Estimating regional fluxes of CO₂ and CH₄ using space-borne observations of XCH₄: XCO₂

We use the GEOS-Chem global 3-D atmospheric chemistry transport model to interpret XCH₄:XCO₂ column ratios retrieved from the Japanese Greenhouse Gases Observing Satellite (GOSAT). The advantage of these data over CO₂ and CH₄ columns retrieved independently using a full physics optimal estimation algorithm is that they are less prone to scattering-related regional biases. We show that the model is able to reproduce observed global and regional spatial (mean bias =0.7%) and temporal variations (global <i>r</i>²=0.92) of this ratio with a model bias < 2.5%. We also show that these variations are driven by emissions of CO₂ and CH₄ that are typically 6 months out of phase, which may reduce the sensitivity of the ratio to changes in either gas. To simultaneously estimate fluxes of CO₂ and CH₄ we use a maximum likelihood estimation approach. We use two approaches to resolve independent flux estimates of these two gases using GOSAT observations of XCH₄:XCO₂: (1) the a priori error covariance between CO₂ and CH₄ describing common source from biomass burning; and (2) also fitting independent surface atmospheric measurements of CH₄ and CO₂ mole fraction that provide additional constraints, improving the effectiveness of the observed GOSAT ratio to constrain flux estimates. We demonstrate the impact of these two approaches using numerical experiments. A posteriori flux estimates inferred using only the GOSAT ratios and taking advantage of the error covariance due to biomass burning are not consistent with the true fluxes in our experiments, as the inversion system cannot judge which species' fluxes to adjust. This reflects the weak dependence of XCH₄:XCO₂ on biomass burning. We find that adding the surface data effectively provides an "anchor" to the inversion that dramatically improves the ability of the GOSAT ratios to infer both CH₄ and CO₂ fluxes. We show that the regional flux estimates inferred from GOSAT XCH₄:XCO₂ ratios together with the surface mole fraction data during 2010 are typically consistent with or better than the corresponding values inferred from fitting XCH₄ or the full-physics XCO₂ data products, as judged by a posteriori uncertainties. We show that the fluxes inferred from the ratio measurements perform best over regions where there is a large seasonal cycle such as Tropical South America, for which we report a small but significant annual source of CO₂ compared to a small annual sink inferred from the XCO₂ data. We argue that given that the ratio measurements are less compromised by systematic error than the full physics data products, the resulting a~posteriori estimates and uncertainties provide a more faithful description of the truth. Based on our analysis we also argue that by using the ratios we may be reaching the current limits on the precision of these observed space-based data