Marissa L. Yates

Climate change is expected to alter the metocean conditions that determine the performance and design of offshore wind farms, yet its decision-relevant consequences for a given coastline remain little studied. This study assesses climate-change impacts on wind, waves and water levels along the French coasts and translates them into consequences for energy production, structural design and coastal infrastructure. CMIP6 models are bias-corrected with the CDF-t method against in-situ-validated reanalyses at six offshore points in the English Channel, the Atlantic and the Mediterranean, and extremes are estimated with a non-stationary, monthly-block extreme-value model, under up to four emission scenarios and two time horizons. Mean wind speed and significant wave height tend to decrease, while mean sea level rises by 15 to 17 cm by 2031–2050, and extreme wave heights and storm surges intensify under most scenarios even as mean conditions weaken; for means and extremes alike, inter-model spread is often as large as the projected change. Annual energy production decreases by 1 % to 8 % by the end of the century and tower-base fatigue loads by up to about 2 % on average, both with wide model spread, and at a representative cable-landfall site the beach response to a 50-year storm depends more on the accompanying storm surge than on changes in wave conditions. Offshore wind planning along the French coasts therefore cannot rely on average-climate trends alone, and should incorporate explicit uncertainty ranges and forward-looking, scenario-informed design conditions.

In this study, we develop a surrogate modeling framework for fully nonlinear potential flow (FNPF), for use in studying nearshore wave propagation, to avoid mesh dependency and numerical instability in conventional numerical models. A Physics-Informed Neural Network (PINN), called Wave2D-DeepONet, is constructed to map a time-series of the free surface elevation measured at a single location to the corresponding spatio-temporal wave field over a variable bathymetry. The training and test datasets are generated using a Boundary Element Method approach. For solitary waves, by embedding the governing equations and boundary conditions into the loss function, the proposed model accurately reconstructs the free surface elevation and velocity potential, as well as the associated horizontal and vertical velocities. The results demonstrate clear advantages of using a PINN over purely Data-Driven approaches in terms of physical consistency and accuracy, particularly near wave crests, troughs, and boundaries. For periodic waves, the generalization of the model is systematically examined. The Data-Driven results indicate that prediction accuracy is primarily governed by the diversity and coverage of the training wave conditions rather than by the choice of loss weighting strategies. By improving the numerical stability of the outputs using QR-decomposition and enriching the training wave dataset, accurate predictions for previously unseen wave cases are achieved. These findings suggest that physics-informed operator learning models provide a feasible surrogate modeling approach for nonlinear periodic wave propagation.

With climate change and accelerating sea-level rise (SLR), long-term predictions of shoreline evolution are crucial to assess climate adaptation plans in coastal areas. Meanwhile, knowledge gaps in the physics of shoreline response to the combined action of waves and SLR hinder making reliable long-term shoreline projections. Equilibrium beach theory states that a beach profile shape equilibrates with its local wave and sea-level conditions. In the context of equilibrium beach theory, we present a physical interpretation of beach response to SLR that leads to the identification of two main contributing processes: passive flooding and increased wave-driven erosion efficiency (i.e. wave reshaping effect). Using this new interpretation, we analyze data from existing laboratory studies that measured the equilibrium beach response to controlled SLR and wave conditions. The data indicate a clear relationship among the analyzed variables, corroborating the potential of the proposed concept, and improving the understanding of shoreline response to SLR. Our results support the integration of SLR-driven recession into equilibrium shoreline models for future studies, making a step towards the development of a generalized equilibrium shoreline model.

The evolution of coastal hazards in the context of climate change has been addressed at the regional scale by studying the height and frequency of extreme sea levels (ESL). However, sea level is not the only factor determining the hazard changes that can be used at this scale. Therefore, this article proposes an assessment method of coastal hazard changes integrating other determinants: geographical configurations (continental or island), tidal regimes and meteo-oceanic event types. This method, applied to the coasts of France (mainland and overseas), reveals significant differences in the evolution of coastal hazards: coasts subjected to high tidal ranges and storms (e.g., Atlantic, English Channel and North Sea) will experience a relatively moderate evolution of the hazard, thanks to «training» for the future conditions that present-day high variations constitute. Conversely, the microtidal shorelines of temperate latitudes (e.g., those of the Mediterranean) benefit from only a small variability generated mainly by storm surges, and are therefore poorly prepared for sea level rise. The situation of the small tropical islands is of particular concern: with the passage of cyclones these territories are subjected to very energetic sea states, but by their form, the surges remain moderate, which constitutes, as well as the low tidal ranges, a limiting factor for preparing for sea level rise. In addition to this approach at the regional level, geological, sedimentary and biological evolutions, as well as local hydraulic phenomena, should be considered to assess at a finer spatio-temporal scale the hazard changes.

Coastal systems are highly dynamic morphological environments due to erosion and sedimentation at different spatio-temporal scales as a result of natural forcing

Understanding the interactions between dune systems and beaches is critical to determining the short‐term shoreline response and the long‐term resilience. In this study, almost 15 years of monthly beach/dune measurements were analyzed for three different profiles at Vougot Beach, France to understand and predict shoreline changes from intra‐annual to multi‐annual time‐scales. Four migration modes: advance/retreat (translation modes) and steepening/flattening (rotation modes) were identified through a centroid analysis. The analysis showed that translation and rotation can occur simultaneously, with long‐term trends of beach retreat and profile steepening (lower beach retreating and upper beach advancing), which was interrupted by two energetic wave events causing profile flattening (lower beach advancing and upper beach retreating). These two observations are evidence of how the sediment contribution resulting from the dune erosion events temporarily caused a large advance in the shoreline position. A recent modeling approach that accounts for different time‐scales is applied to predict the shoreline changes, showing significant improvements in comparison to a traditional shoreline equilibrium model when time‐scales related with the dune erosion and recovery are considered. The results showed that the dune system affects the beach profile evolution both spatially, with different impacts at different elevations along the cross‐shore profile, and temporally, by periodically redistributing the sediment in the system.

Wave dynamics contribute significantly to coastal hazards and were thus investigated at Vougot Beach by simulating both historical and projected future waves considering climate change impacts. The historical period included a major storm event. This period was projected to the future using three globally averaged sea level rise (SLR) scenarios for 2100, and combined SLR and wave climate scenarios for A1B, A2, and B1 emissions paths of the IPCC. The B1 wave climate predicts an increase in the occurrence of storm events. The simulated waves in all scenarios showed larger relative changes at the beach than in the nearshore area. The maximum increase of wave energy for the combined SLR and wave scenarios was 95%, while only 50% for the SLR-only scenarios. The effective bed shear stress from waves and currents showed different spatial variability than that of the wave height, emphasizing the importance of interactions between nearshore waves and currents. Increases in the effective bed shear stress (combined scenarios: up to 190%, and SLR-only scenarios: 35%) indicate that the changes in waves and currents will likely have significant impacts on the nearshore sediment transport. This work emphasizes that combined SLR and future wave climate scenarios need to be used to evaluate future changes in local hydrodynamics and their impacts. These results provide preliminary insights into potential future wave dynamics at Vougot Beach under different climate change scenarios. Further studies are necessary to generalize the results by investigating the wave dynamics during storm events with different hydrodynamical conditions and to evaluate potential changes in sediment transport and morphological evolution due to climate change.