Geoscientific Model Development
Geoscientific Model Development
GMD
Articles | Volume 19, issue 14
Articles | Volume 19, issue 14
https://doi.org/10.5194/gmd-19-6497-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-19-6497-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 19, issue 14
Model description paper
 | 
17 Jul 2026
Model description paper |  | 17 Jul 2026

SNOWstorm (v1.0) – a deep-learning based model for near-surface winds and drifting snow in mountain environments

Manuel Saigger, Brigitta Goger, and Thomas Mölg

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Short summary
We present a new model to predict near-surface winds and wind-driven transport of snow in mountain regions at high resolutions. With its deep-learning based design, it is several orders of magnitude less computationally expensive compared to traditional numerical methods, while being applicable over a wide range of topographic settings and atmospheric conditions. A first application case study on a glacier in the European Alps showed good agreement with numerical simulations and observations.
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