The principal component analysis/empirical orthogonal function analysis (PCA/EOF) has been widely used in data analysis and image compression, its main objective is to reduce a data set containing a large number of variables to a data set containing fewer variables, but that still represents a large fraction of the variability contained in the original data set. In climate studies, EOF analysis is often used to study possible spatial modes (i.e., patterns) of variability and how they change with time . In statistics, EOF analysis is known as principal component analysis (PCA).
