Salīdzināt metodes

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