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

Dejene Sahlu,Semu A Moges,Dereje Hailu,Emmanouil N Anagnostou,Efthymios I Nikolopoulos

doi:10.1155/2017/4957960

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.

Highlights

Rainfall is an important parameter for the characterization of water cycle
We examined the performance of the six satellite-based precipitation estimates (SPEs) and the three reanalysis products using categorical statistics of Probability of Detection (POD), False Alarm Ratio (FAR), and Critical success index (CSI)
The MWbased products provide better estimate of precipitation event detection than the IR-based estimate. Both products of CMORPH are a result from propagation and morphing techniques of MW-based estimate which are superior in rainfall event detection performance among the six SPEs in this study (Figure 4(a)), and the plus symbol below the whiskers shows that the performance of rainfall event detection is nearly 70% to 80% in some locations

Summary

Introduction

Rainfall is an important parameter for the characterization of water cycle. In Africa, assessment, planning, and management of water resources are often constrained by lack of reliable rainfall data [1,2,3]. One of the reasons is that spatial and temporal availability of rain gauge networks in Africa and in particular in Ethiopia is deteriorating by the year. The density and spatial distribution of rain gauges in the Upper Blue Nile Basin is uneven and time-varying. Satellite-based and reanalysis global precipitation estimates are steadily rising, which offers precipitation datasets at high spatial and temporal resolution, which could potentially support research and operational water resources applications in these data-poor environments. In accession to the satellite-based precipitation estimates, a newly released European Center for Medium range

Methods

Results

Conclusion