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In view of the high vulnerability of the small islands of the Lesser Antilles to cyclonic hazards, realistic very fine scale numerical simulation of hurricane-induced winds is essential to prevent and manage risks. The present innovative modeling aims at combining the most realistically simulated strongest gusts driven by tornado-scale vortices within the eyewall and the most realistic complex terrain effects. The Weather Research and Forecasting (WRF) model with the nonlinear backscatter and anisotropy (NBA) large eddy simulation (LES) configuration was used to reconstruct the devastating landfall of category 5 Hurricane Irma (2017) on Saint Barthélemy and Saint Martin. The results pointed out that the 30 m scale seems necessary to simulate structures of multiple subtornadic-scale vortices leading to extreme peak gusts of 132 m s−1 over the sea. Based on the literature, such extreme gust values have already been observed and are expected for category 5 hurricanes like Irma. Risk areas associated with terrain gust speed-up factors greater than 1 have been identified for the two islands. The comparison between the simulated gusts and the remote sensing building damage highlighted the major role of structure strength linked with the socio-economic development of the territory. The present modeling method could be easily extended to other small mountainous islands to improve the understanding of observed past damage and to develop safer urban management and appropriate building standards.

Tsunamis are among the deadliest threats to coastal areas as reminded by the recent tragic events in the Indian Ocean in 2004 and in Japan in 2011. A large number of tropical islands are indeed exposed due to their proximity to potential tsunami sources in tectonic subduction zones. For these territories, assessing tsunamis’ impact is of major concern for early warning systems and management plans. The effectiveness of inundation predictions relies, among other things, on processes engaged at the scale of the local bathymetry and topography. As part of the project C3AF that aimed to study the consequences of climate change on the French West Indies, we used the numerical model SCHISM to simulate the propagation of several potential tsunamis as well as their impacts on the Guadeloupe islands (French West Indies). Working from the findings of the most recent studies, we used the simulations of four scenarios of collapse of the Cumbre Vieja volcano in La Palma, Canary islands. We then used FUNWAVE-TVD to simulate trans-Atlantic wave propagation until they reached the Guadeloupe archipelago where we used SCHISM to assess their final impact. Inundation is quantified for the whole archipelago and detailed for the most exposed areas. Finally, in a climate change perspective, inundation is compared for different sea levels and degrees of vegetation cover deterioration using modified friction coefficients. We then discuss the results showing that climate change-related factors would amplify the impact more in the case of smaller inundation along with model limitations and assumptions.

This study aims to better understand coastal processes associated with extreme cyclonic events through the study of the coastal changes, flooding and damage that resulted from the passage of a category 5 hurricane (Irma) on 6 September 2017 over the islands of Saint-Martin and Saint-Barth&eacute, lemy in the Lesser Antilles. Hurricane Irma was contextualized from tropical cyclone track data and local weather observations collected by M&eacute, t&eacute, o-France, as well as high-resolution numerical modelling. Field work involved the study of accretion coasts through qualitative observations, topo-morphological and sedimentary surveys, as well as image acquisition with Unmanned Aerial Vehicle (UAV) surveys during two trips that were made 2 and 8 months after the catastrophe. Wave propagation and flood numerical models are presented and compared to field data. Our field analysis also reports on the devastating impacts of storm surges and waves, which reached 4 and 10 meters height, respectively, especially along east-facing shores. The approaches reveal a variety of morpho-sedimentary responses over both natural and highly urbanized coasts. The analysis shows the effects of coastal structures and streets on flow channeling, on the amplification of some erosion types, and on water level increase. Positive spatial correlation is found between damage intensity and marine flood depth. The signatures of ocean-induced damage are clear and tend to validate the relevance of the intensity scale used in this study.

International audience; In Bangladesh, the Ganges, Brahmaputra, and Meghna Rivers come together to form the largest delta in the world. This low-lying region is one of the most densely populated area in the world and is prone to monsoonal flooding and frequent inter-monsoon cyclones. Sea-level rise, along with tectonic, sediment load and groundwater extraction induced land subsidence, significantly exacerbate the Bangladesh's coastal vulnerability. A comprehensive understanding of relative sea level variability in this region is therefore crucial and should help to anticipate the impacts of climate change and implement adaptation strategies. For the first time, by combining a unique set of 100 water/sea level measurements, we reconstructed the regional relative water level changes since the 1970s. These information are analyzed against storm surge hazard maps, obtained from a probabilistic study of a large ensemble of statistically and physically consistent synthetic cyclone events representative of the current climate (1980-2015). Thus, a regional vulnerability assessment is conducted, with some specific geographical areas thoughtfully discussed. This work is an essential first step to reduce the consequences of relative sea level rise and storm-surge inundation impacts on the Bangladesh's population.

Almost every year, Bangladesh experiences disasters such as tropical cyclones, storm surges, coastal erosion or floods. Tropical cyclones originate from the North Indian Ocean and often cause devastating flood inundations in Bangladesh. Storm surges of the Bay of Bengal (BOB) are larger compared to other regions of the world for similar cyclones due to amplification by the shallow water depth, huge continental shelf and convergent coastlines. This scenario of inundation for such storm surges in the future when the sea level rise (SLR) occurs due to global warming will be different from the present. The densely populated coastal region of Bangladesh is likely to become more vulnerable in the future due to SLR. Disaster risks can be reduced if storm surges can be predicted well ahead. To assess the possible changes of inundation in the future, a widely used coastal model, Delft3D, has been applied for this BOB region. The model has been validated for the storm surge of three recent devastating cyclones, namely, Sidr, Aila and Roanu in the southern coast of Bangladesh. The validated model has been run to produce inundation maps and statistics for cyclonic storm surges such as Sidr, Aila and Roanu and probable SLR. Three possible SLR boundary conditions are chosen from the business-as-usual climate scenario representative concentration pathway 8.5 with values of 0.5m (lower limit), 1m (upper limit) and 1.5m (extreme case, considering the subsidence and a rapid collapse of the Antarctic ice sheet). It is found that a category 4 cyclone such as cyclone Sidr would inundate 2.6%, 3.67% and 5.84% of the area of the country if the SLR is 0.5, 1 and 1.5m, which will affect the livelihood of nearly 4.1, 7.0 and 9.1 million people of Bangladesh, respectively. It will also inundate up to 21.0%, 42.1% and 65.1% of the Sundarbans mangrove forest, which will undoubtedly affect the ecology of this unique ecosystem.

In the Lesser Antilles, coastal inundations from hurricane-induced storm surges pose a great threat to lives, properties and ecosystems. Assessing current and future storm surge hazards with sufficient spatial resolution is of primary interest to help coastal planners and decision makers develop mitigation and adaptation measures. Here, we use wave–current numerical models and statistical methods to investigate worst case scenarios and 100-year surge levels for the case study of Martinique under present climate or considering a potential sea level rise. Results confirm that the wave setup plays a major role in the Lesser Antilles, where the narrow island shelf impedes the piling-up of large amounts of wind-driven water on the shoreline during extreme events. The radiation stress gradients thus contribute significantly to the total surge – up to 100 % in some cases. The nonlinear interactions of sea level rise (SLR) with bathymetry and topography are generally found to be relatively small in Martinique but can reach several tens of centimeters in low-lying areas where the inundation extent is strongly enhanced compared to present conditions. These findings further emphasize the importance of waves for developing operational storm surge warning systems in the Lesser Antilles and encourage caution when using static methods to assess the impact of sea level rise on storm surge hazard.