Implementing a warm cloud microphysics parameterization for convective clouds in NCAR CESM

Most of cumulus convection schemes use simple empirical approaches to convert cloud liquid mass to rain water or cloud ice to snow e.g. using a constant autoconversion rate and dividing cloud liquid mass into cloud water and ice as function of air temperature (e.g. Zhang and McFarlane scheme in NCAR CAM model). There are few studies trying to use cloud microphysical schemes to better simulate such precipitation processes in the convective schemes of global models (e.g. Lohmann [2008] and Song, Zhang, and Li [2012]). A two-moment warm cloud parameterization (i.e. Chen and Liu [2004]) is implemented into the deep convection scheme of CAM5.2 of CESM model for treatment of conversion of cloud liquid water to rain water. Short-term AMIP type global simulations are conducted to evaluate the possible impacts from the modification of this physical parameterization. Simulated results are further compared to observational results from AMWG diagnostic package and CloudSAT data sets. Several sensitivity tests regarding to changes in cloud top droplet concentration (here as a rough testing for aerosol indirect effects) and changes in detrained cloud size of convective cloud ice are also carried out to understand their possible impacts on the cloud and precipitation simulations.