Articles | Volume 12, issue 3
https://doi.org/10.5194/essd-12-1973-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/essd-12-1973-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
A deep learning reconstruction of mass balance series for all glaciers in the French Alps: 1967–2015
Jordi Bolibar
CORRESPONDING AUTHOR
Univ. Grenoble Alpes, CNRS, IRD, G-INP, Institut des Géosciences de l'Environnement
(IGE, UMR 5001), Grenoble, France
INRAE, UR RiverLy, Lyon-Villeurbanne, France
Antoine Rabatel
Univ. Grenoble Alpes, CNRS, IRD, G-INP, Institut des Géosciences de l'Environnement
(IGE, UMR 5001), Grenoble, France
Isabelle Gouttevin
Univ. Grenoble Alpes, Université de Toulouse, Météo-France, CNRS, CNRM, Centre
d'Études de la Neige, Grenoble, France
Clovis Galiez
Univ. Grenoble Alpes, CNRS, G-INP, LJK, Grenoble, France
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Cited
13 citations as recorded by crossref.
- Universal differential equations for glacier ice flow modelling J. Bolibar et al. 10.5194/gmd-16-6671-2023
- Detecting the impact of climate change on alpine mass movements in observational records from the European Alps M. Jacquemart et al. 10.1016/j.earscirev.2024.104886
- Evaluating the affecting factors of glacier mass balance in Tanggula Mountains using explainable machine learning and the open global glacier model Q. Xu et al. 10.1007/s11629-024-9047-4
- The Holocene history of Arsine Glacier (Western European Alps): a detailed 10Be record of oscillations driven by climate and modulated by rock avalanches M. Le Roy et al. 10.1016/j.quascirev.2025.109455
- Twentieth century temperature and snow cover changes in the French Alps J. Beaumet et al. 10.1007/s10113-021-01830-x
- EisNet: Extracting Bedrock and Internal Layers From Radiostratigraphy of Ice Sheets With Machine Learning S. Dong et al. 10.1109/TGRS.2021.3136648
- Multiproxy tree ring reconstruction of glacier mass balance: insights from Pinus cembra trees growing near Silvretta Glacier (Swiss Alps) J. Lopez-Saez et al. 10.5194/cp-20-1251-2024
- Interpreting Deep Machine Learning for Streamflow Modeling Across Glacial, Nival, and Pluvial Regimes in Southwestern Canada S. Anderson & V. Radić 10.3389/frwa.2022.934709
- Last Glacial Maximum Climate and Glacial Scale Affected by the Monsoon Inferred from Reconstructing the Tianchi Area, Changbai Mountains, Eastern China H. Zhao & W. Zhang 10.3390/app14073019
- Nonlinear sensitivity of glacier mass balance to future climate change unveiled by deep learning J. Bolibar et al. 10.1038/s41467-022-28033-0
- Artificial intelligence achieves easy-to-adapt nonlinear global temperature reconstructions using minimal local data M. Wegmann & F. Jaume-Santero 10.1038/s43247-023-00872-9
- Automated Delineation of Supraglacial Debris Cover Using Deep Learning and Multisource Remote Sensing Data S. Kaushik et al. 10.3390/rs14061352
- A deep learning reconstruction of mass balance series for all glaciers in the French Alps: 1967–2015 J. Bolibar et al. 10.5194/essd-12-1973-2020
12 citations as recorded by crossref.
- Universal differential equations for glacier ice flow modelling J. Bolibar et al. 10.5194/gmd-16-6671-2023
- Detecting the impact of climate change on alpine mass movements in observational records from the European Alps M. Jacquemart et al. 10.1016/j.earscirev.2024.104886
- Evaluating the affecting factors of glacier mass balance in Tanggula Mountains using explainable machine learning and the open global glacier model Q. Xu et al. 10.1007/s11629-024-9047-4
- The Holocene history of Arsine Glacier (Western European Alps): a detailed 10Be record of oscillations driven by climate and modulated by rock avalanches M. Le Roy et al. 10.1016/j.quascirev.2025.109455
- Twentieth century temperature and snow cover changes in the French Alps J. Beaumet et al. 10.1007/s10113-021-01830-x
- EisNet: Extracting Bedrock and Internal Layers From Radiostratigraphy of Ice Sheets With Machine Learning S. Dong et al. 10.1109/TGRS.2021.3136648
- Multiproxy tree ring reconstruction of glacier mass balance: insights from Pinus cembra trees growing near Silvretta Glacier (Swiss Alps) J. Lopez-Saez et al. 10.5194/cp-20-1251-2024
- Interpreting Deep Machine Learning for Streamflow Modeling Across Glacial, Nival, and Pluvial Regimes in Southwestern Canada S. Anderson & V. Radić 10.3389/frwa.2022.934709
- Last Glacial Maximum Climate and Glacial Scale Affected by the Monsoon Inferred from Reconstructing the Tianchi Area, Changbai Mountains, Eastern China H. Zhao & W. Zhang 10.3390/app14073019
- Nonlinear sensitivity of glacier mass balance to future climate change unveiled by deep learning J. Bolibar et al. 10.1038/s41467-022-28033-0
- Artificial intelligence achieves easy-to-adapt nonlinear global temperature reconstructions using minimal local data M. Wegmann & F. Jaume-Santero 10.1038/s43247-023-00872-9
- Automated Delineation of Supraglacial Debris Cover Using Deep Learning and Multisource Remote Sensing Data S. Kaushik et al. 10.3390/rs14061352
1 citations as recorded by crossref.
Latest update: 28 Aug 2025
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.
We present a dataset of annual glacier mass changes for all the 661 glaciers in the French Alps...
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