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-26-1565-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/acp-26-1565-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 26, issue 2
Research article
 | 
29 Jan 2026
Research article |  | 29 Jan 2026

Shortening of the Arctic cold air outbreak season detected by a phenomenological machine learning approach

Filip Severin von der Lippe, Tim Carlsen, Trude Storelvmo, and Robert Oscar David

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Latest update: 31 Oct 2026
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Short summary
This paper investigates how clouds associated with Arctic marine cold air outbreaks (CAOs) respond to climate change. By utilizing machine learning methods and remote sensing data from the past 25 years, the study identifies trends indicating a shortening of the CAO season. This has implications for the Arctic energy balance, underscoring the importance of further investigating these clouds to understand the trajectory of future Arctic climate.
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