Seasonal prediction of East African rainfall

The detrimental impacts of climate variability on water, agriculture, and food resources in East Africa underscore the importance of reliable seasonal climate predictions. This study compares several forecasting methods using sea surface temperature (SST) anomalies to predict East African rains with various lead times. It is shown that the forecasts can explain more than 50% of the short rains (boreal autumn) variance across large regions of Ethiopia, Somalia, and Kenya, and reaffirm the importance of the Walker-like circulation over the Indian Ocean. The forecasts also explain more than 50% of the long rains (boreal spring) over Uganda, Lake Victoria, and western Kenya, and demonstrate the strong connection of the long rains to the SSTs in the southern Atlantic Ocean, Mediterranean Sea, southwestern Indian Ocean, and Arabian Sea. For the unimodal rains in Tanzania, the forecasts explain more than 40% of the rainfall variance over northwestern Tanzania based on SST predictors in the southwestern Indian Ocean and the subtropical North Atlantic. For the South Sudan and Ethiopian Kiremt rains, the forecast skill is less pronounced. The predictor regions (dipoles) for a recently developed method are validated through composite maps of surface and atmospheric reanalysis variables. Lastly, 2010–2011 forecasts for both the long and short rains demonstrate skill in predicting the recent drought suggesting that seasonal climate forecasts can inform natural disaster preparedness and water resources planning in East Africa.