Evaluation and Comparison of Precipitation Datasets by Reanalysis and Satellite Models in Different Parts of Iran

Abstract

Rainfall is a crucial component of the hydrological cycle and plays a key role in water resource planning. Recent research has investigated the use of gridded data as a supplement to and replacement for traditional rain gauge measurements, particularly in areas with limited gauge coverage. Gridded precipitation data offering a structured method to represent precipitation patterns across large regions by dividing the data into grids. This enables more precise spatial analysis of precipitation distribution and variability. The study assessed the accuracy of six high-resolution gridded rainfall product estimates (ERA5, ERA-Interim, CMORPH, PERSIANN, PERSIANN-CDR, and PERSIANN-CCS) at 12 rain gauge stations in Iran at various time scales. Comparisons with rain gauge network data using statistical and graphical methods revealed that ERA5, ERA-Interim, and PERSIANN-CDR data outperformed other models on annual and monthly scales, so that the highest correlation coefficient in monthly scale was obtained by ERA5 model at Doroodzan station with correlation coefficient of 0.93. Also, the results on a daily scale indicate the appropriateness of the output data of the reanalysis models (ERA5, ERA-Interim) compared to other models in such a way that the lowest RMSE value in all stations except Sefidroud Dam is related to the reanalysis data and the lowest RMSE value is equal to with 0.78 mm at the Chahnimeh station and the highest value of the correlation coefficient equal to 0.63 corresponds to the Karaj dam rain gauge station; Also, in correctly detecting rainy and non-rainy days, ERA5 model has the most accuracy in all stations.

Keywords

• evaluation indicators
• iran dams
• rainfall estimation
• reanalysis data
• satellite data