Numerical Wave Model Research Articles

Surrogate light curve models for kilonovae with comprehensive wind ejecta outflows and parameter estimation for AT2017gfo

The electromagnetic emission resulting from neutron star mergers have been shown to encode properties of the ejected material in their light curves. The ejecta properties inferred from the kilonova emission has been in tension with those calculated based on the gravitational wave signal and numerical relativity models. Motivated by this tension, we construct a broad set of surrogate light curve models derived for kilonova ejecta. The four-parameter family of two-dimensional anisotropic simulations and its associated surrogate explore different assumptions about the wind outflow morphology and outflow composition, keeping the dynamical ejecta component consistent. We present the capabilities of these surrogate models in interpolating kilonova light curves across various ejecta parameters and perform parameter estimation for AT2017gfo both without any assumptions on the outflow and under the assumption that the outflow must be representative of solar r-process abundance patterns. Our parameter estimation for AT2017gfo shows these surrogate models help alleviate the ejecta property discrepancy while also illustrating the impact of systematic modeling uncertainties on these properties, urging further investigation.

Wave climate and energy resources in American Samoa from a 42-year high-resolution hindcast

This paper presents an analysis of the wave climate and a characterization of the wave energy resources in American Samoa, a U.S. territory covering seven south central Pacific islands and atolls. A numerical wave model based on WAVEWATCH III® and unstructured SWAN was developed, validated, and executed for 1979–2020 to generate a hindcast dataset suitable for resource characterization. Model-data comparisons were performed with measurements collected in situ and from satellite-based altimeters. The model was found to perform well with a bias in significant wave height of −0.14 m and −0.06 m against buoy and altimeters, respectively. The multimodal sea state of American Samoa is investigated by identifying the sources of energy reaching the islands and partitioning the wave spectrum accordingly. The wave resources characterization follows the International Electrotechnical Commission Technical Specifications to be compatible with studies performed for other U.S. regions. The average omnidirectional wave power at 2 km from shore around Tutuila, the main island of American Samoa, is 14 kW/m. Locations east and west of the islands have a more consistent resource throughout the year because the northwest and southwest swells that are dominant during different seasons complement each other.

Numerical lamb wave modeling and analysis for cure cycle shortening of carbon fiber composites

Advanced carbon fiber composites are renowned for their great tenacity as, although being thin, they provide great strength, keeping structures light in weight. The composites industry struggles with longer cure times when compared to other traditional material production. In this study, a computational model for a carbon fiber reinforced polymers (CFRP) plate is developed to imitate experimental monitoring of its cure cycle and degree of cure. The CFRP storage modulus is measured during the curing cycle with the aid of dynamic mechanical analysis, and its trend is incorporated into COMSOL combined structural and electrostatics multiphysics to replicate the same mechanical fluctuations during oven curing. Then, Lamb waves are excited and sensed via sandwiched piezoelectric transducers in a reusable Polytetrafluoroethylene sensing film to monitor the structural health of the structure. Minimum viscosity, gelation and vitrification are cure parameters observed from analyzing voltage and velocity curves of the A0 mode of the sensed signal. The cure cycle is trimmed, and the same cure parameters are shown offset by the 1 h deducted, proving that the numerical model is valid. Further analysis of the numerical voltage and velocity curves suggests an additional cure parameter defined as “gelation initiation” when compared directly to the experimental trends. Additionally, the decomposition of different wavefield modes is scrutinized to describe their scattering throughout the layered structure. Results show a new entrapped antisymmetric mode appearing inside the CFRP laminate at the start of the cure, which suggests that the previously studied A0 mode had been initially converted from the CFRP S0 mode.

A Cartesian grid-based two-dimensional plus time method for simulating ship bow waves

Numerical modeling of ship bow waves is still hard work, partly due to their multiscale features. Direct three-dimensional (3D) computational fluid dynamics simulation could be an appropriate choice to investigate the problem. However, limited by computational resources, small scale phenomena such as spraying and wave breaking that could be observed during the ship wave generation process are usually simplified or not fully distinguished in a 3D simulation. In order to accurately capture the small scales flow field information with the available computational resource, a new Cartesian grid-based two-dimensional plus time (2D+t) method is developed in this paper, which is suitable for 3D slender ships. With this method, a 3D steady ship wave-making problem is transformed into a 2D unsteady wave-making problem of a deformable body. The boundary velocity of the deformable body is obtained with a novel interpolation algorithm, which is then enforced on the background Cartesian grid by a newly proposed immersed boundary method. The pressure boundary condition on the surface of the deformable body is explicitly considered in the solution of the pressure Poisson equation. Moreover, an extra open boundary condition is applied to the upper boundary of the computational domain to achieve a better conservation. The proposed model is validated with selected cases, showing that the model is capable of simulating both non-wave-breaking and wave-breaking problems.

Typhoon field construction and wind-induced wave model optimization based on topographic parameters

In recent years, most of the research on typhoon in Fujian Province of China has stayed in the typhoon wave simulation under the influence of wind fields. In order to study the influence of land terrain on typhoon wave fields, the terrain height parameters are introduced into the wind field simulation through the third-generation typhoon wave numerical model. The numerical simulation results of the model are verified and analyzed by referring to the data of significant wave height and wind speed of typhoon Fung-wong (200808) and typhoon Jangmi (200815) when it is across Taiwan Island. The results show that the relative error of the maximum wind speed and the significant wave height is reduced after the wind field optimization, which is more consistent with the observed data. The model accuracy is improved after optimization; Typhoon Fung-Wong, which crossed Taiwan, showed the most significant reduction in wind speed. Significant wave height is positively correlated with wind speed. The wave height distribution shows a gradually decreasing trend from the cyclone center to the coast, and the significant wave heights of the typhoon moving direction show pronounced asymmetry. Affected by the land topography, the distribution of significant wave height generally shows a downward trend, and the area of height water level area decreases.

Statistical and Dynamical Characteristics of Extreme Wave Crests Assessed with Field Measurements from the North Sea

Abstract Wave crests of unexpected height and steepness pose a danger to activities at sea, and long-term field measurements provide important clues for understanding the environmental conditions that are conducive to their generation and behavior. We present a novel dataset of high-frequency laser altimeter measurements of the sea surface elevation gathered over a period of 18 years from 2003 to 2020 on an offshore platform in the central North Sea. Our analysis of crest height distributions in the dataset shows that mature, high sea states with high spectral steepness and narrow directional spreading exhibit crest height statistics that significantly deviate from standard second-order models. Conversely, crest heights in developing sea states with similarly high steepness but wide directional spread correspond well to second-order theory adjusted for broad frequency bandwidth. The long-term point time series measurements are complemented with space–time stereo video observations from the same location, collected during five separate storm events during the 2019/20 winter season. An examination of the crest dynamics of the space–time extreme wave crests in the stereo video dataset reveals that the crest speeds exhibit a slowdown localized around the moment of maximum crest elevation, in line with prevailing theory on nonlinear wave group dynamics. Extending on previously published observations focused on breaking crests, our results are consistent for both breaking and nonbreaking extreme crests. We show that wave crest steepness estimated from time series using the linear dispersion relation may overestimate the geometrically measured crest steepness by up to 25% if the crest speed slowdown is not taken into account. Significance Statement Better understanding of the statistics and dynamical behavior of extreme ocean surface wave crests is crucial for improving the safety of various operations at sea. Our study provides new, long-term field evidence of the combined effects of wave field steepness and directionality on the statistical distributions of crest heights in storm conditions. Moreover, we show that the dynamical characteristics of extreme wave crests are well described by recently identified nonlinear wave group dynamics. This finding has implications, for example, for wave force calculations and the treatment of wave breaking in numerical wave models.

Comparative Study on Numerical Simulation of Wave-Current Nonlinear Interaction Based on Improved Mass Source Function

In coastal waters, wave propagation is often affected by rivers and tides. The wave current interaction increases the complexity of the wave propagation. In this study, we consider the Boussinesq type equation with an improved dispersion term as the governing equation and establish a numerical model of wave propagation in the coexistence of wave current environment. Firstly, we use the MIKE 21 BW model to simulate the propagation of dual-frequency waves. The Navier–Stokes equation wave model is used to verify the results and the Fourier transform is used to analyze and discuss the dual-frequency waves. Our findings show that the numerical model established by the Boussinesq equation can better describe the nonlinear interaction between waves more accurately at a much higher computational efficiency compared with the Navier–Stokes equation wave model. In addition, we set the constant current source point in the wave numerical model and conduct the numerical simulation of waves in the current environment, by improving the mass source wave generation method. The numerical simulation of wave-current interactions between uniform and variable water depths is performed, thus demonstrating its capability to describe accurately the influence of water flow on wave propagation.

Numerical Modelling of Wash Waves Generated by Ships Moving over An Uneven Bottom

Numerical Modelling of Wash Waves Generated by Ships Moving over An Uneven Bottom

The Feasibility of the ERA5 Forced Numerical Wave Model in Fetch-Limited Basins

Numerical wave models are critical in hindcasting reliable long-term time series of significant wave heights, which play a crucial role in coastal and ocean engineering activities. Although wind fields are an important input to numerical wave models, few studies have investigated the feasibility of the widely used ERA5 wind reanalysis dataset in fetch-limited basins. In this work, we investigated the feasibility of the ERA5 forced numerical wave model (SWAN) in fetch-limited basins. ERA5 wind velocities were first compared to ground-based meteorological stations, showing poorer accuracy compared to finer gridded ALADIN wind data. Subsequently, the white-capping coefficient Cds in the Janssen white-capping formulation was calibrated separately using a surrogate model when establishing the ERA5 and ALADIN forced wave models. The calibrated ERA5 forced model showed a similar agreement to wave buoy data as the calibrated ALADIN forced wave model during the calibration period and even superior accuracy in the validation period. Overall, these results show that the wave model calibration procedure mitigates the effect of the poorer accuracy of the ERA5 wind data on the significant wave height results. Nevertheless, both ERA5 and ALADIN forced wave models showed an alarming overprediction for high simulated significant wave heights.

Numerical modelling of long waves in wide rectangular channels in lagrangian coordinates

The paper discusses the possibility of using Lagrangian coordinates to predict the transformation of long waves of different origins near the coasts, necessary in the design, construction, and operation of protective structures, as well as a wide range of environmental problems related, among others, to the spread of pollutants. Results of numerical investigations, compared with analytical solutions, showed satisfactory coincidence.

Длинные волны на шельфе юго-западного побережья о. Сахалин

The results of the study of long-wave motions with periods of more than 20 hours on the shelf of the southwest coast of Sakhalin Island using the time series of sea level fluctuations obtained in full-scale experiments with a discreteness of 1 s and a duration of 4 to 6 months are considered. Spectral analysis of the time series of sea level fluctuations for the period range from 8 to 200 hours revealed the presence of long-wave processes with periods from 26.1 to 46.7 hours, which significantly exceed the inertial period of 16.48 hours. Numerical modeling of shelf waves for exponentially convex profiles of the seabed, carried out using the dispersion relation of V.T. Buchwald and J. K. Adams for waves of the continental shelf, showed that the detected wave processes with periods from 31.2 h to 46.7 h are shelf waves. Their amplitudes increase during storms. The possibility of energy transferring from atmospheric disturbances to shelf waves, which contribute to the formation of sea level, is shown, that confirms the earlier made assumption. Using the calculation of the phase difference of the observed shelf waves at a distance of 12.4 km between Nevelsk and Gornazovodsk and determined by means of the theoretical model, it is shown that the second mode of the shelf wave with a frequency of 0.152 cycle/h is close to the theoretical one. It is shown for the wave with a period of 26.1 h recorded in Ilyinsky and Gornozavodsk for the distance between the points of 173.6 km, that this wave cannot be a shelf wave, but it is a Kelvin wave. This is confirmed by the calculated dispersion diagram, according to which the wavelength of about 689 km corresponds well to the phase difference for the distance Ilyinsky – Gornozavodsk. It is found that shelf waves, one of the generation mechanisms of which is the wind tension along the coast, have the different amplitudes in summer and winter, that is due to the seasonal direction of the offshore wind. In summer, the directions of shelf wave propagation and wind are opposite, which weakens the shelf waves.

A Real-Time Spatiotemporal Machine Learning Framework for the Prediction of Nearshore Wave Conditions

Abstract The safe and successful operation of offshore infrastructure relies on a detailed awareness of ocean wave conditions. Ongoing growth in offshore wind energy is focused on very large-scale projects, deployed in ever more challenging environments. This inherently increases both cost and complexity and therefore the requirement for efficient operational planning. To support this, we propose a new machine learning framework for the short-term forecasting of ocean wave conditions to support critical decision-making associated with marine operations. Here, an attention-based long short-term memory (LSTM) neural network approach is used to learn the short-term temporal patterns from in situ observations. This is then integrated with an existing, low computational cost spatial nowcasting model to develop a complete framework for spatiotemporal forecasting. The framework addresses the challenge of filling gaps in the in situ observations and undertakes feature selection, with seasonal training datasets embedded. The full spatiotemporal forecasting system is demonstrated using a case study based on independent observation locations near the southwest coast of the United Kingdom. Results are validated against in situ data from two wave buoy locations within the domain and compared to operational physics-based wave forecasts from the Met Office (the United Kingdom’s national weather service). For these two example locations, the spatiotemporal forecast is found to have an accuracy of R2 = 0.9083 and 0.7409 in forecasting 1-h-ahead significant wave height and R2 = 0.8581 and 0.6978 in 12-h-ahead forecasts, respectively. Importantly, this represents respectable levels of accuracy, comparable to traditional physics-based forecast products, but requires only a fraction of the computational resources. Significance Statement Spectral wave models, based on modeling the underlying physics and physical processes, are traditionally used to generate wave forecasts but require significant computational cost. In this study, we propose a machine learning forecasting framework developed using both in situ buoy observations and a surrogate regional numerical wave model. The proposed framework is validated against in situ measurements at two renewable energy sites and found to have very similar 12-h forecasting errors when benchmarked against the Met Office’s physics-based forecasting model but requires far less computational power. The proposed framework is highly flexible and has the potential for offering a low-cost, low computational resource approach for the provision of short-term forecasts and can operate with other types of observations and other machine learning algorithms to improve the availability and accuracy of the prediction.

An experimental study on oscillatory characteristics of young mangroves behind a portable reef

ABSTRACT Approximately half of the world’s mangroves are concentrated in Asia, but they have been logged at an alarming rate. To compensate for this, mangrove plantations are being attempted at various sites but with many failures. In this study, we investigated the role of a small portable reef in protecting young mangrove plants from hydrodynamic disturbances caused by short-period waves. To investigate the effectiveness of such a small reef, an experiment using a large wave flume was conducted with two types of real-sized portable reefs (stone and block reefs). A numerical wave model was also constructed to analyze in detail the turbulence around the reef. Our previous study showed that short-period waves can cause resonant oscillations in young mangrove plants. To confirm whether this occurs even behind a reef system, a young mangrove model made of flexible olefin resin was tested with a small wave flume placed behind porous and non-porous reefs, and its oscillation was precisely measured using a high-speed camera. These experiments yielded several new findings. If appropriately designed, small porous reefs can minimize oscillations with adverse effects and provide a favorable environment for the initial growth of mangroves at restoration sites.

A Deep Learning‐Based Bias Correction Method for Predicting Ocean Surface Waves in the Northwest Pacific Ocean

AbstractOcean waves, especially extreme waves, are vital for air‐sea interaction and shipping. However, current wave models still have significant biases. Based on a numerical wave model and a deep learning model, a BU‐Net by adding batch normalization layers to a U‐Net, we accurately predict the significant wave height (SWH) of the Northwest Pacific Ocean. For each day in 2017–2021, we conducted a 3‐day hindcast experiment using WAVEWATCH3 (WW3) to obtain the SWH forecasts at lead times of 24, 48, and 72 hr, forced by GFS real‐time forecast surface winds. After using BU‐Net, the mean Root Mean Squared Errors (RMSEs) of the SWH forecast from WW3 at lead times of 24, 48, and 72 hr are reduced by 40%, 38%, and 30%, respectively. During typhoon passages, the drop percentages of RMSEs all exceed 20% for three lead times. Therefore, combining numerical models and deep learning is very promising in wave forecasting.

Spatial and temporal variability of shorefaces: A morpho-hydrodynamic controlled system

Shorefaces are transitional zones between the shelf and surfzone/beach systems. They are subdivided into ‘upper’ and ‘lower’ shoreface sectors which display particular morphodynamic behaviour, with the upper shoreface morphologically active over short (annual) time scales, and the lower shoreface evolving over much longer time scales (decadal and beyond).We examine morphodynamics using three distinct examples from the high-energy coast of Ireland. Numerical wave modelling (SWAN) is used to characterize wave energy dissipation across the shoreface. Our results show that zonation patterns and the physical extent of shorefaces display distinct spatial as well as temporal variations. The shoreface’s physical limits and internal zonation patterns are driven by the combination of local wave forcing and pre-existing shoreface morphology. Shoreface behaviour therefore, falls within a spectum between gradual and intensive wave energy dissipation.We show that particular seabed morphology controls the extent of, as well as the bed shear stress distribution across the shoreface. This can have significant implications for any adjoining beach systems as waves arriving at the surf zone acquire specific characteristics depending on the shoreface configuration, even under similar offshore wave conditions. Additionally, the variation of shoreface extent impacts the volume of sediment available for transport, both to the nearshore zone as well as local beach systems. The influence of shoreface morphology is therefore an important, but largely overlooked element in the study of mesoscale coastal behaviour as well as coastal response to global climate change and secular sea-level rise.

Improvement of wave predictions in marginal seas around Korea through correction of simulated sea winds

One of the main error sources in predicting ocean surface waves is the uncertainty of numerical sea wind products used as input to wave prediction models. In particular, the complexity of atmospheric physics and limitations of numerical computation in time and space increase the uncertainty of numerical sea winds in the area of marginal seas. So, a process is proposed to improve wave prediction in marginal seas by correcting numerical sea-wind products (i.e., herein, ERA5 wind reanalysis data produced around the Korean Peninsula). To evaluate and correct the ERA5 data, Korea Meteorological Administration (KMA) buoy and MetOp-B (ASCAT) satellite data were used. In the procedure, firstly, the ASCAT winds in space were calibrated using the buoy data, and secondly the calibrated satellite winds were used to evaluate and correct the ERA5 wind data. Finally, the corrected ERA5 wind data were used as input to a numerical wave model (i.e., WAVEWATCH-Ⅲ). When the corrected wind data were applied to the wave numerical model, the resulted predictions showed a better match to the in situ wave measurements. In the results, the bias error was reduced from (0.21 to 0.04) m, and the best fit slope was improved from (0.84 to 0.93) on average, compared to the predictions by the original sea winds. This procedure can be applied to other marginal seas in which sea winds are strongly influenced by neighbouring continents, and not well reproduced by numerical approaches.

Accuracy of numerical wave model results: application to the Atlantic coasts of Europe

Abstract. Numerical wave models are generally less accurate in the coastal ocean than offshore. It is generally suspected that a number of factors specific to coastal environments can be blamed for these larger model errors: complex shoreline and topography, relatively short fetches, combination of remote swells and local wind seas, less accurate wind fields, presence of strong currents, bottom friction, etc. These factors generally have strong local variations, making it all the more difficult to adapt a particular model setup from one area to another. Here we investigate a wide range of modeling choices including forcing fields, spectral resolution, and parameterizations of physical processes in a regional model that covers most of the Atlantic and North Sea coasts. The effects of these choices on the model results are analyzed with buoy spectral data and wave parameter time series. Additionally, satellite altimeter data are employed to provide a more complete performance assessment of the modeled wave heights as a function of the distance to the coast and to identify areas where wave propagation is influenced by bottom friction. We show that the accurate propagation of waves from offshore is probably the most important factor on exposed shorelines, while other specific effects can be important locally, including winds, currents, and bottom friction.

Model order reduction strategies for weakly dispersive waves

We focus on the numerical modeling of water waves by means of depth averaged models. We consider in particular PDE systems which consist in a nonlinear hyperbolic model plus a linear dispersive perturbation involving an elliptic operator. We propose two strategies to construct reduced order models for these problems, with the main focus being the control of the overhead related to the inversion of the elliptic operators, as well as the robustness with respect to variations of the flow parameters. In a first approach, only a linear reduction strategies is applied only to the elliptic component, while the computations of the nonlinear fluxes are still performed explicitly. This hybrid approach, referred to as pdROM, is compared to a hyper-reduction strategy based on the empirical interpolation method to reduce also the nonlinear fluxes. We evaluate the two approaches on a variety of benchmarks involving a generalized variant of the BBM–KdV model with a variable bottom, and a one-dimensional enhanced weakly dispersive shallow water system. The results show the potential of both approaches in terms of cost reduction, with a clear advantage for the pdROM in terms of robustness, and for the EIMROM in terms of cost reduction.

Numerical Study on Hydrodynamics of Submerged Permeable Breakwater under Impacts of Focused Wave Groups Using a Nonhydrostatic Wave Model

Extreme waves, called rogue waves or freak waves, usually occur unexpectedly and with very large wave heights. In recent years, extreme waves were reported not only in deep ocean waters but also in shallow waters, which threaten the safety and intactness of the coastal regions. To prevent the coastal infrastructures and communities from the devastating power of extreme surges and waves, many coastal defense structures were built along the coastline, i.e., submerged permeable breakwaters. However, the number of studies on the hydrodynamic characteristics of a submerged permeable breakwater under the impact of extreme waves is relatively few. In addition, wave focusing has been widely used to generate extreme waves in the past few decades. Hence, as a necessary supplement to the previous research work, the hydrodynamic performance of a submerged permeable breakwater under the impacts of focused wave groups was numerically studied by using a nonhydrostatic numerical wave model (NHWAVE). The influences of several main factors, such as the incident significant wave height, water depth, wave peak period, porosity of the breakwater (n), and the side slope angle of the breakwater, were considered. It is expected that the results of this study will further strengthen the research on the hydrodynamic characteristics of a submerged permeable breakwater under extreme wave conditions.

Characterization of the Thermospheric Mean Winds and Circulation During Solstice Using ICON/MIGHTI Observations

AbstractUsing the horizontal neutral wind observations from the Michelson Interferometer for Global High‐resolution Thermospheric Imaging (MIGHTI) instrument onboard NASA's Ionospheric Connection Explorer (ICON) spacecraft with continuous coverage, we determine the climatology of the mean zonal and meridional winds and the associated mean circulation at low‐to middle latitudes (10°S–40°N) for Northern Hemisphere summer solstice conditions between 90 and 200 km altitudes, specifically on 20 June 2020 solstice as well as for a one‐month period from 8 June–7 July 2020 and for Northern winter season from 16 December 2019–31 January 2020, which spans a 47‐day period, providing full local time coverage. The data are averaged within appropriate altitude, longitude, latitude, solar zenith angle, and local time bins to produce mean wind distributions. The geographical distributions and local time variations of the mean horizontal circulation are evaluated. The instantaneous horizontal winds exhibit a significant degree of spatiotemporal variability often exceeding ±150 m s−1. The daily averaged zonal mean winds demonstrate day‐to‐day variability. Eastward zonal winds and northward (winter‐to‐summer) meridional winds are prevalent in the lower thermosphere, which provides indirect observational evidence of the eastward momentum deposition by small‐scale gravity waves. The mean neutral winds and circulation exhibit smaller scale structures in the lower thermosphere (90–120 km), while they are more homogeneous in the upper thermosphere, indicating the increasingly dissipative nature of the thermosphere. The mean wind and circulation patterns inferred from ICON/MIGHTI measurements can be used to constrain and validate general circulation models, as well as input for numerical wave models.