Working with the RGI files#

The glacier outlines obtained from the Randolph Glacier Inventory are the reference dataset for global and regional applications in OGGM. The current version is V6, and OGGM ships with a slightly modified version which we called 62.

Download the glacier outlines#

To download this version, simply do:

# this might take a couple of minutes!
from oggm import utils
utils.get_rgi_dir(version='62')  # path to the data after download

'/github/home/OGGM/rgi/RGIV62'

Access a region file#

The RGI is divided in 19 regions (and many more sub-regions, not plotted here):

rgi-map Source: the RGI consortium

fr = utils.get_rgi_region_file(11, version='62')  # Central Europe

The RGI region files are shapefiles, a vector format commonly used in GIS applications. The library of choice to read shapefiles in python is geopandas:

import geopandas as gpd
gdf = gpd.read_file(fr)

The RGI files and their attributes#

The gdf variable is a GeoDataFrame, i.e. you can use most of the tools you know from pandas’ DataFrames:

len(gdf)

3927

gdf.head()
RGIId GLIMSId BgnDate EndDate CenLon CenLat O1Region O2Region Area Zmin ... Lmax Status Connect Form TermType Surging Linkages Name check_geom geometry
0 RGI60-11.00001 G013599E47495N 20030799 20030999 13.5987 47.4949 11 1 0.122 2191 ... 461 0 0 0 0 9 9 NaN NaN POLYGON ((13.60035 47.49330, 13.59995 47.49332...
1 RGI60-11.00002 G013614E47485N 20030799 20030999 13.6135 47.4845 11 1 2.292 2203 ... 1853 0 0 0 0 9 9 NaN NaN POLYGON ((13.60638 47.47578, 13.60599 47.47579...
2 RGI60-11.00003 G013596E47484N 20030799 20030999 13.5960 47.4835 11 1 0.851 2280 ... 1140 0 0 0 0 9 9 NaN NaN POLYGON ((13.59765 47.47613, 13.59726 47.47614...
3 RGI60-11.00004 G013583E47481N 20030799 20030999 13.5829 47.4807 11 1 0.053 2319 ... 382 0 0 0 0 9 9 NaN NaN POLYGON ((13.58283 47.47969, 13.58243 47.47971...
4 RGI60-11.00005 G013603E47477N 20030799 20030999 13.6026 47.4774 11 1 0.057 2656 ... 202 0 0 0 0 9 9 NaN NaN POLYGON ((13.60076 47.47519, 13.60036 47.47521...

5 rows × 24 columns

gdf[['Area']].plot(kind='hist', bins=100, logy=True);
../../_images/working_with_rgi_15_0.png 
gdf[['Aspect']].plot(kind='hist', bins=45);
../../_images/working_with_rgi_16_0.png

Selecting glaciers per attribute#

You may want to select all glaciers in the subregion 2 (Pyrenees):

gdf_sel = gdf.loc[gdf.O2Region == '2']

'Glacier area in the Pyrenees: {} km2'.format(gdf_sel.Area.sum())

'Glacier area in the Pyrenees: 3.183 km2'

Selecting glaciers in a basin#

Let’s use a file shipped with OGGM for a start:

path = utils.get_demo_file('rofental_hydrosheds.shp')
basin = gpd.read_file(path)

basin.plot();
../../_images/working_with_rgi_24_0.png

And select all glaciers within this shape:

import shapely.geometry as shpg
in_bas = [basin.geometry.contains(shpg.Point(x, y))[0] for
          (x, y) in zip(gdf.CenLon, gdf.CenLat)]
gdf_sel = gdf.loc[in_bas]

ax = basin.plot();
gdf_sel.plot(ax=ax, edgecolor='k');
../../_images/working_with_rgi_27_0.png

Select glaciers by their ID#

Each glacier in the RGI has a unique ID. It is sometimes difficult to find out which one, but some tools can help you out. For example, the GLIMS viewer allows to select glaciers and then see their ID. For example, the Aletsch Glacier in the Swiss Alps:

al = utils.get_rgi_glacier_entities(['RGI60-11.01450'], version='62')
al.plot(edgecolor='k');
../../_images/working_with_rgi_30_0.png

Use the RGI files to start an OGGM run#

RGI files can be given as input to OGGM to make a run:

from oggm import cfg, workflow, tasks
cfg.initialize(logging_level='WARNING')
cfg.PARAMS['continue_on_error'] = True
cfg.PARAMS['use_multiprocessing'] = True
cfg.PARAMS['border'] = 80
cfg.PATHS['working_dir'] = utils.gettempdir(dirname='OGGM-Rofental', reset=True)

# Go - get the pre-processed glacier directories
base_url = 'https://cluster.klima.uni-bremen.de/~oggm/gdirs/oggm_v1.6/L3-L5_files/2023.1/elev_bands/W5E5'
gdirs = workflow.init_glacier_directories(gdf_sel, prepro_base_url=base_url, from_prepro_level=5)

2023-03-10 20:16:03: oggm.cfg: Reading default parameters from the OGGM `params.cfg` configuration file.
2023-03-10 20:16:03: oggm.cfg: Multiprocessing switched OFF according to the parameter file.
2023-03-10 20:16:03: oggm.cfg: Multiprocessing: using all available processors (N=2)
2023-03-10 20:16:03: oggm.cfg: PARAMS['continue_on_error'] changed from `False` to `True`.
2023-03-10 20:16:03: oggm.cfg: Multiprocessing switched ON after user settings.
2023-03-10 20:16:03: oggm.workflow: init_glacier_directories from prepro level 5 on 54 glaciers.
2023-03-10 20:16:03: oggm.workflow: Execute entity tasks [gdir_from_prepro] on 54 glaciers

workflow.execute_entity_task(tasks.run_random_climate, gdirs, nyears=100,
                             y0=2009, halfsize=10, output_filesuffix='_2000')
ds2000 = utils.compile_run_output(gdirs, input_filesuffix='_2000')

2023-03-10 20:16:08: oggm.workflow: Execute entity tasks [run_random_climate] on 54 glaciers
2023-03-10 20:16:21: oggm.utils: Applying global task compile_run_output on 54 glaciers
2023-03-10 20:16:21: oggm.utils: Applying compile_run_output on 54 gdirs.

ds2000.sum(dim='rgi_id').volume.plot();
../../_images/working_with_rgi_35_0.png

This shows the summed up volume evolution of all glaciers of the Rofental basin.

What’s next?#