AvaRelPro: A Novel Method for Estimating Avalanche Release Probability and Mass

Accurate and sufficient use of climate data is essential for understanding the frequency of extreme weather events and avalanche cycles. However, current approaches to estimating avalanche release probability and fracture heights often fail to fully utilize available climate data, potentially leading to inaccurate results.

Existing methods for determining fracture heights typically rely on return values of three-day snow height increases, adjusted for wind load and slope. These methods, however, overlook the properties of the old snowpack and fail to quantify the probability of fractures occurring within it. This omission may lead to misleading fracture height estimates, especially in diverse climate conditions. Furthermore, current methods often rely purely on the height of the fracture disregarding the snow density. This introduces more often then not inconsistencies in the mass balance of observed release masses and those used in avalanche models.

To address these limitations, we developed AvaRelPro, a novel method for estimating avalanche release probabilities using gridded climate data. AvaRelPro combines daily climate variables, such as snow water equivalent and air temperature, to estimate shear strength and assess snowpack stability under various conditions. Monte Carlo simulations over 2.5 million synthetic days calculate release probabilities and corresponding fracture heights, accounting for both new and old snow layers. The model also incorporates adjustments for vegetation effects, wind drift, and snowpack stability.

AvaRelPro has been tested on several well-known avalanche paths in Norway, yielding promising results. This methodology enables the combined quantification of release probability and initial release mass for specific climates, slopes, and vegetation covers. Additionally, AvaRelPro is well-suited for studies exploring how changing climatic conditions impact avalanche release probabilities.