PNNL

Abstract

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. Droplet nucleation involves the simultaneous condensational growth of an aerosol population until maximum supersaturation is achieved and a subset of the particles are large enough to grow spontaneously into cloud droplets. Numerical models of droplet nucleation are capable of representing much of the complexity of the process, but at a computational cost that limits their application to simulations of hours or days. Parameterizations of droplet nucleation are designed to quickly estimate the number nucleated as a function of the primary controlling parameters: the cooling rate and the size distribution of aerosol number and hygroscopicity. Here we compare and contrast the key assumptions used in developing each of the most popular parameterizations and compare the performance of each under a variety of conditions. In general we find that the more complex parameterizations perform well under a wider variety of conditions, but all parameterizations perform well under the most common conditions. We then discuss the various applications of the parameterizations to cloud-resolving, regional and global models to study aerosol effects on clouds at a wide range of spatial and temporal scales. We conclude with a summary of the outstanding challenges remaining for further development.