Articles | Volume 11, issue 3
Atmos. Meas. Tech., 11, 1501–1514, 2018
https://doi.org/10.5194/amt-11-1501-2018
Atmos. Meas. Tech., 11, 1501–1514, 2018
https://doi.org/10.5194/amt-11-1501-2018

Research article 15 Mar 2018

Research article | 15 Mar 2018

Adaptive selection of diurnal minimum variation: a statistical strategy to obtain representative atmospheric CO2 data and its application to European elevated mountain stations

Ye Yuan 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 Ye Yuan on behalf of the Authors (05 Dec 2017)  Author's response    Manuscript
ED: Referee Nomination & Report Request started (03 Jan 2018) by Dominik Brunner
RR by Anonymous Referee #1 (16 Jan 2018)
ED: Publish subject to minor revisions (review by editor) (29 Jan 2018) by Dominik Brunner
AR by Ye Yuan on behalf of the Authors (01 Feb 2018)  Author's response    Manuscript
ED: Publish subject to technical corrections (11 Feb 2018) by Dominik Brunner
AR by Ye Yuan on behalf of the Authors (18 Feb 2018)  Author's response    Manuscript
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Short summary
This paper presents a novel statistical method, ADVS, for baseline selection of representative CO2 data at elevated mountain measurement stations. It provides insights on how data processing techniques are critical for measurements and data analyses. Compared with other statistical methods, our method appears to be a good option as a generalized approach with improved comparability, which is important for research on measurement site characteristics and comparisons between stations.