Weather and Climate Systems

Multi-Model Ensemble Prediction of Ethiopian Monthly-to-Seasonal Monsoon Rainfall

Dr. Zewdu Tessema Segele


25 September 2013, 1:00 PM

National Weather Center, Room 1313
120 David L. Boren Blvd.
University of Oklahoma
Norman, OK

Seasonal rainfall prediction is important to sub-Saharan Africa where recurring droughts severely affect the majority of the population that depends on subsistence farming. A multi-model ensemble prediction framework is designed to predict monthly to seasonal rainfall at local and regional scales well in advance of the monsoon season over Ethiopia. In the ensemble prediction framework, variables observed in March/April predict June-September rainfall.
Significant prediction improvements are achieved from a simple averaging of the multi-model ensemble compared to individual member forecasts. For a leave-one-out prediction strategy with 30 years of independent verification data, the ensemble-based prediction framework provides highly skillful predictions of all-Ethiopian monsoon rainfall one to two months in advance, with the correlation between observed and predicted rainfall being +0.71/+0.72. More importantly, the ensemble prediction is successful in identifying signs of rainfall anomalies for 28 out of 30 years. The ensemble forecasts significantly outperform climatology and persistence, with mean squared error reductions of 43-52% over climatology versus 78-81% over persistence. The skill also was assessed for a localized prediction. The prediction captured the relative interannual variability well, with a correlation skill of +0.69 and a reduction in mean squared error of the prediction of 46% compared to 1970-1999 climatology.

Speaker bio

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