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

The validity of two reanalysis (ERA5 and MEERA2) and seven satellite-based (CHIRPS, IMERG, PERSIANN-CCS, PERSIANN-CDR, PERSIANN-PDIR, PERSIANN, and TRMM) precipitation products was assessed in relation to the observations of in situ weather stations installed in different topographical and climatic regions of Pakistan. From 2010 to 2018, all precipitation products were evaluated on daily, monthly, seasonal, and annual bases at a point-to-pixel scale and over the entire spatial domain. The accuracy of the products was evaluated using commonly used evaluation and categorical indices, including Root Mean Square Error (RMSE), Correlation Coefficient (CC), Bias, Relative Bias (rBias), Critical Success Index (CSI), Success Ratio (SR) Probability of Detection (POD), and False Alarm Ratio (FAR). The results show that: (1) Over the entire country, the spatio-temporal distribution of observed precipitation could be represented by IMERG and TRMM products. (2) All products (reanalysis and SPPs) demonstrated good agreement with the reference data at the monthly scale compared to the daily data (CC > 0.7 at monthly scale). (3) All other products were outperformed by IMERG and TRMM in terms of their capacity to detect precipitation events throughout the year, regardless of the season (i.e., winter, spring, summer, and autumn). Furthermore, both products (IMERG and TRMM) consistently depicted the incidence of precipitation events across Pakistan's various topography and climatic regimes. (4) Generally, CHIRPS and ERA5 products showed moderate performances in the plan areas. PERSIANN, PERSIANN-CCS, PDIR, PERSIANN-CDR, and MEERA2 products were uncertain to detect the occurrence and precipitation over the higher intensities and altitudes. Considering the finding of this assessment, we recommend the use of daily and monthly estimates of the IMERG product for hydro climatic studies in Pakistan. [ABSTRACT FROM AUTHOR]