A high-resolution snow dataset for Switzerland (2016–2025) combining physics-based simulations and in situ observations

Abstract. We present a high-resolution snow dataset that provides daily estimates of snow depth, snow water equivalent, snow cover fraction, and snowmelt runoff for Switzerland and hydrologically connected bordering regions, covering water years 2016 to 2025. The dataset is based on fully distributed simulations at 250 m resolution using the multi-layer, physics-based snow model FSM2OSHD, operated by the Swiss Operational Snow Hydrological Service. To capture the high spatial heterogeneity of snow cover dynamics in complex mountainous terrain, the modeling framework combines dedicated dynamical and statistical downscaling of numerical weather prediction data with the upscaling of hyper-resolution terrain, forest, and light-availability datasets, explicitly accounting for subgrid variability. The particle filter-based assimilation of in situ snow depth observations from 444 monitoring stations across the domain dynamically corrects spatiotemporal error patterns in the meteorological forcing data. This approach ensures consistent input data quality over the entire 10-year period and mitigates potential discontinuities caused by changes within the numerical weather prediction system. Example applications demonstrate the dataset’s ability to capture regional and interannual variability of snow water resources, snow cover extent, and snow duration. With 10 years of physically consistent estimates at high spatial and temporal resolution, this dataset represents, to our knowledge, the most accurate and comprehensive record of snow cover dynamics for Switzerland to date. It expands the snow data record for the European Alps and bridges the gap between coarse global reanalyses and detailed local observations. The dataset is publicly and freely available providing a valuable resource for a wide range of scientific and applied studies in hydrology, ecology, climate, and cryospheric research.