Articles | Volume 21, issue 23
Atmos. Chem. Phys., 21, 17727–17741, 2021
https://doi.org/10.5194/acp-21-17727-2021

Special issue: Particle-based methods for simulating atmospheric aerosol...

Atmos. Chem. Phys., 21, 17727–17741, 2021
https://doi.org/10.5194/acp-21-17727-2021

Research article 03 Dec 2021

Research article | 03 Dec 2021

Quantifying the structural uncertainty of the aerosol mixing state representation in a modal model

Zhonghua Zheng et al.

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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 acp-2021-409', Anonymous Referee #3, 14 Aug 2021
  • RC2: 'Comment on acp-2021-409', Anonymous Referee #1, 30 Aug 2021
  • RC3: 'Comment on acp-2021-409', Anonymous Referee #2, 09 Sep 2021
  • AC1: 'Response to referees', Zhonghua Zheng, 12 Oct 2021

Peer review completion

AR: Author's response | RR: Referee report | ED: Editor decision
AR by Zhonghua Zheng on behalf of the Authors (12 Oct 2021)  Author's response    Author's tracked changes    Manuscript
ED: Publish as is (26 Oct 2021) by Qiang Zhang

Post-review adjustments

AA: Author's adjustment | EA: Editor approval
AA by Zhonghua Zheng on behalf of the Authors (24 Nov 2021)   Author's adjustment   Manuscript
EA: Adjustments approved (30 Nov 2021) by Qiang Zhang
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Short summary
Aerosol mixing state is an important emergent property that affects aerosol radiative forcing and aerosol–cloud interactions, but it has not been easy to constrain this property globally. We present a framework for evaluating the error in aerosol mixing state induced by aerosol representation assumptions, which is one of the important contributors to structural uncertainty in aerosol models. Our study provides insights into potential improvements to model process representation for aerosols.
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