What is SVD?
	q Any m by n matrix A can be factored into q The columns of U (m by m) are the EOFs q The columns of V (n by n) are the PCs. q The diagonal values of S are the eigenvalues represent the amplitudes of the EOFs, but not the variance explained by the EOF. q The square of the eigenvalue from the SVD is equal to the eigenvalue from the eigen analysis of the covariance matrix.