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Empirical Orthogonal Functions
Springer Atmospheric Sciences, 2021This chapter describes the idea behind, and develops the theory of empirical orthogonal functions (EOFs) along with a historical perspective. It also shows different ways to obtain EOFs and provides examples from climate and discusses their physical interpretation. Strength and weaknesses of EOFs are also mentioned.
Abdel Hannachi
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Empirical Orthogonal Functions: The Medium is the Message
Journal of Climate, 2009Abstract Empirical orthogonal function (EOF) analysis is a powerful tool for data compression and dimensionality reduction used broadly in meteorology and oceanography. Often in the literature, EOF modes are interpreted individually, independent of other modes. In fact, it can be shown that no such attribution can generally be made. This
Adam H. Monahan +4 more
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Empirical Orthogonal Functions
2009The 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 ...
Antonio Navarra, Valeria Simoncini
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Empirical Orthogonal Functions
2011This chapter focuses on empirical orthogonal functions (EOFs). One of the most useful and common eigen-techniques in data analysis is the construction of EOFs. EOFs are a transform of the data; the original set of numbers is transformed into a different set with some desirable properties.
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Sampling Errors in the Estimation of Empirical Orthogonal Functions
Monthly Weather Review, 1982Abstract Empirical Orthogonal Functions (EOF's), eigenvectors of the spatial cross-covariance matrix of a meteorological field, are reviewed with special attention given to the necessary weighting factors for gridded data and the sampling errors incurred when too small a sample is available.
Gerald R. North +3 more
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Empirical Orthogonal Function Estimates of Local Predictability
Journal of Applied Meteorology, 1982Abstract Predictability times are estimated from 500 mb heights resolved for horizontal scales from 5 × 106 to 8 × 106 m. These scales are defined through eigenvector analysis of seven years of winter data over a portion of the Northern Hemisphere centered over the western United States.
Julia N. Paegle, Reed B. Haslam
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Quantification of transients using empirical orthogonal functions
Chaos, Solitons & Fractals, 1997Abstract The method of empirical orthogonal functions (EOFs) is used to analyse spatio-temporal data obtained from simulations of heterogeneous catalysis. It is found that EOFs are well suited for the quantitative determination of transients in the data.
Jörg Arndt +4 more
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Analysis of Geomagnetic Variability by Empirical Orthogonal Functions
2020<p>We examine the secular variations of global geomagnetic field on long temporal scales using the IGRF model given in Gauss coefficients for 1900 - 2020. We apply the Empirical Orthogonal Function (EOF) analysis to the geomagnetic field truncated at degree 6 and downward continue it to the core-mantle boundary (CMB) under the ...
Chi-Hua Chung, Benjamin Fong Chao
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Empirical Orthogonal Functions
2006The purpose of this chapter is to discuss Empirical Orthogonal Functions (EOF), both in method and application. When dealing with teleconnections in the previous chapter we came very close to EOF, so it will be a natural extension of that theme. However, EOF opens the way to an alternative point of view about space–time relationships, especially ...
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