Numerical Experiments to Analyze Cloud Microphysical Processes Depicted in Vertical Profiles of Radar Reflectivity of Warm Clouds

Information about microphysical processes in warm clouds embedded in satellite measurements must be untangled to be used to improve the parameterization in global models. In this paper, the relationship between vertical profiles of horizontally averaged radar reflectivity Z(m) and cloud optical depth from cloud top (d) was investigated using a hybrid cloud microphysical model and a forward simulator of satellite measurements. The particle size distributions were explicitly simulated using a bin method in a kinematic framework. In contrast to previous interpretations of satellite-observed data, three patterns of the Z(m)-(d) relationship related to microphysical processes were identified. The first is related to the autoconversion process, which causes Z(m) to increase upward with decreasing (d). Before the initiation of surface precipitation, Z(m) increases downward with (d) in the upper part of the cloud, which is considered to be a second characteristic pattern and is caused by the accretion process. The appearance of this pattern corresponds to the initiation of efficient production of raindrops in the cloud. The third is related to the sedimentation and evaporation of raindrops causing Z(m) to decrease downward with (d) in the lower part of the Z(m)-(d) relationship. It was also found that the bulk collection efficiency has a partially positive correlation with the slope factor of Z(m) with regard to (d) and that the slope factor could be a gross measure of the collection efficiency in partial cases. This study also shows that differences in the aerosol concentration modulate the duration of these three patterns and change the slope factor of Z(m).