Articles | Volume 14, issue 6
Geosci. Model Dev., 14, 3715–3739, 2021
https://doi.org/10.5194/gmd-14-3715-2021
Geosci. Model Dev., 14, 3715–3739, 2021
https://doi.org/10.5194/gmd-14-3715-2021

Development and technical paper 22 Jun 2021

Development and technical paper | 22 Jun 2021

Retrieval of process rate parameters in the general dynamic equation for aerosols using Bayesian state estimation: BAYROSOL1.0

Matthew Ozon et al.

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Interactive discussion

Status: closed
Status: closed
AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
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Peer-review completion

AR: Author's response | RR: Referee report | ED: Editor decision
AR by Matthew Ozon on behalf of the Authors (24 Mar 2021)  Author's response    Author's tracked changes    Manuscript
ED: Referee Nomination & Report Request started (20 Apr 2021) by Christina McCluskey
RR by Anonymous Referee #2 (27 Apr 2021)
RR by Anonymous Referee #1 (02 May 2021)
ED: Publish as is (05 May 2021) by Christina McCluskey
AR by Matthew Ozon on behalf of the Authors (11 May 2021)  Author's response    Manuscript
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Short summary
Experimental research has provided large amounts of high-quality data on aerosol over the last 2 decades. However, inference of the process rates (e.g., the rates at which particles are generated) is still typically done by simple curve-fitting methods and does not assess the credibility of the estimation. The devised method takes advantage of the Bayesian framework to not only retrieve the state of the observed aerosol system but also to estimate the process rates (e.g., growth rate).