Geoscientific Model Development
Geoscientific Model Development
GMD
Articles | Volume 18, issue 5
Articles | Volume 18, issue 5
https://doi.org/10.5194/gmd-18-1829-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-18-1829-2025
© Author(s) 2025. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 18, issue 5
Development and technical paper
 | 
17 Mar 2025
Development and technical paper |  | 17 Mar 2025

Towards deep-learning solutions for classification of automated snow height measurements (CleanSnow v1.0.2)

Jan Svoboda, Marc Ruesch, David Liechti, Corinne Jones, Michele Volpi, Michael Zehnder, and Jürg Schweizer

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Short summary
Accurately measuring snow height is key for modeling approaches in climate science, snow hydrology, and avalanche forecasting. Erroneous snow height measurements often occur when snow height is low or changes, for instance during snowfall in summer. We prepare a new benchmark dataset with annotated snow height data and demonstrate how to improve the measurement quality using modern deep-learning approaches. Our approach can be easily implemented in a data pipeline for snow modeling.
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