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Ocean Dynamics

, Volume 62, Issue 5, pp 753–769 | Cite as

M2 tidal dynamics in Bohai and Yellow Seas: a hybrid data assimilative modeling study

  • Zhigang Yao
  • Ruoying He
  • Xianwen Bao
  • Dexing Wu
  • Jun Song
Article
Part of the following topical collections:
  1. Topical Collection on the 3rd International Workshop on Modelling the Ocean 2011

Abstract

A high-resolution hybrid data assimilative (DA) modeling system is adapted to study the M2 barotropic tidal characteristics and dynamics in the Bohai and Yellow Seas. In situ data include tidal harmonics extracted from both coastal sea level and bottom pressure observations. The hybrid DA system consists of both forward and inverse models. The former is three-dimensional, finite-difference, nonlinear Regional Ocean Modeling System (ROMS). The latter is a three-dimensional, linearized, frequency-domain, finite-element model TRUXTON. The DA system assimilates in situ observations via the inversion of the barotropic tidal open boundary conditions (OBCs). Model skill is evaluated by comparing misfits between the observed and modeled tidal harmonics. The assimilation scheme is found effective and efficient in correcting the tidal OBCs, which in turn improves ROMS tidal solutions. Up to 50% reduction of model/data misfits is achieved after data assimilation. M2 co-tidal maps constructed from the posterior (data assimilative) ROMS solutions agree well with observational analysis of (Fang et al. 2004). Detailed analyses on tidal mixing, residual current, energy flux, dissipation, and momentum term balance dynamics are performed for M2 constituent, revealing complex M2 tidal characteristics in the study region and the important role of coastal geometry and topography in affecting regional tidal dynamics.

Keywords

Tidal inversion Boundary conditions Hybrid data assimilation Refining 

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Copyright information

© Springer-Verlag 2012

Authors and Affiliations

  • Zhigang Yao
    • 1
    • 2
    • 3
  • Ruoying He
    • 2
  • Xianwen Bao
    • 1
    • 3
  • Dexing Wu
    • 1
  • Jun Song
    • 3
    • 4
  1. 1.College of Physical and Environmental OceanographyOcean University of ChinaQingdaoChina
  2. 2.Department of Marine, Earth and Atmospheric SciencesNorth Carolina State UniversityRaleighUSA
  3. 3.Key Laboratory of Physical OceanographyOcean University of ChinaQingdaoChina
  4. 4.National Marine Data and Information ServiceState Oceanic AdministrationTianjinChina

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