Evaluation of Reprocessed Fengyun-3B Global Outgoing Longwave Radiation Data: Comparison with CERES OLR

Outgoing longwave radiation (OLR) at the top of the atmosphere (TOA) is a key parameter for understanding and interpreting the relationship between clouds, radiation, and climate interactions. It has been one of the operational products of the Fengyun (FY) meteorological satellites. OLR accuracy has gradually improved with advancements in satellite payload performance and the OLR retrieval algorithm. Supported by the National Key R&D Program Retrospective Calibration of Historical Chinese Earth Observation Satellite data (Richceos) project, a long-term OLR climate data record (CDR) was reprocessed based on the recalibrated Level 1 data of FY series satellites using the latest OLR retrieval algorithm. In this study, Fengyun-3B (FY-3B)’s reprocessed global OLR data from 2010 to 2018 were evaluated by using the Clouds and the Earth’s Radiant Energy System (CERES) global daily OLR data. The results showed that there was a high consistency between the FY-3B instantaneous OLR and CERES Single Scanner Footprint (SSF) OLR. Globally, between the two CDR datasets, the correlation coefficient reached 0.98, and the root-mean-square error (RMSE) was approximately 8–9 W m⁻². The bias mainly came from the edge regions of the satellite orbit, which may be related to the satellite zenith angle and cloud cover distribution. It was shown that the long-term FY-3B OLR had temporal stability compared to CERES OLR long-term data. In terms of spatial distribution, the mean deviations showed zonal and seasonal characteristics, although seasonal fluctuations were observed in the differences between the two datasets. Effects of FY-3B OLR application to the South China Sea monsoon region and ENSO were demonstrated and analyzed, and the results showed that the seasonal deviation of FY-3B’s OLR comes mainly from the retrieval algorithm. However, it has little effect on the analysis of climate events.