Articles | Volume 8, issue 12
https://doi.org/10.5194/amt-8-5301-2015
https://doi.org/10.5194/amt-8-5301-2015
Research article
 | 
18 Dec 2015
Research article |  | 18 Dec 2015

Comparison of the regional CO2 mole fraction filtering approaches at a WMO/GAW regional station in China

S. X. Fang, P. P. Tans, M. Steinbacher, L. X. Zhou, and T. Luan

Abstract. The identification of atmospheric CO2 observation data which are minimally influenced by very local emissions/removals is essential for trend analysis, for the estimation of regional sources and sinks, and for the modeling of long-range transport of CO2. In this study, four approaches are used to filter the atmospheric CO2 observation records from 2009 to 2011 at one World Meteorological Organization/Global Atmosphere Watch (WMO/GAW) regional station (Lin'an, LAN) in China. The methods are based on the concentration of atmospheric black carbon (BC), on a statistical approach (robust extraction of baseline signal, REBS), on CH4 as an auxiliary tracer (AUX), and on meteorological parameters (MET). All approaches do suitably well to capture the seasonal CO2 cycle at LAN. Differences are observed in the average regional mole fractions with annual values in the REBS method at least 1.7 ± 0.2 ppm higher than the other methods. The BC method may underestimate the regional CO2 mole fractions during the winter–spring period and should be treated with caution. The REBS method is a purely statistical method and it may also introduce errors on the regional CO2 mole fraction evaluations, as the filtered trend may be influenced by the "noisy" raw data series. Although there are correlations between CH4 and CO2 mole fractions at LAN, the different source/sink regimes may introduce bias on the regional CO2 estimation in the AUX method, typically in summer. Overall, the MET method seems to be the most favorable because it mainly focuses on the influence of potential local sources and sinks, and considers diurnal variations and meteorological conditions. Using the MET method, the annual growth rate of regional CO2 at LAN is determined to be 3.1 ± 0.01 ppm yr−1 (standard error) from 2009 to 2011.

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Short summary
The identification of atmospheric CO2 observation data which are minimally influenced by very local emissions/removals is essential for trend analysis and for the estimation of regional sources and sinks. We compared four data filtering regimes based on the observation records at Lin'an station in China, and found that the use of meteorological parameters was the most favorable. This conclusion will aid regional data selection at the Lin'an station.