The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY (한국해양학회지:바다)

The Korean Society of Oceanography (한국해양학회)
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Sensitivity of Simulated Water Temperature to Vertical Mixing Scheme and Water Turbidity in the Yellow Sea

수직 혼합 모수화 기법과 탁도에 따른 황해 수온 민감도 실험

  • Kwak, Myeong-Taek (School of Earth and Environmental Sciences, Seoul National University) ;
  • Seo, Gwang-Ho (School of Earth and Environmental Sciences, Seoul National University) ;
  • Choi, Byoung-Ju (Department of Oceanography, Kunsan National University) ;
  • Kim, Chang-Sin (School of Earth and Environmental Sciences, Seoul National University) ;
  • Cho, Yang-Ki (School of Earth and Environmental Sciences, Seoul National University)
  • 곽명택 (서울대학교 지구환경과학부) ;
  • 서광호 (서울대학교 지구환경과학부) ;
  • 최병주 (군산대학교 해양학과) ;
  • 김창신 (서울대학교 지구환경과학부) ;
  • 조양기 (서울대학교 지구환경과학부)
  • Received : 2013.01.15
  • Accepted : 2013.06.03
  • Published : 2013.08.31
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Abstract

Accurate prediction of sea water temperature has been emphasized to make precise local weather forecast and to understand change of ecosystem. The Yellow Sea, which has turbid water and strong tidal current, is an unique shallow marginal sea. It is essential to include the effects of the turbidity and the strong tidal mixing for the realistic simulation of temperature distribution in the Yellow Sea. Evaluation of ocean circulation model response to vertical mixing scheme and turbidity is primary objective of this study. Three-dimensional ocean circulation model(Regional Ocean Modeling System) was used to perform numerical simulations. Mellor- Yamada level 2.5 closure (M-Y) and K-Profile Parameterization (KPP) scheme were selected for vertical mixing parameterization in this study. Effect of Jerlov water type 1, 3 and 5 was also evaluated. The simulated temperature distribution was compared with the observed data by National Fisheries Research and Development Institute to estimate model's response to turbidity and vertical mixing schemes in the Yellow Sea. Simulations with M-Y vertical mixing scheme produced relatively stronger vertical mixing and warmer bottom temperature than the observation. KPP scheme produced weaker vertical mixing and did not well reproduce tidal mixing front along the coast. However, KPP scheme keeps bottom temperature closer to the observation. Consequently, numerical ocean circulation simulations with M-Y vertical mixing scheme tends to produce well mixed vertical temperature structure and that with KPP vertical mixing scheme tends to make stratified vertical temperature structure. When Jerlov water type is higher, sea surface temperature is high and sea bottom temperature is low because downward shortwave radiation is almost absorbed near the sea surface.

지역규모의 정확한 일기예보와 해양생태계 변화 이해에 있어서 수온 예측은 매우 중요하다. 황해는 조류가 매우 빠르고 탁도가 높다. 이러한 해역에서는 수치 모델의 수직 혼합 기법 및 해수의 탁도에 따른 수형(water type)이 수온 구조 결정에 많은 영향을 미친다. 수직 혼합 기법 변화와 탁도의 변화에 따른 황해 수온 모사의 민감도를 알아보기 위해 3차원 해양 순환 모델인 Regional Ocean Modeling System (ROMS)을 사용하여 수치 실험을 수행하였다. 수직 혼합 기법은 해양 순환 모델에서 많이 사용되는 Mellor-Yamada level 2.5 closure(M-Y)와 K-Profile parameterization (KPP)을 사용하고, 탁도는 Jerlov의 분류에 따른 수형 1, 3, 5를 사용하여 수치 실험을 수행하고 그 결과를 국립수산과학원에서 제공하는 정선 해양 관측 자료와 비교, 분석하였다. M-Y 기법은 수직적 혼합을 상대적으로 강하게 모의하였으며 그 결과로 저층수온이 높게 형성되었다. 높은 저층 수온은 탁도를 높게 설정하면 완화되지만 표층 수온이 높아지는 단점이 있다. KPP 기법은 M-Y 기법보다는 수직 혼합을 약하게 모의하고 이 약한 수직 혼합 때문에 황해 연안을 따라 형성되는 조석전선을 잘 재현하지 못하였으나, 저층 수온은 관측 수온에 더 가깝게 재현하였다. 결과적으로 황해 3차원 해양순환 모델실험에서 M-Y 기법은 수직 혼합이 잘 되어 표층과 저층의 수온 차이가 작게 나타나고, KPP 기법은 이와 반대로 모의하였다. 탁도의 영향을 표현하는 Jerlov 수형은 높을수록 일사량이 낮은 수심까지만 투과되어 성층을 잘 표현하였고, 낮을수록 깊은 수심까지 일사량이 투과되어 표층과 저층의 수온차를 작게 모의하였다.

Keywords

References

  1. Ahn, Y.H., P. Shanmugam, and S. Gallegos, 2004. Evolution of suspended sediment patterns in the East China and Yellow seas. Journal of the Korean Society of Oceanography, 39(1): 26−24.
  2. Arakawa, A. and V.R. Lamb, 1977. Methods of computational physics. Academic Press. 17: 174−265.
  3. Beardsley, R.C., R. Limeburner, H. Yu, and G.A. Cannon, 1985. Discharge of the Changjiang (Yangtze River) into the East China Sea. Continental Shelf Research. 4: 57−76.
  4. Beckmann, A. and D.B. Haidvogel, 1992. Numerical Simulation of Flow around a Tall Isolated Seamount. Part I: Problem Formulation and Model Accuracy. Journal of Physical Oceanography. pp. 1736−1753.
  5. Burchard, H. and K. Bolding, 2001. Comparative analysis of four secondmoment turbulence closure models for the oceanic mixed layer, J. Phys. Oceanogr., 31: 1943-1968. https://doi.org/10.1175/1520-0485(2001)031<1943:CAOFSM>2.0.CO;2
  6. Cho, Y.K., B.H. Choi and H.W. Chung, 1995. Variation of tidal front in the southwestern sea of Korea. J. Korean Soc. Coast. ocean Eng., 7: 170-175.
  7. Cho, Y.K., M.O. Kim and B.C. Kim, 2000. Sea Fog around the Korea Peninsula, American Meteorological Society, 39: 2473-2479.
  8. Cho, Y.K., G.H. Seo, B.J. Choi, S. Kim, Y. Kim and E.P. Dever, 2009. Connectivity among straits of the Northwest Pacific Marginal Seas. Journal of Geophysical Research. 114. 2008JC005218.
  9. Chu, P., C. Yuchun and K. Akira, 2005. Seasonal Variability of the Yellow Sea/East China Sea Surface Fluxes and Thermohaline Structure. Advances in Atmospheric Sciences, 22(1): 1-20. https://doi.org/10.1007/BF02930865
  10. Dai, D., F. Qiao, C. Xia and K.-T. Jung, 2006. A numerical study on dynamic mechanisms of seasonal temperature variability in the Yellow Sea. J. Geophys. Res., 111: C11S05, doi:10.1029/2005JC003253.
  11. Durski, S.M., S.M. Glenn and D.B. Haidvogel, 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: C01015 https://doi.org/10.1029/2002JC001702
  12. Egbert, G.D. and S.Y. Erofeeva, 2002. Efficient inverse modeling of barotropic ocean tides. Journal of Atmospheric and Oceanic Technology, 19(2): 183-204. https://doi.org/10.1175/1520-0426(2002)019<0183:EIMOBO>2.0.CO;2
  13. Fairall, C.W., E.F. Bradley, D.P. Rogers, J.B. Edson and G.S. Young, 1996. Bulk parameterization of air-sea fluxes in Toga Coare. Journal of Geophysical Research, 101: 3747-3767. https://doi.org/10.1029/95JC03205
  14. Halliwell, G.R., 2004. Evaluation of vertical coordinate and vertical mixing algorithms in the HYbrid-Coordinate Ocean Model (HYCOM). Ocean Modeling, 7: 285-322. https://doi.org/10.1016/j.ocemod.2003.10.002
  15. Hirose, N., H.C. Lee and J.H. Yoon, 1999. Surface heat flux in the East China Sea and Yellow Sea. Journal of Physical Oceanography., 29: 401-417. https://doi.org/10.1175/1520-0485(1999)029<0401:SHFITE>2.0.CO;2
  16. Hu, D., 1994. Some striking features of circulation in Huanghai Sea and East China Sea. In : Oceanology of China Seas, Vol. 1, edited by D. Zhou. Y.B. Liang and C.K. Zeng Kluwer Academic Publishers, Dordrecht, Netherlands, pp. 27-38.
  17. Ichikawa, H. and R.C. Beardsley, 2002. The Current System in the Yellow and East China Seas. Journal of Oceanography, 58(1): 77-92. https://doi.org/10.1023/A:1015876701363
  18. Illicak, M., T.M. Ozgokmen, H. Perters, H.Z. Baumert, M. Iskandarani, 2008. Performance of two-equation turbulence closures in three-dimensional simulations of the Red Sea overflow. Ocean Modeling, 24: 122-139. https://doi.org/10.1016/j.ocemod.2008.06.001
  19. Jang, C.J. and H.W. Kang, 2004. Effects of Vertical Mixing Parameterization on the Mixed Layer Depth over the North Pacific in a Global OGCM. Ocean Science Journal, 44: 205-214.
  20. Jerlov, N.G., 1976. Marine Optics. Vol. 14 of Elsevier Oceanography Series, Elsevier.
  21. Kantha, L.H. and C.A. Clayson, 1994. An improved mixed layer model for geopysical applications, J. Geophys. Res., 99: 25,235-25,266. https://doi.org/10.1029/94JC02257
  22. Kwon, K.M., B.J. Choi, S.H. Lee, Y.K. Cho and C.J. Jang, 2011. Coastal Current Along the Eastern Boundary of the Yellow Sea in Summer: Numerical Simulations. J. Oceano. Soc. Korean, 16(4): pp. 155-168. https://doi.org/10.7850/jkso.2011.16.4.155
  23. Large, W.G., J.C. McWilliams and S.C. Doney, 1994. Oceanic vertical mixing: a review and a model with a nonlocal boundary layer parameterization. Reviews of Geophysics, 32: 363-403. https://doi.org/10.1029/94RG01872
  24. Large, W.G. and P.R. Gent, 1999. Validation of vertical mixing in an equatorial ocean model using large eddy simulations with observations, J. Phys. Oceanogr., 29: 449-464. https://doi.org/10.1175/1520-0485(1999)029<0449:VOVMIA>2.0.CO;2
  25. Lee, S.H. and R.C. Beardsley, 1999. Infuence of stratification on residual tidal currents in the Yellow Sea. J. Geophy. Res., 104: 15679-15701. https://doi.org/10.1029/1999JC900108
  26. Lie, H.J., 1984. A note on water masses and general circulation in the Yellow Sea (Hwanghae). Journal of the Korean Society of Oceanography, 19: 187-184.
  27. Lie, H.J., 1989. Tidal fronts in the southern Hwanghae (Yellow Sea), Cont. Shelf Res., 9: 527-546. https://doi.org/10.1016/0278-4343(89)90019-8
  28. Lie, H.J. and C.H. Cho, 2002. Recent advances in understanding the circulation and hydrography of the East China Sea. Fisheries Oceanography 11(6): 318-328. https://doi.org/10.1046/j.1365-2419.2002.00215.x
  29. Ma, J., F. Qiao, C. Xia and C.-S. Kim, 2006. Effects of the Yellow Sea Warm Current on the winter temperature distribution in a numerical model. J. Geophys. Res. Vol. 111, C11S04, doi:10.1029/2005JC003171.
  30. Mellor, G.L. and T. Yamada, 1982. Developement of a turbulence closure model for geophysical fluid problems. Reviews of Geophysics, 20: 851-875. https://doi.org/10.1029/RG020i004p00851
  31. Noh, Y., C.J. Jang, T. Yamagata, P.C. Chu and C.-H. Kim, 2002. Simulation of More Realistic Upper-Ocean Processes from an OGCM with a New Ocean Mixed Layer Model. J. Phys. Oceanogr., 32: 1284-1307. https://doi.org/10.1175/1520-0485(2002)032<1284:SOMRUO>2.0.CO;2
  32. Pang, I.-C., 2000. A seasonal Circulation in the East China Sea and Yellow Sea and its Possible Cause. Journal of the Korean Society of Oceanography, 35(4): 161-169.
  33. Price, J.F., R.F. Weller and R. Pinkel, 1986. Diurnal cycling: Observations and models of the upper ocean response to diurnal heating, cooling and wind mixing, J. Geophys. Res., 91: 8411-8427. https://doi.org/10.1029/JC091iC07p08411
  34. Seo, S.N., 2008. Digital 30sec Gridded Bathymetric Data of Korea Marginal Seas - KorBathy30s. J. Korean Soc. Coast. ocean Eng., 20: 110-120.
  35. Shchepetkin, A. and J.C. McWilliams, 1998. The regional oceanic modeling system (ROMS): a split-explicit, free-surface, topography-following-coordinate oceanic model. Ocean Modelling, 9: 347-404.
  36. Song, Y. and D.B. Haidvogel, 1994. A semi-implicit ocean circulation model using a generalized topography-following coordinate system. Journal of Computational Physics, 115(1): 228-244. https://doi.org/10.1006/jcph.1994.1189
  37. Wijesekera, H., J. Allen and P. Newberger, 2003. Modeling study of turbulent mixing over the continental shelf: Comparison of turbulent closure schemes, J. Geophys. Res., 108(C3): 3103, doi:10.1029/2001JC001234.

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