Articles | Volume 9, issue 9
https://doi.org/10.5194/amt-9-4843-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/amt-9-4843-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Research article
| 
28 Sep 2016
Research article |
| 28 Sep 2016
Evaluation of column-averaged methane in models and TCCON with a focus on the stratosphere
Andreas Ostler
Karlsruhe Institute of Technology, IMK-IFU, 82467 Garmisch-Partenkirchen, Germany
Karlsruhe Institute of Technology, IMK-IFU, 82467 Garmisch-Partenkirchen, Germany
Prabir K. Patra
Research Institute for Global Change, JAMSTEC, Yokohama, 236-0001, Japan
Sander Houweling
Institute for Marine and Atmospheric Research Utrecht, Utrecht University, 3584 CC Utrecht, the Netherlands
SRON Netherlands Institute for Space Research, 3584 CA Utrecht, the Netherlands
Marko De Bruine
Institute for Marine and Atmospheric Research Utrecht, Utrecht University, 3584 CC Utrecht, the Netherlands
Gabriele P. Stiller
Karlsruhe Institute of Technology, IMK-ASF, 76021 Karlsruhe, Germany
Florian J. Haenel
Karlsruhe Institute of Technology, IMK-ASF, 76021 Karlsruhe, Germany
Johannes Plieninger
Karlsruhe Institute of Technology, IMK-ASF, 76021 Karlsruhe, Germany
Philippe Bousquet
Laboratoire des Sciences du Climat et de l'Environnement, IPSL-LSCE, CEA-CNRS-UVSQ, UMR8212, 91191 Gif-sur-Yvette, France
Université de Versailles Saint Quentin en Yvelines, 78000 Versaille, France
Laboratoire des Sciences du Climat et de l'Environnement, IPSL-LSCE, CEA-CNRS-UVSQ, UMR8212, 91191 Gif-sur-Yvette, France
Université de Versailles Saint Quentin en Yvelines, 78000 Versaille, France
Marielle Saunois
Laboratoire des Sciences du Climat et de l'Environnement, IPSL-LSCE, CEA-CNRS-UVSQ, UMR8212, 91191 Gif-sur-Yvette, France
Université de Versailles Saint Quentin en Yvelines, 78000 Versaille, France
Kaley A. Walker
Department of Physics, University of Toronto, Toronto, Ontario M5S 1A7, Canada
Nicholas M. Deutscher
School of Chemistry, University of Wollongong, Wollongong, NSW 2522, Australia
Institute of Environmental Physics, University of Bremen, 28334 Bremen, Germany
David W. T. Griffith
School of Chemistry, University of Wollongong, Wollongong, NSW 2522, Australia
Thomas Blumenstock
Laboratoire des Sciences du Climat et de l'Environnement, IPSL-LSCE, CEA-CNRS-UVSQ, UMR8212, 91191 Gif-sur-Yvette, France
Frank Hase
Laboratoire des Sciences du Climat et de l'Environnement, IPSL-LSCE, CEA-CNRS-UVSQ, UMR8212, 91191 Gif-sur-Yvette, France
Thorsten Warneke
Institute of Environmental Physics, University of Bremen, 28334 Bremen, Germany
Zhiting Wang
Institute of Environmental Physics, University of Bremen, 28334 Bremen, Germany
Rigel Kivi
Finnish Meteorological Institute, Arctic Research Center, 99600 Sodankylä, Finland
John Robinson
Department of Atmospheric Research, National Institute of Water and Atmospheric Research
(NIWA) Ltd, Wellington 6021, New Zealand
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Cited
20 citations as recorded by crossref.
- Improved Chemical Tracer Simulation by MIROC4.0-based Atmospheric Chemistry-Transport Model (MIROC4-ACTM) P. Patra et al. 10.2151/sola.2018-016
- Contributions of the troposphere and stratosphere to CH4 model biases Z. Wang et al. 10.5194/acp-17-13283-2017
- Influence of methane emissions on the GHG emissions of fossil fuels B. Pieprzyk & P. Hilje 10.1002/bbb.1959
- Analysis of total column CO2 and CH4 measurements in Berlin with WRF-GHG X. Zhao et al. 10.5194/acp-19-11279-2019
- Characterizing model errors in chemical transport modeling of methane: using GOSAT XCH4 data with weak-constraint four-dimensional variational data assimilation I. Stanevich et al. 10.5194/acp-21-9545-2021
- Investigation of the renewed methane growth post-2007 with high-resolution 3-D variational inverse modeling and isotopic constraints J. Thanwerdas et al. 10.5194/acp-24-2129-2024
- The arctic seasonal cycle of total column CO2 and CH4 from ground-based solar and lunar FTIR absorption spectrometry M. Buschmann et al. 10.5194/amt-10-2397-2017
- Evaluation of single-footprint AIRS CH4 profile retrieval uncertainties using aircraft profile measurements S. Kulawik et al. 10.5194/amt-14-335-2021
- How do Cl concentrations matter for the simulation of CH4 and δ13C(CH4) and estimation of the CH4 budget through atmospheric inversions? J. Thanwerdas et al. 10.5194/acp-22-15489-2022
- CH4 Fluxes Derived from Assimilation of TROPOMI XCH4 in CarbonTracker Europe-CH4: Evaluation of Seasonality and Spatial Distribution in the Northern High Latitudes A. Tsuruta et al. 10.3390/rs15061620
- Characterizing model errors in chemical transport modeling of methane: impact of model resolution in versions v9-02 of GEOS-Chem and v35j of its adjoint model I. Stanevich et al. 10.5194/gmd-13-3839-2020
- Seasonal variability of stratospheric methane: implications for constraining tropospheric methane budgets using total column observations K. Saad et al. 10.5194/acp-16-14003-2016
- Retrieval of atmospheric CH4 vertical information from ground-based FTS near-infrared spectra M. Zhou et al. 10.5194/amt-12-6125-2019
- Influences of Uncertainties in the STT Flux on Modeled Tropospheric Methane Z. Wang 10.1029/2023JD039107
- Atmospheric CO and CH4 time series and seasonal variations on Reunion Island from ground-based in situ and FTIR (NDACC and TCCON) measurements M. Zhou et al. 10.5194/acp-18-13881-2018
- New ground-based Fourier-transform near-infrared solar absorption measurements of XCO2, XCH4 and XCO at Xianghe, China Y. Yang et al. 10.5194/essd-12-1679-2020
- The Methane Isotopologues by Solar Occultation (MISO) Nanosatellite Mission: Spectral Channel Optimization and Early Performance Analysis D. Weidmann et al. 10.3390/rs9101073
- Intercomparison of low- and high-resolution infrared spectrometers for ground-based solar remote sensing measurements of total column concentrations of CO2, CH4, and CO M. Sha et al. 10.5194/amt-13-4791-2020
- Global inverse modeling of CH4 sources and sinks: an overview of methods S. Houweling et al. 10.5194/acp-17-235-2017
- Coupled Stratospheric Chemistry–Meteorology Data Assimilation. Part I: Physical Background and Coupled Modeling Aspects R. Ménard et al. 10.3390/atmos11020150
20 citations as recorded by crossref.
- Improved Chemical Tracer Simulation by MIROC4.0-based Atmospheric Chemistry-Transport Model (MIROC4-ACTM) P. Patra et al. 10.2151/sola.2018-016
- Contributions of the troposphere and stratosphere to CH4 model biases Z. Wang et al. 10.5194/acp-17-13283-2017
- Influence of methane emissions on the GHG emissions of fossil fuels B. Pieprzyk & P. Hilje 10.1002/bbb.1959
- Analysis of total column CO2 and CH4 measurements in Berlin with WRF-GHG X. Zhao et al. 10.5194/acp-19-11279-2019
- Characterizing model errors in chemical transport modeling of methane: using GOSAT XCH4 data with weak-constraint four-dimensional variational data assimilation I. Stanevich et al. 10.5194/acp-21-9545-2021
- Investigation of the renewed methane growth post-2007 with high-resolution 3-D variational inverse modeling and isotopic constraints J. Thanwerdas et al. 10.5194/acp-24-2129-2024
- The arctic seasonal cycle of total column CO2 and CH4 from ground-based solar and lunar FTIR absorption spectrometry M. Buschmann et al. 10.5194/amt-10-2397-2017
- Evaluation of single-footprint AIRS CH4 profile retrieval uncertainties using aircraft profile measurements S. Kulawik et al. 10.5194/amt-14-335-2021
- How do Cl concentrations matter for the simulation of CH4 and δ13C(CH4) and estimation of the CH4 budget through atmospheric inversions? J. Thanwerdas et al. 10.5194/acp-22-15489-2022
- CH4 Fluxes Derived from Assimilation of TROPOMI XCH4 in CarbonTracker Europe-CH4: Evaluation of Seasonality and Spatial Distribution in the Northern High Latitudes A. Tsuruta et al. 10.3390/rs15061620
- Characterizing model errors in chemical transport modeling of methane: impact of model resolution in versions v9-02 of GEOS-Chem and v35j of its adjoint model I. Stanevich et al. 10.5194/gmd-13-3839-2020
- Seasonal variability of stratospheric methane: implications for constraining tropospheric methane budgets using total column observations K. Saad et al. 10.5194/acp-16-14003-2016
- Retrieval of atmospheric CH4 vertical information from ground-based FTS near-infrared spectra M. Zhou et al. 10.5194/amt-12-6125-2019
- Influences of Uncertainties in the STT Flux on Modeled Tropospheric Methane Z. Wang 10.1029/2023JD039107
- Atmospheric CO and CH4 time series and seasonal variations on Reunion Island from ground-based in situ and FTIR (NDACC and TCCON) measurements M. Zhou et al. 10.5194/acp-18-13881-2018
- New ground-based Fourier-transform near-infrared solar absorption measurements of XCO2, XCH4 and XCO at Xianghe, China Y. Yang et al. 10.5194/essd-12-1679-2020
- The Methane Isotopologues by Solar Occultation (MISO) Nanosatellite Mission: Spectral Channel Optimization and Early Performance Analysis D. Weidmann et al. 10.3390/rs9101073
- Intercomparison of low- and high-resolution infrared spectrometers for ground-based solar remote sensing measurements of total column concentrations of CO2, CH4, and CO M. Sha et al. 10.5194/amt-13-4791-2020
- Global inverse modeling of CH4 sources and sinks: an overview of methods S. Houweling et al. 10.5194/acp-17-235-2017
- Coupled Stratospheric Chemistry–Meteorology Data Assimilation. Part I: Physical Background and Coupled Modeling Aspects R. Ménard et al. 10.3390/atmos11020150
Latest update: 01 Jul 2025
Short summary
Our evaluation of column-averaged methane (XCH4) in models and TCCON reveals latitudinal biases between 0.4 % and 2.1 % originating from an inter-model spread in stratospheric CH4. Substituting model stratospheric CH4 fields by satellite data significantly reduces the large XCH4 bias observed for one model. For other models, showing only minor biases, the impact is ambiguous; i.e., the satellite uncertainty range hinders a more accurate model evaluation needed to improve inverse modeling.
Our evaluation of column-averaged methane (XCH4) in models and TCCON reveals latitudinal biases...
