Сравнение методов

	Эмпирический ортогональный телесвязный анализ	Анализ максимальной ковариации
Область	Метеорология	Метеорология
Семейство	Process / pipeline	Process / pipeline
Год появления	1956	1992
Автор метода	Lorenz, Wallace	Bretherton, Wallace
Тип	Data analysis and pattern identification	Covariance decomposition method
Основополагающий источник	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.
Другие названия	EOF analysis, Empirical orthogonal function, Teleconnection patterns, PCA meteorology	MCA, Singular value decomposition, SVD analysis, Covariance analysis
Связанные	2	2
Сводка	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.