A globally consistent local-scale assessment of future tropical cyclone risk
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 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.
Bloemendaal, Nadia
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de Moel, Hans
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Martinez, Andrew B.
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Muis, Sanne
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Haigh, Ivan
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van der Wiel, Karin
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Haarsma, Reindert J.
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Ward, Philip J.
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Roberts, Malcolm J.
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Dullaart, Job C.M.
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Aerts, Jeroen C.J.H.
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Bloemendaal, Nadia
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de Moel, Hans
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Martinez, Andrew B.
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Muis, Sanne
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Haigh, Ivan
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van der Wiel, Karin
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Haarsma, Reindert J.
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Ward, Philip J.
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Roberts, Malcolm J.
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Dullaart, Job C.M.
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Aerts, Jeroen C.J.H.
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Bloemendaal, Nadia, de Moel, Hans, Martinez, Andrew B., Muis, Sanne, Haigh, Ivan, van der Wiel, Karin, Haarsma, Reindert J., Ward, Philip J., Roberts, Malcolm J., Dullaart, Job C.M. and Aerts, Jeroen C.J.H.
(2022)
A globally consistent local-scale assessment of future tropical cyclone risk.
Science Advances, 8 (17).
(doi:10.1126/sciadv.abm8438).
Abstract
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.
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sciadv.abm8438
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Accepted/In Press date: 9 March 2022
e-pub ahead of print date: 27 April 2022
Identifiers
Local EPrints ID: 490381
URI: http://eprints.soton.ac.uk/id/eprint/490381
ISSN: 2375-2548
PURE UUID: 6b0bfd30-9233-4d25-97ac-80fb8e39f3d8
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Date deposited: 24 May 2024 16:37
Last modified: 25 May 2024 01:41
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Contributors
Author:
Nadia Bloemendaal
Author:
Hans de Moel
Author:
Andrew B. Martinez
Author:
Sanne Muis
Author:
Karin van der Wiel
Author:
Reindert J. Haarsma
Author:
Philip J. Ward
Author:
Malcolm J. Roberts
Author:
Job C.M. Dullaart
Author:
Jeroen C.J.H. Aerts
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