Analysis of snow-free vegetation and bare soil albedos and application to numerical weather prediction

Land surface albedo is considered to be a fundamental quantity for accurate assessment of the surface energy budget. Whereas satellite products usually provide total surface albedo, land surface models often require a separation of snow-free surface albedos of the vegetation canopy and the underlying bare soil. Visible and near infrared vegetation and bare soil albedos are here retrieved from a decade of MODIS data at global scale by using a Kalman-filter-based method. The retrieved quantities show good agreement with those derived in previous studies. The main advantage of the proposed method over other approaches is that it provides albedo components efficiently throughout the year, thus allowing the seasonal cycles to be captured. In a second step, the snow-free vegetation and bare soil albedos derived from the satellite surface albedo product are exploited to evaluate the value added of the use of satellite albedo in Numerical Weather Prediction (NWP) models.