南海海面风、浪场时空变化特征及其关系分析

海洋学研究 ›› 2013, Vol. 31 ›› Issue (4): 1-9.

• 研究论文 • 下一篇

南海海面风、浪场时空变化特征及其关系分析

裘沙怡^1,2, 梁楚进^*1,2, 董昌明³, 刘正礼⁴

1.卫星海洋环境动力学国家重点实验室,浙江杭州 310012;
2.国家海洋局第二海洋研究所,浙江杭州 310012;
3.地球与行星物理研究所,美国加州大学洛杉机分校,美国加利福尼亚州洛杉机 90095;
4.中海石油(中国)有限公司深圳分公司钻井部,广东深圳 518067

收稿日期:2013-06-25 修回日期:2013-10-15 出版日期:2013-12-15 发布日期:2022-11-29
通讯作者: *梁楚进,研究员,E-mail:cjliang@sio.org.cn
作者简介:裘沙怡(1988-),女,浙江杭州市人,硕士研究生,主要从事物理海洋方面的研究。E-mail:qiushayi@163.com
基金资助:
国家重点基础研究发展计划项目资助(2012CB417303);全球变化与海气相互作用专项

Analysis of the temporal and spatial variations in the wind and wave over the South China Sea

QIU Sha-yi^1,2, LIANG Chu-jin^*1,2, DONG Chang-ming³, LIU Zheng-li⁴

1. State Key Laboratory of Satellite Ocean Environment Dynamics, Hangzhou 310012, China;
2. The Second Institute of Oceanography, SOA, Hangzhou 310012, China;
3. Institute of Geophysics and Planetary Physics, University of California, Los Angeles CA 90095, USA;
4. Drilling Department, Shenzhen Branch of CNOOC Ltd., Shenzhen 518067, China

Received:2013-06-25 Revised:2013-10-15 Online:2013-12-15 Published:2022-11-29

摘要/Abstract

摘要： 利用长时间序列的卫星观测数据,对南海海域的风、浪场时空分布及其相互关系进行了分析。结果显示,海面风距平场VEOF分解后得到的第一模态具有明显的季节变化,即季风特征,说明季风是影响整个南海风速的主要因素;第二模态具有较强的区域变化特征,是季风转换时期的距平场特征;第三模态反映的是海面风距平场受陆地地形影响所表现的分布特征。有效波高距平场EOF分解后得到的第一模态、第二模态与风距平场的前2个模态的空间分布较为相似,并且,风、浪距平场第一模态间的相关系数达0.76,均说明南海作为边缘海其波浪场与风场变化有很好的相关性。有效波高第三模态的分布与风场的第三模态相关性较弱,反映的是受海底地形影响所表现的分布特征。

关键词: 南海, 风场, 有效波高, 卫星遥感

Abstract: Based on satellite remote sensing products, the seasonal and interannual variations in the wind and wave over the South China Sea (SCS) were presented in the study. A vector empirical orthogonal function (VEOF) method was employed to study the temporal and spatial patterns of the wind field. Results indicate that the first VEOF is a seasonal oscillation mode, which represents the monsoon feature in the SCS. The second VEOF is an approximate annual oscillation mode, it represents the wind field features during the monsoon transition period. The third VEOF shows that the wind field is the land-sea interaction mode. For SWH, an empirical orthogonal function (EOF) method was employed and the similar two modes are forced by the first two modes of wind data, the third mode is caused by the bottom topography variation. The correlation coefficient (CC) between wind field's first mode and SWH's first mode is 0.76, which shows that the wave variation is forced by the sea surface wind. The two third modes are nearly unconnected, there may be a link between the bottom topography and SWH's third mode.

Key words: South China Sea, wind field, significant wave height, satellite remote sensing

中图分类号:

P731
P732

裘沙怡, 梁楚进, 董昌明, 刘正礼. 南海海面风、浪场时空变化特征及其关系分析[J]. 海洋学研究, 2013, 31(4): 1-9.

QIU Sha-yi, LIANG Chu-jin, DONG Chang-ming, LIU Zheng-li. Analysis of the temporal and spatial variations in the wind and wave over the South China Sea[J]. Journal of Marine Sciences, 2013, 31(4): 1-9.

参考文献

[1] WITTER D L,CHELTON D B. A geosat altimeter wind speed algorithm development[J]. J Geophys Res,1991,96(C5):8 853-8 860.
[2] QI Yi-quan,SHI Ping,MAO Qing-wen. Relationship and characteristic of the sea surface wind and wave fields over the South China Sea derived from T/P altimeter[J]. Journal of Hydrodynamics, 2003,18(5):619-624.
齐义泉,施平,毛庆文.基于T/P资料分析南海海面风、浪场特征及其关系[J].水动力学研究与进展,2003,18(5):619-624.
[3] ZHAO Xi-xi,HOU Yi-jun,QI Peng. Study on temporal and spatial characteristics of sea surface wind in China seas[J].Chinese High Technology Letters,2007,17(5):523-528.
赵喜喜,侯一筠,齐鹏.中国海海面风场时空变化特征分析[J].高技术通讯,2007,17(5):523-528.
[4] SHEN Chun,JIANG Guo-rong,SHI Wei-lai,et al. Characteristic analysis of the variability of QuikSCAT wind in the South China Sea[J]. Marine Forecasts,2012,29(3):1-8.
沈春,蒋国荣,施伟来,等.南海QuikSCAT海面风场变化特征分析[J].海洋预报,2012,29(3):1-8.
[5] LÜ Ke-wei,HU Jian-yu,YANG Xiao-yi. Spatical patterns in seasonal variability of sea surface wind over the South China Sea and its adjacent ocean[J]. Journal of Tropical Oceanography,2012,31(6):41-47.
吕柯伟,胡建宇,杨小怡.南海及邻近海域海面风场季节性变化的空间差异[J].热带海洋学报,2012,31(6):41-47.
[6] QI Yi-quan, CHU P C,SHI Ping, et al. Analysis of significant wave height from WWATCH and TOPEX/Poseidon Altimetry[J].Acta Oceanologica Sinica,2003,25(4):1-9.
齐义泉,朱伯承,施平,等.WWATCH模式模拟南海海浪场的结果分析[J].海洋学报,2003,25(4):1-9.
[7] CHU P C,CHENG K F. South China Sea wave characteristics during typhoon Muifa passage in winter 2004[J]. Journal of Oceanography,2008,64(1):1-21.
[8] ZHOU Liang-ming,WU Lun-yu,GUO Pei-fang,et al. Simulation and study of wave in South China Sea using WAVEWATCH-III[J]. Journal of Tropical Oceanography,2007,26(5):1-8.
周良明,吴伦宇,郭佩芳,等.应用WAVEWATCH-III模式对南海的波浪场进行数值计算、统计分析和研究[J].热带海洋学报,2007,26(5):1-8.
[9] ZHOU Zhao-li,YANG Xian-yu. Numerical simulation of wave field in South China Sea using WWATCH-III[J]. Journal of Tropical Oceanography,2008,27(2):1-6.
周兆黎,杨显宇.WWATHC-III模式模拟南海冷空气过程海浪场的有效性检验[J].热带海洋学报,2008,27(2):1-6.
[10] ZHENG Chong-wei,LIN Gang,SUN Yan,et al. Simulation of wave energy resources in the South China Sea during the past 22 years[J]. Journal of Tropical Oceanography,2012,31(6):13-19.
郑崇伟,林刚,孙岩,等.近22年南海波浪能资源模拟研究[J].热带海洋学报,2012,31(6):13-19.
[11] MEI Yong,SONG Shui,ZHOU Lin. Annual variation characteristics of wave fields and wind fields over the North Indian Ocean and South China Sea[J].Marine Forecasts,2010,27(5):27-33.
梅勇,宋帅,周林.北印度洋-南海海域海浪场、风场的年际变化特征分析[J].海洋预报,2010,27(5):27-33.
[12] ZHOU Lin,MEI Yong,WANG Hui-juan,et al. Interdecadal variations of sea surface wind and significant wave height in the North Indian Ocean and South China Sea[J]. Transactions of Atmospheric Sciences,2011,34(5):547-554.
周林,梅勇,王慧娟,等.北印度洋-南海海面风速和有效波高的年代际变化[J].大气科学学报,2011,34(5):547-554.
[13] ZHENG Chong-wei,CHEN Zhi-lu,JIA Ben-kai, et al. Characteristics of sea surface wind field and wave field analysis in the China Sea[J]. China Science and Technology Information,2011(10):32-33.
郑崇伟,陈志禄,贾本凯,等.中国海海表风场、风浪、涌浪、混合浪场时空分布特征研究[J].中国科技信息,2011(10):32-33.
[14] LIU Liang-ming,LIU Ting,LIU Jian-qiang,et al. An introduction to satellite oceanic remote sensing[M]. Wuhan:Wuhan University Press,2005:126-130.
刘良明,刘廷,刘建强,等.卫星海洋遥感导论[M]. 武汉:武汉大学出版社,2005:126-130.
[15] CHEN Shang-ji,MA Ji-rui. Analysis methods and application of ocean data[M]. Beijing:Ocean Press,1991:312-320.
陈上及,马继瑞.海洋数据处理分析方法及其应用[M]. 北京:海洋出版社,1991:312-320.
[16] HARDY D M, WALTON J J. Principal components analysis of vector wind measurement[J]. Journal of Applied Meteorology,1978,17(8):1 153-1 162.
[17] QI Yi-quan,SHI Ping,MAO Qing-wen. The satellite remote sensing analysis of seasonal average characteristics of wind field and wave field in South China Sea[J]. China Offshore Platform,1997(3):118-123.
齐义泉,施平,毛庆文.南海海面风场和波浪场季节平均特征的卫星遥感分析[J].中国海洋平台,1997(3):118-123.

南海海面风、浪场时空变化特征及其关系分析

Analysis of the temporal and spatial variations in the wind and wave over the South China Sea

PDF

可视化

摘要/Abstract

引用本文

使用本文

参考文献

相关文章 15

编辑推荐

Metrics

[1]	周益飞, 廖光洪. 基于GHSOM网络的南海风场时空变化特征分析[J]. 海洋学研究, 2022, 40(2): 19-31.
[2]	王维扬, 唐勇, 任建业, 李赫, 赵阳慧, 方银霞, . 南海西南次海盆被动陆缘构造单元划分及伸展演化过程[J]. 海洋学研究, 2021, 39(3): 31-43.
[3]	陈莹, 赵辉, . 南海中西部叶绿素时空变化特征分析[J]. 海洋学研究, 2021, 39(3): 84-94.
[4]	熊一璇, 麻书畅, 张霄宇, 黄国容, 陈嘉星, 韩亚超. 基于多源遥感数据的大襟岛海域叶绿素a反演及富营养化评价[J]. 海洋学研究, 2021, 39(2): 43-51.
[5]	蒋锦刚, 冯慧云, 张亚国, 何贤强. 空间变异对海洋叶绿素a质量浓度遥感产品精度验证的影响[J]. 海洋学研究, 2021, 39(1): 9-19.
[6]	王勤, 李尚鲁, 卢美, 郭敬, 丁骏. 海浪灾害对贻贝脱落率的影响[J]. 海洋学研究, 2021, 39(1): 86-92.
[7]	陆怡, 初凤友, 董彦辉, 朱志敏, 朱继浩, 鲁江姑. 南海东北部陆坡结核成因及对冷泉活动的指示[J]. 海洋学研究, 2020, 38(2): 16-25.
[8]	粟丽, 陈作志, 黄梓荣, 许友伟. 2015年春季南海北部陆架海域网采浮游植物群落结构及其与环境因子关系[J]. 海洋学研究, 2019, 37(3): 86-96.
[9]	刘丛舒, 丁巍伟, 殷绍如, 方鹏高, 丁航航. 南海北部陆坡区海底峡谷地貌、沉积特征及控制因素[J]. 海洋学研究, 2019, 37(2): 28-43.
[10]	李海龙, 吴招才, 许明炬. 南海东北部陆缘地壳结构特征及下地壳高速层成因[J]. 海洋学研究, 2019, 37(2): 44-56.
[11]	张小龙, 付东洋, 刘大召, 刘贝, 余果, 钟雅枫, 王焕. 基于EOF分析中西太平洋金枪鱼围网渔场的海洋环境[J]. 海洋学研究, 2019, 37(2): 81-94.
[12]	刘源, 邱振戈, 栾奎峰, 侍炯, 朱卫东, 刘鲁燕, 沈蔚, 曹彬才. 基于地理加权回归模型的水深反演算法研究[J]. 海洋学研究, 2018, 36(4): 35-42.
[13]	薛淑君. 南海土台风强度变化特征分析[J]. 海洋学研究, 2018, 36(3): 1-16.
[14]	张东凌, 卢姁, 张铭. 春季Wyrtki急流异常及其与亚洲热带夏季风的关系[J]. 海洋学研究, 2018, 36(1): 16-26.
[15]	陈橙, 李焱. 基于SWAN模型的南中国海“莫拉菲”台风浪研究[J]. 海洋学研究, 2017, 35(4): 14-19.