{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "e73071c6-9ef0-4a54-856c-139194dcf8b5",
   "metadata": {},
   "source": [
    "## Aggregate all glaciers via filling\n",
    "\n",
    "- idea aggregate on each batch directly... "
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0511d98e-7d59-44dd-a0e7-18ef25426938",
   "metadata": {},
   "source": [
    "- weird glaicer list checked in 00d_weird_glacier_check ..."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "00c32fa8-b5c1-451c-afa2-52f2460235ff",
   "metadata": {},
   "outputs": [],
   "source": [
    "import logging\n",
    "from datetime import timedelta\n",
    "import os\n",
    "import sys\n",
    "import numpy as np\n",
    "import xarray as xr\n",
    "\n",
    "import pandas as pd\n",
    "import geopandas as gpd\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "# Import and verify\n",
    "import oggm\n",
    "import gc\n",
    "\n",
    "\n",
    "import oggm.cfg as cfg\n",
    "from oggm import utils, tasks, entity_task\n",
    "import seaborn as sns\n",
    "from func_add_terrafirma import SCENARIO_PARENTS\n",
    "from pathlib import Path\n",
    "\n",
    "variables = ['volume', 'volume_bsl', 'area','is_partial_output']\n",
    "\n",
    "rgi_regions = [f\"{region:02d}\" for region in range(1, 20)]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c8521ce9-ae17-423d-869a-629a434d3eb1",
   "metadata": {},
   "source": [
    "## Concatenate the normal runs (with MB elevation feedback)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "7f030036-92b3-49b1-9181-7ff4f421192a",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
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      "18 finished\n",
      "19 3\n",
      "19 finished\n"
     ]
    }
   ],
   "source": [
    "_fp_init = f'run_terrafirma_UKESM1-2-LL_esm_up2p0_bc_1975_2014_to_0_40_sim_year_starting_at_1979_glacier_state_from_0_sim_year_climate_*.nc'\n",
    "\n",
    "### this will be concatenated over the batches... \n",
    "error_glaciers_dict = {}\n",
    "growing_border_glaciers_dict = {}\n",
    "list_ds_reg_filled = []\n",
    "for rgi_reg in rgi_regions:\n",
    "    error_glaciers = []\n",
    "    growing_border_glaciers = []\n",
    "    ds_reg_filled_l = []\n",
    "\n",
    "    p = f'/home/www/lschuster/terrafirma_oggm_proj/output_dir/RGI{rgi_reg}/'    \n",
    "    base_path = Path(p)\n",
    "    matching_files = sorted(base_path.rglob(f'{_fp_init}'))\n",
    "    print(rgi_reg, len(matching_files))\n",
    "\n",
    "    for mi in matching_files:\n",
    "        _,b = str(mi).split('Batch')\n",
    "        dict_ds = []\n",
    "        for scenario in SCENARIO_PARENTS.keys():\n",
    "            if 'up2p0' in scenario:\n",
    "                fp =f'run_terrafirma_UKESM1-2-LL_esm_{scenario}_bc_1975_2014_to_0_40_sim_year_starting_at_1979_glacier_state_from_0_sim_year_climate_'\n",
    "                _d = xr.open_dataset(f'{p}{fp}Batch{b}')\n",
    "                _d = _d.reset_coords()\n",
    "                _d = _d[variables]\n",
    "                _d = _d.load()\n",
    "                if len(_d.is_partial_output.where(_d.is_partial_output==1).dropna(dim='rgi_id'))>0:\n",
    "                    #print(scenario, len(_d.is_partial_output.where(_d.is_partial_output==1).dropna(dim='rgi_id')))\n",
    "                    error_glaciers.append(list(_d.rgi_id.where(_d.is_partial_output.isnull(), drop=True).values))\n",
    "                    growing_border_glaciers.append(list(_d.rgi_id.where(_d.is_partial_output == 1.0, drop=True).values))\n",
    "                # Add scenario as a new dimension and coordinate\n",
    "                _d = _d.expand_dims(scenario=[scenario])\n",
    "                dict_ds.append(_d)\n",
    "        ds_reg = xr.concat(dict_ds,\n",
    "        dim=\"scenario\",\n",
    "        join=\"outer\",\n",
    "        coords=\"minimal\",\n",
    "        data_vars=\"all\",\n",
    "        compat=\"no_conflicts\",\n",
    "        )\n",
    "        ### we do this on every batch individually... \n",
    "        # remove the glacier(s) that is not working in any scenario at all time periods\n",
    "        ds_reg = ds_reg.dropna(dim='rgi_id', how='all')\n",
    "        # fill temporary over entire time axis \n",
    "        volume_filled_raw = ds_reg.volume.ffill(dim='time')\n",
    "        volume_bsl_filled_raw = ds_reg.volume_bsl.ffill(dim='time')\n",
    "        area_filled_raw = ds_reg.area.ffill(dim='time')\n",
    "        \n",
    "        # where do values exist (this is the same for each variable)\n",
    "        # sufficient that one glacier works (this is just to check how long the scenario goes...)\n",
    "        scenario_mask = ds_reg.volume.sum(dim='rgi_id', skipna=True, min_count=1).notnull() \n",
    "        \n",
    "        # only keep those years, where the actual scenario exists \n",
    "        volume_filled = volume_filled_raw.where(scenario_mask)\n",
    "        volume_bsl_filled = volume_bsl_filled_raw.where(scenario_mask)\n",
    "        area_filled = area_filled_raw.where(scenario_mask)\n",
    "        \n",
    "        # regional sum ... \n",
    "        regional_volume_filled = volume_filled.sum(dim='rgi_id', skipna=False)\n",
    "        regional_volume_bsl_filled = volume_bsl_filled.sum(dim='rgi_id', skipna=False)\n",
    "        regional_area_filled = area_filled.sum(dim='rgi_id', skipna=False)\n",
    "         \n",
    "        # initial area \n",
    "        # check that it is the same for each scenario\n",
    "        np.testing.assert_allclose(area_filled.isel(time=0).std(dim='scenario')/area_filled.isel(time=0).mean(dim='scenario'),\n",
    "                                   0, \n",
    "                                   atol=1e-3)\n",
    "        initial_area = area_filled.isel(time=0)\n",
    "        \n",
    "        # Mask for values that were filled and fall within the true scenario lifespan\n",
    "        was_filled = volume_filled_raw.notnull() & ds_reg.volume.isnull()\n",
    "        was_filled = was_filled.where(scenario_mask, False) # Discard fills past the scenario's true end\n",
    "        \n",
    "        # Initial Area represented by filled glaciers at each scenario and timestep\n",
    "        initial_area_filled = (\n",
    "            was_filled.astype(float) * initial_area).sum(\n",
    "            dim=\"rgi_id\",\n",
    "            skipna=True)        \n",
    "        \n",
    "        initial_area_filled.name = \"initial area_filled\"\n",
    "        \n",
    "        initial_area_filled.attrs = {\n",
    "            \"long_name\": \"initial glacier area represented by filled volume values\",\n",
    "            \"units\": \"m2\",\n",
    "            \"description\": (\n",
    "                \"For every scenario and timestep, initial\"\n",
    "                \"glacier area belonging to glaciers whose volume value was filled.\"\n",
    "            ),\n",
    "        }\n",
    "        \n",
    "        ds_reg_filled_b = regional_volume_filled.to_dataset()\n",
    "        ds_reg_filled_b['volume_bsl'] = regional_volume_bsl_filled\n",
    "        ds_reg_filled_b['area'] = regional_area_filled\n",
    "        ds_reg_filled_b['area_filled'] = initial_area_filled\n",
    "        ds_reg_filled_b['rgi_reg'] = rgi_reg\n",
    "        ds_reg_filled_b['batch'] = b[1:-3]\n",
    "        ds_reg_filled_b = ds_reg_filled_b.set_coords('batch')\n",
    "    \n",
    "        ds_reg_filled_l.append(ds_reg_filled_b)\n",
    "\n",
    "        for _ds in dict_ds:\n",
    "            _ds.close()\n",
    "        \n",
    "        ds_reg.close()\n",
    "        \n",
    "        # Remove the large glacier-level arrays before the next batch\n",
    "        del (dict_ds,\n",
    "            ds_reg,\n",
    "            volume_filled_raw,\n",
    "            volume_bsl_filled_raw,\n",
    "            area_filled_raw,\n",
    "            volume_filled,\n",
    "            volume_bsl_filled,\n",
    "            area_filled,\n",
    "            scenario_mask,\n",
    "            initial_area,\n",
    "            was_filled,\n",
    "            initial_area_filled,\n",
    "            regional_volume_filled,\n",
    "            regional_volume_bsl_filled,\n",
    "            regional_area_filled)\n",
    "        gc.collect()\n",
    "\n",
    "    ds_reg_filled = xr.concat(ds_reg_filled_l, dim='batch')\n",
    "    ds_reg_filled = ds_reg_filled.sum(dim='batch', skipna = False)\n",
    "    ds_reg_filled = ds_reg_filled.reset_coords()\n",
    "    ds_reg_filled = ds_reg_filled[['volume','volume_bsl','area','area_filled']]\n",
    "    ds_reg_filled['perc_init_area_filled'] = 100*ds_reg_filled['area_filled']/ds_reg_filled['area'].isel(time=0)\n",
    "        \n",
    "    ds_reg_filled['rgi_reg'] = rgi_reg\n",
    "    ds_reg_filled = ds_reg_filled.set_coords('rgi_reg')\n",
    "    list_ds_reg_filled.append(ds_reg_filled)\n",
    "    growing_border_glaciers_dict[rgi_reg] = list(set(np.concatenate(growing_border_glaciers)))\n",
    "    error_glaciers_dict[rgi_reg] = list(set(np.concatenate(error_glaciers)))\n",
    "    print(rgi_reg, 'finished')\n",
    "ds_reg_filled_all = xr.concat(list_ds_reg_filled, dim='rgi_reg')\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "fc2b90b9-954c-443f-856f-8c8f76ad990e",
   "metadata": {},
   "source": [
    "#### Compute SLE since 1975 and save it as additional variable "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 86,
   "id": "24ec73d6-cbed-4738-b063-6dba6df1cf3f",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "336.75494\n"
     ]
    }
   ],
   "source": [
    "### similarly done as in Schuster et al. (2025): \n",
    "# http://localhost:7269/lab/tree/www_lschuster/provide/gfdl-esm2m_oversh_stab_uni_bern/B_main_analysis_figure_creation/2a_fig_2_suppl_prcp.ipynb\n",
    "# sea level makes only sense globally probably\n",
    "ds_reg_filled_all['volume_asl']= ds_reg_filled_all['volume']-ds_reg_filled_all['volume_bsl']\n",
    "# in 1975 (start of simluations), we just have one estimate, check this \n",
    "assert np.all(ds_reg_filled_all.sel(time=1975).volume_asl.std(dim='scenario')/ds_reg_filled_all.sel(time=1975).volume_asl.mean(dim='scenario')<0.001)\n",
    "ds_1975_volume_asl = ds_reg_filled_all.sel(time=1975).volume_asl.mean(dim='scenario')\n",
    "# test when assuming that entire volume above sea level completely melts \n",
    "vol_asl_diff_1975 = ds_1975_volume_asl\n",
    "# convert m3 into sea-level equivalent \n",
    "A_ocean = 3.625 * 10**8 * 1e6 # km2 --> 1e6\n",
    "m_slr_all_1975_volume_lost = (vol_asl_diff_1975/A_ocean) *900/1028 # rhoice/rho_ocean\n",
    "mm_slr_all_1975_volume_lost = m_slr_all_1975_volume_lost * 1000\n",
    "### Farinotti et al 2019 states around 333mm in 2000, so around 336 in 1975 sounds reasonable... oK! \n",
    "# also note that this is the OGGM above sea-level estimates, thus can be different to the Farinotti et al. 2019 community estimate \n",
    "# (even if we would look at the same date, but here we also look at another date, i.e. 1975 and not the inventory year)\n",
    "print(mm_slr_all_1975_volume_lost.sum().values)\n",
    "## now compute slr from glacier melt from the various scenarios\n",
    "# in 2500, volume asl depends on scenario\n",
    "ds_volume_asl = ds_reg_filled_all.volume_asl\n",
    "\n",
    "vol_asl_diff = vol_asl_diff_1975 - ds_volume_asl\n",
    "# convert m3 into sea-level equivalent \n",
    "m_slr = (vol_asl_diff/A_ocean) *900/1028 # rhoice/rho_ocean\n",
    "mm_slr = m_slr * 1000\n",
    "ds_reg_filled_all['mm_slr_since_1975'] = mm_slr\n",
    "ds_reg_filled_all = ds_reg_filled_all.drop_vars('volume_asl')\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 88,
   "id": "8821134b-a973-43b2-b015-5ee9c5cb3af9",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(323.96343994)"
      ]
     },
     "execution_count": 88,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "mm_slr_global_since_1975 = ds_reg_filled_all['mm_slr_since_1975'].sum(dim='rgi_reg') \n",
    "assert np.all(mm_slr_global_since_1975 >-2)\n",
    "# the total glacier slr contribution since 1975 should be less than if all glaciers melted away (assuming 1975 volume)\n",
    "assert np.all(mm_slr_global_since_1975< mm_slr_all_1975_volume_lost.sum())\n",
    "\n",
    "mm_slr_global_since_1975.max().values"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 102,
   "id": "008d6abe-de05-4091-b939-9a07244ddacf",
   "metadata": {},
   "outputs": [],
   "source": [
    "\n",
    "ds_reg_filled_all.attrs['OGGM_version'] = 'oggm_v163 (but includes option that saves glacier outputs that grow out of border, see OGGM_commit)'\n",
    "ds_reg_filled_all.attrs['OGGM_commit'] = 'git+https://github.com/fmaussion/oggm.git@8adcdb863afc02cd7a90d52565f54302aa05f38c'\n",
    "ds_reg_filled_all.attrs['RGI_version'] = 'rgiv62'\n",
    "\n",
    "ds_reg_filled_all.attrs['info'] = \"\"\"Reanalysis dataset used for calibration: W5E5.\n",
    "Bias correction period: 1975–2014, applied from W5E5 to up2p0 simulation years 0–39.\n",
    "Simulations were initialized using the 1979 glacier state from the dynamical spinup\n",
    "\"\"\"\n",
    "\n",
    "ds_reg_filled_all.attrs['time_validity'] = \"\"\"All variables describe the state at the beginning of the given year.\n",
    "For all \"up2p0\"-related scenarios, the time variable was shifted to start in 1975 instead of 1850, to match the adjusted climate period more realistically.\n",
    "\"\"\"\n",
    "# For the \"hist\"-scenario, we start in the original 1975 year.  <-- not used anymore...\n",
    "\n",
    "ds_reg_filled_all.attrs['rgi_reg_info'] = 'sum over all rgi_reg to get global estimates'\n",
    "ds_reg_filled_all.volume.attrs['unit'] = 'm3'\n",
    "ds_reg_filled_all.area.attrs['unit'] = 'm2'\n",
    "ds_reg_filled_all.area_filled.attrs['unit'] = 'm2'\n",
    "ds_reg_filled_all.perc_init_area_filled.attrs['unit'] = '%'\n",
    "\n",
    "ds_reg_filled_all.mm_slr_since_1975.attrs['unit'] = 'mm sea-level rise since 1975 from glaciers'\n",
    "ds_reg_filled_all.volume_bsl.attrs['unit'] = 'm3' \n",
    "ds_reg_filled_all.volume_bsl.attrs['info'] = 'Regional glacier volume below sea-level from all glaciers that did not fail already at the beginning, out of border growing glaciers filled with last estimate'\n",
    "ds_reg_filled_all.volume.attrs['info'] = 'Regional total glacier volume from all glaciers that did not fail already at the beginning, out of border growing glaciers filled with last estimate'\n",
    "ds_reg_filled_all.area.attrs['info'] = 'Regional total glacier area from all glaciers that did not fail already at the beginning, out of border growing glaciers filled with last estimate'\n",
    "ds_reg_filled_all.area_filled.attrs['info'] = 'Regional total glacier area that got \"filled\" by using estimates from a previous step where the glaciers did not yet grow out of border'\n",
    "ds_reg_filled_all.perc_init_area_filled.attrs['info'] = 'Regional percentage of the total initial glacier area belonging to glaciers whose volume value was filled with the last available estimate.'\n",
    "\n",
    "ds_reg_filled_all.mm_slr_since_1975.attrs['info'] = \"\"\"\n",
    "Sea-level rise contribution from glaciers.\n",
    "Same approach as in Schuster et al. (2025).\n",
    "\n",
    "Steps:\n",
    "1. ds_reg_filled_all['volume_asl'] = ds_reg_filled_all['volume'] - ds_reg_filled_all['volume_bsl']\n",
    "2. ds_1975_volume_asl = ds_reg_filled_all.sel(time=1975).volume_asl.mean(dim='scenario')\n",
    "2. A_ocean = 3.625e8 * 1e6  # km² --> m²\n",
    "3. vol_asl_diff = ds_1975_volume_asl - ds_reg_filled_all['volume_asl']  # compute difference relative to 1975\n",
    "4. m_slr = (vol_asl_diff / A_ocean) * 900 / 1028  # convert volume to m sea-level rise\n",
    "5. mm_slr = m_slr * 1000  # convert meters to millimeters\n",
    "\"\"\"\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 104,
   "id": "7191b42b-2ce4-4d31-9308-6f2939d06b99",
   "metadata": {},
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       "    --jp-layout-color2,\n",
       "    hsl(from var(--pst-color-on-background, white) h s calc(l - 15))\n",
       "  );\n",
       "}\n",
       "\n",
       "html[theme=\"dark\"],\n",
       "html[data-theme=\"dark\"],\n",
       "body[data-theme=\"dark\"],\n",
       "body.vscode-dark {\n",
       "  --xr-font-color0: var(\n",
       "    --jp-content-font-color0,\n",
       "    var(--pst-color-text-base, rgba(255, 255, 255, 1))\n",
       "  );\n",
       "  --xr-font-color2: var(\n",
       "    --jp-content-font-color2,\n",
       "    var(--pst-color-text-base, rgba(255, 255, 255, 0.54))\n",
       "  );\n",
       "  --xr-font-color3: var(\n",
       "    --jp-content-font-color3,\n",
       "    var(--pst-color-text-base, rgba(255, 255, 255, 0.38))\n",
       "  );\n",
       "  --xr-border-color: var(\n",
       "    --jp-border-color2,\n",
       "    hsl(from var(--pst-color-on-background, #111111) h s calc(l + 10))\n",
       "  );\n",
       "  --xr-disabled-color: var(\n",
       "    --jp-layout-color3,\n",
       "    hsl(from var(--pst-color-on-background, #111111) h s calc(l + 40))\n",
       "  );\n",
       "  --xr-background-color: var(\n",
       "    --jp-layout-color0,\n",
       "    var(--pst-color-on-background, #111111)\n",
       "  );\n",
       "  --xr-background-color-row-even: var(\n",
       "    --jp-layout-color1,\n",
       "    hsl(from var(--pst-color-on-background, #111111) h s calc(l + 5))\n",
       "  );\n",
       "  --xr-background-color-row-odd: var(\n",
       "    --jp-layout-color2,\n",
       "    hsl(from var(--pst-color-on-background, #111111) h s calc(l + 15))\n",
       "  );\n",
       "}\n",
       "\n",
       ".xr-wrap {\n",
       "  display: block !important;\n",
       "  min-width: 300px;\n",
       "  max-width: 700px;\n",
       "  line-height: 1.6;\n",
       "}\n",
       "\n",
       ".xr-text-repr-fallback {\n",
       "  /* fallback to plain text repr when CSS is not injected (untrusted notebook) */\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-header {\n",
       "  padding-top: 6px;\n",
       "  padding-bottom: 6px;\n",
       "  margin-bottom: 4px;\n",
       "  border-bottom: solid 1px var(--xr-border-color);\n",
       "}\n",
       "\n",
       ".xr-header > div,\n",
       ".xr-header > ul {\n",
       "  display: inline;\n",
       "  margin-top: 0;\n",
       "  margin-bottom: 0;\n",
       "}\n",
       "\n",
       ".xr-obj-type,\n",
       ".xr-obj-name,\n",
       ".xr-group-name {\n",
       "  margin-left: 2px;\n",
       "  margin-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-group-name::before {\n",
       "  content: \"📁\";\n",
       "  padding-right: 0.3em;\n",
       "}\n",
       "\n",
       ".xr-group-name,\n",
       ".xr-obj-type {\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-sections {\n",
       "  padding-left: 0 !important;\n",
       "  display: grid;\n",
       "  grid-template-columns: 150px auto auto 1fr 0 20px 0 20px;\n",
       "  margin-block-start: 0;\n",
       "  margin-block-end: 0;\n",
       "}\n",
       "\n",
       ".xr-section-item {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-section-item input {\n",
       "  display: inline-block;\n",
       "  opacity: 0;\n",
       "  height: 0;\n",
       "  margin: 0;\n",
       "}\n",
       "\n",
       ".xr-section-item input + label {\n",
       "  color: var(--xr-disabled-color);\n",
       "  border: 2px solid transparent !important;\n",
       "}\n",
       "\n",
       ".xr-section-item input:enabled + label {\n",
       "  cursor: pointer;\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-section-item input:focus + label {\n",
       "  border: 2px solid var(--xr-font-color0) !important;\n",
       "}\n",
       "\n",
       ".xr-section-item input:enabled + label:hover {\n",
       "  color: var(--xr-font-color0);\n",
       "}\n",
       "\n",
       ".xr-section-summary {\n",
       "  grid-column: 1;\n",
       "  color: var(--xr-font-color2);\n",
       "  font-weight: 500;\n",
       "}\n",
       "\n",
       ".xr-section-summary > span {\n",
       "  display: inline-block;\n",
       "  padding-left: 0.5em;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:disabled + label {\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-section-summary-in + label:before {\n",
       "  display: inline-block;\n",
       "  content: \"►\";\n",
       "  font-size: 11px;\n",
       "  width: 15px;\n",
       "  text-align: center;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:disabled + label:before {\n",
       "  color: var(--xr-disabled-color);\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked + label:before {\n",
       "  content: \"▼\";\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked + label > span {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-section-summary,\n",
       ".xr-section-inline-details {\n",
       "  padding-top: 4px;\n",
       "}\n",
       "\n",
       ".xr-section-inline-details {\n",
       "  grid-column: 2 / -1;\n",
       "}\n",
       "\n",
       ".xr-section-details {\n",
       "  display: none;\n",
       "  grid-column: 1 / -1;\n",
       "  margin-top: 4px;\n",
       "  margin-bottom: 5px;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked ~ .xr-section-details {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-group-box {\n",
       "  display: inline-grid;\n",
       "  grid-template-columns: 0px 20px auto;\n",
       "  width: 100%;\n",
       "}\n",
       "\n",
       ".xr-group-box-vline {\n",
       "  grid-column-start: 1;\n",
       "  border-right: 0.2em solid;\n",
       "  border-color: var(--xr-border-color);\n",
       "  width: 0px;\n",
       "}\n",
       "\n",
       ".xr-group-box-hline {\n",
       "  grid-column-start: 2;\n",
       "  grid-row-start: 1;\n",
       "  height: 1em;\n",
       "  width: 20px;\n",
       "  border-bottom: 0.2em solid;\n",
       "  border-color: var(--xr-border-color);\n",
       "}\n",
       "\n",
       ".xr-group-box-contents {\n",
       "  grid-column-start: 3;\n",
       "}\n",
       "\n",
       ".xr-array-wrap {\n",
       "  grid-column: 1 / -1;\n",
       "  display: grid;\n",
       "  grid-template-columns: 20px auto;\n",
       "}\n",
       "\n",
       ".xr-array-wrap > label {\n",
       "  grid-column: 1;\n",
       "  vertical-align: top;\n",
       "}\n",
       "\n",
       ".xr-preview {\n",
       "  color: var(--xr-font-color3);\n",
       "}\n",
       "\n",
       ".xr-array-preview,\n",
       ".xr-array-data {\n",
       "  padding: 0 5px !important;\n",
       "  grid-column: 2;\n",
       "}\n",
       "\n",
       ".xr-array-data,\n",
       ".xr-array-in:checked ~ .xr-array-preview {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-array-in:checked ~ .xr-array-data,\n",
       ".xr-array-preview {\n",
       "  display: inline-block;\n",
       "}\n",
       "\n",
       ".xr-dim-list {\n",
       "  display: inline-block !important;\n",
       "  list-style: none;\n",
       "  padding: 0 !important;\n",
       "  margin: 0;\n",
       "}\n",
       "\n",
       ".xr-dim-list li {\n",
       "  display: inline-block;\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "}\n",
       "\n",
       ".xr-dim-list:before {\n",
       "  content: \"(\";\n",
       "}\n",
       "\n",
       ".xr-dim-list:after {\n",
       "  content: \")\";\n",
       "}\n",
       "\n",
       ".xr-dim-list li:not(:last-child):after {\n",
       "  content: \",\";\n",
       "  padding-right: 5px;\n",
       "}\n",
       "\n",
       ".xr-has-index {\n",
       "  font-weight: bold;\n",
       "}\n",
       "\n",
       ".xr-var-list,\n",
       ".xr-var-item {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-var-item > div,\n",
       ".xr-var-item label,\n",
       ".xr-var-item > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-even);\n",
       "  border-color: var(--xr-background-color-row-odd);\n",
       "  margin-bottom: 0;\n",
       "  padding-top: 2px;\n",
       "}\n",
       "\n",
       ".xr-var-item > .xr-var-name:hover span {\n",
       "  padding-right: 5px;\n",
       "}\n",
       "\n",
       ".xr-var-list > li:nth-child(odd) > div,\n",
       ".xr-var-list > li:nth-child(odd) > label,\n",
       ".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-odd);\n",
       "  border-color: var(--xr-background-color-row-even);\n",
       "}\n",
       "\n",
       ".xr-var-name {\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-var-dims {\n",
       "  grid-column: 2;\n",
       "}\n",
       "\n",
       ".xr-var-dtype {\n",
       "  grid-column: 3;\n",
       "  text-align: right;\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-var-preview {\n",
       "  grid-column: 4;\n",
       "}\n",
       "\n",
       ".xr-index-preview {\n",
       "  grid-column: 2 / 5;\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-var-name,\n",
       ".xr-var-dims,\n",
       ".xr-var-dtype,\n",
       ".xr-preview,\n",
       ".xr-attrs dt {\n",
       "  white-space: nowrap;\n",
       "  overflow: hidden;\n",
       "  text-overflow: ellipsis;\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-var-name:hover,\n",
       ".xr-var-dims:hover,\n",
       ".xr-var-dtype:hover,\n",
       ".xr-attrs dt:hover {\n",
       "  overflow: visible;\n",
       "  width: auto;\n",
       "  z-index: 1;\n",
       "}\n",
       "\n",
       ".xr-var-attrs,\n",
       ".xr-var-data,\n",
       ".xr-index-data {\n",
       "  display: none;\n",
       "  border-top: 2px dotted var(--xr-background-color);\n",
       "  padding-bottom: 20px !important;\n",
       "  padding-top: 10px !important;\n",
       "}\n",
       "\n",
       ".xr-var-attrs-in + label,\n",
       ".xr-var-data-in + label,\n",
       ".xr-index-data-in + label {\n",
       "  padding: 0 1px;\n",
       "}\n",
       "\n",
       ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
       ".xr-var-data-in:checked ~ .xr-var-data,\n",
       ".xr-index-data-in:checked ~ .xr-index-data {\n",
       "  display: block;\n",
       "}\n",
       "\n",
       ".xr-var-data > table {\n",
       "  float: right;\n",
       "}\n",
       "\n",
       ".xr-var-data > pre,\n",
       ".xr-index-data > pre,\n",
       ".xr-var-data > table > tbody > tr {\n",
       "  background-color: transparent !important;\n",
       "}\n",
       "\n",
       ".xr-var-name span,\n",
       ".xr-var-data,\n",
       ".xr-index-name div,\n",
       ".xr-index-data,\n",
       ".xr-attrs {\n",
       "  padding-left: 25px !important;\n",
       "}\n",
       "\n",
       ".xr-attrs,\n",
       ".xr-var-attrs,\n",
       ".xr-var-data,\n",
       ".xr-index-data {\n",
       "  grid-column: 1 / -1;\n",
       "}\n",
       "\n",
       "dl.xr-attrs {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  display: grid;\n",
       "  grid-template-columns: 125px auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt,\n",
       ".xr-attrs dd {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  float: left;\n",
       "  padding-right: 10px;\n",
       "  width: auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt {\n",
       "  font-weight: normal;\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-attrs dt:hover span {\n",
       "  display: inline-block;\n",
       "  background: var(--xr-background-color);\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-attrs dd {\n",
       "  grid-column: 2;\n",
       "  white-space: pre-wrap;\n",
       "  word-break: break-all;\n",
       "}\n",
       "\n",
       ".xr-icon-database,\n",
       ".xr-icon-file-text2,\n",
       ".xr-no-icon {\n",
       "  display: inline-block;\n",
       "  vertical-align: middle;\n",
       "  width: 1em;\n",
       "  height: 1.5em !important;\n",
       "  stroke-width: 0;\n",
       "  stroke: currentColor;\n",
       "  fill: currentColor;\n",
       "}\n",
       "\n",
       ".xr-var-attrs-in:checked + label > .xr-icon-file-text2,\n",
       ".xr-var-data-in:checked + label > .xr-icon-database,\n",
       ".xr-index-data-in:checked + label > .xr-icon-database {\n",
       "  color: var(--xr-font-color0);\n",
       "  filter: drop-shadow(1px 1px 5px var(--xr-font-color2));\n",
       "  stroke-width: 0.8px;\n",
       "}\n",
       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt; Size: 17MB\n",
       "Dimensions:                (rgi_reg: 19, scenario: 31, time: 881)\n",
       "Coordinates:\n",
       "  * rgi_reg                (rgi_reg) &lt;U2 152B &#x27;01&#x27; &#x27;02&#x27; &#x27;03&#x27; ... &#x27;17&#x27; &#x27;18&#x27; &#x27;19&#x27;\n",
       "  * scenario               (scenario) &lt;U23 3kB &#x27;up2p0&#x27; ... &#x27;up2p0-gwl6p0-200y...\n",
       "  * time                   (time) float64 7kB 1.975e+03 1.976e+03 ... 2.855e+03\n",
       "Data variables:\n",
       "    volume                 (rgi_reg, scenario, time) float32 2MB ...\n",
       "    volume_bsl             (rgi_reg, scenario, time) float32 2MB ...\n",
       "    area                   (rgi_reg, scenario, time) float32 2MB ...\n",
       "    area_filled            (rgi_reg, scenario, time) float64 4MB 0.0 0.0 ... 0.0\n",
       "    perc_init_area_filled  (rgi_reg, scenario, time) float64 4MB 0.0 0.0 ... 0.0\n",
       "    mm_slr_since_1975      (rgi_reg, scenario, time) float32 2MB -5.065e-06 ....\n",
       "Attributes:\n",
       "    OGGM_version:   oggm_v163 (but includes option that saves glacier outputs...\n",
       "    RGI_version:    rgiv62\n",
       "    info:           Reanalysis dataset used for calibration: W5E5.\\nBias corr...\n",
       "    time_validity:  All variables describe the state at the beginning of the ...\n",
       "    rgi_reg_info:   sum over all rgi_reg to get global estimates\n",
       "    OGGM_commit:    git+https://github.com/fmaussion/oggm.git@8adcdb863afc02c...</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-7724fe96-09c9-4e6e-9a74-29c9af3b4afb' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-7724fe96-09c9-4e6e-9a74-29c9af3b4afb' 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'>rgi_reg</span>: 19</li><li><span class='xr-has-index'>scenario</span>: 31</li><li><span class='xr-has-index'>time</span>: 881</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-26f7d338-6c06-4432-8042-0afc3336f9f8' class='xr-section-summary-in' type='checkbox'  checked><label for='section-26f7d338-6c06-4432-8042-0afc3336f9f8' class='xr-section-summary' >Coordinates: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>rgi_reg</span></div><div class='xr-var-dims'>(rgi_reg)</div><div class='xr-var-dtype'>&lt;U2</div><div class='xr-var-preview xr-preview'>&#x27;01&#x27; &#x27;02&#x27; &#x27;03&#x27; ... &#x27;17&#x27; &#x27;18&#x27; &#x27;19&#x27;</div><input id='attrs-c4d6d684-9182-44c8-a556-eefa670e3253' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-c4d6d684-9182-44c8-a556-eefa670e3253' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-c033be34-d67b-40a5-bc0a-4b5850747023' class='xr-var-data-in' type='checkbox'><label for='data-c033be34-d67b-40a5-bc0a-4b5850747023' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;01&#x27;, &#x27;02&#x27;, &#x27;03&#x27;, &#x27;04&#x27;, &#x27;05&#x27;, &#x27;06&#x27;, &#x27;07&#x27;, &#x27;08&#x27;, &#x27;09&#x27;, &#x27;10&#x27;, &#x27;11&#x27;, &#x27;12&#x27;,\n",
       "       &#x27;13&#x27;, &#x27;14&#x27;, &#x27;15&#x27;, &#x27;16&#x27;, &#x27;17&#x27;, &#x27;18&#x27;, &#x27;19&#x27;], dtype=&#x27;&lt;U2&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>scenario</span></div><div class='xr-var-dims'>(scenario)</div><div class='xr-var-dtype'>&lt;U23</div><div class='xr-var-preview xr-preview'>&#x27;up2p0&#x27; ... &#x27;up2p0-gwl6p0-200y-d...</div><input id='attrs-0f32ef08-f2f2-4c4a-80ed-11e7d7fdbb32' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-0f32ef08-f2f2-4c4a-80ed-11e7d7fdbb32' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f0c223af-2916-48ac-b8a1-fc2d64226b4a' class='xr-var-data-in' type='checkbox'><label for='data-f0c223af-2916-48ac-b8a1-fc2d64226b4a' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;up2p0&#x27;, &#x27;up2p0-gwl1p5&#x27;, &#x27;up2p0-gwl1p5-50y-dn1p0&#x27;,\n",
       "       &#x27;up2p0-gwl1p5-200y-dn1p0&#x27;, &#x27;up2p0-gwl2p0&#x27;, &#x27;up2p0-gwl2p0-50y-dn0p5&#x27;,\n",
       "       &#x27;up2p0-gwl2p0-50y-dn1p0&#x27;, &#x27;up2p0-gwl2p0-50y-dn2p0&#x27;,\n",
       "       &#x27;up2p0-gwl2p0-200y-dn0p5&#x27;, &#x27;up2p0-gwl2p0-200y-dn1p0&#x27;, &#x27;up2p0-gwl3p0&#x27;,\n",
       "       &#x27;up2p0-gwl3p0-50y-dn0p5&#x27;, &#x27;up2p0-gwl3p0-50y-dn1p0&#x27;,\n",
       "       &#x27;up2p0-gwl3p0-50y-dn2p0&#x27;, &#x27;up2p0-gwl3p0-200y-dn0p5&#x27;,\n",
       "       &#x27;up2p0-gwl3p0-200y-dn1p0&#x27;, &#x27;up2p0-gwl4p0&#x27;, &#x27;up2p0-gwl4p0-50y-dn0p5&#x27;,\n",
       "       &#x27;up2p0-gwl4p0-50y-dn2p0&#x27;, &#x27;up2p0-gwl4p0-200y-dn1p0&#x27;, &#x27;up2p0-gwl5p0&#x27;,\n",
       "       &#x27;up2p0-gwl5p0-50y-dn2p0&#x27;, &#x27;up2p0-gwl5p0-200y-dn0p5&#x27;,\n",
       "       &#x27;up2p0-gwl5p0-200y-dn1p0&#x27;, &#x27;up2p0-gwl5p0-200y-dn2p0&#x27;, &#x27;up2p0-gwl6p0&#x27;,\n",
       "       &#x27;up2p0-gwl6p0-50y-dn1p0&#x27;, &#x27;up2p0-gwl6p0-50y-dn2p0&#x27;,\n",
       "       &#x27;up2p0-gwl6p0-200y-dn0p5&#x27;, &#x27;up2p0-gwl6p0-200y-dn1p0&#x27;,\n",
       "       &#x27;up2p0-gwl6p0-200y-dn2p0&#x27;], dtype=&#x27;&lt;U23&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>1.975e+03 1.976e+03 ... 2.855e+03</div><input id='attrs-de3db3e4-75b7-4afe-b46b-b8073a8d1794' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-de3db3e4-75b7-4afe-b46b-b8073a8d1794' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-43ade7fe-4a5c-4441-acc9-7267a7f92425' class='xr-var-data-in' type='checkbox'><label for='data-43ade7fe-4a5c-4441-acc9-7267a7f92425' 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([1975., 1976., 1977., ..., 2853., 2854., 2855.])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-959a0a5b-7ed2-426e-9be0-5378dfef6f7b' class='xr-section-summary-in' type='checkbox'  checked><label for='section-959a0a5b-7ed2-426e-9be0-5378dfef6f7b' class='xr-section-summary' >Data variables: <span>(6)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>volume</span></div><div class='xr-var-dims'>(rgi_reg, scenario, time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-8881ed2c-9456-4983-9405-17cf06b0af75' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-8881ed2c-9456-4983-9405-17cf06b0af75' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-eee24f90-2fc0-47b5-9793-723b2a441e50' class='xr-var-data-in' type='checkbox'><label for='data-eee24f90-2fc0-47b5-9793-723b2a441e50' 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>m3</dd><dt><span>info :</span></dt><dd>Regional total glacier volume from all glaciers that did not fail already at the beginning, out of border growing glaciers filled with last estimate</dd></dl></div><div class='xr-var-data'><pre>[518909 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>volume_bsl</span></div><div class='xr-var-dims'>(rgi_reg, scenario, time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-545bac60-8707-4515-81db-fd2f4fe52314' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-545bac60-8707-4515-81db-fd2f4fe52314' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6d893dad-eb97-4b89-9516-e552cf722e04' class='xr-var-data-in' type='checkbox'><label for='data-6d893dad-eb97-4b89-9516-e552cf722e04' 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>m3</dd><dt><span>info :</span></dt><dd>Regional glacier volume below sea-level from all glaciers that did not fail already at the beginning, out of border growing glaciers filled with last estimate</dd></dl></div><div class='xr-var-data'><pre>[518909 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>area</span></div><div class='xr-var-dims'>(rgi_reg, scenario, time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-e42a1dff-9034-4991-aa01-2c4cdcfafc8c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e42a1dff-9034-4991-aa01-2c4cdcfafc8c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-589758a5-4c3e-450d-93a8-5ee2b84eabca' class='xr-var-data-in' type='checkbox'><label for='data-589758a5-4c3e-450d-93a8-5ee2b84eabca' 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>m2</dd><dt><span>info :</span></dt><dd>Regional total glacier area from all glaciers that did not fail already at the beginning, out of border growing glaciers filled with last estimate</dd></dl></div><div class='xr-var-data'><pre>[518909 values with dtype=float32]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>area_filled</span></div><div class='xr-var-dims'>(rgi_reg, scenario, 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-35db5cb4-f1c7-4c98-8245-cadb468f4185' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-35db5cb4-f1c7-4c98-8245-cadb468f4185' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7a8f5048-5200-49dc-b63f-988cea1ab517' class='xr-var-data-in' type='checkbox'><label for='data-7a8f5048-5200-49dc-b63f-988cea1ab517' 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>m2</dd><dt><span>info :</span></dt><dd>Regional total glacier area that got &quot;filled&quot; by using estimates from a previous step where the glaciers did not yet grow out of border</dd></dl></div><div class='xr-var-data'><pre>array([[[0., 0., ..., 0., 0.],\n",
       "        [0., 0., ..., 0., 0.],\n",
       "        ...,\n",
       "        [0., 0., ..., 0., 0.],\n",
       "        [0., 0., ..., 0., 0.]],\n",
       "\n",
       "       [[0., 0., ..., 0., 0.],\n",
       "        [0., 0., ..., 0., 0.],\n",
       "        ...,\n",
       "        [0., 0., ..., 0., 0.],\n",
       "        [0., 0., ..., 0., 0.]],\n",
       "\n",
       "       ...,\n",
       "\n",
       "       [[0., 0., ..., 0., 0.],\n",
       "        [0., 0., ..., 0., 0.],\n",
       "        ...,\n",
       "        [0., 0., ..., 0., 0.],\n",
       "        [0., 0., ..., 0., 0.]],\n",
       "\n",
       "       [[0., 0., ..., 0., 0.],\n",
       "        [0., 0., ..., 0., 0.],\n",
       "        ...,\n",
       "        [0., 0., ..., 0., 0.],\n",
       "        [0., 0., ..., 0., 0.]]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>perc_init_area_filled</span></div><div class='xr-var-dims'>(rgi_reg, scenario, 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-f5718abd-73c3-4335-a724-14ce99b3e9cd' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f5718abd-73c3-4335-a724-14ce99b3e9cd' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-672c36ea-2e6b-439e-80c5-3136ca94fe09' class='xr-var-data-in' type='checkbox'><label for='data-672c36ea-2e6b-439e-80c5-3136ca94fe09' 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>%</dd><dt><span>info :</span></dt><dd>Regional percentage of the total initial glacier area belonging to glaciers whose volume value was filled with the last available estimate.</dd></dl></div><div class='xr-var-data'><pre>array([[[0., 0., ..., 0., 0.],\n",
       "        [0., 0., ..., 0., 0.],\n",
       "        ...,\n",
       "        [0., 0., ..., 0., 0.],\n",
       "        [0., 0., ..., 0., 0.]],\n",
       "\n",
       "       [[0., 0., ..., 0., 0.],\n",
       "        [0., 0., ..., 0., 0.],\n",
       "        ...,\n",
       "        [0., 0., ..., 0., 0.],\n",
       "        [0., 0., ..., 0., 0.]],\n",
       "\n",
       "       ...,\n",
       "\n",
       "       [[0., 0., ..., 0., 0.],\n",
       "        [0., 0., ..., 0., 0.],\n",
       "        ...,\n",
       "        [0., 0., ..., 0., 0.],\n",
       "        [0., 0., ..., 0., 0.]],\n",
       "\n",
       "       [[0., 0., ..., 0., 0.],\n",
       "        [0., 0., ..., 0., 0.],\n",
       "        ...,\n",
       "        [0., 0., ..., 0., 0.],\n",
       "        [0., 0., ..., 0., 0.]]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>mm_slr_since_1975</span></div><div class='xr-var-dims'>(rgi_reg, scenario, time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-5.065e-06 -0.09113 ... nan nan</div><input id='attrs-3a7402f3-4053-4ee5-9471-558c83435ab2' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3a7402f3-4053-4ee5-9471-558c83435ab2' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7adcecc4-0783-4db9-99b0-ece9c848e60d' class='xr-var-data-in' type='checkbox'><label for='data-7adcecc4-0783-4db9-99b0-ece9c848e60d' 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>mm sea-level rise since 1975 from glaciers</dd><dt><span>info :</span></dt><dd>\n",
       "Sea-level rise contribution from glaciers.\n",
       "Same approach as in Schuster et al. (2025).\n",
       "\n",
       "Steps:\n",
       "1. ds_reg_filled_all[&#x27;volume_asl&#x27;] = ds_reg_filled_all[&#x27;volume&#x27;] - ds_reg_filled_all[&#x27;volume_bsl&#x27;]\n",
       "2. ds_1975_volume_asl = ds_reg_filled_all.sel(time=1975).volume_asl.mean(dim=&#x27;scenario&#x27;)\n",
       "2. A_ocean = 3.625e8 * 1e6  # km² --&gt; m²\n",
       "3. vol_asl_diff = ds_1975_volume_asl - ds_reg_filled_all[&#x27;volume_asl&#x27;]  # compute difference relative to 1975\n",
       "4. m_slr = (vol_asl_diff / A_ocean) * 900 / 1028  # convert volume to m sea-level rise\n",
       "5. mm_slr = m_slr * 1000  # convert meters to millimeters\n",
       "</dd></dl></div><div class='xr-var-data'><pre>array([[[-5.0649051e-06, -9.1132835e-02, -1.6637199e-01, ...,\n",
       "                    nan,            nan,            nan],\n",
       "        [-5.0649051e-06, -9.1132835e-02, -1.6637199e-01, ...,\n",
       "                    nan,            nan,            nan],\n",
       "        [-5.0649051e-06, -9.1132835e-02, -1.6637199e-01, ...,\n",
       "                    nan,            nan,            nan],\n",
       "        ...,\n",
       "        [-5.0649051e-06, -9.1132835e-02, -1.6637199e-01, ...,\n",
       "                    nan,            nan,            nan],\n",
       "        [-5.0649051e-06, -9.1132835e-02, -1.6637199e-01, ...,\n",
       "                    nan,            nan,            nan],\n",
       "        [-5.0649051e-06, -9.1132835e-02, -1.6637199e-01, ...,\n",
       "                    nan,            nan,            nan]],\n",
       "\n",
       "       [[ 0.0000000e+00, -1.1160518e-02,  4.1551213e-03, ...,\n",
       "                    nan,            nan,            nan],\n",
       "        [ 0.0000000e+00, -1.1160518e-02,  4.1551213e-03, ...,\n",
       "                    nan,            nan,            nan],\n",
       "        [ 0.0000000e+00, -1.1160518e-02,  4.1551213e-03, ...,\n",
       "                    nan,            nan,            nan],\n",
       "...\n",
       "        [-3.9569571e-08, -1.3854097e-03, -2.4535507e-03, ...,\n",
       "                    nan,            nan,            nan],\n",
       "        [-3.9569571e-08, -1.3854097e-03, -2.4535507e-03, ...,\n",
       "                    nan,            nan,            nan],\n",
       "        [-3.9569571e-08, -1.3854097e-03, -2.4535507e-03, ...,\n",
       "                    nan,            nan,            nan]],\n",
       "\n",
       "       [[ 2.0259620e-05,  4.0848456e-02,  1.8841445e-02, ...,\n",
       "                    nan,            nan,            nan],\n",
       "        [ 2.0259620e-05,  4.0848456e-02,  1.8841445e-02, ...,\n",
       "                    nan,            nan,            nan],\n",
       "        [ 2.0259620e-05,  4.0848456e-02,  1.8841445e-02, ...,\n",
       "                    nan,            nan,            nan],\n",
       "        ...,\n",
       "        [ 2.0259620e-05,  4.0848456e-02,  1.8841445e-02, ...,\n",
       "                    nan,            nan,            nan],\n",
       "        [ 2.0259620e-05,  4.0848456e-02,  1.8841445e-02, ...,\n",
       "                    nan,            nan,            nan],\n",
       "        [ 2.0259620e-05,  4.0848456e-02,  1.8841445e-02, ...,\n",
       "                    nan,            nan,            nan]]], dtype=float32)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-4fc37471-7820-4b0f-a7b5-3e25b3b19e97' class='xr-section-summary-in' type='checkbox'  checked><label for='section-4fc37471-7820-4b0f-a7b5-3e25b3b19e97' class='xr-section-summary' >Attributes: <span>(6)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>OGGM_version :</span></dt><dd>oggm_v163 (but includes option that saves glacier outputs that grow out of border, see OGGM_commit)</dd><dt><span>RGI_version :</span></dt><dd>rgiv62</dd><dt><span>info :</span></dt><dd>Reanalysis dataset used for calibration: W5E5.\n",
       "Bias correction period: 1975–2014, applied from W5E5 to up2p0 simulation years 0–39.\n",
       "Simulations were initialized using the 1979 glacier state from the dynamical spinup\n",
       "</dd><dt><span>time_validity :</span></dt><dd>All variables describe the state at the beginning of the given year.\n",
       "For all &quot;up2p0&quot;-related scenarios, the time variable was shifted to start in 1975 instead of 1850, to match the adjusted climate period more realistically.\n",
       "</dd><dt><span>rgi_reg_info :</span></dt><dd>sum over all rgi_reg to get global estimates</dd><dt><span>OGGM_commit :</span></dt><dd>git+https://github.com/fmaussion/oggm.git@8adcdb863afc02cd7a90d52565f54302aa05f38c</dd></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.Dataset> Size: 17MB\n",
       "Dimensions:                (rgi_reg: 19, scenario: 31, time: 881)\n",
       "Coordinates:\n",
       "  * rgi_reg                (rgi_reg) <U2 152B '01' '02' '03' ... '17' '18' '19'\n",
       "  * scenario               (scenario) <U23 3kB 'up2p0' ... 'up2p0-gwl6p0-200y...\n",
       "  * time                   (time) float64 7kB 1.975e+03 1.976e+03 ... 2.855e+03\n",
       "Data variables:\n",
       "    volume                 (rgi_reg, scenario, time) float32 2MB ...\n",
       "    volume_bsl             (rgi_reg, scenario, time) float32 2MB ...\n",
       "    area                   (rgi_reg, scenario, time) float32 2MB ...\n",
       "    area_filled            (rgi_reg, scenario, time) float64 4MB 0.0 0.0 ... 0.0\n",
       "    perc_init_area_filled  (rgi_reg, scenario, time) float64 4MB 0.0 0.0 ... 0.0\n",
       "    mm_slr_since_1975      (rgi_reg, scenario, time) float32 2MB -5.065e-06 ....\n",
       "Attributes:\n",
       "    OGGM_version:   oggm_v163 (but includes option that saves glacier outputs...\n",
       "    RGI_version:    rgiv62\n",
       "    info:           Reanalysis dataset used for calibration: W5E5.\\nBias corr...\n",
       "    time_validity:  All variables describe the state at the beginning of the ...\n",
       "    rgi_reg_info:   sum over all rgi_reg to get global estimates\n",
       "    OGGM_commit:    git+https://github.com/fmaussion/oggm.git@8adcdb863afc02c..."
      ]
     },
     "execution_count": 104,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ds_reg_filled_all"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 105,
   "id": "080f01f9-7f03-4bb9-8b6e-8e6d684ace91",
   "metadata": {},
   "outputs": [],
   "source": [
    "ds_reg_filled_all.to_netcdf('terrafirma_ukesm2m_glac_proj_regional_filled_v20260713.nc')\n",
    "\n",
    "import json\n",
    "\n",
    "with open(\"growing_border_glaciers_dict.json\", \"w\") as f:\n",
    "    json.dump(growing_border_glaciers_dict, f)\n",
    "\n",
    "with open(\"error_glaciers_dict.json\", \"w\") as f:\n",
    "    json.dump(error_glaciers_dict, f)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "8df00153-22ef-41ee-a7b9-0b48f52d07cd",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "raw",
   "id": "83ebfcf7-3046-47b6-9911-df26c939f5d9",
   "metadata": {},
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "6384fe82-29f3-42dd-8861-f14abfdd7cea",
   "metadata": {},
   "source": [
    "### Repeat the same now with the runs without MB elevation feedback"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "15dae183-555e-4d07-9882-b7ad2b186dbb",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "01 28\n",
      "01 finished\n",
      "02 19\n",
      "02 finished\n",
      "03 5\n",
      "03 finished\n",
      "04 8\n",
      "04 finished\n",
      "05 20\n",
      "05 finished\n",
      "06 1\n",
      "06 finished\n",
      "07 2\n",
      "07 finished\n",
      "08 4\n",
      "08 finished\n",
      "09 2\n",
      "09 finished\n",
      "10 6\n",
      "10 finished\n",
      "11 4\n",
      "11 finished\n",
      "12 2\n",
      "12 finished\n",
      "13 55\n",
      "13 finished\n",
      "14 28\n",
      "14 finished\n",
      "15 14\n",
      "15 finished\n",
      "16 3\n",
      "16 finished\n",
      "17 16\n",
      "17 finished\n",
      "18 4\n",
      "18 finished\n",
      "19 3\n",
      "19 finished\n"
     ]
    }
   ],
   "source": [
    "_fp_init_no_fb = 'run_terrafirma_UKESM1-2-LL_esm_up2p0-gwl6p0-50y-dn2p0_bc_1975_2014_to_0_40_sim_year_mb_elev_feedback_never_starting_at_1979_glacier_state_from_0_sim_year_climate_Batch_*.nc'\n",
    "### this will be concatenated over the batches... \n",
    "error_glaciers_dict_no_fb = {}\n",
    "growing_border_glaciers_dict_no_fb = {}\n",
    "list_ds_reg_filled = []\n",
    "for rgi_reg in rgi_regions:\n",
    "    error_glaciers = []\n",
    "    growing_border_glaciers = []\n",
    "    ds_reg_filled_l = []\n",
    "\n",
    "    p = f'/home/www/lschuster/terrafirma_oggm_proj/output_dir/RGI{rgi_reg}/'    \n",
    "    base_path = Path(p)\n",
    "    matching_files = sorted(base_path.rglob(f'{_fp_init_no_fb}'))\n",
    "    print(rgi_reg, len(matching_files))\n",
    "\n",
    "    for mi in matching_files:\n",
    "        _,b = str(mi).split('Batch')\n",
    "        dict_ds = []\n",
    "        for scenario in SCENARIO_PARENTS.keys():\n",
    "            if 'up2p0' in scenario:\n",
    "                fp_no_fb =f'run_terrafirma_UKESM1-2-LL_esm_{scenario}_bc_1975_2014_to_0_40_sim_year_mb_elev_feedback_never_starting_at_1979_glacier_state_from_0_sim_year_climate_'\n",
    "                _d = xr.open_dataset(f'{p}{fp_no_fb}Batch{b}')\n",
    "                _d = _d.reset_coords()\n",
    "                _d = _d[variables]\n",
    "                _d = _d.load()\n",
    "                if len(_d.is_partial_output.where(_d.is_partial_output==1).dropna(dim='rgi_id'))>0:\n",
    "                    #print(scenario, len(_d.is_partial_output.where(_d.is_partial_output==1).dropna(dim='rgi_id')))\n",
    "                    error_glaciers.append(list(_d.rgi_id.where(_d.is_partial_output.isnull(), drop=True).values))\n",
    "                    growing_border_glaciers.append(list(_d.rgi_id.where(_d.is_partial_output == 1.0, drop=True).values))\n",
    "                # Add scenario as a new dimension and coordinate\n",
    "                _d = _d.expand_dims(scenario=[scenario])\n",
    "                dict_ds.append(_d)\n",
    "        ds_reg = xr.concat(dict_ds,\n",
    "        dim=\"scenario\",\n",
    "        join=\"outer\",\n",
    "        coords=\"minimal\",\n",
    "        data_vars=\"all\",\n",
    "        compat=\"no_conflicts\",\n",
    "        )\n",
    "        ### we do this on every batch individually... \n",
    "        # remove the glacier(s) that is not working in any scenario at all time periods\n",
    "        ds_reg = ds_reg.dropna(dim='rgi_id', how='all')\n",
    "        # fill temporary over entire time axis \n",
    "        volume_filled_raw = ds_reg.volume.ffill(dim='time')\n",
    "        volume_bsl_filled_raw = ds_reg.volume_bsl.ffill(dim='time')\n",
    "        area_filled_raw = ds_reg.area.ffill(dim='time')\n",
    "        \n",
    "        # where do values exist (this is the same for each variable)\n",
    "        # sufficient that one glacier works (this is just to check how long the scenario goes...)\n",
    "        scenario_mask = ds_reg.volume.sum(dim='rgi_id', skipna=True, min_count=1).notnull() \n",
    "        \n",
    "        # only keep those years, where the actual scenario exists \n",
    "        volume_filled = volume_filled_raw.where(scenario_mask)\n",
    "        volume_bsl_filled = volume_bsl_filled_raw.where(scenario_mask)\n",
    "        area_filled = area_filled_raw.where(scenario_mask)\n",
    "        \n",
    "        # regional sum ... \n",
    "        regional_volume_filled = volume_filled.sum(dim='rgi_id', skipna=False)\n",
    "        regional_volume_bsl_filled = volume_bsl_filled.sum(dim='rgi_id', skipna=False)\n",
    "        regional_area_filled = area_filled.sum(dim='rgi_id', skipna=False)\n",
    "         \n",
    "        # initial area \n",
    "        # check that it is the same for each scenario\n",
    "        np.testing.assert_allclose(area_filled.isel(time=0).std(dim='scenario')/area_filled.isel(time=0).mean(dim='scenario'),\n",
    "                                   0, \n",
    "                                   atol=1e-3)\n",
    "        initial_area = area_filled.isel(time=0)\n",
    "        \n",
    "        # Mask for values that were filled and fall within the true scenario lifespan\n",
    "        was_filled = volume_filled_raw.notnull() & ds_reg.volume.isnull()\n",
    "        was_filled = was_filled.where(scenario_mask, False) # Discard fills past the scenario's true end\n",
    "        \n",
    "        # Initial Area represented by filled glaciers at each scenario and timestep\n",
    "        initial_area_filled = (\n",
    "            was_filled.astype(float) * initial_area).sum(\n",
    "            dim=\"rgi_id\",\n",
    "            skipna=True)        \n",
    "        \n",
    "        initial_area_filled.name = \"initial area_filled\"\n",
    "        \n",
    "        initial_area_filled.attrs = {\n",
    "            \"long_name\": \"initial glacier area represented by filled volume values\",\n",
    "            \"units\": \"m2\",\n",
    "            \"description\": (\n",
    "                \"For every scenario and timestep, initial\"\n",
    "                \"glacier area belonging to glaciers whose volume value was filled.\"\n",
    "            ),\n",
    "        }\n",
    "        \n",
    "        ds_reg_filled_b = regional_volume_filled.to_dataset()\n",
    "        ds_reg_filled_b['volume_bsl'] = regional_volume_bsl_filled\n",
    "        ds_reg_filled_b['area'] = regional_area_filled\n",
    "        ds_reg_filled_b['area_filled'] = initial_area_filled\n",
    "        ds_reg_filled_b['rgi_reg'] = rgi_reg\n",
    "        ds_reg_filled_b['batch'] = b[1:-3]\n",
    "        ds_reg_filled_b = ds_reg_filled_b.set_coords('batch')\n",
    "    \n",
    "        ds_reg_filled_l.append(ds_reg_filled_b)\n",
    "\n",
    "        for _ds in dict_ds:\n",
    "            _ds.close()\n",
    "        \n",
    "        ds_reg.close()\n",
    "        \n",
    "        # Remove the large glacier-level arrays before the next batch\n",
    "        del (dict_ds,\n",
    "            ds_reg,\n",
    "            volume_filled_raw,\n",
    "            volume_bsl_filled_raw,\n",
    "            area_filled_raw,\n",
    "            volume_filled,\n",
    "            volume_bsl_filled,\n",
    "            area_filled,\n",
    "            scenario_mask,\n",
    "            initial_area,\n",
    "            was_filled,\n",
    "            initial_area_filled,\n",
    "            regional_volume_filled,\n",
    "            regional_volume_bsl_filled,\n",
    "            regional_area_filled)\n",
    "        gc.collect()\n",
    "\n",
    "    ds_reg_filled = xr.concat(ds_reg_filled_l, dim='batch')\n",
    "    ds_reg_filled = ds_reg_filled.sum(dim='batch', skipna = False)\n",
    "    ds_reg_filled = ds_reg_filled.reset_coords()\n",
    "    ds_reg_filled = ds_reg_filled[['volume','volume_bsl','area','area_filled']]\n",
    "    ds_reg_filled['perc_init_area_filled'] = 100*ds_reg_filled['area_filled']/ds_reg_filled['area'].isel(time=0)\n",
    "        \n",
    "    ds_reg_filled['rgi_reg'] = rgi_reg\n",
    "    ds_reg_filled = ds_reg_filled.set_coords('rgi_reg')\n",
    "    list_ds_reg_filled.append(ds_reg_filled)\n",
    "    growing_border_glaciers_dict_no_fb[rgi_reg] = list(set(np.concatenate(growing_border_glaciers)))\n",
    "    error_glaciers_dict_no_fb[rgi_reg] = list(set(np.concatenate(error_glaciers)))\n",
    "    print(rgi_reg, 'finished')\n",
    "ds_reg_filled_all_no_fb = xr.concat(list_ds_reg_filled, dim='rgi_reg')\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b9ebad04-4e3f-49b0-ac31-ff03a30eb017",
   "metadata": {},
   "source": [
    "#### Compute SLE since 1975 and save it as additional variable "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "4701c168-713f-436d-96e3-d09747ee2e3d",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "336.75494\n"
     ]
    }
   ],
   "source": [
    "### similarly done as in Schuster et al. (2025): \n",
    "# http://localhost:7269/lab/tree/www_lschuster/provide/gfdl-esm2m_oversh_stab_uni_bern/B_main_analysis_figure_creation/2a_fig_2_suppl_prcp.ipynb\n",
    "# sea level makes only sense globally probably\n",
    "ds_reg_filled_all_no_fb['volume_asl']= ds_reg_filled_all_no_fb['volume']-ds_reg_filled_all_no_fb['volume_bsl']\n",
    "# in 1975 (start of simluations), we just have one estimate, check this \n",
    "assert np.all(ds_reg_filled_all_no_fb.sel(time=1975).volume_asl.std(dim='scenario')/ds_reg_filled_all_no_fb.sel(time=1975).volume_asl.mean(dim='scenario')<0.001)\n",
    "ds_1975_volume_asl = ds_reg_filled_all_no_fb.sel(time=1975).volume_asl.mean(dim='scenario')\n",
    "# test when assuming that entire volume above sea level completely melts \n",
    "vol_asl_diff_1975 = ds_1975_volume_asl\n",
    "# convert m3 into sea-level equivalent \n",
    "A_ocean = 3.625 * 10**8 * 1e6 # km2 --> 1e6\n",
    "m_slr_all_1975_volume_lost = (vol_asl_diff_1975/A_ocean) *900/1028 # rhoice/rho_ocean\n",
    "mm_slr_all_1975_volume_lost = m_slr_all_1975_volume_lost * 1000\n",
    "### Farinotti et al 2019 states around 333mm in 2000, so around 336 in 1975 sounds reasonable... oK! \n",
    "# also note that this is the OGGM above sea-level estimates, thus can be different to the Farinotti et al. 2019 community estimate \n",
    "# (even if we would look at the same date, but here we also look at another date, i.e. 1975 and not the inventory year)\n",
    "print(mm_slr_all_1975_volume_lost.sum().values)\n",
    "## now compute slr from glacier melt from the various scenarios\n",
    "# in 2500, volume asl depends on scenario\n",
    "ds_volume_asl = ds_reg_filled_all_no_fb.volume_asl\n",
    "\n",
    "vol_asl_diff = vol_asl_diff_1975 - ds_volume_asl\n",
    "# convert m3 into sea-level equivalent \n",
    "m_slr = (vol_asl_diff/A_ocean) *900/1028 # rhoice/rho_ocean\n",
    "mm_slr = m_slr * 1000\n",
    "ds_reg_filled_all_no_fb['mm_slr_since_1975'] = mm_slr\n",
    "ds_reg_filled_all_no_fb = ds_reg_filled_all_no_fb.drop_vars('volume_asl')\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "1ede8c09-b000-4589-a621-fb787c6e42a8",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array(320.97616577)"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "mm_slr_global_since_1975_no_fb = ds_reg_filled_all_no_fb['mm_slr_since_1975'].sum(dim='rgi_reg') \n",
    "assert np.all(mm_slr_global_since_1975_no_fb >-2)\n",
    "# the total glacier slr contribution since 1975 should be less than if all glaciers melted away (assuming 1975 volume)\n",
    "assert np.all(mm_slr_global_since_1975_no_fb< mm_slr_all_1975_volume_lost.sum())\n",
    "\n",
    "mm_slr_global_since_1975_no_fb.max().values"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "6a1d4762-64cd-4fac-8634-247b55188cd1",
   "metadata": {},
   "outputs": [],
   "source": [
    "\n",
    "ds_reg_filled_all_no_fb.attrs['OGGM_version'] = 'oggm_v163 (but includes option that saves glacier outputs that grow out of border, see OGGM_commit)'\n",
    "ds_reg_filled_all_no_fb.attrs['OGGM_commit'] = 'git+https://github.com/fmaussion/oggm.git@8adcdb863afc02cd7a90d52565f54302aa05f38c'\n",
    "ds_reg_filled_all_no_fb.attrs['RGI_version'] = 'rgiv62'\n",
    "\n",
    "ds_reg_filled_all_no_fb.attrs['info'] = \"\"\"Attention, mass-balance elevation feedback was set to never. Only use this for specific comparative analyses!!!. Reanalysis dataset used for calibration: W5E5.\n",
    "Bias correction period: 1975–2014, applied from W5E5 to up2p0 simulation years 0–39.\n",
    "Simulations were initialized using the 1979 glacier state from the dynamical spinup\n",
    "\"\"\"\n",
    "\n",
    "ds_reg_filled_all_no_fb.attrs['time_validity'] = \"\"\"All variables describe the state at the beginning of the given year.\n",
    "For all \"up2p0\"-related scenarios, the time variable was shifted to start in 1975 instead of 1850, to match the adjusted climate period more realistically.\n",
    "\"\"\"\n",
    "# For the \"hist\"-scenario, we start in the original 1975 year.  <-- not used anymore...\n",
    "\n",
    "ds_reg_filled_all_no_fb.attrs['rgi_reg_info'] = 'sum over all rgi_reg to get global estimates'\n",
    "ds_reg_filled_all_no_fb.volume.attrs['unit'] = 'm3'\n",
    "ds_reg_filled_all_no_fb.area.attrs['unit'] = 'm2'\n",
    "ds_reg_filled_all_no_fb.area_filled.attrs['unit'] = 'm2'\n",
    "ds_reg_filled_all_no_fb.perc_init_area_filled.attrs['unit'] = '%'\n",
    "\n",
    "ds_reg_filled_all_no_fb.mm_slr_since_1975.attrs['unit'] = 'mm sea-level rise since 1975 from glaciers'\n",
    "ds_reg_filled_all_no_fb.volume_bsl.attrs['unit'] = 'm3' \n",
    "ds_reg_filled_all_no_fb.volume_bsl.attrs['info'] = 'Regional glacier volume below sea-level from all glaciers that did not fail already at the beginning, out of border growing glaciers filled with last estimate'\n",
    "ds_reg_filled_all_no_fb.volume.attrs['info'] = 'Regional total glacier volume from all glaciers that did not fail already at the beginning, out of border growing glaciers filled with last estimate'\n",
    "ds_reg_filled_all_no_fb.area.attrs['info'] = 'Regional total glacier area from all glaciers that did not fail already at the beginning, out of border growing glaciers filled with last estimate'\n",
    "ds_reg_filled_all_no_fb.area_filled.attrs['info'] = 'Regional total glacier area that got \"filled\" by using estimates from a previous step where the glaciers did not yet grow out of border'\n",
    "ds_reg_filled_all_no_fb.perc_init_area_filled.attrs['info'] = 'Regional percentage of the total initial glacier area belonging to glaciers whose volume value was filled with the last available estimate.'\n",
    "\n",
    "ds_reg_filled_all_no_fb.mm_slr_since_1975.attrs['info'] = \"\"\"\n",
    "Sea-level rise contribution from glaciers.\n",
    "Same approach as in Schuster et al. (2025).\n",
    "\n",
    "Steps:\n",
    "1. ds_reg_filled_all_no_fb['volume_asl'] = ds_reg_filled_all_no_fb['volume'] - ds_reg_filled_all_no_fb['volume_bsl']\n",
    "2. ds_1975_volume_asl = ds_reg_filled_all_no_fb.sel(time=1975).volume_asl.mean(dim='scenario')\n",
    "2. A_ocean = 3.625e8 * 1e6  # km² --> m²\n",
    "3. vol_asl_diff = ds_1975_volume_asl - ds_reg_filled_all_no_fb['volume_asl']  # compute difference relative to 1975\n",
    "4. m_slr = (vol_asl_diff / A_ocean) * 900 / 1028  # convert volume to m sea-level rise\n",
    "5. mm_slr = m_slr * 1000  # convert meters to millimeters\n",
    "\"\"\"\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "1b3a44f6-3a9e-4b52-90cb-1aae677dcb26",
   "metadata": {},
   "outputs": [],
   "source": [
    "ds_reg_filled_all_no_fb = ds_reg_filled_all_no_fb.rename(\n",
    "    {var: f\"{var}_no_mb_elev_fb\" for var in ds_reg_filled_all_no_fb.data_vars}\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "f730aa9a-ffe3-42e0-b972-ce0de314db51",
   "metadata": {},
   "outputs": [
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       "  margin-top: 0;\n",
       "  margin-bottom: 0;\n",
       "}\n",
       "\n",
       ".xr-obj-type,\n",
       ".xr-obj-name,\n",
       ".xr-group-name {\n",
       "  margin-left: 2px;\n",
       "  margin-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-group-name::before {\n",
       "  content: \"📁\";\n",
       "  padding-right: 0.3em;\n",
       "}\n",
       "\n",
       ".xr-group-name,\n",
       ".xr-obj-type {\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-sections {\n",
       "  padding-left: 0 !important;\n",
       "  display: grid;\n",
       "  grid-template-columns: 150px auto auto 1fr 0 20px 0 20px;\n",
       "  margin-block-start: 0;\n",
       "  margin-block-end: 0;\n",
       "}\n",
       "\n",
       ".xr-section-item {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-section-item input {\n",
       "  display: inline-block;\n",
       "  opacity: 0;\n",
       "  height: 0;\n",
       "  margin: 0;\n",
       "}\n",
       "\n",
       ".xr-section-item input + label {\n",
       "  color: var(--xr-disabled-color);\n",
       "  border: 2px solid transparent !important;\n",
       "}\n",
       "\n",
       ".xr-section-item input:enabled + label {\n",
       "  cursor: pointer;\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-section-item input:focus + label {\n",
       "  border: 2px solid var(--xr-font-color0) !important;\n",
       "}\n",
       "\n",
       ".xr-section-item input:enabled + label:hover {\n",
       "  color: var(--xr-font-color0);\n",
       "}\n",
       "\n",
       ".xr-section-summary {\n",
       "  grid-column: 1;\n",
       "  color: var(--xr-font-color2);\n",
       "  font-weight: 500;\n",
       "}\n",
       "\n",
       ".xr-section-summary > span {\n",
       "  display: inline-block;\n",
       "  padding-left: 0.5em;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:disabled + label {\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-section-summary-in + label:before {\n",
       "  display: inline-block;\n",
       "  content: \"►\";\n",
       "  font-size: 11px;\n",
       "  width: 15px;\n",
       "  text-align: center;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:disabled + label:before {\n",
       "  color: var(--xr-disabled-color);\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked + label:before {\n",
       "  content: \"▼\";\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked + label > span {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-section-summary,\n",
       ".xr-section-inline-details {\n",
       "  padding-top: 4px;\n",
       "}\n",
       "\n",
       ".xr-section-inline-details {\n",
       "  grid-column: 2 / -1;\n",
       "}\n",
       "\n",
       ".xr-section-details {\n",
       "  display: none;\n",
       "  grid-column: 1 / -1;\n",
       "  margin-top: 4px;\n",
       "  margin-bottom: 5px;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked ~ .xr-section-details {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-group-box {\n",
       "  display: inline-grid;\n",
       "  grid-template-columns: 0px 20px auto;\n",
       "  width: 100%;\n",
       "}\n",
       "\n",
       ".xr-group-box-vline {\n",
       "  grid-column-start: 1;\n",
       "  border-right: 0.2em solid;\n",
       "  border-color: var(--xr-border-color);\n",
       "  width: 0px;\n",
       "}\n",
       "\n",
       ".xr-group-box-hline {\n",
       "  grid-column-start: 2;\n",
       "  grid-row-start: 1;\n",
       "  height: 1em;\n",
       "  width: 20px;\n",
       "  border-bottom: 0.2em solid;\n",
       "  border-color: var(--xr-border-color);\n",
       "}\n",
       "\n",
       ".xr-group-box-contents {\n",
       "  grid-column-start: 3;\n",
       "}\n",
       "\n",
       ".xr-array-wrap {\n",
       "  grid-column: 1 / -1;\n",
       "  display: grid;\n",
       "  grid-template-columns: 20px auto;\n",
       "}\n",
       "\n",
       ".xr-array-wrap > label {\n",
       "  grid-column: 1;\n",
       "  vertical-align: top;\n",
       "}\n",
       "\n",
       ".xr-preview {\n",
       "  color: var(--xr-font-color3);\n",
       "}\n",
       "\n",
       ".xr-array-preview,\n",
       ".xr-array-data {\n",
       "  padding: 0 5px !important;\n",
       "  grid-column: 2;\n",
       "}\n",
       "\n",
       ".xr-array-data,\n",
       ".xr-array-in:checked ~ .xr-array-preview {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-array-in:checked ~ .xr-array-data,\n",
       ".xr-array-preview {\n",
       "  display: inline-block;\n",
       "}\n",
       "\n",
       ".xr-dim-list {\n",
       "  display: inline-block !important;\n",
       "  list-style: none;\n",
       "  padding: 0 !important;\n",
       "  margin: 0;\n",
       "}\n",
       "\n",
       ".xr-dim-list li {\n",
       "  display: inline-block;\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "}\n",
       "\n",
       ".xr-dim-list:before {\n",
       "  content: \"(\";\n",
       "}\n",
       "\n",
       ".xr-dim-list:after {\n",
       "  content: \")\";\n",
       "}\n",
       "\n",
       ".xr-dim-list li:not(:last-child):after {\n",
       "  content: \",\";\n",
       "  padding-right: 5px;\n",
       "}\n",
       "\n",
       ".xr-has-index {\n",
       "  font-weight: bold;\n",
       "}\n",
       "\n",
       ".xr-var-list,\n",
       ".xr-var-item {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-var-item > div,\n",
       ".xr-var-item label,\n",
       ".xr-var-item > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-even);\n",
       "  border-color: var(--xr-background-color-row-odd);\n",
       "  margin-bottom: 0;\n",
       "  padding-top: 2px;\n",
       "}\n",
       "\n",
       ".xr-var-item > .xr-var-name:hover span {\n",
       "  padding-right: 5px;\n",
       "}\n",
       "\n",
       ".xr-var-list > li:nth-child(odd) > div,\n",
       ".xr-var-list > li:nth-child(odd) > label,\n",
       ".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-odd);\n",
       "  border-color: var(--xr-background-color-row-even);\n",
       "}\n",
       "\n",
       ".xr-var-name {\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-var-dims {\n",
       "  grid-column: 2;\n",
       "}\n",
       "\n",
       ".xr-var-dtype {\n",
       "  grid-column: 3;\n",
       "  text-align: right;\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-var-preview {\n",
       "  grid-column: 4;\n",
       "}\n",
       "\n",
       ".xr-index-preview {\n",
       "  grid-column: 2 / 5;\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-var-name,\n",
       ".xr-var-dims,\n",
       ".xr-var-dtype,\n",
       ".xr-preview,\n",
       ".xr-attrs dt {\n",
       "  white-space: nowrap;\n",
       "  overflow: hidden;\n",
       "  text-overflow: ellipsis;\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-var-name:hover,\n",
       ".xr-var-dims:hover,\n",
       ".xr-var-dtype:hover,\n",
       ".xr-attrs dt:hover {\n",
       "  overflow: visible;\n",
       "  width: auto;\n",
       "  z-index: 1;\n",
       "}\n",
       "\n",
       ".xr-var-attrs,\n",
       ".xr-var-data,\n",
       ".xr-index-data {\n",
       "  display: none;\n",
       "  border-top: 2px dotted var(--xr-background-color);\n",
       "  padding-bottom: 20px !important;\n",
       "  padding-top: 10px !important;\n",
       "}\n",
       "\n",
       ".xr-var-attrs-in + label,\n",
       ".xr-var-data-in + label,\n",
       ".xr-index-data-in + label {\n",
       "  padding: 0 1px;\n",
       "}\n",
       "\n",
       ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
       ".xr-var-data-in:checked ~ .xr-var-data,\n",
       ".xr-index-data-in:checked ~ .xr-index-data {\n",
       "  display: block;\n",
       "}\n",
       "\n",
       ".xr-var-data > table {\n",
       "  float: right;\n",
       "}\n",
       "\n",
       ".xr-var-data > pre,\n",
       ".xr-index-data > pre,\n",
       ".xr-var-data > table > tbody > tr {\n",
       "  background-color: transparent !important;\n",
       "}\n",
       "\n",
       ".xr-var-name span,\n",
       ".xr-var-data,\n",
       ".xr-index-name div,\n",
       ".xr-index-data,\n",
       ".xr-attrs {\n",
       "  padding-left: 25px !important;\n",
       "}\n",
       "\n",
       ".xr-attrs,\n",
       ".xr-var-attrs,\n",
       ".xr-var-data,\n",
       ".xr-index-data {\n",
       "  grid-column: 1 / -1;\n",
       "}\n",
       "\n",
       "dl.xr-attrs {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  display: grid;\n",
       "  grid-template-columns: 125px auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt,\n",
       ".xr-attrs dd {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  float: left;\n",
       "  padding-right: 10px;\n",
       "  width: auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt {\n",
       "  font-weight: normal;\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-attrs dt:hover span {\n",
       "  display: inline-block;\n",
       "  background: var(--xr-background-color);\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-attrs dd {\n",
       "  grid-column: 2;\n",
       "  white-space: pre-wrap;\n",
       "  word-break: break-all;\n",
       "}\n",
       "\n",
       ".xr-icon-database,\n",
       ".xr-icon-file-text2,\n",
       ".xr-no-icon {\n",
       "  display: inline-block;\n",
       "  vertical-align: middle;\n",
       "  width: 1em;\n",
       "  height: 1.5em !important;\n",
       "  stroke-width: 0;\n",
       "  stroke: currentColor;\n",
       "  fill: currentColor;\n",
       "}\n",
       "\n",
       ".xr-var-attrs-in:checked + label > .xr-icon-file-text2,\n",
       ".xr-var-data-in:checked + label > .xr-icon-database,\n",
       ".xr-index-data-in:checked + label > .xr-icon-database {\n",
       "  color: var(--xr-font-color0);\n",
       "  filter: drop-shadow(1px 1px 5px var(--xr-font-color2));\n",
       "  stroke-width: 0.8px;\n",
       "}\n",
       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt; Size: 17MB\n",
       "Dimensions:                              (rgi_reg: 19, scenario: 31, time: 881)\n",
       "Coordinates:\n",
       "  * rgi_reg                              (rgi_reg) &lt;U2 152B &#x27;01&#x27; &#x27;02&#x27; ... &#x27;19&#x27;\n",
       "  * scenario                             (scenario) object 248B &#x27;up2p0&#x27; ... &#x27;...\n",
       "  * time                                 (time) float64 7kB 1.975e+03 ... 2.8...\n",
       "Data variables:\n",
       "    volume_no_mb_elev_fb                 (rgi_reg, scenario, time) float32 2MB ...\n",
       "    volume_bsl_no_mb_elev_fb             (rgi_reg, scenario, time) float32 2MB ...\n",
       "    area_no_mb_elev_fb                   (rgi_reg, scenario, time) float32 2MB ...\n",
       "    area_filled_no_mb_elev_fb            (rgi_reg, scenario, time) float64 4MB ...\n",
       "    perc_init_area_filled_no_mb_elev_fb  (rgi_reg, scenario, time) float64 4MB ...\n",
       "    mm_slr_since_1975_no_mb_elev_fb      (rgi_reg, scenario, time) float32 2MB ...\n",
       "Attributes:\n",
       "    OGGM_version:   oggm_v163 (but includes option that saves glacier outputs...\n",
       "    OGGM_commit:    git+https://github.com/fmaussion/oggm.git@8adcdb863afc02c...\n",
       "    RGI_version:    rgiv62\n",
       "    info:           Attention, mass-balance elevation feedback was set to nev...\n",
       "    time_validity:  All variables describe the state at the beginning of the ...\n",
       "    rgi_reg_info:   sum over all rgi_reg to get global estimates</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-c9058331-ad53-46ce-bd73-76a1fd58fcb5' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-c9058331-ad53-46ce-bd73-76a1fd58fcb5' 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'>rgi_reg</span>: 19</li><li><span class='xr-has-index'>scenario</span>: 31</li><li><span class='xr-has-index'>time</span>: 881</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-02e19994-79fc-46dc-8760-a02c16b88843' class='xr-section-summary-in' type='checkbox'  checked><label for='section-02e19994-79fc-46dc-8760-a02c16b88843' class='xr-section-summary' >Coordinates: <span>(3)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>rgi_reg</span></div><div class='xr-var-dims'>(rgi_reg)</div><div class='xr-var-dtype'>&lt;U2</div><div class='xr-var-preview xr-preview'>&#x27;01&#x27; &#x27;02&#x27; &#x27;03&#x27; ... &#x27;17&#x27; &#x27;18&#x27; &#x27;19&#x27;</div><input id='attrs-0c66fcc7-08d6-4e2f-8dd3-7470f2e42afd' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-0c66fcc7-08d6-4e2f-8dd3-7470f2e42afd' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-32086a6f-c384-4bdd-aa8e-3e138e506135' class='xr-var-data-in' type='checkbox'><label for='data-32086a6f-c384-4bdd-aa8e-3e138e506135' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;01&#x27;, &#x27;02&#x27;, &#x27;03&#x27;, &#x27;04&#x27;, &#x27;05&#x27;, &#x27;06&#x27;, &#x27;07&#x27;, &#x27;08&#x27;, &#x27;09&#x27;, &#x27;10&#x27;, &#x27;11&#x27;, &#x27;12&#x27;,\n",
       "       &#x27;13&#x27;, &#x27;14&#x27;, &#x27;15&#x27;, &#x27;16&#x27;, &#x27;17&#x27;, &#x27;18&#x27;, &#x27;19&#x27;], dtype=&#x27;&lt;U2&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>scenario</span></div><div class='xr-var-dims'>(scenario)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>&#x27;up2p0&#x27; ... &#x27;up2p0-gwl6p0-200y-d...</div><input id='attrs-0471330d-04eb-4256-bfe5-821dcbd43993' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-0471330d-04eb-4256-bfe5-821dcbd43993' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-805bd920-b9bf-413d-91e0-2d296be19fae' class='xr-var-data-in' type='checkbox'><label for='data-805bd920-b9bf-413d-91e0-2d296be19fae' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;up2p0&#x27;, &#x27;up2p0-gwl1p5&#x27;, &#x27;up2p0-gwl1p5-50y-dn1p0&#x27;,\n",
       "       &#x27;up2p0-gwl1p5-200y-dn1p0&#x27;, &#x27;up2p0-gwl2p0&#x27;, &#x27;up2p0-gwl2p0-50y-dn0p5&#x27;,\n",
       "       &#x27;up2p0-gwl2p0-50y-dn1p0&#x27;, &#x27;up2p0-gwl2p0-50y-dn2p0&#x27;,\n",
       "       &#x27;up2p0-gwl2p0-200y-dn0p5&#x27;, &#x27;up2p0-gwl2p0-200y-dn1p0&#x27;, &#x27;up2p0-gwl3p0&#x27;,\n",
       "       &#x27;up2p0-gwl3p0-50y-dn0p5&#x27;, &#x27;up2p0-gwl3p0-50y-dn1p0&#x27;,\n",
       "       &#x27;up2p0-gwl3p0-50y-dn2p0&#x27;, &#x27;up2p0-gwl3p0-200y-dn0p5&#x27;,\n",
       "       &#x27;up2p0-gwl3p0-200y-dn1p0&#x27;, &#x27;up2p0-gwl4p0&#x27;, &#x27;up2p0-gwl4p0-50y-dn0p5&#x27;,\n",
       "       &#x27;up2p0-gwl4p0-50y-dn2p0&#x27;, &#x27;up2p0-gwl4p0-200y-dn1p0&#x27;, &#x27;up2p0-gwl5p0&#x27;,\n",
       "       &#x27;up2p0-gwl5p0-50y-dn2p0&#x27;, &#x27;up2p0-gwl5p0-200y-dn0p5&#x27;,\n",
       "       &#x27;up2p0-gwl5p0-200y-dn1p0&#x27;, &#x27;up2p0-gwl5p0-200y-dn2p0&#x27;, &#x27;up2p0-gwl6p0&#x27;,\n",
       "       &#x27;up2p0-gwl6p0-50y-dn1p0&#x27;, &#x27;up2p0-gwl6p0-50y-dn2p0&#x27;,\n",
       "       &#x27;up2p0-gwl6p0-200y-dn0p5&#x27;, &#x27;up2p0-gwl6p0-200y-dn1p0&#x27;,\n",
       "       &#x27;up2p0-gwl6p0-200y-dn2p0&#x27;], dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>1.975e+03 1.976e+03 ... 2.855e+03</div><input id='attrs-c313f497-e6d3-4a4e-901b-2e9621fcc6df' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-c313f497-e6d3-4a4e-901b-2e9621fcc6df' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-2033f449-6352-441a-8843-0f785ca0373c' class='xr-var-data-in' type='checkbox'><label for='data-2033f449-6352-441a-8843-0f785ca0373c' 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([1975., 1976., 1977., ..., 2853., 2854., 2855.])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-55157b19-d6d1-472c-b8c8-208d9a51a4c3' class='xr-section-summary-in' type='checkbox'  checked><label for='section-55157b19-d6d1-472c-b8c8-208d9a51a4c3' class='xr-section-summary' >Data variables: <span>(6)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>volume_no_mb_elev_fb</span></div><div class='xr-var-dims'>(rgi_reg, scenario, time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>2.01e+13 2.014e+13 ... nan nan</div><input id='attrs-2916e999-63c9-4b3c-a77b-a03754b5bddb' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-2916e999-63c9-4b3c-a77b-a03754b5bddb' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-0b048a6f-1655-4326-affc-1c3ffebd2e72' class='xr-var-data-in' type='checkbox'><label for='data-0b048a6f-1655-4326-affc-1c3ffebd2e72' 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>m3</dd><dt><span>info :</span></dt><dd>Regional total glacier volume from all glaciers that did not fail already at the beginning, out of border growing glaciers filled with last estimate</dd></dl></div><div class='xr-var-data'><pre>array([[[2.0103637e+13, 2.0141234e+13, 2.0171930e+13, ...,\n",
       "                   nan,           nan,           nan],\n",
       "        [2.0103637e+13, 2.0141234e+13, 2.0171930e+13, ...,\n",
       "                   nan,           nan,           nan],\n",
       "        [2.0103637e+13, 2.0141234e+13, 2.0171930e+13, ...,\n",
       "                   nan,           nan,           nan],\n",
       "        ...,\n",
       "        [2.0103637e+13, 2.0141234e+13, 2.0171930e+13, ...,\n",
       "                   nan,           nan,           nan],\n",
       "        [2.0103637e+13, 2.0141234e+13, 2.0171930e+13, ...,\n",
       "                   nan,           nan,           nan],\n",
       "        [2.0103637e+13, 2.0141234e+13, 2.0171930e+13, ...,\n",
       "                   nan,           nan,           nan]],\n",
       "\n",
       "       [[1.1107975e+12, 1.1154185e+12, 1.1090508e+12, ...,\n",
       "                   nan,           nan,           nan],\n",
       "        [1.1107975e+12, 1.1154185e+12, 1.1090508e+12, ...,\n",
       "                   nan,           nan,           nan],\n",
       "        [1.1107975e+12, 1.1154185e+12, 1.1090508e+12, ...,\n",
       "                   nan,           nan,           nan],\n",
       "...\n",
       "        [7.3694470e+10, 7.4268090e+10, 7.4704945e+10, ...,\n",
       "                   nan,           nan,           nan],\n",
       "        [7.3694470e+10, 7.4268090e+10, 7.4704945e+10, ...,\n",
       "                   nan,           nan,           nan],\n",
       "        [7.3694470e+10, 7.4268090e+10, 7.4704945e+10, ...,\n",
       "                   nan,           nan,           nan]],\n",
       "\n",
       "       [[4.5401801e+13, 4.5446051e+13, 4.5479505e+13, ...,\n",
       "                   nan,           nan,           nan],\n",
       "        [4.5401801e+13, 4.5446051e+13, 4.5479505e+13, ...,\n",
       "                   nan,           nan,           nan],\n",
       "        [4.5401801e+13, 4.5446051e+13, 4.5479505e+13, ...,\n",
       "                   nan,           nan,           nan],\n",
       "        ...,\n",
       "        [4.5401801e+13, 4.5446051e+13, 4.5479505e+13, ...,\n",
       "                   nan,           nan,           nan],\n",
       "        [4.5401801e+13, 4.5446051e+13, 4.5479505e+13, ...,\n",
       "                   nan,           nan,           nan],\n",
       "        [4.5401801e+13, 4.5446051e+13, 4.5479505e+13, ...,\n",
       "                   nan,           nan,           nan]]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>volume_bsl_no_mb_elev_fb</span></div><div class='xr-var-dims'>(rgi_reg, scenario, time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>9.272e+11 9.27e+11 ... nan nan</div><input id='attrs-624a57fc-562e-468b-b294-30fa16e529e2' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-624a57fc-562e-468b-b294-30fa16e529e2' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-00f86606-40b0-4c8b-81a6-fa2bedfb36d8' class='xr-var-data-in' type='checkbox'><label for='data-00f86606-40b0-4c8b-81a6-fa2bedfb36d8' 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>m3</dd><dt><span>info :</span></dt><dd>Regional glacier volume below sea-level from all glaciers that did not fail already at the beginning, out of border growing glaciers filled with last estimate</dd></dl></div><div class='xr-var-data'><pre>array([[[9.2717875e+11, 9.2704303e+11, 9.2682722e+11, ...,\n",
       "                   nan,           nan,           nan],\n",
       "        [9.2717875e+11, 9.2704303e+11, 9.2682722e+11, ...,\n",
       "                   nan,           nan,           nan],\n",
       "        [9.2717875e+11, 9.2704303e+11, 9.2682722e+11, ...,\n",
       "                   nan,           nan,           nan],\n",
       "        ...,\n",
       "        [9.2717875e+11, 9.2704303e+11, 9.2682722e+11, ...,\n",
       "                   nan,           nan,           nan],\n",
       "        [9.2717875e+11, 9.2704303e+11, 9.2682722e+11, ...,\n",
       "                   nan,           nan,           nan],\n",
       "        [9.2717875e+11, 9.2704303e+11, 9.2682722e+11, ...,\n",
       "                   nan,           nan,           nan]],\n",
       "\n",
       "       [[5.0245568e+08, 5.0245568e+08, 5.0245568e+08, ...,\n",
       "                   nan,           nan,           nan],\n",
       "        [5.0245568e+08, 5.0245568e+08, 5.0245568e+08, ...,\n",
       "                   nan,           nan,           nan],\n",
       "        [5.0245568e+08, 5.0245568e+08, 5.0245568e+08, ...,\n",
       "                   nan,           nan,           nan],\n",
       "...\n",
       "        [0.0000000e+00, 0.0000000e+00, 0.0000000e+00, ...,\n",
       "                   nan,           nan,           nan],\n",
       "        [0.0000000e+00, 0.0000000e+00, 0.0000000e+00, ...,\n",
       "                   nan,           nan,           nan],\n",
       "        [0.0000000e+00, 0.0000000e+00, 0.0000000e+00, ...,\n",
       "                   nan,           nan,           nan]],\n",
       "\n",
       "       [[1.2488082e+13, 1.2549238e+13, 1.2573558e+13, ...,\n",
       "                   nan,           nan,           nan],\n",
       "        [1.2488082e+13, 1.2549238e+13, 1.2573558e+13, ...,\n",
       "                   nan,           nan,           nan],\n",
       "        [1.2488082e+13, 1.2549238e+13, 1.2573558e+13, ...,\n",
       "                   nan,           nan,           nan],\n",
       "        ...,\n",
       "        [1.2488082e+13, 1.2549238e+13, 1.2573558e+13, ...,\n",
       "                   nan,           nan,           nan],\n",
       "        [1.2488082e+13, 1.2549238e+13, 1.2573558e+13, ...,\n",
       "                   nan,           nan,           nan],\n",
       "        [1.2488082e+13, 1.2549238e+13, 1.2573558e+13, ...,\n",
       "                   nan,           nan,           nan]]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>area_no_mb_elev_fb</span></div><div class='xr-var-dims'>(rgi_reg, scenario, time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>8.745e+10 8.864e+10 ... nan nan</div><input id='attrs-ea16d838-b0dc-4c6b-8f4e-3a826efc9770' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ea16d838-b0dc-4c6b-8f4e-3a826efc9770' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-620b9348-9784-4391-a3c9-2594791e952f' class='xr-var-data-in' type='checkbox'><label for='data-620b9348-9784-4391-a3c9-2594791e952f' 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>m2</dd><dt><span>info :</span></dt><dd>Regional total glacier area from all glaciers that did not fail already at the beginning, out of border growing glaciers filled with last estimate</dd></dl></div><div class='xr-var-data'><pre>array([[[8.74459873e+10, 8.86376366e+10, 8.83844465e+10, ...,\n",
       "                    nan,            nan,            nan],\n",
       "        [8.74459873e+10, 8.86376366e+10, 8.83844465e+10, ...,\n",
       "                    nan,            nan,            nan],\n",
       "        [8.74459873e+10, 8.86376366e+10, 8.83844465e+10, ...,\n",
       "                    nan,            nan,            nan],\n",
       "        ...,\n",
       "        [8.74459873e+10, 8.86376366e+10, 8.83844465e+10, ...,\n",
       "                    nan,            nan,            nan],\n",
       "        [8.74459873e+10, 8.86376366e+10, 8.83844465e+10, ...,\n",
       "                    nan,            nan,            nan],\n",
       "        [8.74459873e+10, 8.86376366e+10, 8.83844465e+10, ...,\n",
       "                    nan,            nan,            nan]],\n",
       "\n",
       "       [[1.48956621e+10, 1.52841492e+10, 1.50909553e+10, ...,\n",
       "                    nan,            nan,            nan],\n",
       "        [1.48956621e+10, 1.52841492e+10, 1.50909553e+10, ...,\n",
       "                    nan,            nan,            nan],\n",
       "        [1.48956621e+10, 1.52841492e+10, 1.50909553e+10, ...,\n",
       "                    nan,            nan,            nan],\n",
       "...\n",
       "        [1.16175654e+09, 1.20915661e+09, 1.20947315e+09, ...,\n",
       "                    nan,            nan,            nan],\n",
       "        [1.16175654e+09, 1.20915661e+09, 1.20947315e+09, ...,\n",
       "                    nan,            nan,            nan],\n",
       "        [1.16175654e+09, 1.20915661e+09, 1.20947315e+09, ...,\n",
       "                    nan,            nan,            nan]],\n",
       "\n",
       "       [[1.32970439e+11, 1.35846257e+11, 1.36299651e+11, ...,\n",
       "                    nan,            nan,            nan],\n",
       "        [1.32970439e+11, 1.35846257e+11, 1.36299651e+11, ...,\n",
       "                    nan,            nan,            nan],\n",
       "        [1.32970439e+11, 1.35846257e+11, 1.36299651e+11, ...,\n",
       "                    nan,            nan,            nan],\n",
       "        ...,\n",
       "        [1.32970439e+11, 1.35846257e+11, 1.36299651e+11, ...,\n",
       "                    nan,            nan,            nan],\n",
       "        [1.32970439e+11, 1.35846257e+11, 1.36299651e+11, ...,\n",
       "                    nan,            nan,            nan],\n",
       "        [1.32970439e+11, 1.35846257e+11, 1.36299651e+11, ...,\n",
       "                    nan,            nan,            nan]]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>area_filled_no_mb_elev_fb</span></div><div class='xr-var-dims'>(rgi_reg, scenario, 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-06c79a87-cd49-4424-8168-12541f917aaa' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-06c79a87-cd49-4424-8168-12541f917aaa' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4b7c31a0-2270-4d38-aadb-611dabf143ed' class='xr-var-data-in' type='checkbox'><label for='data-4b7c31a0-2270-4d38-aadb-611dabf143ed' 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>m2</dd><dt><span>info :</span></dt><dd>Regional total glacier area that got &quot;filled&quot; by using estimates from a previous step where the glaciers did not yet grow out of border</dd></dl></div><div class='xr-var-data'><pre>array([[[0., 0., 0., ..., 0., 0., 0.],\n",
       "        [0., 0., 0., ..., 0., 0., 0.],\n",
       "        [0., 0., 0., ..., 0., 0., 0.],\n",
       "        ...,\n",
       "        [0., 0., 0., ..., 0., 0., 0.],\n",
       "        [0., 0., 0., ..., 0., 0., 0.],\n",
       "        [0., 0., 0., ..., 0., 0., 0.]],\n",
       "\n",
       "       [[0., 0., 0., ..., 0., 0., 0.],\n",
       "        [0., 0., 0., ..., 0., 0., 0.],\n",
       "        [0., 0., 0., ..., 0., 0., 0.],\n",
       "        ...,\n",
       "        [0., 0., 0., ..., 0., 0., 0.],\n",
       "        [0., 0., 0., ..., 0., 0., 0.],\n",
       "        [0., 0., 0., ..., 0., 0., 0.]],\n",
       "\n",
       "       [[0., 0., 0., ..., 0., 0., 0.],\n",
       "        [0., 0., 0., ..., 0., 0., 0.],\n",
       "        [0., 0., 0., ..., 0., 0., 0.],\n",
       "        ...,\n",
       "...\n",
       "        ...,\n",
       "        [0., 0., 0., ..., 0., 0., 0.],\n",
       "        [0., 0., 0., ..., 0., 0., 0.],\n",
       "        [0., 0., 0., ..., 0., 0., 0.]],\n",
       "\n",
       "       [[0., 0., 0., ..., 0., 0., 0.],\n",
       "        [0., 0., 0., ..., 0., 0., 0.],\n",
       "        [0., 0., 0., ..., 0., 0., 0.],\n",
       "        ...,\n",
       "        [0., 0., 0., ..., 0., 0., 0.],\n",
       "        [0., 0., 0., ..., 0., 0., 0.],\n",
       "        [0., 0., 0., ..., 0., 0., 0.]],\n",
       "\n",
       "       [[0., 0., 0., ..., 0., 0., 0.],\n",
       "        [0., 0., 0., ..., 0., 0., 0.],\n",
       "        [0., 0., 0., ..., 0., 0., 0.],\n",
       "        ...,\n",
       "        [0., 0., 0., ..., 0., 0., 0.],\n",
       "        [0., 0., 0., ..., 0., 0., 0.],\n",
       "        [0., 0., 0., ..., 0., 0., 0.]]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>perc_init_area_filled_no_mb_elev_fb</span></div><div class='xr-var-dims'>(rgi_reg, scenario, 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-c89c9ffa-04c0-4dc7-9b59-a98d20d9e166' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-c89c9ffa-04c0-4dc7-9b59-a98d20d9e166' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ff95dcb8-eaa8-4fa7-b821-8338eb0d38c2' class='xr-var-data-in' type='checkbox'><label for='data-ff95dcb8-eaa8-4fa7-b821-8338eb0d38c2' 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>%</dd><dt><span>info :</span></dt><dd>Regional percentage of the total initial glacier area belonging to glaciers whose volume value was filled with the last available estimate.</dd></dl></div><div class='xr-var-data'><pre>array([[[0., 0., 0., ..., 0., 0., 0.],\n",
       "        [0., 0., 0., ..., 0., 0., 0.],\n",
       "        [0., 0., 0., ..., 0., 0., 0.],\n",
       "        ...,\n",
       "        [0., 0., 0., ..., 0., 0., 0.],\n",
       "        [0., 0., 0., ..., 0., 0., 0.],\n",
       "        [0., 0., 0., ..., 0., 0., 0.]],\n",
       "\n",
       "       [[0., 0., 0., ..., 0., 0., 0.],\n",
       "        [0., 0., 0., ..., 0., 0., 0.],\n",
       "        [0., 0., 0., ..., 0., 0., 0.],\n",
       "        ...,\n",
       "        [0., 0., 0., ..., 0., 0., 0.],\n",
       "        [0., 0., 0., ..., 0., 0., 0.],\n",
       "        [0., 0., 0., ..., 0., 0., 0.]],\n",
       "\n",
       "       [[0., 0., 0., ..., 0., 0., 0.],\n",
       "        [0., 0., 0., ..., 0., 0., 0.],\n",
       "        [0., 0., 0., ..., 0., 0., 0.],\n",
       "        ...,\n",
       "...\n",
       "        ...,\n",
       "        [0., 0., 0., ..., 0., 0., 0.],\n",
       "        [0., 0., 0., ..., 0., 0., 0.],\n",
       "        [0., 0., 0., ..., 0., 0., 0.]],\n",
       "\n",
       "       [[0., 0., 0., ..., 0., 0., 0.],\n",
       "        [0., 0., 0., ..., 0., 0., 0.],\n",
       "        [0., 0., 0., ..., 0., 0., 0.],\n",
       "        ...,\n",
       "        [0., 0., 0., ..., 0., 0., 0.],\n",
       "        [0., 0., 0., ..., 0., 0., 0.],\n",
       "        [0., 0., 0., ..., 0., 0., 0.]],\n",
       "\n",
       "       [[0., 0., 0., ..., 0., 0., 0.],\n",
       "        [0., 0., 0., ..., 0., 0., 0.],\n",
       "        [0., 0., 0., ..., 0., 0., 0.],\n",
       "        ...,\n",
       "        [0., 0., 0., ..., 0., 0., 0.],\n",
       "        [0., 0., 0., ..., 0., 0., 0.],\n",
       "        [0., 0., 0., ..., 0., 0., 0.]]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>mm_slr_since_1975_no_mb_elev_fb</span></div><div class='xr-var-dims'>(rgi_reg, scenario, time)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-5.065e-06 -0.09113 ... nan nan</div><input id='attrs-18f63155-de58-4c32-be1d-ba7aa3c9a2a8' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-18f63155-de58-4c32-be1d-ba7aa3c9a2a8' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-07e184f7-5d96-4e31-bef6-718694425cee' class='xr-var-data-in' type='checkbox'><label for='data-07e184f7-5d96-4e31-bef6-718694425cee' 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>mm sea-level rise since 1975 from glaciers</dd><dt><span>info :</span></dt><dd>\n",
       "Sea-level rise contribution from glaciers.\n",
       "Same approach as in Schuster et al. (2025).\n",
       "\n",
       "Steps:\n",
       "1. ds_reg_filled_all_no_fb[&#x27;volume_asl&#x27;] = ds_reg_filled_all_no_fb[&#x27;volume&#x27;] - ds_reg_filled_all_no_fb[&#x27;volume_bsl&#x27;]\n",
       "2. ds_1975_volume_asl = ds_reg_filled_all_no_fb.sel(time=1975).volume_asl.mean(dim=&#x27;scenario&#x27;)\n",
       "2. A_ocean = 3.625e8 * 1e6  # km² --&gt; m²\n",
       "3. vol_asl_diff = ds_1975_volume_asl - ds_reg_filled_all_no_fb[&#x27;volume_asl&#x27;]  # compute difference relative to 1975\n",
       "4. m_slr = (vol_asl_diff / A_ocean) * 900 / 1028  # convert volume to m sea-level rise\n",
       "5. mm_slr = m_slr * 1000  # convert meters to millimeters\n",
       "</dd></dl></div><div class='xr-var-data'><pre>array([[[-5.0649051e-06, -9.1132835e-02, -1.6578951e-01, ...,\n",
       "                    nan,            nan,            nan],\n",
       "        [-5.0649051e-06, -9.1132835e-02, -1.6578951e-01, ...,\n",
       "                    nan,            nan,            nan],\n",
       "        [-5.0649051e-06, -9.1132835e-02, -1.6578951e-01, ...,\n",
       "                    nan,            nan,            nan],\n",
       "        ...,\n",
       "        [-5.0649051e-06, -9.1132835e-02, -1.6578951e-01, ...,\n",
       "                    nan,            nan,            nan],\n",
       "        [-5.0649051e-06, -9.1132835e-02, -1.6578951e-01, ...,\n",
       "                    nan,            nan,            nan],\n",
       "        [-5.0649051e-06, -9.1132835e-02, -1.6578951e-01, ...,\n",
       "                    nan,            nan,            nan]],\n",
       "\n",
       "       [[ 0.0000000e+00, -1.1160518e-02,  4.2184326e-03, ...,\n",
       "                    nan,            nan,            nan],\n",
       "        [ 0.0000000e+00, -1.1160518e-02,  4.2184326e-03, ...,\n",
       "                    nan,            nan,            nan],\n",
       "        [ 0.0000000e+00, -1.1160518e-02,  4.2184326e-03, ...,\n",
       "                    nan,            nan,            nan],\n",
       "...\n",
       "        [-3.9569571e-08, -1.3854097e-03, -2.4404728e-03, ...,\n",
       "                    nan,            nan,            nan],\n",
       "        [-3.9569571e-08, -1.3854097e-03, -2.4404728e-03, ...,\n",
       "                    nan,            nan,            nan],\n",
       "        [-3.9569571e-08, -1.3854097e-03, -2.4404728e-03, ...,\n",
       "                    nan,            nan,            nan]],\n",
       "\n",
       "       [[ 2.0259620e-05,  4.0848456e-02,  1.8790796e-02, ...,\n",
       "                    nan,            nan,            nan],\n",
       "        [ 2.0259620e-05,  4.0848456e-02,  1.8790796e-02, ...,\n",
       "                    nan,            nan,            nan],\n",
       "        [ 2.0259620e-05,  4.0848456e-02,  1.8790796e-02, ...,\n",
       "                    nan,            nan,            nan],\n",
       "        ...,\n",
       "        [ 2.0259620e-05,  4.0848456e-02,  1.8790796e-02, ...,\n",
       "                    nan,            nan,            nan],\n",
       "        [ 2.0259620e-05,  4.0848456e-02,  1.8790796e-02, ...,\n",
       "                    nan,            nan,            nan],\n",
       "        [ 2.0259620e-05,  4.0848456e-02,  1.8790796e-02, ...,\n",
       "                    nan,            nan,            nan]]], dtype=float32)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-646aac24-0d65-4382-b3db-da2d97330d3d' class='xr-section-summary-in' type='checkbox'  checked><label for='section-646aac24-0d65-4382-b3db-da2d97330d3d' class='xr-section-summary' >Attributes: <span>(6)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>OGGM_version :</span></dt><dd>oggm_v163 (but includes option that saves glacier outputs that grow out of border, see OGGM_commit)</dd><dt><span>OGGM_commit :</span></dt><dd>git+https://github.com/fmaussion/oggm.git@8adcdb863afc02cd7a90d52565f54302aa05f38c</dd><dt><span>RGI_version :</span></dt><dd>rgiv62</dd><dt><span>info :</span></dt><dd>Attention, mass-balance elevation feedback was set to never. Only use this for specific comparative analyses!!!. Reanalysis dataset used for calibration: W5E5.\n",
       "Bias correction period: 1975–2014, applied from W5E5 to up2p0 simulation years 0–39.\n",
       "Simulations were initialized using the 1979 glacier state from the dynamical spinup\n",
       "</dd><dt><span>time_validity :</span></dt><dd>All variables describe the state at the beginning of the given year.\n",
       "For all &quot;up2p0&quot;-related scenarios, the time variable was shifted to start in 1975 instead of 1850, to match the adjusted climate period more realistically.\n",
       "</dd><dt><span>rgi_reg_info :</span></dt><dd>sum over all rgi_reg to get global estimates</dd></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.Dataset> Size: 17MB\n",
       "Dimensions:                              (rgi_reg: 19, scenario: 31, time: 881)\n",
       "Coordinates:\n",
       "  * rgi_reg                              (rgi_reg) <U2 152B '01' '02' ... '19'\n",
       "  * scenario                             (scenario) object 248B 'up2p0' ... '...\n",
       "  * time                                 (time) float64 7kB 1.975e+03 ... 2.8...\n",
       "Data variables:\n",
       "    volume_no_mb_elev_fb                 (rgi_reg, scenario, time) float32 2MB ...\n",
       "    volume_bsl_no_mb_elev_fb             (rgi_reg, scenario, time) float32 2MB ...\n",
       "    area_no_mb_elev_fb                   (rgi_reg, scenario, time) float32 2MB ...\n",
       "    area_filled_no_mb_elev_fb            (rgi_reg, scenario, time) float64 4MB ...\n",
       "    perc_init_area_filled_no_mb_elev_fb  (rgi_reg, scenario, time) float64 4MB ...\n",
       "    mm_slr_since_1975_no_mb_elev_fb      (rgi_reg, scenario, time) float32 2MB ...\n",
       "Attributes:\n",
       "    OGGM_version:   oggm_v163 (but includes option that saves glacier outputs...\n",
       "    OGGM_commit:    git+https://github.com/fmaussion/oggm.git@8adcdb863afc02c...\n",
       "    RGI_version:    rgiv62\n",
       "    info:           Attention, mass-balance elevation feedback was set to nev...\n",
       "    time_validity:  All variables describe the state at the beginning of the ...\n",
       "    rgi_reg_info:   sum over all rgi_reg to get global estimates"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ds_reg_filled_all_no_fb"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "f9e7ae07-1c4c-47ec-9e17-5d4cb611df41",
   "metadata": {},
   "outputs": [],
   "source": [
    "ds_reg_filled_all_no_fb.to_netcdf('terrafirma_ukesm2m_glac_proj_regional_filled_no_mb_elev_fb_v20260721.nc')\n",
    "\n",
    "import json\n",
    "\n",
    "with open(\"growing_border_glaciers_dict_no_mb_elev_fb_v20260721.json\", \"w\") as f:\n",
    "    json.dump(growing_border_glaciers_dict_no_fb, f)\n",
    "\n",
    "with open(\"error_glaciers_dict_no_mb_elev_fb_v20260721.json\", \"w\") as f:\n",
    "    json.dump(error_glaciers_dict_no_fb, f)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "f3a0875b-13fb-45a4-8f8a-684273a262ea",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "920ff657-5e56-41e1-9e2f-bdf3bde0da50",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "2e683bbf-f7b2-411b-809b-5cb52f9f6fb5",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "f6952fed-6456-4f36-83ed-f5b3f303fd00",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "08074910-c662-4b23-8539-d96d00d98980",
   "metadata": {},
   "source": [
    "# Old"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "6b250964-87af-47b1-914c-f0290ea7ae3a",
   "metadata": {},
   "outputs": [],
   "source": [
    "growing_border_glaciers_all = list(set(np.concatenate(growing_border_glaciers)))\n",
    "print(len(growing_border_glaciers_all))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "6bb5f2d2-bd0d-454d-b1af-713fda011a89",
   "metadata": {},
   "outputs": [],
   "source": [
    "## option which just removes the glaicers (here only kept for comparison..)\n",
    "ds_reg_vol_rm_all = ds_reg.volume.drop_sel(rgi_id=growing_border_glaciers_all)\n",
    "ds_reg_vol_rm_all = ds_reg_vol_rm_all.drop_sel(rgi_id=list(set(np.concatenate(error_glaciers))))\n",
    "regional_volume_rm_glacier = ds_reg_vol_rm_all.sum(dim='rgi_id', skipna=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "60742fae-e9cf-4b40-a0f2-e196c5aaf730",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "c25aec20-a5e7-4b7d-ab8a-9c44c51b7f98",
   "metadata": {},
   "source": [
    "[2:14 PM]wenn's geht, einfach filled erstmal probieren aber irgendwo als variable specihern wie viel % der initial area der filling uebernimmt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "1fe1382f-deab-46bf-8151-476c77387e1f",
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "\n",
    "# Mask for values that were valid in the original dataset\n",
    "was_valid = ds_reg_vol.notnull()\n",
    "\n",
    "# Mask for values that were filled and fall within the true scenario lifespan\n",
    "was_filled = volume_filled_raw.notnull() & ds_reg_vol.isnull()\n",
    "was_filled = was_filled.where(scenario_mask, False) # Discard fills past the scenario's true end\n",
    "\n",
    "stats = []\n",
    "\n",
    "# Loop through each unique scenario to compute individual statistics\n",
    "for scenario in ds_reg_vol.scenario.values:\n",
    "    scen_filled = was_filled.sel(scenario=scenario)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "61856279-4df1-45a6-9967-005bc5996a8a",
   "metadata": {},
   "outputs": [
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       "  grid-column: 1 / -1;\n",
       "  display: grid;\n",
       "  grid-template-columns: 20px auto;\n",
       "}\n",
       "\n",
       ".xr-array-wrap > label {\n",
       "  grid-column: 1;\n",
       "  vertical-align: top;\n",
       "}\n",
       "\n",
       ".xr-preview {\n",
       "  color: var(--xr-font-color3);\n",
       "}\n",
       "\n",
       ".xr-array-preview,\n",
       ".xr-array-data {\n",
       "  padding: 0 5px !important;\n",
       "  grid-column: 2;\n",
       "}\n",
       "\n",
       ".xr-array-data,\n",
       ".xr-array-in:checked ~ .xr-array-preview {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-array-in:checked ~ .xr-array-data,\n",
       ".xr-array-preview {\n",
       "  display: inline-block;\n",
       "}\n",
       "\n",
       ".xr-dim-list {\n",
       "  display: inline-block !important;\n",
       "  list-style: none;\n",
       "  padding: 0 !important;\n",
       "  margin: 0;\n",
       "}\n",
       "\n",
       ".xr-dim-list li {\n",
       "  display: inline-block;\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "}\n",
       "\n",
       ".xr-dim-list:before {\n",
       "  content: \"(\";\n",
       "}\n",
       "\n",
       ".xr-dim-list:after {\n",
       "  content: \")\";\n",
       "}\n",
       "\n",
       ".xr-dim-list li:not(:last-child):after {\n",
       "  content: \",\";\n",
       "  padding-right: 5px;\n",
       "}\n",
       "\n",
       ".xr-has-index {\n",
       "  font-weight: bold;\n",
       "}\n",
       "\n",
       ".xr-var-list,\n",
       ".xr-var-item {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-var-item > div,\n",
       ".xr-var-item label,\n",
       ".xr-var-item > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-even);\n",
       "  border-color: var(--xr-background-color-row-odd);\n",
       "  margin-bottom: 0;\n",
       "  padding-top: 2px;\n",
       "}\n",
       "\n",
       ".xr-var-item > .xr-var-name:hover span {\n",
       "  padding-right: 5px;\n",
       "}\n",
       "\n",
       ".xr-var-list > li:nth-child(odd) > div,\n",
       ".xr-var-list > li:nth-child(odd) > label,\n",
       ".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-odd);\n",
       "  border-color: var(--xr-background-color-row-even);\n",
       "}\n",
       "\n",
       ".xr-var-name {\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-var-dims {\n",
       "  grid-column: 2;\n",
       "}\n",
       "\n",
       ".xr-var-dtype {\n",
       "  grid-column: 3;\n",
       "  text-align: right;\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-var-preview {\n",
       "  grid-column: 4;\n",
       "}\n",
       "\n",
       ".xr-index-preview {\n",
       "  grid-column: 2 / 5;\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-var-name,\n",
       ".xr-var-dims,\n",
       ".xr-var-dtype,\n",
       ".xr-preview,\n",
       ".xr-attrs dt {\n",
       "  white-space: nowrap;\n",
       "  overflow: hidden;\n",
       "  text-overflow: ellipsis;\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-var-name:hover,\n",
       ".xr-var-dims:hover,\n",
       ".xr-var-dtype:hover,\n",
       ".xr-attrs dt:hover {\n",
       "  overflow: visible;\n",
       "  width: auto;\n",
       "  z-index: 1;\n",
       "}\n",
       "\n",
       ".xr-var-attrs,\n",
       ".xr-var-data,\n",
       ".xr-index-data {\n",
       "  display: none;\n",
       "  border-top: 2px dotted var(--xr-background-color);\n",
       "  padding-bottom: 20px !important;\n",
       "  padding-top: 10px !important;\n",
       "}\n",
       "\n",
       ".xr-var-attrs-in + label,\n",
       ".xr-var-data-in + label,\n",
       ".xr-index-data-in + label {\n",
       "  padding: 0 1px;\n",
       "}\n",
       "\n",
       ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
       ".xr-var-data-in:checked ~ .xr-var-data,\n",
       ".xr-index-data-in:checked ~ .xr-index-data {\n",
       "  display: block;\n",
       "}\n",
       "\n",
       ".xr-var-data > table {\n",
       "  float: right;\n",
       "}\n",
       "\n",
       ".xr-var-data > pre,\n",
       ".xr-index-data > pre,\n",
       ".xr-var-data > table > tbody > tr {\n",
       "  background-color: transparent !important;\n",
       "}\n",
       "\n",
       ".xr-var-name span,\n",
       ".xr-var-data,\n",
       ".xr-index-name div,\n",
       ".xr-index-data,\n",
       ".xr-attrs {\n",
       "  padding-left: 25px !important;\n",
       "}\n",
       "\n",
       ".xr-attrs,\n",
       ".xr-var-attrs,\n",
       ".xr-var-data,\n",
       ".xr-index-data {\n",
       "  grid-column: 1 / -1;\n",
       "}\n",
       "\n",
       "dl.xr-attrs {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  display: grid;\n",
       "  grid-template-columns: 125px auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt,\n",
       ".xr-attrs dd {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  float: left;\n",
       "  padding-right: 10px;\n",
       "  width: auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt {\n",
       "  font-weight: normal;\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-attrs dt:hover span {\n",
       "  display: inline-block;\n",
       "  background: var(--xr-background-color);\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-attrs dd {\n",
       "  grid-column: 2;\n",
       "  white-space: pre-wrap;\n",
       "  word-break: break-all;\n",
       "}\n",
       "\n",
       ".xr-icon-database,\n",
       ".xr-icon-file-text2,\n",
       ".xr-no-icon {\n",
       "  display: inline-block;\n",
       "  vertical-align: middle;\n",
       "  width: 1em;\n",
       "  height: 1.5em !important;\n",
       "  stroke-width: 0;\n",
       "  stroke: currentColor;\n",
       "  fill: currentColor;\n",
       "}\n",
       "\n",
       ".xr-var-attrs-in:checked + label > .xr-icon-file-text2,\n",
       ".xr-var-data-in:checked + label > .xr-icon-database,\n",
       ".xr-index-data-in:checked + label > .xr-icon-database {\n",
       "  color: var(--xr-font-color0);\n",
       "  filter: drop-shadow(1px 1px 5px var(--xr-font-color2));\n",
       "  stroke-width: 0.8px;\n",
       "}\n",
       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.DataArray &#x27;volume&#x27; (time: 881, rgi_id: 567)&gt; Size: 500kB\n",
       "array([[False, False, False, ..., False, False, False],\n",
       "       [False, False, False, ..., False, False, False],\n",
       "       [False, False, False, ..., False, False, False],\n",
       "       ...,\n",
       "       [False, False, False, ..., False, False, False],\n",
       "       [False, False, False, ..., False, False, False],\n",
       "       [False, False, False, ..., False, False, False]])\n",
       "Coordinates:\n",
       "  * time            (time) float64 7kB 1.975e+03 1.976e+03 ... 2.855e+03\n",
       "  * rgi_id          (rgi_id) &lt;U14 32kB &#x27;RGI60-06.00001&#x27; ... &#x27;RGI60-06.00568&#x27;\n",
       "    scenario        &lt;U23 92B &#x27;up2p0-gwl6p0-200y-dn2p0&#x27;\n",
       "    hydro_year      (time) float64 7kB 1.975e+03 1.976e+03 1.977e+03 ... nan nan\n",
       "    hydro_month     (time) float64 7kB 4.0 4.0 4.0 4.0 4.0 ... nan nan nan nan\n",
       "    calendar_year   (time) float64 7kB 1.975e+03 1.976e+03 1.977e+03 ... nan nan\n",
       "    calendar_month  (time) float64 7kB 1.0 1.0 1.0 1.0 1.0 ... nan nan nan nan</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-obj-name'>&#x27;volume&#x27;</div><ul class='xr-dim-list'><li><span class='xr-has-index'>time</span>: 881</li><li><span class='xr-has-index'>rgi_id</span>: 567</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-e5abb76d-bb4e-4cae-8e29-a7e09e571e44' class='xr-array-in' type='checkbox' checked><label for='section-e5abb76d-bb4e-4cae-8e29-a7e09e571e44' 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>False False False False False False ... False False False False False</span></div><div class='xr-array-data'><pre>array([[False, False, False, ..., False, False, False],\n",
       "       [False, False, False, ..., False, False, False],\n",
       "       [False, False, False, ..., False, False, False],\n",
       "       ...,\n",
       "       [False, False, False, ..., False, False, False],\n",
       "       [False, False, False, ..., False, False, False],\n",
       "       [False, False, False, ..., False, False, False]])</pre></div></div></li><li class='xr-section-item'><input id='section-0b3df053-7e16-4c4f-adbb-deb1b57f4a9b' class='xr-section-summary-in' type='checkbox'  checked><label for='section-0b3df053-7e16-4c4f-adbb-deb1b57f4a9b' class='xr-section-summary' >Coordinates: <span>(7)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>1.975e+03 1.976e+03 ... 2.855e+03</div><input id='attrs-387c8c09-87e3-4a93-8c71-c482f11f42d5' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-387c8c09-87e3-4a93-8c71-c482f11f42d5' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5cc78ab6-87a9-45a5-ab96-f5b4c78aa4d1' class='xr-var-data-in' type='checkbox'><label for='data-5cc78ab6-87a9-45a5-ab96-f5b4c78aa4d1' 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([1975., 1976., 1977., ..., 2853., 2854., 2855.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>rgi_id</span></div><div class='xr-var-dims'>(rgi_id)</div><div class='xr-var-dtype'>&lt;U14</div><div class='xr-var-preview xr-preview'>&#x27;RGI60-06.00001&#x27; ... &#x27;RGI60-06.0...</div><input id='attrs-2b2e82c0-ce0f-4494-9827-ff12230fa512' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-2b2e82c0-ce0f-4494-9827-ff12230fa512' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-858916ac-1793-49f3-b412-42fbdf550751' class='xr-var-data-in' type='checkbox'><label for='data-858916ac-1793-49f3-b412-42fbdf550751' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>description :</span></dt><dd>RGI glacier identifier</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;RGI60-06.00001&#x27;, &#x27;RGI60-06.00002&#x27;, &#x27;RGI60-06.00003&#x27;, ...,\n",
       "       &#x27;RGI60-06.00566&#x27;, &#x27;RGI60-06.00567&#x27;, &#x27;RGI60-06.00568&#x27;], dtype=&#x27;&lt;U14&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>scenario</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>&lt;U23</div><div class='xr-var-preview xr-preview'>&#x27;up2p0-gwl6p0-200y-dn2p0&#x27;</div><input id='attrs-3b65f702-5d1a-431a-9fbb-27c3769fa00d' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-3b65f702-5d1a-431a-9fbb-27c3769fa00d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6b42ad2e-da1b-495b-961c-4fb0c8b8cc7c' class='xr-var-data-in' type='checkbox'><label for='data-6b42ad2e-da1b-495b-961c-4fb0c8b8cc7c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array(&#x27;up2p0-gwl6p0-200y-dn2p0&#x27;, dtype=&#x27;&lt;U23&#x27;)</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'>float64</div><div class='xr-var-preview xr-preview'>1.975e+03 1.976e+03 ... nan nan</div><input id='attrs-e5137017-4001-4c78-9bfd-e502662b477b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e5137017-4001-4c78-9bfd-e502662b477b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-01c20bd7-1c0d-48af-a2cf-15ac299d7ec1' class='xr-var-data-in' type='checkbox'><label for='data-01c20bd7-1c0d-48af-a2cf-15ac299d7ec1' 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([1975., 1976., 1977., 1978., 1979., 1980., 1981., 1982., 1983.,\n",
       "       1984., 1985., 1986., 1987., 1988., 1989., 1990., 1991., 1992.,\n",
       "       1993., 1994., 1995., 1996., 1997., 1998., 1999., 2000., 2001.,\n",
       "       2002., 2003., 2004., 2005., 2006., 2007., 2008., 2009., 2010.,\n",
       "       2011., 2012., 2013., 2014., 2015., 2016., 2017., 2018., 2019.,\n",
       "       2020., 2021., 2022., 2023., 2024., 2025., 2026., 2027., 2028.,\n",
       "       2029., 2030., 2031., 2032., 2033., 2034., 2035., 2036., 2037.,\n",
       "       2038., 2039., 2040., 2041., 2042., 2043., 2044., 2045., 2046.,\n",
       "       2047., 2048., 2049., 2050., 2051., 2052., 2053., 2054., 2055.,\n",
       "       2056., 2057., 2058., 2059., 2060., 2061., 2062., 2063., 2064.,\n",
       "       2065., 2066., 2067., 2068., 2069., 2070., 2071., 2072., 2073.,\n",
       "       2074., 2075., 2076., 2077., 2078., 2079., 2080., 2081., 2082.,\n",
       "       2083., 2084., 2085., 2086., 2087., 2088., 2089., 2090., 2091.,\n",
       "       2092., 2093., 2094., 2095., 2096., 2097., 2098., 2099., 2100.,\n",
       "       2101., 2102., 2103., 2104., 2105., 2106., 2107., 2108., 2109.,\n",
       "       2110., 2111., 2112., 2113., 2114., 2115., 2116., 2117., 2118.,\n",
       "       2119., 2120., 2121., 2122., 2123., 2124., 2125., 2126., 2127.,\n",
       "       2128., 2129., 2130., 2131., 2132., 2133., 2134., 2135., 2136.,\n",
       "       2137., 2138., 2139., 2140., 2141., 2142., 2143., 2144., 2145.,\n",
       "       2146., 2147., 2148., 2149., 2150., 2151., 2152., 2153., 2154.,\n",
       "...\n",
       "         nan,   nan,   nan,   nan,   nan,   nan,   nan,   nan,   nan,\n",
       "         nan,   nan,   nan,   nan,   nan,   nan,   nan,   nan,   nan,\n",
       "         nan,   nan,   nan,   nan,   nan,   nan,   nan,   nan,   nan,\n",
       "         nan,   nan,   nan,   nan,   nan,   nan,   nan,   nan,   nan,\n",
       "         nan,   nan,   nan,   nan,   nan,   nan,   nan,   nan,   nan,\n",
       "         nan,   nan,   nan,   nan,   nan,   nan,   nan,   nan,   nan,\n",
       "         nan,   nan,   nan,   nan,   nan,   nan,   nan,   nan,   nan,\n",
       "         nan,   nan,   nan,   nan,   nan,   nan,   nan,   nan,   nan,\n",
       "         nan,   nan,   nan,   nan,   nan,   nan,   nan,   nan,   nan,\n",
       "         nan,   nan,   nan,   nan,   nan,   nan,   nan,   nan,   nan,\n",
       "         nan,   nan,   nan,   nan,   nan,   nan,   nan,   nan,   nan,\n",
       "         nan,   nan,   nan,   nan,   nan,   nan,   nan,   nan,   nan,\n",
       "         nan,   nan,   nan,   nan,   nan,   nan,   nan,   nan,   nan,\n",
       "         nan,   nan,   nan,   nan,   nan,   nan,   nan,   nan,   nan,\n",
       "         nan,   nan,   nan,   nan,   nan,   nan,   nan,   nan,   nan,\n",
       "         nan,   nan,   nan,   nan,   nan,   nan,   nan,   nan,   nan,\n",
       "         nan,   nan,   nan,   nan,   nan,   nan,   nan,   nan,   nan,\n",
       "         nan,   nan,   nan,   nan,   nan,   nan,   nan,   nan,   nan,\n",
       "         nan,   nan,   nan,   nan,   nan,   nan,   nan,   nan,   nan,\n",
       "         nan,   nan,   nan,   nan,   nan,   nan,   nan,   nan])</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'>float64</div><div class='xr-var-preview xr-preview'>4.0 4.0 4.0 4.0 ... nan nan nan nan</div><input id='attrs-e7bc83b5-e18f-4742-bc5a-a668bdef842c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e7bc83b5-e18f-4742-bc5a-a668bdef842c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f9fb49c8-7300-49ac-8d97-691c402c2a86' class='xr-var-data-in' type='checkbox'><label for='data-f9fb49c8-7300-49ac-8d97-691c402c2a86' 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.,\n",
       "        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.,\n",
       "        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.,\n",
       "        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.,\n",
       "        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.,\n",
       "        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.,\n",
       "        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.,\n",
       "        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.,\n",
       "        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.,\n",
       "        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.,\n",
       "        4.,  4.,  4.,  4.,  4.,  4.,  4.,  4.,  4.,  4.,  4.,  4.,  4.,\n",
       "...\n",
       "        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.,\n",
       "        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.,\n",
       "        4.,  4.,  4.,  4.,  4.,  4.,  4.,  4.,  4.,  4.,  4.,  4.,  4.,\n",
       "        4.,  4.,  4.,  4.,  4.,  4.,  4., nan, nan, nan, nan, nan, nan,\n",
       "       nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan,\n",
       "       nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan,\n",
       "       nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan,\n",
       "       nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan,\n",
       "       nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan,\n",
       "       nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan,\n",
       "       nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan,\n",
       "       nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan,\n",
       "       nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan,\n",
       "       nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan,\n",
       "       nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan,\n",
       "       nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan,\n",
       "       nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan,\n",
       "       nan, nan, nan, nan, nan, nan, nan, nan, nan, nan])</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'>float64</div><div class='xr-var-preview xr-preview'>1.975e+03 1.976e+03 ... nan nan</div><input id='attrs-f09c2a31-a129-4f95-8807-de870f09db63' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f09c2a31-a129-4f95-8807-de870f09db63' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d8204854-963d-4f78-b4b8-31d1f7ddbaf6' class='xr-var-data-in' type='checkbox'><label for='data-d8204854-963d-4f78-b4b8-31d1f7ddbaf6' 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([1975., 1976., 1977., 1978., 1979., 1980., 1981., 1982., 1983.,\n",
       "       1984., 1985., 1986., 1987., 1988., 1989., 1990., 1991., 1992.,\n",
       "       1993., 1994., 1995., 1996., 1997., 1998., 1999., 2000., 2001.,\n",
       "       2002., 2003., 2004., 2005., 2006., 2007., 2008., 2009., 2010.,\n",
       "       2011., 2012., 2013., 2014., 2015., 2016., 2017., 2018., 2019.,\n",
       "       2020., 2021., 2022., 2023., 2024., 2025., 2026., 2027., 2028.,\n",
       "       2029., 2030., 2031., 2032., 2033., 2034., 2035., 2036., 2037.,\n",
       "       2038., 2039., 2040., 2041., 2042., 2043., 2044., 2045., 2046.,\n",
       "       2047., 2048., 2049., 2050., 2051., 2052., 2053., 2054., 2055.,\n",
       "       2056., 2057., 2058., 2059., 2060., 2061., 2062., 2063., 2064.,\n",
       "       2065., 2066., 2067., 2068., 2069., 2070., 2071., 2072., 2073.,\n",
       "       2074., 2075., 2076., 2077., 2078., 2079., 2080., 2081., 2082.,\n",
       "       2083., 2084., 2085., 2086., 2087., 2088., 2089., 2090., 2091.,\n",
       "       2092., 2093., 2094., 2095., 2096., 2097., 2098., 2099., 2100.,\n",
       "       2101., 2102., 2103., 2104., 2105., 2106., 2107., 2108., 2109.,\n",
       "       2110., 2111., 2112., 2113., 2114., 2115., 2116., 2117., 2118.,\n",
       "       2119., 2120., 2121., 2122., 2123., 2124., 2125., 2126., 2127.,\n",
       "       2128., 2129., 2130., 2131., 2132., 2133., 2134., 2135., 2136.,\n",
       "       2137., 2138., 2139., 2140., 2141., 2142., 2143., 2144., 2145.,\n",
       "       2146., 2147., 2148., 2149., 2150., 2151., 2152., 2153., 2154.,\n",
       "...\n",
       "         nan,   nan,   nan,   nan,   nan,   nan,   nan,   nan,   nan,\n",
       "         nan,   nan,   nan,   nan,   nan,   nan,   nan,   nan,   nan,\n",
       "         nan,   nan,   nan,   nan,   nan,   nan,   nan,   nan,   nan,\n",
       "         nan,   nan,   nan,   nan,   nan,   nan,   nan,   nan,   nan,\n",
       "         nan,   nan,   nan,   nan,   nan,   nan,   nan,   nan,   nan,\n",
       "         nan,   nan,   nan,   nan,   nan,   nan,   nan,   nan,   nan,\n",
       "         nan,   nan,   nan,   nan,   nan,   nan,   nan,   nan,   nan,\n",
       "         nan,   nan,   nan,   nan,   nan,   nan,   nan,   nan,   nan,\n",
       "         nan,   nan,   nan,   nan,   nan,   nan,   nan,   nan,   nan,\n",
       "         nan,   nan,   nan,   nan,   nan,   nan,   nan,   nan,   nan,\n",
       "         nan,   nan,   nan,   nan,   nan,   nan,   nan,   nan,   nan,\n",
       "         nan,   nan,   nan,   nan,   nan,   nan,   nan,   nan,   nan,\n",
       "         nan,   nan,   nan,   nan,   nan,   nan,   nan,   nan,   nan,\n",
       "         nan,   nan,   nan,   nan,   nan,   nan,   nan,   nan,   nan,\n",
       "         nan,   nan,   nan,   nan,   nan,   nan,   nan,   nan,   nan,\n",
       "         nan,   nan,   nan,   nan,   nan,   nan,   nan,   nan,   nan,\n",
       "         nan,   nan,   nan,   nan,   nan,   nan,   nan,   nan,   nan,\n",
       "         nan,   nan,   nan,   nan,   nan,   nan,   nan,   nan,   nan,\n",
       "         nan,   nan,   nan,   nan,   nan,   nan,   nan,   nan,   nan,\n",
       "         nan,   nan,   nan,   nan,   nan,   nan,   nan,   nan])</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'>float64</div><div class='xr-var-preview xr-preview'>1.0 1.0 1.0 1.0 ... nan nan nan nan</div><input id='attrs-d0883f9d-dfb7-48d4-ae02-27f9ef2b44e7' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d0883f9d-dfb7-48d4-ae02-27f9ef2b44e7' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e8d16b8a-7e16-4dac-9291-738877e77938' class='xr-var-data-in' type='checkbox'><label for='data-e8d16b8a-7e16-4dac-9291-738877e77938' 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.,\n",
       "        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.,\n",
       "        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.,\n",
       "        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.,\n",
       "        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.,\n",
       "        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.,\n",
       "        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.,\n",
       "        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.,\n",
       "        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.,\n",
       "        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.,\n",
       "        1.,  1.,  1.,  1.,  1.,  1.,  1.,  1.,  1.,  1.,  1.,  1.,  1.,\n",
       "...\n",
       "        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.,\n",
       "        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.,\n",
       "        1.,  1.,  1.,  1.,  1.,  1.,  1.,  1.,  1.,  1.,  1.,  1.,  1.,\n",
       "        1.,  1.,  1.,  1.,  1.,  1.,  1., nan, nan, nan, nan, nan, nan,\n",
       "       nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan,\n",
       "       nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan,\n",
       "       nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan,\n",
       "       nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan,\n",
       "       nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan,\n",
       "       nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan,\n",
       "       nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan,\n",
       "       nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan,\n",
       "       nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan,\n",
       "       nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan,\n",
       "       nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan,\n",
       "       nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan,\n",
       "       nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan, nan,\n",
       "       nan, nan, nan, nan, nan, nan, nan, nan, nan, nan])</pre></div></li></ul></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.DataArray 'volume' (time: 881, rgi_id: 567)> Size: 500kB\n",
       "array([[False, False, False, ..., False, False, False],\n",
       "       [False, False, False, ..., False, False, False],\n",
       "       [False, False, False, ..., False, False, False],\n",
       "       ...,\n",
       "       [False, False, False, ..., False, False, False],\n",
       "       [False, False, False, ..., False, False, False],\n",
       "       [False, False, False, ..., False, False, False]])\n",
       "Coordinates:\n",
       "  * time            (time) float64 7kB 1.975e+03 1.976e+03 ... 2.855e+03\n",
       "  * rgi_id          (rgi_id) <U14 32kB 'RGI60-06.00001' ... 'RGI60-06.00568'\n",
       "    scenario        <U23 92B 'up2p0-gwl6p0-200y-dn2p0'\n",
       "    hydro_year      (time) float64 7kB 1.975e+03 1.976e+03 1.977e+03 ... nan nan\n",
       "    hydro_month     (time) float64 7kB 4.0 4.0 4.0 4.0 4.0 ... nan nan nan nan\n",
       "    calendar_year   (time) float64 7kB 1.975e+03 1.976e+03 1.977e+03 ... nan nan\n",
       "    calendar_month  (time) float64 7kB 1.0 1.0 1.0 1.0 1.0 ... nan nan nan nan"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "scen_filled"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "id": "9b2e67ca-2cea-4159-bcdf-162f778e22b3",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Scenario</th>\n",
       "      <th>Glaciers Stopped Prematurely</th>\n",
       "      <th>Total Years Filled (Until Scenario End)</th>\n",
       "      <th>Avg Years Filled per Affected Glacier</th>\n",
       "      <th>Max Years Filled (Single Glacier)</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>up2p0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
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       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>up2p0-gwl1p5</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
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       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>up2p0-gwl1p5-50y-dn1p0</td>\n",
       "      <td>80</td>\n",
       "      <td>2030</td>\n",
       "      <td>25.4</td>\n",
       "      <td>66.0</td>\n",
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       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>up2p0-gwl1p5-200y-dn1p0</td>\n",
       "      <td>9</td>\n",
       "      <td>160</td>\n",
       "      <td>17.8</td>\n",
       "      <td>41.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>up2p0-gwl2p0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>up2p0-gwl2p0-50y-dn0p5</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>up2p0-gwl2p0-50y-dn1p0</td>\n",
       "      <td>162</td>\n",
       "      <td>2791</td>\n",
       "      <td>17.2</td>\n",
       "      <td>75.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>up2p0-gwl2p0-50y-dn2p0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
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       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>up2p0-gwl2p0-200y-dn0p5</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>up2p0-gwl2p0-200y-dn1p0</td>\n",
       "      <td>15</td>\n",
       "      <td>320</td>\n",
       "      <td>21.3</td>\n",
       "      <td>32.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>up2p0-gwl3p0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>up2p0-gwl3p0-50y-dn0p5</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>up2p0-gwl3p0-50y-dn1p0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
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       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>up2p0-gwl3p0-50y-dn2p0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>up2p0-gwl3p0-200y-dn0p5</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>up2p0-gwl3p0-200y-dn1p0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>up2p0-gwl4p0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>up2p0-gwl4p0-50y-dn0p5</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>up2p0-gwl4p0-50y-dn2p0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>up2p0-gwl4p0-200y-dn1p0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>up2p0-gwl5p0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>up2p0-gwl5p0-50y-dn2p0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>up2p0-gwl5p0-200y-dn0p5</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>up2p0-gwl5p0-200y-dn1p0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>up2p0-gwl5p0-200y-dn2p0</td>\n",
       "      <td>4</td>\n",
       "      <td>12</td>\n",
       "      <td>3.0</td>\n",
       "      <td>5.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>up2p0-gwl6p0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>up2p0-gwl6p0-50y-dn1p0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>up2p0-gwl6p0-50y-dn2p0</td>\n",
       "      <td>174</td>\n",
       "      <td>4167</td>\n",
       "      <td>23.9</td>\n",
       "      <td>53.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>up2p0-gwl6p0-200y-dn0p5</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>up2p0-gwl6p0-200y-dn1p0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>up2p0-gwl6p0-200y-dn2p0</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
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      ],
      "text/plain": [
       "                   Scenario  Glaciers Stopped Prematurely  \\\n",
       "0                     up2p0                             0   \n",
       "1              up2p0-gwl1p5                             0   \n",
       "2    up2p0-gwl1p5-50y-dn1p0                            80   \n",
       "3   up2p0-gwl1p5-200y-dn1p0                             9   \n",
       "4              up2p0-gwl2p0                             0   \n",
       "5    up2p0-gwl2p0-50y-dn0p5                             0   \n",
       "6    up2p0-gwl2p0-50y-dn1p0                           162   \n",
       "7    up2p0-gwl2p0-50y-dn2p0                             0   \n",
       "8   up2p0-gwl2p0-200y-dn0p5                             0   \n",
       "9   up2p0-gwl2p0-200y-dn1p0                            15   \n",
       "10             up2p0-gwl3p0                             0   \n",
       "11   up2p0-gwl3p0-50y-dn0p5                             0   \n",
       "12   up2p0-gwl3p0-50y-dn1p0                             0   \n",
       "13   up2p0-gwl3p0-50y-dn2p0                             0   \n",
       "14  up2p0-gwl3p0-200y-dn0p5                             0   \n",
       "15  up2p0-gwl3p0-200y-dn1p0                             0   \n",
       "16             up2p0-gwl4p0                             0   \n",
       "17   up2p0-gwl4p0-50y-dn0p5                             0   \n",
       "18   up2p0-gwl4p0-50y-dn2p0                             0   \n",
       "19  up2p0-gwl4p0-200y-dn1p0                             0   \n",
       "20             up2p0-gwl5p0                             0   \n",
       "21   up2p0-gwl5p0-50y-dn2p0                             0   \n",
       "22  up2p0-gwl5p0-200y-dn0p5                             0   \n",
       "23  up2p0-gwl5p0-200y-dn1p0                             0   \n",
       "24  up2p0-gwl5p0-200y-dn2p0                             4   \n",
       "25             up2p0-gwl6p0                             0   \n",
       "26   up2p0-gwl6p0-50y-dn1p0                             0   \n",
       "27   up2p0-gwl6p0-50y-dn2p0                           174   \n",
       "28  up2p0-gwl6p0-200y-dn0p5                             0   \n",
       "29  up2p0-gwl6p0-200y-dn1p0                             0   \n",
       "30  up2p0-gwl6p0-200y-dn2p0                             0   \n",
       "\n",
       "    Total Years Filled (Until Scenario End)  \\\n",
       "0                                         0   \n",
       "1                                         0   \n",
       "2                                      2030   \n",
       "3                                       160   \n",
       "4                                         0   \n",
       "5                                         0   \n",
       "6                                      2791   \n",
       "7                                         0   \n",
       "8                                         0   \n",
       "9                                       320   \n",
       "10                                        0   \n",
       "11                                        0   \n",
       "12                                        0   \n",
       "13                                        0   \n",
       "14                                        0   \n",
       "15                                        0   \n",
       "16                                        0   \n",
       "17                                        0   \n",
       "18                                        0   \n",
       "19                                        0   \n",
       "20                                        0   \n",
       "21                                        0   \n",
       "22                                        0   \n",
       "23                                        0   \n",
       "24                                       12   \n",
       "25                                        0   \n",
       "26                                        0   \n",
       "27                                     4167   \n",
       "28                                        0   \n",
       "29                                        0   \n",
       "30                                        0   \n",
       "\n",
       "    Avg Years Filled per Affected Glacier  Max Years Filled (Single Glacier)  \n",
       "0                                     0.0                                0.0  \n",
       "1                                     0.0                                0.0  \n",
       "2                                    25.4                               66.0  \n",
       "3                                    17.8                               41.0  \n",
       "4                                     0.0                                0.0  \n",
       "5                                     0.0                                0.0  \n",
       "6                                    17.2                               75.0  \n",
       "7                                     0.0                                0.0  \n",
       "8                                     0.0                                0.0  \n",
       "9                                    21.3                               32.0  \n",
       "10                                    0.0                                0.0  \n",
       "11                                    0.0                                0.0  \n",
       "12                                    0.0                                0.0  \n",
       "13                                    0.0                                0.0  \n",
       "14                                    0.0                                0.0  \n",
       "15                                    0.0                                0.0  \n",
       "16                                    0.0                                0.0  \n",
       "17                                    0.0                                0.0  \n",
       "18                                    0.0                                0.0  \n",
       "19                                    0.0                                0.0  \n",
       "20                                    0.0                                0.0  \n",
       "21                                    0.0                                0.0  \n",
       "22                                    0.0                                0.0  \n",
       "23                                    0.0                                0.0  \n",
       "24                                    3.0                                5.0  \n",
       "25                                    0.0                                0.0  \n",
       "26                                    0.0                                0.0  \n",
       "27                                   23.9                               53.0  \n",
       "28                                    0.0                                0.0  \n",
       "29                                    0.0                                0.0  \n",
       "30                                    0.0                                0.0  "
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "\n",
    "# Mask for values that were valid in the original dataset\n",
    "was_valid = ds_reg_vol.notnull()\n",
    "\n",
    "# Mask for values that were filled and fall within the true scenario lifespan\n",
    "was_filled = volume_filled_raw.notnull() & ds_reg_vol.isnull()\n",
    "was_filled = was_filled.where(scenario_mask, False) # Discard fills past the scenario's true end\n",
    "\n",
    "stats = []\n",
    "\n",
    "# Loop through each unique scenario to compute individual statistics\n",
    "for scenario in ds_reg_vol.scenario.values:\n",
    "    scen_filled = was_filled.sel(scenario=scenario)\n",
    "    \n",
    "    # Count how many glaciers crashed before the true end of this scenario\n",
    "    num_glaciers_affected = int((scen_filled.sum(dim='time') > 0).sum().values)\n",
    "    \n",
    "    # Count total data points (glacier-years) patched up to the scenario's end\n",
    "    total_points_filled = int(scen_filled.sum().values)\n",
    "\n",
    "    # Calculate the total years filled per individual glacier\n",
    "    years_per_glacier = scen_filled.sum(dim='time')\n",
    "    \n",
    "    # Calculate the average number of years filled per affected glacier\n",
    "    if num_glaciers_affected > 0:\n",
    "        years_per_affected_glacier = scen_filled.sum(dim='time')\n",
    "        avg_years = float(years_per_affected_glacier.where(years_per_affected_glacier > 0).mean().values)\n",
    "        max_years = int(years_per_glacier.max().values)\n",
    "    else:\n",
    "        avg_years = 0.0\n",
    "        max_years = 0.0\n",
    "        \n",
    "    stats.append({\n",
    "        \"Scenario\": scenario,\n",
    "        \"Glaciers Stopped Prematurely\": num_glaciers_affected,\n",
    "        \"Total Years Filled (Until Scenario End)\": total_points_filled,\n",
    "        \"Avg Years Filled per Affected Glacier\": round(avg_years, 1),\n",
    "        \"Max Years Filled (Single Glacier)\": max_years\n",
    "    })\n",
    "\n",
    "# Convert the results into a clean Pandas DataFrame for display\n",
    "df_stats = pd.DataFrame(stats)\n",
    "df_stats"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "id": "0b8cdc3f-9be0-4b78-962a-038ef7715f16",
   "metadata": {},
   "outputs": [],
   "source": [
    "from func_add_terrafirma import get_scenario_style"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "id": "d65b0f43-01fe-4556-ac25-c38e0dab3e81",
   "metadata": {},
   "outputs": [
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       "  grid-column: 1 / -1;\n",
       "  margin-top: 4px;\n",
       "  margin-bottom: 5px;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked ~ .xr-section-details {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-group-box {\n",
       "  display: inline-grid;\n",
       "  grid-template-columns: 0px 20px auto;\n",
       "  width: 100%;\n",
       "}\n",
       "\n",
       ".xr-group-box-vline {\n",
       "  grid-column-start: 1;\n",
       "  border-right: 0.2em solid;\n",
       "  border-color: var(--xr-border-color);\n",
       "  width: 0px;\n",
       "}\n",
       "\n",
       ".xr-group-box-hline {\n",
       "  grid-column-start: 2;\n",
       "  grid-row-start: 1;\n",
       "  height: 1em;\n",
       "  width: 20px;\n",
       "  border-bottom: 0.2em solid;\n",
       "  border-color: var(--xr-border-color);\n",
       "}\n",
       "\n",
       ".xr-group-box-contents {\n",
       "  grid-column-start: 3;\n",
       "}\n",
       "\n",
       ".xr-array-wrap {\n",
       "  grid-column: 1 / -1;\n",
       "  display: grid;\n",
       "  grid-template-columns: 20px auto;\n",
       "}\n",
       "\n",
       ".xr-array-wrap > label {\n",
       "  grid-column: 1;\n",
       "  vertical-align: top;\n",
       "}\n",
       "\n",
       ".xr-preview {\n",
       "  color: var(--xr-font-color3);\n",
       "}\n",
       "\n",
       ".xr-array-preview,\n",
       ".xr-array-data {\n",
       "  padding: 0 5px !important;\n",
       "  grid-column: 2;\n",
       "}\n",
       "\n",
       ".xr-array-data,\n",
       ".xr-array-in:checked ~ .xr-array-preview {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-array-in:checked ~ .xr-array-data,\n",
       ".xr-array-preview {\n",
       "  display: inline-block;\n",
       "}\n",
       "\n",
       ".xr-dim-list {\n",
       "  display: inline-block !important;\n",
       "  list-style: none;\n",
       "  padding: 0 !important;\n",
       "  margin: 0;\n",
       "}\n",
       "\n",
       ".xr-dim-list li {\n",
       "  display: inline-block;\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "}\n",
       "\n",
       ".xr-dim-list:before {\n",
       "  content: \"(\";\n",
       "}\n",
       "\n",
       ".xr-dim-list:after {\n",
       "  content: \")\";\n",
       "}\n",
       "\n",
       ".xr-dim-list li:not(:last-child):after {\n",
       "  content: \",\";\n",
       "  padding-right: 5px;\n",
       "}\n",
       "\n",
       ".xr-has-index {\n",
       "  font-weight: bold;\n",
       "}\n",
       "\n",
       ".xr-var-list,\n",
       ".xr-var-item {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-var-item > div,\n",
       ".xr-var-item label,\n",
       ".xr-var-item > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-even);\n",
       "  border-color: var(--xr-background-color-row-odd);\n",
       "  margin-bottom: 0;\n",
       "  padding-top: 2px;\n",
       "}\n",
       "\n",
       ".xr-var-item > .xr-var-name:hover span {\n",
       "  padding-right: 5px;\n",
       "}\n",
       "\n",
       ".xr-var-list > li:nth-child(odd) > div,\n",
       ".xr-var-list > li:nth-child(odd) > label,\n",
       ".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-odd);\n",
       "  border-color: var(--xr-background-color-row-even);\n",
       "}\n",
       "\n",
       ".xr-var-name {\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-var-dims {\n",
       "  grid-column: 2;\n",
       "}\n",
       "\n",
       ".xr-var-dtype {\n",
       "  grid-column: 3;\n",
       "  text-align: right;\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-var-preview {\n",
       "  grid-column: 4;\n",
       "}\n",
       "\n",
       ".xr-index-preview {\n",
       "  grid-column: 2 / 5;\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-var-name,\n",
       ".xr-var-dims,\n",
       ".xr-var-dtype,\n",
       ".xr-preview,\n",
       ".xr-attrs dt {\n",
       "  white-space: nowrap;\n",
       "  overflow: hidden;\n",
       "  text-overflow: ellipsis;\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-var-name:hover,\n",
       ".xr-var-dims:hover,\n",
       ".xr-var-dtype:hover,\n",
       ".xr-attrs dt:hover {\n",
       "  overflow: visible;\n",
       "  width: auto;\n",
       "  z-index: 1;\n",
       "}\n",
       "\n",
       ".xr-var-attrs,\n",
       ".xr-var-data,\n",
       ".xr-index-data {\n",
       "  display: none;\n",
       "  border-top: 2px dotted var(--xr-background-color);\n",
       "  padding-bottom: 20px !important;\n",
       "  padding-top: 10px !important;\n",
       "}\n",
       "\n",
       ".xr-var-attrs-in + label,\n",
       ".xr-var-data-in + label,\n",
       ".xr-index-data-in + label {\n",
       "  padding: 0 1px;\n",
       "}\n",
       "\n",
       ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
       ".xr-var-data-in:checked ~ .xr-var-data,\n",
       ".xr-index-data-in:checked ~ .xr-index-data {\n",
       "  display: block;\n",
       "}\n",
       "\n",
       ".xr-var-data > table {\n",
       "  float: right;\n",
       "}\n",
       "\n",
       ".xr-var-data > pre,\n",
       ".xr-index-data > pre,\n",
       ".xr-var-data > table > tbody > tr {\n",
       "  background-color: transparent !important;\n",
       "}\n",
       "\n",
       ".xr-var-name span,\n",
       ".xr-var-data,\n",
       ".xr-index-name div,\n",
       ".xr-index-data,\n",
       ".xr-attrs {\n",
       "  padding-left: 25px !important;\n",
       "}\n",
       "\n",
       ".xr-attrs,\n",
       ".xr-var-attrs,\n",
       ".xr-var-data,\n",
       ".xr-index-data {\n",
       "  grid-column: 1 / -1;\n",
       "}\n",
       "\n",
       "dl.xr-attrs {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  display: grid;\n",
       "  grid-template-columns: 125px auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt,\n",
       ".xr-attrs dd {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  float: left;\n",
       "  padding-right: 10px;\n",
       "  width: auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt {\n",
       "  font-weight: normal;\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-attrs dt:hover span {\n",
       "  display: inline-block;\n",
       "  background: var(--xr-background-color);\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-attrs dd {\n",
       "  grid-column: 2;\n",
       "  white-space: pre-wrap;\n",
       "  word-break: break-all;\n",
       "}\n",
       "\n",
       ".xr-icon-database,\n",
       ".xr-icon-file-text2,\n",
       ".xr-no-icon {\n",
       "  display: inline-block;\n",
       "  vertical-align: middle;\n",
       "  width: 1em;\n",
       "  height: 1.5em !important;\n",
       "  stroke-width: 0;\n",
       "  stroke: currentColor;\n",
       "  fill: currentColor;\n",
       "}\n",
       "\n",
       ".xr-var-attrs-in:checked + label > .xr-icon-file-text2,\n",
       ".xr-var-data-in:checked + label > .xr-icon-database,\n",
       ".xr-index-data-in:checked + label > .xr-icon-database {\n",
       "  color: var(--xr-font-color0);\n",
       "  filter: drop-shadow(1px 1px 5px var(--xr-font-color2));\n",
       "  stroke-width: 0.8px;\n",
       "}\n",
       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.DataArray &#x27;scenario&#x27; (scenario: 31)&gt; Size: 3kB\n",
       "array([&#x27;up2p0&#x27;, &#x27;up2p0-gwl1p5&#x27;, &#x27;up2p0-gwl1p5-50y-dn1p0&#x27;,\n",
       "       &#x27;up2p0-gwl1p5-200y-dn1p0&#x27;, &#x27;up2p0-gwl2p0&#x27;, &#x27;up2p0-gwl2p0-50y-dn0p5&#x27;,\n",
       "       &#x27;up2p0-gwl2p0-50y-dn1p0&#x27;, &#x27;up2p0-gwl2p0-50y-dn2p0&#x27;,\n",
       "       &#x27;up2p0-gwl2p0-200y-dn0p5&#x27;, &#x27;up2p0-gwl2p0-200y-dn1p0&#x27;, &#x27;up2p0-gwl3p0&#x27;,\n",
       "       &#x27;up2p0-gwl3p0-50y-dn0p5&#x27;, &#x27;up2p0-gwl3p0-50y-dn1p0&#x27;,\n",
       "       &#x27;up2p0-gwl3p0-50y-dn2p0&#x27;, &#x27;up2p0-gwl3p0-200y-dn0p5&#x27;,\n",
       "       &#x27;up2p0-gwl3p0-200y-dn1p0&#x27;, &#x27;up2p0-gwl4p0&#x27;, &#x27;up2p0-gwl4p0-50y-dn0p5&#x27;,\n",
       "       &#x27;up2p0-gwl4p0-50y-dn2p0&#x27;, &#x27;up2p0-gwl4p0-200y-dn1p0&#x27;, &#x27;up2p0-gwl5p0&#x27;,\n",
       "       &#x27;up2p0-gwl5p0-50y-dn2p0&#x27;, &#x27;up2p0-gwl5p0-200y-dn0p5&#x27;,\n",
       "       &#x27;up2p0-gwl5p0-200y-dn1p0&#x27;, &#x27;up2p0-gwl5p0-200y-dn2p0&#x27;, &#x27;up2p0-gwl6p0&#x27;,\n",
       "       &#x27;up2p0-gwl6p0-50y-dn1p0&#x27;, &#x27;up2p0-gwl6p0-50y-dn2p0&#x27;,\n",
       "       &#x27;up2p0-gwl6p0-200y-dn0p5&#x27;, &#x27;up2p0-gwl6p0-200y-dn1p0&#x27;,\n",
       "       &#x27;up2p0-gwl6p0-200y-dn2p0&#x27;], dtype=&#x27;&lt;U23&#x27;)\n",
       "Coordinates:\n",
       "  * scenario  (scenario) &lt;U23 3kB &#x27;up2p0&#x27; ... &#x27;up2p0-gwl6p0-200y-dn2p0&#x27;</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-obj-name'>&#x27;scenario&#x27;</div><ul class='xr-dim-list'><li><span class='xr-has-index'>scenario</span>: 31</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-8235f3cc-37ab-48a3-ac12-b21b26643d23' class='xr-array-in' type='checkbox' checked><label for='section-8235f3cc-37ab-48a3-ac12-b21b26643d23' 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>&#x27;up2p0&#x27; &#x27;up2p0-gwl1p5&#x27; ... &#x27;up2p0-gwl6p0-200y-dn2p0&#x27;</span></div><div class='xr-array-data'><pre>array([&#x27;up2p0&#x27;, &#x27;up2p0-gwl1p5&#x27;, &#x27;up2p0-gwl1p5-50y-dn1p0&#x27;,\n",
       "       &#x27;up2p0-gwl1p5-200y-dn1p0&#x27;, &#x27;up2p0-gwl2p0&#x27;, &#x27;up2p0-gwl2p0-50y-dn0p5&#x27;,\n",
       "       &#x27;up2p0-gwl2p0-50y-dn1p0&#x27;, &#x27;up2p0-gwl2p0-50y-dn2p0&#x27;,\n",
       "       &#x27;up2p0-gwl2p0-200y-dn0p5&#x27;, &#x27;up2p0-gwl2p0-200y-dn1p0&#x27;, &#x27;up2p0-gwl3p0&#x27;,\n",
       "       &#x27;up2p0-gwl3p0-50y-dn0p5&#x27;, &#x27;up2p0-gwl3p0-50y-dn1p0&#x27;,\n",
       "       &#x27;up2p0-gwl3p0-50y-dn2p0&#x27;, &#x27;up2p0-gwl3p0-200y-dn0p5&#x27;,\n",
       "       &#x27;up2p0-gwl3p0-200y-dn1p0&#x27;, &#x27;up2p0-gwl4p0&#x27;, &#x27;up2p0-gwl4p0-50y-dn0p5&#x27;,\n",
       "       &#x27;up2p0-gwl4p0-50y-dn2p0&#x27;, &#x27;up2p0-gwl4p0-200y-dn1p0&#x27;, &#x27;up2p0-gwl5p0&#x27;,\n",
       "       &#x27;up2p0-gwl5p0-50y-dn2p0&#x27;, &#x27;up2p0-gwl5p0-200y-dn0p5&#x27;,\n",
       "       &#x27;up2p0-gwl5p0-200y-dn1p0&#x27;, &#x27;up2p0-gwl5p0-200y-dn2p0&#x27;, &#x27;up2p0-gwl6p0&#x27;,\n",
       "       &#x27;up2p0-gwl6p0-50y-dn1p0&#x27;, &#x27;up2p0-gwl6p0-50y-dn2p0&#x27;,\n",
       "       &#x27;up2p0-gwl6p0-200y-dn0p5&#x27;, &#x27;up2p0-gwl6p0-200y-dn1p0&#x27;,\n",
       "       &#x27;up2p0-gwl6p0-200y-dn2p0&#x27;], dtype=&#x27;&lt;U23&#x27;)</pre></div></div></li><li class='xr-section-item'><input id='section-2a1a4190-aa80-49af-809b-9072a8672c47' class='xr-section-summary-in' type='checkbox'  checked><label for='section-2a1a4190-aa80-49af-809b-9072a8672c47' class='xr-section-summary' >Coordinates: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>scenario</span></div><div class='xr-var-dims'>(scenario)</div><div class='xr-var-dtype'>&lt;U23</div><div class='xr-var-preview xr-preview'>&#x27;up2p0&#x27; ... &#x27;up2p0-gwl6p0-200y-d...</div><input id='attrs-2783d562-6f4b-4361-9d83-d045eb250930' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-2783d562-6f4b-4361-9d83-d045eb250930' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-06a48858-c2c0-4e11-8dfb-422a505a6b1c' class='xr-var-data-in' type='checkbox'><label for='data-06a48858-c2c0-4e11-8dfb-422a505a6b1c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;up2p0&#x27;, &#x27;up2p0-gwl1p5&#x27;, &#x27;up2p0-gwl1p5-50y-dn1p0&#x27;,\n",
       "       &#x27;up2p0-gwl1p5-200y-dn1p0&#x27;, &#x27;up2p0-gwl2p0&#x27;, &#x27;up2p0-gwl2p0-50y-dn0p5&#x27;,\n",
       "       &#x27;up2p0-gwl2p0-50y-dn1p0&#x27;, &#x27;up2p0-gwl2p0-50y-dn2p0&#x27;,\n",
       "       &#x27;up2p0-gwl2p0-200y-dn0p5&#x27;, &#x27;up2p0-gwl2p0-200y-dn1p0&#x27;, &#x27;up2p0-gwl3p0&#x27;,\n",
       "       &#x27;up2p0-gwl3p0-50y-dn0p5&#x27;, &#x27;up2p0-gwl3p0-50y-dn1p0&#x27;,\n",
       "       &#x27;up2p0-gwl3p0-50y-dn2p0&#x27;, &#x27;up2p0-gwl3p0-200y-dn0p5&#x27;,\n",
       "       &#x27;up2p0-gwl3p0-200y-dn1p0&#x27;, &#x27;up2p0-gwl4p0&#x27;, &#x27;up2p0-gwl4p0-50y-dn0p5&#x27;,\n",
       "       &#x27;up2p0-gwl4p0-50y-dn2p0&#x27;, &#x27;up2p0-gwl4p0-200y-dn1p0&#x27;, &#x27;up2p0-gwl5p0&#x27;,\n",
       "       &#x27;up2p0-gwl5p0-50y-dn2p0&#x27;, &#x27;up2p0-gwl5p0-200y-dn0p5&#x27;,\n",
       "       &#x27;up2p0-gwl5p0-200y-dn1p0&#x27;, &#x27;up2p0-gwl5p0-200y-dn2p0&#x27;, &#x27;up2p0-gwl6p0&#x27;,\n",
       "       &#x27;up2p0-gwl6p0-50y-dn1p0&#x27;, &#x27;up2p0-gwl6p0-50y-dn2p0&#x27;,\n",
       "       &#x27;up2p0-gwl6p0-200y-dn0p5&#x27;, &#x27;up2p0-gwl6p0-200y-dn1p0&#x27;,\n",
       "       &#x27;up2p0-gwl6p0-200y-dn2p0&#x27;], dtype=&#x27;&lt;U23&#x27;)</pre></div></li></ul></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.DataArray 'scenario' (scenario: 31)> Size: 3kB\n",
       "array(['up2p0', 'up2p0-gwl1p5', 'up2p0-gwl1p5-50y-dn1p0',\n",
       "       'up2p0-gwl1p5-200y-dn1p0', 'up2p0-gwl2p0', 'up2p0-gwl2p0-50y-dn0p5',\n",
       "       'up2p0-gwl2p0-50y-dn1p0', 'up2p0-gwl2p0-50y-dn2p0',\n",
       "       'up2p0-gwl2p0-200y-dn0p5', 'up2p0-gwl2p0-200y-dn1p0', 'up2p0-gwl3p0',\n",
       "       'up2p0-gwl3p0-50y-dn0p5', 'up2p0-gwl3p0-50y-dn1p0',\n",
       "       'up2p0-gwl3p0-50y-dn2p0', 'up2p0-gwl3p0-200y-dn0p5',\n",
       "       'up2p0-gwl3p0-200y-dn1p0', 'up2p0-gwl4p0', 'up2p0-gwl4p0-50y-dn0p5',\n",
       "       'up2p0-gwl4p0-50y-dn2p0', 'up2p0-gwl4p0-200y-dn1p0', 'up2p0-gwl5p0',\n",
       "       'up2p0-gwl5p0-50y-dn2p0', 'up2p0-gwl5p0-200y-dn0p5',\n",
       "       'up2p0-gwl5p0-200y-dn1p0', 'up2p0-gwl5p0-200y-dn2p0', 'up2p0-gwl6p0',\n",
       "       'up2p0-gwl6p0-50y-dn1p0', 'up2p0-gwl6p0-50y-dn2p0',\n",
       "       'up2p0-gwl6p0-200y-dn0p5', 'up2p0-gwl6p0-200y-dn1p0',\n",
       "       'up2p0-gwl6p0-200y-dn2p0'], dtype='<U23')\n",
       "Coordinates:\n",
       "  * scenario  (scenario) <U23 3kB 'up2p0' ... 'up2p0-gwl6p0-200y-dn2p0'"
      ]
     },
     "execution_count": 42,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "regional_volume_filled.scenario"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "3aef473e-4164-4819-a2c4-7214b72156c0",
   "metadata": {},
   "outputs": [],
   "source": [
    "regional_volume_rm_glacier"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 85,
   "id": "a119a377-e387-4047-b7a8-f154120dd803",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 2500x1400 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.rc('font', size=20) \n",
    "plt.figure(figsize=(25,14))\n",
    "\n",
    "for scenario in regional_volume_rm_glacier.scenario.values:\n",
    "    regional_volume_rm_glacier_scenario = regional_volume_rm_glacier.sel(scenario=scenario)\n",
    "    regional_volume_filled_scenario = regional_volume_filled.sel(scenario=scenario)\n",
    "\n",
    "    plt.plot(regional_volume_rm_glacier_scenario.time,\n",
    "             (regional_volume_filled_scenario.values/1e9 - regional_volume_rm_glacier_scenario.values/1e9),\n",
    "             label=scenario, \n",
    "            color=get_scenario_style(scenario)['color'],\n",
    "            ls=get_scenario_style(scenario)['linestyle'],\n",
    "            lw= get_scenario_style(scenario)['linewidth']+1)\n",
    "#plt.legend()\n",
    "plt.ylabel('Volume difference (filled–removed glaciers, km³)')\n",
    "plt.savefig('test_rgi06_filled_minus_removed_opt.png')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 84,
   "id": "a26ac7c5-66c7-4333-81c0-52bd44c0e378",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 2500x1400 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.rc('font', size=20) \n",
    "plt.figure(figsize=(25,14))\n",
    "for scenario in regional_volume_rm_glacier.scenario.values:\n",
    "    regional_volume_rm_glacier_scenario = regional_volume_rm_glacier.sel(scenario=scenario)\n",
    "    regional_volume_filled_scenario = regional_volume_filled.sel(scenario=scenario)\n",
    "\n",
    "    plt.plot(regional_volume_rm_glacier_scenario.time,\n",
    "             100*(regional_volume_filled_scenario.values - regional_volume_rm_glacier_scenario.values)/regional_volume_filled_scenario.values[0],\n",
    "             label=scenario, \n",
    "            color=get_scenario_style(scenario)['color'],\n",
    "            ls=get_scenario_style(scenario)['linestyle'],\n",
    "            lw= get_scenario_style(scenario)['linewidth']+1)\n",
    "#plt.legend()\n",
    "plt.ylabel('Volume difference (filled–removed glaciers, % rel. to initial filled volume)') \n",
    "#### maximum 1% difference ... in RGI06\n",
    "plt.savefig('test_rgi06_filled_minus_removed_perc_opt.png')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "id": "a6623801-31b3-4eaf-a723-2b4613d07f43",
   "metadata": {},
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       ".xr-header {\n",
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       "\n",
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       "\n",
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       ".xr-group-name,\n",
       ".xr-obj-type {\n",
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       ".xr-sections {\n",
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       ".xr-section-item input {\n",
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       "  color: var(--xr-disabled-color);\n",
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       "\n",
       ".xr-section-item input:enabled + label {\n",
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       "  color: var(--xr-font-color2);\n",
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       "\n",
       ".xr-section-item input:focus + label {\n",
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       "\n",
       ".xr-section-item input:enabled + label:hover {\n",
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       "\n",
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       "\n",
       ".xr-section-summary > span {\n",
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       "\n",
       ".xr-section-summary-in:disabled + label {\n",
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       "\n",
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       "\n",
       ".xr-group-box-hline {\n",
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       ".xr-array-preview,\n",
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       ".xr-var-attrs-in + label,\n",
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       "\n",
       "dl.xr-attrs {\n",
       "  padding: 0;\n",
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       "  grid-template-columns: 125px auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt,\n",
       ".xr-attrs dd {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  float: left;\n",
       "  padding-right: 10px;\n",
       "  width: auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt {\n",
       "  font-weight: normal;\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-attrs dt:hover span {\n",
       "  display: inline-block;\n",
       "  background: var(--xr-background-color);\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-attrs dd {\n",
       "  grid-column: 2;\n",
       "  white-space: pre-wrap;\n",
       "  word-break: break-all;\n",
       "}\n",
       "\n",
       ".xr-icon-database,\n",
       ".xr-icon-file-text2,\n",
       ".xr-no-icon {\n",
       "  display: inline-block;\n",
       "  vertical-align: middle;\n",
       "  width: 1em;\n",
       "  height: 1.5em !important;\n",
       "  stroke-width: 0;\n",
       "  stroke: currentColor;\n",
       "  fill: currentColor;\n",
       "}\n",
       "\n",
       ".xr-var-attrs-in:checked + label > .xr-icon-file-text2,\n",
       ".xr-var-data-in:checked + label > .xr-icon-database,\n",
       ".xr-index-data-in:checked + label > .xr-icon-database {\n",
       "  color: var(--xr-font-color0);\n",
       "  filter: drop-shadow(1px 1px 5px var(--xr-font-color2));\n",
       "  stroke-width: 0.8px;\n",
       "}\n",
       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.DataArray &#x27;volume&#x27; ()&gt; Size: 8B\n",
       "array(3836.11437056)\n",
       "Coordinates:\n",
       "    scenario        &lt;U23 92B &#x27;up2p0-gwl6p0-200y-dn2p0&#x27;\n",
       "    time            float64 8B 1.975e+03\n",
       "    hydro_year      float64 8B 1.975e+03\n",
       "    hydro_month     float64 8B 4.0\n",
       "    calendar_year   float64 8B 1.975e+03\n",
       "    calendar_month  float64 8B 1.0</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-obj-name'>&#x27;volume&#x27;</div></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-f05ccb3f-5254-4bd2-8b35-d891bb4dda3d' class='xr-array-in' type='checkbox' checked><label for='section-f05ccb3f-5254-4bd2-8b35-d891bb4dda3d' 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>3.836e+03</span></div><div class='xr-array-data'><pre>array(3836.11437056)</pre></div></div></li><li class='xr-section-item'><input id='section-12579a7d-375d-446c-8d7e-2a11b7987243' class='xr-section-summary-in' type='checkbox'  checked><label for='section-12579a7d-375d-446c-8d7e-2a11b7987243' class='xr-section-summary' >Coordinates: <span>(6)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>scenario</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>&lt;U23</div><div class='xr-var-preview xr-preview'>&#x27;up2p0-gwl6p0-200y-dn2p0&#x27;</div><input id='attrs-9b0cecc3-abc1-4d6b-9435-57a33155836c' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-9b0cecc3-abc1-4d6b-9435-57a33155836c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5e48b087-f982-4651-8a0b-070cfb74903d' class='xr-var-data-in' type='checkbox'><label for='data-5e48b087-f982-4651-8a0b-070cfb74903d' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array(&#x27;up2p0-gwl6p0-200y-dn2p0&#x27;, dtype=&#x27;&lt;U23&#x27;)</pre></div></li><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'>1.975e+03</div><input id='attrs-355ea297-1ce0-4849-a277-ca24d4242d2b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-355ea297-1ce0-4849-a277-ca24d4242d2b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-38db80a9-a152-463c-93a6-64f40c0ff782' class='xr-var-data-in' type='checkbox'><label for='data-38db80a9-a152-463c-93a6-64f40c0ff782' 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(1975.)</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'>float64</div><div class='xr-var-preview xr-preview'>1.975e+03</div><input id='attrs-88dae6ab-fac5-4248-9b26-cfccd6a0dd70' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-88dae6ab-fac5-4248-9b26-cfccd6a0dd70' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-da1c7e29-2859-4e18-9e5b-49205c57137e' class='xr-var-data-in' type='checkbox'><label for='data-da1c7e29-2859-4e18-9e5b-49205c57137e' 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(1975.)</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'>float64</div><div class='xr-var-preview xr-preview'>4.0</div><input id='attrs-f428a067-5700-44e9-b5c4-e7c43a765038' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f428a067-5700-44e9-b5c4-e7c43a765038' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-96df0ece-4fef-4dec-9167-93f1175223b1' class='xr-var-data-in' type='checkbox'><label for='data-96df0ece-4fef-4dec-9167-93f1175223b1' 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><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'>float64</div><div class='xr-var-preview xr-preview'>1.975e+03</div><input id='attrs-b2550df0-69cd-4826-84fb-2bfbdff58582' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b2550df0-69cd-4826-84fb-2bfbdff58582' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7b3aa638-333a-4bbc-b75e-413cf63e3200' class='xr-var-data-in' type='checkbox'><label for='data-7b3aa638-333a-4bbc-b75e-413cf63e3200' 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(1975.)</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'>float64</div><div class='xr-var-preview xr-preview'>1.0</div><input id='attrs-e070fcc5-8cb7-4c4a-833d-7c884567c287' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-e070fcc5-8cb7-4c4a-833d-7c884567c287' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ef76ae4e-fa02-42c2-9731-df894b4b5981' class='xr-var-data-in' type='checkbox'><label for='data-ef76ae4e-fa02-42c2-9731-df894b4b5981' 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></ul></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.DataArray 'volume' ()> Size: 8B\n",
       "array(3836.11437056)\n",
       "Coordinates:\n",
       "    scenario        <U23 92B 'up2p0-gwl6p0-200y-dn2p0'\n",
       "    time            float64 8B 1.975e+03\n",
       "    hydro_year      float64 8B 1.975e+03\n",
       "    hydro_month     float64 8B 4.0\n",
       "    calendar_year   float64 8B 1.975e+03\n",
       "    calendar_month  float64 8B 1.0"
      ]
     },
     "execution_count": 67,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "regional_volume_filled_scenario[0]/1e9"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 83,
   "id": "662ba8eb-bf1f-4fbe-86e6-faecc5e49421",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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oQZ1fGnV+5ep88zfH888/70z379/feYXiXIyW30uu9Wv/tX6oROs5fCACt5oAAFBLnfTE30oscenHp4r+0HW0OM9/9a7ZNZIvAAAA+DM3SY877jhNmTJFf/zxh3Jzc5331157TUcddZTeeeedAyoysz0jWECIr/nz5+voo492boSaYJzs7Gxt377daQAyDUE33nhjwM/NnTvXu59+/foF3X5iYqJ69+7t/YwJ2AnKnSvZPutdiX6rN2zYoCOPPFITJkxwAnn279+vnTt36n//+5/GjBmjM888M+j24+LinBvUxtSpUwOm8b1RPWPGDKfhOFgaExzVtWuJBzpCIGKPXQjk5eUF/e5mncmD0adPHydvwXi+k/mOJrDTlzmuJdMFYoLKTKOoMXNm8YM6CQkJuvTSS53pr7/+2mlALe//uuf8M0FaVWEC5A477DA9/PDDWrFihXJycpSRkeE0wg4fPtw59yvDNMYec8wxevnll7Vu3TqnbLdt2+YEVZj/I8F+fypadj169HCCQkqWXSjPYSDSUO9XTbTU++YhBPMdjIkTJzo3/6qCej8w6v3qqferQ7Sdw0Ag1PmxV+fPmjXLe114/vnne5eb77Bq1Spt3rzZv2OIGPy95Fq/dl/rV4doO4erioAzAEBEOfKMU81dOr9lT4wr6gXAsFLbSFZC8cp9q2QX+D/xDwAAgOr1888/6+qrr3aeWnzmmWf0448/avr06U5vF+YGpGlYufjii73BNZVlGpM8vaSZJyTLYhpATYNoZmam80TlDz/84OTn6aefVvPmzZ00Tz31lJ544olSn/Xtia28/XjWFxQUOA1Nwbn9g8ziioJWDNNQZhqlTIOtYXqX+uijj5xGLNN4ZtZ9+umnuvPOO4Nu3dNY9dNPP5Xq+co0Ts2eXfxAhimThQsXBm2ENtsyT26GUmQfuwNjyjorKytonsy+TR6Crfflu75kj4FV+e7m5ofpYcfjiiuucN7NTYPXX3896OfNOfXvf//bmT711FPVsmVLVZY5vqeddppzk8LTK9vnn3/unPdvvfWWE9xlbmqZAIaK+OWXX3TRRRc5Tzk/++yzzlPO5ry/++67nZ4WzY2XK6+80mnkLqmiZRcfH68OHTqU+kwoz+GSzJPPptcj0+hsfltNrwIPPfSQ87Q4EG7U+1WrO6Kp3r/mmmuc3zzz+3vyySdXaRvU+8FR71dPvR9q0XYOA4FQ58dmne/bc5R5OMq05ZhruHr16qlTp05q0aKF07OTuY40QUCx9nvJtX7tv9YPtWg7hw/IAQ6pigiSmZnpjPFq3gEgkv29fn97sAb7vX5573PvevfKJ2z3/IuLX6ueCmt+AQBA1WRnZ9vLli1z3lH9Ro0a5Vwztm3btsx0kydPdtKZ15o1a/zWmc961pnpzZs3l/r8999/b8fHxztpevToUaW83nzzzd79PProo2V+H/NKSEiwp0+fXirNxo0b7VatWjlpUlNT7a1bt/qtv+2227zbmDdvXpl5MvnwpP3yyy/L/Q7uwlzbned/ff7EE094t3H99dcH/JxZ7kljXlOnTvVb/+OPP3rXffHFF37rZsyY4SxPS0uz+/XrF7D8du7cabtcLmfd008/XWr/nmNsyjdWj11VnXfeed79vPfee6XWm+NVXtl4mO/kSTt+/Hi/dSNGjPCuy8jIKHM71113nTft8uXL/dadeOKJzvJOnToF/fyHH37o/fz7779vV8W4ceO823jggQdKrc/Ly7NPPfVUv/O+5G9Pyd+fY445xt69e3epNP/+97+9acz/t5KOPfZYZ12dOnXKzfeQIUO828rJyQn5OWxMmDDB73sHetWvX9/++OOPy80vUBL1fvjrjmip9998803v79GWLVu8y01ePXkzv2fBUO9T74er3g/Gs+3yroui/RxG9KDOD///uUiv80ePHu3d98SJE71tOsGuTwL9Dkbz7yXX+rX/Wj9W6/zsKratVyauiB7OAAAR5/ZVpceqnnD+0yaIumimnemC1efpjN3zZeftrsEcAgCAcLCzMuTe+GvoX9sDP51plnvTZARJs2NDyPJhvl8kefzxx50h+0oaMGCAxo4d60ybpxpLDgdYHvPE4D//+U9nulWrVrr22mvL/cxVV12lE088sdRy8xSuyafn6UQz3KevPXv2eKfr1q1b5j48w+sZJZ82DsRyJcpKSPNb9sILL3jz9eijjwb8nFlu1gdjhhYwTxmXHFLDML3MGSeccIK395GSacxTmZ6hMEwPSqEULceuKj744AO9//773mN07rnnlkoTqjyHajueXs7MU7RmmJdAJk+e7B2SZejQoaos09uhZxuHH3640wtiSWaIz0mTJjnvFWWekk5PTy+1fOTIkd7/P77DZ5Ysu/LKrTLnTVXPYY/u3bs7PR188sknTm8G5iluk9b0KGfs3r3bOZ/MsB2xJnv9eu2cOTPkr6wlSwLuzyz3plm8OGCaPcuWhSQP5rtFGur9youGet8MBXbTTTc50w8++KDT48SBoN4PjHq/eur96hAt53Bts239Ni2duTTkr7VL1gbcn1nuTbM4cJr1y9aHLB/m+0US6vzYq/NNfe9h6n3Tk9Stt96q33//3bmmMz233XzzzU6vaeb65JxzzvEOwRntv5dc60fGtX51iJZz+EDFH/AWAACoYXUbNVDv1tKcDcXLcuXS+xffqPPffEpWfJrstMOlrEV/rrWlVY9LXe/jWAEAEMUKl3ynwjnvhny7VtsjlXjuXaWWF0x/Tfa6n4vStDpMicNL/61ROOMNuVfPD0k+4noPV/xxFygSNGjQQGeddVbQ9Zdffrmee+45Z/rbb79Vz549K7TdrVu36rzzznO6kjcNmabRJjU1tdzPXXbZZUHXDRs2TPXr13caRU1ebrnlFu+6nJwc77QZxq4sZqhQj+zsbFWWaYxdsWKFMz18+HBnOIBAzHLTbb/pmj+QuLg4HX/88fryyy9LNTB75k3j8rHHHutMz5w502ksNp/zTWOG7uvWrZtCJZqPXXmWL1/u/R4pKSnOEJWBhi8JVZ5DtR1zvG644QanfE1DsTmvSh5TT5CTGSK3vH0FYgKoPENCjho1Si5X4GdjTYCiCbD67LPPyt2mCdAyDdqBmHI/6qijtGnTJq1evbrUek/ZVeS7VPS8qeo5bNx4443O8CAlmf+/l156qXPjygxfbP4PmwBBc6PHnGOxYv0rr2jlPfeEfLtNTj1Vx371Vanlv/7tb8r4+mtnumG/fjquxG+ssXz8eG395JMDzkOnCRN0SIBjX1tR78duvW9uLpvhss32zRBGB4p6PzDq/eqp96tDNJzDtdE3r3yjt+55K+TbPfrUo3XfV6Wv4yf9bZIWfL3Ame7er7semvZQqTSTx0/W3E/mhiQfIyeM1EV3X6RIQJ0fm3X+vn37/AKJTHCc+RvAo0OHDs6yhg0b6u9//7t27NjhBKKbYQ+j+feSa/3IudavDtFwDocCPZwBACLS+N8+kEtFT2N4vP7WbyrIyyuaaTPa/wPZa2Xn1c7obwAAgGhjGnni44M/43bkkUd6G1WWBOlJpiTzBOCQIUP0xx9/OPMPPPCATjrppHI/Z/YTrEHKME9SmvwGyotvQ3Ce5+/MIEyjq4dvwIe5CWu2G+i1Zs0abzrffZsnl8vSo0ePMtf369fP28DneQIyPz9fs2bN8muENvnMzMzUwoULvZ/1NEKbpzQDBUVVRbQfu7KYxs7TTz/dKQNTnubp3a5duwZMG4o8h3I7Zt48JWy8++67fjcZjDfeeMMJIPQEkZa8qRKs7HyfdF/s00tUeYGnvXr1UkV06dKlzPXmJkjJp4pLll155VZe2YXiHDZMA3V5T1R7eqIz59qHH5buDRyoCdT7sVnvm8+agGRzI/v5558PeiOxoqj3g6Per556P9TCfQ4DNYE6PzbrfN/fKBMg5OndtCQTVNO8eXNnesqUKcWjEtWy30uu9WPvWj/Uwn0O1yYEnAEAIlJCcrIuvMi/MnfLpa//WtT7iJXUWEos0Y3/2mdqMosAAAAxq2nTpmWuN8FonoYg36EZgjFP/5ke00yjqjFu3DiNHz++Qnkx+ykr+M3wDP9UMi+e4Soq0nW9bwOdb5f4EydOdJ7CDPTyfRrS8+RnRcqvSZMmZa73DI9hGgjNU83G3Llzna7809LSnEYv0zjWp08fv4Zn8+TlL7/84teQfaBi4dgFY/JkntRdu7ZoGB7zpPqFF14YNH0o8hzK7Rie4W9Ng60ZKsSXZ3gM03hsysTXHXfcEbTszLqqnPcVHaatvJ7zPAER5mn/kjxlV5GhKsoruwM9hyvKBJ2VHEoHqGnU+7FX75ubX57fH9MbpnmY4EBR7wdHvV899X6ohfscBmoCdX7s1fklf6NOOeUUb69pJZnfQM/DZaaXs2APaoX795Jr/di71g+1cJ/DtQlDagIAItaFbzykd94crAKf+OmXnv9Zg4tGZ5I6jpOW+YwLnr/beaIiVD01AACA2iWu28lytT0i9BtOCtygEd9vlJR7ftFMYuA0cSdcoriew0KSDateY0WKivy9FexJ15JMQ6oZdmLq1KnOvOnN5/HHH6+RvJgndz1M71xlPW28YUPxeO+tW7dWOJl8moYo03BlGpgHDRrkDUQ54YQTvI3DprH6+++/d9KY4TB++OEHud1uv4bsAxHLx8402ppyX7p0qTN/33336S9/+UuZnymZ57KUleeS22ncuHG52zFl7fs5DxNAYJ7CNwGDptHZDONo/Pjjj1q2bFnAJ54rw/f4lXe8K/qbcSBMGZjvZhp1zU2ZsnoY85SduSnkO8xFqM5hOz9HikuQ5Qp8M8fDt8c83yfKY0Gbyy9Xk4EDQ77d+CDH/dDHH1en3buL0qSnB0zT5aGH1OHWWw84Dylt2iiSUO/HXr1velT87bffnBtt5nfI9GJSkqee8PTs4Eljel5p3759qfTU+8FR70eGSD6Ha7tTLj9FRw488MDWkurUrxNw+ZjHx+iC3RcUpUkPnOayhy7TebeeF5J8NGlTdpBRbUKdH3t1fsnfmkDXjcHSmp7EDj744Kj6veRaPzKv9UMtks/hUCPgDAAQsUyF3qeVrRk+92LyFKe87BwlpiTLSmkhu34Paff8opU5m6SsxVJ68G5OAQBA5LLSmjivmuJq3Lb8NI1qZ2NAWU8CehohgynZ1X4gW7duLTcQyfO0o6ens0BMXi655BJ98sknzvyIESP0wgsvqDLMU7Xm6cZgT+B6GkED5cU3kGP58uVl7sez3tx47dixo3f53XffrQn/uFXK3VKcOLGhrAT/gIYGDRqUyk8wGRkZZa43eTjuuOP09ddfe59o9rz7Ni57pmfMmOGUkSeNyUvJp1grK1qOnXlVVnZ2toYOHap58+Z5hxX5xz/+Ue7nOnfu7HxX850rmmfj0EMPLfO7l9XrjGc7puGyTp3AN9NMoKAJODM3MlavXu3cMPA88WyGdAjUa9urr77qvMrje9zM74Ypg2DK+38RCqbsPE93m7Lp3bt30N+w33//PWD5h+IcNg3T9u4t5j+S7OS6slLTZSUkRU3jfKiYoKyaDMxK69at3DT1ggyZWxtR74e37oj0et8zvI/5PfT0kFEW89vq+X01dUiggDPq/eCo9yNDuM/haNa0TVPnVVPadWtXbpo2XSMnOJw6nzr/QK/1DzvsMO90eb1H+a4P1gNUuH8vudaPvWv9UAv3OVybMKQmACCiXTPv9VLLvr2xaFhNR+tLTN8ixfNbP6+hnAEAAEQWT5fuplefsqxYsaLcbf3888/ODchgFi1apLy8PGe6Wxk38M1QTZ7eMM444wy98cYb3sbyijL7MfsLxuTT5DdQXszwAWY4ivKGqjP7mDNnTqnPFO9kj8+MJcUVd58fqAF3/vw/H5gIorz1vsNkmMZDE9w3a9asUjeeTQ8jphExKytLCxcu9DZCn3jiiZUu56g9dpWUn5+vc88917vPq6++Wo888kiFPmv23atXL2d69uzZ3v8jgXi2b3rWKvk0bN++fUulC2TLli1O7zTG8ccfHzTdyJEjnaErTGDTa6+95gTUeY7tOeeco/QgPT1VhO/NDk+AXjDlrQ+Fipad+T/oCb4tq+yqfA7n7ZcKCyTbLWVnSXnZQbfh24NQixYtgqYDSqLeD2/dEW31fihQ71Pv13S9H2qReA4jNlDnU+cfaJ1vPufhefAmGN/1LVu2jJrfS671I/taP9Qi8RyuLuG/igAA4ACkH9RUlvx74Xh/0kLvtJXYUGpYNF69Y89S2fvXUuYAAAAleHqaMMMDBAsqM40dnt4pyrJz505vz1aBvPLKK97pgUGGQxs3bpxefvllZ/rkk0/W+++/r4SEhCodNxMkE8xHH33k7W2tZF5Mw7zZt/Htt98GHebQDCtlbt4aw4YFGEI1sYFkejRzJUjxqQGHyDNd6nue+HzvvfeUk5MTcF9muVlfHs8NZtPI9eSTTzrBMWlpaTrqqKOKs5WYqD59iv5W/vjjj72NZZ6b1lUVVceuEszTrSY464svvnDmTQ9vEydOrNQ2zj77bOfd5MnkLRDzXcx3Msx39NxA8jDnkafXrXfffVf79+8PuB3fp5LL+u7mvDFDo3qOhzmemZmZzvyYMWN0IMxwnZ5efkxQYrDeusxQkabnnupm/t94AujMdw2Wn4qWnWc7lT2H7Zy9xYnMUB0ppYNUPXx7DjzQ/7uILdT74a07Ir3eHz16dFFvjGW8PENqGxMmTPAuN58Nhnq/NOr9yBJJ5zBiB3U+df6BXuubc8jzN8VXX30V9BrTtCd98803znSHDh3UvHnzqPi95Fo/8q/1q0MkncPVykbMyMzMNP+TnXcAiCZPHn6OPViDva8zdLqduz/bu969b53tnn9x8WvZP2x3QW5Y8wwAAMqXnZ1tL1u2zHlH9VuwYIFzzWheY8eOLbXe7XbbV199tTeNea1Zs8YvTdu2bb3r2rVrZ2/ZsqXUdqZNm2bHx8c7aY455piAeZkwYYJ3O8cdd5y9d+/eSn+fUaNGebeRkJBgz5gxo1SazZs3223atHHSpKam2lu3bi2V5rvvvvNu58wzz7QLCgr81mdkZHi3Ub9+fXvnzp1B82TK0O0uDLr+8ccf9+7r+uuvD5jGLPc9BlOnTg2YLi8vz/lOJk16errzPmTIkFLp7r33Xr805mXOhWA8x9iUbywdu/KYY3vZZZd593fuueeW2l9F7Nixw3ssTFlv377db73Z5tChQ737+f777wNuZ9KkSd401113Xan1q1atstPS0pz1HTp0sPPz88vM18yZM73bO+igg5z39u3bO9/7QI0bN8677YcffrjUepO3008/vczfnoqcmyXPL5M+kDvvvNO7n0ceeaTU+lmzZnl/w/r161ct57C7sNBeNG+2vWL+TLtwV+nfUY/nn3/e77hU5f8bYhf1fvjrjmio98ti8urZh/n7IBjqfer9cNb7gXi2XdHPROI5jNhCnR/+/3PRUOe/88473u2YtqFAxowZ403z6KOPRsXvJdf60XOtH4t1fnYV29YrE1dEwFkMIeAMQLTavXmrX8CZeX33wES/NO6VT/gHnS39R9jyCwAAKoaAs5rXu3dvb4OHaUQxwSw//fSTPWXKFLt///7O8j59+pQbcHbEEUc4DS8tW7a0n332WXvu3LlOI8ztt99uJycnO2lMwMacOXNK5eHpp5/2bt983gS6LF68uMyXaXAN1gjUpEkTJ19mv2b/Jh8mPyZfLVq08O7LNAAHc8EFF3jTDRgwwP7Pf/5jz5s3z37llVecYB3POhP8cSByc3Ptbt26ebc3ePBgZ1/mGJh304hslvfq1cubxgTwBTNw4EC/hrtADb4//PCDXxrTkFVYGDworqyGvlg+dr4NqeYYmmNW3nevSBCRyaPJq8mzybv5Dp51F154YdBtmMbK448/3i8A7ssvv7R//PFH+5lnnrGbNm3qLHe5XPbnn39eoe946KGH+p0r5gZGKOzevdtu1aqV3/f64osvnDJ8++237Z49ezrLPe/V3QidlZVld+7c2buvK6+80vktnD17tv3AAw/YdevWdZanpKTYCxcuLHMfB3IOT5482Y6Li3P+H5v1X3/9tVMm5hi+9tpr9imnnOL9vElnzg+gsqj3A6PeD0/AGfU+9X446v2VK1c6da7vq1GjRs5nzHvJdeYmcjScw4g91PmBUedX7nfVtFF4fodM+4T5jTJBbB9//LE9aNAg77qjjjoqYIBLJP5ecq0fPdf6sVjnZxNwhlAi4AxANBthneoXcDYm4RS/9e7cDP+AM/Pa+VPY8gsAAMpHwFnN+/XXX72BKIFepqHNNLqUF3BmGmBeeuklby9AJV+JiYlO41IgpsegYPsP9grUIOXb0GQabBo3bhz08zfccEOZ5bJ//36/htWSLxO0U9aN1MpYt26dX8NSydepp57qNNB55gMF7Xncd999fp815RAoyM0EznjSmN6zylJWQ18sHzvf3v0q+irLXXfdZVuWFfSz5juV94SqeSLWt+E20P/DF198scLf8bHHHvMrt/Xr19uhsmTJEm/PaYFepve4sn57Qv3Us2mI7tSpU9D8mN7hPvnkkwrto6rnsO/3LetlGsbNDR6gKqj3A6PeD0/AGfU+9X446v2K1rdl9TgUiecwYg91fmDU+ZX7Xd2zZ4/TJlHW76S5Bg0UqBOpv5dc60fPtX4s1vnZNRBw5qreATsBAKgZpw3p6De/NT9eedk53nkrsbGU0tr/Q2ue5fAAAAD46NKlixYsWKBrrrlGbdu2VWJiopo0aaJBgwbps88+0+OPP17h8rriiis0Y8YMDR8+XC1atHC21bJlS1166aVauHChLrjgghor+x49ejjf64YbblCHDh2UnJysRo0aOd/r888/11NPPVXm51NSUpzv/+abb+qUU05R06ZNne/TunVrjRw5UjNnztTdd98dkry2adNGixYt0j333KNu3bo5+65fv7569+6tiRMn6osvvlBOTvHfuenp6UG31b9/f790Rx11VKk05nscd9xx3vl+/fqpNomkYxdK5vibvJk8mryaPJu8m+/w1ltvOd/JlEVZGjdurFmzZjnnTd++fZ1yM585+OCDNXbsWKdczXtFXXLJJd5pkw+Tr1A57LDDtHTpUt16663q1KmTkpKSnPwPGDDA+b6vvPKKalLHjh2d36mHH37YOQfN/8HU1FQdcsghuummm/TLL7/ojDPOqNZzePDgwZo0aZLzW3rMMceoVatWzvlsPm9+U08//XTns6tXr9ZZZ50V4hJArKDeD4x6P3yo96n3w1Hvh1KsnsOo/ajzA6POr5y6devqq6++0ttvv+38rh100EFKSEhw2o3Mb5b5/Z49e7azvDyx+nvJtX54r/VDKVbP4ZIsE3VWaimiUlZWltPAnJmZqbS0tHBnBwBCKmtrhi48aLTfsqsu7agzXyuu0O3CPOnnK/4MDv9TtydlJTXmaAAAUAuZoJo1a9aoffv25QZWoHZo166d1q1bp1GjRunVV18Na15Gjx6t1157zQmcW7t2bVjyYBfsk1yJslwJId3u/fffrzvvvFPx8fHas2dP1P3/qA3HDqV99913GjhwoDP9zjvvOMGkCIxzGLGCer9mUO8jHKj3K456H7GAOr9mUOcjHKjzo7fOz6li23pl4oro4QwAEBXSmjVRkgr9lk1+fYXfvBWXKLW62P+DO/9XE9kDAABAjLHd+VLuNil7g+zsTbIL9odmu7btBPsYRx55ZNQFm6H28jx5bJ7YpUet0DP/t91ZGbJz9znTAOD5baDeRzhQ7wNAzaLOR7hQ5+NAEHAGAIgavVr5V2t5ivMbVtPR9BQpqVnx/I4ZNOYDAAAg9PJ3F/es6y7xN2kZzBOSBQUFQdffddddWrJkiTNtepIDaoI5L9977z1n+rLLLnOGvESIFeRJ+zNl79osO2Ot7NzQBKkCqN2o91EbUe8DQPX8tnKtj9qGOh8HKv6AtwAAQC1x7fzXNKPEsJrfjL9XQ556wDtvWZbsRidIm94vWpC7Vdr7m1TvkJrOLgAAAKJUUe9EPj0UuZKkuJQKfdYMRTp58mSNHDlSxx9/vFq0aKH8/Hz9+uuvTrf906ZNc9J17dpVY8eOra6vAGjjxo3av3+/M/zC+PHjnfPQ9Kh34403UjrVIXdf8bS7UIqj2RaIBdT7qC2o9wGgelHno7agzkco0XIBAIiqYTVdcsvt04Hnz2//T0OeKpGwUV9p0wfFNwF3/EDAGQAAAELGPOSgpKay49Ol/J1SQv2iZRW0fv16PfTQQ0HXd+nSRZ999hm9TKFaXXTRRZo+fbrfsnvvvVctW7ak5KuBbYLMzO+ECViNT5QVn0g5AzGCeh+1AfU+AFQ/6nzUBtT5CCUCzgAAUWX4sHaa8tF67/zqHfHavztTqfXTvcusxEay07pJWYuLFuyYKbvZmbJSfIbaBAAAAA6QFWd6Nmteqc+MGTNG6enp+uqrr7Rq1SplZGQoOztbDRs21BFHHKFhw4bp8ssvV2IiwSioGampqercubPTsxnDuFYfV1oT2XUbSgylCcQU6n3UNtT7AFA9qPNR21DnIxQsu2icB8SArKwsp9E6MzNTaWlp4c4OAFSLrK0Zuu6gi7RTCd5ll5/XUue+96JfOnvLp9LGd4oXJDSQdfjTHBUAAGqRnJwcZyi39u3bO8O4AQAAAAAAAACA6mlbr0xcUfGYYwAARMmwmke0zPdbNvXj35Sfk+OfsGFf//n8XbI3/acGcggAAAAAAAAAAAAAQOQi4AwAEHXO+eAJparQO7+mIFVfjrnRL42VWF9KP8b/gy5GmgYAAEDV2QX7RUfyAAAAAAAAAKIdAWcAgKhz8LFHqXuDfT5LLD3/1jq5C4uD0JylHW+UXElSYlPp8GdlHTSkxvMKAACA6GAX5kq5W6TsDbLzs2Tb7nBnCQAAAAAAAACqBQFnAICodObLd5RY4tJnl99UOuERz8vq/rishPSayhoAAACijNOrWe62P2cKpLztktt/mHcACMSdtc152XnZ9JAIAAAAAAAiBgFnAICodMSw02TJv1eJV19fUSqdxTCaAAAAOECWZUnx9YoXxKXKikuiXAGUyXYXStl7pP1ZsndulL0ngxIDAAAAAAARgYAzAEDU3vTr1SzHb5ltnh53M7QRAAAAqoHpMdeVLFnxUmIjihhA+XL3mS4SvbNWYiqlBgAAAAAAIgIBZwCAqHX1zMlKVKG6JmSotZaqqVboj5+XlfkZuzBP9urnZO+cXWP5BAAAQJT0cpbUREppKcuVEO7sAIgEpsdtT5CZK05KIuAMAAAAAABEhvhwZwAAgOrStGM7deuYo4xV27zLlnwxTW2O7hYw0Ey/3iHlbilakLVYatiHgwMAAIAKI9AMQGVYSanOyy4skAryZFk8GwwAAAAAACIDrRgAgKjW7fT+fvNLPp8aMJ0Vlyjlbi1eULhHdvYf1Z09AAAARCC7MFt2YW64swEgSlhx8U7gGQAAAAAAQKQg4AwAENW6DfYPOFszZ6H27dwdOHGdzv7zq5+txpwBAAAgYuXvlnI2yc7bKdt2hzs3AAAAAAAAAFCjCDgDAES1Tv16KyE5yTtf30rQD3c/GjjxwX/xn8/ZKHvPimrOIQAAACKJE2BWmGOmigLP8neFO0sAAAAAAAAAUKMIOAMARLXElGS1qN9Yf+hQbdBh+qWwo1565qeAaa3EdKnJKf4L1zxXMxkFAABAZPAEm3m4ksOZGwARyM7ZS++IAAAAAAAgohFwBgCIeoVWHdk+VV6u4pSXbW4UBtDqYv+bhvk7ZG+fXgO5BAAAQERwJUqJjaW4OpIVJ8WlhDtHACKInZcje/cW2RnrZO/dKdtdGO4sAQAAAAAAVBoBZwCAqHfN7FdKLXtv0AUB01oul9TqQv+Fmz6srqwBAAAgwliueFkJabKSm0kpbWRZsdW00q5dO1mWpdGjR4c7K4gxr776qnPumdfatWsVqez9u4sm3IVOwJl5B4DainofAIDYQJ2PcImWa/1YFVutogCAmNSobSu55PZb9sEPuUHTW01OkuLTixfk75Sd9Wt1ZhEAAAA+1q9fr+eee04jRozQIYccojp16ig5OVmtWrXSWWedpbffflsFBQU1XmZTpkzRaaedpubNmzv5ad++vS655BLNmTOH4xdhx840pof62K1YsUJPPvmkzj77bOfcSElJUWpqqjNtyuOzzz6TbfsMx1qO2bNnO3k0eTV5NnkfNGiQ810qypT1Cy+8oBNPPFFNmjRx8tSxY0ddffXVWrZsWRW/aXTbu3evfvjhBz322GMaPny4c/w8jd/mWBwIpzez3H3FC5LryIpPrDXnMBAusVx3RLr+/ft7fyPLe9Ukjh0A1E7U+dEhPz/fCRIaMmSI2rRpo6SkJDVu3Fjdu3fXFVdcoffee6/G8sK1Ptf6FcXvTzWxETMyMzNNq6bzDgCx5rUzrrQHa7DfK2PlmqDp3Zv+a7vnX1z8+uXGGs0vAACw7ezsbHvZsmXOO2LHnXfeaVuW5Vy/lvXq0aOHvW7duhrJkzkHzzjjjKB5cblc9r333mvHgrZt2zrfedSoUaXWxfKxu/TSS8v93uZ12mmn2bt27Sp3e/fcc4+Tt2DbGTp0aLm/jdu3b7ePPfbYoNtISkqyJ02aZEeKyZMne/O+Zk3wa7kD1b9//6BlZs7/A+UuLLDd+3bbhds32O6cfeWm5/cH0S6W645Ir/eNfv36Vaj+q6lbURw7AKi9qPMju873WLRokd2tW7cy6/z09PRqzy/X+lzrV0as/v5kV7FtvTJxRfRwBgCICRe+99SfdXSxJ469IvgHmg7yn8/bLrtwbzXlDgAAAB6bNm1yeoEyvZtcfPHFmjx5smbOnKn58+frjTfeUM+ePZ10Zn7gwIFOb0TVbcyYMfr000+d6QEDBujjjz/W3LlzNWnSJHXo0EFut1t33XWXXn755Zg+kLF87DZu3Oi8N2zYUFdeeaXeeustzZo1y9mX6WHM9NhjfPXVVxo6dKiz32BMXiZMmOCkMXk0eTXbMXk338H45JNPnCfHgyksLNQ555yjH3/80Zk301988YUz//TTT6tp06bKzc118mryhGK+vdA1aNBAp5xyiurWrRuyIrJccbJS0+Vq1EpWUmq56fn9QbSL5bojmvTo0UOLFy8u81UTOHYAUHtR50e+X375xfnbaMmSJUpMTNRVV13l/J1k/k779ttvnb+VRo4cqbS0tGrPC9f6XOtXBr8/1egAAuIQYejhDECsG5twsl8PZ0N0ul1YUBA0vXvJeP9ezlY+UaP5BQAg1tHDWWy69dZb7YcfftjOysoKuL6goMAePny494m/6u5hZNq0acW9Sp1xup2fn+e3PiMjw27Tpo2zvkGDBhXqvSpan3qu1cdu6FBn/9V17Ex5vPDCC3ZOTk7A9fv27bP79u3rzc/rr78eMJ3JQ/369Z00Jm8mj77MdzDfxbOd6dOnl9sb2LXXXltq/cqVK+20tDRnfadOnez8/Hy7tqupHs7McXzzzTedMip53oeih7Paeg4D4RLLdUc09XBm3sONYwcAtRt1fmTX+aaNrnPnzk6a5s2b24sXLw66rdzc3GrMKdf6XOtXXqz+/mTXQA9nBJzFEALOAMS6X6fPKjWs5ryXAt/oMdx71/gHnP16T43mFwCAWEfAGcoaKjAxMdFp/Dj88MOrtaAGDx7s7CcuLs5ev2Km7d631nbn7rDd7uLGoLffftvbUPTYY49F9YGr6DAbte3YbdiwIWCamjx2pkHes68zzzwzYJpHHnnEm8bkLRDzXcx3MmnM8AuBdO3a1dswaYLdAnnwwQe9+3r//fft2q6mAs4CCVfAWW07h4FwieW6I9wiKeCMYwcAkY86v/bW+ffdd5/375+pU6fa4VTb6nyu9SP3Wj/af3+yGVITAIDQ6XJiH8XJf+iax8a+HjS9VaedlHZ48YJ9K2XnbuOQAACAqDR69GhZlqV27dqVme7VV1910pnX2rVr/daZz5rlZlvGvHnzdOGFF6p169ZKTk523s26X3/99YDy2qhRIx1+eNHfab///nuFvo8Z8nDcuHHq3LmzUlNT1aRJEw0ePNgZZjAYM2zXd99950yfctIJatWyuWQXSgV7zF+L3nRmuELPkBEffvihDtS+fft07733qnv37s4QY+b79u3bV6+88ooz7Ni0adO8x8BM+w6jmJ6e7iy//fbbA277/vvv937WDO0YiBkSw5Nm6dKlCqWwHLtTTlGrVq0Cpgv1sStLt27d1Lhx4zK/uyl7w+TJ5C0Q813MsHLGN998U2p4uZUrV2rZsmXO9IgRI5wyC8Tz/7Tkd8/Pz9dBBx3kHIPTTz+93O9lhlPxnC8PPPCAqmrXrl0aP368unTpopSUFGfYT/M933vvvQp9vuTvz/LlyzV27FhneVJSkpo1a6Zhw4Zpzpw5qm7Reg4julDv157/d9Fc71cEv5kAULO/s8HE7LU+dX65zN8czz//vDPdv39/51UVkXzsysK1fnRc60f77091cVXblgEAqIWOauFf9e1RogoLCoJ/oEWJmzw7ZlZTzgAAAKKLuUl63HHHacqUKfrjjz+Um5vrvL/22ms66qij9M477xzQ9s32DJer/KaN+fPn6+ijj9aTTz7pBONkZ2dr+/btTgOQaQi68cYbA35u7ty53v2c2LdX8Yr4urKs4v0mJiaqd+/e3s+YgJ2q2rBhg4488khNmDDBCeTZv3+/du7cqf/9738aM2aMzjzzzKDbj4uLc25QG1OnTg2YxvdG9YwZM5yG42BpTHBU165dFWo1fez69esXdPuhPHYVkZeXF/S7m3UmD0afPn2cvAXj+U7mO5qbPb7McS2ZLhATVGYaRY2ZM4uvcxISEnTppZc6019//bXTgFre/3XP+Tdq1ChVhQmQO+yww/Twww9rxYoVysnJUUZGhtMIO3z4cOfcrwzTGHvMMcfo5Zdf1rp165yy3bZtmxNUYf6PHOjvT2VE2zkMxEq9X1P/72Kh3q+MSDp2ABCrqPNjr86fNWuW97rw/PPP9y4332HVqlXavHmz3G7/zh5irc7nWj86rvWj9ZqjOhFwBgCIKX+ZWfQUhq95Dz0S/AOpB0vJLYrnd8yQbVfuD2cAAIBY8/PPP+vqq692nlp85pln9OOPP2r69Om67bbbnKcPTcPKxRdf7A2uqSzTmOR5cto8IVkW0wBqGkQzMzOdJyp/+OEHJz9PP/20mjdv7qR56qmn9MQTT5T6rO/T2V26HyslNpZcSVJ80ROGvjz5KCgocBqaqsI0lJlGKdNga5jepT766COnEcs0npl1n376qe68886g2/A0Vv3000+ler4yjVOzZ8/2zpsyWbhwYdBGaLMt8+RmKIXl2JWzn1Acu4owZZ2VlRU0T2bfJg/B1vvyXV+yF4GqfHdz88P0sONxxRVXOO/mpsHrrwfvFdqcU//+97+d6VNPPVUtW7ZUZZnje9pppzk3KTy9sn3++efOef/WW2+pR48ezk2tiRMnVmh7v/zyiy666CLnKednn33WecrZnPd333230/uCufFy5ZVXOo3c1c33HL7t+qs07aO3NPur/zjnbSSew0BM1fs18P8umup909NEz549Va9ePee31vTUcNZZZzl1SEVvjkXSsQOAWEWdH5t1vm/PUebhKPM3nbmGM/V+p06d1KJFC6dnJ3MdaYKAYq3O51o/Oq71o/Wao9od4PCiiCCZmZnOGK/mHQBi2RANsgdrsPd1gQaWmd69+VPbPf/i4lfmkhrLKwAAsSw7O9tetmyZ847qN2rUKOeasW3btmWmmzx5spPOvNasWeO3znzWs85Mb968udTnv//+ezs+Pt5J06NHjyrl9eabb/bu59FHHy3z+5hXQkKCPX369FJpNm7caLdq1cpJk5qaam/dutVv/W233ebdxrx588rMk8mHJ+2XX35Zpe/1xBNPeLdx/fXXB0xjlnvSmNfUqVP91v/444/edV988YXfuhkzZjjL09LS7H79+gUsv507d9oul8tZ9/TTT5fav+cYm/Ktimg9dhVx3nnneffz3nvvlVpvjld5ZeNhvpMn7fjx4/3WjRgxwrsuIyOjzO1cd9113rTLly/3W3fiiSc6yzt16hT08x9++KH38++//75dFePGjfNu44EHHii1Pi8vzz711FP9zvuSvz0lf3+OOeYYe/fu3aXS/Pvf//amMf/fKsqz7fJ+H4Odw1P/845duHll0WvHHxF7DiO6UO+H//9dNNT7nu2W9eratavzN30w0VrvA0BtQZ0f/noj0uv80aNHe/c9ceJEb5tOoFf9+vUD1uXRXOdzrR+51/rR3l6VXcW29crEFcVXf0gbAAC1y2FpOVqSleqd36cEFebnKy4hIfAHGh0vbXzXPN9fNL/2ZenwJ2sotwAAoKLsrAzZe7aHvsCSUuVq3LbUYvf2dVLu/qKZxFS5mgRIs2ODlOP/5GlVWfUay0prokjx+OOPO0P2lTRgwACNHTtWzz33nPNUoxkO0PSIUVHmicF//vOfzrTpPePaa68t9zNXXXWVTjzxxFLLzVO4Jp/mKUvzdKIZ9uuWW27xrt+zZ493um7dumXuo06dOt7pkk8bV9QLL7zgzdejjz4aMI1ZboYQ2LRpU8D1ZmgB85Sxybt5ennQoEHedaa3GeOEE07Qscce68ybNDfffLM3jXkq0zMURv/+/RVK0XzsyvPBBx/o/fff9x6jc889t1SaUOU5VNsxT6eb88E8RWuGeTn++ONLfX7y5MneIVmGDh2qyjK9Hnm2cfjhhzu9IZVkhvicNGmSDj744Ar3kmOekk5PTy+1fOTIkbr11lud/z9mmJmbbrpJ1c08YX3icb2lgqLhVK2k1Ig8h2ujXeu3aff6yj293uSQVqrbxP/cKMjL14a5v1VqO8npddS8e7tSy7csW6/sncXHriJaHt1BianJinTU+7FZ75vhhk4++WSnZ5YjjjhCjRo1cvKyYMEC5/uZHhzMUErm7z/TG0qbNm1iot4HEFrb1m9TRiXr/IqoU7+O2nUrXZ+vXbJW+3YX9f5bJ72O2gWo89cvW689lazzg2nSpomatmmqSEGdH3t1vhn608NcQ5mepMx1lam3zbW96TH7+eefd86N3bt365xzztGiRYvK7AE7Wup8rvWj41o/lturDhQBZwCAmHPLotc1qv3V3vlCWVrw5tvqOfrSgOmthPqyExpI+TuKFuRvl529SVaKz1CbAAAg7AqXfKfCOSZIPLSstkcq8dy7Si0vmP6a7HU/F6VpdZgSh99XOk8z3pB79fyQ5COu93DFH3eBIkGDBg2cYZSCufzyy52AM+Pbb7+tcMDZ1q1bdd555zldyZvhH0yjTWpq8YMEwVx22WVB1w0bNkz169d3GkVNXnwbgXJycrzTiYmJZe7DDBnmkZ2drcrauHGjVqxY4UwPHz7cGQ4gELPcdNtvuuYPJC4uzgkM+vLLL73DZXh45k3jsmmENmbOnOk0FpvP+aYxN4y7deumUInmY1eRYcY83yMlJcUZXizQ8CWhynOotmOO1w033OCUr2koLhlwZo7pF1984UybofLK21cgZjiYXbt2OdOjRo1yAhcCMQ2+ZsjOzz77rNxtdu/e3WnQDsSU+1FHHeU0Qq9evVo1wfzeuRq3kV2YL+VlSwkpEXcO11ZzX/lW39zzdqU+c9FbN+uoC4uGI/LYv2OP/nXC+Ept5+B+3XTttAdLLf98/Gta9knlho28dflzanpIK0Uy6v3YrffNjXHzO1aSueFtbtSZhwxMnW/qjBtvvNFJH+31PoDQ++aVb/TWPW+FfLtHn3q07vuq9HX8pL9N0oKvFzjT3ft110PTHiqVZvL4yZpbyTo/mJETRuqiuy9SJKDOj806f9++ogBMTyCRCY7zDWbr0KGDs6xhw4b6+9//rh07dujBBx90hj2M5jqfa/3ouNaP5faqUAh8ZAEAiGKN27VWqgr9lr16zRtlfyilxBOYvxdFugMAAKA008gTHx/8GbcjjzzS26iyZMmSChWheQJwyJAh+uOPP5z5Bx54QCeddFK5nzP7CdYg5Xmi0uQ3UF58G3by8op6JwrGNLp6mKAij23btjnbDfRas2aNN53vvs2Ty2Xp0aNHmev79evnbeDzPAFpnhadNWuWXyO0yWdmZqYWLlzo/aynEdo8pRkoKKoqwnHsfBvxq/vYlcU0dp5++ulOGZjyNE/vdu3aNWDaUOQ5lNsx8+YpYePdd9/1u8lgvPHGG06DrCeoquRNlWBlZ9Z5LF682DtdXuBpr169VBFdunQpc725CVLyqeLq4nsOW3EJslLSZMUn1Ng5DNSUaKn3a7LuiJZ6P1CwmW9Zv/zyy97f5Y8++sivDqhtxw4AUD7q/Nis833rWRMgFKz3KBNU07x5c2d6ypQpsm0zKl/tq/O51udaP9KvOWoTAs4AADGpb+9mfvPrchKUs9f/BoqftmP853O3yC74cwgtAAAA+GnatOzhQMxNaU/Qh+/QDMGYp/9Mj2mmUdUYN26cxo+vWG80Zj9l3QQ3mjVrFjAv9VJdFe663jcYx7dL/IkTJzpPYQZ6+T4N6XnysyLl16RJ2UOreobHMMFA5qlmwwxjZbryT0tLcxq9TONYnz59/BqezZOXv/zyi19D9oEK27GrV6/Gjl0wJk/mSd21a9c68+ZJ9QsvvDBo+lDkOZTbMUzPNJ5GWDNUiC/P8BgmUMyUia877rgjaNmZdVU57z3HujzlPYnsebLaPO1f3cJ9DgM1JWrq/RqsO6K13i/JHIsxY8aUGvKrNh47AED5qPNjs873rWdPOeUUb69pJZl63BOsY3o5C/agVrjrfK71udaP9GuO2oQhNQEAMWn0h4/q6xbFf/TbsvTZ2Jt17ttFQzuVZCWmy05pJ2Wv9X5CGV9Lzc+uoRwDAIDyxHU7Wa62R4S+oJICBy/E9xsl5Z5fNJMYOE3cCZcoruewkGTDqtdYkaIiT8sGe9K1JNOQaoadmDp1qjN/xRVX6PHHH6/2vNiFuWrVvLjMN6xZUebTxhs2bPBOt27dWuFk8mkaokzDlWlgHjRokPcGrxniytM4bBqrv//+eyeNGQ7jhx9+kNvt9q47UOE6dp6nrj3Mk6o1fexMgJYp96VLlzrz9913n/7yl7+U+ZmSeS5LWXkuuZ3GjRuXux1T1r6f8+2VyDyFbxpgTYDZpZde6iz/8ccftWzZsoC9m1WG7/Er73hX9DejNonkczgS9Lp8oDoPrFy93yTA0JWpjerpuhmlh8oqS3J6nYDLBz80SgNuPadS26rfOnLq92iu9yP5/11tqfeD8e3Zs6wezmLx2AGomFMuP0VHDjwy5MVVp37g+nzM42N0we4LitIEqfMve+gynXfreSHJR5M2ZQcZ1SbU+bFZ5/vWl4GuG4OlNT2JHXzwwVFV53OtHx3X+lxzhA4BZwCAmJTevKkaufK1w108nMnkKWt17ttlfKjz36Vl46X8P6PRt3wuu8lAWfG1M6ocAIBYY6U1cV41xdW4bflpGkXOTSxPrz+eRshgSg6rF8jWrVvLbdjxPOXr6fEkEJOXSy65RJ988okzP2LECL3wwguqDPNUrenJKNgTuJ5G0FJ5KchS1y4dvbPLV3kePAhs+fLlzrt5wrFjx+LP3X333c6rPA0aNCiVn2AyMjLKXG/ycNxxx+nrr7/2PtHsefdtXPZMz5gxwykjTxqTl5I9VlVWWI9diZvbnmNTXceupOzsbA0dOlTz5s3zDivyj3/8o9zPde7c2fmu5jtXNM/GoYceWuZ3N0Fj5W3HNL7XqRP4ZpoJ9jABZ+ZGxurVq50bBp7ezcyQDoF6bXv11VedV3l8j5v53TBlEEx5/y9qo3Cfw9GuQZumzutAxScmqH3fw0KSp4O6tlGkoN4Pb90RbfV+KG4i8psJIJimbZo6r5rSrlu7ctO0oc6P3Gt96nxV1mGHFf+tXF5P0b7rg/UAFSnHriSu9aPjWj8afn9qE4bUBADErAv/MdRv3pZLWxfMD5reik+RWvj0UOLOljb8W7Zd9k1ZAACASODp0t0MtVCWFStWlLutn3/+2WloDmbRokXKy8tzprt16xY03VVXXaUpU6Y402eccYbeeOMN7w3yijL7MfsLxuTT5LdUXuLT1LNXH2c4CuOHH2aWuY85c+Z4hxf0fKaqDbjz5wf/m7Qi632HyTCBQqbBf9asWaVuPB977LFOwFBWVpYWLlzovfF84oknVrqca9WxK3Ecyhq+KxTHzld+fr7OPfdc7z6vvvpqPfLIIxX6rNl3r169nOnZs2d7/48E4tl+UlJSqSe6+/btWypdIFu2bNFvv/3mTB9//PFB040cOdIZptIEDLz22mtOI7vn2J5zzjlKT09XVfkGOHgC9IIpb31tZI7hz7Ony87LDhhwURvPYcQO6v3w/r+Ltnq/LJ4eMY0WLVpEVb0PAJGAOp86/0DrfPM5j99//73MtL7rW7ZsGTV1Ptf60XOtH6vtVdWFgDMAQMw65Y6rSi37R89byv5Qo75SUtG4246d/5NWPiK7MPjNIAAAgEjQvn177/AAwYLKTGPHBx98UO62du7c6X1SMJBXXnnFOz1w4MCAacaNG6eXX37ZmT755JP1/vvvKyGhuHfayjBBMsF89NFH3iewffNixSUprUkHnXzSAGf+22+/DTrM4YcffujcvDWGDavaEKpmWAjPE5/vvfeecnJyAqYzy8368nhuMJtGrieffNLpmS4tLU1HHXWUN41prOrTp48z/fHHH3sbyzw3rasq3MfOc1PF7Lsmjp2HebrVBGd98cUXzrx5YnbixImV2sbZZ5/tvJs8mbwFYr6L+U6G+Y6eG0ge5jzy9Hr27rvvav/+/QG34/tUclnf3Zw3Zng7z/EwxzMzM9OZHzNmjA6EGa7T08uPaeQN1guOGYLN9NwTiV579TXZOzdK+4rO1dp8DiO2UO+H9/9dNNX7ZTH58f27z/eGdaTX+wAQKajzqfMPtM4355Dnb4qvvvoq6DWmaU/65ptvnOkOHTqoefPmUVHnc60fPdf6sdpeVa1sxIzMzEzzP9l5BwAUuUgn2YM12PsaqkF2zr79ZRaPO/MX2z3/Uts9/+Li10+X2+7cPRQrAAAhlJ2dbS9btsx5R/VbsGCBc81oXmPHji213u1221dffbU3jXmtWbPGL03btm2969q1a2dv2bKl1HamTZtmx8fHO2mOOeaYgHmZMGGCdzvHHXecvXfv3kp/n1GjRnm3kZCQYM+YMaNUms2bN9tt2rRx0qSmptpbt24tlea7777zbufMM8+0CwoK/NZnZGR4t1G/fn17586ddlU9/vjj3n1df/31AdOY5b7HYOrUqQHT5eXlOd/JpElPT3fehwwZUirdvffe65fGvMy5EIznGJvyDSRWj535/3HZZZd593fuueeW2l9F7Nixw3ssTFlv377db73Z5tChQ737+f777wNuZ9KkSd401113Xan1q1atstPS0pz1HTp0sPPz88vM18yZM73bO+igg5z39u3bO9/7QI0bN8677YcffrjUepO3008/vczfnoqcmyXPL5O+ojzbruhnSp7D0z9+23bnZtfqcxixh3o//P/vIr3eN3XQrl27gn7W5Mn399DUX9FS7wNAJKHOD3+9Eel1vvHOO+94t2PahgIZM2aMN82jjz4aFXU+1/rRc60fi+1V2VVsW69MXBEBZzGEgDMAKO2Pxcv9As6G6HT74zMvLLeo3Dvn2e75l/gHnc0fZbtztlHMAACECAFnNa93797eBg/TiGJuJP7000/2lClT7P79+zvL+/TpU27A2RFHHOE0vLRs2dJ+9tln7blz5zqNMLfffrudnJzspDFBZ3PmzCmVh6efftq7ffN5E+iyePHiMl+mwTVYI1CTJk2cfJn9mv2bfJj8mHy1aNHCuy/TABzMBRdc4E03YMAA+z//+Y89b948+5VXXnGCdTzrnn/++QMq/9zcXLtbt27e7Q0ePNjZlzkG5t00IpvlvXr18qYxAXzBDBw40K/hLlCD7w8//OCXxjRkFRYWBt1mWQ19sXzsfBtSzTE0x6y87x6MyYtnWyaPJq8mzybv5jt41l14YfDrFtNYefzxx/sFwH355Zf2jz/+aD/zzDN206ZNneUul8v+/PPPK/QdDz30UL9zxdzACIXdu3fbrVq18vteX3zxhVOGb7/9tt2zZ09nuee9uhuhV65caU+ePNnv1ahRI+cz5r3kOtOYHGwfTRo3stu2amknJyfZ48ePr9XnMGIT9X5g1PsV+201y+rWrWuPHDnSfvHFF+3p06fbCxcudH7r/vnPf/rVG6beWb16dcDyjsR6HwAiDXV+YNT5lbueMm0UnrrUtE+YetYEsX388cf2oEGDvOuOOuqogAEukVjnc60fHdf6sdpelU3AGUKJgDMACOzu+n39gs5GWyfbO37/vdzicv8+sUTA2aW2OyeDYgYAIEQIOKt5v/76qzcQJdDLNLSZAIvyAs5MA8xLL73k7cms5CsxMdFpXAqkX79+Qfcf7BWoQcq3ock02DRu3Djo52+44YYyy2X//v1+DaslXyZoxzwpGQrr1q3za1gq+Tr11FOdBjrPfKCgPY/77rvP77OmHAIFuaWkpJTb+0hFGvpi+dj59u5X0VdZ7rrrLtuyrKCfNd+pvCdUzROxvg23gf4fmgCBinrsscf8ym39+vV2qCxZssTbc1qgl+k9rqzfnlAGnPnupyKvQD0P+O5j7pzZEXEOIzZR7wdGvV/xgLOK/E52797dXrp0adDzMBLrfQCINNT5gVHnV+56as+ePU6bRFn1vrkGDfRQTqTW+VzrR8e1fqy2V2XXQMCZq3oH7AQAoPYb/d1E1VOBd36bnaT3Th9T7uesg6+RGg8oXtBlgqykxtWVTQAAgGrXpUsXLViwQNdcc43atm2rxMRENWnSRIMGDdJnn32mxx9/vMLbuuKKKzRjxgwNHz5cLVq0cLbVsmVLXXrppVq4cKEuuOAC1ZQePXo43+uGG25Qhw4dlJycrEaNGjnf6/PPP9dTTz3lpLPzM2Xn75Ftu/0+n5KS4nz/N998U6eccoqaNm3qfJ/WrVtr5MiRmjlzpu6+++6Q5LVNmzZatGiR7rnnHnXr1s3Zd/369dW7d29NnDhRX3zxhXJycrzp09PTg26rf//+fumOOuqoUmnM9zjuuOO88/369VNtUtFjF0xNHrtQMsff5M3k0eTV5Nnk3XyHt956y/lOpizK0rhxY82aNcs5b/r27euUm/nMwQcfrLFjxzrlat4r6pJLLvFOm3yYfIXKYYcdpqVLl+rWW29Vp06dlJSU5OR/wIABzvd95ZVXFKl6Hts7Js9hRIZYr/eDod6vmNtuu01PPvmkc8zN3yzNmjVTQkKC6tat65T7iBEj9N577znHv2vXrlF37AAgklDnB0adXzmmjv/qq6/09ttvO3XzQQcd5NT95u9HU++a67bZs2c7y8sTq3U+1/rRc60fq+dwSZaJOiu1FFEpKyvLaWDOzMxUWlpauLMDALXKs4efpS8WFwedpahQD396vToMOaPcz9qbP5FSWsmqX/oGHgAAqDoTVLNmzRq1b9++3MAK1A7t2rXTunXrNGrUKL366qthzcvo0aP12muvOTfQ165dW2562y6UsjdIJtjMipMSGspKqKfa6P7779edd96p+Ph47dmzJ+r+f1T22KFmfPfddxo4cKAz/c477zgBBgiMcxixIpLr/UhCvQ8ACDfq/JpBnY9w4Fo/eq85cqrYtl6ZuCJ6OAMAwPyR8P1ktbD2e8siW3GacMaTFSobq/lQgs0AAAAiXcGeomAzwwSfWZZqI/PcoAn2MY488sioCzZD7eV58tg8sXvWWWeFOzsAEBOo9wEAiA3U+QgXrvVxIAg4AwDAdAXcuKH6DGrnVxa7lKzcd+6qcvnYhYWULQAAQCQxPZs57/FSXJ2wZME8IVlQUNzzbkl33XWXlixZ4kybHmWAmjovzbBoxmWXXeYMeYnA7MLg/38BINDvK/U+AADRjzoftRHX+jhQ8Qe8BQAAosQ5Lz+kD1pe7rfsm2e+1Rkj7q30tuzVz0m7ZsluM0ZWk/4hzCUAAACqg5VQX3Z8mlSw18zJClMPZ2ZIssmTJ2vkyJE6/vjj1aJFC+Xn5+vXX391uu2fNm2ak65r164aO3ZsWPKI2LBx40bt37/fGX5h/PjxznloetS78cYbw521Ws3O2iY7x/yOAED5qPcBAIgN1PmoLbjWRygRcAYAwJ/qt2gml9xy+3QA+tr/6urU7P1KTEmtUDnZ2dukZbdK+rN3sw2vSQScAQAARATLckkJaeHOhtavX6+HHnoo6PouXbros88+o5cpVKuLLrpI06dP91t27733qmXLlpR8EHZBnpS7v3h4Xje9XgMoH/U+AACxgToftQHX+gglAs4AAPAxtG9T/Wfmdllyq0vCDu1371BO1r4KB5wpqbG5zVA8bxfIXjdJVtsxlDMAAADKNWbMGKWnp+urr77SqlWrlJGRoezsbDVs2FBHHHGEhg0bpssvv1yJiYmUJmpEamqqOnfu7PRsxjCu5cjO8p93FT/MBACBUO8DABAbqPNR23Ctj1CwbNv2uSuOaJaVleU0WmdmZiotLfxPbANAbZSzd59ubdZDefuzvcvOf/JOnXxjxQPG7C2fSxvfLl5gJUhHPi/LxU1BAAAqVS/n5DhDubVv394Zxg0AgNrMNj2aZe+RvT/TCTZzNWod7iwBAAAAAIAYlFPFtvXKxBXxmB0AAD6S69bRUecM8iuTuW/+p1JlZB00WIr3qYDtfGnZ32W7CyhrAACAWsIu2Cs7Z4vsgn3iWTwAoWC54mTVqS+rcRtZ9ZtTqAAAAAAAIGoRcAYAQAnHXjLMb37d/F+UtTWjcuXU6Tb/+dyt0q93yna7KW8AAIDaoGCPVLi/6O+0nD8IOgMQMpZlyYqLp0Q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      "text/plain": [
       "<Figure size 2500x1400 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.rc('font', size=20) \n",
    "plt.figure(figsize=(25,14))\n",
    "for scenario in regional_volume_filled.scenario.values:\n",
    "    regional_volume_filled_scenario = regional_volume_filled.sel(scenario=scenario)\n",
    "    plt.plot(regional_volume_filled_scenario.time,\n",
    "             regional_volume_filled_scenario.values/1e9,\n",
    "             label=scenario, \n",
    "            color=get_scenario_style(scenario)['color'],\n",
    "            ls=get_scenario_style(scenario)['linestyle'],\n",
    "            lw= get_scenario_style(scenario)['linewidth']+1)\n",
    "plt.legend(ncol=3)\n",
    "plt.ylabel('Volume (km³)')\n",
    "plt.tight_layout()\n",
    "plt.savefig('test_rgi06_filled_opt.png')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 73,
   "id": "1e1b90fd-5ca5-45e4-86de-347af7b12171",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x7f453e91ff90>"
      ]
     },
     "execution_count": 73,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1200x1000 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure(figsize=(12,10))\n",
    "for scenario in regional_volume_filled.scenario.values:\n",
    "    regional_volume_filled_scenario = regional_volume_filled.sel(scenario=scenario)\n",
    "    plt.plot(regional_volume_filled_scenario.time,\n",
    "             100*regional_volume_filled_scenario.values/regional_volume_filled_scenario.values[0],\n",
    "             label=scenario, \n",
    "            color=get_scenario_style(scenario)['color'],\n",
    "            ls=get_scenario_style(scenario)['linestyle'],\n",
    "            lw= get_scenario_style(scenario)['linewidth']+1)\n",
    "plt.legend(ncol=3)\n",
    "plt.ylabel('Volume (%, rel. to 1975)')\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "id": "b7bfc28e-524c-428b-95cf-e6ab3b3d5372",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x7f4551e878d0>"
      ]
     },
     "execution_count": 41,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "for scenario in regional_volume_filled.scenario.values:\n",
    "    regional_volume_filled_scenario = regional_volume_filled.sel(scenario=scenario)\n",
    "    plt.plot(regional_volume_filled_scenario.time,\n",
    "             100*regional_volume_filled_scenario.values/regional_volume_filled_scenario.values[0],\n",
    "             label=scenario, \n",
    "            color=get_scenario_style(scenario)['color'],\n",
    "            ls=get_scenario_style(scenario)['linestyle'],\n",
    "            lw= get_scenario_style(scenario)['linewidth']+1)\n",
    "plt.legend()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "15aa93f9-054c-409e-8766-a845335ed0d4",
   "metadata": {},
   "outputs": [],
   "source": [
    "p = '/home/www/lschuster/terrafirma_oggm_proj/output_dir/RGI06/'    \n",
    "\n",
    "plt.rcParams[\"font.size\"] = 22\n",
    "fig, axes = plt.subplots(4, 5, figsize=(30,35))\n",
    "axes = axes.flatten()\n",
    "fig.delaxes(axes[-1])\n",
    "\n",
    "for j,gdir in enumerate(gdirs):\n",
    "    try:\n",
    "        #ds_spinup_hist = xr.open_dataset(gdir.get_filepath('model_diagnostics',\n",
    "                                                           filesuffix='_spinup_historical')).volume_m3/1e9\n",
    "        rgi_id = gdir.rgi_id\n",
    "        ax = axes[j]\n",
    "        ax.set_title(rgi_id)\n",
    "        ax.plot(ds_spinup_hist.time, ds_spinup_hist.values, label='spinup historical',\n",
    "                color='grey', lw=5, alpha=0.7)\n",
    "    \n",
    "        for scenario in SCENARIO_PARENTS.keys():\n",
    "            _d = xr.open_dataset(f'{p}run_terrafirma_UKESM1-2-LL_esm_{scenario}_bc_1975_2014_to_0_40_sim_year_starting_at_1979_glacier_state_from_0_sim_year_climate_Batch_0_1000.nc')\n",
    "\n",
    "            ax.plot(_test.time, _test.values, label=scenario, \n",
    "                    color=get_scenario_style(scenario)['color'],\n",
    "                    ls=get_scenario_style(scenario)['linestyle'],\n",
    "                    lw= get_scenario_style(scenario)['linewidth']+1)\n",
    "            # we started with the glacier state fro 1979, but in year 1975, \n",
    "            #so the 1975 volume should be similar to the 1979 historical spinup volume\n",
    "            try:\n",
    "                np.testing.assert_allclose(_test.sel(time=1975), ds_spinup_hist.sel(time=1979), rtol = 0.01)\n",
    "            except:\n",
    "                print(gdir.rgi_id, (_test.sel(time=1975).values/ds_spinup_hist.sel(time=1979).values).round(2),\n",
    "                     (_test.sel(time=1979).values/ds_spinup_hist.sel(time=1979).values).round(2))\n",
    "        # secondary x-axis \n",
    "        t0 = _test.time.values[0]          # simulation start\n",
    "    \n",
    "        def to_sim_year(t):\n",
    "            return t -t0\n",
    "    \n",
    "        def to_calendar_year(sim):\n",
    "            return sim + t0\n",
    "    \n",
    "        secax = ax.secondary_xaxis('top', functions=(to_sim_year, to_calendar_year))\n",
    "        if j == 0:\n",
    "            secax.set_xlabel(\"Simulation year\")\n",
    "            ax.set_xlabel('Calendar year starting in 1975\\n(assuming 0–40 is similar to 1975–2024)')\n",
    "            ax.set_ylabel('Volume (km³)')\n",
    "    except:\n",
    "        print(gdir.rgi_id, 'failed')\n",
    "#plt.tight_layout()\n",
    "axes[-5].legend(loc='upper left', bbox_to_anchor=(0.1,-0.1), ncol=4)\n",
    "\n",
    "plt.savefig('00b_test_projections_w_largest_glacier_of_each_region_new_oggm_commit.png')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
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   "cell_type": "code",
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   "cell_type": "code",
   "execution_count": 49,
   "id": "700105ac-fa8a-4e0b-92c7-5390b087fd14",
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       "  margin-bottom: 4px;\n",
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       "\n",
       ".xr-header > div,\n",
       ".xr-header > ul {\n",
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       "  padding-right: 0.3em;\n",
       "}\n",
       "\n",
       ".xr-group-name,\n",
       ".xr-obj-type {\n",
       "  color: var(--xr-font-color2);\n",
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       "\n",
       ".xr-sections {\n",
       "  padding-left: 0 !important;\n",
       "  display: grid;\n",
       "  grid-template-columns: 150px auto auto 1fr 0 20px 0 20px;\n",
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       "  margin: 0;\n",
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       "\n",
       ".xr-section-item input + label {\n",
       "  color: var(--xr-disabled-color);\n",
       "  border: 2px solid transparent !important;\n",
       "}\n",
       "\n",
       ".xr-section-item input:enabled + label {\n",
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       ".xr-section-item input:focus + label {\n",
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       "\n",
       ".xr-section-item input:enabled + label:hover {\n",
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       "\n",
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       ".xr-section-summary-in:disabled + label {\n",
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       ".xr-section-summary-in + label:before {\n",
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       "\n",
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       "\n",
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       "\n",
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       ".xr-array-preview,\n",
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       "\n",
       ".xr-var-item > .xr-var-name:hover span {\n",
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       ".xr-var-dtype {\n",
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       ".xr-var-preview {\n",
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       ".xr-var-name,\n",
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       "  padding-bottom: 20px !important;\n",
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       ".xr-var-attrs-in + label,\n",
       ".xr-var-data-in + label,\n",
       ".xr-index-data-in + label {\n",
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       ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
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       ".xr-var-data > table {\n",
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       "\n",
       ".xr-var-data > pre,\n",
       ".xr-index-data > pre,\n",
       ".xr-var-data > table > tbody > tr {\n",
       "  background-color: transparent !important;\n",
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       "\n",
       ".xr-var-name span,\n",
       ".xr-var-data,\n",
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       ".xr-var-attrs,\n",
       ".xr-var-data,\n",
       ".xr-index-data {\n",
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       "  grid-template-columns: 125px auto;\n",
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       "\n",
       ".xr-attrs dt,\n",
       ".xr-attrs dd {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  float: left;\n",
       "  padding-right: 10px;\n",
       "  width: auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt {\n",
       "  font-weight: normal;\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-attrs dt:hover span {\n",
       "  display: inline-block;\n",
       "  background: var(--xr-background-color);\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-attrs dd {\n",
       "  grid-column: 2;\n",
       "  white-space: pre-wrap;\n",
       "  word-break: break-all;\n",
       "}\n",
       "\n",
       ".xr-icon-database,\n",
       ".xr-icon-file-text2,\n",
       ".xr-no-icon {\n",
       "  display: inline-block;\n",
       "  vertical-align: middle;\n",
       "  width: 1em;\n",
       "  height: 1.5em !important;\n",
       "  stroke-width: 0;\n",
       "  stroke: currentColor;\n",
       "  fill: currentColor;\n",
       "}\n",
       "\n",
       ".xr-var-attrs-in:checked + label > .xr-icon-file-text2,\n",
       ".xr-var-data-in:checked + label > .xr-icon-database,\n",
       ".xr-index-data-in:checked + label > .xr-icon-database {\n",
       "  color: var(--xr-font-color0);\n",
       "  filter: drop-shadow(1px 1px 5px var(--xr-font-color2));\n",
       "  stroke-width: 0.8px;\n",
       "}\n",
       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt; Size: 8MB\n",
       "Dimensions:            (time: 609, rgi_id: 568)\n",
       "Coordinates:\n",
       "  * time               (time) float64 5kB 1.975e+03 1.976e+03 ... 2.583e+03\n",
       "  * rgi_id             (rgi_id) &lt;U14 32kB &#x27;RGI60-06.00001&#x27; ... &#x27;RGI60-06.00568&#x27;\n",
       "    hydro_year         (time) int64 5kB ...\n",
       "    hydro_month        (time) int64 5kB ...\n",
       "    calendar_year      (time) int64 5kB ...\n",
       "    calendar_month     (time) int64 5kB ...\n",
       "Data variables:\n",
       "    volume             (time, rgi_id) float32 1MB 2.274e+08 5.256e+07 ... 0.0\n",
       "    volume_bsl         (time, rgi_id) float32 1MB 0.0 0.0 0.0 ... 0.0 0.0 0.0\n",
       "    area               (time, rgi_id) float32 1MB 4.731e+06 1.421e+06 ... 0.0\n",
       "    length             (time, rgi_id) float32 1MB 2.87e+03 1.334e+03 ... 0.0 0.0\n",
       "    calving            (time, rgi_id) float32 1MB 0.0 0.0 0.0 ... 0.0 0.0 0.0\n",
       "    calving_rate       (time, rgi_id) float32 1MB 0.0 0.0 0.0 ... 0.0 0.0 0.0\n",
       "    water_level        (rgi_id) float32 2kB 0.0 0.0 0.0 0.0 ... 0.0 0.0 0.0 0.0\n",
       "    glen_a             (rgi_id) float32 2kB 6.458e-24 6.458e-24 ... 6.458e-24\n",
       "    fs                 (rgi_id) float32 2kB 0.0 0.0 0.0 0.0 ... 0.0 0.0 0.0 0.0\n",
       "    is_partial_output  (rgi_id) float32 2kB 0.0 0.0 0.0 0.0 ... 0.0 0.0 0.0 0.0\n",
       "    error_during_run   (rgi_id) object 5kB &#x27;&#x27; &#x27;&#x27; &#x27;&#x27; &#x27;&#x27; &#x27;&#x27; &#x27;&#x27; ... &#x27;&#x27; &#x27;&#x27; &#x27;&#x27; &#x27;&#x27; &#x27;&#x27;\n",
       "    scenario           (rgi_id) object 5kB &#x27;up2p0-gwl1p5&#x27; ... &#x27;up2p0-gwl1p5&#x27;\n",
       "Attributes:\n",
       "    description:    OGGM model output\n",
       "    oggm_version:   0.1.dev1472+g8adcdb863\n",
       "    calendar:       365-day no leap\n",
       "    creation_date:  2026-06-24 17:17:31</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-4229db29-e549-4da2-8292-e93eb1d97903' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-4229db29-e549-4da2-8292-e93eb1d97903' 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>: 609</li><li><span class='xr-has-index'>rgi_id</span>: 568</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-3569494e-48b3-4835-8c63-eae5f40d04cc' class='xr-section-summary-in' type='checkbox'  checked><label for='section-3569494e-48b3-4835-8c63-eae5f40d04cc' class='xr-section-summary' >Coordinates: <span>(6)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>1.975e+03 1.976e+03 ... 2.583e+03</div><input id='attrs-20251bef-414f-4ef5-8945-c4592f8d6288' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-20251bef-414f-4ef5-8945-c4592f8d6288' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3ab4b701-ad66-455c-867c-9033ef4cc32f' class='xr-var-data-in' type='checkbox'><label for='data-3ab4b701-ad66-455c-867c-9033ef4cc32f' 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([1975., 1976., 1977., ..., 2581., 2582., 2583.])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>rgi_id</span></div><div class='xr-var-dims'>(rgi_id)</div><div class='xr-var-dtype'>&lt;U14</div><div class='xr-var-preview xr-preview'>&#x27;RGI60-06.00001&#x27; ... &#x27;RGI60-06.0...</div><input id='attrs-5a7636ab-c659-4cbc-8643-2fc8b3064437' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-5a7636ab-c659-4cbc-8643-2fc8b3064437' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-157961f1-1930-463e-8ea2-6b74eb6845f0' class='xr-var-data-in' type='checkbox'><label for='data-157961f1-1930-463e-8ea2-6b74eb6845f0' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>description :</span></dt><dd>RGI glacier identifier</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;RGI60-06.00001&#x27;, &#x27;RGI60-06.00002&#x27;, &#x27;RGI60-06.00003&#x27;, ...,\n",
       "       &#x27;RGI60-06.00566&#x27;, &#x27;RGI60-06.00567&#x27;, &#x27;RGI60-06.00568&#x27;], dtype=&#x27;&lt;U14&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>hydro_year</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-2c0a06a1-0f9a-4fad-bd25-748a28fc81ae' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-2c0a06a1-0f9a-4fad-bd25-748a28fc81ae' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7fe54227-d636-4460-88e7-93f17349f24d' class='xr-var-data-in' type='checkbox'><label for='data-7fe54227-d636-4460-88e7-93f17349f24d' 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>[609 values with dtype=int64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>hydro_month</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-85470dc0-4559-49f9-877c-0335dc4e1028' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-85470dc0-4559-49f9-877c-0335dc4e1028' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-4a858867-ef84-4383-84a2-a71f3e8215cb' class='xr-var-data-in' type='checkbox'><label for='data-4a858867-ef84-4383-84a2-a71f3e8215cb' 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>[609 values with dtype=int64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>calendar_year</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-107f8961-d808-4f01-8c26-ed8adf90cd3e' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-107f8961-d808-4f01-8c26-ed8adf90cd3e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d1da3816-c0fb-4d3f-aa24-e8f2d574237a' class='xr-var-data-in' type='checkbox'><label for='data-d1da3816-c0fb-4d3f-aa24-e8f2d574237a' 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>[609 values with dtype=int64]</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>calendar_month</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>int64</div><div class='xr-var-preview xr-preview'>...</div><input id='attrs-bdc93a8e-9ae6-4c0f-8855-d46d3908bd43' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-bdc93a8e-9ae6-4c0f-8855-d46d3908bd43' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f257ee3a-8e22-475f-9456-abd1a4c4c6f6' class='xr-var-data-in' type='checkbox'><label for='data-f257ee3a-8e22-475f-9456-abd1a4c4c6f6' 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>[609 values with dtype=int64]</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-07bb4a67-57b5-41b0-8ff1-2d29a8f45ee7' class='xr-section-summary-in' type='checkbox'  checked><label for='section-07bb4a67-57b5-41b0-8ff1-2d29a8f45ee7' class='xr-section-summary' >Data variables: <span>(12)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>volume</span></div><div class='xr-var-dims'>(time, rgi_id)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>2.274e+08 5.256e+07 ... 0.0 0.0</div><input id='attrs-984116a0-2956-4b95-9e76-87d1f08c5a26' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-984116a0-2956-4b95-9e76-87d1f08c5a26' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-db6e4a13-9268-4f31-afe0-d1a4eee1ceaa' class='xr-var-data-in' type='checkbox'><label for='data-db6e4a13-9268-4f31-afe0-d1a4eee1ceaa' 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([[2.27441056e+08, 5.25591560e+07, 1.02294890e+07, ...,\n",
       "        2.13339040e+08, 1.26016734e+05, 3.42942048e+08],\n",
       "       [2.35308944e+08, 5.67420680e+07, 1.17437380e+07, ...,\n",
       "        2.14722304e+08, 5.32922375e+05, 3.48559136e+08],\n",
       "       [2.40619344e+08, 5.93212400e+07, 1.27141890e+07, ...,\n",
       "        2.13957584e+08, 7.22138125e+05, 3.51651552e+08],\n",
       "       ...,\n",
       "       [5.41821760e+07, 2.50264300e+06, 4.66439650e+06, ...,\n",
       "        0.00000000e+00, 0.00000000e+00, 0.00000000e+00],\n",
       "       [5.32341920e+07, 2.26373075e+06, 4.48311450e+06, ...,\n",
       "        0.00000000e+00, 0.00000000e+00, 0.00000000e+00],\n",
       "       [5.10353400e+07, 2.06178100e+06, 4.11159875e+06, ...,\n",
       "        0.00000000e+00, 0.00000000e+00, 0.00000000e+00]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>volume_bsl</span></div><div class='xr-var-dims'>(time, rgi_id)</div><div class='xr-var-dtype'>float32</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-a21c24ca-95f1-441d-b5db-dde57dd5c8a2' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a21c24ca-95f1-441d-b5db-dde57dd5c8a2' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5b1be74c-87cb-4142-8e6c-1ba368f4db56' class='xr-var-data-in' type='checkbox'><label for='data-5b1be74c-87cb-4142-8e6c-1ba368f4db56' 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.],\n",
       "       [0., 0., 0., ..., 0., 0., 0.],\n",
       "       [0., 0., 0., ..., 0., 0., 0.],\n",
       "       ...,\n",
       "       [0., 0., 0., ..., 0., 0., 0.],\n",
       "       [0., 0., 0., ..., 0., 0., 0.],\n",
       "       [0., 0., 0., ..., 0., 0., 0.]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>area</span></div><div class='xr-var-dims'>(time, rgi_id)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>4.731e+06 1.421e+06 ... 0.0 0.0</div><input id='attrs-047aaba3-1b55-4a4a-898a-eb5a13c5b316' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-047aaba3-1b55-4a4a-898a-eb5a13c5b316' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-85264356-0e29-40f2-a0ee-61ab39134634' class='xr-var-data-in' type='checkbox'><label for='data-85264356-0e29-40f2-a0ee-61ab39134634' 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([[4731448.   , 1421289.4  ,  378537.5  , ..., 2856470.8  ,\n",
       "          59397.4  , 4831714.   ],\n",
       "       [4739838.5  , 1687205.5  ,  661661.7  , ..., 2859246.   ,\n",
       "         465171.66 , 4838563.5  ],\n",
       "       [4744763.5  , 1653504.2  ,  629885.44 , ..., 2857757.5  ,\n",
       "         454622.4  , 4842395.5  ],\n",
       "       ...,\n",
       "       [1695335.   ,  369578.22 ,  228120.64 , ...,       0.   ,\n",
       "              0.   ,       0.   ],\n",
       "       [1509972.5  ,   99505.516,  227395.9  , ...,       0.   ,\n",
       "              0.   ,       0.   ],\n",
       "       [1506805.5  ,   98575.414,  202543.05 , ...,       0.   ,\n",
       "              0.   ,       0.   ]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>length</span></div><div class='xr-var-dims'>(time, rgi_id)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>2.87e+03 1.334e+03 ... 0.0 0.0</div><input id='attrs-f451f529-c1db-4ad6-88bf-c88cd6bebf09' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f451f529-c1db-4ad6-88bf-c88cd6bebf09' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ba622cd8-1d07-459f-98b3-dcc416caf0c8' class='xr-var-data-in' type='checkbox'><label for='data-ba622cd8-1d07-459f-98b3-dcc416caf0c8' 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([[2870., 1334.,  836., ..., 2856.,  144., 3116.],\n",
       "       [2870., 1624., 1452., ..., 2856., 1440., 3116.],\n",
       "       [2870., 1566., 1276., ..., 2856., 1332., 3116.],\n",
       "       ...,\n",
       "       [1312.,  522.,  572., ...,    0.,    0.,    0.],\n",
       "       [1230.,  232.,  572., ...,    0.,    0.,    0.],\n",
       "       [1230.,  232.,  528., ...,    0.,    0.,    0.]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>calving</span></div><div class='xr-var-dims'>(time, rgi_id)</div><div class='xr-var-dtype'>float32</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-44f0e57b-2d44-4576-a248-a3d59c66e7a9' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-44f0e57b-2d44-4576-a248-a3d59c66e7a9' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-9a2ee427-ede8-41eb-b659-c6c50ff4f623' class='xr-var-data-in' type='checkbox'><label for='data-9a2ee427-ede8-41eb-b659-c6c50ff4f623' 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.],\n",
       "       [0., 0., 0., ..., 0., 0., 0.],\n",
       "       [0., 0., 0., ..., 0., 0., 0.],\n",
       "       ...,\n",
       "       [0., 0., 0., ..., 0., 0., 0.],\n",
       "       [0., 0., 0., ..., 0., 0., 0.],\n",
       "       [0., 0., 0., ..., 0., 0., 0.]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>calving_rate</span></div><div class='xr-var-dims'>(time, rgi_id)</div><div class='xr-var-dtype'>float32</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-a3342f21-9b51-45a7-bdc4-e8f0aefb9c3c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a3342f21-9b51-45a7-bdc4-e8f0aefb9c3c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6d8fdceb-875b-4c09-8e99-fbfd15302ba4' class='xr-var-data-in' type='checkbox'><label for='data-6d8fdceb-875b-4c09-8e99-fbfd15302ba4' 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.],\n",
       "       [0., 0., 0., ..., 0., 0., 0.],\n",
       "       [0., 0., 0., ..., 0., 0., 0.],\n",
       "       ...,\n",
       "       [0., 0., 0., ..., 0., 0., 0.],\n",
       "       [0., 0., 0., ..., 0., 0., 0.],\n",
       "       [0., 0., 0., ..., 0., 0., 0.]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>water_level</span></div><div class='xr-var-dims'>(rgi_id)</div><div class='xr-var-dtype'>float32</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-aa73f3ea-34aa-4899-82ac-51ef2a21704d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-aa73f3ea-34aa-4899-82ac-51ef2a21704d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-1c4ad89e-0cf4-4241-94a0-808d8baf0f23' class='xr-var-data-in' type='checkbox'><label for='data-1c4ad89e-0cf4-4241-94a0-808d8baf0f23' 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 water level</dd><dt><span>units :</span></dt><dd>m</dd></dl></div><div class='xr-var-data'><pre>array([ 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.,\n",
       "        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.,\n",
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       "        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.,\n",
       "        0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,  0., nan,  0.,  0.,  0.,\n",
       "        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.,\n",
       "        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.,\n",
       "        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.,\n",
       "        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.,\n",
       "        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.,\n",
       "        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.,\n",
       "        0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,\n",
       "        0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>glen_a</span></div><div class='xr-var-dims'>(rgi_id)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>6.458e-24 6.458e-24 ... 6.458e-24</div><input id='attrs-c20ceba8-9bcc-46bf-9181-141debebe1d8' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-c20ceba8-9bcc-46bf-9181-141debebe1d8' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-77c07c16-c813-4ea4-b0f8-124dd14e067a' class='xr-var-data-in' type='checkbox'><label for='data-77c07c16-c813-4ea4-b0f8-124dd14e067a' 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>Simulation Glen A</dd><dt><span>units :</span></dt><dd></dd></dl></div><div class='xr-var-data'><pre>array([6.4583664e-24, 6.4583664e-24, 6.4583664e-24, 6.4583664e-24,\n",
       "       6.4583664e-24, 6.4583664e-24, 6.4583664e-24, 6.4583664e-24,\n",
       "       6.4583664e-24, 6.4583664e-24, 6.4583664e-24, 6.4583664e-24,\n",
       "       6.4583664e-24, 6.4583664e-24, 6.4583664e-24, 6.4583664e-24,\n",
       "       6.4583664e-24, 6.4583664e-24, 6.4583664e-24, 6.4583664e-24,\n",
       "       6.4583664e-24, 6.4583664e-24, 6.4583664e-24, 6.4583664e-24,\n",
       "       6.4583664e-24, 6.4583664e-24, 6.6242772e-24, 6.4583664e-24,\n",
       "       6.4583664e-24, 6.4583664e-24, 6.4583664e-24, 6.4583664e-24,\n",
       "       6.4583664e-24, 6.4583664e-24, 6.4583664e-24, 6.4583664e-24,\n",
       "       6.4583664e-24, 6.4583664e-24, 6.4583664e-24, 6.3028771e-24,\n",
       "       6.4583664e-24, 6.4583664e-24, 6.4583664e-24, 6.4583664e-24,\n",
       "       6.4583664e-24, 6.4583664e-24, 6.4583664e-24, 6.4583664e-24,\n",
       "       6.4583664e-24, 6.4583664e-24, 6.4583664e-24, 6.4583664e-24,\n",
       "       6.4583664e-24, 6.4583664e-24, 6.4583664e-24, 6.4583664e-24,\n",
       "       6.4583664e-24, 6.4583664e-24, 6.4583664e-24, 6.4583664e-24,\n",
       "       6.4583664e-24, 6.4583664e-24, 6.4583664e-24, 6.4583664e-24,\n",
       "       6.4583664e-24, 6.4583664e-24, 6.4583664e-24, 6.4583664e-24,\n",
       "       6.4583664e-24, 6.4583664e-24, 6.4583664e-24, 6.4583664e-24,\n",
       "       6.4582658e-24, 6.4583664e-24, 6.4583664e-24, 6.4583664e-24,\n",
       "       6.4583664e-24, 6.4583664e-24, 6.4583664e-24, 6.4583664e-24,\n",
       "...\n",
       "       6.4583664e-24, 6.4583664e-24, 6.4583664e-24, 6.4583664e-24,\n",
       "       6.4583664e-24, 6.4583664e-24, 6.4583664e-24, 6.4583664e-24,\n",
       "       6.4583664e-24, 6.4583664e-24, 6.2760764e-24, 6.4583664e-24,\n",
       "       6.4583664e-24, 6.4583664e-24, 6.4583664e-24, 6.4583664e-24,\n",
       "       6.4583664e-24, 6.4583664e-24, 6.4583664e-24, 6.4583664e-24,\n",
       "       6.4583664e-24, 6.4583664e-24, 6.4583664e-24, 6.4196719e-24,\n",
       "       6.4583664e-24, 6.4583664e-24, 6.4583664e-24, 6.4583664e-24,\n",
       "       6.2347349e-24, 6.4583664e-24, 6.3817435e-24, 6.4583664e-24,\n",
       "       6.4583664e-24, 6.4583664e-24, 6.4583664e-24, 6.4583664e-24,\n",
       "       6.4583664e-24, 6.4583664e-24, 6.4583664e-24, 6.4583664e-24,\n",
       "       6.4583664e-24, 6.4583664e-24, 6.4583664e-24, 6.4583664e-24,\n",
       "       6.4583664e-24, 6.4583664e-24, 6.3716232e-24, 6.3611101e-24,\n",
       "       6.4583664e-24, 6.4583664e-24, 6.4583664e-24, 6.4111542e-24,\n",
       "       6.3768372e-24, 6.4583664e-24, 6.4583664e-24, 6.4583664e-24,\n",
       "       6.4583664e-24, 6.4583664e-24, 6.4583664e-24, 6.4583664e-24,\n",
       "       6.4583664e-24, 6.4583664e-24, 6.4583664e-24, 6.4583664e-24,\n",
       "       6.4583664e-24, 6.4208698e-24, 6.4583664e-24, 6.4583664e-24,\n",
       "       6.4076189e-24, 6.4583664e-24, 6.4583664e-24, 6.4583664e-24,\n",
       "       6.4583664e-24, 6.3953707e-24, 6.2087132e-24, 6.4583664e-24],\n",
       "      dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>fs</span></div><div class='xr-var-dims'>(rgi_id)</div><div class='xr-var-dtype'>float32</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-f3b78b71-7a62-4934-84f0-d560499ef236' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f3b78b71-7a62-4934-84f0-d560499ef236' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-940141ab-ced3-4e06-855a-8ab569d4e5e6' class='xr-var-data-in' type='checkbox'><label for='data-940141ab-ced3-4e06-855a-8ab569d4e5e6' 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>Simulation sliding parameter</dd><dt><span>units :</span></dt><dd></dd></dl></div><div class='xr-var-data'><pre>array([ 0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,\n",
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       "        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.,\n",
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       "        0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,\n",
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       "        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.,\n",
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       "        0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,\n",
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       "        0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,\n",
       "        0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>is_partial_output</span></div><div class='xr-var-dims'>(rgi_id)</div><div class='xr-var-dtype'>float32</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-df900a5b-d526-48f1-b6a0-a68665618caf' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-df900a5b-d526-48f1-b6a0-a68665618caf' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3761cb6b-7968-4b5d-bbe7-58a5d6bee74b' class='xr-var-data-in' type='checkbox'><label for='data-3761cb6b-7968-4b5d-bbe7-58a5d6bee74b' 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>Whether the run was truncated by a mid-run error (1), completed (0) or the output file was missing (NaN)</dd></dl></div><div class='xr-var-data'><pre>array([ 0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,\n",
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       "        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.,\n",
       "        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.,\n",
       "        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.,\n",
       "        0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.,  0.], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>error_during_run</span></div><div class='xr-var-dims'>(rgi_id)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>&#x27;&#x27; &#x27;&#x27; &#x27;&#x27; &#x27;&#x27; &#x27;&#x27; ... &#x27;&#x27; &#x27;&#x27; &#x27;&#x27; &#x27;&#x27; &#x27;&#x27;</div><input id='attrs-0f56aa35-7535-43fa-9fa4-74a75ffa135e' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-0f56aa35-7535-43fa-9fa4-74a75ffa135e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ffe4d6ad-ecf3-43de-97e4-cd3360d4305e' class='xr-var-data-in' type='checkbox'><label for='data-ffe4d6ad-ecf3-43de-97e4-cd3360d4305e' 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>Error message if the run failed mid-simulation, empty otherwise</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;,\n",
       "       &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;,\n",
       "       &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;,\n",
       "       &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;,\n",
       "       &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;,\n",
       "       &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;,\n",
       "       &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;,\n",
       "       &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;,\n",
       "       &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;,\n",
       "       &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;,\n",
       "       &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;,\n",
       "       &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;,\n",
       "       &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;,\n",
       "       &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;,\n",
       "       &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;,\n",
       "       &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;,\n",
       "       &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;,\n",
       "       &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;,\n",
       "       &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;,\n",
       "       &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;,\n",
       "       &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;,\n",
       "       &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;,\n",
       "       &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, nan, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;,\n",
       "       &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;,\n",
       "       &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;,\n",
       "       &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;,\n",
       "       &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;,\n",
       "       &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;,\n",
       "       &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;,\n",
       "       &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;,\n",
       "       &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;,\n",
       "       &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;,\n",
       "       &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;,\n",
       "       &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;, &#x27;&#x27;], dtype=object)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>scenario</span></div><div class='xr-var-dims'>(rgi_id)</div><div class='xr-var-dtype'>object</div><div class='xr-var-preview xr-preview'>&#x27;up2p0-gwl1p5&#x27; ... &#x27;up2p0-gwl1p5&#x27;</div><input id='attrs-04d6102c-54bc-45f6-b1fa-82a0b518c8dd' class='xr-var-attrs-in' type='checkbox' disabled><label for='attrs-04d6102c-54bc-45f6-b1fa-82a0b518c8dd' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-bca06429-06a6-4ce9-9a53-af7db915c5d6' class='xr-var-data-in' type='checkbox'><label for='data-bca06429-06a6-4ce9-9a53-af7db915c5d6' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'></dl></div><div class='xr-var-data'><pre>array([&#x27;up2p0-gwl1p5&#x27;, &#x27;up2p0-gwl1p5&#x27;, &#x27;up2p0-gwl1p5&#x27;, &#x27;up2p0-gwl1p5&#x27;,\n",
       "       &#x27;up2p0-gwl1p5&#x27;, &#x27;up2p0-gwl1p5&#x27;, &#x27;up2p0-gwl1p5&#x27;, &#x27;up2p0-gwl1p5&#x27;,\n",
       "       &#x27;up2p0-gwl1p5&#x27;, &#x27;up2p0-gwl1p5&#x27;, &#x27;up2p0-gwl1p5&#x27;, &#x27;up2p0-gwl1p5&#x27;,\n",
       "       &#x27;up2p0-gwl1p5&#x27;, &#x27;up2p0-gwl1p5&#x27;, &#x27;up2p0-gwl1p5&#x27;, &#x27;up2p0-gwl1p5&#x27;,\n",
       "       &#x27;up2p0-gwl1p5&#x27;, &#x27;up2p0-gwl1p5&#x27;, &#x27;up2p0-gwl1p5&#x27;, &#x27;up2p0-gwl1p5&#x27;,\n",
       "       &#x27;up2p0-gwl1p5&#x27;, &#x27;up2p0-gwl1p5&#x27;, &#x27;up2p0-gwl1p5&#x27;, &#x27;up2p0-gwl1p5&#x27;,\n",
       "       &#x27;up2p0-gwl1p5&#x27;, &#x27;up2p0-gwl1p5&#x27;, &#x27;up2p0-gwl1p5&#x27;, &#x27;up2p0-gwl1p5&#x27;,\n",
       "       &#x27;up2p0-gwl1p5&#x27;, &#x27;up2p0-gwl1p5&#x27;, &#x27;up2p0-gwl1p5&#x27;, &#x27;up2p0-gwl1p5&#x27;,\n",
       "       &#x27;up2p0-gwl1p5&#x27;, &#x27;up2p0-gwl1p5&#x27;, &#x27;up2p0-gwl1p5&#x27;, &#x27;up2p0-gwl1p5&#x27;,\n",
       "       &#x27;up2p0-gwl1p5&#x27;, &#x27;up2p0-gwl1p5&#x27;, &#x27;up2p0-gwl1p5&#x27;, &#x27;up2p0-gwl1p5&#x27;,\n",
       "       &#x27;up2p0-gwl1p5&#x27;, &#x27;up2p0-gwl1p5&#x27;, &#x27;up2p0-gwl1p5&#x27;, &#x27;up2p0-gwl1p5&#x27;,\n",
       "       &#x27;up2p0-gwl1p5&#x27;, &#x27;up2p0-gwl1p5&#x27;, &#x27;up2p0-gwl1p5&#x27;, &#x27;up2p0-gwl1p5&#x27;,\n",
       "       &#x27;up2p0-gwl1p5&#x27;, &#x27;up2p0-gwl1p5&#x27;, &#x27;up2p0-gwl1p5&#x27;, &#x27;up2p0-gwl1p5&#x27;,\n",
       "       &#x27;up2p0-gwl1p5&#x27;, &#x27;up2p0-gwl1p5&#x27;, &#x27;up2p0-gwl1p5&#x27;, &#x27;up2p0-gwl1p5&#x27;,\n",
       "       &#x27;up2p0-gwl1p5&#x27;, &#x27;up2p0-gwl1p5&#x27;, &#x27;up2p0-gwl1p5&#x27;, &#x27;up2p0-gwl1p5&#x27;,\n",
       "       &#x27;up2p0-gwl1p5&#x27;, &#x27;up2p0-gwl1p5&#x27;, &#x27;up2p0-gwl1p5&#x27;, &#x27;up2p0-gwl1p5&#x27;,\n",
       "       &#x27;up2p0-gwl1p5&#x27;, &#x27;up2p0-gwl1p5&#x27;, &#x27;up2p0-gwl1p5&#x27;, &#x27;up2p0-gwl1p5&#x27;,\n",
       "       &#x27;up2p0-gwl1p5&#x27;, &#x27;up2p0-gwl1p5&#x27;, &#x27;up2p0-gwl1p5&#x27;, &#x27;up2p0-gwl1p5&#x27;,\n",
       "       &#x27;up2p0-gwl1p5&#x27;, &#x27;up2p0-gwl1p5&#x27;, &#x27;up2p0-gwl1p5&#x27;, &#x27;up2p0-gwl1p5&#x27;,\n",
       "       &#x27;up2p0-gwl1p5&#x27;, &#x27;up2p0-gwl1p5&#x27;, &#x27;up2p0-gwl1p5&#x27;, &#x27;up2p0-gwl1p5&#x27;,\n",
       "...\n",
       "       &#x27;up2p0-gwl1p5&#x27;, &#x27;up2p0-gwl1p5&#x27;, &#x27;up2p0-gwl1p5&#x27;, &#x27;up2p0-gwl1p5&#x27;,\n",
       "       &#x27;up2p0-gwl1p5&#x27;, &#x27;up2p0-gwl1p5&#x27;, &#x27;up2p0-gwl1p5&#x27;, &#x27;up2p0-gwl1p5&#x27;,\n",
       "       &#x27;up2p0-gwl1p5&#x27;, &#x27;up2p0-gwl1p5&#x27;, &#x27;up2p0-gwl1p5&#x27;, &#x27;up2p0-gwl1p5&#x27;,\n",
       "       &#x27;up2p0-gwl1p5&#x27;, &#x27;up2p0-gwl1p5&#x27;, &#x27;up2p0-gwl1p5&#x27;, &#x27;up2p0-gwl1p5&#x27;,\n",
       "       &#x27;up2p0-gwl1p5&#x27;, &#x27;up2p0-gwl1p5&#x27;, &#x27;up2p0-gwl1p5&#x27;, &#x27;up2p0-gwl1p5&#x27;,\n",
       "       &#x27;up2p0-gwl1p5&#x27;, &#x27;up2p0-gwl1p5&#x27;, &#x27;up2p0-gwl1p5&#x27;, &#x27;up2p0-gwl1p5&#x27;,\n",
       "       &#x27;up2p0-gwl1p5&#x27;, &#x27;up2p0-gwl1p5&#x27;, &#x27;up2p0-gwl1p5&#x27;, &#x27;up2p0-gwl1p5&#x27;,\n",
       "       &#x27;up2p0-gwl1p5&#x27;, &#x27;up2p0-gwl1p5&#x27;, &#x27;up2p0-gwl1p5&#x27;, &#x27;up2p0-gwl1p5&#x27;,\n",
       "       &#x27;up2p0-gwl1p5&#x27;, &#x27;up2p0-gwl1p5&#x27;, &#x27;up2p0-gwl1p5&#x27;, &#x27;up2p0-gwl1p5&#x27;,\n",
       "       &#x27;up2p0-gwl1p5&#x27;, &#x27;up2p0-gwl1p5&#x27;, &#x27;up2p0-gwl1p5&#x27;, &#x27;up2p0-gwl1p5&#x27;,\n",
       "       &#x27;up2p0-gwl1p5&#x27;, &#x27;up2p0-gwl1p5&#x27;, &#x27;up2p0-gwl1p5&#x27;, &#x27;up2p0-gwl1p5&#x27;,\n",
       "       &#x27;up2p0-gwl1p5&#x27;, &#x27;up2p0-gwl1p5&#x27;, &#x27;up2p0-gwl1p5&#x27;, &#x27;up2p0-gwl1p5&#x27;,\n",
       "       &#x27;up2p0-gwl1p5&#x27;, &#x27;up2p0-gwl1p5&#x27;, &#x27;up2p0-gwl1p5&#x27;, &#x27;up2p0-gwl1p5&#x27;,\n",
       "       &#x27;up2p0-gwl1p5&#x27;, &#x27;up2p0-gwl1p5&#x27;, &#x27;up2p0-gwl1p5&#x27;, &#x27;up2p0-gwl1p5&#x27;,\n",
       "       &#x27;up2p0-gwl1p5&#x27;, &#x27;up2p0-gwl1p5&#x27;, &#x27;up2p0-gwl1p5&#x27;, &#x27;up2p0-gwl1p5&#x27;,\n",
       "       &#x27;up2p0-gwl1p5&#x27;, &#x27;up2p0-gwl1p5&#x27;, &#x27;up2p0-gwl1p5&#x27;, &#x27;up2p0-gwl1p5&#x27;,\n",
       "       &#x27;up2p0-gwl1p5&#x27;, &#x27;up2p0-gwl1p5&#x27;, &#x27;up2p0-gwl1p5&#x27;, &#x27;up2p0-gwl1p5&#x27;,\n",
       "       &#x27;up2p0-gwl1p5&#x27;, &#x27;up2p0-gwl1p5&#x27;, &#x27;up2p0-gwl1p5&#x27;, &#x27;up2p0-gwl1p5&#x27;,\n",
       "       &#x27;up2p0-gwl1p5&#x27;, &#x27;up2p0-gwl1p5&#x27;, &#x27;up2p0-gwl1p5&#x27;, &#x27;up2p0-gwl1p5&#x27;],\n",
       "      dtype=object)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-cce4d80c-3ac4-4e93-aeee-9f55cc204a5e' class='xr-section-summary-in' type='checkbox'  checked><label for='section-cce4d80c-3ac4-4e93-aeee-9f55cc204a5e' class='xr-section-summary' >Attributes: <span>(4)</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>0.1.dev1472+g8adcdb863</dd><dt><span>calendar :</span></dt><dd>365-day no leap</dd><dt><span>creation_date :</span></dt><dd>2026-06-24 17:17:31</dd></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.Dataset> Size: 8MB\n",
       "Dimensions:            (time: 609, rgi_id: 568)\n",
       "Coordinates:\n",
       "  * time               (time) float64 5kB 1.975e+03 1.976e+03 ... 2.583e+03\n",
       "  * rgi_id             (rgi_id) <U14 32kB 'RGI60-06.00001' ... 'RGI60-06.00568'\n",
       "    hydro_year         (time) int64 5kB ...\n",
       "    hydro_month        (time) int64 5kB ...\n",
       "    calendar_year      (time) int64 5kB ...\n",
       "    calendar_month     (time) int64 5kB ...\n",
       "Data variables:\n",
       "    volume             (time, rgi_id) float32 1MB 2.274e+08 5.256e+07 ... 0.0\n",
       "    volume_bsl         (time, rgi_id) float32 1MB 0.0 0.0 0.0 ... 0.0 0.0 0.0\n",
       "    area               (time, rgi_id) float32 1MB 4.731e+06 1.421e+06 ... 0.0\n",
       "    length             (time, rgi_id) float32 1MB 2.87e+03 1.334e+03 ... 0.0 0.0\n",
       "    calving            (time, rgi_id) float32 1MB 0.0 0.0 0.0 ... 0.0 0.0 0.0\n",
       "    calving_rate       (time, rgi_id) float32 1MB 0.0 0.0 0.0 ... 0.0 0.0 0.0\n",
       "    water_level        (rgi_id) float32 2kB 0.0 0.0 0.0 0.0 ... 0.0 0.0 0.0 0.0\n",
       "    glen_a             (rgi_id) float32 2kB 6.458e-24 6.458e-24 ... 6.458e-24\n",
       "    fs                 (rgi_id) float32 2kB 0.0 0.0 0.0 0.0 ... 0.0 0.0 0.0 0.0\n",
       "    is_partial_output  (rgi_id) float32 2kB 0.0 0.0 0.0 0.0 ... 0.0 0.0 0.0 0.0\n",
       "    error_during_run   (rgi_id) object 5kB '' '' '' '' '' '' ... '' '' '' '' ''\n",
       "    scenario           (rgi_id) object 5kB 'up2p0-gwl1p5' ... 'up2p0-gwl1p5'\n",
       "Attributes:\n",
       "    description:    OGGM model output\n",
       "    oggm_version:   0.1.dev1472+g8adcdb863\n",
       "    calendar:       365-day no leap\n",
       "    creation_date:  2026-06-24 17:17:31"
      ]
     },
     "execution_count": 49,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "_d.where(_d.is_partial_output==0)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "id": "e2e4c7f8-c2e5-47cd-97ee-d82b916321b0",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "12"
      ]
     },
     "execution_count": 48,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(_d.where(_d.is_partial_output==0))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "e9085a98-2881-4bd7-9892-98653d5f81cb",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "51c487e0-50bb-4e9b-b11c-ed3b50acae73",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "id": "bc8c0a14-a5f6-47d5-8a21-5b392e8ae2ab",
   "metadata": {},
   "outputs": [
    {
     "ename": "FileNotFoundError",
     "evalue": "[Errno 2] No such file or directory: '/home/www/lschuster/terrafirma_oggm_proj/output_dir/RGIlargest_glaciers/run_terrafirma_UKESM1-2-LL_esm_up2p0-gwl1p5-50y-dn1p0_bc_1975_2014_to_0_40_sim_year_starting_at_1979_glacier_state_from_0_sim_year_climate_largest_glaciers_only.nc'",
     "output_type": "error",
     "traceback": [
      "\u001b[31m---------------------------------------------------------------------------\u001b[39m",
      "\u001b[31mKeyError\u001b[39m                                  Traceback (most recent call last)",
      "\u001b[36mFile \u001b[39m\u001b[32m~/mambaforge/envs/oggm_env_2025/lib/python3.11/site-packages/xarray/backends/file_manager.py:219\u001b[39m, in \u001b[36mCachingFileManager._acquire_with_cache_info\u001b[39m\u001b[34m(self, needs_lock)\u001b[39m\n\u001b[32m    218\u001b[39m \u001b[38;5;28;01mtry\u001b[39;00m:\n\u001b[32m--> \u001b[39m\u001b[32m219\u001b[39m     file = \u001b[38;5;28;43mself\u001b[39;49m\u001b[43m.\u001b[49m\u001b[43m_cache\u001b[49m\u001b[43m[\u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[43m.\u001b[49m\u001b[43m_key\u001b[49m\u001b[43m]\u001b[49m\n\u001b[32m    220\u001b[39m \u001b[38;5;28;01mexcept\u001b[39;00m \u001b[38;5;167;01mKeyError\u001b[39;00m:\n",
      "\u001b[36mFile \u001b[39m\u001b[32m~/mambaforge/envs/oggm_env_2025/lib/python3.11/site-packages/xarray/backends/lru_cache.py:56\u001b[39m, in \u001b[36mLRUCache.__getitem__\u001b[39m\u001b[34m(self, key)\u001b[39m\n\u001b[32m     55\u001b[39m \u001b[38;5;28;01mwith\u001b[39;00m \u001b[38;5;28mself\u001b[39m._lock:\n\u001b[32m---> \u001b[39m\u001b[32m56\u001b[39m     value = \u001b[38;5;28;43mself\u001b[39;49m\u001b[43m.\u001b[49m\u001b[43m_cache\u001b[49m\u001b[43m[\u001b[49m\u001b[43mkey\u001b[49m\u001b[43m]\u001b[49m\n\u001b[32m     57\u001b[39m     \u001b[38;5;28mself\u001b[39m._cache.move_to_end(key)\n",
      "\u001b[31mKeyError\u001b[39m: [<class 'netCDF4._netCDF4.Dataset'>, ('/home/www/lschuster/terrafirma_oggm_proj/output_dir/RGIlargest_glaciers/run_terrafirma_UKESM1-2-LL_esm_up2p0-gwl1p5-50y-dn1p0_bc_1975_2014_to_0_40_sim_year_starting_at_1979_glacier_state_from_0_sim_year_climate_largest_glaciers_only.nc',), 'r', (('clobber', True), ('diskless', False), ('format', 'NETCDF4'), ('persist', False)), '84ceb4e7-bf37-40ed-be1e-226200f37c5a']",
      "\nDuring handling of the above exception, another exception occurred:\n",
      "\u001b[31mFileNotFoundError\u001b[39m                         Traceback (most recent call last)",
      "\u001b[36mCell\u001b[39m\u001b[36m \u001b[39m\u001b[32mIn[38]\u001b[39m\u001b[32m, line 4\u001b[39m\n\u001b[32m      2\u001b[39m scenario = \u001b[33m\"\u001b[39m\u001b[33mup2p0-gwl1p5-50y-dn1p0\u001b[39m\u001b[33m\"\u001b[39m\n\u001b[32m      3\u001b[39m \u001b[38;5;66;03m#scenario = \"up2p0\"\u001b[39;00m\n\u001b[32m----> \u001b[39m\u001b[32m4\u001b[39m _d = \u001b[43mxr\u001b[49m\u001b[43m.\u001b[49m\u001b[43mopen_dataset\u001b[49m\u001b[43m(\u001b[49m\u001b[33;43mf\u001b[39;49m\u001b[33;43m'\u001b[39;49m\u001b[38;5;132;43;01m{\u001b[39;49;00m\u001b[43mp\u001b[49m\u001b[38;5;132;43;01m}\u001b[39;49;00m\u001b[33;43mrun_terrafirma_UKESM1-2-LL_esm_\u001b[39;49m\u001b[38;5;132;43;01m{\u001b[39;49;00m\u001b[43mscenario\u001b[49m\u001b[38;5;132;43;01m}\u001b[39;49;00m\u001b[33;43m_bc_1975_2014_to_0_40_sim_year_starting_at_1979_glacier_state_from_0_sim_year_climate_largest_glaciers_only.nc\u001b[39;49m\u001b[33;43m'\u001b[39;49m\u001b[43m)\u001b[49m\n\u001b[32m      5\u001b[39m _d[\u001b[33m'\u001b[39m\u001b[33mscenario\u001b[39m\u001b[33m'\u001b[39m] = scenario\n",
      "\u001b[36mFile \u001b[39m\u001b[32m~/mambaforge/envs/oggm_env_2025/lib/python3.11/site-packages/xarray/backends/api.py:596\u001b[39m, in \u001b[36mopen_dataset\u001b[39m\u001b[34m(filename_or_obj, engine, chunks, cache, decode_cf, mask_and_scale, decode_times, decode_timedelta, use_cftime, concat_characters, decode_coords, drop_variables, create_default_indexes, inline_array, chunked_array_type, from_array_kwargs, backend_kwargs, **kwargs)\u001b[39m\n\u001b[32m    584\u001b[39m decoders = _resolve_decoders_kwargs(\n\u001b[32m    585\u001b[39m     decode_cf,\n\u001b[32m    586\u001b[39m     open_backend_dataset_parameters=backend.open_dataset_parameters,\n\u001b[32m   (...)\u001b[39m\u001b[32m    592\u001b[39m     decode_coords=decode_coords,\n\u001b[32m    593\u001b[39m )\n\u001b[32m    595\u001b[39m overwrite_encoded_chunks = kwargs.pop(\u001b[33m\"\u001b[39m\u001b[33moverwrite_encoded_chunks\u001b[39m\u001b[33m\"\u001b[39m, \u001b[38;5;28;01mNone\u001b[39;00m)\n\u001b[32m--> \u001b[39m\u001b[32m596\u001b[39m backend_ds = \u001b[43mbackend\u001b[49m\u001b[43m.\u001b[49m\u001b[43mopen_dataset\u001b[49m\u001b[43m(\u001b[49m\n\u001b[32m    597\u001b[39m \u001b[43m    \u001b[49m\u001b[43mfilename_or_obj\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m    598\u001b[39m \u001b[43m    \u001b[49m\u001b[43mdrop_variables\u001b[49m\u001b[43m=\u001b[49m\u001b[43mdrop_variables\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m    599\u001b[39m \u001b[43m    \u001b[49m\u001b[43m*\u001b[49m\u001b[43m*\u001b[49m\u001b[43mdecoders\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m    600\u001b[39m \u001b[43m    \u001b[49m\u001b[43m*\u001b[49m\u001b[43m*\u001b[49m\u001b[43mkwargs\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m    601\u001b[39m \u001b[43m\u001b[49m\u001b[43m)\u001b[49m\n\u001b[32m    602\u001b[39m ds = _dataset_from_backend_dataset(\n\u001b[32m    603\u001b[39m     backend_ds,\n\u001b[32m    604\u001b[39m     filename_or_obj,\n\u001b[32m   (...)\u001b[39m\u001b[32m    615\u001b[39m     **kwargs,\n\u001b[32m    616\u001b[39m )\n\u001b[32m    617\u001b[39m \u001b[38;5;28;01mreturn\u001b[39;00m ds\n",
      "\u001b[36mFile \u001b[39m\u001b[32m~/mambaforge/envs/oggm_env_2025/lib/python3.11/site-packages/xarray/backends/netCDF4_.py:744\u001b[39m, in \u001b[36mNetCDF4BackendEntrypoint.open_dataset\u001b[39m\u001b[34m(self, filename_or_obj, mask_and_scale, decode_times, concat_characters, decode_coords, drop_variables, use_cftime, decode_timedelta, group, mode, format, clobber, diskless, persist, auto_complex, lock, autoclose)\u001b[39m\n\u001b[32m    722\u001b[39m \u001b[38;5;28;01mdef\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[34mopen_dataset\u001b[39m(\n\u001b[32m    723\u001b[39m     \u001b[38;5;28mself\u001b[39m,\n\u001b[32m    724\u001b[39m     filename_or_obj: T_PathFileOrDataStore,\n\u001b[32m   (...)\u001b[39m\u001b[32m    741\u001b[39m     autoclose=\u001b[38;5;28;01mFalse\u001b[39;00m,\n\u001b[32m    742\u001b[39m ) -> Dataset:\n\u001b[32m    743\u001b[39m     filename_or_obj = _normalize_path(filename_or_obj)\n\u001b[32m--> \u001b[39m\u001b[32m744\u001b[39m     store = \u001b[43mNetCDF4DataStore\u001b[49m\u001b[43m.\u001b[49m\u001b[43mopen\u001b[49m\u001b[43m(\u001b[49m\n\u001b[32m    745\u001b[39m \u001b[43m        \u001b[49m\u001b[43mfilename_or_obj\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m    746\u001b[39m \u001b[43m        \u001b[49m\u001b[43mmode\u001b[49m\u001b[43m=\u001b[49m\u001b[43mmode\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m    747\u001b[39m \u001b[43m        \u001b[49m\u001b[38;5;28;43mformat\u001b[39;49m\u001b[43m=\u001b[49m\u001b[38;5;28;43mformat\u001b[39;49m\u001b[43m,\u001b[49m\n\u001b[32m    748\u001b[39m \u001b[43m        \u001b[49m\u001b[43mgroup\u001b[49m\u001b[43m=\u001b[49m\u001b[43mgroup\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m    749\u001b[39m \u001b[43m        \u001b[49m\u001b[43mclobber\u001b[49m\u001b[43m=\u001b[49m\u001b[43mclobber\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m    750\u001b[39m \u001b[43m        \u001b[49m\u001b[43mdiskless\u001b[49m\u001b[43m=\u001b[49m\u001b[43mdiskless\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m    751\u001b[39m \u001b[43m        \u001b[49m\u001b[43mpersist\u001b[49m\u001b[43m=\u001b[49m\u001b[43mpersist\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m    752\u001b[39m \u001b[43m        \u001b[49m\u001b[43mauto_complex\u001b[49m\u001b[43m=\u001b[49m\u001b[43mauto_complex\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m    753\u001b[39m \u001b[43m        \u001b[49m\u001b[43mlock\u001b[49m\u001b[43m=\u001b[49m\u001b[43mlock\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m    754\u001b[39m \u001b[43m        \u001b[49m\u001b[43mautoclose\u001b[49m\u001b[43m=\u001b[49m\u001b[43mautoclose\u001b[49m\u001b[43m,\u001b[49m\n\u001b[32m    755\u001b[39m \u001b[43m    \u001b[49m\u001b[43m)\u001b[49m\n\u001b[32m    757\u001b[39m     store_entrypoint = StoreBackendEntrypoint()\n\u001b[32m    758\u001b[39m     \u001b[38;5;28;01mwith\u001b[39;00m close_on_error(store):\n",
      "\u001b[36mFile \u001b[39m\u001b[32m~/mambaforge/envs/oggm_env_2025/lib/python3.11/site-packages/xarray/backends/netCDF4_.py:524\u001b[39m, in \u001b[36mNetCDF4DataStore.open\u001b[39m\u001b[34m(cls, filename, mode, format, group, clobber, diskless, persist, auto_complex, lock, lock_maker, autoclose)\u001b[39m\n\u001b[32m    520\u001b[39m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[32m    521\u001b[39m     manager = CachingFileManager(\n\u001b[32m    522\u001b[39m         netCDF4.Dataset, filename, mode=mode, kwargs=kwargs\n\u001b[32m    523\u001b[39m     )\n\u001b[32m--> \u001b[39m\u001b[32m524\u001b[39m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43mcls\u001b[39;49m\u001b[43m(\u001b[49m\u001b[43mmanager\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mgroup\u001b[49m\u001b[43m=\u001b[49m\u001b[43mgroup\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mmode\u001b[49m\u001b[43m=\u001b[49m\u001b[43mmode\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mlock\u001b[49m\u001b[43m=\u001b[49m\u001b[43mlock\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mautoclose\u001b[49m\u001b[43m=\u001b[49m\u001b[43mautoclose\u001b[49m\u001b[43m)\u001b[49m\n",
      "\u001b[36mFile \u001b[39m\u001b[32m~/mambaforge/envs/oggm_env_2025/lib/python3.11/site-packages/xarray/backends/netCDF4_.py:428\u001b[39m, in \u001b[36mNetCDF4DataStore.__init__\u001b[39m\u001b[34m(self, manager, group, mode, lock, autoclose)\u001b[39m\n\u001b[32m    426\u001b[39m \u001b[38;5;28mself\u001b[39m._group = group\n\u001b[32m    427\u001b[39m \u001b[38;5;28mself\u001b[39m._mode = mode\n\u001b[32m--> \u001b[39m\u001b[32m428\u001b[39m \u001b[38;5;28mself\u001b[39m.format = \u001b[38;5;28;43mself\u001b[39;49m\u001b[43m.\u001b[49m\u001b[43mds\u001b[49m.data_model\n\u001b[32m    429\u001b[39m \u001b[38;5;28mself\u001b[39m._filename = \u001b[38;5;28mself\u001b[39m.ds.filepath()\n\u001b[32m    430\u001b[39m \u001b[38;5;28mself\u001b[39m.is_remote = is_remote_uri(\u001b[38;5;28mself\u001b[39m._filename)\n",
      "\u001b[36mFile \u001b[39m\u001b[32m~/mambaforge/envs/oggm_env_2025/lib/python3.11/site-packages/xarray/backends/netCDF4_.py:533\u001b[39m, in \u001b[36mNetCDF4DataStore.ds\u001b[39m\u001b[34m(self)\u001b[39m\n\u001b[32m    531\u001b[39m \u001b[38;5;129m@property\u001b[39m\n\u001b[32m    532\u001b[39m \u001b[38;5;28;01mdef\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[34mds\u001b[39m(\u001b[38;5;28mself\u001b[39m):\n\u001b[32m--> \u001b[39m\u001b[32m533\u001b[39m     \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43mself\u001b[39;49m\u001b[43m.\u001b[49m\u001b[43m_acquire\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\n",
      "\u001b[36mFile \u001b[39m\u001b[32m~/mambaforge/envs/oggm_env_2025/lib/python3.11/site-packages/xarray/backends/netCDF4_.py:527\u001b[39m, in \u001b[36mNetCDF4DataStore._acquire\u001b[39m\u001b[34m(self, needs_lock)\u001b[39m\n\u001b[32m    526\u001b[39m \u001b[38;5;28;01mdef\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[34m_acquire\u001b[39m(\u001b[38;5;28mself\u001b[39m, needs_lock=\u001b[38;5;28;01mTrue\u001b[39;00m):\n\u001b[32m--> \u001b[39m\u001b[32m527\u001b[39m \u001b[43m    \u001b[49m\u001b[38;5;28;43;01mwith\u001b[39;49;00m\u001b[43m \u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[43m.\u001b[49m\u001b[43m_manager\u001b[49m\u001b[43m.\u001b[49m\u001b[43macquire_context\u001b[49m\u001b[43m(\u001b[49m\u001b[43mneeds_lock\u001b[49m\u001b[43m)\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;28;43;01mas\u001b[39;49;00m\u001b[43m \u001b[49m\u001b[43mroot\u001b[49m\u001b[43m:\u001b[49m\n\u001b[32m    528\u001b[39m \u001b[43m        \u001b[49m\u001b[43mds\u001b[49m\u001b[43m \u001b[49m\u001b[43m=\u001b[49m\u001b[43m \u001b[49m\u001b[43m_nc4_require_group\u001b[49m\u001b[43m(\u001b[49m\u001b[43mroot\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[43m.\u001b[49m\u001b[43m_group\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[43m.\u001b[49m\u001b[43m_mode\u001b[49m\u001b[43m)\u001b[49m\n\u001b[32m    529\u001b[39m     \u001b[38;5;28;01mreturn\u001b[39;00m ds\n",
      "\u001b[36mFile \u001b[39m\u001b[32m~/mambaforge/envs/oggm_env_2025/lib/python3.11/contextlib.py:137\u001b[39m, in \u001b[36m_GeneratorContextManager.__enter__\u001b[39m\u001b[34m(self)\u001b[39m\n\u001b[32m    135\u001b[39m \u001b[38;5;28;01mdel\u001b[39;00m \u001b[38;5;28mself\u001b[39m.args, \u001b[38;5;28mself\u001b[39m.kwds, \u001b[38;5;28mself\u001b[39m.func\n\u001b[32m    136\u001b[39m \u001b[38;5;28;01mtry\u001b[39;00m:\n\u001b[32m--> \u001b[39m\u001b[32m137\u001b[39m     \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28mnext\u001b[39m(\u001b[38;5;28mself\u001b[39m.gen)\n\u001b[32m    138\u001b[39m \u001b[38;5;28;01mexcept\u001b[39;00m \u001b[38;5;167;01mStopIteration\u001b[39;00m:\n\u001b[32m    139\u001b[39m     \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mRuntimeError\u001b[39;00m(\u001b[33m\"\u001b[39m\u001b[33mgenerator didn\u001b[39m\u001b[33m'\u001b[39m\u001b[33mt yield\u001b[39m\u001b[33m\"\u001b[39m) \u001b[38;5;28;01mfrom\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[38;5;28;01mNone\u001b[39;00m\n",
      "\u001b[36mFile \u001b[39m\u001b[32m~/mambaforge/envs/oggm_env_2025/lib/python3.11/site-packages/xarray/backends/file_manager.py:207\u001b[39m, in \u001b[36mCachingFileManager.acquire_context\u001b[39m\u001b[34m(self, needs_lock)\u001b[39m\n\u001b[32m    204\u001b[39m \u001b[38;5;129m@contextmanager\u001b[39m\n\u001b[32m    205\u001b[39m \u001b[38;5;28;01mdef\u001b[39;00m\u001b[38;5;250m \u001b[39m\u001b[34macquire_context\u001b[39m(\u001b[38;5;28mself\u001b[39m, needs_lock: \u001b[38;5;28mbool\u001b[39m = \u001b[38;5;28;01mTrue\u001b[39;00m) -> Iterator[T_File]:\n\u001b[32m    206\u001b[39m \u001b[38;5;250m    \u001b[39m\u001b[33;03m\"\"\"Context manager for acquiring a file.\"\"\"\u001b[39;00m\n\u001b[32m--> \u001b[39m\u001b[32m207\u001b[39m     file, cached = \u001b[38;5;28;43mself\u001b[39;49m\u001b[43m.\u001b[49m\u001b[43m_acquire_with_cache_info\u001b[49m\u001b[43m(\u001b[49m\u001b[43mneeds_lock\u001b[49m\u001b[43m)\u001b[49m\n\u001b[32m    208\u001b[39m     \u001b[38;5;28;01mtry\u001b[39;00m:\n\u001b[32m    209\u001b[39m         \u001b[38;5;28;01myield\u001b[39;00m file\n",
      "\u001b[36mFile \u001b[39m\u001b[32m~/mambaforge/envs/oggm_env_2025/lib/python3.11/site-packages/xarray/backends/file_manager.py:225\u001b[39m, in \u001b[36mCachingFileManager._acquire_with_cache_info\u001b[39m\u001b[34m(self, needs_lock)\u001b[39m\n\u001b[32m    223\u001b[39m     kwargs = kwargs.copy()\n\u001b[32m    224\u001b[39m     kwargs[\u001b[33m\"\u001b[39m\u001b[33mmode\u001b[39m\u001b[33m\"\u001b[39m] = \u001b[38;5;28mself\u001b[39m._mode\n\u001b[32m--> \u001b[39m\u001b[32m225\u001b[39m file = \u001b[38;5;28;43mself\u001b[39;49m\u001b[43m.\u001b[49m\u001b[43m_opener\u001b[49m\u001b[43m(\u001b[49m\u001b[43m*\u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[43m.\u001b[49m\u001b[43m_args\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43m*\u001b[49m\u001b[43m*\u001b[49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n\u001b[32m    226\u001b[39m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;28mself\u001b[39m._mode == \u001b[33m\"\u001b[39m\u001b[33mw\u001b[39m\u001b[33m\"\u001b[39m:\n\u001b[32m    227\u001b[39m     \u001b[38;5;66;03m# ensure file doesn't get overridden when opened again\u001b[39;00m\n\u001b[32m    228\u001b[39m     \u001b[38;5;28mself\u001b[39m._mode = \u001b[33m\"\u001b[39m\u001b[33ma\u001b[39m\u001b[33m\"\u001b[39m\n",
      "\u001b[36mFile \u001b[39m\u001b[32msrc/netCDF4/_netCDF4.pyx:2517\u001b[39m, in \u001b[36mnetCDF4._netCDF4.Dataset.__init__\u001b[39m\u001b[34m()\u001b[39m\n",
      "\u001b[36mFile \u001b[39m\u001b[32msrc/netCDF4/_netCDF4.pyx:2154\u001b[39m, in \u001b[36mnetCDF4._netCDF4._ensure_nc_success\u001b[39m\u001b[34m()\u001b[39m\n",
      "\u001b[31mFileNotFoundError\u001b[39m: [Errno 2] No such file or directory: '/home/www/lschuster/terrafirma_oggm_proj/output_dir/RGIlargest_glaciers/run_terrafirma_UKESM1-2-LL_esm_up2p0-gwl1p5-50y-dn1p0_bc_1975_2014_to_0_40_sim_year_starting_at_1979_glacier_state_from_0_sim_year_climate_largest_glaciers_only.nc'"
     ]
    }
   ],
   "source": [
    "p = '/home/www/lschuster/terrafirma_oggm_proj/output_dir/RGIlargest_glaciers/'\n",
    "scenario = \"up2p0-gwl1p5-50y-dn1p0\"\n",
    "#scenario = \"up2p0\"\n",
    "_d = xr.open_dataset(f'{p}run_terrafirma_UKESM1-2-LL_esm_{scenario}_bc_1975_2014_to_0_40_sim_year_starting_at_1979_glacier_state_from_0_sim_year_climate_largest_glaciers_only.nc')\n",
    "_d['scenario'] = scenario"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "id": "bf166fec-aee6-4022-9b5a-7f3dd13dd49d",
   "metadata": {},
   "outputs": [
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       ".xr-section-summary {\n",
       "  grid-column: 1;\n",
       "  color: var(--xr-font-color2);\n",
       "  font-weight: 500;\n",
       "}\n",
       "\n",
       ".xr-section-summary > span {\n",
       "  display: inline-block;\n",
       "  padding-left: 0.5em;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:disabled + label {\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-section-summary-in + label:before {\n",
       "  display: inline-block;\n",
       "  content: \"►\";\n",
       "  font-size: 11px;\n",
       "  width: 15px;\n",
       "  text-align: center;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:disabled + label:before {\n",
       "  color: var(--xr-disabled-color);\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked + label:before {\n",
       "  content: \"▼\";\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked + label > span {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-section-summary,\n",
       ".xr-section-inline-details {\n",
       "  padding-top: 4px;\n",
       "}\n",
       "\n",
       ".xr-section-inline-details {\n",
       "  grid-column: 2 / -1;\n",
       "}\n",
       "\n",
       ".xr-section-details {\n",
       "  display: none;\n",
       "  grid-column: 1 / -1;\n",
       "  margin-top: 4px;\n",
       "  margin-bottom: 5px;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked ~ .xr-section-details {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-group-box {\n",
       "  display: inline-grid;\n",
       "  grid-template-columns: 0px 20px auto;\n",
       "  width: 100%;\n",
       "}\n",
       "\n",
       ".xr-group-box-vline {\n",
       "  grid-column-start: 1;\n",
       "  border-right: 0.2em solid;\n",
       "  border-color: var(--xr-border-color);\n",
       "  width: 0px;\n",
       "}\n",
       "\n",
       ".xr-group-box-hline {\n",
       "  grid-column-start: 2;\n",
       "  grid-row-start: 1;\n",
       "  height: 1em;\n",
       "  width: 20px;\n",
       "  border-bottom: 0.2em solid;\n",
       "  border-color: var(--xr-border-color);\n",
       "}\n",
       "\n",
       ".xr-group-box-contents {\n",
       "  grid-column-start: 3;\n",
       "}\n",
       "\n",
       ".xr-array-wrap {\n",
       "  grid-column: 1 / -1;\n",
       "  display: grid;\n",
       "  grid-template-columns: 20px auto;\n",
       "}\n",
       "\n",
       ".xr-array-wrap > label {\n",
       "  grid-column: 1;\n",
       "  vertical-align: top;\n",
       "}\n",
       "\n",
       ".xr-preview {\n",
       "  color: var(--xr-font-color3);\n",
       "}\n",
       "\n",
       ".xr-array-preview,\n",
       ".xr-array-data {\n",
       "  padding: 0 5px !important;\n",
       "  grid-column: 2;\n",
       "}\n",
       "\n",
       ".xr-array-data,\n",
       ".xr-array-in:checked ~ .xr-array-preview {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-array-in:checked ~ .xr-array-data,\n",
       ".xr-array-preview {\n",
       "  display: inline-block;\n",
       "}\n",
       "\n",
       ".xr-dim-list {\n",
       "  display: inline-block !important;\n",
       "  list-style: none;\n",
       "  padding: 0 !important;\n",
       "  margin: 0;\n",
       "}\n",
       "\n",
       ".xr-dim-list li {\n",
       "  display: inline-block;\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "}\n",
       "\n",
       ".xr-dim-list:before {\n",
       "  content: \"(\";\n",
       "}\n",
       "\n",
       ".xr-dim-list:after {\n",
       "  content: \")\";\n",
       "}\n",
       "\n",
       ".xr-dim-list li:not(:last-child):after {\n",
       "  content: \",\";\n",
       "  padding-right: 5px;\n",
       "}\n",
       "\n",
       ".xr-has-index {\n",
       "  font-weight: bold;\n",
       "}\n",
       "\n",
       ".xr-var-list,\n",
       ".xr-var-item {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-var-item > div,\n",
       ".xr-var-item label,\n",
       ".xr-var-item > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-even);\n",
       "  border-color: var(--xr-background-color-row-odd);\n",
       "  margin-bottom: 0;\n",
       "  padding-top: 2px;\n",
       "}\n",
       "\n",
       ".xr-var-item > .xr-var-name:hover span {\n",
       "  padding-right: 5px;\n",
       "}\n",
       "\n",
       ".xr-var-list > li:nth-child(odd) > div,\n",
       ".xr-var-list > li:nth-child(odd) > label,\n",
       ".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-odd);\n",
       "  border-color: var(--xr-background-color-row-even);\n",
       "}\n",
       "\n",
       ".xr-var-name {\n",
       "  grid-column: 1;\n",
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       "\n",
       ".xr-var-dims {\n",
       "  grid-column: 2;\n",
       "}\n",
       "\n",
       ".xr-var-dtype {\n",
       "  grid-column: 3;\n",
       "  text-align: right;\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-var-preview {\n",
       "  grid-column: 4;\n",
       "}\n",
       "\n",
       ".xr-index-preview {\n",
       "  grid-column: 2 / 5;\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-var-name,\n",
       ".xr-var-dims,\n",
       ".xr-var-dtype,\n",
       ".xr-preview,\n",
       ".xr-attrs dt {\n",
       "  white-space: nowrap;\n",
       "  overflow: hidden;\n",
       "  text-overflow: ellipsis;\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-var-name:hover,\n",
       ".xr-var-dims:hover,\n",
       ".xr-var-dtype:hover,\n",
       ".xr-attrs dt:hover {\n",
       "  overflow: visible;\n",
       "  width: auto;\n",
       "  z-index: 1;\n",
       "}\n",
       "\n",
       ".xr-var-attrs,\n",
       ".xr-var-data,\n",
       ".xr-index-data {\n",
       "  display: none;\n",
       "  border-top: 2px dotted var(--xr-background-color);\n",
       "  padding-bottom: 20px !important;\n",
       "  padding-top: 10px !important;\n",
       "}\n",
       "\n",
       ".xr-var-attrs-in + label,\n",
       ".xr-var-data-in + label,\n",
       ".xr-index-data-in + label {\n",
       "  padding: 0 1px;\n",
       "}\n",
       "\n",
       ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
       ".xr-var-data-in:checked ~ .xr-var-data,\n",
       ".xr-index-data-in:checked ~ .xr-index-data {\n",
       "  display: block;\n",
       "}\n",
       "\n",
       ".xr-var-data > table {\n",
       "  float: right;\n",
       "}\n",
       "\n",
       ".xr-var-data > pre,\n",
       ".xr-index-data > pre,\n",
       ".xr-var-data > table > tbody > tr {\n",
       "  background-color: transparent !important;\n",
       "}\n",
       "\n",
       ".xr-var-name span,\n",
       ".xr-var-data,\n",
       ".xr-index-name div,\n",
       ".xr-index-data,\n",
       ".xr-attrs {\n",
       "  padding-left: 25px !important;\n",
       "}\n",
       "\n",
       ".xr-attrs,\n",
       ".xr-var-attrs,\n",
       ".xr-var-data,\n",
       ".xr-index-data {\n",
       "  grid-column: 1 / -1;\n",
       "}\n",
       "\n",
       "dl.xr-attrs {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  display: grid;\n",
       "  grid-template-columns: 125px auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt,\n",
       ".xr-attrs dd {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  float: left;\n",
       "  padding-right: 10px;\n",
       "  width: auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt {\n",
       "  font-weight: normal;\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-attrs dt:hover span {\n",
       "  display: inline-block;\n",
       "  background: var(--xr-background-color);\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-attrs dd {\n",
       "  grid-column: 2;\n",
       "  white-space: pre-wrap;\n",
       "  word-break: break-all;\n",
       "}\n",
       "\n",
       ".xr-icon-database,\n",
       ".xr-icon-file-text2,\n",
       ".xr-no-icon {\n",
       "  display: inline-block;\n",
       "  vertical-align: middle;\n",
       "  width: 1em;\n",
       "  height: 1.5em !important;\n",
       "  stroke-width: 0;\n",
       "  stroke: currentColor;\n",
       "  fill: currentColor;\n",
       "}\n",
       "\n",
       ".xr-var-attrs-in:checked + label > .xr-icon-file-text2,\n",
       ".xr-var-data-in:checked + label > .xr-icon-database,\n",
       ".xr-index-data-in:checked + label > .xr-icon-database {\n",
       "  color: var(--xr-font-color0);\n",
       "  filter: drop-shadow(1px 1px 5px var(--xr-font-color2));\n",
       "  stroke-width: 0.8px;\n",
       "}\n",
       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.DataArray &#x27;is_partial_output&#x27; (rgi_id: 2)&gt; Size: 8B\n",
       "array([1., 1.], dtype=float32)\n",
       "Coordinates:\n",
       "  * rgi_id   (rgi_id) &lt;U14 112B &#x27;RGI60-16.01251&#x27; &#x27;RGI60-17.05181&#x27;\n",
       "Attributes:\n",
       "    description:  Whether the run was truncated by a mid-run error (1), compl...</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-obj-name'>&#x27;is_partial_output&#x27;</div><ul class='xr-dim-list'><li><span class='xr-has-index'>rgi_id</span>: 2</li></ul></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-551994fe-2331-4b65-bb18-170ac2f5b04d' class='xr-array-in' type='checkbox' checked><label for='section-551994fe-2331-4b65-bb18-170ac2f5b04d' 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>1.0 1.0</span></div><div class='xr-array-data'><pre>array([1., 1.], dtype=float32)</pre></div></div></li><li class='xr-section-item'><input id='section-0b9ec17f-ae7e-45c1-8742-48934083b77d' class='xr-section-summary-in' type='checkbox'  checked><label for='section-0b9ec17f-ae7e-45c1-8742-48934083b77d' class='xr-section-summary' >Coordinates: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>rgi_id</span></div><div class='xr-var-dims'>(rgi_id)</div><div class='xr-var-dtype'>&lt;U14</div><div class='xr-var-preview xr-preview'>&#x27;RGI60-16.01251&#x27; &#x27;RGI60-17.05181&#x27;</div><input id='attrs-1c8a97dc-e865-4782-a743-d19ab29b82dc' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-1c8a97dc-e865-4782-a743-d19ab29b82dc' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-03e1feb9-dc00-4454-a819-56d56fcdcb29' class='xr-var-data-in' type='checkbox'><label for='data-03e1feb9-dc00-4454-a819-56d56fcdcb29' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>description :</span></dt><dd>RGI glacier identifier</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;RGI60-16.01251&#x27;, &#x27;RGI60-17.05181&#x27;], dtype=&#x27;&lt;U14&#x27;)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-09d2d549-540b-4cab-bdb5-df4995810c2a' class='xr-section-summary-in' type='checkbox'  checked><label for='section-09d2d549-540b-4cab-bdb5-df4995810c2a' class='xr-section-summary' >Attributes: <span>(1)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>description :</span></dt><dd>Whether the run was truncated by a mid-run error (1), completed (0) or the output file was missing (NaN)</dd></dl></div></li></ul></div></div>"
      ],
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       "<xarray.DataArray 'is_partial_output' (rgi_id: 2)> Size: 8B\n",
       "array([1., 1.], dtype=float32)\n",
       "Coordinates:\n",
       "  * rgi_id   (rgi_id) <U14 112B 'RGI60-16.01251' 'RGI60-17.05181'\n",
       "Attributes:\n",
       "    description:  Whether the run was truncated by a mid-run error (1), compl..."
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "_d.is_partial_output.where(_d.is_partial_output==1).dropna(dim='rgi_id')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "4528b5cb-7607-432b-9ad0-8ca272bb4d23",
   "metadata": {},
   "outputs": [],
   "source": [
    "add =''\n",
    "eq_dir = f'/home/www/lschuster/terrafirma_oggm_proj/output_dir/tests{add}'\n",
    "\n",
    "plt.rcParams[\"font.size\"] = 22\n",
    "fig, axes = plt.subplots(4, 5, figsize=(30,35))\n",
    "axes = axes.flatten()\n",
    "fig.delaxes(axes[-1])\n",
    "\n",
    "for j,gdir in enumerate(gdirs):\n",
    "    try:\n",
    "        ds_spinup_hist = xr.open_dataset(gdir.get_filepath('model_diagnostics',\n",
    "                                                           filesuffix='_spinup_historical')).volume_m3/1e9\n",
    "        rgi_id = gdir.rgi_id\n",
    "        ax = axes[j]\n",
    "        ax.set_title(rgi_id)\n",
    "\n",
    "        for scenario in SCENARIOS_sel:\n",
    "            rid = f'_terrafirma_UKESM1-2-LL_esm_{scenario}_bc_1975_2014'\n",
    "            ds_vol_km3 = xr.open_dataset(os.path.join(eq_dir,\n",
    "                                                      f'run{rid}_from_simyear_0_starting_at_1979_glacier_state_test{add}.nc')).volume/1e9\n",
    "            _test = ds_vol_km3.sel(rgi_id=rgi_id)\n",
    "            ax.plot(_test.time, _test.values, label=scenario, \n",
    "                    color=get_scenario_style(scenario)['color'],\n",
    "                    ls=get_scenario_style(scenario)['linestyle'],\n",
    "                    lw= get_scenario_style(scenario)['linewidth']+1)\n",
    "            # we started with the glacier state fro 1979, but in year 1975, \n",
    "            #so the 1975 volume should be similar to the 1979 historical spinup volume\n",
    "            try:\n",
    "                np.testing.assert_allclose(_test.sel(time=1975), ds_spinup_hist.sel(time=1979), rtol = 0.01)\n",
    "            except:\n",
    "                print(gdir.rgi_id, (_test.sel(time=1975).values/ds_spinup_hist.sel(time=1979).values).round(2),\n",
    "                     (_test.sel(time=1979).values/ds_spinup_hist.sel(time=1979).values).round(2))\n",
    "        # secondary x-axis \n",
    "        t0 = _test.time.values[0]          # simulation start\n",
    "    \n",
    "        def to_sim_year(t):\n",
    "            return t -t0\n",
    "    \n",
    "        def to_calendar_year(sim):\n",
    "            return sim + t0\n",
    "    \n",
    "        secax = ax.secondary_xaxis('top', functions=(to_sim_year, to_calendar_year))\n",
    "        if j == 0:\n",
    "            secax.set_xlabel(\"Simulation year\")\n",
    "            ax.set_xlabel('Calendar year starting in 1975\\n(assuming 0–40 is similar to 1975–2024)')\n",
    "            ax.set_ylabel('Volume (km³)')\n",
    "        ax.text(1,1,)\n",
    "    except:\n",
    "        print(gdir.rgi_id, 'failed')\n",
    "#plt.tight_layout()\n",
    "axes[-5].legend(loc='upper left', bbox_to_anchor=(0.1,-0.1), ncol=4)\n",
    "\n",
    "plt.savefig('00b_test_projections_w_largest_glacier_of_each_region.png')"
   ]
  }
 ],
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