Articles | Volume 17, issue 2
https://doi.org/10.5194/tc-17-977-2023
https://doi.org/10.5194/tc-17-977-2023
Research article
 | 
01 Mar 2023
Research article |  | 01 Mar 2023

Spatio-temporal reconstruction of winter glacier mass balance in the Alps, Scandinavia, Central Asia and western Canada (1981–2019) using climate reanalyses and machine learning

Matteo Guidicelli, Matthias Huss, Marco Gabella, and Nadine Salzmann

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Latest update: 14 Apr 2024
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Short summary
Spatio-temporal reconstruction of winter glacier mass balance is important for assessing long-term impacts of climate change. However, high-altitude regions significantly lack reliable observations, which is limiting the calibration of glaciological and hydrological models. We aim at improving knowledge on the spatio-temporal variations in winter glacier mass balance by exploring the combination of data from reanalyses and direct snow accumulation observations on glaciers with machine learning.