Articles | Volume 20, issue 22
Atmos. Chem. Phys., 20, 13771–13780, 2020
https://doi.org/10.5194/acp-20-13771-2020
Atmos. Chem. Phys., 20, 13771–13780, 2020
https://doi.org/10.5194/acp-20-13771-2020

Research article 16 Nov 2020

Research article | 16 Nov 2020

Snow-induced buffering in aerosol–cloud interactions

Takuro Michibata et al.

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AR by Takuro Michibata on behalf of the Authors (26 Aug 2020)  Author's response    Manuscript
ED: Referee Nomination & Report Request started (09 Sep 2020) by Corinna Hoose
RR by Anonymous Referee #1 (28 Sep 2020)
ED: Publish as is (09 Oct 2020) by Corinna Hoose
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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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