2023.02.16_AK temperature.ipynb

{
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"
    }
   },
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Alaska Berry Futures\n",
    "### Temperature change over time\n",
    "\n",
    "**Author: Lindsey V. Parkinson    \n",
    "Date: May 19, 2023 **   \n",
    "\n",
    "\n",
    "Using SNAP temperature models to investigate temperature thresholds for flowering and growth across Alaska   \n",
    "http://data.snap.uaf.edu/data/Base/Other/Community_charts_tool_database/    \n",
    "https://catalog.snap.uaf.edu/geonetwork/srv/eng/catalog.search#/metadata/b3b9581e-cccc-440f-bb2f-0fd6754d8d41    \n",
    "\n",
    "Lowbush cranberry fruitset goes down when temperatures in the flowering period exceed 25 C. The optimum is about 15-20 C during the flowering period. In figure 6 we say 15-24.9 C is termed \"ideal\" \n",
    "\n",
    "![grafik.png](attachment:88b22f07-b8eb-45c2-8539-d3ddf90b36c8.png)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import os\n",
    "import numpy as np\n",
    "\n",
    "import geopandas as gpd\n",
    "from shapely.geometry import Point\n",
    "\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [],
   "source": [
    "#pip install --upgrade pyopenssl\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "working_directory = os.getcwd()\n",
    "\n",
    "all_temp_data =  pd.read_csv(working_directory + \"\\\\SNAP_Community_Climate_Charts_Data_20230313.csv\", skiprows=4)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "AK_temp = all_temp_data[(all_temp_data['country']==\"US\")&\n",
    "              (all_temp_data['type']=='Temperature')&\n",
    "              (all_temp_data['scenario'].isin(['rcp85','prism']))].copy() #Also rcp45 and rcp85 available"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\LindseyParkinson\\anaconda3\\lib\\site-packages\\pyproj\\crs\\crs.py:141: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  in_crs_string = _prepare_from_proj_string(in_crs_string)\n",
      "C:\\Users\\LindseyParkinson\\anaconda3\\lib\\site-packages\\IPython\\core\\interactiveshell.py:3338: FutureWarning: The `op` parameter is deprecated and will be removed in a future release. Please use the `predicate` parameter instead.\n",
      "  if (await self.run_code(code, result,  async_=asy)):\n"
     ]
    }
   ],
   "source": [
    "\n",
    "# Specify the CRS of the alaska_ecoregions shapefile\n",
    "crs = {'init': 'epsg:3338'}\n",
    "\n",
    "# Load the shapefile into a GeoDataFrame and set the CRS\n",
    "alaska_ecoregions = gpd.read_file(working_directory + '\\\\UnifiedEcoregionsAlaska2001\\\\akecoregions-ShapeFile\\\\akecoregions.shp', crs=crs)\n",
    "alaska_ecoregions = alaska_ecoregions.set_crs(epsg=3338)\n",
    "\n",
    "\n",
    "# Perform a spatial join between the two dataframes based on the latitude and longitude columns\n",
    "communities = AK_temp[['community', 'latitude', 'longitude']]\n",
    "\n",
    "# convert the latitude and longitude coordinates to a Point object\n",
    "geometry = [Point(xy) for xy in zip(AK_temp.longitude, AK_temp.latitude)]\n",
    "communities = communities.drop(['longitude', 'latitude'], axis=1)\n",
    "crs = {'init': 'epsg:4326'}\n",
    "geo_df = gpd.GeoDataFrame(communities, crs=crs, geometry=geometry)\n",
    "\n",
    "# Reproject the alaska_ecoregions GeoDataFrame to the same CRS as the communities GeoDataFrame\n",
    "alaska_ecoregions = alaska_ecoregions.to_crs(crs)\n",
    "\n",
    "# Perform the spatial join between the two GeoDataFrames\n",
    "joined_df = gpd.sjoin(geo_df, alaska_ecoregions, how=\"left\", op=\"within\")\n",
    "\n",
    "AK_temp = pd.merge(AK_temp, joined_df[['community','LEVEL_2']], on='community', how='left')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['Coastal Rainforests', 'Bering Taiga', 'Aleutian Meadows',\n",
       "       'Intermontane Boreal', nan, 'Alaska Range Transition',\n",
       "       'Arctic Tundra', 'Bering Tundra', 'Coast Mountains Transition',\n",
       "       'Pacific Mountains Transition'], dtype=object)"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "joined_df['LEVEL_2'].unique()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Mean monthly temp"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [],
   "source": [
    "columns_to_drop = [col for col in AK_temp.columns if 'Min' in col or 'Max' in col]\n",
    "AK_temp_mean = AK_temp.drop(columns_to_drop, axis=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "# Convert the relevant columns to numeric data type\n",
    "numeric_columns = ['janMean', 'febMean', 'marMean', 'aprMean', 'mayMean', 'junMean', 'julMean', 'augMean', 'sepMean', 'octMean', 'novMean', 'decMean']\n",
    "\n",
    "AK_temp_mean[numeric_columns] = AK_temp_mean[numeric_columns].apply(pd.to_numeric, errors='coerce')\n",
    "\n",
    "# Group by 'LEVEL_2' and 'daterange' - find mean of regional means\n",
    "regional_temp_mean = AK_temp_mean.groupby(['LEVEL_2', 'daterange'])[numeric_columns].mean()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {
    "collapsed": true,
    "jupyter": {
     "outputs_hidden": true
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[14.025000000000015,\n",
       " 15.52115384615385,\n",
       " 17.284615384615396,\n",
       " 11.27884615384614,\n",
       " 10.278378378378378,\n",
       " 11.718918918918915,\n",
       " 13.03513513513515,\n",
       " 8.243243243243224,\n",
       " 7.6333333333333355,\n",
       " 9.133333333333333,\n",
       " 10.806666666666668,\n",
       " 5.42,\n",
       " 12.17790697674416,\n",
       " 13.763953488372099,\n",
       " 15.09302325581394,\n",
       " 9.84651162790698,\n",
       " 9.520689655172408,\n",
       " 11.313793103448278,\n",
       " 12.489655172413798,\n",
       " 6.989655172413799,\n",
       " 13.699999999999998,\n",
       " 15.199999999999996,\n",
       " 17.166666666666664,\n",
       " 11.166666666666666,\n",
       " 13.275324675324674,\n",
       " 14.615584415584394,\n",
       " 16.096103896103898,\n",
       " 10.979220779220778,\n",
       " 16.195744680851064,\n",
       " 17.67659574468084,\n",
       " 19.12021276595746,\n",
       " 13.731914893617018,\n",
       " 15.01538461538462,\n",
       " 16.661538461538473,\n",
       " 18.43846153846154,\n",
       " 11.838461538461532]"
      ]
     },
     "execution_count": 49,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#VACVIT flowers in June\n",
    "regional_temp_mean['junMean'].to_list()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Max monthly temp"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {},
   "outputs": [],
   "source": [
    "columns_to_drop = [col for col in AK_temp.columns if 'Min' in col or 'Mean' in col]\n",
    "AK_temp_max = AK_temp.drop(columns_to_drop, axis=1)\n",
    "\n",
    "# Convert the relevant columns to numeric data type\n",
    "numeric_columns = ['janMax', 'febMax', 'marMax', 'aprMax', 'mayMax', 'junMax', 'julMax', 'augMax', 'sepMax', 'octMax', 'novMax', 'decMax']\n",
    "\n",
    "AK_temp_max[numeric_columns] = AK_temp_max[numeric_columns].apply(pd.to_numeric, errors='coerce')\n",
    "\n",
    "# Group by 'LEVEL_2' and 'daterange' - find mean of regional max temps\n",
    "regional_temp_max = AK_temp_max.groupby(['LEVEL_2', 'daterange'])[numeric_columns].mean()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {
    "collapsed": true,
    "jupyter": {
     "outputs_hidden": true
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[20.180769230769215,\n",
       " 22.25961538461542,\n",
       " 22.64615384615384,\n",
       " nan,\n",
       " 12.862162162162162,\n",
       " 14.821621621621615,\n",
       " 15.932432432432435,\n",
       " nan,\n",
       " 12.993333333333327,\n",
       " 15.82666666666666,\n",
       " 16.879999999999992,\n",
       " nan,\n",
       " 17.43837209302324,\n",
       " 19.852325581395345,\n",
       " 20.074418604651147,\n",
       " nan,\n",
       " 14.203448275862065,\n",
       " 17.13103448275863,\n",
       " 17.268965517241377,\n",
       " nan,\n",
       " 19.133333333333336,\n",
       " 22.63333333333333,\n",
       " 23.166666666666668,\n",
       " nan,\n",
       " 17.820779220779237,\n",
       " 20.4792207792208,\n",
       " 20.987012987012985,\n",
       " nan,\n",
       " 23.080851063829744,\n",
       " 25.340425531914885,\n",
       " 25.50531914893617,\n",
       " nan,\n",
       " 21.500000000000004,\n",
       " 24.25384615384617,\n",
       " 24.307692307692317,\n",
       " nan]"
      ]
     },
     "execution_count": 48,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#VACVIT flowers in June\n",
    "regional_temp_max['junMax'].to_list()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Min monthly temp"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "columns_to_drop = [col for col in AK_temp.columns if 'Max' in col or 'Mean' in col]\n",
    "AK_temp_min = AK_temp.drop(columns_to_drop, axis=1)\n",
    "\n",
    "# Convert the relevant columns to numeric data type\n",
    "numeric_columns = ['janMin', 'febMin', 'marMin', 'aprMin', 'mayMin', 'junMin', 'julMin', 'augMin', 'sepMin', 'octMin', 'novMin', 'decMin']\n",
    "\n",
    "AK_temp_min[numeric_columns] = AK_temp_min[numeric_columns].apply(pd.to_numeric, errors='coerce')\n",
    "\n",
    "# Group by 'LEVEL_2' and 'daterange' - find mean of regional max temps\n",
    "regional_temp_min = AK_temp_min.groupby(['LEVEL_2', 'daterange'])[numeric_columns].mean()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "collapsed": true,
    "jupyter": {
     "outputs_hidden": true
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[8.634615384615378,\n",
       " 10.636538461538466,\n",
       " 11.555769230769219,\n",
       " nan,\n",
       " 7.53783783783783,\n",
       " 9.686486486486492,\n",
       " 10.575675675675683,\n",
       " nan,\n",
       " 2.7266666666666675,\n",
       " 3.9933333333333323,\n",
       " 5.266666666666669,\n",
       " nan,\n",
       " 7.711627906976739,\n",
       " 9.336046511627908,\n",
       " 9.89302325581394,\n",
       " nan,\n",
       " 5.537931034482756,\n",
       " 7.165517241379309,\n",
       " 8.006896551724136,\n",
       " nan,\n",
       " 8.366666666666665,\n",
       " 10.266666666666666,\n",
       " 12.066666666666668,\n",
       " nan,\n",
       " 8.8974025974026,\n",
       " 10.866233766233764,\n",
       " 12.20909090909091,\n",
       " nan,\n",
       " 9.593617021276605,\n",
       " 10.749999999999991,\n",
       " 11.790425531914881,\n",
       " nan,\n",
       " 8.93846153846154,\n",
       " 10.869230769230768,\n",
       " 12.753846153846151,\n",
       " nan]"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#VACVIT flowers in June\n",
    "regional_temp_min['junMin'].to_list()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th>janMin</th>\n",
       "      <th>febMin</th>\n",
       "      <th>marMin</th>\n",
       "      <th>aprMin</th>\n",
       "      <th>mayMin</th>\n",
       "      <th>junMin</th>\n",
       "      <th>julMin</th>\n",
       "      <th>augMin</th>\n",
       "      <th>sepMin</th>\n",
       "      <th>octMin</th>\n",
       "      <th>novMin</th>\n",
       "      <th>decMin</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>LEVEL_2</th>\n",
       "      <th>daterange</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th rowspan=\"4\" valign=\"top\">Alaska Range Transition</th>\n",
       "      <th>2030-2039</th>\n",
       "      <td>-17.557692</td>\n",
       "      <td>-16.559615</td>\n",
       "      <td>-11.126923</td>\n",
       "      <td>-4.453846</td>\n",
       "      <td>3.269231</td>\n",
       "      <td>8.634615</td>\n",
       "      <td>10.753846</td>\n",
       "      <td>9.438462</td>\n",
       "      <td>5.269231</td>\n",
       "      <td>-3.550000</td>\n",
       "      <td>-13.344231</td>\n",
       "      <td>-16.034615</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2060-2069</th>\n",
       "      <td>-15.694231</td>\n",
       "      <td>-10.678846</td>\n",
       "      <td>-7.044231</td>\n",
       "      <td>-0.869231</td>\n",
       "      <td>5.257692</td>\n",
       "      <td>10.636538</td>\n",
       "      <td>12.638462</td>\n",
       "      <td>11.538462</td>\n",
       "      <td>6.515385</td>\n",
       "      <td>-1.771154</td>\n",
       "      <td>-7.821154</td>\n",
       "      <td>-13.696154</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2090-2099</th>\n",
       "      <td>-9.482692</td>\n",
       "      <td>-8.069231</td>\n",
       "      <td>-4.338462</td>\n",
       "      <td>1.251923</td>\n",
       "      <td>7.150000</td>\n",
       "      <td>11.555769</td>\n",
       "      <td>13.673077</td>\n",
       "      <td>12.561538</td>\n",
       "      <td>8.696154</td>\n",
       "      <td>-0.551923</td>\n",
       "      <td>-7.315385</td>\n",
       "      <td>-9.963462</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Historical</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"4\" valign=\"top\">Aleutian Meadows</th>\n",
       "      <th>2030-2039</th>\n",
       "      <td>-3.981081</td>\n",
       "      <td>-4.970270</td>\n",
       "      <td>-2.351351</td>\n",
       "      <td>0.164865</td>\n",
       "      <td>4.143243</td>\n",
       "      <td>7.537838</td>\n",
       "      <td>10.564865</td>\n",
       "      <td>11.227027</td>\n",
       "      <td>8.616216</td>\n",
       "      <td>3.867568</td>\n",
       "      <td>-0.416216</td>\n",
       "      <td>-2.305405</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2060-2069</th>\n",
       "      <td>-2.575676</td>\n",
       "      <td>-1.872973</td>\n",
       "      <td>-0.656757</td>\n",
       "      <td>2.191892</td>\n",
       "      <td>5.905405</td>\n",
       "      <td>9.686486</td>\n",
       "      <td>12.513514</td>\n",
       "      <td>13.229730</td>\n",
       "      <td>10.137838</td>\n",
       "      <td>5.113514</td>\n",
       "      <td>1.729730</td>\n",
       "      <td>-0.567568</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2090-2099</th>\n",
       "      <td>0.591892</td>\n",
       "      <td>0.213514</td>\n",
       "      <td>1.451351</td>\n",
       "      <td>3.800000</td>\n",
       "      <td>7.097297</td>\n",
       "      <td>10.575676</td>\n",
       "      <td>13.794595</td>\n",
       "      <td>14.535135</td>\n",
       "      <td>12.021622</td>\n",
       "      <td>6.472973</td>\n",
       "      <td>3.259459</td>\n",
       "      <td>1.651351</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Historical</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"4\" valign=\"top\">Arctic Tundra</th>\n",
       "      <th>2030-2039</th>\n",
       "      <td>-29.820000</td>\n",
       "      <td>-30.706667</td>\n",
       "      <td>-29.393333</td>\n",
       "      <td>-22.093333</td>\n",
       "      <td>-8.500000</td>\n",
       "      <td>2.726667</td>\n",
       "      <td>6.786667</td>\n",
       "      <td>5.633333</td>\n",
       "      <td>0.300000</td>\n",
       "      <td>-10.120000</td>\n",
       "      <td>-18.066667</td>\n",
       "      <td>-24.293333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2060-2069</th>\n",
       "      <td>-22.473333</td>\n",
       "      <td>-25.066667</td>\n",
       "      <td>-23.933333</td>\n",
       "      <td>-15.840000</td>\n",
       "      <td>-4.933333</td>\n",
       "      <td>3.993333</td>\n",
       "      <td>9.340000</td>\n",
       "      <td>8.140000</td>\n",
       "      <td>3.086667</td>\n",
       "      <td>-5.933333</td>\n",
       "      <td>-11.206667</td>\n",
       "      <td>-18.313333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2090-2099</th>\n",
       "      <td>-16.333333</td>\n",
       "      <td>-21.053333</td>\n",
       "      <td>-19.446667</td>\n",
       "      <td>-12.173333</td>\n",
       "      <td>-3.000000</td>\n",
       "      <td>5.266667</td>\n",
       "      <td>10.126667</td>\n",
       "      <td>10.173333</td>\n",
       "      <td>4.733333</td>\n",
       "      <td>-3.800000</td>\n",
       "      <td>-9.686667</td>\n",
       "      <td>-14.313333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Historical</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"4\" valign=\"top\">Bering Taiga</th>\n",
       "      <th>2030-2039</th>\n",
       "      <td>-17.126744</td>\n",
       "      <td>-17.088372</td>\n",
       "      <td>-13.117442</td>\n",
       "      <td>-8.012791</td>\n",
       "      <td>1.309302</td>\n",
       "      <td>7.711628</td>\n",
       "      <td>10.503488</td>\n",
       "      <td>10.054651</td>\n",
       "      <td>6.343023</td>\n",
       "      <td>-1.693023</td>\n",
       "      <td>-9.343023</td>\n",
       "      <td>-13.322093</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2060-2069</th>\n",
       "      <td>-13.888372</td>\n",
       "      <td>-11.863953</td>\n",
       "      <td>-9.552326</td>\n",
       "      <td>-3.544186</td>\n",
       "      <td>3.638372</td>\n",
       "      <td>9.336047</td>\n",
       "      <td>12.365116</td>\n",
       "      <td>11.976744</td>\n",
       "      <td>7.626744</td>\n",
       "      <td>-0.506977</td>\n",
       "      <td>-5.434884</td>\n",
       "      <td>-11.967442</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2090-2099</th>\n",
       "      <td>-7.450000</td>\n",
       "      <td>-8.526744</td>\n",
       "      <td>-6.327907</td>\n",
       "      <td>-1.409302</td>\n",
       "      <td>4.819767</td>\n",
       "      <td>9.893023</td>\n",
       "      <td>14.101163</td>\n",
       "      <td>13.423256</td>\n",
       "      <td>9.919767</td>\n",
       "      <td>1.374419</td>\n",
       "      <td>-4.191860</td>\n",
       "      <td>-7.650000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Historical</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"4\" valign=\"top\">Bering Tundra</th>\n",
       "      <th>2030-2039</th>\n",
       "      <td>-18.651724</td>\n",
       "      <td>-20.306897</td>\n",
       "      <td>-19.906897</td>\n",
       "      <td>-14.348276</td>\n",
       "      <td>-2.003448</td>\n",
       "      <td>5.537931</td>\n",
       "      <td>9.441379</td>\n",
       "      <td>9.106897</td>\n",
       "      <td>5.034483</td>\n",
       "      <td>-2.486207</td>\n",
       "      <td>-8.644828</td>\n",
       "      <td>-14.375862</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2060-2069</th>\n",
       "      <td>-12.303448</td>\n",
       "      <td>-16.210345</td>\n",
       "      <td>-15.144828</td>\n",
       "      <td>-8.241379</td>\n",
       "      <td>0.848276</td>\n",
       "      <td>7.165517</td>\n",
       "      <td>10.927586</td>\n",
       "      <td>10.910345</td>\n",
       "      <td>6.689655</td>\n",
       "      <td>-0.427586</td>\n",
       "      <td>-5.231034</td>\n",
       "      <td>-9.844828</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2090-2099</th>\n",
       "      <td>-7.234483</td>\n",
       "      <td>-12.368966</td>\n",
       "      <td>-11.341379</td>\n",
       "      <td>-6.034483</td>\n",
       "      <td>2.289655</td>\n",
       "      <td>8.006897</td>\n",
       "      <td>12.541379</td>\n",
       "      <td>12.644828</td>\n",
       "      <td>8.689655</td>\n",
       "      <td>1.365517</td>\n",
       "      <td>-3.579310</td>\n",
       "      <td>-7.044828</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Historical</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"4\" valign=\"top\">Coast Mountains Transition</th>\n",
       "      <th>2030-2039</th>\n",
       "      <td>-26.066667</td>\n",
       "      <td>-22.133333</td>\n",
       "      <td>-15.200000</td>\n",
       "      <td>-6.066667</td>\n",
       "      <td>1.933333</td>\n",
       "      <td>8.366667</td>\n",
       "      <td>10.133333</td>\n",
       "      <td>8.833333</td>\n",
       "      <td>2.633333</td>\n",
       "      <td>-8.866667</td>\n",
       "      <td>-19.966667</td>\n",
       "      <td>-24.566667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2060-2069</th>\n",
       "      <td>-24.733333</td>\n",
       "      <td>-17.500000</td>\n",
       "      <td>-11.000000</td>\n",
       "      <td>-3.133333</td>\n",
       "      <td>4.033333</td>\n",
       "      <td>10.266667</td>\n",
       "      <td>12.400000</td>\n",
       "      <td>10.933333</td>\n",
       "      <td>4.200000</td>\n",
       "      <td>-5.833333</td>\n",
       "      <td>-15.033333</td>\n",
       "      <td>-22.566667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2090-2099</th>\n",
       "      <td>-19.266667</td>\n",
       "      <td>-16.666667</td>\n",
       "      <td>-8.400000</td>\n",
       "      <td>-1.300000</td>\n",
       "      <td>5.200000</td>\n",
       "      <td>12.066667</td>\n",
       "      <td>13.200000</td>\n",
       "      <td>11.633333</td>\n",
       "      <td>6.566667</td>\n",
       "      <td>-3.600000</td>\n",
       "      <td>-14.700000</td>\n",
       "      <td>-18.933333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Historical</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"4\" valign=\"top\">Coastal Rainforests</th>\n",
       "      <th>2030-2039</th>\n",
       "      <td>-8.262338</td>\n",
       "      <td>-7.333766</td>\n",
       "      <td>-3.989610</td>\n",
       "      <td>0.666234</td>\n",
       "      <td>5.312987</td>\n",
       "      <td>8.897403</td>\n",
       "      <td>11.594805</td>\n",
       "      <td>11.607792</td>\n",
       "      <td>8.087013</td>\n",
       "      <td>2.294805</td>\n",
       "      <td>-3.601299</td>\n",
       "      <td>-6.200000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2060-2069</th>\n",
       "      <td>-7.070130</td>\n",
       "      <td>-2.075325</td>\n",
       "      <td>-1.416883</td>\n",
       "      <td>2.815584</td>\n",
       "      <td>7.080519</td>\n",
       "      <td>10.866234</td>\n",
       "      <td>13.166234</td>\n",
       "      <td>13.114286</td>\n",
       "      <td>9.274026</td>\n",
       "      <td>4.149351</td>\n",
       "      <td>-0.222078</td>\n",
       "      <td>-4.642857</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2090-2099</th>\n",
       "      <td>-2.279221</td>\n",
       "      <td>-1.235065</td>\n",
       "      <td>0.862338</td>\n",
       "      <td>4.384416</td>\n",
       "      <td>8.600000</td>\n",
       "      <td>12.209091</td>\n",
       "      <td>14.571429</td>\n",
       "      <td>14.231169</td>\n",
       "      <td>11.444156</td>\n",
       "      <td>5.420779</td>\n",
       "      <td>0.393506</td>\n",
       "      <td>-1.237662</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Historical</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"4\" valign=\"top\">Intermontane Boreal</th>\n",
       "      <th>2030-2039</th>\n",
       "      <td>-29.302128</td>\n",
       "      <td>-26.758511</td>\n",
       "      <td>-20.389362</td>\n",
       "      <td>-9.457447</td>\n",
       "      <td>1.695745</td>\n",
       "      <td>9.593617</td>\n",
       "      <td>11.532979</td>\n",
       "      <td>8.870213</td>\n",
       "      <td>3.406383</td>\n",
       "      <td>-8.357447</td>\n",
       "      <td>-20.569149</td>\n",
       "      <td>-25.120213</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2060-2069</th>\n",
       "      <td>-25.704255</td>\n",
       "      <td>-20.656383</td>\n",
       "      <td>-14.770213</td>\n",
       "      <td>-5.371277</td>\n",
       "      <td>4.263830</td>\n",
       "      <td>10.750000</td>\n",
       "      <td>13.711702</td>\n",
       "      <td>11.274468</td>\n",
       "      <td>4.937234</td>\n",
       "      <td>-6.113830</td>\n",
       "      <td>-14.814894</td>\n",
       "      <td>-24.010638</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2090-2099</th>\n",
       "      <td>-19.889362</td>\n",
       "      <td>-18.336170</td>\n",
       "      <td>-11.809574</td>\n",
       "      <td>-2.825532</td>\n",
       "      <td>5.488298</td>\n",
       "      <td>11.790426</td>\n",
       "      <td>14.479787</td>\n",
       "      <td>12.619149</td>\n",
       "      <td>7.126596</td>\n",
       "      <td>-4.500000</td>\n",
       "      <td>-13.600000</td>\n",
       "      <td>-20.330851</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Historical</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"4\" valign=\"top\">Pacific Mountains Transition</th>\n",
       "      <th>2030-2039</th>\n",
       "      <td>-27.800000</td>\n",
       "      <td>-22.869231</td>\n",
       "      <td>-15.907692</td>\n",
       "      <td>-6.430769</td>\n",
       "      <td>2.161538</td>\n",
       "      <td>8.938462</td>\n",
       "      <td>10.930769</td>\n",
       "      <td>8.892308</td>\n",
       "      <td>3.284615</td>\n",
       "      <td>-7.338462</td>\n",
       "      <td>-21.084615</td>\n",
       "      <td>-25.400000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2060-2069</th>\n",
       "      <td>-26.069231</td>\n",
       "      <td>-18.069231</td>\n",
       "      <td>-11.830769</td>\n",
       "      <td>-3.230769</td>\n",
       "      <td>3.915385</td>\n",
       "      <td>10.869231</td>\n",
       "      <td>13.092308</td>\n",
       "      <td>10.930769</td>\n",
       "      <td>4.930769</td>\n",
       "      <td>-5.000000</td>\n",
       "      <td>-15.184615</td>\n",
       "      <td>-23.446154</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2090-2099</th>\n",
       "      <td>-20.646154</td>\n",
       "      <td>-16.769231</td>\n",
       "      <td>-9.369231</td>\n",
       "      <td>-1.100000</td>\n",
       "      <td>5.700000</td>\n",
       "      <td>12.753846</td>\n",
       "      <td>13.792308</td>\n",
       "      <td>11.692308</td>\n",
       "      <td>7.184615</td>\n",
       "      <td>-2.953846</td>\n",
       "      <td>-14.592308</td>\n",
       "      <td>-19.861538</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Historical</th>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                            janMin     febMin     marMin  \\\n",
       "LEVEL_2                      daterange                                     \n",
       "Alaska Range Transition      2030-2039  -17.557692 -16.559615 -11.126923   \n",
       "                             2060-2069  -15.694231 -10.678846  -7.044231   \n",
       "                             2090-2099   -9.482692  -8.069231  -4.338462   \n",
       "                             Historical        NaN        NaN        NaN   \n",
       "Aleutian Meadows             2030-2039   -3.981081  -4.970270  -2.351351   \n",
       "                             2060-2069   -2.575676  -1.872973  -0.656757   \n",
       "                             2090-2099    0.591892   0.213514   1.451351   \n",
       "                             Historical        NaN        NaN        NaN   \n",
       "Arctic Tundra                2030-2039  -29.820000 -30.706667 -29.393333   \n",
       "                             2060-2069  -22.473333 -25.066667 -23.933333   \n",
       "                             2090-2099  -16.333333 -21.053333 -19.446667   \n",
       "                             Historical        NaN        NaN        NaN   \n",
       "Bering Taiga                 2030-2039  -17.126744 -17.088372 -13.117442   \n",
       "                             2060-2069  -13.888372 -11.863953  -9.552326   \n",
       "                             2090-2099   -7.450000  -8.526744  -6.327907   \n",
       "                             Historical        NaN        NaN        NaN   \n",
       "Bering Tundra                2030-2039  -18.651724 -20.306897 -19.906897   \n",
       "                             2060-2069  -12.303448 -16.210345 -15.144828   \n",
       "                             2090-2099   -7.234483 -12.368966 -11.341379   \n",
       "                             Historical        NaN        NaN        NaN   \n",
       "Coast Mountains Transition   2030-2039  -26.066667 -22.133333 -15.200000   \n",
       "                             2060-2069  -24.733333 -17.500000 -11.000000   \n",
       "                             2090-2099  -19.266667 -16.666667  -8.400000   \n",
       "                             Historical        NaN        NaN        NaN   \n",
       "Coastal Rainforests          2030-2039   -8.262338  -7.333766  -3.989610   \n",
       "                             2060-2069   -7.070130  -2.075325  -1.416883   \n",
       "                             2090-2099   -2.279221  -1.235065   0.862338   \n",
       "                             Historical        NaN        NaN        NaN   \n",
       "Intermontane Boreal          2030-2039  -29.302128 -26.758511 -20.389362   \n",
       "                             2060-2069  -25.704255 -20.656383 -14.770213   \n",
       "                             2090-2099  -19.889362 -18.336170 -11.809574   \n",
       "                             Historical        NaN        NaN        NaN   \n",
       "Pacific Mountains Transition 2030-2039  -27.800000 -22.869231 -15.907692   \n",
       "                             2060-2069  -26.069231 -18.069231 -11.830769   \n",
       "                             2090-2099  -20.646154 -16.769231  -9.369231   \n",
       "                             Historical        NaN        NaN        NaN   \n",
       "\n",
       "                                            aprMin    mayMin     junMin  \\\n",
       "LEVEL_2                      daterange                                    \n",
       "Alaska Range Transition      2030-2039   -4.453846  3.269231   8.634615   \n",
       "                             2060-2069   -0.869231  5.257692  10.636538   \n",
       "                             2090-2099    1.251923  7.150000  11.555769   \n",
       "                             Historical        NaN       NaN        NaN   \n",
       "Aleutian Meadows             2030-2039    0.164865  4.143243   7.537838   \n",
       "                             2060-2069    2.191892  5.905405   9.686486   \n",
       "                             2090-2099    3.800000  7.097297  10.575676   \n",
       "                             Historical        NaN       NaN        NaN   \n",
       "Arctic Tundra                2030-2039  -22.093333 -8.500000   2.726667   \n",
       "                             2060-2069  -15.840000 -4.933333   3.993333   \n",
       "                             2090-2099  -12.173333 -3.000000   5.266667   \n",
       "                             Historical        NaN       NaN        NaN   \n",
       "Bering Taiga                 2030-2039   -8.012791  1.309302   7.711628   \n",
       "                             2060-2069   -3.544186  3.638372   9.336047   \n",
       "                             2090-2099   -1.409302  4.819767   9.893023   \n",
       "                             Historical        NaN       NaN        NaN   \n",
       "Bering Tundra                2030-2039  -14.348276 -2.003448   5.537931   \n",
       "                             2060-2069   -8.241379  0.848276   7.165517   \n",
       "                             2090-2099   -6.034483  2.289655   8.006897   \n",
       "                             Historical        NaN       NaN        NaN   \n",
       "Coast Mountains Transition   2030-2039   -6.066667  1.933333   8.366667   \n",
       "                             2060-2069   -3.133333  4.033333  10.266667   \n",
       "                             2090-2099   -1.300000  5.200000  12.066667   \n",
       "                             Historical        NaN       NaN        NaN   \n",
       "Coastal Rainforests          2030-2039    0.666234  5.312987   8.897403   \n",
       "                             2060-2069    2.815584  7.080519  10.866234   \n",
       "                             2090-2099    4.384416  8.600000  12.209091   \n",
       "                             Historical        NaN       NaN        NaN   \n",
       "Intermontane Boreal          2030-2039   -9.457447  1.695745   9.593617   \n",
       "                             2060-2069   -5.371277  4.263830  10.750000   \n",
       "                             2090-2099   -2.825532  5.488298  11.790426   \n",
       "                             Historical        NaN       NaN        NaN   \n",
       "Pacific Mountains Transition 2030-2039   -6.430769  2.161538   8.938462   \n",
       "                             2060-2069   -3.230769  3.915385  10.869231   \n",
       "                             2090-2099   -1.100000  5.700000  12.753846   \n",
       "                             Historical        NaN       NaN        NaN   \n",
       "\n",
       "                                            julMin     augMin     sepMin  \\\n",
       "LEVEL_2                      daterange                                     \n",
       "Alaska Range Transition      2030-2039   10.753846   9.438462   5.269231   \n",
       "                             2060-2069   12.638462  11.538462   6.515385   \n",
       "                             2090-2099   13.673077  12.561538   8.696154   \n",
       "                             Historical        NaN        NaN        NaN   \n",
       "Aleutian Meadows             2030-2039   10.564865  11.227027   8.616216   \n",
       "                             2060-2069   12.513514  13.229730  10.137838   \n",
       "                             2090-2099   13.794595  14.535135  12.021622   \n",
       "                             Historical        NaN        NaN        NaN   \n",
       "Arctic Tundra                2030-2039    6.786667   5.633333   0.300000   \n",
       "                             2060-2069    9.340000   8.140000   3.086667   \n",
       "                             2090-2099   10.126667  10.173333   4.733333   \n",
       "                             Historical        NaN        NaN        NaN   \n",
       "Bering Taiga                 2030-2039   10.503488  10.054651   6.343023   \n",
       "                             2060-2069   12.365116  11.976744   7.626744   \n",
       "                             2090-2099   14.101163  13.423256   9.919767   \n",
       "                             Historical        NaN        NaN        NaN   \n",
       "Bering Tundra                2030-2039    9.441379   9.106897   5.034483   \n",
       "                             2060-2069   10.927586  10.910345   6.689655   \n",
       "                             2090-2099   12.541379  12.644828   8.689655   \n",
       "                             Historical        NaN        NaN        NaN   \n",
       "Coast Mountains Transition   2030-2039   10.133333   8.833333   2.633333   \n",
       "                             2060-2069   12.400000  10.933333   4.200000   \n",
       "                             2090-2099   13.200000  11.633333   6.566667   \n",
       "                             Historical        NaN        NaN        NaN   \n",
       "Coastal Rainforests          2030-2039   11.594805  11.607792   8.087013   \n",
       "                             2060-2069   13.166234  13.114286   9.274026   \n",
       "                             2090-2099   14.571429  14.231169  11.444156   \n",
       "                             Historical        NaN        NaN        NaN   \n",
       "Intermontane Boreal          2030-2039   11.532979   8.870213   3.406383   \n",
       "                             2060-2069   13.711702  11.274468   4.937234   \n",
       "                             2090-2099   14.479787  12.619149   7.126596   \n",
       "                             Historical        NaN        NaN        NaN   \n",
       "Pacific Mountains Transition 2030-2039   10.930769   8.892308   3.284615   \n",
       "                             2060-2069   13.092308  10.930769   4.930769   \n",
       "                             2090-2099   13.792308  11.692308   7.184615   \n",
       "                             Historical        NaN        NaN        NaN   \n",
       "\n",
       "                                            octMin     novMin     decMin  \n",
       "LEVEL_2                      daterange                                    \n",
       "Alaska Range Transition      2030-2039   -3.550000 -13.344231 -16.034615  \n",
       "                             2060-2069   -1.771154  -7.821154 -13.696154  \n",
       "                             2090-2099   -0.551923  -7.315385  -9.963462  \n",
       "                             Historical        NaN        NaN        NaN  \n",
       "Aleutian Meadows             2030-2039    3.867568  -0.416216  -2.305405  \n",
       "                             2060-2069    5.113514   1.729730  -0.567568  \n",
       "                             2090-2099    6.472973   3.259459   1.651351  \n",
       "                             Historical        NaN        NaN        NaN  \n",
       "Arctic Tundra                2030-2039  -10.120000 -18.066667 -24.293333  \n",
       "                             2060-2069   -5.933333 -11.206667 -18.313333  \n",
       "                             2090-2099   -3.800000  -9.686667 -14.313333  \n",
       "                             Historical        NaN        NaN        NaN  \n",
       "Bering Taiga                 2030-2039   -1.693023  -9.343023 -13.322093  \n",
       "                             2060-2069   -0.506977  -5.434884 -11.967442  \n",
       "                             2090-2099    1.374419  -4.191860  -7.650000  \n",
       "                             Historical        NaN        NaN        NaN  \n",
       "Bering Tundra                2030-2039   -2.486207  -8.644828 -14.375862  \n",
       "                             2060-2069   -0.427586  -5.231034  -9.844828  \n",
       "                             2090-2099    1.365517  -3.579310  -7.044828  \n",
       "                             Historical        NaN        NaN        NaN  \n",
       "Coast Mountains Transition   2030-2039   -8.866667 -19.966667 -24.566667  \n",
       "                             2060-2069   -5.833333 -15.033333 -22.566667  \n",
       "                             2090-2099   -3.600000 -14.700000 -18.933333  \n",
       "                             Historical        NaN        NaN        NaN  \n",
       "Coastal Rainforests          2030-2039    2.294805  -3.601299  -6.200000  \n",
       "                             2060-2069    4.149351  -0.222078  -4.642857  \n",
       "                             2090-2099    5.420779   0.393506  -1.237662  \n",
       "                             Historical        NaN        NaN        NaN  \n",
       "Intermontane Boreal          2030-2039   -8.357447 -20.569149 -25.120213  \n",
       "                             2060-2069   -6.113830 -14.814894 -24.010638  \n",
       "                             2090-2099   -4.500000 -13.600000 -20.330851  \n",
       "                             Historical        NaN        NaN        NaN  \n",
       "Pacific Mountains Transition 2030-2039   -7.338462 -21.084615 -25.400000  \n",
       "                             2060-2069   -5.000000 -15.184615 -23.446154  \n",
       "                             2090-2099   -2.953846 -14.592308 -19.861538  \n",
       "                             Historical        NaN        NaN        NaN  "
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "regional_temp_min"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Melt and visualize"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "# reshape the data using melt\n",
    "df = pd.melt(regional_temp_min.reset_index(), id_vars=['LEVEL_2', 'daterange'], var_name='month', value_name='temperature')\n",
    "\n",
    "# rename the columns\n",
    "df = df.rename(columns={'month': 'month_name'})\n",
    "\n",
    "# remove the 'Mean' part from the month names\n",
    "df['month_name'] = df['month_name'].str.replace('Min', '')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>LEVEL_2</th>\n",
       "      <th>daterange</th>\n",
       "      <th>month_name</th>\n",
       "      <th>temperature</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Alaska Range Transition</td>\n",
       "      <td>2030-2039</td>\n",
       "      <td>jan</td>\n",
       "      <td>-17.557692</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>Alaska Range Transition</td>\n",
       "      <td>2060-2069</td>\n",
       "      <td>jan</td>\n",
       "      <td>-15.694231</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Alaska Range Transition</td>\n",
       "      <td>2090-2099</td>\n",
       "      <td>jan</td>\n",
       "      <td>-9.482692</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>Alaska Range Transition</td>\n",
       "      <td>Historical</td>\n",
       "      <td>jan</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Aleutian Meadows</td>\n",
       "      <td>2030-2039</td>\n",
       "      <td>jan</td>\n",
       "      <td>-3.981081</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>427</th>\n",
       "      <td>Intermontane Boreal</td>\n",
       "      <td>Historical</td>\n",
       "      <td>dec</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>428</th>\n",
       "      <td>Pacific Mountains Transition</td>\n",
       "      <td>2030-2039</td>\n",
       "      <td>dec</td>\n",
       "      <td>-25.400000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>429</th>\n",
       "      <td>Pacific Mountains Transition</td>\n",
       "      <td>2060-2069</td>\n",
       "      <td>dec</td>\n",
       "      <td>-23.446154</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>430</th>\n",
       "      <td>Pacific Mountains Transition</td>\n",
       "      <td>2090-2099</td>\n",
       "      <td>dec</td>\n",
       "      <td>-19.861538</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>431</th>\n",
       "      <td>Pacific Mountains Transition</td>\n",
       "      <td>Historical</td>\n",
       "      <td>dec</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>432 rows × 4 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                          LEVEL_2   daterange month_name  temperature\n",
       "0         Alaska Range Transition   2030-2039        jan   -17.557692\n",
       "1         Alaska Range Transition   2060-2069        jan   -15.694231\n",
       "2         Alaska Range Transition   2090-2099        jan    -9.482692\n",
       "3         Alaska Range Transition  Historical        jan          NaN\n",
       "4                Aleutian Meadows   2030-2039        jan    -3.981081\n",
       "..                            ...         ...        ...          ...\n",
       "427           Intermontane Boreal  Historical        dec          NaN\n",
       "428  Pacific Mountains Transition   2030-2039        dec   -25.400000\n",
       "429  Pacific Mountains Transition   2060-2069        dec   -23.446154\n",
       "430  Pacific Mountains Transition   2090-2099        dec   -19.861538\n",
       "431  Pacific Mountains Transition  Historical        dec          NaN\n",
       "\n",
       "[432 rows x 4 columns]"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "#df.to_excel(\"alaska_regional_temp_predictions_melt.xlsx\", index=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "Interior = df[df['LEVEL_2']=='Intermontane Boreal'].copy()\n",
    "\n",
    "# specify the order of daterange levels\n",
    "daterange_order = ['Historical', '2030-2039', '2060-2069', '2090-2099']\n",
    "\n",
    "# create the bar plot with the specified order of daterange levels\n",
    "sns.barplot(data=Interior, x=\"month_name\", y=\"temperature\", hue=\"daterange\", palette=\"gist_earth\", hue_order=daterange_order)\n",
    "plt.title(\"Min temp in Interior Alaska\")\n",
    "plt.savefig(\"interior_precipitation.png\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Historical Data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [],
   "source": [
    "historical_temp =  pd.read_csv(working_directory + \"\\\\Historic Climate Data for AK Communities and Regions_Predicting Percent Days Above 18, 20, 25C - AK communities climate data.csv\")\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "metadata": {},
   "outputs": [],
   "source": [
    "historical_temp_june = historical_temp[historical_temp['Month']==6].copy()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "metadata": {},
   "outputs": [],
   "source": [
    "historical_temp_june.groupby(['NAME','Year'])['TMAX>=20'].sum()#.to_csv('AK_historical_temp_june_max20.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "metadata": {},
   "outputs": [],
   "source": [
    "historical_temp_june.groupby(['NAME','Year'])['TMAX>=25'].sum()#.to_csv('AK_historical_temp_june_max25.csv')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### min temps"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [],
   "source": [
    "historical_temp_june_july = historical_temp[historical_temp['Month']==6|7].copy()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [],
   "source": [
    "historical_temp_june_july.groupby(['NAME','Year'])['TMIN<=-3.5'].sum()#.to_csv('AK_historical_temp_june_july_min3.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
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       "<style scoped>\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>STATION</th>\n",
       "      <th>NAME</th>\n",
       "      <th>DATE</th>\n",
       "      <th>Month</th>\n",
       "      <th>Year</th>\n",
       "      <th>PRCP</th>\n",
       "      <th>SNOW</th>\n",
       "      <th>SNWD</th>\n",
       "      <th>TMAX</th>\n",
       "      <th>TMIN</th>\n",
       "      <th>TMEAN</th>\n",
       "      <th>TMEAN&gt;=18</th>\n",
       "      <th>TMEAN&gt;=20</th>\n",
       "      <th>TMEAN&gt;=25</th>\n",
       "      <th>TMAX&gt;=20</th>\n",
       "      <th>TMAX&gt;=25</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>181</th>\n",
       "      <td>USW00027502</td>\n",
       "      <td>BARROW AIRPORT, AK US</td>\n",
       "      <td>7/1/1930</td>\n",
       "      <td>7</td>\n",
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       "      <td>0.0</td>\n",
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       "    <tr>\n",
       "      <th>182</th>\n",
       "      <td>USW00027502</td>\n",
       "      <td>BARROW AIRPORT, AK US</td>\n",
       "      <td>7/2/1930</td>\n",
       "      <td>7</td>\n",
       "      <td>1930</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>10.0</td>\n",
       "      <td>2.8</td>\n",
       "      <td>6.40</td>\n",
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       "      <td>0</td>\n",
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       "    <tr>\n",
       "      <th>183</th>\n",
       "      <td>USW00027502</td>\n",
       "      <td>BARROW AIRPORT, AK US</td>\n",
       "      <td>7/3/1930</td>\n",
       "      <td>7</td>\n",
       "      <td>1930</td>\n",
       "      <td>2.3</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>6.1</td>\n",
       "      <td>1.1</td>\n",
       "      <td>3.60</td>\n",
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       "      <th>184</th>\n",
       "      <td>USW00027502</td>\n",
       "      <td>BARROW AIRPORT, AK US</td>\n",
       "      <td>7/4/1930</td>\n",
       "      <td>7</td>\n",
       "      <td>1930</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>5.6</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2.80</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
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       "    <tr>\n",
       "      <th>185</th>\n",
       "      <td>USW00027502</td>\n",
       "      <td>BARROW AIRPORT, AK US</td>\n",
       "      <td>7/5/1930</td>\n",
       "      <td>7</td>\n",
       "      <td>1930</td>\n",
       "      <td>6.6</td>\n",
       "      <td>0.0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>13.3</td>\n",
       "      <td>1.1</td>\n",
       "      <td>7.20</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
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       "    <tr>\n",
       "      <th>172494</th>\n",
       "      <td>USW00026442</td>\n",
       "      <td>VALDEZ WEATHER SERVICE OFFICE, AK US</td>\n",
       "      <td>7/27/2013</td>\n",
       "      <td>7</td>\n",
       "      <td>2013</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>22.2</td>\n",
       "      <td>12.2</td>\n",
       "      <td>17.20</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
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       "      <td>1</td>\n",
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       "    <tr>\n",
       "      <th>172495</th>\n",
       "      <td>USW00026442</td>\n",
       "      <td>VALDEZ WEATHER SERVICE OFFICE, AK US</td>\n",
       "      <td>7/28/2013</td>\n",
       "      <td>7</td>\n",
       "      <td>2013</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>23.3</td>\n",
       "      <td>10.0</td>\n",
       "      <td>16.65</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
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       "    <tr>\n",
       "      <th>172496</th>\n",
       "      <td>USW00026442</td>\n",
       "      <td>VALDEZ WEATHER SERVICE OFFICE, AK US</td>\n",
       "      <td>7/29/2013</td>\n",
       "      <td>7</td>\n",
       "      <td>2013</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>21.7</td>\n",
       "      <td>10.0</td>\n",
       "      <td>15.85</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
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       "    <tr>\n",
       "      <th>172497</th>\n",
       "      <td>USW00026442</td>\n",
       "      <td>VALDEZ WEATHER SERVICE OFFICE, AK US</td>\n",
       "      <td>7/30/2013</td>\n",
       "      <td>7</td>\n",
       "      <td>2013</td>\n",
       "      <td>0.3</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>21.1</td>\n",
       "      <td>12.2</td>\n",
       "      <td>16.65</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
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       "      <td>0</td>\n",
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       "    <tr>\n",
       "      <th>172498</th>\n",
       "      <td>USW00026442</td>\n",
       "      <td>VALDEZ WEATHER SERVICE OFFICE, AK US</td>\n",
       "      <td>7/31/2013</td>\n",
       "      <td>7</td>\n",
       "      <td>2013</td>\n",
       "      <td>0.3</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>18.9</td>\n",
       "      <td>12.8</td>\n",
       "      <td>15.85</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
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       "  </tbody>\n",
       "</table>\n",
       "<p>14781 rows × 16 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "            STATION                                  NAME       DATE  Month  \\\n",
       "181     USW00027502                 BARROW AIRPORT, AK US   7/1/1930      7   \n",
       "182     USW00027502                 BARROW AIRPORT, AK US   7/2/1930      7   \n",
       "183     USW00027502                 BARROW AIRPORT, AK US   7/3/1930      7   \n",
       "184     USW00027502                 BARROW AIRPORT, AK US   7/4/1930      7   \n",
       "185     USW00027502                 BARROW AIRPORT, AK US   7/5/1930      7   \n",
       "...             ...                                   ...        ...    ...   \n",
       "172494  USW00026442  VALDEZ WEATHER SERVICE OFFICE, AK US  7/27/2013      7   \n",
       "172495  USW00026442  VALDEZ WEATHER SERVICE OFFICE, AK US  7/28/2013      7   \n",
       "172496  USW00026442  VALDEZ WEATHER SERVICE OFFICE, AK US  7/29/2013      7   \n",
       "172497  USW00026442  VALDEZ WEATHER SERVICE OFFICE, AK US  7/30/2013      7   \n",
       "172498  USW00026442  VALDEZ WEATHER SERVICE OFFICE, AK US  7/31/2013      7   \n",
       "\n",
       "        Year  PRCP  SNOW  SNWD  TMAX  TMIN  TMEAN  TMEAN>=18  TMEAN>=20  \\\n",
       "181     1930   0.0   0.0   NaN  11.1  -0.6   5.25          0          0   \n",
       "182     1930   0.0   0.0   NaN  10.0   2.8   6.40          0          0   \n",
       "183     1930   2.3   0.0   NaN   6.1   1.1   3.60          0          0   \n",
       "184     1930   0.0   0.0   NaN   5.6   0.0   2.80          0          0   \n",
       "185     1930   6.6   0.0   NaN  13.3   1.1   7.20          0          0   \n",
       "...      ...   ...   ...   ...   ...   ...    ...        ...        ...   \n",
       "172494  2013   0.0   0.0   0.0  22.2  12.2  17.20          0          0   \n",
       "172495  2013   0.0   0.0   0.0  23.3  10.0  16.65          0          0   \n",
       "172496  2013   0.0   0.0   0.0  21.7  10.0  15.85          0          0   \n",
       "172497  2013   0.3   0.0   0.0  21.1  12.2  16.65          0          0   \n",
       "172498  2013   0.3   0.0   0.0  18.9  12.8  15.85          0          0   \n",
       "\n",
       "        TMEAN>=25  TMAX>=20  TMAX>=25  \n",
       "181             0         0         0  \n",
       "182             0         0         0  \n",
       "183             0         0         0  \n",
       "184             0         0         0  \n",
       "185             0         0         0  \n",
       "...           ...       ...       ...  \n",
       "172494          0         1         0  \n",
       "172495          0         1         0  \n",
       "172496          0         1         0  \n",
       "172497          0         1         0  \n",
       "172498          0         0         0  \n",
       "\n",
       "[14781 rows x 16 columns]"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "historical_temp_june_july.groupby(['NAME','Year'])['TMIN']"
   ]
  }
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