Our project aims at reducing uncertainties associated with aerosol indirect effect via acting as cloud condensation nuclei (CCN) and ice nuclei (IN) to better represent aerosol-cloud-precipitation-climate feedbacks in regional and global climate/Earth system models. The model we used is the coupled Weather Research and Forecasting model with chemistry (WRF/Chem) with the physics package from the National Center for Atmospheric Research's Community Atmospheric model (CAM5) (i.e., WRF-CAM5). WRF-CAM5 was recently developed to explore the behavior of CAM5 physics for high-resolution global and regional modeling. In this work, WRF-CAM5 is further developed by parameterizing aerosol effects on deep convection (e.g., deep convective clouds and their stratiform and anvils), improving ice nucleation parameterizations (e.g., with varying degrees of complexity for mixed-phase and ice clouds), improving aerosol microphysical treatments (e.g., new particle formation through nucleation and dust dynamics and chemistry), and accounting for activation of various types of aerosols by all types of clouds (e.g., mineral dust and insoluble black carbon to serve as CCN and IN). The simulation domain is over East Asia, which provides an ideal testbed to study aerosol feedbacks into climate via direct and indirect effects because of high anthropogenic emissions and special climatology that favor natural emissions of biogenic organic compounds and mineral dust and long range transport of pollutants. We have applied the improved WRF-CAM5 over East Asia at a 36-km grid resolution for 6 full years (2001, 2005, 2006, 2008, 2010, and 2011) to examine the impacts of aerosol on deep convective clouds and precipitation, differences in simulated cloud variables among various mixed-phase heterogeneous ice nucleation parameterizations, and sensitivity of the model predictions to various treatments for dust emissions, aerosol microphysics, and aerosol activation parameterizations. We are also performing nested simulations at 12- and 4-km over eastern China to study chemistry-climate interactions at a finer scale. Our results show that WRF-CAM5 with the parameterization of aerosol impacts on deep convective clouds improves precipitation pattern and rate, compared with the original model without the effects included. The predicted cloud properties are sensitive to different mixed-phase heterogeneous ice nucleation parameterizations. Model predictions are sensitive to treatments for dust emissions, new particle formation, and aerosol activation, which affect aerosol direct/indirect effects via affecting aerosol number and mass concentrations, and chemical and optical properties. The evaluation of multi-year WRF-CAM5 simulations shows good skills in capturing meteorological and chemical observations.