Empirical Eigenvectors of Sea-Level Pressure, Surface Temperature and Precipitation Complexes over North America

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  • 1 University of Wisconsin, Madison
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Abstract

The combined representation of fields of three climatic variables with empirical orthogonal functions, herein referred to as eigenvectors, is discussed. The eigenvectors are derived from measurements of monthly mean sea-level pressure, surface temperature and precipitation at 23 points in North America for 25 Januarys.

Selected eigenvectors of the individual climatic variables are presented; however, the major part of the paper is devoted to the presentation of eigenvectors consisting of combinations of three climatic variables. Empirical eigenvectors derived from fields of two or more meteorological variables have been used in statistical prediction models, but none of the studies to date displayed examples of these eigenvectors or discussed the internal consistency of the combined representations. In this paper it is shown that the structure of the covariances between the three climatic variables,as portrayed by the combined representations, is consistent with synoptic experience. This result illustrates that eigenvector representations derived from fields of several variables can be of considerable descriptive or diagnostic value.

Abstract

The combined representation of fields of three climatic variables with empirical orthogonal functions, herein referred to as eigenvectors, is discussed. The eigenvectors are derived from measurements of monthly mean sea-level pressure, surface temperature and precipitation at 23 points in North America for 25 Januarys.

Selected eigenvectors of the individual climatic variables are presented; however, the major part of the paper is devoted to the presentation of eigenvectors consisting of combinations of three climatic variables. Empirical eigenvectors derived from fields of two or more meteorological variables have been used in statistical prediction models, but none of the studies to date displayed examples of these eigenvectors or discussed the internal consistency of the combined representations. In this paper it is shown that the structure of the covariances between the three climatic variables,as portrayed by the combined representations, is consistent with synoptic experience. This result illustrates that eigenvector representations derived from fields of several variables can be of considerable descriptive or diagnostic value.

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