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Abstract Glide-snow avalanches release at the soil-snow interface and are currently difficult to predict. This is mostly due to a limited understanding of the release process and a lack of data, particularly of the snowpack and underlying soil conditions prior to release. Here, we synthesize the current process understanding on the source of interfacial water—a key factor in glide-snow avalanche release—in a simple explanatory model. The model classifies days with and without glide-snow avalanche activity using thresholds applied to proxies including snow liquid water content (LWC), soil temperature, soil LWC and meteorological parameters. These proxies were measured on Dorfberg (Davos, Switzerland) in the 2021/22 to 2023/24 seasons. The best-performing thresholds for the snow, soil and meteorological time series were determined through quasi-random sampling and were in line with previous field studies. Soil temperature and snow LWC were the most relevant variables to explain avalanche occurrence. These results demonstrate the importance of combining snow, soil and meteorological data for improving the forecasting of glide-snow avalanche activity.
Fees et al. (Wed,) studied this question.