Hostname: page-component-76fb5796d-dfsvx Total loading time: 0 Render date: 2024-04-26T03:53:42.645Z Has data issue: false hasContentIssue false

Kinetic equations in a third-generation spectral wave model

Published online by Cambridge University Press:  22 January 2021

Qingxiang Liu*
Affiliation:
Department of Infrastructure Engineering, University of Melbourne, VIC 3010, Australia
Odin Gramstad
Affiliation:
Group Technology and Research, DNV GL, 1363 Høvik, Norway
Alexander Babanin
Affiliation:
Department of Infrastructure Engineering, University of Melbourne, VIC 3010, Australia Laboratory for Regional Oceanography and Numerical Modeling, National Laboratory for Marine Science and Technology, 266237 Qingdao, PR China
*
Email addresses for correspondence: qingxiang.liu@unimelb.edu.au, qxiangliu@gmail.com

Abstract

The Hasselmann kinetic equation (HKE) forms the cornerstone of present-day spectral wave models. It describes the redistribution of energy over the wave spectrum as a result of resonant four-wave interactions, and theoretically prescribes wave evolution on a slow $O(1/\varepsilon ^4\omega _0)$ time scale, where $\varepsilon$ and $\omega _0$ are typical wave steepness and frequency. Alternatives to the HKE (e.g. the generalized kinetic equation (GKE)), including the effects of non-resonant four-wave interactions, are believed capable of evolving wave fields on a fast $O(1/\varepsilon ^2\omega _0)$ time scale. It is beyond doubt that these alternatives could reasonably predict changes of unidirectional waves whereas the HKE cannot. For angular spread wave fields, however, it is still ambiguous whether the GKE behaves remarkably differently from the HKE because previous research in this direction was not fully consistent. In this study, we revised the GKE algorithm implemented in the spectral wave model WAVEWATCH III (WW3) by correcting two numerical aspects related to the discretization of the GKE and to the source term integration. It is proved that once updated, the GKE in WW3 does not give rise to significant deviation from the HKE-based results, provided that the wave spectra are fairly smooth and the directionality is sufficiently broad. These results, although unexpected, are in good agreement with findings reported by Annenkov & Shrira. More strikingly, the HKE and GKE are observed to operate at the same fast $O(1/\varepsilon ^2\omega _0)$ time scale for the spectral peak downshift and angular broadening, indicating that the HKE, solved by the well-established Webb–Resio–Tracy algorithm, seems more robust than usually expected.

Type
JFM Papers
Copyright
© The Author(s), 2021. Published by Cambridge University Press

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

REFERENCES

Andrade, D., Stuhlmeier, R. & Stiassnie, M. 2019 On the generalized kinetic equation for surface gravity waves, blow-up and its restraint. Fluids 4 (1), 2.CrossRefGoogle Scholar
Annenkov, S.Y. & Shrira, V.I. 2006 Role of non-resonant interactions in the evolution of nonlinear random water wave fields. J. Fluid Mech. 561, 181207.CrossRefGoogle Scholar
Annenkov, S.Y. & Shrira, V.I. 2009 “Fast” nonlinear evolution in wave turbulence. Phys. Rev. Lett. 102 (2), 14.CrossRefGoogle ScholarPubMed
Annenkov, S.Y. & Shrira, V.I. 2015 Modelling the impact of squall on wind waves with the generalized kinetic equation. J. Phys. Oceanogr. 45 (3), 807812.CrossRefGoogle Scholar
Annenkov, S.Y. & Shrira, V.I. 2016 Modelling transient sea states with the generalised kinetic equation. In Rogue and Shock Waves in Nonlinear Dispersive Media (ed. M. Onorato, S. Residori & F. Baronio), pp. 159–178. Springer.CrossRefGoogle Scholar
Annenkov, S.Y. & Shrira, V.I. 2018 Spectral evolution of weakly nonlinear random waves: kinetic description versus direct numerical simulations. J. Fluid Mech. 844, 766795.CrossRefGoogle Scholar
Annenkov, S.Y. & Shrira, V.I. 2019 Modelling evolution of directional spectra of water waves. In Workshop on Nonlinear Water Waves, RIMS Kokyuroku (ed. S. Murashige), vol. 2109, pp. 100–114. Kyoto University.Google Scholar
Babanin, A.V., Chalikov, D., Young, I.R. & Savelyev, I. 2010 Numerical and laboratory investigation of breaking of steep two-dimensional waves in deep water. J. Fluid Mech. 644, 433463.CrossRefGoogle Scholar
Babanin, A.V., Young, I.R. & Banner, M.L. 2001 Breaking probabilities for dominant surface waves on water of finite constant depth. J. Geophys. Res. 106, 11659.CrossRefGoogle Scholar
Badulin, S.I., Babanin, A.V., Zakharov, V.E. & Resio, D. 2007 Weakly turbulent laws of wind-wave growth. J. Fluid Mech. 591, 339378.CrossRefGoogle Scholar
Badulin, S.I., Pushkarev, A.N., Resio, D. & Zakharov, V.E. 2005 Self-similarity of wind-driven seas. Nonlinear. Process. Geophys. 12 (6), 891945.CrossRefGoogle Scholar
Barstow, S.F., et al. . 2005 Measuring and Analysing the Directional Spectrum of Ocean Waves. COST Office.Google Scholar
Benoit, M. 2005 Evaluation of methods to compute the non-linear quadruplet interactions for deep-water wave spectra. In Proceedings of the Fifth International Symposium on Ocean Waves Measurement and Analysis (ed. B.L. Edge & J.C. Santas), pp. 1–10. IAHR Secretariat.Google Scholar
Bidlot, J.-R. 2001 ECMWF wave-model products. ECMWF Newsl. 91, 915.Google Scholar
Cavaleri, L., et al. . 2007 Wave modelling – the state of the art. Prog. Oceanogr. 75 (4), 603674.CrossRefGoogle Scholar
Cavaleri, L., et al. . 2018 Wave modelling in coastal and inner seas. Prog. Oceanogr. 167, 164233.CrossRefGoogle Scholar
Chalikov, D. 2018 Numerical modeling of surface wave development under the action of wind. Ocean Sci. 14 (3), 453470.CrossRefGoogle Scholar
Cheng, S., et al. . 2017 Calibrating a viscoelastic sea ice model for wave propagation in the arctic fall marginal ice zone. J. Geophys. Res. 122 (11), 87708793.CrossRefGoogle Scholar
Dommermuth, D.G. & Yue, D.K.P. 1987 A high-order spectral method for the study of nonlinear gravity waves. J. Fluid Mech. 184, 267288.CrossRefGoogle Scholar
Donelan, M.A., Babanin, A.V., Young, I.R. & Banner, M.L. 2006 Wave-follower field measurements of the wind-input spectral function. Part II: parameterization of the wind input. J. Phys. Oceanogr. 36 (8), 16721689.CrossRefGoogle Scholar
Donelan, M.A., Hamilton, J. & Hui, W.H. 1985 Directional spectra of wind-generated waves. Phil. Trans. R. Soc. Lond. A 315 (1534), 509562.Google Scholar
Dysthe, K.B., Trulsen, K., Krogstad, H.E. & Socquet-Juglard, H. 2003 Evolution of a narrow-band spectrum of random surface gravity waves. J. Fluid Mech. 478, 110.CrossRefGoogle Scholar
Goda, Y. 2010 Random Seas and Design of Maritime Structures. World Scientific.CrossRefGoogle Scholar
Gramstad, O. & Babanin, A. 2016 The generalized kinetic equation as a model for the nonlinear transfer in third-generation wave models. Ocean Dyn. 66 (4), 509526.CrossRefGoogle Scholar
Gramstad, O. & Stiassnie, M. 2013 Phase-averaged equation for water waves. J. Fluid Mech. 718, 280303.CrossRefGoogle Scholar
Hasselmann, K. 1962 On the non-linear energy transfer in a gravity-wave spectrum. Part 1. General theory. J. Fluid Mech. 12 (4), 481500.CrossRefGoogle Scholar
Hasselmann, K., et al. . 1973 Measurements of wind-wave growth and swell decay during the Joint North Sea Wave Project (JONSWAP). Tech. Rep. Deutches Hydrographisches Institut.Google Scholar
Hasselmann, S. & Hasselmann, K. 1985 Computations and parameterizations of the nonlinear energy transfer in a gravity-wave spectrum. Part I: a new method for efficient computations of the exact nonlinear transfer integral. J. Phys. Oceanogr. 15 (11), 13691377.2.0.CO;2>CrossRefGoogle Scholar
Hasselmann, S., Hasselmann, K., Allender, J.H. & Barnett, T.P. 1985 Computations and parameterizations of the nonlinear energy transfer in a gravity-wave specturm. Part II: parameterizations of the nonlinear energy transfer for application in wave models. J. Phys. Oceanogr. 15 (11), 13781392.2.0.CO;2>CrossRefGoogle Scholar
Holthuijsen, L.H. 2007 Waves in Oceanic and Coastal Waters. Cambridge University Press.CrossRefGoogle Scholar
Janssen, P.A.E.M. 2003 Nonlinear four-wave interactions and freak waves. J. Phys. Oceanogr. 33 (4), 863884.2.0.CO;2>CrossRefGoogle Scholar
Janssen, P.A.E.M. 2004 The Interaction of Ocean Waves and Wind. Cambridge University Press.CrossRefGoogle Scholar
Janssen, P.A.E.M. 2008 Progress in ocean wave forecasting. J. Comput. Phys. 227 (7), 35723594.Google Scholar
Janssen, P.A.E.M. 2009 On some consequences of the canonical transformation in the Hamiltonian theory of water waves. J. Fluid Mech. 637, 144.CrossRefGoogle Scholar
Janssen, P.A.E.M. & Janssen, A.J.E.M. 2019 Asymptotics for the long-time evolution of kurtosis of narrow-band ocean waves. J. Fluid Mech. 859, 790818.Google Scholar
Janssen, P.A.E.M., Lionello, P., Reistad, M. & Hollingsworth, A. 1989 Hindcasts and data assimilation studies with the WAM model during the Seasat period. J. Geophys. Res. 94 (C1), 973993.CrossRefGoogle Scholar
Komatsu, K. & Masuda, A. 1996 A new scheme of nonlinear energy transfer among wind waves: RIAM method-algorithm and performance. J. Oceanogr. 52 (4), 509537.CrossRefGoogle Scholar
Komen, G.J., Cavaleri, L., Donelan, M.A., Hasselmann, K., Hasselmann, S. & Janssen, P.A.E.M. 1994 Dynamics and Modelling of Ocean Waves. Cambridge University Press.CrossRefGoogle Scholar
Komen, G.J., Hasselmann, K. & Hasselmann, K. 1984 On the existence of a fully developed wind-sea spectrum. J. Phys. Oceanogr. 14 (8), 12711285.2.0.CO;2>CrossRefGoogle Scholar
Krasitskii, V.P. 1994 On reduced equations in the Hamiltonian theory of weakly nonlinear surface waves. J. Fluid Mech. 272 (5), 120.Google Scholar
Liu, Q., Rogers, W.E., Babanin, A., Li, J. & Guan, C. 2020 Spectral modeling of ice-induced wave decay. J. Phys. Oceanogr. 50 (6), 15831604.CrossRefGoogle Scholar
Liu, Q., Rogers, W.E., Babanin, A.V., Young, I.R., Romero, L., Zieger, S., Qiao, F. & Guan, C. 2019 Observation-based source terms in the third-generation wave model WAVEWATCH III: updates and verification. J. Phys. Oceanogr. 49 (2), 489517.CrossRefGoogle Scholar
Longuet-Higgins, M.S. & Cokelet, E.D. 1976 The deformation of steep surface waves on water. I. A numerical method of computation. Proc. R. Soc. Lond. A 350 (1660), 126.Google Scholar
Masson, D. & Leblond, P.H. 1989 Spectral evolution of wind-generated surface gravity waves in a dispersed ice field. J. Fluid Mech. 202 (-1), 43.CrossRefGoogle Scholar
Meylan, M.H., Bennetts, L.G., Mosig, J.E.M., Rogers, W.E., Doble, M.J. & Peter, M.A. 2018 Dispersion relations, power laws, and energy loss for waves in the marginal ice zone. J. Geophys. Res. 123, 113.CrossRefGoogle Scholar
Onorato, M., et al. . 2009 Statistical properties of mechanically generated surface gravity waves: a laboratory experiment in a three-dimensional wave basin. J. Fluid Mech. 627, 235257.CrossRefGoogle Scholar
Onorato, M., Osborne, A.R., Serio, M., Cavaleri, L., Brandini, C. & Stansberg, C.T. 2006 Extreme waves, modulational instability and second order theory: wave flume experiments on irregular waves. Eur. J. Mech. B/Fluids 25 (5), 586601.CrossRefGoogle Scholar
Onorato, M., Osborne, A.R., Serio, M., Resio, D., Pushkarev, A., Zakharov, V.E. & Brandini, C. 2002 Freely decaying weak turbulence for sea surface gravity waves. Phys. Rev. Lett. 89 (14), 144501.CrossRefGoogle ScholarPubMed
Polnikov, V.G. 1997 Nonlinear energy transfer through the spectrum of gravity waves for the finite depth case. J. Phys. Oceanogr. 27 (8), 14811491.2.0.CO;2>CrossRefGoogle Scholar
Polnikov, V.G. & Lavrenov, I.V. 2007 Calculation of the nonlinear energy transfer through the wave spectrum at the sea surface covered with broken ice. Oceanology 47 (3), 334343.CrossRefGoogle Scholar
Pushkarev, A.N. & Zakharov, V.E. 2000 Turbulence of capillary waves–theory and numerical simulation. Physica D 135 (1–2), 98116.CrossRefGoogle Scholar
Resio, D.T. & Perrie, W. 1991 A numerical study of nonlinear energy fluxes due to wave-wave interactions. Part 1: methodology and basic results. J. Fluid Mech. 223, 603629.Google Scholar
Resio, D.T. & Perrie, W. 2008 A two-scale approximation for efficient representation of nonlinear energy transfers in a wind wave spectrum. Part I: theoretical development. J. Phys. Oceanogr. 38 (12), 28012816.Google Scholar
Rogers, W.E., Babanin, A.V. & Wang, D.W. 2012 Observation-consistent input and whitecapping dissipation in a model for wind-generated surface waves: description and simple calculations. J. Atmos. Ocean. Technol. 29 (9), 13291346.CrossRefGoogle Scholar
Rogers, W.E., Meylan, M. & Kohout, A.L. 2018 Frequency distribution of dissipation of energy of ocean waves by sea ice using data from Wave Array 3 of the ONR “Sea State” field experiment. Tech. Rep. Naval Research Laboratory, Stennis Space Center, MS 39529–5004. Available at https://www7320.nrlssc.navy.mil/pubs/2018/rogers2-2018.pdf.Google Scholar
Rogers, W.E., Thomson, J., Shen, H.H., Doble, M.J., Wadhams, P. & Cheng, S. 2016 Dissipation of wind waves by pancake and frazil ice in the autumn Beaufort Sea. J. Geophys. Res. 121 (11), 79918007.CrossRefGoogle Scholar
Romero, L. & Melville, W.K. 2010 Airborne observations of fetch-limited waves in the Gulf of Tehuantepec. J. Phys. Oceanogr. 40 (3), 441465.CrossRefGoogle Scholar
Shrira, V.I. & Annenkov, S.Y. 2013 Towards a new picture of wave turbulence. In Advances in Wave Turbulence (ed. V. Shrira & S. Nazarenko), pp. 239–281. World Scientific.Google Scholar
The WAMDI Group 1988 The WAM model – a third generation ocean wave prediction model. J. Phys. Oceanogr. 18 (12), 17751810.2.0.CO;2>CrossRefGoogle Scholar
The WAVEWATCH III® Development Group (WW3DG) 2019 User manual and system documentation of WAVEWATCH III® version 6.07. Tech. Note 333. NOAA/NWS/NCEP/MMAB, College Park, MD, USA, 465 pp. + Appendices.Google Scholar
Tolman, H.L. 1992 Effects of numerics on the physics in a third-generation wind-wave model. J. Phys. Oceanogr. 22 (10), 10951111.2.0.CO;2>CrossRefGoogle Scholar
Tolman, H.L. 2009 User manual and system documentation of wavewatch III version 3.14. Tech. Rep. 276. NOAA/NWS/NCEP/MMAB, 194 pp. + Appendices.Google Scholar
Tolman, H.L. 2011 A conservative nonlinear filter for the high-frequency range of wind wave spectra. Ocean Model. 39 (3–4), 291300.Google Scholar
Tolman, H.L. 2013 A generalized multiple discrete interaction approximation for resonant four-wave interactions in wind wave models. Ocean Model. 70, 1124.CrossRefGoogle Scholar
Tracy, B. & Resio, D.T. 1982 Theory and calculation of the nonlinear energy transfer between sea waves in deep water. WES Report 11. US Army Corps of Engineers.Google Scholar
van Vledder, G.P. 2000 Improved method for obtaining the integration space for the computation of nonlinear quadruplet wave-wave interaction. In Proceedings of the 6th International Workshop on Wave Forecasting and Hindcasting (ed. D.T. Resio), pp. 418–431. Meteorological Service of Canada, Environment Canada.Google Scholar
van Vledder, G.P. 2006 The WRT method for the computation of non-linear four-wave interactions in discrete spectral wave models. Coast. Engng 53 (2–3), 223242.CrossRefGoogle Scholar
van Vledder, G.P. & Holthuijsen, L.H. 1993 The directional response of ocean waves to turning winds. J. Phys. Oceanogr. 23 (2), 177192.2.0.CO;2>CrossRefGoogle Scholar
Wadhams, P., Squire, V.A., Ewing, J.A. & Pascal, R.W. 1986 The effect of the marginal ice zone on the directional wave spectrum of the ocean. J. Phys. Oceanogr. 16 (2), 358376.2.0.CO;2>CrossRefGoogle Scholar
Waseda, T., Kinoshita, T. & Tamura, H. 2009 Evolution of a random directional wave and freak wave occurrence. J. Phys. Oceanogr. 39 (3), 621639.CrossRefGoogle Scholar
Webb, D.J. 1978 Non-linear transfers between sea waves. Deep-Sea Res. 25 (3), 279298.CrossRefGoogle Scholar
Xiao, W., Liu, Y., Wu, G. & Yue, D.K.P. 2013 Rogue wave occurrence and dynamics by direct simulations of nonlinear wave-field evolution. J. Fluid Mech. 720, 357392.CrossRefGoogle Scholar
Young, I.R. 1999 Wind Generated Ocean Waves. Elsevier Science Ltd.Google Scholar
Young, I.R. 2006 Directional spectra of hurricane wind waves. J. Geophys. Res. 111 (8), 114.Google Scholar
Young, I.R. & van Vledder, G.P. 1993 A review of the central role of nonlinear interactions in wind-wave evolution. Phil. Trans. R. Soc. Lond. A 342 (1666), 505524.Google Scholar
Zakharov, V.E. 1968 Stability of periodic waves of finite amplitude on the surface of a deep fluid. J. Appl. Mech. Tech. Phys. 9 (2), 190194.CrossRefGoogle Scholar
Zieger, S., Babanin, A.V., Rogers, W.E. & Young, I.R. 2015 Observation-based source terms in the third-generation wave model WAVEWATCH. Ocean Model. 218, 124.Google Scholar