An Assessment of MJO Circulation Influence on Air–Sea Interactions for Improved Seasonal Rainfall Predictions over East Africa

Rainfall variability affects agriculture planning and water resource management. In extreme flood and drought events, lives and property are destroyed. This study aims to improve East Africa’s seasonal rainfall prediction by determining the impact of the standard eight Real-time Multivariate Madden–Julian Oscillation (MJO) (RMM) phases on rainfall and using sea surface temperature (SST) response to test the predictability of the March–May (MAM) and October–December (OND) main rainfall seasons over a period of 33 years (1981–2013). Pearson correlation patterns, composite maps, and regression analyses were applied, and the Brier skill score (BSS) and correlation coefficients (CC) were utilized as validation metrics. Low correspondence of rainfall to MJO 1 and MJO 2 was observed except for the months of November and December. Seasonally, MAM and OND correlation patterns with MJO 2 revealed enhanced rainfall over the highlands and insignificant correspondence over coastal areas. Conversely, enhanced MJO 8 corresponded to suppressed rainfall during the June–August season over the coast and the eastern highlands. MAM rainfall was shown to be predictable using Maritime Continent SST indices, with a BSS of 0.41, while OND rainfall was shown to be predictable using Atlantic and Maritime Continent SSTs with a BSS of 0.62. Positive and negative MJO 2 corresponded, respectively, to enhanced and suppressed rainfall during the OND season and was confirmed to be related to, respectively, a positive and negative Indian Ocean dipole (IOD). An IOD year could possibly be triggered by changes in MJO 2 amplitudes observed as early peaks between February and June.