Evaluating Global Atmospheric Inversions of Terrestrial Net Ecosystem Exchange CO₂ Over North America on Seasonal and Sub‐Continental Scales

Abstract

Atmospheric inversion estimates of net ecosystem exchange (NEE) of CO2 are increasingly relevant to climate policy. We evaluated sub‐continental, seasonal estimates of CO2 NEE from nine global inversion systems that participated in the Orbiting Carbon Observatory‐2 model intercomparison project (OCO‐2 v9 MIP), using 98 research flights conducted over the central and eastern United States from 2016 to 2018 as part of the Atmospheric Carbon and Transport ‐ America mission. We found that the seasonal amplitude of NEE in the central and eastern United States is underestimated in these models and model‐data biases are largest for those inversions with the smallest seasonal flux amplitudes. These results were independent of whether the inversions used satellite or in situ data. The largest NEE biases were observed in the Midwest croplands and eastern forests. Future experiments are needed to determine the causes of the persistent biases and if they are associated with biases in annual flux estimates.

Constraining respiration flux and carbon pools in a simple ecosystem carbon model

“…In CARDAMOM studies that have a regional or global focus, beyond FLUXNET sites, atmospheric inversion of net biosphere exchange (NBE) is used in the assimilation with the caveat that it can have large uncertainties (e.g., H. Wang et al, 2019;Cui et al, 2022).…”

“…This is expected since the site-level net ecosystem exchange comprises more signal than averaged over the grid cell observational SIF and VOD. However, given less reliable global net ecosystem exchange assessments (e.g., Peylin et al, 2013;Cui et al, 2022), this finding can be wavered on a global scale. Satellite-based observational SIF and VOD may be expected to further outperform the globally available version of net ecosystem exchange obtained from CO 2 inversion.…”

“…When investigating the effects of assimilating additional datasets in CARDAMOM, we employ a multi-objective approach and examine the impact of different model formulations, varying data quality (including information content and data uncertainty), and implicit and explicit constraints introduced in the model. We investigate the following research questions: 1) Given the error-prone nature of NBE at the global scale (e.g., Deng & Chen, 2011;Chevallier et al, 2019;Cui et al, 2022), how well can remote sensing data such as SIF and VOD help constrain the carbon cycle instead? 2) Which of the SIF and VOD data is more useful in this task, and how does it depend on local conditions?…”

Reduced northern mid-latitude carbon sink estimates from atmospheric CO2 data

“…The overestimated annual carbon sink in EXP-mid and EXP-low can be attributed to biases in the seasonal cycle. Recent aircraft campaigns of Atmospheric Carbon and Transport-America find notable underestimation of seasonal strength of N. America biosphere in the OCO2MIP inversions 20 . Our high-resolution results support this finding and extend it to most of the NH area (Fig.…”

Development of the tangent linear and adjoint models of the global online chemical transport model MPAS-CO2 v7.3

“…In addition to forming a key component of variational assimilation systems (Baker et al, 2006;Zheng et al, 2018;Tian and Zou, 2021), adjoint models are powerful tools for sensitivity analysis (Errico and Vukicevic, 1992;Errico, 1997;Zou et al, 1997;Tian and Zou, 2020). Studies focused on carbon flux estimation are often interested in exploring the sensitivity of atmospheric CO 2 measurements to surface CO 2 fluxes; these maps are commonly referred to as observation influence functions or footprints (Cui et al, 2022). The computation of observation footprints using forward models requires a large number of model runs, making it impractical, except at coarse horizontal resolutions.…”