
       "      <td>0.911514</td>\n",
       "      <td>0.002251</td>\n",
       "      <td>0.909364</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.038659</td>\n",
       "      <td>7.093484</td>\n",
       "      <td>7.093208</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>104</th>\n",
       "      <td>2010-12-01</td>\n",
       "      <td>-3.092725</td>\n",
       "      <td>-7.012038</td>\n",
       "      <td>3.349813</td>\n",
       "      <td>1.051848</td>\n",
       "      <td>0.001609</td>\n",
       "      <td>1.052040</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-3.919313</td>\n",
       "      <td>3.180323</td>\n",
       "      <td>3.180387</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>105</th>\n",
       "      <td>2011-01-01</td>\n",
       "      <td>-7.178684</td>\n",
       "      <td>-14.531868</td>\n",
       "      <td>3.349813</td>\n",
       "      <td>2.625930</td>\n",
       "      <td>0.002665</td>\n",
       "      <td>2.627608</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-7.353184</td>\n",
       "      <td>2.077719</td>\n",
       "      <td>2.079841</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>106</th>\n",
       "      <td>2011-02-01</td>\n",
       "      <td>-11.015123</td>\n",
       "      <td>-33.733873</td>\n",
       "      <td>6.864693</td>\n",
       "      <td>3.296961</td>\n",
       "      <td>0.002504</td>\n",
       "      <td>3.299031</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-22.718750</td>\n",
       "      <td>6.020000</td>\n",
       "      <td>6.021135</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>107</th>\n",
       "      <td>2011-03-01</td>\n",
       "      <td>-14.317424</td>\n",
       "      <td>-26.306923</td>\n",
       "      <td>2.821568</td>\n",
       "      <td>3.611973</td>\n",
       "      <td>0.002062</td>\n",
       "      <td>3.614012</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-11.989499</td>\n",
       "      <td>2.258283</td>\n",
       "      <td>2.255017</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>108</th>\n",
       "      <td>2011-04-01</td>\n",
       "      <td>-15.753109</td>\n",
       "      <td>-31.614222</td>\n",
       "      <td>1.647603</td>\n",
       "      <td>4.589185</td>\n",
       "      <td>0.001055</td>\n",
       "      <td>4.590205</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-15.861113</td>\n",
       "      <td>4.284319</td>\n",
       "      <td>4.283226</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>109</th>\n",
       "      <td>2011-05-01</td>\n",
       "      <td>-13.520199</td>\n",
       "      <td>-26.429849</td>\n",
       "      <td>1.898686</td>\n",
       "      <td>6.007111</td>\n",
       "      <td>0.000683</td>\n",
       "      <td>6.006562</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-12.909650</td>\n",
       "      <td>5.698578</td>\n",
       "      <td>5.699156</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>110</th>\n",
       "      <td>2011-06-01</td>\n",
       "      <td>-7.912388</td>\n",
       "      <td>-7.342447</td>\n",
       "      <td>1.898686</td>\n",
       "      <td>7.620030</td>\n",
       "      <td>0.003307</td>\n",
       "      <td>7.617259</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.569941</td>\n",
       "      <td>7.376831</td>\n",
       "      <td>7.379692</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>111</th>\n",
       "      <td>2011-07-01</td>\n",
       "      <td>3.621960</td>\n",
       "      <td>22.140427</td>\n",
       "      <td>8.946698</td>\n",
       "      <td>6.513959</td>\n",
       "      <td>0.002156</td>\n",
       "      <td>6.512256</td>\n",
       "      <td>0.0</td>\n",
       "      <td>18.518467</td>\n",
       "      <td>6.134650</td>\n",
       "      <td>6.132842</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>112</th>\n",
       "      <td>2011-08-01</td>\n",
       "      <td>10.812213</td>\n",
       "      <td>39.163391</td>\n",
       "      <td>9.122002</td>\n",
       "      <td>3.587518</td>\n",
       "      <td>0.003377</td>\n",
       "      <td>3.587011</td>\n",
       "      <td>0.0</td>\n",
       "      <td>28.351177</td>\n",
       "      <td>8.387149</td>\n",
       "      <td>8.386933</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>113</th>\n",
       "      <td>2011-09-01</td>\n",
       "      <td>11.598311</td>\n",
       "      <td>30.268203</td>\n",
       "      <td>4.592569</td>\n",
       "      <td>3.203456</td>\n",
       "      <td>0.001120</td>\n",
       "      <td>3.204180</td>\n",
       "      <td>0.0</td>\n",
       "      <td>18.669893</td>\n",
       "      <td>3.290125</td>\n",
       "      <td>3.290830</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>114</th>\n",
       "      <td>2011-10-01</td>\n",
       "      <td>8.697771</td>\n",
       "      <td>15.900142</td>\n",
       "      <td>8.355080</td>\n",
       "      <td>3.626842</td>\n",
       "      <td>0.002072</td>\n",
       "      <td>3.624923</td>\n",
       "      <td>0.0</td>\n",
       "      <td>7.202371</td>\n",
       "      <td>7.527768</td>\n",
       "      <td>7.526844</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>115</th>\n",
       "      <td>2011-11-01</td>\n",
       "      <td>1.467283</td>\n",
       "      <td>2.367258</td>\n",
       "      <td>8.491849</td>\n",
       "      <td>2.527809</td>\n",
       "      <td>0.002592</td>\n",
       "      <td>2.525227</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.899975</td>\n",
       "      <td>8.107695</td>\n",
       "      <td>8.106891</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>116</th>\n",
       "      <td>2011-12-01</td>\n",
       "      <td>-3.933093</td>\n",
       "      <td>-10.946929</td>\n",
       "      <td>8.491849</td>\n",
       "      <td>1.209030</td>\n",
       "      <td>0.002727</td>\n",
       "      <td>1.206700</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-7.013836</td>\n",
       "      <td>8.405674</td>\n",
       "      <td>8.405340</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>117</th>\n",
       "      <td>2012-01-01</td>\n",
       "      <td>-7.634749</td>\n",
       "      <td>-21.137810</td>\n",
       "      <td>7.371879</td>\n",
       "      <td>1.519832</td>\n",
       "      <td>0.002222</td>\n",
       "      <td>1.520573</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-13.503061</td>\n",
       "      <td>7.213352</td>\n",
       "      <td>7.213509</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>118</th>\n",
       "      <td>2012-02-01</td>\n",
       "      <td>-11.593522</td>\n",
       "      <td>-23.971587</td>\n",
       "      <td>7.393879</td>\n",
       "      <td>2.143481</td>\n",
       "      <td>0.002676</td>\n",
       "      <td>2.145792</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-12.378066</td>\n",
       "      <td>7.075663</td>\n",
       "      <td>7.076364</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>119</th>\n",
       "      <td>2012-03-01</td>\n",
       "      <td>-15.937175</td>\n",
       "      <td>-38.308842</td>\n",
       "      <td>9.561214</td>\n",
       "      <td>3.043960</td>\n",
       "      <td>0.002644</td>\n",
       "      <td>3.046575</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-22.371667</td>\n",
       "      <td>9.062847</td>\n",
       "      <td>9.063726</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>120</th>\n",
       "      <td>2012-04-01</td>\n",
       "      <td>-15.493318</td>\n",
       "      <td>-36.232712</td>\n",
       "      <td>7.794970</td>\n",
       "      <td>4.600056</td>\n",
       "      <td>0.000183</td>\n",
       "      <td>4.599952</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-20.739395</td>\n",
       "      <td>6.293012</td>\n",
       "      <td>6.292936</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>121</th>\n",
       "      <td>2012-05-01</td>\n",
       "      <td>-15.980019</td>\n",
       "      <td>-27.817640</td>\n",
       "      <td>7.794970</td>\n",
       "      <td>5.807102</td>\n",
       "      <td>0.000174</td>\n",
       "      <td>5.806949</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-11.837621</td>\n",
       "      <td>5.200086</td>\n",
       "      <td>5.199915</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>122</th>\n",
       "      <td>2012-06-01</td>\n",
       "      <td>-4.902328</td>\n",
       "      <td>-1.383129</td>\n",
       "      <td>11.747057</td>\n",
       "      <td>7.584923</td>\n",
       "      <td>0.003732</td>\n",
       "      <td>7.581939</td>\n",
       "      <td>0.0</td>\n",
       "      <td>3.519198</td>\n",
       "      <td>8.972599</td>\n",
       "      <td>8.970077</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>123</th>\n",
       "      <td>2012-07-01</td>\n",
       "      <td>5.244708</td>\n",
       "      <td>20.241577</td>\n",
       "      <td>13.409412</td>\n",
       "      <td>5.612009</td>\n",
       "      <td>0.003427</td>\n",
       "      <td>5.609634</td>\n",
       "      <td>0.0</td>\n",
       "      <td>14.996869</td>\n",
       "      <td>12.179669</td>\n",
       "      <td>12.178575</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>124</th>\n",
       "      <td>2012-08-01</td>\n",
       "      <td>6.108717</td>\n",
       "      <td>34.821778</td>\n",
       "      <td>12.495307</td>\n",
       "      <td>4.047168</td>\n",
       "      <td>0.002426</td>\n",
       "      <td>4.046365</td>\n",
       "      <td>0.0</td>\n",
       "      <td>28.713061</td>\n",
       "      <td>11.821997</td>\n",
       "      <td>11.821723</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>125</th>\n",
       "      <td>2012-09-01</td>\n",
       "      <td>9.431675</td>\n",
       "      <td>33.388951</td>\n",
       "      <td>5.091280</td>\n",
       "      <td>2.576630</td>\n",
       "      <td>0.001773</td>\n",
       "      <td>2.576498</td>\n",
       "      <td>0.0</td>\n",
       "      <td>23.957277</td>\n",
       "      <td>4.391217</td>\n",
       "      <td>4.391140</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>126</th>\n",
       "      <td>2012-10-01</td>\n",
       "      <td>9.648070</td>\n",
       "      <td>22.806979</td>\n",
       "      <td>5.091280</td>\n",
       "      <td>2.097192</td>\n",
       "      <td>0.000983</td>\n",
       "      <td>2.096299</td>\n",
       "      <td>0.0</td>\n",
       "      <td>13.158909</td>\n",
       "      <td>4.639683</td>\n",
       "      <td>4.639280</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>127</th>\n",
       "      <td>2012-11-01</td>\n",
       "      <td>2.918423</td>\n",
       "      <td>-5.061290</td>\n",
       "      <td>9.165106</td>\n",
       "      <td>1.768768</td>\n",
       "      <td>0.001800</td>\n",
       "      <td>1.767067</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-7.979713</td>\n",
       "      <td>8.993144</td>\n",
       "      <td>8.992810</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>128</th>\n",
       "      <td>2012-12-01</td>\n",
       "      <td>-2.571346</td>\n",
       "      <td>-14.711763</td>\n",
       "      <td>8.750240</td>\n",
       "      <td>0.689160</td>\n",
       "      <td>0.002507</td>\n",
       "      <td>0.686998</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-12.140417</td>\n",
       "      <td>8.723229</td>\n",
       "      <td>8.723059</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>129</th>\n",
       "      <td>2013-01-01</td>\n",
       "      <td>-7.066858</td>\n",
       "      <td>-20.768341</td>\n",
       "      <td>11.668906</td>\n",
       "      <td>1.446105</td>\n",
       "      <td>0.002739</td>\n",
       "      <td>1.447584</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-13.701483</td>\n",
       "      <td>11.578767</td>\n",
       "      <td>11.578952</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>130</th>\n",
       "      <td>2013-02-01</td>\n",
       "      <td>-10.778987</td>\n",
       "      <td>-26.297268</td>\n",
       "      <td>12.367746</td>\n",
       "      <td>2.260413</td>\n",
       "      <td>0.001970</td>\n",
       "      <td>2.262162</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-15.518282</td>\n",
       "      <td>12.159102</td>\n",
       "      <td>12.159427</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>131</th>\n",
       "      <td>2013-03-01</td>\n",
       "      <td>-14.913901</td>\n",
       "      <td>-32.619819</td>\n",
       "      <td>12.367746</td>\n",
       "      <td>3.069739</td>\n",
       "      <td>0.002600</td>\n",
       "      <td>3.072319</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-17.705918</td>\n",
       "      <td>11.980066</td>\n",
       "      <td>11.980728</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>132</th>\n",
       "      <td>2013-04-01</td>\n",
       "      <td>-18.012370</td>\n",
       "      <td>-38.926057</td>\n",
       "      <td>3.770150</td>\n",
       "      <td>4.569732</td>\n",
       "      <td>0.001320</td>\n",
       "      <td>4.570885</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-20.913687</td>\n",
       "      <td>2.584368</td>\n",
       "      <td>2.582329</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>133</th>\n",
       "      <td>2013-05-01</td>\n",
       "      <td>-15.034970</td>\n",
       "      <td>-23.942002</td>\n",
       "      <td>5.693676</td>\n",
       "      <td>6.085455</td>\n",
       "      <td>0.001425</td>\n",
       "      <td>6.084380</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-8.907032</td>\n",
       "      <td>2.145166</td>\n",
       "      <td>2.148212</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>134</th>\n",
       "      <td>2013-06-01</td>\n",
       "      <td>-6.124813</td>\n",
       "      <td>-0.357636</td>\n",
       "      <td>11.584090</td>\n",
       "      <td>7.878916</td>\n",
       "      <td>0.002860</td>\n",
       "      <td>7.876589</td>\n",
       "      <td>0.0</td>\n",
       "      <td>5.767177</td>\n",
       "      <td>8.494145</td>\n",
       "      <td>8.491987</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>135</th>\n",
       "      <td>2013-07-01</td>\n",
       "      <td>0.223026</td>\n",
       "      <td>18.255137</td>\n",
       "      <td>8.826279</td>\n",
       "      <td>7.145002</td>\n",
       "      <td>0.002591</td>\n",
       "      <td>7.142825</td>\n",
       "      <td>0.0</td>\n",
       "      <td>18.032111</td>\n",
       "      <td>5.184905</td>\n",
       "      <td>5.181906</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>136</th>\n",
       "      <td>2013-08-01</td>\n",
       "      <td>4.643764</td>\n",
       "      <td>25.502380</td>\n",
       "      <td>8.826279</td>\n",
       "      <td>5.432832</td>\n",
       "      <td>0.003246</td>\n",
       "      <td>5.430534</td>\n",
       "      <td>0.0</td>\n",
       "      <td>20.858615</td>\n",
       "      <td>6.957909</td>\n",
       "      <td>6.956115</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>137</th>\n",
       "      <td>2013-09-01</td>\n",
       "      <td>7.332894</td>\n",
       "      <td>25.220097</td>\n",
       "      <td>8.826279</td>\n",
       "      <td>2.969328</td>\n",
       "      <td>0.000426</td>\n",
       "      <td>2.969275</td>\n",
       "      <td>0.0</td>\n",
       "      <td>17.887203</td>\n",
       "      <td>8.311835</td>\n",
       "      <td>8.311816</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>138</th>\n",
       "      <td>2013-10-01</td>\n",
       "      <td>6.969243</td>\n",
       "      <td>16.939429</td>\n",
       "      <td>5.374220</td>\n",
       "      <td>2.087871</td>\n",
       "      <td>0.000233</td>\n",
       "      <td>2.087938</td>\n",
       "      <td>0.0</td>\n",
       "      <td>9.970185</td>\n",
       "      <td>4.952045</td>\n",
       "      <td>4.952074</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>139</th>\n",
       "      <td>2013-11-01</td>\n",
       "      <td>1.463449</td>\n",
       "      <td>-0.061541</td>\n",
       "      <td>7.831260</td>\n",
       "      <td>1.022621</td>\n",
       "      <td>0.002620</td>\n",
       "      <td>1.022872</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-1.524990</td>\n",
       "      <td>7.764172</td>\n",
       "      <td>7.764205</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>140</th>\n",
       "      <td>2013-12-01</td>\n",
       "      <td>-4.234731</td>\n",
       "      <td>-16.441322</td>\n",
       "      <td>11.313657</td>\n",
       "      <td>1.152871</td>\n",
       "      <td>0.002714</td>\n",
       "      <td>1.155549</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-12.206591</td>\n",
       "      <td>11.254490</td>\n",
       "      <td>11.254765</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>141</th>\n",
       "      <td>2014-01-01</td>\n",
       "      <td>-8.568650</td>\n",
       "      <td>-27.396191</td>\n",
       "      <td>14.475045</td>\n",
       "      <td>2.431528</td>\n",
       "      <td>0.002707</td>\n",
       "      <td>2.434158</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-18.827541</td>\n",
       "      <td>14.268910</td>\n",
       "      <td>14.269358</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>142</th>\n",
       "      <td>2014-02-01</td>\n",
       "      <td>-12.200487</td>\n",
       "      <td>-32.860465</td>\n",
       "      <td>14.475045</td>\n",
       "      <td>3.377492</td>\n",
       "      <td>0.002113</td>\n",
       "      <td>3.379573</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-20.659978</td>\n",
       "      <td>14.074992</td>\n",
       "      <td>14.075492</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>143</th>\n",
       "      <td>2014-03-01</td>\n",
       "      <td>-14.361022</td>\n",
       "      <td>-38.516782</td>\n",
       "      <td>12.821175</td>\n",
       "      <td>4.132407</td>\n",
       "      <td>0.002218</td>\n",
       "      <td>4.134604</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-24.155760</td>\n",
       "      <td>12.136209</td>\n",
       "      <td>12.136957</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>144</th>\n",
       "      <td>2014-04-01</td>\n",
       "      <td>-18.183774</td>\n",
       "      <td>-44.376058</td>\n",
       "      <td>11.359414</td>\n",
       "      <td>5.195123</td>\n",
       "      <td>0.002083</td>\n",
       "      <td>5.196969</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-26.192284</td>\n",
       "      <td>10.100881</td>\n",
       "      <td>10.101831</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>145</th>\n",
       "      <td>2014-05-01</td>\n",
       "      <td>-17.017089</td>\n",
       "      <td>-35.747123</td>\n",
       "      <td>5.140356</td>\n",
       "      <td>6.466529</td>\n",
       "      <td>0.000888</td>\n",
       "      <td>6.465825</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-18.730035</td>\n",
       "      <td>3.922198</td>\n",
       "      <td>3.923358</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>146</th>\n",
       "      <td>2014-06-01</td>\n",
       "      <td>-5.079386</td>\n",
       "      <td>-17.084963</td>\n",
       "      <td>4.161103</td>\n",
       "      <td>8.173345</td>\n",
       "      <td>0.004236</td>\n",
       "      <td>8.170101</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-12.005577</td>\n",
       "      <td>7.031059</td>\n",
       "      <td>7.034827</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>147</th>\n",
       "      <td>2014-07-01</td>\n",
       "      <td>3.938709</td>\n",
       "      <td>12.110315</td>\n",
       "      <td>4.161103</td>\n",
       "      <td>6.546566</td>\n",
       "      <td>0.002479</td>\n",
       "      <td>6.544724</td>\n",
       "      <td>0.0</td>\n",
       "      <td>8.171606</td>\n",
       "      <td>5.051597</td>\n",
       "      <td>5.053983</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>148</th>\n",
       "      <td>2014-08-01</td>\n",
       "      <td>4.818862</td>\n",
       "      <td>27.284087</td>\n",
       "      <td>9.384167</td>\n",
       "      <td>5.580374</td>\n",
       "      <td>0.002839</td>\n",
       "      <td>5.578922</td>\n",
       "      <td>0.0</td>\n",
       "      <td>22.465225</td>\n",
       "      <td>7.545742</td>\n",
       "      <td>7.544669</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>149</th>\n",
       "      <td>2014-09-01</td>\n",
       "      <td>10.148856</td>\n",
       "      <td>31.324232</td>\n",
       "      <td>8.793588</td>\n",
       "      <td>3.230351</td>\n",
       "      <td>0.001716</td>\n",
       "      <td>3.230540</td>\n",
       "      <td>0.0</td>\n",
       "      <td>21.175376</td>\n",
       "      <td>8.178680</td>\n",
       "      <td>8.178754</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>150</th>\n",
       "      <td>2014-10-01</td>\n",
       "      <td>7.127653</td>\n",
       "      <td>18.077322</td>\n",
       "      <td>3.237446</td>\n",
       "      <td>2.614579</td>\n",
       "      <td>0.001161</td>\n",
       "      <td>2.613696</td>\n",
       "      <td>0.0</td>\n",
       "      <td>10.949669</td>\n",
       "      <td>1.910405</td>\n",
       "      <td>1.909197</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>151</th>\n",
       "      <td>2014-11-01</td>\n",
       "      <td>0.635511</td>\n",
       "      <td>-1.317866</td>\n",
       "      <td>3.944801</td>\n",
       "      <td>1.332829</td>\n",
       "      <td>0.002584</td>\n",
       "      <td>1.330542</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-1.953378</td>\n",
       "      <td>3.713638</td>\n",
       "      <td>3.712819</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>152</th>\n",
       "      <td>2014-12-01</td>\n",
       "      <td>-4.847977</td>\n",
       "      <td>-14.632054</td>\n",
       "      <td>3.944801</td>\n",
       "      <td>0.346538</td>\n",
       "      <td>0.002772</td>\n",
       "      <td>0.347781</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-9.784077</td>\n",
       "      <td>3.929440</td>\n",
       "      <td>3.929550</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>153</th>\n",
       "      <td>2015-01-01</td>\n",
       "      <td>-8.949626</td>\n",
       "      <td>-16.559125</td>\n",
       "      <td>7.994013</td>\n",
       "      <td>1.905764</td>\n",
       "      <td>0.002491</td>\n",
       "      <td>1.907758</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-7.609499</td>\n",
       "      <td>7.763034</td>\n",
       "      <td>7.763525</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>154</th>\n",
       "      <td>2015-02-01</td>\n",
       "      <td>-12.536945</td>\n",
       "      <td>-24.590272</td>\n",
       "      <td>4.713931</td>\n",
       "      <td>2.770295</td>\n",
       "      <td>0.002211</td>\n",
       "      <td>2.772418</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-12.053327</td>\n",
       "      <td>3.812458</td>\n",
       "      <td>3.814002</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>155</th>\n",
       "      <td>2015-03-01</td>\n",
       "      <td>-16.024448</td>\n",
       "      <td>-36.800895</td>\n",
       "      <td>20.366958</td>\n",
       "      <td>3.644564</td>\n",
       "      <td>0.002014</td>\n",
       "      <td>3.646530</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-20.776448</td>\n",
       "      <td>20.037860</td>\n",
       "      <td>20.038217</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>156</th>\n",
       "      <td>2015-04-01</td>\n",
       "      <td>-14.457575</td>\n",
       "      <td>-34.975426</td>\n",
       "      <td>7.103857</td>\n",
       "      <td>5.135913</td>\n",
       "      <td>0.000117</td>\n",
       "      <td>5.135801</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-20.517851</td>\n",
       "      <td>4.907987</td>\n",
       "      <td>4.907870</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>157</th>\n",
       "      <td>2015-05-01</td>\n",
       "      <td>-12.170089</td>\n",
       "      <td>-26.560353</td>\n",
       "      <td>7.103857</td>\n",
       "      <td>6.536235</td>\n",
       "      <td>0.001500</td>\n",
       "      <td>6.535107</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-14.390265</td>\n",
       "      <td>2.785169</td>\n",
       "      <td>2.782520</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>158</th>\n",
       "      <td>2015-06-01</td>\n",
       "      <td>-3.834861</td>\n",
       "      <td>-5.363297</td>\n",
       "      <td>7.103857</td>\n",
       "      <td>7.777533</td>\n",
       "      <td>0.001971</td>\n",
       "      <td>7.775992</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-1.528436</td>\n",
       "      <td>3.162477</td>\n",
       "      <td>3.166265</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>159</th>\n",
       "      <td>2015-07-01</td>\n",
       "      <td>4.730574</td>\n",
       "      <td>26.348469</td>\n",
       "      <td>7.077970</td>\n",
       "      <td>6.625984</td>\n",
       "      <td>0.002928</td>\n",
       "      <td>6.623962</td>\n",
       "      <td>0.0</td>\n",
       "      <td>21.617895</td>\n",
       "      <td>2.494150</td>\n",
       "      <td>2.488774</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>160</th>\n",
       "      <td>2015-08-01</td>\n",
       "      <td>8.890923</td>\n",
       "      <td>36.129698</td>\n",
       "      <td>6.728706</td>\n",
       "      <td>4.573083</td>\n",
       "      <td>0.002939</td>\n",
       "      <td>4.572463</td>\n",
       "      <td>0.0</td>\n",
       "      <td>27.238775</td>\n",
       "      <td>4.936402</td>\n",
       "      <td>4.935828</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>161</th>\n",
       "      <td>2015-09-01</td>\n",
       "      <td>12.943853</td>\n",
       "      <td>42.836019</td>\n",
       "      <td>5.569472</td>\n",
       "      <td>2.809521</td>\n",
       "      <td>0.001757</td>\n",
       "      <td>2.810608</td>\n",
       "      <td>0.0</td>\n",
       "      <td>29.892166</td>\n",
       "      <td>4.808274</td>\n",
       "      <td>4.808910</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>162</th>\n",
       "      <td>2015-10-01</td>\n",
       "      <td>7.483835</td>\n",
       "      <td>32.254047</td>\n",
       "      <td>5.569472</td>\n",
       "      <td>3.408084</td>\n",
       "      <td>0.001888</td>\n",
       "      <td>3.406470</td>\n",
       "      <td>0.0</td>\n",
       "      <td>24.770212</td>\n",
       "      <td>4.406243</td>\n",
       "      <td>4.404995</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>163</th>\n",
       "      <td>2015-11-01</td>\n",
       "      <td>0.043566</td>\n",
       "      <td>0.912898</td>\n",
       "      <td>5.569472</td>\n",
       "      <td>2.217372</td>\n",
       "      <td>0.002549</td>\n",
       "      <td>2.215086</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.869333</td>\n",
       "      <td>5.110030</td>\n",
       "      <td>5.109039</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>164</th>\n",
       "      <td>2015-12-01</td>\n",
       "      <td>-5.451805</td>\n",
       "      <td>-18.400302</td>\n",
       "      <td>14.974012</td>\n",
       "      <td>0.508334</td>\n",
       "      <td>0.002720</td>\n",
       "      <td>0.505648</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-12.948497</td>\n",
       "      <td>14.965472</td>\n",
       "      <td>14.965381</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>165</th>\n",
       "      <td>2016-01-01</td>\n",
       "      <td>-9.743533</td>\n",
       "      <td>-18.094659</td>\n",
       "      <td>10.623876</td>\n",
       "      <td>1.226281</td>\n",
       "      <td>0.002516</td>\n",
       "      <td>1.228498</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-8.351126</td>\n",
       "      <td>10.552608</td>\n",
       "      <td>10.552866</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>166</th>\n",
       "      <td>2016-02-01</td>\n",
       "      <td>-13.386906</td>\n",
       "      <td>-24.008938</td>\n",
       "      <td>7.624608</td>\n",
       "      <td>2.381587</td>\n",
       "      <td>0.002480</td>\n",
       "      <td>2.384052</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-10.622032</td>\n",
       "      <td>7.242302</td>\n",
       "      <td>7.243114</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>167</th>\n",
       "      <td>2016-03-01</td>\n",
       "      <td>-16.737690</td>\n",
       "      <td>-41.653081</td>\n",
       "      <td>16.117496</td>\n",
       "      <td>3.629467</td>\n",
       "      <td>0.001917</td>\n",
       "      <td>3.631238</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-24.915391</td>\n",
       "      <td>15.703114</td>\n",
       "      <td>15.703523</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>168</th>\n",
       "      <td>2016-04-01</td>\n",
       "      <td>-16.775564</td>\n",
       "      <td>-39.599503</td>\n",
       "      <td>16.117496</td>\n",
       "      <td>5.212458</td>\n",
       "      <td>0.001793</td>\n",
       "      <td>5.213907</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-22.823939</td>\n",
       "      <td>15.250864</td>\n",
       "      <td>15.251359</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>169</th>\n",
       "      <td>2016-05-01</td>\n",
       "      <td>-14.141611</td>\n",
       "      <td>-24.228774</td>\n",
       "      <td>7.041642</td>\n",
       "      <td>6.574786</td>\n",
       "      <td>0.001748</td>\n",
       "      <td>6.573525</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-10.087163</td>\n",
       "      <td>2.524579</td>\n",
       "      <td>2.521293</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>170</th>\n",
       "      <td>2016-06-01</td>\n",
       "      <td>-8.485388</td>\n",
       "      <td>-7.443967</td>\n",
       "      <td>9.958436</td>\n",
       "      <td>7.620228</td>\n",
       "      <td>0.003302</td>\n",
       "      <td>7.617674</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.041421</td>\n",
       "      <td>6.414163</td>\n",
       "      <td>6.411129</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>171</th>\n",
       "      <td>2016-07-01</td>\n",
       "      <td>4.199413</td>\n",
       "      <td>26.616230</td>\n",
       "      <td>15.375426</td>\n",
       "      <td>5.974893</td>\n",
       "      <td>0.005259</td>\n",
       "      <td>5.970964</td>\n",
       "      <td>0.0</td>\n",
       "      <td>22.416817</td>\n",
       "      <td>14.168673</td>\n",
       "      <td>14.167017</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>172</th>\n",
       "      <td>2016-08-01</td>\n",
       "      <td>6.806015</td>\n",
       "      <td>23.882781</td>\n",
       "      <td>5.718043</td>\n",
       "      <td>3.406830</td>\n",
       "      <td>0.001612</td>\n",
       "      <td>3.406150</td>\n",
       "      <td>0.0</td>\n",
       "      <td>17.076766</td>\n",
       "      <td>4.592837</td>\n",
       "      <td>4.592333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>173</th>\n",
       "      <td>2016-09-01</td>\n",
       "      <td>9.861633</td>\n",
       "      <td>22.240682</td>\n",
       "      <td>5.718043</td>\n",
       "      <td>2.321377</td>\n",
       "      <td>0.002778</td>\n",
       "      <td>2.321258</td>\n",
       "      <td>0.0</td>\n",
       "      <td>12.379050</td>\n",
       "      <td>5.225684</td>\n",
       "      <td>5.225632</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>174</th>\n",
       "      <td>2016-10-01</td>\n",
       "      <td>9.279866</td>\n",
       "      <td>16.511887</td>\n",
       "      <td>5.718043</td>\n",
       "      <td>1.851374</td>\n",
       "      <td>0.000635</td>\n",
       "      <td>1.850903</td>\n",
       "      <td>0.0</td>\n",
       "      <td>7.232021</td>\n",
       "      <td>5.410192</td>\n",
       "      <td>5.410031</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>175</th>\n",
       "      <td>2016-11-01</td>\n",
       "      <td>2.557216</td>\n",
       "      <td>-6.131447</td>\n",
       "      <td>12.553759</td>\n",
       "      <td>1.480118</td>\n",
       "      <td>0.002314</td>\n",
       "      <td>1.477886</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-8.688663</td>\n",
       "      <td>12.466464</td>\n",
       "      <td>12.466199</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>176</th>\n",
       "      <td>2016-12-01</td>\n",
       "      <td>-3.265592</td>\n",
       "      <td>-26.048456</td>\n",
       "      <td>17.447426</td>\n",
       "      <td>0.386057</td>\n",
       "      <td>0.002769</td>\n",
       "      <td>0.384361</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-22.782864</td>\n",
       "      <td>17.443192</td>\n",
       "      <td>17.443155</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>177</th>\n",
       "      <td>2017-01-01</td>\n",
       "      <td>-8.148221</td>\n",
       "      <td>-21.652114</td>\n",
       "      <td>12.605880</td>\n",
       "      <td>1.510550</td>\n",
       "      <td>0.002759</td>\n",
       "      <td>1.512801</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-13.503893</td>\n",
       "      <td>12.514776</td>\n",
       "      <td>12.515049</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>178</th>\n",
       "      <td>2017-02-01</td>\n",
       "      <td>-12.262706</td>\n",
       "      <td>-27.116389</td>\n",
       "      <td>12.605880</td>\n",
       "      <td>2.582784</td>\n",
       "      <td>0.002812</td>\n",
       "      <td>2.585507</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-14.853683</td>\n",
       "      <td>12.337883</td>\n",
       "      <td>12.338453</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>179</th>\n",
       "      <td>2017-03-01</td>\n",
       "      <td>-15.149123</td>\n",
       "      <td>-28.819250</td>\n",
       "      <td>12.605880</td>\n",
       "      <td>3.566262</td>\n",
       "      <td>0.000641</td>\n",
       "      <td>3.566897</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-13.670127</td>\n",
       "      <td>12.090717</td>\n",
       "      <td>12.090905</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>180</th>\n",
       "      <td>2017-04-01</td>\n",
       "      <td>-13.168843</td>\n",
       "      <td>-21.678501</td>\n",
       "      <td>9.323574</td>\n",
       "      <td>4.763738</td>\n",
       "      <td>0.000849</td>\n",
       "      <td>4.762937</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-8.509658</td>\n",
       "      <td>8.015202</td>\n",
       "      <td>8.014725</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>181</th>\n",
       "      <td>2017-05-01</td>\n",
       "      <td>-7.908985</td>\n",
       "      <td>-17.684483</td>\n",
       "      <td>7.548454</td>\n",
       "      <td>6.351039</td>\n",
       "      <td>0.001116</td>\n",
       "      <td>6.350166</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-9.775499</td>\n",
       "      <td>4.080999</td>\n",
       "      <td>4.079641</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>182</th>\n",
       "      <td>2017-06-01</td>\n",
       "      <td>-1.121785</td>\n",
       "      <td>-6.393769</td>\n",
       "      <td>7.853885</td>\n",
       "      <td>7.024724</td>\n",
       "      <td>0.002072</td>\n",
       "      <td>7.023011</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-5.271984</td>\n",
       "      <td>3.515795</td>\n",
       "      <td>3.512373</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>183</th>\n",
       "      <td>2017-07-01</td>\n",
       "      <td>6.670890</td>\n",
       "      <td>22.801509</td>\n",
       "      <td>7.853885</td>\n",
       "      <td>4.486926</td>\n",
       "      <td>0.004547</td>\n",
       "      <td>4.483774</td>\n",
       "      <td>0.0</td>\n",
       "      <td>16.130619</td>\n",
       "      <td>6.448198</td>\n",
       "      <td>6.446007</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>184</th>\n",
       "      <td>2017-08-01</td>\n",
       "      <td>12.614343</td>\n",
       "      <td>32.773613</td>\n",
       "      <td>7.853885</td>\n",
       "      <td>2.170411</td>\n",
       "      <td>0.004428</td>\n",
       "      <td>2.172765</td>\n",
       "      <td>0.0</td>\n",
       "      <td>20.159270</td>\n",
       "      <td>7.547356</td>\n",
       "      <td>7.548035</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>185</th>\n",
       "      <td>2017-09-01</td>\n",
       "      <td>13.760002</td>\n",
       "      <td>34.088046</td>\n",
       "      <td>7.853885</td>\n",
       "      <td>2.933993</td>\n",
       "      <td>0.002799</td>\n",
       "      <td>2.936756</td>\n",
       "      <td>0.0</td>\n",
       "      <td>20.328044</td>\n",
       "      <td>7.284158</td>\n",
       "      <td>7.285273</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>186</th>\n",
       "      <td>2017-10-01</td>\n",
       "      <td>13.772820</td>\n",
       "      <td>26.591011</td>\n",
       "      <td>7.853885</td>\n",
       "      <td>3.670570</td>\n",
       "      <td>0.000056</td>\n",
       "      <td>3.670514</td>\n",
       "      <td>0.0</td>\n",
       "      <td>12.818191</td>\n",
       "      <td>6.943403</td>\n",
       "      <td>6.943373</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>187</th>\n",
       "      <td>2017-11-01</td>\n",
       "      <td>7.462075</td>\n",
       "      <td>NaN</td>\n",
       "      <td>7.853885</td>\n",
       "      <td>3.969545</td>\n",
       "      <td>0.002346</td>\n",
       "      <td>3.967245</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>6.778235</td>\n",
       "      <td>6.776889</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>188</th>\n",
       "      <td>2017-12-01</td>\n",
       "      <td>1.826449</td>\n",
       "      <td>NaN</td>\n",
       "      <td>7.853885</td>\n",
       "      <td>3.143437</td>\n",
       "      <td>0.002210</td>\n",
       "      <td>3.141420</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>7.198263</td>\n",
       "      <td>7.197382</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>189</th>\n",
       "      <td>2018-01-01</td>\n",
       "      <td>-2.984228</td>\n",
       "      <td>NaN</td>\n",
       "      <td>7.853885</td>\n",
       "      <td>2.552773</td>\n",
       "      <td>0.002798</td>\n",
       "      <td>2.551365</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>7.427923</td>\n",
       "      <td>7.427440</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>190</th>\n",
       "      <td>2018-02-01</td>\n",
       "      <td>-7.540334</td>\n",
       "      <td>NaN</td>\n",
       "      <td>7.853885</td>\n",
       "      <td>2.258052</td>\n",
       "      <td>0.002344</td>\n",
       "      <td>2.258264</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>7.522217</td>\n",
       "      <td>7.522281</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>191</th>\n",
       "      <td>2018-03-01</td>\n",
       "      <td>-12.530506</td>\n",
       "      <td>NaN</td>\n",
       "      <td>7.853885</td>\n",
       "      <td>1.989469</td>\n",
       "      <td>0.002091</td>\n",
       "      <td>1.991342</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>7.597240</td>\n",
       "      <td>7.597732</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>192</th>\n",
       "      <td>2018-04-01</td>\n",
       "      <td>-12.737886</td>\n",
       "      <td>NaN</td>\n",
       "      <td>7.853885</td>\n",
       "      <td>3.414111</td>\n",
       "      <td>0.000626</td>\n",
       "      <td>3.413529</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>7.073283</td>\n",
       "      <td>7.073002</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>193</th>\n",
       "      <td>2018-05-01</td>\n",
       "      <td>-9.379234</td>\n",
       "      <td>NaN</td>\n",
       "      <td>7.853885</td>\n",
       "      <td>5.115145</td>\n",
       "      <td>0.001688</td>\n",
       "      <td>5.113761</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>5.960953</td>\n",
       "      <td>5.959766</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>194</th>\n",
       "      <td>2018-06-01</td>\n",
       "      <td>-1.275246</td>\n",
       "      <td>-7.063498</td>\n",
       "      <td>14.480953</td>\n",
       "      <td>6.410427</td>\n",
       "      <td>0.003108</td>\n",
       "      <td>6.407827</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-5.788252</td>\n",
       "      <td>12.986060</td>\n",
       "      <td>12.984777</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>195</th>\n",
       "      <td>2018-07-01</td>\n",
       "      <td>3.697021</td>\n",
       "      <td>14.653356</td>\n",
       "      <td>15.506794</td>\n",
       "      <td>4.911624</td>\n",
       "      <td>0.003306</td>\n",
       "      <td>4.909188</td>\n",
       "      <td>0.0</td>\n",
       "      <td>10.956335</td>\n",
       "      <td>14.709199</td>\n",
       "      <td>14.708386</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>196</th>\n",
       "      <td>2018-08-01</td>\n",
       "      <td>7.926255</td>\n",
       "      <td>21.900599</td>\n",
       "      <td>15.506794</td>\n",
       "      <td>3.702775</td>\n",
       "      <td>0.002843</td>\n",
       "      <td>3.701632</td>\n",
       "      <td>0.0</td>\n",
       "      <td>13.974344</td>\n",
       "      <td>15.058505</td>\n",
       "      <td>15.058224</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>197</th>\n",
       "      <td>2018-09-01</td>\n",
       "      <td>8.267585</td>\n",
       "      <td>22.309800</td>\n",
       "      <td>15.506794</td>\n",
       "      <td>2.842774</td>\n",
       "      <td>0.000995</td>\n",
       "      <td>2.842912</td>\n",
       "      <td>0.0</td>\n",
       "      <td>14.042215</td>\n",
       "      <td>15.243966</td>\n",
       "      <td>15.243992</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>198</th>\n",
       "      <td>2018-10-01</td>\n",
       "      <td>3.913075</td>\n",
       "      <td>13.396497</td>\n",
       "      <td>15.506794</td>\n",
       "      <td>2.283703</td>\n",
       "      <td>0.001895</td>\n",
       "      <td>2.283274</td>\n",
       "      <td>0.0</td>\n",
       "      <td>9.483422</td>\n",
       "      <td>15.337774</td>\n",
       "      <td>15.337711</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>199</th>\n",
       "      <td>2018-11-01</td>\n",
       "      <td>-3.135130</td>\n",
       "      <td>-7.341910</td>\n",
       "      <td>12.544031</td>\n",
       "      <td>1.478911</td>\n",
       "      <td>0.002618</td>\n",
       "      <td>1.479386</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-4.206781</td>\n",
       "      <td>12.456489</td>\n",
       "      <td>12.456546</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>200</th>\n",
       "      <td>2018-12-01</td>\n",
       "      <td>-7.794605</td>\n",
       "      <td>-21.223143</td>\n",
       "      <td>16.966742</td>\n",
       "      <td>1.635726</td>\n",
       "      <td>0.002337</td>\n",
       "      <td>1.637905</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-13.428538</td>\n",
       "      <td>16.887498</td>\n",
       "      <td>16.887710</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>201</th>\n",
       "      <td>2019-01-01</td>\n",
       "      <td>-11.788565</td>\n",
       "      <td>-28.158920</td>\n",
       "      <td>16.579218</td>\n",
       "      <td>2.692976</td>\n",
       "      <td>0.002801</td>\n",
       "      <td>2.695752</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-16.370355</td>\n",
       "      <td>16.358588</td>\n",
       "      <td>16.359045</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>202</th>\n",
       "      <td>2019-02-01</td>\n",
       "      <td>-14.565860</td>\n",
       "      <td>-33.116796</td>\n",
       "      <td>15.733234</td>\n",
       "      <td>3.659852</td>\n",
       "      <td>0.001359</td>\n",
       "      <td>3.661204</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-18.550935</td>\n",
       "      <td>15.301315</td>\n",
       "      <td>15.301638</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>203</th>\n",
       "      <td>2019-03-01</td>\n",
       "      <td>-16.923111</td>\n",
       "      <td>-33.108929</td>\n",
       "      <td>14.553711</td>\n",
       "      <td>4.511426</td>\n",
       "      <td>0.001944</td>\n",
       "      <td>4.513206</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-16.185817</td>\n",
       "      <td>13.836237</td>\n",
       "      <td>13.836818</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>204</th>\n",
       "      <td>2019-04-01</td>\n",
       "      <td>-15.283052</td>\n",
       "      <td>-32.333142</td>\n",
       "      <td>9.447103</td>\n",
       "      <td>5.798712</td>\n",
       "      <td>0.000168</td>\n",
       "      <td>5.798837</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-17.050090</td>\n",
       "      <td>7.457965</td>\n",
       "      <td>7.458062</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>205</th>\n",
       "      <td>2019-05-01</td>\n",
       "      <td>-13.245628</td>\n",
       "      <td>-23.295709</td>\n",
       "      <td>7.823373</td>\n",
       "      <td>7.018478</td>\n",
       "      <td>0.001401</td>\n",
       "      <td>7.017429</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-10.050081</td>\n",
       "      <td>3.458445</td>\n",
       "      <td>3.456316</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>206</th>\n",
       "      <td>2019-06-01</td>\n",
       "      <td>-8.129267</td>\n",
       "      <td>-10.373096</td>\n",
       "      <td>12.419019</td>\n",
       "      <td>8.241059</td>\n",
       "      <td>0.001382</td>\n",
       "      <td>8.239928</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-2.243829</td>\n",
       "      <td>9.291696</td>\n",
       "      <td>9.290693</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>207</th>\n",
       "      <td>2019-07-01</td>\n",
       "      <td>4.503919</td>\n",
       "      <td>21.549014</td>\n",
       "      <td>14.667119</td>\n",
       "      <td>6.606316</td>\n",
       "      <td>0.003452</td>\n",
       "      <td>6.603965</td>\n",
       "      <td>0.0</td>\n",
       "      <td>17.045094</td>\n",
       "      <td>13.096260</td>\n",
       "      <td>13.095074</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>208</th>\n",
       "      <td>2019-08-01</td>\n",
       "      <td>7.620849</td>\n",
       "      <td>25.469069</td>\n",
       "      <td>12.620491</td>\n",
       "      <td>4.220526</td>\n",
       "      <td>0.001257</td>\n",
       "      <td>4.220231</td>\n",
       "      <td>0.0</td>\n",
       "      <td>17.848220</td>\n",
       "      <td>11.893967</td>\n",
       "      <td>11.893862</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>209</th>\n",
       "      <td>2019-09-01</td>\n",
       "      <td>10.372987</td>\n",
       "      <td>18.301898</td>\n",
       "      <td>8.073955</td>\n",
       "      <td>2.729963</td>\n",
       "      <td>0.002912</td>\n",
       "      <td>2.730251</td>\n",
       "      <td>0.0</td>\n",
       "      <td>7.928911</td>\n",
       "      <td>7.598320</td>\n",
       "      <td>7.598424</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>210</th>\n",
       "      <td>2019-10-01</td>\n",
       "      <td>8.859891</td>\n",
       "      <td>19.431464</td>\n",
       "      <td>12.628502</td>\n",
       "      <td>1.943497</td>\n",
       "      <td>0.000958</td>\n",
       "      <td>1.942739</td>\n",
       "      <td>0.0</td>\n",
       "      <td>10.571573</td>\n",
       "      <td>12.478174</td>\n",
       "      <td>12.478056</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>211</th>\n",
       "      <td>2019-11-01</td>\n",
       "      <td>2.660688</td>\n",
       "      <td>1.184124</td>\n",
       "      <td>16.905909</td>\n",
       "      <td>1.419184</td>\n",
       "      <td>0.002142</td>\n",
       "      <td>1.417120</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-1.476564</td>\n",
       "      <td>16.846409</td>\n",
       "      <td>16.846236</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>212</th>\n",
       "      <td>2019-12-01</td>\n",
       "      <td>-2.704361</td>\n",
       "      <td>-8.885002</td>\n",
       "      <td>18.050723</td>\n",
       "      <td>0.708779</td>\n",
       "      <td>0.002786</td>\n",
       "      <td>0.707650</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-6.180641</td>\n",
       "      <td>18.036846</td>\n",
       "      <td>18.036802</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>213</th>\n",
       "      <td>2020-01-01</td>\n",
       "      <td>-6.190122</td>\n",
       "      <td>-21.177874</td>\n",
       "      <td>21.716871</td>\n",
       "      <td>1.901966</td>\n",
       "      <td>0.002060</td>\n",
       "      <td>1.903032</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-14.987753</td>\n",
       "      <td>21.633330</td>\n",
       "      <td>21.633424</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>214</th>\n",
       "      <td>2020-02-01</td>\n",
       "      <td>-10.061119</td>\n",
       "      <td>-32.265350</td>\n",
       "      <td>20.766811</td>\n",
       "      <td>2.690424</td>\n",
       "      <td>0.001991</td>\n",
       "      <td>2.691960</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-22.204231</td>\n",
       "      <td>20.591595</td>\n",
       "      <td>20.591795</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>215</th>\n",
       "      <td>2020-03-01</td>\n",
       "      <td>-12.852488</td>\n",
       "      <td>-33.386396</td>\n",
       "      <td>18.280027</td>\n",
       "      <td>3.185171</td>\n",
       "      <td>0.001935</td>\n",
       "      <td>3.187055</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-20.533908</td>\n",
       "      <td>18.000057</td>\n",
       "      <td>18.000390</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>216</th>\n",
       "      <td>2020-04-01</td>\n",
       "      <td>-13.647930</td>\n",
       "      <td>-37.362294</td>\n",
       "      <td>16.088099</td>\n",
       "      <td>4.286053</td>\n",
       "      <td>0.000288</td>\n",
       "      <td>4.286334</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-23.714364</td>\n",
       "      <td>15.506588</td>\n",
       "      <td>15.506666</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>217</th>\n",
       "      <td>2020-05-01</td>\n",
       "      <td>-8.349763</td>\n",
       "      <td>-20.234787</td>\n",
       "      <td>10.925664</td>\n",
       "      <td>6.139752</td>\n",
       "      <td>0.001861</td>\n",
       "      <td>6.138237</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-11.885024</td>\n",
       "      <td>9.038373</td>\n",
       "      <td>9.037344</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>218</th>\n",
       "      <td>2020-06-01</td>\n",
       "      <td>1.707554</td>\n",
       "      <td>3.318717</td>\n",
       "      <td>12.198396</td>\n",
       "      <td>6.624536</td>\n",
       "      <td>0.003818</td>\n",
       "      <td>6.621538</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1.611163</td>\n",
       "      <td>10.244808</td>\n",
       "      <td>10.242870</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>219</th>\n",
       "      <td>2020-07-01</td>\n",
       "      <td>11.219558</td>\n",
       "      <td>43.325321</td>\n",
       "      <td>10.682909</td>\n",
       "      <td>3.230235</td>\n",
       "      <td>0.004371</td>\n",
       "      <td>3.229320</td>\n",
       "      <td>0.0</td>\n",
       "      <td>32.105763</td>\n",
       "      <td>10.183124</td>\n",
       "      <td>10.182835</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>220</th>\n",
       "      <td>2020-08-01</td>\n",
       "      <td>12.053084</td>\n",
       "      <td>34.463163</td>\n",
       "      <td>10.688950</td>\n",
       "      <td>3.203375</td>\n",
       "      <td>0.001862</td>\n",
       "      <td>3.204597</td>\n",
       "      <td>0.0</td>\n",
       "      <td>22.410079</td>\n",
       "      <td>10.197265</td>\n",
       "      <td>10.197649</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>221</th>\n",
       "      <td>2020-09-01</td>\n",
       "      <td>15.017552</td>\n",
       "      <td>29.498407</td>\n",
       "      <td>9.639095</td>\n",
       "      <td>2.478384</td>\n",
       "      <td>0.003472</td>\n",
       "      <td>2.481580</td>\n",
       "      <td>0.0</td>\n",
       "      <td>14.480855</td>\n",
       "      <td>9.314177</td>\n",
       "      <td>9.315029</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>222</th>\n",
       "      <td>2020-10-01</td>\n",
       "      <td>13.221290</td>\n",
       "      <td>32.547862</td>\n",
       "      <td>15.387149</td>\n",
       "      <td>4.363169</td>\n",
       "      <td>0.000799</td>\n",
       "      <td>4.362380</td>\n",
       "      <td>0.0</td>\n",
       "      <td>19.326572</td>\n",
       "      <td>14.755813</td>\n",
       "      <td>14.755579</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>223</th>\n",
       "      <td>2020-11-01</td>\n",
       "      <td>5.768155</td>\n",
       "      <td>6.290697</td>\n",
       "      <td>21.247063</td>\n",
       "      <td>4.192047</td>\n",
       "      <td>0.002496</td>\n",
       "      <td>4.189594</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.522541</td>\n",
       "      <td>20.829906</td>\n",
       "      <td>20.829412</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>224</th>\n",
       "      <td>2020-12-01</td>\n",
       "      <td>0.015571</td>\n",
       "      <td>-7.802380</td>\n",
       "      <td>21.916328</td>\n",
       "      <td>3.194324</td>\n",
       "      <td>0.002753</td>\n",
       "      <td>3.191927</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-7.817951</td>\n",
       "      <td>21.682643</td>\n",
       "      <td>21.682290</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>225</th>\n",
       "      <td>2021-01-01</td>\n",
       "      <td>-4.987467</td>\n",
       "      <td>-20.422047</td>\n",
       "      <td>23.138380</td>\n",
       "      <td>2.409556</td>\n",
       "      <td>0.002697</td>\n",
       "      <td>2.408298</td>\n",
       "      <td>0.0</td>\n",
       "      <td>-15.434580</td>\n",
       "      <td>23.012708</td>\n",
       "      <td>23.012576</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          time   mean_tws  twsa_fill  grace_std   std_tws  std_canopy  \\\n",
       "0   2002-04-01 -11.229002  -6.532770  11.323719  2.782853    0.000433   \n",
       "1   2002-05-01  -6.748051   0.028998  12.902123  3.786122    0.002202   \n",
       "2   2002-06-01   2.031710  19.116401  12.902123  4.163500    0.004866   \n",
       "3   2002-07-01  16.156021  51.594553  12.902123  2.256581    0.007013   \n",
       "4   2002-08-01  17.587461  56.115878  17.343568  5.322464    0.003253   \n",
       "5   2002-09-01  15.443497  43.263017  17.926438  5.213158    0.001283   \n",
       "6   2002-10-01  14.230325  32.766144  10.485881  5.730409    0.001592   \n",
       "7   2002-11-01   7.516800  10.102582   9.234070  5.576715    0.002231   \n",
       "8   2002-12-01   2.094432  -1.095195   7.788890  4.919833    0.002713   \n",
       "9   2003-01-01  -2.489345  -2.082164  10.765632  4.664026    0.002426   \n",
       "10  2003-02-01  -6.028713 -12.836875  10.677366  4.342949    0.001781   \n",
       "11  2003-03-01  -8.011217 -18.238363  12.887024  3.528340    0.001079   \n",
       "12  2003-04-01  -9.767217  -9.153495  12.141384  3.130991    0.000408   \n",
       "13  2003-05-01  -9.338281  -5.839181  11.729268  3.761060    0.000961   \n",
       "14  2003-06-01  -3.469807  13.248222  11.729268  5.126579    0.004736   \n",
       "15  2003-07-01  10.941452  48.122491  19.449624  1.226065    0.003634   \n",
       "16  2003-08-01  13.254915  42.298563  15.783157  2.489112    0.002329   \n",
       "17  2003-09-01  12.810863  42.530672  16.563646  3.135990    0.001856   \n",
       "18  2003-10-01  15.323859  32.059766   9.730202  4.705950    0.000414   \n",
       "19  2003-11-01   9.223135  17.615395  12.080150  5.719372    0.002556   \n",
       "20  2003-12-01   3.334581   2.424833   8.919454  5.184244    0.001803   \n",
       "21  2004-01-01  -0.982065  -8.009696  10.543709  4.800630    0.002189   \n",
       "22  2004-02-01  -5.613434  -6.965889  12.049297  4.327398    0.002820   \n",
       "23  2004-03-01 -10.185071 -21.437331  12.064621  3.021555    0.001876   \n",
       "24  2004-04-01 -11.324487 -11.132193  14.907668  2.758243    0.000230   \n",
       "25  2004-05-01  -9.574932   2.722408  12.772406  4.069171    0.001459   \n",
       "26  2004-06-01   0.818719  14.628752  18.884368  4.914883    0.004938   \n",
       "27  2004-07-01  14.497416  58.404716  25.159448  1.498047    0.004690   \n",
       "28  2004-08-01  13.887342  52.079701  19.168102  4.345226    0.001625   \n",
       "29  2004-09-01  17.315240  50.818241  11.859462  4.568966    0.003375   \n",
       "30  2004-10-01  15.869274  45.318906   6.739501  5.818468    0.000739   \n",
       "31  2004-11-01   7.680985  17.903008  11.007083  6.230897    0.002732   \n",
       "32  2004-12-01   1.555081  -6.864831  10.095491  5.346214    0.002793   \n",
       "33  2005-01-01  -3.233837 -13.593327  11.199849  4.603600    0.002002   \n",
       "34  2005-02-01  -7.134987 -14.452025  11.415825  3.800555    0.002255   \n",
       "35  2005-03-01 -10.223869 -12.044153  12.825885  2.256807    0.001028   \n",
       "36  2005-04-01 -12.765896 -14.018963  11.763851  2.529005    0.001077   \n",
       "37  2005-05-01 -13.779052  -7.585786  18.515487  4.253897    0.000395   \n",
       "38  2005-06-01  -6.053177   2.516844  16.912282  6.371356    0.001859   \n",
       "39  2005-07-01   5.048038  29.894489  17.435816  5.329369    0.003641   \n",
       "40  2005-08-01  12.969151  39.780794  14.757584  2.436030    0.003871   \n",
       "41  2005-09-01  13.881463  37.185736  13.371876  3.486384    0.001113   \n",
       "42  2005-10-01  15.328437  29.471504  10.005572  4.069964    0.000226   \n",
       "43  2005-11-01  10.693533  10.314751   7.335094  5.271275    0.002623   \n",
       "44  2005-12-01   4.162937  -0.910949   6.972660  4.598862    0.002806   \n",
       "45  2006-01-01  -1.432504 -12.298131   7.277517  3.456537    0.002817   \n",
       "46  2006-02-01  -6.741870 -18.143863   7.321646  2.205315    0.002808   \n",
       "47  2006-03-01 -12.302053 -26.642624   6.416209  1.370398    0.002578   \n",
       "48  2006-04-01 -15.227662 -29.219403  11.720964  3.271488    0.001246   \n",
       "49  2006-05-01 -15.237675 -25.487442  12.453093  5.021224    0.001441   \n",
       "50  2006-06-01  -1.448422  11.436324  11.203513  6.820291    0.003816   \n",
       "51  2006-07-01   5.209481  27.750855   9.867478  4.582654    0.002047   \n",
       "52  2006-08-01   6.352994  24.377789   8.392375  3.497628    0.001556   \n",
       "53  2006-09-01  10.399671  28.976714   8.690446  2.141101    0.002388   \n",
       "54  2006-10-01  10.040683  24.034197   8.407208  2.588272    0.001185   \n",
       "55  2006-11-01   3.269239   2.876260   9.569891  2.125421    0.002165   \n",
       "56  2006-12-01  -2.477746  -3.765012   5.703908  1.412641    0.002689   \n",
       "57  2007-01-01  -7.605655 -19.622432   7.482212  1.787315    0.002831   \n",
       "58  2007-02-01 -10.028605 -18.181312   7.307836  2.628142    0.000550   \n",
       "59  2007-03-01 -12.934819 -23.211356  10.611340  3.218929    0.002474   \n",
       "60  2007-04-01 -16.183223 -20.189578   6.739960  4.502524    0.001625   \n",
       "61  2007-05-01 -16.516297 -17.979053   3.777471  5.657269    0.000628   \n",
       "62  2007-06-01  -2.753546  11.231308  11.846230  6.824715    0.004048   \n",
       "63  2007-07-01   7.367433  36.262122  10.423697  4.052601    0.005301   \n",
       "64  2007-08-01  15.237857  59.456432  11.004005  3.091184    0.003093   \n",
       "65  2007-09-01  17.101064  53.836445   9.324450  4.601147    0.003604   \n",
       "66  2007-10-01  14.267415  31.877598   2.374934  5.604014    0.000861   \n",
       "67  2007-11-01   8.071233   9.736710   4.327803  5.561957    0.002003   \n",
       "68  2007-12-01   2.473500   3.641468   1.611227  4.869285    0.002781   \n",
       "69  2008-01-01  -2.167325 -14.570775   8.354411  4.153670    0.001811   \n",
       "70  2008-02-01  -5.047356 -16.582186   6.967726  3.763908    0.002506   \n",
       "71  2008-03-01  -8.857948 -17.176624   3.700120  2.731230    0.001243   \n",
       "72  2008-04-01 -12.005633 -14.612592   5.450157  2.569548    0.001306   \n",
       "73  2008-05-01 -13.379781 -14.622052   4.257626  4.404862    0.001519   \n",
       "74  2008-06-01  -2.819744   4.560556   9.099045  6.634129    0.002586   \n",
       "75  2008-07-01   7.163965  38.139954   8.630185  4.909314    0.003969   \n",
       "76  2008-08-01  13.168807  47.684170  11.563436  2.417443    0.003981   \n",
       "77  2008-09-01  15.047499  48.172022   9.077226  3.811473    0.002331   \n",
       "78  2008-10-01  12.463551  27.939612   4.919838  4.375666    0.000115   \n",
       "79  2008-11-01   6.960910   0.174751   4.714551  4.230669    0.002425   \n",
       "80  2008-12-01   1.351667 -12.277944   4.934047  3.930062    0.002716   \n",
       "81  2009-01-01  -3.677429 -16.777630   5.882510  3.740274    0.002765   \n",
       "82  2009-02-01  -8.494066 -21.535492   7.306811  3.142305    0.002522   \n",
       "83  2009-03-01 -13.303445 -25.337450   3.457748  2.472357    0.002197   \n",
       "84  2009-04-01 -16.607549 -29.567565   4.661347  3.640013    0.001820   \n",
       "85  2009-05-01 -13.747132 -25.353675   5.991832  5.623733    0.001743   \n",
       "86  2009-06-01 -11.066009  -8.967745   7.651303  7.023500    0.001620   \n",
       "87  2009-07-01  -2.610020  13.963624  13.918995  7.855471    0.002676   \n",
       "88  2009-08-01   9.982275  36.883740   8.940083  4.013251    0.003875   \n",
       "89  2009-09-01  11.930132  28.345383   2.093557  2.820072    0.001125   \n",
       "90  2009-10-01  10.825113  20.465428   3.047585  2.996949    0.000666   \n",
       "91  2009-11-01   4.330891   5.010420   0.791013  2.669655    0.002290   \n",
       "92  2009-12-01  -1.178747 -12.466815   4.178950  1.537391    0.002715   \n",
       "93  2010-01-01  -6.031552 -14.202218   6.283838  1.361619    0.002775   \n",
       "94  2010-02-01 -10.368890 -22.706006   7.457794  2.017035    0.002405   \n",
       "95  2010-03-01 -14.532393 -35.873630   7.818610  2.971242    0.002297   \n",
       "96  2010-04-01 -16.630136 -25.760638   5.785051  4.700112    0.000609   \n",
       "97  2010-05-01 -12.523227 -12.391820   6.989732  6.511458    0.001030   \n",
       "98  2010-06-01  -3.665323   5.616780  12.938643  7.954845    0.004152   \n",
       "99  2010-07-01   4.451830  30.736937  12.635755  6.324845    0.003088   \n",
       "100 2010-08-01   7.717196  29.286877  13.855310  4.062070    0.002850   \n",
       "101 2010-09-01  10.614531  33.495004  12.678095  2.431727    0.001053   \n",
       "102 2010-10-01   7.531755  24.344580   8.572335  1.998037    0.000733   \n",
       "103 2010-11-01   1.593469   3.632127   7.151535  0.911514    0.002251   \n",
       "104 2010-12-01  -3.092725  -7.012038   3.349813  1.051848    0.001609   \n",
       "105 2011-01-01  -7.178684 -14.531868   3.349813  2.625930    0.002665   \n",
       "106 2011-02-01 -11.015123 -33.733873   6.864693  3.296961    0.002504   \n",
       "107 2011-03-01 -14.317424 -26.306923   2.821568  3.611973    0.002062   \n",
       "108 2011-04-01 -15.753109 -31.614222   1.647603  4.589185    0.001055   \n",
       "109 2011-05-01 -13.520199 -26.429849   1.898686  6.007111    0.000683   \n",
       "110 2011-06-01  -7.912388  -7.342447   1.898686  7.620030    0.003307   \n",
       "111 2011-07-01   3.621960  22.140427   8.946698  6.513959    0.002156   \n",
       "112 2011-08-01  10.812213  39.163391   9.122002  3.587518    0.003377   \n",
       "113 2011-09-01  11.598311  30.268203   4.592569  3.203456    0.001120   \n",
       "114 2011-10-01   8.697771  15.900142   8.355080  3.626842    0.002072   \n",
       "115 2011-11-01   1.467283   2.367258   8.491849  2.527809    0.002592   \n",
       "116 2011-12-01  -3.933093 -10.946929   8.491849  1.209030    0.002727   \n",
       "117 2012-01-01  -7.634749 -21.137810   7.371879  1.519832    0.002222   \n",
       "118 2012-02-01 -11.593522 -23.971587   7.393879  2.143481    0.002676   \n",
       "119 2012-03-01 -15.937175 -38.308842   9.561214  3.043960    0.002644   \n",
       "120 2012-04-01 -15.493318 -36.232712   7.794970  4.600056    0.000183   \n",
       "121 2012-05-01 -15.980019 -27.817640   7.794970  5.807102    0.000174   \n",
       "122 2012-06-01  -4.902328  -1.383129  11.747057  7.584923    0.003732   \n",
       "123 2012-07-01   5.244708  20.241577  13.409412  5.612009    0.003427   \n",
       "124 2012-08-01   6.108717  34.821778  12.495307  4.047168    0.002426   \n",
       "125 2012-09-01   9.431675  33.388951   5.091280  2.576630    0.001773   \n",
       "126 2012-10-01   9.648070  22.806979   5.091280  2.097192    0.000983   \n",
       "127 2012-11-01   2.918423  -5.061290   9.165106  1.768768    0.001800   \n",
       "128 2012-12-01  -2.571346 -14.711763   8.750240  0.689160    0.002507   \n",
       "129 2013-01-01  -7.066858 -20.768341  11.668906  1.446105    0.002739   \n",
       "130 2013-02-01 -10.778987 -26.297268  12.367746  2.260413    0.001970   \n",
       "131 2013-03-01 -14.913901 -32.619819  12.367746  3.069739    0.002600   \n",
       "132 2013-04-01 -18.012370 -38.926057   3.770150  4.569732    0.001320   \n",
       "133 2013-05-01 -15.034970 -23.942002   5.693676  6.085455    0.001425   \n",
       "134 2013-06-01  -6.124813  -0.357636  11.584090  7.878916    0.002860   \n",
       "135 2013-07-01   0.223026  18.255137   8.826279  7.145002    0.002591   \n",
       "136 2013-08-01   4.643764  25.502380   8.826279  5.432832    0.003246   \n",
       "137 2013-09-01   7.332894  25.220097   8.826279  2.969328    0.000426   \n",
       "138 2013-10-01   6.969243  16.939429   5.374220  2.087871    0.000233   \n",
       "139 2013-11-01   1.463449  -0.061541   7.831260  1.022621    0.002620   \n",
       "140 2013-12-01  -4.234731 -16.441322  11.313657  1.152871    0.002714   \n",
       "141 2014-01-01  -8.568650 -27.396191  14.475045  2.431528    0.002707   \n",
       "142 2014-02-01 -12.200487 -32.860465  14.475045  3.377492    0.002113   \n",
       "143 2014-03-01 -14.361022 -38.516782  12.821175  4.132407    0.002218   \n",
       "144 2014-04-01 -18.183774 -44.376058  11.359414  5.195123    0.002083   \n",
       "145 2014-05-01 -17.017089 -35.747123   5.140356  6.466529    0.000888   \n",
       "146 2014-06-01  -5.079386 -17.084963   4.161103  8.173345    0.004236   \n",
       "147 2014-07-01   3.938709  12.110315   4.161103  6.546566    0.002479   \n",
       "148 2014-08-01   4.818862  27.284087   9.384167  5.580374    0.002839   \n",
       "149 2014-09-01  10.148856  31.324232   8.793588  3.230351    0.001716   \n",
       "150 2014-10-01   7.127653  18.077322   3.237446  2.614579    0.001161   \n",
       "151 2014-11-01   0.635511  -1.317866   3.944801  1.332829    0.002584   \n",
       "152 2014-12-01  -4.847977 -14.632054   3.944801  0.346538    0.002772   \n",
       "153 2015-01-01  -8.949626 -16.559125   7.994013  1.905764    0.002491   \n",
       "154 2015-02-01 -12.536945 -24.590272   4.713931  2.770295    0.002211   \n",
       "155 2015-03-01 -16.024448 -36.800895  20.366958  3.644564    0.002014   \n",
       "156 2015-04-01 -14.457575 -34.975426   7.103857  5.135913    0.000117   \n",
       "157 2015-05-01 -12.170089 -26.560353   7.103857  6.536235    0.001500   \n",
       "158 2015-06-01  -3.834861  -5.363297   7.103857  7.777533    0.001971   \n",
       "159 2015-07-01   4.730574  26.348469   7.077970  6.625984    0.002928   \n",
       "160 2015-08-01   8.890923  36.129698   6.728706  4.573083    0.002939   \n",
       "161 2015-09-01  12.943853  42.836019   5.569472  2.809521    0.001757   \n",
       "162 2015-10-01   7.483835  32.254047   5.569472  3.408084    0.001888   \n",
       "163 2015-11-01   0.043566   0.912898   5.569472  2.217372    0.002549   \n",
       "164 2015-12-01  -5.451805 -18.400302  14.974012  0.508334    0.002720   \n",
       "165 2016-01-01  -9.743533 -18.094659  10.623876  1.226281    0.002516   \n",
       "166 2016-02-01 -13.386906 -24.008938   7.624608  2.381587    0.002480   \n",
       "167 2016-03-01 -16.737690 -41.653081  16.117496  3.629467    0.001917   \n",
       "168 2016-04-01 -16.775564 -39.599503  16.117496  5.212458    0.001793   \n",
       "169 2016-05-01 -14.141611 -24.228774   7.041642  6.574786    0.001748   \n",
       "170 2016-06-01  -8.485388  -7.443967   9.958436  7.620228    0.003302   \n",
       "171 2016-07-01   4.199413  26.616230  15.375426  5.974893    0.005259   \n",
       "172 2016-08-01   6.806015  23.882781   5.718043  3.406830    0.001612   \n",
       "173 2016-09-01   9.861633  22.240682   5.718043  2.321377    0.002778   \n",
       "174 2016-10-01   9.279866  16.511887   5.718043  1.851374    0.000635   \n",
       "175 2016-11-01   2.557216  -6.131447  12.553759  1.480118    0.002314   \n",
       "176 2016-12-01  -3.265592 -26.048456  17.447426  0.386057    0.002769   \n",
       "177 2017-01-01  -8.148221 -21.652114  12.605880  1.510550    0.002759   \n",
       "178 2017-02-01 -12.262706 -27.116389  12.605880  2.582784    0.002812   \n",
       "179 2017-03-01 -15.149123 -28.819250  12.605880  3.566262    0.000641   \n",
       "180 2017-04-01 -13.168843 -21.678501   9.323574  4.763738    0.000849   \n",
       "181 2017-05-01  -7.908985 -17.684483   7.548454  6.351039    0.001116   \n",
       "182 2017-06-01  -1.121785  -6.393769   7.853885  7.024724    0.002072   \n",
       "183 2017-07-01   6.670890  22.801509   7.853885  4.486926    0.004547   \n",
       "184 2017-08-01  12.614343  32.773613   7.853885  2.170411    0.004428   \n",
       "185 2017-09-01  13.760002  34.088046   7.853885  2.933993    0.002799   \n",
       "186 2017-10-01  13.772820  26.591011   7.853885  3.670570    0.000056   \n",
       "187 2017-11-01   7.462075        NaN   7.853885  3.969545    0.002346   \n",
       "188 2017-12-01   1.826449        NaN   7.853885  3.143437    0.002210   \n",
       "189 2018-01-01  -2.984228        NaN   7.853885  2.552773    0.002798   \n",
       "190 2018-02-01  -7.540334        NaN   7.853885  2.258052    0.002344   \n",
       "191 2018-03-01 -12.530506        NaN   7.853885  1.989469    0.002091   \n",
       "192 2018-04-01 -12.737886        NaN   7.853885  3.414111    0.000626   \n",
       "193 2018-05-01  -9.379234        NaN   7.853885  5.115145    0.001688   \n",
       "194 2018-06-01  -1.275246  -7.063498  14.480953  6.410427    0.003108   \n",
       "195 2018-07-01   3.697021  14.653356  15.506794  4.911624    0.003306   \n",
       "196 2018-08-01   7.926255  21.900599  15.506794  3.702775    0.002843   \n",
       "197 2018-09-01   8.267585  22.309800  15.506794  2.842774    0.000995   \n",
       "198 2018-10-01   3.913075  13.396497  15.506794  2.283703    0.001895   \n",
       "199 2018-11-01  -3.135130  -7.341910  12.544031  1.478911    0.002618   \n",
       "200 2018-12-01  -7.794605 -21.223143  16.966742  1.635726    0.002337   \n",
       "201 2019-01-01 -11.788565 -28.158920  16.579218  2.692976    0.002801   \n",
       "202 2019-02-01 -14.565860 -33.116796  15.733234  3.659852    0.001359   \n",
       "203 2019-03-01 -16.923111 -33.108929  14.553711  4.511426    0.001944   \n",
       "204 2019-04-01 -15.283052 -32.333142   9.447103  5.798712    0.000168   \n",
       "205 2019-05-01 -13.245628 -23.295709   7.823373  7.018478    0.001401   \n",
       "206 2019-06-01  -8.129267 -10.373096  12.419019  8.241059    0.001382   \n",
       "207 2019-07-01   4.503919  21.549014  14.667119  6.606316    0.003452   \n",
       "208 2019-08-01   7.620849  25.469069  12.620491  4.220526    0.001257   \n",
       "209 2019-09-01  10.372987  18.301898   8.073955  2.729963    0.002912   \n",
       "210 2019-10-01   8.859891  19.431464  12.628502  1.943497    0.000958   \n",
       "211 2019-11-01   2.660688   1.184124  16.905909  1.419184    0.002142   \n",
       "212 2019-12-01  -2.704361  -8.885002  18.050723  0.708779    0.002786   \n",
       "213 2020-01-01  -6.190122 -21.177874  21.716871  1.901966    0.002060   \n",
       "214 2020-02-01 -10.061119 -32.265350  20.766811  2.690424    0.001991   \n",
       "215 2020-03-01 -12.852488 -33.386396  18.280027  3.185171    0.001935   \n",
       "216 2020-04-01 -13.647930 -37.362294  16.088099  4.286053    0.000288   \n",
       "217 2020-05-01  -8.349763 -20.234787  10.925664  6.139752    0.001861   \n",
       "218 2020-06-01   1.707554   3.318717  12.198396  6.624536    0.003818   \n",
       "219 2020-07-01  11.219558  43.325321  10.682909  3.230235    0.004371   \n",
       "220 2020-08-01  12.053084  34.463163  10.688950  3.203375    0.001862   \n",
       "221 2020-09-01  15.017552  29.498407   9.639095  2.478384    0.003472   \n",
       "222 2020-10-01  13.221290  32.547862  15.387149  4.363169    0.000799   \n",
       "223 2020-11-01   5.768155   6.290697  21.247063  4.192047    0.002496   \n",
       "224 2020-12-01   0.015571  -7.802380  21.916328  3.194324    0.002753   \n",
       "225 2021-01-01  -4.987467 -20.422047  23.138380  2.409556    0.002697   \n",
       "\n",
       "       std_sm  std_swe  gw_storage  uncertainty_paper  uncertainty  \n",
       "0    2.782432      0.0    4.696232          10.976552    10.976445  \n",
       "1    3.784017      0.0    6.777050          12.334747    12.334101  \n",
       "2    4.158756      0.0   17.084691          12.213496    12.211881  \n",
       "3    2.262857      0.0   35.438532          12.702134    12.703252  \n",
       "4    5.325474      0.0   38.528416          16.505716    16.506687  \n",
       "5    5.214303      0.0   27.819520          17.151333    17.151681  \n",
       "6    5.728845      0.0   18.535820           8.782598     8.781578  \n",
       "7    5.574764      0.0    2.585782           7.361389     7.359911  \n",
       "8    4.917898      0.0   -3.189627           6.039957     6.038381  \n",
       "9    4.662937      0.0    0.407181           9.703394     9.702870  \n",
       "10   4.342648      0.0   -6.808162           9.754361     9.754227  \n",
       "11   3.528575      0.0  -10.227145          12.394537    12.394604  \n",
       "12   3.131246      0.0    0.613722          11.730666    11.730734  \n",
       "13   3.760173      0.0    3.499101          11.110213    11.109913  \n",
       "14   5.122245      0.0   16.718029          10.551697    10.549593  \n",
       "15   1.224863      0.0   37.181040          19.411017    19.410941  \n",
       "16   2.491428      0.0   29.043648          15.585276    15.585646  \n",
       "17   3.137670      0.0   29.719809          16.263745    16.264069  \n",
       "18   4.706036      0.0   16.735906           8.516458     8.516506  \n",
       "19   5.717083      0.0    8.392260          10.641663    10.640433  \n",
       "20   5.182810      0.0   -0.909747           7.259141     7.258118  \n",
       "21   4.799495      0.0   -7.027631           9.388005     9.387425  \n",
       "22   4.326930      0.0   -1.352455          11.245587    11.245407  \n",
       "23   3.022218      0.0  -11.252260          11.679952    11.680124  \n",
       "24   2.758018      0.0    0.192294          14.650321    14.650278  \n",
       "25   4.067878      0.0   12.297340          12.107300    12.106866  \n",
       "26   4.910270      0.0   13.810033          18.234818    18.233575  \n",
       "27   1.502733      0.0   43.907300          25.114530    25.114810  \n",
       "28   4.346806      0.0   38.192359          18.668728    18.669096  \n",
       "29   4.572028      0.0   33.503001          10.942732    10.944011  \n",
       "30   5.817771      0.0   29.449632           3.402119     3.400926  \n",
       "31   6.228481      0.0   10.222023           9.075346     9.073687  \n",
       "32   5.344062      0.0   -8.419912           8.565041     8.563698  \n",
       "33   4.602517      0.0  -10.359490          10.210458    10.209970  \n",
       "34   3.800068      0.0   -7.317037          10.764782    10.764610  \n",
       "35   2.257276      0.0   -1.820283          12.625689    12.625773  \n",
       "36   2.530077      0.0   -1.253067          11.488555    11.488791  \n",
       "37   4.253686      0.0    6.193266          18.020250    18.020200  \n",
       "38   6.369921      0.0    8.570020          15.666825    15.666241  \n",
       "39   5.326925      0.0   24.846451          16.602154    16.601371  \n",
       "40   2.437925      0.0   26.811643          14.554821    14.555138  \n",
       "41   3.487495      0.0   23.304272          12.909084    12.909384  \n",
       "42   4.070113      0.0   14.143068           9.140331     9.140397  \n",
       "43   5.268741      0.0   -0.378782           5.103329     5.100712  \n",
       "44   4.596342      0.0   -5.073886           5.243245     5.241036  \n",
       "45   3.454466      0.0  -10.865626           6.405382     6.404264  \n",
       "46   2.204349      0.0  -11.401993           6.981929     6.981624  \n",
       "47   1.372796      0.0  -14.340572           6.267628     6.268153  \n",
       "48   3.272605      0.0  -13.991740          11.254824    11.255148  \n",
       "49   5.020188      0.0  -10.249767          11.396369    11.395913  \n",
       "50   6.817257      0.0   12.884746           8.890651     8.888325  \n",
       "51   4.581153      0.0   22.541373           8.739575     8.738788  \n",
       "52   3.496866      0.0   18.024795           7.629147     7.628798  \n",
       "53   2.141063      0.0   18.577043           8.422571     8.422562  \n",
       "54   2.587100      0.0   13.993514           7.999253     7.998874  \n",
       "55   2.123278      0.0   -0.392979           9.331372     9.330885  \n",
       "56   1.411139      0.0   -1.287266           5.526594     5.526211  \n",
       "57   1.788608      0.0  -12.016777           7.265285     7.265603  \n",
       "58   2.628513      0.0   -8.152707           6.818753     6.818896  \n",
       "59   3.221399      0.0  -10.276537          10.110545    10.111332  \n",
       "60   4.504026      0.0   -4.006355           5.014061     5.015410  \n",
       "61   5.656841      0.0   -1.462756           4.210767     4.211342  \n",
       "62   6.821504      0.0   13.984854           9.685052     9.682790  \n",
       "63   4.049263      0.0   28.894688           9.605046     9.603639  \n",
       "64   3.094214      0.0   44.218575          10.560017    10.560905  \n",
       "65   4.604623      0.0   36.735381           8.108193     8.110167  \n",
       "66   5.603176      0.0   17.610183           5.074965     5.075890  \n",
       "67   5.560143      0.0    1.665477           3.490747     3.493635  \n",
       "68   4.867257      0.0    1.167967           4.592836     4.594985  \n",
       "69   4.152811      0.0  -12.403450           7.249161     7.248669  \n",
       "70   3.763609      0.0  -11.534830           5.863826     5.863634  \n",
       "71   2.731683      0.0   -8.318675           2.495755     2.496252  \n",
       "72   2.570854      0.0   -2.606959           4.805718     4.806416  \n",
       "73   4.403662      0.0   -1.242272           1.124662     1.129352  \n",
       "74   6.632092      0.0    7.380300           6.229604     6.227436  \n",
       "75   4.906649      0.0   30.975988           7.099639     7.097797  \n",
       "76   2.419674      0.0   34.515363          11.307441    11.307919  \n",
       "77   3.813775      0.0   33.124524           8.237181     8.238247  \n",
       "78   4.375607      0.0   15.476061           2.249192     2.249078  \n",
       "79   4.228494      0.0   -6.786159           2.084905     2.080490  \n",
       "80   3.928355      0.0  -13.629611           2.985438     2.983191  \n",
       "81   3.739615      0.0  -13.100201           4.540837     4.540295  \n",
       "82   3.142780      0.0  -13.041426           6.596394     6.596621  \n",
       "83   2.474308      0.0  -12.034005           2.415329     2.417327  \n",
       "84   3.641745      0.0  -12.960016           2.909613     2.911780  \n",
       "85   5.622395      0.0  -11.606543           2.071405     2.067770  \n",
       "86   7.022163      0.0    2.098265           3.038366     3.035275  \n",
       "87   7.853235      0.0   16.573644          11.491959    11.490430  \n",
       "88   4.011694      0.0   26.901465           7.989455     7.988673  \n",
       "89   2.820763      0.0   16.415252           1.890429     1.889398  \n",
       "90   2.996287      0.0    9.640316           0.556810     0.553236  \n",
       "91   2.667394      0.0    0.679529           2.547409     2.549775  \n",
       "92   1.534941      0.0  -11.288068           3.886847     3.885879  \n",
       "93   1.361952      0.0   -8.170666           6.134468     6.134542  \n",
       "94   2.018969      0.0  -12.337117           7.179307     7.179851  \n",
       "95   2.973514      0.0  -21.341237           7.231104     7.232038  \n",
       "96   4.700597      0.0   -9.130502           3.372122     3.372798  \n",
       "97   6.510691      0.0    0.131407           2.543081     2.541117  \n",
       "98   7.951608      0.0    9.282103          10.206879    10.204358  \n",
       "99   6.322702      0.0   26.285107          10.940098    10.938859  \n",
       "100  4.060870      0.0   21.569680          13.246847    13.246479  \n",
       "101  2.432197      0.0   22.880472          12.442609    12.442701  \n",
       "102  1.997555      0.0   16.812826           8.336349     8.336233  \n",
       "103  0.909364      0.0    2.038659           7.093484     7.093208  \n",
       "104  1.052040      0.0   -3.919313           3.180323     3.180387  \n",
       "105  2.627608      0.0   -7.353184           2.077719     2.079841  \n",
       "106  3.299031      0.0  -22.718750           6.020000     6.021135  \n",
       "107  3.614012      0.0  -11.989499           2.258283     2.255017  \n",
       "108  4.590205      0.0  -15.861113           4.284319     4.283226  \n",
       "109  6.006562      0.0  -12.909650           5.698578     5.699156  \n",
       "110  7.617259      0.0    0.569941           7.376831     7.379692  \n",
       "111  6.512256      0.0   18.518467           6.134650     6.132842  \n",
       "112  3.587011      0.0   28.351177           8.387149     8.386933  \n",
       "113  3.204180      0.0   18.669893           3.290125     3.290830  \n",
       "114  3.624923      0.0    7.202371           7.527768     7.526844  \n",
       "115  2.525227      0.0    0.899975           8.107695     8.106891  \n",
       "116  1.206700      0.0   -7.013836           8.405674     8.405340  \n",
       "117  1.520573      0.0  -13.503061           7.213352     7.213509  \n",
       "118  2.145792      0.0  -12.378066           7.075663     7.076364  \n",
       "119  3.046575      0.0  -22.371667           9.062847     9.063726  \n",
       "120  4.599952      0.0  -20.739395           6.293012     6.292936  \n",
       "121  5.806949      0.0  -11.837621           5.200086     5.199915  \n",
       "122  7.581939      0.0    3.519198           8.972599     8.970077  \n",
       "123  5.609634      0.0   14.996869          12.179669    12.178575  \n",
       "124  4.046365      0.0   28.713061          11.821997    11.821723  \n",
       "125  2.576498      0.0   23.957277           4.391217     4.391140  \n",
       "126  2.096299      0.0   13.158909           4.639683     4.639280  \n",
       "127  1.767067      0.0   -7.979713           8.993144     8.992810  \n",
       "128  0.686998      0.0  -12.140417           8.723229     8.723059  \n",
       "129  1.447584      0.0  -13.701483          11.578767    11.578952  \n",
       "130  2.262162      0.0  -15.518282          12.159102    12.159427  \n",
       "131  3.072319      0.0  -17.705918          11.980066    11.980728  \n",
       "132  4.570885      0.0  -20.913687           2.584368     2.582329  \n",
       "133  6.084380      0.0   -8.907032           2.145166     2.148212  \n",
       "134  7.876589      0.0    5.767177           8.494145     8.491987  \n",
       "135  7.142825      0.0   18.032111           5.184905     5.181906  \n",
       "136  5.430534      0.0   20.858615           6.957909     6.956115  \n",
       "137  2.969275      0.0   17.887203           8.311835     8.311816  \n",
       "138  2.087938      0.0    9.970185           4.952045     4.952074  \n",
       "139  1.022872      0.0   -1.524990           7.764172     7.764205  \n",
       "140  1.155549      0.0  -12.206591          11.254490    11.254765  \n",
       "141  2.434158      0.0  -18.827541          14.268910    14.269358  \n",
       "142  3.379573      0.0  -20.659978          14.074992    14.075492  \n",
       "143  4.134604      0.0  -24.155760          12.136209    12.136957  \n",
       "144  5.196969      0.0  -26.192284          10.100881    10.101831  \n",
       "145  6.465825      0.0  -18.730035           3.922198     3.923358  \n",
       "146  8.170101      0.0  -12.005577           7.031059     7.034827  \n",
       "147  6.544724      0.0    8.171606           5.051597     5.053983  \n",
       "148  5.578922      0.0   22.465225           7.545742     7.544669  \n",
       "149  3.230540      0.0   21.175376           8.178680     8.178754  \n",
       "150  2.613696      0.0   10.949669           1.910405     1.909197  \n",
       "151  1.330542      0.0   -1.953378           3.713638     3.712819  \n",
       "152  0.347781      0.0   -9.784077           3.929440     3.929550  \n",
       "153  1.907758      0.0   -7.609499           7.763034     7.763525  \n",
       "154  2.772418      0.0  -12.053327           3.812458     3.814002  \n",
       "155  3.646530      0.0  -20.776448          20.037860    20.038217  \n",
       "156  5.135801      0.0  -20.517851           4.907987     4.907870  \n",
       "157  6.535107      0.0  -14.390265           2.785169     2.782520  \n",
       "158  7.775992      0.0   -1.528436           3.162477     3.166265  \n",
       "159  6.623962      0.0   21.617895           2.494150     2.488774  \n",
       "160  4.572463      0.0   27.238775           4.936402     4.935828  \n",
       "161  2.810608      0.0   29.892166           4.808274     4.808910  \n",
       "162  3.406470      0.0   24.770212           4.406243     4.404995  \n",
       "163  2.215086      0.0    0.869333           5.110030     5.109039  \n",
       "164  0.505648      0.0  -12.948497          14.965472    14.965381  \n",
       "165  1.228498      0.0   -8.351126          10.552608    10.552866  \n",
       "166  2.384052      0.0  -10.622032           7.242302     7.243114  \n",
       "167  3.631238      0.0  -24.915391          15.703114    15.703523  \n",
       "168  5.213907      0.0  -22.823939          15.250864    15.251359  \n",
       "169  6.573525      0.0  -10.087163           2.524579     2.521293  \n",
       "170  7.617674      0.0    1.041421           6.414163     6.411129  \n",
       "171  5.970964      0.0   22.416817          14.168673    14.167017  \n",
       "172  3.406150      0.0   17.076766           4.592837     4.592333  \n",
       "173  2.321258      0.0   12.379050           5.225684     5.225632  \n",
       "174  1.850903      0.0    7.232021           5.410192     5.410031  \n",
       "175  1.477886      0.0   -8.688663          12.466464    12.466199  \n",
       "176  0.384361      0.0  -22.782864          17.443192    17.443155  \n",
       "177  1.512801      0.0  -13.503893          12.514776    12.515049  \n",
       "178  2.585507      0.0  -14.853683          12.337883    12.338453  \n",
       "179  3.566897      0.0  -13.670127          12.090717    12.090905  \n",
       "180  4.762937      0.0   -8.509658           8.015202     8.014725  \n",
       "181  6.350166      0.0   -9.775499           4.080999     4.079641  \n",
       "182  7.023011      0.0   -5.271984           3.515795     3.512373  \n",
       "183  4.483774      0.0   16.130619           6.448198     6.446007  \n",
       "184  2.172765      0.0   20.159270           7.547356     7.548035  \n",
       "185  2.936756      0.0   20.328044           7.284158     7.285273  \n",
       "186  3.670514      0.0   12.818191           6.943403     6.943373  \n",
       "187  3.967245      0.0         NaN           6.778235     6.776889  \n",
       "188  3.141420      0.0         NaN           7.198263     7.197382  \n",
       "189  2.551365      0.0         NaN           7.427923     7.427440  \n",
       "190  2.258264      0.0         NaN           7.522217     7.522281  \n",
       "191  1.991342      0.0         NaN           7.597240     7.597732  \n",
       "192  3.413529      0.0         NaN           7.073283     7.073002  \n",
       "193  5.113761      0.0         NaN           5.960953     5.959766  \n",
       "194  6.407827      0.0   -5.788252          12.986060    12.984777  \n",
       "195  4.909188      0.0   10.956335          14.709199    14.708386  \n",
       "196  3.701632      0.0   13.974344          15.058505    15.058224  \n",
       "197  2.842912      0.0   14.042215          15.243966    15.243992  \n",
       "198  2.283274      0.0    9.483422          15.337774    15.337711  \n",
       "199  1.479386      0.0   -4.206781          12.456489    12.456546  \n",
       "200  1.637905      0.0  -13.428538          16.887498    16.887710  \n",
       "201  2.695752      0.0  -16.370355          16.358588    16.359045  \n",
       "202  3.661204      0.0  -18.550935          15.301315    15.301638  \n",
       "203  4.513206      0.0  -16.185817          13.836237    13.836818  \n",
       "204  5.798837      0.0  -17.050090           7.457965     7.458062  \n",
       "205  7.017429      0.0  -10.050081           3.458445     3.456316  \n",
       "206  8.239928      0.0   -2.243829           9.291696     9.290693  \n",
       "207  6.603965      0.0   17.045094          13.096260    13.095074  \n",
       "208  4.220231      0.0   17.848220          11.893967    11.893862  \n",
       "209  2.730251      0.0    7.928911           7.598320     7.598424  \n",
       "210  1.942739      0.0   10.571573          12.478174    12.478056  \n",
       "211  1.417120      0.0   -1.476564          16.846409    16.846236  \n",
       "212  0.707650      0.0   -6.180641          18.036846    18.036802  \n",
       "213  1.903032      0.0  -14.987753          21.633330    21.633424  \n",
       "214  2.691960      0.0  -22.204231          20.591595    20.591795  \n",
       "215  3.187055      0.0  -20.533908          18.000057    18.000390  \n",
       "216  4.286334      0.0  -23.714364          15.506588    15.506666  \n",
       "217  6.138237      0.0  -11.885024           9.038373     9.037344  \n",
       "218  6.621538      0.0    1.611163          10.244808    10.242870  \n",
       "219  3.229320      0.0   32.105763          10.183124    10.182835  \n",
       "220  3.204597      0.0   22.410079          10.197265    10.197649  \n",
       "221  2.481580      0.0   14.480855           9.314177     9.315029  \n",
       "222  4.362380      0.0   19.326572          14.755813    14.755579  \n",
       "223  4.189594      0.0    0.522541          20.829906    20.829412  \n",
       "224  3.191927      0.0   -7.817951          21.682643    21.682290  \n",
       "225  2.408298      0.0  -15.434580          23.012708    23.012576  "
      ]
     },
     "execution_count": 56,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "merged_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "id": "458a22e6-c14d-4916-bbb7-2087f5aaca5f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "count    226.000000\n",
       "mean       9.108675\n",
       "std        4.802625\n",
       "min        0.556810\n",
       "25%        5.284981\n",
       "50%        8.324092\n",
       "75%       12.128982\n",
       "max       25.114530\n",
       "Name: uncertainty_paper, dtype: float64"
      ]
     },
     "execution_count": 57,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "merged_df.uncertainty_paper.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "id": "5f34c312-b2fc-46e5-aa7a-017ccc708041",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "count    226.000000\n",
       "mean       9.108400\n",
       "std        4.802779\n",
       "min        0.553236\n",
       "25%        5.283284\n",
       "50%        8.324025\n",
       "75%       12.129434\n",
       "max       25.114810\n",
       "Name: uncertainty, dtype: float64"
      ]
     },
     "execution_count": 58,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "merged_df.uncertainty.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "id": "1fc39113-3b00-49fe-b511-66b65ca155c9",
   "metadata": {},
   "outputs": [],
   "source": [
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "id": "577e1921-c64a-460a-aa28-9a258023d844",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.collections.PolyCollection at 0x7f63a7e86a90>"
      ]
     },
     "execution_count": 60,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 2520x540 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(1, 1, figsize=(35,7.5))\n",
    "ax.plot(merged_df.time, merged_df.gw_storage)\n",
    "ax.fill_between(merged_df.time, merged_df.gw_storage - merged_df.uncertainty, merged_df.gw_storage + merged_df.uncertainty, alpha=0.35)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "id": "b9bfed60-d0f9-4c91-b73e-a8ba95c29b7d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='time'>"
      ]
     },
     "execution_count": 61,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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h1RERERERERERERFRpjFgT/ry8734zbkxPHLvWvzF7S3QaVQ42c8KXCKJwxuGxaRf9PsK9Rq892ArDvfY8WIXWyUT0crWPeVFTWkBCnTqRb/3lZuq4A5GcaiHr31EREREREREREREqxUDdgDPd07h07/rwCs3V+HdL2uGXqPGltoSnBxgwJ5pvlAUH/35eTh84Wwvha4himKiRXzh4hXsAPAne+tRU1qAT/++A6IoKrw6IiLldE140LZIe3jJ/rYyFOk1ePzcmMKrIiIiIiIiIiIiIqJsyfuAfcDuw/u/fxrttiL8xx9thiAIAIAdDRZcHHUhGIlleYX55XifA985OoifvjSc7aXQNfzhGELReEot4gFAr1Hjr+5qw7lhF353gfOIiWhlisVF9E77Fp2/LtFr1LhrvQ1PXJpAJMY28URERERERERERESrUV4H7P5wFA9/+xQA4Ctv3QmjTjP7ZzsbzIjERJwdcmZpdflp2BkAAPzh8kSWV0LXkjoKpBqwA8CD22rQUm7Cfz5xBVEGTUS0Ag3P+BGOxlMO2AHgvo2VcAUiOMUuOERERERERERERESrUt4G7KIo4pEfn0PnhAefe9M21FuN1/35jgYzALBNfIaNzCQC9hP9M3D62SY+V9iTAbs1jYBdo1bhb+9Zg54pH356ekSppRERKaZ70gsAaK0oSvlnNlQXAwD6pn2KrImIiIiIiIiIiIiIsitvA/YvP9+L35wbw4fuW4sD7eU3/bnZpENLuYkVaBk24gxAoxIQi4t49spUtpdDSQ5fCEB6FexAopJzc20J/vsPXQhFOW6BiFaWrtmAPfUK9qqSAmhUAgYdfqWWRURERERERERERERZlJcB+/OdU/j07zrwqs1VePhA87zft7PBgpP9DsTjYgZXl99GnQHsaDCjvEiPJ9kmPmfYvVIFuz6tnxMEAY/cuwYjzgC+e3RQiaURESmme9KL8iI9Sgq0Kf+MWiWgurQAQwzYiYiIiIiIiIiIiFalvAvYR5wBvP/7p9FuK8Kn/2gzBEGY93t3NJrhDkbRPeXN4Arz28hMALVmI+5cW4HnrkwhHOXs7lwwO4O9ML0KdgDY31qGfc1WfOGZbnhDUbmXRkSkmO5JL9rSqF6X1FkKMJQceUJEREREREREREREq0veBey/PT8GVyCCL/zJdhh1mgW/d1ejBQBwsp9t4jMhHI1jwhNEjbkAd62zwRuK4nifI9vLIiRmsOs0Kph06rR/VhAEPHLfGth9YXz9xT4FVkdEJD9RFNE96U2rPbykzmzEMCvYiYiIiIiIiIiIiFalvAvYhxx+FOk1aC4zLfq9jVYjrCYdTg4w5M2EcVcQogjUlhbg1tYyGLQq/IFt4nOC3RuG1aRbsOPDQrbXm3H3ehu++nwvZpLV8EREuWzCHYI3FF1awG4xwu4Lw8euHURERERERERERESrTt4F7AMOP+osxpSCQkEQsKPBjFMDrGDPhGFnotqvxlyAAp0a+1vL8eSlCYiimOWVkcMXgsWUfnv4a/3tPWvgDUfxxed6ZFoVEZFyuicT42GWErDXmgsAAMNsE59xQw7/7GNHREREREREREREpIS8C9gHHX40WI0pf//ORjMG7H5MeUIKroqAxPx1AKgpTQQTd6+vwIgzgI5xTzaXRUjMYF9uwL6msgiv3VqDRw/3Y9wVlGllRETK6JpMvPcsJWCvtySuM4bYJj6jHL4wHvziYdz92efwoR+fxaSb7zVEREREREREREQkv7wK2GNxEcOOwOzGdyp2NCTmsJ9im3jFjTgTAXtVqQEAcHBtBQDgD5fYJj7b7L5Ei/jl+sDd7YiLIv77qS4ZVkVEpJzuSS+KDRqUF+rT/tk6KWCfYcCeKaIo4u9/eg4ufwRv3FWHn50ewe3/+Sz+56kuBMKxbC+PiIiIiIiIiIiIVpG8Ctgn3EGEY3HUp1HBvrGmGDqNCif72SZeaSMzAVQU6aHXqAEAFUUGbK0r5Rz2HJCoYE8/ZLpRncWIN+2uxw9PDqFv2ifDyoiIlNE96UWbrSilkTI3spp0KNCqMeRgi/hM+fGpYfz+4gT+5p52fPLBzfjDB1+G29eU4zNPduLgfz6Ln740jHicI2eIiIiIiIiIiIho+fIqYB+wJyrJ0qlg12vU2FJbgpOcw664EWcANcm5tZK719twdtjFNq9ZFIzE4A/HYC1cfgU7ALzvjlbo1Cr85xNXZLk9IiIldE960Vqefnt4ABAEAXWWAgyyRXxGDDn8+OdfXcKeJgv+7LZmAECD1YT//ZMd+NG796GiWI8P/vAs7v/CIRzrtWd5tURERERERERERLTS5VXALs1CbbCY0vq5HQ0WXBhxscWowkacgdn565K71tkAAE91TGZjSYREe3gAy57BLqkoMuDPDzTjN+fGcLh7WpbbJCKS04wvDLsvvKT565I6sxHDbBGvuFhcxAceOwMBwH+9YQvUqus7DuxqtODn77kV/++Pt2LaG8Iff+UoHv72Sbj8kewsmIiIiIiIiIiIiFa8vArYBxw+qFXC7IzvVO1sMCMaF3F22KnMwgjxuIgxZ/CmCvZ2WyHqLAWcw55FDq+8ATsAvOf2FtRbjPjoLy4gHI3LdrtERHLonvICAFptywjYLUYMOfwQRbYlV9KXnuvByYEZfPyBDag1z92hSKUS8MC2Gjz9N7fjb+5ux+8vTuB7xwczvFIiIiIiIiIiIiJaLfIqYB90JCqkter0/m/vaDADAE6xTbxiprwhhGNx1N5QwS4IAu5aZ8OL3dPwh6NZWl1+s/tCABIzheVi0Krxz/dvQO+UD199oVe22yUikkPXRDJgX2KLeACoNRfAF45hhpXSirkw4sJnn+zEKzdX4YGtNYt+f4FOjfff2YayQj36pr0ZWCERERERERERERGtRvkVsNt9ac1fl5hNOrRWFOJkv0OBVREADM8EAOCmCnYg0SY+FI3jxS62E88Gh8wt4iUH11Tgvg2V+J+numbHNxAR5YLuSS8KtOqbxpakoy55vcHXN2UEIzH89WNnYC3U4RMPbIQgCIv/UFKj1Yh+Ox8XIiIiIiIiIiIiWpr8CtgdftRb0w/YgUSb+FMDM4jH2epVCSPOZMBeevPjs7vJgiKDBn+4zDbx2SAF7FaTXvbb/qdXr4daJeCff3VR9tsmIlqq7ikvWipMUKlSD21vVJdsVz7EOeyK+NRvO9A96cV/vn4LSo3pHQBrsJowYPcptDIiIiIiIiIiIqKV7emOCfzZoyeYiS4gbwJ2dzCCGX9kSRXsQKJNvDsYnZ3LSvIaWaCCXatW4fY1FXi6Y5JP5iyw+8LQqAQUF2hkv+3q0gL81Z1t+MPlSTx5iQcoiCg3dE94ltUeHgDqLIn3syFHQI4l0TWe75zCNw/34x23NOK2tvK0f77RasSEO4RAOKbA6oiIiIiIiIiIiFa2F7qm8YfLk+gY92R7KTkrbwL2wWQr0IYlBuw7Gy0AgJP9nMOuhBGnHyUFWhTq5w5x71pXgWlvGGeGnZldGMHhDcNi0qXVfjcd79rfhHZbIT72y4vwh6OK3AcRUap8oShGXUG0ViwvYC8yaGE2alnBLjOnP4xHfnwWbRWF+PDL1y7pNhrKTAASnY2IiIiIiIiIiIjoelJn4yO99iyvJHflT8Ce3EStW2LA3mg1wmrS4eQA57ArYWQmsOCs29vbK6BRCfgDq5wzzu4Lyz5//VpatQr/+sAmjDgD+PzT3YrdDxFRKnqSnWpaK4qWfVt1FiNnsMtIFEV85GcX4PCF8dk/3gqDVr2k22lMjgvqZ5t4IiIiIiIiIiKim8wG7D0M2Oez7IBdEASDIAjHBUE4KwjCRUEQ/jn5dYsgCE8KgtCV/NW8/OUunRSwL3UGuyAI2NFgZgW7QkacgTnbw0tKjFrsarRwDnsWOHwhWAuVC9gBYHeTBa/bXouvvtCL7km2HCGi7OmakAL25VWwA4k57AzY5fN0xyR+c34MH7i7HRtrSpZ8Ow2WRAU757ATERERERERERHdzO5NBOzH+uyIcXTznOSoYA8BuEMUxS0AtgK4TxCEvQA+DOApURTbADyV/H3WDNj9MBu1KDZol3wbOxvNGHT4MekJyrgyEkVx0Qp2ALhrvQ2dE97Zdv+UGQ5fGBaTXvH7+ftXrEWBVo1//PlFiCJfsIkoO7qnvNCoBDQs8UDetWotBRhxBngRKpOzwy4IAvBn+5uXdTslRi1KjVr083qCiIiIiIiIiIjoJjP+MIr0GniCUVwcdWV7OTlp2QG7mOBN/lab/J8I4H4Ajya//iiAB5Z7X8sx5PCj3mpa1m3saEjMYT/FKnZZuQIR+MIx1C5QwQ4k5rADYBV7htl9YVgVbBEvKSvU40P3rcWRXjt+eXZU8fsjIppL96QXTWUmaNXLP4NYZzYiEhMx4ebBPDlMuIIoK9RDp1n+Y9NgNbGCnYiIiIiIiIiI6AaiKMLuC+Pu9TYAbBM/H1lmsAuCoBYE4QyASQBPiqJ4DIBNFMUxAEj+WiHHfS3VgMOH+iXOX5dsrCmGXqPCyQEG7HIangkAwKIV7A1WE9pthQzYMygcjcMTjCo6g/1ab9pdjy11pfiXX1+GKxDJyH0SEV2re9IrS3t4IDGDHQDbxMtk3B1EZbFBlttqtBrRP83HhYiIiIhIDqFojN0IiYiIVglfOIZwNI41lUVoKTfhMAP2OckSsIuiGBNFcSuAWgC7BUHYmOrPCoLwkCAIJwVBODk1NSXHcm4SicUx6gyiYZkBu16jxpbaUgbsMht1JgP2RSrYAeCudTYc63PA5Z87fBVFEZ0THnzrSD86xt2yrjMfzfgTczYyFbCrVQL+9f6NcPhC+MwTVzJyn0REklA0hgG7T76APfm+NpQ8SEbLM+EOwlYsz8iSBqsJo64AQtGYLLdHRERERJSvOsbd2PfJp/Gp33VkeylEREQkA0dy/rrZpMO+FitO9DsQicWzvKrcI0vALhFF0QngWQD3AZgQBKEKAJK/Ts7zM18RRXGnKIo7y8vL5VzOrNHk/NPlVrADwI5GMy6OuBAIc0NWLiPJgL16kQp2IDGHPRYX8Wzn1X9Odm8Ivzgzgr/90Vns/eRTuOezz+OffnER//E7BrTLZU++kGaiRbxkU20J3rq3Ad8+OoALI5ztQUSZ0z/tR1yEbAF7jbkAgsAKdrkkAnb5KthF8WoXHSIiIiIiSt+A3Ye3fu04HL4wvnmoH5MejsciIiJa6Rz+q7nQLS1l8IdjODfMrOZGyw7YBUEoFwShNPnfBQDuAtAB4JcA3p78trcD+MVy72upBpMb2/XW5QfsOxvMiMZFnB12Lvu2KGFkJgCDVpVSiLu1thRlhTr84PgQ/v13HXjV517Ajn/9A/7qB2fw5KUJ7Gy04FMPbsKdaytwaYwV7Mvl8GW2gl3ywXvWQCUIePz8WEbvl4jyW9ekB4B8Abteo0ZlsQFDMwzYlysYiWHGH5GtRXyD1QQAnMNORERERLREE+4g3vK1Y4jG4vjq23YiEovjay/0ZXtZREREtEwOXwhAIhfa22wFABztZZv4G2lkuI0qAI8KgqBGIrD/oSiKvxYE4QiAHwqC8KcABgG8Xob7WpIBezJgl6OCvcEMADg1MDP7D4uWZ8QZQHVpAQRBWPR7VSoBd62z4QcnhnCi34HtDWb87T3tuK2tHBtrSqBWJW7DE4ziqY5JOHzhjIfDq4k9+UJqLczs32FJgRZVpQa2VSaijOqe9EIQgJZyeQJ2AKgzGzHs4GvZck26E+9HthL5KtgBcA47EREREdESzPjCeOvXjsHhDeN7f74XW+pK8eot1fj20QG8+2UtMHMvjoiIaMW62tlYD4tJh7WVRTjcM433HmzN8spyy7IDdlEUzwHYNsfX7QDuXO7ty2HI4YdOrZKl6qnUqENrRSFO9jtkWBkBiYC9JoX28JK/u28tXrGpCtvqS1Fk0M75PRuqiwEAF0dduK1NmdED+eBqBbs8M2/TUWc2YphVn0SUQV2TXtSaC2DQqmW7zVpLAY708ITnco27E60m5apgt5h0KNRrWMFORESy8AQjePXnXsRHXrked6+3ZXs5RESK8oaieMc3T6Df7sc337kLW+pKAQDvPdiKX5wZxTcO9+ODd7dnd5FERES0ZFIuZDYl8rd9LVZ879ggQtEY9Br59k1XOllnsOeqAbsftZYCqFSLV0inYmeDGacGZhCPi7LcXr4bmQmg1px6wG426XCgvXzecB0A1s8G7GwTvxwOXxgqASgtmP/vWil1ZiOGWPVJRBnUPeFFe0WRrLdZZzZi3B1EKBqT9XbzzWzALlMFuyAIaLAa0W/nQS4iWhlmfGH8/U/PwRWIZHspNIfzIy702/34xG8uIRKLZ3s5RESKCUZieOhbJ3FhxIUvvHk7bmkpm/2zdlsR7t1gwzcP9cEd5PsVERHRSuXwhaFTq1CoT9Ro72u2IhSN48ygM7sLyzF5EbAPOvxokKE9vGRHgxnuYBRdk17ZbjNfBcIx2H3htCrYU1Fq1KGmtIAB+zLZfWGYjTrZDqeko85SgGlvCIEwQykiUl4kFkfvtBdtNpkDdosRopg4TEZLN+FKBOy2InkCdgBotJpYwU5EK8Zvzo/h+8eH8MTF8WwvhebQMeYBAPTb/fjJqeEsr4aISBnRWBx/+f3TONxjx3/80eY5O3a872Ab3MEovn1kIAsrJCIiIjlIo5elsc57mqwQBOAwu3ReZ9UH7KIoYtDhl2X+umRnowUAcHKAbeKXa8SZCBxq0qhgT9X66mJcGnXJfrv5xOHN3gz7uuRzlm3iiSgTBux+RGIi2irkm78OAHXJ97chBuzLMuEOwqBVobhg2dONZjVYjRieCSDKSkMiWgGO9CY2Mjh2JDd1jLthNemwta4U//NUFzvXENGqE4+L+PBPz+OJSxP42KvX48HttXN+36baEty+phxfe7EP/nA0w6skIiIiOUgBu6TEqMXG6pLZz6WUsOoD9hl/BN5QFPVWk2y32Wg1wlas52kNGcwG7KXyHYCQbKguRu+0jxf0y2D3hbIWsNeaE/8mhhiwE1EGdE8mKs/aFahgB4AhB1/LlmPcHURlsWH25KwcGq0mROMiRp1B2W6TiEgJoijimBSw99ohihxVlms6xj1YV1WMR+5dg1FXEN87NpjtJRERyUYURfzrby7jx6eG8YG72vGOW5sW/P73HWyFwxfG948PZWiFREREJCe7Lwxr4fW50L4WK84MOtlx+BqrPmCXWn/KWcEuCAJubS3D4e5pzmFfJqllriIV7FXFEEXgcrJdH6VvrhfSTKmzJKs+OYediDKgcyIx9qWlQr4DeQBgKzZAqxZ4WGiZJtxB2Irlaw8PJCrYAaCfbeKJKMf1THkx7Q1jc20JxlxBDNj5npJLYnERV8Y9WFtZhFtby7Cv2YovPNPNg95EtGp841A/vn6oD++8tRF/eWfrot+/s9GCvc0WfOX5Hnb0ICIiWoEcydHB19rXbEU4FsepgZksrSr3rPqAfTBZMSZtosplf2sZZvwRXBrjjO/lGHH6oVYJsBXpZb/tDTUlAMA28ctwYyuQTCov1EOvUbHqU2bxuIizQ04eDiK6QdekF3WWAhh18rUgBwC1SkBNaQGGeVhoWcbdQVSWyBuwN5YlDlNwDnvmnBly4gfHWdVJlC6pLfwH7m4HwLl3uabf7kMoGsfaqmIAwN/euwbT3jC+cag/uwsjIpJBMBLDF57pxm1tZfjHV65PuaPU++9ow4Q7hB+fGlZ4hURERCS3mTlyoV1NFqhVAo70TmdpVbln9QfsydP9dWZ5A/ZbW8sAAIe6+Y9pOUZmAqgsNkCjlv+fYnWJAaVGLQ9BLFE0FofTH4HFJP/hh1QIgoBacwGrPmXkCkTw5986ifu/cAhfeKY728shyildEx60VcjbHl5SZzHytWwZRFHEhDuESpkr2CuK9DBoVehnJWjGfO6pLnz05xdY1UmUpqO9DlSXGHB7ezlsxXrOvcsxl5OfN9dWJq4jdjSYccfaCnz5uR64ApFsLo2IaNl+eWYUdl8Yf/GyFqhUqY9ruqXFiq11pfjisz2IxOIKrpCIiIjkFIrG4AlFYb0hYC/Ua7C5tmT2ADjlQ8Du8KOiSI8CnVrW27UVG9BuK8SLDNiXZcQZUKQ9PJAIaDdUF+PiKAP2pZjxJzaDbnwhzaQ6i5Et4mXSOeHBA184hOc6p7CppgT/76kunBlyZntZRDkhGoujd8qHNluhIrefeC1jiLtUM/4IwtE4KmQO2AVBQKPVxAr2DInHRZwcmEE0LuLMoDPby8lLvzk3BneQYd9KI4oijvbasbfZCkEQsK/ZiiM9nMOeSzrGPFCrBLRWXL2O+Jt72uEORvF/L/RmcWVERMsjiiK+fqgPayuLsK/FmtbPCoKA99/RiuGZAH55ZlShFRIREZHcZnyJfQPLHKOD9zVbcXbYBW+IhRNAHgTsAw6/rPPXr3VraxmO9zkQjHCe0FKNzARQW6pMwA4AG6pL0DHu4WnZJXD4wgCQtRbxQKLzBKs+l+/x82N44AuH4AlG8f2H9uI7f7YHlcUGfOCxM/DxzZAIAw4/wrG4chXsZiNm/BF4GGwtyYQ7CACyV7ADQL3FyAr2DOmc9MxWch7vd2R5Nfmnf9qH937vJXzy8cvZXgqlqWvSC7svjL3NiWDjlpYyTHtD6J70ZnllJOkYd6Ol3ASD9uqh/g3VJXjlpip8/cU+2L2hLK6OiGjpDnXb0THuwbv2N6XcGv5ad6ytwLqqYnzh2W7EOKaOiIhoRbD7Ep9fLMabc6FbWsoQi4s4wX0dAHkQsA85/KiXef66ZH9rGULROF4amFHk9le7SCyOcXdQsQp2AFhfVYxwNI6eKW5ApUt6Ic1uBXsBPMEoXH6GUksRi4v41G878J7vvoQ1lUX49fv3Y1ejBSUFWvzXG7ag3+7Dv/6GG+1EXROJ94h2xSrYE+9z7MixNONSwF4i/8iSxjITBu1+bvhlwPG+xIevskI9Tvbz2jnTeqcTr3M/PDmMvml2bVhJjibbwUuVg9KvbBOfOy6PebC2svimr3/g7nYEIjF88dmeLKyKiGj5vn6oD2WFOrxmS/WSfl4QBLzvYCt6p3z47YUxmVdHRERESpitYJ8jF9rRYIZWLeAo28QDWOUBezASw7g7qFgF+55mK9QqgW3il2jcFURcBGoUrWBPbHRcYpv4tM1WsM/RCiRT6syJ5y6r2NM34wvjHd84ji8914M376nHDx7ai8qSq9Wfe5utePhAC75/fBBPXBzP4kqJsq9rwgMAaClXKGDna9myTLgSAbtNgQr2BqsR4eSBP1LW8T4HqkoMeMWmSrw0OIMouwtlVN904vVHrRLw2Sc7s7waSseRHjtqSgtQmzyUXGcxoqa0AIe7uaGRC9zBCEacAayturkLTmtFIR7cXotvHR3AmIuH7IhoZemZ8uLpjkn8yZ6G6zp0pOu+jZVoKTfh8093c7wJERHRCjBbeDlHLlSgU2NbnZkHvpNWdcA+PBOAKCY2T5VQqNdgW10pDjFgX5IRZ2KTQckK9ubyQhi0Ks5hX4KcaBGfPBzD2cXpuTjqwqs//yKO9TrwqQc34d9euwl6zc0fiD94dzs2VBfjwz89j0kPwyXKX12TXtSUFsCk1yhy+3wtWx4p/K4okj9gb7SaAIBz2BUmion2YbsaLdjVaIE/HMOlMV6bZVLftBfFBg3+bH8Tfnl2lIdPV4h4XMSxPsfs/HXJLS1WHO2zI87uG1l3ZTxxSG/dHBXsAPBXd7ZBFEV87unuTC6LiGjZvnGoDzq1Cm/Z27Cs21GrBLzn9lZ0jHvw1OVJmVZHRERESrmaC83dSXJvixUXRlyzYwDz2aoO2Acdic1SpSrYAWB/WxnOjbjYwnoJRmaSAbuCFexqlYC1lcW4OOpS7D5WK7s38UJqnmPWRqaw6jN9j58fw+u+eBjRmIjHHt6LN+6un/d7dRoV/vuNW+ELRfHIj87xNDnlrc4Jj2Lt4QHAbNTCpFNjeIbVa0sx4Q6irFAHnUb+y1bpEOYA57AratDhx4Q7hF1NiYAdAE6wTXxG9U/70VRmwsMHWlBs0OC/nriS7SVRCjonPXD4wtjbbLnu6/tarHD6I7g8zoMS2daRPCw0VwU7kDhk98Zd9fjhiSEM8r2GiFYIpz+Mn5wawf1bq1FetPwxTa/ZWo06SwE+9wyr2ImIiHKdwxeGIAAlBdo5//yWFivi4tVRgPlsdQfsyQ+w9RaTYvexv7UMoggc7mEVe7qkCvZqBQN2AFhfXYxLo25exKfJ4QujpEALrTp7LxMlRi2KDBqGUikSRREf/sk5tNuK8Kv378e2evOiP9NaUYSPvnIdnuucwrePDmRglUS5JRqLo3fahzbb3BvjchAEAXUWIyvYl2jcFVSkeh0AqkoKoFOr0M8KdkVJH7r2NFlQWWJAnaUAJ/hBLKP6pn1oLDOhxKjFu29vwVMdkzg1wMcg10lz7fY2W6/7+uwcds69y7pLYx6UFGhRucAYk/fd0Qq1SsD/+wPHMxDRyvD940MIRGJ4561NstyeVq3CwwdacHbIyQ6TREREOc7hC8Ns1EGtEub88231pdBrVPw8ilUesA84/DDq1ChTcIb0lrpSmHRqzmFfgpGZAMoK9cua5ZSKDdXFcAejDGnT5PCFYc1ie3hJnZmhVKqmPCG4g1E8uK0mrVPmb9nbgINryvGJ31yenUVNlC8GHX6Eo3G0VShXwQ4AtWYju3Es0YQ7hMoSZQJ2tUpAnaUAA9N8bJR0ot+BUqMWreWJ59muBgtODjh4+DFDgpEYRl2B2ZEI77ilEWWFenz6d1f4GOS4o70O1JoLZkeNSKpKCtBUZsJRzr3Luo5xN9ZVFV3Xwv9GtmID3nFLI352ZgSdvNYmohwXicXx6OF+3NJixfrqucdfLMWOhkQBADtHERER5TaHL7zg2GC9Ro0dDWYWHWOVB+xDDj/qLcYFP+wul1atwt5mK+ewL8GIM6Do/HXJhuoSAOAp2TTZfaGszl+X1FkKMMTDESnpmUpUYDaVpxcUCoKAT//RFhTqNfirH5xBOBpXYnlEOalr0gsAilawA8nXMkeAYdYSTLiDsC1QGbhcjVYTK9gVdqJ/BjsbLFAlTz/varJg2htGPzdYM2LI4YcoAs3liYDdqNPg/Xe04lifAy908TNMrorHRRzts99UvS7Z22zFsV4HojFet2VLPC7iyrgHa+eZv36td7+sBSadBp95glXsRJTbfnthHOPuIN4lU/W6ROr0MeEOynq7REREJC/7IgE7kGgT3zHumZ3Xnq9WdcA+YPffdNpfCfvbytBv97PKNk0jzgBqSpXbMJesrSyCSgAucQ57Why+MKwKdn9IVZ3ZiOEZP0OpFPRNJwKi5rL0x2KUF+nx76/bjEtjbvzXk5zLSvlD6trQqnAFe73FiEAkBnueX3imKxRN/J0t1Hp3uRqsJgzY+T6jlElPEH3TPuxpujpDeldjooKJbeIzozd5fSBVsAPAG3fXoaa0AP/xe1ax56orEx44/RHsmydgv6XFCk8oykPEWTQ044c/HMO6eeavX8ts0uGdtzbidxfHGS4RUc4SRRFfe7EPTWUm3LG2QtbbLjVqodOoMOHhayAREVEuc/jCsBgXzoWksWXH8ryr2qoN2EVRxKDDj4ZMBOytZQA4hz0doigmA3blK9gNWjVaygu5+ZSmRCuQ1NuMK6XOYkQwEseUN5TtpeS83ikv9BrVkp9Xd6234c176vGV53s5Q4XyRtekFzWlBSjUaxS9nzpz4nqEh/HSM+lOvPZXlij3ftRgTRx+mPLwfUYJJ/pmACSq1iUt5YUwG7U40c+APRP6pYD9mgN4eo0aH7i7HedHXPjdhfFsLY0WIF2L7Wm2zPnnUmX7YV6zZc3lscQhvVQq2AHgrnU2AMDJ/hnF1kREtBwvDc7g7JAT77y1cbbzkFwEQYCtWI8JFwN2IiKiXDbjC8OySOHl5tpSGHXqvP88umoD9klPCKFoHPVW5QP21opCVBTp2WIxDdPeMMLReEYCdiAxh/3SGAP2VMXjImb8kdyYwW5J/BsZcrBN/GJ6p31oKjMt64PwR1+5Dk1WEz70k7OIx1nRRqtf14QXbTZlq9cBzHbUGWTAnhapyk/JFvENyWtFtitXxol+Bwq0amy4ZoanIAjY2WhhwJ4h/XYfLCYdSgq01339tdtq0FpRiP984gpifM/POUd77aizFKDWPPfn2fIiPdoqCnEkzysGsqlj3A1BANpTHDOzvroYBq0KpwYYsBNRbvr6i/0oNmjwuu21ity+rciACTcPtRIREeWqRC4UXjQX0qpV2NVoyfvPo6s2YJc2sOszUMEuCAL2t5bhcI+dgVSKRpyJsLRmng0juW2oLsGYK5j3MyFS5QpEEIuLuTGDPflvZHiGwcdieqe8s/NVl8qo0+A9B1sx5AigY9wj08qIclMsLqJnyos2hdvDA0CtOXFYaHiGh4XSIW3AKT2DHQAGOIddEcf6HNjRYIZWff3Hjl2NZvTb/Zhkm1DF9U370DjHoWO1SsDf3N2OnikffnZ6ZNHbicdF/O7CGA9GZEA8LuJYn2Pe9vCSW1qsONnvQDjKOezZ0DHmQZPVhAKdOqXv16pV2FJbilMDfA4RUe4ZnvHjtxfG8Kbd9TAp1N3LVmLgmAwiIqIc5gxEEBeRUi60r8WK7klvXu/rrNqAfcCeuYAdSMxhd/jCuDzOKulUjCQDhkxWsAPARc5hT4k0IzgXZrDXsq1ySsLROIZmAmguW35QKI29eLF7atm3RdcbdQZmDxhR9g05/AhF42hLsfJsOUx6DawmHV/L0jSe3IBTcgZ7jbkAapUwe+1I8nEFIugYd2NX480trncmv3aKrZIV1zftQ9M81wf3bazEppoSfPbJToSisTm/RxRFPNMxiVd+7kW8+zsv4T3ffQmRGANdJV0ed8MViMy2gZ/PvhYr/OEYzg07M7Mwus7lcTfWVaXWHl6ys9GMi6NuBMJzP9+IiLLl0cP9EAQBb7ulUbH7SFSw5+8mPBERUa5z+BKFLikF7MnPq/k8anbVBuyDDj8EAfO21JPbrclA6lA328SnYsSZ2MSuMWcmYF8/G7DzAEQqpEr/XKhgL9CpUVaoZ4v4RQw6fIjFxWVXsANAZYkBbRWFHHuhgPd+7yW84UtH5g0xKLM6JxJdGjJRwQ4AtRYjhtiNIy0T7iB0GhVKjdrFv3mJtGoVas0F6GcFu+xeGpiBKAK7msw3/dnG6hIYtCocZzW0ovzhKCbcITSVzf2ZSBAEPHLvGow4A/jB8aGb/vxkvwN//OWjeOc3T8AXiuJP9zdhyhPCk5cmlF56Xjvam3heLBaw72myQhDye0MjW3yhKAbsfqytTO+Q3s4GC6JxEWd5KILoOu/97ks4+J/P4uenRzi2JAu8oSh+cGII922sVLQQprJED184Bk8woth9rDaeYASv++JhnB7koVQiIlKe3Zt6LrShuhhFBk1efx5dvQG73YfqkgLoNJn5v2grTgRSL3bn7z+mdIzMBFCk19w0C1IppUYdakoLGLCnKJ2TSplQay5gKLWInqlEMNRcLk9QuL+tDMf7HAhGGATLxRWI4OyQEyPOAL59ZCDbyyEAXZNeAMhIBTsA1JkLeFgoTeOuICqLDRAEQdH7abCaWMGugGN9DmjVArbV3Ryw6zQqbK0rxUlWsCuqfzrx77qxbP4DeLe1lWFPkwWfe7ob/nAUAHB5zI0//eYJ/NGXjqDP7sO/PLARf/jgy/APr1iHmtICfPcY38eUdKTHjgarEdWLhBxmkw7rKotxOI83NLLlSvKQ3to0K9i31ZcCAOewE11DFEU83zWFkZkA/vqxM3jFf7+A318chygyaM+UH58cgieYOEinJGnsE+ewp65zwoNTAzP4zJOd2V4KERHlgRl/6gG7Rq3C/tYyPN0xmbejs1dvwO7wZ6w9vOTW1jIc77MzkErBiDOQsep1yfrqYlxii/iUzLaIN+mzvJKEOlZ9Lqp3NmBffgU7kNhsD0XjDD5kdLzPgbgIVJcY8Lmnu+Hy89R+tnVNeFBdYkChQjMGb1RnMWLUGWBVThrG3UFF28NLGq1G9Nt93MiV2Yl+BzbVlMw7n3hXowUXR13whqIZXln+kDozNFrnvz4QBAEfum8Npr0h/Mfvr+ADj53BK/7nBRzvd+CRe9fguUdux1v3NkCnUUGtEvDmPfU41G1H75Q3U/838kosLuJ4nx17mxauXpfsa7Hi1OAMP4NmWMdYMmBPs4K91KhDW0UhTrJ7B9GscXcQnmAUH33VOnzuTdsQicXx8LdP4YEvHMILXVO8PlNYLC7iG4f7sa2+FNvrbz4UKaerATvbxKdqxJn4u3qhaxoXRrinSUREyko3F7pngw2TnlDeduhiwC6j29rKEIzE8RLb9ixqeCaQsfnrkg3Vxeid9s1W5tD8HMlWIGZTZjoMLKbOXIBRZxBRzvucV++UF2WFehQb5HnM9jRZoVULeIFz2GVzuGcaeo0KX3zLDriDEXzh2e5sLynvdU16M1a9DgB1ZiOicRFjLlaxp2rCHYStRPmAvcFqgicYxQwPvsgmGEnMhd7VdPP8dcmuRgviItjyUkF904mAvWmBCnYA2NFgwZ1rK/CNQ/14/PwYHj7Qghc+dBDvPdgKo+76Q0hv2FkHjUrA944NKrbufHZ5zA13MIp9LakF7Le0WBGO8jNopnWMu1Go16B2CYfGdzSY8dKgM2+rPIhu1DEuHVgpxqu3VOOJDxzAp1+3GdPeMN76teN401eP4tQAD6Uo5VivHQN2P955q7LV6wAD9qUYcyY+Oxp1anz5+d4sr4aIiFa7dHOhO9bYoFYJeTtGblUG7L5QFNPeMOqtmQ3Y9zRboVYJnMOegmxUsG+oLoEoApeT1QY0P7svjCK9BnrN3BVnmVZnMSIWFzHm4oew+fRO+2SrXgcAk16DbfVmvMg57LI50mPHzkYzttSV4nXba/HNQ/0YcrAzQ7bE4iK6J70Zm78OYPbgH9vEp0YURUy4g6gsVr6bSmPympFz2OVzetCJSEzE7sb5A/Zt9aVQCcAJdktRTN+0DxVFephS6NTxz/dvwAfvbsfzHzqID798LUqNc7eEKy/S496NlfjRqWFWTSvgaG+i3fti89clu5osUAnAUbaJz6iOMQ/WVhYtaYTJjgYzXIEIetgFgggA0JkM2NckD75q1Cq8YVcdnv7bl+Fjr16P7kkfXvfFI3jXN0/AkayqIvn0Ja9/dzUqW70OALbkdf04A/aUjToDKDJo8Na9DfjNuVEMcqwVEREpyO4LozCNXKjEqMXeZgueYMC+egwmA4tMV7AX6jXYVlfKOeyLcAcj8ASjGa9gX1+dmI/HNvGLc/jCsBTmxvx1IFH1CYBt4hfQN+1D8yLVaek60FaGi6Nu2L2cj7Zcdm8IHeMe7Etulv/NPe0QBHCOWhYNz/gRisbRZstcwF5nSbzv8bUsNe5AFMFIfLbSRUkNyYB9gAG7bE70OyAIwM6G+QP2IoMW66qKcaKPVWlK6Z/2LTh//Vq1ZiP+8s62lJ5zb9nTAFcggt+cG1vuEukGR3vtaCozoTLF7h3FBi021ZTgSC8/g2aKKIq4PO7GujTnr0t2Jg8eneQc9ow60mNn1WyOujLhQWWxASXG6yul9Bo13nFrE57/0O340H1r8HTHJL5zdCBLq1y9JlxBqASgvFD5Q61GnQZFBg0mOYM9ZSPOIGpKC/DOW5ugVgn4vxdZxU5ERMqZ8YdTmr9+rXvWV6J70puXB4iXHbALglAnCMIzgiBcFgThoiAIf5X8ukUQhCcFQehK/qr8UcgkKWBvyHAFO5CYw35+2MnZugsYmUlU7mW6gr26xIBSoxaXxtwZvd+VyOFL/4VUSVIoNTzDqs+5OP1hOHxhWSvYAWB/WzkA4BAropbtWDI82tdSBgCoKinAn+5vws9Oj3COWpZ0TiQu+jLZIr66tAAqAexckCKpsiUTAXut2QhBAAZYESKbE/0OrLEV3bRZfqNdjRacHppBhGNgFNFv96FpgfnrS7W32YLmchO+e4xBh5xicRHH+hzY2zz/wZS57Gspw5khJ0dhZciIMwBPMIq1VUu7hmi0GmE16XCKAXvG/OLMCN701aP44y8fgdPPCuhcc2Xcg/bK+Z9PRp0G77m9FWsri3Cin4fy5DbmCqKsUA+NOjM1WJXFBoyzO2HKxlwBVJUYUFliwGu31eCHJ4dYBEFERIpZSi5093obAORlm3g5rp6iAP5GFMV1APYCeK8gCOsBfBjAU6IotgF4Kvn7jJDa5WS6gh0A9reVIS4CR3rZVnk+swF7hivYBUHAhupiXBxlwL4Yuy8Maw4F7FIoNcxQak49U4mKy+YyeStxN9WUoKRAixe7OId9uQ73TMOoU2Nzbcns1959ewvMRi0++dvLEEXO4My0rslEK8rWDLaI16pVqCopYMCeIilgT7WKczkMWjWqSwoYsMskGovj1MAMdi8wf12yq9GCYCTOw0YKcAcjmPaG0STzATwgcV39J3sa8NKgE5d4bS2bS6NueILRlNvDS/a1WBGJiTjJcQsZ0TF2dV70UgiCgO0NZgbsGXK0145HfnQOG6qLMeoM4j3ffYmHunJILC6ia9KLNSl0ldrdZMGpAR7Kk9u4O4iqDFxvS2zFBkx4GLCnatQZQHVy//ShAy0IRuJ49AgPOK40oijCH45izBXA5TE3jvba8bsL4/jhiSF89fle/MfvO/DLs6PZXiYREeze9HOh6tICbKwpxhMXxxVaVe5adsAuiuKYKIovJf/bA+AygBoA9wN4NPltjwJ4YLn3lapBhx/FBs28cwOVtLWuFCadGi9yDvu8RpzZqWAHEnPYO8Y9/EC2CLs3lFMV7LOhFCvY59SbbL8idwW7WiXglhYrXuyaZgC8TEd67NjdZIH2mqqAYoMWf3lnGw512/FcJw8xZFrXhBdVJQYUGxaurpVbrZmvZamaSFa2VGaggh1IdD7iDHZ5XBx1wx+OpRiwJ5pcMRiUX/904t9zowIV7ADwR9trodeoWMUuo3Tnr0t2NZqhUQk4zK5DGdExnjhUsmaBitvF7Gwwo2/axypEhXVPevDQt06i3mrE9/5sL/7twU043GPHx355kZ9vcsSA3YdwNI41KRxY2d1kgT8cY9GEzCbcwYx0jJLYig2z1/m0sEA4hhl/ZDZgb60oxN3rbfjWkX52rVlBjvbaseWfn8D6f/o99n3yabz8v1/AG79yFO/+zil86Cfn8InHL+MLz/Tgb390Ft4QH1ciyi6HLwzzEnKhe9ZX4vSQE5N5NpJJ1v4/giA0AtgG4BgAmyiKY0AihAdQMc/PPCQIwklBEE5OTckTMAw4/KjPQnt4IBEE7m224hDnsM9rxBmATqNCmUn5+U43Wl9VjHA0npfzIFIlimJy1kbmH5+F1JpZ9Tmf3mkfNCoBdQp07djfVoZRV3C2Sp7SN+FO/P3tm2Oz/E/2NKDeYsSnftuBWJybfJnUNenJaPW6pM5i5GtZiqQK9orizLwfNVhNrGCXidS+dXfj4gF7RbEBDVYjW74qoC8ZsDelOIM9XSVGLV69pRo/Pz3CzUCZHOm1o7nMlHbQYdRpsLWulHPYM+TyuAf1FiMK9Zol38aOhsThIlaxK2fSE8Tbv34Ceq0a33znLpQYtfijHbV4+EAzvntsEN9iBWhO6JxIdIRYk8LYJum64ngfX+vkNOYKZqRjlMRWrMekJ4Q4P/8uatSVOJhdXXr18Xn3y1rg9Efw2ImhbC2L0hCMxPD3Pz2PEqMWf3ffWnzywU343z/Zju/92R78+v378eLfHcT5j92Dxx7ai3A0jqc7JrO9ZCLKY6IowuFfWmfjezbYIIrAHy7n1+uYbAG7IAiFAH4C4K9FUUz5OKkoil8RRXGnKIo7y8vLZVnLkMOPBosyG0mpuLW1DH3TPgzPcJN2LiMzAdSUFkClEjJ+3xuqE6ei2cpyfu5gFJGYmFMt4oFkKMXn1Jx6p7yotxqvq46Wy22tiddltolfuiPJarJbkvPXr6XTqPCh+9agY9yDn740nOml5a14XET3pBftGZy/LqkzGzHpCSEYiWX8vleaCXcQFpMOeo06I/fXaDXC4QvDFYhk5P5Ws2N9DjRYjahIMSTc2WDByYEZVhPKrH86cd3UoODB4z/ZUw9fOIafnx5R7D7yRTQWx4k+B/a2pFe9LtnXYsX5YSfcQb6GKa1jzI21y6heB4CNNSXQqVUM2BXiC0Xxrm+ewIw/jK+/fRdqzVdfBz9031rcta4CH//1JbzAzzhZ1zHugSCkNrapotiApjITjvfxeSMXfzgKTzCa0YC9ssSAaFyE3RfO2H2uVKPJDqDVJVc7gO5oMGNXoxn/90Ifu3OuAF9+rhd90z584oFN+IvbW/Cm3fV4xaYq3NJaho01Jag1G1Fk0GJnowXlRXr89vxYtpdMRHnMF44hHI0vqbPxGlsR6i1GPHlpaW3iV+p+kCxpjCAIWiTC9e+KovjT5JcnBEGoSv55FYCMHF2IxUUMz/gVqeRM1f62RIhymFXscxp2BjI+f13SXF4Ig1bFlmILcCQ/5ORSi3ggEUpNuBlKzaV3yif7/HVJvdWIeouRYy+W4UiPHcUGDdZXz9328JWbqrClrhT/9UQn/31nyPBMAMFIHG1ZqWAvmF0DLWzCHURFUea6qTQk22gPsop9WeJxESf7HSlVr0t2N5nh8IXZLUVm/XYfakoLYNAqd0hla10pNlQX47vHBlfsB+JccXHUDU8o/fnrkn0tVsRF4EQfu0EoKRiJoW/ah3VVS5u/LjFo1dhYU8yAXQHRWBzv//5pXBp14wtv3o5NtSXX/blaJeD/vXEb2ioK8Z7vvsTudlnWOeFBo9WEAl1q71W7Gy040e9g9bNMxjM8kgkAKooS9zWRZy1kl2LMmfg7qr5hD/XdL2vBiDOAX5/jzO5c1j/twxee7cYrN1fhQPvCRYVqlYCXb6zEM1cm2f6fiLLG4V16LiQIAu5Zb8OhbnvaHe6+c3QAt37qaYSjK+/g2LIDdkEQBABfA3BZFMXPXPNHvwTw9uR/vx3AL5Z7X6kYcwUQiYmKVmospq2iEBVFerzAQGpOUgV7NqhVAtZWFuPiqCsr978SOHyJOYCWwhwL2JOh1IiTodS1YnERA3Y/WmSev36t/W1lONrr4OnoJTrcO409zVao5+naIQgC/uHlazHuDuLrh/oyvLr81DWZaEXZlo0K9uQBQHbkWNy4O7PtKhvLEo8N57AvT8+UFzP+CHalMH9dsjMZxrNNvLx6p32z/66VIggC/mRPAy6PuXF6yKnofa12s/PX03juXGt7vRk6jWq2cw4po3PCg7gIrKta/jXEzkYLzo24EIrygKVcRFHE//fLi3i6YxL/+sAmHFw756RCFOo1+OrbdkKnVuHPHj0Jp5+VtNlyZdyDdlvqh153N1ngCkTQmbyep+XJRsAuXd8zYF/ciDMAQcBNo2MOrqlAu60QX36ulwccc5QoivinX16ETq3CP71qfUo/8/KNVQhG4nimg91ViCg77FIutMTCy3s2VCIci+O5K6m/jnlDUXzmyU6MuoIrMveRo4L9VgBvBXCHIAhnkv97BYBPAbhbEIQuAHcnf684qeqoPosV7IIgYH9rGQ53T/NU7Q2CkRimvSHUmLMTsAPA+upiXBp18yJ0HvbkSaVcbBEPgLOLbzA840c4FkezggH7gbYyeENRnOHGedqGHH4MOQK4ZZF2r3uarbhrnQ1ffKZntovEXALhGI712vG7C+N8DVuGzolEpVI2ZrBL1yfDfC1b1LgrlNHNPumxGWDAvizH+lKfvy5pLjPBatIxYJdZ/7QPjVblx2bdv7UahXoNvnOU84yX42ivHS3lppRHK9zIoFVje30pDjNgV1THWCLUW1u5vAp2INHmNxyN48IID3/L5UvP9eK7xwbxnttb8OY99Qt+b53FiC+9dQeGZ/x47/de4mHiLAhGYui3+1Oavy7Z3STNYec1gxzGkyF3pmewA8CEO5Sx+1ypRp0BVBTpodNcv32vUgl46EALOsY9eLaTYWwuevz8OJ7vnMLf3NN+0wGJ+exusqCsUIfHL7BNPBFlx4x/eZ2NdzSYYTHp8EQabeIfPdw/uxe+EnOfZQfsoii+KIqiIIriZlEUtyb/97goinZRFO8URbEt+WtGrn4HHdkP2IFEiz67L4zeabYbu5Y0PyhbFexAYg67Oxhle9555HKLeAAY4uN2nd7pRBDUXK5cULivpQwqAXihi1050nUkWY22L4V5qh9++Rr4wlF87ukuAIkTz0MOP35xZgQf++VFvPpzL2LTx36PP/7KUbz7O6fw1OWMTF5ZlbomPagsNqCkQJvx+y4vTGyQ8LVsYZFYHHZfKOXNCDkYdRpUFOkxwBbxy3Ki34GKIn1a3aQEQcDORjNO9rNVslxmfGG4AhE0lSkfsJv0Grx2Ww1+fW6MVaBLJIoiTg7MYHfT0trDS/Y0WdEx7k67JR+l7vK4GwVatSz7DdvrzQDANvEy+cWZEfz77zpw/9Zq/O09a1L6mV2NFvzbazfhULcdH//VJYVXSDfqmfIiFhfRXpl6wF5rLkB1iWH2QB8tTzYC9vJCPQTh6n3T/MZcQVSVzL1/+pot1agqMeDLz/VkeFW0GE8wgn/+1UVsqC7GW/c2pPxzapWAezdU4unLkwiE2d2GiDLvauHl0sY1qlUC7lxbgac7JlNq9+4ORvCV53uxqSYx0mkwHwP2XDPg8EOjElCVwYvDuUgz2bonGbBfS2rzkM0K9g3ViScs57DPze5b3gupUiqK9NCpVaz6vEFvcl5ts4Ib6CUFWmyuLcWLXTwZna6jPXZYTTq0Vyy+adRaUYQ/3lWP7xwdwEPfOond//YUbvv0M/irH5zBYyeGUKjX4OGXNeNrb9+J5jIT/v13HYixS8qSdE140ZZGK0o5qVQCas0FnPO9iElPCKKY2c0+AGi0mhiwL9OJPgd2NVmQmCKVul2NFgw6/GwXKpO+ZCeGTATsAPDmPfUIR+P48anhjNzfamP3heEJRtNqkzyXrfWliIvAuWGnPAujm3SMebCmsgiqeUb/pKO8SI9Gq5GHi2Rwot+BR350DnuaLPj0H21O6/F5/c46PHSgGd8+OoBvH+lXbpF0k84JqSNE6gG7IAjY3WTB8T4HO3rJYNwVRLFBA6NOk7H71KhVKCvUY5LXfIsadc4/YlOnUeFP9zfhaK+D3QZzzGee7MSUN4RPvHYTNOr0opdXbKpCIBLDc50sqCCizJstvFzG6OB7NlTCE4ziWN/indW+/mIfXIEIPvHajdCpVflZwZ5rBh1+1JoL0n4Dk5u0mdUzxTaj1xqZyX4F+9rKIqgE4BLnsM/J4QujQKtGgU6d7aVcR6USUGMu4NziG/ROeVFs0CjeceC2tjKcHXbBHYwoej+riSiKONxjx95ma8qbfB+4qw0lBVpcmfBgf2sZ/uX+Dfj1+/fj/Mfuwfcf2otH7l2LO9fZ8Mi9a9A16cVPGGSkLR4X0T3pRVsKhx6UUmc28rVsEVLImskW8QDQYDVyBvsyDM/4MeoKptUeXsI57PLqS34GacxQwL6uqhg7Gsz43rFBBh5LIB3sSafzw1y21pYCADfaFSKKIjrG3bLMX5fsaLDg1MAMnzfL9OXnemE2afGVt+6EXpP+59i/u28t7lxbgY/96hK6JjjbO1M6xj3QqVVoSHOcya4mC6Y8IfTzUOSyjbuCGT/QCiSu8VnBvjBRFDHqCixYQPbG3fUoNmhYxZ5DLoy48Ojhfrx5dz221pWm/fN7miywmHR4/Hzq7ZWJVqvuSQ8+91QXXv+lw/jDpYlsLycvOHxh6DQqmJaRC93WVoYCrRpPLvKYOf1hfO2FPty7wYbNtaWotazM3Gf1Bex2/+ys5mwy6TWoKjGgZ4oV7NcadQagEjJfkXYtg1aNlvJCVrDPw+EL51x7eEmtuQBDDrZVvlbvlA/N5YVpVwqma39rGWJxEUc41zNl/XY/xt3BlNrDSyqKDTjxkbvw3CMH8dk/3oq37mvExpqSmw6N3bexElvrSvGZJzsRjLB1WDpGnAEEIrGsVbADQJ2lAIMOPzfTFzDhSmy4VRRntptKY5kJk54Q/GG2V14KaR6qNB81HRuqi1GgVeMEW77Kot/ug0q4OmInE96ytx690z5eKyzBQPJgT71leQcizCYdGq1GnBl0yrAqutGkJ4QZf2S2W50cdjSYYfeF2T1lmc6POHFLSxlKjEsb/6NWCfjU6zYjLor49TnOvs2UznEPmstN0KZZILNndg4732+Wa8IdzOhIJomtWM8Z7IuY8UcQjMRRvUCBUqFeg7fta8TvLo6jl/vPWRePi/jozy/AYtLhQ/euXdJtaNQq3LvBhqcuT3Cvh/KOKIq4OOrCfz1xBXd95jnc9Znn8V9PduLMkBOPnRzK9vLygsMXhsWoW1bOYNCqcaC9DE9cnFhw3/P/XuiDJxTFX9/VDiAx8pst4nPAoMO/7JP/cmkpL2QF+w2GnQHYig1pf4CS24bqYlwaY8A+F7svDOsy2oAoqc7Cqs8b9U570VyufHXatnozjDo1XmCb+JQd7knMrL8ljYAdQEoXMYIg4MMvX4txdxDfPNy/lOXlra7JRFXSctvwLkdTWSE8wehs6yW62XgWK9gBMOhYohP9DhQbNFhjS7+6U6tWYVt9KU6wVbIs+qZ9qDUbodNk7pr75RurYDZq8d1jgxm7z9ViwO6HICQOYC3Xtnozzgw5eYhLAZeTnx/XVsoXsO9sTMxhP8k57Es26Q5iwh2and24VOVFeuxsMOMJVkhlTOeEN6328JKW8kJYTDrOYZdBYsZ3NgJ2A8cCLWI0OWJzoYAdAN5+SyO0ahW++kJvJpZFC/j+iUGcGXLiI69ct+QDX0DimtoXjuH5Tu6/0eoniiJOD87gk49fxsv+41m88n9exBee6UZ5oR4fv38Djv3DnXhwWy2O9zkQ55hMxclVeHnP+kqMu4M4PzJ3B2mHL4xvHOrDKzdXzR5erjMbV+Q4zVUVsNu9IbgCETQs8+S/XJrLTeid8nJz4xojM/PPD8qkDdUlGHMFGW7MweEL5WwFe53ZCKc/Ag/blAMAvKEoJtwhtJQrHxTqNCrsbbbixa5pxe9rtTjcY4etWK/Y/Nu9zVbcsbYC//tMN5x+vpalqnMicbK/tTx7LeKlQzE8hDe/cXcQOrUq4+9HjckWpQNsE78kx/sc2NloWfJs4l2NFnSMuzmORAb9dl/G5q9LDFo1Xr+zDr+/OM65qmkadPhRXVKwpNbWN9paV4pJTwhjLj4Gcrs8ljikt2YJgeB8WssLUWzQ4BQD9iWTNu421S4vYAcSm4GXx9wrcv7jSuMJRjDiDKB9Cc8nQRCwu9Ey2zmHliYai2PaG8r4gVYgEbA7fGGEoqzQnc/VgH3hx6e8SI/X76jFT06NzP4MZd60N4R//20H9jVb8cDWmmXd1r4WK0qNWvz2AtvE0+r3L7++jNf+72F87cU+NJaZ8KkHN+HER+7C9x/ai7fta4St2IA9zRa4AhF0jHOMj9LkKry8Y20F1CoBT1yc++Dql5/rgT8Swwfuapv9Wr3FCHcwCpd/Ze0HraqAXTr1vbW+NLsLSWopT1SoTXnZ9kgyPBNAjTkXAvbEyZj5TtHkM4c3d1vES1U9bBOfIM1Xbc7QBvr+1jL02/3ccEqBKIo42mPHLS1lirbv/9B9a+AJRfHFZzlzLVVdE15UFOmXdaJ8uVqTh2I4RmZ+E64gKor1io+/uFF9soKdMz3TN+0NoWfKt6T28JJdjRbEReAlBk3LIooi+qf9GQ/YAeBNu+sRjYv4zXm2WE5Hv92HepnGnEnzPk+zTbzsOsbdqCktQEmBfNcQKpWA7Q1mnBpgULhU54ZdUAnAehla99+93gYArGLPgM7krPuldL0BEuNohmcCGGGguGRT3hDiImDL0gx2AJhkm/h5pVrBDgB/cXsLAOB/nupSdE00v3/7zWUEIjH8ywMbl/0ZVqtW4Z71Nvzh0gQPodCqd3poBptrS3Dqo3fjW+/ajTfuroe18PpRgXuaE51Bj/ZyNIzS5KpgN5t02N1owROXbj4oNOUJ4dEj/bh/SzVaK65eB0pjv1da9+JVFbCf6HNAp1Fhswwnl+UgVZX2TLIKCkhU2444A7PBQjZtrS+FTqPCC2y3cx1RFBMnlXI1YE/OER1eYS+0SumdToRzzRl6Tt3WVgYAeLGbVeyL6Zzwwu4LY19zeu3h07W2shgPbqvFNw7387R6iromPWhf4kaeXKpLC6DXqNAzyYB9PuPuYFaqaYoNWlhNOlawL4E083lng3nJt7GtvhRqlcCKtGWa8obgDUXRmIWxWU1lJlhNOnSMsbogHYN2+cacrasqhk6jwpkhHlSRW8eYZ0ntrBezs8GMzgnviqvWyBUXRlxorSiESa9Z9m01lpmwxlaEJy6yalBpV8YT18FLvS6XDvSd4DXDkkmdTrLRIr6iOBGeTHrYbWU+o64gdBpVSvtztWYj3rynHj86NcxZ7FlwpMeOn54ewUMHmtFaIc/+3Ms3VcETirKLJK16Q44A1lYWLVgEU1NagHqLkQF7Bjh8YZiN8uRCd6+3oXPCi/7p6/fXvvhsDyIxEX+VnL0ukQorV9oc9lUVsB/vd2BrXaksrfXkcLUFLC9uAKAjObNunQwny5fLqNNgX7MVT3dMZnspOcUfjiEUjcNi0i/+zVlw9SQTg0Qg0V5aECDbhuxiWisKUVls4AV+Co4k56/vS3P++lJ88J7EBclnn+xU/L5WunhcRPekV7YPvUulVgloKjOhd5oh7nwm3aGsVNMAiddUzmBP35WJ5bdONuk12NVoxuPnxzhiaRn6pxP/fhuzUMEOAG22QnROMmBPlScYgd0XRoNVnsdLp1FhQ3Uxzgw5Zbk9SghFY+iZ8mJtlfwB+/bkwaSXeCgibaIo4tyICxuXOX/9WvdssOFEv4Pj5BTWOeGBSadG7RI7HK6rKkaRXoPj/QzYl2oiGbDbsnCotTJ5nT/uYgX7fEadAVSXGFKuhn7fHa3Qa1T4DPcFMu5jv7yIWnMB3newbfFvTtGtLWUoNmjw+Hke+KLVKxCOYdobmi2oW8jeZguOcQ67okLRGLyhqGyFl1JnqCev6Qw17griO8cG8OC2mps67s3mPgzYs8MbiuLiqBt7ltGWUm6VxQYYdWr0csYqAOByMmBfX539gB0A7lxXgd5pH093XkPaRJBj1oYSzEYtTDr1inuhVUrvlBe15gIYtJk5VCQIAva3leFQzzRivKBZ0OEeO+osBbMXB0qqKS3A2/c14CcvDeMK5xEtaMQZgD8cy3oFO5DocsMDeHMTRRHj7iBsRdkK2E0M2Jega8KDmtICFBmW1zr5we216Lf7cZrh4JJJJ8Sby7JzmKjdVoTuCS8PSaRIer2R88Dktjozzo+4EInFZbvNfNcz6UM0LipyWHxrXaJ7x6l+BuzpmnCHMOUJYbOcAfv6SsRF4KnLbBOvpI5xN9ori5bcSlmtErCz0cyuN8sgVbBnZQZ78jp/ws0K9vmMOgMptYeXlBXq8af7m/Drc2O4wHGYGeMORnBlwoO37G1AgU6+vTmdRoW711fiyUvjCEd5PUer04gz8Tkolb3Tvc1WzmFX2Iwv0U3LIlMuVGcxYn1V8XVt4v/32W7E4yL+8s6bDyQVG7QwG7WsYM+WlwZmEIuL2NWYOwG7SiWgudzEDfSkS2NulBq1WWk/NZeDayoAgFXs17BLAXuOtogXBAF1FiNbxCf1Tfsyvnl+W1sZnP4ILo7yA9t8YnERx/ocireHv9Z7D7bCpNfg07/ryNh9rkTdyZbsbbbsjyppKTdhyOHnTLU5eEJR+MMxVJZkp5tKg9WIUVcAwQgfm3RcmfCiXYbn1ss3VkKvUeGnLw3LsKr81Gf3QasWUF2anWvutopCeEJRjHPTPCXSBoJcM9iBxDisYCTOg3cy6hhPHBZfWyl/wG7UabChuhgnOYc9beeTIdImGccEbqwpRlWJgXPYFSSKIq6Me5Y8f12yu8mK7kkvpr2sgl6KCXcQOrVKllmr6So1aqHTqBiwL2DMFURVSXodHv78QDNKCrT4zyeuKLQqupE0qm+p3TgW8opNlXAHozjUwy6StDoNORLPH6k1+EI4h115dl/iekrOXOieDTacHJjBtDeEEWcAPzg+hNfvrJv3UEWdxciAPVtO9DugEq62V8sVrFC76tKoG+uripd8QlludRYj1tiKGLBfw5F8Ic3GB6xU1ZqNs2/A+UwUxUTAXp7Z9q+3tibmsL/ANvHzujzmhisQwS0tZRm7z1KjDu+5vRVPdUziGC8259WZbGHdluUW8QDQUlGIuAhWSs8hm+0qgUTIJYqJjgeUmmgsjp5JryzdIYoMWtyzoRK/PjfGAyhL1DflQ53FCI06Ox/12pL/Djon+BkoFcpUsJcCADtByOjymBt6jQqNCo1m2l5vxtkhdh1I1/lhJ1QCsL5KvoBdEATcs96GF7qmEAjzfUgJ094wZvyRZY2VAa7OYT/JNvFLMu4Owlaiz8oenSAIsBXrGbDPIxKLY8IdRE2ahyWLDVr8xe0tePbKFLs7ZIgUsKd7GCIV+9vKUKTX4Lfnx2S/baJcMJQsoKtNoUW8NIf9WB/3PJUidTaWawY7kOgMJSY7Q33+6S4AiZEm80kUVq6svbhVE7Af63NgY00JCvWabC/lOs1lhRhxsgoqGoujY9yD9Tkwf/1ad6yrwPE+B9zBSLaXkhPsXqmCPTdnsAOJU21DM/68bzs67g7CH46huTyzQWFZoR7rqorxQtdURu93JTmcwfnr13rnrY2oLDbgU7/ryPvnx3y6Jr0oL9KjVMaLxaVqST53eyYZQN1IqnrNRrtK4OrmyLiLG36p6rf7EY7FZRu/8OD2Gjj9ETzTwfeapei3+9Ak0zzvpZD+HXRNsHo6FYMOH6wm3bLHK1yr1lwAq0mHM4NO2W4z33WMe9BuK1Ls4MrORjMCkdjsWDVKzbkRF9ptRbK25QWAezZUIhiJ43l+5lGE1F1juRXsm2pKYNCqcIxB4pKMuYKoKpY/FExVZbGB3W7mMeEOIi4irRbxkrfva0RFkR6f5r5ARow6E/+Ga5bwWC1Gr1HjrvU2PHFpggfwaFUacvih06hQXphaDrGniXPYlaTE6OB1VUWoNRfg20cH8KOTw3jj7roFXy/rk52LV9Jo2lURsIeiMZwZcuZUe3hJS4UJopho5ZzP+qZ9CEXjOTN/XXLn2gpE4yJe6GQ1LnD1hVSuWRtKqDMb4Q/HZtear3qnpPmqmd9Av62tDKcGZuAPRzN+3yvBkR47mstNGa++NWjV+MDdbTg96MTvL7Kl5Vy6JuVpYS2HpuRzl11ubiYF25VZGikjtdUeY8CeMilIXW4lmuS21jKUFerxs9NsE5+ueFxMBOxZuD6QWEw6lBXqZruG0ML6p/2ol7kqWhAEbKsvxZkhzvSWgyiKODfswsYa5T7L7kh24jvJOewpE0URF0Zc2Cjj/HXJ7iYLig0aPMFrakVcSb4/tC/zukGnUWFbHeewL9WEOwhbFkc4VhQbMOlme/+5SJ9DqpYQ2hbo1PjLO9twcmAGz1xhx06ljToD0KgElBcpU6j08o2VcPojONLDql1afYYcAdSaC6BSpdZJZW+zFU5/ZPY6guQ1mwvJWHiZ6AxViQsjbqhVAt57cP7qdSCR+0Ri4oo6gLcqAvbzwy6Eo/HZ9lC5ZLZCLc830C8lT+LnWsC+rd6MUqMWT3XwgzOQeCHVaVQwyVwBICdpRsfQCmsXIrfe5GtKplvEA8D+1jJEYiIrBeYQicVxPMPz16/1uu21aK0oxKd/34EoTzhfRxRFdE940FYhTwC4XCa9BlUlhtnDMnTVpCex0ZatFvHS/Y6xRXzKrkx4IAhAq0zjFzRqFe7fWo2nOybh9Of3gbp0TXiCCEbiaMxiwA4AbRVFbBGfokGHHw0yzl+XbK0rRc+UDy4/O3UtV9+0D65ABFuTrfeVUFVSgJrSApwaZMCeqjFXENPeMDbLOH9dolWrcOc6G57qmOA1tQI6xz0oK9ShLMWKtYXsbrLg0pibXQnTJIoixl1BVBZnr3uhVMHOKuubSW3H020RL/njXXVosBrxH7/vZKWnwsZcQdiKDVCnGBCm60B7OUw6NX57gW3iafUZmvGjLoX28JI9zYnsj3PYleHwhaESgJIC+TqrAYk57ADwlr0Ni+7z1Uu5zwqaw74qAnYp5MnFCvamMhMEAeiZzO8N9EujbujUqtkDB7lCrRJwcE0Fnr0ytaJaTyjF7gvDatJlZQZXquosiRO8K+mFVgk9Uz4YdeqstFDe3WSBTqPCIc5hv8n5ERd84VhG569fS6NW4UP3rkHvlA8/OsXKz2uNuoLwhWNoy5EKdiBxCC/fD+DNZdwVREmBFgZtdg57GbRqWEw6jK2gE7PZ1jnhQYPFKOtj9tptNYjERPzqHDeT0tGXPLSTzQp2AGi3FaJ70stN80WEojGMugJoUKCl/9a6REX02WGn7Ledb84kZ9lLf6dK2dFgxqn+GT5vUnR+xAUg0SZcCfest8Hpj+AEuwrIrmPCI9tYmT1NFogicIqPU1qc/ghC0TgqFZgbnSpbsR7+cAzeEDvj3WhkmXO9tWoVPnh3Oy6PufFrzu9W1IgzoEh7eIlBq8ad62z4/UUe+FLSpVE3numYxO8ujOOXZ0fx41PD+O6xAXzjUB++/FwPPvdUFx47MZjtZa46wzOB2X3+VNSajaizFDBgV4jdF0apUSf7gaE9TRb89xu34oN3ty/6vVLAPriCcp/cGli+RCf6HWirKITFlHttrQ1aNWpKC9A7nd8b6JfG3GivLIRWoZl1y3FwbQV+dnoEZ4acs6358lEwEkP3pDcnn0fXqjVLFewr54VWCb3TvuQBnswfhjBo1dhYXYwLo66M33euk9p27W3O3oGvu9fbsKWuFN86MoA37a7P2jpyjdSquDWHDno1l5vw05dGIIpiTh9syrRxdzBr89clVSUGVrCn4cq4fBvlkg3VxVhjK8LPXhrGW/c2yHrbq1mfPRGwZ72C3VYEbyiKMVdwSfND88WQIwBRBBpkbhEPAJvrSiAIiXD4QHu57LefT84MOVGo18jWpWM+OxrM+OXZUYy6gopu1q8W54ddUKsErKtSpkvegfZy6DQqPHFpHPtastOdajWKx0V0TXjwhp11stzetnozNCoBx/ocOLi2QpbbzAdS69VsXnNLVWwT7iCKDPJWy610Y87EgWOTfunb9q/eXI0vPtuDzzxxBS/fWJmT+7GrwZgrgO31yu4lv2JTJX55dhTH+hy4tTU7xRyr2Q9PDuFDPz6X0vdWlRTwulom7mAErkAkrQp2ANjbZMWTlycQj4spt5an1Mz4workQoIg4P6tNSl9b1WpASphZRVWrvh311hcxKn+GezKwfbwknyvUBNFEZdG3Viv0Aff5XpZWznUKgHPdOTvbKJnrkzins8+jzNDTrx8Y2W2l7OgQr0GZqMWQ478Dj56p7xozmJQ2G4rwpVxDytsbnCkx461lUWwytDucKkEQcC+Zit6Jr2I8ITzrJ7JxPtwm8wh4HK0lBfCG4rOtkSnhGzPgwSSATtnsKckFI2h3+6Xbf66RBAEvHZ7DV4adKJvOr87QaWjf9oHvUaFqiwfUmlLBpGcw76wQUfi37YSAXuxQYvW8sLZ6mtautODTmyuLVGs/avk6hx2jmFKxbkRF9ptRYp1vDHpNbittQxPXJzgZx4ZjTgD8Idjsl03FOjU2FxbguN9rGZLx2zAXpK9z61XA3Z+FrrRqDOw7AOKKpWAv71nDfrtfvzoJLvbKSEWT4xaUPow6e1rKmDUqfE4uxHI7tSAAx/92QXc2mrFz95zC37zl/vxhw8ewPOPHMTRv78TL/3j3bjwz/fi4j/fi1pzAT712w6OXZCJFKDWphuwcw67YuwKBezp0KpVqC4tYMCeSZfH3PCEotidg+3hJc3lJvRO+fL2Q9mUJwS7L6zYyfLlKjFqsbPBjKfyMGAfdQbwF985hXd+4wS0agHf+/M9eN8dbdle1qLqLEYM53EFezASw4gzgOYsVqe124ow449g2svZuJJQNIYT/Y6cqHBZU1mIcCyOATtDKYnUoSPbF4vXksam5PMhvLlkex4kkDiZzoA9Nb1TPsTiouwV7ABw/9ZqCALws9Mjst/2atU37Uej1ZT10/zSv4cuzmFf0IA9cT1bb1Hmmm5rXSnODDnz9nOoHIKRGC6PuRWdvy5ZW1kEk06NUwNsdb0YURRxYcSFTTXK7jHcs8GGEWcAl8bcit5PPrkyntgQl/Ng3u4mK84NuxAIx2S7zdVu3CUF7NnrliFVz4/zmvsmo64gqmU4cHznugpsry/Ffz/ViWCEzw+5TXtDiMREWR6rhRi0ahxcW4HfXxzneFMZjToDePjbL6Gq1IAvvHk7ttWbsaG6BK0VRai3GlFZYoDFpEOhXgOTXoO/vWcNLo258Yuz/GwqB6lwLp0W8cDVOezH2CZedo7k6OBsq7cYV1SL+BUfsB9Pzl/fneMV7P5wbPaEaL65mPwwmqsV7EDiovPymBujedIONhKL46vP9+KuzzyHpzsm8ci9a/DbvzqQtbnR6aozG1fUSSa59dt9EMXE4Z1subpxzhODkjODToSicexrzn7ALj0+V8YZbEi6J7051R4eAFoqEs/hnikehJBEY3FMe0NZbxFfWWKAKxCBP8yZkIuRKpSVCNirSgpwa0sZfnZ6mAFhivqmvWgsk78aOl1mkw5lhXpWsC9iwO6HSadGWaEyGxlb60vh8IVX1AZFrrk46kI0LmYkYNeoVdhYU4ILIxzDtJgRZwAOXxibaksVvZ8719kgCMATFycUvZ98IlWctck4cmFPkwXRuIjTgzyckqpxVxCCAFQU5UAFuyc/90oXIkcFO5DoCPWh+9Ziwh3Ct470L39hdB1pDzkT45BesbEK097wbA5CyxMIx/DQt08iGInh/962E6XGxa/FX7OlGhuqi/Gfv+eBFTlIhXPptoivNRtRay7A0V4+F+Tm8IVhzoGAvc5sxOAK6ly84gP2E/0O1JQW5PRsv9kKtcn83EC/NJoI2NdV527AfsdaGwDg6TyoYj/Z78CrP/ciPvH4ZexrtuIPH3wZ3nuwFTrNynk5qLUUYMQZyNuTm33JMK4lmy3iKxP3zZY8V50bTmyG7syBjiot5YVQCXx8JKIoonvKixaFZ6emq7LYAKNOPdu+noBpbxhxEVlvEV9dyoqaVF0Z90CjEtCkUFeV126rwZAjgJOs6FxULC5iyBHI+vx1SbutEJ18fVvQgN2HeqsJgqBMxwEpFGab+KU7PegEkDiskAn1FiNGnXzvWcz55HX35poSRe+nrFCPnQ1mPHGJAbtcrox7UFNaIOvM7R2NZggCcJzjFVI24Q7CatJndS53gU6NYoMGE7zevo4vFIUrEJFtn3tvsxUH2svxv8/2wBOMyHKblCC9X2cikzi4thwGrYpt4mUgiiIe+fFZXBx147/fuDXlMYIqlYAPv3wtRpwBfOfogMKrXP2GZwIo1GtQakz/emBvsxXH+uxs1y+jWFyE058jFexWI6a9oRXTmWjlJGpzEEURx/sc2JPD1esA0FIuVajl5wbTpTE36iwFKJbxA5TcWspNaLAaV3XA7gtF8ciPzuKPvnQE7kAEX37rDvzf23eizpL9Kqd01ZmNiMRETObpSefe5CxapcKMVJQX6mE2atHJ1q+zxlxBGHVqmJdwcSg3g1aNxjITroyznSWQmCPk9EfQmmMBuyAIiTEynC89S+r2YyvKcgV7cWKThG3iF9c54UVzuUmxg3r3baxEgVaNn77EVnyLGXUGEI7F0WTNlYC9CN0THnYfWMCAw48GBa/F19iKUKBVz4bElL4zQ07UlBagIkPvS9WlBZjwBBGJxTNyfyvV+REXNCpB1jbj87lnfSUuj7nzuoOanDonPFgr8+NWbNBifVUxKzvTMOYKoirLB1qBRBU7Z7Bfb8wlVUXL9/g8cs8aOP0RfPWFPtluk655rDIwasGo0+ALb96Ov7i9RfH7Wu3+99ke/PrcGB65dw3uXGdL62dvayvHbW1l+Pwz3XAFeGBlOYYcftSaC5Z00HhvsxUz/gg6J1lUJBdXIIK4iJwYqyllVUMrZDzwig7Ye6d9sPvC2JXjAXt5kR5Fek3eBuyXR9053R4eSIQcd6ytwKHu6RVzOiZd3zk6gB+dGsbDL2vGH/7mZbh3Q6Vi1TJKm32hXUHtQuTUM+VFZbEBJr0ma2sQBAFttiK2fr3GuDuAymJDzjyv1tiKeAAiqTtZQZlrATuQ6DbACvarrs6DzI0Kdgbsi+uc8CjSHl5i0mtw38ZK/PrcKFvxLaIvBw7gXavNVghfOIaRPBnBlK5YXMSwI4AGBVv6a9QqbKotYQX7MpwZcmakPbykprQAosgOKos5P+LCmsoiGLRqxe/r7vWJzXdWsS9fJBZHz5QX7QocjNjdZMFLgzMIR3k4JRUT7uBsi/Zsqiwx5O04zfmMKFAVvam2BPdtqMQ3DvXBzSp22Yw4AzDp1CguyMze3J3rbDndwXclePLSBP7ziSt4zZZq/MXLlnZY4e/uWwunP4IvPtsj8+ryy9CMf8lFf1Kx7dEezmGXi8OXOOyWEwG7OfE6N2hnwK64Eytg/jqQrFCrKERvHs5Y9YWi6LP7sL5K2dZtcrhzrQ2haByHe6azvRRFnBlyosFqxN+/fB2MuuwFs3KQXmjztYqgd8qX1fnrkjW2InSOszJNMu4KZj0UvFa7rQj9dh8DKeR2wN5cVogRZ2DVHu5K14RUwZ7lDT/p/scYDC7IH45i0OFXNGAHgAe318ATjK7qTkNy6LfnWMBekfh30cVDRHMacyU6DjRYlH28ttWV4tKoG6Eo32fSNeUJYXgmgG0Zag8PXA1URvn+My9RFHFu2IVNCreHlzSWmbDGVoQnLo5n5P5Ws75pHyIxEWsUuG7Y02RBMBLH+RGX7Le9Go25gqgsyd78dUlFkQGTDNivI73+y91h4H13tMITjOLbR9jaWi6jzgCqSpdWgUuZ1znhwV//4DQ2Vpfg03+0ecmP28aaEjywtRrfONQ328WA0iOKidFmtealHRips3AOu9zs3jAAwGrK/rVBPSvYM+d4nwNlhTo058gm0kJaykx5WcHeMe6BKALrc3j+umR3kwUmnRpPrdLN20xuQiitxlwAQVg5L7RyEkURvVPenNg8b7cVwhOK8sR50rgriMocqAKQrKksgiheDZfzWfekF0adGtU5dABC0lKReC73TvNxAhIt4rVqIetznwxaNSwmHcb4+ragrmSXDKUD9ltaymAr1uOnLw0rej8rXe+UDyadGuVF2f9QDCSuEwCgi91u5iSdyG+wKjuuaWtdKcKxOC6NcmxMuqTK/0xWsEsdVEa5YTuv4ZkAXIEINtVm7rPtPRtsONHvgMMXzth9rkZXxhPvB0pcN+xsTBTesE384oKRGFyBCKoy0NZ6MbZiPSY9Ic7RvcaYMwCVIP+B4401Jbh9TTm+9mIf/OGorLedr8ZcQVaUrxAzvjD+7NGTMOo1+Mrbdiy7A87f3LMGogh89slOmVaYX+y+MAKRGOrMS/8ctLfZiuP9Dr5/yGTGn7jGNZuyP/bUYtLBpFNjcIUUVq7sgL3fgZ0NlhVxUqylohBjriB8ofy6iLk0ltjIWQkBu06jwm1t5Xj68uSqq8id9oYw4gxgcwY3IZSk16hhKzLkZYt4uy8MdzCK5vLsV+JKGyPSRkk+i8dFTHpCOVfBDvDxARJjFVrKC3PyeqEl+VzOxy43c5lwBVFRZIBKlf3HqqrEwAr2RUhjQpSegatWCbh/aw2evTIFu5dzOufTb/ehwWrKmde6UqMO5UV6jiuZx0Byw6BewRnsALA1WX3NNvHpOzM0A41KwMYMHlK+WsHOA17zOTecqFDeXFOasfu8Z30l4iLw1GW2iV+OK+MeqFXC7AFTOZUV6tFSbsLxPraLXYw0giLbHaOARIv4aFyEnYdXZo04E+37tWr5t+zfd7AVDl8Y3z8+JPtt56NRZwA1pdl/HtHCIrE43vu9lzDuCuLLb90hy+GiOosRb93XgB+fGubozCWQOtIutUU8kOhc4/CF2S1NJtL7cC5UsAuCgDqLccV0Ll6xAfuoM4DhmUDOt4eXtCTbOUuzEfPFpVE3Sgq0OVk1OJc71lVg3B2cPRiwWkht0jbXlmZ3ITKqsxTkZQW7FMLlQot4KcDt4sY5pn0hRONiTgXsjVYjdGoVL/aRqGDPxfbwQKKVsyAgL7vczGXCE4StOPsX9EAyYOcM3AV1Tnig16gUDwiBRJv4aFzEr86OKn5fK1X/tA9NOXB9cK12WyEr2OcxYPdDqxYUr3yqKilAZbGBAfsSnBlyYm1VZuZ8SwxaNawmHUZ4wGte50dc0KoFtFdm7tpuY00xqkoMnMO+TFcmPGgqM0GvUeY5tbvJipP9M4ixmm1B0vWt3C3Il6KiKLGGCXaNmjXmCij22OxstGBPkwVfeb6Ho2OWKRiJYdobzolOELSw//j9FRzusePfHtyE7fVm2W73fQdbYdJr8O+/7ZDtNvPF8EziOrfOsvTnz95mKwDgaC8P1snB4c2dCnYAyYB9ZXwekiVgFwTh64IgTAqCcOGar1kEQXhSEISu5K/yvYIBONG/MuavS6QKtXzbQL885sb6quKcqaRZzME1FQCApy+vrjbx54ZcEARgwwroJJCqOrMRwyvkJJOcepOvIS1l2Q8LzaZEZdoVbpznVBWARKNWoaWiMO8fH28oijFXMGcDdoNWjZrSAvSwgh1A4rmUK8+jqpICBuyLuDKROLyizkDHgbWVxVhXVYyfnR5R/L5WokgsjqGZAJqsuRWwt1UUoWvSy9Z9cxiw+1BnNmbk+bO1rhSnB52K389qEouLODvkymh7eEl1aQFnsC/g/IgTayuLFQtp5yIIAu5Zb8MLXVMIhBlKLVXnhEeR+euSnQ1meELR2c/MNDcpzM6Fa27pgDoD9qtGnQFFD9+9745WTLhD+MkpXlMvh7QHxBbxue/np0dw34ZK/NGOWllv12zS4S9ub8FTHZM4xpA3LVLB3HJaxNdZjKgpLUg5YLd7QxyhuQC7L4wivSaj19cLqbcYMejwr4gu03JVsH8TwH03fO3DAJ4SRbENwFPJ38vmWJ8DhXoN1lWtjMCw3mqESgB68uiJHIuL6Bh3r5jHCADKi/TYUle66uawnx9xornMhCJDbpxCkkOtxYgxdxDhaDzbS8mo3mkfdBoVasy5cRG/xlbECmlc/XCVC1UA11pjK0RnnreIl953W3JgrMJ8WsoLuRGYNOEO5cRmH5DY8HMFIpxRuIDOcWU3ym/0uu01ODvs4gfjOQw5/IjFRTSW5VbA3m4rgj8cYzXuHAbsftQrPH9dsrW+FIMOP0cspKFnygtvKIqtdbLWCaSkutTAgH0eoiji/LAro/PXJfdsqEQwEsfzXVMZv+/VwB+OYtDhV3SszIaaxN7TxdHV1ZFQbuPJMDsXuq9Jnasm3Hx/AhKvcaMKz/Xe31qGLbUl+NJzPYjG8ms/TU7S+/RK6diar3yhKCY9IcWuG951axMqiw345G87VkQQmCuGHIHEnG29Zlm3s7fZimN9i89hH3cF8cD/HsJbv3aMj9M8HL4wzCZdtpcxq95iRCDZKSTXyRKwi6L4PADHDV++H8Cjyf9+FMADctyX5ESfAzsazBk58S8HvUaNeosxryrU+qZ9CEbiK2L++rXuXFuBs8NOTK+iDahzwy5sWUXt4QGgzlwAUUTebT71TnnRaM1MtVMq2myF6JpgZZp04r4yR4JBSXtlEUZdQbiDkWwvJWukIC5XK9gBKWD35f3zyBuKwhuK5sRmH5AIOICrB2joeq5ABOPuINoVnr9+rddsqYZKAH52ejhj97lS9NsTnzGayjIT2Kaq3ZZ47eWhiOuJoohBhx+NGeo4IFVhnx12ZuT+VoMzyYr/bFWwj8wEuAE4h0GHH+5gFJtqMh+w726yoNigwRMX2SZ+KbomvBDFq2PGlNBSXgidRoWLoy7F7mM1GHcFUaTXoHCZwYYcygv1EISroX++s/vCCEfjioa2giDgvQdbMejw41fnOHppqUZZwb4iSKN6mxU6hGzQqvHBu9txZsiJ314YV+Q+VqPhGT9qZSgc29u8+Bz2GV8Yb/3aMQw5AhhzBfl+M48ZfxiWHArYpfEBK2E8sJIz2G2iKI4BQPLXirm+SRCEhwRBOCkIwsmpqdROAktPnJXSHl7SUl6YVy3ipTnm61dQBTsA3LG2AqIIPHtldZxMn3AHFT2tly3SvNeV8EIrp95pH5pzoD28ZI2tCIFIbHZ+Tr4acwWhVgmwFubG7GiJVFmaz/Nvu6e80KgENGSoSnApmstNCERiGMvzC30pyM6VgyqVxYkLeraJn5v0upLJCvaKYgNuayvHz0+P5v2BlBv1TSeuh5py6BoBSLSIB8BuNzew+8LwhqKz17NK21xbApVwNTSmxZ0ecqLYoFFsQ3YhNaUF8IVjcAfZQeVG54YTwWk2AnatWoU71lbgmSuTPPywBNLYKiUr2LVqFdZWFrGCfRHjriBsOXKgVaNWoaxQj8k8/xwkma2KVji0vWudDWtsRfjfZ3p4Tb1E0mOVK4fDaW5SwN5Urtz13Ot21KLdVoj/+P0VRNgVIiVDDv+y2sNLpDnsx/rmbhPvCUbw9m8cx4DDjw/dtwbA1WtJup7dG4Y1hwL22dxnBYwHVjJgT4koil8RRXGnKIo7y8vLU/qZlTZ/XdJcbkLftA+xPLl4uTTqhlYt5HTV4Fw2VBfDVqzH0x2r42T62SEngMTG2moitdQcXAEvtHKJxOIYtPvRrOCFYbrabNw4BxIn7m1F+pzpLCCRKkSujOfP4a4bdU960Vhmglad9UueeUnt6/NpjMxccmkeJHC1gp0B+9ykjfI2W2av8x7cXoMRZwAnB2Yyer+5rn/ah2KDBmZjbo0DKjFqUVGkR+dEfr++3WjAnrh+zdThL6NOgzWVxTid/FxAizsz5MSWulKosnBtJwUr+dapKxXnR1zQqVWKVkEvZFdTolIqnz6DyqVz3AODVqX4waIN1cW4OOrmIYgFjLuDOXOgFUgcrmVFYUKmAnaVSsB7Draga9KLJy6x6nYpxlwBlBXqYNDmxrximpsUsCvZNUqtEvB3961F37QPPzg+qNj9rBaxuIgRZwC1luW/zi00hz0YieHPv3USF0fd+N83b8e7bm2CRiXgHDt6zcnhy60K9trkAYxBe+5fcyu52zwhCEIVACR/lW2o9Yk+B3Qa1YoLDFvKCxGKxvPmg/KlMTfaKoqg0+RuqDEXQRBwx1obnu+cXhXzvc+PuKBWCVhftbKeL4uxFRmgU6vyanNjyOFHNC6iOYdmSUutX6/ke8CeQ1UA16opLYBJp87rAxA9k1605tBzZi4tFYkPe/k+h30ih+ZBAleD/rE8uW5LV+e4ByadGjUZbot4cG0F1CoBz16R7aPFqtA37UNTmQmCkFsHvYDEYa+uyfx9H5rLoCOx2ZfJ7ipb60pxZsjJSrUU+MNRXBl3Y1sW2sMDQFXyfTBf9g3ScX7YhXVV2dtjkEYGnGY3iLRdmfCgraJI8QPJ66tL4ApE8r7D2kLGXcGcud4GEnPYOYM9YdSZubbjr9pcjUarEZ9/ppsHUpZgxBlke/gVoG/ah+oSg+IHIe5YW4FNNSX42ekRRe9nNZj0BBGJibJUsAPAnmYLjvY6rnsdi8TieN/3XsKxPgc+84YtuGu9DQatGu22Ilawz0EUxZwL2A1aNSqK9Csi91HyU8kvAbw9+d9vB/ALuW74eL8DW+tKodesrFNiLclK7nxpE39p1L3i5q9L7lhbAW8oOtstYSU7N+xCW0UhCnQr6/myGJVKQK2lYEW0CpFL71RydlAOVbAXGbSoKS3I6wAXSFQBVOXQJoVEpRLQZivClfH8fHzC0TgGHP6c76RSXqhHkUGDnuRzPF+Nz1aw58aoBYNWDYtJl/et++fTOeFFe2VRxgPdYoMW2+tL8ULXdEbvN5dFYnGcGXJiQxZaJqeizVaIrgkvg91rDNj9EISrJ/MzYVtdKTzBKHqn8/u9JhXnh12Ii8DW+tKs3H8NK9jnFI+LuDDiyuroszW2IhRo1TjDbhBpuzLuyUjngQ3JPSi2iZ9bLC5iyhvKqQp2W7Fh9qBtvht1BqDXqDLSkUitEvAXt7fgwogbz3WujhGZmTTmDOTkHhBdr2/ap2h7eIkgCNjRYMaVcQ8/8yxiyJG4vq2TqaPN3mbrdXPY43ERf/ujs/jD5Ul8/P6NuH9rzez3bqkrwblhFw8V3cAXjiEci+dUwA4k2sSvhNHAsgTsgiB8H8ARAGsEQRgWBOFPAXwKwN2CIHQBuDv5+2XzhqK4OOrG7saV1R4ewOz8tnzYQJ/0BDHtDa24+euSW1ut0GlUeOryyq6OEkUR54adK67bQ6rqLcYVcZJJLr3TiYuFbMyCXEibrTCvW7+KopioYM+hTYprrbEV5e0BiH57YixLrgfsgiCgubwwbw7gzWfCFUSRQQOjTpPtpcyqKjGwgn0enRMetFdkp0XvgbZyXBh1we5ltROQGAfkDUVxW2tZtpcyp3ZbEQKRGEb4XJo1YPejqlj5apprSWExg8HFSa30t9SWZuX+ywr10KoFjDgZOF1rwOGHJxTNyvx1iUatwqbaEo5bSNOML4xJTwhrKpW/Jl9XWQyVAFwaZYXaXKa9IcTiYk51X7MVG+DwhRGKxrK9lKwbcwVRU1qQsQOsr91Wi+oSA77wTHdG7m+1EEURo84AK9hznCiK6J3yoilDe6hrK4vgC8fYQWURUqFcnVme58++5Bz2o712iKKI/++XF/GLM6N45N41eOvehuu+d1NNKVyBSF5lCalweMMAkJsBuyP3n0+yBOyiKL5JFMUqURS1oijWiqL4NVEU7aIo3imKYlvyV1lKgV8amEEsLq64+etA4h9pqVGbFxvol5KnhVdqBbtRp8EtLVY8tcLnsA/PBDDjj2BzljaHlFZvMa6IWRxyGHEG8N1jg6guMaDUmFtveGtsReiZ9CIaW/kjFZbCE4rCH47lVBXAtdori2D3hTGdh0FUd/IEa64H7ADQUm6a7VKRr3JtHiSQDNg5g/0m094Q7L4w2iuzFLC3l0MUgRe7WcUOJP4eBAG4pSVXA/bEa3C+Hvaay4Ddh/oMtocHgNbyQhTpNTgzNJPR+12Jzgw6UW8xwlqYnY4qKpWAqpICVrDfQJqZuammNKvr2FZXisujboaBaZDGia2pVH5/qECnRnN5ISvY5yFd11bl0DW3dP0/yTbxGMlwaKvTqPDQgWac6J/BsTlmGNPc3IEofOEYqksYsOeyGX8E7mAUTWWZ2Q9amywyvDzO95+FSBXJcr3W1ZoLZuew/+cTV/DtowN4+GXNeM/tLTd9r1SAyDbx17P7Eu+/1sLcyhtqLUaMugI5P8J5ZQ3HBnCi3wGVAGxvMGd7KWkTBAEt5YXomVz9AfvlscQHqHUrtIIdAA6uqcCA3b+iA9zzI4k3jNVcwe4ORuHyR7K9FEUN2H14w5eOwOEL43Nv3p7t5dykzVaEcCyO/hX8XFmOCVduzY2+0ZpkK8bOPGwTLwXsuTRWYT4t5YUYdwfhDUWzvZSsGXeHcu55VFVSwIB9DtLryZoMtHqdy8aaEpQatXi+kwE7ALzYNY3NNSUoyUA70aVoTXY66MqDz0CpGnT40WDJ7HuTSiVgc10JZ0en4MyQc3bWdrZUlxoYsN/g/LALeo0KbbbsHpzcWleKcCw+W1RAi5MOWLVn6LHbWF3MgH0e4zn42bUiOR5q0sNr7tEstB1/4+56lBXq8HlWsads1JV4f2YFe27ry3AX0HZbIQQB6BjLv723dAw5ArAV62Xr5CUIAvY0W/DExQl84ZkevGl3PT5839o5O4GsqSyCTqOaPbRJCQ5fooLdnGMFffUWI0Qx98dmrbiA/XifAxtrSlCoz532oeloLjPlxdy7S2Nu1JQWoKQgNzf6UnFrss3mSq6OOjvshFYtYE2WKsyUJs1rWc2tXbonvXjDl4/AH47i+3++Fzty8HCRFLB05WllmjQ3OtcqbyXtyVaMV/Lw8eme9KKmtCCnWo7Pp6U88Tj15kGXm/lM5OCohcoSA1yBCPzh/D34MJfZjfIMtHqdi1olYH9rGV7omsr7+WmeYASnh5zY35ab1esAUFKgha1Yzwr2JG8oimlvGA1lma1gBxLBYMe4B4EwK2/nM+4KYtwdxLYszV+XVJeygv1G50dcWFdVDK06u9tYHLeQvgG7HwatKmOflzZUl2DcHeQomTlIs85zKWCX1jLuyu/HKxyNY8obynhoa9Cq8af7m/FC1zTO8nUtJdL7c3Vp7jyP6GZSh8DGDAXsRp0GTVYTLo/xgNdChmb8qDPL+zloX7MV0biIV22uwr8+sHHeMRtatQrrq4pZwX4DKWC3mrLTvWs+9Ssk91lRAXsoGsPpISd2rcD565KWikJMeUJwBVZ3xe2lUdeKbQ8vaSk3obLYgEMrOGA/P+zC2spi6DWZm++YSSvlhXapLo268cdfPoJYHPjBQ/uwMYvzBhfSWpE4pZmPAS5wtc1eLm1SXKu8UA+zUZuXwUb3pHdFtIcHEu85APK2TXwsLmLKG8q5gyrSpsk4q9ivc2XCi1KjFuVZap8MJNrET3pC6MjD7hzXOtrrQCwuYn9rebaXsqB2WxG6JvL3ANG1BuyJ1/lMV7ADwNY6M2JxERc4m3heUgv9bFew15QWYNwdzNsRTDeKx0VcGHHlRGe2qpIC2Ir1DNjTMDITQK3ZmLG50huSe1GsYr/ZmCsIrVqAJYeq1GxFiettKfzPVxPuIEQx8fqfaW/ZW49ig4az2FM0mvxsyAr23NY37YNGJaBWplnfqVhbVYQOtohf0MhMYLZgTi6v3VaDL71lOz7zhq1Qqxa+1thSW4ILIy7E4vl9UP9aUsBuybEW8XWWxHM313OfFRWwnx92IRyNr+yAPQ8q1PzhKHqnfVi/gtvDA4kWI/vbynCoZxrxFfiiG4+LOJ8jmxBKWc0V7GeHnHjTV49Cp1Hhhw/vzekuBAU6NeotxrzdOJdaxOda5a1EEAS024pwJc9CqHhcRO/0ygnY661GqFUCelbx9cFCxlwBxOJizh1UqSxOXNCzTfz1Oic8aLcVZWyjfC63JSu2X+iaytoacsGh7mkUaNXY3lCa7aUsqK2iCN2T3hV5TS03afxUQ4ZnsANXQ+MzbBM/r9ODTujUqqwfFq8uLUBcBCY8+V3RKemd9sEXjuXMgeOtdaUM2NMw4gxkNDRcz4B9XhPuICqKDFAtEkBkUqlRC51GlfcB+0iyKroqC1XRRQYt3nFrE564NJGXB/PTNeoMQKsWsnrYmBbXb/eh3mLMaOebtZXFGHD44cvj0X8LicTiGHMFUCfzoQeNWoX7NlZBp1n8sd5UWwpfOLaqs7l0OXxh6DQqmHS5VaBpKzJAp1ZhaCa3c58VFbAf63MAAHY15l6L5FTlQ4XalXEPRBFZ35SQw/7WMjj9EVxage1d+u0+eILRVR2wF+o1sJh0qy5gP9HvwJ/83zEUF2jww4f3obk89wPCdltR3lawj7uDMBu1ss0PUsKayiJ0TnjzqpXyiDOAYCS+YgJ2vSZxUCVfA3apW8zOHLvGkyrYGbBfJYoiOsc9WZu/LqkqKUC7rTDv57C/0DWF3U2WnO9W1G4rRCASw/AMW14PJK9b67MQsJcX6dFcbsIfLk9k/L5XitNDTqyrzn4HMKkqjm3iEy6MJLou5Mpn2611ZgzY/bMVP7Sw4Rk/ajJYQVhq1KGmtAAX2a3jJmOuzM/4XowgCLAV6/M+YB/L8lzvt+1rAAA83TGZlftfSUadAdiKc+ugCt2sd8qHpgy1h5esrSyCKIIHVeYx6gwgLgK1Mlewp2NL8lqSbeKvsvvCsJp0WS2gmItKJaDWUoChHM99VkzAPukJ4uenR9BaUQjrCj4hVmcxQrPKK9SkMHqlV7ADwC2tVgArcw77+eQmxKaa0uwuRGF1FmPOv9Cm43D3NN72teOoKNLjhw/vk71tjlLabYXom/YhFM2/mZ7jriAqS3K7NVi7rQjeUHS2lVk+6J5MvM+ulIAdAJrLTOiZXL0H8BbyTMcUKosNWQ9tbyR1phhjwDFr3B2EJxRFew50VjnQVo7j/Y68nSc95gqgZ8o3W82fy9qSz21uNiVaxFtMOhQbtFm5/9dtr8WxPgf6pvPz/WYh0Vgc54dd2Jbl9vAAUJM84MWAPeHcsAsGrQqtOXLwWOoGwXnFi/OHo5jxRzLaohdItIm/xAr2m0y4Q7DlWMAOAJXFBoznecA+6ky2Hc/S3kJZoR5lhXpWdaZgzBlke/gcF4+L6LdnPmBfl8xCLo/xM89chhyJ69pMXxNcq7m8EEadGueGnVlbQ66Z8YVhzqHRMdeqMxtzvrByRQTsl8fceODzhzA8E8BHXrEu28tZFq1ahQbr6q5QuzTqRpFBk9UXS7lUFCU2+1fiHPZzwy7oNSq023JjE0Ip9Zbcf6FN1TMdk3jHN0+g3mLEYw/vQ1WOh7bXarcVIRYX83KzdtwdRGVxbh/8kkYMdOZRm/jZgD1HNmJT0VJRiD67L+9mQUVicRzqnsbBteU5d2LWoFXDYtJhLM83/K4ljZtoz4HDK7e1lyMcjeNYnz3bS8mKF7oS16f7V0TAnvj30jmZP+9D8xmw+1GfxQOUr99RC7VKwGMnhrK2hlzVOeFFIBLL+vx1ALOfA6TAJd+dH3FifVUxNBls87qQzbUlUAmJjge0sJFk55JMz5XeUF2CPruPbXqvIYpi4nB4Do42qyg2YNKd3yMxRp0BmI1aFGSxRW9LuQk9q7jjqlwyPfaC0jfuDiIYiaMxwwF7rbkAhXoN57DPQ2r1XWfO3mchtUrAxpoSnBthBbvE7gvDmmPz1yX1FuPswYxclRufThbwh0sTeN0XDyMuAj969z4cXFuR7SUtW0t54apuEX9pzI31VcU5t0m+VLe2luF4nwPByMqqjjo37MSG6tzZhFBKvaUAI84AorF4tpeyLB3jbjz07ZNotxXiBw/tRXlRbge2N5IC3Hyb8w1IFey5t0lxrfaK5OOTR5WD3ZNeWE06mE25eZE4l5ZyE8LR+OxGZL44NTADTyiKl7Xn5jVeVYmBFezXkCqQ23Og28CeJgv0GlXetol/sWsa5UX6nOv8MJdigxaVxQZ0T6zeQ8apGrD7szJ/XVJRbMAdayvw41PDiKzw62e5STO1t9WXZnUdAGDSa1Bq1LKCHUAsLuLiqBuba0uzvZRZJr0G7bYinB6cyfZScp40GiQbFeyimCjYoQR3IIpAJJZzLeKBqxXs+TTS7EajzkDWq6JbKgpZwb6IWFzEhDuYk88jukoq/mnOcMAuCALWVhahgxXscxpy+KFWCVl//myuKcGlUTc/CyU5fGFYcnTvtN5ihCsQgcsfyfZS5pWzyZsoivi/F3rx598+iZbyQvzifbdiY01uzNtarubyQvTbfSs+EJxLLC6iY8yzKuavS/a3WRGKxvHSwMr58ByLi7gwklubEEqptxgRi4srfj7uT18aAQA8+s7dKyoQlDSVmaBWCejKs43zUDQGuy+MyuLcPr1cYkwEG3lVwT7lRUsOVNimoyVZbb+au9zM5Zkrk9CqBdyaHMuSa6pKDCv+PUZOV8a9qCjS58R7lUGrxu4mC57vmsr2UjIuHhdxqHsa+1vLVsyh1jZbYd5XsIeiMYy6AmiwZnaz70Zv3FWHaW8IT13mnNVrnRmagcWky2qHgWtVlxQwYAfQO+WFPxzDphzbD9pWX4qzQ07E86zzULqGnVLAntnn1YaaxJ7UBVaozZJasNtysILdVqyHPxyDN487Dow6g1nvYthcZsKMPwKHL/z/s3fW0XFd59p/zrCGBTMaMbMsM2OcxA423EADhbRN2rS96S3DveWvbdpb5pTDzJwmMaNsy5bFPNKMpJGGGc73x2hkxxFrRof2b62s1VoDrz2ac/be7/s8D6N1sJlRdxCRGM34MARhZhIN9hLD0q+5q3M0aLG6BD0wNB1mux+5egXjYsCGAj2CkRiJL5uAzQ32RHRuwv2AjbCywR6KxPD1Z07jBy+34PJ6E5749EZWLgAXSplBhXCUxgAPFWp9Y174w1Fe5K8nWFeSCYmI4lQOe9do3N6wIZ9dhxCpIHGh5bJNPE3TeLnJgi3lWchUc0u5nkAuEaMkSyUohTSASRs7k479n1ulSSOYz4emaXSOeDiVvw7EB/AA4TXY32sbxZqiDGgYyiOejRxdGmmwn0fHiHvStYQNbKswoHPEI7gmVKvVjTFvCJvL2W8Pn6AyW4POEY+gm1Fmux80DRQx3MDdXmmASavAY0f7Ga2DbZzod2B5vo41Qyu5+rhTl9A5O6FATjRM2cKKAj1cgQh6xvjrTpgMzHYfZGIRDEu8zzVpFchQydBMctgnSTTY2ei+ljjzHRZwLNOQ0488PbOfTWJAXWj70fmQuC/nMvxZEWamx+ZFmlSMbM3Sf041OVq4AxGyhpuCAbuPUXv4BA0TQ5tNZjKEF4zEh9sy2JrBnhEfZhpgcd+HdQ12hy+EO/92GI8dHcB9F5Xjt7euYjR/JhVMLlhG+LdgSWx++aRgV8slWFmo51SD/dSEvaEQGuyFPGiwN5mdGHT4ccWyHKZLWRSV2WrBTf+xWQVwIVXZanSMeASR723zhOD0hzmVvw4AGSoZ0pVSQeXeDTn8aLW6cVG1gelSpsWkU8DpD8MXEq6iJkEsRqN92I0KI4sa7JXx3529AlOx7+uM/323cKrBrkYgHGP19Hmq6R+L/92ZtIgHAIlYhJvW5OO99lHBDadMhzsQRueoBysK0pkuZZI8vYJ8PohHUElEFEqz2LWuS/yunOx3MFsIyxmcUKuJREs7uEJRFOpytaTBfh5WZ/x6wsYM9nMNdmHmsLsCYbgDEeQwrIpO7J/5eF6dLCzORIOdKNjZTI/Ni+Is1ZLfewCg2hTviRCb+A8yMO5nRYO9KFMJXZqUNNgB2L1x6/UMlmawc0FYyaoGezASw3W/P4DGPgd+cfNyfGl3FSMXwlRTNrEx7Lbxb8FydsgFiYjinGpwNjaXZ+H0oBMOHzdskk4POqGSiVHCskOIVJCjS4NERLH6Qjsbr5y2QCqmsKvWxHQpi6IyW4P+cR/8oSjTpSwZ1glVK9NWbnOhMluDUCSGPgGobDonDgS4eC8qM6gFpRh4rz3eJNxRxc78deCcOsFKVOwYsPsQCMdQZWLPd6syWw2TViG4HPa9HTZUGNWsVKFNR8VEVny7wOJkzidxDy5kuMEOAB9eUwAAeOLYAMOVsIMmsxM0DaxgQf56glx9GlyBCNwB9mYOLgXtwx6UZKkgk7Dq+ArlRjVUMjFOTgy3E6Zm0OFH3hLnryeoy9WhY8SNUIR/8YwLweqMN6/ZOByeaPoLdb1tccT/3kw3bXP1aZBLRILaj86XIQdpsHOBHpt3yfPXEyTc3lqtZMDrfPyhKGyeIPIZWhOcD0VRaMjXocnsYLoUxhnzxtcGmSy1iNcqpEhXSlnd92HVDqVrxAOXP4xHPrke163MZ7qclKFTSpGllqFrhH9NjrMWF8qNasgl/HId2FKeBZoGDnaNMV3KnGgyO1Gfp4OYhwMqFyIWUchPT2P1hXYmaJrGy6ct2FyeBZ2SnfbIc6UqWwOaPtfcFAIJCzs2qgAuJLHIF4LLQOcodxvspQYVugV0oPFO6whydQpUsPizMmnjG0BiEx9XEQLxgR22QFEUtlZkYV+nTRAOHQAQCEdxtHccWyq4o14HMPk9F8J9aDp6x3xQysRLbpU8FQUZSmwpz8KTx8yC+e7MRKJJuiJfz2gd55M4vBf6/adjxM2q+04CsYhCQ76eNNhnwWz3I4+hRlRdrhbhKC3o+875WF0BZKpkrBtWAc5TsLuFeb0bmlBFM20RLxZRKMlSoVtAjmrzZcgRgFougZal8WYEIByNoX/ch+IsZgZa1XIJCjOUaLGSe8/5mCdczAoYjspKsCxPhzarG4GwcERiUzHujYtJM1TM70+noyBDyeqobVatqqRiEZ777GasKc5gupSUU8pThdrZIRev7OETLC/QQyUTc8ImPhyN4azFJQh7+AQFGUpWZ3HMxOlBJ8x27tvDA+cr04SziLQ4A0iTiqFNkzBdyqyUG9WgKKDNyr97z4V0jXigkomRwyFlZ4Iygzpuce/jv1otFIlhf6cNO6qNrMm7nYqEgl3oDQ4A6JgYoKpgWaNja6UBTn9YMBPojX12BMIxTtnDA4BGIUWOToEOAa0TLqR/3IfCDCVrrnk3ry3AoMMvuIiFqTjR70BplopVA6+JBruQMzz9oSj6x32oyGbnIN6KQj1aLC7BH85ORyAcxag7iHyG7GDrJs6mzhKbeABxi3i2Ot+kycTQKiQYFuh6O6GKZoMzntAc1ebLkMNP8tdZjtnuRzRGM+rqWpOjQYuF3HvOZ2Cywc78dQ4AGvL1iMRowX9O5xrs7NkDXQjb+z6sarBXZKtZM8WSasoMKnTb+DUROOoOYsQdRG0O/xrsUrEIG0ozsZ8DDfY2a9wCbRmL1BeppjBDyVkF+8unLZCIKOyqzWa6lEVTnKmETCwSVIPd6grApFOw5qB8JpSy+BStED6fzhEPyoxqTnwuF1KWyL3jYYzMhRzrHYc3FMWOSvbmrwPnFDUWATc4ErRZ3cjTp0EtZ9dQ0dbyLFAUBGMTv7fTBomIwvrSTKZLmTcV2ZrJQQ0h0jfmZTx//Xwurc1GhkqGx48K2yaepmmcHLCzyh4ewKTqV8g57J0jHtA0u5xTzmdFQfxwtnmIZHhOReJ3lykFe3GmCiqZmHw+E1hdQVY7r2VrFYLNYLc4AhCLKBg1zCsIywwq9I/7EIyQwaGpsDgDrBiEIExPz8RZSglDFvFAPIe91+YVVITmbJgnFMhsyGAHMClMFHoOOxcU7IUZSpjtPta6rrGqwS4kygxqjHtDk7/EfCAx8cNHBTsQz2HvHfOxemIGiCuiAWC5gBTshRlKOHxhOP3cUnzSNI1XJuzh9Up2Zp3MB4lYhFKDCm0CaOAmsDoDyNaydxFyIZXZGkF8Pp0jHpQb2Kl0mo2yCQvlLgE0oN5tH4VUTGEzy1W4CqkYGSoZLC5hKmrOp33YPRk3wSbSVTI05OkEo8Ld12HDqsJ01g06zIVKoxqdIx7Wbo5TSTRGY2Dcj+JM5g77LkQuEeP6lXl48+wwRt3CbGoA8QM/myeElQV6pkt5HwaNHBIRJegGe2IwtJKlCvbE78yJfgejdbCVhPsCU3mrIhGFmhwtmomCHUA83oytCnYAMOkUsAp0vT3k8MOkVUAiZv6YvsyoRowG+sbYffbJFHEFO2mws5lExAFTGexAXMEeo+MxN4Q4A+M+yCUiGFgwSAQAOToFstRy0mD3hiCiAH0aixXs6UqEo/RkTCvbYP7OLVASCjU+5awmNi18VLADmMy5PNDFbnVUk9kJrSKuVBUKib8r24cfLuTMoAsD435cyQN7+ARVJg06hvlzXZsNK8eml6uyNeixeXk9je4OhGF1BSYb1VyjID0NUjHFO5ebqXindQTrSjKg4kCTMEenELyCPRyNoXvUy1oV4dYKA04MOOAKcGvYbr7YvSGcGXJyLn89QWW2BsFIjHNrtmRgdQUQisZQyCIFOwDcsq4AkRiNZxrNTJfCGJP56wXpzBZyAWIRBZNOgSEHOw+TloL2ETekYgpFLBpMOR+jVoFcnYLksE/D4IRaLY+hBjsQt4lvsbgQE+Bg1/kEwlGMe0OsVrAbNQqMsPTwPNUMOvysiTfj43l1sgiEoxjzhpBHLOJZTY/NC71SinQVc0KmalO8NyJ0+/HzGRj3Iz89jTVOkxRFoSFfJ5iYuekY84aQrpRBJGLH5zIVib4PW92LSYOdIUoN8Q0iX3JtBsZ9eHBvN6pNGl4ocaeiwqiGQSPHvs4xpkuZkSazAw35etbcsJaCAo422Cft4eu4bw+foDJbg0GHH26eNzgAIBajMeIOTNpHc4FKkwbRGD050ctHuib+buUcbbBLxCIUZap4r2A3233oGPHgoioj06XMiRydQvAZ7H1jXoSiMVSZ2Pnd2lZpQDRG4wAH4nwWw4GuMdA0WO/8MB2JHGUhxJVcSN9Y/P5UlMGuRmG5UYM1Rel4/OgAaFqYDajmIRekYoqVDh25+jRBZ7B3DHtQmqWGlAWqzulYUagnDfZpMNv98UERBvdLdbk6eENR9I7xd/8zF0YmrNezWdLEnQqTTo4Rd1CQwxAWZ4A1quiErXYXj88MFkpiP8glkYUQ6bF5GXeMKsxQQikTo8UivD3PdAzYfchniT18goZ8HTpHPfAGI0yXwhjjnhCjwyhzgTTYCVOSnx7PKuZDk8PpD+Ojfz+CSIzG7z6yiulyUgZFUdhSnoUDnTbWLvgD4SjarO7JHBGhkFACsfVCOxUJe/hNPLGHT5BQNgohX3XMG0I4SsPEIYv4qonPh8+Njc6J3z2uNtiBeO4dXwbwpuPdtriV944qduevJ8jRpQm+wd5mjf9OVhjZ14ACgJWFeqjlEuzp4HeDfV/nKDQKCWejgCoEtE64kP4Jq1U2ZbAnuGVdIbptXhzpGWe6FEboHPGgOFMFmYR9xyN5+jTBW8RXsnDw4XxWFqTDbPcLOmZhOgZZYHudiDAUuk18wnqdLSrpqcjWKhCJ0RjjUZTmXIjFaFicfuSwRBWtkkuQo1PwfuB7ISTux2wZhiBMTY/Ny6g9PBCPKKkyadBqFfa953wGxn0oyGDXd6chXweaBs4MCtcmftwXQgbLG+w5egVEFGBmad+HfTtIgSAWUSjJ4v4BeigSw70PHUf/uA9/vH31pJUQX9lSnoUxbwitVnY2p1qtbkRitOAa7FqFFHqllFMN9uYhF/rHfbhymYnpUpLKZAOXpd+RZJLIfjFxaHq5JEsFiYhCG48/n84RT9xKlMMxGWUGNfrHfQhHY0yXkjLebRtFnj6NM+sGk04Bpz8MX0i4k81tw26IKPYOr0jFImwsy8Se9lHeqnBpmsbeDhs2lmayIqNzIajlEuTp03g96DUdvWM+SMUUK5sbVywzQSOX4LGjA0yXwghdox7WXtty9QpYnQFEWTrgnUq8wQjMdj8qWfrZJFhRqAcAomKfgkG7n1F7eCA+AC4VU4JvsFuc8cYgmy3iE85wbM1YTRU2TxDhKI08FjVtywxqzp9Xp4JzDXb2fo+Ejj8UhcUZmHRiYJJqkxatVjdv96bzwekPwxWIoIBlCvZleXoAEHQO+7g3hEyWN9ilYhFy9Wms7ftw82SGJ1SaNDg54EAows0DdJqm8a3nTuNA1xh+fH0DNpZlMl1SyknYce5nqf1oIjdkWb6e0TqYoDBDydoL7VS8fNoCsYjCrlp+Ndjz09OQJhWjTQAH51ZnosHOnc2VTCJCqUHF68ZGQoXG1eYTAJQa1AhHac7FXsyVYCSKA102XFRt4EycSeIQxSpgFXvHsBvFmSoopGKmS5mWbZUGmO1+9Ni47xA1FX1jPpjtfmzlaP56gnKjGh3Dwju07R/3Ij9dycr7k1ImwTUrc/HKaQucPv7H/JxPMBJF35iXtQ32HF0aIjFakOrohCtRwvmCrdTn6iAWUTg5YGe6FNZhtvuQz3CDXSYRocKoQfOQcA/PgXNNazZbxAu1wT40sb/IZdHgftxRzUsagxcw5ODeGZDQSMSBlBiYb7DX5Gjg8IUnHUSEjNkeP9sqYJkQxqCRI1enQJOQFexe9ivYAXb3fdi3uxcQ16/Kg80TwqtnLEyXsiD+8F4Xnjhmxud3luOG1flMl7MkmHQKlBvV2MfaBrsTWWoZcgW42CvIUHKmGTVpD1+Wyfqck/kiElGoyBbGwbmFAzZ7U1GZreH1AASbVWhzpczA79y7oz12+EJR7KjkRv46AJi08QMvIdvEtw27J2NA2Mr2injkwF6e2sTvnVh/bqngRrTCdFRmx1VRQlPk9o35JvPj2MgtawsRjMTw/KlBpktZUnpsXsRo9rpzJBSNQsxhT6xXK7PZ+dkkSJOJUT0hniCcIxyNweoKIJ8Fqty6XC2ah1yCbhZanAGoZGJo5BKmS5mWhLpeaM2ohCqaLRbxQHzg2xOMCHK4ayaGHH4YNHLIJewdOBY6iUFrNijYa3LiESWtJIcdA+Px6xzbFOwA0JCvnxQsCo1ojIbdx34FOxD/3Rmws3M/RBrsDLK9woCSLBX+caCX6VLmzUtNQ/jpa2340PJc3H9pJdPlLClbyrNwpGccwUiU6VI+wGmzE8vydJxRBCaTwgwlzHY/Jw5rm4dc6Bvz4cplOUyXkhIqjPxu4CYYdgYgFlHIUnMngx2I2/gPjPvhDfLP6prtKrS5Ujphm85XW75320YgE4uwqZw7zjcJBbtQG+yBcBS9Ni/rmxyFmUoUZSqxp32U6VJSwv4OG/L0aShmYYb3fKjL1SEYieFEv3DUnjRNo2/Mx+rPrj5Ph7pcLR49MiCoJlRCJc3WtUMi51WIOewdw27IJCIUZTJ/SD4bKwr0aBpwIsaBvehSYXUGEKPBuEU8EG+wj3tDgmvcns+wK4BsnYLVZ0VZahlEFDDsElZTN3F9Z5tFPAB08nQ/ulCGnH5BCpq4RKLBXsyCtUOVKT6c3kJy2M9TsLPnOpegoUCHvjGf4Fy8gLh1P02DE+K/wkwlRt1B+EPs68eRBjuDiEQU7txYhBP9Dpzi0LTz8T47vvjEKawpSsdPb2xg9QI9FWwuz4I/HMWJfgfTpbwPXyiCjhG3IO3hgXiDPRKjJ7PF2MykPXwdv+zhE1SZ1Bh1B2H3hpguJaVYXQEY1HKIRdy6BlZOLPI7Rvi3We61+VitQpsrujQpjBo5fvVWBz78x4P4/ktn8dyJQXSNenhxcPtO2wjWl2ZAKWOvguZCEpaVFgE2OACgY9iDGH1uCp/NbKsw4GD3GGcjmKYjGqNxoMuGLeVZnF97X1qbDY1cgocO9TFdypIx7g3BE4ygkAWHfTNxy7pCtFhcOC0gm8TOEQ8o6lwzgW0kBryE2GBvH/agzKDmxFp7RYEe7mCEt8ORC8E8oTLKZ4FarT5PBwBoHhRuk8PqDLA6fx0AJGIRstRyDAtsoHXIEUCaVAxdmpTpUiYpM/LbUW2hDDn8k4NvBHbSPepFtlYOFQvcOrQKKfL0aUTBDmBg3Ae1XMKq61yChkQO+6CD0TqYYMwTH2jjgkV8Il5gwM4+92LSYGeYG1fnQyUT458cUbH3j/nwqX8dQ45OgT/fuYbVOZypYn1pBsQiinU57M1DLsRooGFi8yg0EpabbM3jSHC+PTwXbmALIWEhzOecb2DikIKD08tVic/Hyr/PJ6FCY+sh+Xz45S0r8OE1+YjEYnjoUB/+6/GTuPjn76Hhu2/gw386iB+8dBYvNQ0hEuVWE3Fg3IeuUS+2V3LL4lohFSNDJZuMhhAaLZb4gXQ1FxrslQb4QlEc7+OXOrrJ7IArEMEWjuevA4BKLsENq/PxymkrbB5hqNT6JtanRSy2iAeAa1bkQiEV4dEjA0yXsmR0jniQn57G2n2tRiGFRiERZIO9Y9jNeueUBCsL9QCAExwSTqSaQRapcmtytKCo+JmJUOHK3jVbq8CwW1jr7XjTll3uAiatAkqZGF08HMpfKDRNw+IMIEfH/DWNMD29Y15W2MMnqMnRTO6lhcyA3Y/89DRWXecSLJvoozSZhTNgnCAxRMUFt6iCCUckNsYDkwY7w2gUUty4Oh8vNg2xPtvG6QvjY/84gkiMxt8+upa3zcHZ0CqkWJ6vY10Oe+JG0JAv7Aa7eZzdh08Je/greGoPDwiowe5ivwpgKgoylFBIRby08We7Cm0+bCrLwnevqcczn9mM5u/uxmv/tRU/vbEB16/KQygSw78P9eG+R07gjbPDTJc6L95tGwEAXFTNnfz1BDk6hWAV7C1WF9KkYlbnRyfYUJoBiYjCng5+2cTvm8iV31zO/QY7ANy+oQihaAyPHxVGI7d/bKLBzmKLeCC+z7lyWS5eODnIyyiZqegc8aDCqGG6jBnJ06dh0CGshpM7EMaQMzC5r2A7pVlqaBQSksN+Hgk7WDbkSqvkEpRkqtA8JLzDcwCIxWiMuIOc2LtmaxWwCk3B7mSfKpqiKJQZ1Oi2EQV7Aqc/DF8oOuksQ2AnPTYvSrLYcx5Uk6NFt82LQJh9ttZLidnum1Qgsw2dUoriTKUgc9hbLC6IqHNCLDbDZmFlyhvsFEVdRlFUG0VRnRRFfS3V78dF7txUjHCUxqNH+pkuZVrC0Rjuffg4+sd9+OPtq3nRvFgMW8qzcGrAAVeAPfkcTWYHTFoFjBzYNKWCHJ0CYhHFygvt+bwyYQ+/m6f28ED8s9DIJWgf5ve0M1dUABciFlGoMGp4OQDROepBnj4NaTJ2qtAWikQsQrVJiw+vKcD3rqnHc5/djFP/uwsSEYUzHLPxfbdtFAUZaShl0VT5XMnRKQSbwd5qcaPKpOGETa9GIcWqonTe5bDv67ShLlfLmwHXcqMam8oy8cjhfkR5EH0xG71jXlAUWHuwdD43ry2ANxTFWy3cGuBaCNEYjW6bl/XRMrn6NE7EYCWTRJQRVxrsIhGF5fl6nGRZjByTDNr9yNbKIZewY11em6sVrILd5g0iEqORw4G9a45OgSGHHzTN/7UBAIQiMbRa3ay81pUaVETBfh5scuUgTI3DF8K4N8Sqs4ZqkxbRGD3ptihEaJrGwLgfBSyIjJmOhny9IBXsLRYXirNUnDhDzVDJoJKJWdn3SWmDnaIoMYDfAbgcQC2AWymKqk3le3KRMoMa2yoNeOhQ37zzIq3OAH7w0ln4QqlVGLzTOoIDXWP4/jX12FiWmdL34gKby7MQo4FDXWNMlzLJabMTywSqXgfiDag8fRorL7QJEvbwG0v5aw8PxKedK7LVvFRIJ/AEI/AEI5xssAPxw8o2nlrEs/2QPFkopGKUGdScshsLhKPY32XDRVVGVlqDzUaOLk2QDXaaptFqdaEmh30Hf9OxuSwLZy0ueHiiwPUGI2jst/PCHv587thQhEGHH++0jjBdSsrptXlh0ipYa0N+PmuK0pGlluONZv432AfGfQhFYihn+fB4rl4hOIv4jol9BFcs4oF4DnvbsBv+kLBVagnMdj+rGlF1uToMOvxw+EJMl7LkJBTh2RwQY1Rkq+EKRDDsYrfDZ7JosbgQisSwqjCd6VI+QJlBjUGHn1zTJrBMOMnksOi6Rng/PROOC8VsarBP7KFbeXj+NlfGvCH4w1EUZLD3u9OQr4PFGcCIwCJKWqwu1HAgBhCI9xoKMpST33M2kWoF+zoAnTRNd9M0HQLwGIBrUvyenORjm4ox4g7itWbrnJ8Ti9H44hMn8eC+HrzcZElhdcCxPjtkYhGuW5WX0vfhCisL05EmFbMmh90VCKPb5sVyATfYgbhdCJsb7GctLvTy3B4+QZUprpDm6+R54pCCCzZ7U1FlUmPEHYTdy58DpmiMRveoh/WH5MmkJkfDqY3akZ5xBMIx7KjiVv56ApNOMWENyI+m7VwZcQdh94VRbeLGxgsAGgp0oOn48CEfONIzjnCUxtZybn53puPS2mxka+X416E+pktJOa3WuAsEFxCJKFxam41320Z4b2eZUBOVsXw4L1efBrtPWPefNqsHCqmI1WqnC1lZqEc0RuM0x9yFUsWgw498Fn1+dbnxdcxZAarYJ/euHBgOT6w3W6zC+Jwa++0AgFVFemYLmYKEc2m3TbjK2/MZmnCSIRbx7CXReGNTBntxpgoKqYhTwohkk8jMZvOariFfD4A/5wdzwR0IY2Dcj1qONNgBYG1xxsS5Irv2qKlusOcBOD9YzzzxZ4QL2F5pQHGmEv/Y3zPn5/zzYC8OdI1BJhbhxRQ32I/32bEsX8caey+mkUlEWF+awZoc9qaBRP66ntlCGKYgQzl542Yj5+zhs5kuJeVUZmvg8IUx6uHn5DmXDimmImFBxyeb+EG7H8FITDAKdgCoztHC4gxwRonzTtsIZBIRNpZyU4WbOEwRWi7k2YnDgGqONAcBYPnEeogvOWp7O2yQS0RYU8w+ddNikIhFuG1dEfa0j6KXhZPoySIYiaJzxMMZdQAA7KrLhjcUxUEWuXWlgoQNOdvXDgkV8JCActg7RtwoN6oh4kA0SYIVBXoAwMkBO7OFsIBojIbF6UdeOnvUaokGuxBt4odd3Nm7JobRWi382afORGO/Azk6BXJ07PmuJCgzxpuU3aP8XaPNhyFHAFIxhSyVnOlSCNPQY/NCRJ3LamYDYhGFqmwNWgUyNDQVA/b4cEo+ixXsdblaiCgIyiY+4WrKpXOenTVG+EJRHO4ZZ7qU95HqBvtUu6H3yRkpivoURVHHKIo6NjrKr6zE+SASUbhzYzEa+x1zOgzsHPHgx6+2Yme1ER/fUoL9nTaMp0iJGAhHcdrsxJoifh3qLZYt5VnoGvWyIg8vsYlfPrGpFyqFGUqMeUOstISN28NbsaE0A5lq/i/IEw1cruVDzxWri+sK9vjn84f3unCwawwxHuTfdo7GF4dsPyRPJolmTQtHDqDeaxvFhtJMTuQ7TYVJG98QCs0mPnHAySUFe4ZKhvz0NN5skPd1jmJdSQYn7MXnyy3rCiARUXj4MH9V7J0jHkRiNKca7JvKMqGSifHG2bm7q3GRzhEPjBo5dGlSpkuZkdzJBjvz+86lon3YjUojdw78ACBTLUdBRhpOkBx2jLgDCEdpVlnEZ6rlMGkVaB7ix9pgPlicAUhE3GgM6tKkyNOnCaYZ1dhnZ6U9PBBX3lIU0DVKFOxA/B6co0vj1OCX0OixeVGQoYRMkup21/yoNmnRYuGvw+dscEHBrpJLUG5U82ZAfy4kXBW4tEfdWJqJNKkY/2lhV5RZqq84ZgAF5/3/fABD5z+Apuk/0zS9hqbpNQYDv2wP58uNa/KhkonxjwO9Mz4uHI3hi0+chFImxo9vWIYPLc9FNEbj1TOpUbE3DzkRisawijTY38fm8rgCb18H8yr2E/0OlBlUrD8cSjWJPBc2qthbLG702Ly4clku06UsCasK4/mdf3yvm5eLSC6pAKbCpFXg09tLcbRnHLf+5RC2/OQ/+MlrrZN5l1xk0uZVYBbxADhhN9Y35kW3zYsdldxd6yUU7IJrsFtdyNOnQafk1hpjeb4ep3iwQR5xBdA+7Jlcd/KNbK0Cu+tMeOKYmXVWb8kiMQRVm8OdZqFcIsaOaiPePDuMKA+G8Kajc9TDicE8oTXYnf4whl1BVGRz5zuTYEVBOk4OOJgug3EGE2o1FinYgbhCTYgKdqsrAKNGzpnGYLVJM6ms4zMjrgAGHX6sLNQzXcqUKKRi5KenoYso2AHE78HEHp7d9Ni8rLKHT1Cdo8G4N8Rbh8/ZMNv9yFDJoJJLmC5lRpbl6XF60MnLM+ypOGtxQ5cmRQ6HzrUVUjE2l2fh7dYRVn1OqW6wHwVQQVFUCUVRMgC3AHghxe/JWbQKKW5YnY+XTlkw6p7+ovv7d7rQZHbih9ctg1GjQE2OBqUGFV48NTTtcxbDsd6JTCCWTlUyRVW2BllqGd5tZ9Z5gaZpnBxwYEUB+XwSNkBszGEXkj08AKTJxPjcznIc6RnHHhYMoSQbi9MPvVLKWTUhRVH4+uU1OPatS/GrW1ag0qTBn/d049Jf7MGVv96LB/d2Y8TFrSZi54gHmSoZ0lUypktZMgxqOTJVMk402N9ti98rL6o2MlzJwsmecKywCKTBkaDV4uaUbViChnwdzHY/xjh+kJGII9rC0wY7ANyxsQhOfxgvpGgvwzQtFhfkEhGKM9l34DcTu2qzYfOEeGt3TdM0uka40WDP1sghooTTYE8MfFaZ2P/ZXMiKAj0szsDkMK5QGXSwt8HeNeqBP8TPga7pGHYFODUYXp2jQeeIB6FIjOlSUsq5/HX2nuWVGdToGiEKdiA+ZJ3LQit/QhyaptFj87JyvZ1wguOK82CyMdt9KGDZemAqlhfoYPOEMCQQQUWLxYWaHA0oihvDdwkurjHCbPdPRn2xgZQ22GmajgC4D8DrAFoAPEHTdHMq35Pr3LmxGKFoDI8e6Z/y501mB37znw5cuyIXVyzLARBvlFzdkIvDPeMpaYgc77OjOFMJg4b9dlJLiUhE4aqGXLzZPLwoe36bJ4jXFuE+YLb7MeYNsXbqdSlJNNjZomAfdQfx2hkrfvjyWTxypF8w9vAJbl1XiPz0NDzweisvLMjPx+oMctYe/nzSZGJcsyIP//jYOhz6+sX4n6tqIRZR+MHLLdjw/97GPf8+zhlFYeeIB2UcOCRPJhRFoSZHi1aWKzxarS48crgfRZlKVk6UzxWFVIwMlQwWAR2aByNRdI16UM0h5W2Chokc9tMcjyrZ12FDpkqGWg5Zt82X9SUZqDCq8dAhftrEt1hcqDJpIBGzy65yNi6qNkIqpvBGM7ss+JLFsCsITzDCiQa7RCyCSavAoEAy2NuH4wdmFRyziAfO5bAL3SbePKFgz9Ozyw62NleHGA3B2I8nsDi51WCvMmkRidG8tyZv7HdAJhahLpe9a7wygxrdNg/vznPmSzRGw+oKTDrKENjHiDsIXyiKUgP7zhsSzoOtHBBGpIKBcR/yM9i1HpiKyfMDHrjgzUY0RqPN6uaUPXyCi6riop23W0YYruQcKd/l0zT9Ck3TlTRNl9E0/cNUvx/XKTeqsa3SgIcO9SEcff+0ZiAcxRefOIUstRzf/VD9+3529fIc0DTw8unk2sTTNI3jfXZWT1QyyW3rCxGKxvD0cfOCX+NHL7fgnocaF6xISEy9rhB4/joQz+vSKCSMKNhjEzenRw7344tPnMT2B97B2h++hXseOo5/HuxDaZYKX95dveR1MYlMIsL9l1TizKALr57hV4an1eWfVLPyBYNGjo9vKcEL923BW1/cho+sL8JrzVYc6h5jurRZabO60WJxozKb/YfkyaYmR4O2YTciUfYpPKzOAL7y1Clc8au9sDj9+Opl3L8G5ugUglKwJ7KjuZS/nmBZvg4UBU7nsNM0jX2dNmwqz+KMretCoCgKd2wsQpPZiVM8s1amaTquDuDgd0irkGJDaSZeb7ayyoIvWXSMxIfTuNBgB+I28UJRsLcPu6GUiVmV3z1X6nK1kIopwdvEm+1+ZKpkSJOxy+2rPi9+LT4jIJt4mqYx7Axwau9aM+GcxPdBiMY+O+rytJBL2PU9OZ9SgwqBcExQA8ZTMeIOIBqjkUMs4llL90SUARsH+vVKGXJ0CtYLI1JBNEZj0OFndf56gmqTBlIxhQNd7D8DXSx9Y174w1FONthNOgXq87T4Tyt7hsC5NUYvED66qQgj7uAHGlIPvN6GzhEPHrip4QM5mOVGDWpytEm3ie8b82HMG8Kaooykvi5fqMzWYG1xOh450r+gic4RVwAvNsU/s8M9C7uAnxxwQCEVcdK+NdlQFIXCDOWSN9ifODqAFd97A7t/uQffePY03msbRVW2Bt+4ohpP37sJp7+zC0/du0mQQxDXrsxDZbYaP3+zjZUNwIVidQY5lVMzX8qNGnz18mqIqLiLCZvpHPHgIw8egkYhwSe3ljJdzpJTbdIiFImhx8aebDxPMIKfv9GGHT97B8+eGMTHNpdgz1cumnTe4TI5OoWgMthbJ2zsajioYFfLJSgzqNHE4Qn09mEPRtxBbCnPZLqUlHPdyjyoZGL86yC/VOzDriDsvjAnv0MAsKvOhN4xHzpZZMGXLBJ/J0412J3CabBXGNWcHCxSSMWozdWhkeXr51RjtvuQx0I72Dx9GnRpUpwd4u7w3XwZcgbgDUVRysKm03SUZKkgE4sm16F8JBSJoWnQyfoozjJD/B4pdJv4xIAbUbCzl94x9jbYgXjzlgvRfslm2BVAOEqzLjJmKhRSMa5enovHjw7AyvMzn0RcAVdd8nZWZ+N4nx32RThKJxPSYGchOyqNKMpU4p8Heif/7ECXDX/d14M7NxZha4Vhyudd1ZCDxn4HzPbkNRcTjZXVRME+LbetL0SPzYuDC1B5PnS4H5EYjTSpGIe6xhf0/icHHGjI03POdjJVLHWD3ReK4EevtqAoU4Wf3bQc735pB4596xL8+c41+NS2MqwuSmf1RHKqEYso/PeuKnSPevF048KdHthEKBLDmDfIKRXAQlDLJajJ0eJYL3sPCHttXtz2l0MAgEc+uQFFLMzbSjWJidMWFkxDR6IxPHSoDzseeAe/+U8nLqnJxttf3IFvX1ULvVLGdHlJIUeXJqwGu5Wb2dEJGvJ1OGV2clZ9O5m/Ps3an09oFFJctyoPLzYNsWajnAwSB2lcVAcAwKU12QCAN86yRyGQLDpHPNAqJDBwJL4pV58GiyMgCJve9mEPKrK5OZQCAGuK0nHK7EAwwo2YpVQw6PCz8jCdoig05OtYvb9JNs0TUTl1eTqGK5k7ErEIFdlqVuxvUkWLxYVQJMadBjvP7fpnY2giooVksLOXHpsXMomItZ9RdY4WXaMehCL8ER7NhUSEawEHLOIB4P5LKhGjafz6Px1Ml5JSWiwuiEUUZwaNL+TiaiNiNPBe+yjTpQAgDXZWIhJRuHNjMY732dFkdsAdCOPLTzahJEuFr10+vb3q1Q25AICXm5JnE3+szw6NQoIKjn7hloLL63OgV0rxyOH+eT0vEI7i4UN9uLjaiC0VWTi0AAV7MBJF86ALK0j++iSFGUqYx/1Ldvj09HEzHL4w/ufqWty4Oh/FWSpQFPfUFqlkV202lhfo8au3OjiT5z0TI+4AaBq8VrAnWFOUjpMDjg9ElrCBgXEfbvvLIYSjMTx89wbOLgwXS7lRDYmIYnQamqZpvHl2GLt/uQffeu4MSrJUePYzm/Db21ahMJMbG6m5YtIp4PSH4QtFmC5lSWi1ulGZzb3s6ATL8/UYdQdh5ait5b6OUZRmqThpk7wQbt9QhFAkhiePDzBdStI4O3FtruZog92kU2B5gR5vNPMr6geIN9jLjWrOrNvz9AqEojHYvEGmS0kpdm8INk+Q07E/a4vTEYzEcGZQeEo1IL4uHLT7WXvvuqjKiI4RD6vcn1LJmSEXRBQ4F1VSbdKijccW8Ymox1VFemYLmYUstQxahYQ02CcV7Pw/A+Iq3aNelGSqWOt+U5OjRThKC+67lLDFL+HIwH5BhhK3rivEE0cH0MvjdUKLxYUygwoKKTcFgcvydMhSy/F2Kzty2Ll5WiYAblqTD6VMjH8c6MV3XzwLi9OPn394OZQyybTPKcxUYnmBftJyPBk09tmxqjCdtTcoNqCQinHjqny83mzFiHvuB7gvnhrCmDeEj20uwYbSTPSN+eadq9dicSMUjQnSenw6CjKUCEVjGJ7HZ7FQojEaf93Xg+UFeqwhLg/TQlEUvrK7CkPOAB6e5yAKGxmeaNRkC6DBvro4A/5wlHVWVkMOP2578BA8wQj+/Yn1qBJwRIZMIkK5Uc3oZ/Svg3345L+OgaaBP92xGk98eiNWslyNsVAShyp8twxL0GJxczqCpiE/rtY6NcA9K9hQJIbDPePYUpHFdClLRrVJi3XFGXjo0MKil9hIi8U1aUnMVXbVZuOU2QkLz+zJO0c8qDBy5/qWsKVNqOj4Svtw/CCWywr21RPxesf7FuZQx3VsnhCCkRjyWZq3uqsu7szxOg8Hh6bi7JATpQY10mTcOkSvNmkw7ApinEeuNufT2O9Ajk6BHJaqbRNQFIUyo3oy31qoDDn80Cgk0Ci4u57jOz02D4qz2HnfAYCaiT11K48Hh6bijbNWlBpUnBJe3HdROSRiCr94q53pUlJGi8XFWYc1IC5O3lltwHttI6wQhJEGO0vRKqS4cXU+nj85hKeOm/GZHeVzsg66uiEHZwZd6E7CRJTTH0b7iJvYw8+BW9cXIhKj8eSxuVlg0zSNv+3vRVW2BpvKMrGhNL4Jn28O+8mJqdeVRME+SeGE7Uz/WOpt4t9qGUbvmA+f3FrCGfULU2wuz8Lm8kz87p1OeILcVn5anXHlkInnFvEAJgdH2GSjOOIK4CMPHobDG8a/P7Ee9RyyO0wVNTlaxjIKI9EY/rynG2uL0/H6/duwu87E6+uhSRs/BBOCTfyoOwibJ8hZ5S0Q/25IRBQnc9gb++3whaLYXC6cBjsA3LGxCP3jPrzXwQ67t8XC9cMLANg90Yx6i0c28XZvCGPeEKfcb8412Pk16HAh7RM5v1UcbrAbNHIUZSpZtX5eSgYnfkfZqmDPT1eiPk8rmAZ785ALdbncuw9V5/C7GZUQM3GB0iy14FS3FzLkDLDWepwQP5PoH/ehJIu967qSLBVkYhFj5zZM4PCFcKh7HLvrTEyXMi+MWgU+trkEL5waYp3YKBk4fCEMOQOc36PurDbCFYhMxlszCWmws5g7NxYjGqNRm6PF5y+umNNzrmzIAQC8lASb+BP9dtA0iDJ3DpQZ1NhYmolHj8xNcXO4ZxwtFhc+vqUYFEWhxqSFLk067xz2EwMOZGvlrJ96XUomG+xLkMP+4N5u5OnTcBnHFgtM8eXd1Rj3hvDXvT1Ml7IoEgouIVjE5+rTkKtTsGLBAgA2TxC3PXgYw64A/vHxtVhO3DsAADU5GlhdAUZyi988O4xBhx93by2FlKM24vMhoWAXQoM9caBZw2EFu0IqRpVJgyYz9xTs+zttEIsobCzLZLqUJWV3nQlZajkeOtjHdCmLJhCOosfmRW0Od79DQHyfU5ql4lUOe+dEo4A02NlHx7AbGrmE8+vsNUUZON5nB03zw41jPgzaJxrsLMxgT7C71oQT/Y5JZzK+MuYJwuIMoD6XewPJ1ROW9nxsRo24Ahh0+DkjlCkzqjDsCsIdCDNdCmMMOfzEHp7FDDkCCEdplGax14ZcIhahIls9GR8lBN5uGUE0RnOuwQ4A92wrg1ouwc/faGO6lKTTMnFf5bJTIQBsqTBAKqbwDgts4vl/Esphyo1q/Ovj6/D3j62FTDK3jypHl4Z1xRl4KQk28Y19dohFFGlgzJGPbCiE2e7Hnjkobv62rwfpSimuWZEHIG5tsa4kY9457CcHHMQe/gJy9WkQUfF85lRyot+Oo712fHxLCWezaZeaFQV67K7Lxl/2dnPa6m3YFYBcIuK03et8WFOcgWN944wfENq9Idz+4GGY7T78/aNrJ+03CecOoJiYrv37/l4UZKThkprsJX9vJsiecK6w8LzBAZw70OSygh0AGvL1aDI7GL+GzZe9HTYsz9dBKzArSplEhFvXFeA/bSMpX8ulmjarGzEanFcHUBSFS+uycbBrDE4/Pw7XO0e412DXKiRQyyWT6mC+0mZ1ozxbzXk3nDXF6RjzhgST830+Znv82s3qBnt9/LCfT4NDU9E8FN8bcFHBbtDIkaWW8VLBfi5/nRtipjJD/F4pZJt4izOAHJa6chCAblt8XVdiYG+DHZhwHrTyb2hoOl5vtsKkVaCBg66TOqUU92wvw1stI7yL/EncV2s5vkdVyyXYUJrJihx20hViOdsqDZOHuXPl6uU5aB/2oG2RF+1jfXbU5Gigkk+f+044x65aE7LUslkzpvvHfHizZRgfWV8EhfRcDtZ8c9jHvSH0jfl4m3O7UGQSEXJ0aSlXsD+4twcahQQ3ry1I6fvwjS/tqoIvFMEf3u1kupQFY3UFYdIpOH/wN1fWFKdj2BWE2c7cga7TF8btfz2MbpsXD965FutLhaXonI1E86ZliTdrZwadONI7jrs2FkMsEsb3QSEVI0Mlg4XniicAaLG6kK2VI0MlY7qURbE8XwdXIILeJYiOSRZOXxhNZge2VBiYLoURbltfCBFFzbqmZjuJoSeuN9iB+D4nEqPxbhvzBxjJoGPYA4VUxFoL66mgKAq5egX/FewjHlQaua2oAc6LWWKJC9RSMujwQ6uQsHpArMKoRnGmEm/w3CY+0WCv5WCDHYgPEfOxGdXY74BMLOLM4EOiwS5Um3h/KIpxb4hTawahkRhmK2Gxgh2IK4YTMWx8xx+KYk/HKHbVZUPE0bOij20uRpZahp++1sa5Yf2ZaLG4kKmSwaCRM13KotlZbUTniAd9Y8wOgJEGOw+5fFkORBTw4qmFq9gj0RhODjiwmjRv54xMIsJNawrwn9aRSQvpqfjnwV6IKQp3bCx635/PN4f91IADAIiCfQoKM5QpbbAPjPvw6hkLbltfCDUZQJkXFdkaXLcyH/882Dfj94TNWJ1+QeSvJ1g9cUDIpE38d15sRsewB3++YzW2VAgrj3guxBUe8iVXsP99fy+UMjFuWiOsQaMcnUIQCvYWi3vSHYHLNOTrAYBTOewHu22I0cBWgV7vcnRpuKzehH8c6EHHMHcP1lssLqhk4sn4Ii6zskCPLLUcbzTzQ+3ZOepBmUHNuQO/HF0ahhz8HfCyeYIY94ZQkc0dZ4HpKDOooUuT4rgAc9jNdj/y0tl93aMoCrvrTLxy5piK5iEn8vRp0Cu5OSxZbdKgfdiN6BxiGLlEY58ddXlayCXi2R/MAgozlBCLKMEq2Icmzq2IRTx76bF5oZFLkMnywfDE0C0foy8u5L32UQTCMU7awydQyiS476JyHO4Zx94OG9PlJI0Wixs1OVpeiMZ2VhsBAP9hWMVOGuw8JEstx6ayLLzUNLTgCZtWqxu+UJQzlkVs4da1hYjGaDx+dGDKn3uCETxxdABXNuR8wJlgvjnsJ/rtEFHAMg5araSaeIM9dc2Pv+3vgYii8NFNxSl7Dz7zX5dUgKZp/PptbqrYra4ATBzPhZwP1SYt1HIJjjFkizTuDeHlpvhAy44qIyM1cIGaHM2SWiiOuoN48dQQbliVL5i4hAQ5OgXvM9jD0Rg6R9yo5nh2NABUZquhkIo4lcO+t8MGlUws6CHK/726FiqZBJ979AQC4SjT5SyIFosbVSYN55q4UyESUbi0Nhvvto1w9vM4n64RD6fs4RPk6tN4rWBvnxioqczm/r1HJKKwpigdR3lmKzoXBu1+5LPYHj7Brrq4MwcbsjtTxdkhF+rzuDssWWXSIBCOMa5MSyahSAxNg06s4pCYSSYRoShDKVgFu2VisC1Hx/7rmlDpsXlRYlCxvmGYsOQ+OcD/4bs3mq3QpUmxroTb0Y63ri9Enj4ND7zODxV7JBpD27AbNTw45wGAokwVyo1q0mAnpIarl+egd8yHM4MLO2xPKBXXFHP7QrjUFGYqsa3SgMePDiASjX3g508dG4A7GMHHNpd84GfzzWE/MeBAZTax8J+KwkwlbJ4gfKFI0l/b6Qvj8aMDuHp5LllgL5CCDCVuW1eIJ44NcC6XkKZpDDuDgmqwi0UUVhbqcYwhBc4zjWaEojHcsk5YKun5UpOjRfuwZ8p7Typ49Eg/QtEYPrq5eEnej03k6NJ432DvHvUiHKVRwwMFu0QsQl2ujlMK9v2dNmwozYRULNytmlGjwM9uWo5Wqxs/ea2V6XLmDU3TaLG6eGEPn2BXXTa8oSgOds1tr8JWvMEIBh1+lBu412DP0ysw5g3xYshhKjqG482bKhM/Dv1WF6eje9SLcW+I6VKWDJqmMejwc8JKeWWBHkaNHK/z1CbeE4yg2+ZFXS53BRmTak8e2cS3WFwIRWKcarADQKlBLdgGe2KwjQvXNaHSPeplvT08AKSrZKjN0WJfJ3/U0FMRjsbwVsswLqnJ5vx+Vi4R4/5LK3F60InXznB/vdBj8yIUifFqj3pxtRGHusfgCSa/BzRXuP1bTpiW3XUmSMUUXmxamE38sT47TFoFcgXUREoWt60rhMUZwDtto+/781iMxj8O9GJVoX5aRdJcc9hjMRqnBhwkf30aCiasOAdSoGJ/5Eg/fKEo7t76wSEJwty5b2cFZGIR/u/NdqZLmRfj3hBC0ZigLOKBuE1827AbrsDSWijSNI3Hjg5gRYGeF1bVqaQmR4NQJIbuJRhaCUVi+PehPmyvNExm8gkJk04Bpz+ckiEutpBwQ+DLxqshX4czg64lG0BZDAPjPvSO+UgcBoCLqo346KZi/H1/L+cUhma7H+5AhDffIQDYVJYJlUyMN85y+3ApYXHLRRvy3InDfb4OebUPu6FVSGDkQSYkAKwpiosVmIxZWmqc/jA8wQgnFOznnDlGeTm0koiO4krO91SUG9UQUUDrEsdgpZLG/vj1YFWRntlC5kmZUYVem493dv1zYcjpB0XhAy6kBHYQCEcx5PRzosEOAFsqsnC8z87rs4RD3WNwBSLYXZfNdClJ4bqVeSg3qvGzN9o4cZ4wE2ct/DrnAeI28eEojX0do7M/OEWQBjtP0Stl2FZhwEunhhBbwAKosc+O1cXprLdXYSMX1xiRrZXjkcN97/vzd9pG0Dvmm1K9nmCuOezdNi9cgQhWCtg6dCYSWZfJzmEPRWL4x4EebC7P5PQkOBswaOT42OZivNQ0hF4OqditrviBptAa7GuKMkDTwIl+x5K+7/E+OzpHPLiVqNdnJTGAsBQ57K+ctmDUHcTHBKheB87l71l52uAA4tbWUjGFUgM3DipmY3m+Hv5wFJ0cUN4kFA1CzV+/kK9dXo1qkwZfevIURtzc+c618PDwQi4RY0e1EW+eHeb0AXvHSFwJyVWLeAC8tYlvH3ajMlvDmzOIhnwdpGIKx3qFYxNvtsd/N7nQYAfiwhR/OMqrbNUEzYPxaBwun1sopGKUGtRo4ZGCvbHfgRydgnNuiGUGNULRGMz25J6xcQGz3Q+DWg6ZhLRQ2Ej/uA80De402MuzEI7SONLD37XB681WpEnF2FZpYLqUpCAWUfjSrkp0jXrx7IlBpstZFIlzHj4JZVYXpUOrkODtFuYG8sndgcdctTwHQ84ATswz28Pi9GPQ4cdqoo5eEFKxCDevKcC77aMYOK/B+7f9PcjRKXBZvWna5841h/3kgAMAsKJQn4ySeUeqGuwvNQ1h2BXE3VtLk/q6QuWuTcUQUxT+dbBv9gezhERDTUgW8UD8WiOigONLfED46JEBqGRiXNWQu6Tvy0XKDGpIxRRaLKk9gKJpGn/f34NSgwrbKvixYZovJi2/FYRAvDlYbtRw3tItQUN+/HC5aYD9Oez7OmzI1sp5teldDAqpGL+5dSU8wQj++4lTCxocZoIWixsUBVTzxOo6wa7abNg8IU5nR3aOeCARUSjK5MZB7Pkk7GkHedhgp2ka7cMeVPAgfz2BQirGsjwdjglIwZ5osOfplQxXMjc2lGZCo5DgDR7axDcPuZClliFby21HiGqTZtJZiQ809tk5Zw8PAGUTQ7dCs4kfdQfx6mkL1pL4VNaScCbiSoN9XUkGZBIR9vFwsAuIO+6+0TyM7ZUGKKRipstJGrvrTGjI1+GXb3UgGOGu603inIdPA0MSsQg7qox4p22EsbMC/vxrEj7AJTXZkEtEePGUZV7PO5e/zr1FH1u4eV0hKACPHe0HALRZ3djfOYY7NhbNeFg91xz2kwN2aOQSTmYHLgXpSinUcsn7BhwWC03T+MveHlQY1djBkyk8psnWKnDFshw8eWwAXgazUubDpIJdYA12tVyCmhztkh4QOv1hvHx6CB9akQeVXLJk78tVZBIRyo2alCvYG/sdOGV24mObiiES8UNhNl8SCnY+N9hbrS7U8KgxWJypgkYhwSmW57DHYjT2d9mwpdzAGwVnMqjI1uDbV9Vib4cNf9vfw3Q5c6LF4kJRhpJ396+Lqo2Qiim80TzMdCkLpnPEg6JMJScHiLK1ClAUPxXso+4gnP4wKjlo3T8Ta4ozcNrs5KUF+VQkhj+4omCXSUTYWW3EWy3DnLd9vZDmIRdqc3WcX09UmzQYGPczmq2aLEZcAQw6/FjJQaFMaVb82tw1wh33wWTw67c7EIjE8MVdlUyXQpiGnglHzGKONNgVUjHWFKXzNof9pNmBEXcQu+v5YQ+fgKIofHl3FQYdfjx6uJ/pchZMi8WFmhz+nPMkuLjGCJsnhKZBZgQV3NtVEuaMRiHFzmojXmqyzMvG73ifHQqpiFeWhktNnj4NF1UZ8fhRM8LRGP6+vwcKqQi3ri2c9blzyWE/0e9AQ4FOsM2N2aAoCgUZyqQq2A90jaHF4sLdW0s4v0llE3dtKoY7GMEzHLHZGXYGIKIAg5rbSoCFsKYoHScHHEt2+PTCyUEEwjFiDz8PapZA4fH3/T3QKCS4flV+St+HzSTy9yw8bHAAwLg3hGFXENU82niJRBQa8nVoMrNbwd485ILDFyb28FPwkfWF2FWbjZ+81oozDG2c50OL1cXLvZRWIcWG0ky83mwFTXPDTeBCOkc9qDBy8/omk4hg1Mh52WBvH46rIit5pGAH4raVoWiME9etZDBo90MpE0OvlDJdypzZXWeC3RfG0V7+OA0EI1G0D7s5nb+eIBGD1cYDm/hz+evcEzOlq2TIVMkEpWDvGvXgkSP9uG1dIXGWYjEVRjU+sr4QWgV37jtbKrLQanVzKv5qrrzebIVERGFnFb8a7EDc3n9jaSZ++04nZ0Ri5zPmCWLEHUQtD/eo2ysNEFHAf1qYGQInDXaec1VDLmyeIA53z6yIPp/jfXYsz9dzcqqfTXxkQyFsniAePzqAZ08M4vpV+UhXyWZ93mw57P5QFK1WN1aQ/PUZKcxIS2qD/c97upGlluGaFXlJe00CsKpQj2V5OvzzQC8nDmotzgAMGjkkArw+ri7OgC8UTbkFORB3jHj0yABqc7RYlsfd3MClpiZHi2FXEOPeUEpe3+L049UzVty8poB3qsz5oJCKkaGSweLi34YYwOSQBt+agw35erRaXay2dNvbOQoA2FxOGuwXQlEUfnJDAzJUMnz+sRPwhdh7qOENRtA35uPddyjBrjoTesd86Bzh3iF7KBJD35iPk/nrCXL1aRhy8O/+0z4cX19W8EzBvnqikcan5u1MmO0+5KencWogfXulATKJCK/zyCa+Y9iDSIzmR4N9YuCTDzbxjf0OyMQizn4uZQa1oBrsP32tFQqJCJ+/uILpUggzcEltNn543TKmy5gXW8vjrqgHOufeq+ECNB23h99Ylgkdhwbt5gpFUfj8xRWweUJ4u5W5vO+FkjjLTQyu8Qm9UoY1RRmMfS7C6xAIjJ3VRihlYrzYNDebeF8oguYhF7GHTwLbK43I06fhuy82IxiJ4WObiuf0vNly2M8MORGN0VhZQD6jmSjMUGJg3JeU/I32YTfeax/FXRuLeZUhwwYoisJHNxWjc8SD/RxYXFpdAZi0wrKHT7Bm4oDwWF/qc9hPDzpx1uLCresKOHVAxzSJZk6qbOIfOtQHmqZx1xzvZ3wmR6fgrYK9lacbr4Y8HcJRekmGhBbKvg4bqk0aGDTCc0mZC+kqGX5x8wr02Lz43otnmS5nWlqtie8Qv5S4CS6tiStS3jjLPZv43jEvojGaBw12/t1/OkbcSFdKeecSlaWWozRLheNLsH5mA4MOP/L03LCHT6CSS7CtIgtvnh3mxMD3XGgeijsm1Odyf1A5T58GjVwyuT7lMo19dtTlaSGXcPNMqdSgmsy75jtHe8fxevMw7tleRtblhKRTm6uFXinFXp7lsHeMeNBj82JXnYnpUlLGupIM6NKk2NM+ynQp8yZxTshHi3gA2FljRPOQC1YGohxJg53npMnEuKzOhOdODM5p0vDUQLx5u5qDlkVsQyyicMvaAoSjNLZWZKFijnZ3s+Wwn+x3AABWcDC3aSkpzFAiGIlh1BNc9Gs9uLcbCqkIt28oSkJlhAu5ankOMlUy/ONAL9OlzIrVGRBc/nqCXH0acnWKJclhf/TIABRSEa5ZSRwj5kNC4ZGKBnsgHMUjh/txSU02CjKUSX99rlGcqcJZi2teETxcocXiQpZaxrvDpIYJ558mluaw+0NRHOu1YwtRr8/IprIs3Lu9DI8dHcArp+c2QLzUnDu84NeQSgKTToHlBXpOqj0TqnsuN9jz9GkYdPh50whM0D7sQUW2hpeDlauL0nG8z56UwW+2M+jwI48j+evns6vOhEGHH2cGua+SBuKRM2q5BIU8WLNTFIXqnNTHYKWaUCSGpkEnVhVy96y1zKDGmDcEe4rc0tgCTdP40SstyNbKcffWUqbLIfAQsYjC5rIs7O+08Wo99/qZ+N5gVy3/7OETiEUUtlZk4b32Uc59di1WF4waOTJ5NsyaYGe1EQDwTtvSq9hJg10AfPXyaiikInz+0ROz2mJOZgJxeNHHJm5eV4AKoxqf2zk/S6GZcthPDNiRn56GLJ5eEJNFogG0WJv4EVcAz50Ywo2r52bxT5g/cokYt64rxNutwxhIoq1/KhCygh2I28Qf77WndCHpDUbwwslBXLksl1M5WmwgSy2HQSNPiUL3+ZODsPvC+NjmkqS/Nhe5fJkJw64gDs0jgocrtFrdvFOvA0CuToEstQynBtiZg3u0dxyhaAxbSP76rNx/aSWWF+jxtaebMMhCJW+LxQWNQoJ8DjaZ5srl9SY0mZ3o5phVbOeIBxQFTmep5uoUCEZiKYuDYQKaptFudaOSZ/bwCdYUp8PuC6Pbxq3vy3zxBCNw+MLIT+deU/eSmmyIKHBycGgqzgw6UZujhUjEj4GVapMWrVY355oZ59NicSEUiXH6rLXMqAIA3l/LXj1jxYl+B754aSXSZNx0GyCwny0VWbC6AryKXXj9rBWrCvXI5vmZ6fZKA0bdQVY7401Fi8XN2wFwAKgwqpGfnoa3W0iDnZACsrUKPHDjcjQPufDAa20zPvZ4nx3lRjX0StJITAZGjQJvfnE71pVkzOt5M+Wwn+x3YCWHF+VLRWJau39s4Q3bcDSGzz92AqCAu7eQydVUcvuGIogoCv862Mt0KdPiDUbgDkSQLVAFOxC3ibe6AiltaLzUNARvKIpb1xWk7D34TE2ONukKdpqm8ff9vag2aSbvT0LnkppsaOQSPHtikOlSkkokGkP7sJuX1tYURaEhX4/Tgw6mS5mSfZ02yMQirC/JZLoU1iMVi/DrW1bAE4zg8SP9TJfzAVosLtSYtLxU4ia4fmUexCIKTx03M13KvOgY8SBPn8bpA/PcCfttPuWwW10BuIMRVM7R8Y1rrCmOr52O8TyHfdAe3x9wzSIeADJUMqwrycAbZ+fWYLc4/Xji6AArXQmisXgcTi1Hc76nosqkgTsQwRADtq/JYlLMVKRntpBFkBhO6xrhr018KBLDT15rRWW2GjeuJucRhNSRcC3ji0282e7DmUEXdvPYHj7B9koDAOA9DtnEhyIxdI7wu8FOURQurjZif6cNgfDMAuNkQxrsAuGS2mzcubEID+7rwbvTWCXEYjSO99mxmjRvGWe6HPZhVwBDzgBWTNicEqYnLz0NFLU4BfsPXjqLQ93j+PH1y1CcpUpidYQLMekUuKzehMePDsAXijBdzpRYXfENfY6AG+yJ+JDjKbSJf/TIAMqNahJVskBqTBp0jngQjsaS9poHu8fQanXj45tLeN0wmg8KqRiXLzPh1dMW+ENLu3hPJb1jPgQjMd5uvBrydegc8cAbZN99Zm+HDauL0jnd+FtKijJVKMpUoWOEXaqPWIxGq9XN22y7BEatAtsrDXi60cypqIzOEQ+n7eGBcw12Nro3LJT24fj3uMLIz+9NaZYKGSrZksQsMYnZHt93c9W9Y1etCe3D8fzYmTg75MK1v9uPrzzdhGdYOGjZY/PCH46iPo/7+esJEvfU1hTEYC0Vjf0O5OgUyNFx8/sBAPnpSsjEInTxWMH+yOE+9I358PXLayDmiQMEgZ0UZChRlKnE/k5+NNhfbx4GAEE02I1aBWpytHivfemV0gula9SDcJTm/R51Z002/OEoDnYtrdMkabALiG9cUYNqkwZfevIURt0fzKXutnng9Iexupg0NZhmuhz2E4n8ddJgnxW5RIwcrWLBluOPHenHPw/24ZNbS3D9qvwkV0eYio9uKoYrEMFzJ4aYLmVKhicm5vludzQT1SYNVDLxnBU4NE3jwb3dON43PvuDAbRaXTg54MAtawtII3eB1ORoEYrG0D2aPGXB3/f3IkMlw4dW5CbtNfnAtSvz4A1F8WbLMNOlJI1EvmU1Tzdey/P1iNFx69TZCISj+NfBXjj94ZTXFbeYcxF7+HlSZlBPZmqzhf5xH3yhKG+HVM7nw2vyMewKYk8HN9Qb0RiN7lEPyjlsDw8ABelKUBRwpGduaysu0DEct9jkq0U8RVFYVZie0gFVNpAY+uBiBjsA7KqLZ8bOZBO/t2MUH/7TQYgoCtUmDX72ehvrBi2bh+JrnDoeKdgT7hatVm7Z8Z5PY5+d0/bwQDx7uDhLyVsFuysQxq/e7sCmskzsqDIwXQ5BAGwpz8Kh7vGkiiOY4vVmK6qyNYIRp22vNOBYrx0eFg7uT0XC5bKW53vUDaUZUMslSx75QxrsAkIhFeM3t66EOxDBfz956gN2VomGCVENsoOpcthPDjggFVO82iylkoIMJVqs7nkvVo71juPbz5/B1oosfPWy6hRVR7iQNUXpqMvV4h8HeliZr5ZQsAs5g10iFmFlYfqcFTjPnRzED15uwS1/PoRnGme3kX3syABkYhEZalkEiaZOolG6WJrMDrzVMoxb1xVAISXK2vPZUJKJHJ0Cz87hd5srtFhcEIsozis8p6MhP67majLP3GCnaRrfeOY0/uf5Zvzw5bMpr+tAV1y5kLAKJMyNcqMavWNeRFh0KJU4vBBCg31ndTYyVDI8eWyA6VLmxKDdj2AkhgqON3F1SiluWp2Pfx3sZd2AyUJpH3YjUyVDplrOdCkpY01xOnps3imFDnxh0O6HTCJCloqbn2N+uhL1edppD2WfPDaAj/39KPLT0/DsZzbje9fUw+oK4MG93Utc6cw0D7kgk4h4tZbTKKQoyEibcwxW16gHV/9mH946y44h2JGJiLWVhXqmS1k0ZQY1ujmUGX2i344R99yiBf74bhfsvjC+fnkNGfYnLAlbyrPgCUZwcsDBdCmLYswTxLHeceyeGFQTAtsrDYjEaBzgiANBiyW+Nijh+QCEXCLGzmoj3jg7vKRnBKTBLjAqsjX49lW12NM+ir/t73nfz4732ZGulKKU5182rjBVDvvJATtqc7SkyTFHdteZ0GJx4fYHD8/5MGPI4cc9DzUiT5+G3966ChIxuUwuFRRF4a5NxWgf9uBg99LaucwFy4SC3SRgi3ggPoTVZnXBHZhZ1TnmCeJ7L57FigI91hRl4ItPnML/vdk+7fBEIBzFM41m7KqLH9gTFkapQQWZWISzSbBQdPhCuPehRuTq0nD3ltIkVMcvRCIK16zIw54OG2wefhyYt1rcKDOoIJfwc52RqZYjT5+GU2bHjI/754FePHNiEKUGFZ44ZsaJ/tSqDvd12KBLk/LKznUpqDCqEY7S6FtEHFCyabG4IKLiebF8RyYR4doVeXjz7DDGvSGmy5mVztG48pEPTaevXFaNNJkY33mhmZVDqfOlfdjD2/z1BGuLUx+zxDRmux/5+jSIOGyrvLvWhBP9Dgy7zjXkaJrGr97qwJefasKG0kw8ec9GmHQKrCvJwO66bPzhva45N/CWguYhJ6qyNZDy7Byj2qSds4L9x6+24vSgE59+6DgrhsDO5a9zX8xUZlCjb9yHUIQ9w43T0WZ147rfH8C2n76DH73SgrEZ9mtDDj/+uq8H167IxbJ8sh4nLA2byrIgouJ7QS7zVsswYjSwSwD28AlWF6VDJRNzJoe9xeJGVbZGED2Oy+tNGPeGcKR36dy++P+vSvgAH1lfiF212fjJa604fZ6C53i/HauL0smkHku4MIc9GqPRZHYSe/h58PEtJfjFzctxyuzAVb/ZO+uBRiAcxaf/fRyBcBR/uXMNdErpElVKSPCh5blIV0rxzwO9TJfyAYZdAWgVEihlEqZLYZQ1xemI0eciK6bj+y+dhScYwU9vbMA/P74ON63Ox6/f7sD9j59EMPJBK8VXz1jgCkRw67rCFFUuDKTiuGKlxbI4C8VYjMb9j5/EiDuA331kFdLJ0MOUXL8qD9EYjRdPsTPaYr60Wt2oNvFbebu8QDejgv1Izzh+8HILLqkx4rnPboZRI8f/PN+cspxpmqaxr9OGzeWZJOtxniQapR3D7FFSnbW4UZKlEsww7E1r8hGO0nj+JPtyiC8k8XtSbuB+IzdLLcd/X1qJfZ22JbdATDaxGI2OYTdv7eET1OfpIJOI5hybxEXMDj9n7eET7K6PNwfemFA+h6MxfO3p0/jFW+24flUe/vbRtdAozp0RfO3yGoQiMfzizQ5G6r0QmqbRPORCfR7/1nLVJg16bF4EwjNb8h/rHcebZ4fxmR1l2FSWiS8/1YQ/7+laoiqnprHfAZlYxAsnynKjGtEYjR4b+23if/9uJ5QyMS6rM+HBvd3Y+tN38MDrrXD4PjgUGBcCAF/aXcVApQSholNKsSxfj30cUUFPx+vNw8jTp/HiGjdXZBIRNpVn4b32UdYPu9I0jRaLi/f56wm2VxmgkIrw2pml2yMtqsFOUdRNFEU1UxQVoyhqzQU/+zpFUZ0URbVRFLV7cWUSkglFUfjpjQ3IUsvx+cdOwBuMYNwbQveoF6uLMpgujzDBhTns7cNu+EJRrOR4btNSc93KfDxz72bIJWLc8ueD+PfB3ilvfjRN42tPN+HMkBO/vHkFKniuomArCqkYt64rxJtnh2G2s0eRBsQV7Dk6bh8aJYOVhekQUZjRJv6dthE8d3IIn9lRjspsDWQSEX56YwO+vLsKz50cwh0PHoH9ArXbo0cGUJihxMbSzFT/FXhPTY4WrYtUsP/+3U680zaK/7mqlgx2zUBltga1OVo8d4L9zaXZcPrDGHT4eZu/nqAhX4/+cd8HrkEAYHH68ZmHj6MwQ4n/u3kFtAopvnllDU4POvFEihRQvWM+WJwBbCoj9vDzpWyiwd7FIqvS+OGFcA6XanK0WJanw5PH2B+V0TniQZZazpsB2ts3FKHapMH3X2phXQb0fOgZ88IbiqKW54eycokYDXk6HO3lr4J90O5Hnp7be6UKoxolWSq80WyFJxjB3f88hsePDeDzO8vx85uWQyZ5/xFqSZYKt28owuNH+9E+zHw++JAzAIcvjNpc/ilwq01aRGP0jNEYNE3jx6+2wqiR476d5XjwrjW4clkOfvRKK378aitjTZDGPjvq8rS8cIhKOPQkK44sVfSNefHiqSF8ZH0hfnnLSrxx/3bsrDbid+90YetP3sEv32qHa8KR7+yQC083mvHRzcXIT1cyXDlBaGwpz8TJAcfk7yPX8AQj2Ndhw+46k+AEm9sqDTDb/awfOBp1BzHmDfFeSJFAKZPgoiojXjtj/UA8dqpYrIL9DIDrAew5/w8piqoFcAuAOgCXAfg9RVHcX0nwCL1Shl/cvAK9Y15854VmNPaR/HU2cn4OeyKThTQ65k9trhYv3rcFWysM+PbzzfjvJ0594CDqL3u78dzJIfz3pZW4pFY4uTFs5PYNRaAoCv8+1Md0Ke9j2BVAtsDt4QFALZeg2qSdVoHjDUbwrWfPoNyoxmcuKpv8c4qi8NmLyvGbW1fipNmB6/9wYHIh2jXqwZGecdy8toDTtpJsoSZHgxF3cEYbvJnY32nD/73ZjmtW5OL2DUVJro5/XL8qD6fMTlY1+RZC24TtJt+bg5M57IPvV7EHI1Hc+1Aj/KEo/nTHamgnFGofWp6LdcUZ+OlrUyteFkvThF09WYPPH7VcghydgjU51IkhFb5/hy7kw2vycdbiwpnB6Z0h2EDnqAcVPLCHTyARi/DdD9Vh0OHHH97tZLqcBZO4Bjbk6xmtYylYXZyO5iHnrApcLhIIR2HzBJHPcQU7RVHYVZeNg11j+PAfD2Jfpw0/vn4ZvriratrGwRcuroBKLsGPXmlZ4mo/SPPEdZiPKsLEAOhMNvFvt4zgWJ8dX7ikAkqZBHKJGL++dSU+sr4Qf3yvC197+vSSZrICQCgSQ9OgE6t4IpQpM6ghEVGT+wa28sf3uiARifDJrfGYs3KjGr+9bRVe+6+t2FSeiV++1YGtP3kHv3unEz96pQVahRSf3VHOcNUEIbKl3IBojMbhbm463LzbNoJQNCao/PUE2ysMAMB6m/hEfKSQ9qiX1Zsw4g5ORrSkmkU12GmabqFpum2KH10D4DGapoM0TfcA6ASwbjHvRUg+G0ozcd9F5XjyuBn/92Y7pGJq8tCRwA7Oz2E/0W9HulKKokwyUbkQdEopHrxzDe6/pBLPnhzE9X84gP6xuEL63bYR/PjVVly5LAefvYgsqpkmV5+GXbXZePzoAKsUOVZnACatnOkyWMGa4nSc6HdMeUDx8zfaMeT04yc3LJtySv/q5bl49JPr4fSHcd3v9+NIzzgePzoAsYjCTavzl6J83pNYOC/EJt7qDODzj55AmUGN/3f9MsFNIS+EDy3PhYgC51XsLYmNF88nm5dN5Jw3TQwuJvjOC804OeDAz25a/j4XG4qi8N1r6uD0h/HzN9qTXk+T2Qm5RMSrxt9SUm5Us6bBnnAOqRXQ4QUAfGh5HmQSEStybqeDpuOqRz7kr5/P+tJMXLMiF3/c042+MXarZ6ajyeyEQiqMa+DaogyEozROXXD/4QODDj8AcN4iHgB21ZoQidHoHfPiwbvW4JZZ4qvSVTJ8bmc53m0bxd4OZg/Zzwy5IKL4uZYrzlRBLhFN69IVjdH4yWutKM1S4cNrCib/XCyi8INr6/H5iyvw+LEBfObhxiUdcmmxuBCKxHjTYJdJRCg1qFjdYLc4/XjquBk3rcmHUft+gUS1SYs/3bEGL31uC1YXpeOB19uwr9OGz+0s543DDYFbrCrSI00qxj6G7x8L5fXmYWSqZFhTLDxH5MJMJUqzVKxvsCfOBYW0R91ZbYRMLMKrS2QTn6oM9jwA5++wzRN/RmAZX7i4AqsK9ThrcaEuVyeYvECucH4O+8kBB1YU6EmzYxGIRBS+cEkF/nbXWgzafbj6t/vw8OE+fO7RE6jM1uCBmxrIvy9L+OimYjh8YdZkeoajMYx6gjARi3gAcaWlLxT9gILgRL8dfz/Qg9vXF80YObK6KAPPfmYTMlQy3P7gYTx6uB8XVxs/sAEmLIzqBVr3haMxfPaRRvjDUfzh9tVQyiSpKI93GLUKbC7PwrMnBpfMgioVtFpd0CulyOb5IJFGIUWpQYVT5+WwP3qkH48eGcC9O8pw+bKcDzynJkeLOzcW4+HDfUlX6Z4edKI2VwuJOFXbMn6TaLCz4bvXIkB1ABAfYt1dZ8JzJ4dYq8wdcQfhDkR412AHgG9cUQOpiML3XjzLdCkLosnsRH2uThDXwIRTyUwxS1zFbI832Plgr7yyQI9vXVmDJ+/ZiIuqjHN6zl2bipGfnoYfvtyCKIP3o7NDTpQa1EiT8e9cTyyiUGXSTKtgf7rRjI4RD768uwrSC64nFEXhi5dW4jtX1+KNs8P46N+PwL1EdswJ9dyqIv2SvN9SUGXSzugkwDR/2dODGA3cs71s2sfU5+nwt4+uxTOf2YQv767CHRuJaxuBGeQSMdaVZGAvB3PYA+Eo3mkdwaW12RAL1IlyW6UBh7rHWLsHAuJ71FydQlBDRBqFFFsrsvDaGeuSxMPMuouhKOotiqLOTPHfNTM9bYo/m/JvQ1HUpyiKOkZR1LHRUXZPfPARiViEX92yEro0KbaUk+xHtpHIYX+3fQQdIx6sKODH1CvTXFRtxEuf24pcfRq++ewZSMUi/OXONaSZxCLWlWSg2qTBPw70MpaVdj4Hu8ZA00ABD1QZySAxnXqs95yNVSgSw9efOY1sjQJfuaxq1tcoylTh2Xs3Y1WRHu5gBLeun1kdQpg7mWo5jBr5pBXUXPl/r7TieJ8dP7mhgZdNiFRy3co8mO1+HF8iC6pU0GJxo9qkEcSg2fJ8PU4POgDEB4P+9/lmbK3Iwpd2TX/tuv/SSqQrZfjfF5qTdl+Kxmg0DzrRkEccpBZKuVENfziKIaef6VLQYnEjXQBDKlNx0+p8OP1hvNUyzHQpU5JwOeDjvS1bq8AXLqnA260jeJul//7TEYnG0DzkxDKBuOilq2QoM6jet37mC4MTDXauZ7AD8TOYu7eWom4eOeZyiRhfvawarVY3nm40p7C6mWkecqGeh/bwCaqyNVMOEAfCUfzizXYsL9DjsnrTtM//6OYS/OqWFTjWa8ctfz6EUffC4rTmw2mzEwaNHDk8GtSvNmkw6PAv2ZDCfBjzBPHIkT5csyIXBRmzD/ysKkzHZy8qn9J5j0BYKrZWZKF71IshB/P7mfnwbtsIPMEIrphiQF0obK8yIBCO4UgPe9d2LRaX4AbAgbhN/KDDj9NLEGM2a4OdpulLaJqun+K/52d4mhlAwXn/Px/A0DSv/2eaptfQNL3GYDDMr3pCUijIUGLPVy7CFy6pYLoUwhRsKM3EsCsImgZWFOqZLoc3FGYq8cy9m/CFiyvw94+undPim7B0UBSFj24qRqvVzfhCxROM4OvPnEZplgpXL89ltBa2kKdPQ45O8T4Fzp/3dKHV6sb3r62HRjG3yUidUop/fXw9nv3MpjkrRAhzoyZHOy+L+JebLPjb/h58dFMx+T1fALvrTEiTivFMIztcN+ZLLEajzepGNQ8tRaeiIV+HYVcQZwaduPehRhi1cvz6lpUzTt7r0qT4ymVVON5nx7NJigPosXngDUWxTADZw6mi3BBvmLLBJr7FGj+8EMKQyoVsLs9Crk6BJ48x11iaicTvB19tyD+6qQRlBhW+99JZVitoLqRjxINAOIblAroGrinKwPE+OytcN5LJoMMHiYhCtoDdqK5qyMGKAj1+/kYbfKHIkr//mCcIizMwr8EArlGdo4XNE/pAY/xfB3thcQbwtcuqZ70HX7MiD3+5aw26Rj24829HUlkugPjQwzKeDVJWTUQptQ8zv/a6kL/t70EwEsNndkyvXicQ2MaWirjgcR/HVOzPnxxCllqOTWWZTJfCGBtKMiGTiFhrEx8IR9Ft8wqywX5pbTYkImpJbOJT5cP1AoBbKIqSUxRVAqACQOpXLoQFo0uTfsBGicAOEjnsALBCQIcPS0GaTIz7L63E8gI906UQpuCaFXnQK6W4429HcMMfDuD7L53FS01DGHT4l1TV/pNXWzHk9OOnNzaQGI3zWF2UjuMTDfbOEQ9+/XYnrmzIwaW12fN6HZlEhJU8yaRjEzU5WnSOuBGOxmZ9bNeoB1956hRWFurxjStqlqA6/qGSS3BZvQkvNw0hGOFOcyNB37gP/nBUMLlcDRPrqbv+dgQOfwh/umM10lWyWZ930+oCLM/X4UevtCZFtdM0YVPfIBD1ZipIKJKZbrBHojG0Wd2CPLwA4ta9N6zOx56OUVhY4CZwIZ0jHmgUEhg0/HQXkElE+M6H6tA35sODe7uZLmfONJkdAIR1DVxTnA5XIILOUfY1phaD2e5Hjl4hWItYID4g/u2rajDsCuIve3qW/P2bh+LK7joeK9hrJmKwzs//dvrC+N07XdhRZcDGOTZ5Lqoy4v5LKtFiccHmSZ2K3R+KomPEzTtXgaopPgc24AqE8a8DfbiszoRyo4bpcgiEOVOVrUGWWo59HdxpsLsCYbzdOoKrGnIEEfMzHWkyMdaXZLC2wd454kE0Rgtyj6pXyrCxLBOvnrakvIewqG8ARVHXURRlBrARwMsURb0OADRNNwN4AsBZAK8B+CxN09w7bSQQWEAih73UoBJUXgaBkCYT46FPrMcdG+J5WP8+1If7HjmBzT/+D9b96G186l/H8Pt3O3G4eyxlN8uDXWP496E+fGxTyaQtOiHOmqJ0WJwBmO0+fOOZ00iTifGdq+uYLoswQU2OBuEoja5ZDnB9oQjufeg45FIxfnfbKsgkwt0cLZZrV+bBFYjgndYRpkuZN60TcQLVOcI4jKrL1UIiojDmDeEnNzTMWe0lElH43jX1GPMG8au3OhZdR5PZiTSpGGUGfqpql4JMtRwZKtms17pU0zvmRTASE+ThRYIbV+eDpsFKJ4+OETfKjWpeuwtsrTDg8noTfvtOJ8x2H9PlzIlTZic0CgmKM1VMl7JkJPYTR3lmEz9o9/PCHn6xrC7KwBXLTPjTni6MuAJL+t6JBnstz5q555No7J5vE/+H97rgCoTxld3V83qtxNqvPYVN4larCzEaqOWZq0CePg0qmRhtU9j1M8m/D/bBHYzgsxeVM10KgTAvKIrClvJM7O+0ccbh5rUzVoQiMVy7Mo/pUhhne6UBnSMeVq6/E7GRNQI557mQy+pN6B3zoTXFA2GLOkWlafpZmqbzaZqW0zSdTdP07vN+9kOapstomq6iafrVxZdKIAgTkYjCFy6uwD3biMURQXjU5+nw7atq8fS9m3DmO7vxwn2b8d0P1WFLeRbah9346WttuPnPh/DDl1uS/t6+UARffboJRZlKfHn37JniQiNxQPi1p0/jSO84vnllDW+VYVwk0eRpncYmPhyN4Z3WEdz9z2PoGPHgV7esQC45GF0Um8syYdDIk2YfvpQ09tshooAKgag9FFIxrluZhy9cXIFrVszvUGB5gR43rynAPw70omN4cRu104NO1OdpBa34SwblBjU6GLYpPTtxrRXq4QUAFGWqsKE0A08cG1hSp6G50DninYwT4DPfuqoWAFKyLk4FTWYHluXpIBLQNbA4U4lMlQzHe+2zP5hDmO1+5KeTyDUA+Opl1QhHY/i/N9uX9H2bh5zIT0+DXjm7Iw9XyVTLYdTIJ2OwrM4A/r6/B9euyJv3YEGlKX5PSOWh+5mJoYf6PH4NPYhEFCpNmpQ3LOaDLxTBX/f1YEeVAfU8s+QnCIMtFQaMeUOs+l7NxPMnB1GUqcRyAbkQTceOqnjk9Z529jkQtFhcSJOKUSSgYdbz2VVrgohCym3iiUyJQOAAH99Sgg+vLWC6DAKBUWQSERry9bhrUzF+cfMKvPvli9D47Utx2/pCPLivB48e6U/q+z3wehv6x334yQ0NSJMRa/gLqTZpoJSJsa/Thk1lmbhpdT7TJRHOozRLBZlYhBbLOWVBLEbjaO84vvXcaaz74Vv42D+OonnIhe9+qA5bKwwMVssPJGIRPrQ8F/9pHYHDF2K6nDnRanXho38/gr/s7cH6kkxBXeseuGk57r+0ckHP/fLuKihlYnznxeYFNxIj0RjODrmwLE+/oOcTzlFmVKNz1LOgzyIcjcEfWrzRWovFBYmImrSsFyo3rS5A35gPR3rYo851+sKweYKoyOb/Z5OnT8N9F5Xj1TNW7O1gp1VlgkA4ijarezKyQyhQFIU1xek41sefBnsoEsOwO0AU7BMUZapw58ZiPHFs4H1K61RzdsjFa3v4BNU52sl/11++1Q6aBr64gPWcQS1HulKK9kUOS87E2SEn9EopL78b1SYN2obdrBmoe+zIAMa9IaJeJ3CWLeWJHHZ2r98AYMQVwIGuMVyzIo/X7lBzpcygRp4+De+1s8/JsMXiQpVJI9iBfoNGjrXFGXjtjCWl70Ma7AQCgUDgLBkqGb73oTpsqzTg28+dwYGu5EwMHu0dxz8O9OKujUXYUDq3LDehIRGLsKowHXKJCD+6bhlZWLMMiViEimw1zlpcODvkwo9fbcXWn76Dm/54EE8dN2NLhQEP3rkGR795Ce7cWMx0ubzhupV5CEdpvHw6tQt4AOgb8+L/vdqCDT96Gzf+4QAeO9IP1xxzwS1OP7785Clc/qu9aOyz4xtXVOPvH1ub4or5Q6Zaji/trsL+zrEFT0N3jXrhD0exLJ//h+GpptyohsMXxph3/oMt33jmNC7/1R74QpFF1dBicaHcqIZcIpwhlam4fJkJarkETx43M13KJMf64s3+uUZBcJ27t5aiKFOJ/32hGcNLbFE9H1qtboSjtCCVT2uKMtA/7ltyC/FU0TfmBU0D+en8ayIulM/tLIdGIcXPXl8aFbsnGEHPmFcQ17lqkwYdwx60Wl144tgAbt9QhIKM+bsnUBSFqokmcao4MxgfeuDjPrkqWwOHL4wRd+oy7OdKMBLFn/d0Y11JBtaSWD8CRzHpFCg3qrGvc4zpUmblhVNDoGngQ8tzmS6FFVAUhW2VWdjfOYZwNMZ0OZPEYjTODrl4HR0zFy6vN6F92JPSSDnSYCcQCAQCp5GIRfjtbStRkqXCvQ81onuRN01/KIqvPNWE/PQ0fOWy+WW5CY3vfKgOD929HsVZwrQbYjs1OVrs7bDhil/vxV/2dqMyW41f3rwCx791KX5z60pcUptNMteTTF2uFhVGNZ5NUQZxJBrDa2esuOOvh7H9gXfx4N4e1OVq4fCH8bVn4s4EX3jsBPZ2jCI6RX6bKxDGA6+34qKfvYvnTw7hE5tLsOcrF+FT28qgkAq7MThfbltXiJocLX74csuU/9az0WR2AABRsCeBhGq8c2R+93+aprGnYxS9Yz78YpFWvi0Wl6Dz1xMoZRJc1ZCDl5ss8ASnH1oIRqJ48tgA7v7nsZTnFe5pH4VCKsLqovSUvg9bUEjF+OG1y2C2+3HJz9/Dvw/1sTLPM3ENbCjQM1oHE6wvjTeA3m1nv0ptLrzYZAFFgbghnYdeKcOH1+RjT/vooge45kKLxQWahjAU7CYNQtEY/uuxk1DKJLhv58IVy1XZGrRb3Sm5RoYiMbRZ3ajn6dBDlWkijowFdtbPNA7C6grgPqJeJ3CcLeVZONIzhkB48e5aqeSFU0Ooz9MK3rnrfLZXGuAJRnCi38F0KZP0jnnhCkQEOcx6PpfV5wAAXkuhTTw5VSUQCAQC59EqpPjrXWshFlG4+5/HFmXP/H9vtqHH5sVPrm+ASi5JYpX8o9yoJlPiLOa6lXnYUWXA96+tx5FvXIy/f2wdrl2ZR36vUwhFUbhuVR6O9dnRP5a8ppHF6ccv3mzH5p/8B/c8dBydIx7cf0kl9n91J/760bV48/5teO6zm3Hj6ny80zqCO/56BFt+8h888Horukc9CEVi+Mf+Hux44F387p0u7K4z4e3/3o5vXVXL66zOVCIRi/DpbaUYdPhxZtA57+efHnRCJROjlAwoLZqKBTbYzXY/hl1BGDVy/HVfz2TDb76Me0MYdgUFnb9+PjetKYA/HMUrTR908nD6w/jDu13Y+pN38OWnmvBWyzBeODWU0nr2dNiwoTRTUENEWyqy8Pp/bcOyfB2+/dwZ3PSngym1QV4IpwacyFTJkKtTMF3KkrMsT4eSLBWeZpHTw0KJxWg802jGlvIsmAT4Wc7EjiojQtEYDnalXo3YPLEOEUL2dPV5jd1PbytFhmrh69hKkwbeUBSDDn+yypukY8SNUDSGOp5+JtWm+JqnbQljEKYiEo3hj+91YVmeDlsrshithUBYLFvKsxAIx9DI4hiZ7lEPmsxOXLsij+lSWMWm8iyIRRSrbOJPTextlwtwmPV8TDoFVhbq8WoKbeLJCSuBQCAQeEFhphJ/umM1PvKXw/jMw43458fXQSqe3xxZY78df93Xg9vWF2JTOdmgEbjN5vIsbCa/x0vONSvy8NPX2vDcyUF8/uKKaR837g2hY9iNYCSGcDT+X/x/05P/PxSJ4UjPON5uHUGMprG90oAfXFuEi6oMkJx3faMoCisK9FhRoMe3rqzF2y0jeOr4AP7wbhd+904X9EopHL4wNpZm4htX1GCZwKeYk8WWiYO8Pe2j8964NpmdqM/TQSTQPLRkkqNTQCUTz7vBfnzi8OrXt67E5x89ga89fRrP37d53muH/Z3xeBqiYI+zqlCPUoMKTxwbwIfXFgAAzHYf/ravF48f7Yc3FMWW8iz87Kbl+P5LZ3G4exyf2ZGaWgbGfeixeXHnxqLUvAGLKclS4eG71+OZxkH84OWzuPLXe/HpbWW4b2c5K4YNTg860JCv46V18mxQFIUbVuXhZ2+0Y2DctyB7a7ZwrM8Os92PL+2qYroU1rGmOB1KmRjvtY/i4prslL5X85ALWWoZjBp5St+HDZQZVZCIKOiVMnxia8miXqsqO94kbh92J/172DwUbzzX89RVIF0V/31jWsH+8mkL+sZ8+OPtqwV5PyHwiw1lmZCIKOzrtLH2PPL5k0OgKOCqBmIPfz5ahRSrC9PxXvsovrybHU6opwacSJOKUW4gTgOX15vwo1da0T/mQ2Fm8tfdpMFOIBAIBN6wtjgD/+/6ZfjvJ0/hf55vxo+uq5/zRisQjuLLT56CSavA1y9nx4KIQCBwjzx9GjaUZuC5E4P43M5yUBSFQDiKsxYXTvY7cHLAgVNmB/rmqHDPVMnwqW2luG1d4ZwO/xRSMa5syMGVDTkYcQXw3MlBNPY5cPO6AuyoNJDDpySSpZajPi8exfC5GYYpLiQcjeGsxYW7BNj0SwUURaHMqJ53g/1Y3zjUcgnWFmfge9fU4Z6HGvHg3h7cu6Nszq/ROeLGN549jWqThji6TEBRFD68pgA/frUVr5y24LUzVrx8An66mgAANf5JREFU2gIKwNXLc3H31pLJnOANpZl4ptGMSDT2vqGhZPHehAX3tkphWldTFIUbVufjomojfvDyWfz2nU68fNqCH15Xj01lzB3ceoMRdI54cPmEZaMQuW5VPn7+ZjuebjTjvy6pZLqcBfP0cTNUMjF21aW2gcxF5BIxNpVl4t22UdA0ndL1V/OQC7W5whhYkUvE+K9LKlCbq4VStrgj7coJFXar1Z30IYjmCaei4kz+OhVVmTRoY7DBHovR+N07najMVmNXLbkGEbiPWi7BykI99nXa8BWmi5kCmqbx/MlBbCzNJK41U7C9yoAHXm/DqDsIAwsG3k6ZHViWp0vJHotrXF6fgx+90orXmi341La57/XnCmmwEwgEAoFX3LA6H12jHvz+3S6UGVS4e2vpnJ73q7c70DXqxb8+vg4ahTTFVRIIBD5z3co8fPXp07j/8ZPotnnRYnEhHI3nO5q0Cqwo0OPWdYWozdFCJZdAJhZBKqEgFYvi/1ssglRMQSoRQSWTQLxAlbNRq0jJBoJwjq0VBvxlTzfcgfCc7x3tw26EIjEsy9entjgBUW5Q48A8bXiP9dqxslAPsYjCZfU52F2XjV++1Y7L600onoN1v90bwif+eQxyiQgP3rWGFapgtnD9yjw88HobPvNwI9RyCT6+uRgf21yCXH3a+x63vjQD/z7UhzNDLqxIgX3he+2jyNOnCT6KIUMlw/99eAWuX5mPbz53Grf95TBuXJ2Pb15Rg/RF2CsvlDODTsRoYHmBcN1U8vRp2FyWhacbzfj8zgpOupkEwlG8fNqCy5flLLrRyVe2VxrwVssIemxelKZIQRaMRNE+7Mb2KuEMEt23c+5DjTOhVUiRq1OkJELjzJALtblaTn6350q1SYN/Huyb95BcKBLD5x89gZocLe7eWrLg+LI3W4bRPuzBL29ewet/Z4Kw2FJuwC/fbseJfjtWFqYzXc77aDI70Tvmm9cwspDYXhlvsO/tGMX1q/IZrSUcjaF5yIU7N5CBfgAoyFCiLleLV89YU3I+RkYYCAQCgcA7vrSrCpfVmfDDV1rwn9bhWR/f2G/Hn97rws1rCgSrciIQCMnj8mU50KVJ8cbZYShlYnxiSyn+ePsqHPr6xTj0jYvxxztW457tZdhWacDqonQsy9eh2qRFmUGNggwlTDoFMtVyaBXSBTfXCUvD1oosRGL0vDJWE5ntDTzN5WSCMqMaVlcA7kB4To93BcJoG3ZjddG5g6vvXVMPmViErz9zGjRNz/j8UCSGex46DoszgD/dsQb56dy1eE4FRq0C37m6Ft+4ohoHvr4T37yy9gPNdQBYVxJX/R/uTn5GcXgi+3gbce6YJJHN/pkdZXjuxCB2/XLPZMTBUtJkjl8Dl+Xpl/y92cQNq/MwMO7H0d5xpktZEG+cHYYnGMH1q0gO63TsqDICOOemkQo6hj2IxGjU55I1xUKoTIEKOxqj0WJxTbq18JUqkxahSAy9c3TlStDYb8drzVb84q127PjZu3jkcD8i0dicn98/5sM3nj2Nzz1yAsWZSlzVIFw3FAL/uGNjEfLT0/DJfx3HoMPPdDnv47mTg5CJRbhMwA5EM1Gbo0WWWpbSe/5cabPGB/qFnr9+Plcsy8GJfgcszuR/r0iDnUAgEAi8QySi8H83L0d9rg6fe+QEWq0ujHtDaOy349kTZvzizXb812MncO3v9mPF997A9b8/AKNGgW9eVcN06QQCgQdoFVIc+vrFOP2d3XjsUxvxtcurcVl9DrFS4yGri+IZq3s75t6kajI7oVFIUJSC/C+hUmGMKwO7Rr1zevyJfgdoGlhTdM7WPVurwNeuqMbB7jE8ecw87XNpmsa3nzuDwz3j+OkNDe9r0hPOccfGYnxqWxm0Mzg7GDUKlBlUOJSCBntjnx2eYATbK9mZYckUCqkYX7msGi/ctwW6NClu/+th/Oz1tnk1NxZL06ATuToFK+wzmWR3nQlquQRPHZ/+esNmnmk0I1enwIaSTKZLYS0FGUqUGlR4ty11h+3NQ/GBlTqeZn2nmiqTBt2jXoSTeA3ssXnhC0VRz/NByuoJi/35Dijs67BBLKLwz4+vQ1GGEt949jR2/3IP3mi2zjjg2D7sxv2Pn8RFP38XTx0z48Y1+Xj4kxuI/TGBV2SoZPjrXWsRDEdx9z+PwRuMMF0SgPjg0IunLLio2gBdGnH8nAqRiMK2CgP2tI8iGpt5WDvVnDI7AADLiWPeJJfVmwAAr5+xJv21yV2IQCAQCLxEKZPgL3eugVohwRW/2otV338T1//+AO5//BR+/Z8OHO21QyUX44plOfjGFdV4/NMbZjwEJhAIhPmQJhMT9bkAkEvE2FCaib0dcz88Pz3oxLI8YWSlLhXlEw32jjnavB7vHYeIAlYU6t/357euLcS64gz88JUWjLgDUz73r/t68PixAXxuZzmuXUmUm4tlfWkmjvXak34QtadjFGIRhU3lpME+FbW5Wrxw32Z8eHUBfvtOJ27586ElU0o1mR1oIAd+UMokuGKZCa+ctsAXYscB+lwZcQewp30U163KI9bMs7C90oBD3WMIhKMpef0zgy6o5RIUZpChvYVQla1BKBpDr21uA3pzQShDD+VGNUQU0DZPi/19nTYsz9dhe6UBT96zEX++YzVoAJ/693F8+E8H0dhvf9/jm8wOfPrfx7DrF3vw2hkrPrapGHu/ehF+dN0y5E3hjkMgcJ3KbA1+c9tKtFld+MJjJxlv1gLAgS4bbJ4grl1B9j4zsb3KALsvPOlYxxSnBhxIV0pRkEGukQnKDGpUZqvxKmmwEwgEAoEwd0w6BR76xHrcvbUU37qyBn+9aw3e+uJ2tH7/Muz/2k48fPcG/Oi6ZfjUtjIUZQo7n5NAIBAIC2NrRRZ6x3zon4NFZjASRYvFhWX5/FY1LTWFGUrIxCJ0jnrm9PhjfXbU5GihviD3UySi8KPrl8EfiuK7L579wPPebhnGD19pwRXLTLj/ksqk1C501pdkwB2M4OyQK6mvu6fdhpUFejI8OQNKmQQ/ubEBv7plBVqtblz+y3jzIpU4fCH0jfnQIOD89fO5cXUBvKFoyv/dk80LJ4cQo8F4xigX2FFlRDASS4lTRzgaw+vNVqwvySCDDgukMntChZ3EHPYzg07IJKLJ4T++opCKUZypQpt17vdvpz+MJrMDWyrisXwURWFXnQlv/Nc2/PC6evSO+XD97w/g3oeO47UzFtzx18P40G/342DXGD5/cQUOfG0nvnVVLbK1xBWMwG92VBnxP1fV4q2WYfz0tVamy8HzJ4egkUtwUbWR6VJYzZbyLFBUaqNh5kKT2YmGfD0Z6L+Ay+pzUhLNRBrsBAKBQOA1FdkafOOKGty9tRQX12Sj3KiGXCJmuiwCgUAg8IRtlfFDwj1zULG3Wz0IR2k0CDx7ONlIxCIUZynRNTJ7gz0SjeHkgANrprF2Lzeq8bmd5Xi5yYK3zg5P/nmr1YXPP3oC9bk6/PymFaSZkSQ2lMbtpZPZfBrzBHFmyDn53STMzDUr8vDy57egOEuFex46jv95/kzK1LaJ/HVyDYyztjgdhRlKztnEP3XcjBUFepQZ+N1ATAbrSzIgl4hSYhP/dsswRtxB3LquMOmvLRQSKuz2JOawNw+5UGPSQCoA6/KqeWbYH+oeQ4yON6HORyIW4SPri/Dul3bg/ksqsad9FPc81IgWiwtfu7wa+7+2E1+8tBLpKlmy/woEAmu5a1Mxbt9QiD/t6cYTxwYYqyMQjg8C7q43QSElZ6kzkamWoyFPh3fbRhirwReKoH3YTfLXp+DyehNSYQjB/7s9gUAgEAgEAoFAIKSI0iwV8vRpc7KJbxp0AAAaiII96VQYNeicQ4O9xeKGLxTF6uKMaR/z6e1lqMrW4NvPn4E7EIbNE8Qn/nEMakU8fiZNRg6XkkW2VoGSLBUO9ySvwb6v0waajlszE+ZGUaYKT92zCZ/cWoJ/HezDtb/bP6fv03w5PWGZSVw84lAUhRtW5eNg9xjM9tldUNjA2SEXWq1u3LCK2MTOBYVUjI1lmdiTAjXbw4f7katTEEXhIlBIxSjOUqE1SQ12mqZxZtCJ2lxhXOOqTBr0jfvmHHOxr8MGpUyMFdM0flRyCb5wSQXe/fJF+Muda7Dvqztxz/YyaIgbDUGAUBSF/726DlvKs/DNZ0+nxAllLvyndQSeYITYw8+Ri6qNODHgwIhr6rixVHNm0IUYDSwna+0PUG3SoDgz+ZE6pMFOIBAIBAKBQCAQCAuEoihsrcjCgc4xhKOxGR972uyEXilFfjrJQ0s2ZUY1+sd9sypvj/XFbeGmU7ADgEwiwv+7YRmsrgB+9EoLPv3v4xjzBvHgnWth0hFb0mSzviQDh3vGk5Yx+V77KNKVUtTnkYOl+SCTiPDNK2vx94+uxYg7iKt/sw8vNQ0l9T1ODThQkqWCLo00SxJcvyoPNA082zjIdClz4plGM6RiClc15DJdCmfYXmlAt807pyiZudI35sXeDhtuXlsIMXFUWRRV2Rq0J8ki3mz3wxWIoD6P3/nrCapNGtA00DE8t4Gs/Z02rC/JgEwyczvCoJHj0tpsopYlCB6pWITffWQVCjOUuOeh4+i1eZe8hudPDsKgkWNjWeaSvzcXuaohBzQNvHzawsj7nxpwAAAa8vWMvD+boSgKl9XnJP11SYOdQCAQCAQCgUAgEBbBtkoD3MHI5IZ2Ok4POrEsT0fy0FJAuVGNGA30zHLwdKzPjlydArn6mYccVhWm466NxXj0yACO99nxfx9eQVS3KWJDaSbcgQhaLIvPYY/FaOxpt2FLhYE0nRbIRdVGvPqFrajL1eK+R07gwb3dSXvtJnP8Gkg4R0GGEhtLM/F0oxk0nQLfyiQSicbw3Mkh7Kw2EqvmebCjKq4wf689eZaxjx4ZgFhE4ea1BUl7TaFSmR1XYftDi4/GaB6Ku3TUC0bBHh8kmItN/KDDj26bdzJ/nUAgzA1dmhR/vWstAOAT/zwKpz+8ZO/t9IXxTusorm7IJevqOVJu1KDapMGLp5I7pDpXTpkdyNOnwaCRM/L+bCcVDkykwU4gEAgEAoFAIBAIi2BzWRZEFLCnwzbtYwLhKNqsbtJcShHlE1nAM9la0zSN4732Ge3hz+dLu6uwtjgd37qyBlcsS/60OyHO+tL453G4Z3zRr9VidcHmCWJbRdbsDyZMS7ZWgYfuXo8rlpnwg5db8N0XmxftMDDiCsDqCpCIjCm4YXU+esd8ON5nZ7qUGdnbaYPNE8T1q/KZLoVTlGSpUJSpTFoOeygSw5PHBnBxtZG4qiSBSRX2yOJV7GcGXRCLKFSZNEmojP0UZiihkIrmZLG/vzO+Rr4wf51AIMxOcZYKf7x9NfrHfbjvkUZEZnFNmw2nP4znTw7C5gnO+LjXmi0IRWO4ZgVxrZkPVy/PRWO/g5H4n1NmB5YXkLX2dFRkJ//+TBrsBAKBQCAQCAQCgbAIdEoplhfoZ8xYbbW6EYnRpLmUIkoNKlDUzA32QYcfVldgRnv481HLJXjynk24e2tpssokTEGOLg2FGcqkZEvuaY8f4G8j+euLRiEV47e3rsLHN5fg7/t7cd8jjbNGMMxEkzmu7Fw+TfaukLm83gSlTIynjpuZLmVGnmkchF4pxUVVJPN7vmyvNOBA19iivkMJXm+2Yswbwm3rC5NQGaFyohk+FxX2bJwZcqLCqBaMtblYRKEyW4O24dkdaPZ12JCllqMyW70ElREI/GNDaSZ+eO0y7O2w4evPnF7w4KPNE8TNfzqILzx2Eut/9Dbu+OthPHXcDHfgg8r4504MoSRLRfav8+TqiRidl5uW1iZ+zBPEwLgfy4k9/JJCGuwEAoFAIBAIBAKBsEi2VhjQZHbA4QtN+fPTZgcAYBnZ8KYEhVSMwgwlOkenb7An1KGr59hgJywdG0ozcLR3HLFFqqT3tI+i2qRBtpaoOpOBSEThf66uxbeurMGrZ6y446+Hp73GzUaT2QERBdTlCiObeD6o5BJcsSwHLzdZkmJTnQpcgTDeaLbiQ8tzZ81PJnyQHVUG+MNRHOtdvEvBI4f7kZ+ehm3EajspFGUoIZOIkpLDfmbQhTqB2MMnqMrWzDqcEIvR2N9pw5byTBKTRCAsgg+vLcDnL67Ak8fN+PS/j897zWB1BvDhPx1E75gXP7tpOT69rRQ9Ni++9OQprP7BW7j3oeN47YwFgXAUVmcAh3rG8KHlueR7O08KM5VYnq/Di01LaxPfNBgfZiX560sLWRUTCAQCgUAgEAgEwiLZVpGFGA0c6JpahdtkdiJTJUMusXNNGeUGNbpmULAf67VDJROjWiDWrVxifUkmHL4w2hbR4PAGIzjWN07U6yng7q2l+O1tK3FqwIkb/nAAA+Pzt7w8ZXaiwqiBUiZJQYXc54ZV+XAHI3jjrJXpUqbklSYLgpEYbiD28AtiQ2kmZGIR3m1bXA5716gHB7vHcOu6QohIHm5SkIhFqDCq0TY8/fphLoy4ArB5gqjPE9YQUZVJA5snNKPVdNuwG2PeEDYTe3gCYdF88dJKfO+aOvyndRi3/OXQrDbvCQbGfbjpTwcw4griXx9fjxtX5+Mrl1Vj71cuwtP3bsJt6wpxtNeOex5qxNofvIVP/fsYaBrEHn6BXL08F2cGXeixeZfsPU8NOEBRwDLiOLCkkAY7gUAgEAgEAoFAICySFQV6aOSSaW3iTw86sSxfRxQAKaTcqEb3qHfaXMJjfXasLEyHREy2wWwjkcO+GJv4Q91jCEdpbCcN9pRwVUMu/v2JdRh1B3H9Hw7gzIRKZi7QNI0ms4NYjM7A+pIM5KensdYm/pnGQZQZiE3sQlHKJFhfmoH3ZoiSmQuPHu6HREThpjVk0CGZxFXYs9ucz8SZofg1UWgK9mpTfKBgJhX7ZP56BWmwEwjJ4M6Nxfjj7avRZnXhhj8cQO8sTdyuUQ8+/KeDcPkjePju9VhXkjH5M4qisLooHd/5UB0OfX0n/v2Jdbis3oQemxfrSjJQaiCxDgvhyoYcAMBLp5ZOxd5kdqLcoIZaToZZlxJyskAgEAgEAoFAIBAIi0QiFmFTeSb2dthA0++3ufaHougY8aAhT1iHrktNmVGNUDSGAbv/Az9zB8Jos7qIPTxLyU9XIj89DYe7xxf8GnvaR5EmFWNNMfmMU8X60kw8de8mSEUUbv7TwTk3C812P+y+MBpI/vq0iEQUrl+Vj32dNlicH7yGMUn/mA9Hesdx/ap8MiS2CLZXGtAx4sGgY2GfbyAcxVONZuyqy4ZRQ9xwkkmlSYNhV3DBERhA3B4eAGoFFoNRNeEK1DpDg31vhw1lBhVydGlLVRaBwHt21ZnwyCc3wB2I4Po/HEBj/9QRJC0WF27+00GEozE89qkNWD7DWkwiFmFrhQEP3LQcx791KR6+e32Kquc/Obo0rCvOWDKbeJqmcWrAMePnS0gNpMFOIBAIBAKBQCAQCElga4UBgw4/ui9QEZy1uBCN0SR/PcWUG+MKi84pbOJP9DsQo0GaryxmfUkmjiwih31Phw0bSjMgl4iTXBnhfCqzNXj2s5tRmKnCJ/5xFIfn4DrQZI4rO5cT9fOM3LAqDzQdV4uziWdPDIKigGtX5jFdCqfZURV311ioTfxrZ6xw+ML4yPqiZJZFwLkmcfsibOKbh5wozVIJTjlo0MiRqZKhfZoGezASxZGecWwh9vAEQtJZVZiOp+/dBI1Cgtv+cghvNL8/ZubUgAO3/PkQJCIRHvvURtTkzH0ASCYRQUpcvxbFVctz0D7smdHhI1kMOvwY84bIWpsByLeEQCAQCAQCgUAgEJJAwpr6Qpv402YHAGAZUbCnlJka7Mf67BBRwMpC0mBnKxtKMzDuDaFjis9vNvrHfOixeUn++hKRrVXg8U9vQGGGEvc9egIjrsCMj28yOyAVU5NNLMLUFGWqsK4kA083mj/ghMIUNE3jmRNmbCzNRJ6eqE8XQ5lBjTx9Gt5rW5hN/MOH+1CcqcTG0swkV0aoyo5fmxZjE39m0IU6ga7zKrM1aB2euoF0ot8BfzhK8tcJhBRRkqXC0/duQpVJi3seOo5/H+wFABztHcdHHjwMbZoET96zcXKfRFg6Lq/PgYgCXloCFfupgYlhVqJgX3JIg51AIBAIBAKBQCAQkkBBhhLFmUrs7bC978+bBp0waOTI1soZqkwYaBVSZGvl6Bj54CHv8b5xVJu0glOWcYkNE02jwz3zz2F/ryPesCIN9qVDq5DiD7evhicQwX2PnkAkGpv2sU1mJ2pytMRdYA7cuCof3aNenBhwMF0KAKCx346+MR+uX0UyvxcLRVHYXmXA/k4bQpHpvy9T0T7sxtFeO25dVwiRiNj0J5scnQIauQRt0zSJZ8PuDWHQ4UedwOzhE1SZNOgYdk/pQLO/0waxiMKGMjIYQiCkiiy1HI9+cj12Vhvx7eebcf/jJ3HnX4/AqJXjiU9vREGGkukSBYlBI8emsiy8eGoo5YOTTWYHZGIRqk3CvA8xCWmwEwgEAoFAIBAIBEKS2FphwMGuMQQj0ck/O212oiFPR7Jrl4ByoxpdFyigI9EYTvQ7iD08y8lPT0OuToFDc7Acv5A97aPI06ehNEuVgsoI01Fl0uBH19fjSM84Hni9bcrHxGI0zgw60UAsK+fEFQ05SJOK8dRxM9OlAACebhxEmlSMy+tNTJfCC3ZUGuANRXG8b+qs3Ol45HA/ZGIRblxNBh1SAUVRqDRp0G5dmEV881Bc+V6fK8zrXLVJA18oigG77wM/29thw/J8HbQKKQOVEQjCQSmT4I+3r8btGwrx7IlBFGUq8finNiJHR9xnmOTq5TnoHfPhzODCHVLmwskBB2pytZBJSLt3qSH/4gQCgUAgEAgEAoGQJLZVGuAPnzs89wYj6Bz1YBlpLi0J5QY1uka971MJtFjc8IWiWF1EGuxshqIobCjNxJGe8XmpPMLRGA52jWFbpYEMsTDAdSvzcfuGQvxpTzdevyD7EwC6bV64gxE05OuXvjgOopZLcHm9CU8fN+PJYwOM1hKOxvDKaQt212VDRdw/ksKm8ixIxRTebZ97Drs/FMXTjWZcVm9Cppo44aSKKpMGrVbXglSGzUNxa14hK9gBoPWCnGGnP4wms4PkrxMIS4RELML3r6nHw3evx+Of3giDhtwzmGZ3nQkSEYUXU2gTH50YZl1BzhsYYVENdoqiHqAoqpWiqCaKop6lKEp/3s++TlFUJ0VRbRRF7V50pQQCgUAgEAgEAoHAcjaUZkAioiZt4puHXKBpEPXmElFuVMMTjMB6Xib0sb5xAMCa4gymyiLMkfWlGbB5QuganbuKsLHPDk8wgu2V5ACfKb59VS2W5+vwpSdOodfmfd/PmswOAOQaOB++fkUNVhWm48tPNeGLj5+ENxhhpI4DXWNw+MK4siGXkffnI2q5BGuKMuaVw/5S0xDcgQhuW1+YwsoIVdkauAIRDLuC837umSEX8vRpSFfJUlAZ+6mczLB/f4P9UPcYYjRI/jqBsIRQFIXN5VnQpRHXCDagV8qwrdKAl5ssU8ZoJIOuUQ+8oSgZZmWIxSrY3wRQT9N0A4B2AF8HAIqiagHcAqAOwGUAfk9RFAnbIhAIBAKBQCAQCLxGo5BiVWE69k5kQp8ejKua6vNIc2kpKDfGD3k7z7OJP9ZnR45OgTw9sUhkO+tL4hmtB7vH5/ycPR2jEIsobCIH+Iwhl4jxu4+sglhM4Z6HjsMfOheR0WR2Ik0qRrlBzWCF3MKgkeOhu9fj/ksq8dzJQVz9m304O5Raa9GpeKXJArVcgq0V5LuVTHZUGdBqdcPqDMz+YACPHOlHmUGF9SVkSCyVTDaJF5DD3jzoFKx6HQBUcgkKM5QfaLDv77RBKRNjZSFxECIQCMLl6uU5GHT4cWJgfvEwc+XUgAMAsLxAn5LXJ8zMohrsNE2/QdN0YpT2EIBEGNA1AB6jaTpI03QPgE4A6xbzXgQCgUAgEAgEAoHABbZVZuHMoAs2TxCnzQ7k6BQwahRMlyUIyo3xJl7HcLzBTtM0jvfaiT08RyjKVMKkVeDwPHLY97TbsKpQT/JdGSY/XYlf3rwCbcNufOu5M5M2y01mB+rztJCISULhfBCLKHzhkgo8fPcGeIIRXPv7/fj3ob4F2VcvhHA0htfPWnFJjREKKdHLJJPtVQYAwHtzsIk/O+TCiX4HbltfRCIwUkzC5rzdOr8GuycYQbfNK/hByoTF/vns67BhfUkGyQQmEAiC5pKabMglIrx4ypKS1z9ldkAjl6A0S5WS1yfMTDLvcB8H8OrE/84DcH5YlHnizwgEAoFAIBAIBAKB12ytiB+e7++0oWnQKfhD16UkSy2DLk2KzgmL8UGHH1ZXAGtIg50TUBSF9aUZODzHHHabJ4jTg05sm/jOEZhlR5URn9tZgacbzXjs6ADC0Riah1zEsnIRbCzLxKtf2IpNZZn49nNn8JmHG+H0h1P+vgcn7OGvWJaT8vcSGlXZGpi0CrzXPrtN/CNH+iCTiHDDKnKkmmoyVDIYNPIP5IjPRosl3lSuzxOugh0Aqk0a9I75EAjHHUwGHX5027zEHp5AIAgejUKKi6qMePm0BdEU2MQ3mZ1Ylq+DSEQG8Zhg1gY7RVFvURR1Zor/rjnvMd8EEAHwcOKPpnipKX97KIr6FEVRxyiKOjY6OvcMIgKBQCAQCAQCgUBgI/V5OuiVUrxy2oLuUS8aSIN9yaAoCuVG9aRF/PG+uBUfyV/nDutLMjHqDqL7gizvqdjXYQMAbKskDXa28IWLK7C1Igv/+0Iznm0cRDASI/nriyRTLcff7lqLr19ejTfPDuPKX+/FyQk70FTxyum4PTz5biUfiqKwo8qAvR02RKKxKR8TCEfRPerBcyeGcFVDDvRKYWZ7LzVV2Rq0z9Mi/sxEFFBdrrCvc1UmDaIxenL9tb8zfn/eQiImCAQCAVcvz8WoO4jDPXNz6XL4QnN6XCAcRYuFDLMyiWS2B9A0fclMP6co6i4AVwG4mD43Ym4GUHDew/IBDE3z+n8G8GcAWLNmzdJ4XREIBAKBQCAQCARCihCLKGwpz8LLp+M2cMtIc2lJqTCq8ebZYQDAsV47lDIxqiesXwnsZ0NpfBjicPc4ymbJ7f5P6wjSlVLiEsEixCIKv7plJa769V587ZkmACCHfklAJKLw6e1lWFuSgc89cgI3/uEAfnJDA25YnT/7k+dJOBrD681WXEzs4VPG9koDHjs6gF++1QGRiMKwM4BhdwBWZwDDrgDsvnMuBR9ZX8RgpcKiyqTBw4f7EI3REM9RCXhm0IUstRxGjTzF1bGbxDqrzepGfZ4O+zttyFLLUZVN1l8EAoGws9oIpUyMF09ZsKls+sEjpz+M7714Fk83mvHD6+pnXQO0WFwIR2msKCB7IaZYlEU8RVGXAfgqgA/RNO0770cvALiFoig5RVElACoAHFnMexEIBAKBQCAQCAQCV9hWYUBi/HgZaf4tKeVGNca8IYx7QzjWZ8fKQj3Jf+YQJVkqGDRyHJohh33cG8LnHj2BF04N4bL6nDk3QghLQ4ZKht99ZBXEIgpahQTFmUqmS+INqwrT8crnt2JtcQa+/uzpeatt58Lh7nHYfWFcXk/s4VPF5oospEnF+O07nfjNfzrwn7YR2DxB5Ken4YplOfjvSyvx0xsb8NQ9G7GaRJwsGVXZGgTCMfSP+2Z/8ATNQ07U52lBUcK+DxVnqiCTiNA27EYsRmN/pw1byjMF/+9CIBAIAJAmE+PS2my8esaC8DTuNe+2jWD3L/bguZODKDOo8N0Xzs7qWNRkjruokGFW5phVwT4LvwUgB/DmxA3zEE3T99A03UxR1BMAziJuHf9Zmqaji3wvAoFAIBAIBAKBQOAEWyvjk+l5+jRkqoWtalpqyoxx1fPJATvarC7ct7OC4YoI84GiKKwvycDhnjHQNP2Bw/mXmyz4n+fPwBUI44uXVuLeHWUMVUqYiZWF6fjVLSth94VIgyXJ6JRS/Oa2lbjsl3vw+UdP4Pn7NkMuSZ7S/OXTFqhkYuyoIvbwqUKrkOLdL+9A9P+3d+/RVdVnGsef9+TkfoVAgBCQe4IEYoqtiFUrdrygrdrW8dKirnacWtt66WVqO52u1i67OnV1tFVbx2Xr6oyjUnRa6g1Hah0LTrWCWIKIoEi5BYg0ELBc884f54CRBj052Tl7J/v7WYuVsLPPzrsXPDknv/fsd3e6hpYXKp83gUXCpC5XYY8dUvqe++/Zf1Crt+7ShycP6+vSIi+Zl9CEoWVa1dqhVVs61LZrH/dfB4Auzp1Wq/nLNmnRmjadVl9zePuuvQd006Mv6/7n12tiTZnuumy6Rg8u0bm3LdLV9y7RI9ecrMGl3d8q5qX17RpaXqgRlUW5Og0coVev4Nx9gruPcvfj0n+u6vK1m9x9vLvXu/v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      "text/plain": [
       "<Figure size 2520x360 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "merged_df.plot(x='time', y='gw_storage', figsize=(35,5))"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.10"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}