Articles | Volume 12, issue 3
Earth Syst. Sci. Data, 12, 1973–1983, 2020
https://doi.org/10.5194/essd-12-1973-2020
Earth Syst. Sci. Data, 12, 1973–1983, 2020
https://doi.org/10.5194/essd-12-1973-2020

Data description paper 03 Sep 2020

Data description paper | 03 Sep 2020

A deep learning reconstruction of mass balance series for all glaciers in the French Alps: 1967–2015

Jordi Bolibar et al.

Data sets

A deep learning reconstruction of mass balance series for all glaciers in the French Alps: 1967-2015 Jordi Bolibar, Antoine Rabatel, Isabelle Gouttevin and Clovis Galiez https://doi.org/10.5281/zenodo.3925378

Model code and software

ALpine Parameterized Glacier Model (ALPGM) v1.2 Jordi Bolibar https://doi.org/10.5281/zenodo.3609136

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Short summary
We present a dataset of annual glacier mass changes for all the 661 glaciers in the French Alps for the 1967–2015 period, reconstructed using deep learning (i.e. artificial intelligence). We estimate an average annual mass loss of –0.69 ± 0.21 m w.e., the highest being in the Chablais, Ubaye and Champsaur massifs and the lowest in the Mont Blanc, Oisans and Haute Tarentaise ranges. This dataset can be of interest to hydrology and ecology studies on glacierized catchments in the French Alps.