基于飞机观测的内蒙古阴山地区层状云微物理特征 postprint

Abstract: To gain an in-depth understanding of precipitation processes in the Yinshan Mountains region of Inner Mongolia, this paper presents a systematic investigation of the microphysical characteristics of a stratiform precipitating cloud system based on aircraft observation data collected on April 19, 2024. The results show that: (1) Due to mountain blocking, moisture accumulation, and orographic forced lifting, significant differences in cloud microphysical characteristics were observed between the northern and southern sides of the mountains at the same flight altitude. On the northern side, the cloud system was characterized by lower liquid water content, with cloud particles predominantly consisting of small droplets with diameters less than 15 μm, exhibiting high total number concentrations and a relatively narrow spectral width. In contrast, on the southern side, higher liquid water content, fewer particles, and a significantly broader spectral width were observed. (2) The spatial distribution of liquid water content at the edges of the cloud area was uneven. Particle sizes in this region were significantly smaller than those in the interior of the cloud body due to the effects of turbulence and evaporation. The concentration of small cloud droplets decreased due to the coalescence process of melting ice crystals near the 0 °C level, while the concentration of large cloud droplets increased significantly, accompanied by a broadening of the particle spectral width measured by both instruments. (3) Vertical observations indicate that large precipitation particles at higher altitudes undergo melting during descent, resulting in the presence of a substantial number of partially melted cloud particles at lower levels. Meanwhile, the breakup of precipitation particles during their fall leads to a narrowing of the precipitation particle spectrum at lower levels and an increase in the number concentration of cloud particles. This study systematically elucidates the refined effects of factors such as topography and turbulence on cloud microphysical structure. The findings can be directly applied to improve numerical weather prediction models and cloud seeding operation strategies for this region.