Third-generation Wave Model Research Articles

Assessment of Extreme and Metocean Conditions in the Swedish Exclusive Economic Zone for Wave Energy

Here, accessibility to near-shore and offshore marine sites is evaluated based on wave and ice conditions. High-resolution third-generation wave model results are used to examine the operation and maintenance conditions for renewable energy sources with a focus on wave energy. Special focus is given to the wave field and ice characteristics for areas within the Swedish Exclusive Economic Zone including analysis of return levels for extreme values for significant wave height, which provides guidance for dimensioning wave energy converters. It is shown that the number of weather windows and accessibility are influenced by distance from the coast and sea-ice conditions. The longest waiting periods for the closest weather window that is available for Operation and Maintenance (O&M) is in ice-free conditions shown to be strongly correlated with the fetch conditions. The sheltered Baltic Sea is shown to have very high accessibility if marine infrastructure and vessels are designed for access limits of significant wave height up to 3 m. In the northern basins, the waiting periods increase significantly, if and when the ice-conditions are found to be critical for the O&M activity considered. The ice-conditions are examined based on compiled operational sea-ice data over a climatic time period of 34 years. The results are location specific for the Swedish Exclusive Economic Zone, but the analysis methods are transferable and applicable to many other parts of the world, to facilitate assessment of the most promising areas in different regions.

Wave energy assessment based on a 33-year hindcast for the Canary Islands

A wave energy assessment is performed in the Canary Islands, based on a 33-year hindcast, between 1979 and 2011. The third-generation wave models WAVEWATCH III and SWAN are used to study the generation of the waves in the North Atlantic basin and the transformation of the waves in the Canary Islands, respectively. The hindcast system was validated in a prior study, showing a relevant wave energy resource distribution with an average annual energy availability of 25–30 kW/m. This study intends to offer a detail description of the wave climate, combining the previous results with the new studies. The results show that the seasonal mean distribution of wave energy varies between 15 and 20 kW/m, in the spring and 25–30 kW/m, in the winter, while in the less energetic areas the seasonal average varies between 10 and 15 kW/m, in the spring, and 15–20 kW/m, in the winter. Also, the temporal variability indexes suggest that the East coast of the islands presents less variability and that the North/Northwest coast of the islands exhibits greater energy availability.

10-Year Wind and Wave Energy Assessment in the North Indian Ocean

With increasing energy shortages and global warming, clean and renewable energy sources, such as wind and wave energy, have gained widespread attention. In this study, the third-generation wave model WAVEWATCH-III (WW3) is used to simulate wave height in the North Indian Ocean (NIO), from 2008 to 2017, using the wind data from the European Centre for Medium-Range Weather Forecasts Renalysis datasets. The simulated results show good correlation with data obtained from altimetry. Analysis of wind and wave energy resources in the NIO is carried out considering energy density, the exploitable energy, the energy density stability, and monthly and seasonal variability indices. The results show that most areas of the NIO have abundant wind energy and at the Somali Waters are rich in wave energy resources, with wind energy densities above 200 W/m2 and wave energy densities above 15 KW/m. The most energy-rich areas are the Somali Waters, the Arabian Sea, and the southern part of the NIO (wind energy density 350–650 W/m2, wave energy density 9–24 KW/m), followed by the Laccadive sea (wind energy density 150–350 W/m2, wave energy density 6–9 KW/m), while the central part of the NIO is relatively poor (wind energy density less than 150 W/m2, wave energy density below 6 KW/m).

Effect of the drag coefficient on a typhoon wave model

The effect of the drag coefficient on a typhoon wave model is investigated. Drag coefficients for Pingtan Island are derived from the progress of nine typhoons using COARE 3.0 software. The wind parameters are obtained using the Weather Research and Forecasting model. The simulation of wind agrees well with observations. Typhoon wave fields are then simulated using the third-generation wave model SWAN. The wave model includes exponential and linear growths of the wind input, which determine the wave-growth mode. A triple triangular mesh is adopted with spatial resolution as fine as 100 m nearshore. The SWAN model performs better when using the new drag coefficient rather than the original coefficient.

Impact of Ice Data Quality and Treatment on Wave Hindcast Statistics in Seasonally Ice-Covered Seas

The seasonal ice cover has significant effect on the wave climate of the Baltic Sea. We used the third-generation wave model WAM to simulate the Baltic Sea wave field during four ice seasons (2009†-2012). We used data from two different sources: daily ice charts compiled by FMI’s Ice Service and modeled daily mean ice concentration from SMHI’s NEMO†Nordic model. We utilized two different methods: a fixed threshold of 30 % ice concentration, after which wave energy is set to zero, and a grid obstruction method up to 70 % ice concentration, after which wave energy is set to zero. The simulations run using ice chart data had slightly better accuracy than the simulation using NEMO-Nordic ice data, when compared to altimeter measurements. The analysis of the monthly mean statistics of significant wave height (SWH) showed that the differences between the simulations were relatively small and mainly seen in the Bothnian Bay, the Quark, and the eastern Gulf of Finland. There were larger differences, up to 3.2 m, in the monthly maximum values of SWH. These resulted from individual high wind situations during which the ice edge in the ice chart and NEMO-Nordic was located differently. The two different methods to handle ice concentration resulted only in small differences in the SWH statistics, typically near the ice edge. However, in some individual cases the two methods resulted in quite large differences in the simulated SWH and the handling of ice concentrations as additional grid obstructions could be important, for example, in operational wave forecasting.

Hydroelastic responses of a 3-module VLFS in the waves influenced by complicated geographic environment

During the Very Large Floating Structure (VLFS) is deployed not far from the shore line or near the island, the ocean waves and hydroelastic responses of VLFS could be greatly influenced by the complicated geographic environment, particularly for the depth-varying seabed. Firstly, the extreme wave parameters of different recurrence periods at the deployed location are solved by the numerical simulations of wave evolution and propagation in an archipelagic water field using the third-generation wave model. The numerical results are compared with the data from the on-site measurement and model test in a shallow water wave basin. Secondly, one hydroelastic numerical coupled model of the floating structure responding to the waves in shallow water with a specified seabed profile is proposed and validated by comparing with the model test results. Finally, based on the above model, the hydroelastic responses of the VLFS in the waves influenced by complicated geographic environment are obtained. It is concluded that the wave statistics experiences obviously changes when propagating and approaching towards the island; meanwhile, the complicated seabed profile has an apparent influence on the hydroelastic responses of the VLFS.

Variations in Winter Ocean Wave Climate in the Japan Sea under the Global Warming Condition

Future variations in the ocean wave climate caused by global warming could affect various coastal issues. Using a third-generation wave model, this study produced projections of the ocean wave climate for winter around Japan, focusing on the Japan Sea side. Wave simulation forcing (sea surface wind) was generated through five different global warming experiments. More than half the future wave projections showed an increasing tendency of the climatological mean significant wave height during winter. However, the maximum significant wave height did not show any clear tendency in future variation. The top 1% of significant wave heights and mean wave periods showed apparent increases in frequencies of higher/longer waves in three out of the five future projections. Frequency distributions of significant wave height, mean wave period, mean wavelength and wave direction showed various future variations (reduction of small ocean waves, increasing frequency of waves from the west). There are large uncertainties in future variations of wave climate in the Japan Sea, but the high probability of variations in daily wave climate is recognized, based on the future wave projections. Variations in daily wave climate are important because they could affect the topography and environment of the coast through long-term repetitive actions.

Surface wave simulation during winter with sea ice in the Bohai Sea

Sea ice can attenuate wave energy significantly when waves propagate through ice covers. In this study, a third-generation wave model called simulating wave nearshore (SWAN) was advanced to include damping of wave energy due to friction in the boundary layer below the ice. With the addition of an eddy viscosity wave-ice model, the resulting new SWAN model was applied to simulate wave height in the Bohai Sea during the freezing winter. Its performance was validated with available buoy data near the ice edge, and the new model showed an improvement in accuracy because it considered the ice effect on waves. We then performed a wave hindcast for the Bohai Sea during a freezing period in the winter of 2016 that had the severest ice conditions in recent years and found that the mean significant wave height changed by approximately 16.52%. In the Liaodong Bay, where sea ice concentration is highest, the change reached 32.57%, compared with the most recent SWAN model version. The average influence of sea ice on wave height simulation was also evaluated over a five-year (2013-2017) hindcast during January and February. We found that the wave height decrease was more significant in storm conditions even the eddy viscosity wave-ice model itself showed no advantage on damping stronger waves.

Characterization of Wave Energy Potential for the Baltic Sea with Focus on the Swedish Exclusive Economic Zone

In this study, a third-generation wave model is used to examine the wave power resource for the Baltic Sea region at an unprecedented one-kilometer-scale resolution for the years 1998 to 2013. Special focus is given to the evaluation and description of wave field characteristics for the Swedish Exclusive Economic Zone (SEEZ). It is carried out to provide a more detailed assessment of the potential of waves as a renewable energy resource for the region. The wave energy potential is largely controlled by the distance from the coast and the fetch associated with the prevailing dominant wave direction. The ice cover is also shown to significantly influence the wave power resource, especially in the most northern basins of the SEEZ. For the areas in focus here, the potential annual average wave energy flux reaches 45 MWh/m/year in the two sub-basins with the highest wave energies, but local variations are up to 65 MWh/m/year. The assessment provides the basis for a further detailed identification of potential sites for wave energy converters. An outlook is given for additional aspects studied within a broad multi-disciplinary project to assess the conditions for offshore wave energy conversion within the SEEZ.

Observation-Based Source Terms in the Third-Generation Wave Model WAVEWATCH III: Updates and Verification

AbstractThe observation-based source terms available in the third-generation wave model WAVEWATCH III (i.e., the ST6 package for parameterizations of wind input, wave breaking, and swell dissipation terms) are recalibrated and verified against a series of academic and realistic simulations, including the fetch/duration-limited test, a Lake Michigan hindcast, and a 1-yr global hindcast. The updated ST6 not only performs well in predicting commonly used bulk wave parameters (e.g., significant wave height and wave period) but also yields a clearly improved estimation of high-frequency energy level (in terms of saturation spectrum and mean square slope). In the duration-limited test, we investigate the modeled wave spectrum in a detailed way by introducing spectral metrics for the tail and the peak of the omnidirectional wave spectrum and for the directionality of the two-dimensional frequency–direction spectrum. The omnidirectional frequency spectrum E(f) from the recalibrated ST6 shows a clear transition behavior from a power law of approximately f−4 to a power law of about f−5, comparable to previous field studies. Different solvers for nonlinear wave interactions are applied with ST6, including the Discrete Interaction Approximation (DIA), the more expensive Generalized Multiple DIA (GMD), and the very expensive exact solutions [using the Webb–Resio–Tracy method (WRT)]. The GMD-simulated E(f) is in excellent agreement with that from WRT. Nonetheless, we find the peak of E(f) modeled by the GMD and WRT appears too narrow. It is also shown that in the 1-yr global hindcast, the DIA-based model overestimates the low-frequency wave energy (wave period T > 16 s) by 90%. Such model errors are reduced significantly by the GMD to ~20%.

NUMERICAL SIMULATION OF CYCLONE NARGIS (2008) AND ITS RELATED WAVE FIELD AT MYANMAR COAST BY USING WRF-SWAN MODEL

Understanding potentially extreme wave conditions during cyclonic events is essential for many coastal projects such as port planning, construction and coastline protection. For that purpose, numerical modeling techniques have been utilized efficiently to predict cyclonic wind and wave fields. In this study, cyclone Nargis (2008), which is the most severe cyclone in recorded history of Myanmar and its related wind generated waves (offshore and nearshore) are reproduced by using Advanced Weather Research and Forecasting (WRF-ARW, Skamarock et al., 2008) and Simulating WAves Nearshore (SWAN, a third-generation wave model developed at TU Delft). In fact, a number of studies have been conducted on simulating the cyclone Nargis and its subsequent storm surges (such as Raju et al., 2011 and Tasnim et al., 2015). By contrast, this research mainly focuses on configuration of wind waves caused by cyclone Nargis in order to understand the extreme wave figure at Myanmar coast during cyclone Nargis. The reliability and performance of the WRF-SWAN model is also checked. The model results are compared with observed data from different sources (JTWC, IMD, NOAA etc.).

An Assessment of Two Models of Wave Propagation in an Estuary Protected by Breakwaters

Breakwaters influence coastal wave climate and circulation by blocking and dissipating wave energy. In a large harbor, these effects are combined with wave generation, refraction and reflection. Accurate representation of these processes is essential to the determination of coastal circulation and wave processes. MIKE21SW and SWAN are two third-generation spectral wave models which are used widely in coastal research and engineering applications. Recently improved versions of the models are able to consider the influence of breakwater structures. In this study, we used available observations to evaluate the accuracy of model simulations of waves in New Haven Harbor, Connecticut, USA, an estuary with three detached breakwaters near the mouth. The models were executed on their optimum unstructured triangular grid. The boundary conditions were derived from a bottom mounted Acoustic Doppler Current Profilers (ADCP) on the offshore side of the breakwaters. Wind forcing was applied using data from the Central Long Island Sound buoy. We found that both models were largely consistent with observations during storms. However, MIKE21SW predicted some of storm peaks slightly better. SWAN required the finer grid to achieve the optimum condition, but as it uses a fast, fully implicit algorithm, the computational times were similar. Also, the sensitivity analysis represents that wind forcing and the breakwaters have significant impact on the results.

Characteristics of global waves based on the third-generation wave model SWAN

Long-term wave data at a global scale are crucial for the studying characteristics of global waves, such as spatial distributions and extreme waves. These characteristics play significant roles in the design, construction, installation and operation activities of marine structures. Because of the limited resolution and coverage of instrumental measurements, the global wave hindcast is widely used. To develop this hindcast, the Simulating WAves Nearshore (SWAN) model is forced with the ERA-Interim wind database from 1979 to 2017 with a resolution of 0.25° in both longitude and latitude. The hourly wave parameters, such as the significant wave height and the mean period, are validated against buoy measurements over the Northwest Pacific Ocean, the Northeast Pacific Ocean and the Northwest Atlantic Ocean. Based on the 39-year simulated results, the spatial distributions of mean and maximal significant wave heights are analysed for all 39 years, every decade, 4 seasons, 12 months and special years; extreme waves are studied at the global scale and at every computational point.

Influence of Wave State and Sea Spray on the Roughness Length: Feedback on Medicanes

Occasionally, storms that share many features with tropical cyclones, including the presence of a quasi-circular “eye” a warm core and strong winds, are observed in the Mediterranean. Generally, they are known as Medicanes, or tropical-like cyclones (TLC). Due to the intense wind forcings and the consequent development of high wind waves, a large number of sea spray droplets—both from bubble bursting and spume tearing processes—are likely to be produced at the sea surface. In order to take into account this process, we implemented an additional Sea Spray Source Function (SSSF) in WRF-Chem, model version 3.6.1, using the GOCART (Goddard Chemistry Aerosol Radiation and Transport) aerosol sectional module. Traditionally, air-sea momentum fluxes are computed through the classical Charnock relation that does not consider the wave-state and sea spray effects on the sea surface roughness explicitly. In order to take into account these forcing, we implemented a more recent parameterization of the sea surface aerodynamic roughness within the WRF surface layer model, which may be applicable to both moderate and high wind conditions. The implemented SSSF and sea surface roughness parameterization have been tested using an operative model sequence based on COAWST (Coupled Ocean Atmosphere Wave Sediment Transport) and WRF-Chem. The third-generation wave model SWAN (Simulating Waves Nearshore), two-way coupled with the WRF atmospheric model in the COAWST framework, provided wave field parameters. Numerical simulations have been integrated with the WRF-Chem chemistry package, with the aim of calculating the sea spray generated by the waves and to include its effect in the Charnock roughness parametrization together with the sea state effect. A single case study is performed, considering the Medicane that affected south-eastern Italy on 26 September 2006. Since this Medicane is one of the most deeply analysed in literature, its investigation can easily shed some light on the feedbacks between sea spray and drag coefficients.

The impact of climate change on the wave climate in the Gulf of St. Lawrence

The purpose of this study is to investigate possible local changes in the wave climate for the coastal waters off eastern Canada, particularly in the Gulf of St. Lawrence (GSL) related to changes in marine winds, storm and the sea ice climate, due to climate change. These analyses are based on application of a dynamical downscaling approach whereby a regional climate model is driven by climate change estimates from the Canadian Global Climate Model (CGCM3) to provide relatively high resolution winds to drive a wave model. The CGCM3 simulation follows the A1B climate change scenario of the Special Report on Emission Scenarios from the Fourth Assessment Report (AR4) of the Intergovernmental Panel on Climate Change (IPCC AR4, 2007). The analyses of the wave climate are based on simulations of the waves from a third-generation wave model, WAVEWATCHIII™, and the downscaled winds obtained from the Canadian Regional (atmospheric) Climate Model (CRCM). We show that the significant wave heights in the Gulf of St. Lawrence (hereafter GSL) and neighboring coastal waters will slightly increase in the winter and decrease in the summer, in response to changes in storms and sea ice in the future climate (2040–2069) compared to the present wave climate, represented as 1970–1999. This time period is denoted as the “historical” wave climate in this study. In summer, the changes in significant wave heights (Hs) are associated with estimated decreases in the frequency of the occurrence of the cyclones. Projected changes in return values for summer extremes in the wave climate are consistent with the associated changes in the maximum Hs values. In winter, the projected increases in return values are mostly concentrated in the St. Lawrence Estuary, the northern and southwestern GSL, consistent with changes in the maximum waves in these regions. An important factor related to change in the winter wave climate is change in the sea ice.

Co-located wave-wind farms for improved O&M efficiency

Co-located wave-wind farms enhance the competitiveness of marine energy in a number of ways, and in particular through their benefits in terms of Operation and Maintenance (O&M) – the subject of this work. The objective is to investigate how the reduction in significant wave height within a co-located farm caused by the extraction of wave power by the wave energy converters (WECs), also known as the shadow effect, results in enlarged weather windows for O&M tasks. This investigation is carried out through a case study of four wind farms in the North Sea, including a sensitivity analysis in terms of: (i) location (depth and distance from the coast), (ii) sea climate, and (iii) wind farm layout. Real (observed) sea conditions are considered, and a third-generation wave model (SWAN) is implemented on a high-resolution grid. It is found that the combination of wave and offshore wind energy increases the accessibility for O&M tasks over 13% in all the cases considered, leading to accessibility values of up to 82%. The best results are obtained for wind farms with square-like geometries, where the co-located WECs intercept both the prevailing and secondary wave directions, and with small spacings between converters. Besides, proximity to land is found to not be a favourable factor for exploiting this synergy between wave and offshore wind power.

South China Sea Wave Characteristics under Combined Wind Forcing of Typhoon and Winter Monsoon

Since monsoon winds prevail in South China Sea (SCS), SCS is unique for investigating wave characteristics during a typhoon’s passage in conjunction with steady monsoon wind forcing. This study investigated SCS wave characteristics using Wave Watch III, the third-generation wave model with winter typhoon forcing. The model was forced by a high resolution wind field from NASA’s Cross Calibrated Multi Platform (CCMP) ocean surface winds combined with the tropical cyclone wind model. The Wave Watch III model was evaluated using Jason-2 altimetry observations during the period of Typhoon Durian (2006).

A global high-resolution ocean wave model improved by assimilating the satellite altimeter significant wave height

This study examines the effects of data assimilation using Significant Wave Height (SWH) from three satellite altimeters, notably the Jason-2, Jason-3 and SAtellite with ARgos and ALtiKa (SARAL), orbiting in space and incorporating the data into a global high-resolution ocean wave model. The third-generation wave model, WAVEWATCH III (WW3), was adopted for numerical simulation and its spatial resolution was refined to 0.2°. Data assimilation is carried out using the Optimal Interpolation (OI) scheme to demonstrate the feasibility and the benefits of simultaneously assimilating the along-track SWH data from multi-satellite altimeters into a global ocean wave model. Higher resolution global ocean wave models can advantageously account for the swell propagation from deep ocean waters without open boundary conditions, as well as simulate smaller scale wind waves from the coastal zones conveniently, effectively and in tandem. The Root Mean Square (RMS) of non-assimilation experiment is 0.54 m, which is smaller than the previous coarse resolution global wave modelling. Minor improvement is found when only one 10-min frequency, SWH data from the Jason-2 altimeter was assimilated into the global ocean wave model. However, the RMS against buoy observations is highly reduced (i.e. approximately 0.42 m) when the SWH data from three satellite altimeters (i.e. Jason-2, Jason-3 and SARAL) are simultaneously assimilated into the global high-resolution ocean wave model and in return, led to significant model improvement. This study can also provide some implications for wave predictions in global oceans.

Interannual variability of significant wave height in the northern South China Sea

Based on the hindcast data from third-generation wave model WAVEWATCH III, this study presents a notable interannual variability of significant wave height in the northern South China Sea. As indicated by the empirical orthogonal function analysis result of the significant wave height during 1976–2005, the first mode of this analysis captures a monopole structure with maximum amplitude in the southwestern Luzon Strait. Power spectrum analysis of the first empirical orthogonal function time series indicates that the significant wave height peaks at 2.67 and 8 year periods in the northern South China Sea. The first-time series had good correlation with El Niño events, with a correlation coefficient of -0.58. By comparing frequency and total duration of the intense tropical cyclones with the significant wave height in the northern South China Sea, it is revealed that the two were associated during 1978–1998 and that the recent increase of the significant wave height is due to the increase in total duration of intense tropical cyclones during 1999–2005. The sea level pressures also support the interannual variability of significant wave height in the northern South China Sea.

Prediction of Uncertainty Using the Third Generation Wave Model WAVEWATCH III Driven By ERA-40 and Blended Winds in the North Indian Ocean

Simulation of waves in North Indian Ocean using ERA-40 and QuikSCAT/NCEP blended winds over 1° × 1° grid resolutions has been realised globally as well regionally using the third-generation wave model WAVEWATCH III (WWIII). Moreover, the model performance was evaluated by quantifying the uncertainty`s. So, WWIII simulations have been carried out for the North Indian Ocean from 50°E to 100°E and 0°N to 30°N with the past analysed winds (hindcasting) and the boundary conditions from the global run. The model outputs such as significant wave height (Hs) and mean wave period (Tc) are compared with the buoy measurements. To assess the performance, various statistical errors have been estimated by validating the model results against moored buoy data in the Arabian Sea and Bay of Bengal. The validation of WWIII with buoy measurements gave promising results for the North Indian Ocean with Model Performance Index ranging from 0.86 to 0.99, irrespective of the input winds. Also, Percentage Error ranges from 3.1 to 18.8% for the selected periods (January, July and October) except April. Further, the model was examined with different wind forcing’s and the study revealed better performances with blended winds, which could accurately predict Hs and Tc at buoy locations. This study concludes that, WWIII model predicts the sea-state evolution with acceptable uncertainty, which is reliable for the Indian Seas (North Indian Ocean) using the analysed wind fields. Further, better accuracy is achieved using blended wind products.