1. How do warm-rain and ice crystal processes compete to influence surface precipitation in each mesoscale convective system? 
2. What factors (e.g., cloud base height and solute aerosol conditions) contribute to the prevalence of warm-rain or ice-crystal processes in total surface precipitation? 
3. What is the importance of using a microphysically advanced cloud-resolving model in studying precipitation processes?

         A rigorous treatment of the various ice-crystal processes is implemented in the aerosol-cloud (AC) model. Here, we devised a sophisticated tracer-tagging technique to investigate precipitation formation pathways in a cloud-system resolving model; these pathways are summarized in Figure 1 (see article). Figure 1 illustrates qualitatively how these interrelated microphysical processes control precipitation's warm-rain (red line) and ice crystal (blue line) processes. Contributions from warm and cold precipitation to the total surface precipitation in nature are determined by several interactions between hydrometeors by processes, such as coalescence and riming. Some of these are temperature-dependent. For instance, the melting of snow and cold graupel from the growth of ice crystals (see article) causes cold rain. Snow can only form by the "ice-crystal process," which involves vapor growth of crystals and coagulation, such as aggregation, and therefore all snow is "cold." 

          Using the tagging tracer technique in the AC model, we simulated and quantified the contributions of warm-rain and cold-rain components to the surface precipitation in three contrasting convective storms in STEPS (cold-based at ~1℃), MC3E (warm-based ~17℃;) and GoAmazon (very-warm based; ~28℃) cases. We found that approximately 80% of accumulated surface precipitation originated from the ice-crystal process in STEPS and MC3E control simulations and from the warm-rain process in the GoAmazon control simulation.

          The key question is why we see such contrasting competition between warm-rain and ice-crystal processes in convective storms. This question can be answered by conducting a few sensitivity simulations, especially to determine the cause for the competition between warm-rain and ice-crystal processes in each deep cloud.

          With the lowering of cloud base in STEPS and MC3E sensitivity simulations, most of the precipitation is switched to the warm-rain process. For instance, in STEPS case, when the cloud base temperature was increased to 17℃ (sensitivity) from 1℃ (control), most of the precipitation was switched to the warm-rain process from the control run (see Figure 9 in the article). In another sensitivity simulation related to GoAmazon, increasing the solute aerosol conditions in GoAmazon switched warm-rain process precipitation to the ice-crystal process. This shows that cloud base temperature and solute aerosol conditions control the balance between the warm-rain process and the cold-rain process in each storm.

          For uneven precipitation patterns in a warming climate, assessing the dominance of precipitation types in a given storm becomes even more important. These sophisticated tracer-tagging techniques should be implemented in the global climate model to assess better the influence of microphysical processes on the frequency and intensity of precipitation types, which requires the attention of climate researchers.

Acknowledgment: We acknowledge all of the co-authors and funding agencies listed in the published article.