Abstract

Prognostic precipitation is added to a cloud microphysical scheme for global climate models. Results indicate very similar performance to other commonly used mesoscale schemes in an offline driver for idealized warm rain cases, better than the previous version of the global model microphysics sch... Show morePrognostic precipitation is added to a cloud microphysical scheme for global climate models. Results indicate very similar performance to other commonly used mesoscale schemes in an offline driver for idealized warm rain cases, better than the previous version of the global model microphysics scheme with diagnostic precipitation. In the mixed phase regime, there is significantly more water and less ice, which may address a common bias seen with the scheme in climate simulations in the Arctic. For steady forcing cases, the scheme has limited sensitivity to time step out to the ~15-min time steps typical of global models. The scheme is similar to other schemes with moderate sensitivity to vertical resolution. The limited time step sensitivity bodes well for use of the scheme in multiscale models from the mesoscale to the large scale. The scheme is sensitive to idealized perturbations of cloud drop and crystal number. Precipitation decreases and condensate increases with increasing drop number, indicating substantial decreases in precipitation efficiency. The sensitivity is less than with the previous version of the scheme for low drop number concentrations (Nc < 100 cm⁻³). Ice condensate increases with ice number, with large decreases in liquid condensate as well for a mixed phase case. As expected with prognostic precipitation, accretion is stronger than with diagnostic precipitation and the accretion to autoconversion ratio increases faster with liquid water path (LWP), in better agreement with idealized models and earlier studies than the previous version. Show less