

FOLLOWUS
1.College of Oceanic and Atmospheric Sciences, Ocean University of China, Qingdao 266100, China
2.Physical Oceanography Laboratory/CIMST, Ocean University of China and Qingdao National Laboratory for Marine Science and Technology, Qingdao 266100, China
3.The First Institute of Oceanography, Ministry of Natural Resources, Qingdao 266061, China
4.Laboratory for Regional Oceanography and Numerical Modeling, Qingdao National Laboratory for Marine Science and Technology, Qingdao 266000, China
5.China National Environmental Monitoring Centre, Beijing 100012, China
6.Operational Oceanography Institution, Dalian Ocean University, Dalian 116023, China
Zhigang YAO, E-mail:yaozhigang@ouc.edu.cn
收稿:2019-10-10,
录用:2019-11-12,
网络首发:2019-12-03,
纸质出版:2021-01
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The sensitivity of numerical simulation to vertical mixing parameterization schemes: a case study for the Yellow Sea Cold Water Mass[J]. 海洋湖沼学报(英文), 2021,39(1):64-78.
Congcong BI, Zhigang YAO, Xianwen BAO, et al. The sensitivity of numerical simulation to vertical mixing parameterization schemes: a case study for the Yellow Sea Cold Water Mass[J]. Journal of Oceanology and Limnology, 2021, 39(1): 64-78.
The sensitivity of numerical simulation to vertical mixing parameterization schemes: a case study for the Yellow Sea Cold Water Mass[J]. 海洋湖沼学报(英文), 2021,39(1):64-78. DOI: 10.1007/s00343-019-9262-y.
Congcong BI, Zhigang YAO, Xianwen BAO, et al. The sensitivity of numerical simulation to vertical mixing parameterization schemes: a case study for the Yellow Sea Cold Water Mass[J]. Journal of Oceanology and Limnology, 2021, 39(1): 64-78. DOI: 10.1007/s00343-019-9262-y.
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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