Revisiting the seasonal wave height variability in the South China Sea with merged satellite altimetry observations

SU Hui; WEI Chunlei; JIANG Shaocai; LI Peiliang; ZHAI Fangguo

doi:10.1007/s13131-017-1073-4

基于多源融合卫星高度计观测数据的南海海浪有效波高的季节变化研究

doi: 10.1007/s13131-017-1073-4

1.
厦门海洋环境监测中心站, 国家海洋局, 厦门, 361008
2.
北海海洋环境监测中心站, 国家海洋局, 北海, 536007
3.
海洋与大气学院, 中国海洋大学, 266100

计量
- 文章访问数: 1289
- HTML全文浏览量: 111
- PDF下载量: 751
- 被引次数: 0
出版历程
- 收稿日期: 2016-03-22
- 修回日期: 2016-08-25

Revisiting the seasonal wave height variability in the South China Sea with merged satellite altimetry observations

1.
Central Marine Environmental Monitoring Station of Xiamen, East China Sea Branch, State Oceanic Administration, Xiamen 361008, China
2.
Beihai Marine Environmental Monitoring Center, South China Sea Branch, State Oceanic Administration, Beihai 536007, China
3.
College of Oceanic and Atmospheric Sciences, Ocean University of China, Qingdao 266100, China

摘要

摘要: 本论文利用2009年9月至2015年8月期间的格点化日平均卫星观测资料，研究了南海海浪有效波高的季节变化。结果显示整个南海的有效波高呈现一致的季节变化，其最大值发生在12月或者1月，最小值发生在5月。在全年12个月中，南海海浪有效波高均在吕宋海峡附近最大，并向南逐渐减小。南海海表面风也具有类似的季节变化，但是在大部分月份中其空间分布和有效波高的空间分布并不一致。进一步分析表明有效波高的变化主要是由涌浪主导，而相比而言风浪则非常小。在东北季风期间，风浪的最大值出现在台湾岛的西南海域和越南沿岸的东南海域；而在西南季风期间，风浪的最大值则出现在南海的中、南部。南海的极端波浪条件也存在显著地季节变化。在南海北部和中部的大部分区域，大于充分发展海浪有效波高理论值的1/100大波波高的极大值主要出现在8月-9月，这与南海及太平洋区域的强热带气旋活动密切相关。与前人工作相比，本论文研究成果也表明太平洋的海浪场对南海海浪场的时间变化具有重要影响。
- 有效波高 /
- 季节变化 /
- 南海 /
- 卫星观测
Abstract: The seasonal variability of the significant wave height (SWH) in the South China Sea (SCS) is investigated using the most up-to-date gridded daily altimeter data for the period of September 2009 to August 2015. The results indicate that the SWH shows a uniform seasonal variation in the whole SCS, with its maxima occurring in December/January and minima in May. Throughout the year, the SWH in the SCS is the largest around Luzon Strait (LS) and then gradually decreases southward across the basin. The surface wind speed has a similar seasonal variation, but with different spatial distributions in most months of the year. Further analysis indicates that the observed SWH variations are dominated by swell. The wind sea height, however, is much smaller. It is the the largest in two regions southwest of Taiwan Island and southeast of Vietnam Coast during the northeasterly monsoon, while the largest in the central/southern SCS during the southwesterly monsoon. The extreme wave condition also experiences a significant seasonal variation. In most regions of the northern and central SCS, the maxima of the 99th percentile SWH that are larger than the SWH theoretically calculated with the wind speed for the fully developed seas mainly appear in August–November, closely related to strong tropical cyclone activities. Compared with previous studies, it is also implied that the wave climate in the Pacific Ocean plays an important role in the wave climate variations in the SCS.
- significant wave height /
- seasonal variability /
- South China Sea /
- satellite observations

HTML全文

参考文献(49)

?Alves J H G M. 2006. Numerical modeling of ocean swell contributions to the global wind-wave climate. Ocean Modell, 11(1–2):98-122

Anoop T R, Kumar V S, Shanas P R, et al. 2015. Surface wave climatology and its variability in the North Indian Ocean based on ERA-interim reanalysis. J Atmos Oceanic Technol, 32(7):1372-1385

Booij N, Ris R C, Holthuijsen L H. 1999. A third-generation wave model for coastal regions:1. Model description and validation. J Geophys Res, 104(C4):7649-7666

Chan J C L. 2005. Interannual and interdecadal variations of tropical cyclone activity over the western North Pacific. Meteor Atmos Phys, 89(1–4):143-152

Chen Qili. 1987. The South China Sea wave climate and some problems about its forecast. Mar Forecast (in Chinese), 4(2):39-46

Chen Ge, Chapron B, Ezraty R, et al. 2002. A global view of swell and wind sea climate in the ocean by satellite altimeter and scatterometer. J Atmos Oceanic Technol, 19(11):1849-1859

Chen Hongxia, Hua Feng, Yuan Yeli. 2006. Seasonal characteristics and temporal variations of ocean wave in the Chinese offshore waters and adjacent sea areas. Adv Mar Sci (in Chinese), 24(4):407-415

Chia H H, Ropelewski C F. 2002. The interannual variability in the genesis location of tropical cyclones in the Northwest Pacific. J Climate, 15(20):2934-2944

Chu P C, Qi Yiquan, Chen Yuchun, et al. 2004. South China Sea wind-wave characteristics:Part I. Validation of wavewatch-Ⅲ using TOPEX/Poseidon data.. J Atmos Oceanic Technol, 21(11):1718-1733

Dee D P, Uppala S M, Simmons A J, et al. 2011. The ERA-Interim reanalysis:configuration and performance of the data assimilation system. Quart J Roy Meteor Soc, 137(656):553-597,, doi: 10.1002/qj.828

Ewing J A, Laing A K. 1987. Directional spectra of seas near full development. J Phys Oceanogr, 17(10):1696-1706

Fan Yalin, Lin S J, Held I M, et al. 2012. Global ocean surface wave simulation using a coupled atmosphere-wave model. J Climate, 25(18):6233-6252

Fang Wendong, Fang Guohong, Shi Ping, et al. 2002. Seasonal structures of upper layer circulation in the southern South China Sea from in situ observations. J Geophys Res, 107(C11):23-1,, doi: 10.1029/2002JC001343

Gulev S K, Grigorieva V, Sterl A, et al. 2003. Assessment of the reliability of wave observations from voluntary observing ships:insights from the validation of a global wind wave climatology based on voluntary observing ship data. J Geophys Res, 108(C7):3236, doi: 10.1029/2002JC001437

Guo Suiping, Zhuang Hui, Zheng Chongwei, et al. 2012. The relationship between El Niño and wave field in the South China Sea. Mar Forecast (in Chinese), 29(6):37-43

Ha K J, Heo K Y, Lee S S, et al. 2012. Variability in the East Asian Monsoon:a review. Meteor Appl, 19(2):200-215

Hanley K E, Belcher S E, Sullivan P P. 2010. A global climatology of wind-wave interaction. J Phys Oceanogr, 40(6):1263-1282

Hasselmann S, Hasselmann K, Bauer E, et al. 1988. The WAM model:A third generation ocean wave prediction model. J Phys Oceanogr, 18:1775-1810

Izaguirre C, Méndez F J, Menéndez M, et al. 2011. Global extreme wave height variability based on satellite data. Geophys Res Lett, 38(10):L10607, doi: 10.1029/2011GL047302

Jiang Haoyu, Chen Ge. 2013. A global view on the swell and wind sea climate by the Jason-1 mission:a revisit. J Atmos Oceanic Technol, 30(8):1833-1841

Li Chongyin. 1988. Actions of typhoons over the western Pacific (including the South China Sea) and El Niño. Adv Atmos Sci, 5(1):107-115

Li Xunqiang, Zheng Chongwei, Su Qin, et al. 2012. Wave climate and wind climate analysis in the China Sea from 1988 to 2009. Period Ocean Univ China (in Chinese), 42(S):1-9

Liu K S, Chan J C L. 2003. Climatological characteristics and seasonal forecasting of tropical cyclones making landfall along the South China coast. Mon Wea Rev, 131(8):1650-1662

Liu Qinyu, Kaneko A, Su Jilan. 2008. Recent progress in studies of the South China Sea circulation. J Oceanogr, 64(5):753-762

Pierson Jr W J. 1991. Comment on "effects of sea maturity on satellite altimeter measurements" by Roman E. Glazman and Stuart H. Pilorz. J Geophys Res, 96(C3):4973-4977

Pierson Jr W J, Moskowitz L. 1964. A proposed spectral form for fully developed wind seas based on the similarity theory of S. A. Kitaigorodskii. J Geophys Res, 69(24):5181-5190

Qi Yiquan, Shi Ping. 1999. Analysis on monthly average distribution characteristics of sea surface wind and wave in South China Sea using altimetric data. Trop Oceanol (in Chinese), 18(2):90-96

Qi Yiquan, Shi Ping, Mao Qinwen. 1997. The satellite remote sensing analysis of seasonal average characteristics of wind field and wave field in South China Sea. China Offs Plat (in Chinese), 12(3):118-122

Sasaki W, Iwasaki S I, Matsuura T, et al. 2005. Recent increase in summertime extreme wave heights in the western North Pacific. Geophys Res Lett, 32(15):L15607, doi: 10.1029/2005GL023722

Semedo A, Sušelj K, Rutgersson A, et al. 2011. A global view on the wind sea and swell climate and variability from ERA-40. J Climate, 24(5):1461-1479

Shanas P R, Kumar V S. 2015. Trends in surface wind speed and significant wave height as revealed by ERA-Interim wind wave hindcast in the Central Bay of Bengal. Int J Climatol, 35(9):2654-2663

Sverdrup H U, Munk W H. 1947. Wind, sea and swell. Theory of Relations for Forecasting. Washington DC:U. S. Navy Hydrographic Office Publication 601, 50

Tao S Y, Chen L X. 1987. A review of recent research of the East Asian summer monsoon in China. In:Chang C P, Krishnamurti T N, eds. Monsoon Meteorology. New York:Oxford University Press, 60-92

Tolman H L. 1990. A third-generation model for wind waves on slowly varying, unsteady, and inhomogeneous depths and currents. J Phys Oceanogr, 21(6):782-797

Uppala S M, Kållberg P W, Simmons A J, et al. 2005. The ERA-40 re-analysis. Quart J Roy Meteor Soc, 131(612):2961-3012

Wan Yong, Zhang Jie, Meng Junmin, et al. 2015. A wave energy resource assessment in the China's seas based on multi-satellite merged radar altimeter data. Acta Oceanol Sin, 34(3):115-124

Wang Bin, Chan J C L. 2002. How strong ENSO events affect Tropical Storm activity over the western North Pacific. J Climate, 15(13):1643-1658

Wang Lei, Fung C H, Lau L K. 2007. The upper ocean thermal structure and the genesis locations of tropical cyclones in the South China Sea. J Ocean Univ China, 6(2):125-131

Wu Lingli, Wang X L, Feng Yang. 2014. Historical wave height trends in the South and East China Seas, 1911-2010. J Geophys Res, 119(7):4399-4409

Xie Shangping, Xie Qiang, Wang Dongxiao, et al. 2003. Summer upwelling in the South China Sea and its role in regional climate variations. J Geophys Res, 108(C8):3261, doi: 10.1029/2003JC001867

Yu Mugeng. 1984. Analysing the characteristics of wave distribution in the South China Sea on the basis of ship reports. Mar Sci Bull (in Chinese), 3(4):1-8

Zhai Fangguo, Wang Qingye, Wang Fujun, et al. 2014. Variation of the North Equatorial Current, Mindanao Current, and Kuroshio Current in a high-resolution data assimilation during 2008-2012. Adv Atmos Sci, 31(6):1445-1459,, doi: 10.1007/s00376-014-3241-1

Zhang Jie, Wang Weili, Guan Changlong. 2011. Analysis of the global swell distributions using ECMWF re-analyses wind wave data. J Ocean Univ China, 10(4):325-330

Zheng Chongwei, Li Chongyin. 2015. Variation of the wave energy and significant wave height in the China Sea and adjacent waters. Renew Sust Energy Rev, 43:381-387

Zheng Chongwei, Liu Tiejun, Qian Yuehai. 2014. The relationship between sea surface wind field, wave field and El Niño in the China Sea. J Yunnan Univ (in Chinese), 36(2):214-223

Zheng Chongwei, Zhou Lin. 2012. Wave climate and wave energy analysis of the South China Sea in recent 10 years. Acta Energ Solar Sin (in Chinese), 33(8):1349-1356

Zhou Liangming, Wu Lunyu, Guo Peifang, et al. 2007. Simulation and study of wave in South China Sea using WAVEWATCH-Ⅲ. J Trop Oceanogr (in Chinese), 26(5):1-8

Zhu Geli, Lin Wantao, Zhao Sen, et al. 2015. Spatial and temporal variation characteristics of ocean waves in the South China Sea during the boreal winter. Acta Oceanol Sin, 34(1):23-28

Zong Fangyi, Wu Kejian. 2014. Research on distributions and variations of wave energy in South China Sea based on recent 20 years' wave simulation results using SWAN wave model. Trans Oceanol Limnol (in Chinese),(3):1-12

施引文献

资源附件(0)

访问统计

点击查看大图

计量

文章访问数: 1289
HTML全文浏览量: 111
PDF下载量: 751
被引次数: 0

基于多源融合卫星高度计观测数据的南海海浪有效波高的季节变化研究

doi: 10.1007/s13131-017-1073-4

计量

出版历程

Revisiting the seasonal wave height variability in the South China Sea with merged satellite altimetry observations

计量

出版历程

目录