Articles | Volume 11, issue 3
https://doi.org/10.5194/amt-11-1501-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/amt-11-1501-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
15 Mar 2018
Research article |
| 15 Mar 2018
| 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
CORRESPONDING AUTHOR
Department of Ecology and Ecosystem Management, Technical University of Munich (TUM), Freising, Germany
Ludwig Ries
German Environment Agency (UBA), Zugspitze, Germany
Hannes Petermeier
Department of Mathematics, Technical University of Munich (TUM), Freising, Germany
Martin Steinbacher
Empa, Laboratory for Air Pollution/Environmental Technology, Dübendorf, Switzerland
Angel J. Gómez-Peláez
Izaña Atmospheric Research Center, Meteorological State Agency of Spain (AEMET), Santa Cruz de Tenerife, Spain
now at: Meteorological State Agency of Spain (AEMET), Delegation in Asturias, Oviedo, Spain
Markus C. Leuenberger
Climate and Environmental Physics Division, Physics Institute and Oeschger Centre for Climate Change Research, University of Bern, Bern, Switzerland
Marcus Schumacher
Meteorological Observatory Hohenpeissenberg, Deutscher Wetterdienst (DWD), Hohenpeissenberg, Germany
Thomas Trickl
Institute of Meteorology and Climate Research, Atmospheric Environmental Research (IMK-IFU), Karlsruhe Institute of Technology, Garmisch-Partenkirchen, Germany
Cedric Couret
German Environment Agency (UBA), Zugspitze, Germany
Frank Meinhardt
German Environment Agency (UBA), Schauinsland, Germany
Annette Menzel
Department of Ecology and Ecosystem Management, Technical University of Munich (TUM), Freising, Germany
Institute for Advanced Study, Technical University of Munich (TUM), Garching, Germany
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- Transport of Po Valley aerosol pollution to the northwestern Alps – Part 2: Long-term impact on air quality H. Diémoz et al. 10.5194/acp-19-10129-2019
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- Long-term trends of black carbon and particle number concentration in the lower free troposphere in Central Europe J. Sun et al. 10.1186/s12302-021-00488-w
- The isotopic composition of atmospheric nitrous oxide observed at the high-altitude research station Jungfraujoch, Switzerland L. Yu et al. 10.5194/acp-20-6495-2020
- Comparison of Continuous In-Situ CO2 Measurements with Co-Located Column-Averaged XCO2 TCCON/Satellite Observations and CarbonTracker Model Over the Zugspitze Region Y. Yuan et al. 10.3390/rs11242981
- On the diurnal, weekly, and seasonal cycles and annual trends in atmospheric CO<sub>2</sub> at Mount Zugspitze, Germany, during 1981–2016 Y. Yuan et al. 10.5194/acp-19-999-2019
- Local emission and long-range transport impacts on the CO, CO2, and CH4 concentrations at a tropical rural site C. Jain et al. 10.1016/j.atmosenv.2021.118397
- Comparison of atmospheric CO, CO2 and CH4 measurements at the Schneefernerhaus and the mountain ridge at Zugspitze A. Hoheisel et al. 10.5194/amt-16-2399-2023
- High-altitude aerosol chemical characterization and source identification: insights from the CALISHTO campaign O. Zografou et al. 10.5194/acp-24-8911-2024
- Multivariate statistical air mass classification for the high-alpine observatory at the Zugspitze Mountain, Germany A. Sigmund et al. 10.5194/acp-19-12477-2019
- Zugspitze ozone 1970–2020: the role of stratosphere–troposphere transport T. Trickl et al. 10.5194/acp-23-8403-2023
- Thirty Years of Atmospheric CO2 Observations at the Plateau Rosa Station, Italy F. Apadula et al. 10.3390/atmos10070418
- Pollution Events at the High-Altitude Mountain Site Zugspitze-Schneefernerhaus (2670 m a.s.l.), Germany H. Ghasemifard et al. 10.3390/atmos10060330
Latest update: 20 Nov 2024
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...
