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DOI10.1175/JCLI-D-19-0413.1
Principal Component Analysis for Extremes and Application to U.S. Precipitation
Jiang Y.; Cooley D.; Wehner M.F.
发表日期2020
ISSN0894-8755
起始页码6441
结束页码6451
卷号33期号:15
英文摘要We propose a method for analyzing extremal behavior through the lens of a most efficient basis of vectors. The method is analogous to principal component analysis, but is based on methods from extreme value analysis. Specifically, rather than decomposing a covariance or correlation matrix, we obtain our basis vectors by performing an eigendecomposition of a matrix that describes pairwise extremal dependence.We apply the method to precipitation observations over the contiguous United States. We find that the time series of large coefficients associated with the leading eigenvector shows very strong evidence of a positive trend, and there is evidence that large coefficients of other eigenvectors have relationships with El Ninõ-Southern Oscillation. © 2020 American Meteorological Society. All rights reserved.
英文关键词Atmospheric pressure; Eigenvalues and eigenfunctions; Basis vector; Correlation matrix; Eigen decomposition; Extremal; Extremal behavior; Extreme value analysis; Southern oscillation; Through the lens; Covariance matrix; decomposition analysis; eigenvalue; El Nino-Southern Oscillation; matrix; precipitation (climatology); principal component analysis; vector; United States
语种英语
来源期刊Journal of Climate
文献类型期刊论文
条目标识符http://gcip.llas.ac.cn/handle/2XKMVOVA/171198
作者单位Colorado State University, Fort Collins, CO, United States; Lawrence Berkeley National Laboratory, Berkeley, CA, United States
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GB/T 7714
Jiang Y.,Cooley D.,Wehner M.F.. Principal Component Analysis for Extremes and Application to U.S. Precipitation[J],2020,33(15).
APA Jiang Y.,Cooley D.,&Wehner M.F..(2020).Principal Component Analysis for Extremes and Application to U.S. Precipitation.Journal of Climate,33(15).
MLA Jiang Y.,et al."Principal Component Analysis for Extremes and Application to U.S. Precipitation".Journal of Climate 33.15(2020).
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