Deterministic non-linear wave prediction using probe data

The accurate prediction of non-linear sea states represents a great challenge, with a number of applications in oceanography, marine engineering, security of people and marine transportation, etc. In this paper, we report on the development of two efficient deterministic prediction models for 2D irregular wave-fields. These models are based on the exploitation of wave elevation time series given by one or more probes and on the use of two different numerical models for the wave-fields simulation. Two effective data assimilation processes are developed to improve the wave-field estimates obtained from the study of one or several probe signals, so that we obtain proper initial conditions for the forecast. The assimilation schemes have been validated on the reconstruction of model-generated observations and accurate predictions of the corresponding synthetic wave-fields evolution have been obtained.     

Near-optimal control of a wave energy device in irregular waves with deterministic-model driven incident wave prediction

This paper investigates wave-by-wave control of a wave energy converter using incident wave prediction based on up-wave surface elevation measurement. The goal of control is to approach the hydrodynamically optimum velocity leading to optimum power absorption. This work aims to study the gains in energy conversion from a deterministic wave propagation model that accounts for a range of group velocities in deriving the prediction. The up-wave measurement distance is assumed to be small enough to allow a deterministic propagation model, and further, both wave propagation and device response are assumed to be linear. For deep water conditions and long-crested waves, the propagation process is also described using an impulse response function (e.g. [1]). Approximate low and high frequency limits for realistic band-limited spectra are used to compute the corresponding group velocity limits. The prediction time into the future is based on the device impulse response function needed for the evaluation of the control force. The up-wave distance and the duration of measurement are then determined using the group velocity limits above.A 2-body axisymmetric heaving device is considered, for which power capture is through the relative heave oscillation between the two co-axial bodies. The power take-off is assumed to be linear and ideal as well as capable of applying the necessary resistive and reactive load components on the relative heave oscillation. The predicted wave profile is used along with device impulse response functions to compute the actuator force components at each instant. Calculations are carried out in irregular waves generated using a number of uni-modal wave spectra over a range of energy periods and significant wave heights. Results are compared with previous studies based on the use of instantaneous up-wave wave-profile measurements, both without and with oscillation constraints imposed. Considerable improvements in power capture are observed with the present approach over the range of wave conditions studied.     

基于Newton法优化ARMA模型参数的船舶升沉运动预测研究

为解决波浪补偿系统中时延现象导致的控制性能下降问题,通过建立Newton-ARMA模型提前预测船舶升沉运动来消除时延现象。首先设计卡尔曼滤波器对船舶升沉运动加速度信号进行降噪滤波处理;然后使用加速度二次积分模块将加速度信号转换为位移信号;最后建立自回归滑动平均(ARMA)模型,并使用牛顿(Newton)法对模型参数进行优化,得到船舶升沉运动的Newton-ARMA预测模型。仿真结果表明,Newton-ARMA模型对船舶升沉运动的预测时间可达10 s,预测误差随着预测时间的增加而增大; Newton-ARMA模型对二级海况、三级海况和四级海况下的船舶升沉运动平均预测精度分别达到89.43%、88.53%以及87.78%,远高于ARMA模型对船舶升沉运动预测的精度,说明采用Newton法优化ARMA模型参数可以显著提高船舶升沉运动的预测精度,也即Newton-ARMA模型对控制波浪补偿系统时延具有较好的补偿效果。     

Mathematical models for ship path prediction in manoeuvring simulation systems

The problem of simulating the ship manoeuvring motion is studied mainly in connection with manoeuvring simulators. Several possible levels of solution to the problem with different degrees of complexity and accuracy are discussed. It is shown that the structure of the generic manoeuvring mathematical model leads naturally to two basic approaches based respectively on dynamic and purely kinematic prediction models. A simplified but fast dynamic manoeuvring model is proposed as well as two new advances in kinematic prediction methods: a prediction based on current values of velocities and accelerations and a method of anticipating the ship's trajectory in a course changing manoeuvre.     

海洋资料同化对气候季节-年际预测技巧及初始场的影响试验

集合卡尔曼滤波(Ensemble Kalman filter, EnKF)是一种国内外广泛使用的海洋资料同化方案, 用集合成员的状态集合表征模式的背景误差协方差, 结合观测误差协方差, 计算卡尔曼增益矩阵, 有效地将观测信息添加到模式初始场中。由于季节、年际预测很大程度上受到初始场的影响, 因此资料同化可以提高模式的预测性能。本文在NUIST-CFS1.0预测系统逐日SST nudging的初始化方案上, 利用EnKF在每个月末将全场(full field)海表温度(sea surface temperature, SST)、温盐廓线(in-situ temperature and salinity profiles, T-S profiles)以及卫星观测海平面高度异常(sea level anomalies, SLA)观测资料同化到模式初始场中, 对比分析了无海洋资料同化以及加入同化后初始场的区别、加入海洋资料同化后模式提前1~24个月预测性能的差异以及对于厄尔尼诺-南方涛动(El Niño-southern oscillation, ENSO)预测技巧的影响。结果表明, 加入海洋资料同化能有效地改进初始场, 并且呈现随深度增加初始场改进越显著的特征。加入同化后, 对全球SST、次表层海水温度的平均预测技巧均有一定的提高, 也表现出随深度增加预测技巧改进越明显的特征。但加入海洋资料同化后, 模式对ENSO的预测技巧有所下降, 可能是由于模式误差的存在, 使得同化后的预测初始场从接近观测的状态又逐渐恢复到与模式动力相匹配的状态, 加剧了赤道太平洋冷舌偏西、中东部偏暖的气候平均态漂移。     

Exploring conventional tidal prediction schemes for improved coastal numerical forecast modeling

This study provides a practical guide to the use of classical tidal prediction algorithms in coastal numerical forecasting models such as tide and tide-storm-surge models. Understanding tidal prediction parameter formulas and their limitations is key to successfully modifying and upgrading tidal prediction modules in order to increase the accuracy of perpetual interannual simulations and, in particular, storm-surge modeling studies for tide-dominated coastal environments. The algorithms for the fundamental prediction parameters, the five astronomical variables, used in tidal prediction are collated and tested. Comparisons between their estimation using different parameterizations shows that these methods yield essentially the same results for the period 1900–2099, revealing all are applicable for tidal forecasting simulation. Through experiments using a numerical model and a harmonic prediction program, the effects of nodal modulation correction and its update period on prediction accuracy and sensitivity are examined and discussed using a case study of the tidally-dominated coastal regime off the west coast of Korea. Results indicate that this correction needs updating within <30 days for accurate perpetual interannual tidal and mean sea-level predictions, and storm-surge model predictions requiring centimeter accuracy, for tidally-dominated coastal regimes. Otherwise, unacceptable systematic errors occur.     

台湾地震区地震活动性的灰色预测

本文利用灰色系统理论中的GM(1,1)模型,对台湾地震区地震活动性进行预测,结果表明:①开始于1986年的第7个活动期将于1992年左右结束;②第7个平静期将于1993年左右开始并延续至1999年左右;③最近一次M_s=7.6级的大震发生在1986年11月15日,未来下一次7.5级以上地震预计将在1992年底发生,发震地区仍在本区的东带。     

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.     

中国近海海平面变化半经验预测方法研究

由于用数值模式预测未来海平面变化存在很大的不确定性,而统计预测方法又通常不考虑相关物理过程,为此Rahmstorf通过建立海平面变化与全球气温变化的相关模型,提出了一个可行的半经验方法预测全球海平面.本文将Rahmstoff模型应用于中国近海,初步建立了一个在气候变暖背景下中国近海海平面长期变化的预测方法,预测结果表明...     

浅水港口潮汐预报准调和方法的改进

文中提出了浅水港口潮汐预报准调和方法的两个改进方案.一个是在方国洪等(1981)《浅水港口潮汐预报的一个方法》基础上,增加14周/日、16周/日以及与前期潮汐状况有关的浅水准调和项共6项(方案Ⅰ);另一个在是王骥(2001)提出的方案基础上改进的方案,该方案与方案Ⅰ相比,增加了5个准调和项(方案Ⅱ).这两个方案选用相同的57个调和分潮,但分潮的组合及派生出的准调和项有所不同.方案Ⅰ用40项准调和项表示浅水效应,方案Ⅱ则包含长周期、全日、半日周期的准调和项18项.经过大量实测水位资料的分析和预报检验,表明改进后两个方案对浅水港口潮汐的预报精度均较改进前的准调和方法和传统调和法有明显提高,对第一类浅水港(以吴淞港为例),文中所列的8项预报指标都有显著提高,特别是低潮时均方差由26.8min降至15.1min;对第二类浅水港(以成山角为例),高潮时均方差显著减小,由39.6min减至26.7min.     

A model for numerical simulation of nonstationary sonar reverberation using linear spectral prediction

An innovative approach to the numerical generation of nonstationery reverberation time series is presented and demonstrated. The computer simulated reverberation time series are of high quality, in that they are accurate representations of those which would result from an actual sonar system (transmit/receive and horizontal/ vertical beampatterns; pulse type, shape, length, and power; frequency and sampling rate), platform (speed and depth), and environment (wind speed and direction, backscattering strengths, and propagation loss). Volume, surface, and/or bottom reverberation as seen by a multiple beam sonar on a moving platform is generated. The approach utilizes recent developments in linear spectral prediction research in which the spectra of stochastic processes are modeled as rational functions and algorithms are used to efficiently compute optimal estimates of coefficients which specify the spectra. A two-fold sequence is formulated; first, the expected reverberation spectra for all beams are predicted and, second, the stochastic time series are generated from the expected spectra. The expected spectra are predicted using a numerical implementation, referred to as the REVSPEC (reverberation spectrum) model, of a general formulation of Faure, Ol'shevskii, and Middleton. Given the spectra, the Levinson-Durbin method is used to solve the Yule-Walker equations of the autoregressive formulation of linear spectral prediction. The numerical implementation of the approach, referred to as the REVSIM (reverberation simulation) model, produces nonstationary coherent multiple-beam reverberation time series. The formulation of the REVSIM model is presented and typical results given. A comparison is made between the simulation outputs of the REVSIM model and those of the REVGEN (reverberation generator) model, a standard well-accepted time series simulation model, to demonstrate the validity of the new approach.     

Development of wavelet network model for accurate water levels prediction with meteorological effects

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).     

A new nudging scheme for the current operational climate prediction system of the National Marine Environmental Forecasting Center of China

A new nudging scheme is proposed for the operational prediction system of the National Marine Environmental Forecasting Center(NMEFC) of China, mainly aimed at improving El Ni?o–Southern Oscillation(ENSO) and Indian Ocean Dipole(IOD) predictions. Compared with the origin nudging scheme of NMEFC, the new scheme adds a nudge assimilation for wind components, and increases the nudging weight at the subsurface. Increasing the nudging weight at the subsurface directly improved the simulation performa...     

中国近海2011年灾害性海浪分析及2012年预测

总结分析了2011年中国近海有效波高为4 m以上的灾害性海浪过程及灾情概况,并对本年度的预测结果进行了检验评估。依据1968—2011年有效波高≧4 m的灾害性海浪的统计资料,结合2012年副热带高压及热带风暴的分析预测资料,预测了2012年中国近海灾害性海浪过程的出现次数,以及分海区的出现天数,预测结果可为今年的海洋防灾减灾提供技术支持。     

基于机器学习的海洋浮标寿命及轨迹预测

Argo计划(Array or Real-time Geostrophic Oceanography)为海洋和大气研究提供了宝贵的资料,在短期天气预报和长期气候预测中起到了重要作用.为保证Argo观测阵列的正常运转,需要时刻关注浮标的运行状态,以保证研究区域内维持一定数量和密度的浮标.然而Argo浮标投放费用高昂,投放...     

中国近海2012年灾害性海浪分析及2013年预测

总结分析了2012年中国近海有效波高≧4 m的灾害性海浪过程及灾情概况,并对2012年度的预测结果进行了检验评估。依据1968—2012年有效波高≧4 m的灾害性海浪的统计资料,结合2013年副热带高压及热带风暴的分析预测资料,预测了2013年中国近海灾害性海浪过程的出现次数,以及分海区的出现天数,预测结果可为今年的海洋防灾减灾提供技术支持。     

MDI地震属性技术在储层预测中的应用

地震资料在油气勘探中发挥着重要的作用。为了充分利用地震资料所提供的信息,需要使用地震属性技术进行储层预测。MDI是俄罗斯PANGEA公司研制的多属性储层预测系统。根据所研究的地震工区和目标的不同,在多种地震属性和岩石物性分析的基础上,运用这一预测系统可以利用多种定性或定量方法,综合多地震属性预测储层及含油气性,在实际工区中取得了一定的效果。     

基于BELLHOP 模型的宽带信号波形预报

为解决信号级声纳仿真系统的水声传输信道宽带信号波形预报问题,采用射线模型的基本原理,推导了基于射线的宽带水声信道响应函数.并在Pekeris环境条件下,分析比较了基于BELLHOP射线模型的时域宽带模型与基于BDRM模型的频域宽带模型波形预报结果.结果表明,水声信道具有典型的时域数字滤波器特征,其本质是对脉冲信号进行延迟、加权和求和,这种延迟求和会导致系统频域幅度响应函数呈现“梳状滤波器”形状.在一定条件下,射线模型与简正波模型具有同等计算精度,由于射线模型通过一次计算就能得到所有本征声线的幅度和延迟,相对于简正波模型来说,计算效率更高.同时利用射线模型,能够方便地选择接收特定角度出射的本征声线.     

基于双隐层ANN模型的叶绿素a浓度智能预报方法

利用2019年5月WZ02生态浮标监测数据,建立了两种不同隐层人工神经网络(ANN)模型的叶绿素a(Chl-a)智能预报方法,并对单隐层和双隐层模型的预测结果做了对比.结果表明:双隐层结构预测结果精度更高,泛化能力更强,一定程度上说明了深层学习比浅层学习对信息的主要特征提取能力更有优势.同时,对数据样本集合进行了系统预...     

地震资料极性判别技术在储层预测中的应用

在储层地震属性预测技术研究方面,过去人们关注的焦点主要集中于地震关键面时窗选取、地震属性选择和地震属性优化及融合等方面,很少注意到地震资料极性对储层预测效果的影响。实际应用表明,地震资料的极性判断错误,可能导致储层地震属性预测失败。针对这些问题,文章在论述如何判别地震极性的基础上,利用地震属性技术对渤海海域某构造储层的横向展布进行预测,取得了较好的效果。