Hindcast Wave Data Research Articles

Accuracy verification of the 2D spectral AIS method by the hull monitoring data

Accuracy validation of the 2D spectral AIS method (AIS method using two-dimensional wave spectrum; 2D-AIS method) using hull monitoring data of a large ore carrier is discussed. The AIS method predicts the response of actual ships using AIS-based ship position data, hindcast wave data, and response characteristics data. The conventional AIS method uses representative parameters(H, T, θ) from wave spectrum modeling. The modeling involves many uncertainties. By using the 2D wave spectrum as it is, the effect of uncertainties associated with wave spectrum modeling is investigated. Compared to the analysis of the monitoring data conducted in this study, it was found that the 2D-AIS method improves the accuracy to about 15 %, while the conventional AIS method shows an error of up to about 35 % compared to the actual measurements in the long-term maximum expected values. This enhancement is attributed to the inability of the modeled wave spectrum to accurately represent the two-peak wave spectrum observed in extreme sea states, leading to a deficiency in reproducing wave frequency components corresponding to peak frequencies of the response. The findings underscore the effectiveness of the 2D-AIS method in refining long-term hull stress estimations, thus offering valuable insights for enhancing the safety and performance of hull structures.

Predicting Characteristic Length Scales of Barrier Island Segmentation in Microtidal Environments

AbstractSegmented barrier islands can be found in regions with small tidal ranges. In contrast to tidally dominated barriers, where inlet dynamics are thought to control island length scales, the controls on barrier island length scales in wave‐dominated environments have not been quantified. These microtidal barriers typically have a curved shoreline, suggesting the influence of wave‐driven alongshore sediment transport. Microtidal barriers are also typically hydrodynamically isolated from one another, as weak tidal flows limit interactions between adjoining barriers. To better understand the controls on and scales of barrier segmentation in the relative absence of tides, here we develop a theoretical framework to estimate the alongshore length scales at which a barrier will either breach or heal following a disturbance in the barrier morphology. The non‐dimensional framework compares the timescales of overwash (advective) and alongshore sediment transport (diffusive) processes along barrier island chains. We then apply this framework to modern barrier islands in the microtidal Gulf of Mexico using wave hindcast data and the lengths, widths, heights, and lagoon depths measured from remotely sensed geospatial data and topobathymetric data. We find that most of these barriers are currently longer than their critical length scale, often as a result of coastal restoration efforts. Our critical length scale analysis suggests that most of the Gulf of Mexico barriers are vulnerable to segmentation despite coastal restoration efforts intended to protect fisheries and the mainland coasts.

Role of the forcing sources in morphodynamic modelling of an embayed beach

Abstract. The sensitivity of a 2DH coastal area (XBeach) and a reduced-complexity (Q2Dmorfo) morphodynamic model to using different forcing sources is studied. The models are tested by simulating the morphodynamic response of an embayed beach in the NW Mediterranean over a 6-month period. Wave and sea-level forcing from in situ data, propagated buoy measurements, and hindcasts, as well as combinations of these different data sources, are used, and the outputs are compared to in situ bathymetric measurements. Results show that when the two models are calibrated with in situ measurements, they accurately reproduce the morphodynamic evolution with a “good” Brier skill score (BSS). The calibration process reduces the errors by 65 %–85 % compared with the default setting. The wave data propagated from the buoy also produce reliable morphodynamic simulations but with a slight decrease in the BSS. Conversely, when the models are forced with hindcast wave data, the mismatch between the modelled and observed beach evolution increases. This is attributed to a large extent to biased mean directions in hindcast waves. Interestingly, in this small tide site, the accuracy of the simulations hardly depends on the sea-level data source, and using filtered or non-filtered tides also yields similar results. These results have implications for long-term morphodynamic studies, like those needed to validate models for climate change projections, emphasizing the need to use accurate forcing sources such as those obtained by propagating buoy data.

Dynamic analysis of lift-off operation of offshore wind turbine jacket foundation from the transportation barge

The lift-off operation of the offshore wind turbine jacket foundation from a barge is investigated in this study. Firstly, the hydrodynamic analysis of the two ships is carried out via AQWA, considering the series configuration and L-shaped configuration. The damping lid method is introduced to address viscous correction and validated by a frequency-time-domain validation. The damping lid factor for the two configurations are set to be 0.02 and 0.04. The time-domain simulation of multi-body lifting system, including lifting wires, slings, and deck fenders, are then carried out. In the nonstationary time-domain simulation, the sensitivity of wave direction, vessel configuration and deck fender stiffness are investigated, indicating that the most critical stage during the lift-off operation corresponds to when about 70% weight of the jacket is lifted by the heavy-lift vessel. The series configuration under head sea in 70% load transfer stage is chosen for subsequent steady-state simulations. Extreme value analysis is carried out based on the Gumbel distribution. The allowable sea states are then evaluated. The operability is obtained by using the 20-year hindcast wave data of three certain sites off Guangdong, Fujian and Zhejiang coast, which are 60%, 55% and 65%, respectively.

Evaluating Wave Potential and Assessing the Economic Viability of Wave Energy Converters in the South Java Seas

As an archipelagic nation, Indonesia holds substantial potential for wave energy as a renewable resource. Certain coastlines of islands facing the Indian Ocean, particularly in the western and southern regions, exhibit significant wave energy throughout the year. To identify suitable locations for Wave Energy Converter (WEC) installation, it is essential to assess wave hindcast data. This study utilizes NOAA and ERA5 reanalysis wave data to analyze wave characteristics in Indonesia from 2008 to 2018. Data processing with Ocean Data View is employed to estimate key wave parameters at various locations, including significant wave height, mean wave period, and mean wave direction. Two locations in the South Java seas were identified for WEC installation based on this research. The average values for the period 2008 to 2018 indicate a significant wave height of around 2m, with a maximum height of 5m, a wave period of 10–14s, and a wave direction of 195–210 degrees. Notably, NOAA data suggests a higher estimation of significant wave height compared to ERA5 data. The average annual wave power potential based on ERA5 and NOAA is 164.43 MW/m and 252.15 MW/m, respectively. Furthermore, this study incorporates an economic simulation for the construction of a multi-point absorber WEC. The objective is to offer insights into the Levelized Cost of Electricity (LCOE) and compare it with other WEC technologies. Assuming a WEC capacity of 130 kW, the total construction cost is estimated at $2,093,725, resulting in a Levelized Cost of Energy (LCOE) of $91/MWh.

Global extreme wave estimates and their sensitivity to the analysed data period and data sources

In the absence of wave measuring buoys operating over extended periods, wave hindcast data or satellite observations are indispensable for estimating global extreme wave heights. However, the results may depend on the analysed wind wave sources and the period's length. The sensitivity of the estimated extreme significant wave heights (SWH) to the analysed data sources and periods is investigated in this study. Global extreme wave heights are estimated using ECMWF Reanalysis v5 data (ERA5), global wave hindcast developed based on Simulating WAves Nearshore forced by the Japanese 55-year Reanalysis (SWAN-JRA55), satellite altimeter observations, and long-term wave buoy measurements. Both Annual Maximum fitting to the Generalized Extreme Value Distribution (AM-GEV) and Peaks Over Threshold fitted to the Generalized Pareto Distribution (POT-GPD) models are used. The results show that the global extreme SWH estimates considerably depend on the analysed data sources. The relative differences observed between the analysed data sources are >20% in large parts of the world. Thus, the relative differences in extreme SWH are mainly lower by increasing the analysed data periods. However, they can reach 30% and are more critical using AM-GEV. Besides, by comparing the extreme values from reanalysis and hindcast wave data to those from long-term wave measurements, underestimations of up to 2 m are observed for a return period of 100 years in the North-West Atlantic and North-East Pacific.

A comparison of Baltic Sea wave properties simulated using two modelled wind data sets

We calculated two sets of idealised ice-free wave hindcast data on a high-resolution, three-layer nested grid covering the Baltic Sea, using two different wind datasets (ERA5 and BaltAn65+), to evaluate the performance of the model in the open and sheltered parts of the sea. The highest resolution of the grids is 260 m. The outcome of simulations is compared against the available in-situ measurements. The main statistical properties of the Baltic Sea wave climate as well as the timing and maximum values of extreme significant wave heights are well replicated in the Baltic proper using the 3 nautical mile (nmi) grid. Simulations using BaltAn65+ have a better match with recorded average wave properties while the ERA5 forcing better replicates wave extremes. The largest differences between the two simulations occur in the Sea of Bothnia, Bay of Bothnia and to the east of large islands. Wave climate in the Gulf of Finland is replicated with a resolution of 1 nmi in the open part of the gulf a down to a resolution of 260 m in selected coastal areas. The wave intensity is the largest in the central part of the gulf and decreases towards the coast and from the West to the East. The use of ERA5 winds yields higher wave heights at the entrance of the gulf and in the central part of the gulf along its axis. Simulations using BaltAn65+ winds show higher waves in the nearshore regions.

Long‐term drivers of shoreline change over two centuries on a headland‐embayment beach

AbstractShoreline evolution over the last two centuries was analysed for Dundrum Bay, Co. Down, Northern Ireland, using historical and recent shoreline datasets from 1833 to 2020. The area of interest comprises two sandy beaches and vegetated coastal dune fields, Newcastle–Murlough and Ballykinler, separated by an inlet channel which connects the inner with the outer bay. Twenty‐four temporal shorelines were extracted, and a quantitative assessment of their positional uncertainty was performed. This was combined with analysis of foredune volume variations by applying the Structure‐from‐Motion‐Multi‐View‐Stereo technique to 1963 aerial photography and comparing it with a 2014 Light Detection And Ranging (LiDAR) dataset to better inform on links between the sediment dynamics and the observed shoreline changes. Storm events were identified using recorded extreme water levels (EWLs) (1901–2020) and hindcasted wave data (1948–2020). In the first 87 years, the shoreline was largely stable, and change was focused at the inlet area. In the 20th century, localised retreat characterised the western (Newcastle–Murlough) sector, whereas the eastern sector (Ballykinler) experienced general shoreline advance. The rate and extent of shoreline retreat in the western sector increased post‐1997 in concert with accelerated accretion at Ballykinler. The strongest erosional episodes were recorded in 1920–1951, 1997–2005, and 2012–2014. Although no direct link was established between single storms and shoreline retreat rates, the three major retreat periods coincided with several consecutive EWLs or EWLs with a return period greater than 100 years. These were generated by storm directions ranging from south to southwest. The long‐term pattern of shoreline change points to a complex coastal system that is still evolving.

Assessing the impact of wave model calibration in the uncertainty of wave energy estimation

The accuracy of estimated sea conditions, specifically wave height and peak/average wave periods, affects the estimation of electrical energy production from wave energy converters. This study investigates the uncertainty in wave energy harvesting estimated by the SWAN wave model and determines possible improvements by adjusting the model's tunable parameters. Three different wave energy converters (OEBuoy, WaveBob, and Pontoon) and ten different locations along the Atlantic coast of the Iberian Peninsula are used in the study. The SWAN model is calibrated using the ST6 term package based on both wave height and peak period wave parameters. Different wave hindcast data produced by different model settings are used to estimate the wave energy produced by the wave energy converters at ten buoy locations and compared to wave energy produced estimated based on wave observations. The study finds that the physical settings of the SWAN model have a considerable influence on the uncertainty in the estimation of the power output produced by the device. The best-fitting calibrated model improved the mean energy output value of all locations compared to the SWAN default settings. The study concludes that adjusting the SWAN model parameters can improve the accuracy of the estimation of the energy output.

Environmental Contours in the Adriatic Sea for Design and Analysis of Marine Structures

The environmental contours represent an approach for defining extreme environmental conditions, resulting in extreme responses of marine structures with a given return period. Over the past decade, an increasing number of studies have been developed dealing with the methods for defining environmental contours and enhancing their practical application in different marine environments. In the present study, environmental contours describing significant wave heights and peak wave periods are created for the Adriatic Sea. This small semi-enclosed sea basin within the Mediterranean Sea encounters increasing maritime and offshore activities. Considering also a great but still unused potential for the installation of renewable energy facilities, the main motives for the presented study are concluded. The environmental contours are established based on 24 years of hindcast wave data extracted from the WorldWaves database. Joint distributions consisting of the marginal distribution of significant wave height and conditional distributions of peak wave periods are used as a basis for the creation of environmental contours using the IFORM and ISORM methods. Return periods of 1 year, 25 years, and 100 years are considered relevant for the marine operation, design of ships, and offshore structures, respectively. A possibility of environmental contour practical application to the calculation of global wave loads upon ship structures is presented. Based on the uncertainty assessment performed, conservative environmental contours for the whole Adriatic are also presented.

Determining depth of closure based on time-series beach profiles and empirical formulas: A case study along the Florida coast

Depth of closure (DOC) is defined as the most landward depth seaward of which there is no significant change in bed elevation and no significant net sediment exchange between the nearshore and the offshore over a certain period of time, such as 5 to 20 years. DOC is an essential parameter used in beach and shore protection, sediment management, and many other aspects of coastal studies. Taking advantage of advancements in wave hindcast and bathymetry measurement in the past 20 years (2000-2019), this study determined the DOC at 12 locations along the Florida coast, including three from the northwest Gulf coast, three from the west Gulf coast, and six from the east Atlantic coast. The 12 sites covered a wide range of coastal morphodynamic conditions, with considerable difference in tidal ranges, incident wave heights, as well as nearshore and offshore morphology. Hindcast wave data from WAVEWATCHIII, available since 2005, were analyzed and applied to calculate the closure depth using various empirical formulas. At all the 12 study sites, time-series profiles demonstrated an apparent convergence point indicating the presences of a DOC. The bed-level change at DOC, as quantified by the standard deviation of elevation variation, ranged from 0.05 m to 0.19 m. Along the studied northwest Florida Gulf coast the DOC ranged from 9.12 m to 9.76 m. The DOC along the studied west Florida Gulf coast ranged from 1.59 m to 4.06 m and is influenced by the shallow flat inner continental shelf. Along the studied east Florida Atlantic coast, the DOC ranged from 4.35 m to 8.20 m, with considerable alongshore variation. The Birkemeier formula yielded the closest predictions to the measured values. A linear relationship between the seaward slope of the outer bar and DOC was identified. Incorporating the seaward slope of the outer bar into the Birkemeier formula improved the accuracy of DOC prediction.

Uncertainty in wave hindcasts in the North Atlantic Ocean

Accurate knowledge of ocean surface waves is crucial for ship design. With the significant advancements in model physics and numerical resources, recent numerical wave hindcast data has the potential to provide environmental conditions for estimating the wave load in the ship design process. To help estimate extreme wave loads with quantified uncertainty for strength assessments of ship structures, this study aims to quantify model uncertainty in the state-of-the-art numerical wave hindcast products. Model uncertainty was deduced from inter-model comparisons with four numerical wave hindcast products after model evaluations. For model evaluations, wave buoys distributed over the Northwest Atlantic and Northeast Atlantic were used as wave buoy arrays. In general, all four models accurately estimated the significant wave height Hs. However, as the wave condition becomes extreme with the increase of Hs, the model estimations of Hs deviate from the buoy data and differ from each other. For the extreme wave conditions, two wave hindcast products consistently showed better performance based on the buoy observations for both the Northwest Atlantic and Northeast Atlantic. In addition to Hs, the mean wave period Tm02 from the hindcast products are also examined in this study. Although evaluations of Tm02 are not often seen in previous studies, Tm02 is another crucial wave parameter because the ship response is often calculated as a function of Hs and Tm02. Based on careful comparisons, it is found that all the wave hindcast products underestimate Tm02 under the extreme wave conditions of Hs>10m. The joint probabilities of Hs and Tm02 for extreme wave conditions of Hs>10m and 8s<Tm02<14s are further calculated as a scatter diagram for extreme wave conditions (SDE). Among the SDEs from the buoys and four model products, the total number of samples varied by 50%, although the mean value of the four model products is close to the result from the buoys. The significance of the variation is further described in the context of the extreme wave load estimation for strength assessments of ship structures.

Power Performance and Response Analysis of a Semi-Submersible Wind Turbine Combined With Flap-Type and Torus Wave Energy Converters

Abstract An integrated offshore wind and wave energy system is an attractive concept in areas with abundant wind and wave energy resources. The sharing of supporting platform and facilities, e.g., mooring systems, offers significant cost savings. This will effectively lower the levelized cost of energy (LCOE). In the present study, a conceptual design consisting of a braceless semi-submersible floating horizontal axis wind turbine (FHAWT), three flap-type wave energy converters (WECs), as well as a torus (donut-shaped) point absorber-type WEC is proposed. The flap-type WECs harvest wave energy through the flap motion caused by oscillating wave surge, while the torus WEC absorbs wave energy generated from its heaving motion. The absorbed mechanical power of the power take-off (PTO) systems is calculated based on linear damping forces and the motions of the WECs relative to the supporting platform. Hydrodynamic interaction between the WECs and the supporting platform is considered by including the coupling terms in the added mass and potential damping coefficient matrices. A fully coupled aero-servo-hydro-elastic numerical model of the concept is constructed. The feasibility study of the concept is carried out using time-domain simulations. Only operational environmental conditions are simulated based on simultaneous wind and wave hindcast data of a selected offshore site. The effects of the WECs on the wind turbine, platform motions, and WEC power take-off are examined. Based on the power performance of WECs, recommendations are also provided for optimum power absorption.

Towards improved understanding of naval ship structural performance via virtual hull monitoring

Weight-optimised ships, such as High Speed Light Craft (HSLC), are operated by navies around the world. Naval ships must perform in harsh and contested ocean environments. Operations in high sea states result in large linear and nonlinear ship motions which in turn, induce significant loads on ship structures and accelerate structural fatigue. Monitoring and assessment of fatigue on ship structures is important for navies, to understand the performance, limitations, and life-cycle costs of their ships. An established method for monitoring structural responses is via long-term measurements, using Instrumented Hull Monitoring (IHM). However, this approach is generally too resource-intensive to be implemented on a broad scale. Virtual Hull Monitoring (VHM) is a technique to couple on-board ship data, such as Global Positioning System (GPS) data, with hindcast wave data. The resulting enriched dataset enables robust numerical fatigue analysis, because the structural responses are related to the encountered wave environment, rather than based on global wave statistics. Thus, the concept of VHM is receiving increased attention in both commercial and military sectors. This is due to its low cost and the relative ease of implementation compared to IHM. Using a Royal Australian Navy HSLC as the test bed, this study presents an investigation into the feasibility of VHM by comparing results with available IHM data. An efficient framework was developed in PythonTM to extract and couple hindcast wave data to ship speed and position, calculating the resultant stresses on the ship structure, and comparing with the measured stresses from IHM. The novel aspects of this work include the use of a semi-displacement hullform, and the utilisation of both sea-trials and long-term measurements. The study shows promising results for VHM. Finally, recommendations for further work are provided.

A Wave Directionality and a Within-Year Wave Climate Variability Effects on the Long-Term Extreme Significant Wave Heights Prediction in the Adriatic Sea

The extreme significant wave height predictions often neglect within-year wave climate variability and wave directionality. Depending on a geographical region, local wind patterns and year climate variability could have an influence on the long-term prediction of waves. The Adriatic Sea having two dominant wind patterns of different characteristics, Bura and Jugo, is a great example for the case study. The 23-year hindcast wave data used in the presented study is extracted from the WorldWaves database. Based on wind and wave data, annual extreme significant wave heights generated by different wind patterns and for different months are fitted by Gumbel distribution using maximum likelihood estimation. Combined long-term extremes are then predicted by calculating system probability. It was found that considering the wave directionality, and especially the seasonality of wave climate, leads to a larger prediction of extreme significant wave heights. The extreme value prediction considering wave directionality on average yields 4% larger significant wave heights, while considering within-year climate variability leads to, on average, 8% larger extremes compared to the predictions when both effects are neglected.

Analyzing wave direction scenarios for large waves in deep water and its impact on littoral drift

In this study, four types of wave direction scenarios in large waves greater than 3 m in deep water are examined by analyzing NOAA's wave hindcast data spanning over 40 years. The results reveal that wave direction changes at the starting, peak and ending of large/storm waves, accompanying by changing wave heights with wave direction becoming in perpendicular to the coastal orientation when waves reaching a peak. Within the bulk of NOAA wave data which last 1.65 days, 55.1% of the large/storm waves had wave direction returning to the starting direction on the wane of the waves, while the remaining 44.9% reversed to the opposite side of the starting direction. Based on this finding, littoral drift is calculated for each scenario by the CERC equation, on the basis of deep water wave parameters. The resulting littoral drift is then used in a numerical model to calculate shoreline changes at Jeongdongjin Beach in Korea, where a natural groin block the longshore sediment transport. The result of shoreline change in the vicinity of the groin suggests beach may become stable about one day after the end of a short-term large wave/storm event, or 2 days after the peak wave height.

Nearshore Wave Energy Resource Assessment for Off-Grid Islands: A Case Study in Cuyo Island, Palawan, Philippines

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 (Hs), peak period (Tp) and wave power density (Pd) during a northeast monsoon are Hs = 1.35 m, Tp = 4.79 s and Pd = 4.05 kW/m, respectively, while a southwest monsoon, which is sheltered by the mainland, results in Hs = 0.52 m, Tp = 3.37 s and Pd = 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.

Modelling and simulation of extreme wave heights around agatti island of lakshadweep, west coast of India

Small islands experience variation in wave energy regime along shorter shoreline due to refraction, diffraction and variability in direction of wave travel. Nearshore wave climate around these islands is quite complex due to wave transformation associated with configuration of islands, and high steepness in the bathymetry. Understanding wave energy will help in identifying suitable locations for coastal structures, wave energy devices and sediment budgeting. Assessment of extreme wave climate around the islands play a crucial role in the design and survival of coastal infrastructure for any developmental activities in islands. This study investigates the extreme wave climate around the Agatti island of Union Territory of Lakshadweep located in west coast of India. The spatial variability of wave power distribution around the Agatti island is analyzed based on 10 years of wave hindcast data from spectral wave modelling for the period between 2011 and 2020 using spectral wave model. In this study, third-generation spectral wave model was used to simulate the wave climate over the Arabian Sea. Regional model was established using ECMWF model winds and the offshore wave parameters were validated with deep water ocean observations AD07 and AD09 deployed in the Arabian Sea. To understand the nearshore wave transformation along the Agatti island, local wave model of fine resolution was established using high resolution bathymetry and is validated using the coastal buoy (CB02) deployed near Agatti. Nearshore wave parameters such as Significant wave height, Peak wave period (Tp) and Mean wave direction (θm) were analyzed. The wave power distribution around the island was quantified and demarcated for siting of offshore structures for developmental activities. The study reveals that the south zone of the island is more energetic with annual mean wave power of 8–12 kW/m and during monsoon, wave power more than 28 kW/m is observed. The extreme value theory based on Generalized Extreme Value distribution is applied to the extreme wave height estimate based on modelled wave data around the Agatti island. The extreme wave heights for different return periods were estimated around the Agatti island for design and analysis of coastal infrastructure.

Evaluation of ship operational effect based on long-term encountered sea states using wave hindcast combined with storm avoidance model

Ships avoid severe sea states for the safety of lives and property and to save energy. Therefore, the actual sea states encountered by ships differ from nature and are affected by human operational effects that we refer to as the “ship operational effect”. The evaluation of the ship operational effect is crucial for the rational design of structural strength of the hull. In this study, we derived the sea states encountered over 25 years in the North Atlantic, by considering storm avoidance by merchant ships. We then performed long-term predictions of the ship motions and wave loads of 75 merchant ships. Existing pioneering studies used automatic identification system (AIS)-based ship locations and timestamps to subsample wave hindcast data along ship tracks for a limited duration. Unlike existing studies, we used a statistical storm avoidance model of merchant ships to reconstruct the sea states, encountered over 25 years, in the North Atlantic. Owing to the ship operational effect, the long-term prediction values of roll motion, pitch motion, vertical bending moment amidships, and hydrodynamic pressure on bottom centerline amidships of merchant ships, at the probability level 10−8, were reduced by approximately 10–20%, and the coefficient of the ship operational effect was 0.8–0.9. Furthermore, we evaluated the uncertainties in the ship operational effect. The values deviated by as much as 6%, depending on the choice of wave hindcast products (TodaiWW3-NK, IOWAGA, and ERA5). The variation based on the parameter settings of the storm avoidance model (severity of the storm, radius of influence of the storm, and number of ship locations) was up to approximately 1 m at a probability level of 10−5 of the encountered sea states for 25 years.

Systematization of short-term forecasts of regional wave heights using a machine learning technique and long-term wave hindcast

Machine-learning techniques have been applied to wave forecasting to address the implementational and computational challenges of conventional numerical wave models. Most previous studies emphasized the accuracy of approaches based on in situ wave measurements, but such approaches are site-specific and lack the spatial and temporal fidelity required by regional wave climate forecasts. This study presents a novel systematization of forecasting regional wave heights at sufficient spatial resolution and coverage, using long-term wave hindcasts generated by numerical wave models as a training dataset for a long short-term memory (LSTM). This systematization not only ensures the accuracy of the model's forecasts but demonstrates the applicability of long-term wave hindcasts as input data. It involves thoroughly investigating the dependence of model accuracy on multi-task LSTM structures (training variables, input data record periods, and forecast lead times), and on regional wave climates (different wave sites and sea states). The resulting model performance is spatially heterogeneous in global wave forecasts, underlining the need for validation of wave forecasting models to global wave climates. This study reveals that machine-learning techniques that leverage validated long-term wave hindcasts can successfully forecast regional wave climates. As access to high-resolution regional wave hindcast data improves, accuracy will also increase.