共查询到19条相似文献，搜索用时 109 毫秒
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水位在忽略观测误差的前提下,可分解为潮位和余水位,后者具有较强的空间相关性以及非平稳特征,是影响水位预报精度的主要因素。港口工程、航运计划编制等方面对实时高精度水位预报具有重要需求,这对余水位预报模型构建提出了更高要求。另外,利用高精度余水位预报模型可减少验潮站布设数量。针对余水位短期预测模型精度不高的现状,本文对余水位进行集合经验模态(EEMD)分解,获得余水位在时间序列上的本征模函数(IMF);使用快速傅立叶变换(FFT)分析各本征模函数的频谱特征;再利用BP神经网络对各个本征模函数进行训练,预测了未来6 h、12 h、24 h的余水位值。对哥伦比亚河下游河口处的3组典型验潮站的余水位数据的预测结果表明,在未来6 h、12 h内的余水位的预测精度达到厘米级,在24 h内接近厘米级,证明了该组合模型在余水位短期预测方面的可行性。 相似文献
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面对近年海图测量逐渐由近海向外延伸的发展现状,其对水位改正的要求越来越高,水位改正是海图测量中的一个尤为重要的技术环节,对保证测量精度起着极其重要作用。实际测量作业中,在一些潮汐性质变化复杂的海域,采用传统水位改正方法面临设站数量多、难度大、易丢失、精度难保证等难点。针对测区潮波分布的复杂性与特殊性,基于POM模式,采用"混合"同化法同化由T/P卫星测高数据反演的沿迹潮汐参数构建了高分辨率高精度的潮汐模型,利用余水位的空间相关性,称之为基于潮汐模型与余水位监控的水位改正法。通过海图测量实例中基于潮汐模型与余水位监控法的应用,对测量成果精度进行了分析和验证,为海图测量在水位改正方法的选择提供了技术支持,进而对保证测量精度有着重要的现实意义。 相似文献
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文章以山东省警戒潮位核定为基础,对其沿岸验潮站的实测数据情况进行分类;根据不同类别,分别采用相关分析、数值模拟等方法补充实测数据,获得年极值水位序列,并采用极值Ⅰ型方法计算重现期高潮位。在警戒潮位核定中建立年极值水位序列所使用方法的顺序是,有实测数据优先采用实测数据、没有实测数据利用相关关系、没有相关关系再使用数值模拟和调和分析的方法进行。值得注意的是,在使用相关关系建立年极值水位序列中,计算重现期高潮位时一定要满足潮汐性质相同、所受风暴潮过程相似等条件;在使用数值模拟建立年极值水位序列中,须与其全年天文潮最大值进行对比。 相似文献
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针对新一代天气雷达数据存在风轮机杂波污染问题，统计分析了5种雷达基数据特征量，风轮机杂波具有较高的反射率因子隆起度和水平通道信噪比隆起度以及较大的速度奇异率，其信号质量指数接近1，谱宽接近0或大于7.0 m·s-1。以特征量统计结果为基础，使用模糊逻辑算法对雷达基数据中的风轮机杂波进行特征识别，结果显示，模糊逻辑算法能有效地把风轮机杂波从各种强度的气象降水回波和固定地物杂波中识别出来。针对被识别出来的风轮机杂波，使用区域平均插值方法对雷达基数据中的风轮机杂波进行剔除，杂波剔除结果显示，气象降水条件下获得了较好的风轮机杂波剔除效果。 相似文献
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ATOVS反演数据在大气中尺度模式MM5中的同化试验 总被引：1，自引：1，他引：0
基于中国海洋大学卫星地面站接收到的NOAA系列卫星数据,利用1种神经网络反演方法获取大气温度、湿度及风矢量垂直廓线数据。以2004年第14号台风"云娜"为例,在中尺度气象模式MM5中运用松弛逼近法对这些反演数据进行了一系列同化试验。结果表明:仅同化温度与湿度的效果比同时同化风矢量、温度与湿度的效果好;台风的路径与强度有所改善,不采用人造涡旋方案时同化效果相对采用人造涡旋方案时更能体现出改进作用。 相似文献
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1992 - 1 996年 ,对广西近海水深浅于 2 0 m的整个海域 ,利用 2 8个锚碇浮标和 2 3个周日连续观测站 ,对水位和海流进行了观测。根据观测结果 ,对该海域的潮汐性质 ,潮流特征和余流分布进行了分析 ,并对潮汐与潮流性质差异的动因和影响余流变化的主要因子进行初步探讨。结果表明 :广西近海的潮汐性质属于正规日潮。潮流性质大部分属于不正规半日潮或不正规日潮。余流主要由潮余流和风海流组成。潮流大小潮变化和风的变化是导致余流变化的主要原因。潮流绕海角运动 ,流速增强 ,并能诱导经向离岸流 相似文献
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Open coast storm surge water levels consist of a wind shear forcing component generally referred to as wind setup; a wave setup component caused by wind-induced waves transferring momentum to the water column; an atmospheric pressure head component due to the atmospheric pressure deficit over the spatial extent of the storm system; a Coriolis-forced component due to effects of the rotation of the earth acting on the wind-driven alongshore current at the coast; and, if astronomical tides are present, an astronomical tide component. Astronomical tide is considered to be predictable and, therefore, not a meteorological driven component of storm surge although there may be interaction between the tide and meteorological driven water levels. Typically the most important component of storm surge on the US East Coast and Gulf of Mexico shorelines is the wind setup component. The importance of inland flooding due to the wind setup component of storm surge is considered herein with special reference to the effect of subaerial slope on inland flooding where three different linear slopes are considered and storm surge is calculated for the region above still water level, using an analytic solution. The present study findings show that the inland storm surge from the wind setup component can be of considerable importance and lead to significantly higher storm surges than found for storm surge at the still water level intersection of the beach/land. It is shown that mild slopes can lead to very high water levels at the land–water interface (i.e. above the still water level intersection of the beach). 相似文献
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基于天津港主航道连续观测点31 d的实测海流资料,利用调和分析对主航道潮流和余流特征进行研究,同时结合同步风速资料研究风对表层余流的影响。结果表明:(1)航道附近属于弱流海区,表层平均流速为31.4 cm/s,流速总体上由表至底逐渐减小,流速方向大致集中在NW—SE向。(2)观测海域潮流以正规半日往复潮占主导,优势分潮为M2,浅水分潮较为显著,涨潮流流速大于落潮流流速。(3)观测期间表层平均余流流速为2.8~13.8 cm/s,随着深度增加余流流速逐渐减小,方向大多为NW向。该站表层余流受风的影响显著,东南风将使余流方向偏向西北。 相似文献
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大亚湾及其邻近海域冬、夏季各14个临时水位观测点1个月的实测潮位资料显示:各站的水位曲线均呈现明显的"双峰"现象,且湾顶比湾口更为明显。本文采用了调和分析方法,给出M_2、S_2、K_1、O_1四个主要分潮及M_4、M_6、2MS_6三个浅水分潮的振幅和迟角同潮图,分析大亚湾的主要潮汐特征,探讨了浅水分潮对双峰结构的贡献,并采用交叉谱分析对余水位与风的相关性进行了讨论。结果表明:(1)大亚湾海域各主要分潮振幅均由湾口向湾顶递增;高潮发生时间由湾口向湾顶推迟;涨潮历时均大于落潮历时;平均潮差在湾顶达到最大;(2)大亚湾内属于不正规半日潮,而考洲洋及其湾外海域则属于不正规全日潮;(3)大亚湾内浅水效应明显,从湾口至湾顶,六分之一日分潮的振幅呈5—7倍的增长,主导了大亚湾潮波系统的形变;(4)分潮重构结果显示,四分之一日和六分之一日浅水分潮(尤其是2MS_6分潮)的异常增长,是导致大亚湾潮汐双峰现象的主要原因;(5)冬季大亚湾内各点的余水位与风速呈现正相关,相关系数均在0.53以上;(6)周期为0.45—0.53 d的沿岸风对各站余水位的影响最大。 相似文献
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The long-term variation and seasonal variation of sea level have a notable effect on the calculation of engineering water level. Such an effect is first analyzed in this paper. The maximal amplitude of inter-annual anomaly of monthly mean sea level along the China coast is larger than 60 cm. Both the storm surge disaster and cold wave disaster are seasonal disasters in various regions, so the water level corresponding to the 1% of the cumulative frequency in the cumulative frequency curve of hourly water level data for different seasons in various sea areas is different from design water level, for example, the difference between them reaches maximum in June, July and August for northern sea area, and maximum in September, October and November for Southern China Sea. The hourly water level data of 19 gauge stations along the China coast are analyzed. Firstly, the annual mean sea level for every station is obtained; secondly, linear chan ging rates of annual mean sea level are obtained with the stochasti 相似文献
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本文基于2016年11月8日—2019年6月29日大沽河入海口水深观测数据分析了大沽河河口水位变化特征,并结合风场、降水量、卫星高度计融合产品资料对其影响因素展开了讨论。结果表明:1)大沽河口水位变化由潮汐过程主导,潮汐类型为正规半日潮,M2分潮占主导;2)余水位在2017年7月—2019年1月存在周期约为110—150天的显著季节内变化,主要受到纬向风的影响,监测系统处在大沽河入海口西岸,东向(西向)风将驱动水体向东(西)输运,导致西岸监测系统处水量减少(增加),从而观测到余水位下降(上升);3)观测期间,余水位存在显著下降趋势,约为–0.53×10–2 m/月,主要受到大沽河流域降水量减少的影响。 相似文献
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Accurate water levels modeling and prediction is essential for safety of coastal navigation and other maritime applications. Water levels modeling and prediction is traditionally developed using the least-squares-based harmonic analysis method that estimates the harmonic constituents from the measured water levels. If long water level measurements are not obtained from the tide gauge, accurate water levels prediction cannot be estimated. To overcome the above limitations, the current state-of-the-art artificial neural network has recently been developed for water levels prediction from short water level measurements. However, a highly nonlinear and efficient wavelet network model is proposed and developed in this paper for water levels modeling and prediction using short water level measurements. Water level measurements (about one month and a week) from six different tide gauges are employed to develop the proposed model and investigate the atmospheric changes effect. It is shown that the majority of error values, the differences between water level measurements and the modeled and predicted values, fall within the −5 cm and +5 cm range and root-mean-squared (RMS) errors fall within 1–6 cm range. A comparison between the developed highly nonlinear wavelet network model and the harmonic analysis method and the artificial neural networks shows that the RMS of the developed wavelet network model when compared with the RMS of the harmonic analysis method is reduced by about 70% and when compared with the RMS of the artificial neural networks is reduced by about 22%. It is also worth noting that if the atmospheric changes effect (meteorological effect) of the air pressure, the air temperature, the relative humidity, wind speed and wind direction are considered, the performance accuracy of the developed wavelet network model is improved by about 20% (based on the estimated RMS values). 相似文献