Impact of a Multi‐Layer Snow Scheme on Near‐Surface Weather Forecasts

Abstract

Abstract Snow cover properties have a large impact on the partitioning of surface energy fluxes and thereby on near‐surface weather parameters. Snow schemes of intermediate complexity have been widely used for hydrological and climate studies, whereas their impact on typical weather forecast time scales has received less attention. A new multilayer snow scheme is implemented in the European Centre for Medium‐range Weather Forecasts Integrated Forecasting System and its impact on snow and 2‐m temperature forecasts is evaluated. The new snow scheme is evaluated offline at well‐instrumented field sites and compared to the current single‐layer scheme. The new scheme largely improves the representation of snow depth for most of the sites considered, reducing the root‐mean‐square error averaged over all sites by more than 30%. The improvements are due to a better description of snow density in thick and cold snowpacks, but also due to an improved representation of sporadic melting episodes because of the inclusion of a thin top snow layer with a low thermal inertia. The evaluation of coupled 10‐day weather forecasts shows an improved representation of snow depth at all lead times, demonstrating a positive impact at the global scale. Regarding the impact on weather parameters, the multilayer snow scheme improves the simulated minimum 2‐m temperature, by decreasing the positive bias and improving the amplitude of the diurnal cycle over snow‐covered regions. However, the increased variability of the 2‐m temperature can have a detrimental impact in regions characterized by preexisting errors in the daily mean temperature, associated with errors in cloud processes or surface albedo.

Keywords

• Snow
• numerical weather prediction
• weather forecasts
• snow‐atmosphere coupling