Articles | Volume 23, issue 24
https://doi.org/10.5194/acp-23-15589-2023
https://doi.org/10.5194/acp-23-15589-2023
Research article
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20 Dec 2023
Research article | Highlight paper |  | 20 Dec 2023

Drivers controlling black carbon temporal variability in the lower troposphere of the European Arctic

Stefania Gilardoni, Dominic Heslin-Rees, Mauro Mazzola, Vito Vitale, Michael Sprenger, and Radovan Krejci

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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-2023-1376', Anonymous Referee #1, 18 Jul 2023
    • AC1: 'Reply on RC1', Stefania Gilardoni, 27 Sep 2023
  • RC2: 'Comment on egusphere-2023-1376', Anonymous Referee #2, 18 Jul 2023
    • AC2: 'Reply on RC2', Stefania Gilardoni, 27 Sep 2023

Peer review completion

AR: Author's response | RR: Referee report | ED: Editor decision | EF: Editorial file upload
AR by Stefania Gilardoni on behalf of the Authors (28 Sep 2023)  Author's response   Author's tracked changes   Manuscript 
ED: Referee Nomination & Report Request started (29 Sep 2023) by Lynn M. Russell
RR by Anonymous Referee #2 (06 Oct 2023)
RR by Anonymous Referee #1 (10 Oct 2023)
ED: Publish subject to technical corrections (18 Oct 2023) by Lynn M. Russell
AR by Stefania Gilardoni on behalf of the Authors (06 Nov 2023)  Author's response   Manuscript 
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Executive editor
Black carbon is a key source of uncertainty in regional climate predictions through aerosol-radiation interactions, cloud modifications and enhanced snow melt, and the arctic is particularly sensitive to these effects. Understanding the influence of continental emissions on arctic aerosols is crucial in earth system science, and this influence can be expected to evolve with changes to the atmospheric circulation in response to climate change. This paper uses a machine learning approach to study the factors controlling observations of black carbon in the arctic and quantitatively links these to meteorological processes and trends. This phenomenological assessment will facilitate predictions in the long range transport of black carbon transport under various climate change scenarios.
Short summary
Models still fail in reproducing black carbon (BC) temporal variability in the Arctic. Analysis of equivalent BC concentrations in the European Arctic shows that BC seasonal variability is modulated by the efficiency of removal by precipitation during transport towards high latitudes. Short-term variability is controlled by synoptic-scale circulation patterns. The advection of warm air from lower latitudes is an effective pollution transport pathway during summer.
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