A high-resolution snow dataset for Switzerland (2016–2025) combining physics-based simulations and in situ observations

Oberrauch, Moritz; Cluzet, Bertrand; Magnusson, Jan; Mazzotti, Giulia; Mott, Rebecca; Quéno, Louis; Webster, Clare; Zolles, Tobias; Jonas, Tobias

doi:10.5194/tc-20-3387-2026

Articles | Volume 20, issue 6

https://doi.org/10.5194/tc-20-3387-2026

© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.

https://doi.org/10.5194/tc-20-3387-2026

© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.

Articles | Volume 20, issue 6

Research article

|

15 Jun 2026

Research article |

| 15 Jun 2026

A high-resolution snow dataset for Switzerland (2016–2025) combining physics-based simulations and in situ observations

Moritz Oberrauch, Bertrand Cluzet, Jan Magnusson, Giulia Mazzotti, Rebecca Mott, Louis Quéno, Clare Webster, Tobias Zolles, and Tobias Jonas

Data sets

A high-resolution snow dataset for Switzerland (2016–2025) combining physics-based simulations and in situ observations M. Oberrauch et al. https://doi.org/10.5281/zenodo.17313889

Model code and software

FSM2oshd (v1.1.3) R. Mott et al. https://doi.org/10.5281/zenodo.20410047

Short summary

We present a snow dataset that provides daily information on snow depth, snow amount, and meltwater for Switzerland from 2016 to 2025. It combines weather data, computer simulations, and ground observations to give the most complete picture of how snow changes over time. Because mountain snow strongly affects avalanches, floods, water resources, and ecosystems, this freely available dataset supports better understanding and decision-making in these areas.