Atmospheric Chemistry and Physics
Atmospheric Chemistry and Physics
ACP
Articles | Volume 20, issue 22
Articles | Volume 20, issue 22
https://doi.org/10.5194/acp-20-13771-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/acp-20-13771-2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 20, issue 22
Research article
 | 
16 Nov 2020
Research article |  | 16 Nov 2020

Snow-induced buffering in aerosol–cloud interactions

Takuro Michibata, Kentaroh Suzuki, and Toshihiko Takemura

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Latest update: 25 Apr 2024
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Short summary
This work reveals that prognostic precipitation significantly reduces the magnitude of aerosol–cloud interactions (ERFaci), mainly due to the collection process associated with snowflakes and underlying cloud droplets. This precipitation-driven buffering effect, which is missing in traditional GCMs, can explain the model–observation discrepancy in ERFaci. These results underscore the necessity for a prognostic precipitation framework in GCMs for more reliable climate simulations.
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