Rights statement: This is the author’s version of a work that was accepted for publication in Ocean Engineering. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Ocean Engineering, 238, 2021 DOI: 10.1016/j.oceaneng.2021.109642
Accepted author manuscript, 1.81 MB, PDF document
Available under license: CC BY-NC-ND
Final published version
Research output: Contribution to Journal/Magazine › Journal article › peer-review
Research output: Contribution to Journal/Magazine › Journal article › peer-review
}
TY - JOUR
T1 - Efficient estimation of distributional properties of extreme seas from a hierarchical description applied to calculation of un-manning and other weather-related operational windows
AU - Towe, R.
AU - Zanini, E.
AU - Randell, D.
AU - Feld, G.
AU - Jonathan, P.
N1 - This is the author’s version of a work that was accepted for publication in Ocean Engineering. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Ocean Engineering, 238, 2021 DOI: 10.1016/j.oceaneng.2021.109642
PY - 2021/10/15
Y1 - 2021/10/15
N2 - Methods of computational statistics allow efficient estimation of extreme ocean environments, and facilitate optimal operational decision making. We describe estimation of extreme quantiles of total water level and related quantities from a non-stationary hierarchical model for ocean storms. The model incorporates a directional–seasonal extreme value model for occurrences of storm peak significant wave height, a conditional directional model for within-storm evolution of sea states relative to storm peak, a conditional model for the maximum crest within a sea state, and models for total water level. Importance sampling is used for efficient computation of marginal total water level characteristics. We use the model to estimate an optimal un-manning procedure for a notional North Sea offshore structure in severe conditions.
AB - Methods of computational statistics allow efficient estimation of extreme ocean environments, and facilitate optimal operational decision making. We describe estimation of extreme quantiles of total water level and related quantities from a non-stationary hierarchical model for ocean storms. The model incorporates a directional–seasonal extreme value model for occurrences of storm peak significant wave height, a conditional directional model for within-storm evolution of sea states relative to storm peak, a conditional model for the maximum crest within a sea state, and models for total water level. Importance sampling is used for efficient computation of marginal total water level characteristics. We use the model to estimate an optimal un-manning procedure for a notional North Sea offshore structure in severe conditions.
KW - Covariate
KW - Extreme
KW - Hierarchical statistical model
KW - Importance sampling
KW - Return value
KW - Un-manning
KW - Weather window
KW - Computational efficiency
KW - Decision making
KW - Hierarchical systems
KW - Ocean currents
KW - Offshore oil well production
KW - Offshore structures
KW - Water levels
KW - Covariates
KW - Distributional property
KW - Efficient estimation
KW - Hierarchical description
KW - Sea state
KW - Storms
U2 - 10.1016/j.oceaneng.2021.109642
DO - 10.1016/j.oceaneng.2021.109642
M3 - Journal article
VL - 238
JO - Ocean Engineering
JF - Ocean Engineering
SN - 0029-8018
M1 - 109642
ER -