FengYun-3 meteorological satellites’ microwave radiation Imagers enhance land surface temperature measurements across the diurnal cycle

Land Surface Temperature (LST) is a vital meteorological variable for assessing hydrological, ecological, and climatological dynamics, as well as energy exchanges at the land–atmosphere interface. Accurate and frequent LST measurement is essential for meteorological satellites. However, existing retrieval algorithms often fail to capture the nuances of diurnal temperature variations. This study utilizes the exceptional diurnal sampling capabilities of the Microwave Radiation Imagers (MWRI) on China’s FengYun-3 (FY-3) satellites to improve LST measurements throughout the day. The objective is to develop a global algorithm that can distinguish between frozen and thawed states of near-surface landscape. This algorithm integrates multi-channel brightness temperature data and an array of microwave indices to enhance accuracy across diverse land cover types. Validation against in-situ measurements, alongside the comparative analysis with ERA5 and MODIS LST products demonstrate the algorithm’s high robustness. Results reveal a correlation coefficient exceeding 0.87 between FY-3 MWRI-derived LST and 5-cm soil temperature, with a root mean squared error (RMSE) near 4 K, except at 14:00 for FY-3D. The theoretical uncertainty, estimated using triple collocation analysis of the three LST datasets from FY-3 MWRI, ERA5 and MODIS, is less than 4 K for the majority of the globe. Additionally, the FY-3 MWRI exhibits reduced diurnal variation in LST as compared to MODIS LST, the peak temperatures recorded by FY-3 MWRI occur with a certain time lag relative to MODIS, and the diurnal temperature range is generally narrower, showcasing its adeptness in delineating diurnal temperature cycles when deployed across the FY-3B/C/D satellite constellation.