Comparer des méthodes

	Analyse de Covariance Maximale	Modèle WRF
Domaine	Météorologie	Météorologie
Famille	Process / pipeline	Process / pipeline
Année d'origine	1992	2000
Auteur d'origine	Bretherton, Wallace	Skamarock and Klemp
Type	Covariance decomposition method	Atmospheric simulation system
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.	Skamarock, W. C., Klemp, J. B., Dudhia, J., et al. (2008). A Description of the Advanced Research WRF Version 3. NCAR Technical Note NCAR/TN-475+STR.
Alias	MCA, Singular value decomposition, SVD analysis, Covariance analysis	Weather Research and Forecasting, WRF, ARW, NMM
Apparentées	2	4
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.	The Weather Research and Forecasting (WRF) model is a mesoscale atmospheric simulation system used for weather forecasting, research, and climate applications. Developed cooperatively by NCAR, NOAA, and academic institutions, WRF became operational in 2004 and has become one of the most widely used atmospheric models worldwide.