Abstract
Many analyses of climate data sets suffer from high dimensions of the variables representing the state of the system at any given time. Often it is advisable to split the full phase space into two subspaces. The “signal” space is spanned by few characteristic patterns and is supposed to represent the dynamics of the considered process. The “noise subspace”, on the other hand, is high-dimensional and contains all processes which are purportedly irrelevant in their details for the “signal subspace”.
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© 1995 Springer-Verlag Berlin Heidelberg
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von Storch, H. (1995). Spatial Patterns: EOFs and CCA. In: von Storch, H., Navarra, A. (eds) Analysis of Climate Variability. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-03167-4_13
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DOI: https://doi.org/10.1007/978-3-662-03167-4_13
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-662-03169-8
Online ISBN: 978-3-662-03167-4
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