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A 100-member ensemble simulations of global historical (1951–2010) wave heights
The d4PDF-WaveHs dataset represents the first single model initial-condition large ensemble of historical significant ocean wave height (H(s)) at a global scale. It was produced using an advanced statistical model with predictors derived from Japan’s d4PDF ensemble of historical simulations of sea l...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10244329/ https://www.ncbi.nlm.nih.gov/pubmed/37280216 http://dx.doi.org/10.1038/s41597-023-02058-6 |
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author | Casas-Prat, Mercè Wang, Xiaolan L. Mori, Nobuhito Feng, Yang Chan, Rodney Shimura, Tomoya |
author_facet | Casas-Prat, Mercè Wang, Xiaolan L. Mori, Nobuhito Feng, Yang Chan, Rodney Shimura, Tomoya |
author_sort | Casas-Prat, Mercè |
collection | PubMed |
description | The d4PDF-WaveHs dataset represents the first single model initial-condition large ensemble of historical significant ocean wave height (H(s)) at a global scale. It was produced using an advanced statistical model with predictors derived from Japan’s d4PDF ensemble of historical simulations of sea level pressure. d4PDF-WaveHs provides 100 realizations of H(s) for the period 1951–2010 (hence 6,000 years of data) on a 1° × 1° lat.-long. grid. Technical comparison of model skill against modern reanalysis and other historical wave datasets was undertaken at global and regional scales. d4PDF-WaveHs provides unique data to understand better the poorly known role of internal climate variability in ocean wave climate, which can be used to estimate better trend signals. It also provides a better sampling of extreme events. Overall, this is crucial to properly assess wave-driven impacts, such as extreme sea levels on low-lying populated coastal areas. This dataset may be of interest to a variety of researchers, engineers and stakeholders in the fields of climate science, oceanography, coastal management, offshore engineering, and energy resource development. |
format | Online Article Text |
id | pubmed-10244329 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-102443292023-06-08 A 100-member ensemble simulations of global historical (1951–2010) wave heights Casas-Prat, Mercè Wang, Xiaolan L. Mori, Nobuhito Feng, Yang Chan, Rodney Shimura, Tomoya Sci Data Data Descriptor The d4PDF-WaveHs dataset represents the first single model initial-condition large ensemble of historical significant ocean wave height (H(s)) at a global scale. It was produced using an advanced statistical model with predictors derived from Japan’s d4PDF ensemble of historical simulations of sea level pressure. d4PDF-WaveHs provides 100 realizations of H(s) for the period 1951–2010 (hence 6,000 years of data) on a 1° × 1° lat.-long. grid. Technical comparison of model skill against modern reanalysis and other historical wave datasets was undertaken at global and regional scales. d4PDF-WaveHs provides unique data to understand better the poorly known role of internal climate variability in ocean wave climate, which can be used to estimate better trend signals. It also provides a better sampling of extreme events. Overall, this is crucial to properly assess wave-driven impacts, such as extreme sea levels on low-lying populated coastal areas. This dataset may be of interest to a variety of researchers, engineers and stakeholders in the fields of climate science, oceanography, coastal management, offshore engineering, and energy resource development. Nature Publishing Group UK 2023-06-06 /pmc/articles/PMC10244329/ /pubmed/37280216 http://dx.doi.org/10.1038/s41597-023-02058-6 Text en © Environment and Climate Change Canada 2023 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/) . |
spellingShingle | Data Descriptor Casas-Prat, Mercè Wang, Xiaolan L. Mori, Nobuhito Feng, Yang Chan, Rodney Shimura, Tomoya A 100-member ensemble simulations of global historical (1951–2010) wave heights |
title | A 100-member ensemble simulations of global historical (1951–2010) wave heights |
title_full | A 100-member ensemble simulations of global historical (1951–2010) wave heights |
title_fullStr | A 100-member ensemble simulations of global historical (1951–2010) wave heights |
title_full_unstemmed | A 100-member ensemble simulations of global historical (1951–2010) wave heights |
title_short | A 100-member ensemble simulations of global historical (1951–2010) wave heights |
title_sort | 100-member ensemble simulations of global historical (1951–2010) wave heights |
topic | Data Descriptor |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10244329/ https://www.ncbi.nlm.nih.gov/pubmed/37280216 http://dx.doi.org/10.1038/s41597-023-02058-6 |
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