Inverse modeling of CO<sub>2</sub> sources and sinks using satellite observations of CO<sub>2</sub> from TES and surface flask measurements

Abstract

Abstract. We infer CO 2 surface fluxes using satellite observations of mid-tropospheric CO 2 from the Tropospheric Emission Spectrometer (TES) and measurements of CO 2 from surface flasks in a time-independent inversion analysis based on the GEOS-Chem model. Using TES CO 2 observations over oceans, spanning 40 • S-40 • N, we find that the horizontal and vertical coverage of the TES and flask data are complementary. This complementarity is demonstrated by combining the datasets in a joint inversion, which provides better constraints than from either dataset alone, when a posteriori CO 2 distributions are evaluated against independent ship and aircraft CO 2 data. In particular, the joint inversion offers improved constraints in the tropics where surface measurements are sparse, such as the tropical forests of South America. Aggregating the annual surface-to-atmosphere fluxes from the joint inversion for the year 2006 yields −1.13±0.21 Pg C for the global ocean, −2.77±0.20 Pg C for the global land biosphere and −3.90±0.29 Pg C for the total global natural flux (defined as the sum of all biospheric, oceanic, and biomass burning contributions but excluding CO 2 emissions from fossil fuel combustion). These global ocean and global land fluxes are shown to be near the median of the broad range of values from other inversion resultsCorrespondence to: R. Nassar (ray.nassar@ec.gc.ca) for 2006. To achieve these results, a bias in TES CO 2 in the Southern Hemisphere was assessed and corrected using aircraft flask data, and we demonstrate that our results have low sensitivity to variations in the bias correction approach. Overall, this analysis suggests that future carbon data assimilation systems can benefit by integrating in situ and satellite observations of CO 2 and that the vertical information provided by satellite observations of mid-tropospheric CO 2 combined with measurements of surface CO 2 , provides an important additional constraint for flux inversions.

Diagnostic methods for atmospheric inversions of long-lived greenhouse gases

“…Finally, large dipoles in estimated fluxes between large regions can point to a lack of observational constraint for certain regions, to overfitting of the observations that do exist, and/or to biases in large-scale transport (e.g., Alexe et al, 2015;Nassar et al, 2011). The presence of flux dipoles can, however, also be representative of real spatial flux patterns, and sensitivity tests focusing on factors such as the coverage of observational constraints can help to evaluate such patterns in posterior fluxes (Cressot et al, 2014;Rivier et al, 2010).…”

“…However, the informational value and robustness of the information provided by satellite observations is still the subject of ongoing research, and thus their use as constraints in inversions requires special consideration of the impacts of any potential biases. Several studies have included satellite total column or mixing ratio data as an additional constraint on a model otherwise constrained only by in situ concentration measurements to determine whether remotely sensed total column concentrations provide a significant amount of additional information (e.g., Alexe et al, 2015;Houweling et al, 2014;Nassar et al, 2011;Pandey et al, 2016;Saeki et al, 2013a). An inversion constrained only by in situ measurements may also be compared to an inversion constrained only by satellite measurements (e.g., Cressot et al, 2014).…”

“…An inversion constrained only by in situ measurements may also be compared to an inversion constrained only by satellite measurements (e.g., Cressot et al, 2014). The spatial distribution and magnitude of fluxes and the source/sink status of particular regions are often the major posterior features compared between inversions constrained by different subsets of available data (e.g., Alexe et al, 2015;Cressot et al, 2014;Houweling et al, 2014;Nassar et al, 2011). The differences in the geographical flux patterns can be attributed through the use of various methods focusing on quantifying the information content and geographical coverage of satellite data.…”

Simulated retrievals for the remote sensing of CO<sub>2</sub>, CH<sub>4</sub>, CO, and H<sub>2</sub>O from geostationary orbit

“…One exception is SCIAMACHY that had a revisit time of 6 days. The sources and sinks of greenhouse gases are then inferred through flux inversions (e.g., Baker et al, 2010;Nassar et al, 2011). However, the low spatiotemporal measurement densities of the current Earth observing system in LEO result in a lack of information about emissions on smaller spatiotemporal scales (Chevallier et al, 2005;Hungershoefer et al, 2010;Wecht et al, 2014).…”

A multiresolution spatial parameterization for the estimation of fossil-fuel carbon dioxide emissions via atmospheric inversions

“…The ffCO 2 emissions f are defined on a grid, and are assumed to be non-zero only within R. The estimation of CO 2 fluxes, typically biospheric (Nassar et al, 2011;Chatterjee et al, 2012;Gourdji et al, 2012), is usually posed as the minimization of an objective function J ,…”