This collaborative project among North Carolina State University, Pacific Northwest National Laboratory, and Scripps Institution of Oceanography, University of California San Diego addresses the critical need for an accurate representation of aerosol indirect effect in climate and Earth system models.

One of the most important and least understood climate feedbacks that controls climate response to increasing CO₂ forcing is related to aerosols and their influence on the energy and water cycles in the Earth systems. This project addresses critical gaps in representations of aerosol properties and processes, and their indirect effects on cloud and precipitation in climate models, with an emphasis on deep convective clouds and the associated anvils and cirrus clouds. Our overall objective is to reduce uncertainties associated with indirect effect of aerosols by improving parameterizations for aerosol-cloud-precipitation feedbacks in regional and global climate models and conducting high resolution regional climate simulations to estimate aerosol indirect effects. This research will produce improved treatments of climatically-relevant aerosols and fully link aerosol, cloud microphysics, and cumulus convection to better represent aerosol-cloud-precipitation interactions and their influence on the radiative balance and hydrological cycle in climate models. Our specific tasks are as follows:

1. Improve parameterizations for formation and early growth of new particles as well as model treatments for secondary organic aerosol formation and dust effects.
2. Improve and evaluate the Zhang and McFarlane convective parameterization with consideration of aerosol and cloud microphysical effects on convection and precipitation as well as ice nucleation schemes that link ice formation to aerosols to better represent the influence of aerosols on clouds and precipitation.
3. Conduct and evaluate coupled aerosol-climate simulations using WRF/Chem over East China at 4–12 km horizontal resolution and analyze aerosol indirect effects under different cloud regimes and their interannual variability.