4. Summary and conclusions
In this study, we brought forward previously published knowledge of wet-snow avalanche forecasting by focusing on spatial mapping over complex topography to improve wet-snow avalanche forecasting. Spatial probability maps for wet-snow avalanching are based on proba-bility density functions of two meteorological parameters associated with observed wet-snow avalanches. Each probability density function (pdf) was derived from high-quality avalanche observations over a 6-year period recorded with time-lapse photography and from nearby measured airtemperature andSWradiation.Weuse large-scalemeteo-rological forecast data of air temperature and SW radiation covering Switzerland to obtain the spatial probability maps for wet-snow avalanching. Incident SW radiation was corrected for subgrid topo-graphicinfluences.Wealsoincludeda pdfformeanslopesofpreviously
observed avalanches during the current wet-snow avalanche cycle. Our spatial maps show that a simple approach works reasonably well; typi-cal terrain related patterns were clearly captured and even large-scale spatial patterns were realistic (Fig. 6). Our method thus may form a step toward automatic spatial wet-snow avalanche forecasts which would facilitate current avalanche forecasting practices, still in part based on experience.