A recent study published in the ISPRS Journal of Photogrammetry and Remote Sensing highlights how China's FengYun-3 (FY-3) meteorological satellites have improved global tracking of land surface temperature (LST) throughout daily cycles. Led by Prof. ZHAO Tianjie from the Aerospace Information Research Institute of the Chinese Academy of Sciences, the study utilizes the unique capabilities of the FY-3's Microwave Radiation Imagers (MWRI) to overcome the limitations of traditional satellite-based LST retrieval methods.

LST is a crucial parameter for weather forecasts, agricultural planning, ecosystem tracking, and disaster management. Historically, it has relied on thermal infrared (TIR) sensors. However, TIR measurements face challenges from cloud cover—which affects approximately 60% of land areas—and are limited to capturing surface "skin" temperature.

The FY-3 satellite constellation addresses these issues with its advanced MWRI sensors, providing an all-weather solution and deeper thermal insights. By taking advantage of the satellite's multi-pass observation capability, researchers have achieved more frequent and consistent LST measurements throughout the day.

"Our study confirms that the MWRI sensors on FY-3 satellites offer unprecedented accuracy in LST monitoring," stated Prof. ZHAO. "Microwaves can penetrate clouds, allowing for continuous observation even in overcast conditions. Unlike TIR's surface-level temperature measurements, microwave data provides an integrated effective temperature that reflects the combined thermal states of soil and vegetation."

Moreover, the researchers developed a novel algorithm that distinguishes between frozen and thawed soil states, significantly enhancing temperature measurements in high-latitude and mountainous regions where soil moisture phase changes can drastically impact thermal properties and radiative transfer. This algorithm incorporates multiple microwave indices to minimize errors caused by vegetation cover, snow conditions, and atmospheric water vapor interference.

According to the study, the LST data derived from FY-3 MWRI shows high validation accuracy, with a strong correlation of over 0.87 with ground-based measurements and an error margin of just 4 K. It also aligns closely with widely used datasets such as MODIS and ERA5.

Notably, FY-3's LST exhibits a narrower diurnal range and delayed peak temperatures compared to MODIS. This reflects a greater soil thermal inertia, which benefits hydrological and climate modeling. The FY-3 B/C/D satellite constellation reduces the average error in reconstructing 24-hour temperature cycles to 5.2 K, significantly better than MODIS’s four-daily sampling, thus offering superior temporal resolution for improving climate models and tracking heatwaves and droughts, as well as understanding climate-driven changes in ecosystems.

"FY-3's microwave sensors address a critical gap in our Earth observation capabilities," emphasized Prof. ZHAO. "By capturing the thermal inertia of deeper soil layers, operating continuously day and night through cloud cover, and enabling multiple daily observations, these data are transformative for hydrological models and climate adaptation strategies."

This research was funded by China's National Key R&D Program, and all datasets have been made publicly available via the National Tibetan Plateau Data Center.

FY-3 Satellite Constellation MWRI Multi-Pass Land Surface Temperature (LST). (Image by AIR)