Comparison of two high-resolution gridded precipitation data sets at the upstream of the Maroun dam in Iran

Satellite-based precipitation estimations are important and necessary because they are used to compensate the limited rain measurements in areas where there is no continuous monitoring of rainfall due to the dispersion of rain ague networks. Satellite-based precipitation estimation systems can provide information in areas where rainfall data are not available. Therefore, the accuracy of this type of data is very important. In this study, rainfall data of two long-term satellite data sets (FARSI-CDR and PERSIANN-CCS) at the upstream of Maroun Dam (Dehno, Ghale-Raeesi, Idenak, Margoon stations) during 2003-2014 were used and evaluated on daily, monthly, seasonally and annually basis. The results show that the annual precipitation of each dataset is underestimated in all stations, but the PERSIANN-CCS model compare to the PERSIANN-CDR has better estimations for annual observations. For estimation of seasonal precipitation, the results indicate that the PERSIANN-CCS model is better than the other one for rainfall estimation and rainfall detection. For estimation of monthly and daily precipitation, the results indicate that PERSIANN-CDR data are more appropriate than the other data set. Also, regarding to POD (probability of detection) and FAR (False alarm rate) estimated data, It was found that according to POD index, PERSIANN-CCS precipitation daily data and according to FAR, daily precipitation data of PERSIANN-CDR model have better performance in detecting rainy and non-rainy days.