Forecasting the SST space-time variability of the Alboran Sea with genetic algorithms

We propose a nonlinear ocean forecasting technique based on a
combination of genetic algorithms and empirical orthogonal
function (EOF) analysis.
The method is used to forecast the space-time
variability of the sea surface temperature (SST) in the Alboran
Sea. The genetic algorithm finds the equations that best describe
the behaviour of the different temporal amplitude functions in the
EOF decomposition and, therefore, enables global forecasting of
the future time-variability.
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Also available at LANL preprint server as paper
chao-dyn/9911012.

The reprint version is available from AGU at

http://www.agu.org/GRL/articles/1999GL011226/GL10555W01.html.