Articles | Volume 14, issue 9
https://doi.org/10.5194/amt-14-6119-2021
https://doi.org/10.5194/amt-14-6119-2021
Research article
 | 
17 Sep 2021
Research article |  | 17 Sep 2021

An algorithm to detect non-background signals in greenhouse gas time series from European tall tower and mountain stations

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Cited articles

Apadula, F., Cassardo, C., Ferrarese, S., Heltai, D., and Lanza, A.: Thirty Years of Atmospheric CO2 Observations at the Plateau Rosa Station, Italy, Atmosphere, 10, 418, https://doi.org/10.3390/atmos10070418, 2019. 
Balzani Loöv, J. M., Henne, S., Legreid, G., Staehelin, J., Reimann, S., Prévôt, A. S. H., Steinbacher, M., and Vollmer, M. K.: Estimation of background concentrations of trace gases at the Swiss Alpine site Jungfraujoch (3580 m a.s.l.), J. Geophys. Res., 113, D22305, https://doi.org/10.1029/2007JD009751, 2008. 
Biraud, S., Ciais, P., Ramonet, M., Simmonds, P., Kazan, V., Monfray, P., O'Doherty, S., Spain, T. G., and Jennings, S. G.: European greenhouse gas emissions estimated from continuous atmospheric measurements and radon 222 at Mace Head, Ireland, J. Geophys. Res., 105, 1351–1366, https://doi.org/10.1029/1999JD900821, 2000. 
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Short summary
We present a technical description of a statistical methodology for extracting synoptic- and seasonal-length anomalies from greenhouse gas time series. The definition of what represents an anomalous signal is somewhat subjective, which we touch on throughout the paper. We show, however, that the method performs reasonably well in extracting portions of time series influenced by significant North Atlantic Oscillation weather episodes and continent-wide terrestrial biospheric aberrations.
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