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Climate Dynamics

, Volume 43, Issue 5–6, pp 1715–1730 | Cite as

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

  • Lin LiuEmail author
  • Shang-Ping Xie
  • Xiao-Tong Zheng
  • Tim Li
  • Yan Du
  • Gang Huang
  • Wei-Dong Yu
Article

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.

Keywords

Indian Ocean Dipole zonal model CMIP3 CMIP5 Interannual variability Bjerknes feedback Thermodynamic feedback 

Notes

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).

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Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Lin Liu
    • 1
    Email author
  • Shang-Ping Xie
    • 2
    • 3
  • Xiao-Tong Zheng
    • 3
  • Tim Li
    • 4
  • Yan Du
    • 5
  • Gang Huang
    • 6
    • 7
  • Wei-Dong Yu
    • 1
  1. 1.Center for Ocean and Climate ResearchFirst Institute of Oceanography, State Oceanic Administration (SOA)QingdaoChina
  2. 2.Scripps Institution of OceanographyUniversity of CaliforniaSan Diego, La JollaUSA
  3. 3.Physical Oceanography LaboratoryOcean University of ChinaQingdaoChina
  4. 4.International Pacific Research Center and Department of MeteorologyUniversity of Hawaii at ManoaHonoluluUSA
  5. 5.State Key Laboratory of Tropical Oceanography, South China Sea Institute of OceanologyChinese Academy of SciencesGuangzhouChina
  6. 6.Key Laboratory of Regional Climate-Environment Research for Temperate East Asia, Institute of Atmospheric PhysicsChinese Academy of SciencesBeijingChina
  7. 7.Collaborative Innovation Center on Forecast and Evaluation of Meteorological DisastersNanjing University of Information Science and TechnologyNanjingChina

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