The Land Surface as a Source of Predictability on Sub-Seasonal Time Scales

Abstract:

Land surface states, namely soil moisture and snow cover, are a potential source of predictability on time scales between those of conventional weather forecasts dominated by atmospheric initial conditions, and seasonal forecasts dominated by global ocean states. This is the same range of time scales that is the focus of the S2S (Sub-seasonal to Seasonal) Project of the World Weather and Climate Research Programmes (WWRP/WCRP). This overview will present the theory behind land-atmosphere interactions as a source of predictability, recent research results that demonstrate impacts on prediction skill, and the challenges we still face. The promise of the newly established S2S database of operational model predictions and retrospective forecasts to advance the utilization of land surface predictability will be discussed.