Evaluation and Bias correction of Tropical Applications of Meteorology using SATellite (TAMSAT) daily rainfall estimates over the data-scarce region of Southern Ethiopia

Abstract

Precipitation data is an intrinsic parameter of rainfall-runoff simulation. since it is strongly hooked into the accuracy of the spatial and temporal representation of the precipitation. In regions where rainfall stations are scarce, additional data sources could also be needed. Satellite platforms have provided a satisfactory alternative because of their global coverage. Tropical Applications of Meteorology using SATellite (TAMSAT) is one such data source provided by the research group of the University of Reading, UK. This dataset provides rainfall estimates across Africa which captures the rainfall pattern in GenaleDawa River 
basin (southern Ethiopia) but with a magnitude bias of over-estimation and under-estimations. In this study, magnitude bias correction of the TAMSAT dataset with a linear scaling technique resulted in a rainfall grid of the area with ~4 km spatial resolution of a 35 year (1983–2017) daily rainfall dataset. Intercomparison between Satellite rainfall product and observed data were done using point to grid method selecting nine representative metrological stations.The average correlation R is 0.45 and the average NS is 0.028 and the Categorical index POD, FAR, FB and HSS, values were 0.49,0.4,0.84, and 0.4) before bias correction. After bias correction, these values were improved to the average value of R=0.87 and NS =0.764 and POD, FAR, FB, and HSS of (0.71,0.22, 0.92, and 0.66 respectively.