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The sensitivity of numerical simulation to vertical mixing parameterization schemes: a case study for the Yellow Sea Cold Water Mass

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Abstract

The vertical mixing parameterization scheme, by providing the effects of some explicitly missed physical processes and more importantly closing the energy budgets, is a critical model component and therefore imposes significant impacts on model performance. The Yellow Sea Cold Water Mass (YSCWM), as the most striking and unique phenomenon in the Yellow Sea during summer, is dramatically affected by vertical mixing process during its each stage and therefore seriously sensitive to the proper choice of parameterization scheme. In this paper, a hindcast of YSCWM in winter of 2006 was implemented by using the Regional Ocean Modeling System (ROMS). Three popular parameterization schemes, including the level 2.5 Mellor-Yamada closure (M-Y 2.5), Generic Length Scale closure (GLS) and K-Profile Parameterization (KPP), were tested and compared with each other by conducting a series of sensitivity model experiments. The influence of different parameterization schemes on modeling the YSCWM was then carefully examined and assessed based on these model experiments. Although reasonable thermal structure and its seasonal variation were well reproduced by all schemes, considerable differences could still be found among all experiments. A warmer and spatially smaller simulation of YSCWM, with very strong thermocline, appeared in M-Y 2.5 experiment, while a spatially larger YSCWM with shallow mixed layer was found in GLS and KPP schemes. Among all the experiments, the discrepancy, indicated by core temperature, appeared since spring, and grew gradually by the end of November. Additional experiments also confirmed that the increase of background diffusivity could effectively weaken the YSCWM, in either strength or coverage. Surface wave, another contributor in upper layer, was found responsible for the shrinkage of YSCWM coverage. The treatment of wave effect as an additional turbulence production term in prognostic equation was shown to be more superior to the strategy of directly increasing diffusivity for a coastal region.

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Acknowledgment

We thank the Data and Simulation Center of the Physical Oceanography Laboratory, Ocean University of China, for providing super computers for all the model simulations. We thank the National Science & Technology Infrastructure-the Dalian branch of National Marine Scientific Data Center (http://odc.dlou.edu.cn/) for providing data support. We also thank the National Marine Data and Information Service of China, Sung Kyun Kwan University (Korea), OSU Tidal Data Inversion, European Centre for Medium-Range Weather Forecasts (ECMWF), HYCOM Consortium, National Ocean and Atmosphere Administration (NOAA), and Bureau of Hydrology, Ministry of Water Resources of China for providing valuable data.

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Authors and Affiliations

  1. College of Oceanic and Atmospheric Sciences, Ocean University of China, Qingdao, 266100, China

    Congcong Bi, Zhigang Yao & Xianwen Bao

  2. Physical Oceanography Laboratory, Ocean University of China and Qingdao National Laboratory for Marine Science and Technology, Qingdao, 266100, China

    Congcong Bi, Zhigang Yao, Xianwen Bao & Yang Ding

  3. The First Institute of Oceanography Ministry of Natural Resources, Qingdao, 266061, China

    Cong Zhang

  4. Laboratory for Regional Oceanography and Numerical Modeling, Qingdao National Laboratory for Marine Science and Technology, Qingdao, 266000, China

    Cong Zhang

  5. China National Environmental Monitoring Centre, Beijing, 100012, China

    Xihui Liu

  6. Operational Oceanography Institution, Dalian Ocean University, Dalian, 116023, China

    Junru Guo

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  1. Congcong Bi
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Correspondence to Zhigang Yao.

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Supported by the National Natural Science Foundation of China (Nos. 41606005, 41430963, 41676004), the National Program on Global Change and Air-Sea Interaction (No. GASI-GEOGE-03), the Liaoning Revitalization Talents Program (No. XLYC1807161), and the Dalian High-level Talents Innovation Support Plan (No. 2017RQ063)

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Bi, C., Yao, Z., Bao, X. et al. The sensitivity of numerical simulation to vertical mixing parameterization schemes: a case study for the Yellow Sea Cold Water Mass. J. Ocean. Limnol. 39, 64–78 (2021). https://doi.org/10.1007/s00343-019-9262-y

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  • DOI: https://doi.org/10.1007/s00343-019-9262-y

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