The Shortcomings of Nonlinear Principal Component Analysis in Identifying Circulation Regimes
The Shortcomings of Nonlinear Principal Component Analysis in Identifying Circulation Regimes
复制标题
非线性主成分分析在识别循环状态中的缺点
DOI：
10.1175/jcli3569.1
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发表时间：
2005
影响因子：
4.9
通讯作者：
B. Christiansen
中科院分区：
文献类型：
--
作者：
B. Christiansen
摘要近年来，对大气外变率的区域行为的研究是基于主成分分析的非线性扩展。在非线性主成分中发现了多峰现象，并将其解释为多环流体系存在的证据。在这里，多模态被证明是丰富的非线性主成分分析时，充分各向同性的数据，即使这些数据是固有的单峰。建议非线性主成分分析不应用于检测多模态和状态行为。
Abstract Recent studies of regime behavior in the extratropical variability have been based on a nonlinear extension to principal component analysis. Multimodality has been identified in the nonlinear principal component, and the multimodality has been interpreted as evidence for the existence of multiple circulation regimes. Here, multimodality is shown to be abundant in nonlinear principal component analysis when applied to sufficiently isotropic data even if these data are inherently unimodal. It is recommended that the nonlinear principal component analysis should not be used for detection of multimodality and regime behavior.