Estimation of return values for significant wave height from satellite data

Estimation of extreme wave height across the oceans is important for marine safety and design, but is hampered by lack of data. Buoy and platform data are geographically limited, and though satellite observations offer global coverage, they suffer from temporal sparsity and intermittency, making application of standard methods of extreme value estimation problematical. A possible strategy in the face of such difficulty is to use extra model assumptions to compensate for lack of data. In this spirit we report initial exploration of an approach to estimation of extreme wave heights using crossings methods based on a log-Gaussian model. The suggested procedure can utilize either intermittent satellite data or regular time series data such as obtained from a buoy, and it is adapted to seasonal variation in the wave height climate. The paper outlines derivation of the method and illustrates its application to data from the Atlantic and Pacific oceans. A numerical comparison is made with the results of an annual maximum analysis for sites at which both satellite and buoy data are available. The paper concludes with a discussion of the applicability of the new approach, its relationship to other extreme value methods and desirable directions for further development