A Bayesian model for predicting local El Niño events using tree ring widths and cellulose δ¹⁸O

Abstract

18 O values, we created a model to estimate the probability that a given annual tree ring was formed during an El Niño or non-El Niño year. The methods used in this analysis differ from standard dendrochronological technique because we explicitly account for the varying relationship between climate and tree ring characteristic during an El Niño or non-El Niño year. Moreover, our approach accommodates uncertainty in model parameters and predictions better than traditional classification methods. The application of this model to prehistory tree samples or samples of unknown age may allow for El Niño detection and subsequent determination of changes in El Niño frequency.