diff --git a/doc/jupyter/Demo/Demo_9_seaIceExtent_ivanova.ipynb b/doc/jupyter/Demo/Demo_9_seaIceExtent_ivanova.ipynb
index 955dbf1b3..72438dcae 100644
--- a/doc/jupyter/Demo/Demo_9_seaIceExtent_ivanova.ipynb
+++ b/doc/jupyter/Demo/Demo_9_seaIceExtent_ivanova.ipynb
@@ -40,7 +40,7 @@
     "The PCMDI Metrics Package (PMP) sea ice driver produces metrics that compare modeled and observed sea ice extent. This notebook demonstrates how to run the PMP sea ice code.\n",
     "\n",
     "**Authors**   \n",
-    "Ana Ordonez, Jiwoo Lee, Paul Durack, Peter Gleckler (PCMDI, Lawrence Livermore National Laboratory)\n",
+    "Ana Ordonez, Jiwoo Lee, Paul Durack, Peter Gleckler ([PCMDI](https://pcmdi.llnl.gov/), [Lawrence Livermore National Laboratory](https://www.llnl.gov/))\n",
     "\n",
     "**Reference**  \n",
     "Ivanova, D. P., P. J. Gleckler, K. E. Taylor, P. J. Durack, and K. D. Marvel, 2016: Moving beyond the Total Sea Ice Extent in Gauging Model Biases. J. Climate, 29, 8965–8987, https://doi.org/10.1175/JCLI-D-16-0026.1. \n",
@@ -55,6 +55,10 @@
    "metadata": {},
    "source": [
     "## Demo data\n",
+    "\n",
+    "\n",
+    "### Model output\n",
+    "\n",
     "This demo uses three CMIP6 models. The Sea-Ice Area Percentage (Ocean Grid; 'siconc') and Grid-Cell Area for Ocean Variables ('areacello') variables are needed and can be found in the following directories. In addition, six other models are available that can be added to the analyses in this demo:\n",
     "```\n",
     "/p/user_pub/pmp/demo/sea-ice/links_siconc\n",
@@ -62,17 +66,98 @@
     "```"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": 16,
+   "id": "519bf2cc",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "siconc_SImon_E3SM-1-0_historical_r1i2p2f1_gr_185001-185912.nc\n",
+      "siconc_SImon_E3SM-1-0_historical_r1i2p2f1_gr_186001-186912.nc\n",
+      "siconc_SImon_E3SM-1-0_historical_r1i2p2f1_gr_187001-187912.nc\n",
+      "siconc_SImon_E3SM-1-0_historical_r1i2p2f1_gr_188001-188912.nc\n",
+      "siconc_SImon_E3SM-1-0_historical_r1i2p2f1_gr_189001-189912.nc\n",
+      "siconc_SImon_E3SM-1-0_historical_r1i2p2f1_gr_190001-190912.nc\n",
+      "siconc_SImon_E3SM-1-0_historical_r1i2p2f1_gr_191001-191912.nc\n",
+      "siconc_SImon_E3SM-1-0_historical_r1i2p2f1_gr_192001-192912.nc\n",
+      "siconc_SImon_E3SM-1-0_historical_r1i2p2f1_gr_193001-193912.nc\n",
+      "siconc_SImon_E3SM-1-0_historical_r1i2p2f1_gr_194001-194912.nc\n",
+      "siconc_SImon_E3SM-1-0_historical_r1i2p2f1_gr_195001-195912.nc\n",
+      "siconc_SImon_E3SM-1-0_historical_r1i2p2f1_gr_196001-196912.nc\n",
+      "siconc_SImon_E3SM-1-0_historical_r1i2p2f1_gr_197001-197912.nc\n",
+      "siconc_SImon_E3SM-1-0_historical_r1i2p2f1_gr_198001-198912.nc\n",
+      "siconc_SImon_E3SM-1-0_historical_r1i2p2f1_gr_199001-199912.nc\n",
+      "siconc_SImon_E3SM-1-0_historical_r1i2p2f1_gr_200001-200912.nc\n",
+      "siconc_SImon_E3SM-1-0_historical_r1i2p2f1_gr_201001-201112.nc\n"
+     ]
+    }
+   ],
+   "source": [
+    "!ls /p/user_pub/pmp/demo/sea-ice/links_siconc/E3SM-1-0/historical/r1i2p2f1/siconc"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 17,
+   "id": "a5bc009b",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "areacello_Ofx_E3SM-1-0_historical_r1i1p1f1_gr.nc\n"
+     ]
+    }
+   ],
+   "source": [
+    "!ls /p/user_pub/pmp/demo/sea-ice/links_area/E3SM-1-0/"
+   ]
+  },
   {
    "cell_type": "markdown",
    "id": "00d48042",
    "metadata": {},
    "source": [
+    "### Reference dataset\n",
+    "\n",
     "The observational dataset provided is the satellite derived sea ice concentration dataset from EUMETSAT OSI-SAF. More data information can be found at the [osi-450-a product page](https://osi-saf.eumetsat.int/products/osi-450-a). The path to this data is:\n",
     "```\n",
     "/p/user_pub/pmp/demo/sea-ice/EUMETSAT\n",
     "```"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": 20,
+   "id": "8f2af9d9",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "ice_conc_nh_ease2-250_cdr-v3p0_198801-202012.nc\n",
+      "ice_conc_sh_ease2-250_cdr-v3p0_198801-202012.nc\n"
+     ]
+    }
+   ],
+   "source": [
+    "!ls /p/user_pub/pmp/demo/sea-ice/EUMETSAT/OSI-SAF-450-a-3-0/v20231201"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "bf862633",
+   "metadata": {},
+   "source": [
+    "**NOTE** Further explore for the above datasets can be found in our supplemental Jupyter notebook: [Demo_9b_seaIce_data_explore.ipynb](Demo_9b_seaIce_data_explore.ipynb)"
+   ]
+  },
   {
    "cell_type": "markdown",
    "id": "0b854017",
@@ -86,7 +171,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 1,
+   "execution_count": 30,
    "id": "b6d75e4e",
    "metadata": {},
    "outputs": [
@@ -96,8 +181,8 @@
      "text": [
       "Creating Arctic map\n",
       "Creating Antarctic map\n",
-      "CPU times: user 8.72 ms, sys: 4.33 ms, total: 13 ms\n",
-      "Wall time: 27.3 s\n"
+      "CPU times: user 8.92 ms, sys: 2.89 ms, total: 11.8 ms\n",
+      "Wall time: 37.3 s\n"
      ]
     }
    ],
@@ -109,7 +194,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 2,
+   "execution_count": 27,
    "id": "a82ee330",
    "metadata": {},
    "outputs": [],
@@ -120,7 +205,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 3,
+   "execution_count": 31,
    "id": "6a7eb6da",
    "metadata": {},
    "outputs": [
@@ -169,7 +254,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 4,
+   "execution_count": 25,
    "id": "a6cb929f",
    "metadata": {},
    "outputs": [
@@ -177,15 +262,15 @@
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "2024-01-25 22:44:28,596 [WARNING]: dataset.py(open_dataset:109) >> \"No time coordinates were found in this dataset to decode. If time coordinates were expected to exist, make sure they are detectable by setting the CF 'axis' or 'standard_name' attribute (e.g., ds['time'].attrs['axis'] = 'T' or ds['time'].attrs['standard_name'] = 'time'). Afterwards, try decoding again with `xcdat.decode_time`.\"\n"
+      "2024-01-26 17:31:53,248 [WARNING]: dataset.py(open_dataset:109) >> \"No time coordinates were found in this dataset to decode. If time coordinates were expected to exist, make sure they are detectable by setting the CF 'axis' or 'standard_name' attribute (e.g., ds['time'].attrs['axis'] = 'T' or ds['time'].attrs['standard_name'] = 'time'). Afterwards, try decoding again with `xcdat.decode_time`.\"\n"
      ]
     },
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "CPU times: user 6.37 ms, sys: 1.71 ms, total: 8.08 ms\n",
-      "Wall time: 15.1 s\n"
+      "CPU times: user 5.27 ms, sys: 5.02 ms, total: 10.3 ms\n",
+      "Wall time: 18 s\n"
      ]
     }
    ],
@@ -197,20 +282,20 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 5,
+   "execution_count": 29,
    "id": "3120f819",
    "metadata": {},
    "outputs": [
     {
      "data": {
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"
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"
      },
      "metadata": {},
      "output_type": "display_data"
     },
     {
      "data": {
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"
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"
      },
      "metadata": {},
      "output_type": "display_data"
diff --git a/doc/jupyter/Demo/Demo_9b_seaIce_data_explore.ipynb b/doc/jupyter/Demo/Demo_9b_seaIce_data_explore.ipynb
new file mode 100644
index 000000000..0e8cf0da3
--- /dev/null
+++ b/doc/jupyter/Demo/Demo_9b_seaIce_data_explore.ipynb
@@ -0,0 +1,3686 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "\n",
+    "# PCMDI Metrics Package Sea Ice Demo\n",
+    "## _Supplementary: Explore the Sea Ice Data_\n",
+    "\n",
+    "\n",
+    "<div style=\"text-align: right\">\n",
+    "<p>\n",
+    "    <img src=\"https://pcmdi.github.io/assets/PCMDI/100px-PCMDI-Logo-NoText-square-png8.png\"\n",
+    "         width=\"65\"\n",
+    "         style=\"margin-right: 30px\"\n",
+    "         title=\"Program for Climate Model Diagnosis and Intercomparison\"\n",
+    "         alt=\"Program for Climate Model Diagnosis and Intercomparison\"\n",
+    "    >&nbsp;\n",
+    "    <img src=\"https://pcmdi.github.io/assets/DOE/480px-DOE_Seal_Color.png\"\n",
+    "         width=\"65\"\n",
+    "         style=\"margin-right: 30px\"\n",
+    "         title=\"United States Department of Energy\"\n",
+    "         alt=\"United States Department of Energy\"\n",
+    "    >&nbsp;\n",
+    "    <img src=\"https://pcmdi.github.io/assets/LLNL/212px-LLNLiconPMS286-WHITEBACKGROUND.png\"\n",
+    "         width=\"65\"\n",
+    "         style=\"margin-right: 30px\"\n",
+    "         title=\"Lawrence Livermore National Laboratory\"\n",
+    "         alt=\"Lawrence Livermore National Laboratory\"\n",
+    "    >\n",
+    "</p>\n",
+    "</div>"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "**Summary**  \n",
+    "\n",
+    "In this notebook, we are going to explore the dataset used for the [PMP Sea Ice demo notebook](Demo_9_seaIceExtent_ivanova.ipynb). Let's explore the sea ice data for fun!\n",
+    "\n",
+    "\n",
+    "**Notebook Authors**: Jiwoo Lee, Ana Ordonez, Paul Durack, Peter Gleckler ([PCMDI](https://pcmdi.llnl.gov/), [Lawrence Livermore National Laboratory](https://www.llnl.gov/))\n",
+    "\n",
+    "## 1. Environment setup\n",
+    "\n",
+    "We will use multiple libraries for this analysis.\n",
+    "\n",
+    "- [xCDAT](https://xcdat.readthedocs.io): an open source Python tool developed based on the xarray to ease climate data analysis. The [xCDAT](https://xcdat.readthedocs.io) is an extension of [xarray](https://xarray.dev/) for climate data analysis on structured grids.\n",
+    "- [numpy](https://numpy.org): needed for calculating the metrics.\n",
+    "- [matplotlib](https://matplotlib.org/) and [cartopy](https://scitools.org.uk/cartopy/docs/latest/): required for data visualizations."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import xcdat as xc\n",
+    "import numpy as np\n",
+    "import matplotlib.pyplot as plt\n",
+    "import cartopy.crs as ccrs"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Optional packages for interactive visualization\n",
+    "\n",
+    "- [hvplot](https://hvplot.holoviz.org/): this tool used for 2-D interactive plots. Following optional packages are also required for interactive visualizations: [geoviews](https://geoviews.org) and [jupyter_bokeh](https://github.com/bokeh/jupyter_bokeh).\n",
+    "\n",
+    "To install them, delete the triple quotations on lines 1&3 from below cell and install with pip:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "'\\n!pip install hvplot geoviews jupyter_bokeh\\n'"
+      ]
+     },
+     "execution_count": 2,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "\"\"\"\n",
+    "!pip install hvplot geoviews jupyter_bokeh\n",
+    "\"\"\""
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "application/javascript": "(function(root) {\n  function now() {\n    return new Date();\n  }\n\n  var force = true;\n  var py_version = '3.3.1'.replace('rc', '-rc.').replace('.dev', '-dev.');\n  var reloading = false;\n  var Bokeh = root.Bokeh;\n\n  if (typeof (root._bokeh_timeout) === \"undefined\" || force) {\n    root._bokeh_timeout = Date.now() + 5000;\n    root._bokeh_failed_load = false;\n  }\n\n  function run_callbacks() {\n    try {\n      root._bokeh_onload_callbacks.forEach(function(callback) {\n        if (callback != null)\n          callback();\n      });\n    } finally {\n      delete root._bokeh_onload_callbacks;\n    }\n    console.debug(\"Bokeh: all callbacks have finished\");\n  }\n\n  function load_libs(css_urls, js_urls, js_modules, js_exports, callback) {\n    if (css_urls == null) css_urls = [];\n    if (js_urls == null) js_urls = [];\n    if (js_modules == null) js_modules = [];\n    if (js_exports == null) js_exports = {};\n\n    root._bokeh_onload_callbacks.push(callback);\n\n    if (root._bokeh_is_loading > 0) {\n      console.debug(\"Bokeh: BokehJS is being loaded, scheduling callback at\", now());\n      return null;\n    }\n    if (js_urls.length === 0 && js_modules.length === 0 && Object.keys(js_exports).length === 0) {\n      run_callbacks();\n      return null;\n    }\n    if (!reloading) {\n      console.debug(\"Bokeh: BokehJS not loaded, scheduling load and callback at\", now());\n    }\n\n    function on_load() {\n      root._bokeh_is_loading--;\n      if (root._bokeh_is_loading === 0) {\n        console.debug(\"Bokeh: all BokehJS libraries/stylesheets loaded\");\n        run_callbacks()\n      }\n    }\n    window._bokeh_on_load = on_load\n\n    function on_error() {\n      console.error(\"failed to load \" + url);\n    }\n\n    var skip = [];\n    if (window.requirejs) {\n      window.requirejs.config({'packages': {}, 'paths': {'jspanel': 'https://cdn.jsdelivr.net/npm/jspanel4@4.12.0/dist/jspanel', 'jspanel-modal': 'https://cdn.jsdelivr.net/npm/jspanel4@4.12.0/dist/extensions/modal/jspanel.modal', 'jspanel-tooltip': 'https://cdn.jsdelivr.net/npm/jspanel4@4.12.0/dist/extensions/tooltip/jspanel.tooltip', 'jspanel-hint': 'https://cdn.jsdelivr.net/npm/jspanel4@4.12.0/dist/extensions/hint/jspanel.hint', 'jspanel-layout': 'https://cdn.jsdelivr.net/npm/jspanel4@4.12.0/dist/extensions/layout/jspanel.layout', 'jspanel-contextmenu': 'https://cdn.jsdelivr.net/npm/jspanel4@4.12.0/dist/extensions/contextmenu/jspanel.contextmenu', 'jspanel-dock': 'https://cdn.jsdelivr.net/npm/jspanel4@4.12.0/dist/extensions/dock/jspanel.dock', 'gridstack': 'https://cdn.jsdelivr.net/npm/gridstack@7.2.3/dist/gridstack-all', 'notyf': 'https://cdn.jsdelivr.net/npm/notyf@3/notyf.min'}, 'shim': {'jspanel': {'exports': 'jsPanel'}, 'gridstack': {'exports': 'GridStack'}}});\n      require([\"jspanel\"], function(jsPanel) {\n\twindow.jsPanel = jsPanel\n\ton_load()\n      })\n      require([\"jspanel-modal\"], function() {\n\ton_load()\n      })\n      require([\"jspanel-tooltip\"], function() {\n\ton_load()\n      })\n      require([\"jspanel-hint\"], function() {\n\ton_load()\n      })\n      require([\"jspanel-layout\"], function() {\n\ton_load()\n      })\n      require([\"jspanel-contextmenu\"], function() {\n\ton_load()\n      })\n      require([\"jspanel-dock\"], function() {\n\ton_load()\n      })\n      require([\"gridstack\"], function(GridStack) {\n\twindow.GridStack = GridStack\n\ton_load()\n      })\n      require([\"notyf\"], function() {\n\ton_load()\n      })\n      root._bokeh_is_loading = css_urls.length + 9;\n    } else {\n      root._bokeh_is_loading = css_urls.length + js_urls.length + js_modules.length + Object.keys(js_exports).length;\n    }\n\n    var existing_stylesheets = []\n    var links = document.getElementsByTagName('link')\n    for (var i = 0; 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i < urls.length; i++) {\n        skip.push(urls[i])\n      }\n    }    if (((window['GridStack'] !== undefined) && (!(window['GridStack'] instanceof HTMLElement))) || window.requirejs) {\n      var urls = ['https://cdn.holoviz.org/panel/1.3.8/dist/bundled/gridstack/gridstack@7.2.3/dist/gridstack-all.js'];\n      for (var i = 0; i < urls.length; i++) {\n        skip.push(urls[i])\n      }\n    }    if (((window['Notyf'] !== undefined) && (!(window['Notyf'] instanceof HTMLElement))) || window.requirejs) {\n      var urls = ['https://cdn.holoviz.org/panel/1.3.8/dist/bundled/notificationarea/notyf@3/notyf.min.js'];\n      for (var i = 0; i < urls.length; i++) {\n        skip.push(urls[i])\n      }\n    }    var existing_scripts = []\n    var scripts = document.getElementsByTagName('script')\n    for (var i = 0; i < scripts.length; i++) {\n      var script = scripts[i]\n      if (script.src != null) {\n\texisting_scripts.push(script.src)\n      }\n    }\n    for (var i = 0; i < js_urls.length; 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+      "application/vnd.holoviews_load.v0+json": ""
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<style>*[data-root-id],\n",
+       "*[data-root-id] > * {\n",
+       "  box-sizing: border-box;\n",
+       "  font-family: var(--jp-ui-font-family);\n",
+       "  font-size: var(--jp-ui-font-size1);\n",
+       "  color: var(--vscode-editor-foreground, var(--jp-ui-font-color1));\n",
+       "}\n",
+       "\n",
+       "/* Override VSCode background color */\n",
+       ".cell-output-ipywidget-background:has(\n",
+       "    > .cell-output-ipywidget-background > .lm-Widget > *[data-root-id]\n",
+       "  ),\n",
+       ".cell-output-ipywidget-background:has(> .lm-Widget > *[data-root-id]) {\n",
+       "  background-color: transparent !important;\n",
+       "}\n",
+       "</style>"
+      ]
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+      "text/html": [
+       "<div id='p1002'>\n",
+       "  <div id=\"d0da5d49-8242-4703-8625-054f76280595\" data-root-id=\"p1002\" style=\"display: contents;\"></div>\n",
+       "</div>\n",
+       "<script type=\"application/javascript\">(function(root) {\n",
+       "  var docs_json = {\"07abeadb-48ec-444e-bd76-de9a441f852c\":{\"version\":\"3.3.1\",\"title\":\"Bokeh Application\",\"roots\":[{\"type\":\"object\",\"name\":\"panel.models.browser.BrowserInfo\",\"id\":\"p1002\"},{\"type\":\"object\",\"name\":\"panel.models.comm_manager.CommManager\",\"id\":\"p1003\",\"attributes\":{\"plot_id\":\"p1002\",\"comm_id\":\"d4341de136b74006a326c4f4c8f6fa86\",\"client_comm_id\":\"b5fa3072d05c41d398146e05a21a8a43\"}}],\"defs\":[{\"type\":\"model\",\"name\":\"ReactiveHTML1\"},{\"type\":\"model\",\"name\":\"FlexBox1\",\"properties\":[{\"name\":\"align_content\",\"kind\":\"Any\",\"default\":\"flex-start\"},{\"name\":\"align_items\",\"kind\":\"Any\",\"default\":\"flex-start\"},{\"name\":\"flex_direction\",\"kind\":\"Any\",\"default\":\"row\"},{\"name\":\"flex_wrap\",\"kind\":\"Any\",\"default\":\"wrap\"},{\"name\":\"justify_content\",\"kind\":\"Any\",\"default\":\"flex-start\"}]},{\"type\":\"model\",\"name\":\"FloatPanel1\",\"properties\":[{\"name\":\"config\",\"kind\":\"Any\",\"default\":{\"type\":\"map\"}},{\"name\":\"contained\",\"kind\":\"Any\",\"default\":true},{\"name\":\"position\",\"kind\":\"Any\",\"default\":\"right-top\"},{\"name\":\"offsetx\",\"kind\":\"Any\",\"default\":null},{\"name\":\"offsety\",\"kind\":\"Any\",\"default\":null},{\"name\":\"theme\",\"kind\":\"Any\",\"default\":\"primary\"},{\"name\":\"status\",\"kind\":\"Any\",\"default\":\"normalized\"}]},{\"type\":\"model\",\"name\":\"GridStack1\",\"properties\":[{\"name\":\"mode\",\"kind\":\"Any\",\"default\":\"warn\"},{\"name\":\"ncols\",\"kind\":\"Any\",\"default\":null},{\"name\":\"nrows\",\"kind\":\"Any\",\"default\":null},{\"name\":\"allow_resize\",\"kind\":\"Any\",\"default\":true},{\"name\":\"allow_drag\",\"kind\":\"Any\",\"default\":true},{\"name\":\"state\",\"kind\":\"Any\",\"default\":[]}]},{\"type\":\"model\",\"name\":\"drag1\",\"properties\":[{\"name\":\"slider_width\",\"kind\":\"Any\",\"default\":5},{\"name\":\"slider_color\",\"kind\":\"Any\",\"default\":\"black\"},{\"name\":\"value\",\"kind\":\"Any\",\"default\":50}]},{\"type\":\"model\",\"name\":\"click1\",\"properties\":[{\"name\":\"terminal_output\",\"kind\":\"Any\",\"default\":\"\"},{\"name\":\"debug_name\",\"kind\":\"Any\",\"default\":\"\"},{\"name\":\"clears\",\"kind\":\"Any\",\"default\":0}]},{\"type\":\"model\",\"name\":\"copy_to_clipboard1\",\"properties\":[{\"name\":\"fill\",\"kind\":\"Any\",\"default\":\"none\"},{\"name\":\"value\",\"kind\":\"Any\",\"default\":null}]},{\"type\":\"model\",\"name\":\"FastWrapper1\",\"properties\":[{\"name\":\"object\",\"kind\":\"Any\",\"default\":null},{\"name\":\"style\",\"kind\":\"Any\",\"default\":null}]},{\"type\":\"model\",\"name\":\"NotificationAreaBase1\",\"properties\":[{\"name\":\"js_events\",\"kind\":\"Any\",\"default\":{\"type\":\"map\"}},{\"name\":\"position\",\"kind\":\"Any\",\"default\":\"bottom-right\"},{\"name\":\"_clear\",\"kind\":\"Any\",\"default\":0}]},{\"type\":\"model\",\"name\":\"NotificationArea1\",\"properties\":[{\"name\":\"js_events\",\"kind\":\"Any\",\"default\":{\"type\":\"map\"}},{\"name\":\"notifications\",\"kind\":\"Any\",\"default\":[]},{\"name\":\"position\",\"kind\":\"Any\",\"default\":\"bottom-right\"},{\"name\":\"_clear\",\"kind\":\"Any\",\"default\":0},{\"name\":\"types\",\"kind\":\"Any\",\"default\":[{\"type\":\"map\",\"entries\":[[\"type\",\"warning\"],[\"background\",\"#ffc107\"],[\"icon\",{\"type\":\"map\",\"entries\":[[\"className\",\"fas fa-exclamation-triangle\"],[\"tagName\",\"i\"],[\"color\",\"white\"]]}]]},{\"type\":\"map\",\"entries\":[[\"type\",\"info\"],[\"background\",\"#007bff\"],[\"icon\",{\"type\":\"map\",\"entries\":[[\"className\",\"fas fa-info-circle\"],[\"tagName\",\"i\"],[\"color\",\"white\"]]}]]}]}]},{\"type\":\"model\",\"name\":\"Notification\",\"properties\":[{\"name\":\"background\",\"kind\":\"Any\",\"default\":null},{\"name\":\"duration\",\"kind\":\"Any\",\"default\":3000},{\"name\":\"icon\",\"kind\":\"Any\",\"default\":null},{\"name\":\"message\",\"kind\":\"Any\",\"default\":\"\"},{\"name\":\"notification_type\",\"kind\":\"Any\",\"default\":null},{\"name\":\"_destroyed\",\"kind\":\"Any\",\"default\":false}]},{\"type\":\"model\",\"name\":\"TemplateActions1\",\"properties\":[{\"name\":\"open_modal\",\"kind\":\"Any\",\"default\":0},{\"name\":\"close_modal\",\"kind\":\"Any\",\"default\":0}]},{\"type\":\"model\",\"name\":\"BootstrapTemplateActions1\",\"properties\":[{\"name\":\"open_modal\",\"kind\":\"Any\",\"default\":0},{\"name\":\"close_modal\",\"kind\":\"Any\",\"default\":0}]},{\"type\":\"model\",\"name\":\"MaterialTemplateActions1\",\"properties\":[{\"name\":\"open_modal\",\"kind\":\"Any\",\"default\":0},{\"name\":\"close_modal\",\"kind\":\"Any\",\"default\":0}]}]}};\n",
+       "  var render_items = [{\"docid\":\"07abeadb-48ec-444e-bd76-de9a441f852c\",\"roots\":{\"p1002\":\"d0da5d49-8242-4703-8625-054f76280595\"},\"root_ids\":[\"p1002\"]}];\n",
+       "  var docs = Object.values(docs_json)\n",
+       "  if (!docs) {\n",
+       "    return\n",
+       "  }\n",
+       "  const py_version = docs[0].version.replace('rc', '-rc.').replace('.dev', '-dev.')\n",
+       "  function embed_document(root) {\n",
+       "    var Bokeh = get_bokeh(root)\n",
+       "    Bokeh.embed.embed_items_notebook(docs_json, render_items);\n",
+       "    for (const render_item of render_items) {\n",
+       "      for (const root_id of render_item.root_ids) {\n",
+       "\tconst id_el = document.getElementById(root_id)\n",
+       "\tif (id_el.children.length && (id_el.children[0].className === 'bk-root')) {\n",
+       "\t  const root_el = id_el.children[0]\n",
+       "\t  root_el.id = root_el.id + '-rendered'\n",
+       "\t}\n",
+       "      }\n",
+       "    }\n",
+       "  }\n",
+       "  function get_bokeh(root) {\n",
+       "    if (root.Bokeh === undefined) {\n",
+       "      return null\n",
+       "    } else if (root.Bokeh.version !== py_version) {\n",
+       "      if (root.Bokeh.versions === undefined || !root.Bokeh.versions.has(py_version)) {\n",
+       "\treturn null\n",
+       "      }\n",
+       "      return root.Bokeh.versions.get(py_version);\n",
+       "    } else if (root.Bokeh.version === py_version) {\n",
+       "      return root.Bokeh\n",
+       "    }\n",
+       "    return null\n",
+       "  }\n",
+       "  function is_loaded(root) {\n",
+       "    var Bokeh = get_bokeh(root)\n",
+       "    return (Bokeh != null && Bokeh.Panel !== undefined)\n",
+       "  }\n",
+       "  if (is_loaded(root)) {\n",
+       "    embed_document(root);\n",
+       "  } else {\n",
+       "    var attempts = 0;\n",
+       "    var timer = setInterval(function(root) {\n",
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+       "        clearInterval(timer);\n",
+       "        embed_document(root);\n",
+       "      } else if (document.readyState == \"complete\") {\n",
+       "        attempts++;\n",
+       "        if (attempts > 200) {\n",
+       "          clearInterval(timer);\n",
+       "\t  var Bokeh = get_bokeh(root)\n",
+       "\t  if (Bokeh == null || Bokeh.Panel == null) {\n",
+       "            console.warn(\"Panel: ERROR: Unable to run Panel code because Bokeh or Panel library is missing\");\n",
+       "\t  } else {\n",
+       "\t    console.warn(\"Panel: WARNING: Attempting to render but not all required libraries could be resolved.\")\n",
+       "\t    embed_document(root)\n",
+       "\t  }\n",
+       "        }\n",
+       "      }\n",
+       "    }, 25, root)\n",
+       "  }\n",
+       "})(window);</script>"
+      ]
+     },
+     "metadata": {
+      "application/vnd.holoviews_exec.v0+json": {
+       "id": "p1002"
+      }
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "import hvplot.xarray"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## 2. Data\n",
+    "\n",
+    "### 2.1 Model output data\n",
+    "\n",
+    "#### 2.1.1 Load dataset\n",
+    "\n",
+    "This demo uses one of CMIP6 models -- E3SM-1-0. The Sea-Ice Area Percentage (Ocean Grid; 'siconc') and Grid-Cell Area for Ocean Variables ('areacello') variables are needed and can be found in the following directories. In addition, six other models are available that can be added to the analyses in this demo:\n",
+    "```\n",
+    "/p/user_pub/pmp/demo/sea-ice/links_siconc\n",
+    "/p/user_pub/pmp/demo/sea-ice/links_area\n",
+    "```\n",
+    "\n",
+    "This data can be found from ESGF (https://esgf-node.llnl.gov/). \n",
+    "- e.g., Search query: https://aims2.llnl.gov/search?project=CMIP6&activeFacets={\"experiment_id\":\"historical\",\"variable_id\":\"siconc\"}"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "siconc_SImon_E3SM-1-0_historical_r1i2p2f1_gr_185001-185912.nc\n",
+      "siconc_SImon_E3SM-1-0_historical_r1i2p2f1_gr_186001-186912.nc\n",
+      "siconc_SImon_E3SM-1-0_historical_r1i2p2f1_gr_187001-187912.nc\n",
+      "siconc_SImon_E3SM-1-0_historical_r1i2p2f1_gr_188001-188912.nc\n",
+      "siconc_SImon_E3SM-1-0_historical_r1i2p2f1_gr_189001-189912.nc\n",
+      "siconc_SImon_E3SM-1-0_historical_r1i2p2f1_gr_190001-190912.nc\n",
+      "siconc_SImon_E3SM-1-0_historical_r1i2p2f1_gr_191001-191912.nc\n",
+      "siconc_SImon_E3SM-1-0_historical_r1i2p2f1_gr_192001-192912.nc\n",
+      "siconc_SImon_E3SM-1-0_historical_r1i2p2f1_gr_193001-193912.nc\n",
+      "siconc_SImon_E3SM-1-0_historical_r1i2p2f1_gr_194001-194912.nc\n",
+      "siconc_SImon_E3SM-1-0_historical_r1i2p2f1_gr_195001-195912.nc\n",
+      "siconc_SImon_E3SM-1-0_historical_r1i2p2f1_gr_196001-196912.nc\n",
+      "siconc_SImon_E3SM-1-0_historical_r1i2p2f1_gr_197001-197912.nc\n",
+      "siconc_SImon_E3SM-1-0_historical_r1i2p2f1_gr_198001-198912.nc\n",
+      "siconc_SImon_E3SM-1-0_historical_r1i2p2f1_gr_199001-199912.nc\n",
+      "siconc_SImon_E3SM-1-0_historical_r1i2p2f1_gr_200001-200912.nc\n",
+      "siconc_SImon_E3SM-1-0_historical_r1i2p2f1_gr_201001-201112.nc\n"
+     ]
+    }
+   ],
+   "source": [
+    "!ls /p/user_pub/pmp/demo/sea-ice/links_siconc/E3SM-1-0/historical/r1i2p2f1/siconc"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "areacello_Ofx_E3SM-1-0_historical_r1i1p1f1_gr.nc\n"
+     ]
+    }
+   ],
+   "source": [
+    "!ls /p/user_pub/pmp/demo/sea-ice/links_area/E3SM-1-0/"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "2024-01-29 11:20:48,263 [WARNING]: dataset.py(open_dataset:109) >> \"No time coordinates were found in this dataset to decode. If time coordinates were expected to exist, make sure they are detectable by setting the CF 'axis' or 'standard_name' attribute (e.g., ds['time'].attrs['axis'] = 'T' or ds['time'].attrs['standard_name'] = 'time'). Afterwards, try decoding again with `xcdat.decode_time`.\"\n"
+     ]
+    }
+   ],
+   "source": [
+    "# Load model dataset\n",
+    "ds = xc.open_mfdataset(\n",
+    "    \"/p/user_pub/pmp/demo/sea-ice/links_siconc/E3SM-1-0/historical/r1i2p2f1/siconc/siconc_SImon_E3SM-1-0_historical_r1i2p2f1_*_*.nc\"\n",
+    ")\n",
+    "area = xc.open_dataset(\n",
+    "    \"/p/user_pub/pmp/demo/sea-ice/links_area/E3SM-1-0/areacello_Ofx_E3SM-1-0_historical_r1i1p1f1_gr.nc\"\n",
+    ")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "See what is in the dataset:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
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+       "\n",
+       ".xr-array-in:checked ~ .xr-array-data,\n",
+       ".xr-array-preview {\n",
+       "  display: inline-block;\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list {\n",
+       "  display: inline-block !important;\n",
+       "  list-style: none;\n",
+       "  padding: 0 !important;\n",
+       "  margin: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list li {\n",
+       "  display: inline-block;\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list:before {\n",
+       "  content: '(';\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list:after {\n",
+       "  content: ')';\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list li:not(:last-child):after {\n",
+       "  content: ',';\n",
+       "  padding-right: 5px;\n",
+       "}\n",
+       "\n",
+       ".xr-has-index {\n",
+       "  font-weight: bold;\n",
+       "}\n",
+       "\n",
+       ".xr-var-list,\n",
+       ".xr-var-item {\n",
+       "  display: contents;\n",
+       "}\n",
+       "\n",
+       ".xr-var-item > div,\n",
+       ".xr-var-item label,\n",
+       ".xr-var-item > .xr-var-name span {\n",
+       "  background-color: var(--xr-background-color-row-even);\n",
+       "  margin-bottom: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-var-item > .xr-var-name:hover span {\n",
+       "  padding-right: 5px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-list > li:nth-child(odd) > div,\n",
+       ".xr-var-list > li:nth-child(odd) > label,\n",
+       ".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
+       "  background-color: var(--xr-background-color-row-odd);\n",
+       "}\n",
+       "\n",
+       ".xr-var-name {\n",
+       "  grid-column: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-var-dims {\n",
+       "  grid-column: 2;\n",
+       "}\n",
+       "\n",
+       ".xr-var-dtype {\n",
+       "  grid-column: 3;\n",
+       "  text-align: right;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-var-preview {\n",
+       "  grid-column: 4;\n",
+       "}\n",
+       "\n",
+       ".xr-index-preview {\n",
+       "  grid-column: 2 / 5;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-var-name,\n",
+       ".xr-var-dims,\n",
+       ".xr-var-dtype,\n",
+       ".xr-preview,\n",
+       ".xr-attrs dt {\n",
+       "  white-space: nowrap;\n",
+       "  overflow: hidden;\n",
+       "  text-overflow: ellipsis;\n",
+       "  padding-right: 10px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-name:hover,\n",
+       ".xr-var-dims:hover,\n",
+       ".xr-var-dtype:hover,\n",
+       ".xr-attrs dt:hover {\n",
+       "  overflow: visible;\n",
+       "  width: auto;\n",
+       "  z-index: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs,\n",
+       ".xr-var-data,\n",
+       ".xr-index-data {\n",
+       "  display: none;\n",
+       "  background-color: var(--xr-background-color) !important;\n",
+       "  padding-bottom: 5px !important;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
+       ".xr-var-data-in:checked ~ .xr-var-data,\n",
+       ".xr-index-data-in:checked ~ .xr-index-data {\n",
+       "  display: block;\n",
+       "}\n",
+       "\n",
+       ".xr-var-data > table {\n",
+       "  float: right;\n",
+       "}\n",
+       "\n",
+       ".xr-var-name span,\n",
+       ".xr-var-data,\n",
+       ".xr-index-name div,\n",
+       ".xr-index-data,\n",
+       ".xr-attrs {\n",
+       "  padding-left: 25px !important;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs,\n",
+       ".xr-var-attrs,\n",
+       ".xr-var-data,\n",
+       ".xr-index-data {\n",
+       "  grid-column: 1 / -1;\n",
+       "}\n",
+       "\n",
+       "dl.xr-attrs {\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "  display: grid;\n",
+       "  grid-template-columns: 125px auto;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt,\n",
+       ".xr-attrs dd {\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "  float: left;\n",
+       "  padding-right: 10px;\n",
+       "  width: auto;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt {\n",
+       "  font-weight: normal;\n",
+       "  grid-column: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt:hover span {\n",
+       "  display: inline-block;\n",
+       "  background: var(--xr-background-color);\n",
+       "  padding-right: 10px;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dd {\n",
+       "  grid-column: 2;\n",
+       "  white-space: pre-wrap;\n",
+       "  word-break: break-all;\n",
+       "}\n",
+       "\n",
+       ".xr-icon-database,\n",
+       ".xr-icon-file-text2,\n",
+       ".xr-no-icon {\n",
+       "  display: inline-block;\n",
+       "  vertical-align: middle;\n",
+       "  width: 1em;\n",
+       "  height: 1.5em !important;\n",
+       "  stroke-width: 0;\n",
+       "  stroke: currentColor;\n",
+       "  fill: currentColor;\n",
+       "}\n",
+       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt;\n",
+       "Dimensions:    (time: 1944, bnds: 2, lat: 180, lon: 360)\n",
+       "Coordinates:\n",
+       "  * lat        (lat) float64 -89.5 -88.5 -87.5 -86.5 ... 86.5 87.5 88.5 89.5\n",
+       "  * lon        (lon) float64 0.5 1.5 2.5 3.5 4.5 ... 356.5 357.5 358.5 359.5\n",
+       "    type       |S7 b&#x27;sea_ice&#x27;\n",
+       "  * time       (time) object 1850-01-16 12:00:00 ... 2011-12-16 12:00:00\n",
+       "Dimensions without coordinates: bnds\n",
+       "Data variables:\n",
+       "    time_bnds  (time, bnds) object dask.array&lt;chunksize=(1, 2), meta=np.ndarray&gt;\n",
+       "    lat_bnds   (lat, bnds) float64 dask.array&lt;chunksize=(180, 2), meta=np.ndarray&gt;\n",
+       "    lon_bnds   (lon, bnds) float64 dask.array&lt;chunksize=(360, 2), meta=np.ndarray&gt;\n",
+       "    siconc     (time, lat, lon) float32 dask.array&lt;chunksize=(1, 180, 360), meta=np.ndarray&gt;\n",
+       "Attributes: (12/48)\n",
+       "    Conventions:            CF-1.7 CMIP-6.2\n",
+       "    activity_id:            CMIP\n",
+       "    branch_method:          standard\n",
+       "    branch_time_in_child:   0.0\n",
+       "    creation_date:          2023-01-30T21:36:30Z\n",
+       "    data contact:           Sam Stevenson (sstevenson@ucsb.edu)\n",
+       "    ...                     ...\n",
+       "    variant_label:          r1i2p2f1\n",
+       "    license:                CMIP6 model data produced by E3SM-Project is lice...\n",
+       "    cmor_version:           3.7.0\n",
+       "    references:             Stevenson, S., Huang, X., Zhao, Y., Di Lorenzo, E...\n",
+       "    version:                v20230811\n",
+       "    branch_time_in_parent:  3560.0</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-70b7f6de-7f79-4a11-ac25-86cab82763dd' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-70b7f6de-7f79-4a11-ac25-86cab82763dd' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>time</span>: 1944</li><li><span>bnds</span>: 2</li><li><span class='xr-has-index'>lat</span>: 180</li><li><span class='xr-has-index'>lon</span>: 360</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-e547bcb3-a5f1-4ed6-88cf-ecd616a0951d' class='xr-section-summary-in' type='checkbox'  checked><label for='section-e547bcb3-a5f1-4ed6-88cf-ecd616a0951d' 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'>-89.5 -88.5 -87.5 ... 88.5 89.5</div><input id='attrs-87033bac-60b1-4172-b1da-73b3941e9a1a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-87033bac-60b1-4172-b1da-73b3941e9a1a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c051e0d3-8de9-4e81-b132-ce881f3f8c37' class='xr-var-data-in' type='checkbox'><label for='data-c051e0d3-8de9-4e81-b132-ce881f3f8c37' 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>bounds :</span></dt><dd>lat_bnds</dd><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>axis :</span></dt><dd>Y</dd><dt><span>long_name :</span></dt><dd>Latitude</dd><dt><span>standard_name :</span></dt><dd>latitude</dd></dl></div><div class='xr-var-data'><pre>array([-89.5, -88.5, -87.5, -86.5, -85.5, -84.5, -83.5, -82.5, -81.5, -80.5,\n",
+       "       -79.5, -78.5, -77.5, -76.5, -75.5, -74.5, -73.5, -72.5, -71.5, -70.5,\n",
+       "       -69.5, -68.5, -67.5, -66.5, -65.5, -64.5, -63.5, -62.5, -61.5, -60.5,\n",
+       "       -59.5, -58.5, -57.5, -56.5, -55.5, -54.5, -53.5, -52.5, -51.5, -50.5,\n",
+       "       -49.5, -48.5, -47.5, -46.5, -45.5, -44.5, -43.5, -42.5, -41.5, -40.5,\n",
+       "       -39.5, -38.5, -37.5, -36.5, -35.5, -34.5, -33.5, -32.5, -31.5, -30.5,\n",
+       "       -29.5, -28.5, -27.5, -26.5, -25.5, -24.5, -23.5, -22.5, -21.5, -20.5,\n",
+       "       -19.5, -18.5, -17.5, -16.5, -15.5, -14.5, -13.5, -12.5, -11.5, -10.5,\n",
+       "        -9.5,  -8.5,  -7.5,  -6.5,  -5.5,  -4.5,  -3.5,  -2.5,  -1.5,  -0.5,\n",
+       "         0.5,   1.5,   2.5,   3.5,   4.5,   5.5,   6.5,   7.5,   8.5,   9.5,\n",
+       "        10.5,  11.5,  12.5,  13.5,  14.5,  15.5,  16.5,  17.5,  18.5,  19.5,\n",
+       "        20.5,  21.5,  22.5,  23.5,  24.5,  25.5,  26.5,  27.5,  28.5,  29.5,\n",
+       "        30.5,  31.5,  32.5,  33.5,  34.5,  35.5,  36.5,  37.5,  38.5,  39.5,\n",
+       "        40.5,  41.5,  42.5,  43.5,  44.5,  45.5,  46.5,  47.5,  48.5,  49.5,\n",
+       "        50.5,  51.5,  52.5,  53.5,  54.5,  55.5,  56.5,  57.5,  58.5,  59.5,\n",
+       "        60.5,  61.5,  62.5,  63.5,  64.5,  65.5,  66.5,  67.5,  68.5,  69.5,\n",
+       "        70.5,  71.5,  72.5,  73.5,  74.5,  75.5,  76.5,  77.5,  78.5,  79.5,\n",
+       "        80.5,  81.5,  82.5,  83.5,  84.5,  85.5,  86.5,  87.5,  88.5,  89.5])</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'>0.5 1.5 2.5 ... 357.5 358.5 359.5</div><input id='attrs-0768718e-1aed-453f-8f8f-f9bd1c42721c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-0768718e-1aed-453f-8f8f-f9bd1c42721c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-eda5f15e-db5a-418c-beaf-667df3bd98c1' class='xr-var-data-in' type='checkbox'><label for='data-eda5f15e-db5a-418c-beaf-667df3bd98c1' 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>bounds :</span></dt><dd>lon_bnds</dd><dt><span>units :</span></dt><dd>degrees_east</dd><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></dl></div><div class='xr-var-data'><pre>array([  0.5,   1.5,   2.5, ..., 357.5, 358.5, 359.5])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>type</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>|S7</div><div class='xr-var-preview xr-preview'>b&#x27;sea_ice&#x27;</div><input id='attrs-420f1e5d-4ce9-4525-b1e3-9b64cdef32b6' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-420f1e5d-4ce9-4525-b1e3-9b64cdef32b6' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-dac536f6-b904-47df-a3d5-6f8cd7a6503b' class='xr-var-data-in' type='checkbox'><label for='data-dac536f6-b904-47df-a3d5-6f8cd7a6503b' 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>Sea Ice area type</dd><dt><span>standard_name :</span></dt><dd>area_type</dd></dl></div><div class='xr-var-data'><pre>array(b&#x27;sea_ice&#x27;, dtype=&#x27;|S7&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>1850-01-16 12:00:00 ... 2011-12-...</div><input id='attrs-2dc3715b-b1f8-4fba-bb84-62be49d3aef1' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-2dc3715b-b1f8-4fba-bb84-62be49d3aef1' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b2aa9742-16b8-426b-a50a-74f30f9a8c3a' class='xr-var-data-in' type='checkbox'><label for='data-b2aa9742-16b8-426b-a50a-74f30f9a8c3a' 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>bounds :</span></dt><dd>time_bnds</dd><dt><span>axis :</span></dt><dd>T</dd><dt><span>long_name :</span></dt><dd>time</dd><dt><span>standard_name :</span></dt><dd>time</dd></dl></div><div class='xr-var-data'><pre>array([cftime.DatetimeNoLeap(1850, 1, 16, 12, 0, 0, 0, has_year_zero=True),\n",
+       "       cftime.DatetimeNoLeap(1850, 2, 15, 0, 0, 0, 0, has_year_zero=True),\n",
+       "       cftime.DatetimeNoLeap(1850, 3, 16, 12, 0, 0, 0, has_year_zero=True),\n",
+       "       ...,\n",
+       "       cftime.DatetimeNoLeap(2011, 10, 16, 12, 0, 0, 0, has_year_zero=True),\n",
+       "       cftime.DatetimeNoLeap(2011, 11, 16, 0, 0, 0, 0, has_year_zero=True),\n",
+       "       cftime.DatetimeNoLeap(2011, 12, 16, 12, 0, 0, 0, has_year_zero=True)],\n",
+       "      dtype=object)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-4787ff80-5ea5-4e10-81f1-f5798e0a6d0c' class='xr-section-summary-in' type='checkbox'  checked><label for='section-4787ff80-5ea5-4e10-81f1-f5798e0a6d0c' 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>time_bnds</span></div><div class='xr-var-dims'>(time, bnds)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 2), meta=np.ndarray&gt;</div><input id='attrs-fd982fd2-0ae1-4afe-bd25-21d994d78b8f' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-fd982fd2-0ae1-4afe-bd25-21d994d78b8f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-742bdfa3-47ee-4e80-a04e-69e37887fa07' class='xr-var-data-in' type='checkbox'><label for='data-742bdfa3-47ee-4e80-a04e-69e37887fa07' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><table>\n",
+       "    <tr>\n",
+       "        <td>\n",
+       "            <table style=\"border-collapse: collapse;\">\n",
+       "                <thead>\n",
+       "                    <tr>\n",
+       "                        <td> </td>\n",
+       "                        <th> Array </th>\n",
+       "                        <th> Chunk </th>\n",
+       "                    </tr>\n",
+       "                </thead>\n",
+       "                <tbody>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 30.38 kiB </td>\n",
+       "                        <td> 16 B </td>\n",
+       "                    </tr>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Shape </th>\n",
+       "                        <td> (1944, 2) </td>\n",
+       "                        <td> (1, 2) </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 1944 chunks in 52 graph layers </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> object numpy.ndarray </td>\n",
+       "                    </tr>\n",
+       "                </tbody>\n",
+       "            </table>\n",
+       "        </td>\n",
+       "        <td>\n",
+       "        <svg width=\"75\" height=\"170\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
+       "\n",
+       "  <!-- Horizontal lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"25\" y2=\"0\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"0\" y1=\"6\" x2=\"25\" y2=\"6\" />\n",
+       "  <line x1=\"0\" y1=\"12\" x2=\"25\" y2=\"12\" />\n",
+       "  <line x1=\"0\" y1=\"18\" x2=\"25\" y2=\"18\" />\n",
+       "  <line x1=\"0\" y1=\"25\" x2=\"25\" y2=\"25\" />\n",
+       "  <line x1=\"0\" y1=\"31\" x2=\"25\" y2=\"31\" />\n",
+       "  <line x1=\"0\" y1=\"37\" x2=\"25\" y2=\"37\" />\n",
+       "  <line x1=\"0\" y1=\"44\" x2=\"25\" y2=\"44\" />\n",
+       "  <line x1=\"0\" y1=\"50\" x2=\"25\" y2=\"50\" />\n",
+       "  <line x1=\"0\" y1=\"56\" x2=\"25\" y2=\"56\" />\n",
+       "  <line x1=\"0\" y1=\"63\" x2=\"25\" y2=\"63\" />\n",
+       "  <line x1=\"0\" y1=\"69\" x2=\"25\" y2=\"69\" />\n",
+       "  <line x1=\"0\" y1=\"75\" x2=\"25\" y2=\"75\" />\n",
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+       "  <line x1=\"0\" y1=\"94\" x2=\"25\" y2=\"94\" />\n",
+       "  <line x1=\"0\" y1=\"101\" x2=\"25\" y2=\"101\" />\n",
+       "  <line x1=\"0\" y1=\"107\" x2=\"25\" y2=\"107\" />\n",
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+       "\n",
+       "  <!-- Vertical lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"0\" y2=\"120\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"25\" y1=\"0\" x2=\"25\" y2=\"120\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Colored Rectangle -->\n",
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+       "\n",
+       "  <!-- Text -->\n",
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+       "</svg>\n",
+       "        </td>\n",
+       "    </tr>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lat_bnds</span></div><div class='xr-var-dims'>(lat, bnds)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(180, 2), meta=np.ndarray&gt;</div><input id='attrs-a8431729-8abd-454f-bf3e-1afde803b1af' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-a8431729-8abd-454f-bf3e-1afde803b1af' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d183d98d-418b-49e9-ae39-1f5bdbfb9419' class='xr-var-data-in' type='checkbox'><label for='data-d183d98d-418b-49e9-ae39-1f5bdbfb9419' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><table>\n",
+       "    <tr>\n",
+       "        <td>\n",
+       "            <table style=\"border-collapse: collapse;\">\n",
+       "                <thead>\n",
+       "                    <tr>\n",
+       "                        <td> </td>\n",
+       "                        <th> Array </th>\n",
+       "                        <th> Chunk </th>\n",
+       "                    </tr>\n",
+       "                </thead>\n",
+       "                <tbody>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 2.81 kiB </td>\n",
+       "                        <td> 2.81 kiB </td>\n",
+       "                    </tr>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Shape </th>\n",
+       "                        <td> (180, 2) </td>\n",
+       "                        <td> (180, 2) </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 1 chunks in 80 graph layers </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> float64 numpy.ndarray </td>\n",
+       "                    </tr>\n",
+       "                </tbody>\n",
+       "            </table>\n",
+       "        </td>\n",
+       "        <td>\n",
+       "        <svg width=\"75\" height=\"170\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
+       "\n",
+       "  <!-- Horizontal lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"25\" y2=\"0\" style=\"stroke-width:2\" />\n",
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+       "\n",
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+       "\n",
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+       "  <!-- Text -->\n",
+       "  <text x=\"12.962080\" y=\"140.000000\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >2</text>\n",
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+       "</svg>\n",
+       "        </td>\n",
+       "    </tr>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lon_bnds</span></div><div class='xr-var-dims'>(lon, bnds)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(360, 2), meta=np.ndarray&gt;</div><input id='attrs-79fd468b-a8d3-4b62-87d9-ad558603724b' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-79fd468b-a8d3-4b62-87d9-ad558603724b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e5814e59-c4f4-4a89-910d-3fd05afc1b9e' class='xr-var-data-in' type='checkbox'><label for='data-e5814e59-c4f4-4a89-910d-3fd05afc1b9e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><table>\n",
+       "    <tr>\n",
+       "        <td>\n",
+       "            <table style=\"border-collapse: collapse;\">\n",
+       "                <thead>\n",
+       "                    <tr>\n",
+       "                        <td> </td>\n",
+       "                        <th> Array </th>\n",
+       "                        <th> Chunk </th>\n",
+       "                    </tr>\n",
+       "                </thead>\n",
+       "                <tbody>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 5.62 kiB </td>\n",
+       "                        <td> 5.62 kiB </td>\n",
+       "                    </tr>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Shape </th>\n",
+       "                        <td> (360, 2) </td>\n",
+       "                        <td> (360, 2) </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 1 chunks in 80 graph layers </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> float64 numpy.ndarray </td>\n",
+       "                    </tr>\n",
+       "                </tbody>\n",
+       "            </table>\n",
+       "        </td>\n",
+       "        <td>\n",
+       "        <svg width=\"75\" height=\"170\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
+       "\n",
+       "  <!-- Horizontal lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"25\" y2=\"0\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"0\" y1=\"120\" x2=\"25\" y2=\"120\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Vertical lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"0\" y2=\"120\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"25\" y1=\"0\" x2=\"25\" y2=\"120\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Colored Rectangle -->\n",
+       "  <polygon points=\"0.0,0.0 25.412616514582485,0.0 25.412616514582485,120.0 0.0,120.0\" style=\"fill:#ECB172A0;stroke-width:0\"/>\n",
+       "\n",
+       "  <!-- Text -->\n",
+       "  <text x=\"12.706308\" y=\"140.000000\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >2</text>\n",
+       "  <text x=\"45.412617\" y=\"60.000000\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(-90,45.412617,60.000000)\">360</text>\n",
+       "</svg>\n",
+       "        </td>\n",
+       "    </tr>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>siconc</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'>dask.array&lt;chunksize=(1, 180, 360), meta=np.ndarray&gt;</div><input id='attrs-a9b90488-5ec6-45c9-88bd-45260c11578b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a9b90488-5ec6-45c9-88bd-45260c11578b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-30008616-33d5-4909-bb67-b581a4586402' class='xr-var-data-in' type='checkbox'><label for='data-30008616-33d5-4909-bb67-b581a4586402' 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>sea_ice_area_fraction</dd><dt><span>long_name :</span></dt><dd>Sea-Ice Area Percentage (Ocean Grid)</dd><dt><span>comment :</span></dt><dd>Percentage of grid cell covered by sea ice</dd><dt><span>units :</span></dt><dd>%</dd><dt><span>cell_methods :</span></dt><dd>area: mean where sea time: mean</dd><dt><span>cell_measures :</span></dt><dd>area: areacello</dd><dt><span>history :</span></dt><dd>2023-01-30T21:36:30Z altered by CMOR: Treated scalar dimension: &#x27;type&#x27;. 2023-01-30T21:36:30Z altered by CMOR: replaced missing value flag (9.96921e+36) and corresponding data with standard missing value (1e+20).</dd></dl></div><div class='xr-var-data'><table>\n",
+       "    <tr>\n",
+       "        <td>\n",
+       "            <table style=\"border-collapse: collapse;\">\n",
+       "                <thead>\n",
+       "                    <tr>\n",
+       "                        <td> </td>\n",
+       "                        <th> Array </th>\n",
+       "                        <th> Chunk </th>\n",
+       "                    </tr>\n",
+       "                </thead>\n",
+       "                <tbody>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 480.54 MiB </td>\n",
+       "                        <td> 253.12 kiB </td>\n",
+       "                    </tr>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Shape </th>\n",
+       "                        <td> (1944, 180, 360) </td>\n",
+       "                        <td> (1, 180, 360) </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 1944 chunks in 35 graph layers </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
+       "                    </tr>\n",
+       "                </tbody>\n",
+       "            </table>\n",
+       "        </td>\n",
+       "        <td>\n",
+       "        <svg width=\"172\" height=\"158\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
+       "\n",
+       "  <!-- Horizontal lines -->\n",
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+       "\n",
+       "  <!-- Vertical lines -->\n",
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+       "\n",
+       "  <!-- Text -->\n",
+       "  <text x=\"101.427368\" y=\"128.754326\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >360</text>\n",
+       "  <text x=\"142.266502\" y=\"89.671280\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(-90,142.266502,89.671280)\">180</text>\n",
+       "  <text x=\"35.294118\" y=\"93.460208\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(45,35.294118,93.460208)\">1944</text>\n",
+       "</svg>\n",
+       "        </td>\n",
+       "    </tr>\n",
+       "</table></div></li></ul></div></li><li class='xr-section-item'><input id='section-b65a9a74-e9ff-442f-961d-8b14be110bc7' class='xr-section-summary-in' type='checkbox'  ><label for='section-b65a9a74-e9ff-442f-961d-8b14be110bc7' class='xr-section-summary' >Indexes: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>lat</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-b9c19e3f-bf64-4686-903c-3c3806dbb54e' class='xr-index-data-in' type='checkbox'/><label for='index-b9c19e3f-bf64-4686-903c-3c3806dbb54e' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([-89.5, -88.5, -87.5, -86.5, -85.5, -84.5, -83.5, -82.5, -81.5, -80.5,\n",
+       "       ...\n",
+       "        80.5,  81.5,  82.5,  83.5,  84.5,  85.5,  86.5,  87.5,  88.5,  89.5],\n",
+       "      dtype=&#x27;float64&#x27;, name=&#x27;lat&#x27;, length=180))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>lon</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-f55d5ffa-d99e-4b78-9e3b-bd24d6cccf71' class='xr-index-data-in' type='checkbox'/><label for='index-f55d5ffa-d99e-4b78-9e3b-bd24d6cccf71' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([  0.5,   1.5,   2.5,   3.5,   4.5,   5.5,   6.5,   7.5,   8.5,   9.5,\n",
+       "       ...\n",
+       "       350.5, 351.5, 352.5, 353.5, 354.5, 355.5, 356.5, 357.5, 358.5, 359.5],\n",
+       "      dtype=&#x27;float64&#x27;, name=&#x27;lon&#x27;, length=360))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>time</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-7654ed96-837d-4017-8061-09e4f34affa6' class='xr-index-data-in' type='checkbox'/><label for='index-7654ed96-837d-4017-8061-09e4f34affa6' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(CFTimeIndex([1850-01-16 12:00:00, 1850-02-15 00:00:00, 1850-03-16 12:00:00,\n",
+       "             1850-04-16 00:00:00, 1850-05-16 12:00:00, 1850-06-16 00:00:00,\n",
+       "             1850-07-16 12:00:00, 1850-08-16 12:00:00, 1850-09-16 00:00:00,\n",
+       "             1850-10-16 12:00:00,\n",
+       "             ...\n",
+       "             2011-03-16 12:00:00, 2011-04-16 00:00:00, 2011-05-16 12:00:00,\n",
+       "             2011-06-16 00:00:00, 2011-07-16 12:00:00, 2011-08-16 12:00:00,\n",
+       "             2011-09-16 00:00:00, 2011-10-16 12:00:00, 2011-11-16 00:00:00,\n",
+       "             2011-12-16 12:00:00],\n",
+       "            dtype=&#x27;object&#x27;, length=1944, calendar=&#x27;noleap&#x27;, freq=&#x27;None&#x27;))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-8f0ea04e-d800-47e5-8be1-c912017ebf5f' class='xr-section-summary-in' type='checkbox'  ><label for='section-8f0ea04e-d800-47e5-8be1-c912017ebf5f' class='xr-section-summary' >Attributes: <span>(48)</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-1.7 CMIP-6.2</dd><dt><span>activity_id :</span></dt><dd>CMIP</dd><dt><span>branch_method :</span></dt><dd>standard</dd><dt><span>branch_time_in_child :</span></dt><dd>0.0</dd><dt><span>creation_date :</span></dt><dd>2023-01-30T21:36:30Z</dd><dt><span>data contact :</span></dt><dd>Sam Stevenson (sstevenson@ucsb.edu)</dd><dt><span>data_specs_version :</span></dt><dd>01.00.33</dd><dt><span>experiment :</span></dt><dd>all-forcing simulation of the recent past</dd><dt><span>experiment_id :</span></dt><dd>historical</dd><dt><span>external_variables :</span></dt><dd>areacello</dd><dt><span>forcing_index :</span></dt><dd>1</dd><dt><span>frequency :</span></dt><dd>mon</dd><dt><span>further_info_url :</span></dt><dd>https://furtherinfo.es-doc.org/CMIP6.UCSB.E3SM-1-0.historical.none.r1i2p2f1</dd><dt><span>grid :</span></dt><dd>data regridded to a CMIP6 standard 1x1 degree lonxlat grid from the native grid using an area-average preserving method.</dd><dt><span>grid_label :</span></dt><dd>gr</dd><dt><span>history :</span></dt><dd>2023-01-30T21:36:30Z ;rewrote data to be consistent with CMIP for variable siconc found in table SImon.;\n",
+       "20191024.en1.LE_ens_1.ne30_oECv3_ICG.compy</dd><dt><span>initialization_index :</span></dt><dd>2</dd><dt><span>institution :</span></dt><dd>Bren School of Environmental Science and Management, University of California, Santa Barbara. Mailing address: c/o Samantha Stevenson, 2400 Bren Hall, University of California Santa Barbara, Santa Barbara, CA 93106, USA</dd><dt><span>institution_id :</span></dt><dd>UCSB</dd><dt><span>mip_era :</span></dt><dd>CMIP6</dd><dt><span>nominal_resolution :</span></dt><dd>100 km</dd><dt><span>parent_activity_id :</span></dt><dd>CMIP</dd><dt><span>parent_experiment_id :</span></dt><dd>piControl</dd><dt><span>parent_mip_era :</span></dt><dd>CMIP6</dd><dt><span>parent_source_id :</span></dt><dd>E3SM-1-0</dd><dt><span>parent_time_units :</span></dt><dd>days since 0001-01-01</dd><dt><span>parent_variant_label :</span></dt><dd>r1i1p1f1</dd><dt><span>physics_index :</span></dt><dd>2</dd><dt><span>product :</span></dt><dd>model-output</dd><dt><span>project PI :</span></dt><dd>Sam Stevenson (sstevenson@ucsb.edu), Emanuele Di Lorenzo (e.dilorenzo@brown.edu)</dd><dt><span>realization_index :</span></dt><dd>1</dd><dt><span>realm :</span></dt><dd>seaIce</dd><dt><span>source :</span></dt><dd>E3SM 1.0 (2018): \n",
+       "aerosol: MAM4 with resuspension, marine organics, and secondary organics (same grid as atmos)\n",
+       "atmos: EAM (v1.0, cubed sphere spectral-element grid; 5400 elements with p=3; 1 deg average grid spacing; 90 x 90 x 6 longitude/latitude/cubeface; 72 levels; top level 0.1 hPa)\n",
+       "atmosChem: Troposphere specified oxidants for aerosols. Stratosphere linearized interactive ozone (LINOZ v2) (same grid as atmos)\n",
+       "land: ELM (v1.0, cubed sphere spectral-element grid; 5400 elements with p=3; 1 deg average grid spacing; 90 x 90 x 6 longitude/latitude/cubeface; satellite phenology mode), MOSART (v1.0, 0.5 degree latitude/longitude grid)\n",
+       "landIce: none\n",
+       "ocean: MPAS-Ocean (v6.0, oEC60to30 unstructured SVTs mesh with 235160 cells and 714274 edges, variable resolution 60 km to 30 km; 60 levels; top grid cell 0-10 m)\n",
+       "ocnBgchem: none\n",
+       "seaIce: MPAS-Seaice (v6.0, same grid as ocean)</dd><dt><span>source_id :</span></dt><dd>E3SM-1-0</dd><dt><span>source_type :</span></dt><dd>AOGCM AER</dd><dt><span>sub_experiment :</span></dt><dd>none</dd><dt><span>sub_experiment_id :</span></dt><dd>none</dd><dt><span>table_id :</span></dt><dd>SImon</dd><dt><span>table_info :</span></dt><dd>Creation Date:(18 November 2020) MD5:926d66e1a62ce074375d24e09d01cc11</dd><dt><span>title :</span></dt><dd>E3SM-1-0 output prepared for CMIP6</dd><dt><span>tracking_id :</span></dt><dd>hdl:21.14100/695ad132-b79f-4393-a828-89c0647b31a8</dd><dt><span>variable_id :</span></dt><dd>siconc</dd><dt><span>variant_label :</span></dt><dd>r1i2p2f1</dd><dt><span>license :</span></dt><dd>CMIP6 model data produced by E3SM-Project is licensed under a Creative Commons Attribution 4.0 International License (https://creativecommons.org/licenses/by/4.0/). Consult https://pcmdi.llnl.gov/CMIP6/TermsOfUse for terms of use governing CMIP6 output, including citation requirements and proper acknowledgment. Further information about this data, including some limitations, can be found via the further_info_url (recorded as a global attribute in this file) and at https://pcmdi.llnl.gov/. The data producers and data providers make no warranty, either express or implied, including, but not limited to, warranties of merchantability and fitness for a particular purpose. All liabilities arising from the supply of the information (including any liability arising in negligence) are excluded to the fullest extent permitted by law.</dd><dt><span>cmor_version :</span></dt><dd>3.7.0</dd><dt><span>references :</span></dt><dd>Stevenson, S., Huang, X., Zhao, Y., Di Lorenzo, E., Newman, M., van Roekel, L., Xu, T., &amp; Capotondi, A. 2023: Ensemble Spread Behavior in Coupled Climate Models: Insights from the Energy Exascale Earth System Model version 1, JAMES</dd><dt><span>version :</span></dt><dd>v20230811</dd><dt><span>branch_time_in_parent :</span></dt><dd>3560.0</dd></dl></div></li></ul></div></div>"
+      ],
+      "text/plain": [
+       "<xarray.Dataset>\n",
+       "Dimensions:    (time: 1944, bnds: 2, lat: 180, lon: 360)\n",
+       "Coordinates:\n",
+       "  * lat        (lat) float64 -89.5 -88.5 -87.5 -86.5 ... 86.5 87.5 88.5 89.5\n",
+       "  * lon        (lon) float64 0.5 1.5 2.5 3.5 4.5 ... 356.5 357.5 358.5 359.5\n",
+       "    type       |S7 b'sea_ice'\n",
+       "  * time       (time) object 1850-01-16 12:00:00 ... 2011-12-16 12:00:00\n",
+       "Dimensions without coordinates: bnds\n",
+       "Data variables:\n",
+       "    time_bnds  (time, bnds) object dask.array<chunksize=(1, 2), meta=np.ndarray>\n",
+       "    lat_bnds   (lat, bnds) float64 dask.array<chunksize=(180, 2), meta=np.ndarray>\n",
+       "    lon_bnds   (lon, bnds) float64 dask.array<chunksize=(360, 2), meta=np.ndarray>\n",
+       "    siconc     (time, lat, lon) float32 dask.array<chunksize=(1, 180, 360), meta=np.ndarray>\n",
+       "Attributes: (12/48)\n",
+       "    Conventions:            CF-1.7 CMIP-6.2\n",
+       "    activity_id:            CMIP\n",
+       "    branch_method:          standard\n",
+       "    branch_time_in_child:   0.0\n",
+       "    creation_date:          2023-01-30T21:36:30Z\n",
+       "    data contact:           Sam Stevenson (sstevenson@ucsb.edu)\n",
+       "    ...                     ...\n",
+       "    variant_label:          r1i2p2f1\n",
+       "    license:                CMIP6 model data produced by E3SM-Project is lice...\n",
+       "    cmor_version:           3.7.0\n",
+       "    references:             Stevenson, S., Huang, X., Zhao, Y., Di Lorenzo, E...\n",
+       "    version:                v20230811\n",
+       "    branch_time_in_parent:  3560.0"
+      ]
+     },
+     "execution_count": 7,
+     "metadata": {},
+     "output_type": "execute_result"
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+   "source": [
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+   ]
+  },
+  {
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+   "execution_count": 8,
+   "metadata": {},
+   "outputs": [
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+       "  margin: 0;\n",
+       "  display: grid;\n",
+       "  grid-template-columns: 125px auto;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt,\n",
+       ".xr-attrs dd {\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "  float: left;\n",
+       "  padding-right: 10px;\n",
+       "  width: auto;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt {\n",
+       "  font-weight: normal;\n",
+       "  grid-column: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt:hover span {\n",
+       "  display: inline-block;\n",
+       "  background: var(--xr-background-color);\n",
+       "  padding-right: 10px;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dd {\n",
+       "  grid-column: 2;\n",
+       "  white-space: pre-wrap;\n",
+       "  word-break: break-all;\n",
+       "}\n",
+       "\n",
+       ".xr-icon-database,\n",
+       ".xr-icon-file-text2,\n",
+       ".xr-no-icon {\n",
+       "  display: inline-block;\n",
+       "  vertical-align: middle;\n",
+       "  width: 1em;\n",
+       "  height: 1.5em !important;\n",
+       "  stroke-width: 0;\n",
+       "  stroke: currentColor;\n",
+       "  fill: currentColor;\n",
+       "}\n",
+       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt;\n",
+       "Dimensions:    (lat: 180, bnds: 2, lon: 360)\n",
+       "Coordinates:\n",
+       "  * lat        (lat) float64 -89.5 -88.5 -87.5 -86.5 ... 86.5 87.5 88.5 89.5\n",
+       "  * lon        (lon) float64 0.5 1.5 2.5 3.5 4.5 ... 356.5 357.5 358.5 359.5\n",
+       "Dimensions without coordinates: bnds\n",
+       "Data variables:\n",
+       "    lat_bnds   (lat, bnds) float64 ...\n",
+       "    lon_bnds   (lon, bnds) float64 ...\n",
+       "    areacello  (lat, lon) float32 ...\n",
+       "Attributes: (12/46)\n",
+       "    Conventions:            CF-1.7 CMIP-6.2\n",
+       "    activity_id:            CMIP\n",
+       "    branch_method:          standard\n",
+       "    branch_time_in_child:   0.0\n",
+       "    branch_time_in_parent:  36500.0\n",
+       "    creation_date:          2021-01-28T04:40:15Z\n",
+       "    ...                     ...\n",
+       "    title:                  E3SM-1-0 output prepared for CMIP6\n",
+       "    tracking_id:            hdl:21.14100/aaa3a5b2-c4c4-4bf6-b7a3-b59915926fc0\n",
+       "    variable_id:            areacello\n",
+       "    variant_label:          r1i1p1f1\n",
+       "    license:                CMIP6 model data produced by E3SM is licensed und...\n",
+       "    cmor_version:           3.6.0</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-e73f52aa-e88c-416a-bbdc-10d041f84552' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-e73f52aa-e88c-416a-bbdc-10d041f84552' 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>: 180</li><li><span>bnds</span>: 2</li><li><span class='xr-has-index'>lon</span>: 360</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-c82ef0ac-8abb-4109-9b2e-aa084dc1626b' class='xr-section-summary-in' type='checkbox'  checked><label for='section-c82ef0ac-8abb-4109-9b2e-aa084dc1626b' 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 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'>-89.5 -88.5 -87.5 ... 88.5 89.5</div><input id='attrs-2a0ebb49-4350-49ed-bb87-e70bf3ea5af0' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-2a0ebb49-4350-49ed-bb87-e70bf3ea5af0' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-790b2c23-c8e9-4a52-ac03-619f503d4cf9' class='xr-var-data-in' type='checkbox'><label for='data-790b2c23-c8e9-4a52-ac03-619f503d4cf9' 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>bounds :</span></dt><dd>lat_bnds</dd><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>axis :</span></dt><dd>Y</dd><dt><span>long_name :</span></dt><dd>Latitude</dd><dt><span>standard_name :</span></dt><dd>latitude</dd></dl></div><div class='xr-var-data'><pre>array([-89.5, -88.5, -87.5, -86.5, -85.5, -84.5, -83.5, -82.5, -81.5, -80.5,\n",
+       "       -79.5, -78.5, -77.5, -76.5, -75.5, -74.5, -73.5, -72.5, -71.5, -70.5,\n",
+       "       -69.5, -68.5, -67.5, -66.5, -65.5, -64.5, -63.5, -62.5, -61.5, -60.5,\n",
+       "       -59.5, -58.5, -57.5, -56.5, -55.5, -54.5, -53.5, -52.5, -51.5, -50.5,\n",
+       "       -49.5, -48.5, -47.5, -46.5, -45.5, -44.5, -43.5, -42.5, -41.5, -40.5,\n",
+       "       -39.5, -38.5, -37.5, -36.5, -35.5, -34.5, -33.5, -32.5, -31.5, -30.5,\n",
+       "       -29.5, -28.5, -27.5, -26.5, -25.5, -24.5, -23.5, -22.5, -21.5, -20.5,\n",
+       "       -19.5, -18.5, -17.5, -16.5, -15.5, -14.5, -13.5, -12.5, -11.5, -10.5,\n",
+       "        -9.5,  -8.5,  -7.5,  -6.5,  -5.5,  -4.5,  -3.5,  -2.5,  -1.5,  -0.5,\n",
+       "         0.5,   1.5,   2.5,   3.5,   4.5,   5.5,   6.5,   7.5,   8.5,   9.5,\n",
+       "        10.5,  11.5,  12.5,  13.5,  14.5,  15.5,  16.5,  17.5,  18.5,  19.5,\n",
+       "        20.5,  21.5,  22.5,  23.5,  24.5,  25.5,  26.5,  27.5,  28.5,  29.5,\n",
+       "        30.5,  31.5,  32.5,  33.5,  34.5,  35.5,  36.5,  37.5,  38.5,  39.5,\n",
+       "        40.5,  41.5,  42.5,  43.5,  44.5,  45.5,  46.5,  47.5,  48.5,  49.5,\n",
+       "        50.5,  51.5,  52.5,  53.5,  54.5,  55.5,  56.5,  57.5,  58.5,  59.5,\n",
+       "        60.5,  61.5,  62.5,  63.5,  64.5,  65.5,  66.5,  67.5,  68.5,  69.5,\n",
+       "        70.5,  71.5,  72.5,  73.5,  74.5,  75.5,  76.5,  77.5,  78.5,  79.5,\n",
+       "        80.5,  81.5,  82.5,  83.5,  84.5,  85.5,  86.5,  87.5,  88.5,  89.5])</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'>0.5 1.5 2.5 ... 357.5 358.5 359.5</div><input id='attrs-6f519c71-3749-46e2-bc3c-51a6b539e9c3' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-6f519c71-3749-46e2-bc3c-51a6b539e9c3' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-557196bd-4d9b-460d-8141-3c53a3da5696' class='xr-var-data-in' type='checkbox'><label for='data-557196bd-4d9b-460d-8141-3c53a3da5696' 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>bounds :</span></dt><dd>lon_bnds</dd><dt><span>units :</span></dt><dd>degrees_east</dd><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></dl></div><div class='xr-var-data'><pre>array([  0.5,   1.5,   2.5, ..., 357.5, 358.5, 359.5])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-c3544d07-87a5-4e00-abe3-e09d4d3f4ec0' class='xr-section-summary-in' type='checkbox'  checked><label for='section-c3544d07-87a5-4e00-abe3-e09d4d3f4ec0' class='xr-section-summary' >Data variables: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>lat_bnds</span></div><div class='xr-var-dims'>(lat, bnds)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-abcd377a-070d-4a08-b896-1197577227e1' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-abcd377a-070d-4a08-b896-1197577227e1' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-000a4cb7-6836-49d4-b38e-c73cc42f975b' class='xr-var-data-in' type='checkbox'><label for='data-000a4cb7-6836-49d4-b38e-c73cc42f975b' 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>[360 values with dtype=float64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lon_bnds</span></div><div class='xr-var-dims'>(lon, bnds)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-fd144e9c-ca42-487b-9357-6c28a724e154' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-fd144e9c-ca42-487b-9357-6c28a724e154' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b785bd46-086f-43e2-be05-35117245247f' class='xr-var-data-in' type='checkbox'><label for='data-b785bd46-086f-43e2-be05-35117245247f' 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>[720 values with dtype=float64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>areacello</span></div><div class='xr-var-dims'>(lat, lon)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-35ed1cb9-83fa-4183-88b0-1ac91766f87a' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-35ed1cb9-83fa-4183-88b0-1ac91766f87a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-733a6a4a-cd1a-4fda-8aaf-d5911c244235' class='xr-var-data-in' type='checkbox'><label for='data-733a6a4a-cd1a-4fda-8aaf-d5911c244235' 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>cell_area</dd><dt><span>long_name :</span></dt><dd>Grid-Cell Area for Ocean Variables</dd><dt><span>comment :</span></dt><dd>Horizontal area of ocean grid cells</dd><dt><span>units :</span></dt><dd>m2</dd><dt><span>cell_methods :</span></dt><dd>area: sum</dd><dt><span>history :</span></dt><dd>2021-01-28T04:40:15Z altered by CMOR: replaced missing value flag (9.96921e+36) and corresponding data with standard missing value (1e+20).</dd></dl></div><div class='xr-var-data'><pre>[64800 values with dtype=float32]</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-7f7b0145-fbb2-4b80-93ed-26740ec3a530' class='xr-section-summary-in' type='checkbox'  ><label for='section-7f7b0145-fbb2-4b80-93ed-26740ec3a530' class='xr-section-summary' >Indexes: <span>(2)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>lat</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-aeaf8cd0-cfbb-4750-9427-10e62d52bc7a' class='xr-index-data-in' type='checkbox'/><label for='index-aeaf8cd0-cfbb-4750-9427-10e62d52bc7a' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([-89.5, -88.5, -87.5, -86.5, -85.5, -84.5, -83.5, -82.5, -81.5, -80.5,\n",
+       "       ...\n",
+       "        80.5,  81.5,  82.5,  83.5,  84.5,  85.5,  86.5,  87.5,  88.5,  89.5],\n",
+       "      dtype=&#x27;float64&#x27;, name=&#x27;lat&#x27;, length=180))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>lon</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-2295dc67-b1b1-4fac-a0f7-fab91cbeeafe' class='xr-index-data-in' type='checkbox'/><label for='index-2295dc67-b1b1-4fac-a0f7-fab91cbeeafe' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([  0.5,   1.5,   2.5,   3.5,   4.5,   5.5,   6.5,   7.5,   8.5,   9.5,\n",
+       "       ...\n",
+       "       350.5, 351.5, 352.5, 353.5, 354.5, 355.5, 356.5, 357.5, 358.5, 359.5],\n",
+       "      dtype=&#x27;float64&#x27;, name=&#x27;lon&#x27;, length=360))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-b7429660-2533-4beb-8d8c-2616abf4155a' class='xr-section-summary-in' type='checkbox'  ><label for='section-b7429660-2533-4beb-8d8c-2616abf4155a' class='xr-section-summary' >Attributes: <span>(46)</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-1.7 CMIP-6.2</dd><dt><span>activity_id :</span></dt><dd>CMIP</dd><dt><span>branch_method :</span></dt><dd>standard</dd><dt><span>branch_time_in_child :</span></dt><dd>0.0</dd><dt><span>branch_time_in_parent :</span></dt><dd>36500.0</dd><dt><span>creation_date :</span></dt><dd>2021-01-28T04:40:15Z</dd><dt><span>data contact :</span></dt><dd>E3SM-DATA-SUPPORT@LISTSERV.LLNL.GOV</dd><dt><span>data_specs_version :</span></dt><dd>01.00.31</dd><dt><span>experiment :</span></dt><dd>all-forcing simulation of the recent past</dd><dt><span>experiment_id :</span></dt><dd>historical</dd><dt><span>forcing_index :</span></dt><dd>1</dd><dt><span>frequency :</span></dt><dd>fx</dd><dt><span>further_info_url :</span></dt><dd>https://furtherinfo.es-doc.org/CMIP6.E3SM-Project.E3SM-1-0.historical.none.r1i1p1f1</dd><dt><span>grid :</span></dt><dd>data regridded to a CMIP6 standard 1x1 degree lonxlat grid from the native grid using an area-average preserving method.</dd><dt><span>grid_label :</span></dt><dd>gr</dd><dt><span>history :</span></dt><dd>2021-01-28T04:40:15Z ;rewrote data to be consistent with CMIP for variable areacello found in table Ofx.</dd><dt><span>initialization_index :</span></dt><dd>1</dd><dt><span>institution :</span></dt><dd>LLNL (Lawrence Livermore National Laboratory, Livermore, CA 94550, USA); ANL (Argonne National Laboratory, Argonne, IL 60439, USA); BNL (Brookhaven National Laboratory, Upton, NY 11973, USA); LANL (Los Alamos National Laboratory, Los Alamos, NM 87545, USA); LBNL (Lawrence Berkeley National Laboratory, Berkeley, CA 94720, USA); ORNL (Oak Ridge National Laboratory, Oak Ridge, TN 37831, USA); PNNL (Pacific Northwest National Laboratory, Richland, WA 99352, USA); SNL (Sandia National Laboratories, Albuquerque, NM 87185, USA). Mailing address: LLNL Climate Program, c/o David C. Bader, Principal Investigator, L-103, 7000 East Avenue, Livermore, CA 94550, USA</dd><dt><span>institution_id :</span></dt><dd>E3SM-Project</dd><dt><span>mip_era :</span></dt><dd>CMIP6</dd><dt><span>nominal_resolution :</span></dt><dd>100 km</dd><dt><span>parent_activity_id :</span></dt><dd>CMIP</dd><dt><span>parent_experiment_id :</span></dt><dd>piControl</dd><dt><span>parent_mip_era :</span></dt><dd>CMIP6</dd><dt><span>parent_source_id :</span></dt><dd>E3SM-1-0</dd><dt><span>parent_time_units :</span></dt><dd>days since 0001-01-01</dd><dt><span>parent_variant_label :</span></dt><dd>r1i1p1f1</dd><dt><span>physics_index :</span></dt><dd>1</dd><dt><span>product :</span></dt><dd>model-output</dd><dt><span>project PI :</span></dt><dd>Dave Bader (bader2@llnl.gov)</dd><dt><span>realization_index :</span></dt><dd>1</dd><dt><span>realm :</span></dt><dd>ocean</dd><dt><span>references :</span></dt><dd>Golaz, J.-C., P. M. Caldwell, L. P. Van Roekel and co-authors, 2019: The DOE E3SM coupled model version 1: Overview and evaluation at standard resolution. JAMES, doi: 10.1029/2018MS001603; http://e3sm.org&#x27;</dd><dt><span>source :</span></dt><dd>E3SM 1.0 (2018): \n",
+       "aerosol: MAM4 with resuspension, marine organics, and secondary organics (same grid as atmos)\n",
+       "atmos: EAM (v1.0, cubed sphere spectral-element grid; 5400 elements with p=3; 1 deg average grid spacing; 90 x 90 x 6 longitude/latitude/cubeface; 72 levels; top level 0.1 hPa)\n",
+       "atmosChem: Troposphere specified oxidants for aerosols. Stratosphere linearized interactive ozone (LINOZ v2) (same grid as atmos)\n",
+       "land: ELM (v1.0, cubed sphere spectral-element grid; 5400 elements with p=3; 1 deg average grid spacing; 90 x 90 x 6 longitude/latitude/cubeface; satellite phenology mode), MOSART (v1.0, 0.5 degree latitude/longitude grid)\n",
+       "landIce: none\n",
+       "ocean: MPAS-Ocean (v6.0, oEC60to30 unstructured SVTs mesh with 235160 cells and 714274 edges, variable resolution 60 km to 30 km; 60 levels; top grid cell 0-10 m)\n",
+       "ocnBgchem: none\n",
+       "seaIce: MPAS-Seaice (v6.0, same grid as ocean)</dd><dt><span>source_id :</span></dt><dd>E3SM-1-0</dd><dt><span>source_type :</span></dt><dd>AOGCM AER</dd><dt><span>sub_experiment :</span></dt><dd>none</dd><dt><span>sub_experiment_id :</span></dt><dd>none</dd><dt><span>table_id :</span></dt><dd>Ofx</dd><dt><span>table_info :</span></dt><dd>Creation Date:(05 February 2020) MD5:2d0925db3b70f8bc27a1cb25c4b1d7b6</dd><dt><span>title :</span></dt><dd>E3SM-1-0 output prepared for CMIP6</dd><dt><span>tracking_id :</span></dt><dd>hdl:21.14100/aaa3a5b2-c4c4-4bf6-b7a3-b59915926fc0</dd><dt><span>variable_id :</span></dt><dd>areacello</dd><dt><span>variant_label :</span></dt><dd>r1i1p1f1</dd><dt><span>license :</span></dt><dd>CMIP6 model data produced by E3SM is licensed under a Creative Commons Attribution ShareAlike 4.0 International License (https://creativecommons.org/licenses). Consult https://pcmdi.llnl.gov/CMIP6/TermsOfUse for terms of use governing CMIP6 output, including citation requirements and proper acknowledgment. Further information about this data, including some limitations, can be found via the further_info_url (recorded as a global attribute in this file) and at https:///pcmdi.llnl.gov/. The data producers and data providers make no warranty, either express or implied, including, but not limited to, warranties of merchantability and fitness for a particular purpose. All liabilities arising from the supply of the information (including any liability arising in negligence) are excluded to the fullest extent permitted by law.</dd><dt><span>cmor_version :</span></dt><dd>3.6.0</dd></dl></div></li></ul></div></div>"
+      ],
+      "text/plain": [
+       "<xarray.Dataset>\n",
+       "Dimensions:    (lat: 180, bnds: 2, lon: 360)\n",
+       "Coordinates:\n",
+       "  * lat        (lat) float64 -89.5 -88.5 -87.5 -86.5 ... 86.5 87.5 88.5 89.5\n",
+       "  * lon        (lon) float64 0.5 1.5 2.5 3.5 4.5 ... 356.5 357.5 358.5 359.5\n",
+       "Dimensions without coordinates: bnds\n",
+       "Data variables:\n",
+       "    lat_bnds   (lat, bnds) float64 ...\n",
+       "    lon_bnds   (lon, bnds) float64 ...\n",
+       "    areacello  (lat, lon) float32 ...\n",
+       "Attributes: (12/46)\n",
+       "    Conventions:            CF-1.7 CMIP-6.2\n",
+       "    activity_id:            CMIP\n",
+       "    branch_method:          standard\n",
+       "    branch_time_in_child:   0.0\n",
+       "    branch_time_in_parent:  36500.0\n",
+       "    creation_date:          2021-01-28T04:40:15Z\n",
+       "    ...                     ...\n",
+       "    title:                  E3SM-1-0 output prepared for CMIP6\n",
+       "    tracking_id:            hdl:21.14100/aaa3a5b2-c4c4-4bf6-b7a3-b59915926fc0\n",
+       "    variable_id:            areacello\n",
+       "    variant_label:          r1i1p1f1\n",
+       "    license:                CMIP6 model data produced by E3SM is licensed und...\n",
+       "    cmor_version:           3.6.0"
+      ]
+     },
+     "execution_count": 8,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "area"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "#### 2.1.2 Visualize the data"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Let's get a quick look of the data snapshot to get an idea how it look like:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<matplotlib.collections.QuadMesh at 0x7f2cbc736b60>"
+      ]
+     },
+     "execution_count": 9,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 2 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "ds[\"siconc\"].isel(time=0).plot()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "array([[      nan,       nan,       nan, ...,       nan,       nan,\n",
+       "              nan],\n",
+       "       [      nan,       nan,       nan, ...,       nan,       nan,\n",
+       "              nan],\n",
+       "       [      nan,       nan,       nan, ...,       nan,       nan,\n",
+       "              nan],\n",
+       "       ...,\n",
+       "       [99.87347 , 99.88154 , 99.88288 , ..., 99.86003 , 99.861336,\n",
+       "        99.86454 ],\n",
+       "       [99.656136, 99.65681 , 99.657486, ..., 99.655624, 99.65451 ,\n",
+       "        99.65535 ],\n",
+       "       [99.54839 , 99.55058 , 99.554344, ..., 99.54922 , 99.54881 ,\n",
+       "        99.54852 ]], dtype=float32)"
+      ]
+     },
+     "execution_count": 10,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "ds[\"siconc\"].isel(time=0).to_numpy()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Another angle view:\n",
+    "- Example map scripts are adapted and revised from https://docs.xarray.dev/en/latest/user-guide/plotting.html#maps."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from cartopy.feature import LAND as cartopy_land\n",
+    "from cartopy.feature import OCEAN as cartopy_ocean"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "Text(0.5, 1.0, 'sea ice concentration over the polar region')"
+      ]
+     },
+     "execution_count": 12,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 2 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "ax = plt.axes(projection=ccrs.Orthographic(-80, 35))\n",
+    "\n",
+    "ax.set_global()\n",
+    "\n",
+    "# Color over the ocean\n",
+    "ax.add_feature(cartopy_ocean, zorder=1, edgecolor=\"k\", facecolor=\"lightblue\")\n",
+    "\n",
+    "# Data\n",
+    "ds[\"siconc\"].isel(time=0).plot.pcolormesh(ax=ax, transform=ccrs.PlateCarree(), cmap=\"Blues_r\", zorder=3)\n",
+    "\n",
+    "# Color over the land\n",
+    "ax.add_feature(cartopy_land, zorder=2, edgecolor=\"k\", facecolor=\"lightgrey\")\n",
+    "\n",
+    "# Add coastlines\n",
+    "ax.coastlines(color=\"black\", zorder=4)\n",
+    "\n",
+    "ax.set_title(\"sea ice concentration over the polar region\")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Another additional angle view with eleborating the plot:\n",
+    "\n",
+    "Additional matplotlib colorshemes can be found [here](https://matplotlib.org/stable/users/explain/colors/colormaps.html)."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "Text(0.5, 1.0, 'sea ice concentration over the polar region')"
+      ]
+     },
+     "execution_count": 13,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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I9erVS7ROzpw5AfV5aYQ6Loldk/hYW1tz8eJFBEHQsSEgIACFQpFuv2mRn4N0m8ebJUsWevToQcWKFfnvv/8AKFGiBBYWFty9e5dChQol+tLX1wfUP/j4N559+/bx6tWrb7KnatWqPHz4UNtdmBg1atQgMDAQpVKZqG2aP6jE8PDwwN3dnRUrViSIOtRgYmJCkSJF2L59u86TqEqlYt26dTg7O+Ph4ZGq86pUqRIymYyFCxcmWSY11z01fMsTdUq/19R42Jru13Xr1ulsv3z5Mvfu3aNChQqpsjEpNO3EP84///xDWFhYguO0bduWixcvcvbsWfbs2UPr1q2RyWTa/TVq1EAQBF69epXod5I3b95vtvVbeijiYmxsTLly5bh27Rr58uVL1L7EvKz4HDt2TEd8lEolmzdvxt3dXfuQVKFCBY4fP54gWn/NmjUYGxsn+bAI6X+fSI6cOXOSI0cObty4keTfkuYBvUyZMhw/flynZ0ClUrF169Zkj1OhQgU+f/6cYJ78mjVrtPtFfh++2eMNCQmhXLlyNGvWDE9PT8zMzLh8+TIHDx7UPhmampoyd+5cWrduTVBQEA0aNMDOzo73799z48YN3r9/rxWQGjVqsGrVKjw9PcmXLx9Xr15l6tSp3zx/s3fv3mzevJnatWszePBgfH19iYiI4NSpU9SoUYNy5crRpEkT1q9fT7Vq1ejVqxe+vr7o6enx8uVLTpw4Qe3atalbt26Sx5g/fz41a9akaNGi9OnThyxZsvDixQsOHTrE+vXrAZg4cSIVK1akXLly9O/fH319fRYsWMDt27fZuHFjqp/Is2XLxtChQ/nf//5HRESEdgrQ3bt3+fDhA2PGjEnVdU8NefPm5eTJk+zZswdHR0fMzMy++nACKf9e3d3dMTIyYv369eTKlQtTU1MyZ86s7X6MS86cOenUqRNz585FKpVStWpVnj17xogRI3BxcaFPnz6pPrfEqFixIpUrV2bQoEGEhoZSokQJbt68yahRo/Dx8aFly5Y65Zs2bUrfvn1p2rQpUVFRCcaGS5QoQadOnWjbti1XrlyhdOnSmJiY8ObNG86ePUvevHnp2rXrN9mqEe3JkydTtWpVZDIZ+fLlS9UD1uzZsylZsiSlSpWia9euZMuWjU+fPvH48WP27Nnz1YdYDTY2NpQvX54RI0ZgYmLCggULuH//vs6UolGjRrF3717KlSvHyJEjsbKyYv369ezbt48pU6aQKVOmJNtP7/tESli8eDFVq1alcuXKtGnTBicnJ4KCgrh37x7//fefVliHDRvGnj17qFChAsOGDcPIyIhFixZp4ymk0qT9nFatWjF//nxat27Ns2fPyJs3L2fPnmXChAlUq1btq7EqIr8g3xqVFRkZKXTp0kXIly+fYG5uLhgZGQk5c+YURo0aJYSFhemUPXXqlFC9enXByspK0NPTE5ycnITq1avrTDEIDg4W2rdvL9jZ2QnGxsZCyZIlhTNnziSI/kuK+FHNmjZ79eolZMmSRdDT0xPs7OyE6tWr60w7iImJEaZNmybkz59fMDQ0FExNTQVPT0+hc+fOwqNHj5I97vnz54WqVasKmTJlEgwMDAR3d/cEUdhnzpwRypcvL5iYmAhGRkZC0aJFhT179uiU0UQGX758WWe7JjrzxIkTOtvXrFkjFC5cWGuzj49PgujPlFx3TcRw3EjMuPbEjcS8fv26UKJECcHY2FgAtN9LUrYLQuq+140bNwqenp6Cnp6eAAijRo3SsTEuSqVSmDx5suDh4SHo6ekJNjY2QosWLbRTkDSUKVNGyJ07dwK7WrduLWTNmjXB9vhEREQIgwYNErJmzSro6ekJjo6OQteuXYXg4OBEyzdr1kwAhBIlSiTZ5ooVK4QiRYpofw/u7u5Cq1athCtXriRrd1JERUUJHTp0EGxtbQWJRKLz3QFC9+7dE9RJ7G/Gz89PaNeuneDk5CTo6ekJtra2QvHixYVx48Yla4PmOAsWLBDc3d0FPT09wdPTU1i/fn2Csrdu3RJq1qwpZMqUSdDX1xfy58+f4PebWFRzSn9Pmr+buL/1r6E51tSpUxPdf+PGDaFRo0aCnZ2doKenJzg4OAjly5cXFi1apFPuzJkzQpEiRQQDAwPBwcFBGDBggDYyWROtLQgJo5oFQRACAwOFLl26CI6OjoJcLheyZs0qDBkyRDstTENqvk+RnxOJIAhChqu9iIjIb4dEIqF79+7MmzfvR5vyU1GpUiWePXvGw4cPf7QpIj8Jv03KSBEREZEfTd++ffHx8cHFxYWgoCDWr1/PkSNHEmSVE/mzEYVXREREJJ1QKpWMHDmSt2/fIpFI8PLyYu3atbRo0eJHmybyEyF2NYuIiIiIiGQgv82ygCIiIiIiIr8CovCKiIiIiIhkIKLwioiIiIiIZCApDq6KjIwkOjr6e9oiIiIiIvId0NfXT3Ixl/QivTQiI2z90aRIeCMjI3HMkpWP71O+Uo2IiIiIyM+Bg4MDfn5+303QIiMjcXV1TVFe6uT43rb+DKRIeKOjo/n4PoAlJ69gZJr0wgEiIiIiIj8XEZ8/0alsIaKjo7+bmEVHR/P27VsePvXH3Nz8m9sJDQ3Fw83lu9r6M5CqebxGpmYYi8IrIiIiIpII5ubmaRLePwUxgYaIiIiISLogfPmXlvp/AqLwioiIiIikD8KXV1rq/wGI04lEREREREQyENHjFRERERFJF0SHN2WIwisiIiIiki4IgvqVlvp/AmJXs4iIiIiISAYierwiIiIiIumCGNWcMkThFRERERFJH8RB3hQhCq+IiIiISLog6m7KEMd4RUREREREMhDR4xURERERSRfEqOaUIXq8IiIiIqlEpVJxes8/zBvSm5vnzvxoc34ahHT49ycgerwiIiIiKeTO5QtsmTeN+/9dRhETA8CJHVuQyfXI4uFJyeq1qdykFUYmpj/YUpGfGdHjFREREUkB/k8eMbJlPW5fPIeDvT09e/bk4MGDtGvXDhdnJ57fv8PaqeNoUdCDpf8b9qPN/SFouprT8voTED1eERERkRSwYvxwAHbt2oWbm5t2e58+fejTpw8qlYpDhw4xc+ZMDq5fid/dW4xdux25XLzNiugierwiIiIiX0GlUrF83HBunjtLtmzZdEQ3LlKplKpVq3Lw4EFKlizJg2tX6Fy2EEHv3mawxSI/O6LwioiIiCTBqV3/0KqwJ/vXrcDGxpqZM2cmW0cqlbJw4UK6du3Kxw8BdKtYlDuXL2SAtT8esas5ZYh9ICIiIiKJMHdwL07u3Iqevj69e/emffv2qarfrVs3vLy86N2nD6Na1SeLRy4QBARBhUoQEFQqhC9qI5XJ6Dl5Dtnz5P9OZ5NRpDUy+c9QXlF4RUREROJxdOt6Tu7cSrZs2di6dSuGhobf1E7ZsmXZtXMn7du3543fYwAkEgkSiUT7HomEiPBw/lk0h0HzlqfbOYj8vIjCKyIiIhKH5w/vs3jUIIyNjdm8efM3i66GrFmzcvTo0a+W8fX15fmDu2k6zs+AmEAjZYhjvCIiIiJfCHz7huHN6yAIAitXrsTY2DhDjps5c2aC3r3JkGN9T4R0eP0JiB6viIjIH4tCoeD8wT2c2LGFRzevEf4pFIAhQ4bg5eWVITb4+/vzwt8fQRDoW6sCQQFviQgLQxETjbO7B7P3ncwQO9IFcZWEFCEKr4iIyB/JtF6duHB4nzrACbC2tqZM1ao0bdoUHx+fDLEhODiYBg0booiJwcregecP72Fra0tmN1f8/PwIDtCdihQaFIhSqcTS1i5D7BP5PojCKyIi8kNp3mS89v36TRmT8WlGny6cP7QXBwcHWrVqRf369TOsWzkuLVu2JDwsjPbDx7N83DC8vb1Zu3YtAFWrVuX169esnDQaV8/c7Fw2H//HDzE2M2Pt5QdJthkTHc2n4CCs7B0y6jS0pDXfspirWURERCSDad5k/HcX3x1L5/Pvgd14enqydevWr5a9cOEC8+bNIyoqClDP0ZXL5ejp6aGvr6/9X19fnxw5ctChQ4ck27py5QqhoaGUL19euy1fvnw8f/6cjbMmYWhszIOHD1GpVEilUurXr8+iRYvYu2qJ9tgWFhZ8/PiRN8/9cMzqqtN+wCt/lo8bwbXTx1AqlcjkcqzsHHDLnfdbL1WqEYOrUoZEEJI/1dDQUDJlysTaKw8wNjXLCLtERET+AOJ6u/H5HgL8yu8xf1crg0WmTBw5ciTJiOU7d+4wdOhQnj59ikQiQSbX+7Indv6t5hWXM2fOYGFhof0cGBjIvHnzOHToEJ8+fQJg3bp15M8fO19306ZNTJw4EZVKBUDx4sUxNDREpVIxefJkbt++za1bt2jatCmPHz+mefPm1GzTmTaDRwFw+fhh1s+YgP/jh4A6UMvX15d79+7x7Nkz7UNDSEgI5ubmab6GiaHRiEf+HzBLwzE+hYaSw8Xmu9r6MyB6vCIiIhnG14Q2sbLpLb5rpowDQWD16tWJiq6/vz8DBw7k9u3bSCQSCpWtSI9JszCzsPxqu/8snsOGmZN48uQJPj4+bN26lbVr1/L8+XMATMzNKV+vCSd2bqFXr14cP34cqVQ9qaRJkyb4+vrSqlUrQkJCOHfunLbd4cOHM2PGDHx9fQHYu3cvAO9evWDDrMkc2riazyEfkUgkFC5cmMGDB+Ph4aGtv3nzZsaNG5e2i5YKxNiqlCEKr4iISIaQGtGNXyc9BFilUnH97AkcHR0Tzbc8d+5clixRd+t6FSpC72kLsHZwTFHbjtnU7Y0ePZqXL1+iUCiQymR4FS5Kk78HkrtwUQDMLC3ZtXwhs2fPpk+fPtr6bm5unDx5ks6dO3Pp0iWMTc2QyeUcOXKEevXqERoaysePH4mKiiKTlQ1Xjh3m0pEDGBkZ0ahRI/r165dgjFqlUnHp0qVvulbfjKi8KUIUXhERkZ+e9PB+D6xfiSImhhYtWiTY9/DhQ5YuXYq5pTVj127DJXvOVLXtmlM99ejZs2fYOblQpXlbqrfqkGBlohb9hnFy51ZWrVpF/vz5dcZ75XI5y5cvZ82aNcyePZvwz+qu6cePH2NoYoK5tS0+pcoRGhzEhcP7GDNmDPXq1UvUnvXr1zNv3jw+f/6MiZk5YV+mSYn8HIhjvCIiIt+dFHm7Mr3Y98oYnV2CIgohOhiJiSMbNg5NtHrw+wD2rl5KleZtsHV0SrC/a4UiBL17w9WrV7XdvBr++usvAgICmLn3JC7uOZK3NRHOHdhNDu+CiR47Lo9vXmN4i7rEREdTrVo1Jk6cmMAelUrFjh07WLFiBS9evADAIUs2pu88yoJhffn3wG5u3bqVoG1/f3+aNm1KSEgI+gaG1OnYneqtOtDaN1eGjPE+ePE+zWO8ObPY/vZjvGLmKhERkZ8Pa2edjzGvzhD98B+ibq+iUY22NO2yCFAnwNizagndKxWnQylvdi6bz+TubRM09+a5HwGv/ClWrFgCkZs2bRrv3r2javO23yy6AMWr1kpWdAGy5/NhycmrOLt7sH//fv766y/8/f11ymiimvft28fhw4epUKECb188o0/NcvAlz3NiXLt2jZCQEAqVq8T6a49p3KNfgvP9noirE6UMUXhFRES+K4l6uzK92Jfmc3y+iK8qOgRV8ANkdgWQZcqG8tlJok+OpUHx0jTN78qqSaN5//olvr6+ZMmSBb97d/gcGqLT1OZ509VNWltro4cBDh06xJo1a7C0taPt0LHpc8IpwNzKmtn7TlKnQ3fev/9AjRo12LBhQ6JlHR0dmTVrFs2bNyfglT8XDu1Lst2yZcsCYGBklKGCK5I6xDFeERGRdCdVgVTWzvDxXexnC3vtW2n2gsRcWgJ6psgzF0WSOSdyRRSqtzdQvr6Ki7MzLVq0oFGjRkilUs6dO0fnzp1ZP2MinUdP0raTLWcu/t0vY+fOnRw4cIBSpUpx8eJFPn36hFQmY9jidT9EqFr2H4ZvhcqM69iciRMncvjwYSpWrEhMTAwKhQKFQkHevHkpUaIEgwcPJjg4mP379wNqbz/+GLK5uTkGBgY8vXMzw88FxNiqlCIKr4iISLqSrOgm5t1a2KvFN47oAqg+vUX54iJ6+RqDMhoAidwAmbMvMmdf9k4ur1O+ePHimJubc2bPdjqPnsSnj8FM6dmeu18WopfJ5SCVcfToUYxMTKneqgPNeg/G8AdkrdKQ06cQy8/eYFyn5ly9dJ6rV68mKCOXy/Hw8KBmzZoEBgZy8eJFjh07xvPnz/H29tZON/rw4QNRUVHJTn/6XogJNFKGKLwiIiLpRqqnDMURWmMvtXiEv1bPfZVa2hN9fSMgEHNzEwCyiMroeVQD4HI80dVQu3Zt1q5dy+Qe7bl64ghKpYL8+fNTq1YtJkyYQHRkBHU7dqdFv4xJT5kS9A0NGbvmH/zu3iYk8D0yPT3k+gbIZFKunDjC+UP7uHfvPnfvxi4d2L9/f+37HDlyMG3aNObOnQtA26FjMvwc1Ig+b0oQo5pFRETShRSJrqGp+v+YqATerXHmrNr34a+fI7W0RxX8HGXAXSQGZshCHhPx6DR6hbvy34puSR4iPDycokWLIggCmTJlIsKxOlJDtQe4fUJ1atWqhVKpZNu9V6k/yR+IQqHgzJ7tXD97Eis7BzJnc8PR1Y1dyxbw3+njAEgkEqwdMrP4xGVtvfDPn2hZKGeGRDXffRaQ5qhmr2x2v31Us+jxioiIZDyZv2RXClcHQcUVXQDbXF4Evg1EapkVqWVWLG0tEQQBZVggwtN91Fhajb0dsyVotnBLdbSz3K0WbcrbseaSHtI4UcB1/l6GQqGgQJkK3+e8viNyuZxydRtRrm4jne15fIvzyu8xM/p05dmDuzTvO/gHWSh2NacUMexNREQkzaTK242LcaYEm0wymQBg7WANgKWt2luVSCSYF2xETOALol7foeay5zr1NKILIDNzZu1lfSRxRFdQxhDz4igSEwcGzl2evL2/EE6u2Zm+8wj/3HtF6Zr1f5gd37LwffzXn4AovCIiIt8fuX7se1td79YsqxsyPRkQK7oavLxdcXSywNHJQr3ftQByi8x8unkAgNor1fNfNaKrCntL1L31KN79hyDEThsSFFHEvDyJoAhHL0sF2rSamq6nJyKSGsSuZhERkTSR4oAqRbSuAANmttba9/kKqgX5yeMPiVZ3zmLJu7efMclenM/3TyCVqf0GjfgqP/kT47cfidwExZvzKEOfoZe5OMqPT1AG3gFBidy5LFIDCx27M2oN4D8BgTR2NaebJT83oscrIiLyfYkrtpaOagFGV3Tj4p7dBgB7h4TBNfYOpkj0jBGUCp3tEhMJMX77kJo6oe/ZGP3sdRCiPxH96B+UgXeR2ebDIHcb5Na5ErT5LYs3iCSOkA7//gRE4RUREflmkhWteB6uhsw5smFmETtDInc+3RSRvRvm0fksk8WO1eob6oMqVnhDbx0k4tx85C6+mFQdhUSqh9TUCQPPJuhlq4pB7tboZS6ORM8EJInf8n418VUoFMkXEvlpEYVXROQPIyY6mpvnznz/A8UX3Xhju4CO+ManaaksgK7oAkhkcgSVAn09CDq3jg9H5qCXvTxGxTojkcqRuBX4Us4AmYUbEnm8dXedvRI93s8sviqVivnD+tGpbCEa581G4zxZ6FyuEB/evv7RpukiRlelCFF4RUT+EALfvmFyj3Y098nOmHaNuf7vqTS1lxqhkrvl177PnMtDZ1+pEu46n2v6OGjf57b4RDZiFxAIDY1SC68ihhebh/Lx4kYM8tbHsGArJBIpMVHqVY004puUh/sriW/451B6VinJ8X82EvkpBNdsWSlatCgf3rym219FOb1n+482UYuouylDFF4Rkd+cm+fO0K/OX3QqW5BLRw+ip6eOqTQwMEymZtJ8Sxez3MwiyeJWZgaAruiGvH/L1uFtObF0IqXyxG5HKgdBhSLQn7xdZlGkbR8kEolWdDXYlqyEbYm/dA/k5Kl9q+9ZJFFbfibx9X/yiE5lC/H2xTMaNmzIhQsX2L59O0uXLmX58uXoyeXMHtCDnlVKsm/tcrEL+hdBFF4Rkd+YU7v+YUy7xjx/cA9vb282bdpEnTp1AHB0df965XQirrfbsEU5ShSMXTrPO7ed9v3EGl4Ud7KiuJMVipholg7rRvjHQCJCg9XtEIPq+Rn0zG3JXKoBBfqvxDJHQQBq18hPg/qFEj2+VnzjiK6Gn1l8Lx45QN9a5YkMC2PEiBGMHDlSZ7+vry8nTpzA19eXd/7PWTF+BE3zuzKtV6cfZLG4LGBKEYVXROQ3JSY6msWjBmJgYMDp06dZu3YtuXPn1i6sbmFt803tJitKEil8iTqOK7pxiSu+iRF97QhvH93Gs3Q1IkKD2DBpKBfG1OHBhnG4Gnwge93e6JtZAZDVPnacWCO+Npl1z61Ym6Y6n/VTkPr2R4rv49s3mNKzPXK5nDVr1tCoUaNEy5mamrJ8+XKuXLnCkCFDcHRw4PyhvYzv3DKDLVYjRjWnDFF4RUR+U2b260ZUZARDhw7FwsJCu/3+/fuYZrJIsl56IXPNhyAIaNLB163to7N/RJPc1MxrC8CAMrre9yv/Fzg5OePuWx5FdBQfbp5CIpEiN8mET/VmFMuprhdXdDXMHqibDjJ7DnXZYhXVx08gurZZEw38gsTFt3mT8dpXSranFpVKxfhOLZBIpezcsQNvb+9k68jlcpo1a8bBgwfx9vbmv1PHmNG3a5rs+CbEQd4UIQqviMhvwL0rF2leIDutCnvSpbwvA+pX4eKR/bi7u1OvXj1tuejoaIKCgnD1yvOV1pImRd5uInRtVVTnc/kcFtr3Q8vn0Nlna2ZAyMdgLKysmNWvE/l7zCd3+0koIj9TrlUvDE3V83sHVsxB43wOOnVLuatTUI5oofa0NaKrIVdh3e7m6MC3cQ6cuPjGJTGx/dr2b2HRyIGEBgXSsUMHXFxcUl1/9erV2Nra8u/+Xdy6cPab7RD5fojCK5LhqFQqFo4YwLTenVCpVMlXEEmW6X27EBURgZmJMRGhH3nx4C5GxsbMnz9fp9yxY8cAKFy+MpB+XhoAUpn2rSx7gQS7HTKpA6jiiq4GvS9ZqGy/BFkFBweRycIKfX19Vvasxf31Y7F2cSd/lYRdrhrx1YiuhvU9S+l8/vgxAgD3XOpubh3RTYK4Wa2Sukap3f41FAoFJ3dswc7Ojp49e6a6PsCaNWt4//49FjZ25PROfNz7eyE6vClDFF6RDOXqqaO09s3F0a3rOX9wL4c2rf7RJv3y7FqxiOCAdzRu3JgjR45w/vx5rl27xqWLF3Fy0h1LPXz4MABlajdI9XFSJCQSSYJN3VoX074fWi67zr68thba96YGciKilUREKwkJDsbKyorPnz7RpnEdFJFhZGs2DplcD4BSWSx02unmm0Xns6el2iseU0Xt4WpEV0N0VDSYWuka+l530YWUiC6Q9JSl5Oolwv61y1EqFbRr1y5V9QAOHDhAxUqVmD59OmaWVsw9eBp9w2+PXP8m0hpY9Ycoryi8IhlCTHQ0I1rWY0LnVkSEfQZAT9+AElVq/WDLfm2iIyPZOGsyxiYmDBkyJNnyN2/exNjUDFPzTOkbPJSMtxuXos42BLx6weUtyxLt8Xjl/5xHD+9jYmpKp1aN8HvyiNwdpmFk48S/9wKSbDevtdrj1Yiuhr7l3XQ+37vuF/tBI77xRDcuKRLdr4hvajiwbgVyuZymTZsmX/gL/v7+lC5dmoEDBxIQEEDxKjVZcOQcxqa/73q2vzriIgkiGcLo1g25f+0y+fPn59mzZ4SEhDBsyVrMrRLP1yuSOAGv/Ll98V+e3LnFyycP8X/0gJjoKEaPGolU+vWbv0KhICAoFJl1Hpo3nZiq436rSHdqETu2265A7HjlnQNbWbNkDkZGRjRt1x0Dudr2E4f3MaxvF0zNzPF79pzrl87h0W4qpk6x48Am+rrnaW0YO2e4nKsdbz5Gaj+HRKvzQo+tl5uR2+9w9+pDhMiPEBGMEBGEEB6EEPAIIfqT+hXzGSRSpKbONK54F5mZMxL9JAQsvtgamkLk5wTFmjcZn6KFGAJe+RPwyp8SJUok+11qUKlUtG3bluDgj1Rp1obWA0dmvJcbh7RGJv8pUc2i8Ip8dzbMmsz9a5cpVqwY/v7+hISE0Kh7X/IWLZnqtpITgN95pZmnd24xoH5l7WeJRIKRkREVKlSgVq3kew727NkDikhk5lmSLZsqNMkyVEpk7j4JdiuUAvJ4aR/PnTqKsYkpcyaPxs2nGMW88zNn8mhWLZ5D6b+qUaN+MwZ2bUGNrkP5GKfNSvnV47n/vQ2lgIO5jujamKvHh831FFy9eY8Hj+7z+oUfr58/4fVzP+7ffwBRn3SNkxkg0TNFom+K1MQRib4ZgjIK1eeXKPwfo0BAom+OzM4HuU1sQFq5zq04sWRdbDsGxur/0yC+66apf9t9+/ZNsoxKpeL58+e4uroCMH78eN69e0f1Vh1oN3TsV9vPENLaXfxn6K4ovCLfl9N7/uGfRbOxtbUlICCAly9fUq1FOxr37J+i+j9DIoOfBUs7ewAKFizIpEmTcHBwSKaGLmMX7AWZPhITx0T3p9QzS5Ks+XQ+xvV22/g4oxIEpBIJz1+84PGDu4ydsYg1i+cwZVBXjE3MeHT7Gr2GjqN249a0qFGS/IWKUbJ+G6QyGbuvvtaKroYcNqYABH2OxsbcgHOnTzB57FDu3rqhLWNmYUXmLK6EBb2jcD5PrinzIDGyRGJkheTdcySyxBdxAPUavs19VazacQbFy1OgUiC386Zc51YAlOvUQi2+GtHV8I3ie+XEEaytrfHw8EiyzODBgzlw4ABlypShU6dObNmyBdvMzj+H6IqkGFF4Rb4b965cZM7AvzEyMqJx48bMmzePEtVq0374uETLiyL7dWQy9TiqUqlMsei23RW7tq0y9DlSsyxIUhAMFF8g1m8alvj3Ey81pFKhRCaX6Yhuh0KxXczWZvpsPHUMqVRK6QpVsMrqQe8mVbC0tqXnvE00/qsCk0f0JejDe1pMXIH0yzmPqJaTi69CtO00zpMZUE+PenTrEiOXzuPIgT0U9C3G/CUrcc+eAzf3HDwIFcjG+wRmF265COKI7uW1XdTb4nBlYy8AevXqRYEKLVC8Pke5gbrXoHznFhxflUiuZJkeKGMSbE5KfCPCPhMVGUHFvyok2KdBpVJx7NgxJFIpp06d4tSpU0ilUsas3ppknYxGdHhThii8It+F5w/vM6pNQ6RSKWvXrqV58+YYGBnz95S52jKi0CYk7jWJf4Me064JAB07dkx1uzFhIQgRAWSp1AqbglW5s31H2gwFtbhocMmtfVu9en5eBUfgZGmkI7oarp0/QR7vQoTJjHDNmZu5244SomeGgbEJ/fp359+dG6jb53/YOGUDIP+XJBlFnDJx7vkHcinesmj2ei6eO8V/ly4QGRmBQ2ZnZi5aTfNmTZHEiazOFno/UdPjCu3ltV2S3AZwMSITzTu3ZM34gUjlseesOUz5NvV0xTcmKvb6JCK+ifH07m0A3N2TTuO5f/9+oqOjadSjHzFRkexeuZjmfYdi75L8/OOMIq1pH/+UlJGi8IqkK+cP7ePghpXc/+8KgkrFuHHjGDRoEFFRUejnqE/rFpPTfhCjOMEumi49QR0dm5TH9qsyvXdnggLeYmFrx7P7dyhfvjylS5dOdTuhjy+DIGCeo7B6g+2Xcd6AZymqn+RDkiAkOoUIoKGXAyHhauHJZKyHrbkBCoWC0yeP0aXb3xTNZs2FZ4HEWDsjDf/MkkEdeXDlX0ZMmkudxq049uwD+e3NEASBIzs3c/LADu79d4nw8DBMTM0oVKQ4PQYMx7d4aTxz58PR0jhRO5Iirrgmte18mFr0w0M/omdgSBUPUw4/iUzqlGNFFxBiwoh5dgQkMmTWnkj0zJDIDIgI+4yRialOtWf37wCQI4duMpG4rFixAolUSt0O3dE3NKRFv9/jN/4nIgqvSLrx8MbVLwnaBczMzLCxcWLo0KEglSPPXAKpSerGJLXETW6vEdrw0DTb+7Pz8ukjzh3co/1samrK9OnTU1z/wAdjGpVQC+ykrRcxcsiOvnm8/MyabmchdlpPih5a4ni70qx5AXVXaK3aiU8lMtZXdxn/d+USIR8/Ur6iOkisdHZbSiitKF7hL57eukrXaSuoU6c2AO0KZ+HC43fM+98gDv6znhKly9O972CKliiNZx5vnSlMAG+f3cchm6fO57SgEV0AfUMjYqIi6VMpP3YursgdPMiUzQtDC1veXjuBIkCF3DavtrwqMpiYRzsQVAokckNinu7T7mtRcDVehYsydNEarQB/DvkIwKtXrxK1JTo6mkePHpEjf4EfGrWcHGJUc8oQhVckXYiJjuZ/7ZshlUrYu3cfdfptwO/eOmRWnsgdiyHRS5k3Ypi7mM7nqAi1ByFEhae7zT87m+dOA2DXrl18+PABV1dX5PLU/8mqVCoi/K7iU6URUcCdM1dTVT+lQwI+RXPg/+4TLvZm9C7hmmB/WKSCIwf3Y2llhU+B2IxKY0YN4/6lM3SeuoJ2X0QXIPDDB8Z3b8qVSxeZOncpdRs11+6LUujO/1UFqefmplVsk6JMvRZ4FirOs7s3eXbvBs/u3uDBjhOoFNEgMwBBiRD2FmR6CIoIVCHPkciNMPCoA3qmCJFBDGuWi4CAAM6cOcPNyxdoWzwv+YqWQiKRcOXkEQA+ffqU6PE104syWf7k0+/EQd4UIQqvSLrQomoLFJ8/o5+9DvWG7kP1Wf3kLs9cEoncIMl6pt6xaf0kUnX/Xfx1Vb+FxMTiZ+1+TkrY/jt1HCsrK9zc3HBzc0u0TFIc+BD7oPPywS0iQoNxK1Sa408/YuXmTtDTJ/D+RZL2aK5VorZJpKBSglSGNFu+BLub+uhGTTtaqD20mJgYNq1fQ936jZHJZOjLpWzdvJGZ06YwbuIUunZuwbP3YQBEvPejXqO6hH3+zLrtByjoq/tApgryQ2qVUNzTk2Imn7Rer0QiwSGrOw5Z3SlatS4A26+85Pii5UhkBsS8OI4qMhAUUSA3Qmbhpn7glKvP/cq22N9ely5d2Lt3L5MmT+bqqaOAemx3/Pjx5M6dm8SQy+UYGhpy5eQRWhTyYOzqf3DLnTfRsj8SUXdThii8IumCEBmMxMgaqWlmBEGJ8v11pKZOCURXliPW05HJZURHRaNvkPSUjqRwjDMH+M3Dp+o37778r4hO/Qmkga8FRH0rKiGa6PAwZs1bjE2WnHx48SDZOrK4QvThHQCCILB/+UxMLG1x8swPTx+q98dEgYU9fHyn082sIUkvN25EtH3s8fL76gYFvQuPxN7YUCu6AP8eP8C7t29o3b4DADeuX6N7lw40btKcLj36AJDN1oR1W3YwrFc7smTJyo59h9FTReq0HRHwBIj1cr8nccU3PidXbkNqoM6Wpe9WLclAqsTGkmvUqEGNGjUIDw/nxYsXeHomXCs4Pr1792bJkiUEBQWxfclc+s9ekoozEfmZEIVXJH2IE86ofH8DIfIjeh4VtbvjdiHHRKfeo+3YQb2Y+aM36iklDx4FpsXaDCe1QV+qD3dBqk/FqjUAsM2SE4D3KRBggCKZLQCYMX8OT6+eodGYJazd/zDxwhJpouKbaLn4dkZ8QmoUK0wDq8TOQTU30iMsSomJgQwzIzmrli/Bt2gxcufJhxQVLZo2xDOXF9PnLtJGIu/bs4s+HRpTqUo1Fi5fw+cP6p4Tjdj+CBIT32Imn7i8qj2F2yxXb0iF6MbF2Ng4RaIL0Lx5cx4+fMj27dtpNXBEiupkNGJUc8oQhVckzZzZuwNl0F1ktt4I0Z9RvL2MzLUsUs/yAMgNDVHEKJDrff3ntqJPGe37j1+6m1+Hqsd4X4akvfv5ZyBRT9JCnRiDj++0m5Qhz5DoGRHyMRhj4+THx2WJdLv6PbrPvkWTKFq7JdkLl+HsbnXkbNCDu99mfFwcYxc7sHWy5fWrUDI7JZ5aUaES+O/KJU6dOMaCZavQl0k5/+9Znvk9ZenyMxgZGQFw4dxZOrVtTs3adVm+ZgNvniXxoPADiCu+xUxix2Evr2qfYP4vJC+4qeH06dOsWbOGokWLcveu+rsLCwkBp9QvGfi9EYOrUoYovCJpIujdW+YO7oWBgQE4FkUR9hjkRshz1U6+8hdW9iv7fYyLF7EbX/RS2y2c1vrJMXamOlXgyD4z0MtajuiHO6lUugirNv5DocJFUtzO+89RREdH8b9+nbBydKFyp4EcuxuAW3Zbnj6Ok0wijtCnCEGlvqZxRDcuLUpm4fXnSDKbGpLDOtZDDA4KpE2LJhQoVJhGDRsDsHvXDhwcHClcpChSqYSbN2/RrFEdCvkWYdHy1dpkIT8TcQX3a6SH6CoUCtatW8eRI0e4ffs2KpWKixcvAmBgZIxD1mxpPobIj0MUXpE0MbJVfZQKBSbVJiM1syN07x6ktp5I9IyS7Dca2yN2HqqTmQFhMQpMkvGG49Pkr9ib/0kH9ZSMO9fV423Rz79Etkak7Eb5rWiFWDOtRRBiFx/4IvbfIs73j6qnDN18NJIGZfOxf/eOrwqvYJENhUp9reVSCR+DApkzfgjPnjyky7xt6BnEjrOGBIYgs3FC+SHOtJW43cyJTC/SQSaPnftrlw377AmDvrJbxc5R1ZNB/+7tiAgPZ8GKDUQopegJAnt27aB6rdpIpVLu3b1Do7rVcXbJwrrN2zE0NOTlk3tfuUI/F0kl3kgL9Rs04OmTJ0gkEmwcnWg1aCTGpmZ4+hTGMAU9ID8MMboqRYjCK5IiVCoVKpUqwXSWty+ekTdvXl6aOxD9/CKqkFfo52ueaBu7R1bTvr/8NjhFx63uETv393OkAvI68uqzemrRlVffV1jTg+bNJqnffBFnm2Lq7vcP/x5Jtu7V86eIjoqkeOmyCEBSORs0xERHs3jRbFYtmgWCQJ2+43HM7sXB64ks+J7JXv16fjPxxjTzdL+SeUliaErAywDsnO0Y2DiPzj5BEJBIJCydN4MzJ46yfNMunJzVc4rPnzvDixfP8fTMRfPG9dm7Zxeubu5s3bGXTJky/VKiqyE9u5YBXr18iaGxCasv3fumKWQ/ClF3U0aqFpG8ee4MoUG/VlCLSPowqlV9GufJQodS3ty5fEG7Xa6nR3i4WghjXl1Hau6I1Eod4bp/SgP2T2nA7rE1OD2lHqYG6hvIa/9nfAr+kPAgQAk3G0q42VA9lyNlXG0xN/p1bjqpQepeEKl7QfI1aki+SrqZqARBYM60CYzp25EK1etRppw6sOz9iwcY2LprX4DOerZL501j0cwJ1KzfjH5rj1Gkan2ddq9dfJzQEMfskPlLQFRiOZxdfdQv0MnLLMkSK7S5PG2170tniU3Q8flTKIvnTqdVh25U/JIw49XLFzRr3AAzM3MG9O3FvXt3mT1/Meeu3MAxc+ZfUnS/B4ULFyYyPIzAN4kn1PgaG2ZNpnXR3Dy4duU7WPZzoVAoGD58OK6urhgZGeHm5sbYsWN1/i4EQWD06NFkzpwZIyMjypYty507d36g1an0eKf+rZ4GgESCvr4+RqZmmFtaY2XvQP4SZajdrgvP7t/l5vkzfA75SMTnT4R9CiUiLIwCpcpRsXGL73EOIt+ZhzeucvfKRSwtLQkJ/MD4Ts1Z8e8tDqxfSUx0NK6urgQBcht3ov3OsrBfaYzNzPEPCsbB1ISPQR8QzEwxNc/EwA4NuXDmOFly5afXou2Uy26nPY5cKv1aBsIU41ikhPb9m1u3IPiLxxfPe4sfaZxsogiNF/glk1bJivkBOLtyo04xVWQQysB7yB19kZCyscp/V6kT8tsYS+jdtQ07tm2m/d9DaNWtf6Iez4N7txk1sCd3b98ks3MWMjtn5drl8zRp3YU+w8dz/Jn6wcbvQyQ5nS148PKjtq4yRpGgPc186s83/k2QEQrApoQ6Qv3DxVM6oqthz4131Mxvr/0skUjYtmEVERHhDB44EIBPoaG0bFCDj8HB5PDIybCRy6lWs5Z2PFcU3ViqV6/O2bNnuXP5fKpyMW9bOJt/Fs0GYHiLuoxdvY2snl7fy8wEZHRU8+TJk1m0aBGrV68md+7cXLlyhbZt25IpUyZ69VL/TU2ZMoUZM2awatUqPDw8GDduHBUrVuTBgweYmSU+Vex7kyrh/fvvv3nz5g0vX74kICCA4OBgAvyf4f/4ITf+PcX66eNRKpWJ1r109ADrpo+nUc/+VG/ZPl2MF8kY5gz8W30j3baNI0eOMGnSJJaMGczp3dvJlCkTU6dOpfz0u7Ts3JzFl1ay+9AxmjSoy8TuLQh5/5YPAW+JiY6iefvuXD53ioatu7B19SK8VAEolM4J1moFCAsLY+OG9bjnyEn23AUTFZ9CTmba/6+//cxf+R25+kzdhX3vQeIe9ffAtXJ1APyOHUEQVEiCLqEMeAQSKXpOxROUjwnyR/nuGTJ73WQJgiDQrkVjzp05xdqNW6hbrwH/Pfuo3W9g6050VBQLZk1iydzpuLpnp/+Qkbx9/Rr/53545fOhdZfeidro62GLr4cti9eej90YnTAbmENptWf69uxRSERga/VoyZ7d17Sfy/wVew5FMlsBatGNiY5m7dJ51KjbGCdnZxQKBc3aNOHpk8fY2tpy+PgpQgPfiaKbBNHR6rnoevpJJ5+JT2R4OBtnT8bMzIxZs2bRqXNnRrZqwMB5K76XmQnI6Kjm8+fPU7t2bapXV/8NZsuWjY0bN3LlitrbFwSBWbNmMWzYMOrVqwfA6tWrsbe3Z8OGDXTu3PmbbU0LqRLepk2bYmpqmmC7SqViyJAhPHr0iCJFilCqVClsbGywsrLCwsICgFmzZrFx40ZWjB/B6sljQACVSolcT49hS9Z906LoIt+fz6EhvHnuR5EiRbCzs+PMmTMAPLh2BUFQsWzZMuqteY2FrQWHb0dhamXL/bMH6blxPgFP72FpY09MtHpK0Prl8+ndfxCDh4/mzOHd/LNlA/m81bl9FQoFSokEAz09Pn/+TJ1qf/HfVfUfTzY3d0b8bwoVq1QnWqnCxlyfoM/qG5N/6M+TSlKICSPm+XFUQY8w8ShJ2KNzuFZrQWCMLcrQNzjyiNc7+vLptTrRh0Hx3jzesIaYz0Gcth9GdFQkxw4fZO3mHdT9kjrRRF/G66AILE31+e/yBYb17caLZ0/o0XcQPfsOwsDAANmXLoLPUWpPVqkSqOXpwO77Ccd2G9UrCMDGzRe120zt7BOUq9ylOYf2q9e1tcmsm9+5Zi0f9uy+piO646rmAtDOx92/exvv3r7GxtKMOTOnc/HCOc6eOo5UKmXj1u2EBqojqkXBTZw8edQPPfOH9cXJNXuKslQZGhtjbmVNWMhHvLy8WL9uHS1atGByj7bf29x0JzRUNxe7gYGBeuZEPEqWLMmiRYt4+PAhHh4e3Lhxg7NnzzJr1iwA/Pz8ePv2LZUqVdJpq0yZMpw7d+7XEN6kkEqlTJ789VVn+vfvT+/evZk7dy5nz57F0NAQY2Njrly5wtj2TRm7ehu5CqV8yoRIxrBvzTIAWrRowcOHD/n333+xc3Lh7YtnFCtWTD35/1xs6sGIKCX3Tu3F0MwCO6csjFuzhzeXjiGTyXj88D79Bw9HLpeTPWcu7t+7i1Kp5PSJEwzs3Q1DQ0Nmzl1EJntnrv13lY49+hITE82qxfPo270D1x74Jz4O+YMRBIGQm4eIurkSJBJsqw7ANGdpAv4ZwvNt41DJTVAGPyfMwBiH/KXIW6czFxYPI+rcLOS2TkiMrejTXp1GsVKV6lrR1fAp9COz/jeBdSuXkN+nEDsOn8PbW52qUfaVfvlqOeyplgNmnk2Y4alnB3XX8twFh7TbTDPpPlRXrpZfK74AxQtn0b5fMFg97rz5yhut6Ma9HisXzgRg1fKlmJiYYGJqSrZsrhQpVpzCvsV49ujHjrH97Hh4eDBz5kz69evHoIbV6D9nKUX+qpJsvS5jpzKlRzsmT57M//73PzZu3EizZs2IUaUgQUp6kE7RVS4uunOUR40axejRoxMUHzRoECEhIXh6eiKTyVAqlYwfP56mTZsC8Pat+uHT3l734dLe3p7nz5+nwdC0kaGRK3K5nD59+tCnTx/ttjt37tC8RQtGtm7AuHU7yOlT6CstiGQ0N8+dBmDmzJk8ffoU5MYERpojkUi0D1u722Wh1gq1+ApKBUbmlrScsYU+1b50s+bKjomBukvR8Mv/ZSpUYvyIQZQokAv/F88pVaYckZER1Khcjtr1GpEnvw9L580AIK93QabOXohcLidambIbSM4c6mTy0ZE5gZwEPvqS8enjuwQpJbVTgIzV05FQfhkDtVdPlTG1sgCgRmX1WFl0jHo4pXORLAzfdgH/zSMJ87uK1CY3ei5lMMtVDoAs9YbwdP0QMHHAMG9dyjaqj0zfEGMDOdHhoUikMlxL1GBMVS/OnznB/n82MHjkWK1d916GsHf7RuZNGU1keDgjx02hbaduGH9JsaknV4tuZLRKx9uNT+8S2QBYeS1hoE6HDuqx2027Y6Ob8+eJvUlN7quOwp66KfHo5/kN1OPcwWHRGOqpv9sLZ0/y+IHak9259yBly6nbKO5bQDumli1HblF8k+Gvv/5i/fr1tG7dmik92tG831Dqduius95wfIr8VQWJVMrLly8B8PT0ZOPGjTRo0CBDbE6vqGZ/f3/MzWMTsiTm7QJs3ryZdevWsWHDBnLnzs3169fp3bs3mTNnpnXr1tpy8a+ZJur+R/HD3YfcuXOzetUqJMDQprWZP7SvTkSayI+lx8RZuOfJz1P/AKSZ3DDwbIIQHYqNjQ2WlpYJylsUacKIwQPoWeTrSwC27/I32/afoFBhX+YsWMyeA0fYd+QUU2fN4+aN/7h1/T8GjPgfh87dYPO+E3jlSZiMH8DdyhR3K1OKOmeiqHMmSmS3pkT2jFnB5b/zp7kytTWqID969uzJjRObcCpXQ7vfwNKBXD1WYlrqb/SzFEamHzufNnu5BriXqYtUrodEIqF46fIsWbkWN1dXohUqLl6+QremVRkzoBvFS5XlyPnrdOjaM9HEEsYGMuzMdW9MCmXC21/PYuogHRuzhLmxh7QtTM96uRJs17CmZ0m6FFV7vFW9El5fZysj7fvIiHCMjI0xNjEhb34f7cNAVFQU+vqxx3b1yI2rR+KLAoioyZMnD/v27cPc3Jz10yfQJF82hjWvw8UjB5KsI5VKiYiI0H52cnLKCFOB2OCqtLwAzM3NdV5JCe+AAQMYPHgwTZo0IW/evLRs2ZI+ffowcaL6YdrBQX0f0ni+GgICAhJ4wRnJTzFXI3/+/Gzfvp1u3btzfPsmLh7dT6+p8yhY5q8fbdofT/9BG0BeEsPcsWPwQtRHgox0F+ze3e5LN2S7nilqN+ztY3K62LBq3SbtNqlUStsOnWnaqgOli+Tnhd9TsrmpE2VYmMSu/yoIYGtmQGiEOko58HPGLYoQFvSO51dO8eHJLTae2U3mPEUo13MSnYqpxWhX28TS+Nkx7HxkItvjlPginPfv3WXuzGls3rgOj5y52LjzEEVLlk5RtKejhSF+T5/yMVqCpbX6piLEqzi6knrq0Lzzz4iITviAO7Wtesx93eVXlPdMKLDTa6m9/qOP31E6m53OPhszfT58iqZu3TrUrl2LqKgoLCy+rO6Dep6x/pcbaFxnwz1nHp48uJ38Cf6hODg4cOzYMZYtW8b+/fu5f/US969eIn/JMgxfsl67ZKAGmUxOZOTXf2+/C+Hh4Ymcv0zrvLm6uuLg4MCRI0fw8VFPi4uOjubUqVPJDo9+T34K4QVwc3Pj4IEDLFu2jHnz5jGhcyv0DAzIkc+Hqs3aULxqrR9t4h9FUlNrBJUSIfoTCEqio6N1PJivEfL6kfr/FJSVSCSUKVeBHVs3Ub9xU8qXK0e0QoW+/Md10Cg/BXBu2TYen9yJIAiY2bvQoc8wBN+GSGUykutgG19Md/Hy8f/pTum5eOEcs6dP4eD+vWR2cuZ/k6bRtkMXolRqhZJKJChVaOc1J+bRApQrXYwP79/jnj07eQsWo0ChohQqVopcOXUflDTr5U488QRX64TexLgq6ilTx5+9J69twhzMdfM4ax94NMMIEOv5fo5SYGepO1UjKjoKfT39RKeLieL7dQwNDenRowc9evQgPDyc9u3bc+PsKXpWKcm0HYcxMokdnzc0MeHJkyeUKlWKWrVq6XS5fm8yOqq5Zs2ajB8/nixZspA7d26uXbvGjBkzaNeuHaC+l/Tu3ZsJEyaQI0cOcuTIwYQJEzA2NqZZs2bfbGdakQjxH4kTITQ0lEyZMnH+/PlEo5rTm+DgYJYsWcKxY8d48+YNAKVq1qP31Hnf/dh/OsnNZRUEFTHPDqIK8UNiYMn4UQOoWbPmNx8vS/bYOYYxX8ZvAz9F8z7gLQO6t+P82VNMmTGHdp26aoVX84uN6/G+ClV3rV1/q85mZWGkFoPrr9Truz4LUG/3+zI9JyggmPBQ9b7K1b0BCHjzlqd7FiCxdMXUvTDTulbhld9jDq9bxJ5/NmFkbkHd1l2o2LAV2WzVkb7rb6p/nz09U3+zscuaE0EQ6NGxDdu2bMTDMxe9+gygfqMmqATYu3sHSxbOw8bOnkUr1T0DGuHVXIsYpQrpFyWTSSUU8s6DhYUF3j4FOHPmDHdv30QQBAoULkKDpq2oWbcB5uaZkH9Z+1hj9eabL8mSKba72PNLrmXTL8fz+xBGDrvYv30zQz3ttY8rvJpxXj2ZRCeNJYB7NieqVK3GvIVLteWlcVRYIoHH90Xxjc+BAwdwcnIiT548SKVSLl26RPv2sVMyTczMWXbmOvqG6oe74PcBrJ02jotHDhAZHoZEIlEHAIaE6IybpicajTh10x9Ts28/xudPoZTJ55JiWz99+sSIESPYsWMHAQEBZM6cmaZNmzJy5EitUyAIAmPGjGHx4sUEBwdTpEgR5s+fr40c/xH8lMIbl/DwcJo1a8aTJ0/oNGoilZtm3NPbn0iSnq4g4Fy2AlJ9dZ7YZzsWEfN4F/IsFbi2b1a62qBvow5qUqlUtK5fBfNM5mz6Z3cC4dXctKMVasEO+SLEr4LVInzzfUiqhPfqhpm8OrMNBAFBGYOtoxMf3r7G1t6BQvXaUahaY/I6qwXXU5b2DG52WXOyb/cO2rVozIw5C2nXoQOBHz6wYtlSVixdxJs3rzE1NSOzswuHz/4HJBRezTWIUaqQSSW0aNKQjx+D2X/oGEFh0YSGhHDi6CG2blzL6RNHcczsxKVbsRmsNH/8Gvk79zxQK7oQK7wGcql2rFYjuqAWe4CwKIWO6GpQqASt8E6bOolRw4cyYfJUSpUuy7X/ruLomJnqNWpqvWBReHXZs2cPQ4cO/fJJgpmZKZGRkahUKvIWK8XLp4+I+PyZWXtOYGWfMK7i8vHDbJ47Fb97d35L4f1V+Wm6mpPC2NiYDRs2UKFCBZaOHYp7Xm+y58n/o836oxAEASsjf54taolzyznoWzph6ZqFgMcSZBbuyTfwjUilUqQymXYuuHbqjET9Su8YvMgPL7Fwy4997eGEP7tOPn1/XNxy0KltB/Y9DUrfg6FOEjJicH8qV61O+b8q0bVjO/7ZuhmZTEajJs1p3r4rKxbN4/7d28ikEq3wJdblHh0ZwcwZUzl86AB58+UnKEzdDWyeKRO16jWkROmylC2SnyLFS2nrJPbEXcrVhvdflmI0jZeuM64Nms8aTAzkKFWCjugC6uQoXxJN9xswiJCPHxk6aIB2v6GhIXcfPsXR0RGA7J55RPGNw4oVK5BIpdTr1JOHN67y6uljomJi6DpmCuXqNU62fuHylcjtW4yWhXJmgLViruaU8sOjmlOCsbExa9euRSKRMLJFPfyfPPrRJv22JFhNxzYryrCnvLmwB6lcn6DDMxCUCj7dP0XpchV4fHIOFk45Em8sDZgZyTHWl+D35BE2dg5IJRKiFN832t3QOjNhb56CoMLMoxgdBv2Pyg1baQOC0ptZ0yby4X0AI8dMoEn9Wpw4fpQRo//H3UcvmD1/Mbm88hAeHoaxiQkApoa6Ec1SiQSlUsma1SvJl9uDaZMn0rlrd1Zs2qkto+nQmjR2BIIgMHbilASZwuIPudrGi5A2iCP0Bl+82riiqyHBti8fY76MR0skEsaOn8jufYc4eeY8T56/xsDAgBnTpuhUy+7547oAfyY+f/7M48dPcM+dj2a9BzF65RaWnvqPjdefpkh0fwTpFdX8u/PTe7wasmfPzsSJExk8eDB9a5Wn74yFFKtcI/mKImlC9fIWiseHkLmWR2LrxadL8+hteZdxL29Ra0DCBcDTin1WT+37c2dO8e7tG6rVrJNo2aioKM6ePkWhoiW0i6kDZLFWd4dbGOlROosNUQoVEV/m3r4JU3dDB0equ6WdzYxw+7KMXUSxMZQpto8yYUeZNXEenyJiA6Bq22uiRNMnWvTMmTPMmT4Fr8JFadq8EQH+zzn570W8cufR8eTDw8MwjrMMnJ4sNp/18WNHGTKoP7du3qBBw8b8b/xEsrm68vj+bYI/Beg8EH0M+UhEeBinjh+lQeNmmH3xZkPjnGNc4bS3MCQsSqEjunKZ9Mv/X8aHE7lJqgSQfumRiEuMQkBPLkEqkfJXRXUWIYkE6jdoxK6d25k6fWbqLuAfQHBwsHrc+9Z1JndvR6+p875pScCt88Vr+7PxywgvQLVq1XB2dqZdu3ZM69WJuh170KLf0OQriqSY+GO8yg+3QKaP3LU8Epk+ufJ6s2HtKgRBIGeu2DmYFk45+PgqfXsidu/YikuWrBRMZC3aT58+0aheHU6fOoGllRU9e/dDX1+fmOgYWnbqiZ6eXiItfh139+y069iFjetWM2PWnPQ4hSSZMGECAE/v3CQyPJyqVatioi9N0H0eFRnJzev/0a5ZXZycnMmSJQuZMzuxY/tWDh3YT5GixTh55jy+RYomCE7SfB+mjtmZvXg1I/v3oHvHNpw4ehhBpeTFi+dER0UxZfos8hQoqq0n/SLAmYzU1zAyRqkV3bgklYRAG1QlkxCjiFVnpVLdESmXSbVjuufP/0vJkrqrM4ldzWpcXFzYt28fPXv25NKxg7Qu4kWRv6rQvO+QFC+csGvFInavTP8H5KTI6KjmX5Vfoqs5Lvny5ePQoUPY2dmxY+k8xrRtLCbcSCfii64q/D3KwNvIrL2QyNQRgsVKVeDJQ3VWIqVS+V27hl48f0Y+7wJIJBIM9KQY6ElBou6yXLlsKadPnQAgOCiIsSOHMXzwAMaMHMqxQ/u/+ZiVq1YjICCAq1e+75JqHTt2JE+ePJiZmJDf25tJk9Tr9vo/uat9AXTvPYA6DRojlUq5evkic2fPoEvHtjy4f4+1GzazZPEirC1Mv7qi0+c3j7EwNWL2wmWMGDuB6/9dIeDdOzw8cmJgaEiNKn+xZf1KIFZ042KoJ9MGSBnr63Z3fy02Mzwq8QVTFF/+Xu/fu8e9u3ep16Dhl7ZE0Y2Pi4sLO3fuZOLEiWQyN+PfA7vpVrEYXcr7snP5AhSKhCtNxcXZPXsGWfoFIR1efwC/lMerwdramsOHD9OxY0cunz9D1wpFmPrPQcytMiZj0e9GYpHMQkw40X77kRhYIncoDO+fc3ltFy7c8WfFgukAKJRf/6P/FiIiIrj+3xUsrax4+eI5hQr7YmIgR6WCuPPkK1epxqNHD3jp/5KTJ45pV3MBUKbBriJFi2NhYcGe3TvxzFsgLafyVerVq6ddLSUpPr56SG53J/6aNVe7zUAuIywsDGNjQ54/vq/dnpxgBTxXp8wcMHAQAwYO0m6PiYlhYL/e9OnRhTu3bvK/SdOQyfW0QhsXQ7kUlUpAKpWgihNkFaVQam1TfRFiTaR5jFKFnkyKtjntuK8KqVSKTCbj3L9nqV5DPU9fnM+bODVq1KBGjRrcv3+f2bNnc+HCRdZOHcfaqePQMzDAxMwcSzsHuo+bjqtX7Bi5T6ny2ulEIj8Pv6Twgjo7yYoVK5g2bRqrV6+mc7nCdBg5ngr1m/5o09gwazKv/Z5gbGZOZlc3KjVugbHprxMaLyijiX6yCwQV+q7VkEhju21f3b+kfe/mrh5DTK8uZie3XEwcN5qpE8cBYGllRaOmzRMt65krF3MXLEalglcvX7Jz5z8UL1kaRXQMBQsXJigwkCsnjxEZHUP5ilVxssqEQimQw149nqvx7PRkEvQ13agSkMv0aNm6LfPmzKJFyzZIhYzLipUUb/zu63x2y/ntaRafP1J70llzqOdP6+npMXnGXHLlzsvgfr24f+8uazdswdraWttlHJ+49/C4ubNDImIwM5RrRVeDShDU057iablbdg8mTJrKoAF9KVy4CHXq1f/m8/pT8PT0ZOHChahUKrZt28bJkyd58+YNgYGB+N29xZj2TVjx701tNiepVIqhsQkRYZ8zxD4xqjll/PTzeFPCgQMHGD58ONHR0Vg7ONJjwizyxZk2kRbePFev7OKY1TVF5ddM/R+7li9MsN3Y1AxBELB2yEyvKXNTtMxXRhHf4xWkEHV9MVJTF/Rcq2rH8QRBQPZoFeHh4RQpUZZli+Ym1lyqsHGJneagVMZQslBe8vsUoFmLVhQtXhKLTOqFC6QSidbjlRBrD6gDetRlQCkIKBQKyhT35dZN9co6OXN5sXbLLhydsminuyQmvDGKGEaNGMqWTRt58/o1RYsVZ/GihQlS0v1OOLrGCWY7e4a2zRthZGTEoKHDqde4Bfr6+sikEh0PWONBxRXdyBj1ez2ZRCcphiZgSy6VEBUdReCHD3z48J7A9x8IDPxAUOAHJo4fS1RUFFeu3SYm8tP3PuXflnnz5rF48WKqNG9LxxHqv+ldKxaxZop64Y2MmMd77NoLTNIwjzfsUygVfLL89vN4f4s7StWqVTl//jx169YlOOAdY9o1pm/tv9I87Wjx6MH0qFyCHpVL0CS/K6NaN0h2TMXCxg6pVIok3s3aUF8PK4tMvHr6iAH1K7N53vQ02ZaeaKcQGZmDkTkSA3P0stdCFeqH4u3l2IKKCMLD1evfujjaJNLStzN/9jScrU145veU9h27UKlKtQR/eEqlgFIpoFCqEl2FR4Pf0yfcunmD1es3c/rSdcLDwilVKA99unfg5vVridYJCAigZtVKzJ8zmypVq1OjZm3MzM2T/b5/deJ608VLluLUv5co7FuEv7t3oYh3LlYtX0xEnLy/mocwiUSCgVw93hsZoyI8LIxbN66xbdN6xo8Zwd9dO9CiUR0qli1OgTweONtbYpvJGE/3LJQsUpDaNSrTrnVzhg0ZiKGREZ65vDh57GDGnvxvRo8ePbCzs+PQhlXM6t+dcwd2s2HmJO10tIxASId/fwK/hccbl48fPzJo0CDOnTsHQOZsblRp3pbKTVsjl3+9Z/3x7RusmjSaV08fI5frERTwFmdnZwoXLszx48cJCQlJVerK4PcB/HtgNysnjMTa2pqjR4/y5MkT7RJdC46cT3F0YkbQvG2sByuolETfWAZSGQYejbTbB9S0YuPGjSxbtgxr67SPqdu45OTVS39KFspN7XoNqdugMRUrVdYJ8pHE6aPUbJZIJNr38T3e0NBQnO0sWbZyLbUaNCEwMIh1q5axevkS3r19zcUbD3D+st6nnkyCnlRCx3atuX7tP+YsWESJErG9JX/SeGPWOOk7b9y6xcypk9ixbTMOjpnp028gbdp1ICoqigf37/Hg/j3u37/Lwwf3uX/vLs+fPdPWdczshJOzMzY2tlhZ22Bna4uNjS3WtjbY2NhqX/b2dpiYmCCRSP6o6/w9uXv3Lu3atSMsLEy7bezYsYwcOTJDPN6j156n2eP9yyfrb+/x/nbCq8HPz48xY8Zw/fp1lEolUpmMrB65yFmgMFWatsIle07uXL7AzL5dCAsNRU9fn7BPoYB6SaqwsDCqVavGuHHjmDRpEhs3bgSg6/+m8lfDxMcdk2LzvOlsmTcdHx8frl1Te1yuXnkYt27nN83LSy9UKhXP7t3h2tkTPLx2lWt33iIoo0CqDzFhqEKeoZ+nBVK5OZfXdvkuNti45OT40UM0b1CT3QeOUrJ0WUJDQrhx7SreBQtxYN8e5syYyrt3b3FyciF7jhxMmDQNJ2fnRIVXg5O9FX37D6Ju7di53sYWDnhkc6Brj15079mLSxfP88zvKe7u2WnRtBF79h2i/F8Vefrwz10nViO+mmQljx/eZ+a0SWzbvBF9fX3tqjcSiYRsrq54enrhmSsX2bLnxCNnLnJ45CQi+E2C9gCeP76rfe+eMzYASBTd9CcwMJADBw6gUCho0KABxYoVyxjh/S8dhLeAKLzArym8GhQKBZs3b2bTpk34+/ujVKojMPMUKcHti/8ilcnI4uLCp0+fKFCgAIMGDdKu03jt2jV69epFcHAwUpkMN6+8VG7aitK1GiTrPcdnXMfmXDujnv5SqUkrOo+elL4nmkruXbnI6LaNUcTEBg8ZGRkRZeCIoIwBVQwyex/k9t5cXvL9VvGwccmJvgxKFStIZEQE/QYO5emTR0yfMlFbpnLV6hQqXIRXL/3Zv283bm7Z2XfomM7KSJrYHaVSyeVLF2nWpAE1a9WhV8/u2jKZXXPRv3cPVi7TnddobW3Np0+feP4qAHNz8z9aeAEcsqnHfeNOUXr13I/dO7fj7OyCh2cucnrm1Ela8jlS3SWviZ7WoBHeuKILscIriu735/PnzxkmvEfSQXgrisKr5lcW3rjcvHmTFi1aaINyNBGCNjYJxysPHTpE//79tZ9lMplWtCUSCZmzuTNmzTYsbdVrkqpUKh7fukb2vD6JBuOoVCr61a6AQqFg9r5TPzRg5/qZE4zv3BKJVErrVq0oUaIEBQoUQC6XU7jTBm257ym4cXFx9+L2rZs0b1yP58/8MDU1JW8+bxo2aUaBgoXw9ikYa9PFc1SrVJ48efOxZMUaPD3Vi7dLJHDl0kUaNahDwLt32NjYMHHydIr6xk4JyuyqLhvw9g0XL5zFp0AhZk6bxKoVywGYt2Axbdt3/OOFF3SDrjSLH2iCpuKPwz19IF6vnxlReH8+fkvhHTFiBGfOnMHX15dSpUpRoUIFVqxYweIlS0AQkMlkjBo1irp16+Ln58eUKVPw9/dHLpejp6eHoaEh169f17bn7e3NwoULkcvl7Ny5k71793Ljxg1MzMyZvHU/WxbM4vyhPcRERWFsZk6vKXMpVK7ij7sAiXDvv8scWLeC2xfOEhIUiJ6eHuvWrcPLyyv5yt8ZF3cvVCoVVqbqaUtly//F+s3bMTZRd8O/fHJPWzZrDi+u/XeVDm1a8tL/BYuWrqReg0ZERkZQvLAPpmZmTJ0+iyJFiyGTyXQ8Ko3wyqSxEdJ1qlfh+LEjgPpBbOvWrRlxyr8Mrh7qqUtxI5WfPLitndIkiu7PT0YK76H/nmGShqmTYZ9DqVwgmyi88OsJb7Vq1fD390+w3cjUjIjPn3B0dMTHx4c7d+7w/PlzAPQNDVHExKBSxmbb0dPTY/To0dSqVStBW5s2bWL8+NhpONbW1hQtWpRDhw6hUCjI6pELfSMjPocEE/7pE0qFgvpdelGrbWeddiLCPussYp1abp47w57VS3j15BH6hkYYmphgZGKCsak5xmbmvH/tz/3/LhMTpV5xxszMDG9vb4YMGYLLlwCjn4HM2XLStWMbnF2y0H/wcAJf+yVaTjP/9N8zp6lasRztO3Zm1tyFzJ4xleFDB3H42ClKllKnINRohb+/P/+ePUPjJk2RSCQ6ySZmzpzJq1evuHr1Ku7u7ixbtuz7nugviDge+2uTkcJ7MB2Et4oovGp+NeG9dOkSHTp0QBAEpDIZdk4u5PYtTuWmrfhf+6aEfQpVC6xEgo29IzHR0YQEfQBAKpNhbWVF3rx5GT9+/FfPd9OmTRw4cICePXtSqFAhQH2tevfuzZUrV5BKpegbGGBkaEhERAQRERHkyOeDlb0jwQFv8bt/h5ioKOydszBk0Rpcsnuk+BxvXTjLxK6tiYpQJ/03NjZGqVSiUCpRKZU6mWocHB2p+NdftGzZUrv82q9K1hxePH3yhIrlSuLq6sa+Q0cxMTbhxo3r1KpeGTMzM3buPkD2HDm0wjtvzmwG9OtNjVq12bJtB08S8dIqVqxI1qxZReEV+e0Qhffn47cUXlCv7DFu3DiOHTuGUqlE38CQ7Pm8KV+vCQ+uX+HS0YOEBKrF1sjIiIIFC9K2bVt8fX2/iz2RkZG0bt2au3fVQSYSiQQnJyecnZ25ePEiggClatSlWJUaGJuaYmRsgpGZGfYu2RIEcp3dv4tZ/bohk8lo3rw5bdu2TXRqj2bOrfEPjJxOK5GRkezcuZMyZcrg6OhIeLRA7RqVMTM14/CJM9jZ2SJBgoDAMz8/6tWqzocP79nyzy6KlygBwNUrVyhZrDAAbz985P2bhL0hovCK/K5kpPAeuJp24a1a8PcX3l82ZWRyWFpaMn36dCIjI5k3bx5Hjhzh7uUL3L18AVCLUdmyZWnXrh0+Pj7f3R5DQ0M2b96c6L6nT5/So0cPzuzdzpm923X2yWRyytRpSMcR49E3NNRmotG05+bmluQxf2XBPXr0KI+fPmPrlk0EvHuHQgVVqtWgXq1qOLtkYefeg9ja2urUyebqyrHT/9KsUX2qVa5A7tx5kOvp6QSyRUZGihG1IiLfCXF1opTx23q8iREeHs6GDRswNjamWbOMidhNDRcuXODFixdERkYSHh7O58+f2b9/P+/fv0cml+Ps7sHzB3fJlCkT27dvx87O7keb/F1QqVR4e3sjCAKdu3TjypXLvH8fQOCHD+TNl5+tO/ZiaWkBaKYRSbR/sFKJhKioKGbNmMZLf3+io6OJiYnhwoVz+D19yoBBQxg9dnyCpA2ixyvyu5KRHu/+q35p9nirFXQVPd7fCWNjYzp06PCjzUiSokWLUrRoUZ1t/fv3Z//+/UyZMoXnD+6SJ08eVq5ciaGh4Q+y8vsjlUpp1aoV69evV6dyrF2HlcuW0qJVG8aOn4SxcWwKPE20bdzsVgYGBgwaMkynTUEQmDljGsMGD+TVy5csWCwKrIhIeqMSYhPafGv9P4E/Snh/VapVq0a1aup1Yn9XLzc+/fv3p3rNurRo1ohDB/dTv2Ejev7dB1NN3lmJrtgmh0QioW+/Abi4ZKFD21a8fv2KoUMG//LBZiIiPxPq1YnS0tX8Z/BbLJLwp/CniK6G6jVrcfveY/oPHMyxo0f4q3wpHj9K28IXDRs1Zt+ho9y4fo0ePXry7v1H3HPm4emLN5w4cyGdLBcR+TMRhLS//gRE4RX5aXn68A5Ozs4MGjKcs+evkMk8E1UqleP0qZNpardkyVIcP3WOly9fUrFCaebPnZ0+BouIiIikAFF4RX4J7O3t2XfoGO7u2alaqTzdOnfg9KmTxMQoUAkCqlQ+Kuf09OTC5WtkymTBgH69ad2y6XeyXETkz0FcFjBliMIr8svg6OjIgSPHmTR1OkcOH6JKxXLk8/LQ5tBOLdlz5ODJ81fqSOnNm+jSqT3R0dHJV4zDw4cPGTJkCB8/fvwmG0REfic0wVVpef0JiMFVIj818RcscMuZm569+tC9Zy9GDB3MkkULvnnBCQEBQyNDLly5xv9Gj2Tq5IkEBwWxcu16jAyN0MRuxZ2uBLH5iZs2bcrt2+opSWFhYcyZM+eb7BAREfmzED1ekV+Oz58/s2vHdk6dPEE2VzckkpRHNyfFiNFj2bx1B0ePHKJ44QLs3rWDpKa4u+XMTbYcufDz86NqtRrUrlOP06dPp9pbFhH53RC7mlOGKLwivxTBwcF45/GkRdNGKGJiGDh4KFKJRGf1nG+lavUanDx7gSzZstG0UX3Kly7B6VMnCQsLIzIyUqdLWyqVUrxkKWIUMQwYPBSlUsmDJ89w9ciNW5yXiMifhBjVnDJE4RX5pZg+ZRKhISFcvX6Hi1dv0LhJ+gZF5cmbl117D7D3wBFiYmKoWrE8tpamWJsbY5PJhDYtm3Pu37MIgkDBgoW5eP4cBQoUpHiJkgwe0JeundoxYthg/rt6BVAvq5cthyjAIiIisYhjvCK/DFZ2TiycP5c+/QaQKw3rCKufrAUUiURyyKVqz7lchQqcLneRkyeO8+H9e5RKJa9evWTNqhVULLcRr9x5+PgxmFKlywIwbeYcJvxvDA/u3+fI4UPMnD6Vjp26MGLMOCwsLMmWI7d2tSSVIPD80d1vtl9E5GclrV7rn+LxisIr8sugUqmIjIwkd568GXI8qVRK+Qp/6Wzr238gJ08cZ9niRfx79jT/mzAJAYH83t5s2rYDAKVCweKF8xk7egQrli+lYCFffAoUICQkBAsLC8ZOmEzWHF6i+Ir8dggIqMRFEpJFFF6RXwYLCwv09fV5+dKfdBjSBSAiIoLdO//hwf37PHn8CEVMDKvWbsDI2CjR8hoxji/IgNYmuZ6c7n/3on6jxuzZtZNTJ09w4vgxrKytuXr5EkgkTJ42M31OQERE5JdDFF6RX4bLly4SHR1NgQIF06U9/xcvaNqwDrdu3sDZ2YVsrm6cPXOK27duUrhIkTS37+DgQMfOXejYuQsqlVqYJ034H+PGjKLfgMHpcAYiIj8Xv1tXc0hICDt27ODMmTM8e/aM8PBwbG1t8fHxoXLlyhQvXvyb2hWDq0R+arJ75iG7Zx6cs2VnxrTJODg4ULxEyRTXV6mE2Jcg6Pxhz5s9nVs3b7Bm/SZu3HmAsbExhoaGWFvb6LQhSeRfapFK1NOC7929i3v2HNjEW0tYROR34HeZTvTmzRs6duyIo6MjY8eOJSwsDG9vbypUqICzszMnTpygYsWKeHl5JbnO+tcQPV6Rn5Lsnnm07wVBoEnDepw8cZylK1Yjk8m+WlcTPJWcPtZr0JhDB/bTrnULfHwK8tTvCVu378bN3T1Z+xIT3+RuGq9fvWLn9m1MnDID8ZlX5Hfkd/F48+fPT6tWrbh06RJ58uRJtExERAQ7d+5kxowZ+Pv7079//xS3LwqvyE/P4oULOHTwADv37Kdylarp1m6x4iW4dO02q1Ys4emTJ0yaNoOiRYulW/vxeernh1KppEgx3e6prNnVEdrPH4vBViIiPwN37tzBNpleKSMjI5o2bUrTpk15//59qtoXhVfkp0Dj4T6+f1u77d27dyxbsojpUyfTuWv3dBVdDYaGhnTr8ff3XQj0S9vePgWQy+Uc2LeH/N4FEhTLmt1LFF+RXxpVGqOa01I3PUlOdNNaXhRekR9K3C5lzWeN+Pbp1YPDBw9QsXIVJkyakuq2pRJJkt3NEolEt7M3kXKCwFejp1PbLWZiYkyHTl2YNH4sL54/p02r5hQtVUGnTNbsXgjAC1GARX5Bfpeu5sT49OkTY8eO5eTJkyiVSkqUKMGoUaOwsbFJvnI8ROEVyXDiim1kZCQSiYSoqCgqlitN3foNqFOrBkFBQezbs5v/jZ/E3737pKhdnaUBJckLZ1rRtJ2am8XUGbPx9ilIv9492LZlI6XLlqNa9ZpUrVYTJ2fn72OoiIhImunYsSNGRkaMGTOGmJgYlixZQvPmzTl06FCq2xKFVyTdiSuscbuO4+5bMG8uSxYv4MH9+4B6vPXmzRvcvHmDDevXolQqUSqVNG7aLNnjaYQv/ipCGU3cgKuk7ZDQvGVryparwM4d2ziwby8D+/Wmb68e5Pf2Yc6CJXj7JOyGFhH5FRBI26jNz+Twzpw5k969e2sXYbl8+TIPHz7UBnfmzJmTokWLflPbovCKpBvuOdWiGtfT1HQdK5Fz6OABni9eyuNHDzl86CCNmzSjYMHCbFi/Fn19fTZu+QcTExN279yBTCYjv7cP9vb2OsfQiux39GTTHQkJ7ihOzs5079mb7j178/HjR44ePsjY0SOYOmk86zf/80PMFBFJK4IgJLmqV0rr/yw8fvyYIkWKsHjxYnx8fKhYsSLVq1enTp06xMTEsHbtWipXrvxNbYvCK5IuuHnkRhAE7dOhIEBQUCBXLl9ixfKl7Nm1EwMDA7Jmy0a2bK7MmDWXLt26AxLmLVyCoaEhoBbUipWS/jFLJCnv2k2rOKeruH8ZbpZIQKXS3WVhYUGDRk14++4to4YNJjgoOB0PLCIi8i3Mnz+f8+fP065dO8qVK8fEiRNZt24dR44cQalU0rBhQ3r06PFNbYvCK5Jm3HJ+WX3ny/xZiUSC/4sXFC3sTXBwMDlyeLBw8TKaNGuOgYGBumgc8dSIbnogQZLh3nDc46XkoUAaJ6orrgjXb9CIYYP6s3vXdlq1aQ+A/xMxyErk10H15ZWW+j8TxYoV4/Lly0yaNIlixYoxdepU/vkn7T1SovCKJIu2C/lLf+nTB3e0+7SiC7wLeMepE8d55veUnTu2Y2xiwtGTZ8mZ0xOpVPpNwUgpITVe8PdGY4tmvDe5MWepdsUicHB0pHTZcmzdvFErvCIivxK/U1ezBrlczvDhw2ncuDFdunRh9erVzJs3DwcHh29uU0yfI/JVNKILsWLiljO39vXx40dWr1xO1UoVyJ7VibatmjN/7mz09PRYs24TuXJ5IfmiLirhS9rGRMRImzAuBX93v9L4bkpTTEol6ulP3j4F8Xv6JAMsExER+Rq3bt3C19cXMzMzSpQogUql4tixY1SrVo3ixYuzcOHCb25bFF6RFKNUKlm+dAl5PLOT2dYSO0szXBxs6N6lEzKZjHkLF/Ps1Tuevw7g1L8XKBongXh8sY37WRAEneCj9Hzo1cwrTOv8wrSSaJ7nROx59/YNmTM7AWI3s8ivh5AOr5+Ftm3bUrJkSS5fvkzDhg3p0qULAO3atePixYucPXuWYsW+LdOd2NUskmL27NrJ39270LBRE7wLqLMwmZqaUrlKNRwzZ06yXrLdrpqoXwEEiRBbPu603GScxl/NC4Z4Dx9f/v/8+RPBwUFERIT9AMtERNLG79TV/ODBAzZt2kT27NnJkSMHs2bN0u6ztbVl/fr1HD58+JvaFoVX5Ks8eXBb291snikTAKPGjMPN3T2BkMafRxu/i1WzP9Htkq97vd87GUZ6ktKx7NgIcHVBlSDQf9BQqlUsR9uWTdm4ZQcyuYznj0TPV+TX4HcKripbtiydOnWiSZMmHD9+nBIlSiQoU6lSpW9qW+xqFkmWJw9uIyBol7ILCHgHJBTWuKKa1Ljm18Y7pVIJUknyUcnf2nX8swq3RKI+bwAfn4Ks3rCZI4cO0rdXdwRBwMXd6wdbKCLy57FmzRoKFCjArl27cHNzS9OYbnxEj1ckWTSRy/4vngPg7JJFuy+xbFGpXa9WnVJZkmBbarqa46IS0mZPevAtPWayL0FolSpXZe6CJXTr3B4nZxf6DxqGk1suZFKJTg5nN4/YiPKnD+8kaE9EJKP5nbqaLS0tmTZt2ndpW/R4Rb6KRnSvXrnMyOFDsbG1JbNTZp1Fq5Pzcr9GSsZuUyK6P0MAVUpJ7nxkUgktW7dl6IjRjBszkvVrV2n3Zc2h9n7dPHIzZ9YMDh7YD4BrHBEWEflRxA9m/JbXz8CLFy9SVf7Vq1epKi8Kr0iSaET33bt3VChTEgMDA/bsP6wdmwQSiG9KSYmgpmb/z9aNnNpzi99rIJXAkGEjaN22A726d+bEscPaOtly5ObmzRsMGdSfNi2bcuPGdZ75+YniKyKSThQuXJiOHTty6dKlJMuEhISwdOlS8uTJw/bt21PVvtjVLJIocZNmvHn9mpiYGOYuWES+/PlT3Mb3TJiREXXSSkoyWilUqq+Oa/fqO4A3b17Tulkj9h85gY9PQQAm/G8M2bK5Eh0TTXHfAkilUq7duo9bjtw8eyR2O4v8OH4SpzVN3Lt3jwkTJlClShX09PQoVKgQmTNnxtDQkODgYO7evcudO3coVKgQU6dOpWrV1K0VLnq8Il9FgoTIyAgADA2NUl4vCW80pV3HaUES/99P4A3HP+/EhFjba/AlwHv50iUUyJsTWzt7snvkpGHdmhzYv5eF8+ewZ/dOho4YxfFT51i/eRsmJiZs2rAOiO2OFhHJaDRJctLy+hmwsrJi2rRpvH79moULF+Lh4cGHDx949OgRAM2bN+fq1av8+++/qRZdED1ekUSIm60KwO/JUwBs7ewSlE2sizkpofvugpvKnMk/AvUiCSpWLF/G4oXz0dPTY9vOvTg4xK7CJAAKpcCuneqcsP9s2UjxEqUICQ6mUb1aAJQuW45GTZohl8txdnHhwL69rFyxlKyurlSvWVvnmHGjosWkHCIiKcfQ0JB69epRr169dG1X9HhFdHDLmVs73nju37PMmjGNNWtWUqBgIWy/TCcCdXrDxLpIf5To/kpcvHCBnt06A/DmzWtqVK6ASplwBqNLlmzkyZuftRu3cfzYESpVrsp/N+8SGBLO/kPHkMtjn5v7DRyCq6s7XTq0xdPNBT1jS7Jm98Ixqwcf3r/XlnNyy/X9T1Dkj+V3ylz1PRGFVyRRBARmTp/K0MEDOH3yBLXrxD7xSeOpqKYbVRTXlFGkaDGqVa/Jq5f+/G/8JO7du8ulixfUDzxf7jwyqYRixYpx+9YNBvXrBcDr16/I6emJoVHC1Zxy5MjBkROn2b3/MGFhYfi/eMbSxQspkDcnBfJ6oFQqf5puPJHfF810orS8/gTErmYRLW4euWMfOSVg72CPra0tm7buoLBvkZ9mvDQl/Ox2Ll6+ijLFfZk9czrm5ubs2rWdt2/fcOL4McaOn4SZmTnNWrTG2saWfXt28XfvvtSqG/vwk9SKTFbW6l6J2tUrERkZiWcuL148f8bnsDDMzMx49fReRp2iyB/I75S56nsiCq8IoBbdVy9fMmb0CAz09clkYYGhoRHv37+nT68eXLh87Ueb+FugUqnV0tLSknWbtvJX2ZKEh4dz9/Yd5sycgVwu58zpU2zcuoPs2XNQpWp1qlarobOGr4b44isI4OziTDZXN8qUK0+vvgO4e+cOLRrXI/TzZ0Lfv8ygsxQREfkaovCK4J4zD8HBwTx69JD1a1fj5OyMgYEBIR8/IpfLadykGfDze5G/CgLqdSHy5/dmy/ZdTJ8yiaNHDjFq7Hhq1q5DkwZ1KV+qKBMmT6N0mfJkzZb1S42EaMRXI8BWVlbcvPcIQQClSmDB3NlY29hiYWHJx4iPGXSGIn8qaU2C8Yf0NIvCK6KmaaN63LxxHYlEQslSZVixei0QJyuVKLppJv5NRSKRUK5cBc79e5aLF87TsXM3zDOZc/zMeTq3a023zh0AGDnmfwwaMkw7tp4wJaYmMCXuUosQHBTE+rWr6NGrHx/f+H3PUxMRAUBF2qYEqX7S8KqHDx9y8uRJAgICUKl0O8RHjhyZ6vbE4Ko/HPeceYiMjOTC+XM4O7sgCAK7dvxDeFg48GXhA1F00w2Nt6tBKpXQrn1HoqKi2LhB/bBjbWXJtp27efriLc4uLnz8GJwgoE2nQXQfjJRKgYsXzjGg79+olEqK+xb4LuciIvInsHTpUry8vBg5ciTbtm1jx44d2tfOnTu/qU3R4/2D0czXVSgU6OnpUaJUaeYtWsK2rZuRyWUJ1sUVBThtSCQgk0hQqQSdtJtOTk7UrFWH5UsW0bVbd+12Wzs7oqOjsbSw1GlH6/mqEnoHKhWMHzuKaZPHY2FpSbFixciePft3OiMREV1+x67mcePGMX78eAYNGpRubYoerwiRkZHY2Npy7b+r+PoWZcrUmRgYGGi9XYkEgoICWbVyBbdu3vop/zh+JaTShN33nbt15/69u4wYMhhBEFCp4Np/VwkKDMTC0uqr7QjEdj/v/GcL0yaPZ8iIMdx9+pqNu75toW4RkW/hR2SuevXqFS1atMDa2hpjY2O8vb25evWqdr8gCIwePZrMmTNjZGRE2bJluXMn5WlVg4ODadiwYart+hqi8P4huOfMkyAj1aVLF+nYrjU53bPwKTSU5SvXavfNnTWTLh3bM2vGdOrVrkk2Zwe6dmpP7ZpVCAgIEMU3jcQVXZUgULpMWaZOn8XMGVMpXbwIY0cNp0KZ4uTNl5+69Rokeb3jiq6gEujf929q1qlHr/6DkUhlfHjx4PufjIjIDyI4OJgSJUqgp6fHgQMHuHv3LtOnT8fCwkJbZsqUKcyYMYN58+Zx+fJlHBwcqFixIp8+fUrRMRo2bMjhw+n7ACt2Nf8BZPeMFVz3nHlQKpWMGzuayRPH4ebuzqAhw2nVpi2Ojo6Aurtn5fKlvH37ho3r11KwUGEmT5tJseIlqFW9Mq1bNmXPvkPI5XKx+zmdkCChe89eODm7MHniOKZPnUSPv3szdtxE9PX1E60jCOpuZ5WgTrzx4sVzPrx/T8vWbRCQiKIrkuGoBPUrLfVTw+TJk3FxcWHlypXabdmyZdO+FwSBWbNmMWzYMG3ax9WrV2Nvb8+GDRvo3LlzssfInj07I0aM4MKFC+TNmxc9PT2d/X///XfqjEYU3j+O9+8DaN2iKadPnWTM/ybQb8AgpFJpgoUMwiPC6dKtJyNGjUH6ZRKpgMDaDZupUaUiQwb3Z9r0WT/mJH4zpBKJ1qOtU7cederWQ6FQ6KSEjE9cD1gulaJQqbh18zoA+fJ5Y6Iv48N3tFlEJDHSa4w3NDRUZ7uBgQEGBgYJyu/evZvKlSvTsGFDTp06hZOTE926daNjx44A+Pn58fbtWypVqqTTVpkyZTh37lyKhHfJkiWYmppy6tQpTp06pbNPIpF8k/CKXc2/McHBwTre7vNnzyhTsih3795h38GjDBg0JIHoaggPC8PE1EQruk8e3ObpgzvqLtEZs5g/ZzabNmwQu5zTifgpNzWiq9mWXM+CXCrFzt4BgK2bNibYnzWHl7hqkcgvg4uLC5kyZdK+Jk6cmGi5p0+fsnDhQnLkyMGhQ4fo0qULf//9N2vWrAHg7du3ANjb2+vUs7e31+5LDj8/vyRfT58+/abzE4X3N2XTpk2ULl2atatXq+d0Bn/kr/KlAdi1+wDu7tl5/OgR4eHhidZXqVScOHaUV690sx09fXCHCmVL07hpc3r17Mrz589E8f1OfE10E9tWrFgx/u7dj7GjhxMYGIixuQ2Hj5/CIYu7towoviLfExVCml8A/v7+hISEaF9DhgxJ/HgqFQUKFGDChAn4+PjQuXNnOnbsyMKFC3XKSeL9wQiCkGBbSkivfNKi8P6GnDx5kvHjxwOwds1KBEFgw7o1vPT35927dxQrUgAP9yzky+1Bh3atuH3rFtWrVKRG1Uoc2L+PiIgIqteszc0b1ylTsijnTh/TaV8qldK2dUvMM2WiQd1aTJ44jgP796NQKH/E6f5WpNTDjY8meUbPXn1RKBT069Wdgt5e9OvVgzWrVuiUzZpdFF+R74QQ2938LS/NvHRzc3OdV2LdzACOjo54een+nnPlysWLFy8AcHBQ9wLF924DAgISeMFfY82aNeTNmxcjIyOMjIzIly8fa9euTb5iEojC+xvSr18/9PQN8P2rKmdOn8Irpxv9+/YiT958RISHM33mHHbvO4SFhQVRkZF079qJJ08ec/3af0wYN5aSxQqzbs0qMllY8DE4mO07dyc4hpOTE506dsTa2prZM6dTr3Z1tm3ZnOYxHpGUia5OjuY42X4yZ3akWPGSbP9nK9Vr1KZy1eosmDMLpVKpKSwi8t3QBFel5ZUaSpQowYMHukGEDx8+JGvWrAC4urri4ODAkSNHtPujo6M5deoUxYsXT9ExZsyYQdeuXalWrRpbtmxh8+bNVKlShS5dujBz5szUGfwFUXh/M65evUp0dDTVWraj3bCxyGRyXr95g7mVNXdu3+KvipXo2Lkrf1WsRFhYGIcPH+bSxQssWrIcJydnrly+BMDW7bsIDQnBxtaWhfPn8ik8Wme8GKBu3bocOHKcfgMHo6+vT7kKfwFioo3vyVcfbL5sX7x0BSfOXGDR0hUMGjKcJ08ec2DvHhDg+eO7PH98N8PsFRH5nvTp04cLFy4wYcIEHj9+zIYNG1iyZAndu6sT0UgkEnr37s2ECRPYsWMHt2/fpk2bNhgbG9OsWbMUHWPu3LksXLiQyZMnU6tWLWrXrs2UKVNYsGABc+bM+Sa7xajm34wtW7YAULVFOxRR0SiVClQqJWGKjxQrVoypUybz/Ml9Hj58SExMDAByuR6Z7W24efMGALv3HcLJyYl7f//NyJEjMTUzY9WKZfgUWJDgeEqFksUL59OoSTNs7WxF0f2OqGcNCbEZxdBxe7W4ubuTzU09rlvI15eixUowd/ZM8np5ZKS5In8g35oEI2791FC4cGF27NjBkCFDGDt2LK6ursyaNYvmzZtrywwcOJCIiAi6detGcHAwRYoU4fDhw5iZmaXoGG/evEnUOy5evDhv3rxJlb0aROH9zbh06RJGJqbYOjqxZsr/APX4hLe3t065/v37a997e+dHKpXSvWcvgoOCcHJyAtQe7b///suhQ4dYumQR3bt10UY5A5ha2FKvdnVevXxJ9x69vv/J/cYkl5ZTI7oQT3CTQCJR38Q+vH+PIAhcuXyRDx8+YGNjk14mi4gk4EekjKxRowY1atRIcr9EImH06NGMHj36m2zKnj07W7ZsYejQoTrbN2/eTI4cOb6pTVF4fzOCgoNxzaXuEr514SwymSyB6AI8e/ZM+75Hjx4AdOnUIUF38qRJkzh06BCCIHDy5EnKly8PqKcq1atXn8DAD6zftI383t5a0RAEsbs5NSR3s4krugl3Jr1JKpEwfMhA7ty+ybad+/AuUoqXT+6lyVYRkT+NMWPG0LhxY06fPk2JEiWQSCScPXuWY8eOaXsYU4sovL8BKpWKbdu2cfDgQVRKJWGhIQC8ffEsSQ9HExI/fPhwChYsqN3++P5tnXJyuRwzMzPCw8MJi4zWbt+2fScvXjznwuXr5PT01BHayMgI1q9dg5OzC2XKlsPIyEgU4hSQ2DVKVJQ1Sxx9RXQ1eOXJxz9bN1OoSNG0GygikgwZnbkqI6hfvz4XL15k5syZ7Ny5E0EQ8PLy4tKlS/j4+HxTm6Lw/gbMnz+fJUuWAGBhY0e1lu1RKBSEf/6ET/58idYpVKgQ5cqVo3Hjxgn2abze2TNnkNnJic5duzNn1gz2791DTHQ05/49y+FDB/nf+Enk9PRMUL9vr56sWrkcgFFj/segIcNFL/grfK17WVsGSez8QQmx/ydzo6pSrTrDB/fn5LGjVK9VmyzZvXghBleJfCfSOs81PebIfg8KFizIunXr0q09UXh/Axo0aMCyZcswzWSJe+58rJs2nqd3bwFqgU2MuLlNk2L1quXcu3uXHB4exMTEcPbMaW7dvEHBQoWZNmM2HTt3BdAuDu3g4IBEAhcunKNz124YGBoydfJEWrRqg7Ozc/qd8G9OUvceiUSS7PhufC32zJkTj5yerF+7iuo1a4lPPyIiKSA0NBRzc3Pt+6+hKZcaxOlEvwGOjo60adOG0OBArp46ikqp4OQO9diDnZ1dqtqKO8arJ9fDMXNmDA0M+WfnHp6+eM2b98HsO3iEbj16IpfL2bd3D955clK0UH4ePniAIKgjnZVKJYOHjsDYxIT/jR6Zruf7uxI/MCUlGpmS7DuDh43k4P69VC5fmtUrl+PsnisNVoqIJE1Gz+P9XlhaWhIQEACAhYUFlpaWCV6a7d+C6PH+JvTp0wczMzNKly7NjRs3GDt2LAC3b9+mVq1aqWrr2n//sW3rZvz8ntKkaXPmzNdNvxYTE4Oenh4REeG0admUkqVK8+LFc6pVqcDR46cpU64cJ44fI1OmTPQbMIgRQwczYvRY0etNBXEzWGnEOL63KyFeGrxE2hEEaNCwMdu2bGL/3t1cunie5q3apL/BIiL8PmO8x48fx8pKvQ72iRMn0r19UXh/Izp06ACgTWUmkUh49OhRqtoIDf1EyWKFMTY2pkHDxnTrobvyxvVr1yhV3BdvnwLUb9iIsLAwpk6fhamZGZUqlCGPlwe5CxXj6ZMnREdH0659JyZPGMe8ObOYNGVa+pzob8jXPN3kBFeiWRowDqo4d7DLly6yf686+9hT/wBkUlk6WCwi8vtSpkwZ7XtXV1dcXFwSzffs7+//Te2LXc2/Ea4euXH1yE32nLmQydQ3V5VKlWy9yMhIVCoV7jnzYGZmRtv2HVEoFPT4uzeeuXS7JdeuWYWVlRXP/J4ybPBA8ubNRw4PDxwdHdl/6BiCSsWjW9cQBIExwwdjZmZGkWLFOX70iJhKMgm+dl0EQVdoE3i5X4JZBEHgxPFj9O3Vk3q1a7B61Uo+hYWjUAnkypOPMuUqIJFIMM+UCf8nYnCVyPdBSId/Pxuurq68f/8+wfagoCBcXV2/qU1ReH8T3r17x7o1q6he+S+mTZ5IlarVEAQBD4+vZyt68+YNhQsXJn/+/GRzcaCQdx6OHztCZGQk+/fvTVA+IOAd7tlzUKNmbVQqFXXrN9DuMzAwIG/efBgZ6GNqnok5c+bQuEFdDh3YT+u27cW4niSIvxYyJJ6IQCqRaJcPVHdBaxJqwIRxY6hZtSJ79+wiNDSEv7t1pIhPbrZv24KBgQE5PXMhk8l58/xhxpyUyB/J7zLGG5ekVjL6/PkzhoaG39Sm2NX8i+LqkVvnc9Vq1Xj18iUlS5dh7oLFTJ4wDiMjI3r27PnVdhwdHbGzsyMgIICAd+8IePdO3b6bG1WrVk9QvmChwuzfu4c+/QawZvVK6jdoRFBQECdPHGfwwH5ERUaybcceChYqxNLFixjQrzcAufPkTZ8T/02J/3f9tbFdDZqt5/49y8RxYxk8fBQDBg9HIpHw+NFDRg0bRIfWzVi6aB6hIaGYmpp8vxMQEeHHZK76XvTt2xdQD+WMGDECY2Nj7T6lUsnFixcTTU6UEkTh/Q2IiYnhpb8/s+YuoEOnLjRpWI/omGiWL1+eZKi7e0519PKTB7c5duwYbwKCOH/uX169eslLf3/+PXuaBfPmsGDxUp16hQr7Eh4eTtas2Th09AQd27fh8qWLCIJAkaLFWLthMy4uLgD0+LsXLVu3Yf++vZQsVer7XoTfEI3ganMzCwm9Y4VSYMWyJbhnz8HgocNRCeoCRjIlUyZNIGcOd5YsWfLlO8ua4ecgIvKrcu3aNUDt8d66dQt9fX3tPn19ffLnz6+Tejc1iML7i6NSqejXW+3V5smbj/+uXmHv7p0sW7mG2vWbaMvF7Sq5eOE89/bsxtnZBWcXly8h8feoV6cmTlmzM3vmdA4fOsB/V6/w+NEjssfJR2puphbyiIgI5syeybX/rlK9Zi3Kli1Pvvz5tZHLgiCwd89uVq1YRt58+ZHLxZ9aapFKJAk8gPhe8KdPoeza8Q8DBg9DKpXi/0h3/LZ9+/a0b9+eV69ekSlTpowwW+QPRhBSv9BB/Po/C5po5rZt2zJ79uxvmq+bFOLd8BdFAigUCjp3bMeWTRtYsHgZxYoVp1njBlhYWJDLKzfz586mTt36ODk7IyDw+fNnhgzsx4plul6sRCLh/+yddVgUaxuH712WblTAwERFxe7u7vbY3V1Hj9157G49dh/zKHZ3ByqghEh3LhvfH8Muu5SImN/eXnPJ7sy8884wzG+e933C0tISK2trPvn6Eh8fD8DTp0/Ys3sXM2bNUW/r7u4GQCFHR65duUxCQgKnTvzLqRP/AjBv4WLGjpvAzRvX6dS+DY6FC3Pm9ClKOJekRctWGBsbf58L9JuSfNj5o7c3sbGxlClbDhEi8hcuwYd3L1Pspyp8oUPHt+R3CSfSJCPJhr4UnfD+wty8cZ39e3ezaesOunXvCUCVqtU4c/ok1SsL+ZfFYjFDh4/k2dOn/NG5HQH+/qxet5HmLVrh4+ONj7c3ISHBhIWGEhoSwrGjh/HwcKddh468eP4Mby8vrWO6u7thaWlJtmzZcPf8yJZNG9m8aT3OJUvx7OkTpk7+k169+1LUSfCGHjtuIkMHD2DurBkM7NebqzfuUiqNNJY6UpLCp0OpkToSKFGiBA4OeTl7+iQNGzX5vp3ToeP/hPv373Po0CG8vLyQSqVa644ePfrF7emE9xfG0NAQgHLlk9JCjhw9luYtWuH6+hWdOrTB0NCQM6dP0bvHHxRyLMzJ0+cpWEio1Wpvb0+FChW12pw5Zx6LFsxl/tzZWFhY0LN3H631YrGYyMhIZs2YRt/+A5k0cRwApiamBAUGMnrseGxsbBCJRNSqXYehgwcA8PbtGwCGDx3ItZt3vs0F+U1Jz8lKJBLRpn0HVq9Yhpm5OTPnzP/OvdOhI4nfyblKxf79++nZsyeNGjXCxcWFRo0a8e7dO/z8/Gjbtm2m2tQJ7y9IwUSPZisrIV1ZSHCw1vpCjo7kzJULExMTRgwbjEgkokXL1mzbuRtT05SerYGBgcyZNZ2EhAS6de/JlGkzaN+hE7Z2dursLSpGjBxNfFwc8+fOZtGCeQCsWLWWQUOGpmj32InTrF65nIqVKtOr+x8EBQVRt179LLkG/0+oauuqUP2kUChRKBTcvnUTgP17dzNj9rwf0EMdOgQUKL9qjlfxE8bxzp8/n+XLlzNs2DDMzc1ZuXIlBQoUYNCgQeTMmTNTbeqE9xfmw3sPAHLn1k7F+OHDexbMm8PJsy54uLshlUrp1buvVhF7FadOnmD4ECFhRmRkJIEBAdSsVStF4gwV+vr6TJ4yjV59+vHwwX18vL3p069/qtuamJjw5+QpAOzcvQ+lUkn9Bg2/5pR1IMzvxybICQ0JYfnShTy4d5cKFSqwceNGvN1df3T3dOj4rXB3d6d5cyG00tDQkOjoaEQiEWPGjKFevXrMmjXri9vUCe8vzNOngrv78KGDyJ0nDwsWLeXhg/v06dmV0NBQnj55zKVrNzE1SWnlvnv7lsUL57Fn9y6aNW/JoCHDaN2iCWdOnyRvLluaNmvB2g2bUvVGlkqlhIeF0bhJUy0X+/SoV7/B153sT8r3KncoT8XrZNmSBaxfvQKAkiVLZvh3oUPHt+J3HGq2sbEhMjISEJwUX7x4QcmSJQkLCyMmJiZTbeoyV2WC7A5FtZYfRfOWrRkwcDBWVlYc2LeHbVs20b5NC0qXLcdZl0u4vXtLvVrV8XB319pv0IC+lHYuypnTJ9mweRuHjv6rTnBRvkJF2nXoxJ7duxjUv6+WI49SqSQ+Pp5dO7ZTrnQJclibU6VCWbZv3ZJmH7ds2kj3rp05eeJfli9byovnz7/NxfjdUcgZPWIY1SqWo1mjekRHRbFz6yaq1ajJuImT6dix44/uoQ4dKLJg+dmoWbMmLi4uAHTq1IlRo0YxYMAA/vjjD+rXz9zUmUiZgcrDERERWFpacvv2bczMzDJ1oN8Fb29vLGzzkjNnbkwS50uDvN/88D41b96cHLkdCPDxYsasOUycPIULLudp3bwJbdq2Z++Bw4Bg6ZZ2LsqMWXMZNWacVsozmUyGvr4EuVxO/To1ef7sKV6+AZiamhIfH0+71i24cvkSlpaWJCQkMHvuAsaOHkGLVq05dOR4in4plUqszIxSeAFGx8tTHfb+VVBZud/L2gWYPXM6ixfOp3PXnhzYu4vxf80gMiyEdatX0KlLV0aPnaD2FheJRHi8SRlSpOP/k6ioKKpWrUp4eHiWxqJqotKI0YceYmiSeY2Ij4liRcfy37SvX0pISAhxcXHkypULhULB0qVLuXHjBo6OjkybNi1TpQF1Q80ZwC6fk/rnnr368PjRAwAsLCyxz5WLXLkdqF2vAc1atiW3Q15Cfb5tPtyxY8fi4uKCk5MTTk5OXLlyBaVSSWy0MBzSqk07Xr54wYQxo8iZKxczNRxuTM3MMDQ0JCEhASMjI9zfvFCvW7lyJUNHjCEyMpK7d27zz94DamesI4cOcuniBWbPW4Dn+/fksLVlyLDh3L59k6uXLxEUFET27NnVbfn6+jJ4QF+kUinzFy0hNiaGZUsXU6duvV9adFV8D9FVvRLfu3eXRQvmMeGv6Yyd+BfmFhasXraIh09eUa5cecaMHMrB/XsxNDREKpUycdJfTJ85B4+3OvHV8X1RKL/SueonG2uWyWScPHmSxo0bA0JUx8SJE5k4ceJXtasT3i/gk+9HHj96wLg/p1KgkCN+n3z55OuLu9tbFsyayqwpEylTviLDRo6leat26mxRWW0Rv30rCLurqyuuroIzTb12Xbh0dD9Vq1Vn/pxZHDl8kEKOjigUCtq3bUHBQo4ULFiIggUL0bNXX1YsW4KFhQUBfh+pVKkSkydP5v379+zevZsBg4YAQriRCnFitaOaNWszbvxEtXjOX7iEwgUcOHRgP0OGDQcES7dNi6Y8f/6MqdNnYm5mztxZMyhbrjxbd/yTpdfie/Mjngv79vyDQqGgdKmSvHjygF69e3Nw3z9M/Wsi23btpWWbdty5fRPXly84dHA/t27e+P6d1KGD32+OVyKRMGTIEF6/fp217WZpa78pisSya6dOHkcsFjNw6AisNcNslBAZEYHLuTPs272TAb3+oFyFSkybvYCq1bM+R/GpU6dwc3Nj8eLF3L59G6dyFRk2fxlGJiac2b0NPYkEcytr3N3caNy0GUWLOuHh7s6Na1fZuX0renoS8jg4MHP6FOLi4tTtFnIuTbkSxVi9cjlisRiJRF+9Lk+ePFhZW1O3VjXsc+akZq3a5MuXX53JytPzg3pbzw8feP78GQBzZ88EoFWbtuzYteeXzlz1PR4KmsdQKpXcuHEDmVyORCKha6f2WtseOXSAqTNm4+hYmHr1GlCvXgOUwKQJY/lr8kS6du6oldhdh45vze+Yuapy5co8fvw4S3Od64Q3DSIiIti/fz/Xrl3DOpstz54+JiQ4iDr1GmqLbiLmFha069iFdh27cO3KJebM+Iu2zerTsEkz2rdpRfXq1bO0f46OjixatIhatWrh+ug+nUvmxz5vPoqUKc/bJw+JDAulYsWKLJw/T8szObu9A1P/+pOtmzfi4JAXb++kzFTuL57i/uIpZmZm9O7bn6JOwhD7yxcv6NalI9FRUTRs1JhCjoV58fwZd+/cRiKRYGtrR3x8PB7u7hQsVAiZTEbtuvV4/eol0vh4rKyt6dqtxy8tusn51sPMb1xdGTdmBJcuXkAsFpM7j1B4IiwslM3bdhIVGUl8fDx58uRR90WhVDJk+EgUCgXTp0xi2+aNXLp0KdOly3To0AFDhw5l3Lhx+Pj4UL58+RS5EEqV+vJMfDrnqmScOnWKC5eucuvGVWJjY7G1s6dMufKULF2WUmXKUa1GbbJZp59sXiYXEhucPH6EuTOn4vnBg65duzJ58uQs7+/bt285fPgwd+/exdvbm4SEBAoXLsycOXMoUaJEiu0dnYSqRF06tefkv8epULESw0aMIk8eB6ysrPDz+8QFl/Ns3rie4iWc+c/lElUqlsXQwJBOf3Rl8YJ5dOzUhbUbNhEeHk71KhX45OuLWCxGJBKxeOly/l66GA93N8aOn4iHhztHDx9i7oJFjBv/dfMiPxLNv5JvKboRkdEsmj+H1SuXkSePAwuXLqdBw8bo6+vz5PEjalWryJHjp2jaTIgr1JwTU/2sVCopV7IYnh8+cPv2LZ3w/p/zPZ2rhu67/9XOVev+qPhTOVel5pMiEonUdXrlcvkXt6mzeJNx8uRJbt26xbTZC2jYuClFnYpnysVdLBbTul1H6jdqyoTRQ9i7dy/G5lbMmreY0E/vs6y/RYoU4a+//lJ/VigU6TovRUVFMWvGNE4cP0a+/Pm5d/cOlpaWTJ85h+IlSlC8RAnq1W9A23YdqFW9MmdOneLtmzdM+HMy0RFhJCQksG3rZsp17IWepyse7u48evqShfPn8uL5M4YNGYhCIVyxw4cO4OPtTbnyFejeoxd+fn5s3rieJ48fERgYSOMmTenVp5+6otHPyrceYlbF6Lq7udG1c3vc3d4xYdIURo2dgLGGaLqc/w9jY2OqVksaPdHqmzLp//DwMEqWdNaJro7vyu841Pz+fdY9r1XohDcZVatW5datWzRu3JRiJQTrMLUi5ekh0UvawMrSnA1bd1G5anWm/jmO+Pg4/hw3Jqu7raZwsVIoFArGjx1FjRq1aNehIwqFgls3b7B/3x6OHTlEXFwc8xctYdjwkZz49zhzZk2ndo0qzJgxg3bt2gEQ6OcDQFx8HFWrVWfJogXCAUQiSlSsysF1K3B7eJtateuwbOliDuzfS6/efXn5UvCSnvTXVMLCwhABRZycOHv6FGNHj0AikVC9Rk3y5s3HsqWLWbRgHp3/6MaUqdPJX6DAN7suPzNKJYSFhVG7eiWsbbJx+cZdiifee55uQpm/CxcuMHfWdLr37I2VlVXSvpop9kSAUngbr1y5KhcvnOfhw4eUL1/+O56NDh2/F56enlSrVi1FMiGZTMatW7cyNferE95ktGzZkhUrVnD3zi218H4tIpGIvgMG4+X5gWOHD7JuvXZZPtXDNau4c/sWG9atYcO6NdTZXA83t3f4eHuTN18++g8cTL/+A8mXPz8A7Tt0pHWbtlQsV4oFCxZgYWFBgwYNuHbtGgAlS5ZizLgJPHv6hOjoaFAqeXn/tpCcv117xo3/kxpVKzJz9lyGjRiFhaUlCoWCYSNG0blD2xQeto+evqRY8eIolcLw1JxZ01m7eiW7d+0gIkaKvr5+8tP5oagsym85vCwSgYWFOU7FinP3zm0O7tlB37598fDwIDgskps3rnHk0EGcS5ZizryFWvsqkg3HiBP7+Ue3Hpw/d5YJEyfi6u6NRCLBK4vvMx06kqP8Sov3Z/NqBqhbty6fPn3C1tZW6/vw8HDq1q2rG2rOCmJiYpBIJMTERKsftnpi7aduiuLkn0nsLU5sqELFyqxZ8TflShXDwsKS+g0bM2nK9K/u88OHD7l16xZ6eno0btaK3bt2kCt3bhYsXMqK5Utp2qwFXf7oRuUqVdHTSzkMLZFIWL1uI/379GTs2LG079iJjz4+ODuXpFjx4nT7oyNly5Vn6PCR2NvnRF9fH39/P6RSKTdvXAeEjFdmZmYsXroMEDJW3b1zm0NH/6VJ02bMmTGF06dPo5TF4eYqWMUKhQIUMvT09JDL5Zw+dRIrKyuq16j5wwX4ez4ARIBET4+9B44wavgQli9fzotXr3n44D4hwcE4ORWjS9fuTJsxGytrK637La0XglZt2nHijAtNG9bh5YvnlC5T9vucjI7/a5SJESBfs//PhmouNznBwcGpFp3JCDrhTcaCBQtQKpV06tIty9tu1KQZM+csICgokIAAf/5ePJ+njx8ydcrkTGU/UTFp0iT8/PwAWL9+PSDUwe3YuQsdO3dRbyeTydi/dzcfPrzH79Mn/Pw+IZVKqVylKrXq1OX+o2cc3L+PhQvm4uPtzT97D3D82FHc3r1jx669lK8glB+8c/s23bp0JD4+HoAWLVvjXFLbs+/SpQtUqFiJFi1bAdCjRw969OihXu/o5MzSJYtYu3Ytdvb26InF/JEYLlO6dBkuX7/1Q72gVZmpvgVptWtnZ8e+g0c4evQw06dMxsrKmjv3n2jNgX/2waTxfChdrgIGBgacPnUC51Jlvr7jOnT8H6GadhOJRPTu3VtdhhVALpfz7NkzqlWrlqm2f/0UQlmAQ6HiOBQqTq78Rfng6UW7jp2xs7NDLBKprdUvQSRKfTE2NmLUuAnMnr+YDVt2cuDoSc6fO4ur23vyOhYnr2PxTPV/9+7dOCWG/tjnzMmxE2eYNTepLuvTJ0+oXqUCfXp2o3/fXmxcv5YH9+8hkwnW5qoVy2hYtxb5ctvh5eXJo6cvuXjlBu07dGTLpg3UrVdfLbpnTp+icYM6lCtfgYOJaSJPnfyXCmWcCQwMRKlU4ufnR548Dri9e8vpUyfVzlaa3L1zh5nTpmBiYkqAvz+FixTl/MUr/OdyiadPn3D86JFMXYvM8kNftEVJi0gson37jjx94cr9R89SOJ6JRKJki/Y9pomJsTH9Bg5h8fw5HNj7aycu0fFr8Dvlara0tMTS0hKlUom5ubn6s6WlJfb29gwcOJDdu3dnqm2dxavB2dMn8fbyZNDg4d/lePUbNiZHDls8P3zI1P4RERGYmJhgZ2fH+vXradu2LX6fPvHG9TWNmzQF4MXzZ9SvU10Q5KNCvmaXS9co6uSkHvKVSqWcP3+e0PBIli1dzOVLF7l09QZSqZT79+4yb8Fi9TFPHD9GwUKFOHPuAgf37xO+O/0fPbt1oXaNKoSHhRESEkKDho2JjIykQ9tW5M6Th8qVKtGrVy9Gjx6Np6enWoydihXjwOFjWgLTvEVLRo8cxqtXL5k46S/Mzc0zdX0yirrQ/HcS3+RTEyKSKaZIKL+or6//2bnl5C+G2uegZN7CpURHRTF0YF9mzJhB+/baSTh06MhKfqeh5u3btwOQP39+xo8fn+lh5dTQWbyAVK4gMiaW2TOmUrlqdcqUL49S45+GQZL8EQkID84v+qdhoeTNl4//zpwmwN8/Q30tVNQZ+zwF2PnPXurWrUulSpVo1bo1Xbt1QyqVsnbDZkaMSvKa/vf4UYyMjLj/6BnnL16lV+++ascqFQYGBrRo0YJZc+Zx+j8X7t+7y6mTJwgLCyM2NpZsGjmYPTzcKVa8BEZGRri6viZnrlw0bNSY1es2Uq58BVq1bgvABZdzmJmZUcixMJ98fTl69CitW7fm/fv3WhawUiEnLioMN9cX6mXjlh3kyePA0sULOXXiRAZ/i78uaY2QZGSwJb17U4kSkVjEstXrEIlEfPDywc6hIPkKFyd7rnx4e3tn/cno0PGbMWPGjCwVXdBZvGqWL57Pew83Nu+6912PO332PPr37k6VCqVYvmodpUsUTTcO9/79e3Tr0oHAgABGjRlPzly58PHyIiIygpGjxuJYuLDW9jdvXKdqtRoYG5tQrXoN7LJb4fPBLUW7V69eZfWadcTGxmJjY8P6tavVSRriNdJKenl5UqBAQQBu3bxBlarCHEeHjp0oU7I4JUuWVG/bvHlzBg4cSMOGDdWpKfPnz8/EiRMZOnQoQKoPfxMTY169EhL89+3dnTdvXjNj1pxUHRy+BZqH+RYv4Mkt3PSO8dlTTqm2alTWsFgiYdzEySxbspAL589RqXIVzv13hjwOebn/JKlIhuc7ndezjq/jd8vVDODv78/48eO5ePEiAQEBKaxynVdzJjm0fw8r/17E2D+nUKy482fndT83VPg5L2elEjZvWItNtuy069CJKdsPMatPJ3p27YRYLMbWzo4O7dvTr1+/FLFjrq9f4fvxIzY2NlhbW9O5S9c0HbPCwsK4cvkSDRo00KpCpIlCoaBR48b4+/khkUgoULAgISEhXLt6BblcTh4HB54+fYLKLapP3/7MmTWDocNHUrJkKVxczqm9/uLi4hCJRBgbG3Pw4EF1fNvFixe5ePEiJiYmNG7cmI0bN6qPn1ouYWNjY67fuoeXlydPnzxm0YJ5FC5chG49eqZ7XTNLer/u76H16d4vSu0OpIgp17j3FEql1no9jQ8zZs2hS9fuzJs1HXd3N6rXrIXLuf+Ij4/XchrRoeNr+N2qEwH07t0bLy8vpk2bRs6cObPEAPi/TBmZp1Ax9c+b1q/lz3Gj6NazD8tWrUcikWglwICURoVc+XXCC9Ckfi3u3r5F67btMStQBEQiXt+/i4/HO0L8PiGTJaCnp0fFihVp0aIF1atXJ3v27BQq6oy7mxtLlyxkzz87kcvlODuXpGr1GpQsVZrYmBjCw8OJiAjn1cuXXLxwnv3796eaPlJFs2bN8PHxQalUYmBgwNTpM2nWvCUlnJ0ZOWwIFy6c56WrGyKRiISEBIo65qdDx840btKUFk0bcevuQ8qWK6eeM/4cCoWClStXsn//frp27cqoUaNSbFOoaFIMdYumDYmMjOTazTsZav9L+J41dVND8bmgx2R9S29ON/l9lyLsTePztSuXad6kPncfv6RwkaIAfPTI2gosOn4OvmfKyF477mDwFSkjpTFR7Oxd5adKGWlubs7169cpU6ZMlrX5f23xhoeFMXXSePoOGMLiZavSfJP5Fu9g5cpX4MG9u1y7epnQY6l78Mrlcu7cucOdO4LgjBs3jjkLllLI0ZH1G7cwdfosLl44z62bN7h88QKbNqzDxMQEC0tLDAwM8PL0xNDQMF3RdXRy5q2HFwqFglcvX7JqxTLmzJpB/QaNAGjavAWbN23g7Zs3FHVyQl9fn8aNm3LB5RxDhgpOaB8/+lC2XLkMn7tYLGbMmDGMGZOxDF7GxiZcuniByMjIb+5o9cP5zEvAlxgEKURdo+3gkCAArKwyH8amQ8f/Aw4ODlnu9PV/6VwlVyiRK5ScOX2ShIQExk6chFgsyrBDy9fw4vkz2rdqyqb1azE1M+PZaw927NjB9u3b2bp1K4sXL6ZMmTLql4CpW/ZhncMOIEXqv9y5c9OzVx82bNrK05dviIyVcffuXVzOn6db164A5MiRI0P9EovFOJcsyZr1GylZshQ9u3chKioK88S3TlXMLoBD3ryEhoZyweU8enp61KhZC4D8hUtoLV+D+5sX6qVunVqYmZkxf+7sr2ozNX6ktSt0gLS9o0B469NYVF6jSqWS5P+Sb6tItmg6+L149gxbWzuy57BFqdRZuzqyBq37M5PLz8aKFSuYNGkSHzIZfZIa/9cW78l/j1GxchVy5cqd7nZZOe/w9PEjLl1woXbd+mzbuRdzc3Pad0mau1QqlUyZMgWlUsnIMeOY2K0Tm6eOoU+/AbRs1wW5QsmHdy/V22sOyeolFqsHcHMTHKg+ZyEmHx7WNzLDwNAQdzc33ri6EhEeDghOVaVKlyYwMJCjhw+R0z4nt27ewMLCAt+Pvty6eZMB/XpRrHgJlq1cQ758+VMc68GDBzx48IDBgwdn/IIBjRs35rzLBdzc3n3Rfr8kyW41TaM1xUtC2gYtkJQ+MjUCAvzJlj1jL2U6dGSU39G5qnPnzsTExFCoUCFMTExSZNULCQn54jb/b4X3+bMnnDtzioVLV3xzq0dzDrhbj964vn7FmpXLOHniKH36DdTaNiYmBgeHvBgYGjJ3/mJEIhGNGjflosv5VCsPpeY0VaioM/a58iAWizOcgUuhUPDXX39x6dIlRCIR5ctXQKlU0qRpM5q3aEnvHl2pW68+t27eQF9fn7PnLyGXK3jy+BHVq5QnZ65chAQH8+6NK5XLCVmscuTIwdatW8mZMycTJkzgypUrAFSvXl3L+zkj5M6dhyePH33RPj87SmVK5yhNkn9WJssukPwZlcIpMJ3iHmXLV2Ln9q2cPX0Sx8JFcCzkiKGhIbGxsbx7+4YNa5bTpk0bihQp8iWnpEPHb8eKFSuyvM3/S+FVKpVMHjeawkWc6NGn/zc/Xnx8PJcunMfY2JgateowZ/5i4uPjGT18CPfu3GHB4r+xsbEBYPqUP/Hy8uTB01fq4eY+/Qbyz87tjBk5lKXLV6dov2AR7WHde3fvsGHdGkQiERaWadcOjoqKomPHjgQHBxMfH49CoUAikZAvX34ePXrIsr8Xs3f/Ibbt3M3fSxZx7eoV+g0YpFVk4cadB/w1aQKbNqwD4NRZF3x8vPHy9GT2zGl06NCBHLa2fPL1RSQWo1QoGDlyJIsWLaJSpUoZun6OTs44FinCwQP7MrT9r4JKCNN6y0/utKf4nPOUxnqxWKS1f/J3ywYNG2FhYUH3zm0TtxeTPUcOAjXCJcLDw5k3b14Gz0aHjt/Tq7lXr15Z3ub/pfBedDnHnds3OXLyP/T19bXCLiDrnanGjx7OPzu3AVCiZCk2bN7B4r9XUrJUaaZOnsAFl/+4fO0OMTHRbN28kVlzF1CokKN6/4qVKrN63SbGjBzKh/fvmThhHLlz5yYqKoqBAwfyyc+PmjVr06xFSwL8/VmzegXlylfg7p3bSCR6aXULsViMr68vCoWCXAUK4fvenTp163Hg8DF69+xGbEwMABYWFsyak/oD2NTUhJWr1zJi5GhssmXDxsaGkqUEi7d123YcPXyIF8+f0bf/QCpUrEjj9h25duIw/fv3Z9iwYeqhcAcHB2rWrAnAypUrCQ8PZ+jQoVSpUUc4jokpMYn9+V1IXvlIlHzoWKy9XXo3ZvLQ7+TPr+TGcN68efH0DcL340fee7jj4eHGo4cP2L51M8bGxtSrV485c+Zk+Fx06IAkF4Ov2f9nxN3dne3bt+Pu7s7KlSuxtbXlv//+w8HBIV3n1bT4vxTe8NBgAGrWrIV+KtV6PkdySyT5XJo82d0TFRVJiZKlWLJsFcMG9WP+nBnsO3Sc7NlzIJfJsLCwxMjYmBnTJpM7dx4GDx2hfTwR9OnXnwIFC9K9SwdGjhxFuQoVefLoIe7ubvTo2ZuHDx8woG8vTExMqFy1Gpu37qBbl46cPPEv9WrXTPU8TExMmDBhAosWLSIqPAyAMmXLYWJigjQ+HplMluFrkjxxB4Dvx48cPXKI169eYmdvT9ly5Ri1eBXtBg5jXJuGrFmzRmt7IyMjcubMqS48fezYMdas24hzyVIcOXyQMr9RhR2pTIFIJFS+ShLgpBtJyJgmSvxecAjUHEqWJct/rUwW75tODhb1erFYj3z585Ivf16q16pDQoKQu/vKzfuY6P+sj0AdOr4vV69epWnTplSvXp1r164xb948bG1tefbsGVu2bOHw4cNf3Ob/pVezsbGQtOFbWlCqAgtikYguXXvg/u4tE8aMJG/efHh7eQHw9+IFlC5bnhOnz3P75nWOHTnE8FFjMTYyRCxCvaioU7cel6/fwSFvPry9PCnqVIyrN++yev1Gbt17yIeP/vgFh3Pq7Hly5spFrz59uehynj///JOoqKhU+9m9e3fatGlDRIjwMrJs6WIuuJzn3H9nad6iVabOXeVgMfnP8fj7+9GxUxcWL5xPu9Yt8Pf2xMGxKFtvPGXKpt3kKVQYIxMT9A0MkcnleHoJmaz0JBJEYjGDB/ajRtWK3Lt7h7+mzchUf34GklugMrmSBJkSmVxY1B7Lqn9KYdhN9S9BrtBaFAq0l8QhPtWS3Fk6mcOzloezVKZAiRJvby9y5spNEScn8hQqpl506Mgov6NX86RJk5g7dy4uLi4YGBiov69bty63b9/OVJv/lxavKu9mXEwMokyW49NKK5jss55IpPWgbdikGRev3aF3985cvXKJbNmzo5DLePniGcNGjKZcKSfi4uIoXsKZHr36pHusIkWLcOL0f6n2KXnoUMfOf7Brx3bOnDmDkZERs2bNSnW/OXPmoK+vz6FDh1AoFPTr3YMGDRsxaMjQz14H0J6XUSqViEViXr54wbWrV9i1ez9lS5fAyFCfVatWceGCC11HT6LtgGE4FC6Kj/s7zMzMMLc0JSgoSP2HJ9HXJz42FoBq1Wuwau16SpRwTvX4PxOpJeRIXoQhMi5BnbNbKlNipK8nhPuoFBKNOdnEzzFS7bR0cck+25gZaH1O/vjS7FLyeHWVJR0REY6enl6a9Ud16PgcqtC1r9n/Z+P58+fs3bs3xfc5cuQgODg4U23+n1q8Qp3XmNiMWbxikXaRg4ygaW1IxCJKOJfk8o17LF+1ju3/7Mfd7R1xcXGULVceUzMzevTqw50HTzEzM/v8zZda7KemOZOIiYkJgYEBGBsbM3r06DSbc3RyxuejLyUTa+qaW1iwaeuOdHNGp4ZUKqV5k4Y0b9KAq1cuAdC0uZDvuX///mzbtg1TExN2/z2PYY2qsWL8MACWL1/OpUuXePLkCRs3bmTylGnkzpWLvQcOs23HP7x7+4Y2LZtluorT9yK1KkdpOYso0bBORUn1f9VtgPr3GxaTIFitiet9Q2MJiZaqF2tTA/U6pRL09cRan5PfsckLMURGRhEcFEy9+o3w/PCeyxddsvbC6NDxC2NlZcWnT59SfP/48WNy504/FDUt/i8tXtXcpZ5Eok7/+KV1d1M8zDKQNtLMzIw+/QcBEBMdRSHHwgwb3J/w8HBq1KydtpWhTOWAGSAyMhJvLy/mzF+YZj5ngBvXr3H71k32HzpKxUqVM52PdPLEcdy6cR1TU1MuX7oIaMe4VahQgRs3bjBt2jROnDiBn9cHbG1t1d7NYrGYatWqUa0aTJ+ZlCyjZu061K9Tg949u3Hp6o2f1hpTiSekTOWouj/8wuOEud3EczA20CNBrkAiFic5WaHdhr5E+wXodXCE1ucCObQrp6iH69SXKe00k3v+2cWAftpem+1bNSNb9uwEBwWxY/d+ypf+umQoOv5/+J3KAqro2rUrf/75J4cOHUIkEqFQKLh58ybjx4+nZ8/M5Y//LYXX1N5R63N4WCiXXP4jwO8TUmk87m/fAGBgkHZy+M+ERKYgRZ7cxP8VCgU7t2/h4f371KxdhzbtOmJgYICZuRkul6/T449OFHVyolv3HimGr9M9fopQkiSOHTlM0aJODB8yECMjI+rVb5hmv8PCwhg6eACVKlehRctWWkk4voTjR4+wYd1aVqxaS+06dSlbqjgAfp8+YWOZJAxisZh58+YxZswY5HI5dnZ2n207LioMQwMD7ty+xbw5s8iTx4HeffsBQlrNwMBA7Ozs1dv/SF3WEl+N34oSJRGxMgwlYqRyBTJF0gufQgGyxBLghhI9dRYq1WnESuVaL4Z3vCKxMJIgT5Didu8KIQ6mlKtQhbz5CwhtqIadVYdP7vGs0S9Do9T/BoKDhJSSr58/1gmvji/iJ9TOr2LevHn07t2b3Llzo1QqKV68OHK5nK5duzJ16tRMtflbCG9yoQUIDQnm/OkTnD15jFvXLyOTybC0shYKjBsYULFyFWyyZVNv/8UP6wxuv2zpIubMmIp9zlz8s3MbPh99GTJyLKaGemTPkYOzFy6rO6AETv57HLFYTFGnYuQvUCCpOlGymzkyMpKd27eyf98elEolFpaWjBk7gXz5C9Djj07q7ebNm4dRGr/lVatWsW/fPqKionj87FWmRVeWkMCUyRNp1rwlAwYNQSQS0axZM86cOcOalX8zffr0FPtk16jxmxqaGbUcnZwp6lSMd+/esXjhfExNTbG2sWHp4oW8evmCmJgY+g8cjLW1DTEx0fQfMBinYk6ZOpcvJbU5XZFII0+y5ty/WISehrecob4YfT0RCXIlKidllSiqrHr/cKGcoiqGd9djH+zNBWF1vX+D4/NHcBywsrbh8JnLVCzjrHWrJPfalyebx6hVtyEffIMJDgpk/97dLFk4l3kLluDr+5Fq1WtQqkTRL7wiOv6f+R0tXn19ffbs2cOcOXN49OgRCoWCsmXLUjiVSI6M8tvN8cbFxrJ22SJqlivKlPHDkckSmDV/Kc/eevLOO4BXHh956vqe85dvaHmofZbP5NRN7mWq2uz5k8cAREcLXsWWqqT0yd1MAZdz//FHp3Z07tCGMs5FsbMx59zZM6l2p03LpkyZPJECBQpSoUJFoqOi6NW9C5cvXwCgcuXKLF++nFatUvdMzulQgG3btmFkZMTRf0/hVCzz3qvBwcF8eP+e2nXqqgXj0LFTdOnShQEDBmS6XRBEF2D/oaNExEjp3qMXYWFhdOnYDoVCwfSZc5g2YzZbNm1g3ZqVHDqwj/JlSrBy+bLPV/75StJ6Rig0J1YTf78RsTL1Q0VfIlYPH0vlCvT1RMIiESFXJHk0fwqLQ5aYV1y13HEPIY+VAXmsDFBG+GFkZMRLd2+MjIzZuXltivnb5HmdNT2jHz9+THFHB/LnykbHti3Ilj0btWrXZe2aleTJm49Tp05Svnx5KlSowNatW7/ptdSh42enYMGCdOjQgU6dOn2V6MJvJLwGeiL+O3GEhtXKsGrpPHr0GcCj1x84dOIcvQcMwT5nrvQbSEUIP4emA0tarFizgb0HjjBu/CRWbtjKHz16p7ntxPFjqF2nHm/cvTl51gUHh7wcP5Z6jFjhIkXI4+DA6vUbWbFmHb369CUiIoLFS/9GLBazZcsWGjRokOaxTE1NmTF7rpYncWbJmTMnXbv1YMniBYSGhQpWmwimTJlCzpw5v6ptFXp6eni6v+H6tSsAzJozj5t37jNqzFg6dWjLhAkTePbqHW/cvRg9ZjyTJo5jQN9exMTEfpOhL6053GQ/q+f7E/+LkcrRE4lQKDWEUKlUW59SuQKpXCG0o9TO/iNOHAlRAv33PSY2Xsbhh34cfuhHvmzZkEqliEViSpcty6eP3in6qX73SGxEJeChoWH06t6ZQo5FWLtxG5UqV2XS+DHExsUS4O/H5AljePLoITny5EVP34AVK1bQsGFDnj9/DsCZM2coW7YsgwYNIiIiIsVxdfx/krwwR2aWn40OHTqwcOHCFN8vWbKEjh07ZqrN30J4X9x2oV2z+gzt1x3nUqW5dPsx0+csIodt0vyhgZ5Ya1EN+yUf/kuP5FZtcrQsjcTvbGxsqFGrDrny5ObcqRMM7PUHkWGhxMsUWjebTK4kQSolX/585M6Tm7r16tOoSVOuXhGGopPfj4MGD8Pv0ydy29pQrHABRg4bgo2dPcF+vtja2n72XNxcX9CwYWP09PQ4deLfDJ1/esyet4CY6GiWLV6k/q5g0a+fG1QNOav+DwgIAKBDx85a3/fs2ZOYiGAMDQ2Zu2ARO3bt5eiRQwwe0Pe7zvkmOUgJPygRhphVDlUH9u2meoVStGxSn4SEBLWFK0KETC4MNCuV8DEkTp0kQxUPHhUlJSpKSmBwDIHBMRSvXg9EIlZu243IPDufPvpoxY8Lx1eq77HYBLn6/pw6aSzBQYFs332ALt16snbTdrbvPsDrly/UL2KvX73Az/M9+gYGmFpa4ufnR9euXalSpQpTpkxBLpdz69YtatWqRfXq1SlXrhzNmjUjLi7u+11wHT8Vv2Mc79WrV2meGJ2hSZMmTbh27Vqm2vzlhVehUNC7d2/evXXlwL9n2b73MIUcC2Okr6e1ZAQtozcDv3/NIcDkYSNBgYHs2LaF9q2bUyivPQP79iLA349b16/SoXUTId5VjNbSrWcvjh4+pE52UatOPbw8PXF1dU3Rn7LlyvPyjQer1qyndZt2HDryL7VatUOWIKVPn5SxwJCY8zhxkSOhZbNGlC5TlgWLl2bo+qRH7ty5GT12PGtWr1AnCMkqNOd7nZ2FoWdZfHSKykqQVDSiU5c/mDNvIcePHclU9ZDPkZ6YizSGmUWARE94uVMo5Iwc1Be3t67cu3WdZy9eExART1CklBipHLkyKaGGQinM+8oUCmQKBXMuvsO5UDb8PoULi284f+17jUSiT3xcLNntcvHRxzvV2RDVMLOmKAf4+5M3X34srKzVx6hQujiLFi2iSJEitGnThlatWuHk5IRcGk90YpUqgNjYOPSNjChTow62efIil8tRivWwy5sfb29vevTokeXXW4eOH0VUVFSq05L6+vqZHu35ZYVXYZkfhWV+/jlyhpCQEFau30LN2vU+u5/vx49s3bQehULxxUPLqiHAq1cu0bxxXf5ePJ+3b1zV60UiePH8Kb27d6Zw/lyMHjGEuLg4Fiz+G1c3L85fucmYCZN48/pVqlZ29+69iI6O5tiRQ4iAevUbYpMtG1s3rQdSjobb29vTb8AgFi1ZRvWatfB8eBcTExO6dOmS7nkolbBm9UqMjI05eeYclukUUvgSxoybgLm5OWvXrPyimOcvYePGjTx9+jTdGGNVHd8Onbogl8s5fvRIlvdDRWphYypU8916IhESPRHbNq3VWp8zV05CoqXESuVExcmIT1AQI5Xz0CuUqDgZikQhnnX+rVpMG9QoSIMaBQkJCCHozSOk8XGc/mBG7TJFCQsLIzYx6YjquJpoCu/YCZPw/PCeWpXLcP7safU2tWrV4uDBg8yZM4d58+axf/9+bt++za5du6hUqRJ6enooFHJio6J4fP0yAT7CS1ZUeBhFylSgetNWuLq6Ur16dU6ePPmVV1fHr0byZ1Rmlp8NZ2dnDhw4kOL7/fv3U7x48Uy1+Ut7Nb98+ogVC6bTY8BwGjRulmK9RE/7wRMaGkq7Vk1wff2K4OAgJv01TWu9VKY9fmwgSflw9/Hxpm/PP7CwsGTF0kXMmzWdok7FaN6yNa9fveDs6VPkz1+AxctW0q5dR3JoDPsmyBWEBAdha2efaixq3nz5qFuvAZs2rFOX9OvbbyAb169Boq/PvTtCerJs2bJTqkwZypQpR5kyZfHwcGf0iKH4+/sxfvz4dEVJZTl7eXlSpmw5dVWkrMDMzIwOnTpz+OAB5i9YgkSih6OTc6qW6deQ2vnFxcXRtGlT7O3tGTFiBNWqVcPOzo569RtwYP9e+vb/OicvTZKPPgjhPyK1pSukbFTlWRYlDqHBXxPHae33+ME9cpasrv4cK5Wz+vYHajtaaW0nVyiJiZepX9aqFbSi4KCazBlzGiRGRCosyZFDmFYJCAggb7586n1V4huXoH1vl65YjYu3HvPn6KH06NyW7r37M//v1YT7uqV6zmXLlmXr1q0oFAr279/P5cuXqVmzJh06dMDNzY3x48dz6cg+ipWvTPvBo/h363r++usv6tevj4mJSQauqo7fgd+xOtG0adNo37497u7u1KsnGHcXL15k3759HDp0KFNt/rIWb2REOBOH9aZo8VKM+nNWijnb5EnkPTzc6dqxLf7+fvTuN4AFc2dx7txZ5EqlevkcCQlS+nbvjLGxCS5XbuLu7c++Q8coX6Ei27ZsxN3NjY1bd/DohSsDBw8lu20OPrx7qV4A/P38sLOzV8dvJqd33348fvSQQf37EOD/iYGDhxIbG8vGdWvIX6AghYsUJT4+ns0b19OlY1ucCuenWeP62GTLxuVrt9Od7NcUQF8fH3LnzpPBq51xSpcuyydfX+LiYj+/cRby9u1bgoKCePHiBYMGDWLosOFs27qZuLg4bt+6SUJCwle1r3qgJL9NkuZylSgUSrUntaYlLBIJ9+RbTz/6DByGlbXwsvM2zgCP8GhiEuT4R8XRbeNt3vqEcdUtDN/oWF6HRNBi3jm8/COBpKmN8RM3Y2MsoVppe8wtLPDf25fstkK6UH9/f61sVWlZEUqlkpy5crPzwHHmLlnJ7h1bOLBnJ1a5C2OVO22PTbFYTNeuXdm8eTM9e/bExMSEUqVKcf78eWrUqMHrh3dxe/6EwbMXA3Dq1KkvvNI6dPxctGrViuPHj+Pm5sbQoUMZN24cPj4+XLhwgTZt2mSqzV/W4r1x+T98vN4zcMQ4TExSTwIgk8k4d/Y0Wzdv4KLLeaxtbDhw6DiVqlTF96MPA/v25MrNe+TNlx9IGfOoiVQqZczwITx98pizF66SLXt2xCIRzVu2onnLVhnKb/vR4zWxsTGYmpmlul6uVNKufUdGjxhKgYKFyJPHASWwZ/9hHPLmpVTpMuptlUolvh8/8jQxXKlp8xbq479/+zLdfoSFhfH+vQddunZPd7vM8PTpEwoXKYJZ4jlmtbWbFqVKlWL48OEcPHiQgIAArl+7yvVrV7G2tmbvgcPo6+unuW96+ZUzggiR9pCzEhChLnagcmjKZW/LkmUrWLJsBdvufVBb7h7h0VgZSYiNSSAEeKvRduSb52jaoI//PQfA+ImbkQd4kRASQFRUNLlyCS9Rb968VmcCU51SfGIlJHWbcULmNrFIeCno1W8QTx49YOZf46lWszZ58xXI+MlrsH79evr27cv9m1eRSPQRicUsXLSIYsWKUbJkyUy1qePX4nNRHhnZ/2ekefPmqTpYZZZf1uJt0rIddRs1Z+7UcWxYuZiTx4/w5NEDgoIC8ff7xLLF8ynlVIiundoRGhLK2o1beP3OkyrVqiMWi9m0dRcWFpbUrVGZbZs3IpfL0zyWu7sbDevW4NCBvaxat4nyFYUHm+awSEbTGJqbWxAUFIhCqUhKlqDxz8PdnZCQEAYPHa7ep3nLVlqiqzpe7jx5aNaiJc1atMzQ8R2dnBGJ4K9JExCLxXT+o1uW3+iPHj6gfPmKKJXfT3RVDBo0CBcXF61iCvsPHaVFy8xVWfocSVZw4kXU9mhCoUAdIgSC+Bob6HHVLZBCNkI2r9gEBVK5ksGLLyGTyQTxDYnlzrNP7Ft3BMR6RL55zuMTLjw+fAIUSfepyFiICc/fcALFu65DZOHA8SPa4WdypRKJnkhrfjepilGiR71CyfT5S7GytmH0kP4EhEQgyVZQvZjZO2KWSpKa1NiyZQvOzs48vHoBmxx2JEilrF+/PlPXV8evx+/o1axCKpXi4+ODl5eX1pIZflmL18DAgC279jF22AA2r16qLtquwtjYmA6d/6DfgMGULVce0H4u2tjYcPHKTWZM+4txo4axfcsmZsyeR5VqNdTF2QP8/Tl25BCzZ0zB1s6eC1duUqpsuXT75fnuVbrra9Wtx64dWxnQuwfrt+xAKZGgrzEX/c+u7VhaWtK2XQd1nz0+Y8GmhaurK9u2bWPPgSMYGxsjk8uZMnkiO7ZtYfW6jeTJk7kE36kRExPDqOFDuXf3Dj17982ydr8UsVjM3ytWMWXynzx8cB8TUzNu3LjOqxcvqFmrNsUy6QyhQmXFprJC6wZTKJNyNCuUSW+4H4JicDA3wTsyhgJWxoRJExj25z9gak04YJndksgIGUG3hFzXmNmAONErX6kAeVKNZJGpMK+rjA0BM3v0cjhzweUcgUFBKTKDqabFP4UJoT4GErH6xTEiRgZ6Jsz+eyODurakVplClC5XkSLFSlC0mDMtWrflvfs7rl50QaIvYfOaZUilUlavXk2FChWSHUfMnj176NSpE2/evEEikTB79mx06PhVeffuHX379uXWrVta36tGOdMz2tJCpMzAK0ZERASWlpbcvn1bPYT4M2CdpwggXICw0BD8fb3x9vIiOjqKxk1bYJtd23HIyy2lKOYpVIyH9+8xafxoHty/h0gkomAhRywtrXj86AEikYjOf3Rj6fLVmJubp5gL9nF//cX93nvwCAvmzOTu45cULlJUPcQtl8spUaQATZs1Z+WaJCshM8Lr6OTM1L8m8feSRRRydGT5qrXs+WcXB/fvZemylQwdPuKL20wLpRLWr13NnxPGsnzVWvr07Y9YLFaH9nxvlGKDVFMdmpiYsGX7Ltq2a6+9/WeGmlW5k5M+ayNK/kEjEYBmgYSgqHhQCgk1ouNkxMrkNJ3yL4qwAEFQTa3RNzUj4c29xLY0BqSUiQ4BEiGsIWfNBnz68Im406OR2FdAkq82L3YPpmjBPCxdvooBg4aoz0NzGNwnRJh7VzlqhURJtc4lOvgTJ47s5+XTR7x1fYm353vyFShEfFwsfp98MTExpUTZinz0+oBSqWT50kWUKJEyXluhUDBx4kRatWpFrVq1UqzX8f2IioqiatWqhIeHY2Fh8U2OodKIFquvoG+ceY1IiI3i1Ig637SvX0r16tWRSCRMmjQp1QIypUuX/uI2f1mLVxORSIS1TTbsbHNQqkySRZqa0CZHLBJRsVJlXK7c5OWL5zx7+pjnT58SFBRI/0GDadq0Bdk0rIfMCG1ynj99gnPJ0jgWLqL+bv3aVfx35jQfP/qoa/Jm1tIF4YF7+dJF6tSth1QqpVWzxhgYGLBr937ad+z0+Qa+4Dig5NjRw9SpV59+/QcC/DDRBdi4YR0AVatVp0/fAZQuUxaHfHnp3qUTUyZNTCG8qY3SaxY7SLEObfFVAnEJcgwkYsGLWCRYuIrExBgJGkUREIGJgWDBTj3uikOhXHi7I4hvdCgJPhr3rDIV7zuZIJTZspkAOfG0yI1SHoUoR16y57Clbv0G/LNzB336D0KcKK4q4fcIiAZQp6YEuOmjHeNcPU9O/hg4BisTQeA/erkzamBPwsNCuXz/FSLT7Hi8fcXaRTN4ePsqa9euZd26dSm6KRaLWbr06+PDdfxa/I5ezU+ePOHhw4c4OWVd/vffQnhV+H9w/fxGaSAWiylZqjQlS5UGjfh/L7dXRIUFfHXfchcUciG7vXvL2dMnWfT3SvWbU0hICDOmTiZnzly0aNWGsuUrZlp0CxUV5jdDQ0N58vgRazdspkfP3uzfu4dCjo5UqVo1xT7qKcpMhN2KRLBuzRpuXL/G3gOHf6jgqmjbuiXjJ07C1s5OLToyuQwbGxvee7hn6bEOHzuBWKSkcOHCFC/mhFyRaE2qLd+kB4mpoYToeBmIYP1dL3JaG6vXebuDwu1hxg5qaMqLk2dxbtmU4DxFiXp9kSrZ3zP97EuGjxxLmxaN2bxhPQMGD0UsTrJ4bS0FJ8SA8HgAdj75qNWspZEe5z2CaFQwO2ExgsDndCjI3pNXiI6K5L3bW9YuH82tK+fJnbcAk+evok39ypm8cjp+R35H56rixYsTlFitK6v4pYU31Oft5zfKBBmxlDPL4vlzsLWzp2evPkgSLZJd27cil8u5cOWmVtzvl6ISXYDr166iUCioU6ceenpiuqWSTSgrbvKLF1yYOH4MI0ePVVuS39upKjl2dnZEhQWRLYctKJW8e/uGIQP7cv/eXebMS5lz9UtIkAsX7fmzZ2zctIHd2zaq1xV1Ks6uvftxLuGsHn8WiZKGdWUKJaaGEtbf/qDeRyW+nonFLTKEXAiNenHyLEpRHopXq8eVLfNJiItBr/0A+g4YzPQpE6lVtx5Fizol9luBRCxCplCqBbhOfisArnwIAyAyXpirOu8hPGQq57YkPD6BFw/vsHvdEp7cuU6Bwk7MWLqR+s3bIZFIMInzyXi/dej4BVm0aBETJ05k/vz5lCxZMkWERGaGxH9Zr+aswsvtVYrlWyASwYtnTzhyaD/jJk7GyMhIve6fXdtp36EzOWxttWJ+0+Lo0aO0b9+esmXLplmI2cPdDVNTU/IXyJ+p/mbkzdXt3Tu6/9GJ+g0aMn+hELf5o0VXhW2eAkRFRXFg3x6qVSpLaEgIF6/cYNyEiRl+4VBV91HFz8ZIBWF67+FO+1ZN2LtjMwBHTl9gz8F/eeP6itHDh6rnd8XiRI91DfH1Do6hpJ0ZOcz0MTcS/oA1Ld8MkTjcjDwBkZ4hnf5aRvGaTXlz/SwAM+YuJGfuPAzp3wtpQoKQ0CMxpEkiFiERi/gQGE0OkyQBVokwCAIcGS/n8P03jB7aj/E9WxEZHkafPn04enAfLdp1wdjQAHOd6OpIxo/2al6wYAEikYjRo0dr9WnmzJnkypULY2Nj6tSpw8uXGR9RbNCgAXfu3KF+/frY2tpibW2NtbU1VlZWWFtbZ6qfv7TF+ytx49oVunfpgFPxEvTo3VdtEUVGRvL2jStjxk/8rOACXLp0iTlz5mCfMyf16jfg/Ln/cP/gTeMmTbUExcramujoaGQyWVJNXw1SJIIQaa/73LBzdHQ0nTu2xdbOjp2796Gnp/fTiO7jx4/pqRE32qlLV9Zt2IypaVIGJc3z/9Ih9uFDBhAvjefm07dEhofjVKwEVib6DBs5BpdzZxMPQJLViwh54nytjWlSztfnRLHr0AOkkUKCDAyMQZp24pE9+6cA0K3LvCTxtbJj/rx9tK7VmANzRiIN/oiJiSPrNm2naf2abNm4jsHDRqrDiFTn6hUpRAHkNReuyX/ugZgaJL2H33j4iltLBqGUxdNgxDyK123DgMLCOUiiszYXt47fh6+tMPQ1+96/f59NmzZRqlQpre8XL17MsmXL2LFjB0WKFGHu3Lk0bNiQN2/eqCNY0uPy5cuZ71Qa/N9bvN+L3bt2YGRkxH8XrmJkmJTw49ULocxayVJJnnEvX75k0aJFKdooVLQEx47/S/4CBXjx+h1H/z2FnZ0dG9atAbQFRBovzONFR0enaCc90U3tc/J9FQolI4YO5sP79+w/eBQrK6ufRnQB2nXqRq06dQFo3qIVGzZvw9j4C63KVAgJDubc2dO4vXtLeFgYg7p34MHNS1iZ6HH1yiUOH9hHtuw51DGyqjneBHmiYIlFmBpJsDE1IJ+lCbZmEho2LIGBuTnYJiatMEi9nyrR1frZwBhihCTtx68Ifghr+zZg7OyFlK9YmR69+7Fw3iwC/IV1qjjes65+SBP75BUZg1dkDI8Sh5sBwgN8ubl0MOjpU3PqHkxKNlKLrg4dPyNRUVF069aNzZs3a1mhSqWSFStWMGXKFNq1a4ezszM7d+4kJiaGvXv3Zqjt2rVrp7tkBp3wfkPyOhZXL1WrVScoMDBFnuHnz58ikUgo6iQ4XykUCrp06cLu3bsB7YpCZ8+c5srlSyz5eyUGBoZs2bwJf39/xk34U92eSAQhIcHMnzuLVm3aploAIXmxdBXpDS+r1olEcPzYEfbt3c2a9ZsoVrz4TyW6APHx8QT4+VGmbDn2HTyMsVHqmc2+hB3bNlM0vz2d27dCoVBgYGCAq+tr/vpzApYmBrRs2pAiTk7s+Gc/SiWJFauS9lddO4lY8Cg21tfDycaCBk42avE1KFQKDE1TiK+m6Gqhso5jIhDFx1GglRAidnzzck688KJS1+GIRWJmz5ii/v098golp6kwzaGqAzxizU3u3vvAow9h3Hz8ho1juiESiak4ei0is2zEJXx5nKKO/0+UWfAPhPAkzSU+0ZBIi2HDhtG8efMUNcjfv3+Pn58fjRo1Un9naGhI7dq1U8TlpkdYWBh///03/fv3Z8CAASxfvpxwjYpdX4pOeL8TterUQy6Xc/vmdWEEMvGh/PL5c4o6FcPI0Ij8hUswd+5cQCg4oFnPVqmE48eOUrx4CRo3aYqv70emT5lE7z79qFFTO05y4rgxSKVSVqzSrobzOWGF1ONZlUoha8vtWzdZMG8O48aMpGmz5lQsV/qnE92CRUswb85MPDzc2bJtl9oRQqSRsUnzDzy16kIJcgXR8TKCo6R8DI1j7+FTjB4xFIvEl5jho8dx9fYDyiYmUylbrhybNm/nxOnz5Mxpj2bhKbEoqd6zMjGGV4WduaFafIuUcMDG1gascyaJbxrWL2iIsTQWpLHkrlkPceGmlB69lciwEA6fOEebCsUY/9cM9u3ewdzZ0wmLiMTCQB8LA31ymhqR09SIPfc+Uq58XgDu3vvArT2biQ36iLx4d+5eecnVYxf5u5ZpJn8bOv7fUD0vvmYBcHBwwNLSUr0sWLAgzWPu37+fR48epbqNn58fIDhcamJnZ6de9zkePHhAoUKFWL58OSEhIQQFBbFs2TIKFSrEo0ePMnhltNHN8X5jYqKjOXPqBAcPCMMaL54/o0nT5upQoqjIKCwtrQAhrMjFxQWAv6bNAJJuRKVSyeVLF2jbrgNKlEwcNwZDIyPmJTo1qbh4wYW9e/5h4+Zt2NvnVFtanxNcSDuJxIplS5k3ZybR0dFYWlpSq05d2rdtk7kL8g0pWLQETx4/ZuXyv5k6fRbFU0nskBqa1YRSiyO8e/MKhkZGXLn9iCdPnlCvXgMsLUy5ePUG+/fuYfSIoWzZspE/evRSO4colEpQJDlV6YlFhMUkoCcWYagvvO9KZQrszA255iUjZw5TggKjsS+QBz+A0E8QKXgXd+syL1Wrd8/+KcJ8L/DxpSu5SzgRKbbH2C4/9/87yt3ObejRdyAB/n6sXbGUvf/spMeA4cjkCqIiwokID+NNpDm2lVqqxXfe6MVUq3CO+OtJ99WePZF069YtQ9dSh46swNvbW8tb2NAw9VErb29vRo0axfnz57UcVpOTPOlFRnLrqxgzZgytWrVi8+bNan8ZmUxG//79GT16NNeuXctQO5roLN5vhJVdXpYsmo9TIQf69e5OWGgYS5evZsiwkVq/8Bx2OQgKDEAshnmzpxEWFgYIyR9UKFFy+/ZNfLy9qVOvPn6f/Dh65BDTZ87B0krbq27ZkoXo6enRsnXbpP2VaQ8tQ8rvk3Po4H7KlivP9dv3uXTpEvPnzqF8+fKZvzjfCiVMGDuKYsWKM3b8hCxrtnGLdsTGxPDy+TMaNmmOiYkJCTIl79++onBRJ6Kjo2nbrgPjRg/nzGntGrSaHtGqIWiRSBBfA4mYo68/qbctWVwIJbMvkEctuipUApsqevoQ6MXHl674vnpD8w6dCXtxDZcje7jvHUrtHiM5dfURzqXLsXT2ZDatWMDJw3s4uGsTXhf/ASA0PI7Q8Dgc8hXizMUbbNm5h4PHTlK6TDkuXLxE7oJO5ClULIuuqI7fFuXXeTarBqAsLCy0lrSE9+HDhwQEBFC+fHkkEgkSiYSrV6+yatUqJBKJ2tJNbt0GBASksILT4sGDB/z5559aTqoSiYSJEyfy4MGDTFwknfBmObYOjpy7eJUKJYuyaN5sunTryZNXbpy7dJ3+g4aqU26qxC5HDlsCAwN49/YtWzdvIlfu3BgaGlK6TFlAEN33Hh4M7NebcuUr0KhRE65fvwpA02YtUCpBJk8qSbdxy04UCgWHDu7/bF8/J7iqdWZmZty+dZNXL19gYGCQ9g4/kIJFS+D27h23bt5g0pRpGBgYqC39r41XLlayDCVLl2XbpvW88Yvk+cdwnn8U5ndWr1hGwUKOPHnymE0b1jGgTw+2bFpPXEw0YlFSjmQAQ32xWnyvfwjiqmcg5oZ66ImhQgHhBapkcVv8rp79sg4mxvUS6AWBXjzSr0aNFh3YMGcC/+4UUo+2mn+Nm/pNeekTycN3/sQVFgpHWJRqgd+nSPw+RbKjV0WCo6SULFWGajXrEhoaTnFnZx7cv8fJf4993UXU8X+Byqv5a5YvoX79+jx//pwnT56olwoVKtCtWzeePHlCwYIFsbe3V48kgjBtdvXqVapVq5ahY1hYWKRaDMHb2ztDXtGpoRtqzkLOnj3Lho2beO/hTsfOXZk8bSYFChRMsZ2m2Nna2REaGsrUyX+SM1cuqlSpxocP79VveA/u36N9m5ZYWlryz54D6Onp8eDeXQDatW6Ora0dOWxtsbW1RS6Xc/rkCZRKJS8TvaW/hsePHnPnzi2OHD9F/jx2bFy3mmqVd351u9+Kgwf2Ym5uTrPmLVKs08y3rNT8jkRPbaUCmVyJb2gsvpGxeIRFc+CeL25vAwnyDSR7weY8PzaXsof+oXmnpNhpG5ts6OmJuXrlErnz5CF/gYKMHTWcnLny0LxFSwAkeiJATLxMgaG+mP1PfbAzS3qBMTfUIzJejsvG3am+JaTpXKWJSnzzFMfXzQexUw/yF3vOe7c3dJt2HKVCjiLwFWV7LKVJ9ZxE3NiESfHGGBZrhjROyuYRNXAPjqJQNjOCo6QsXDCPXZvXoq+vj62tHXFxcZ/vgw4d3xlzc3OcnZ21vjM1NSVbtmzq70ePHs38+fMpXLgwhQsXZv78+ZiYmNC1a9cMHaNz587069ePpUuXUq1aNUQiETdu3GDChAn88ccfmeq3TnizkJMnT+Lj7cW12w8pUTIplkzT6lGiRKyRVt82hzDccerkv2zetpP/zp7BzNycoKAgzp45xZgRwyhVugyHjp5QV5zp03cA5uYWBAT4ExgYyIf3Hty/e4d4aTwNGzZmRbt11E4Mp1EfNwOxuSoePnzIqOFDePjgPgDn/jtDTEwMNWvWzMxl+T4o4eD+fbRu0y5LQoeSY1GsJrn827B63mScSpWjkJPwR13c2ZmtmzewfssOBvbpQccu3bl5/VpSdpvEeF6JWMSWR97EJiiwMNIjSirDzED484uKl2NuqCdUIZLLhOIIqeVpTgXNeV4AfF5BnuL4uHogUVjz4cxRDAtHIPV5gjLaHxBx+rqEAhXq0GjCUsR6euSy0OeJfwRl7CxwD44CIJuNNbZ29rx291ZPjWRFnnIdvzdfmwTjW5QFnDhxIrGxsQwdOpTQ0FAqV67M+fPnM2ytLl26FJFIRM+ePZHJhOpg+vr6DBkyhIULM5cJTye8WYB9fiEtX/M2Hbh16xalSpVKdeJenMp3JUuVopCjIyNGjaVL1+6cOnmCG9euki+XMN/Xtl0HtmzfpSUmxYoXZ9qMWWpHIHWzGkkbUuNz4qtUKtm8cQMTxo2meAlnDh75l0cPH7Bw/hwAGjdunM5V+LG4vn7Nu3dvWfz3ii96yfgSHNuNwiTUnSlDujLkzzkM6t2NmLhLKBQKrK2tMTAwYMXShZQpV5469ZPCF1DC/Q+h6o8RcYJns5kBGEv0GDYosZiAnkRYEsV3z77JGepXWuKbULAduXPl4+OVvejndMa45lAsJGHEfnpHk3Gz0dcX/vxf+UZptde1dB4e2mQnKDCAqLgE9PT0vll6Vh2/Fz9DruYrV65ofRaJRMycOZOZM2dmqj0DAwNWrlzJggULcHd3R6lU4ujoiImJyed3TgOd8GYRcXFx7Nq2hWLFnVNdn0J0Ez/mzpOHZ6/eqm+4bt17Ym9vT+UqValatTp58+VL1/tOtUqEkJhfMzxGsySd5rZpcef2bUaNGEr/gYNZ8vcKDA0NcXQsrBZeBweH9Bv4gaji/LLnyKH+TstjG1GqoUMZwdDECI//TuOhb0SOamOR39zA7DH9KF4gJ48f3Me5VGnqN2yCp18orm9csbcTSoclyJW884tSvyDlsTTEJzye2ATBmvWPkjJ55N9J5f/kMrX47tn9lc5hPq8QicQEY0XleRcQicU8uXiXILkxTi1bcOt1KBCKubkwpeGQw1QtwDFOCRw7uA/HosWQKSDik050dWSM37E6UXh4OHK5HBsbG0pqZMQLCQlBIpFkKlezTniziAWzp+H27g0Xr91BJBIllYFLxECSGK6S+L2enoYgJubzVSiVNGvRkuYtW6q/T4/ULGhNVPtn1PoLCPAHYPrMOeo5Zj0SMrbzD8I6Ry6OHzvCtStCWrcoVfrFNFAiXGfV33eCXEF8goLw2AR8w2N55BfBDhc3PO4+gqhQiE/M/JVYjF5iYUvu6m0Icb2Lra09jkWKcu7sSZRKpeAUV6o0IdFSIuNkSGVJw8XGEr2kn/XFTB61XKNTCi3xzailq0kKq1ej3aeHjiZ9l90B15tCFaTKzQTPeYVCiXdgNLmzGaFUKDh2YDdPHt5l55GzxMt0Gat0/H/TpUsXWrZsydChQ7W+P3jwICdOnODMmTNf3KZOeLMAvw+unDpxHCNjY548fkSxEs4pMlRBkuiqSC6sGfEwTu2FMEWe5c8IdloYGAhiu3D+HDp16Yqzc0nEYjGzZs1Szy//THh7e1O1alViYmIoULAgBgYG6pjob4mhtR0mZhb06dqeDl26ExEezpNX7jgWyp/iZchQX0x8ggKFUkl+c1P6Dlqe5AgFSfO5SkXGnKjSIU3x1STIG7ILIxcJCXL09fUQi0XEhYdwbG5/KpUtTbSVNQULF6Vi1Z94Tl/HT4mSrxxqzrKeZB13795l2bJlKb6vU6cOU6Zk7m9WJ7xZxNmL15g5ZRIjhvRnx7ZNdOzcVZjvUCiEPElKJfnz5cO5VGkKFCiIQiFCL5VgrtRE80vmK8Ui0Rff+KrtGzZqzNTps1i5fCnr1qxCJBLh7FyStWvXZLoKx7ekZt1GmJqZ0a17T5atWoNCoUAv0TL9liNWFnmdKD12K8+2TuXvhXMQi8XExiblxDaU6BEvS8pQZagvpuGMM0R90qh/q5nV5AucqT5HquKriVIBQd6U+6MjkCS+AfdPEx/qz/VL52nbuQce797g/8mX7Abpp+rToUOTn9G56muJj49XO1VpkpCQQGxs2kVN0kMXx5tF5MyZi43bdnHq3CUSpAlM/2sis6ZNYu6sqcyfPZ35s6fT/Y+OlClRhHmzZ6TaRkYs1YyIsOY2qW2v6QARGxvHmdOnuHH9KiIR/DV1OrfvPcbRsTBKpZIy5cpnOlbtW6Onp0fbdu05efJfFApFqqMMKlRJIpOPOmQYhRyksXy65sKtPcd5/CiA4oNX02v6cg6cv0ehwoKDnUQjX6RYDMtuvKf7pjtJ7ZhZCwkvIFF8FWrRTVcwv4DPWs5KBUFBMeqPCQlySprHkd+xKNlt7Tl24B/KV6mBYXzWFv/WoeNXpGLFimzatCnF9xs2bMh0IiGdxZvFVKtRiz27dwGQq0AxjTy9Srp1bsdFl3M0adZcPaf7uXna1EieAjItL97kw9Oq/aRSKRdcznH40EFOn/yXyMR5UVtbW4o6FePmjevY2tlx6OgJmrdoifubnysfM0C+wsWRK5TkzOVAaEjIZ4VXkwSZkojYBEKjE/AMj+ZlYBTX3gTzwTMML9cPWuka00MsMaBi3Tbky5U0GiCVK3j8MZSPkXG89E96G7bLbQNAlKebIL6hn1K0970o06UTgFp8T46pyWCXBeR0yE/Dlh14+/IZYwZ2/yqvTR3/n/wMXs1Zzbx582jQoAFPnz6lfv36AFy8eJH79+9z/vz5TLWpE94s4qNHyhhH3/evcShUHIDFC+Zw5tQJdu7ZT6XKVYBEIUzmeZxZNMU3uSgDyBLLwLm9fUPDejUJDg7GqVgxRo0ZR/sOnQiPiOD40cO8fv2KFavX0bFTFywtLX9K0dXk4oXz1KpdF32J/g/rwz3fUJYfe03dSg5ULWBBNiPt7F7litvx6JXguGaWz5GoJ9d/RDeBJNEFsLERQtReBkTwydeHshWq0O2PrkiDqvyo7un4xfkdh5qrV6/O7du3WbJkCQcPHsTY2JhSpUqxdetWChcunKk2dcL7HTh7+gQL5s5i2qy5tO/Q6YtjTJNbtOndm6lVGVKJrkyhZMeObYhEIu4/ekYJZ2d1qJJSCZUqVVbv4/7mBUF+3l/W0e9IVFQU2zZv5PbN6yxY/Heq22TVS00KZFLwfcPTox48PWGAQb5i5MidvvNZueJ2HDr9b7rbfK1zlYrUhqwr9+qKnbUgtF5+SZ7fJfLbcPp1EB8/+lCuXjakQR5Z0gcdOn4nypQpw549e7KsPZ3wfkNyFyzGp0+fGD5kAM1btGLCxMkpRPRLhEFdqSjR9y/5vslFV1OgHz16xPK/F3Hi2BH6DRyCs0Y8mqq0X6GiQgzyz27l5itcnIsu55k6eSK5c+ehRcvWaW6rUApFCuITFMRI5YTHJOARGsV1z3C6l8r1ZQdWKiDxJUYVXpQeJeyMGTdmm+A8lZB2ysWsElxIY57YriB3/7tD5SZVsLM2Jq+9MGdfPq8Qf/jKO4TIsFB85D/nXL6OX4ffcaj5W6AT3m9A7oJCFRelUsnwwf2QSCSsXr9ZKxFGeoKbXFgFr+gvSwKhOcR86MA++vXuTv4CBfl71TqqViij3k6znu7PLriaqIo1nDp/iTyZTOwx/OATXj/zJjY4EPw9Ep8aX+5dLI0IhUSL9/b7CHZvOy8kwogMSXe/rBTcNDHPDjERYGKhFl+A/HZmvPKLpri9KbaiCAC6VC+ZXks6dHyW33Go+Vvw0wivq6sr3bp1o2DBgvTv3/+nTk+YUTZvWMtFl3McPHaKHIkZldLz/0lNVJNnokq+LjUBTz6vu27NKurUa8DBY6fw93oH8NMVsM8orq6unDj9n9opTZqYseqbDStnhFA/Pl5yY/d1Q7C01baGDU2FYvUafEvB1QonkhhAbAQYW2iJb+MOtQiLlmJlasArv2gMAwVHL1v73MSaOmAc/fNOMejQ8Tvw0whvrly5UCgUuLq6Mn78eKZOnUrNmjUZM2bMT52qMC1ev3rJjCl/MnDIcBo0agKkLbppWbEZsW7TEhyV6L56+YKHD+6x58BhTIx+zpJ+GSWfY3GePH/NlEma6RRTf1lRKISsVAaSbxQxp5ALi2oIWSTWXgdgbiNYvUoFKOTfx8IF0DdKmm9QyLXEN1+1qri6BePkmC1JfN95AmCbUxh614mvjsyis3gzxhcJb3h4uLqebFZjYWHBzJkzmTp1KiDkPnZxccHFxQVTU1OKFy9O06ZNadmyJUZGRt+kD1lBXsfixMXFMbBPD/IXLMSMOQvQT5YpQ1MoM5s/OC00c52KxSL+2bmN7Dly0KxZC0RAwSIl8Hj7MkuP+a2RyWRIpVIAatauh1gsZujwkVSpVoPixUsIdYXTsHaj4mTESOXEJs7v3vYN4eLrIO7e9iD6k4+QyUmRlOwiPXH8bJytTArhAYLVq8LcJkOhSVlFtz8WCJauyplArKcWXzPnygR6+cCHC3gfeEvROi2QV2xInZxi7hsaIktIAKOsr+yk4/+H33mO183NDXd3d2rVqoWxsTFKpTLdPPrp8UXmwPLlyz+/0VfQunVrOnXqlFRSLZHo6Gju37/P7NmzqVixIvXq1WPixIm8ffvzJG/P61icvI5C6NDMqZN599aVHbv2YmFmqrXdtxgOVYm3SnSlMgUyhZI7t2+xa8c2unbr8dMWsM8I7dq1o3HjxowcNpgZUyehUCioXqMm7dq1z/SN/00JDxDmjH3fCksiWZUgIy3U7cuElxT1U0ysh9KuAGF39xN6ZBQh946ilMXzeMdsHs7rQv1GTTEwMGT+xMHYWxjorF0dmUZl8X7N8rMRHBxMgwYNKFKkCM2aNePTJ2Fqpn///owbNy5TbX6R8J47dy7V1FlZybRp03jw4AHLli2jTJky6OkJ82UikQhDY2PsHPITFRvL2bNn6dChAwcOHPim/fkSRCK44PIf69euYta8hTiXLIWeWKReMiO6GX2DVImvKjH/yX+P0aJJA0qXKcufk6eqt/vVrN2CRUtQo1Zt5HI5t2/d4NrVywwdPpJWrdsCQopMtROaUqkeYv/uJA4nI41NMaf7PVCLrso5TEN8h/7ZHf0785C9Po7IKj827VdhUm8KRYqVwD5Xboo4FWPN5h1cOHcGlzPphzzp0PH/xpgxY5BIJHh5eWkllencuTP//fdfptr84jnepUuXMmnSpEwdLKOIxWIaNmxIw4YNUSgU/Pvvv+zbtw9XV1f8vT/QrHtfGnXpwV9dWjF37lxcXV2ZMSP1NIzfg3yFBUs3MCCAIQP6Ur9hI4YNH/nZeN0Uw8yqj6LMDbnIE9MhHti7m6ED+9CufUc2b9uprjT0K4muv78/PXv2JH+BglSsVBkra2vuPnqBWITwEpPOxY2TKpDKFETHywiPTeBVUATlcmZNrunUhqIzasl+qznetKoSIZNSpGVrXJ4EUKZpZx6f2kt0wEvCHx/n3K7FNNj1kj969iMuQUFUjDBXXaiQI7kLFks1IYwOHZ/jdxxqPn/+POfOnSNPnjxa3xcuXBhPT89MtflFwmthbcPevXvp0KEDjo6OWuuuXbvG6dOnKViwIM2bN0/RycwiFotp27Ytbdu2JSAggB49enBm9zae3rzGspOXmNW7E4cPH+bWrVtUr16dNm3aUKpUqSw5dkYwNLNmzMhhvHn9mpcvn6Onp8emLTs+m74wLdGVK5Wg1C75p7qZkzepGRMskwsN+Hh7MWHMcLp07c6mLdvV/fiVRBdgzZo1+Pr64uvri6fnB2KiozGQiNOt0pQe40+85MVLP0L8Q5B/SPTo1oitzYgoZkY4v5tDVXKUCkxL1+CjZyC58+UgomArhuwYwPV/VvLw3x1IJPr8NWsh82dMwvXlU/w+faJq9RqUKlP2x/RXx2/B7+hcFR0dnWr61KCgILVR86V80VDzn2u3A9C3b18UCmFIa/v27ZQvX55hw4Zx5swZ1qxZQ9OmTSlfvjxt27bF1dU1Ux1LDVtbW86ePUurVq34+N6NEY2r03vSTKo2bkFAYBCHDh2iW7dulClThr1792bZcdPj+LEj7Ni6GVt7OwYPGc7p/y5iZ28PJKWE1ESpTtef+FnjDVGucdOp5mvVoUEKhVZ9V837UyW6sVIZY0YMxcLSkr+Xr0IsFuPx9uUvJ7oAY8eOVc/1f/TxoXkaSTJ+xj/UPfunqJcv5fWj+3x876b++8ro8VKQI5/6x4+egQCcf+TPrhWLsLHJxsQRfcmZOw9zlqzG/5Mv5StWZurMbzsHrUPHr0itWrXYtWuX+rNIJEKhULBkyRLq1q2bqTa/yOLNW8SJ1v2HcnzzWk6cOIGvry/r16/HxNyCFr0H0arvYN6/esHNs//y6v5d3N3d6datG2fOnMHOzi5THUyOWCxm3rx51K1bl4kTJ7JgSC8adu7Ogecf8HZ/x6XD+zi3fydLliyhTZs23zzRu7vbOxwLF2HnP/u1vk8+EppqjK7GV3KFEs0pYEFMlejriZElewirM1hpiHZcgpxXL59z0eU/Nu3Yi9jQlMi4bzsf/y3YuHEj2bNnp3379mzauoM+PbvRslUbxk34M819lEolcqUSmVxJdLwcE4PPZ5XKSrLCqlUoFPzVuSXvnj9WfyfW08PA0BDHkmWZtfNQmvuG+Pvx58haLFhyShiCNzQDaRRRnm8wyemASN+Yj56BbBlbBxNTU5as3sjiOdMY0b87xsbGnDx7AbtsFtjnd0KuUOL3IetelnX8n/GVQ80/Y0HeJUuWUKdOHR48eIBUKmXixIm8fPmSkJAQbt68mak2RcoMmAwRERFYWlryz4M3SCT6/FGmILa2tgQEBCDR16fziPG0GzgixX53L/zH4uF9sbCwwMXFJctFMDg4mB49euDt7c2w+cuo164LALfPnWbpqAHUrl2bNWvWZOkxNclfuARtWzbF0MiI/YeOAaCuCidS/ZeUfUpF8iuuLlUnSrJeAcJjhILpVqaC5RcrFcJeLIz1tdpIkCtIkCtYOGcG2zat57mbj9qLOdDrzVef5/dCoVBQunRpAKKlCtzd3ChVvAjHT52lUWIsdPKhZtXtqym8wZHxvAwK5+zrYO498wPA69krcjgW+qqh5m/FJ8/3LB87BPeXz6hUqRIlSpTg48eP+Pn58ezZM8ytbZixdT9HN62mbK26VGvSCgMjI/7bu5NTOzfh753+PJNJtpzkKleXsaNGkNMhPxUchPnuUH8funRog33OnBw/+R+ebq++x+nq+M5ERUVRtWpVwsPDsbCw+CbHUGlEuWmn0DMy/fwOaSCPi+bRnBbftK+Zwc/Pj/Xr1/Pw4UMUCgXlypVj2LBh5MyZM1PtfbFzlYGRESWr1uD57RsAyBIS2LNsQarCW7lBE/r8NZvt86fTunVr/v333ywV32zZsnH8+HGqVavG1rnTqNOmE2KxmKqNm+PgWIRr164RFBRE9uzpJ7D/UvIXLqH++d3bN7Ru1x5xKr4+aeVS1kQlunGJw8iqeq4q0VWhEl2AoEgp2cwEYU1I9OJVKpWcOHaYJi1a/ZKiC0KpLU0KFiyEkZERr16+oFGjJl9cXCI5gQ9uQXyMVlrIHym4CoWC8W0a4vlWcGSqWbMm69atU6/ftGkTz549I5udPWunjOX96xfc+u8ka/8ai1hPD4Vcjp6eHlWrVqVGjRokJCSw9oy3xvkpwTI78cFueN89x5iu51i+5yQPgOoFs/PWzZ2iRZ04dvQwjx4+IJulrgygDh2pYW9vz6xZs7KsvUyl9Zm6eS/mVkleoipLMzVa9OxPm/7D8PPzo3nz5kRERGTmkKlSsccGqvfbhtKhKXEx0WyZk/QQHTx7CUqlkjlz5mTZ8ZLz9u0bPD0/UK1qde0VyYeZEx2mNFEolClEV4Wm6MZI5fiGJllmUllSQyrRjY6X8+zZc9zd3tGqbQfg1xPdAwcOMGVqUthTaGgovh8/EhcXR8GCjqnuo1AK4wjxsh8UQvSVeLx6jufb1zg5OXHkyBEt0QUhrj1v3rx8cH3F+9cvsLOzY+bMmdSoUYMC+fMzbtw4Hjx4wKZNm+jZsyf9+vXj0ZGZ6FkVFBb70ugZ50a/dDeo/hf6JmaM790e0/goevfoToeWjTl+7AgGBgbs3rH5B10FHb8Tqumvr1l+NrZv386hQymneg4dOsTOnTsz1WamhFcikbDs34s079mfYfOXMWz+snS37zF+Cp2GjyMoKIhmzZrh7++fqc5qUrHHBvXPYrPciC0Lcf7AP0jj4kiQSnnz5AHZ7HNx5coVYmJivvp4mnx4JzgrnTh2GDMzMxo0SswrLSJ10dVAU3ABEjSGloMi4vELSxLZGA0rF5JEVySCkGghTjM6Xtjm1PEjWFpaUbtufcSpmd8/MUOHDmXu3LnEx8dTuWEzAK5dvcqFCy4AVKla7bNtfAyJ4/TrTww99PSb9jUrefvkEQDDhg2jSJEiKdbb2dlx+vRpli9fjoODA3379qV9+/asX7+e48eP07t3bySSlINW97f1FpZ1wksYwT6IDC1IKDWEmOBPzFuzljPHDzD6r7n4hcfjExzNqFGjvum56vj/4HdMoLFw4cJUR01tbW2ZP39+ptrMdK5mGzt7+v41O8Pbdx4+DhMzc3YsnEnjxo2ZPHkynTt3Jjg4GENDw8+moqw4/ny668WmdsjC3ZHLZRxZt5pjm1ajb2iIQqFg6dKlTJ8+PcN9zQgf3r3k1MkTNG7SDEMjYxRKUgw3a87rylO5oZKLroqPoUICBmtTYcg4Tirnk1RONnNDreHW8NgEJGIx8fHxHDu0l6aqYWYl2OVzwt/zxzvJqCo1pRcXWrt2bW7fvo1MJsPeTEhZ2LVTOwAKFy5CDtscXzTM3HLJZQACfQLA9412QgvRN8rdnAk+uAovcGXKlEl3uwYNGtCgQYNMHeP+ug5UHHoYgn24taIV5c9PIjYiTDhuhar4BMdiEOWVqbZ16Ph/wNPTkwIFCqT4Pl++fHh5Ze5v57sWSWjZeyAFS5RiweCezJ07l8OHD/P27VvMzc25du1aqrGvqQmuUhqNzOsSSqUCPcuCiC0cUET6IDZ3wNjUjJd3BU+zhPh4jM3MOX/+fJYLL4CZmTlR0dGf3U5LdEWAMkl0w5LN5aosWRVxWnO78eSwEOLGVOFGMoWCDauX8cn3I0NGjskSr0BHJ2f1z5pVjFSJQgA8373K0D4gxCQ7FCqOt3vqzjsTpsxi1ISp7Nm1nUULhKkB55KlGDZiNKUSna1UCKP2X1GJKHH+80fO7bo9e8zOxbN58+QhYrEYKyurb3o8leUbFhYGgPfjqwDcCoinvE50dWQhv2MCDVtbW549e0b+/Pm1vn/69CnZsmXLVJvf/fW/RMUqbLv5jFLVagoxviIR4eHhzJ6tbT1XHH8+VdFVhLgTf+tv5JGeKGMDSfhwlvjn21BE+SA2E5J2fHzvrhZxh8JFCQ8Px8PDI0vPI59jceo3aMT1q5eJTyxNlzz0MpWpXeQKpVqI0xPdOLmcTxFJlppmO5qFEF67vmXV3wsYMmIMxYo587VoCqhCqaRgUcGRTFN0k3/W3EephPyOxXBxceHe4xdEhIcDQrap/IVLULCIsKhQ5beWyWTYZLOhhLNQE/b1q5eULVeeMmXLaiUTUSGTK1AolITHJPDqY9b5DXxrPnm+56+urXn14C62OXIwevTo73bsyZMnA5C3iDAKUc/q17luOn4Nfseh5i5dujBy5EguX76MXC5HLpdz6dIlRo0aRZcuafs3pccPKQtoYGTEjG0HeHHvFrkLODK5cwuOHj1Kr169UjXpAZRKBXKPi8jcziGyLohB6R6IwgJRxIWhCPdAEe2L2MqRbl3mkRAdTYECBXB3d8c6u1ApZtOmTSxcuDBL+p8vUSzqNWjI9KmTuHPrJrXr1gME8RWLU765yRXaX0THJ8XY+ofHaa2Lk2vP7ar2FItEBEdKsTYTwoti4uXMnzae7DnsGD52stY+mRlm1hRQmVzOG1dX8hcoSIEiJbTEXtWXAhoCChAbG8eaVStY/vdiQkNDAcieIwd9+w+mUuXKlCtXATs7WxLkSnLkLsi6FYswNLHg3t3bXLpwnsjISMqWr8D8xX/TqVNncuXKneHqTTPOv+HCJeGcTS0yH87wLZHGxTGpU3MUcjlbt26lUqVK3+W4YWFhnDx5khs3bpC3sBPZ7YUQCFWNaB06sorf0eKdO3cunp6e1K9fX+1ToVAo6Nmz5/ef4/1apPHxyGUyLLNlZ8qmfxjdoi7jxo3j6NGjKbZVyuJJeLoLRdAbJI6N0XNshEgkhrBAxEZWiI3KAeXU2xsYGxEbG4tYLCYsKAAzC0tu3BDCnzSdsu7/M/iL+60SXYCSpUpjaWXFndtJwguC+KqMtOSCCxAZm7ro+ifmy7U0FIQ1TqbgU1Qc9mZGWlZfcKRgGUtjIrhx2YUlqzZiYmqKNNHLOdTny6s2qUTX88MHNm/awKGD+/Hy9MTMzIyGjZvSqElTqteoRb78+dHTmBIQIbzlHjpwgGlTJ+H78SN9+w+kddv25MqdhyUL57N541oWJw4h58njQPYctrx88YyEhASMjY0pW64Cw0aOpWOXLhQuLDgZ6SVOmIsQJf4xKzPsNBZ495pQJECZurfzjxhmHrfhEaE3dxEVGcmE8eO/qeh++PCBEydOcPv2bTw8PNTOhWKxHmNXbOTq8YMAtG3blsmTJ9OiRYtv1hcdOn51DAwMOHDgAHPmzOHp06cYGxtTsmRJ8uXL9/md0+C7C29sdBRb5kzh+qljyGUyzK1tGPv3ekpVq8mzW9d5+fIlJUokWVJKaRTxDzZDlB96RVuhl6+mILr6RpC3JHg9T3EMMwsrIiLCUCqVGJuaUbZ2fa6fPEaFP5YjkmRdvdH4hASio6LIlkacsKboikUiFEqlWnQ9g4WHoV6ioH6K1q5ooxli9CkqltzmQoylpuXp+d4dgOLOpb4qxlUluu89PKhdsyqyhATatu9I8xatePrkMSdPHGfIgL7Cto6F6dG7D1KplLDQUMLCwnj54jlPHj+ieYtWHD/5H44qD10lbNi8Tejrhw88efyABw8eEBDgzx/de1K5clVKlCyFoaE+eiKRegheLw2BlcmVKJRKJHq/jtd2ty7zsK/TFIVMSuSz01iUbUPPnj2/ybGmTZvG6dOnSUgQpjDEYjE2dvaUrlmPKo2bU7lBU/QNDOg6ZjJiPQn/bl3H5MmTOXfuHKtXr/4mfdLx/4WSr8zV/DOmrkqkSJEiqUYfZIbvKrwntm/knyVzUSjk5MiRgypVqnDmzBlm9e1MwRJCYYPp06dz5MgR7i9tRIWxZ5DeWwNx4aCUIX/zLyKxCEnhJukeJ0RmizLGF6VSyQtPEXphViASIfN/hH7u6kJxcKBir83c3zngi87B0+0V+RyLI1cqOXH8KDKZjEKFnbS2UaQyuRuXkDR8rBJdFZqiGxqfQGh8AvYmRoD2jZh8uNfdzQ2APA4OX3QOmqgs+ODgYNq0bIaFhQUXr94ke/YcKJXQqEkzxkycTGhICLdv3WTvru0snDcHC0tLrK2ssbK2xsEhL3MXLKJO3fopzl9VRahAwQIULFiAlm06qFNgSsRircIPEnHK9JiQMiQrTipsI5Urfuq0mJpVg2Lf30MRH415iYbf5Fh37tzh+PHjABSvUJmuoydRtFzFVB0WxWIxXUf/Se3W7RnZtBbBwcHfpE86/v/4XYaax44dy5w5czA1NWXs2LHpbrtsWfrhtKnxXYX3yfXLKBRyFi9eTNOmTQEYN24cI0eO5NmzZwC8ffuWV69eUbx4cZSxoSijAwERIos8KCN8UMqSwm7wfimEhyQbUhSb5iQhQIiRFOkZIZIYI8lZFZnvTcTmudGzKpSib+OuJXkn/10r7TnCPIWKIVcquXn9KkMH9KF9xy5UrV4TqUyBgUScQhw1BReS4m4B3oZFAmBlIAwth8ZrO1upRFepBJ+IGHKZa1vrjk4lMDQ0YtLY4WzYvhc9Pb0vGmbO51gchULB7l3/MHXKJOQyGZeu3SJHjhwp/gAsrWxo0qwlTZq1RCyGqDgZNqYG6rhl1fYJckUKi1XTGtfXE5E834WexgbqfZWkiIlOC8/IaFqXzEFIZDz3br0DiUFSPdqfhKjXlzCwK4K+TdZU7UqORCLBxMSEmJgYXj24y7Se7SldrRbTtiQVC1k/bQIPr1wgOiIcaXzSFEfr1qkXoNCh4/+Vx48fq0eOHj9+nOZ26ZUnTY/vKrz1OvzB01vX8Pb2Vn+XLVs29uzZw5UrV5g8eTJRUVEsWrRIyAgiV4msEmWEDyLrgkicWgqCmw5ii3yIrQqDIgGxuQOIxOjZlkUR40fCBxdETtkQG1kB2oKbHnkKFVP//Mb1NV07taNKtRqs2bgNcaLlJlMo1HOxCakUZA+JShJWlegCPP4UBUB+GyFUKCZBjkd4NAUsTbQE0DcyFn2xmBymwnbFSzizZP1OxgzoyuRxI/hz7Mh0yxFKpVJu3rmHq+tr/D75ERgQgJfnBzw9P9ChY2fmLVxMHgcH9TFFIsEJzECS1KZm8+4B0RSyS3pJUWfSihNeLuJkcrKbCX3VvD2N9ZOKGKQW36xCplCoh+tlciVG+l9Q/MDIDOKjheL0yejWZd53neeVx4QT++EhNrWF0ZWWWz052S/z80OpUaFCBe7evYu/vz9Hjx7l9OnTPLlxhe0LZtBnspDq7uq/h1DI5eTLl4+cOXOSP39+SpUqRbNmzbK0Lzr+f/ldygJevnw51Z+ziu8aTlStSUsk+gasXr2aJk2acOzYMfW6OnXqcPPmTfr06UP79u2p2HMTBGkmfxchSohHlJroJkuKsPfAVA7duYpBweaIJIkPfpEI/XwNEOmbkOBxGlN7M2zKaju4xMXLiIuXMcwlPN3zcDn3H5EREWzZsRcDA4MUdXI1RVdlwWmKboLGcOr7YA0LHkF0VXiEaQ9J62scSCWGrVu3ZtGK9ezduZVTLtfS7fftew8YOWwIF11cCAoMxM7enmYtW3P6/GW27NyLdY5cWturPK89AoSXE9XhozSGd939o7n0JkD9WTUMrOJTmLbHdnJSjcdN428vMi6B0OiE1Ff+xMS53wBEmBap+c2PZWdnx5AhQzhx4gQ5c+bk1M7NPL2VdF8YGhoyePBgNmzYwKRJk3SiqyNL+R3Dib4F31V4xWIxq85cpUKdhnzy82P69OlUqlSJJUuWoFAoEIvF7HtixpzDQkUZpTzpISsyzo4ixl97qFkTkVirBqrm/FrSJgboF2yO2EBC8Jn5+G7tweXpXXh9cCl+L+5pbZua+CoUwlKzdl2USiXPnj1OIbrJvZjjEhRaGao0Y3OTi+5Nj6Rjqu6/9+GC+GqKbmC0sJ+liTBE3bFrT/IXLISPpwd2+bTnmwsUKUGBIiWwzZ2P2TOn07HzH9x/8oJT5y6wbss/LFi8jOo1aqlr/XoGCcdTia5PiNBfl7d+Wu0mF8AV1921z1uW9ALxPiD9UQWFEmQKJVHxqc/XalZsAoiMkxEUJaTXfB3w88SidusyL2npuhDEejg0bEHE8/MY56+AnrHld+uLWCzmn3/+QSKRsHBIb6IjwqnWrDWxcXFMnDiRcePGfbe+6NChQ5vvnkDDziEfkzfsZO9jd9oPHomevgG7du2ifv36vH2bbH5SnDS0KDYVisvL/O+nmNPds28ye/YJcayqB1+q6EkQm9pi330D9j02Yl1/BMa5iuD35AbP1o/kw9ktKBUKHt5+x8Pb76gy+4Gwn1V+fIKTBFMvsV9RUdqCovmyFpegIC4hmfWXKLpvQiK1itoDfNSwDDXbiZcpcQ1OKVwBUdqWZFREBFZW1ojFkLOAIL6qONvomDj+HD+G8LAwZswWro2mZarqS1CUIOiX3wZoNs27EGFY/JyrHzPPv9Na5xkWzVN/Yf3IY9qjEQkyJfGJFrxHQDQvfSK47ZHSkUdzXjwgPJ6AiHhcP0Wm2C4tTCQS7nlH4R8QRT7HnEgcimrdOz+SWO/nxAe4Y1H6+1uWdnZ2zJ8/H2l8HJO7tKRomfLUb/8HehIJ58+fT/n3pkPHV/I7Fkn4FvywxLX6BgZ0HT2Jnfde06rPYIKDg+nQoQNdyyaJjNgsD2KLfCCSIA96DgoZ8sDnKOLDBfFVKtSCmy56EmFJRCQSYW6fl+zlmmLXZAz5Bmwjf7OBeLns5NaykSgTNEJ7rPKrf/QNjSUiPJypf00gZ67cNGzSTG3Nat4wyUN34xMU6qHhNyFJgpLbUrBYVaIrlSm4+z7JgovXqET0TMOy008Mp3kXILRlJBETFhaKtbWVehuV6N68eZNaVcuze9dOZi9YSt58+bRE1yuZh7V7sDDffM8zhKXXtLN93fYSjtfzn0ck542/0M7E06/psv1+ivWaZQ1PvvTl5EtfXN6kXyzjplswB5/6pLtNuiiVKaYhNEdFvgehD45ikD0fRnnLqr/L6vnd9GjatClNmzblo4cbm2ZO4sKhPchlwsjCixcvPrO3Dh1fhm6oOWP8sAQamvT6czr12ndmVp/ObNu2jVq1anE3opQwL5u3PvGv9iAyzobYNCfKuBBQpnSYSZNUkigE3b2KQ91G6s/REbGQpzGGNUyIv7OR2ItzWbz0byrXqKe1n4frU0YM6EFoSDAbt+1GX18fEcJQqGouV5aougYSMVKZgngNq9dYom2FPfuUJHqaFvC9DxEolUrKOAiFoFU347OACErZJhWHtjDUxz88juxGSmQyGWaJhaMTZEqksRHMmj6FTRvWUa58RVyu36V4iZJ4B8eSw1yY9/ZLTN7hFx7H66AIStolDYVe8wwDYNj+J4xulOQF/sxTyEg16uhz3r8Pwc/di6mjkkJkvAIE4W6+7BphIdGcm5K0LkKacn72/ocQyuez1voueb7qoy8+8iEknqDE4e2YeBnTGxZO0dbPhiIujDi3O1jXG4FCruDMoII/pB8LFy6kdu3aGBoaUqpUKWxtbX9IP3To0CHwUwgvgINjUTZdfcTUbm24du0aejnCkOSuiUjfFP189Uh4fxaRdREkOUqC2AClQv7VlWaiwmNQxEUiC/NBFuqNMjKcvoOHc/roPiYM+gNzC0tqN2hKg0aNCQzwZ/GcaRRzLsXhE/9RoEDKh6hMw9SVy5VaYTIBEYLIlbG14klAmJbo+oXFYpPoGplSWQAASnJJREFU/Qvann3J3wBdQ6IomcMci8TsVgDhcUpy53Fg7oypFHR0ws/3I5PHjyQ8PIx5i/6m94Ah6OnpEZSY8SowMl4tvgCvgwRrev4lNzqXtleL7vUXgkW64rw77m/86Nq6lHqf9+9D1D/PnbaNjsOTcpYGBkapf248z4WQT4FcW9ZZ6zzC/X159u41TkWckMvzEyqVcdsrgpHV8pMRxhwXrLU4qZzg4BjqlM2dof2+JXv2T0ma5lDI0TOWg54BpkVq/dB+icVimjdv/kP7oOP/g98ljvdb89MILwgPiPn7TrB83FBunP4XpTQK/fyNeXRiMc2bv8TL6zqyj9c196C90zpqtmzH6CVrAOHh17XzHECEMvoTUs/ziA2tEJnaIzaxRSmPRxkXgvuGQyCLQhEbJjQlEiOSGLDrlRxZYvyWdbYcPHv8gFNH9wPQb8hIps6cJ5Te00BJStHVRCW6KmI0rOAPiRZiSFQ8NmaGWkJ7xyOUygWs1J9Vw9V+0XFq4TUxEH6Fu45dZGT/LjSvXx25XE7dBo2Zt3QV2ezyoKeXcr7zoVcouS2N1aJ78mUgACO2PqBjA+3C8+5vBMeqjauOUrV1XbXo+rknVbY5tGY/xEdTuYe2wIZ8Etqt1UVIGYlCzl/D67JoZE+iIwVnMkub7CzYfQYwp+9eIWYuMDCKJV3KpOh3Why/JCQTCQ0IRRbiB8ZmEJO+d/q3Rhb4Dkm2gogkBp/fOBlSqZRx48Yhz1cBh9LVyJ6/KCKxmP6Fft6EITp0KBRKRKmkyf2S/f8f+KmEV8WYv9dh55CPIxtWovduJ+/fN+XYsWNU7TIfpSIB5PGIP10hPj4ePYk+lRs0Ve/r9uwxCc83opSYgcQIFDLQM0Qe+ha5/0NBYA0tERnZYFK4ChLrvEis82CV1xGxxICdAyoTFxfL+ROH2LdtLZ98vNh3+gY2FsY4OycVEVAlzEhRfUizxm5kSg/sWx+TLEWV6Krw9I8kr61Ql1iVeOPu+zAqF7BSi24OkyRLVyW6ANls7dl28D92b1xK0eIladmmg9q5Kyw6geAoqdoL2itUsLZ3PP5IZQdzdRs3HgjzqYcuuOH37j1lapZSi26kpyBst/85hH2N+kmdDkqMyY4X5ubv7txLwWatUpy3CkXkR6b3a0/xMuUZPmsZ0YF+TB/ZmwtH95CvpXbu7JE7HwJQqIA1ZZMNR2cIPckPTaQhC3LDsED1L95PKpXSddxs3l67hp7kDtd3LsXUOgetp29iC0468dXx06KzeDPGTym8AF1H/4l93nysmzKOdu3aMWjQIO4enIpEImHGjBkcPRpP4ZJlmbJ5N+ZWSQ/lxSMHoFAoyJfTGk8fP8QWBTDIJwiFEgUgRpTo8SoDTOycMJAHE/nyIgnhfjQ6sYACpnEE+X/Cz9cHhUKB1/s3lG6nbckpgXhZktOUai5XkjjXqym6ZoYSouJlWqL7MZlTU6RmSUCNWF6lEu54hFGriI2W6L4KjqBCThvhPBLjhg2NjOgx7C/srYy02g6OSmpbJbouHkJf7npH4nLfm9JFkyrV+L17D8CTY6cxL14+qaGIIGH9jYuCoDloVydSJavwOHMi6bt8pbTWK6J9QSHjjXc8Y6bvw6JMTWo2bcvlfw/QtUEP/O7/h/9DF0yd6mLkKMS9xoUF8Nj7EblKVOL600BCA8OpVCX1KlY/C0ppJMqYEOQxcgJvXhC+HDTws/u13OpJ/J2N+N07Tf2RCylWozGfXJ9wedMcLq6bQefF+79xz3Xo0PGt+WmFF6Beuy7kyJWHBUN6sXbtWjZu3ES9enV58+YNEn19Fh46nWKf0tVqcenofrp27cqyM2Fo5kwSIdYKM1HK4wnYm/QwFBuYkKuIM1JzexpVqkauPHkpUrQoFarUSNonlX5qOlDJFEoCwuO0sj1d8wrS2v7qG0H09PXEJMgVatFVKJR88IvEPptQEEHz7e+yazCdyiWGVCWuePApBD2RiJI5BKcolYOWX1gc0QlyclkaaYnu2Xf+lMieZOECuNwXLNajxx9hm0fD6SbRko189RCksWBtn7ROZUVqJjNJK3zHU0gFir7wMqBnVwEQIft4E2VcEAqnMtyPL0Fo4C7W96iOIiEeo2y5CHmziOy1Aoj9+Ao397soFXIMTMwxKdYAPedO3LvznqiwSAj7BIBdqbKpH/87o/KY3jZ/OqdfCelLvwR5XBSf7pykWq8JFK7ZHBngULIS+crW5OnZvSjkMibdjGNh9awr9qFDR1bxu2Su+tb81MILULJKDXY/fMe5/Ts5unE158+fB8A6R+qemYNmL+bm2X+FxNVOfdW5NFUlACv22qze9sHu4cybF86/N54T6/OSmj1HU6ZFDwB6ls6FsaG2mIRESbE2056vC49J0EplGKBR5i+54EKS6AK8eiust7c305rb8AuOQSQCW2tBgFVJOQ4+8lOLL2jnONb0io5OtJivegbinE0QZZW1/TIoklNP/ChXMJtadN1fC/8H+ASg8HsPlhrXVpoYWhXiK+RATotUUjNqkRCHUilH5nMNJMaIbYqiCHElzuMGFqVbYurcguz21uSu1pLX7vHIr60k6MoWDLLnx6njGIpXqMLTE9txu34MqzzVkFhrF4bwv3cj6U1FnvD5/nxjXt2/g8jAApG+yRftJwv9CECCbVL5yYT4WJ6fO0C+2h15H5R+JjAdOn4oXxuL+/+huz+/8ILgdNW0ax+adu3Dm8cP2L1sPpXqp16hSCKR0HfKXNZPHUez3J4sWrRIa33yakQX9RujX9AGInwJ+yQ4C9mYSDj1LoCOzknWSnKHKUiKTY1LkGOkr6clulc9g7SKAxx5KFhmZkbCcLFKdAHc3wZQwDFpqFdzv+SZsI4/D6CFcw4t0X0aEEYxGyGUSCW67xJzQb8IDleLL8CpJ8Kc7Z4Tz7HNaaXVtsJPGGLGz11bZFUhWZ+ZL00va5hwMlLkYR4gT7pOBrlLA2BRrQ+FSwopK0Xv32NWayTy8E/oWeVhyOCqvPgUg1n2XIgNTNAzy1wB9+8Zv/vJ0wOR6ZcXREgIE4TX2NaBNx/DiY+XEfTsCglxMeSt0SaLe6lDh44fwQ9LoJFZipatwJx/jtKyd9rzZQ06/IF93vycPXtWqyBDiu1WuhLnfpOIa+uIjQzHyNwKG5Okd5FDLwSx1BTd0MShW82EEH7hcXwISkr8cTvRulS9+alEF+DGjXfcuJGU/Sk6Qphzfe8meP9qiu7HZM5XBvrCr+vo46TEE6qsT69DIjj/XmjjXZh21qdVtz4ASaL7+oUvAAGfwnh3TxgKVouuCplU7TCVETRFLS2BE0mM0c8vvDDlz5+fI0eOcG1WA61tHt0T+iESS5BYO6hHLJxzmvDyymn081ZEpK89h/2zER0ZTlxMjDrb2v1dA7m/6/Pzu5Vn3SciOBwQEeDpQ0hius6gp5cwy1MEsXWu9BvQoeMHIzhXfU0CjR99Bt+HX054M8qEVVtQKpX07dsXRbIar03WudFkneClq2cuWE/5B2wjxEE71tHUQMyZt9rZlUJjEtRFAyApCYWK2xoOVAAnnybt/+TBB611KtFV4fEuKVVjQuK8sV+ioKtEV5r4/aFH2rmTvcMFZ66Nd720vr/0Rkh4setSMmEFwr2FbRXerklfxiaKtipPdioJSDKCKkNUchHef3od1Zu24sOHD/zzzz8AnB9RhPMjUi8wfXViSfXPhraFkQW6oVQqiQoKBj83iIuGMH+Ii0p1/x/B+f3CeS0c3SpDgquJnkMlJObZ8LuyE4CIkHBCX9/GrpzwghIrlenmd3X8tOhSRmaM31Z48zsVp2XvQfj5+WkVMlYJrgqJlTAcGHJnP9JgQYhMDcSYGmhfmtCYBEJjtDMvJRfd/9wDtT6fepa26Prc0y7KoOlUkKDhrBUTI8XDSxBPabLcz7vuCOE/KtF98VEQH5XYqv5/5S7kRw4JieXZI6Hik0p0kw6qEfokT5lhKi0ykoJRU4S3L5zJ7fOCU5y7u3ZhheV1zLg6saSW2Gpi7twAefhHZMEeqa4nPlpYZFJhjlch/+4pIgGunTiCnp4eDRt+edF7kZ4+FsXrEf7mFgARb26jSIjHqkRtXj33ZWVd88+0oEOHjp+d31Z4AXpPmkHBEiW5ePEip06dSiG6AFYOBbAo1YSotzfw2TeBc48/pthm9zNfrc+PA8I4k6xazzUvwdINT6xFqym6L59ptxnzQRhqDnUVsi9piu6bl0nHiolJmlN99Fzb8o6VCrGcq/5LeU4AWy9/SPGdzwfBog730lgXptFudFiqbaVFZgTt0ZULKORycuTIwZYtW9LcLjUB1jMVwqek3g+/+LjfS3xlMhk+7u8oXLhwurWRU+PujIoARL9/gGmBCgCEvbqKSe5ifAz6OYo+6NCRHrpczRnjtxZegDn/HEMkErF3716t74P9ggkPDkckEmHXeBT2LSYhj40gLkRbZAOjBYE7nTgH+zggTL3ukb/ws0p0VZx7mWT5Pn4kzDHrGwhOVSrRVRH65Lb6Z1lCYv3bt368eJRk1cXEJCa1dxXaVYluSKgwB3jstjdbTr5Rb//eN1z9/60HwvFVoqsm+RCyynv5M9ZuWkPIGWXZiUuUrl6bwMBA6tSty71kln9q1LWM5uU/i/DZPRqRUTYUCWaZOvb34NqJwygUClq3bp2p/RVhXsQHeBBvU5bXTzwI93hGvFlSruyGq96ks7cOHT8WnfBmjF/CqzkzKBQKts6dQjb7XJhZWePu7s7dvY40WedGsF9SaTpvt484OOYmd3FnfIFoXzeO3c9D24q51aKrYu3tD1QrZKX+/MArkgdekTjZmaq/u+OeJMIq0VUR45XMOo1LcoJSiS5ATFTS3K9KdFXcf+CFc6lcatEFCA5K2l4lugCffIV0kO6vvTE0FnIzx/hpWN8qa1clup+Zz80Kq1HfwIDpW/dx4fA+Ns34k379+tG2bVtmzpypZSFKpVIuX77MlStXePLkCT4+PogtC6CftwEiPQPwefXVffkWuBzcg0gkokOHDhnep+IEF+EHPX0S3K+CoTliO2f+1955h0VxdXH43VnqgoCCgBhssWuMjdgSJIoajRpj770be5dYY4ktauwaey+xfrao2HvviAURFVCRKuCy5ftjZQEBXbrCfZ9nnsDMnTtngvDbc+655xAdAspwJOsCGWOsQCDIErKt8Ia8esnBjWsSnIuOjuZg36K4jIsTXgtTNS881+DnexoAVVQ4RkZy9l4LoGpxO/24J690SU5nH4VQ/WsbLj+NE02vwLeUdLDQi+69B4l7zoY+vKf7QpLp+gbGiq5GTci1M1iWrQIkFN2HF2/gVDauOlRUhE4gL5x5QLHSurXp+KJ72NOLoiV1W6BiRTeWd1Hv9OKrM+i9Vx6TNftC3Zu3ocL3bozt0JSdO3dy/PhxqlWrhq+vL76+vkRExCVLGZua8m2NmnhFlNFnOSdHZq/nxkej0fD4zk2cnZ0xM0t55rU2Jgr1swsYFfoBubEJMS91a/gya2dCXgVz6Y+q6W2yQJC+aEnbXtyc4fBm31BzHgdHin2TsJpR165dGTlyJMPL6hKMcuXORdjxuby9shmVpKBMrznkrxZXZ/j8+722saIL8MQ/jI2nEyYmPXv9liN3dKHc+KKby0YXEtWLLugEL/z9Ht54RR4ibl8g4uZZ/feaMN08L27rqkPFiu7bcJ0tD+4m7FMb/n4L0UMvf25ciAtnx/fuI5/7xtkAcaIrk2WKt/shto75WHT4HM37DiY0NJT9+/dzz8sLY4UFFV1r0WXMJP45dZ3NN3wYt2LTJ0U3q1k74w9UMTEp8nbjo35yAtRKjIq/b1mp1q3xy6LfCtEVfBGIULNhZFuPF2DM0rX8PXIA/r4+hAe/4c7du9y6dYv9+/djWnsy5M6FxXcdCTs2F9XrR7x+a4FdgnCnipO3AyjgoMskfeKf0It89jrhPtdH73vV6q8/+CBzODRe1rMyKmGRivcirHl8HalI+QS3vbhwltxlEpdEvHPRC8ciCcOQb0N1nuJLv0DsnR3059VvAhLb8MGzs4o2A4bTvPdA1CoVZorkKz19skBHFhL2Joh96/4hT548dOnSJUX3XppZh8qD9qDyOYa8QA3ABI3/Y31t7BT1nxYIshAtaSwZmUNc3mwtvFZ5bPl9+QYAggL8WegxhBsXL4P6HbE1nLWqaLRRwZh+VR5JoWu2oFQm7v7yoeieu/YCZ+e4ilCBgTqP08REQqnUJBRdawddNahY4leCMjJJJHyah1fAvpDum7e6NdvgO9dAHYNJYV3oWfk+FBvw+ClEhmLxVaFENr/08kJukzdOdCPifTBIQYg5M8K3xiYmGJt8pCRlPLIynJwcMwd0R6NWJ6qUZijqp6d13q5TFX07Q5mZDSBD7X8Nl4GWXJqXfNenpHDpFrfUcmlFp1TZJRAI0p9sLbyx7Fu3gpVTxoJMjvyrKsiL1EZmYoEmKoxwzzkYO5QgT93hyCQ5d274UaxUXKlIv6fB+D0NJv9XNvpzQUG6sK+fXyjOztZ60Y3lhY9/gu+TFN1YVMqEDQbii/DbeP1k42UbK+Otf8b+kX777Am8iwS79x7wW53Iqp8/APMP9n7GF91kvN3PUdw+V+5cOs/dyxcoX748VaumPCTs0mUlqicnkOcth8zUSn9esnBAXuB7VI8PI+Up8ul5uq7WffE+JK8O9QWNCilX/hTbJBCkBtEkwTCy7RpvfNatPwmASfUhGJdtiaSwRRsZSvDhOQDkrj0YmZEJymjdmtqDezrh9Hsa5yE+fxYCxIluLLHlF2N5cl+XNSwZvW/h9zHRjSVW/OKL4MsncV/HF91HN+POx2/0/i5eFaz3oqvflxsVDqEfbCf6CEJ0DeeV/3Om9e6IJEnMnTs39RNpQWZimfDnCBjl/x6ZWR5ibm6kcrv5yd7u0mFJ3FTKcJTeu4i5v42YBzt5d3UBLi4u3Lx5M9n7BYL0QKzxGka293jbtZ6ib82m9buK9msL1E/Po355C234c4xLt0KusNGLbizXTt/BrkDC2ri3rjzGqVCcNxwRqlvjffMqnDx5c+lFV0988fxU3eOkPM9YATWzTDgm8LGutprV+6zr+H+s/R/EnY8l/h5dtSquIHQWr+1+6fjcvc3oNo2IefeOsWPHYmtrm+q5ZEZmaFXxIhEmZhDsjwwwLlAb5f3NaMJ8E90XX3ABVK9uonp6HOQmGBdthEzhgDrgMtEvrxMaGprofsGnuXv3LoUKFULxkfwDgSAlZFvhjZ+AIzPJhWRViBi/Y/D0KMjkSLbFMSrgijxvKd543cayUFyt4IigN4nmexOoO/fiiT9OhfLpRTeWxze8kczi9vNqXsQrlGFAs4GPJg5FR8SJL8QVNA17nVBkY8s+hr3WiaxJMjV9tdqE3Rg+oF3rKcLr/QTXz5xgas/2aLVa5s2bR61atdI2odwUlBG6KEZkQoGUzG2RmeZGE558ww8AVcA1VH6eyO3KYlTADZmRbkuTWq1EZpabH374IW025kA8PT0ZOHAgklxO7Vq1GDduHDY2Nllt1ueL2E5kENky1JyUeBkXqofcvgJGBd0xrT4Ck7JtkOctpb8e8cRb9994ovv6qS6MHCu6sTy7k7B6UMgLXWhaE60T2NSK7odfJyC5JgAhgYnPxYamlVEJ71PHSxoT3m6qObH7XyZ3b4skSaxduzbNontpVVdkchO0MVHJjpFyfYU6zC9Rw49Y1GFPUPkdQ563HEaF6iKTm4JKiSbsBeqQR0g2RXHpvCJNduY0oqOjGTVqFEbGxtg65OPw4cP8+OOP3LhxI6tN+2wRoWbDyHbCm9xWE5mRKcb5a2BkWxpZVNJiGHHnUsITwf68vpGwLrDmrS67OeSZbh9trOjqr/vFq6gUlTATOilS5Fkqo+LCxhAnnlHhSddZTmrtGFLdcUgA/k8e8/eoAZiZm7Nz506+/fbb9JlYbopWnXymuZSrAMSE065dOxYtWqQvMHJpXW/U4X7EPDmEZFUQI6caaEN8UD2/gNLnEEqvTciMFBjZJd14QpA0/v7+tGrViqioKHqM/5MlnhcZs3QtWq2WTp06cfny5aw2UfAFk21DzZ/kwzBtbAZxwCNw/BqC4wRVE+CD5FhYL7qxhNy+AnnirQO/ircGl0rRNXiPanwxjf1aGaUT1SS2KKFSgkwySHRFmDl55gztC1otGzdsoGDBguk2r2RqgyrkIeqwp8itdJnp8X8OEWGhjGh2mzt37nD79m1WrVrFypUrWbRoETGPziDl+grjArVR+R1D/cYLZHJkZrkxyl8Ded5vkcmN083W7M64cePYtWsXWq2WqnV/xr15GwAq1XRn8sZd/N7uV7p168bixYupXr16Flv7eSGymg0j23m8KRKN2AIF8bftxESD351EQzWPryc8ERvijW2qkA6iazDJbQf6VNa0EN00cf/aZR7duYmLiwtFixZN17nl9hWRcjkT43OAdg2dEv0cLK2sWXT4HFvv+NHnj5kolTG0bduW06dPU7x8RV0C1qM9qIMfYORcC9NyPTEt0Qojh4rIJDloNVxa3S1dbc6OvHz5kp07d2KT157p2w8w/O/lCa4X/7YSIxeuRKPRJGg3KtAhQs2GkS093g2bPRJ7jhp1wv2ysedCAsH4fV3d5IpKxCa7BD4GhyIJ11WjI+CFNxi/r4OsTH6dLr59aSZ2HVf2/rNTfFGNvzdYrOWmG6f+txOAUaNGpfvclzf0IySkHQ0aNGDFZA8uHNnPyAUrUFhaJRgnSRLuLdpR7NtK/NmnE9UbNOantp3p06A+2phITIo1Q1LkBXRhaEHKOHbsGABdR0+kaNnEywjXTx1jej/dB5ju3btnqm2C7EO283gN5kNB+lB0I94nVMXPMNWoddt1Yvkw4SmzRDc+H/NyUyi6wtv9OF+XKQfA/fsZ05rPxsaGffv2UbZsWW6fP0PnqmW5d/lCkmMLFi/J4qMXaDNwJEMb10arDMfk68ZIirxcWtdbiG4quXRJl+dRwTXphLlZg3ohQ8vy5cuF8CaFNh2OFDBt2jRcXFzIlSsX9vb2NGnSJNHvp1arZcKECTg5OWFubo6bmxt37iSOamYm2VZ4kxSR5JKNkvN0I+JlM394TwaJbqrELx2SpYTofppy1V0BuH79eoY9I3fu3GzatIn58+ejVqk4uGnNR8fHvIsmMiKc/I52XNnuIQQ3jXh7e2Nsaoq5ReKezyf3/kvU2wg6dOiQqgplOYHMDjWfOHGCfv36cf78eQ4fPoxKpaJu3bq8fRuXQDtjxgz++usvFixYwKVLl3B0dKROnTqEh4d/ZOaMJVuGmmNJNuScUj68JyosLsQL6b52mtye3vhzfI6NArI7to75kEkS3t7eGf6sEiVKAGBta/fRceYWllRyq8PlY/+xaNEiJElCoVDQsWPHDLcxuxEZGcmTJ08oUKxkktd3LNVVDuvUSdS9To7MTq46ePBggu9XrVqFvb09V65cwdXVFa1Wy9y5c/Hw8KBp06YArFmzBgcHBzZu3EivXr1SbWtayLYebyxp9uSSE+pYsc3AhKWP7e9NTw9VeLuGY2GZixcvXnx6YBrx89MVy8id1+ETI6H/9HmYKSxYvHgxCxcuZObMmTkmSSU9mT9/Plqtllb9hyV5vVq9hgD8/PPP+PomriImSD/CwsISHO/evTPovtjqbHny5AHAx8eHgIAA6tatqx9jampKzZo1OXv2bJJzZAbZXnjBcGFJatyGzR7J358JWcIfe74QzMwnj2M+goODPz0wjQQE6DpK2eVz+sRIXcbzusv36TJmEsamuiQ/T0/PDLUvO7J//37MFBZUqVM/yeut+g+j98QZREZG8uuvvxIZGZnkuKQICwujffv2TJo0SR8xCQwM5MiRI6xatYqQkJD0eIUsJ71Czc7OzlhbW+uPadOmGfTsIUOG8P3331O2bFkg7vfIwSHhB1gHBwf9tawgW4eaP8aH4dzY7+OHpz/0OFMa3s0MYUxtj1oh2qnjqyLFeOrtRXR0NGZmZhn2nNh1ZDunrwwaL0kSDTt2p1bTlnSoXJINGzZQu3btDLMvO5InTx6CHz8mRqlMtkXlm1eBaLVaFArFR3/+3t7e2NnZ6T2v1atXc+PGDW7cuMG2bdsSjffz82PcuHHp8yJZSHqFmv38/LCyisvoN33/gfJj/Pbbb9y8eZPTp08nuib7oESuVqtNdC4zyREeLyQftk3Ko0zOy0zNOm1m8TGvOCPD1DmNr7/RbTG5cuXKJ0amnilTprBt2zYsrawpVq7CJ8df8vyPcR2aERL0GoWlFbaOTty+fTvD7MuudOnSBa1Gw87lC5O8vnvlErYumI2NjQ2//PILgwcP5vz58wnG+Pn50bRpU5o1a0bNmjWpVasWERERnDlzBkmS89ceT+q0ak/57934qW1n3Jq0AEj3feFfOlZWVgmOTwlv//792bNnD8eOHeOrr+I+rDo6OgIk8m5fvnyZyAvOTHKUx5segpOU55uc95zZfGibQTWgBSnimyrfAzrhrVGjRrLjNBoN7u7uyOVy9u3bh0kyHtSHREREsHnzZvI4OPL3/pMYGX38VzQiLJRZA3uiilHS+8fKDJu3nIo1a3F4y3q8vb0pXrz4R+8XxOHu7o6HhwdXTx6lZb/Bia4bGeuqf4WEhLB27VpAF9I3MzOjcuXKmJqa4unpiVarpcIPPyI3Mubysf8YPXo0T548wcLamoLFS9J74gz9nMsnjQbIPg0sMrlJglarpX///uzcuZPjx49TuHDhBNcLFy6Mo6Mjhw8fpkIF3YdYpVLJiRMnmD59ehoMTRs5SnjTi4+Fo7Oaz8GG7Ezh0mVBJuPq1asfHTd58mRevXoFQMeOHdm8ebNB8ysUCmQyGU6Fv05yS8uHTO3VAVWMko4dO7Jp0yam9emEkbFO5G/duiWENwXEhnp/6donyes/d+hGgWIlOLhxDW5NWlCifCX+XTafs/v36MObToWKMOzvfyhYXJcZPfBnN44fP66bIDKSCV1aMm7FZiRJ4t7VSxzftQ25XI6zs3OGv19mkNlZzf369WPjxo3s3r2bXLly6T1ba2trzM3NkclkDBo0iKlTp1KsWDGKFSvG1KlTUSgUtG3bNtV2phWZ1oA3DQsLw9pal8ChsMyVGXYJBJ8tPVwrEv02nAsfhBlj8fX1pVGjRtg6OlGkTDkuHjlAu3btDK54Va1aNUwtrVh2/NOF+Nt8WwRHB3v27dvH69ev6da9O2GhofTp04eWLVum6L1yMsHBwdSsWRP7rwqw6PC5FN//JjCA1wHPKf5tpQTngwL8mdStNc8exRXeyZ3XngqutfH8dxOSJDFy5MgMFYGIiAiqVatGaGhognXT9CRWI/K0XYlkkvq+xRplJG82djXY1uTWaVetWkXnzp0BnZhPnDiRpUuXEhwcTJUqVVi4cKE+ASsrEB6vQJBCylSpzqm9O/D39ydfvnyJrvft2xetVsvoxWsoULwkPVwrsnnzZgYMGGBQM/V8+fLh88Sw7SoajRpLS51nbGdnx+5du1L0LgIdjx49QqvVUqN+41Tdn8fBkTwOjonO2zrmY96+E7wJDGDPqiXsXb2M8JBgPP/dhJWVFdu3b0/y39CXSmZ7vIaMl8lkTJgwgQkTJqTSqvQnxyRXCXIm965eIuptMr2MU0mdlu0Bkgwfr1u3jqdPn/JDo6YUKlkaSZLoOX4aarWaiRMnGjR/sWLFUMUoiYz4dLMNjUaDXC7/5DjBx6lYsSIymYy7V5Iu0ZlW8jg40nnUBP71esHq83ewtLImLCyMe/fusWXLFlxcXNi/f3+GPDtTSetWohyy/1wIryDbsmfVUn5v+wvtKxWnVblCtPqmIC1Kf8X+9avSNG8Zl6oYGZuwevVqxo8fj1KpRKPRsGLFCmbPno25hSW/TZurH1+lTn3yOn3FwYMHCQv7tJjGJoHcOHPqk2Nz2eTm0aNHqX4XgQ5JkrC1tcXvQcbU4Y6PuYUls3YfwdjUlMGDBzN58mSio6MZ4+GBv78/0dHR/Pnnn7Rp0yZT9owLMh8hvIJsSURYKOtnT8HCwoLq1atTqEAB0GrRaDQ4FSyU5vnHrtiITV57duzYQbVq1ahWrRpz587FyMSEYX8vT5CN7OvtRe+J09FoNAbt1YzNlr598dOVdWrUb0xkZCQXL15M/csIAChZsiRvw0JRRidTuz0dyZsvP5M37AKZDDOFgqFzlqBWqfj111+pWrUqGzZs4Pbt2/xUv76+itkXQSY3SfhSEcIryJZM690JtUrF9OnTWbp0KaNHj0alUlG8fCXK//Bjmucv+111lp+4Su9JMzAxMwe5nDYDR7D+ygPK16ipH7d47HCGNK7FpWP/ka9gYTw9PXn9+vVH547NcA3y/3RpyhZ9ddte5s+fn4a3EQC4ubkBsHn+rHRfnkiKomW/ZfnJa6w6e5vq9Rvza49+vH37FltHJwbNWki/qX8RFRnJL02acOvWrQy3Jz0Q/XgNQwivINvh9+gBXlcvUrFiRWrWrIlGo2HYsGFIkkTzPgPxe3ifiLDQT09kAHVatmfNxXusu3Sf5n0GIUlxv1Irp47jyLYNADy4cY1+0+ai1Wo/2U5Oo9GVIjWzsPjk863y2FLsmwpcv349y1udfenUr18fSZLYvWIR7SsVp2WZAnSuWoahv9bB+0bGFEyxsbXD5H0FrPZDPdhy+ymLj17gh4a/Uqtpa0YvWYNapaZ9hw7s3bs3Q2xIT7SkUXhziMsrhFeQ7dizcgkAY8eOBWD58uUEBwej0WiY2qsjgxr+SKfvSrF0Qvo3tAddmHv74nkc3LAKW1tbFAoFoW9eU6qiCzXqN+bRo0f8888/yd8fofO2DNnHCzD072XIZDKGDx+eLvbnVKysrNi7dy/Dhw+nQYMGlChRHBO5hK/XXca2b4q/r0+G2/BhwZRKNd2ZtnkPcrmcMWPG8P3337N06VL9hzPBl4kQXkG249opTxQKhb4MX/78+SlUqBC1atWiX79+NGnSBEj8Ry49iI6MpGv1b9g0T1cVZ8SIEURGRlKoRBkABsxcgKW1DfPnz+f58+cJ7vXz82P16tX67GdzAzxe0K0XFi1XAT8/P65du5aOb5PzKFCgAB07dmT69Ols2bKF48ePs2SJbv11eNN6nNj9L4F+mduZqGi5Cqy96EWD9l2JeveOBQsW0KhRo0y1wVB0iclp8Xqz+g0yB7GPV5CtiIwII/hlINWqVdOfa9iwIQ0bNtR/v2jRIgCq1G2Q7s/fs2opapWKgQMH0rVrV5RKJZIkcffKBXatWESTbn0Zs2QtY9o0pkePHgm2kDRp0gSlUgmAJJdT5rtqyT0mAav/nMiDG1fJnTu3vo+vIP2oXr06EyZMYPz48fw9sr/+vImpGRbW1uSxdySPvSNWeWyxdXCkVKUqlK1aA0mSCArwZ+bAHkSEBlOygkuCbPeUYGJmRrffJ9NlzCSm9urAtVPHOH/+PFWrVk2nt0wf0rolKKes8QrhFWQrzuzbA/DRzjznzp1DJpNRunL6/9G6fvoYkiTRtWtXJEnCzMyMTp06sWbNGtbNnEz9tl3IX6QYVnls8fPz4+TJk7i6uqJUKlEqlXxb3ZVhfy9DYWlYhaEVk39n//qV5MuXj127dhlUoEOQcpo2bUqNGjW4cOEC9+7dw8fHhxcvXvDmzRueeN3h0e0bCcbLZDJy2eQh6m04Me8/TL2LikqzHZIk8fzxQyS5nHLlyqV5PkHWIIRXkK2o5OYOwL59+2jVqlWi63fv3uX69esUKFYiQSJUevEuOgpJkhLMnTt3bv2a3L71K9j41zT9J/tZs2bh6urKvXv3ACjtUtVg0QU4s383CoWC/fv3Z0joXBCHg4MDjRs3pnHjpKtbhYWF4efnx+nTp7lw4QIPHz7E2MgIM1NTwsPDGTxrcZptuHf1Ei+f++Hu7v55fsjK5CYJXyriN1WQrcjj4EiBYiW5fv06Go0mkbgOHDgQmUzGqEWrM+T5XxUpxpN7d4iMjNT/Ydy4cSMACitrNsyeiomJCR07duSff/7Bx8eHf//9V18Fq0iZpL2YqLcReLT5BX9fHzQaNSZmZjTtOYDItxGYm5rmCNHVaDS8efMGOzu7rDYlSaysrChTpgxlypShV69eAERHR+Pi4kLuvPaUdqmS5mcsnzgamUzG77//nua5MgIRajYMkVwlyHY4Ff4arVabSHSXLl1KQEAA7i3b4eBcMEOeXfSb8gBcunQJ0PX9DAgIoKJrLWLee8OnTp1i4MCB+laBEyZMwMvLC/v8zpT9rnqiOYMC/Old6zt8ve+R3ykfxYsVIzI8nPWzp6BSKhOsZ2dnWrVqxY8//sjOnTuz2hSDMTMzo06dOgS/esn8UQPTNJffowf43r9L5cqVsbW1TScLBVmBEF5BtiMiLATQ7ct8+PCh/vyOHTsAOLxlPd1qlNOvvaUn5aq7Arp+vQCrV68GoEmP36jgWhuNRkOvXr14+fIlSqUSqzy2NO87mDUX77H46AX9ns5YfL29+K1eDSJCQxgxYgR79uxhy5YtTJgwgVGjRnH58mVmzZqV7u/xuTFnzhy8vLwA+N///pfF1qSMWbNmUaRIEY7v2saBjakrV6rRaJg7VNeucPz48elpXroiCmgYhhBeQbYj5LWuD+6zZ88S7G1dt24dgwYNokqVKoQEvWb3ikXp/mznosWRGxmxY+dONBqNvvXY8V3bGPzXYuzzO3P9+nXc3XVr0dXqNaTNgOFYWlknmuv2xbMMb1oXVYySWbNm0aFDB/21Zs2a0a5dO73XnJ05dOgQK1euBOI6zXxJSJLEpk2bsLCwYPW0iSkuSanRaBjVogFPvO7i5uZGwYIZE61JD4TwGoYQXsEXza4Vi+hUpTSdqpZhUEM3wkOCeRMYoL8eHh6u/9re3p5u3bqxbNkyTE1NObhxTbrbI0kSTbr3IzQkhL/++osGDRpgb2/Pid3bMDExYfHRC/T9YxbS+45CldzcUalUieY5e2APEzq1RAasXLmSevXqpbutXwInT55M8OGpTp06X2TTeIVCgYeHB6oYJZvnzzT4vhilkgH1XXl05ybu7u6iNGg2QQiv4ItEo9EwvV9X1s2cjFr5DoWJMX4PvRnR7CeGzl1K/iK64hljxoxJdK8kSbi5uRH8KhCfu7fT3ba2g0ZiYWWtD23Xq1cPtUrFhr+m8dznIbVbtGXTDR/aDBrJ1F4daF2uEIMb/ciuFYtQqVSc2P0vswf3xtTUhG3btlGpUqVPPDH7Mnr0aORGRhiZmCCTyfj555/1e52/NOrUqQNAuIEdhyLCQulbpyr+vo9p0aIFc+bMyUjz0gXh8RqGEF7BF0egny+9fqzMxaMHKVOmDCdPnuTo0aO0adOGl8/9OLRxDd9U+wHQresmVWB+6NChAKyd9UeG2Ph12XKEh4ej0Who3LgxMpmMHcvmM6C+K/3qVmfPyiVs+Xsm5goFJUuU4Pnjh6ybOZlu1b9hweiBmJubs2/fPn31rZyIj48PYWFhVKnTALVKhVarZeDAgbRp0yarTUsTZ/bvTrL2c0jQa8Z3ak7XGuVoVbYgnb4rxZvAAHr27GlQV6vPAtGdyCCE8Aq+KPauXsZv9WrwJjCAjh07snnzZszeJySNGTOGUqVKcfHoQUq7VMHW0YkTJ07Qtm1batSogb+/v36efPny4ezszO0LZ7l60jPd7SxbRdfab/fu3ZQsWZKrV6+ybNkyvvrqKwKePmH97CmYmZuzetUqtm7dytWrV/ntt9+IjNCFxteuXYu9vX262/WloFKp9CHmpj37s+n6Y6Zt2YvCMhdBQUFZbF3qMDMzY9q0acTEKBndujEe7Zpw/9plAA5tWkPPmhW5feEscq2GYsWK0qBBAxYsWED//v0/MfPng/B4DUOmNeBNw8LCsLa2Zt3l+ygsc2WGXQJBIsZ3bM7ti2extLRk6dKlSVbu+emnn3jx4gWLjpzHPr8zL5/78e+SvzmybQPlypVjw4YN+rFHjhxhyJAhaLVaSleuwh/r02+bijI6mg4uJbHKZcmJEyf05/fs2cPUqVNp0aIFgwcPTrTlKSgoiMjIyC9yHTO9CA8Pp2mzZgT4+/Ode31GLlihv9andhUiQ4M5d+5cFlqYNh4/fszQoUP1GffmlpZERUSgUCiYM2cO1asn3lKWFiIiIqhWrRqhoaFYWRlenCUlxGqEWaMFyIzNUz2PNiaK6L2/ZaitnwPC4xV8ESijo7l98SyFChXixIkTSYruli1beP78OTV/aY59fp1w2ed3ps8fMylVuQo3b95M0ETA3d2d06dPU6hQIe5evkB0ZGS62PrE6y4XPQ+h1SbuINO4cWPOnz/P0KFDk6ycZWtrm6NFF6Bnz54E+PvTuEvvBKILYGquICYmJossSx+KFCnCzp07OXr0KA0aNMBYkqhRowanTp1Kd9HNbITHaxhCeAVfBCZmZsgkCVtb22S30GzatAmQ0Wfy7ETXhs5ZCsiYOTNhRqmVlZW+ytCBDanbYxnL2QN7aPVNQYY2cWfOkD6oVSp9pyGBYQQHB3P79m2+LvstnUYmXtc0NjVNMgv8S8Te3p7p06dz5swZlixZkj22hsVWrkrLkQPI/nXmBNkGM3MFAQEByV6PjIzEwspKXz7x7KH/ER78hoo1a5PLOjegJW/evInua9CgAb///jsn92zn1x79UmSTv68PM/t3J/DZU95FRSJJEm3btuXgwYOUKFECNze3FM2X0/nrr78A6DDMI8H52xfP8jY0lMd3b+Ho4JDovlOnTuHp6Unu3LlxcHDAycmJQoUK4eTkhPz91q0dO3Zw4MAB1Go1MpmMzp0788MPP2T8SwkEHyCEV/DFYJU7D8FvXid73cjICI1a5w0po6OZPbCn/ppMJgNIsryiJEkUK1aM+97eqFQqg+oeazQaVk0dx4ENq9BqtTg7O2Nh4UyLFi1o2bIlo0ePTunrCdCtf37I8kmjE+y5VqlUdO3alZiYGLy9vYn8xBKBXC5HLpfrtyHJJAmtRsPFixepUaMGc+fO1SfoCdKIVqM70nJ/DkAIr+CLQaPR8C6ZPZxKpZLXr18jGRsDcPJ/ukSpFi1aYGRkxL1794iIiEi2s8yvv/7KtGnTOLB+JY0690xyTHw7etdyISjAH3t7exYuXEjJkiXT8GaCWGbMmEHDhg2Z0rM9zfsM4trp43hduYhMJkOr1ZLH3pHw8DAuX76CVqtBJpNhlceW4t9W4rs6P/E2NJQ3gQGEBr0iLPgNyugoYmJiCA16TfWfGtFm0EiMjIwIDwlmco92nDlzBteaNfE8ehRLS8usfv0vn7SGi0WoWSD4fNi6cA6vXjyjbt26SV4fOnQoUVFRdB+u69py7uBeAIYNG2ZQ+7TWrVsza9YstsyfhfJdND82aUkeB8ckx149cZSgAH/q16/PjBkzUvlGgqTInz8/c+bMoX///myap/t/6+TkhL+/P5ZW1iw/eVU/NqnuU4aSyyY307ft58DGVfwzyYMJEybkiJrXgs8DkVwl+Ozxe/SArQtmY2Njkyg5CuDMmTMcP36cwqXKUr9tFwBy5c4DxHUJ+hSSJNG9e3eiI9+ycc6f9KhZkR6uFZMce2Sbrs2fCCcbjkajYezYsezevRvQtctbtmwZDRo0oGLFijRs2BBfX18A3NzcOHbsGBs3bmT+/PkEBgYiNzLmz237E8yZHv2U67ftQh4HRzw9038vd44kNtScliMHIDxewWeNRqNhYucWgJbly5cn+GMbFBTEggUL2L17N3IjI8at2KS/1nP8VM7s383kyZOpWbOmQc/q27cvvXv35vTp00yYMIHXr18mOe7elQvY2NiQO3fuNL1bTkGpVNKqVSsePnzI7t27WbVqFY8fP0ar1WJkbIwkyfH19cXLy0vfAMDOzg47Ozvc3NzQaLVMWbudfAULZ4h9b8PCsLGxyZC5cxwi1GwQQngFnzUPblwl+NVLZDIZEydOpEOHDoSFhbF+/Xq9h2RhZUXPCdOxyqPrUbpx7nQOb12PRq3m1atXKXqeJEm4urpiZWVFaFh4oushQa+JCA2hVq1aaX+5HEKzZs148uQJLrXqcfWkJ499fChS+hsadu5BGZfq9PqxMo6OjokaQXh6ehIUFIR7i3aUqFA5Q2y7c+k876Iiqdv01wyZXyBICiG8gs+aEhUq033cFA5uWM2dO3cYOXIkAJJcTpnvqtFmwAhKVa6iHx/o58u/S+ZhbGzMzz//zMCBKW8+fuvWLZ48eaIX8vgc2qTLrm3WrFkq3yjn4efnh3PREoxatIroyEiMTEz0meNj2jRGq9XSo0cPpk+fjq+vL7NmzUKhUDBr1iwkSaLzqIzrP7tzma7bT/fu3TPsGTkKkdVsEEJ4BZ899dt2oX7bLkRHRrJv3T+Ymiv4qW3nJLf9ODgXxNjUFBMjI4oVK5aqbSJdunRBq4VBsxP36z1/aB9yuZzvv/8+Ve+SEzEzM0MZHaX7+oNEN39fHwD++COuWcXy5ctxd3fHz8+PSjXdMbfImGxjv0cPuHX+DPb29tjZ2WXIM3IcWm0ahTdnhJpFcpXgi8FMoaBZrwE07Nj9o3ttf2rTmcjISObOnYurqyvffPMNkyZNMvg51tbWIIOvyyQsS7l0wiiePvCiTJky6ZLYk1MwNzcn8m1Ektd+7tCdEhUq06z3AP7a44lcbsTGjRv1HmividPT3R6NRsNCj6EMauiGKkZJ37590/0ZORZRucogxF8PQbaj86jxzNnrqS+aAXDv3j2D7x8wYAAatZpV0yagjI5m7cw/aFexGP9tXouzszOrVqWttGROIzo6OlmvtXmfgUzdtIe2g0ZRsHhJSrtUJTo6GpVGS702nbB1zJeutmg0GoY1qYPnv5twypePnTt3imUDQaYjQs2CbMfDm9fwaNcE0O3P7dq1K/nyGfYHPDAwkGnTpgG67OV2FYui0WiwtLSkZ8+e9OvXT3i7KSQqKgqnrw0L5U5YvTVDbfmzb2d8ve/RoEEDpk9Pf29akNYtQWKNVyD44rh1/jSTuukapS9ZskTf7eXMmTOcPXtW3xXI29ubffv2cfHiRcLDw5HJZMjlcp49e8a7d+8oUaEy969dpnDhwvTp04f69etn5Wt9sahUKtRqNXb58me1Kaz6cwJXjh+hfPnyQnQzCrGdyCCE8AqyDReOHGTmgO7IJYmRI0fqu70cOnSI4cOHo9Vq2bZ9O8p371Cr1YBu+5CJmZmuJZlGi9zImMHT5rJ1wWxMTEzYs2dPVr7SF09ISAgA0ZFvs+T53jeusHP5Im6fP01kRDhOTk6sWbPm0zcKBBmIEF5BtkDXJagbkiRRtGhRpkyZAugK5KvVakzMzKj5S3POH9qHY8EilHapyvc//0LxbyslOd/C0YNxdEy6ZKTAcOzs7MiVKxe3L5zN8GcF+vnidfUyj+7cwNf7Hg9vXtP3WM6dOzd1mzRh9OjRYqkgIxHbiQxCCK8gW2Bta4siVy7ehoXh5eVF8W8rUrZKDS4fO8y76CjGr9yMg3NBek/8eG3lyIgwFo4ZivJdNGXKlMkk67MnPj4+DBs2jPDwcCrVdE/3+f9d+jf/bV5LeEgw76KigfhhShl589rRuGFDunfvbvAavyCNiFCzQQjhFWQLFJZWrDh9k4VjBlO8fGUatNfVbG43JHE95TXTJ1HapSouteIaLiijo1k6cRQn9/yLRq3G2dlZX6xDkDquXr2Kt7c3ciNjBsycn27zhocEM75TC3zv38XMzAzH9/13ixQpQunSpalQoQLOzs7p9jyBIL0RwivINhibmDBo1sJPjvvf2uXsWbUE18bN6Tf1L9b8OYFDm9ehVsXg4ODAuHHjcHV1zQSLszeNGjVi0qRJfPV1MSytrNNlzrMH9vD3yAHEKJW4u7sze/ZsETr+nBChZoMQwivIcZhbWPI2LJSTe7Zz6n870Go05MmTh5EjR9KgQYOsNi/bYGJiQokSJfDyuocyOhqTNDabnzmgB+f/24eJiQnz5s0T9bI/R0So2SDER0VBjiO3vQMmJiZ07NiR/E5OjB07lhMnTgjRzQDat2+PVqtl37oVaZpn4ZghnP9vHyVLluTEiRNCdAVfNMLjFWQ7Av182Tx/Nr5ed3j14hmREREYGRvjXLQ4Ves2wNYhH88eejN48GCGDx+e1eZmaxo2bMj48eM5un0jv/bol6o5jmzbgOeOzRQqVIgtW7aI0PLnjAg1G4QQXkG2Y8HoQdy9fAFjY2NsbW35pkxpAgIC8L1/F597t/Xjbt26RYUKFbLQ0uyPJElYWVkRHhKcqvsf37nFkvEjsbCwEKL7JSBCzQYhhFeQ7dBoNMjlcq5evZro/MmTJ9mxYwe+vr58/fXXWWRhzkGlUvHmTTBlvquaqvtnDeyBDFi7di2KDzobCT5DhMdrEEJ4BdkOSZLQJvHJWZIk3NzccHNzy3yjciiXL18GtJSrlvIscb9HDwh89hRXV1eKFy+e/sYJBFmEiNsIsh2KXNZoNBpq1qzJunXr0Ghyxqfoz5H8+XU1msOCg1J87+pp4wEYMWJEutqU0zh16lTmPUyjTfuRAxDCK8h2DJ69iFpNWxMeEcGMGTOoUqUKf/75pxDgLCC2kMULn0cpui9GqeTmuVM4OztTsGDBjDAtR6DRaBg1alTmPVCrjQs3p+oQwisQfJGYKRT0m/oXG68/ps3AkRiZmrFhwwa6deuW1ablSExNTXl85ybK6GiDxocEvWZSt9Zo1Gp69+6dwdZlbyRJonHjxllthuADhPAKsi2SJNG8z0DWXLhL+e/duHz5sghbZgGNGjUi9E0QPd0q8fK5X7Ljnvs8ZGyHpnT//lvuXjpPsWLFhGikA5la+jRN3m5ae/l+OQjhFeQIPJatp1DJMhw4cID169dntTk5ivHjxzNo0CDCQ4IZ0MCVoAD/BNfvXb3EkF/cGVDfVS+4q1evZseOHVlksSDVxG4nSsuRAxBZzYIcgSRJTN9+gM5VSjN79mwaN26MlZVVVptlEEeOHGHy5Mmo1WrCw8Pp2bMnffv2zWqzUkS3bt0oWLAggwcPpk/tKhgZG6NWq1DFxAAgk8moVKkS48ePp3DhwllsrUCQsQiPV5BjMDIyYuDMBahUKvr1S10Vpczm0KFDDBkyhJDQMEJCQlCr1dy/f58xY8YwY8YMDh06lNUmGoy7uzvjxo3DySkf+Z3yoTA311+bOnUqq1evFqL7pSNCzQYhhFeQo3CpVZfSLlW5fv06hw8fzmpzPoqXlxfDhw/H2NSUefuO03HEOEBXcWvv3r2sW7eOYcOG4eXllcWWGk6LFi1Yv349lpaWhIWF6c8/f/48C60SpBsi1GwQQngFOY7Ri1djZGyCx++/o1KpstqcZHn48CFarZbmfQaRr2BhXBs1RZIkXr16hbWtHVM37QHg999/R6lUZrG1hrF161Zq1arFzZs3+aba96w4cxMAX1/fLLZMIMg8hPAKchwKSyvqtmpPVGQk9+7dy2pzkuWnn35CkiTO/7cfgNx57Rm/eivGJiZUcqtDiQqVqfhDLe7fv4+rqytBQSkvUpHZzJw5E7mxMeNXbqFF3yEM/7UuQJbtsZ4zZw4NGzbMkmdnS0So2SBEcpUgR6J89w6IK/DwOWJkZISlpSWhQa/158p+V53NN5/ov/dYvp4u1b8h7E0QCxcuZNy4cVlgqWGcOXOG6Oho3Fu0ZfP8mdy/dhlJkmjdujWjR4/OdHvmzJnDypUrM/252RrRJMEghMcryJG8eRkAgI2NTdYa8gkkSSI06BUh8cT3Q4b8tRgjY2O2bdtG7969P5uw8+vXr5k1a5beE//7778BOLJ9E/evXaZixYp4enri4eGRKV2HtFotW7ZsoXXr1lSsWFEvujKZjDt37mT483MGafV2hccrEGRbQl+/wsjo8//n/8cff9C/f39GtWjAzB2HyGWTO9GYb6p+z6pzt5jUpQ1nzpzB1dWVb7/9lsKFC1OqVCnq1auHmZlZpth79+5dNm3axLVr1/TrtpcuXWLJkiXcvXsXACO5nH/++YdKlSplik2xHDhwgMmTJyOTSTgWKMh37j/xLiqSgxvX0Lp1a2xtbfn333+xtbXNVLsEOQ/h8QpyJOGhIZiammbJs1UqFcuWLcPT0/OTY93c3GjdujWvXjyjc7WyjG7diIc3ryUap7C04s9t++jq8QdqLZw9e44NGzbw+++/U6VKFXr27MnFixczNJls1apVtGrVil27dvH8hT8lK7rgVOhr7t69S506dfTjSpYsmemiC3D69GmdneduseDQGToOH0uPcdNYcuwSVev+TFBQEJs2bcp0u7IVIqvZID7/j/wCQQYQGR6GhYVFpj/Xy8uLTp06ERkZCYCZmRlVq1bFxcWFevXq4eDgkOgeDw8P6tSpw8yZM/G6foWRLX/mh0ZNGTRzQaKxP3foxs8ddDWpA/18uX76OP9bs5xz585x7tw5ABQKBY6OjlSsWJF27dpRtGjRNL/XqFGj2LdvH7lscjNt817yFSqiv7Zs4mgObVqD3MgItUpF7dq10/y81PDgwQPkRkaJogZ58+Vn6NyltCj9VaIezoIUIvrxGoTweAU5knfRUZleuUqj0dCzZ0+ioqJoP9SDX3v0wzyXNcePH2fmzJnUr18/2fXZ7777jm3btnH06FEKFSrEqb07OLzl46UvHZwLUq9NJ+YfPM2iw+doM3AEFV1rYZnblqd+z9i+fTtNmzZl0aJF+g8CqaF9+/bs27ePAsVKsuz4lQSiC9Bz/DT+PnCSUpW+A6B58+apflZq0Wg0PHv2DKvcSYeRJUnCPr8zly5dYv/+/ZlsnSCnIYRX8Fmj0Wg49b+dSYZX04JKqSR37sTrpRmFRqNh+PDhBAcH06zPIH7t0Y/2Qz3459Q11l/xpuVvQ4mJiWHZsmUfncfe3p4tW7agsLBg2cRR+D16YNDzHZwL0rzPIDyWrWfx0QtsufWE2buOYGFlzeLFi6larVqqaiNrNBq8vb0BCHzmy/JJY4iMCEs0Ln/hojz1vo+1tXWmJ7S9fv2aevXqERERQSU3dwDWz57Cpr9nJhg3bcv/MDU3Z9SoUVy+fDlTbcw2iFCzQQjhFXyWaDQadi5fSKfvSjF3WD9GtvyZ9pWLM2tgT5543U3T3CFBr9FqteTNmzedrP04N27cwMXFhf/++w+nwl/TZsDwBNfNLSxp9dtQTM0VbN68+ZPzKRQKVq5YgVarZVSLBlw9+em14qQoVLI0/5y6Tpcxk5AhY/Xq1Qbf6+fnxz///INGo+H06dP06tULuUyG547NzBvWP8l7wkPeEBYWRqtWrdi6dWum7N09f/489erVIyAggF+69aHPHzO5efYUO5cv5N/FcxOMtbHLy/Rt+5Hkcnr27Cn6N6eGLNrHu2jRIgoXLoyZmRmVKlXi1KlT6fxi6YsQXsFnhUajYfvieXSoXIL1s6egUavo2rUrzZo1w8zYmHOH/sfQJu40K+lEq28K0em7UvR1r8pfQ3rz8PYNg54xqWtrQFe+MKPx8fGhc+cuqNRqOo4Yx5y9x5Id++OvLQgNDeX48eOfnLdMmTKMHTuWmHfRTOnZnmFN6xLol/LqT8YmJjTs2B0zhYJoA/vlAowePZp58+ZRrVo11q5dS3BwMNHv3iE3MqbtkKT35PYYP438RYpy7949/vjjD+bNm5die5PD29ubwYMHM2XKFLZu3YqXlxeLFi2iR48eqDUaRi1aTcfhY4lRKpnYTffzb9C+a6J5nIuWoF7rjsTExIgyll8IW7ZsYdCgQXh4eHDt2jV++OEH6tevz9OnT7PatGSRabWf9u3DwsKwtrZm3eX7KCxzZYZdghxK71rf8erFMxQKBV26dKFnz54J9nj6+vqyYcMGnj59yuvXrwkJCSE8PFy/Rmlqbo7DVwXRarVo1GpMzMywtLHBOo8dNnnteRsawrGdW6lduzZz585Nk60ajYbt27ezY8cOjIyMsLOzw8HBgXz58lGgQAHs7Ozo3r070dHR/P7PRsrXqJlojk1/z+TS0UPM2vkf76Ii6eBSEnMzM9asWUPJkiU/aUNYWBjDhw/n7Nmzug4/bu5EhIXic+cWMkmi35TZVK//6Z62w36ty1Pve1y/ft2gd2/UqBFPnjzRJ0wB5LLJzZglayle/uMZy9GRkbSrWJQmTZrwxx9/GPS85AgKCmLEiBFcvHgxyevWtnZM336AvPnyo9FomNilJbcvnAVg3WUvFJaJ1/kPbVrDsomjmT9/Pm5ubmmy73MgIiKCatWqERoammF5DbEaYVquFzK5Sarn0aqVvLu5NEW2VqlShYoVK7J48WL9uVKlStGkSROmTZuWalsykhRlNUdFhGeUHQKBHplMxt69e1EoFImSfmxtbRkwYECie54/f86GDRs4ffo0Ab6PkclkyGQy1Go1KpWK+J8vLS0tmTBhAhEREamyz8vLi6VLl3L58mVUKhUymYRMJkOjUSc5vs/kWRT/tiKRH/z+HNiwmu2L5gBwet8uKv9Yh66jJ7Jy6nhatmzJ0KFDadas2UdtkSSJ2bNn4+3tjYeHB5eP6Ro/ODg4EBgYyIIxgyn/w4+ffKeyVarjc+82p0+fpnz58p8cP3LkSPr27YuZuYIGHbqRv0hR/frph+/5IbEhXKVSmeqfAcCSJUtYu24dWo2GwqXK8Nu0eRgZG/Po9g2e3L+HWqWied9BGBkZcf6//Sz0GEJkeNz685whfRn81+JE8+ZxcALg/v37VK5cOdX2fS6k5f9xilFFo01LZrI6ZcVflEolV65cYdSoUQnO161bl7Nnz6bejoxGawBRUVFaR0dHLSAOcYhDHOL4wg5HR0dtVFSUIX/uU0V6aoSjo6M2MDBQGxoaqj+io6OTfO7z58+1gPbMmTMJzk+ZMkVbvHjxDHvftGKQx2tmZoaPj89nU4pOIBAIBIZjYmKSodXL0lMjZsyYkWg/+/jx45kwYUKy98hksgTfa7XaROc+JwwONZuZmWVa2TmBQCAQfFmkl0aMHTuWESNGJDiXXJU5Ozs75HI5AQEBCc6/fPkyyWI0nwsiq1kgEAgEnw2mpqZYWVklOJITXhMTEypVqsThw4cTnD98+DDVq1fPDHNThSgZKRAIBIIvliFDhtChQwcqV65MtWrVWLZsGU+fPqV3795ZbVqyCOEVCAQCwRdLq1atCAoKYtKkSfj7+1O2bFn2799PwYIFs9q0ZDFoH69AIBAIBIL0QazxCgQCgUCQiQjhFQgEAoEgExHCKxAIBAJBJiKEVyAQCASCTEQIr0AgEAgEmYgQXoFAIBAIMhEhvAKBQCAQZCJCeAUCgUAgyESE8AoEAoFAkIkI4RUIBAKBIBMRwisQCAQCQSYihFcgEAgEgkzk/+9SlavmM+1SAAAAAElFTkSuQmCC",
+      "text/plain": [
+       "<Figure size 640x480 with 2 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# Generate a map\n",
+    "proj = ccrs.NorthPolarStereo()\n",
+    "ax = plt.subplot(111, projection=proj)\n",
+    "ax.set_global()\n",
+    "\n",
+    "# Color over the ocean\n",
+    "ax.add_feature(cartopy_ocean, zorder=1, edgecolor=\"k\", facecolor=\"lightblue\")\n",
+    "\n",
+    "# Color over the land\n",
+    "ax.add_feature(cartopy_land, zorder=2, edgecolor=\"k\", facecolor=\"lightgrey\")\n",
+    "\n",
+    "# Data\n",
+    "ds[\"siconc\"].isel(time=0).plot.pcolormesh(\n",
+    "    ax=ax,\n",
+    "    x=\"lon\",\n",
+    "    y=\"lat\",\n",
+    "    transform=ccrs.PlateCarree(),\n",
+    "    cmap=\"Blues_r\",\n",
+    "    cbar_kwargs={\"label\": \"ice concentration (%)\"},\n",
+    "    zorder=3,\n",
+    ")\n",
+    "\n",
+    "# Add coastlines\n",
+    "ax.coastlines(color=\"black\", zorder=4)\n",
+    "\n",
+    "ax.set_extent([-180, 180, 43, 90], ccrs.PlateCarree())\n",
+    "ax.set_title(\"sea ice concentration over the polar region\")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "This data is a time series dataset. Let's get an idea how the data evolves in time using interactive visualization. The example script can be found [here](https://hvplot.holoviz.org/reference/xarray/image.html)."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "#### 2.1.4 (Optional) Visualize the data with interactivity"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 14,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "b25b870cbce94c448b67bb69d8a3b48e",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "BokehModel(combine_events=True, render_bundle={'docs_json': {'941069a9-d132-4c1e-8b43-836e1d86e264': {'version…"
+      ]
+     },
+     "execution_count": 14,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "ds[\"siconc\"].isel(time=slice(0,12)).hvplot.image(\n",
+    "    geo=True,\n",
+    "    project=True,\n",
+    "    frame_width=400,\n",
+    "    coastline=True,  # geoviews needed\n",
+    "    cmap=\"Blues_r\",\n",
+    "    clim=(0, 100),  # colorbar range\n",
+    ")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Another angle using example script from [here](https://hvplot.holoviz.org/user_guide/Geographic_Data.html#declaring-an-output-projection):"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 15,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "application/vnd.jupyter.widget-view+json": {
+       "model_id": "bd0d6893ba1d4cee9b7cc87ea8bc395b",
+       "version_major": 2,
+       "version_minor": 0
+      },
+      "text/plain": [
+       "BokehModel(combine_events=True, render_bundle={'docs_json': {'0b32c7dd-f76f-4507-80d7-7c3eeb7d69da': {'version…"
+      ]
+     },
+     "execution_count": 15,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "ds[\"siconc\"].isel(time=slice(0,12)).hvplot.image(\n",
+    "    geo=True,\n",
+    "    projection=ccrs.Orthographic(-90, 60),  # longitude, latitude. Try change 60 to -60 to see Antartica\n",
+    "    project=True,\n",
+    "    global_extent=True, \n",
+    "    frame_height=540, \n",
+    "    coastline=True,\n",
+    "    cmap='Blues_r',\n",
+    "    clim=(0, 100),  # colorbar range\n",
+    ")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "The above example demonstrates the first one year of the data. To check different or longer time period, you can consider replacing `ds[\"siconc\"].isel(time=slice(0,12))` part to, for example, `ds[\"siconc\"].sel({\"time\": slice(\"1981-01-01\", \"2010-12-31\")})`."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### 2.2 Sea ice extent"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Below, we will calculate the sea ice extent from sea ice concentration."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 16,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "sea_ice_extent = (ds.siconc.where(ds.lat > 0) * 1e-2 * area.areacello * 1e-6).where(ds.siconc > 15).sum((\"lat\", \"lon\"))"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Note for the above line\n",
+    "- where siconc > 15: to consider sea ice extent instead of total sea ice area\n",
+    "- multiply 1e-2: to convert percentage (%) to fraction\n",
+    "\n",
+    "To learn more about the sea ice extent, see this [article](https://nsidc.org/learn/ask-scientist/what-difference-between-sea-ice-area-and-extent) from NSIDC."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Visualize the sea ice extent time series:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 17,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "[<matplotlib.lines.Line2D at 0x7f295428a740>]"
+      ]
+     },
+     "execution_count": 17,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "sea_ice_extent.sel({\"time\": slice(\"1981-01-01\", \"2010-12-31\")}).plot()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Let's add the `sea_ice_extent` dataArray to the dataset (`ds`) for later use:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 18,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "ds[\"extent\"] = sea_ice_extent"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 19,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
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+       ".xr-wrap {\n",
+       "  display: block !important;\n",
+       "  min-width: 300px;\n",
+       "  max-width: 700px;\n",
+       "}\n",
+       "\n",
+       ".xr-text-repr-fallback {\n",
+       "  /* fallback to plain text repr when CSS is not injected (untrusted notebook) */\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-header {\n",
+       "  padding-top: 6px;\n",
+       "  padding-bottom: 6px;\n",
+       "  margin-bottom: 4px;\n",
+       "  border-bottom: solid 1px var(--xr-border-color);\n",
+       "}\n",
+       "\n",
+       ".xr-header > div,\n",
+       ".xr-header > ul {\n",
+       "  display: inline;\n",
+       "  margin-top: 0;\n",
+       "  margin-bottom: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-obj-type,\n",
+       ".xr-array-name {\n",
+       "  margin-left: 2px;\n",
+       "  margin-right: 10px;\n",
+       "}\n",
+       "\n",
+       ".xr-obj-type {\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-sections {\n",
+       "  padding-left: 0 !important;\n",
+       "  display: grid;\n",
+       "  grid-template-columns: 150px auto auto 1fr 20px 20px;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item {\n",
+       "  display: contents;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item input {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-section-item input + label {\n",
+       "  color: var(--xr-disabled-color);\n",
+       "}\n",
+       "\n",
+       ".xr-section-item input:enabled + label {\n",
+       "  cursor: pointer;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-section-item input:enabled + label:hover {\n",
+       "  color: var(--xr-font-color0);\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary {\n",
+       "  grid-column: 1;\n",
+       "  color: var(--xr-font-color2);\n",
+       "  font-weight: 500;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary > span {\n",
+       "  display: inline-block;\n",
+       "  padding-left: 0.5em;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:disabled + label {\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in + label:before {\n",
+       "  display: inline-block;\n",
+       "  content: '►';\n",
+       "  font-size: 11px;\n",
+       "  width: 15px;\n",
+       "  text-align: center;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:disabled + label:before {\n",
+       "  color: var(--xr-disabled-color);\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:checked + label:before {\n",
+       "  content: '▼';\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:checked + label > span {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary,\n",
+       ".xr-section-inline-details {\n",
+       "  padding-top: 4px;\n",
+       "  padding-bottom: 4px;\n",
+       "}\n",
+       "\n",
+       ".xr-section-inline-details {\n",
+       "  grid-column: 2 / -1;\n",
+       "}\n",
+       "\n",
+       ".xr-section-details {\n",
+       "  display: none;\n",
+       "  grid-column: 1 / -1;\n",
+       "  margin-bottom: 5px;\n",
+       "}\n",
+       "\n",
+       ".xr-section-summary-in:checked ~ .xr-section-details {\n",
+       "  display: contents;\n",
+       "}\n",
+       "\n",
+       ".xr-array-wrap {\n",
+       "  grid-column: 1 / -1;\n",
+       "  display: grid;\n",
+       "  grid-template-columns: 20px auto;\n",
+       "}\n",
+       "\n",
+       ".xr-array-wrap > label {\n",
+       "  grid-column: 1;\n",
+       "  vertical-align: top;\n",
+       "}\n",
+       "\n",
+       ".xr-preview {\n",
+       "  color: var(--xr-font-color3);\n",
+       "}\n",
+       "\n",
+       ".xr-array-preview,\n",
+       ".xr-array-data {\n",
+       "  padding: 0 5px !important;\n",
+       "  grid-column: 2;\n",
+       "}\n",
+       "\n",
+       ".xr-array-data,\n",
+       ".xr-array-in:checked ~ .xr-array-preview {\n",
+       "  display: none;\n",
+       "}\n",
+       "\n",
+       ".xr-array-in:checked ~ .xr-array-data,\n",
+       ".xr-array-preview {\n",
+       "  display: inline-block;\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list {\n",
+       "  display: inline-block !important;\n",
+       "  list-style: none;\n",
+       "  padding: 0 !important;\n",
+       "  margin: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list li {\n",
+       "  display: inline-block;\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list:before {\n",
+       "  content: '(';\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list:after {\n",
+       "  content: ')';\n",
+       "}\n",
+       "\n",
+       ".xr-dim-list li:not(:last-child):after {\n",
+       "  content: ',';\n",
+       "  padding-right: 5px;\n",
+       "}\n",
+       "\n",
+       ".xr-has-index {\n",
+       "  font-weight: bold;\n",
+       "}\n",
+       "\n",
+       ".xr-var-list,\n",
+       ".xr-var-item {\n",
+       "  display: contents;\n",
+       "}\n",
+       "\n",
+       ".xr-var-item > div,\n",
+       ".xr-var-item label,\n",
+       ".xr-var-item > .xr-var-name span {\n",
+       "  background-color: var(--xr-background-color-row-even);\n",
+       "  margin-bottom: 0;\n",
+       "}\n",
+       "\n",
+       ".xr-var-item > .xr-var-name:hover span {\n",
+       "  padding-right: 5px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-list > li:nth-child(odd) > div,\n",
+       ".xr-var-list > li:nth-child(odd) > label,\n",
+       ".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
+       "  background-color: var(--xr-background-color-row-odd);\n",
+       "}\n",
+       "\n",
+       ".xr-var-name {\n",
+       "  grid-column: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-var-dims {\n",
+       "  grid-column: 2;\n",
+       "}\n",
+       "\n",
+       ".xr-var-dtype {\n",
+       "  grid-column: 3;\n",
+       "  text-align: right;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-var-preview {\n",
+       "  grid-column: 4;\n",
+       "}\n",
+       "\n",
+       ".xr-index-preview {\n",
+       "  grid-column: 2 / 5;\n",
+       "  color: var(--xr-font-color2);\n",
+       "}\n",
+       "\n",
+       ".xr-var-name,\n",
+       ".xr-var-dims,\n",
+       ".xr-var-dtype,\n",
+       ".xr-preview,\n",
+       ".xr-attrs dt {\n",
+       "  white-space: nowrap;\n",
+       "  overflow: hidden;\n",
+       "  text-overflow: ellipsis;\n",
+       "  padding-right: 10px;\n",
+       "}\n",
+       "\n",
+       ".xr-var-name:hover,\n",
+       ".xr-var-dims:hover,\n",
+       ".xr-var-dtype:hover,\n",
+       ".xr-attrs dt:hover {\n",
+       "  overflow: visible;\n",
+       "  width: auto;\n",
+       "  z-index: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs,\n",
+       ".xr-var-data,\n",
+       ".xr-index-data {\n",
+       "  display: none;\n",
+       "  background-color: var(--xr-background-color) !important;\n",
+       "  padding-bottom: 5px !important;\n",
+       "}\n",
+       "\n",
+       ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
+       ".xr-var-data-in:checked ~ .xr-var-data,\n",
+       ".xr-index-data-in:checked ~ .xr-index-data {\n",
+       "  display: block;\n",
+       "}\n",
+       "\n",
+       ".xr-var-data > table {\n",
+       "  float: right;\n",
+       "}\n",
+       "\n",
+       ".xr-var-name span,\n",
+       ".xr-var-data,\n",
+       ".xr-index-name div,\n",
+       ".xr-index-data,\n",
+       ".xr-attrs {\n",
+       "  padding-left: 25px !important;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs,\n",
+       ".xr-var-attrs,\n",
+       ".xr-var-data,\n",
+       ".xr-index-data {\n",
+       "  grid-column: 1 / -1;\n",
+       "}\n",
+       "\n",
+       "dl.xr-attrs {\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "  display: grid;\n",
+       "  grid-template-columns: 125px auto;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt,\n",
+       ".xr-attrs dd {\n",
+       "  padding: 0;\n",
+       "  margin: 0;\n",
+       "  float: left;\n",
+       "  padding-right: 10px;\n",
+       "  width: auto;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt {\n",
+       "  font-weight: normal;\n",
+       "  grid-column: 1;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dt:hover span {\n",
+       "  display: inline-block;\n",
+       "  background: var(--xr-background-color);\n",
+       "  padding-right: 10px;\n",
+       "}\n",
+       "\n",
+       ".xr-attrs dd {\n",
+       "  grid-column: 2;\n",
+       "  white-space: pre-wrap;\n",
+       "  word-break: break-all;\n",
+       "}\n",
+       "\n",
+       ".xr-icon-database,\n",
+       ".xr-icon-file-text2,\n",
+       ".xr-no-icon {\n",
+       "  display: inline-block;\n",
+       "  vertical-align: middle;\n",
+       "  width: 1em;\n",
+       "  height: 1.5em !important;\n",
+       "  stroke-width: 0;\n",
+       "  stroke: currentColor;\n",
+       "  fill: currentColor;\n",
+       "}\n",
+       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt;\n",
+       "Dimensions:    (time: 1944, bnds: 2, lat: 180, lon: 360)\n",
+       "Coordinates:\n",
+       "  * lat        (lat) float64 -89.5 -88.5 -87.5 -86.5 ... 86.5 87.5 88.5 89.5\n",
+       "  * lon        (lon) float64 0.5 1.5 2.5 3.5 4.5 ... 356.5 357.5 358.5 359.5\n",
+       "    type       |S7 b&#x27;sea_ice&#x27;\n",
+       "  * time       (time) object 1850-01-16 12:00:00 ... 2011-12-16 12:00:00\n",
+       "Dimensions without coordinates: bnds\n",
+       "Data variables:\n",
+       "    time_bnds  (time, bnds) object dask.array&lt;chunksize=(1, 2), meta=np.ndarray&gt;\n",
+       "    lat_bnds   (lat, bnds) float64 dask.array&lt;chunksize=(180, 2), meta=np.ndarray&gt;\n",
+       "    lon_bnds   (lon, bnds) float64 dask.array&lt;chunksize=(360, 2), meta=np.ndarray&gt;\n",
+       "    siconc     (time, lat, lon) float32 dask.array&lt;chunksize=(1, 180, 360), meta=np.ndarray&gt;\n",
+       "    extent     (time) float32 dask.array&lt;chunksize=(1,), meta=np.ndarray&gt;\n",
+       "Attributes: (12/48)\n",
+       "    Conventions:            CF-1.7 CMIP-6.2\n",
+       "    activity_id:            CMIP\n",
+       "    branch_method:          standard\n",
+       "    branch_time_in_child:   0.0\n",
+       "    creation_date:          2023-01-30T21:36:30Z\n",
+       "    data contact:           Sam Stevenson (sstevenson@ucsb.edu)\n",
+       "    ...                     ...\n",
+       "    variant_label:          r1i2p2f1\n",
+       "    license:                CMIP6 model data produced by E3SM-Project is lice...\n",
+       "    cmor_version:           3.7.0\n",
+       "    references:             Stevenson, S., Huang, X., Zhao, Y., Di Lorenzo, E...\n",
+       "    version:                v20230811\n",
+       "    branch_time_in_parent:  3560.0</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-640549f3-4fb8-4958-936c-87d365a14b51' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-640549f3-4fb8-4958-936c-87d365a14b51' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>time</span>: 1944</li><li><span>bnds</span>: 2</li><li><span class='xr-has-index'>lat</span>: 180</li><li><span class='xr-has-index'>lon</span>: 360</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-82896d8e-2ff7-4ad2-ad78-a3badb2e97d8' class='xr-section-summary-in' type='checkbox'  checked><label for='section-82896d8e-2ff7-4ad2-ad78-a3badb2e97d8' 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'>-89.5 -88.5 -87.5 ... 88.5 89.5</div><input id='attrs-5ca9d1b9-e703-436c-a749-fc55d45b8965' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-5ca9d1b9-e703-436c-a749-fc55d45b8965' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6c6ec3d3-4845-4b59-b663-f98477843cff' class='xr-var-data-in' type='checkbox'><label for='data-6c6ec3d3-4845-4b59-b663-f98477843cff' 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>bounds :</span></dt><dd>lat_bnds</dd><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>axis :</span></dt><dd>Y</dd><dt><span>long_name :</span></dt><dd>Latitude</dd><dt><span>standard_name :</span></dt><dd>latitude</dd></dl></div><div class='xr-var-data'><pre>array([-89.5, -88.5, -87.5, -86.5, -85.5, -84.5, -83.5, -82.5, -81.5, -80.5,\n",
+       "       -79.5, -78.5, -77.5, -76.5, -75.5, -74.5, -73.5, -72.5, -71.5, -70.5,\n",
+       "       -69.5, -68.5, -67.5, -66.5, -65.5, -64.5, -63.5, -62.5, -61.5, -60.5,\n",
+       "       -59.5, -58.5, -57.5, -56.5, -55.5, -54.5, -53.5, -52.5, -51.5, -50.5,\n",
+       "       -49.5, -48.5, -47.5, -46.5, -45.5, -44.5, -43.5, -42.5, -41.5, -40.5,\n",
+       "       -39.5, -38.5, -37.5, -36.5, -35.5, -34.5, -33.5, -32.5, -31.5, -30.5,\n",
+       "       -29.5, -28.5, -27.5, -26.5, -25.5, -24.5, -23.5, -22.5, -21.5, -20.5,\n",
+       "       -19.5, -18.5, -17.5, -16.5, -15.5, -14.5, -13.5, -12.5, -11.5, -10.5,\n",
+       "        -9.5,  -8.5,  -7.5,  -6.5,  -5.5,  -4.5,  -3.5,  -2.5,  -1.5,  -0.5,\n",
+       "         0.5,   1.5,   2.5,   3.5,   4.5,   5.5,   6.5,   7.5,   8.5,   9.5,\n",
+       "        10.5,  11.5,  12.5,  13.5,  14.5,  15.5,  16.5,  17.5,  18.5,  19.5,\n",
+       "        20.5,  21.5,  22.5,  23.5,  24.5,  25.5,  26.5,  27.5,  28.5,  29.5,\n",
+       "        30.5,  31.5,  32.5,  33.5,  34.5,  35.5,  36.5,  37.5,  38.5,  39.5,\n",
+       "        40.5,  41.5,  42.5,  43.5,  44.5,  45.5,  46.5,  47.5,  48.5,  49.5,\n",
+       "        50.5,  51.5,  52.5,  53.5,  54.5,  55.5,  56.5,  57.5,  58.5,  59.5,\n",
+       "        60.5,  61.5,  62.5,  63.5,  64.5,  65.5,  66.5,  67.5,  68.5,  69.5,\n",
+       "        70.5,  71.5,  72.5,  73.5,  74.5,  75.5,  76.5,  77.5,  78.5,  79.5,\n",
+       "        80.5,  81.5,  82.5,  83.5,  84.5,  85.5,  86.5,  87.5,  88.5,  89.5])</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'>0.5 1.5 2.5 ... 357.5 358.5 359.5</div><input id='attrs-ac9c6455-fa08-4b06-abf6-3f26f12c1bdd' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ac9c6455-fa08-4b06-abf6-3f26f12c1bdd' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9f06c803-0d1b-4827-bf63-dbb5b6f2548f' class='xr-var-data-in' type='checkbox'><label for='data-9f06c803-0d1b-4827-bf63-dbb5b6f2548f' 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>bounds :</span></dt><dd>lon_bnds</dd><dt><span>units :</span></dt><dd>degrees_east</dd><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></dl></div><div class='xr-var-data'><pre>array([  0.5,   1.5,   2.5, ..., 357.5, 358.5, 359.5])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>type</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>|S7</div><div class='xr-var-preview xr-preview'>b&#x27;sea_ice&#x27;</div><input id='attrs-8b8bf3f1-e71a-4f81-938d-12397faf0330' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-8b8bf3f1-e71a-4f81-938d-12397faf0330' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9802f97d-c8a1-4b9c-a944-df6cb6d185e3' class='xr-var-data-in' type='checkbox'><label for='data-9802f97d-c8a1-4b9c-a944-df6cb6d185e3' 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>Sea Ice area type</dd><dt><span>standard_name :</span></dt><dd>area_type</dd></dl></div><div class='xr-var-data'><pre>array(b&#x27;sea_ice&#x27;, dtype=&#x27;|S7&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>1850-01-16 12:00:00 ... 2011-12-...</div><input id='attrs-da5582b8-5335-4cb5-adbc-a9832bed0176' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-da5582b8-5335-4cb5-adbc-a9832bed0176' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-cf599a20-6b23-4e48-9cf4-573145b7c1ba' class='xr-var-data-in' type='checkbox'><label for='data-cf599a20-6b23-4e48-9cf4-573145b7c1ba' 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>bounds :</span></dt><dd>time_bnds</dd><dt><span>axis :</span></dt><dd>T</dd><dt><span>long_name :</span></dt><dd>time</dd><dt><span>standard_name :</span></dt><dd>time</dd></dl></div><div class='xr-var-data'><pre>array([cftime.DatetimeNoLeap(1850, 1, 16, 12, 0, 0, 0, has_year_zero=True),\n",
+       "       cftime.DatetimeNoLeap(1850, 2, 15, 0, 0, 0, 0, has_year_zero=True),\n",
+       "       cftime.DatetimeNoLeap(1850, 3, 16, 12, 0, 0, 0, has_year_zero=True),\n",
+       "       ...,\n",
+       "       cftime.DatetimeNoLeap(2011, 10, 16, 12, 0, 0, 0, has_year_zero=True),\n",
+       "       cftime.DatetimeNoLeap(2011, 11, 16, 0, 0, 0, 0, has_year_zero=True),\n",
+       "       cftime.DatetimeNoLeap(2011, 12, 16, 12, 0, 0, 0, has_year_zero=True)],\n",
+       "      dtype=object)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-210c8891-89ed-4f05-81c9-3750909ccb6f' class='xr-section-summary-in' type='checkbox'  checked><label for='section-210c8891-89ed-4f05-81c9-3750909ccb6f' 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>time_bnds</span></div><div class='xr-var-dims'>(time, bnds)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1, 2), meta=np.ndarray&gt;</div><input id='attrs-a0d0b156-81f8-40cd-a848-9033884b77e3' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-a0d0b156-81f8-40cd-a848-9033884b77e3' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b157ee1f-2c30-4347-a4c7-b792b5c81d26' class='xr-var-data-in' type='checkbox'><label for='data-b157ee1f-2c30-4347-a4c7-b792b5c81d26' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><table>\n",
+       "    <tr>\n",
+       "        <td>\n",
+       "            <table style=\"border-collapse: collapse;\">\n",
+       "                <thead>\n",
+       "                    <tr>\n",
+       "                        <td> </td>\n",
+       "                        <th> Array </th>\n",
+       "                        <th> Chunk </th>\n",
+       "                    </tr>\n",
+       "                </thead>\n",
+       "                <tbody>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 30.38 kiB </td>\n",
+       "                        <td> 16 B </td>\n",
+       "                    </tr>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Shape </th>\n",
+       "                        <td> (1944, 2) </td>\n",
+       "                        <td> (1, 2) </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 1944 chunks in 52 graph layers </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> object numpy.ndarray </td>\n",
+       "                    </tr>\n",
+       "                </tbody>\n",
+       "            </table>\n",
+       "        </td>\n",
+       "        <td>\n",
+       "        <svg width=\"75\" height=\"170\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
+       "\n",
+       "  <!-- Horizontal lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"25\" y2=\"0\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"0\" y1=\"6\" x2=\"25\" y2=\"6\" />\n",
+       "  <line x1=\"0\" y1=\"12\" x2=\"25\" y2=\"12\" />\n",
+       "  <line x1=\"0\" y1=\"18\" x2=\"25\" y2=\"18\" />\n",
+       "  <line x1=\"0\" y1=\"25\" x2=\"25\" y2=\"25\" />\n",
+       "  <line x1=\"0\" y1=\"31\" x2=\"25\" y2=\"31\" />\n",
+       "  <line x1=\"0\" y1=\"37\" x2=\"25\" y2=\"37\" />\n",
+       "  <line x1=\"0\" y1=\"44\" x2=\"25\" y2=\"44\" />\n",
+       "  <line x1=\"0\" y1=\"50\" x2=\"25\" y2=\"50\" />\n",
+       "  <line x1=\"0\" y1=\"56\" x2=\"25\" y2=\"56\" />\n",
+       "  <line x1=\"0\" y1=\"63\" x2=\"25\" y2=\"63\" />\n",
+       "  <line x1=\"0\" y1=\"69\" x2=\"25\" y2=\"69\" />\n",
+       "  <line x1=\"0\" y1=\"75\" x2=\"25\" y2=\"75\" />\n",
+       "  <line x1=\"0\" y1=\"82\" x2=\"25\" y2=\"82\" />\n",
+       "  <line x1=\"0\" y1=\"88\" x2=\"25\" y2=\"88\" />\n",
+       "  <line x1=\"0\" y1=\"94\" x2=\"25\" y2=\"94\" />\n",
+       "  <line x1=\"0\" y1=\"101\" x2=\"25\" y2=\"101\" />\n",
+       "  <line x1=\"0\" y1=\"107\" x2=\"25\" y2=\"107\" />\n",
+       "  <line x1=\"0\" y1=\"113\" x2=\"25\" y2=\"113\" />\n",
+       "  <line x1=\"0\" y1=\"120\" x2=\"25\" y2=\"120\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Vertical lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"0\" y2=\"120\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"25\" y1=\"0\" x2=\"25\" y2=\"120\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Colored Rectangle -->\n",
+       "  <polygon points=\"0.0,0.0 25.412616514582485,0.0 25.412616514582485,120.0 0.0,120.0\" style=\"fill:#8B4903A0;stroke-width:0\"/>\n",
+       "\n",
+       "  <!-- Text -->\n",
+       "  <text x=\"12.706308\" y=\"140.000000\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >2</text>\n",
+       "  <text x=\"45.412617\" y=\"60.000000\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(-90,45.412617,60.000000)\">1944</text>\n",
+       "</svg>\n",
+       "        </td>\n",
+       "    </tr>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lat_bnds</span></div><div class='xr-var-dims'>(lat, bnds)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(180, 2), meta=np.ndarray&gt;</div><input id='attrs-dd7ad08a-6d4d-4e23-9b8f-12026798b0ba' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-dd7ad08a-6d4d-4e23-9b8f-12026798b0ba' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3361684d-d723-4f81-b3c6-e01a8b480ae7' class='xr-var-data-in' type='checkbox'><label for='data-3361684d-d723-4f81-b3c6-e01a8b480ae7' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><table>\n",
+       "    <tr>\n",
+       "        <td>\n",
+       "            <table style=\"border-collapse: collapse;\">\n",
+       "                <thead>\n",
+       "                    <tr>\n",
+       "                        <td> </td>\n",
+       "                        <th> Array </th>\n",
+       "                        <th> Chunk </th>\n",
+       "                    </tr>\n",
+       "                </thead>\n",
+       "                <tbody>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 2.81 kiB </td>\n",
+       "                        <td> 2.81 kiB </td>\n",
+       "                    </tr>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Shape </th>\n",
+       "                        <td> (180, 2) </td>\n",
+       "                        <td> (180, 2) </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 1 chunks in 80 graph layers </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> float64 numpy.ndarray </td>\n",
+       "                    </tr>\n",
+       "                </tbody>\n",
+       "            </table>\n",
+       "        </td>\n",
+       "        <td>\n",
+       "        <svg width=\"75\" height=\"170\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
+       "\n",
+       "  <!-- Horizontal lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"25\" y2=\"0\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"0\" y1=\"120\" x2=\"25\" y2=\"120\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Vertical lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"0\" y2=\"120\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"25\" y1=\"0\" x2=\"25\" y2=\"120\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Colored Rectangle -->\n",
+       "  <polygon points=\"0.0,0.0 25.924160051965714,0.0 25.924160051965714,120.0 0.0,120.0\" style=\"fill:#ECB172A0;stroke-width:0\"/>\n",
+       "\n",
+       "  <!-- Text -->\n",
+       "  <text x=\"12.962080\" y=\"140.000000\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >2</text>\n",
+       "  <text x=\"45.924160\" y=\"60.000000\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(-90,45.924160,60.000000)\">180</text>\n",
+       "</svg>\n",
+       "        </td>\n",
+       "    </tr>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lon_bnds</span></div><div class='xr-var-dims'>(lon, bnds)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(360, 2), meta=np.ndarray&gt;</div><input id='attrs-6eaf2fa3-252a-4c52-9a2f-8896cb8531be' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-6eaf2fa3-252a-4c52-9a2f-8896cb8531be' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f7803c97-cbf6-4430-bf01-a66967bb1beb' class='xr-var-data-in' type='checkbox'><label for='data-f7803c97-cbf6-4430-bf01-a66967bb1beb' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><table>\n",
+       "    <tr>\n",
+       "        <td>\n",
+       "            <table style=\"border-collapse: collapse;\">\n",
+       "                <thead>\n",
+       "                    <tr>\n",
+       "                        <td> </td>\n",
+       "                        <th> Array </th>\n",
+       "                        <th> Chunk </th>\n",
+       "                    </tr>\n",
+       "                </thead>\n",
+       "                <tbody>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 5.62 kiB </td>\n",
+       "                        <td> 5.62 kiB </td>\n",
+       "                    </tr>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Shape </th>\n",
+       "                        <td> (360, 2) </td>\n",
+       "                        <td> (360, 2) </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 1 chunks in 80 graph layers </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> float64 numpy.ndarray </td>\n",
+       "                    </tr>\n",
+       "                </tbody>\n",
+       "            </table>\n",
+       "        </td>\n",
+       "        <td>\n",
+       "        <svg width=\"75\" height=\"170\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
+       "\n",
+       "  <!-- Horizontal lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"25\" y2=\"0\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"0\" y1=\"120\" x2=\"25\" y2=\"120\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Vertical lines -->\n",
+       "  <line x1=\"0\" y1=\"0\" x2=\"0\" y2=\"120\" style=\"stroke-width:2\" />\n",
+       "  <line x1=\"25\" y1=\"0\" x2=\"25\" y2=\"120\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Colored Rectangle -->\n",
+       "  <polygon points=\"0.0,0.0 25.412616514582485,0.0 25.412616514582485,120.0 0.0,120.0\" style=\"fill:#ECB172A0;stroke-width:0\"/>\n",
+       "\n",
+       "  <!-- Text -->\n",
+       "  <text x=\"12.706308\" y=\"140.000000\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >2</text>\n",
+       "  <text x=\"45.412617\" y=\"60.000000\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(-90,45.412617,60.000000)\">360</text>\n",
+       "</svg>\n",
+       "        </td>\n",
+       "    </tr>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>siconc</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'>dask.array&lt;chunksize=(1, 180, 360), meta=np.ndarray&gt;</div><input id='attrs-9572acb9-4199-46c4-b44b-427ddbcfbadc' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-9572acb9-4199-46c4-b44b-427ddbcfbadc' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a027034a-9c3f-4185-a893-8016b5695902' class='xr-var-data-in' type='checkbox'><label for='data-a027034a-9c3f-4185-a893-8016b5695902' 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>sea_ice_area_fraction</dd><dt><span>long_name :</span></dt><dd>Sea-Ice Area Percentage (Ocean Grid)</dd><dt><span>comment :</span></dt><dd>Percentage of grid cell covered by sea ice</dd><dt><span>units :</span></dt><dd>%</dd><dt><span>cell_methods :</span></dt><dd>area: mean where sea time: mean</dd><dt><span>cell_measures :</span></dt><dd>area: areacello</dd><dt><span>history :</span></dt><dd>2023-01-30T21:36:30Z altered by CMOR: Treated scalar dimension: &#x27;type&#x27;. 2023-01-30T21:36:30Z altered by CMOR: replaced missing value flag (9.96921e+36) and corresponding data with standard missing value (1e+20).</dd></dl></div><div class='xr-var-data'><table>\n",
+       "    <tr>\n",
+       "        <td>\n",
+       "            <table style=\"border-collapse: collapse;\">\n",
+       "                <thead>\n",
+       "                    <tr>\n",
+       "                        <td> </td>\n",
+       "                        <th> Array </th>\n",
+       "                        <th> Chunk </th>\n",
+       "                    </tr>\n",
+       "                </thead>\n",
+       "                <tbody>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 480.54 MiB </td>\n",
+       "                        <td> 253.12 kiB </td>\n",
+       "                    </tr>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Shape </th>\n",
+       "                        <td> (1944, 180, 360) </td>\n",
+       "                        <td> (1, 180, 360) </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 1944 chunks in 35 graph layers </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
+       "                    </tr>\n",
+       "                </tbody>\n",
+       "            </table>\n",
+       "        </td>\n",
+       "        <td>\n",
+       "        <svg width=\"172\" height=\"158\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
+       "\n",
+       "  <!-- Horizontal lines -->\n",
+       "  <line x1=\"10\" y1=\"0\" x2=\"80\" y2=\"70\" style=\"stroke-width:2\" />\n",
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+       "\n",
+       "  <!-- Vertical lines -->\n",
+       "  <line x1=\"10\" y1=\"0\" x2=\"10\" y2=\"38\" style=\"stroke-width:2\" />\n",
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+       "\n",
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+       "  <text x=\"35.294118\" y=\"93.460208\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(45,35.294118,93.460208)\">1944</text>\n",
+       "</svg>\n",
+       "        </td>\n",
+       "    </tr>\n",
+       "</table></div></li><li class='xr-var-item'><div class='xr-var-name'><span>extent</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>dask.array&lt;chunksize=(1,), meta=np.ndarray&gt;</div><input id='attrs-4ca8c76f-bd87-4ab2-8f51-a0bdeb14d941' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-4ca8c76f-bd87-4ab2-8f51-a0bdeb14d941' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-cc1433e8-ce29-4f26-8c9c-839543142d8e' class='xr-var-data-in' type='checkbox'><label for='data-cc1433e8-ce29-4f26-8c9c-839543142d8e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><table>\n",
+       "    <tr>\n",
+       "        <td>\n",
+       "            <table style=\"border-collapse: collapse;\">\n",
+       "                <thead>\n",
+       "                    <tr>\n",
+       "                        <td> </td>\n",
+       "                        <th> Array </th>\n",
+       "                        <th> Chunk </th>\n",
+       "                    </tr>\n",
+       "                </thead>\n",
+       "                <tbody>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Bytes </th>\n",
+       "                        <td> 7.59 kiB </td>\n",
+       "                        <td> 4 B </td>\n",
+       "                    </tr>\n",
+       "                    \n",
+       "                    <tr>\n",
+       "                        <th> Shape </th>\n",
+       "                        <td> (1944,) </td>\n",
+       "                        <td> (1,) </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Dask graph </th>\n",
+       "                        <td colspan=\"2\"> 1944 chunks in 48 graph layers </td>\n",
+       "                    </tr>\n",
+       "                    <tr>\n",
+       "                        <th> Data type </th>\n",
+       "                        <td colspan=\"2\"> float32 numpy.ndarray </td>\n",
+       "                    </tr>\n",
+       "                </tbody>\n",
+       "            </table>\n",
+       "        </td>\n",
+       "        <td>\n",
+       "        <svg width=\"170\" height=\"75\" style=\"stroke:rgb(0,0,0);stroke-width:1\" >\n",
+       "\n",
+       "  <!-- Horizontal lines -->\n",
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+       "  <line x1=\"0\" y1=\"25\" x2=\"120\" y2=\"25\" style=\"stroke-width:2\" />\n",
+       "\n",
+       "  <!-- Vertical lines -->\n",
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+       "\n",
+       "  <!-- Colored Rectangle -->\n",
+       "  <polygon points=\"0.0,0.0 120.0,0.0 120.0,25.412616514582485 0.0,25.412616514582485\" style=\"fill:#8B4903A0;stroke-width:0\"/>\n",
+       "\n",
+       "  <!-- Text -->\n",
+       "  <text x=\"60.000000\" y=\"45.412617\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" >1944</text>\n",
+       "  <text x=\"140.000000\" y=\"12.706308\" font-size=\"1.0rem\" font-weight=\"100\" text-anchor=\"middle\" transform=\"rotate(0,140.000000,12.706308)\">1</text>\n",
+       "</svg>\n",
+       "        </td>\n",
+       "    </tr>\n",
+       "</table></div></li></ul></div></li><li class='xr-section-item'><input id='section-e8303113-321c-426c-8404-615b944c1dbb' class='xr-section-summary-in' type='checkbox'  ><label for='section-e8303113-321c-426c-8404-615b944c1dbb' class='xr-section-summary' >Indexes: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>lat</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-7462be87-cb02-4a96-9e99-515d60b1874d' class='xr-index-data-in' type='checkbox'/><label for='index-7462be87-cb02-4a96-9e99-515d60b1874d' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([-89.5, -88.5, -87.5, -86.5, -85.5, -84.5, -83.5, -82.5, -81.5, -80.5,\n",
+       "       ...\n",
+       "        80.5,  81.5,  82.5,  83.5,  84.5,  85.5,  86.5,  87.5,  88.5,  89.5],\n",
+       "      dtype=&#x27;float64&#x27;, name=&#x27;lat&#x27;, length=180))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>lon</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-b76a570c-0eb6-4b89-a806-a969282e7555' class='xr-index-data-in' type='checkbox'/><label for='index-b76a570c-0eb6-4b89-a806-a969282e7555' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([  0.5,   1.5,   2.5,   3.5,   4.5,   5.5,   6.5,   7.5,   8.5,   9.5,\n",
+       "       ...\n",
+       "       350.5, 351.5, 352.5, 353.5, 354.5, 355.5, 356.5, 357.5, 358.5, 359.5],\n",
+       "      dtype=&#x27;float64&#x27;, name=&#x27;lon&#x27;, length=360))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>time</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-36a9050b-c1dc-4935-a951-08800bfb8f6f' class='xr-index-data-in' type='checkbox'/><label for='index-36a9050b-c1dc-4935-a951-08800bfb8f6f' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(CFTimeIndex([1850-01-16 12:00:00, 1850-02-15 00:00:00, 1850-03-16 12:00:00,\n",
+       "             1850-04-16 00:00:00, 1850-05-16 12:00:00, 1850-06-16 00:00:00,\n",
+       "             1850-07-16 12:00:00, 1850-08-16 12:00:00, 1850-09-16 00:00:00,\n",
+       "             1850-10-16 12:00:00,\n",
+       "             ...\n",
+       "             2011-03-16 12:00:00, 2011-04-16 00:00:00, 2011-05-16 12:00:00,\n",
+       "             2011-06-16 00:00:00, 2011-07-16 12:00:00, 2011-08-16 12:00:00,\n",
+       "             2011-09-16 00:00:00, 2011-10-16 12:00:00, 2011-11-16 00:00:00,\n",
+       "             2011-12-16 12:00:00],\n",
+       "            dtype=&#x27;object&#x27;, length=1944, calendar=&#x27;noleap&#x27;, freq=&#x27;None&#x27;))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-d47bddcd-6319-4443-b59b-bbce65f76daf' class='xr-section-summary-in' type='checkbox'  ><label for='section-d47bddcd-6319-4443-b59b-bbce65f76daf' class='xr-section-summary' >Attributes: <span>(48)</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-1.7 CMIP-6.2</dd><dt><span>activity_id :</span></dt><dd>CMIP</dd><dt><span>branch_method :</span></dt><dd>standard</dd><dt><span>branch_time_in_child :</span></dt><dd>0.0</dd><dt><span>creation_date :</span></dt><dd>2023-01-30T21:36:30Z</dd><dt><span>data contact :</span></dt><dd>Sam Stevenson (sstevenson@ucsb.edu)</dd><dt><span>data_specs_version :</span></dt><dd>01.00.33</dd><dt><span>experiment :</span></dt><dd>all-forcing simulation of the recent past</dd><dt><span>experiment_id :</span></dt><dd>historical</dd><dt><span>external_variables :</span></dt><dd>areacello</dd><dt><span>forcing_index :</span></dt><dd>1</dd><dt><span>frequency :</span></dt><dd>mon</dd><dt><span>further_info_url :</span></dt><dd>https://furtherinfo.es-doc.org/CMIP6.UCSB.E3SM-1-0.historical.none.r1i2p2f1</dd><dt><span>grid :</span></dt><dd>data regridded to a CMIP6 standard 1x1 degree lonxlat grid from the native grid using an area-average preserving method.</dd><dt><span>grid_label :</span></dt><dd>gr</dd><dt><span>history :</span></dt><dd>2023-01-30T21:36:30Z ;rewrote data to be consistent with CMIP for variable siconc found in table SImon.;\n",
+       "20191024.en1.LE_ens_1.ne30_oECv3_ICG.compy</dd><dt><span>initialization_index :</span></dt><dd>2</dd><dt><span>institution :</span></dt><dd>Bren School of Environmental Science and Management, University of California, Santa Barbara. Mailing address: c/o Samantha Stevenson, 2400 Bren Hall, University of California Santa Barbara, Santa Barbara, CA 93106, USA</dd><dt><span>institution_id :</span></dt><dd>UCSB</dd><dt><span>mip_era :</span></dt><dd>CMIP6</dd><dt><span>nominal_resolution :</span></dt><dd>100 km</dd><dt><span>parent_activity_id :</span></dt><dd>CMIP</dd><dt><span>parent_experiment_id :</span></dt><dd>piControl</dd><dt><span>parent_mip_era :</span></dt><dd>CMIP6</dd><dt><span>parent_source_id :</span></dt><dd>E3SM-1-0</dd><dt><span>parent_time_units :</span></dt><dd>days since 0001-01-01</dd><dt><span>parent_variant_label :</span></dt><dd>r1i1p1f1</dd><dt><span>physics_index :</span></dt><dd>2</dd><dt><span>product :</span></dt><dd>model-output</dd><dt><span>project PI :</span></dt><dd>Sam Stevenson (sstevenson@ucsb.edu), Emanuele Di Lorenzo (e.dilorenzo@brown.edu)</dd><dt><span>realization_index :</span></dt><dd>1</dd><dt><span>realm :</span></dt><dd>seaIce</dd><dt><span>source :</span></dt><dd>E3SM 1.0 (2018): \n",
+       "aerosol: MAM4 with resuspension, marine organics, and secondary organics (same grid as atmos)\n",
+       "atmos: EAM (v1.0, cubed sphere spectral-element grid; 5400 elements with p=3; 1 deg average grid spacing; 90 x 90 x 6 longitude/latitude/cubeface; 72 levels; top level 0.1 hPa)\n",
+       "atmosChem: Troposphere specified oxidants for aerosols. Stratosphere linearized interactive ozone (LINOZ v2) (same grid as atmos)\n",
+       "land: ELM (v1.0, cubed sphere spectral-element grid; 5400 elements with p=3; 1 deg average grid spacing; 90 x 90 x 6 longitude/latitude/cubeface; satellite phenology mode), MOSART (v1.0, 0.5 degree latitude/longitude grid)\n",
+       "landIce: none\n",
+       "ocean: MPAS-Ocean (v6.0, oEC60to30 unstructured SVTs mesh with 235160 cells and 714274 edges, variable resolution 60 km to 30 km; 60 levels; top grid cell 0-10 m)\n",
+       "ocnBgchem: none\n",
+       "seaIce: MPAS-Seaice (v6.0, same grid as ocean)</dd><dt><span>source_id :</span></dt><dd>E3SM-1-0</dd><dt><span>source_type :</span></dt><dd>AOGCM AER</dd><dt><span>sub_experiment :</span></dt><dd>none</dd><dt><span>sub_experiment_id :</span></dt><dd>none</dd><dt><span>table_id :</span></dt><dd>SImon</dd><dt><span>table_info :</span></dt><dd>Creation Date:(18 November 2020) MD5:926d66e1a62ce074375d24e09d01cc11</dd><dt><span>title :</span></dt><dd>E3SM-1-0 output prepared for CMIP6</dd><dt><span>tracking_id :</span></dt><dd>hdl:21.14100/695ad132-b79f-4393-a828-89c0647b31a8</dd><dt><span>variable_id :</span></dt><dd>siconc</dd><dt><span>variant_label :</span></dt><dd>r1i2p2f1</dd><dt><span>license :</span></dt><dd>CMIP6 model data produced by E3SM-Project is licensed under a Creative Commons Attribution 4.0 International License (https://creativecommons.org/licenses/by/4.0/). Consult https://pcmdi.llnl.gov/CMIP6/TermsOfUse for terms of use governing CMIP6 output, including citation requirements and proper acknowledgment. Further information about this data, including some limitations, can be found via the further_info_url (recorded as a global attribute in this file) and at https://pcmdi.llnl.gov/. The data producers and data providers make no warranty, either express or implied, including, but not limited to, warranties of merchantability and fitness for a particular purpose. All liabilities arising from the supply of the information (including any liability arising in negligence) are excluded to the fullest extent permitted by law.</dd><dt><span>cmor_version :</span></dt><dd>3.7.0</dd><dt><span>references :</span></dt><dd>Stevenson, S., Huang, X., Zhao, Y., Di Lorenzo, E., Newman, M., van Roekel, L., Xu, T., &amp; Capotondi, A. 2023: Ensemble Spread Behavior in Coupled Climate Models: Insights from the Energy Exascale Earth System Model version 1, JAMES</dd><dt><span>version :</span></dt><dd>v20230811</dd><dt><span>branch_time_in_parent :</span></dt><dd>3560.0</dd></dl></div></li></ul></div></div>"
+      ],
+      "text/plain": [
+       "<xarray.Dataset>\n",
+       "Dimensions:    (time: 1944, bnds: 2, lat: 180, lon: 360)\n",
+       "Coordinates:\n",
+       "  * lat        (lat) float64 -89.5 -88.5 -87.5 -86.5 ... 86.5 87.5 88.5 89.5\n",
+       "  * lon        (lon) float64 0.5 1.5 2.5 3.5 4.5 ... 356.5 357.5 358.5 359.5\n",
+       "    type       |S7 b'sea_ice'\n",
+       "  * time       (time) object 1850-01-16 12:00:00 ... 2011-12-16 12:00:00\n",
+       "Dimensions without coordinates: bnds\n",
+       "Data variables:\n",
+       "    time_bnds  (time, bnds) object dask.array<chunksize=(1, 2), meta=np.ndarray>\n",
+       "    lat_bnds   (lat, bnds) float64 dask.array<chunksize=(180, 2), meta=np.ndarray>\n",
+       "    lon_bnds   (lon, bnds) float64 dask.array<chunksize=(360, 2), meta=np.ndarray>\n",
+       "    siconc     (time, lat, lon) float32 dask.array<chunksize=(1, 180, 360), meta=np.ndarray>\n",
+       "    extent     (time) float32 dask.array<chunksize=(1,), meta=np.ndarray>\n",
+       "Attributes: (12/48)\n",
+       "    Conventions:            CF-1.7 CMIP-6.2\n",
+       "    activity_id:            CMIP\n",
+       "    branch_method:          standard\n",
+       "    branch_time_in_child:   0.0\n",
+       "    creation_date:          2023-01-30T21:36:30Z\n",
+       "    data contact:           Sam Stevenson (sstevenson@ucsb.edu)\n",
+       "    ...                     ...\n",
+       "    variant_label:          r1i2p2f1\n",
+       "    license:                CMIP6 model data produced by E3SM-Project is lice...\n",
+       "    cmor_version:           3.7.0\n",
+       "    references:             Stevenson, S., Huang, X., Zhao, Y., Di Lorenzo, E...\n",
+       "    version:                v20230811\n",
+       "    branch_time_in_parent:  3560.0"
+      ]
+     },
+     "execution_count": 19,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "ds"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## 3. Reference dataset\n",
+    "\n",
+    "The observational dataset provided is the satellite derived sea ice concentration dataset from EUMETSAT OSI-SAF. More data information can be found at the [osi-450-a product page](https://osi-saf.eumetsat.int/products/osi-450-a). The path to this data is:\n",
+    "```\n",
+    "/p/user_pub/pmp/demo/sea-ice/EUMETSAT\n",
+    "```"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 20,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "obs_file = \"/p/user_pub/pmp/demo/sea-ice/EUMETSAT/OSI-SAF-450-a-3-0/v20231201/ice_conc_nh_ease2-250_cdr-v3p0_198801-202012.nc\"\n",
+    "obs_ds = xc.open_dataset(obs_file)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 21,
+   "metadata": {},
+   "outputs": [
+    {
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+       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt;\n",
+       "Dimensions:                 (xc: 432, yc: 432, time: 396, nv: 2, bnds: 2)\n",
+       "Coordinates:\n",
+       "  * xc                      (xc) float64 -5.388e+03 -5.362e+03 ... 5.388e+03\n",
+       "  * yc                      (yc) float64 5.388e+03 5.362e+03 ... -5.388e+03\n",
+       "    lat                     (yc, xc) float32 16.62 16.82 17.02 ... 16.82 16.62\n",
+       "    lon                     (yc, xc) float32 -135.0 -135.1 -135.3 ... 44.87 45.0\n",
+       "  * time                    (time) object 1988-01-16 12:00:00 ... 2020-12-16 ...\n",
+       "Dimensions without coordinates: nv, bnds\n",
+       "Data variables:\n",
+       "    Lambert_Azimuthal_Grid  int32 ...\n",
+       "    ice_conc                (time, yc, xc) float64 ...\n",
+       "    raw_ice_conc_values     (time, yc, xc) float64 ...\n",
+       "    status_flag             (time, yc, xc) float32 ...\n",
+       "    time_bnds               (time, nv) object ...\n",
+       "    xc_bnds                 (xc, bnds) float64 ...\n",
+       "Attributes: (12/43)\n",
+       "    title:                     Monthly Sea Ice Concentration Climate Data Rec...\n",
+       "    summary:                   This climate data record of sea ice concentrat...\n",
+       "    topiccategory:             Oceans ClimatologyMeteorologyAtmosphere\n",
+       "    geospatial_lat_min:        16.62393\n",
+       "    geospatial_lat_max:        90.0\n",
+       "    geospatial_lon_min:        -180.0\n",
+       "    ...                        ...\n",
+       "    algorithm:                 SICCI3LF (19V, 37V, 37H)\n",
+       "    references:                Product User Manual v3 (2022),Algorithm Theore...\n",
+       "    contributor_name:          Thomas Lavergne,Atle Soerensen,Rasmus Tonboe,C...\n",
+       "    contributor_role:          PrincipalInvestigator,author,author,author,aut...\n",
+       "    source:                    FCDR of SMMR / SSMI / SSMIS Brightness Tempera...\n",
+       "    product_status:            released</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-48df0dcd-c62a-4b15-83b5-fe1816cbf01e' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-48df0dcd-c62a-4b15-83b5-fe1816cbf01e' 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'>xc</span>: 432</li><li><span class='xr-has-index'>yc</span>: 432</li><li><span class='xr-has-index'>time</span>: 396</li><li><span>nv</span>: 2</li><li><span>bnds</span>: 2</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-d21a2eec-df1e-47d3-98e5-f00d04994ac8' class='xr-section-summary-in' type='checkbox'  checked><label for='section-d21a2eec-df1e-47d3-98e5-f00d04994ac8' 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'>xc</span></div><div class='xr-var-dims'>(xc)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-5.388e+03 -5.362e+03 ... 5.388e+03</div><input id='attrs-a2d8a949-55f5-4980-b104-2d042a485e29' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a2d8a949-55f5-4980-b104-2d042a485e29' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ef40f4b1-a079-4da0-a1e7-fd3e98e6ed93' class='xr-var-data-in' type='checkbox'><label for='data-ef40f4b1-a079-4da0-a1e7-fd3e98e6ed93' 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>km</dd><dt><span>long_name :</span></dt><dd>x coordinate of projection (eastings)</dd><dt><span>standard_name :</span></dt><dd>projection_x_coordinate</dd><dt><span>bounds :</span></dt><dd>xc_bnds</dd></dl></div><div class='xr-var-data'><pre>array([-5387.5, -5362.5, -5337.5, ...,  5337.5,  5362.5,  5387.5])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>yc</span></div><div class='xr-var-dims'>(yc)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>5.388e+03 5.362e+03 ... -5.388e+03</div><input id='attrs-084a7bdf-1e89-420d-9c8c-a2e9da7608b7' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-084a7bdf-1e89-420d-9c8c-a2e9da7608b7' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d0734d43-d9ca-4f82-bf6c-c12a1d68f374' class='xr-var-data-in' type='checkbox'><label for='data-d0734d43-d9ca-4f82-bf6c-c12a1d68f374' 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>km</dd><dt><span>long_name :</span></dt><dd>y coordinate of projection (northings)</dd><dt><span>standard_name :</span></dt><dd>projection_y_coordinate</dd></dl></div><div class='xr-var-data'><pre>array([ 5387.5,  5362.5,  5337.5, ..., -5337.5, -5362.5, -5387.5])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lat</span></div><div class='xr-var-dims'>(yc, xc)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>16.62 16.82 17.02 ... 16.82 16.62</div><input id='attrs-a4aa91b3-3e71-46b8-b03a-5fcbcffb7d74' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a4aa91b3-3e71-46b8-b03a-5fcbcffb7d74' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c342bc59-ad20-440b-9f86-c00773af6838' class='xr-var-data-in' type='checkbox'><label for='data-c342bc59-ad20-440b-9f86-c00773af6838' 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 coordinate</dd><dt><span>standard_name :</span></dt><dd>latitude</dd></dl></div><div class='xr-var-data'><pre>array([[16.623926, 16.822655, 17.020658, ..., 17.020658, 16.822655, 16.623926],\n",
+       "       [16.822655, 17.021584, 17.219795, ..., 17.219795, 17.021584, 16.822655],\n",
+       "       [17.020658, 17.219795, 17.418213, ..., 17.418213, 17.219795, 17.020658],\n",
+       "       ...,\n",
+       "       [17.020658, 17.219795, 17.418213, ..., 17.418213, 17.219795, 17.020658],\n",
+       "       [16.822655, 17.021584, 17.219795, ..., 17.219795, 17.021584, 16.822655],\n",
+       "       [16.623926, 16.822655, 17.020658, ..., 17.020658, 16.822655, 16.623926]],\n",
+       "      dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lon</span></div><div class='xr-var-dims'>(yc, xc)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-135.0 -135.1 -135.3 ... 44.87 45.0</div><input id='attrs-9194e164-f4df-4970-b45c-4115dfa10620' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-9194e164-f4df-4970-b45c-4115dfa10620' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1c996b6d-4585-45f7-b329-63550338bc5e' class='xr-var-data-in' type='checkbox'><label for='data-1c996b6d-4585-45f7-b329-63550338bc5e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>long_name :</span></dt><dd>longitude coordinate</dd><dt><span>standard_name :</span></dt><dd>longitude</dd></dl></div><div class='xr-var-data'><pre>array([[-135.      , -135.13324 , -135.2671  , ...,  135.2671  ,  135.13324 ,\n",
+       "         135.      ],\n",
+       "       [-134.86676 , -135.      , -135.13387 , ...,  135.13387 ,  135.      ,\n",
+       "         134.86676 ],\n",
+       "       [-134.7329  , -134.86613 , -135.      , ...,  135.      ,  134.86613 ,\n",
+       "         134.7329  ],\n",
+       "       ...,\n",
+       "       [ -45.267113,  -45.13387 ,  -45.      , ...,   45.      ,   45.13387 ,\n",
+       "          45.267113],\n",
+       "       [ -45.133247,  -45.      ,  -44.86613 , ...,   44.86613 ,   45.      ,\n",
+       "          45.133247],\n",
+       "       [ -45.      ,  -44.866753,  -44.732887, ...,   44.732887,   44.866753,\n",
+       "          45.      ]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>1988-01-16 12:00:00 ... 2020-12-...</div><input id='attrs-a2a1b3c9-7c68-4fa3-97c5-11c9b2348c33' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a2a1b3c9-7c68-4fa3-97c5-11c9b2348c33' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-fe2838d6-de3f-4004-b53a-4f65fb23e6a5' class='xr-var-data-in' type='checkbox'><label for='data-fe2838d6-de3f-4004-b53a-4f65fb23e6a5' 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>reference time of product</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_bnds</dd></dl></div><div class='xr-var-data'><pre>array([cftime.DatetimeGregorian(1988, 1, 16, 12, 0, 0, 0, has_year_zero=False),\n",
+       "       cftime.DatetimeGregorian(1988, 2, 16, 12, 0, 0, 0, has_year_zero=False),\n",
+       "       cftime.DatetimeGregorian(1988, 3, 16, 12, 0, 0, 0, has_year_zero=False),\n",
+       "       ...,\n",
+       "       cftime.DatetimeGregorian(2020, 10, 16, 12, 0, 0, 0, has_year_zero=False),\n",
+       "       cftime.DatetimeGregorian(2020, 11, 16, 12, 0, 0, 0, has_year_zero=False),\n",
+       "       cftime.DatetimeGregorian(2020, 12, 16, 12, 0, 0, 0, has_year_zero=False)],\n",
+       "      dtype=object)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-a2c9ef97-35e5-4e54-b593-2e93d18f4ca3' class='xr-section-summary-in' type='checkbox'  checked><label for='section-a2c9ef97-35e5-4e54-b593-2e93d18f4ca3' 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>Lambert_Azimuthal_Grid</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>int32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-8b77ba0f-d9b6-4329-938a-543751e987fe' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-8b77ba0f-d9b6-4329-938a-543751e987fe' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0402b604-e19c-4425-960a-7dcce245c53e' class='xr-var-data-in' type='checkbox'><label for='data-0402b604-e19c-4425-960a-7dcce245c53e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>grid_mapping_name :</span></dt><dd>lambert_azimuthal_equal_area</dd><dt><span>longitude_of_projection_origin :</span></dt><dd>0.0</dd><dt><span>latitude_of_projection_origin :</span></dt><dd>90.0</dd><dt><span>false_easting :</span></dt><dd>0.0</dd><dt><span>false_northing :</span></dt><dd>0.0</dd><dt><span>semi_major_axis :</span></dt><dd>6378137.0</dd><dt><span>inverse_flattening :</span></dt><dd>298.257223563</dd><dt><span>proj4_string :</span></dt><dd>+proj=laea +lon_0=0 +datum=WGS84 +ellps=WGS84 +lat_0=90.0</dd></dl></div><div class='xr-var-data'><pre>[1 values with dtype=int32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>ice_conc</span></div><div class='xr-var-dims'>(time, yc, xc)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-d21a7953-f128-413f-a13a-5592c40f964b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d21a7953-f128-413f-a13a-5592c40f964b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-82f509a9-71b8-42cc-9826-56adddc3ce36' class='xr-var-data-in' type='checkbox'><label for='data-82f509a9-71b8-42cc-9826-56adddc3ce36' 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>fully filtered concentration of sea ice using atmospheric correction of brightness temperatures and open water filters</dd><dt><span>standard_name :</span></dt><dd>sea_ice_area_fraction</dd><dt><span>units :</span></dt><dd>%</dd><dt><span>valid_min :</span></dt><dd>0</dd><dt><span>valid_max :</span></dt><dd>10000</dd><dt><span>grid_mapping :</span></dt><dd>Lambert_Azimuthal_Grid</dd><dt><span>ancillary_variables :</span></dt><dd>total_standard_uncertainty status_flag</dd><dt><span>comment :</span></dt><dd>this field is the primary sea ice concentration estimate for this climate data record</dd></dl></div><div class='xr-var-data'><pre>[73903104 values with dtype=float64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>raw_ice_conc_values</span></div><div class='xr-var-dims'>(time, yc, xc)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-c484b46b-d3b1-4fa2-9754-acafc2c532dc' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-c484b46b-d3b1-4fa2-9754-acafc2c532dc' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9dd04f60-3f53-4be3-b04d-a32f3561ff91' class='xr-var-data-in' type='checkbox'><label for='data-9dd04f60-3f53-4be3-b04d-a32f3561ff91' 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>sea ice concentration estimates as retrieved by the algorithm, and that were edited away by the various filters</dd><dt><span>units :</span></dt><dd>%</dd><dt><span>grid_mapping :</span></dt><dd>Lambert_Azimuthal_Grid</dd><dt><span>comment :</span></dt><dd>this field can be used in combination with &#x27;ice_conc&#x27; to access un-bounded normal distribution of sea ice concentration estimates corresponding to the uncertainty estimate in &#x27;total_standard_uncertainty&#x27;. It does also feature some amount of un-physical data (below 0% and above 100%).</dd></dl></div><div class='xr-var-data'><pre>[73903104 values with dtype=float64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>status_flag</span></div><div class='xr-var-dims'>(time, yc, xc)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-a8f3211d-790e-4e25-be05-0ad09aa50936' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a8f3211d-790e-4e25-be05-0ad09aa50936' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d54b729f-ff4e-4e28-bc96-d55a55bc47fc' class='xr-var-data-in' type='checkbox'><label for='data-d54b729f-ff4e-4e28-bc96-d55a55bc47fc' 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>status flag bit array for sea ice concentration retrievals</dd><dt><span>standard_name :</span></dt><dd>sea_ice_area_fraction status_flag</dd><dt><span>valid_min :</span></dt><dd>0</dd><dt><span>valid_max :</span></dt><dd>32767</dd><dt><span>grid_mapping :</span></dt><dd>Lambert_Azimuthal_Grid</dd><dt><span>flag_masks :</span></dt><dd>[  1   2   4   8  16  32  64 128]</dd><dt><span>flag_meanings :</span></dt><dd>land lake open_water_filtered land_spill_over high_t2m spatial_interp temporal_interp max_ice_climo</dd><dt><span>flag_descriptions :</span></dt><dd>\n",
+       "all bits to 0 (flag 0): Nominal retrieval by the SIC algorithm\n",
+       "bit 1 (flag 1): Position is over land\n",
+       "bit 2 (flag 2): Position is lake\n",
+       "bit 3 (flag 4): SIC is set to zero by the open water filter\n",
+       "bit 4 (flag 8): SIC value is changed for correcting land spill-over effects\n",
+       "bit 5 (flag 16): Handle with caution, the 2m air temperature is high at this position, and this might be false ice\n",
+       "bit 6 (flag 32): Value is the result of spatial interpolation\n",
+       "bit 7 (flag 64): Value is the result of temporal interpolation\n",
+       "bit 8 (flag 128): SIC is set to zero since position is outside maximum sea ice climatology.</dd><dt><span>comment :</span></dt><dd>Flag values found in the map might be combinations of those listed above. For example flag value 80 (= 2^4 + 2^6 = 16 + 64) indicates high_t2m AND temporal_interp</dd></dl></div><div class='xr-var-data'><pre>[73903104 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>time_bnds</span></div><div class='xr-var-dims'>(time, nv)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-e948553a-61b0-4a27-a428-8e299bc70717' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-e948553a-61b0-4a27-a428-8e299bc70717' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9aaea080-9829-4ec7-851e-84268b6ee6fa' class='xr-var-data-in' type='checkbox'><label for='data-9aaea080-9829-4ec7-851e-84268b6ee6fa' 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>[792 values with dtype=object]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>xc_bnds</span></div><div class='xr-var-dims'>(xc, bnds)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-c40076f1-8e70-43ed-86b3-c012e2ae06e9' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-c40076f1-8e70-43ed-86b3-c012e2ae06e9' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-dc5a0e46-7e2a-4be7-b2a0-f8579bcaf921' class='xr-var-data-in' type='checkbox'><label for='data-dc5a0e46-7e2a-4be7-b2a0-f8579bcaf921' 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>xcdat_bounds :</span></dt><dd>True</dd></dl></div><div class='xr-var-data'><pre>[864 values with dtype=float64]</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-da109816-e7ac-4c46-8ef8-64977d52c968' class='xr-section-summary-in' type='checkbox'  ><label for='section-da109816-e7ac-4c46-8ef8-64977d52c968' class='xr-section-summary' >Indexes: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>xc</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-268a51e9-8e20-4551-aafb-79ff2717f5a9' class='xr-index-data-in' type='checkbox'/><label for='index-268a51e9-8e20-4551-aafb-79ff2717f5a9' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([-5387.5, -5362.5, -5337.5, -5312.5, -5287.5, -5262.5, -5237.5, -5212.5,\n",
+       "       -5187.5, -5162.5,\n",
+       "       ...\n",
+       "        5162.5,  5187.5,  5212.5,  5237.5,  5262.5,  5287.5,  5312.5,  5337.5,\n",
+       "        5362.5,  5387.5],\n",
+       "      dtype=&#x27;float64&#x27;, name=&#x27;xc&#x27;, length=432))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>yc</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-cb2251a0-2a9c-431b-971b-56c6efcbd453' class='xr-index-data-in' type='checkbox'/><label for='index-cb2251a0-2a9c-431b-971b-56c6efcbd453' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Index([ 5387.5,  5362.5,  5337.5,  5312.5,  5287.5,  5262.5,  5237.5,  5212.5,\n",
+       "        5187.5,  5162.5,\n",
+       "       ...\n",
+       "       -5162.5, -5187.5, -5212.5, -5237.5, -5262.5, -5287.5, -5312.5, -5337.5,\n",
+       "       -5362.5, -5387.5],\n",
+       "      dtype=&#x27;float64&#x27;, name=&#x27;yc&#x27;, length=432))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>time</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-16112a12-86f8-4001-9fc3-22e6e7ed8e23' class='xr-index-data-in' type='checkbox'/><label for='index-16112a12-86f8-4001-9fc3-22e6e7ed8e23' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(CFTimeIndex([1988-01-16 12:00:00, 1988-02-16 12:00:00, 1988-03-16 12:00:00,\n",
+       "             1988-04-16 12:00:00, 1988-05-16 12:00:00, 1988-06-16 12:00:00,\n",
+       "             1988-07-16 12:00:00, 1988-08-16 12:00:00, 1988-09-16 12:00:00,\n",
+       "             1988-10-16 12:00:00,\n",
+       "             ...\n",
+       "             2020-03-16 12:00:00, 2020-04-16 12:00:00, 2020-05-16 12:00:00,\n",
+       "             2020-06-16 12:00:00, 2020-07-16 12:00:00, 2020-08-16 12:00:00,\n",
+       "             2020-09-16 12:00:00, 2020-10-16 12:00:00, 2020-11-16 12:00:00,\n",
+       "             2020-12-16 12:00:00],\n",
+       "            dtype=&#x27;object&#x27;, length=396, calendar=&#x27;standard&#x27;, freq=&#x27;None&#x27;))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-8bb8c042-43fd-4761-8998-c3ff5e0b5bb0' class='xr-section-summary-in' type='checkbox'  ><label for='section-8bb8c042-43fd-4761-8998-c3ff5e0b5bb0' class='xr-section-summary' >Attributes: <span>(43)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>title :</span></dt><dd>Monthly Sea Ice Concentration Climate Data Record Version 3 (SMMR, SSM/I, and SSMIS) from the EUMETSAT OSI SAF</dd><dt><span>summary :</span></dt><dd>This climate data record of sea ice concentration is obtained from coarse resolution passive microwave satellite data (SMMR, SSM/I, and SSMIS) over the polar regions (Arctic and Antarctic). The processing chain features: 1) dynamic tuning of tie-points and algorithms,  2) correction of atmospheric noise using a Radiative Transfer Model,  3) computation of per-pixel uncertainties, and 4) an optimal hybrid sea ice concentration algorithm. This dataset was generated by the EUMETSAT Ocean and Sea Ice Satellite Application Facility (OSI SAF). The ESA CCI Programme contributed with Research and Development on the algorithms.</dd><dt><span>topiccategory :</span></dt><dd>Oceans ClimatologyMeteorologyAtmosphere</dd><dt><span>geospatial_lat_min :</span></dt><dd>16.62393</dd><dt><span>geospatial_lat_max :</span></dt><dd>90.0</dd><dt><span>geospatial_lon_min :</span></dt><dd>-180.0</dd><dt><span>geospatial_lon_max :</span></dt><dd>180.0</dd><dt><span>geospatial_vertical_min :</span></dt><dd>0.0</dd><dt><span>geospatial_vertical_max :</span></dt><dd>0.0</dd><dt><span>sensor :</span></dt><dd>SMMR,SSM/I,SSMIS</dd><dt><span>platform :</span></dt><dd>Nimbus-7,DMSP-F&lt;08,10,11,13,14,15&gt;,DMSP-F&lt;16,17,18&gt;</dd><dt><span>time_coverage_start :</span></dt><dd>1978-11-01T00:00:00Z</dd><dt><span>time_coverage_end :</span></dt><dd>1978-12-01T00:00:00Z</dd><dt><span>time_coverage_duration :</span></dt><dd>P1M</dd><dt><span>time_coverage_resolution :</span></dt><dd>P1M</dd><dt><span>project :</span></dt><dd>OSI SAF - EUMETSAT</dd><dt><span>institution :</span></dt><dd>OSISAF - EUMETSAT</dd><dt><span>creator_name :</span></dt><dd>OSISAF - EUMETSAT</dd><dt><span>creator_type :</span></dt><dd>institution</dd><dt><span>creator_url :</span></dt><dd>https://osi-saf.eumetsat.int/</dd><dt><span>creator_email :</span></dt><dd>osi-saf.helpdesk@meteo.fr</dd><dt><span>license :</span></dt><dd>All intellectual property rights of the Ocean and Sea Ice SAF products belong to EUMETSAT. The use of these products is granted to every user, free of charge. If users wish to use these products, EUMETSAT&#x27;s copyright credit must be shown by displaying the words &#x27;Copyright EUMETSAT&#x27; under each of the products shown. EUMETSAT offers no warranty and accepts no liability in respect of the Ocean and Sea Ice SAF products. EUMETSAT neither commits to nor guarantees the continuity, availability, or quality or suitability for any purpose of, the Ocean and Sea Ice SAF products.</dd><dt><span>history :</span></dt><dd>2023-03-20T12:29:37Z creation</dd><dt><span>date_created :</span></dt><dd>2023-03-20</dd><dt><span>cdm_data_type :</span></dt><dd>Grid</dd><dt><span>spatial_resolution :</span></dt><dd>25.0 km grid spacing</dd><dt><span>geospatial_bounds_crs :</span></dt><dd>EPSG:6931</dd><dt><span>product_version :</span></dt><dd>3.0</dd><dt><span>tracking_id :</span></dt><dd>2d0c7fd8-c092-4cff-9409-421010ba4167</dd><dt><span>naming_authority :</span></dt><dd>int.eumetsat</dd><dt><span>standard_name_vocabulary :</span></dt><dd>CF Standard Name Table (Version 78, 21 September 2021)</dd><dt><span>product_id :</span></dt><dd>osi-450-a</dd><dt><span>product_name :</span></dt><dd>osi_saf_sea_ice_conc_climate_data_record_smmrssmissmis</dd><dt><span>doi :</span></dt><dd>10.15770/EUM_SAF_OSI_0013</dd><dt><span>keywords :</span></dt><dd>GCMDSK:Earth Science &gt; Cryosphere &gt; Sea Ice &gt; Sea Ice Concentration, GCMDSK:Earth Science &gt; Oceans &gt; Sea Ice &gt; Sea Ice Concentration, GCMDSK:Earth Science &gt; Climate Indicators &gt; Cryospheric Indicators &gt; Sea Ice Concentration, GCMDLOC:Geographic Region &gt; Northern Hemisphere, GCMDLOC:Vertical Location &gt; Sea Surface, GCMDPROV: Government Agencies-non-US &gt; Norway &gt; NO/MET &gt; Norwegian Meteorological Institute</dd><dt><span>keywords_vocabulary :</span></dt><dd>GCMDSK:GCMD Science Keywords:https://gcmd.earthdata.nasa.gov/kms/concepts/concept_scheme/sciencekeywords, GCMDPROV:GCMD Providers:https://gcmd.earthdata.nasa.gov/kms/concepts/concept_scheme/providers, GCMDLOC:GCMD Locations:https://gcmd.earthdata.nasa.gov/kms/concepts/concept_scheme/locations</dd><dt><span>Conventions :</span></dt><dd>CF-1.7,ACDD-1.3</dd><dt><span>algorithm :</span></dt><dd>SICCI3LF (19V, 37V, 37H)</dd><dt><span>references :</span></dt><dd>Product User Manual v3 (2022),Algorithm Theoretical Basis Document v3 (2022),Validation Report v3 (2022),https://osi-saf.eumetsat.int/products/osi-450-a</dd><dt><span>contributor_name :</span></dt><dd>Thomas Lavergne,Atle Soerensen,Rasmus Tonboe,Courtenay Strong,Matilde Kreiner,Roberto Saldo,Anton Birkedal,Fabrizio Baordo,Trygve Aspenes,Steinar Eastwood</dd><dt><span>contributor_role :</span></dt><dd>PrincipalInvestigator,author,author,author,author,author,author,author,author,author</dd><dt><span>source :</span></dt><dd>FCDR of SMMR / SSMI / SSMIS Brightness Temperatures R4 from EUMETSAT Climate Monitoring SAF (doi:10.5676/EUM_SAF_CM/FCDR_MWI/V004), ERA5</dd><dt><span>product_status :</span></dt><dd>released</dd></dl></div></li></ul></div></div>"
+      ],
+      "text/plain": [
+       "<xarray.Dataset>\n",
+       "Dimensions:                 (xc: 432, yc: 432, time: 396, nv: 2, bnds: 2)\n",
+       "Coordinates:\n",
+       "  * xc                      (xc) float64 -5.388e+03 -5.362e+03 ... 5.388e+03\n",
+       "  * yc                      (yc) float64 5.388e+03 5.362e+03 ... -5.388e+03\n",
+       "    lat                     (yc, xc) float32 16.62 16.82 17.02 ... 16.82 16.62\n",
+       "    lon                     (yc, xc) float32 -135.0 -135.1 -135.3 ... 44.87 45.0\n",
+       "  * time                    (time) object 1988-01-16 12:00:00 ... 2020-12-16 ...\n",
+       "Dimensions without coordinates: nv, bnds\n",
+       "Data variables:\n",
+       "    Lambert_Azimuthal_Grid  int32 ...\n",
+       "    ice_conc                (time, yc, xc) float64 ...\n",
+       "    raw_ice_conc_values     (time, yc, xc) float64 ...\n",
+       "    status_flag             (time, yc, xc) float32 ...\n",
+       "    time_bnds               (time, nv) object ...\n",
+       "    xc_bnds                 (xc, bnds) float64 ...\n",
+       "Attributes: (12/43)\n",
+       "    title:                     Monthly Sea Ice Concentration Climate Data Rec...\n",
+       "    summary:                   This climate data record of sea ice concentrat...\n",
+       "    topiccategory:             Oceans ClimatologyMeteorologyAtmosphere\n",
+       "    geospatial_lat_min:        16.62393\n",
+       "    geospatial_lat_max:        90.0\n",
+       "    geospatial_lon_min:        -180.0\n",
+       "    ...                        ...\n",
+       "    algorithm:                 SICCI3LF (19V, 37V, 37H)\n",
+       "    references:                Product User Manual v3 (2022),Algorithm Theore...\n",
+       "    contributor_name:          Thomas Lavergne,Atle Soerensen,Rasmus Tonboe,C...\n",
+       "    contributor_role:          PrincipalInvestigator,author,author,author,aut...\n",
+       "    source:                    FCDR of SMMR / SSMI / SSMIS Brightness Tempera...\n",
+       "    product_status:            released"
+      ]
+     },
+     "execution_count": 21,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "obs_ds"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 22,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "obs_area = 625\n",
+    "obs_sea_ice_extent = (obs_ds.ice_conc.where(obs_ds.lat > 0).where(obs_ds.ice_conc > 15) * 1e-2 * obs_area).sum((\"xc\", \"yc\"))"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Note for the above lines\n",
+    "- obs_area = 625  # area size represented by each grid (625 km^2 = 25 km x 25 km resolution)\n",
+    "- where ice_conc > 15: to consider sea ice extent instead of total sea ice area\n",
+    "- multiply 1e-2: to convert percentage (%) to fraction"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 23,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "[<matplotlib.lines.Line2D at 0x7f29542f33d0>]"
+      ]
+     },
+     "execution_count": 23,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "obs_sea_ice_extent.plot()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Let's add the `obs_arctic` dataArray to the dataset (`obs_ds`) for later use:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 24,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "obs_ds[\"extent\"] = obs_sea_ice_extent"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## 4. Analysis: get climatology\n",
+    "\n",
+    "We will use [xCDAT](https://xcdat.readthedocs.io)'s [`temporal.climatology`](https://xcdat.readthedocs.io/en/latest/generated/xarray.Dataset.temporal.climatology.html) capability to get climatology field. "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 25,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "obs_ds_clim = obs_ds.temporal.climatology(\n",
+    "    \"extent\", freq=\"month\", reference_period=(\"1981-01-01\", \"2010-12-31\"))\n",
+    "\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 26,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "ds_clim = ds.temporal.climatology(\n",
+    "    \"extent\", freq=\"month\", reference_period=(\"1981-01-01\", \"2010-12-31\"))\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 27,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<matplotlib.legend.Legend at 0x7f294074fb50>"
+      ]
+     },
+     "execution_count": 27,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "fig, ax = plt.subplots()\n",
+    "\n",
+    "# Unify the time axis to plot lines on a same figure\n",
+    "ds_clim[\"time\"] = [x for x in range(1, 13)]\n",
+    "obs_ds_clim[\"time\"] = [x for x in range(1, 13)]\n",
+    "\n",
+    "# Add lines\n",
+    "ds_clim[\"extent\"].plot(ax=ax, label=\"Model (E3SM-1-0)\")\n",
+    "obs_ds_clim[\"extent\"].plot(ax=ax, label=\"OBS (OSI-SAF)\")\n",
+    "\n",
+    "# Attach legend\n",
+    "plt.title(\"Arctic climatological sea ice extent\\n1981-2010\")\n",
+    "plt.xlabel(\"month\")\n",
+    "plt.ylabel(\"Extent (km${^2}$)\")\n",
+    "plt.legend(loc=\"upper right\", fontsize=9)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "[Optional] Interactive line plot example can be found [here](https://hvplot.holoviz.org/user_guide/Gridded_Data.html#d-plots)."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 28,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {},
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "application/vnd.holoviews_exec.v0+json": "",
+      "text/html": [
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+       "</div>\n",
+       "<script type=\"application/javascript\">(function(root) {\n",
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+       "  var render_items = [{\"docid\":\"01cc8e2a-e074-41f1-90e2-57b7578c381e\",\"roots\":{\"p1655\":\"b0e7ad6b-6807-40e4-bdd3-daaa033a5b5d\"},\"root_ids\":[\"p1655\"]}];\n",
+       "  var docs = Object.values(docs_json)\n",
+       "  if (!docs) {\n",
+       "    return\n",
+       "  }\n",
+       "  const py_version = docs[0].version.replace('rc', '-rc.').replace('.dev', '-dev.')\n",
+       "  function embed_document(root) {\n",
+       "    var Bokeh = get_bokeh(root)\n",
+       "    Bokeh.embed.embed_items_notebook(docs_json, render_items);\n",
+       "    for (const render_item of render_items) {\n",
+       "      for (const root_id of render_item.root_ids) {\n",
+       "\tconst id_el = document.getElementById(root_id)\n",
+       "\tif (id_el.children.length && (id_el.children[0].className === 'bk-root')) {\n",
+       "\t  const root_el = id_el.children[0]\n",
+       "\t  root_el.id = root_el.id + '-rendered'\n",
+       "\t}\n",
+       "      }\n",
+       "    }\n",
+       "  }\n",
+       "  function get_bokeh(root) {\n",
+       "    if (root.Bokeh === undefined) {\n",
+       "      return null\n",
+       "    } else if (root.Bokeh.version !== py_version) {\n",
+       "      if (root.Bokeh.versions === undefined || !root.Bokeh.versions.has(py_version)) {\n",
+       "\treturn null\n",
+       "      }\n",
+       "      return root.Bokeh.versions.get(py_version);\n",
+       "    } else if (root.Bokeh.version === py_version) {\n",
+       "      return root.Bokeh\n",
+       "    }\n",
+       "    return null\n",
+       "  }\n",
+       "  function is_loaded(root) {\n",
+       "    var Bokeh = get_bokeh(root)\n",
+       "    return (Bokeh != null && Bokeh.Panel !== undefined)\n",
+       "  }\n",
+       "  if (is_loaded(root)) {\n",
+       "    embed_document(root);\n",
+       "  } else {\n",
+       "    var attempts = 0;\n",
+       "    var timer = setInterval(function(root) {\n",
+       "      if (is_loaded(root)) {\n",
+       "        clearInterval(timer);\n",
+       "        embed_document(root);\n",
+       "      } else if (document.readyState == \"complete\") {\n",
+       "        attempts++;\n",
+       "        if (attempts > 200) {\n",
+       "          clearInterval(timer);\n",
+       "\t  var Bokeh = get_bokeh(root)\n",
+       "\t  if (Bokeh == null || Bokeh.Panel == null) {\n",
+       "            console.warn(\"Panel: ERROR: Unable to run Panel code because Bokeh or Panel library is missing\");\n",
+       "\t  } else {\n",
+       "\t    console.warn(\"Panel: WARNING: Attempting to render but not all required libraries could be resolved.\")\n",
+       "\t    embed_document(root)\n",
+       "\t  }\n",
+       "        }\n",
+       "      }\n",
+       "    }, 25, root)\n",
+       "  }\n",
+       "})(window);</script>"
+      ],
+      "text/plain": [
+       ":Overlay\n",
+       "   .Curve.Model :Curve   [time]   (extent)\n",
+       "   .Curve.OBS   :Curve   [time]   (extent)"
+      ]
+     },
+     "execution_count": 28,
+     "metadata": {
+      "application/vnd.holoviews_exec.v0+json": {
+       "id": "p1655"
+      }
+     },
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "ds_clim[\"extent\"].hvplot(label=\"Model\") * obs_ds_clim[\"extent\"].hvplot(label=\"OBS\")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## 4. Evaluation Metrics\n",
+    "\n",
+    "The term \"Metric\" indicates a score or statistics that can represent model's performance on reproducing the observed features. It can be defined in many different ways, but the primary purpose of metrics is to summarize the performances of many different models and provide a framework for the benchmarking.\n",
+    "\n",
+    "In this notebook, we define **Mean Square Error (MSE)** and **Temporal MSE** as metrics.\n",
+    "\n",
+    "### 4.1 Mean Square Error (Annual Mean)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 29,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "mse = (ds_clim[\"extent\"].data.mean() - obs_ds_clim[\"extent\"].data.mean()) ** 2 * 1e-12"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 30,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Mean Square Error: 1.9092291476097731 10^12 km^4\n"
+     ]
+    }
+   ],
+   "source": [
+    "print(f\"Mean Square Error: {float(mse)} 10^12 km^4\")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### 4.2 Temporal Mean Square Error (Annual Cycle)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 31,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "tmse = np.sum(((ds_clim[\"extent\"].data - obs_ds_clim[\"extent\"].data) ** 2)) / len(ds_clim[\"extent\"]) * 1e-12"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 32,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Temporal Mean Square Error: 3.808760315117328 10^12 km^4\n"
+     ]
+    }
+   ],
+   "source": [
+    "print(f\"Temporal Mean Square Error: {float(tmse)} 10^12 km^4\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "pcmdi_metrics_dev_20231129",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.10.10"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}
diff --git a/doc/jupyter/Demo/sea_ice_line_plots.py b/doc/jupyter/Demo/sea_ice_line_plots.py
index c3c01132a..df61cb795 100644
--- a/doc/jupyter/Demo/sea_ice_line_plots.py
+++ b/doc/jupyter/Demo/sea_ice_line_plots.py
@@ -3,6 +3,8 @@
 import xarray as xr
 import xcdat as xc
 
+# Load data -- model
+
 ds = xc.open_mfdataset(
     "/p/user_pub/pmp/demo/sea-ice/links_siconc/E3SM-1-0/historical/r1i2p2f1/siconc/siconc_SImon_E3SM-1-0_historical_r1i2p2f1_*_*.nc"
 )
@@ -10,15 +12,35 @@
     "/p/user_pub/pmp/demo/sea-ice/links_area/E3SM-1-0/areacello_Ofx_E3SM-1-0_historical_r1i1p1f1_gr.nc"
 )
 
-arctic = (ds.where(ds.lat > 0) * 1e-2 * area.areacello * 1e-6).sum(("lat", "lon"))
+arctic = (
+    (ds.siconc.where(ds.lat > 0) * 1e-2 * area.areacello * 1e-6)
+    .where(ds.siconc > 15)
+    .sum(("lat", "lon"))
+)
+"""
+Note for the above line
+- where siconc > 15: to consider sea ice extent instead of total sea ice area (criteria: 15%)
+- multiply 1e-2: to convert percentage (%) to fraction
+"""
+
+# Load data -- observation
 
-f_os_n = "/p/user_pub/pmp/demo/sea-ice/EUMETSAT/OSI-SAF-450-a-3-0/v20231201/ice_conc_nh_ease2-250_cdr-v3p0_198801-202012.nc"
-obs = xc.open_dataset(f_os_n)
+obs_file = "/p/user_pub/pmp/demo/sea-ice/EUMETSAT/OSI-SAF-450-a-3-0/v20231201/ice_conc_nh_ease2-250_cdr-v3p0_198801-202012.nc"
+obs = xc.open_dataset(obs_file)
 obs_area = 625
-obs_arctic = (obs.ice_conc.where(obs.lat > 0) * 1e-2 * obs_area).sum(("xc", "yc"))
+obs_arctic = (
+    obs.ice_conc.where(obs.lat > 0).where(obs.ice_conc > 15) * 1e-2 * obs_area
+).sum(("xc", "yc"))
+"""
+Note for the above lines
+- obs_area = 625  # area size represented by each grid (625 km^2 = 25 km x 25 km resolution)
+- where siconc > 15: to consider sea ice extent instead of total sea ice area (criteria: 15%)
+- multiply 1e-2: to convert percentage (%) to fraction
+"""
+
 
 # Time series plot
-arctic.siconc.sel({"time": slice("1981-01-01", "2010-12-31")}).plot(label="E3SM-1-0")
+arctic.sel({"time": slice("1981-01-01", "2010-12-31")}).plot(label="E3SM-1-0")
 obs_arctic.plot(label="OSI-SAF")
 plt.title("Arctic monthly sea ice extent")
 plt.ylabel("Extent (km${^2}$)")
@@ -35,7 +57,7 @@
 
 # Climatology plot
 arctic_ds = xr.Dataset(
-    data_vars={"siconc": arctic.siconc, "time_bnds": ds.time_bnds},
+    data_vars={"siconc": arctic, "time_bnds": ds.time_bnds},
     coords={"time": ds.time},
 )
 arctic_clim = arctic_ds.sel(
diff --git a/doc/jupyter/Demo/sea_ice_sector_plots.py b/doc/jupyter/Demo/sea_ice_sector_plots.py
index d9f65b790..053ef0d41 100644
--- a/doc/jupyter/Demo/sea_ice_sector_plots.py
+++ b/doc/jupyter/Demo/sea_ice_sector_plots.py
@@ -12,8 +12,8 @@
 # ----------
 print("Creating Arctic map")
 # Load and process data
-f_os_n = "/p/user_pub/pmp/demo/sea-ice/EUMETSAT/OSI-SAF-450-a-3-0/v20231201/ice_conc_nh_ease2-250_cdr-v3p0_198801-202012.nc"
-obs = xc.open_dataset(f_os_n)
+obs_file = "/p/user_pub/pmp/demo/sea-ice/EUMETSAT/OSI-SAF-450-a-3-0/v20231201/ice_conc_nh_ease2-250_cdr-v3p0_198801-202012.nc"
+obs = xc.open_dataset(obs_file)
 obs = obs.mean("time")
 mask = create_land_sea_mask(obs, lon_key="lon", lat_key="lat")
 obs["ice_conc"] = obs["ice_conc"].where(mask < 1)