Salīdzināt metodes

	Maksimālās kovariācijas analīze	Empīriskā ortogonālā telekomunikācija
Nozare	Meteoroloģija	Meteoroloģija
Saime	Process / pipeline	Process / pipeline
Izcelsmes gads	1992	1956
Autors	Bretherton, Wallace	Lorenz, Wallace
Tips	Covariance decomposition method	Data analysis and pattern identification
Pirmavots	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.
Citi nosaukumi	MCA, Singular value decomposition, SVD analysis, Covariance analysis	EOF analysis, Empirical orthogonal function, Teleconnection patterns, PCA meteorology
Saistītās	2	2
Kopsavilkums	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.