Atmospheric Chemistry and Physics
Atmospheric Chemistry and Physics
ACP
Articles | Volume 26, issue 2
Articles | Volume 26, issue 2
https://doi.org/10.5194/acp-26-1459-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/acp-26-1459-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 26, issue 2
Research article
 | 
28 Jan 2026
Research article |  | 28 Jan 2026

Inferring the controlling factors of ice aggregation from targeted cloud seeding experiments

Huiying Zhang, Fabiola Ramelli, Christopher Fuchs, Nadja Omanovic, Anna J. Miller, Robert Spirig, Zhaolong Wu, Yunpei Chu, Xia Li, Ulrike Lohmann, and Jan Henneberger
Editorial note: on 5 May 2026 the figures 3 and D1 were corrected by removing the label "log" which had been inserted by mistake.

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Short summary
Ice crystals in clouds aggregate, shaping snow and rain, yet rates are hard to measure. Using cloud seeding, we sampled crystals downwind after known times. A deep-learning algorithm quantified aggregation by counting crystal components. Initial ice concentration was the main driver, confirmed by causal analysis, physics, and machine learning, though weaker than theory predicts. Temperature, size, and shape also mattered, while turbulence was negligible.
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