Sailing synthetic seas: Stochastic simulation of benchmark sea state time series

Coastal and offshore engineering relies on the analysis of sea state parameters, such as significant wave height (Hm0), zero-crossing mean wave period (Tm02), and mean wave direction (Θm). Since observed records of these parameters usually span only a few years, proper uncertainty assessment requires the simulation of unobserved but equally plausible time series. This study suggests a simple stochastic method, named SyntheSeas, to generate synthetic sequences that preserve marginal distributions and power spectra along with power cross-spectra of Hm0, Tm02, and Θm. SyntheSeas is a tailored version of the multivariate Iterative Amplitude Adjusted Fourier Transform (IAAFT) method, and has several desirable properties: (i) it relies on minimal assumptions, (ii) it accounts for the limiting steepness condition that constrains the relationship between Hm0 and Tm02 without using ad hoc parametrisation, and (iii) it accounts for the modelling problems due to the circular behaviour of Θm with satisfactory approximation. Thanks to its simplicity and transparency, SyntheSeas (i) allows the identification of the key properties required to simulate realistic time series of Hm0, Tm02, and Θm, (ii) provides a benchmark to test parametric models and their components, and (iii) enables quick applications, such as preliminary uncertainty and sensitivity analyses, without requiring advanced expertise in stochastic modelling. As a proof of concept, we discuss an application to data recorded from four wave buoys deployed around the United Kingdom. © 2022 The Author(s)