Temporal significant wave height estimation from wind speed by perceptron Kalman filtering

Significant wave height estimates are necessary for many applications in coastal and offshore engineering and therefore various estimation models are proposed in the literature for this purpose. Unfortunately, most of these models provide simultaneous wave height estimations from wind speed measurements. However, in practical studies, the prediction of significant wave height is necessary from previous time interval measurements. This paper presents a dynamic significant wave height prediction procedure based on the perceptron Kalman filtering concepts. Past measurements of significant wave height and wind speed variables are used for training the adaptive model and it is then employed to predict the significant wave height amounts for future time intervals from the wind speed measurements only. The verification of the proposed model is achieved through the dynamic significant wave height and wind speed time series plots, observed versus predicted values scatter diagram and the classical linear significant wave height models. The application of the proposed model is presented for a station in USA.     

Predicting significant wave height off the northeast coast of the United States

To develop a simple method to predict the significant wave height, we analyze 18 years of hourly observations from 12 different buoys that are off the northeast coast of the United States. Water depths ranged from 19 to 4427 m for these moored buoys. We find that, on average, all of these buoys exhibit a region of constant wave height for 10-m wind speeds between 0 and 4 m s⁻¹. That wave height does, however, depend on water depth. For wind speeds above 4 m s^–1, the wave height increases as the square of the wind speed; but the multiplicative factor is again a function of water depth. We synthesize these results in a prediction scheme that yields the significant wave height from simple functions of water depth and 10-m wind speed for wind speeds up to 25 m s^–1.     

Estimation of wind speed and wave height during cyclones

Wave and wind characteristics based on the cyclones, in the vicinity of the Nagapattinam coastline (east coast of India) were estimated. In all, 11 cyclones have crossed near the study region during 1960–1996. For the four severe cyclones, the isobaric charts were collected at three hourly intervals from the India Meteorological Department. The storm variables such as central pressure, radius of maximum wind, speed of forward motion and direction of storm movement were extracted and the method based on standard Hydromet pressure profile, were used for the hindcast of storm wind fields. For all the cyclones the maximum significant wave height within the storm and its associated spectral peak period was estimated using the Young’s model considering the moving wind field and the results are compared with the hurricane wave prediction techniques provided in the shore protection manual published by the US Army Corps of Engineers in 1984. The study shows that the estimated wind speed and the data reported by ships were comparable. Empirical expressions relating wind speed, wave height and wave period to storm parameters were derived. The design wave height for different return periods was obtained by fitting a two-parameter Weibull distribution to the estimated significant wave heights. The design wave height was 9.39 m for 1 in 100 year return period for a direct hit of cyclone.     

基于HY-2 卫星观测分析南海风浪关系

海面有效波高(H1/3)是表征海浪的重要参数,随着卫星遥感技术的发展,雷达高度计已成为获取海面有效波高的重要手段,但也只能对卫星星下点轨迹处进行有效观测,远无法满足大范围应用的需求.本研究结合2013年10月HY-2雷达高度计观测的海面有效波高和微波散射计观测的海面风场资料,分别对高、低风速下风浪数据进行拟合,建立了适用于0~40 m/s风速范围内的南海海域风浪关系模型,经模型比对和结果验证,结果表明,基于HY-2卫星数据分析建立的南海海域风浪关系模型是可信的,特别是低风速的风浪模型与实测数据建立的风浪模型具有很好的一致性;根据建立的风浪关系模型,从卫星散射计大面观测的海面风场出发,能推算出风浪条件下海面有效波高的大面信息,数据覆盖远高于卫星高度计的星下点观测,能为分析和预报海浪、风暴潮灾害提供大范围的海面有效波高信息.     

A novel technique in analyzing non-linear wave-wave interaction

During wave growth non-linear wave–wave interactions cause transfer of some wave energy from lower to higher wave periods as the spectrum grows. Wavelet bicoherence, which is a new technique in the analysis of wind–wave and wave–wave interactions, is used to analyze non-linear wave–wave interactions. A selected record of wind wave that contains the maximum wave height observed during 6 h of wave generation is divided into five segments and wavelet bicoherence is computed for the whole record, and for all divided segments. The study shows that the non-linear wave–wave interaction occurs at different bicoherence levels and these levels are different from one segment to another due to the non-stationarity feature of the examined data set.     

强台风“卡努”过境期间的风和海浪特征分析

南海北部海域夏季台风活动频繁,对海上生产活动和人民生命财产安全造成极大威胁,由于台风路径的不确定性,其中心附近区域的风浪观测资料十分稀少。中国气象局(China Meteorological Administration, CMA)热带气旋最佳路径数据显示2017年10月强台风“卡努”中心经过南海北部陆坡的SF301浮标,该浮标完整记录了台风过境的风浪数据。利用浮标观测资料,分析了强台风“卡努”过境期间的风和海浪特征。观测结果表明,“卡努”经过浮标时,中心气压为959.9 hPa,风速随时间呈双峰分布,前、后眼壁区的10 min平均风速分别为30.2 m/s和24.9 m/s, 1 s极大风速分别为44.2和38.6 m/s。海浪以风浪为主,观测有效波高和最大波高最大值分别为10.8和14.3 m,滞后最大风速30 min,波向和风向变化趋势一致。台风过境期间,有效波高与海面10 m风速接近线性关系,非台风期间二者呈二次多项式关系。海浪无因次波高和周期呈幂指数关系,无论是台风期间还是非台风期间二者关系十分接近Toba提出的3/2指数律。     

Prediction of significant wave height using regressive support vector machines

Wave parameters prediction is an important issue in coastal and offshore engineering. In this literature, several models and methods are introduced. In the recent years, the well-known soft computing approaches, such as artificial neural networks, fuzzy and adaptive neuro-fuzzy inference systems and etc., have been known as novel methods to form intelligent systems, these approaches has also been used to predict wave parameters, as well. It is not a long time that support vector machine (SVM) is introduced as a strong machine learning and data mining tool. In this paper, it is used to predict significant wave height (H_s). The data set used in this study comprises wave wind data gathered from deep water locations in Lake Michigan. Current wind speed (u) and those belonging up to six previous hours are given as input variables, while the significant wave height is the output parameter. The SVM results are compared with those of artificial neural networks, multi-layer perceptron (MLP) and radial basis function (RBF) models. The results show that SVM can be successfully used for prediction of H_s. Furthermore, comparisons indicate that the error statistics of SVM model marginally outperforms ANN even with much less computational time required.     

基于核函数NPSSB模型的HY-2A卫星雷达高度计海况偏差研究

利用机器学习的方法,对14个周期HY-2A卫星高度计数据:风速、有效波高和海面高度差值进行训练,探究海况偏差和风速、有效波高之间的关系,创建海况偏差核函数非参数模型(NPSSB),并与参数模型中具有代表性的BM3、BM4模型进行对比。研究表明:(1)核函数NPSSB模型能够很好的反映SSB与U、SWH之间的关系,SSB与U呈二次函数关系,SSB与SWH呈反比例函数关系;(2)核函数NPSSB模型对SSB的模拟能力与训练数据集相关,数据量越多,模拟能力越好;(3)核函数NPSSB模型与BM3、BM4模型都存在0^-0.03 m的差值,随着风速和有效波高的增加,差值的绝对值越大。     

The relationship between the amplitudinal characteristics of the high-frequency spectral components of wind-generated waves and the wind velocity over the sea

The relationship between the RMS amplitudes of the wind wave spectral components and the wind speed has been studied at ten frequencies in the band of 0.65–23 Hz. To measure the parameters of the high-frequenci waves, a resistance elevation wave gauge was operated, which was deployed in the Black See on an oceanographic platform near Katsively. The correlation between the wave amplitudes and the wind velocity at high frequencies of 5–23 Hz, corresponding to gravitation-capillary ripples, was found to reach a value of 0.8. At lower frequencies of 0.65–4.3 Hz, corresponding to short gravity waves, it dropped to 0.5–0.7. The response of spectral components to the wind speed variations in the gravity-capillary range is higher than in the range of short gravity waves. The results obtained differ from Phillips' idea about a saturated range for the frequency form of the spectrum of high-frequency gravity waves, since a linear dependence of the spectral amplitudes on the wind speed is established at a wind of force 1–8.Translated by Mikhail M. Trufanov.     

Triple diagram method for the prediction of wave height and period

Many formulations have been developed so far to predict the wave height and period from fetch length and wind blowing duration for a constant wind speed. This study aimed to predict wave parameters from fetch length and meteorological factors by using triple diagram methodology based on Kriging principles. Proposed model results were compared with Joint North Sea Wave Project (JONSWAP) model which is used so commonly in the ocean and coastal engineering studies. For the implementation of the methodology hourly wave and wind data were obtained from a buoy located in Lake Ontario. Numerical and graphical comparisons demonstrated that the proposed method outperforms the classical formulation.     

Comparison between M5′ model tree and neural networks for prediction of significant wave height in Lake Superior

Prediction of wave height is of great importance in marine and coastal engineering. Soft computing tools such as artificial neural networks (ANNs) are recently used for prediction of significant wave height. However, ANNs are not as transparent as semi-empirical regression-based models. In addition, neural networks approach needs to find network parameters such as number of hidden layers and neurons by trial and error, which is time consuming. Therefore, in this work, model trees as a new soft computing method was invoked for prediction of significant wave height. The main advantage of model trees is that, compared to neural networks, they represent understandable rules. These rules can be readily expressed so that humans can understand them. The data set used for developing model trees comprises of wind and wave data gathered in Lake Superior from 6 April to 10 November 2000 and 19 April to 6 November 2001. M5′ algorithm was employed for building and evaluating model trees. Training and testing data include wind speed (U₁₀) as the input variable and the significant wave height (H_s) as the output variable. Results indicate that error statistics of model trees and feed-forward back propagation (FFBP) ANNs were similar, while model trees was marginally more accurate. In addition, model tree shows that for wind speed above 4.7 m/s, the wave height increases nonlinearly by the wind speed.     

Growth of Wind Waves with Fetch in the Sea of Japan under Winter Monsoon Investigated Using Data from Satellite Altimeters and Scatterometer

By using wind vector fields observed by the NASA Scatterometer (NSCAT) and significant wave heights observed by the TOPEX/POSEIDON and European Remote Sensing Satellite-2 (ERS-2) altimeters, one-dimensional fetch growth of wind waves has been investigated under conditions of strong wind and high waves caused by the East Asian winter monsoon in the Sea of Japan. The evolution of fetch-limited wind waves can be observed by the altimeters along their ground tracks. The fetch is estimated by using vector wind fields observed by NSCAT. The derived growth characteristics of wind waves are compared with empirical relationships between the non-dimensional fetch and significant wave height proposed by previous studies. Good agreement is discernible with Toba's fetch graph formula normalized by the friction velocity, while Wilson's well-known formula normalized by the wind speed at a height of 10 m tends to underestimate the wave height under such severe conditions of high wind and very long fetch. This discrepancy is explained by the wind-speed dependence of the drag coefficient. A simple correction to Wilson's formula for the high wind conditions is proposed and compared with the observed data.     

两类典型台风路径影响下的黄、渤海海浪场特征研究

台风引起的海浪灾害对我国黄、渤海沿岸影响巨大,严重威胁相关区域人民群众生命财产安全.本文主要利用ERA5(the fifth generation European Center for Medium-Range Weather forecasts atmospheric reanalysis of the globa...     

A Practical bi-parameter formula of gas transfer velocity depending on wave states

The parameter that describes the kinetics of the air-sea exchange of a poorly soluble gas is the gas transfer velocity which is often parameterized as a function of wind speed. Both theoretical and experimental studies suggest that wind waves and their breaking can significantly enhance the gas exchange at the air-sea interface. A relationship between gas transfer velocity and a turbulent Reynolds number related to wind waves and their breaking is proposed based on field observations and drag coefficient formulation. The proposed relationship can be further simplified as a function of the product of wind speed and significant wave height. It is shown that this bi-parameter formula agrees quantitatively with the wind speed based parameterizations under certain wave age conditions. The new gas transfer velocity attains its maximum under fully developed wave fields, in which it is roughly dependent on the square of wind speed. This study provides a practical approach to quantitatively determine the effect of waves on the estimation of air-sea gas fluxes with routine observational data.     

1988—2009年中国海波候、风候统计分析

利用高精度、高时空分辨率、长时间序列的CCMP(Cross-Calibrated,Multi-Platform)风场,驱动国际先进的第三代海浪模式WAVEWATCH-Ⅲ(WW3),得到中国海1988年1月～2009年12月的海浪场。对中国海的波候(风候)进行精细化的统计分析,分析了海表风场和浪场的季节特征、极值风速与极值波高、风力等级频率和浪级频率、海表风速和波高的逐年变化趋势,结果显示:(1)中国海的海浪场与海表风场具有较好的一致性,尤其是在DJF(December,January,February)期间;海表风速和波高在MAM(March,April,May)期间为全年最低,在DJF期间达到全年最大;MAM和JJA(June,July,August)期间,中国海大部分海域的波周期在3～5.5s,SON(September,October,November)和DJF期间为4.5～6.5s。(2)中国海极值风速、极值波高的大值区分布于渤海中部海域、琉球群岛附近海域和台湾以东广阔洋面、台湾海峡、东沙群岛附近海域、北部湾海域、中沙群岛南部海域。(3)吕宋海峡在MAM、SON、DJF期间均为6级以上大风和4m以上大浪的相对高频海域,JJA期间,6级以上大风的高频海域位于中国南半岛东南部海域,4m以上大浪主要出现在10°N以北。(4)在近22a期间,中国海大部分海域的海表风速、有效波高呈显著性逐年线性递增趋势,风速递增趋势约0.06～0.15m.s-1.a-1,波高递增趋势约0.005～0.03m.a-1。     

基于ERA-Interim再分析资料的南沙海域风、浪场特征分析

基于ERA-Interim再分析资料,统计分析了南沙海域的风场、海浪场的时空特征,并进一步研究了风浪成长关系,建立了适用于南沙海域的风浪模型。月平均场分析结果表明:在季风期,南沙海域的月平均有效波高与风场的时空分布特征有良好的对应关系,位于中南半岛的东南部存在一个风速和有效波高的大值中心,冬季强于夏季,中心位置随季节转换稍向下风向移动。频率分析结果表明:南沙海域全年以4级以内风力和3级以内海浪出现的频率最高,6级以上大风和5级以上海浪主要出现在冬季风期间;全年最大风速和浪高出现在10、11月,最大风速达到8级,最大有效波高可达6级,但频率非常小;整个海域风速和浪高最小的时期是4—5月。     

Characteristics of abnormal waves in North Sea storm sea states

A data set of storm wave records from the North Sea is analysed. Using current definitions of abnormal waves, eight of the largest wind waves are defined as abnormal waves. Twenty-four of the largest waves in time series, with a height larger than 10 m and with big vertical asymmetry are chosen for further analysis. Their individual characteristics are investigated and related to the global sea state characteristics. A comparison between measured data, second-order theory predictions and offshore basin data is made. The results for the chosen waves do not coincide with predictions of second-order theory. Considering that wind wave is second- and third-order non-linear, a new relationship between skewness and kurtosis is proposed for the sea states in which extremely asymmetric large waves have occurred. Another relationship between kurtosis and abnormality index of maximum waves is proposed too.     

The temporal and spatial variations in the Pacific wind and wave fields for the period 2002–2011

本文利用第三代海浪模式（WAVEWATCH III）分析了2002-2011年太平洋风速和海浪场的时空变化特征。首先,使用浮标观测数据对模式模拟的有效波高结果进行验证。结果表明模式可以有效地后报太平洋的有效波高。模式偏差较大的区域为中低纬度地区。随后将太平洋分为多个子区域,分别讨论了其风速和有效波高的时空变化特征。多年平均太平洋风速和有效波高存在类似的纬向分布特征,各子区域之间风速和有效波高的季节变化存在差别。模式刻画的太平洋有效波高年际变化最大的区域为南半球中高纬区域。进一步,我们研究了波浪能量的输入与耗散。相应的源函数项的各区域平均值显示了量化的表面波的变化。最后,对日平均的风速与有效波高值进行功率谱分析寻找序列的显著周期。结果表明有效波高时间变化对应的频谱和风速谱具有一定的差异。     

OSMAR-S100便携式高频地波雷达海浪和海面风探测性能分析

OSMAR-S系列便携式高频地波雷达系统采用单极子/交叉环紧凑型天线阵,通过单站雷达即可实现有效探测距离约10km内海浪和海面风的单点观测。为了更好地了解OSMAR-S100雷达系统海浪和海面风的综合探测性能,于2013年1月29日至3月7日在台湾海峡西南部海域进行了雷达与浮标观测的对比试验,得到了有效波高、有效波周期、平均风速和平均风向数据。对比结果表明,OSMAR-S100便携式高频地波雷达可有效观测距雷达10km以内有效波高0.5m以上的海浪平均状况和平均风速5m/s以上的海面风,雷达反演有效波高和有效波周期的均方根误差分别为0.60m和1.60s,反演平均风速和平均风向的均方根误差为1.83m/s和16.7°。在未经区域化标定的情况下,此结果说明了该型雷达产品已初步具备了海浪和海面风的业务化观测水平。     

SWAN模型中不同风拖曳力系数对风浪模拟的影响

本文以荷兰哈灵水道海域为实验区域,通过敏感性实验,研究了在14 m/s、31.5 m/s和50 m/s（分别代表一般大风、强热带风暴和强台风的极端条件）定常风速下SWAN模型中不同风拖曳力系数对风浪模拟的影响程度。结果表明,对于近岸浅水区域（水深小于20 m）,风拖曳力系数计算方案的选择对有效波高影响较小,而且当风速增加到一定程度后,波浪破碎成为影响波高值的主要因素;对于深水区域（水深大于30 m）,一般大风条件下风拖曳力系数计算方案的选择对有效波高影响仍然较小,随着风速的继续增大,风拖曳力系数计算方案的选择对有效波高的影响逐渐显著。对于平均周期,风拖曳力系数计算方案的选择和风速的改变对其影响均较小,而由水深变浅导致的波浪破碎对其影响较为显著。根据敏感性实验结果,本文对SWAN模型中风拖曳力系数计算方案的选择做出如下建议:计算近岸浅水区域风浪场或深水区域一般大风条件风浪场时,其风拖曳力系数可以直接采用模型默认选项;而对于深水区域更大风速条件,可首先采用模型默认选项试算,然后结合当地海域实测波浪资料进行修正。