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A Guide to Empirical Orthogonal Functions for Climate Data AnalysisEmpirical Orthogonal Functions

A Guide to Empirical Orthogonal Functions for Climate Data Analysis: Empirical Orthogonal Functions [The atmospheric fields are three-dimensional fields by nature, the variation in longitude, latitude and altitude of winds, temperatures and the other quantities are normal. A major jump forward in the development of climate science was reached when it was realized that the analysis of simultaneous values of the variables contained significant information. Indeed, to advance scientific understanding it is essential to have a view of the relation that links together various climate variables, for instance the temperature and the pressure in various places.] http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png

A Guide to Empirical Orthogonal Functions for Climate Data AnalysisEmpirical Orthogonal Functions

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References (1)

Publisher
Springer Netherlands
Copyright
© Springer Science+Business Media B.V. 2010
ISBN
978-90-481-3701-5
Pages
39 –67
DOI
10.1007/978-90-481-3702-2_4
Publisher site
See Chapter on Publisher Site

Abstract

[The atmospheric fields are three-dimensional fields by nature, the variation in longitude, latitude and altitude of winds, temperatures and the other quantities are normal. A major jump forward in the development of climate science was reached when it was realized that the analysis of simultaneous values of the variables contained significant information. Indeed, to advance scientific understanding it is essential to have a view of the relation that links together various climate variables, for instance the temperature and the pressure in various places.]

Published: Nov 27, 2009

Keywords: Covariance Matrix; Observation Point; Empirical Orthogonal Function; Singular Vector; Bottom Left Panel

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