Scenario-based wind drifted snow indication maps for site-specific operational avalanche forecasting in Iceland

Abstract. Wind speed and direction strongly influence avalanche conditions in Iceland, where wind-transported snow can rapidly accumulate in avalanche starting zones. However, operational tools for predicting the spatial distribution and magnitude of wind-driven snow accumulation remain limited. This study investigates whether the terrain-based wind shelter index can support the development of scenario-based wind-driven snow accumulation indication maps for site-specific avalanche forecasting. We analysed terrestrial laser scanning measurements from two study sites near Ísafjörður in the Westfjords of Iceland and selected five wind-driven snow events from the 2025–2026 winter season for detailed analysis. We first compared snow thickness and its changes derived from terrestrial laser scanning with continuous point measurements from an in-situ SM4 snow-depth sensor. We then calculated the wind shelter index for the observed wind conditions and fitted linear relationships between the index and measured snow-thickness changes. The fitted relationships varied among events, highlighting the influence of precipitation, wind speed, initial snow conditions, and the chronology of meteorological conditions. Based on these findings, we developed preliminary indication maps of relative wind-driven snow accumulation patterns for different wind directions. The maps can help identify potentially critical starting zones and situations in which small changes in wind direction lead to substantial changes in terrain shelter. The results demonstrate the potential of the wind shelter index as a transparent and computationally efficient basis for scenario mapping. However, the current maps should be considered a proof of concept rather than quantitative predictions of snow depth or avalanche occurrence. Further development should incorporate wind speed, precipitation, event duration, and snow availability and proceed in close collaboration with operational forecasters to evaluate the practical value of the maps.