Journal of Meteorological Research

, Volume 33, Issue 1, pp 80–88 | Cite as

An Assessment of ENSO Stability in CAMS Climate System Model Simulations

  • Lijuan Hua
  • Lin ChenEmail author
  • Xinyao Rong
  • Jian Li
  • Guo Zhang
  • Lu Wang
Special Collection on CAMS-CSM


We present an overview of the El Niño–Southern Oscillation (ENSO) stability simulation using the Chinese Academy of Meteorological Sciences climate system model (CAMS-CSM). The ENSO stability was quantified based on the Bjerknes (BJ) stability index. Generally speaking, CAMS-CSM has the capacity of reasonably representing the BJ index and ENSO-related air–sea feedback processes. The major simulation biases exist in the underestimated thermodynamic damping and thermocline feedbacks. Further diagnostic analysis reveals that the underestimated thermodynamic feedback is due to the underestimation of the shortwave radiation feedback, which arises from the cold bias in mean sea surface temperature (SST) over central–eastern equatorial Pacific (CEEP). The underestimated thermocline feedback is attributed to the weakened mean upwelling and weakened wind–SST feedback (μa) in the model simulation compared to observation. We found that the weakened μa is also due to the cold mean SST over the CEEP. The study highlights the essential role of reasonably representing the climatological mean state in ENSO simulations.

Key words

coupled general circulation model (CGCM) Bjerknes (BJ) stability index air–sea feedback 


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An Assessment of ENSO Stability in CAMS Climate System Model Simulations


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Copyright information

© The Chinese Meteorological Society and Springer-Verlag GmbH Germany, part of Springer Nature 2019

Authors and Affiliations

  • Lijuan Hua
    • 1
  • Lin Chen
    • 3
    • 2
    Email author
  • Xinyao Rong
    • 1
  • Jian Li
    • 1
  • Guo Zhang
    • 1
  • Lu Wang
    • 3
    • 2
  1. 1.State Key Laboratory of Severe Weather, Chinese Academy of Meteorological SciencesChina Meteorological AdministrationBeijingChina
  2. 2.Key Laboratory of Meteorological Disaster, Ministry of Education/Joint International Research Laboratory of Climate and Environmental Change/Collaborative Innovation Center on Forecast and Evaluation of Meteorological DisastersNanjing University of Information Science & TechnologyNanjingChina
  3. 3.State Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics, Institute of Atmospheric PhysicsChinese Academy of SciencesBeijingChina

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