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DOE OSTI2022

Deep learning to estimate permeability using geophysical data

Time-lapse electrical resistivity tomography (ERT) is a popular geophysical method to estimate three-dimensional (3D) permeability fields from electrical potential difference measurements. Traditional inversion and data assimilation methods are used to ingest this ERT data into hydrogeophysical models to estimate permeability. Due to ill-posedness and the curse of dimensionality, existing inversion strategies provide poor estimates and low resolution of the 3D permeability field. Recent advances in deep learning provide us with powerful algorithms to overcome this challenge. This paper presents a deep learning (DL) framework to estimate the 3D subsurface permeability from time-lapse ERT data. To test the feasibility of the proposed framework, we train DL-enabled inverse models on simulation data. Each measurement in both synthetic and field data is standardized by removing the mean and scaling the time-series to unit variance. This pre-processing step is necessary to bring simulation data closer to field observations. Subsurface process models based on hydrogeophysics are used to generate this synthetic data. Training performed on limited simulation data resulted in the DL model over-fitting. An advanced data augmentation based on mixup is implemented to generate additional training samples to overcome this issue. This mixup technique creates weakly labeled (low-fidelity) samples from strongly labeled (high-fidelity) data. The weakly labeled training data is then used to develop DL-enabled inverse models and reduce over-fitting. As both time-lapse ERT (1133048 features/realization) and 3D permeability (585453 features/realization) data samples are from a high-dimensional space, principal component analysis (PCA) is employed to reduce dimensionality. Encoded ERT and encoded permeability are generated using the trained PCA estimators. A deep neural network is then trained to map the encoded ERT to encoded permeability. This mixup training and unsupervised learning allowed us to build a fast and reasonably accurate DL-based inverse model under limited simulation data. Results show that proposed weak supervised learning can capture salient spatial features in the 3D permeability field. Quantitatively, the average mean squared error (in terms of the natural log) on the strongly labeled training, validation, and test datasets is less than 0.5. The R 2 -score (global metric) is greater than 0.75, and the percent error in each cell (local metric) is less than 10%. Finally, an added benefit in terms of computational cost is that the proposed DL-based inverse model is at least O(10 4 ) times faster than running a forward model once it is trained. Data generation, DL model training, and hyperparameter tuning to identify optimal neural network architectures utilized high-performance computing resources while the DL inference is performed on a standard laptop. Approximately, O(10 5 ) processor hours are used for generating data and DL tuning and training. We acknowledge that the data generation and DL model development are expensive. But once a DL model is trained, it can be re-used for inversion rapidly for the given system, with set physics and domain. Note that traditional inversion may require multiple forward model simulations (e.g., in the order of 10 to 1000), which are very expensive. This computational savings ≈ O(10 5 ) – O(10 7 )) makes the proposed DL-based inverse model attractive for subsurface imaging and real-time ERT monitoring applications due to fast and yet reasonably accurate estimations of permeability field.

58 GEOSCIENCES↗

NASA NTRS2009

Assessing the Uncertainty of Land Surface Fluxes Derived from Operational Analyses

Operational numerical weather prediction systems assimilate tremendous amounts of observations to produce global analyses of the atmospheric states. Since the systems include significant contributions from the model components, physical fields, such as the turbulent heat fluxes, can also be derived. However, the physical fields are indirectly constrained by the data assimilation, and so subject to uncertainty in the model parameterizations. Recently, 10 international operational analyses have been collected and reprocessed through the Coordinated Enhanced. Observing Period (CEOP). Comparisons against independent observations (global precipitation and outgoing longwave radiation) show that while there is significant range of the individual analyses, the ensemble of analyses provide data closest the observations. Here, we evaluate the collection of land surface turbulent heat fluxes. The data are available for Oct 2002 - Dec 2004, at 6 hourly, daily and monthly intervals. An ensemble mean and its variance have been computed. we will analyze the range of analysis results at daily and seasonal time scales, and where possible compare with existing observations.

Bosilovich, Michael G.↗

NASA NTRS2001

Bias Correction and Random Error Characterization for the Assimilation of HRDI Line-of-Sight Wind Measurements

A new approach to the analysis of systematic and random observation errors is presented in which the error statistics are obtained using forecast data rather than observations from a different instrument type. The analysis is carried out at an intermediate retrieval level, instead of the more typical state variable space. This method is carried out on measurements made by the High Resolution Doppler Imager (HRDI) on board the Upper Atmosphere Research Satellite (UARS). HRDI, a limb sounder, is the only satellite instrument measuring winds in the stratosphere, and the only instrument of any kind making global wind measurements in the upper atmosphere. HRDI measures doppler shifts in the two different O2 absorption bands (alpha and B) and the retrieved products are tangent point Line-of-Sight wind component (level 2 retrieval) and UV winds (level 3 retrieval). This analysis is carried out on a level 1.9 retrieval, in which the contributions from different points along the line-of-sight have not been removed. Biases are calculated from O-F (observed minus forecast) LOS wind components and are separated into a measurement parameter space consisting of 16 different values. The bias dependence on these parameters (plus an altitude dependence) is used to create a bias correction scheme carried out on the level 1.9 retrieval. The random error component is analyzed by separating the gamma and B band observations and locating observation pairs where both bands are very nearly looking at the same location at the same time. It is shown that the two observation streams are uncorrelated and that this allows the forecast error variance to be estimated. The bias correction is found to cut the effective observation error variance in half.

Tangborn, Andrew↗

NASA NTRS2019

Regularization and Error Characterization of GRACE Mascons

We present a new global time-variable gravity mascon solution derived from Gravity Recovery and Climate Experiment (GRACE) Level 1B data. The new product from the NASA Goddard Space Flight Center (GSFC) results from a novel approach that combines an iterative solution strategy with geographical binning of inter-satellite range-acceleration residuals in the construction of time-dependent regularization matrices applied in the inversion of mascon parameters. This estimation strategy is intentionally conservative as it seeks to maximize the role of the GRACE measurements on the final solution while minimizing the influence of the regularization design process. We fully reprocess the Level 1B data in the presence of the final mascon solution to generate true post-fit inter-satellite residuals, which are utilized to confirm solution convergence and to validate the mascon noise uncertainties. We also present the mathematical case that regularized mascon solutions are biased, and that this bias, or leakage, must be combined with the estimated noise variance to accurately assess total mascon uncertainties. The estimated leakage errors are determined from the monthly resolution operators. We present a simple approach to compute the total uncertainty for both individual mascon and regional analysis of the GSFC mascon product, and validate the results in comparison with independent mascon solutions and calibrated Stokes uncertainties. Lastly, we present the new solution and uncertainties with global analyses of the mass trends and annual amplitudes, and compute updated trends for the global ocean, and the respective contributions of the Greenland Ice Sheet, Antarctic Ice Sheet, Gulf of Alaska, and terrestrial water storage. This analysis highlights the successful closure of the global mean sea level budget, that is, the sum of global ocean mass from the GSFC mascons and the steric component from Argo floats agrees well with the total determined from sea surface altimetry.

B. D. Loomis↗

NASA NTRS2019

Regularization and Error Characterization of GRACE Mascons

Loomis, B. D.↗

DOE OSTI2026

Analysis of Second Target Station Target Removal Dose Rates

The Second Target Station (STS) project at Oak Ridge National Laboratory’s spallation neutron source is a crucial initiative for maintaining U.S. leadership in neutron sciences. The STS aims to create the world’s brightest pulsed cold neutron source, enabling cutting-edge research across various scientific disciplines. To ensure safe and efficient maintenance operations, understanding the effects of shutdown dose rates from activated components within the STS target systems is essential. This study establishes a computational framework for calculating decay gamma sources and subsequent shutdown dose rates utilizing advanced methods to account for all activation channels, including high-energy interactions down to thermal neutron capture. This study describes a novel integration of multiple tools and provides an effective means of analyzing activation and shutdown dose rates at spallation neutron facilities. A custom-developed script automates the decay gamma source generation process, ensuring proper sampling during the variance reduction phase, which is critical for accurate predictions of shutdown dose rates.

Transmutation↗

DOE OSTI2025

Geothermal well testing pressure prediction by using a hybrid transformer model system: FORGE well use case

Geothermal has huge potential to become an indispensable component in achieving the goal of sustainable energy economy, given its capability to provide consistent baseload power to the electric grid. Injection tests are crucial in geothermal energy system as they naturally help to evaluate reservoir properties, understand fluid flow and even enhance reservoir performance. In this research, we developed a hybrid model system that integrates machine learning (ML) regression, a physics-based mathematical model, and transformer deep learning. Trained and validated using FORGE injection test dataset, this system can forecast the pressure variations both upward and downward over time. The pressure prediction achieved prediction accuracy within 3-6% variance of true pressure values. The system can significantly save time and reduce costs by testing only a few cycles and then using model predictions for further analysis, instead of conducting additional real injection cycle tests. The developed model system also holds promise for designing injection test processes and maintaining well production in geothermal energy. Presented at the IMAGE ‘25 Conference led by Shell.

FORGE↗

DOE OSTI2017

Development of Fusion Neutronics Methodology, Software, and Testing Facility in FDS Team

Fusion neutronics including methodology, software, experiments, etc. is studied concerning the generation, utilizing and protection of neutrons in fusion facilities. Achievements have been made in the past decades to solve the new problems fusion neutronics. However there is still some way to go such as following. Automatic modeling method based on CAD has been developed to avoid the heavy burden of manual geometry description. The pre-processing costs much time to simplify the CAD model for converting to Constructive Solid Geometry (CSG), 2D or 3D mesh based geometry. This problem has become a new focus. Deep penetration of radiation shielding is notable problem for fusion. Adaptive variance reduction methods such as Consistent Adjoint Driven Importance Sampling (CADIS) were developed to accelerate convergence. However the gap still exists between engineering requirements and current methodology. The geometry simplification, homogenizing based tally, error in nuclear data and error propagation in coupled calculation, etc., causes considerable uncertainty, which leads to 'safety factor' applied in simulation results to achieve required safety margin. It can significantly raise the cost and even makes it impractical to initiate the fusion facilities. Uncertainty qualification, error analysis and error propagation problem should be studied. New methodology and software should be validated. For example the (n,p), (n,a), (n,t) cross section of Cu, Fe, W, Ni which is important for evaluation of material radiation damage is absent. The validation of neutronics properties of special components such as first wall, blanket and coil are needed. The D-T fusion neutron generator can directly represent the neutron environment in fusion reactors. However the neutron yield is several orders of magnitudes lower than requirements. To resolve obstacles in fusion neutronics, broad improvements of methodology, software and testing facility have been achieved by FDS Team in recent years and the main progress was introduced in this paper.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

NASA NTRS1976

Some new results on the statistics of radio wave scintillation. I - Empirical evidence for Gaussian statistics

This paper presents an analysis of ionospheric scintillation data which shows that the underlying statistical structure of the signal can be accurately modeled by the additive complex Gaussian perturbation predicted by the Born approximation in conjunction with an application of the central limit theorem. By making use of this fact, it is possible to estimate the in-phase, phase quadrature, and cophased scattered power by curve fitting to measured intensity histograms. By using this procedure, it is found that typically more than 80% of the scattered power is in phase quadrature with the undeviated signal component. Thus, the signal is modeled by a Gaussian, but highly non-Rician process. From simultaneous UHF and VHF data, only a weak dependence of this statistical structure on changes in the Fresnel radius is deduced. The signal variance is found to have a nonquadratic wavelength dependence. It is hypothesized that this latter effect is a subtle manifestation of locally homogeneous irregularity structures, a mathematical model proposed by Kolmogorov (1941) in his early studies of incompressible fluid turbulence.

Rino, C. L.↗

DOE OSTI2023

Tensor-to-scalar ratio forecasts for extended LiteBIRD frequency configurations

LiteBIRD is a planned JAXA-led cosmic microwave background (CMB) B-mode satellite experiment aiming for launch in the late 2020s, with a primary goal of detecting the imprint of primordial inflationary gravitational waves. Its current baseline focal-plane configuration includes 15 frequency bands between 40 and 402 GHz, fulfilling the mission requirements to detect the amplitude of gravitational waves with the total uncertainty on the tensor-to-scalar ratio, δr, down to δr < 0.001. A key aspect of this performance is accurate astrophysical component separation, and the ability to remove polarized thermal dust emission is particularly important. In this paper we note that the CMB frequency spectrum falls off nearly exponentially above 300 GHz relative to the thermal dust spectral energy distribution, and a relatively minor high frequency extension can therefore result in even lower uncertainties and better model reconstructions. Specifically, we compared the baseline design with five extended configurations, while varying the underlying dust modeling, in each of which the High-Frequency Telescope (HFT) frequency range was shifted logarithmically toward higher frequencies, with an upper cutoff ranging between 400 and 600 GHz. In each case, we measured the tensor-to-scalar ratio r uncertainty and bias using both parametric and minimum-variance component-separation algorithms. When the thermal dust sky model includes a spatially varying spectral index and temperature, we find that the statistical uncertainty on r after foreground cleaning may be reduced by as much as 30–50% by extending the upper limit of the frequency range from 400 to 600 GHz, with most of the improvement already gained at 500 GHz. We also note that a broader frequency range leads to higher residuals when fitting an incorrect dust model, but also it is easier to discriminate between models through higher χ 2 sensitivity. Even in the case in which the fitting procedure does not correspond to the underlying dust model in the sky, and when the highest frequency data cannot be modeled with sufficient fidelity and must be excluded from the analysis, the uncertainty on r increases by only about 5% for a 500 GHz configuration compared to the baseline.

79 ASTRONOMY AND ASTROPHYSICS↗

NASA NTRS2023

Tensor-to-scalar ratio forecasts for extended LiteBIRD frequency configurations

LiteBIRD is a planned JAXA-led cosmic microwave background (CMB) B -mode satellite experiment aiming for launch in the late 2020s, with a primary goal of detecting the imprint of primordial inflationary gravitational waves. Its current baseline focal-plane configuration includes 15 frequency bands between 40 and 402 GHz, fulfilling the mission requirements to detect the amplitude of gravitational waves with the total uncertainty on the tensor-to-scalar ratio, δr , down to δr < 0.001. A key aspect of this performance is accurate astrophysical component separation, and the ability to remove polarized thermal dust emission is particularly important. In this paper we note that the CMB frequency spectrum falls off nearly exponentially above 300 GHz relative to the thermal dust spectral energy distribution, and a relatively minor high frequency extension can therefore result in even lower uncertainties and better model reconstructions. Specifically, we compared the baseline design with five extended configurations, while varying the underlying dust modeling, in each of which the High-Frequency Telescope (HFT) frequency range was shifted logarithmically toward higher frequencies, with an upper cutoff ranging between 400 and 600 GHz. In each case, we measured the tensor-to-scalar ratio r uncertainty and bias using both parametric and minimum-variance component-separation algorithms. When the thermal dust sky model includes a spatially varying spectral index and temperature, we find that the statistical uncertainty on r after foreground cleaning may be reduced by as much as 30–50% by extending the upper limit of the frequency range from 400 to 600 GHz, with most of the improvement already gained at 500 GHz. We also note that a broader frequency range leads to higher residuals when fitting an incorrect dust model, but also it is easier to discriminate between models through higher χ 2 sensitivity. Even in the case in which the fitting procedure does not correspond to the underlying dust model in the sky, and when the highest frequency data cannot be modeled with sufficient fidelity and must be excluded from the analysis, the uncertainty on r increases by only about 5% for a 500 GHz configuration compared to the baseline.

U. Fuskeland↗

DOE OSTI2019

I Asked 30,000 People in the Nuclear Industry About Safety Culture; This is What I Learned - 19204

Organizations in the nuclear industry place a high value on maintaining the safety of the workforce and community. Some of these organizations do a better job than others when it comes to developing and sustaining a healthy safety culture. We spent six years studying nuclear organizations to better understand the factors that influence safety culture. We used mixed methods to evaluate perceptions of safety culture in these organizations including administering a valid and reliable safety culture survey, conducting one-on-one interviews with managers, and facilitating focus groups with members of the workforce. We analyzed the quantitative and qualitative data collected from more than 30,000 workers in U.S. based organizations. All of the organizations had a nuclear component to their operations. They operated nuclear reactors, processed nuclear materials, decontaminated and decommissioned buildings with radiological contamination, cleaned-up hazardous/mixed waste, and conducted basic science research and development. We talked to craft workers, technicians, engineers, scientific professionals, support personnel, production workers, supervisors and managers. We conducted extensive statistical analysis and learned that, with rare exception, there is a gap between the perceptions of managers and the workforce that they manage. Managers almost always have a more positive perception of safety culture than the people that are actually performing the work. It is not a question of whether there will be a gap; it is simply a matter of the magnitude of the gap. We also learned through exploratory factor analysis that there is one dominant factor that accounted for almost all (75%) of the variance in the perceptions of safety culture. It was the behavior of the leaders, the decisions they made, and the systems they implemented that most influenced the workforce's perception of safety culture. Personal accountability for safety accounted for 14% of the variance, communication and reporting accounted for another 6%. Everything else accounted for the remaining 5%. Management systems, decision making and behavior is the dominant factor and managers almost always have a more positive perception than the people that work for them. People that work in organizations where management exhibits positive decision-making and safety-related behaviors tend to have more positive perceptions of safety culture. Based upon these results, we developed a theory that there were a few important factors on which management could focus on if they sought to influence the safety culture in their organization. Our experience and research suggests that management often fails to recognize five root causes of employee discontent. Employees seek: - To be recognized as an individual; - To be respected; - A sense of stability; - Fairness; - To make a difference. Understanding the perceptions of the workforce is critical because perceptions influence attitudes, which contribute to behaviors that determine individual performance. An organisation's performance is simply the sum of the performance of all of the members of that organization. To change an organisation's safety culture, interventions should target management behavior and decision making for the greatest return on investment. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2020

Evolution of AISI 304L stainless steel part properties due to powder recycling in laser powder-bed fusion

Selective laser melting (SLM) is a powder-bed fusion process in Additive Manufacturing (AM) that uses a laser beam to selectively fuse layers of powder into near net-shape components with little porosity. However, inconsistencies in the part properties due to the presence of defects in as-built components has hindered the widespread adoption of SLM for industrial applications forcing researchers to study the sources of variation for quality control purposes. A critical area suspected of creating variation in the part properties is the feedstock, where batch-to-batch differences as well as changes in the powder properties with reuse have the potential to affect performance. During processing, laser spatter and condensate eject from the melt pool and deposit into the powder-bed surrounding the parts. These particulates, more commonly known as ejecta, differ morphologically and chemically from the virgin powder compromising its reusability. In this study, 304L stainless steel powder was recycled for a total of 5 times through a systematic approach aimed at accelerating powder degradation to reveal the influence on both the tensile and impact toughness properties. Through analysis of variance (ANOVA), it was found that tensile properties did not change with reuse, while the impact toughness showed a steady decline illustrating the differences in static and dynamic part properties due to powder recycling.

36 MATERIALS SCIENCE↗

DOE OSTI2021

Accurate determination of genotypic variance of cell wall characteristics of a Populus trichocarpa pedigree using high-throughput pyrolysis-molecular beam mass spectrometry

Abstract Background Pyrolysis-molecular beam mass spectrometry (py-MBMS) analysis of a pedigree of Populus trichocarpa was performed to study the phenotypic plasticity and heritability of lignin content and lignin monomer composition. Instrumental and microspatial environmental variability were observed in the spectral features and corrected to reveal underlying genetic variance of biomass composition. Results Lignin-derived ions (including m/z 124, 154, 168, 194, 210 and others) were highly impacted by microspatial environmental variation which demonstrates phenotypic plasticity of lignin composition in Populus trichocarpa biomass. Broad-sense heritability of lignin composition after correcting for microspatial and instrumental variation was determined to be H 2 = 0.56 based on py-MBMS ions known to derive from lignin. Heritability of lignin monomeric syringyl/guaiacyl ratio ( S / G ) was H 2 = 0.81. Broad-sense heritability was also high (up to H 2 = 0.79) for ions derived from other components of the biomass including phenolics (e.g., salicylates) and C5 sugars (e.g., xylose). Lignin and phenolic ion abundances were primarily driven by maternal effects, and paternal effects were either similar or stronger for the most heritable carbohydrate-derived ions. Conclusions We have shown that many biopolymer-derived ions from py-MBMS show substantial phenotypic plasticity in response to microenvironmental variation in plantations. Nevertheless, broad-sense heritability for biomass composition can be quite high after correcting for spatial environmental variation. This work outlines the importance in accounting for instrumental and microspatial environmental variation in biomass composition data for applications in heritability measurements and genomic selection for breeding poplar for renewable fuels and materials.

09 BIOMASS FUELS↗

NASA NTRS1980

Vector space methods of photometric analysis. II - Refinement of the MK grid for B stars. III - The two components of ultraviolet reddening

This paper discusses systematic errors which arise from exclusive use of the MK system to determine reddening. It is found that implementation of uvby, beta photometry to refine the qualitative MK grid substantially reduces stellar mismatch error. A working definition of 'identical' ubvy, beta types is investigated and the relationship of uvby to B-V color excesses is determined. A comparison is also made of the hydrogen based uvby, beta types with the MK system based on He and metal lines. A small core correlated effective temperature luminosity error in the MK system for the early B stars is observed along with a breakdown of the MK luminosity criteria for the late B stars. The second part investigates the wavelength dependence of interstellar extinction in the ultraviolet wavelength range observed with the TD-1 satellite. In this study the sets of identical stars employed to find reddening are determined more precisely than in previous studies and consist only of normal, nonsupergiant stars. A multivariate analysis of variance techniques in an unbiased coordinate system is used for determining the wavelength dependence of reddening.

Massa, D.↗

NASA NTRS1995

Statistically generated weighted curve fit of residual functions for modal analysis of structures

A statistically generated weighting function for a second-order polynomial curve fit of residual functions has been developed. The residual flexibility test method, from which a residual function is generated, is a procedure for modal testing large structures in an external constraint-free environment to measure the effects of higher order modes and interface stiffness. This test method is applicable to structures with distinct degree-of-freedom interfaces to other system components. A theoretical residual function in the displacement/force domain has the characteristics of a relatively flat line in the lower frequencies and a slight upward curvature in the higher frequency range. In the test residual function, the above-mentioned characteristics can be seen in the data, but due to the present limitations in the modal parameter evaluation (natural frequencies and mode shapes) of test data, the residual function has regions of ragged data. A second order polynomial curve fit is required to obtain the residual flexibility term. A weighting function of the data is generated by examining the variances between neighboring data points. From a weighted second-order polynomial curve fit, an accurate residual flexibility value can be obtained. The residual flexibility value and free-free modes from testing are used to improve a mathematical model of the structure. The residual flexibility modal test method is applied to a straight beam with a trunnion appendage and a space shuttle payload pallet simulator.

Bookout, P. S.↗

NASA NTRS1979

Polar motion from laser range measurements of GEOS-3

Using two-day arcs of GEOS-3 laser data, simultaneous solutions for pole position components, x sub p and y sub p, and orbit elements have been obtained for the period spanning 3 February to 6 March 1976 using three NASA Goddard Space Flight Center laser stations located near Washington, D.C. (STALAS) and on the islands of Bermuda and Grand Turk. The results are in general agreement with the BIH results. However, because of the locations of the laser sites, the x sub p solution is weaker than the y sub p solution. The x sub p and y sub p estimates were smoothed with a straight line by weighted least squares using the variance associated with the pole estimates as weights in order to reflect the effect of widely different data distributions. The smoothed y sub p differs by one meter with respect to the BIH smoothed values and the smoothed x sub p differs by about two meters. Spectral analysis of the results has identified frequencies associated with the orbital motion indicating the need for further improvements in the model of the physical system.

Schutz, B. E.↗

NASA NTRS1994

Angular momentum exchange among the solid Earth, atmosphere, and oceans: A case study of the 1982-1983 El Nino event

The 1982-1983 El Nino/Southern Oscillation (ENSO) event was accompanied by the largest interannual variation in the Earth's rotation rate on record. In this study we demonstrate that atmospheric forcing was the dominant cause for this rotational anomaly, with atmospheric angular momentum (AAM) integrated from 1000 to 1 mbar (troposphere plus stratosphere) accounting for up to 92% of the interannual variance in the length of day (LOD). Winds between 100 and 1 mbar contributed nearly 20% of the variance explained, indicating that the stratosphere can play a significant role in the Earth's angular momentum budget on interannual time scales. Examination of LOD, AAM, and Southern Oscillation Index (SOI) data for a 15-year span surrounding the 1982-1983 event suggests that the strong rotational response resulted from constructive interference between the low-frequency (approximately 4-6 year) and quasi-biennial (approximately 2-3 year) components of the ENSO phenomenon, as well as the stratospheric Quasi-Biennial Oscillation (QBO). Sources of the remaining LOD discrepancy (approximately 55 and 64 microseconds rms residual for the European Centre for Medium-Range Forecasting (EC) and U.S. National Meteorological Center (NMC) analyses) are explored; noise and systematic errors in the AAM data are estimated to contribute 18 and 33 microseconds, respectively, leaving a residual (rms) of 40 (52) microseconds unaccounted for by the EC (NMC) analysis. Oceanic angular momentum contributions (both moment of inertia changes associated with baroclinic waves and motion terms) are shown to be candidates in closing the interannual axial angular momentum budget.

Dickey, J. O.↗