5_Distributed_preprocessing.ipynb

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    "# Part V: Producing a distributed dataset\n",
    "\n",
    "Authors: Jordi Bolibar & Facundo Sapienza\n",
    "\n",
    "```{note}\n",
    "Before running this notebook, be sure you Jupyter kernel (top left corner of the notebook) has been configure to work with the *finse_modelling* conda environment. \n",
    "```"
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   "source": [
    "## 5.1. Context"
   ]
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    "As you might have realized, the glacier-wide geodetic mass balance data used in the previous notebooks is extremely noisy. Moreover, the scientific interest of such dataset is limited in terms of prediction, since we deliberately used a simple dataset to explain the basic machine learning workflow. Generally, remote sensing datasets have a very good spatial coverage, but low temporal resolution. The actual dataset from [Hugonnet et al. (2021)](https://www.nature.com/articles/s41586-021-03436-z) consist on raster grids with the distributed geodetic mass balance of each glacier in the world for multiple periods. This means that we have additional spatial mass balance information than just a single glacier-wide value. Exploiting such data can be very interesting, due to the increased richness of information. \n",
    "\n",
    "Alternatively, the [OGGM Shop](https://docs.oggm.org/en/stable/shop.html) also provides access to a wide range of datasets of glaciers, which can be used for training machine learning models. As we will shown in this notebook, with just a few lines of code we can get all the necessary data for a region of interest in order to start training machine learning models. \n",
    "\n",
    "Here, we propose two different more advanced projects to exploit spatially distributed (i.e. gridded) raster data. These projects can be tackled with the previous methods seen in Notebook 3, or for the boldest ones, you can try to use convolutional neural networks in order to extract spatial information present in the gridded data. These notebooks will draw heavily from the awesome resources provided by OGGM, particularly from [this machine learning-oriented notebook](https://oggm.org/tutorials/stable/notebooks/10minutes/machine_learning.html), and [this new tutorial on retrieving state-of-the-art datasets](https://oggm.org/training-lahore/day_4/01_data_prep.html)."
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   "source": [
    "```{note}\n",
    "In this notebook, we will adapt Notebook 1 in order to produce a similar dataset but in a distributed fashion, i.e. in 2D, so we can model each grid cell of the glacier instead of using glacier-wide information. \n",
    "```"
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   "source": [
    "## 5.2. Re-computing a distributed dataset"
   ]
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      "text/plain": [
       "'1.6.0'"
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   "source": [
    "import oggm\n",
    "oggm.__version__"
   ]
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   "source": [
    "We import all the necessary dependencies to retrieve the data with OGGM and to postprocess it. We use multiprocessing with OGGM to make things faster."
   ]
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     "text": [
      "2023-04-20 14:25:27: oggm.cfg: Reading default parameters from the OGGM `params.cfg` configuration file.\n",
      "2023-04-20 14:25:27: oggm.cfg: Multiprocessing switched OFF according to the parameter file.\n",
      "2023-04-20 14:25:27: oggm.cfg: Multiprocessing: using all available processors (N=16)\n",
      "2023-04-20 14:25:27: oggm.cfg: PARAMS['border'] changed from `80` to `10`.\n",
      "2023-04-20 14:25:27: oggm.cfg: Multiprocessing switched ON after user settings.\n",
      "2023-04-20 14:25:27: oggm.cfg: PARAMS['continue_on_error'] changed from `False` to `True`.\n"
     ]
    }
   ],
   "source": [
    "import xarray as xr\n",
    "import numpy as np\n",
    "import rioxarray\n",
    "import pandas as pd\n",
    "import geopandas as gpd\n",
    "import matplotlib.pyplot as plt\n",
    "import oggm\n",
    "from oggm import cfg, utils, workflow, tasks, graphics\n",
    "from oggm import entity_task, global_tasks\n",
    "from oggm.utils import compile_climate_input\n",
    "from oggm.core import gis\n",
    "from oggm.utils import DEM_SOURCES\n",
    "from pathlib import Path\n",
    "import os\n",
    "import logging\n",
    "from datetime import datetime, timedelta\n",
    "\n",
    "pd.set_option('display.max_columns',None)\n",
    "\n",
    "cfg.initialize(logging_level='WARNING')\n",
    "cfg.PARAMS['border'] = 10\n",
    "cfg.PARAMS['use_multiprocessing'] = True \n",
    "cfg.PARAMS['continue_on_error'] = True\n",
    "# Module logger\n",
    "log = logging.getLogger('.'.join(__name__.split('.')[:-1]))"
   ]
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   "source": [
    "Choose your OGGM path where you want to store all the data. Since we are all working in the same Hub, we can store the information in the same shared folder. Here we use a different folder than in notebook 1, specifying that it deals with distributed data. "
   ]
  },
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   "source": [
    "parent_path = os.path.dirname(Path().resolve())\n",
    "workspace_path = os.path.join(parent_path, 'OGGM_data_Finse_distributed')\n",
    "#workspace_path = '/home/jovyan/shared/glacier-ml-2022/Mass_Balance_ML_Modelling/Data'\n",
    "\n",
    "if not os.path.exists(workspace_path):\n",
    "    os.mkdir(workspace_path)\n",
    "\n",
    "cfg.PATHS['working_dir'] = workspace_path"
   ]
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   "source": [
    "As it was done in notebook 1, here we create a new entity task in order to produce the distributed dataset. Both the distributed data and the climate data are available for each glacier directory as netCDF files, which we will read and process using `xarray`."
   ]
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   "source": [
    "We re-introduce the helper function in order to convert `datetimes` to the right format."
   ]
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    "def decimal_to_datetime(ds):\n",
    "    datetimes = []\n",
    "    for dec_year in ds.time.data:\n",
    "        year = int(dec_year)\n",
    "        rem = dec_year - year\n",
    "\n",
    "        base = datetime(year, 1, 1)\n",
    "        calendar_time = base + timedelta(seconds=(base.replace(year=base.year + 1) - base).total_seconds() * rem)\n",
    "        datetimes.append(calendar_time)\n",
    "        \n",
    "    climate_ds['time'] = datetimes\n",
    "        \n",
    "    return climate_ds"
   ]
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   "source": [
    "And now we declare the actual entity task."
   ]
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   "id": "f6cf8dbd-8e73-449f-b82f-3be31b0919a1",
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    "@entity_task(log)\n",
    "def get_gridded_features(gdir):\n",
    "    \"\"\"Retrieves and processes gridded and climate data for a gdir in order to create the dataset\n",
    "        to be fed to machine learning models.\n",
    "    \"\"\"\n",
    "    # Retrieve gridded data\n",
    "    with xr.open_dataset(gdir.get_filepath('gridded_data')) as ds:\n",
    "        gridded_ds = ds.load()\n",
    "    # Retrieve climate data\n",
    "    with xr.open_dataset(gdir.get_filepath('climate_historical')) as ds:\n",
    "        climate_ds = ds.load()\n",
    "        \n",
    "    #### Latitude and Longitude \n",
    "    lon, lat = gdir.grid.ll_coordinates\n",
    "    \n",
    "    #### Climate data ####\n",
    "    # First we start by processing the climate data\n",
    "    # Trim climate dataset to desired period of the Hugonnet et al. (2021) dataset\n",
    "    climate_ds = climate_ds.sel(time=slice('2000-01-01','2019-12-01')) \n",
    "    \n",
    "    # Now we downscale the climate data to the specific glacier \n",
    "    # Temperature\n",
    "    temps_2D = np.empty((climate_ds.temp.data.size, gridded_ds.topo.data.shape[0], gridded_ds.topo.data.shape[1]))\n",
    "    i = 0\n",
    "    for temp in climate_ds.temp.data:\n",
    "        temps_2D[i,:,:] = np.tile(temp,gridded_ds.topo.data.shape) + 6.0/1000.0*(gridded_ds.topo.data - climate_ds.ref_hgt.data)\n",
    "        i=i+1\n",
    "    \n",
    "    PDD_2D = np.sum(np.where(temps_2D > 0.0, temps_2D, 0.0), axis=0)\n",
    "    \n",
    "    # Rain\n",
    "    rain_period_2D = np.empty((climate_ds.prcp.data.size, gridded_ds.topo.data.shape[0], gridded_ds.topo.data.shape[1]))\n",
    "    i = 0\n",
    "    for prcp in climate_ds.prcp.data:\n",
    "        rain_period_2D[i,:,:] = np.tile(prcp,gridded_ds.topo.data.shape) \n",
    "        i=i+1\n",
    "    \n",
    "    rain_2D = np.sum(rain_period_2D, axis=0)\n",
    "    \n",
    "    # Snow\n",
    "    snow_2D = np.sum(np.where(temps_2D < 0.0, rain_period_2D, 0.0), axis=0)\n",
    "        \n",
    "    # Now we create a dictionary with the full dataset, including the previous climate data\n",
    "    # and all the interesting gridded datasets \n",
    "    training_data = {'lon': lon,\n",
    "                     'lat': lat,\n",
    "                     'PDD_2D': PDD_2D,\n",
    "                     'rain_2D': rain_2D,\n",
    "                     'snow_2D': snow_2D,\n",
    "                     'topo': gridded_ds.topo.data,\n",
    "                     'aspect': gridded_ds.aspect.data,\n",
    "                     'slope': gridded_ds.slope.data,\n",
    "                     'dis_from_border': gridded_ds.dis_from_border.data,\n",
    "                     'glacier_mask': gridded_ds.glacier_mask.data,\n",
    "                     'millan_ice_velocities': np.nan_to_num(gridded_ds.millan_v.data),\n",
    "                     'millan_ice_thickness': np.nan_to_num(gridded_ds.millan_ice_thickness.data),\n",
    "                     'hugonnet_dhdt': np.nan_to_num(gridded_ds.hugonnet_dhdt.data),\n",
    "                     'ID': gdir.rgi_id\n",
    "        }\n",
    "    \n",
    "    return training_data"
   ]
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   "source": [
    "Download all data from glaciers in Scandinavia (RGI region '08'). We use a specific directory with preprocessed data, including all the nice distributed datasets that we need. "
   ]
  },
  {
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   "execution_count": 7,
   "id": "f64bf74b-5a03-4e84-890c-21d300530870",
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     "text": [
      "2023-04-20 14:35:30: oggm.workflow: init_glacier_directories from prepro level 3 on 3417 glaciers.\n",
      "2023-04-20 14:35:30: oggm.workflow: Execute entity tasks [gdir_from_prepro] on 3417 glaciers\n"
     ]
    }
   ],
   "source": [
    "rgi_region = '08' # Scandinavia\n",
    "rgi_version = '6'\n",
    "rgi_dir = utils.get_rgi_dir(version=rgi_version)\n",
    "path = utils.get_rgi_region_file(region=rgi_region, version=rgi_version)\n",
    "rgidf = gpd.read_file(path)\n",
    "# We use the directories with the shop data in it: \"W5E5_w_data\"\n",
    "base_url = 'https://cluster.klima.uni-bremen.de/~oggm/gdirs/oggm_v1.6/L3-L5_files/2023.1/elev_bands/W5E5_w_data/'\n",
    "gdirs = workflow.init_glacier_directories(rgidf, from_prepro_level=3, prepro_base_url=base_url, prepro_border=10)"
   ]
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   "source": [
    "Let's add some additional data to all that."
   ]
  },
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   "cell_type": "code",
   "execution_count": 8,
   "id": "734c817f-357c-4621-beaf-d2e5cd8f6692",
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     "text": [
      "2023-04-20 14:36:45: oggm.workflow: Execute entity tasks [gridded_attributes] on 3417 glaciers\n",
      "2023-04-20 14:37:54: oggm.workflow: Execute entity tasks [gridded_mb_attributes] on 3417 glaciers\n"
     ]
    }
   ],
   "source": [
    "# Tested tasks\n",
    "task_list = [\n",
    "    tasks.gridded_attributes,\n",
    "    tasks.gridded_mb_attributes,\n",
    "]\n",
    "for task in task_list:\n",
    "    workflow.execute_entity_task(task, gdirs, print_log=False)"
   ]
  },
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   "source": [
    "## 5.3. Exploring the dataset"
   ]
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   "source": [
    "In order to get a rough idea on how the data looks like, let's take a quick look at the gridded data we added to our dataset. We'll use the netCDF file read with `xarray`. This is different to the dataset we have created, since for that we just kept raw data as matrices, which is what is needed for the machine learning models. Let's take a look at the famous Nigardsbreen."
   ]
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   "execution_count": 9,
   "id": "104ddbef-2a85-4f58-a334-bd32ec0346fa",
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   "source": [
    "for gdir in gdirs:\n",
    "    if (gdir.name == 'Nigardsbreen'):\n",
    "        break"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "4c2cfc00-7b54-4bd2-a995-cce6e92ac050",
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       "  cursor: pointer;\n",
       "  color: var(--xr-font-color2);\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",
       "  padding-bottom: 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-bottom: 5px;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked ~ .xr-section-details {\n",
       "  display: contents;\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",
       "  margin-bottom: 0;\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",
       "}\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",
       "  background-color: var(--xr-background-color) !important;\n",
       "  padding-bottom: 5px !important;\n",
       "}\n",
       "\n",
       ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
       ".xr-var-data-in:checked ~ .xr-var-data,\n",
       ".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-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",
       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt;\n",
       "Dimensions:                  (x: 108, y: 108)\n",
       "Coordinates:\n",
       "  * x                        (x) float32 -4.117e+03 -4.016e+03 ... 6.69e+03\n",
       "  * y                        (y) float32 6.848e+06 6.848e+06 ... 6.837e+06\n",
       "Data variables: (12/20)\n",
       "    topo                     (y, x) float32 545.2 473.4 365.1 ... 716.0 623.4\n",
       "    topo_smoothed            (y, x) float32 585.5 530.5 436.3 ... 667.4 612.1\n",
       "    topo_valid_mask          (y, x) int8 1 1 1 1 1 1 1 1 1 ... 1 1 1 1 1 1 1 1 1\n",
       "    glacier_mask             (y, x) int8 0 0 0 0 0 0 0 0 0 ... 0 0 0 0 0 0 0 0 0\n",
       "    glacier_ext              (y, x) int8 0 0 0 0 0 0 0 0 0 ... 0 0 0 0 0 0 0 0 0\n",
       "    consensus_ice_thickness  (y, x) float32 nan nan nan nan ... nan nan nan nan\n",
       "    ...                       ...\n",
       "    aspect                   (y, x) float32 0.528 0.638 0.7656 ... 0.7515 0.706\n",
       "    slope_factor             (y, x) float32 1.123 1.071 1.016 ... 1.192 1.238\n",
       "    dis_from_border          (y, x) float32 9.213e+03 9.143e+03 ... 1.428e+03\n",
       "    catchment_area           (y, x) float32 nan nan nan nan ... nan nan nan nan\n",
       "    lin_mb_above_z           (y, x) float32 nan nan nan nan ... nan nan nan nan\n",
       "    oggm_mb_above_z          (y, x) float32 nan nan nan nan ... nan nan nan nan\n",
       "Attributes:\n",
       "    author:         OGGM\n",
       "    author_info:    Open Global Glacier Model\n",
       "    pyproj_srs:     +proj=tmerc +lat_0=0 +lon_0=7.099 +k=0.9996 +x_0=0 +y_0=0...\n",
       "    max_h_dem:      1970.0707\n",
       "    min_h_dem:      88.412544\n",
       "    max_h_glacier:  1939.6395\n",
       "    min_h_glacier:  311.37354</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-34ead568-6abe-4368-8316-2078451f869f' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-34ead568-6abe-4368-8316-2078451f869f' 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'>x</span>: 108</li><li><span class='xr-has-index'>y</span>: 108</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-4f6e4bb7-b1f8-46a5-b44c-53e11f2685bd' class='xr-section-summary-in' type='checkbox'  checked><label for='section-4f6e4bb7-b1f8-46a5-b44c-53e11f2685bd' class='xr-section-summary' >Coordinates: <span>(2)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>x</span></div><div class='xr-var-dims'>(x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-4.117e+03 -4.016e+03 ... 6.69e+03</div><input id='attrs-bd91d9e8-1f23-4b09-a414-d2947489fb8e' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-bd91d9e8-1f23-4b09-a414-d2947489fb8e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-fc879eee-9f9c-4407-b658-e46c7b77b56c' class='xr-var-data-in' type='checkbox'><label for='data-fc879eee-9f9c-4407-b658-e46c7b77b56c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>m</dd><dt><span>long_name :</span></dt><dd>x coordinate of projection</dd><dt><span>standard_name :</span></dt><dd>projection_x_coordinate</dd></dl></div><div class='xr-var-data'><pre>array([-4117.1313  , -4016.1313  , -3915.1313  , -3814.1313  , -3713.1313  ,\n",
       "       -3612.1313  , -3511.1313  , -3410.1313  , -3309.1313  , -3208.1313  ,\n",
       "       -3107.1313  , -3006.1313  , -2905.1313  , -2804.1313  , -2703.1313  ,\n",
       "       -2602.1313  , -2501.1313  , -2400.1313  , -2299.1313  , -2198.1313  ,\n",
       "       -2097.1313  , -1996.1315  , -1895.1315  , -1794.1315  , -1693.1315  ,\n",
       "       -1592.1315  , -1491.1315  , -1390.1315  , -1289.1315  , -1188.1315  ,\n",
       "       -1087.1315  ,  -986.1315  ,  -885.1315  ,  -784.1315  ,  -683.1315  ,\n",
       "        -582.1315  ,  -481.13147 ,  -380.13147 ,  -279.13147 ,  -178.13147 ,\n",
       "         -77.13146 ,    23.868538,   124.86854 ,   225.86853 ,   326.86853 ,\n",
       "         427.86853 ,   528.8685  ,   629.8685  ,   730.8685  ,   831.8685  ,\n",
       "         932.8685  ,  1033.8685  ,  1134.8685  ,  1235.8685  ,  1336.8685  ,\n",
       "        1437.8685  ,  1538.8685  ,  1639.8685  ,  1740.8685  ,  1841.8685  ,\n",
       "        1942.8685  ,  2043.8685  ,  2144.8687  ,  2245.8687  ,  2346.8687  ,\n",
       "        2447.8687  ,  2548.8687  ,  2649.8687  ,  2750.8687  ,  2851.8687  ,\n",
       "        2952.8687  ,  3053.8687  ,  3154.8687  ,  3255.8687  ,  3356.8687  ,\n",
       "        3457.8687  ,  3558.8687  ,  3659.8687  ,  3760.8687  ,  3861.8687  ,\n",
       "        3962.8687  ,  4063.8687  ,  4164.8687  ,  4265.8687  ,  4366.8687  ,\n",
       "        4467.8687  ,  4568.8687  ,  4669.8687  ,  4770.8687  ,  4871.8687  ,\n",
       "        4972.8687  ,  5073.8687  ,  5174.8687  ,  5275.8687  ,  5376.8687  ,\n",
       "        5477.8687  ,  5578.8687  ,  5679.8687  ,  5780.8687  ,  5881.8687  ,\n",
       "        5982.8687  ,  6083.8687  ,  6184.8687  ,  6285.8687  ,  6386.8687  ,\n",
       "        6487.8687  ,  6588.8687  ,  6689.8687  ], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>y</span></div><div class='xr-var-dims'>(y)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>6.848e+06 6.848e+06 ... 6.837e+06</div><input id='attrs-7d4d2d0c-c69a-409e-9424-ee6a5f789a30' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-7d4d2d0c-c69a-409e-9424-ee6a5f789a30' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-39669ecf-669d-43af-9b87-aeab55071139' class='xr-var-data-in' type='checkbox'><label for='data-39669ecf-669d-43af-9b87-aeab55071139' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>m</dd><dt><span>long_name :</span></dt><dd>y coordinate of projection</dd><dt><span>standard_name :</span></dt><dd>projection_y_coordinate</dd></dl></div><div class='xr-var-data'><pre>array([6847880., 6847779., 6847678., 6847577., 6847476., 6847375., 6847274.,\n",
       "       6847173., 6847072., 6846971., 6846870., 6846769., 6846668., 6846567.,\n",
       "       6846466., 6846365., 6846264., 6846163., 6846062., 6845961., 6845860.,\n",
       "       6845759., 6845658., 6845557., 6845456., 6845355., 6845254., 6845153.,\n",
       "       6845052., 6844951., 6844850., 6844749., 6844648., 6844547., 6844446.,\n",
       "       6844345., 6844244., 6844143., 6844042., 6843941., 6843840., 6843739.,\n",
       "       6843638., 6843537., 6843436., 6843335., 6843234., 6843133., 6843032.,\n",
       "       6842931., 6842830., 6842729., 6842628., 6842527., 6842426., 6842325.,\n",
       "       6842224., 6842123., 6842022., 6841921., 6841820., 6841719., 6841618.,\n",
       "       6841517., 6841416., 6841315., 6841214., 6841113., 6841012., 6840911.,\n",
       "       6840810., 6840709., 6840608., 6840507., 6840406., 6840305., 6840204.,\n",
       "       6840103., 6840002., 6839901., 6839800., 6839699., 6839598., 6839497.,\n",
       "       6839396., 6839295., 6839194., 6839093., 6838992., 6838891., 6838790.,\n",
       "       6838689., 6838588., 6838487., 6838386., 6838285., 6838184., 6838083.,\n",
       "       6837982., 6837881., 6837780., 6837679., 6837578., 6837477., 6837376.,\n",
       "       6837275., 6837174., 6837073.], dtype=float32)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-cb83735a-3687-412e-ab7e-4941333b5db0' class='xr-section-summary-in' type='checkbox'  ><label for='section-cb83735a-3687-412e-ab7e-4941333b5db0' class='xr-section-summary' >Data variables: <span>(20)</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>topo</span></div><div class='xr-var-dims'>(y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>545.2 473.4 365.1 ... 716.0 623.4</div><input id='attrs-53fd9a59-0749-4f1b-aa96-abbfbf1beb73' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-53fd9a59-0749-4f1b-aa96-abbfbf1beb73' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-bec86a6a-81f5-4a9f-9d51-0c9b5f07d418' class='xr-var-data-in' type='checkbox'><label for='data-bec86a6a-81f5-4a9f-9d51-0c9b5f07d418' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>m</dd><dt><span>long_name :</span></dt><dd>DEM topography</dd></dl></div><div class='xr-var-data'><pre>array([[ 545.1795 ,  473.4484 ,  365.08377, ..., 1415.9094 , 1408.3987 ,\n",
       "        1402.916  ],\n",
       "       [ 726.2191 ,  663.2171 ,  569.7414 , ..., 1407.1855 , 1396.9126 ,\n",
       "        1389.5471 ],\n",
       "       [ 832.0955 ,  790.24   ,  725.3345 , ..., 1400.2191 , 1383.1841 ,\n",
       "        1370.933  ],\n",
       "       ...,\n",
       "       [1867.2922 , 1865.6664 , 1863.2028 , ...,  570.8708 ,  493.51477,\n",
       "         436.83463],\n",
       "       [1867.3635 , 1865.3616 , 1862.2352 , ...,  684.87854,  585.51215,\n",
       "         498.68124],\n",
       "       [1868.0181 , 1865.0441 , 1861.9004 , ...,  797.0461 ,  715.97205,\n",
       "         623.40985]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>topo_smoothed</span></div><div class='xr-var-dims'>(y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>585.5 530.5 436.3 ... 667.4 612.1</div><input id='attrs-4e280cd5-0ada-45e1-b4cc-1b50d40174eb' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-4e280cd5-0ada-45e1-b4cc-1b50d40174eb' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-bbaf0da4-f3e8-45af-b540-a0ae2e16365a' class='xr-var-data-in' type='checkbox'><label for='data-bbaf0da4-f3e8-45af-b540-a0ae2e16365a' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>m</dd><dt><span>long_name :</span></dt><dd>DEM topography smoothed with radius: 3e+02 m</dd></dl></div><div class='xr-var-data'><pre>array([[ 585.5164 ,  530.51733,  436.34274, ..., 1420.8114 , 1405.8021 ,\n",
       "        1399.928  ],\n",
       "       [ 679.80896,  631.1107 ,  543.54083, ..., 1417.3423 , 1398.886  ,\n",
       "        1391.2009 ],\n",
       "       [ 779.726  ,  740.5945 ,  667.6581 , ..., 1415.3445 , 1391.582  ,\n",
       "        1380.8159 ],\n",
       "       ...,\n",
       "       [1866.6481 , 1865.2585 , 1862.7579 , ...,  578.67596,  515.6842 ,\n",
       "         471.65384],\n",
       "       [1866.6215 , 1864.9573 , 1862.1144 , ...,  669.5512 ,  599.1168 ,\n",
       "         547.2646 ],\n",
       "       [1866.6924 , 1864.8212 , 1861.7565 , ...,  739.6079 ,  667.3558 ,\n",
       "         612.08875]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>topo_valid_mask</span></div><div class='xr-var-dims'>(y, x)</div><div class='xr-var-dtype'>int8</div><div class='xr-var-preview xr-preview'>1 1 1 1 1 1 1 1 ... 1 1 1 1 1 1 1 1</div><input id='attrs-33dd9982-102d-4396-90c1-9b0711e4fdd4' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-33dd9982-102d-4396-90c1-9b0711e4fdd4' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8485e7be-4afc-4d2a-91db-e373ebe1287c' class='xr-var-data-in' type='checkbox'><label for='data-8485e7be-4afc-4d2a-91db-e373ebe1287c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>-</dd><dt><span>long_name :</span></dt><dd>DEM validity mask according to geotiff input (1-0)</dd></dl></div><div class='xr-var-data'><pre>array([[1, 1, 1, ..., 1, 1, 1],\n",
       "       [1, 1, 1, ..., 1, 1, 1],\n",
       "       [1, 1, 1, ..., 1, 1, 1],\n",
       "       ...,\n",
       "       [1, 1, 1, ..., 1, 1, 1],\n",
       "       [1, 1, 1, ..., 1, 1, 1],\n",
       "       [1, 1, 1, ..., 1, 1, 1]], dtype=int8)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>glacier_mask</span></div><div class='xr-var-dims'>(y, x)</div><div class='xr-var-dtype'>int8</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-877934fd-c537-4a04-9910-cb20df5c0787' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-877934fd-c537-4a04-9910-cb20df5c0787' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-30343a6b-e3ec-40fa-bb62-b3b104d601ef' class='xr-var-data-in' type='checkbox'><label for='data-30343a6b-e3ec-40fa-bb62-b3b104d601ef' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>-</dd><dt><span>long_name :</span></dt><dd>Glacier mask</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=int8)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>glacier_ext</span></div><div class='xr-var-dims'>(y, x)</div><div class='xr-var-dtype'>int8</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-91d1142d-b57e-463f-a85e-3f3e5db32ccb' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-91d1142d-b57e-463f-a85e-3f3e5db32ccb' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-ccb5edab-9d25-4d03-8fe1-0ac68c990c67' class='xr-var-data-in' type='checkbox'><label for='data-ccb5edab-9d25-4d03-8fe1-0ac68c990c67' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>-</dd><dt><span>long_name :</span></dt><dd>Glacier external boundaries</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=int8)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>consensus_ice_thickness</span></div><div class='xr-var-dims'>(y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-c3ed63bc-88ec-4028-a3cf-55899f42d078' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-c3ed63bc-88ec-4028-a3cf-55899f42d078' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-dfafbee4-e4cd-401b-83cd-8ccb4c7863f3' class='xr-var-data-in' type='checkbox'><label for='data-dfafbee4-e4cd-401b-83cd-8ccb4c7863f3' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>m</dd><dt><span>long_name :</span></dt><dd>Ice thickness from the consensus estimate</dd><dt><span>base_url :</span></dt><dd>https://cluster.klima.uni-bremen.de/~fmaussion/icevol/composite/</dd></dl></div><div class='xr-var-data'><pre>array([[nan, nan, nan, ..., nan, nan, nan],\n",
       "       [nan, nan, nan, ..., nan, nan, nan],\n",
       "       [nan, nan, nan, ..., nan, nan, nan],\n",
       "       ...,\n",
       "       [nan, nan, nan, ..., nan, nan, nan],\n",
       "       [nan, nan, nan, ..., nan, nan, nan],\n",
       "       [nan, nan, nan, ..., nan, nan, nan]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>millan_ice_thickness</span></div><div class='xr-var-dims'>(y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-08c61156-bf2e-455d-8d26-e3eeaf55af32' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-08c61156-bf2e-455d-8d26-e3eeaf55af32' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-16b9b2c5-728d-4d21-8e1c-50251e225597' class='xr-var-data-in' type='checkbox'><label for='data-16b9b2c5-728d-4d21-8e1c-50251e225597' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>m</dd><dt><span>long_name :</span></dt><dd>Ice thickness from Millan et al. 2022</dd><dt><span>data_source :</span></dt><dd>RGI-8.1_2021July09</dd></dl></div><div class='xr-var-data'><pre>array([[        nan,         nan,         nan, ...,  58.248283 ,\n",
       "         59.66584  ,  64.56927  ],\n",
       "       [        nan,         nan,         nan, ...,  26.359922 ,\n",
       "         32.933975 ,  49.64755  ],\n",
       "       [        nan,         nan,         nan, ...,   5.2576118,\n",
       "          3.2674696,  13.248252 ],\n",
       "       ...,\n",
       "       [312.84695  , 286.25818  , 269.75522  , ...,         nan,\n",
       "                nan,         nan],\n",
       "       [293.789    , 253.95651  , 243.43933  , ...,         nan,\n",
       "                nan,         nan],\n",
       "       [235.2894   , 196.90355  , 193.44304  , ...,         nan,\n",
       "                nan,         nan]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>millan_v</span></div><div class='xr-var-dims'>(y, x)</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-56309ecd-2be1-476d-bb92-19646afe586c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-56309ecd-2be1-476d-bb92-19646afe586c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d44d2232-e097-4fcc-a7e0-e5adb2f7b674' class='xr-var-data-in' type='checkbox'><label for='data-d44d2232-e097-4fcc-a7e0-e5adb2f7b674' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>m</dd><dt><span>long_name :</span></dt><dd>Ice velocity from Millan et al. 2022</dd><dt><span>data_source :</span></dt><dd>RGI-8.1_2021July01</dd></dl></div><div class='xr-var-data'><pre>array([[  0.      ,   0.      ,   0.      , ...,  23.739285,  23.856474,\n",
       "         23.549473],\n",
       "       [  0.      ,   0.      ,   0.      , ...,  16.669441,  17.779236,\n",
       "         16.21056 ],\n",
       "       [  0.      ,   0.      ,   0.      , ...,   9.96451 ,  13.657956,\n",
       "         11.023152],\n",
       "       ...,\n",
       "       [157.32738 ,  44.86963 ,  55.800674, ...,   0.      ,   0.      ,\n",
       "          0.      ],\n",
       "       [109.21127 ,  58.944916,  33.205807, ...,   0.      ,   0.      ,\n",
       "          0.      ],\n",
       "       [ 60.77322 ,  29.05252 ,  36.97415 , ...,   0.      ,   0.      ,\n",
       "          0.      ]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>millan_vx</span></div><div class='xr-var-dims'>(y, x)</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-5c2293fb-f51b-4ae4-b3c1-dae07609479c' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-5c2293fb-f51b-4ae4-b3c1-dae07609479c' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-595056d1-6e86-40f1-93d7-b507eb00a479' class='xr-var-data-in' type='checkbox'><label for='data-595056d1-6e86-40f1-93d7-b507eb00a479' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>m</dd><dt><span>long_name :</span></dt><dd>Ice velocity in map x direction from Millan et al. 2022</dd><dt><span>data_source :</span></dt><dd>RGI-8.1_2021July01</dd></dl></div><div class='xr-var-data'><pre>array([[  0.       ,   0.       ,   0.       , ...,  14.067449 ,\n",
       "         15.626997 ,   9.484013 ],\n",
       "       [  0.       ,   0.       ,   0.       , ...,   4.3050795,\n",
       "          9.61807  ,   6.7231874],\n",
       "       [  0.       ,   0.       ,   0.       , ...,  -1.5701752,\n",
       "          6.55792  ,   4.9475317],\n",
       "       ...,\n",
       "       [109.41435  ,  34.519325 ,  55.31455  , ...,   0.       ,\n",
       "          0.       ,   0.       ],\n",
       "       [-83.644196 ,   3.1862   ,  30.698572 , ...,   0.       ,\n",
       "          0.       ,   0.       ],\n",
       "       [ 19.286077 ,  -6.3201256,  17.99883  , ...,   0.       ,\n",
       "          0.       ,   0.       ]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>millan_vy</span></div><div class='xr-var-dims'>(y, x)</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-b70da7e3-67a2-45c6-9eba-259a6cda2e63' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-b70da7e3-67a2-45c6-9eba-259a6cda2e63' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f9612970-c45a-484c-80bf-e1d2f585aa3e' class='xr-var-data-in' type='checkbox'><label for='data-f9612970-c45a-484c-80bf-e1d2f585aa3e' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>m</dd><dt><span>long_name :</span></dt><dd>Ice velocity in map y direction from Millan et al. 2022</dd><dt><span>data_source :</span></dt><dd>RGI-8.1_2021July01</dd></dl></div><div class='xr-var-data'><pre>array([[  0.       ,   0.       ,   0.       , ..., -19.122252 ,\n",
       "        -18.025768 , -21.555305 ],\n",
       "       [  0.       ,   0.       ,   0.       , ..., -16.10393  ,\n",
       "        -14.953059 , -14.7506275],\n",
       "       [  0.       ,   0.       ,   0.       , ...,  -9.84002  ,\n",
       "        -11.980544 ,  -9.850473 ],\n",
       "       ...,\n",
       "       [113.050446 ,  28.665304 ,  -7.349542 , ...,   0.       ,\n",
       "          0.       ,   0.       ],\n",
       "       [-70.21931  , -58.858738 , -12.657937 , ...,   0.       ,\n",
       "          0.       ,   0.       ],\n",
       "       [-57.631863 , -28.356745 , -32.297523 , ...,   0.       ,\n",
       "          0.       ,   0.       ]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>hugonnet_dhdt</span></div><div class='xr-var-dims'>(y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>-0.0005632 -9.848e-05 ... 0.004648</div><input id='attrs-82ac62d9-1b33-44d5-bac9-da77164333ba' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-82ac62d9-1b33-44d5-bac9-da77164333ba' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d31e39da-0759-44c0-b2fe-8d044d2a2c25' class='xr-var-data-in' type='checkbox'><label for='data-d31e39da-0759-44c0-b2fe-8d044d2a2c25' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>m</dd><dt><span>long_name :</span></dt><dd>dhdt (2000-2020) from Hugonnet et al. 2021</dd><dt><span>data_source :</span></dt><dd>/home/data/download/cluster.klima.uni-bremen.de/~oggm/geodetic_ref_mb_maps/dhdt/N61E007_2000-01-01_2020-01-01_dhdt.tif</dd></dl></div><div class='xr-var-data'><pre>array([[-5.6320900e-04, -9.8481723e-05, -5.6609901e-04, ...,\n",
       "        -1.3831767e+00, -1.4525334e+00, -1.5610031e+00],\n",
       "       [ 2.5778809e-03,  2.1310311e-03,            nan, ...,\n",
       "        -1.3186703e+00, -1.5128096e+00, -1.6851543e+00],\n",
       "       [ 3.5505602e-03,  4.0776148e-03,  7.3802075e-03, ...,\n",
       "        -1.0913084e+00, -1.3037287e+00, -1.3575602e+00],\n",
       "       ...,\n",
       "       [ 7.6284692e-02, -5.1296008e-01, -8.1240624e-01, ...,\n",
       "        -1.8805382e-03, -2.5451833e-03, -1.7975159e-03],\n",
       "       [ 2.0857887e-01, -4.8336223e-01, -1.1133050e+00, ...,\n",
       "         1.1470253e-03,            nan,            nan],\n",
       "       [-2.7200729e-02, -4.5498994e-01, -9.9119705e-01, ...,\n",
       "         5.7469513e-03,  4.4402881e-03,  4.6484685e-03]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>glacier_ext_erosion</span></div><div class='xr-var-dims'>(y, x)</div><div class='xr-var-dtype'>int8</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-6f6dd6a8-6f4a-4413-bcb7-b888c01e024e' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-6f6dd6a8-6f4a-4413-bcb7-b888c01e024e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a66e4fac-7e4b-4064-b3e1-67058ab5be61' class='xr-var-data-in' type='checkbox'><label for='data-a66e4fac-7e4b-4064-b3e1-67058ab5be61' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>-</dd><dt><span>long_name :</span></dt><dd>Glacier exterior with binary erosion method</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=int8)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>ice_divides</span></div><div class='xr-var-dims'>(y, x)</div><div class='xr-var-dtype'>int8</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-57099429-4659-4130-afb9-01b348faae9d' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-57099429-4659-4130-afb9-01b348faae9d' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-761f6eb5-c4af-4017-b403-2a036abe2451' class='xr-var-data-in' type='checkbox'><label for='data-761f6eb5-c4af-4017-b403-2a036abe2451' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>-</dd><dt><span>long_name :</span></dt><dd>Glacier ice divides</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=int8)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>slope</span></div><div class='xr-var-dims'>(y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.8242 0.8921 ... 0.7463 0.7007</div><input id='attrs-88da95f1-eb99-415e-828f-2a9e9738742e' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-88da95f1-eb99-415e-828f-2a9e9738742e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-a2b015da-1537-461d-99d3-b8c200d6be3b' class='xr-var-data-in' type='checkbox'><label for='data-a2b015da-1537-461d-99d3-b8c200d6be3b' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>rad</dd><dt><span>long_name :</span></dt><dd>Local slope based on smoothed topography</dd></dl></div><div class='xr-var-data'><pre>array([[0.82420784, 0.8920897 , 0.97410065, ..., 0.22710483, 0.12337482,\n",
       "        0.1037826 ],\n",
       "       [0.8217877 , 0.8919826 , 0.99096286, ..., 0.26267847, 0.14626831,\n",
       "        0.12082311],\n",
       "       [0.69949645, 0.7835894 , 0.9267669 , ..., 0.31120247, 0.1729776 ,\n",
       "        0.12457968],\n",
       "       ...,\n",
       "       [0.01377494, 0.01954414, 0.02967212, ..., 0.78783953, 0.73253155,\n",
       "        0.6646147 ],\n",
       "       [0.01647704, 0.02241334, 0.03263173, ..., 0.79416233, 0.76732904,\n",
       "        0.71270025],\n",
       "       [0.01853807, 0.02446746, 0.03451509, ..., 0.7530009 , 0.74627423,\n",
       "        0.7006636 ]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>aspect</span></div><div class='xr-var-dims'>(y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>0.528 0.638 0.7656 ... 0.7515 0.706</div><input id='attrs-f23d9ac9-5629-475e-9feb-b2e5dc95e30e' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-f23d9ac9-5629-475e-9feb-b2e5dc95e30e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-15619531-13a2-4b9e-b78f-4b0a13efb002' class='xr-var-data-in' type='checkbox'><label for='data-15619531-13a2-4b9e-b78f-4b0a13efb002' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>rad</dd><dt><span>long_name :</span></dt><dd>Local aspect based on smoothed topography</dd></dl></div><div class='xr-var-data'><pre>array([[0.5280357 , 0.63801867, 0.7655758 , ..., 1.7199816 , 2.1558092 ,\n",
       "        2.549152  ],\n",
       "       [0.46484843, 0.5754309 , 0.72276825, ..., 1.6716172 , 2.0689976 ,\n",
       "        2.4642897 ],\n",
       "       [0.47850925, 0.5905313 , 0.74922425, ..., 1.5375232 , 1.7794669 ,\n",
       "        2.1233106 ],\n",
       "       ...,\n",
       "       [1.6220999 , 1.7428269 , 1.8069654 , ..., 0.63139015, 0.62984127,\n",
       "        0.59003216],\n",
       "       [1.5574839 , 1.6675359 , 1.7232627 , ..., 0.67156464, 0.67854595,\n",
       "        0.6360695 ],\n",
       "       [1.5329125 , 1.6258909 , 1.6736066 , ..., 0.7375835 , 0.7514761 ,\n",
       "        0.7059833 ]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>slope_factor</span></div><div class='xr-var-dims'>(y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>1.123 1.071 1.016 ... 1.192 1.238</div><input id='attrs-1a6b053a-128e-47cc-b2e9-18ce11e32759' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-1a6b053a-128e-47cc-b2e9-18ce11e32759' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-7ed7680e-8ae8-483d-84b6-090d9fcb5cbe' class='xr-var-data-in' type='checkbox'><label for='data-7ed7680e-8ae8-483d-84b6-090d9fcb5cbe' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>-</dd><dt><span>long_name :</span></dt><dd>Slope factor as defined in Farinotti et al 2009</dd></dl></div><div class='xr-var-data'><pre>array([[1.1229954, 1.0709146, 1.015869 , ..., 2.433684 , 3.5096524,\n",
       "        3.8724234],\n",
       "       [1.1249785, 1.0709919, 1.0054618, ..., 2.2302077, 3.1689098,\n",
       "        3.5539393],\n",
       "       [1.2391638, 1.1575689, 1.046689 , ..., 2.014532 , 2.8655374,\n",
       "        3.489247 ],\n",
       "       ...,\n",
       "       [3.8724234, 3.8724234, 3.8724234, ..., 1.153818 , 1.2053251,\n",
       "        1.2777858],\n",
       "       [3.8724234, 3.8724234, 3.8724234, ..., 1.1482975, 1.1722251,\n",
       "        1.2253379],\n",
       "       [3.8724234, 3.8724234, 3.8724234, ..., 1.1855577, 1.191958 ,\n",
       "        1.2379248]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>dis_from_border</span></div><div class='xr-var-dims'>(y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>9.213e+03 9.143e+03 ... 1.428e+03</div><input id='attrs-ea66358d-459f-40a4-80b8-0b5d4d9513d9' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-ea66358d-459f-40a4-80b8-0b5d4d9513d9' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-5bf544c2-36be-4f0e-9abd-7260fa03d198' class='xr-var-data-in' type='checkbox'><label for='data-5bf544c2-36be-4f0e-9abd-7260fa03d198' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>m</dd><dt><span>long_name :</span></dt><dd>Distance from glacier boundaries</dd></dl></div><div class='xr-var-data'><pre>array([[9213.171 , 9142.593 , 9072.589 , ..., 5496.85  , 5532.92  ,\n",
       "        5570.5874],\n",
       "       [9141.477 , 9070.34  , 8999.774 , ..., 5402.32  , 5439.0166,\n",
       "        5477.3296],\n",
       "       [9070.34  , 8998.641 , 8927.509 , ..., 5308.028 , 5345.372 ,\n",
       "        5384.3516],\n",
       "       ...,\n",
       "       [5764.0835, 5665.0107, 5566.0073, ..., 1142.6846, 1216.201 ,\n",
       "        1293.4312],\n",
       "       [5784.4   , 5685.681 , 5587.044 , ..., 1216.201 , 1285.5201,\n",
       "        1358.816 ],\n",
       "       [5806.402 , 5708.064 , 5609.8203, ..., 1293.4312, 1358.816 ,\n",
       "        1428.3557]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>catchment_area</span></div><div class='xr-var-dims'>(y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-a75564cb-6918-47df-bdd7-4c7c5d9241c1' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-a75564cb-6918-47df-bdd7-4c7c5d9241c1' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8317050f-49f0-4e15-b04a-3fc4e2005072' class='xr-var-data-in' type='checkbox'><label for='data-8317050f-49f0-4e15-b04a-3fc4e2005072' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>m^2</dd><dt><span>long_name :</span></dt><dd>Catchment area above point</dd><dt><span>description :</span></dt><dd>This is a very crude method: just the area above the points elevation on glacier.</dd></dl></div><div class='xr-var-data'><pre>array([[nan, nan, nan, ..., nan, nan, nan],\n",
       "       [nan, nan, nan, ..., nan, nan, nan],\n",
       "       [nan, nan, nan, ..., nan, nan, nan],\n",
       "       ...,\n",
       "       [nan, nan, nan, ..., nan, nan, nan],\n",
       "       [nan, nan, nan, ..., nan, nan, nan],\n",
       "       [nan, nan, nan, ..., nan, nan, nan]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lin_mb_above_z</span></div><div class='xr-var-dims'>(y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-14259479-f0d3-492a-8074-bcdb969b32d9' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-14259479-f0d3-492a-8074-bcdb969b32d9' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3d1e4c07-f2f7-49c4-9fb1-ae17c4d0a47d' class='xr-var-data-in' type='checkbox'><label for='data-3d1e4c07-f2f7-49c4-9fb1-ae17c4d0a47d' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>kg/year</dd><dt><span>long_name :</span></dt><dd>MB above point from linear MB model, without catchments</dd><dt><span>description :</span></dt><dd>Mass balance cumulated above the altitude of thepoint, hence in unit of flux. Note that it is a coarse approximation of the real flux. The mass balance model is a simple linear functionof altitude.</dd></dl></div><div class='xr-var-data'><pre>array([[nan, nan, nan, ..., nan, nan, nan],\n",
       "       [nan, nan, nan, ..., nan, nan, nan],\n",
       "       [nan, nan, nan, ..., nan, nan, nan],\n",
       "       ...,\n",
       "       [nan, nan, nan, ..., nan, nan, nan],\n",
       "       [nan, nan, nan, ..., nan, nan, nan],\n",
       "       [nan, nan, nan, ..., nan, nan, nan]], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>oggm_mb_above_z</span></div><div class='xr-var-dims'>(y, x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>nan nan nan nan ... nan nan nan nan</div><input id='attrs-976890fa-2a6b-4a5a-996d-9347a9493dda' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-976890fa-2a6b-4a5a-996d-9347a9493dda' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b0d9e255-1cae-4d26-97f2-121814fa6c65' class='xr-var-data-in' type='checkbox'><label for='data-b0d9e255-1cae-4d26-97f2-121814fa6c65' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>kg/year</dd><dt><span>long_name :</span></dt><dd>MB above point from OGGM MB model, without catchments</dd><dt><span>description :</span></dt><dd>Mass balance cumulated above the altitude of thepoint, hence in unit of flux. Note that it is a coarse approximation of the real flux. The mass balance model is a calibrated temperature index model like OGGM.</dd></dl></div><div class='xr-var-data'><pre>array([[nan, nan, nan, ..., nan, nan, nan],\n",
       "       [nan, nan, nan, ..., nan, nan, nan],\n",
       "       [nan, nan, nan, ..., nan, nan, nan],\n",
       "       ...,\n",
       "       [nan, nan, nan, ..., nan, nan, nan],\n",
       "       [nan, nan, nan, ..., nan, nan, nan],\n",
       "       [nan, nan, nan, ..., nan, nan, nan]], dtype=float32)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-b9a429ba-519a-4612-a9cc-d9ac89c360a5' class='xr-section-summary-in' type='checkbox'  ><label for='section-b9a429ba-519a-4612-a9cc-d9ac89c360a5' class='xr-section-summary' >Indexes: <span>(2)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-index-name'><div>x</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-7e52728b-5477-4727-aae4-818f1c118b4e' class='xr-index-data-in' type='checkbox'/><label for='index-7e52728b-5477-4727-aae4-818f1c118b4e' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Float64Index([-4117.13134765625, -4016.13134765625, -3915.13134765625,\n",
       "              -3814.13134765625, -3713.13134765625, -3612.13134765625,\n",
       "              -3511.13134765625, -3410.13134765625, -3309.13134765625,\n",
       "              -3208.13134765625,\n",
       "              ...\n",
       "               5780.86865234375,  5881.86865234375,  5982.86865234375,\n",
       "               6083.86865234375,  6184.86865234375,  6285.86865234375,\n",
       "               6386.86865234375,  6487.86865234375,  6588.86865234375,\n",
       "               6689.86865234375],\n",
       "             dtype=&#x27;float64&#x27;, name=&#x27;x&#x27;, length=108))</pre></div></li><li class='xr-var-item'><div class='xr-index-name'><div>y</div></div><div class='xr-index-preview'>PandasIndex</div><div></div><input id='index-471e27fc-bce7-4cef-b23f-82a310e1b091' class='xr-index-data-in' type='checkbox'/><label for='index-471e27fc-bce7-4cef-b23f-82a310e1b091' title='Show/Hide index repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-index-data'><pre>PandasIndex(Float64Index([6847880.0, 6847779.0, 6847678.0, 6847577.0, 6847476.0, 6847375.0,\n",
       "              6847274.0, 6847173.0, 6847072.0, 6846971.0,\n",
       "              ...\n",
       "              6837982.0, 6837881.0, 6837780.0, 6837679.0, 6837578.0, 6837477.0,\n",
       "              6837376.0, 6837275.0, 6837174.0, 6837073.0],\n",
       "             dtype=&#x27;float64&#x27;, name=&#x27;y&#x27;, length=108))</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-7e8db2ab-ac48-4e14-89ab-99fb715aa18f' class='xr-section-summary-in' type='checkbox'  checked><label for='section-7e8db2ab-ac48-4e14-89ab-99fb715aa18f' class='xr-section-summary' >Attributes: <span>(7)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'><dt><span>author :</span></dt><dd>OGGM</dd><dt><span>author_info :</span></dt><dd>Open Global Glacier Model</dd><dt><span>pyproj_srs :</span></dt><dd>+proj=tmerc +lat_0=0 +lon_0=7.099 +k=0.9996 +x_0=0 +y_0=0 +datum=WGS84 +units=m +no_defs</dd><dt><span>max_h_dem :</span></dt><dd>1970.0707</dd><dt><span>min_h_dem :</span></dt><dd>88.412544</dd><dt><span>max_h_glacier :</span></dt><dd>1939.6395</dd><dt><span>min_h_glacier :</span></dt><dd>311.37354</dd></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.Dataset>\n",
       "Dimensions:                  (x: 108, y: 108)\n",
       "Coordinates:\n",
       "  * x                        (x) float32 -4.117e+03 -4.016e+03 ... 6.69e+03\n",
       "  * y                        (y) float32 6.848e+06 6.848e+06 ... 6.837e+06\n",
       "Data variables: (12/20)\n",
       "    topo                     (y, x) float32 545.2 473.4 365.1 ... 716.0 623.4\n",
       "    topo_smoothed            (y, x) float32 585.5 530.5 436.3 ... 667.4 612.1\n",
       "    topo_valid_mask          (y, x) int8 1 1 1 1 1 1 1 1 1 ... 1 1 1 1 1 1 1 1 1\n",
       "    glacier_mask             (y, x) int8 0 0 0 0 0 0 0 0 0 ... 0 0 0 0 0 0 0 0 0\n",
       "    glacier_ext              (y, x) int8 0 0 0 0 0 0 0 0 0 ... 0 0 0 0 0 0 0 0 0\n",
       "    consensus_ice_thickness  (y, x) float32 nan nan nan nan ... nan nan nan nan\n",
       "    ...                       ...\n",
       "    aspect                   (y, x) float32 0.528 0.638 0.7656 ... 0.7515 0.706\n",
       "    slope_factor             (y, x) float32 1.123 1.071 1.016 ... 1.192 1.238\n",
       "    dis_from_border          (y, x) float32 9.213e+03 9.143e+03 ... 1.428e+03\n",
       "    catchment_area           (y, x) float32 nan nan nan nan ... nan nan nan nan\n",
       "    lin_mb_above_z           (y, x) float32 nan nan nan nan ... nan nan nan nan\n",
       "    oggm_mb_above_z          (y, x) float32 nan nan nan nan ... nan nan nan nan\n",
       "Attributes:\n",
       "    author:         OGGM\n",
       "    author_info:    Open Global Glacier Model\n",
       "    pyproj_srs:     +proj=tmerc +lat_0=0 +lon_0=7.099 +k=0.9996 +x_0=0 +y_0=0...\n",
       "    max_h_dem:      1970.0707\n",
       "    min_h_dem:      88.412544\n",
       "    max_h_glacier:  1939.6395\n",
       "    min_h_glacier:  311.37354"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "with xr.open_dataset(gdir.get_filepath('gridded_data')) as ds:\n",
    "    ds = ds.load()\n",
    "# List all variables\n",
    "ds"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "bb5ca26c-3d91-447d-ac56-431b28d3075b",
   "metadata": {
    "user_expressions": []
   },
   "source": [
    "We can see there's a huge amount of data available here. Since we interested in modelling distributed mass balance, we'll take a look at the `hugonnet_dhdt` data."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "62ce9c46-8960-4fb4-b999-506791b87d3e",
   "metadata": {
    "user_expressions": []
   },
   "source": [
    "First we prepare the map to start plotting the datasets."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "2da21154-0746-4295-9078-ec6ae2097ce2",
   "metadata": {},
   "outputs": [],
   "source": [
    "smap = ds.salem.get_map(countries=False)\n",
    "smap.set_shapefile(gdir.read_shapefile('outlines'))\n",
    "smap.set_topography(ds.topo.data);"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d33fe379-8f97-47ca-82b8-c6c3a42c2cca",
   "metadata": {
    "user_expressions": []
   },
   "source": [
    "And now we plot the Hugonnet et al. (2021) geodetic mass balance data for this glacier:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "807e043a-4812-44a6-88a6-dde88ee1e929",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 900x900 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# get the axes ready\n",
    "f, ax = plt.subplots(figsize=(9, 9))\n",
    "\n",
    "smap.set_data(ds.hugonnet_dhdt)\n",
    "smap.set_cmap('RdBu')\n",
    "smap.set_plot_params(vmin=-3, vmax=3)\n",
    "smap.plot(ax=ax)\n",
    "smap.append_colorbar(ax=ax, label='dh/dt')\n",
    "\n",
    "ax.set_title('Hugonnet dh/dt');"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b0aad9ef-2081-45e7-af5a-682cbbc9010a",
   "metadata": {
    "user_expressions": []
   },
   "source": [
    "## 5.4. Creating the ML dataset"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1d201b60-d275-451c-9739-e74b65f0b737",
   "metadata": {
    "user_expressions": []
   },
   "source": [
    "We now can use the previously declared entity task to create the training dataset using all gridded data of interest for all glaciers in Scandinavia. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "1eb61c27-4362-40d2-b859-7ec9bbc7299d",
   "metadata": {},
   "outputs": [
    {
     "ename": "NameError",
     "evalue": "name 'workflow' is not defined",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mNameError\u001b[0m                                 Traceback (most recent call last)",
      "Cell \u001b[0;32mIn[1], line 1\u001b[0m\n\u001b[0;32m----> 1\u001b[0m training_data \u001b[38;5;241m=\u001b[39m \u001b[43mworkflow\u001b[49m\u001b[38;5;241m.\u001b[39mexecute_entity_task(get_gridded_features, gdirs)\n",
      "\u001b[0;31mNameError\u001b[0m: name 'workflow' is not defined"
     ]
    }
   ],
   "source": [
    "training_data = workflow.execute_entity_task(get_gridded_features, gdirs)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ae4c13b0-de07-4505-99dd-4a5501d72a5d",
   "metadata": {
    "user_expressions": []
   },
   "source": [
    "Since there are a few glaciers without the required data, we need to delete some `None` values."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "32bd0fe2-9b70-4149-87f6-ab6fd44b6651",
   "metadata": {},
   "outputs": [],
   "source": [
    "training_dict = np.delete(training_data, np.where(np.array(training_data) == None))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c0841dcc-0f73-489f-93d0-35e27aea675c",
   "metadata": {
    "user_expressions": []
   },
   "source": [
    "And then we convert the numpy array to a Python list, which then can be turned into a pandas `DataFrame`. This `DataFrame` contains all the matrices with the training data."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "b9d2de76-f9b2-4508-8987-f66d11dc937c",
   "metadata": {},
   "outputs": [],
   "source": [
    "df_training = pd.DataFrame.from_dict(training_dict.tolist())"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c185c765-e33c-4185-8b1d-c77c0990b86a",
   "metadata": {
    "user_expressions": []
   },
   "source": [
    "In order to polish it up, we set the RGI ID as the index."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "7e1dfc6e-00b0-47d0-a592-8394d2f369e1",
   "metadata": {},
   "outputs": [],
   "source": [
    "df_training.index = df_training.ID\n",
    "df_training.index.name = 'RGI_ID'\n",
    "df_training = df_training.drop(columns='ID')\n",
    "df_training.head(3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "ed0d88bd-d687-4747-8e5a-414e0f4bf77a",
   "metadata": {},
   "outputs": [],
   "source": [
    "df_training.iloc[0].topo.shape, df_training.iloc[0].snow_2D.shape,"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "7dc3b7e9-e3c2-4e9d-9648-22af5243f3c7",
   "metadata": {},
   "outputs": [],
   "source": [
    "df_training.to_csv(\"Data/df_distributed_training_raw.csv\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9b33999f-dcd8-4f1f-be0a-0f7289288dbc",
   "metadata": {},
   "source": [
    "## 5.5. Ravel version of the dataset"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "1a893a64-a694-4ce0-a7fe-d62a3e3e4333",
   "metadata": {},
   "outputs": [],
   "source": [
    "def pd_ravel(row, key):\n",
    "    res = row[key].ravel()\n",
    "    return pd.DataFrame({key: res})"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3ed8d3f9-04f8-41cf-8ca9-7562ac716c6b",
   "metadata": {},
   "source": [
    "Total number of observations:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "2890ee8c-5928-48e6-abb9-20268f5fa176",
   "metadata": {},
   "outputs": [],
   "source": [
    "res = 0\n",
    "for i in range(df_training.shape[0]):\n",
    "    df_rgi = df_training.iloc[i]\n",
    "    res += df_rgi.PDD_2D.size\n",
    "res"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "02b046ee-aa9b-4ee2-982f-5c7ab770962c",
   "metadata": {},
   "outputs": [],
   "source": [
    "df_rgi.PDD_2D.size"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "f20cb78b-9b99-4f41-9c0d-1192ed22fdc1",
   "metadata": {},
   "outputs": [],
   "source": [
    "rgi_list = []\n",
    "\n",
    "for i in range(df_training.shape[0]):\n",
    "    df_rgi = df_training.iloc[i]\n",
    "    n_tot = df_rgi.PDD_2D.size\n",
    "    print(n_tot)\n",
    "    dict_rgi = {'RGI_ID': np.repeat(df_rgi.name, n_tot)}\n",
    "    for key in df_training.columns:\n",
    "        dict_rgi[key] = df_rgi[key].ravel()\n",
    "        #print(key, df_rgi[key].ravel().size)\n",
    "    df_rgi = pd.DataFrame(dict_rgi)\n",
    "    rgi_list.append(df_rgi)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "070b8d09-9e60-455e-9409-a3ce7eb92285",
   "metadata": {},
   "outputs": [],
   "source": [
    "len(rgi_list)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "b0891626-089e-42f1-ac95-7841321ce76e",
   "metadata": {},
   "outputs": [],
   "source": [
    "df_all = pd.concat(rgi_list)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d6f73b81-3c33-47b4-b571-d3d2be878491",
   "metadata": {
    "user_expressions": []
   },
   "source": [
    "Finally, in order to avoid having to run these computationally expensive tasks every time, we save the `DataFrame` on disk to use it later on."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "2f875cf4-03f0-4e0f-8686-0baf1aa23bda",
   "metadata": {},
   "outputs": [],
   "source": [
    "df_all"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "cbceafc3-6637-4a6d-aa82-abae78f70ba9",
   "metadata": {},
   "source": [
    "We also filter just those columns for which we have ice. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "dc0615a3-14a3-412d-bfa9-d5f3eb7cdb7a",
   "metadata": {},
   "outputs": [],
   "source": [
    "df_all = df_all[df_all.glacier_mask==1]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "7485217c-035b-4c35-bb69-62bddf298afa",
   "metadata": {},
   "outputs": [],
   "source": [
    "df_all.to_csv('Data/df_distributed_training.csv', index=False)"
   ]
  },
  {
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