Effects of wave-induced sea ice break-up and mixing in a high-resolution coupled ice-ocean model

Arctic sea ice plays a vital role in modulating the global climate. In the most recent decades, the rapid decline of the Arctic summer sea ice cover has exposed increasing areas of ice-free ocean, with sufficient fetch for waves to develop. This has highlighted the complex and not well-understood nature of wave-ice interactions, requiring modeling effort. Here, we introduce two independent parameterizations in a high-resolution coupled ice-ocean model to investigate the effects of wave-induced sea ice break-up (through albedo change) and mixing on the Arctic sea ice simulation. Our results show that wave-induced sea ice break-up leads to increases in sea ice concentration and thickness in the Bering Sea, the Baffin Sea and the Barents Sea during the ice growth season, but accelerates the sea ice melt in the Chukchi Sea and the East Siberian Sea in summer. Further, wave-induced mixing can decelerate the sea ice formation in winter and the sea ice melt in summer by exchanging the heat fluxes between the surface and subsurface layer. As our baseline model underestimates sea ice cover in winter and produces more sea ice in summer, wave-induced sea ice break-up plays a positive role in improving the sea ice simulation. This study provides two independent parameterizations to directly include the wave effects into the sea ice models, with important implications for the future sea ice model development

A recent increase in global wave power as a consequence of oceanic warming

Wind-generated ocean waves drive important coastal processes that determine flooding and erosion. Ocean warming has been one factor affecting waves globally. Most studies have focused on studying parameters such as wave heights, but a systematic, global and long-term signal of climate change in global wave behavior remains undetermined. Here we show that the global wave power, which is the transport of the energy transferred from the wind into sea-surface motion, has increased globally (0.4% per year) and by ocean basins since 1948. We also find long-term correlations and statistical dependency with sea surface temperatures, globally and by ocean sub-basins, particularly between the tropical Atlantic temperatures and the wave power in high south latitudes, the most energetic region globally. Results indicate the upper-ocean warming, a consequence of anthropogenic global warming, is changing the global wave climate, making waves stronger. This identifies wave power as a potentially valuable climate change indicator.Funding for this project was partly provided by RISKOADAPT (BIA2017-89401-R) Spanish Ministry of Science, Innovation and Universities and the ECLISEA project part of the Horizon 2020 ERANET ERA4CS (European Research Area for Climate Services) 2016 Call

A collection of wet beam models for wave-ice interaction

Abstract. Theoretical models for the prediction of decay rate and dispersion process of gravity waves traveling into an integrated ice cover expanded over a long way are introduced. The term “wet beam” is chosen to refer to these models as they are developed by incorporating water-based damping and added mass forces. Presented wet beam models differ from each other according to the rheological behavior considered for the ice cover. Two-parameter viscoelastic solid models accommodating Kelvin–Voigt (KV) and Maxwell mechanisms along with a one-parameter elastic solid model are used to describe the rheological behavior of the ice layer. Quantitative comparison between the landfast ice field data and model predictions suggests that wet beam models, adopted with both KV and Maxwell mechanisms, predict the decay rate more accurately compared to a dry beam model. Furthermore, the wet beam models, adopted with both KV and Maxwell mechanisms, are found to construct decay rates of disintegrated ice fields, though they are built for a continuous ice field. Finally, it is found that wet beam models can accurately construct decay rate curves of freshwater ice, though they cannot predict the dispersion process of waves accurately. To overcome this limitation, three-parameter solid models, termed standard linear solid (SLS) mechanisms, are suggested to be used to re-formulate the dispersion relationship of wet beam models, which were seen to construct decay rates and dispersion curves of freshwater ice with an acceptable level of accuracy. Overall, the two-parameter wet beam dispersion relationships presented in this research are observed to predict decay rates and dispersion process of waves traveling into actual ice covers, though three-parameter wet beam models were seen to reconstruct the those of freshwater ice formed in a wave flume. The wet beam models presented in this research can be implemented in spectral models on a large geophysical scale

Clinical oral implants research : official publication of the European Association for Osseointegration

An extremely large ('freak') wave is a typical though rare phenomenon observed in the sea. Special theories (for example, the modulation instability theory) were developed to explain mechanics and appearance of freak waves as a result of nonlinear wave-wave interactions. In this paper, it is demonstrated that the freak wave appearance can be also explained by superposition of linear modes with the realistic spectrum. The integral probability of trough-to-crest waves is calculated by two methods: the first one is based on the results of the numerical simulation of a wave field evolution performed with one-dimensional and two-dimensional nonlinear models. The second method is based on calculation of the same probability over the ensembles of wave fields constructed as a superposition of linear waves with random phases and the spectrum similar to that used in the nonlinear simulations. It is shown that the integral probabilities for nonlinear and linear cases are of the same order of value

Parameterization of wave boundary layer

It is known that drag coefficient varies in broad limits depending on wind velocity and wave age as well as on wave spectrum and some other parameters. All those effects produce large scatter of the drag coefficient, so, the data is plotted as a function of wind velocity forming a cloud of points with no distinct regularities. Such uncertainty can be overcome by the implementation of the WBL model instead of the calculations of drag with different formulas. The paper is devoted to the formulation of theWave Boundary Layer (WBL) model for the parameterization of the ocean-atmosphere interactions in coupled ocean-atmosphere models and wave prediction models. The equations explicitly take into account the vertical flux of momentum generated by the wave-produced fluctuations of pressure, velocity and stresses (WPMF). Their surface values are calculated with the use of the spectral beta-functions whose expression was obtained by means of the 2-D simulation of the WBL. Hence, the model directly connects the properties of the WBL with an arbitrary wave spectrum. The spectral and direct wave modeling should also take into account the momentum flux to a subgrid part of the spectrum. The parameterization of this effect in the present paper is formulated in terms of wind and cut-off frequency of the spectrum

Coupling spectral and phase-resolving wave model for forecasting of extreme waves in wind seas

"Freak" or "Rogue" waves, when single individual wave height exceed two times of the significant wave height (Hi>2Hs), has been considered as one of the most dangerous sea states. Freak waves are believed to have caused many catastrophes, which result in ship damage and human casualties (Kharif and Pelinovsky, 2003). Occurrence of such waves are extremely unlikely according to Rayleigh distribution (Dean, 1990), however, in real ocean conditions occurrence of such events are higher than commonly used distributions. The main objective of this study is the coupling of Spectral WaveWatch III (WW3) model and phase resolving wave models, which will advance the application of the third generation wave models one-step further and increase the precision of model outputs and forecasting of such "unlikely" extreme conditions