Articles | Volume 19, issue 5
Atmos. Chem. Phys., 19, 2965–2990, 2019
https://doi.org/10.5194/acp-19-2965-2019

Special issue: Global and regional assessment of intercontinental transport...

Atmos. Chem. Phys., 19, 2965–2990, 2019
https://doi.org/10.5194/acp-19-2965-2019

Research article 07 Mar 2019

Research article | 07 Mar 2019

Aerosol optical properties over Europe: an evaluation of the AQMEII Phase 3 simulations against satellite observations

Laura Palacios-Peña 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 Pedro Jimenez-Guerrero on behalf of the Authors (21 Jun 2018)  Author's response    Manuscript
ED: Referee Nomination & Report Request started (02 Aug 2018) by Nikolaos Mihalopoulos
RR by Anonymous Referee #1 (12 Aug 2018)
RR by Anonymous Referee #3 (18 Aug 2018)
ED: Reconsider after major revisions (27 Aug 2018) by Nikolaos Mihalopoulos
AR by Svenja Lange on behalf of the Authors (09 Oct 2018)  Author's response
ED: Referee Nomination & Report Request started (17 Nov 2018) by Nikolaos Mihalopoulos
RR by Anonymous Referee #1 (27 Nov 2018)
RR by Anonymous Referee #3 (30 Jan 2019)
ED: Publish subject to minor revisions (review by editor) (30 Jan 2019) by Nikolaos Mihalopoulos
AR by Laura Palacios-Peña on behalf of the Authors (31 Jan 2019)  Author's response    Manuscript
ED: Publish as is (13 Feb 2019) by Nikolaos Mihalopoulos
AR by Laura Palacios-Peña on behalf of the Authors (14 Feb 2019)  Author's response    Manuscript
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Short summary
The main uncertainties regarding the estimation of changes in the Earth’s energy budget are related to the role of atmospheric aerosols. Our study evaluates the representation of aerosol optical properties by different atmospheric chemistry models against remote-sensing observations in order to reduce this uncertainty. Results show that the representation of aerosol optical properties is strongly dependent on the used model.
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