Journal of Oceanography

, Volume 74, Issue 5, pp 471–483 | Cite as

Evaluation of spatial distribution of turbulent mixing in the central Pacific

  • Lingqiao Cheng
  • Guoping Gao
Original Article


A long-term mean turbulent mixing in the depth range of 200–1000 m produced by breaking of internal waves across the middle and low latitudes (40°S–40°N) of the Pacific between 160°W and 140°W is examined by applying fine-scale parameterization depending on strain variance to 8-year (2005–2012) Argo float data. Results show that elevated turbulent dissipation rate (ε) is related to significant topographic regions, along the equator, and on the northern side of 20°N spanning to 24°N throughout the depth range. Two patterns of latitudinal variations of ε and the corresponding diffusivity (Kρ) for different depth ranges are confirmed: One is for 200–450 m with significant larger ε and Kρ, and the maximum values are obtained between 4°N and 6°N, where eddy kinetic energy also reaches its maximum; The other is for 350–1000 m with smaller ε and Kρ, and the maximum values are obtained near the equator, and between 18°S and 12°S in the southern hemisphere, 20°N and 22°N in the northern hemisphere. Most elevated turbulent dissipation in the depth range of 350–1000 m relates to rough bottom roughness (correlation coefficient = 0.63), excluding the equatorial area. In the temporal mean field, energy flux from surface wind stress to inertial motions is not significant enough to account for the relatively intensified turbulent mixing in the upper layer.


Turbulent mixing Mean latitudinal variation Argo float data Fine-scale parameterization 



We would like to thank Prof. Kitade Yujiro from Tokyo University of Marine Science and Technology for his helpful advices and comments. We are also grateful to the three anonymous reviewers for their constructive comments to improve this study. Argo float data were collected and made freely available by the International Argo Program and the national programs that contribute to it (, The Argo Program is part of the Global Ocean Observing System. NCEP Reanalysis data were provided by the NOAA/OAR/ESRL PSD, Boulder, Colorado, USA, from their website at This work is supported by Shanghai Pujiang Program (Grant No. 15PJ1403000) and the National Natural Science Foundation of China (Grant No. 41506219).


  1. Alford MH (2001) Internal swell generation: the spatial distribution of energy flux from the wind to mixed layers near-inertial motions. J Phys Oceanogr 31:2359–2368CrossRefGoogle Scholar
  2. Alford MH (2003) Improved global maps and 54-year history of wind-work on ocean inertial motions. Geophys Res Lett 30(8).
  3. Alford M, Gregg M (2001) Near-inertial mixing: modulation of shear, strain and microstructure at low latitude. J Geophys Res 106:16947–16968CrossRefGoogle Scholar
  4. Alford MH, MacKinnon JA, Zhao Z, Pinkel R, Klymak J, Peacock T (2007) Internal waves across the Pacific. Geophys Res Lett 34:L24601. CrossRefGoogle Scholar
  5. Amante C, Eakins BW (2009) ETOPO1: 1 Arc-Minute Global Relief Model: procedures, data sources and analysis, NOAA Technical Memorandum NESDIS NGDC-24. National Geophysical Data Center, BoulderGoogle Scholar
  6. Cheng Lingqiao, Kitade Y (2014) Quantitative evaluation of turbulent mixing in the Central Equatorial Pacific. J Oceanogr 70:63–79. CrossRefGoogle Scholar
  7. D’Asaro E (1985) The energy flux from the wind to near-inertial motions in the mixed layer. J Phys Oceanogr 15:943–959CrossRefGoogle Scholar
  8. Egbert GD, Ray RD (2003) Semi-diurnal and diurnal tidal dissipation from TOPEX/Poseidon altimetry. Geophys Res Lett 30(17):1907. CrossRefGoogle Scholar
  9. Gargett AE (1990) Do we really know how to scale the turbulent kinetic energy dissipation rate ε due to breaking of oceanic internal wave? J Geophys Res 95(C9):15971–15974CrossRefGoogle Scholar
  10. Garrett CJR, Munk WH (1975) Space-time scales of internal waves: a progress report. J Geophys Res 80:291–297. CrossRefGoogle Scholar
  11. Garrett CJR, Munk WH (1979) Internal waves in the ocean. Annu Rev Fluid Mech 11:339–369CrossRefGoogle Scholar
  12. Gregg MC (1989) Scaling turbulent dissipation in the thermocline. J Geophys Res 94(C7):9686–9698CrossRefGoogle Scholar
  13. Gregg MC, Sanford TB, Winkel DP (2003) Reduced mixing from the breaking of internal waves in equatorial waters. Nature 422:513–515CrossRefGoogle Scholar
  14. Henyey FS, Wright J, Flatte SM (1986) Energy and action flow through the internal waves field: an eikonal approach. J Geophys Res 91(C7):8487–8495CrossRefGoogle Scholar
  15. Hibiya T, Nagasawa M (2004) Latitudinal dependence of diapycnal diffusivity in the thermocline estimated using a finescale parameterization. Geophys Res Lett 31:L01301. CrossRefGoogle Scholar
  16. Kalnay EM et al (1996) The NCEP/NCAR 40-year reanalysis project. Bull Am Meteorol Soc 77:437–470CrossRefGoogle Scholar
  17. Kunze E, Smith SGL (2004) The role of small-scale topography in turbulent mixing of the global ocean. Oceanography 17(1):55–64CrossRefGoogle Scholar
  18. Kunze E, Hummon JM, Chereskin TK, Thurnherr AM (2006) Global abyssal mixing inferred from lowered ADCP shear and CTD strain profiles. J Phys Oceanogr 36:1553–1576CrossRefGoogle Scholar
  19. McComas CH, Muller P (1981) The dynamic balance of internal waves. J Phys Oceanogr 11:970–986CrossRefGoogle Scholar
  20. Munk WH (1966) Abyssal recipes. Deep-Sea Res 13:707–730Google Scholar
  21. Munk W (1981) Internal waves and small-scale processes. In: Wunsch WBAC (eds) Evolution of physical oceanography: scientific surveys in honor of henry stommel, MIT Press, pp 264–291.
  22. Munk W, Wuncsh C (1998) Abyssal recipes II: energetics of tidal and wind mixing. Deep-Sea Res 45:1977–2010CrossRefGoogle Scholar
  23. Osborn TR (1980) Estimates of the local rate of vertical diffusion from dissipation measurements. J Phys Oceanogr 10:83–89CrossRefGoogle Scholar
  24. Polzin KL, Toole JM, Schmitt RW (1995) Finescale parameterizations of turbulent dissipation. J Phys Oceanogr 25:306–328CrossRefGoogle Scholar
  25. Polzin KL, Naveira Garabato AC, Huussen TN, Sloyan BM, Waterman S (2014) Finescale parameterizations of turbulent dissipation. J Geophys Res Oceans 119:1383–1419. CrossRefGoogle Scholar
  26. Watanabe M, Hibiya T (2002) Global estimates of the wind-induced energy flux to inertial motions in the surface mixed layer. Geophys Res Lett 29(8):1239. CrossRefGoogle Scholar
  27. Whalen CB, Talley LD, MacKinnon JA (2012) Spatial and temporal variability of global ocean mixing inferred from Argo profiles. Geophys Res Lett 39:L18612. CrossRefGoogle Scholar
  28. Whalen CB, MacKinnon JA, Talley LD, Waterhouse AF (2015) Estimating the mean diapycnal mixing using a finescale strain parameterization. J Phys Oceanogr 45:1174–1188. CrossRefGoogle Scholar
  29. Wijesekera H, Padman L, Dillon T, Levine M, Paulson C, Rinkel R (1993) The application of internal-wave dissipation models to a region of strong mixing. J Phys Oceanogr 23:269–286CrossRefGoogle Scholar
  30. Wu Lixin, Jing Z, Riser S, Visbeck M (2011) Seasonal and spatial variations of Southern Ocean diapycnal mixing from Argo profiling floats. Nat Geosci 4(6):363–366. CrossRefGoogle Scholar
  31. Wyrtki K, Kilonsky B (1984) Mean water and current structure during the Hawaii-to-Tahiti Shuttle Experiment. J Phys Oceanogr 14:242–254CrossRefGoogle Scholar

Copyright information

© The Oceanographic Society of Japan and Springer Japan KK, part of Springer Nature 2018

Authors and Affiliations

  1. 1.College of Marine SciencesShanghai Ocean UniversityShanghaiChina

Personalised recommendations