Predicting the future?
Comparative Forecasting and a Test for Persistence in the El Nino Southern Oscillation and new ideas

Daniel S. Zachary
John Hopkins University
noon 27 May Conference Center

We present a statistical analysis on El Nino. Analysis is done for two single-indicator forecasting methods for the El Nino Southern Oscillation based on oscillation persistence. We use the Southern Oscillation Index (SOI) to produce short term 5 month forecasts and a Bayesian approach to explore SOI persistence, with results compared to a benchmarking Taylor Series expansion. We find signal persistence is important when forecasting more than a few months and the models presented may provide a relatively simple approach to environmental risk forecasting in situations where the underlying phenomenon exhibits substantial persistence. We update the analysis with new results for 2014. We supplement the discussion with some new ideas and initial results that are expected to improve the analysis and strengthen the statistical forecasting method.