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One of the greatest sources of uncertainty in simulations of climate and climate change is the influence of aerosols on the optical properties of clouds. The root of this influence is the droplet nucleation process, which involves the spontaneous growth of aerosol into cloud droplets at cloud edges, during the early stages of cloud formation, and in some cases within the interior of mature clouds. Numerical models of droplet nucleation represent much of the complexity of the process, but at a computational cost that limits their application to simulations of hours or days. Physically-based parameterizations of droplet nucleation are designed to quickly estimate the number nucleated as a function of the primary controlling parameters: the aerosol number size distribution, hygroscopicity and cooling rate. Here we compare and contrast the key assumptions used in developing each of the most popular parameterizations and compare their performances under a variety of conditions. We find that the more complex parameterizations perform well under a wider variety of nucleation conditions, but all parameterizations perform well under the most common conditions. We then discuss the various applications of the parameterizations to cloudresolving, regional and global models to study aerosol effects on clouds at a wide range of spatial and temporal scales. We compare estimates of anthropogenic aerosol indirect effects using two different parameterizations applied to the same global climate model, and find that the estimates of indirect effects differ by only 10%. We conclude with a summary of the outstanding challenges remaining for further development and application.




An edited version of this paper was published by AGU. Copyright 2011 American Geophysical Union.

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