Seeing through the Sea with Satellites: Reconstructing Ocean Subsurface Temperature and Salinity with Satellite Observations

Abstract. In-situ measurements of ocean temperature and salinity are critical to ocean-related studies but are limited in space and time. Satellite retrievals provide high-resolution, globally-covered sea surface temperature (SST), salinity (SSS) and cannot directly measure the subsurface information., and height (SSH), but are limited to the ocean surface and cannot directly measure the subsurface information. Here we design a physics-informed algorithm that can reconstruct the vertical distributions of upper ocean temperature and salinity based purely on satellite observations. The algorithm stresses the tight ocean surface-subsurface coupling and the co-variability of ocean temperature and salinity. It is firstly tested with climate model simulations and then validated with actual observations by Argo floats, moored buoys and multiple ocean reanalysis datasets. The resultant satellite-based upper ocean temperature and salinity dataset has a global coverage, a high spatial resolution, and resolves ocean thermohaline structure from surface to 400 m. This dataset complements existing ocean subsurface products as an independent satellite-based observational dataset. The success of our reconstruction algorithm highlights a pressing need to maintain and advance the satellite observations of SST, SSS, and SSH. The reconstructed ocean temperature and salinity dataset can be accessed at https://doi.org/10.5281/zenodo.13145129 (Liu, 2024) and be used by researchers to study mesoscale ocean phenomena, assess the ocean heat content in various sea areas and etc.