Liu Lei

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Liu
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Lei
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  • Article
    Retrieving density and velocity fields of the ocean's interior from surface data
    (John Wiley & Sons, 2014-12-12) Liu, Lei ; Peng, Shiqiu ; Wang, Jinbo ; Huang, Rui Xin
    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.
  • Article
    Reconstruction of ocean's interior from observed sea surface information
    (John Wiley & Sons, 2017-02-10) Liu, Lei ; Peng, Shiqiu ; Huang, Rui Xin
    Observational surface data are used to reconstruct the ocean's interior through the “interior + surface quasigeostrophic” (isQG) method. The input data include the satellite-derived sea surface height, satellite-derived sea surface temperature, satellite-derived or Argo-based sea surface salinity, and an estimated stratification of the region. The results show that the isQG retrieval of subsurface density anomalies is quite promising compared to Argo profile data. At ∼1000 m depth, the directions of retrieved velocity anomalies are comparable to those derived from Argo float trajectories. The reconstruction using surface density input field approximated only by SST (with constant SSS) performs less satisfactorily than that taking into account the contribution of SSS perturbations, suggesting that the observed SSS information is important for the application of the isQG method. Better reconstruction is obtained in the warm season than in the cold season, which is probably due to the stronger stratification in the warm season that confines the influence of the biases in the surface input data (especially SSS) in a shallow layer. The comparison between the performance of isQG with Argo-based SSS input and that with satellite-derived SSS input suggests that the biases in the SSS products could be a major factor that influences the isQG performance. With reduced biases in satellite-derived SSS in the future, the measurement-based isQG method is expected to achieve better reconstruction of ocean interior and thus is promising in practical application.