Author Posting. © American Geophysical Union, 2014. This article is posted here by permission of American Geophysical Union for personal use, not for redistribution. The definitive version was published in Journal of Geophysical Research: Oceans 119 (2014): 8512–8529, doi:10.1002/2014JC010221.
Using the “interior + surface quasigeostrophic” (isQG) method, the density and horizontal velocity fields of the ocean's interior can be retrieved from surface data. This method was applied to the Simple Ocean Data Assimilation (SODA) and the Hybrid Coordinate Ocean Model (HYCOM)/Navy Coupled Ocean Data Assimilation (NCODA) reanalysis data sets. The input surface data include sea surface height (SSH), sea surface temperature (SST), sea surface salinity (SSS), and a region-averaged stratification. The retrieved subsurface fields are compared with reanalysis data for three tested regions, and the results indicate that the isQG method is robust. The isQG method is particularly successful in the energetic regions like the Gulf Stream region with weak stratification, and the Kuroshio region with strong correlation between sea surface density (SSD) and SSH. It also works, though less satisfactorily, in the Agulhas leakage region. The performance of the isQG method in retrieving subsurface fields varies with season, and peaks in winter when the mixed layer is deeper and stratification is weaker. In addition, higher-resolution data may facilitate the isQG method to achieve a more successful reconstruction for the velocity retrieval. Our results suggested that the isQG method can be used to reconstruct the ocean interior from the satellite-derived SSH, SST, and SSS data in the near future.
This work was jointly supported by the MOST of China (grant 2011CB403505 & 2014CB953904), the China Special Fund for Meteorological Research in the Public Interest (NO. GYHY201406008), the Strategic Priority Research Program of the Chinese Academy of Sciences (grant XDA11010304), National Natural Science Foundation of China (grant 41376021). J. Wang is supported by the National Science Foundation (NSF) through grant OCE-1234473.
Sea surface and interior
Satellite remote sensing
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