Articles | Volume 26, issue 11
https://doi.org/10.5194/nhess-26-5633-2026
https://doi.org/10.5194/nhess-26-5633-2026
Research article
 | 
05 Nov 2026
Research article |  | 05 Nov 2026

Comparing and validating modelled snow stability metrics

Jürg Schweizer, Benjamin Reuter, Christoph Mitterer, Fabiano Monti, and Stephanie Mayer

Viewed

Total article views: 564 (including HTML, PDF, and XML)
HTML PDF XML Total BibTeX EndNote
342 178 44 564 38 51
  • HTML: 342
  • PDF: 178
  • XML: 44
  • Total: 564
  • BibTeX: 38
  • EndNote: 51
Views and downloads (calculated since 28 Jul 2026)
Cumulative views and downloads (calculated since 28 Jul 2026)

Viewed (geographical distribution)

Total article views: 564 (including HTML, PDF, and XML) Thereof 526 with geography defined and 38 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 
Latest update: 05 Nov 2026
Download
Short summary
Avalanche forecasting increasingly relies on numerical predictions of snow stability. We present the first detailed comparison of traditional and AI-based stability metrics and validate them against avalanche observations. The metrics show a similar level of performance. Combining both process-based and data-driven metrics provides the most reliable forecasts.
Share
Altmetrics
Final-revised paper
Preprint