Author:
Yu Qinglong,Qin Yinghao,Wan Liying
Abstract
Abstract
With more and more global gap-free fusion products of the sea surface temperature, understanding the consistency and discrepancy of the different SST fusion products will not only help data providers to improve their algorithms, but also help them to select the one that may better suit their applications. In this article, we have compared and analysed 10 sets of global gap-free fusion products of sea surface temperature in 2022, with different fusion techniques and related configurations. It is found that each SST analysis product has the same spatial distribution, with the minimum NMEFC mean value (20.11) and the maximum MGDSST mean value (20.31). Compared with ARGO in-situ data, the RMSE ranges are from 0.3233 (OSTIA) to 0.5180 (MGDSST). The RMSE between NMEFC fusion products and Argo in-situ data is 0.3861, ranked fifth out of 10 sets of fusion products. Compared with GMPE analysis among 9 sets of fusion products, the RMSE ranges are from 0.1579 (CMC) to 0.3199 (K10), and the NMEFC fusion product has a RMSE of 0.3040, which is at the intermediate level, ranked sixth out of 9 fusion products.