Impact of heterogeneous particle distributions on secondary ice production through the rime-splintering process in isolated convective clouds

The rime-splintering (RS) process, which is one of the most important secondary ice production mechanisms, plays a crucial role in regulating ice crystal number concentrations and precipitation formation in convective clouds. The initiation and efficiency of the RS process are modulated by the spatial distributions of liquid and ice particles, which are highly heterogeneous. However, numerical models are developed based on the idealized assumption of homogeneous liquid-ice mixing in a given volume, which causes large uncertainties in modeling ice production in convective clouds. Based on in-situ measurements from The Convective Precipitation Experiment (COPE), this study investigates how the heterogeneous particle distribution affects the RS process by defining an impact factor F HM . The liquid-ice mixing homogeneity (χ) in a given cloud is quantified using information-theoretic entropy, and the spread of riming rate (Δ R rim ) is quantified using the maximum R rim minus the minimum one. The results show that F HM increases with χ at a given temperature, indicating that a greater liquid-ice mixing homogeneity enhances the occurrence of RS process. Since the RS process is non-linear, in most of the observed clouds F HM exceeds 1, and increases with increasing Δ R rim , suggesting the heterogeneous particle distribution enhances the mean ice production rate compared to that assuming homogeneous particle distribution. Among the various meteorological factors that influence χ and Δ R rim , vertical wind shear (WS) and condensed water content (CWC) show the strongest yet opposing correlations with χ, while temperature (T) and WS contribute the most to Δ R rim . These insights provide a new perspective for advancing subgrid-scale parameterization of the RS process.