Search Results (45)

This study examines the variation and trends in wave parameters across the Arctic, including the marginal ice zone (MIZ), by comparing historical data (1980–2009) with projections for a future climate scenario (2070–2099) as outlined by the IPCC. Utilizing the WAVEWATCH III (WW3) numerical wave prediction model, we simulate the wave climate for these periods, incorporating advanced parameterizations to account for wave-ice interactions within the MIZ. Our analysis focuses on the extreme values of significant wave heights (Hs), mean wave periods (T0), and dominant mean wave direction (MWD), calculated for both winter and summer seasons. To assess changes in wave climate under future climate scenarios, we first use a similarity matrix, applying the kappa variable and cell-by-cell numerical comparison methods to assess model congruence across different conditions. We also follow a standard approach, by assessing the extreme wave conditions for 20 and 100-year return periods using standard stochastic models, including Gumbel, exponential, and Weibull distributions. Full article

Determining/predicting the environment dominates a variety of marine operations, such as route planning and offshore installation. Significant wave height (Hs) is a critical parameter-defining wave, a dominating marine load. Data-driven machine learning methods have been increasingly applied to Hs prediction, but challenges remain in hyperparameter tuning and spatial generalization. This study explores a novel effective approach for intelligent Hs forecasting for marine operations. Multiple automated machine learning (AutoML) frameworks, namely H2O, PyCaret, AutoGluon, and TPOT, have been systematically evaluated on buoy-based Hs prediction tasks, which reveal their advantages and limitations under various forecast horizons and data quality scenarios. The results indicate that PyCaret achieves superior accuracy in short-term forecasts, while AutoGluon demonstrates better robustness in medium-term and long-term predictions. To address the limitations of single-point prediction models, which often exhibit high dependence on localized data and limited spatial generalization, a multi-point data fusion framework incorporating Principal Component Analysis (PCA) is proposed. The framework utilizes Hs data from two stations near the California coast to predict Hs at another adjacent station. The results indicate that it is possible to realize cross-station predictions based on the data from adjacent (high relevance) stations. Full article

The Beluga Reefer accident underscores the hidden risks associated with complex wave–current interactions along South Africa’s coastline, particularly in the Agulhas Current retroflection zone. This study utilized ERA5 reanalysis and CMEMS surface current data to analyze the sea state conditions at the time of the accident. While the wind speeds were moderate (5.42 m/s) and windsea heights were relatively low (0.99 m), the significant wave height (Hs) peaked at 3.24 m, with a strong opposing NE Agulhas Current (1.27 m/s) inducing wave steepening and group compression, creating transient hazardous conditions despite a low overall wave steepness (0.0209). Just before the accident, the directional disparity (Δθ) between the swell and windsea systems collapsed sharply from 167.45° to 8.98°, providing a false sense of stability. The synergy of these conditions at the accident site triggered the event, demonstrating that visually aligned wave conditions can mask dangerous underlying interactions. These findings highlight the critical need for integrated wave–current diagnostics in maritime forecasting to better predict complex hazards and enhance vessel safety. Full article

As a renewable and clean energy source with abundant reserves, the development of wave energy relies on accurate predictions of significant wave height (Hs). The fluctuation of Hs is a non-stationary process influenced by seasonal variations in marine climate conditions, which poses significant challenges for accurate predictions. This study proposes a deep learning method based on buoy datasets collected from four research locations in China’s offshore waters over three years (2021–2023, 3-hourly). The hybrid modal decomposition CEEMDAN-VMD is employed for reducing non-stationarity of the Hs sequence, with peak information incorporated as a data augmentation strategy to enhance the performance of deep learning. A probabilistic deep learning model, QRCNN-BiLSTM, was developed using quantile regression, achieving 12-, 24-, and 36-h interval predictions of Hs based on 12 days of historical data with three input features (Hs and wave velocities only). Furthermore, an optimization algorithm that integrates the proposed innovative enhancement strategies is used to automatically adjust the network parameters, making the model more lightweight. Results demonstrate that under a 0.95 prediction interval nominal confidence (PINC), the prediction interval coverage probability (PICP) reaches 100% for at least 6 days across all datasets, indicating that the developed system exhibits superior performance in short-term wave forecasting. Full article

With the rapid advancement of the marine economy, conventional salvage equipment has become increasingly inadequate in meeting the operational demands of complex aquatic environments and deep-sea salvage operations. This study presents the preliminary design of a novel salvage catamaran and proposes a multi-level fuzzy comprehensive evaluation framework for hydrodynamic performance under multi-sea-state and multi-operational conditions. A hydrodynamic performance evaluation indicator system was established, integrating resistance and seakeeping criteria. Computational fluid dynamics (CFDs) simulations with overset grids were employed to calculate the resistance characteristics. Potential flow-theory-based analysis quantified motion responses under irregular waves. The framework effectively distinguishes performance variations across five sea states and two sets of loading conditions through composite scoring. Key findings demonstrate that wave-added resistance coefficients increase proportionally with a significant wave height (Hs) and spectral peak period (Tp), while payload variations predominantly influence heave amplitudes. A fuzzy mathematics-driven model assigned entropy–Analytic Hierarchy Process (AHP) hybrid weights, revealing operational trade-offs: Case1-Design achieved optimal seakeeping and resistance, whereas Case5-Light exhibited critical motion thresholds. Adaptive evaluation strategies were proposed, including dynamic weight adjustments for long/short-wave-dominated regions via sliding window entropy updates. This work advances the systematic evaluation of catamarans, offering a validated methodology for balancing hydrodynamic efficiency and operational safety in salvage operations. Full article

Wave energy is an increasingly attractive renewable energy source due to its potential and predictability. Various Wave Energy Converters (WECs) have been developed, including attenuators, overtopping devices, and point absorbers. The Wave Dragon, an overtopping device, is a floating structure anchored to the seabed with a mooring system. It uses two reflectors to guide incoming waves into a central reservoir, where the captured water flows through turbines to generate electricity. This study enhances the realism of Wave Dragon simulations by modeling it as a moving structure with moorings, addressing key gaps in prior research. Real-time wave data from the Caspian Sea, collected over a year, were used to develop a 3D model and analyze the device’s performance under varying wave conditions. Four significant wave heights (Hs) of 1.5, 2.5, 3.5, and 4.5 m were tested. The results demonstrate that higher wave heights increase water flow through the turbines, leading to higher energy output, with monthly energy generation recorded as 16.03, 25.95, 31.45, and 56.5 MWh for the respective wave heights. The analysis also revealed that higher wave heights significantly increase pressure forces on the Wave Dragon, from 2.97 × 10⁵ N at 1.5 m to 1.95 × 10⁶ N at 4.5 m, representing a 6.5-fold increase. These findings underscore the potential of Wave Dragons to enhance renewable energy production while ensuring structural robustness in varying wave conditions. Full article

To meet the needs of marine disaster prevention and mitigation, this paper proposes a systematic methodological framework to describe the annual risk situation of Disastrous Sea Waves (DSWs) from four perspectives. Its application is demonstrated for the China Sea in 2023 as a case study. The systematic approach is reflected in the following: (1) a comprehensive description of DSW risks based on three dimensions: occurrence frequency, maximum intensity, and hazard index; (2) an overview of the DSW risk characteristics for the year through spatial and monthly distributions; (3) a comparative analysis of the year’s DSWs, with historical data based on anomalies and return periods used to assess the risk characteristics and extremities; and (4) an analysis of the causes of the year’s characteristics based on monthly anomalies and weather systems. Through its application to the China Sea in 2023, the analysis process is introduced as follows. (1) High-Frequency and Intensity Areas: DSWs frequently occurred in the northeastern South China Sea (SCS) and Taiwan Strait, exceeding 450 h. The maximum significant wave height (H_s), reaching 11.3 m, was recorded in the southern East China Sea (ECS) in August. (2) Extremity in Frequency and Attribution: The occurrence frequency was extremely high, with the cumulative hours exceeding the historical average by 159 h (9.1%). The southwestern SCS showed the most significant excess, up to 168 h (>120%). The reason for this was that DSWs in January caused by prolonged cold air lasted 236 h longer (121%). (3) Extremity in Intensity and Attribution: The maximum H_s in the southern ECS and Taiwan Strait was 2 m (30%) higher than the historical average. The intensified cold air waves caused the higher intensities. (4) Hazard Levels: Higher risk occurred in the southwestern SCS, southern ECS, and Taiwan Strait, while the highest extremity occurred in the Bohai Sea. Full article

Typhoons, extratropical cyclones, and cold fronts cause strong winds leading to storm surges and waves in the Bohai Sea. A wave–flow coupled numerical model is established for storm events observed in 2022 caused by three weather systems, to investigate how storm waves are modulated by wave–tide–surge interaction (WTSI). Wave response is basically controlled by water level change in coastal areas, where bottom friction or breaking dominates the energy dissipation, and determined by the current field in deep water by altering whitecapping. Wave height increases/decreases are induced by positive/negative water level or obtuse/acute wave–current interaction angle, leading to six types of field patterns for significant wave height (Hs) responses. For the three storm events, Hs basically changed within ±5% in central deep water, while the maximum increase/decrease reached 160%/−60% in the coastal area of Laizhou Bay/Liaodong Bay. Based on maximum Hs and its occurrence time, WTSI modulation is manifested as the superposition effect of wave–tide and wave–surge interactions in both space and time scales, and occurrence time depends more on tide than surge for all three storms. The enhancement/abatement of WTSI modulation happens for consistent/opposite changing trends of wave–tide and wave–surge interaction, with the ultimate result showing the side with a higher effect. Full article

The Copernicus Sentinel-6 Michael Freilich (S6-MF) and Jason-3 (J3) Tandem Experiment (S6-JTEX) provided over 12 months of closely collocated altimeter sea state measurements, acquired in “low-resolution” (LR) and synthetic aperture radar “high-resolution” (HR) modes onboard S6-MF. The consistency and uncertainties associated with these measurements of sea state are examined in a region of the eastern North Pacific. Discrepancies in mean significant wave height (Hs, 0.01 m) and root-mean-square deviation (0.06 m) between J3 and S6-MF LR are found to be small compared to differences with buoy data (0.04, 0.29 m). S6-MF HR data are found to be highly correlated with LR data (0.999) but affected by a nonlinear sea state-dependent bias. However, the bias can be explained robustly through regression modelling based on Hs. Subsequent triple collocation analysis (TCA) shows very little difference in measurement error (0.18 ± 0.03 m) for the three altimetry datasets, when analysed with buoy data (0.22 ± 0.02 m) and ERA5 reanalysis (0.27 ± 0.02 m), although statistical precision, limited by total collocations (N = 535), both obscures interpretation and motivates the use of a larger dataset. However, we identify uncertainties in the collocation methodology, with important consequences for methods such as TCA. Firstly, data from some commonly used buoys are found to be statistically questionable, possibly linked to erroneous buoy operation. Secondly, we develop a methodology based on altimetry data to show how statistically outlying data also arise due to sampling over local sea state gradients. This methodology paves the way for accurate collocation closer to the coast, bringing larger collocation sample sizes and greater statistical robustness. Full article

In the face of depleting fossil energy and the imperative of sustainable development, there is a compelling drive towards advancing renewable energies. In this context, sustainable and predictable alternatives, like marine energy, gain prominence. Marine energy presents a cleaner option devoid of the adverse effects associated with fossil fuels, playing a crucial role in environmental sustainability by safeguarding coastlines against erosion. This study focuses on Astara Port in the Caspian Sea, exploring the utilization of wave energy converters (WECs). The originality of this study’s research lies in exploring WECs’ dual role in energy generation and coastal protection. Using MIKE21 software simulations, the impact of number, location, arrangement, and orientation of WECs across various scenarios was investigated, including two WEC number scenarios (11 and 13), three structural placement scenarios (north, front, and south of the port), two structural arrangement scenarios (linear and staggered), two port layout scenarios (original layout and modified layout), and two orientation scenarios for the structures (facing north-east, which is the dominant wave direction, and facing southeast). The results show a remarkable decrease in the significant wave height behind WECs, notably with 13 staggered devices facing dominant waves (from northeast), reducing the significant wave height Hs by 23–25%. This setup also shows the highest wave height reduction, notably 36.26% during a storm event. However, linear WEC setup offers more extensive coastline protection, covering 47.88% of the model boundary during storms. Furthermore, the 11 staggered WECs facing southeast (SE) arrangement had the lowest sediment accumulation at 0.0358 m over one year, showing effective sedimentation mitigation potential. Conversely, the 13 linear WECs facing northeast (NE) had the highest accumulation at 0.1231 m. Finally, the proposed port design redirects high-velocity flow away from the port entrance and removes rotatory flow, reducing sediment accumulation near the harbor entrance. Full article

The morphological responses of two mesotidal beaches located in different coastal settings (embayed and open sandy beaches) on the northwestern Iberian coast were monitored during the winter of 2018/19. The offshore wave time series analysis is related to high-resolution topo-bathymetric measurements to explore spatial-temporal morphological variability at monthly to seasonal scales. Both locations are subjected to the North Atlantic wave climate which exhibits a pronounced seasonality. Throughout the last decade (2010–2020), significant wave heights reached values of up to H_s~9 m during winters and up to H_s~6 m during summers. On average, approximately 12 storms occurred annually in this region. The results clearly reveal divergent morphological responses and sediment transport behaviors at the upper beach and the intertidal zone during the winter for each location. In the embayed beach (Patos), sediment transport in the nearshore is governed by cross-shore processes between the beach berm and a submerged sandbar. In contrast, the open beach (Mira) showed dynamic sediment exchanges and three-dimensional morphologies alternating between accumulation and erosion zones. Overall, both beaches exhibited an erosional trend after the winter, particularly concerning berm erosion and the subaerial beach volume/shoreline retreat. This study highlights the contrasting morphodynamic response on open and embayed beaches to winter conditions, integrating both the subaerial and submerged zones. Local geological and environmental factors, as well as the coastal management strategies applied, will influence how the beach responds to winter wave events. Monitoring and understanding these responses are essential for effective coastal management and adaptation to changing climate. Full article

Knowledge of wave climate is essential for efficient management of the world’s coastal areas. Senegal is a relevant case, given its high coastal vulnerability to energetic wave conditions. This study investigates wave climates along the coastal zone of Senegal based on a new high-resolution hindcast covering the period 1980–2021. This study evaluates the average, seasonal, and extreme values for the significant wave heights (Hs), periods (T_m02/T_p), and mean directions (DIR). In boreal winter, the wave climate is dominated by swells coming from the North-Atlantic lows. In contrast, in boreal summer, the Southern Coast (from Dakar to Casamance) is exposed to swells generated in the South Atlantic Ocean. Throughout their refraction around the Dakar Peninsula, NW swells rotate by ~100° from NW to SW, while their Hs is roughly halved when reaching the Southern Coast of Senegal. Over the studied period, trends in Hs are weak (~0.6 cm.decade⁻¹) on the Northern Coast and double on the Southern Coast (~1.2 cm.decade⁻¹), mostly due to an increase during boreal summer (2 cm.decade⁻¹). The wave periods show weak trends (~0.05 s.decade⁻¹), and DIRs show weak counterclockwise rotation (−1°.decade⁻¹). These trends are explained by the main climate modes of the Atlantic Ocean (NAO/EA during winter, SAM during summer) and are important for future research and long-term monitoring of the Senegalese Coast. Full article

This paper investigates the spatial and temporal variability of significant wave height (Hs) and wind speed (U10) using altimeter data from the Australian Ocean Data Network (AODN) and buoy data from the National Data Buoy Center (NDBC). The main goal is to evaluate spatial and temporal criteria for collocating altimeter data to fixed-point positions and to provide practical guidance on altimeter collocation in deep waters. The results show that a temporal criterion of 30 min and a spatial criterion between 25 km and 50 km produce the best results for altimeter collocation, in close agreement with buoy data. Applying a 25 km criterion leads to slightly better error metrics but at the cost of fewer matchups, whereas using 50 km augments the resulting collocated dataset while keeping the differences to buoy measurements very low. Furthermore, the study demonstrates that using the single closest altimeter record to the buoy position leads to worse results compared to the collocation method based on temporal and spatial averaging. The final validation of altimeter data against buoy observations shows an RMSD of 0.21 m, scatter index of 0.09, and correlation coefficient of 0.98 for Hs, confirming the optimal choice of temporal and spatial criteria employed and the high quality of the calibrated AODN altimeter dataset. Full article

In order to protect fragile shoreline and coastal assets during extreme storms, a combined floating breakwater-windbreak has been proposed to reduce both wind and wave energies in the sheltered area. The 1 km-long breakwater has a porous hull with internal tubes to allow free passage of water; thereby further dissipating wave energy. The deck of the structure is designed to have a slope of 25 degrees facing the upstream side, and arrays of cylindrical tubes are placed on the sloping deck to form a windbreak. A reduced-scale (1:50) model test was carried out in a wave flume to examine wave sheltering performance under significant wave heights H_s = 3.0 m to 7.5 m and peak wave periods T_p = 9.4 s to 14 s sea states. Both regular and random wave conditions with different wave heights were considered. It is found that transmission coefficients ranging from 0.4 to 0.6 can be achieved under tested wave conditions. Porous breakwater hull increases the wave dissipation coefficients and is effective in reducing the wave reflection at the upstream side. The wave run-up length is dependent on the Iribarren number if the reduction induced by vertical freeboard is considered. Based on experimental data, empirical formulae have been proposed to predict the wave run-up responses in regular waves, probability of non-zero wave run-up occurrence, modified Weibull distribution of the wave run-up peaks and extreme wave run-up in random waves. Full article

Electrifying off-grid and isolated islands in the Philippines remains one of the challenges that hinders community development, and one of the solutions seen to ensure energy security, energy access and promote a low-carbon future is the use of renewable energy sources. This study determines the nearshore wave energy resource during monsoon seasons in Cuyo Island using a 40-year wave hindcast and 8-year on-site wind speed data as inputs to develop a high-resolution wave energy model using SWAN and assesses its annual energy production through matching with wave energy devices. The results show that the average significant wave height (H_s), peak period (T_p) and wave power density (P_d) during a northeast monsoon are H_s = 1.35 m, T_p = 4.79 s and P_d = 4.05 kW/m, respectively, while a southwest monsoon, which is sheltered by the mainland, results in H_s = 0.52 m, T_p = 3.37 s and P_d = 0.34 kW/m. While the simulated model was observed to overestimate the significant wave height (bias = 0.398, RMSE = 0.54 and SI = 1.34), it has a strong relationship with the “observed values” (average r = 0.9). The annual energy production for Wave Dragon, Archimedes Wave Swing and Seawave Slot-Cone Generator are highest at 1970.6 MWh, 2462.04 MWh, 62.424 MWh and 4099.23 MWh, respectively. Full article