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The HiDyn Model developed in "Long-Lead Prediction of Pacific SSTs
via Bayesian Dynamic Modeling" by L.M. Berliner, C.K. Wikle, and N.
Cressie (2000), Journal of Climate, 13, 3953-3968, uses
current values of SST anomalies, the Southern Oscillation Index (SOI),
and a summary of westerly surface-wind bursts as predictor variables.
Rather than viewing the prediction as restricted to a single model,
several statistical prediction models are developed. These models
condition on the current regime (Warm, Normal, or Cool), classified
according to the current value of SOI, and then provide probabilistic
forecasts of the future regimes (Warm, Normal, or Cool)
seven months later. The probabilities
of the future regimes are estimated based on the current SOI and
wind-burst statistics. This model was trained on monthly data begining
in 1970.
The HiDyn-Model output is the predictive distribution for SST anomalies in the Tropical
Pacific Region, with a seven-month lead. Key summaries of this distribution
include (i) probabilities of each of the three temperature-regime
states; and (ii) SST mean-field estimates for each temperature regime.
This page shows (i) and (ii). When a probability-weighted average of
the Warm, Normal, and Cool mean-field estimates in (ii) is taken (with
probabilities given by (i)), we obtain (iii) a combined mean-field
estimate that yields the SST-field forecasts seen on most of the other
ENSO webpages.
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