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Unified distribution models for met-ocean variables: Application to series of significant wave height

机译：海洋变量的统一分布模型：在一系列重要波高中的应用

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摘要

The design of maritime works requires statistical models for several met-ocean variables, such as significant wave height H_s that adequately represent the probability of occurrence and the uncertainty for the entire range of values of the variables. In general, the mean climate of H_s is modeled empirically or by log-normal or two-parameter Weibull distributions using all available data. Extremal climate studies are conducted separately, usually by means of the peaks-over-threshold (POT) method. The methods used to define the threshold tend to be subjective and generally do not allow for calculation of the associated uncertainty. This paper proposes to use a mixture model for the marginal distribution of H_s that includes thresholds between the central regime and minimum and maximum regimes as parameters of the model. The parameters of the model are estimated by maximum likelihood, for which specific recommendations are given. The distribution is able to parametrically model the mean climate of the variable. For calculating extreme values, a simple methodology is described that accounts for the uncertainty stemming from the estimation of the threshold.The implementation of this model using two H_s series shows that it provides a better fit for the data than that obtained with parametric distributions such as log-normal or Weibull. Furthermore, this model automatically and objectively determines the threshold necessary to apply the POT method and the uncertainty associated with the threshold. It was observed that the proposed method for the estimation of the threshold is less sensitive to the presence of a potential outliers than other analyzed methods.
机译：海上工程的设计需要几个海洋变量的统计模型，例如足够代表变量值整个范围的发生概率和不确定性的有效波高H_s。通常，H_s的平均气候是根据经验或使用所有可用数据通过对数正态或两参数威布尔分布建模的。极端气候研究是分开进行的，通常是通过阈值以上的峰值（POT）方法进行的。用于定义阈值的方法往往是主观的，通常不允许计算相关的不确定性。本文建议使用混合模型来计算H_s的边际分布，其中包括中心状态与最小和最大状态之间的阈值作为模型的参数。通过最大似然估计模型的参数，并给出具体建议。该分布能够对变量的平均气候进行参数化建模。为了计算极值，描述了一种简单的方法，该方法解决了因阈值估计而产生的不确定性。使用两个H_s序列对该模型的实施表明，与通过参数分布（例如）获得的数据相比，该模型更适合数据对数正态或Weibull。此外，该模型自动，客观地确定应用POT方法所需的阈值以及与该阈值相关的不确定性。可以观察到，与其他分析方法相比，所提出的阈值估计方法对潜在异常值的敏感性较低。

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  • 来源
    《Coastal engineering》 |2012年第2012期|p.67-77|共11页
  • 作者

    Sebastian Solari; Miguel Angel Losada;

  • 作者单位

    Universidad de Granada, Grupo de Dinamica de Flujos Ambientales, Av. del Mediterraneo s Edificio CEAMA, 18006 Granada, Spain,Universidad de Granada, Crupo de DinSmica de Flujos Ambientales, Av. del Mediterraneo s Edificio CEAMA, 18006 Granada, Spain;

    Universidad de Granada, Grupo de Dinamica de Flujos Ambientales, Av. del Mediterraneo s Edificio CEAMA, 18006 Granada, Spain;

  • 收录信息 美国《科学引文索引》(SCI);美国《工程索引》(EI);
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    wave statistics; threshold selection; generalized pareto distribution; extremes;

    机译：波浪统计阈值选择;广义pareto分布极端;

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