Abstract
Abstract. Successful simulation of cloud-aerosol interactions (indirect aerosol effects) in climate models requires relating grid-scale aerosol, dynamic, and thermodynamic fields to small-scale processes like aerosol activation. A turbulence and cloud parameterization, based on multi-variate probability density functions of sub-grid vertical velocity, temperature, and moisture, has been extended to treat aerosol activation. Multi-variate probability density functions with dynamics (MVD PDFs) offer a solution to the problem of the gap between the resolution of climate models and the scales relevant for aerosol activation and a means to overcome the limitations of diagnostic estimates of cloud droplet number concentration based only on aerosol concentration. Incorporated into the single-column version of GFDL AM3, the MVD PDFs successfully simulate cloud properties including precipitation for cumulus, stratocumulus, and cumulus-under-stratocumulus. The extension to treat aerosol activation predicts droplet number concentrations in good agreement with large eddy simulations (LES). The droplet number concentrations from the MVD PDFs match LES results more closely than diagnostic relationships between aerosol concentration and droplet concentration. In the single-column model simulations, as aerosol concentration increases, droplet concentration increases, precipitation decreases, but liquid water path can increase or decrease.
Highlights
The diversity of climate sensitivity among current model projections is explained in part by low-level clouds, and models probably fail to include processes which could introduce further uncertainty (Webb et al, 2006; Forster et al, 2007)
Aerosol activation depends on local super-saturation and vertical velocity at scales far below those resolved in climate models with horizontal spacing of ∼ 100 km
This paper evaluates the performance of the MVD probability density functions (PDFs) in the framework of the single column model (SCM) of GFDL atmospheric general circulation model (AM3) (Donner et al, 2010), because the SCM configuration is an efficient framework for implementing and performing the initial evaluations of new physical packages and avoids the complexity of a full general circulation model (GCM) (Randall et al, 1996)
Summary
The diversity of climate sensitivity among current model projections is explained in part by low-level clouds, and models probably fail to include processes which could introduce further uncertainty (Webb et al, 2006; Forster et al, 2007). Due to the significant sub-grid variability in vertical velocity (Leary and Houze, 1980; Donner et al, 1999; Stevens et al, 2005) and the nonlinear dependence of aerosol activation on vertical velocity, using average fields at the coarse resolution of climate models for aerosol activation is highly problematic In face of these conceptual difficulties, we have adopted a multi-variate probability density function approach to represent the sub-grid variations in vertical velocity, liquid water potential temperature, and total water content in a model grid box (Golaz et al, 2002a, b, 2007; Larson et al, 2002; Larson and Golaz, 2005).
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