Global coastal wave storminess

Coastal wave storms pose a massive threat to over 10% of the world?s population now inhabiting the low elevation coastal zone and to the trillions of $ worth of coastal zone infrastructure and developments therein. Using a~40-year wave hindcast, we here present a world-first assessment of wind-wave...

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Bibliographic Details
Published in:Scientific Reports
Main Authors: Lobeto Alonso, Hector, Semedo, Álvaro, Lemos, Gil, Dastgheib, Ali, Menéndez García, Melisa, Ranasinghe, Roshanka, Bidlot, Jean-Raymond
Other Authors: Universidad de Cantabria
Format: Article in Journal/Newspaper
Language:English
Published: Nature Publishing Group 2024
Subjects:
Online Access:https://hdl.handle.net/10902/32497
https://doi.org/10.1038/s41598-024-51420-0
Description
Summary:Coastal wave storms pose a massive threat to over 10% of the world?s population now inhabiting the low elevation coastal zone and to the trillions of $ worth of coastal zone infrastructure and developments therein. Using a~40-year wave hindcast, we here present a world-first assessment of wind-wave storminess along the global coastline. Coastal regions are ranked in terms of the main storm characteristics, showing Northwestern Europe and Southwestern South America to suffer, on average, the most intense storms and the Yellow Sea coast and the South-African and Namibian coasts to be impacted by the most frequent storms. These characteristics are then combined to derive a holistic classification of the global coastlines in terms of their wave environment, showing, for example, that the open coasts of northwestern Europe are impacted by more than 10 storms per year with mean significant wave heights over 6 m. Finally, a novel metric to classify the degree of coastal wave storminess is presented, showing a general latitudinal storminess gradient. Iceland, Ireland, Scotland, Chile and Australia show the highest degree of storminess, whereas Indonesia, Papua-New Guinea, Malaysia, Cambodia and Myanmar show the lowest. H.L. and M.M. acknowledge the financial support from the European Commission through the project CoCliCo (101003598, Call: H2020-LC-CLA-2020-2), and the ThinkInAzul programme, with funding from European Union NextGenerationEU/PRTR-C17.I1 and the Comunidad de Cantabria. The authors acknowledge the European Centre for Medium-range Weather Forecasts for providing the data to conduct the analysis.