Articles | Volume 25, issue 13
https://doi.org/10.5194/acp-25-7007-2025
https://doi.org/10.5194/acp-25-7007-2025
Research article
 | 
10 Jul 2025
Research article |  | 10 Jul 2025

Aerosol–cloud interactions in cirrus clouds based on global-scale airborne observations and machine learning models

Derek Ngo, Minghui Diao, Ryan J. Patnaude, Sarah Woods, and Glenn Diskin

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Interactive discussion

Status: closed

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on egusphere-2024-2122', Anonymous Referee #1, 09 Oct 2024
  • RC2: 'Comment on egusphere-2024-2122', Anonymous Referee #2, 15 Oct 2024
  • AC1: 'Comment on egusphere-2024-2122', Minghui Diao, 31 Jan 2025
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Short summary
Key controlling factors of cirrus clouds were individually quantified using machine learning models based on global-scale in situ observations from 12 campaigns at 67° S–87° N. Relative humidity shows much larger effects on cirrus occurrences and ice water content (IWC) fluctuations than vertical velocity. Aerosol–cloud interactions are seen for both large and small aerosols, with higher IWC and ice crystal number concentration under higher aerosol concentrations. Large aerosols are more impactful than small aerosols.
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