Extreme climate events are becoming more frequent, with poorly understood implications for carbon sequestration by terrestrial ecosystems. A better understanding will critically depend on accurate and precise quantification of ecosystems responses to these events. Taking the 2019 US Midwest floods as a case study, we investigate current capabilities for tracking regional flux anomalies with “top-down” inversion analyses that assimilate atmospheric CO2 observations. For this analysis, we develop a regionally nested version of the NASA Carbon Monitoring System-Flux (CMS-Flux) that allows high resolution atmospheric transport (0.5° × 0.625°) over a North America domain. Relative to a 2018 baseline, we find US Midwest growing season net carbon uptake is reduced by 11-57 TgC (3-16%) for 2019 (inversion mean estimates across experiments). These estimates are found to be consistent with independent “bottom-up” estimates of carbon uptake based on vegetation remote sensing. We then investigate current limitations in tracking regional carbon emissions and removals by ecosystems using “top-down” methods. In a set of observing system simulation experiments, we show that the ability to recover regional carbon flux anomalies is still limited by observational coverage gaps for both in situ and satellite observations. Future space-based missions that allow for daily observational coverage across North America would largely mitigate these observational gaps, allowing for improved top-down estimates of ecosystem responses to extreme climate events.

This study explores an optimal inversion strategy for assimilating the Orbiting Carbon Observatory-2 (OCO-2) column-averaged atmospheric CO2 concentration (XCO2) observations to constrain air-sea CO2 fluxes. The performance of different inversion set-ups is evaluated through Observing System Simulation Experiments (OSSEs) by comparing the optimized fluxes with assumed true fluxes. The results indicate that the conventional inversion, simultaneously optimizing terrestrial biosphere and air-sea fluxes, reduces root mean square errors (RMSEs) in regional monthly air-sea fluxes by up to 22–24% and 6–10% in the low (<40°) and high (>40°) latitudes, respectively, with up to 22% error reduction in global annual air-sea fluxes. These limited adjustments are associated with an order of magnitude higher variability of terrestrial biosphere fluxes compared to the air-sea fluxes. To isolate ocean signals within XCO2 variations, we employ a sequential inversion, first optimizing terrestrial biosphere fluxes with land XCO2 data and then optimizing air-sea fluxes with ocean XCO2 data while prescribing the optimized terrestrial biosphere fluxes. This approach achieves an 11% additional error reduction in global annual air-sea fluxes and a 33% further RMSE reduction in monthly air-sea fluxes in the southern high latitudes. However, we find that potential biases (+0.2 ppm) in ocean XCO2 measurements over this region could induce a 24% RMSE increase despite the application of sequential inversion. Our results show that sequential inversion is a promising technique for improving seasonal air-sea flux estimates in the Southern Ocean but mitigation of OCO-2 measurement biases is required for practical applications.

East Asia (China, Japan, Koreas and Mongolia) has been the world’s economic engine over at least the past two decades, exhibiting a rapid increase in fossil fuel emissions of greenhouse gases (GHGs) and has expressed the recent ambition to achieve climate neutrality by mid-century. However, the GHG balance of its terrestrial ecosystems remains poorly constrained. Here, we present a synthesis of the three most important long-lived greenhouse gases (CO2, CH4 and N2O) budgets over East Asia during the decades of 2000s and 2010s, following a dual constraint bottom-up and top-down approach. We estimate that terrestrial ecosystems in East Asia is close to neutrality of GHGs, with a magnitude of between 196.9 ± 527.0 Tg CO2eq yr-1 (the top-down approach) and -20.8 ± 205.5 Tg CO2eq yr-1 (the bottom-up approach) during 2000-2019. This net GHG emission includes a large land CO2 sink (-1251.3 ± 456.9 Tg CO2 yr-1 based on the top-down approach and -1356.1 ± 155.6 Tg CO2 yr-1 based on the bottom-up approach), which is being fully offset by biogenic CH4 and N2O emissions, predominantly coming from the agricultural sector. Emerging data sources and modelling capacities have helped achieve agreement between the top-down and bottom-up approaches to within 20% for all three GHGs, but sizeable uncertainties remain in several flux terms. For example, the reported CO2 flux from land use and land cover change varies from a net source of more than 300 Tg CO2 yr-1 to a net sink of ~-700 Tg CO2 yr-1.