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Geoscientific Model Development An interactive open-access journal of the European Geosciences Union
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Volume 10, issue 3
Geosci. Model Dev., 10, 1261-1289, 2017
https://doi.org/10.5194/gmd-10-1261-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.
Geosci. Model Dev., 10, 1261-1289, 2017
https://doi.org/10.5194/gmd-10-1261-2017
© Author(s) 2017. This work is distributed under
the Creative Commons Attribution 3.0 License.

Model evaluation paper 27 Mar 2017

Model evaluation paper | 27 Mar 2017

Global methane emission estimates for 2000–2012 from CarbonTracker Europe-CH4 v1.0

Aki Tsuruta1, Tuula Aalto1, Leif Backman1, Janne Hakkarainen2, Ingrid T. van der Laan-Luijkx3,5, Maarten C. Krol3,4,5, Renato Spahni6, Sander Houweling4,5, Marko Laine2, Ed Dlugokencky7, Angel J. Gomez-Pelaez8, Marcel van der Schoot9, Ray Langenfelds9, Raymond Ellul10, Jgor Arduini11,12, Francesco Apadula13, Christoph Gerbig14, Dietrich G. Feist14, Rigel Kivi15, Yukio Yoshida16, and Wouter Peters3,17 Aki Tsuruta et al.
  • 1Climate Research, Finnish Meteorological Institute, Helsinki, Finland
  • 2Earth Observation, Finnish Meteorological Institute, Helsinki, Finland
  • 3Meteorology and Air Quality, Wageningen University & Research, Wageningen, the Netherlands
  • 4SRON Netherlands Institute for Space Research, Utrecht, the Netherlands
  • 5Institute for Marine and Atmospheric Research, Utrecht University, Utrecht, the Netherlands
  • 6Climate and Environmental Physics, Physics Institute, and Oeschger Centre for Climate Change Research, University of Bern, Bern, Switzerland
  • 7NOAA Earth System Research Laboratory, Global Monitoring Division, Boulder, Colorado, USA
  • 8Izaña Atmospheric Research Center, Agencia Estatal de Meteorología (AEMET), Tenerife, Spain
  • 9CSIRO Oceans and Atmosphere, Aspendale, Australia
  • 10Atmospheric Research, Department of Geosciences, University of Malta, Msida, Malta
  • 11Department of Pure and Applied Sciences, University of Urbino, Urbino, Italy
  • 12National Research Council, Institute of Atmospheric Sciences and Climate, Bologna, Italy
  • 13Ricerca sul Sistema Energetico – RSE SpA, Milano, Italy
  • 14Max Planck Institute for Biogeochemistry, Jena, Germany
  • 15Arctic Research, Finnish Meteorological Institute, Sodankylä, Finland
  • 16Center for Global Environmental Research, National Institute for Environmental Studies, Tsukuba, Ibaraki, Japan
  • 17University of Groningen, Centre for Isotope Research, Groningen, the Netherlands

Abstract. We present a global distribution of surface methane (CH4) emission estimates for 2000–2012 derived using the CarbonTracker Europe-CH4 (CTE-CH4) data assimilation system. In CTE-CH4, anthropogenic and biospheric CH4 emissions are simultaneously estimated based on constraints of global atmospheric in situ CH4 observations. The system was configured to either estimate only anthropogenic or biospheric sources per region, or to estimate both categories simultaneously. The latter increased the number of optimizable parameters from 62 to 78. In addition, the differences between two numerical schemes available to perform turbulent vertical mixing in the atmospheric transport model TM5 were examined. Together, the system configurations encompass important axes of uncertainty in inversions and allow us to examine the robustness of the flux estimates. The posterior emission estimates are further evaluated by comparing simulated atmospheric CH4 to surface in situ observations, vertical profiles of CH4 made by aircraft, remotely sensed dry-air total column-averaged mole fraction (XCH4) from the Total Carbon Column Observing Network (TCCON), and XCH4 from the Greenhouse gases Observing Satellite (GOSAT). The evaluation with non-assimilated observations shows that posterior XCH4 is better matched with the retrievals when the vertical mixing scheme with faster interhemispheric exchange is used. Estimated posterior mean total global emissions during 2000–2012 are 516±51Tg CH4yr−1, with an increase of 18Tg CH4yr−1 from 2000–2006 to 2007–2012. The increase is mainly driven by an increase in emissions from South American temperate, Asian temperate and Asian tropical TransCom regions. In addition, the increase is hardly sensitive to different model configurations ( < 2Tg CH4yr−1 difference), and much smaller than suggested by EDGAR v4.2 FT2010 inventory (33Tg CH4yr−1), which was used for prior anthropogenic emission estimates. The result is in good agreement with other published estimates from inverse modelling studies (16–20Tg CH4yr−1). However, this study could not conclusively separate a small trend in biospheric emissions (−5 to +6.9Tg CH4yr−1) from the much larger trend in anthropogenic emissions (15–27Tg CH4yr−1). Finally, we find that the global and North American CH4 balance could be closed over this time period without the previously suggested need to strongly increase anthropogenic CH4 emissions in the United States. With further developments, especially on the treatment of the atmospheric CH4 sink, we expect the data assimilation system presented here will be able to contribute to the ongoing interpretation of changes in this important greenhouse gas budget.

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In this study, we found that the average global methane emission for 2000–2012, estimated by the CTE-CH4 model, was 516±51 Tg CH4 yr-1, and the estimates for 2007–2012 were 4 % larger than for 2000–2006. The model estimates are sensitive to inputs and setups, but according to sensitivity tests the study suggests that the increase in atmospheric methane concentrations during 21st century was due to an increase in emissions from the 35S-EQ latitudinal bands.
In this study, we found that the average global methane emission for 2000–2012, estimated by the...
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