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Uncertainty quantification in estimation of extreme environments

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Uncertainty quantification in estimation of extreme environments. / Jones, Matthew; Hansen, Hans Fabricius; Zeeberg, Allan Rod et al.
In: Coastal Engineering, Vol. 141, 11.2018, p. 36-51.

Research output: Contribution to Journal/MagazineJournal articlepeer-review

Harvard

Jones, M, Hansen, HF, Zeeberg, AR, Randell, D & Jonathan, P 2018, 'Uncertainty quantification in estimation of extreme environments', Coastal Engineering, vol. 141, pp. 36-51. https://doi.org/10.1016/j.coastaleng.2018.07.002

APA

Jones, M., Hansen, H. F., Zeeberg, A. R., Randell, D., & Jonathan, P. (2018). Uncertainty quantification in estimation of extreme environments. Coastal Engineering, 141, 36-51. https://doi.org/10.1016/j.coastaleng.2018.07.002

Vancouver

Jones M, Hansen HF, Zeeberg AR, Randell D, Jonathan P. Uncertainty quantification in estimation of extreme environments. Coastal Engineering. 2018 Nov;141:36-51. Epub 2018 Jul 12. doi: 10.1016/j.coastaleng.2018.07.002

Author

Jones, Matthew ; Hansen, Hans Fabricius ; Zeeberg, Allan Rod et al. / Uncertainty quantification in estimation of extreme environments. In: Coastal Engineering. 2018 ; Vol. 141. pp. 36-51.

Bibtex

@article{5dd154ea05b840ff898945b9ce2e7f55,
title = "Uncertainty quantification in estimation of extreme environments",
abstract = "We estimate uncertainties in ocean engineering design values due to imperfect knowledge of the ocean environment from physical models and observations, using Bayesian uncertainty analysis. Statistical emulators provide computationally efficient approximations to physical wind–wave environment (i.e. “hindcast”) simulators and characterise simulator uncertainty. Discrepancy models describe differences between hindcast simulator outputs and the true wave environment, where the only measurements available are subject to measurement error. System models (consisting of emulator–discrepancy model combinations) are used to estimate storm peak significant wave height (henceforth HS), spectral peak period and storm length jointly in the Danish sector of the North Sea. Using non-stationary extreme value analysis of system output HS, we estimate its 100-year maximum distribution from two different system models, the first based on 37 years of wind–wave simulation, the second on 1200 years; estimates of distributions of 100-year maxima are found to be in good general agreement, but the influence of different sources of uncertainty is nevertheless clear. We also estimate the distribution of 100-year maximum HS using non-stationary extreme value analysis of storm peak wind speed, propagating simulated extreme winds through a system model for HS; we find estimates to be in reasonable agreement with those based on extreme value analysis of HS itself.",
keywords = "Bayesian uncertainty analysis, Emulation, Discrepancy, Extreme, Significant wave height, Non-stationary",
author = "Matthew Jones and Hansen, {Hans Fabricius} and Zeeberg, {Allan Rod} and David Randell and Philip Jonathan",
year = "2018",
month = nov,
doi = "10.1016/j.coastaleng.2018.07.002",
language = "English",
volume = "141",
pages = "36--51",
journal = "Coastal Engineering",
issn = "0378-3839",
publisher = "Elsevier",

}

RIS

TY - JOUR

T1 - Uncertainty quantification in estimation of extreme environments

AU - Jones, Matthew

AU - Hansen, Hans Fabricius

AU - Zeeberg, Allan Rod

AU - Randell, David

AU - Jonathan, Philip

PY - 2018/11

Y1 - 2018/11

N2 - We estimate uncertainties in ocean engineering design values due to imperfect knowledge of the ocean environment from physical models and observations, using Bayesian uncertainty analysis. Statistical emulators provide computationally efficient approximations to physical wind–wave environment (i.e. “hindcast”) simulators and characterise simulator uncertainty. Discrepancy models describe differences between hindcast simulator outputs and the true wave environment, where the only measurements available are subject to measurement error. System models (consisting of emulator–discrepancy model combinations) are used to estimate storm peak significant wave height (henceforth HS), spectral peak period and storm length jointly in the Danish sector of the North Sea. Using non-stationary extreme value analysis of system output HS, we estimate its 100-year maximum distribution from two different system models, the first based on 37 years of wind–wave simulation, the second on 1200 years; estimates of distributions of 100-year maxima are found to be in good general agreement, but the influence of different sources of uncertainty is nevertheless clear. We also estimate the distribution of 100-year maximum HS using non-stationary extreme value analysis of storm peak wind speed, propagating simulated extreme winds through a system model for HS; we find estimates to be in reasonable agreement with those based on extreme value analysis of HS itself.

AB - We estimate uncertainties in ocean engineering design values due to imperfect knowledge of the ocean environment from physical models and observations, using Bayesian uncertainty analysis. Statistical emulators provide computationally efficient approximations to physical wind–wave environment (i.e. “hindcast”) simulators and characterise simulator uncertainty. Discrepancy models describe differences between hindcast simulator outputs and the true wave environment, where the only measurements available are subject to measurement error. System models (consisting of emulator–discrepancy model combinations) are used to estimate storm peak significant wave height (henceforth HS), spectral peak period and storm length jointly in the Danish sector of the North Sea. Using non-stationary extreme value analysis of system output HS, we estimate its 100-year maximum distribution from two different system models, the first based on 37 years of wind–wave simulation, the second on 1200 years; estimates of distributions of 100-year maxima are found to be in good general agreement, but the influence of different sources of uncertainty is nevertheless clear. We also estimate the distribution of 100-year maximum HS using non-stationary extreme value analysis of storm peak wind speed, propagating simulated extreme winds through a system model for HS; we find estimates to be in reasonable agreement with those based on extreme value analysis of HS itself.

KW - Bayesian uncertainty analysis

KW - Emulation

KW - Discrepancy

KW - Extreme

KW - Significant wave height

KW - Non-stationary

U2 - 10.1016/j.coastaleng.2018.07.002

DO - 10.1016/j.coastaleng.2018.07.002

M3 - Journal article

VL - 141

SP - 36

EP - 51

JO - Coastal Engineering

JF - Coastal Engineering

SN - 0378-3839

ER -