The dominant role of aerosol’s CCN effect in cloud glaciation

Abstract The microphysical process of glaciation in clouds plays a crucial role in determining cloud dynamics, precipitation, atmospheric heat budgets, and the water cycle. Utilizing a year of global satellite data from Moderate Resolution Imaging Spectroradiometer (MODIS) and Modern-Era Retrospective analysis for Research and Applications (MERRA2) reanalysis, this study investigates the impact of aerosols on glaciation temperature (Tg) in deep convective clouds. Our results highlight the critical role of cloud droplet effective radius (r e ) at –5 °C in determining the Tg, where a greater r e at –5 °C (r e-5 ) corresponds to a warmer Tg, indicating the dominant role of the cloud drop size rather than INP. Specifically, the accelerated glaciation process is primarily due to the presence of larger supercooled droplets that freeze more rapidly. Large supercooled cloud droplets may enhance the secondary Ice Process (SIP), which could mask the influence of ice nucleating particles (INPs) in primary ice nucleation. Notably, at a fixed r e-5 , increasing the concentration of both fine and coarse aerosols has a minimal impact on Tg, indicating that the influence of INPs is weaker compared to the effect of r e-5 in determining cloud glaciation temperature. Consequently, aerosols functioning as cloud condensation nuclei (CCN) substantially impact cloud glaciation rather than INP. Additionally, we observe that fine and coarse aerosols acting as CCN have significant yet opposing effects on r e-5 . Although fine and coarse aerosols impact r e-5 , the r e-5 maintains a fairly consistent relationship with Tg. Based on these insights, a multiple linear regression model predicts Tg with a robust correlation coefficient of 0.87, serving as a reference for establishing a parameter space of Tg by r e-5 and aerosols, which can be applied for improving climate and global models.

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Publication Details

Journal
npj Climate and Atmospheric Science
Published
2025-03-26
DOI
https://doi.org/10.1038/s41612-025-00999-w
Citations
5
Primary Topic
Atmospheric aerosols and clouds
Type
article
Field-Weighted Citation Impact
5.53
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article

The dominant role of aerosol’s CCN effect in cloud glaciation

Jihu Liu, Yannian Zhu, Minghuai Wang, Daniel Rosenfeld et al.
5 citations
npj Climate and Atmospheric Science
Atmospheric aerosols and clouds
5.53
article

The dominant role of aerosol’s CCN effect in cloud glaciation

Jihu Liu, Yannian Zhu, Minghuai Wang, Daniel Rosenfeld, Iqra Munawar, Yichuan Wang
article en
5 citations

Abstract

Abstract The microphysical process of glaciation in clouds plays a crucial role in determining cloud dynamics, precipitation, atmospheric heat budgets, and the water cycle. Utilizing a year of global satellite data from Moderate Resolution Imaging Spectroradiometer (MODIS) and Modern-Era Retrospective analysis for Research and Applications (MERRA2) reanalysis, this study investigates the impact of aerosols on glaciation temperature (Tg) in deep convective clouds. Our results highlight the critical role of cloud droplet effective radius (r e ) at –5 °C in determining the Tg, where a greater r e at –5 °C (r e-5 ) corresponds to a warmer Tg, indicating the dominant role of the cloud drop size rather than INP. Specifically, the accelerated glaciation process is primarily due to the presence of larger supercooled droplets that freeze more rapidly. Large supercooled cloud droplets may enhance the secondary Ice Process (SIP), which could mask the influence of ice nucleating particles (INPs) in primary ice nucleation. Notably, at a fixed r e-5 , increasing the concentration of both fine and coarse aerosols has a minimal impact on Tg, indicating that the influence of INPs is weaker compared to the effect of r e-5 in determining cloud glaciation temperature. Consequently, aerosols functioning as cloud condensation nuclei (CCN) substantially impact cloud glaciation rather than INP. Additionally, we observe that fine and coarse aerosols acting as CCN have significant yet opposing effects on r e-5 . Although fine and coarse aerosols impact r e-5 , the r e-5 maintains a fairly consistent relationship with Tg. Based on these insights, a multiple linear regression model predicts Tg with a robust correlation coefficient of 0.87, serving as a reference for establishing a parameter space of Tg by r e-5 and aerosols, which can be applied for improving climate and global models.

npj Climate and Atmospheric ScienceVol. 8(1)
Hebrew University of Jerusalem (IL), Nanjing University (CN)
Openalex Percentile: Top 5%
Atmospheric aerosols and clouds
5.53
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