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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-Barthélemy in the Lesser Antilles. Hurricane Irma was contextualized from tropical cyclone track data and local weather observations collected by Météo-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.

Using multi-date satellite imagery and field observations, this paper assesses the inferred impacts of September 2017 cyclones on the beaches of Saint-Martin Island. Twenty-two beaches out of 30 predominantly exhibited shoreline retreat, with the highest retreat value (-166.45 m) recorded on the north-eastern coast. While erosion predominated on beaches and at the sand dune front, inner areas generally exhibited accretion, with sand sheets (up to 135 m from the pre-cyclone vegetation line) indicating landward sediment transfer. Natural back-reef beaches exhibited the formation of new beach ridges, marked (up to 2 m) upward growth and alongshore beach extension. The high spatial variability of inferred impacts is attributed to the cyclone's track, coast exposure, beach configuration and, importantly, human-driven environmental change. Whereas vegetation removal exacerbated marine inundation and inhibited the vertical accretion of beaches, shoreline hardening aggravated wave-induced sediment loss while also inhibiting sediment deposition. Four beach response modes are distinguished. Based on findings, we identified three major areas of action for risk reduction and adaptation to climate change. Depending on beach response and site specificities, relocation and the determination of set-back lines, coastal buffer restoration, or engineered structures' upgrading should be prioritized.

Parametric cyclonic wind fields are widely used worldwide for insurance risk underwriting, coastal planning, and storm surge forecasts. They support high-stakes financial, development and emergency decisions. Yet, there is still no consensus on a potentially “best” parametric approach, nor guidance to choose among the great variety of published models. The aim of this paper is to demonstrate that recent progress in estimating extreme surface wind speeds from satellite remote sensing now makes it possible to assess the performance of existing parametric models, and select a relevant one with greater objectivity. In particular, we show that the Cyclone Global Navigation Satellite System (CYGNSS) mission of NASA, along with the Advanced Scatterometer (ASCAT), are able to capture a substantial part of the tropical cyclone structure, and to aid in characterizing the strengths and weaknesses of a number of parametric models. Our results suggest that none of the traditional empirical approaches are the best option in all cases. Rather, the choice of a parametric model depends on several criteria, such as cyclone intensity and the availability of wind radii information. The benefit of using satellite remote sensing data to select a relevant parametric model for a specific case study is tested here by simulating hurricane Maria (2017). The significant wave heights computed by a wave-current hydrodynamic coupled model are found to be in good agreement with the predictions given by the remote sensing data. The results and approach presented in this study should shed new light on how to handle parametric cyclonic wind models, and help the scientific community conduct better wind, wave, and surge analyses for tropical cyclones.

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