Efficient estimation of distributional properties of extreme seas from a hierarchical description applied to calculation of un-manning and other weather-related operational windows

OCEAN ENGINEERING

卷:238

Article

Towe, Ross¹  Zanini, Elena¹  Randell, David²  Feld, Graham³  Jonathan, Philip^1,4 

[1] Shell Res Ltd, London SE1 7NA, England

[2] Shell Global Solut Int BV, NL-1031 HW Amsterdam, Netherlands

[3] Shell UK Ltd, Aberdeen AB12 3FY, Scotland

[4] Univ Lancaster, Dept Math & Stat, Lancaster LA1 4YF, England

关键词: Hierarchical statistical model;    Extreme;    Retur n value;    Covariate;    Importance sampling;    Weather window;    Un-manning;   

DOI  :  10.1016/j.oceaneng.2021.109642

来源: Elsevier

【 摘 要 】

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-stationa r y 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 structu r e in severe conditions.

【 授权许可】

Free