Assessment of ice cloud modeling capabilities for the irregularly shaped Voronoi models in climate simulations with CAM5

Abstract. Climate models and satellite remote sensing applications require accurate descriptions of ice cloud optical and radiative properties through parameterization of their scattering properties. While abundant irregularly shaped ice particle habits present a challenge for modelling ice clouds. An irregularly shaped ice particle habit (Voronoi model) has been developed and recently suggested to be effective in inferring the microphysical and radiative properties of ice clouds from Himawari-8 and GCOM-C satellite measurements. As a continuation of previous work by Letu et al. (2016), in this study, we develop a broadband ice cloud scheme based on the Voronoi model through parameterization for use in the Community Atmosphere Model, Version 5 (CAM5). With single scattering properties of Voronoi model, ice cloud bulk scattering properties are integrate over particle size distributions of 11 field campaigns and are parameterized over particle effective diameter. The new ice cloud scheme is compared with four ice cloud schemes (the Yi, Mitchell, Baum-yang and Fu scheme), and is evaluated through the General circulation model version of the Rapid Radiative Transfer Model (RRTMG), and simulations of the top of atmosphere (TOA) shortwave and longwave cloud forcing (SWCF and LWCF) in CAM5. The Clouds and the Earth's Radiant Energy System (CERES) satellite data was selected as validation data. Results indicated that the Voronoi scheme can minimize differences between the satellite-based measurements and CAM5 simulations of global TOA SWCF compared to other four schemes, but performance is not significant for TOA LWCF. For tropical ice clouds, Voronoi scheme has advantages of ice cloud modelling capabilities for shortwave (SW) and longwave (LW) spectrum over other four schemes. In general, it is found that the Voronoi model has advantages over conventional ice cloud schemes and is sufficient for ice cloud modelling in climate simulations with CAM5.