Rapid deterministic wave prediction using a sparse array of buoys. (15th May 2021)

• Record Type: Journal Article
• Authors: Fisher, Alexander; Thomson, Jim; Schwendeman, Michael
• Is Part Of: Ocean engineering. Volume 228(2021)
• Publication Date: 2021-05-15
• Subjects: Irregular ocean waves -- Sea surface reconstruction -- Phase-resolved modeling -- Data-driven prediction; Ocean engineering -- Periodicals; Ocean engineering; Periodicals; 620.4162
• DOI: 10.1016/j.oceaneng.2021.108871
• Languages: English
• ISSNs: 0029-8018

Abstract

Abstract: A long-standing problem in maritime operations and ocean development projects has been the prediction of instantaneous wave energy. Wave measurements collected using an array of freely drifting arrays of Surface Wave Instrument Float with Tracking (SWIFT) buoys are used to test methods for phase-resolved wave prediction in a wide range of observed sea states. Using a linear inverse model in directionally-rich, broadbanded wave fields can improve instantaneous heave predictions by an average of 63% relative to statistical forecasts based on wave spectra. Numerical simulations of a Gaussian sea, seeded with synthetic buoys, were used to supplement observations and characterize the spatiotemporal extent of reconstruction accuracy. Observations and numerical results agree well with theoretical deterministic prediction zones proposed in previous studies and suggest that the phase-resolved forecast horizon is between 1–3 average wave periods for a maximum measurement interval of 10 wave periods for ocean wave fields observed during the experiment. Prediction accuracy is dependent on the geometry and duration of the measurements and is discussed in the context of the nonlinearity and bandwidth of incident wave fields. Highlights: Phase-resolved wave prediction methods are developed using sparse arrays of SWIFT buoys. Deterministic wave reconstruction improves accuracy by 63% relative to spectral forecasts. Wave prediction accuracy is dependent on nonlinearity, bandwidth, and decorrelation scale.