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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
Authors:
 [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:
Type:
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
Publisher:
European Geosciences Union
Research Org:
Karlsruhe Inst. of Technology (KIT) Garmisch-Partenkirchen (Germany)
Sponsoring Org:
USDOE
Country of Publication:
United States
Language:
English
Subject:
54 ENVIRONMENTAL SCIENCES
OSTI Identifier:
1375417

Ostler, Andreas, Sussmann, Ralf, Patra, Prabir K., Houweling, Sander, De Bruine, Marko, Stiller, Gabriele P., Haenel, Florian J., Plieninger, Johannes, Bousquet, Philippe, Yin, Yi, Saunois, Marielle, Walker, Kaley A., Deutscher, Nicholas M., Griffith, David W. T., Blumenstock, Thomas, Hase, Frank, Warneke, Thorsten, Wang, Zhiting, Kivi, Rigel, and Robinson, John. Evaluation of column-averaged methane in models and TCCON with a focus on the stratosphere. United States: N. p., Web. doi:10.5194/amt-9-4843-2016.
Ostler, Andreas, Sussmann, Ralf, Patra, Prabir K., Houweling, Sander, De Bruine, Marko, Stiller, Gabriele P., Haenel, Florian J., Plieninger, Johannes, Bousquet, Philippe, Yin, Yi, Saunois, Marielle, Walker, Kaley A., Deutscher, Nicholas M., Griffith, David W. T., Blumenstock, Thomas, Hase, Frank, Warneke, Thorsten, Wang, Zhiting, Kivi, Rigel, & Robinson, John. Evaluation of column-averaged methane in models and TCCON with a focus on the stratosphere. United States. doi:10.5194/amt-9-4843-2016.
Ostler, Andreas, Sussmann, Ralf, Patra, Prabir K., Houweling, Sander, De Bruine, Marko, Stiller, Gabriele P., Haenel, Florian J., Plieninger, Johannes, Bousquet, Philippe, Yin, Yi, Saunois, Marielle, Walker, Kaley A., Deutscher, Nicholas M., Griffith, David W. T., Blumenstock, Thomas, Hase, Frank, Warneke, Thorsten, Wang, Zhiting, Kivi, Rigel, and Robinson, John. 2016. "Evaluation of column-averaged methane in models and TCCON with a focus on the stratosphere". United States. doi:10.5194/amt-9-4843-2016. https://www.osti.gov/servlets/purl/1375417.
@article{osti_1375417,
title = {Evaluation of column-averaged methane in models and TCCON with a focus on the stratosphere},
author = {Ostler, Andreas and Sussmann, Ralf and Patra, Prabir K. and Houweling, Sander and De Bruine, Marko and Stiller, Gabriele P. and Haenel, Florian J. and Plieninger, Johannes and Bousquet, Philippe and Yin, Yi and Saunois, Marielle and Walker, Kaley A. and Deutscher, Nicholas M. and Griffith, David W. T. and Blumenstock, Thomas and Hase, Frank and Warneke, Thorsten and Wang, Zhiting and Kivi, Rigel and Robinson, John},
abstractNote = {The distribution of methane (CH4) in the stratosphere can be a major driver of spatial variability in the dry-air column-averaged CH4 mixing ratio (XCH4), which is being measured increasingly for the assessment of CH4 surface emissions. Chemistry-transport models (CTMs) therefore need to simulate the tropospheric and stratospheric fractional columns of XCH4 accurately for estimating surface emissions from XCH4. Simulations from three CTMs are tested against XCH4 observations from the Total Carbon Column Network (TCCON). We analyze how the model–TCCON agreement in XCH4 depends on the model representation of stratospheric CH4 distributions. Model equivalents of TCCON XCH4 are computed with stratospheric CH4 fields from both the model simulations and from satellite-based CH4 distributions from MIPAS (Michelson Interferometer for Passive Atmospheric Sounding) and MIPAS CH4 fields adjusted to ACE-FTS (Atmospheric Chemistry Experiment Fourier Transform Spectrometer) observations. Using MIPAS-based stratospheric CH4 fields in place of model simulations improves the model–TCCON XCH4 agreement for all models. For the Atmospheric Chemistry Transport Model (ACTM) the average XCH4 bias is significantly reduced from 38.1 to 13.7 ppb, whereas small improvements are found for the models TM5 (Transport Model, version 5; 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 CH4 fields adjusted to ACE-FTS reduces the average XCH4 bias for ACTM (3.3 ppb), but increases the average XCH4 bias for TM5 (10.8 ppb) and LMDz (20.0 ppb). These findings imply that model errors in simulating stratospheric CH4 contribute to model biases. Current satellite instruments cannot definitively measure stratospheric CH4 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 CH4 and, hence, its contribution to XCH4. 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 CH4 and XCH4.},
doi = {10.5194/amt-9-4843-2016},
journal = {Atmospheric Measurement Techniques (Online)},
number = 9,
volume = 9,
place = {United States},
year = {2016},
month = {9}
}

Works referenced in this record:

Bias corrections of GOSAT SWIR XCO2 and XCH4 with TCCON data and their evaluation using aircraft measurement data
journal, January 2016
  • Inoue, Makoto; Morino, Isamu; Uchino, Osamu
  • Atmospheric Measurement Techniques, Vol. 9, Issue 8, p. 3491-3512
  • DOI: 10.5194/amt-9-3491-2016