A multi-distribution approach to POT methods for determining extreme wave heights

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.     

A statistical analysis of typhoon frequency and application in design wave height

A typhoon leading is an important natural disaster to many disasters to China. A giant wave caused by it has brought large threat for an offshore project. Based on the maximum entropy principle,one new model which has 4 undetermined parameters is constructed,which is called the discrete maximum entropy probabilistic model. In practical applications,the design wave height is considered as soon as possible in a typhoon affected sea areas,the result fits the observed data well. Further more this model does not have the priority compared with other distributions as Poisson distribution. The model provides a theoretical basis for the engineering design more reasonable when considering typhoon factors comprehensively.     

一种利用浮标站资料改进海浪模式有效波高预报的方法

基于浮标站海浪历史数据,利用回归分析方法建立了海浪数值模式有效波高预报产品的一元二次回归方程订正统计模型。通过2017年7月1日-2018年10月10日期间业务试运行结果发现:订正方程能有效改善有效波高数值预报产品的预报精度,且预报时效越短订正效果越显著。其中,第6~11 h预报时效内的订正前后平均绝对误差值减小0.17~0. 241 m,第6~18 h预报时效内订正前后均方根误差减小幅度为0.103~0. 28 m。这说明应用订正统计模型对海浪模式输出产品进行订正,也是改进海浪模式预报准确率的一种有效途径。     

基于WW3的南海北部有效波高时空变化及其极值重现期估算方法分析

本文基于第3代海浪模式WAVEWATCH III （WW3）模拟的1996–2015年海浪后报数据,分析了南海北部有效波高及其极值的时空变化特征,并采用Pearson-III和Gumbel两种极值分布方法对该区极值波高重现期进行了估算。结果表明,南海北部有效波高的季节变化和空间分布与季风风场基本一致,呈现秋冬高春夏低,并自吕宋海峡西侧向西南降低的特征,与ERA5再分析数据结果高度相似。有效波高极值（简称极值波高）的时空分布特征受时间分辨率强烈影响,采用极值数据的分辨率越高（如逐小时）,所展现的台风型波浪特征越显著。扣除季节变化信号后的有效波高和年极值波高均体现出较强的线性增高趋势,近20年升高的比例分别为7.7%和31.6%,值得警惕和关注。该区多年一遇极值波高存在若干个大值区,且与台风的路径、强度有直接联系,表明台风是引发该区域极端大浪的最主要机制。对比Pearson-III和Gumbel极值分布估算结果发现：若极值波高较低,频率随极值波高升高缓慢降低,此时两种极值分布的估算都比较准确,差异极小,可忽略不计;但当研究时间范围内,某年极值波高远超其他年份时,Pearson-III极值分布估算结果明显高于Gumbel极值分布估算结果,且更接近实际极值波高,即Pearson-III极值分布在此情况下表现更好。本研究表明对于特定海区,在出现超强台风引发极值波高远超出其他年份时,不同计算方法对极值波高的估算差异较大,会显著影响重现期的评估。此外,南海北部年极值波高的强烈增高趋势,也可能给计算未来极值波高重现期和海上工程防护带来不可忽视的影响。     

极值波高建模中不确定性的模糊量化方法

A non-traditional fuzzy quantification method is presented in the modeling of an extreme significant wave height. First, a set of parametric models are selected to fit time series data for the significant wave height and the extrapolation for extremes are obtained based on high quantile estimations. The quality of these results is compared and discussed. Then, the proposed fuzzy model, which combines Poisson process and generalized Pareto distribution(GPD) model, is applied to characterizing the wave extremes in the time series data. The estimations for a long-term return value are considered as time-varying as a threshold is regarded as non-stationary. The estimated intervals coupled with the fuzzy theory are then introduced to construct the probability bounds for the return values. This nontraditional model is analyzed in comparison with the traditional model in the degree of conservatism for the long-term estimate. The impact on the fuzzy bounds of extreme estimations from the non stationary effect in the proposed model is also investigated.     

基于现场和卫星有效波高数据评估WAVEWATCH III的输入/耗散项

基于WAVEWATCH III,在输入相同的风场条件下,评估了三个输入耗散项WAM3,WAM4以及TC96在是否考虑大气稳定性时的模拟能力。通过5组实验,用南海的测波雷达数据以及研究区域内HY-2高度计的有效波高数据对不同源项的模拟结果进行了比较分析,研究区域为100-135°E,0-35°N。对TC96中的风速校正参数进行了敏感性分析。结果表明,这几种源项在涌浪占主导时的模拟效果都不太理想;考虑大气不稳定性的TC96源项模拟的效果最好;大气不稳定性的影响是以一种所谓的“高效风速”的策略来反映的,其中最重要的一个参数为风速转换参数,这个参数非常敏感,在对特定区域进行模拟之前,应先分析出这个参数的最优值。