Can we detect regional methane anomalies? A comparison between three observing systems

C Cressot; I Pison; JP Rayner; P Bousquet; A Fortems-Cheiney; F Chevallier

Journal article

Can we detect regional methane anomalies? A comparison between three observing systems

C Cressot, I Pison, JP Rayner, P Bousquet, A Fortems-Cheiney, F Chevallier

Atmospheric Chemistry and Physics | COPERNICUS GESELLSCHAFT MBH | Published : 2016

DOI: 10.5194/acp-16-9089-2016

Abstract

A Bayesian inversion system is used to evaluate the capability of the current global surface network and of the space-borne GOSAT/TANSO-FTS and IASI instruments to quantify surface flux anomalies of methane at various spatial (global, semi-hemispheric and regional) and time (seasonal, yearly, 3-yearly) scales. The evaluation is based on a signal-to-noise ratio analysis, the signal being the methane fluxes inferred from the surface-based inversion from 2000 to 2011 and the noise (i.e., precision) of each of the three observing systems being computed from the Bayesian equation. At the global and semi-hemispheric scales, all observing systems detect flux anomalies at most of the tested timescal..

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University of Melbourne Researchers

Peter Rayner Author

Related Projects (1)

Assimilation of trace atmospheric constituents for climate (ATACC): Linking chemical weather and climate

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Grants

Awarded by Australian Professorial Fellowship

Awarded by GENCI (Grand Equipement National de Calcul Intensif)

Funding Acknowledgements

The authors are very grateful to the many people involved in the surface and satellite measurement and in the archiving of these data. The authors particularly thank E. J. Dlugokencky (NOAA), S. A. Montzka (NOAA), C. Crevoisier (LMD), H. Boesch (University of Leicester), R. Parker (University of Leicester), P. B. Krummel (CSIRO), L. P. Steele (CSIRO), R. L. Langenfelds (CSIRO), S. Nichol (NIWA) and D. Worthy (EC). We acknowledge the contributors to the World Data Center for Greenhouse Gases for providing their data of methane and methyl-chloroform atmospheric mole fractions. The first author is funded by CNES and CEA. P. J. Rayner is in receipt of an Australian Professorial Fellowship (DP1096309). This work was performed using HPC resources from CCRT under the allocation 2014-t2014012201 made by GENCI (Grand Equipement National de Calcul Intensif) and a DSM allocation. We also thank the computing support team of the LSCE led by F. Marabelle.