1SRON Netherlands Institute for Space Research, Utrecht, the Netherlands
2Institute for Marine and Atmospheric Research (IMAU), Utrecht University, Utrecht, the Netherlands
3Department of Meteorology and Air Quality (MAQ), Wageningen University and Research Centre, Wageningen, the Netherlands
4European Commission Joint Research Centre, Institute for Environment and Sustainability, Ispra (Va), Italy
5Jet Propulsion Laboratory, Pasadena, CA, USA
6NOAA Earth System Research Laboratory, Global Monitoring Division, Boulder, CO, USA
7Center for Global Environmental Research, National Institute for Environmental Studies (NIES) Onogawa 16-2, Tsukuba, Ibaraki 305-8506, Japan
8Institute of Environmental Physics, University of Bremen, Bremen, Germany
9National Institute of Water and Atmospheric Research (NIWA), P.O. Box 14-901, Wellington, New Zealand
10Caltech, Pasadena, CA, USA
11Max Planck Institute for Biogeochemistry, Jena, Germany
12Center for Isotope Research (CIO), University of Groningen, the Netherlands
13CIRES, University of Colorado, Boulder, CO, USA
14Department of Atmospheric, Oceanic and Space Sciences, University of Michigan, Ann Arbor, MI, USA
Received: 21 Aug 2013 – Published in Atmos. Chem. Phys. Discuss.: 30 Oct 2013
Abstract. This study investigates the use of total column CH4 (XCH4) retrievals from the SCIAMACHY satellite instrument for quantifying large-scale emissions of methane. A unique data set from SCIAMACHY is available spanning almost a decade of measurements, covering a period when the global CH4 growth rate showed a marked transition from stable to increasing mixing ratios. The TM5 4DVAR inverse modelling system has been used to infer CH4 emissions from a combination of satellite and surface measurements for the period 2003–2010. In contrast to earlier inverse modelling studies, the SCIAMACHY retrievals have been corrected for systematic errors using the TCCON network of ground-based Fourier transform spectrometers. The aim is to further investigate the role of bias correction of satellite data in inversions. Methods for bias correction are discussed, and the sensitivity of the optimized emissions to alternative bias correction functions is quantified. It is found that the use of SCIAMACHY retrievals in TM5 4DVAR increases the estimated inter-annual variability of large-scale fluxes by 22% compared with the use of only surface observations. The difference in global methane emissions between 2-year periods before and after July 2006 is estimated at 27–35 Tg yr−1. The use of SCIAMACHY retrievals causes a shift in the emissions from the extra-tropics to the tropics of 50 ± 25 Tg yr−1. The large uncertainty in this value arises from the uncertainty in the bias correction functions. Using measurements from the HIPPO and BARCA aircraft campaigns, we show that systematic errors in the SCIAMACHY measurements are a main factor limiting the performance of the inversions. To further constrain tropical emissions of methane using current and future satellite missions, extended validation capabilities in the tropics are of critical importance.
Revised: 02 Mar 2014 – Accepted: 07 Mar 2014 – Published: 22 Apr 2014
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Houweling, S., Krol, M., Bergamaschi, P., Frankenberg, C., Dlugokencky, E. J., Morino, I., Notholt, J., Sherlock, V., Wunch, D., Beck, V., Gerbig, C., Chen, H., Kort, E. A., Röckmann, T., and Aben, I.: A multi-year methane inversion using SCIAMACHY, accounting for systematic errors using TCCON measurements, Atmos. Chem. Phys., 14, 3991-4012, doi:10.5194/acp-14-3991-2014, 2014.