U.S. Department of Energy Office of Biological and Environmental Research

BER Research Highlights


Improving Convection Precipitation in the Community Atmosphere Model
Published: January 25, 2013
Posted: March 26, 2013

Scientists working to improve atmospheric climate simulations have few systematic methods to determine what aspect of the atmosphere is responsible for poor simulations, such as rainfall from particular cloud types. A U.S. Department of Energy team from Pacific Northwest National Laboratory and Scripps Institution of Oceanography used an uncertainty quantification (UQ) technique to improve convective precipitation in the Community Atmosphere Model version 5 (CAM5). In this model, the simulated precipitation looks reasonable but the partitioning of rain between convective and stratiform clouds is very different from observation-based estimates. The team examined the sensitivity of precipitation and circulation to key parameters in the deep convection scheme in CAM5, using a statistical algorithm that can progressively converge to optimal parameter values. They then evaluated the impact of improved deep convection on the global circulation and climate, including extreme rain events. Their results showed that the simulated convective precipitation is most sensitive to certain model parameters related to convective timescales, air mass entrainment rate, and the maximum permitted cloud downdraft mass flux fraction. Using the optimal parameters constrained by observations from the Tropical Rainfall Measuring Satellite Mission, the model remarkably improved the simulation of the convective to stratiform precipitation ratio and rain rates. As the optimal parameters are used, they also found improvement in aspects of the atmospheric circulation and simulated climate extremes. These new UQ statistical methods will help scientists converge more quickly toward improved model parameters.

Reference: Yang, B., Y. Qian, G. Lin, L. R. Leung, P. J. Rasch, G. J. Zhang, S. A. McFarlane, C. Zhao, Y. Zhang, H. Wang, M. Wang, and X. Liu. 2013. “Uncertainty Quantification and Parameter Tuning in the CAM5 Zhang-McFarlane Convection Scheme and Impact of Improved Convection on the Global Circulation and Climate,” Journal of Geophysical Research-Atmospheres 118, 395–415. DOI: 10.1029/2012JD018213. (Reference link)

Contact: Dorothy Koch, SC-23.1, (301) 903-0105
Topic Areas:

  • Research Area: Earth and Environmental Systems Modeling
  • Research Area: Atmospheric System Research

Division: SC-23.1 Climate and Environmental Sciences Division, BER

 

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