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.

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Cited articles

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Berthier, E., Vincent, C., Magnússon, E., Gunnlaugsson, À. Þ., Pitte, P., Le Meur, E., Masiokas, M., Ruiz, L., Pálsson, F., Belart, J. M. C., and Wagnon, P.: Glacier topography and elevation changes derived from Pléiades sub-meter stereo images, The Cryosphere, 8, 2275–2291, https://doi.org/10.5194/tc-8-2275-2014, 2014. a
Berthier, E., Cabot, V., Vincent, C., and Six, D.: Decadal Region-Wide and Glacier-Wide Mass Balances Derived from Multi-Temporal ASTER Satellite Digital Elevation Models. Validation over the Mont-Blanc Area, Front. Earth Sci., 4, 63, https://doi.org/10.3389/feart.2016.00063, 2016. a
Bolibar, J.: ALPGM (ALpine Parameterized Glacier Model) v1.1, Zenodo, https://doi.org/10.5281/zenodo.3609136, 2020. a, b, c
Bolibar, J., Rabatel, A., Gouttevin, I., and Galiez, C.: A deep learning reconstruction of mass balance series for all glaciers in the French Alps: 1967–2015, Zenodo, https://doi.org/10.5281/zenodo.3922935, 2020a. a, b, c, d
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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.