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Based on the WAVEWATCH III wave model, China's National Marine Environmental Forecasting Center has developed an operational global ocean wave forecasting system that covers the Arctic region. In this study, in situ buoy observations and satellite remote sensing data were used to perform a detailed evaluation of the system's forecasting results for 2022, with a focus on China's offshore and global ocean waters, so as to comprehensively understand the model's forecasting performance. The study results showed the following: In China's coastal waters, the model had a high forecasting accuracy for significant wave heights. The model tended to underestimate the significant wave heights in autumn and winter and overestimate them in spring and summer. In addition, the model slightly underestimated low (below 1 m) wave heights, while overestimating them in other ranges. In terms of spatial distribution, negative deviations and high scatter indexes were observed in the forecasting of significant wave heights in semi-enclosed sea areas such as the Bohai Sea, Yellow Sea, and Beibu Gulf, with the largest negative deviation occurring near Liaodong Bay of the Bohai Sea (−0.18 m). There was a slight positive deviation (0.01 m) in the East China Sea, while the South China Sea exhibited a more significant positive deviation (0.17 m). The model showed a trend of underestimation for the forecasting of the mean wave period in China's coastal waters. In the global oceanic waters, the forecasting results of the model were found to have obvious positive deviations for most regions, with negative deviations mainly occurring on the east coast and in relatively closed basins. There were latitude differences in the forecasting deviations of the model: specifically, the most significant positive deviations occurred in the Southern Ocean, with smaller positive deviations toward the north, while a slight negative deviation was observed in the Arctic waters. Overall, the global wave model has high reliability and can meet the current operational forecasting needs. In the future, the accuracy and performance of ocean wave forecasting can be further improved by adjusting the parameterization scheme, replacing the wind fields with more accurate ones, adopting spherical multiple-cell grids, and data assimilation. [ABSTRACT FROM AUTHOR]

This study focusses on the processes that control the morphodynamics of the seabed in the shoaling wave domain, widely known as the shoreface. Shoreface morphodynamics is not only controlled by the local wave climate but also by associated wave- and wind-driven currents, the grain-size, and antecedent geomorphology. This paper provides basic information on sedimentological action of monochromatic waves at the seabed in the shoaling zone to the non-specialist without him-/herself having to solve the complex equations before arriving at workable solutions. It is emphasized that the traditional oceanographically defined wave base (0.5L0) is not relevant in a geological/sedimentological context and should be replaced by a grain-size dependent effective wave base (EWB). Furthermore, open ocean swell-dominated shorefaces have to be distinguished from those of marginal seas dominated by local wind-generated waves. For convenience, a collection of tables and diagrams are provided in the electronic supplementary material (ESM) attached to this paper. They highlight the depths of effective wave bases for a range of grain sizes, wave heights and wave periods between 2 and 16 s. [ABSTRACT FROM AUTHOR]

Experimental parameters of wind-driven waves obtained with a measuring pole near the coastal line of Lake Baikal using video recorders placed on a slightly submerged mast are analyzed in the present work. The measurements were carried out during the fall period. The short-period dynamics of the characteristics of surface wind-driven waves arising on the shallow water surface is analyzed. Dependences are established of the wave heights on the wind speed and direction in an open region of Lake Baikal in the daytime; their maxima are recorded in the second half of the day at the western wind direction. The temporal variations of the wave periods and heights are shown, and the nonlinear gravitational wave modes are detected on the shallow water surface. As a result of these processes, the short-period wave heights reach their maximum values. Radar measurements of the wind-driven wave characteristics have shown a dependence of the back-reflected signal intensities on the variations in the wind-driven wave heights. Small-scale inhomogeneities observed on the water surface in the form of ripples, responsible for backscattering of wind-driven wave crests, are well recognized with a nanosecond radar. [ABSTRACT FROM AUTHOR]

In this study, a deep learning network for extracting spatial-temporal features is proposed to estimate significant wave height ( H s ) and wave period ( T s ) from X-band marine radar images. Since the shore-based radar image in this study is interfered with by other radar radial noise lines and solid target objects, to ensure that the proposed convolutional neural network (CNN) extracts the image features accurately, it is necessary to pre-process the radar image to eliminate interference. Firstly, a pre-trained GoogLeNet is used to extract multi-scale depth space features from the radar images to estimate H s and T s . Since CNN-based models cannot analyze the temporal behavior of wave features in radar image sequences, self-attention is connected after the deep convolutional layer of the CNN to construct a convolutional self-attention (CNNSA)-based model that generates spatial-temporal features for H s and T s estimation. Simultaneously, H s and T s measured by nearby buoys are used for model training and reference. The experimental results show that the proposed CNNSA model reduces the RMSD by 0.24 m and 0.11 m, respectively, in H s estimation compared to the traditional SNR-based and CNN-based methods. In T s estimation, the RMSD is reduced by 0.3 s and 0.08 s, respectively. [ABSTRACT FROM AUTHOR]

Based on the WAVEWATCH III wave model, China’s National Marine Environmental Forecasting Center has developed an operational global ocean wave forecasting system that covers the Arctic region. In this study, in situ buoy observations and satellite remote sensing data were used to perform a detailed evaluation of the system’s forecasting results for 2022, with a focus on China’s offshore and global ocean waters, so as to comprehensively understand the model’s forecasting performance. The study results showed the following: In China’s coastal waters, the model had a high forecasting accuracy for significant wave heights. The model tended to underestimate the significant wave heights in autumn and winter and overestimate them in spring and summer. In addition, the model slightly underestimated low (below 1 m) wave heights, while overestimating them in other ranges. In terms of spatial distribution, negative deviations and high scatter indexes were observed in the forecasting of significant wave heights in semi-enclosed sea areas such as the Bohai Sea, Yellow Sea, and Beibu Gulf, with the largest negative deviation occurring near Liaodong Bay of the Bohai Sea (−0.18 m). There was a slight positive deviation (0.01 m) in the East China Sea, while the South China Sea exhibited a more significant positive deviation (0.17 m). The model showed a trend of underestimation for the forecasting of the mean wave period in China’s coastal waters. In the global oceanic waters, the forecasting results of the model were found to have obvious positive deviations for most regions, with negative deviations mainly occurring on the east coast and in relatively closed basins. There were latitude differences in the forecasting deviations of the model: specifically, the most significant positive deviations occurred in the Southern Ocean, with smaller positive deviations toward the north, while a slight negative deviation was observed in the Arctic waters. Overall, the global wave model has high reliability and can meet the current operational forecasting needs. In the future, the accuracy and performance of ocean wave forecasting can be further improved by adjusting the parameterization scheme, replacing the wind fields with more accurate ones, adopting spherical multiple-cell grids, and data assimilation.

Crew boat is a type of vessels used for the mobility of offshore workers and logistical supply needed for the offshore platform. Crew boat KCT-1901 is categorized as a planning boat with hard chine body. KCT-1901 requires an added power when it is sailing through a seaway. The reason behind this is because when a ship sails through a seaway, the ships experienced a heave and pitch motion resulted in added resistance and hence added power. The goal of the investigation is to estimate added resistance and added power of the crew boat using computational fluid dynamic (CFD) method and tested in calm water and in waves with several Froude numbers (Fr) and wave periods. A method developed by Savitsky is used for verification at high-speed mode. The largest total resistance using CFD in calm water is 38.98 kN and using Savitsky method is 39.00 kN obtained at Fr 0.72. Both are in good agreement and the discrepancy is less than 0.1%. Comparative study was carried out against experimental test in a towing tank. The drag forces tested at Fr 0.12 and 0.24, between the two approaches, showed a discrepancy of about 4%. Further CFD test was conducted on wave pattern analysis, which demonstrated that as the Fr increases the becomes clearer and stronger and tests in waves condition at lower wave period showed that the transverse wave becomes more apparent. Therefore, overall can be said that the CFD simulation showed such a good agreement with empirical Savitsky method and experimental tank test.

In this study, a deep learning network for extracting spatial-temporal features is proposed to estimate significant wave height (Hs) and wave period (Ts) from X-band marine radar images. Since the shore-based radar image in this study is interfered with by other radar radial noise lines and solid target objects, to ensure that the proposed convolutional neural network (CNN) extracts the image features accurately, it is necessary to pre-process the radar image to eliminate interference. Firstly, a pre-trained GoogLeNet is used to extract multi-scale depth space features from the radar images to estimate Hs and Ts. Since CNN-based models cannot analyze the temporal behavior of wave features in radar image sequences, self-attention is connected after the deep convolutional layer of the CNN to construct a convolutional self-attention (CNNSA)-based model that generates spatial-temporal features for Hs and Ts estimation. Simultaneously, Hs and Ts measured by nearby buoys are used for model training and reference. The experimental results show that the proposed CNNSA model reduces the RMSD by 0.24 m and 0.11 m, respectively, in Hs estimation compared to the traditional SNR-based and CNN-based methods. In Ts estimation, the RMSD is reduced by 0.3 s and 0.08 s, respectively.

The wave is one of the fundamental parameters in the evolution of a coastline. The knowledge of its detailed behavior, as it depends on different stochastic variables, is very complex. However, through the analysis of time series it is possible to have an idea of the wave conditions in a coastal area. This paper describes and analyzes the swell conditions in Santa Elena Bay, in the sector between Salinas and Salango beaches, in the period 2016-2020. Different wave conditions were simulated for each month of the study period, considering the variables significant wave height, period and wave direction, using the DELFT3D model, WAVE module. The results were compared with the Global Ocean Physics Reanalysis simulation, from two virtual buoys near the coast. According to the results, near the coast of Santa Elena Bay, wave conditions are found with heights from 0.60 m to 0.93 m, approach direction from 221.1° to 270.1° and periods from 11.5 s to 16.0 s. The results obtained allow us to have a continuous spatial grid of reference on the wave behavior in Santa Elena, which could be improved with field data over time. [ABSTRACT FROM AUTHOR]

Due to climate change, hydroclimatic extremes are becoming more frequent and intense and their characterization and analysis is essential for climate modelling. One of the regions that will be most affected by these extremes is the Mediterranean coast of Spain. Therefore, this paper analyses the significant wave height (Hs), peak wave period (Tp) and sea level (SL) extremes and their correlation along the Spanish Mediterranean coast. After conducting this analysis, it is finally concluded that and adjustment of the extreme long-term distribution of Tp is urgently needed to create accurate models and projections, which must be considered in combination with the intense extremes happening in the Levantine basin when modelling this area and designing new projects. [ABSTRACT FROM AUTHOR]

The constraint conditions have a great influence on the geometry of reservoir landslides during mass movement and are one of the most important parameters for predicting landslide-generated waves. To explore the effects of constraint conditions on the characteristics of landslide-generated waves (such as wave height, amplitude and period), 54 sets of landslide-generated wave physical model experiments based on the orthogonal experimental design method were conducted in this paper. Furthermore, the wave characteristics under constrained and semiconstrained conditions were analysed using statistical methods. The results indicate that the wave period is basically unaffected by the constraint conditions, while the wave height and amplitude of the semiconstrained model are smaller than those of the constrained model, the initial wave height of the semiconstrained model is approximately 0.95 times higher than that of the constrained model, and the maximum amplitude of the semiconstrained model is approximately 0.9 times that of the constrained model. Therefore, it is safer to predict the initial wave height and maximum amplitude by using the geometric parameters before failure, although the geometry of the landslide has been greatly changed from its original state.This study can provide a theoretical basis for landslide-tsunamis prediction.

Nature-based coastal protection that integrates vegetated wetlands for wave attenuation and erosion mitigation shows great potential. However, there is a lack of consensus on whether longer wave periods contribute to an increase or a reduction in the attenuation of waves in vegetated wetlands, which is primarily due to the disregard of vegetation submersion states. In the current study, we modified a classic model to pinpoint the conditional role of the period. Wave attenuation by vegetation is quantified as the product of two terms: wave decay rate and time of wave group travel through a unit length. By tracing the dynamics of these two terms, the model is in good agreement with the measurements and can well explain why wave attenuation increased with longer period (from 2 to 10 s) in submerged canopies (up to 10 times) but decreased in emergent canopies (by 75%). A maximum response period (2–10 s) was found, beyond which period has no effect on wave attenuation. Furthermore, we found that in field conditions, the variation in wave period can lead to a sharp reduction in wave dissipation. which is critical for coastal safety. For instance, a 62% decrease in wave period at Galveston Island corresponded to a 40% drop in wave dissipation. This work provides a comprehensive understanding on the role of wave period in wave dissipation by wetland vegetation, which would assist in safely implementing wetlands for coastal defence. • An analytical model was modified to simulate wave dissipation by vegetation. • The role of wave period is explained by combining wave decay rate and time of wave group travel through a unit length. • Period variation may sharply reduce the storm wave attenuation capacity of marshes. [ABSTRACT FROM AUTHOR]

• ANNs and Monte Carlo simulations are used to obtain future shallow water climate. • Monte Carlo simulations and statistics aid regional climate change projections. • ANNs exploit the data generated by Monte Carlo simulations. • An adaptation of the equation for Tp is necessary to reflect new climate conditions. • Up to 1.6 m increase in extreme Hs are expected in Western Mediterranean by 2050. This paper proposes a new model to study future coastal maritime climate under climate change context. This new model combines statistical analysis, Monte Carlo simulations and Artificial Neural Networks (ANNs). Statistical analysis and Monte Carlo simulations are used to extrapolate future wave climate under climate change context at a regional level and ANNs are used to propagate these projected sea states obtained in deep water to the coast. The use of ANNs allows for the utilization of large amounts of data at a very low computational cost, and the use of Monte Carlo simulations enables the generation of future climate change projections at a regional level. The combination of the two methodologies results in a very accurate (MSE of 0.02 m and 1 s) and computationally inexpensive hybrid model that allows projections of coastal maritime climate considering climate change. This new methodology has been validated and applied in the Western Mediterranean for the long-term regime and for extreme events, obtaining increases in extreme events up to 1.5 m in wave height and up to 1.8 s in wave period by 2050. [Display omitted] [ABSTRACT FROM AUTHOR]

A small-aperture receiving array occupying a small area provides convenience for the layout of high-frequency (HF) radars. However, this kind of antennas has a wide beam, which adversely affects the wave measurements. To solve this problem, a method for extracting wave parameters from wide-beam radar echoes, which models current variations across the beam, is proposed in this article. The nondirectional wave spectrum is extracted from the echoes of a small-aperture HF radar, and wave parameters such as the significant wave height, peak, and mean wave period are then calculated from it. Simulation is carried out to assess the performance of the method for different current velocities, radar frequencies, and wind conditions. The proposed method is then applied to a nine-day dataset collected by a multifrequency HF radar with a circular receiving array (MHF-C) radar for further validation via comparisons between the radar-estimated and the buoy-measured wave parameters. Some factors that may affect the performance of wave height measurements are analyzed, such as the signal-to-noise ratio and radial current velocity. The correlation coefficient (CC) between the radar-estimated and the buoy-measured significant wave height is 0.90, and the root mean square difference (RMSD) is 0.51 m. For the mean wave period, the CC is 0.61 and the RMSD is 0.67 s. The results demonstrate that the significant wave height and the mean wave period extracted by the proposed method are consistent with the buoy-measured values, and the proposed method can overcome the broadening influence of the Doppler spectrum caused by ocean currents. [ABSTRACT FROM AUTHOR]

The head of a breakwater warrants special consideration to achieve the necessary stability at vulnerable part of its structure. To widen the entrance to a harbour, a caisson is used for the breakwater head. Therefore, the wave force on the caisson head under oblique waves was analysed in this study. Physical model tests were performed in a wave tank, where wave loads on two weathering sections (S1 and S2) of the caisson head were measured under oblique-regular and irregular wave attacks. The results have shown that the improved Goda's method can predict the wave forces on the caisson head. The wave forces on the two sections increased with an increase in the period under different incident angles. The phase lag between the horizontal forces on S1 and S2 was evidently influenced by the incident angle. The relationship between the maximum wave force on one section and its accompanying wave force on another section was described, and the results have demonstrated that under the same incident angle, as the period increased, the maximum wave force of S1/S2 is gradually equal to its accompany wave force of another section. [ABSTRACT FROM AUTHOR]

In the future, shifts in wind storms across the North and Baltic Seas are highly unpredictable, challenging the projection of wave conditions for managing coastal hazards. Moreover, regional sea level rise (SLR), with very large uncertainty, complicates the situation for stakeholders seeking recommendations for climate adaptation plans. The purpose of this study is to examine the change of the storm surge and wind wave components of the water level due to climate change in a low tidal range Køge Bay near the entrance of the Baltic Sea. Under a high greenhouse gas emission scenario RCP8.5, we employed a regional climate model (HIRHAM) forced wave model (WAM) and focused on the wave model results during the “storm surge conditions” (exceeding 20 years storm surge events) and “stormy conditions” (exceeding 90th percentile of wave heights). We find that the change in both wave height and period in the future is negligible under “stormy conditions”. Nevertheless, under “storm surge conditions” when considering SLR, the simulated wave height is projected to double in the near future (mid-century) under RCP 8.5, and the wave period may also increase by about 1.5 seconds. This is because some high significant wave height events in the future are associated with the storm surge events when considering SLR. The findings suggest that the combined effects of mean sea level rise, storm surge and waves are likely to increase the risk to a bay with geography and exposure comparable to Køge Bay. As a result, the future plan for climate engineering protection should place a premium on the additional wave energy protection associated with storm surges.

Existing sheet flow experimental data show the measured time-averaged suspended sediment concentration (TSSC) may increase, decrease, or even remain constant if the wave period decreases. With respect to the available sheet flow experimental data, it is confirmed that the TSSC of relatively fine sand undergoes three stages, i.e. first decreases, then increases, and finally decreases again in the case that the wave period decreases from 12 s to 2 s, whereas for the relatively coarse sand, its vertical profile remains almost unchanged. The criterion for identifying the relatively fine or coarse sand was proposed in terms of the nondimensional ratio between the settling velocity and the root-mean-square flow velocity. If this ratio is less than 0.04–0.043, it is deemed as relatively fine sand. Otherwise, it is classified as relatively coarse sand. Applying the classical gradient diffusion model, sediment diffusivity is confirmed to be insensitive to the wave period. Keeping other experimental conditions uniform, TSSCs with different wave periods are proportional to each other and only affected by the reference concentration. Subsequently, a simple quantitative expression considering the wave period effect on the TSSC under the oscillatory sheet flow regime was proposed and verified with the experimental data. [ABSTRACT FROM AUTHOR]

In this paper, the accuracy of wave parameters of the European Centre for Medium-Range Weather Forecasting Reanalysis v5 (ERA5) in the South China Sea (SCS) is systematically examined with field measured data of two buoys at offshore sites and a subsea-based platform at a nearshore site, which has a total observational period of nearly three years. It is suggested that the wave parameters provided by ERA5, such as significant wave height (Hs) and mean wave period (Tm), are in good agreement with the observational data of the three sites. Compared with the in situ data, the correlation coefficient of ERA5 Hs is in the range of 0.87–0.93, and the root mean square error is only in the range of 0.22–0.57 m. The error of standard deviation does not exceed 0.29 m and is even as low as 0.04 m at two sites. The wave propagation directions of the ERA5 and in situ data are also basically the same. However, when the data are applied in engineering, some wave parameters extracted from ERA5 may deviate from the measured statistics. It is possible to significantly overestimate the average duration of a particular Hs. Further analysis shows that the possible errors of ERA5 wave parameters may be due to insufficient description of topographic conditions, which shows that the error value changes obviously with the wave direction. The results preliminarily confirm the validity of ERA5 data in the SCS, but also indicate that it is necessary to calibrate and validate the data adequately when applying the global model and its reanalysis data to specific ocean areas. [ABSTRACT FROM AUTHOR]

Maritime Autonomous Surface Ships are in the development stage and they play an important role in the upcoming future. Present generation ships are semi-autonomous and controlled by the ship crew. The performance of the ship is predicted using the data collected from the ship with the help of machine learning and deep learning methods. Path planning for an autonomous ship is necessary for estimating the best possible route with minimum travel time and it depends on the weather. However, even during the navigation, there will be changes in weather and it should be predicted in order to reroute the ship. The weather information such as wave height, wave period, seawater temperature, humidity, atmospheric pressure, etc., is collected by ship external sensors, weather stations, buoys, and satellites. This paper investigates the ensemble machine learning approaches and seasonality approach for wave data prediction. The historical meteorological data are collected from six stations near Puerto Rico offshore and Hawaii offshore. We explore ensemble machine learning techniques on the data collected. The collected data are divided into training and testing data and apply machine learning models to predict the test data. The hyperparameter optimization is performed to find the best parameters before fitting on train data, this is essential to find the best results. Multivariate analysis is performed with all the methods and errors are computed to find the best models. [ABSTRACT FROM AUTHOR]

The relationship between significant wave height ( H 1 / 3 ) and period ( T 1 / 3 ) was obtained using wave data from the East and Yellow coasts of the Korean Peninsula to facilitate the calculations of the wave parameters. In addition, the JONSWAP spectral parameters were estimated and analyzed for all wave height ranges. The relational expression between the two wave variables ( H 1 / 3 ~ T 1 / 3 ) obtained from this study showed a significant difference from the previously proposed relational expressions, most of which tended to follow the lower limit of the data. Meanwhile, the suggested peak enhancement factor (PEF,   γ ) is 1–7; however, for this study, a peak control factor (PCF,   γ c ) with a range of 0–10 was introduced. As a result of the analysis, the PCF was determined to be 1.13–1.42, which is approximately 40% smaller than the previously proposed γ   =   3.3 . The probability density distribution of the appropriate PCF was then calculated, and the gamma and log-normal distributions for the East and Yellow coasts of the Korean Peninsula were found, respectively. This study covered waves of all range heights, and the analysis results can be used as important data to explain the characteristics of the sea area. [ABSTRACT FROM AUTHOR]

Results from a comparative study of the joint distribution of surf parameter and wave period are provided. First, two transformed joint distributions of wave height and wave period are compared. One of the distributions is a parametric model originating from a best fit to relatively broad-band field data covering a wide range of wave conditions, whilst the other distribution is theoretically based. It appears that the theoretically based distribution does not represent the features of the parametric model especially well, suggesting that parametric models should be used to describe relatively broad-banded data. Then, the theoretically based joint distribution of wave height and wave period is transformed to the joint distributions of surf parameter with wave height and wave period and it is demonstrated how these distributions are affected by the spectral bandwidth. Finally, the theoretically based distribution of wave height and wave period is also transformed to the joint distribution of wave runup time and wave period due to its relation to the stability of rubble-mound breakwaters. Comparisons are made with a limited set of data representing results from small-scale laboratory experiments related to stability of rubble-mound breakwaters. The agreement between measurements and predictions of the distribution of the surf parameter is fair, whilst the agreement is poorer for the probability of resonance. [ABSTRACT FROM AUTHOR]

For the design and optimization processes of Oscillating Water Column (OWC) systems, knowledge of their hydrodynamic performance behavior is essential. While there have been extensive research efforts on understanding the hydrodynamic performance behavior of fixed-floating offshore OWCs, studies focusing on quantifying the effect of applied damping over a broad range of incoming wave heights are limited. Besides, no attempt has thus far been undertaken to optimize the hydrodynamic efficiency of fixed-floating offshore OWCs using the sequential optimization procedure proposed and used in a 2D onshore OWC in the literature. This paper addresses these omissions by deeply investigating the influence of wave height, wave period, and turbine damping parameters on the hydrodynamic performance behavior of a fixed-floating offshore OWC system. To realize these objectives, a nonlinear 3D incompressible Computational Fluid Dynamics (CFD) model based on the Reynolds-Averaged Navier-Stokes (RANS) equations and the Volume of Fluid (VOF) approach was implemented in the open-source OpenFOAM® suite to numerically simulate fluid-structure interaction under regular wave conditions. The validity of this numerical model was verified using experimental measurements in the literature, where a reasonably good correlation was achieved. The results demonstrate that the aforementioned design parameters strongly affect the device's hydrodynamic performance. It has also been shown through a sequential optimization approach that at an optimum wave period of 1.07 s, optimum wave height of 0.01948 m, and a pneumatic damping value of 0.02 m, about 87% of peak hydrodynamic efficiency is possible for the fixed-floating offshore OWC device used in the study. [ABSTRACT FROM AUTHOR]

The stability of an artificial pebble beach deposited in front of a concrete slope bank protection and a rock-fill berm during an upsurge of the Sea of Azov is investigated. Design features of coastal protection structures influencing the drift intensity of pebble material are considered. [ABSTRACT FROM AUTHOR]

Medium-long period waves significantly affect the construction of coastal engineering structures. This study investigated the interaction between regular waves and a vertical breakwater through laboratory experiments and smoothed particle hydrodynamics (SPH) simulations. Four SPH models, established using different diffusion terms and turbulence models, were compared. The numerical results were consistent with the test results. The experimental results and the improved Goda's results were consistent. The medium-long period wave force was 1.5–2 times greater than the short-period wave force. Consequently, a new formula was proposed to describe the relationship between the wave force and wave period. Furthermore, the energy evolution of wave propagation with and without a vertical breakwater was studied. It was found that the longer the period, the slower the attenuation of the wave kinetic and potential energies. The dynamic potential energy per unit length in front of the breakwater increased with an increase in the period.

Summary: In recent years, the penetration level of renewable energy generation units such as wave, wind, photovoltaic, and tidal power plants in the modern power systems has increased. It began in the 1970s with a sudden change in oil price and today, large‐scale power plants based on renewable resources have been put into operation. Due to large potential of wave energies, the share of these power plants is expected to increase. Hence, it is necessary to study the effect of wave energy converters on the different aspects of power systems. For this purpose, the effect of variation in the generated power of wave energy converters arising from variation in the wave height and wave period on the operation studies of power‐system must be investigated. For the first time, the impact of large‐scale wave energy converters on the operation studies of the power system is investigated, and the numerical results of the wave dragon converter as a commercial‐scale wave energy power plant are considered. For this purpose, a multistate reliability model of wave energy converters is developed considering both uncertain nature of the generated power and failures of composed components of the wave power plant. To determine the optimal reliability model of the wave generator, XB‐index is calculated and fuzzy c‐means clustering technique is utilized. Then, the proposed multistate reliability model based on the modified PJM method, which is suitable for short‐term studies, is used to perform the operation studies of the power systems containing large‐scale wave energy converters. Numerical results of the operation studies of RBTS and IEEE‐RTS including wave farms are given in the paper to study the impact of wave energy converters on the reliability‐based operation indices of the power systems. [ABSTRACT FROM AUTHOR]

Due to climate change, hydroclimatic extremes are becoming more frequent and intense and their characterization and analysis is essential for climate modelling. One of the regions that will be most affected by these extremes is the Mediterranean coast of Spain. Therefore, this paper analyses the significant wave height (Hs), peak wave period (Tp) and sea level (SL) extremes and their correlation along the Spanish Mediterranean coast. After conducting this analysis, it is finally concluded that and adjustment of the extreme long-term distribution of Tp is urgently needed to create accurate models and projections, which must be considered in combination with the intense extremes happening in the Levantine basin when modelling this area and designing new projects.

In this paper, the accuracy of wave parameters of the European Centre for Medium-Range Weather Forecasting Reanalysis v5 (ERA5) in the South China Sea (SCS) is systematically examined with field measured data of two buoys at offshore sites and a subsea-based platform at a nearshore site, which has a total observational period of nearly three years. It is suggested that the wave parameters provided by ERA5, such as significant wave height (Hs) and mean wave period (Tm), are in good agreement with the observational data of the three sites. Compared with the in situ data, the correlation coefficient of ERA5 Hs is in the range of 0.87–0.93, and the root mean square error is only in the range of 0.22–0.57 m. The error of standard deviation does not exceed 0.29 m and is even as low as 0.04 m at two sites. The wave propagation directions of the ERA5 and in situ data are also basically the same. However, when the data are applied in engineering, some wave parameters extracted from ERA5 may deviate from the measured statistics. It is possible to significantly overestimate the average duration of a particular Hs. Further analysis shows that the possible errors of ERA5 wave parameters may be due to insufficient description of topographic conditions, which shows that the error value changes obviously with the wave direction. The results preliminarily confirm the validity of ERA5 data in the SCS, but also indicate that it is necessary to calibrate and validate the data adequately when applying the global model and its reanalysis data to specific ocean areas.

The relationship between significant wave height (H1/3) and period (T1/3) was obtained using wave data from the East and Yellow coasts of the Korean Peninsula to facilitate the calculations of the wave parameters. In addition, the JONSWAP spectral parameters were estimated and analyzed for all wave height ranges. The relational expression between the two wave variables (H1/3~T1/3) obtained from this study showed a significant difference from the previously proposed relational expressions, most of which tended to follow the lower limit of the data. Meanwhile, the suggested peak enhancement factor (PEF, γ) is 1–7; however, for this study, a peak control factor (PCF, γc) with a range of 0–10 was introduced. As a result of the analysis, the PCF was determined to be 1.13–1.42, which is approximately 40% smaller than the previously proposed γ = 3.3. The probability density distribution of the appropriate PCF was then calculated, and the gamma and log-normal distributions for the East and Yellow coasts of the Korean Peninsula were found, respectively. This study covered waves of all range heights, and the analysis results can be used as important data to explain the characteristics of the sea area.

Wave parameters, such as wave height and wave period, are important for human activities, such as navigation, ocean engineering and sediment transport, etc. In this study, wave data from six buoys around Chinese waters, are used to assess the quality of wave height and wave period in the ERA5 reanalysis of the European Centre for Medium-Range Weather Forecasts. Annual hourly data with temporal resolution are used. The difference between the significant wave height (SWH) of ERA 5 and that of the buoy varies from −0.35 m to 0.30 m for the three shallow locations; for the three deep locations, the variation ranges from −0.09 m to 0.09 m. The ERA5 SWH data show positive biases, indicating an overall overestimation for all locations, except for E2 and S1 where underestimation is observed. During the tropical cyclone period, a large (about 32%) underestimation of the maximum SWH in the ERA5 data is observed. Hence, the ERA5 SWH data cannot be used for design applications without site-specific validation. The difference between the annual wave period from ERA5 and the mean wave period from the buoys varies from −1.31s to 0.4s. Inter-comparisons suggest that the ERA5 dataset is consistent with the annual mean SWH. However, for the average period, the performance is not good, and half of the correlation coefficients in the four points are less 50%. Overall, the deep water area simulation effect is better than that in the shallow water. [ABSTRACT FROM AUTHOR]

Pontoon breakwaters are one of the most common types of floating breakwaters. Floating breakwaters are mainly used for wave reflection and energy dissipation. Wave energy loss by turbulence in the current is caused by the transmission of waves through the structure. Also, since waves break on the upper side of the structure, wave energy decay occurs. The efficiency of floating breakwaters is generally presented by a factor that is called transmission coefficient. The transmission coefficient is a ratio of the transmission wave height to the incident wave. This study tries to investigate the performance of floating breakwaters. For a realistic assessment, the Caspian sea's hydrodynamic conditions are used. Also, two types of floating pontoon breakwaters have been modeled. This research aims to evaluate the performance sensitivity of breakwaters in relation to their geometry and wave characteristics like wave height and period. Hydrodynamic conditions are simulated by ANSYS AQWA finite element software. At first, a rectangular model (No.1) was simulated by hydrostatic analysis and time history analysis by applying average 20-year wave conditions and then using time history analysis by applying the critical wave characteristics. Then, the same procedure was performed on a trapezoidal model (No.2). According to the results, the transmission coefficient increases with increasing the wave period, but the increase in wave height has no effect on the breakwater efficiency. [ABSTRACT FROM AUTHOR]

Marine dynamics plays an important role in understanding the variations in offshore suspended sediment distribution and transport direction. In this study, variations in total suspended sediment concentration (TSSC) over Terrebonne Bay in the northern Gulf of Mexico were investigated by using remote sensing technology in relation to ocean-atmospheric dynamics. The terrestrial rainfall/runoff and river discharge in the lower Mississippi River estuarine area during the study period played an important role in the surface TSSC distribution. In most cases, the wave period and wind speed affected TSSC and its distribution. There was an inverse relationship between TSSC and wave period, but wind speed exhibited a positive relationship with TSSC distribution; however, there was a slight delay. The southeast (onshore) wind accounted for 57.0% of the wind direction over the study area and played a major role in the control of the surface sediment concentration in Terrebonne Bay in July 2010. The onshore wind lifted the underlying sediment, increasing the TSSC at the sea surface. The maximum TSSC was 1056.47 mg/l in the southeast direction (96.75°, onshore) on July 1. Other higher TSSCs were also observed in the southeast wind direction: 996.38, 820.55, and 605.27 mg/l with wind directions of 99.63, 127.33, and 120.17° on 2, 5, and 6 July 2010, respectively. The correlation coefficients between TSSC and wave period and wind speed were 0.45 and 0.47, respectively (significant level of 99%). The sediment concentration in the coastal area was related to coastal erosion and river discharge. The sediment transport not only was related to the physical properties of the sediment, but also depended on the flow velocity. The wind-driven flow field is one of the main factors that drive sediment transport. The sediments in the estuary and bay have many similarities in their dynamic environment and development evolution. The study of the dynamic response of offshore sediments is a supplement to the theory of sediment transport in the estuary and coastal zones. The study of the relationship between ocean dynamics and sediment transport can provide a reference for the site selection of offshore engineering structures. [ABSTRACT FROM AUTHOR]

The generated power of the Sea‐wave slot‐coned generator (SSG), as one of the high capacity wave energy converters, is dependent on the period and height of the waves. The generated power of this energy‐converter changes due to the variation in these parameters. Thus, different aspects of the power systems may be affected that must be investigated by increasing the share of these converters for electricity production in the power‐systems. In this paper reliability assessment of composite power‐systems containing large‐scale SSG is performed. The Xie and Beni (XB) index is calculated for obtaining the optimum number of states in the reliability model of the SSG and fuzzy c‐means clustering technique is proposed for reducing the number of states of the model. The contingency analysis method is proposed for calculating the reliability indices of the composite power‐system incorporating large‐scale SSG. DC load‐flow method, which considers line capacity, is used to perform load‐flow in the composite power‐system including generation and transmission networks. In the proposed technique, a load‐shedding program with the goal of minimizing the value of lost load is solved using of the linear programming method based on the interior‐point‐approach for contingency states leading to the load curtailment. [ABSTRACT FROM AUTHOR]

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The wave parameters and long-term statistics of wave height are important parameters required for coastal/offshore engineering design and analysis. The 20-year wave simulation has been carried out using MIKE-21 spectral wave model developed by the Danish Hydraulic Institute. The model was forced with the wind data from ECMWF operational archive wind data from 1998 to 2017. The MIKE C-MAP bathymetry data for less than 250 m depth in the North Indian Ocean and ETOPO1 for above 250 m depth were utilized for model bathymetry. The wave measurements available at various depths in the North Indian Ocean were utilized to validate model result. Wave parameters extracted at 27 locations at an interval of 1 degree at 25 m water depth were used for showing monthly variability of significant wave height, average wave period and mean wave direction. The extreme value analysis of significant wave height was carried out using Weibull analysis for 2, 5, 20 and 50 years return period. The maximum wave height of 5.7 m near Odisha coast in 50 years return period was calculated from the extreme value analysis. [ABSTRACT FROM AUTHOR]

Surface wave spectral properties of centimeter to decameter (cmDm) wavelengths are of great interest to microwave remote sensing of the ocean. They are obviously different from the high-frequency extension of the wind-wave spectrum models developed for ocean science and engineering applications, which focus on the longer waves in the energetic peak region of the wave spectrum. For more than six decades, the cmDm waves are generally considered to be in the equilibrium range, and its spectral function has a constant slope: −5 or −4 in the 1-D frequency spectrum, and −3 or −2.5 in the 1-D wavenumber spectrum. The observed wind-wave spectral slopes, however, are not constant. As a result, the cmDm wave properties are significantly different from those inferred from an equilibrium spectrum model. Surface slope measurements are more suited for studying the cmDm waves. Microwave radar backscattering cross sections have been used to study the shorter range of cmDm waves. L-band lowpass-filtered mean square slope (LPMSS) is contributed by waves longer than about 0.6 m, here referred to as the decimeter to decameter (dmDm) waves. The analysis of LPMSS has improved the modeling of dmDm waves. Ultimately, the spectral slope variation is a critical characteristic of cmDm waves. The wave spectrum model formulated with the variable spectral slope consideration produces very good agreement with L-band scatterometer and reflectometer measurements. [ABSTRACT FROM AUTHOR]

The wave parameters (the wave height and period) are important environmental factors in the ocean engineering design. General numerical wave models, such as SWAN and WAVEWATCH, are widely employed to simulate the wave conditions. However, significant differences were observed between the measurement and the simulation for both the wave height and period, which asks for wave model improvements. The differences are mainly due to the uncertainty of parameterizing various physical processes, including the wave breaking. The energy transfer and loss during the wave breaking involves an important physical mechanism, and the energy dissipation and the period changes are not well studied. This paper studies the deep and shallow water wave breaking using the wave focusing and the slope platform random wave experiments. The characteristics of the wave periods under different conditions are studied in detail, including the period variation. The results show that the periods change during the wave propagation and breaking processes. The energy transfer caused by the strongly nonlinear interaction between the wave components, as well as the energy loss caused by the wave breaking, are the primary causes. The corresponding relationships are established by fitting the data. For the deep water breaking waves induced by the wave focusing, the spectrally averaged period (SAP) increases, and a positive correlation between the rate of change and the wave steepness is found. In the shallow water, the nonlinear interactions are stronger than in the deep water, the wave periods are significantly reduced, and a negative correlation between the rate of change and a nonlinear parameter is found. The inherent mechanism of the period variation is analyzed based on the energy spectrum distribution variations. The contributions of the nonlinear interactions and the wave breaking to the SAP evolution are discussed. [ABSTRACT FROM AUTHOR]

WAM, SWAN and WAVEWATCH III® were implemented to the Finnish archipelago with a 0.1 nmi grid. A comparison with coastal wave buoy observations showed that the models agreed on the significant wave height, with biases and root-mean-square-errors (RMSE) differing at most 0.06 m. In a general sense, WAM propagated most long wave energy into the archipelago, while SWAN generated the highest local waves. The performance of WAVEWATCH III was wind direction dependent. The model tendencies caused them to disagree on the peak period near the coast, with differences in mean values being up to 1.4 s. The large scatter (RMSE>2 s) inside the archipelago was mostly explained by the ill-defined nature of the parameter in more complex wave conditions. The mean period had less scatter (RMSE<1.5 s), but changes in the upper integration frequency from 0.6 Hz to 1 Hz affected the bias by roughly 1 s in all models. WAM and WAVEWATCH III underestimated the high-frequency wave energy for certain wind directions, possibly because of a too small friction velocity. A wind forcing taken every 3 h from a 7.4 km operational atmospheric model was found to be sufficient to force the high-resolution wave models. [ABSTRACT FROM AUTHOR]

Drifting buoys collect wave data in the open ocean far from land and in areas with strong currents. However, the validation of the drifting buoy wave data is limited. Here, we compared the drifting buoy wave data, ERA5 wave data, and moored GPS buoy wave data. Data from 2009 to 2018 near the coast of Japan were used. The agreement of the drifting buoy-observed wave parameters with the moored GPS buoy-observed wave parameters is better than that of ERA5 wave parameters, which is statistically significant. In particular, the accuracy of the ERA5 wave heights tends to be lower where the ocean currents are fast. On the other hand, the agreement between the drifting buoy-observed wave heights and the moored GPS buoy-observed wave heights was good even in the areas with strong currents. It is confirmed that the drifting buoy wave data can be used as reference data for wave modeling study.

One of the advantages of floating offshore wind turbines (FOWTs) is that they can be designed to be easily wet towed and installed to reduce the cost of offshore construction. In this paper, a fully coupled towing system numerical model is established for a novel 10 MW FOWT concept, namely, a submerged floating offshore wind turbine (SFOWT) to investigate the towing performance. Firstly, the numerical simulation is validated by comparison with model experiment results. Then, a series of numerical simulations are conducted to predict and compare the towing performance for a three-column SFOWT (TC-SFOWT) and a four-column SFOWT (FC-SFOWT) under different wave conditions. The results show that the two forms of SFOWT have good towing performance when the significant wave height is less than 5 m, which is the maximum wave height for the allowable towing condition. The FC-SFOWT shows relatively better performance in heave motion and roll motion, but the towing force is relatively larger compared with the TC-SFOWT under the same condition. When the significant wave height is 5 m, the maximum values of heave motion, pitch motion, and roll motion of the TC-SFOWT are 2.51 m, 2.14°, and 1.38°, respectively, while they are 2.25 m, 2.70°, and 1.21°, respectively, for the FC-SFOWT. Both the roll motion and the pitch motion are satisfied with the requirement that the roll and pitch are less than 5° during the towing process. The mean towing force of FC-SFOWT is 159.1 t at the significant wave height of 5 m, which is 52.8% larger than that of TC-SFOWT. The peak period mainly influences the frequency where the response peak appears in power spectra. The findings in this paper could provide some guidelines for wet towed operations.

Prediction of wave parameters is one of the significant component for several coastal applications; for instance, coastal erosion, inshore and offshore structures, wave energy and others. The current research investigates the potential of the Chaos theory integrated with multiple linear regression (Chaos-MLR) in prediction of wave heights and wave periods. The wave data were collected at four moorings in the coastal environment of Tasmania. In the first stage, reconstructing the phase space and determine the input data for Chaos-MLR model, the delay time and embedding dimension are computed using average mutual information and false nearest neighbors’ analyses. The presence of chaotic dynamics in the used data is identified by the correlation dimension methods. In the second stage, the Chaos-MLR and pure MLR models are constructed for prediction model. Absolute error and best-fit-goodness diagnostic indicators are utilized to inspect the proficient of the proposed model in comparison with the pure MLR model. The inter-comparisons demonstrated that the Chaos-MLR and pure MLR models yield almost the same accuracy in predicting the significant wave heights and the zero-up-crossing wave periods. Whereas, the augmented Chaos-MLR model is performed better results in term of the prediction accuracy vis-a-vis the previous prediction applications of the same case study.

The main aim of this study is to investigate the effect of berm breakwater on wave run-up. A total of 200 numerical analysis tests have been carried out in this paper to investigate the effect of berm width, wave height, and wave period on the wave run-up, using an integrating technique of Computer-Aided Design (CAD) and Computational Fluid Dynamics (CFD). Direct application of Navier Stokes equations within the berm width has been used to provide a more reliable approach for studying the wave run-up over berm breakwaters. A well tested Reynolds-averaged Navier–Stokes (RANS) code with the Volume of Fluid (VOF) scheme was adopted for numerical computations. The computational results were compared with theoretical data to validate the model outputs. Numerical results showed that the simulation method can provide accurate estimations for wave run-up over berm breakwaters. It was found that the wave run-up may be decreased by increasing the berm width up to about 36 percent. Furthermore, the wave run-up may increase by increasing the wave height and wave period up to about 53 and 36 percent, respectively. These results may convince the engineers to use this model for design of berm breakwater in actual scale by calculating the Reynolds numbers.

In order to stabilise floating wind turbines, an innovative motion stabilisation measure is proposed and verified here through conducting a series of numerical researches with the aid of SESAM. In the research, the numerical model of a spar-supported 5 MW floating turbine was developed first to investigate its motion stability in different depths water and under different wave conditions. Then, a new concept of motion stabiliser is proposed, which consists of a number of heave plates that are connected to floating turbine foundation via structural arms. The influences of both the number of heave plates and their arm length on motion reduction are then investigated in order to explore an optimal design of the proposed stabiliser. Considering the dynamic motions of a floating turbine is mainly affected by sea waves, the motion stabilising capability of the proposed stabiliser is investigated over a wide range of wave period 4–36 s. It has been found that after using the proposed motion stabiliser, both the pitch and heave motions of the floating turbine are successfully limited within the most range of wave period, especially when the wave period exceeds 12 s.

Wave energy resource assessment and trends around Indonesian's ocean has been carried out by means of analyzing satellite observations. Wave energy flux or wave power can be approximated using parameterized sea states derived from satellite data. Unfortunately, only some surface parameters can be measured from remote sensing satellites, for example for ocean surface waves: significant wave height. Others, like peak wave period and energy period are not available, but can instead be estimated using empirical models. The results have been assessed by meteorological season. The assessment shows clearly where and when the wave power resource is promising around Indonesian's ocean. The most striking result was found from June to August, in which about 30–40 kW/m (the 90th percentile: 40–60 kW/m, the 99th percentile: 50–70 kW/m) wave power energy on average has been found around south of the Java Island. The significant trends of wave energy at the 95% level have also been studied and it is found that the trends only occurred for the extreme cases, which is the 99th percentile (i.e., highest 1%). Wave power energy could increase up to 150 W/m per year. The significant wave heights and wave power have been compared with the results obtained from global wave model hindcast carried out by wave model WAVEWATCH III. The comparisons indicated excellent agreements. [ABSTRACT FROM AUTHOR]

• A trivariate model is set up for significant wave height, period and direction. • The Vine copula theory is applied to decompose the trivariate distribution. • A special bivariate copula function of linear and circular variables is derived. • The seasonal and directional variability of wave energy resource is analyzed. • A theoretical guide is provided for WEC array optimal design and its operation. Based on the Vine copula theory, a trivariate statistical model of significant wave height, characterized wave period and mean wave direction was constructed. To maintain the properties of the different types of variables, a special copula function was derived from the model developed by Johnson and Wehrly based on the maximum entropy principle. It was then combined with the Archimedean copulas to construct the proposed model. An effective algorithm for generating corresponding joint pseudo-random numbers was also developed. Statistical analysis of hindcast data for the significant wave height, mean wave period, and direction, which were collected from an observation point in the North Atlantic every three hours from 1997 to 2001, was performed. The marginal distributions of the significant wave height and mean wave period were fitted by a modified maximum entropy distribution, and the mean wave direction was fitted by a mixture of von Mises distributions. It was shown that the proposed model is a good fit for the data. The seasonal wave energy resources in the target area were assessed using the model estimates. Histograms of the directional wave energy, wave energy roses, and scatter and energy diagrams were presented. [ABSTRACT FROM AUTHOR]

Measured wave data covering two years simultaneously at 3 locations along the eastern Arabian Sea reveals the presence of long-period (peak wave period > 18 s) low-amplitude waves (significant wave height

The assimilated coastal wave data are useful for wave climate study, coastal engineering, and design for marine disaster protection. However, the assimilated coastal wave data are few. Here, wave analysis data produced by the JMA (Japan Meteorological Agency) and ERA5 wave data were compared with GPS (Global Positioning System) buoy-measured wave data. In addition, the accuracy of ERA5 wave data for various conditions was investigated. The accuracy of JMA analysis wave height was better than that of ERA5 wave height. The ERA5 wave height was underestimated as the wave height increased. The accuracy of the ERA5 wave height was significantly different in fetch-unlimited and fetch-limited conditions. The difference of the skill metrics between fetch-unlimited and fetch-limited conditions was due to the overestimation of the fetch in the ERA5 grid. This result also applied to the wave period.