Assessment of Merged Satellite Precipitation Datasets in Monitoring Meteorological Drought over Pakistan

The current study evaluates the potential of merged satellite precipitation datasets (MSPDs) against rain gauges (RGs) and (SPDs) in monitoring meteorological drought over Pakistan during 2000–2015. MSPDs evaluated include Regional Weighted Average Least Square (RWALS), (WALS), Dynamic Clustered Bayesian model Averaging (DCBA), Model (DBMA) algorithms, while set SPDs is Global Precipitation Measurement (GPM)-based Integrated Multi-Satellite Retrievals for GPM (IMERG-V06), Tropical Rainfall Mission (TRMM) Analysis (TMPA 3B42 V7), Estimation from Remotely Sensed Information using Artificial Neural Networks (PERSIANN), ERA-Interim (re-analyses dataset). Several standardized indices (SPIs), including SPI-1, SPI-3, SPI-12, are used to evaluate performances RGs, SPDs, across as well on a regional scale. Mann–Kendall (MK) test assess trend different climate regions these SPI indices. Results revealed higher performance than when compared RGs estimates. seasonal evaluation SPIs MSPDs, representative year (2008) mildly moderate wetness monsoon season mild winter Pakistan. However, severity ranges severe years regions. MAPD (mean absolute percentage difference) shows high accuracy (MAPD <10%) RWALS-MSPD, good (10% < <20%) WALS-MSPD DCBA-MSPD, reasonable (20% 50%) DCBA Furthermore, show consistent with poor performance. Overall, this demonstrated significantly improved drought.