Analysis and prediction of the El Niño Southern Oscillation phenomenon using Principal Oscillation Pattern analysis

Principal Oscillation Pattern (POP) analysis, which is a technique for deriving the space-time characteristics of a complex system, is used for analyzing and predicting the Southern Oscillation. Pairs of patterns are derived from the POP analysis of the Southern Hemisphere sea level pressure field and from the associated correlation pattern analysis of other atmospheric and oceanic parameters. The two vectors, that are combined from these pairs of patterns, form basis vectors of a two-dimensional space. It is shown that the dynamic process of the Southern Oscillation can be described as a damped oscillation in this reduced space. The oscillatory feature is characterized by the eastward migration of the ascending branch of the Walker Circulation and of the anomalies in the sea level and upper layer temperature. The coefficient time series of the two basis vectors in the reduced space may be understood as a bivariate index of the Southern Oscillation, whlch describes both, the "peak" phase and the "onset" phase of the phenomenon, Generalizing the original concept, the POP framework is used to predict this index and the traditional univariate SO index. In a series of hindcast experiments the POP prediction scheme is tested. It turns out to be skillful for a lead time of about two seasons. In terms of the hindcast correlation the POP forecast scores better than persistence and a conventional ARMA model in forecasting the traditional so index