Evaluation of FY-3/VIRR Sea Surface Temperature Data for Climate Applications

We evaluated the sea surface temperature(SST) products derived from the visible infrared radiometer on board the Fengyun-3 satellites(FY-3/VIRR) during 2016–2018 from the perspective of climate applications. The data had previously been reprocessed by the National Satellite Meteorological Center of China Meteorological Administration based on an updated SST retrieval algorithm. The overall consistency between the FY-3/VIRR SST data and the optimum interpolation SST version 2.1(OIv2.1) was better for monthly means than for pentad means, and showed a clear dependence on the season and location. There was better consistency in winter than in summer, and in the tropical central–eastern Pacific than in the western Pacific warm pool, tropical North Indian Ocean, and tropical Atlantic Ocean. The monthly deviation of the global average SST anomaly was-0.03 ± 0.07°C and the average root-meansquare errors(RMSEs) presented clear seasonal fluctuations with a maximum of approximately 0.5°C in summer.The poor consistency of the FY-3/VIRR SST in summer may be partially attributed to the bias of the OIv2.1 data in global oceans(especially the Indian Ocean) as a result of the spatially heterogeneous in situ measurements from ships, buoys, and Argo floats. Convective activities and clouds in the tropics may also influence the accuracy of the FY-3/VIRR SST retrievals. The Ni?o SST indices based on both FY-3/VIRR and OIv2.1 SST data displayed a generally similar evolution, including the start and end of El Ni?o and La Ni?a events and their amplitudes, although the deviations were slightly larger when the Pacific SST anomaly was in the neutral state of the El Ni?o–Southern Oscillation(ENSO). The deviations varied greatly with season in the tropical Indian and Atlantic oceans, suggesting the need to perform further analyses and validation of the FY-3/VIRR SST products in these two basins.