UBC Theses and Dissertations
Wave hindcast sensitivity to wind forcing Hodgins, Sandra Leella Margaret
Efficient planning and safe operation of marine vessels and coastal structures require good understanding of wave properties, usually expressed in statistical terras. In the absence of very long direct measurement records, spectral wave hindcasting is routinely used to derive design and operating criteria. The method involves solution of a time-dependent energy balance equation including spatial propagation, growth due to local wind, non-linear transfers between frequency components and dissipation processes. The most important source of errors in a careful hindcast is the input wind which is normally derived from historical surface pressure data. Since spectral wave models generate a sea-state that is almost in balance with local winds, wind sea is largely independent of the preceding storm history. Swell energy, on the other hand, propagates freely at off-wind angles perpetuating any errors that occurred in its generation. Shallow water near-shore zones are usually modelled with a small-area, nested subgrid that receives boundary data from the surrounding large-area model. Since the wave energy solution within the submodel can be dominated by the boundary conditions, errors in the large-area model must be minimized. The purpose of this study was to investigate the sensitivity of hindcast wave fields to prescribed errors in the evolution of the wind patterns. Using a radially symmetric model of surface pressure, five parameters were used to define storm evolution: storm trajectory, minimum central low pressure, rate of storm intensification, advection rate and storm size. Sensitivity analyses of each parameter were used to obtain the likely maximum attributable variation in the significant wave height field. On this basis, and considering wind sea only, the three most important parameters are (1) trajectory, (2) minimum central pressure and (3) advection rate. With careful wind field re-construction, wave hindcasts of specific events can be performed to acceptable engineering standards for extreme value analysis. However, for the present, climatological (continuous multi-year) wave databases constructed by spectral hindcasting will be too inaccurate to warrant their cost. The most promising advance for wave hindcasting (and forecasting) is the possibility of acquiring high-resolution wind and wave data with satellite sensors to eliminate the need for inherently inaccurate surface pressure data.
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