Modelling the predictability of the El Nino/southern oscillation
( J Filar with B Chiera and D Zachary)
Recent catastrophic climatic events and their impacts have led to
increased research into the El Nino/Southern Oscillation (ENSO) event
and its predictability.
This quasi-periodic phenomenon manifests itself in the fluctuations of the ocean and atmosphere, causing widespread damage in the form of drought, flood, increased cyclonic activity and rising/declining sea levels.
The aim of this research is to model the predictability of the occurrence of an ENSO event using a probabilistic approach. In particular, the methods of Markov Chains, Martingale and Bayesian modelling are adopted. Validation of these models is performed using the Southern Oscillation Index (SOI) data set.