Validation of operational seasonal rainfall forecast in Ethiopia
Article first published online: 22 NOV 2013
©2013. American Geophysical Union. All Rights Reserved.
Water Resources Research
Volume 49, Issue 11, pages 7681–7697, November 2013
How to Cite
2013), Validation of operational seasonal rainfall forecast in Ethiopia, Water Resour. Res., 49, 7681–7697, doi:10.1002/2013WR013760., and (
- Issue published online: 19 DEC 2013
- Article first published online: 22 NOV 2013
- Accepted manuscript online: 5 NOV 2013 11:49AM EST
- Manuscript Accepted: 28 OCT 2013
- Manuscript Revised: 10 OCT 2013
- Manuscript Received: 1 MAR 2013
- Ethiopian Malaria Prediction System (EMaPS)
- Development, Research and Education (NUFU) . Grant Number: NUFUPRO-2007/10121
 Operational rainfall forecasts using the analog method have been issued in Ethiopia since 1987. We evaluate the performance of the forecast system for February–May and June–September rainy seasons over the period 1999–2011. Verification is performed using rainfall data obtained from Ethiopian meteorological stations covering eight homogeneous rainfall regions used in the forecasts. The results reveal that forecasts issued by the National Meteorological Agency (NMA) of Ethiopia, for the past 12 years have a weak positive skill for all eight regions compared with climatology. In terms of ranked probability skill scores, the values are all lower than 10% indicating that the forecast skill is modest. The results further suggest that the forecasting system has bias toward forecasting near-normal conditions and has problems in capturing below average events. In contrast, the forecast has some positive skills in ranking the wet years of February–May season, particularly over the regions where there is high seasonal rainfall variability with significantly positive rank correlations for the above average years. For the main season, however, the forecast is not able to rank wet years or dry years. The extreme low and high rainfall events are mostly missed by the forecast scheme. The results indicate rather low forecast skill for extreme rainfall events in both seasons. Generally, the results indicate that NMA's forecasts have low but positive skill as it is common with results from other forecasting systems for the Greater Horn of Africa region. The underforecasting of dry events is the most serious shortcoming of the system.