北海港热带气旋风暴潮特性和预报

一、引言 广西北海港位于北部湾顶。北部湾颇似长方形,纵轴走向为东北-西南向,偏西南风对湾顶增水有利;横轴在海南岛东方县至越南海防市一线,台风在横轴移行北海增减水效应显著。北部湾是个半封闭海区,受雷州半岛和海南岛阻隔,北海港不易受南海自由长波影响,但常有明显的港湾振动,即使没有激烈的天气系统,增水曲线也常有波动,波动周期多为24小时,振幅多在0.30m左右,波峰出现在天文潮腰附近。北海港的潮型属正规全日潮,每月有两次大潮汛和两次小潮汛;大潮发生在月球赤纬最大后1～2天;多年平均潮位2.53m,平均高潮位4.99m,平均最高潮位5.30m,实测最高潮位5.93m,防潮警戒水位5.50m。     

热带气旋的风险评估

利用基于信息扩散理论的风险评估方法,对中国东南沿海各省,市,自治区的热带气旋进行了风险分析。该方法简单易行,分析结果意义清楚,对防灾抗灾具有一定的指导作用。     

连云港温带风暴潮及可能最大温带风暴潮的计算

用46a资料首次对连云港温带风暴潮进行了统计分析,计算了不同重现期的温带风暴潮(增、减水)值,并划分引起温带风暴潮的天气类型;进而首次构造引起连云港可能最大温带风暴潮(增、减水)的天气系统;最后,采用经过典型温带风暴潮过程数值模拟检验的风暴潮数学模型,计算了连云港可能最大温带风暴潮,计算结果已被江苏田湾(连云港)核电站厂址设计部门采用.     

影响广西沿海的热带气旋分析

应用《台风年鉴》1953—2012年热带气旋(TC)最佳路径资料,统计分析了影响广西沿海TC和易引发广西沿海显著增水的TC的时空分布特征以及年际变化特征。结果表明:影响广西沿海的TC主要集中于7、8、9三个月份,以南海为主要源地,而引起广西沿海显著增水的TC多源于菲律宾以东大洋洋面。从影响广西沿海的TC在近60年频数和强度变化来看,广西沿海TC最大强度存在下降趋势,但每年的平均强度存在上升趋势。     

热带气旋影响下上海港水位数值模拟和预报方法研究

基于二维台风风暴潮动力－数值模式和二维天文潮动力－数值模式，本文提出了一个包含天文潮和风暴潮非线性相互作用的综合水位数值模拟和数值预报方法。该方法经对１９５１－１９８６年间对上海港影响较大的８场台风期间的综合水位进行数值模拟，结果令人满意。运用该方法对９０１５号台风期间的上海港综合水位的试报和后报结果比较表明，水位误差主要来自台风路径和强度的预报而不是水位预报方法本身。所提出的适用于上海港水位数值     

热带气旋资料长度对风暴潮危险性评估结果的影响

热带气旋历史样本数不足一直困扰着风暴潮风险评估研究,本文基于西北太平洋62 a(1949-2010年)历史观测热带气旋事件集资料和用随机模拟方法构造的1000 a模拟热带气旋随机事件集,以福建省连江县为例,开展了资料长度对风暴潮灾害危险性评估结果的影响分析。文中用ADCIRC模型模拟了两种数据集强迫下的风暴潮增水,采用极值Ⅰ型分布法得到了典型重现期的风暴潮增水,经过对计算结果分析发现典型重现期的风暴潮增水计算结果与所用数据资料长度有着密切相关性,数据资料越长,结果越稳定。对于1000 a一遇的风暴潮增水值,使用500 a长度的资料已经趋于稳定,并接近用1000 a资料计算得到的结果。在进行风暴潮危险性评估时,相比用几十年尺度的热带气旋历史数据集,1000 a的热带气旋模拟数据集的计算结果更具实际意义。     

一个新的热带气旋参数调整方案

基于前人的统计经验公式和现有的实测资料,尤其是详实的热带气旋中心气压资料,对热带气旋的最大风速半径的确定提出一个新的调整方案,使之能较好反映热带气旋风场.比较结果表明,所计算的海浪场与实测资料吻合较好.     

滨海核电可能最大台风浪的推算

采用当前国际流行的第三代波浪模式SWAN探讨了滨海核电工程可能最大台风浪的计算,并分析了可能最大台风浪与相伴随的可能最大风暴潮成长规律.分析得可能最大台风浪通常滞后可能最大风暴潮增水峰值,推算得到的可能最大台风浪高于遮浪海洋站观测到的最大波高,为滨海核电工程可能最大台风浪的推算提供参考.     

镇海可能最大台风增水的计算

本文采用笔者建立并经过模拟检验的台风风暴潮数值模式,由已确定的可能最大台风,按3种类型的13条台风路径分别进行了计算,并对产生可能最大风暴潮的假想登陆台风进行了不同移速的计算,由此确定了镇海的可能最大台风增水(PMSS)值.对当地工程项目的建设和防灾规划的制定有重要参考意义.     

Numerical Simulation of Extreme Sea Levels for the Tamil Nadu (India) and Sri Lankan Coasts

Numerical modeling of extreme sea levels associated with tropical cyclones in the Indian seas has been confined to the northern part of the Bay of Bengal (north of Tamil Nadu). However, limited attempts have been made for modeling of surges along the Tamil Nadu and Sri Lankan coasts. Although, very rarely, cyclones form south of 10°N, there are some instances of severe cyclonic storms hitting these areas and causing widespread destruction to life and property. Keeping this in view, a suitable location-specific, high-resolution, numerical model has been developed for the prediction of storm surges in these regions with a grid resolution of 3 km. Using the model, numerical experiments are performed to simulate the storm surge associated with the 1964 Rameswaram cyclone, the 1978 Batticaloa cyclone, the 1992 Tuticorin cyclone, the 1993 Karaikal cyclone, and the 1994 Madras cyclone. During the years 1964, 1978, and 1992, the cyclones struck both Sri Lanka and Tamil Nadu coasts, while in 1993 and 1994, the cyclones struck only the Tamil Nadu coast. It is found that the computed sea surface elevations are in close agreement with the available observations/estimates.     

Numerical Simulation of Extreme Sea Levels for the Tamil Nadu (India) and Sri Lankan Coasts

Numerical modeling of extreme sea levels associated with tropical cyclones in the Indian seas has been confined to the northern part of the Bay of Bengal (north of Tamil Nadu). However, limited attempts have been made for modeling of surges along the Tamil Nadu and Sri Lankan coasts. Although, very rarely, cyclones form south of 10°N, there are some instances of severe cyclonic storms hitting these areas and causing widespread destruction to life and property. Keeping this in view, a suitable location-specific, high-resolution, numerical model has been developed for the prediction of storm surges in these regions with a grid resolution of 3 km. Using the model, numerical experiments are performed to simulate the storm surge associated with the 1964 Rameswaram cyclone, the 1978 Batticaloa cyclone, the 1992 Tuticorin cyclone, the 1993 Karaikal cyclone, and the 1994 Madras cyclone. During the years 1964, 1978, and 1992, the cyclones struck both Sri Lanka and Tamil Nadu coasts, while in 1993 and 1994, the cyclones struck only the Tamil Nadu coast. It is found that the computed sea surface elevations are in close agreement with the available observations/estimates.     

Response based design metocean conditions for a permanently moored FPSO during tropical cyclones: Estimation of greenwater risk

Response based analysis (RBA) is used to establish the design metocean conditions (DMCs) of a generic weather-vaning FPSO off the North West Shelf (NWS) of Australia for determining greenwater severity. A vessel heading prediction tool, an essential component of the RBA analysis for weather-vaning vessels, is developed and evaluated by comparing with full-scale measurements from an operating FPSO. Locations at the bow, amidships and the stern of the vessel are found to be susceptible to greenwater risks and the vessel is often exposed to oblique waves during tropical cyclones. Long-term extrapolation is performed to estimate 1 in. N-year return relative wave-vessel motions represented by both the most probable maximum relative wave-vessel motion within a storm r_mp, and the maximum individual relative wave-vessel motion r_Max. It is observed that r_Max ˜ (1.1–1.2) r_mp. The use of r_Max allows for the variability of the short term maxima per storm and also the fact that the peak in response might not come in the most severe sea-state. Given the focus on greenwater rather than wave severity, the slightly larger value of r_Max at a given return period is used for assessment of greenwater risk. The sea-states that lead to r_Max at a 1 in 100 year level are identified and subsequently used for characterising the wave groups causing maximum relative wave-vessel motion at various locations around the vessel. For a given location, the shapes of the wave time histories which give rise to extreme relative wave-vessel motions in a set of design metocean conditions are similar, indicating that a ‘design wave’, derived within the framework of linear wave theory, may be a useful approach to tackle highly nonlinear and complex greenwater overtopping problems.