The analysis of extreme wave conditions is crucial for understanding and mitigating coastal hazards. As global wave reanalyses allow to extend the evaluation of wave conditions to periods and locations not covered by in-situ measurements, their direct use is common. However, in coastal areas, the accuracy of global reanalyses is lower, particularly for extreme waves. Here we compare two leading global wave reanalyses against 326 coastal buoys, demonstrating that both reanalyses consistently underestimate significant wave height, 50-year return period and mean wave period in most coastal locations around the world. Different calibration methods applied to improve the modelled extreme waves, resulting in a 53% reduction in the underestimation of extreme wave heights. Importantly, the 50-year return period for significant wave height is improved on average by 55%. Extreme wave statistics determined for coastal areas directly from global wave reanalyses require careful consideration, with calibration largely reducing uncertainty and improving confidence.

Coastal storms can cause erosion and flooding of coastal areas, often accompanied by significant social-economic disruption. As such, storm characterisation is crucial for an improved understanding of storm impacts and thus for coastal management. However, storm definitions are commonly different between authors, and storm thresholds are often selected arbitrarily, with the statistical and meteorological independence between storm events frequently being neglected. In this work, a storm identification algorithm based on statistically defined criteria was developed to identify independent storms in time series of significant wave height for high wave energy environments. This approach proposes a minimum duration between storms determined using the extremal index. The performance of the storm identification algorithm was tested against the commonly used peak-over-threshold. Both approaches were applied to 40 and 70-year-long calibrated wave reanalyses datasets for Western Scotland, where the intense and rapid succession of extratropical storms during the winter makes the identification of independent storm events notably challenging. The storm identification algorithm provides results that are consistent with regional meteorological processes and timescales, allowing to separate independent storms during periods of rapid storm succession, enabling an objective and robust storm characterisation. Identifying storms and their characteristics using the proposed algorithm allowed to determine a statistically significant increasing long-term trend in storm duration, which contributes to the increase in storm wave power in the west of Scotland. The coastal storm identification algorithm is found to be particularly suitable for high-energy, storm-dominated coastal environments, such as those located along the main global extratropical storm tracks.

Outer shelf sedimentary records are promising for determining the recurrence intervals of tsunamis. However, compared to onshore deposits, offshore deposits are more difficult to access, and so far, studies of outer shelf tsunami deposits are scarce. Here, an example of studying these deposits is presented to infer implications for tsunami-related signatures in similar environments and potentially contribute to pre-historic tsunami event detections. A multidisciplinary approach was performed to detect the sedimentary imprints left by the 1755 CE tsunami in two cores, located in the southern Portuguese continental shelf at water depths of 58 and 91 m. Age models based on ¹⁴C and ²¹⁰Pb_xs allowed a probable correspondence with the 1755 CE tsunami event. A multi-proxy approach, including sand composition, grain-size, inorganic geochemistry, magnetic susceptibility, and microtextural features on quartz grain surfaces, yielded evidence for a tsunami depositional signature, although only a subtle terrestrial signal is present. A low contribution of terrestrial material to outer shelf tsunami deposits calls for methodologies that reveal sedimentary structures linked to tsunami event hydrodynamics. Finally, a change in general sedimentation after the tsunami event might have influenced the signature of the 1755 CE tsunami in the outer shelf environment.

Storm-induced morphological changes in coastal barriers are primarily driven by hydrodynamic forcing. However, in rock-fronted coasts the presence of geological features can modulate storm impacts, but the extent to which these non-dynamic variables influence barrier morphological response to storms is still poorly understood. This study explores the influence of intertidal rock platforms on storm-driven morphological changes. Using the process-based XBeach model, dune erosion during an energetic winter storm was simulated across different schematic cross-shore profiles, incorporating variable intertidal rock platform configurations. The schematic profiles are based on existing barrier profiles in the Outer Hebrides, NW Scotland. Calibration of the model involved adjusting friction coefficients of exposed bedrock surfaces to improve the ability to reproduce observed nearshore wave heights and morphological changes in pre- and post-storm profiles. The results show that higher intertidal rock platforms (above mean sea level) are associated with reduced dune erosion, while lower rock platforms are associated with more extensive dune erosion. This highlights the complex interaction between geological control and storm impacts, with implications for improved understanding of coastal resilience and storm-driven morphosedimentary dynamics in rock-fronted barrier systems.

Quantifying and understanding coastal geomorphological change are of paramount importance for coastal management and policy making (Boak and Turner, 2005). For wave-dominated coastal barriers, contemporary morphological change is mainly determined by hydrodynamic forcing conditions and antecedent beach morphology (e.g., Burvingt and Castelle, 2023). However, in geologically controlled barriers, beach morphodynamic processes and responses are additionally influenced by the pre-existing geological framework (Robinet et al., 2020). These geological controls are rarely considered in shoreline change assessments, despite being essential for predicting future coastal change at the management scales (Cooper et al., 2018). This work examines the influence of foreshore configuration with varying degrees of geological control on shoreline evolution using seven years of satellite derived shoreline data from three beaches in the Outer Hebrides barriers (NW Scotland).