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A database of global storm surge reconstructions

Storm surges are among the deadliest coastal hazards and understanding how they have been affected by climate change and variability in the past is crucial to prepare for the future. However, tide gauge records are often too short to assess trends and perform robust statistical analyses. Here we use...

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Autores principales: Tadesse, Michael Getachew, Wahl, Thomas
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8096961/
https://www.ncbi.nlm.nih.gov/pubmed/33947872
http://dx.doi.org/10.1038/s41597-021-00906-x
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author Tadesse, Michael Getachew
Wahl, Thomas
author_facet Tadesse, Michael Getachew
Wahl, Thomas
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description Storm surges are among the deadliest coastal hazards and understanding how they have been affected by climate change and variability in the past is crucial to prepare for the future. However, tide gauge records are often too short to assess trends and perform robust statistical analyses. Here we use a data-driven modeling framework to simulate daily maximum surge values at 882 tide gauge locations across the globe. We use five different atmospheric reanalysis products for the storm surge reconstruction, the longest one going as far back as 1836. The data that we generate can be used, for example, for long-term trend analyses of the storm surge climate and identification of regions where changes in the intensity and/or frequency of storms surges have occurred in the past. It also provides a better basis for robust extreme value analysis, especially for tide gauges where observational records are short. The data are made available for public use through an interactive web-map as well as a public data repository.
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spelling pubmed-80969612021-05-05 A database of global storm surge reconstructions Tadesse, Michael Getachew Wahl, Thomas Sci Data Data Descriptor Storm surges are among the deadliest coastal hazards and understanding how they have been affected by climate change and variability in the past is crucial to prepare for the future. However, tide gauge records are often too short to assess trends and perform robust statistical analyses. Here we use a data-driven modeling framework to simulate daily maximum surge values at 882 tide gauge locations across the globe. We use five different atmospheric reanalysis products for the storm surge reconstruction, the longest one going as far back as 1836. The data that we generate can be used, for example, for long-term trend analyses of the storm surge climate and identification of regions where changes in the intensity and/or frequency of storms surges have occurred in the past. It also provides a better basis for robust extreme value analysis, especially for tide gauges where observational records are short. The data are made available for public use through an interactive web-map as well as a public data repository. Nature Publishing Group UK 2021-05-04 /pmc/articles/PMC8096961/ /pubmed/33947872 http://dx.doi.org/10.1038/s41597-021-00906-x Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) applies to the metadata files associated with this article.
spellingShingle Data Descriptor
Tadesse, Michael Getachew
Wahl, Thomas
A database of global storm surge reconstructions
title A database of global storm surge reconstructions
title_full A database of global storm surge reconstructions
title_fullStr A database of global storm surge reconstructions
title_full_unstemmed A database of global storm surge reconstructions
title_short A database of global storm surge reconstructions
title_sort database of global storm surge reconstructions
topic Data Descriptor
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8096961/
https://www.ncbi.nlm.nih.gov/pubmed/33947872
http://dx.doi.org/10.1038/s41597-021-00906-x
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