How Do IMERG V07, IMERG V06, and ERA5 Precipitation Products Perform over Snow–Ice-Free and Snow–Ice-Covered Surfaces at a Range of Near-Surface Temperatures?

Abstract Accurate precipitation estimation is essential for hydrological research and applications. This study assesses the performance of Integrated Multi-satellitE Retrievals for Global Precipitation Measurement (GPM), version 7 (IMERG V07), IMERG V06, and the fifth major global reanalysis produced by the European Centre for Medium-Range Weather Forecasts (ERA5) over snow–ice-covered and snow–ice-free surfaces, using 3 years (2018–20) of Multi-Radar Multi-Sensor (MRMS) system gauge-adjusted data as a reference. Mountainous regions were largely excluded from the analysis due to known uncertainties in precipitation estimates over complex terrain. Besides the IMERG final products, the study compares precipitation estimates from the infrared (IR) and passive microwave (PMW) components of IMERG V07 under different surface and environmental conditions. This is particularly relevant as both calibrated IR and PMW products, which rely on the Combined Radar–Radiometer Algorithm (CORRA) for calibration, face significant limitations over cold regions, especially over snow–ice-covered surfaces, complicating the choice of products for integration in the merged products like IMERG. We found that IMERG V07 offers notable improvements over IMERG V06 and generally outperforms ERA5 over snow–ice-free regions, demonstrating enhanced accuracy in precipitation intensity and spatial coverage. Conversely, ERA5 outperforms IMERG V07 over snow–ice surfaces, highlighting remaining challenges in satellite-based precipitation products over cold regions. An evaluation of PMW precipitation products indicates that while they generally perform better than IR precipitation products in warmer conditions, IR precipitation is still invaluable in cold regions with snow–ice cover. Among the PMW products and over snow–ice surfaces, Advanced Microwave Scanning Radiometer, version 2 (AMSR2), underperforms other PMW precipitation products for most statistical metrics, while GPM Microwave Imager (GMI), Special Sensor Microwave Imager/Sounder (SSMIS), and Microwave Humidity Sounder (MHS) products perform relatively better than others. The results emphasize the need for improving spaceborne sensors and algorithms to improve their accuracy across diverse environmental conditions, especially over cold regions in the presence of snow or ice on the surface.