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A globally consistent local-scale assessment of future tropical cyclone risk
There is considerable uncertainty surrounding future changes in tropical cyclone (TC) frequency and intensity, particularly at local scales. This uncertainty complicates risk assessments and implementation of risk mitigation strategies. We present a novel approach to overcome this problem, using the...
Autores principales: | , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
American Association for the Advancement of Science
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9045717/ https://www.ncbi.nlm.nih.gov/pubmed/35476436 http://dx.doi.org/10.1126/sciadv.abm8438 |
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author | Bloemendaal, Nadia de Moel, Hans Martinez, Andrew B. Muis, Sanne Haigh, Ivan D. van der Wiel, Karin Haarsma, Reindert J. Ward, Philip J. Roberts, Malcolm J. Dullaart, Job C. M. Aerts, Jeroen C. J. H. |
author_facet | Bloemendaal, Nadia de Moel, Hans Martinez, Andrew B. Muis, Sanne Haigh, Ivan D. van der Wiel, Karin Haarsma, Reindert J. Ward, Philip J. Roberts, Malcolm J. Dullaart, Job C. M. Aerts, Jeroen C. J. H. |
author_sort | Bloemendaal, Nadia |
collection | PubMed |
description | There is considerable uncertainty surrounding future changes in tropical cyclone (TC) frequency and intensity, particularly at local scales. This uncertainty complicates risk assessments and implementation of risk mitigation strategies. We present a novel approach to overcome this problem, using the statistical model STORM to generate 10,000 years of synthetic TCs under past (1980–2017) and future climate (SSP585; 2015–2050) conditions from an ensemble of four high-resolution climate models. We then derive high-resolution (10-km) wind speed return period maps up to 1000 years to assess local-scale changes in wind speed probabilities. Our results indicate that the probability of intense TCs, on average, more than doubles in all regions except for the Bay of Bengal and the Gulf of Mexico. Our unique and innovative methodology enables globally consistent comparison of TC risk in both time and space and can be easily adapted to accommodate alternative climate scenarios and time periods. |
format | Online Article Text |
id | pubmed-9045717 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | American Association for the Advancement of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-90457172022-05-04 A globally consistent local-scale assessment of future tropical cyclone risk Bloemendaal, Nadia de Moel, Hans Martinez, Andrew B. Muis, Sanne Haigh, Ivan D. van der Wiel, Karin Haarsma, Reindert J. Ward, Philip J. Roberts, Malcolm J. Dullaart, Job C. M. Aerts, Jeroen C. J. H. Sci Adv Earth, Environmental, Ecological, and Space Sciences There is considerable uncertainty surrounding future changes in tropical cyclone (TC) frequency and intensity, particularly at local scales. This uncertainty complicates risk assessments and implementation of risk mitigation strategies. We present a novel approach to overcome this problem, using the statistical model STORM to generate 10,000 years of synthetic TCs under past (1980–2017) and future climate (SSP585; 2015–2050) conditions from an ensemble of four high-resolution climate models. We then derive high-resolution (10-km) wind speed return period maps up to 1000 years to assess local-scale changes in wind speed probabilities. Our results indicate that the probability of intense TCs, on average, more than doubles in all regions except for the Bay of Bengal and the Gulf of Mexico. Our unique and innovative methodology enables globally consistent comparison of TC risk in both time and space and can be easily adapted to accommodate alternative climate scenarios and time periods. American Association for the Advancement of Science 2022-04-27 /pmc/articles/PMC9045717/ /pubmed/35476436 http://dx.doi.org/10.1126/sciadv.abm8438 Text en Copyright © 2022 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works. Distributed under a Creative Commons Attribution License 4.0 (CC BY). https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution license (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Earth, Environmental, Ecological, and Space Sciences Bloemendaal, Nadia de Moel, Hans Martinez, Andrew B. Muis, Sanne Haigh, Ivan D. van der Wiel, Karin Haarsma, Reindert J. Ward, Philip J. Roberts, Malcolm J. Dullaart, Job C. M. Aerts, Jeroen C. J. H. A globally consistent local-scale assessment of future tropical cyclone risk |
title | A globally consistent local-scale assessment of future tropical cyclone risk |
title_full | A globally consistent local-scale assessment of future tropical cyclone risk |
title_fullStr | A globally consistent local-scale assessment of future tropical cyclone risk |
title_full_unstemmed | A globally consistent local-scale assessment of future tropical cyclone risk |
title_short | A globally consistent local-scale assessment of future tropical cyclone risk |
title_sort | globally consistent local-scale assessment of future tropical cyclone risk |
topic | Earth, Environmental, Ecological, and Space Sciences |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9045717/ https://www.ncbi.nlm.nih.gov/pubmed/35476436 http://dx.doi.org/10.1126/sciadv.abm8438 |
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