Climate Dynamics

, Volume 41, Issue 7–8, pp 1955–1968 | Cite as

How is the Indian Ocean Subtropical Dipole excited?



Based on experiments using a coupled general circulation model which resolves tropical ocean–atmosphere coupled phenomena such as El Niño/Southern Oscillation (ENSO) and the Indian Ocean Dipole, forcing mechanisms of the Indian Ocean subtropical dipole (IOSD) are investigated. In the control experiment, as in the observation, several types of the IOSD are generated by the variations in the Mascarene High during austral summer and characterized by a dipole pattern of sea surface temperature (SST) anomalies in the northeastern and southwestern parts of the southern Indian Ocean. In another experiment, where the SST outside the southern Indian Ocean is nudged toward the monthly climatology of the simulated SST, one type of the IOSD occurs, but it is less frequent and associated with the zonal wavenumber four pattern of equivalently barotropic geopotential height anomalies in high latitudes, suggesting an interesting link with the Antarctic Circumpolar Wave. This indicates that, even without the atmospheric teleconnection from tropical coupled climate modes, the IOSD may develop in association with the atmospheric variability in high latitudes of the Southern Hemisphere. In the other experiment, where only the southern Indian Ocean and the tropical Pacific are freely interactive with the atmosphere, two types of both positive and negative IOSD occur. Since the occurrence frequency of the IOSD significantly increases as compared to the second experiment, this result confirms that the atmospheric teleconnection from ocean-atmosphere coupled modes in the tropical Pacific such as ENSO may also induce the variations in the Mascarene High that generate the IOSD. The present research, even within the realm of model studies, shows clearly that the predictability of the IOSD in mid-latitudes is related to both low and high-latitudes climate variations.


Indian Ocean Subtropical Dipole Mascarene High Antarctic Oscillation Antarctic Circumpolar Wave 



The CGCM was run on the HITACHI SR11000/J1 of the Information Technology Center at the University of Tokyo as a part of cooperative research with the Atmosphere and Ocean Research Institute of the University of Tokyo. We thank three anonymous reviewers for their constructive comments. The SOM_PAK software was provided by the Neural Network Research Centre at the Helsinki University of Technology and is available at The present research is supported by Japan Science and Technology Agency/Japan International Cooperation Agency through the Science and Technology Research Partnership for Sustainable Development (SATREPS). Also, the first author is supported by Research Fellowship of the Japan Society for the Promotion of Science (JSPS).


  1. Behera SK, Yamagata T (2001) Subtropical SST dipole events in the southern Indian Ocean. Geophys Res Lett 28:327–330CrossRefGoogle Scholar
  2. Chakraborty A, Tozuka T, Miyasaka T, Mujumdar M, Behera SK, Yamagata T (2003) Development of the University of Tokyo Community Model (UTCM) for climate system: preliminary results. Technical Report for Mitsubishi Heavy Industries Ltd. pp 49Google Scholar
  3. Chakraborty A, Behera SK, Mujumdar M, Ohba R, Yamagata T (2006) Diagnosis of tropospheric moisture over Saudi Arabia and influences of IOD and ENSO. Mon Wea Rev 134:598–617. doi: 10.1175/MWR3085.1 CrossRefGoogle Scholar
  4. Doi T, Tozuka T, Yamagata T (2010) The Atlantic meridional mode and its coupled variability with the Guinea dome. J Clim 23:455–475. doi: 10.1175/2009JCLI3198.1 CrossRefGoogle Scholar
  5. Fauchereau N, Trzaska S, Richard Y, Roucou P, Camberlin P (2003) Sea-surface temperature co-variability in the southern Atlantic and Indian Oceans and its connections with the atmospheric circulation in the Southern Hemisphere. Int J Climatol 23:663–677. doi: 10.1002/joc.905 CrossRefGoogle Scholar
  6. Fogt RL, Bromwich DH (2006) Decadal variability of the ENSO teleconnection to the high-latitude South Pacific governed by coupling with the Southern Annular Mode. J Clim 19:979–997CrossRefGoogle Scholar
  7. Guan Z, Iizuka S, Chiba M, Yamane S, Ashok K, Honda M, Yamagata T (2000) Frontier atmospheric general circulation model version 1.0 (FrAM 1.0): model climatology. Technical Report FTR-1, pp 27Google Scholar
  8. Hermes JC, Reason CJC (2005) Ocean model diagnosis of interannual coevolving SST variability in the South Indian and South Atlantic Oceans. J Clim 18:2864–2882CrossRefGoogle Scholar
  9. Iskandar I, Tozuka T, Masumoto Y, Yamagata T (2008) Impact of Indian Ocean Dipole on intraseasonal zonal currents at 90°E on the equator as revealed by self-organizing map. Geophys Res Lett 35. doi: 10.1029/2008GL033468
  10. Kalnay E et al (1996) The NCEP/NCAR 40-year reanalysis project. Bull Am Meteor Soc 77:437–471CrossRefGoogle Scholar
  11. Kataoka T, Tozuka T, Masumoto Y, Yamagata T (2012) The Indian Ocean subtropical dipole mode simulated in the CMIP3 models. Clim Dyn 39:1385–1399. doi: 10.1007/s00382-011-1271-2 CrossRefGoogle Scholar
  12. Kohonen T (1982) Self-organized formation of topologically correct feature maps. Biol Cybern 43:59–69CrossRefGoogle Scholar
  13. Kohonen T (2001) Self-organizing maps, 3rd edn. Springer, Berlin, pp 501Google Scholar
  14. Kuo HL (1974) Further studies of the parameterization of the influence of cumulus convection on large-scale flow. J Atmos Sci 31:1232–1240CrossRefGoogle Scholar
  15. L’Heureux ML, Thompson DWJ (2006) Observed relationships between the El Niño-Southern Oscillation and the extratropical zonal-mean circulation. J Clim 19:276–287CrossRefGoogle Scholar
  16. Lacis AA, Hansen JE (1974) A parameterization for the absorption of solar radiation in the earth’s atmosphere. J Atmos Sci 31:118–133CrossRefGoogle Scholar
  17. Leloup JA, Lachkar Z, Boulanger JP, Thiria S (2007) Detecting decadal changes in ENSO using neural networks. Clim Dyn 28:147–162. doi: 10.1007/s00382-006-0173-1 CrossRefGoogle Scholar
  18. Leloup J, Lengaigne M, Boulanger JP (2008) Twentieth century ENSO characteristics in the IPCC database. Clim Dyn 30:277–291. doi: 10.1007/s00382-007-0284-3 CrossRefGoogle Scholar
  19. Levitus S, Boyer TP (1994) World Ocean Atlas. Vol. 4: Temperature. NOAA Atlas NESDIS 4, US Govt Printing Office, pp 117Google Scholar
  20. Levitus S, Burgett R, Boyer TP (1994) World Ocean Atlas. Vol. 3: salinity. NOAA Atlas NESDIS 3, US Govt Printing Office, pp 99Google Scholar
  21. Liu Y, Weisberg RH, Mooers CNK (2006) Performance evaluation of the self-organizing map for feature extraction. J Geophys Res 111. doi: 10.1029/2005JC003117
  22. Louis J, Tiedtke M, Geleyn JF (1982) A short history of PBL parameterization at ECMWF. Workshop on planetary boundary layer parameterization, ECMWF, pp 59–80Google Scholar
  23. Mason SJ (1995) Sea-surface temperature—South African rainfall associations, 1910–1989. Int J Climatol 15:119–135CrossRefGoogle Scholar
  24. Miyasaka T, Nakamura H (2010) Structure and mechanisms of the Southern Hemisphere summertime subtropical anticyclones. J Clim 23:2115–2130. doi: 10.1175/2009JCLI3008.1 CrossRefGoogle Scholar
  25. Mo KC (2000) Relationships between low-frequency variability in the Southern Hemisphere and sea surface temperature anomalies. J Clim 13:3599–3610CrossRefGoogle Scholar
  26. Morioka Y, Tozuka T, Yamagata T (2010) Climate variability in the southern Indian Ocean as revealed by self-organizing maps. Clim Dyn 35:1059–1072. doi: 10.1007/s00382-010-0843-x CrossRefGoogle Scholar
  27. Morioka Y, Tozuka T, Yamagata T (2012) Subtropical Dipole modes simulated in a coupled general circulation model. J Clim 25:4029–4047. doi: 10.1175/JCLI-D-11-00396.1 CrossRefGoogle Scholar
  28. North GR, Bell TL, Cahalan RF, Moeng FJ (1982) Sampling errors in the estimation of empirical orthogonal functions. Mon Wea Rev 110:699–706CrossRefGoogle Scholar
  29. Pacanowski RC, Griffies SM (1999) MOM3.0 manual. NOAA/GFDL, pp 680Google Scholar
  30. Pacanowski RC, Philander SGH (1981) Parameterization of vertical mixing in numerical models of tropical oceans. J Phys Oceanogr 11:1443–1451CrossRefGoogle Scholar
  31. Palmer TN, Shutts GJ, Swinbank R (1986) Alleviation of a systematic westerly bias in general circulation and numerical weather prediction models through an orographic gravity wave drag parameterization. Q J R Meteor Soc 112:1001–1039CrossRefGoogle Scholar
  32. Rayner NA, Parker DE, Horton EB, Folland CK, Alexander LV, Rowell DP, Kent EC, Kaplan A (2003) Global analysis of sea surface temperature, sea ice, and night marine air temperature since the late nineteenth century. J Geophys Res 108(D14) 4407. doi: 10.1029/2002JD002670
  33. Saji NH, Goswami BN, Vinayachandran PN, Yamagata T (1999) A dipole mode in the tropical Indian Ocean. Nature 401:360–363Google Scholar
  34. Shibata K (1989) An economical scheme for the vertical integral of atmospheric emission in longwave radiative transfer. J Meteor Soc Jpn 67:1047–1055Google Scholar
  35. Shibata K, Aoki T (1989) An infrared radiative scheme for the numerical models of weather and climate. J Geophys Res 94:14923–14943CrossRefGoogle Scholar
  36. Slingo A, Slingo JM (1991) Response of the National Center for Atmospheric Research Community Climate Model to improvements in the representation of clouds. J Geophys Res 96:15341–15357CrossRefGoogle Scholar
  37. Smagorinsky J (1963) General circulation experiments with the primitive equations. I. The basic experiments. Mon Wea Rev 91:99–164CrossRefGoogle Scholar
  38. Suzuki R, Behera SK, Iizuka S, Yamagata T (2004) Indian Ocean Subtropical Dipole simulated using a coupled general circulation model. J Geophys Res 109 C09001. doi: 10.1029/2003JC001974
  39. Thompson RORY (1979) Coherence significance levels. J Atmos Sci 36:2020–2021CrossRefGoogle Scholar
  40. Thompson T (1981) Proposed format for gridded sea ice information (SIGRID). Report prepared for the World Climate ProgrammeGoogle Scholar
  41. Thompson DWJ, Wallace JM (2000) Annular modes in the extratropical circulation. Part I: month-to-month variability. J Clim 13:1000–1016CrossRefGoogle Scholar
  42. Tozuka T, Miyasaka T, Chakraborty A, Mujumdar M, Behera SK, Masumoto Y, Nakamura H, Yamagata T (2006) University of Tokyo coupled general circulation model (UTCM1.0). Ocean–Atmosphere Research Report 7, pp 44Google Scholar
  43. Tozuka T, Luo JJ, Masson S, Yamagata T (2008) Tropical Indian Ocean variability revealed by self-organizing maps. Clim Dyn 31:333–343. doi: 10.1007/s00382-007-0356-4 CrossRefGoogle Scholar
  44. Tozuka T, Qu T, Masumoto Y, Yamagata T (2009) Impacts of the South China sea throughflow on seasonal and interannual variations of the Indonesian throughflow. Dyn Atmos Ocean 47:73–85. doi: 10.1016:j.dynatmoce.2008.09.001 CrossRefGoogle Scholar
  45. Tozuka T, Doi T, Miyasaka T, Keenlyside N, Yamagata T (2011) Key factors in simulating the equatorial Atlantic zonal sea surface temperature gradient in a coupled general circulation model. J Geophys Res 116 C06010. doi: 10.1029/2010JC006717
  46. Viterbo P, Beljaars ACM (1995) An improved land surface parameterization scheme in the ECMWF model and its validation. J Clim 8:2716–2748Google Scholar
  47. Walker ND (1990) Links between South African summer rainfall and temperature variability of the Agulhas and Benguela current systems. J Geophys Res 95:3297–3319CrossRefGoogle Scholar
  48. Washington R, Preston A (2006) Extreme wet years over southern Africa: Role of Indian Ocean sea surface temperatures. J Geophys Res 111 D15104. doi: 10.1029/2005JD006724
  49. Watterson IG (2002) The sensitivity of subannual and intraseasonal tropical variability to model ocean mixed layer depth. J Geophys Res 107 D24020. doi: 10.1029/2001JD000671
  50. White WB, Peterson RG (1996) An Antarctic circumpolar wave in surface pressure, wind, temperature, and sea-ice extent. Nature 380:699–702CrossRefGoogle Scholar
  51. Yuan C, Tozuka T, Yamagata T (2012a) IOD influence on the early winter Tibetan Plateau snow cover: diagnostic analyses and an AGCM simulation. Clim Dyn 39:1643–1660. doi: 10.1007/s00382-011-1204-0 CrossRefGoogle Scholar
  52. Yuan C, Tozuka T, Luo JJ, Yamagata T (2012b) Predictability of the Subtropical Dipole modes in a coupled ocean-atmosphere model. Clim Dyn (submitted)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  1. 1.Research Institute for Global ChangeJAMSTECYokohamaJapan
  2. 2.Department of Earth and Planetary Science, Graduate School of ScienceThe University of TokyoTokyoJapan
  3. 3.Application LaboratoryJAMSTECYokohamaJapan

Personalised recommendations