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The formation and fate of internal waves in the South China Sea

Nature volume 521, pages 65–69 (2015)Cite this article

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A Corrigendum to this article was published on 18 November 2015

Abstract

Internal gravity waves, the subsurface analogue of the familiar surface gravity waves that break on beaches, are ubiquitous in the ocean. Because of their strong vertical and horizontal currents, and the turbulent mixing caused by their breaking, they affect a panoply of ocean processes, such as the supply of nutrients for photosynthesis1, sediment and pollutant transport2 and acoustic transmission3; they also pose hazards for man-made structures in the ocean4. Generated primarily by the wind and the tides, internal waves can travel thousands of kilometres from their sources before breaking5, making it challenging to observe them and to include them in numerical climate models, which are sensitive to their effects6,7. For over a decade, studies8,9,10,11 have targeted the South China Sea, where the oceans’ most powerful known internal waves are generated in the Luzon Strait and steepen dramatically as they propagate west. Confusion has persisted regarding their mechanism of generation, variability and energy budget, however, owing to the lack of in situ data from the Luzon Strait, where extreme flow conditions make measurements difficult. Here we use new observations and numerical models to (1) show that the waves begin as sinusoidal disturbances rather than arising from sharp hydraulic phenomena, (2) reveal the existence of >200-metre-high breaking internal waves in the region of generation that give rise to turbulence levels >10,000 times that in the open ocean, (3) determine that the Kuroshio western boundary current noticeably refracts the internal wave field emanating from the Luzon Strait, and (4) demonstrate a factor-of-two agreement between modelled and observed energy fluxes, which allows us to produce an observationally supported energy budget of the region. Together, these findings give a cradle-to-grave picture of internal waves on a basin scale, which will support further improvements of their representation in numerical climate predictions.

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Figure 1: Overview of internal waves in the South China Sea.
Figure 2: Near-field processes in the Luzon Strait.
Figure 3: Internal wave energy fluxes in the South China Sea.
Figure 4: The Kuroshio and its impact on wave propagation.

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Acknowledgements

This article is dedicated to the memory of author T.-Y. Tang. Our work was supported by the US Office of Naval Research and the Taiwan National Science Council. We are indebted to the captains and crew of all of the research vessels that supported this work, as well as to the technical staff of the seagoing institutions. Without the skill and hard work of all of these people, these observations would not have been possible.

Author information

Author notes

  1. David M. Farmer

    Present address: †Present address: School of Earth and Ocean Sciences, University of Victoria, British Columbia V8P 5C, Canada.,

Authors and Affiliations

  1. Scripps Institution of Oceanography, University of California San Diego, La Jolla, 92037, California, USA

    Matthew H. Alford, Jennifer A. MacKinnon, Luca R. Centurioni, T. M. Shaun Johnston, Ruth Musgrave, Robert Pinkel & Daniel L. Rudnick

  2. University of Washington, Seattle, 98105, Washington, USA

    Matthew H. Alford, Ren-Chieh Lien, Andrew I. Pickering & Luc Rainville

  3. Massachusetts Institute of Technology (MIT), Cambridge, 02139, Massachusetts, USA

    Thomas Peacock & Andrew I. Pickering

  4. Oregon State University, Corvallis, 97370, Oregon, USA

    Jonathan D. Nash & James N. Moum

  5. University of Southern Mississippi, Stennis Space Center, 39529, Mississippi, USA

    Maarten C. Buijsman

  6. University of Maryland, Cambridge, 21613, Maryland, USA

    Shenn-Yu Chao

  7. Institute of Oceanography, National Taiwan University, 10617, Taipei, Taiwan

    Ming-Huei Chang, Sen Jan, Joe Wang, Yiing J. Yang & Tswen-Yung (David) Tang

  8. University of Rhode Island, 02882, Rhode Island, USA

    David M. Farmer

  9. Stanford University, Stanford, 94305, California, USA

    Oliver B. Fringer

  10. National Sun-Yat Sen University, Kaohsiung, 80424, Taiwan

    Ke-Hsien Fu, I-Huan Lee & Yu-Huai Wang

  11. Naval Research Laboratories (NRL), Stennis Space Center, 39529, Mississippi, USA

    Patrick C. Gallacher & Dong S. Ko

  12. University of Miami, Miami, 33149, Florida, USA

    Hans C. Graber

  13. Woods Hole Oceanographic Institution, Falmouth, 02543, Massachusetts, USA

    Karl R. Helfrich & Louis C. St Laurent

  14. Florida Institute of Technology, Melbourne, 32901, Florida, USA

    Steven M. Jachec

  15. Global Ocean Associates, Alexandria, 22310, Virginia, USA

    Christopher R. Jackson

  16. University of Victoria, Victoria, V8W 3P6, British Columbia, Canada

    Jody M. Klymak

  17. Princeton University, 08542, New Jersey, USA

    Sonya Legg

  18. Institut de Mécanique des Fluides de Toulouse, Toulouse, 31400, France

    Matthieu J. Mercier

  19. Korea Institute of Ocean Science and Technology, Ansan, 426–744, South Korea

    Jae-Hun Park

  20. Soliton Ocean Services, Carmel, 93924, California, USA

    Steven R. Ramp

  21. University of California San Diego, La Jolla, 92037, California, USA

    Sutanu Sarkar

  22. University of North Carolina, Chapel Hill, 25599, North Carolina, USA

    Alberto Scotti

  23. University of Alaska at Fairbanks, Fairbanks, 99775, Alaska, USA

    Harper L. Simmons

  24. Colorado State University, Fort Collins, 80523, Colorado, USA

    Subhas K. Venayagamoorthy

  25. Office of Naval Research, Arlington, Virginia, USA

    Theresa Paluszkiewicz

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  1. Matthew H. Alford
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Contributions

All authors contributed to the paper in multiple ways. Primary writing: M.H.A., T. Peacock, J.A.M. & J.D.N. Synthesis and overall coordination: T. Paluszkiewicz & T.-Y.T. Energy flux calculations: M.H.A. & A.I.P. Energy budget calculation: M.H.A., M.C.B., M.-H.C., R.-C.L., J.M.K. & L.C.S.L. Near-field moorings and calculations: M.H.A., A.I.P., L.R., J.D.N., J.N.M. & M.-H.C. Far-field moorings and calculations: L.R.C., M.-H.C., R.-C.L., S.R.R., Y.J.Y. & T.-Y.T. Near-field CTD measurements (Fig. 2d): R.P. & R.M. Near-field lowered acoustic Doppler current profiler measurements: M.H.A., J.D.N., J.A.M., L.R., H.L.S., A.I.P & R.M. Pressure inverted echo sounder measurements: D.M.F., J.-H.P., Y.J.Y. & M.H.A. Microstructure measurements: L.C.S.L., K.-H.F., H.L.S. & Y.-H.W. Remote sensing: C.R.J. & H.C.G. Theory: K.R.H. & D.M.F. Glider measurements: T.M.S.J. & D.L.R. Regional contextualization and logistical support: S.-Y.C., I-H.L., S.R.R., J.W., Y.J.Y. & T.-Y.T. Far-field modelling: S.J. & H.L.S. Two-dimensional modelling: J.M.K., S.S., S.M.J., A.S., R.M. & K.V. Near-field modelling: M.C.B., O.B.F., S.L. & S.M.J. Kuroshio modelling: P.C.G., S.J. & D.S.K. Laboratory measurements: T. Peacock & M.J.M.

Corresponding author

Correspondence to Matthew H. Alford.

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The authors declare no competing financial interests.

Extended data figures and tables

Extended Data Figure 1 Comparison of observed and model energy flux.

Left, Scatter plot of flux magnitude F from observations (x axis) and far-field (UAF; University of Alaska Fairbanks) model (y axis). Error bars are ±20% for observed values and ±10% for model values (see Methods). Right, As for the left panel, but for direction θ; error bars are ±30°. See source data and ref. 15 for station locations. Black, semi-diurnal; red, diurnal.

Source data

Extended Data Table 1 Conversion and radiated flux integrated over the region 19° to 21.5° N, 120° to 122.5° E.
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Alford, M., Peacock, T., MacKinnon, J. et al. The formation and fate of internal waves in the South China Sea. Nature 521, 65–69 (2015). https://doi.org/10.1038/nature14399

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