Articles | Volume 8, issue 1
Development and technical paper
06 Jan 2015
Development and technical paper |  | 06 Jan 2015

Parameterizing deep convection using the assumed probability density function method

R. L. Storer, B. M. Griffin, J. Höft, J. K. Weber, E. Raut, V. E. Larson, M. Wang, and P. J. Rasch


Interactive discussion

Status: closed
Status: closed
AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
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Peer-review completion

AR: Author's response | RR: Referee report | ED: Editor decision
AR by Rachel Storer on behalf of the Authors (30 Oct 2014)  Author's response   Manuscript 
ED: Publish as is (21 Nov 2014) by Richard Neale
AR by Rachel Storer on behalf of the Authors (29 Nov 2014)
Short summary
Representing clouds in climate models is a challenging problem. It is particularly difficult to represent deep convective clouds and, historically, deep convective parameterization is separate from the representation of other cloud types. Here we use a single-column cloud model to simulate three deep convective cases, and two shallow cloud cases. The results look reasonable, demonstrating that it may be possible to use one parameterization within a climate model for all cloud types.