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.

Nitrous oxide (N2O), a potent greenhouse gas and ozone depleting substance, plays a crucial role in the atmosphere. Anthropogenic emissions from agriculture contribute to a rising trend in global N2O emissions and atmospheric concentrations. However, due to insufficient direct observations, regional N2O emissions derived in bottom-up and top-down studies are highly uncertain. The U.S. Midwest is one of the most intensive agriculture areas worldwide and hence may contribute significantly to the observed trend. Recent top-down studies suggest that bottom-up estimates underestimate agricultural emissions in that area by up to an order of magnitude. Here we quantify nitrous oxide emissions in the Midwest in October 2017 and June-July 2019 with a top-down approach. Unique continuous aircraft-based measurements of N2O conducted during the ACT-America campaign together with forward WRF-Chem model simulations are used to scale the EDGAR inventory thus quantifying emissions. On average we had to upscale October 2017 and June-July 2019 agricultural EDGAR 4.3.2/5.0 emissions by a factor of 6.3/3.5 and 11.4/9.9, resulting in 0.42 nmol m-2 s-1 and 1.06 nmol m-2 s-1 emissions in the Midwest, respectively. Finally, calculations of direct soil N2O emissions from the DayCent biogeochemical model are compared to our estimates.

The U.S. Midwest, with its intensive agriculture, is a prominent source of nitrous oxide (N2O) but top-down and bottom-up N2O emission estimates differ significantly. We quantify Midwest N2O emissions by combining observations from the Atmospheric Carbon and Transport-America campaign with model simulations to scale the Emissions Database for Global Atmospheric Research (EDGAR). In October 2017 we increased agricultural EDGAR version 4.3.2/5.0 emissions by a factor of 6.3±4.6/3.5±2.7, resulting in Midwest N2O emissions of 0.42±0.28 nmol m-2 s-1. In June/July 2019, a period when extreme flooding was occurring in the Midwest, EDGAR was increased by a factor of 11.4±6.6/9.9±5.7, resulting in N2O emissions of 1.06±0.57 nmol m-2 s-1. Agricultural emissions estimated with the process-based model DayCent (Daily version of the CENTURY ecosystem model) were larger than in EDGAR but still substantially smaller than our estimates. Due to the complexity of N2O emissions, further studies are necessary to fully characterize Midwest emissions.