Articles | Volume 16, issue 17
https://doi.org/10.5194/gmd-16-5237-2023
https://doi.org/10.5194/gmd-16-5237-2023
Model description paper
 | 
13 Sep 2023
Model description paper |  | 13 Sep 2023

J-GAIN v1.1: a flexible tool to incorporate aerosol formation rates obtained by molecular models into large-scale models

Daniel Yazgi and Tinja Olenius

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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-2022-1464', Anonymous Referee #1, 03 May 2023
  • RC2: 'Comment on egusphere-2022-1464', Anonymous Referee #2, 06 May 2023
  • AC1: 'Reply to reviewers', Tinja Olenius, 14 Jun 2023

Peer review completion

AR: Author's response | RR: Referee report | ED: Editor decision | EF: Editorial file upload
AR by Tinja Olenius on behalf of the Authors (14 Jun 2023)  Author's response   Author's tracked changes   Manuscript 
ED: Publish subject to minor revisions (review by editor) (03 Aug 2023) by Andrea Stenke
AR by Tinja Olenius on behalf of the Authors (07 Aug 2023)  Author's response   Author's tracked changes   Manuscript 
ED: Publish as is (14 Aug 2023) by Andrea Stenke
AR by Tinja Olenius on behalf of the Authors (15 Aug 2023)
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Short summary
We present flexible tools to implement aerosol formation rate predictions in climate and chemical transport models. New-particle formation is a significant but uncertain factor affecting aerosol numbers and an active field within molecular modeling which provides data for assessing formation rates for different chemical species. We introduce tools to generate and interpolate formation rate lookup tables for user-defined data, thus enabling the easy inclusion and testing of formation schemes.