Articles | Volume 25, issue 4
https://doi.org/10.5194/nhess-25-1331-2025
https://doi.org/10.5194/nhess-25-1331-2025
Research article
 | 
08 Apr 2025
Research article |  | 08 Apr 2025

Assessing the performance and explainability of an avalanche danger forecast model

Cristina Pérez-Guillén, Frank Techel, Michele Volpi, and Alec van Herwijnen

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Cited articles

Ancey, C., Gervasoni, C., and Meunier, M.: Computing extreme avalanches, Cold Reg. Sci. Technol., 39, 161–180, https://doi.org/10.1016/j.coldregions.2004.04.004, 2004. a
Badoux, A., Andres, N., Techel, F., and Hegg, C.: Natural hazard fatalities in Switzerland from 1946 to 2015, Nat. Hazards Earth Syst. Sci., 16, 2747–2768, https://doi.org/10.5194/nhess-16-2747-2016, 2016. a
Birkeland, K. W., van Herwijnen, A., Reuter, B., and Bergfeld, B.: Temporal changes in the mechanical properties of snow related to crack propagation after loading, Cold Reg. Sci. Technol., 159, 142–152, https://doi.org/10.1016/j.coldregions.2018.11.007, 2019. a
Breiman, L.: Random forests, Mach. Learn., 45, 5–32, https://doi.org/10.1023/A:1010933404324, 2001. a
Bründl, M., Etter, H.-J., Steiniger, M., Klingler, Ch., Rhyner, J., and Ammann, W. J.: IFKIS – a basis for managing avalanche risk in settlements and on roads in Switzerland, Nat. Hazards Earth Syst. Sci., 4, 257–262, https://doi.org/10.5194/nhess-4-257-2004, 2004. a
Short summary
This study assesses the performance and explainability of a random-forest classifier for predicting dry-snow avalanche danger levels during initial live testing. The model achieved ∼ 70 % agreement with human forecasts, performing equally well in nowcast and forecast modes, while capturing the temporal dynamics of avalanche forecasting. The explainability approach enhances the transparency of the model's decision-making process, providing a valuable tool for operational avalanche forecasting.
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