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. Methane ( CH4 ) is an important greenhouse gas, and its atmosphericbudget is determined by interacting sources and sinks in a dynamic globalenvironment. Methane observations indicate that after almost a decade ofstagnation, from 2006, a sudden and continuing global mixing ratio increasetook place. We applied a general circulation model to simulate the globalatmospheric budget, variability, and trends of methane for the period1997–2016. Using interannually constant CH4 a priori emissions from11 biogenic and fossil source categories, the model results are comparedwith observations from 17 Advanced Global Atmospheric Gases Experiment (AGAGE)and National Oceanic and Atmospheric Administration (NOAA) surface stations andintercontinental Civil Aircraft forthe Regular observation of the atmosphere Based on an InstrumentedContainer (CARIBIC) flights, with > 4800  CH4 samples,gathered on > 320 flights in the upper troposphere and lowermoststratosphere. Based on a simple optimization procedure, methane emission categories havebeen scaled to reduce discrepancies with the observational data for theperiod 1997–2006. With this approach, the all-station mean dry air molefraction of 1780 nmol mol −1 could be improved from an a priori root meansquare deviation (RMSD) of 1.31 % to just 0.61 %, associated with acoefficient of determination ( R2 ) of 0.79. The simulated a prioriinterhemispheric difference of 143.12 nmol mol −1 was improved to131.28 nmol mol −1 , which matched the observations quite well (130.82 nmol mol −1 ). Analogously, aircraft measurements were reproduced well, with a global RMSDof 1.1 % for the measurements before 2007, with even better results on aregional level (e.g., over India, with an RMSD of 0.98 % and R2=0.65 ). With regard to emission optimization, this implied a30.2 Tg  CH4  yr −1 reduction in predominantly fossil-fuel-relatedemissions and a 28.7 Tg  CH4  yr −1 increase of biogenic sources. With the same methodology, the CH4 growth that started in 2007 andcontinued almost linearly through 2013 was investigated, exploring thecontributions by four potential causes, namely biogenic emissions fromtropical wetlands, from agriculture including ruminant animals, and fromrice cultivation, and anthropogenic emissions (fossil fuel sources, e.g.,shale gas fracking) in North America. The optimization procedure adopted inthis work showed that an increase in emissions from shale gas (7.67 Tg yr −1 ),rice cultivation (7.15 Tg yr −1 ), and tropical wetlands (0.58 Tg yr −1 ) for theperiod 2006–2013 leads to an optimal agreement (i.e., lowest RMSD) betweenmodel results and observations.

Model simulations of atmospheric methane (1997–2016) and their evaluation using NOAA and AGAGE surface and IAGOS-CARIBIC aircraft observations