  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.
