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Neural network prediction of a storm surge 总被引：4，自引：0，他引：4
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. 相似文献
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台风预报的准确性在风暴潮预报中起着重要作用。台风强度和路径的不确定性意味着使用集合模式来预报风暴潮。本文利用中央气象台的最优路径台风参数驱动国家海洋环境预报中心业务化的水动力学模型，开展华南沿海的风暴潮模拟，模式模拟结果与实测吻合较好。为了改进计算效率，采用CUDA Fortran 语言对模型进行了改造，改造后的模型在计算结果与原模型基本一致的基础上，计算时间缩短了99%以上。通过融合欧洲中期天气预报中心（ECWMF）的50条路径与3种可能台风强度构造出了150个台风事件，并用150个台风事件驱动改进的风暴潮数值模型，计算结果可以提供集合预报产品和概率预报产品。通过“山竹”台风风暴潮过程可以发现集合平均预报结果和概率预报结果与实测吻合较好。改进的数值模型可以运行普通工作站上，非常适合风暴潮集合预报，并且可以提供更好的决策产品。 相似文献
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A numerical study on the impact of tidal waves on the storm surge in the north of Liaodong Bay 总被引：1，自引：0，他引：1
KONG Xiangpeng 《海洋学报(英文版)》2014,33(1):35-41
A storm surge is an abnormal sharp rise or fall in the seawater level produced by the strong wind and low pressure field of an approaching storm system.A storm tide is a water level rise or fall caused by the combined effect of the storm surge and an astronomical tide.The storm surge depends on many factors,such as the tracks of typhoon movement,the intensity of typhoon,the topography of sea area,the amplitude of tidal wave,the period during which the storm surge couples with the tidal wave.When coupling with different parts of a tidal wave,the storm surges caused by a typhoon vary widely.The variation of the storm surges is studied.An once-in-a-century storm surge was caused by Typhoon 7203 at Huludao Port in the north of the Liaodong Bay from July 26th to 27th,1972.The maximum storm surge is about 1.90 m.The wind field and pressure field used in numerical simulations in the research were derived from the historical data of the Typhoon 7203 from July 23rd to 28th,1972.DHI Mike21 is used as the software tools.The whole Bohai Sea is defined as the computational domain.The numerical simulation models are forced with sea levels at water boundaries,that is the tide along the Bohai Straits from July 18th to 29th（2012）.The tide wave and the storm tides caused by the wind field and pressure field mentioned above are calculated in the numerical simulations.The coupling processes of storm surges and tidal waves are simulated in the following way.The first simulation start date and time are 00：00 July 18th,2012; the second simulation start date and time are 03：00 July 18th,2012.There is a three-hour lag between the start date and time of the simulation and that of the former one,the last simulation start date and time are 00：00 July 25th,2012.All the simulations have a same duration of 5 days,which is same as the time length of typhoon data.With the first day and the second day simulation output,which is affected by the initial field,being ignored,only the 3rd to 5th day simulation results are used to study the rules of the storm surges in the north of the Liaodong Bay.In total,57 cases are calculated and analyzed,including the coupling effects between the storm surge and a tidal wave during different tidal durations and on different tidal levels.Based on the results of the 57 numerical examples,the following conclusions are obtained：For the same location,the maximum storm surges are determined by the primary vibration（the storm tide keeps rising quickly） duration and tidal duration.If the primary vibration duration is a part of the flood tidal duration,the maximum storm surge is lower（1.01,1.05 and 1.37 m at the Huludao Port,the Daling Estuary and the Liaohe Estuary respectively）.If the primary vibration duration is a part of the ebb tidal duration,the maximum storm surge is higher（1.92,2.05 and 2.80 m at the Huludao Port,the Daling Estuary and the Liaohe Estuary respectively）.In the mean time,the sea level restrains the growth of storm surges.The hour of the highest storm tide has a margin of error of plus or minus 80 min,comparing the high water hour of the astronomical tide,in the north of the Liaodong Bay. 相似文献
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台风风暴潮异模式集合数值预报技术研究及应用 总被引：2，自引：2，他引：0
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。 相似文献
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东海风暴潮与天文潮的非线性相互作用 总被引：1，自引：0，他引：1
中国东海的风暴潮具有明显的周期性波动。凤暴潮除了决定于风应力和长波效应外,还受到天文潮与风暴潮相互作用的影响。本文利用一个二维数值模式对天文潮与风暴潮相互作用的水位进行了模拟。我们选取了8114号台风加以计算。计算结果与实测资料基本相符,由此说明水位曲线中的潮周期波动主要是由于天文潮与风暴潮之间的非线性相互作用所致。数值实验还表明,如果考虑到天文潮与风暴潮的相互作用可以显著改善水位的预报精度。 相似文献
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宁德地区是我国受风暴潮影响较为严重的区域之一,同时也是宁德核电站等众多沿海大型工程所在地.鉴于该区域特殊的地理位置和海洋灾害的严重性,以宁德核电站为中心,对该区域所面临风暴潮风险的特征参数进行全面、综合的定量评估,包括潮汐特征、平均海平面变化、台风和风暴潮基本特征,特别是可能最大风暴潮的计算.研究结果表明,该区域10%超越频率的天文潮高、低潮位分别为355、-341 cm;平均海平面变化速率为0.162 cm/a;千年一遇的台风中心气压约为895h Pa,该气压时的最大台风风速半径为40 km.在进行大量敏感性实验的基础上,对台风移速、移向和风暴增水/减水的关系,以及增水和减水的差异就行了详细的研究,得出:台风增水主要是由移向在305°左右(295°~315°)、路过核电站下方(核电站以南)的台风引起,且增水随台风移速增大而增大;可能最大台风风暴增水由路径经过核电厂址南40 km的台风(移向295°、移速28 km/h)引起,最大台风增水值为526.8 cm;对于可能最大台风减水而言,最有利于台风风暴减水的移向在355°~360°和0°~15°之间,其中可能最大台风减水为-301.9 cm,由移向5°、移速30 km/h、路径经过核电厂址南30 km(0.75台风最大风速半径)的台风引起. 相似文献
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广东沿海台风风暴潮可视化预报系统 总被引：5，自引：0，他引：5
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。 相似文献
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刘安国 《中国海洋大学学报(自然科学版)》1989,(3)
作者根据地方史志资料进行分析与统计,提出山东沿岸风暴潮的特点:存在风潮和台风暴潮两种型式。在风潮中,春季风潮占绝对优势,秋季风潮是次要的。三者的关系是:台风暴潮:春季风潮:秋季风潮=50％:37％:13％。此外,还分析了在风暴潮记载中的有关气象记录问题以及历代王朝有关风暴潮记录的特点。提出历史风暴潮灾情的个例,举出1985年山东沿岸发生的风暴潮灾情,以说明风暴潮灾害的严重性。 相似文献
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长江口受台风影响严重,台风风暴潮、上游洪峰及天文大潮相遇将致使长江下游至长江口水位暴涨,对沿岸至河口的防汛安全构成严重威胁。基于ADCIRC模型构建东中国海至长江口风暴潮数学模型,模拟9711号台风和0012号台风两场典型台风水位过程。以典型台风为基础构成多种台风路径,分析不同登陆位置和走向对长江沿线风暴增水影响。研究大洪水、不同路径台风、天文大潮共同影响下长江下游沿线风暴增水分布规律。结果表明:登陆位置处于长江口南侧情况下长江河道沿线增水大于正面登陆长江口和北侧登陆型台风;平行于长江河道方向移动的台风造成沿线增水大于斜向穿越长江口的台风,不同台风走向对于风暴增水影响程度小于登陆位置;台风风暴潮、上游洪峰及天文大潮“三碰头”情形下长江沿线增水分布呈单峰型,从大通至江阴不断增大,江阴至中浚维持高位,中浚至口外迅速减小。 相似文献
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一个高分辨率的长江口台风风暴潮数值预报模式及其应用 总被引：13，自引：1，他引：13
利用河口海岸海洋模式(ECOM-Si)建立了一个适用于长江口区风暴潮的数值预报模式.该模式采用对岸线有较好拟合能力的自然正交水平坐标系统和能分辨较复杂海底地形的垂直σ坐标系统.模式考虑了长江口径流量对风暴潮的影响,部分地考虑了天文潮和风暴潮非线性相互作用对风暴增水的影响.风暴潮预报的大气强迫场用模型气压场和模型风场.利用所建立的模式对长江口区台风风暴潮进行了8个个例模拟,模拟增水与实测增水的峰值相比较,平均绝对误差不足10cm.利用本研究建立的模式,就气象因子对风暴潮位的敏感性进行了数值试验.试验结果表明,台风中心气压降低(升高)20hPa可导致约100cm的风暴潮位升高(或降低).台风最大风速半径误差对台风增水的变化影响也较显著.试验还表明,长江径流量增加1倍(减半),可以造成风暴潮的平均增加25cm(减小13cm).天文潮位相变化对风暴增水的影响数值试验表明,当台风暴潮与天文潮在不同位相相互作用,可使风暴潮位最大增加达70cm或减小90cm. 相似文献
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风暴潮可能给沿海城市造成巨大破坏, 而深圳位于易受台风影响的南海北部沿岸, 经济和人口总量巨大, 但有关深圳近海风暴潮的研究工作却十分匮乏。本文基于区域海洋模式系统(regional ocean model system, ROMS)建立了一个以深圳近海为中心的三层嵌套模型, 用于研究深圳近海台风所致风暴潮的影响因素。首先对2018年台风“山竹”过境深圳导致的风暴潮进行模拟, 模拟结果与观测结果较为一致。在此基础上, 进行一系列参数调整试验, 研究台风登陆地点、登陆角度、台风尺度、台风强度以及移动速度的改变对风暴潮及其分布的影响。结果表明, 在深圳西边登陆的台风, 比在深圳东边登陆的台风产生的最大增水高1.5m左右。由东往西移动并登陆深圳的台风, 比由南向北移动的台风产生的最大增水高1.0m左右。台风最大风速半径增加15%, 最大增水上升0.2m左右。台风强度增强15%, 最大增水上升0.4m左右。台风移动速度总体上对风暴潮影响不大, 但不同登陆地点存在明显差异。当台风在深圳西边或者东边登陆时, 台风移动速度增加30%, 深圳沿海各海湾的最大增水反而上升0.2~0.6m。当台风从深圳中部登陆时, 台风移动速度增加30%, 珠江口的最大增水降低0.1m左右, 大鹏湾和大亚湾的最大增水却相反地上升0.2m左右, 不同海湾对台风移动速度呈现不同的变化特征, 与各海湾水体重新分布到稳定状态时间和台风作用时间有关。 相似文献
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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. 相似文献
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海口湾沿岸风暴潮漫滩风险计算 总被引：4，自引：0，他引：4
引用《海港水文规范》(1998)中的方法计算海口湾的极值高水位,计算不同重现期的风暴潮与最高天文潮位的组合高水位;同时应用经检验为可靠的台风风暴潮数值模式,由气候学统计方法得出的可能最强台风的参数,按3种路径类型12条路径分别计算,并对产生可能最大风暴潮的假想台风路径根据移速变化分别计算,由此确定海口湾可能最大风暴潮(PMSS)。计算所得3组数据作为海口湾风暴潮漫滩风险值,1000a一遇的极值高水位、1000a一遇的风暴潮与最高天文潮的组合高水位及可能最大风暴潮与最高天文潮的组合高水位分别为546cm,634cm和977cm。 相似文献
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Storm surges pose significant danger and havoc to the coastal residents' safety, property, and lives, particularly at offshore locations with shallow water levels. Predictions of storm surges with hours of warning time are important for evacuation measures in low-lying regions and coastal management plans. In addition to experienced predictions and numerical models, artificial intelligence (AI) techniques are also being used widely for short-term storm surge prediction owing to their merits in good level of prediction accuracy and rapid computations. Convolutional neural network (CNN) and long short-term memory (LSTM) are two of the most important models among AI techniques. However, they have been scarcely utilised for surge level (SL) forecasting, and combinations of the two models are even rarer. This study applied CNN and LSTM both individually and in combination towards multi-step ahead short-term storm surge level prediction using observed SL and wind information. The architectures of the CNN, LSTM, and two sequential techniques of combining the models (LSTM–CNN and CNN–LSTM) were constructed via a trial-and-error approach and knowledge obtained from previous studies. As a case study, 11 a of hourly observed SL and wind data of the Xiuying Station, Hainan Province, China, were organised as inputs for training to verify the feasibility and superiority of the proposed models. The results show that CNN and LSTM had evident advantages over support vector regression (SVR) and multilayer perceptron (MLP), and the combined models outperformed the individual models (CNN and LSTM), mostly by 4％–6％. However, on comparing the model computed predictions during two severe typhoons that resulted in extreme storm surges, the accuracy was found to improve by over 10％ at all forecasting steps. 相似文献
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珠江是我国三条最大的河流之一，由三大支流——东江、北江和西江组成。珠江口是三角洲网河区型的河口,无数水道彼此交织,方向各异。大小不一,地形十分复杂。每当台风侵袭本区时,强制波夹带盛潮进入河口向内推移,与洪水相遇时,则相互拥高,水位暴涨,严重威胁着珠江三角洲地区人民的生命财产。
统计表明(见图1),1949-1970年间,侵袭广东沿岸地区的台风共有149次;平均每年7次，八、九月份出现最多,约占58%，五月和十一月份最少,占8%。可以认为,珠江河口区是我国风暴潮的多发区。
近几年来,关于珠江河口区台风暴潮的研究和预报已有论述,获得了一些有益的成果。本文仅对珠江口(伶仃洋)台风暴潮的一些特性从理论和实相结合的角度予以讨论。 相似文献