Main Article Content
Evaluation of performances of satellite rainfall estimates (SREs) for representing the spatial and temporal variability of rainfall in data-poor catchments such as Upper Gilgel Abay is vital. Hence, the focus of this study was to test the effectiveness of satellite rainfall estimates at high spatial and temporal resolutions in Upper Gilgel Abay Catchment. The study period of 2006-2010 was used for downloading the 1-hr temporal and 8 km × 8 km spatial resolution CMORPH (Climate Prediction Centre Morphing Method) data (selected from SREs). For correcting the systematic biases, time and space variant bias correction algorithm was applied for a time window of 7 days and a minimum rain accumulation of 5 mm within these days. Bias correction selected for this study aimed at correcting both in space and time domains. Based on the findings of this study, CMORPH underestimates rainfall up to 18% during the analysis period (2006-2010). Spatially, there are clear variations on the performance of CMORPH across rain gauging stations.