丁裕国,江志红. 1996. SVD方法在气象场诊断分析中的普适性[J]. 气象学报, 54(3):365-372, doi:10.11676/qxxb1996.037
SVD方法在气象场诊断分析中的普适性
GENERALITY OF SINGULAR VALUE DECOMPOSITION IN DIAGNOSTIC ANALYSIS OF METEOROLOGICAL FIELD
投稿时间:1994-03-21  修订日期:1994-11-01
DOI:10.11676/qxxb1996.037
中文关键词:  奇异值分解  典型相关分析  气象场分解  诊断分析
英文关键词:Singular value decomposition  Canonical correlation analysis. Analyses of meteorological feilds. Diagnostic analysis
基金项目:国家自然科学基金;中国气象局重点项目基金
作者单位
丁裕国 南京气象学院, 南京, 210044 
江志红 南京气象学院, 南京, 210044 
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中文摘要:
      本文首次从理论上推导证明两个气象场的奇异值分解(SVD)在气象场时空分布耦合信号的诊断分析中具有普适性。结果表明,两个场的SVD求解准则不同于典型相关分析(CCA),且CCA模型可视为SVD之特例,尤其当各个场经PCA滤波后,其CCA完全与SVD等价。SVD分析的结果不但可完全代替CCA,且计算更简便,所得耦合信号的物理解释更清晰,特别适合于大尺度气象场的遥相关型研究。
英文摘要:
      Theoretically,it is proved that SVD is a method in broad sense which is applied to the diagnostic analyses of spatialtemporal distributions as well as coupled signal for the individual meteorological field or between the two meteorological fields. The researches show that the derivation criterion of SVD is different from CCA model. and the CCA can be regarded as a special case of the SVD. and particularly the CCA of the two fields which be filtered by using PCA can be regarded as a equivalent method to SVD. as a rule. CCA can not only perfectly be replaced by SVD. but the advantage of SVD over the CCA is the effective interpretation of physical sense for the coupled signal and simple computation.Thus. SVD is a suitable method for the research of teleconnection patterns in the large spatial scale.
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