A detailed climatology of ocean wind waves in the South Atlantic Ocean, based on ERA-5 reanalysis and in a higher-resolution wave hindcast (ERA-5H), both developed by the European Centre for Medium-Range Weather Forecasts, is presented. The higher resolution of the wave fields in the ERA-5H (22 km) allowed for a better description of the wind sea and swell features compared to previous global and regional studies along the Brazilian coast. Overall, it is shown that swell waves are more prevalent and carry more energy in the offshore area of the study area, while wind sea waves dominate the nearshore regions, especially along the northern coast of Brazil. The influence of different climate indices on the significant wave heights patterns is also presented, with two behavioral groups showing opposite correlations to the North Atlantic Oscillation and Southern Annular Mode than to the Southern Oscillation Index. The analysis of the decadal trends of wind sea and swell heights during the ERA-5H period (1979–2020) shows that the long-term trends of the total significant wave height in the South Atlantic Ocean are mostly due to swell events and the wave propagation effect from Southern Ocean storms.

Coastal flooding is among the most damaging natural hazards in Europe, yet large-scale assessments have typically relied on simplified static “bathtub” models and coarse elevation data. Here, we present a novel pan-European methodology that applies a dynamic flood model at 25 m resolution, forced by location-specific total water level hydrographs. These hydrographs integrate mean sea level, tides, storm surge, and wave setup with spatially varying foreshore slopes, allowing storm type, duration, and shape to be explicitly represented. More than 51 000 coastal target points were used to reconstruct events, and the methodology was validated against 12 local-scale historical floods across diverse coastlines. The validation results confirmed the robustness of the large-scale methodology while highlighting the strong dependence of the results on the resolution and vertical accuracy of the underlying digital elevation model. At continental-scale, sensitivity analyses quantified uncertainty from model selection, hydrograph shape, and storm type. Results show that static flood models systematically overestimate inundation, with errors exceeding 25 % in low-lying coastal floodplains such as Belgium and the United Kingdom. At the continental scale, storm type variability explains 41 % of flood map uncertainty, while hydrograph shape has a smaller but measurable effect. Including coastal protection standards reduces the estimated exposed floodplain by more than half, underscoring the critical role of defenses. By bridging the gap between global static assessments and local dynamic models, this study establishes a methodological benchmark for continental-scale flood hazard mapping.

Coastal storm-induced flooding threatens millions of people and infrastructures, highlighting the need for comprehensive flood risk assessments. A key component of these assessments is the spatial characterization of total water level (TWL), the primary driver of coastal flooding. We propose a flexible methodology for developing large-scale TWL hindcasts to estimate extreme events, considering possible spatial variabilities in marine dynamics. This methodology is applied to the European coastline, integrating downscaled nearshore waves, storm surges, and tides. The resulting hourly time series of the TWL have a spatial resolution of 1 km and covers the period from 1985 to 2021. Spatial variability is considered in foreshore slopes and extreme value detection thresholds, addressing common simplifications in large-scale studies. In addition to a characterization of extreme events based on the relative contributions of TWL components, sensitivity analyses of the wave contribution, wave data resolution, foreshore slopes, and wave setup formulations are conducted. The tide-dominated Atlantic coast is where the TWL is most affected by the wave dataset. The storm surge-dominated Baltic region exhibits the lowest confidence in estimating TWL return levels, partially due to the data and methods used. The Mediterranean Sea, characterized as a mixed environment, is the most sensitive to the inclusion of wave contribution. A classification of TWL extremes revealed that no regions have extreme events dominated by wave setup when compared to the remaining components, while those dominated by tides show the highest return levels.

Coastal flooding is among the most damaging natural hazards in Europe, yet large-scale assessments have typically relied on simplified static "bathtub" models and coarse elevation data. Here, we present a novel pan-European methodology that applies a dynamic flood model (RFSM-EDA) at 25 m resolution, forced by location-specific total water level (TWL) hydrographs. These hydrographs integrate mean sea level, tides, storm surge, and wave setup with spatially varying foreshore slopes, allowing storm type, duration, and shape to be explicitly represented. More than 51,000 coastal target points were used to reconstruct events, and the methodology was validated against 12 historical floods across diverse coastlines. Sensitivity analyses quantified uncertainty from model selection, DEM resolution, hydrograph shape, and storm type. Results show that static flood models systematically overestimate inundation, with errors exceeding 25 % in low-lying coastal floodplains such as Belgium and the United Kingdom. At the continental scale, storm type variability explains 41 % of flood map uncertainty, while hydrograph shape has a smaller but measurable effect. Including coastal protection standards reduces the estimated exposed floodplain by more than half, underscoring the critical role of defenses. By bridging the gap between global static assessments and local dynamic models, this study establishes a methodological benchmark for continental-scale flood hazard mapping. The framework not only advances scientific understanding of large-scale coastal flooding but also provides actionable evidence to support the EU Floods Directive, adaptation planning, and climate risk management in the finance and insurance sectors.

Analyzing extreme events and determining their impacts in terms of coastal flooding are crucial for understanding and preventing potential risks caused by such hazards. These risks include damage to coastal infrastructure and the built environment and impacts on the population. Identifying the key components of the total water level (TWL) reaching the coast and treating them properly to model flood propagation over land is a challenge whose complexity increases as the spatial scale increases. Although TWL calculation and flood modeling at large scales have been addressed in the literature before, there is still room for improvement if adaptation policies are to be developed, as they ought to be based on the most accurate and least uncertain risk analysis possible. For example, the resolution often adopted in existing studies for the TWL reconstruction (12.5 km to 70 km) is not high enough when it comes to estimating coastal impacts. This is mainly because such studies do not use downscaled wave dynamics but rather offshore conditions. Additionally, most research to date does not consider all main components of TWL neglecting the wave contribution, which can be an important driver of coastal flooding. Out of the ones that include it through wave setup, the majority use a simple approach (0.2Hs) and only a few adopt a semi-empirical formula, although with a spatially constant nearshore slope. As for the flood modeling itself, the highest resolution of digital elevation model (DEM) adopted is 25 m but with a static flood modeling approach, while the only pan-European dynamic flood modeling is applied to a 90 m DEM. This work aims to develop a process-based hindcast of coastal flood hazards at the pan-European scale, addressing key gaps in resolution, accuracy, and uncertainty sampling to meet the demands of risk-based adaptation frameworks. The approach combines downscaled wave conditions with still water levels to reconstruct the TWL hindcast, which is then used as climate forcing for a hydraulic model to simulate coastal flooding. The study consists of a process-based approach coupling a 2D flood model with TWL extreme cases over a 25 m resolution DEM along the European coastline. The approach has three main parts: (1) calculating TWL at 1 km resolution by combining storm surges, astronomical tide, and wave setup; (2) constructing hydrographs considering the spatial variability of storm duration, shape, and return levels derived from a peak-over-threshold analysis with spatially variable thresholds correspondent to an average of two events per year; and (3) simulating coastal flooding using RFSM-EDA flood model, which incorporates topography as a sub-element of the computational mesh and uses hydrographs and 30 m resolution land-use based Manning roughness coefficients as inputs. In addition to the main findings of the European-scale coastal flood simulations, it will be shown how the study is supported by 10 local-scale control cases which helped with the identification of the main uncertainty sources through sensitivity analysis of: (a) DEM resolution; (b) wave contribution and foreshore slope methods of calculation; (c) inclusion of terrain roughness; and (d) flood model applied.