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Gauging mixed climate extreme value distributions in tropical cyclone regions
In tropical cyclone (TC) regions, tide gauge or numerical hindcast records are usually of insufficient length to have sampled sufficient cyclones to enable robust estimates of the climate of TC-induced extreme water level events. Synthetically-generated TC populations provide a means to define a bro...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8931004/ https://www.ncbi.nlm.nih.gov/pubmed/35301336 http://dx.doi.org/10.1038/s41598-022-08382-y |
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author | O’Grady, J. G. Stephenson, A. G. McInnes, K. L. |
author_facet | O’Grady, J. G. Stephenson, A. G. McInnes, K. L. |
author_sort | O’Grady, J. G. |
collection | PubMed |
description | In tropical cyclone (TC) regions, tide gauge or numerical hindcast records are usually of insufficient length to have sampled sufficient cyclones to enable robust estimates of the climate of TC-induced extreme water level events. Synthetically-generated TC populations provide a means to define a broader set of plausible TC events to better define the probabilities associated with extreme water level events. The challenge is to unify the estimates of extremes from synthetically-generated TC populations with the observed records, which include mainly non-TC extremes resulting from tides and more frequently occurring atmospheric-depression weather and climate events. We find that extreme water level measurements in multiple tide gauge records in TC regions, some which span more than 100 years, exhibit a behaviour consistent with the combining of two populations, TC and non-TC. We develop an equation to model the combination of two populations of extremes in a single continuous mixed climate (MC) extreme value distribution (EVD). We then run statistical simulations to show that long term records including both historical and synthetic events can be better explained using MC than heavy-tailed generalised EVDs. This has implications for estimating extreme water levels when combining synthetic cyclone extreme sea levels with hindcast water levels to provide actionable information for coastal protection. |
format | Online Article Text |
id | pubmed-8931004 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-89310042022-03-21 Gauging mixed climate extreme value distributions in tropical cyclone regions O’Grady, J. G. Stephenson, A. G. McInnes, K. L. Sci Rep Article In tropical cyclone (TC) regions, tide gauge or numerical hindcast records are usually of insufficient length to have sampled sufficient cyclones to enable robust estimates of the climate of TC-induced extreme water level events. Synthetically-generated TC populations provide a means to define a broader set of plausible TC events to better define the probabilities associated with extreme water level events. The challenge is to unify the estimates of extremes from synthetically-generated TC populations with the observed records, which include mainly non-TC extremes resulting from tides and more frequently occurring atmospheric-depression weather and climate events. We find that extreme water level measurements in multiple tide gauge records in TC regions, some which span more than 100 years, exhibit a behaviour consistent with the combining of two populations, TC and non-TC. We develop an equation to model the combination of two populations of extremes in a single continuous mixed climate (MC) extreme value distribution (EVD). We then run statistical simulations to show that long term records including both historical and synthetic events can be better explained using MC than heavy-tailed generalised EVDs. This has implications for estimating extreme water levels when combining synthetic cyclone extreme sea levels with hindcast water levels to provide actionable information for coastal protection. Nature Publishing Group UK 2022-03-17 /pmc/articles/PMC8931004/ /pubmed/35301336 http://dx.doi.org/10.1038/s41598-022-08382-y Text en © Crown 2022 https://creativecommons.org/licenses/by/4.0/ Open AccessThis 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 licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence 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 licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Article O’Grady, J. G. Stephenson, A. G. McInnes, K. L. Gauging mixed climate extreme value distributions in tropical cyclone regions |
title | Gauging mixed climate extreme value distributions in tropical cyclone regions |
title_full | Gauging mixed climate extreme value distributions in tropical cyclone regions |
title_fullStr | Gauging mixed climate extreme value distributions in tropical cyclone regions |
title_full_unstemmed | Gauging mixed climate extreme value distributions in tropical cyclone regions |
title_short | Gauging mixed climate extreme value distributions in tropical cyclone regions |
title_sort | gauging mixed climate extreme value distributions in tropical cyclone regions |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8931004/ https://www.ncbi.nlm.nih.gov/pubmed/35301336 http://dx.doi.org/10.1038/s41598-022-08382-y |
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