Seasonal variability of the wind-generated near-inertial energy flux in the South China Sea

Sun Baonan; Lian Zhan; Yuan Yeli; Xu Haiyang

doi:10.1007/s13131-018-1338-6

南海风生近惯性能通量的敏感性分析

doi: 10.1007/s13131-018-1338-6

1.
海洋与大气学院, 中国海洋大学, 山东青岛, 266100;海洋环境与数值模拟研究室, 自然资源部第一海洋研究所, 山东青岛, 266061;区域海洋动力学与数值模拟功能实验室, 青岛海洋科学与技术试点国家实验室, 山东青岛, 266037
2.
海洋环境与数值模拟研究室, 自然资源部第一海洋研究所, 山东青岛, 266061;区域海洋动力学与数值模拟功能实验室, 青岛海洋科学与技术试点国家实验室, 山东青岛, 266037
3.
海洋环境与数值模拟研究室, 自然资源部第一海洋研究所, 山东青岛, 266061

基金项目: The National Natural Science Foundation of China under contract No. 40976016; the Basic Scientific Fund for the National Public Research Institutes of China under contract No. GY0217Q06; the National Science and Technology Major Project of the Ministry of Science and Technology of China under contract No. 2018YFF01014100; the Natural Science Foundation of Shandong Province, China under contract No. ZR2015PD009.

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- 收稿日期: 2018-05-23

Seasonal variability of the wind-generated near-inertial energy flux in the South China Sea

1.
College of Oceanic and Atmospheric Sciences, Ocean University of China, Qingdao 266100, China;Key Laboratory of Marine Science and Numerical Modeling, First Institute of Oceanography, Ministry of Natural Resources, Qingdao 266061, China;Laboratory for Regional Oceanography and Numerical Modeling, Pilot National Laboratory for Marine Science and Technology (Qingdao), Qingdao 266237, China
2.
Key Laboratory of Marine Science and Numerical Modeling, First Institute of Oceanography, Ministry of Natural Resources, Qingdao 266061, China;Laboratory for Regional Oceanography and Numerical Modeling, Pilot National Laboratory for Marine Science and Technology (Qingdao), Qingdao 266237, China
3.
Key Laboratory of Marine Science and Numerical Modeling, First Institute of Oceanography, Ministry of Natural Resources, Qingdao 266061, China

摘要

摘要: 有研究表明南海（SCS）的湍流混合率显著高于深海海洋，而风生的近惯性能量通量（NIEF）是其主要的能量来源。针对NIEF的计算方法，本文设计了一系列试验方案并分析了南海NIEF对不同计算方法中的各类参数的敏感性。结果表明，混合层深度（MLD）的定义对NIEF的量值影响明显，采用不同的MLD定义计算得到的NIEF最大值和最小值差值可达到后者的2倍以上。此外，在同样的MLD定义下，不同方法得到的NIEF在南海的差异可达2.5GW（1GW=1×10⁹ W）。基于时空特征的分析表明，不同方法得到的NIEF在南海南部和北半球的秋冬季差异更为显著。经过诊断计算，我们证实了台风是南海NIEF的重要来源，其提供的NIEF约占年平均结果的30%。海表风场增强可导致MLD加深，随之引起的NIEF减小量约为年平均的10%。是否考虑台风和相应的MLD变化，不会影响NIEF对于不同计算方案的敏感性。本文最终重新估计了南海年平均NIEF值为10±4 GW，显示基于多方案多参数的统计平均结果显著大于以往研究采用单一计算方案所得到的数值。
- 近惯性能量通量 /
- 混合层深度 /
- 敏感性分析 /
- 南海 /
- 台风影响
Abstract: After validated by the in-situ observation, the slab model is used to study the wind-generated near-inertial energy flux (NIEF) in the South China Sea (SCS) based on satellite-observed wind data, and its dependence on calculation methods and threshold criteria of the mixed layer depth (MLD) is investigated. Results illustrate that the total amount of NIEF in the SCS could be doubled if different threshold criteria of MLD are adopted. The NIEF calculated by the iteration and spectral solutions can lead to a discrepancy of 2.5 GW (1 GW=1×10⁹ W). Results also indicate that the NIEF exhibits spatial and temporal variations, which are significant in the boreal autumn, and in the southern part of the SCS. Typhoons are an important generator of NIEF in the SCS, which could account for approximately 30% of the annual mean NIEF. In addition, deepening of the MLD due to strong winds could lead to a decrease of NIEF by approximately by 10%. We re-estimate the annual mean NIEF in the SCS, which is (10±4) GW and much larger than those reported in previous studies.
- near-inertial energy flux /
- mixed layer depth /
- South China Sea /
- typhoon /

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参考文献(39)

Alford M H. 2001. Internal swell generation:the spatial distribution of energy flux from the wind to mixed layer near-inertial motions. Journal of Physical Oceanography, 31(8):2359-2368, doi: 10.1175/1520-0485(2001)031<2359:ISGTSD>2.0.CO;2

Alford M H. 2003. Improved global maps and 54-year history of wind-work on ocean inertial motions. Geophysical Research Letters, 30(8):1424-1429

Alford M H, Cronin M F, Klymak J M. 2012. Annual cycle and depth penetration of wind-generated near-inertial internal waves at ocean station papa in the northeast Pacific. Journal of Physical Oceanography, 42(6):889-909, doi: 10.1175/JPO-D-11-092.1

Alford M H, Mackinnon J A, Simmons H L, et al. 2015a. Near-inertial internal gravity waves in the ocean. Annual Review of Marine Science, 8:95-123

Alford M H, Peacock T, Mackinnon J A, et al. 2015b. The formation and fate of internal waves in the South China Sea. Nature, 528(7580):65-69

Carton J A, Chepurin G, Cao Xianhe, et al. 2000. A simple ocean data assimilation analysis of the global upper ocean 1950-95. Part I:methodology. Journal of Physical Oceanography, 30(2):311-326, doi: 10.1175/1520-0485(2000)030<0311:ASODAA>2.0.CO;2

Chen Gengxin, Xue Huijie, Wang Dongxiao, et al. 2013. Observed near-inertial kinetic energy in the northwestern South China Sea. Journal of Geophysical Research:Oceans, 118(10):4965-4977, doi: 10.1002/jgrc.20371

D'Asaro E A. 1985. The energy flux from the wind to near-inertial motions in the surface mixed layer. Journal of Physical Oceanography, 15(8):1043-1059, doi: 10.1175/1520-0485(1985)015<1043:TEFFTW>2.0.CO;2

D'Asaro E A, Black P G, Centurioni L R, et al. 2014. Impact of typhoons on the ocean in the Pacific. Bulletin of the American Meteorological Society, 95(9):1405-1418, doi: 10.1175/BAMS-D-12-00104.1

De Boyer Montégut C, Madec G, Fischer A S, et al. 2004. Mixed layer depth over the global ocean:An examination of profile data and a profile-based climatology. Journal of Geophysical Research:Oceans, 109(C12):C12003, doi: 10.1029/2004JC002378

Furuichi N, Hibiya T, Niwa Y. 2008. Model-predicted distribution of wind-induced internal wave energy in the world's oceans. Journal of Geophysical Research:Oceans, 113(C9):C09034

Huang Ruixin. 1998. Mixing and available potential energy in a boussinesq ocean. Journal of Physical Oceanography, 28(4):669-678, doi: 10.1175/1520-0485(1998)028<0669:MAAPEI>2.0.CO;2

Jan S, Lien R C, Ting C H. 2008. Numerical study of baroclinic tides in Luzon Strait. Journal of Oceanography, 64(5):789-802, doi: 10.1007/s10872-008-0066-5

Jia Xujing, Liu Qinyu, Sun Jilin. 2001. A comparison between two different definitions of the mixlayer and the thermocline in the South China Sea. Transactions of Oceanology and limnology, (1):1-7

Jochum M, Briegleb B P, Danabasoglu G, et al. 2013. The impact of oceanic near-inertial waves on climate. Journal of Climate, 26(9):2833-2844, doi: 10.1175/JCLI-D-12-00181.1

Kara A B, Rochford P A, Hurlburt H E. 2000. An optimal definition for ocean mixed layer depth. Journal of Geophysical Research:Oceans, 105(C7):16803-16821, doi: 10.1029/2000JC900072

Klymak J M, Alford M H, Pinkel R, et al. 2011. The breaking and scattering of the internal tide on a continental slope. Journal of Physical Oceanography, 41(5):926-945, doi: 10.1175/2010JPO4500.1

Li Juan, Liu Junliang, Cai Shuqun, et al. 2015. The spatiotemporal variation of the wind-induced near-inertial energy flux in the mixed layer of the South China Sea. Acta Oceanologica Sinica, 34(1):66-72, doi: 10.1007/s13131-015-0597-8

Li Ziliang, Wen Ping. 2017. Comparison between the response of the Northwest Pacific Ocean and the South China Sea to Typhoon Megi (2010). Advances in Atmospheric Sciences, 34(1):79-87, doi: 10.1007/s00376-016-6027-9

Lian Zhan, Fang Guohong, Wei Zexun, et al. 2015. A comparison of wind stress datasets for the South China Sea. Ocean Dynamics, 65(5):721-734, doi: 10.1007/s10236-015-0832-z

Liu Junliang, Cai Shuqun, Wang Shengan. 2014. Diurnal wind and nonlinear interaction between inertial and tidal currents in the South China Sea during the passage of Typhoon Conson. Acta Oceanologica Sinica, 33(5):1-7, doi: 10.1007/s13131-014-0467-9

Milliff R F, Large W G, Morzel J, et al. 1999. Ocean general circulation model sensitivity to forcing from scatterometer winds. Journal of Geophysical Research:Oceans, 104(C5):11337-11358, doi: 10.1029/1998JC900045

Pan Jiayi, Sun Yujuan. 2013. Estimate of ocean mixed layer deepening after a typhoon passage over the South China Sea by using satellite data. Journal of Physical Oceanography, 43(3):498-506, doi: 10.1175/JPO-D-12-01.1

Plueddemann A J, Farrar J T. 2006. Observations and models of the energy flux from the wind to mixed-layer inertial currents. Deep Sea Research Part Ⅱ:Topical Studies in Oceanography, 53(1-2):5-30

Pollard R T, Millard R C Jr. 1970. Comparison between observed and simulated wind-generated inertial oscillations. Deep Sea Research and Oceanographic Abstracts, 17(4):813-821, doi: 10.1016/0011-7471(70)90043-4

Qu Tangdong. 2000. Upper-layer circulation in the South China Sea. Journal of Physical Oceanography, 30(6):1450-1460, doi: 10.1175/1520-0485(2000)030<1450:ULCITS>2.0.CO;2

Rimac A, Von Storch J S, Eden C, et al. 2013. The influence of high-resolution wind stress field on the power input to near-inertial motions in the ocean. Geophysical Research Letters, 40(18):4882-4886, doi: 10.1002/grl.50929

Silverthorne K E, Toole J M. 2009. Seasonal kinetic energy variability of near-inertial motions. Journal of Physical Oceanography, 39(4):1035-1049, doi: 10.1175/2008JPO3920.1

Sprintall J, Roemmich D. 1999. Characterizing the structure of the surface layer in the Pacific Ocean. Journal of Geophysical Research:Oceans, 1042(C10):23297-23311

Sprintall J, Tomczak M. 1992. Evidence of the barrier layer in the surface layer of the tropics. Journal of Geophysical Research:Oceans, 97(C5):7305-7316, doi: 10.1029/92JC00407

Sun Chengxue, Liu Qinyu, Jia Yinglai. 2007. Annual and interannual variations of the mixed layer in the South China Sea. Periodical of Ocean University of China (in Chinese), 37(2):197-203

Sun Lu, Zheng Quanan, Wang Dongxiao, et al. 2011. A case study of near-inertial oscillation in the South China Sea using mooring observations and satellite altimeter data. Journal of Oceanography, 67(6):677-687, doi: 10.1007/s10872-011-0081-9

Tian Jiwei, Yang Qingxuan, Zhao Wei. 2009. Enhanced diapycnal mixing in the South China Sea. Journal of Physical Oceanography, 39(12):3191-3203, doi: 10.1175/2009JPO3899.1

Von Storch J S, Sasaki H, Marotzke J. 2007. Wind-generated power input to the deep ocean:an estimate using a 1/10° general circulation model. Journal of Physical Oceanography, 37(3):657-672, doi: 10.1175/JPO3001.1

Watanabe M, Hibiya T. 2002. Global estimates of the wind-induced energy flux to inertial motions in the surface mixed layer. Geophysical Research Letters, 29(8):1239

Wu Qiaoyan, Chen Dake. 2012. Typhoon-induced variability of the oceanic surface mixed layer observed by Argo floats in the Western North Pacific Ocean. Atmosphere-Ocean, 50(S1):4-14

Yang Qingxuan, Zhao Wei, Liang Xinfeng, et al. 2016. Three-dimensional distribution of turbulent mixing in the South China Sea. Journal of Physical Oceanography, 46(3):769-788, doi: 10.1175/JPO-D-14-0220.1

Yang Qingxuan, Zhou Lei, Tian Jiwei, et al. 2015. The roles of Kuroshio intrusion and mesoscale eddy in upper mixing in the Northern South China Sea. Journal of Coastal Research, 30(1):192-198

Zhai Xiaoming, Greatbatch R J, Eden C, et al. 2009. On the loss of wind-induced near-inertial energy to turbulent mixing in the upper ocean. Journal of Physical Oceanography, 39(11):3040-3045, doi: 10.1175/2009JPO4259.1

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文章访问数: 558
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PDF下载量: 286
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南海风生近惯性能通量的敏感性分析

doi: 10.1007/s13131-018-1338-6

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出版历程

Seasonal variability of the wind-generated near-inertial energy flux in the South China Sea

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出版历程

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