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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