Data mining-based machine learning methods for improving hydrological data: a case study of salinity field in the Western Arctic Ocean

Salinity variations in Arctic Ocean determine the strength of stratification, ocean circulation, and biogeochemical cycles. Therefore, accurate salinity product is of great significance for our study of the Arctic Ocean. The mean density structure and wind-driven surface circulation of the Arctic Ocean are largely dominated by the anti-cyclonic Beaufort Gyre in the Canadian Basin, along with the Transpolar Drift (Hall et al.,2022). We focus on the salinity in Western Arctic Ocean. Multiple machine learning methods were used to reconstruct annual salinity product in the Western Arctic Ocean temporal for the period 2003-2022.