Identification and Correction for Sun Glint Contamination in Microwave Radiation Imager-Rainfall Mission Global Ocean Observations Onboard the FY-3G Satellite

Microwave radiometers are vital for global ocean observations, yet they are prone to errors from radio frequency interference, sun glint, and other contamination. This paper focuses on the newly launched Chinese FY-3G satellite’s Microwave Radiation Imager-Rainfall Mission (MWRI-RM) instrument, aiming to detect sun glint contamination and set a critical angle for data quality control. The model regression difference method is employed to simulate uncontaminated brightness temperatures at 10.65 GHz. By comparing the observed and simulated values, this study finds that sun glint contamination, which causes a 0–5 K increase in brightness temperature, is strongly related to sun glint angle. Based on the statistical analysis of contaminated pixels from November 2023 to July 2024, it is recommended that a critical angle of 25° be used to flag contaminated areas. The method also identifies persistent television frequency interference along the U.S. coastline at 18.7 GHz, which the radio frequency interference (RFI) Flag in Level 1 data failed to detect. Through the utilization of the model regression difference method, the warm biases in the MWRI-RM observations can be corrected. This research offers a practical way to enhance the accuracy of the MWRI-RM data and can be applied to other microwave radiometry missions.