Data Access

Presentation

The product “ice thickness distribution” is derived from the study of Millan et al. (2022). This is the first comprehensive mapping of ice thicknesses based on glacial flow velocities (cf. product “glacier surface flow velocity”), for more than 200,000 glaciers on Earth. This dataset provides a better understanding of the distribution of ice masses on Earth and can be used to initialize models of glacier evolution.

The thicknesses of the glaciers are distributed at a horizontal resolution of 50 m and are representative of the decade 2010-2020.

Map of the glacier ice thickness distribution of the Academy of Science Ice Cap, Russian Arctic. Similar data are available for all major glacial regions on Earth

Data and Methods

The glaciers mapped are based on the Randolph Glacier Inventory 6.0.

The ice thickness distribution is estimated from the surface flow velocity and the surface slope using the Shallow Ice Approximation (SIA) method. Slopes were calculated using three different digital elevation model sources, with ASTER GDEM v3 (Abrams et al., 2020), TanDEM-X (DLR, 2018) and the  ArcticDEM from Worldview (Porter et al., 2018). The inversions are calibrated using in situ ice thickness measurements from the  Glacier Thickness Database, when available.

More scientific information is available in Millan et al., 2019, doi: 10.3390/rs11212498 and Millan et al., 2022, Nature Geoscience doi.org/10.1038/s41561-021-00885-z and its supplement.

The products can be downloaded by tiles at maps.theia-land.fr

Bulk downloading is available at the Sedoo site of Observatoire Midi-Pyrénées.

Contacts

Romain Millan
Université Grenoble Alpes, CNRS, IRD | IGE
@R. Millan 

Jérémie Mouginot
Université Grenoble Alpes, CNRS | IGE
@J.Mouginot

Antoine Rabatel

Antoine Rabatel
Université Grenoble Alpes, CNRS, IRD | IGE
@A.Rabatel

Mathieu Morlighem
Dartmouth College, Hanover, USA
@M.Morlighem

References

Millan, R., Mouginot, J., Rabatel, A., & Morlighem, M. Ice velocity and thickness of the world’s glaciers. Nature Geoscience, (2022) doi: 10.1038/s41561-021-00885-z

Abrams, M., Crippen, R. & Fujisada, H. ASTER Global Digital Elevation Model 590 (GDEM) and ASTER Global Water Body Dataset (ASTWBD). 12 (2020).

DLR, German Aerospace Center. TanDEM-X – Digital Elevation Model (DEM) – Global, 90m. 592 (2018) doi:10.15489/JU28HC7PUI09.

Porter, C. et al. ArcticDEM. (2018) doi:10.7910/DVN/OHHUKH.