Cite this paper:
Congcong BI, Zhigang YAO, Xianwen BAO, Cong ZHANG, Yang DING, Xihui LIU, Junru GUO. 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
Congcong BI1,2, Zhigang YAO1,2, Xianwen BAO1,2, Cong ZHANG3,4, Yang DING2, Xihui LIU5, Junru GUO6
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
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.
Key words:    Yellow Sea Cold Water Mass (YSCWM)|vertical mixing parameterizations|thermocline|background diffusivity|surface wave induced mixing   
Received: 2019-10-10   Revised: 2019-11-12
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References:
Babanin A V, Ganopolski A, Phillips W R C. 2009. Waveinduced upper-ocean mixing in a climate model of intermediate complexity. Ocean Modelling, 29(3):189-197.
Cho K D. 1982. On the influence of the Yellow Sea Bottom Cold Water on the demersal fishing grounds. Journal of the Korean Society of Fisheries and Ocean Technology, 18(1):25-33.
Craig P D, Banner M L. 1994. Modeling wave-enhanced turbulence in the ocean surface layer. Journal of Physical Oceanography, 24(12):2 546-2 559.
Durski S M, Glenn S M, Haidvogel D B. 2004. Vertical mixing schemes in the coastal ocean:comparison of the level 2.5 Mellor-Yamada scheme with an enhanced version of the K profile parameterization. Journal of Geophysical Research, 109(C1):C01015.
Editorial Board for Marine Atlas. 1992. Marine Atlas of Bohai Sea, Yellow Sea, East China Sea:Hydrology. China Ocean Press, Beijing, China. p.89. (in Chinese)
Galperin B, Kantha L H, Hassid S, Rosati A. 1988. A quasiequilibrium turbulent energy model for geophysical flows.Journal of the Atmospheric Sciences, 45(1):55-62.
Ghantous M, Babanin A V. 2014. One-dimensional modelling of upper ocean mixing by turbulence due to wave orbital motion. Nonlinear Processes in Geophysics, 21(1):325-338.
Guan B X. 1963. A preliminary study of the temperature variations and the characteristics of the circulation of the cold water mass of the Yellow Sea. Oceanologia et Limnologia Sinica, 5(4):255-284. (in Chinese with English abstract)
Han L, Yuan Y L. 2014. An ocean circulation model based on Eulerian forward-backward difference scheme and threedimensional, primitive equations and its application in regional simulations. Journal of Hydrodynamics, 26(1):37-49.
Ho C P, Wang Y X, Lei Z Y, Xu S. 1959. A prelimenary study of the formation of Yellow Sea Cold Mass and its properties. Oceanologia et Limnologia Sinica, 2(1):11-15. (in Chinese with English abstract)
Jochum M, Briegleb B P, Danabasoglu G, Large W G, Norton N J, Jayne S R, Bryan F O. 2013. The impact of oceanic near-inertial waves on climate. Journal of Climate, 26(9):2 833-2 844.
Large W G, McWilliams J C, Doney S C. 1994. Oceanic vertical mixing:a review and a model with a nonlocal boundary layer parameterization. Reviews of Geophysics, 32(4):363-403.
Li A, Yu F, Diao X Y, Si G C. 2015. Interannual variability of temperature of the northern Yellow Sea Cold Water Mass.Acta Oceanologica Sinica, 37(1):30-42. (in Chinese with English abstract)
Li A. 2016. The Study on Interannual Variability of Yellow Sea Cold Water Mass. Institute of Oceanology, University of Chinese Academy of Sciences, Beijing, China. p.23-26.(in Chinese with English abstract)
Li M, Zhong L J, Boicourt W C. 2005. Simulations of Chesapeake Bay estuary:sensitivity to turbulence mixing parameterizations and comparison with observations.Journal of Geophysical Research, 110(C12):C12004.
Liu J, Ning P. 2011. Species composition and faunal characteristics of fishes in the Yellow Sea. Biodiversity Science, 19(6):764-769. (in Chinese with English abstract)
Lü X G, Qiao F L, Xia C S, Wang G S, Yuan Y L. 2010.Upwelling and surface cold patches in the Yellow Sea in summer:effects of tidal mixing on the vertical circulation.Continental Shelf Research, 30(6):620-632.
Mellor G L, Yamada T. 1982. Development of a turbulence closure model for geophysical fluid problems. Reviews of Geophysics, 20(4):851-875.
Mellor G. 2003. The three-dimensional current and surface wave equations. Journal of Physical Oceanography, 33(9):1 978-1 989.
Miao J B, Liu X Q, Xue Y. 1991. Study on the formational mechanism of the Northern Yellow (Huanghai) Sea cold water mass (I)-solution of the model. Science in China Series B, 34(8):963-976.
Moon J H, Hirose N, Yoon J H. 2009. Comparison of wind and tidal contributions to seasonal circulation of the Yellow Sea. Journal of Geophysical Research, 114(C8):C08016.
Murphy A H. 1988. Skill scores based on the mean square error and their relationships to the correlation coefficient.Monthly Weather Review, 116(12):2 417-2 424.
Noh Y, Ok H, Lee E, Toyoda T, Hirose N. 2016. Parameterization of Langmuir circulation in the ocean mixed layer model using LES and its application to the OGCM. Journal of Physical Oceanography, 46(1):57-78.
Qiao F L, Yuan Y L, Ezer T, Xia C S, Yang Y Z, Lü X G, Song Z Y. 2010. A three-dimensional surface wave-ocean circulation coupled model and its initial testing. Ocean Dynamics, 60(5):1 339-1 355.
Qiao F L, Yuan Y L, Yang Y Z, Zheng Q A, Xia C S, Ma J. 2004. Wave-induced mixing in the upper ocean:distribution and application to a global ocean circulation model. Geophysical Research Letters, 31(11):L11303.
Ren H J, Zhan J M. 2005. A numerical study on the seasonal variability of the Yellow Sea cold water mass and the related dynamics. Journal of Hydrodynamics, 20(S1):887-896. (in Chinese with English abstract)
Shchepetkin A F, McWilliams J C. 2003. A method for computing horizontal pressure-gradient force in an oceanic model with a nonaligned vertical coordinate.Journal of Geophysical Research, 108(C3):3 090.
Shchepetkin A F, McWilliams J C. 2005. The regional oceanic modeling system (ROMS):a split-explicit, free-surface, topography-following-coordinate oceanic model. Ocean Modelling, 9(4):347-404.
Smyth W D, Skyllingstad E D, Crawford G B, Wijesekera H. 2002. Nonlocal fluxes and Stokes drift effects in the K-profile parameterization. Ocean Dynamics, 52(3):104-115.
Song X, Lin X P, Wang Y. 2009. The preliminary study of long-term variability of the Yellow Sea cold water in summer and its possible reasons. Journal of Guangdong Ocean University, 29(3):59-63. (in Chinese with English abstract)
Su Y S, Su J. 1996. A preliminary study on the surface cold water in the Bohai and Yellow Sea during summer and its formation mechanisms. Acta Oceanologica Sinica, 18(1):13-20. (in Chinese)
Umlauf L, Burchard H. 2003. A generic length-scale equation for geophysical turbulence models. Journal of Marine Research, 61(2):235-265.
Wang B D. 2000. Characteristics of variations and interrelations of biogenic elements in the Huanghai Sea Cold Water Mass. Acta Oceanologica Sinica, 22(6):47-54. (in Chinese with English abstract)
Warner J C, Sherwood C R, Arango H G, Signell R P. 2005.Performance of four turbulence closure models implemented using a generic length scale method. Ocean Modelling, 8(1-2):81-113.
Wijesekera H W, Allen J S, Newberger P A. 2003. Modeling study of turbulent mixing over the continental shelf:comparison of turbulent closure schemes. Journal of Geophysical Research, 108(C3):3 103.
Xin M, Ma D Y, Wang B D. 2015. Chemicohydrographic characteristics of the Yellow Sea Cold Water Mass. Acta Oceanologica Sinica, 34(6):5-11.
Yang H W, Cho Y K, Seo G H, You S H, Seo J W. 2014.Interannual variation of the southern limit in the Yellow Sea Bottom Cold Water and its causes. Journal of Marine Systems, 139:119-127.
Yao Z G, Bao X W, Li N, Li X B, Wan K, Song J. 2012.Seasonal evolution of the northern Yellow Sea Cold Water Mass. Periodical of Ocean University of China, 42(6):9-15. (in Chinese with English abstract)
Yu F, Zhang Z X, Diao X Y, Guo J S, Tang Y X. 2006. Analysis of evolution of the Huanghai Sea Cold Water Mass and its relationship with adjacent water masses. Acta Oceanologica Sinica, 28(5):26-34. (in Chinese with English abstract)
Yu X J, Guo X Y. 2018. Intensification of water temperature increase inside the bottom cold water by horizontal heat transport. Continental Shelf Research, 165:26-36.
Zhang Y K, He X M, Gao Y F. 1983. Preliminary analysis on the modified water masses in the north Yellow Sea and the Bohai Sea. Transactions of Oceanology and Limnology, 2:19-26. (in Chinese with English abstract)
Zhang Y K, Yang Y L. 1996. Analyses of the variational characteristics of the north Huanghai Sea Cold Water Mass. Marine Forecasts, 13(4):15-21. (in Chinese with English abstract)
Zhao B R. 1985. The fronts of the Huanghai Sea Cold Water Mass induced by tidal mixing. Oceanologia et Limnologia Sinica, 16(6):451-460. (in Chinese with English abstract)
Zhao B R. 1987. The continental shelf fronts induced by tidal mixing in the Huanghai Sea. Journal of Oceanography of Huanghai & Bohai Seas, 5(2):16-23. (in Chinese with English abstract)
Zhao B R. 1989. The study on the basic characteristics and formation mechanisms of the intense thermocline in the Bohai Sea, Yellow Sea and the northern East Sea. Acta Oceanologica Sinica, 11(4):401-410. (in Chinese)
Zhu J Y, Shi J, Guo X Y, Gao H W, Yao X H. 2018. Air-sea heat flux control on the Yellow Sea Cold Water Mass intensity and implications for its prediction. Continental Shelf Research, 152:14-26.
Zieger S, Babanin A V, Erick Rogers W, Young I R. 2015.Observation-based source terms in the third-generation wave model WAVEWATCH. Ocean Modelling, 96:2-25.
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