Kenneth Davis

and 29 more

The Atmospheric Carbon and Transport (ACT) – America NASA Earth Venture Suborbital Mission set out to improve regional atmospheric greenhouse gas (GHG) inversions by exploring the intersection of the strong GHG fluxes and vigorous atmospheric transport that occurs within the midlatitudes. Two research aircraft instrumented with remote and in situ sensors to measure GHG mole fractions, associated trace gases, and atmospheric state variables collected 1140.7 flight hours of research data, distributed across 305 individual aircraft sorties, coordinated within 121 research flight days, and spanning five, six-week seasonal flight campaigns in the central and eastern United States. Flights sampled 31 synoptic sequences, including fair weather and frontal conditions, at altitudes ranging from the atmospheric boundary layer to the upper free troposphere. The observations were complemented with global and regional GHG flux and transport model ensembles. We found that midlatitude weather systems contain large spatial gradients in GHG mole fractions, in patterns that were consistent as a function of season and altitude. We attribute these patterns to a combination of regional terrestrial fluxes and inflow from the continental boundaries. These observations, when segregated according to altitude and air mass, provide a variety of quantitative insights into the realism of regional CO2 and CH4 fluxes and atmospheric GHG transport realizations. The ACT-America data set and ensemble modeling methods provide benchmarks for the development of atmospheric inversion systems. As global and regional atmospheric inversions incorporate ACT-America’s findings and methods, we anticipate these systems will produce increasingly accurate and precise sub-continental GHG flux estimates.

Yaxing Wei

and 49 more

The ACT-America project is a NASA Earth Venture Suborbital-2 mission designed to study the transport and fluxes of greenhouse gases. The open and freely available ACT-America datasets provide airborne in-situ measurements of atmospheric carbon dioxide, methane, trace gases, aerosols, clouds, and meteorological properties, airborne remote sensing measurements of aerosol backscatter, atmospheric boundary layer height and columnar content of atmospheric carbon dioxide, tower-based measurements, and modeled atmospheric mole fractions and regional carbon fluxes of greenhouse gases over the Central and Eastern United States. We conducted 121 research flights during five campaigns in four seasons during 2016-2019 over three regions of the US (Mid-Atlantic, Midwest and South) using two NASA research aircraft (B-200 and C-130). We performed three flight patterns (fair weather, frontal crossings, and OCO-2 underflights) and collected more than 1,140 hours of airborne measurements via level-leg flights in the atmospheric boundary layer, lower, and upper free troposphere and vertical profiles spanning these altitudes. We also merged various airborne in-situ measurements onto a common standard sampling interval, which brings coherence to the data, creates geolocated data products, and makes it much easier for the users to perform holistic analysis of the ACT-America data products. Here, we report on detailed information of datasets collected, and the workflow for datasets including storage and processing of the quality controlled and quality assured harmonized observations, and their archival and formatting for users. Finally, we provide some important information on the dissemination of data products including metadata and highlights of applications of datasets for future investigations.

Tobias Gerken

and 7 more

Atmospheric CO2 inversion typically relies on the specification of prior flux and atmospheric model transport errors, which have large uncertainties. Here, we use ACT-America 30 airborne observations to compare total CO 2 model-observation mismatch in the eastern U.S. and during four climatological seasons for the mesoscale WRF(-Chem) and global scale CarbonTracker/TM5 (CT) models. Models used identical surface carbon fluxes, and CT was used as CO 2 boundary condition for WRF. Both models show reasonable agreement with observations, and CO 2 residuals follow near symmetric peaked (i.e. non-Gaussian) distribution with near zero bias of both models (CT: −0.34 +/- 3.12 ppm; WRF: 0.82 +/- 4.37 ppm). We also encountered large magnitude residuals at the tails of the distribution that contribute considerably to overall bias. Atmospheric boundary-layer biases (1-10 ppm) were much larger than free tropospheric biases (0.5-1 ppm) and were of same magnitude as model-model differences, whereas free tropospheric biases were mostly governed by CO2 background conditions. Results revealed systematic differences in atmospheric transport, most pronounced in the warm and cold sectors of synoptic systems, highlighting the importance of transport for CO2 residuals. While CT could reproduce the principal CO2 dynamics associated with synoptic systems, WRF showed a clearer distinction for CO2 differences across fronts. Variograms were used to quantify spatial coherence of residuals and showed characteristic residual length scales of approximately 100 km to 300 km. Our findings suggest that inclusion of synoptic weather-dependent and non-Gaussian error structure may benefit inversion systems.

Sha Feng

and 7 more

Terrestrial biosphere models (TBMs) play a key role in detection and attribution of carbon cycle processes at local to global scales and in projections of the coupled carbon-climate system. TBM evaluation commonly involves direct comparison to eddy-covariance flux measurements. This study uses atmospheric CO2 mole fraction ([CO2]) measured in situ from aircraft and tower, in addition to flux-measurements from summer 2016 to evaluate the CASA TBM. WRF-Chem is used to simulate [CO2] using biogenic CO2 fluxes from a CASA parameter-based ensemble and CarbonTracker version 2017 (CT2017) in addition to transport and CO2 boundary condition ensembles. The resulting “super ensemble” of modeled [CO2] demonstrates that the biosphere introduces the majority of uncertainty to the simulations. Both aircraft and tower [CO2] data show that the CASA ensemble net ecosystem exchange (NEE) of CO2 is biased high (NEE too positive) and identify the maximum light use efficiency Emax a key parameter that drives the spread of the CASA ensemble. These findings are verified with flux-measurements. The direct comparison of the CASA flux ensemble with flux-measurements indicates that modeled [CO2] biases are mainly due to missing sink processes in CASA. Separating the daytime and nighttime flux, we discover that the underestimated net uptake results from missing sink processes that result in overestimation of respiration. NEE biases are smaller in the CT2017 posterior biogenic fluxes, which assimilates observed [CO2]. Flux tower analyses, however, reveal unrealistic overestimation of nighttime respiration in CT2017.