Articles | Volume 18, issue 1
https://doi.org/10.5194/gmd-18-193-2025
https://doi.org/10.5194/gmd-18-193-2025
Methods for assessment of models
 | 
17 Jan 2025
Methods for assessment of models |  | 17 Jan 2025

Clustering simulated snow profiles to form avalanche forecast regions

Simon Horton, Florian Herla, and Pascal Haegeli

Data sets

Clustering simulated snow profiles to form avalanche forecast regions – Code and Data Simon Horton et al. https://doi.org/10.17605/OSF.IO/4U2AZ

Model code and software

Clustering simulated snow profiles to form avalanche forecast regions – Code and Data Simon Horton et al. https://doi.org/10.17605/OSF.IO/4U2AZ

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Short summary
We present a method for avalanche forecasters to analyze patterns in snowpack model simulations. It uses fuzzy clustering to group small regions into larger forecast areas based on snow characteristics, locations, and temporal history. Tested in the Columbia Mountains in two winter seasons, it closely matched real forecast regions regions and identified major avalanche hazard patterns. This approach simplifies complex model outputs, helping forecasters make informed decisions.