Please use this identifier to cite or link to this item: http://hdl.handle.net/20.500.11765/8848
Adaptive selection of diurnal minimum variation: a statistical strategy to obtain representative atmospheric CO2 data and its application to European elevated mountain stations
Title: Adaptive selection of diurnal minimum variation: a statistical strategy to obtain representative atmospheric CO2 data and its application to European elevated mountain stations
Authors: Yuan, YenRies, LudwigPetermeier, HannesSteinbacher, MartinGómez Peláez, Ángel Jesús ORCID RESEARCHERID SCOPUSID Autor AEMETLeuenberger, Markus C.Schumacher, MarcusTrickl, ThomasCouret, CedricMeinhardt, FrankMenzel, Annette
Keywords: Atmospheric gases; Remote measurement; Carbon dioxide; Statistical method
Issue Date: 2018
Publisher: European Geosciences Union
Citation: Atmospheric Measurement Techniques. 2018, 11(3), p. 1501-1514
Publisher version: https://dx.doi.org/10.5194/amt-11-1501-2018
Abstract: 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.
Sponsorship : This work was supported by a scholarship from China Scholarship Council (CSC) under grant CSC No. 201508080110.
URI: http://hdl.handle.net/20.500.11765/8848
ISSN: 1867-1381
1867-8548
Appears in Collections:Artículos científicos 2015-2018


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