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    Wind-wave climate changes and their impacts

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    WindWaveClimate.pdf (24.89Mb)
    Identificadores
    URI: https://hdl.handle.net/10902/35450
    DOI: 10.1038/s43017-023-00502-0
    ISSN: 2662-138X
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    Autoría
    Casas Prat, Mercè; Hemer, Mark A.; Dodet, Guillaume; Morim, Joao; Wang, Xiaolan L.; Mori, Nobuhito; Young, Ian; Erikson, Li; Kamranzad, Bahareh; Kumar, Prashant; Menéndez García, MelisaAutoridad Unican; Feng, Yang
    Fecha
    2024
    Derechos
    © The authors © Nature Research
    Publicado en
    Nature Reviews. Earth & Environment 2024, 5(1), 23-42 - (CORRIGENDUM), 2024, 5(2), 152
    Editorial
    Nature Research
    Enlace a la publicación
    https://doi.org/10.1038/s43017-023-00502-0
    Resumen/Abstract
    Wind-waves have an important role in Earth system dynamics through air-sea interactions and are key drivers of coastal and offshore hydro-morphodynamics that affect communities, ecosystems, infrastructure and operations. In this Review, we outline historical and projected changes in the wind-wave climate over the world's oceans, and their impacts. Historical trend analysis is challenging owing to the presence of temporal inhomogeneities from increased numbers and types of assimilated data. Nevertheless, there is general agreement over a consistent historical increase in mean wave height of 1-3 cm yr-1 in the Southern and Arctic Oceans, with extremes increasing by >10 cm yr-1 for the latter. By 2100, mean wave height is projected to rise by 5-10% in the Southern Ocean and eastern tropical South Pacific, and by >100% in the Arctic Ocean. By contrast, reductions in mean wave height up to 10% are expected in the North Atlantic and North Pacific, with regional variability and uncertainty for changes in extremes. Differences between 1.5 °C and warmer worlds reveal the potential benefit of limiting anthropogenic warming. Resolving global-scale climate change impacts on coastal processes and atmospheric-ocean-wave interactions requires a step-up in observational and modeling capabilities, including enhanced spatiotemporal resolution and coverage of observations, more homogeneous data products, multidisciplinary model improvement, and better sampling of uncertainty with larger ensembles.
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    UNIVERSIDAD DE CANTABRIA

    Repositorio realizado por la Biblioteca Universitaria utilizando DSpace software
    Contacto | Sugerencias
    Metadatos sujetos a:licencia de Creative Commons Reconocimiento 4.0 España