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1.
Determination of extreme wave heights using a Peaks-Over-Threshold (POT) approach is revisited. Firstly, the GPD-Poisson model is recalled. A double threshold is presented and justified, with objective tools for determining the high threshold. This model is then extended to other statistical distributions, namely the Weibull and Gamma distributions. Objective criteria (BIC and AIC) based upon likelihood are used to select the best-fitting distribution. This method is tested on two locations: the historical IAHR Haltenbanken dataset and a location at the entry of the Strait of Gibraltar. Finally, sensitivity analyses are carried out with respect to the high threshold and to the duration of the dataset to estimate the robustness of the approach presented. 相似文献
2.
This paper proposes a new methodology to select an optimal threshold level to be used in the peak over threshold (POT) method for the prediction of short-term distributions of load extremes of offshore wind turbines. Such an optimal threshold level is found based on the estimation of the variance-to-mean ratio for the occurrence of peak values, which characterizes the Poisson assumption. A generalized Pareto distribution is then fitted to the extracted peaks over the optimal threshold level and the distribution parameters are estimated by the method of the maximum spacing estimation. This methodology is applied to estimate the short-term distributions of load extremes of the blade bending moment and the tower base bending moment at the mudline of a monopile-supported 5MW offshore wind turbine as an example. The accuracy of the POT method using the optimal threshold level is shown to be better, in terms of the distribution fitting, than that of the POT methods using empirical threshold levels. The comparisons among the short-term extreme response values predicted by using the POT method with the optimal threshold levels and with the empirical threshold levels and by using direct simulation results further substantiate the validity of the proposed new methodology. 相似文献
3.
A new hybrid method for the time-domain nonlinear simulation of the hydroelastic load effects and the peak-over-threshold (POT) method for the calculation of the short-term extreme responses are briefly described and applied to a flexible containership of the latest design. Statistical analysis has been carried out to study the sensitivity of the predicted extreme vertical bending moments and vertical shear forces to the changes in the threshold of the POT method, as well as the statistical uncertainty in the prediction due to the limited duration of the nonlinear simulation. It is recommended that 90%–95% quantile should be used as the threshold in the POT method and more than 100 h of time-domain simulation should be carried out in order to obtain satisfactory predictions of the short-term extreme nonlinear load effects. 相似文献
4.
Fernando J. Mndez Melisa Menndez Alberto Luceo Raúl Medina Nicholas E. Graham 《Ocean Engineering》2008,35(1):131-138
This paper presents a statistical model to characterize the long-term extreme value distribution of significant wave height, conditioning to the duration of the storm and accounting for seasonality. A time-dependent version of the peak over threshold (POT) approach is used to build the model, which is then applied to specific reanalysis time series and NOAA buoy records. The model considers the annual and semiannual cycles which are parameterized in terms of harmonic functions. The inclusion of seasonal variabilities substantially reduces the residuals of the fitted model. The information obtained in this study can be useful to design maritime works, because (a) the model improves the understanding of the variability of extreme wave climate along a year and (b) the model accounts for the duration of the storm, which is a key parameter in several formulations for rubble mound breakwater design. 相似文献
5.
With noticing an increasing number of failure events for offshore structures in the present days, it is now realized that modeling the marine environment especially for exceptional environmental conditions is quite important. It is recognized that a possible improvement in the traditional modeling of environmental characteristics, which are the basis for the load models for structural analysis and design, may be needed. In this paper, the seasonal and directional varying properties in modeling the ocean parameter, the wave height, are studied. The peak over threshold (POT) method is selected to model the extreme wave height by utilizing a non-stationary discrete statistical extreme model. The varying parameters are taken into account with a changing pattern to reflect the seasonal and directional dependent behavior. Both the magnitude and the occurrence rate of the extreme values are investigated. Detailed discussion on the continuity of the established model is also given. The importance of the proposed model is demonstrated in reliability analysis for a jacket structure. The sensitivity to the changing marine environment in reliability analyses is investigated. 相似文献
6.
With noticing an increasing number of failure events for offshore structures in the present days, it is now realized that modeling the marine environment especially for exceptional environmental conditions is quite important. It is recognized that a possible improvement in the traditional modeling of environmental characteristics, which are the basis for the load models for structural analysis and design, may be needed. In this paper, the seasonal and directional varying properties in modeling the ocean parameter, the wave height, are studied. The peak over threshold (POT) method is selected to model the extreme wave height by utilizing a non-stationary discrete statistical extreme model. The varying parameters are taken into account with a changing pattern to reflect the seasonal and directional dependent behavior. Both the magnitude and the occurrence rate of the extreme values are investigated. Detailed discussion on the continuity of the established model is also given. The importance of the proposed model is demonstrated in reliability analysis for a jacket structure. The sensitivity to the changing marine environment in reliability analyses is investigated. 相似文献
7.
A new hybrid method for the time-domain nonlinear simulation of the hydroelastic load effects and the peak over threshold (POT) method for the calculation of the short-term extreme responses are briefly described and applied to a flexible SL-7 class containership and a flexible liquefied natural gas (LNG) ship. Three stiffness levels, three stiffness distributions and three modal damping ratios are used to study the influence of the hull flexibility and structural damping on the short-term prediction of extreme vertical hydroelastic load effects. The results give justification for some simplified treatment of the first vertical flexible mode in early design stage when structural details are not available. 相似文献
9.
Newly exposed concepts of POT declustering (Bernardara et al., 2014) within the GPD-Poisson model are applied to the joint probability of tide and surge for determining extreme sea levels, as a variation of the Revised Joint Probability Method (RJPM, Tawn and Vassie, 1989). A mixture model is proposed for the meteorological residual (surge) component with a non-parametric (empirical) density for the bulk values and parametric models for both the lower and upper tails. In particular, a distinction is made between values observed at regular time steps, called sequential values, and the clusters of extreme values, or events, on which the statistical extrapolations are performed. The sea level distribution is obtained by convolution of the tide and surge density functions. Confidence intervals are also proposed. This model is applied to the case study of Brest, France using both hourly and high water values. Two methods for handling tide–surge interaction are presented and discussed and a comparison with a direct approach is made. 相似文献
10.
基于阈值区间的海洋锋面提取模型 总被引：1，自引：0，他引：1
A model （Bayesian oceanic front detection, BOFD） of sea surface temperature （SST） front detection in satel- lite-derived SST images based on a threshold interval is presented, to be used in different applications such as climatic and environmental studies or fisheries. The model first computes the SST gradient by using a Sobel algorithm template. On the basis of the gradient value, the threshold interval is determined by a gradi- ent cumulative histogram. According to this threshold interval, front candidates can be acquired and prior probability and likelihood can be calculated. Whether or not the candidates are front points can be deter- mined by using the Bayesian decision theory. The model is evaluated on the Advanced Very High-Resolution Radiometer images of part of the Kuroshio front region. Results are compared with those obtained by using several SST front detection methods proposed in the literature. This comparison shows that the BOFD not only suppresses noise and small-scale fronts, but also retains continuous fronts. 相似文献
11.
In using the PGCEVD (Poisson-Gumbel Compound Extreme Value Distribution) model to calculate return values of typhoon wave height, the quantitative selection of the threshold has blocked its application. By analyzing the principle of the threshold selection of PGCEVD model and in combination of the change point statistical methods, this paper proposes a new method for quantitative calculation of the threshold in PGCEVD model. Eleven samples from five engineering points in several coastal waters of Guangdong and Hainan, China, are calculated and analyzed by using PGCEVD model and the traditional Pearson type III distribution (P-Ⅲ) model, respectively. By comparing the results of the two models, it is shown that the new method of selecting the optimal threshold is feasible. PGCEVD model has more stable results than that of P-Ⅲ model and can be used for the return wave height in every direction. 相似文献
12.
风暴增水随机分析的过阈法及其统计计算模式 总被引：6，自引：4，他引：2
以青岛大港观测站 32年增水过程为例 ,探讨风暴增水工程设计参数的频率分析法 ,进行了不同阈值序列及各种理论线型的分布拟合。首次提出 Poisson- Pearson- III型分布模式 ,并将其用于工程计算 :对比分析 POT法与年极值法的计算结果 ;给出青岛大港站风暴增水多年一遇设计值 ,为进一步科学地确定海岸防潮工程设计水位奠定了基础。 相似文献
13.
Linear autoregressive models and non-linear threshold autoregressive (TAR) models are used in the present work to describe the time series of the significant wave height of sea-states at Figueira da Foz, located in the Portuguese coast. The seasonal components of this series are identified and a TAR model with two regimes is proposed. A simulation study was carried out with the purpose of verifying if both the non-linear and linear models are suited to describe the probabilistic structure of the process. It is shown that both methods are adequate to describe the lower statistical moments of the original data, but the non-linear model represents better the skewness and the kurtosis of the data. 相似文献
14.
在集合数据同化中,协方差局地化（covariance localization,CL）方法的使用存在限制。集合转换卡尔曼滤波（ensemble transform Kalman filter,ETKF）作为集合平方根滤波的变种方法,是一种应用较广、计算高效的数据同化方法。本文分析了CL方法应用于ETKF方法的困难,从而改进CL方法使其可以适用于ETKF方法。另外,结合浅水方程,利用Askey函数作为多元局地化函数,提出了一种适用于多元数值模型的CL方法。通过具体实验验证,得到了较好的分析结果。 相似文献
15.
Interest in Colombia’s offshore industry has increased over the past years. Therefore a detailed characterization of extreme wind and waves, in terms of return periods, numbers of events and its duration during the annual cycle, is needed. Two sets of high-resolution data are used in the statistical extreme value analysis (EVA). The significant wave height data (0.125°, 6 h) are from the European Centre for Medium-Range Weather Forecasts (ECMWF) ERA-Interim reanalysis available for the past 35 years (1979–2014). Surface winds (0.25°, 6 h) from the Cross-Calibrated Multi-Platform Ocean Surface Wind Vector Analyses (CCMP) of NASA/GSFC/NOAA (NASA/Goddard Space Flight Center/National Oceanic and Atmospheric Administration) are available for the past 24 years (1987–2011). Three well-known methods are applied to the data: the Block Maxima (BM), the Peak-Over-Threshold (POT) and the Method of Independent Storm (MIS). Several probabilistic models (Gumbel, Generalized Extreme Value, Weibull and Pareto) are evaluated for the BM and different threshold values for the POT and MIS. The results show that waves can reach up to 3.8 m and winds can be as strong as 31 m/s when considering the 50–100-year return periods. However, the wave model could underestimate values by up to one meter; hence, there is a probability of higher values in the region. Seasonally, most extreme events occur during the dry season (December–March) and during the Mid-Summer-Drought (MDS) or Veranillo months (June–July). Local conditions, including the reinforcement of the Caribbean Low Level Jet (CLLJ) and the occurrence of cold atmospheric fronts, are important drivers of extreme metoceanic variability. The total number of extreme wind events varied spatially and temporally from 15 to 65 and the mean duration from 15 to 25 h. A total number of extreme wave events ranging from <10 to 80 were computed during the annual cycle in the areas of interest, with a mean duration of less than 40 h. 相似文献
16.
利用1921–2020年的海平面气压、海平面高度、热含量数据以及海冰密集度作为太平洋年代际振荡（Pacific Decadal Oscillation, PDO）指数的预报要素,建立了关于PDO指数时间序列预测的多变量长短期记忆（Long Short Term Memory, LSTM）神经网络模型,对比分析了2011–2020年不同时间序列预测模型的PDO指数预测结果,最后利用多变量LSTM神经网络模型实现了2021–2030年的PDO指数预测。结果显示,多变量LSTM神经网络模型的预测值与观测值经过交叉验证后的平均相关系数和均方根误差分别为0.70和0.62;PDO未来10年将一直处于冷位相,PDO神经网络指数出现两次波动,于2025年出现最小值。相比于其他时间序列预测模型,本文采用的多变量LSTM神经网络模型预测结果误差小、拟合效果好,可以作为一种新型的预测PDO指数的手段。 相似文献
17.
《Applied Ocean Research》2004,26(3-4):114-136
Two successive wave heights are modeled by a Gaussian copula, which is referred to as the Nataf model. Results with two initial distributions for the transformation are presented, the Næss model [Næss A. On the distribution of crest to trough wave heights. Ocean Engineering (1985);12(3):221–34] and a two-parameter Weibull distribution, where the latter is in best agreement with data. The results are compared with existing models. The Nataf model has also been used for modeling three successive wave heights.Results show that the Nataf transformation of three successive wave heights can be approximated by a first order autoregressive model. This means that the distribution of the wave height given the previous wave height is independent of the wave heights prior to the previous wave height. Thus, the joint distribution of three successive wave heights can be obtained by combining conditional bivariate distributions. The simulation of successive wave heights can be done directly without simulating the time series of the complete surface elevation.Successive wave periods with corresponding wave heights exceeding a certain threshold have also been studied. Results show that the distribution for successive wave periods when the corresponding wave heights exceed the root-mean-square value of the wave heights, can be approximated by a multivariate Gaussian distribution.The theoretical distributions are compared with observed wave data obtained from field measurements in the central North Sea and in the Japan Sea, with laboratory data and numerical simulations. 相似文献
18.
针对利用传统瞬时水边线提取方法处理高分辨率遥感影像存在提取结果不连续、效率不高和无法同时提取多片水域等问题, 提出了一种顾及轮廓信息和距离正则化水平集演化(distance regularized level set evolution, DRLSE)模型的遥感影像瞬时水边线快速提取方法, 并将其应用于福建泉州附近海域瞬时水边线提取。首先,使用DRLSE模型提取地物轮廓信息, 以解决经典阈值方法水边线提取结果不连续问题; 其次, 利用DRLSE模型的初始矩形轮廓中心位置和周长信息, 对噪声点等轮廓进行自动剔除, 并提取多片水域, 以提高瞬时水边线提取后处理效率。研究结果表明:相较于泛洪算法、Canny算子和CV(Chan-Vese)模型, 应用本方法进行大陆海岸线瞬时水边线提取更高效, 且提取结果连续、精度更高。 相似文献
19.
The generalised Pareto distribution (GPD) is often used to model the distribution of storm peak wave heights exceeding a high threshold, from which return values can be calculated. There are large differences in the performance of various parameter and quantile estimators for the GPD. Commonly used estimation methods such as maximum likelihood or probability weighted moments are not optimal, especially for smaller sample sizes. The performance of several estimators for the GPD is compared by the Monte Carlo simulation and the implications for estimating return values of significant wave height are discussed. Of the estimators compared, the likelihood-moment (LM) estimator has close to the lowest bias and variance over a wide range of sample sizes and GPD shape parameters. The LM estimator always exists, is simple to compute and has a low sensitivity to choice of threshold. It is recommended that the LM estimator is used for calculating return values of significant wave height when the sample size is less than 500. For sample sizes above 500 the NEW estimator of Zhang and Stephens (2009) can give accurate results for low computational cost. 相似文献
20.
基于数据挖掘的GF-1 遥感影像绿潮自适应阈值分区智能检测方法研究 总被引：1，自引：0，他引：1
由于受到云雾的影响，可见光影像能够高效用于绿潮检测的数据源较为有限，特别是云覆盖较为严重的可见光影像，基本无法用于检测绿潮。即使影像数据是在薄云、薄雾、无云覆盖的情况下获取的，由于其光谱反射值存在较大差异，依然很难采用同一阈值进行绿潮检测。基于此，为了提高可见光影像的利用率，实现不同云覆盖情况下，绿潮的高精度自适应阈值的自动检测，本文以GF-1影像为数据源，首先采用K-means聚类和C4.5决策树方法实现影像云覆盖情况的自动识别；其次，选取大量不同云覆盖情况下子图像样本（每个子图像样本中均包含绿潮和海水两类），分析得出不同云覆盖情况下绿潮和海水的区分阈值y与影像光谱差x=bandnir-bandred之间所具有的线性关系；然后，利用分析得出的线性关系提出一种适用于GF-1影像的绿潮分区自适应阈值自动检测方法。最后，为验证提出方法的有效性，分别采用NDVI方法、EVI方法和本文提出的自适应阈值自动检测方法进行绿潮提取实验。实验结果表明，对于GF-1卫星遥感数据，本文提出的绿潮自适应阈值分区自动检测方法明显优于传统的NDVI和EVI检测方法，不仅提高了绿潮的监测精度，而且实现了绿潮提取的全自动化。 相似文献