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At least 397 records · Page 22
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Quantifying albedo susceptibility biases in shallow clouds

The evaluation of radiative forcing associated with aerosol–cloud interactions remains a significant source of uncertainty in future climate projections. The problem is confounded by the fact that aerosol particles influence clouds locally and that averaging to larger spatial and/or temporal scales carries biases that depend on the heterogeneity and spatial correlation of the interacting fields and the nonlinearity of the responses. Mimicking commonly applied satellite data analyses for calculation of albedo susceptibility S o , we quantify S o aggregation biases using an ensemble of 127 large eddy simulations of marine stratocumulus. We explore the cloud field properties that control this spatial aggregation bias and quantify the bias for a large range of shallow stratocumulus cloud conditions manifesting a variety of morphologies and ranges of cloud fractions. We show that S o spatial aggregation biases can be on the order of hundreds of percent, depending on the methodology. Key uncertainties emanate from the typically applied adiabatic drop concentration N d retrieval, the correlation between aerosol and cloud fields, and the extent to which averaging reduces the variance in cloud albedo A c and N d . So biases are more often positive than negative and are highly correlated with biases in the liquid water path adjustment. Temporal aggregation biases are shown to offset spatial aggregation biases. Both spatial and temporal biases have significant implications for observationally based assessments of aerosol indirect effects and our inferences of underlying aerosol–cloud–radiation effects.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Imaging Carrier Dynamics and Transport in Hybrid Perovskites with Transient Absorption Microscopy

In this review, the recent progress in using transient absorption microscopy to image charge transport and dynamics in semiconducting hybrid organic–inorganic perovskites is discussed. The basic principles, instrumentation, and resolution of transient absorption microscopy are outlined. With temporal resolution as high as 10 fs, sub-diffraction-limit spatial resolution, and excited-state structural resolution, these experiments have provided crucial details on charge transport mechanisms that have been previously obscured in conventional ultrafast spectroscopy measurements. Morphology-dependent mapping unveils spatial heterogeneity in carrier recombination and cooling dynamics. By spatially separating the pump and probe beams, carrier transport across grain boundaries has been directly visualized. Further, femtosecond temporal resolution allows for the examination of nonequilibrium transport directly, revealing extraordinarily long-range hot carrier migration. The application of transient absorption microscopy is not limited to hybrid perovskites but can also be useful for other polycrystalline materials in which morphology plays an important role in carrier transport.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Tensor factorization for elucidating mechanisms of piezoresponse relaxation via dynamic Piezoresponse Force Spectroscopy

Spatially resolved time and voltage-dependent polarization dynamics in PbTiO 3 thin films is explored using dynamic piezoresponse force microscopy (D-PFM) in conjunction with interferometric displacement sensing. This approach gives rise to 4D data sets containing information on bias-dependent relaxation dynamics at each spatial location without long-range electrostatic artifacts. To interpret these data sets in the absence of defined physical models, we employ a non-negative tensor factorization method which clearly presents the data as a product of simple behaviors allowing for direct physics interpretation. Correspondingly, we perform phase-field modeling finding the existence of ‘hard’ and ‘soft’ domain wall edges. This approach can be extended to other multidimensional spectroscopies for which even exploratory data analysis leads to unsatisfactory results due to many components in the decomposition.

36 MATERIALS SCIENCE↗
NASA NTRS1985

The expected cosmic ray density and stream distributions at the heliolatitudinal asymmetry of solar wind

The results of the spatial distribution of cosmic ray density, gradients, and anisotropy obtained on the basis of the numerical solution of the anisotropic diffusion equation with an account of solar wind velocity change depending on the latitudinal angle theta of the form U=u sub oe sup alpha theta and the diffusion coefficient depending on the spatial coordinates and the particle rigidity are presented. It is shown that the increase of the solar wind velocity and the diffusion coefficient with heliolatitude leads to gradient distributions that are in accord with experimental data observed in space. The results of the energetic spectrum of 11 and 22-year cosmic ray variations obtained with an account of direction of the general magnetic field of the Sun are presented are given.

Alania, M. V.↗
NASA NTRSDate not supplied

Simulation of Radiation-Induced DNA Damage With the Code RITRACKS

INTRODUCTION DNA damage is one of the most physiologically important effects of ionizing radiation. Clustered DNA damage events, like double-strand breaks (DSBs), have the most notable biological consequences. DNA damage types depend on both the track structure of the radiation and the spatial organization of the DNA. High linear energy transfer (LET) charged nuclei, found in galactic cosmic rays (GCR), are known to produce large numbers of complex DNA damage events. The human genome is packaged into chromatin, which can take on locus-dependent and cell type-dependent spatial conformations that correspond to epigenetic states, such as more open, extended structures in transcriptionally active chromatin. These epigenetic differences can affect DNA break patterns in response to ionizing radiation, potentially creating distinct DNA repair and signaling outcomes across the genome in different cells. MATERIAL AND METHODS The code RITRACKS (Relativistic Ion Tracks), which simulates stochastic radiation track structures and radiation chemistry, was used to model damage on isolated and histone-bound DNA by various types of ions and photons. The changes made to the code to perform radiation-induced DNA damage, and simulation results on single nucleosomes are given in our recent paper. In this work, the DNA building capabilities of RITRACKS have been extended to simulate more complex DNA structures build on the coarse-grain simulation framework meso-WLCsim. This code can sample generic chromatin fiber conformation ensembles based on the geometry of nucleosomes and mechanical properties of DNA. Using RITRACKS, we simulated the fragment length distributions (FLD) of irradiated DNA structures built using the chromatin conformations of WLCsim and obtained results representative of those obtained with Radiation-Induced Correlated Cleavage with sequencing (RICC-Seq) experiments [6]. We have also performed Fe ion and photon irradiations of K562, IMR90, BJ and RPE-1 cells at NSRL to experimentally validate results. Sample processing and data analysis are in progress and any available preliminary results will be discussed. DISCUSSION The recent updates in the code RITRACKS allow the calculation of several quantities such as the DNA damage yield and the FLD. This approach can be used to model epigenetic state-specific chromatin structure parameters to leverage the epigenetic state data available for many human cell types to infer relative DNA damage sensitivity among genomic loci.

I Plante↗
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↗
DOE OSTI2022

Special Issue: Geostatistics and Machine Learning

Abstract Recent years have seen a steady growth in the number of papers that apply machine learning methods to problems in the earth sciences. Although they have different origins, machine learning and geostatistics share concepts and methods. For example, the kriging formalism can be cast in the machine learning framework of Gaussian process regression. Machine learning, with its focus on algorithms and ability to seek, identify, and exploit hidden structures in big data sets, is providing new tools for exploration and prediction in the earth sciences. Geostatistics, on the other hand, offers interpretable models of spatial (and spatiotemporal) dependence. This special issue on Geostatistics and Machine Learning aims to investigate applications of machine learning methods as well as hybrid approaches combining machine learning and geostatistics which advance our understanding and predictive ability of spatial processes.

58 GEOSCIENCES↗
NASA NTRS1980

Propagation in a shearing plasma. II - Turbulence and the frequency range of pulsar microstructure

Numerical calculations are presented which explore the propagation of radio waves and pulses through a turbulent shearing plasma. A stochastic model is used to describe the turbulent velocity field, in which random fluctuations are superposed on a mean profile. Both Gaussian wave packets and shot-noise pulses polarized in the plane of shearing acquire quasi-periodic intensity modulations above the rest-frame plasma frequency. The frequency range over which these modulations appear is shown to depend on the spatial correlation length of the turbulent fluctuations and on their standard deviation from the mean velocity. The period of the modulations is variable from one realization of the random process to the next, and the average period is frequency dependent. The results of these calculations lend further support to a model for pulsar microstructure in which periodic micropulses are pure temporal modulations of the emitted radiation due to propagation effects in magnetospheric shearing regions. It is shown that turbulence on a scale of approximately 10 cm can produce these quasi-periodic modulations over a frequency range comparable to that of observed microstructure.

Harding, A. K.↗
NASA NTRS1989

Galaxy clustering and the origin of large-scale flows

Peebles's 'cosmic virial theorem' is extended from its original range of validity at small separations, where hydrostatic equilibrium holds, to large separations, in which linear gravitational stability theory applies. The rms pairwise velocity difference at separation r is shown to depend on the spatial galaxy correlation function xi(x) only for x less than r. Gravitational instability theory can therefore be tested by comparing the two up to the maximum separation for which both can reliably be determined, and there is no dependence on the poorly known large-scale density and velocity fields. With the expected improvement in the data over the next few years, however, this method should yield a reliable determination of omega.

Juszkiewicz, R.↗
NASA NTRS1987

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

A stochastic spatial computer model addressing coastal resource problems in Lousiana is being refined and validated using thematic mapper (TM) imagery. The TM images of brackish marsh sites were processed and data were tabulated on spatial parameters from TM images of the salt marsh sites. The Fisheries Image Processing Systems (FIPS) was used to analyze the TM scene. Activities were concentrated on improving the structure of the model and developing a structure and methodology for calibrating the model with spatial-pattern data from the TM imagery.

Browder, Joan A.↗
DOE OSTI2024

Large-scale spatially explicit analysis of carbon capture at cellulosic biorefineries

The large-scale production of cellulosic biofuels would involve spatially distributed systems including biomass fields, logistics networks and biorefineries. Better understanding of the interactions between landscape-related decisions and the design of biorefineries with carbon capture and storage (CCS) in a supply chain context is needed to enable efficient systems. Here we analyse the cost and greenhouse gas mitigation potential for cellulosic biofuel supply chains in the US Midwest using realistic spatially explicit land availability and crop productivity data and consider fuel conversion technologies with detailed CCS design for their associated CO 2 streams. Optimization methods identify trade-offs and design strategies leading to systems with attractive environmental and economic performance. Strategic and operational decisions depend on underlying spatial features and are sensitive to biofuel demand and CCS incentives. US CCS incentives neglect to motivate greenhouse gas mitigation from all supply chain emission sources, which leverage spatial interactions between CCS, electricity prices and the biomass landscape.

09 BIOMASS FUELS↗
NASA NTRS1987

Evaluation of several classification schemes for mapping forest cover types in Michigan

Landsat MSS data were evaluated for mapping forest cover types in the northern Lower Peninsula of Michigan. The study examined seasonal variations, interpretation procedures and vegetation composition/distribution and their effect on overall classification accuracy and ability to identify individual pine species. Photographic images were used for visual interpretations while digital analysis was performed using a common (ERDAS) microcomputer image processing system. The classification schemes were evaluated using contingency tables and were ranked using the KAPPA statistic. The various classification schemes were ranked differentially according to study site location. Visual interpretation procedures ranked best, or least accurate, depending on the spatial distribution and complexity of the forest cover. Supervised classification techniques were more accurate than unsupervised clustering over all sites and seasons. Maximum likelihood classification of June data was superior to any digital classification technique of February data. The study indicates that classification accuracy is more dependent on the composition and distribution of forests in the northern lower Peninsula of Michigan than on the selection of a particular classification scheme.

Hudson, W. D.↗
DOE OSTI2023

Stochastic Models, Indices & Optimization Algorithms for Pricing & Hedging Reliability Risks in Modern Power Grids: Data Plan - Princeton

We collected and cleaned the synthetic grid data produced by NREL for the Texas and New York synthetic grids. We developed a high dimensional joint stochastic model for load at the zone level, and solar and wind power productions at the asset level, capturing the spatial and temporal dependencies between all the variables, and demonstrated how such a model could be fitted to historical data. We designed and implemented a simulation engine which can produce Monte Carlo scenarios for the hourly day-ahead values of load, and solar and wind power productions at the spatial and temporal resolutions of the historical data used to fit the model. Finally we developed an open-source Python package which can, from an input grid model, efficiently use forecasts and large numbers of Monte Carlo scenarios to provide unit commitment and economic dispatch for each of these scenarios. The high dimensional stochastic model and the subsequent Monte Carlo simulation engine were implemented in the package PGscen and the corresponding UC and ED optimization programs in the package Vatic.

14 SOLAR ENERGY↗
DOE OSTI2020

Time-dependent Ginzburg-Landau treatment of rf magnetic vortices in superconductors: Vortex semiloops in a spatially nonuniform magnetic field

We apply time-dependent Ginzburg-Landau (TDGL) numerical simulations to study the finite frequency electrodynamics of superconductors subjected to an intense rf magnetic field. Much recent TDGL work has focused on spatially uniform external magnetic fields and largely ignores the Meissner state screening response of the superconductor. In this paper, we solve the TGDL equations for a spatially nonuniform magnetic field created by a point magnetic dipole in the vicinity of a semi-infinite superconductor. A two-domain simulation is performed to accurately capture the effect of the inhomogeneous applied fields and the resulting screening currents. The creation and dynamics of vortex semiloops penetrating deep into the superconductor domain are observed and studied, and the resulting third-harmonic nonlinear response of the sample is calculated. Further, the effect of pointlike defects on vortex semi-loop behavior is also studied. This simulation method will assist our understanding of the limits of superconducting response to intense rf magnetic fields.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
NASA NTRS1993

An Imaging Interferometer for Terrestrial Remote Sensing

A prototype imaging interferometer called DASI (digital array scanned interferometer) is under development at our laboratories. Our objective is to design an instrument for remote sensing of Earth's atmosphere and surface. This paper describes the unusual characteristics of DASIs which make them promising candidates for ground and aircraft-based terrestrial measurements. These characteristics include superior signal-to-noise, design simplicity and compactness, relative to dispersion based imaging spectrometers. Perhaps one of the most notable features of DASIs is their ability to acquire an entire interferogram simultaneously without any moving optical elements. We also describe selected laboratory and ground based field measurements using the prototype DASI. A CCD detector array was placed at the DASI detector plane for wavelength coverage from 0.4 to 1.0 micron. A NICMOS MCT detector was used for coverage from 1.1 to 2.2 micron. The DASI was configured to have a spectral resolution of about 300 1/cm, a spatial field of view of 5 degrees, and a constant number of transverse spatial elements (detector dependent) for each exposure frame. Frame exposure rates were up to 0.6 Hz with the potential to achieve 5 Hz. Image cube measurements of laboratory targets and terrestrial scenes were obtained by multiple frame scanning over the field of view. These data sets reveal the potential science yields from obtaining simultaneous high resolution spatial and spectral information.

Hammer, Philip D.↗
NASA NTRS1992

Mars: Wavelength-dependent dual polarization global scattering

During the 1988 and 1990 Mars oppositions, the first continuous-wave (CW) multi-wavelength radar observations were performed that include the entire echo in both polarizations. These observations, coordinated in subradar coverage when possible, were made with the Arecibo S-band (12.6 cm lambda) and Goldstone X-band (3.5 cm lambda) facilities. The CW spectra obtained during these oppositions have been studied using a variety of techniques to explore the spatial and wavelength dependence of both the Same-sense Circular (SC) and Opposite-sense Circular (OC) polarization returns. Earlier multi-wavelength comparisons dealt primarily with the quasispecular component of the echoes. Our work in contrast has much new information (at high signal-to-noise) for the SC 'depolarized component. The unique value of these radar observations lies in their potential for probing the subsurface scattering behavior in 'appropriate' terrain. The clearest case for wavelength dependence in the SC component is the scattering behavior over Tharsis, where the X-band features are significantly weaker than the S-band features. This hypothesis was advanced to account for the low thermal inertia of Tharsis, but also can explain the S/X differences if the layer is about 40 cm thick. In contrast to the Tharsis result, the depolarized echo from the heavily cratered terrain is actually stronger at X-band. The obvious interpretation is that more scatterers exist at the scale of the shorter wavelength, either at the surface or as a distributed subsurface scatterers. The strongest depolarized feature of the X-band spectra is associated with the south residual polar cap. The radar cross section of this feature corresponds to an equivalent full-disk albedo of unity.

Harmon, J. K.↗
NASA NTRS1989

Combined first- and second-order Fermi acceleration in cometary environments

Two-dimensional (one velocity space and one spatial dimension), time-dependent model calculations indicate that an interplay between velocity and spatial diffusion may be responsible for the acceleration of implanted heavy ions in the cometary preshock region. Velocity diffusion (second-order Fermi acceleration) accelerates the pickup ions to moderate energies, thus creating a seed population for the more efficient diffusive-compressive shock acceleration. Solar wind convection limits the time available for diffusive-compressive acceleration. Therefore, the resulting energy spectrum above the pickup energy is a combination of an exponential decrease at lower energies (up to about 100 keV) and a power law spectrum at higher energies. The calculated energy spectra constitute a surprisingly good fit to the published Vega and Giotto energy spectra above the pickup energy.

Gombosi, T. I.↗
NASA NTRSDate not supplied

Determining True Sensor Spatial Resolution of Very High Resolution Optical Imagery

Some satellite data is delivered in images with gridded pixels. This gridded pixel size is often assumed to be the spatial resolution of the satellite sensor; however, this is not always the case. An image can be grided to any arbitrary pixel size, but the sensor resolution will remain constant. For example, an image with a pixel grid size much smaller than the sensor resolution will appear blurry along what should be sharp transitions. This discrepancy between an image’s pixel size and true sensor spatial resolution can be the source of much confusion and even misinformation among data users, which may lead them to waste time and resources on using images that do not suit their spatial resolution needs. This presentation will highlight our evaluation of the true spatial resolution of various government and commercial images in the pixel size range of 0.3 m to 60 m. Images evaluated include ESA’s Sentinel-2 (60 m, 20 m, 10 m pixels), USGS’s Landsat 8/9 (30 m & 15 m pixels), Planet’s SuperDoves (3 m pixels), BlackSky’s Globals (~1 m pixels), and the optical bands of Maxar’s WorldView-2 (2.4 m – 0.41 m pixels) and WorldView-3 (1.38 m – 0.31 m pixels). Our evaluation of true sensor spatial resolution, or ‘footprint size’ is based on the sensor’s line spread function (LSF). We calculate the width at half the height of the LSF to find the full width at half maximum (FWHM). The FWHM is how we report sensor spatial resolution. Different objects are examined for constructing the LSF depending on the sensor spatial resolution. Coarser resolution sensors in this evaluation such as Sentinel-2 and Landsat 8/9 are examined at bridges over a dark water background. The bright bridge acts as a line impulse, giving a sensor’s line spread function (LSF) in one direction. Additionally, we simulate the impacts of bridge width on the apparent LSF to obtain a true LSF without the effects of bridge width for these sensors. Finer resolution sensors will image the irregularities in bridges such as trusses, sidewalks, and in some cases painted lines, interfering with the LSF construction. Instead, these sensors are evaluated at large (60 m – 140 m) black and white checkerboards known as Cal/Val sites. At these locations, the image’s transition from black to white is extracted as an edge spread function (ESF). We calculate the derivative of this ESF to obtain the sensor’s LSF. From there, we find the FWHM as we do for the coarser resolution images. With the FWHM and pixel size, we determine how over- or under-sampled the images are. When the ratio of a sensor’s spatial resolution and the gridded image’s pixel size is less than 1, the image is considered under-sampled. In this case, each pixel’s information is unique but only a portion of that pixel’s ground area has been measured. On the other side, if the ratio is greater than 1, the image is considered over-sampled. That is, each pixel’s information is sourced from within the ground extent of the pixel and some extent outside additionally. We will show the true spatial resolution and the extent of over-/under-sampling in the imagery from ESA’s Sentinel-2 (60 m, 20 m, 10 m pixels), USGS’s Landsat 8/9 (30 m & 15 m pixels), Planet’s SuperDoves (3 m pixels), BlackSky’s Globals (~1 m pixels), and the optical bands of Maxar’s WorldView-2 (2.4 m – 0.41 m pixels) and WorldView-3 (1.38 m – 0.31 m pixels).

Alana Semple↗