New SST indices and strength of their correlation with long and short rains over East Africa at different lead times relative to some existing indices.

This study assesses the skill of existing indices and newly introduced sea surface temperature (SST) indices in predicting rainfall over East Africa (EA) during short rains from September to December (SOND) and long rains from March to May (MAM). The existing and newly introduced indices were selected based on grid point correlation and spatial mean correlation. West–east SST gradient over the Indian Ocean (WEIO), north–south SST gradient over the Pacific Ocean (NSPO), anomalies over the western Indian Ocean (WIO) and anomalies over the eastern Pacific Ocean (EPO) from newly developed indices, and bivariate ENSO time series (BEST), Oceanic Niño Index (ONI), Niño3.4, western Pacific gradient (WPG) and dipole index moment (DMI) from existing indices have a positive correlation with SOND rainfall at 5% (p<0.05$$ p<0.05 $$) significance level. West–east SST gradient over the Pacific Ocean (WEPO) and SST anomalies over the southern Pacific Ocean (SPO) from new indices and Southern Oscillation Index (SOI) from existing indices have a significant negative correlation with SOND rainfall over EA. SST anomalies over central and eastern Pacific and Indian oceans significantly correlate with SOND rainfall over southern EA (SEA) and equatorial EA (EEA). Rainfall over northern EA (NEA) has a significant negative correlation with SST over the east and central Pacific oceans. Negative correlation extends northeast and southeast from North of Australia over the Pacific Ocean during MAM. WEIO, WIO, NSPO, Niño3.4, Atlantic Oscillation (AO) and WPG have shown strong and significant (p<0.05$$ p<0.05 $$) relations at least over one subregion. The new SST and existing oceanic indices have a stronger and more significant correlation with short rains than long rains over EA, except in the northern part of EA. Correlation, RMSE and skill score of regression models revealed that new indices showed higher performance than existing indices over EEA and SEA in predicting rainfall, unlike over NEA during both seasons. [ABSTRACT FROM AUTHOR]