Climate Dynamics

, Volume 31, Issue 2–3, pp 333–343 | Cite as

Tropical Indian Ocean variability revealed by self-organizing maps

  • Tomoki Tozuka
  • Jing-Jia Luo
  • Sebastien Masson
  • Toshio Yamagata


The tropical Indian Ocean climate variability is investigated using an artificial neural network analysis called self-organizing map (SOM) for both observational data and coupled model outputs. The SOM successfully captures the dipole sea surface temperature anomaly (SSTA) pattern associated with the Indian Ocean Dipole (IOD) and basin-wide warming/cooling associated with ENSO. The dipole SSTA pattern appears only in boreal summer and fall, whereas the basin-wide warming/cooling appears mostly in boreal winter and spring owing to the phase-locking nature of these phenomena. Their occurrence also undergoes significant decadal variation. Composite diagrams constructed for nodes in the SOM array based on the simulated SSTA reveal interesting features. For the nodes with the basin-wide warming, a strong positive SSTA in the eastern equatorial Pacific, a negative Southern Oscillation, and a negative precipitation anomaly in East Africa are found. The nodes with the positive IOD are associated with a weak positive SSTA in the central equatorial Pacific or positive SSTA in the eastern equatorial Pacific, a positive (negative) sea level pressure anomaly in the eastern (western) tropical Indian Ocean, and a positive precipitation anomaly over East Africa. The warming in the central equatorial Pacific appears to correspond to El Niño Modoki discussed recently. These results suggest usefulness of SOM in studying large-scale ocean–atmosphere coupled phenomena.


Indian Ocean Dipole El Niño-Southern Oscillation Self-organizing map Decadal variability Seasonal phase-locking 



This study is benefited from discussions with Dr. S. K. Behera and Dr. I. Iskandar. Constructive comments from three reviewers helped us to improve our manuscript. We are indebted to Dr. R. Zhang for data management. The SINTEX-F1 model was run on the Earth Simulator. 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 the 21st century COE grant from the Ministry of Education, Culture, Sports, Science, and Technology of Japan for the “Predictability of the Evolution and Variation of the Multi-scale Earth System: An Integrated COE for Observational and Computational Earth Science” of the University of Tokyo, and the Japan Society for Promotion of Science through Grant-in-Aid for Scientific Research (A) 17204040.


  1. Allan NJ, Chambers D, Drosdowsky W, Hendon H, Latif M, Nicholls N, Smith I, Stone R, Tourre Y (2001) Is there an Indian Ocean Dipole, and is it independent of El Niño-Southern Oscillation? CLIVAR Exch 6:18–22Google Scholar
  2. An SI, Ye Z, Hsieh WW (2006) Changes in the leading ENSO modes associated with the late 1970s climate shift: role of surface zonal current. Geophys Res Lett 33: doi: 10.1029/2006GL026604
  3. Annamalai H, Murtugudde R (2004) Role of the Indian Ocean in regional climate variability. In Earth’s climate: the ocean–atmosphere interaction. Geophys Monogr Ser 147:213–211Google Scholar
  4. Ashok K, Guan Z, Yamagata T (2001) Impact of the Indian Ocean Dipole on the decadal relationship between the Indian monsoon rainfall and ENSO. Geophys Res Lett 28:4499–4502CrossRefGoogle Scholar
  5. Ashok K, Behera SK, Rao SA, Weng H, Yamagata T (2007) El Niño-Modoki and its possible teleconnections. J Geophys Res 112: doi: 10.1029/2006JC003798
  6. Behera SK, Yamagata T (2003) Influence of the Indian Ocean Dipole on the Southern Oscillation. J Meteor Soc Japan 81:169–177CrossRefGoogle Scholar
  7. Behera SK, Rao SA, Saji HN, Yamagata T (2003) Comments on “A cautionary note on the interpretation of EOFs”. J Clim 16:1087–1093CrossRefGoogle Scholar
  8. Behera SK, Luo JJ, Masson S, Delecluse P, Gualdi S, Navarra A, Yamagata T (2005) Paramount impact of the Indian Ocean Dipole on the East African short rains: a CGCM study. J Clim 18:4514–4530CrossRefGoogle Scholar
  9. Black E, Slingo J, Sperber KR (2003) An observational study of the relationship between excessively strong short rains in coastal East Africa and Indian Ocean SST. Mon Wea Rev 131:74–94CrossRefGoogle Scholar
  10. Chang P, Yamagata T, Schopf P, Behera SK, Carton J, Kessler WS, Meyers G, Qu T, Schott F, Shetye S, Xie SP (2006) Climate fluctuations of tropical coupled systems-The role of ocean dynamics. J Clim 19:5122–5174CrossRefGoogle Scholar
  11. Cheng P, Wilson RE (2006) Temporal variability of vertical nontidal circulation pattern in a partially mixed estuary: comparison of self-organizing map and empirical orthogonal functions. J Geophys Res 111: doi: 10.1029/ 2005JC003241
  12. Collins DC, Reason CJC, Tangang F (2004) Predictability of Indian Ocean sea surface temperature using canonical correlation analysis. Clim Dyn 22:481–497CrossRefGoogle Scholar
  13. Dommenget D, Latif M (2002) A cautionary note on the interpretation of EOFs. J Clim 15:216–225CrossRefGoogle Scholar
  14. Guan Z, Yamagata T (2003) The unusual summer of 1994 in East Asia: IOD teleconnections. Geophys Res Lett 30: doi: 10.1029/2002GL016831
  15. Gualdi S, Guilyardi E, Navarra A, Masina S, Delecluse P (2003) The interannual variability in the tropical indian ocean as simulated by a coupled GCM. Clim Dyn 20:567–582Google Scholar
  16. Klein SA, Soden BJ, Lau NC (1999) Remote sea surface temperature variations during ENSO: evidence for a tropical atmospheric bridge. J Clim 12:917–932CrossRefGoogle Scholar
  17. Kohonen T (1982) Self-organized information of topologically correct features maps. Biol Cybern 43:59–69CrossRefGoogle Scholar
  18. Kohonen T (2001) Self-organizing maps. 3rd edn. Springer, Berlin, p 501 Google Scholar
  19. Kohonen T, Hynninen J, Kangas J, Laaksonen J (1995) SOM_PAK, The self-organizing map program package version 3.1, Laboratory of Computer and Information Science, Helsinki University of Technology, Finland, 27 ppGoogle Scholar
  20. Leloup JA, Lachkar Z, Boulanger JP, Thiria S (2007a) Detecting decadal changes in ENSO using neural networks. Clim Dyn 28:147–162CrossRefGoogle Scholar
  21. Leloup JA, Lengaigne M, Boulanger JP (2007b) Twentieth century ENSO characteristics in the IPCC database. Clim Dyn: doi: 10.1007/s00382-007-0284-3
  22. 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
  23. Luo JJ, Masson S, Behera SK, Gualdi S, Navarra A, Delecluse P, Yamagata T (2003) South Pacific source of the decadal ENSO-like variation as reproduced by a coupled GCM. Geophys Res Lett 30: doi: 10.1029/2003GL018649
  24. Madec G, Delecluse P, Imbard M, Levy C (1998) OPA version 8.1 ocean general circulation model reference manual. Tech Rep/Note, 11: LODYC/IPSL, Paris, 91 ppGoogle Scholar
  25. North GR, Bell LT, Cahalan RF (1982) Sampling errors in the estimation of empirical orthogonal functions. Mon Wea Rev 110:699–706CrossRefGoogle Scholar
  26. Rayner NA, Parker DE, Horton EB, Folland CK, Alexander LV, Rowell DP, Kent EC, Kaplan A (2003) Global analysis of SST, sea ice and night marine air temperature since the late nineteenth century. J Geophys Res 108: doi: 10.1029 /2002JD002670
  27. Richardson AJ, Risien C, Shillington FA (2003) Using self-organizing maps to identify patterns in satellite imagery. Prog Oceanogr 59:223–239CrossRefGoogle Scholar
  28. Roeckner E et al (1996) The atmospheric general circulation model ECHAM4: model description and simulation of present day climate. Max-Plank Institute fur Meteorologie Rep 218: Hamburg, 90 ppGoogle Scholar
  29. Saji NH, Yamagata T (2003) Possible impacts of Indian Ocean Dipole events on global climate. Clim Res 25:151–169CrossRefGoogle Scholar
  30. Saji NH, Goswami BN, Vinayachandran PN, Yamagata T (1999) A dipole mode in the tropical Indian Ocean. Nature 401:360–363Google Scholar
  31. Tozuka T, Luo JJ, Masson S, Behera SK, Yamagata T (2005) Annual ENSO simulated in a coupled ocean–atmosphere model. Dyn Atmos Ocean 39:41–60CrossRefGoogle Scholar
  32. Tozuka T, Luo JJ, Masson S, Yamagata T (2007) Decadal modulations of the Indian Ocean Dipole in the SINTEX-F1 coupled GCM. J Clim 20:2881–2894CrossRefGoogle Scholar
  33. Valcke S, Terray L, Piacentini A (2000) The OASIS coupler user guide version 2.4. Tech Rep TR/CMGC/00–10, CERFACS, Toulouse, p 85Google Scholar
  34. Vecchi GA, Harrison DE (2004) Interannual Indian rainfall variability and Indian Ocean sea surface temperature anomalies. In Earth’s climate: the ocean–atmosphere interaction. Geophys Monogr Ser 147:247–259Google Scholar
  35. Walker GT (1924) Correlations in seasonal variations of weather. IX Mem India Meteorol Dep 24:275–332Google Scholar
  36. Webster PJ, Moore A, Loschnigg J, Leban M (1999) Coupled ocean-atmosphere dynamics in the Indian Ocean during 1997–98. Nature 401:356–360CrossRefGoogle Scholar
  37. Weng H, Ashok K, Behera SK, Rao SA, Yamagata T (2007) Impacts of recent El Niño Modoki on dry/wet conditions in the Pacific rim during boreal summer. Clim Dyn 29:113–129CrossRefGoogle Scholar
  38. Wu A, Hsieh WW (2003) Nonlinear interdecadal changes of the El Niño-Southern Oscillation. Clim Dyn 21:719–730Google Scholar
  39. Yamagata T, Behera SK, Luo J-J, Masson S, Jury MR, Rao SA (2004) Coupled ocean-atmosphere variability in the tropical Indian Ocean. In Earth’s climate: The ocean-atmosphere interaction. Geophys Monogr Ser 147:189–211Google Scholar

Copyright information

© Springer-Verlag 2007

Authors and Affiliations

  • Tomoki Tozuka
    • 1
  • Jing-Jia Luo
    • 2
  • Sebastien Masson
    • 3
  • Toshio Yamagata
    • 1
    • 2
  1. 1.Department of Earth and Planetary Science, Graduate School of ScienceThe University of TokyoTokyoJapan
  2. 2.Frontier Research Center for Global Change/JAMSTECYokohamaJapan
  3. 3.LOCEANParisFrance

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