방법 비교

	최대 공분산 분석	WRF 모델
분야	기상학	기상학
계열	Process / pipeline	Process / pipeline
기원 연도	1992	2000
창시자	Bretherton, Wallace	Skamarock and Klemp
유형	Covariance decomposition method	Atmospheric simulation system
원전	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.
별칭	MCA, Singular value decomposition, SVD analysis, Covariance analysis	Weather Research and Forecasting, WRF, ARW, NMM
관련	2	4
요약	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.