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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 595 records · Page 33
All sourcesNASA NTRSDOE OSTI
NASA NTRS2019

Dynamic Smagorinsky Modeled Large-Eddy Simulations of Turbulence Using Tetrahedral Meshes

Eddy-resolving numerical computations of turbulent flows are emerging as viable alternatives to Reynolds Averaged Navier-Stokes (RANS) calculations for flows with an intrinsically steady mean state due to the advances in large-scale parallel computing. In these computations, medium to large turbulent eddies are resolved by the numerics while the smaller or subgrid scales are either modeled or taken care of by the inherent numerical dissipation. To advance the state of the art of unstructured-mesh turbulence simulation capabilities, large eddy simulations (LES) using the dynamic Smagorinsky model (DSM) on tetrahedral meshes are carried out with the space-time conservation element, solution element (CESE) method. In contrast to what has been reported in the literature, the present implementation of dynamic models allows for active backscattering without any ad-hoc limiting of the eddy viscosity calculated from the subgrid-scale model. For the benchmark problems involving compressible isotropic turbulence decay as well as the shock/turbulent boundary layer interaction benchmark problems, no numerical instability associated with kinetic energy growth is observed and the volume percentage of the backscattering portion accounts for about 38-40% of the simulation domain. A slip-wall model in conjunction with the implemented DSM is used to simulate a relatively high Reynolds number Mach 2.85 turbulent boundary layer over a 30° ramp with several tetrahedral meshes and a wall-normal spacing of either Δγ& = 10 or Δγ& = 20. The computed mean wall pressure distribution, separation region size, mean velocity profiles, and Reynolds stress agree reasonably well with experimental data.

CESE method↗
DOE OSTI2022

Setup and verification of a SCALE/KENO platform for generic FHR benchmark calculations

The work presented in this article is preliminary to downstream analysis of a generic fluoride salt-cooled high-temperature reactor (gFHR) core performed by the University of Tennessee in collaboration with Kairos Power (KP). A Monte Carlo transport model of the publicly available gFHR equilibrium core is developed in SCALE/KENO with multigroup energy treatment. Several output quantities of interest are used to verify the simulations against a benchmark model developed by KP using the continuous energy Monte Carlo code Serpent 2. Good agreement is seen in flux and fission rate profiles with a maximum relative difference of 1.4% and 2.8% respectively. Furthermore, an effective multiplication factor bias of 44 pcm was observed between the two simulations. The fuel temperature reactivity coefficient calculated with SCALE is within uncertainty to the reference model. This verification acts as a publicly reproducible benchmark for the gFHR in SCALE/KENO. A simplified depletion model is also presented where a single fuel pebble is depleted to discharge burnup through the equilibrium core while the equilibrium core is assumed to be invariant. This method produces results that intercept the equilibrium core concentrations in every case, however, an interesting artifact of this particular depletion model is uncovered. The phenomenon is shown to be a fundamental feature of the differential rate equations and inspires questions about how this system behaves when the time evolution of the equilibrium core is considered. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2022

Recent MOOSE Update Slides for a DOE CI visit

This is an updated slide deck for which much of the content has been previously cleared. This slide deck incorporates recent NRIC Virtual Test Bed work with several updates on modeling and simulation of benchmark advanced reactor problems. Note that none of the models or results contained within these slides is proprietary. Many of these have been openly published on the Virtual Test Bed.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2021

Modeling of the Molten Salt Reactor Experiment with SCALE

A SCALE model was developed for the Molten Salt Reactor Experiment (MSRE) benchmark that was recently added to the International Handbook of Evaluated Reactor Physics Benchmark Experiments. This SCALE model served as a basis for criticality calculations and nuclear data sensitivity and uncertainty analyses with the Monte Carlo code Shift and the TSUNAMI computational capabilities in the SCALE code system. The focus of this work is the assessment of the impact of nuclear data on the calculated eigenvalue results in support of the discussion of differences between the calculated and the experimental eigenvalue result. The differences in the eigenvalues obtained using the ENDF/B-VII.0, ENDF/B-VII.1, and ENDF/B-VIII.0 nuclear data libraries cover a relatively small range of ~230 pcm. Since eigenvalue sensitivity of the MSRE is dominated by the neutron multiplicity and neutron capture of 235 U and elastic scattering in graphite, relevant changes in the ENDF/B libraries for nuclear reactions (such as carbon capture) that caused large differences in other graphite-moderated systems did not have a significant impact. Propagation of nuclear data uncertainty results in an eigenvalue uncertainty of ~700 pcm with the major contributors being 235 U neutron multiplicity, graphite elastic scattering, and 7Li neutron capture. All calculations resulted in large differences of ~2000 pcm in eigenvalue compared to the benchmark experimental value. Several potential contributors to this difference—including uncertainties and gaps in the knowledge of the material, geometry, and nuclear data—were identified. Simplified models of the full MSRE core were developed, and similarity assessments were conduced with the full MSRE core model. It was found that simplified models can serve as adequate surrogates of the full-core model such that they can be used for performing selected nuclear data performance assessments with a lower computational burden.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2026

Can classical DEM simultaneously capture compressibility and flowability of milled biomass?

Accurate prediction of the rheological behavior of biomass is essential for the design and operation of hoppers, feeders, and storage systems in biorefineries. This study examines whether the classical, coarse-grained discrete element method (DEM) formulation can simultaneously reproduce the compressibility and flowability of milled herbaceous biomass, using Miscanthus × giganteus as a representative material. The model represents particles as rigid spheres interacting through Hertz-Mindlin elastic-frictional contacts augmented with an area-dependent cohesion term. Laboratory cyclic compression and wedge-shaped hopper discharge experiments were used as calibration benchmarks. Although the model can independently reproduce each behavior by appropriately tuning particle Young's modulus E and cohesion energy density k, an extensive parametric investigation comprising more than 600 simulations reveals that the optimal parameter regions for compression and hopper flow are distinct and non-overlapping in (E, k) space. Surrogate surface analysis further shows that the corresponding objective-function valleys exhibit similar trends but are approximately parallel and spatially offset, precluding a unified calibration within the explored domain. Sensitivity analysis indicates that compressibility is governed predominantly by stiffness and cohesion, whereas the slope of the mass flow rate-opening relation in hopper discharge is primarily controlled by tangential friction. Extensions incorporating particle size distribution and clumped-sphere representations do not eliminate the incompatibility. These results systematically reveal, for the first time, the structural limitation of simplified DEM formulations in representing biomass rheological behavior, underscoring the necessity for models incorporating additional physical mechanisms, such as particle deformability or enhanced interlocking, to achieve unified predictive capability for biomass handling behavior.

09 BIOMASS FUELS↗
DOE OSTI2022

IER 555: Godiva Benchmark Update CED-2 (Final Design Report)

The International Criticality Safety Benchmark Evaluation Project (ICSBEP) evaluation of the Godiva IV critical assembly, HEU-MET-FAST-086: GODIVA-IV DELAYED-CRITICAL EXPERIMENTS (HMF-086), was completed by Russ Mosteller. Five critical experiment configurations performed at the Los Alamos National Laboratory (LANL) Technical Area (TA)-18 were evaluated as acceptable benchmark cases. The five cases consist of four delayed critical configurations which differ in control rod positions and one prompt critical configuration. All cases calculated a lower $k_{eff}$ than measured by experiment. This data is referred to as the TA-18 Godiva IV benchmark in this report. In 2005, Godiva IV was disassembled for relocation to the Nevada Test Site (NTS), now Nevada National Security Site (NNSS), at the National Criticality Experiments Research Center (NCERC). Following the disassembly and subsequent reassembly and startup of Godiva IV at NCERC, additional information about the Godiva IV components was obtained. An errata note was added to the HMF-086 evaluation in the ICSBEP handbook to provide this new information until a revision to the benchmark evaluation could be performed. In addition to those corrections, there are differences between the Godiva IV assembly at TA-18 and the Godiva IV assembly at NCERC. These differences include both assembly-specific differences (differences in the safety block gap, differences in the control rod positions, a new NCERC Top Hat and contamination shield) as well as environmental differences, such as the size and shape of the experimental building where the assembly is located. An additional model with similar cases, referred to as the NCERC Godiva IV benchmark in this report, will be added to the revised HMF-086 to capture these additional differences. This will provide the best benchmark model of Godiva for use by those performing experiments at NCERC. The IER 555 CED-2 report documents the information that will be updated in the HMF-086 revision, both the corrections to the TA-18 Godiva IV benchmark and the subsequent changes to create a NCERC Godiva IV benchmark. It describes the measurements that will be performed for cases similar to those performed at TA-18. It also describes measurements that will be included in the evaluation as additional data.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2020

Effect of Nuclear Data Covariances on Integral Experiment Design with Sensitivity and Uncertainty Analysis

Washington River Protection Solutions (WRPS) uses MCNP6.2 and the Whisper code for criticality safety analyses of the Hanford Tank Farm. Together the codes derive baseline upper subcritical limits (USLs) for the waste models using experimental benchmarks. Whisper returns higher USLs, i.e. , has less of a conservative penalty, when the neutronic similarity of the experimental benchmarks to the application is high. Unfortunately, few critical benchmarks have high similarity to the Hanford tanks. The waste in the tanks is highly dilute in plutonium and contains large masses of weakly neutron-absorbing elements like iron and manganese. Experimental benchmarks typically have low sensitivity to these absorbers because they are present as structural materials. Lacking similar benchmarks, new Thermal Epithermal eXperiment (TEX) configurations with high Pu content and interstitial iron absorbers have been designed for the criticality safety validation. The features of the design have been iterated upon to maximize the similarity between the experiment and different Hanford waste models. The similarity is quantified with sensitivity analysis and uncertainty quantification using the representativity coefficient, or c k . The representativity calculation requires nuclear data covariances, which may differ between nuclear data libraries and between library versions. Because of these variations, the optimal design may depend on the nuclear data covariances library. A scenario can be envisioned where an experiment is designed, and c k is maximized, with one set of covariance data. However, when the covariance data is changed, say from ENDF/B-VII.1 to ENDF/B-VIII.0, and the benchmark is used in a criticality safety evaluation, the experiment becomes suboptimal with respect to c k . In this paper, we present how the optimal design of the new TEX experiments varied depending on the nuclear data covariances used to calculate c k . We compare ENDF/B-VII.1 and ENDF/B-VIII.0, as if the library had been updated since the design of the experiment. Additionally, we use JEFF3.3 to simulate if the covariance data of a different library had been used. The results show that the covariances do have an important effect on the designs, less so for thermal systems (where the data are more consistent between evaluations) and more so for epithermal systems where more differences exist.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2021

25-Pin metallic fuel performance benchmark case based on the EBR-II X430 experiments series

A metallic fuel benchmark case was developed for the fuel performance code BISON based on 25 uranium-zirconium and uranium-plutonium-zirconium pins of the Experimental Breeder Reactor II X430 experiment series. Results of the benchmarks were compared with measurements and calculations made at the time of the experiment as well as subsequent measurements reported in 2019. The comparisons were used to quantify the accuracy of the BISON predictions and to identify patterns in the BISON differences.BISON predicted burnup, plenum pressure, and fission gas release fractions accurately. BISON temperature predictions were somewhat cooler than the temperatures determined at the time of the experiment but appeared to be reasonably accurate considering uncertainties in the legacy temperature calculations, uncertainties in the legacy linear heat rate calculations, and the high sensitivities of the BISON-predicted temperatures to BISON inputs. Fuel axial elongation predictions had errors correlated to fuel composition; BISON tended to underpredict the elongation of binary fuels and overpredict the elongation of ternary fuels. BISON cladding radial dilation predictions were also significantly lower than legacy PIE measurements.Recommendations were made to improve the BISON fuel gaseous swelling model to account for fuel composition, to add additional capabilities to the coolant channel temperature model to ease benchmark development, and to continue developing benchmark cases based on a wide range of experiments in several reactors. Once a wide array of benchmarks is developed, an attempt can be made to enhance or calibrate BISON models to improve the cladding dilation predictions.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2024

Report on the AAPM grand challenge on deep generative modeling for learning medical image statistics

Abstract Background The findings of the 2023 AAPM Grand Challenge on Deep Generative Modeling for Learning Medical Image Statistics are reported in this Special Report. Purpose The goal of this challenge was to promote the development of deep generative models for medical imaging and to emphasize the need for their domain‐relevant assessments via the analysis of relevant image statistics. Methods As part of this Grand Challenge, a common training dataset and an evaluation procedure was developed for benchmarking deep generative models for medical image synthesis. To create the training dataset, an established 3D virtual breast phantom was adapted. The resulting dataset comprised about 108 000 images of size 512 512. For the evaluation of submissions to the Challenge, an ensemble of 10 000 DGM‐generated images from each submission was employed. The evaluation procedure consisted of two stages. In the first stage, a preliminary check for memorization and image quality (via the Fréchet Inception Distance [FID]) was performed. Submissions that passed the first stage were then evaluated for the reproducibility of image statistics corresponding to several feature families including texture, morphology, image moments, fractal statistics, and skeleton statistics. A summary measure in this feature space was employed to rank the submissions. Additional analyses of submissions was performed to assess DGM performance specific to individual feature families, the four classes in the training data, and also to identify various artifacts. Results Fifty‐eight submissions from 12 unique users were received for this Challenge. Out of these 12 submissions, 9 submissions passed the first stage of evaluation and were eligible for ranking. The top‐ranked submission employed a conditional latent diffusion model, whereas the joint runners‐up employed a generative adversarial network, followed by another network for image superresolution. In general, we observed that the overall ranking of the top 9 submissions according to our evaluation method (i) did not match the FID‐based ranking, and (ii) differed with respect to individual feature families. Another important finding from our additional analyses was that different DGMs demonstrated similar kinds of artifacts. Conclusions This Grand Challenge highlighted the need for domain‐specific evaluation to further DGM design as well as deployment. It also demonstrated that the specification of a DGM may differ depending on its intended use.

Radiology, Nuclear Medicine & Medical Imaging↗
NASA NTRS2015

A Fast Visible-Infrared Imaging Radiometer Suite Simulator for Cloudy Atmopheres

A fast instrument simulator is developed to simulate the observations made in cloudy atmospheres by the Visible Infrared Imaging Radiometer Suite (VIIRS). The correlated k-distribution (CKD) technique is used to compute the transmissivity of absorbing atmospheric gases. The bulk scattering properties of ice clouds used in this study are based on the ice model used for the MODIS Collection 6 ice cloud products. Two fast radiative transfer models based on pre-computed ice cloud look-up-tables are used for the VIIRS solar and infrared channels. The accuracy and efficiency of the fast simulator are quantify in comparison with a combination of the rigorous line-by-line (LBLRTM) and discrete ordinate radiative transfer (DISORT) models. Relative errors are less than 2 for simulated TOA reflectances for the solar channels and the brightness temperature differences for the infrared channels are less than 0.2 K. The simulator is over three orders of magnitude faster than the benchmark LBLRTM+DISORT model. Furthermore, the cloudy atmosphere reflectances and brightness temperatures from the fast VIIRS simulator compare favorably with those from VIIRS observations.

VIIRS Instrument Simulator↗
DOE OSTI2023

Interaction energy and isosteric heat of adsorption between hydrogen and magnesium diboride

Hydrogen storage materials form a crucial research topic for future energy utilization employing hydrogen and among those of interest magnesium diboride (MgB 2 ) has shown its prevalence. In this study, a first-principles analytical adsorption model of one hydrogen molecule in the vicinity of various magnesium diboride crystal surfaces was developed in order to obtain surface thermodynamic properties as a function of molecular and lattice properties. Henry's law constant (K H ) and isosteric heat of adsorption (ΔH ads ) indicators of the affinity between a gaseous molecule and a solid surface are thus calculated. The results in this paper not only address questions pertaining to the first stage of hydrogen storage processes but also advance the understanding of physisorption thermodynamics of a neutral molecule (H 2 ) coming in contact with a layered metallic-like surface (MgB 2 ). Although the model is built from a framework of classical calculations, quantum effects are incorporated as the fractional charge of the ions on the free surfaces, which is essential for the calculation of analytic thermodynamic values that approximate calculations from other methods. To benchmark our theoretical models, periodic density functional calculations were performed to determine the interactions between H 2 and different MgB 2 surfaces from first-principles. By considering both the top and sublayers of MgB 2 in calculating interaction energy, we have analytically and computationally calculated the interaction energies of H 2 molecules and MgB 2 's terminated planes, and witnessed the strong dependence of interaction energies on surface charges. We have also observed a dipole flipping phenomenon which explains the discontinuity seen in the interaction energy graph of Mg(0001). Both analytical and computational results showed heat of adsorption at zero coverage varying at a very low range (<7 kJ mol -1 ).

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Selection and Ranking of Experiments from the Halden Database in support of Multiscale Model Validation

Validating fuel performance codes, such as BISON, requires an extensive amount of experiments covering a wide range of operating conditions and fuel types. Within the light-water reactor (LWR) space, there have been several international experimental programs that have contributed to the wealth of available experimental data available for use. One of those international programs, the Halden Reactor Project (HRP), began in 1958 and utilized the Halden Boiling Water Reactor to conduct many highly instrumented experiments until the reactor closed in 2018. Idaho National Laboratory, through the U.S. Department of Energy, has utilized several Halden experiments to perform the initial validation of the BISON code based upon their inclusion in international modeling and simulation benchmarks. Recently, the HRP has provided member organizations a complete copy of all available data, reports, and presentations since the HRP began. This report provides an initial exploration of the data available in the database for use in validating the multiscale models under development in the Nuclear Energy Advanced Modeling and Simulation (NEAMS) program for LWR applications. Ranking tables that identify potential validation cases are provided for the high priority models of interest. It was found that some of the recommended high priority experiments correspond to additional rods in existing assemblies already available in the BISON validation suite. It is expected that several of these cases will be incorporated into future NEAMS milestones in the fuels technical area for increased validation of BISON.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2026

Depletion Benchmark Analysis on a Lead Fast Reactor Using PyARC/OpenMC

PyARC is a user-friendly fast reactor analysis tool that automates multiphysics workflows using the “extended suite” of Argonne Reactor Computation (ARC) codes by providing a single common input for model definition, code execution, and output post-processing. A lead fast reactor (LFR) benchmark model is used to perform depletion calculations using the newly integrated OpenMC depletion capability in PyARC, building on previous analysis using the ARC codes through PyARC and Serpent. Results for core lifetime k-effective, shutdown decay heat, and end-of-life heavy-metal inventory are compared to verify the PyARC/OpenMC integration against the PyARC/ARC workflow and Serpent for depletion analysis of LFR designs. The results show satisfactory agreement among all three methods, with remaining discrepancies largely attributable to differences in nuclear data libraries and decay-chain modeling detail rather than to fundamental modeling limitations.

Kiesling, Kalin R.↗
DOE OSTI2021

Ultraviolet spectra of extreme nearby star-forming regions: Evidence for an overabundance of very massive stars

ABSTRACT As deep spectroscopic campaigns extend to higher redshifts and lower stellar masses, the interpretation of galaxy spectra depends increasingly upon models for very young stellar populations. Here we present new HST/COS ultraviolet spectroscopy of seven nearby (<120 Mpc) star-forming regions hosting very young stellar populations (∼4–20 Myr) with optical Wolf–Rayet stellar wind signatures, ideal laboratories in which to benchmark these stellar models. We detect nebular C iii] in all seven, but at equivalent widths uniformly <10 Å. This suggests that even for very young stellar populations, the highest equivalent width C iii] emission at ≥15 Å is reserved for inefficiently cooled gas at metallicities at or below that of the SMC. The spectra also reveal strong C iv P-Cygni profiles and broad He ii emission formed in the winds of massive stars, including some of the most prominent He ii stellar wind lines ever detected in integrated spectra. We find that the latest stellar population synthesis prescriptions with improved treatment of massive stars nearly reproduce the entire range of stellar He ii wind strengths observed here. However, we find that these models cannot simultaneously match the strongest wind features alongside the optical nebular line constraints. This discrepancy can be naturally explained by an overabundance of very massive stars produced by a high incidence of binary mass transfer and mergers occurring on short ≲10 Myr time-scales, suggesting these processes may be crucial for understanding systems dominated by young stars both nearby and in the early Universe.

Senchyna, Peter↗
DOE OSTI2022

An iron evaluation story: from TALYS model parameters to validation on the ASPIS benchmark with the Monte-Carlo code TRIPOLI-4

Iron is a widespread structural material in nuclear applications. However some benchmark studies show that for many libraries, including TENDL-2019, producing good iron evaluations is still an open challenge. This work aims at improving TENDL-2019 {sup 56}Fe and {sup 54}Fe evaluations through feedbacks from experimental data and Monte Carlo results of the iron benchmark ASPIS. Part of the T6 code infrastructure was used to produce the evaluations. In the new evaluations, particular attention to resonance parameters and formalism was paid to address the importance of elastic scattering. The total inelastic scattering and inelastic continuum cross sections were shaped by modifying the input parameters of TALYS, one of the T6 codes. Additionally, it was necessary to normalise some reaction channels to those of JENDL-4.0. With the new files ASPIS results, obtained with the Monte Carlo code TRIPOLI-4, improved noticeably compared to TENDL 2019. The evaluations and parameter setting modifications are to be included into TENDL-2021. (authors)

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2023

Verification and Benchmarking of High Fidelity Physics Peat Smoldering Model

Peat fires are a major contributor to greenhouse gas emissions. The estimates of these emissions currently contain major uncertainties, due to the difficulty of determining the mass of peat burned in a fire. To address these uncertainties, we develop a computational physics-based peat smoldering model, which will be leveraged for high-fidelity quantitative estimates of peat fire emissions relevant to climate change. We present the verification of the 2-D axisymmetric model, a first step towards developing a full 3-D model. Verification includes the solution verification against a literature model for the 0-D smoldering case and verification of the heat transfer problem in 1-D and 2-D. Also presented is the effect of reaction mechanism on the smoldering model, for which we found a relatively simple three-step reaction mechanism is able to capture key behavior. These verification results provide the foundation for moving forward with validation against experimental data of the 2-D model.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
NASA NTRS1991

Error associated with a reduced order linear model of a spur gear pair

The paper proposes a reduced-order analytical model of a spur gear pair which consists of two identical spur gears, two identical flexible shafts, and four identical rolling element bearings of a given radial stiffness. The error associated with the undamped eigensolution is estimated by a comparison with a benchmark finite element model.

Kahraman, A.↗
NASA NTRS2020

Atmospheric Carbon Cycle Dynamics Over the Above Domain: an Integrated Analysis Using Aircraft Observations (Arctic-CA) and Model Simulations (GEOS)

The Arctic Carbon Atmospheric Profiles (Arctic-CAP) project conducted six airborne surveys of Alaska and northwestern Canada between April and November 2017 to capture the spatial and temporal gradients of northern high-latitude carbon dioxide (CO2), methane (CH4) and carbon monoxide (CO) as part of NASA's Arctic-Boreal Vulnerability Experiment (ABoVE). The Arctic-CAP sampling strategy involved acquiring vertical profiles of CO2, CH4 and CO from the surface to 5 km altitude at 25 sites around the ABoVE domain on a 4- to 6-week time interval. We observed vertical gradients of CO2, CH4 and CO that vary by eco-region and duration of the sampling period, which spanned the majority of the seasonal cycle. All Arctic-CAP measurements were compared to a global simulation using the Goddard Earth Observing System (GEOS) modeling system. Comparisons with GEOS simulations of atmospheric CO2, CH4 and CO highlight the potential of these multi-species observations to inform improvements in surface flux estimates and the representation of atmospheric transport. GEOS simulations provide estimates of the near surface average CO2 and CH4 enhancements that are well correlated with aircraft observations (R=0.74 and R=0.60 respectively), suggesting that GEOS has reasonable fidelity over this complex and heterogeneous region. This model-data comparison over the ABoVE domain reveals that while current state-of-the-art models and flux estimates are able to capture broadscale spatial and temporal patterns in near-surface CO2 and CH4 concentrations, more work is needed to resolve fine-scale flux features that are observed. The study also provides a framework for benchmarking a global model at regional scales, which is needed to use climate models as tools to investigate high-latitude carbon-climate feedbacks.

C Sweeney↗