Articles | Volume 8, issue 12
Geosci. Model Dev., 8, 3801–3821, 2015
https://doi.org/10.5194/gmd-8-3801-2015
Geosci. Model Dev., 8, 3801–3821, 2015
https://doi.org/10.5194/gmd-8-3801-2015

Development and technical paper 01 Dec 2015

Development and technical paper | 01 Dec 2015

A unified parameterization of clouds and turbulence using CLUBB and subcolumns in the Community Atmosphere Model

K. Thayer-Calder1,2, A. Gettelman1, C. Craig1, S. Goldhaber1, P. A. Bogenschutz1, C.-C. Chen1, H. Morrison1, J. Höft2, E. Raut2, B. M. Griffin2, J. K. Weber2, V. E. Larson2, M. C. Wyant3, M. Wang4,5,6, Z. Guo6, and S. J. Ghan6 K. Thayer-Calder et al.
  • 1National Center for Atmospheric Research, Boulder, CO, USA
  • 2University of Wisconsin – Milwaukee, Department of Mathematical Sciences, Milwaukee, WI, USA
  • 3University of Washington, Department of Atmospheric Sciences, Seattle, WA, USA
  • 4Institute for Climate and Global Change Research and School of Atmospheric Sciences, Nanjing University, Nanjing, 210093, China
  • 5Collaborative Innovation Center of Climate Change, Jiangsu Province, 210093, China
  • 6Pacific Northwest National Laboratory, Richland, WA, USA

Abstract. Most global climate models parameterize separate cloud types using separate parameterizations. This approach has several disadvantages, including obscure interactions between parameterizations and inaccurate triggering of cumulus parameterizations.

Alternatively, a unified cloud parameterization uses one equation set to represent all cloud types. Such cloud types include stratiform liquid and ice cloud, shallow convective cloud, and deep convective cloud. Vital to the success of a unified parameterization is a general interface between clouds and microphysics. One such interface involves drawing Monte Carlo samples of subgrid variability of temperature, water vapor, cloud liquid, and cloud ice, and feeding the sample points into a microphysics scheme.

This study evaluates a unified cloud parameterization and a Monte Carlo microphysics interface that has been implemented in the Community Atmosphere Model (CAM) version 5.3. Model computational expense is estimated, and sensitivity to the number of subcolumns is investigated. Results describing the mean climate and tropical variability from global simulations are presented. The new model shows a degradation in precipitation skill but improvements in shortwave cloud forcing, liquid water path, long-wave cloud forcing, precipitable water, and tropical wave simulation.

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Short summary
This study evaluates a unified cloud parameterization and a Monte Carlo microphysics interface that is implemented in CAM v5.3. We show mean climate and tropical variability results from global simulations. The model has a degradation in precipitation skill but improvements in shortwave cloud forcing, liquid water path, long-wave cloud forcing, precipitable water, and tropical wave simulation. We also show estimation of computational expense and sensitivity to number of subcolumns.