Skip to main content

Advertisement

SpringerLink
Log in

Indian Ocean variability in the CMIP5 multi-model ensemble: the zonal dipole mode

  • Published:
Climate Dynamics Aims and scope Submit manuscript

Abstract

The performance of 21 Coupled Model Intercomparison Project Phase 5 (CMIP5) models in the simulation of the Indian Ocean Dipole (IOD) mode is evaluated. Compared to CMIP3, CMIP5 models exhibit a similar spread in IOD intensity. A detailed diagnosis was carried out to understand whether CMIP5 models have shown improvement in their representation of the important dynamical and thermodynamical feedbacks in the tropical Indian Ocean. These include the Bjerknes dynamic air-sea feedback, which includes the equatorial zonal wind response to sea surface temperature (SST) anomaly, the thermocline response to equatorial zonal wind forcing, the ocean subsurface temperature response to the thermocline variations, and the thermodynamic air-sea coupling that includes the wind-evaporation-SST and cloud-radiation-SST feedback. Compared to CMIP3, the CMIP5 ensemble produces a more realistic positive wind-evaporation-SST feedback during the IOD developing phase, while the simulation of Bjerknes dynamic feedback is more unrealistic especially with regard to the wind response to SST forcing and the thermocline response to surface wind forcing. The overall CMIP5 performance in the IOD simulation does not show remarkable improvements compared to CMIP3. It is further noted that the El Niño-Southern Oscillation (ENSO) and IOD amplitudes are closely related, if a model generates a strong ENSO, it is likely that this model also simulates a strong IOD.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11
Fig. 12
Fig. 13
Fig. 14
Fig. 15
Fig. 16
Fig. 17

Similar content being viewed by others

References

  • Ashok K, Guan Z, Saji NH, Yamagata T (2004) Individual and combined influences of ENSO and Indian Ocean dipole on the Indian summer monsoon. J Clim 17:3141–3155

    Article  Google Scholar 

  • Behera SK, Luo JJ, Masson S, Delecluse P, Gualdi S, Navarra A (2005) Paramount impact of the Indian Ocean dipole on the east African short rains: a CGCM study. J Clim 18:4514–4530

    Article  Google Scholar 

  • Bellenger H, Guilyardi E, Leloup J, Lengaigne M, Vialard J (2013) ENSO representation in climate models: from CMIP3 to CMIP5. Clim Dyn. doi:10.1007/s00382-013-1783-z

  • Bjerknes J (1966) A possible response of the atmospheric Hadley circulation to equatorial anomalies of ocean temperature. Tellus 18:820–829

    Article  Google Scholar 

  • Bjerknes J (1969) Atmospheric teleconnections from the equatorial Pacific. Mon Weather Rev 97:163–172

    Article  Google Scholar 

  • Cai W, Cowan T (2013) Why is the amplitude of the Indian Ocean Dipole overly large in CMIP3 and CMIP5 climate models? Geophys Res Lett 40:1200–1205. doi:10.1002/grl.50208

    Article  Google Scholar 

  • Cai W, Qiu Y (2013) An observation-based assessment of nonlinear feedback processes associated with the Indian Ocean Dipole. J Clim 26:2880–2890

    Article  Google Scholar 

  • Cai WJ, Hendon HH, Meyers G (2005) Indian Ocean dipole like variability in the CSIRO Mark 3 coupled climate model. J Clim 18:1449–1468

    Article  Google Scholar 

  • Cai W, Sullivan A, Cowan T (2011) Interactions of ENSO, the IOD, and the SAM in CMIP3 Models. J Clim 24:1688–1704

    Article  Google Scholar 

  • Cai W, Rensch PV, Cowan T, Hendon HH (2012) An asymmetry in the IOD and ENSO teleconnection pathway and its impact on Australian climate. J Clim 25:6318–6329

    Article  Google Scholar 

  • Carton JA, Chepurin G, Cao X, Giese B (2000) A simple ocean data assimilation analysis of the global upper ocean 1950–95. Part I: methodology. J Phys Oceanogr 30:294–309

    Article  Google Scholar 

  • Du Y, Qu T, Meyers G, Masumoto Y, Sasaki H (2005) Seasonal heat budget in the mixed layer of the southeastern tropical Indian Ocean in a high-resolution ocean general circulation model. J Geophys Res 110:C04012. doi:10.1029/2004JC002845

  • Du Y, Qu T, Meyers G (2008) Interannual variability of the sea surface temperature off Java and Sumatra in a global GCM. J Clim 21:2451–2465

    Article  Google Scholar 

  • Du Y, Cai W, Wu Y (2013a) A new type of the Indian Ocean Dipole since the mid-1970s. J Clim 26:959–972

    Article  Google Scholar 

  • Du Y, Xie S-P, Yang Y, Zheng X-T, Liu L, Huang G (2013b) Indian Ocean variability in the CMIP5 multi-model ensemble: the basin mode. J Clim. doi:10.1175/JCLI-D-12-00678.1

  • England MH, Ummenhofer CC, Santoso A (2006) Interannual rainfall extremes over Southwest Western Australia linked to Indian Ocean climate variability. J Clim 19:1948–1969

    Article  Google Scholar 

  • Gill AE (1980) Some simple solutions for heat-induced tropical circulation. Q J R Meteorol Soc 106:447–462

    Article  Google Scholar 

  • Hendon H (2003) Indonesian rainfall variability: impacts of ENSO and local air–sea interaction. J Clim 16:1775–1790

    Article  Google Scholar 

  • Hong C–C, Li T, Ho L, Kug J-S (2008) Asymmetry of the Indian Ocean Dipole. Part I: observational analysis. J Clim 21:4834–4848

    Article  Google Scholar 

  • Ishii M, Kimoto M (2009) Reevaluation of historical ocean heat content variations with time-varying XBT and MBT depth bias corrections.J. Oceanography 65(3):287–299

    Article  Google Scholar 

  • Kistler R, Kalnay E, Collins W, Saha S, White G, Woollen J, Chelliah M, Ebisuzaki W, Kanamitsu M, Kousky V, van den Dool H, Jenne R, Fiorino M (2001) The NCEP-NCAR 50-year reanalysis: monthly means CD-ROM and documentation. Bull Am Meteorol Soc 82:247–268

    Article  Google Scholar 

  • Li G, Xie S-P (2012) Origins of tropical-wide SST biases in CMIP multi-model ensembles. Geophys Res Lett 39:L22703. doi:10.1029/2012GL053777

    Google Scholar 

  • Li T, Zhang YS, Lu E, Wang D (2002) Relative role of dynamic and thermodynamic processes in the development of the Indian Ocean dipole. Geophy Res Let 29:2110–2113

    Article  Google Scholar 

  • Li T, Wang B, Chang C-P, Zhang Y (2003) A theory for the Indian Ocean dipole-zonal mode. J Atmos Sci 60:2119–2135

    Article  Google Scholar 

  • Lindzen RS, Nigam S (1987) On the role of sea surface temperature gradients in forcing low level winds and convergence in the tropics. J Atmos Sci 44:2418–2436

    Article  Google Scholar 

  • Liu L, Yu W, Li T (2011) Dynamic and thermodynamic air–sea coupling associated with the Indian Ocean Dipole diagnosed from 23 WCRP CMIP3 models. J Clim 24:4941–4958

    Article  Google Scholar 

  • Liu L, Feng L, Yu W, Wang HW, Liu YL, Sun SW (2013) The distribution and variability of simulated chlorophyll concentration over the tropical Indian Ocean from five CMIP5 models. J Ocean Univ China 12(2):253–259

    Article  Google Scholar 

  • Luo J–J, Masson S, Behera S, Yamagata T (2007) Experimental forecasts of the Indian Ocean dipole using a coupled OAGCM. J Clim 20:2178–2190

    Article  Google Scholar 

  • Luo J–J, Behera S, Masumoto Y, Sakuma H, Yamagata T (2008) Successful prediction of the consecutive IOD in 2006 and 2007. Geophys Res Lett 35:L14S02. doi:10.1029/2007GL032793

    Article  Google Scholar 

  • Luo J–J, Zhang RC, Behera SK, Masumoto Y, Jin F–F, Lukas R, Yamagata T (2010) Interaction between El Nino and extreme Indian Ocean dipole. J Clim 23:726–742

    Article  Google Scholar 

  • Meehl GA et al (2009) Decadal prediction. Bull Am Meteorol Soc 90:1467–1485. doi:10.1175/2009BAMS2778.1

    Article  Google Scholar 

  • Rayner NA, Parker DE, Horton EB, Folland CK, Alexander LV, Rowell DP, Kent EC, Kaplan A (2003) Global analyses 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

    Article  Google Scholar 

  • Saji NH, Yamagata T (2003a) Possible impacts of Indian Ocean Dipole mode events on global climate. Clim Res 25:151–169

    Article  Google Scholar 

  • Saji NH, Yamagata T (2003b) Structure of SST and surface wind variability during Indian Ocean dipole mode years: COADS observations. J Clim 16:2735–2751

    Article  Google Scholar 

  • Saji NH, Goswami BN, Vinayachandran PN, Yamagata T (1999) A dipole mode in the tropical Indian Ocean. Nature 401:360–363

    Google Scholar 

  • Saji NH, Xie SP, Yamagata T (2006) Tropical Indian Ocean variability in the IPCC twentieth-century climate simulations. J Clim 19:4397–4417

    Article  Google Scholar 

  • Shi G, Ribbe J, Cai W, Cowan T (2007) Multidecadal variability in the transmission of ENSO signals to the Indian Ocean. Geophys Res Lett 34:L09706. doi:10.1029/2007GL029528

    Google Scholar 

  • Shi GJ, Cai W, Cowan T, Ribbe J, Rotstayn L, Dix M (2008) Variability and trend of North West Australia rainfall: observations and coupled climate modeling. J Clim 21:2938–2959

    Article  Google Scholar 

  • Simmons AJ, Gibson JK (2000) The ERA-40 project plan. ERA-40 Project Rep. Series No. 1, ECMWF, p 63

  • Smith TM, Reynolds RW (2003) Extended reconstruction of global sea surface temperatures based on COADS data (1854–1997). J Clim 16:1495–1510

    Article  Google Scholar 

  • Song Q, Vecchi GA, Rosati AJ (2007) Indian Ocean variability in the GFDL coupled climate model. J Clim 20:2895–2916

    Article  Google Scholar 

  • Taylor KE, Stouffer RJ, Meehl GA (2012) An overview of CMIP5 and the experiment design”. Bull Am Meteorol Soc 93:485–498. doi:10.1175/BAMS-D-11-00094.1

    Article  Google Scholar 

  • Wang X, Li CY, Zhou W (2006) Interdecadal variation of the relationship between Indian rainfall and SSTA modes in the Indian Ocean. Int J Climatol 26:595–606

    Article  Google Scholar 

  • Webster PJ, Moore AM, Loschnigg JP, Leben RR (1999) Coupled ocean–atmosphere dynamics in the Indian Ocean during 1997–98. Nature 401:356–360

    Article  Google Scholar 

  • Weller E, Cai W (2013) Realism of the Indian Ocean Dipole in CMIP5 models: the implication for climate projections. J Clim. doi:10.1175/JCLI-D-12-00807.1

  • Wijffels S, Meyers GA (2004) An intersection of oceanic wave guides: variability in the Indonesian through flow region. J Phys Oceanogr 34:1232–1253

    Article  Google Scholar 

  • Xie S-P, Philander SGH (1994) A coupled ocean-atmosphere model of relevance to the ITCZ in the eastern Pacific. Tellus 46A:340–350

    Article  Google Scholar 

  • Xie S-P, Annamalai H, Schott FA, McCreary JP (2002) Structure and mechanisms of south Indian Ocean climate variability. J Clim 15:864–878

    Article  Google Scholar 

  • Yamagata T, Behera SK, Luo J-J, Masson S, Jury MR, Rao SA (2004) Coupled ocean-atmosphere variability in the tropical Indian Ocean. In: Wang C, Xie S-P, Carton JA (eds) Earth climate: the ocean-atmosphere interaction. Geophysical Monograph 147,  American Geophysical Union, pp 189–212

  • Yu W, Xiang B, Liu L, Liu N (2005) Understanding the origins of interannual thermocline variations in the tropical Indian Ocean. Geophys Res Lett 32:L24706. doi:10.1029/2005GL024327

    Article  Google Scholar 

  • Zheng X-T, Xie S-P, Vecchi GA, Liu Q, Hafner J (2010) Indian Ocean dipole response to global warming: analysis of ocean–atmospheric feedbacks in a coupled model. J Clim 23:1240–1253

    Article  Google Scholar 

  • Zheng X-T, Xie S-P, Du Y, Liu L, Huang G, Liu Q-Y (2013) Indian Ocean Dipole response to global warming in the CMIP5 multi-model ensemble. J Clim. doi:10.1175/JCLI-D-12-00638.1

  • Zhong A, Hendon HH, Alves O (2005) Indian Ocean variability and its association with ENSO in a global coupled model. J Clim 18:3634–3649

    Article  Google Scholar 

Download references

Acknowledgments

We acknowledge the World Climate Research Programme’s Working Group on Coupled Modelling, which is responsible for CMIP, and we thank the climate modeling groups for producing and making available their model output. For CMIP the U.S. Department of Energy’s Program for Climate Model Diagnosis and Intercomparison provides coordinating support and led development of software infrastructure in partnership with the Global Organization for Earth System Science Portals. We wish to thank L. X. Xu and L. Feng for data preparation. This work was supported by Chinese National Basic Research Program grants: 2010CB950304, 2012CB955601 and ARCP2013-27NSY-Liu grants and the Natural Science Foundation of China (41376037, 41306030, and 41106010).

Author information

Authors and Affiliations

  1. Center for Ocean and Climate Research, First Institute of Oceanography, State Oceanic Administration (SOA), Qingdao, 266061, China

    Lin Liu & Wei-Dong Yu

  2. Scripps Institution of Oceanography, University of California, San Diego, La Jolla, CA, USA

    Shang-Ping Xie

  3. Physical Oceanography Laboratory, Ocean University of China, Qingdao, China

    Shang-Ping Xie & Xiao-Tong Zheng

  4. International Pacific Research Center and Department of Meteorology, University of Hawaii at Manoa, Honolulu, HI, USA

    Tim Li

  5. State Key Laboratory of Tropical Oceanography, South China Sea Institute of Oceanology, Chinese Academy of Sciences, Guangzhou, China

    Yan Du

  6. Key Laboratory of Regional Climate-Environment Research for Temperate East Asia, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, China

    Gang Huang

  7. Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters, Nanjing University of Information Science and Technology, Nanjing, China

    Gang Huang

Authors
  1. Lin Liu
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Shang-Ping Xie
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Xiao-Tong Zheng
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Tim Li
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Yan Du
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Gang Huang
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Wei-Dong Yu
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Lin Liu.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Liu, L., Xie, SP., Zheng, XT. et al. Indian Ocean variability in the CMIP5 multi-model ensemble: the zonal dipole mode. Clim Dyn 43, 1715–1730 (2014). https://doi.org/10.1007/s00382-013-2000-9

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00382-013-2000-9

Keywords

Search

Navigation