Abstract
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 timescales. At the regional scale, some seasonal flux anomalies are detected by the three observing systems, but year-to-year anomalies and longer-term trends are only poorly detected. Moreover, reliably detected regions depend on the reference surface-based inversion used as the signal. Indeed, tropical flux inter-annual variability, for instance, can be attributed mostly to Africa in the reference inversion or spread between tropical regions in Africa and America. Our results show that inter-annual analyses of methane emissions inferred by atmospheric inversions should always include an uncertainty assessment and that the attribution of current trends in atmospheric methane to particular regions' needs increased effort, for instance, gathering more observations (in the future) and improving transport models. At all scales, GOSAT generally shows the best performance of the three observing systems.
Highlights
As the second most important anthropogenic greenhouse gas after carbon dioxide in terms of radiative forcing, methane (CH4) is an important climate driver
As the 2004– 2005 reference corresponds to a period of minimum atmospheric methane growth rate (Dlugokencky et al, 2011), it leads to more positive anomalies for the longer timescales
The regional scale is based on the regions defined and shown in Fig. 2 and large latitudinal bands are defined as boreal zone (BorN) for latitudes higher than 60◦ N, MidN between 30 and 60◦ N, TropN between 0 and 30◦ N, TropS between 0 and 30◦ S, MidS between 30 and 60 ◦ S and BorS higher than 60◦ S
Summary
As the second most important anthropogenic greenhouse gas after carbon dioxide in terms of radiative forcing, methane (CH4) is an important climate driver. These two objectives are combined in atmospheric inversion systems Such systems infer the space–time variations of the global or regional emissions from the assimilation of observations of atmospheric mole fractions into chemistry-transport models (CTMs) (Houweling et al, 1999; Bergamaschi et al, 2007; Bousquet et al, 2011; Pison et al, 2013). For these systems, explaining the trends of CH4 concentrations, such as their stability between 2000 and 2006 and their later increase (Kirschke et al, 2013), is a major scientific objective. In a previous study, Cressot et al (2014) applied objective tuning methods imported from nu-
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