Abstract
It is known that wave period can be estimated from altimeter measurements of wave height, wind speed, radar backscatter cross section, etc., using empirical relationship. Of late, the data adaptive approach of neural networks has been used to derive wave period from altimeter data, and it has been shown that the technique appears to be superior compared to the empirical approaches. Another powerful data adaptive approach of genetic algorithm has been advocated more recently in oceanographic studies. Although primarily used for forecasting time series, the algorithm can be tuned to find a relationship between input and output variables. In the present work, this algorithm has been used to find estimates of wave period from altimeter-observed parameters, and the performance of the algorithm has been found to be quite satisfactory. It has been also found that the introduction of wave age leads to significant enhancement of the accuracy of the estimate.
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