Reconstructing the Ocean Interior from High-Resolution Sea Surface Information

Author:

Liu Lei1,Xue Huijie2,Sasaki Hideharu3

Affiliation:

1. State Key Laboratory of Tropical Oceanography, South China Sea Institute of Oceanology, Chinese Academy of Sciences, Guangzhou, China

2. State Key Laboratory of Tropical Oceanography, South China Sea Institute of Oceanology, and Institution of South China Sea Ecology and Environmental Engineering, Chinese Academy of Sciences, Guangzhou, China, and School of Marine Sciences, University of Maine, Orono, Maine

3. Application Laboratory, Japan Agency for Marine-Earth Science and Technology, Yokohama, Japan

Abstract

AbstractWhen evaluated against the 1/30°-resolution, submesoscale-resolving OFES model outputs, the previously published “interior + surface quasigeostrophic” method (from the 2013 study by Wang et al., denoted W13) for reconstructing the ocean interior from sea surface information is found to perform improperly in depicting smaller-scale oceanic motions (associated with horizontal scales smaller than about 150 km). This could be attributed to the fact that the W13 method uses only the barotropic and first baroclinic modes for the downward projection of sea surface height (SSH), while SSH at smaller scales significantly reflects other higher-order modes. To overcome this limitation of W13, an extended method (denoted L19) is proposed by employing a scale-dependent vertical projection of SSH. Specifically, the L19 method makes the projection via two gravest modes as proposed in the W13 method only for larger-scale (>150 km) signals, but for smaller scales (≤150 km) it exploits the framework of the “effective” surface quasigeostrophic (eSQG) method. Evaluation of the W13, eSQG, and L19 methods shows that the proposed L19 method can achieve the most satisfactory subsurface reconstruction in terms of both the flow and density fields in the upper 1000 m. Our encouraging results highlight the potential applicability of L19 method to the high-resolution SSH data from the upcoming Surface Water and Ocean Topography (SWOT) satellite mission.

Funder

National Natural Science Foundation of China

Publisher

American Meteorological Society

Subject

Oceanography

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