Seasonal predictability of summer north african subtropical high in operational climate prediction models

Abstract

Abstract Seasonal predictability of summer North African Subtropical High (NASH) is investigated in this study by utilizing the hindcast data from four operational climate prediction models, including BCC_CSM1.1(m), NCEP CFSv2, ECMWF System 4, and JMA CPSv2. By reconstructing indices describing the variations in intensity, area, eastern boundary and ridge line of the NASH, it is shown that the intensity and area indices present high prediction skills compared to the relatively low prediction skills of position indices. The multi-model ensemble (MME) mean, calculated as the arithmetic average of the four models, presents relatively higher and stabler skills than individual models. Further investigation indicates that the prediction skill of the NASH is largely reliant on the models’ ability in reproducing the relationship between the NASH indices and the tropical-to-subtropical sea surface temperature (SST) anomalies associated with the El Niño/Southern Oscillation (ENSO). The pattern of atmospheric circulation anomaly over the North Africa in response to ENSO is well captured by the models, which suggests the dominant source of predictability of the NASH.