Ar. Deelvira et Mjo. Bevia, APPLICATION OF STATISTICAL TECHNIQUES TO THE ANALYSIS AND PREDICTION OF ENSO - BAYESIAN OSCILLATION PATTERNS AS A PREDICTION SCHEME, Dynamics of atmospheres and oceans, 22(1-2), 1995, pp. 91-114
Here we study the low-frequency variability of the tropical Indian and
Pacific basins with a new statistical technique, Bayesian oscillation
patterns (BOP). To describe the climatic system in this region, zonal
wind and sea surface temperature (SST) are the selected variables. Th
eir variability can be explained in terms of a reduced number of frequ
encies and spatial. patterns, These are identified for each field by a
statistical procedure. With the help of the patterns and the frequenc
ies a predictive scheme is devised and applied in two forecast experim
ents. In the first, zonal wind anomalies are predicted using patterns
and frequencies identified in the wind field. A more sophisticated sch
eme, a linear model which includes non-harmonic oscillations and inter
actions between patterns, is used when forecasting SST seasonal anomal
ies in the Ni ($) over tilde no3 region. In this case, the predictors
include the values of the frequencies identified in the BOP analysis o
f both wind and SST fields, and the corresponding patterns.