{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Error analysis oggm_v16 versions: TODO currently --> adding 2025.6 "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "#per_glacier/  per_glacier_spinup/  regional_spinup/"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "2025-11-21 12:26:28: oggm.cfg: Reading default parameters from the OGGM `params.cfg` configuration file.\n",
      "2025-11-21 12:26:28: oggm.cfg: Multiprocessing switched OFF according to the parameter file.\n",
      "2025-11-21 12:26:28: oggm.cfg: Multiprocessing: using all available processors (N=32)\n"
     ]
    }
   ],
   "source": [
    "from oggm import cfg, workflow, utils, shop\n",
    "import pandas as pd\n",
    "import os, glob\n",
    "import numpy as np\n",
    "import xarray as xr\n",
    "import seaborn as sns\n",
    "import matplotlib.pyplot as plt\n",
    "sns.set_style(\"whitegrid\")\n",
    "\n",
    "cfg.initialize()\n",
    "\n",
    "import matplotlib\n",
    "matplotlib.rcParams['figure.figsize'] = (14, 8)\n",
    "\n",
    "# makes sure that the pandas output columns are not cropped!\n",
    "pd.set_option(\"max_colwidth\", None)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "rgi_reg_l = []\n",
    "for rgi_reg in np.arange(1,20,1):\n",
    "    if rgi_reg <10:\n",
    "        rgi_reg = f'0{rgi_reg}'\n",
    "    else:\n",
    "        rgi_reg = f'{rgi_reg}'\n",
    "    rgi_reg_l.append(rgi_reg)\n",
    "rgi_reg_l.append('all')\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "#base_url = 'https://cluster.klima.uni-bremen.de/~oggm/gdirs/oggm_v1.6/L3-L5_files/2023.3/elev_bands/W5E5_spinup/'\n",
    "base_url = 'https://cluster.klima.uni-bremen.de/~oggm/gdirs/oggm_v1.6/L3-L5_files/2025.6/elev_bands/W5E5/tests/per_glacier_spinup_newbias/'\n",
    "base_url_2023biasmethod = 'https://cluster.klima.uni-bremen.de/~oggm/gdirs/oggm_v1.6/L3-L5_files/2025.6/elev_bands/W5E5/tests/per_glacier_spinup_2023biasmethod/'\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "1449    dynamic melt_f calibration (full success)\n",
      "Name: used_spinup_option, dtype: object\n",
      "W5E5_spinup 2023.3 b_080\n",
      "1449    dynamic melt_f calibration (full success)\n",
      "Name: used_spinup_option, dtype: object\n",
      "W5E5_spinup 2023.3 b_160\n",
      "1449    dynamic melt_f calibration (full success)\n",
      "Name: used_spinup_option, dtype: object\n",
      "W5E5_spinup 2025.6 b_160\n",
      "1449    dynamic melt_f calibration (full success)\n",
      "Name: used_spinup_option, dtype: object\n",
      "W5E5_spinup 2025.6_2023biasmethod b_160\n",
      "W5E5 2023.3 b_080\n",
      "W5E5 2023.3 b_160\n",
      "W5E5 2025.6 b_160\n"
     ]
    }
   ],
   "source": [
    "### ### now adding 2025.6\n",
    "\n",
    "opts = ['dynamic melt_f calibration (full success)', 'dynamic melt_f calibration (part success)', 'dynamic spinup only','fixed geometry spinup']\n",
    "opts_w = ['dynamic melt_f calibration (full success)_ratio', 'dynamic melt_f calibration (part success)_ratio', 'dynamic spinup only_ratio','fixed geometry spinup_ratio']\n",
    "\n",
    "columns = ['rgi_reg', 'option','version','border', 'perc_area_miss', 'perc_glac_miss'] + opts + opts_w\n",
    "pd_stats_l = []\n",
    "working_rgis_l = []\n",
    "for option in ['W5E5_spinup', 'W5E5']: #'W5E5_spinup_10', \n",
    "    for version in [ '2023.3', '2025.6', '2025.6_2023biasmethod']: # '2023.2',\n",
    "        for border in ['b_080', 'b_160']:\n",
    "            if (version == '2023.2') and (border == 'b_080'):\n",
    "                continue\n",
    "            elif (option == 'W5E5_spinup_10') and ((version == '2023.2') or (border == 'b_080')): \n",
    "                continue\n",
    "            elif (version =='2025.6') and (border == 'b_080'):\n",
    "                continue\n",
    "            elif (version == '2025.6_2023biasmethod') and (border == 'b_080'):\n",
    "                continue\n",
    "            elif (version == '2025.6_2023biasmethod') and (option == 'W5E5'):\n",
    "                continue\n",
    "            else:\n",
    "                pd_stats = pd.DataFrame(columns=columns, index = rgi_reg_l)\n",
    "                path = '/home/www/oggm/gdirs/oggm_v1.6/'\n",
    "                add = f'L3-L5_files/{version}/elev_bands/{option}/RGI62/{border}/L5/summary/'\n",
    "                if (version == '2025.6') and (option == 'W5E5_spinup'):\n",
    "                    add = 'L3-L5_files/2025.6/elev_bands/W5E5/tests/per_glacier_spinup_newbias/RGI62/b_160/L5/summary/'\n",
    "                elif (version == '2025.6') and (option == 'W5E5'):\n",
    "                    add = 'L3-L5_files/2025.6/elev_bands/W5E5/per_glacier/RGI62/b_160/L5/summary/'\n",
    "                elif (version == '2025.6_2023biasmethod') and (option == 'W5E5_spinup'):\n",
    "                    add = 'L3-L5_files/2025.6/elev_bands/W5E5/tests/per_glacier_spinup_2023biasmethod/RGI62/b_160/L5/summary/'\n",
    "                    \n",
    "                stats_l = []\n",
    "                for rgi_reg in rgi_reg_l[:-1]:\n",
    "                    stats_l.append(pd.read_csv(path+add+f'glacier_statistics_{rgi_reg}.csv', low_memory=False))\n",
    "                stats = pd.concat(stats_l)  \n",
    "\n",
    "                stats_w = stats.loc[stats.error_msg.isna()]\n",
    "                working_rgis_l.append(stats_w.rgi_id.values)\n",
    "                perc_area_miss = 100-100*stats_w.rgi_area_km2.sum()/stats.rgi_area_km2.sum()\n",
    "                perc_glac_miss = 100-100*stats_w.rgi_id.count()/stats.rgi_id.count()\n",
    "                if 'W5E5_spinup' in option:\n",
    "                    stats_spinup_option = tuple(stats.groupby(['used_spinup_option']).count()['rgi_id'].loc[opts].values)\n",
    "                    stats_spinup_option_w = tuple(stats_w.groupby(['used_spinup_option']).count()['rgi_id'].loc[opts].values/len(stats))\n",
    "                    print(stats.loc[stats.rgi_id=='RGI60-11.01450']['used_spinup_option'])\n",
    "                else:\n",
    "                    stats_spinup_option = (np.NaN, np.NaN, np.NaN, np.NaN)\n",
    "                    stats_spinup_option_w = (np.NaN, np.NaN, np.NaN, np.NaN)\n",
    "\n",
    "                pd_stats.loc['all'] = ('all',option,version, border, perc_area_miss,perc_glac_miss)+stats_spinup_option+stats_spinup_option_w\n",
    "                for rgi_r in np.arange(1,20,1):\n",
    "                    stats_r = stats.loc[stats.rgi_region==rgi_r]\n",
    "                    if 'W5E5_spinup' in option:\n",
    "                        _p = stats_r.groupby(['used_spinup_option']).count()['rgi_id']\n",
    "                        # it can be that one of the options occurs for none of the glaciers in one RGI region\n",
    "                        for o in opts:\n",
    "                            if o not in _p.index:\n",
    "                                _p.loc[o] = 0\n",
    "                        stats_spinup_option = tuple(_p.loc[opts].values)\n",
    "                    else:\n",
    "                        stats_spinup_option = (np.NaN, np.NaN, np.NaN, np.NaN)\n",
    "                    rgi_reg = str(rgi_r).zfill(2)\n",
    "                    stats_w_r = stats_r.loc[stats_r.error_msg.isna()]\n",
    "                    if 'W5E5_spinup' in option:\n",
    "                        _p = stats_w_r.groupby(['used_spinup_option']).count()['rgi_id']\n",
    "                        # it can be that one of the options occurs for none of the glaciers in one RGI region\n",
    "                        for o in opts:\n",
    "                            if o not in _p.index:\n",
    "                                _p.loc[o] = 0\n",
    "                        stats_spinup_option_w = tuple(_p.loc[opts].values/len(stats_r))\n",
    "                    else:\n",
    "                        stats_spinup_option_w = (np.NaN, np.NaN, np.NaN, np.NaN)\n",
    "                    \n",
    "                    perc_area_miss = 100-100*stats_w_r.rgi_area_km2.sum()/stats_r.rgi_area_km2.sum()\n",
    "                    perc_glac_miss = 100-100*stats_w_r.rgi_id.count()/stats_r.rgi_id.count()\n",
    "                    pd_stats.loc[rgi_reg] = (rgi_reg,option,version, border, perc_area_miss,perc_glac_miss) + stats_spinup_option + stats_spinup_option_w\n",
    "                pd_stats_l.append(pd_stats.reset_index())\n",
    "                print(option, version, border)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "7"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(working_rgis_l)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [],
   "source": [
    "common_working_rgi_ids = set(working_rgis_l[0])\n",
    "for lst in working_rgis_l[1:]:\n",
    "    common_working_rgi_ids = common_working_rgi_ids.intersection(lst)\n",
    "common_working_rgi_ids = list(common_working_rgi_ids)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "212269"
      ]
     },
     "execution_count": 31,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(list(set(common_working_rgi_ids)))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "212269"
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(common_working_rgi_ids)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [],
   "source": [
    "pd.DataFrame(index=common_working_rgi_ids).to_csv('common_working_rgi_ids_prepro_2023.3_vs_2025.6_new_vs_old_bias.csv')\n",
    "#pd.DataFrame(index=common_working_rgi_ids).to_csv('/home/www/lschuster/runs_oggm_v16/analysis_notebooks/common_working_rgi_ids_prepro_2023.3_vs_2025.6.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [],
   "source": [
    "pd_stats_all = pd.concat(pd_stats_l).reset_index()\n",
    "ind_n_l = []\n",
    "for k in pd_stats_all.index:\n",
    "    o,v,b = pd_stats_all[['option','version','border']].iloc[k].values\n",
    "    ind_n = f'{o}_{v}_{b}'\n",
    "    ind_n_l.append(ind_n)\n",
    "pd_stats_all['option_version_border'] = ind_n_l\n",
    "pd_stats_all['dynamic melt_f calibration (full+part success)'] = (pd_stats_all['dynamic melt_f calibration (full success)'] + \n",
    "                                                                  pd_stats_all['dynamic melt_f calibration (part success)'])\n",
    "#pd_stats_all['dynamic melt_f calibration (full+part success)_ratio'] = (pd_stats_all['dynamic melt_f calibration (full success)_ratio'] + \n",
    "#                                                                  pd_stats_all['dynamic melt_f calibration (part success)_ratio'])\n",
    "pd_stats_all['total'] = (pd_stats_all['dynamic melt_f calibration (full+part success)']+\n",
    "                         pd_stats_all['fixed geometry spinup']+\n",
    "                         pd_stats_all['dynamic spinup only'])\n",
    "\n",
    "\n",
    "pd_stats_all['dynamic calib full success / total (%)'] = 100*(pd_stats_all['dynamic melt_f calibration (full success)'] / pd_stats_all['total'])\n",
    "pd_stats_all['dynamic calib full + part success / total (%)'] = 100*(pd_stats_all['dynamic melt_f calibration (full+part success)'] / pd_stats_all['total'])\n",
    "\n",
    "#pd_stats_all['dynamic calib full success_ratio / total (%)'] = 100*pd_stats_all['dynamic melt_f calibration (full success)_ratio'] #/ pd_stats_all['total'])\n",
    "#pd_stats_all['dynamic calib full + part success_ratio / total (%)'] = 100*pd_stats_all['dynamic melt_f calibration (full+part success)_ratio']# / pd_stats_all['total'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [],
   "source": [
    "pd_all = pd_stats_all.loc[pd_stats_all.rgi_reg=='all']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "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>rgi_reg</th>\n",
       "      <th>option</th>\n",
       "      <th>version</th>\n",
       "      <th>border</th>\n",
       "      <th>perc_area_miss</th>\n",
       "      <th>perc_glac_miss</th>\n",
       "      <th>dynamic melt_f calibration (full success)</th>\n",
       "      <th>dynamic melt_f calibration (part success)</th>\n",
       "      <th>dynamic spinup only</th>\n",
       "      <th>fixed geometry spinup</th>\n",
       "      <th>dynamic melt_f calibration (full+part success)</th>\n",
       "      <th>total</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>all</td>\n",
       "      <td>W5E5_spinup</td>\n",
       "      <td>2023.3</td>\n",
       "      <td>b_080</td>\n",
       "      <td>0.102574</td>\n",
       "      <td>1.072156</td>\n",
       "      <td>186128</td>\n",
       "      <td>9322</td>\n",
       "      <td>4437</td>\n",
       "      <td>14441</td>\n",
       "      <td>195450</td>\n",
       "      <td>214328</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>39</th>\n",
       "      <td>all</td>\n",
       "      <td>W5E5_spinup</td>\n",
       "      <td>2023.3</td>\n",
       "      <td>b_160</td>\n",
       "      <td>0.098552</td>\n",
       "      <td>1.022051</td>\n",
       "      <td>185467</td>\n",
       "      <td>9922</td>\n",
       "      <td>4453</td>\n",
       "      <td>14485</td>\n",
       "      <td>195389</td>\n",
       "      <td>214327</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>59</th>\n",
       "      <td>all</td>\n",
       "      <td>W5E5_spinup</td>\n",
       "      <td>2025.6</td>\n",
       "      <td>b_160</td>\n",
       "      <td>0.09159</td>\n",
       "      <td>0.883798</td>\n",
       "      <td>180507</td>\n",
       "      <td>14082</td>\n",
       "      <td>4052</td>\n",
       "      <td>15743</td>\n",
       "      <td>194589</td>\n",
       "      <td>214384</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>79</th>\n",
       "      <td>all</td>\n",
       "      <td>W5E5_spinup</td>\n",
       "      <td>2025.6_2023biasmethod</td>\n",
       "      <td>b_160</td>\n",
       "      <td>0.091014</td>\n",
       "      <td>0.888437</td>\n",
       "      <td>182455</td>\n",
       "      <td>12161</td>\n",
       "      <td>4112</td>\n",
       "      <td>15656</td>\n",
       "      <td>194616</td>\n",
       "      <td>214384</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>99</th>\n",
       "      <td>all</td>\n",
       "      <td>W5E5</td>\n",
       "      <td>2023.3</td>\n",
       "      <td>b_080</td>\n",
       "      <td>0.097996</td>\n",
       "      <td>0.936687</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>119</th>\n",
       "      <td>all</td>\n",
       "      <td>W5E5</td>\n",
       "      <td>2023.3</td>\n",
       "      <td>b_160</td>\n",
       "      <td>0.09531</td>\n",
       "      <td>0.902819</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>139</th>\n",
       "      <td>all</td>\n",
       "      <td>W5E5</td>\n",
       "      <td>2025.6</td>\n",
       "      <td>b_160</td>\n",
       "      <td>0.083675</td>\n",
       "      <td>0.563218</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": [
       "    rgi_reg       option                version border perc_area_miss  \\\n",
       "19      all  W5E5_spinup                 2023.3  b_080       0.102574   \n",
       "39      all  W5E5_spinup                 2023.3  b_160       0.098552   \n",
       "59      all  W5E5_spinup                 2025.6  b_160        0.09159   \n",
       "79      all  W5E5_spinup  2025.6_2023biasmethod  b_160       0.091014   \n",
       "99      all         W5E5                 2023.3  b_080       0.097996   \n",
       "119     all         W5E5                 2023.3  b_160        0.09531   \n",
       "139     all         W5E5                 2025.6  b_160       0.083675   \n",
       "\n",
       "    perc_glac_miss dynamic melt_f calibration (full success)  \\\n",
       "19        1.072156                                    186128   \n",
       "39        1.022051                                    185467   \n",
       "59        0.883798                                    180507   \n",
       "79        0.888437                                    182455   \n",
       "99        0.936687                                       NaN   \n",
       "119       0.902819                                       NaN   \n",
       "139       0.563218                                       NaN   \n",
       "\n",
       "    dynamic melt_f calibration (part success) dynamic spinup only  \\\n",
       "19                                       9322                4437   \n",
       "39                                       9922                4453   \n",
       "59                                      14082                4052   \n",
       "79                                      12161                4112   \n",
       "99                                        NaN                 NaN   \n",
       "119                                       NaN                 NaN   \n",
       "139                                       NaN                 NaN   \n",
       "\n",
       "    fixed geometry spinup dynamic melt_f calibration (full+part success)  \\\n",
       "19                  14441                                         195450   \n",
       "39                  14485                                         195389   \n",
       "59                  15743                                         194589   \n",
       "79                  15656                                         194616   \n",
       "99                    NaN                                            NaN   \n",
       "119                   NaN                                            NaN   \n",
       "139                   NaN                                            NaN   \n",
       "\n",
       "      total  \n",
       "19   214328  \n",
       "39   214327  \n",
       "59   214384  \n",
       "79   214384  \n",
       "99      NaN  \n",
       "119     NaN  \n",
       "139     NaN  "
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd_all[['rgi_reg', 'option', 'version', 'border',\n",
    "       'perc_area_miss', 'perc_glac_miss',\n",
    "       'dynamic melt_f calibration (full success)',\n",
    "       'dynamic melt_f calibration (part success)', 'dynamic spinup only',\n",
    "       'fixed geometry spinup','dynamic melt_f calibration (full+part success)','total']]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1500x1000 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(15,10))\n",
    "pd_sel_area_miss = pd_stats_all[['rgi_reg','option_version_border','perc_area_miss']].pivot(columns='option_version_border', index = 'rgi_reg')\n",
    "pd_sel_area_miss.columns = pd_sel_area_miss.columns.get_level_values(1)\n",
    "pd_sel_area_miss = pd_sel_area_miss.astype(float)\n",
    "sns.heatmap(pd_sel_area_miss,\n",
    "            #y= 'rgi_reg', x='option_version_border',\n",
    "            linewidths=.5, cmap=\"PuRd\", cbar_kws={'label':'relative failing glacier area (in %)'},\n",
    "           annot=True, fmt=\".3f\")\n",
    "plt.tight_layout()\n",
    "plt.savefig('error_analysis_2025_6_old_vs_new_bias_vs_2023_3_prepro_failing_glacier_area.png')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 1400x1200 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(14,12))\n",
    "\n",
    "pd_sel_glac_miss = pd_stats_all[['rgi_reg','option_version_border','perc_glac_miss']].pivot(columns='option_version_border', index = 'rgi_reg')\n",
    "pd_sel_glac_miss.columns = pd_sel_glac_miss.columns.get_level_values(1)\n",
    "pd_sel_glac_miss = pd_sel_glac_miss.astype(float)\n",
    "sns.heatmap(pd_sel_glac_miss,\n",
    "            #y= 'rgi_reg', x='option_version_border',\n",
    "            linewidths=.5, cmap=\"PuRd\", cbar_kws={'label':'relative failing glacier amount (in %)'},\n",
    "           annot=True, fmt=\".2f\")\n",
    "plt.tight_layout()\n",
    "plt.savefig('error_analysis_2025_6_old_vs_new_bias_vs_2023_3_prepro_failing_glaciers.png')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1400x1200 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(14,12))\n",
    "\n",
    "sns.set(font_scale = 1.3)\n",
    "\n",
    "pd_sel_dynamic_success_total = pd_stats_all[['rgi_reg','option_version_border','dynamic calib full success / total (%)']].pivot(columns='option_version_border', index = 'rgi_reg')\n",
    "\n",
    "pd_sel_dynamic_success_total.columns = pd_sel_dynamic_success_total.columns.get_level_values(1)\n",
    "pd_sel_dynamic_success_total = pd_sel_dynamic_success_total.astype(float)\n",
    "pd_sel_dynamic_success_total = pd_sel_dynamic_success_total.dropna(axis=1, how='all')\n",
    "\n",
    "sns.heatmap(pd_sel_dynamic_success_total,\n",
    "            #y= 'rgi_reg', x='option_version_border',\n",
    "            linewidths=.5, cmap=\"Blues\", cbar_kws={'label':'relative amount of glaciers with full success\\nin the dynamiccalibration (in %)'},\n",
    "           annot=True, fmt=\".2f\")\n",
    "ax = plt.gca()\n",
    "ax.figure.axes[-1].yaxis.label.set_size(18)\n",
    "ax.set_ylabel('RGI region', fontsize=20);\n",
    "plt.tight_layout()\n",
    "plt.savefig('error_analysis_2025_6_old_vs_new_bias_vs_2023_3_spinup_calib.png')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "ename": "KeyError",
     "evalue": "\"['dynamic calib full success_w/ total (%)'] not in index\"",
     "output_type": "error",
     "traceback": [
      "\u001b[31m---------------------------------------------------------------------------\u001b[39m",
      "\u001b[31mKeyError\u001b[39m                                  Traceback (most recent call last)",
      "\u001b[36mCell\u001b[39m\u001b[36m \u001b[39m\u001b[32mIn[29]\u001b[39m\u001b[32m, line 3\u001b[39m\n\u001b[32m      1\u001b[39m sns.set(font_scale = \u001b[32m1.3\u001b[39m)\n\u001b[32m----> \u001b[39m\u001b[32m3\u001b[39m pd_sel_dynamic_success_total = \u001b[43mpd_stats_all\u001b[49m\u001b[43m[\u001b[49m\u001b[43m[\u001b[49m\u001b[33;43m'\u001b[39;49m\u001b[33;43mrgi_reg\u001b[39;49m\u001b[33;43m'\u001b[39;49m\u001b[43m,\u001b[49m\u001b[33;43m'\u001b[39;49m\u001b[33;43moption_version_border\u001b[39;49m\u001b[33;43m'\u001b[39;49m\u001b[43m,\u001b[49m\u001b[33;43m'\u001b[39;49m\u001b[33;43mdynamic calib full success_w/ total (\u001b[39;49m\u001b[33;43m%\u001b[39;49m\u001b[33;43m)\u001b[39;49m\u001b[33;43m'\u001b[39;49m\u001b[43m]\u001b[49m\u001b[43m]\u001b[49m.pivot(columns=\u001b[33m'\u001b[39m\u001b[33moption_version_border\u001b[39m\u001b[33m'\u001b[39m, index = \u001b[33m'\u001b[39m\u001b[33mrgi_reg\u001b[39m\u001b[33m'\u001b[39m)\n\u001b[32m      5\u001b[39m pd_sel_dynamic_success_total.columns = pd_sel_dynamic_success_total.columns.get_level_values(\u001b[32m1\u001b[39m)\n\u001b[32m      6\u001b[39m pd_sel_dynamic_success_total = pd_sel_dynamic_success_total.astype(\u001b[38;5;28mfloat\u001b[39m)\n",
      "\u001b[36mFile \u001b[39m\u001b[32m~/mambaforge/envs/oggm_env_2025/lib/python3.11/site-packages/pandas/core/frame.py:4119\u001b[39m, in \u001b[36mDataFrame.__getitem__\u001b[39m\u001b[34m(self, key)\u001b[39m\n\u001b[32m   4117\u001b[39m     \u001b[38;5;28;01mif\u001b[39;00m is_iterator(key):\n\u001b[32m   4118\u001b[39m         key = \u001b[38;5;28mlist\u001b[39m(key)\n\u001b[32m-> \u001b[39m\u001b[32m4119\u001b[39m     indexer = \u001b[38;5;28;43mself\u001b[39;49m\u001b[43m.\u001b[49m\u001b[43mcolumns\u001b[49m\u001b[43m.\u001b[49m\u001b[43m_get_indexer_strict\u001b[49m\u001b[43m(\u001b[49m\u001b[43mkey\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[33;43m\"\u001b[39;49m\u001b[33;43mcolumns\u001b[39;49m\u001b[33;43m\"\u001b[39;49m\u001b[43m)\u001b[49m[\u001b[32m1\u001b[39m]\n\u001b[32m   4121\u001b[39m \u001b[38;5;66;03m# take() does not accept boolean indexers\u001b[39;00m\n\u001b[32m   4122\u001b[39m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mgetattr\u001b[39m(indexer, \u001b[33m\"\u001b[39m\u001b[33mdtype\u001b[39m\u001b[33m\"\u001b[39m, \u001b[38;5;28;01mNone\u001b[39;00m) == \u001b[38;5;28mbool\u001b[39m:\n",
      "\u001b[36mFile \u001b[39m\u001b[32m~/mambaforge/envs/oggm_env_2025/lib/python3.11/site-packages/pandas/core/indexes/base.py:6212\u001b[39m, in \u001b[36mIndex._get_indexer_strict\u001b[39m\u001b[34m(self, key, axis_name)\u001b[39m\n\u001b[32m   6209\u001b[39m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[32m   6210\u001b[39m     keyarr, indexer, new_indexer = \u001b[38;5;28mself\u001b[39m._reindex_non_unique(keyarr)\n\u001b[32m-> \u001b[39m\u001b[32m6212\u001b[39m \u001b[38;5;28;43mself\u001b[39;49m\u001b[43m.\u001b[49m\u001b[43m_raise_if_missing\u001b[49m\u001b[43m(\u001b[49m\u001b[43mkeyarr\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mindexer\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43maxis_name\u001b[49m\u001b[43m)\u001b[49m\n\u001b[32m   6214\u001b[39m keyarr = \u001b[38;5;28mself\u001b[39m.take(indexer)\n\u001b[32m   6215\u001b[39m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28misinstance\u001b[39m(key, Index):\n\u001b[32m   6216\u001b[39m     \u001b[38;5;66;03m# GH 42790 - Preserve name from an Index\u001b[39;00m\n",
      "\u001b[36mFile \u001b[39m\u001b[32m~/mambaforge/envs/oggm_env_2025/lib/python3.11/site-packages/pandas/core/indexes/base.py:6264\u001b[39m, in \u001b[36mIndex._raise_if_missing\u001b[39m\u001b[34m(self, key, indexer, axis_name)\u001b[39m\n\u001b[32m   6261\u001b[39m     \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mKeyError\u001b[39;00m(\u001b[33mf\u001b[39m\u001b[33m\"\u001b[39m\u001b[33mNone of [\u001b[39m\u001b[38;5;132;01m{\u001b[39;00mkey\u001b[38;5;132;01m}\u001b[39;00m\u001b[33m] are in the [\u001b[39m\u001b[38;5;132;01m{\u001b[39;00maxis_name\u001b[38;5;132;01m}\u001b[39;00m\u001b[33m]\u001b[39m\u001b[33m\"\u001b[39m)\n\u001b[32m   6263\u001b[39m not_found = \u001b[38;5;28mlist\u001b[39m(ensure_index(key)[missing_mask.nonzero()[\u001b[32m0\u001b[39m]].unique())\n\u001b[32m-> \u001b[39m\u001b[32m6264\u001b[39m \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mKeyError\u001b[39;00m(\u001b[33mf\u001b[39m\u001b[33m\"\u001b[39m\u001b[38;5;132;01m{\u001b[39;00mnot_found\u001b[38;5;132;01m}\u001b[39;00m\u001b[33m not in index\u001b[39m\u001b[33m\"\u001b[39m)\n",
      "\u001b[31mKeyError\u001b[39m: \"['dynamic calib full success_w/ total (%)'] not in index\""
     ]
    }
   ],
   "source": [
    "sns.set(font_scale = 1.3)\n",
    "\n",
    "pd_sel_dynamic_success_total = pd_stats_all[['rgi_reg','option_version_border','dynamic calib full success_w/ total (%)']].pivot(columns='option_version_border', index = 'rgi_reg')\n",
    "\n",
    "pd_sel_dynamic_success_total.columns = pd_sel_dynamic_success_total.columns.get_level_values(1)\n",
    "pd_sel_dynamic_success_total = pd_sel_dynamic_success_total.astype(float)\n",
    "pd_sel_dynamic_success_total = pd_sel_dynamic_success_total.dropna(axis=1, how='all')\n",
    "\n",
    "sns.heatmap(pd_sel_dynamic_success_total,\n",
    "            #y= 'rgi_reg', x='option_version_border',\n",
    "            linewidths=.5, cmap=\"Blues\", cbar_kws={'label':'relative amount of working glaciers with full success vs total glaciers (in %)'},\n",
    "           annot=True, fmt=\".2f\")\n",
    "ax = plt.gca()\n",
    "ax.figure.axes[-1].yaxis.label.set_size(18)\n",
    "ax.set_ylabel('RGI region', fontsize=20);"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### OLD???"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "sns.set(font_scale = 1.3)\n",
    "plt.figure(figsize=(16,10))\n",
    "plt.subplot(111)\n",
    "plt.title('Relative failing glacier area per RGI region\\n(match_geod_pergla, qc0)', fontsize=20)\n",
    "#plt.title(', fontsize=22)\n",
    "pd_stats_all_sel\n",
    "sns.heatmap(pd_stats_all,\n",
    "            linewidths=.5, cmap=\"PuRd\", cbar_kws={'label':'relative failing glacier area (in %)'},\n",
    "           annot=True, fmt=\".2f\")\n",
    "ax = plt.gca()\n",
    "ax.figure.axes[-1].yaxis.label.set_size(18)\n",
    "ax.set_ylabel('RGI region', fontsize=20);\n",
    "ax.set_xticklabels(['CRU_pcp2.5\\n(b80)', 'ERA5_pcp1.6\\n(b80)', 'W5E5_pcp2.6\\n(b160)', 'W5E5_pcp_via\\nwinter_prcp (b160)'])\n",
    "ax.set_xlabel('climate dataset & prcp. fac', fontsize=20)\n",
    "plt.savefig('relative_failing_glacier_area_regional_match_geod_pergla_clim_pcp.png')\n",
    "\n",
    "plt.figure(figsize=(24,10))\n",
    "plt.subplot(122)\n",
    "ax = plt.gca()\n",
    "sns.boxplot(x = 'rgi_region', y='glacier_prcp_scaling_factor', data = pd_glac_stats_all, ax = ax)\n",
    "plt.axhline(2.6, ls= '--', lw = 3, color = 'grey', label = 'applied constant prcp. fac\\n(median from reference glaciers matching std.)')\n",
    "plt.axhline(pd_glac_stats_all['glacier_prcp_scaling_factor'].quantile([0.5]).values,\n",
    "            ls= ':', lw = 3, color = 'gray', label = 'median prcp. fac over all glaciers')\n",
    "plt.legend()\n",
    "plt.title('glacier-specific varying prcp. fac depending on the winter prcp. (using W5E5)', fontsize=20)\n",
    "\n",
    "plt.subplot(121)\n",
    "ax = plt.gca()\n",
    "sns.boxplot(x = 'rgi_region', y='winter_prcp', data = pd_glac_stats_all, ax = ax)\n",
    "\n",
    "plt.legend()\n",
    "plt.ylabel(r'winter daily precipitation (kg m$^{-2}$, avg. 1979-2019)')\n",
    "plt.title('(uncorrected) winter prcp. with W5E5', fontsize=20)\n",
    "plt.tight_layout()\n",
    "plt.savefig('W5E5_prcp_fac_via_winterpcp_boxplots.png')\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [],
   "source": [
    "def error_analysis_w_plot(dfserr={}, pd_rel_error_area = None,\n",
    "                          level='L2', exp='elev_bands', pcp ='', clim='', \n",
    "                          qc = '', match = '', border = 160,\n",
    "                          version = '',\n",
    "                          rgi_reg = 'all', \n",
    "                          path = '/home/www/oggm/gdirs/oggm_v1.6/', subplot = False, xlim=None, plot=True, rename_match =True):\n",
    "    \"\"\" Estimates for a specific preprocessed gdirs the relative glacier area with errors\n",
    "    and the relative amount of glaciers with errors (both in %). \n",
    "    \n",
    "    Plots the error counts for the different error types.\n",
    "    \n",
    "    Works only if the glacier statistics were estimated!\n",
    "    \n",
    "    Parameters\n",
    "    ----------\n",
    "    dfserr : dictionary\n",
    "        dictionary where already errors of largest glaciers from other preprocessed gdirs are saved, default is an empty dictionary\n",
    "    pd_rel_error_area : pd.DataFrame\n",
    "        pandas DataFrame with statistics about relative area and amount of errors on glaciers. \n",
    "        Default is None, which creates a new pandas DataFrame\n",
    "    level : str\n",
    "        the preprocessing level where the errors should be estimated and plotted.\n",
    "        So far, it works only for 'L2' and 'L5'. Default is 'L2'.\n",
    "    exp : str\n",
    "        which glacier flowlines are used. Either 'elev_bands' (default) or 'centerlines'\n",
    "    pcp : str\n",
    "        precipitation factor applied (depends on clim). Has to be set!\n",
    "    clim : str\n",
    "        which baseline is applied. Either 'ERA5' or 'CRU'. Has to be set!\n",
    "    qc : str\n",
    "        whether a glacier climate quality check and correction was applied. If yes, set it to 'qc3', \n",
    "        otherwise to 'qc0'. Has to be set!\n",
    "    match: str\n",
    "        which calibration & other methods are chosen: Has to be set if above level 2!\n",
    "        - \"no_match\" : only direct glaciological WGMS data used\n",
    "        - \"match_geod\" : same as no_match, but regionally the geodetic estimates are matched by changing epsilon\n",
    "        - \"match_geod_pergla\" : only per-glacier-individual geodetic estimates of Hugonnet et al. (2021) matched\n",
    "        - \"match_geod_pergla_massredis\" : same as match_geod_pergla, but instead of the Shallow-Ice Approximation, \n",
    "          a mass-redistribution is applied (see: https://docs.oggm.org/en/latest/mass-redistribution.html)\n",
    "    border : str\n",
    "        which size of the local glacier map was used (prepro_border). For qc0, e.g., \n",
    "        most preprocessing directories are available for border=80. Default is 160\n",
    "    rgi_reg : str\n",
    "        default is all RGI regions. But you can also choose a single RGI region (e.g. rgi_reg = '11') or all RGI \n",
    "        regions except 19 (i.e. not available for CRU!, rgi_reg='all_without_19')\n",
    "    path : str\n",
    "        path to the general gdirs folder\n",
    "    subplot : bool\n",
    "        Default is False. If you want to use several plots, set it to True\n",
    "    xlim : int\n",
    "        Default is None. Maximum of single type errors in the plot. Useful for subplots\n",
    "    plot : bool\n",
    "        If an error type plot should be returned or not!\n",
    "    \n",
    "    Returns\n",
    "    -------\n",
    "    dfserr : dictionary\n",
    "        dictionary where for each preprocessed gdir, a pd.DataFrame exists which lists the \n",
    "        type of errors and area of the 15 largest glaciers with errors\n",
    "    pd_rel_error_area : pd.DataFrame\n",
    "        pandas DataFrame with statistics about relative area and amount of errors on glaciers. \n",
    "        If repeated, for several preprocessed gdirs, each row represents the statistics of \n",
    "        one preprocessed gdirs.\n",
    "        \n",
    "    \"\"\"\n",
    "    if clim == 'CRU' and rgi_reg == 'all':\n",
    "        raise InvalidParamsError(\"CRU is NOT available for RGI 19, use rgi_reg='all_without_19' instead\")\n",
    "    if pd_rel_error_area is None:\n",
    "        pd_rel_error_area = pd.DataFrame(columns=['rel_error_area_in_percent', 'level', 'exp', 'pcp_clim', 'match', 'qc'])\n",
    "\n",
    "    if level == 'L2':\n",
    "        fd = f'{path}/L1-L2_files/{exp}/RGI62/b_{border:03d}/L2/summary/'\n",
    "        err_msg = \"In preprocessing level 2, climate, precipitation factor and qc should not be defined\"\n",
    "        assert pcp == '' and clim == '' and qc == '', err_msg\n",
    "        title = f'{level}: {exp}, border: {border}'\n",
    "        dict_key = f'{level}_{exp}_b{border}_rgi_{rgi_reg}'\n",
    "    elif level == 'L5':\n",
    "        if (pcp == 'via_winterprcp') or (pcp == '2.6'):\n",
    "            fd = f'{path}/L3-L5_files/{clim}/{exp}/{qc}/{match}/RGI62/b_{border:03d}/L5/summary/'\n",
    "        elif pcp == 'v1.6':\n",
    "            fd = f'{path}/L3-L5_files/{version}/{exp}/{clim}/RGI62/b_{border:03d}/L5/summary/'\n",
    "        else:\n",
    "            fd = f'{path}/L3-L5_files/{clim}/{exp}/{qc}/{pcp}/{match}/RGI62/b_{border:03d}/L5/summary/'\n",
    "        #err_msg = \"In preprocessing level 5, need to prescribe climate (clim), match, precipitation factor (pcp) and quality check type (qc)\"\n",
    "        #assert pcp != '' and clim != '' and qc != '' and match !='' , err_msg\n",
    "\n",
    "        title = f'{level}: {exp}, {pcp}, {clim}, {match}, {qc}, border: {border}, rgi_{rgi_reg}, version: {version}'\n",
    "        dict_key = f'{level}_{exp}_{pcp}_{clim}_{match}_{qc}_b{border}_rgi_{rgi_reg}_version_{version}'\n",
    "    else:\n",
    "        raise InvalidParamsError('Only L2 and L5 can be used, but the function can be adapted easily in order that it works for other levels!')\n",
    "        \n",
    "    # get the statistics file which lists errors and their type\n",
    "    fs = glob.glob(fd+'glacier_statistics*.csv')\n",
    "    \n",
    "    if rgi_reg == 'all_without_19':\n",
    "        for f in fs:\n",
    "            if 'statistics_19' in f:\n",
    "                fs.remove(f)\n",
    "        assert len(fs) == 18\n",
    "    elif rgi_reg == 'all':\n",
    "        print(len(fs))\n",
    "        assert len(fs) == 19\n",
    "    else:\n",
    "        for f in fs:\n",
    "            if f'statistics_{rgi_reg}' in f:\n",
    "                fs = [f]\n",
    "                break\n",
    "        assert len(fs) == 1\n",
    "    \n",
    "    df = []\n",
    "    for f in fs:\n",
    "        df.append(pd.read_csv(f, index_col=0, low_memory=False))\n",
    "    df = pd.concat(df).sort_index()\n",
    "    \n",
    "    rel_error_area = df.loc[~df['error_task'].isnull()].rgi_area_km2.sum() / df.rgi_area_km2.sum() * 100\n",
    "    \n",
    "    # plot the amount of errors for each error type\n",
    "    if plot:\n",
    "        title = title + '\\n relative glacier area with errors: {:.2f}%'.format(rel_error_area)\n",
    "        if not subplot:\n",
    "            plt.figure()\n",
    "        plt.title(title, fontsize=12)\n",
    "        sns.countplot(y=\"error_task\", data=df.sort_values(by='error_task'));\n",
    "        if xlim is not None:\n",
    "            plt.xlim([0,xlim])\n",
    "\n",
    "    # save the glaciers that result in errors sorted from largest to smallest glacier area\n",
    "    dfserr[dict_key] = df.loc[~df['error_task'].isnull()].sort_values(by='rgi_area_km2', ascending=False)[['rgi_area_km2', 'error_task', 'error_msg']]\n",
    "    # .iloc[:15]\n",
    "    # save statistics about relative area and amount of errors on glaciers\n",
    "    pd_rel_error_area.loc[dict_key] = np.NaN\n",
    "    pd_rel_error_area.loc[dict_key]['rel_error_area_in_percent'] = rel_error_area\n",
    "    pd_rel_error_area.loc[dict_key]['rgi_reg'] = rgi_reg\n",
    "    pd_rel_error_area.loc[dict_key]['level'] = level\n",
    "    pd_rel_error_area.loc[dict_key]['border'] = border\n",
    "    pd_rel_error_area.loc[dict_key]['exp'] = exp\n",
    "    if rename_match:\n",
    "        if match == 'match_geod_pergla_2.6':\n",
    "            pd_rel_error_area.loc[dict_key]['match'] = match[:-4]\n",
    "        elif match == 'match_geod_pergla_winterprcp':\n",
    "            pd_rel_error_area.loc[dict_key]['match'] = 'match_geod_pergla'\n",
    "\n",
    "        else:\n",
    "            pd_rel_error_area.loc[dict_key]['match'] = match\n",
    "    else:\n",
    "        pd_rel_error_area.loc[dict_key]['match'] = match\n",
    "\n",
    "    pd_rel_error_area.loc[dict_key]['clim_pcp'] = f'{clim}_{pcp}'\n",
    "    pd_rel_error_area.loc[dict_key]['qc'] = qc\n",
    "    \n",
    "    return dfserr, pd_rel_error_area"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [],
   "source": [
    "# could be changed, but not all pre-processed directories are available for all prepro_border options!\n",
    "border = 160 # 80 if qc0\n",
    "# these are just containers to save and later compare the error statistics! \n",
    "dfserr = {}\n",
    "pd_rel_error_area = pd.DataFrame(columns=['rel_error_area_in_percent', 'level', 'exp',\n",
    "                                          'clim_pcp', 'match', 'qc', 'border', 'rgi_reg'])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "tags": []
   },
   "source": [
    "## Analysis for Level 2 pre-processing directories!\n",
    "\n",
    "In pre-processing level 2, we only distinguish between elevation bands and centerlines (see the [Flowlines documentation](https://docs.oggm.org/en/stable/flowlines.html#glacier-flowlines) for an explanation about the differences). "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "19\n",
      "19\n"
     ]
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 1400x300 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(14,3))\n",
    "plt.subplot(121)\n",
    "dfserr, pd_rel_error_area = error_analysis_w_plot(dfserr=dfserr, pd_rel_error_area=pd_rel_error_area,\n",
    "                                                  level='L2', subplot=True,\n",
    "                                                  exp='elev_bands', border=border, xlim = 800)\n",
    "plt.subplot(122)\n",
    "dfserr, pd_rel_error_area = error_analysis_w_plot(dfserr=dfserr, pd_rel_error_area=pd_rel_error_area,\n",
    "                                                  level='L2',  subplot=True,\n",
    "                                                  exp='centerlines', border=border, xlim = 800)\n",
    "plt.tight_layout()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "- failing glacier area on pre-processing level 2 is ~0.1% or less\n",
    "- less glaciers will fail when using elev_bands than centerlines"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Here you can analyse the failing glaciers with the largest area and the type of error that has occurred!**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "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>rgi_area_km2</th>\n",
       "      <th>error_task</th>\n",
       "      <th>error_msg</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>rgi_id</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>RGI60-10.00002</th>\n",
       "      <td>48.144</td>\n",
       "      <td>simple_glacier_masks</td>\n",
       "      <td>GeometryError: RGI60-10.00002 is a nominal glacier.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>RGI60-19.01418</th>\n",
       "      <td>20.427</td>\n",
       "      <td>define_glacier_region</td>\n",
       "      <td>HttpDownloadError: (403, 'https://download.geoservice.dlr.de/TDM90/files/DEM/S75/W130/TDM1_DEM__30_S75W134.zip')</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>RGI60-10.00006</th>\n",
       "      <td>12.966</td>\n",
       "      <td>simple_glacier_masks</td>\n",
       "      <td>GeometryError: RGI60-10.00006 is a nominal glacier.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>RGI60-12.01364</th>\n",
       "      <td>9.250</td>\n",
       "      <td>simple_glacier_masks</td>\n",
       "      <td>GeometryError: RGI60-12.01364 is a nominal glacier.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>RGI60-09.00635</th>\n",
       "      <td>8.144</td>\n",
       "      <td>define_glacier_region</td>\n",
       "      <td>HttpDownloadError: (403, 'https://download.geoservice.dlr.de/TDM90/files/DEM/N79/E050/TDM1_DEM__30_N79E058.zip')</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                rgi_area_km2             error_task  \\\n",
       "rgi_id                                                \n",
       "RGI60-10.00002        48.144   simple_glacier_masks   \n",
       "RGI60-19.01418        20.427  define_glacier_region   \n",
       "RGI60-10.00006        12.966   simple_glacier_masks   \n",
       "RGI60-12.01364         9.250   simple_glacier_masks   \n",
       "RGI60-09.00635         8.144  define_glacier_region   \n",
       "\n",
       "                                                                                                                       error_msg  \n",
       "rgi_id                                                                                                                            \n",
       "RGI60-10.00002                                                               GeometryError: RGI60-10.00002 is a nominal glacier.  \n",
       "RGI60-19.01418  HttpDownloadError: (403, 'https://download.geoservice.dlr.de/TDM90/files/DEM/S75/W130/TDM1_DEM__30_S75W134.zip')  \n",
       "RGI60-10.00006                                                               GeometryError: RGI60-10.00006 is a nominal glacier.  \n",
       "RGI60-12.01364                                                               GeometryError: RGI60-12.01364 is a nominal glacier.  \n",
       "RGI60-09.00635  HttpDownloadError: (403, 'https://download.geoservice.dlr.de/TDM90/files/DEM/N79/E050/TDM1_DEM__30_N79E058.zip')  "
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dfserr['L2_elev_bands_b160_rgi_all'].head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "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>rgi_area_km2</th>\n",
       "      <th>error_task</th>\n",
       "      <th>error_msg</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>rgi_id</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>RGI60-19.01521</th>\n",
       "      <td>94.963</td>\n",
       "      <td>initialize_flowlines</td>\n",
       "      <td>RuntimeError: Altitude range of main flowline too small: 0.11659260120634536</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>RGI60-10.00002</th>\n",
       "      <td>48.144</td>\n",
       "      <td>glacier_masks</td>\n",
       "      <td>GeometryError: RGI60-10.00002 is a nominal glacier.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>RGI60-03.04079</th>\n",
       "      <td>35.752</td>\n",
       "      <td>initialize_flowlines</td>\n",
       "      <td>RuntimeError: Altitude range of main flowline too small: 2.0788404120956593e-05</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>RGI60-19.00780</th>\n",
       "      <td>25.152</td>\n",
       "      <td>initialize_flowlines</td>\n",
       "      <td>RuntimeError: Altitude range of main flowline too small: 0.0031179319468100314</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>RGI60-19.01418</th>\n",
       "      <td>20.427</td>\n",
       "      <td>define_glacier_region</td>\n",
       "      <td>HttpDownloadError: (403, 'https://download.geoservice.dlr.de/TDM90/files/DEM/S75/W130/TDM1_DEM__30_S75W134.zip')</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                rgi_area_km2             error_task  \\\n",
       "rgi_id                                                \n",
       "RGI60-19.01521        94.963   initialize_flowlines   \n",
       "RGI60-10.00002        48.144          glacier_masks   \n",
       "RGI60-03.04079        35.752   initialize_flowlines   \n",
       "RGI60-19.00780        25.152   initialize_flowlines   \n",
       "RGI60-19.01418        20.427  define_glacier_region   \n",
       "\n",
       "                                                                                                                       error_msg  \n",
       "rgi_id                                                                                                                            \n",
       "RGI60-19.01521                                      RuntimeError: Altitude range of main flowline too small: 0.11659260120634536  \n",
       "RGI60-10.00002                                                               GeometryError: RGI60-10.00002 is a nominal glacier.  \n",
       "RGI60-03.04079                                   RuntimeError: Altitude range of main flowline too small: 2.0788404120956593e-05  \n",
       "RGI60-19.00780                                    RuntimeError: Altitude range of main flowline too small: 0.0031179319468100314  \n",
       "RGI60-19.01418  HttpDownloadError: (403, 'https://download.geoservice.dlr.de/TDM90/files/DEM/S75/W130/TDM1_DEM__30_S75W134.zip')  "
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dfserr['L2_centerlines_b160_rgi_all'].head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let's just look at the level 2 errors for only RGI region 12 "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
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      "text/plain": [
       "<Figure size 1400x300 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "rgi_reg = '12'\n",
    "plt.figure(figsize=(14,3))\n",
    "plt.subplot(121)\n",
    "dfserr, pd_rel_error_area = error_analysis_w_plot(dfserr=dfserr, pd_rel_error_area=pd_rel_error_area, level='L2', subplot=True,\n",
    "                                                      exp='elev_bands', rgi_reg=rgi_reg,\n",
    "                                                      border=border, xlim = 400)\n",
    "plt.subplot(122)\n",
    "dfserr, pd_rel_error_area = error_analysis_w_plot(dfserr=dfserr, pd_rel_error_area=pd_rel_error_area, level='L2',  subplot=True,\n",
    "                                                      exp='centerlines', rgi_reg=rgi_reg,\n",
    "                                                      border=border, xlim = 400)\n",
    "plt.tight_layout()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "rgi_id\n",
       "RGI60-12.01364    GeometryError: RGI60-12.01364 is a nominal glacier.\n",
       "RGI60-12.01372    GeometryError: RGI60-12.01372 is a nominal glacier.\n",
       "RGI60-12.01374    GeometryError: RGI60-12.01374 is a nominal glacier.\n",
       "RGI60-12.01500    GeometryError: RGI60-12.01500 is a nominal glacier.\n",
       "RGI60-12.01443    GeometryError: RGI60-12.01443 is a nominal glacier.\n",
       "                                         ...                         \n",
       "RGI60-12.01628    GeometryError: RGI60-12.01628 is a nominal glacier.\n",
       "RGI60-12.01545    GeometryError: RGI60-12.01545 is a nominal glacier.\n",
       "RGI60-12.01546    GeometryError: RGI60-12.01546 is a nominal glacier.\n",
       "RGI60-12.01547    GeometryError: RGI60-12.01547 is a nominal glacier.\n",
       "RGI60-12.01350    GeometryError: RGI60-12.01350 is a nominal glacier.\n",
       "Name: error_msg, Length: 339, dtype: object"
      ]
     },
     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dfserr['L2_elev_bands_b160_rgi_12']['error_msg']"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "In RGI region 12, ~12% of the glacier area can not run even in pre-processing level 2. The reasons are glacier masks errors because many of the glaciers in RGI region 12 are \"nominal\" glaciers. Nominal means here that the glaciers don't have a glacier outline but only a location and area and hence can not be run with OGGM. "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Analysis for Level 5 pre-processing directories! \n",
    "\n",
    "In pre-processing level 5, we distinguish between:\n",
    "- different flowline types (exp = 'elev_bands' or 'centerlines', see the [Flowlines documentation](https://docs.oggm.org/en/stable/flowlines.html#glacier-flowlines))\n",
    "- different climate and precipitation factors (here: clim='CRU' with pcp='pcp2.5' or 'ERA5' with 'pcp1.6', or 'GSWP3_W5E5' with 'pcp2.5' or with varying prcp. fac depending on winter prcp.)\n",
    "- different ways to calibrate the mass balance (see [documentation on available mass-balance calibration methods](https://docs.oggm.org/en/latest/input-data.html#d-option-mass-balance-calibration-method)):\n",
    "    - match = \"no_match\" : only direct glaciological WGMS data used\n",
    "    - match = \"match_geod\" : same as no_match, but regionally the geodetic estimates are matched by changing epsilon\n",
    "    - match = \"match_geod_pergla\" : only per-glacier-individual geodetic estimates of Hugonnet et al. (2021) matched\n",
    "- applying the climate quality check and correction (qc='qc3') or not (qc='qc0'), see [historical_climate_qc](https://docs.oggm.org/en/latest/generated/oggm.tasks.historical_climate_qc.html#oggm.tasks.historical_climate_qc).\n",
    "    - at the moment we compare match_geod_pergla \"qc0\" and \"qc3\" although technically, after the newest OGGM release, there should be no difference in between. When we have preprocessed gdirs with match_geod_pergla with qc0, we will remove the match_geod_pergla qc3 gdirs as they will be outdated and should not be used. We will update the notebook afterwards!\n",
    "- using either the default shallow-ice approximation or a simple mass-redistribution (see: https://docs.oggm.org/en/latest/mass-redistribution.html). For the mass-redistribution, we only have one preprocessed glacier directory at the moment. You can check it out under:\n",
    "    - match = 'match_geod_pergla_massredis' (same as match_geod_pergla but with mass redistribution instead of SIA)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [],
   "source": [
    "level = 'L5'\n",
    "rgi_reg = 'all'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "19\n",
      "19\n",
      "19\n",
      "19\n"
     ]
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 2600x800 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(26,8))\n",
    "for j, clim in enumerate(['W5E5_spinup', 'W5E5']):\n",
    "    if j == 1:\n",
    "        plt.subplot(2,2,j*2+1) #, sharey=ax1)\n",
    "    else:\n",
    "        plt.subplot(2,2,j*2+1)\n",
    "    dfserr_median_prcp_fac, pd_rel_error_area = error_analysis_w_plot(dfserr=dfserr,\n",
    "                                                                      pd_rel_error_area = pd_rel_error_area,\n",
    "                              level=level, exp='elev_bands', #pcp = '2.6',\n",
    "                           match ='match_geod_pergla', clim=clim, \n",
    "                              version='2023.2', pcp='v1.6', border = 160,xlim=1000,\n",
    "                              rgi_reg = rgi_reg, \n",
    "                              path = '/home/www/oggm/gdirs/oggm_v1.6/', subplot = True, plot=True)\n",
    "    \n",
    "    ax1 = plt.gca()\n",
    "    \n",
    "    if j == 1:\n",
    "        plt.subplot(2,2,j*2+2) #, sharey=ax2)\n",
    "    else:\n",
    "        plt.subplot(2,2,j*2+2)\n",
    "    dfserr_median_prcp_fac, pd_rel_error_area = error_analysis_w_plot(dfserr=dfserr,\n",
    "                                                                      pd_rel_error_area = pd_rel_error_area,\n",
    "                              level=level, exp='elev_bands', #pcp = '2.6',\n",
    "                           match ='match_geod_pergla', clim=clim, \n",
    "                              version='2023.3', pcp='v1.6', border = 160,xlim=1000,\n",
    "                              rgi_reg = rgi_reg, \n",
    "                              path = '/home/www/oggm/gdirs/oggm_v1.6/', subplot = True, plot=True)\n",
    "    ax2 = plt.gca()\n",
    "    \n",
    "plt.tight_layout()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "19\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 2000x400 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(20,4))\n",
    "plt.subplot(1,2,1)\n",
    "dfserr_median_prcp_fac, pd_rel_error_area = error_analysis_w_plot(dfserr=dfserr, pd_rel_error_area = pd_rel_error_area,\n",
    "                          level=level, exp='elev_bands', #pcp = '2.6',\n",
    "                       match ='match_geod_pergla', clim='W5E5_spinup', \n",
    "                          version='2023.2', pcp='v1.6', border = 160,xlim=3800,\n",
    "                          rgi_reg = rgi_reg, \n",
    "                          path = '/home/www/oggm/gdirs/oggm_v1.6/', subplot = True, plot=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Let's get all level 5 statistics (for both, qc0 and qc3!)\n",
    "pd_rel_error_area_L5 = pd_rel_error_area[(pd_rel_error_area.level == 'L5') & (pd_rel_error_area.rgi_reg =='all')]\n",
    "condi1 = (pd_rel_error_area_L5.border == 160) \n",
    "pd_rel_error_area_L5 = pd_rel_error_area_L5[condi1] #| condi2]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<a id='id-total-error-area-summary'></a>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "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>rel_error_area_in_percent</th>\n",
       "      <th>level</th>\n",
       "      <th>exp</th>\n",
       "      <th>clim_pcp</th>\n",
       "      <th>match</th>\n",
       "      <th>qc</th>\n",
       "      <th>border</th>\n",
       "      <th>rgi_reg</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "Empty DataFrame\n",
       "Columns: [rel_error_area_in_percent, level, exp, clim_pcp, match, qc, border, rgi_reg]\n",
       "Index: []"
      ]
     },
     "execution_count": 43,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd_rel_error_area_L5"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "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>rel_error_area_in_percent</th>\n",
       "      <th>level</th>\n",
       "      <th>exp</th>\n",
       "      <th>clim_pcp</th>\n",
       "      <th>match</th>\n",
       "      <th>qc</th>\n",
       "      <th>border</th>\n",
       "      <th>rgi_reg</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>L2_elev_bands_b160_rgi_all</th>\n",
       "      <td>0.052851</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>160.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>L2_centerlines_b160_rgi_all</th>\n",
       "      <td>0.086374</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>160.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>L5_elev_bands_v1.6_W5E5_spinup_match_geod_pergla__b160_rgi_all_version_2023.2</th>\n",
       "      <td>0.095824</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>160.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>L5_elev_bands_v1.6_W5E5_spinup_match_geod_pergla__b160_rgi_all_version_2023.3</th>\n",
       "      <td>0.098552</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>160.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>L5_elev_bands_v1.6_W5E5_match_geod_pergla__b160_rgi_all_version_2023.2</th>\n",
       "      <td>0.095310</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>160.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>L5_elev_bands_v1.6_W5E5_match_geod_pergla__b160_rgi_all_version_2023.3</th>\n",
       "      <td>0.095310</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>NaN</td>\n",
       "      <td>160.0</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                                                                               rel_error_area_in_percent  \\\n",
       "L2_elev_bands_b160_rgi_all                                                                      0.052851   \n",
       "L2_centerlines_b160_rgi_all                                                                     0.086374   \n",
       "L5_elev_bands_v1.6_W5E5_spinup_match_geod_pergla__b160_rgi_all_version_2023.2                   0.095824   \n",
       "L5_elev_bands_v1.6_W5E5_spinup_match_geod_pergla__b160_rgi_all_version_2023.3                   0.098552   \n",
       "L5_elev_bands_v1.6_W5E5_match_geod_pergla__b160_rgi_all_version_2023.2                          0.095310   \n",
       "L5_elev_bands_v1.6_W5E5_match_geod_pergla__b160_rgi_all_version_2023.3                          0.095310   \n",
       "\n",
       "                                                                               level  \\\n",
       "L2_elev_bands_b160_rgi_all                                                       NaN   \n",
       "L2_centerlines_b160_rgi_all                                                      NaN   \n",
       "L5_elev_bands_v1.6_W5E5_spinup_match_geod_pergla__b160_rgi_all_version_2023.2    NaN   \n",
       "L5_elev_bands_v1.6_W5E5_spinup_match_geod_pergla__b160_rgi_all_version_2023.3    NaN   \n",
       "L5_elev_bands_v1.6_W5E5_match_geod_pergla__b160_rgi_all_version_2023.2           NaN   \n",
       "L5_elev_bands_v1.6_W5E5_match_geod_pergla__b160_rgi_all_version_2023.3           NaN   \n",
       "\n",
       "                                                                               exp  \\\n",
       "L2_elev_bands_b160_rgi_all                                                     NaN   \n",
       "L2_centerlines_b160_rgi_all                                                    NaN   \n",
       "L5_elev_bands_v1.6_W5E5_spinup_match_geod_pergla__b160_rgi_all_version_2023.2  NaN   \n",
       "L5_elev_bands_v1.6_W5E5_spinup_match_geod_pergla__b160_rgi_all_version_2023.3  NaN   \n",
       "L5_elev_bands_v1.6_W5E5_match_geod_pergla__b160_rgi_all_version_2023.2         NaN   \n",
       "L5_elev_bands_v1.6_W5E5_match_geod_pergla__b160_rgi_all_version_2023.3         NaN   \n",
       "\n",
       "                                                                               clim_pcp  \\\n",
       "L2_elev_bands_b160_rgi_all                                                          NaN   \n",
       "L2_centerlines_b160_rgi_all                                                         NaN   \n",
       "L5_elev_bands_v1.6_W5E5_spinup_match_geod_pergla__b160_rgi_all_version_2023.2       NaN   \n",
       "L5_elev_bands_v1.6_W5E5_spinup_match_geod_pergla__b160_rgi_all_version_2023.3       NaN   \n",
       "L5_elev_bands_v1.6_W5E5_match_geod_pergla__b160_rgi_all_version_2023.2              NaN   \n",
       "L5_elev_bands_v1.6_W5E5_match_geod_pergla__b160_rgi_all_version_2023.3              NaN   \n",
       "\n",
       "                                                                               match  \\\n",
       "L2_elev_bands_b160_rgi_all                                                       NaN   \n",
       "L2_centerlines_b160_rgi_all                                                      NaN   \n",
       "L5_elev_bands_v1.6_W5E5_spinup_match_geod_pergla__b160_rgi_all_version_2023.2    NaN   \n",
       "L5_elev_bands_v1.6_W5E5_spinup_match_geod_pergla__b160_rgi_all_version_2023.3    NaN   \n",
       "L5_elev_bands_v1.6_W5E5_match_geod_pergla__b160_rgi_all_version_2023.2           NaN   \n",
       "L5_elev_bands_v1.6_W5E5_match_geod_pergla__b160_rgi_all_version_2023.3           NaN   \n",
       "\n",
       "                                                                               qc  \\\n",
       "L2_elev_bands_b160_rgi_all                                                    NaN   \n",
       "L2_centerlines_b160_rgi_all                                                   NaN   \n",
       "L5_elev_bands_v1.6_W5E5_spinup_match_geod_pergla__b160_rgi_all_version_2023.2 NaN   \n",
       "L5_elev_bands_v1.6_W5E5_spinup_match_geod_pergla__b160_rgi_all_version_2023.3 NaN   \n",
       "L5_elev_bands_v1.6_W5E5_match_geod_pergla__b160_rgi_all_version_2023.2        NaN   \n",
       "L5_elev_bands_v1.6_W5E5_match_geod_pergla__b160_rgi_all_version_2023.3        NaN   \n",
       "\n",
       "                                                                               border  \\\n",
       "L2_elev_bands_b160_rgi_all                                                      160.0   \n",
       "L2_centerlines_b160_rgi_all                                                     160.0   \n",
       "L5_elev_bands_v1.6_W5E5_spinup_match_geod_pergla__b160_rgi_all_version_2023.2   160.0   \n",
       "L5_elev_bands_v1.6_W5E5_spinup_match_geod_pergla__b160_rgi_all_version_2023.3   160.0   \n",
       "L5_elev_bands_v1.6_W5E5_match_geod_pergla__b160_rgi_all_version_2023.2          160.0   \n",
       "L5_elev_bands_v1.6_W5E5_match_geod_pergla__b160_rgi_all_version_2023.3          160.0   \n",
       "\n",
       "                                                                               rgi_reg  \n",
       "L2_elev_bands_b160_rgi_all                                                         NaN  \n",
       "L2_centerlines_b160_rgi_all                                                        NaN  \n",
       "L5_elev_bands_v1.6_W5E5_spinup_match_geod_pergla__b160_rgi_all_version_2023.2      NaN  \n",
       "L5_elev_bands_v1.6_W5E5_spinup_match_geod_pergla__b160_rgi_all_version_2023.3      NaN  \n",
       "L5_elev_bands_v1.6_W5E5_match_geod_pergla__b160_rgi_all_version_2023.2             NaN  \n",
       "L5_elev_bands_v1.6_W5E5_match_geod_pergla__b160_rgi_all_version_2023.3             NaN  "
      ]
     },
     "execution_count": 42,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd_rel_error_area"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/tmp/ipykernel_466059/2060589157.py:10: UserWarning: Boolean Series key will be reindexed to match DataFrame index.\n",
      "  pd_rel_error_area_L5 = pd_rel_error_area_L5[(condi1 |condi2|condi3)]\n"
     ]
    }
   ],
   "source": [
    "# Let's get all level 5 statistics (for both, qc0 and qc3!)\n",
    "pd_rel_error_area_L5 = pd_rel_error_area[(pd_rel_error_area.level == 'L5') & (pd_rel_error_area.rgi_reg =='all_without_19')]\n",
    "# we only use border = 80 for qc0 as this is the option where most preprocessed directories are available\n",
    "condi1 = ((pd_rel_error_area_L5.border == 80) & (pd_rel_error_area_L5.qc=='qc0'))\n",
    "# we only use border = 160 for qc3 as this is the option where most preprocessed directories are available\n",
    "condi2 = ((pd_rel_error_area_L5.border == 160) & (pd_rel_error_area_L5.qc=='qc3'))\n",
    "# \n",
    "condi3 = (('GSWP3_W5E5_2.6' == pd_rel_error_area['clim_pcp']) | ('GSWP3_W5E5_via_winterprcp' == pd_rel_error_area['clim_pcp']))\n",
    "\n",
    "pd_rel_error_area_L5 = pd_rel_error_area_L5[(condi1 |condi2|condi3)]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Method to get those glaciers that work for all preprocessed glacier directories? This is important when later trying to compare volume estimates between each other!"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [],
   "source": [
    "pd_geodetic = utils.get_geodetic_mb_dataframe()[utils.get_geodetic_mb_dataframe().period=='2000-01-01_2020-01-01']\n",
    "# we do not model RGI region 19 because we want to compare it to CRU!!! \n",
    "pd_geodetic = pd_geodetic[pd_geodetic.reg != 19]\n",
    "\n",
    "total_area = pd_geodetic.area.sum()\n",
    "total_counts = len(pd_geodetic)\n",
    "# pd_geodetic.area\n",
    "pd_working = pd.DataFrame(index = pd_geodetic.index,\n",
    "                        columns=dfserr.keys())\n",
    "# we will set those that are not running afterwards to np.NaN value\n",
    "pd_working.loc[pd_geodetic.index] = True\n",
    "pd_working['area'] = pd_geodetic.area\n",
    "pd_working['all_running_rgis'] = np.NaN\n",
    "pd_working['rgi_reg'] = pd_geodetic.reg\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [],
   "source": [
    "for key in dfserr.keys():\n",
    "    if 'rgi_all_without_19' in key: \n",
    "        failing_rgis = dfserr[key].index.values\n",
    "\n",
    "\n",
    "\n",
    "        # pd_error[cmip6_output_type] = False\n",
    "        # set those glaciers that did not work to np.NaN\n",
    "        pd_working.loc[failing_rgis,key] = np.NaN\n",
    "        \n",
    "        # check if it worked\n",
    "        assert len(failing_rgis) == len(pd_working.loc[pd_working[key].isna()])\n",
    "    else:\n",
    "        pd_working = pd_working.drop(columns=key)\n",
    "        pass\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {},
   "outputs": [],
   "source": [
    "all_running_rgis = pd_working[pd_working.columns[:-3]].dropna().index"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {},
   "outputs": [],
   "source": [
    "pd_working.loc[all_running_rgis, 'all_running_rgis'] = True\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Amount of glaciers (without Antarctica RGI region 19) that run without glaciers for all compared preprocessed gdirs: 212795\n",
      "Relative percentage of glacier amount where all analysed L5 preprocessed gdirs do not fail: 100.00%\n",
      "Relative percentage of glacier area where all analysed L5 preprocessed gdirs do not fail: 100.00%\n"
     ]
    }
   ],
   "source": [
    "all_running_rel = len(all_running_rgis)*100/len(pd_geodetic)\n",
    "all_running_rel_area = pd_working.loc[all_running_rgis].area.sum()*100/pd_working.area.sum()\n",
    "\n",
    "print(f'Amount of glaciers (without Antarctica RGI region 19) that run without glaciers for all compared preprocessed gdirs: {len(all_running_rgis)}')\n",
    "print(f'Relative percentage of glacier amount where all analysed L5 preprocessed gdirs do not fail: {all_running_rel:0.2f}%')\n",
    "print(f'Relative percentage of glacier area where all analysed L5 preprocessed gdirs do not fail: {all_running_rel_area:0.2f}%')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Amount of glaciers (without Antarctica RGI region 19) that run without glaciers for all compared preprocessed gdirs: 200674\n",
      "Relative percentage of glacier amount where all analysed L5 preprocessed gdirs do not fail: 94.30%\n",
      "Relative percentage of glacier area where all analysed L5 preprocessed gdirs do not fail: 93.82%\n"
     ]
    }
   ],
   "source": [
    "all_running_rel = len(all_running_rgis)*100/len(pd_geodetic)\n",
    "all_running_rel_area = pd_working.loc[all_running_rgis].area.sum()*100/pd_working.area.sum()\n",
    "\n",
    "print(f'Amount of glaciers (without Antarctica RGI region 19) that run without glaciers for all compared preprocessed gdirs: {len(all_running_rgis)}')\n",
    "print(f'Relative percentage of glacier amount where all analysed L5 preprocessed gdirs do not fail: {all_running_rel:0.2f}%')\n",
    "print(f'Relative percentage of glacier area where all analysed L5 preprocessed gdirs do not fail: {all_running_rel_area:0.2f}%')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "metadata": {},
   "outputs": [],
   "source": [
    "pd_rel_error_area_L5.to_csv('rel_error_area_statistics_for_prepro_level5_gdirs.csv')\n",
    "pd_working.to_csv('working_rgis_for_prepro_level5_gdirs.csv')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We will use it in [this notebook which analyses the volume, mass change and specific mass balance differences between the preprocessed gdir options](https://nbviewer.org/urls/cluster.klima.uni-bremen.de/~lschuster/error_analysis/working_glacier_gdirs_comparison.ipynb). Feel free to check it out afterwards!"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Regional RGI error check for the different options:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0\n",
      "19\n",
      "0\n",
      "19\n",
      "19\n",
      "0\n",
      "19\n",
      "0\n"
     ]
    }
   ],
   "source": [
    "level = 'L5'\n",
    "exp = 'elev_bands' #, 'centerlines']:\n",
    "\n",
    "dfserr_reg = {}\n",
    "pd_rel_error_area_reg = pd.DataFrame(columns=['rel_error_area_in_percent', 'level', 'exp',\n",
    "                                              'clim_pcp', 'match', 'qc', 'border', 'rgi_reg'])\n",
    "\n",
    "missing = []\n",
    "# different match options only available for elev_bands\n",
    "for pcp, clim in zip(pcps, clims):\n",
    "    for match in ['no_match', 'match_geod', 'match_geod_pergla', 'match_geod_pergla_massredis']:  # \n",
    "        for qc in ['qc0', 'qc3']:\n",
    "            for rgi_reg in np.arange(0,21,1):\n",
    "                if 0<rgi_reg <10:\n",
    "                    rgi_reg = f'0{rgi_reg}'\n",
    "                elif rgi_reg == 20:\n",
    "                    rgi_reg = 'all'\n",
    "                else:\n",
    "                    rgi_reg = str(rgi_reg)\n",
    "                if qc == 'qc0':\n",
    "                    border = 80\n",
    "                else:\n",
    "                    border = 160\n",
    "                try:\n",
    "                    # todo remove this, when all preprocessed gdirs are inside of main oggm \n",
    "                    if 'match_geod_pergla' in match:\n",
    "                        path = '/home/www/oggm/gdirs/oggm_v1.6/'\n",
    "                    else:\n",
    "                        path = '/home/www/oggm/gdirs/oggm_v1.4/'\n",
    "                    dfserr_reg, pd_rel_error_area_reg = error_analysis_w_plot(dfserr=dfserr_reg, pd_rel_error_area=pd_rel_error_area_reg,\n",
    "                                                                      level=level,exp=exp, pcp =pcp, clim=clim, \n",
    "                                                                      qc=qc,border=border, match=match, path=path,\n",
    "                                                                      rgi_reg=rgi_reg, plot = False)\n",
    "\n",
    "                except:\n",
    "                    missing.append(f'{level}_{exp}_{pcp}_{clim}_{match}_{qc}_b{border}_rgi_{rgi_reg}')\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "metadata": {},
   "outputs": [],
   "source": [
    "pd_rel_error_area_reg_qc0 = pd_rel_error_area_reg[pd_rel_error_area_reg.qc == 'qc0']\n",
    "pd_rel_error_area_reg_qc0 = pd_rel_error_area_reg_qc0.loc[(pd_rel_error_area_reg_qc0.rgi_reg != '19') & (pd_rel_error_area_reg_qc0.rgi_reg != 'all')]\n",
    "pd_rel_error_area_reg_qc0 = pd_rel_error_area_reg_qc0.loc[pd_rel_error_area_reg_qc0.border == 80]\n",
    "pd_rel_error_area_reg_qc0 = pd_rel_error_area_reg_qc0.loc[pd_rel_error_area_reg_qc0.clim_pcp == 'CRU_pcp2.5']\n",
    "pd_rel_error_area_reg_qc0.index = pd_rel_error_area_reg_qc0['rgi_reg']\n",
    "pd_rel_error_area_reg_qc0 = pd_rel_error_area_reg_qc0[['rel_error_area_in_percent','match']]\n",
    "pd_rel_error_area_reg_qc0 = pd_rel_error_area_reg_qc0.pivot(columns=['match'])\n",
    "pd_rel_error_area_reg_qc0.columns = pd_rel_error_area_reg_qc0.columns.droplevel(0)\n",
    "pd_rel_error_area_reg_qc0 = pd_rel_error_area_reg_qc0.astype(\"float32\")\n",
    "pd_rel_error_area_reg_qc0 = pd_rel_error_area_reg_qc0[['no_match', 'match_geod', 'match_geod_pergla', 'match_geod_pergla_massredis']]\n",
    "pd_rel_error_area_reg_qc0 = pd_rel_error_area_reg_qc0.rename({'all_without_19':'all'})\n",
    "pd_rel_error_area_reg_qc0= pd_rel_error_area_reg_qc0.rename(columns={'match_geod_pergla_massredis': 'match_geod_pergla\\nmassredis'})\n",
    "\n",
    "pd_rel_error_area_reg_qc3 = pd_rel_error_area_reg[pd_rel_error_area_reg.qc == 'qc3']\n",
    "pd_rel_error_area_reg_qc3 = pd_rel_error_area_reg_qc3.loc[pd_rel_error_area_reg_qc3.border == 160]\n",
    "pd_rel_error_area_reg_qc3 = pd_rel_error_area_reg_qc3.loc[(pd_rel_error_area_reg_qc3.rgi_reg != '19') & (pd_rel_error_area_reg_qc3.rgi_reg != 'all')]\n",
    "pd_rel_error_area_reg_qc3 = pd_rel_error_area_reg_qc3.loc[pd_rel_error_area_reg_qc3.clim_pcp == 'CRU_pcp2.5']\n",
    "pd_rel_error_area_reg_qc3.index = pd_rel_error_area_reg_qc3['rgi_reg']\n",
    "pd_rel_error_area_reg_qc3 = pd_rel_error_area_reg_qc3[['rel_error_area_in_percent','match']]\n",
    "pd_rel_error_area_reg_qc3 = pd_rel_error_area_reg_qc3.pivot(columns=['match'])\n",
    "pd_rel_error_area_reg_qc3.columns = pd_rel_error_area_reg_qc3.columns.droplevel(0)\n",
    "pd_rel_error_area_reg_qc3 = pd_rel_error_area_reg_qc3.astype(\"float32\")\n",
    "pd_rel_error_area_reg_qc3 = pd_rel_error_area_reg_qc3[['no_match', 'match_geod']] #, 'match_geod_pergla']]\n",
    "pd_rel_error_area_reg_qc3 = pd_rel_error_area_reg_qc3.rename({'all_without_19':'all'})"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<a id='id-rgi-diff'></a>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 2016x720 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.set(font_scale = 1.3)\n",
    "plt.figure(figsize=(28,10))\n",
    "plt.suptitle(f'Relative failing glacier area per RGI region (using {clim})', fontsize=24)\n",
    "plt.subplot(121)\n",
    "plt.title('using no climate check and correction (qc0)', fontsize=22)\n",
    "sns.heatmap(pd_rel_error_area_reg_qc0,\n",
    "            linewidths=.5, cmap=\"PuRd\", cbar_kws={'label':'relative failing glacier area (in %)'},\n",
    "           annot=True, fmt=\".2f\")\n",
    "ax = plt.gca()\n",
    "ax.figure.axes[-1].yaxis.label.set_size(18)\n",
    "ax.set_ylabel('RGI region (without RGI region 19)', fontsize=20);\n",
    "ax.set_xlabel('MB calibration type or other methods', fontsize=20)\n",
    "plt.subplot(122)\n",
    "plt.title('difference between qc0 and qc3', fontsize=22)\n",
    "\n",
    "sns.heatmap(pd_rel_error_area_reg_qc0.drop(columns=['match_geod_pergla','match_geod_pergla\\nmassredis']) - pd_rel_error_area_reg_qc3,\n",
    "            linewidths=.5, cmap='coolwarm', \n",
    "            cbar_kws={'label':'relative failing glacier area difference (in %)\\n (qc0-qc3)'},\n",
    "           annot=True,center=0, fmt=\".2f\")\n",
    "ax = plt.gca()\n",
    "ax.figure.axes[-1].yaxis.label.set_size(18)\n",
    "ax.set_ylabel('');\n",
    "ax.set_xlabel('MB calibration type', fontsize=20)\n",
    "\n",
    "plt.tight_layout()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "- `no_match` and `match_geod` have almost the same amount of relative failing glacier area\n",
    "- with `qc0`, most relative glacier area fails in:\n",
    "    - RGI region 5, 16, 17, 10 (descending order) with more MB calibration errors if using the no_match or match_geod options!\n",
    "    - RGI region 12 mostly from missing outlines of nominal glaciers\n",
    "    - RGI region 13 if using the match_geod_pergla method (no mu* could be found even when correcting the climate, which happens in that case for both qc0 and qc3!)\n",
    "- differences between qc0 and qc3:\n",
    "    - only in RGI region 5 (Greenland) more glaciers fail when using qc3, but RGI region 5 is the RGI region with the largest glacier area!!!\n",
    "    - for all other RGI regions, more glaciers fail with qc0 (specifically for RGI region 16 & 10, where there are more MB calibration errors for qc0 than for qc3)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**Let's also estimate the regional missing area for the W5E5 preprocessed gdirs:**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "19\n",
      "19\n"
     ]
    }
   ],
   "source": [
    "for match, pcp in zip(['match_geod_pergla_winterprcp', 'match_geod_pergla_2.6'],['via_winterprcp', '2.6']):\n",
    "    for rgi_reg in np.arange(0,21,1):\n",
    "        if 0<rgi_reg <10:\n",
    "            rgi_reg = f'0{rgi_reg}'\n",
    "        elif rgi_reg == 0:\n",
    "            rgi_reg = 'all_without_19'\n",
    "        elif rgi_reg == 20:\n",
    "            rgi_reg = 'all'\n",
    "        else:\n",
    "            rgi_reg = str(rgi_reg)\n",
    "        dfserr_reg, pd_rel_error_area_reg = error_analysis_w_plot(dfserr=dfserr_reg, pd_rel_error_area=pd_rel_error_area_reg, rename_match=True,\n",
    "                  level='L5', exp='elev_bands', pcp = pcp,\n",
    "                      match =match, clim='GSWP3_W5E5', \n",
    "                      qc = 'qc0', border = 160,\n",
    "                      rgi_reg = rgi_reg, \n",
    "                      path = '/home/www/fmaussion/runs/new_gdirs/oggm_v1.6/', subplot = False, xlim=None, plot=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "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>rel_error_area_in_percent</th>\n",
       "      <th>level</th>\n",
       "      <th>exp</th>\n",
       "      <th>clim_pcp</th>\n",
       "      <th>match</th>\n",
       "      <th>qc</th>\n",
       "      <th>border</th>\n",
       "      <th>rgi_reg</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>L5_elev_bands_pcp2.5_CRU_no_match_qc0_b80_rgi_all_without_19</th>\n",
       "      <td>2.345166</td>\n",
       "      <td>L5</td>\n",
       "      <td>elev_bands</td>\n",
       "      <td>CRU_pcp2.5</td>\n",
       "      <td>no_match</td>\n",
       "      <td>qc0</td>\n",
       "      <td>80</td>\n",
       "      <td>all_without_19</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>L5_elev_bands_pcp2.5_CRU_no_match_qc0_b80_rgi_01</th>\n",
       "      <td>0.114866</td>\n",
       "      <td>L5</td>\n",
       "      <td>elev_bands</td>\n",
       "      <td>CRU_pcp2.5</td>\n",
       "      <td>no_match</td>\n",
       "      <td>qc0</td>\n",
       "      <td>80</td>\n",
       "      <td>01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>L5_elev_bands_pcp2.5_CRU_no_match_qc0_b80_rgi_02</th>\n",
       "      <td>0.01733</td>\n",
       "      <td>L5</td>\n",
       "      <td>elev_bands</td>\n",
       "      <td>CRU_pcp2.5</td>\n",
       "      <td>no_match</td>\n",
       "      <td>qc0</td>\n",
       "      <td>80</td>\n",
       "      <td>02</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>L5_elev_bands_pcp2.5_CRU_no_match_qc0_b80_rgi_03</th>\n",
       "      <td>0.799821</td>\n",
       "      <td>L5</td>\n",
       "      <td>elev_bands</td>\n",
       "      <td>CRU_pcp2.5</td>\n",
       "      <td>no_match</td>\n",
       "      <td>qc0</td>\n",
       "      <td>80</td>\n",
       "      <td>03</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>L5_elev_bands_pcp2.5_CRU_no_match_qc0_b80_rgi_04</th>\n",
       "      <td>0.039192</td>\n",
       "      <td>L5</td>\n",
       "      <td>elev_bands</td>\n",
       "      <td>CRU_pcp2.5</td>\n",
       "      <td>no_match</td>\n",
       "      <td>qc0</td>\n",
       "      <td>80</td>\n",
       "      <td>04</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>L5_elev_bands_2.6_GSWP3_W5E5_match_geod_pergla_2.6_qc0_b160_rgi_16</th>\n",
       "      <td>0.064843</td>\n",
       "      <td>L5</td>\n",
       "      <td>elev_bands</td>\n",
       "      <td>GSWP3_W5E5_2.6</td>\n",
       "      <td>match_geod_pergla</td>\n",
       "      <td>qc0</td>\n",
       "      <td>160</td>\n",
       "      <td>16</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>L5_elev_bands_2.6_GSWP3_W5E5_match_geod_pergla_2.6_qc0_b160_rgi_17</th>\n",
       "      <td>4.867621</td>\n",
       "      <td>L5</td>\n",
       "      <td>elev_bands</td>\n",
       "      <td>GSWP3_W5E5_2.6</td>\n",
       "      <td>match_geod_pergla</td>\n",
       "      <td>qc0</td>\n",
       "      <td>160</td>\n",
       "      <td>17</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>L5_elev_bands_2.6_GSWP3_W5E5_match_geod_pergla_2.6_qc0_b160_rgi_18</th>\n",
       "      <td>0.0</td>\n",
       "      <td>L5</td>\n",
       "      <td>elev_bands</td>\n",
       "      <td>GSWP3_W5E5_2.6</td>\n",
       "      <td>match_geod_pergla</td>\n",
       "      <td>qc0</td>\n",
       "      <td>160</td>\n",
       "      <td>18</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>L5_elev_bands_2.6_GSWP3_W5E5_match_geod_pergla_2.6_qc0_b160_rgi_19</th>\n",
       "      <td>0.211799</td>\n",
       "      <td>L5</td>\n",
       "      <td>elev_bands</td>\n",
       "      <td>GSWP3_W5E5_2.6</td>\n",
       "      <td>match_geod_pergla</td>\n",
       "      <td>qc0</td>\n",
       "      <td>160</td>\n",
       "      <td>19</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>L5_elev_bands_2.6_GSWP3_W5E5_match_geod_pergla_2.6_qc0_b160_rgi_all</th>\n",
       "      <td>0.810195</td>\n",
       "      <td>L5</td>\n",
       "      <td>elev_bands</td>\n",
       "      <td>GSWP3_W5E5_2.6</td>\n",
       "      <td>match_geod_pergla</td>\n",
       "      <td>qc0</td>\n",
       "      <td>160</td>\n",
       "      <td>all</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>240 rows × 8 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                                                                    rel_error_area_in_percent  \\\n",
       "L5_elev_bands_pcp2.5_CRU_no_match_qc0_b80_rgi_all_without_19                         2.345166   \n",
       "L5_elev_bands_pcp2.5_CRU_no_match_qc0_b80_rgi_01                                     0.114866   \n",
       "L5_elev_bands_pcp2.5_CRU_no_match_qc0_b80_rgi_02                                      0.01733   \n",
       "L5_elev_bands_pcp2.5_CRU_no_match_qc0_b80_rgi_03                                     0.799821   \n",
       "L5_elev_bands_pcp2.5_CRU_no_match_qc0_b80_rgi_04                                     0.039192   \n",
       "...                                                                                       ...   \n",
       "L5_elev_bands_2.6_GSWP3_W5E5_match_geod_pergla_2.6_qc0_b160_rgi_16                   0.064843   \n",
       "L5_elev_bands_2.6_GSWP3_W5E5_match_geod_pergla_2.6_qc0_b160_rgi_17                   4.867621   \n",
       "L5_elev_bands_2.6_GSWP3_W5E5_match_geod_pergla_2.6_qc0_b160_rgi_18                        0.0   \n",
       "L5_elev_bands_2.6_GSWP3_W5E5_match_geod_pergla_2.6_qc0_b160_rgi_19                   0.211799   \n",
       "L5_elev_bands_2.6_GSWP3_W5E5_match_geod_pergla_2.6_qc0_b160_rgi_all                  0.810195   \n",
       "\n",
       "                                                                    level  \\\n",
       "L5_elev_bands_pcp2.5_CRU_no_match_qc0_b80_rgi_all_without_19           L5   \n",
       "L5_elev_bands_pcp2.5_CRU_no_match_qc0_b80_rgi_01                       L5   \n",
       "L5_elev_bands_pcp2.5_CRU_no_match_qc0_b80_rgi_02                       L5   \n",
       "L5_elev_bands_pcp2.5_CRU_no_match_qc0_b80_rgi_03                       L5   \n",
       "L5_elev_bands_pcp2.5_CRU_no_match_qc0_b80_rgi_04                       L5   \n",
       "...                                                                   ...   \n",
       "L5_elev_bands_2.6_GSWP3_W5E5_match_geod_pergla_2.6_qc0_b160_rgi_16     L5   \n",
       "L5_elev_bands_2.6_GSWP3_W5E5_match_geod_pergla_2.6_qc0_b160_rgi_17     L5   \n",
       "L5_elev_bands_2.6_GSWP3_W5E5_match_geod_pergla_2.6_qc0_b160_rgi_18     L5   \n",
       "L5_elev_bands_2.6_GSWP3_W5E5_match_geod_pergla_2.6_qc0_b160_rgi_19     L5   \n",
       "L5_elev_bands_2.6_GSWP3_W5E5_match_geod_pergla_2.6_qc0_b160_rgi_all    L5   \n",
       "\n",
       "                                                                            exp  \\\n",
       "L5_elev_bands_pcp2.5_CRU_no_match_qc0_b80_rgi_all_without_19         elev_bands   \n",
       "L5_elev_bands_pcp2.5_CRU_no_match_qc0_b80_rgi_01                     elev_bands   \n",
       "L5_elev_bands_pcp2.5_CRU_no_match_qc0_b80_rgi_02                     elev_bands   \n",
       "L5_elev_bands_pcp2.5_CRU_no_match_qc0_b80_rgi_03                     elev_bands   \n",
       "L5_elev_bands_pcp2.5_CRU_no_match_qc0_b80_rgi_04                     elev_bands   \n",
       "...                                                                         ...   \n",
       "L5_elev_bands_2.6_GSWP3_W5E5_match_geod_pergla_2.6_qc0_b160_rgi_16   elev_bands   \n",
       "L5_elev_bands_2.6_GSWP3_W5E5_match_geod_pergla_2.6_qc0_b160_rgi_17   elev_bands   \n",
       "L5_elev_bands_2.6_GSWP3_W5E5_match_geod_pergla_2.6_qc0_b160_rgi_18   elev_bands   \n",
       "L5_elev_bands_2.6_GSWP3_W5E5_match_geod_pergla_2.6_qc0_b160_rgi_19   elev_bands   \n",
       "L5_elev_bands_2.6_GSWP3_W5E5_match_geod_pergla_2.6_qc0_b160_rgi_all  elev_bands   \n",
       "\n",
       "                                                                           clim_pcp  \\\n",
       "L5_elev_bands_pcp2.5_CRU_no_match_qc0_b80_rgi_all_without_19             CRU_pcp2.5   \n",
       "L5_elev_bands_pcp2.5_CRU_no_match_qc0_b80_rgi_01                         CRU_pcp2.5   \n",
       "L5_elev_bands_pcp2.5_CRU_no_match_qc0_b80_rgi_02                         CRU_pcp2.5   \n",
       "L5_elev_bands_pcp2.5_CRU_no_match_qc0_b80_rgi_03                         CRU_pcp2.5   \n",
       "L5_elev_bands_pcp2.5_CRU_no_match_qc0_b80_rgi_04                         CRU_pcp2.5   \n",
       "...                                                                             ...   \n",
       "L5_elev_bands_2.6_GSWP3_W5E5_match_geod_pergla_2.6_qc0_b160_rgi_16   GSWP3_W5E5_2.6   \n",
       "L5_elev_bands_2.6_GSWP3_W5E5_match_geod_pergla_2.6_qc0_b160_rgi_17   GSWP3_W5E5_2.6   \n",
       "L5_elev_bands_2.6_GSWP3_W5E5_match_geod_pergla_2.6_qc0_b160_rgi_18   GSWP3_W5E5_2.6   \n",
       "L5_elev_bands_2.6_GSWP3_W5E5_match_geod_pergla_2.6_qc0_b160_rgi_19   GSWP3_W5E5_2.6   \n",
       "L5_elev_bands_2.6_GSWP3_W5E5_match_geod_pergla_2.6_qc0_b160_rgi_all  GSWP3_W5E5_2.6   \n",
       "\n",
       "                                                                                 match  \\\n",
       "L5_elev_bands_pcp2.5_CRU_no_match_qc0_b80_rgi_all_without_19                  no_match   \n",
       "L5_elev_bands_pcp2.5_CRU_no_match_qc0_b80_rgi_01                              no_match   \n",
       "L5_elev_bands_pcp2.5_CRU_no_match_qc0_b80_rgi_02                              no_match   \n",
       "L5_elev_bands_pcp2.5_CRU_no_match_qc0_b80_rgi_03                              no_match   \n",
       "L5_elev_bands_pcp2.5_CRU_no_match_qc0_b80_rgi_04                              no_match   \n",
       "...                                                                                ...   \n",
       "L5_elev_bands_2.6_GSWP3_W5E5_match_geod_pergla_2.6_qc0_b160_rgi_16   match_geod_pergla   \n",
       "L5_elev_bands_2.6_GSWP3_W5E5_match_geod_pergla_2.6_qc0_b160_rgi_17   match_geod_pergla   \n",
       "L5_elev_bands_2.6_GSWP3_W5E5_match_geod_pergla_2.6_qc0_b160_rgi_18   match_geod_pergla   \n",
       "L5_elev_bands_2.6_GSWP3_W5E5_match_geod_pergla_2.6_qc0_b160_rgi_19   match_geod_pergla   \n",
       "L5_elev_bands_2.6_GSWP3_W5E5_match_geod_pergla_2.6_qc0_b160_rgi_all  match_geod_pergla   \n",
       "\n",
       "                                                                      qc  \\\n",
       "L5_elev_bands_pcp2.5_CRU_no_match_qc0_b80_rgi_all_without_19         qc0   \n",
       "L5_elev_bands_pcp2.5_CRU_no_match_qc0_b80_rgi_01                     qc0   \n",
       "L5_elev_bands_pcp2.5_CRU_no_match_qc0_b80_rgi_02                     qc0   \n",
       "L5_elev_bands_pcp2.5_CRU_no_match_qc0_b80_rgi_03                     qc0   \n",
       "L5_elev_bands_pcp2.5_CRU_no_match_qc0_b80_rgi_04                     qc0   \n",
       "...                                                                  ...   \n",
       "L5_elev_bands_2.6_GSWP3_W5E5_match_geod_pergla_2.6_qc0_b160_rgi_16   qc0   \n",
       "L5_elev_bands_2.6_GSWP3_W5E5_match_geod_pergla_2.6_qc0_b160_rgi_17   qc0   \n",
       "L5_elev_bands_2.6_GSWP3_W5E5_match_geod_pergla_2.6_qc0_b160_rgi_18   qc0   \n",
       "L5_elev_bands_2.6_GSWP3_W5E5_match_geod_pergla_2.6_qc0_b160_rgi_19   qc0   \n",
       "L5_elev_bands_2.6_GSWP3_W5E5_match_geod_pergla_2.6_qc0_b160_rgi_all  qc0   \n",
       "\n",
       "                                                                    border  \\\n",
       "L5_elev_bands_pcp2.5_CRU_no_match_qc0_b80_rgi_all_without_19            80   \n",
       "L5_elev_bands_pcp2.5_CRU_no_match_qc0_b80_rgi_01                        80   \n",
       "L5_elev_bands_pcp2.5_CRU_no_match_qc0_b80_rgi_02                        80   \n",
       "L5_elev_bands_pcp2.5_CRU_no_match_qc0_b80_rgi_03                        80   \n",
       "L5_elev_bands_pcp2.5_CRU_no_match_qc0_b80_rgi_04                        80   \n",
       "...                                                                    ...   \n",
       "L5_elev_bands_2.6_GSWP3_W5E5_match_geod_pergla_2.6_qc0_b160_rgi_16     160   \n",
       "L5_elev_bands_2.6_GSWP3_W5E5_match_geod_pergla_2.6_qc0_b160_rgi_17     160   \n",
       "L5_elev_bands_2.6_GSWP3_W5E5_match_geod_pergla_2.6_qc0_b160_rgi_18     160   \n",
       "L5_elev_bands_2.6_GSWP3_W5E5_match_geod_pergla_2.6_qc0_b160_rgi_19     160   \n",
       "L5_elev_bands_2.6_GSWP3_W5E5_match_geod_pergla_2.6_qc0_b160_rgi_all    160   \n",
       "\n",
       "                                                                            rgi_reg  \n",
       "L5_elev_bands_pcp2.5_CRU_no_match_qc0_b80_rgi_all_without_19         all_without_19  \n",
       "L5_elev_bands_pcp2.5_CRU_no_match_qc0_b80_rgi_01                                 01  \n",
       "L5_elev_bands_pcp2.5_CRU_no_match_qc0_b80_rgi_02                                 02  \n",
       "L5_elev_bands_pcp2.5_CRU_no_match_qc0_b80_rgi_03                                 03  \n",
       "L5_elev_bands_pcp2.5_CRU_no_match_qc0_b80_rgi_04                                 04  \n",
       "...                                                                             ...  \n",
       "L5_elev_bands_2.6_GSWP3_W5E5_match_geod_pergla_2.6_qc0_b160_rgi_16               16  \n",
       "L5_elev_bands_2.6_GSWP3_W5E5_match_geod_pergla_2.6_qc0_b160_rgi_17               17  \n",
       "L5_elev_bands_2.6_GSWP3_W5E5_match_geod_pergla_2.6_qc0_b160_rgi_18               18  \n",
       "L5_elev_bands_2.6_GSWP3_W5E5_match_geod_pergla_2.6_qc0_b160_rgi_19               19  \n",
       "L5_elev_bands_2.6_GSWP3_W5E5_match_geod_pergla_2.6_qc0_b160_rgi_all             all  \n",
       "\n",
       "[240 rows x 8 columns]"
      ]
     },
     "execution_count": 65,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd_rel_error_area_reg"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 83,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 79,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0       561.749772\n",
       "1       564.601981\n",
       "2       561.905215\n",
       "3       584.397095\n",
       "4       538.729916\n",
       "           ...    \n",
       "2747    381.330360\n",
       "2748    156.925992\n",
       "2749    552.939853\n",
       "2750    496.680765\n",
       "2751    471.011642\n",
       "Name: mu_star_glacierwide, Length: 2343, dtype: float64"
      ]
     },
     "execution_count": 79,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "_g_stats_W5E5_cte['m_star_glacierwide'].dropna()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 104,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.0    0.871099\n",
       "0.5    3.639807\n",
       "1.0    8.454943\n",
       "Name: glacier_prcp_scaling_factor, dtype: float64"
      ]
     },
     "execution_count": 104,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "### get the prcp. factor distributions for every RGI region \n",
    "\n",
    "pd_glac_stats_all_d = {}\n",
    "pd_clim_stats_all_d = {}\n",
    "for clim_p in ['CRU_pcp2.5', 'ERA5_pcp1.6', 'W5E5_pcp2.6', 'W5E5_pcp_via\\nwinterprcp']:\n",
    "    _g_stats_l = []\n",
    "    _c_stats_l = []\n",
    "    if clim_p == 'CRU_pcp2.5':\n",
    "        rgi_regs = np.arange(1,19,1)\n",
    "    else:\n",
    "        rgi_regs = np.arange(1,20,1)\n",
    "    for rgi_reg in rgi_regs:\n",
    "        if 0<rgi_reg <10:\n",
    "            rgi_reg = f'0{rgi_reg}'\n",
    "        else:\n",
    "            rgi_reg = str(rgi_reg)\n",
    "        if clim_p == 'W5E5_pcp_via\\nwinterprcp':\n",
    "            _g_stats = pd.read_csv(f'/home/www/fmaussion/runs/new_gdirs/oggm_v1.6/L3-L5_files/GSWP3_W5E5/elev_bands/qc0/match_geod_pergla_winterprcp/RGI62/b_160/L5/summary/glacier_statistics_{rgi_reg}.csv')#[['glacier_prcp_scaling_factor']]\n",
    "            _c_stats = pd.read_csv(f'/home/www/fmaussion/runs/new_gdirs/oggm_v1.6/L3-L5_files/GSWP3_W5E5/elev_bands/qc0/match_geod_pergla_winterprcp/RGI62/b_160/L5/summary/climate_statistics_{rgi_reg}.csv')#[['glacier_prcp_scaling_factor']]\n",
    "\n",
    "        elif clim_p == 'W5E5_pcp2.6':\n",
    "            _g_stats = pd.read_csv(f'/home/www/fmaussion/runs/new_gdirs/oggm_v1.6/L3-L5_files/GSWP3_W5E5/elev_bands/qc0/match_geod_pergla_2.6/RGI62/b_160/L5/summary/glacier_statistics_{rgi_reg}.csv')#[['glacier_prcp_scaling_factor']]\n",
    "            _c_stats = pd.read_csv(f'/home/www/fmaussion/runs/new_gdirs/oggm_v1.6/L3-L5_files/GSWP3_W5E5/elev_bands/qc0/match_geod_pergla_2.6/RGI62/b_160/L5/summary/climate_statistics_{rgi_reg}.csv')#[['glacier_prcp_scaling_factor']]\n",
    "\n",
    "        elif clim_p == 'CRU_pcp2.5':\n",
    "            _g_stats = pd.read_csv(f'/home/www/oggm/gdirs/oggm_v1.6/L3-L5_files/CRU/elev_bands/qc0/pcp2.5/match_geod_pergla/RGI62/b_080/L5/summary/glacier_statistics_{rgi_reg}.csv')#[['glacier_prcp_scaling_factor']]\n",
    "            _c_stats = pd.read_csv(f'/home/www/oggm/gdirs/oggm_v1.6/L3-L5_files/CRU/elev_bands/qc0/pcp2.5/match_geod_pergla/RGI62/b_080/L5/summary/climate_statistics_{rgi_reg}.csv')#[['glacier_prcp_scaling_factor']]\n",
    "\n",
    "        elif clim_p == 'ERA5_pcp1.6':\n",
    "            _g_stats = pd.read_csv(f'/home/www/oggm/gdirs/oggm_v1.6/L3-L5_files/ERA5/elev_bands/qc0/pcp1.6/match_geod_pergla/RGI62/b_080/L5/summary/glacier_statistics_{rgi_reg}.csv')#[['glacier_prcp_scaling_factor']]\n",
    "            _c_stats = pd.read_csv(f'/home/www/oggm/gdirs/oggm_v1.6/L3-L5_files/ERA5/elev_bands/qc0/pcp1.6/match_geod_pergla/RGI62/b_080/L5/summary/climate_statistics_{rgi_reg}.csv')#[['glacier_prcp_scaling_factor']]\n",
    "\n",
    "\n",
    "\n",
    "        _g_stats_l.append(_g_stats)\n",
    "        _c_stats_l.append(_c_stats)\n",
    "\n",
    "\n",
    "    pd_glac_stats_all = pd.concat(_g_stats_l)\n",
    "    pd_clim_stats_all = pd.concat(_c_stats_l)\n",
    "\n",
    "    pd_glac_stats_all.index = pd_glac_stats_all.rgi_id\n",
    "    pd_clim_stats_all.index = pd_clim_stats_all.rgi_id\n",
    "\n",
    "    pd_glac_stats_all_d[clim_p] = pd_glac_stats_all.loc[pd_glac_stats_all['mu_star_glacierwide'].dropna().index]\n",
    "    pd_clim_stats_all_d[clim_p] = pd_clim_stats_all.loc[pd_glac_stats_all['mu_star_glacierwide'].dropna().index]\n",
    "\n",
    "\n",
    "### get winter prcp. (back from prcp. fac. )\n",
    "pd_glac_stats_all = pd_glac_stats_all_d['W5E5_pcp_via\\nwinterprcp']\n",
    "prcp_fac_dist = pd_glac_stats_all['glacier_prcp_scaling_factor']#####.values\n",
    "winter_prcp_factor_ab = -1.0614, 3.9200\n",
    "winter_prcp_factor_range = 0.1, 10\n",
    "a, b = winter_prcp_factor_ab  # cfg.PARAMS['winter_prcp_factor_ab']\n",
    "r0, r1 = winter_prcp_factor_range  # cfg.PARAMS['winter_prcp_factor_range']\n",
    "assert np.all(prcp_fac_dist < r1)\n",
    "assert np.all(prcp_fac_dist > r0)\n",
    "w_prcp = np.exp((prcp_fac_dist - b)/a)\n",
    "pd_glac_stats_all.loc[w_prcp.index, 'winter_prcp'] = w_prcp.values\n",
    "\n",
    "\n",
    "pd_glac_stats_all['glacier_prcp_scaling_factor'].quantile([0,0.5, 1])\n",
    "\n",
    "\n",
    "\n",
    "#pd_rel_error_area_reg_qc0"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "metadata": {},
   "outputs": [],
   "source": [
    "pd_rel_error_area_reg_qc0 = pd_rel_error_area_reg[pd_rel_error_area_reg.qc == 'qc0']\n",
    "pd_rel_error_area_reg_qc0 = pd_rel_error_area_reg_qc0.loc[(pd_rel_error_area_reg_qc0.border == 160) | (pd_rel_error_area_reg_qc0.clim_pcp == 'CRU_pcp2.5')|(pd_rel_error_area_reg_qc0.clim_pcp == 'ERA5_pcp1.6')] # only have border 80 for CRU ... \n",
    "pd_rel_error_area_reg_qc0.index = pd_rel_error_area_reg_qc0['rgi_reg']\n",
    "pd_rel_error_area_reg_qc0 = pd_rel_error_area_reg_qc0.loc[pd_rel_error_area_reg_qc0.match == 'match_geod_pergla']\n",
    "pd_rel_error_area_reg_qc0 = pd_rel_error_area_reg_qc0[['rel_error_area_in_percent','clim_pcp']]\n",
    "pd_rel_error_area_reg_qc0 = pd_rel_error_area_reg_qc0.pivot(columns=['clim_pcp'])\n",
    "pd_rel_error_area_reg_qc0.columns = pd_rel_error_area_reg_qc0.columns.droplevel(0)\n",
    "pd_rel_error_area_reg_qc0 = pd_rel_error_area_reg_qc0.astype(\"float32\")\n",
    "pd_rel_error_area_reg_qc0 = pd_rel_error_area_reg_qc0.rename({'all_without_19':'all_no19'})"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Comparison of relative failing glacier area for different climate datasets & W5E5 variable prcp. factor distributions"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1152x720 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 1728x720 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.set(font_scale = 1.3)\n",
    "plt.figure(figsize=(16,10))\n",
    "plt.subplot(111)\n",
    "plt.title('Relative failing glacier area per RGI region\\n(match_geod_pergla, qc0)', fontsize=20)\n",
    "#plt.title(', fontsize=22)\n",
    "pd_rel_error_area_reg_qc0 = pd_rel_error_area_reg_qc0.round(2)\n",
    "sns.heatmap(pd_rel_error_area_reg_qc0,\n",
    "            linewidths=.5, cmap=\"PuRd\", cbar_kws={'label':'relative failing glacier area (in %)'},\n",
    "           annot=True, fmt=\".2f\")\n",
    "ax = plt.gca()\n",
    "ax.figure.axes[-1].yaxis.label.set_size(18)\n",
    "ax.set_ylabel('RGI region', fontsize=20);\n",
    "ax.set_xticklabels(['CRU_pcp2.5\\n(b80)', 'ERA5_pcp1.6\\n(b80)', 'W5E5_pcp2.6\\n(b160)', 'W5E5_pcp_via\\nwinter_prcp (b160)'])\n",
    "ax.set_xlabel('climate dataset & prcp. fac', fontsize=20)\n",
    "plt.savefig('relative_failing_glacier_area_regional_match_geod_pergla_clim_pcp.png')\n",
    "\n",
    "plt.figure(figsize=(24,10))\n",
    "plt.subplot(122)\n",
    "ax = plt.gca()\n",
    "sns.boxplot(x = 'rgi_region', y='glacier_prcp_scaling_factor', data = pd_glac_stats_all, ax = ax)\n",
    "plt.axhline(2.6, ls= '--', lw = 3, color = 'grey', label = 'applied constant prcp. fac\\n(median from reference glaciers matching std.)')\n",
    "plt.axhline(pd_glac_stats_all['glacier_prcp_scaling_factor'].quantile([0.5]).values,\n",
    "            ls= ':', lw = 3, color = 'gray', label = 'median prcp. fac over all glaciers')\n",
    "plt.legend()\n",
    "plt.title('glacier-specific varying prcp. fac depending on the winter prcp. (using W5E5)', fontsize=20)\n",
    "\n",
    "plt.subplot(121)\n",
    "ax = plt.gca()\n",
    "sns.boxplot(x = 'rgi_region', y='winter_prcp', data = pd_glac_stats_all, ax = ax)\n",
    "\n",
    "plt.legend()\n",
    "plt.ylabel(r'winter daily precipitation (kg m$^{-2}$, avg. 1979-2019)')\n",
    "plt.title('(uncorrected) winter prcp. with W5E5', fontsize=20)\n",
    "plt.tight_layout()\n",
    "plt.savefig('W5E5_prcp_fac_via_winterpcp_boxplots.png')\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "- When using a constant prcp. fac of 2.6 with W5E5, we have in most RGI regions, the same or more missing glacier area compared to CRU or ERA5\n",
    "    - a larger failing glacier area occurs specifically for RGI region 13 & 17, and to a smaller extent RGI region 16\n",
    "    - a slighlty smaller failing glacier area occurs for the largest RGI region 5 & for RGI region 19\n",
    "- When using W5E5 together with a glacier-specific winter prcp. dependent prcp. fac, we have for all RGI regions the same or much less failing glacier area compared to the median prcp. fac W5E5 gdirs.\n",
    "    - this effect is strongly visible for RGI regions 13 & 17: \n",
    "        - With W5E5 using a variable prcp. fac there is for RGI region 13 less failing glacier area compared to CRU or constant prcp. fac W5E5, but still more than when using ERA5. \n",
    "        - Glaciers in RGI13 have rather low amount of precipitation. When adding more prcp. to it by using a larger prcp. fac of ~5, less glaciers seem to fail. Probably in ERA5 more prcp. happens for RGI region 13? (similar as for CRU, mostly the glaciers that have positive observed MB can not be calibrated). \n",
    "\n",
    "-> **When comparing all datasets, the climate which results in the least amount of failing glacier area is still ERA5, but W5E5 that uses variable winter prcp. is similar (only slightly worse in RGI region 13 & 17).**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "##### Comparison of ref_hgt_calib_diff\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "\n",
    "plt.figure(figsize=(24,10))\n",
    "plt.subplot(122)\n",
    "ax = plt.gca()\n",
    "sns.boxplot(x = 'rgi_region', y='ref_hgt_calib_diff', data = pd_glac_stats_all, ax = ax)\n",
    "#plt.axhline(2.6, ls= '--', lw = 3, color = 'grey', label = '')\n",
    "#plt.axhline(pd_glac_stats_all['glacier_prcp_scaling_factor'].quantile([0.5]).values,\n",
    "#            ls= ':', lw = 3, color = 'gray', label = 'median prcp. fac over all glaciers')\n",
    "#plt.legend()\n",
    "#plt.title('glacier-specific varying prcp. fac depending on the winter prcp. (using W5E5)', fontsize=20)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Comparison of precipitation between the datasets"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 222,
   "metadata": {},
   "outputs": [],
   "source": [
    "pd_glac_running = []\n",
    "for clim_p in ['CRU_pcp2.5', 'ERA5_pcp1.6', 'W5E5_pcp2.6', 'W5E5_pcp_via\\nwinterprcp']:\n",
    "    pd_glac_running.append(pd_clim_stats_all_d[clim_p].index)\n",
    "pd_glac_running_all= list(set(pd_glac_running[0]).intersection(pd_glac_running[1]).intersection(pd_glac_running[2]).intersection(pd_glac_running[3]))\n",
    "_pd_prcp_l = []\n",
    "for clim_p in ['CRU_pcp2.5', 'ERA5_pcp1.6', 'W5E5_pcp2.6', 'W5E5_pcp_via\\nwinterprcp']:\n",
    "\n",
    "    _pd_prcp = pd.DataFrame()\n",
    "    _pd_prcp['rgi_id'] = pd_glac_running_all\n",
    "    _pd_prcp['1980-2010_avg_prcp'] = pd_clim_stats_all_d[clim_p].loc[pd_glac_running_all]['1980-2010_avg_prcp'].values\n",
    "    _pd_prcp['1980-2010_avg_prcpsol_mean_elev'] = pd_clim_stats_all_d[clim_p].loc[pd_glac_running_all]['1980-2010_avg_prcpsol_mean_elev'].values\n",
    "    _pd_prcp['ref_hgt_calib_diff'] = pd_glac_stats_all_d[clim_p].loc[pd_glac_running_all]['ref_hgt_calib_diff'].values\n",
    "    _pd_prcp['rgi_region'] =  pd_glac_stats_all_d[clim_p].loc[pd_glac_running_all]['rgi_region'].values\n",
    "    # replace it by 0 for the statistics...\n",
    "    _pd_prcp.loc[np.isnan(_pd_prcp['ref_hgt_calib_diff']), 'ref_hgt_calib_diff'] = 0\n",
    "    _pd_prcp['clim_pcp'] = clim_p\n",
    "    _pd_prcp['prcp_factor'] = 'corrected_prcp'\n",
    "\n",
    "    _pd_prcp_l.append(_pd_prcp)\n",
    "    \n",
    "    if 'winterprcp' in clim_p:\n",
    "        pcp = pd_glac_stats_all_d[clim_p].loc[pd_glac_running_all]['glacier_prcp_scaling_factor'].values\n",
    "    else:\n",
    "        pcp = float(clim_p[-3:])\n",
    "    _pd_prcp_no_prcp_fac = pd.DataFrame()\n",
    "    _pd_prcp_no_prcp_fac['rgi_id'] = pd_glac_running_all\n",
    "    _pd_prcp_no_prcp_fac['1980-2010_avg_prcp'] = pd_clim_stats_all_d[clim_p].loc[pd_glac_running_all]['1980-2010_avg_prcp'].values/pcp\n",
    "    _pd_prcp_no_prcp_fac['1980-2010_avg_prcpsol_mean_elev'] = pd_clim_stats_all_d[clim_p].loc[pd_glac_running_all]['1980-2010_avg_prcpsol_mean_elev'].values/pcp\n",
    "    \n",
    "    # just to have a nicer table, these things are the same\n",
    "    _pd_prcp_no_prcp_fac['ref_hgt_calib_diff'] = pd_glac_stats_all_d[clim_p].loc[pd_glac_running_all]['ref_hgt_calib_diff'].values\n",
    "    _pd_prcp_no_prcp_fac['rgi_region'] =  pd_glac_stats_all_d[clim_p].loc[pd_glac_running_all]['rgi_region'].values\n",
    "    # replace it by 0 for the statistics...\n",
    "    _pd_prcp_no_prcp_fac.loc[np.isnan(_pd_prcp_no_prcp_fac['ref_hgt_calib_diff']), 'ref_hgt_calib_diff'] = 0  \n",
    "    _pd_prcp_no_prcp_fac['clim_pcp'] = clim_p\n",
    "\n",
    "    _pd_prcp_no_prcp_fac['prcp_factor'] = 'uncorrected_prcp'\n",
    "\n",
    "    _pd_prcp_l.append(_pd_prcp_no_prcp_fac)\n",
    "\n",
    "pd_prcp = pd.concat(_pd_prcp_l)\n",
    "pd_prcp = pd_prcp.reset_index()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 223,
   "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>index</th>\n",
       "      <th>rgi_id</th>\n",
       "      <th>1980-2010_avg_prcp</th>\n",
       "      <th>1980-2010_avg_prcpsol_mean_elev</th>\n",
       "      <th>ref_hgt_calib_diff</th>\n",
       "      <th>rgi_region</th>\n",
       "      <th>clim_pcp</th>\n",
       "      <th>prcp_factor</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>RGI60-14.14686</td>\n",
       "      <td>1076.216437</td>\n",
       "      <td>544.484230</td>\n",
       "      <td>0.0</td>\n",
       "      <td>14</td>\n",
       "      <td>CRU_pcp2.5</td>\n",
       "      <td>corrected_prcp</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>RGI60-13.15533</td>\n",
       "      <td>2024.289065</td>\n",
       "      <td>1815.313027</td>\n",
       "      <td>0.0</td>\n",
       "      <td>13</td>\n",
       "      <td>CRU_pcp2.5</td>\n",
       "      <td>corrected_prcp</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2</td>\n",
       "      <td>RGI60-17.06667</td>\n",
       "      <td>2262.269807</td>\n",
       "      <td>1412.045519</td>\n",
       "      <td>0.0</td>\n",
       "      <td>17</td>\n",
       "      <td>CRU_pcp2.5</td>\n",
       "      <td>corrected_prcp</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>3</td>\n",
       "      <td>RGI60-13.27602</td>\n",
       "      <td>579.943412</td>\n",
       "      <td>414.010951</td>\n",
       "      <td>0.0</td>\n",
       "      <td>13</td>\n",
       "      <td>CRU_pcp2.5</td>\n",
       "      <td>corrected_prcp</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>4</td>\n",
       "      <td>RGI60-13.20733</td>\n",
       "      <td>2288.944279</td>\n",
       "      <td>1840.195214</td>\n",
       "      <td>0.0</td>\n",
       "      <td>13</td>\n",
       "      <td>CRU_pcp2.5</td>\n",
       "      <td>corrected_prcp</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1666331</th>\n",
       "      <td>208287</td>\n",
       "      <td>RGI60-14.02150</td>\n",
       "      <td>153.039118</td>\n",
       "      <td>113.290625</td>\n",
       "      <td>0.0</td>\n",
       "      <td>14</td>\n",
       "      <td>W5E5_pcp_via\\nwinterprcp</td>\n",
       "      <td>uncorrected_prcp</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1666332</th>\n",
       "      <td>208288</td>\n",
       "      <td>RGI60-02.10847</td>\n",
       "      <td>719.925040</td>\n",
       "      <td>498.517150</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2</td>\n",
       "      <td>W5E5_pcp_via\\nwinterprcp</td>\n",
       "      <td>uncorrected_prcp</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1666333</th>\n",
       "      <td>208289</td>\n",
       "      <td>RGI60-17.11974</td>\n",
       "      <td>1198.084835</td>\n",
       "      <td>896.347553</td>\n",
       "      <td>0.0</td>\n",
       "      <td>17</td>\n",
       "      <td>W5E5_pcp_via\\nwinterprcp</td>\n",
       "      <td>uncorrected_prcp</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1666334</th>\n",
       "      <td>208290</td>\n",
       "      <td>RGI60-17.02434</td>\n",
       "      <td>595.221264</td>\n",
       "      <td>276.167502</td>\n",
       "      <td>0.0</td>\n",
       "      <td>17</td>\n",
       "      <td>W5E5_pcp_via\\nwinterprcp</td>\n",
       "      <td>uncorrected_prcp</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1666335</th>\n",
       "      <td>208291</td>\n",
       "      <td>RGI60-04.07009</td>\n",
       "      <td>193.791625</td>\n",
       "      <td>171.829744</td>\n",
       "      <td>0.0</td>\n",
       "      <td>4</td>\n",
       "      <td>W5E5_pcp_via\\nwinterprcp</td>\n",
       "      <td>uncorrected_prcp</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1666336 rows × 8 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "          index          rgi_id  1980-2010_avg_prcp  \\\n",
       "0             0  RGI60-14.14686         1076.216437   \n",
       "1             1  RGI60-13.15533         2024.289065   \n",
       "2             2  RGI60-17.06667         2262.269807   \n",
       "3             3  RGI60-13.27602          579.943412   \n",
       "4             4  RGI60-13.20733         2288.944279   \n",
       "...         ...             ...                 ...   \n",
       "1666331  208287  RGI60-14.02150          153.039118   \n",
       "1666332  208288  RGI60-02.10847          719.925040   \n",
       "1666333  208289  RGI60-17.11974         1198.084835   \n",
       "1666334  208290  RGI60-17.02434          595.221264   \n",
       "1666335  208291  RGI60-04.07009          193.791625   \n",
       "\n",
       "         1980-2010_avg_prcpsol_mean_elev  ref_hgt_calib_diff  rgi_region  \\\n",
       "0                             544.484230                 0.0          14   \n",
       "1                            1815.313027                 0.0          13   \n",
       "2                            1412.045519                 0.0          17   \n",
       "3                             414.010951                 0.0          13   \n",
       "4                            1840.195214                 0.0          13   \n",
       "...                                  ...                 ...         ...   \n",
       "1666331                       113.290625                 0.0          14   \n",
       "1666332                       498.517150                 0.0           2   \n",
       "1666333                       896.347553                 0.0          17   \n",
       "1666334                       276.167502                 0.0          17   \n",
       "1666335                       171.829744                 0.0           4   \n",
       "\n",
       "                         clim_pcp       prcp_factor  \n",
       "0                      CRU_pcp2.5    corrected_prcp  \n",
       "1                      CRU_pcp2.5    corrected_prcp  \n",
       "2                      CRU_pcp2.5    corrected_prcp  \n",
       "3                      CRU_pcp2.5    corrected_prcp  \n",
       "4                      CRU_pcp2.5    corrected_prcp  \n",
       "...                           ...               ...  \n",
       "1666331  W5E5_pcp_via\\nwinterprcp  uncorrected_prcp  \n",
       "1666332  W5E5_pcp_via\\nwinterprcp  uncorrected_prcp  \n",
       "1666333  W5E5_pcp_via\\nwinterprcp  uncorrected_prcp  \n",
       "1666334  W5E5_pcp_via\\nwinterprcp  uncorrected_prcp  \n",
       "1666335  W5E5_pcp_via\\nwinterprcp  uncorrected_prcp  \n",
       "\n",
       "[1666336 rows x 8 columns]"
      ]
     },
     "execution_count": 223,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd_prcp"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 166,
   "metadata": {},
   "outputs": [],
   "source": [
    "#sns.kdeplot(x='1980-2010_avg_prcp', hue='clim_pcp', data = pd_prcp, log_scale=True) #[['clim_pcp', '1980-2010_avg_prcp']])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 183,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:xlabel='1980-2010_avg_prcpsol_mean_elev', ylabel='Density'>"
      ]
     },
     "execution_count": 183,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 2016x576 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, axs = plt.subplots(1,2, figsize=(28,8))\n",
    "sns.kdeplot(x='1980-2010_avg_prcp', hue='clim_pcp', data = pd_prcp, cut = True, lw = 2, ax = axs[0]) #[['clim_pcp', '1980-2010_avg_prcp']])\n",
    "sns.kdeplot(x='1980-2010_avg_prcpsol_mean_elev', hue='clim_pcp', data = pd_prcp, cut = True, ax = axs[1], lw=2) #[['clim_pcp', '1980-2010_avg_prcp']])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 237,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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5jYwRi8QZhiFP+mAFhp8iX/5EffLJJ7r66l/o0Uf/umdsYwAAAADoI2pqqiWzbeCis86rDV+W1qxdI9d1D3lfAAAAAIDehcAF+gTHcfTww3+WTI98+SXJLgfoFQzTkjdnjAIjviArfbheeeVF/fLyS/XKKy8qEokkuzwAAAAA6BQ1NTXtBi46i+XPVk11lcrLd3fZcwAAAAAAeiY72QUAneGNN17V2rWr5R8wTabtS3Y53cJKHZDsEvocX8HkZJeQFKbtl3/AkfJkHa7G0vf16KN/0auvvqSzzjpXEyZMSnZ5AAAAAHBIqmtqZFipbZZ39Lz6QOeKViBbkrRu3VplZ+ckXiAAAAAAoNeihwv0euXl5Zo//++yUgtkZwxLdjndxpc7Vr7csckuo0+x/Fmy/FnJLiNpLH+mAoOPVWDQbO2sqNEdd/xOt912k7Zs2Zzs0gAAAADgoNXV1siw2l6c0dHz6gOdK5q+TMkwtX792kMpEwAAAADQCxG4QK/36KN/USgclr9wqgzDSHY5QK9mGIbstCIFhn9evoISrVj5qa655nLNm/egqqurkl0eAAAAACQkHA6rsbFBhtV1Q4oYpi3Ll0HgAgAAAAD6IYYUQa/2wQdL9d5778ibN16mNy3Z5QB9hmFY8mYXy04fptDOZXrt9Vf19ttv6eSTT9W0aTNVWMiQNgAAAAB6vpqaGklqt4eLzmT6s7R27Rq5rsvFIAAAAADQjxC4QK/V0NCgefMekuXPkDdndLLL6XZ1G16VJKUMPSHJlaAvM22f/IVT5Mk6TKHSD/X000/q6aef1KBBQzRt2gwdeeR05ecXJLtMAAAAAGhXVVWspz7Dbhu46MzzaiuQp/qKtVq7do1GjjzskPcHAAAAAOgdCFyg1/rXv55QefkupQz9nAzDSnY5QJ9m+TIUGDxHTrhOkepN2rZrk5588nE9+eTjGjJkmKZNm6GpU6cpLy8/2aUCAAAAQFx1dbUkdemQIpJkpxXJ2GFp8eKFBC4AAAAAoB8hcIFeaf36tXr55RfkyTxMVkpusssB+g3TkyJvdrG82cVywrWKVG3SlrJNeuKJv+uJJ/6uoUNHaNq06Zo6dZpyc/OSXS4AAACAfm5P4KJrhxQxLK+s1AFavPhtnXnmOTJNs0ufDwAAAADQMxC4QK8TjUb10MN/lmH75cufkOxyksabMzbZJfQ5DNOSGNOTKm/OaHlzRssJ1ShSvUmbSzdpw/xHNX/+oxo+fKSOOmq6jjxyurKzc5JdLgAAAIB+aH89XHT0vLqj54p2+hBVb1moTz9doTFjxiVYKQAAAACgNyJwgV7nlVde0KaN6+UvmtnlXYL2ZHZwQLJLAOJMb1DenDHy5oyRE6pRuGqTNm7fpHWP/02PP/43jRh5uKZMnqphw0Zo8OAhCgbTkl0yAAAAgH5gf4GLzj6vtoMDZVoeLV68kMAFAAAAAPQTBC7Qq+zcWaannnpCdnCg7LTByS4HQDtMb1C+3DFS7hg5oWqFqzZpw5ZNWrvm7/FtMjIyNWTIMA0ePKTpNlSFhQPodhcAAABAp6qurpZhmJLR9U1ghmnLCg7SWwv/q1NO+aIKCrhQAgAAAAD6OgIX6DVc19W8Rx5SJOoopXCKDMNIdklJFW0olyRZ/qwkVwLsm+lNky93rJQ7Vk6kQU5DhZzGCtU2lGv5qvX6eNlHkutIkmzbo6KiQRoyZKgGDx4aD2OkpKQm+VUAAAAA6K2qqqpk2v522xC64rzamzdB9TVb9PDDf9YvfnFVv2+7AAAAAIC+jsAFeo13312sjz/6QL78STI9fAHbuGOppAOPIQv0FKbtlxkslIKF8WWuE5UTqpLTUKFoY4U2l1Vo05ZFcv77enybrKxsDRkyVNnZOcrIyFR6eoYyMjKVkZERn/d4PN3/ggAAAAD0eNXV1fscjrQrzqtNT0CevAn69NN39fLLz+ukk07ttH0DAAAAAHoeAhfoFerqavXII3+RFciWJ3tUsssB0EkM05Llz5Llz1JzZMJ1XbmRBjmN5Yo2VKi6sULLPl0nN7JcTqSx3f0EAilKz8hUVmaWCgpy5fOltgpkBAIp8vm88np98vl88npj9y3L6r4XCwAAAKDbVVdXyzW7N6DtyRypaM1WPfbYIyorK9VXv3qWfD5ft9YAAAAAAOgeBC7QK/zjH4+purpKKcNOjI29CnQB08fwLD2BYRgyPAGZnoDs4MBW61w3KjfSKDfSIDdSLyfSIDfaoEikQbtq67WzaodWr9uoaLherhM54HOZliWvxytPUwDD5/XK5/PJ5/PHAxqpqanKzMxqumU2TbMVDAZlmrwfAQAAAD1ZZWWVDOvQwg6JnisahiH/oFlqLP1Qr776kv7zn9c1efJUnXXWuUpPzzikWgAAAAAAPQuBC/R4q1d/ptdff1We7GJZgexkl9Nj+ItmJruEPsdfODnZJeAADMOS4UmRPCkH3NZ1wrGeMiINkhOW60QlJyLXbT2NOlFF3YjqQ1GpISLXrZWcSklObDsnJCfc0Gb/pmUpPT1D2VnZysrKahHK2HPLycmV3+/vgp8EAAAAgI6oqq6WYbXfltDR8+qDOVc0DFP+ghLZaYMUqdygxYsX6r33luj6629WYeGAhPcHAAAAAOiZCFygR4tEInrooftleVPlyzsi2eX0KKYdSHYJQI9mmB4ZXo9Mb9oh7yvWs0asV436re9IriM7fbBqIvWq3lGtjVvL5ETq5URCrWswTI0ceZjGj5+kCRMmavDgofSKAQAAAHQT13VVW1MtK7P9gEN3nFfbKXmyU/IUrd+lSGOFbv5/N+iW390hj8fb5c8NAAAAAOh6BC7Qo73wwrPatm2LAoNmy+jmMVcBoFmsZ41UyZMq0451R+zLn9hmO9eJNA11Ui83XC+nsVLrtmzX6tXz9c9/zlcwLV0Txk/U+PETNW7ceAWDhx4GAQAAANC+hoYGRaNR2Vbyww2GZcv0pauqskLvvvuOZsyYleySAAAAAACdgMAFeqzS0h16+pmnZKcNlp1WlOxyepxwxVpJkidzRJIrAfoXb87Yfa4zTFuGN22vXjUmyIk0KFq7TQ0127TonXe0cOF/ZRiGhg0bqQkTYgGMYcNG0PsFAAAA0Ilqa2skSYbla3d9d55Xe3PGynVdhcs+0KsLXiZwAQAAAAB9BIEL9FgrVy5XNBJRSt74ZJfSI4Ur10kicAF0NzuY+HjLpu2XmTFcnozhcl1HTkO5IjVbtXH7dq1b96SefvpJpaSkanxT7xdHHDFB6ekZXVA9AAAA0H80NjbG7pjtN39153l183mEG67W2jXva+PG9RoyZFiXPy8AAAAAoGsRuECP5bqupNgV4wDQVxiGKSuQIyuQI+WNlxNpVLR2u0K127Rk6VItXrxQkjR06HDNmHG0pk+fpfT09CRXDQAAAKAzeDKGK1T2sV5//VWdd94FyS4HAAAAAHCI+CYb6KUMO5DsEvochmlBR0QbyiVJlj+rU/Zn2j6ZGUPlyRgq13VjvV/UbtPm0i167LFHNH/+o5o4cbJmzTpG48dPlG3zrxsAAADoDB09r+6Mc8WW5xFWsEhLlizWOed8m2EFAQAAAKCX41sboJcKFM1Mdgl9DsO0oCMadyyVJKUMPaHT920YhqxAtqxAtpQ7TtHGSoUr1urDZcv0/vvvKpiWrqNnztasWceoqGhQpz8/AAAA0J909Ly6M84VW55H2GlFqt2yQatXf6ZRo0Yf9D4BAAAAAMlH4AIAgB7K8mXIKiiRmz9R0Zptaqhcpxdfel4vvvichg4doTlzjtFRR81Qamow2aUCAAAA6CA7dYAMw9T7779H4AIAAAAAejn6LQQAoIczDFN2WpECg2Yp9bDT5Cso0eYduzVv3kO65NIf6n//904tW/ahHMdJdqkAAAAADsCwPDJT8vXe0iVyXTfZ5QAAAAAADgE9XAC9VMP2WHek/sLJSa4E6F/8SR7Ox7T98mYXy5M1Sk5DucKV6/Te++9ryZJFyszM0tFHz9GsWXNUUDAgqXUCAAAAPV13nlfvfR5hpxVp5/b3tHXrFoYLBAAAAIBejMAF0Es5jeXJLgHol0w7kOwSJEmGYcgKZMsKZMvNn6RIzVbVVK7Vc889o+eee1oDBhRpzJixGj16rEaNGqP09PRklwwAAAD0KN15Xr33eYQdLFKj3tO77y4mcAEAAAAAvRiBCwAAejnDtORJHyxP+mA54XpFqjaotGqHtr/+mhYseFmSNGDgII0dM1bFxWNVXDxaaWkEMAAAAIBkMT0pslIH6NVXX9Ipp8yV1+tNdkkAAAAAgINA4ALopaxUhgvobL4ChmfBgYUr1kqSPJkjklxJ+0xPQN6c0fLmjJbrOnIaditSW6rSylJtf22BXn31JUnSwIGDNGbMOI0ePUbFxWMUDKYlufJ9c11XjuO0urmuo2g0Ksdx4/Ner1d+f0C2zcebvshxYr/z2O89qkgk2jQfaVoXia/f1800TXm9Xnk8Hnk8Xnm9sanH41VqqqVIJMLxAwBAP9LR8+rOOFds7zzCmzNaNRtf01tvvaHjjjsxvtx1XdXW1igQSJFlWQk9j+u6qqqq1LZtWxUMBlVUNFiGYRxy/QAAAACA9tGiDPRSvtyxyS6hz7H8WckuAb1AuHKdpJ4buGjJMExZgVxZgVxJY2MBjPrditSVakdlqba99qpeffVFSVJR0eD4ECQDBgyUZdnyeDxNU1u2bcuybJmm2eHnD4VCqqmpVk1NjWpra+L3Y/PVqq6uVm1tjaqrq1VdU626ujo50eieYIXryHUcua6b0Ou2bY98fr8C/oACKSlKCQQUCKQoMzNNhuFRIBBQIBCQ3++X3x9omk9pMU1RSkoKX7y34LquQqGQ6upqVVtbq4aGeoVCIYVCjQqFwgqHm++H2syHw2E1NjY2LYvdWoYgItGonGhU0abQhBN1FHWi8WMh6sSmSvA4OFiGacq2PfJ4PPJ6YuEMr9er1NRU5eXlKy8vX7m5eU3TfGVkZCT0dwEAAHqOjp5Xd8a5YnvnEVZKvqxAjv7v+Wc1a9axqq2t0aOP/lXvf/CeopGIMjKydPLJp+rYY0+Q3+/f577Xrl2t995bouXLl2n79m1qbGyIr8vKytG5535bkyZxgQEAAAAAdAW+SQAAoJ8wDFNWSq6slOYARlROfbkidTu0vaJUWxe8qldeeXG/+zBNU5a1J4Bh23tuHo9HjuuqpiYWpIiEw/vej+WRYfkkyyuZHhmWX4YnXfKakmHIkCHbMCQZUqupGbtCr3lZy/VuVK4TlpywQtGIGkNhlTeEJKdWhhOR3IicaFhuNCTXdQ7487I9nlhooymA0XxrGcqIBTcC8vl88np9TVNvm3mv15fw1YmdxXVdhcPheACisTE2ra+vU21trerqauNBipb3a2trVVNTo7q6OtXX1ykajSTwrIZMy5ZhWpJhSaYtyYzdN5qnhgzDlGRLhkcyTBkyJNuMbSNDMszYcRCfb3pMi/WxeaNp/83HT9Oypm2N5vVy5TrR2LHiRqXm+3stc92owk5UITcqNUal+qjc3bu0Zv1GRUN1rV6pZdvKzclTfn5+PIQRC2bkKTc3XykpKZ3ziwQAAH2OYRjy5IzRrs1v6kc/+o5M01Q4EpGdMUK2J1W1NVs1f/7f9NxzT+vUU+fq6KPnKD09I/74TZs26oknHtWyZR9JTWFrM2WwfJlpMr3pcsK1qqpYpXvv/YN+/vNf6fDDi5P4agEAAACgbyJw0Qdt3rxZJ5xwgh5//HFNmjQp2eUAQJ9i2IFkl9BpDMNqEcAYJ9eNKlq/W264TnJjw3TIdZq+iG6+78h1o4q4jiKuowbXkUKO1BiV68YCFoaVKSMtX17LJ8Pyymg1bbpvJid80Mx19oQz3GhYrhO7qcV9NxpWgxNSfX1Yu2rrJKdSciNSNBQLbjiJBBAU7zUkHsTwxaaWaco0Y6EAs937pkxz7/nYNpFIWI2Ne3qTaGhsbApUNPUuEQopHA51uEbTjv1+ZHpiQRjTK8POlZXplWV6m36PXhmmRzItGU1hCsOIBSsM05JMS/FgTB/kOlG54Vo54Vo5oRo54VrtqqvRzlUb5a5YISfS+ucdSElVfl6+Bg0arKKiwRo0KHbLyMjssz8jAAA6or+1XezrPMKTNkjGoNmK1JXKiYaUkjtWprdpuL+c0YrW7VTjzmV64om/6x//eEwjRhymrKxsbdu2VVu2bJJpeeXLnyRP5ojY57i92GmD1LDxVd1xxy269trfKD+/oCtfJgAAAAD0O90euHjsscd04403asmSJQoE9pxsHn/88aqsrNQ777wTvwLUdV3NmDFD55xzjgYOHKgrrriizf5eeuklDR06VJJ011136e677273eT/55BPZtr3PbZrX9wUDBgzQm2++qczMzGSXgi5Ut+FVSVLK0BOSXAnQvwSKZia7hC5jGJbslLxkl9EtDLMpHKB9d818IK7r7AlouFHJiTT1lNA0dSItlkckN6qoE1W9G1FdYyTWa4Jb1TRUhiu5ik3jN8loWufKbXU/PrxGvLeIPT1JGIYtmT4ZHlvyWfKatmTY8TBEbL0lw/TEwxPNIQsCAAdmmJYMX7pMX3q7691oKB7EcMM1ioRqtXlntTZvXaJo+D/x7QIpqRo8aLAGDx4SD2IUFQ1SIECPGADQE9B20fV6QttFd55X7+88wk4rkp1W1O46KyVXgSHHKtpYqUjlBq3fVqb1m7dLll++ghJ50ofJsH373Ldp++QfNEf161/Ugw/ep1/84iqGQwMAAACATtTtZ+kzZsxQOBzWu+++q9mzZ0uSNm7cqNLSUmVmZmrZsmWaOHGiJGnlypUqLy/XjBkztGHDBnm9Xi1YsKDV/rKzs1vNDx06VH/729/aPG/LBon2tukrDRaSZFmW8vL6xxdmAAAki2GYku2ToX03cKP/MSyvrEC2rEB2m3VOpFFOY4WcxkpFGiu1ZtNOrV6zRk50z/A7mVnZGjJ4iAYNGqKiokEaNGiI8vPz5fMdfDgIAJA42i66Hm0XibF8GbLyJxzUY01vUN78En322TtasOBlfe5zJ3dydQAAAADQf3X7mfrQoUM1cOBALVq0KN5osWjRIk2cOFEDBgyI329enpKSogkTJmjDhg2SdMCTcdM0O2Wbfbn88stVVlamGTNm6OGHH1ZNTY2OOeYY3XDDDUpP33Ol47///W898MADWrNmjVJSUlRSUqI//OEP8vl8OvfcczVs2DAFg0E99dRTikQi+sIXvqCrrrpKXm/b7h9beuutt/Td735Xr7/+uvLz8+PLH3/8cd1222168803VVpa2qpbTtd1dfXVV2vRokUqLS1VXl6evvCFL+iiiy464PMBAACgc5i2T6ZdIKXu6crbdV25kTo5DRWKNlaqprFCn3y2Xh9//FGsF5Umqalpys3LU15unnLjt1zl5MSmBDIAoHPRdkHbRV9jZwyXXb1J8+c/qiFDhmrUqNHJLgkAAAAA+oSkXBoxffp0LVq0KD6/aNEiTZ8+XYWFhfq///s/XXjhhfHlRx55pDwejyQpHA7r+OOPVzgc1uGHH64f/OAHOvLIIxN+/q1bt2rOnDmyLEtjxozRxRdfrNGjO36i+f7778vv9+uBBx5QeXm5rrrqKl199dX6wx/+IEl64okn9Otf/1oXX3yxTjjhBIXDYb355ptynD2N5s8995y++MUv6tFHH9X69et15ZVXKhgM6he/+MV+n3vGjBnKycnRc889p29/+9vx5U8//bROOeWUdhshXNdVTk6ObrvtNuXk5Oizzz7TtddeK9u2dfHFF3f4daNn8eaMTXYJfQ7DtKAjGrYvlST5CycnuRIAfYFhGDI8qTI9qa26EnfdqJzGajmNlXLCtQqFa7W5rFabt62QE1rSKowh7TuQkZ6eoUAgIL8/RYFAQB4PQ8cAh8p1XUWjUYXDIYXDYbluvbZvL1c4HI4vC4fDCoVCrZZFIhEFAgGlpaUpLS1dwWBsGggE+LvsoWi76PttFx09r+6Mc8Vkn0cYhiHfgGlq2LhAd9xxi375y6s0dOjwLn3OnTvLtGrVpxo58nDl5xcc+AEAAAAA0AslJXAxY8YMPf3006qqqlJ6erreeecdnXnmmSosLNSNN96oUCgk0zS1ZMkSXXTRRZKk4cOH67e//a1Gjx6t+vp6PfHEEzrvvPM0b948TZ06Nb7v9evXq6SkpNXzjR07Nt4N54QJE3TTTTdp5MiRqqio0EMPPaSzzjpL//rXv+LjqXbE//t//0/BYFCSdPXVV+vCCy/U1q1bNXDgQN199936xje+oe9973vx7fduFMnOztZ1110n0zQ1cuRIbd++Xb/73e90ySWX7PfKDdM0NXfuXD399NPxRotNmzZp6dKluuyyy/b5mEsvvTQ+P2jQIG3ZskXz5s0jcNGL2cEByS4B6JecxvJklwCgHzAMS5Y/U5Y/s826WK8YDXLDtXKabrFARo02b9vZbiCjmWma8vkD8vsDSgkElJKSokAgFsaIBTP2TH0+n0zTlGVZMgxTlmXKNK2mZaZMMzYfW2/Isqz4MtM05ThO0y3a4n7s5rrOXsvcdte5rttimbvXfGz9nmWxqWEYTXW1rHFPre29ppbrbduO3ywrNnWcOlVWNsq2rVbrTNPs4iMB3cVxHFVVVaqyskIVFRWqrKxodb+iolzlFRWqralWOByS67qd9tymZSk1Nai0YJrS0zOaAhlp8UBGc0AjKytbOTm58S/10fVou+j7bRfdeV7dE84jTNsv/+Bj1LBxgW644WpNn360SkqmKDMzW/X1daqsrFBVVaUcx1Vubq4GDCjSwIFFCQ9lU11dpT/+8W6tWLFMkmR7PPraGWfrhBNOImAGAAAAoM9JWg8X0WhU77zzjoYNG6bq6mpNmjRJXq9XWVlZev/99+X1elVbW6sZM2ZIkkpKSlo1RkyZMkXbt2/XAw880KrRYtCgQXrggQdaPZ/Pt2ds9WOOOabVuilTpmju3LmaN2+errrqqg7VP2rUqHiDhSRNnjxZrutq7dq18vl82r59u2bOnLnffUycOLFVA+2UKVPU0NCgLVu2aPjw/V9hcPrpp+uBBx7QZ599plGjRumZZ57RkCFDNHnyvq+SmD9/vp544glt2bJF9fX1ikQindpICAAAgO4R6xUjIHkCspTbZn3LQIYbbZTrhOVGw3KdsOSEFXEiqo6GVV0ZllteLrllkhORnJCcaFiuE03Cq+qdjKbwhm3FAhiWZcmybdlNwY3meU/T/ZYhDqvFNrEQh0ceT+zm9Xqb7nv3M79nmc/nldfrS/gLsb4uHA6rurpKNTXVqq5uvlU1BSsqVVlZrvLyclVUxoIU7Z0fmbZPhu2XTJ8MO1VGMEcew5JMS4ZhSYYlmWb8vmG2nrZaZphyo6HY32W0UW6kMX6/IdKo+qpG7SjfITmb5EYb5UQa23lVhjIzs5Sfn6+8vLa39PQMvszsRLRd0HbRF5meVPmHfE6hXSv09qK3tXDhf/e7vW17VFQ0SEOHDtOYMeM0btx4BYNp+9x+06aNuvPOW7W7vFzevAmyU/IV2vmJHn30Lyov360zzjirs18SAAAAACRVUlrk8vPzNXLkSC1atEjbt29XSUlJ/MqIo446SosWLYo3YOyvu8xJkybpxRdfbLXMtu2ErvbweDwaP3681q9ff1CvJRmKi4s1ZswYPf300/r5z3+uZ555Rqeddto+t3/++ed1/fXX67LLLtPUqVMVDAb10ksv6bbbbuvGqtHZog2xq2Msf1aSKwH6FyuV3mUA9GwtAxkHw3WjUjQi141IrivJbfqyy5VcJ75MritXTfMt1rtN62QYMmRIhiHtNTVktrtcMpq+LG6elyRTMhRb12r72LJW+9jzKmK1NtfpupKcVnXG6m/9mlzXaZqP3dz93o82PYejqOso6sTuu1FHijhSQ2wb1w3v2adiNRnN+4g/f1Su48h1IvvsnaQjLMuW1xsLX/j8fvl9Pvn9fvn9fnm9sfs+n6/N/ZYhjtjj94Q59iyPzXdXqMNxHIXDoRbDcuwZmiMUCqmurq5VmCI2rVJlVVVseXW1QqH2AguSZMjy+CU7IFl+mXauPNmDZNgBGXZApscvw/LH5k2rU1+XYXklBQ+4nSS5rrMnoBFpkBuukxOuUU24VtWbdmnNuo2KhutaPcb2eJSXm98qkJGbm6+cnJym3jPSZVmd+5r6MtouDk1vaLvozvPqnnQeYXoC8hdOlps3Xk6oWm6kXrK8Mu3Y+58MyQnVymmsVLRhtzaXVWjTloX6z39ek2mamjChRDNnztK4cRMUCMQ+bzQ0NGjBgpf0z38+Idf0KjDkeFmBHEmSf/AcNW5/T88//29lZWXrc587OZkvHwAAAAA6VdIugZoxY0a80WLatGnx5dOmTdM//vEPeb1eTZs2bb9X5yxfvlx5eXmHVIfjOFq5cqWOOOKIDj9m1apVqq2tVWpqqiRp6dKlMgxDI0aMUE5OjgoKCrRw4cI2V6S09NFHH8lxnPiVIkuXLpXf71dRUdE+H9PS6aefroceekif+9zntH79ep1++un73Pbdd9/VEUccoW9961vxZVu2bOnQ86DnatwRG//1UMaQBZA4X27HxnkGgN7KMCzJtmTId+CNeyxDMsyWc72G67pNYY5YCENuUwjDicbCMG601X3XaZ5GJCeiiBNR2Imoti4itzYkObWSG5XRtI3rRGI9nhxksMMwzT29cdgemaYpwzRkGKZMw5Bh7jVtvt/O8uYgxd6hikgkLMfpeH2Gacu0fZLlk0yvDCtVRjBbXssno/lmN9/3y7A8MoyePxyMYZix3jVsv+TLaHcb14nICdfJDdfEvhwN16isukal5evlLlsmJxpu85iUlFSlp2coMzNT6ekZSk/PUEZGLIzRfD+2PF0ez76HjOgvaLvo220X3Xle3RPPIwzLIyuQ3e665qHNPBmxYJDrOnIayhWu2qSPPlmuDz54T6ZlKTc3X36fT5u3bJITjcpOGyR/4VSZtn/P8xiGfIWT5Ubq9eijf1FlZbm+9KUzuiUA5rquQqFG1dXVKSMjk+HAAAAAAHS6pAYuHnnkEW3ZskUXXHBBfPlRRx2la6+9VqZp6le/+lV8+d13360JEyZo2LBhqqur0z/+8Q/95z//0T333NNqv47jqKysrM3zZWdny7Is3XzzzTruuOM0cODA+Dio69at00033dTh2l3X1eWXX64f//jHKi8v14033qiTTjpJAwcOlCT96Ec/0g033KCcnBydcMIJikajeuutt3TmmWfGk/+7du3SDTfcoHPOOUcbNmzQXXfdpbPPPnu/Y6C29MUvflG33HKLrrvuOk2ePFmDBw/e57bDhw/Xk08+qQULFuiwww7Ta6+9phdeeKHDrxcAAABA9zAMQzJsSbaMLvweKhbiiDQFNpqnTqxnk+ZAh7NXqKNF2CPsRBVyo5LjNnXcsafnk6ZnaOrVQ3K1p7eU2PKm9U3DbMj0SUaKDI8l+SzZhiUZ5j6G5WgawsP07glRmP13KBXDtGX50iVfept1ruvGesgI18RCGU09ZYQjDdpZ26CyytLY8CWRhnaDGZLk8/kVDKa16PXE0+p+y6Fw2r8fG0bHbBp+xzBMWZYp07Ti05SUgGbMmNru8/cEtF3QdoEYwzBlBXJkBXLk5k9QtH6nojXbtLuuRm5Ng+zMw2WlDpSVktduAMkwTPmLZqpxx3t67rlntPT99zRp4mQNHTpceXn5Kioa1O5xFRsGZ7XeeWeR1q5do7KyUqUGg8rOylJh4UDl5uYqIyNLmZmZysjIVGpqUK7ratOmDfroo/e1ePEiVVdXSpK8Xp+GDBmq7OxspaYGZVmWMjOzNGTIMA0ePIRhmQAAAAAclKS1TB111FHxVPn48ePjywcPHqz8/Hxt2bJF06dPjy+vrq7Wddddp7KyMqWkpGjUqFF68MEH24w3umHDBs2aNavN87300ksaOnSoSktL9fOf/1y7d+9WZmamxo4dq7///e8JXSVSUlKi8ePH69vf/rZqamp0zDHH6Prrr4+v//rXvy6v16sHH3xQd955p4LBoEpKSnT22WfHt/nCF74gr9ers846S5FIRF/4whd0ySWXdLiGvLw8zZw5U//9739bPXd7vv71r+uzzz7T5ZdfrkgkomOOOUYXX3zxAR/XW7hOROHyNbHG4X7Eaeo+uHHnJ0mupO9ovtKTnykAAMA+mJYMWZLV9T2HxIdxUVhutIufrL9oGnLI2HvIIdeJ95LS3BOKmnpLKa8JS25jmyF4DO01XI/r7Bl+KAH5+fmaMeOBznqFnY62C9ouJMn0MZRnS4Zhyk7Jl52Sn9jjTEv+AUfJSslXacUaPf/Cc/FwnmmaKioarKFDhykvr0CmaWjHjh1asWKZdu3aKcO0ZPqzZHiyVFcdVmn5Fi1fuVLuPgJjzXVawYHy5g+TYdhyQlVat6Vc6zZtl5yQXMeREw3Ft/f7A/J6fbJsWz6vV8FgUNnZ2fL7AzJNUw0N9aqvr1c0GpVkyOfzKhBIUTCYpszMTGVmZislJUWWZWn58kZ99tlarV27Wlu3bVVlRYW8Pp8yM7NUNLBIhYUDlJ6eIZ8v1qOY67pyHEfRaESRSEShUFjRaESGYWjy5CM1ePCQxH9RAAAAALqF4bpuYq0h/dzll1+usrIyPfDAwTcInXvuuRo+fHiPaDRI1K5dNXKcrj9k8vLS9OSTz+jhh+9vZ0zuvRxEox4AAAAAIPny8/MP6fwa7evvbRdSrP1i8+bNuuqqn8sQrQbovQxDnTYUViJDdvV1F1/8M02aNCXZZXS6vLw0lZVVJ7sM9EMce0gGjjskC8de/2SahnJygu2u6799r6LHKymZovLy3YpE9t9zRTgc1qpVn6qxsVHRaEThcETRSFiRSFiRSOzKgGgCJ5Q+y5DXMuWzDfktQwGPoTSvpTSvqaDXVJrXjM+neMxeNSY4gP7prx+XS5LOG8+VeUAy8bcIoLP0pfcTb0ZOsktAH1ZYOEDnn3++5j/+uGpqayVJA4K2DsvyJbmymI9K6yVJE/IDB9iydzxPT6+hp4u6rrbVRLSzLqLGqKtQ1FWKx1CW31ZOwFK6z5SRQCtUY9TR1uqINlfvuxeQ/iojI1N5eQXJLgMAAAB9BIGLFrZu3aovfOEL+1x///3394gapk7tuePbdqa0tHSdfvr/dMq+HMdRKBRSfX29GhrqmqYNTdP6eLeQe+YbmubrVFNdpa0V5aqtq22zX9MwFPRaSvMaCnrMPaEMn9kqpJHqMWUyDiiAZGl6+7FM3oeApOJvEUBn6UPvJxbnSQmj7aLjTNPUl7/8ZU2ZMlNvvPGaXnrpOW2rqNDgNI9OHpmW9ONvY1VsOIsThrV/lVRve56eXkNPVB2KasXORn22u1EbqyIKRVtfMFQXdlUXDmtLdVhBr6WiNFuFqbay/Zay/JZMw1DUddUYdVXZEFVFY1Q766IqrXdUXr8naJGfn68RIw7T0KHDVVBQqIyMTAWDaXKcqMLhiBobG1RfX6e6ulgwxrJMWZattLR0paWlKRhMk9/vjw+x1Mx1XYVCjaqurlZFRbkqKipUV1erurpaRSIRpaamKhBIVU5OjvLzC5Weni6D930AAAD0MQwp0kIkEtGWLVv2ub6goEB+v7/P17A/3TmkSE/rjiccDqmysjJ+AllZWR6/H5vuVmVFRfyqmZZMQ0r12k3BjD09ZmT4LWX6LGX6LaV7zT7RYAqg51m1u1GSdHh2z7iSD+ivHvpotyTp2xOyk1wJgN6uL/1v96bnaPz3/1+yy+hVekK7QU+o4UCa2y9ati9EIhE9+eTjevHF53RYlldfHZ0hv905QzUcjO76W+4Jn0H60vuWJIUdV6t3N2pzdVi76qMqb3QUdSVTkm1K6V5TGT5T6T5LGb5YG5AhKeJKNaGoNleHtbk6om3VYbmKBSLGjZuo0aPHaMiQoQoEUuX3+1VVVamyslJt27ZVa9eu1urVn6qsrFT7as21LEv5efkaNHioiooGacSIkRo+fKRSUwm69Bc9sU0V/QPHHpKB4w7JwrHXPzGkSAfZtq2hQ4f2+xrQPo/Hq9zcPOXm5u13u0gkosrKilZhjD3z5aoo361tlRWqrqlp9ThDUrrfVobXUGaLIEaGz2yaWrIJZAA4CH2lURMAAMTwv71/6wntBj2hhoNh27a+/vVvqKCgUI888qD+8nGFzhufqUCSQhf96W+5L7xWx3W1riKkj0obtHJ3SI0RJx5wKBw0QB6PR67rqLGxUZWVu7VuR6kaQ/Xt7svr8WjosBE6/YTxmjLlKA0cWNRuzw/N7VBjxozT8cefKCk2tO7OnWXatatMrhs7rr1er7Kzc5WRkdGmFwoAAAAAXYvARZPi4mLdfvvt++0SE+gI27aVk5OrnJzc/W4XDodVXr5bO3eWNZ0o74yfMG8uK9XHZRVq2QGNISnos5XpM5Ths5TpN+OhjMymKyY8FoEMAAAAAOiraLvoHMcee4Kys7N1112369FPKnXOERnyWXxJjZio6yoUiQ3TUR2KqqwuqtLaiJbvCqmqMaKA368jp8/RtGkzVFw8Rrbdtnk1Ly9NpaVVqq+v0+7du1RRUS7JkMfjUWpqqgYMKJJlWQdVn8fj0YABAzVgwMBDfKUAAAAAOgOBiyZvvvmm0tPTO7x9WVmZZs2apb/+9a+aNm1aF1aGvsrj8Sg/v0D5+QXtro9EIqqoKN8rjBGbbi/boeVbyuU4rcf2DPpiPWRk+Exl+Cyl+0yle5umPktBr5n0MWoBdL9tNbGxewcEPUmuBOjfClP5GwTQOfjf3n/RdtF5Jkwo0fe//2P97//+QY8tr9TZ4zLl6eZeJbvrb7knfAbpye9bUcfV6vKQ1lY0amNVRNtrYsN8tGTbtsaMGadZs47RpEmT5fF4D7hfwzCUkpKqlJRUDRo0pGuKBwAAAJB0BC6a5OXtf5iIrhQKheT1HvhErbMfi57Ntu39DmHiOM5egYyd2rWrqbeMnaVaVVqucDjc6jGmEQtlpHuMeAgj3ds8piihDKCvemFtbDy5ZI7ZDEA6ZWRasksA0Efwv73/ou2ic02ZcpTOP//7+vOf/1d//6RCZ47NlLcbe47srr/lnvAZpKe9b0UcV1uqw1qxs1Ef72xUbSgqj8ejkSMPU8mIw5WeniG/36/09HQNGFCkvLx8huoAAAAA0K4+G7j473//qx/+8Id699135fP5VF1drWnTpmn27Nm67777JEnPPvusbrjhBi1atEijR4+Od8u5efNmnXDCCfrDH/6gp556SosXL1ZeXp5+8pOfaO7cuZKkWbNmSZLOO+88SVJRUZEWLFggSfrPf/6ju+66S59++qmys7N1/PHH66c//amCwaAk6dxzz9WwYcOUmZmpp556Sj6fTwsWLNDxxx+v008/Xdu3b9eLL74or9erM888Uz/5yU/i4zg2b7Nz5069+OKLKi4u1rx587R+/XrddtttWrRokUKhkIYPH67LL79c06dP11NPPaVrr71W9957r2666SZt2rRJY8eO1fXXX6/i4uJu/b2g85imqezsHGVn57S73nVd1dXVavfu3Sov36Xdu3dr9+5dKi+PTXfv3qnVpbsV2iuUYUhK89tK8xhK97boKaNFjxlBrym7m6/8AQAAAIC+hraL5LddzJw5W47j6KGH/qRHllXo7HEZ8tt8sd6X1IcdbawKq7QuooqGqHbVR7WlJqJw1JFlWZo0abJmzTpW48aNb3d4EAAAAADYnz57FjFlyhS5rqulS5dqxowZeuedd5SRkaF3331X0WhUlmVp8eLFOuqoo+INAnu79dZbddlll+nKK6/U/PnzdcUVV6ikpESDBg3SM888o9NOO0133XWXSkpK4uMuLly4UBdffLF++ctfaubMmdq1a5d+85vf6KqrrtIdd9wR3/ezzz6rL3/5y/rrX/+qaDQaX/6Xv/xF3/72t/Xkk0/qgw8+0HXXXae8vDx94xvfaLXNBRdcoPnz5ysajaq0tFRnnXWWxo0bpz/96U/Kzs7WypUrW72WSCSi3//+9/r1r3+ttLQ03Xrrrbrwwgv10ksv9cirTHDoDMNQampQqalBDR7cfteVzaGMWAhjTyAjHsrYtVNrd+5WYyjU5rFBXyyUkeY14sOWpDX1mJHWNE8jFQAAAADsG20XPaPtYtasY+Tz+XTffXfrLx9X6JxxmUr1cj7bmzVGHS3dXq8PSxu1o8UQIampqcrLK9QxR47S6NFjVVw8RqmpwaTWCgAAAKB367OBi5SUFI0fP16LFi3SjBkztHjxYp1++ul69tln9fHHH2vSpElavHhx/CqP9px33nn6/Oc/L0m69NJL9cgjj2jJkiUaNGiQsrNjXSBmZGS06tLz3nvv1be+9S2dddZZkqShQ4fq2muv1RlnnKFrrrkm/rjCwkJdffXVbRpMxo0bpx//+MeSpOHDh2vVqlV6+OGHWzValJSU6Ec/+lF8/ve//71s29bdd98tv98ff96WHMfR5ZdfriOPPFKSdMstt+jYY4/V888/r9NPPz2Bnyz6kpahjH2NJ+q6rurr6+KBjIqK8ngoo7x8t8p379KW8t2qratt81ivFesZI81jKM1nxnvISPPu6TEj1WPKZAgToEt9dXRGsksAAACdiP/tfQdtFz2n7eLII6fL6/Xp3nt+rwc/Ltc54zKV5be69Dn7099yd73Whoijt7fU6Z1tDaoPRzVy5GE6/XOTVFw8RkOGDFMgEOiWOgAAAAD0H302cCFJ06ZN06JFiyRJixYt0qWXXqqysjItWrRIBQUF2rBhg6ZPn77Px48ZMyZ+37ZtZWdna+fOnft9zmXLlunDDz/UX/7yl/gy143l6Dds2BBvtDjiiCPavTqlpKSk1fzkyZP14IMPqrGxUT6fT5I0fvz4VtssX75cU6ZMiTdYtMcwDE2aNCk+n5WVpeHDh2vNmjX7fT2AYRhKSUlVSkqqBg0avM/tQqFQizBGucrLd6m8vFwVFbFgxqZdu1S5s1KO47R6nGnEesvI8JrKCZjKDdjKCVjKTbGV5bcYugToBGnerm0oBgAA3Yv/7X0LbRd7JLvtYuLEEl328yv1hzt+pwc/Ktc54zJUkOrpsufrT3/LXf1aQ1FXS7bV6c3N9aoPR1VSMkWnnnqaRo48vEufFwAAAAD6dOBi+vTpuv/++7V582atXbtWRx55pHbu3KnnnntOhYWFys3N1WGHHbbPx3s8rU+qDcOIN0Dsi+M4+v73v68vfvGLbdYVFBTE7x9Koj4lJeWgHwt0Fa/Xq/z8AuXnF+xzG8dxVF1d1SKUEQtjVFSUa2dZqdZu26oPdlTFtzcNKTPgUY7faBXEyA1YSvWY++xSFwAAAAB6C9ouepbDDy/W5Vdcp9tv+60e+aRKF07KUpDhRbpdTSiqj8sa9OmukOoirhqirkxJ+SmmClI9SvOa8lmGIq6r1btDWlMRVijqaPwRE/SV/zlTQ4cOS/ZLAAAAANBP9OnARfP4pPfee6/Gjh2rYDCo6dOn68Ybb1ROTo6mTZt20PtubtDY+2r9cePGae3atW26xeyoDz74oNX8+++/r0GDBsWvEGnP2LFj9c9//lMNDQ37vFLEdV19+OGH8W45KyoqtG7dOn3rW986qDqBg2GapjIyMpWRkalhw9rfpq6uTjt2bNO2bVu1ffs2bd++Vdu2bdW7O7YrHInEt/PbpnICViyEEbCUE7CVm2IpO2DLQ68YQCvv76iXJJUU0H0ukEz8LQLoLLyf9C20XezRU9ouBg0arEsuvVy/ufFqPflppc49IrNLhsLsrr/lnvCe0dEadtdH9Mr6Gq3c1SjHlYYMHqLB+QUKBFIVCjVq86YNWr1le6tjOjMjUzNnz9L06Udr1KjRXfo6AAAAAGBvfTpw4fP5NGnSJD399NO64IILJEmDBw9WTk6OXnjhBV1zzTUHve/MzEylpaXpzTff1GGHHSav16uMjAxdfPHF+s53vqPCwkLNnTtXfr9fa9eu1WuvvaYbbrjhgPtdtmyZ7rnnHp166qn68MMP9be//U2XXXbZfh9z9tln67HHHtNFF12kH/3oR8rNzdWnn34ab6SRYl9033zzzbriiisUDAZ1++23KyMjQ6eccspB/wyArpCSkqLhw0dq+PCRrZY7jqPdu3dp+/atqq7erdWr12v79q3atG2LPiqtiG9nSMoI2Mrxm8oNWMoN2CoM2hoQ9DA8CfqtD3pAAysA/hYBdB7eT/oW2i56ZtvFkCFDdc655+uhh/6k1zfU6vhhwU5/ju76W+4J7xkHqiEcdfXm5lq9tblOlsejkz8/V0cfPUcDBxa12TYSiaiurlb19fVyHEeFhQPoARMAAABA0vTpwIUUGwt18eLFrcY7nT59up588sn9joHaEddcc43+8Ic/6OGHH1ZBQYEWLFigGTNm6MEHH9Tdd9+tv/3tbzIMQ4MGDdKJJ57YoX1+85vf1MaNG/WVr3xFXq9X5513ns4+++z9PqagoECPPvqobrnlFl1wwQVyHEcjRozQL3/5y/g2tm3r4osv1lVXXaXNmzdrzJgxuu+++/Z79QnQk5imqdzcPOXm5ikvL01lZdXxdQ0NDU29YsR6xNi+fZu2b9uiD3ZsV2Mo1qhjm4YKg7YGp3k0KM2jwekepfv6z3i5AAAAQE/huq7CjlQbduRaEY1PdkE9AG0XMT2t7WL27GO1atWn+s+bb2h4plfDM71JqaOv21QV0r9W1WhXXVjTps3U1752trKysve5vW3bSk/PUHp6RjdWCQAAAADtM9wDDeyJbnP88cfrzDPP1Pe+971O3e9TTz2la6+9Vh9//PEh72vXrho5TtcfMnt/oQ601NHjw3Vd7d69S+vWrdWaNau0ZvWnWr9hvSJNQ5Nk+G0NCloalO7R4DSvCoM2vWCgT3piRYUk6YwxmUmtA+jvHvpotyTp2xP2/QUCAHREMv63N4ckQlFHjVFXoai7Zxpx218ebblcCjlSKOqqPhxVpOm8Mj8/Xw888EC3vQ4cut7QdiHtab841PaFUCikK3/1U/lC1frupKxO7Umhu/6We8JnkPZea33Y0Zuba7VwS52yMrN1/gXf19ixRySnwE5GuxaShWMPycKxh2TguEOycOz1T6ZpKCen/Z4P+3wPFwD6L8MwlJOTq5ycXE2depSkWNejGzasjwUwmkIYn6wtlxTrBWNA0I73gDEojV4w0DcQtAAAoH2OGwsL1EUc1YUdhaKuIo4UcVxF3X3cd5ruuy3ut9leirhS1GmeujKM2PB3hmHIlFrMt56aTVM1LTPVcr0RmzZt87dPYp9j5baaxKZue/Puvte3szzkKBaWiLhqjETV0ei9x+OR3+eT3x+QPzUgvz+gjEBAfr9ffn9AKSkpSktLVzCYpry8vA7uFUgOr9er0790hh588D6t2NWosbn+Ttt3X/6c7rquyhui2lwdlmkYmlIYkNc2taEypLDjauWuRn1Y2qhw1NHRRx+js846VykpKckuGwAAAAASRuACQL9i27ZGjjxMI0ceJik2DnB5+W6tWbM6HsBYsmG93t5SJ2lPLxiD070alO5RYSq9YAAAAPRUYcdVXdiJ32rDjurCLZZFmqdSXcRVXSiiRDvwsy1Ltm3Ltm15PB75fF4ZtiWPxyuPx6OA7Wm6b8u2PfJ4PLIsS64rua4jx3Hkum7Tbc+847hNU0eu67S4v2d5fJ3jKtr0WGlPECM2YzTNx1IZsYBHLKUR2ya2rvkWe8ie6Z77pvz+ptBEU1Ci9bS9ZQH5fD5ZVsdDyyafrdELzJw5W8//3zNasKFMo3N8Mjuxl4u+JuK4emNjrT4sa1RVQ2Sf29m2rekzZutzn/u8hgwZ2o0VAgAAAEDnYkgRJIQhRdATdPXxEQ6HtXHjhqZeMD7T6tWfqby8ZS8YHg1OszU43aOhGV6leMwuqwUA0Hf0hO68gd4kHI31PFEfcVTfFJqojziqj7hNQYrm8IQbC1CEogpFnXb3ZRiGUpt7VUhLV3p6rHeFYDBNaWnpSkuL3ff7/U0hiViYwrY98dCEx2PLsmyZZuvPfpy7HJr9dckJHIrOGlKk2bvvvqN7771Dp49KV0lBoBMq7D7d9RlkW01Y//ysWqW1YU2cOFlHHDFBhx9eLMuyVFNTrfr6+qb3U48GDBiotLT0Lq0nmfjfgGTh2EOycOwhGTjukCwce/0TQ4oAQAI8Hs8+esFYpdWrV2nN6s/0zoZ1WrilToakwqBHwzI8Gp7p1dB0j3w2AQz0LM+viX34O2VkWpIrAfq3z4/gbxD9U9Rx40GJeGgi3BSmCO+1PKqmcEVUkf0EvX1ebywskZ6m7LR0DW0KTTQPUxELUqTFl6WkpLYJSgBAIqZMOVJDhwzTGxs3a0KeX1Yn9M7SXZ/Tu/ozSDjq6j+bavXW5jqlpaXrkku+pwkTSrr0OQEAAACgpyBwAQAdkJWVralTp2nq1GmSYr1grF+/VitXLteKFcu0ZPUqvb2lTqYhDUzzaHiGV8MzPBqc7pXHortZJNf22nCySwAgaUDQk+wScACO6yrsuApFD3CLb+O0Wh5xJEdubOgIKT51mudb3ndjN0exce7j69zYfHx50/aGJMs0ZBqSacSmltE8v9dNLdaZse2t+PrWjzXUXENzfW7rul23Vc3x19eidmcfr7chKtWHo2qMtN/rhCSZpqnUlBQFg5kKZqcpMzVNwWBQwWBQqamxWzCYptTU1KYgRWyZ1+vtoqMAANpnGIZO/9JXdeedt2rZzgZNzD/0Xi6663P6oXwGKW+IqqwuotqQo4aoowyfpZyArYBtqCbsaFddRK9trNPu+ohmzpytM888V8EgvdYAAAAA6D8IXADAQfB4PDr88GIdfnix5s79skKhkNasWaUVKz7RiuXL9Nb6tfrvplpZpqHBaR4Nz4yFMAameWQzTjXQL0WcWBf44Wjsiu3mLyfj9xX7hrL5S9m29922j2lxX64ryzRkGYYsMzYEkmU0T1svMxh3HH2I48bCDo1RV40RVw1RR42RpvmW91usaw5MhB0pFFVsPuLscziK9pimKZ/XK5/PJ7/fL19KQB6vVx7TlGmaMgyjaRqbb73MaLNs/48x5DiOolFH0Wik6X40fnOclvcdRSKR2LJIVKFoVNFoRNGmeSf+uNi+XNfdRy2mTNOQaZkyTFNmU01G03rTMGU1zVuW1U7thgKBlKbARLDNtDlE4fcHeE8C0GtMmDBJAwoH6O0tOzUhz99n37+ijqsVuxr13vZ6rasIHXD7gvwC/fyi72jMmHHdUB0AAAAA9CwELgCgE3i9Xo0ZMy7WwPSVr6m+vl6rVn2qlSs/0fLly/T6xg16za2VxzI1JN2O9YCR6dWAoC2zjzbSoec4LMuX7BL6HNd11RCNdYFfG3ZUF3ZUF9573lFtxFV9RKoNRRP6IrerxQIYRiyA0Tw1FAtlGGq63zKwofi2e+5Ldnw/sX3u2c9ey1psu/fjjaYr7Ju/sIjPN92XWq8/FE7TlfixW+x+tJ1lLbfb1/qWPRg4zYEYt0VPAXv3WND0/K17AWjdk4C0p4cCQy17Lmj/foe2abm8aXtj7+1lNC3be/8H93N34z/b2Bc2Uddtcb/tNNK8jaNW24ad5pCEq8aIEw9NNEZdNTpqmnf223tCS/6mYEQgkCK/P6BUf0B+v19+v08+n18+nz8WnPD55G9a5/PF1hUWZqu+3mmx3i/b9vTZL9oAAO0zTVMnf/6Levjh+7W2IqSRh/g5O5HP6RHH1cLNtdpWE1HIceU4UkGqrcHpHg1O9yjdZx1wH47r7vf8Mxx1tXRHvRZuqVdlQ0Q52dn68pc/p7Fjxyk9PUOBQEC7du3U9u3bVFdXp4yMDGVkZGrIkGHyeOjJCwAAAED/ROACALpAIBDQhAmTNGHCJElSTU2NPv10RVMA42O9sn6bJMlvmxqa4YkHMPJTLL68QaebPTg12SX0Cq7rqi7iqrw+qorGaOvgRPP9iFQXcVUXispp7l5iLx6PR2nBoIJp6cpOz1AwmKa0tPSmaZp8Pp8Mw4jfpNjV61LzMrVa13LbPctjDf6SWi2LRCKKRiMKhyOKRMKKRCIKh8NtlsVu4f0vC4cViYRVH7+/Zx/RaEThSOwq++7S/M5oGEY8jNE2pGGo5VtoPCDhuPGwQ0/V/Hvszp9pRzSHMPYEN4xWQQ5DTcGUeGgiduvMn7XP61UgEJDfH1AgmKL0lBQFAikKBALxqd8fUEpKLEgRW956nd/vj//NHIy8vDSVlVV34qsCAPRWM2bM0lNPPqaFW+oPOXDR0c/p22rC+udn1SqtDWtA4YB470Dvbd6oRVvrJEkZfluD02xl+k35LFOmIVU0RLW7PqqqsKvakKP6cFR+j6Usv6kMr6kMv6VMn6WGiKOtNWFtqo6qPhzVYSMP0ze/8CVNmDCpzf/PYDBNQ4cOP6TXDQAAAAB9CYELAOgGwWBQU6YcqSlTjpQkVVZWaMWK5Vq58hOtWP6xPl27U5KU6rU0LN3W4HSvCoO2ClNt+e2D/4Kov3NcV/VhV1WhqKpDjqoaY9Pm+43RFlepNz2m5XyrdW7bZW6LL3D3XO0eW+KzTAVsKWAbSvGYCtimUjxG09RUim0o4DHj67wWQZvu4Liuqhod7W6Iqrw+Eps2RFXeEFvW3pXyqSkpSkvLVDAzQ0Vp6UpLS2u6pbcJU8QCFf4kvLLkaB66oHV4I6xIJNq0LHzAcIfrOrG/pfhN7SxL9Bb7PVqWLcsyZZqWLCt2M5uGP4jdt2RZpizLVkZGiurqwk3rWz4uNt/8uObhFloOndD+kBBG62EZ2tm+5eOaNb+G5qEhYkNF7Jm6rtNiCAmnnW2iLR6/Z3nzcBTN28emTqvnabusvfloi2Wxn7VlWbJtW7Zty7Ls+P2Wt5bL995mX49v7mniUIISAAB0No/Ho8+deIqeemq+tteGVZi6/54dHNfVxqqwakOOGqKOcvy2hmV6O/x8H+6o1zOrqpWalqZLLrlEEyaUxNdFIhFt2rRBq1d/plWrPtOa1Z9q+a6qeIAz4PeroGCghuTmKT09Q6mpQdXW1qisrFQ7y0q1unSXwuE6GYZUWDhAJaMP0+zZx2rUqNFcCAAAAAAAHUTgAgCSICMjU9Onz9T06TMlSTt3lmnlyuVaseITrVi+TJ+srYhvmx3wqDDV1ICgR4WptgYEbQW9B+4utq8LR5uCFI1OPFDR6n7IVXUoqqjT+jprwzCUFgwqMytfwdRg/EvP2M1s1dOAabbugcAwTLXX20DzreWXgvX19aqpqVZNdbW21FSrtrJGDY2N+3w9tmkoxWspYBsKWGoR0jDjoY1YUMNU0Bu72SaNoO0JR12VN0S1uyESm9Y3hSoaXVXURxRt0TOFZVnKzclV/vBCjc0vUF5evvLyCpSXt6dR2rL4e9sX0zTl9Xrl9Xb8S4Oeqqf0YNDe+wkAAOhZjj32c3ru2X/pPxtr9bUxmfvcLuy4emplpVbsan0ecESeT58fka6gd///79dWhPT0qmqNKh6tH/7wEgWDaa3W27at4cNHavjwkTrxxFMkxcKbzaHXQCCw3+CE67qqrq6W1+uV399/QsMAAAAA0JkIXABAD5Cbm6dZs47RrFnHSJIqKsq1ceN6bdiwQRs2rNPGDWu1fP2u+PZpPjsWwkj1qDBoa0DQo0yf2WeuQmqIOKpsdFTZGFVlY4tQRaOj6rCr6qbucPfm83qVk5Ot9NxsDcrKVmZmljIzs5SVla2srNg0PT1Dtp2cf3+RSES1tTWqrq5WbW1NLJBRU6OamhrV1u65X1NTrd3VVaqprlZtXV2814y9BTxWLHxhG/EQRpq3OZBhKeiJzT+2vEIypG9PyO7eF9wFXNdVY9RVbdMwH5UN0XgvFbvrHZU3OqpujLR6jN/vV35eoUaPHaz09Gzl5xcovylckZ2dwxfbAAAASEgwGNTJn/+innnmKa0tb9SIdoYWqQ87emxFpTZUhvTVr56pCRMmye8PaOHC/+rZf/9Tayp2K+iJBa3b+5xeVhfR/JWVKiwcoIsu+plSUlI6VJthGB0OxBqGofT09A7tFwAAAADQPgIXANADNQcFWnYXW1dXq40bNzQFMdZrw/q1+u/mbfEv4/0eS4UplgYE7VgII9WjnBRLVg8LYThuLDBR2RhVZUO0VbCiMuSqstFRw15hCsMwlJGersysbBVlZSszc0+AomWoIhAIKD8/vUdcpd4e27aVkZGpjIzMDj/GcRzV19fFwxjV1VWqqqpURUW5KisrVVVVoYqKcm2rKFfljkqFI5F292MZ0v0f7I6FMjx7esmIhTRiwQ2vZcg2DdmGui280xygqGsKUDTf6sJNoYqQE1sXcVUXcVXbTq8lkpSZkaG8ggJNyC9UXl5+U6CiQPn5+QoG02QYRo/pwQAAAAC936mnnqa3F/5X/7e2XN8v8bbqfa425Oivyyq0s8HRhRdepGnTZsbXnXbaVzR16jT9+c/3av36dcrwuXJcV2aLz9+ltRH9fUWlPL5UXXLpLzsctgAAAAAAdD8CFwDQS6SkpGr06LEaPXpsfFkoFNLmzRu1cWOsJ4wNG9ZpyeZNimypkxQbpqIg1daA1FgIIz/Vlsc0ZBmGLFMyDUOW0TQ1JcswZBqxL+cP9gv3xr16p6hsdFTRELtfFXJV1RjR3t+XpwQCyskp0IAheToiJ1fZ2TnKaZpmZ+coIyOz3w7rYJqmUlODSk0NqqBg/9u6rqv6+npVVlbsdWsOaFSosrJcWyoqVFNbu9992aYh24oNWxK7SR5DskzJNhRf7mlat2e7vedj+6sLtw5V1IXdWIgiFFWknQCFFOuxJC0tTWmZGSrIyFBaWnqLW5rS0tKVk5Or3Nw8+XxtryoEAAAAuorX69U3zvm27rjjd3p7S51mD06VtCdssTskXXLJLzRu3Pg2jx04sEhXXHGt/vKXB7Rw4X/12PJKTSkMaFi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      "text/plain": [
       "<Figure size 2160x2160 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "hue_order = ['uncorrected_prcp', 'corrected_prcp']\n",
    "fig, axs = plt.subplots(2,2, figsize=(30,30))\n",
    "sns.violinplot(x='1980-2010_avg_prcp', y='clim_pcp', data = pd_prcp, cut = 0, inner='quartile', lw = 2, split = True, hue='prcp_factor',hue_order =hue_order,\n",
    "              ax = axs[0][0]) #[['clim_pcp', '1980-2010_avg_prcp']])\n",
    "axs[0][0].set_xlim([-100,3300])\n",
    "axs[0][0].set_title('zoom')\n",
    "sns.violinplot(x='1980-2010_avg_prcp', y='clim_pcp', data = pd_prcp, cut = 0, inner='quartile', lw = 2, split = True, hue='prcp_factor',hue_order =hue_order,\n",
    "              ax = axs[0][1]) #[['clim_pcp', '1980-2010_avg_prcp']])\n",
    "axs[0][1].set_xlim([-100,29000])\n",
    "\n",
    "sns.violinplot(x='1980-2010_avg_prcpsol_mean_elev', y='clim_pcp', data = pd_prcp, cut = 0, inner = 'quartile', split = True, hue='prcp_factor',hue_order =hue_order,\n",
    "              ax = axs[1][0]) #[['clim_pcp', '1980-2010_avg_prcp']])\n",
    "axs[1][0].set_xlim([-20,2300])\n",
    "sns.violinplot(x='1980-2010_avg_prcpsol_mean_elev', y='clim_pcp', data = pd_prcp, cut = 0, inner = 'quartile', split = True, hue='prcp_factor',hue_order =hue_order,\n",
    "              ax = axs[1][1]) #[['clim_pcp', '1980-2010_avg_prcp']])\n",
    "axs[1][1].set_xlim([-20,17700])\n",
    "plt.tight_layout()\n",
    "plt.savefig('global_glacier_prcp_distributions.png')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 229,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(-100.0, 3000.0)"
      ]
     },
     "execution_count": 229,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 2016x1728 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "hue_order = ['uncorrected_prcp', 'corrected_prcp']\n",
    "fig, axs = plt.subplots(2,1, figsize=(28,24))\n",
    "sns.violinplot(x='1980-2010_avg_prcp', y='clim_pcp', data = pd_prcp, cut = True, inner='quartile', lw = 2, split = True, hue='prcp_factor',hue_order =hue_order,\n",
    "              ax = axs[0]) #[['clim_pcp', '1980-2010_avg_prcp']])\n",
    "axs[0].set_xlim([-100,4000])\n",
    "sns.violinplot(x='1980-2010_avg_prcpsol_mean_elev', y='clim_pcp', data = pd_prcp, cut = True, inner = 'quartile', split = True, hue='prcp_factor',hue_order =hue_order,\n",
    "              ax = axs[1]) #[['clim_pcp', '1980-2010_avg_prcp']])\n",
    "axs[1].set_xlim([-100,3000])\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "sns.catplot(x='ref_hgt_calib_diff', y='clim_pcp', data = pd_prcp, #cut = True, lw = 2,\n",
    "            kind='boxen',  aspect=2) #[['clim_pcp', '1980-2010_avg_prcp']])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 250,
   "metadata": {},
   "outputs": [],
   "source": [
    "pd_prcp['applied temp. bias\\nref_hgt_calib_diff * -0.0065'] = pd_prcp['ref_hgt_calib_diff']*-0.0065 "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 258,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "clim_pcp                       \n",
       "CRU_pcp2.5                0.025   -1.462500\n",
       "                          0.975    2.437500\n",
       "ERA5_pcp1.6               0.025   -3.737206\n",
       "                          0.975    0.000000\n",
       "W5E5_pcp2.6               0.025   -2.437500\n",
       "                          0.975    3.575000\n",
       "W5E5_pcp_via\\nwinterprcp  0.025   -2.762500\n",
       "                          0.975    1.462500\n",
       "Name: applied temp. bias\\nref_hgt_calib_diff * -0.0065, dtype: float64"
      ]
     },
     "execution_count": 258,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd_prcp.groupby('clim_pcp').quantile([0.025, 0.975])['applied temp. bias\\nref_hgt_calib_diff * -0.0065']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 254,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "clim_pcp\n",
       "CRU_pcp2.5                  0.082267\n",
       "ERA5_pcp1.6                -0.336441\n",
       "W5E5_pcp2.6                 0.121195\n",
       "W5E5_pcp_via\\nwinterprcp   -0.099101\n",
       "Name: applied temp. bias\\nref_hgt_calib_diff * -0.0065, dtype: float64"
      ]
     },
     "execution_count": 254,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd_prcp.groupby('clim_pcp').mean()['applied temp. bias\\nref_hgt_calib_diff * -0.0065']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 275,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt;\n",
       "Dimensions:        (time: 1032, lon: 720, lat: 360)\n",
       "Coordinates:\n",
       "  * time           (time) datetime64[ns] 2015-01-01 2015-02-01 ... 2100-12-01\n",
       "  * lon            (lon) float64 -179.8 -179.2 -178.8 ... 178.8 179.2 179.8\n",
       "  * lat            (lat) float64 89.75 89.25 88.75 ... -88.75 -89.25 -89.75\n",
       "Data variables:\n",
       "    tasAdjust_std  (time, lat, lon) float32 ...\n",
       "Attributes: (12/24)\n",
       "    title:                     ISIMIP3b bias-adjusted climate input data\n",
       "    institution:               Potsdam Institute for Climate Impact Research ...\n",
       "    contact:                   ISIMIP cross-sectoral science team &lt;info@isimi...\n",
       "    summary:                   CMIP6 daily output data bias-adjusted and stat...\n",
       "    project:                   isimip3b\n",
       "    product:                   input\n",
       "    ...                        ...\n",
       "    creation_date:             2021-05-13T20:28:04Z\n",
       "    licence:                   CC0 1.0\n",
       "    description:               UKESM1-0-LL bias corrected impact model input ...\n",
       "    postprocessing_date:       2021-05-22\n",
       "    postprocessing_scientist:  lilian.schuster@student.uibk.ac.at\n",
       "    postprocessing_actions:    using xarray: ds = xr.open_mfdataset(isimip3b/...</pre><div class='xr-wrap' hidden><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-91ebe1b7-2767-4f83-bb9c-23093d22c15e' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-91ebe1b7-2767-4f83-bb9c-23093d22c15e' 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>: 1032</li><li><span class='xr-has-index'>lon</span>: 720</li><li><span class='xr-has-index'>lat</span>: 360</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-deb65757-c58d-41bf-89cd-1ad0341c9263' class='xr-section-summary-in' type='checkbox'  checked><label for='section-deb65757-c58d-41bf-89cd-1ad0341c9263' class='xr-section-summary' >Coordinates: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2015-01-01 ... 2100-12-01</div><input id='attrs-cf870863-c240-496e-8c81-ce1c2bfc735a' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-cf870863-c240-496e-8c81-ce1c2bfc735a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5bea1872-e7c9-424e-8dd9-0edd9fd48a47' class='xr-var-data-in' type='checkbox'><label for='data-5bea1872-e7c9-424e-8dd9-0edd9fd48a47' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;2015-01-01T00:00:00.000000000&#x27;, &#x27;2015-02-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;2015-03-01T00:00:00.000000000&#x27;, ..., &#x27;2100-10-01T00:00:00.000000000&#x27;,\n",
       "       &#x27;2100-11-01T00:00:00.000000000&#x27;, &#x27;2100-12-01T00:00:00.000000000&#x27;],\n",
       "      dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>lon</span></div><div class='xr-var-dims'>(lon)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-179.8 -179.2 ... 179.2 179.8</div><input id='attrs-39b52939-d352-4a26-b22a-1de1187e0112' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-39b52939-d352-4a26-b22a-1de1187e0112' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e605141d-cb9b-4254-bfc6-75a36fc29cbf' class='xr-var-data-in' type='checkbox'><label for='data-e605141d-cb9b-4254-bfc6-75a36fc29cbf' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>longitude</dd><dt><span>long_name :</span></dt><dd>Longitude</dd><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>axis :</span></dt><dd>X</dd></dl></div><div class='xr-var-data'><pre>array([-179.75, -179.25, -178.75, ...,  178.75,  179.25,  179.75])</pre></div></li><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'>89.75 89.25 88.75 ... -89.25 -89.75</div><input id='attrs-4801eb45-19fb-4954-b32d-31eaf5f7a2c1' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-4801eb45-19fb-4954-b32d-31eaf5f7a2c1' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b4c8a1a7-d52c-4387-b056-fc2296f94768' class='xr-var-data-in' type='checkbox'><label for='data-b4c8a1a7-d52c-4387-b056-fc2296f94768' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>standard_name :</span></dt><dd>latitude</dd><dt><span>long_name :</span></dt><dd>Latitude</dd><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>axis :</span></dt><dd>Y</dd></dl></div><div class='xr-var-data'><pre>array([ 89.75,  89.25,  88.75, ..., -88.75, -89.25, -89.75])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-06f6c583-e831-43ef-96f1-21dc828e35f7' class='xr-section-summary-in' type='checkbox'  checked><label for='section-06f6c583-e831-43ef-96f1-21dc828e35f7' class='xr-section-summary' >Data variables: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>tasAdjust_std</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'>...</div><input id='attrs-3fe7c2ee-6f71-4624-82b4-1f096ea93d7e' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3fe7c2ee-6f71-4624-82b4-1f096ea93d7e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e6d3eeb5-062c-4465-b075-493410f62e63' class='xr-var-data-in' type='checkbox'><label for='data-e6d3eeb5-062c-4465-b075-493410f62e63' 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>K</dd><dt><span>standard_name :</span></dt><dd>air_temperature_daily_std</dd><dt><span>long_name :</span></dt><dd>Near-Surface Air Temperature daily standard deviation</dd></dl></div><div class='xr-var-data'><pre>[267494400 values with dtype=float32]</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-a7ab8dd8-90d6-4dbd-ba32-5955c4cd2411' class='xr-section-summary-in' type='checkbox'  ><label for='section-a7ab8dd8-90d6-4dbd-ba32-5955c4cd2411' class='xr-section-summary' >Attributes: <span>(24)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>title :</span></dt><dd>ISIMIP3b bias-adjusted climate input data</dd><dt><span>institution :</span></dt><dd>Potsdam Institute for Climate Impact Research (PIK)</dd><dt><span>contact :</span></dt><dd>ISIMIP cross-sectoral science team &lt;info@isimip.org&gt; &lt;https://www.isimip.org&gt;</dd><dt><span>summary :</span></dt><dd>CMIP6 daily output data bias-adjusted and statistically downscaled to 0.5 degree horizontal resolution using ISIMIP3BASD v2.5.0 and W5E5 v2.0</dd><dt><span>project :</span></dt><dd>isimip3b</dd><dt><span>product :</span></dt><dd>input</dd><dt><span>dataset_type :</span></dt><dd>Climate atmosphere simulated</dd><dt><span>bias_correction :</span></dt><dd>W5E5-ISIMIP3BASD2-5-0</dd><dt><span>world_region :</span></dt><dd>Global</dd><dt><span>country :</span></dt><dd>ALL</dd><dt><span>time_frequency :</span></dt><dd>day</dd><dt><span>model :</span></dt><dd>UKESM1-0-LL</dd><dt><span>experiment :</span></dt><dd>ssp585</dd><dt><span>ensemble :</span></dt><dd>r1i1p1f2</dd><dt><span>publisher :</span></dt><dd>ISIMIP coordination team &lt;info@isimip.org&gt;</dd><dt><span>doi :</span></dt><dd>NA</dd><dt><span>creator :</span></dt><dd>ISIMIP Coordination Team &lt;info@isimip.org&gt;</dd><dt><span>tracking_id :</span></dt><dd>e264b3b8-3432-4371-a506-42f428e870ac</dd><dt><span>creation_date :</span></dt><dd>2021-05-13T20:28:04Z</dd><dt><span>licence :</span></dt><dd>CC0 1.0</dd><dt><span>description :</span></dt><dd>UKESM1-0-LL bias corrected impact model input prepared for ISIMIP3b. Data Set Details: https://www.isimip.org/gettingstarted/input-data-bias-correction/details/85/, ISIMIP Terms of Use: https://www.isimip.org/protocol/terms-of-use/, Bias Correction: https://www.isimip.org/gettingstarted/isimip3b-bias-correction/, Published under CC0 1.0 licence.</dd><dt><span>postprocessing_date :</span></dt><dd>2021-05-22</dd><dt><span>postprocessing_scientist :</span></dt><dd>lilian.schuster@student.uibk.ac.at</dd><dt><span>postprocessing_actions :</span></dt><dd>using xarray: ds = xr.open_mfdataset(isimip3b/ukesm1-0-ll_r1i1p1f2_w5e5_ssp585_tasAdjust_global_daily_*.nc, concat_dim=&#x27;time&#x27;) \n",
       "ds_tas_daily_std = ds.resample(time=&#x27;MS&#x27;, keep_attrs=True).std(keep_attrs=True)\n",
       "ds_tas_daily_std = ds_tas_daily_std.rename_vars(dict(tasAdjust=&#x27;tasAdjust_std&#x27;))\n",
       "ds_tas_daily_std.tasAdjust_std.attrs[&#x27;standard_name&#x27;] = &#x27;air_temperature_daily_std&#x27;\n",
       "ds_tas_daily_std.tasAdjust_std.attrs[&#x27;long_name&#x27;] = &#x27;Near-Surface Air Temperature daily standard deviation&#x27;\n",
       "ds_tas_daily_std.to_netcdf(isimip3b/isimip3b_tasAdjust_std_monthly/ukesm1-0-ll_r1i1p1f2_w5e5_ssp585_tasAdjust_std_global_monthly_2015_2100.nc)\n",
       "</dd></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.Dataset>\n",
       "Dimensions:        (time: 1032, lon: 720, lat: 360)\n",
       "Coordinates:\n",
       "  * time           (time) datetime64[ns] 2015-01-01 2015-02-01 ... 2100-12-01\n",
       "  * lon            (lon) float64 -179.8 -179.2 -178.8 ... 178.8 179.2 179.8\n",
       "  * lat            (lat) float64 89.75 89.25 88.75 ... -88.75 -89.25 -89.75\n",
       "Data variables:\n",
       "    tasAdjust_std  (time, lat, lon) float32 ...\n",
       "Attributes: (12/24)\n",
       "    title:                     ISIMIP3b bias-adjusted climate input data\n",
       "    institution:               Potsdam Institute for Climate Impact Research ...\n",
       "    contact:                   ISIMIP cross-sectoral science team <info@isimi...\n",
       "    summary:                   CMIP6 daily output data bias-adjusted and stat...\n",
       "    project:                   isimip3b\n",
       "    product:                   input\n",
       "    ...                        ...\n",
       "    creation_date:             2021-05-13T20:28:04Z\n",
       "    licence:                   CC0 1.0\n",
       "    description:               UKESM1-0-LL bias corrected impact model input ...\n",
       "    postprocessing_date:       2021-05-22\n",
       "    postprocessing_scientist:  lilian.schuster@student.uibk.ac.at\n",
       "    postprocessing_actions:    using xarray: ds = xr.open_mfdataset(isimip3b/..."
      ]
     },
     "execution_count": 275,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "xr.open_dataset('/home/users/lschuster/www_lschuster/isimip3b/isimip3b_tasAdjust_std_monthly/ukesm1-0-ll_r1i1p1f2_w5e5_ssp585_tasAdjust_std_global_monthly_2015_2100.nc')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 276,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 1.0, '90% intervals in grey')"
      ]
     },
     "execution_count": 276,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x576 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.subplots(1,1,figsize=(15,8))\n",
    "ax = plt.gca()\n",
    "sns.boxenplot(x='applied temp. bias\\nref_hgt_calib_diff * -0.0065', y='clim_pcp',\n",
    "               data = pd_prcp,\n",
    "              saturation=0.6,\n",
    "              ax=ax) \n",
    "sns.boxplot(x='applied temp. bias\\nref_hgt_calib_diff * -0.0065', y='clim_pcp',\n",
    "               data = pd_prcp,\n",
    "            #kind='boxen',  \n",
    "            whis = [5,95], \n",
    "                    linewidth=4,\n",
    "                    saturation=0.8,\n",
    "                    capprops={'color':'grey', 'alpha':0.8},\n",
    "                    whiskerprops={'color':'grey', 'alpha':0.8},\n",
    "            fliersize=0, color = 'grey',\n",
    "              ax=ax)\n",
    "plt.title('90% intervals in grey')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "uncorrected:\n",
    "ERA5 has the most  and W5E5 the least amount of prcp. over glacier regions\n",
    "ERA5 has the most and W5E5 & CRU similar lower amount of solid prcp.\n",
    "correcting with constant factor:\n",
    "balances out most \"global\" differences for prcp. between CRU, ERA5, W5E5,\n",
    "but differences remain in the corrected solid prcp. amount: even with larger prcp. correction factors, ERA5 has still considerably larger solid prcp. amounts.\n",
    "correcting with variable prcp. fac (and mostly larger prcp. fac.) for W5E5:\n",
    "results for most glaciers in even more total and solid prcp. than with ERA5_pcp1.6 (and CRU). But, for some glaciers ERA5 gives still more prcp."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 240,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 12.84800000000002, 'ref_hgt_calib_diff\\n reference - uncorrected height')"
      ]
     },
     "execution_count": 240,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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iiBQol5SUWOXUZcrgNGdEpCgmvEREVC0SiQTaCmS8QuELFKQnqmWbD7JfAOA0Z0SkGCa8RERUK14zMcD7nrZqaeuH/yWopR0iejVwDC/RKy4hoeKXBVSnPXW3S0RE9Ysy1/u6vifU6x7e4OBgHDhwoNxyS0tL/P333/Dz88O5c+cAADo6OrC0tETfvn0xc+ZMmJiYyNR59uwZevfuDQA4efIkDA0Nq9xW6Xbqk99//x27du3C1atX8eTJE+zevRtubm4K1f3ll1/w448/4s6dO9DX14eLiws2bNhQswFTvXb8+G/Yvn0zxo+fBB+fAWprr2tXD8TGnlVbu1S/CYIAhQbxqpm6xgRzLDCR8v673rsjNvZcpdd7dd9rVFGvE14A8PDwwMqVK2WWaWtrS/89bNgwzJ49G8XFxbh16xbmzZuHJ0+elKtz5MgRdOjQAYIg4MiRIxg5cmSV2yq7nfri+fPn6Ny5MwYPHoyQkBCF623fvh2rVq3Cxx9/DE9PTwiCgGvXrtVgpFTfFRQUYOfOrQCAnTu3oFcvb+jp6amlvdjYs2prl6giQuELFGYkV6uN1Kd5SEpKxNmzZ1RugwkzvWpkr/clHY8VXe/Vfa9RVb1PeHV1dWFubl7hen19fen6Fi1aYMiQIXJ7hffs2YPRo0cDAKKjo+UmvFVtqzJ+fn6wtbWFsbEx9u/fj6KiIgwZMgQhISHSX6wgCNi6dSt27tyJ5ORkNGnSBL169cKyZcsAAP369cPQoUORlpaG3377DXp6ehgzZgxmzpwJkaik+2TYsGEAgPv37yscW3Z2Nr766ivMnTsXo0aNki63t7dXaV9JM6xdGwmJRAKg5KGjdeuiEBj4sVraK6WOdokqYtXUEFN7O1arjXV/30Tq0zwUZqWqVD81K7faCXMpJs7UUChzvVf3vUZV9T7hVUZiYiL++usv6OjI7taNGzdw+/ZtDB48GIIgYPHixbh58yYcHWUvlBcvXkSPHj1gZGQEV1dXfPTRR7C2tlZ4+0eOHMGbb76JHTt2ICEhAfPmzYOxsTE+++wzAMA333yDrVu34rPPPkP37t2Rk5ODmJgYmTY2b96MyZMnY9++fbh48SIWLFgAc3NzjB8/XsWjApw+fRrPnz+Hrq4ufH198ejRIzg6OmL27NlwcnJSuV1quJKTE3Hx4nmZZXFxsbh/PxnW1q3U0l7ZdhctCoG+vn65dUlJ6nlivzIiESAIQH7+C4XrvHwhJ81m1cwY0193VanummOXkJr1DEVP06oVQ0pmDm7evI4tW9ZXqx1quLS0FH+sSl/fQO3bb93apsoyc+aEVnm9L3sfUfe9pjrq/UNr//vf/yAWi2V+Pv30U+n6ffv2QSwWw8XFBQMGDMDdu3fx/vvvy7Sxe/duvP766zA2Nkbjxo3h4+ODPXv2yJTx8vJCeHg4Nm7ciJCQENy/fx9jxozBkydPFI7V1NQUCxYsgL29PXx8fBAYGIjt27ejoKAAz549w8aNGzFr1iyMGTMGtra2cHFxKRdrx44dERgYCDs7O/j6+mL8+PHYtGmT0setrOTkkq/8IiIiMHXqVKxbtw4WFhbw8/PDo0ePqtU2NUwHD+6Vu/zAgWi1tlfq8WOeZ0REmqCq633Z+4i67zXVUe97eMViMZYsWSKzrOwDZ4MGDUJQUBDy8vKwbds2ZGZmwt/fX7o+Ly8PP//8M1atWiVdNnToUMyePRuffvopDAxK/kp68803pesdHR3RuXNnvP766zh48CAmTZqkUKydOnWS+QutS5cuePHiBVJSUpCTk4P8/Hz07Nmzyv0tq3PnztiwYQPy8/Pl9pApQhAEAEBAQAAGDRoEAAgLC8Pp06dx8OBBfPDBByq1Sw2Xr+8oxMWV/wvd17f8UJ/qtFfqs89Ca/2v+VLm5o2Rnp5TJ9tuyP7887jCX9OXjuFrqFKzcrHm2CWV6xYUC0h9ml+tGETaerC0bI6mTZtVWk5XVxuFhcVy13FIhPrwulGxqq73Ze8j6r7XVEe9T3gNDAxgY1NxN7uRkZF0fVhYGMaMGYM1a9ZgxowZAEpmJsjJyUFAQIBMveLiYhw9elQ6JvZljRs3hr29Pe7du6eeHalDpeOSy47Z1dXVhY2NDR48eFBXYVEdsrZuBTe3LjJfNYnFXVVOSuW1p452qe54e/sonDyNHPlWDUdTs0Q6+tBtZqVSXZtmtZtoMhGjuqbM9V7d95rqUCnhFQQBWVlZaNasmfRhqvpAJBIhMDAQ06dPx8iRI2FpaYno6GiMGDECEydOlCm7bds2REdHV5jwPn/+HPfu3UOPHj0U3v6lS5cgkUikvbwXLlyAgYEBWrZsicLCQujp6eH06dOVPix28eJFmc9xcXGwtrZWuXcXKOklBoB79+6ha9euAEoS/uTkZHh7e6vcLjVsAQGBmD79Xek5O3XqDLW1V0od7RJVJPXJc6z7+2b12niaB5s2DpgzJ1RNURFpPmWu9+q+16hKqTG8p0+fxtixY+Hq6oqePXvC1dUV48aNw5kz1X86tSKFhYVIT08v91MRLy8v2NnZYfXq1bh16xbi4uIwYsQIODg4yPyMGDECsbGxiI+Px7NnzxAeHo4LFy7g/v37OH/+PD788EMUFRXhnXfeUTjWjIwMhIWFIT4+HidOnEBkZCTGjRsHPT09GBkZYfLkyfjmm2+wa9cuJCYm4tq1a1i/XvYBhStXrmD16tW4d+8eDh48iO3bt8sMqXjy5AmuX7+O+Ph4AEBCQgKuX7+O1NT/njDetm2bdOgCANja2mLgwIGIjIzEyZMncffuXYSFheH58+cYOnSowvtHmkVPTw9jx/oBAMaO9a/2NDFl2+va1UNt7RJVRKRrAF2zVtX6sWnjAA8PxTs2iOjl6707gIqv9+q+16hK4R7eAwcOYO7cuXBycsKMGTNgZmaGjIwM/Pbbb5gyZQqWLl1aYW9pdZw9exZeXl7lll+9erXCOlOmTMHcuXORlpYGKysruS9mcHV1hbW1NaKjozFr1izcunULhw4dQnZ2NszMzNC5c2fs2bMHr732msKxDhky5P//YsdKpyWbNWuWdP1HH32EJk2aYMOGDVi8eDGaNm2KXr16ybQxceJEJCUlYfjw4dDT04O/vz/GjRsnXX/ixAnMnTtX+nnOnDkAAF9fX+n0ZllZWeWGYixduhTLly/H7NmzUVRUBGdnZ2zZskXladhIM/j4DIS9fTvY2rZRe3sJCXfV1i7VbyXf9Am1vt3WrW3YM0tUR5S53qv7XqMKkVD6RFMV+vfvD1dX13IvdACAjz/+GJcvX8Yff/yh9gAbCj8/P9jZ2WHRokUqt9GvXz+MGTOmXj9ElpGRC4mk9m9smohj8WoHj3PNGzXqbWiLBHw11KXCMutjHyAttxCvmahnOqUH2S9gY+/4yiW8PJ9rB49z7aiJ42xu3ljucoV7eB89egRfX1+563x9fXH8+HHVIiMiogZNS0sLEOTPHFCWSNcAeuZVz/WpCBtzcCgCESlM4YS3Q4cOiI+Plzu8ID4+Hh06dFBrYPVJbGxsuflyyzpy5EgtRkNEVL9oaWlDKK464eUQBCKqKwonvPPnz8fMmTOho6ODgQMHyozh3bFjByIiImoyzjrl7OyMgwcPVrjewsICW7durfZ2Tpw4Ue02iIiIiEiWwgnviBEjpK/lXbx4scw6kUiEESNGyCy7cuWKeiKsB6qaC5iIiIiI6i+FE96AgIB6NecuEREREZEiFE54AwMDazIOIiIiIqIaoXDCm5ubi+fPn8PCwqLcukePHsHIyAhGRkZqDY6IiBqGIknJ1GMVScstgI1lLQZERFSGwgnvF198AQMDAyxZsqTcuoiICOTl5cmdo5eIiDSboWEj5OUB+pYVTypvY8lpxIio7iic8J47dw5ffPGF3HV9+vRBWFiY2oIiIqKGw9DQGCYmJpxyjIjqLS1FCz59+hSNG8t/e4WRkRGysrLUFhQRERERkboonPBaWVkhNjZW7rrz58+jRYsWaguKiIiIiEhdFE5433rrLfzwww/Yt28fJBIJAEAikWD//v348ccf8dZbb9VYkEREREREqlJ4DO/UqVNx5coVzJs3DwsWLJC+aa2wsBB9+/bFtGnTajJOIiIiIiKVKJzw6urqYu3atThz5gzOnDmDp0+folmzZvD09ISnp2dNxkhEREREpDKFE95SPXr0QI8enFqGiIiIiBoGpRPeM2fO4OLFi0hPT4e5uTnEYjF7eImIiIio3lI44c3IyMCMGTMQFxcHPT09mJqaIjMzE4WFhRCLxYiMjISZmVlNxkpEREREpDSFZ2lYuHAh7t27hzVr1uDSpUv4888/cenSJURFReHu3btYuHBhTcZJRERERKQShXt4T548iZCQEPTr109muY+PDzIzM+W+cpiIiIiIqK4p3MNraGiI5s2by11nbm6ORo0aqS0oIiIiIiJ1UTjhHTFiBLZs2YLCwkKZ5YWFhdiyZQtGjhyp9uCIiIiIiKpL4SENenp6uHPnDnx8fNC3b1/piyf+7//+D1paWujatSvWrl0LABCJRJg6dWqNBU1ERPVHRMRamJs3Rnp6Tl2HQkQkl0gQBEGRgu3bt1e8UZEI169fVzkoqr8yMnIhkSh0ylAVmCDUDh7n2sHjXDt4nGsHj3PtqInjbG7eWO5yhXt4b9y4obZgiIiIiIhqi8JjeJUhkUjg7++PhISEmmieiIiIiEhhNZLwCoKAc+fO4dmzZzXRPBERERGRwmok4SUiIiIiqi+Y8BIRERGRRmPCS0REREQajQkvEREREWk0JrxEREREpNGY8BIRERGRRquRhFdbWxtLly6FtbV1TTRPRERERKQwhd+0BgA5OTk4efIkHj58iPz8fJl1IpEIU6dOlX729fVVT4RERERERNWgcMJ7+vRpBAUFVfgyiZcTXiIiIiKi+kDhhHfJkiVwcnLCF198AVtbW+jq6tZkXERE1EAEBQVAR0cLq1atqetQiIjkUngMb2pqKgICAtCuXTsmu0RERETUYCic8Lq6uiIlJaUmYyEiIiIiUjuFE97Q0FBs3boVx44dQ15eXk3GRERERESkNgqP4W3dujWcnZ0RGBgIoGTqsZdduXJFfZEREREREamBwgnv559/jt9++w39+/eHnZ0dx/ESERERUYOgcMJ74sQJfPbZZ/Dz86vJeIiIiIiI1ErhMbxGRkaws7OryViIiIiIiNRO4YR33LhxiI6OrslYiIiIiIjUTuEhDYIg4PLlyxg2bBg8PT3RpEkTmfV80xoRERER1UcKJ7wREREASl5AcePGjXLrmfASERERUX2kcMIrL8klIiIiIqrvFB7DS0RERETUEFXaw/vw4UOYmZlBR0cHDx8+rLIxS0tLtQVGRERERKQOlSa83t7e2L17N1xdXdGnTx+IRKJKG7t+/bpagyMiovrrzz+P4+zZM3j8OB3GxkZ1HQ4RUYUqTXiXLFmCVq1aSf9dVcJLRESvjrNnz+DW3ZsoLCzAs2d1HQ0RUcUqTXh9fX2l/x4+fHiNB0NERA2LXlMD4Gl2XYdBRFQpPrRGRERERBqt0h7e0NBQhRsSiURYtGhRtQMiIiIiIlKnShPe06dPK9wQx/cSERERUX1UacJ74sSJ2oqDiIiIiKhGKPymtV9++QWpqal47733yq1bv349rKysMHjwYLUGR0RE1VM6dVhNSEpKBIxL/l1YWIjw8LBKy3t49IC3t0+NxEJEVBmFE97vv/9eZtaGsvT19fHDDz8w4SUiqmfOnj2D23dvQd+0kdrbzi96AV0YAAAEQUDSk+SKy2bmAQATXiKqEwonvImJiXBwcJC7rm3btkhISFBXTEREpEb6po3QaqCj2ttN/u0mJBIJAECkLap0G8m/3VT79omIFKVwwqujo4OsrCy56zIzM6v90NquXbuwePFi/PPPP2jU6L+eiH79+uHp06c4d+4ctLW1AZT0JHh6emLChAmwsrLC3Llzy7X3+++/w8bGBgAQGRmJqKgoudu9evUqdHR0KixTur6++OGHH/D777/j7t270NbWhpOTE2bOnAmxWFxl3V9++QU//vgj7ty5A319fbi4uGDDhg21ELVmS0i4C1vbNgqXP3PmJHr06FWDEZEmUNdQhKSkRMCkfsxAmZSUWOWwB0VwaATRf5S9B6lapzr16gOFMzmxWIxNmzZhwIABMglgUVERNm/eDDc3t2oF4unpicLCQsTGxqJXr5JkICkpCY8ePULTpk1x5coVdOrUCQBw48YNZGVlwdPTE4mJidDT0yv3gJ2pqanMZxsbG2zfvr3cdsvui7wy9SnZBYBz585h1KhRcHFxga6uLn788Ue8++67OHjwoDTBl2f79u1YtWoVPv74Y3h6ekIQBFy7dq0WI9dMx4//hu3bN2P8+Enw8RlQZfk1a75BbOw5XLx4AfPnh9RChNRQnT17Brfv3UIj0+q9sje/KB/6UP9wBlXkF+Xj/tOUarWRl1nySjcmvETK34NUrVOdevWFwtncjBkzMGHCBLzxxhsYNmwYLCws8PDhQ/z000948OABtm3bVq1AbGxsYGVlhZiYGGnCGxMTg06dOuG1116T/rt0uaGhIVxdXZGYmAgAMDc3r7R9LS0ttZSpSHBwMNLT0+Hp6YlNmzYhNzcXffr0QVhYGExMTKTlfv75Z6xfvx7x8fEwNDSEWCzGt99+C319ffj5+cHW1hbGxsbYv38/ioqKMGTIEISEhEBPTw9ASQ9vWV9++SVOnDiBv//+G35+fnJjy87OxldffYW5c+di1KhR0uX29vYq7SuVKCgowM6dWwEAO3duQa9e3tLfkzy5ubmIjT0HAIiNPYvc3NxaiZPqRnV7aJOSEtHI1AjthrhWK47bRy5BIkiq1Ya6NDJTz/6wp5hI+XuQqnWqU68+UTjhdXV1xaZNm7BixQpERUVBIpFAS0sLYrEY4eHhcHWt3kUMALp3746YmBjp55iYGHTv3h0tWrTAL7/8gqlTp0qXd+vWDbq6ugBKng7u168fCgsL0a5dO0ybNg3dunVTevupqano3bs3tLW10aFDBwQFBaF9+/YK14+Li4OBgQHWr1+PrKwshISEIDQ0FN9++y0AIDo6GgsXLkRQUBB8fHxQWFiIU6dOScfAAcCRI0fw5ptvYseOHUhISMC8efNgbGyMzz77TO428/PzUVBQIJNUv+z06dN4/vw5dHV14evri0ePHsHR0RGzZ8+Gk5OTwvtHstaujZT+7iQSCdati0Jg4McVlg8J+VTm8/Tp07Fy5eoajZFKqJp8PnmShexs1V6bm5//AiIdLRg1b6xS/YLiAhgofol+pRQUF+BBTlq12nj2OAe3b99EdPROldswMTFB06bNFCrL5JrUTdl7kKp1qlOvPlHqatq5c2fs3LkTL168wNOnT9GkSRMYGBioLRhPT08cOnQI2dnZMDExwblz5zBmzBi0aNECixcvRkFBAbS0tPDPP/9gxowZAAA7OzssWbIE7du3R15eHqKjo+Hv74+tW7eia9eu0rYTEhLKjXN1cnKSDmFwdXXF0qVLYW9vjydPnmDjxo0YO3ZslUMFXhYeHg5j45J5ekJDQzF16lSkpqbCysoKUVFRGD9+PD744ANp+ZcTalNTUyxYsABaWlqwt7dHWloali9fjlmzZsn9a2r58uUwMTGBj0/FF9Lk5JInpyMiIjBnzhxYW1tj27Zt8PPzw6+//goLCwuF949KJCcn4uLF8zLL4uJicf9+MqytW5Ur/88/McjOfiqzrOSPok/RuHH5P1aSkhKVjik//0WF68r+UUXK0dHTgbF5E6XrFaQXwKh5YzgP61p1YTmuHIxFsaRYpbqarjrHtdSVg7F49jhH5dkrctOf4uHDNDx8qFjiffPmdWzZsl6lbVHt09Kq/rh3fX3V8qPWravOOcaN81fqHgQof9+qbr36RqXuAwMDA7UmuqW6d++O4uJinDt3Dra2tsjJyYGbmxv09PTQrFkzxMXFQU9PD8+ePYOnpyeAkrHFZRPZLl26IC0tDevXr5dJeK2trbF+vezFRl9fX/rvPn36yKzr0qUL3nrrLWzduhUhIYqNtXRwcJAmu0DJHwiCIODu3bvQ19dHWloaevToUWkbnTp1kvmP1qVLF7x48QIpKSmws7OTKbtmzRocPnwYGzdulNnuywRBAAAEBARg0KBBAICwsDCcPn0aBw8elEnASTEHD+6Vu/zAgWi5f/Xu2LFZbvmHD9PkJrykGZ49zsGVg7Eq1zUwNVRzRJqhOse1bBtEDZWy9yBV61SnXn1Tr74vs7CwgL29PWJiYpCWlgaxWCzt1XR3d0dMTIw0+a1sqIGbmxt+++03mWU6OjpK9dTq6urCxcWl3k63FhERga1bt2LDhg1wdnautGzpuOSyY3Z1dXVhY2ODBw8e1GicmsrXdxTi4s7LWT5SbvkJEyZj9epvyi0PCAhEly7u6g6PyjA3b4z0dNWSm+qMw9Uv0kV2djYKs/JVqi8UsVe+IkKRROXjWkpPW69kSIKxYkMSXmZpbFEnwxSqcz6T4ur7cb5/P1mpe1DJOuXuW9WtV9/Uq4QXKBnWUJrwenh4SJd7eHhg79690NPTg4eHR6XToF27dk3lh89KSSQS3Lhxo8pksqzbt2/j2bNnMDIqear6woULEIlEaNOmDczMzGBpaYkzZ86U600u69KlS9Lx0aVtGBgYoGXLltIyK1asQHR0NDZu3KhQfJ07dwYA3Lt3T9rrXVxcjOTkZHh7eyu8f/Qfa+tWcHPrIvM1j1jctcKvd7p0cYeJSROZYQ3NmjVjslvPeXv71Nm4y/DwMNy+dwu3j1yqVjt5Gc9q5KUTqsjLeFb9/cl8hnbtHDFnTqiaoiJqeJS9B6lapzr16pt6mfBu27YNKSkpmDJlinS5u7s75s+fDy0tLXz++efS5VFRUXB1dYWtrS2eP3+OvXv34u+//8bq1bIPA0kkEqSnp5fbnqmpKbS1tbFs2TL07dsXVlZW0jG89+7dw9KlSxWOXRAEBAcHIzAwEFlZWVi8eDEGDBgAKysrAMCHH36IsLAwmJmZwcfHB8XFxTh9+jTGjBkjnXs4IyMDYWFhmDBhAhITExEZGYlx48ZJe7rDwsKwf/9+fPvtt7C0tJTuk4GBARo3Lnk4Ztu2bdi2bRuOHj0KALC1tcXAgQMRGRmJFi1aoGXLltiyZQueP3+OoUOHKrx/JCsgIBDTp78r/QNl6tQZlZZfvHgFgoL+Gz6yZs0a5OUJNR0mNVAeHpUPf1JU0lPlx4PXFH0dfVg3aVl1wco0Ud+xIWrIlL0HqVqnOvXqk3qX8Lq7u0t7N11cXKTLW7VqBQsLC6SkpKB79+7S5Tk5OViwYAHS09NhaGgIBwcHbNiwodxY2cTERHh5eZXbXukLKh49eoRPP/0UmZmZaNq0KZycnLBz506lenjFYjFcXFwwefJk6bRkixYtkq4fPXo09PT0sGHDBkRERMDY2BhisRjjxo2TlhkyZAj09PQwduxY6bRks2bNkq4vnf7t/fffl9m2r68vli1bBqDkYah79+7JrF+6dCmWL1+O2bNno6ioCM7OztiyZUu1e8JfZSW/Jz9s374ZY8f6VzlFi7GxMbp2dUds7Dl07eoBY2Nj5OXV36/MqG6pq3c5PDys0lf+1qbWrW3YM0ukJsreg1StU5169YlIKH2iiaqldB7elx+MU4afnx/s7OxkkuT6JiMjFxIJT5myVH3TWn0fI6YpXvXjXJrw1uSrhR8nPoIIQOeAiodrJf92E62btmLCW02v+vlcWxrScW7Ib1qrieNsbi5/Ksh618NL1NAo+5+frxWm2pafmYfk327WQLvPodu0ZMYeoViodBv5mXlAU7WHQPTKUyUBVTVpbaivFQaY8CokNTUVQ4YMqXD9y28/IyKqL2pyvGtSdiJK55IQiURo3bSSh1iacuwtEdUdDmlQQFFREVJSKn7/u6WlZY3MS1wfcUiD+jSkr8waMh7nmhMeHoaEzEQ8TnwEPW1dbN++r65D0ng8n2sHj3Pt4JCGekbZOXyJiIiIqP6o/rvziIiIiIjqMSa8RERERKTRmPASERERkUZjwktERCorePICKOaDrERUv/GhNSIiUknpNGP/5lyEkZFRHUdDRFQx9vASEZFKvL19MGdOKJo3N4exsXFdh0NEVCEmvERERESk0ZjwEhEREZFGY8JLRERERBqNCS8RERERaTQmvERERESk0ZjwEhEREZFGY8JLRERERBqNCS8RERERaTQmvERERESk0ZjwEhEREZFGY8JLRERERBqNCS8RERERaTSdug6AiIgatoiItTA3b4z09Jy6DoWISC728BIRERGRRmPCS0REREQajQkvEREREWk0JrxEREREpNGY8BIRERGRRmPCS0REREQajQkvEREREWk0JrxEREREpNGY8BIRERGRRmPCS0REREQajQkvEREREWk0JrxEREREpNGY8BIRERGRRmPCS0RE1RIUFAA/P7+6DoOIqEJMeImIiIhIozHhJSIiIiKNxoSXiIiIiDQaE14iIiIi0mhMeImIiIhIozHhJSIiIiKNxoSXiIiIiDQaE14iIiIi0mhMeImIiIhIozHhJSIiIiKNxoSXiIiIiDQaE14iIiIi0mhMeImIiIhIo+nUdQBERNSwPX6cDpGorqMgIqoYe3iJiIiISKMx4dVA9+/fh6OjIy5evFjXoRARERHVuVof0rBr1y4sXrwY//zzDxo1aiRd3q9fPzx9+hTnzp2DtrY2AEAQBHh6emLChAmwsrLC3Llzy7X3+++/w8bGBgAQGRmJqKgoudu9evUqdHR0KixTul4TvPbaazh16hSaNm1a16EQERER1blaz/A8PT1RWFiI2NhY9OrVCwCQlJSER48eoWnTprhy5Qo6deoEALhx4waysrLg6emJxMRE6Onp4cSJEzLtmZqayny2sbHB9u3by223bDIrr4ymJLsAoK2tDXNz87oOg4iIiKheqPUhDTY2NrCyskJMTIx0WUxMDDp16oTu3buXW25oaAhXV1fpMnNzc5mf0t7gUlpaWuXKvJz8ySujqODgYEyZMgU//vgjvLy84ObmhpkzZyI7O1um3M8//4xhw4bBxcUFHh4eCAgIQH5+PgDAz88PoaGhCA8Ph4eHB7p06YIvvvgCBQUFVW7/9OnTcHJywqNHj2SW7969G+7u7igoKCg3pEEQBISEhOD111+Hq6srfHx8sGrVKoW2R0RERNTQ1Um3przEtnv37mjRogV++eUXTJ06Vbq8W7du0NXVBQAUFhaiX79+KCwsRLt27TBt2jR069ZN6e2npqaid+/e0NbWRocOHRAUFIT27dsrXD8uLg4GBgZYv349srKyEBISgtDQUHz77bcAgOjoaCxcuBBBQUHw8fFBYWEhTp06BYlEIm3jyJEjePPNN7Fjxw4kJCRg3rx5MDY2xmeffVbptj09PWFmZoYjR45g8uTJ0uWHDh3C4MGDoaenV66OIAgwMzPDypUrYWZmhlu3bmH+/PnQ0dFBUFCQwvtNRCSPRFIMiUSC8PAwpep5ePSAt7dPDUVFRPSfOkl4PT09cejQIWRnZ8PExATnzp3DmDFj0KJFCyxevBgFBQXQ0tLCP//8gxkzZgAA7OzssGTJErRv3x55eXmIjo6Gv78/tm7diq5du0rbTkhIgFgsltmek5OTdAiDq6srli5dCnt7ezx58gQbN27E2LFjcfDgQelYYEWEh4fD2NgYABAaGoqpU6ciNTUVVlZWiIqKwvjx4/HBBx9Iy7+cUJuammLBggXQ0tKCvb090tLSsHz5csyaNUtu0lpKS0sLb731Fg4dOiRNeJOTk3HhwgXMnj27wjofffSR9LO1tTVSUlKwdetWJrxEVG0SiQSCIOBZYoLCddILSr7xYsJLRLWhznp4i4uLce7cOdja2iInJwdubm7Q09NDs2bNEBcXBz09PTx79gyenp4AALFYLJPIdunSBWlpaVi/fr1MwmttbY3169fLbE9fX1/67z59+sis69KlC9566y1s3boVISEhCsXv4OAgTXYBoHPnzhAEAXfv3oW+vj7S0tLQo0ePStvo1KkTtLT+G1HSpUsXvHjxAikpKbCzs6u07tChQ7F+/XrcunULDg4O+Omnn9C6dWt07ty5wjp79uxBdHQ0UlJSkJeXh6KiIgiCoND+EhEpYpR1a4XL7rmfVIOREBHJqpNpySwsLGBvb4+YmBjExMRALBZLezXd3d2ly5s1a1bpUAM3NzckJCTILNPR0YGNjY3MT4sWLSpsQ1dXFy4uLuXaqc8cHR3RoUMHHDp0CADw008/4e23366w/K+//opFixZhyJAh+P7773HgwAEEBgaisLCwtkKmOpKQcFfpMorUISKi+qn0Gq7qtVxT7wF1NjWBp6cnYmJikJaWBg8PD+lyDw8P7N27F3p6evDw8ICoktf3XLt2rdqzEUgkEty4cQPOzs4K17l9+zaePXsGIyMjAMCFCxcgEonQpk0bmJmZwdLSEmfOnCnXm1zWpUuXIJFIpL28Fy5cgIGBAVq2bKlQDEOHDsXGjRvx+uuvIyEhAUOHDq2wbGxsLJydnTFp0iTpspSUFIW2Qw3X8eO/Yfv2zRg/fhJ8fAYoVEaROqR5/vzzOM6ePaNyfVW/LUpKSlR63K88HAtMVKL0Gt61qztiY88pfS3X5HtAnSa827ZtQ0pKCqZMmSJd7u7ujvnz50NLSwuff/65dHlUVBRcXV1ha2uL58+fY+/evfj777+xevVqmXYlEgnS09PLbc/U1BTa2tpYtmwZ+vbtCysrK+kY3nv37mHp0qUKxy4IAoKDgxEYGIisrCwsXrwYAwYMgJWVFQDgww8/RFhYGMzMzODj44Pi4mKcPn0aY8aMkc49nJGRgbCwMEyYMAGJiYmIjIzEuHHjKh2/W9abb76JFStWYMGCBejcuTNatWpVYVk7Ozvs27cPJ06cQNu2bfF///d/OHr0qML7Sw1PQUEBdu7cCgDYuXMLevXyLnduvVzGw6NHlXVIM509ewYJt2/Boszc6LVBkv8Cz+8nV6uNR3l5ADgWmKjsNT029hwA5a7litw3GrI6S3jd3d2lvZsuLi7S5a1atYKFhQVSUlLQvXt36fKcnBwsWLAA6enpMDQ0hIODAzZs2FBurGxiYiK8vLzKba/0BRWPHj3Cp59+iszMTDRt2hROTk7YuXOnUj28YrEYLi4umDx5MnJzc9GnTx8sWrRIun706NHQ09PDhg0bEBERAWNjY4jFYowbN05aZsiQIdDT08PYsWNRVFSEIUOGYNasWQrHYG5ujh49euDkyZMy25Zn9OjRuHXrFoKDg1FUVIQ+ffogKCioynrUcK1dGymdFUQikWDduigEBn5caZmQkE+rrEO1T9ne1ydPsspNk1iV/PwXaNnIEGPt2ykbHgAgNO2BSvUsqrHNUjvjb+P27Zv48MP3qtUOAJiYmKBp02Yq12dPM9Wlstf0UspcyxW5bzRkIoFPLiklODgY6enp5R6MU4afnx/s7OwaZMKZkZELiYSnjDqYmzdGenqO2ttNTk7E/Pnl30q4aFE4rK1bVVrmZba2bWQe+iyVlJSocDz5+S8qXPfyxZnk09fRQYsyD8pWJi2n5JyyNDRSuP2Hz5/BwqCR6gnv6b8BAPPFXaso+Z8995Mg0tZWS8L76EWeUvsrz8PnzwAALRo3Vql+Wm4u8ouKqhUD1R9lHypXlb6+gVLlW7dWfKaosubMCa3yml72+i+PIveNmlAT90Fzc/n/hzXn9WJEBAA4eHCv3OUHDkRL/1qvqMzLHj9+hJYta+5iRzXD0tAIfh1dqi74/229ehlCA/7jQ9n9lWfr1cvSpJeooanqml72+q9M/arqNSRMeMtITU3FkCFDKlz/ww8/1IsYyk7DRvQyX99RiIs7L2f5yCrLvOyzz0Jr9K/72qDOHgRVH+5SZZhBqaKiIhQWFyFZwfoSiQQPnz/D1quXFd5GaQ9vQ6Xs/lbURn5xscLHWR5dXT2FX1Ov6vCJ11/vhy5deipdj5RTU9/A1ZSqrullr//K1K+qXkPChLcMCwsLHDx4sML1lpaWakk2t27dWq0YiCpjbd0Kbm5dcPHifxcvsbirTOIqr4yJSRNkZz+tsA6VPBhV38doqpKUaykxRKU+0tLTRyMrxWa4qYgtGsYY3IaWiFHtkHdNL6XItVyR+0ZDxzG8pBSO4VWfmrxxFRQUYPr0d6VT361Zs0HuLA1ly3zzzVrMmhVQaZ2GiAlC1cLDw6o1S8O1///QmrJjeNML8mHRyFClbZZ6lJcH23YOmDMntFrtNBQ8n2tHQzzOZa/ppZS5lity31A3juGtA46Ojli1alWlwwmIGoqSGUD8sH37Zowd6y/3ovVyGWNj4yrrkGby8Kj8zZBVUnGWBi19AxhWswfJFmqIn0gDlL2ml87Dq8y1XJH7RkPGHt7/Lz09HSYmJnKfSK+ovJeXF7Zs2SLz4gxNxx5e9amNHoSEhLuwtW2jVBlF6jQkDbGnpqEZNeptCIKgdA+vkY3tK9Mzqy48n2tHQz7OpddwVa/ltXkPYA9vHajuG9uqo6CgQOW/pKpTlzSfIhetl8toUrJLtWvP/SSFy6YX5KN6E4kRkTyl13BVr+Waeg+o/kRz9dTJkyfh4uKC/Px8ACUvrnBycsLUqVOlZQ4fPgwPDw8IggBHR0ccOXIEAHD//n04Ojri6NGj+OCDD9CpUye8/vrr+Pnnn6V1S19u4e/vD0dHR/Tr10+67u+//8bIkSPh6uoKb29vLFq0CLm5udL1fn5+CA0NxcqVK9GzZ08MGjQIANCvXz98++23mDt3Ljp37ozu3bvjm2++kXltZ2mZ0NBQuLu7S99Sl5CQgMDAQHTr1g2dOnXCsGHDEBMTAwDYv38/XFxccPLkSbzxxhtwcXHB6NGjcfPmTbUecyJ6NWlpaUEkEsHIxlbhH9t2jhyKQES1RmN7eLt06QJBEHDhwgV4enri3LlzaNKkCWJjY1FcXAxtbW2cPXsW7u7uEIlEctv46quvMHv2bMybNw979uzB3LlzIRaLYW1tjZ9++glvv/02IiMjIRaLoa2tDQA4c+YMgoKCMGfOHPTo0QMZGRn48ssvERISgm+++Uba9uHDh+Hr64stW7aguLhYunzz5s2YPHky9u3bh4sXL2LBggUwNzfH+PHjZcpMmTIFe/bsQXFxMR49eoSxY8eiY8eO+P7772FqaoobN27I7EtRURG+/vprLFy4EI0bN8ZXX32FqVOn4vfff2cPMRFVi5aWNrS1tTk8gYjqLY3t4TU0NISLi4u0l/Ps2bMYOnQoGjVqhMuXL0uXVTb+1t/fH4MGDYKNjQ0++ugjaGtr459//gEAmJqaAgCaNGkCc3Nz6ec1a9Zg0qRJGDt2LGxsbNC5c2fMnz8fv/76KzIzM6Vtt2jRAqGhobC3t4eDg4N0eceOHREYGAg7Ozv4+vpi/Pjx2LRpk0xcYrEYH374IWxtbWFvb4/t27dDR0cHUVFREIvFsLGxwcCBA2VezSyRSBAcHIxu3bqhffv2WLFiBbKysvDrr79W4ygTERER1X8a28MLAB4eHtKENyYmBh999BHS09MRExMDS0tLJCYmyiSFL+vQoYP03zo6OjA1NcXjx48r3eaVK1fw77//YvPmzdJlpUMSEhMTpYmxs7Oz3J5lsVgs87lz587YsGED8vPzpQ/UubjIvlHo2rVr6NKlCwwMKn6NoUgkgpubm/Rzs2bNYGdnh/j4+Er3h4iIiKih0+iEt3v37vjhhx9w//593L17F926dcPjx49x5MgRtGjRAs2bN0fbtm0rrK+rqyvzWSQSoapJLSQSCQICAvDmm2+WW1f2pRGNVJzvEijpvSYiIiIixWjskAYA0rG1a9asgZOTE4yNjdG9e3fExcXh5MmT1ZpOrDQZlrz0/vmOHTvi7t27sLGxKfdTWQ9sqYsXL8p8jouLg7W1daXTpTk5OeHChQt48eJFhWUEQcC///4r/fzkyRPcu3cPbdpo5tOYRERERKU0OuHV19eHm5sbDh06JB260KpVK5iZmeHo0aPVSnibNm2Kxo0b49SpU0hPT8fTpyWvZA0KCsLRo0exYsUK3LhxAwkJCThx4gRCQxV7mOPKlStYvXo17t27h4MHD2L79u2YNGlSpXXGjRuH/Px8zJgxA3FxcUhOTsaxY8ekwzmAkqeoly1bhtjYWNy4cQOfffYZmjRpgsGDB6t8DIiIiIgaAo1OeIGScbxFRUUyY3W7d+9ebpkqvvjiCxw9ehTe3t7w9fUFAHh6emLDhg24dOkSxowZA19fX3z99dcKz/M7ceJEJCUlYfjw4Vi6dCn8/f0xbty4SutYWlpix44d0NHRwZQpU/DWW29hzZo1MmOEdXR0EBQUhJCQEIwYMQJZWVlYt26dwi/aICIiImqo+Ka1eqRfv34YM2YMPvjgA7W2u3//fsyfP186O0V18E1r6tOQ3+TTkPA417ygoADo6Ghh1ao1dR2KxuP5XDt4nGtHbb5pTeN7eImIiIjo1caEl4iIiIg0mkZPS9bQnDhxokbaHT58OIYPH14jbRMRERHVd+zhJSIiIiKNxoSXiIiIiDQaE14iIiIi0mhMeImIiIhIozHhJSIiIiKNxoSXiIiIiDQaE14iIiIi0mhMeImIiIhIozHhJSIiIiKNxoSXiIiIiDQaXy1MRETVEhGxFubmjZGenlPXoRARycUeXiIiIiLSaEx4iYiIiEijMeElIiIiIo3GhJeIiIiINBoTXiIiIiLSaJylgZSipSWq6xA0Co9n7eBxrh08zrWDx7l28DjXjto6ziJBEIRa2RIRERERUR3gkAYiIiIi0mhMeImIiIhIozHhJSIiIiKNxoSXiIiIiDQaE14iIiIi0mhMeImIiIhIozHhJSIiIiKNxoSXiIiIiDQaE14iIiIi0mhMeInU5IcffsDIkSPRpUsXuLu7Y9KkSYiLiytX7vjx43jrrbfg7OyMAQMGYO/eveXKXLhwASNHjoSLiwv69OmDdevWlSsTHx+PiRMnwtXVFZ6enli2bBkKCwtrZN/qk3/++QcBAQHw8vKCo6Mjjhw5Irecuo7hw4cPMWPGDIjFYnTr1g1z585Fbm5ujexbQ6PIuUz/UeTc5XlbfbwW147du3dj6NCh6NKlC8RiMYYOHYoDBw7IlKlXx1ggIrV47733hD179gjXr18X7ty5IwQHBwtubm5CQkKCtMzFixeFDh06CBEREcKdO3eErVu3Ch06dBD++OMPaZn79+8Lbm5uQmhoqHD79m3h559/FlxdXYVNmzZJy+Tk5AheXl7Chx9+KFy/fl34888/he7duwtffvllre5zXfjzzz+FVatWCb///rvg4OAgHD58uFwZdR3DoqIi4e233xbGjBkjXLp0Sfjnn3+EAQMGCNOnT6+Vfa3PFDmXSVZV5y7PW/Xgtbh2nDhxQjh+/LgQHx8vJCYmCps2bRI6dOggHD9+XBCE+neMmfAS1ZDi4mLB3d1d2LJli3TZrFmzhAkTJsiUmz17tjB69Gjp5xUrVgj9+vUTJBKJdNnXX38t9OrVS7psx44dgpubm/Ds2TNpmT179gjOzs5CTk5OTe1SvVNRwquuY/jXX38JDg4OQnJysrTMmTNnBAcHB+Hu3bs1tVsNgiLnMlVM3rnL87Zm8Fpce4YNGyYsW7ZMEIT6d4w5pIGohuTn56OgoAAmJibSZXFxcfDy8pIp16tXL1y5ckX69UxcXBx69uwJkUgkU+bhw4dISUmRluncuTMMDQ2lZXr37o2CggJcvXq1JnerQVDXMYyLi4OtrS2sra2lZTw8PKCnpyf3K9JXiSLnMimH523N4LW45kkkEpw+fRr37t2Dh4cHgPp3jJnwEtWQ5cuXw8TEBD4+PtJljx8/hpmZmUw5c3NzFBYWIisrq9IyAJCenl5hGTMzM4hEImmZV5m6juHjx4/RvHlzmTJaWlowNTV95Y+zIucyKYfnbc3gtbjmpKamQiwWw8XFBdOmTUNISAi8vb0B1L9jrKPUnhG9YiIjIxEVFVVpmdDQUEyYMEFm2Zo1a3D48GFs3LgRxsbGNRmiRlD1OBMRVYbX4pplYWGBgwcP4vnz5zhz5gyWLl0KS0tL9OrVq65DK4cJL1Elxo8fjzfeeKPSMqV/jZaKiIjA1q1bsWHDBjg7O8usa968OTIyMmSWPX78GDo6OmjWrFmlZcpuS16ZjIwMCIJQLp6GQJXjXBl1HcPmzZvj3LlzMmUkEgkyMzMb5HFWJ0XOZVIOz1v14rW45uno6MDGxgYA0KFDB9y/fx+RkZHo1atXvTvGHNJAVAlTU1PY29tX+lN2XNiKFSuwbds2bNy4ES4uLuXaE4vFOH36tMyykydPwsXFBbq6utIyZ86cKVfG0tISLVu2lJa5cOEC8vLyZMro6emhY8eOatv/2qLsca6Kuo6hWCxGQkKCdCwZAJw9exYFBQUQi8XV2eUGT5FzmZTD81Z9eC2uGxKJBPn5+QDq4TFW9gk8IpJv0aJFgpubm/DXX38Jjx49kv5kZ2dLy5RO0xIZGSnEx8cL27Ztq3Calvnz5wt37twRDh8+LHTq1EnYuHGjtExOTo7Qs2dPYcaMGcKNGzeEv/76S/D09BQWL15cm7tcJ3Jzc4Vr164J165dExwcHIR169YJ165dk5lySF3HsHR6p7FjxwqXL1+WTu80bdq02tzlekmRc5lkVXXu8rxVD16La8fKlSuFmJgYISkpSbhz546wYcMGoWPHjsKGDRsEQah/x1gkCIKgShZPRLIcHR3lLvf19cWyZcukn48dO4ZvvvkGCQkJaNGiBaZOnYqRI0fK1Dl//jyWLl2KGzduwNTUFOPGjUNAQIBMmTt37iAsLAxxcXEwNDTE0KFDMXv2bI3vXTt79iz8/f3LLXd3d8fWrVuln9V1DB8+fIhFixbhzJkz0NbWRv/+/TFv3jyOB4Ri5zL9R5Fzl+dt9fFaXDu++OILnD59Go8ePYKhoSFsbW0xduxYDBs2TFqmPh1jJrxEREREpNE4hpeIiIiINBoTXiIiIiLSaEx4iYiIiEijMeElIiIiIo3GhJeIiIiINBoTXiIiIiLSaEx4iYiIiEijMeElImpgBEFAeHg4vLy80L59e0yfPr3KOvv374ejoyPS0tLUEsOxY8ewZcsWtbSlCnn7069fP8ybN0/6OTIyEk5OTjWy/bS0NDg6OmL//v3SZX5+fpg0aZJMuZMnT+Ltt9+Gi4sLHB0dkZ2djfz8fMydOxeenp5wdHTEl19+WSMxEtF/dOo6ACIiUs6JEyewYcMGBAcHw83NDU2bNq31GI4dO4bz58/LfXNYXYmKikLjxo3rbPvz58+HSCSSfhYEAbNnz4azszNCQ0Ohq6sLIyMjbN++HYcOHcKSJUtga2sLc3PzOouZ6FXBhJeIqJ4oKCiAnp5eleXi4+MBABMnToSWFr+oK1VTvbmKatu2rcznjIwMPHnyBIMHD0a3bt2ky+Pj42FhYSHzClYiqlm8UhIR1YHg4GD0798fMTExeOedd+Ds7IwdO3YgMTERM2fOhLu7O1xdXTFmzBjExsZK6/n5+WHlypUAgA4dOpT7Wr0q6enpCAoKglgshre3NyIjIyGRSGTKHDt2DIMHD4aLiwuGDRuGmJgY9O/fH8HBwdLYDxw4gKSkJDg6OsLR0RF+fn4Kx3Dp0iV88MEH6Nq1K9zc3DB06FAcPnxYun7z5s0YNWoUunXrBnd3d0yYMAHnz5+vst2XhzSUunbtGkaPHg1XV1e8/vrrSh2vUuvWrYOXlxc6deqEKVOm4P79++XKlB3SsH//fvTs2RMAMG/ePOkx6tevH3bt2oUHDx5Ij93Zs2eVjoeIlMMeXiKiOpKVlYXPP/8cU6dOha2tLUQiEUaNGoWWLVtiwYIFMDIywq5duzB58mRER0ejffv2mD9/PrZs2YLdu3dj9+7dAIDWrVsrvM3Zs2dj2LBhGDNmDP7++29ERUWhZcuWGD58OICS5DAoKAg9evTAnDlz8PjxY4SEhODp06fSNqZPn47MzEzcvHkT3377LQDA2NhYoe1fuHABEydOhKOjIxYsWABTU1PcunULqamp0jIPHjzA6NGjYWVlhYKCAhw+fBj+/v7Yt28f2rdvr/C+AiXDCoKCgjBhwgR8+OGHOHjwIObOnQtzc3P06tVLoTa2b9+OVatWwc/PD97e3rhw4QI+/fTTSut4e3vju+++w7Rp0zBt2jR4e3vD2NgYBQUFiIyMxOXLlxEVFQWgfM8wEakfE14iojqSk5ODyMhIeHp6AgDmzp0LPT09bNmyRZpAenl54c0338TatWvxzTffoG3btmjRogUAwM3NTeltjhgxAu+//z4AoEePHjh9+jR+/fVXacK7bt06mJub47vvvoOuri4AwMLCQloHKEmwTU1Noaenp3QMK1asgKWlJXbs2CEdvtGjRw+ZMqU9yQBQXFyMnj174tq1a9i7dy9CQkKU2p5EIsHEiROlPdC9e/dGQkICVq9erVDCW1xcjLVr12LQoEHSbXt5eeHZs2fYtGlThfVMTU2lQyxat24tc5xUPXZEpDoOaSAiqiOGhobSZBcATp06hb59+8LAwABFRUUoKiqCIAjo0aOHzLCG6ujdu7fM53bt2uHBgwfSz5cvX0afPn2kyS4A9OrVC/r6+tXedl5eHi5evIhhw4ZVOlb50qVLeO+99+Dp6QknJyd07NgRd+7cwb1791Ta7sCBA2U+DxgwAFeuXEFxcXGVddPS0vDo0SP079+/0jaJqH5jDy8RUR0xMzOT+ZyZmSkzVKGssglodTRp0kTms56eHvLz86Wf09PTYWpqKlNGJBKhWbNm1d52dnY2JBIJLC0tKyyTmpqKyZMno127dggJCYGlpSX09fUxf/58FBQUqLTdl4+zmZkZCgsLkZWVhebNm1daNz09XW4bVdUjovqFCS8RUR0pO4UVUJKMenp6lpvLVV7ZmmJubo7MzEyZZYIgICsrq9ptm5iYQEtLCw8fPqywzKlTp5Cbm4vIyEiZ6bqys7NhZGSk0nYzMjJgYWEh81lXV1ehJL40hoyMDJnljx8/VikWIqobHNJARFRPeHl54datW3B0dISLi4vMj7Ozc63E4OLigr/++guFhYXSZX///bdMLzBQvmdYEY0aNYJYLMZPP/1UYW9tXl4eAEBH57/+mPPnzyM5OVmpbZX122+/yXz+/fff4ezsDG1t7Srrvvbaa7CwsMAff/xRaZtEVL+xh5eIqJ6YOXMmRowYAX9/f4wbNw4tWrRAVlYWrl69Ci0tLcyaNavGY5g6dSpGjBiBadOmYcKECcjIyMCaNWtgYmIi08vcpk0b7NmzB/v370fbtm1hbGyMNm3aVNn+p59+Cj8/P0yYMAETJ06Eqakp7ty5gxcvXuD999+Hp6cntLW1ERwcDH9/f6SmpiIyMlL6oJ6ytLS0sHnzZhQXF6NNmzY4ePAgrl69ih9//FHh+gEBAVi0aBEWL14snaXh999/VykeIqob7OElIqonWrZsib1798LGxgbh4eF499138eWXX+L27dvo2rVrrcTg5OSEiIgIpKSkYMaMGdi0aRPCwsKgo6Mj8xazkSNH4u2338aKFSswatQozJ8/X6H2xWIxtm/fDmNjY4SEhGD69OnYt28fWrZsCQBwcHBAeHg4EhISEBAQgG3btiEsLAx2dnYq7Y9IJEJkZCR+/fVXfPjhh/j333+xdOlShackA4Dx48fjo48+wtGjR6VtfPXVVyrFQ0R1QyQIglDXQRARUf118+ZNvP3221i2bBl8fX3rOhwiIqUx4SUiIhkLFy5Et27dYGZmhqSkJHz33XeQSCT45ZdfYGhoWNfhEREpjWN4iYgauOLiYlTWd6Gtra3ULA/Pnj3D0qVLkZWVBUNDQ3h4eODTTz+tMtktKiqqdH3ZB9Hqi4YYMxEpjz28REQNnJ+fH86dO1fh+qVLl0rfpFaTHB0dK11//PhxWFtb13gcirp//z58fHwqLXPz5s1aioaIahITXiKiBu7u3bt49uxZheutra3V8uKIqly+fLnS9Y6OjpW+Ya22FRQUVJnQuri41FI0RFSTmPASERERkUbjtGRE9MoQBAHh4eHw8vJC+/btMX369LoOiRqQTZs24fjx42pt89ChQ3B0dMT9+/crLHP//n04Ojri0KFDatnm/v374ejoiLS0NKXqKRrH/fv3ERkZidTU1OqESaRWHI1PRK+MEydOYMOGDQgODoabmxuaNm1a1yFRA7JlyxZ4enpWOe63vvP29sbu3bthampaI+2npKQgKioKnp6esLKyqpFtECmLCS8RNWgFBQUKjwuNj48HAEycOBFaWtX/gkuZbVPNqej3wN+PfKampjWW7BLVVxzSQEQNRnBwMPr374+YmBi88847cHZ2xo4dOwAAiYmJmDlzJtzd3eHq6ooxY8YgNjZWWtfPzw8rV64EAHTo0AGOjo7Yv38/ACA3NxdLlixBnz594OzsjIEDB2LPnj0y246MjISTkxNu3LiBCRMmoFOnTli+fDkA4PHjx/j888/Rs2dPODs7Y+jQoTh27Jjc2P/991+MGjUKnTp1whtvvCH3FbWnTp3ChAkTIBaL0blzZ4wePRpnzpyRri8sLERUVBT69+8PZ2dn9OvXD2vXrq10ajJl+fn5ITg4uNxyR0dHrFmzRqbcpEmT8Oeff+Ktt95Cp06dMHz4cJljX+rw4cN455130KlTJ7i7u8Pf3x/Xrl2Trk9LS8PHH38s/R2OGDECf/31l0wbFZ0DpV/Tnz9/HgEBARCLxZg5cyYAxX6/AHDv3j3MnDkTHh4ecHV1xeDBg7F582YAQL9+/ZCSkoK9e/fC0dERjo6OiIyMlNY9c+YMxo8fDzc3N3Tp0gVBQUF48OCBTPu5ubmYO3cuOnfuDHd3d8yfPx/5+fmK/DoAlEyhtmLFCnh6esLDwwOffPIJnj59Wm4bVe2rvCENOTk5mDNnjjS2hQsXIjo6Wu5wi8riOHv2LPz9/QGUvKGu9FhVNmSDqDawh5eIGpSsrCx8/vnnmDp1KmxtbdGkSROkpKRg1KhRaNmyJRYsWAAjIyPs2rULkydPRnR0NNq3b4/58+djy5Yt2L17N3bv3g0AaN26NQoLC/Hee+8hKSkJH374Iezs7HDq1CnMnz8fxcXFGDt2rHTbgiAgMDAQ48aNw4wZM9CoUSPk5ORg3LhxEAQBn3zyCSwsLPDLL79gxowZWLduHfr06SOt/+TJE8ydOxdTpkyBpaUlNm3ahFmzZuHXX3+FjY0NAODXX3/FRx99hJ49e2Lp0qUwMjLClStXkJKSIm3nk08+walTpxAQEABnZ2dcunQJq1evRm5uLmbPnl1Lv4n/3LlzB6tWrUJAQACMjY0RERGBgIAAnDhxAiYmJgCADRs2IDw8HG+++SamT58ObW1txMXF4eHDh3ByckJubi78/PyQl5eH4OBgmJqaYufOnQgICMD3338v8ypgeedAaeI8e/ZsDB8+XNqLr+jvNzExEaNGjYKpqSk+++wzWFlZISEhAcnJyQCAqKgofPDBB3BxccHUqVMBAC1atABQMt3ajBkzMGjQILz//vt4/vw5oqKi4O/vj0OHDknnL543bx7++usvzJo1C23atMGBAwcQFRWl8HEuHSawfPlyJCUlYcWKFdDV1cWyZcsAQKlz+WVz587F6dOn8dFHH8HW1hY///xzhbFVFkfHjh3xxRdfYNGiRVi0aJF0qjoLCwuF95OoRghERA3EnDlzBAcHB+HMmTMyy4ODgwUvLy8hJydHuqyoqEgYNGiQMHPmTOmy1atXCw4ODjJ1Dxw4IDg6Ogr//vuvzPJ58+YJPXv2FIqLiwVBEISIiAjBwcFBiI6OlikXGRkpdOrUSUhJSZFZPmnSJGHEiBHlYi+7nYyMDKF9+/bC999/LwiCIEgkEqF3797CuHHjBIlEIvcYnDt3TnBwcBCOHj0qs3zNmjWCs7Oz8OTJE7n1lDVhwgRhzpw55ZY7ODgIq1evlinn7Owss/9XrlwRHBwchCNHjgiCIAjZ2dlCp06dhE8++aTC7W3ZsqXc8SkuLhYGDx4sjBw5UrqsonNg3759goODg/DNN9/ILFf09/vJJ58IXbp0ETIyMiqMsW/fvsLnn39ebrmPj4/wwQcfyCxLSkoSOnbsKGzfvl0QBEG4c+eO4OjoKGzbtk2mnK+vr+Dg4CAkJydXuN3k5GTBwcFBeO+992SWh4WFCa6urkrva+mxevDggSAIgnDr1i3BwcFB2LFjh0y9kSNHysSmaBwxMTGCg4OD8M8//1S4T0S1jUMaiKhBMTQ0hKenp8yyU6dOoW/fvjAwMEBRURGKioogCAJ69Ogh96v1sk6ePAlbW1s4OTlJ6xYVFcHLywvp6elITEyUKd+vX79y2+7SpQssLCzK1b9y5YrMV9ZNmzaFq6ur9LOpqSnMzMykX33fvXsXaWlpGDFiRIVvRjt16hQMDQ3Rt29fme317NkTBQUFlc6FW7Z8VW8YU0a7du1kHk5q164dAEj3Ky4uDnl5eRg1alSFbfzzzz+wsbGROT5aWloYPHgwLl++LHMc5Z0DpV7+/Sj6+/3f//6H/v37Kz22tbQX+M0335Rp/7XXXoOdnR3Onz8PALh06RIEQUD//v1l6g8YMEDhbfXu3Vvmc9u2bfHixQtkZmYqta8vu3LlCgDg9ddfl1le0cN5VcVBVB9xSAMRNShmZmbllmVmZsoMVShLV1e30vYyMzNx7949dOzYUe76J0+eSP+tpaVVLiHKzMxEXFxchfWfPn0q/Tq39Ov9svT09KTJXOm2LC0tK4w3IyMDz58/r/CFCGXjfdnLMarrzWcv71fpg2LK7Fd2djaaN29ebnnz5s0hkUiQk5MDfX19APLPgbLly1L09/vkyROVvnbPyMgAUDKUQt5wktI209PT5cZe2b68rKLjXFBQAEC5c7ms0thePrcrSv6rioOoPmLCS0QNiryezyZNmsDT0xOTJk1SqPzLde3s7LBixQq569u0aVPltj08PPDpp5/Kra/MG85Kyz58+LDSeI2NjbFp0ya561u1alVh3b1798p8rizB09PTQ2FhocyyrKysCstXpux+lY5VfpmJiQlu3LhRbvnjx4+hpaWFxo0bS5dV9jt9eZ2iv99mzZrh0aNHle+IHKVT2wUHB6Nr167l1hsbGwMAzM3NAZQkyGWPe2nCrA7KnMtllf6RkJmZKY2z9DORpmDCS0QNnpeXF65fv67Sq2u9vLxw4sQJNG3atNJksbL6e/bsQevWrdGkSROl65dlZ2cHKysr7Nu3D76+vhVu78cff0RRURHEYrFS7SvzmlwrKytcvHhRZtnLMyYoSiwWw9DQEHv37oW7u7vcMt26dcNvv/2GK1euwNnZGQAgkUhw9OhRuLi4SHt3laXo79fT0xPHjh3DnDlzKpyfWVdXt9ysCm3atEHLli1x7949TJ48ucL2XV1dIRKJ8Mcff2D8+PHS5fJm6VCVqudy6Xlx7NgxmQfbXp5pRFHs8aX6iAkvETV4M2fOxIgRI+Dv749x48ahRYsWyMrKwtWrV6GlpYVZs2ZVWHfo0KHYt28fJk6ciHfffRdt27ZFXl4e7t69i3///RcRERGVbnvy5Mn45ZdfMH78eEycOBGtW7dGTk4Obt68iYcPH2LRokUK74dIJMKcOXMwa9YsvP/++xgxYgSMjY1x9epVmJqaYsSIEfD09MTgwYMxbdo0vPvuu3B2dkZhYSGSk5Nx/Phx/Pjjj9DW1lZ4mxV54403sGfPHixZsgR9+/bFjRs3pNO4KcvY2BhBQUHS2QQGDRoEHR0dxMXFwdXVFX379sXw4cOxZcsWTJs2DR9//DGaNWuGXbt24e7du/j+++9V3g9Ff7+BgYH4888/MWbMGHzwwQewsrJCcnIyEhISpL339vb2OHfuHP7++280a9YMFhYWsLS0REhICAIDA/HixQsMGDAAjRs3xqNHj3D27Fn06tULAwcOhL29PQYOHIgVK1agqKgIdnZ2OHDgAB4/fqzyvqm6ry9r164d+vfvj+XLl6OwsBB2dnb46aefpD3eys5ZbWtrC21tbezduxcGBgbQ1dVV6Y9RInViwktEDV7Lli2xd+9eREREIDw8HE+fPoWpqSk6duwo05smj66uLjZs2IC1a9di8+bNePDgARo3bgw7OzsMGTKkym2bmJhg165diIyMxOrVq/H48WM0bdoUDg4OeOedd5Tel0GDBmHdunX47rvv8Nlnn0FHRwft2rWTzikLACtXrsSmTZuwf/9+REREwNDQEK1bt4a3t7daXqgBlPR4hoaGYtOmTdi9ezfc3NwQGRmJgQMHqtTe5MmT0axZM2zatAm//vorGjVqhA4dOkgf2jIyMsLWrVuxfPlyLFmyBC9evICjoyPWrl0rMyWZshT9/bZu3Rq7du3C119/jaVLlyI/Px/W1tYyPZ6ffPIJFi5ciI8++gi5ubmYMWMGAgMD0a9fP2zevBnfffcd5syZg8LCQlhaWqJbt27SB/gA4Msvv8TixYvxzTffQEdHB2+88QYCAwMREhKi8v6psq/yLF26FGFhYfj666+ho6ODwYMHw9/fH8uXL5cZTqKIZs2aYeHChfjhhx/g7++PwsJCtY0XJ1KVSBDUOFM5ERERaYTAwEBcvXoVJ06cqOtQiKqNPbxERESvuD/++ANJSUlo3769tEf2999/x7x58+o6NCK1YA8vERHRK+706dNYuXIlEhISUFBQgFatWmH8+PGYMGFCXYdGpBZMeImIiIhIo/FNa0RERESk0ZjwEhEREZFGY8JLRERERBqNCS8RERERaTQmvERERESk0ZjwEhEREZFG+391ewLheGd2YgAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<Figure size 720x360 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, axs= plt.subplot(1,1,figsize=(15,8))\n",
    "sns.violinplot(x='ref_hgt_calib_diff', y='clim_pcp', data = pd_prcp, cut=0,#cut = True, lw = 2,\n",
    "            kind='boxen',  axs) #[['clim_pcp', '1980-2010_avg_prcp']])\n",
    "plt.gca().set_xlabel('ref_hgt_calib_diff\\n reference - uncorrected height')\n",
    "# if positive: the height is now higher, hence it is acting like reducing the temperature !!!"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "sns.catplot(x='ref_hgt_calib_diff', y='clim_pcp', data = pd_prcp, #cut = True, lw = 2,\n",
    "            col='rgi_region', kind='boxen', col_wrap=4, aspect=2) #[['clim_pcp', '1980-2010_avg_prcp']])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 283,
   "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>index</th>\n",
       "      <th>rgi_id</th>\n",
       "      <th>1980-2010_avg_prcp</th>\n",
       "      <th>1980-2010_avg_prcpsol_mean_elev</th>\n",
       "      <th>ref_hgt_calib_diff</th>\n",
       "      <th>rgi_region</th>\n",
       "      <th>clim_pcp</th>\n",
       "      <th>prcp_factor</th>\n",
       "      <th>applied_temp_bias\\nref_hgt_calib_diff * -0.0065</th>\n",
       "      <th>applied temp. bias\\nref_hgt_calib_diff * -0.0065</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>RGI60-14.14686</td>\n",
       "      <td>1076.216437</td>\n",
       "      <td>544.484230</td>\n",
       "      <td>0.0</td>\n",
       "      <td>14</td>\n",
       "      <td>CRU_pcp2.5</td>\n",
       "      <td>corrected_prcp</td>\n",
       "      <td>-0.0</td>\n",
       "      <td>-0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>RGI60-13.15533</td>\n",
       "      <td>2024.289065</td>\n",
       "      <td>1815.313027</td>\n",
       "      <td>0.0</td>\n",
       "      <td>13</td>\n",
       "      <td>CRU_pcp2.5</td>\n",
       "      <td>corrected_prcp</td>\n",
       "      <td>-0.0</td>\n",
       "      <td>-0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2</td>\n",
       "      <td>RGI60-17.06667</td>\n",
       "      <td>2262.269807</td>\n",
       "      <td>1412.045519</td>\n",
       "      <td>0.0</td>\n",
       "      <td>17</td>\n",
       "      <td>CRU_pcp2.5</td>\n",
       "      <td>corrected_prcp</td>\n",
       "      <td>-0.0</td>\n",
       "      <td>-0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>3</td>\n",
       "      <td>RGI60-13.27602</td>\n",
       "      <td>579.943412</td>\n",
       "      <td>414.010951</td>\n",
       "      <td>0.0</td>\n",
       "      <td>13</td>\n",
       "      <td>CRU_pcp2.5</td>\n",
       "      <td>corrected_prcp</td>\n",
       "      <td>-0.0</td>\n",
       "      <td>-0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>4</td>\n",
       "      <td>RGI60-13.20733</td>\n",
       "      <td>2288.944279</td>\n",
       "      <td>1840.195214</td>\n",
       "      <td>0.0</td>\n",
       "      <td>13</td>\n",
       "      <td>CRU_pcp2.5</td>\n",
       "      <td>corrected_prcp</td>\n",
       "      <td>-0.0</td>\n",
       "      <td>-0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1666331</th>\n",
       "      <td>208287</td>\n",
       "      <td>RGI60-14.02150</td>\n",
       "      <td>153.039118</td>\n",
       "      <td>113.290625</td>\n",
       "      <td>0.0</td>\n",
       "      <td>14</td>\n",
       "      <td>W5E5_pcp_via\\nwinterprcp</td>\n",
       "      <td>uncorrected_prcp</td>\n",
       "      <td>-0.0</td>\n",
       "      <td>-0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1666332</th>\n",
       "      <td>208288</td>\n",
       "      <td>RGI60-02.10847</td>\n",
       "      <td>719.925040</td>\n",
       "      <td>498.517150</td>\n",
       "      <td>0.0</td>\n",
       "      <td>2</td>\n",
       "      <td>W5E5_pcp_via\\nwinterprcp</td>\n",
       "      <td>uncorrected_prcp</td>\n",
       "      <td>-0.0</td>\n",
       "      <td>-0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1666333</th>\n",
       "      <td>208289</td>\n",
       "      <td>RGI60-17.11974</td>\n",
       "      <td>1198.084835</td>\n",
       "      <td>896.347553</td>\n",
       "      <td>0.0</td>\n",
       "      <td>17</td>\n",
       "      <td>W5E5_pcp_via\\nwinterprcp</td>\n",
       "      <td>uncorrected_prcp</td>\n",
       "      <td>-0.0</td>\n",
       "      <td>-0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1666334</th>\n",
       "      <td>208290</td>\n",
       "      <td>RGI60-17.02434</td>\n",
       "      <td>595.221264</td>\n",
       "      <td>276.167502</td>\n",
       "      <td>0.0</td>\n",
       "      <td>17</td>\n",
       "      <td>W5E5_pcp_via\\nwinterprcp</td>\n",
       "      <td>uncorrected_prcp</td>\n",
       "      <td>-0.0</td>\n",
       "      <td>-0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1666335</th>\n",
       "      <td>208291</td>\n",
       "      <td>RGI60-04.07009</td>\n",
       "      <td>193.791625</td>\n",
       "      <td>171.829744</td>\n",
       "      <td>0.0</td>\n",
       "      <td>4</td>\n",
       "      <td>W5E5_pcp_via\\nwinterprcp</td>\n",
       "      <td>uncorrected_prcp</td>\n",
       "      <td>-0.0</td>\n",
       "      <td>-0.0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1666336 rows × 10 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "          index          rgi_id  1980-2010_avg_prcp  \\\n",
       "0             0  RGI60-14.14686         1076.216437   \n",
       "1             1  RGI60-13.15533         2024.289065   \n",
       "2             2  RGI60-17.06667         2262.269807   \n",
       "3             3  RGI60-13.27602          579.943412   \n",
       "4             4  RGI60-13.20733         2288.944279   \n",
       "...         ...             ...                 ...   \n",
       "1666331  208287  RGI60-14.02150          153.039118   \n",
       "1666332  208288  RGI60-02.10847          719.925040   \n",
       "1666333  208289  RGI60-17.11974         1198.084835   \n",
       "1666334  208290  RGI60-17.02434          595.221264   \n",
       "1666335  208291  RGI60-04.07009          193.791625   \n",
       "\n",
       "         1980-2010_avg_prcpsol_mean_elev  ref_hgt_calib_diff  rgi_region  \\\n",
       "0                             544.484230                 0.0          14   \n",
       "1                            1815.313027                 0.0          13   \n",
       "2                            1412.045519                 0.0          17   \n",
       "3                             414.010951                 0.0          13   \n",
       "4                            1840.195214                 0.0          13   \n",
       "...                                  ...                 ...         ...   \n",
       "1666331                       113.290625                 0.0          14   \n",
       "1666332                       498.517150                 0.0           2   \n",
       "1666333                       896.347553                 0.0          17   \n",
       "1666334                       276.167502                 0.0          17   \n",
       "1666335                       171.829744                 0.0           4   \n",
       "\n",
       "                         clim_pcp       prcp_factor  \\\n",
       "0                      CRU_pcp2.5    corrected_prcp   \n",
       "1                      CRU_pcp2.5    corrected_prcp   \n",
       "2                      CRU_pcp2.5    corrected_prcp   \n",
       "3                      CRU_pcp2.5    corrected_prcp   \n",
       "4                      CRU_pcp2.5    corrected_prcp   \n",
       "...                           ...               ...   \n",
       "1666331  W5E5_pcp_via\\nwinterprcp  uncorrected_prcp   \n",
       "1666332  W5E5_pcp_via\\nwinterprcp  uncorrected_prcp   \n",
       "1666333  W5E5_pcp_via\\nwinterprcp  uncorrected_prcp   \n",
       "1666334  W5E5_pcp_via\\nwinterprcp  uncorrected_prcp   \n",
       "1666335  W5E5_pcp_via\\nwinterprcp  uncorrected_prcp   \n",
       "\n",
       "         applied_temp_bias\\nref_hgt_calib_diff * -0.0065  \\\n",
       "0                                                   -0.0   \n",
       "1                                                   -0.0   \n",
       "2                                                   -0.0   \n",
       "3                                                   -0.0   \n",
       "4                                                   -0.0   \n",
       "...                                                  ...   \n",
       "1666331                                             -0.0   \n",
       "1666332                                             -0.0   \n",
       "1666333                                             -0.0   \n",
       "1666334                                             -0.0   \n",
       "1666335                                             -0.0   \n",
       "\n",
       "         applied temp. bias\\nref_hgt_calib_diff * -0.0065  \n",
       "0                                                    -0.0  \n",
       "1                                                    -0.0  \n",
       "2                                                    -0.0  \n",
       "3                                                    -0.0  \n",
       "4                                                    -0.0  \n",
       "...                                                   ...  \n",
       "1666331                                              -0.0  \n",
       "1666332                                              -0.0  \n",
       "1666333                                              -0.0  \n",
       "1666334                                              -0.0  \n",
       "1666335                                              -0.0  \n",
       "\n",
       "[1666336 rows x 10 columns]"
      ]
     },
     "execution_count": 283,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd_prcp"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 286,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/users/lschuster/.local/lib/python3.9/site-packages/seaborn/categorical.py:3775: UserWarning: catplot is a figure-level function and does not accept target axes. You may wish to try boxenplot\n",
      "  warnings.warn(msg, UserWarning)\n",
      "/home/users/lschuster/.local/lib/python3.9/site-packages/seaborn/categorical.py:3775: UserWarning: catplot is a figure-level function and does not accept target axes. You may wish to try boxplot\n",
      "  warnings.warn(msg, UserWarning)\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "Text(0.5, 0.98, '90% intervals in grey')"
      ]
     },
     "execution_count": 286,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
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      "text/plain": [
       "<Figure size 2160x1800 with 20 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 2880x1800 with 18 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 2880x1800 with 18 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig,axs=plt.subplots(5,4,figsize=(30,25))\n",
    "#ax = plt.gca()\n",
    "sns.catplot(x='applied temp. bias\\nref_hgt_calib_diff * -0.0065', y='clim_pcp',\n",
    "               data = pd_prcp, kind='boxen', col_wrap=4, aspect=2,col='rgi_region',\n",
    "              saturation=0.6 #,ax=axs,\n",
    "              ) \n",
    "sns.catplot(x='applied temp. bias\\nref_hgt_calib_diff * -0.0065', y='clim_pcp',\n",
    "               data = pd_prcp,kind='box', col_wrap=4, aspect=2,col='rgi_region',\n",
    "            #kind='boxen',  \n",
    "            whis = [5,95], \n",
    "                    linewidth=4,\n",
    "                    saturation=0.8,\n",
    "                    capprops={'color':'grey', 'alpha':0.8},\n",
    "                    whiskerprops={'color':'grey', 'alpha':0.8},\n",
    "            fliersize=0, color = 'grey',ax=axs,\n",
    "              )\n",
    "plt.suptitle('90% intervals in grey')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 280,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<seaborn.axisgrid.FacetGrid at 0x7feb02124ac0>"
      ]
     },
     "execution_count": 280,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 2880x1800 with 18 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.catplot(x='ref_hgt_calib_diff', y='clim_pcp', data = pd_prcp, #cut = True, lw = 2,\n",
    "            col='rgi_region', kind='boxen', col_wrap=4, aspect=2) #[['clim_pcp', '1980-2010_avg_prcp']])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 203,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<seaborn.axisgrid.FacetGrid at 0x7feb05f9a820>"
      ]
     },
     "execution_count": 203,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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PampqOiMWAAAAjnG1tbV66635evfdt+VIyJQjtvdBre9MGqTSkmItW7a0gxICQPfWvlNEuqiSkhI9++yzWrhwoQoKChQfH6/s7Gz95Cc/0bnnnqurr75aS5YskSQ5HA6lpaXptNNO0x133KH4+PjQdgYNGqQnn3xSkydPDtv+U089pXfeeUfvv/9+p76u/fnnP/+p+fPna8OGDfL7/crNzdVNN92kiRMn7ne9008/XTt3hn9QecEFF+hPf/pTB6YFgKPL+vVrZXfFyuaMadFmGHbZ4/tr2bJvVVFRrvj4hAgkBAAAwLHMNE29+upc2V2xcvbIbbOfPSpJkrRlyyb17duvs+IBAAAAIRs3bpDdkyDD7tpvP0dcX3lL1uuvf52uO++8WzYbcy0BAADg8FiWpYqKChUV7VZx8V6VlZWqtLREOwt2alP+RtXW1sgRmy5PWt5Bb9sRmy67K1bvv/+Oxo49oQPSA0D3dtQWLO/atUtXXHGFnE6nbr/9dg0ZMkQ2m01Lly7VU089pVGjRkmSpkyZorvuukuBQEDr16/X/fffr7KyMv35z3+O8Cs4NF9//bXOOuss3XvvvYqNjdUbb7yhW265RS+99JLGjh2733VvuukmXXnllaHnHo+no+MCwFHDsiyt+2GdjKiUNvs4E7PkK/lBixd/rnPOOb8T0wEAAADSl19+oR07tsmTPk6Gzd5mP8MZK5vdpS1bNumUUyZ2XkAAAABAwWOtG/M3yObuecC+9qhkudPGaNWqpXrttZd1+eVXHnAdAAAAoIHP59WuXQXauXOHtm7drK1bt2jb9m2qrakO62fYHLK54mS4eyo6LfeAVwJpi2HY5OgxUJs2fae33pqvyZMv5KQ7ADgIR23B8sMPPyyfz6e33npLsbGxoeWZmZm68MILQ8/dbrdSU1MlSb169dLkyZP15ptvHvE8DbMx33TTTZo+fbqKiop0/PHH65FHHlF6enqo3xdffKEZM2Zo7dq1cjqdGjZsmJ544gmlpaXp3nvvVVFRkcaNG6cXXnhBVVVVmjBhgh555JHQjNB//OMfw/b785//XJ9//rk++uijAxYsx8TEhL4WAIBwhYW7VF1VKXevwaFlgZq98tfskSO6p+zRKbK7E2SPTtGnn36ss8+eLMMwIpgYAAAA3Z1pmqqrq1NtbY1qamr0+uuvyR6VJEd8+KzJzcethmHI8PTQV18tVs+eaZo4cZLcbk5aBgAAQMcyTVPbt2/T999/p9qaarl7hU8O0Xzc2sDVI0dmfbkWLHhXGRl9NX78hM6ODgAAgAgzTVP19XWqq6vfdzy0WlVVVaqqqlRVVZWqqytVXV2tmppqVVcH20pKilVZWSnJkiQZNrts7kTZ3GlyxyXK5oyV4YqRzREl2ZwtPt+3LEu+0o3yVxVIlr9xecAnywzIEZcud8/RLdZzJmYrULtXb775mvLz1+vUU0/TgAFZSkhIlN3e9kQTAICjtGC5rKxMn376qW6//fawYuUGbre71fW2bt2qTz/9VA5Hx7zswsJCzZs3T9OnT5dpmnrooYd0xx13aN68eZKCxcrXX3+9/uM//kMPP/xwaEboQCAQ2sayZcvk8Xg0c+ZMlZaW6oEHHtCDDz6o//mf/2l1n5ZlqaqqKlTQvD8vvviiZs6cqZ49e2rChAm6+eabFRMTc2RePNrFsixt374t7D3vTGVl0SotrWma6ABrdJVizAPljBzLCs92KAWslmWptDRGpaXVba7ffD+t7e9Afdpqb21bB9pmeB9JssL6WlbwuWmaYfeSJdNsvs3gsuA65r77xm0G12/a1ny7ZottNmyr+f6b3wd/h1aqrKxUBbsKJEmO6OCJHYGavTKLvtQ5Z5yhBR99JKWOkz06Rc6ELO3etUSLF3+u3r3T1R7HdmFzW6/98H7/NP4+a3s7ycmp7fr7CADo+kpKilVeXnaAXkfr39vmf8v29zr2//eztbHb/sYh7RnrNR9LNoxb99e3PZruu73j1ZbbkMLHjC3HesH2xvFpcEypsHFnw7LGsaqlQCAg0zSb3PsVCJgyzUDY9k3TDBuTNq4TUCAQaLGOaZry+Xzy+byqr69Xvdcrv88nv98fvAX8Cux7HFzf3+J1R/U7Pexr3da41Z02RvW7v9Orr87V2+/8S+ecfZ4GDx56UO9Te/ru7307mP9Xmvc5kmPog/leb8+6B3pdzbdVWhqtsrKaFv26hyP1Pu3/PWJsD6C7sixLO3Zsl9/v64CtH+oxmf1tp+11D3YserjrHWh77Rm3HuoYob3j1taKIRrHjy3Hkg1f39bGqE2PnTYcKzVNM2xfhmE0GfdaoXGs3x8cV7a276YZGsaugUCgxXHZ8HFuQ/9AKEPDdrdv36bq6ipJkt2TKEds71DGtsatDdxpeTK9FXrxxedUXl6mmJhYOZ1OORwO2e122Wy20M0wbDKM4Ox2zb8GDbdgP+OgZ7vb31jvYMe37dGwnZbrte9nrz3bbq6t7+vwzyna3v+R+Fykydrt6LP//R9+hqC+fft32GfIAAAcitLSUpWWFoeeN4z3mjqcsUvDGK/pscimz5uOLRu2FRyX2eVw2GW320PjhoZxZH19verrgwXHtbW1ofuGQmS/37fv+KhPPr9PPq9PXm+9vF7vgf8vMmyyO1ySzSnZXJLNJZsjRa6UfrK542Vzxcvmjg8bIzbwlW2Wr3xTy6+Br1aWr6rFco/Ho7POPUsLFixQ1YZtsrtb1qY5EjJlj0rRypXfa8WK5aHlbrdn380tt9stjyf42Ol0yeFwhI1vG8e59hbL7HZ76Ottt4ePhRset7adxn5G2PdM02PYDWw2o8X+g+NnY994+8gcHz7YY//7k5ycotTUuCO2PQCd76j8r2vbtm0yTVM5OTkH7Pv666/rrbfekt/vl9frlSTdd999HZKrrq5Ojz/+uPr27StJeuKJJzR58mQtXbpUY8eO1dNPP61JkybpnnvuCa2Tm5vbYjt/+MMfQoXYDz74oG688UYVFBSEzdTcYObMmSouLtZFF12032xXXnmlhgwZoqSkJK1du1ZPPvmk1q5dq5kzZx7OS8ZBevvt+XrzzXmRjgGgDfbonjJcwcGtv2aPzjnjDF1//f+TJL3/5WbZo1PkiOsr7VqimTP/GsmoaAfDMPTXvz4vp9MV6SgAgMOwe3eh7rvv55GOAXQ8wyHDZg/O9GGLkuFyyG5zyuaMkuGMkc0RLZsnUXZPj7DV2hq32t0Jiu53mvzVhare9olef/3VSLwq4Iiw2Wz63/99Xk6nM9JRAOCIevfdt/T66/+IdAzgyDFscvfMkyO+n2zOqLCmtsatoVUNmzzpJ6l6w5uMXRERo0cfp9tv/0WkYwAAIEmqrKzQL37xn5GO0fFsDhl2lwxHnOwej2wOjwxHlAxHdPC4qN0dbLd7gn2P9ERhZutF0meddZauv/56WZalt95+t9U+hgw5kwbKmZilQF2pAlU7FaivkM9XLW91rSoqyo5sVoS8+ir/LwBHs6OyYPlgzrw455xzdPvtt6u2tlZz5sxRSUmJrrrqqg7JlZKSEipWlqScnBzFx8crPz9fY8eO1Zo1a8KKlVszcODAsFmjx4wZI8uytGnTphYFy/Pnz9dTTz2l6dOnq0+fPvvd7rXXXht6PGjQIGVkZOhnP/uZ1qxZo6FDhx7My8RhOPnkU7Vjx3bt2bM7Ivt3Ou3y+cJndz7YGX0jpSvPUNsQ7XC+ZE3fm6ZnKDZ9bBjBfexvf03bGvo33U7zbTTfTtP9Nd9m0+22tv8D7aN5toPd/4G2eaAsTb8WDfemaaqqqkoVFWXBM0hrimQF6mU4PHJE9wzO9CFpwUcfyZE6TpIUqAuexRoTE6vU1J7tyrm/19ceh7rekXI4uffncH7/NP2ZaWs7kyadRbEyAHQDKSmpuuSSy/Xtt0va7NPVxq4H63BneAtvb3zcni9LW+Or1tY3DMnhsMvvDxywb3u0NV5tK8vBjC8P93lTYWMhQ7LM8PF605npQjMym6bMQHBWEdMyZTXp4w/4ZTWZxaJxR35ZAb8UqA+bP6zpf3B2Z7Q8/SfJ5my8WlJb41bL9MtXulG+0h8kBWf26NWrt2y2huwH93VoEXc//6u0tX57xslNvy9aaz9Uh/NaD/V1NXA4bPL7W3nPj3JH+nfv/t7jM844m2JlAN3SSSeN144d27R7d+EB+x7M38NDPSbTnu3sb91DPSbW7rHYAbI2HU/Y7TYFAmaT9sZxxoGOuTZ93Hz/B3MMtHk+m80IbbNhTNZ8vda2czjj4Oavsen4OzQLc8NYNRBQwAzIDDReUcSygu0N49mAGZBlWqExbss3wlT9nmXyV2yRPaaXXCnDZNiCH0W2NW5tyle6XpLUp0+GXC5X2Otq/r9Dg7ba2jNePdDx9APt40DH7NvK09rz5us1dyjbacjY9DXvb72GY67t+dk/Ep+LHMx48kCfWzTd5qH87xAVFaUpUy456PUAAOgosbFx+tnPrtbixZ/vdxzSnuVNx6LNx4atjRWbbqc996bZcv+WZcnr9YZmWfZ661v/22/6ZZl+Wb7g1cmaVbPI5ggWLMvmkmF3S3anDJtrXxGza19hc7RsrjgZ9raPHTkTM+VMzGyx3Fu6QfWF37ZYvmDBAlmWpQ8//FDOHrnypI1udbuBujJ593wvs65YZsDb5v6l4An5dodTDrtdtoaZkW12GTabHPbG+4YZkyW1+Lrub8zavF9r78v+3vf2fB+1dr+/7be13cO5P+WU0xQdHa3q6sr9fr0BdF1HZcFy//79ZbPZtHHjRp155pn77RsTE6P+/ftLkh555BFdfvnleuaZZ3TrrbeG9amsbPmLrKKiQnFxXXMa+Xnz5unRRx/V9OnTNWHChINef9SoUTIMQ1u2bKFguRMlJSXr5ptvj9j+U1PjVFTEH+2uiPcmskzT1Jo1q/Tkk48rULNXtviM4OweqeP0/peb5WhyeUJf2SZFRUXrySdnUAwbQfzMAMC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      "text/plain": [
       "<Figure size 2880x1800 with 18 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.catplot(x='ref_hgt_calib_diff', y='clim_pcp', data = pd_prcp, #cut = True, lw = 2,\n",
    "            col='rgi_region', kind='violin', col_wrap=4, aspect=2) #[['clim_pcp', '1980-2010_avg_prcp']])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 101,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "pd_clim_stats_all_d['CRU_pcp2.5'][]\n",
    "pd_glac_stats_all_d['CRU_pcp2.5'].columns\n",
    "pd_glac_stats_all['ref_hgt_calib_diff'].dropna()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Some more regional checks, just to see the type of the error:"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**RGI region 13 check**\n",
    "\n",
    "- What is so specific in RGI region 13 that **match_geod_pergla** works less good using CRU specifically (more than twice as much errors and 3\\*times as much area, see below) than when using the direct reference glacier calibration data (no_match)?\n",
    "    - The problem is actually that precipitation is so low for these glaciers, that it can not reproduce the observed geodetic **positive** specific mass balance."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 183,
   "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>rgi_area_km2</th>\n",
       "      <th>error_task</th>\n",
       "      <th>error_msg</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>rgi_id</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>RGI60-13.37825</th>\n",
       "      <td>51.478</td>\n",
       "      <td>mu_star_calibration_from_geodetic_mb</td>\n",
       "      <td>MassBalanceCalibrationError: We could not find a way to correct the climate data and fit within the prescribed bounds for mu*.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>RGI60-13.54059</th>\n",
       "      <td>42.521</td>\n",
       "      <td>mu_star_calibration_from_geodetic_mb</td>\n",
       "      <td>MassBalanceCalibrationError: We could not find a way to correct the climate data and fit within the prescribed bounds for mu*.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>RGI60-13.37587</th>\n",
       "      <td>32.259</td>\n",
       "      <td>mu_star_calibration_from_geodetic_mb</td>\n",
       "      <td>MassBalanceCalibrationError: We could not find a way to correct the climate data and fit within the prescribed bounds for mu*.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>RGI60-13.53668</th>\n",
       "      <td>29.870</td>\n",
       "      <td>mu_star_calibration_from_geodetic_mb</td>\n",
       "      <td>MassBalanceCalibrationError: We could not find a way to correct the climate data and fit within the prescribed bounds for mu*.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>RGI60-13.38833</th>\n",
       "      <td>27.602</td>\n",
       "      <td>mu_star_calibration_from_geodetic_mb</td>\n",
       "      <td>MassBalanceCalibrationError: We could not find a way to correct the climate data and fit within the prescribed bounds for mu*.</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                rgi_area_km2                            error_task  \\\n",
       "rgi_id                                                               \n",
       "RGI60-13.37825        51.478  mu_star_calibration_from_geodetic_mb   \n",
       "RGI60-13.54059        42.521  mu_star_calibration_from_geodetic_mb   \n",
       "RGI60-13.37587        32.259  mu_star_calibration_from_geodetic_mb   \n",
       "RGI60-13.53668        29.870  mu_star_calibration_from_geodetic_mb   \n",
       "RGI60-13.38833        27.602  mu_star_calibration_from_geodetic_mb   \n",
       "\n",
       "                                                                                                                                     error_msg  \n",
       "rgi_id                                                                                                                                          \n",
       "RGI60-13.37825  MassBalanceCalibrationError: We could not find a way to correct the climate data and fit within the prescribed bounds for mu*.  \n",
       "RGI60-13.54059  MassBalanceCalibrationError: We could not find a way to correct the climate data and fit within the prescribed bounds for mu*.  \n",
       "RGI60-13.37587  MassBalanceCalibrationError: We could not find a way to correct the climate data and fit within the prescribed bounds for mu*.  \n",
       "RGI60-13.53668  MassBalanceCalibrationError: We could not find a way to correct the climate data and fit within the prescribed bounds for mu*.  \n",
       "RGI60-13.38833  MassBalanceCalibrationError: We could not find a way to correct the climate data and fit within the prescribed bounds for mu*.  "
      ]
     },
     "execution_count": 183,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dfserr_reg['L5_elev_bands_pcp2.5_CRU_match_geod_pergla_qc0_b80_rgi_13'].head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 284,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 0, 'dmdtda')"
      ]
     },
     "execution_count": 284,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1008x576 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.hist(pd_geodetic.loc[dfserr_reg['L5_elev_bands_pcp2.5_CRU_match_geod_pergla_qc0_b80_rgi_13'].index].dmdtda,\n",
    "        label='CRU_pcp2.5')\n",
    "plt.hist(pd_geodetic.loc[dfserr_reg['L5_elev_bands_2.6_GSWP3_W5E5_match_geod_pergla_2.6_qc0_b160_rgi_13'].index].dmdtda, alpha = 0.5, label = 'GSWP3_W5E5_constant_prcp_fac')\n",
    "plt.hist(pd_geodetic.loc[dfserr_reg['L5_elev_bands_via_winterprcp_GSWP3_W5E5_match_geod_pergla_winterprcp_qc0_b160_rgi_13'].index].dmdtda,\n",
    "         alpha = 0.5, label = 'GSWP3_W5E5 variable (larger) prcp. fac')\n",
    "plt.legend()\n",
    "plt.xlabel('dmdtda')\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "- all failing glaciers have a positive mass balance. This is the reason that glaciers are failing. \n",
    "    - maybe a larger precipitation factor for CRU would be necessary in this region specifically !!!\n",
    "    - If we use instead ERA5 (see below), much less glaciers fail in this region!\n",
    "    - Using a variable (and mostly) larger prcp. fac results in much less failing glaciers with W5E5. Then only those glaciers with larger positive dmdtda from the last 20 years are still failing"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 285,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "with match_geod_pergla:\n",
      "amount of glaciers failing in RGI 13: 2357\n",
      "failing glacier area in RGI 13:  2653.1 km2\n"
     ]
    }
   ],
   "source": [
    "print('with match_geod_pergla:')\n",
    "print(f\"amount of glaciers failing in RGI 13: {len(dfserr_reg['L5_elev_bands_pcp2.5_CRU_match_geod_pergla_qc0_b80_rgi_13'])}\")\n",
    "print(f\"failing glacier area in RGI 13:  {dfserr_reg['L5_elev_bands_pcp2.5_CRU_match_geod_pergla_qc0_b80_rgi_13'].rgi_area_km2.sum():0.1f} km2\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 286,
   "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>rgi_area_km2</th>\n",
       "      <th>error_task</th>\n",
       "      <th>error_msg</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>rgi_id</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>RGI60-13.38733</th>\n",
       "      <td>30.849</td>\n",
       "      <td>local_t_star</td>\n",
       "      <td>MassBalanceCalibrationError: RGI60-13.38733: mu* out of specified bounds: 3.57</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>RGI60-13.38742</th>\n",
       "      <td>20.997</td>\n",
       "      <td>local_t_star</td>\n",
       "      <td>MassBalanceCalibrationError: RGI60-13.38742: mu* out of specified bounds: 4.26</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>RGI60-13.38768</th>\n",
       "      <td>18.447</td>\n",
       "      <td>local_t_star</td>\n",
       "      <td>MassBalanceCalibrationError: RGI60-13.38768: mu* out of specified bounds: 4.19</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>RGI60-13.38924</th>\n",
       "      <td>13.702</td>\n",
       "      <td>local_t_star</td>\n",
       "      <td>MassBalanceCalibrationError: RGI60-13.38924: mu* out of specified bounds: 4.51</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>RGI60-13.37368</th>\n",
       "      <td>13.572</td>\n",
       "      <td>local_t_star</td>\n",
       "      <td>MassBalanceCalibrationError: RGI60-13.37368: mu* out of specified bounds: 2.67</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                rgi_area_km2    error_task  \\\n",
       "rgi_id                                       \n",
       "RGI60-13.38733        30.849  local_t_star   \n",
       "RGI60-13.38742        20.997  local_t_star   \n",
       "RGI60-13.38768        18.447  local_t_star   \n",
       "RGI60-13.38924        13.702  local_t_star   \n",
       "RGI60-13.37368        13.572  local_t_star   \n",
       "\n",
       "                                                                                     error_msg  \n",
       "rgi_id                                                                                          \n",
       "RGI60-13.38733  MassBalanceCalibrationError: RGI60-13.38733: mu* out of specified bounds: 3.57  \n",
       "RGI60-13.38742  MassBalanceCalibrationError: RGI60-13.38742: mu* out of specified bounds: 4.26  \n",
       "RGI60-13.38768  MassBalanceCalibrationError: RGI60-13.38768: mu* out of specified bounds: 4.19  \n",
       "RGI60-13.38924  MassBalanceCalibrationError: RGI60-13.38924: mu* out of specified bounds: 4.51  \n",
       "RGI60-13.37368  MassBalanceCalibrationError: RGI60-13.37368: mu* out of specified bounds: 2.67  "
      ]
     },
     "execution_count": 286,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# what are the glaciers failing for no match???\n",
    "dfserr_reg['L5_elev_bands_pcp2.5_CRU_no_match_qc0_b80_rgi_13'].head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 287,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "with no_match:\n",
      "amount of glaciers failing in RGI 13: 1015\n",
      "failing glacier area in RGI 13:  826.3 km2\n"
     ]
    }
   ],
   "source": [
    "print('with no_match:')\n",
    "print(f\"amount of glaciers failing in RGI 13: {len(dfserr_reg['L5_elev_bands_pcp2.5_CRU_no_match_qc0_b80_rgi_13'])}\")\n",
    "print(f\"failing glacier area in RGI 13:  {dfserr_reg['L5_elev_bands_pcp2.5_CRU_no_match_qc0_b80_rgi_13'].rgi_area_km2.sum():0.1f} km2\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Let's get a list of only those that fail for match_geod_pergla, but not for no_match!"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 288,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/tmp/ipykernel_323319/3363420844.py:3: FutureWarning: Index.__and__ operating as a set operation is deprecated, in the future this will be a logical operation matching Series.__and__.  Use index.intersection(other) instead\n",
      "  rgi_fail_both = rgi_fail_no_match & rgi_fail_match_geod_pergla\n"
     ]
    }
   ],
   "source": [
    "rgi_fail_no_match = dfserr_reg['L5_elev_bands_pcp2.5_CRU_no_match_qc0_b80_rgi_13'].index\n",
    "rgi_fail_match_geod_pergla = dfserr_reg['L5_elev_bands_pcp2.5_CRU_match_geod_pergla_qc0_b80_rgi_13'].index.values\n",
    "rgi_fail_both = rgi_fail_no_match & rgi_fail_match_geod_pergla\n",
    "pd_failing_rgi13_pergla = dfserr_reg['L5_elev_bands_pcp2.5_CRU_match_geod_pergla_qc0_b80_rgi_13']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 289,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
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       "\n",
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>rgi_area_km2</th>\n",
       "      <th>error_task</th>\n",
       "      <th>error_msg</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>rgi_id</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>RGI60-13.37825</th>\n",
       "      <td>51.478</td>\n",
       "      <td>mu_star_calibration_from_geodetic_mb</td>\n",
       "      <td>MassBalanceCalibrationError: We could not find a way to correct the climate data and fit within the prescribed bounds for mu*.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>RGI60-13.54059</th>\n",
       "      <td>42.521</td>\n",
       "      <td>mu_star_calibration_from_geodetic_mb</td>\n",
       "      <td>MassBalanceCalibrationError: We could not find a way to correct the climate data and fit within the prescribed bounds for mu*.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>RGI60-13.37587</th>\n",
       "      <td>32.259</td>\n",
       "      <td>mu_star_calibration_from_geodetic_mb</td>\n",
       "      <td>MassBalanceCalibrationError: We could not find a way to correct the climate data and fit within the prescribed bounds for mu*.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>RGI60-13.53668</th>\n",
       "      <td>29.870</td>\n",
       "      <td>mu_star_calibration_from_geodetic_mb</td>\n",
       "      <td>MassBalanceCalibrationError: We could not find a way to correct the climate data and fit within the prescribed bounds for mu*.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>RGI60-13.38833</th>\n",
       "      <td>27.602</td>\n",
       "      <td>mu_star_calibration_from_geodetic_mb</td>\n",
       "      <td>MassBalanceCalibrationError: We could not find a way to correct the climate data and fit within the prescribed bounds for mu*.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>RGI60-13.52437</th>\n",
       "      <td>0.015</td>\n",
       "      <td>mu_star_calibration_from_geodetic_mb</td>\n",
       "      <td>MassBalanceCalibrationError: We could not find a way to correct the climate data and fit within the prescribed bounds for mu*.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>RGI60-13.51818</th>\n",
       "      <td>0.015</td>\n",
       "      <td>mu_star_calibration_from_geodetic_mb</td>\n",
       "      <td>MassBalanceCalibrationError: We could not find a way to correct the climate data and fit within the prescribed bounds for mu*.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>RGI60-13.52388</th>\n",
       "      <td>0.013</td>\n",
       "      <td>mu_star_calibration_from_geodetic_mb</td>\n",
       "      <td>MassBalanceCalibrationError: We could not find a way to correct the climate data and fit within the prescribed bounds for mu*.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>RGI60-13.52461</th>\n",
       "      <td>0.012</td>\n",
       "      <td>mu_star_calibration_from_geodetic_mb</td>\n",
       "      <td>MassBalanceCalibrationError: We could not find a way to correct the climate data and fit within the prescribed bounds for mu*.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>RGI60-13.52143</th>\n",
       "      <td>0.012</td>\n",
       "      <td>mu_star_calibration_from_geodetic_mb</td>\n",
       "      <td>MassBalanceCalibrationError: We could not find a way to correct the climate data and fit within the prescribed bounds for mu*.</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1860 rows × 3 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                rgi_area_km2                            error_task  \\\n",
       "rgi_id                                                               \n",
       "RGI60-13.37825        51.478  mu_star_calibration_from_geodetic_mb   \n",
       "RGI60-13.54059        42.521  mu_star_calibration_from_geodetic_mb   \n",
       "RGI60-13.37587        32.259  mu_star_calibration_from_geodetic_mb   \n",
       "RGI60-13.53668        29.870  mu_star_calibration_from_geodetic_mb   \n",
       "RGI60-13.38833        27.602  mu_star_calibration_from_geodetic_mb   \n",
       "...                      ...                                   ...   \n",
       "RGI60-13.52437         0.015  mu_star_calibration_from_geodetic_mb   \n",
       "RGI60-13.51818         0.015  mu_star_calibration_from_geodetic_mb   \n",
       "RGI60-13.52388         0.013  mu_star_calibration_from_geodetic_mb   \n",
       "RGI60-13.52461         0.012  mu_star_calibration_from_geodetic_mb   \n",
       "RGI60-13.52143         0.012  mu_star_calibration_from_geodetic_mb   \n",
       "\n",
       "                                                                                                                                     error_msg  \n",
       "rgi_id                                                                                                                                          \n",
       "RGI60-13.37825  MassBalanceCalibrationError: We could not find a way to correct the climate data and fit within the prescribed bounds for mu*.  \n",
       "RGI60-13.54059  MassBalanceCalibrationError: We could not find a way to correct the climate data and fit within the prescribed bounds for mu*.  \n",
       "RGI60-13.37587  MassBalanceCalibrationError: We could not find a way to correct the climate data and fit within the prescribed bounds for mu*.  \n",
       "RGI60-13.53668  MassBalanceCalibrationError: We could not find a way to correct the climate data and fit within the prescribed bounds for mu*.  \n",
       "RGI60-13.38833  MassBalanceCalibrationError: We could not find a way to correct the climate data and fit within the prescribed bounds for mu*.  \n",
       "...                                                                                                                                        ...  \n",
       "RGI60-13.52437  MassBalanceCalibrationError: We could not find a way to correct the climate data and fit within the prescribed bounds for mu*.  \n",
       "RGI60-13.51818  MassBalanceCalibrationError: We could not find a way to correct the climate data and fit within the prescribed bounds for mu*.  \n",
       "RGI60-13.52388  MassBalanceCalibrationError: We could not find a way to correct the climate data and fit within the prescribed bounds for mu*.  \n",
       "RGI60-13.52461  MassBalanceCalibrationError: We could not find a way to correct the climate data and fit within the prescribed bounds for mu*.  \n",
       "RGI60-13.52143  MassBalanceCalibrationError: We could not find a way to correct the climate data and fit within the prescribed bounds for mu*.  \n",
       "\n",
       "[1860 rows x 3 columns]"
      ]
     },
     "execution_count": 289,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd_failing_rgi13_pergla.drop(rgi_fail_both)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "It is not just one glacier that does not work with the match_geod_pergla method, but rather a lot of different mid-size glaciers. "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "When using a varying prcp. fac, there are much less errors in region 13. We will have to check the prcp. fac distribution "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**RGI region 5 check**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 290,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>rgi_area_km2</th>\n",
       "      <th>error_task</th>\n",
       "      <th>error_msg</th>\n",
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       "      <th></th>\n",
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       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>RGI60-05.10988</th>\n",
       "      <td>207.766</td>\n",
       "      <td>local_t_star</td>\n",
       "      <td>MassBalanceCalibrationError: RGI60-05.10988: mu* out of specified bounds: 3.31</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>RGI60-05.11001</th>\n",
       "      <td>182.955</td>\n",
       "      <td>local_t_star</td>\n",
       "      <td>MassBalanceCalibrationError: RGI60-05.11001: mu* out of specified bounds: 1.59</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>RGI60-05.10885</th>\n",
       "      <td>170.533</td>\n",
       "      <td>local_t_star</td>\n",
       "      <td>MassBalanceCalibrationError: RGI60-05.10885: mu* out of specified bounds: 3.18</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>RGI60-05.10615</th>\n",
       "      <td>167.934</td>\n",
       "      <td>local_t_star</td>\n",
       "      <td>MassBalanceCalibrationError: RGI60-05.10615: mu* out of specified bounds: 3.01</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>RGI60-05.11026</th>\n",
       "      <td>160.435</td>\n",
       "      <td>local_t_star</td>\n",
       "      <td>MassBalanceCalibrationError: RGI60-05.11026: mu* out of specified bounds: 1.59</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                rgi_area_km2    error_task  \\\n",
       "rgi_id                                       \n",
       "RGI60-05.10988       207.766  local_t_star   \n",
       "RGI60-05.11001       182.955  local_t_star   \n",
       "RGI60-05.10885       170.533  local_t_star   \n",
       "RGI60-05.10615       167.934  local_t_star   \n",
       "RGI60-05.11026       160.435  local_t_star   \n",
       "\n",
       "                                                                                     error_msg  \n",
       "rgi_id                                                                                          \n",
       "RGI60-05.10988  MassBalanceCalibrationError: RGI60-05.10988: mu* out of specified bounds: 3.31  \n",
       "RGI60-05.11001  MassBalanceCalibrationError: RGI60-05.11001: mu* out of specified bounds: 1.59  \n",
       "RGI60-05.10885  MassBalanceCalibrationError: RGI60-05.10885: mu* out of specified bounds: 3.18  \n",
       "RGI60-05.10615  MassBalanceCalibrationError: RGI60-05.10615: mu* out of specified bounds: 3.01  \n",
       "RGI60-05.11026  MassBalanceCalibrationError: RGI60-05.11026: mu* out of specified bounds: 1.59  "
      ]
     },
     "execution_count": 290,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dfserr_reg['L5_elev_bands_pcp2.5_CRU_match_geod_qc0_b80_rgi_05'].head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 291,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "      <th>rgi_area_km2</th>\n",
       "      <th>error_task</th>\n",
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       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>RGI60-05.10735</th>\n",
       "      <td>392.607</td>\n",
       "      <td>local_t_star</td>\n",
       "      <td>MassBalanceCalibrationError: RGI60-05.10735: mu* out of specified bounds: 0.91</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>RGI60-05.10634</th>\n",
       "      <td>388.067</td>\n",
       "      <td>local_t_star</td>\n",
       "      <td>MassBalanceCalibrationError: RGI60-05.10634: mu* out of specified bounds: 2.07</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>RGI60-05.10617</th>\n",
       "      <td>373.290</td>\n",
       "      <td>local_t_star</td>\n",
       "      <td>MassBalanceCalibrationError: RGI60-05.10617: mu* out of specified bounds: 3.45</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>RGI60-05.10762</th>\n",
       "      <td>309.061</td>\n",
       "      <td>local_t_star</td>\n",
       "      <td>MassBalanceCalibrationError: RGI60-05.10762: mu* out of specified bounds: 1.34</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>RGI60-05.10988</th>\n",
       "      <td>207.766</td>\n",
       "      <td>local_t_star</td>\n",
       "      <td>MassBalanceCalibrationError: RGI60-05.10988: mu* out of specified bounds: 1.25</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                rgi_area_km2    error_task  \\\n",
       "rgi_id                                       \n",
       "RGI60-05.10735       392.607  local_t_star   \n",
       "RGI60-05.10634       388.067  local_t_star   \n",
       "RGI60-05.10617       373.290  local_t_star   \n",
       "RGI60-05.10762       309.061  local_t_star   \n",
       "RGI60-05.10988       207.766  local_t_star   \n",
       "\n",
       "                                                                                     error_msg  \n",
       "rgi_id                                                                                          \n",
       "RGI60-05.10735  MassBalanceCalibrationError: RGI60-05.10735: mu* out of specified bounds: 0.91  \n",
       "RGI60-05.10634  MassBalanceCalibrationError: RGI60-05.10634: mu* out of specified bounds: 2.07  \n",
       "RGI60-05.10617  MassBalanceCalibrationError: RGI60-05.10617: mu* out of specified bounds: 3.45  \n",
       "RGI60-05.10762  MassBalanceCalibrationError: RGI60-05.10762: mu* out of specified bounds: 1.34  \n",
       "RGI60-05.10988  MassBalanceCalibrationError: RGI60-05.10988: mu* out of specified bounds: 1.25  "
      ]
     },
     "execution_count": 291,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dfserr_reg['L5_elev_bands_pcp2.5_CRU_match_geod_qc3_b160_rgi_05'].head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 292,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'MassBalanceCalibrationError: RGI60-05.10735: mu* out of specified bounds: 0.91'"
      ]
     },
     "execution_count": 292,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dfserr_reg['L5_elev_bands_pcp2.5_CRU_match_geod_qc3_b160_rgi_05']['error_msg'].iloc[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 293,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "9165.776"
      ]
     },
     "execution_count": 293,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dfserr_reg['L5_elev_bands_pcp2.5_CRU_match_geod_qc0_b80_rgi_05'].rgi_area_km2.sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 294,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "11154.001"
      ]
     },
     "execution_count": 294,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dfserr_reg['L5_elev_bands_pcp2.5_CRU_match_geod_qc3_b160_rgi_05'].rgi_area_km2.sum()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "- around 20% more glacier area fails with qc3 in RGI reg 5 (with match_geod and CRU), because of bigger glaciers with MassBalanceCalibrationErrors!!!."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "**RGI region 16 check**"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 295,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
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       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>rgi_area_km2</th>\n",
       "      <th>error_task</th>\n",
       "      <th>error_msg</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>rgi_id</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>RGI60-16.01443</th>\n",
       "      <td>10.263</td>\n",
       "      <td>local_t_star</td>\n",
       "      <td>MassBalanceCalibrationError: RGI60-16.01443: mu* out of specified bounds: 4.91</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>RGI60-16.01473</th>\n",
       "      <td>7.372</td>\n",
       "      <td>local_t_star</td>\n",
       "      <td>MassBalanceCalibrationError: RGI60-16.01473: mu* out of specified bounds: 71516.08</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>RGI60-16.00410</th>\n",
       "      <td>6.440</td>\n",
       "      <td>local_t_star</td>\n",
       "      <td>MassBalanceCalibrationError: RGI60-16.00410: mu* out of specified bounds: 0.84</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>RGI60-16.01483</th>\n",
       "      <td>5.482</td>\n",
       "      <td>local_t_star</td>\n",
       "      <td>MassBalanceCalibrationError: RGI60-16.01483: mu* out of specified bounds: 109115.38</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>RGI60-16.01394</th>\n",
       "      <td>5.454</td>\n",
       "      <td>local_t_star</td>\n",
       "      <td>MassBalanceCalibrationError: RGI60-16.01394: mu* out of specified bounds: 0.02</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                rgi_area_km2    error_task  \\\n",
       "rgi_id                                       \n",
       "RGI60-16.01443        10.263  local_t_star   \n",
       "RGI60-16.01473         7.372  local_t_star   \n",
       "RGI60-16.00410         6.440  local_t_star   \n",
       "RGI60-16.01483         5.482  local_t_star   \n",
       "RGI60-16.01394         5.454  local_t_star   \n",
       "\n",
       "                                                                                          error_msg  \n",
       "rgi_id                                                                                               \n",
       "RGI60-16.01443       MassBalanceCalibrationError: RGI60-16.01443: mu* out of specified bounds: 4.91  \n",
       "RGI60-16.01473   MassBalanceCalibrationError: RGI60-16.01473: mu* out of specified bounds: 71516.08  \n",
       "RGI60-16.00410       MassBalanceCalibrationError: RGI60-16.00410: mu* out of specified bounds: 0.84  \n",
       "RGI60-16.01483  MassBalanceCalibrationError: RGI60-16.01483: mu* out of specified bounds: 109115.38  \n",
       "RGI60-16.01394       MassBalanceCalibrationError: RGI60-16.01394: mu* out of specified bounds: 0.02  "
      ]
     },
     "execution_count": 295,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dfserr_reg['L5_elev_bands_pcp2.5_CRU_match_geod_qc0_b80_rgi_16'].head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 296,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "267.156"
      ]
     },
     "execution_count": 296,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dfserr_reg['L5_elev_bands_pcp2.5_CRU_match_geod_qc0_b80_rgi_16'].rgi_area_km2.sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 297,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "176.732"
      ]
     },
     "execution_count": 297,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dfserr_reg['L5_elev_bands_pcp2.5_CRU_match_geod_qc3_b160_rgi_16'].rgi_area_km2.sum()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "- there is around 50% more failing glacier area for qc0 than for qc3 (with match_geod and CRU)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#####  RGI region 17 check"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 200,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
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       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>rgi_area_km2</th>\n",
       "      <th>error_task</th>\n",
       "      <th>error_msg</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>rgi_id</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>RGI60-17.05181</th>\n",
       "      <td>1234.714</td>\n",
       "      <td>mu_star_calibration_from_geodetic_mb</td>\n",
       "      <td>MassBalanceCalibrationError: We could not find a way to correct the climate data and fit within the prescribed bounds for mu*.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>RGI60-17.04982</th>\n",
       "      <td>61.974</td>\n",
       "      <td>mu_star_calibration_from_geodetic_mb</td>\n",
       "      <td>MassBalanceCalibrationError: We could not find a way to correct the climate data and fit within the prescribed bounds for mu*.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>RGI60-17.04963</th>\n",
       "      <td>40.424</td>\n",
       "      <td>mu_star_calibration_from_geodetic_mb</td>\n",
       "      <td>MassBalanceCalibrationError: We could not find a way to correct the climate data and fit within the prescribed bounds for mu*.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>RGI60-17.05044</th>\n",
       "      <td>32.994</td>\n",
       "      <td>mu_star_calibration_from_geodetic_mb</td>\n",
       "      <td>MassBalanceCalibrationError: We could not find a way to correct the climate data and fit within the prescribed bounds for mu*.</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>RGI60-17.04969</th>\n",
       "      <td>7.921</td>\n",
       "      <td>mu_star_calibration_from_geodetic_mb</td>\n",
       "      <td>MassBalanceCalibrationError: We could not find a way to correct the climate data and fit within the prescribed bounds for mu*.</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                rgi_area_km2                            error_task  \\\n",
       "rgi_id                                                               \n",
       "RGI60-17.05181      1234.714  mu_star_calibration_from_geodetic_mb   \n",
       "RGI60-17.04982        61.974  mu_star_calibration_from_geodetic_mb   \n",
       "RGI60-17.04963        40.424  mu_star_calibration_from_geodetic_mb   \n",
       "RGI60-17.05044        32.994  mu_star_calibration_from_geodetic_mb   \n",
       "RGI60-17.04969         7.921  mu_star_calibration_from_geodetic_mb   \n",
       "\n",
       "                                                                                                                                     error_msg  \n",
       "rgi_id                                                                                                                                          \n",
       "RGI60-17.05181  MassBalanceCalibrationError: We could not find a way to correct the climate data and fit within the prescribed bounds for mu*.  \n",
       "RGI60-17.04982  MassBalanceCalibrationError: We could not find a way to correct the climate data and fit within the prescribed bounds for mu*.  \n",
       "RGI60-17.04963  MassBalanceCalibrationError: We could not find a way to correct the climate data and fit within the prescribed bounds for mu*.  \n",
       "RGI60-17.05044  MassBalanceCalibrationError: We could not find a way to correct the climate data and fit within the prescribed bounds for mu*.  \n",
       "RGI60-17.04969  MassBalanceCalibrationError: We could not find a way to correct the climate data and fit within the prescribed bounds for mu*.  "
      ]
     },
     "execution_count": 200,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dfserr_reg['L5_elev_bands_2.6_GSWP3_W5E5_match_geod_pergla_2.6_qc0_b160_rgi_17'].head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## A closer look to RGI region 19: we only look here at ERA5 & qc3"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1152x1296 with 8 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.set_style('whitegrid')\n",
    "\n",
    "exp = 'elev_bands'\n",
    "qc = 'qc3'\n",
    "pcp = 'pcp1.6'\n",
    "clim = 'ERA5'\n",
    "# when we compare between ERA5 and CRU, we have to omit region 19 because CRU has no climate date for RGI region 19!\n",
    "rgi_reg = '19'\n",
    "missing = []\n",
    "# different match options only available for elev_bands\n",
    "dfserr_rgi19 = {}\n",
    "pd_rel_error_area_rgi19 = pd.DataFrame(columns=['rel_error_area_in_percent', 'level', 'exp',\n",
    "                                              'clim_pcp', 'match', 'qc', 'border', 'rgi_reg'])\n",
    "\n",
    "plt.figure(figsize=(16,18))\n",
    "n = 1\n",
    "for match in ['no_match', 'match_geod', 'match_geod_pergla', 'match_geod_pergla_massredis']:  # \n",
    "    for exp in ['elev_bands', 'centerlines']:\n",
    "        plt.subplot(4,2,n)\n",
    "        n += 1\n",
    "        try:\n",
    "            dfserr, pd_rel_error_area = error_analysis_w_plot(dfserr=dfserr_rgi19, pd_rel_error_area=pd_rel_error_area_rgi19,\n",
    "                                                              level=level,exp=exp, pcp =pcp, clim=clim, \n",
    "                                                              qc=qc,border=border, match=match,\n",
    "                                                              rgi_reg = rgi_reg,\n",
    "                                                              subplot=True, xlim=300)\n",
    "        except:\n",
    "            missing.append(f'{level}_{exp}_{pcp}_{clim}_{match}_{qc}')\n",
    "            plt.title(f'missing: {level}_{exp}_{pcp}_{clim}_{match}_{qc}')\n",
    "plt.tight_layout()\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<a id='id-rgi-19'></a>"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "in RGI 19 with ERA5 and qc3:\n",
    "- most errors are coming from preprocessing level 2 or lower (e.g. (simple_)glacier_masks or elevation_band_flowline).\n",
    "- similar as for the other regions, more errors occur for 'no_match' or 'match_geod' than for 'match_geod_pergla'. \n",
    "- However, 'match_geod_pergla_massredis' (~1% relative failing glacier area), has twice as large failing glacier area than 'no_match'"
   ]
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   "source": []
  }
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