Ground validation of GPM-IMERG precipitation products across the Kingdom of Saudi Arabia

Accurate precipitation estimation is vital for understanding hydrological processes, managing water resources, and mitigating climate-related risks. In arid regions such as the Kingdom of Saudi Arabia (KSA), where ground-based rainfall measurement networks are sparse, satellite-based precipitation products provide a valuable alternative. Since 2022, the National Center for Meteorology (NCM) has launched a cloud seeding program to increase rainfall across the KSA. Therefore, it is crucial to have a quality-assured precipitation dataset that covers the KSA both spatially and regionally, in order to monitor the precipitation patterns across the cloud seeding area of interest.

This study evaluates the performance of the latest Global Precipitation Measurement (GPM) Integrated Multi-satellite Retrievals for GPM (IMERG) Version 07 (V07) precipitation products over KSA. The accuracy of IMERG V07 precipitation products (Early, Late, and Final) was evaluated on multiple temporal scales (daily and monthly) by using reference precipitation measurements from NCM’s ground-based rainfall measurement networks during 2001−2023. The error analysis was conducted using key performance metrics, including mean bias error (MBE), root mean square error (RMSE), correlation coefficient (CC), and categorical statistics such as the probability of detection (POD), false alarm ratio (FAR), and frequency bias index (FBI).

The performance of IMERG products compared to the ground-based rain gauge measurements indicated an adequately high correlation among all three products (daily: 0.74−0.85, monthly: 0.85−0.97), with the final product presenting the best performance. The three IMERG products suffer from systematic overestimation of daily and monthly precipitation (20.4−34.1%) across KSA. The two indices of precipitation detection ability, POD and FAR, presented records around 93−95% and 45−48%, respectively. The findings highlight the strengths and limitations of IMERG V07 for capturing precipitation patterns in arid environments and provide valuable insights for improving its application in hydrological modeling, climate, and cloud seeding studies in KSA.