Articles | Volume 16, issue 14
https://doi.org/10.5194/acp-16-9089-2016
https://doi.org/10.5194/acp-16-9089-2016
Research article
 | 
25 Jul 2016
Research article |  | 25 Jul 2016

Can we detect regional methane anomalies? A comparison between three observing systems

Cindy Cressot, Isabelle Pison, Peter J. Rayner, Philippe Bousquet, Audrey Fortems-Cheiney, and Frédéric Chevallier

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Subject: Gases | Research Activity: Atmospheric Modelling and Data Analysis | Altitude Range: Troposphere | Science Focus: Chemistry (chemical composition and reactions)
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Cited articles

Berchet, A., Pison, I., Chevallier, F., Bousquet, P., Bonne, J.-L., and Paris, J.-D.: Objectified quantification of uncertainties in Bayesian atmospheric inversions, Geosci. Model Dev., 8, 1525–1546, https://doi.org/10.5194/gmd-8-1525-2015, 2015.
Bergamaschi, P., Frankenberg, C., Meirink, J., Krol, M., Dentener, F., Wagner, T., Platt, U., Kaplan, J., Körner, S., Heimann, M., Dlugokencky, E. J., and Goede, A.: Satellite chartography of atmospheric methane from SCIAMACHY on board ENVISAT: 2. Evaluation based on inverse model simulations, J. Geophys. Res.-Atmos., 112, D02304, https://doi.org/10.1029/2006JD007268, 2007.
Bergamaschi, P., Houweling, S., Segers, A., Krol, M., Frankenberg, C., Scheepmaker, R., Dlugokencky, E., Wofsy, S., Kort, E., Sweeney, C., Schuck, T., Brenninkmeijer, C., Chen, H., Beck, V., and Gerbig, C.: Atmospheric CH4 in the first decade of the 21st century: Inverse modeling analysis using SCIAMACHY satellite retrievals and NOAA surface measurements, J. Geophys. Res.-Atmos., 118, 7350–7369, 2013.
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Several hypothesis have been made to attribute current trends in atmospheric methane to particular regions. In this context, this work aims at evaluating how well anomalies in methane emissions can be detected at the regional scale with currently available observing systems: two space-borne instruments and a surface network. Our results show that inter-annual analyses of methane emissions inferred by atmospheric inversions should always include an uncertainty assessment.
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