Abstract The microphysical variability of stratiform precipitation over North China is investigated using in situ aircraft observations from eight vertical spirals in three stratiform events sampled during the ‘Demonstration Project for Precipitation Enhancement and Hail Suppression on the Eastern Side of Taihang Mountain’ (PPEHS) field campaign (22 May 2017; 21 May 2018; 20 April 2019). A King Air 350 equipped with cloud microphysical probes documented particle size distributions, habits, and bulk properties from the ice region down through the melting layer, together with the ambient thermodynamic and vertical airflow conditions. All events exhibit a robust mean vertical structure in which the volume‐weighted diameter D m increases and the total number concentration N t decreases toward the melting layer, indicating efficient aggregation and riming in the lower ice region. Superimposed on this common pattern, however, are pronounced differences in D m , N t , particle habits, and particle size distribution (PSD) shape among spirals and among cases, even under similar values of convective available potential energy (CAPE), relative humidity, and vertical wind shear. In the 22 May 2017 event, layered peaks and valleys in D m indicate alternating dominance of aggregation, riming, breakup, and secondary ice production, while the three spirals sample distinctly different melting‐layer structures. The 2018 and 2019 events confirm strong horizontal contrasts between small‐particle‐rich and large‐particle‐rich sectors and show that large aggregates and rimed particles carry a substantial fraction of the condensate mass. Compared with midlatitude field campaigns such as BAMEX and PECAN, the stratiform events sampled over North China exhibit weaker fractional decreases in N t but stronger growth in D m and total water content, implying more efficient production of large ice particles. These findings highlight significant subkilometer to mesoscale microphysical heterogeneity in relatively uniform stratiform precipitation events and provide observational constraints for improving microphysical parameterizations in numerical models.
Hu et al. (Sat,) studied this question.