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Abstract
Abstract
Highlights
Recent years have seen a surge of interest in deterministic wave forecasting for marine decision support systems, a sector that is poised to continue to grow along with further investment in the marine environment
Deriving the measurements from reference ocean surfaces generated from Joint North Sea Wave Observation Project (JONSWAP) and PM wavenumber spectra as described in § 2.1 allows for the effects of nonlinearity on the forecast to be examined in detail
A schematic of our forecasting approach using a JONSWAP spectral shape is given in figure 2
Summary
Recent years have seen a surge of interest in deterministic wave forecasting for marine decision support systems, a sector that is poised to continue to grow along with further investment in the marine environment. Qi et al (2018a) employed HOS to extend the general linear predictable zone of Qi et al (2018b), as well as comparing with tank data They emphasize the importance of nonlinearity in reconstructing a sea state, and develop a method to optimize this reconstruction for a given number of wave modes. Other approaches to nonlinear forecasting focus on using particular closed-form equations, such as the narrow-band cubic Schrödinger equation (NLS), and its extensions (Trulsen 2005; Simanesew et al 2017) Such model equations have the advantages of providing analytical insight and tractability, as well as computational efficiency, albeit with some loss of predictability for broad-banded or short-crested seas.
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