Cloud Susceptibility to Aerosols: Comparing Cloud‐Appearance Versus Cloud‐Controlling Factors Regimes

云计算 环境科学 大气科学 气象学 液态水含量 计算机科学 物理 操作系统
作者
Jihu Liu,Yannian Zhu,Minghuai Wang,Daniel Rosenfeld,Yang Cao,Tianle Yuan
出处
期刊:Journal Of Geophysical Research: Atmospheres [Wiley]
卷期号:129 (14)
标识
DOI:10.1029/2024jd041216
摘要

Abstract Clouds can be classified into regimes based on their appearance or meteorological controlling factors. The cloud appearance regimes inherently include adjustments to aerosol effects, such as transitions between closed and open cells. Therefore, calculating cloud susceptibilities to aerosols for each cloud‐appearance regime individually and then aggregating them excludes much of the cloud adjustment component of the susceptibilities. In contrast, aggregating susceptibilities over regimes defined by cloud‐controlling factors includes the full effects of cloud adjustments. Here we compared the susceptibilities of the two kinds of cloud regimes and demonstrated this effect. Overall, increasing cloud droplet number concentration ( N d ) consistently correlates to weaker precipitation, higher cloud fraction (CF), and reduced liquid water path, regardless of how the regime is defined. However, their susceptibilities to N d aggregated over cloud‐appearance regimes are significantly lower than those aggregated over cloud‐controlling factors regimes, with lower‐tropospheric stability (LTS) serving as an example to define cloud‐controlling factors regimes. This underestimation is more pronounced for CF susceptibility, where the susceptibility for cloud appearance regimes is only 1/4 of the susceptibility for cloud controlling regimes. These findings imply that relying solely on cloud‐appearance regimes may underestimate the effective radiative forcing produced by cloud adjustment (ERF aci ). Nevertheless, the substantial variability in the magnitude of cloud adjustment across appearance regimes at similar LTS also suggests that a single cloud‐controlling factor is not sufficient to fully separate cloud regimes to quantify cloud adjustment. Therefore, identifying a comprehensive set of cloud‐controlling factors is essential for accurately quantifying cloud adjustments in future studies.
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