Global Sea Surface Temperature Analysis Based on Domestic Ocean Satellite Data. Part I: Methods and Results

Abstract

Abstract Sea surface temperature is widely used in research and applications such as upper ocean processes, air-sea heat exchange, numerical simulation and prediction of the ocean and atmosphere. In this article, the global gap-free fusion data of sea surface temperature has been developed using optimal interpolation (OI) method which is commonly used by international operational institution, merging satellite remote sensed H1C, H2B, AVHRR, AMSR data and GTS in-situ data. According to three data fusion experiments, it is found that the fusion results of domestic satellite remote sensed data during the test period are qualitatively better than those of foreign satellites in the Northwest Pacific region. Further quantitative analysis is compared with Argo surface SST data, a total of 41842 data pairs are matched in 2022, with a deviation of -0.0756 and a root mean square error of 0.4283.