Articles | Volume 22, issue 6
https://doi.org/10.5194/nhess-22-2031-2022
https://doi.org/10.5194/nhess-22-2031-2022
Research article
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14 Jun 2022
Research article | Highlight paper |  | 14 Jun 2022

Data-driven automated predictions of the avalanche danger level for dry-snow conditions in Switzerland

Cristina Pérez-Guillén, Frank Techel, Martin Hendrick, Michele Volpi, Alec van Herwijnen, Tasko Olevski, Guillaume Obozinski, Fernando Pérez-Cruz, and Jürg Schweizer

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Latest update: 23 May 2024
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Executive editor
The paper could have a strong impact in the entire Alpine region, where avalanche forecasting is a critical issue to manage
Short summary
A fully data-driven approach to predicting the danger level for dry-snow avalanche conditions in Switzerland was developed. Two classifiers were trained using a large database of meteorological data, snow cover simulations, and danger levels. The models performed well throughout the Swiss Alps, reaching a performance similar to the current experience-based avalanche forecasts. This approach shows the potential to be a valuable supplementary decision support tool for assessing avalanche hazard.
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