Seasonal predictability and spatial coherence of rainfall

This study examines space-time characteristics of seasonal rainfall predictability in a tropical region, by analyzing observed data and model simulations over Senegal. Predictability is analyzed in terms of the spatial coherence of observed interannual variability at the station scale, and within-ensemble coherence of general circulation model (GCM) simulations with observed sea surface temperatures (SSTs) prescribed. Seasonal-mean rainfall anomalies are decomposed in terms of daily rainfall frequency, and daily mean intensity. The observed spatial coherence is computed from a 13-station network of daily rainfall during the July–September season 1961–98, in terms of (a) interannual variability of a standardized anomaly index (i.e. the average of the normalized anomalies of each station), (b) the external variance (i.e. the fraction of common variance amongst stations) and, (c) the number of spatio-temporal degrees of freedom. Spatial coherence of interannual anomalies across stations is found to be much stronger for seasonal rainfall amount and daily occurrence frequency, compared to daily mean intensity of rainfall. Combinatorial analysis of the station observations suggests that, for occurrence and seasonal amount, the empirical number of spatial degrees of freedom is largely insensitive to the number of stations considered, and is between 3 and 4 for Senegal. For daily mean intensity, by contrast, each station is found to convey almost independent information, and the number of degrees of freedom would be expected to increase for a denser network of stations. The GCM estimates of potential predictability and skill associated with the SST forcing are found to be remarkably consistent with 3 those inferred from the observed spatial coherence: there is a moderate-to-strong skill at reproducing the interannual variations of seasonal amounts and rainfall occurrence whereas the skill is weak for the mean intensity of rainfall. Over Senegal during July-September, we conclude that (a) regional-scale seasonal amount and rainfall occurrence frequency are predictable from SST, (b) daily mean intensity of rainfall is spatially incoherent and largely unpredictable at regional scale, and (c) point-score estimates of seasonal rainfall predictability and skill are subject to large sampling variability.