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The atmospheric boundary layer mediates the exchange of energy, matter, and momentum between the land surface and the free troposphere, integrating a range of physical, chemical, and biological processes and is defined as the lowest layer of the atmosphere (ranging from a few meters to 3 km). In this review, we investigate how continuous, automated observations of the atmospheric boundary layer can enhance the scientific value of co-located eddy covariance measurements of land-atmosphere fluxes of carbon, water, and energy, as are being made at FLUXNET sites worldwide. We highlight four key opportunities to integrate tower-based flux measurements with continuous, long-term atmospheric boundary layer measurements: (1) to interpret surface flux and atmospheric boundary layer exchange dynamics and feedbacks at flux tower sites, (2) to support flux footprint modelling, the interpretation of surface fluxes in heterogeneous and mountainous terrain, and quality control of eddy covariance flux measurements, (3) to support regional-scale modeling and upscaling of surface fluxes to continental scales, and (4) to quantify land-atmosphere coupling and validate its representation in Earth system models. Adding a suite of atmospheric boundary layer measurements to eddy covariance flux tower sites, and supporting the sharing of these data to tower networks, would allow the Earth science community to address new emerging research questions, better interpret ongoing flux tower measurements, and would present novel opportunities for collaborations between FLUXNET scientists and atmospheric and remote sensing scientists.

Atmospheric CO2 inversion typically relies on the specification of prior flux and atmospheric model transport errors, which have large uncertainties. Here, we used ACT‐America airborne observations to compare CO2 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 CO2 boundary condition for WRF. Both models showed reasonable agreement with observations, and CO2 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 found 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 correlation of residuals and showed characteristic residual length scales of approximately 100–300 km. Our findings suggest that inclusion of synoptic weather‐dependent and non‐Gaussian error structure may benefit inversion systems. Key Points: CO2 observed by aircraft in Eastern U.S. compares well to models, but residuals are strongly non‐GaussianModel biases affect representation of cross‐frontal CO2 gradients governing CO2 transport in stormsInversion models may benefit from model‐data mismatch errors dependent upon synoptic sector [ABSTRACT FROM AUTHOR]

Quantification of regional terrestrial carbon dioxide (CO2) fluxes is critical to our understanding of the carbon cycle. We evaluate inverse estimates of net ecosystem exchange (NEE) of CO2 fluxes in temperate North America, and their sensitivity to the observational data used to drive the inversions. Specifically, we consider the state‐of‐the‐science CarbonTracker global inversion system, which assimilates (a) in situ measurements (IS), (b) the Orbiting Carbon Observatory‐2 (OCO‐2) v9 column CO2 (XCO2) retrievals over land (LNLG), (c) OCO‐2 v9 XCO2 retrievals ocean‐glint (OG), and (d) a combination of all these observational constraints (LNLGOGIS). We use independent CO2 observations from the Atmospheric Carbon and Transport (ACT)—America aircraft mission to evaluate the inversions. We diagnose errors in the flux estimates using the differences between modeled and observed biogenic CO2 mole fractions, influence functions from a Lagrangian transport model, Bayesian inference, and root‐mean‐square error (RMSE) and bias metrics. The IS fluxes have the smallest RMSE among the four products, followed by LNLG. Both IS and LNLG outperform the OG and LNLGOGIS inversions with regard to RMSE. Regional errors do not differ markedly across the four sets of posterior fluxes. The CarbonTracker inversions appear to overestimate the seasonal cycle of NEE in the Midwest and Western Canada, and overestimate dormant season NEE across the Central and Eastern US. The CarbonTracker inversions may overestimate annual NEE in the Central and Eastern US. The success of the LNLG inversion with respect to independent observations bodes well for satellite‐based inversions in regions with more limited in situ observing networks. Plain Language Summary: Biological CO2 fluxes, an important component of the earth's climate system, remain uncertain, especially at continental and sub‐continental spatial domains. Different global CO2 observing systems imply significantly different net biological fluxes of CO2. We use independent CO2 measurements from an extensive multi‐seasonal aircraft campaign to evaluate biological CO2 flux estimates derived from four different observational systems entered into a common data analysis system. The observations include both ground and satellite‐based measurements. We found that one of the the satellite‐based CO2 estimates performs nearly as well as the estimates based on ground‐based measurements. This suggests that the satellite data may serve to estimate regional variations in biological CO2 fluxes in portions of the globe with more limited ground‐based observing networks. The inversions all appear to overestimate dormant season release of biological CO2 to the atmosphere, thus may underestimate the net uptake of CO2 by ecosystems in the Central and Eastern United States. Key Points: In situ measurements and the land nadir/land glint inversions are the most reliable products of CarbonTracker in temperate North America, superior to ocean‐glint or LNLGOGIS inversionsErrors in these CarbonTracker regional flux estimates are not strongly dependent on the observational data sourcesCarbonTracker overestimates seasonal net ecosystem exchange (NEE) for the Eastern and Central US, thus the annual NEE may underestimate continental uptake of CO2 [ABSTRACT FROM AUTHOR]