Articles | Volume 19, issue 5
https://doi.org/10.5194/acp-19-2881-2019
https://doi.org/10.5194/acp-19-2881-2019
Research article
 | 
07 Mar 2019
Research article |  | 07 Mar 2019

Advanced methods for uncertainty assessment and global sensitivity analysis of an Eulerian atmospheric chemistry transport model

Ksenia Aleksankina, Stefan Reis, Massimo Vieno, and Mathew R. Heal

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AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
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AR: Author's response | RR: Referee report | ED: Editor decision
AR by Ksenia Aleksankina on behalf of the Authors (15 Dec 2018)  Manuscript 
ED: Referee Nomination & Report Request started (19 Dec 2018) by Robert Harley
RR by Anonymous Referee #1 (04 Jan 2019)
ED: Publish subject to minor revisions (review by editor) (17 Jan 2019) by Robert Harley
AR by Ksenia Aleksankina on behalf of the Authors (06 Feb 2019)  Author's response   Manuscript 
ED: Publish as is (08 Feb 2019) by Robert Harley
AR by Ksenia Aleksankina on behalf of the Authors (12 Feb 2019)  Manuscript 
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Short summary
Atmospheric chemistry transport models are widely used to underpin policies to mitigate the detrimental effects of air pollution on human health and ecosystems. Understanding the level of confidence in model predictions is thus vital. We present a comprehensive approach for uncertainty assessment and global variance-based sensitivity analysis to propagate uncertainty from model input data and identify the extent to which uncertainty in different emissions drives the model output uncertainty.
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