Interactive comment on “Introduction of prognostic rain in ECHAM5: design and Single Column Model simulations” by R. Posselt and U. Lohmann

Introduction of prognostic rain in ECHAM5: design and Single Column Model simulations

Prognostic equations for the rain mass mixing ratio and the rain drop number concentration are introduced into the large-scale cloud microphysics parameterization of the ECHAM5 general circulation model (ECHAM5-RAIN). For this a rain flux from one level to the next with the appropriate fall speed is introduced. This maintains rain water in 5 the atmosphere to be available for the next time step...

Introduction of prognostic rain in ECHAM5

Prognostic precipitation in the ECHAM5-HAM

Introduction Conclusions References Tables Figures

Influence of Giant CCN on warm rain processes in the ECHAM5 GCM

Increased Cloud Condensation Nuclei (CCN) load due to anthropogenic activity might lead to non-precipitating clouds because the cloud drops become smaller (for a constant liquid water content) and, therefore, less efficient in rain formation (aerosol indirect effect). Adding giant CCN (GCCN) into such a cloud can initiate precipitation (namely, drizzle) and, therefore, might counteract the aero...

Prognostic precipitation with three liquid water classes in the ECHAM5–HAM GCM

A new parameterization with three prognostic liquid water classes was implemented into the general circulation model (GCM) ECHAM5 with the aerosol module HAM in order to improve the global representation of rain formation in marine stratiform clouds. The additionally introduced drizzle class improves the physical representation of the droplet spectrum and, more importantly, improves the microph...