Evaluation of Soil Moisture-Based Satellite Precipitation Products over Semi-Arid Climatic Region

The ground validation of satellite-based precipitation products (SPPs) is very important for their hydroclimatic application. This study evaluated the performance assessment four soil moisture-based SPPs (SM2Rain, SM2Rain- ASCAT, SM2Rain-CCI, and GPM-SM2Rain). All data were compared with 64 weather stations in Pakistan from January 2005 to December 2020. estimations on daily, monthly, seasonal, yearly scales, over whole spatial domain, at point-to-pixel scale. Widely used evaluation indices (root mean square error (RMSE), correlation coefficient (CC), bias, relative bias (rBias)) along categorical (false alarm ratio (FAR), probability detection (POD), success (SR), critical index (CSI) analysis. results our signposted that: (1) On a monthly scale, all better agreement gauge as daily scales. Moreover, SM2Rain GPM-SM2Rain accurately traced spatio-temporal variability CC >0.7 rBIAS within acceptable range (±10) country. (2) seasonal scale (spring, summer, winter, autumn), performed more satisfactorily other SPPs. (3) capturing light events, indicated by Probability Density Function (PDF); however, summer season, displayed considerable over/underestimates respect PDF (%). GPM-SM2RAIN beat terms detection. Consequently, we suggest use hydro climate applications semi-arid zone (Pakistan).