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

• Main Authors: P. H. Zimmermann, C. A. M. Brenninkmeijer, A. Pozzer, P. Jöckel, F. Winterstein, A. Zahn, S. Houweling, J. Lelieveld
• Format: Article
• Language: English
• Published: Copernicus Publications 2020-05-01
• Series: Atmospheric Chemistry and Physics
• Online Access: https://www.atmos-chem-phys.net/20/5787/2020/acp-20-5787-2020.pdf

<p>Methane (<span class="inline-formula">CH₄</span>) is an important greenhouse gas, and its atmospheric budget is determined by interacting sources and sinks in a dynamic global environment. Methane observations indicate that after almost a decade of stagnation, from 2006, a sudden and continuing global mixing ratio increase took place. We applied a general circulation model to simulate the global atmospheric budget, variability, and trends of methane for the period 1997–2016. Using interannually constant <span class="inline-formula">CH₄</span> a priori emissions from 11 biogenic and fossil source categories, the model results are compared with observations from 17 Advanced Global Atmospheric Gases Experiment (AGAGE) and National Oceanic and Atmospheric Administration (NOAA) surface stations and intercontinental Civil Aircraft for the Regular observation of the atmosphere Based on an Instrumented Container (CARIBIC) flights, with &gt;&thinsp;4800 <span class="inline-formula">CH₄</span> samples, gathered on &gt;&thinsp;320 flights in the upper troposphere and lowermost stratosphere.</p> <p>Based on a simple optimization procedure, methane emission categories have been scaled to reduce discrepancies with the observational data for the period 1997–2006. With this approach, the all-station mean dry air mole fraction of 1780&thinsp;nmol&thinsp;mol<span class="inline-formula">⁻¹</span> could be improved from an a priori root mean square deviation (RMSD) of 1.31&thinsp;% to just 0.61&thinsp;%, associated with a coefficient of determination (<span class="inline-formula"><i>R</i>²</span>) of 0.79. The simulated a priori interhemispheric difference of 143.12&thinsp;nmol&thinsp;mol<span class="inline-formula">⁻¹</span> was improved to 131.28&thinsp;nmol&thinsp;mol<span class="inline-formula">⁻¹</span>, which matched the observations quite well (130.82&thinsp;nmol&thinsp;mol<span class="inline-formula">⁻¹</span>).</p> <p>Analogously, aircraft measurements were reproduced well, with a global RMSD of 1.1&thinsp;% for the measurements before 2007, with even better results on a regional level (e.g., over India, with an RMSD of 0.98&thinsp;% and <span class="inline-formula"><i>R</i>²=0.65</span>). With regard to emission optimization, this implied a 30.2&thinsp;Tg&thinsp;<span class="inline-formula">CH₄</span>&thinsp;yr<span class="inline-formula">⁻¹</span> reduction in predominantly fossil-fuel-related emissions and a 28.7&thinsp;Tg&thinsp;<span class="inline-formula">CH₄</span>&thinsp;yr<span class="inline-formula">⁻¹</span> increase of biogenic sources.</p> <p>With the same methodology, the <span class="inline-formula">CH₄</span> growth that started in 2007 and continued almost linearly through 2013 was investigated, exploring the contributions by four potential causes, namely biogenic emissions from tropical wetlands, from agriculture including ruminant animals, and from rice cultivation, and anthropogenic emissions (fossil fuel sources, e.g., shale gas fracking) in North America. The optimization procedure adopted in this work showed that an increase in emissions from shale gas (7.67&thinsp;Tg&thinsp;yr<span class="inline-formula">⁻¹</span>), rice cultivation (7.15&thinsp;Tg&thinsp;yr<span class="inline-formula">⁻¹</span>), and tropical wetlands (0.58&thinsp;Tg&thinsp;yr<span class="inline-formula">⁻¹</span>) for the period 2006–2013 leads to an optimal agreement (i.e., lowest RMSD) between model results and observations.</p>