Objective evaluation of surface- and satellite-driven carbon dioxide atmospheric inversions

Abstract

Abstract. We study an ensemble of six multi-year global Bayesian carbon dioxide (CO2) atmospheric inversions that vary in terms of assimilated observations (either column retrievals from one of two satellites or surface air sample measurements) and transport model. The time series of inferred annual fluxes are first compared with each other at various spatial scales. We then objectively evaluate the small inversion ensemble based on a large dataset of accurate aircraft measurements in the free troposphere over the globe, which are independent of all assimilated data. The measured variables are connected with the inferred fluxes through mass-conserving transport in the global atmosphere and are part of the inversion results. Large-scale annual fluxes estimated from the bias-corrected land retrievals of the second Orbiting Carbon Observatory (OCO-2) differ greatly from the prior fluxes, but are similar to the fluxes estimated from the surface network within the uncertainty of these surface-based estimates. The OCO-2-based and surface-based inversions have similar performance when projected in the space of the aircraft data, but the relative strengths and weaknesses of the two flux estimates vary within the northern and tropical parts of the continents. The verification data also suggest that the more complex and more recent transport model does not improve the inversion skill. In contrast, the inversion using bias-corrected retrievals from the Greenhouse Gases Observing Satellite (GOSAT) or, to a larger extent, a non-Bayesian inversion that simply adjusts a recent bottom-up flux estimate with the annual growth rate diagnosed from marine surface measurements both estimate much different fluxes and fit the aircraft data less. Our study highlights a way to rate global atmospheric inversions. Without any general claim regarding the usefulness of all OCO-2 retrieval datasets vs. all GOSAT retrieval datasets, it still suggests that some satellite retrievals can now provide inversion results that are, despite their uncertainty, comparable with respect to credibility to traditional inversions using the accurate but sparse surface network and that are therefore complementary for studies of the global carbon budget.

Improved Constraints on Northern Extratropical CO2 Fluxes Obtained by Combining Surface‐Based and Space‐Based Atmospheric CO2 Measurements

“…These differences are similar to the magnitude of data-model differences between flux inversions, suggesting that transport model errors limit the ability of evaluating CO 2 flux estimates with aircraft-based measurements. This result is in contrast to Chevallier et al (2019), who found that data-model mismatches were not strongly impacted by the version of Laboratoire de Météorologie Dynamique (LMDz) transport model employed.…”

“…The results of this study suggest that surface-based and space-based atmospheric CO 2 constraints provide consistent constraints on NEE fluxes and can be combined in a flux inversion framework. This result stands in contrast to earlier attempts to combine these data sets (Houweling et al, 2015) and suggests that the improved consistency between the data sets has been made possible by the considerable effort spent refining the ACOS retrieval algorithm (Chevallier et al, 2019;Eldering et al, 2017;Kiel et al, 2019;Miller & Michalak, 2020;O'Dell et al, 2018).…”

“…Chevallier et al (2019) found that flux inversions assimilating OCO-2 ACOS version 9 measurements gave similar net annual fluxes to those assimilating surface-based measurements and that both compared well against aircraft measurements. Interestingly, Chevallier et al (2019) also found that GOSAT OCO Full Physics (OCFP) v7.1 XCO 2 retrievals did not compare as well against aircraft measurements. Comparisons between the ACOS 7.3 and OCFP v7.1 (downloaded from the Copernicus Climate Change Service: https://climate.copernicus.eu/) show substantial differences in zonal mean X CO2 ( Figure S12).…”

Spatially asynchronous changes in strength and stability of terrestrial net ecosystem productivity

“…Why not using NEE derived from atmospheric inversions though (e.g. Jena CarboScope (Rödenbeck et al, 2018), CAMSv17r1 (Chevallier et al, 2005(Chevallier et al, , 2019 and CarbonTracker-EU (Peters et al, 2010)). At least, we know that this data capture some processes that contribute to IAV_NEP, which are not being captured with eddycovariance data (e.g.…”

Scaling carbon fluxes from eddy covariance sites to globe: Synthesis and evaluation of the FLUXCOM approach

“…For the comparison with GPP, we used gridded monthly SIF GOME-2 (Köhler et al, 2015) retrievals from the far-red spectral range, and for the evaluation of NEE atmospheric inversion-based estimates from Jena CarboScope , CAMSv17r1 (Chevallier et al, 2005;Chevallier et al, 2019), and CarbonTracker-EU (CTE2018, Peters et al, 2010;van der Laan-Luijkx et al, 2017). We further include comparisons to the previous GPP and NEE upscaling products of Jung et al, 2011 (hereafter referred as Ju11).…”