Prediction of natural dry-snow avalanche activity  using physics-based snowpack simulations

Mayer, Stephanie; Techel, Frank; Schweizer, Jürg; van Herwijnen, Alec

doi:https://doi.org/10.5194/nhess-23-3445-2023

Articles | Volume 23, issue 11

https://doi.org/10.5194/nhess-23-3445-2023

© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.

https://doi.org/10.5194/nhess-23-3445-2023

© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.

Articles | Volume 23, issue 11

Research article

|

09 Nov 2023

Research article |

| 09 Nov 2023

Prediction of natural dry-snow avalanche activity using physics-based snowpack simulations

Stephanie Mayer, Frank Techel, Jürg Schweizer, and Alec van Herwijnen

Data sets

Data-set for prediction of natural dry-snow avalanche activity and avalanche size using physics-based snowpack simulations S. Mayer and F. Techel https://doi.org/10.16904/envidat.425

Short summary

We present statistical models to estimate the probability for natural dry-snow avalanche release and avalanche size based on the simulated layering of the snowpack. The benefit of these models is demonstrated in comparison with benchmark models based on the amount of new snow. From the validation with data sets of quality-controlled avalanche observations and danger levels, we conclude that these models may be valuable tools to support forecasting natural dry-snow avalanche activity.