Articles | Volume 21, issue 21
© Author(s) 2021. This work is distributed underthe Creative Commons Attribution 4.0 License.
Influence of springtime atmospheric circulation types on the distribution of air pollutants in the Arctic
- Final revised paper (published on 12 Nov 2021)
- Preprint (discussion started on 11 Jun 2021)
Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor |
: Report abuse
RC1: 'Comment on acp-2021-458', Anonymous Referee #1, 12 Jul 2021
- AC1: 'Response to Reviewer 1 (RC1)', Manu Thomas, 03 Sep 2021
RC2: 'Comment on acp-2021-458', Anonymous Referee #2, 17 Jul 2021
- AC2: 'Response to Reviewer 2 (RC2)', Manu Thomas, 03 Sep 2021
Peer review completion
AR: Author's response | RR: Referee report | ED: Editor decision
AR by Manu Thomas on behalf of the Authors (24 Sep 2021)  Author's response Author's tracked changes Manuscript
ED: Referee Nomination & Report Request started (24 Sep 2021) by Bryan N. Duncan
RR by Anonymous Referee #1 (07 Oct 2021)
RR by Anonymous Referee #2 (07 Oct 2021)
ED: Publish subject to minor revisions (review by editor) (08 Oct 2021) by Bryan N. Duncan
AR by Manu Thomas on behalf of the Authors (11 Oct 2021)  Author's response Author's tracked changes Manuscript
ED: Publish as is (11 Oct 2021) by Bryan N. Duncan
This paper applies Self-Organizing Maps to sea level pressure fields to identify 20 circulation patters in the Arctic spring, and then analyzes the observed distributions of pollutants associated with these patterns. The analysis aims to demonstrate how the transport and distribution of pollutants in the Arctic varies depending on the circulation pattern and to provide an observation-based test of chemistry transport models. This is an original and interesting idea, and the Self-Organizing Map method is state-of-the-art. However, more discussion of uncertainties and sampling of the satellite data in the Arctic is needed. In addition, the inclusion of 20 different circulation patterns makes the results complicated to interpret. I list general and specific comments below.
Line 141: Please define TqJ
Line 167: Why is the weighting needed? To ensure each month of spring receives equal weight?
Line 171: It is stated here that only statistically significant anomalies are shown, but some figures (like Fig. 3) appear to show anomalies everywhere. How is significance or non-significance indicated?
Line 206: What does “those circulation types” refer to?
Lines 268-295: I find it difficult to relate this discussion to the large number of alternating positive and negative anomalies that appear in Fig. 7. Perhaps the analysis would be more convincing if multiple circulation types were grouped together to improve sample size and data coverage.
Fig. 1: A discrete colorbar might be easier to interpret.
Fig. 2: Streamlines might be a nice addition to help visualize the direction of transport