OGGM tutorials#
If you are new to jupyter notebooks or to jupyterlab, we recommend to have a look at our introduction to jupyter notebooks first!
If you are reading this from our webpage (https://oggm.org/tutorials), remember that each page displayed here is in fact a jupyter notebook! You can start an interactive version of these tutorials online with MyBinder by clicking on the “launch button” on the top right of this page (the little rocket 🚀).
Ready to go?
10 minutes tutorials#
These new tutorials are designed to illustrate one single OGGM concept at a time. They are a good way to get started with OGGM, or for returning users to learn about new features!
10 minutes to… a preprocessed directory (start with this tutorial if you are new to OGGM)
10 minutes to… a glacier change projection with GCM data
10 minutes to… OGGM as an accelerator for modelling and machine learning
10 minutes to… the new dynamical spinup in OGGM v1.6
OGGM workflow#
working_with_rgi will show you how to read glacier outline files and prepare them for a run
store_and_compress_glacierdirs: storing glacier directories for later use
deal_with_errors: dealing with errors after a run
elevation_bands_vs_centerlines: differences between “elevation band” and “centerline” flowlines
full_prepro_workflow: what’s in your preprocessed directories? A full OGGM workflow, step by step
rebuilding_the_prepro_gdirs.ipynb: Step-by-Step guide to rebuilding the preprocessed directories from scratch
Mass balance#
plot_mass_balance: fetch and plot the simulated mass-balance as well as other diagnostics
massbalance_calibration: A look into the new mass balance calibration in OGGM v1.6
massbalance_global_params: Global distribution of the mass-balance model parameters
massbalance_perturbation: Mass balance parameter perturbation experiments
Hydrological output#
hydrological_output: hydrological mass-balance output
You might find the following notebooks in OGGM-Edu interesting as well!
Dynamical runs#
run_with_a_spinup_and_gcm_data: start from a glacier state different than the RGI inventory date
dynamical_spinup: a deeper dive into the dynamical spinup for past simulations
numeric_solvers: Understand the difference between the ice dynamic solvers in OGGM
Ice thickness#
inversion: run the OGGM ice thickness inversion model with various ice parameters
observed_thickness_with_dynamic_spinup: how to create OGGM flowlines from thickness observations and dynamically initialise the model
OGGM shop and additional data#
oggm_shop: OGGM-Shop and Glacier Directories in OGGM
use_your_own_inventory: use custom glacier inventories with OGGM
ingest_gridded_data_on_flowlines: ingest gridded products such as ice velocity into OGGM (and compare them with model output)
dem_sources: create local topography maps from different DEM sources with OGGM
rgitopo_rgi6: RGI-TOPO for RGI v6.0
rgitopo_rgi7: RGI-TOPO for RGI v7.0 (new!)
Visualisation and post-processing#
distribute_flowline: compute area and thickness changes from the flowline on a 2D grid (experimental!)
where_are_the_flowlines: how to access the OGGM flowlines location before, during, and after a run.
centerlines_to_shape: compute the centerlines for a custom inventory and DEM and write them to disk
preprocessing_errors: error analysis of the global pre-processing workflow
merge_gcm_runs_and_visualize: how to merge different GCM runs into one dataset, analyse them on a regional scale and visualize with HoloViz
holoviz_intro: (not OGGM) an introduction to the HoloViz vizualisation ecosystem
Tutorials in (re-)construction#
inversion_with_frontal_ablation: a case study about ice thickness inversion with frontal ablation
kcalving_parameterization: the Oerlemans & Nick frontal ablation parameterization in OGGM
merging_glaciers: a tutorial about how to merge two or more glaciers for advancing glacier scenarios
area_length_filter: a short tutorial about how to filter spikes in the area and length outputs
Have fun learning OGGM!
Package versions used to build this documentation:
# Package versions
from oggm.utils import show_versions
print(show_versions())
# OGGM environment:
## System info:
python: 3.11.9.final.0
python-bits: 64
OS: Linux
OS-release: 6.5.0-1018-azure
machine: x86_64
processor: x86_64
## Packages info:
oggm: 1.6.2.dev35+g7489be1
numpy: 1.26.4
scipy: 1.13.0
pandas: 2.2.2
geopandas: 0.14.3
netCDF4: 1.6.5
matplotlib: 3.8.4
rasterio: 1.3.10
fiona: 1.9.6
pyproj: 3.6.1
shapely: 2.0.4
xarray: 2024.3.0
dask: 2024.4.2
salem: 0.3.11.dev1+g046b13a
OGGM git identifier: 88131bcc86418f4a7fa8f7a1d73b342feb576e98