Evaluating three non-gauge-corrected satellite precipitation estimates by a regional gauge interpolated dataset over Iran

Study region: Iran has about 1.648 million km2, is placed between 44 degrees and 64 degrees E and 25-40 degrees N in the southwest of the Middle East and North Africa. It is characterized by a tough precipitation gradient with a mean annual precipitation of 250 mm, concentrating primarily during the wet months (January to April). Study focus: In this study, we evaluated the performance of three non-gauge-corrected satellite precipitation estimates and a linear combination of these products (SPC) versus the Asfezari (Iran national reanalysis dataset) using four continuous statistics (R2, NSE, RMSE, and BIAS) and three categorical metrics (POD, FAR, and CSI). New hydrological insights for the region: The foremost issue for hydrologists in Iran, and many other developing countries, is off-line rainfall data without near real-time availability. For this reason, researchers are using satellite products. These gridded datasets have their benefits and drawbacks with regard to their resolution, time span, time steps, and accuracy. Therefore, testing the quality of gridded datasets is the primary step of using them in hydrological assessments. Current research compares the satellite products with a national gridded dataset (Asfezari) over Iran for the first time. Overall, the SPC dataset had better accuracy than other datasets. Then SM2RAINASCAT showed better accuracy than PERSIANN-CCS and CMORPH in both statistical accuracy and detection.

Automated summary

This study evaluated the performance of non-gauge-corrected satellite precipitation estimates in Iran, finding that the SPC dataset showed the best accuracy compared to the national dataset and two other satellite datasets. The use of satellite products is crucial due to the lack of real-time rainfall data in Iran and other developing countries.