Articles | Volume 21, issue 3
Atmos. Chem. Phys., 21, 1717–1736, 2021
https://doi.org/10.5194/acp-21-1717-2021
Atmos. Chem. Phys., 21, 1717–1736, 2021
https://doi.org/10.5194/acp-21-1717-2021
Research article
09 Feb 2021
Research article | 09 Feb 2021

Atmospheric-methane source and sink sensitivity analysis using Gaussian process emulation

Angharad C. Stell et al.

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Cited articles

Bergamaschi, P., Brenninkmeijer, C. A. M., Hahn, M., Röckmann, T., Scharffe, D. H., Crutzen, P. J., Elansky, N. F., Belikov, I. B., Trivett, N. B. A., and Worthy, D. E. J.: Isotope analysis based source identification for atmospheric CH4 and CO sampled across Russia using the Trans-Siberian railroad, J. Geophys. Res.-Atmos., 103, 8227–8235, https://doi.org/10.1029/97JD03738, 1998. a
Bergamaschi, P., Houweling, S., Segers, A., Krol, M., Frankenberg, C., Scheepmaker, R. A., Dlugokencky, E., Wofsy, S. C., Kort, E. A., 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, https://doi.org/10.1002/jgrd.50480, 2013. a, b, c
Bloom, A. A., Bowman, K. W., Lee, M., Turner, A. J., Schroeder, R., Worden, J. R., Weidner, R., McDonald, K. C., and Jacob, D. J.: A global wetland methane emissions and uncertainty dataset for atmospheric chemical transport models (WetCHARTs version 1.0), Geosci. Model Dev., 10, 2141–2156, https://doi.org/10.5194/gmd-10-2141-2017, 2017. a, b
Bousquet, P., Ringeval, B., Pison, I., Dlugokencky, E. J., Brunke, E.-G., Carouge, C., Chevallier, F., Fortems-Cheiney, A., Frankenberg, C., Hauglustaine, D. A., Krummel, P. B., Langenfelds, R. L., Ramonet, M., Schmidt, M., Steele, L. P., Szopa, S., Yver, C., Viovy, N., and Ciais, P.: Source attribution of the changes in atmospheric methane for 2006–2008, Atmos. Chem. Phys., 11, 3689–3700, https://doi.org/10.5194/acp-11-3689-2011, 2011. a, b, c
Burkholder, J. B., Sander, S. P., Abbatt, J., Barker, J. R., Huie, R. E., Kolb, C. E., Kurylo, M. J., Orkin, V. L., Wilmouth, D. M., and Wine, P. H.: Chemical Kinetics and Photochemical Data for Use in Atmospheric Studies, Evaluation Number 18, Tech. Rep. 10, Jet Propulsion Laboratory, Pasadena, https://doi.org/10.1002/kin.550171010, 2015. a
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Short summary
Although it is the second-most important greenhouse gas, our understanding of the atmospheric-methane budget is limited. The uncertainty highlights the need for new tools to investigate sources and sinks. Here, we use a Gaussian process emulator to efficiently approximate the response of atmospheric-methane observations to changes in the most uncertain emission or loss processes. With this new method, we rigorously quantify the sensitivity of atmospheric observations to budget uncertainties.
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