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Title: Evaluation of column-averaged methane in models and TCCON with a focus on the stratosphere

The distribution of methane (CH 4) in the stratosphere can be a major driver of spatial variability in the dry-air column-averaged CH 4 mixing ratio (XCH 4), which is being measured increasingly for the assessment of CH 4 surface emissions. Chemistry-transport models (CTMs) therefore need to simulate the tropospheric and stratospheric fractional columns of XCH 4 accurately for estimating surface emissions from XCH 4. Simulations from three CTMs are tested against XCH 4 observations from the Total Carbon Column Network (TCCON). We analyze how the model–TCCON agreement in XCH 4 depends on the model representation of stratospheric CH 4 distributions. Model equivalents of TCCON XCH 4 are computed with stratospheric CH 4 fields from both the model simulations and from satellite-based CH 4 distributions from MIPAS (Michelson Interferometer for Passive Atmospheric Sounding) and MIPAS CH 4 fields adjusted to ACE-FTS (Atmospheric Chemistry Experiment Fourier Transform Spectrometer) observations. Using MIPAS-based stratospheric CH 4 fields in place of model simulations improves the model–TCCON XCH 4 agreement for all models. For the Atmospheric Chemistry Transport Model (ACTM) the average XCH 4 bias is significantly reduced from 38.1 to 13.7 ppb, whereas small improvements are found for the models TM5 (Transport Model, version 5;more » from 8.7 to 4.3 ppb) and LMDz (Laboratoire de Météorologie Dynamique model with zooming capability; from 6.8 to 4.3 ppb). Replacing model simulations with MIPAS stratospheric CH 4 fields adjusted to ACE-FTS reduces the average XCH 4 bias for ACTM (3.3 ppb), but increases the average XCH 4 bias for TM5 (10.8 ppb) and LMDz (20.0 ppb). These findings imply that model errors in simulating stratospheric CH 4 contribute to model biases. Current satellite instruments cannot definitively measure stratospheric CH 4 to sufficient accuracy to eliminate these biases. Applying transport diagnostics to the models indicates that model-to-model differences in the simulation of stratospheric transport, notably the age of stratospheric air, can largely explain the inter-model spread in stratospheric CH 4 and, hence, its contribution to XCH 4. Furthermore, it would be worthwhile to analyze how individual model components (e.g., physical parameterization, meteorological data sets, model horizontal/vertical resolution) impact the simulation of stratospheric CH 4 and XCH 4.« less
 [1] ;  [1] ;  [2] ;  [3] ;  [4] ;  [5] ;  [5] ;  [5] ;  [6] ;  [6] ;  [6] ;  [7] ;  [8] ;  [9] ;  [10] ;  [10] ;  [11] ;  [11] ;  [12] ;  [13]
  1. Karlsruhe Institute of Technology, Garmisch-Partenkirchen (Germany)
  2. Research Institute for Global Change, Yokohama (Japan)
  3. Utrecht Univ., Utrecht (The Netherlands); SRON Netherlands Institute for Space Research, Utrecht (The Netherlands)
  4. Utrecht Univ., Utrecht (The Netherlands)
  5. Karlsruhe Institute of Technology, Karlsruhe (Germany)
  6. Lab. des Sciences du Climat et de l'Environnement, Gif-sur-Yvette (France); Univ. de Versailles Saint Quentin en Yvelines, Versaille (France)
  7. Univ. of Toronto, Toronto, ON (Canada)
  8. Univ. of Wollongong, Wollongong (Australia); Univ. of Bremen, Bremen (Germany)
  9. Univ. of Wollongong, Wollongong (Australia)
  10. Lab. des Sciences du Climat et de l'Environnement, Gif-sur-Yvette (France)
  11. Univ. of Bremen, Bremen (Germany)
  12. Finnish Meteorological Institute, Sodankyla (Finland)
  13. National Institute of Water and Atmospheric Research (NIWA) Ltd., Wellington (New Zealand)
Publication Date:
Accepted Manuscript
Journal Name:
Atmospheric Measurement Techniques (Online)
Additional Journal Information:
Journal Name: Atmospheric Measurement Techniques (Online); Journal Volume: 9; Journal Issue: 9; Journal ID: ISSN 1867-8548
European Geosciences Union
Research Org:
Karlsruhe Inst. of Technology (KIT) Garmisch-Partenkirchen (Germany)
Sponsoring Org:
Country of Publication:
United States
OSTI Identifier: