Acta Oceanologica Sinica

, Volume 33, Issue 7, pp 72–82 | Cite as

Assimilating the along-track sea level anomaly into the regional ocean modeling system using the ensemble optimal interpolation

  • Guokun Lyu
  • Hui Wang
  • Jiang Zhu
  • Dakui Wang
  • Jiping Xie
  • Guimei Liu
Article

Abstract

The ensemble optimal interpolation (EnOI) is applied to the regional ocean modeling system (ROMS) with the ability to assimilate the along-track sea level anomaly (TSLA). This system is tested with an eddy-resolving system of the South China Sea (SCS). Background errors are derived from a running seasonal ensemble to account for the seasonal variability within the SCS. A fifth-order localization function with a 250 km localization radius is chosen to reduce the negative effects of sampling errors. The data assimilation system is tested from January 2004 to December 2006. The results show that the root mean square deviation (RMSD) of the sea level anomaly decreased from 10.57 to 6.70 cm, which represents a 36.6% reduction of error. The data assimilation reduces error for temperature within the upper 800 m and for salinity within the upper 200 m, although error degrades slightly at deeper depths. Surface currents are in better agreement with trajectories of surface drifters after data assimilation. The variance of sea level improves significantly in terms of both the amplitude and position of the strong and weak variance regions after assimilating TSLA. Results with AGE error (AGE) perform better than no AGE error (NoAGE) when considering the improvements of the temperature and the salinity. Furthermore, reasons for the extremely strong variability in the northern SCS in high resolution models are investigated. The results demonstrate that the strong variability of sea level in the high resolution model is caused by an extremely strong Kuroshio intrusion. Therefore, it is demonstrated that it is necessary to assimilate the TSLA in order to better simulate the SCS with high resolution models.

Key words

ensemble optimal interpolation regional ocean modeling system along-track sea level anomaly South China Sea variability 

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Copyright information

© The Chinese Society of Oceanography and Springer-Verlag Berlin Heidelberg 2014

Authors and Affiliations

  • Guokun Lyu
    • 1
    • 3
  • Hui Wang
    • 2
    • 3
  • Jiang Zhu
    • 4
  • Dakui Wang
    • 3
  • Jiping Xie
    • 5
  • Guimei Liu
    • 3
  1. 1.Physical Oceanography LaboratoryOcean University of ChinaQingdaoChina
  2. 2.College of Environmental Science and EngineeringOcean University of ChinaQingdaoChina
  3. 3.Key Laboratory of Research on Marine Hazards Forecasting, National Marine Environmental Forecasting CenterState Oceanic AdministrationBeijingChina
  4. 4.State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry, Institute of Atmospheric PhysicsChinese Academy of SciencesBeijingChina
  5. 5.International Center for Climate and Environmental Sciences, Institute of Atmospheric PhysicsChinese Academy of SciencesBeijingChina

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