Comparar métodos

	Análise de Covariância Máxima	Teleconexão Ortogonal Empírica
Área	Meteorologia	Meteorologia
Família	Process / pipeline	Process / pipeline
Ano de origem	1992	1956
Autor original	Bretherton, Wallace	Lorenz, Wallace
Tipo	Covariance decomposition method	Data analysis and pattern identification
Fonte seminal	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.
Outros nomes	MCA, Singular value decomposition, SVD analysis, Covariance analysis	EOF analysis, Empirical orthogonal function, Teleconnection patterns, PCA meteorology
Relacionados	2	2
Resumo	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.