Articles | Volume 18, issue 11
https://doi.org/10.5194/acp-18-8373-2018
https://doi.org/10.5194/acp-18-8373-2018
Research article
 | 
15 Jun 2018
Research article |  | 15 Jun 2018

Maximizing ozone signals among chemical, meteorological, and climatological variability

Benjamin Brown-Steiner, Noelle E. Selin, Ronald G. Prinn, Erwan Monier, Simone Tilmes, Louisa Emmons, and Fernando Garcia-Menendez

Download

Interactive discussion

Status: closed
Status: closed
AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
Printer-friendly Version - Printer-friendly version Supplement - Supplement

Peer-review completion

AR: Author's response | RR: Referee report | ED: Editor decision
AR by Benjamin Brown-Steiner on behalf of the Authors (29 Mar 2018)  Manuscript 
ED: Referee Nomination & Report Request started (05 Apr 2018) by Jayanarayanan Kuttippurath
RR by Anonymous Referee #1 (13 Apr 2018)
RR by Anonymous Referee #2 (07 May 2018)
ED: Publish subject to minor revisions (review by editor) (09 May 2018) by Jayanarayanan Kuttippurath
AR by Benjamin Brown-Steiner on behalf of the Authors (19 May 2018)  Author's response   Manuscript 
ED: Publish as is (26 May 2018) by Jayanarayanan Kuttippurath
AR by Benjamin Brown-Steiner on behalf of the Authors (30 May 2018)
Download
Short summary
Detecting signals in observations and simulations of atmospheric chemistry is difficult due to the underlying variability in the chemistry, meteorology, and climatology. Here we examine the scale dependence of ozone variability and explore strategies for reducing or averaging this variability and thereby enhancing ozone signal detection capabilities. We find that 10–15 years of temporal averaging, and some level of spatial averaging, reduces the risk of overconfidence in ozone signals.
Altmetrics
Final-revised paper
Preprint