Estimating regional fluxes of CO2 and CH4 using space-borne observations of XCH4 : XCO2
2015-07-13T13:26:20Z (GMT) by
We use the GEOS-Chem global 3-D atmospheric chemistry transport model to interpret XCH[subscript: 4]:XCO[subscript: 2] column ratios retrieved from the Japanese Greenhouse Gases Observing Satellite (GOSAT). The advantage of these data over CO[subscript: 2] and CH[subscript: 4] 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 r[superscript: 2] =0.92) of this ratio with a model bias < 2.5%. We also show that these variations are driven by emissions of CO[subscript: 2] and CH[subscript: 4] 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 [subscript: 2] and CH[subscript: 4] we use a maximum likelihood estimation approach. We use two approaches to resolve independent flux estimates of these two gases using GOSAT observations of XCH[subscript: 4]:XCO[subscript: 2]: (1) the a priori error covariance between CO[subscript: 2] and CH[subscript: 4] describing common source from biomass burning; and (2) also fitting independent surface atmospheric measurements of CH[subscript: 4] and CO[subscript: 2] 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 XCH[subscript: 4]:XCO[subscript: 2] 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 CH[subscript: 4] and [subscript: 2] fluxes. We show that the regional flux estimates inferred from GOSAT XCH[subscript: 4]:XCO[subscript: 2] ratios together with the surface mole fraction data during 2010 are typically consistent with or better than the corresponding values inferred from fitting XCH[subscript: 4] or the full-physics XCO[subscript: 2] 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 CO[subscript: 2] compared to a small annual sink inferred from the XCO[subscript: 2] 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.