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南海多维海洋资料非线性检测
魏恩泊1, 宋金宝1, 田纪伟2
1.中国科学院海洋研究所;2.中国海洋大学物理海洋实验室
摘要:
利用多维物理参量信息余量函数的非线性检测方法对南海水温、气温及风速(侯采样间隔)之间的非线性结构进行了定性和定量分析。结果表明,南海气温和风速之间具有明显的非线性;水温与风速之间不具有明显的非线性,仅具有琐碎非线性;水温与气温之间在定性方面具有非线性特征;水温、气温及风速组成的三维系统具有琐碎非线性。因而气温和风速之间的非线性结构使南海海气相互作用加强。另外,风速在南海海气非线性相互作用中起着重要作用。
关键词:  代用数据,信息余量,琐碎非线性
DOI:10.11693/hyhz200301014014
分类号:
基金项目:国家自然科学基金资助项目:49476254号;上海市博士后基金资助;中国科学院百人计划资助
DETECTING NONLINEARITY IN MULTIVARIATE TIME SERIES FOR THE SOUTH CHINA SEA
WEI En-Bo1, SONG Jin-Bao1, TIAN Ji-Wei2
1.Institute of Oceanology, The Chinese Academy of Science;2.Physical Oceanography Laboratory, China Ocean University
Abstract:
Pentad records of sea surface temperature (s), sea surface atmospheric temperature (a) and wind speed (w) in the South China Sea are analyzed to delineate the nonlinearity in the multivariate time series using the information redundancy function method. According to the results of the quantitative and qualitative analyses, some remarked nonlinear behaviors exist between a and w.For s and w,there is only trivial nonlinearity. The nonlinearity is detected only qualitatively between s and a. Trivial nonlinearity between the three physical quantities (s,a,w) is identified through information redundancy function analysis of the multivariate time series. The nonlinearity between w and a enhances the nonlinear interaction of the South China Sea; however, the nonlinear interaction of the South China Sea can be reduced because there is no strong nonlinearity between s and w (or a).Thus, w is a very important physical factor in the nonlinear interaction of the South China Sea.
Key words:  Surrogate data, Information redundancy, Trivial nonlinearity
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