Climate forecast skill and teleconnections on seasonal time scales over Central Africa based on the North American Multi-Model Ensemble (NMME)

This study examines the skill of the North American Multi-Model Ensemble (NMME) seasonal precipitation forecast and the influence of tropical sea surface temperature (SST) anomalies and their teleconnections on precipitation prediction skill over Central Africa (CA). The skill is assessed for December-February (DJF), March-May (MAM), June-August (JJA), and September-November (SON) seasons, at 0-, 3-, and 6- month lead time. Results show that for all seasons and at all lead times, models used in this study have tendency to overestimate the observed SSTs over the tropical areas. The multi-model ensemble mean (MME) generally succeeds in capturing the spatial differences in the seasonal mean climatology of precipitation and clearly determines the bi-modal and uni-modal natures of observed precipitation over CA. The El Nino-Southern Oscillation 3.4 index (Nino3.4), Indian Ocean Dipole (IOD) western pole index (IODWP), and IOD eastern pole index (IODEP) teleconnections with tropical SST are well represented by the MME at all seasons and lead times with a pattern correlation coefficient (PCC) >0.6. The quality of these teleconnections decreases when the lead time increases. The Nino3.4-induced precipitation's teleconnection is better represented in MAM at all lead times, and it is found that precipitation is reinforced over northern CA during the El Nino years and weakened during the La Nina years. IODWP and IODEP teleconnections with CA precipitation are well represented in MAM and SON, with PCC > 0.8. The IODWP and IODEP could be a very good indicators to predict the increase or decrease of precipitation in CA during MAM and SON seasons.