Projecting Three-dimensional Ocean Thermohaline Structure in the North Indian Ocean from the Satellite Sea Surface Data Based on a Variational Method

Abstract:

This study uses a variational method combined with satellite observations to reconstruct three-dimensional temperature and salinity profiles for the Northern Indian Ocean (NIO). Sensitivity of reconstruction results show that when applied to various types of sea surface parameters, sea surface temperature (SST) can improve the temperature reconstruction of upper 100 m; sea surface salinity (SSS) can improve upper 100 m salinity reconstruction; sea surface height anomaly (SSHA) can improve the reconstruction of thermocline, especially in the temperature field. The temperature reconstruction of thermocline can be greatly improved by preprocessing altimeter data. Three different types of data were used to evaluate the results of reconstruction. Comparing with Simple Ocean Data Assimilation (SODA) in 2016, the spectral correlation between the reconstructions and the SODA density anomalies at the four-square regions. The results show that compared with SODA, the reconstructions can retrieve mesoscale signal and large-scale signal better. And the reconstruction has a significant improvement in surface salinity in the Bay of Bengal. Compared with CTD and Argo observations, the reconstruction can reflect the changes of the mixed layer and thermocline well. Four regions were selected to test the results. Compared with the Ocean Atlas 2013(WOA13) climatology, the reconstruction can better reflect the properties of upper water mass.