Atmos. Chem. Phys. Discuss., 13, 3735-3782, 2013
www.atmos-chem-phys-discuss.net/13/3735/2013/
doi:10.5194/acpd-13-3735-2013
© Author(s) 2013. This work is distributed
under the Creative Commons Attribution 3.0 License.
Review Status
This discussion paper has been under review for the journal Atmospheric Chemistry and Physics (ACP). Please refer to the corresponding final paper in ACP.
Towards better error statistics for atmospheric inversions of methane surface fluxes
A. Berchet1, I. Pison1, F. Chevallier1, P. Bousquet1, S. Conil2, M. Geever3, T. Laurila4, J. Lavrič5, M. Lopez1, J. Moncrieff6, J. Necki7, M. Ramonet1, M. Schmidt1, M. Steinbacher8, and J. Tarniewicz1
1Laboratoire des Sciences du Climat et de l'Environnement, CEA-CNRS-UVSQ, UMR8212, IPSL, Gif-sur-Yvette, France
2Andra, DRD/OS, Observatoire Pérenne de l'Environnement, France
3National University of Ireland, Galway, Ireland
4FMI, Finnish Meteorological Institute, Helsinki, Finland
5Max Planck Institute for Biogeochemistry, Jena, Germany
6University of Edinburgh, Edinburgh, UK
7AGH University of Science and Technology, Krakow, Poland
8Empa, Laboratory for Air Pollution/Environmental Technology, Duebendorf, Switzerland

Abstract. In this study, we adapt general statistical methods to compute the optimal error covariance matrices in a regional inversion system inferring methane surface emissions from atmospheric concentrations. We optimally estimate the error statistics with a minimal set of physical hypotheses on the patterns of errors. With this very general approach applied within a real-data framework, we recover sources of errors in the observations and in the prior state of the system that are consistent with expert knowledge. By not assuming any specific error patterns, our results show the variability and the inter-dependency of errors induced by complex factors such as the mis-representation of the observations in the transport model or the inability of the model to reproduce well the situations of steep gradients of air mass composition in the atmosphere. By analyzing the sensitivity of the inversion to each observation, ways to improve data selection in regional inversions are also proposed. We applied our method to a recent significant accidental methane release from an offshore platform in the North Sea.

Citation: Berchet, A., Pison, I., Chevallier, F., Bousquet, P., Conil, S., Geever, M., Laurila, T., Lavrič, J., Lopez, M., Moncrieff, J., Necki, J., Ramonet, M., Schmidt, M., Steinbacher, M., and Tarniewicz, J.: Towards better error statistics for atmospheric inversions of methane surface fluxes, Atmos. Chem. Phys. Discuss., 13, 3735-3782, doi:10.5194/acpd-13-3735-2013, 2013.
 
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