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1 JANUARY 2002 111A I R E S E T A L . 2002 American Meteorological Society
 

Summary: 1 JANUARY 2002 111A I R E S E T A L .
2002 American Meteorological Society
Rotation of EOFs by the Independent Component Analysis: Toward a Solution of the
Mixing Problem in the Decomposition of Geophysical Time Series
FILIPE AIRES
NASA Goddard Institute for Space Studies, Department of Applied Physics, Columbia University, New York, New York
WILLIAM B. ROSSOW
NASA Goddard Institute for Space Studies, New York, New York
ALAIN CHE´ DIN
CNRS Laboratoire de Me´te´orologie Dynamique, Palaiseau, France
(Manuscript received 11 January 2001, in final form 14 May 2001)
ABSTRACT
The Independent Component Analysis (ICA) is a recently developed technique for component extraction. This
new method requires the statistical independence of the extracted components--a stronger constraint that uses
higher-order statistics--instead of the classical decorrelation (in the sense of ``no correlation''), which is a weaker
constraint that uses only second-order statistics. This technique has been used recently for the analysis of
geophysical time series with the goal of investigating the causes of variability in observed data (i.e., exploratory
approach). The authors demonstrate with a data simulation experiment that, if initialized with a Principal Com-
ponent Analysis (PCA), the ICA performs a rotation of the classical PCA (or EOF) solution. This experiment
is conducted using a synthetic dataset, where the correct answer is known, to more clearly illustrate and understand

  

Source: Aires, Filipe - Laboratoire de Météorologie Dynamique du CNRS, Université Pierre-et-Marie-Curie, Paris 6
Fridlind, Ann - Earth Science Division, NASA Ames Research Center

 

Collections: Environmental Sciences and Ecology; Geosciences