Comparison of PERSIANN and V7 TRMM Multi-satellite Precipitation Analysis (TMPA) products with rain gauge data over Iran

Abstract

The objective of this research is to evaluate daily rain rates derived from three widely used high-resolution satellite precipitation products (PERSIANN, TMPA-3B42V7, and TMPA-3B42RT) using rain gauge observations over the entire country of Iran. Evaluations are implemented for 47 comprehensive daily rainfall events during the winter and spring seasons from 2003 to 2006. These events are selected because each encompasses more than 50% of the country’s area. In this study, daily rainfall observations derived from 1180 rain gauges distributed throughout the country are employed as reference surface data. Six statistical indices: bias, multiplicative bias (MBias), relative bias (RBias), mean absolute error (MAE), root mean square error (RMSE), and linear correlation coefficient (CC), as well as a contingency table are applied to evaluate the satellite rainfall estimates qualitatively. The spatially averaged results over the entire country indicate that 3B42V7, with an average bias value of –1.47 mmd⁻¹, RBias of –13.6%, MAE of 4.5 mmd⁻¹, RMSE of 6.5 mmd⁻¹, and CC of 0.61, leads to better estimates of daily precipitation than those of PERSIANN and 3B42RT. Furthermore, PERSIANN with an average MBias value of 0.56 tends to underestimate precipitation, while 3B42V7 and 3B42RT with average MBias values of 0.86 and 1.02, respectively, demonstrate a reasonable agreement in regard to rainfall estimations with the rain gauge data. With respect to the categorical verification technique implemented in this study, PERSIANN exhibits better results associated with the probability of detection of rainfall events; however, its false alarm ratio is worse than that of 3B42V7 and 3B42RT.

Acknowledgements

The authors would like to thank the two anonymous reviewers whose comments helped to improve the presentation of this article significantly.