Satellite-Based Diagnostics of Precipitation Process in Mixed-Phase Clouds: Extension From Warm Rain Process Statistics

This study proposes a methodology for analyzing the precipitation process in mixed-phase clouds using multisensor satellite data, including radar, lidar, and imager. By leveraging a specific multivariate statistic, we elucidate the vertical microphysical structures of mixed-phase clouds and their transitions associated with cloud particle growth and phase change. Expanding upon previous warm rain process diagnostics, we integrate cloud thermodynamic phase information from lidar and imager, representing the phase near the cloud top and column, respectively, to classify the vertical microphysical structures obtained from radar. Our global composite analysis reveals a systematic transition from non-precipitating to precipitating characteristics with increasing ice phase fraction of the cloud column, rather than near the cloud top, and increasing cloud-top particle size. These findings offer valuable observational references for evaluating numerical models in precipitation physics.