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Local sea level trends, accelerations and uncertainties over 1993–2019
Satellite altimetry missions provide a quasi-global synoptic view of sea level variations over more than 25 years and provide regional sea level (SL) indicators such as trends and accelerations. Estimating realistic uncertainties on these quantities is crucial to address current climate science ques...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7791125/ https://www.ncbi.nlm.nih.gov/pubmed/33414438 http://dx.doi.org/10.1038/s41597-020-00786-7 |
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author | Prandi, Pierre Meyssignac, Benoit Ablain, Michaël Spada, Giorgio Ribes, Aurélien Benveniste, Jérôme |
author_facet | Prandi, Pierre Meyssignac, Benoit Ablain, Michaël Spada, Giorgio Ribes, Aurélien Benveniste, Jérôme |
author_sort | Prandi, Pierre |
collection | PubMed |
description | Satellite altimetry missions provide a quasi-global synoptic view of sea level variations over more than 25 years and provide regional sea level (SL) indicators such as trends and accelerations. Estimating realistic uncertainties on these quantities is crucial to address current climate science questions. While uncertainty estimates are available for the global mean sea level (GMSL), information is not available at local scales so far. We estimate a local satellite altimetry error budget and use it to derive local error variance-covariance matrices, and estimate confidence intervals on trends and accelerations at the 90% confidence level. Over 1993–2019, we find that the average local sea level trend uncertainty is 0.83 mm.yr(−1) with values ranging from 0.78 to 1.22 mm.yr(−1). For accelerations, uncertainties range from 0.057 to 0.12 mm.yr(−1), with a mean value of 0.062. We also perform a sensitivity study to investigate a range of plausible error budgets. Local error levels, error variance-covariance matrices, SL trends and accelerations, along with corresponding uncertainties are provided. |
format | Online Article Text |
id | pubmed-7791125 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-77911252021-01-15 Local sea level trends, accelerations and uncertainties over 1993–2019 Prandi, Pierre Meyssignac, Benoit Ablain, Michaël Spada, Giorgio Ribes, Aurélien Benveniste, Jérôme Sci Data Data Descriptor Satellite altimetry missions provide a quasi-global synoptic view of sea level variations over more than 25 years and provide regional sea level (SL) indicators such as trends and accelerations. Estimating realistic uncertainties on these quantities is crucial to address current climate science questions. While uncertainty estimates are available for the global mean sea level (GMSL), information is not available at local scales so far. We estimate a local satellite altimetry error budget and use it to derive local error variance-covariance matrices, and estimate confidence intervals on trends and accelerations at the 90% confidence level. Over 1993–2019, we find that the average local sea level trend uncertainty is 0.83 mm.yr(−1) with values ranging from 0.78 to 1.22 mm.yr(−1). For accelerations, uncertainties range from 0.057 to 0.12 mm.yr(−1), with a mean value of 0.062. We also perform a sensitivity study to investigate a range of plausible error budgets. Local error levels, error variance-covariance matrices, SL trends and accelerations, along with corresponding uncertainties are provided. Nature Publishing Group UK 2021-01-07 /pmc/articles/PMC7791125/ /pubmed/33414438 http://dx.doi.org/10.1038/s41597-020-00786-7 Text en © The Author(s) 2021 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/. The Creative Commons Public Domain Dedication waiver http://creativecommons.org/publicdomain/zero/1.0/ applies to the metadata files associated with this article. |
spellingShingle | Data Descriptor Prandi, Pierre Meyssignac, Benoit Ablain, Michaël Spada, Giorgio Ribes, Aurélien Benveniste, Jérôme Local sea level trends, accelerations and uncertainties over 1993–2019 |
title | Local sea level trends, accelerations and uncertainties over 1993–2019 |
title_full | Local sea level trends, accelerations and uncertainties over 1993–2019 |
title_fullStr | Local sea level trends, accelerations and uncertainties over 1993–2019 |
title_full_unstemmed | Local sea level trends, accelerations and uncertainties over 1993–2019 |
title_short | Local sea level trends, accelerations and uncertainties over 1993–2019 |
title_sort | local sea level trends, accelerations and uncertainties over 1993–2019 |
topic | Data Descriptor |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7791125/ https://www.ncbi.nlm.nih.gov/pubmed/33414438 http://dx.doi.org/10.1038/s41597-020-00786-7 |
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