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.     

Implementation and application of a nested numerical storm surge forecast model in the East China Sea

A nested numerical storm surge forecast model for the East China Sea is developed. Aone-way relaxing nest method is used to exchange the information between coarse grid and fine grid. In the inner boundary of the fine grid model a transition area is set up to relax the forecast variables. This ensures that the forecast variables of the coarse model may transit to those of fine grid gradually, which enhances the model stability. By using this model, a number of hindcasts and forecast are performed for six severe storm surges caused by tropical cyclones in the East China Sea. The results show good agreement with the observations.     

A simplified hindcast method for the estimation of extreme storm surge events in semi-enclosed basins

Human presence, coastal erosion, and tourism activities are increasing the attention to coastal flooding risk. To perform risk assessments, long time series of observed or hindcast wave parameters and tide levels are then necessary. In some cases, only a few years of observation are available, so that observed extreme data are not always representative and reliable. A hindcast system aimed to reconstruct long time series of total tide levels may be of great help to perform robust extreme events analysis and then to protect human life, activities as well as to counteract coastal erosion by means of risk assessments. This work aims to propose a simplified method to hindcast storm surge levels time series in semi-enclosed basins with low computational costs. The method is an extension of a previous work of some of the authors and consists of a mixed approach in which the estimation of storm surge obtained by using the theory of linear dynamic system is corrected by using a statistical method. Both steps are characterized by low computational costs. Nevertheless, the results may be considered reliable enough also in view of the simplicity of the approach. The proposed method has been applied to the Manfredonia case study, a small village located in the Southern Adriatic Italian coast and often prone to coastal flooding events. The comparison of extreme events estimated on the basis of hindcast levels time series is satisfactorily similar to those estimated on the basis of observed tide series.     

台风风暴潮异模式集合数值预报技术研究及应用

台风风暴潮数值预报的准确性在很大程度上取决于台风路径预报和强度预报的精度以及风暴潮预报模型的计算精度。目前,国际上24/48 h台风路径预报平均误差分别约为120/210 km左右[1],对于走向异常的台风误差更大;更有,根据单一的台风路径和单族的风暴潮数值预报模式并不能保证获得可靠的风暴潮预报结果。考虑多重网格法原理具有在疏密不同的网格层上进行迭代以达到平滑不同频率的误差分量,使得计算快速收敛,精度提高的特性。在前期研究基础上基于业务化高分辨率(结构网格/有限差分算法)和精细化(非结构网格/有限元算法)台风风暴潮集合数值预报模型构建多模型台风风暴潮集合数值预报系统。采用"非同族"模型进行集合预报很大程度上降低了误差相似遗传的可能性。应用该方法对典型台风风暴潮过程进行了试应用,试报结果表明:该方法对风暴潮增、减水预报效果高于单一集合预报,具有一定的应用前景。     

Artificial neural network-based storm surge forecast model: Practical application to Sakai Minato,Japan

The present study describes a novel way of a systematic and objective selection procedure for the development of an Artificial Neural Network-based storm Surge Forecast Model (ANN-SFM) with the 5, 12 and 24 h-lead times and its application to Sakai Minato area on the Tottori coast, Japan. The selection procedure guides how to determine the superiority of the best performing model in terms of the appropriate combination of unit number in the hidden layer and parameter in the input layer. In the application of ANN-SFM to Sakai Minato, it is found that the best 5 and 12 h-forecast ANN-SFMs are established with the most suitable set of 70 units (the number of hidden neurons) and the input components of surge level, sea level pressure, the depression rate of sea level pressure, longitude, latitude, central atmospheric pressure and highest wind speed. The best 24 h-forecast ANN-SFM is determined with 160 units and the input parameters of surge level, sea level pressure, the depression rate of sea level pressure, longitude and latitude. The proposed method of the selection procedure is able to be adaptable to other coastal locations for the development of the artificial neural network-based storm surge forecast model as establishing the superiority of the most relevant set combining unit numbers and input parameters.     

Reconstruction of Hurricane Katrina's wind fields for storm surge and wave hindcasting

As the most costly US natural disaster in history, Hurricane Katrina fostered the IPET forensic study to better understand the event. All available observations from several hundred space-, land-, sea-, and aircraft-based measurement platforms were gathered and processed to a common framework for height, exposure, and averaging time, to produce a series of wind field snapshots at 3 h intervals to depict the wind structure of Katrina when in the Gulf of Mexico. The stepped-frequency microwave radiometer was calibrated against GPS sondes to establish the upper range of the instrument and then used to determine the wind field in the storm's core region in concert with airborne Doppler radar winds adjusted to the surface from near the top of the PBL (500 m). The SFMR data were used to develop a method to estimate surface winds from 3 km level reconnaissance aircraft observations, taking into consideration the observed azimuthal variation of the reduction factor. The “SFMR method” was used to adjust reconnaissance flight-level measurements to the surface in the core region when SFMR and Doppler winds were not available. A variety of coastal and inland mesonet data were employed, including portable towers deployed by Texas Tech University, University of Louisiana at Monroe, and the Florida Coastal Monitoring Program, as well as fixed mesonet stations from Louisiana State Universities Marine Consortium, University of Southern Mississippi, and Agricultural Networks from Louisiana, Mississippi, and Alabama, and the Coastal Estuarine Network of Alabama and Mississippi. Also included were land- (WSR-88D VAD and GBVTD, ASOS, Metar, LLWAS, HANDAR), space- (QuikScat, GOES cloud drift winds, WindSat), and marine- (GPS sondes, Buoys, C-MAN, ships) platforms. The wind fields serve as an analysis of record and were used to provide forcing for wave and storm surge models to produce hindcasts of water levels in the vicinity of flood control structures.     

A real-time, event-triggered storm surge forecasting system for the state of North Carolina

A new real-time, event-triggered storm surge prediction system has been developed for the State of North Carolina to assist emergency managers, policy-makers and other government officials with evacuation planning, decision-making and resource deployment during tropical storm landfall and flood inundation events. The North Carolina Forecast System (NCFS) was designed and built to provide a rapid response assessment of hurricane threat, accomplished by driving a high-resolution, two-dimensional, depth-integrated version of the ADCIRC (Advanced Circulation) coastal ocean model with winds from a synthetic asymmetric gradient wind vortex. These parametric winds, calculated at exact finite-element mesh node locations and directly coupled to the ocean model at every time step, are generated from National Hurricane Center (NHC) forecast advisories the moment they are inserted into the real-time weather data stream, maximizing the number of hours of forecast utility. Tidal harmonic constituents are prescribed at the open water boundaries and applied as tidal potentials in the interior of the ocean model domain. A directional surface roughness parameterization that modulates the wind speed at a given location based on the types of land cover encountered upwind, a forest canopy sheltering effect, and a spatially varying distribution of Manning’s–n friction coefficient used for computing the bottom/channel bed friction are also included in the storm surge model. Comparisons of the simulated wind speeds and phases against their real meteorological counterparts, of model elevations against actual sea surface elevations measured by NOAA tide gauges along the NC coast, and of simulated depth-averaged current velocities against Acoustic Doppler Current Profiler (ADCP) data, indicate that this new system produces remarkably realistic predictions of winds and storm surge.     

一个东海嵌套网格台风暴潮数值预报模式的研制与应用

建立了一个覆盖东海的两重嵌套网格高分辨率台风暴潮数值预报模式.粗、细网格模式分辨率分别为6'和2'.两套网格的嵌套采用单向松弛套网格技术,即在细网格的内边界附近建立了一个“过渡区”,对预报的物理量进行松弛,使粗、细网格模式变量逐步过渡,避免了边界附近寄生波的产生,从而增加了模式的稳定性.利用该模式,对显着影响东中国海地区的6次风暴潮过程进行了后报和预报试验.与观测资料比较,数值结果令人满意.     

厦门港潮汐、风暴潮耦合模型

建立一个适合台湾海峡及小港湾,特别是能够反映小港湾的漫滩及潮汐、风暴潮耦合效应的数值模型,对小港湾风暴潮进行数值预报,有重要的社会和经济意义.文中以厦门港作为小港湾研究区域,在漫滩、风暴潮的耦合、开边界条件等方面对小港湾风暴潮数值计算作了一定的尝试,提出了一种能够模拟小港湾台风增水,潮位和流场变化情况的途径.     

杰氏风暴潮预报方法在珠海及粤西海域的应用

珠海及粤西海域是风暴潮灾害的多发区,本文通过杰氏风暴潮预报方法对历史上给珠海和粤西海域造成较大影响的台风增水事件进行后报试验并通过统计分析方法对原有的预报公式进行订正,总结出适合珠海及粤西海域的风暴潮预报公式。并利用5年的时间对珠海及粤西海域的台风增水进行试报,结果表明预报准确率分别达95.0%和87.6%,这说明订正后的公式能对珠海及粤西海域的风暴潮预报起到较好的预报效果。     

Development and application of an operational tide and storm surge prediction model for the seas around Taiwan

Storm surges are abnormal rises in sea level along coastal areas and are mainly formed by strong wind and atmospheric depressions.When storm surges coincide with high tide,coastal flooding can occur.Creating storm surge prediction systems has been an important and operational task worldwide.This study developed a coupled tide and storm surge numerical model of the seas around Taiwan for operational purposes at the Central Weather Bureau.The model was calibrated and verified by using tidal records from seas around Taiwan.Model skill was assessed based on measured records,and the results are presented in details.At 3-minute resolution,tides were generally well predicted,with the root mean-square errors of less than 0.11 m and an overall correlation of more than 0.9.Storms(winds and depressions) were introduced into the model forcing by using the parameter typhoon model.Five typical typhoons that threatened Taiwan were simulated for assessment.The surges were well predicted compared with the records.     

基于多源数据的台风风暴潮概率预报研究:台风集合的构建

建立了一套用于台风风暴潮集合预报的台风集合构建方案.首先基于中国中央气象台、中国香港天文台、中国台湾中央气象局、美国联合台风预警中心、日本气象厅和韩国气象台6家预报中心的预报数据,构建一个误差更小的24 h、48h和72 h预报时效的台风分析数据;然后基于分析数据构建9个路径样本(1条分析路径+2个概率圆上的8条概率路...     

杰氏风暴潮预报方法在珠海及粤西海域的应用

本文通过杰氏风暴潮预报方法对历史上给珠海和粤西海域造成较大影响的台风增水事件进行后报试验,并通过统计分析方法对原有的预报公式进行订正,总结出适合珠海及粤西海域的风暴潮预报公式.利用5a的时间对珠海及粤西海域的台风增水进行试报,结果表明预报准确率分别达95.0%和87.6%,尤其对一些增水较大、影响较严重的台风增水预报相对更加准确,预报准确率均达90.0%以上.这说明订正后的公式对珠海及粤西海域的风暴潮预报能得到较好的预报效果.     

南海风暴潮对风场和外围海水敏感性研究

为探索来自西北太平洋台风风暴潮与南海局地生成台风风暴潮不同,本研究在假设两种台风气象条件相同情况下,研究随台风而来外围海水所形成增水对南海沿岸的影响。以0814"黑格比"强台风风暴潮为基础,使用ROMS(regional ocean modeling system)模式进行数值模拟并通过设计对比试验方法进行研究,研究发现在台风登陆时引起的增水最大,最大增水出现在台风路径右侧,其中在沿岸区域,外围海水形成增水约占总增水10%,且大约3 h后出现增水回震现象。同时,设计对比试验,研究来自西北太平洋台风风暴潮对台风路径、台风强度、台风移动速度和流入角等气象条件敏感性,并获得与前人一致的结果。     

Numerical storm surge model with higher order finite difference method of lines for the coast of Bangladesh

In this study, the method of lines (MOLs) with higher order central difference approximation method coupled with the classical fourth order Runge-Kutta (RK(4,4)) method is used in solving shallow water equations (SWEs) in Cartesian coordinates to foresee water levels associated with a storm accurately along the coast of Bangladesh. In doing so, the partial derivatives of the SWEs with respect to the space variables were discretized with 5-point central difference, as a test case, to obtain a system of ordinary differential equations with time as an independent variable for every spatial grid point, which with initial conditions were solved by the RK(4,4) method. The complex land-sea interface and bottom topographic details were incorporated closely using nested schemes. The coastal and island boundaries were rectangularized through proper stair step representation, and the storing positions of the scalar and momentum variables were specified according to the rules of structured C-grid. A stable tidal regime was made over the model domain considering the effect of the major tidal constituent, M₂ along the southern open boundary of the outermost parent scheme. The Meghna River fresh water discharge was taken into account for the inner most child scheme. To take into account the dynamic interaction of tide and surge, the generated tidal regime was introduced as the initial state of the sea, and the surge was then made to come over it through computer simulation. Numerical experiments were performed with the cyclone April 1991 to simulate water levels due to tide, surge, and their interaction at different stations along the coast of Bangladesh. Our computed results were found to compare reasonable well with the limited observed data obtained from Bangladesh Inland Water Transport Authority (BIWTA) and were found to be better in comparison with the results obtained through the regular finite difference method and the 3-point central difference MOLs coupled with the RK(4,4) method with regard to the root mean square error values.     

湛江红树林保护区现代沉积物粒度特征及其对风暴事件的响应

沉积物粒度是描述沉积环境的重要指标之一,利用沉积物粒度参数可以反演沉积物堆积过程、沉积水动力特征.通过对湛江红树林国家级自然保护内海湾、河口、潮坪区的红树林表层沉积物粒度分析的研究,结果表明：河口与海湾区的红树林沉积物以泥质为主;有堤坝保护的河口区红树林沉积物颗粒细,为悬移质体含量高且连续稳定的低能环境;红树林发育差的潮坪区红树林沉积物为砂含量较大且水动力较强的高能环境.并通过推算海湾区沉积物的沉积年代,结合样品粒度分析的结果得出了该地区风暴潮发生的大致时间.     

近岸海浪、风暴潮及海啸灾害远程实时监测系统的现场试验及应用

利用自主研发的近岸海浪、风暴潮及海啸灾害远程实时监测系统,在广东省阳江市闸坡附近海域进行了远程实时监测试验.文章介绍了监测系统的组成,对2007年9月1日-10月3日的观测记录进行了分析,计算出台风增水、波高和波周期,采用低通滤波方法获得重力外波.实验结果表明,研发的近岸海浪、风暴潮及海啸灾害远程实时监测系统可供实际推广应用.