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| Main Authors: | , , , , |
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| Format: | Recurso digital |
| Language: | |
| Published: |
Zenodo
2024
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| Online Access: | https://doi.org/10.1038/s43247-024-01707-x |
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- <p><strong>This is the accepted version. The published version is available on this DOI: <a href="https://doi.org/10.1038/s43247-024-01707-x">https://doi.org/10.1038/s43247-024-01707-x</a></strong></p> <p><strong>Abstract:</strong></p> <p>Tropical cyclone-induced storm surge is a major coastal risk, which will be further amplified by rising sea levels under global warming. Here, we present a computational efficient, globally applicable modeling approach in which ocean surge and coastal inundation dynamics are modeled in a single step by the open-source solver GeoClaw. We compare our approach to two state-of-the-art, globally applicable approaches: (i) using a static inundation model to translate coastal water level time series<br>from a full-scale physical ocean dynamics into inundated areas, and (ii) a fully static approach directly mapping wind fields to inundation areas. For a global set of 71 storms, we compare the modeled flooded areas to satellite-based floodplain observations. We find that, overall, the models have only moderate skill in reproducing the observed floodplains. GeoClaw performs better than the two other modeling approaches that lack a process-based representation of inundation dynamics. The computational efficiency of the presented approach opens up new perspectives for global assessments of coastal risks from tropical cyclones.</p> <h3>Cite this article</h3> <p>Vogt, T., Treu, S., Mengel, M. <em>et al.</em> Modeling surge dynamics improves coastal flood estimates in a global set of tropical cyclones. <em>Commun Earth Environ</em> <strong>5</strong>, 529 (2024). https://doi.org/10.1038/s43247-024-01707-x</p>