Spatial Weighting and Iterative Projection Methods for EOFs

Often there is a need to consider spatial weighting in methods for finding spatial patterns in climate data. The focus of this paper is on techniques that maximize variance, such as empirical orthogonal functions (EOFs). A weighting matrix is introduced into a generalized framework for dealing with...

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Veröffentlicht in:	Journal of climate 2009-01, Vol.22 (2), p.234-243
Hauptverfasser:	Baldwin, Mark P., Stephenson, David B., Jolliffe, Ian T.
Format:	Artikel
Sprache:	eng
Schlagworte:	Algorithms Analysis Analysis of covariance Angular momentum Climatic analysis Climatic data Climatology. Bioclimatology. Climate change Cluster analysis Correlation analysis Covariance Covariance matrices Data reduction Datasets Earth, ocean, space Eigenvectors Empirical analysis Empirical orthogonal functions Exact sciences and technology External geophysics Geophysics. Techniques, methods, instrumentation and models Iterative methods Meteorology Methods Multivariate analysis Northern hemisphere Orthogonal functions Pattern analysis Prewhitening Principal components analysis Signal to noise ratio Statistical analysis Statistical methods Statistical variance Studies Term weighting Time series Variables Variance Weighting
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