{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "0690ad59-8593-4b88-805d-93f37246d063",
   "metadata": {},
   "outputs": [],
   "source": [
    "end_yr = 2100"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 78,
   "id": "21567acc-fce7-4aea-bd78-c63d4fd4aaad",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "2023-05-12 10:09:51: oggm.cfg: Reading default parameters from the OGGM `params.cfg` configuration file.\n",
      "2023-05-12 10:09:51: oggm.cfg: Multiprocessing switched OFF according to the parameter file.\n",
      "2023-05-12 10:09:51: oggm.cfg: Multiprocessing: using all available processors (N=32)\n",
      "2023-05-12 10:09:51: oggm.cfg: PARAMS['border'] changed from `80` to `160`.\n",
      "2023-05-12 10:09:51: oggm.cfg: PARAMS['store_model_geometry'] changed from `False` to `True`.\n",
      "2023-05-12 10:09:51: oggm.workflow: init_glacier_directories from prepro level 5 on 1 glaciers.\n",
      "2023-05-12 10:09:51: oggm.workflow: Execute entity tasks [gdir_from_prepro] on 1 glaciers\n",
      "2023-05-12 10:09:51: oggm.cfg: PARAMS['store_diagnostic_variables'] changed from `['volume', 'volume_bsl', 'volume_bwl', 'area', 'length', 'calving', 'calving_rate', 'off_area', 'on_area', 'melt_off_glacier', 'melt_on_glacier', 'liq_prcp_off_glacier', 'liq_prcp_on_glacier', 'snowfall_off_glacier', 'snowfall_on_glacier']` to `['volume', 'volume_bsl', 'volume_bwl', 'area', 'length', 'calving', 'calving_rate', 'off_area', 'on_area', 'melt_off_glacier', 'melt_on_glacier', 'liq_prcp_off_glacier', 'liq_prcp_on_glacier', 'snowfall_off_glacier', 'snowfall_on_glacier', 'model_mb', 'residual_mb', 'snow_bucket']`.\n",
      "2023-05-12 10:09:54: oggm.utils: InvalidWorkflowError occurred during task merge_consecutive_run_outputs_merged_from_2000_run_CMIP6_CESM2-WACCM_ssp126_endyr2100_bc_2000_2019 on RGI60-01.16122: The two files seem incompatible by data on variable : volume_bwl_m3\n"
     ]
    },
    {
     "ename": "InvalidWorkflowError",
     "evalue": "The two files seem incompatible by data on variable : volume_bwl_m3",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mInvalidWorkflowError\u001b[0m                      Traceback (most recent call last)",
      "Input \u001b[0;32mIn [78]\u001b[0m, in \u001b[0;36m<cell line: 108>\u001b[0;34m()\u001b[0m\n\u001b[1;32m     81\u001b[0m         process_cmip_data(gdir,filesuffix\u001b[38;5;241m=\u001b[39mrid\u001b[38;5;241m+\u001b[39m\u001b[38;5;124m'\u001b[39m\u001b[38;5;124m_bc_2000_2019\u001b[39m\u001b[38;5;124m'\u001b[39m,  \u001b[38;5;66;03m# recognize the climate file for later\u001b[39;00m\n\u001b[1;32m     82\u001b[0m                                      fpath_temp\u001b[38;5;241m=\u001b[39mft,  \u001b[38;5;66;03m# temperature projections\u001b[39;00m\n\u001b[1;32m     83\u001b[0m                                      fpath_precip\u001b[38;5;241m=\u001b[39mfp,  \u001b[38;5;66;03m# precip projections\u001b[39;00m\n\u001b[1;32m     84\u001b[0m                                      year_range\u001b[38;5;241m=\u001b[39m(\u001b[38;5;124m'\u001b[39m\u001b[38;5;124m2000\u001b[39m\u001b[38;5;124m'\u001b[39m, \u001b[38;5;124m'\u001b[39m\u001b[38;5;124m2019\u001b[39m\u001b[38;5;124m'\u001b[39m),\n\u001b[1;32m     85\u001b[0m                                      \u001b[38;5;66;03m#y0=2000-10,y1=2100+10,\u001b[39;00m\n\u001b[1;32m     86\u001b[0m                                      );\n\u001b[1;32m     90\u001b[0m         tasks\u001b[38;5;241m.\u001b[39mrun_with_hydro(gdir,\n\u001b[1;32m     91\u001b[0m                  run_task\u001b[38;5;241m=\u001b[39mtasks\u001b[38;5;241m.\u001b[39mrun_from_climate_data,\n\u001b[1;32m     92\u001b[0m                              ys\u001b[38;5;241m=\u001b[39m\u001b[38;5;241m2020\u001b[39m, \u001b[38;5;66;03m# this is important! Start from 2020 glacier\u001b[39;00m\n\u001b[0;32m   (...)\u001b[0m\n\u001b[1;32m    104\u001b[0m                  \u001b[38;5;66;03m# add monthly diagnostics\u001b[39;00m\n\u001b[1;32m    105\u001b[0m                  store_monthly_hydro\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mTrue\u001b[39;00m);\n\u001b[0;32m--> 108\u001b[0m \u001b[43mutils\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mmerge_consecutive_run_outputs\u001b[49m\u001b[43m(\u001b[49m\u001b[43mgdir\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m    109\u001b[0m \u001b[43m                        \u001b[49m\u001b[43minput_filesuffix_1\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[38;5;124;43m_historical_from_2000_run\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[43m,\u001b[49m\n\u001b[1;32m    110\u001b[0m \u001b[43m                        \u001b[49m\u001b[43minput_filesuffix_2\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;124;43mf\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[38;5;124;43m_future_run\u001b[39;49m\u001b[38;5;132;43;01m{\u001b[39;49;00m\u001b[43mrid\u001b[49m\u001b[38;5;132;43;01m}\u001b[39;49;00m\u001b[38;5;124;43m'\u001b[39;49m\u001b[38;5;241;43m+\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[38;5;124;43m_bc_2000_2019\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[43m,\u001b[49m\n\u001b[1;32m    111\u001b[0m \u001b[43m                        \u001b[49m\u001b[43moutput_filesuffix\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;124;43mf\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[38;5;124;43m_merged_from_2000_run\u001b[39;49m\u001b[38;5;132;43;01m{\u001b[39;49;00m\u001b[43mrid\u001b[49m\u001b[38;5;132;43;01m}\u001b[39;49;00m\u001b[38;5;124;43m_endyr\u001b[39;49m\u001b[38;5;132;43;01m{\u001b[39;49;00m\u001b[43mend_yr\u001b[49m\u001b[38;5;132;43;01m}\u001b[39;49;00m\u001b[38;5;124;43m_bc_2000_2019\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[43m,\u001b[49m\n\u001b[1;32m    112\u001b[0m \u001b[43m                        \u001b[49m\u001b[43mdelete_input\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;28;43;01mFalse\u001b[39;49;00m\u001b[43m,\u001b[49m\n\u001b[1;32m    113\u001b[0m \u001b[43m                       \u001b[49m\u001b[43m)\u001b[49m\n",
      "File \u001b[0;32m~/.local/lib/python3.10/site-packages/oggm/utils/_workflow.py:491\u001b[0m, in \u001b[0;36mentity_task.__call__.<locals>._entity_task\u001b[0;34m(gdir, reset, print_log, return_value, continue_on_error, add_to_log_file, **kwargs)\u001b[0m\n\u001b[1;32m    489\u001b[0m     signal\u001b[38;5;241m.\u001b[39malarm(cfg\u001b[38;5;241m.\u001b[39mPARAMS[\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mtask_timeout\u001b[39m\u001b[38;5;124m'\u001b[39m])\n\u001b[1;32m    490\u001b[0m ex_t \u001b[38;5;241m=\u001b[39m time\u001b[38;5;241m.\u001b[39mtime()\n\u001b[0;32m--> 491\u001b[0m out \u001b[38;5;241m=\u001b[39m \u001b[43mtask_func\u001b[49m\u001b[43m(\u001b[49m\u001b[43mgdir\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\u001b[1;32m    492\u001b[0m ex_t \u001b[38;5;241m=\u001b[39m time\u001b[38;5;241m.\u001b[39mtime() \u001b[38;5;241m-\u001b[39m ex_t\n\u001b[1;32m    493\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m cfg\u001b[38;5;241m.\u001b[39mPARAMS[\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mtask_timeout\u001b[39m\u001b[38;5;124m'\u001b[39m] \u001b[38;5;241m>\u001b[39m \u001b[38;5;241m0\u001b[39m:\n",
      "File \u001b[0;32m~/.local/lib/python3.10/site-packages/oggm/utils/_workflow.py:1055\u001b[0m, in \u001b[0;36mmerge_consecutive_run_outputs\u001b[0;34m(gdir, input_filesuffix_1, input_filesuffix_2, output_filesuffix, delete_input)\u001b[0m\n\u001b[1;32m   1053\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mlen\u001b[39m(ds2[v]\u001b[38;5;241m.\u001b[39mdata\u001b[38;5;241m.\u001b[39mshape) \u001b[38;5;241m==\u001b[39m \u001b[38;5;241m1\u001b[39m:\n\u001b[1;32m   1054\u001b[0m     \u001b[38;5;28;01mif\u001b[39;00m ds2[v]\u001b[38;5;241m.\u001b[39mdata[\u001b[38;5;241m0\u001b[39m] \u001b[38;5;241m!=\u001b[39m \u001b[38;5;241m0\u001b[39m:\n\u001b[0;32m-> 1055\u001b[0m         \u001b[38;5;28;01mraise\u001b[39;00m InvalidWorkflowError(\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mThe two files seem incompatible \u001b[39m\u001b[38;5;124m'\u001b[39m\n\u001b[1;32m   1056\u001b[0m                                    \u001b[38;5;124mf\u001b[39m\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mby data on variable : \u001b[39m\u001b[38;5;132;01m{\u001b[39;00mv\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m'\u001b[39m)\n\u001b[1;32m   1057\u001b[0m     bucket \u001b[38;5;241m=\u001b[39m ds1[v]\u001b[38;5;241m.\u001b[39mdata[\u001b[38;5;241m-\u001b[39m\u001b[38;5;241m1\u001b[39m]\n\u001b[1;32m   1058\u001b[0m \u001b[38;5;28;01melif\u001b[39;00m \u001b[38;5;28mlen\u001b[39m(ds2[v]\u001b[38;5;241m.\u001b[39mdata\u001b[38;5;241m.\u001b[39mshape) \u001b[38;5;241m==\u001b[39m \u001b[38;5;241m2\u001b[39m:\n",
      "\u001b[0;31mInvalidWorkflowError\u001b[0m: The two files seem incompatible by data on variable : volume_bwl_m3"
     ]
    }
   ],
   "source": [
    "import os\n",
    "import logging \n",
    "import sys\n",
    "\n",
    "# Libs\n",
    "import xarray as xr\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "import geopandas as gpd\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "# Locals\n",
    "import oggm.cfg as cfg\n",
    "\n",
    "from oggm import utils, workflow, tasks\n",
    "\n",
    "# only after PR is accepted\n",
    "from oggm.shop.gcm_climate import process_cmip_data\n",
    "\n",
    "# Initialize OGGM and set up the default run parameters\n",
    "cfg.initialize(logging_level='ERROR')\n",
    "rgi_version = '62'\n",
    "\n",
    "cfg.PARAMS['border'] = 160 # changed for OGGM v16\n",
    "\n",
    "cfg.PARAMS['continue_on_error'] = False\n",
    "cfg.PARAMS['use_multiprocessing']=False\n",
    "cfg.PARAMS['store_model_geometry'] = True\n",
    "           \n",
    "\n",
    "cfg.PATHS['working_dir'] = utils.gettempdir('OGGM_gcm_run', reset=False)\n",
    "\n",
    "\n",
    "rgi_reg = '17'\n",
    "\n",
    "\n",
    "# RGI glaciers \n",
    "rgi_ids = ['RGI60-01.16122']\n",
    "\n",
    "# Go - get the pre-processed glacier directories\n",
    "# TODO -> need to change the preprocessed directory here \n",
    "base_url = 'https://cluster.klima.uni-bremen.de/~oggm/gdirs/oggm_v1.6/L3-L5_files/2023.2/elev_bands/W5E5_spinup'\n",
    "# ole_v2023.1: base_url = 'https://cluster.klima.uni-bremen.de/~oggm/gdirs/oggm_v1.6/L3-L5_files/2023.1/elev_bands/W5E5_spinup'\n",
    "gdirs = workflow.init_glacier_directories(rgi_ids, from_prepro_level=5, prepro_border=160,\n",
    "                                          prepro_base_url=base_url, prepro_rgi_version=rgi_version)\n",
    "\n",
    "ALL_DIAGS = ['volume', 'volume_bsl', 'volume_bwl',\n",
    "             'area', 'length',  'calving', 'calving_rate',\n",
    "             'off_area', 'on_area', 'melt_off_glacier',\n",
    "             'melt_on_glacier', 'liq_prcp_off_glacier', 'liq_prcp_on_glacier',\n",
    "             'snowfall_off_glacier', 'snowfall_on_glacier', 'model_mb',\n",
    "             'residual_mb', 'snow_bucket']\n",
    "# Add debug vars\n",
    "cfg.PARAMS['store_diagnostic_variables'] = ALL_DIAGS\n",
    "\n",
    "\n",
    "\n",
    "        \n",
    "tasks.run_with_hydro(gdir, run_task=tasks.run_from_climate_data,\n",
    "                     climate_filename='climate_historical',\n",
    "                     ys=2000, init_model_yr=2000,\n",
    "                     store_monthly_hydro=True,\n",
    "                     init_model_filesuffix='_spinup_historical',\n",
    "                     ref_geometry_filesuffix='_spinup_historical',\n",
    "                     ref_area_yr = 2000,\n",
    "                     output_filesuffix='_historical_from_2000_run')\n",
    "\n",
    "gcms_cmip6 = pd.read_csv('/home/www/oggm/cmip6/all_gcm_list.csv', index_col=0)\n",
    "# take all gcms (can't say that we only want to process 2000-2100 ....\n",
    "for gcm in gcms_cmip6.gcm.unique()[:1]: ##TEST:\n",
    "    df1 = gcms_cmip6.loc[gcms_cmip6.gcm == gcm]\n",
    "    for ssp in df1.ssp.unique()[:1]:\n",
    "        df2 = df1.loc[df1.ssp == ssp]\n",
    "        assert len(df2) == 2\n",
    "        ft = df2.loc[df2['var'] == 'tas'].iloc[0]\n",
    "        fp = df2.loc[df2['var'] == 'pr'].iloc[0].path\n",
    "        rid = ft.fname.replace('_r1i1p1f1_tas.nc', '')\n",
    "        rid='_CMIP6_' + rid\n",
    "        ft = ft.path\n",
    "\n",
    "        process_cmip_data(gdir,filesuffix=rid+'_bc_2000_2019',  # recognize the climate file for later\n",
    "                                     fpath_temp=ft,  # temperature projections\n",
    "                                     fpath_precip=fp,  # precip projections\n",
    "                                     year_range=('2000', '2019'),\n",
    "                                     #y0=2000-10,y1=2100+10,\n",
    "                                     );\n",
    "\n",
    "\n",
    "            \n",
    "        tasks.run_with_hydro(gdir,\n",
    "                 run_task=tasks.run_from_climate_data,\n",
    "                             ys=2020, # this is important! Start from 2020 glacier\n",
    "                             ye=end_yr,\n",
    "                 # use gcm_data, not climate_historical\n",
    "                 climate_filename='gcm_data',\n",
    "                 # use the chosen scenario\n",
    "                 climate_input_filesuffix=rid+'_bc_2000_2019',\n",
    "                 # we start from the previous run, \n",
    "                 init_model_filesuffix='_historical_from_2000_run',\n",
    "                 ref_geometry_filesuffix='_historical_from_2000_run', \n",
    "                 ref_area_yr = 2000,\n",
    "                 # recognize the run for later\n",
    "                 output_filesuffix=f'_future_run{rid}'+'_bc_2000_2019',\n",
    "                 # add monthly diagnostics\n",
    "                 store_monthly_hydro=True);\n",
    "\n",
    "\n",
    "utils.merge_consecutive_run_outputs(gdir,\n",
    "                        input_filesuffix_1='_historical_from_2000_run',\n",
    "                        input_filesuffix_2=f'_future_run{rid}'+'_bc_2000_2019',\n",
    "                        output_filesuffix=f'_merged_from_2000_run{rid}_endyr{end_yr}_bc_2000_2019',\n",
    "                        delete_input=False,\n",
    "                       ) # we will delete that later"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 79,
   "id": "8f9db756-2816-45d8-b4a1-c2428e248120",
   "metadata": {},
   "outputs": [],
   "source": [
    "df = xr.open_dataset(f'/tmp/OGGM/OGGM_gcm_output/per_glacier/RGI60-01/RGI60-01.16/RGI60-01.16122/model_diagnostics_future_run{rid}'+'_bc_2000_2019.nc')\n",
    "dh = xr.open_dataset('/tmp/OGGM/OGGM_gcm_output/per_glacier/RGI60-01/RGI60-01.16/RGI60-01.16122/model_diagnostics_historical_from_2000_run.nc')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 82,
   "id": "d7eb8b99-a248-4034-aa1b-a1d65c4cebac",
   "metadata": {},
   "outputs": [
    {
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       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.DataArray &#x27;volume_bwl_m3&#x27; ()&gt;\n",
       "array(2.916507e+09)\n",
       "Coordinates:\n",
       "    time            float64 2.02e+03\n",
       "    calendar_year   int64 2020\n",
       "    calendar_month  int64 1\n",
       "    hydro_year      int64 2020\n",
       "    hydro_month     int64 4\n",
       "Attributes:\n",
       "    description:  Glacier volume below water-level\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_bwl_m3'</div></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-16d9a9a0-a914-4248-858b-3e16df058500' class='xr-array-in' type='checkbox' checked><label for='section-16d9a9a0-a914-4248-858b-3e16df058500' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>2.917e+09</span></div><div class='xr-array-data'><pre>array(2.916507e+09)</pre></div></div></li><li class='xr-section-item'><input id='section-828598b4-f9a8-4d7a-9a4e-1fe4ad2ffcb3' class='xr-section-summary-in' type='checkbox'  checked><label for='section-828598b4-f9a8-4d7a-9a4e-1fe4ad2ffcb3' 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>time</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>2.02e+03</div><input id='attrs-90875f5c-cd09-4be9-b42d-c54befa9fcab' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-90875f5c-cd09-4be9-b42d-c54befa9fcab' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-899e023d-32c3-4792-8b83-2f4937f13a9b' class='xr-var-data-in' type='checkbox'><label for='data-899e023d-32c3-4792-8b83-2f4937f13a9b' 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(2020.)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>calendar_year</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-fb0ff407-99d5-4654-9871-e81ef29fca00' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-fb0ff407-99d5-4654-9871-e81ef29fca00' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3801be86-ef1d-4a27-8426-b49973594634' class='xr-var-data-in' type='checkbox'><label for='data-3801be86-ef1d-4a27-8426-b49973594634' 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(2020)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>calendar_month</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-6242ebc2-a573-4bf3-a14f-6270a94223cc' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-6242ebc2-a573-4bf3-a14f-6270a94223cc' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-57883893-4f1d-462e-b385-31b622017251' class='xr-var-data-in' type='checkbox'><label for='data-57883893-4f1d-462e-b385-31b622017251' 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)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>hydro_year</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-688dc771-aaa9-40f0-9649-a63389c7f717' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-688dc771-aaa9-40f0-9649-a63389c7f717' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3bb193fa-7d74-491c-9f9c-1d7d5408c41a' class='xr-var-data-in' type='checkbox'><label for='data-3bb193fa-7d74-491c-9f9c-1d7d5408c41a' 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(2020)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>hydro_month</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-073b447f-f7be-49cf-8a25-a041677bae0b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-073b447f-f7be-49cf-8a25-a041677bae0b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ecddf06b-577e-4717-bc5c-eb8ef1c8b5c3' class='xr-var-data-in' type='checkbox'><label for='data-ecddf06b-577e-4717-bc5c-eb8ef1c8b5c3' 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(4)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-cb70534d-dbb4-4517-a2e5-569ce1221b7a' class='xr-section-summary-in' type='checkbox'  checked><label for='section-cb70534d-dbb4-4517-a2e5-569ce1221b7a' 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>Glacier volume below water-level</dd><dt><span>unit :</span></dt><dd>m 3</dd></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.DataArray 'volume_bwl_m3' ()>\n",
       "array(2.916507e+09)\n",
       "Coordinates:\n",
       "    time            float64 2.02e+03\n",
       "    calendar_year   int64 ...\n",
       "    calendar_month  int64 ...\n",
       "    hydro_year      int64 ...\n",
       "    hydro_month     int64 ...\n",
       "Attributes:\n",
       "    description:  Glacier volume below water-level\n",
       "    unit:         m 3"
      ]
     },
     "execution_count": 82,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dh.volume_bwl_m3.sel(time=2020), \n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 81,
   "id": "f8e56c38-24e7-4b93-8731-927fcb56b008",
   "metadata": {},
   "outputs": [
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       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.DataArray &#x27;volume_bwl_m3&#x27; (time: 81)&gt;\n",
       "array([2.029594e+09, 2.029594e+09, 2.029594e+09, 2.029594e+09, 2.023112e+09,\n",
       "       2.016336e+09, 2.006386e+09, 2.000814e+09, 1.991653e+09, 1.982263e+09,\n",
       "       1.970191e+09, 1.960187e+09, 1.948230e+09, 1.935669e+09, 1.917310e+09,\n",
       "       1.899247e+09, 1.878210e+09, 1.854544e+09, 1.824109e+09, 1.789316e+09,\n",
       "       1.757660e+09, 1.723041e+09, 1.693973e+09, 1.664198e+09, 1.635968e+09,\n",
       "       1.602742e+09, 1.572505e+09, 1.531707e+09, 1.496572e+09, 1.452187e+09,\n",
       "       1.422061e+09, 1.378542e+09, 1.333578e+09, 1.283958e+09, 1.240207e+09,\n",
       "       1.190983e+09, 1.133951e+09, 1.076799e+09, 1.029195e+09, 9.713440e+08,\n",
       "       9.143386e+08, 8.624094e+08, 8.184969e+08, 7.859111e+08, 7.563120e+08,\n",
       "       7.268151e+08, 6.957368e+08, 6.677581e+08, 6.368683e+08, 5.997715e+08,\n",
       "       5.632919e+08, 5.341504e+08, 5.087423e+08, 4.773650e+08, 4.518088e+08,\n",
       "       4.196475e+08, 3.797101e+08, 3.481730e+08, 3.160744e+08, 2.739612e+08,\n",
       "       2.332571e+08, 2.048595e+08, 1.820051e+08, 1.668449e+08, 1.566938e+08,\n",
       "       1.534813e+08, 1.534813e+08, 1.534813e+08, 1.534813e+08, 1.534813e+08,\n",
       "       1.534813e+08, 1.534813e+08, 1.534813e+08, 1.534813e+08, 1.534813e+08,\n",
       "       1.534813e+08, 1.534813e+08, 1.534813e+08, 1.534813e+08, 1.534813e+08,\n",
       "       1.534813e+08])\n",
       "Coordinates:\n",
       "  * time            (time) float64 2.02e+03 2.021e+03 ... 2.099e+03 2.1e+03\n",
       "    calendar_year   (time) int64 2020 2021 2022 2023 ... 2097 2098 2099 2100\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",
       "    hydro_year      (time) int64 2020 2021 2022 2023 ... 2097 2098 2099 2100\n",
       "    hydro_month     (time) int64 4 4 4 4 4 4 4 4 4 4 4 ... 4 4 4 4 4 4 4 4 4 4 4\n",
       "Attributes:\n",
       "    description:  Glacier volume below water-level\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_bwl_m3'</div><ul class='xr-dim-list'><li><span class='xr-has-index'>time</span>: 81</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-fe2b1b91-f33b-4048-8b35-d7def64496f9' class='xr-array-in' type='checkbox' checked><label for='section-fe2b1b91-f33b-4048-8b35-d7def64496f9' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>2.03e+09 2.03e+09 2.03e+09 2.03e+09 ... 1.535e+08 1.535e+08 1.535e+08</span></div><div class='xr-array-data'><pre>array([2.029594e+09, 2.029594e+09, 2.029594e+09, 2.029594e+09, 2.023112e+09,\n",
       "       2.016336e+09, 2.006386e+09, 2.000814e+09, 1.991653e+09, 1.982263e+09,\n",
       "       1.970191e+09, 1.960187e+09, 1.948230e+09, 1.935669e+09, 1.917310e+09,\n",
       "       1.899247e+09, 1.878210e+09, 1.854544e+09, 1.824109e+09, 1.789316e+09,\n",
       "       1.757660e+09, 1.723041e+09, 1.693973e+09, 1.664198e+09, 1.635968e+09,\n",
       "       1.602742e+09, 1.572505e+09, 1.531707e+09, 1.496572e+09, 1.452187e+09,\n",
       "       1.422061e+09, 1.378542e+09, 1.333578e+09, 1.283958e+09, 1.240207e+09,\n",
       "       1.190983e+09, 1.133951e+09, 1.076799e+09, 1.029195e+09, 9.713440e+08,\n",
       "       9.143386e+08, 8.624094e+08, 8.184969e+08, 7.859111e+08, 7.563120e+08,\n",
       "       7.268151e+08, 6.957368e+08, 6.677581e+08, 6.368683e+08, 5.997715e+08,\n",
       "       5.632919e+08, 5.341504e+08, 5.087423e+08, 4.773650e+08, 4.518088e+08,\n",
       "       4.196475e+08, 3.797101e+08, 3.481730e+08, 3.160744e+08, 2.739612e+08,\n",
       "       2.332571e+08, 2.048595e+08, 1.820051e+08, 1.668449e+08, 1.566938e+08,\n",
       "       1.534813e+08, 1.534813e+08, 1.534813e+08, 1.534813e+08, 1.534813e+08,\n",
       "       1.534813e+08, 1.534813e+08, 1.534813e+08, 1.534813e+08, 1.534813e+08,\n",
       "       1.534813e+08, 1.534813e+08, 1.534813e+08, 1.534813e+08, 1.534813e+08,\n",
       "       1.534813e+08])</pre></div></div></li><li class='xr-section-item'><input id='section-d35e9bb5-8220-4474-9e61-a95a806fdba6' class='xr-section-summary-in' type='checkbox'  checked><label for='section-d35e9bb5-8220-4474-9e61-a95a806fdba6' 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'>2.02e+03 2.021e+03 ... 2.1e+03</div><input id='attrs-0b3efe9f-fdb1-4631-b109-9e9bcb85f45c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-0b3efe9f-fdb1-4631-b109-9e9bcb85f45c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b9a1f421-54eb-4fa9-bc92-3b1a57f6c939' class='xr-var-data-in' type='checkbox'><label for='data-b9a1f421-54eb-4fa9-bc92-3b1a57f6c939' 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([2020., 2021., 2022., 2023., 2024., 2025., 2026., 2027., 2028., 2029.,\n",
       "       2030., 2031., 2032., 2033., 2034., 2035., 2036., 2037., 2038., 2039.,\n",
       "       2040., 2041., 2042., 2043., 2044., 2045., 2046., 2047., 2048., 2049.,\n",
       "       2050., 2051., 2052., 2053., 2054., 2055., 2056., 2057., 2058., 2059.,\n",
       "       2060., 2061., 2062., 2063., 2064., 2065., 2066., 2067., 2068., 2069.,\n",
       "       2070., 2071., 2072., 2073., 2074., 2075., 2076., 2077., 2078., 2079.,\n",
       "       2080., 2081., 2082., 2083., 2084., 2085., 2086., 2087., 2088., 2089.,\n",
       "       2090., 2091., 2092., 2093., 2094., 2095., 2096., 2097., 2098., 2099.,\n",
       "       2100.])</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'>2020 2021 2022 ... 2098 2099 2100</div><input id='attrs-572500c4-dd2c-45bb-85e2-bf3335879090' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-572500c4-dd2c-45bb-85e2-bf3335879090' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-eab96685-d8e6-4a32-9464-be64439c9baa' class='xr-var-data-in' type='checkbox'><label for='data-eab96685-d8e6-4a32-9464-be64439c9baa' 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([2020, 2021, 2022, 2023, 2024, 2025, 2026, 2027, 2028, 2029, 2030, 2031,\n",
       "       2032, 2033, 2034, 2035, 2036, 2037, 2038, 2039, 2040, 2041, 2042, 2043,\n",
       "       2044, 2045, 2046, 2047, 2048, 2049, 2050, 2051, 2052, 2053, 2054, 2055,\n",
       "       2056, 2057, 2058, 2059, 2060, 2061, 2062, 2063, 2064, 2065, 2066, 2067,\n",
       "       2068, 2069, 2070, 2071, 2072, 2073, 2074, 2075, 2076, 2077, 2078, 2079,\n",
       "       2080, 2081, 2082, 2083, 2084, 2085, 2086, 2087, 2088, 2089, 2090, 2091,\n",
       "       2092, 2093, 2094, 2095, 2096, 2097, 2098, 2099, 2100])</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'>1 1 1 1 1 1 1 1 ... 1 1 1 1 1 1 1 1</div><input id='attrs-f448fdc7-9409-4981-9c55-0dda57670ff6' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f448fdc7-9409-4981-9c55-0dda57670ff6' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b3210583-a22f-432a-a861-128ea21762ea' class='xr-var-data-in' type='checkbox'><label for='data-b3210583-a22f-432a-a861-128ea21762ea' 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])</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'>2020 2021 2022 ... 2098 2099 2100</div><input id='attrs-915e0b00-0e9e-4884-853e-bba1e908c05d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-915e0b00-0e9e-4884-853e-bba1e908c05d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b50ff5de-f322-4c53-840c-d1fdda2bd633' class='xr-var-data-in' type='checkbox'><label for='data-b50ff5de-f322-4c53-840c-d1fdda2bd633' 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([2020, 2021, 2022, 2023, 2024, 2025, 2026, 2027, 2028, 2029, 2030, 2031,\n",
       "       2032, 2033, 2034, 2035, 2036, 2037, 2038, 2039, 2040, 2041, 2042, 2043,\n",
       "       2044, 2045, 2046, 2047, 2048, 2049, 2050, 2051, 2052, 2053, 2054, 2055,\n",
       "       2056, 2057, 2058, 2059, 2060, 2061, 2062, 2063, 2064, 2065, 2066, 2067,\n",
       "       2068, 2069, 2070, 2071, 2072, 2073, 2074, 2075, 2076, 2077, 2078, 2079,\n",
       "       2080, 2081, 2082, 2083, 2084, 2085, 2086, 2087, 2088, 2089, 2090, 2091,\n",
       "       2092, 2093, 2094, 2095, 2096, 2097, 2098, 2099, 2100])</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'>4 4 4 4 4 4 4 4 ... 4 4 4 4 4 4 4 4</div><input id='attrs-b90b5e13-ed99-4d89-a11d-b272e0f1763c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b90b5e13-ed99-4d89-a11d-b272e0f1763c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f0f0fcc5-0caa-4cc3-ab60-2f868e522841' class='xr-var-data-in' type='checkbox'><label for='data-f0f0fcc5-0caa-4cc3-ab60-2f868e522841' 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([4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4,\n",
       "       4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4,\n",
       "       4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4,\n",
       "       4, 4, 4, 4, 4, 4, 4, 4, 4])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-bbc3c1c4-52d9-4992-92a6-f4cd8e4bc381' class='xr-section-summary-in' type='checkbox'  checked><label for='section-bbc3c1c4-52d9-4992-92a6-f4cd8e4bc381' 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>Glacier volume below water-level</dd><dt><span>unit :</span></dt><dd>m 3</dd></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.DataArray 'volume_bwl_m3' (time: 81)>\n",
       "array([2.029594e+09, 2.029594e+09, 2.029594e+09, 2.029594e+09, 2.023112e+09,\n",
       "       2.016336e+09, 2.006386e+09, 2.000814e+09, 1.991653e+09, 1.982263e+09,\n",
       "       1.970191e+09, 1.960187e+09, 1.948230e+09, 1.935669e+09, 1.917310e+09,\n",
       "       1.899247e+09, 1.878210e+09, 1.854544e+09, 1.824109e+09, 1.789316e+09,\n",
       "       1.757660e+09, 1.723041e+09, 1.693973e+09, 1.664198e+09, 1.635968e+09,\n",
       "       1.602742e+09, 1.572505e+09, 1.531707e+09, 1.496572e+09, 1.452187e+09,\n",
       "       1.422061e+09, 1.378542e+09, 1.333578e+09, 1.283958e+09, 1.240207e+09,\n",
       "       1.190983e+09, 1.133951e+09, 1.076799e+09, 1.029195e+09, 9.713440e+08,\n",
       "       9.143386e+08, 8.624094e+08, 8.184969e+08, 7.859111e+08, 7.563120e+08,\n",
       "       7.268151e+08, 6.957368e+08, 6.677581e+08, 6.368683e+08, 5.997715e+08,\n",
       "       5.632919e+08, 5.341504e+08, 5.087423e+08, 4.773650e+08, 4.518088e+08,\n",
       "       4.196475e+08, 3.797101e+08, 3.481730e+08, 3.160744e+08, 2.739612e+08,\n",
       "       2.332571e+08, 2.048595e+08, 1.820051e+08, 1.668449e+08, 1.566938e+08,\n",
       "       1.534813e+08, 1.534813e+08, 1.534813e+08, 1.534813e+08, 1.534813e+08,\n",
       "       1.534813e+08, 1.534813e+08, 1.534813e+08, 1.534813e+08, 1.534813e+08,\n",
       "       1.534813e+08, 1.534813e+08, 1.534813e+08, 1.534813e+08, 1.534813e+08,\n",
       "       1.534813e+08])\n",
       "Coordinates:\n",
       "  * time            (time) float64 2.02e+03 2.021e+03 ... 2.099e+03 2.1e+03\n",
       "    calendar_year   (time) int64 2020 2021 2022 2023 ... 2097 2098 2099 2100\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",
       "    hydro_year      (time) int64 2020 2021 2022 2023 ... 2097 2098 2099 2100\n",
       "    hydro_month     (time) int64 4 4 4 4 4 4 4 4 4 4 4 ... 4 4 4 4 4 4 4 4 4 4 4\n",
       "Attributes:\n",
       "    description:  Glacier volume below water-level\n",
       "    unit:         m 3"
      ]
     },
     "execution_count": 81,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "id": "11af6345-83d4-4fa4-8f23-9c2d5227174b",
   "metadata": {},
   "outputs": [],
   "source": [
    "input_filesuffix_1 = '_historical_from_2000_run'\n",
    "input_filesuffix_2 = f'_future_run{rid}'+'_bc_2000_2019'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 69,
   "id": "018b9b53-8890-48c4-af9f-dc642d337b52",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "152176563455.63937"
      ]
     },
     "execution_count": 69,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ds1[v].data[-1]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 70,
   "id": "871fe4a6-19f3-41c9-9d1f-4c8f68d7c3d2",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "152176563455.63928"
      ]
     },
     "execution_count": 70,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ds2[v].data[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 72,
   "id": "6a1d5079-26ba-4374-824b-ab63c7cde473",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "True"
      ]
     },
     "execution_count": 72,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "np.allclose(ds1[v].data[-1], ds2[v].data[0])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 63,
   "id": "27833849-b937-4cc1-a0b0-35f2cb97d98d",
   "metadata": {},
   "outputs": [
    {
     "ename": "NameError",
     "evalue": "name 'InvalidWorkflowError' is not defined",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mNameError\u001b[0m                                 Traceback (most recent call last)",
      "Input \u001b[0;32mIn [63]\u001b[0m, in \u001b[0;36m<cell line: 12>\u001b[0;34m()\u001b[0m\n\u001b[1;32m     21\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mlen\u001b[39m(ds2[v]\u001b[38;5;241m.\u001b[39mdata\u001b[38;5;241m.\u001b[39mshape) \u001b[38;5;241m==\u001b[39m \u001b[38;5;241m1\u001b[39m:\n\u001b[1;32m     22\u001b[0m     \u001b[38;5;28;01mif\u001b[39;00m ds2[v]\u001b[38;5;241m.\u001b[39mdata[\u001b[38;5;241m0\u001b[39m] \u001b[38;5;241m!=\u001b[39m \u001b[38;5;241m0\u001b[39m:\n\u001b[0;32m---> 23\u001b[0m         \u001b[38;5;28;01mraise\u001b[39;00m \u001b[43mInvalidWorkflowError\u001b[49m(\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mThe two files seem incompatible \u001b[39m\u001b[38;5;124m'\u001b[39m\n\u001b[1;32m     24\u001b[0m                                    \u001b[38;5;124mf\u001b[39m\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mby data on variable : \u001b[39m\u001b[38;5;132;01m{\u001b[39;00mv\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m'\u001b[39m)\n\u001b[1;32m     25\u001b[0m     bucket \u001b[38;5;241m=\u001b[39m ds1[v]\u001b[38;5;241m.\u001b[39mdata[\u001b[38;5;241m-\u001b[39m\u001b[38;5;241m1\u001b[39m]\n\u001b[1;32m     26\u001b[0m \u001b[38;5;28;01melif\u001b[39;00m \u001b[38;5;28mlen\u001b[39m(ds2[v]\u001b[38;5;241m.\u001b[39mdata\u001b[38;5;241m.\u001b[39mshape) \u001b[38;5;241m==\u001b[39m \u001b[38;5;241m2\u001b[39m:\n",
      "\u001b[0;31mNameError\u001b[0m: name 'InvalidWorkflowError' is not defined"
     ]
    }
   ],
   "source": [
    "    # Read in the input files and check\n",
    "    fp1 = gdir.get_filepath('model_diagnostics', filesuffix=input_filesuffix_1)\n",
    "    with xr.open_dataset(fp1) as ds:\n",
    "        ds1 = ds.load()\n",
    "    fp2 = gdir.get_filepath('model_diagnostics', filesuffix=input_filesuffix_2)\n",
    "    with xr.open_dataset(fp2) as ds:\n",
    "        ds2 = ds.load()\n",
    "    if ds1.time[-1] != ds2.time[0]:\n",
    "        raise InvalidWorkflowError('The two files are incompatible by time')\n",
    "\n",
    "    # Samity check for all variables as well\n",
    "    for v in ds1:\n",
    "        if not np.all(np.isfinite(ds1[v].data[-1])):\n",
    "            # This is the last year of hydro output - we will discard anyway\n",
    "            continue\n",
    "        if np.allclose(ds1[v].data[-1], ds2[v].data[0]):\n",
    "            # This means that we're OK - the two match\n",
    "            continue\n",
    "\n",
    "        # This has to be a bucket of some sort, probably snow or calving\n",
    "        if len(ds2[v].data.shape) == 1:\n",
    "            if ds2[v].data[0] != 0:\n",
    "                raise InvalidWorkflowError('The two files seem incompatible '\n",
    "                                           f'by data on variable : {v}')\n",
    "            bucket = ds1[v].data[-1]\n",
    "        elif len(ds2[v].data.shape) == 2:\n",
    "            if ds2[v].data[0, 0] != 0:\n",
    "                raise InvalidWorkflowError('The two files seem incompatible '\n",
    "                                           f'by data on variable : {v}')\n",
    "            bucket = ds1[v].data[-1, -1]\n",
    "        # Carry it to the rest\n",
    "        ds2[v] = ds2[v] + bucket\n",
    "\n",
    "    # Merge by removing the last step of file 1 and delete the files if asked\n",
    "    out_ds = xr.concat([ds1.isel(time=slice(0, -1)), ds2], dim='time')\n",
    "    if delete_input:\n",
    "        os.remove(fp1)\n",
    "        os.remove(fp2)\n",
    "    # Write out and return\n",
    "    fp = gdir.get_filepath('model_diagnostics', filesuffix=output_filesuffix)\n",
    "    out_ds.to_netcdf(fp)\n",
    "    return out_ds"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 68,
   "id": "db1ef923-34d7-4923-946a-890c4d2525c0",
   "metadata": {},
   "outputs": [
    {
     "ename": "SyntaxError",
     "evalue": "'continue' not properly in loop (2530398915.py, line 4)",
     "output_type": "error",
     "traceback": [
      "\u001b[0;36m  Input \u001b[0;32mIn [68]\u001b[0;36m\u001b[0m\n\u001b[0;31m    continue\u001b[0m\n\u001b[0m    ^\u001b[0m\n\u001b[0;31mSyntaxError\u001b[0m\u001b[0;31m:\u001b[0m 'continue' not properly in loop\n"
     ]
    }
   ],
   "source": [
    "v = 'volume_m3'\n",
    "if not np.all(np.isfinite(ds1[v].data[-1])):\n",
    "    # This is the last year of hydro output - we will discard anyway\n",
    "    continue\n",
    "if np.allclose(ds1[v].data[-1], ds2[v].data[0]):\n",
    "    # This means that we're OK - the two match\n",
    "    continue"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "521e2175-f324-4bbc-a718-2f747c27d6fa",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "ff122912-5e6b-4b49-a08a-4c722326b7df",
   "metadata": {},
   "outputs": [],
   "source": [
    "   for v in ds1:\n",
    "        if not np.all(np.isfinite(ds1[v].data[-1])):\n",
    "            # This is the last year of hydro output - we will discard anyway\n",
    "            continue\n",
    "        if np.allclose(ds1[v].data[-1], ds2[v].data[0]):\n",
    "            # This means that we're OK - the two match\n",
    "            continue"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "id": "e925dd86-3344-4ed1-bd1f-f97f2708b11b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "False"
      ]
     },
     "execution_count": 66,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "not np.all(np.isfinite(ds1[v].data[-1]))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "id": "4a9ade9d-788a-4a3e-a61e-ff94f48f736c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "False"
      ]
     },
     "execution_count": 65,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "np.allclose(ds1[v].data[-1], ds2[v].data[0])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 64,
   "id": "e7808893-96a2-48ab-8037-773a422bdc31",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'volume_bwl_m3'"
      ]
     },
     "execution_count": 64,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "v"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "cf4dd238-ef11-4c2b-8ccb-25f58bf227bf",
   "metadata": {},
   "outputs": [],
   "source": [
    "            \n",
    "# Now comes the actual run\n",
    "# first using gcm from 2000-end_yr (this is how it is done in Rounce et al., 2023)\n",
    "workflow.execute_entity_task(run_hydro_from_2000_ref_area_2000_hist_gcm, gdirs, end_yr = end_yr)\n",
    "# then using W5E5 from 2000-2019, and GCM from 2020-end_yr (this is how it has normally be done in OGGM)\n",
    "workflow.execute_entity_task(run_hydro_from_2000_ref_area_2000_hist_w5e5, gdirs, end_yr = end_yr)\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "7f63d443-d876-4e84-b142-25aa1aa3740f",
   "metadata": {},
   "outputs": [],
   "source": [
    "gdir = gdirs[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "id": "7069ca58-efde-4d05-8ea8-6076169bb765",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "id": "309f3696-ca87-4c5b-9107-597b90d46577",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "5b15e196-c489-450b-a1fe-b5bae98c2661",
   "metadata": {},
   "outputs": [],
   "source": [
    "ds2[v].data[0] != 0:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "id": "3bb473e3-ecbb-4984-b800-ddb13e5a7561",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "2950032038.9243755"
      ]
     },
     "execution_count": 47,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dh.volume_bwl_m3.data[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "id": "d2a80fef-4322-4ba1-a13e-97b290f5db8d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.DataArray &#x27;volume_m3&#x27; (time: 81)&gt;\n",
       "array([1.521766e+11, 1.514835e+11, 1.506315e+11, 1.498516e+11, 1.488973e+11,\n",
       "       1.478050e+11, 1.464810e+11, 1.459238e+11, 1.448239e+11, 1.436834e+11,\n",
       "       1.427770e+11, 1.425485e+11, 1.419761e+11, 1.412991e+11, 1.400268e+11,\n",
       "       1.394348e+11, 1.384967e+11, 1.373183e+11, 1.366982e+11, 1.356508e+11,\n",
       "       1.347067e+11, 1.340160e+11, 1.331507e+11, 1.322606e+11, 1.314263e+11,\n",
       "       1.307169e+11, 1.300671e+11, 1.293298e+11, 1.286855e+11, 1.273352e+11,\n",
       "       1.265453e+11, 1.256855e+11, 1.246239e+11, 1.235209e+11, 1.228155e+11,\n",
       "       1.218040e+11, 1.204660e+11, 1.191776e+11, 1.182569e+11, 1.165477e+11,\n",
       "       1.154732e+11, 1.143682e+11, 1.134244e+11, 1.127307e+11, 1.117880e+11,\n",
       "       1.106711e+11, 1.093848e+11, 1.085510e+11, 1.067833e+11, 1.051568e+11,\n",
       "       1.036594e+11, 1.029821e+11, 1.024501e+11, 1.017731e+11, 1.013637e+11,\n",
       "       1.004901e+11, 9.944304e+10, 9.807448e+10, 9.707007e+10, 9.621630e+10,\n",
       "       9.503362e+10, 9.410968e+10, 9.325639e+10, 9.239167e+10, 9.118798e+10,\n",
       "       8.964416e+10, 8.837261e+10, 8.749102e+10, 8.653839e+10, 8.567434e+10,\n",
       "       8.448103e+10, 8.337853e+10, 8.197230e+10, 8.068535e+10, 7.907771e+10,\n",
       "       7.816809e+10, 7.697217e+10, 7.561935e+10, 7.422438e+10, 7.320322e+10,\n",
       "       7.234413e+10])\n",
       "Coordinates:\n",
       "  * time            (time) float64 2.02e+03 2.021e+03 ... 2.099e+03 2.1e+03\n",
       "    calendar_year   (time) int64 2020 2021 2022 2023 ... 2097 2098 2099 2100\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",
       "    hydro_year      (time) int64 2020 2021 2022 2023 ... 2097 2098 2099 2100\n",
       "    hydro_month     (time) int64 4 4 4 4 4 4 4 4 4 4 4 ... 4 4 4 4 4 4 4 4 4 4 4\n",
       "Attributes:\n",
       "    description:  Total glacier volume\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_m3'</div><ul class='xr-dim-list'><li><span class='xr-has-index'>time</span>: 81</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-f9b6f011-12f9-4418-bf11-a81261867cfb' class='xr-array-in' type='checkbox' checked><label for='section-f9b6f011-12f9-4418-bf11-a81261867cfb' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>1.522e+11 1.515e+11 1.506e+11 ... 7.422e+10 7.32e+10 7.234e+10</span></div><div class='xr-array-data'><pre>array([1.521766e+11, 1.514835e+11, 1.506315e+11, 1.498516e+11, 1.488973e+11,\n",
       "       1.478050e+11, 1.464810e+11, 1.459238e+11, 1.448239e+11, 1.436834e+11,\n",
       "       1.427770e+11, 1.425485e+11, 1.419761e+11, 1.412991e+11, 1.400268e+11,\n",
       "       1.394348e+11, 1.384967e+11, 1.373183e+11, 1.366982e+11, 1.356508e+11,\n",
       "       1.347067e+11, 1.340160e+11, 1.331507e+11, 1.322606e+11, 1.314263e+11,\n",
       "       1.307169e+11, 1.300671e+11, 1.293298e+11, 1.286855e+11, 1.273352e+11,\n",
       "       1.265453e+11, 1.256855e+11, 1.246239e+11, 1.235209e+11, 1.228155e+11,\n",
       "       1.218040e+11, 1.204660e+11, 1.191776e+11, 1.182569e+11, 1.165477e+11,\n",
       "       1.154732e+11, 1.143682e+11, 1.134244e+11, 1.127307e+11, 1.117880e+11,\n",
       "       1.106711e+11, 1.093848e+11, 1.085510e+11, 1.067833e+11, 1.051568e+11,\n",
       "       1.036594e+11, 1.029821e+11, 1.024501e+11, 1.017731e+11, 1.013637e+11,\n",
       "       1.004901e+11, 9.944304e+10, 9.807448e+10, 9.707007e+10, 9.621630e+10,\n",
       "       9.503362e+10, 9.410968e+10, 9.325639e+10, 9.239167e+10, 9.118798e+10,\n",
       "       8.964416e+10, 8.837261e+10, 8.749102e+10, 8.653839e+10, 8.567434e+10,\n",
       "       8.448103e+10, 8.337853e+10, 8.197230e+10, 8.068535e+10, 7.907771e+10,\n",
       "       7.816809e+10, 7.697217e+10, 7.561935e+10, 7.422438e+10, 7.320322e+10,\n",
       "       7.234413e+10])</pre></div></div></li><li class='xr-section-item'><input id='section-5de0bd66-e38b-4e65-adad-25c6fc1a7392' class='xr-section-summary-in' type='checkbox'  checked><label for='section-5de0bd66-e38b-4e65-adad-25c6fc1a7392' 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'>2.02e+03 2.021e+03 ... 2.1e+03</div><input id='attrs-8a74a121-b25d-43a1-8b25-ff24513c3444' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-8a74a121-b25d-43a1-8b25-ff24513c3444' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ae9c4c6c-0152-4e60-a1ec-aa4045a2b6b5' class='xr-var-data-in' type='checkbox'><label for='data-ae9c4c6c-0152-4e60-a1ec-aa4045a2b6b5' 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([2020., 2021., 2022., 2023., 2024., 2025., 2026., 2027., 2028., 2029.,\n",
       "       2030., 2031., 2032., 2033., 2034., 2035., 2036., 2037., 2038., 2039.,\n",
       "       2040., 2041., 2042., 2043., 2044., 2045., 2046., 2047., 2048., 2049.,\n",
       "       2050., 2051., 2052., 2053., 2054., 2055., 2056., 2057., 2058., 2059.,\n",
       "       2060., 2061., 2062., 2063., 2064., 2065., 2066., 2067., 2068., 2069.,\n",
       "       2070., 2071., 2072., 2073., 2074., 2075., 2076., 2077., 2078., 2079.,\n",
       "       2080., 2081., 2082., 2083., 2084., 2085., 2086., 2087., 2088., 2089.,\n",
       "       2090., 2091., 2092., 2093., 2094., 2095., 2096., 2097., 2098., 2099.,\n",
       "       2100.])</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'>2020 2021 2022 ... 2098 2099 2100</div><input id='attrs-ccd74749-241f-4bc3-97a6-992636e9142e' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ccd74749-241f-4bc3-97a6-992636e9142e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-991aac3d-0002-49ab-915a-54f0521fe20d' class='xr-var-data-in' type='checkbox'><label for='data-991aac3d-0002-49ab-915a-54f0521fe20d' 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([2020, 2021, 2022, 2023, 2024, 2025, 2026, 2027, 2028, 2029, 2030, 2031,\n",
       "       2032, 2033, 2034, 2035, 2036, 2037, 2038, 2039, 2040, 2041, 2042, 2043,\n",
       "       2044, 2045, 2046, 2047, 2048, 2049, 2050, 2051, 2052, 2053, 2054, 2055,\n",
       "       2056, 2057, 2058, 2059, 2060, 2061, 2062, 2063, 2064, 2065, 2066, 2067,\n",
       "       2068, 2069, 2070, 2071, 2072, 2073, 2074, 2075, 2076, 2077, 2078, 2079,\n",
       "       2080, 2081, 2082, 2083, 2084, 2085, 2086, 2087, 2088, 2089, 2090, 2091,\n",
       "       2092, 2093, 2094, 2095, 2096, 2097, 2098, 2099, 2100])</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'>1 1 1 1 1 1 1 1 ... 1 1 1 1 1 1 1 1</div><input id='attrs-31f924ae-f7a0-4f67-8e76-d4678575327d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-31f924ae-f7a0-4f67-8e76-d4678575327d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ff6caa5f-d97b-4e35-bb71-aac1f71632f5' class='xr-var-data-in' type='checkbox'><label for='data-ff6caa5f-d97b-4e35-bb71-aac1f71632f5' 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])</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'>2020 2021 2022 ... 2098 2099 2100</div><input id='attrs-c4f9a14c-9e5f-4f04-90bc-4d7ad689de88' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-c4f9a14c-9e5f-4f04-90bc-4d7ad689de88' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3cf541f4-af8b-4ba6-b7a3-b322d6e52cdc' class='xr-var-data-in' type='checkbox'><label for='data-3cf541f4-af8b-4ba6-b7a3-b322d6e52cdc' 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([2020, 2021, 2022, 2023, 2024, 2025, 2026, 2027, 2028, 2029, 2030, 2031,\n",
       "       2032, 2033, 2034, 2035, 2036, 2037, 2038, 2039, 2040, 2041, 2042, 2043,\n",
       "       2044, 2045, 2046, 2047, 2048, 2049, 2050, 2051, 2052, 2053, 2054, 2055,\n",
       "       2056, 2057, 2058, 2059, 2060, 2061, 2062, 2063, 2064, 2065, 2066, 2067,\n",
       "       2068, 2069, 2070, 2071, 2072, 2073, 2074, 2075, 2076, 2077, 2078, 2079,\n",
       "       2080, 2081, 2082, 2083, 2084, 2085, 2086, 2087, 2088, 2089, 2090, 2091,\n",
       "       2092, 2093, 2094, 2095, 2096, 2097, 2098, 2099, 2100])</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'>4 4 4 4 4 4 4 4 ... 4 4 4 4 4 4 4 4</div><input id='attrs-abddd94f-c080-4ac5-acab-96efeb06ead5' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-abddd94f-c080-4ac5-acab-96efeb06ead5' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8a60dc48-bc23-4854-afca-cc60a367c2b6' class='xr-var-data-in' type='checkbox'><label for='data-8a60dc48-bc23-4854-afca-cc60a367c2b6' 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([4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4,\n",
       "       4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4,\n",
       "       4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4,\n",
       "       4, 4, 4, 4, 4, 4, 4, 4, 4])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-10cc3c1f-10e1-4242-9a51-3900868b501d' class='xr-section-summary-in' type='checkbox'  checked><label for='section-10cc3c1f-10e1-4242-9a51-3900868b501d' 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</dd><dt><span>unit :</span></dt><dd>m 3</dd></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.DataArray 'volume_m3' (time: 81)>\n",
       "array([1.521766e+11, 1.514835e+11, 1.506315e+11, 1.498516e+11, 1.488973e+11,\n",
       "       1.478050e+11, 1.464810e+11, 1.459238e+11, 1.448239e+11, 1.436834e+11,\n",
       "       1.427770e+11, 1.425485e+11, 1.419761e+11, 1.412991e+11, 1.400268e+11,\n",
       "       1.394348e+11, 1.384967e+11, 1.373183e+11, 1.366982e+11, 1.356508e+11,\n",
       "       1.347067e+11, 1.340160e+11, 1.331507e+11, 1.322606e+11, 1.314263e+11,\n",
       "       1.307169e+11, 1.300671e+11, 1.293298e+11, 1.286855e+11, 1.273352e+11,\n",
       "       1.265453e+11, 1.256855e+11, 1.246239e+11, 1.235209e+11, 1.228155e+11,\n",
       "       1.218040e+11, 1.204660e+11, 1.191776e+11, 1.182569e+11, 1.165477e+11,\n",
       "       1.154732e+11, 1.143682e+11, 1.134244e+11, 1.127307e+11, 1.117880e+11,\n",
       "       1.106711e+11, 1.093848e+11, 1.085510e+11, 1.067833e+11, 1.051568e+11,\n",
       "       1.036594e+11, 1.029821e+11, 1.024501e+11, 1.017731e+11, 1.013637e+11,\n",
       "       1.004901e+11, 9.944304e+10, 9.807448e+10, 9.707007e+10, 9.621630e+10,\n",
       "       9.503362e+10, 9.410968e+10, 9.325639e+10, 9.239167e+10, 9.118798e+10,\n",
       "       8.964416e+10, 8.837261e+10, 8.749102e+10, 8.653839e+10, 8.567434e+10,\n",
       "       8.448103e+10, 8.337853e+10, 8.197230e+10, 8.068535e+10, 7.907771e+10,\n",
       "       7.816809e+10, 7.697217e+10, 7.561935e+10, 7.422438e+10, 7.320322e+10,\n",
       "       7.234413e+10])\n",
       "Coordinates:\n",
       "  * time            (time) float64 2.02e+03 2.021e+03 ... 2.099e+03 2.1e+03\n",
       "    calendar_year   (time) int64 2020 2021 2022 2023 ... 2097 2098 2099 2100\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",
       "    hydro_year      (time) int64 2020 2021 2022 2023 ... 2097 2098 2099 2100\n",
       "    hydro_month     (time) int64 4 4 4 4 4 4 4 4 4 4 4 ... 4 4 4 4 4 4 4 4 4 4 4\n",
       "Attributes:\n",
       "    description:  Total glacier volume\n",
       "    unit:         m 3"
      ]
     },
     "execution_count": 48,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.volume_m3"
   ]
  },
  {
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   "execution_count": 34,
   "id": "40ce506e-2c98-4f61-93b9-5d10ea6a1229",
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       "  text-overflow: ellipsis;\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-var-name:hover,\n",
       ".xr-var-dims:hover,\n",
       ".xr-var-dtype:hover,\n",
       ".xr-attrs dt:hover {\n",
       "  overflow: visible;\n",
       "  width: auto;\n",
       "  z-index: 1;\n",
       "}\n",
       "\n",
       ".xr-var-attrs,\n",
       ".xr-var-data {\n",
       "  display: none;\n",
       "  background-color: var(--xr-background-color) !important;\n",
       "  padding-bottom: 5px !important;\n",
       "}\n",
       "\n",
       ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
       ".xr-var-data-in:checked ~ .xr-var-data {\n",
       "  display: block;\n",
       "}\n",
       "\n",
       ".xr-var-data > table {\n",
       "  float: right;\n",
       "}\n",
       "\n",
       ".xr-var-name span,\n",
       ".xr-var-data,\n",
       ".xr-attrs {\n",
       "  padding-left: 25px !important;\n",
       "}\n",
       "\n",
       ".xr-attrs,\n",
       ".xr-var-attrs,\n",
       ".xr-var-data {\n",
       "  grid-column: 1 / -1;\n",
       "}\n",
       "\n",
       "dl.xr-attrs {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  display: grid;\n",
       "  grid-template-columns: 125px auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt,\n",
       ".xr-attrs dd {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  float: left;\n",
       "  padding-right: 10px;\n",
       "  width: auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt {\n",
       "  font-weight: normal;\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-attrs dt:hover span {\n",
       "  display: inline-block;\n",
       "  background: var(--xr-background-color);\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-attrs dd {\n",
       "  grid-column: 2;\n",
       "  white-space: pre-wrap;\n",
       "  word-break: break-all;\n",
       "}\n",
       "\n",
       ".xr-icon-database,\n",
       ".xr-icon-file-text2 {\n",
       "  display: inline-block;\n",
       "  vertical-align: middle;\n",
       "  width: 1em;\n",
       "  height: 1.5em !important;\n",
       "  stroke-width: 0;\n",
       "  stroke: currentColor;\n",
       "  fill: currentColor;\n",
       "}\n",
       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt;\n",
       "Dimensions:                       (time: 102, month_2d: 12)\n",
       "Coordinates:\n",
       "  * time                          (time) float64 2e+03 2.001e+03 ... 2.1e+03\n",
       "    calendar_year                 (time) int64 2000 2001 2002 ... 2098 2099 2100\n",
       "    calendar_month                (time) int64 1 1 1 1 1 1 1 1 ... 1 1 1 1 1 1 1\n",
       "    hydro_year                    (time) int64 2000 2001 2002 ... 2098 2099 2100\n",
       "    hydro_month                   (time) int64 4 4 4 4 4 4 4 4 ... 4 4 4 4 4 4 4\n",
       "  * month_2d                      (month_2d) int64 1 2 3 4 5 6 7 8 9 10 11 12\n",
       "    hydro_month_2d                (month_2d) int64 4 5 6 7 8 9 10 11 12 1 2 3\n",
       "    calendar_month_2d             (month_2d) int64 1 2 3 4 5 6 7 8 9 10 11 12\n",
       "Data variables: (12/26)\n",
       "    volume_m3                     (time) float64 1.607e+11 ... 7.234e+10\n",
       "    volume_bsl_m3                 (time) float64 0.0 0.0 0.0 0.0 ... 0.0 0.0 0.0\n",
       "    volume_bwl_m3                 (time) float64 2.95e+09 2.95e+09 ... 1.535e+08\n",
       "    area_m2                       (time) float64 4.414e+08 ... 3.965e+08\n",
       "    length_m                      (time) float64 4.92e+04 4.92e+04 ... 4.12e+04\n",
       "    calving_m3                    (time) float64 0.0 0.0 0.0 0.0 ... 0.0 0.0 0.0\n",
       "    ...                            ...\n",
       "    snowfall_on_glacier_monthly   (time, month_2d) float64 1.254e+11 ... nan\n",
       "    snow_bucket                   (time) float64 0.0 3.616e-05 ... 5.78e+10\n",
       "    snow_bucket_monthly           (time, month_2d) float64 0.0 4e-06 ... 0.0 0.0\n",
       "    model_mb                      (time) float64 4.454e+11 -1.153e+11 ... nan\n",
       "    residual_mb                   (time) float64 -4.101e+09 -4.07e+09 ... nan\n",
       "    residual_mb_monthly           (time, month_2d) float64 0.0 0.0 ... nan nan\n",
       "Attributes:\n",
       "    description:          OGGM model output\n",
       "    oggm_version:         1.3.2.dev394+gb45b78b\n",
       "    calendar:             365-day no leap\n",
       "    creation_date:        2023-05-12 07:34:16\n",
       "    water_level:          491.3637909324272\n",
       "    glen_a:               7.830101237437472e-24\n",
       "    fs:                   0\n",
       "    mb_model_class:       MultipleFlowlineMassBalance\n",
       "    mb_model_hemisphere:  nh</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-f35c78c9-deed-4f95-a429-65319c669df0' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-f35c78c9-deed-4f95-a429-65319c669df0' 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>: 102</li><li><span class='xr-has-index'>month_2d</span>: 12</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-26b4e6e7-8a13-4d9c-800a-01ab82591bc5' class='xr-section-summary-in' type='checkbox'  checked><label for='section-26b4e6e7-8a13-4d9c-800a-01ab82591bc5' class='xr-section-summary' >Coordinates: <span>(8)</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'>2e+03 2.001e+03 ... 2.1e+03</div><input id='attrs-31d4975e-9b00-45ce-bb0f-c8b3e9f8c9d2' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-31d4975e-9b00-45ce-bb0f-c8b3e9f8c9d2' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-87bebc71-03c1-458a-949d-d6fe923f6859' class='xr-var-data-in' type='checkbox'><label for='data-87bebc71-03c1-458a-949d-d6fe923f6859' 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([2000., 2001., 2002., 2003., 2004., 2005., 2006., 2007., 2008., 2009.,\n",
       "       2010., 2011., 2012., 2013., 2014., 2015., 2016., 2017., 2018., 2019.,\n",
       "       2020., 2020., 2021., 2022., 2023., 2024., 2025., 2026., 2027., 2028.,\n",
       "       2029., 2030., 2031., 2032., 2033., 2034., 2035., 2036., 2037., 2038.,\n",
       "       2039., 2040., 2041., 2042., 2043., 2044., 2045., 2046., 2047., 2048.,\n",
       "       2049., 2050., 2051., 2052., 2053., 2054., 2055., 2056., 2057., 2058.,\n",
       "       2059., 2060., 2061., 2062., 2063., 2064., 2065., 2066., 2067., 2068.,\n",
       "       2069., 2070., 2071., 2072., 2073., 2074., 2075., 2076., 2077., 2078.,\n",
       "       2079., 2080., 2081., 2082., 2083., 2084., 2085., 2086., 2087., 2088.,\n",
       "       2089., 2090., 2091., 2092., 2093., 2094., 2095., 2096., 2097., 2098.,\n",
       "       2099., 2100.])</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'>2000 2001 2002 ... 2098 2099 2100</div><input id='attrs-2d8b68ec-db7d-442e-bb5f-5ea7066d9a41' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-2d8b68ec-db7d-442e-bb5f-5ea7066d9a41' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e2e70d21-b304-4ab1-881c-842a67ab4eab' class='xr-var-data-in' type='checkbox'><label for='data-e2e70d21-b304-4ab1-881c-842a67ab4eab' 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([2000, 2001, 2002, 2003, 2004, 2005, 2006, 2007, 2008, 2009, 2010,\n",
       "       2011, 2012, 2013, 2014, 2015, 2016, 2017, 2018, 2019, 2020, 2020,\n",
       "       2021, 2022, 2023, 2024, 2025, 2026, 2027, 2028, 2029, 2030, 2031,\n",
       "       2032, 2033, 2034, 2035, 2036, 2037, 2038, 2039, 2040, 2041, 2042,\n",
       "       2043, 2044, 2045, 2046, 2047, 2048, 2049, 2050, 2051, 2052, 2053,\n",
       "       2054, 2055, 2056, 2057, 2058, 2059, 2060, 2061, 2062, 2063, 2064,\n",
       "       2065, 2066, 2067, 2068, 2069, 2070, 2071, 2072, 2073, 2074, 2075,\n",
       "       2076, 2077, 2078, 2079, 2080, 2081, 2082, 2083, 2084, 2085, 2086,\n",
       "       2087, 2088, 2089, 2090, 2091, 2092, 2093, 2094, 2095, 2096, 2097,\n",
       "       2098, 2099, 2100])</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'>1 1 1 1 1 1 1 1 ... 1 1 1 1 1 1 1 1</div><input id='attrs-1c1f2472-12f2-438e-ab06-498529f364cd' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-1c1f2472-12f2-438e-ab06-498529f364cd' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e244efa6-9563-4ec7-96b1-b3082cb892b7' class='xr-var-data-in' type='checkbox'><label for='data-e244efa6-9563-4ec7-96b1-b3082cb892b7' 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,\n",
       "       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,\n",
       "       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])</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'>2000 2001 2002 ... 2098 2099 2100</div><input id='attrs-a48e5601-2895-4c99-9738-b127cbf62a64' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a48e5601-2895-4c99-9738-b127cbf62a64' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6b59c465-62a0-497c-be4b-ac71a3cc7847' class='xr-var-data-in' type='checkbox'><label for='data-6b59c465-62a0-497c-be4b-ac71a3cc7847' 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([2000, 2001, 2002, 2003, 2004, 2005, 2006, 2007, 2008, 2009, 2010,\n",
       "       2011, 2012, 2013, 2014, 2015, 2016, 2017, 2018, 2019, 2020, 2020,\n",
       "       2021, 2022, 2023, 2024, 2025, 2026, 2027, 2028, 2029, 2030, 2031,\n",
       "       2032, 2033, 2034, 2035, 2036, 2037, 2038, 2039, 2040, 2041, 2042,\n",
       "       2043, 2044, 2045, 2046, 2047, 2048, 2049, 2050, 2051, 2052, 2053,\n",
       "       2054, 2055, 2056, 2057, 2058, 2059, 2060, 2061, 2062, 2063, 2064,\n",
       "       2065, 2066, 2067, 2068, 2069, 2070, 2071, 2072, 2073, 2074, 2075,\n",
       "       2076, 2077, 2078, 2079, 2080, 2081, 2082, 2083, 2084, 2085, 2086,\n",
       "       2087, 2088, 2089, 2090, 2091, 2092, 2093, 2094, 2095, 2096, 2097,\n",
       "       2098, 2099, 2100])</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'>4 4 4 4 4 4 4 4 ... 4 4 4 4 4 4 4 4</div><input id='attrs-a69182bd-14af-437d-9657-034b2dcd9420' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a69182bd-14af-437d-9657-034b2dcd9420' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-734ae809-ca90-40d2-97a7-2c617ecbb9f4' class='xr-var-data-in' type='checkbox'><label for='data-734ae809-ca90-40d2-97a7-2c617ecbb9f4' 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([4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4,\n",
       "       4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4,\n",
       "       4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4,\n",
       "       4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4,\n",
       "       4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4, 4])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>month_2d</span></div><div class='xr-var-dims'>(month_2d)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>1 2 3 4 5 6 7 8 9 10 11 12</div><input id='attrs-db1048a5-2f7a-4dbb-9b2a-9be363593fa2' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-db1048a5-2f7a-4dbb-9b2a-9be363593fa2' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ae61a8fe-a281-437f-9048-95ae7394273d' class='xr-var-data-in' type='checkbox'><label for='data-ae61a8fe-a281-437f-9048-95ae7394273d' 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,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11, 12])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>hydro_month_2d</span></div><div class='xr-var-dims'>(month_2d)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>4 5 6 7 8 9 10 11 12 1 2 3</div><input id='attrs-e16788cc-cbe5-48ca-a839-8ef86d33e7fd' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-e16788cc-cbe5-48ca-a839-8ef86d33e7fd' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4aac95d4-8503-494f-86a4-7b4c49edeece' class='xr-var-data-in' type='checkbox'><label for='data-4aac95d4-8503-494f-86a4-7b4c49edeece' 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,  5,  6,  7,  8,  9, 10, 11, 12,  1,  2,  3])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>calendar_month_2d</span></div><div class='xr-var-dims'>(month_2d)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>1 2 3 4 5 6 7 8 9 10 11 12</div><input id='attrs-f9cfb93c-b992-4f0a-8ead-db61f9380ed4' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-f9cfb93c-b992-4f0a-8ead-db61f9380ed4' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-963a8127-2944-4732-a796-374285e38e61' class='xr-var-data-in' type='checkbox'><label for='data-963a8127-2944-4732-a796-374285e38e61' 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,  2,  3,  4,  5,  6,  7,  8,  9, 10, 11, 12])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-f0a562b9-7f20-4c6d-8bee-5b474fe5e47f' class='xr-section-summary-in' type='checkbox'  ><label for='section-f0a562b9-7f20-4c6d-8bee-5b474fe5e47f' class='xr-section-summary' >Data variables: <span>(26)</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_m3</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>1.607e+11 1.612e+11 ... 7.234e+10</div><input id='attrs-ab60b527-8286-4cb4-8d23-e70b96b156fb' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ab60b527-8286-4cb4-8d23-e70b96b156fb' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-77519878-15ae-4c2d-8656-8f2e5df39816' class='xr-var-data-in' type='checkbox'><label for='data-77519878-15ae-4c2d-8656-8f2e5df39816' 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>Total glacier volume</dd><dt><span>unit :</span></dt><dd>m 3</dd></dl></div><div class='xr-var-data'><pre>array([1.60719104e+11, 1.61214041e+11, 1.61085883e+11, 1.60539850e+11,\n",
       "       1.60058309e+11, 1.60112391e+11, 1.59960368e+11, 1.59512371e+11,\n",
       "       1.58945736e+11, 1.58957794e+11, 1.58468583e+11, 1.57729492e+11,\n",
       "       1.57300702e+11, 1.56654468e+11, 1.55943199e+11, 1.55533331e+11,\n",
       "       1.55179285e+11, 1.54369489e+11, 1.53786952e+11, 1.52965929e+11,\n",
       "       1.52176563e+11, 1.52176563e+11, 1.51483536e+11, 1.50631479e+11,\n",
       "       1.49851597e+11, 1.48897316e+11, 1.47804959e+11, 1.46480958e+11,\n",
       "       1.45923849e+11, 1.44823902e+11, 1.43683378e+11, 1.42776962e+11,\n",
       "       1.42548517e+11, 1.41976071e+11, 1.41299094e+11, 1.40026835e+11,\n",
       "       1.39434767e+11, 1.38496705e+11, 1.37318327e+11, 1.36698207e+11,\n",
       "       1.35650834e+11, 1.34706719e+11, 1.34015976e+11, 1.33150746e+11,\n",
       "       1.32260559e+11, 1.31426268e+11, 1.30716884e+11, 1.30067079e+11,\n",
       "       1.29329805e+11, 1.28685470e+11, 1.27335230e+11, 1.26545258e+11,\n",
       "       1.25685532e+11, 1.24623902e+11, 1.23520863e+11, 1.22815502e+11,\n",
       "       1.21803964e+11, 1.20466006e+11, 1.19177650e+11, 1.18256934e+11,\n",
       "       1.16547693e+11, 1.15473160e+11, 1.14368206e+11, 1.13424409e+11,\n",
       "       1.12730657e+11, 1.11788000e+11, 1.10671095e+11, 1.09384759e+11,\n",
       "       1.08550978e+11, 1.06783310e+11, 1.05156849e+11, 1.03659368e+11,\n",
       "       1.02982140e+11, 1.02450066e+11, 1.01773054e+11, 1.01363717e+11,\n",
       "       1.00490089e+11, 9.94430362e+10, 9.80744783e+10, 9.70700746e+10,\n",
       "       9.62162952e+10, 9.50336150e+10, 9.41096823e+10, 9.32563938e+10,\n",
       "       9.23916707e+10, 9.11879770e+10, 8.96441631e+10, 8.83726137e+10,\n",
       "       8.74910176e+10, 8.65383856e+10, 8.56743395e+10, 8.44810322e+10,\n",
       "       8.33785280e+10, 8.19722966e+10, 8.06853477e+10, 7.90777133e+10,\n",
       "       7.81680922e+10, 7.69721705e+10, 7.56193544e+10, 7.42243834e+10,\n",
       "       7.32032186e+10, 7.23441330e+10])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>volume_bsl_m3</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0 0.0 0.0 0.0 ... 0.0 0.0 0.0 0.0</div><input id='attrs-254d1a71-2d94-4ca2-bfc3-4a694898cd74' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-254d1a71-2d94-4ca2-bfc3-4a694898cd74' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6d708417-05c4-4391-acba-a2164031cd8b' class='xr-var-data-in' type='checkbox'><label for='data-6d708417-05c4-4391-acba-a2164031cd8b' 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>Glacier volume below sea-level</dd><dt><span>unit :</span></dt><dd>m 3</dd></dl></div><div class='xr-var-data'><pre>array([0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
       "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
       "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
       "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
       "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
       "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>volume_bwl_m3</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>2.95e+09 2.95e+09 ... 1.535e+08</div><input id='attrs-28ca05e1-4a01-44a6-a75c-9288db1560d1' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-28ca05e1-4a01-44a6-a75c-9288db1560d1' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0a0d70e3-1bab-4053-a008-1e8f519fab97' class='xr-var-data-in' type='checkbox'><label for='data-0a0d70e3-1bab-4053-a008-1e8f519fab97' 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>Glacier volume below water-level</dd><dt><span>unit :</span></dt><dd>m 3</dd></dl></div><div class='xr-var-data'><pre>array([2.95003204e+09, 2.95003204e+09, 2.95003204e+09, 2.95003204e+09,\n",
       "       2.95003204e+09, 2.95003204e+09, 2.95003204e+09, 2.95003204e+09,\n",
       "       2.95003204e+09, 2.95003204e+09, 2.95003204e+09, 2.94719596e+09,\n",
       "       2.94532092e+09, 2.94302359e+09, 2.94024149e+09, 2.93786250e+09,\n",
       "       2.93510261e+09, 2.93080980e+09, 2.92708550e+09, 2.92245726e+09,\n",
       "       2.91650674e+09, 2.02959438e+09, 2.02959438e+09, 2.02959438e+09,\n",
       "       2.02959438e+09, 2.02311214e+09, 2.01633581e+09, 2.00638608e+09,\n",
       "       2.00081432e+09, 1.99165341e+09, 1.98226281e+09, 1.97019106e+09,\n",
       "       1.96018703e+09, 1.94823013e+09, 1.93566855e+09, 1.91731018e+09,\n",
       "       1.89924681e+09, 1.87821040e+09, 1.85454401e+09, 1.82410912e+09,\n",
       "       1.78931599e+09, 1.75765955e+09, 1.72304088e+09, 1.69397258e+09,\n",
       "       1.66419784e+09, 1.63596756e+09, 1.60274207e+09, 1.57250500e+09,\n",
       "       1.53170732e+09, 1.49657163e+09, 1.45218700e+09, 1.42206113e+09,\n",
       "       1.37854218e+09, 1.33357818e+09, 1.28395768e+09, 1.24020691e+09,\n",
       "       1.19098255e+09, 1.13395141e+09, 1.07679947e+09, 1.02919480e+09,\n",
       "       9.71344011e+08, 9.14338642e+08, 8.62409380e+08, 8.18496940e+08,\n",
       "       7.85911113e+08, 7.56311978e+08, 7.26815112e+08, 6.95736829e+08,\n",
       "       6.67758104e+08, 6.36868256e+08, 5.99771467e+08, 5.63291884e+08,\n",
       "       5.34150383e+08, 5.08742323e+08, 4.77365040e+08, 4.51808821e+08,\n",
       "       4.19647541e+08, 3.79710123e+08, 3.48173044e+08, 3.16074421e+08,\n",
       "       2.73961167e+08, 2.33257079e+08, 2.04859536e+08, 1.82005135e+08,\n",
       "       1.66844859e+08, 1.56693848e+08, 1.53481275e+08, 1.53481275e+08,\n",
       "       1.53481275e+08, 1.53481275e+08, 1.53481275e+08, 1.53481275e+08,\n",
       "       1.53481275e+08, 1.53481275e+08, 1.53481275e+08, 1.53481275e+08,\n",
       "       1.53481275e+08, 1.53481275e+08, 1.53481275e+08, 1.53481275e+08,\n",
       "       1.53481275e+08, 1.53481275e+08])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>area_m2</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>4.414e+08 4.415e+08 ... 3.965e+08</div><input id='attrs-0fd1ad75-ab47-44fa-b080-0d13c35aaad3' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-0fd1ad75-ab47-44fa-b080-0d13c35aaad3' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-501cded0-d43f-4947-83f4-db243f9645bd' class='xr-var-data-in' type='checkbox'><label for='data-501cded0-d43f-4947-83f4-db243f9645bd' 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>Total glacier area</dd><dt><span>unit :</span></dt><dd>m 2</dd></dl></div><div class='xr-var-data'><pre>array([4.41402668e+08, 4.41513030e+08, 4.41492670e+08, 4.41376007e+08,\n",
       "       4.41269208e+08, 4.41272654e+08, 4.41256356e+08, 4.41176349e+08,\n",
       "       4.41072136e+08, 4.41104256e+08, 4.41017309e+08, 4.40864089e+08,\n",
       "       4.40786729e+08, 4.40661341e+08, 4.40516803e+08, 4.40453308e+08,\n",
       "       4.40385030e+08, 4.40224060e+08, 4.40103502e+08, 4.39933802e+08,\n",
       "       4.39761533e+08, 4.39761533e+08, 4.39615490e+08, 4.39443985e+08,\n",
       "       4.39270453e+08, 4.39063077e+08, 4.38848967e+08, 4.38561710e+08,\n",
       "       4.38449372e+08, 4.38206201e+08, 4.37940699e+08, 4.37726735e+08,\n",
       "       4.37653402e+08, 4.37507052e+08, 4.37348603e+08, 4.37052304e+08,\n",
       "       4.36900013e+08, 4.36673941e+08, 4.36385558e+08, 4.36209507e+08,\n",
       "       4.35941683e+08, 4.35703007e+08, 4.33897152e+08, 4.33670722e+08,\n",
       "       4.33441071e+08, 4.33220896e+08, 4.33009870e+08, 4.32825460e+08,\n",
       "       4.32601010e+08, 4.32423782e+08, 4.32089800e+08, 4.31887090e+08,\n",
       "       4.31656444e+08, 4.31378229e+08, 4.31080779e+08, 4.30873846e+08,\n",
       "       4.30588935e+08, 4.30230080e+08, 4.29908124e+08, 4.28878431e+08,\n",
       "       4.28455067e+08, 4.28164964e+08, 4.26520467e+08, 4.25380329e+08,\n",
       "       4.23921757e+08, 4.22624783e+08, 4.22334992e+08, 4.22002129e+08,\n",
       "       4.20800069e+08, 4.20368242e+08, 4.19976889e+08, 4.19609265e+08,\n",
       "       4.18523902e+08, 4.18344190e+08, 4.18135877e+08, 4.17992146e+08,\n",
       "       4.17744563e+08, 4.16606941e+08, 4.16254583e+08, 4.15966642e+08,\n",
       "       4.15713378e+08, 4.13990995e+08, 4.13748800e+08, 4.11351273e+08,\n",
       "       4.09493778e+08, 4.06361976e+08, 4.05194846e+08, 4.04897996e+08,\n",
       "       4.04671178e+08, 4.02819252e+08, 4.02609114e+08, 4.02331418e+08,\n",
       "       4.02057629e+08, 4.00244423e+08, 3.99936029e+08, 3.99576395e+08,\n",
       "       3.99340216e+08, 3.99046230e+08, 3.97242954e+08, 3.96915727e+08,\n",
       "       3.96682774e+08, 3.96465850e+08])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>length_m</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>4.92e+04 4.92e+04 ... 4.12e+04</div><input id='attrs-2ed7c1c1-2f82-44d7-94a9-2e4c81c245c3' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-2ed7c1c1-2f82-44d7-94a9-2e4c81c245c3' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d3d208e5-d171-49c8-b6b4-3e8026f70afd' class='xr-var-data-in' type='checkbox'><label for='data-d3d208e5-d171-49c8-b6b4-3e8026f70afd' 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>Glacier length</dd><dt><span>unit :</span></dt><dd>m</dd></dl></div><div class='xr-var-data'><pre>array([49200., 49200., 49200., 49200., 49200., 49200., 49200., 49200.,\n",
       "       49200., 49200., 49200., 49200., 49200., 49200., 49200., 49200.,\n",
       "       49200., 49200., 49200., 49200., 49200., 49200., 49200., 49200.,\n",
       "       49200., 49200., 49200., 49200., 49200., 49200., 49200., 49200.,\n",
       "       49200., 49200., 49200., 49200., 49200., 49200., 49200., 49200.,\n",
       "       49200., 49200., 48800., 48800., 48800., 48800., 48800., 48800.,\n",
       "       48800., 48800., 48800., 48800., 48800., 48800., 48800., 48800.,\n",
       "       48800., 48800., 48800., 48400., 48400., 48400., 48000., 47600.,\n",
       "       47200., 46800., 46800., 46800., 46400., 46400., 46400., 46400.,\n",
       "       46000., 46000., 46000., 46000., 46000., 45600., 45600., 45600.,\n",
       "       45600., 44800., 44800., 44000., 43600., 42800., 42400., 42400.,\n",
       "       42400., 42000., 42000., 42000., 42000., 41600., 41600., 41600.,\n",
       "       41600., 41600., 41200., 41200., 41200., 41200.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>calving_m3</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0 0.0 0.0 0.0 ... 0.0 0.0 0.0 0.0</div><input id='attrs-7987357c-f96a-41af-b701-6ac3989ec1c7' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-7987357c-f96a-41af-b701-6ac3989ec1c7' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d0990f4f-534f-49cc-87f6-28f8660554be' class='xr-var-data-in' type='checkbox'><label for='data-d0990f4f-534f-49cc-87f6-28f8660554be' 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>Total accumulated calving flux</dd><dt><span>unit :</span></dt><dd>m 3</dd></dl></div><div class='xr-var-data'><pre>array([0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
       "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
       "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
       "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
       "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
       "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>calving_rate_myr</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0 0.0 0.0 0.0 ... 0.0 0.0 0.0 0.0</div><input id='attrs-e50bba41-0e42-4d81-812c-aefe5016fe29' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e50bba41-0e42-4d81-812c-aefe5016fe29' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-fb694c15-9095-4cb2-b6b0-1f7b4136359e' class='xr-var-data-in' type='checkbox'><label for='data-fb694c15-9095-4cb2-b6b0-1f7b4136359e' 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>Calving rate</dd><dt><span>unit :</span></dt><dd>m yr-1</dd></dl></div><div class='xr-var-data'><pre>array([0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
       "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
       "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
       "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
       "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.,\n",
       "       0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>off_area</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>1.409e-08 61.64 ... 4.472e+07 nan</div><input id='attrs-cb2e50a9-5a7f-407f-acbc-c5d95eb52568' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-cb2e50a9-5a7f-407f-acbc-c5d95eb52568' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-17f6e404-339d-4424-a463-03b7a5494456' class='xr-var-data-in' type='checkbox'><label for='data-17f6e404-339d-4424-a463-03b7a5494456' 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>Off-glacier area</dd><dt><span>unit :</span></dt><dd>m 2</dd></dl></div><div class='xr-var-data'><pre>array([1.40862539e-08, 6.16409567e+01, 2.23489877e+04, 7.81209281e+04,\n",
       "       1.50861209e+05, 1.56607968e+05, 1.69629593e+05, 2.27407645e+05,\n",
       "       3.30531703e+05, 3.03127439e+05, 3.85359175e+05, 5.38578738e+05,\n",
       "       6.15938834e+05, 7.41327139e+05, 8.85864441e+05, 9.49360146e+05,\n",
       "       1.01763754e+06, 1.17860733e+06, 1.29916593e+06, 1.46886624e+06,\n",
       "                  nan, 1.64113448e+06, 1.78717776e+06, 1.95868293e+06,\n",
       "       2.13221508e+06, 2.33959068e+06, 2.55370054e+06, 2.84095801e+06,\n",
       "       2.95329553e+06, 3.19646698e+06, 3.46196876e+06, 3.67593236e+06,\n",
       "       3.74926539e+06, 3.89561604e+06, 4.05406454e+06, 4.35036421e+06,\n",
       "       4.50265522e+06, 4.72872728e+06, 5.01710952e+06, 5.19316034e+06,\n",
       "       5.46098524e+06, 5.69966109e+06, 7.50551622e+06, 7.73194593e+06,\n",
       "       7.96159691e+06, 8.18177163e+06, 8.39279738e+06, 8.57720827e+06,\n",
       "       8.80165819e+06, 8.97888550e+06, 9.31286749e+06, 9.51557828e+06,\n",
       "       9.74622424e+06, 1.00244388e+07, 1.03218885e+07, 1.05288215e+07,\n",
       "       1.08137331e+07, 1.11725882e+07, 1.14945442e+07, 1.25242369e+07,\n",
       "       1.29476004e+07, 1.32377041e+07, 1.48822013e+07, 1.60223393e+07,\n",
       "       1.74809109e+07, 1.87778853e+07, 1.90676755e+07, 1.94005388e+07,\n",
       "       2.06025983e+07, 2.10344254e+07, 2.14257785e+07, 2.17934025e+07,\n",
       "       2.28787655e+07, 2.30584781e+07, 2.32667909e+07, 2.34105215e+07,\n",
       "       2.36581044e+07, 2.47957266e+07, 2.51480846e+07, 2.54360263e+07,\n",
       "       2.56892898e+07, 2.74116730e+07, 2.76538675e+07, 3.00513946e+07,\n",
       "       3.19088900e+07, 3.50406919e+07, 3.62078218e+07, 3.65046719e+07,\n",
       "       3.67314899e+07, 3.85834157e+07, 3.87935541e+07, 3.90712493e+07,\n",
       "       3.93450390e+07, 4.11582444e+07, 4.14666390e+07, 4.18262730e+07,\n",
       "       4.20624520e+07, 4.23564377e+07, 4.41597134e+07, 4.44869411e+07,\n",
       "       4.47198939e+07,            nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>on_area</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>4.414e+08 4.415e+08 ... nan</div><input id='attrs-15844182-b0a6-423c-ab0f-32886b5b0a62' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-15844182-b0a6-423c-ab0f-32886b5b0a62' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-178bc60c-f077-4405-921c-e4f3df25ffc2' class='xr-var-data-in' type='checkbox'><label for='data-178bc60c-f077-4405-921c-e4f3df25ffc2' 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>unit :</span></dt><dd>m 2</dd><dt><span>description :</span></dt><dd>On-glacier area</dd></dl></div><div class='xr-var-data'><pre>array([4.41402668e+08, 4.41513030e+08, 4.41492670e+08, 4.41376007e+08,\n",
       "       4.41269208e+08, 4.41272654e+08, 4.41256356e+08, 4.41176349e+08,\n",
       "       4.41072136e+08, 4.41104256e+08, 4.41017309e+08, 4.40864089e+08,\n",
       "       4.40786729e+08, 4.40661341e+08, 4.40516803e+08, 4.40453308e+08,\n",
       "       4.40385030e+08, 4.40224060e+08, 4.40103502e+08, 4.39933802e+08,\n",
       "                  nan, 4.39761533e+08, 4.39615490e+08, 4.39443985e+08,\n",
       "       4.39270453e+08, 4.39063077e+08, 4.38848967e+08, 4.38561710e+08,\n",
       "       4.38449372e+08, 4.38206201e+08, 4.37940699e+08, 4.37726735e+08,\n",
       "       4.37653402e+08, 4.37507052e+08, 4.37348603e+08, 4.37052304e+08,\n",
       "       4.36900013e+08, 4.36673941e+08, 4.36385558e+08, 4.36209507e+08,\n",
       "       4.35941683e+08, 4.35703007e+08, 4.33897152e+08, 4.33670722e+08,\n",
       "       4.33441071e+08, 4.33220896e+08, 4.33009870e+08, 4.32825460e+08,\n",
       "       4.32601010e+08, 4.32423782e+08, 4.32089800e+08, 4.31887090e+08,\n",
       "       4.31656444e+08, 4.31378229e+08, 4.31080779e+08, 4.30873846e+08,\n",
       "       4.30588935e+08, 4.30230080e+08, 4.29908124e+08, 4.28878431e+08,\n",
       "       4.28455067e+08, 4.28164964e+08, 4.26520467e+08, 4.25380329e+08,\n",
       "       4.23921757e+08, 4.22624783e+08, 4.22334992e+08, 4.22002129e+08,\n",
       "       4.20800069e+08, 4.20368242e+08, 4.19976889e+08, 4.19609265e+08,\n",
       "       4.18523902e+08, 4.18344190e+08, 4.18135877e+08, 4.17992146e+08,\n",
       "       4.17744563e+08, 4.16606941e+08, 4.16254583e+08, 4.15966642e+08,\n",
       "       4.15713378e+08, 4.13990995e+08, 4.13748800e+08, 4.11351273e+08,\n",
       "       4.09493778e+08, 4.06361976e+08, 4.05194846e+08, 4.04897996e+08,\n",
       "       4.04671178e+08, 4.02819252e+08, 4.02609114e+08, 4.02331418e+08,\n",
       "       4.02057629e+08, 4.00244423e+08, 3.99936029e+08, 3.99576395e+08,\n",
       "       3.99340216e+08, 3.99046230e+08, 3.97242954e+08, 3.96915727e+08,\n",
       "       3.96682774e+08,            nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>melt_off_glacier</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>1.605e-05 8.443e+04 ... nan</div><input id='attrs-354d7525-c165-4598-b7b6-906ba1e5dbbb' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-354d7525-c165-4598-b7b6-906ba1e5dbbb' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3c8e2703-68fa-4c00-ab20-11b02491d840' class='xr-var-data-in' type='checkbox'><label for='data-3c8e2703-68fa-4c00-ab20-11b02491d840' 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>Off-glacier melt</dd><dt><span>unit :</span></dt><dd>kg yr-1</dd></dl></div><div class='xr-var-data'><pre>array([1.60546206e-05, 8.44252013e+04, 6.68075726e+06, 4.36242183e+07,\n",
       "       1.91695805e+08, 2.17745496e+08, 2.15484692e+08, 2.83952218e+08,\n",
       "       3.78888225e+08, 5.69026008e+08, 4.52935167e+08, 5.79474275e+08,\n",
       "       1.00542467e+09, 1.14163259e+09, 1.13867605e+09, 1.86319521e+09,\n",
       "       1.80810420e+09, 1.77132598e+09, 1.71930208e+09, 2.18919787e+09,\n",
       "                  nan, 1.50338043e+09, 3.21722596e+09, 3.61031037e+09,\n",
       "       3.60391438e+09, 4.65673918e+09, 3.51308646e+09, 4.92042350e+09,\n",
       "       4.78616092e+09, 5.45453458e+09, 5.41578405e+09, 8.98726672e+09,\n",
       "       6.97761564e+09, 8.86874067e+09, 8.33393534e+09, 9.01478727e+09,\n",
       "       8.29811473e+09, 7.17795465e+09, 1.12789559e+10, 1.05293979e+10,\n",
       "       1.23440789e+10, 1.11929782e+10, 1.45811531e+10, 1.09897938e+10,\n",
       "       1.55389272e+10, 1.82689367e+10, 1.82255686e+10, 1.81641679e+10,\n",
       "       1.89360120e+10, 1.53173260e+10, 1.91574726e+10, 1.97069107e+10,\n",
       "       1.80506135e+10, 1.90375809e+10, 1.80619796e+10, 1.81323556e+10,\n",
       "       1.84665012e+10, 1.68279737e+10, 2.08395881e+10, 1.70669811e+10,\n",
       "       2.47793248e+10, 1.90860594e+10, 3.03534078e+10, 2.97196995e+10,\n",
       "       3.19502358e+10, 3.19500352e+10, 3.01272923e+10, 2.64270633e+10,\n",
       "       3.50307334e+10, 2.24483754e+10, 3.06229464e+10, 4.59507897e+10,\n",
       "       4.34210236e+10, 4.42454987e+10, 4.92602023e+10, 4.81717668e+10,\n",
       "       4.26466626e+10, 3.49901173e+10, 3.50346267e+10, 4.47651686e+10,\n",
       "       3.46393443e+10, 5.13390175e+10, 5.02429398e+10, 5.15449616e+10,\n",
       "       4.51122569e+10, 5.09940712e+10, 3.68974490e+10, 6.90981694e+10,\n",
       "       5.16137116e+10, 5.64681615e+10, 8.50745123e+10, 5.79835697e+10,\n",
       "       5.69251558e+10, 6.27914279e+10, 5.73502160e+10, 8.57783940e+10,\n",
       "       7.00631045e+10, 6.79856635e+10, 5.93608148e+10, 9.11055806e+10,\n",
       "       1.02914213e+11,            nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>melt_off_glacier_monthly</span></div><div class='xr-var-dims'>(time, month_2d)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0 0.0 8.007e-22 ... nan nan nan</div><input id='attrs-049e8968-0f7e-4cb8-8977-b62dfb8f40d7' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-049e8968-0f7e-4cb8-8977-b62dfb8f40d7' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c6a1a17c-1746-4803-95c1-467aab90a514' class='xr-var-data-in' type='checkbox'><label for='data-c6a1a17c-1746-4803-95c1-467aab90a514' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[0.00000000e+00, 0.00000000e+00, 8.00710833e-22, ...,\n",
       "        2.70065071e-07, 1.60142167e-21, 0.00000000e+00],\n",
       "       [4.25176373e+03, 0.00000000e+00, 0.00000000e+00, ...,\n",
       "        0.00000000e+00, 0.00000000e+00, 0.00000000e+00],\n",
       "       [0.00000000e+00, 0.00000000e+00, 0.00000000e+00, ...,\n",
       "        0.00000000e+00, 2.06472218e+05, 0.00000000e+00],\n",
       "       ...,\n",
       "       [4.45940885e+09, 1.24337513e+08, 6.94081804e+08, ...,\n",
       "        3.59689526e+07, 4.61025111e+09, 0.00000000e+00],\n",
       "       [3.55474504e+09, 0.00000000e+00, 4.34303293e+08, ...,\n",
       "        9.02321078e+08, 0.00000000e+00, 0.00000000e+00],\n",
       "       [           nan,            nan,            nan, ...,\n",
       "                   nan,            nan,            nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>melt_on_glacier</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>1.145e+12 1.257e+12 ... nan</div><input id='attrs-48981713-39eb-4806-a22b-afce622afc0e' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-48981713-39eb-4806-a22b-afce622afc0e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b1d51a1b-5958-41ff-94e2-415346e1ff44' class='xr-var-data-in' type='checkbox'><label for='data-b1d51a1b-5958-41ff-94e2-415346e1ff44' 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>On-glacier melt</dd><dt><span>unit :</span></dt><dd>kg yr-1</dd></dl></div><div class='xr-var-data'><pre>array([1.14525947e+12, 1.25676221e+12, 1.29468894e+12, 1.29186354e+12,\n",
       "       1.49850434e+12, 1.50813277e+12, 1.33050502e+12, 1.40529137e+12,\n",
       "       1.19058108e+12, 1.41365297e+12, 1.40439121e+12, 1.34568992e+12,\n",
       "       1.22330233e+12, 1.57868380e+12, 1.37388299e+12, 1.48250752e+12,\n",
       "       1.63404948e+12, 1.53930228e+12, 1.51117795e+12, 1.66644113e+12,\n",
       "                  nan, 1.61423425e+12, 1.66616475e+12, 1.66732517e+12,\n",
       "       1.86877918e+12, 1.92094129e+12, 1.98683396e+12, 1.43635475e+12,\n",
       "       1.86450362e+12, 1.82171680e+12, 1.82049806e+12, 1.54292220e+12,\n",
       "       1.46678276e+12, 1.82306443e+12, 2.08175272e+12, 1.57936242e+12,\n",
       "       1.83626101e+12, 1.93925077e+12, 1.83431872e+12, 2.04928128e+12,\n",
       "       1.89925238e+12, 1.80872109e+12, 1.80884153e+12, 1.73250488e+12,\n",
       "       1.83895009e+12, 1.88976184e+12, 1.75486473e+12, 1.84818264e+12,\n",
       "       1.67273150e+12, 2.10648958e+12, 1.67323379e+12, 1.89522395e+12,\n",
       "       1.98723933e+12, 1.98397764e+12, 1.56719153e+12, 1.91384940e+12,\n",
       "       2.07728186e+12, 1.98937135e+12, 1.84221879e+12, 2.31735451e+12,\n",
       "       1.91635181e+12, 1.91704132e+12, 1.89548803e+12, 1.70667183e+12,\n",
       "       1.90397801e+12, 2.00110281e+12, 2.04261355e+12, 1.70657847e+12,\n",
       "       2.22084521e+12, 2.35899640e+12, 2.24640030e+12, 1.79680181e+12,\n",
       "       1.66705055e+12, 1.75093994e+12, 1.59534685e+12, 1.75053734e+12,\n",
       "       1.93845106e+12, 1.84058630e+12, 1.84364401e+12, 1.87815636e+12,\n",
       "       1.92031306e+12, 1.92637639e+12, 1.69691515e+12, 1.68441385e+12,\n",
       "       1.89956861e+12, 2.19244265e+12, 1.98566358e+12, 1.96374601e+12,\n",
       "       1.72194990e+12, 1.85052126e+12, 2.06197909e+12, 1.83456564e+12,\n",
       "       2.18173170e+12, 2.01181829e+12, 2.24017304e+12, 1.84574454e+12,\n",
       "       1.94983322e+12, 2.11407370e+12, 2.10440203e+12, 2.16829488e+12,\n",
       "       1.92771559e+12,            nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>melt_on_glacier_monthly</span></div><div class='xr-var-dims'>(time, month_2d)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0 0.0 5.649e+07 ... nan nan nan</div><input id='attrs-ede41b60-fc55-4245-a27a-0a101f35eb84' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-ede41b60-fc55-4245-a27a-0a101f35eb84' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0866b202-bd17-4937-8684-b89b95844dbb' class='xr-var-data-in' type='checkbox'><label for='data-0866b202-bd17-4937-8684-b89b95844dbb' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[0.00000000e+00, 0.00000000e+00, 5.64901372e+07, ...,\n",
       "        1.24301961e+10, 5.03620033e-05, 0.00000000e+00],\n",
       "       [3.43949585e+08, 0.00000000e+00, 0.00000000e+00, ...,\n",
       "        9.45680544e+09, 0.00000000e+00, 0.00000000e+00],\n",
       "       [0.00000000e+00, 0.00000000e+00, 0.00000000e+00, ...,\n",
       "        7.44382340e+10, 3.77101780e+09, 0.00000000e+00],\n",
       "       ...,\n",
       "       [8.94226548e+08, 2.25551954e-05, 0.00000000e+00, ...,\n",
       "        1.31670870e+11, 1.85615497e+09, 0.00000000e+00],\n",
       "       [4.97289337e+08, 0.00000000e+00, 0.00000000e+00, ...,\n",
       "        2.20859863e+10, 0.00000000e+00, 0.00000000e+00],\n",
       "       [           nan,            nan,            nan, ...,\n",
       "                   nan,            nan,            nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>liq_prcp_off_glacier</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>2.092e-05 1.097e+05 ... nan</div><input id='attrs-fa40dfde-4122-4c35-9ebd-e83bf372ec34' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-fa40dfde-4122-4c35-9ebd-e83bf372ec34' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2577c9ed-4301-4bd2-9b68-8e67248b7997' class='xr-var-data-in' type='checkbox'><label for='data-2577c9ed-4301-4bd2-9b68-8e67248b7997' 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>Off-glacier liquid precipitation</dd><dt><span>unit :</span></dt><dd>kg yr-1</dd></dl></div><div class='xr-var-data'><pre>array([2.09196299e-05, 1.09714102e+05, 8.80814855e+06, 4.31986665e+07,\n",
       "       8.55569719e+07, 1.89500784e+08, 2.16626147e+08, 2.06248694e+08,\n",
       "       5.12526665e+08, 4.03394507e+08, 3.53092301e+08, 6.63099649e+08,\n",
       "       8.65693107e+08, 1.36667172e+09, 1.71107088e+09, 1.83215879e+09,\n",
       "       1.64472869e+09, 2.45916895e+09, 2.68124135e+09, 1.27515808e+09,\n",
       "                  nan, 2.67887136e+09, 3.13761327e+09, 4.55925821e+09,\n",
       "       5.25699290e+09, 4.98990062e+09, 5.26484340e+09, 5.50652132e+09,\n",
       "       5.49186720e+09, 6.77232099e+09, 7.62896530e+09, 5.98956855e+09,\n",
       "       7.29470688e+09, 7.16710543e+09, 8.45595253e+09, 8.91590394e+09,\n",
       "       1.05982555e+10, 7.07917804e+09, 1.15107407e+10, 1.15936000e+10,\n",
       "       1.24618610e+10, 1.05965114e+10, 2.08846965e+10, 1.80667908e+10,\n",
       "       1.44662640e+10, 1.83330323e+10, 1.97006748e+10, 1.85380649e+10,\n",
       "       2.04647218e+10, 1.85951137e+10, 1.34479401e+10, 2.96862688e+10,\n",
       "       2.37240505e+10, 2.53606672e+10, 2.32460285e+10, 2.75046568e+10,\n",
       "       2.10846651e+10, 3.08803044e+10, 2.38890682e+10, 2.59848930e+10,\n",
       "       3.54101689e+10, 2.81118346e+10, 2.89179201e+10, 3.23474780e+10,\n",
       "       5.06087030e+10, 5.68448320e+10, 5.31688851e+10, 4.74530409e+10,\n",
       "       3.38334997e+10, 6.50744983e+10, 5.92142214e+10, 5.22761397e+10,\n",
       "       5.61710624e+10, 5.82232148e+10, 6.49252802e+10, 3.82288389e+10,\n",
       "       5.03570301e+10, 5.03801926e+10, 5.09451844e+10, 6.28523049e+10,\n",
       "       6.90436071e+10, 6.28271591e+10, 6.80943252e+10, 7.94188707e+10,\n",
       "       9.31924043e+10, 9.46141093e+10, 1.12103980e+11, 1.23554322e+11,\n",
       "       9.86034170e+10, 1.20868291e+11, 1.15877054e+11, 1.01252958e+11,\n",
       "       1.02573791e+11, 1.06018596e+11, 7.11337344e+10, 9.93066653e+10,\n",
       "       9.63259543e+10, 1.12709406e+11, 1.23420596e+11, 1.50283541e+11,\n",
       "       1.03595155e+11,            nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>liq_prcp_off_glacier_monthly</span></div><div class='xr-var-dims'>(time, month_2d)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0 0.0 0.0 ... nan nan nan</div><input id='attrs-63758027-34a9-4b7a-9e4c-790c832d7844' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-63758027-34a9-4b7a-9e4c-790c832d7844' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-34d8c983-75f6-452c-b443-1a3dc6450fd7' class='xr-var-data-in' type='checkbox'><label for='data-34d8c983-75f6-452c-b443-1a3dc6450fd7' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[0.00000000e+00, 0.00000000e+00, 0.00000000e+00, ...,\n",
       "        1.56076988e-06, 0.00000000e+00, 0.00000000e+00],\n",
       "       [0.00000000e+00, 0.00000000e+00, 0.00000000e+00, ...,\n",
       "        2.28671048e+04, 0.00000000e+00, 0.00000000e+00],\n",
       "       [0.00000000e+00, 0.00000000e+00, 0.00000000e+00, ...,\n",
       "        5.33865592e+05, 6.46268307e+05, 0.00000000e+00],\n",
       "       ...,\n",
       "       [8.72956808e+09, 0.00000000e+00, 0.00000000e+00, ...,\n",
       "        2.99344196e+10, 1.17988317e+10, 0.00000000e+00],\n",
       "       [4.89522194e+09, 0.00000000e+00, 0.00000000e+00, ...,\n",
       "        1.68892253e+10, 0.00000000e+00, 0.00000000e+00],\n",
       "       [           nan,            nan,            nan, ...,\n",
       "                   nan,            nan,            nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>liq_prcp_on_glacier</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>7.01e+11 4.56e+11 ... 6.723e+11 nan</div><input id='attrs-58359813-66c8-4d60-aa5f-7f87371e8f28' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-58359813-66c8-4d60-aa5f-7f87371e8f28' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c38fdc17-07e5-49f1-bdfe-374b492e315b' class='xr-var-data-in' type='checkbox'><label for='data-c38fdc17-07e5-49f1-bdfe-374b492e315b' 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>On-glacier liquid precipitation</dd><dt><span>unit :</span></dt><dd>kg yr-1</dd></dl></div><div class='xr-var-data'><pre>array([7.00973406e+11, 4.55982612e+11, 6.23024176e+11, 5.05400223e+11,\n",
       "       3.97790793e+11, 8.12415596e+11, 7.96629871e+11, 5.11671145e+11,\n",
       "       7.97660885e+11, 6.84596506e+11, 4.43747669e+11, 6.01161586e+11,\n",
       "       6.73849060e+11, 8.52625838e+11, 8.71739878e+11, 8.17394409e+11,\n",
       "       6.88058181e+11, 8.62428457e+11, 8.36305014e+11, 3.36148736e+11,\n",
       "                  nan, 6.59194187e+11, 7.27378213e+11, 9.27031899e+11,\n",
       "       9.81614945e+11, 8.93477433e+11, 8.25714554e+11, 7.79111280e+11,\n",
       "       7.42547063e+11, 8.14939495e+11, 8.49961119e+11, 5.82572323e+11,\n",
       "       7.22658024e+11, 7.14923343e+11, 8.16814816e+11, 7.54481723e+11,\n",
       "       8.93520238e+11, 5.53281056e+11, 8.08817382e+11, 8.04279381e+11,\n",
       "       8.46502514e+11, 6.56031762e+11, 9.74864941e+11, 8.03537306e+11,\n",
       "       6.05818131e+11, 6.50080173e+11, 8.37597412e+11, 6.45629011e+11,\n",
       "       8.48837009e+11, 7.92786603e+11, 5.54297370e+11, 1.10064963e+12,\n",
       "       8.80021454e+11, 8.88628634e+11, 7.80124013e+11, 9.18306270e+11,\n",
       "       6.65931425e+11, 1.06511849e+12, 7.33164989e+11, 7.88978580e+11,\n",
       "       9.81037591e+11, 7.10978986e+11, 6.53785160e+11, 5.59014424e+11,\n",
       "       9.06848759e+11, 1.01469732e+12, 9.48298203e+11, 8.15393778e+11,\n",
       "       5.53927223e+11, 9.75079606e+11, 9.91663696e+11, 7.09036759e+11,\n",
       "       7.47295375e+11, 6.85762026e+11, 8.56464858e+11, 5.08048193e+11,\n",
       "       6.48199267e+11, 6.80407197e+11, 6.24830875e+11, 6.49948316e+11,\n",
       "       8.54295500e+11, 7.68449282e+11, 8.20986688e+11, 8.04408060e+11,\n",
       "       9.56864508e+11, 8.37582977e+11, 1.07215158e+12, 7.60891115e+11,\n",
       "       8.36688611e+11, 9.81740538e+11, 9.78058129e+11, 7.38894475e+11,\n",
       "       7.06691709e+11, 8.04794666e+11, 5.85760628e+11, 6.89369872e+11,\n",
       "       6.89964291e+11, 7.11276988e+11, 8.17191644e+11, 1.02532237e+12,\n",
       "       6.72275669e+11,            nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>liq_prcp_on_glacier_monthly</span></div><div class='xr-var-dims'>(time, month_2d)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0 0.0 0.0 ... nan nan nan</div><input id='attrs-202b1c00-0718-4247-9179-eeefbb261ad5' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-202b1c00-0718-4247-9179-eeefbb261ad5' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-bc5b1f99-450c-4363-adea-557047205813' class='xr-var-data-in' type='checkbox'><label for='data-bc5b1f99-450c-4363-adea-557047205813' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[0.00000000e+00, 0.00000000e+00, 0.00000000e+00, ...,\n",
       "        2.82871224e+10, 0.00000000e+00, 0.00000000e+00],\n",
       "       [0.00000000e+00, 0.00000000e+00, 0.00000000e+00, ...,\n",
       "        8.33006980e+09, 0.00000000e+00, 0.00000000e+00],\n",
       "       [0.00000000e+00, 0.00000000e+00, 0.00000000e+00, ...,\n",
       "        5.60828021e+10, 4.15056043e+09, 0.00000000e+00],\n",
       "       ...,\n",
       "       [1.28450299e+08, 0.00000000e+00, 0.00000000e+00, ...,\n",
       "        2.05063592e+11, 1.06692381e+09, 0.00000000e+00],\n",
       "       [0.00000000e+00, 0.00000000e+00, 0.00000000e+00, ...,\n",
       "        2.59750747e+10, 0.00000000e+00, 0.00000000e+00],\n",
       "       [           nan,            nan,            nan, ...,\n",
       "                   nan,            nan,            nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>snowfall_off_glacier</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>5.221e-05 1.133e+05 ... nan</div><input id='attrs-27abbd9a-fd6d-4f6c-a087-2f002bed7fc7' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-27abbd9a-fd6d-4f6c-a087-2f002bed7fc7' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0032368a-679d-46f7-9d8c-7dcd10882376' class='xr-var-data-in' type='checkbox'><label for='data-0032368a-679d-46f7-9d8c-7dcd10882376' 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>Off-glacier solid precipitation</dd><dt><span>unit :</span></dt><dd>kg yr-1</dd></dl></div><div class='xr-var-data'><pre>array([5.22134521e-05, 1.13304034e+05, 6.33923608e+07, 1.98199329e+08,\n",
       "       5.79389603e+08, 5.85505562e+08, 4.46097054e+08, 5.18995558e+08,\n",
       "       9.85559053e+08, 7.35957746e+08, 6.80570895e+08, 1.24381323e+09,\n",
       "       9.72594016e+08, 1.64661976e+09, 2.06299329e+09, 2.43828246e+09,\n",
       "       2.03703303e+09, 2.56730228e+09, 2.06716176e+09, 3.03915370e+09,\n",
       "                  nan, 3.47761476e+09, 3.47540890e+09, 3.87579997e+09,\n",
       "       4.40993295e+09, 4.76834617e+09, 4.16759244e+09, 5.59703394e+09,\n",
       "       5.40054372e+09, 4.97306750e+09, 7.03251865e+09, 1.01332740e+10,\n",
       "       7.04807929e+09, 1.00063484e+10, 7.79868006e+09, 9.01086057e+09,\n",
       "       8.83381428e+09, 8.42781044e+09, 1.24607533e+10, 1.11563317e+10,\n",
       "       1.12897329e+10, 1.35138438e+10, 1.37976197e+10, 1.28644013e+10,\n",
       "       1.66480020e+10, 1.75765690e+10, 1.92122900e+10, 1.77318921e+10,\n",
       "       1.90402409e+10, 1.63728662e+10, 1.92385292e+10, 1.92727365e+10,\n",
       "       1.94416918e+10, 1.83240874e+10, 1.77581992e+10, 1.94556942e+10,\n",
       "       1.75667943e+10, 1.83299033e+10, 2.28138643e+10, 1.98047967e+10,\n",
       "       2.29223766e+10, 2.23935022e+10, 3.03936269e+10, 2.94739649e+10,\n",
       "       3.03146122e+10, 3.24886634e+10, 2.95972385e+10, 3.39906456e+10,\n",
       "       2.41294586e+10, 2.85098339e+10, 3.72239726e+10, 4.62144054e+10,\n",
       "       4.96326334e+10, 4.24997595e+10, 5.10040927e+10, 4.42315108e+10,\n",
       "       4.27646814e+10, 2.63562068e+10, 4.35750222e+10, 4.47521327e+10,\n",
       "       3.66391404e+10, 6.05470054e+10, 4.88671468e+10, 4.55474311e+10,\n",
       "       4.49731478e+10, 4.68546328e+10, 5.88774514e+10, 5.05582863e+10,\n",
       "       5.58186811e+10, 7.59303206e+10, 7.35634651e+10, 5.23013104e+10,\n",
       "       5.62336045e+10, 6.45150526e+10, 7.18518714e+10, 8.03659468e+10,\n",
       "       6.83539204e+10, 5.79509359e+10, 6.17944555e+10, 1.04653733e+11,\n",
       "       1.02350103e+11,            nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>snowfall_off_glacier_monthly</span></div><div class='xr-var-dims'>(time, month_2d)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>4e-06 2.854e-06 ... nan nan</div><input id='attrs-d453cd98-4bd1-423d-8016-3d3e4d402f2b' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-d453cd98-4bd1-423d-8016-3d3e4d402f2b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ce404b89-20a4-4a4b-ad9b-e19f519736f9' class='xr-var-data-in' type='checkbox'><label for='data-ce404b89-20a4-4a4b-ad9b-e19f519736f9' 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([[4.00033949e-06, 2.85386916e-06, 6.80409496e-06, ...,\n",
       "        1.19882388e-05, 1.02423126e-05, 4.62373537e-06],\n",
       "       [3.52039295e+04, 2.05777807e+04, 2.49082157e+04, ...,\n",
       "        0.00000000e+00, 1.62704003e+04, 1.26084319e+04],\n",
       "       [1.05014646e+07, 7.06628014e+06, 6.93020298e+05, ...,\n",
       "        6.93271562e+06, 1.12958994e+07, 2.31616158e+06],\n",
       "       ...,\n",
       "       [3.02723777e+10, 1.65910268e+10, 1.55518066e+10, ...,\n",
       "        2.01800791e+08, 1.99539452e+10, 2.19236422e+10],\n",
       "       [3.01980526e+10, 1.98202706e+10, 1.44910377e+10, ...,\n",
       "        4.60880352e+09, 9.44094349e+09, 2.33480649e+10],\n",
       "       [           nan,            nan,            nan, ...,\n",
       "                   nan,            nan,            nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>snowfall_on_glacier</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>1.591e+12 1.141e+12 ... nan</div><input id='attrs-0a7c41cd-46cb-40a0-ad7a-222450c7931e' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-0a7c41cd-46cb-40a0-ad7a-222450c7931e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-713efe63-1a85-4f9e-9cbf-79bd0892e5fe' class='xr-var-data-in' type='checkbox'><label for='data-713efe63-1a85-4f9e-9cbf-79bd0892e5fe' 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>On-glacier solid precipitation</dd><dt><span>unit :</span></dt><dd>kg yr-1</dd></dl></div><div class='xr-var-data'><pre>array([1.59070312e+12, 1.14141979e+12, 8.03259468e+11, 8.58476090e+11,\n",
       "       1.54717870e+12, 1.37131178e+12, 9.27307676e+11, 8.95320301e+11,\n",
       "       1.20143288e+12, 9.73363357e+11, 7.39209401e+11, 9.59778994e+11,\n",
       "       6.41691580e+11, 9.38541641e+11, 1.00500176e+12, 1.16386632e+12,\n",
       "       9.05232834e+11, 1.01501921e+12, 7.72256896e+11, 9.56012209e+11,\n",
       "                  nan, 9.90509608e+11, 8.99313349e+11, 9.65431410e+11,\n",
       "       1.00992659e+12, 9.37819766e+11, 7.95233036e+11, 9.34956355e+11,\n",
       "       8.74551763e+11, 7.95245155e+11, 1.00472359e+12, 1.33732134e+12,\n",
       "       9.51581729e+11, 1.21378500e+12, 9.36719394e+11, 1.04650168e+12,\n",
       "       9.92005327e+11, 8.78710551e+11, 1.27621061e+12, 1.10664496e+12,\n",
       "       1.04954909e+12, 1.18705225e+12, 1.03013482e+12, 9.31336753e+11,\n",
       "       1.08808837e+12, 1.25131605e+12, 1.17004046e+12, 1.18463561e+12,\n",
       "       1.09282971e+12, 8.91273864e+11, 9.62259158e+11, 1.12147095e+12,\n",
       "       1.03177232e+12, 9.91242398e+11, 9.32366327e+11, 1.00346503e+12,\n",
       "       8.73119936e+11, 8.29850801e+11, 1.01357413e+12, 7.79037932e+11,\n",
       "       9.49271799e+11, 9.22583412e+11, 1.04607014e+12, 1.08229558e+12,\n",
       "       1.05558639e+12, 9.95888458e+11, 8.84910584e+11, 9.56176044e+11,\n",
       "       6.29943691e+11, 8.95182140e+11, 8.98667279e+11, 1.18729610e+12,\n",
       "       1.18818386e+12, 1.14162966e+12, 1.22694364e+12, 9.64271788e+11,\n",
       "       9.96103594e+11, 6.08884186e+11, 9.39680691e+11, 1.10975487e+12,\n",
       "       8.55900937e+11, 1.09483696e+12, 9.28955472e+11, 9.06163051e+11,\n",
       "       8.16244300e+11, 8.03010128e+11, 8.41269091e+11, 1.17030954e+12,\n",
       "       8.64581131e+11, 1.07287978e+12, 9.88002504e+11, 8.42311855e+11,\n",
       "       9.16123432e+11, 8.53564254e+11, 7.93302080e+11, 1.02708558e+12,\n",
       "       8.73503685e+11, 8.96539192e+11, 8.48928190e+11, 1.24924655e+12,\n",
       "       1.15453851e+12,            nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>snowfall_on_glacier_monthly</span></div><div class='xr-var-dims'>(time, month_2d)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>1.254e+11 8.943e+10 ... nan nan</div><input id='attrs-569ae1a4-0334-4b90-8ebc-b7ac13bfa93f' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-569ae1a4-0334-4b90-8ebc-b7ac13bfa93f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6b832765-eba5-45b8-8c89-71eb4983582e' class='xr-var-data-in' type='checkbox'><label for='data-6b832765-eba5-45b8-8c89-71eb4983582e' 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([[1.25353449e+11, 8.94279960e+10, 2.13211098e+11, ...,\n",
       "        3.96280589e+11, 3.20950065e+11, 1.44887998e+11],\n",
       "       [2.52153672e+11, 1.47391585e+11, 1.78409006e+11, ...,\n",
       "        1.55459158e+11, 1.16539297e+11, 9.03098732e+10],\n",
       "       [2.07450991e+11, 1.39590702e+11, 1.36902568e+10, ...,\n",
       "        9.14156403e+10, 2.31760774e+11, 4.57545716e+10],\n",
       "       ...,\n",
       "       [3.47849749e+11, 1.48026349e+11, 1.38754350e+11, ...,\n",
       "        6.38139597e+10, 2.82233663e+11, 1.95604331e+11],\n",
       "       [3.11290933e+11, 1.75813475e+11, 1.28541115e+11, ...,\n",
       "        1.64720765e+11, 8.37448242e+10, 2.07106375e+11],\n",
       "       [           nan,            nan,            nan, ...,\n",
       "                   nan,            nan,            nan]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>snow_bucket</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0 3.616e-05 ... 5.78e+10</div><input id='attrs-d638542b-56fc-4245-8dd1-425c0040392d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d638542b-56fc-4245-8dd1-425c0040392d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-03fd59ba-fbc4-4d8c-b8d9-430fdc854b4e' class='xr-var-data-in' type='checkbox'><label for='data-03fd59ba-fbc4-4d8c-b8d9-430fdc854b4e' 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>Off-glacier snow reservoir (state variable)</dd><dt><span>unit :</span></dt><dd>kg</dd></dl></div><div class='xr-var-data'><pre>array([0.00000000e+00, 3.61588314e-05, 2.88788323e+04, 5.67404824e+07,\n",
       "       2.11315593e+08, 5.99009391e+08, 9.66769457e+08, 1.19738182e+09,\n",
       "       1.43242516e+09, 2.03909599e+09, 2.20602772e+09, 2.43366345e+09,\n",
       "       3.09800240e+09, 3.06517175e+09, 3.57015892e+09, 4.49447616e+09,\n",
       "       5.06956341e+09, 5.29849224e+09, 6.09446854e+09, 6.44232822e+09,\n",
       "       7.29228405e+09, 0.00000000e+00, 1.97423432e+09, 2.23241727e+09,\n",
       "       2.49790686e+09, 3.30392544e+09, 3.41553242e+09, 4.07003840e+09,\n",
       "       4.74664885e+09, 5.36103165e+09, 4.87956457e+09, 6.49629917e+09,\n",
       "       7.64230646e+09, 7.71277011e+09, 8.85037780e+09, 8.31512253e+09,\n",
       "       8.31119582e+09, 8.84689537e+09, 1.00967512e+10, 1.12785486e+10,\n",
       "       1.19054824e+10, 1.08511364e+10, 1.31720020e+10, 1.23884686e+10,\n",
       "       1.42630762e+10, 1.53721510e+10, 1.46797833e+10, 1.56665047e+10,\n",
       "       1.52342289e+10, 1.53384578e+10, 1.63939980e+10, 1.64750546e+10,\n",
       "       1.60408804e+10, 1.74319588e+10, 1.67184652e+10, 1.64146848e+10,\n",
       "       1.77380234e+10, 1.68383165e+10, 1.83402461e+10, 2.03145222e+10,\n",
       "       2.30523378e+10, 2.11953896e+10, 2.45028324e+10, 2.45430515e+10,\n",
       "       2.42973169e+10, 2.26616933e+10, 2.32003215e+10, 2.26702678e+10,\n",
       "       3.02338501e+10, 1.93325754e+10, 2.53940338e+10, 3.19950600e+10,\n",
       "       3.22586757e+10, 3.84702855e+10, 3.67245463e+10, 3.84684367e+10,\n",
       "       3.45281807e+10, 3.46461995e+10, 2.60122891e+10, 3.45526846e+10,\n",
       "       3.45396487e+10, 3.65394448e+10, 4.57474327e+10, 4.43716396e+10,\n",
       "       3.83741092e+10, 3.82350001e+10, 3.40955616e+10, 5.60755640e+10,\n",
       "       3.75356809e+10, 4.17406504e+10, 6.12028095e+10, 4.96917623e+10,\n",
       "       4.40095029e+10, 4.33179517e+10, 4.50415765e+10, 5.95432319e+10,\n",
       "       5.41307846e+10, 5.24216005e+10, 4.23868730e+10, 4.48205137e+10,\n",
       "       5.83686665e+10, 5.78045569e+10])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>snow_bucket_monthly</span></div><div class='xr-var-dims'>(time, month_2d)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0 4e-06 6.854e-06 ... 0.0 0.0 0.0</div><input id='attrs-acc83aed-c7d8-46c5-8dd4-5bcdd5685b61' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-acc83aed-c7d8-46c5-8dd4-5bcdd5685b61' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ce12c6f1-19c7-4385-a77d-8e438bc1d37a' class='xr-var-data-in' type='checkbox'><label for='data-ce12c6f1-19c7-4385-a77d-8e438bc1d37a' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[0.00000000e+00, 4.00033949e-06, 6.85420865e-06, ...,\n",
       "        9.57460969e-06, 2.12927835e-05, 3.15350961e-05],\n",
       "       [3.61588314e-05, 3.09521658e+04, 5.15299465e+04, ...,\n",
       "        3.61588314e-05, 3.61588314e-05, 1.62704003e+04],\n",
       "       [2.88788323e+04, 1.05303435e+07, 1.75966236e+07, ...,\n",
       "        3.64021780e+07, 4.33348936e+07, 5.44243208e+07],\n",
       "       ...,\n",
       "       [4.48205137e+10, 7.06334825e+10, 8.71001718e+10, ...,\n",
       "        2.09354985e+10, 2.11013303e+10, 3.64450244e+10],\n",
       "       [5.83686665e+10, 8.50119741e+10, 1.04832245e+11, ...,\n",
       "        2.13090661e+10, 2.50155485e+10, 3.44564920e+10],\n",
       "       [5.78045569e+10, 0.00000000e+00, 0.00000000e+00, ...,\n",
       "        0.00000000e+00, 0.00000000e+00, 0.00000000e+00]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>model_mb</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>4.454e+11 -1.153e+11 ... nan</div><input id='attrs-b4a8053c-cc2e-4f09-a13b-3126641eaf11' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b4a8053c-cc2e-4f09-a13b-3126641eaf11' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-da0912eb-f584-46f7-bb4d-c952734b3de0' class='xr-var-data-in' type='checkbox'><label for='data-da0912eb-f584-46f7-bb4d-c952734b3de0' 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>Annual mass balance from dynamical model</dd><dt><span>unit :</span></dt><dd>kg yr-1</dd></dl></div><div class='xr-var-data'><pre>array([ 4.45443651e+11, -1.15342414e+11, -4.91429473e+11, -4.33387447e+11,\n",
       "        4.86743666e+10, -1.36820982e+11, -4.03197343e+11, -5.09971073e+11,\n",
       "        1.08517993e+10, -4.40289613e+11, -6.65181814e+11, -3.85910929e+11,\n",
       "       -5.81610751e+11, -6.40142162e+11, -3.68881228e+11, -3.18641201e+11,\n",
       "       -7.28816642e+11, -5.24283072e+11, -7.38921058e+11, -7.10428919e+11,\n",
       "                   nan, -6.23724646e+11, -7.66851398e+11, -7.01893757e+11,\n",
       "       -8.58852590e+11, -9.83121522e+11, -1.19160093e+12, -5.01398395e+11,\n",
       "       -9.89951858e+11, -1.02647164e+12, -8.15774470e+11, -2.05600864e+11,\n",
       "       -5.15201026e+11, -6.09279438e+11, -1.14503332e+12, -5.32860739e+11,\n",
       "       -8.44255682e+11, -1.06054022e+12, -5.58108113e+11, -9.42636318e+11,\n",
       "       -8.49703293e+11, -6.21668840e+11, -7.78706712e+11, -8.01168126e+11,\n",
       "       -7.50861718e+11, -6.38445792e+11, -5.84824275e+11, -6.63547032e+11,\n",
       "       -5.79901795e+11, -1.21521572e+12, -7.10974635e+11, -7.73752999e+11,\n",
       "       -9.55467013e+11, -9.92735239e+11, -6.34825205e+11, -9.10384373e+11,\n",
       "       -1.20416192e+12, -1.15952055e+12, -8.28644664e+11, -1.53831658e+12,\n",
       "       -9.67080012e+11, -9.94457911e+11, -8.49417886e+11, -6.24376249e+11,\n",
       "       -8.48391625e+11, -1.00521435e+12, -1.15770297e+12, -7.50402422e+11,\n",
       "       -1.59090152e+12, -1.46381426e+12, -1.34773302e+12, -6.09505709e+11,\n",
       "       -4.78866691e+11, -6.09310280e+11, -3.68403206e+11, -7.86265551e+11,\n",
       "       -9.42347468e+11, -1.23170212e+12, -9.03963315e+11, -7.68401490e+11,\n",
       "       -1.06441212e+12, -8.31539432e+11, -7.67959678e+11, -7.78250795e+11,\n",
       "       -1.08332431e+12, -1.38943253e+12, -1.14439449e+12, -7.93436474e+11,\n",
       "       -8.57368768e+11, -7.77641487e+11, -1.07397658e+12, -9.92253788e+11,\n",
       "       -1.26560827e+12, -1.15825404e+12, -1.44687096e+12, -8.18658953e+11,\n",
       "       -1.07632953e+12, -1.21753451e+12, -1.25547384e+12, -9.19048331e+11,\n",
       "       -7.73177079e+11,             nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>residual_mb</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-4.101e+09 -4.07e+09 ... nan</div><input id='attrs-836da3a6-5d54-4c3b-b3c8-c72e920722da' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-836da3a6-5d54-4c3b-b3c8-c72e920722da' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f727d85e-86e7-4414-a833-6f75292828f6' class='xr-var-data-in' type='checkbox'><label for='data-f727d85e-86e7-4414-a833-6f75292828f6' 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>Difference (before correction) between mb model and dyn model melt</dd><dt><span>unit :</span></dt><dd>kg yr-1</dd></dl></div><div class='xr-var-data'><pre>array([-4.10079963e+09, -4.06987076e+09, -3.64833886e+09, -3.28984880e+09,\n",
       "       -3.09170851e+09, -2.85968681e+09, -2.56565368e+09, -2.25984782e+09,\n",
       "       -2.13315747e+09, -1.95728762e+09, -1.65617908e+09, -1.52485750e+09,\n",
       "       -1.32253694e+09, -1.04983931e+09, -1.01839038e+09, -8.32605068e+08,\n",
       "       -5.82785323e+08, -4.50421404e+08, -2.50846881e+08, -1.51923267e+08,\n",
       "                   nan, -7.05577485e+07,  5.24615826e+07,  2.03449232e+08,\n",
       "        3.45970864e+08,  3.53725292e+08,  5.90181341e+08,  1.48049872e+08,\n",
       "        4.53051070e+08,  5.20063565e+08,  4.17046227e+08,  1.47028057e+08,\n",
       "        2.38066129e+08,  2.82817123e+08,  6.14242459e+08,  2.48792198e+08,\n",
       "        4.53537218e+08,  5.65567388e+08,  3.93437474e+08,  6.00131141e+08,\n",
       "        4.92112538e+08,  1.66934766e+09,  3.59988092e+08,  3.88621463e+08,\n",
       "        3.71113326e+08,  4.48818736e+08,  3.57684165e+08,  4.69336540e+08,\n",
       "        3.19047265e+08,  7.51900858e+08,  2.74963947e+08,  5.53166685e+08,\n",
       "        6.11530062e+08,  6.92988385e+08,  3.84441797e+08,  6.44709381e+08,\n",
       "        8.60543974e+08,  7.64675803e+08,  5.42956410e+09,  1.12596821e+09,\n",
       "        7.14102517e+08,  6.81723350e+09,  6.08830158e+08,  6.96242011e+09,\n",
       "        7.59848618e+09,  7.43489857e+08,  8.26722392e+08,  2.20311792e+09,\n",
       "        1.12411066e+09,  1.11036740e+09,  9.93714587e+08,  1.00903856e+09,\n",
       "        4.02085976e+08,  4.66573826e+08,  3.36582072e+08,  4.42635136e+08,\n",
       "        1.24288930e+09,  7.65552263e+08,  6.27397068e+08,  5.55586803e+08,\n",
       "        5.35809587e+09,  5.29029672e+08,  5.09660827e+09,  9.63628095e+09,\n",
       "        1.39897818e+10,  5.25388056e+09,  7.38699585e+08,  5.38091877e+08,\n",
       "        8.46548047e+09,  4.85959165e+08,  6.92693800e+08,  5.85677744e+08,\n",
       "        7.21579531e+09,  7.38253168e+08,  8.95419489e+08,  5.27521821e+08,\n",
       "        6.83416676e+08,  1.02379992e+10,  9.14065469e+08,  6.58651816e+08,\n",
       "        4.76030802e+08,             nan])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>residual_mb_monthly</span></div><div class='xr-var-dims'>(time, month_2d)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.0 0.0 -2.023e+05 ... nan nan nan</div><input id='attrs-ad748ed3-6308-4a09-9277-9b7e3ceebe26' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-ad748ed3-6308-4a09-9277-9b7e3ceebe26' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-837d87cf-5057-433f-a016-1437ada5b6c1' class='xr-var-data-in' type='checkbox'><label for='data-837d87cf-5057-433f-a016-1437ada5b6c1' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([[ 0.00000000e+00,  0.00000000e+00, -2.02272708e+05, ...,\n",
       "        -4.45084675e+07, -1.80329865e-07,  0.00000000e+00],\n",
       "       [-1.11383868e+06,  0.00000000e+00,  0.00000000e+00, ...,\n",
       "        -3.06247082e+07,  0.00000000e+00,  0.00000000e+00],\n",
       "       [ 0.00000000e+00,  0.00000000e+00,  0.00000000e+00, ...,\n",
       "        -2.09761506e+08, -1.06264527e+07,  0.00000000e+00],\n",
       "       ...,\n",
       "       [ 2.71634612e+05,  6.85147603e-09,  0.00000000e+00, ...,\n",
       "         3.99969848e+07,  5.63834674e+05,  0.00000000e+00],\n",
       "       [ 1.22800813e+05,  0.00000000e+00,  0.00000000e+00, ...,\n",
       "         5.45392163e+06,  0.00000000e+00,  0.00000000e+00],\n",
       "       [            nan,             nan,             nan, ...,\n",
       "                    nan,             nan,             nan]])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-cd8600b6-e492-474f-9399-4b06880347ea' class='xr-section-summary-in' type='checkbox'  checked><label for='section-cd8600b6-e492-474f-9399-4b06880347ea' class='xr-section-summary' >Attributes: <span>(9)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>description :</span></dt><dd>OGGM model output</dd><dt><span>oggm_version :</span></dt><dd>1.3.2.dev394+gb45b78b</dd><dt><span>calendar :</span></dt><dd>365-day no leap</dd><dt><span>creation_date :</span></dt><dd>2023-05-12 07:34:16</dd><dt><span>water_level :</span></dt><dd>491.3637909324272</dd><dt><span>glen_a :</span></dt><dd>7.830101237437472e-24</dd><dt><span>fs :</span></dt><dd>0</dd><dt><span>mb_model_class :</span></dt><dd>MultipleFlowlineMassBalance</dd><dt><span>mb_model_hemisphere :</span></dt><dd>nh</dd></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.Dataset>\n",
       "Dimensions:                       (time: 102, month_2d: 12)\n",
       "Coordinates:\n",
       "  * time                          (time) float64 2e+03 2.001e+03 ... 2.1e+03\n",
       "    calendar_year                 (time) int64 2000 2001 2002 ... 2098 2099 2100\n",
       "    calendar_month                (time) int64 1 1 1 1 1 1 1 1 ... 1 1 1 1 1 1 1\n",
       "    hydro_year                    (time) int64 2000 2001 2002 ... 2098 2099 2100\n",
       "    hydro_month                   (time) int64 4 4 4 4 4 4 4 4 ... 4 4 4 4 4 4 4\n",
       "  * month_2d                      (month_2d) int64 1 2 3 4 5 6 7 8 9 10 11 12\n",
       "    hydro_month_2d                (month_2d) int64 4 5 6 7 8 9 10 11 12 1 2 3\n",
       "    calendar_month_2d             (month_2d) int64 1 2 3 4 5 6 7 8 9 10 11 12\n",
       "Data variables: (12/26)\n",
       "    volume_m3                     (time) float64 1.607e+11 ... 7.234e+10\n",
       "    volume_bsl_m3                 (time) float64 0.0 0.0 0.0 0.0 ... 0.0 0.0 0.0\n",
       "    volume_bwl_m3                 (time) float64 2.95e+09 2.95e+09 ... 1.535e+08\n",
       "    area_m2                       (time) float64 4.414e+08 ... 3.965e+08\n",
       "    length_m                      (time) float64 4.92e+04 4.92e+04 ... 4.12e+04\n",
       "    calving_m3                    (time) float64 0.0 0.0 0.0 0.0 ... 0.0 0.0 0.0\n",
       "    ...                            ...\n",
       "    snowfall_on_glacier_monthly   (time, month_2d) float64 1.254e+11 ... nan\n",
       "    snow_bucket                   (time) float64 0.0 3.616e-05 ... 5.78e+10\n",
       "    snow_bucket_monthly           (time, month_2d) float64 0.0 4e-06 ... 0.0 0.0\n",
       "    model_mb                      (time) float64 4.454e+11 -1.153e+11 ... nan\n",
       "    residual_mb                   (time) float64 -4.101e+09 -4.07e+09 ... nan\n",
       "    residual_mb_monthly           (time, month_2d) float64 0.0 0.0 ... nan nan\n",
       "Attributes:\n",
       "    description:          OGGM model output\n",
       "    oggm_version:         1.3.2.dev394+gb45b78b\n",
       "    calendar:             365-day no leap\n",
       "    creation_date:        2023-05-12 07:34:16\n",
       "    water_level:          491.3637909324272\n",
       "    glen_a:               7.830101237437472e-24\n",
       "    fs:                   0\n",
       "    mb_model_class:       MultipleFlowlineMassBalance\n",
       "    mb_model_hemisphere:  nh"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "xr.concat([dh,df], dim='time')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "e3a29c36-1c64-41dd-b2d6-9858c9ebc167",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'/tmp/OGGM/OGGM_gcm_output/per_glacier/RGI60-01/RGI60-01.16/RGI60-01.16122/climate_historical.nc'"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "gdir.get_filepath('climate_historical')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "id": "1cfc79b6-39bb-4411-ac33-c9f05a0290e2",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "\u001b[0;31mSignature:\u001b[0m\n",
       "\u001b[0mutils\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mmerge_consecutive_run_outputs\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\u001b[0m\n",
       "\u001b[0;34m\u001b[0m    \u001b[0mgdir\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\n",
       "\u001b[0;34m\u001b[0m    \u001b[0minput_filesuffix_1\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mNone\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\n",
       "\u001b[0;34m\u001b[0m    \u001b[0minput_filesuffix_2\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mNone\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\n",
       "\u001b[0;34m\u001b[0m    \u001b[0moutput_filesuffix\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mNone\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\n",
       "\u001b[0;34m\u001b[0m    \u001b[0mdelete_input\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;32mFalse\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\n",
       "\u001b[0;34m\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
       "\u001b[0;31mDocstring:\u001b[0m\n",
       "Merges the output of two model_diagnostics files into one.\n",
       "\n",
       "It assumes that the last time of file1 is equal to the first time of file2.\n",
       "\n",
       "Parameters\n",
       "----------\n",
       "gdir : the glacier directory\n",
       "input_filesuffix_1 : str\n",
       "    how to recognize the first file\n",
       "input_filesuffix_2 : str\n",
       "    how to recognize the second file\n",
       "output_filesuffix : str\n",
       "    where to write the output (default: no suffix)\n",
       "\n",
       "Returns\n",
       "-------\n",
       "The merged dataset\n",
       "\n",
       "Notes\n",
       "-----\n",
       "Files written to the glacier directory:\n",
       "\u001b[0;31mFile:\u001b[0m      ~/.local/lib/python3.10/site-packages/oggm/utils/_workflow.py\n",
       "\u001b[0;31mType:\u001b[0m      function\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "utils.merge_consecutive_run_outputs?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "8e2d2644-0cd6-462d-a145-bde55d08b9ad",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "2023-05-12 09:34:17: oggm.utils: InvalidWorkflowError occurred during task merge_consecutive_run_outputs_merged_from_2000_run_CMIP6_CESM2-WACCM_ssp126_endyr2100_bc_2000_2019 on RGI60-01.16122: The two files seem incompatible by data on variable : volume_bwl_m3\n"
     ]
    },
    {
     "ename": "InvalidWorkflowError",
     "evalue": "The two files seem incompatible by data on variable : volume_bwl_m3",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mInvalidWorkflowError\u001b[0m                      Traceback (most recent call last)",
      "Input \u001b[0;32mIn [17]\u001b[0m, in \u001b[0;36m<cell line: 10>\u001b[0;34m()\u001b[0m\n\u001b[1;32m     17\u001b[0m rid\u001b[38;5;241m=\u001b[39m\u001b[38;5;124m'\u001b[39m\u001b[38;5;124m_CMIP6_\u001b[39m\u001b[38;5;124m'\u001b[39m \u001b[38;5;241m+\u001b[39m rid\n\u001b[1;32m     19\u001b[0m tasks\u001b[38;5;241m.\u001b[39mrun_with_hydro(gdir,\n\u001b[1;32m     20\u001b[0m          run_task\u001b[38;5;241m=\u001b[39mtasks\u001b[38;5;241m.\u001b[39mrun_from_climate_data,\n\u001b[1;32m     21\u001b[0m                      ys\u001b[38;5;241m=\u001b[39m\u001b[38;5;241m2020\u001b[39m, \u001b[38;5;66;03m# this is important! Start from 2020 glacier\u001b[39;00m\n\u001b[0;32m   (...)\u001b[0m\n\u001b[1;32m     33\u001b[0m          \u001b[38;5;66;03m# add monthly diagnostics\u001b[39;00m\n\u001b[1;32m     34\u001b[0m          store_monthly_hydro\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mTrue\u001b[39;00m);\n\u001b[0;32m---> 37\u001b[0m \u001b[43mutils\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mmerge_consecutive_run_outputs\u001b[49m\u001b[43m(\u001b[49m\u001b[43mgdir\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m     38\u001b[0m \u001b[43m                        \u001b[49m\u001b[43minput_filesuffix_1\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[38;5;124;43m_historical_from_2000_run\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[43m,\u001b[49m\n\u001b[1;32m     39\u001b[0m \u001b[43m                        \u001b[49m\u001b[43minput_filesuffix_2\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;124;43mf\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[38;5;124;43m_future_run\u001b[39;49m\u001b[38;5;132;43;01m{\u001b[39;49;00m\u001b[43mrid\u001b[49m\u001b[38;5;132;43;01m}\u001b[39;49;00m\u001b[38;5;124;43m'\u001b[39;49m\u001b[38;5;241;43m+\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[38;5;124;43m_bc_2000_2019\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[43m,\u001b[49m\n\u001b[1;32m     40\u001b[0m \u001b[43m                        \u001b[49m\u001b[43moutput_filesuffix\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;124;43mf\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[38;5;124;43m_merged_from_2000_run\u001b[39;49m\u001b[38;5;132;43;01m{\u001b[39;49;00m\u001b[43mrid\u001b[49m\u001b[38;5;132;43;01m}\u001b[39;49;00m\u001b[38;5;124;43m_endyr\u001b[39;49m\u001b[38;5;132;43;01m{\u001b[39;49;00m\u001b[43mend_yr\u001b[49m\u001b[38;5;132;43;01m}\u001b[39;49;00m\u001b[38;5;124;43m_bc_2000_2019\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[43m,\u001b[49m\n\u001b[1;32m     41\u001b[0m \u001b[43m                        \u001b[49m\u001b[43mdelete_input\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;28;43;01mFalse\u001b[39;49;00m\u001b[43m,\u001b[49m\n\u001b[1;32m     42\u001b[0m \u001b[43m                       \u001b[49m\u001b[43m)\u001b[49m \u001b[38;5;66;03m# we will delete that later\u001b[39;00m\n\u001b[1;32m     43\u001b[0m \u001b[38;5;28mprint\u001b[39m(gcm)\n",
      "File \u001b[0;32m~/.local/lib/python3.10/site-packages/oggm/utils/_workflow.py:491\u001b[0m, in \u001b[0;36mentity_task.__call__.<locals>._entity_task\u001b[0;34m(gdir, reset, print_log, return_value, continue_on_error, add_to_log_file, **kwargs)\u001b[0m\n\u001b[1;32m    489\u001b[0m     signal\u001b[38;5;241m.\u001b[39malarm(cfg\u001b[38;5;241m.\u001b[39mPARAMS[\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mtask_timeout\u001b[39m\u001b[38;5;124m'\u001b[39m])\n\u001b[1;32m    490\u001b[0m ex_t \u001b[38;5;241m=\u001b[39m time\u001b[38;5;241m.\u001b[39mtime()\n\u001b[0;32m--> 491\u001b[0m out \u001b[38;5;241m=\u001b[39m \u001b[43mtask_func\u001b[49m\u001b[43m(\u001b[49m\u001b[43mgdir\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\u001b[1;32m    492\u001b[0m ex_t \u001b[38;5;241m=\u001b[39m time\u001b[38;5;241m.\u001b[39mtime() \u001b[38;5;241m-\u001b[39m ex_t\n\u001b[1;32m    493\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m cfg\u001b[38;5;241m.\u001b[39mPARAMS[\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mtask_timeout\u001b[39m\u001b[38;5;124m'\u001b[39m] \u001b[38;5;241m>\u001b[39m \u001b[38;5;241m0\u001b[39m:\n",
      "File \u001b[0;32m~/.local/lib/python3.10/site-packages/oggm/utils/_workflow.py:1055\u001b[0m, in \u001b[0;36mmerge_consecutive_run_outputs\u001b[0;34m(gdir, input_filesuffix_1, input_filesuffix_2, output_filesuffix, delete_input)\u001b[0m\n\u001b[1;32m   1053\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mlen\u001b[39m(ds2[v]\u001b[38;5;241m.\u001b[39mdata\u001b[38;5;241m.\u001b[39mshape) \u001b[38;5;241m==\u001b[39m \u001b[38;5;241m1\u001b[39m:\n\u001b[1;32m   1054\u001b[0m     \u001b[38;5;28;01mif\u001b[39;00m ds2[v]\u001b[38;5;241m.\u001b[39mdata[\u001b[38;5;241m0\u001b[39m] \u001b[38;5;241m!=\u001b[39m \u001b[38;5;241m0\u001b[39m:\n\u001b[0;32m-> 1055\u001b[0m         \u001b[38;5;28;01mraise\u001b[39;00m InvalidWorkflowError(\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mThe two files seem incompatible \u001b[39m\u001b[38;5;124m'\u001b[39m\n\u001b[1;32m   1056\u001b[0m                                    \u001b[38;5;124mf\u001b[39m\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mby data on variable : \u001b[39m\u001b[38;5;132;01m{\u001b[39;00mv\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m'\u001b[39m)\n\u001b[1;32m   1057\u001b[0m     bucket \u001b[38;5;241m=\u001b[39m ds1[v]\u001b[38;5;241m.\u001b[39mdata[\u001b[38;5;241m-\u001b[39m\u001b[38;5;241m1\u001b[39m]\n\u001b[1;32m   1058\u001b[0m \u001b[38;5;28;01melif\u001b[39;00m \u001b[38;5;28mlen\u001b[39m(ds2[v]\u001b[38;5;241m.\u001b[39mdata\u001b[38;5;241m.\u001b[39mshape) \u001b[38;5;241m==\u001b[39m \u001b[38;5;241m2\u001b[39m:\n",
      "\u001b[0;31mInvalidWorkflowError\u001b[0m: The two files seem incompatible by data on variable : volume_bwl_m3"
     ]
    }
   ],
   "source": [
    "m = tasks.run_with_hydro(gdir, run_task=tasks.run_from_climate_data,\n",
    "                     climate_filename='climate_historical',\n",
    "                     ys=2000, init_model_yr=2000,\n",
    "                     store_monthly_hydro=True,\n",
    "                     init_model_filesuffix='_spinup_historical',\n",
    "                     ref_geometry_filesuffix='_spinup_historical',\n",
    "                     ref_area_yr = 2000,\n",
    "                     output_filesuffix='_historical_from_2000_run')\n",
    "\n",
    "for gcm in gcms_cmip6.gcm.unique()[:5]: ##TEST:\n",
    "        df1 = gcms_cmip6.loc[gcms_cmip6.gcm == gcm]\n",
    "        for ssp in df1.ssp.unique():\n",
    "            df2 = df1.loc[df1.ssp == ssp]\n",
    "            assert len(df2) == 2\n",
    "            ft = df2.loc[df2['var'] == 'tas'].iloc[0]\n",
    "            rid = ft.fname.replace('_r1i1p1f1_tas.nc', '')\n",
    "            rid='_CMIP6_' + rid\n",
    "            \n",
    "            tasks.run_with_hydro(gdir,\n",
    "                     run_task=tasks.run_from_climate_data,\n",
    "                                 ys=2020, # this is important! Start from 2020 glacier\n",
    "                                 ye=end_yr,\n",
    "                     # use gcm_data, not climate_historical\n",
    "                     climate_filename='gcm_data',\n",
    "                     # use the chosen scenario\n",
    "                     climate_input_filesuffix=rid+'_bc_2000_2019',\n",
    "                     # we start from the previous run, \n",
    "                     init_model_filesuffix='_historical_from_2000_run',\n",
    "                     ref_geometry_filesuffix='_historical_from_2000_run', \n",
    "                     ref_area_yr = 2000,\n",
    "                     # recognize the run for later\n",
    "                     output_filesuffix=f'_future_run{rid}'+'_bc_2000_2019',\n",
    "                     # add monthly diagnostics\n",
    "                     store_monthly_hydro=True);\n",
    "            \n",
    "            \n",
    "            utils.merge_consecutive_run_outputs(gdir,\n",
    "                                    input_filesuffix_1='_historical_from_2000_run',\n",
    "                                    input_filesuffix_2=f'_future_run{rid}'+'_bc_2000_2019',\n",
    "                                    output_filesuffix=f'_merged_from_2000_run{rid}_endyr{end_yr}_bc_2000_2019',\n",
    "                                    delete_input=False,\n",
    "                                   ) # we will delete that later\n",
    "            print(gcm)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "3de09366-4b24-4dad-9a78-37d20fa9a50e",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "0186a835-a79a-4953-8e05-ac3539e6cd09",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "2023-05-12 09:28:13: oggm.core.flowline: FileNotFoundError occurred during task run_from_climate_data_gcm_from_2000_run_CMIP6_MRI-ESM2-0_ssp534-over_endyr2100_bc_2000_2019 on RGI60-01.16122: [Errno 2] No such file or directory: b'/tmp/OGGM/OGGM_gcm_output/per_glacier/RGI60-01/RGI60-01.16/RGI60-01.16122/gcm_data_CMIP6_MRI-ESM2-0_ssp534-over_bc_2000_2019.nc'\n",
      "2023-05-12 09:28:13: oggm.core.flowline: FileNotFoundError occurred during task run_with_hydro_gcm_from_2000_run_CMIP6_MRI-ESM2-0_ssp534-over_endyr2100_bc_2000_2019 on RGI60-01.16122: [Errno 2] No such file or directory: b'/tmp/OGGM/OGGM_gcm_output/per_glacier/RGI60-01/RGI60-01.16/RGI60-01.16122/gcm_data_CMIP6_MRI-ESM2-0_ssp534-over_bc_2000_2019.nc'\n"
     ]
    },
    {
     "ename": "FileNotFoundError",
     "evalue": "[Errno 2] No such file or directory: b'/tmp/OGGM/OGGM_gcm_output/per_glacier/RGI60-01/RGI60-01.16/RGI60-01.16122/gcm_data_CMIP6_MRI-ESM2-0_ssp534-over_bc_2000_2019.nc'",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mFileNotFoundError\u001b[0m                         Traceback (most recent call last)",
      "Input \u001b[0;32mIn [8]\u001b[0m, in \u001b[0;36m<cell line: 1>\u001b[0;34m()\u001b[0m\n\u001b[1;32m      7\u001b[0m rid \u001b[38;5;241m=\u001b[39m ft\u001b[38;5;241m.\u001b[39mfname\u001b[38;5;241m.\u001b[39mreplace(\u001b[38;5;124m'\u001b[39m\u001b[38;5;124m_r1i1p1f1_tas.nc\u001b[39m\u001b[38;5;124m'\u001b[39m, \u001b[38;5;124m'\u001b[39m\u001b[38;5;124m'\u001b[39m)\n\u001b[1;32m      8\u001b[0m rid\u001b[38;5;241m=\u001b[39m\u001b[38;5;124m'\u001b[39m\u001b[38;5;124m_CMIP6_\u001b[39m\u001b[38;5;124m'\u001b[39m \u001b[38;5;241m+\u001b[39m rid\n\u001b[0;32m---> 10\u001b[0m \u001b[43mtasks\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mrun_with_hydro\u001b[49m\u001b[43m(\u001b[49m\u001b[43mgdir\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m     11\u001b[0m \u001b[43m         \u001b[49m\u001b[43mrun_task\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mtasks\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mrun_from_climate_data\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m     12\u001b[0m \u001b[43m                     \u001b[49m\u001b[43mys\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;241;43m2000\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;66;43;03m# this is important! Start from 2000 glacier\u001b[39;49;00m\n\u001b[1;32m     13\u001b[0m \u001b[43m                     \u001b[49m\u001b[43minit_model_yr\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;241;43m2000\u001b[39;49m\u001b[43m,\u001b[49m\n\u001b[1;32m     14\u001b[0m \u001b[43m                     \u001b[49m\u001b[43mye\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mend_yr\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m     15\u001b[0m \u001b[43m         \u001b[49m\u001b[38;5;66;43;03m# use gcm_data, not climate_historical\u001b[39;49;00m\n\u001b[1;32m     16\u001b[0m \u001b[43m         \u001b[49m\u001b[43mclimate_filename\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[38;5;124;43mgcm_data\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[43m,\u001b[49m\n\u001b[1;32m     17\u001b[0m \u001b[43m         \u001b[49m\u001b[38;5;66;43;03m# use the chosen scenario\u001b[39;49;00m\n\u001b[1;32m     18\u001b[0m \u001b[43m         \u001b[49m\u001b[43mclimate_input_filesuffix\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mrid\u001b[49m\u001b[38;5;241;43m+\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[38;5;124;43m_bc_2000_2019\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[43m,\u001b[49m\n\u001b[1;32m     19\u001b[0m \u001b[43m         \u001b[49m\u001b[38;5;66;43;03m# we start from the previous run, \u001b[39;49;00m\n\u001b[1;32m     20\u001b[0m \u001b[43m         \u001b[49m\u001b[43minit_model_filesuffix\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[38;5;124;43m_spinup_historical\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[43m,\u001b[49m\n\u001b[1;32m     21\u001b[0m \u001b[43m         \u001b[49m\u001b[43mref_geometry_filesuffix\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[38;5;124;43m_spinup_historical\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[43m,\u001b[49m\n\u001b[1;32m     22\u001b[0m \u001b[43m         \u001b[49m\u001b[43mref_area_yr\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43m \u001b[49m\u001b[38;5;241;43m2000\u001b[39;49m\u001b[43m,\u001b[49m\n\u001b[1;32m     23\u001b[0m \u001b[43m         \u001b[49m\u001b[38;5;66;43;03m# recognize the run for later\u001b[39;49;00m\n\u001b[1;32m     24\u001b[0m \u001b[43m         \u001b[49m\u001b[43moutput_filesuffix\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;124;43mf\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[38;5;124;43m_gcm_from_2000_run\u001b[39;49m\u001b[38;5;132;43;01m{\u001b[39;49;00m\u001b[43mrid\u001b[49m\u001b[38;5;132;43;01m}\u001b[39;49;00m\u001b[38;5;124;43m_endyr\u001b[39;49m\u001b[38;5;132;43;01m{\u001b[39;49;00m\u001b[43mend_yr\u001b[49m\u001b[38;5;132;43;01m}\u001b[39;49;00m\u001b[38;5;124;43m'\u001b[39;49m\u001b[38;5;241;43m+\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[38;5;124;43m_bc_2000_2019\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[43m,\u001b[49m\n\u001b[1;32m     25\u001b[0m \u001b[43m         \u001b[49m\u001b[38;5;66;43;03m# add monthly diagnostics\u001b[39;49;00m\n\u001b[1;32m     26\u001b[0m \u001b[43m         \u001b[49m\u001b[43mstore_monthly_hydro\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;28;43;01mTrue\u001b[39;49;00m\u001b[43m)\u001b[49m;\n\u001b[1;32m     28\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m end_yr \u001b[38;5;241m!=\u001b[39m \u001b[38;5;241m2300\u001b[39m: \n\u001b[1;32m     29\u001b[0m     \u001b[38;5;66;03m# only do that for comparison for the common ssps with isimip3b\u001b[39;00m\n\u001b[1;32m     30\u001b[0m     \u001b[38;5;28;01mif\u001b[39;00m gcm\u001b[38;5;241m.\u001b[39mlower() \u001b[38;5;129;01min\u001b[39;00m [\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mgfdl-esm4\u001b[39m\u001b[38;5;124m'\u001b[39m, \u001b[38;5;124m'\u001b[39m\u001b[38;5;124mmpi-esm1-2-hr\u001b[39m\u001b[38;5;124m'\u001b[39m, \u001b[38;5;124m'\u001b[39m\u001b[38;5;124mmri-esm2-0\u001b[39m\u001b[38;5;124m'\u001b[39m]: \n",
      "File \u001b[0;32m~/.local/lib/python3.10/site-packages/oggm/utils/_workflow.py:491\u001b[0m, in \u001b[0;36mentity_task.__call__.<locals>._entity_task\u001b[0;34m(gdir, reset, print_log, return_value, continue_on_error, add_to_log_file, **kwargs)\u001b[0m\n\u001b[1;32m    489\u001b[0m     signal\u001b[38;5;241m.\u001b[39malarm(cfg\u001b[38;5;241m.\u001b[39mPARAMS[\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mtask_timeout\u001b[39m\u001b[38;5;124m'\u001b[39m])\n\u001b[1;32m    490\u001b[0m ex_t \u001b[38;5;241m=\u001b[39m time\u001b[38;5;241m.\u001b[39mtime()\n\u001b[0;32m--> 491\u001b[0m out \u001b[38;5;241m=\u001b[39m \u001b[43mtask_func\u001b[49m\u001b[43m(\u001b[49m\u001b[43mgdir\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\u001b[1;32m    492\u001b[0m ex_t \u001b[38;5;241m=\u001b[39m time\u001b[38;5;241m.\u001b[39mtime() \u001b[38;5;241m-\u001b[39m ex_t\n\u001b[1;32m    493\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m cfg\u001b[38;5;241m.\u001b[39mPARAMS[\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mtask_timeout\u001b[39m\u001b[38;5;124m'\u001b[39m] \u001b[38;5;241m>\u001b[39m \u001b[38;5;241m0\u001b[39m:\n",
      "File \u001b[0;32m~/.local/lib/python3.10/site-packages/oggm/core/flowline.py:3654\u001b[0m, in \u001b[0;36mrun_with_hydro\u001b[0;34m(gdir, run_task, store_monthly_hydro, fixed_geometry_spinup_yr, ref_area_from_y0, ref_area_yr, ref_geometry_filesuffix, **kwargs)\u001b[0m\n\u001b[1;32m   3651\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m fixed_geometry_spinup_yr \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m:\n\u001b[1;32m   3652\u001b[0m     kwargs[\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mfixed_geometry_spinup_yr\u001b[39m\u001b[38;5;124m'\u001b[39m] \u001b[38;5;241m=\u001b[39m fixed_geometry_spinup_yr\n\u001b[0;32m-> 3654\u001b[0m out \u001b[38;5;241m=\u001b[39m \u001b[43mrun_task\u001b[49m\u001b[43m(\u001b[49m\u001b[43mgdir\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\u001b[1;32m   3656\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m out \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m:\n\u001b[1;32m   3657\u001b[0m     \u001b[38;5;28;01mraise\u001b[39;00m InvalidWorkflowError(\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mThe run task (\u001b[39m\u001b[38;5;132;01m{}\u001b[39;00m\u001b[38;5;124m) did not run \u001b[39m\u001b[38;5;124m'\u001b[39m\n\u001b[1;32m   3658\u001b[0m                                \u001b[38;5;124m'\u001b[39m\u001b[38;5;124msuccessfully.\u001b[39m\u001b[38;5;124m'\u001b[39m\u001b[38;5;241m.\u001b[39mformat(run_task\u001b[38;5;241m.\u001b[39m\u001b[38;5;18m__name__\u001b[39m))\n",
      "File \u001b[0;32m~/.local/lib/python3.10/site-packages/oggm/utils/_workflow.py:491\u001b[0m, in \u001b[0;36mentity_task.__call__.<locals>._entity_task\u001b[0;34m(gdir, reset, print_log, return_value, continue_on_error, add_to_log_file, **kwargs)\u001b[0m\n\u001b[1;32m    489\u001b[0m     signal\u001b[38;5;241m.\u001b[39malarm(cfg\u001b[38;5;241m.\u001b[39mPARAMS[\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mtask_timeout\u001b[39m\u001b[38;5;124m'\u001b[39m])\n\u001b[1;32m    490\u001b[0m ex_t \u001b[38;5;241m=\u001b[39m time\u001b[38;5;241m.\u001b[39mtime()\n\u001b[0;32m--> 491\u001b[0m out \u001b[38;5;241m=\u001b[39m \u001b[43mtask_func\u001b[49m\u001b[43m(\u001b[49m\u001b[43mgdir\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\u001b[1;32m    492\u001b[0m ex_t \u001b[38;5;241m=\u001b[39m time\u001b[38;5;241m.\u001b[39mtime() \u001b[38;5;241m-\u001b[39m ex_t\n\u001b[1;32m    493\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m cfg\u001b[38;5;241m.\u001b[39mPARAMS[\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mtask_timeout\u001b[39m\u001b[38;5;124m'\u001b[39m] \u001b[38;5;241m>\u001b[39m \u001b[38;5;241m0\u001b[39m:\n",
      "File \u001b[0;32m~/.local/lib/python3.10/site-packages/oggm/core/flowline.py:3566\u001b[0m, in \u001b[0;36mrun_from_climate_data\u001b[0;34m(gdir, ys, ye, min_ys, max_ys, fixed_geometry_spinup_yr, store_monthly_step, store_model_geometry, store_fl_diagnostics, climate_filename, mb_model, mb_model_class, climate_input_filesuffix, output_filesuffix, init_model_filesuffix, init_model_yr, init_model_fls, zero_initial_glacier, bias, temperature_bias, precipitation_factor, **kwargs)\u001b[0m\n\u001b[1;32m   3563\u001b[0m     ys \u001b[38;5;241m=\u001b[39m ys \u001b[38;5;28;01mif\u001b[39;00m ys \u001b[38;5;241m<\u001b[39m max_ys \u001b[38;5;28;01melse\u001b[39;00m max_ys\n\u001b[1;32m   3565\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m mb_model \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m:\n\u001b[0;32m-> 3566\u001b[0m     mb_model \u001b[38;5;241m=\u001b[39m \u001b[43mMultipleFlowlineMassBalance\u001b[49m\u001b[43m(\u001b[49m\u001b[43mgdir\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m   3567\u001b[0m \u001b[43m                                           \u001b[49m\u001b[43mmb_model_class\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mmb_model_class\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m   3568\u001b[0m \u001b[43m                                           \u001b[49m\u001b[43mfilename\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mclimate_filename\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m   3569\u001b[0m \u001b[43m                                           \u001b[49m\u001b[43mbias\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mbias\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m   3570\u001b[0m \u001b[43m                                           \u001b[49m\u001b[43minput_filesuffix\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mclimate_input_filesuffix\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m   3572\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m temperature_bias \u001b[38;5;129;01mis\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;28;01mNone\u001b[39;00m:\n\u001b[1;32m   3573\u001b[0m     mb_model\u001b[38;5;241m.\u001b[39mtemp_bias \u001b[38;5;241m+\u001b[39m\u001b[38;5;241m=\u001b[39m temperature_bias\n",
      "File \u001b[0;32m~/.local/lib/python3.10/site-packages/oggm/core/massbalance.py:1194\u001b[0m, in \u001b[0;36mMultipleFlowlineMassBalance.__init__\u001b[0;34m(self, gdir, fls, mb_model_class, use_inversion_flowlines, input_filesuffix, **kwargs)\u001b[0m\n\u001b[1;32m   1190\u001b[0m     \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[1;32m   1191\u001b[0m         rgi_filesuffix \u001b[38;5;241m=\u001b[39m input_filesuffix\n\u001b[1;32m   1193\u001b[0m     \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mflowline_mb_models\u001b[38;5;241m.\u001b[39mappend(\n\u001b[0;32m-> 1194\u001b[0m         \u001b[43mmb_model_class\u001b[49m\u001b[43m(\u001b[49m\u001b[43mgdir\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43minput_filesuffix\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mrgi_filesuffix\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m   1195\u001b[0m \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\u001b[1;32m   1197\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mvalid_bounds \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mflowline_mb_models[\u001b[38;5;241m-\u001b[39m\u001b[38;5;241m1\u001b[39m]\u001b[38;5;241m.\u001b[39mvalid_bounds\n\u001b[1;32m   1198\u001b[0m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mhemisphere \u001b[38;5;241m=\u001b[39m gdir\u001b[38;5;241m.\u001b[39mhemisphere\n",
      "File \u001b[0;32m~/.local/lib/python3.10/site-packages/oggm/core/massbalance.py:439\u001b[0m, in \u001b[0;36mMonthlyTIModel.__init__\u001b[0;34m(self, gdir, filename, input_filesuffix, fl_id, melt_f, temp_bias, prcp_fac, bias, ys, ye, repeat, check_calib_params)\u001b[0m\n\u001b[1;32m    437\u001b[0m \u001b[38;5;66;03m# Read climate file\u001b[39;00m\n\u001b[1;32m    438\u001b[0m fpath \u001b[38;5;241m=\u001b[39m gdir\u001b[38;5;241m.\u001b[39mget_filepath(filename, filesuffix\u001b[38;5;241m=\u001b[39minput_filesuffix)\n\u001b[0;32m--> 439\u001b[0m \u001b[38;5;28;01mwith\u001b[39;00m \u001b[43mncDataset\u001b[49m\u001b[43m(\u001b[49m\u001b[43mfpath\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mmode\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[38;5;124;43mr\u001b[39;49m\u001b[38;5;124;43m'\u001b[39;49m\u001b[43m)\u001b[49m \u001b[38;5;28;01mas\u001b[39;00m nc:\n\u001b[1;32m    440\u001b[0m     \u001b[38;5;66;03m# time\u001b[39;00m\n\u001b[1;32m    441\u001b[0m     time \u001b[38;5;241m=\u001b[39m nc\u001b[38;5;241m.\u001b[39mvariables[\u001b[38;5;124m'\u001b[39m\u001b[38;5;124mtime\u001b[39m\u001b[38;5;124m'\u001b[39m]\n\u001b[1;32m    442\u001b[0m     time \u001b[38;5;241m=\u001b[39m cftime\u001b[38;5;241m.\u001b[39mnum2date(time[:], time\u001b[38;5;241m.\u001b[39munits, calendar\u001b[38;5;241m=\u001b[39mtime\u001b[38;5;241m.\u001b[39mcalendar)\n",
      "File \u001b[0;32m~/.local/lib/python3.10/site-packages/oggm/utils/_workflow.py:361\u001b[0m, in \u001b[0;36mncDataset.__init__\u001b[0;34m(self, *args, **kwargs)\u001b[0m\n\u001b[1;32m    360\u001b[0m \u001b[38;5;28;01mdef\u001b[39;00m \u001b[38;5;21m__init__\u001b[39m(\u001b[38;5;28mself\u001b[39m, \u001b[38;5;241m*\u001b[39margs, \u001b[38;5;241m*\u001b[39m\u001b[38;5;241m*\u001b[39mkwargs):\n\u001b[0;32m--> 361\u001b[0m     \u001b[38;5;28;43msuper\u001b[39;49m\u001b[43m(\u001b[49m\u001b[43mncDataset\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[43m)\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[38;5;21;43m__init__\u001b[39;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\u001b[1;32m    362\u001b[0m     \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mset_auto_mask(\u001b[38;5;28;01mFalse\u001b[39;00m)\n",
      "File \u001b[0;32msrc/netCDF4/_netCDF4.pyx:2353\u001b[0m, in \u001b[0;36mnetCDF4._netCDF4.Dataset.__init__\u001b[0;34m()\u001b[0m\n",
      "File \u001b[0;32msrc/netCDF4/_netCDF4.pyx:1963\u001b[0m, in \u001b[0;36mnetCDF4._netCDF4._ensure_nc_success\u001b[0;34m()\u001b[0m\n",
      "\u001b[0;31mFileNotFoundError\u001b[0m: [Errno 2] No such file or directory: b'/tmp/OGGM/OGGM_gcm_output/per_glacier/RGI60-01/RGI60-01.16/RGI60-01.16122/gcm_data_CMIP6_MRI-ESM2-0_ssp534-over_bc_2000_2019.nc'"
     ]
    }
   ],
   "source": [
    "for gcm in gcms_cmip6.gcm.unique(): ##TEST:\n",
    "    df1 = gcms_cmip6.loc[gcms_cmip6.gcm == gcm]\n",
    "    for ssp in df1.ssp.unique():\n",
    "        df2 = df1.loc[df1.ssp == ssp]\n",
    "        assert len(df2) == 2\n",
    "        ft = df2.loc[df2['var'] == 'tas'].iloc[0]\n",
    "        rid = ft.fname.replace('_r1i1p1f1_tas.nc', '')\n",
    "        rid='_CMIP6_' + rid\n",
    "\n",
    "        tasks.run_with_hydro(gdir,\n",
    "                 run_task=tasks.run_from_climate_data,\n",
    "                             ys=2000, # this is important! Start from 2000 glacier\n",
    "                             init_model_yr=2000,\n",
    "                             ye=end_yr,\n",
    "                 # use gcm_data, not climate_historical\n",
    "                 climate_filename='gcm_data',\n",
    "                 # use the chosen scenario\n",
    "                 climate_input_filesuffix=rid+'_bc_2000_2019',\n",
    "                 # we start from the previous run, \n",
    "                 init_model_filesuffix='_spinup_historical',\n",
    "                 ref_geometry_filesuffix='_spinup_historical',\n",
    "                 ref_area_yr = 2000,\n",
    "                 # recognize the run for later\n",
    "                 output_filesuffix=f'_gcm_from_2000_run{rid}_endyr{end_yr}'+'_bc_2000_2019',\n",
    "                 # add monthly diagnostics\n",
    "                 store_monthly_hydro=True);\n",
    "\n",
    "        if end_yr != 2300: \n",
    "            # only do that for comparison for the common ssps with isimip3b\n",
    "            if gcm.lower() in ['gfdl-esm4', 'mpi-esm1-2-hr', 'mri-esm2-0']: \n",
    "                if ssp in ['ssp126', 'ssp370', 'ssp585']:\n",
    "                    tasks.run_with_hydro(gdir,\n",
    "                             run_task=tasks.run_from_climate_data,\n",
    "                                         ys=2000, # this is important! Start from 2000 glacier\n",
    "                                         init_model_yr=2000,\n",
    "                                         ye=end_yr,\n",
    "                             # use gcm_data, not climate_historical\n",
    "                             climate_filename='gcm_data',\n",
    "                             # use the chosen scenario\n",
    "                             climate_input_filesuffix=rid+'_bc_1979_2014',\n",
    "                             # we start from the previous run, \n",
    "                             init_model_filesuffix='_spinup_historical',\n",
    "                             ref_geometry_filesuffix='_spinup_historical',\n",
    "                             ref_area_yr = 2000,\n",
    "                             # recognize the run for later\n",
    "                             output_filesuffix=f'_gcm_from_2000_run{rid}_endyr{end_yr}'+'_bc_1979_2014',\n",
    "                             # add monthly diagnostics\n",
    "                             store_monthly_hydro=True);"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "384e2541-2b7c-48ee-a51d-1a5d3830e397",
   "metadata": {},
   "outputs": [],
   "source": [
    "\n",
    "\n",
    "# merge data together\n",
    "if end_yr == 2100:\n",
    "    for member in isimip3b_members:    \n",
    "        for ssp in ['ssp126', 'ssp370', 'ssp585']:\n",
    "            rid = f'_ISIMIP3b_{member}_{ssp}'\n",
    "            # for W5E5 as past climate \n",
    "            utils.compile_run_output(gdirs, input_filesuffix=f'_merged_from_2000_run{rid}', \n",
    "                            path=os.path.join(eq_dir, f'run_hydro_w5e5_gcm_merged_endyr2100{rid}_rgi{rgi_reg}_{id0}_{id1}.nc'))\n",
    "            utils.compile_run_output(gdirs, input_filesuffix=f'_merged_from_2000_run{rid}_bc_2000_2019', \n",
    "                            path=os.path.join(eq_dir, f'run_hydro_w5e5_gcm_merged_endyr2100{rid}_bc_2000_2019_rgi{rgi_reg}_{id0}_{id1}.nc'))\n",
    "            \n",
    "            # for the GCM as past climate \n",
    "            utils.compile_run_output(gdirs, input_filesuffix=f'_gcm_from_2000_run{rid}', \n",
    "                            path=os.path.join(eq_dir, f'run_hydro_gcm_from_2000_endyr2100{rid}_rgi{rgi_reg}_{id0}_{id1}.nc'))\n",
    "            utils.compile_run_output(gdirs, input_filesuffix=f'_gcm_from_2000_run{rid}_bc_2000_2019', \n",
    "                            path=os.path.join(eq_dir, f'run_hydro_gcm_from_2000_endyr2100{rid}_bc_2000_2019_rgi{rgi_reg}_{id0}_{id1}.nc'))\n",
    "\n",
    "\n",
    "for gcm in gcms_cmip6.gcm.unique(): \n",
    "    df1 = gcms_cmip6.loc[gcms_cmip6.gcm == gcm]\n",
    "    for ssp in df1.ssp.unique():\n",
    "        df2 = df1.loc[df1.ssp == ssp]\n",
    "        assert len(df2) == 2\n",
    "        ft = df2.loc[df2['var'] == 'tas'].iloc[0]\n",
    "        rid = ft.fname.replace('_r1i1p1f1_tas.nc', '')\n",
    "        rid='_CMIP6_' + rid\n",
    "\n",
    "        utils.compile_run_output(gdirs, input_filesuffix=f'_merged_from_2000_run{rid}_endyr{end_yr}_bc_2000_2019', \n",
    "                                path=os.path.join(eq_dir, f'run_hydro_w5e5_gcm_merged_endyr{end_yr}{rid}_bc_2000_2019_rgi{rgi_reg}_{id0}_{id1}.nc'))\n",
    "\n",
    "        utils.compile_run_output(gdirs, input_filesuffix=f'_gcm_from_2000_run{rid}_endyr{end_yr}_bc_2000_2019', \n",
    "                                path=os.path.join(eq_dir, f'run_hydro_gcm_from_2000_endyr{end_yr}{rid}_bc_2000_2019_rgi{rgi_reg}_{id0}_{id1}.nc'))\n",
    "        \n",
    "        if end_yr == 2100:\n",
    "            # only do that for comparison for the common ssps with isimip3b\n",
    "            if gcm.lower() in ['gfdl-esm4', 'mpi-esm1-2-hr', 'mri-esm2-0']: \n",
    "                if ssp in ['ssp126', 'ssp370', 'ssp585']:\n",
    "                    utils.compile_run_output(gdirs, input_filesuffix=f'_merged_from_2000_run{rid}_endyr{end_yr}_bc_1979_2014', \n",
    "                                            path=os.path.join(eq_dir, f'run_hydro_w5e5_gcm_merged_endyr{end_yr}{rid}_bc_1979_2014_rgi{rgi_reg}_{id0}_{id1}.nc'))\n",
    "\n",
    "                    utils.compile_run_output(gdirs, input_filesuffix=f'_gcm_from_2000_run{rid}_endyr{end_yr}_bc_1979_2014', \n",
    "                                            path=os.path.join(eq_dir, f'run_hydro_gcm_from_2000_endyr{end_yr}{rid}_bc_1979_2014_rgi{rgi_reg}_{id0}_{id1}.nc'))\n",
    "\n",
    "\n",
    "    \n",
    "\n",
    "log.workflow('OGGM Done')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "91c27c56-17c9-4349-a52f-b02ca54c6c47",
   "metadata": {},
   "outputs": [],
   "source": []
  }
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