Triple annual maximum series in wave climate analyses

A recurring problem in wave climate analyses is the need to predict long term events from short duration records. The relative sparsity of the observational record is enhanced by judicious recognition of near-maximum events, in addition to the annual maximum events. This paper pursues the application of triple annual maximum series. Given any extreme value distribution, the theoretical distributions for the annual second largest monthly wave and the annual third largest monthly wave are established. A maximum likelihood method is proposed to fit these simultaneous distributions to the triple annual maximum series. An application of the method to the historical record at the Farallon Is. off San Francisco adopts several of the more common extreme value distributions and demonstrates the potential of triple annual maximum series in enhancing the reliability of distribution fits. Nevertheless, the common practice of extrapolating short duration records to long term events remains precarious.     

The average impulse responce of a rough surface and its applications

This paper is concerned with the theoretical model for short pulse scattering from a statistically random planar surface with particular application to current state of the art radar altimetry. A short review of the assumptions inherent in the convolutional model is presented. Simplified expressions are obtained for both the impulse response and the average backscattered power for near normal incidence under the assumptions common to satellite radar altimetry systems. In particular, it is shown that the conventional two-dimensional surface integration can be reduced to a closed form solution. Two applications of these results are presented relative to radar altimetry, namely, radar antenna pointing angle determination and altitude bias correction for pointing angle and surface roughness effects. It is also shown that these results have direct application to the analysis of the two frequency system proposed by Weissman, and a possible combined long pulse altimeter and two frequency system is suggested.     

极浅海域潮流数值模型

通过对以往的浅水环流数值模型进行改进，建立适用于极浅水域的且能达到较高分辨率的潮汐环流数值模型。模型的主要特点是：（１）通过改进海底摩擦项的表达式来克服传统的二次方律在极浅的潮滩区所产生的不稳定问题；（２）采用逆风格式处理动量方程中的平流项，有效地抑制由于岸边界移动引起的数值短波的扩散。结合老虎滩湾海上工程的需要，利用本模型进行一系列的数值模拟试验。经过实测资料验证表明，改进后的模型具有良好的稳定     

基于多变量LSTM神经网络模型的PDO指数预测研究

利用1921–2020年的海平面气压、海平面高度、热含量数据以及海冰密集度作为太平洋年代际振荡（Pacific Decadal Oscillation, PDO）指数的预报要素,建立了关于PDO指数时间序列预测的多变量长短期记忆（Long Short Term Memory, LSTM）神经网络模型,对比分析了2011–2020年不同时间序列预测模型的PDO指数预测结果,最后利用多变量LSTM神经网络模型实现了2021–2030年的PDO指数预测。结果显示,多变量LSTM神经网络模型的预测值与观测值经过交叉验证后的平均相关系数和均方根误差分别为0.70和0.62;PDO未来10年将一直处于冷位相,PDO神经网络指数出现两次波动,于2025年出现最小值。相比于其他时间序列预测模型,本文采用的多变量LSTM神经网络模型预测结果误差小、拟合效果好,可以作为一种新型的预测PDO指数的手段。     

A predictive Mesoscale model of the erosion and profile development of soft rock shores

The development, application and behaviour of a generic model of retreating soft rock (e.g. clay) shores is described. This represents a broad system, in coastal modelling terms, comprising shore platform, beach, tidal range, wave transformation, cliff and talus. The coast is divided into a series of representative cross-shore profiles, each of which is discretised into a column of elements. Erosion of a platform element at each timestep depends on its gradient. Material strength is dealt with as a calibration constant, wave forces are averaged over durations of a tide or hour and sediment transport is represented in bulk terms. Attention has been focussed on interaction between system parts and the emergence of system properties, in particular profile shape. This is allowed to develop towards dynamic equilibrium and is the principal means of model validation. The emergence of the profile shape is dominated by the distribution of wave scour by the tide and by interaction with a beach, if present. Because the model is process-based, it may be used to model the effects of climate change and engineering intervention. Yet it is also computationally inexpensive, so may be used to explore uncertainty through probabilistic application. The breadth of the included system, coupled with short run-times, enables predictions over timescales of decades, which we refer to as the Mesoscale. The model is used to explore the dynamics of retreating soft rock shore profiles and to predict future behaviour of a study site.     

Nonlinear Model of Mean Free Surface of Waves

-A nonlinear model of mean free surface of waves or wave set-up is presented.The model isbased on that of Roelvink(1993),but the numerical techniques used in the solution are based on theWeighted-Average Flux(WAF)method(Watson et al,1992),with Time-Operator-Splitting(TOS)usedfor the treatment of the source terms.This method allows a small number of computational points to beused,and is particularly efficient in modeling wave set-up.The short wave(or primary wave)energy equa-tion is solved by use of a more traditional Lax-Wendroff technique.A nonlinear wave theory(James,1974)is introduced.The model described in this paper is found to be satisfactory in most respects whencompared with the measurements conducted by Stive(1983)except in modeling the mean free surface veryclose to the mean shoreline.     

Long Waves Associated with Bichromatic Waves

A numerical model of low frequency waves is presented. The model is based on that of Roelvink (1993), but the nu-merical techniques used in the solution are based on the so-called Weighted-Average Flux (WAF) method with Time-Operator-Splitting (TOS) used for the treatment of the source terms. This method allows a small number of computational points to be used, and is particularly efficient in modeling wave setup. The short wave (or primary wave) energy equation is solved with a traditional Lax-Wendroff technique. A nonlinear wave theory is introduced. The model described in this paper is found to be satisfactory in modeling low frequency waves associated with incident bichromalic waves.     

Estimation of mean spectral directions in random seas

A method for obtaining the directional spectrum, on assuming that the frequencies of the elementary waves are all different from one another, is re-proposed in a form suitable for applications to sea states near a coast. The method is applied to an interval of 10 h during which the sea state remained basically steady state off the beach at Reggio Calabria (east coast of the Straits of Messina). It is shown that the directional spectrum converges as the length of the time series data grows. A numerical simulation of a 10 h sea state confirms that the directional spectrum converges as the length of the time series grows, and the convergence is onto the known directional spectrum used to make the numerical simulation. Through the numerical simulation, it is proved that the method, generally, is suitable for applications even with short time series of wind waves (duration of about 100T_p). Finally, it is shown that the method is not necessarily inadequate even with short records of multimodal sea states with different modal directions, modal amplitude ratios and intermodal distances.     

A Numerical Model of Coastal Processes of Sand Beaches Based on Long-Term Wave Series

A numerical model of shoreline change of sand beaches based on long-term field wave data is proposed, the explicit and implicit finite difference forms of the model are described, and an application of the model is presented. Results of the application indicate that the model is sensitive to the order of the input wave data, and that the effects of long-term wave series and the effects of the mean annual wave conditions on the model are different. Instead of a single wave condition, the wave series will make the calibration and the verification of the model more practical and the results of the model more reasonable.     

Bivariate autoregressive models for the time series of significant wave height and mean period

This paper generalises the application of univariate models of the long-term time series of significant wave height to the case of the bivariate series of significant wave height and mean period. A brief review of the basic features of multivariate autoregressive models is presented, and then applications are made to the wave time series of Figueira da Foz, in Portugal. It is demonstrated that the simulated series from these models exhibit the correlation between the two parameters a feature that univariate series cannot reproduce. An application to two series of significant wave height from two neighbouring stations shows the applicability of this type of models to other type of correlated data sets.     

Toward an improved understanding of thruster dynamics forunderwater vehicles

This paper proposes a novel approach to modeling the four quadrant dynamic response of thrusters as used for the motion control of ROV and AUV underwater vehicles. The significance is that these vehicles are small in size and respond quickly to commands. Precision in motion control will require further understanding of thruster performance than is currently available. The model includes a four quadrant mapping of the propeller blades lift and drag forces and is coupled with motor and fluid system dynamics. A series of experiments is described for both long and short period triangular, as well as square wave inputs. The model is compared favorably with experimental data for a variety of differing conditions and predicts that force overshoots are observed under conditions of rapid command changes. Use of the model will improve the control of dynamic thrust on these vehicles     

Temporal and azimuthal dependence of sound propagation in shallowwater with internal waves

The short time scale (minutes) and azimuthal dependence of sound wave propagation in shallow water regions due to internal waves is examined. Results from the shallow water acoustics in random media (SWARM-95) experiment are presented that reflect these dependencies. Time-dependent internal waves are modeled using the dnoidal solution to the nonlinear internal wave equations, so that the effects of both temporal and spatial variability can be assessed. A full wave parabolic equation model is used to simulate broadband acoustic propagation. It is shown that the short term temporal variability and the azimuthal dependence of the sound field are strongly correlated to the internal wave field     

Generating extreme ship responses using non-uniform phase distributions

Modified Gaussian phase distributions are used to generate short time series containing a specific extreme value of a ship response. The corresponding incident wave train is calculated via linear systems theory. Sample response and wave time series are compared to the expected time series as calculated by probabilistic analysis. The average of the sample response time series compares favorably to the expected time series, but the average of the sample wave trains does not, in general, match the expected wave train. These comparisons show the danger in estimating extreme ship responses considering only extreme waves. A sample analysis for a Great Lakes bulk carrier is included for illustration.     

Analytic study to wave scattering by a general Homma island using the explicit modified mild-slope equation

In this paper, an exact analytic solution in terms of Taylor series to the explicit modified mild-slope equation (EMMSE) for wave scattering by a general Homma island is constructed and the convergence of the series solution is analyzed. To validate the new analytic solution, comparisons are made against the existing solutions including analytic solutions to both the long-wave equation and Helmholtz equation, approximate analytic solutions to the modified mild-slope equation, numerical solutions to the mild-slope equation and experimental solutions. Because of the use of the governing equation EMMSE together with mass-conserving matching conditions along the toe of the shoal, the present model is valid for not only waves in the whole spectrum from long waves to short waves but also bathymetries with the maximal seabed slope being as high as 4.27:1. Since the general Homma island is an extension of the original Homma island, the present solution can be very conveniently used to study the effects of bottom topography on combined refraction and diffraction. It is found that the larger the shoal size is, the more significant the wave amplification against the cylinder is.     

基于多变量LSTM神经网络模型的风暴潮临近预报

台风的风暴潮是台风引发的一种重要次生灾害,对沿海城市带来的威胁是多方面的。及时准确地预报风暴潮,对沿海地区采取合理措施减少人员伤亡和经济损失具有重要意义。本文利用长短期记忆神经网络 （LSTM） 模型,综合考虑风速、 风向、气压等气象因素和前时序的潮位数据,建立了风暴潮的临近预报模型。结果表明,基于 LSTM 的临近预报模型具有相当的预报技巧,利用前时序的风速和风向数据以及潮位数据建立的模型可对风暴潮潮位进行准确地预测。研究还表明,仅考虑前时序潮位的预测模型误差最大,考虑气压后的模型预测能力有一定进步,而考虑风的要素以后,预测的效果提升更为明显。     

台风Bogus资料的四维变分同化试验

给出人造台风(即Bogus)资料同化方案,并用于生成台风的初始结构,同时用9608号台风进行了测试,资料同化和预报均采用第5代中尺度模式系统(The Fifth-Generation NCAR/Penn State Mesoscale Model,简称MM5),结果发现该方案能产生成熟台风的许多结构特征,对9608号台风的预报也有明显改进.模式的初始场更适合于预报模式,能有效抑制积分初期的旋转加强(即Spinup)现象;强度预报和路径预报都得到改善,Bogus资料同化方案的各时次路径预报误差均比Bogus资料直接嵌入方案的误差要小.     

A numerically effective calculation of sea water density

Accurate density calculation that includes pressure effects is achieved with negligible computational cost in the context of three-dimensional ocean modelling. Local linear (or quadratic) fits to the full UNESCO (Anon, 1981) equation of state can be used in many model applications where the potential temperature and salinity at a model grid point vary slightly in each model time step. The local polynomial fit is achieved by computing a Taylor series expansion about a local reference state. The terms in the Taylor series are calculated analytically for optimal accuracy and minimal computational cost. All calculations can be done with single precision arithmetic, without compromising accuracy. In a three-dimensional nonhydrostatic ocean model applied to a deep convection problem, the local density calculation reduced the total computational cost of the model by 7% relative to that when the full UNESCO density calculation was used. The computational advantage is 15% for an application in which the nonhydrostatic part of the calculation is turned off. The computational advantage is, however, a function of the nature of both the model being used and the problem being solved.The principal algorithms are coded in Fortran 90, fortran 77, and as Matlab functions. The complete set of routines and test programs is coded in Fortran 90.     

基于EMD-LSTM模型半潜平台运动极短期预报

半潜平台在复杂海洋环境作用下,会发生不规则的六自由度运动响应。这种平台运动的不规则性和随机性对平台作业、栈桥控制以及直升机起落等造成极大的不确定和未知风险。因此,在极短期内准确快速预报平台运动响应对深海浮式平台作业和设备安全具有重要的实际意义。然而目前针对浮式平台运动响应的计算主要是基于势流理论,对确定波浪激励下的平台一阶运动和二阶慢漂运动进行求解,计算的时效性不能满足实际需求。此外,还需要对入射波浪时历进行准确预报,导致平台运动响应准确计算更加困难。针对上述难题,提出了基于EMD-LSTM模型进行平台运动极短期预报的方法。该方法以半潜平台模型试验数据为研究对象,首先对平台运动响应的时间序列进行预处理,接着采用经验模态分解算法(EMD)将时间序列分解成相对平稳的分量,再利用长短期记忆(LSTM)神经网络可以处理复杂非线性长时间序列的优点,对时间序列进行训练预测,最后进行仿真,同时与传统LSTM模型与EMD-BP模型进行对比,仿真结果表明基于EMD-LSTM模型的平台极短期预报方法精度较高,该方法是可行的,具有工程应用的实际意义。     

Prediction of wave parameters by using fuzzy logic approach

The purpose of this study is to investigate the relationship between wind speed, previous and current wave characteristics. It is expected that such a non-linear relationship includes some uncertainties. A fuzzy inference system employing fuzzy IF–THEN rules has an ability to deal with ill-defined and uncertain systems. Compared with traditional approaches, fuzzy logic is more efficient in linking the multiple inputs to a single output in a non-linear domain. In this paper, a sophisticated intelligent model, based on Takagi–Sugeno (TS) fuzzy modeling principles, was developed to predict the changes in wave characteristics such as significant wave height and zero up-crossing period due to the wind speed. Past measurements of significant wave height values 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 such as 1, 3, 6 and 12 h. The verification of the proposed model is achieved through the wave characteristics time series plots and various numerical error criterias. Also the model results were compared with classical Auto Regressive Moving Average with exogenous input (ARMAX) models. For the application of the proposed approach the offshore station located in the Pacific Ocean was used.     

Modelling the long-term time series of significant wave height with non-linear threshold models

Linear autoregressive models and non-linear threshold autoregressive (TAR) models are used in the present work to describe the time series of the significant wave height of sea-states at Figueira da Foz, located in the Portuguese coast. The seasonal components of this series are identified and a TAR model with two regimes is proposed. A simulation study was carried out with the purpose of verifying if both the non-linear and linear models are suited to describe the probabilistic structure of the process. It is shown that both methods are adequate to describe the lower statistical moments of the original data, but the non-linear model represents better the skewness and the kurtosis of the data.