相空间反演方法在表层水温预报中的应用  

APPLICATION OF INVERSE METHOD IN PHASE SPACE TO FORECAST SST

作　　者：魏恩泊[1] 田纪伟[1] 李凤歧 苏育嵩[1] 

机构地区：[1]青岛海洋大学海洋系,青岛266003

出　　处：《海洋与湖沼》1997年第3期315-319,共5页Oceanologia Et Limnologia Sinica

基　　金：国家自然科学基金!49476254;国家"八五"攻关项目!85-903-08-01

摘　　要：利用相空间理论及方法对渤、黄、东海共4个站位近十几年的旬平均SST进行分析。结果表明：表层水温具有混饨特性，其吸引子关联维数平均约为1．23、嵌入相空间维数为6（渤、黄海）和7（东海178号站位）、二阶Renyi熵平均约为3．7×10-4（1／d）及平均可预报时间尺度平均为27个点；基于以上分析结果运用相空间反演方法建立了旬平均SST的反演模型，并且在试预报的前5旬的最大相对误差约为4．2％。Phasc space theory and the inverse method were used to study the decadal averagr SST of the Bohai Sea, Yellow Sea and East China Sea. The results showed that theSST can be described as a chaotic phenomenon with phase space averege correlation dimension, embedding dimension,, two order Renvi entropy, and average predictable timeot of l.23, 6 (Bohai Sea, Yellow Sea ) or7 (East China Sea ), 3.7× l0-4 (l/ d) and 27points, respectivelyUse of the phase space and the above results yielded the inverse equation fo SST below.where, X={X (t), X (t+T), '', X (t+(m- l)}T; T=9t'{x(t0+it), i= l, 2, 3,' ', n- l} is a SST the time , t is the time interval. Used the equation(l), the biggest prediction error of SST is about 4.2% within the firs ptedictable fivepoints' Main conclusions:(l) The analyzed stations SST can be described by no morethan six or seven and no less than two elements though we don't know clearly which corresponding elements affect SST (2) Because of local chaotic traits and the wholepredictable time scale controlled by Lyapunov exponent and two order Renyti entrpy, thepractical time scale is smaller than the Whole predictable one'

关 键 词：海水 水温预报 表层水温 相空间反演 

分 类 号：P731.31[天文地球—海洋科学]