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Atmospheric Measurement Techniques An interactive open-access journal of the European Geosciences Union
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Volume 11, issue 3 | Copyright
Atmos. Meas. Tech., 11, 1501-1514, 2018
https://doi.org/10.5194/amt-11-1501-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.

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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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
Publications Copernicus
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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.
This paper presents a novel statistical method, ADVS, for baseline selection of representative...
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