The Regional Climate Model RegCM4 (Giorgi et al., 2012) treats nonconvective clouds and precipitation following the Subgrid Explicit SUBEX param- eterization (Pal et al., 2000). This scheme includes a simple representation for the formation of raindrops and solves diagnostically the precipitation: rain forms when the cloud water content exceeds the autoconversion threshold, that is an increasing function of the temperature and assumes different values over the land and over the ocean to account for the difference in number of the cloud condensation nuclei over continental and oceanic regions. The SUBEX scheme does not account for the presence of clouds ice, and the fraction of ice is diagnosed as a function of temperature in the radiation scheme. Due to the increasing emphasis on cloud representations in the climate community and the forthcoming increasing resolution due to the inclusion, in the close future, of a non-hydrostatic compressible core, the treatment of the ice microphysics and a prognostic representation of the precipitation is required in RegCM4. This thesis presents the new parameterization for stratiform cloud microphysics and precipitation implemented in RegCM4. The approach of the new parameterization is based on an implicit numerical framework recently developed and implemented into the ECMWF operational forecasting model (Tiedtke, 1993). The new parameterization solves 5 prognostic equations for the water vapour, the liquid water, the rain, the ice and the snow mixing ratios. It allows a proper treatment of mixed-phase clouds and a more physically realistic representation of the precipitation as it is no more an instantaneous response to the microphysical processes occurring in clouds and is subjected to the horizontal advection. A first discussion of the results contains an evaluation of the vertical distributions of the main microphysical quantities, such as the liquid and ice water mixing ratios and the relative fractions. It also presents a series of sensitivity tests to understand how the moisture and radiation quantities respond to the variation of the microphysical parameters used in the scheme, such as the fall speeds of the falling categories, the autoconversion scheme and the evaporation coefficient. Cloud properties are afterwards evaluated through the implementation for RegCM4 of the new cloud evaluation COSP tool (Bodas-Salcedo et al., 2011), developed by the Cloud Feedback Model In- tercomparison Project (CFMIP), that facilitates the comparison of simulated clouds with observations from passive and active remote sensing by diagnosing from model outputs the quantities that would be observed from satellites if they were flying above an atmosphere similar to that predicted by the model. Different hypothesis are presented to explain the reasons for RegCM4 biases in representing different types of clouds over the tropical band and new prospectives for the future investigations designed to answer to the open questions are outlined.
