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NASA NTRS2000

The Impact of ENSO on Extratropical Low Frequency Noise in Seasonal Forecasts

This study examines the uncertainty in forecasts of the January-February-March (JFM) mean extratropical circulation, and how that uncertainty is modulated by the El Nino/Southern Oscillation (ENSO). The analysis is based on ensembles of hindcasts made with an Atmospheric General Circulation Model (AGCM) forced with sea surface temperatures observed during; the 1983 El Nino and 1989 La Nina events. The AGCM produces pronounced interannual differences in the magnitude of the extratropical seasonal mean noise (intra-ensemble variability). The North Pacific, in particular, shows extensive regions where the 1989 seasonal mean noise kinetic energy (SKE), which is dominated by a "PNA-like" spatial structure, is more than twice that of the 1983 forecasts. The larger SKE in 1989 is associated with a larger than normal barotropic conversion of kinetic energy from the mean Pacific jet to the seasonal mean noise. The generation of SKE due to sub-monthly transients also shows substantial interannual differences, though these are much smaller than the differences in the mean flow conversions. An analysis of the Generation of monthly mean noise kinetic energy (NIKE) and its variability suggests that the seasonal mean noise is predominantly a statistical residue of variability resulting from dynamical processes operating on monthly and shorter times scales. A stochastically-forced barotropic model (linearized about the AGCM's 1983 and 1989 base states) is used to further assess the role of the basic state, submonthly transients, and tropical forcing, in modulating the uncertainties in the seasonal AGCM forecasts. When forced globally with spatially-white noise, the linear model generates much larger variance for the 1989 base state, consistent with the AGCM results. The extratropical variability for the 1989 base state is dominanted by a single eigenmode, and is strongly coupled with forcing over tropical western Pacific and the Indian Ocean, again consistent with the AGCM results. Linear calculations that include forcing from the AGCM variance of the tropical forcing and submonthly transients show a small impact on the variability over the Pacific/North American region compared with that of the base state differences.

Schubert, Siegfried D.↗

NASA NTRS1997

A Statistical Study of the Global Structure of the Ring Current

In this paper we derive the average configuration of the ring current as a function of the state of the magnetosphere as indicated by the Dst index. We sort magnetic field data from the Combined Release and Radiation Effects Satellite (CRRES) by spatial location and by the Dst index in order to produce magnetic field maps. From these maps we calculate local current systems by taking the curl of the magnetic field. NN7e find both the westward (outer) and the eastward (inner) components of the ring current. We find that the ring current intensity varies linearly with D.St as expected, and that the ring current is asymmetric for all Dst values. The azimuthal peak of the ring current is located in the afternoon sector for quiet conditions, and near midnight for disturbed conditions. The ring current also moves closer to the Earth during disturbed conditions. We are able to recreate the Dst index by integrating the magnetic perturbations caused by the ring current. We find that we needed to apply a 20 nT offset to Dst, and assume a perfectly conducting Earth to obtain an optimal agreement between the computed and the observed Dst. We interpret the 20 nT offset as the magnetic field generated by the quiet time ring current used as baseline in computing Dst.

Jorgensen, A. M.↗

NASA NTRSDate not supplied

Australian Bushfire in 2020: Accessing MERRA-2 Data in GES DISC Remotely through OPeNDAP & Calculating Statistics with Python3

The evolution and transport of thick haze from the 2020 Australian bushfire is tracked using the NASA Modern-Era Retrospective analysis for Research and Applications version 2 (MERRA-2) data archived at the NASA GES DISC data center. The MERRA-2 provides global data at 0.5 x 0.625 spatial resolution since the year 1980. In this use case, with xarray, a python3 library, we remotely accessed the hourly aerosol optical depth (AOD) and PM2.5 data through the OpeNDAP service provided by GES DISC. We also derived weekly data from hourly ones.

Xiaohua Pan↗

DOE OSTI2023

Evolution of titanium particle combustion in potassium perchlorate and air

Understanding titanium particle combustion processes is critical not only for characterizing existing pyrotechnic systems but also for creating new igniter designs. In order to characterize titanium particle combustion processes, morphologies, and temperatures, simultaneous spatially-resolved electric field holography and imaging pyrometry techniques were used to capture post-ignition data at up to 7 kHz. Due to the phase and thermal distortions present in the combustion cloud, traditional digital in-line holography techniques fail to capture accurate data. Here in this work, electric field holography techniques are used in order to cancel distortions and capture the three-dimensional spatial locations and diameters of the particles. In order to estimate the projected surface temperatures of the titanium particles, an imaging pyrometry method that ratios emission at 750 and 850 nm is utilized. Using these diagnostics, joint statistics are collected for particle size, morphology, velocity, and temperature. Results show that, early in the combustion process, the titanium particles are primarily oxidized by potassium perchlorate inside the igniter cup, resulting in projected surface temperatures near 3000 K. Later in the process, the particles interact with ambient air, resulting in lower surface temperatures around 2400 K and the formation of flame zones. These results are consistent with adiabatic flame temperature predictions as well as particle morphology observations of a titanium core with a TiO 2 surface. Late stage particle expansion, star fragmentation, and molten droplet breakup events are also observed using the time-resolved morphology and temperature diagnostics. These results illustrate the different stages of titanium particle combustion in pyrotechnic environments, which can be used to inform improvements in next-generation igniters.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2025

A Probabilistic Model for Global EMIC Wave Activity Using Van Allen Probes Observations

Electromagnetic ion cyclotron (EMIC) waves play a key role in radiation belt dynamics through resonant interactions. However, their low occurrence probability, high variability, and spatial intermittency pose challenges for accurate modeling. In this study, we present a machine learning (ML)-based global EMIC wave model built on the entire data set from the Van Allen Probes mission. To capture the distinct statistical characteristics of wave occurrence and amplitude, the model is separated into two modules: an occurrence model trained using ML techniques, and a wave amplitude model sampled from observed probability distributions. The input parameters are limited to real-time or predictable variables to ensure practical applicability. Our model shows strong performance across the entire test set and demonstrates improved predictive capability over a baseline random occurrence model, particularly during quiet geomagnetic conditions. Evaluation during both quiet and active periods confirms the model's ability to represent the clustered and intermittent nature of EMIC wave activity. Furthermore, the model provides global estimates of wave power, enabling integration with radiation belt electron data and showing signatures consistent with wave-induced scattering. We found a good correlation between the global wave activity from the model and relativistic electron observation by Van Allen Probes, regardless of the availability of in situ wave observations. The modular structure of the model also allows for straightforward expansion for additional wave properties, such as wave frequency, which can be modeled independently. This flexible, event-sensitive approach offers a promising framework for data-driven radiation belt simulations and space weather applications.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2026

Development of a 95-Year Solar Dataset for Resource Adequacy Studies

Long-term high-resolution solar data provides enhanced understanding of variability of solar generation and enhances our ability to develop strategies for a resilient and reliable electric grid under high deployment of solar energy. Therefore, it is important to develop long-term synthetic datasets that can provide multiple occurrences of various severe weather scenarios that are expected to test the limits of resource adequacy under scenarios contain various energy generation sources. Examples of such scenarios could be long periods of high temperatures when demand for electricity is high or periods where high winds could lead to a shut-down of transmission lines for long periods of time to ensure fire safety. NREL has developed the first version of such a dataset covering a 95-year period covering 2006-2100 at a 4km hourly resolution. This dataset contains all variables necessary to calculate solar generation. During development of this dataset, we focused on creating unbiased, high-resolution solar irradiance through statistical downscaling methods, using Regional Climate Model (RCM) simulations from the North American Coordinated Regional Climate Downscaling Experiment (NA-CORDEX) as input. The National Solar Radiation Database (NSRDB) containing over 25 years of observations was used to calibrate the statistical downscaling models. This presentation will outline the primary steps in developing this dataset, including (1) regridding RCM data to a common grid at 20-km resolution, (2) correcting RCM biases with NSRDB, (3) applying temporal and spatial downscaling methods to generate high-resolution (4-km, hourly) solar and ancillary data. Additionally, we will present an evaluation of the downscaled data against the NSRDB across various zones in the CONUS. Lastly, we will present a user guide for accessing the datasets.

14 SOLAR ENERGY↗

DOE OSTI2022

Inferring the Thermal History of the Intergalactic Medium from the Properties of the Hydrogen and Helium Lyα Forest

The filamentary network of intergalactic medium (IGM) gas that gives origin to the Lyα forest in the spectra of distant quasars encodes information on the physics of structure formation and the early thermodynamics of diffuse baryonic material. Here we use a massive suite of more than 400 high-resolution cosmological hydrodynamical simulations run with the Graphics Processing Unit–accelerated code Cholla to study the IGM at high spatial resolution maintained over the entire computational volume. The simulations capture a wide range of possible IGM thermal histories by varying the photoheating and photoionizing background produced by star-forming galaxies and active galactic nuclei. A statistical comparison of synthetic spectra with the observed 1D flux power spectra of hydrogen at redshifts 2.2 ≤ z ≤ 5.0 and with the helium Lyα opacity at redshifts 2.4 < z < 2.9 tightly constrains the photoionization and photoheating history of the IGM. By leveraging the constraining power of the available Lyα forest data to break model degeneracies, we find that the IGM experienced two main reheating events over 1.2 Gyr of cosmic time. For our best-fit model, hydrogen reionization completes by z R ≈ 6.0 with a first IGM temperature peak of T 0 ≃ 1.3 × 10 4 K and is followed by the reionization of He ii that completes by z R ≈ 3.0 and yields a second temperature peak of T 0 ≃ 1.4 × 10 4 K. We discuss how our results can be used to obtain information on the timing and the sources of hydrogen and helium reionization.

79 ASTRONOMY AND ASTROPHYSICS↗

NASA NTRS1972

A review of some aspects of inferring the ozone profile by inversion of ultraviolet radiance measurements

The mathematical inversion of light-scattering observations to obtain the atmospheric ozone profile is discussed in terms of the filtering properties of the physical and mathematical processes for different spatial scales. Within this context, it is shown that the physical process of scattering acts as a low pass filter; which transfers large-scale profile information efficiently to radiance observations but very strongly attenuates small- or fine-scale profile information. To avoid domination of the mathematical inversion by the random error of radiance measurements, an equivalent spatial-scale filtering in the inversion procedure is essential. The available evidence suggests that mathematical inversion to obtain the low level ozone profile below 25 to 30 km is either inferior to or no better than the statistical estimation of the profile using total ozone as predictor. However, inversion profiles for high level ozone above 25 to 30 km appear to have moderately good accuracy.

Mateer, C. L.↗

NASA NTRS1972

An experimental investigation of the power spectrum of phase modulation induced on a satellite radio signal by the ionosphere

The power spectrum of phase modulation imposed upon satellite radio signals by the inhomogeneous F-region of the ionosphere (100 - 500 km) was studied. Tapes of the S-66 Beacon B Satellite recorded during the period 1964 - 1966 were processed to yield or record the frequency of modulation induced on the signals by ionospheric dispersion. This modulation is produced from the sweeping across the receiving station as the satellite transits of the two dimensional spatial phase pattern are produced on the ground. From this a power spectrum of structure sizes comprising the diffracting mechanism was determined using digital techniques. Fresnel oscillations were observed and analyzed along with some comments on the statistical stationarity of the shape of the power spectrum observed.

Moser, D. T.↗

NASA NTRS1973

Comparative evaluation of spatial features in automatic land use classification from photographic imagery

Five spatial features have been evaluated for their applicability in automatic land use classification of photographic imagery. Data arrays of approximately 10,000 square meters were classified on the basis of an 8 by 8 point data array. Statistical features, information features, sequency features and texture features were evaluated using a distance to prototype classifier and an adaptive classifier. The results indicate approximately 70% accuracy in the classification.

Herzog, J. H.↗

NASA NTRS1985

Influence of spatial variability of hydraulic characteristics of soils on surface parameters obtained from remote sensing data in infrared and microwaves

The correct interpretation of thermal and hydraulic soil parameters infrared from remotely sensed data (thermal infrared, microwaves) implies a good understanding of the causes of their temporal and spatial variability. Given this necessity, the sensitivity of the surface variables (temperature, moisture) to the spatial variability of hydraulic soil properties is tested with a numerical model of heat and mass transfer between bare soil and atmosphere. The spatial variability of hydraulic soil properties is taken into account in terms of the scaling factor. For a given soil, the knowledge of its frequency distribution allows a stochastic use of the model. The results are treated statistically, and the part of the variability of soil surface parameters due to that of soil hydraulic properties is evaluated quantitatively.

Brunet, Y.↗

NASA NTRS1986

Utilizing remote sensing of Thematic Mapper data to improve our understanding of estuarine processes and their influence on the productivity of estuarine-dependent fisheries

LANDSAT thematic mapper (TM) data are being used to refine and validate a stochastic spatial computer model to be applied to coastal resource management problems in Louisiana. Two major aspects of the research are: (1) the measurement of area of land (or emergent vegetation) and water and the length of the interface between land and water in TM imagery of selected coastal wetlands (sample marshes); and (2) the comparison of spatial patterns of land and water in the sample marshes of the imagery to that in marshes simulated by a computer model. In addition to activities in these two areas, the potential use of a published autocorrelation statistic is analyzed.

Browder, J. A.↗

NASA NTRS1993

Cloud properties from the analysis of AVHRR observations for FIRE 2

Preliminary results are presented for cloud properties from the analysis of AVHRR observations for FIRE 2. The properties were obtained from a combination of the spatial coherence method and a multispectral retrieval scheme. Geographically gritted fields for the number of cloud layers were produced. For single layered cloud systems, fractional cloud cover, cloud emission temperature, cloud emissivity, and particle size were retrieved. Statistics on the properties of upper-level clouds and the Coffeeville cloud conditions are presented.

Lin, Xijian↗

NASA NTRS1993

Testing higher-order Lagrangian perturbation theory against numerical simulation. 1: Pancake models

We present results showing an improvement of the accuracy of perturbation theory as applied to cosmological structure formation for a useful range of quasi-linear scales. The Lagrangian theory of gravitational instability of an Einstein-de Sitter dust cosmogony investigated and solved up to the third order is compared with numerical simulations. In this paper we study the dynamics of pancake models as a first step. In previous work the accuracy of several analytical approximations for the modeling of large-scale structure in the mildly non-linear regime was analyzed in the same way, allowing for direct comparison of the accuracy of various approximations. In particular, the Zel'dovich approximation (hereafter ZA) as a subclass of the first-order Lagrangian perturbation solutions was found to provide an excellent approximation to the density field in the mildly non-linear regime (i.e. up to a linear r.m.s. density contrast of sigma is approximately 2). The performance of ZA in hierarchical clustering models can be greatly improved by truncating the initial power spectrum (smoothing the initial data). We here explore whether this approximation can be further improved with higher-order corrections in the displacement mapping from homogeneity. We study a single pancake model (truncated power-spectrum with power-spectrum with power-index n = -1) using cross-correlation statistics employed in previous work. We found that for all statistical methods used the higher-order corrections improve the results obtained for the first-order solution up to the stage when sigma (linear theory) is approximately 1. While this improvement can be seen for all spatial scales, later stages retain this feature only above a certain scale which is increasing with time. However, third-order is not much improvement over second-order at any stage. The total breakdown of the perturbation approach is observed at the stage, where sigma (linear theory) is approximately 2, which corresponds to the onset of hierarchical clustering. This success is found at a considerable higher non-linearity than is usual for perturbation theory. Whether a truncation of the initial power-spectrum in hierarchical models retains this improvement will be analyzed in a forthcoming work.

Buchert, T.↗

NASA NTRS2007

Diurnal Lightning Distributions as Observed by the Optical Transient Detector (OTD) and the Lightning Imaging Sensor (LIS)

Data obtained from the Optical Transient Detector (April 1995 to March 2000) and the Lightning Imaging Sensor (December 1997 to December 2005) satellites (70 and 35 inclination low earth orbits, respectively) are used to statistically determine the number of flashes in the annual and seasonal diurnal cycle as a function of local and universal time. The data are further subdivided by season, land versus ocean, northern versus southern hemisphere, and other spatial (e.g., continents) and temporal (e.g., time of peak diurnal amplitude) categories. The data include corrections for detection efficiency and instrument view time. Continental results display strong diurnal variation, with a lightning peak in the late afternoon and a minimum in late morning. In regions of the world dominated by large mesoscale convective systems the peak in the diurnal curve shifts toward late evening or early morning hours. The maximum diurnal flash rate occurs in June-August, corresponding to the Northern Hemisphere summer, while the minimum occurs in December-February. Summer lightning dominates over winter activity and springtime lightning dominates over autumn activity at most continental locations. This latter behavior occurs especially strongly over the Amazon region in South America in September-November. Oceanic lightning activity in winter and autumn tends to exceed that in summer and spring. Global lightning is well correlated in phase but not in amplitude with the Carnegie curve. The diurnal flash rate varies about 4-35 percent about the mean, while the Carnegie curve varies around 4-15 percent.

Bailey, Jeff C.↗

NASA NTRS2026

CH3OH and HCN in Interstellar Comet 3I/ATLAS Mapped with the ALMA Atacama Compact Array: Distinct Outgassing Behaviors and a Remarkably High CH3OH/HCN Production Rate Ratio

We report the detection of methanol (CH3OH) toward interstellar comet 3I/ATLAS using the At-acama Compact Array of the Atacama Large Millimeter/Submillimeter Array (ALMA) on UT 2025 August 28, September 18 and 22, and October 1, and of hydrogen cyanide (HCN) on September 12 and 15. These observations spanned pre-perihelion heliocentric distances (r H ) of 2.6 – 1.7 au. The molecules showed outgassing patterns distinct from one another, with HCN production being depleted in the sunward hemisphere of the coma, whereas CH3OH was enhanced in that direction. Statistical analysis of molecular scale lengths in 3I/ATLAS indicated that CH3OH included production from coma sources at Lp > 258 km at 99% confidence. However low signal-to-noise on long baselines, which sample emission on small spatial scales closest to the nucleus, prevented definitively ruling out CH3OH as purely a parent species. In contrast, HCN production was indistinguishable from direct nucleus sublimation. The CH3OH production rate increased sharply from August through October, including an uptick near the inner edge of the H2O sublimation zone at rH = 2 au. Compared to comets measured to date at radio wavelengths, the derived CH3OH/HCN ratios in 3I/ATLAS of 124+30−34 and 79+11−14on September 12 and 15, respectively, are among the most enriched values measured in any comet, surpassed only by anomalous solar system comet C/2016 R2 (PanSTARRS)

Comae↗

NASA NTRS2017

On the Impact of Granularity of Space-Based Urban CO2 Emissions in Urban Atmospheric Inversions: A Case Study for Indianapolis, IN

Quantifying greenhouse gas (GHG) emissions from cities is a key challenge towards effective emissions management. An inversion analysis from the INdianapolis FLUX experiment (INFLUX) project, as the first of its kind, has achieved a top-down emission estimate for a single city using CO2 data collected by the dense tower network deployed across the city. However, city-level emission data, used as a priori emissions, are also a key component in the atmospheric inversion framework. Currently, fine-grained emission inventories (EIs) able to resolve GHG city emissions at high spatial resolution, are only available for few major cities across the globe. Following the INFLUX inversion case with a global 1x1 km ODIAC fossil fuel CO2 emission dataset, we further improved the ODIAC emission field and examined its utility as a prior for the city scale inversion. We disaggregated the 1x1 km ODIAC non-point source emissions using geospatial datasets such as the global road network data and satellite-data driven surface imperviousness data to a 3030 m resolution. We assessed the impact of the improved emission field on the inversion result, relative to priors in previous studies (Hestia and ODIAC). The posterior total emission estimate (5.1 MtC/yr) remains statistically similar to the previous estimate with ODIAC (5.3 MtC/yr). However, the distribution of the flux corrections was very close to those of Hestia inversion and the model-observation mismatches were significantly reduced both in forward and inverse runs, even without hourly temporal changes in emissions. EIs reported by cities often do not have estimates of spatial extents. Thus, emission disaggregation is a required step when verifying those reported emissions using atmospheric models. Our approach offers gridded emission estimates for global cities that could serves as a prior for inversion, even without locally reported EIs in a systematic way to support city-level Measuring, Reporting and Verification (MRV) practice implementation.

EIs↗

DOE OSTI2020

GIS-Based Modeling of Contaminated Soil Volumes at Multiple Sites in the Formerly Utilized Sites Remedial Action Program - 20149

The remediation of hazardous, toxic, and radioactive waste (HTRW) sites produces cost-related risks associated with the estimation of contaminated soil or debris volumes. Historical risk-management techniques include cost contingencies to cover volume uncertainties that affect project budgeting and decision-making. The Buffalo District teamed with project partners to lessen volume uncertainty and reduce project risks at multiple HTRW sites managed under the Formerly Utilized Sites Remedial Action Program (FUSRAP). Historical remedial investigations under FUSRAP commonly identified the presence of radiological material in site media, the associated human health risk, and then areas of remediation. To manage remedial execution and reduce risk, pre-design or remediation-phase sampling essentially 'chased' contamination, which was not conducive to efficient predictive budgeting derived from Feasibility Study (FS) cost analyses. The Buffalo District first optimized their approach to better understand volume uncertainty by utilizing the Argonne National Laboratory's Bayesian Approaches for Adaptive Spatial Sampling (BAASS) software [1]. BAASS processed soft data (e.g., gamma walk-over data) and spatial sampling data to estimate the lateral extent of contaminated soil irrespective of depth (i.e., gross contamination extent) and define areas of contaminant uncertainty. The software performed a binary transformation of contaminant concentrations at all sampling points based upon remedial action goals or a sum of ratios approach (i.e., clean, impacted, or range of impacts in soil). The model produced two-dimensional (horizontal) contaminant probability contours and statistical uncertainty in the sampling coverage and resulting contaminant extents. This method was translated vertically by partitioning the sampling data into depth brackets that produced a stacked representation of contaminant extents and uncertainty in the subsurface (i.e., similar to construction lifts). The results commonly led to a better understanding of project uncertainty and the need for sampling strategies that produce high-confidence soil volumes, which control costs. The BAASS-based delineations were eventually replaced by Empirical Bayesian Kriging (EBK) methods available in ArcGIS Spatial or 3D Analysts [2]. The EBK method calculates contaminant probability zones derived from user-controlled semivariograms of the spatial datasets. The resulting probability zones (e.g., 50% or 80% of contaminant probability) represent the two-dimensional surface delineation of the overall horizontal remedial area, similarly to BAASS. However, unlike BAASS, the vertical sampling data within these probability zones became vertical control points to contour a subterranean surface that connects subsurface points to the land-surface delineations of contamination. The resulting representation of horizontal and vertical impacts within an enclosed envelop (volume) of soil included uncertainty distributions that are used to plan uncertainty-reduction sampling. These data-driven and math-based models of three-dimensional sampling results produced well-bounded remedial volumes for project planning and better uncertainty predictions during project budgeting. The EBK method was applied to several FUSRAP sites managed by the Buffalo District and compared to less rigorously modeled sites previously remediated by the District. The comparison of modeled to actual remediated volumes provide a basis for validating the volume-estimation method. This comparison is important to ensure modeled volumes match physical boundaries of site remediation. FUSRAP sites with denser investigative sampling and lesser volume uncertainty proved useful in remedial planning and contracting. The Buffalo District noted that historical sites with sparser sampling arrays had greater disparity between estimated volumes and final remedial volumes. The benefit achieved over the cost of detailed soil sampling appears positive for FUSRAP projects, especially where impacts vary widely and appear unbounded by investigation-phase sampling. The subsequent Empirical Bayesian Kriging of contamination coupled with vertical contouring for soil estimations reduces uncertainty in soil volumes or indicates where sampling is required to reduce uncertainty, which together optimize remedial planning and budgeting. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗