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Estimating surge in extreme North Sea storms

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Estimating surge in extreme North Sea storms. / Ross, Emma; Sam, Samta; Randell, David et al.
In: Ocean Engineering, Vol. 154, 15.04.2018, p. 430-444.

Research output: Contribution to Journal/MagazineJournal articlepeer-review

Harvard

Ross, E, Sam, S, Randell, D, Feld, G & Jonathan, P 2018, 'Estimating surge in extreme North Sea storms', Ocean Engineering, vol. 154, pp. 430-444. https://doi.org/10.1016/j.oceaneng.2018.01.078

APA

Ross, E., Sam, S., Randell, D., Feld, G., & Jonathan, P. (2018). Estimating surge in extreme North Sea storms. Ocean Engineering, 154, 430-444. https://doi.org/10.1016/j.oceaneng.2018.01.078

Vancouver

Ross E, Sam S, Randell D, Feld G, Jonathan P. Estimating surge in extreme North Sea storms. Ocean Engineering. 2018 Apr 15;154:430-444. Epub 2018 Mar 20. doi: 10.1016/j.oceaneng.2018.01.078

Author

Ross, Emma ; Sam, Samta ; Randell, David et al. / Estimating surge in extreme North Sea storms. In: Ocean Engineering. 2018 ; Vol. 154. pp. 430-444.

Bibtex

@article{5f5ee5f88a3e42b9910dea356a2276f8,
title = "Estimating surge in extreme North Sea storms",
abstract = "Characterising storm surge in extreme sea states is important in offshore design. Here we estimate key surge design characteristics such as the maximum surge observed during a storm event of given extreme storm severity and covariates such as storm direction. Inferences are made using a simple non-stationary implementation of the conditional extremes model of Heffernan and Tawn (2004), comprising a set of coupled piecewise stationary marginal and dependence models defined on a partition of the covariate domain. The approach uses samples consisting of pairs of values for peaks over threshold of a conditioning variate, namely storm peak significant wave height, and the corresponding peaks over threshold of an associated value of a key surge characteristic. Each pair is allocated to a particular storm direction covariate interval, and all pairs within the same interval are assumed to exhibit common stationary marginal and conditional extreme value behaviour. Non-stationary marginal extreme value characteristics for each variate are estimated using maximum roughness-penalised generalised Pareto likelihood estimation over covariate intervals. Extremal dependence between variates on a transformed standard Gumbel scale is then estimated using maximum roughness-penalised likelihood estimation for a conditional extremes model, also piecewise stationary with respect to covariates. Sample and threshold uncertainties are quantified using a bootstrapping scheme. Marginal and conditional return value distributions, estimated using numerical integration, incorporate these uncertainties. From offshore radar-based measurements at locations in the northern, central and southern North Sea, we observe that characteristics of surge and significant wave height vary with wave direction at all locations. Surge is a larger contributor to extreme seas in the southern North Sea than in the northern North Sea in particular. There is evidence that extremal dependence between surge characteristics and significant wave height also varies with storm direction. Hence, the size of surge contribution to return values of total water level also varies with storm direction and location.",
keywords = "Conditional extremes, Non-stationary, Return value, Significant wave height, Surge",
author = "Emma Ross and Samta Sam and David Randell and Graham Feld and Philip Jonathan",
year = "2018",
month = apr,
day = "15",
doi = "10.1016/j.oceaneng.2018.01.078",
language = "English",
volume = "154",
pages = "430--444",
journal = "Ocean Engineering",
issn = "0029-8018",
publisher = "Elsevier Ltd",

}

RIS

TY - JOUR

T1 - Estimating surge in extreme North Sea storms

AU - Ross, Emma

AU - Sam, Samta

AU - Randell, David

AU - Feld, Graham

AU - Jonathan, Philip

PY - 2018/4/15

Y1 - 2018/4/15

N2 - Characterising storm surge in extreme sea states is important in offshore design. Here we estimate key surge design characteristics such as the maximum surge observed during a storm event of given extreme storm severity and covariates such as storm direction. Inferences are made using a simple non-stationary implementation of the conditional extremes model of Heffernan and Tawn (2004), comprising a set of coupled piecewise stationary marginal and dependence models defined on a partition of the covariate domain. The approach uses samples consisting of pairs of values for peaks over threshold of a conditioning variate, namely storm peak significant wave height, and the corresponding peaks over threshold of an associated value of a key surge characteristic. Each pair is allocated to a particular storm direction covariate interval, and all pairs within the same interval are assumed to exhibit common stationary marginal and conditional extreme value behaviour. Non-stationary marginal extreme value characteristics for each variate are estimated using maximum roughness-penalised generalised Pareto likelihood estimation over covariate intervals. Extremal dependence between variates on a transformed standard Gumbel scale is then estimated using maximum roughness-penalised likelihood estimation for a conditional extremes model, also piecewise stationary with respect to covariates. Sample and threshold uncertainties are quantified using a bootstrapping scheme. Marginal and conditional return value distributions, estimated using numerical integration, incorporate these uncertainties. From offshore radar-based measurements at locations in the northern, central and southern North Sea, we observe that characteristics of surge and significant wave height vary with wave direction at all locations. Surge is a larger contributor to extreme seas in the southern North Sea than in the northern North Sea in particular. There is evidence that extremal dependence between surge characteristics and significant wave height also varies with storm direction. Hence, the size of surge contribution to return values of total water level also varies with storm direction and location.

AB - Characterising storm surge in extreme sea states is important in offshore design. Here we estimate key surge design characteristics such as the maximum surge observed during a storm event of given extreme storm severity and covariates such as storm direction. Inferences are made using a simple non-stationary implementation of the conditional extremes model of Heffernan and Tawn (2004), comprising a set of coupled piecewise stationary marginal and dependence models defined on a partition of the covariate domain. The approach uses samples consisting of pairs of values for peaks over threshold of a conditioning variate, namely storm peak significant wave height, and the corresponding peaks over threshold of an associated value of a key surge characteristic. Each pair is allocated to a particular storm direction covariate interval, and all pairs within the same interval are assumed to exhibit common stationary marginal and conditional extreme value behaviour. Non-stationary marginal extreme value characteristics for each variate are estimated using maximum roughness-penalised generalised Pareto likelihood estimation over covariate intervals. Extremal dependence between variates on a transformed standard Gumbel scale is then estimated using maximum roughness-penalised likelihood estimation for a conditional extremes model, also piecewise stationary with respect to covariates. Sample and threshold uncertainties are quantified using a bootstrapping scheme. Marginal and conditional return value distributions, estimated using numerical integration, incorporate these uncertainties. From offshore radar-based measurements at locations in the northern, central and southern North Sea, we observe that characteristics of surge and significant wave height vary with wave direction at all locations. Surge is a larger contributor to extreme seas in the southern North Sea than in the northern North Sea in particular. There is evidence that extremal dependence between surge characteristics and significant wave height also varies with storm direction. Hence, the size of surge contribution to return values of total water level also varies with storm direction and location.

KW - Conditional extremes

KW - Non-stationary

KW - Return value

KW - Significant wave height

KW - Surge

U2 - 10.1016/j.oceaneng.2018.01.078

DO - 10.1016/j.oceaneng.2018.01.078

M3 - Journal article

AN - SCOPUS:85042665390

VL - 154

SP - 430

EP - 444

JO - Ocean Engineering

JF - Ocean Engineering

SN - 0029-8018

ER -