Joint stochastic simulation of extreme coastal and offshore significant wave heights

The characterisation of future extreme wave events is crucial because of their multiple impacts, covering a broad range of topics such as coastal flood hazard, coastal erosion, reliability of offshore and coastal structures. The main goal of this paper is to propose and study a stochastic simulator that, given offshore conditions (peak direction Dp, peak period Tp and moderately high significant wave heights Hs), produces jointly offshore and coastal extreme Hs, a quantity measuring the wave severity and which represent a key feature in coastal risk analysis. For this purpose, we rely on bivariate Peaks over Threshold and a nonparametric simulation scheme of bivariate GPD is developed. From this joint simulator, a second generator is derived, allowing for conditional simulations of extreme Hs. Finally, to take into account nonstationarities, the extended generalised Pareto model is also adapted, letting the parameters vary with specific sea state parameters Tp and Dp. The performances of the two proposed generators are illustrated on simulated data and then applied to the simulation of new extreme oceanographic conditions close to the French Brittany coast using hindcast sea state data. Results show that the proposed algorithms successfully simulate future extreme Hs near the coast in a nonparametric way, jointly or conditionally on sea state parameters from a coarser model.

Keyword(s)

Bivariate extremes, multivariate generalised Pareto distribution, simulation of ex-tremes, nonstationarity, extended generalised Pareto distribution, covariate effects, significant wave heights

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Legrand Juliette, Ailliot Pierre, Naveau Philippe, Raillard Nicolas (2023). Joint stochastic simulation of extreme coastal and offshore significant wave heights. Annals Of Applied Statistics. 17 (4). 3363-3383. https://doi.org/10.1214/23-AOAS1766, https://archimer.ifremer.fr/doc/00834/94619/

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