A hybrid efficient method to downscale wave climate to coastal areas

Long-term time series of sea state parameters are required in different coastal engineering applications. In order to obtain wave data at shallow water and due to the scarcity of instrumental data, ocean wave reanalysis databases ought to be downscaled to increase the spatial resolution and simulate the wave transformation process. In this paper, a hybrid downscaling methodology to transfer wave climate to coastal areas has been developed combining a numerical wave model (dynamical downscaling) with mathematical tools (statistical downscaling). A maximum dissimilarity selection algorithm (MDA) is applied in order to obtain a representative subset of sea states in deep water areas. The reduced number of selected cases spans the marine climate variability, guaranteeing that all possible sea states are represented and capturing even the extreme events. These sea states are propagated using a state-of-the-art wave propagation model. The time series of the propagated sea state parameters at a particular location are reconstructed using a non-linear interpolation technique based on radial basis functions (RBFs), providing excellent results in a high dimensional space with scattered data as occurs in the cases selected with MDA. The numerical validation of the results confirms the ability of the developed methodology to reconstruct sea state time series in shallow water at a particular location and to estimate different spatial wave climate parameters with a considerable reduction in the computational effort.     

A simplified method to downscale wave dynamics on vertical breakwaters

A coastal structure is usually designed with the final objective to guarantee its functionality and stability throughout its life cycle. Regarding stability, the three main failure modes are sliding, overturning and failure of the foundations. To accomplish the design objectives, a design sea state is usually used when calculating the loads and scour around the structure. This design sea state corresponds to a certain sea state with specific return period values of a significant wave height. However, the combination of different simultaneous sea state parameters can produce other critical situations compromising the stability of the structure which then require the calculation of long time series of wave forces corresponding to long-term historical wave situations. Moreover, a design force associated to a certain return period can be defined from the time series of the stability parameters. The most accurate techniques which can be used to estimate structure stability are based on numerical and physical models, but these are very time consuming and the calculation of long time series is therefore unfeasible. Here, we propose a hybrid methodology to transform wave conditions into wave forces acting upon vertical structures and scour around it. The methodology consists of a selection of a subset of sea states representative of wave climate at the structure location, using a maximum dissimilarity algorithm, The wave forces acting upon the structure and scour around it, for the wave situations selected, are then estimated as is the reconstruction of the calculated parameters corresponding to historical sea states using an interpolation technique based on radial basis function. The validation of the results, through a direct comparison between reconstructed series and analytically (semi-empirical formulations) calculated ones, confirms the ability of the developed methodology to reconstruct time series of stability parameters on vertical breakwaters. This methodology allows its application to numerical and physical models.     

High resolution downscaled ocean waves (DOW) reanalysis in coastal areas

Large-scale wave reanalysis databases (0.1°–1° spatial resolution) provide valuable information for wave climate research and ocean applications which require long-term time series (> 20 years) of hourly sea state parameters. However, coastal studies need a more detailed spatial resolution (50–500 m) including wave transformation processes in shallow waters. This specific problem, called downscaling, is usually solved applying a dynamical approach by means of numerical wave propagation models requiring a high computational time effort. Besides, the use of atmospheric reanalysis and wave generation and propagation numerical models introduce some uncertainties and errors that must be dealt with. In this work, we present a global framework to downscale wave reanalysis to coastal areas, taking into account the correction of open sea significant wave height (directional calibration) and drastically reducing the CPU time effort (about 1000 ×) by using a hybrid methodology which combines numerical models (dynamical downscaling) and mathematical tools (statistical downscaling). The spatial wave variability along the boundaries of the propagation domain and the simultaneous wind fields are taking into account in the numerical propagations to performance similarly to the dynamical downscaling approach. The principal component analysis is applied to the model forcings to reduce the data dimension simplifying the selection of a subset of numerical simulations and the definition of the wave transfer function which incorporates the dependency of the wave spatial variability and the non-uniform wind forcings. The methodology has been tested in a case study on the northern coast of Spain and validated using shallow water buoys, confirming a good reproduction of the hourly time series structure and the different statistical parameters.     

A methodology for deriving extreme nearshore sea conditions for structural design and flood risk analysis

Extreme sea conditions in the nearshore zone are required for coastal flood risk analysis and structural design. Many multivariate extreme value methods that have been applied in the past have been limited by assumptions relating to the dependence structure in the extremes. A conditional extremes statistical model overcomes a number of these previous limitations. To apply the method in practice, a Monte Carlo sampling procedure is required whereby large samples of synthetically generated events are simulated. The use of Monte Carlo approaches, in combination with computationally intensive physical process models, can raise significant practical challenges in terms of computation. To overcome these challenges there has been extensive research into the use of meta-models. Meta-models are approximations of computationally intensive physical process models (simulators). They are derived by fitting functions to the outputs from simulators. Due to their simplified representation they are computationally more efficient than the simulators they approximate.Here, a methodology for deriving a large Monte Carlo sample of extreme nearshore sea states is described. The methodology comprises the generation of a large sample of offshore sea conditions using the conditional extremes model. A meta-model of the wave transformation process is then constructed. A clustering algorithm is used to aid the development of the meta-model. The large sample of offshore data is then transformed through to the nearshore using the meta-model. The resulting nearshore sea states can be used for the probabilistic design of structures or flood risk analysis. The application of the methodology to a case study site on the North Coast of Spain is described.     

Analysis of clustering and selection algorithms for the study of multivariate wave climate

Recent wave reanalysis databases require the application of techniques capable of managing huge amounts of information. In this paper, several clustering and selection algorithms: K-Means (KMA), self-organizing maps (SOM) and Maximum Dissimilarity (MDA) have been applied to analyze trivariate hourly time series of met-ocean parameters (significant wave height, mean period, and mean wave direction). A methodology has been developed to apply the aforementioned techniques to wave climate analysis, which implies data pre-processing and slight modifications in the algorithms. Results show that: a) the SOM classifies the wave climate in the relevant “wave types” projected in a bidimensional lattice, providing an easy visualization and probabilistic multidimensional analysis; b) the KMA technique correctly represents the average wave climate and can be used in several coastal applications such as longshore drift or harbor agitation; c) the MDA algorithm allows selecting a representative subset of the wave climate diversity quite suitable to be implemented in a nearshore propagation methodology.     

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.     

河北曹妃甸沿海海平面变化分析

采用回归分析方法,对曹妃甸现有海平面数据与邻近的塘沽沿海相对应的海平面数据进行相关分析,用建立的回归方程及塘沽历史海平面时间序列,推算了曹妃甸历史海平面时间序列,进而分析了曹妃甸海平面变化特征,同时预测了曹妃甸未来海平面可能上升的高度。分析结果表明:曹妃甸沿海海平面1951—2013年呈长期波动上升趋势,变化年速率为3.2mm/a;1980—2013年上升加快,变化年速率为6.6mm/a,高于同期中国沿海海平面的上升速率;20世纪90年代至2013年上升更进一步加快,变化年速率为11.1mm/a。可为曹妃甸沿海城市规划、滨岸工程设计和防灾减灾提供参考。     

Wave height statistics for seakeeping assessment of ships in the Adriatic Sea

The paper presents methodology and results of the development of sea states statistics for the Adriatic Sea. Such statistics is still lacking despite a need of the shipping industry. The presented study is based on the Atlas of Climatology containing statistics of sea states observations in the Adriatic Sea made by merchant ships during the period of 15 years. The results, presented in the Atlas in the form of “wave roses”, are digitalized and empirical frequencies of sea state occurrences are obtained. The 3-parametric Weibull distribution is then fitted through empirical data points enabling the “smoothening” of the histogram. The resulting histogram is compared with other studies for the long-term prediction of the sea states in the Adriatic Sea. The paper concludes with the discussion on the accuracy and applicability of the results.     

Prediction of Height and Period Joint Distributions for Stochastic Ocean Waves

This article proposes a new methodology to predict the wave height and period joint distributions by utilizing a transformed linear simulation method. The proposed transformed linear simulation method is based on a Hermite transformation model where the transformation is chosen to be a monotonic cubic polynomial, calibrated such that the first four moments of the transformed model match the moments of the true process. The proposed new approach is applied for calculating the wave height and period joint distributions of a sea state with the surface elevation data measured at an offshore site, and its accuracy and efficiency are favorably validated by using comparisons with the results from an empirical joint distribution model, from a linear simulation model and from a second-order nonlinear simulation model.     

Coastal Wave Height Prediction using Recurrent Neural Networks (RNNs) in the South Caspian Sea

The prediction of wave parameters has a great significance in the coastal and offshore engineering. For this purpose, several models and approaches have been proposed to predict wave parameters, such as empirical, soft computing, and numerical based approaches. Recently, soft computing techniques such as recurrent neural networks (RNN) have been used to develop sea wave prediction models. In this study, the RNN for wave prediction based on the data gathered and the measurement of the sea waves in the Caspian Sea, in the north of Iran is used for this study. The efficiency of RNNs for 3, 6, and 12 hourly and diurnal wave prediction using correlation coefficients is calculated to be 0.96, 0.90, 0.87, and 0.73, respectively. This indicates that wave prediction by using RNNs yields better results than the previous neural network approaches.     

Rogue waves during Typhoon Trami in the East China Sea

As concluded from physical theory and laboratory experiment,it is widely accepted that nonlinearities of sea state play an important role in the formation of rogue waves;however,the sea states and corresponding nonlinearities of real-world rogue wave events remain poorly understood.Three rogue waves were recorded by a directional buoy located in the East China Sea during Typhoon Trami in August 2013.This study used the WAVEWATCHⅢmodel to simulate the sea state conditions pertaining to when and where those rogue waves were observed,based on which a comprehensive and full-scale analysis was performed.From the perspectives of wind and wave fields,wave system tracking,High-Order Spectral method simulation,and some characteristic sea state parameters,we concluded that the rogue waves occurred in sea states dominated by second-order nonlinearities.Moreover,third-order modulational instabilities were suppressed in these events because of the developed or fully developed sea state determined by the typhoon wave system.The method adopted in this study can provide comprehensive and full-scale analysis of rogue waves in the real world.The case studied in this paper is not considered unique,and rules could be found and confirmed in relation to other typhoon sea states through the application of our proposed method.     

Bio-logging of marine migratory species in the law of the sea

The use of advanced and emerging remote data-collection technologies, and in particular bio-logging of marine migratory species, raises fundamental questions about the scope of authority of coastal states to regulate marine scientific research in the waters under their jurisdiction. Bio-logging involves the attachment of devices to marine animals that collect and transmit data about their movements and aspects of the local marine environment, and is now routinely used by marine scientists to support conservation programs and augment oceanographic data collection. Tagged marine life, including seabirds, marine mammals, sea turtles and pelagic fishes, may interact unpredictably with the territorial seas and exclusive economic zones (EEZs) of numerous coastal states. This article explores the legal implications of bio-logging within the legal regime of marine scientific research in the law of the sea. Although bio-logging is a form of marine scientific research, when it is initiated outside a coastal state׳s jurisdiction it does not later fall within it, even if the tagged animals subsequently enters a coastal state׳s territorial sea or EEZ.     

Experimental Study of Overtopping on Sea Dikes and Coastal Flooding Under the Coupled Processes of Tides and Waves

Storm surges are cataclysmic natural disasters that occur along the coasts and are usually accompanied by large waves. The effects of coupled storm surges and waves can pose a significant threat to coastal security. Previous laboratory studies on the effects of storm surges and waves on coastal structures have typically utilized steady water levels and constant wave elements. An indoor simulation of the coupled processes of tides and waves is developed by adding a tide generation system to an existing laboratory wave basin to model continuous dynamic tide levels so that tide generation and wave-making occur synchronously in the pool. Specific experimental methods are given, which are applied to further study waves overtopping on artificial sea dikes and coastal flooding evolution under the coupled actions of tides and waves. The results of the overtopping discharge obtained by the test with a dynamic water level are compared with those obtained from steady water level tests and the existing empirical formula. In addition, the impacts of ecological coastal shelterbelts and structures on coastal flood processes and distributions are also investigated. The proposed simulation methods provide a new approach for studying the effects of storm surges and waves on coastal areas. The study also aims to provide a reference for coastal protective engineering.

     

非结构网格模型在闽东沿海台风浪模拟中的应用

基于加密的非结构三角网格,以Holland模型风场叠加美国国家环境预报中心（NCEP）海面风场构造的合成风场驱动第三代浅水波浪数值模型（SWAN）对2017年影响闽东海域的“纳沙”和“泰利”台风过程进行数值模拟,并运用浮标站的实测数据对模拟结果进行验证.结果表明,模型计算的风速、有效波高与实测值符合较好,合成风场能较好地模拟台风期间的风速变化过程,SWAN模式能够合理地再现闽东沿海台风浪的时空分布特征.由模拟结果可见：台风“纳沙”中心越过台湾岛进入台湾海峡北部海面,受海峡地形的约束,其波浪场呈NE—SW向椭圆状分布,北部海域的浪高大于南部,闽东沿海遍布大范围的巨浪到狂浪;超强台风“泰利”未登陆闽东,当其台风中心与大陆的距离最近时,海面波浪场分布与台风风场结构一致,台风中心附近海域为14 m以上的怒涛区,巨浪遍布于闽东沿海.研究结果可为闽东沿海台风浪灾害预警和应急管理提供技术支撑和参考依据.     

The impact of sea level rise and climate change on inshore wave climate: A case study for East Anglia (UK)

In coastal areas, offshore wave propagation towards the shore is influenced by water depth variations, due to sea bed bathymetry, tides and surges. Considering implications of climate change both on atmospheric forcing and sea level rise, a simple methodology involving numerical modelling is implemented to compute inshore waves from 1960 to 2099. Simulations take into account five scenarios of linear sea level rise and one climatic scenario for storm surges and offshore waves. The methodology is applied to the East Anglia coast (UK). Extreme event analysis is performed to estimate climate change implication on inshore waves and the occurrence of extreme events. It is shown, for this coastal region, that wave statistics are sensitive to the trend in sea level rise, and that the climate change scenario leads to a significant increase of extreme wave heights in the northern part of the domain. For nearshore points, the increase of the mean sea level alters not only extreme wave heights but also the frequency of occurrence of extreme wave conditions.     

Development and application of a methodology for vulnerability assessment of climate change in coastal cities

This research is based on the need to develop methodology for climate change vulnerability assessment in coastal cities. While there have been some studies on the development of methodologies for vulnerability assessment on a national scale, there have been few attempts to develop a method for local vulnerability assessment with application to coastal cities. The objective of this study was to develop a general methodology to assess vulnerability to climate change and to apply it to the metropolitan coastal city of Busan in South Korea. We followed the conceptual framework for assessing climate change vulnerability provided by the Intergovernmental Panel on Climate Change (IPCC), which is composed of climate exposure, sensitivity, and adaptive capacity. Sea level rises of 0.5 m, 1 m, 2 m, and 3 m were considered as the climate exposure. Sensitivity to sea level rise was measured based on the percentage of flooded area calculated using flood simulation with a GIS tool. The population density and the population at age 65 years and over were also included in the calculation of sensitivity index. Sensitivities to heat wave and heavy rainstorm were quantified using the expert opinions from the Delphi survey and information on land use classification. Adaptive capacity was assessed in three sections: economic capability, infrastructure, and institutional capabilities. By combining the adaptive capacity and three different sensitivities, vulnerability to sea level rise (SLR-V), vulnerability to heavy rainstorm (HR-V), and vulnerability to heat wave (HW-V) were separately evaluated in 16 counties of Busan. Using cluster analysis, we could classify four major groups of counties based on SLR-V, HR-V, HW-V, and reported damage cost. For clustered groups, different adaptation strategies were suggested based on the different vulnerability patterns. Application of our methodology to Busan indicated that our methodology is easy to use and provides concrete policy implications when setting up adaptation strategies. The methodology developed in this study could also be used in mainstreaming climate change into Integrated Coastal Management (ICM).     

Climate change, sea level rise and integrated coastal zone management: An IPCC approach

Expansion of economic activities, urbanisation, increased resource use and population growth are continuously increasing the vulnerability of the coastal zone. This vulnerability is now further raised by the threat of climate change and accelerated sea level rise. The potentially severe impacts force policy-makers to also consider long-term planning for climate change and sea level rise. For reasons of efficiency and effectiveness this long-term planning should be integrated with existing short-term plans, thus creating an Integrated Coastal Zone Management programme.As a starting point for coastal zone management, the assessment of a country's or region's vulnerability to accelerated sea level rise is of utmost importance. The Intergovernmental Panel on Climate Change has developed a common methodology for this purpose. Studies carried out according to this Common Methodology have been compared and combined, from which general conclusions on local, regional and global vulnerability have been drawn, the latter in the form of a Global Vulnerability Assessment.In order to address the challenge of coping with climate change and accelerated sea level rise, it is essential to foresee the possible impacts, and to take precautionary action. Because of the long lead times needed for creating the required technical and institutional infrastructures, such action should be taken in the short term. Furthermore, it should be part of a broader coastal zone management and planning context. This will require a holistic view, shared by the different institutional levels that exist, along which different needs and interests should be balanced.     

ERA-Interim和ERA5再分析风资料在中国近海的适用性对比研究

全球再分析海面风资料在波浪模拟和风能资源评估等研究中发挥着重要作用，但风场资料种类繁多，且准确性在不同海域差异较大，使用时需要进行适用性分析。本文基于欧洲中期天气预报中心的ERA5和ERA-Interim再分析风场，利用多个站点的实测数据，分析了其在中国近海的适用性，并将再分析风场输入FVCOM-SWAVE波浪模型，对比了它们在常风天和台风天对波浪模拟的效果。结果表明：（1）常风天条件下ERA5和ERA-Interim资料在中国近海表现相似，风速较实测值略偏大，均能基本反映海表面风场变化和平均风速分布，吻合度指标在各站点均超过0.9;(2) ERA5对台风的模拟显著优于ERA-Interim，能较好模拟台风风速结构，对不同台风模拟精度差异大，整体上会低估台风风速；（3）风场质量是造成波浪模拟误差的主要原因之一，ERA5和ERA-Interim均能较好地模拟常海况下的波浪变化情况，而在台风浪的模拟中ERA5更优，“双台风”现象对风速和波浪的模拟准确度影响大。     

陆架海岸台风沉积记录及信息提取

长时间尺度风暴强度–频率关系与气候变化相关联,而器测记录和历史记载难以提供充分的信息,因此从沉积记录中提取风暴信息成为一个前沿科学问题。在应用上,这项研究可为海岸带城市群应对未来气候和海面变化提供决策依据。本文回顾了台风沉积记录研究进展,显示陆架泥质沉积、海滩及海岸沙丘、潮滩、潟湖、巨砾是台风事件记录的良好载体,可通过层序形态和物质特性分析而识别。同时,还需进一步完善分析方法,以区分台风、冬季风暴、河流洪水和海啸等不同类型的极端事件沉积。在台风强度信息提取方面,陆架泥质沉积所含贝壳–粗颗粒沉积物可作为海底再悬浮强度的指标,但需更多实测数据的率定;海滩及海岸沙丘顶部的台风沉积分布高程指示了台风激浪流的上冲高度,而台风巨砾的重量可以与近岸波浪的波高建立联系。以上数据经过换算后可以得出台风强度的信息,虽然这些间接的沉积学信息还不足以建立风暴强度–频率关系,但有助于台风强度大数据的建立。潮滩、潟湖沉积连续性好,可构成台风事件的时间序列,然而关于台风强度却是多解的,台风最大风力、持续时间、移动路径、登陆地点的不同组合可能产生同样的事件沉积。我们建议,应发展台风信息提取的新方法,来解决这个问题。进行现代过程模拟,根据已知的台风事件资料构建沉积物输运堆积模型,使之能够复演事件沉积的特征;进行多个地点事件沉积的反演模拟,在此情形下,即便每个站位的结果是多解的,但针对多个站位上求取其解的交集之后,多解性将下降,这种模拟方法可称之为“解空间收缩法”;采用大数据融合方式,将其他来源的台风强度数据纳入模拟体系,可进一步降低风暴信息提取的不确定性。动力过程模拟与大数据融合方法的建立,有助于获得与沉积记录同样时间尺度的台风强度–频率关系曲线,进而分析台风动态与气候变化的关系。