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www.geosci-model-dev-discuss.net/3/541/2010/
doi:10.5194/gmdd-3-541-2010
© Author(s) 2010. This work is distributed
under the Creative Commons Attribution 3.0 License.
A dynamic probability density function treatment of cloud mass and number concentrations for low level clouds in GFDL SCM/GCM
1UCAR Visiting Scientist Programs, NOAA/Geophysical Fluid Dynamics Laboratory, Princeton, New Jersey, USA
2NOAA/Geophysical Fluid Dynamics Laboratory, Princeton, New Jersey, USA
3Atmospheric Science Group, Department of Mathematical Sciences, University of Wisconsin-Milwaukee, Milwaukee, Wisconsin, USA
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 multivariate probability density functions (PDFs) of sub-grid vertical velocity, temperature, and moisture, has been extended to treat aerosol activation. This dynamics-PDF approach offers a solution to the problem of the scale 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 a single-column model for GFDL AM3, the dynamics-PDF parameterization successfully simulates cloud fraction and water content for shallow cumulus, stratocumulus, and cumulus-under-stratocumulus regimes. The extension to treat aerosol activation predicts droplet number concentrations in good agreement with large eddy simulation (LES). The dynamics-PDF droplet number concentrations match LES results more closely than state-of-the-science diagnostic relationships between aerosol concentration and droplet number concentration.
Discussion Paper (PDF, 7154 KB) Interactive Discussion (Closed, 4 Comments) Final Revised Paper (GMD)
Notice on Discussion StatusCitation: Guo, H., Golaz, J.-C., Donner, L. J., Larson, V. E., Schanen, D. P., and Griffin, B. M.: A dynamic probability density function treatment of cloud mass and number concentrations for low level clouds in GFDL SCM/GCM, Geosci. Model Dev. Discuss., 3, 541-568, doi:10.5194/gmdd-3-541-2010, 2010. Bibtex EndNote Reference Manager XML
