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

<p><span><span>Salinity variations in Arctic Ocean determine the strength of stratification,</span> <span>ocean circulation, and biogeochemical cycles.&nbsp;Therefore, a<span>ccurate </span>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<span> (Hall </span><span>et al.,2022)</span>. 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.</span></span></p>