Ice discharge uncertainties in Northeast Greenland from boundary conditions and climate forcing of an ice flow model
Explore the source record for details and available documents.
N.‐J. Schlegel↗
SEARCH · Search NASA
Results for “BOX MODELS”
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.
Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.
ReaxFF reactive force field model enables accurate prediction of physiochemical and mechanical properties of crystalline and amorphous shape‐memory polyurethane
Abstract We investigate reactive force field (ReaxFF) prediction of physiochemical and mechanical properties, and stimuli response behavior of a shape‐memory polyurethane (SMPU) rigid segment. We used SMPUs as a platform to link the rigid/hard segment domain crystallinity with properties that can also be experimentally measured. Specifically, we developed models for crystalline and amorphous forms of a common rigid segment of SMPUs, for example, 4,4′‐diphenylmethane diisocyanate (MDI) with n‐butanediol (BDO), denoted as MDI‐BDO. ReaxFF molecular dynamics simulations with equilibrium dynamics are performed by controlling mass, temperature, and pressure or volume to predict the structural and physiochemical properties of crystalline and amorphous rigid segments of SMPU systems, followed by simulating their XRD and FTIR patterns, respectively. Non‐equilibrium ReaxFF simulations are implemented by using uniaxial box deformation technique to study response‐behavior of crystalline SMPU under tensile loading and during stress‐relaxation. The model and simulation scheme presented in this study demonstrates a robust theoretical pathway toward application‐dictated, on‐demand design of high‐performance SMPUs in applications such as soft robotics.
Afroz, Mohammad M.↗
Finite Element Simulations of Two Vertical Drop Tests of F-28 Fuselage Sections
In March 2017, a vertical drop test of a forward fuselage section of a Fokker F-28 MK4000 aircraft was conducted as part of a joint NASA/FAA project to investigate the performance of transport aircraft under realistic crash conditions. In June 2017, a vertical drop test was conducted of a wing-box fuselage section of the same aircraft. Both sections were configured with two rows of aircraft seats, in a triple-double configuration. A total of ten Anthropomorphic Test Devices (ATDs) were secured in seats using standard lap belt restraints. The forward fuselage section was also configured with luggage in the cargo hold. Both sections were outfitted with two hat racks, each with added ballast mass. The drop tests were performed at the Landing and Impact Research facility located at NASA Langley Research Center in Hampton, Virginia. The measured impact velocity for the forward fuselage section was 346.8-in/s onto soil. The wing-box section was dropped with a downward facing pitch angle onto a sloping soil surface in order to create an induced forward acceleration in the airframe. The vertical impact velocity of the wing-box section was 349.2-in/s. A second objective of this project was to assess the capabilities of finite element simulations to predict the test responses. Finite element models of both fuselage sections were developed for execution in LS-DYNA(Registered Trademark), a commercial explicit nonlinear transient dynamic code. The models contained accurate representations of the airframe structure, the hat racks and hat rack masses, the floor and seat tracks, the luggage in the cargo hold for the forward section, and the detailed under-floor structure in the wing-box section. Initially, concentrated masses were used to represent the inertial properties of the seats, restraints, and ATD occupants. However, later simulations were performed that included finite element representations of the seats, restraints, and ATD occupants. These models were developed to more accurately replicate the seat loading of the floor and to enable prediction of occupant impact responses. Models were executed to generate analytical predictions of airframe responses, which were compared with test data to validate the model. Comparisons of predicted and experimental structural deformation and failures were made. Finally, predicted and experimental soil deformation and crater depths were also compared for both drop test configurations.
Jackson, Karen E.↗
Automatic Dynamic Aircraft Modeler (ADAM) for the Computer Program NASTRAN
Large general purpose finite element programs require users to develop large quantities of input data. General purpose pre-processors are used to decrease the effort required to develop structural models. Further reduction of effort can be achieved by specific application pre-processors. Automatic Dynamic Aircraft Modeler (ADAM) is one such application specific pre-processor. General purpose pre-processors use points, lines and surfaces to describe geometric shapes. Specifying that ADAM is used only for aircraft structures allows generic structural sections, wing boxes and bodies, to be pre-defined. Hence with only gross dimensions, thicknesses, material properties and pre-defined boundary conditions a complete model of an aircraft can be created.
Griffis, H.↗
Effect of Anoxic Iron Corrosion on WIPP Brine Geochemistry FY23 Final Report (U)
A 280-day study was completed to evaluate the effect of zero-valent iron (Fe 0 ) on the Waste Isolation Pilot Plant (WIPP) brine geochemistry under anticipated reducing conditions. Hydrogen (H 2 ) gas is expected to be present in the repository after closure due to the anoxic corrosion of a vast quantity of iron contained in the waste forms disposed at WIPP; therefore, a background argon atmosphere containing H 2 was chosen for this study. WIPP groundwater brine pH and E h will impact the mobility and fate of plutonium within the repository. Modeling and laboratory results for Castile WIPP brine indicate that equilibrium fa values relative to the standard hydrogen electrode (SHE) are 40 mV more reducing (i.e., more negative) than those for Salado WIPP brine (-480 mV vs. -440 mV, respectively) because of the higher pH of the Castile brine (pH 9 .3 for Castile vs. pH 8.8 for Salado). The E h and pH data were corrected for the effects of high ionic strength. The experimental results for both brines are consistent with thermodynamic predictions using OLI Systems' Mixed Solvent Electrolyte chemical equilibrium model. The measured and corrected pH and E h data from this study are provided in Table ES-I and Table ES-2, respectively. The experimental study, with four test conditions in triplicate, was performed in a dual glovebox with a nominally 3 vol.% H 2 in argon atmosphere (target H 2 range: 3 ± I vol.%). Simulants containing MgO only ( experimental control) and MgO+Fe 0 (WIPP base case) were prepared for both the Salado and Castile brines. MgO was included in all simulants to account for the use of bulk magnesium oxide in the WIPP repository. Fe 0 was included in some simulants to incorporate the effects of the anoxic corrosion of iron and in-situ hydrogen generation in the study. The brine compositions were developed by Sandia National Laboratory (SNL; Xiong, 2008) and have been used in previous WIPP evaluations. The test method (agitation, etc.) is partially based on ASTM D3987-12. Twelve rounds of periodic measurements of pH and E h were performed over the course of the study. Chemical analysis results for liquids and solids (ICP-MS, ICP-ES, IC Anion, TIC, SEM-EDX) are consistent with the pH, E h , and thermodynamic modeling results. This study included the following conditions that deviate from anticipated post-closure conditions following brine intrusion, but were selected to facilitate bench-scale testing to validate modeling of pH and E h for the post-closure WIP P repository: an anoxic glove box atmosphere containing ≤ 4 vol. % H 2 vs. substantially higher H 2 gas concentrations assumed in the WIPP Performance Assessment (PA); a significantly higher liquid-to-solid test ratio compared to the much lower phase ratio anticipated in the WIP P repository; agitation of the simulant bottles to maximize mass transfer; and finally the use of Fe 0 reagents having a much greater surface area than expected in the WIP P repository. Non-representative conditions were chosen for various reasons such as: to provide bounding conservative results, to provide a margin of safety for testing, or to facilitate simulant sub-sampling and analysis. In a parallel effort, aqueous electrolyte thermodynamic models were developed for the synthetic Salado and Castile brines to inform the experimental design, facilitate laboratory data interpretation, and allow extension of evaluations beyond the parameters tested. Thermodynamic modeling simulations including the MgO and Fe 0 additives that are directly relevant to the experimental measurements (e.g., pH calibration curve, ORP corrections) are included in this report. The measured fa of the simulants was close to the OLI model predictions for both brines and was largely controlled by the background H 2 partial pressure in the vapor phase as well as H 2 generated in situ in the aqueous phase by the Fe 0 corrosion. The H 2 gas-phase concentration tested and thermodynamically evaluated was much lower than is assumed in the WIPP PA; however, H 2 (g) concentrations significantly below this level are still predicted to result in very reducing conditions. In conclusion: • The experimental results are consistent with thermodynamic model predictions for fa, pH, and the effects of high ionic strength. • Evidence to date suggests that the H2 concentration in the glovebox atmosphere ultimately determined the final E h values of the simulants and resulted in highly reducing conditions. As a result, little difference was observed between the control simulants containing only MgO and the WIPP base-case simulants that contained MgO and Fe 0 . • This test methodology is recommended for future studies evaluating WIPP repository conditions. The methodology includes: (1) background H 2 in argon with agitation ( or could alternatively include in-situ-generated H 2 in sealed bottles); (2) carefully measured and corrected ORP data ( with much effort focused on allowing the probes to fully stabilize); and (3) ionic-strength-corrected pH data. Other best practices, such as simulant sparging/handling, ORP probe replacement, etc., should also be considered. • The coupling of experimental studies and thermodynamic modeling is also highly recommended because these methods inform and direct one another leading to greater confidence in and understanding of the results.
12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
On the sensitivity of CTA to gamma-ray boxes from multi-TeV dark matter
Collider, direct and indirect searches for dark matter have typically little or no sensitivity to weakly interacting massive particles (WIMPs) with masses above a few TeV. This rather unexplored regime can however be probed through the search for distinctive gamma-ray spectral features produced by the annihilation of WIMPs at very high energies. Here we present a dedicated search for gamma-ray boxes—sharp spectral features that cannot be mimicked by astrophysical sources—with the upcoming Cherenkov Telescope Array (CTA). Using realistic projections for the instrument performance and detailed background modelling, a profile likelihood analysis is implemented to derive the expected upper limits and sensitivity reach after 100 h of observations towards a 2°×2° region around the Galactic centre. Our results show that CTA will be able to probe gamma-ray boxes down to annihilation cross sections of 10{sup −27}−10{sup −26} cm{sup 3}/s up to tens of TeV. We also identify a number of concrete particle physics models providing thermal dark matter candidates that can be used as target benchmarks in future search campaigns. This constitutes a golden opportunity for CTA to either discover or rule out multi-TeV thermal dark matter in a corner of parameter space where all other experimental efforts are basically insensitive.
79 ASTRONOMY AND ASTROPHYSICS↗
A simple element for aeroelastic analysis of undamaged and damaged wings
The effects of material damage on the aeroelastic response of an anisotropic composite wing are investigated analytically. The wing is modeled as a Timoshenko beam of arbitrary cross section, applying a 24-DOF one-dimensional beam element and Cartesian coordinates. The formulations for the element stiffness matrix, the strain-displacement relations, the box-beam constitutive relations, the contributions of stringers and web, and the warping correction factor are outlined; the application of strip theory in deriving the aerodynamic model is briefly explained; and numerical results are presented in extensive graphs. It is shown that asymmetry and damage can induce bending-stretching coupling phenomena and thereby affect the stability of the aircraft either positively or negatively. The need to take such effects into account in the design of advanced composite wings is stressed.
Kapania, Rakesh K.↗
Lopsidedness of Self-consistent Galaxies Caused by the External Field Effect of Clusters
Adopting Schwarzschild’s orbit-superposition technique, we construct a series of self-consistent galaxy models, embedded in the external field of galaxy clusters in the framework of Milgrom’s MOdified Newtonian Dynamics (MOND). These models represent relatively massive ellipticals with a Hernquist radial profile at various distances from the cluster center. Using N -body simulations, we perform a first analysis of these models and their evolution. We find that self-gravitating axisymmetric density models, even under a weak external field, lose their symmetry by instability and generally evolve to triaxial configurations. A kinematic analysis suggests that the instability originates from both box and nonclassified orbits with low angular momentum. We also consider a self-consistent isolated system that is then placed in a strong external field and allowed to evolve freely. This model, just like the corresponding equilibrium model in the same external field, eventually settles to a triaxial equilibrium as well, but has a higher velocity radial anisotropy and is rounder. The presence of an external field in the MOND universe generically predicts some lopsidedness of galaxy shapes.
79 ASTRONOMY AND ASTROPHYSICS↗
Remote quantification of Cm(III) and HNO 3 by fluorescence spectroscopy and chemometrics
A unique approach to remotely quantify Cm(III) (0–100 µg mL −1 ) in HNO 3 (1–12 M) using steady-state laser fluorescence spectroscopy and multivariate regression models was developed. Photoluminescence is amenable to remote measurements using fiber-optic cables and is sensitive to numerous lanthanide and actinide species. In-line measurements can provide feedback to support complex processing in harsh environments (e.g., hot cells) to help guide and optimize radiochemical separations. In this work, Cm(III) spectra were acquired remotely in a glove box as a function of HNO 3 concentration to better understand spectral characteristics and evaluate the utility of multivariate regression models in this system. Furthermore, the Cm(III) fluorescence peak shape, width, position, and intensity changed significantly as a function of HNO 3 concentration, likely because of the displacement of emission quenching inner-sphere water molecules and complexation with nitrate ions. Despite significant covariance and nonlinearity in the data, a D-optimal design strategy successfully minimized training set sample size and was used to build effective partial least squares regression models for Cm(III) and HNO 3 concentrations without a priori knowledge of solution conditions. Chemometrics for modeling complex fluorescence spectra are promising and may find widespread applicability for online analysis in numerous chemical systems found in the nuclear field.
Actinide↗
A single amino acid change led to structural and functional differentiation of PvHd1 to control flowering in switchgrass
Abstract Switchgrass, a forage and bioenergy crop, occurs as two main ecotypes with different but overlapping ranges of adaptation. The two ecotypes differ in a range of characteristics, including flowering time. Flowering time determines the duration of vegetative development and therefore biomass accumulation, a key trait in bioenergy crops. No causal variants for flowering time differences between switchgrass ecotypes have, as yet, been identified. In this study, we mapped a robust flowering time quantitative trait locus (QTL) on chromosome 4K in a biparental F2 population and characterized the flowering-associated transcription factor gene PvHd1, an ortholog of CONSTANS in Arabidopsis and Heading date 1 in rice, as the underlying causal gene. Protein modeling predicted that a serine to glycine substitution at position 35 (p.S35G) in B-Box domain 1 greatly altered the global structure of the PvHd1 protein. The predicted variation in protein compactness was supported in vitro by a 4 °C shift in denaturation temperature. Overexpressing the PvHd1-p.35S allele in a late-flowering CONSTANS-null Arabidopsis mutant rescued earlier flowering, whereas PvHd1-p.35G had a reduced ability to promote flowering, demonstrating that the structural variation led to functional divergence. Our findings provide us with a tool to manipulate the timing of floral transition in switchgrass cultivars and, potentially, expand their cultivation range.
59 BASIC BIOLOGICAL SCIENCES↗
Hot and turbulent gas in clusters
The gas in galaxy clusters is heated by shock compression through accretion (outer shocks) and mergers (inner shocks). These processes also produce turbulence. To analyse the relation between the thermal and turbulent energies of the gas under the influence of non-adiabatic processes, we performed numerical simulations of cosmic structure formation in a box of 152 Mpc comoving size with radiative cooling, UV background, and a subgrid scale model for numerically unresolved turbulence. By smoothing the gas velocities with an adaptive Kalman filter, we are able to estimate bulk flows towards cluster cores. This enables us to infer the velocity dispersion associated with the turbulent fluctuation relative to the bulk flow. For haloes with masses above 10 13 M ⊙ , we find that the turbulent velocity dispersions averaged over the warm-hot intergalactic medium (WHIM) and the intracluster medium (ICM) are approximately given by powers of the mean gas temperatures with exponents around 0.5, corresponding to a roughly linear relation between turbulent and thermal energies and transonic Mach numbers. However, turbulence is only weakly correlated with the halo mass. Since the power-law relation is stiffer for the WHIM, the turbulent Mach number tends to increase with the mean temperature of the WHIM. This can be attributed to enhanced turbulence production relative to dissipation in particularly hot and turbulent clusters.
79 ASTRONOMY AND ASTROPHYSICS↗
Impact of fragment formation on shear viscosity in the nuclear liquid-gas phase transition region
Within the improved quantum molecular dynamics (ImQMD) model we follow the evolution of nuclear matter for planar Couette flow in a periodic box. We focus on the region of liquid-gas phase transition and extract the shear viscosity coefficient from the local stress tensor, directly following the viscosity definition. Here, by switching on and off the mean field and thus inducing the phase transition, we are able to observe the impact of clumping in the phase transition region on the viscosity.
73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
Process Anomaly Detection for Sparsely Labeled Events in Nuclear Power Plants
An essential aspect of online monitoring, subtle anomaly detection increases the detection lead time for equipment failure and enables a nuclear power plant (NPP) to mitigate unexpected partial or full outages, resulting in significant cost saving to the plant. Once an anomaly is detected by plant staff, its cause and severity are investigated. Because the vast majority of anomalies require some level of investigation, including some that require time-consuming examination, before they are passed over to the engineering organization for further analysis, plants are often equipped with tools to assist the staff in performing anomaly detection. Those tools operate as a black box and are often based on statistical methods that establish sensor correlations using preconfigured mathematical models and flag correlation deviations as anomalies. Due to the number of anomalies detected at a given NPP on a daily basis, a significant number of flagged anomalies usually await examination for days or weeks. A primary cause of this backlog is that the methods used by the tools generate many false positives. Though this is usually attributed to oversensitive model settings due to very narrow normal operation bands, it can also be associated with the model development being inadequate for the process being monitored, or with missing model inputs that could have explained misclassified positives. The performance of anomaly detection tools impacts their plant acceptance and utilization, especially when the effort to address false positives generated by the tool depletes the value or cost saved by using that tool. Thus, means to advance anomaly detection performance have been investigated by the Department of Energy’s Light Water Reactor Sustainability program. Previous and ongoing efforts have targeted unsupervised machine-learning (ML) methods, which do not require the labeling of any data fed into the ML model. By contrast, in supervised anomaly detection methods, every data point is labeled as either a normal or abnormal process condition, and the model is trained to replicate the classification process. Supervised methods usually outperform unsupervised methods, due to the added value in differentiating normal from anomalous states of the monitored process. An NPP’s corrective action program requires it to track and document, via a dedicated report, the resolution of any issues that occur within the plant. Once created, each report is reviewed by a plant screening committee, and several classifications and decisions are made. Recently, a collaborating NPP developed an artificial intelligence and ML-based classifier to categorize a condition report (CR) into classes that can serve to label the data as normal or anomalous. Applying CRs as labels represents a semi-supervised use case. Semi-supervised ML assumes that labels exist for some data points (i.e., labeled anomalies, in this case) but not for the rest. In this effort, semi-supervised ML methods were used to fuse data from CRs with anomaly detection methods in order to test the hypothesis that partially labeled anomalies would improve the accuracy of the anomaly detection methods. Specifically, two methods were used. The first is the deep Semi-supervised Anomaly Detection (deep SAD) method, which can handle labels ranging from fully unsupervised to fully supervised cases. The second is a newly designed ML method developed specifically for this effort and referred to as the high-order feature (HOF)-based method. To evaluate these two methods in controlled environments, synthetic data generators were developed and used. The first datasets used a spring-mass-damper (SMD) system simulator commonly found in mechanical engineering references. This was used to create two use cases: a one- and a three-mass system. Anomalies were introduced by changing the spring and damper coefficients while the system was actuated by random forces. The second datasets used the commercial Dymola-Modelica software to build a simplified nuclear reactor model. Anomalies were added in the form of corrupted sensor readings and/or control commands. The deep SAD method was tested using the SMD system, while the HOF method was tested using both datasets. Application of the deep SAD semi-supervised ML method demonstrated that labels can generate increased confidence in detecting true anomalies. This helped increase the number of true positives and decrease the number of false negatives—something that would aid in addressing the backlog of possible anomalies. Application of the HOF method demonstrated that labels can aid in down selecting from a candidate set of features to a more optimal subset in order to better differentiate between normal and anomalous conditions.
46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
Performance Simulation and Analysis of Occupancy-Based Control for Office Buildings with Variable-Air-Volume Systems
Variable-air-volume (VAV) systems are used in many office buildings. The minimum airflow rate setting of VAV terminal boxes has a significant impact on both energy consumption and indoor air quality. Conventional controls usually have the terminal’s minimum airflow rate at a constant (e.g., 30% or more of the terminal design airflow rate), irrespective of the occupancy status, which may cause problems, such as excessive simultaneous heating and cooling, under ventilation, and thermal comfort issues. This paper examines the potential of energy savings from occupancy-based controls (OBCs). The sensed occupancy information, either occupant presence or people count, is used to determine the airflow rate of terminal boxes, the thermostat setpoints, and the lighting control. Using EnergyPlus, a whole-building energy modeling software, the energy savings of OBC strategies are evaluated for representative existing medium office buildings in the U.S. The simulation results show that the conventional OBC, based on occupant presence sensing, can save 8% of whole-building energy use in Miami (hot climate) for systems without air-side economizer and about 13% in both Baltimore (mixed climate) and Chicago (cold climate). Comparatively, the advanced OBC, based on people counting, can save 8% in Miami to 23% in Baltimore for systems with economizers. The outdoor-air fraction of the supply air from air-handling units significantly affects the potential energy savings from the advanced OBC strategy. In addition to energy savings, the advanced OBC satisfies the zone ventilation during all occupied hours over the whole year.
32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
Measurements of galactic hydrogen and helium isotopes from 1978 through 1983
The differential flux of the hydrogen and helium isotopes was measured using an instrument on the ISEE-3 spacecraft during solar quiet time periods from August 1978 through December 1983. These measurements cover the energy range from 26 MeV/nucleon through 138 MeV/nucleon for both H-1 and He-4, from 24 to 89 MeV/nucleon for H-2, and from 43 to 146 solar activity varied from near minimum to maximum conditions causing the observed flux of galactic cosmic rays to modulate by an order of magnitude. To describe the propagation in the galaxy, it was found that the standard leaky box approximation with an escape path length of 6.7 g/sq cms forms a self consistent model for the light cosmic ray nuclei at the observed energies.
Evenson, P.↗
ISS-CREAM Thermal and Fluid System Design and Analysis
Thermal and Fluids Analysis Workshop (TFAWS), Silver Spring MD NCTS 21070-15. The ISS-CREAM (Cosmic Ray Energetics And Mass for the International Space Station) payload is being developed by an international team and will provide significant cosmic ray characterization over a long time frame. Cold fluid provided by the ISS Exposed Facility (EF) is the primary means of cooling for 5 science instruments and over 7 electronics boxes. Thermal fluid integrated design and analysis was performed for CREAM using a Thermal Desktop model. This presentation will provide some specific design and modeling examples from the fluid cooling system, complex SCD (Silicon Charge Detector) and calorimeter hardware, and integrated payload and ISS level modeling. Features of Thermal Desktop such as CAD simplification, meshing of complex hardware, External References (Xrefs), and FloCAD modeling will be discussed.
Thermal analysis↗
The evolution and discharge of electric fields within a thunderstorm
An analysis of the present three-dimensional thunderstorm electrical model and its finite-difference approximations indicates unconditional stability for the discretization that results from the approximation of the spatial derivatives by a box-schemelike method and of the temporal derivative by either a backward-difference or Crank-Nicholson scheme. Lightning propagation is treated through numerical techniques based on the inverse-matrix modification formula and Cholesky updates. The model is applied to a storm observed at the Kennedy Space Center in 1978, and numerical comparisons are conducted between the model and the theoretical results obtained by Wilson (1920) and Holzer and Saxon (1952).
Hager, William W.↗
Application of PRIM for understanding patterns in carbon dioxide model-observation differences
Reducing uncertainties in regional carbon balances requires a better understanding of CO 2 transport in synoptic weather systems. Here, we apply the Patient Rule Induction Method (PRIM), a data-mining method to identify high-density regions for a target-class within an input parameter space, to airborne observations of potential temperature, wind speed, water vapor mixing ratio, and CO 2 dry mol fraction gathered during the Atmospheric Carbon and Transport (ACT)-America Summer 2016 and Winter 2017 campaigns. ACT observations were targeted at expert-designated cases of fair weather and near-frontal warm and cold sector air at atmospheric boundary-layer, lower-, and higher free tropospheric levels (ABL, LFT, and HFT, respectively). We investigate atmospheric characteristics of these pre-defined cases and associated CO 2 model-observation-differences in the mesoscale WRF-Chem model. PRIM results separate winter- and summertime observations as well as observations from ABL, LFT, and HFT with enrichment factors of 4.0–20.5 inside the PRIM box compared to the entire dataset but cannot distinguish between near-frontal warm and cold sector observations in the higher free troposphere. Analyzing of the parameter space constrained by PRIM, we find that large magnitude model observation differences preferentially associated with times when atmospheric conditions are less typical. This association suggests that PRIM could provide a useful tool for isolating atmospheric conditions with large-magnitude and non-Gaussian CO 2 -residuals for targeted transport model evaluation and to potentially improve inversion results during synoptically active periods.
Gerken, Tobias [James Madison Univ., Harrisonburg,↗