Acta Oceanologica Sinica

, Volume 34, Issue 11, pp 92–101 | Cite as

Mesoscale characteristics of Antarctic Intermediate Water in the South Pacific

  • Ying Feng
  • Xianyao Chen
  • Qin Wang
  • Yeli Yuan


The Argo float observations are used to investigate the mesoscale characteristics of the Antarctic Intermediate Water (AAIW) in the South Pacific in this paper. It is shown that a subsurface mesoscale phenomenon is probably touched by an Argo float during the float’s ascent-descent cycles and is identified by the horizontal salinity gradient between the vertical temperature-salinity profiles. This shows that the transportation of the AAIW may be accompanied with the rich mesoscale characteristics. To derive the spatial length, time, and propagation characteristics of the mesoscale variability of the AAIW, the gridded temperature-salinity dataset ENACT/ENSEMBLE Version 3 constructed on the in-situ observations in the South Pacific since 2005 is used. The Empirical Mode Decomposition method is applied to decompose the isopycnal-averaged salinity anomaly from 26.8 σ θ –27.4 σ θ , where the AAIW mainly resides, into the basin scale and two mesoscale modes. It is found that the first mesoscale mode with the length scale on the order of 1 000 km explains nearly 50% variability of the mesoscale characteristics of the AAIW. Its westward-propagation speeds are slower in the mid-latitude (around 1 cm/s) and faster in the low latitude (around 6 cm/s), but with an increasing in the latitude band on 25°–30°S. The second mesoscale mode is of the length scale on the order of 500 km, explaining about 30% variability of the mesoscale characteristics of the AAIW. Its westward-propagation speed keeps nearly unchanged (around 0.5 cm/s). These results presented the stronger turbulent motion of the subsurface ocean on the spatial scale, and also described the significant role of Argo program for the better understanding of the deep ocean.


mesoscale characteristics subsurface ocean Antarctic Intermediate Water (AAIW) Argo 


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. Alory H, Wijffels S, Meyers G M. 2007. Observed temperature trends in the Indian Ocean over 1960–1999 and associated mechanisms. Geophys Res Lett, 34: L02606Google Scholar
  2. Barron C N, Kara A B, Jacobs G A. 2009. Objective estimates of westward Rossby wave and eddy propagation from sea surface height analyses. J Geophys Res, 114: C03013Google Scholar
  3. Boyer T P, Antonov J I, Garcia H, et al. 2006. World Ocean Databas. 2005. Chapter 1: Introduction, NOAA Atlas NESDIS 60. In: Levitus S, eds. Washington, D C: US Government Printing Office, 182, DVDGoogle Scholar
  4. Casal T G D, Beal L M, Lumpkin R. 2006. A North Atlantic deep-water eddy in the Agulhas current system. Deep-Sea Res Pt I, 53: 1718–1728CrossRefGoogle Scholar
  5. Challenor P G, Cipollini P, Cromwell D. 2001. Use of the 3D Radon transform to examine the properties of oceanic Rossby waves. J Atmos Oceanic Technol, 18(9): 1558–1566CrossRefGoogle Scholar
  6. Chelton D B, Schlax M G. 1996. Global observations of oceanic Rossby waves. Science, 272(5259): 234–238CrossRefGoogle Scholar
  7. Chelton D B, Schlax M G, Lyman J M, et al. 2003. Equatorially trapped Rossby waves in the presence of meridionally sheared baroclinic flow in the Pacific Ocean. Prog Oceanogr, 56(2): 323–380CrossRefGoogle Scholar
  8. Chelton D B, Schlax M G, Samelson R M, et al. 2007. Global observations of large oceanic eddies. Geophys Res Lett, 34: L15606CrossRefGoogle Scholar
  9. Chiswell S M and Sutton P J H. 1998. A deep eddy in the Antarctic Intermediate Water North of the Chatham rise. J Phys Oceanogr, 28: 535–540CrossRefGoogle Scholar
  10. Chen Xianyao, Wu Zhaohua, Huang N E. 2010. The time-dependent intrinsic correlation based on the empirical mode decomposition. Advances in Adaptive Data Analysis, 2(2): 233–265CrossRefGoogle Scholar
  11. Cipollini P, Cromwell D, Challenor P G, et al. 2001. Rossby waves detected in global ocean colour data. Geophys Res Lett, 28(2): 323–326CrossRefGoogle Scholar
  12. Dengler M, Schott F A, Eden C, et al. 2004. Break-up of the Atlantic deep western boundary current into eddies at 81°S. Nature, 432: 1018–1020CrossRefGoogle Scholar
  13. Domingues C M, Church J A, White N J, et al. 2008. Improved estimates of upper-ocean warming and multi-decadal sea level rise. Nature, 453(7198): 1090–1093CrossRefGoogle Scholar
  14. Halliwell G R Jr, Mooers C N K. 1979. The space-time structure and variability of the shelf water-slope water and Gulf Stream surface temperature fronts and associated warm-core eddies. J Geophys Res, 84: 7707–7725CrossRefGoogle Scholar
  15. Halliwell G R, Ro Y J, Cornillon P. 1991. Westward-propagating SST anomalies and baroclinic eddies in the Sargasso Sea. J Phys Oceanogr, 21: 1664–1680CrossRefGoogle Scholar
  16. Hill K L, Robinson I S, Cipollini P. 2000. Propagation characteristics of extratropical planetary waves observed in the ATSR global sea surface temperature record. J Geophys Res, 105(C9): 21927–21945CrossRefGoogle Scholar
  17. Huang N E, Shen Zheng, Long S R, et al. 1998. The empirical mode decomposition and the Hilbert spectrum for nonlinear and non-stationary time series analysis. Proceedings of the Royal Society A: Mathematical, Physical and Engineering Sciences, 454(1971): 903–995CrossRefGoogle Scholar
  18. Huang N E, Wu Zhaohua. 2008. A review on Hilbert-Huang transform: the method and its applications to geophysical studies. Rev Geophys, 46: RG2006CrossRefGoogle Scholar
  19. Huang N E, Wu Zhaohua, Long S R, et al. 2009. On instantaneous frequency. Advances in Adaptive Data Analysis, 1(2): 177–229CrossRefGoogle Scholar
  20. Isern-Fontanet J, Garcia-Ladona E, Font J. 2003. Identification of marine eddies from altimetric maps. J Atmos Oceanic Technol, 20: 772–778CrossRefGoogle Scholar
  21. Ingleby B, Huddleston M. 2007. Quality control of ocean temperature and salinity profiles historical and real-time data. Journal of Marine Systems, 65(1-4): 158–175CrossRefGoogle Scholar
  22. Jacobs G A, Barron C N, Rhodes R C. 2001. Mesoscale characteristics. J Geophys Res, 106(C9): 19581–19595CrossRefGoogle Scholar
  23. McWilliams J C, Owens W B, Hua B L. 1986. An objective analysis of the POLYMODE Local Dynamics Experiment, part I, General formalism and statistical model selection. J Phys Oceanogr, 380(16): 483–504CrossRefGoogle Scholar
  24. Naveira A C, Garabato A C, Jullion L, Stevens D P, et al. 2009. Variability of subantarctic mode water and Antarctic intermediate water in the Drake Passage during the Late-Twentieth and Early-Twenty-First centuries. J Climate, 22(13): 3661–3688CrossRefGoogle Scholar
  25. Oka E. 2005. Long-term sensor drift found in recovered ARGO profiling floats. Journal of Oceanography, 61(4): 775–781CrossRefGoogle Scholar
  26. Richardson P L, Bower A S, Zenk W. 2000. A census of meddies tracked by floats. Prog Oceanogr, 45: 209–250CrossRefGoogle Scholar
  27. Susanto R D, Zheng Quanan, Yan Xiaohai. 1998. Complex singular value decomposition analysis of equatorial waves in the Pacific observed by TOPEX/Poseidon altimeter. J Atmos Oceanic Technol, 15(3): 764–774CrossRefGoogle Scholar
  28. Tomczak M, andrew C. 1997. Eddy formation in the Antarctic Intermediate Water of the subtropical South Pacific Ocean. J Mar Atmos Res, 1: 8–12Google Scholar
  29. Tomczak M. 2006. Variability of Antarctic intermediate water properties in the South Pacific Ocean. Ocean Science Discussions, 3(6): 2021–2058CrossRefGoogle Scholar
  30. Weatherly G, Arhan M, Mercier H, et al. 2002. Evidence of abyssal eddies in the Brazil Basin. J Geophys Res, 107: 3027–3041CrossRefGoogle Scholar
  31. Wu Zhaohua, Huang N E. 2009. Ensemble empirical mode decomposition: A noise-assisted data analysis method. Advances in Adaptive Data Analysis, 1(1): 1–41CrossRefGoogle Scholar
  32. Wu Zhaohua, Huang N E, Long S R, et al. 2007. On the trend, detrending, and variability of nonlinear and nonstationary time series. Proceedings of the National Academy of Sciences of the United States of America, 104(38): 14889–14894CrossRefGoogle Scholar

Copyright information

© The Chinese Society of Oceanography and Springer-Verlag Berlin Heidelberg 2015

Authors and Affiliations

  1. 1.College of Ocean and Earth SciencesXiamen UniversityXiamenChina
  2. 2.Key Laboratory of Physcial OceanographyOcean University of ChinaQingdaoChina
  3. 3.Marine Monitoring and Forecasting Center of ZhejiangHangzhouChina
  4. 4.Key Laboratory of Marine Science and Numerical Modeling, the First Institute of OceanographyState Oceanic AdministrationQingdaoChina

Personalised recommendations