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DOI: 10.5445/IR/1000081493
DOI: 10.5194/amt-11-1501-2018

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

Yuan, Ye; Ries, Ludwig; Petermeier, Hannes; Steinbacher, Martin; Gómez-Pelaéz, Angel J.; Leuenberger, Markus C.; Schumacher, Marcus; Trickl, Thomas; Couret, Cedric; Meinhardt, Frank; Menzel, Annette

Critical data selection is essential for determining representative baseline levels of atmospheric trace gases even at remote measurement sites. Different data selection techniques have been used around the world, which could potentially lead to reduced compatibility when comparing data from different stations. This paper presents a novel statistical data selection method named adaptive diurnal minimum variation selection (ADVS) based on CO₂ diurnal patterns typically occurring at elevated mountain stations. Its capability and applicability were studied on records of atmospheric CO₂ observations at six Global Atmosphere Watch stations in Europe, namely, Zugspitze Schneefernerhaus (Germany), Sonnblick (Austria), Jungfraujoch (Switzerland), Izaña (Spain), Schauinsland (Germany), and Hohenpeissenberg (Germany). Three other frequently applied statistical data selection methods were included for comparison. Among the studied methods, our ADVS method resulted in a lower fraction of data selected as a baseline with lower maxima during winter and higher minima during summer in the selected data. The measured time series were analyzed for lo ... mehr

Zugehörige Institution(en) am KIT Institut für Meteorologie und Klimaforschung - Atmosphärische Umweltforschung (IMK-IFU)
Publikationstyp Zeitschriftenaufsatz
Jahr 2018
Sprache Englisch
Identifikator ISSN: 1867-1381, 1867-8548
URN: urn:nbn:de:swb:90-814933
KITopen ID: 1000081493
Erschienen in Atmospheric measurement techniques
Band 11
Heft 3
Seiten 1501-1514
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