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Modeling surge dynamics improves coastal flood estimates in a global set of tropical cyclones

Urheber*innen
/persons/resource/thomas.vogt

Vogt,  Thomas
Potsdam Institute for Climate Impact Research;

/persons/resource/Simon.Treu

Treu,  Simon
Potsdam Institute for Climate Impact Research;

/persons/resource/matthias.mengel

Mengel,  Matthias
Potsdam Institute for Climate Impact Research;

/persons/resource/Katja.Frieler

Frieler,  Katja       
Potsdam Institute for Climate Impact Research;

/persons/resource/christian.otto

Otto,  Christian       
Potsdam Institute for Climate Impact Research;

Externe Ressourcen

https://doi.org/10.5281/zenodo.10419306
(Ergänzendes Material)

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Zitation

Vogt, T., Treu, S., Mengel, M., Frieler, K., Otto, C. (2024): Modeling surge dynamics improves coastal flood estimates in a global set of tropical cyclones. - Communications Earth and Environment, 5, 529.
https://doi.org/10.1038/s43247-024-01707-x


Zitierlink: https://publications.pik-potsdam.de/pubman/item/item_30285
Zusammenfassung
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
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.