Cloud drop diffusion growth is a fundamental microphysical process in warm clouds. In the present work, a new Lagrangian advection scheme (LAS) is proposed for solving this process. The LAS discretizes cloud drop size distribution (CDSD) with movable bins. Two types of prognostic variable, namely, bin radius and bin width, are included in the LAS. Bin radius is tracked by the well-known cloud drop diffusion growth equation, while bin width is solved by a derived equation. CDSD is then calculated with the information of bin radius, bin width, and prescribed droplet number concentration. The reliability of the new scheme is validated by the reference analytical solutions in a parcel cloud model. Artificial broadening of CDSD, understood as a by-product of numerical diffusion in advection algorithm, is strictly prohibited by the new scheme. The authors further coupled the LAS into a one-and-half dimensional (1.5D) Eulerian cloud model to evaluate its performance. An individual deep cumulus cloud studied in the Cooperative Convective Precipitation Experiment (CCOPE) campaign was simulated with the LAS-coupled 1.5D model and the original 1.5D model. Simulation results of CDSD and microphysical properties were compared with observational data. Improvements, namely, narrower CDSD and accurate reproduction of particle mean diameter, were achieved with the LAS-coupled 1.5D model.

In this study, we investigated the macro- and microstructures of layered precipitation clouds in spring in Jilin Province, China. The premise of the campaign was to observe cloud particles in the melting layer (ML). The weather was developed under the influence of the Mongolia cyclone, which brought a large range of precipitation to the northeast. Combining the Droplet Measurement Technology (DMT) and Particle Measuring Systems (PMS) data, small particles accounted for the majority of all particles at each level above and below the ML. In our observations, both ice crystals (50–300 μm) and snowflakes (>300 μm) had two peaks between −5 and −2 °C. The high concentration of ice crystals at a temperature of −2.65 °C (4865 m) attained a maximum value of 287 L⁻¹ and snowflakes with 47 L⁻¹, which was similar to the previous studies. The Hallett–Mossop ice multiplication process operated most effectively at the temperature of −5 °C in this study. Even at the cloud dissipation stage, new droplets were still generated between −5 and −6 °C, providing abundant liquid water content (LWC) for the upper cloud. Although irregulars were observed, needles and spheres dominated in the observed cloud region of low LWC (<0.1 g m⁻³) at temperatures of −6 to −3 °C. These cloud conditions fit into the Hallett–Mossop criteria.