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    "## Projection simulations check:\n",
    "- check dVdt -> corresponds approximately to Hugonnet et al. by comparing W5E5 vs W5E5_spinup\n",
    "    - e.g.: https://nbviewer.org/urls/cluster.klima.uni-bremen.de/~pschmitt/dynamic_prepro/analysis_dyn_spn.ipynb?flush_cache=true\n",
    "    - and: https://nbviewer.org/urls/cluster.klima.uni-bremen.de/~lschuster/error_analysis/working_glacier_gdirs_comparison.ipynb\n",
    "- \n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "9675e84b-9370-4574-bb6c-aca00ffa202f",
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   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "2023-05-03 15:44:00: oggm.cfg: Reading default parameters from the OGGM `params.cfg` configuration file.\n",
      "2023-05-03 15:44:00: oggm.cfg: Multiprocessing switched OFF according to the parameter file.\n",
      "2023-05-03 15:44:00: 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",
    "cfg.initialize()\n",
    "import seaborn as sns\n",
    "sns.set_context('talk')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "id": "43dc68ac-10ec-4370-b606-089d5c7278b0",
   "metadata": {},
   "outputs": [],
   "source": [
    "pd_geodetic = utils.get_geodetic_mb_dataframe()[utils.get_geodetic_mb_dataframe().period=='2000-01-01_2020-01-01']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "id": "5978bb84-9779-4e24-b08a-807a3b3cb81e",
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    "working_all = True\n",
    "if working_all:\n",
    "    pd_working_all = pd.read_csv('all_common_working_rgi_ids.csv', index_col='rgiid')\n",
    "    all_running_rgis = pd_working_all.index\n",
    "else:\n",
    "    all_running_rgis_d = {}\n",
    "    for hist in ['w5e5_gcm_merged', 'gcm_from_2000']:\n",
    "        #for bc in ['_bc_2000_2019']:\n",
    "        pd_working = pd.read_csv(f'working_rgis_for_oggm_v16_CMIP6{bc}_{hist}.csv', index_col='rgiid', low_memory=False)\n",
    "        all_running_rgis_d[hist] = pd_working['all_running_rgis'].dropna().index.values\n",
    "        print(len(all_running_rgis_d[hist]))\n",
    "    all_running_rgis = list(set(all_running_rgis_d['w5e5_gcm_merged']).intersection(all_running_rgis_d['gcm_from_2000']))\n",
    "    pd_working_all = pd_working.loc[all_running_rgis][['area','all_running_rgis', 'rgi_reg']]\n",
    "    pd_working_all = pd_working_all.dropna()"
   ]
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   "execution_count": 27,
   "id": "4e8e8bbb-9b0a-4a0a-9864-cb27858bb093",
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   "source": [
    "all_running_rgis = pd_working_all.index.values\n",
    "pd_geodetic_running = pd_geodetic.loc[all_running_rgis]"
   ]
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    "\n",
    "\n",
    "period = '2000-01-01_2020-01-01'\n",
    "\n",
    "#dfz = pd.read_csv(utils.get_demo_file('zemp_ref_2006_2016.csv'), index_col=0)\n",
    "#dfh['dmdt_zemp'] = dfz.SMB.values * 1000\n",
    "#dfh['dmdt_zemp_err'] = dfz.SMB_err.values * 1000\n",
    "dfh = pd.read_csv(utils.get_demo_file('table_hugonnet_regions_10yr_20yr_ar6period.csv'), index_col=0)\n",
    "dfh = dfh.loc[dfh.period == period]\n",
    "\n",
    "\n",
    "dfh.index = ['{:02d}'.format(int(rgi_reg)) for rgi_reg in dfh.index]\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "2a3bbe5d-1cbf-4b45-ae5d-6b53b24a9082",
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   "source": [
    "\n",
    "# get those geodetic estimates of the common running glaciers and that do the mean! \n",
    "dmdtda_working_glaciers_geods = {}\n",
    "dmdt_working_glaciers_geods = {}\n",
    "for reg in np.arange(1,20,1):\n",
    "    pd_geodetic_running_reg = pd_geodetic_running[pd_geodetic_running.reg == reg]\n",
    "\n",
    "    dmdtda_working_glaciers_geod = np.average(pd_geodetic_running_reg.dmdtda*1e3, weights=pd_geodetic_running_reg.area)\n",
    "    dmdt_working_glaciers_geod = (pd_geodetic_running_reg.dmdtda*1e3*pd_geodetic_running_reg.area).sum()*1e-12\n",
    "    rgi_reg  = '{:02d}'.format(reg)\n",
    "    dmdtda_working_glaciers_geods[rgi_reg] = dmdtda_working_glaciers_geod\n",
    "    dmdt_working_glaciers_geods[rgi_reg] = dmdt_working_glaciers_geod\n",
    "pd_working_glaciers_geod =pd.DataFrame([dmdt_working_glaciers_geods,dmdtda_working_glaciers_geods],\n",
    "                                       index=['dmdt_geodetic_only_running_glaciers', 'dmdtda_geodetic_only_running_glaciers']).astype(float)\n",
    "\n",
    "\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "id": "b2f0057e-f498-4e89-b029-ffb8b75df9ef",
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   "source": [
    "# ok the summary statistcs are all the same except for glacier_statistics....\n",
    "run = False\n",
    "border = '160'\n",
    "if run:\n",
    "    path = '/home/www/oggm/gdirs/oggm_v1.6/L3-L5_files/2023.2/elev_bands'\n",
    "    for rgi_reg in np.arange(1, 20):\n",
    "        rgi_reg_int = rgi_reg.copy()\n",
    "\n",
    "        rgi_reg = '{:02d}'.format(rgi_reg)\n",
    "        all_running_rgis_reg = pd_working_all.loc[pd_working_all.rgi_reg==rgi_reg_int]['all_running_rgis'].dropna().index\n",
    "\n",
    "        ds_l = []\n",
    "        df_l = []\n",
    "        dfs_l = []\n",
    "        for opt in ['W5E5', 'W5E5_spinup']:\n",
    "\n",
    "            fd = f'{path}/{opt}/RGI62/b_{border}/L5/summary/'\n",
    "\n",
    "\n",
    "            df_l.append(pd.read_csv(fd + f'fixed_geometry_mass_balance_{rgi_reg}.csv'.format(rgi_reg), index_col=0, low_memory=False))\n",
    "            dfs_l.append(pd.read_csv(fd + f'glacier_statistics_{rgi_reg}.csv'.format(rgi_reg), index_col=0, low_memory=False))\n",
    "            with xr.open_dataset(fd + f'historical_run_output_extended_{rgi_reg}.nc') as ds:\n",
    "                ds = ds[['volume', 'area']].sum(dim='rgi_id')\n",
    "                ds_l.append(ds)\n",
    "        np.testing.assert_allclose(df_l[0], df_l[1])\n",
    "        np.testing.assert_allclose(ds_l[0].volume, ds_l[1].volume)\n",
    "        np.testing.assert_allclose(ds_l[0].area, ds_l[1].area)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "f30a9bab-ac32-4f41-b1f8-3c5027efd7de",
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   "source": [
    "run = False\n",
    "border = '160'\n",
    "if run:\n",
    "    for opt in ['W5E5', 'W5E5_spinup']:\n",
    "\n",
    "        path = '/home/www/oggm/gdirs/oggm_v1.6/L3-L5_files/2023.2/elev_bands'\n",
    "        fd = f'{path}/{opt}/RGI62/b_{border}/L5/summary/'\n",
    "\n",
    "        for rgi_reg in np.arange(1, 20):\n",
    "            rgi_reg_int = rgi_reg.copy()\n",
    "            all_running_rgis_reg = pd_working_all.loc[pd_working_all.rgi_reg==rgi_reg_int]['all_running_rgis'].dropna().index\n",
    "            rgi_reg = '{:02d}'.format(rgi_reg)\n",
    "\n",
    "            \n",
    "            try:\n",
    "                df = pd.read_csv(fd + f'fixed_geometry_mass_balance_{rgi_reg}.csv'.format(rgi_reg), index_col=0, low_memory=False)\n",
    "                dfs = pd.read_csv(fd + f'glacier_statistics_{rgi_reg}.csv'.format(rgi_reg), index_col=0, low_memory=False)\n",
    "            except FileNotFoundError:\n",
    "                #print('Not here:',rgi_reg)\n",
    "                continue\n",
    "\n",
    "            df = df.dropna(axis=0, how='all')\n",
    "            # just choose those glaciers that work for all prepro gdirs types!\n",
    "            df = df[all_running_rgis_reg]\n",
    "            # check if there are no np.NaNs (otherwise sth. is wrong with all_running_rgis_reg)\n",
    "            assert ~np.any(df.isna())\n",
    "            #df = df.dropna(axis=1, how='all')\n",
    "            #         odf = pd.DataFrame(df.loc[2006:2016].mean(), columns=['SMB'])\n",
    "            #         odf['AREA'] = dfs.rgi_area_km2\n",
    "\n",
    "            #         dfh.loc[rgi_reg, 'AREA_OGGM'] = odf['AREA'].sum()\n",
    "            #         dfh.loc[rgi_reg, 'SMB_OGGM'] = np.average(odf['SMB'], weights=odf['AREA']) / 1000\n",
    "\n",
    "            odf = pd.DataFrame(df.loc[2000:].mean(), columns=['SMB'])\n",
    "            odf['AREA'] = dfs.rgi_area_km2\n",
    "            dfh.loc[rgi_reg, f'dmdt_OGGM_{opt}'] = (vol_ts.loc[2019] - vol_ts.loc[2000]) * cfg.PARAMS['ice_density'] * 1e-12 / 20\n",
    "            dfh.loc[rgi_reg, f'dmdtda_OGGM_{opt}'] = np.average(odf['SMB'], weights=odf['AREA'])\n",
    "\n",
    "            if opt == 'W5E5':\n",
    "                stat = f'historical_run_output_extended_{rgi_reg}.nc'\n",
    "            else:\n",
    "                stat = f'spinup_historical_run_output_{rgi_reg}.nc'\n",
    "            with xr.open_dataset(fd +stat) as ds:\n",
    "                ds = ds.sel(rgi_id=all_running_rgis_reg)\n",
    "                ds = ds[['volume', 'area']].sum(dim='rgi_id')\n",
    "            vol_ts = ds.volume.to_series()\n",
    "            area_ts = ds.area.to_series()\n",
    "            # dmdt is in kg per year *10e-12\n",
    "            dfh.loc[rgi_reg, f'dmdt_dyna_OGGM_{opt}'] = (vol_ts.loc[2019] - vol_ts.loc[2000]) * cfg.PARAMS['ice_density'] * 1e-12 / 20\n",
    "            dfh.loc[rgi_reg, f'dmdtda_dyna_OGGM_{opt}'] = (vol_ts.loc[2019] - vol_ts.loc[2000]) / area_ts.loc[2000] * cfg.PARAMS['ice_density'] / 20 \n",
    "            dfh.loc[rgi_reg, f'area_OGGM_2000_{opt}'] = area_ts.loc[2000]       \n",
    "            dfh.loc[rgi_reg, f'vol_OGGM_2000_{opt}'] = vol_ts.loc[2000]  \n",
    "            \n",
    "            with xr.open_mfdataset(f'/home/www/lschuster/runs_oggm_v16/output/RGI{rgi_reg}/run_hydro_w5e5_gcm_merged_endyr2100_CMIP6_BCC-CSM2-MR_ssp245_bc_2000_2019_rgi{rgi_reg}*.nc') as dproj:\n",
    "                dproj = dproj.sel(rgi_id=all_running_rgis_reg)\n",
    "                dproj = dproj[['volume', 'area']].sum(dim='rgi_id')\n",
    "            vol_ts = dproj.volume.to_series()\n",
    "            area_ts = dproj.area.to_series()\n",
    "            dproj.close()\n",
    "            \n",
    "            dfh.loc[rgi_reg, f'dmdtda_dyna_OGGM_proj_{opt}'] = (vol_ts.loc[2019] - vol_ts.loc[2000]) / area_ts.loc[2000] * cfg.PARAMS['ice_density'] / 20 \n",
    "            dfh.loc[rgi_reg, f'area_OGGM_2000_proj_{opt}'] = area_ts.loc[2000]       \n",
    "            dfh.loc[rgi_reg, f'vol_OGGM_2000_proj_{opt}'] = vol_ts.loc[2000]  \n",
    "            \n",
    "            \n",
    "    dfhh = pd.concat([dfh,pd_working_glaciers_geod.T], axis=1)\n",
    "    dfhh.to_csv(f'oggm_v161_w5e5_spinup_dmdtda_area_vol_for_prepro_level_5_gdirs.csv')\n",
    "else:\n",
    "    # new with (partly) preprocessed gdirs\n",
    "    dfh = pd.read_csv(f'oggm_v161_w5e5_spinup_dmdtda_area_vol_for_prepro_level_5_gdirs.csv', index_col=[0])\n",
    "    # old with wrong preprocessed gdirs: dfh = pd.read_csv(f'dmdtda_dmdt_for_prepro_level_5_gdirs.csv', index_col=[0])\n",
    "    dfh.index = ['{:02d}'.format(int(rgi_reg)) for rgi_reg in dfh.index]"
   ]
  },
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   "execution_count": 73,
   "id": "3e2b8843-29f0-423b-ac17-231ab86bdaf7",
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       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.DataArray &#x27;is_fixed_geometry_spinup&#x27; (time: 42, rgi_id: 2752)&gt;\n",
       "[115584 values with dtype=float32]\n",
       "Coordinates:\n",
       "  * time            (time) float64 1.979e+03 1.98e+03 ... 2.019e+03 2.02e+03\n",
       "  * rgi_id          (rgi_id) object &#x27;RGI60-19.00001&#x27; ... &#x27;RGI60-19.02752&#x27;\n",
       "    hydro_year      (time) int64 1979 1980 1981 1982 ... 2017 2018 2019 2020\n",
       "    hydro_month     (time) int64 10 10 10 10 10 10 10 ... 10 10 10 10 10 10 10\n",
       "    calendar_year   (time) int64 1979 1980 1981 1982 ... 2017 2018 2019 2020\n",
       "    calendar_month  (time) int64 1 1 1 1 1 1 1 1 1 1 1 ... 1 1 1 1 1 1 1 1 1 1 1\n",
       "Attributes:\n",
       "    description:  Part of the series which are spinup\n",
       "    unit:         -</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'>'is_fixed_geometry_spinup'</div><ul class='xr-dim-list'><li><span class='xr-has-index'>time</span>: 42</li><li><span class='xr-has-index'>rgi_id</span>: 2752</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-a06c9fc5-686f-4563-805e-ad8b1123b5ce' class='xr-array-in' type='checkbox' checked><label for='section-a06c9fc5-686f-4563-805e-ad8b1123b5ce' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>...</span></div><div class='xr-array-data'><pre>[115584 values with dtype=float32]</pre></div></div></li><li class='xr-section-item'><input id='section-c064fee3-e6f2-4ef5-9abb-a5ebe8e17ce6' class='xr-section-summary-in' type='checkbox'  checked><label for='section-c064fee3-e6f2-4ef5-9abb-a5ebe8e17ce6' class='xr-section-summary' >Coordinates: <span>(6)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>1.979e+03 1.98e+03 ... 2.02e+03</div><input id='attrs-899d8029-f9b3-4ab2-9e95-dd47eb70752f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-899d8029-f9b3-4ab2-9e95-dd47eb70752f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-93c63e7b-eb78-42e5-90d7-c087768ba8e7' class='xr-var-data-in' type='checkbox'><label for='data-93c63e7b-eb78-42e5-90d7-c087768ba8e7' 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>description :</span></dt><dd>Floating year</dd></dl></div><div class='xr-var-data'><pre>array([1979., 1980., 1981., 1982., 1983., 1984., 1985., 1986., 1987., 1988.,\n",
       "       1989., 1990., 1991., 1992., 1993., 1994., 1995., 1996., 1997., 1998.,\n",
       "       1999., 2000., 2001., 2002., 2003., 2004., 2005., 2006., 2007., 2008.,\n",
       "       2009., 2010., 2011., 2012., 2013., 2014., 2015., 2016., 2017., 2018.,\n",
       "       2019., 2020.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>rgi_id</span></div><div class='xr-var-dims'>(rgi_id)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>&#x27;RGI60-19.00001&#x27; ... &#x27;RGI60-19.0...</div><input id='attrs-9ae711c2-7675-4a01-910d-ed45434ac268' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-9ae711c2-7675-4a01-910d-ed45434ac268' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-086fcfa1-9d56-40d6-ac02-d7622bf23c35' class='xr-var-data-in' type='checkbox'><label for='data-086fcfa1-9d56-40d6-ac02-d7622bf23c35' 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>description :</span></dt><dd>RGI glacier identifier</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;RGI60-19.00001&#x27;, &#x27;RGI60-19.00002&#x27;, &#x27;RGI60-19.00003&#x27;, ...,\n",
       "       &#x27;RGI60-19.02750&#x27;, &#x27;RGI60-19.02751&#x27;, &#x27;RGI60-19.02752&#x27;], dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>hydro_year</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-49796144-0e46-4f1d-9218-fa573e6c89ae' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-49796144-0e46-4f1d-9218-fa573e6c89ae' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-77c18c1d-a964-4333-8722-d3a711466513' class='xr-var-data-in' type='checkbox'><label for='data-77c18c1d-a964-4333-8722-d3a711466513' 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>description :</span></dt><dd>Hydrological year</dd></dl></div><div class='xr-var-data'><pre>array([1979, 1980, 1981, 1982, 1983, 1984, 1985, 1986, 1987, 1988, 1989, 1990,\n",
       "       1991, 1992, 1993, 1994, 1995, 1996, 1997, 1998, 1999, 2000, 2001, 2002,\n",
       "       2003, 2004, 2005, 2006, 2007, 2008, 2009, 2010, 2011, 2012, 2013, 2014,\n",
       "       2015, 2016, 2017, 2018, 2019, 2020])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>hydro_month</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-0a052787-4d4b-4ad2-88c6-b3ef00b1bdb3' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-0a052787-4d4b-4ad2-88c6-b3ef00b1bdb3' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c022f755-3b12-4e0b-a54e-474c96c17335' class='xr-var-data-in' type='checkbox'><label for='data-c022f755-3b12-4e0b-a54e-474c96c17335' 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>description :</span></dt><dd>Hydrological month</dd></dl></div><div class='xr-var-data'><pre>array([10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10,\n",
       "       10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10,\n",
       "       10, 10, 10, 10, 10, 10])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>calendar_year</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-4c3b5a55-f471-4a56-8a7c-32ae80cd8aaf' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-4c3b5a55-f471-4a56-8a7c-32ae80cd8aaf' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d237096a-1302-4576-ae2a-1d28a6faf906' class='xr-var-data-in' type='checkbox'><label for='data-d237096a-1302-4576-ae2a-1d28a6faf906' 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>description :</span></dt><dd>Calendar year</dd></dl></div><div class='xr-var-data'><pre>array([1979, 1980, 1981, 1982, 1983, 1984, 1985, 1986, 1987, 1988, 1989, 1990,\n",
       "       1991, 1992, 1993, 1994, 1995, 1996, 1997, 1998, 1999, 2000, 2001, 2002,\n",
       "       2003, 2004, 2005, 2006, 2007, 2008, 2009, 2010, 2011, 2012, 2013, 2014,\n",
       "       2015, 2016, 2017, 2018, 2019, 2020])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>calendar_month</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-addbb21a-2f6a-4d20-a4dd-5465dc77479b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-addbb21a-2f6a-4d20-a4dd-5465dc77479b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6940419b-1d43-4724-909e-6332989b9e29' class='xr-var-data-in' type='checkbox'><label for='data-6940419b-1d43-4724-909e-6332989b9e29' 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>description :</span></dt><dd>Calendar month</dd></dl></div><div class='xr-var-data'><pre>array([1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,\n",
       "       1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-2c3bde4a-552b-4eb6-92ed-276ba8ec4702' class='xr-section-summary-in' type='checkbox'  checked><label for='section-2c3bde4a-552b-4eb6-92ed-276ba8ec4702' class='xr-section-summary' >Attributes: <span>(2)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>description :</span></dt><dd>Part of the series which are spinup</dd><dt><span>unit :</span></dt><dd>-</dd></dl></div></li></ul></div></div>"
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       "<xarray.DataArray 'is_fixed_geometry_spinup' (time: 42, rgi_id: 2752)>\n",
       "[115584 values with dtype=float32]\n",
       "Coordinates:\n",
       "  * time            (time) float64 1.979e+03 1.98e+03 ... 2.019e+03 2.02e+03\n",
       "  * rgi_id          (rgi_id) object 'RGI60-19.00001' ... 'RGI60-19.02752'\n",
       "    hydro_year      (time) int64 ...\n",
       "    hydro_month     (time) int64 ...\n",
       "    calendar_year   (time) int64 ...\n",
       "    calendar_month  (time) int64 ...\n",
       "Attributes:\n",
       "    description:  Part of the series which are spinup\n",
       "    unit:         -"
      ]
     },
     "execution_count": 73,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "xr.open_dataset(fd +stat)['is_fixed_geometry_spinup']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "id": "665966b3-0991-4923-9a5c-409612d7307e",
   "metadata": {},
   "outputs": [
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       "      <td>-520.062346</td>\n",
       "      <td>-459.171867</td>\n",
       "      <td>1.504163e+10</td>\n",
       "      <td>1.079413e+12</td>\n",
       "      <td>-468.670707</td>\n",
       "      <td>...</td>\n",
       "      <td>1.015489e+12</td>\n",
       "      <td>-520.062346</td>\n",
       "      <td>-468.847690</td>\n",
       "      <td>1.557374e+10</td>\n",
       "      <td>1.015611e+12</td>\n",
       "      <td>-468.670707</td>\n",
       "      <td>1.557368e+10</td>\n",
       "      <td>1.015489e+12</td>\n",
       "      <td>-7.552034</td>\n",
       "      <td>-520.062346</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>03</th>\n",
       "      <td>2000-01-01_2020-01-01</td>\n",
       "      <td>-30.54</td>\n",
       "      <td>2.42</td>\n",
       "      <td>-292.74</td>\n",
       "      <td>23.41</td>\n",
       "      <td>-290.846673</td>\n",
       "      <td>-313.887098</td>\n",
       "      <td>1.050887e+11</td>\n",
       "      <td>2.832242e+13</td>\n",
       "      <td>-317.177610</td>\n",
       "      <td>...</td>\n",
       "      <td>2.750947e+13</td>\n",
       "      <td>-290.846673</td>\n",
       "      <td>-317.156260</td>\n",
       "      <td>1.054534e+11</td>\n",
       "      <td>2.750947e+13</td>\n",
       "      <td>-317.177610</td>\n",
       "      <td>1.054534e+11</td>\n",
       "      <td>2.750947e+13</td>\n",
       "      <td>-30.564668</td>\n",
       "      <td>-290.846673</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>04</th>\n",
       "      <td>2000-01-01_2020-01-01</td>\n",
       "      <td>-26.48</td>\n",
       "      <td>2.13</td>\n",
       "      <td>-652.65</td>\n",
       "      <td>52.90</td>\n",
       "      <td>-648.224633</td>\n",
       "      <td>-616.083369</td>\n",
       "      <td>4.091611e+10</td>\n",
       "      <td>8.672269e+12</td>\n",
       "      <td>-609.177732</td>\n",
       "      <td>...</td>\n",
       "      <td>8.730872e+12</td>\n",
       "      <td>-648.224633</td>\n",
       "      <td>-609.208031</td>\n",
       "      <td>4.137931e+10</td>\n",
       "      <td>8.730939e+12</td>\n",
       "      <td>-609.177732</td>\n",
       "      <td>4.137927e+10</td>\n",
       "      <td>8.730872e+12</td>\n",
       "      <td>-26.501952</td>\n",
       "      <td>-648.224633</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>05</th>\n",
       "      <td>2000-01-01_2020-01-01</td>\n",
       "      <td>-35.49</td>\n",
       "      <td>2.89</td>\n",
       "      <td>-427.09</td>\n",
       "      <td>35.03</td>\n",
       "      <td>-395.943637</td>\n",
       "      <td>-365.734434</td>\n",
       "      <td>8.969990e+10</td>\n",
       "      <td>1.576957e+13</td>\n",
       "      <td>-372.083244</td>\n",
       "      <td>...</td>\n",
       "      <td>1.548381e+13</td>\n",
       "      <td>-395.943637</td>\n",
       "      <td>-372.086678</td>\n",
       "      <td>9.078941e+10</td>\n",
       "      <td>1.547965e+13</td>\n",
       "      <td>-372.083244</td>\n",
       "      <td>9.078936e+10</td>\n",
       "      <td>1.548381e+13</td>\n",
       "      <td>-35.513797</td>\n",
       "      <td>-395.943637</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>06</th>\n",
       "      <td>2000-01-01_2020-01-01</td>\n",
       "      <td>-9.36</td>\n",
       "      <td>0.70</td>\n",
       "      <td>-877.49</td>\n",
       "      <td>66.59</td>\n",
       "      <td>-846.380030</td>\n",
       "      <td>-785.782785</td>\n",
       "      <td>1.105934e+10</td>\n",
       "      <td>3.785219e+12</td>\n",
       "      <td>-752.360573</td>\n",
       "      <td>...</td>\n",
       "      <td>3.789364e+12</td>\n",
       "      <td>-846.380030</td>\n",
       "      <td>-752.361603</td>\n",
       "      <td>1.107997e+10</td>\n",
       "      <td>3.789366e+12</td>\n",
       "      <td>-752.360573</td>\n",
       "      <td>1.107997e+10</td>\n",
       "      <td>3.789364e+12</td>\n",
       "      <td>-9.360413</td>\n",
       "      <td>-846.380030</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>07</th>\n",
       "      <td>2000-01-01_2020-01-01</td>\n",
       "      <td>-10.53</td>\n",
       "      <td>0.85</td>\n",
       "      <td>-312.12</td>\n",
       "      <td>25.27</td>\n",
       "      <td>-303.312236</td>\n",
       "      <td>-277.946870</td>\n",
       "      <td>3.397060e+10</td>\n",
       "      <td>7.565824e+12</td>\n",
       "      <td>-274.618549</td>\n",
       "      <td>...</td>\n",
       "      <td>7.538178e+12</td>\n",
       "      <td>-303.312236</td>\n",
       "      <td>-273.497472</td>\n",
       "      <td>3.411341e+10</td>\n",
       "      <td>7.544915e+12</td>\n",
       "      <td>-274.618549</td>\n",
       "      <td>3.411341e+10</td>\n",
       "      <td>7.538178e+12</td>\n",
       "      <td>-10.539078</td>\n",
       "      <td>-308.281779</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>08</th>\n",
       "      <td>2000-01-01_2020-01-01</td>\n",
       "      <td>-1.67</td>\n",
       "      <td>0.18</td>\n",
       "      <td>-577.56</td>\n",
       "      <td>62.94</td>\n",
       "      <td>-565.171709</td>\n",
       "      <td>-537.874403</td>\n",
       "      <td>2.948294e+09</td>\n",
       "      <td>3.061147e+11</td>\n",
       "      <td>-519.610319</td>\n",
       "      <td>...</td>\n",
       "      <td>3.081384e+11</td>\n",
       "      <td>-565.171709</td>\n",
       "      <td>-519.660187</td>\n",
       "      <td>3.119956e+09</td>\n",
       "      <td>3.081740e+11</td>\n",
       "      <td>-519.610319</td>\n",
       "      <td>3.119956e+09</td>\n",
       "      <td>3.081384e+11</td>\n",
       "      <td>-1.666295</td>\n",
       "      <td>-565.171709</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>09</th>\n",
       "      <td>2000-01-01_2020-01-01</td>\n",
       "      <td>-10.40</td>\n",
       "      <td>0.94</td>\n",
       "      <td>-202.92</td>\n",
       "      <td>18.47</td>\n",
       "      <td>-202.111130</td>\n",
       "      <td>-216.501646</td>\n",
       "      <td>5.156761e+10</td>\n",
       "      <td>1.468823e+13</td>\n",
       "      <td>-215.229335</td>\n",
       "      <td>...</td>\n",
       "      <td>1.396005e+13</td>\n",
       "      <td>-202.111130</td>\n",
       "      <td>-213.970306</td>\n",
       "      <td>5.175823e+10</td>\n",
       "      <td>1.396682e+13</td>\n",
       "      <td>-215.229335</td>\n",
       "      <td>5.175822e+10</td>\n",
       "      <td>1.396005e+13</td>\n",
       "      <td>-10.422389</td>\n",
       "      <td>-202.111130</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>2000-01-01_2020-01-01</td>\n",
       "      <td>-1.22</td>\n",
       "      <td>0.18</td>\n",
       "      <td>-503.76</td>\n",
       "      <td>73.45</td>\n",
       "      <td>-520.976144</td>\n",
       "      <td>-498.682909</td>\n",
       "      <td>2.321455e+09</td>\n",
       "      <td>1.407462e+11</td>\n",
       "      <td>-491.310310</td>\n",
       "      <td>...</td>\n",
       "      <td>1.335681e+11</td>\n",
       "      <td>-520.976144</td>\n",
       "      <td>-494.567885</td>\n",
       "      <td>2.632843e+09</td>\n",
       "      <td>1.339931e+11</td>\n",
       "      <td>-491.310310</td>\n",
       "      <td>2.632842e+09</td>\n",
       "      <td>1.335681e+11</td>\n",
       "      <td>-1.209430</td>\n",
       "      <td>-520.976144</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>2000-01-01_2020-01-01</td>\n",
       "      <td>-1.69</td>\n",
       "      <td>0.21</td>\n",
       "      <td>-863.75</td>\n",
       "      <td>107.67</td>\n",
       "      <td>-804.911322</td>\n",
       "      <td>-735.565310</td>\n",
       "      <td>2.091841e+09</td>\n",
       "      <td>1.328812e+11</td>\n",
       "      <td>-755.383444</td>\n",
       "      <td>...</td>\n",
       "      <td>1.275209e+11</td>\n",
       "      <td>-804.911322</td>\n",
       "      <td>-756.144075</td>\n",
       "      <td>2.147618e+09</td>\n",
       "      <td>1.275704e+11</td>\n",
       "      <td>-755.383444</td>\n",
       "      <td>2.147616e+09</td>\n",
       "      <td>1.275209e+11</td>\n",
       "      <td>-1.683695</td>\n",
       "      <td>-804.911322</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>2000-01-01_2020-01-01</td>\n",
       "      <td>-0.67</td>\n",
       "      <td>0.09</td>\n",
       "      <td>-540.81</td>\n",
       "      <td>76.48</td>\n",
       "      <td>-508.004299</td>\n",
       "      <td>-448.928361</td>\n",
       "      <td>1.149040e+09</td>\n",
       "      <td>6.012630e+10</td>\n",
       "      <td>-468.323522</td>\n",
       "      <td>...</td>\n",
       "      <td>6.126510e+10</td>\n",
       "      <td>-508.004299</td>\n",
       "      <td>-468.602343</td>\n",
       "      <td>1.162906e+09</td>\n",
       "      <td>6.127591e+10</td>\n",
       "      <td>-468.323522</td>\n",
       "      <td>1.162905e+09</td>\n",
       "      <td>6.126510e+10</td>\n",
       "      <td>-0.673094</td>\n",
       "      <td>-507.318818</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>2000-01-01_2020-01-01</td>\n",
       "      <td>-9.60</td>\n",
       "      <td>1.06</td>\n",
       "      <td>-199.00</td>\n",
       "      <td>22.15</td>\n",
       "      <td>-195.669760</td>\n",
       "      <td>-181.528323</td>\n",
       "      <td>4.921490e+10</td>\n",
       "      <td>3.310739e+12</td>\n",
       "      <td>-188.710806</td>\n",
       "      <td>...</td>\n",
       "      <td>3.306260e+12</td>\n",
       "      <td>-195.669760</td>\n",
       "      <td>-188.998790</td>\n",
       "      <td>5.070877e+10</td>\n",
       "      <td>3.307080e+12</td>\n",
       "      <td>-188.710806</td>\n",
       "      <td>5.070921e+10</td>\n",
       "      <td>3.306260e+12</td>\n",
       "      <td>-9.630135</td>\n",
       "      <td>-195.669760</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>2000-01-01_2020-01-01</td>\n",
       "      <td>-4.56</td>\n",
       "      <td>0.84</td>\n",
       "      <td>-138.59</td>\n",
       "      <td>25.49</td>\n",
       "      <td>-135.945961</td>\n",
       "      <td>-141.278547</td>\n",
       "      <td>3.359802e+10</td>\n",
       "      <td>2.893355e+12</td>\n",
       "      <td>-146.201431</td>\n",
       "      <td>...</td>\n",
       "      <td>2.880236e+12</td>\n",
       "      <td>-135.945961</td>\n",
       "      <td>-146.248605</td>\n",
       "      <td>3.452558e+10</td>\n",
       "      <td>2.880364e+12</td>\n",
       "      <td>-146.201431</td>\n",
       "      <td>3.452543e+10</td>\n",
       "      <td>2.880236e+12</td>\n",
       "      <td>-4.561651</td>\n",
       "      <td>-135.945961</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>2000-01-01_2020-01-01</td>\n",
       "      <td>-6.87</td>\n",
       "      <td>0.71</td>\n",
       "      <td>-477.23</td>\n",
       "      <td>49.28</td>\n",
       "      <td>-468.178425</td>\n",
       "      <td>-435.259180</td>\n",
       "      <td>1.472464e+10</td>\n",
       "      <td>9.025321e+11</td>\n",
       "      <td>-460.624337</td>\n",
       "      <td>...</td>\n",
       "      <td>8.862605e+11</td>\n",
       "      <td>-468.178425</td>\n",
       "      <td>-459.986830</td>\n",
       "      <td>1.492772e+10</td>\n",
       "      <td>8.861898e+11</td>\n",
       "      <td>-460.624337</td>\n",
       "      <td>1.492774e+10</td>\n",
       "      <td>8.862605e+11</td>\n",
       "      <td>-6.893968</td>\n",
       "      <td>-468.178425</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>2000-01-01_2020-01-01</td>\n",
       "      <td>-0.93</td>\n",
       "      <td>0.12</td>\n",
       "      <td>-453.83</td>\n",
       "      <td>58.23</td>\n",
       "      <td>-399.241599</td>\n",
       "      <td>-357.722182</td>\n",
       "      <td>2.340964e+09</td>\n",
       "      <td>9.756558e+10</td>\n",
       "      <td>-332.580099</td>\n",
       "      <td>...</td>\n",
       "      <td>9.301621e+10</td>\n",
       "      <td>-399.241599</td>\n",
       "      <td>-331.450095</td>\n",
       "      <td>2.458291e+09</td>\n",
       "      <td>9.302077e+10</td>\n",
       "      <td>-332.580099</td>\n",
       "      <td>2.458289e+09</td>\n",
       "      <td>9.301621e+10</td>\n",
       "      <td>-0.934576</td>\n",
       "      <td>-399.241599</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>2000-01-01_2020-01-01</td>\n",
       "      <td>-20.68</td>\n",
       "      <td>2.05</td>\n",
       "      <td>-715.61</td>\n",
       "      <td>71.35</td>\n",
       "      <td>-450.563247</td>\n",
       "      <td>-437.735782</td>\n",
       "      <td>1.970439e+10</td>\n",
       "      <td>2.438643e+12</td>\n",
       "      <td>-422.366381</td>\n",
       "      <td>...</td>\n",
       "      <td>2.336176e+12</td>\n",
       "      <td>-450.563247</td>\n",
       "      <td>-422.429981</td>\n",
       "      <td>2.004916e+10</td>\n",
       "      <td>2.336059e+12</td>\n",
       "      <td>-422.366381</td>\n",
       "      <td>2.004910e+10</td>\n",
       "      <td>2.336176e+12</td>\n",
       "      <td>-8.878099</td>\n",
       "      <td>-450.563247</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>2000-01-01_2020-01-01</td>\n",
       "      <td>-0.65</td>\n",
       "      <td>0.10</td>\n",
       "      <td>-718.22</td>\n",
       "      <td>108.68</td>\n",
       "      <td>-554.401058</td>\n",
       "      <td>-464.552979</td>\n",
       "      <td>1.173936e+09</td>\n",
       "      <td>6.891251e+10</td>\n",
       "      <td>-466.099648</td>\n",
       "      <td>...</td>\n",
       "      <td>6.872105e+10</td>\n",
       "      <td>-554.401058</td>\n",
       "      <td>-466.096859</td>\n",
       "      <td>1.179882e+09</td>\n",
       "      <td>6.872100e+10</td>\n",
       "      <td>-466.099648</td>\n",
       "      <td>1.179882e+09</td>\n",
       "      <td>6.872105e+10</td>\n",
       "      <td>-0.644075</td>\n",
       "      <td>-554.401058</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>2000-01-01_2020-01-01</td>\n",
       "      <td>-20.87</td>\n",
       "      <td>2.46</td>\n",
       "      <td>-166.49</td>\n",
       "      <td>19.71</td>\n",
       "      <td>-157.501651</td>\n",
       "      <td>-287.251754</td>\n",
       "      <td>1.355254e+11</td>\n",
       "      <td>4.590611e+13</td>\n",
       "      <td>-247.144597</td>\n",
       "      <td>...</td>\n",
       "      <td>4.532864e+13</td>\n",
       "      <td>-157.501651</td>\n",
       "      <td>-246.172671</td>\n",
       "      <td>1.355425e+11</td>\n",
       "      <td>4.533179e+13</td>\n",
       "      <td>-247.144597</td>\n",
       "      <td>1.355425e+11</td>\n",
       "      <td>4.532864e+13</td>\n",
       "      <td>-20.836318</td>\n",
       "      <td>-157.501651</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>19 rows × 21 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                   period   dmdt  err_dmdt  dmdtda  err_dmdtda  \\\n",
       "01  2000-01-01_2020-01-01 -66.61      5.43 -773.79       63.56   \n",
       "02  2000-01-01_2020-01-01  -7.56      0.85 -529.43       59.52   \n",
       "03  2000-01-01_2020-01-01 -30.54      2.42 -292.74       23.41   \n",
       "04  2000-01-01_2020-01-01 -26.48      2.13 -652.65       52.90   \n",
       "05  2000-01-01_2020-01-01 -35.49      2.89 -427.09       35.03   \n",
       "06  2000-01-01_2020-01-01  -9.36      0.70 -877.49       66.59   \n",
       "07  2000-01-01_2020-01-01 -10.53      0.85 -312.12       25.27   \n",
       "08  2000-01-01_2020-01-01  -1.67      0.18 -577.56       62.94   \n",
       "09  2000-01-01_2020-01-01 -10.40      0.94 -202.92       18.47   \n",
       "10  2000-01-01_2020-01-01  -1.22      0.18 -503.76       73.45   \n",
       "11  2000-01-01_2020-01-01  -1.69      0.21 -863.75      107.67   \n",
       "12  2000-01-01_2020-01-01  -0.67      0.09 -540.81       76.48   \n",
       "13  2000-01-01_2020-01-01  -9.60      1.06 -199.00       22.15   \n",
       "14  2000-01-01_2020-01-01  -4.56      0.84 -138.59       25.49   \n",
       "15  2000-01-01_2020-01-01  -6.87      0.71 -477.23       49.28   \n",
       "16  2000-01-01_2020-01-01  -0.93      0.12 -453.83       58.23   \n",
       "17  2000-01-01_2020-01-01 -20.68      2.05 -715.61       71.35   \n",
       "18  2000-01-01_2020-01-01  -0.65      0.10 -718.22      108.68   \n",
       "19  2000-01-01_2020-01-01 -20.87      2.46 -166.49       19.71   \n",
       "\n",
       "    dmdtda_OGGM_W5E5  dmdtda_dyna_OGGM_W5E5  area_OGGM_2000_W5E5  \\\n",
       "01       -682.867030            -597.772765         7.031038e+10   \n",
       "02       -520.062346            -459.171867         1.504163e+10   \n",
       "03       -290.846673            -313.887098         1.050887e+11   \n",
       "04       -648.224633            -616.083369         4.091611e+10   \n",
       "05       -395.943637            -365.734434         8.969990e+10   \n",
       "06       -846.380030            -785.782785         1.105934e+10   \n",
       "07       -303.312236            -277.946870         3.397060e+10   \n",
       "08       -565.171709            -537.874403         2.948294e+09   \n",
       "09       -202.111130            -216.501646         5.156761e+10   \n",
       "10       -520.976144            -498.682909         2.321455e+09   \n",
       "11       -804.911322            -735.565310         2.091841e+09   \n",
       "12       -508.004299            -448.928361         1.149040e+09   \n",
       "13       -195.669760            -181.528323         4.921490e+10   \n",
       "14       -135.945961            -141.278547         3.359802e+10   \n",
       "15       -468.178425            -435.259180         1.472464e+10   \n",
       "16       -399.241599            -357.722182         2.340964e+09   \n",
       "17       -450.563247            -437.735782         1.970439e+10   \n",
       "18       -554.401058            -464.552979         1.173936e+09   \n",
       "19       -157.501651            -287.251754         1.355254e+11   \n",
       "\n",
       "    vol_OGGM_2000_W5E5  dmdtda_dyna_OGGM_proj_W5E5  ...  \\\n",
       "01        1.407449e+13                 -605.323377  ...   \n",
       "02        1.079413e+12                 -468.670707  ...   \n",
       "03        2.832242e+13                 -317.177610  ...   \n",
       "04        8.672269e+12                 -609.177732  ...   \n",
       "05        1.576957e+13                 -372.083244  ...   \n",
       "06        3.785219e+12                 -752.360573  ...   \n",
       "07        7.565824e+12                 -274.618549  ...   \n",
       "08        3.061147e+11                 -519.610319  ...   \n",
       "09        1.468823e+13                 -215.229335  ...   \n",
       "10        1.407462e+11                 -491.310310  ...   \n",
       "11        1.328812e+11                 -755.383444  ...   \n",
       "12        6.012630e+10                 -468.323522  ...   \n",
       "13        3.310739e+12                 -188.710806  ...   \n",
       "14        2.893355e+12                 -146.201431  ...   \n",
       "15        9.025321e+11                 -460.624337  ...   \n",
       "16        9.756558e+10                 -332.580099  ...   \n",
       "17        2.438643e+12                 -422.366381  ...   \n",
       "18        6.891251e+10                 -466.099648  ...   \n",
       "19        4.590611e+13                 -247.144597  ...   \n",
       "\n",
       "    vol_OGGM_2000_proj_W5E5  dmdtda_OGGM_W5E5_spinup  \\\n",
       "01             1.419259e+13              -682.867030   \n",
       "02             1.015489e+12              -520.062346   \n",
       "03             2.750947e+13              -290.846673   \n",
       "04             8.730872e+12              -648.224633   \n",
       "05             1.548381e+13              -395.943637   \n",
       "06             3.789364e+12              -846.380030   \n",
       "07             7.538178e+12              -303.312236   \n",
       "08             3.081384e+11              -565.171709   \n",
       "09             1.396005e+13              -202.111130   \n",
       "10             1.335681e+11              -520.976144   \n",
       "11             1.275209e+11              -804.911322   \n",
       "12             6.126510e+10              -508.004299   \n",
       "13             3.306260e+12              -195.669760   \n",
       "14             2.880236e+12              -135.945961   \n",
       "15             8.862605e+11              -468.178425   \n",
       "16             9.301621e+10              -399.241599   \n",
       "17             2.336176e+12              -450.563247   \n",
       "18             6.872105e+10              -554.401058   \n",
       "19             4.532864e+13              -157.501651   \n",
       "\n",
       "    dmdtda_dyna_OGGM_W5E5_spinup  area_OGGM_2000_W5E5_spinup  \\\n",
       "01                   -605.642409                7.153690e+10   \n",
       "02                   -468.847690                1.557374e+10   \n",
       "03                   -317.156260                1.054534e+11   \n",
       "04                   -609.208031                4.137931e+10   \n",
       "05                   -372.086678                9.078941e+10   \n",
       "06                   -752.361603                1.107997e+10   \n",
       "07                   -273.497472                3.411341e+10   \n",
       "08                   -519.660187                3.119956e+09   \n",
       "09                   -213.970306                5.175823e+10   \n",
       "10                   -494.567885                2.632843e+09   \n",
       "11                   -756.144075                2.147618e+09   \n",
       "12                   -468.602343                1.162906e+09   \n",
       "13                   -188.998790                5.070877e+10   \n",
       "14                   -146.248605                3.452558e+10   \n",
       "15                   -459.986830                1.492772e+10   \n",
       "16                   -331.450095                2.458291e+09   \n",
       "17                   -422.429981                2.004916e+10   \n",
       "18                   -466.096859                1.179882e+09   \n",
       "19                   -246.172671                1.355425e+11   \n",
       "\n",
       "    vol_OGGM_2000_W5E5_spinup  dmdtda_dyna_OGGM_proj_W5E5_spinup  \\\n",
       "01               1.419516e+13                        -605.323377   \n",
       "02               1.015611e+12                        -468.670707   \n",
       "03               2.750947e+13                        -317.177610   \n",
       "04               8.730939e+12                        -609.177732   \n",
       "05               1.547965e+13                        -372.083244   \n",
       "06               3.789366e+12                        -752.360573   \n",
       "07               7.544915e+12                        -274.618549   \n",
       "08               3.081740e+11                        -519.610319   \n",
       "09               1.396682e+13                        -215.229335   \n",
       "10               1.339931e+11                        -491.310310   \n",
       "11               1.275704e+11                        -755.383444   \n",
       "12               6.127591e+10                        -468.323522   \n",
       "13               3.307080e+12                        -188.710806   \n",
       "14               2.880364e+12                        -146.201431   \n",
       "15               8.861898e+11                        -460.624337   \n",
       "16               9.302077e+10                        -332.580099   \n",
       "17               2.336059e+12                        -422.366381   \n",
       "18               6.872100e+10                        -466.099648   \n",
       "19               4.533179e+13                        -247.144597   \n",
       "\n",
       "    area_OGGM_2000_proj_W5E5_spinup  vol_OGGM_2000_proj_W5E5_spinup  \\\n",
       "01                     7.153719e+10                    1.419259e+13   \n",
       "02                     1.557368e+10                    1.015489e+12   \n",
       "03                     1.054534e+11                    2.750947e+13   \n",
       "04                     4.137927e+10                    8.730872e+12   \n",
       "05                     9.078936e+10                    1.548381e+13   \n",
       "06                     1.107997e+10                    3.789364e+12   \n",
       "07                     3.411341e+10                    7.538178e+12   \n",
       "08                     3.119956e+09                    3.081384e+11   \n",
       "09                     5.175822e+10                    1.396005e+13   \n",
       "10                     2.632842e+09                    1.335681e+11   \n",
       "11                     2.147616e+09                    1.275209e+11   \n",
       "12                     1.162905e+09                    6.126510e+10   \n",
       "13                     5.070921e+10                    3.306260e+12   \n",
       "14                     3.452543e+10                    2.880236e+12   \n",
       "15                     1.492774e+10                    8.862605e+11   \n",
       "16                     2.458289e+09                    9.301621e+10   \n",
       "17                     2.004910e+10                    2.336176e+12   \n",
       "18                     1.179882e+09                    6.872105e+10   \n",
       "19                     1.355425e+11                    4.532864e+13   \n",
       "\n",
       "    dmdt_geodetic_only_running_glaciers  dmdtda_geodetic_only_running_glaciers  \n",
       "01                           -48.012651                            -682.867030  \n",
       "02                            -7.552034                            -520.062346  \n",
       "03                           -30.564668                            -290.846673  \n",
       "04                           -26.501952                            -648.224633  \n",
       "05                           -35.513797                            -395.943637  \n",
       "06                            -9.360413                            -846.380030  \n",
       "07                           -10.539078                            -308.281779  \n",
       "08                            -1.666295                            -565.171709  \n",
       "09                           -10.422389                            -202.111130  \n",
       "10                            -1.209430                            -520.976144  \n",
       "11                            -1.683695                            -804.911322  \n",
       "12                            -0.673094                            -507.318818  \n",
       "13                            -9.630135                            -195.669760  \n",
       "14                            -4.561651                            -135.945961  \n",
       "15                            -6.893968                            -468.178425  \n",
       "16                            -0.934576                            -399.241599  \n",
       "17                            -8.878099                            -450.563247  \n",
       "18                            -0.644075                            -554.401058  \n",
       "19                           -20.836318                            -157.501651  \n",
       "\n",
       "[19 rows x 21 columns]"
      ]
     },
     "execution_count": 33,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dfh"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 91,
   "id": "88c53b61-7bda-417b-b0f9-e2c5b20e8cb6",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<div>\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>period</th>\n",
       "      <th>area</th>\n",
       "      <th>dmdtda</th>\n",
       "      <th>err_dmdtda</th>\n",
       "      <th>reg</th>\n",
       "      <th>is_cor</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>rgiid</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>RGI60-01.00001</th>\n",
       "      <td>2000-01-01_2020-01-01</td>\n",
       "      <td>360000.0</td>\n",
       "      <td>-0.012800</td>\n",
       "      <td>0.217600</td>\n",
       "      <td>1</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>RGI60-01.00002</th>\n",
       "      <td>2000-01-01_2020-01-01</td>\n",
       "      <td>558000.0</td>\n",
       "      <td>-0.229000</td>\n",
       "      <td>0.146000</td>\n",
       "      <td>1</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>RGI60-01.00003</th>\n",
       "      <td>2000-01-01_2020-01-01</td>\n",
       "      <td>1685000.0</td>\n",
       "      <td>-0.797900</td>\n",
       "      <td>0.166900</td>\n",
       "      <td>1</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>RGI60-01.00004</th>\n",
       "      <td>2000-01-01_2020-01-01</td>\n",
       "      <td>3681000.0</td>\n",
       "      <td>-0.407500</td>\n",
       "      <td>0.141600</td>\n",
       "      <td>1</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>RGI60-01.00005</th>\n",
       "      <td>2000-01-01_2020-01-01</td>\n",
       "      <td>2573000.0</td>\n",
       "      <td>0.039000</td>\n",
       "      <td>0.142000</td>\n",
       "      <td>1</td>\n",
       "      <td>False</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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>RGI60-19.02748</th>\n",
       "      <td>2000-01-01_2020-01-01</td>\n",
       "      <td>42000.0</td>\n",
       "      <td>-0.136311</td>\n",
       "      <td>0.295265</td>\n",
       "      <td>19</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>RGI60-19.02749</th>\n",
       "      <td>2000-01-01_2020-01-01</td>\n",
       "      <td>567000.0</td>\n",
       "      <td>-0.826800</td>\n",
       "      <td>0.448800</td>\n",
       "      <td>19</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>RGI60-19.02750</th>\n",
       "      <td>2000-01-01_2020-01-01</td>\n",
       "      <td>4118000.0</td>\n",
       "      <td>-0.411700</td>\n",
       "      <td>0.611200</td>\n",
       "      <td>19</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>RGI60-19.02751</th>\n",
       "      <td>2000-01-01_2020-01-01</td>\n",
       "      <td>11000.0</td>\n",
       "      <td>-0.136311</td>\n",
       "      <td>0.295265</td>\n",
       "      <td>19</td>\n",
       "      <td>True</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>RGI60-19.02752</th>\n",
       "      <td>2000-01-01_2020-01-01</td>\n",
       "      <td>528000.0</td>\n",
       "      <td>-0.038600</td>\n",
       "      <td>0.289700</td>\n",
       "      <td>19</td>\n",
       "      <td>False</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>215547 rows × 6 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "                               period       area    dmdtda  err_dmdtda  reg  \\\n",
       "rgiid                                                                         \n",
       "RGI60-01.00001  2000-01-01_2020-01-01   360000.0 -0.012800    0.217600    1   \n",
       "RGI60-01.00002  2000-01-01_2020-01-01   558000.0 -0.229000    0.146000    1   \n",
       "RGI60-01.00003  2000-01-01_2020-01-01  1685000.0 -0.797900    0.166900    1   \n",
       "RGI60-01.00004  2000-01-01_2020-01-01  3681000.0 -0.407500    0.141600    1   \n",
       "RGI60-01.00005  2000-01-01_2020-01-01  2573000.0  0.039000    0.142000    1   \n",
       "...                               ...        ...       ...         ...  ...   \n",
       "RGI60-19.02748  2000-01-01_2020-01-01    42000.0 -0.136311    0.295265   19   \n",
       "RGI60-19.02749  2000-01-01_2020-01-01   567000.0 -0.826800    0.448800   19   \n",
       "RGI60-19.02750  2000-01-01_2020-01-01  4118000.0 -0.411700    0.611200   19   \n",
       "RGI60-19.02751  2000-01-01_2020-01-01    11000.0 -0.136311    0.295265   19   \n",
       "RGI60-19.02752  2000-01-01_2020-01-01   528000.0 -0.038600    0.289700   19   \n",
       "\n",
       "                is_cor  \n",
       "rgiid                   \n",
       "RGI60-01.00001   False  \n",
       "RGI60-01.00002   False  \n",
       "RGI60-01.00003   False  \n",
       "RGI60-01.00004   False  \n",
       "RGI60-01.00005   False  \n",
       "...                ...  \n",
       "RGI60-19.02748    True  \n",
       "RGI60-19.02749   False  \n",
       "RGI60-19.02750   False  \n",
       "RGI60-19.02751    True  \n",
       "RGI60-19.02752   False  \n",
       "\n",
       "[215547 rows x 6 columns]"
      ]
     },
     "execution_count": 91,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd_geodetic"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "id": "e38cfe91-7506-42c1-9f48-5e43c8bf9c0f",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>area</th>\n",
       "      <th>dmdtda</th>\n",
       "      <th>err_dmdtda</th>\n",
       "      <th>is_cor</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>reg</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>7.031040e+10</td>\n",
       "      <td>-11392.595383</td>\n",
       "      <td>7004.929359</td>\n",
       "      <td>330</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1.452140e+10</td>\n",
       "      <td>-6408.731606</td>\n",
       "      <td>5252.528080</td>\n",
       "      <td>1488</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1.050886e+11</td>\n",
       "      <td>-1710.270166</td>\n",
       "      <td>671.791517</td>\n",
       "      <td>40</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>4.088390e+10</td>\n",
       "      <td>-3144.966749</td>\n",
       "      <td>1490.350682</td>\n",
       "      <td>39</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>8.969407e+10</td>\n",
       "      <td>-5459.371230</td>\n",
       "      <td>3899.777183</td>\n",
       "      <td>177</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>1.105935e+10</td>\n",
       "      <td>-191.571300</td>\n",
       "      <td>105.677100</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>3.418651e+10</td>\n",
       "      <td>-483.117626</td>\n",
       "      <td>238.644855</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>2.948299e+09</td>\n",
       "      <td>-1389.970401</td>\n",
       "      <td>870.950164</td>\n",
       "      <td>48</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>5.156762e+10</td>\n",
       "      <td>-313.633200</td>\n",
       "      <td>143.908800</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>2.321469e+09</td>\n",
       "      <td>-2056.945832</td>\n",
       "      <td>1756.963639</td>\n",
       "      <td>176</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>2.091777e+09</td>\n",
       "      <td>-2339.898779</td>\n",
       "      <td>1570.482648</td>\n",
       "      <td>570</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>1.326768e+09</td>\n",
       "      <td>-714.130208</td>\n",
       "      <td>452.447654</td>\n",
       "      <td>311</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>4.921626e+10</td>\n",
       "      <td>-11252.980441</td>\n",
       "      <td>13896.101259</td>\n",
       "      <td>989</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>3.355488e+10</td>\n",
       "      <td>-3111.328675</td>\n",
       "      <td>7184.219254</td>\n",
       "      <td>1072</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>1.472509e+10</td>\n",
       "      <td>-5715.962898</td>\n",
       "      <td>3613.493733</td>\n",
       "      <td>357</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>2.340879e+09</td>\n",
       "      <td>-952.107914</td>\n",
       "      <td>829.167329</td>\n",
       "      <td>222</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>1.970445e+10</td>\n",
       "      <td>-3490.407444</td>\n",
       "      <td>5002.623670</td>\n",
       "      <td>1467</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>1.161749e+09</td>\n",
       "      <td>-705.293923</td>\n",
       "      <td>1245.119869</td>\n",
       "      <td>550</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>1.322927e+11</td>\n",
       "      <td>-383.345191</td>\n",
       "      <td>660.002154</td>\n",
       "      <td>258</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "             area        dmdtda    err_dmdtda  is_cor\n",
       "reg                                                  \n",
       "1    7.031040e+10 -11392.595383   7004.929359     330\n",
       "2    1.452140e+10  -6408.731606   5252.528080    1488\n",
       "3    1.050886e+11  -1710.270166    671.791517      40\n",
       "4    4.088390e+10  -3144.966749   1490.350682      39\n",
       "5    8.969407e+10  -5459.371230   3899.777183     177\n",
       "6    1.105935e+10   -191.571300    105.677100       0\n",
       "7    3.418651e+10   -483.117626    238.644855       3\n",
       "8    2.948299e+09  -1389.970401    870.950164      48\n",
       "9    5.156762e+10   -313.633200    143.908800       0\n",
       "10   2.321469e+09  -2056.945832   1756.963639     176\n",
       "11   2.091777e+09  -2339.898779   1570.482648     570\n",
       "12   1.326768e+09   -714.130208    452.447654     311\n",
       "13   4.921626e+10 -11252.980441  13896.101259     989\n",
       "14   3.355488e+10  -3111.328675   7184.219254    1072\n",
       "15   1.472509e+10  -5715.962898   3613.493733     357\n",
       "16   2.340879e+09   -952.107914    829.167329     222\n",
       "17   1.970445e+10  -3490.407444   5002.623670    1467\n",
       "18   1.161749e+09   -705.293923   1245.119869     550\n",
       "19   1.322927e+11   -383.345191    660.002154     258"
      ]
     },
     "execution_count": 56,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd_geodetic_running.groupby('reg').sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "id": "d33bb1ae-3846-4a9f-95df-4785e751eb80",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "\n",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>area_OGGM_2000_W5E5</th>\n",
       "      <th>area_OGGM_2000_W5E5_spinup</th>\n",
       "      <th>area_OGGM_2000_proj_W5E5_spinup</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>01</th>\n",
       "      <td>7.031038e+10</td>\n",
       "      <td>7.153690e+10</td>\n",
       "      <td>7.153719e+10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>02</th>\n",
       "      <td>1.504163e+10</td>\n",
       "      <td>1.557374e+10</td>\n",
       "      <td>1.557368e+10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>03</th>\n",
       "      <td>1.050887e+11</td>\n",
       "      <td>1.054534e+11</td>\n",
       "      <td>1.054534e+11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>04</th>\n",
       "      <td>4.091611e+10</td>\n",
       "      <td>4.137931e+10</td>\n",
       "      <td>4.137927e+10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>05</th>\n",
       "      <td>8.969990e+10</td>\n",
       "      <td>9.078941e+10</td>\n",
       "      <td>9.078936e+10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>06</th>\n",
       "      <td>1.105934e+10</td>\n",
       "      <td>1.107997e+10</td>\n",
       "      <td>1.107997e+10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>07</th>\n",
       "      <td>3.397060e+10</td>\n",
       "      <td>3.411341e+10</td>\n",
       "      <td>3.411341e+10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>08</th>\n",
       "      <td>2.948294e+09</td>\n",
       "      <td>3.119956e+09</td>\n",
       "      <td>3.119956e+09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>09</th>\n",
       "      <td>5.156761e+10</td>\n",
       "      <td>5.175823e+10</td>\n",
       "      <td>5.175822e+10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>2.321455e+09</td>\n",
       "      <td>2.632843e+09</td>\n",
       "      <td>2.632842e+09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>2.091841e+09</td>\n",
       "      <td>2.147618e+09</td>\n",
       "      <td>2.147616e+09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>1.149040e+09</td>\n",
       "      <td>1.162906e+09</td>\n",
       "      <td>1.162905e+09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>4.921490e+10</td>\n",
       "      <td>5.070877e+10</td>\n",
       "      <td>5.070921e+10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>3.359802e+10</td>\n",
       "      <td>3.452558e+10</td>\n",
       "      <td>3.452543e+10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>1.472464e+10</td>\n",
       "      <td>1.492772e+10</td>\n",
       "      <td>1.492774e+10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>2.340964e+09</td>\n",
       "      <td>2.458291e+09</td>\n",
       "      <td>2.458289e+09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>1.970439e+10</td>\n",
       "      <td>2.004916e+10</td>\n",
       "      <td>2.004910e+10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>1.173936e+09</td>\n",
       "      <td>1.179882e+09</td>\n",
       "      <td>1.179882e+09</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>1.355254e+11</td>\n",
       "      <td>1.355425e+11</td>\n",
       "      <td>1.355425e+11</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    area_OGGM_2000_W5E5  area_OGGM_2000_W5E5_spinup  \\\n",
       "01         7.031038e+10                7.153690e+10   \n",
       "02         1.504163e+10                1.557374e+10   \n",
       "03         1.050887e+11                1.054534e+11   \n",
       "04         4.091611e+10                4.137931e+10   \n",
       "05         8.969990e+10                9.078941e+10   \n",
       "06         1.105934e+10                1.107997e+10   \n",
       "07         3.397060e+10                3.411341e+10   \n",
       "08         2.948294e+09                3.119956e+09   \n",
       "09         5.156761e+10                5.175823e+10   \n",
       "10         2.321455e+09                2.632843e+09   \n",
       "11         2.091841e+09                2.147618e+09   \n",
       "12         1.149040e+09                1.162906e+09   \n",
       "13         4.921490e+10                5.070877e+10   \n",
       "14         3.359802e+10                3.452558e+10   \n",
       "15         1.472464e+10                1.492772e+10   \n",
       "16         2.340964e+09                2.458291e+09   \n",
       "17         1.970439e+10                2.004916e+10   \n",
       "18         1.173936e+09                1.179882e+09   \n",
       "19         1.355254e+11                1.355425e+11   \n",
       "\n",
       "    area_OGGM_2000_proj_W5E5_spinup  \n",
       "01                     7.153719e+10  \n",
       "02                     1.557368e+10  \n",
       "03                     1.054534e+11  \n",
       "04                     4.137927e+10  \n",
       "05                     9.078936e+10  \n",
       "06                     1.107997e+10  \n",
       "07                     3.411341e+10  \n",
       "08                     3.119956e+09  \n",
       "09                     5.175822e+10  \n",
       "10                     2.632842e+09  \n",
       "11                     2.147616e+09  \n",
       "12                     1.162905e+09  \n",
       "13                     5.070921e+10  \n",
       "14                     3.452543e+10  \n",
       "15                     1.492774e+10  \n",
       "16                     2.458289e+09  \n",
       "17                     2.004910e+10  \n",
       "18                     1.179882e+09  \n",
       "19                     1.355425e+11  "
      ]
     },
     "execution_count": 53,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dfh[['area_OGGM_2000_W5E5', 'area_OGGM_2000_W5E5_spinup', 'area_OGGM_2000_proj_W5E5_spinup']]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "id": "d33282fc-3f56-4612-85a8-cacedb9db913",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>vol_OGGM_2000_W5E5</th>\n",
       "      <th>vol_OGGM_2000_W5E5_spinup</th>\n",
       "      <th>vol_OGGM_2000_proj_W5E5_spinup</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>01</th>\n",
       "      <td>1.407449e+13</td>\n",
       "      <td>1.419516e+13</td>\n",
       "      <td>1.419259e+13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>02</th>\n",
       "      <td>1.079413e+12</td>\n",
       "      <td>1.015611e+12</td>\n",
       "      <td>1.015489e+12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>03</th>\n",
       "      <td>2.832242e+13</td>\n",
       "      <td>2.750947e+13</td>\n",
       "      <td>2.750947e+13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>04</th>\n",
       "      <td>8.672269e+12</td>\n",
       "      <td>8.730939e+12</td>\n",
       "      <td>8.730872e+12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>05</th>\n",
       "      <td>1.576957e+13</td>\n",
       "      <td>1.547965e+13</td>\n",
       "      <td>1.548381e+13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>06</th>\n",
       "      <td>3.785219e+12</td>\n",
       "      <td>3.789366e+12</td>\n",
       "      <td>3.789364e+12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>07</th>\n",
       "      <td>7.565824e+12</td>\n",
       "      <td>7.544915e+12</td>\n",
       "      <td>7.538178e+12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>08</th>\n",
       "      <td>3.061147e+11</td>\n",
       "      <td>3.081740e+11</td>\n",
       "      <td>3.081384e+11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>09</th>\n",
       "      <td>1.468823e+13</td>\n",
       "      <td>1.396682e+13</td>\n",
       "      <td>1.396005e+13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>1.407462e+11</td>\n",
       "      <td>1.339931e+11</td>\n",
       "      <td>1.335681e+11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>1.328812e+11</td>\n",
       "      <td>1.275704e+11</td>\n",
       "      <td>1.275209e+11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>6.012630e+10</td>\n",
       "      <td>6.127591e+10</td>\n",
       "      <td>6.126510e+10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>3.310739e+12</td>\n",
       "      <td>3.307080e+12</td>\n",
       "      <td>3.306260e+12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>2.893355e+12</td>\n",
       "      <td>2.880364e+12</td>\n",
       "      <td>2.880236e+12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>9.025321e+11</td>\n",
       "      <td>8.861898e+11</td>\n",
       "      <td>8.862605e+11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>9.756558e+10</td>\n",
       "      <td>9.302077e+10</td>\n",
       "      <td>9.301621e+10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>2.438643e+12</td>\n",
       "      <td>2.336059e+12</td>\n",
       "      <td>2.336176e+12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>6.891251e+10</td>\n",
       "      <td>6.872100e+10</td>\n",
       "      <td>6.872105e+10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>4.590611e+13</td>\n",
       "      <td>4.533179e+13</td>\n",
       "      <td>4.532864e+13</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "    vol_OGGM_2000_W5E5  vol_OGGM_2000_W5E5_spinup  \\\n",
       "01        1.407449e+13               1.419516e+13   \n",
       "02        1.079413e+12               1.015611e+12   \n",
       "03        2.832242e+13               2.750947e+13   \n",
       "04        8.672269e+12               8.730939e+12   \n",
       "05        1.576957e+13               1.547965e+13   \n",
       "06        3.785219e+12               3.789366e+12   \n",
       "07        7.565824e+12               7.544915e+12   \n",
       "08        3.061147e+11               3.081740e+11   \n",
       "09        1.468823e+13               1.396682e+13   \n",
       "10        1.407462e+11               1.339931e+11   \n",
       "11        1.328812e+11               1.275704e+11   \n",
       "12        6.012630e+10               6.127591e+10   \n",
       "13        3.310739e+12               3.307080e+12   \n",
       "14        2.893355e+12               2.880364e+12   \n",
       "15        9.025321e+11               8.861898e+11   \n",
       "16        9.756558e+10               9.302077e+10   \n",
       "17        2.438643e+12               2.336059e+12   \n",
       "18        6.891251e+10               6.872100e+10   \n",
       "19        4.590611e+13               4.533179e+13   \n",
       "\n",
       "    vol_OGGM_2000_proj_W5E5_spinup  \n",
       "01                    1.419259e+13  \n",
       "02                    1.015489e+12  \n",
       "03                    2.750947e+13  \n",
       "04                    8.730872e+12  \n",
       "05                    1.548381e+13  \n",
       "06                    3.789364e+12  \n",
       "07                    7.538178e+12  \n",
       "08                    3.081384e+11  \n",
       "09                    1.396005e+13  \n",
       "10                    1.335681e+11  \n",
       "11                    1.275209e+11  \n",
       "12                    6.126510e+10  \n",
       "13                    3.306260e+12  \n",
       "14                    2.880236e+12  \n",
       "15                    8.862605e+11  \n",
       "16                    9.301621e+10  \n",
       "17                    2.336176e+12  \n",
       "18                    6.872105e+10  \n",
       "19                    4.532864e+13  "
      ]
     },
     "execution_count": 50,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dfh[['vol_OGGM_2000_W5E5', 'vol_OGGM_2000_W5E5_spinup', 'vol_OGGM_2000_proj_W5E5_spinup']]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "id": "6a87f2f5-4711-4907-b587-2bdd2408311d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(['01', '02', '03', '04', '05', '06', '07', '08', '09', '10', '11',\n",
       "       '12', '13', '14', '15', '16', '17', '18', '19'], dtype=object)"
      ]
     },
     "execution_count": 64,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dfh.index.values"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 70,
   "id": "48d5be71-8513-4d0c-b600-a4d8fdca30ab",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/tmp/ipykernel_2725909/2017426215.py:69: UserWarning: Tight layout not applied. tight_layout cannot make axes width small enough to accommodate all axes decorations\n",
      "  plt.tight_layout()\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 2600x2600 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(26,26))\n",
    "n=17\n",
    "\n",
    "ax = plt.subplot2grid((n, n), (0, 0), colspan=8, rowspan=8)\n",
    "\n",
    "#plt.figure(figsize=(20,10))\n",
    "#f, ax = plt.subplots()\n",
    "markers = {'W5E5': 'o', 'W5E5_spinup': 'x'}\n",
    "for opt in ['W5E5', 'W5E5_spinup']:\n",
    "        if opt=='W5E5_spinup':\n",
    "            #dfh.plot(ax=ax, y=f'dmdtda_OGGM_proj_{opt}', marker='s',\n",
    "            #                 linestyle='none', markersize=4, color = 'black', alpha = 1, #alphas[exp],\n",
    "            #                 label=f'W5E5 dynamical run using prepro {opt}')\n",
    "            dfh.plot(ax=ax, y=f'dmdtda_OGGM_{opt}', marker=markers[opt],\n",
    "                             linestyle='none', markersize=8, color = 'black', alpha = 1, #alphas[exp],\n",
    "                             label=f'{opt} (fixed_geometry)')\n",
    "\n",
    "        else:\n",
    "            dfh.plot(ax=ax, y=f'dmdtda_OGGM_{opt}', marker=markers[opt],\n",
    "                 linestyle='none', markersize=8, color = 'grey', alpha = 1, #alphas[exp],\n",
    "                 label=f'{opt} (fixed_geometry)')\n",
    "            \n",
    "dfh.plot(ax=ax, y='dmdtda', yerr='err_dmdtda', marker='s', linestyle='none', markersize=12,\n",
    "                   label = 'geodetic_observation_Hugonnet2021', color = 'orange', alpha = 0.5)\n",
    "dfh.plot(ax=ax, y='dmdtda_geodetic_only_running_glaciers',  marker=\"_\", linestyle='none', markersize=30,\n",
    "                   label = 'geodetic observation only common running glaciers', color = 'violet', alpha = 1, markeredgewidth=5)\n",
    "plt.ylabel(r'area-weighted specific mass balance (dmdtda, kg m$^{-2}$ year$^{-1}$)')\n",
    "plt.title(r'fixed-geometry:')\n",
    "plt.xlabel('RGI region')\n",
    "plt.xticks(np.arange(0,19,1), dfh.index.values)\n",
    "#f = ax.get_legend()\n",
    "#f.remove()\n",
    "plt.ylim([-1400,-50])\n",
    "\n",
    "\n",
    "\n",
    "\n",
    "ax = plt.subplot2grid((n, n), (0, 9), colspan=8, rowspan=8)\n",
    "\n",
    "#f, ax = plt.subplots()\n",
    "#alphas = {'elev_bands': 1, 'centerlines':0.5}\n",
    "markers = {'W5E5': 'o', 'W5E5_spinup': 'x'}\n",
    "for opt in ['W5E5', 'W5E5_spinup']:\n",
    "        if opt=='W5E5_spinup':\n",
    "            dfh.plot(ax=ax, y=f'dmdtda_dyna_OGGM_proj_{opt}', marker='s',\n",
    "                             linestyle='none', markersize=4, color = 'black', alpha = 1, #alphas[exp],\n",
    "                             label=f'W5E5 dynamical run using prepro {opt}')\n",
    "            dfh.plot(ax=ax, y=f'dmdtda_dyna_OGGM_{opt}', marker=markers[opt],\n",
    "                             linestyle='none', markersize=8, color = 'black', alpha = 1, #alphas[exp],\n",
    "                             label=f'{opt} (spinup_historical_run_output)')\n",
    "\n",
    "        else:\n",
    "            dfh.plot(ax=ax, y=f'dmdtda_dyna_OGGM_{opt}', marker=markers[opt],\n",
    "                 linestyle='none', markersize=8, color = 'grey', alpha = 1, #alphas[exp],\n",
    "                 label=f'{opt} (historical_run_output_extended)')\n",
    "\n",
    "dfh.plot(ax=ax, y='dmdtda', yerr='err_dmdtda', marker='s', linestyle='none', markersize=12,\n",
    "                   label = 'geodetic observation (Hugonnet et al., 2021): all glaciers', color = 'orange', alpha = 0.5)\n",
    "dfh.plot(ax=ax, y='dmdtda_geodetic_only_running_glaciers', marker=\"_\", linestyle='none', markersize=30,\n",
    "                   label = 'geodetic observation (only common running glaciers)', color = 'violet', alpha = 1, markeredgewidth=5)\n",
    "plt.ylabel(r'dynamic specific mass balance (dmdtda, kg m$^{-2}$ year$^{-1}$, area-weighted)')\n",
    "plt.xlabel('RGI region')\n",
    "plt.title('dynamic specific mass balance (modelled volume changes vs Hugonnet)') # from \"spinup/historical_run_output_extended\"\n",
    "plt.xticks(np.arange(0,19,1), dfh.index.values);\n",
    "plt.ylim([-1400,-50])\n",
    "ax.legend(framealpha=0.5, ncol=1, loc='lower right', \n",
    "          title=f'mean of 2000-2020: border {border} (only glaciers that are\\nrunning for all preprocessed gdirs used, i.e. {100*pd_geodetic_running.area.sum()/pd_geodetic.area.sum():0.1f}% of glacier area)')\n",
    "\n",
    "plt.tight_layout()\n"
   ]
  },
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   "execution_count": 71,
   "id": "a012057b-3595-4932-85b5-21b72bc4e7ff",
   "metadata": {},
   "outputs": [
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       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt;\n",
       "Dimensions:         (time: 42)\n",
       "Coordinates:\n",
       "  * time            (time) float64 1.979e+03 1.98e+03 ... 2.019e+03 2.02e+03\n",
       "    hydro_year      (time) int64 1979 1980 1981 1982 ... 2017 2018 2019 2020\n",
       "    hydro_month     (time) int64 10 10 10 10 10 10 10 ... 10 10 10 10 10 10 10\n",
       "    calendar_year   (time) int64 1979 1980 1981 1982 ... 2017 2018 2019 2020\n",
       "    calendar_month  (time) int64 1 1 1 1 1 1 1 1 1 1 1 ... 1 1 1 1 1 1 1 1 1 1 1\n",
       "Data variables:\n",
       "    volume          (time) float32 4.567e+13 4.567e+13 ... 4.459e+13 4.457e+13\n",
       "    area            (time) float32 1.327e+11 1.337e+11 ... 1.344e+11 1.344e+11</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-1bca1069-819c-4239-8136-c7af5c684347' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-1bca1069-819c-4239-8136-c7af5c684347' 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>: 42</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-06bc7f9d-d0e2-4c57-8728-f75afcc8b55d' class='xr-section-summary-in' type='checkbox'  checked><label for='section-06bc7f9d-d0e2-4c57-8728-f75afcc8b55d' class='xr-section-summary' >Coordinates: <span>(5)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>1.979e+03 1.98e+03 ... 2.02e+03</div><input id='attrs-dbefc993-0748-4ebe-90c1-2eb55b7a9c44' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-dbefc993-0748-4ebe-90c1-2eb55b7a9c44' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-cd61be68-9a59-4901-9d25-8830f95a3ffa' class='xr-var-data-in' type='checkbox'><label for='data-cd61be68-9a59-4901-9d25-8830f95a3ffa' 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>description :</span></dt><dd>Floating year</dd></dl></div><div class='xr-var-data'><pre>array([1979., 1980., 1981., 1982., 1983., 1984., 1985., 1986., 1987., 1988.,\n",
       "       1989., 1990., 1991., 1992., 1993., 1994., 1995., 1996., 1997., 1998.,\n",
       "       1999., 2000., 2001., 2002., 2003., 2004., 2005., 2006., 2007., 2008.,\n",
       "       2009., 2010., 2011., 2012., 2013., 2014., 2015., 2016., 2017., 2018.,\n",
       "       2019., 2020.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>hydro_year</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-2dfd5dae-abd3-464d-be39-bacda8d2cba9' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-2dfd5dae-abd3-464d-be39-bacda8d2cba9' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-63cfe779-032e-4dc1-b70d-615f0eced236' class='xr-var-data-in' type='checkbox'><label for='data-63cfe779-032e-4dc1-b70d-615f0eced236' 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>description :</span></dt><dd>Hydrological year</dd></dl></div><div class='xr-var-data'><pre>array([1979, 1980, 1981, 1982, 1983, 1984, 1985, 1986, 1987, 1988, 1989, 1990,\n",
       "       1991, 1992, 1993, 1994, 1995, 1996, 1997, 1998, 1999, 2000, 2001, 2002,\n",
       "       2003, 2004, 2005, 2006, 2007, 2008, 2009, 2010, 2011, 2012, 2013, 2014,\n",
       "       2015, 2016, 2017, 2018, 2019, 2020])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>hydro_month</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-a4acf23a-850c-4e54-8080-d0d913ee74f2' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a4acf23a-850c-4e54-8080-d0d913ee74f2' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c96204ef-74bf-4766-ad29-33679db41f7a' class='xr-var-data-in' type='checkbox'><label for='data-c96204ef-74bf-4766-ad29-33679db41f7a' 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>description :</span></dt><dd>Hydrological month</dd></dl></div><div class='xr-var-data'><pre>array([10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10,\n",
       "       10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10,\n",
       "       10, 10, 10, 10, 10, 10])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>calendar_year</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-2d49a6df-0119-47e5-831c-639065f113e7' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-2d49a6df-0119-47e5-831c-639065f113e7' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b62277c4-e927-4f92-9a27-f4273a2deb3b' class='xr-var-data-in' type='checkbox'><label for='data-b62277c4-e927-4f92-9a27-f4273a2deb3b' 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>description :</span></dt><dd>Calendar year</dd></dl></div><div class='xr-var-data'><pre>array([1979, 1980, 1981, 1982, 1983, 1984, 1985, 1986, 1987, 1988, 1989, 1990,\n",
       "       1991, 1992, 1993, 1994, 1995, 1996, 1997, 1998, 1999, 2000, 2001, 2002,\n",
       "       2003, 2004, 2005, 2006, 2007, 2008, 2009, 2010, 2011, 2012, 2013, 2014,\n",
       "       2015, 2016, 2017, 2018, 2019, 2020])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>calendar_month</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-b20e5cac-f218-4a70-9c58-f1530409252b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b20e5cac-f218-4a70-9c58-f1530409252b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9b0d7b6f-9f06-4809-8b86-7c55949aadda' class='xr-var-data-in' type='checkbox'><label for='data-9b0d7b6f-9f06-4809-8b86-7c55949aadda' 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>description :</span></dt><dd>Calendar month</dd></dl></div><div class='xr-var-data'><pre>array([1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,\n",
       "       1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-3bf99549-cde8-416b-9c2b-1a50b35d5885' class='xr-section-summary-in' type='checkbox'  checked><label for='section-3bf99549-cde8-416b-9c2b-1a50b35d5885' class='xr-section-summary' >Data variables: <span>(2)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>volume</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>4.567e+13 4.567e+13 ... 4.457e+13</div><input id='attrs-655e3ca6-6f49-4145-8aff-68fbf78a7991' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-655e3ca6-6f49-4145-8aff-68fbf78a7991' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-375abd6c-461a-4914-bf50-69b85030d189' class='xr-var-data-in' type='checkbox'><label for='data-375abd6c-461a-4914-bf50-69b85030d189' 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([4.5667091e+13, 4.5665921e+13, 4.5641615e+13, 4.5721026e+13,\n",
       "       4.5768723e+13, 4.5859929e+13, 4.5888014e+13, 4.5902031e+13,\n",
       "       4.5971069e+13, 4.5976933e+13, 4.5965147e+13, 4.5898973e+13,\n",
       "       4.5799132e+13, 4.5791025e+13, 4.5762633e+13, 4.5720858e+13,\n",
       "       4.5669679e+13, 4.5590067e+13, 4.5548766e+13, 4.5503559e+13,\n",
       "       4.5425046e+13, 4.5331786e+13, 4.5324748e+13, 4.5318666e+13,\n",
       "       4.5197665e+13, 4.5161749e+13, 4.5133702e+13, 4.5162294e+13,\n",
       "       4.5061912e+13, 4.5005352e+13, 4.4985102e+13, 4.4899236e+13,\n",
       "       4.4872149e+13, 4.4805158e+13, 4.4810627e+13, 4.4710123e+13,\n",
       "       4.4793313e+13, 4.4762082e+13, 4.4772786e+13, 4.4629970e+13,\n",
       "       4.4590300e+13, 4.4572311e+13], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>area</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>1.327e+11 1.337e+11 ... 1.344e+11</div><input id='attrs-fedeb004-eb57-469c-8c83-62ec3411841a' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-fedeb004-eb57-469c-8c83-62ec3411841a' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-08c87ada-b710-4090-9967-9a2a5b5dee9b' class='xr-var-data-in' type='checkbox'><label for='data-08c87ada-b710-4090-9967-9a2a5b5dee9b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([1.32744987e+11, 1.33694439e+11, 1.33952889e+11, 1.34262997e+11,\n",
       "       1.34655934e+11, 1.34620774e+11, 1.34386008e+11, 1.34319776e+11,\n",
       "       1.35220871e+11, 1.34999507e+11, 1.34718939e+11, 1.34727148e+11,\n",
       "       1.34740394e+11, 1.35174259e+11, 1.35094346e+11, 1.35539261e+11,\n",
       "       1.35418741e+11, 1.35143449e+11, 1.34965666e+11, 1.34962045e+11,\n",
       "       1.35584293e+11, 1.35542514e+11, 1.35699530e+11, 1.35900635e+11,\n",
       "       1.35356277e+11, 1.35475356e+11, 1.35258964e+11, 1.35114498e+11,\n",
       "       1.34976446e+11, 1.35001915e+11, 1.34913294e+11, 1.34737617e+11,\n",
       "       1.34649045e+11, 1.34777586e+11, 1.35317905e+11, 1.34738379e+11,\n",
       "       1.35294665e+11, 1.34721446e+11, 1.34349234e+11, 1.34530212e+11,\n",
       "       1.34431457e+11, 1.34438863e+11], dtype=float32)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-5f08f436-ee4c-4d02-b210-a2f7e161f46f' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-5f08f436-ee4c-4d02-b210-a2f7e161f46f' class='xr-section-summary'  title='Expand/collapse section'>Attributes: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.Dataset>\n",
       "Dimensions:         (time: 42)\n",
       "Coordinates:\n",
       "  * time            (time) float64 1.979e+03 1.98e+03 ... 2.019e+03 2.02e+03\n",
       "    hydro_year      (time) int64 ...\n",
       "    hydro_month     (time) int64 ...\n",
       "    calendar_year   (time) int64 ...\n",
       "    calendar_month  (time) int64 ...\n",
       "Data variables:\n",
       "    volume          (time) float32 4.567e+13 4.567e+13 ... 4.459e+13 4.457e+13\n",
       "    area            (time) float32 1.327e+11 1.337e+11 ... 1.344e+11 1.344e+11"
      ]
     },
     "execution_count": 71,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ds"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "41b981a2-cf44-48f1-bdac-2687da339a32",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "f1a4b1bc-587c-4a60-92ca-2b585f3d173a",
   "metadata": {},
   "outputs": [],
   "source": [
    "border = 160\n",
    "qc = 'qc3'\n",
    "\n",
    "plt.figure(figsize=(26,26))\n",
    "n=17\n",
    "dfh = pd.read_csv('dmdtda_dmdt_for_prepro_level_5_gdirs_new.csv', index_col=[0])\n",
    "dfh.index = ['{:02d}'.format(int(rgi_reg)) for rgi_reg in dfh.index]\n",
    "dfh['dmdt_geodetic_only_running_glaciers'] = pd_working_glaciers_geod.T['dmdt_geodetic_only_running_glaciers'].values\n",
    "dfh['dmdtda_geodetic_only_running_glaciers'] = pd_working_glaciers_geod.T['dmdtda_geodetic_only_running_glaciers'].values\n",
    "###\n",
    "###\n",
    "ax = plt.subplot2grid((n, n), (0, 0), colspan=8, rowspan=8)\n",
    "\n",
    "#plt.figure(figsize=(20,10))\n",
    "ax = plt.gca()\n",
    "#f, ax = plt.subplots()\n",
    "alphas = {'elev_bands': 1, 'centerlines':0.5}\n",
    "markers = {'ERA5': 'o', 'CRU': 'x'}\n",
    "for exp in ['centerlines', 'elev_bands']:\n",
    "    for match in ['no_match', 'match_geod']: #, 'match_geod_pergla', 'match_geod_pergla_massredis']:  # \n",
    "        for pcp, clim in zip(pcps, clims):\n",
    "            try:\n",
    "                dict_key_short = f'{exp}_{pcp}_{clim}_{match}_{qc}_b{border}' #_rgi_{rgi_reg}'\n",
    "                dfh.plot(ax=ax, y=f'dmdt_OGGM_{dict_key_short}', marker=markers[clim],\n",
    "                         linestyle='none', markersize=8, color = colors[match], alpha = alphas[exp],\n",
    "                         label=f'{exp}_{clim}_{pcp}_{match}')\n",
    "            except:\n",
    "                pass\n",
    "dfh.plot(ax=ax, y='dmdt', yerr='err_dmdt', marker='s', linestyle='none', markersize=12,\n",
    "                   label = 'geodetic_observation_Hugonnet2021', color = 'orange', alpha = 0.5)\n",
    "dfh.plot(ax=ax, y='dmdt_geodetic_only_running_glaciers',  marker=\"_\", linestyle='none', markersize=30,\n",
    "                   label = 'geodetic observation only common running glaciers', color = 'violet', alpha = 1, markeredgewidth=5)\n",
    "plt.ylabel(r'regional total mass change (dmdt, Gt year$^{-1}$)')\n",
    "plt.xlabel('RGI region')\n",
    "plt.xticks(np.arange(0,18,1), dfh.index.values)\n",
    "f = ax.get_legend()\n",
    "f.remove()\n",
    "###\n",
    "ax = plt.subplot2grid((n, n), (9, 0), colspan=8, rowspan=8)\n",
    "#f, ax = plt.subplots()\n",
    "alphas = {'elev_bands': 1, 'centerlines':0.5}\n",
    "markers = {'ERA5': 'o', 'CRU': 'x'}\n",
    "dfh.plot(ax=ax, y='dmdtda', yerr='err_dmdtda', marker='s', linestyle='none', markersize=12, linewidth=4,\n",
    "                   label = 'geodetic observation (Hugonnet et al., 2021)', color = 'orange', alpha = 0.7)\n",
    "for exp in ['centerlines', 'elev_bands']:\n",
    "    for match in ['no_match', 'match_geod']: #, 'match_geod_pergla', 'match_geod_pergla_massredis']:  # \n",
    "        for pcp, clim in zip(pcps, clims):\n",
    "            try:\n",
    "                dict_key_short = f'{exp}_{pcp}_{clim}_{match}_{qc}_b{border}' #_rgi_{rgi_reg}'\n",
    "                dfh.plot(ax=ax, y=f'dmdtda_OGGM_{dict_key_short}', marker=markers[clim],\n",
    "                         linestyle='none', markersize=8, color = colors[match], alpha = alphas[exp],\n",
    "                         label=f'{exp}_{clim}_{pcp}_{match}')\n",
    "            except:\n",
    "                pass\n",
    "#t=ax.get_legend_handles_labels()\n",
    "#t[0] = [t[0][-1]].append(t[:-1])\n",
    "\n",
    "dfh.plot(ax=ax, y='dmdtda_geodetic_only_running_glaciers',  marker=\"_\", linestyle='none', markersize=30,\n",
    "                   label = 'geodetic observation only common running glaciers', color = 'violet', alpha = 1, markeredgewidth=5)\n",
    "plt.ylabel(r'area-weighted specific mass balance (dmdtda, kg m$^{-2}$ year$^{-1}$)')\n",
    "plt.xlabel('RGI region')\n",
    "plt.xticks(np.arange(0, 18, 1), dfh.index.values)\n",
    "f = ax.get_legend()\n",
    "f.remove()\n",
    "plt.title('area-weighted mean MB from \"fixed_geometry_mass_balance\"')\n",
    "\n",
    "\n",
    "##\n",
    "#plt.figure(figsize=(20,10))\n",
    "ax = plt.subplot2grid((n, n), (9, 9), colspan=8, rowspan=8)\n",
    "\n",
    "#f, ax = plt.subplots()\n",
    "alphas = {'elev_bands': 1, 'centerlines':0.5}\n",
    "markers = {'ERA5': 'o', 'CRU': 'x'}\n",
    "bu=[]\n",
    "for exp in ['centerlines', 'elev_bands']:\n",
    "    for match in ['no_match', 'match_geod']: #, 'match_geod_pergla', 'match_geod_pergla_massredis']:  # \n",
    "        for pcp, clim in zip(pcps, clims):\n",
    "            try:\n",
    "                dict_key_short = f'{exp}_{pcp}_{clim}_{match}_{qc}_b{border}' #_rgi_{rgi_reg}'\n",
    "                dfh.plot(ax=ax, y=f'dmdtda_dyna_OGGM_{dict_key_short}', marker=markers[clim],\n",
    "                         linestyle='none', markersize=8, color = colors[match], alpha = alphas[exp],\n",
    "                         label=f'{exp}_{clim}_{pcp}_{match}')\n",
    "            except:\n",
    "                pass\n",
    "dfh.plot(ax=ax, y='dmdtda', yerr='err_dmdtda', marker='s', linestyle='none', markersize=12,\n",
    "                   label = 'geodetic observation (Hugonnet et al., 2021)', color = 'orange', alpha = 0.7)\n",
    "dfh.plot(ax=ax, y='dmdtda_geodetic_only_running_glaciers',  marker=\"_\", linestyle='none', markersize=30,\n",
    "                   label = 'geodetic observation (only common running glaciers)', color = 'violet', alpha = 1, markeredgewidth=5)\n",
    "plt.ylabel(r'dynamic specific mass balance (dmdtda, kg m$^{-2}$ year$^{-1}$)')\n",
    "plt.xlabel('RGI region')\n",
    "plt.title('using volume changes from \"historical_run_output_extended\"')\n",
    "plt.xticks(np.arange(0,18,1), dfh.index.values);\n",
    "plt.ylim([-1600,-50])\n",
    "ax.legend(framealpha=0.5, ncol=1, loc=3, bbox_to_anchor=(0.17,1.3),\n",
    "          title=f'mean of 2000-2020: {qc}, border {border} (only glaciers that are\\nrunning for all preprocessed gdirs used, i.e. {len(all_running_rgis)*100/len(pd_working):0.1f}%)')\n",
    "\n",
    "#ax.legend()\n",
    "######\n",
    "#plt.tight_layout()\n",
    "\n",
    "ax = plt.subplot2grid((n, n), (1, 9), rowspan=6, colspan=1)\n",
    "rgi_index = ['{:02d}'.format(int(rgi_reg)) for rgi_reg in np.arange(1,20)]\n",
    "dfh.loc['all', 'dmdt'] = dfh.loc[rgi_index].dmdt.sum()\n",
    "dfh.loc['all', 'err_dmdt'] = dfh.loc[rgi_index].err_dmdt.sum()\n",
    "\n",
    "dfh.loc['all', 'period'] = dfh.period[0]\n",
    "for exp in ['elev_bands', 'centerlines']:\n",
    "        for match in ['no_match', 'match_geod']: #, 'match_geod_pergla', 'match_geod_pergla_massredis']:  \n",
    "            for pcp, clim in zip(pcps, clims):\n",
    "                try:\n",
    "                    dict_key_short = f'{exp}_{pcp}_{clim}_{match}_{qc}_b{border}'\n",
    "                    dfh.loc['all', f'dmdt_OGGM_{opt}'] = dfh.loc[rgi_index, f'dmdt_OGGM_{opt}'].sum()\n",
    "                except:\n",
    "                    pass\n",
    "###\n",
    "#plt.figure(figsize=(3,6))\n",
    "ax = plt.gca()\n",
    "#ax.errorbar(['geodetic observation (Hugonnet et al., 2021)'],\n",
    "#            df_dmdt_all.dmdt, yerr=df_dmdt_all.err_dmdt,\n",
    "#            marker='s', color='orange', alpha=0.8)\n",
    "\n",
    "df_dmdt_all = dfh.loc['all_without_19'][1:].dropna()\n",
    "plt.axhline(df_dmdt_all.dmdt, color='orange', alpha = 0.3)\n",
    "plt.axhspan(df_dmdt_all.dmdt-df_dmdt_all.err_dmdt,\n",
    "            df_dmdt_all.dmdt + df_dmdt_all.err_dmdt, alpha = 0.1, color='orange')\n",
    "\n",
    "#dmdtda_working_glaciers_geods['all_without_19'] = np.average(pd_geodetic_running.dmdtda, weights=pd_geodetic_running.area)*1e3\n",
    "plt.axhline((pd_geodetic_running.dmdtda*1e3*pd_geodetic_running.area).sum()*1e-12,\n",
    "            color='violet', alpha=0.5, linewidth=5)\n",
    "for exp in ['centerlines', 'elev_bands']:\n",
    "    for match in ['no_match', 'match_geod']: #, 'match_geod_pergla', 'match_geod_pergla_massredis']:  # \n",
    "        for pcp, clim in zip(pcps, clims):\n",
    "            try:\n",
    "                dict_key_short = f'{exp}_{pcp}_{clim}_{match}_{qc}_b{border}' #_rgi_{rgi_reg}'\n",
    "                ax.errorbar(x=[f'{exp}_{clim}_{pcp}_{match}'], # [0]\n",
    "                            y=df_dmdt_all[f'dmdt_OGGM_{dict_key_short}'],\n",
    "                            marker=markers[clim],\n",
    "                            linestyle='none', markersize=8, color=colors[match], alpha=alphas[exp],\n",
    "                            label=f'{exp}_{clim}_{pcp}_{match}')\n",
    "            except:\n",
    "                pass\n",
    "plt.ylabel(r'world-wide total mass-change (dmdt, Gt year$^{-1}$)')\n",
    "plt.xticks(ticks=[3.5],labels=['all without RGI 19'])\n",
    "plt.xlim([-1,9.5])\n",
    "plt.grid(axis='x')\n",
    "\n",
    "plt.savefig(f'dmdtda_dmdt_for_prepro_level_gdirs_{qc}_b{border}.png', bbox_inches='tight', pad_inches=0)\n",
    "plt.savefig(f'dmdtda_dmdt_for_prepro_level_gdirs_{qc}_b{border}.pdf', bbox_inches='tight', pad_inches=0.2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "2a7dea5c-b09e-4928-bf06-3bff52940806",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "a26cc726-8608-458a-bf67-cb35a2364470",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 84,
   "id": "44fc50eb-0312-47cf-b2a0-9d53048c98f3",
   "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>period</th>\n",
       "      <th>dmdt</th>\n",
       "      <th>err_dmdt</th>\n",
       "      <th>dmdtda</th>\n",
       "      <th>err_dmdtda</th>\n",
       "      <th>dmdtda_OGGM_W5E5</th>\n",
       "      <th>dmdtda_dyna_OGGM_W5E5</th>\n",
       "      <th>area_OGGM_2000_W5E5</th>\n",
       "      <th>vol_OGGM_2000_W5E5</th>\n",
       "      <th>dmdtda_OGGM_W5E5_spinup</th>\n",
       "      <th>dmdtda_dyna_OGGM_W5E5_spinup</th>\n",
       "      <th>area_OGGM_2000_W5E5_spinup</th>\n",
       "      <th>vol_OGGM_2000_W5E5_spinup</th>\n",
       "      <th>dmdt_geodetic_only_running_glaciers</th>\n",
       "      <th>dmdtda_geodetic_only_running_glaciers</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>01</th>\n",
       "      <td>2000-01-01_2020-01-01</td>\n",
       "      <td>-66.61</td>\n",
       "      <td>5.43</td>\n",
       "      <td>-773.79</td>\n",
       "      <td>63.56</td>\n",
       "      <td>-682.867030</td>\n",
       "      <td>-678.438420</td>\n",
       "      <td>8.671674e+10</td>\n",
       "      <td>1.946116e+13</td>\n",
       "      <td>-682.867030</td>\n",
       "      <td>-678.438420</td>\n",
       "      <td>8.671674e+10</td>\n",
       "      <td>1.946116e+13</td>\n",
       "      <td>-48.012651</td>\n",
       "      <td>-682.867030</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>02</th>\n",
       "      <td>2000-01-01_2020-01-01</td>\n",
       "      <td>-7.56</td>\n",
       "      <td>0.85</td>\n",
       "      <td>-529.43</td>\n",
       "      <td>59.52</td>\n",
       "      <td>-520.062346</td>\n",
       "      <td>-458.972311</td>\n",
       "      <td>1.504937e+10</td>\n",
       "      <td>1.079486e+12</td>\n",
       "      <td>-520.062346</td>\n",
       "      <td>-458.972311</td>\n",
       "      <td>1.504937e+10</td>\n",
       "      <td>1.079486e+12</td>\n",
       "      <td>-7.552034</td>\n",
       "      <td>-520.062346</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>03</th>\n",
       "      <td>2000-01-01_2020-01-01</td>\n",
       "      <td>-30.54</td>\n",
       "      <td>2.42</td>\n",
       "      <td>-292.74</td>\n",
       "      <td>23.41</td>\n",
       "      <td>-290.846673</td>\n",
       "      <td>-313.764167</td>\n",
       "      <td>1.051061e+11</td>\n",
       "      <td>2.832337e+13</td>\n",
       "      <td>-290.846673</td>\n",
       "      <td>-313.764167</td>\n",
       "      <td>1.051061e+11</td>\n",
       "      <td>2.832337e+13</td>\n",
       "      <td>-30.564668</td>\n",
       "      <td>-290.846673</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>04</th>\n",
       "      <td>2000-01-01_2020-01-01</td>\n",
       "      <td>-26.48</td>\n",
       "      <td>2.13</td>\n",
       "      <td>-652.65</td>\n",
       "      <td>52.90</td>\n",
       "      <td>-648.224633</td>\n",
       "      <td>-616.008782</td>\n",
       "      <td>4.091842e+10</td>\n",
       "      <td>8.672361e+12</td>\n",
       "      <td>-648.224633</td>\n",
       "      <td>-616.008782</td>\n",
       "      <td>4.091842e+10</td>\n",
       "      <td>8.672361e+12</td>\n",
       "      <td>-26.501952</td>\n",
       "      <td>-648.224633</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>05</th>\n",
       "      <td>2000-01-01_2020-01-01</td>\n",
       "      <td>-35.49</td>\n",
       "      <td>2.89</td>\n",
       "      <td>-427.09</td>\n",
       "      <td>35.03</td>\n",
       "      <td>-395.943637</td>\n",
       "      <td>-365.575862</td>\n",
       "      <td>8.972035e+10</td>\n",
       "      <td>1.577052e+13</td>\n",
       "      <td>-395.943637</td>\n",
       "      <td>-365.575862</td>\n",
       "      <td>8.972035e+10</td>\n",
       "      <td>1.577052e+13</td>\n",
       "      <td>-35.513797</td>\n",
       "      <td>-395.943637</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>06</th>\n",
       "      <td>2000-01-01_2020-01-01</td>\n",
       "      <td>-9.36</td>\n",
       "      <td>0.70</td>\n",
       "      <td>-877.49</td>\n",
       "      <td>66.59</td>\n",
       "      <td>-846.380030</td>\n",
       "      <td>-785.780554</td>\n",
       "      <td>1.105953e+10</td>\n",
       "      <td>3.785239e+12</td>\n",
       "      <td>-846.380030</td>\n",
       "      <td>-785.780554</td>\n",
       "      <td>1.105953e+10</td>\n",
       "      <td>3.785239e+12</td>\n",
       "      <td>-9.360413</td>\n",
       "      <td>-846.380030</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>07</th>\n",
       "      <td>2000-01-01_2020-01-01</td>\n",
       "      <td>-10.53</td>\n",
       "      <td>0.85</td>\n",
       "      <td>-312.12</td>\n",
       "      <td>25.27</td>\n",
       "      <td>-303.312236</td>\n",
       "      <td>-277.919769</td>\n",
       "      <td>3.397128e+10</td>\n",
       "      <td>7.565840e+12</td>\n",
       "      <td>-303.312236</td>\n",
       "      <td>-277.919769</td>\n",
       "      <td>3.397128e+10</td>\n",
       "      <td>7.565840e+12</td>\n",
       "      <td>-10.539078</td>\n",
       "      <td>-308.281779</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>08</th>\n",
       "      <td>2000-01-01_2020-01-01</td>\n",
       "      <td>-1.67</td>\n",
       "      <td>0.18</td>\n",
       "      <td>-577.56</td>\n",
       "      <td>62.94</td>\n",
       "      <td>-565.171709</td>\n",
       "      <td>-537.845993</td>\n",
       "      <td>2.948529e+09</td>\n",
       "      <td>3.061212e+11</td>\n",
       "      <td>-565.171709</td>\n",
       "      <td>-537.845993</td>\n",
       "      <td>2.948529e+09</td>\n",
       "      <td>3.061212e+11</td>\n",
       "      <td>-1.666295</td>\n",
       "      <td>-565.171709</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>09</th>\n",
       "      <td>2000-01-01_2020-01-01</td>\n",
       "      <td>-10.40</td>\n",
       "      <td>0.94</td>\n",
       "      <td>-202.92</td>\n",
       "      <td>18.47</td>\n",
       "      <td>-202.111130</td>\n",
       "      <td>-216.460018</td>\n",
       "      <td>5.157186e+10</td>\n",
       "      <td>1.468843e+13</td>\n",
       "      <td>-202.111130</td>\n",
       "      <td>-216.460018</td>\n",
       "      <td>5.157186e+10</td>\n",
       "      <td>1.468843e+13</td>\n",
       "      <td>-10.422389</td>\n",
       "      <td>-202.111130</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>2000-01-01_2020-01-01</td>\n",
       "      <td>-1.22</td>\n",
       "      <td>0.18</td>\n",
       "      <td>-503.76</td>\n",
       "      <td>73.45</td>\n",
       "      <td>-520.976144</td>\n",
       "      <td>-497.623844</td>\n",
       "      <td>2.323438e+09</td>\n",
       "      <td>1.407830e+11</td>\n",
       "      <td>-520.976144</td>\n",
       "      <td>-497.623844</td>\n",
       "      <td>2.323438e+09</td>\n",
       "      <td>1.407830e+11</td>\n",
       "      <td>-1.209430</td>\n",
       "      <td>-520.976144</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>2000-01-01_2020-01-01</td>\n",
       "      <td>-1.69</td>\n",
       "      <td>0.21</td>\n",
       "      <td>-863.75</td>\n",
       "      <td>107.67</td>\n",
       "      <td>-804.911322</td>\n",
       "      <td>-735.500422</td>\n",
       "      <td>2.091911e+09</td>\n",
       "      <td>1.328835e+11</td>\n",
       "      <td>-804.911322</td>\n",
       "      <td>-735.500422</td>\n",
       "      <td>2.091911e+09</td>\n",
       "      <td>1.328835e+11</td>\n",
       "      <td>-1.683695</td>\n",
       "      <td>-804.911322</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>2000-01-01_2020-01-01</td>\n",
       "      <td>-0.67</td>\n",
       "      <td>0.09</td>\n",
       "      <td>-540.81</td>\n",
       "      <td>76.48</td>\n",
       "      <td>-508.004299</td>\n",
       "      <td>-448.327761</td>\n",
       "      <td>1.151103e+09</td>\n",
       "      <td>6.017304e+10</td>\n",
       "      <td>-508.004299</td>\n",
       "      <td>-448.327761</td>\n",
       "      <td>1.151103e+09</td>\n",
       "      <td>6.017304e+10</td>\n",
       "      <td>-0.673094</td>\n",
       "      <td>-507.318818</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>2000-01-01_2020-01-01</td>\n",
       "      <td>-9.60</td>\n",
       "      <td>1.06</td>\n",
       "      <td>-199.00</td>\n",
       "      <td>22.15</td>\n",
       "      <td>-195.669760</td>\n",
       "      <td>-181.435905</td>\n",
       "      <td>4.924147e+10</td>\n",
       "      <td>3.311656e+12</td>\n",
       "      <td>-195.669760</td>\n",
       "      <td>-181.435905</td>\n",
       "      <td>4.924147e+10</td>\n",
       "      <td>3.311656e+12</td>\n",
       "      <td>-9.630135</td>\n",
       "      <td>-195.669760</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>2000-01-01_2020-01-01</td>\n",
       "      <td>-4.56</td>\n",
       "      <td>0.84</td>\n",
       "      <td>-138.59</td>\n",
       "      <td>25.49</td>\n",
       "      <td>-135.945961</td>\n",
       "      <td>-141.183575</td>\n",
       "      <td>3.360750e+10</td>\n",
       "      <td>2.893592e+12</td>\n",
       "      <td>-135.945961</td>\n",
       "      <td>-141.183575</td>\n",
       "      <td>3.360750e+10</td>\n",
       "      <td>2.893592e+12</td>\n",
       "      <td>-4.561651</td>\n",
       "      <td>-135.945961</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>2000-01-01_2020-01-01</td>\n",
       "      <td>-6.87</td>\n",
       "      <td>0.71</td>\n",
       "      <td>-477.23</td>\n",
       "      <td>49.28</td>\n",
       "      <td>-468.178425</td>\n",
       "      <td>-434.848781</td>\n",
       "      <td>1.472894e+10</td>\n",
       "      <td>9.026204e+11</td>\n",
       "      <td>-468.178425</td>\n",
       "      <td>-434.848781</td>\n",
       "      <td>1.472894e+10</td>\n",
       "      <td>9.026204e+11</td>\n",
       "      <td>-6.893968</td>\n",
       "      <td>-468.178425</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>2000-01-01_2020-01-01</td>\n",
       "      <td>-0.93</td>\n",
       "      <td>0.12</td>\n",
       "      <td>-453.83</td>\n",
       "      <td>58.23</td>\n",
       "      <td>-399.241599</td>\n",
       "      <td>-357.715037</td>\n",
       "      <td>2.341109e+09</td>\n",
       "      <td>9.756864e+10</td>\n",
       "      <td>-399.241599</td>\n",
       "      <td>-357.715037</td>\n",
       "      <td>2.341109e+09</td>\n",
       "      <td>9.756864e+10</td>\n",
       "      <td>-0.934576</td>\n",
       "      <td>-399.241599</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>2000-01-01_2020-01-01</td>\n",
       "      <td>-20.68</td>\n",
       "      <td>2.05</td>\n",
       "      <td>-715.61</td>\n",
       "      <td>71.35</td>\n",
       "      <td>-450.563247</td>\n",
       "      <td>-682.994657</td>\n",
       "      <td>2.940483e+10</td>\n",
       "      <td>5.339397e+12</td>\n",
       "      <td>-450.563247</td>\n",
       "      <td>-682.994657</td>\n",
       "      <td>2.940483e+10</td>\n",
       "      <td>5.339397e+12</td>\n",
       "      <td>-8.878099</td>\n",
       "      <td>-450.563247</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>2000-01-01_2020-01-01</td>\n",
       "      <td>-0.65</td>\n",
       "      <td>0.10</td>\n",
       "      <td>-718.22</td>\n",
       "      <td>108.68</td>\n",
       "      <td>-554.401058</td>\n",
       "      <td>-464.557271</td>\n",
       "      <td>1.173934e+09</td>\n",
       "      <td>6.891259e+10</td>\n",
       "      <td>-554.401058</td>\n",
       "      <td>-464.557271</td>\n",
       "      <td>1.173934e+09</td>\n",
       "      <td>6.891259e+10</td>\n",
       "      <td>-0.644075</td>\n",
       "      <td>-554.401058</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>2000-01-01_2020-01-01</td>\n",
       "      <td>-20.87</td>\n",
       "      <td>2.46</td>\n",
       "      <td>-166.49</td>\n",
       "      <td>19.71</td>\n",
       "      <td>-157.501651</td>\n",
       "      <td>-289.806633</td>\n",
       "      <td>1.358448e+11</td>\n",
       "      <td>4.596159e+13</td>\n",
       "      <td>-157.501651</td>\n",
       "      <td>-289.806633</td>\n",
       "      <td>1.358448e+11</td>\n",
       "      <td>4.596159e+13</td>\n",
       "      <td>-20.836318</td>\n",
       "      <td>-157.501651</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                   period   dmdt  err_dmdt  dmdtda  err_dmdtda  \\\n",
       "01  2000-01-01_2020-01-01 -66.61      5.43 -773.79       63.56   \n",
       "02  2000-01-01_2020-01-01  -7.56      0.85 -529.43       59.52   \n",
       "03  2000-01-01_2020-01-01 -30.54      2.42 -292.74       23.41   \n",
       "04  2000-01-01_2020-01-01 -26.48      2.13 -652.65       52.90   \n",
       "05  2000-01-01_2020-01-01 -35.49      2.89 -427.09       35.03   \n",
       "06  2000-01-01_2020-01-01  -9.36      0.70 -877.49       66.59   \n",
       "07  2000-01-01_2020-01-01 -10.53      0.85 -312.12       25.27   \n",
       "08  2000-01-01_2020-01-01  -1.67      0.18 -577.56       62.94   \n",
       "09  2000-01-01_2020-01-01 -10.40      0.94 -202.92       18.47   \n",
       "10  2000-01-01_2020-01-01  -1.22      0.18 -503.76       73.45   \n",
       "11  2000-01-01_2020-01-01  -1.69      0.21 -863.75      107.67   \n",
       "12  2000-01-01_2020-01-01  -0.67      0.09 -540.81       76.48   \n",
       "13  2000-01-01_2020-01-01  -9.60      1.06 -199.00       22.15   \n",
       "14  2000-01-01_2020-01-01  -4.56      0.84 -138.59       25.49   \n",
       "15  2000-01-01_2020-01-01  -6.87      0.71 -477.23       49.28   \n",
       "16  2000-01-01_2020-01-01  -0.93      0.12 -453.83       58.23   \n",
       "17  2000-01-01_2020-01-01 -20.68      2.05 -715.61       71.35   \n",
       "18  2000-01-01_2020-01-01  -0.65      0.10 -718.22      108.68   \n",
       "19  2000-01-01_2020-01-01 -20.87      2.46 -166.49       19.71   \n",
       "\n",
       "    dmdtda_OGGM_W5E5  dmdtda_dyna_OGGM_W5E5  area_OGGM_2000_W5E5  \\\n",
       "01       -682.867030            -678.438420         8.671674e+10   \n",
       "02       -520.062346            -458.972311         1.504937e+10   \n",
       "03       -290.846673            -313.764167         1.051061e+11   \n",
       "04       -648.224633            -616.008782         4.091842e+10   \n",
       "05       -395.943637            -365.575862         8.972035e+10   \n",
       "06       -846.380030            -785.780554         1.105953e+10   \n",
       "07       -303.312236            -277.919769         3.397128e+10   \n",
       "08       -565.171709            -537.845993         2.948529e+09   \n",
       "09       -202.111130            -216.460018         5.157186e+10   \n",
       "10       -520.976144            -497.623844         2.323438e+09   \n",
       "11       -804.911322            -735.500422         2.091911e+09   \n",
       "12       -508.004299            -448.327761         1.151103e+09   \n",
       "13       -195.669760            -181.435905         4.924147e+10   \n",
       "14       -135.945961            -141.183575         3.360750e+10   \n",
       "15       -468.178425            -434.848781         1.472894e+10   \n",
       "16       -399.241599            -357.715037         2.341109e+09   \n",
       "17       -450.563247            -682.994657         2.940483e+10   \n",
       "18       -554.401058            -464.557271         1.173934e+09   \n",
       "19       -157.501651            -289.806633         1.358448e+11   \n",
       "\n",
       "    vol_OGGM_2000_W5E5  dmdtda_OGGM_W5E5_spinup  dmdtda_dyna_OGGM_W5E5_spinup  \\\n",
       "01        1.946116e+13              -682.867030                   -678.438420   \n",
       "02        1.079486e+12              -520.062346                   -458.972311   \n",
       "03        2.832337e+13              -290.846673                   -313.764167   \n",
       "04        8.672361e+12              -648.224633                   -616.008782   \n",
       "05        1.577052e+13              -395.943637                   -365.575862   \n",
       "06        3.785239e+12              -846.380030                   -785.780554   \n",
       "07        7.565840e+12              -303.312236                   -277.919769   \n",
       "08        3.061212e+11              -565.171709                   -537.845993   \n",
       "09        1.468843e+13              -202.111130                   -216.460018   \n",
       "10        1.407830e+11              -520.976144                   -497.623844   \n",
       "11        1.328835e+11              -804.911322                   -735.500422   \n",
       "12        6.017304e+10              -508.004299                   -448.327761   \n",
       "13        3.311656e+12              -195.669760                   -181.435905   \n",
       "14        2.893592e+12              -135.945961                   -141.183575   \n",
       "15        9.026204e+11              -468.178425                   -434.848781   \n",
       "16        9.756864e+10              -399.241599                   -357.715037   \n",
       "17        5.339397e+12              -450.563247                   -682.994657   \n",
       "18        6.891259e+10              -554.401058                   -464.557271   \n",
       "19        4.596159e+13              -157.501651                   -289.806633   \n",
       "\n",
       "    area_OGGM_2000_W5E5_spinup  vol_OGGM_2000_W5E5_spinup  \\\n",
       "01                8.671674e+10               1.946116e+13   \n",
       "02                1.504937e+10               1.079486e+12   \n",
       "03                1.051061e+11               2.832337e+13   \n",
       "04                4.091842e+10               8.672361e+12   \n",
       "05                8.972035e+10               1.577052e+13   \n",
       "06                1.105953e+10               3.785239e+12   \n",
       "07                3.397128e+10               7.565840e+12   \n",
       "08                2.948529e+09               3.061212e+11   \n",
       "09                5.157186e+10               1.468843e+13   \n",
       "10                2.323438e+09               1.407830e+11   \n",
       "11                2.091911e+09               1.328835e+11   \n",
       "12                1.151103e+09               6.017304e+10   \n",
       "13                4.924147e+10               3.311656e+12   \n",
       "14                3.360750e+10               2.893592e+12   \n",
       "15                1.472894e+10               9.026204e+11   \n",
       "16                2.341109e+09               9.756864e+10   \n",
       "17                2.940483e+10               5.339397e+12   \n",
       "18                1.173934e+09               6.891259e+10   \n",
       "19                1.358448e+11               4.596159e+13   \n",
       "\n",
       "    dmdt_geodetic_only_running_glaciers  dmdtda_geodetic_only_running_glaciers  \n",
       "01                           -48.012651                            -682.867030  \n",
       "02                            -7.552034                            -520.062346  \n",
       "03                           -30.564668                            -290.846673  \n",
       "04                           -26.501952                            -648.224633  \n",
       "05                           -35.513797                            -395.943637  \n",
       "06                            -9.360413                            -846.380030  \n",
       "07                           -10.539078                            -308.281779  \n",
       "08                            -1.666295                            -565.171709  \n",
       "09                           -10.422389                            -202.111130  \n",
       "10                            -1.209430                            -520.976144  \n",
       "11                            -1.683695                            -804.911322  \n",
       "12                            -0.673094                            -507.318818  \n",
       "13                            -9.630135                            -195.669760  \n",
       "14                            -4.561651                            -135.945961  \n",
       "15                            -6.893968                            -468.178425  \n",
       "16                            -0.934576                            -399.241599  \n",
       "17                            -8.878099                            -450.563247  \n",
       "18                            -0.644075                            -554.401058  \n",
       "19                           -20.836318                            -157.501651  "
      ]
     },
     "execution_count": 84,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dfh"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 74,
   "id": "5c154874-c458-43da-9b32-ceabdf0f5966",
   "metadata": {},
   "outputs": [
    {
     "ename": "InvalidIndexError",
     "evalue": "Reindexing only valid with uniquely valued Index objects",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mInvalidIndexError\u001b[0m                         Traceback (most recent call last)",
      "Input \u001b[0;32mIn [74]\u001b[0m, in \u001b[0;36m<cell line: 1>\u001b[0;34m()\u001b[0m\n\u001b[0;32m----> 1\u001b[0m dfhh \u001b[38;5;241m=\u001b[39m \u001b[43mpd\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mconcat\u001b[49m\u001b[43m(\u001b[49m\u001b[43m[\u001b[49m\u001b[43mdfh\u001b[49m\u001b[43m,\u001b[49m\u001b[43mpd_working_glaciers_geod\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mT\u001b[49m\u001b[43m]\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43maxis\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;241;43m1\u001b[39;49m\u001b[43m)\u001b[49m\n\u001b[1;32m      2\u001b[0m dfhh\u001b[38;5;241m.\u001b[39mto_csv(\u001b[38;5;124mf\u001b[39m\u001b[38;5;124m'\u001b[39m\u001b[38;5;124moggm_v161_w5e5_spinup_dmdtda_area_vol_for_prepro_level_5_gdirs.csv\u001b[39m\u001b[38;5;124m'\u001b[39m)\n",
      "File \u001b[0;32m~/.local/lib/python3.10/site-packages/pandas/util/_decorators.py:311\u001b[0m, in \u001b[0;36mdeprecate_nonkeyword_arguments.<locals>.decorate.<locals>.wrapper\u001b[0;34m(*args, **kwargs)\u001b[0m\n\u001b[1;32m    305\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mlen\u001b[39m(args) \u001b[38;5;241m>\u001b[39m num_allow_args:\n\u001b[1;32m    306\u001b[0m     warnings\u001b[38;5;241m.\u001b[39mwarn(\n\u001b[1;32m    307\u001b[0m         msg\u001b[38;5;241m.\u001b[39mformat(arguments\u001b[38;5;241m=\u001b[39marguments),\n\u001b[1;32m    308\u001b[0m         \u001b[38;5;167;01mFutureWarning\u001b[39;00m,\n\u001b[1;32m    309\u001b[0m         stacklevel\u001b[38;5;241m=\u001b[39mstacklevel,\n\u001b[1;32m    310\u001b[0m     )\n\u001b[0;32m--> 311\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mfunc\u001b[49m\u001b[43m(\u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43margs\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[38;5;241;43m*\u001b[39;49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n",
      "File \u001b[0;32m~/.local/lib/python3.10/site-packages/pandas/core/reshape/concat.py:360\u001b[0m, in \u001b[0;36mconcat\u001b[0;34m(objs, axis, join, ignore_index, keys, levels, names, verify_integrity, sort, copy)\u001b[0m\n\u001b[1;32m    156\u001b[0m \u001b[38;5;124;03m\"\"\"\u001b[39;00m\n\u001b[1;32m    157\u001b[0m \u001b[38;5;124;03mConcatenate pandas objects along a particular axis with optional set logic\u001b[39;00m\n\u001b[1;32m    158\u001b[0m \u001b[38;5;124;03malong the other axes.\u001b[39;00m\n\u001b[0;32m   (...)\u001b[0m\n\u001b[1;32m    345\u001b[0m \u001b[38;5;124;03mValueError: Indexes have overlapping values: ['a']\u001b[39;00m\n\u001b[1;32m    346\u001b[0m \u001b[38;5;124;03m\"\"\"\u001b[39;00m\n\u001b[1;32m    347\u001b[0m op \u001b[38;5;241m=\u001b[39m _Concatenator(\n\u001b[1;32m    348\u001b[0m     objs,\n\u001b[1;32m    349\u001b[0m     axis\u001b[38;5;241m=\u001b[39maxis,\n\u001b[0;32m   (...)\u001b[0m\n\u001b[1;32m    357\u001b[0m     sort\u001b[38;5;241m=\u001b[39msort,\n\u001b[1;32m    358\u001b[0m )\n\u001b[0;32m--> 360\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[43mop\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mget_result\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\n",
      "File \u001b[0;32m~/.local/lib/python3.10/site-packages/pandas/core/reshape/concat.py:591\u001b[0m, in \u001b[0;36m_Concatenator.get_result\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m    589\u001b[0m         obj_labels \u001b[38;5;241m=\u001b[39m obj\u001b[38;5;241m.\u001b[39maxes[\u001b[38;5;241m1\u001b[39m \u001b[38;5;241m-\u001b[39m ax]\n\u001b[1;32m    590\u001b[0m         \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m new_labels\u001b[38;5;241m.\u001b[39mequals(obj_labels):\n\u001b[0;32m--> 591\u001b[0m             indexers[ax] \u001b[38;5;241m=\u001b[39m \u001b[43mobj_labels\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mget_indexer\u001b[49m\u001b[43m(\u001b[49m\u001b[43mnew_labels\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m    593\u001b[0m     mgrs_indexers\u001b[38;5;241m.\u001b[39mappend((obj\u001b[38;5;241m.\u001b[39m_mgr, indexers))\n\u001b[1;32m    595\u001b[0m new_data \u001b[38;5;241m=\u001b[39m concatenate_managers(\n\u001b[1;32m    596\u001b[0m     mgrs_indexers, \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mnew_axes, concat_axis\u001b[38;5;241m=\u001b[39m\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mbm_axis, copy\u001b[38;5;241m=\u001b[39m\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mcopy\n\u001b[1;32m    597\u001b[0m )\n",
      "File \u001b[0;32m~/.local/lib/python3.10/site-packages/pandas/core/indexes/base.py:3721\u001b[0m, in \u001b[0;36mIndex.get_indexer\u001b[0;34m(self, target, method, limit, tolerance)\u001b[0m\n\u001b[1;32m   3718\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_check_indexing_method(method, limit, tolerance)\n\u001b[1;32m   3720\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_index_as_unique:\n\u001b[0;32m-> 3721\u001b[0m     \u001b[38;5;28;01mraise\u001b[39;00m InvalidIndexError(\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_requires_unique_msg)\n\u001b[1;32m   3723\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mlen\u001b[39m(target) \u001b[38;5;241m==\u001b[39m \u001b[38;5;241m0\u001b[39m:\n\u001b[1;32m   3724\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m np\u001b[38;5;241m.\u001b[39marray([], dtype\u001b[38;5;241m=\u001b[39mnp\u001b[38;5;241m.\u001b[39mintp)\n",
      "\u001b[0;31mInvalidIndexError\u001b[0m: Reindexing only valid with uniquely valued Index objects"
     ]
    }
   ],
   "source": [
    "    dfhh = pd.concat([dfh,pd_working_glaciers_geod.T], axis=1)\n",
    "    dfhh.to_csv(f'oggm_v161_w5e5_spinup_dmdtda_area_vol_for_prepro_level_5_gdirs.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 72,
   "id": "ff0a64a7-b5a1-4bbf-a41a-95347d705f69",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
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       "\n",
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       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>period</th>\n",
       "      <th>dmdt</th>\n",
       "      <th>err_dmdt</th>\n",
       "      <th>dmdtda</th>\n",
       "      <th>err_dmdtda</th>\n",
       "      <th>dmdtda_OGGM_W5E5</th>\n",
       "      <th>dmdtda_dyna_OGGM_W5E5</th>\n",
       "      <th>area_OGGM_2000_W5E5</th>\n",
       "      <th>vol_OGGM_2000_W5E5</th>\n",
       "      <th>dmdtda_OGGM_W5E5_spinup</th>\n",
       "      <th>dmdtda_dyna_OGGM_W5E5_spinup</th>\n",
       "      <th>area_OGGM_2000_W5E5_spinup</th>\n",
       "      <th>vol_OGGM_2000_W5E5_spinup</th>\n",
       "      <th>dmdt_geodetic_only_running_glaciers</th>\n",
       "      <th>dmdtda_geodetic_only_running_glaciers</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>01</th>\n",
       "      <td>2000-01-01_2020-01-01</td>\n",
       "      <td>-66.61</td>\n",
       "      <td>5.43</td>\n",
       "      <td>-773.79</td>\n",
       "      <td>63.56</td>\n",
       "      <td>-682.867030</td>\n",
       "      <td>-678.438420</td>\n",
       "      <td>8.671674e+10</td>\n",
       "      <td>1.946116e+13</td>\n",
       "      <td>-682.867030</td>\n",
       "      <td>-678.438420</td>\n",
       "      <td>8.671674e+10</td>\n",
       "      <td>1.946116e+13</td>\n",
       "      <td>-48.012651</td>\n",
       "      <td>-682.867030</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>02</th>\n",
       "      <td>2000-01-01_2020-01-01</td>\n",
       "      <td>-7.56</td>\n",
       "      <td>0.85</td>\n",
       "      <td>-529.43</td>\n",
       "      <td>59.52</td>\n",
       "      <td>-520.062346</td>\n",
       "      <td>-458.972311</td>\n",
       "      <td>1.504937e+10</td>\n",
       "      <td>1.079486e+12</td>\n",
       "      <td>-520.062346</td>\n",
       "      <td>-458.972311</td>\n",
       "      <td>1.504937e+10</td>\n",
       "      <td>1.079486e+12</td>\n",
       "      <td>-7.552034</td>\n",
       "      <td>-520.062346</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>03</th>\n",
       "      <td>2000-01-01_2020-01-01</td>\n",
       "      <td>-30.54</td>\n",
       "      <td>2.42</td>\n",
       "      <td>-292.74</td>\n",
       "      <td>23.41</td>\n",
       "      <td>-290.846673</td>\n",
       "      <td>-313.764167</td>\n",
       "      <td>1.051061e+11</td>\n",
       "      <td>2.832337e+13</td>\n",
       "      <td>-290.846673</td>\n",
       "      <td>-313.764167</td>\n",
       "      <td>1.051061e+11</td>\n",
       "      <td>2.832337e+13</td>\n",
       "      <td>-30.564668</td>\n",
       "      <td>-290.846673</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>04</th>\n",
       "      <td>2000-01-01_2020-01-01</td>\n",
       "      <td>-26.48</td>\n",
       "      <td>2.13</td>\n",
       "      <td>-652.65</td>\n",
       "      <td>52.90</td>\n",
       "      <td>-648.224633</td>\n",
       "      <td>-616.008782</td>\n",
       "      <td>4.091842e+10</td>\n",
       "      <td>8.672361e+12</td>\n",
       "      <td>-648.224633</td>\n",
       "      <td>-616.008782</td>\n",
       "      <td>4.091842e+10</td>\n",
       "      <td>8.672361e+12</td>\n",
       "      <td>-26.501952</td>\n",
       "      <td>-648.224633</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>05</th>\n",
       "      <td>2000-01-01_2020-01-01</td>\n",
       "      <td>-35.49</td>\n",
       "      <td>2.89</td>\n",
       "      <td>-427.09</td>\n",
       "      <td>35.03</td>\n",
       "      <td>-395.943637</td>\n",
       "      <td>-365.575862</td>\n",
       "      <td>8.972035e+10</td>\n",
       "      <td>1.577052e+13</td>\n",
       "      <td>-395.943637</td>\n",
       "      <td>-365.575862</td>\n",
       "      <td>8.972035e+10</td>\n",
       "      <td>1.577052e+13</td>\n",
       "      <td>-35.513797</td>\n",
       "      <td>-395.943637</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>06</th>\n",
       "      <td>2000-01-01_2020-01-01</td>\n",
       "      <td>-9.36</td>\n",
       "      <td>0.70</td>\n",
       "      <td>-877.49</td>\n",
       "      <td>66.59</td>\n",
       "      <td>-846.380030</td>\n",
       "      <td>-785.780554</td>\n",
       "      <td>1.105953e+10</td>\n",
       "      <td>3.785239e+12</td>\n",
       "      <td>-846.380030</td>\n",
       "      <td>-785.780554</td>\n",
       "      <td>1.105953e+10</td>\n",
       "      <td>3.785239e+12</td>\n",
       "      <td>-9.360413</td>\n",
       "      <td>-846.380030</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>07</th>\n",
       "      <td>2000-01-01_2020-01-01</td>\n",
       "      <td>-10.53</td>\n",
       "      <td>0.85</td>\n",
       "      <td>-312.12</td>\n",
       "      <td>25.27</td>\n",
       "      <td>-303.312236</td>\n",
       "      <td>-277.919769</td>\n",
       "      <td>3.397128e+10</td>\n",
       "      <td>7.565840e+12</td>\n",
       "      <td>-303.312236</td>\n",
       "      <td>-277.919769</td>\n",
       "      <td>3.397128e+10</td>\n",
       "      <td>7.565840e+12</td>\n",
       "      <td>-10.539078</td>\n",
       "      <td>-308.281779</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>08</th>\n",
       "      <td>2000-01-01_2020-01-01</td>\n",
       "      <td>-1.67</td>\n",
       "      <td>0.18</td>\n",
       "      <td>-577.56</td>\n",
       "      <td>62.94</td>\n",
       "      <td>-565.171709</td>\n",
       "      <td>-537.845993</td>\n",
       "      <td>2.948529e+09</td>\n",
       "      <td>3.061212e+11</td>\n",
       "      <td>-565.171709</td>\n",
       "      <td>-537.845993</td>\n",
       "      <td>2.948529e+09</td>\n",
       "      <td>3.061212e+11</td>\n",
       "      <td>-1.666295</td>\n",
       "      <td>-565.171709</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>09</th>\n",
       "      <td>2000-01-01_2020-01-01</td>\n",
       "      <td>-10.40</td>\n",
       "      <td>0.94</td>\n",
       "      <td>-202.92</td>\n",
       "      <td>18.47</td>\n",
       "      <td>-202.111130</td>\n",
       "      <td>-216.460018</td>\n",
       "      <td>5.157186e+10</td>\n",
       "      <td>1.468843e+13</td>\n",
       "      <td>-202.111130</td>\n",
       "      <td>-216.460018</td>\n",
       "      <td>5.157186e+10</td>\n",
       "      <td>1.468843e+13</td>\n",
       "      <td>-10.422389</td>\n",
       "      <td>-202.111130</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>2000-01-01_2020-01-01</td>\n",
       "      <td>-1.22</td>\n",
       "      <td>0.18</td>\n",
       "      <td>-503.76</td>\n",
       "      <td>73.45</td>\n",
       "      <td>-520.976144</td>\n",
       "      <td>-497.623844</td>\n",
       "      <td>2.323438e+09</td>\n",
       "      <td>1.407830e+11</td>\n",
       "      <td>-520.976144</td>\n",
       "      <td>-497.623844</td>\n",
       "      <td>2.323438e+09</td>\n",
       "      <td>1.407830e+11</td>\n",
       "      <td>-1.209430</td>\n",
       "      <td>-520.976144</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>2000-01-01_2020-01-01</td>\n",
       "      <td>-1.69</td>\n",
       "      <td>0.21</td>\n",
       "      <td>-863.75</td>\n",
       "      <td>107.67</td>\n",
       "      <td>-804.911322</td>\n",
       "      <td>-735.500422</td>\n",
       "      <td>2.091911e+09</td>\n",
       "      <td>1.328835e+11</td>\n",
       "      <td>-804.911322</td>\n",
       "      <td>-735.500422</td>\n",
       "      <td>2.091911e+09</td>\n",
       "      <td>1.328835e+11</td>\n",
       "      <td>-1.683695</td>\n",
       "      <td>-804.911322</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>2000-01-01_2020-01-01</td>\n",
       "      <td>-0.67</td>\n",
       "      <td>0.09</td>\n",
       "      <td>-540.81</td>\n",
       "      <td>76.48</td>\n",
       "      <td>-508.004299</td>\n",
       "      <td>-448.327761</td>\n",
       "      <td>1.151103e+09</td>\n",
       "      <td>6.017304e+10</td>\n",
       "      <td>-508.004299</td>\n",
       "      <td>-448.327761</td>\n",
       "      <td>1.151103e+09</td>\n",
       "      <td>6.017304e+10</td>\n",
       "      <td>-0.673094</td>\n",
       "      <td>-507.318818</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>2000-01-01_2020-01-01</td>\n",
       "      <td>-9.60</td>\n",
       "      <td>1.06</td>\n",
       "      <td>-199.00</td>\n",
       "      <td>22.15</td>\n",
       "      <td>-195.669760</td>\n",
       "      <td>-181.435905</td>\n",
       "      <td>4.924147e+10</td>\n",
       "      <td>3.311656e+12</td>\n",
       "      <td>-195.669760</td>\n",
       "      <td>-181.435905</td>\n",
       "      <td>4.924147e+10</td>\n",
       "      <td>3.311656e+12</td>\n",
       "      <td>-9.630135</td>\n",
       "      <td>-195.669760</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>2000-01-01_2020-01-01</td>\n",
       "      <td>-4.56</td>\n",
       "      <td>0.84</td>\n",
       "      <td>-138.59</td>\n",
       "      <td>25.49</td>\n",
       "      <td>-135.945961</td>\n",
       "      <td>-141.183575</td>\n",
       "      <td>3.360750e+10</td>\n",
       "      <td>2.893592e+12</td>\n",
       "      <td>-135.945961</td>\n",
       "      <td>-141.183575</td>\n",
       "      <td>3.360750e+10</td>\n",
       "      <td>2.893592e+12</td>\n",
       "      <td>-4.561651</td>\n",
       "      <td>-135.945961</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>2000-01-01_2020-01-01</td>\n",
       "      <td>-6.87</td>\n",
       "      <td>0.71</td>\n",
       "      <td>-477.23</td>\n",
       "      <td>49.28</td>\n",
       "      <td>-468.178425</td>\n",
       "      <td>-434.848781</td>\n",
       "      <td>1.472894e+10</td>\n",
       "      <td>9.026204e+11</td>\n",
       "      <td>-468.178425</td>\n",
       "      <td>-434.848781</td>\n",
       "      <td>1.472894e+10</td>\n",
       "      <td>9.026204e+11</td>\n",
       "      <td>-6.893968</td>\n",
       "      <td>-468.178425</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>2000-01-01_2020-01-01</td>\n",
       "      <td>-0.93</td>\n",
       "      <td>0.12</td>\n",
       "      <td>-453.83</td>\n",
       "      <td>58.23</td>\n",
       "      <td>-399.241599</td>\n",
       "      <td>-357.715037</td>\n",
       "      <td>2.341109e+09</td>\n",
       "      <td>9.756864e+10</td>\n",
       "      <td>-399.241599</td>\n",
       "      <td>-357.715037</td>\n",
       "      <td>2.341109e+09</td>\n",
       "      <td>9.756864e+10</td>\n",
       "      <td>-0.934576</td>\n",
       "      <td>-399.241599</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>2000-01-01_2020-01-01</td>\n",
       "      <td>-20.68</td>\n",
       "      <td>2.05</td>\n",
       "      <td>-715.61</td>\n",
       "      <td>71.35</td>\n",
       "      <td>-450.563247</td>\n",
       "      <td>-682.994657</td>\n",
       "      <td>2.940483e+10</td>\n",
       "      <td>5.339397e+12</td>\n",
       "      <td>-450.563247</td>\n",
       "      <td>-682.994657</td>\n",
       "      <td>2.940483e+10</td>\n",
       "      <td>5.339397e+12</td>\n",
       "      <td>-8.878099</td>\n",
       "      <td>-450.563247</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>2000-01-01_2020-01-01</td>\n",
       "      <td>-0.65</td>\n",
       "      <td>0.10</td>\n",
       "      <td>-718.22</td>\n",
       "      <td>108.68</td>\n",
       "      <td>-554.401058</td>\n",
       "      <td>-464.557271</td>\n",
       "      <td>1.173934e+09</td>\n",
       "      <td>6.891259e+10</td>\n",
       "      <td>-554.401058</td>\n",
       "      <td>-464.557271</td>\n",
       "      <td>1.173934e+09</td>\n",
       "      <td>6.891259e+10</td>\n",
       "      <td>-0.644075</td>\n",
       "      <td>-554.401058</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>2000-01-01_2020-01-01</td>\n",
       "      <td>-20.87</td>\n",
       "      <td>2.46</td>\n",
       "      <td>-166.49</td>\n",
       "      <td>19.71</td>\n",
       "      <td>-157.501651</td>\n",
       "      <td>-289.806633</td>\n",
       "      <td>1.358448e+11</td>\n",
       "      <td>4.596159e+13</td>\n",
       "      <td>-157.501651</td>\n",
       "      <td>-289.806633</td>\n",
       "      <td>1.358448e+11</td>\n",
       "      <td>4.596159e+13</td>\n",
       "      <td>-20.836318</td>\n",
       "      <td>-157.501651</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                   period   dmdt  err_dmdt  dmdtda  err_dmdtda  \\\n",
       "01  2000-01-01_2020-01-01 -66.61      5.43 -773.79       63.56   \n",
       "02  2000-01-01_2020-01-01  -7.56      0.85 -529.43       59.52   \n",
       "03  2000-01-01_2020-01-01 -30.54      2.42 -292.74       23.41   \n",
       "04  2000-01-01_2020-01-01 -26.48      2.13 -652.65       52.90   \n",
       "05  2000-01-01_2020-01-01 -35.49      2.89 -427.09       35.03   \n",
       "06  2000-01-01_2020-01-01  -9.36      0.70 -877.49       66.59   \n",
       "07  2000-01-01_2020-01-01 -10.53      0.85 -312.12       25.27   \n",
       "08  2000-01-01_2020-01-01  -1.67      0.18 -577.56       62.94   \n",
       "09  2000-01-01_2020-01-01 -10.40      0.94 -202.92       18.47   \n",
       "10  2000-01-01_2020-01-01  -1.22      0.18 -503.76       73.45   \n",
       "11  2000-01-01_2020-01-01  -1.69      0.21 -863.75      107.67   \n",
       "12  2000-01-01_2020-01-01  -0.67      0.09 -540.81       76.48   \n",
       "13  2000-01-01_2020-01-01  -9.60      1.06 -199.00       22.15   \n",
       "14  2000-01-01_2020-01-01  -4.56      0.84 -138.59       25.49   \n",
       "15  2000-01-01_2020-01-01  -6.87      0.71 -477.23       49.28   \n",
       "16  2000-01-01_2020-01-01  -0.93      0.12 -453.83       58.23   \n",
       "17  2000-01-01_2020-01-01 -20.68      2.05 -715.61       71.35   \n",
       "18  2000-01-01_2020-01-01  -0.65      0.10 -718.22      108.68   \n",
       "19  2000-01-01_2020-01-01 -20.87      2.46 -166.49       19.71   \n",
       "\n",
       "    dmdtda_OGGM_W5E5  dmdtda_dyna_OGGM_W5E5  area_OGGM_2000_W5E5  \\\n",
       "01       -682.867030            -678.438420         8.671674e+10   \n",
       "02       -520.062346            -458.972311         1.504937e+10   \n",
       "03       -290.846673            -313.764167         1.051061e+11   \n",
       "04       -648.224633            -616.008782         4.091842e+10   \n",
       "05       -395.943637            -365.575862         8.972035e+10   \n",
       "06       -846.380030            -785.780554         1.105953e+10   \n",
       "07       -303.312236            -277.919769         3.397128e+10   \n",
       "08       -565.171709            -537.845993         2.948529e+09   \n",
       "09       -202.111130            -216.460018         5.157186e+10   \n",
       "10       -520.976144            -497.623844         2.323438e+09   \n",
       "11       -804.911322            -735.500422         2.091911e+09   \n",
       "12       -508.004299            -448.327761         1.151103e+09   \n",
       "13       -195.669760            -181.435905         4.924147e+10   \n",
       "14       -135.945961            -141.183575         3.360750e+10   \n",
       "15       -468.178425            -434.848781         1.472894e+10   \n",
       "16       -399.241599            -357.715037         2.341109e+09   \n",
       "17       -450.563247            -682.994657         2.940483e+10   \n",
       "18       -554.401058            -464.557271         1.173934e+09   \n",
       "19       -157.501651            -289.806633         1.358448e+11   \n",
       "\n",
       "    vol_OGGM_2000_W5E5  dmdtda_OGGM_W5E5_spinup  dmdtda_dyna_OGGM_W5E5_spinup  \\\n",
       "01        1.946116e+13              -682.867030                   -678.438420   \n",
       "02        1.079486e+12              -520.062346                   -458.972311   \n",
       "03        2.832337e+13              -290.846673                   -313.764167   \n",
       "04        8.672361e+12              -648.224633                   -616.008782   \n",
       "05        1.577052e+13              -395.943637                   -365.575862   \n",
       "06        3.785239e+12              -846.380030                   -785.780554   \n",
       "07        7.565840e+12              -303.312236                   -277.919769   \n",
       "08        3.061212e+11              -565.171709                   -537.845993   \n",
       "09        1.468843e+13              -202.111130                   -216.460018   \n",
       "10        1.407830e+11              -520.976144                   -497.623844   \n",
       "11        1.328835e+11              -804.911322                   -735.500422   \n",
       "12        6.017304e+10              -508.004299                   -448.327761   \n",
       "13        3.311656e+12              -195.669760                   -181.435905   \n",
       "14        2.893592e+12              -135.945961                   -141.183575   \n",
       "15        9.026204e+11              -468.178425                   -434.848781   \n",
       "16        9.756864e+10              -399.241599                   -357.715037   \n",
       "17        5.339397e+12              -450.563247                   -682.994657   \n",
       "18        6.891259e+10              -554.401058                   -464.557271   \n",
       "19        4.596159e+13              -157.501651                   -289.806633   \n",
       "\n",
       "    area_OGGM_2000_W5E5_spinup  vol_OGGM_2000_W5E5_spinup  \\\n",
       "01                8.671674e+10               1.946116e+13   \n",
       "02                1.504937e+10               1.079486e+12   \n",
       "03                1.051061e+11               2.832337e+13   \n",
       "04                4.091842e+10               8.672361e+12   \n",
       "05                8.972035e+10               1.577052e+13   \n",
       "06                1.105953e+10               3.785239e+12   \n",
       "07                3.397128e+10               7.565840e+12   \n",
       "08                2.948529e+09               3.061212e+11   \n",
       "09                5.157186e+10               1.468843e+13   \n",
       "10                2.323438e+09               1.407830e+11   \n",
       "11                2.091911e+09               1.328835e+11   \n",
       "12                1.151103e+09               6.017304e+10   \n",
       "13                4.924147e+10               3.311656e+12   \n",
       "14                3.360750e+10               2.893592e+12   \n",
       "15                1.472894e+10               9.026204e+11   \n",
       "16                2.341109e+09               9.756864e+10   \n",
       "17                2.940483e+10               5.339397e+12   \n",
       "18                1.173934e+09               6.891259e+10   \n",
       "19                1.358448e+11               4.596159e+13   \n",
       "\n",
       "    dmdt_geodetic_only_running_glaciers  dmdtda_geodetic_only_running_glaciers  \n",
       "01                           -48.012651                            -682.867030  \n",
       "02                            -7.552034                            -520.062346  \n",
       "03                           -30.564668                            -290.846673  \n",
       "04                           -26.501952                            -648.224633  \n",
       "05                           -35.513797                            -395.943637  \n",
       "06                            -9.360413                            -846.380030  \n",
       "07                           -10.539078                            -308.281779  \n",
       "08                            -1.666295                            -565.171709  \n",
       "09                           -10.422389                            -202.111130  \n",
       "10                            -1.209430                            -520.976144  \n",
       "11                            -1.683695                            -804.911322  \n",
       "12                            -0.673094                            -507.318818  \n",
       "13                            -9.630135                            -195.669760  \n",
       "14                            -4.561651                            -135.945961  \n",
       "15                            -6.893968                            -468.178425  \n",
       "16                            -0.934576                            -399.241599  \n",
       "17                            -8.878099                            -450.563247  \n",
       "18                            -0.644075                            -554.401058  \n",
       "19                           -20.836318                            -157.501651  "
      ]
     },
     "execution_count": 72,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dfhh"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "id": "27b1371f-15e0-4c6b-912a-19b42bc1b609",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<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",
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>01</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>02</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>03</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>04</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>05</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>06</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>07</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>08</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>09</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "Empty DataFrame\n",
       "Columns: []\n",
       "Index: [01, 02, 03, 04, 05, 06, 07, 08, 09, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19]"
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     "execution_count": 62,
     "metadata": {},
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    "dfhh"
   ]
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   "cell_type": "code",
   "execution_count": 28,
   "id": "614cce6e-892c-45dd-92a5-e992b0431138",
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       "\n",
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       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.DataArray &#x27;volume&#x27; (time: 119, rgi_id: 2752)&gt;\n",
       "[327488 values with dtype=float32]\n",
       "Coordinates:\n",
       "  * time            (time) float64 1.902e+03 1.903e+03 ... 2.019e+03 2.02e+03\n",
       "  * rgi_id          (rgi_id) object &#x27;RGI60-19.00001&#x27; ... &#x27;RGI60-19.02752&#x27;\n",
       "    hydro_year      (time) int64 1902 1903 1904 1905 ... 2017 2018 2019 2020\n",
       "    hydro_month     (time) int64 10 10 10 10 10 10 10 ... 10 10 10 10 10 10 10\n",
       "    calendar_year   (time) int64 1902 1903 1904 1905 ... 2017 2018 2019 2020\n",
       "    calendar_month  (time) int64 1 1 1 1 1 1 1 1 1 1 1 ... 1 1 1 1 1 1 1 1 1 1 1\n",
       "Attributes:\n",
       "    description:  Total glacier volume (extended with MB data)\n",
       "    unit:         m 3</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'>'volume'</div><ul class='xr-dim-list'><li><span class='xr-has-index'>time</span>: 119</li><li><span class='xr-has-index'>rgi_id</span>: 2752</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-496414d5-8188-45f1-8072-80a43f706469' class='xr-array-in' type='checkbox' checked><label for='section-496414d5-8188-45f1-8072-80a43f706469' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>...</span></div><div class='xr-array-data'><pre>[327488 values with dtype=float32]</pre></div></div></li><li class='xr-section-item'><input id='section-6e96b7ef-b722-4a67-b634-41397ce947ac' class='xr-section-summary-in' type='checkbox'  checked><label for='section-6e96b7ef-b722-4a67-b634-41397ce947ac' class='xr-section-summary' >Coordinates: <span>(6)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>1.902e+03 1.903e+03 ... 2.02e+03</div><input id='attrs-17247921-ac49-4494-b086-866a141703a6' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-17247921-ac49-4494-b086-866a141703a6' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2563c407-d996-4d0f-96cd-45ec129aa033' class='xr-var-data-in' type='checkbox'><label for='data-2563c407-d996-4d0f-96cd-45ec129aa033' 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>description :</span></dt><dd>Floating year</dd></dl></div><div class='xr-var-data'><pre>array([1902., 1903., 1904., 1905., 1906., 1907., 1908., 1909., 1910., 1911.,\n",
       "       1912., 1913., 1914., 1915., 1916., 1917., 1918., 1919., 1920., 1921.,\n",
       "       1922., 1923., 1924., 1925., 1926., 1927., 1928., 1929., 1930., 1931.,\n",
       "       1932., 1933., 1934., 1935., 1936., 1937., 1938., 1939., 1940., 1941.,\n",
       "       1942., 1943., 1944., 1945., 1946., 1947., 1948., 1949., 1950., 1951.,\n",
       "       1952., 1953., 1954., 1955., 1956., 1957., 1958., 1959., 1960., 1961.,\n",
       "       1962., 1963., 1964., 1965., 1966., 1967., 1968., 1969., 1970., 1971.,\n",
       "       1972., 1973., 1974., 1975., 1976., 1977., 1978., 1979., 1980., 1981.,\n",
       "       1982., 1983., 1984., 1985., 1986., 1987., 1988., 1989., 1990., 1991.,\n",
       "       1992., 1993., 1994., 1995., 1996., 1997., 1998., 1999., 2000., 2001.,\n",
       "       2002., 2003., 2004., 2005., 2006., 2007., 2008., 2009., 2010., 2011.,\n",
       "       2012., 2013., 2014., 2015., 2016., 2017., 2018., 2019., 2020.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>rgi_id</span></div><div class='xr-var-dims'>(rgi_id)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>&#x27;RGI60-19.00001&#x27; ... &#x27;RGI60-19.0...</div><input id='attrs-53b90f10-47b9-449e-8ef0-e722266ddd2d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-53b90f10-47b9-449e-8ef0-e722266ddd2d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f963c43a-aaf5-4d38-b85d-41bb591e2c87' class='xr-var-data-in' type='checkbox'><label for='data-f963c43a-aaf5-4d38-b85d-41bb591e2c87' 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>description :</span></dt><dd>RGI glacier identifier</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;RGI60-19.00001&#x27;, &#x27;RGI60-19.00002&#x27;, &#x27;RGI60-19.00003&#x27;, ...,\n",
       "       &#x27;RGI60-19.02750&#x27;, &#x27;RGI60-19.02751&#x27;, &#x27;RGI60-19.02752&#x27;], dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>hydro_year</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-dba6cd05-c439-4ba0-9359-5ebc3bf34567' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-dba6cd05-c439-4ba0-9359-5ebc3bf34567' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-85d83c2a-0f2d-4963-b679-9565f8410c66' class='xr-var-data-in' type='checkbox'><label for='data-85d83c2a-0f2d-4963-b679-9565f8410c66' 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>description :</span></dt><dd>Hydrological year</dd></dl></div><div class='xr-var-data'><pre>array([1902, 1903, 1904, 1905, 1906, 1907, 1908, 1909, 1910, 1911, 1912, 1913,\n",
       "       1914, 1915, 1916, 1917, 1918, 1919, 1920, 1921, 1922, 1923, 1924, 1925,\n",
       "       1926, 1927, 1928, 1929, 1930, 1931, 1932, 1933, 1934, 1935, 1936, 1937,\n",
       "       1938, 1939, 1940, 1941, 1942, 1943, 1944, 1945, 1946, 1947, 1948, 1949,\n",
       "       1950, 1951, 1952, 1953, 1954, 1955, 1956, 1957, 1958, 1959, 1960, 1961,\n",
       "       1962, 1963, 1964, 1965, 1966, 1967, 1968, 1969, 1970, 1971, 1972, 1973,\n",
       "       1974, 1975, 1976, 1977, 1978, 1979, 1980, 1981, 1982, 1983, 1984, 1985,\n",
       "       1986, 1987, 1988, 1989, 1990, 1991, 1992, 1993, 1994, 1995, 1996, 1997,\n",
       "       1998, 1999, 2000, 2001, 2002, 2003, 2004, 2005, 2006, 2007, 2008, 2009,\n",
       "       2010, 2011, 2012, 2013, 2014, 2015, 2016, 2017, 2018, 2019, 2020])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>hydro_month</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-6ef4abe7-de30-4a0f-b3b8-74f15d1906e1' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-6ef4abe7-de30-4a0f-b3b8-74f15d1906e1' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-aac625ff-b43c-4030-beba-a745be36a89a' class='xr-var-data-in' type='checkbox'><label for='data-aac625ff-b43c-4030-beba-a745be36a89a' 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>description :</span></dt><dd>Hydrological month</dd></dl></div><div class='xr-var-data'><pre>array([10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10,\n",
       "       10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10,\n",
       "       10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10,\n",
       "       10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10,\n",
       "       10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10,\n",
       "       10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10,\n",
       "       10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>calendar_year</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-b13c8cb0-c43e-4407-9eea-10a217e416e3' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b13c8cb0-c43e-4407-9eea-10a217e416e3' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9cef0a0a-d023-4318-b000-fc56544195e5' class='xr-var-data-in' type='checkbox'><label for='data-9cef0a0a-d023-4318-b000-fc56544195e5' 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>description :</span></dt><dd>Calendar year</dd></dl></div><div class='xr-var-data'><pre>array([1902, 1903, 1904, 1905, 1906, 1907, 1908, 1909, 1910, 1911, 1912, 1913,\n",
       "       1914, 1915, 1916, 1917, 1918, 1919, 1920, 1921, 1922, 1923, 1924, 1925,\n",
       "       1926, 1927, 1928, 1929, 1930, 1931, 1932, 1933, 1934, 1935, 1936, 1937,\n",
       "       1938, 1939, 1940, 1941, 1942, 1943, 1944, 1945, 1946, 1947, 1948, 1949,\n",
       "       1950, 1951, 1952, 1953, 1954, 1955, 1956, 1957, 1958, 1959, 1960, 1961,\n",
       "       1962, 1963, 1964, 1965, 1966, 1967, 1968, 1969, 1970, 1971, 1972, 1973,\n",
       "       1974, 1975, 1976, 1977, 1978, 1979, 1980, 1981, 1982, 1983, 1984, 1985,\n",
       "       1986, 1987, 1988, 1989, 1990, 1991, 1992, 1993, 1994, 1995, 1996, 1997,\n",
       "       1998, 1999, 2000, 2001, 2002, 2003, 2004, 2005, 2006, 2007, 2008, 2009,\n",
       "       2010, 2011, 2012, 2013, 2014, 2015, 2016, 2017, 2018, 2019, 2020])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>calendar_month</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-047c25ee-5ed7-420a-a037-1ff37819b9ea' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-047c25ee-5ed7-420a-a037-1ff37819b9ea' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b24cc011-62ab-4760-af09-1686ffabe604' class='xr-var-data-in' type='checkbox'><label for='data-b24cc011-62ab-4760-af09-1686ffabe604' 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>description :</span></dt><dd>Calendar month</dd></dl></div><div class='xr-var-data'><pre>array([1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,\n",
       "       1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,\n",
       "       1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,\n",
       "       1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,\n",
       "       1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-f0eaac95-8c88-45ec-866f-e585e7abada8' class='xr-section-summary-in' type='checkbox'  checked><label for='section-f0eaac95-8c88-45ec-866f-e585e7abada8' class='xr-section-summary' >Attributes: <span>(2)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>description :</span></dt><dd>Total glacier volume (extended with MB data)</dd><dt><span>unit :</span></dt><dd>m 3</dd></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.DataArray 'volume' (time: 119, rgi_id: 2752)>\n",
       "[327488 values with dtype=float32]\n",
       "Coordinates:\n",
       "  * time            (time) float64 1.902e+03 1.903e+03 ... 2.019e+03 2.02e+03\n",
       "  * rgi_id          (rgi_id) object 'RGI60-19.00001' ... 'RGI60-19.02752'\n",
       "    hydro_year      (time) int64 ...\n",
       "    hydro_month     (time) int64 ...\n",
       "    calendar_year   (time) int64 ...\n",
       "    calendar_month  (time) int64 ...\n",
       "Attributes:\n",
       "    description:  Total glacier volume (extended with MB data)\n",
       "    unit:         m 3"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "xr.open_dataset(fd + f'historical_run_output_extended_{rgi_reg}.nc').volume"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "id": "aacdd860-1ae8-474d-a05b-12c3d04df3f9",
   "metadata": {},
   "outputs": [],
   "source": [
    "fd_w5e5_spinup = '/home/www/oggm/gdirs/oggm_v1.6/L3-L5_files/2023.2/elev_bands/W5E5_spinup/RGI62/b_160/L5/summary/'\n",
    "fd = '/home/www/oggm/gdirs/oggm_v1.6/L3-L5_files/2023.2/elev_bands/W5E5/RGI62/b_160/L5/summary/'\n",
    "\n",
    "np.testing.assert_allclose(xr.open_dataset(fd_w5e5_spinup + f'historical_run_output_extended_{rgi_reg}.nc').volume,\n",
    "                           xr.open_dataset(fd + f'historical_run_output_extended_{rgi_reg}.nc').volume)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "b8da03c1-9c0b-4af1-b8ea-7dcd0446d02c",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>period</th>\n",
       "      <th>dmdt</th>\n",
       "      <th>err_dmdt</th>\n",
       "      <th>dmdtda</th>\n",
       "      <th>err_dmdtda</th>\n",
       "      <th>dmdtda_dyna_OGGM_W5E5</th>\n",
       "      <th>area_OGGM_2000_W5E5</th>\n",
       "      <th>vol_OGGM_2000_W5E5</th>\n",
       "      <th>dmdtda_dyna_OGGM_W5E5_spinup</th>\n",
       "      <th>area_OGGM_2000_W5E5_spinup</th>\n",
       "      <th>vol_OGGM_2000_W5E5_spinup</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>01</th>\n",
       "      <td>2000-01-01_2020-01-01</td>\n",
       "      <td>-66.61</td>\n",
       "      <td>5.43</td>\n",
       "      <td>-773.79</td>\n",
       "      <td>63.56</td>\n",
       "      <td>-678.438420</td>\n",
       "      <td>8.671674e+10</td>\n",
       "      <td>1.946116e+13</td>\n",
       "      <td>-678.438420</td>\n",
       "      <td>8.671674e+10</td>\n",
       "      <td>1.946116e+13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>02</th>\n",
       "      <td>2000-01-01_2020-01-01</td>\n",
       "      <td>-7.56</td>\n",
       "      <td>0.85</td>\n",
       "      <td>-529.43</td>\n",
       "      <td>59.52</td>\n",
       "      <td>-458.972311</td>\n",
       "      <td>1.504937e+10</td>\n",
       "      <td>1.079486e+12</td>\n",
       "      <td>-458.972311</td>\n",
       "      <td>1.504937e+10</td>\n",
       "      <td>1.079486e+12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>03</th>\n",
       "      <td>2000-01-01_2020-01-01</td>\n",
       "      <td>-30.54</td>\n",
       "      <td>2.42</td>\n",
       "      <td>-292.74</td>\n",
       "      <td>23.41</td>\n",
       "      <td>-313.764167</td>\n",
       "      <td>1.051061e+11</td>\n",
       "      <td>2.832337e+13</td>\n",
       "      <td>-313.764167</td>\n",
       "      <td>1.051061e+11</td>\n",
       "      <td>2.832337e+13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>04</th>\n",
       "      <td>2000-01-01_2020-01-01</td>\n",
       "      <td>-26.48</td>\n",
       "      <td>2.13</td>\n",
       "      <td>-652.65</td>\n",
       "      <td>52.90</td>\n",
       "      <td>-616.008782</td>\n",
       "      <td>4.091842e+10</td>\n",
       "      <td>8.672361e+12</td>\n",
       "      <td>-616.008782</td>\n",
       "      <td>4.091842e+10</td>\n",
       "      <td>8.672361e+12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>05</th>\n",
       "      <td>2000-01-01_2020-01-01</td>\n",
       "      <td>-35.49</td>\n",
       "      <td>2.89</td>\n",
       "      <td>-427.09</td>\n",
       "      <td>35.03</td>\n",
       "      <td>-365.575862</td>\n",
       "      <td>8.972035e+10</td>\n",
       "      <td>1.577052e+13</td>\n",
       "      <td>-365.575862</td>\n",
       "      <td>8.972035e+10</td>\n",
       "      <td>1.577052e+13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>06</th>\n",
       "      <td>2000-01-01_2020-01-01</td>\n",
       "      <td>-9.36</td>\n",
       "      <td>0.70</td>\n",
       "      <td>-877.49</td>\n",
       "      <td>66.59</td>\n",
       "      <td>-785.780554</td>\n",
       "      <td>1.105953e+10</td>\n",
       "      <td>3.785239e+12</td>\n",
       "      <td>-785.780554</td>\n",
       "      <td>1.105953e+10</td>\n",
       "      <td>3.785239e+12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>07</th>\n",
       "      <td>2000-01-01_2020-01-01</td>\n",
       "      <td>-10.53</td>\n",
       "      <td>0.85</td>\n",
       "      <td>-312.12</td>\n",
       "      <td>25.27</td>\n",
       "      <td>-277.919769</td>\n",
       "      <td>3.397128e+10</td>\n",
       "      <td>7.565840e+12</td>\n",
       "      <td>-277.919769</td>\n",
       "      <td>3.397128e+10</td>\n",
       "      <td>7.565840e+12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>08</th>\n",
       "      <td>2000-01-01_2020-01-01</td>\n",
       "      <td>-1.67</td>\n",
       "      <td>0.18</td>\n",
       "      <td>-577.56</td>\n",
       "      <td>62.94</td>\n",
       "      <td>-537.845993</td>\n",
       "      <td>2.948529e+09</td>\n",
       "      <td>3.061212e+11</td>\n",
       "      <td>-537.845993</td>\n",
       "      <td>2.948529e+09</td>\n",
       "      <td>3.061212e+11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>09</th>\n",
       "      <td>2000-01-01_2020-01-01</td>\n",
       "      <td>-10.40</td>\n",
       "      <td>0.94</td>\n",
       "      <td>-202.92</td>\n",
       "      <td>18.47</td>\n",
       "      <td>-216.460018</td>\n",
       "      <td>5.157186e+10</td>\n",
       "      <td>1.468843e+13</td>\n",
       "      <td>-216.460018</td>\n",
       "      <td>5.157186e+10</td>\n",
       "      <td>1.468843e+13</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>2000-01-01_2020-01-01</td>\n",
       "      <td>-1.22</td>\n",
       "      <td>0.18</td>\n",
       "      <td>-503.76</td>\n",
       "      <td>73.45</td>\n",
       "      <td>-497.623844</td>\n",
       "      <td>2.323438e+09</td>\n",
       "      <td>1.407830e+11</td>\n",
       "      <td>-497.623844</td>\n",
       "      <td>2.323438e+09</td>\n",
       "      <td>1.407830e+11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>2000-01-01_2020-01-01</td>\n",
       "      <td>-1.69</td>\n",
       "      <td>0.21</td>\n",
       "      <td>-863.75</td>\n",
       "      <td>107.67</td>\n",
       "      <td>-735.500422</td>\n",
       "      <td>2.091911e+09</td>\n",
       "      <td>1.328835e+11</td>\n",
       "      <td>-735.500422</td>\n",
       "      <td>2.091911e+09</td>\n",
       "      <td>1.328835e+11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>2000-01-01_2020-01-01</td>\n",
       "      <td>-0.67</td>\n",
       "      <td>0.09</td>\n",
       "      <td>-540.81</td>\n",
       "      <td>76.48</td>\n",
       "      <td>-448.327761</td>\n",
       "      <td>1.151103e+09</td>\n",
       "      <td>6.017304e+10</td>\n",
       "      <td>-448.327761</td>\n",
       "      <td>1.151103e+09</td>\n",
       "      <td>6.017304e+10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>2000-01-01_2020-01-01</td>\n",
       "      <td>-9.60</td>\n",
       "      <td>1.06</td>\n",
       "      <td>-199.00</td>\n",
       "      <td>22.15</td>\n",
       "      <td>-181.435905</td>\n",
       "      <td>4.924147e+10</td>\n",
       "      <td>3.311656e+12</td>\n",
       "      <td>-181.435905</td>\n",
       "      <td>4.924147e+10</td>\n",
       "      <td>3.311656e+12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>2000-01-01_2020-01-01</td>\n",
       "      <td>-4.56</td>\n",
       "      <td>0.84</td>\n",
       "      <td>-138.59</td>\n",
       "      <td>25.49</td>\n",
       "      <td>-141.183575</td>\n",
       "      <td>3.360750e+10</td>\n",
       "      <td>2.893592e+12</td>\n",
       "      <td>-141.183575</td>\n",
       "      <td>3.360750e+10</td>\n",
       "      <td>2.893592e+12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>2000-01-01_2020-01-01</td>\n",
       "      <td>-6.87</td>\n",
       "      <td>0.71</td>\n",
       "      <td>-477.23</td>\n",
       "      <td>49.28</td>\n",
       "      <td>-434.848781</td>\n",
       "      <td>1.472894e+10</td>\n",
       "      <td>9.026204e+11</td>\n",
       "      <td>-434.848781</td>\n",
       "      <td>1.472894e+10</td>\n",
       "      <td>9.026204e+11</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>2000-01-01_2020-01-01</td>\n",
       "      <td>-0.93</td>\n",
       "      <td>0.12</td>\n",
       "      <td>-453.83</td>\n",
       "      <td>58.23</td>\n",
       "      <td>-357.715037</td>\n",
       "      <td>2.341109e+09</td>\n",
       "      <td>9.756864e+10</td>\n",
       "      <td>-357.715037</td>\n",
       "      <td>2.341109e+09</td>\n",
       "      <td>9.756864e+10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>2000-01-01_2020-01-01</td>\n",
       "      <td>-20.68</td>\n",
       "      <td>2.05</td>\n",
       "      <td>-715.61</td>\n",
       "      <td>71.35</td>\n",
       "      <td>-682.994657</td>\n",
       "      <td>2.940483e+10</td>\n",
       "      <td>5.339397e+12</td>\n",
       "      <td>-682.994657</td>\n",
       "      <td>2.940483e+10</td>\n",
       "      <td>5.339397e+12</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>2000-01-01_2020-01-01</td>\n",
       "      <td>-0.65</td>\n",
       "      <td>0.10</td>\n",
       "      <td>-718.22</td>\n",
       "      <td>108.68</td>\n",
       "      <td>-464.557271</td>\n",
       "      <td>1.173934e+09</td>\n",
       "      <td>6.891259e+10</td>\n",
       "      <td>-464.557271</td>\n",
       "      <td>1.173934e+09</td>\n",
       "      <td>6.891259e+10</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>2000-01-01_2020-01-01</td>\n",
       "      <td>-20.87</td>\n",
       "      <td>2.46</td>\n",
       "      <td>-166.49</td>\n",
       "      <td>19.71</td>\n",
       "      <td>-289.806633</td>\n",
       "      <td>1.358448e+11</td>\n",
       "      <td>4.596159e+13</td>\n",
       "      <td>-289.806633</td>\n",
       "      <td>1.358448e+11</td>\n",
       "      <td>4.596159e+13</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                   period   dmdt  err_dmdt  dmdtda  err_dmdtda  \\\n",
       "01  2000-01-01_2020-01-01 -66.61      5.43 -773.79       63.56   \n",
       "02  2000-01-01_2020-01-01  -7.56      0.85 -529.43       59.52   \n",
       "03  2000-01-01_2020-01-01 -30.54      2.42 -292.74       23.41   \n",
       "04  2000-01-01_2020-01-01 -26.48      2.13 -652.65       52.90   \n",
       "05  2000-01-01_2020-01-01 -35.49      2.89 -427.09       35.03   \n",
       "06  2000-01-01_2020-01-01  -9.36      0.70 -877.49       66.59   \n",
       "07  2000-01-01_2020-01-01 -10.53      0.85 -312.12       25.27   \n",
       "08  2000-01-01_2020-01-01  -1.67      0.18 -577.56       62.94   \n",
       "09  2000-01-01_2020-01-01 -10.40      0.94 -202.92       18.47   \n",
       "10  2000-01-01_2020-01-01  -1.22      0.18 -503.76       73.45   \n",
       "11  2000-01-01_2020-01-01  -1.69      0.21 -863.75      107.67   \n",
       "12  2000-01-01_2020-01-01  -0.67      0.09 -540.81       76.48   \n",
       "13  2000-01-01_2020-01-01  -9.60      1.06 -199.00       22.15   \n",
       "14  2000-01-01_2020-01-01  -4.56      0.84 -138.59       25.49   \n",
       "15  2000-01-01_2020-01-01  -6.87      0.71 -477.23       49.28   \n",
       "16  2000-01-01_2020-01-01  -0.93      0.12 -453.83       58.23   \n",
       "17  2000-01-01_2020-01-01 -20.68      2.05 -715.61       71.35   \n",
       "18  2000-01-01_2020-01-01  -0.65      0.10 -718.22      108.68   \n",
       "19  2000-01-01_2020-01-01 -20.87      2.46 -166.49       19.71   \n",
       "\n",
       "    dmdtda_dyna_OGGM_W5E5  area_OGGM_2000_W5E5  vol_OGGM_2000_W5E5  \\\n",
       "01            -678.438420         8.671674e+10        1.946116e+13   \n",
       "02            -458.972311         1.504937e+10        1.079486e+12   \n",
       "03            -313.764167         1.051061e+11        2.832337e+13   \n",
       "04            -616.008782         4.091842e+10        8.672361e+12   \n",
       "05            -365.575862         8.972035e+10        1.577052e+13   \n",
       "06            -785.780554         1.105953e+10        3.785239e+12   \n",
       "07            -277.919769         3.397128e+10        7.565840e+12   \n",
       "08            -537.845993         2.948529e+09        3.061212e+11   \n",
       "09            -216.460018         5.157186e+10        1.468843e+13   \n",
       "10            -497.623844         2.323438e+09        1.407830e+11   \n",
       "11            -735.500422         2.091911e+09        1.328835e+11   \n",
       "12            -448.327761         1.151103e+09        6.017304e+10   \n",
       "13            -181.435905         4.924147e+10        3.311656e+12   \n",
       "14            -141.183575         3.360750e+10        2.893592e+12   \n",
       "15            -434.848781         1.472894e+10        9.026204e+11   \n",
       "16            -357.715037         2.341109e+09        9.756864e+10   \n",
       "17            -682.994657         2.940483e+10        5.339397e+12   \n",
       "18            -464.557271         1.173934e+09        6.891259e+10   \n",
       "19            -289.806633         1.358448e+11        4.596159e+13   \n",
       "\n",
       "    dmdtda_dyna_OGGM_W5E5_spinup  area_OGGM_2000_W5E5_spinup  \\\n",
       "01                   -678.438420                8.671674e+10   \n",
       "02                   -458.972311                1.504937e+10   \n",
       "03                   -313.764167                1.051061e+11   \n",
       "04                   -616.008782                4.091842e+10   \n",
       "05                   -365.575862                8.972035e+10   \n",
       "06                   -785.780554                1.105953e+10   \n",
       "07                   -277.919769                3.397128e+10   \n",
       "08                   -537.845993                2.948529e+09   \n",
       "09                   -216.460018                5.157186e+10   \n",
       "10                   -497.623844                2.323438e+09   \n",
       "11                   -735.500422                2.091911e+09   \n",
       "12                   -448.327761                1.151103e+09   \n",
       "13                   -181.435905                4.924147e+10   \n",
       "14                   -141.183575                3.360750e+10   \n",
       "15                   -434.848781                1.472894e+10   \n",
       "16                   -357.715037                2.341109e+09   \n",
       "17                   -682.994657                2.940483e+10   \n",
       "18                   -464.557271                1.173934e+09   \n",
       "19                   -289.806633                1.358448e+11   \n",
       "\n",
       "    vol_OGGM_2000_W5E5_spinup  \n",
       "01               1.946116e+13  \n",
       "02               1.079486e+12  \n",
       "03               2.832337e+13  \n",
       "04               8.672361e+12  \n",
       "05               1.577052e+13  \n",
       "06               3.785239e+12  \n",
       "07               7.565840e+12  \n",
       "08               3.061212e+11  \n",
       "09               1.468843e+13  \n",
       "10               1.407830e+11  \n",
       "11               1.328835e+11  \n",
       "12               6.017304e+10  \n",
       "13               3.311656e+12  \n",
       "14               2.893592e+12  \n",
       "15               9.026204e+11  \n",
       "16               9.756864e+10  \n",
       "17               5.339397e+12  \n",
       "18               6.891259e+10  \n",
       "19               4.596159e+13  "
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dfh"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "16dff48c-03e1-4c93-b258-25e26ca4ec8e",
   "metadata": {},
   "outputs": [],
   "source": []
  }
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