Comparison of Some Statistical Methods of Probabilistic Forecasting of ENSO.

Abstract Numerous models have been developed in recent years to provide predictions of the state of the El Nino–Southern Oscillation (ENSO) phenomenon. Predictions of the ENSO phenomenon are usually presented in deterministic form, but because of the inherent uncertainty involved probabilistic forecasts should be provided. In this paper, various statistical methods are used to calculate probabilities for monthly Nino-3.4 anomalies within predefined ranges, or categories. The statistical methods used are predictive discriminant analysis, canonical variate analysis, and various forms of generalized linear models. In addition, probabilistic forecasts are derived from a multiple regression model by using contingency tables and from the model's prediction intervals. By using identical sets of predictors and predictands, the methods are compared in terms of their performance over an independent retroactive forecast period, which includes the 1980s and 1990s. The models outperform persistence and damped persiste...

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