Comparative Assessment Of Imerg And Era5 Precipitation Products Over Snow-Ice-Covered And Snow-Ice-Free Surfaces
Presenter: Hossein Yousefi Sohi P271
Co-Author(s): Ali Behrangi
Advisor(s): Ali Behrangi
1Hydrology & Atmospheric Sciences
Accurate estimation of precipitation is crucial for hydrological and meteorological research. This study undertakes a rigorous comparison of the Global Precipitation Measurement (GPM) and ERA5 products with the Multi-Radar Multi-Sensor (MRMS) data over the contiguous United States (CONUS) from January 2018 to December 2020. Different types of products from the Integrated Multi-satellite Retrievals for GPM (IMERG) product are investigated, including precipitation estimates from infrared (IR), passive microwave (PMW), and their combination. This paper studies the influence of various factors such as near-surface wet-bulb temperature (Tw), precipitation intensity, and surface conditions, particularly surfaces with or without snow and ice. In the first step, IMERG versions 07 and 06, along with ERA5, are evaluated. The results underscore the significant correlation of IMERG version 07 with MRMS data, highlighting its capability to provide more accurate precipitation measurements compared to IMERG version 06 and ERA5 specially for warmer temperatures (Tw > 0°C). Additionally, the analysis demonstrates that PMW sensors (used in IMERG) are more adept than IR in detecting precipitation events in the absence of snow and ice on the surface. On snow-and ice-covered surfaces, precipitation estimates from PMW sensors are better correlated with MRMS data than those from IR but are prone to relatively large biases at colder temperatures (Tw < -10°C). In these conditions, IR estimates tend to be more consistent in terms of bias and POD. Besides these variations, the integrated use of PMW and IR data in IMERG is validated, especially for its application in snowy and icy conditions. The outcomes of this study can be insightful to users and algorithm developers.