Scientists improve the accuracy of weather and climate models

Scientists from EPFL and the WSL Institute for Snow and Avalanche Research SLF have developed a program that improves the accuracy of a widely used weather forecasting model by incorporating surface phenomena that weren't previously taken into account. Given the challenges associated with climate change and the energy transition, it's essential for weather and climate forecasters to be able to accurately predict what happens to snowfall. But most forecasting models used today don't factor in certain aspects of snow - and therefore lack accuracy. For instance, many of them model snow cover as a single layer when, in fact, it's known that every snowfall will create a separate layer with separate properties. For over 20 years, SLF and EPFL have been further developing a software program called SNOWPACK, which describes complex, snow-related processes. These include the albedo effect, which is the reflection of solar radiation on the snow cover; sublimation, which occurs when ice transitions directly to a vapor state upon contact with dry air; the insulating properties of snow; surface-level snow clouds; and blowing snow near the ground. SNOWPACK is a sophisticated program used worldwide to predict for example avalanches or calculate present or future snow water resources.