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- Improved estimates of extreme wave conditions in coastal areas from calibrated global reanalysesPublication . Fanti, Valeria; Ferreira, Oscar; Kümmerer, Vincent; Loureiro, CarlosThe 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. Leading global wave reanalyses greatly underestimate extreme wave heights in coastal regions but this can be reduced with the use of individual or global calibration equations, according to an evaluation of wave height reanalyses validated against data from 326 coastal buoys.
- Can global datasets be used to predict storm-induced coastal erosion?Publication . Fanti, Valeria; Ferreira, Óscar; Loureiro, CarlosThe scarcity of high-resolution in situ data hampers effective storm impact assessment and the development of early warning systems for coastal bar riers worldwide. This study introduces a novel methodology utilising a SWAN XBeach modelling chain, leveraging global hydrodynamic (WAVERYS and GTSM) and topo-bathymetric (TanDEM-X and ETOPO2022) datasets to perform first-order, globally applicable storm impact assessments for barrier coasts. The approach is validated with high-resolution data from Duck, North Carolina, using pre- and post-storm topographic LiDAR, recorded wave conditions and water levels. The results indicate that global datasets can reasonably reproduce barrier ero sion patterns, despite underestimation of total water levels and dune morphology due to the coarse resolution and inaccuracies in the GTSM and TanDEM-X data. The simulations effectively capture dune retreat and erosion trends, aligning with measured data, but inconsistencies are observed in morphological changes for the upper beach face. These discrepancies are likely due to differences in intertidal elevation and beach face steepness between the LiDAR data and global models at Duck. Additionally, the approach does not account for short-scale (~100 m) longshore variability, which can contribute to deviations in modelled results. This study demonstrates the potential of global datasets for storm impact mod elling, providing a first-order assessment with relevant information about storm induced erosion, which can be particularly useful in areas lacking high resolution data. However, it also highlights the need for further validation across diverse sites to enhance reliability and address methodological constraints.