Articles | Volume 18, issue 12
https://doi.org/10.5194/tc-18-5753-2024
https://doi.org/10.5194/tc-18-5753-2024
Research article
 | 
11 Dec 2024
Research article |  | 11 Dec 2024

Exploring how Sentinel-1 wet-snow maps can inform fully distributed physically based snowpack models

Bertrand Cluzet, Jan Magnusson, Louis Quéno, Giulia Mazzotti, Rebecca Mott, and Tobias Jonas

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Latest update: 11 Jan 2025
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Short summary
We use novel wet-snow maps from Sentinel-1 to evaluate simulations of a snow-hydrological model over Switzerland. These data are complementary to available in situ snow depth observations as they capture a broad diversity of topographic conditions. Wet-snow maps allow us to detect a delayed melt onset in the model, which we resolve thanks to an improved parametrization. This paves the way to further evaluation, calibration, and data assimilation using wet-snow maps.