Contributions of the troposphere and stratosphere to CH4 model biases

• Published in: Atmospheric Chemistry and Physics
• Main Authors: Wang, Zhiting, Warneke, Thorsten, Deutscher, Nicholas M., Notholt, Justus, Karstens, Ute, Saunois, Marielle, Schneider, Matthias, Sussmann, Ralf, Sembhi, Harjinder, Griffith, David W. T., Pollard, Dave F., Kivi, Rigel, Petri, Christof, Velazco, Voltaire A., Ramonet, Michel, Chen, Huilin
• Format: Article in Journal/Newspaper
• Language: English
• Published: European Geosciences Union (EGU), Copernicus Publications 2019
• Subjects: Ny-Ålesund; Sodankylä; Orleans; Ny Ålesund
• Online Access: https://www.atmos-chem-phys.net/17/13283/2017/; http://hdl.handle.net/2381/44825; https://doi.org/10.5194/acp-17-13283-2017

The TCCON data can be obtained from the TCCON Data Archive (http://tccondata.org/). The model outputs are from Marille Saunois (Laboratoire des Sciences du Climat et de l’Environnement, France) for LMDz-PYVAR, Ute Karstens (the Max Plank Institute for Biogeochemistry, Jena, Germany) for TM3, and Peter Bergamaschi (European Commission Joint Research Centre) for TM5-4DVAR. One should contact these authors directly considering the availability the model output. The GOSAT data UoL-OCPRv7, TES data F07_10 and HIPPO data are public available. Surface CH4 measurements from NOAA are publicly available. The in situ CH4 profile measurements by AirCore will become available via the EU project RINGO. Lamont-AirCore measurements have been provided by the Colm Sweeney at the NOAA Carbon Cycle and Greenhouse Gas Group Aircraft Program (http: //www.esrl.noaa.gov/gmd/ccgg/aircraft/). The AirCore data at Sodankylä are from the FTS group there. Inverse modelling is a useful tool for retrieving CH4 fluxes; however, evaluation of the applied chemical transport model is an important step before using the inverted emissions. For inversions using column data one concern is how well the model represents stratospheric and tropospheric CH4 when assimilating total column measurements. In this study atmospheric CH4 from three inverse models is compared to FTS (Fourier transform spectrometry), satellite and in situ measurements. Using the FTS measurements the model biases are separated into stratospheric and tropospheric contributions. When averaged over all FTS sites the model bias amplitudes (absolute model to FTS differences) are 7.4 ± 5.1, 6.7 ± 4.8, and 8.1 ± 5.5 ppb in the tropospheric partial column (the column from the surface to the tropopause) for the models TM3, TM5-4DVAR, and LMDz-PYVAR, respectively, and 4.3 ± 9.9, 4.7 ± 9.9, and 6.2 ± 11.2 ppb in the stratospheric partial column (the column from the tropopause to the top of the atmosphere). The model biases in the tropospheric partial column show a latitudinal gradient for all models; however there are no clear latitudinal dependencies for the model biases in the stratospheric partial column visible except with the LMDz-PYVAR model. Comparing modelled and FTS-measured tropospheric column-averaged mole fractions reveals a similar latitudinal gradient in the model biases but comparison with in situ measured mole fractions in the troposphere does not show a latitudinal gradient, which is attributed to the different longitudinal coverage of FTS and in situ measurements. Similarly, a latitudinal pattern exists in model biases in vertical CH4 gradients in the troposphere, which indicates that vertical transport of tropospheric CH4 is not represented correctly in the models. This research is funded by EU project InGOS. We acknowledge funding from the European Union’s Horizon 2020 research and innovation programme for the project RINGO (grant agreement no. 730944) as well. Nicholas Deutscher is supported by an ARC-DECRA fellowship, DE140100178. TCCON measurements at Park Falls and Lamont are possible thanks to NASA grants NNX14AI60G, NNX11AG01G, NAG5-12247, and NNG05-GD07G, and the NASA Orbiting Carbon Observatory Program, as well as technical support from the DOE ARM programme (Lamont) and Jeff Ayers (Park Falls). Darwin and Wollongong TCCON support is funded by NASA grants NAG5-12247 and NNG05-GD07G and the Australian Research Council grants DP140101552, DP110103118, DP0879468 and LP0562346, as well as support from the GOSAT project and DOE ARM technical support in Darwin. The EU projects InGOS and ICOS-INWIRE and the Senate of Bremen provide financial support for TCCON measurements at Bremen, Orleans, Bialystok and Ny-Ålesund, and Orleans is also support by the RAMCES team at LSCE. The Lauder TCCON programme is core-funded by NIWA through New Zealand’s Ministry of Business, Innovation and Employment. The article processing charges for this open-access publication were covered by the University of Bremen. Peer-reviewed Publisher Version