An airborne study of the aerosol effect on the dispersion of cloud droplets in a drizzling marine stratocumulus cloud over eastern China

云凝聚核 云顶 云层高度 液态水通道 气象学 云量 行星边界层 云分数 云高计
作者
Fei Wang,Zhanqing Li,Delong Zhao,Xiaojun Ma,Yang Gao,Jian Sheng,Ping Tian,Maureen Cribb
出处
期刊:Atmospheric Research [Elsevier]
卷期号:265: 105885-105885 被引量:5
标识
DOI:10.1016/j.atmosres.2021.105885
摘要

Detailed airborne measurements were carried out to explore aerosol-cloud interactions and cloud microphysical properties in a drizzling marine stratocumulus cloud deck over eastern China. Results show that the collision-coalescence of cloud droplets, the condensation of small droplets, and the collision-induced break-up of drizzle were the dominant microphysical processes in the sampled water cloud parcel. The region in the vicinity of the cloud's lateral boundary was spatially divided into sub-regions to better understand aerosol and droplet interactions. Relationships between the relative dispersion (ε) and the cloud’'s microphysical and dynamical characteristics were also examined. A negative relation was found between ε and the cloud droplet number concentration, with ε showing a close relationship with the liquid water content (LWC) and updraft velocity. When LWC was greater than ~0.75 g kg−1, the range of ε values narrowed, and updrafts dominated. By introducing ε in the cloud droplet effect radius (Re) parameterization, we find that ε can further affect indirect forcing by changing the Re distribution for the cloud examined in this study. The dispersion effect (DE) was estimated using the effective radius ratio and the specific cloud water content. An in-depth analysis indicates that DE may offset the Twomey effect by ~12%. Two different methods of estimating the indirect effect (IE) yielded close values (0.084 and 0.077), suggesting that introducing DE into the estimation had a small influence on the IE calculation in the drizzling marine stratocumulus cloud of this study. Note that the estimated IE has a large uncertainty, given the large biases in the cloud properties measured.
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