ABSTRACT
According to the world metrological organization, African countries with complex topography, are suffering from a shortage of metrological information. This study statistically compares four high-resolution satellite rainfall products from CHIRPS, PERSIANN, and TAMSAT with the ground observed rainfall data, all satellite rainfall products which have different spatial resolutions have been converted or re-grided into similar spatial resolution and point to pixel approach throughout 2000-2014. Continuous and categorical Statistical parameters were used to compare with the observed rainfall at each station. For the daily time series statistical comparison, 5479 data records were used and a good agreement was observed at the Wegel-Tana station with TAMSAT 3, TAMSAT 2, PERSIANN-CDR, and CHIRPS, correlation coefficients (r) of (0.6511, 0.620, 0.566 and 0.505) respectively. TAMSAT 2 showed a better correlation coefficient than its latest version in Amba-Mariam and Mankush (r = 0.6514 and r = 0.4923) respectively, and the mean daily comparison shows a better correlation. Lastly, the mean monthly comparison was done by converting the daily data into 12 mean monthly data series, and good agreement was observed at Wereilu and Wegel Tana stations (r = 0.999 and r = 0.998) by CHIRPS respectively, which is better than monthly comparison results, and the lower agreement was (r = 0.851) observed by TAMSAT 2 at Alem-Ketema. The study indicates that satellite rainfall estimates accuracy increases when the time step of comparison increases. Bias-adjusted satellite rainfall estimates showed acceptable model performance, Cor.TAMSAT 3 and Cor.TAMSAT 2 were the best-performing products showing nearly the perfect score correlation function. Generally, satellite rainfall estimates should be adjusted before using for any application, and should be validated or checked for the specific study area before selecting for any application and they can be used as an alternative to solve the rainfall scarcity problems of the area.
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