Probabilistic Estimates of Fractional Snow Cover Area in Mountainous Terrain

This study investigates probabilistic estimates of fractional Snow Cover Area (fSCA) in mountainous terrain, aiming to bridge the gap between mechanistic hydrological models and operational remote sensing measurements. To capture the spatial variability of snow cover, we generate high-resolution ensemble meteorological forcing datasets from in-situ measurements, employing locally weighted regression and random forest methods. We then discretize a physically-based hydrological model tailored for mountainous terrain, incorporating the dominant factors influencing snow cover. Subsequently, fluxes from an intermediate complexity snowpack model are utilized to simulate fSCA, which we evaluate against an operational data source. This research is a progressive step toward integrating ensemble data assimilation techniques, with the goal of improving hydrological forecast performance.