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Journal of Meteorological Research

, Volume 33, Issue 4, pp 651–665 | Cite as

Performance of CAMS-CSM in Simulating the Shortwave Cloud Radiative Effect over Global Stratus Cloud Regions: Baseline Evaluation and Sensitivity Test

  • Yihui Zhou
  • Yi ZhangEmail author
  • Xinyao Rong
  • Jian Li
  • Rucong Yu
Special Collectionon CAMS-CSM
  • 5 Downloads

Abstract

The ability of climate models to correctly reproduce clouds and the radiative effects of clouds is vitally important in climate simulations and projections. In this study, simulations of the shortwave cloud radiative effect (SWCRE) using the Chinese Academy of Meteorological Sciences Climate System Model (CAMS-CSM) are evaluated. The relationships between SWCRE and dynamic-thermodynamic regimes are examined to understand whether the model can simulate realistic processes that are responsible for the generation and maintenance of stratus clouds. Over eastern China, CAMS-CSM well simulates the SWCRE climatological state and stratus cloud distribution. The model captures the strong dependence of SWCRE on the dynamic conditions. Over the marine boundary layer regions, the simulated SWCRE magnitude is weaker than that in the observations due to the lack of low-level stratus clouds in the model. The model fails to simulate the close relationship between SWCRE and local stability over these regions. A sensitivity numerical experiment using a specifically designed parameterization scheme for the stratocumulus cloud cover confirms this assertion. Parameterization schemes that directly depict the relationship between the stratus cloud amount and stability are beneficial for improving the model performance.

Key words

Chinese Academy of Meteorological Sciences Climate System Model (CAMS-CSM) shortwave cloud radiative effect (SWCRE) stratus cloud model errors 

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Notes

Acknowledgments

The constructive comments from two anonymous reviewers have greatly helped improve the manuscript.

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Copyright information

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

Authors and Affiliations

  • Yihui Zhou
    • 1
    • 2
  • Yi Zhang
    • 3
    Email author
  • Xinyao Rong
    • 3
  • Jian Li
    • 3
  • Rucong Yu
    • 3
  1. 1.State Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics, Institute of Atmospheric PhysicsChinese Academy of SciencesBeijingChina
  2. 2.University of Chinese Academy of SciencesBeijingChina
  3. 3.State Key Laboratory of Severe Weather, Chinese Academy of Meteorological SciencesChina Meteorological AdministrationBeijingChina

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