Innovative Wave Transformation Algorithm for Improved Short-term Wave Forecasting

Sean Garber1, Matthew Zed2, Jan Flynn2, David Taylor1, Jarrod Dent1

1Baird Australia, Sydney Australia.

2Woodside Energy Limited, Perth Australia.

This paper presents recent developments and validation of a wave transformation algorithm capable of accurately and efficiently computing shelf scale spectral wave propagation of swell conditions. The computational efficiency of the wave transformation approach makes it applicable for both the development of high-resolution long term hindcasts over large spatial scales and use in operational nearshore wave forecasting.

When coupled with real-time measurements of waves, a transformation algorithm is able to achieve improved accuracy and resolution of short-range wave forecasts compared with global and regional numerical wave forecasts.

An implementation of the wave transformation algorithm that derived relationships between wave energy at a nearshore location and spectral wave buoy measurements located over 300km away will be presented.  The implementation includes the following unique features compared to other wave transfer applications:

  • Use of a spectral transfer method based on the propagation of hypothetical narrow-banded spectral distributions, centred on each frequency-direction bin of the spectral space.
  • Consideration of the influence of hydrodynamics, in terms of both water level and tidal currents, on wave energy transformation.
  • The inclusion of frequency dependent propagation time in the transformation algorithm.

With directional wave spectra as input, the algorithm then computes the nearshore directional wave spectra and associated parameters. Comparisons between measured and forecast/hindcast wave conditions derived from spectral transfer and third-generation spectral wave models are presented to demonstrate the value of the transformation algorithm, particularly for short term swell forecasts.

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