Predictability Associated with Land Surface Moisture States: Studies with the NSIPP System

Abstract

Hydrologists have long speculated that soil moisture information can be used to increase skill in monthly to seasonal forecast systems. For this to be true, though, three conditions must be satisfied: (1) an imposed initial soil moisture anomaly in the forecast system must have some memory, so that it persists into the forecast period; (2) the modeled atmosphere must respond in a predictable way to the persisted anomaly; and (3) the forecast model must correctly represent both the soil moisture memory and the atmospheric response as they occur in nature. In this short paper, we review some recent work at NSIPP (NASA Seasonal-to-Interannual Prediction Project) that addresses all three conditions.