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NASA NTRS1997

Microwave Remote Sensing of Soil Moisture for Estimation of Soil Properties

Surface soil moisture dynamics was derived using microwave remote sensing, and employed to estimate soil physical and hydraulic properties. The L-band ESTAR radiometer was employed in an airborne campaign over the Little Washita watershed, Oklahoma during June 10-18, 1992. Brightness temperature (TB) data were employed in a soil moisture inversion algorithm which corrected for vegetation and soil effects. Analyses of spatial TB and soil moisture dynamics during the dry-down period revealed a direct relationship between changes in TB, soil moisture and soil texture. Extensive regression analyses were carried out which yielded statistically significant quantitative relationships between ratio of percent sand to percent clay (RSC, a term derived to quantify soil texture) and saturated hydraulic conductivity (Ksat) in terms of change components of TB and surface soil moisture. Validation of results indicated that both RSC and Ksat can be estimated with reasonable accuracy. These findings have potential applications for deriving spatial distributions of RSC and Ksat over large areas.

Mattikalli, Nandish M.↗

DOE OSTI2023

ORION: Operational FoRecastIng Of INduced Seismicity

The Operational Forecasting of Induced Seismicity toolkit “ORION” (ORION) is an open-source, observation-based ensemble forecasting toolkit which is geared towards helping operators understand the seismic hazard (i.e., probabilistic assessment of the magnitude and frequency of induced seismic events) at a site. ORION analyzes how the seismic hazard evolves during injection and suggests possible mitigation strategies to employ if an earthquake that exceeds certain threshold is observed. Through its ensemble modeling approach, ORION leverages the benefits of statistical-, physics-, and machine learning-based forecasting methodologies, while reducing the impact of each model’s respective limitations. The ORION toolkit consists of an easy-to-use GUI interface that affords a user as much or as little interaction as desired. Advanced capabilities allow the user to upload local, high-precision earthquake catalogs, projected injection profiles and/or spatiotemporal estimates of pressure/stress, and to tune various model parameters. ORION will then provide a spatial and temporal ensemble forecast of seismicity defined as the probability of exceedance of a given earthquake magnitude over a forecast period. Additionally, ORION will provide probability distribution of the statistically derived maximum possible earthquake magnitude that may be expected. Finally, ORION will provide suggested operational management strategies (e.g. reduce injection volumes at specific wells) based on the level of hazard.

NRAP,NRAP Tools,ORION,Operational Forcasting of In↗

DOE OSTI2026

Statistical White-Line Analysis in High-Throughput TXM-XANES for Chemical State Quantification

The transmission X-ray microscopy (TXM) based X-ray absorption near-edge structure (XANES) technique provides three-dimensional mapping of element-specific chemical states at nanometer-scale spatial resolution and micrometer-scale fields of view. However, compared to conventional volume-averaged XANES (VA-XANES) measurements, the inherently small voxel size in TXM-XANES leads to a lower signal-to-noise ratio, making full-spectrum analysis computationally demanding and less robust. Here, we present the structural and compositional conditions for a statistical white-line analysis framework under which chemical state information can be directly extracted from the white-line peak position in voxel spectra without the need for voxel-wise background subtraction or normalization, under well-defined structural and compositional conditions. The method is validated on layered oxide cathode materials, where low-order polynomial fitting accurately reproduces white-line features, and the extracted energy distributions correlate strongly with VA-XANES results. This statistical approach enables high-throughput, dose-efficient, and noise-robust chemical state quantification in TXM-XANES, offering broad applicability to functional materials requiring nanoscale oxidation-state mapping.

TXM↗

NASA NTRS2000

TRMM/LIS Lightning: Going Beyond Climatological Composites

The high sensitivity, accuracy and pointing stability of the TRMM/LIS allows analysis of not only tropical bulk lightning production, but of storm cell-based statistics. Issues associated with per-storm flash rate identification are presented, including minimum detectable flash rate, 'unbiasing' the low end of observed storm flash rate spectra, and cell identification. Global lightning bulk composites are disaggregated into contributions from storm frequency of occurrence and per-storm flash rate, with the former dominating the global spatial distribution. Local examination of these fields reveals offsets between peaks in flashing storm occurrence and peaks in storm flash rate, often related to geographic effects and diurnal storm evolution. The correlation of storm-level statistics with theoretical measures of meso/large scale coupling (e.g., the gross moist stability of the tropical atmosphere as calculated by Neelin et al) is shown.

Boccippio, Dennis J.↗

DOE OSTI2026

Bayesian Physics Informed Spatio-Temporal Network for Streamflow Data Imputation

Reliable reconstruction of incomplete streamflow records is critical for improving hydrological forecasting, flood preparedness, and water resource management. However, large observational gaps and uncertainties in governing physical parameters limit the accuracy of traditional statistical and machinelearning imputation frameworks. To address these challenges, we develop a Bayesian Physics-Informed Spatio-Temporal Network (BPI-STNet) that jointly captures spatial and temporal dependencies while enforcing hydrologic consistency through embedded physical constraints. The framework integrates a GraphSAGE-LSTM architecture to model spatial connectivity across gauges and temporal flow dynamics, coupled with a Bayesian update mechanism to estimate uncertain parameters in a simplified water-balance framework. Unlike conventional physics-informed networks that rely on sampling-based posterior estimation, BPI-STNet derives an analytic solution to the inverse problem, allowing closed-form Bayesian updates of uncertain parameters Λ={α,β,k} using Gaussian priors and likelihoods. Applied to daily observations from the Susquehanna River Basin (1980-2022), BPI-STNet achieves substantial improvements over a purely data-driven RGNN baseline, which reduced RMSE by 23 % and MAE by 9 %, and achieving an average NSE values up to 0.96. The results demonstrate that coupling Bayesian inference with physics-informed learning yields physically consistent, uncertainty-aware reconstructions that preserve the temporal persistence and statistical distribution of observed flows. The proposed framework establishes a generalizable paradigm for data-sparse hydrologic systems where both data fidelity and physical interpretability are essential.

Krishnan Kutty Ambika, Anukesh [ORNL] (ORCID:00000↗

DOE OSTI2020

A Rapid Population Assessment Method for Wild Pigs Using Baited Cameras at 3 Study Sites

ABSTRACT Reliable and efficient population estimates are a critical need for effective management of invasive wild pigs ( Sus scrofa ). We evaluated the use of 10‐day camera grids for rapid population assessment (RPA) of wild pigs at 3 study sites that varied in vegetation communities and wild pig densities. Study areas included Buck Island Ranch, Florida; Tejon Ranch, California; and the Savannah River Site, South Carolina, USA, during 2016–2018. Rapid population assessments grids were composed of baited camera traps spaced approximately 500 or 750 m apart. Two RPA grids were deployed per study site and each grid was deployed twice (4–6 months apart) to assess changes in response to season or population control efforts. We assessed the ability of RPA grids to track population trends, how camera number influenced estimate precision, and how relative abundance indices related to density estimates. We detected changes in occupancy probability, detection probability, and N‐mixture estimates following removal operations and between seasons, but the ability of RPA grids to track population trends was dependent on the statistical method used and number of cameras traps. Increasing the number of cameras traps used in RPA grids increased precision, and these results can be used in determining survey design and estimate choice. We found that estimates of occupancy probability, detection probability, and N‐mixture estimates were positively correlated with spatially explicit capture–recapture density estimates. Thus, these less labor‐intensive estimates from RPA grids showed potential to index the relative abundance of wild pigs in some systems. Our evaluation of RPAs indicates that using study‐specific combinations of statistical method and number of cameras can provide a useful tool for monitoring wild pig presence, tracking population trends, and evaluating the effectiveness of management actions. © 2020 The Wildlife Society.

Schlichting, Peter E.↗

DOE OSTI2021

Power grid frequency prediction using spatiotemporal modeling

Understanding power system dynamics is essential for interarea oscillation analysis and the detection of grid instabilities. The FNET/GridEye is a GPS-synchronized wide-area frequency measurement network that provides an accurate picture of the normal real-time operational condition of the power system-dynamics, giving rise to new and intricate spatiotemporal patterns of power loads. We propose to model FNET/GridEye grid frequency data from the U.S. Eastern Interconnection with a spatiotemporal statistical model. We predict the frequency data at locations without observations, a critical need during disruption events where measurement data are inaccessible. Spatial information is accounted for either as neighboring measurements in the form of covariates or with a spatiotemporal correlation model captured by a latent Gaussian field. Finally, the proposed method is useful in estimating power system dynamic response from limited phasor measurements and holds promise for predicting instability that may lead to undesirable effects such as cascading outages.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2022

gdess: A framework for evaluating simulated atmospheric CO 2 in Earth System Models

Atmospheric carbon dioxide (CO 2 ) plays a key role in the global carbon cycle and global warming. Climate-carbon feedbacks are often studied and estimated using Earth System Models (ESMs), which couple together multiple model components—including the atmosphere, ocean, terrestrial biosphere, and cryosphere—to jointly simulate mass and energy exchanges within and between these components. Despite tremendous advances, model intercomparisons and benchmarking are aspects of ESMs that warrant further improvement (Fer et al., 2021; Smith et al., 2014). Such benchmarking is critical because comparing the value of state variables in these simulations against observed values provides evidence for appropriately refining model components; moreover, researchers can learn much about Earth system dynamics in the process (Randall et al., 2019). We introduce `gdess` (a.k.a., Greenhouse gas Diagnostics for Earth System Simulations), which parses observational datasets and ESM simulation output, combines them to be in a consistent structure, computes statistical metrics, and generates diagnostic visualizations. In its current incarnation, `gdess` facilitates evaluating a model's ability to reproduce observed temporal and spatial variations of atmospheric CO 2 . The diagnostics implemented modularly in `gdess` support more rapid assessment and improvement of model-simulated global CO 2 sources and sinks associated with land and ocean ecosystem processes. We intend for this set of automated diagnostics to form an extensible, open source framework for future comparisons of simulated and observed concentrations of various greenhouse gases across Earth system models.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2020

Microwave Cast Material Examination

Microwave-cast material dating from the latest prototype development period and subsequent TRL 7 advancement testing was sent to LANL for additional characterization. The initial characterization described here is considered a supplement to and verification of that performed by Y-12 during the Technology Readiness Assessment process. The carbon chemistry results from Y-12 and LANL regarding early prototype microwave cast test object (CTO) and cylinder castings match within expectations. Only one fully intact as-cast CTO was available for examination in which carbon chemistry does not appear to vary spatially, at least at relatively low carbon levels (hypoeutectic). The large as-cast grain size leads to relatively poor grain size statistics and similar difficulties were encountered during the TRA. Small, isolated gas pores were observed in four of the five metallographic samples in prototype CTO casting PT-01. Finally, the next phase of characterization work, which focuses on corrosion behavior, has started and is described briefly.

36 MATERIALS SCIENCE↗

DOE OSTI2022

Characterizing and Mitigating Intraday Variability: Reconstructing Source Structure in Accreting Black Holes with mm-VLBI

The extraordinary physical resolution afforded by the Event Horizon Telescope has opened a window onto the astrophysical phenomena unfolding on horizon scales in two known black holes, M87* and Sgr A*. However, with this leap in resolution has come a new set of practical complications. Sgr A* exhibits intraday variability that violates the assumptions underlying Earth aperture synthesis, limiting traditional image reconstruction methods to short timescales and data sets with very sparse (u, v) coverage. We present a new set of tools to detect and mitigate this variability. We develop a data-driven, model-agnostic procedure to detect and characterize the spatial structure of intraday variability. This method is calibrated against a large set of mock data sets, producing an empirical estimator of the spatial power spectrum of the brightness fluctuations. We present a novel Bayesian noise modeling algorithm that simultaneously reconstructs an average image and statistical measure of the fluctuations about it using a parameterized form for the excess variance in the complex visibilities not otherwise explained by the statistical errors. These methods are validated using a variety of simulated data, including general relativistic magnetohydrodynamic simulations appropriate for Sgr A* and M87*. We find that the reconstructed source structure and variability are robust to changes in the underlying image model. We apply these methods to the 2017 EHT observations of M87*, finding evidence for variability across the EHT observing campaign. The variability mitigation strategies presented are widely applicable to very long baseline interferometry observations of variable sources generally, for which they provide a data-informed averaging procedure and natural characterization of inter-epoch image consistency.

79 ASTRONOMY AND ASTROPHYSICS↗

NASA NTRS1983

Statistical analysis of turbulence data from the NASA Marshall Space Flight Center atmospheric boundary layer tower array facility

Statistical properties of atmospheric turbulence near the Earth's surface are presented. Emphasis is placed on the probability density distribution two point spatial correlation, length scale, and two point and single point spectrum. Comparison of the data with isotropic homogeneous models is made. In general, agreement with the models is poor. For the design of aircraft during operations in the lower levels associated with approach, takeoff, and terrain following, it appears necessary to improve existing models or develop new nonisotropic turbulence models.

Frost, W.↗

NASA NTRS1991

Report of the theory panel

The ultimate goal of this research is to develop an understanding which is sufficiently comprehensive to allow realistic predictions of the behavior of the physical systems. Theory has a central role to play in the quest for this understanding. The level of theoretical description is dependent on three constraints: (1) the available computer hardware may limit both the number and the size of physical processes the model system can describe; (2) the fact that some natural systems may only be described in a statistical manner; and (3) the fact that some natural systems may be observable only through remote sensing which is intrinsically limited by spatial resolution and line of sight integration. From this the report discusses present accomplishments and future goals of theoretical space physics. Finally, the development and use of new supercomputer is examined.

Ashourabdalla, Maha↗

NASA NTRS1994

Trends in surface ozone over Europe, 1978-1990

It has been suggested that surface ozone concentrations in rural areas of Europe have been increasing at a rate of 1 to 3 percent per year over the past two to three decades, presumably due to human influences (Feister and Warmbt, 1987; Bojkov, 1988; Penkett, 1989). Recently, we have analyzed surface ozone data from 20 European stations of differing character (remote, rural, suburban and urban) for a common period of 1978-1988 (Low et al., 1992). It was found that there were pronounced annual and seasonal variations in the linear trends in different areas, and there was no dominant region-wide trend. In spring and, most notably, summer, stations on the maritime fringe of the network generally exhibited negative trends whilst those located further into the continental interior exhibited positive trends. In winter, most of the stations in the network exhibited positive trends. Relatively few of these trends were statistically significant. This paper updates our earlier analysis by extending the data sets of the network up to the year 1990. The spatial variations in surface ozone trends over the extended period 1978-1990 are examined and discussed in comparison to the 1978-1988 patterns. The update confirms the overall conclusions of the earlier analysis, specifically that caution should be exercised in interpreting the results of trend analyses based on station data representative of a limited period of time and/or geographical area.

Low, Pak Sum↗

NASA NTRS2002

Confronting Models with Data: The GEWEX Cloud Systems Study

The GEWEX Cloud System Study (GCSS; GEWEX is the Global Energy and Water Cycle Experiment) was organized to promote development of improved parameterizations of cloud systems for use in climate and numerical weather prediction models, with an emphasis on the climate applications. The strategy of GCSS is to use two distinct kinds of models to analyze and understand observations of the behavior of several different types of clouds systems. Cloud-system-resolving models (CSRMs) have high enough spatial and temporal resolutions to represent individual cloud elements, but cover a wide enough range of space and time scales to permit statistical analysis of simulated cloud systems. Results from CSRMs are compared with detailed observations, representing specific cases based on field experiments, and also with statistical composites obtained from satellite and meteorological analyses. Single-column models (SCMs) are the surgically extracted column physics of atmospheric general circulation models. SCMs are used to test cloud parameterizations in an un-coupled mode, by comparison with field data and statistical composites. In the original GCSS strategy, data is collected in various field programs and provided to the CSRM Community, which uses the data to "certify" the CSRMs as reliable tools for the simulation of particular cloud regimes, and then uses the CSRMs to develop parameterizations, which are provided to the GCM Community. We report here the results of a re-thinking of the scientific strategy of GCSS, which takes into account the practical issues that arise in confronting models with data. The main elements of the proposed new strategy are a more active role for the large-scale modeling community, and an explicit recognition of the importance of data integration.

Randall, David↗

NASA NTRS2006

Low- to Mid-Latitude X-Ray Emission from Jupiter

The Chandra X-ray Observatory (CXO) observed Jupiter during the period 2003 February 24-26 for approx.40 hours (4 Jupiter rotations), using both the spectroscopy array of the Advanced CCD Imaging Spectrometer (ACIS-S) and the imaging array of the High-Resolution Camera (HRC-I). Two ACIS-S exposures, each approx.8.5 hr long, were separated by an HRC-I exposure of approx.20 hr. The low- to mid-latitude non-auroral disk X-ray emission is much more spatially uniform than the auroral emission. However, the low- to mid-latitude X-ray count rate shows a small but statistically significant hour angle dependence, and is higher in regions of relatively low surface magnetic field strength, confirming ROSAT results. In addition, the spectrum from the low surface field region shows an enhancement in the energy band 1.14- 1.38 keV, perhaps partly due to line emission from that region. Correlation of surface magnetic field strength with count rate is not found for the 2000 December HRC-I data, at a time when solar activity was high. The low- to mid-latitude disk X-ray count rate observed by the HRC-I in the 2003 February observation is about 50% of that observed in 2000 December, roughly consistent with a decrease in the solar activity index (F10.7 cm flux) by a similar amount over the same time period. The low- to mid-latitude X-ray emission does not show any oscillations similar to the -45 minute oscillations sometimes seen from the northern auroral zone. The temporal variation in Jupiter's non-auroral X-ray emission exhibits similarities to variations in solar X-ray flux observed by GOES and TIMED/SEE. The two ACIS-S 0.3-2 keV low- to mid-latitude X-ray spectra are harder than the auroral spectrum, and are different from each other at energies above 0.7 keV, showing variability in Jupiter s non-auroral X-ray emission on a time scale of a day. The 0.3-2.0 keV X-ray power emitted at low- to mid-latitudes is 0.21 GW and 0.39 GW for the first and second ACIS-S exposures, respectively. We suggest that X-ray emission from Jupiter's disk may be largely generated by solar X-rays resonantly and fluorescently scattered in its upper atmosphere, especially at times of high incident solar X-ray flux. However, the correlation of higher count rate with low surface magnetic-field strength indicates the presence of some secondary component, possibly ion precipitation from radiation belts closer to the planet than elsewhere at low- to mid-latitudes.

Bhardwaj, Anil↗

NASA NTRS2006

Low- to Middle-Latitude X-Ray Emission from Jupiter

The Chandra X-ray Observatory (CXO) observed Jupiter during the period 24-26 February 2003 for approx. 40 hours (4 Jupiter rotations), using both the spectroscopy array of the Advanced CCD Imaging Spectrometer (ACIS-S) and the imaging array of the High-Resolution Camera (HRC-I). Two ACIS-S exposures, each -8.5 hours long, were separated by an HRC-I exposure of approx. 20 hours. The low- to middle-latitude nonauroral disk X-ray emission is much more spatially uniform than the auroral emission. However, the low- to middle-latitude X-ray count rate shows a small but statistically significant hour angle dependence and depends on surface magnetic field strength. In addition, the X-ray spectra from regions corresponding to 3-5 gauss and 5-7 gauss surface fields show significant differences in the energy band 1.26-1.38 keV, perhaps partly due to line emission occurring in the 3-5 gauss region but not the 5-7 gauss region. A similar correlation of surface magnetic field strength with count rate is found for the 18 December 2000 HRC-I data, at a time when solar activity was high. The low- to middle-latitude disk X-ray count rate observed by the HRC-I in the February 2003 observation is about 50% of that observed in December 2000, roughly consistent with a decrease in the solar activity index (F10.7 cm flux) by a similar amount over the same time period. The low- to middle-latitude X-ray emission does not show any oscillations similar to the approx. 45 min oscillations sometimes seen from the northern auroral zone. The temporal variation in Jupiter's nonauroral X-ray emission exhibits similarities to variations in solar X-ray flux observed by GOES and TIMED/SEE. The two ACIS-S 0.3-2.0 keV low- to middle-latitude X-ray spectra are harder than the auroral spectrum and are different from each other at energies above 0.7 keV, showing variability in Jupiter's nonauroral X-ray emission on a timescale of a day. The 0.3-2.0 keV X-ray power emitted at low to middle latitudes is 0.21 GW and 0.39 GW for the first and second ACIS-S exposures, respectively. We suggest that X-ray emission from Jupiter's disk may be largely generated by the scattering and fluorescence of solar X rays in its upper atmosphere, especially at times of high incident solar X-ray flux. However, the dependence of count rate on surface magnetic-field strength may indicate the presence of some secondary component, possibly ion precipitation from radiation belts close to the planet.

Bhardwaj, Anil↗

NASA NTRS1998

On Geomagnetism and Paleomagnetism

A statistical description of Earth's broad scale, core-source magnetic field has been developed and tested. The description features an expected, or mean, spatial magnetic power spectrum that is neither "flat" nor "while" at any depth, but is akin to spectra advanced by Stevenson and McLeod. This multipole spectrum describes the magnetic energy range; it is not steep enough for Gubbins' magnetic dissipation range. Natural variations of core multipole powers about their mean values are to be expected over geologic time and are described via trial probability distribution functions that neither require nor prohibit magnetic isotropy. The description is thus applicable to core-source dipole and low degree non-dipole fields despite axial dipole anisotropy. The description is combined with main field models of modem satellite and surface geomagnetic measurements to make testable predictions of: (1) the radius of Earth's core, (2) mean paleomagnetic field intensity, and (3) the mean rates and durations of both dipole power excursions and durable axial dipole reversals. The predicted core radius is 0.7% above the 3480 km seismologic value. The predicted root mean square paleointensity (35.6 mu T) and mean Virtual Axial Dipole Moment (about 6.2 lx 1022 Am(exp 2)) are within the range of various mean paleointensity estimates. The predicted mean rate of dipole power excursions, as defined by an absolute dipole moment <20% of the 1980 value, is 9.04/Myr and 14% less than obtained by analysis of a 4 Myr paleointensity record. The predicted mean rate of durable axial dipole reversals (2.26/Myr) is 2.3% more than established by the polarity time-scale for the past 84 Myr. The predicted mean duration of axial dipole reversals (5533 yr) is indistinguishable from an observational value. The accuracy of these predictions demonstrates the power and utility of the description, which is thought to merit further development and testing. It is suggested that strong stable stratification of Earth's uppermost outer core leads to a geologically long interval of no dipole reversals and a very nearly axisymmetric field outside the core. Statistical descriptions of other planetary magnetic fields are outlined.

Voorhies, Coerte V.↗

DOE OSTI2024

Theory and modeling of molecular modes in the NMR relaxation of fluids

Traditional theories of the nuclear magnetic resonance (NMR) autocorrelation function for intra-molecular dipole pairs assume a single-exponential decay, yet the calculated autocorrelation of realistic systems displays a rich, multi-exponential behavior, resulting in anomalous NMR relaxation dispersion (i.e., frequency dependence). We develop an approach to model and interpret the multi-exponential intra-molecular autocorrelation using simple, physical models within a rigorous statistical mechanical development that encompasses both rotational diffusion and translational diffusion in the same framework. Here, we recast the problem of evaluating the autocorrelation in terms of averaging over a diffusion propagator whose evolution is described by a Fokker–Planck equation. The time-independent part admits an eigenfunction expansion, allowing us to write the propagator as a sum over modes. Each mode has a spatial part that depends on the specified eigenfunction and a temporal part that depends on the corresponding eigenvalue (i.e., correlation time) with a simple, exponential decay. The spatial part is a probability distribution of the dipole pair, analogous to the stationary states of a quantum harmonic oscillator. Drawing inspiration from the idea of inherent structures in liquids, we interpret each of the spatial contributions as a specific molecular mode. These modes can be used to model and predict the NMR dipole–dipole relaxation dispersion of fluids by incorporating phenomena on the molecular level. We validate our statistical mechanical description of the distribution in molecular modes with molecular dynamics simulations interpreted without any relaxation models or adjustable parameters: the most important poles in the Padé–Laplace transform of the simulated autocorrelation agree with the eigenvalues predicted by the theory

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗