Cluster analysis of European surface ozone observations for  evaluation of MACC reanalysis data

Lyapina, Olga; Schultz, Martin G.; Hense, Andreas

doi:https://doi.org/10.5194/acp-16-6863-2016

Articles | Volume 16, issue 11

https://doi.org/10.5194/acp-16-6863-2016

© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.

https://doi.org/10.5194/acp-16-6863-2016

© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.

Articles | Volume 16, issue 11

Research article

|

06 Jun 2016

Research article |

| 06 Jun 2016

Cluster analysis of European surface ozone observations for evaluation of MACC reanalysis data

Olga Lyapina, Martin G. Schultz, and Andreas Hense

Download

Final revised paper (published on 06 Jun 2016)
Supplement to the final revised paper
Preprint (discussion started on 08 Feb 2016)
Supplement to the preprint

Interactive discussion

Status: closed

AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment

- Printer-friendly version

- Supplement

RC1: 'Referee review', Anonymous Referee #1, 03 Mar 2016
- AC1: 'Answer to reviews of anonymous Referees#1 and #2', Olga Lyapina, 14 Mar 2016
RC2: 'Comment on Lyapina et al.', Anonymous Referee #2, 04 Mar 2016

Peer-review completion

AR: Author's response | RR: Referee report | ED: Editor decision

AR by Olga Lyapina on behalf of the Authors (06 Apr 2016) Author's response Manuscript

ED: Publish as is (14 Apr 2016) by Jason West

AR by Olga Lyapina on behalf of the Authors (23 Apr 2016) Manuscript

Download

Article (9246 KB)
Full-text XML

Short summary

This study applies numerical clustering for the classification of about 1500 ozone data sets in Europe. We show the usefulness of cluster analysis (CA) for the quantitative evaluation of a global model: pre-selection of stations and validation of a global model in a phase-space produce clearer and more interpretable results. CA can be easily updated for new stations, different length of data, and other type of input properties, as well as other type of data (for example, meteorological).