Journal of Meteorological Research

, Volume 33, Issue 5, pp 949–959 | Cite as

Convectively Coupled Equatorial Waves Simulated by CAMS-CSM

  • Lu WangEmail author
  • Tianjun Zhou
  • Jian Li
  • Xinyao Rong
  • Haoming Chen
  • Yufei Xin
  • Jingzhi Su
Special Collection on CAMS-CSM


The Chinese Academy of Meteorological Sciences developed a Climate System Model (CAMS-CSM) to participate in the upcoming Coupled Model Intercomparison Project phase 6 (CMIP6). In this study, we assessed the model performance in simulating the convectively coupled equatorial waves (CCEWs) by comparing the daily output of precipitation from a 23-yr coupled run with the observational precipitation data from Global Precipitation Climatology Project (GPCP). Four dominant modes of CCEWs including the Kelvin, equatorial Rossby (ER), mixed Rossby-gravity (MRG), tropical depression-type (TD-type) waves, and their annual mean and seasonal cycle characteristics are investigated respectively. It is found that the space-time spectrum characteristics of each wave mode represented by tropical averaged precipitation could be very well simulated by CAMS-CSM, including the magnitudes and the equivalent depths. The zonal distribution of wave associated precipitation is also well simulated, with the maximum centers over the Indian Ocean and the Pacific Ocean. However, the meridional distribution of the wave activities is poorly simulated, with the maximum centers shifted from the Northern Hemisphere to the Southern Hemisphere, especially the Kelvin, MRG, and TD waves. The seasonal cycle of each wave mode is generally captured by the model, but their amplitudes over the Southern Hemisphere during boreal winter are grossly overestimated. The reason for the excessive wave activity over the southern Pacific Ocean in the simulation is discussed.

Key words

CAMS-CSM convectively coupled equatorial waves precipitation seasonal cycle model evaluation 


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We thank the anonymous reviewers and the editor for their constructive comments, which significantly improved this paper.


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Copyright information

© The Chinese Meteorological Society and Springer-Verlag Berlin Heidelberg 2019

Authors and Affiliations

  • Lu Wang
    • 1
    • 2
    Email author
  • Tianjun Zhou
    • 2
  • Jian Li
    • 3
  • Xinyao Rong
    • 3
  • Haoming Chen
    • 3
  • Yufei Xin
    • 3
  • Jingzhi Su
    • 3
  1. 1.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
  2. 2.State Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics, Institute of Atmospheric PhysicsChinese Academy of SciencesBeijingChina
  3. 3.State Key Laboratory of Severe WeatherChinese Academy of Meteorological Sciences, China Meteorological AdministrationBeijingChina

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