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High-resolution satellite-retrieved precipitation products are useful input data for hydrologic predictions and water resources management, especially in developing countries where the availability of ground-based rainfall measurements with high spatial coverage is very limited. In this study, four widely used satellite rainfall estimates (TMPA-3B42V7, TMPA-3B42RT, PERSIANN, and CMORPH) are evaluated with a dense raingauge network over six regions with various physiographic and climate conditions in Iran. Assessments are implemented at daily scale for different seasons during the five years period from 2003 to 2008. Overall, the results show that 3B42V7 leads to better performance than the other three products over different terrains. According to the value of relative bias (RBias) as one of the verification metric used in this study, 3B42V7 with an average value of 13.43% over all the regions matches best with the raingauge observations, while both PERSIANN and 3B42RT overestimate precipitation by 78.13% and 31%,respectively. On the other hand, CMORPH with RBias of -17.6% tends to underestimate the rainfall amount. Furthermore, the evaluations over different seasons indicate that the best performance for PERSIANN and both TMPA products is during the winter, while for CMORPH is during the autumn season. With respect to the critical success index (CSI) in order to assess the rain detecting skill of satellite products, one can conclude that PERSIANN leads to better estimations during the winter and summer, 3B42RT during the spring, and CMORPH during the autumn season. Generally, the implemented analyses in this research provide quantitative information of error characteristics associated with satellite precipitation products over different parts of Iran and thus will offer hydrologic users a better understanding of satellite rainfall estimates applicability in this area.

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