Articles | Volume 11, issue 6
https://doi.org/10.5194/acp-11-2729-2011
https://doi.org/10.5194/acp-11-2729-2011
Research article
 | 
23 Mar 2011
Research article |  | 23 Mar 2011

Evaluating the effects of microphysical complexity in idealised simulations of trade wind cumulus using the Factorial Method

C. Dearden, P. J. Connolly, T. W. Choularton, and P. R. Field

Abstract. The effect of microphysical and environmental factors on the development of precipitation in warm idealised cloud is explored using a kinematic modelling framework. A simple one-dimensional column model is used to drive a suite of microphysics schemes including a flexible multi-moment bulk scheme (including both single and dual moment cloud liquid water) and a state-of-the-art bin-resolved scheme with explicit treatments of liquid and aerosol. The Factorial Method is employed to quantify and compare the sensitivities of each scheme under a set of controlled conditions, in order to isolate the effect of additional microphysical complexity in terms of the impact on surface precipitation. At relatively low updraught speeds, the sensitivity of the bulk schemes was found to depend on the assumptions made with regards the treatment of droplet activation. It was possible to achieve a much closer agreement between the single and dual moment bulk schemes by tuning the specified droplet number concentration in the single moment scheme, suggesting that a diagnostic representation of droplet number may be an acceptable alternative to the more expensive prognostic option. However the effect of changes in CCN concentration were found to produce a relatively stronger effect on precipitation in the bulk schemes compared to the bin scheme; this is believed to be a consequence of differences in the treatment of drop growth by collision and coalescence. Collectively, these results demonstrate the usefulness of the Factorial Method as a model development tool for quantitatively comparing and contrasting the behaviour of microphysics schemes of differing levels of complexity within a specified parameter space.

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