Performance Evaluation of Three Satellites-Based Precipitation Data Sets Over Iran
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The present study aims to evaluate the performance of daily and monthly precipitation data relative to GPM-IMERG, TRMM_3B42 and PERSIANN satellite-based precipitation estimations against historical data for the period 2014–2017 as observed at 70 synoptic stations distributed over Iran. The coefficient of determination (R-squared), root mean square error and the Nash–Sutcliffe model efficiency coefficient were used to evaluate the performance of the used data sets against observed precipitation records at the considered stations. The statistics showed that the considered data sets are generally less successful in estimating daily precipitation at nationwide as the estimation errors were found high at almost all the studied stations. The errors of daily precipitation estimation of GPM-IMERG, TRMM_3B42 and PERSIANN-CDR data sets showed that although there is a considerable similarity between the estimated precipitation by the three data sets, especially between the TRMM_3B42 and GPM-IMERG, the accuracy of GPM-IMERG daily precipitation over Iran is higher than that of TRMM_3B42 and PERSIANN-CDR. The highest R2 value for GPM-IMERG, TRMM_3B42 and PERSIANN-CDR remotely sensed daily precipitation is equal to 0.6, 0.46, and 0.37, respectively. Similarly, on the monthly time scale, the GPM-IMERG, with an average R2 value of 0.83 over the country, performs better than the other two data sets. The TRMM_3B43 with mean nationwide R2 = 0.80 also showed comparative performance with GPM-IMERG, but the PERSIANN-CDR data set with an average R2 value of 0.4 over the stations is not as accurate as the GPM-IMERG and TRMM_3B43.
KeywordsRemote sensing data GPM-IMERG TRMM_3B43 PERSIANN-CDR Performance statistics Precipitation
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