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Jolliffe, I.T.; Uddin, M. and Vines, S.K.
(2002).
DOI: https://doi.org/10.3354/cr020271
URL: http://www.ottokinne.de/abstracts/cr/v20/n3/p271-2...
Abstract
ABSTRACT: Principal component analysis (PCA) is widely used in atmospheric science, and the
resulting empirical orthogonal functions (EOFs) are often rotated to aid interpretation. In this paper 3
methods are described which provide alternatives to the standard 2-stage procedure of PCA followed
by rotation. The techniques are illustrated on a small example involving sea-surface temperatures in
the Mediterranean. Each method is shown to give different simplified interpretations for the major
sources of variation in the data set. All 3 techniques have advantages over standard rotation.