Stochastic simulation of storm surge extremes along the contiguous United States coastlines using the max-stable process

Abstract Extreme sea levels impact coastal society, property, and the environment. Various mitigation measures are engineered to reduce these impacts, which require extreme event probabilities typically estimated site-by-site. The site-by-site estimates usually have high uncertainty, are conditional...
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Autor*in:	Md Mamunur Rashid [verfasserIn] Hamed Moftakhari [verfasserIn] Hamid Moradkhani [verfasserIn]

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2024

Übergeordnetes Werk:	In: Communications Earth & Environment - Nature Portfolio, 2021, 5(2024), 1, Seite 10
Übergeordnetes Werk:	volume:5 ; year:2024 ; number:1 ; pages:10

Links:	Link aufrufen Link aufrufen Link aufrufen Journal toc

DOI / URN:	10.1038/s43247-024-01206-z

Katalog-ID:	DOAJ097415618

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520			\|a Abstract Extreme sea levels impact coastal society, property, and the environment. Various mitigation measures are engineered to reduce these impacts, which require extreme event probabilities typically estimated site-by-site. The site-by-site estimates usually have high uncertainty, are conditionally independent, and do not provide estimates for ungauged locations. In contrast, the max-stable process explicitly incorporates the spatial dependence structure and produces more realistic event probabilities and spatial surfaces. We leverage the max-stable process to compute extreme event probabilities at gridded locations (gauged and ungauged) and derive their spatial surfaces along the contiguous United States coastlines by pooling annual maximum (AM) surges from selected long-record tide gauges. We also generate synthetic AM surges at the grid locations using the predicted distribution parameters and reordering them in the rank space to integrate the spatiotemporal variability. The results will support coastal planners, engineers, and stakeholders to make the most precise and confident decisions for coastal flood risk reduction.
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spelling	10.1038/s43247-024-01206-z doi (DE-627)DOAJ097415618 (DE-599)DOAJ4ba8303e4bd34aa7a379d1f07a8ca05b DE-627 ger DE-627 rakwb eng QE1-996.5 GE1-350 Md Mamunur Rashid verfasserin aut Stochastic simulation of storm surge extremes along the contiguous United States coastlines using the max-stable process 2024 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract Extreme sea levels impact coastal society, property, and the environment. Various mitigation measures are engineered to reduce these impacts, which require extreme event probabilities typically estimated site-by-site. The site-by-site estimates usually have high uncertainty, are conditionally independent, and do not provide estimates for ungauged locations. In contrast, the max-stable process explicitly incorporates the spatial dependence structure and produces more realistic event probabilities and spatial surfaces. We leverage the max-stable process to compute extreme event probabilities at gridded locations (gauged and ungauged) and derive their spatial surfaces along the contiguous United States coastlines by pooling annual maximum (AM) surges from selected long-record tide gauges. We also generate synthetic AM surges at the grid locations using the predicted distribution parameters and reordering them in the rank space to integrate the spatiotemporal variability. The results will support coastal planners, engineers, and stakeholders to make the most precise and confident decisions for coastal flood risk reduction. Geology Environmental sciences Hamed Moftakhari verfasserin aut Hamid Moradkhani verfasserin aut In Communications Earth & Environment Nature Portfolio, 2021 5(2024), 1, Seite 10 (DE-627)1730525067 26624435 nnns volume:5 year:2024 number:1 pages:10 https://doi.org/10.1038/s43247-024-01206-z kostenfrei https://doaj.org/article/4ba8303e4bd34aa7a379d1f07a8ca05b kostenfrei https://doi.org/10.1038/s43247-024-01206-z kostenfrei https://doaj.org/toc/2662-4435 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_2057 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 5 2024 1 10
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allfieldsSound	10.1038/s43247-024-01206-z doi (DE-627)DOAJ097415618 (DE-599)DOAJ4ba8303e4bd34aa7a379d1f07a8ca05b DE-627 ger DE-627 rakwb eng QE1-996.5 GE1-350 Md Mamunur Rashid verfasserin aut Stochastic simulation of storm surge extremes along the contiguous United States coastlines using the max-stable process 2024 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract Extreme sea levels impact coastal society, property, and the environment. Various mitigation measures are engineered to reduce these impacts, which require extreme event probabilities typically estimated site-by-site. The site-by-site estimates usually have high uncertainty, are conditionally independent, and do not provide estimates for ungauged locations. In contrast, the max-stable process explicitly incorporates the spatial dependence structure and produces more realistic event probabilities and spatial surfaces. We leverage the max-stable process to compute extreme event probabilities at gridded locations (gauged and ungauged) and derive their spatial surfaces along the contiguous United States coastlines by pooling annual maximum (AM) surges from selected long-record tide gauges. We also generate synthetic AM surges at the grid locations using the predicted distribution parameters and reordering them in the rank space to integrate the spatiotemporal variability. The results will support coastal planners, engineers, and stakeholders to make the most precise and confident decisions for coastal flood risk reduction. Geology Environmental sciences Hamed Moftakhari verfasserin aut Hamid Moradkhani verfasserin aut In Communications Earth & Environment Nature Portfolio, 2021 5(2024), 1, Seite 10 (DE-627)1730525067 26624435 nnns volume:5 year:2024 number:1 pages:10 https://doi.org/10.1038/s43247-024-01206-z kostenfrei https://doaj.org/article/4ba8303e4bd34aa7a379d1f07a8ca05b kostenfrei https://doi.org/10.1038/s43247-024-01206-z kostenfrei https://doaj.org/toc/2662-4435 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_2057 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 5 2024 1 10
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topic_title	QE1-996.5 GE1-350 Stochastic simulation of storm surge extremes along the contiguous United States coastlines using the max-stable process
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title	Stochastic simulation of storm surge extremes along the contiguous United States coastlines using the max-stable process
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title_sort	stochastic simulation of storm surge extremes along the contiguous united states coastlines using the max-stable process
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title_auth	Stochastic simulation of storm surge extremes along the contiguous United States coastlines using the max-stable process
abstract	Abstract Extreme sea levels impact coastal society, property, and the environment. Various mitigation measures are engineered to reduce these impacts, which require extreme event probabilities typically estimated site-by-site. The site-by-site estimates usually have high uncertainty, are conditionally independent, and do not provide estimates for ungauged locations. In contrast, the max-stable process explicitly incorporates the spatial dependence structure and produces more realistic event probabilities and spatial surfaces. We leverage the max-stable process to compute extreme event probabilities at gridded locations (gauged and ungauged) and derive their spatial surfaces along the contiguous United States coastlines by pooling annual maximum (AM) surges from selected long-record tide gauges. We also generate synthetic AM surges at the grid locations using the predicted distribution parameters and reordering them in the rank space to integrate the spatiotemporal variability. The results will support coastal planners, engineers, and stakeholders to make the most precise and confident decisions for coastal flood risk reduction.
abstractGer	Abstract Extreme sea levels impact coastal society, property, and the environment. Various mitigation measures are engineered to reduce these impacts, which require extreme event probabilities typically estimated site-by-site. The site-by-site estimates usually have high uncertainty, are conditionally independent, and do not provide estimates for ungauged locations. In contrast, the max-stable process explicitly incorporates the spatial dependence structure and produces more realistic event probabilities and spatial surfaces. We leverage the max-stable process to compute extreme event probabilities at gridded locations (gauged and ungauged) and derive their spatial surfaces along the contiguous United States coastlines by pooling annual maximum (AM) surges from selected long-record tide gauges. We also generate synthetic AM surges at the grid locations using the predicted distribution parameters and reordering them in the rank space to integrate the spatiotemporal variability. The results will support coastal planners, engineers, and stakeholders to make the most precise and confident decisions for coastal flood risk reduction.
abstract_unstemmed	Abstract Extreme sea levels impact coastal society, property, and the environment. Various mitigation measures are engineered to reduce these impacts, which require extreme event probabilities typically estimated site-by-site. The site-by-site estimates usually have high uncertainty, are conditionally independent, and do not provide estimates for ungauged locations. In contrast, the max-stable process explicitly incorporates the spatial dependence structure and produces more realistic event probabilities and spatial surfaces. We leverage the max-stable process to compute extreme event probabilities at gridded locations (gauged and ungauged) and derive their spatial surfaces along the contiguous United States coastlines by pooling annual maximum (AM) surges from selected long-record tide gauges. We also generate synthetic AM surges at the grid locations using the predicted distribution parameters and reordering them in the rank space to integrate the spatiotemporal variability. The results will support coastal planners, engineers, and stakeholders to make the most precise and confident decisions for coastal flood risk reduction.
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title_short	Stochastic simulation of storm surge extremes along the contiguous United States coastlines using the max-stable process
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Stochastic simulation of storm surge extremes along the contiguous United States coastlines using the max-stable process

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