Predictability of June-September rainfall in Ethiopia

• Published in: Monthly weather review Vol. 135; no. 2; pp. 628 - 650
• Main Authors: KORECHA, Diriba, BARNSTON, Anthony G
• Format: Journal Article
• Language: English
• Published: Boston, MA American Meteorological Society 01.02.2007
• Subjects: Agriculture; Anomalies; Climate; Disasters; Drought; Earth, ocean, space; El Nino; El Nino phenomena; El Nino-Southern Oscillation event; Environmental monitoring; Exact sciences and technology; External geophysics; Global temperatures; Hydrologic data; Lead time; Local climates; Meteorology; Missing data; Monthly rainfall; Monthly rainfall data; Northern Hemisphere; Oceans; Precipitation; Predictions; Rain; Rainfall; Rainfall anomalies; Rainfall forecasting; Rainfall patterns; Rainy season; Regions; Sea surface; Sea surface temperature; Seasonal rainfall; Seasons; Southern Oscillation; Statistical analysis; Statistical methods; Studies; Summer; Summer climates; Summer rainfall; Surface temperature; Water in the atmosphere (humidity, clouds, evaporation, precipitation); Water resources; Weather; Weather analysis and prediction; Wet season; Wind; East Africa; Ethiopia; Indian Ocean; Senegal; Africa; Sudan; ISW, Indian Ocean; Teleconnection; Seasonal forecast; rainfall; Weather forecast; atmospheric precipitation; Predictor; Africa; Summer; ocean-atmosphere interaction; Statistical forecasting; Dynamical climatology; El Nino; Predictability; drought; Climate variability; Southern oscillation; water resource management; Rainy season; Risk management; Dynamic model
• ISSN: 0027-0644; 1520-0493
• DOI: 10.1175/mwr3304.1

In much of Ethiopia, similar to the Sahelian countries to its west, rainfall from June to September contributes the majority of the annual total, and is crucial to Ethiopia's water resource and agriculture operations. Drought-related disasters could be mitigated by warnings if skillful summer rainfall predictions were possible with sufficient lead time. This study examines the predictive potential for June-September rainfall in Ethiopia using mainly statistical approaches. The skill of a dynamical approach to predicting the El Nino-Southern Oscillation (ENSO), which impacts Ethiopian rainfall, is assessed. The study attempts to identify global and more regional processes affecting the large-scale summer climate patterns that govern rainfall anomalies. Multivariate statistical techniques are applied to diagnose and predict seasonal rainfall patterns using historical monthly mean global sea surface temperatures and other physically relevant predictor data. Monthly rainfall data come from a newly assembled dense network of stations from the National Meteorological Agency of Ethiopia. Results show that Ethiopia's June-September rainy season is governed primarily by ENSO, and secondarily reinforced by more local climate indicators near Africa and the Atlantic and Indian Oceans. Rainfall anomaly patterns can be predicted with some skill within a short lead time of the summer season, based on emerging ENSO developments. The ENSO predictability barrier in the Northern Hemisphere spring poses a major challenge to providing seasonal rainfall forecasts two or more months in advance. Prospects for future breakthroughs in ENSO prediction are thus critical to future improvements to Ethiopia's summer rainfall prediction.