Comparer des méthodes

	Analyse de Covariance Maximale	Télédéconnexion empirique orthogonale
Domaine	Météorologie	Météorologie
Famille	Process / pipeline	Process / pipeline
Année d'origine	1992	1956
Auteur d'origine	Bretherton, Wallace	Lorenz, Wallace
Type	Covariance decomposition method	Data analysis and pattern identification
Source fondatrice	Bretherton, C. S., Widmann, M., Dymnikov, V. P., Wallace, J. M., & Blade, I. (1992). The effective number of spatial degrees of freedom of a time-varying field. Journal of the Atmospheric Sciences, 49(11), 1063-1083.	Wallace, J. M., & Gutzler, D. S. (1981). Teleconnections in the geopotential height field during the Northern Hemisphere winter. Monthly Weather Review, 109(4), 784-812.
Alias	MCA, Singular value decomposition, SVD analysis, Covariance analysis	EOF analysis, Empirical orthogonal function, Teleconnection patterns, PCA meteorology
Apparentées	2	2
Résumé	Maximum covariance analysis (MCA) is a statistical technique that identifies coupled patterns of variability between two spatially distributed fields (e.g., sea surface temperature and precipitation). Unlike EOF analysis which focuses on variance in a single field, MCA identifies spatial patterns that are maximally correlated between two different fields.	Empirical orthogonal function (EOF) analysis is a statistical technique that identifies dominant spatial patterns and temporal variability in atmospheric or oceanic data. When applied to geographically distant locations, EOF analysis reveals teleconnection patterns—coherent patterns of variability that link weather systems across ocean basins and continents.