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Estimating the Ocean Interior from Satellite Observations in the Kerguelen Area (Southern Ocean): A Combined Investigation Using High-Resolution CTD Data from Animal-Borne Instruments

Lei LiuaState Key Laboratory of Tropical Oceanography, South China Sea Institute of Oceanology, Chinese Academy of Sciences, Guangzhou, China
bSouthern Marine Science and Engineering Guangdong Laboratory (Guangzhou), Guangzhou, China

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Huijie XuecState Key Laboratory of Marine Environmental Science, Xiamen University, Xiamen, China
dDepartment of Physical Oceanography, College of Ocean and Earth Sciences, Xiamen University, Xiamen, China

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Abstract

Observational surface data are utilized to reconstruct the subsurface density and geostrophic velocity fields via the “interior + surface quasigeostrophic” (isQG) method in a subdomain of the Antarctic Circumpolar Current (ACC). The input variables include the satellite-derived sea surface height (SSH), satellite-derived sea surface temperature (SST), satellite-derived or Argo-based sea surface salinity (SSS), and a monthly estimate of the stratification. The density reconstruction is assessed against a newly released high-resolution in situ dataset that is collected by a southern elephant seal. The results show that the observed mesoscale structures are reasonably reconstructed. In the Argo-SSS-based experiment, pattern correlations between the reconstructed and observed density mostly exceed 0.8 in the upper 300 m. Uncertainties in the SSS products notably influence the isQG performance, and the Argo-SSS-based experiment yields better density reconstruction than the satellite-SSS-based one. Through the two-dimensional (2D) omega equation, we further employ the isQG reconstructions to diagnose the upper-ocean vertical velocities (denoted wisQG2D), which are then compared against the seal-data-based 2D diagnosis of wseal. Notable discrepancies are found between wisQG2D and wseal, primarily because the density reconstruction does not capture the seal-observed smaller-scale signals. Within several subtransects, the Argo-SSS-based wisQG2D reasonably reproduce the spatial structures of wseal, but present smaller magnitude. We also apply the isQG reconstructions to the 3D omega equation, and the 3D diagnosis of wisQG3D is very different from wisQG2D, indicating the limitations of the 2D diagnostic equation. With reduced uncertainties in satellite-derived products in the future, we expect the isQG framework to achieve better subsurface estimations.

© 2022 American Meteorological Society. For information regarding reuse of this content and general copyright information, consult the AMS Copyright Policy (www.ametsoc.org/PUBSReuseLicenses).

Corresponding author: Huijie Xue, hjxue@xmu.edu.cn

Abstract

Observational surface data are utilized to reconstruct the subsurface density and geostrophic velocity fields via the “interior + surface quasigeostrophic” (isQG) method in a subdomain of the Antarctic Circumpolar Current (ACC). The input variables include the satellite-derived sea surface height (SSH), satellite-derived sea surface temperature (SST), satellite-derived or Argo-based sea surface salinity (SSS), and a monthly estimate of the stratification. The density reconstruction is assessed against a newly released high-resolution in situ dataset that is collected by a southern elephant seal. The results show that the observed mesoscale structures are reasonably reconstructed. In the Argo-SSS-based experiment, pattern correlations between the reconstructed and observed density mostly exceed 0.8 in the upper 300 m. Uncertainties in the SSS products notably influence the isQG performance, and the Argo-SSS-based experiment yields better density reconstruction than the satellite-SSS-based one. Through the two-dimensional (2D) omega equation, we further employ the isQG reconstructions to diagnose the upper-ocean vertical velocities (denoted wisQG2D), which are then compared against the seal-data-based 2D diagnosis of wseal. Notable discrepancies are found between wisQG2D and wseal, primarily because the density reconstruction does not capture the seal-observed smaller-scale signals. Within several subtransects, the Argo-SSS-based wisQG2D reasonably reproduce the spatial structures of wseal, but present smaller magnitude. We also apply the isQG reconstructions to the 3D omega equation, and the 3D diagnosis of wisQG3D is very different from wisQG2D, indicating the limitations of the 2D diagnostic equation. With reduced uncertainties in satellite-derived products in the future, we expect the isQG framework to achieve better subsurface estimations.

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Corresponding author: Huijie Xue, hjxue@xmu.edu.cn

Supplementary Materials

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