异地海域年极值风暴增水同现规律的探讨

以塘沽和龙口海洋观测站20年极值增水值为样本，基于二维冈贝尔逻辑分布模式，探讨了不同海域风暴潮增水极值的联合分布规律。通过对二维分布的联合概率密度、条件概率密度和同现概率的计算，给出了相应的工程设计参数，供有关部门在防潮规划时参考。     

广东沿海台风风暴潮可视化预报系统

广东省地处南海北部,风暴潮灾害严重。为快速准确做好风暴潮预报并将预报结果应用于防灾减灾中,根据南海预报中心多年来在风暴潮数值预报、经验统计方法预报和潮汐预报的实践,研制了可视化软件。此软件可显示广东省28个沿海主要港口的逐时风暴增水与天文潮位的综合潮位曲线与数值,以动态或静态显示广东沿海海面的增水等值线图,成为业务化预报软件。多年的风暴潮数值预报的实践证明,国家海洋环境预报中心王喜年等在八·五攻关项目中推广应用的台风风暴潮模式,在广东沿岸的风暴潮数值预报中效果较好,可视化预报软件采用这一模式是合适的。     

Neural network prediction of a storm surge

The occurrence of storm surge does not only destroy the resident's lives, but also cause the severe flooding in coastal areas. Therefore, accurate prediction of storm surge is an important task during the coming typhoon. Conventional numerical methods and experienced methods for storm surge prediction have been developed in the past, but it is still a complex ocean engineering problem which many factors, including the central pressure of typhoon, the speed of the typhoon, the heavy rainfall, coastal topography and local features influence the variation of storm surge. In fact, this problem is still a complex nonlinear relationship that can not solved efficiently by these two methods. Therefore, this paper presents an application of the neural network for forecasting the storm surge. The original data of Jiangjyun station in Taiwan will be used to test the performance of the present model. The results indicate that the neural network can be efficiently forecasted storm surge using the four input factors, including the wind velocity, wind direction, pressure and harmonic analysis tidal level.     

Fully nonlinear wave-body interactions with surface-piercing bodies

Fully nonlinear wave-body interactions for stationary surface-piercing single and double bodies are studied by a potential-theory-based fully nonlinear 2D numerical wave tank (NWT). The NWT was developed in time domain by using boundary element method (BEM) with constant panels. MEL free surface treatment and Runge–Kutta fourth-order time integration with smoothing scheme was used for free-surface time simulation. The acceleration-potential scheme is employed to obtain accurate time derivative of velocity potential. Using the steady part of nonlinear force time histories, mean and a series of higher-harmonic force components are calculated and compared with the experimental and numerical results of other researchers. The slow-decaying second-harmonic vertical forces are investigated with particle velocities and corresponding body pressure. Typical patterns of two-body interactions, shielding effect, and the pumping/sloshing modes of water column in various gap distances are investigated. The pumping mode in low frequencies is demonstrated by the comparison of velocity magnitudes.     

Application of artificial neural networks in typhoon surge forecasting

A typhoon-surge forecasting model was developed with a back-propagation neural network (BPN) in the present paper. The typhoon's characteristics, local meteorological conditions and typhoon surges at a considered tidal station at time t−1 and t were used as input data of the model to forecast typhoon surges at the following time. For the selection of a better forecasting model, four models (Models A–D) were tested and compared under the different composition of the above-mentioned input factors. A general evaluation index that is a composition of four performance indexes was proposed to evaluate the model's overall performance. The result of typhoon-surge forecasting was classified into five grades: A (excellent), B (good), C (fair), D (poor) and E (bad), according to the value of the general evaluation index. Sixteen typhoon events and their corresponding typhoon surges and local meteorological conditions at Ken–fang Tidal Station in the coast of north-eastern Taiwan between 1993 and 2000 were collected, 12 of them were used in model's calibration while the other four were used in model's verification. The analysis of typhoon-surge forecasting results at Ken–fang tidal station show that the Model D composing 18 input factors has better performance, and that it is a suitable BPN-based model in typhoon-surge forecasting. The Model D was also applied to typhoon-surge forecasting at Cheng-kung Tidal Station in south-eastern coast of Taiwan and at Tung-shih Tidal Station in the coast of south-western Taiwan. Results show that the application of Model D in typhoon-surge forecasting at Cheng-kung Tidal Station has better performance than that at Tung-shih Tidal Station.     

初探我国Argo浮标下潜深度标定

为了使剖面能停留在预定深度,通过水静力学角度对相应的浮标压载标定方法进行研究.试验表明,浮标重量改变1 g,就会造成大约10 m停留深度的变化.论文详细描述了用压力罐进行浮标压载重量标定的方法,并通过一台浮标的压载实验给出浮标配重计算方法.     

我国风暴潮灾害及防灾减灾战略

本文在分析了1949-1997的风暴潮及其重大灾害事件后指出，从上世纪九十年代以来，我国风暴潮灾害的经济损失已呈显著上升的趋势，减轻重大台风风暴潮灾害所造成的经济损失，已成为我国风暴潮减灾工作的当务之急。为此提出了减轻重大风暴潮灾害的战略要点：（1）充分利用一切媒体使人民具有预防重大风暴潮灾害的意识；（2）加强对重大风暴潮及其灾害的科研工作；（3）修订全国沿海岸段的防潮工程规划；（4）制订海洋减灾法规和有关规范；（5）建立风暴减灾保险的机制。     

福建省沙埕港百年一遇台风风暴潮的计算

研究了福建省沙埕港风暴潮状况,根据收集的沙埕验潮站连续50a(1956-2005)的台风过程增水资料以及西北太平洋57 a 的台风资料,采用皮尔逊Ⅲ统计法和数值法分别计算了沙埕港的100a一遇台风暴潮和 100a一遇最大台风暴潮,并得到了产生这两种台风增水的台风路径及强度等台风参数.沙埕港100a一遇台风暴潮为198 cm,100a一遇最大台风暴潮为243 cm,其中产生100a一遇台风暴潮的台风移向为NW方向,移速为19km/h,路径位于沙埕港南12km;产生100a一遇最大台风暴潮的台风移向为 NW 方向,移速为19 km/h,路径位于沙埕港南24km.计算结果为福建沿海海洋工程项目的建设提供了重要参考依据.     

雷州市沿海风暴潮淹没危险性评估*

文章基于近岸海洋数值模式ADCIRC (a parallel advanced circulation model for oceanic, coastal and estuarine waters)和近海波浪数值模式SWAN (simulating waves nearshore), 建立雷州市高分辨率的风暴潮-海浪耦合漫滩数值模型, 并反演了对雷州市影响较为严重的1415号台风“海鸥”的风暴潮过程。经过对比分析得出, 波浪对雷州市沿海海域的风暴潮产生重要影响。然后以8007号台风路径为基础, 构造了7个不同等级共35组台风风暴潮案例, 计算分析出不同等级台风强度下雷州市风暴潮淹没范围及水深。900hPa等级下, 雷州市淹没面积达到463.2km²。文章还构造了60组可能最大风暴潮事件集, 计算得到雷州市可能最大台风风暴潮淹没范围及水深分布。在可能最大台风影响下, 大量海水将漫过海堤, 造成极其严重的淹没灾害, 雷州市总的淹没面积可达602.0km², 其中465.8km²的淹没面积达到了危险性等级 Ⅰ 级, 淹没水深大于3m。雷州市东岸的淹没灾害大于西岸。     

Effects of tropical cyclone paths and shelf bathymetry on inducement of severe storm surges in the Gulf of Thailand

The influences of tropical cyclone paths and shelf bathymetry on the inducement of extreme sea levels in a regional bay are investigated. A finite volume coastal ocean model(FVCOM) has been configured for the Gulf of Thailand-Sunda Shelf. A parametric wind model is used to drive the FVCOM. The contributions of the tropical cyclone characteristics are determined through a scenario-based study. Validation based on a historical extreme sea level event shows that the model can resolve the oscillation mechanism well. The intensification of severe storm surges in the region highly depends on four factors including phase propagation of the storm surge wave determined by the landfall position, funnel effect caused by locality of the coastline, and shelf bathymetry determined by the state of mean sea level and coastline crossing angle of the storm path. The coexistence of these factors can cause particular regions e.g. the Surat Thani Bay, inner Gulf of Thailand and Ca Mau Peninsular to experience a larger surge magnitude. These areas are found to be highly related to monsoon troughs that develop during the onset and early northeastern monsoon season(October–November).