A Comparative Study of the Performance of CHIRPS and ERA5-Land Precipitation Datasets in Detecting Droughts in Iran

The aim of this study is to evaluate the performance of two precipitation datasets, CHIRPS and ERA5-Land, in detecting droughts using the Standardized Precipitation Index (SPI) over Iran. To achieve this, the raster data of the two datasets were evaluated using the standardized precipitation index in 11 time steps, along with precipitation data from 110 meteorological stations and correlation analysis. The study results revealed that both CHIRPS and ERA5-Land datasets exhibited a high degree of correlation with station data in time steps ranging from 1 to 12 months across Iran, except for the northern region (RCHIRPS = 0.56, RERA5 = 0.76). Furthermore, the ERA5-Land dataset demonstrated an acceptable level of performance in higher time steps (24-72 months) compared to CHIRPS. Additionally, the study revealed that the areas affected by drought were relatively similar between both datasets for time steps up to 12 months, although the reliability of CHIRPS was questionable at higher time steps. Moreover, based on the results, it was found that in general, the accuracy and capability of databases in high time steps, with a statistical period length of 30-40 years, have been significantly reduced, and for longer time steps, a longer statistical period should be used.