Spatiotemporal Inter-comparison of WMO’s Gauge Adjusted Satellite Precipitation Product Over India

Satellite precipitation products (SPPs) are valuable tools for characterizing large-scale extreme events, such as droughts and floods, in data-scarce regions. However, due diligence is necessary when validating these products using in-situ observations. This study statistically compares the performance of the World Meteorological Organization-initiated Space-based Weather and Climate Extremes Monitoring Demonstration Project (SEMDP) Global Satellite Mapping of Precipitation product (SEMDP_GSMaP) with Integrated Multi-satellite Retrievals for GPM (IMERG) precipitation products over India for the years 2015–2017, utilizing daily gridded gauge data from the India Meteorological Department. The study found that SEMDP_GSMaP outperformed IMERG SPPs across various temporal, spatial, altitudinal, and rainfall frequency bands. The spatial variability of metrics was similar, with SEMDP_GSMaP demonstrating the highest correlation coefficient (CC > 0.8) and the lowest root mean square error (RMSE < 10 mm) among the SPPs. All SPPs underestimated precipitation in Northeast India but overestimated it in the southern part of the country. The probability of detection for rain events (PODn) was found to exceed 0.8 over most of the mainland, except in the Himalayan foothills and along the southern coast. All SPPs depicted cumulative distribution function patterns for medium precipitation intensities; however, SEMDP_GSMaP showed a better representation for both lighter and higher intensities than the GPM-era SPPs. The elevation effect on precipitation estimates and detection was lower for SEMDP_GSMaP compared to GPM IMERG SPPs. Initially, the gauge-adjusted SEMDP_GSMaP and IMERG_F (final run) were found useful, but SEMDP_GSMaP had a clear advantage over GPM IMERG_E (early run) and IMERG_F (final run).