Inverse modeling of GOSAT-retrieved ratios of total column CH₄ and CO₂ for 2009 and 2010

Abstract. This study investigates the constraint provided by greenhouse gas measurements from space on surface fluxes. Imperfect knowledge of the light path through the atmosphere, arising from scattering by clouds and aerosols, can create biases in column measurements retrieved from space. To minimize the impact of such biases, ratios of total column retrieved CH₄ and CO₂ (X_ratio) have been used. We apply the ratio inversion method described in Pandey et al. (2015) to retrievals from the Greenhouse Gases Observing SATellite (GOSAT). The ratio inversion method uses the measured X_ratio as a weak constraint on CO₂ fluxes. In contrast, the more common approach of inverting proxy CH₄ retrievals (Frankenberg et al., 2005) prescribes atmospheric CO₂ fields and optimizes only CH₄ fluxes.

The TM5–4DVAR (Tracer Transport Model version 5–variational data assimilation system) inverse modeling system is used to simultaneously optimize the fluxes of CH₄ and CO₂ for 2009 and 2010. The results are compared to proxy inversions using model-derived CO₂ mixing ratios (XCO₂^model) from CarbonTracker and the Monitoring Atmospheric Composition and Climate (MACC) Reanalysis CO₂ product. The performance of the inverse models is evaluated using measurements from three aircraft measurement projects.

X_ratio and XCO₂^model are compared with TCCON retrievals to quantify the relative importance of errors in these components of the proxy XCH₄ retrieval (XCH₄^proxy). We find that the retrieval errors in X_ratio (mean  =  0.61 %) are generally larger than the errors in XCO₂^model (mean  =  0.24 and 0.01 % for CarbonTracker and MACC, respectively). On the annual timescale, the CH₄ fluxes from the different satellite inversions are generally in agreement with each other, suggesting that errors in XCO₂^model do not limit the overall accuracy of the CH₄ flux estimates. On the seasonal timescale, however, larger differences are found due to uncertainties in XCO₂^model, particularly over Australia and in the tropics. The ratio method stays closer to the a priori CH₄ flux in these regions, because it is capable of simultaneously adjusting the CO₂ fluxes. Over tropical South America, comparison to independent measurements shows that CO₂ fields derived from the ratio method are less realistic than those used in the proxy method. However, the CH₄ fluxes are more realistic, because the impact of unaccounted systematic uncertainties is more evenly distributed between CO₂ and CH₄. The ratio inversion estimates an enhanced CO₂ release from tropical South America during the dry season of 2010, which is in accordance with the findings of Gatti et al. (2014) and Van der Laan et al. (2015).

The performance of the ratio method is encouraging, because despite the added nonlinearity due to the assimilation of X_ratio and the significant increase in the degree of freedom by optimizing CO₂ fluxes, still consistent results are obtained with respect to other CH₄ inversions.