Articles | Volume 19, issue 2
https://doi.org/10.5194/tc-19-805-2025
https://doi.org/10.5194/tc-19-805-2025
Research article
 | 
21 Feb 2025
Research article |  | 21 Feb 2025

A minimal machine-learning glacier mass balance model

Marijn van der Meer, Harry Zekollari, Matthias Huss, Jordi Bolibar, Kamilla Hauknes Sjursen, and Daniel Farinotti

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This preprint is open for discussion and under review for The Cryosphere (TC).
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Cited articles

Adams, P.: Glossary of Glacier Mass Balance and Related Terms, prepared by the Working Group on Mass-Balance Terminology and Methods of the International Association of Cryospheric Sciences (IASC), ARCTIC, 64, 47, https://doi.org/10.14430/arctic4151, 2011. a
Anilkumar, R., Bharti, R., Chutia, D., and Aggarwal, S. P.: Modelling point mass balance for the glaciers of the Central European Alps using machine learning techniques, The Cryosphere, 17, 2811–2828, https://doi.org/10.5194/tc-17-2811-2023, 2023. a, b
Arthur, D. and Vassilvitskii, S.: K-Means++: The Advantages of Careful Seeding, Proc. Annu. ACM-SIAM Symp. on Discrete Algorithms, 8, 1027–1035, 2007. a
Azam, M. F., Wagnon, P., Berthier, E., Vincent, C., Fujita, K., and Kargel, J. S.: Review of the status and mass changes of Himalayan-Karakoram glaciers, J. Glaciol., 64, 61–74, https://doi.org/10.1017/jog.2017.86, 2018. a
Benn, D. and Evans, D. J. A.: Glaciers and Glaciation, 2nd edition, Routledge, ISBN 9781444128390, https://doi.org/10.4324/9780203785010, 2014. a
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Glacier retreat poses big challenges, making understanding how climate affects glaciers vital. But glacier measurements worldwide are limited. We created a simple machine-learning model called miniML-MB, which estimates annual changes in glacier mass in the Swiss Alps. As input, miniML-MB uses two climate variables: average temperature (May–Aug) and total precipitation (Oct–Feb). Our model can accurately predict glacier mass from 1961 to 2021 but struggles for extreme years (2022 and 2023).
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