Potentially predictable components of African summer rainfall in SST-forced GCM simulations

General circulation model (GCM) integrations forced by observed sea surface temperature (SST) represent the climate response to SST forcing as well as internal variability or "noise." Signal-to-noise analysis is used to identify the most reproducible GCM patterns of African summer precipitation related to the SST forcing. Over Africa, two of these potentially "predictable components" are associated with the precipitation of the Guinea Coast and Sahel regions and correlate well with observations. Projecting model precipitation onto the leading predictable components acts as a filter. The filtered model precipitation better reproduces observed Sahel rainfall variability on both interannual and decadal time-scales. This approach has potential use for better understanding physical mechanisms of SST forced variability and for seasonal forecasting.