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Advances in Meteorology
Volume 2017, Article ID 4957960, 14 pages
https://doi.org/10.1155/2017/4957960
Research Article

Evaluation of High-Resolution Multisatellite and Reanalysis Rainfall Products over East Africa

1Ethiopian Institute of Water Resources, Addis Ababa University, Addis Ababa, Ethiopia
2School of Civil and Environmental Engineering, Addis Ababa Institute of Technology, Addis Ababa University, Addis Ababa, Ethiopia
3Civil and Environmental Engineering, University of Connecticut, Storrs, CT, USA

Correspondence should be addressed to Dejene Sahlu; moc.liamg@ulhasenejed

Received 31 August 2017; Accepted 6 December 2017; Published 25 December 2017

Academic Editor: Bin Yong

Copyright © 2017 Dejene Sahlu et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

The performance of six satellite-based and three newly released reanalysis rainfall estimates are evaluated at daily time scale and spatial grid size of 0.25 degrees during the period of 2000 to 2013 over the Upper Blue Nile Basin, Ethiopia, with the view of improving the reliability of precipitation estimates of the wet (June to September) and secondary rainy (March to May) seasons. The study evaluated both adjusted and unadjusted satellite-based products of TMPA, CMORPH, PERSIANN, and ECMWF ERA-Interim reanalysis as well as Multi-Source Weighted-Ensemble Precipitation (MSWEP) estimates. Among the six satellite-based rainfall products, adjusted CMORPH exhibits the best accuracy of the wet season rainfall estimate. In the secondary rainy season, unadjusted CMORPH and 3B42V7 are nearly equivalent in terms of bias, POD, and CSI error metrics. All error metric statistics show that MSWEP outperform both unadjusted and gauge adjusted ERA-Interim estimates. The magnitude of error metrics is linearly increasing with increasing percentile threshold values of gauge rainfall categories. Overall, all precipitation datasets need further improvement in terms of detection during the occurrence of high rainfall intensity. MSWEP detects higher percentiles values better than satellite estimate in the wet and poor in the secondary rainy seasons.