Articles | Volume 9, issue 9
https://doi.org/10.5194/amt-9-4843-2016
https://doi.org/10.5194/amt-9-4843-2016
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, Ralf Sussmann, Prabir K. Patra, Sander Houweling, Marko De Bruine, Gabriele P. Stiller, Florian J. Haenel, Johannes Plieninger, Philippe Bousquet, Yi Yin, Marielle Saunois, Kaley A. Walker, Nicholas M. Deutscher, David W. T. Griffith, Thomas Blumenstock, Frank Hase, Thorsten Warneke, Zhiting Wang, Rigel Kivi, and John Robinson

Related authors

The imprint of stratospheric transport on column-averaged methane
A. Ostler, R. Sussmann, P. K. Patra, P. O. Wennberg, N. M. Deutscher, D. W. T. Griffith, T. Blumenstock, F. Hase, R. Kivi, T. Warneke, Z. Wang, M. De Mazière, J. Robinson, and H. Ohyama
Atmos. Chem. Phys. Discuss., https://doi.org/10.5194/acpd-15-20395-2015,https://doi.org/10.5194/acpd-15-20395-2015, 2015
Preprint withdrawn
Short summary
Multistation intercomparison of column-averaged methane from NDACC and TCCON: impact of dynamical variability
A. Ostler, R. Sussmann, M. Rettinger, N. M. Deutscher, S. Dohe, F. Hase, N. Jones, M. Palm, and B.-M. Sinnhuber
Atmos. Meas. Tech., 7, 4081–4101, https://doi.org/10.5194/amt-7-4081-2014,https://doi.org/10.5194/amt-7-4081-2014, 2014
Short summary
Retrieval of cirrus cloud optical thickness and top altitude from geostationary remote sensing
S. Kox, L. Bugliaro, and A. Ostler
Atmos. Meas. Tech., 7, 3233–3246, https://doi.org/10.5194/amt-7-3233-2014,https://doi.org/10.5194/amt-7-3233-2014, 2014

Related subject area

Subject: Gases | Technique: Remote Sensing | Topic: Validation and Intercomparisons
Using a portable FTIR spectrometer to evaluate the consistency of Total Carbon Column Observing Network (TCCON) measurements on a global scale: the Collaborative Carbon Column Observing Network (COCCON) travel standard
Benedikt Herkommer, Carlos Alberti, Paolo Castracane, Jia Chen, Angelika Dehn, Florian Dietrich, Nicholas M. Deutscher, Matthias Max Frey, Jochen Groß, Lawson Gillespie, Frank Hase, Isamu Morino, Nasrin Mostafavi Pak, Brittany Walker, and Debra Wunch
Atmos. Meas. Tech., 17, 3467–3494, https://doi.org/10.5194/amt-17-3467-2024,https://doi.org/10.5194/amt-17-3467-2024, 2024
Short summary
Comparison of the H2O, HDO and δD stratospheric climatologies between the MIPAS-ESA V8, MIPAS-IMK V5 and ACE-FTS V4.1/4.2 satellite datasets
Karen De Los Ríos, Paulina Ordoñez, Gabriele P. Stiller, Piera Raspollini, Marco Gai, Kaley A. Walker, Cristina Peña-Ortiz, and Luis Acosta
Atmos. Meas. Tech., 17, 3401–3418, https://doi.org/10.5194/amt-17-3401-2024,https://doi.org/10.5194/amt-17-3401-2024, 2024
Short summary
TROPESS-CrIS CO single-pixel vertical profiles: intercomparisons with MOPITT and model simulations for 2020 western US wildfires
Ming Luo, Helen M. Worden, Robert D. Field, Kostas Tsigaridis, and Gregory S. Elsaesser
Atmos. Meas. Tech., 17, 2611–2624, https://doi.org/10.5194/amt-17-2611-2024,https://doi.org/10.5194/amt-17-2611-2024, 2024
Short summary
TOLNet validation of satellite ozone profiles in the troposphere: impact of retrieval wavelengths
Matthew S. Johnson, Alexei Rozanov, Mark Weber, Nora Mettig, John Sullivan, Michael J. Newchurch, Shi Kuang, Thierry Leblanc, Fernando Chouza, Timothy A. Berkoff, Guillaume Gronoff, Kevin B. Strawbridge, Raul J. Alvarez, Andrew O. Langford, Christoph J. Senff, Guillaume Kirgis, Brandi McCarty, and Larry Twigg
Atmos. Meas. Tech., 17, 2559–2582, https://doi.org/10.5194/amt-17-2559-2024,https://doi.org/10.5194/amt-17-2559-2024, 2024
Short summary
An uncertainty methodology for solar occultation flux measurements: ammonia emissions from livestock production
Johan Mellqvist, Nathalia T. Vechi, Charlotte Scheutz, Marc Durif, Francois Gautier, John Johansson, Jerker Samuelsson, Brian Offerle, and Samuel Brohede
Atmos. Meas. Tech., 17, 2465–2479, https://doi.org/10.5194/amt-17-2465-2024,https://doi.org/10.5194/amt-17-2465-2024, 2024
Short summary

Cited articles

Alexe, M., Bergamaschi, P., Segers, A., Detmers, R., Butz, A., Hasekamp, O., Guerlet, S., Parker, R., Boesch, H., Frankenberg, C., Scheepmaker, R. A., Dlugokencky, E., Sweeney, C., Wofsy, S. C., and Kort, E. A.: Inverse modelling of CH4 emissions for 2010–2011 using different satellite retrieval products from GOSAT and SCIAMACHY, Atmos. Chem. Phys., 15, 113–133, https://doi.org/10.5194/acp-15-113-2015, 2015.
Belikov, D. A., Maksyutov, S., Sherlock, V., Aoki, S., Deutscher, N. M., Dohe, S., Griffith, D., Kyro, E., Morino, I., Nakazawa, T., Notholt, J., Rettinger, M., Schneider, M., Sussmann, R., Toon, G. C., Wennberg, P. O., and Wunch, D.: Simulations of column-averaged CO2 and CH4 using the NIES TM with a hybrid sigma-isentropic (σθ) vertical coordinate, Atmos. Chem. Phys., 13, 1713–1732, https://doi.org/10.5194/acp-13-1713-2013, 2013.
Bergamaschi, P., Krol, M., Dentener, F., Vermeulen, A., Meinhardt, F., Graul, R., Ramonet, M., Peters, W., and Dlugokencky, E. J.: Inverse modelling of national and European CH4 emissions using the atmospheric zoom model TM5, Atmos. Chem. Phys., 5, 2431–2460, https://doi.org/10.5194/acp-5-2431-2005, 2005.
Bergamaschi, P., Houweling, S., Segers, A., Krol, M., Frankenberg, C., Scheepmaker, R. A., Dlugokencky, E., Wofsy, S. C., Kort, E. A., Sweeney, C., Schuck, T., Brenninkmeijer, C., Chen, H., Beck, V., and Gerbig, C.: Atmospheric CH4 in the first decade of the 21st century: inverse modeling analysis using SCIAMACHY satellite retrievals and NOAA surface measurements, J. Geophys. Res., 118, 7350–7369, https://doi.org/10.1002/jgrd.50480, 2013.
Download
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.