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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]

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.

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.

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]

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]

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.

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]

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]

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.

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.

Ocean surface waves in the North Pacific area are affected by storm winds. It is necessary to consider the movement of storms to predict waves. The impact of a time interpolation method for winds that considers the propagation of surface disturbances on ocean wave prediction from 2005 to 2006 in the North Pacific area is demonstrated. It is possible to interpolate surface winds, even when there are multiple cyclones and anticyclones moving in different directions at different distances. This method will be useful for wind fields with increasing amounts of spatial information. The predicted wave heights and periods from the linearly interpolated winds and the winds predicted using this new method are compared with in-situ observations from several moored buoys. The predicted wave heights are also compared with those from several drifting buoys in the northwestern Pacific. The improvement of the wave height and period prediction is evident in the case where the difference in the predicted wave parameters between the linear interpolation and the present method is large. The improvement of the wave height and period prediction is statistically significant at more than 95% in most cases. It is shown that the wave height and period prediction can be improved by improving the time interpolation method; however, the improvement of the wave direction prediction is not evident. [ABSTRACT FROM AUTHOR]

ABSTRACT Yoon, J.C. and Song, D.S., 2018. Preliminary Study for Detecting of Ocean Wave Parameters using CCD Images. In: Shim, J.-S.; Chun, I., and Lim, H.S. (eds.), Proceedings from the International Coastal Symposium (ICS) 2018 (Busan, Republic of Korea). Journal of Coastal Research, Special Issue No. 85, pp. 1371–1375. Coconut Creek (Florida), ISSN 0749-0208. Recently, researchers have been developed the technology for monitoring in the coastal zone using a remote sensing to manage and analyze the beach processes. Many of these approaches translate the data model of beach process as a queue of avoidance of emergency situation in a beach, such as coastal erosion risk management. However, sensor-based approaches have a crucial limitation, which needs a high cost and has a worry about malfunction. To overcome these problems, a video-based beach monitoring system, which can analyze the wave periods and height, was introduced in this study. A CCD camera is one of best choice to monitor a movement of arbitrary behaviour, because it has a several benefits, especially it does not need high cost equipment, then other sensor-based approach relatively, and has a strong resistance to the external environment except for light. The ocean wave change in CCD image clips, when it reaches the shallow water contains an extreme discontinuity, especially a change in the shape of marine space. So our system extracted the contour of video patches in an each frame and then compared their shape using the seven Hu-moments. The Hu-moments constitute a measure of the similarity of the matrix form between video frames. The radial symmetric kernel was applied to the similarity matrix, which is able to express the wave period and height, respectively. The wave period, which was detected by the Hu-moments algorithm at the Gyoam Beach in Republic of Korea were compared with the wave information collected by an under-water pressure type wave meter. The results of this study confirm that the CCD camera with Hu-moments algorithm is applicable to detect wave period with a slight bias and, consequently, to clarify the complex characteristics of wave distribution and its temporal change. [ABSTRACT FROM AUTHOR]

Drifting buoys can measure wave data even in areas far from land and with strong currents, such as the western boundary current. We evaluated the dependence of the difference between ERA5 wave data and buoy data on the Lagrangian surface current speeds derived from the drifting buoy positions. The ERA5 wave data does not consider the effects of ocean currents. The difference between the ERA5 wave heights and the buoy wave heights increases as the surface current speed increases. The ERA5 wave height is notably underestimated in the case of the opposing current to the mean wave direction, and the wave height is overestimated in the case of the following current to the mean wave direction. The magnitude of them is up to 20%. The wave periods from ERA5 data and the drifting buoy also have differences in the case of opposing and following currents, mainly due to the Doppler shift. Marked over- and underestimation of the ERA5 wave heights can be observed at higher surface current speeds in the Kuroshio extension area, where currents are influenced by mesoscale eddies. Overestimation and underestimation of the ERA5 wave heights are also frequent in the Kuroshio area. • Wave data from drifting buoy observations and ERA5 reanalysis are compared. • The ERA5 wave height is underestimated (overestimated) in the case of opposing (following) current to the wave direction. [ABSTRACT FROM AUTHOR]

In recent years, the GPS wave buoy has been developed for in situ wave monitoring based on satellite GPS signals. Many research works have been completed on the GPS-based wave measurement technology and great progress has been achieved. The basic principle of the GPS wave buoy is to calculate the movement velocity of the buoy using the Doppler frequency shift of satellite GPS signals, and then to calculate the wave parameters from the movement velocity according to ocean wave theory. The shortage of the GPS wave buoy is the occasional occurrence of some unusual values in the movement velocity. This is mainly due to the fact that the GPS antenna is occasionally covered by sea water and cannot normally receive high-quality satellite GPS signals. The traditional solution is to remove these unusual movement velocity values from the records, which requires furthering extend the acquisition time of satellite GPS signals to ensure there is a large enough quantity of effective movement velocity values. Based on the traditional GPS wave measurement technology, this paper presents the algorithmic flow and proposes two improvement measures. On the one hand, the neural network algorithm is used to correct the unusual movement velocity data so that extending the acquisition time of satellite GPS signals is not necessary and battery power is saved. On the other hand, the Gaussian low-pass filter is used to correct the raw directional wave spectrum, which can further eliminate the influence of noise spectrum energy and improve the measurement accuracy. The on-site sea test of the SBF7-1A GPS wave buoy, developed by the National Ocean Technology Center in China, and the gravity-acceleration-type DWR-MKIII Waverider buoy are highlighted in this article. The wave data acquired by the two buoys are analyzed and processed. It can be seen from the processed results that the ocean wave parameters from the two kinds of wave buoys, such as wave height, wave period, wave direction, wave frequency spectrum, and directional wave spectrum, are in good consistency, indicating that the SBF7-1A GPS wave buoy is comparable to the traditional gravity-acceleration-type wave buoy in terms of its accuracy. Therefore, the feasibility and validity of the two improvement measures proposed in this paper are confirmed.

One of the most difficult issues in wind measurement using microwave radar is the decreased or loss of sensitivity of the return signal in high winds. Recent analyses of wind speed, wave height, and wave period data from hurricane hunter missions show that surface waves inside hurricanes adhere to the nature of fetch- and duration-limited wind wave generation. Making use of this property, the hurricane wind speed is retrievable from the dominant wave parameter (significant wave height or dominant wave period) using the fetch- or duration-limited wave growth function. An algorithm based on such consideration is developed and applied to two hurricanes of different strengths (categories 2 and 4). The retrieved wind speeds are in good agreement with the reference wind speeds from hurricane hunter measurements. For example, combining the two hurricanes the regression statistics of the bias, slope of linear fitting, root mean squares difference, and correlation coefficient of wind retrieval from significant wave height are 0.50 m/s, 1.01, 4.03 m/s, 0.87 using the fetch-limited wind wave growth function. The range of wind speeds in the combined data is from 22.4 to 65.4 m/s, and there is no indication of saturation problem in the wind retrieval using the dominant wave parameters. [ABSTRACT FROM PUBLISHER]

The study presents the results of long-term monitoring of wind waves was carried out on the offshore fixed gas production platform in the northwestern part of the Black Sea in 1995-2011. The analysis of more than 31000 wave records provided reliable statistical characteristics of wind waves in the analyzed region. It was found that the maximum wave height reached 4.8 m in summer and 8.76 m in winter. The maximum hourly wave height exceeds significant wave height by 1.9 times in the vast majority of cases. The method of annual maxima revealed that in the Karkinit Bay the maximum wave height with the return period of 50 years is equal to 9.2 m. [ABSTRACT FROM AUTHOR]

• 1,First comprehensive experimental data for the wave-current-induced pore pressure along the surface of the pipeline and beneath the pipeline. • 2,Effect of both the wave and the current characteristics on the distribution of the pore pressure around the pipeline are discussed in detail. • 3,Liquefaction risk around the pipeline is tested and investigated for both the exposed and completely embedded pipelines. Wave and current coexist widely in the oceans. Ever-changing wave characteristics, such as height and length, have a significant influence on the dynamic response within the seabed soil due to the presence of currents. Some aspects of wave, seabed and pipeline interactions have been widely investigated over past years, incorporating both experimental and numerical approaches. However, previous studies on seabed dynamic response around pipelines have mainly focused on cases with wave loading. In this experimental laboratory study, the current loading and diverse backfill conditions which commonly occur far offshore are discussed in depth. It is found that when subjected to the combined wave and current loads, the response of the seabed around a pipeline is more complex than that subjected to pure wave loading as current velocity and propagation direction would significantly change the wave characteristics as well as seabed response. Most notably when comparing with the pure wave loading, the pore pressure amplitude and its attenuation rate within the seabed increases when current and wave travel in the same direction. This could increase the possibility of liquefaction around the pipeline. When current travels in opposing direction to the wave, the effect of current on the decrease of pore pressure and its attenuation rate is more significant than that of the co-current actions. This means that the counter-current will reduce the probability of soil liquefaction. [ABSTRACT FROM AUTHOR]

The high-frequency (HF) radar inversion algorithm for spectrum estimation (HIAS) can estimate ocean wave directional spectra from both dual and single radar. Wave data from a dual radar and two single radars are compared with in situ observations. The agreement of the wave parameters estimated from the dual radar with those from in situ observations is the best of the three. In contrast, the agreement of the wave parameters estimated from the single radar in which no Doppler spectra are observed in the cell closest to the in situ observation point is the worst among the three. Wave data from the dual radar and the two single radars are compared. The comparison of the wave heights estimated from the single and dual radars shows that the area sampled by the Doppler spectra for the single radar is more critical than the number of Doppler spectra in terms of agreement with the dual-radar-estimated wave heights. In contrast, the comparison of the wave periods demonstrates that the number of Doppler spectra observed by the single radar is more critical for agreement of the wave periods than the area of the Doppler spectra. There is a bias directed to the radar position in the single radar estimated wave direction. [ABSTRACT FROM AUTHOR]

The modified versions of the linear theoretical model of Longuet-Higgins (1983) are derived in this work and also compared with the laboratory experiments carried out in MARINTEK. The main feature of modifications is to replace the mean frequency in the formulation with the peak frequency of the wave spectrum. These two alternative forms of joint distributions are checked in three typical random sea states characterized by the initial wave steepness. In order to further explore the properties of these models, the associated marginal distributions of wave heights and wave periods are also researched with the observed statistics and some encouraging results are obtained. [ABSTRACT FROM AUTHOR]