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At least 1,135 records · Page 63
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NASA NTRS1979

Volatiles in Chainpur chondrules

A study of volatile element concentrations in individual chondrules in the Chainpur LL3 chondrite is presented. Volatile elements differing in geochemical behavior tended to vary randomly and correlated variations were observed only for those elements inferred to occupy similar mineral sites. Variations in Co and Ni in kamacite show that metal in chondrule interiors has not approached equilibrium, and that postformational element distribution has mainly altered siderophile concentrations in surface metal grains, and has probably left ionic species unaltered. Etching to remove 3 to 5% of the chondrule dissolved siderophiles, enhanced Zn and Na volatiles relative to nonvolatile Cr in the etch, and produced a large Cd enhancement. If metamorphic redistribution of nonsiderophile volatiles was neglible, their high concentrations are inconsistent with chondrule formation by direct condensation, and models involving sudden melting of preexisting solids can explain the observations but require rapid cooling to prevent volatile loss.

Grossman, J. N.↗
NASA NTRS1992

An axisymmetric magnetohydrodynamic model for the Crab pulsar wind bubble

We extend Kennel and Coroniti's (1984) spherical magnetohydrodynamic models for the Crab Nebula to include the pinching effect of the toroidal magnetic field. Since the bulk nebular flow is likely to be very submagnetosonic, a quasi-static treatment is possible. We show that the pinching effect can be responsible for the observed elongation of the pulsar wind bubble, as indicated by the surface brightness contours of optical synchrotron radiation. From the observed elongation we estimate a value for sigma, the ratio of Poynting flux to plasma kinetic energy flux in the free pulsar wind, which is consistent with previous results from spherical models. Using the inferred magnetic field configuration inside the pulsar wind bubble, combined with the observed dimensions of the X-ray nebula, we are able to constrain the particle distribution function. We conclude that, for a power-law injection function, the maximum energy has to be much larger in the pulsar equatorial region than in the polar region.

Begelman, Mitchell C.↗
NASA NTRS2007

Paleomagnetic Analysis Using SQUID Microscopy

Superconducting quantum interference device (SQUID) microscopes are a new generation of instruments that map magnetic fields with unprecedented spatial resolution and moment sensitivity. Unlike standard rock magnetometers, SQUID microscopes map magnetic fields rather than measuring magnetic moments such that the sample magnetization pattern must be retrieved from source model fits to the measured field data. In this paper, we presented the first direct comparison between paleomagnetic analyses on natural samples using joint measurements from SQUID microscopy and moment magnetometry. We demonstrated that in combination with apriori geologic and petrographic data, SQUID microscopy can accurately characterize the magnetization of lunar glass spherules and Hawaiian basalt. The bulk moment magnitude and direction of these samples inferred from inversions of SQUID microscopy data match direct measurements on the same samples using moment magnetometry. In addition, these inversions provide unique constraints on the magnetization distribution within the sample. These measurements are among the most sensitive and highest resolution quantitative paleomagnetic studies of natural remanent magnetization to date. We expect that this technique will be able to extend many other standard paleomagnetic techniques to previously inaccessible microscale samples.

Weiss, Benjamin P.↗
NASA NTRS2009

A Method for Retrieving Ground Flash Fraction from Satellite Lightning Imager Data

A general theory for retrieving the fraction of ground flashes in N lightning observed by a satellite-based lightning imager is provided. An "exponential model" is applied as a physically reasonable constraint to describe the measured optical parameter distributions, and population statistics (i.e., mean, variance) are invoked to add additional constraints to the retrieval process. The retrieval itself is expressed in terms of a Bayesian inference, and the Maximum A Posteriori (MAP) solution is obtained. The approach is tested by performing simulated retrievals, and retrieval error statistics are provided. The ability to retrieve ground flash fraction has important benefits to the atmospheric chemistry community. For example, using the method to partition the existing satellite global lightning climatology into separate ground and cloud flash climatologies will improve estimates of lightning nitrogen oxides (NOx) production; this in turn will improve both regional air quality and global chemistry/climate model predictions.

Koshak, William J.↗
NASA NTRS2012

Sensitivity of Ocean Reflectance Inversion Models for Identifying and Discriminating Between Phytoplankton Functional Groups

The daily, synoptic images provided by satellite ocean color instruments provide viable data streams for observing changes in the biogeochemistrY of marine ecosystems. Ocean reflectance inversion models (ORMs) provide a common mechanism for inverting the "color" of the water observed a satellite into marine inherent optical properties (lOPs) through a combination of empiricism and radiative transfer theory. lOPs, namely the spectral absorption and scattering characteristics of ocean water and its dissolved and particulate constituents, describe the contents of the upper ocean, information critical for furthering scientific understanding of biogeochemical oceanic processes. Many recent studies inferred marine particle sizes and discriminated between phytoplankton functional groups using remotely-sensed lOPs. While all demonstrated the viability of their approaches, few described the vertical distributions of the water column constituents under consideration and, thus, failed to report the biophysical conditions under which their model performed (e.g., the depth and thickness of the phytoplankton bloom(s)). We developed an ORM to remotely identifY Noctiluca miliaris and other phytoplankton functional types using satellite ocean color data records collected in the northern Arabian Sea. Here, we present results from analyses designed to evaluate the applicability and sensitivity of the ORM to varied biophysical conditions. Specifically, we: (1) synthesized a series of vertical profiles of spectral inherent optical properties that represent a wide variety of bio-optical conditions for the northern Arabian Sea under aN Miliaris bloom; (2) generated spectral remote-sensing reflectances from these profiles using Hydrolight; and, (3) applied the ORM to the synthesized reflectances to estimate the relative concentrations of diatoms and N Miliaris for each example. By comparing the estimates from the inversion model to those from synthesized vertical profiles, we were able to identifY those bio-optical conditions under which the inversion model performs both well and poorly.

Werdell, P. Jeremy↗
NASA NTRS2012

Comparison of Aerosol Classification From Airborne High Spectral Resolution Lidar and the CALIPSO Vertical Feature Mask

Knowledge of aerosol composition and vertical distribution is crucial for assessing the impact of aerosols on climate. In addition, aerosol classification is a key input to CALIOP aerosol retrievals, since CALIOP requires an inference of the lidar ratio in order to estimate the effects of aerosol extinction and backscattering. In contrast, the NASA airborne HSRL-1 directly measures both aerosol extinction and backscatter, and therefore the lidar ratio (extinction-to-backscatter ratio). Four aerosol intensive properties from HSRL-1 are combined to infer aerosol type. Aerosol classification results from HSRL-1 are used here to validate the CALIOP aerosol type inferences.

Burton, Sharon P.↗
NASA NTRS2012

Observing Changing Ecological Diversity in the Anthropocene

As the world enters the Anthropocene, the planet's environment is changing rapidly, putting critical ecosystem services at risk. Understanding and forecasting how ecosystems will change over the coming decades requires understanding the sensitivity of species to environmental change. The extant distribution of species and functional groups contains valuable information about the performance of different species in different environments. However, with high rates of environmental change, information inherent in ranges of many species will disappear, since that information exists only under quasi-equilibrium conditions. The information content of distributional data obtained now is greater than data obtained in the future. New remote sensing technologies can map chemical and structural traits of plant canopies and allow inference of trait and in many cases, species ranges. Current satellite remote sensing data can only produce relatively simple classifications, but new techniques have dramatically higher biological information content.

environmental changes↗
NASA NTRSDate not supplied

Evaluation of Spectral Band Adjustment Factors for Cross-Calibration of Visible Imagers

The NASA CERES EBAF dataset provides TOA SW and LW fluxes for long-term monitoring of the Earth’s energy balance and to validate climate models. The EBAF products, based on the Terra, Aqua, and NOAA20 CERES instrument observed radiances, rely on coincident measurements from the onboard MODIS or VIIRS imagers to determine cloud properties used for angular distribution model scene selection, which is required to convert the CERES observed radiances into flux values. Furthermore, CERES utilizes geostationary imager (GEO) hourly fluxes and clouds to infer the regional averaged daily flux in the SYN1deg product. A seamless transition of fluxes and clouds can only occur if the analogous MODIS, VIIRS, and GEO channels are properly inter-calibrated. The analogous band SRFs differ noticeably and require scene dependent spectral band adjustment factors (SBAF) for proper radiometric scaling between them. Given their disparate but overlapping SRFs, the coincident VIIRS I1 and M5 band TOA reflectance measurements provide the optimal opportunity to validate SBAFs over many surface and cloud conditions. The CERES project maintains SCIAMACHY, GOME-2, and Hyperion scene-stratified hyper-spectral reflectance measurements that can be convolved with sensor pair SRFs to compute the corresponding SBAF. This study highlights the SCIAMACHY, GOME-2, and Hyperion based SBAFs for different MODIS, VIIRS, and GEO inter-calibration targets, including all-sky tropical ocean (ATO), Libya-4, Dome-C, and deep convective clouds. To mitigate the observed sensor radiance fluctuations due to atmospheric absorption and aerosol variations, the Earth target observed radiances are correlated with multiple atmospheric parameters, such as precipitable water and ozone. The remaining M5 and I1 mean spectral band radiance difference should be resolved by the SBAF correction. The formulation of hyper-spectral sensor based SBAFs and validation methods can be verified in future utilizing high-accuracy, SI-traceable hyper-spectral measurements from CLARREO Pathfinder.

David R Doelling↗
DOE OSTI2020

Propagating sample variance uncertainties in redshift calibration: simulations, theory, and application to the COSMOS2015 data

ABSTRACT Cosmological analyses of galaxy surveys rely on knowledge of the redshift distribution of their galaxy sample. This is usually derived from a spectroscopic and/or many-band photometric calibrator survey of a small patch of sky. The uncertainties in the redshift distribution of the calibrator sample include a contribution from shot noise, or Poisson sampling errors, but, given the small volume they probe, they are dominated by sample variance introduced by large-scale structures. Redshift uncertainties have been shown to constitute one of the leading contributions to systematic uncertainties in cosmological inferences from weak lensing and galaxy clustering, and hence they must be propagated through the analyses. In this work, we study the effects of sample variance on small-area redshift surveys, from theory to simulations to the COSMOS2015 data set. We present a three-step Dirichlet method of resampling a given survey-based redshift calibration distribution to enable the propagation of both shot noise and sample variance uncertainties. The method can accommodate different levels of prior confidence on different redshift sources. This method can be applied to any calibration sample with known redshifts and phenotypes (i.e. cells in a self-organizing map, or some other way of discretizing photometric space), and provides a simple way of propagating prior redshift uncertainties into cosmological analyses. As a worked example, we apply the full scheme to the COSMOS2015 data set, for which we also present a new, principled SOM algorithm designed to handle noisy photometric data. We make available a catalogue of the resulting resamplings of the COSMOS2015 galaxies.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

Modeling Kilonova Light Curves: Dependence on Nuclear Inputs

The mergers of binary neutron stars, as well as black hole–neutron star systems, are expected to produce an electromagnetic counterpart that can be analyzed to infer the element synthesis that occurred in these events. We investigate one source of uncertainties pertinent to lanthanide-rich outflows: the nuclear inputs to rapid neutron capture nucleosynthesis calculations. We begin by examining 32 different combinations of nuclear inputs: eight mass models, two types of spontaneous fission rates, and two types of fission daughter product distributions. We find that such nuclear physics uncertainties typically generate at least one order of magnitude uncertainty in key quantities such as the nuclear heating (one and a half orders of magnitude at 1 day post-merger), the bolometric luminosity (one order of magnitude at 5 days post-merger), and the inferred mass of material from the bolometric luminosity (factor of 8 when considering the 8–10 day region). Since particular nuclear processes are critical for determining the electromagnetic signal, we provide tables of key nuclei undergoing β-decay, α-decay, and spontaneous fission important for heating at different times, identifying decays that are common among the many nuclear input combinations.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS1972

Investigation of the Martian environment by infrared spectroscopy on Mariner 9

Measurements obtained during and after the planet-wide dust storm indicate that large diurnal variations in atmospheric temperature existed up to at least 30 km; winds inferred from the temperature fields show a strong tidal component and significant ageostrophic behavior. With the dissipation of the dust, the daily maximum in the atmospheric temperature field moved from approximately latitude -60 and late afternoon local time to near the subsolar point in latitude and time. Analysis of spectral features due to the atmospheric dust indicates as SIO2 content of 60 ? 10%, implying that substantial geochemical differentiation has occurred. Water vapor estimates indicate abundances of 10 to 20 precipitable micrometers. Between November 1971 and April 1972 no gross latitudinal or temporal dependence in the water vapor distribution was detected from the south polar region to the equator. Water vapor was not detected over the north polar regions. Surface pressure mapping was carried out from which topographic relief of nearly two pressure scale heights is inferred. Extensive regions were found where the surface pressure exceeds the triple point pressure of water.

Conrath, H. R.↗
DOE OSTI2020

Learning-Accelerated ADMM for Distributed DC Optimal Power Flow

We suggest a novel data-driven method to accelerate the convergence of Alternating Direction Method of Multipliers (ADMM) for solving distributed DC optimal power flow (DC-OPF) where lines are shared between independent network partitions. Using previous observations of ADMM trajectories for a given system under varying load, the method trains a recurrent neural network (RNN) to predict the converged values of dual and consensus variables. Given a new realization of system load, a small number of initial ADMM iterations is taken as input to infer the converged values and directly inject them into the iteration. We empirically demonstrate that the online injection of these values into the ADMM iteration accelerates convergence by a significant factor for partitioned 14-, 118-and 2848-bus test systems under differing load scenarios. The proposed method has several advantages: it maintains the security of private decision variables inherent in consensus ADMM; inference is fast and so may be used in online settings; RNN-generated predictions can dramatically improve time to convergence but, by construction, can never result in infeasible ADMM subproblems; it can be easily integrated into existing software implementations. While we focus on the ADMM formulation of distributed DC-OPF in this paper, the ideas presented are naturally extended to other distributed optimization problems.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2021

Learning-Accelerated ADMM for Distributed DC Optimal Power Flow

We propose a novel data-driven method to accelerate the convergence of Alternating Direction Method of Multipliers (ADMM) for solving distributed DC optimal power flow (DC-OPF) where lines are shared between independent network partitions. Using previous observations of ADMM trajectories for a given system under varying load, the method trains a recurrent neural network (RNN) to predict the converged values of dual and consensus variables. Given a new realization of system load, a small number of initial ADMM iterations is taken as input to infer the converged values and directly inject them into the iteration. We empirically demonstrate that the online injection of these values into the ADMM iteration accelerates convergence by a significant factor for partitioned 14-, 118- and 2848-bus test systems under differing load scenarios. The proposed method has several advantages: it maintains the security of private decision variables inherent in consensus ADMM; inference is fast and so may be used in online settings; RNN-generated predictions can dramatically improve time to convergence but, by construction, can never result in infeasible ADMM subproblems; it can be easily integrated into existing software implementations. While we focus on the ADMM formulation of distributed DC-OPF in this paper, the ideas presented are naturally extended to other distributed optimization problems.

alternating direction method of multipliers↗
DOE OSTI2024

Robust inference of the Galactic Centre gamma-ray excess spatial properties

ABSTRACT The gamma-ray Fermi-LAT Galactic Centre excess (GCE) has puzzled scientists for over 15 yr. Despite ongoing debates about its properties, and especially its spatial distribution, its nature remains elusive. We scrutinize how the estimated spatial morphology of this excess depends on models for the Galactic diffuse emission, focusing particularly on the extent to which the Galactic plane and point sources are masked. Our main aim is to compare a spherically symmetric morphology – potentially arising from the annihilation of dark matter (DM) particles – with a boxy morphology – expected if faint unresolved sources in the Galactic bulge dominate the excess emission. Recent claims favouring a DM-motivated template for the GCE are shown to rely on a specific Galactic bulge template, which performs worse than other templates for the Galactic bulge. We find that a non-parametric model of the Galactic bulge derived from the VISTA Variables in the Via Lactea survey results in a significantly better fit for the GCE than DM-motivated templates. This result is independent of whether a galprop-based model or a more non-parametric ring-based model is used to describe the diffuse Galactic emission. This conclusion remains true even when additional freedom is added in the background models, allowing for non-parametric modulation of the model components and substantially improving the fit quality. When adopted, optimized background models provide robust results in terms of preference for a boxy bulge morphology for the GCE, regardless of the mask applied to the Galactic plane.

Astronomy & Astrophysics↗
DOE OSTI2023

Intergalactic magnetic field studies by means of γ -ray emission from GRB 190114C

The presence of delayed GeV emission after a strong transient, such as a gamma-ray burst (GRB), in the very-high energy (VHE) E > 100 GeV band can be the signature of a nonzero magnetic field in the intergalactic medium. Here we used a synchrotron self-Compton multiwavelength model to infer an analytical description of the intrinsic VHE spectrum (corrected for absorption by the extragalactic background light) of GRB 190114C to predict the light curves and spectral energy distributions of the delayed emission with Monte Carlo simulations for different intergalactic magnetic field (IGMF) configurations (strengths B = 8 × 10 -21 G, 10 -20 G, 3 × 10 -20 G and correlation length $\lambda$ > 1 Mpc), and compared them with the Fermi Large Area Telescope (Fermi LAT) limits computed for several exposure times. We found that the Fermi LAT is not sensitive enough to constrain any IGMF strengths using GRB 190114C.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

A Bayesian Approach for Statistical–Physical Bulk Parameterization of Rain Microphysics. Part I: Scheme Description

A novel framework is proposed for the bulk parameterization of rain microphysics: the Bayesian Observationally Constrained Statistical–Physical Scheme (BOSS). It is designed to facilitate direct constraint by observations using Bayesian inference. BOSS combines existing process-level microphysical knowledge with flexible process rate formulations and parameters constrained by observations within a Bayesian framework. Furthermore, using a raindrop size distribution (DSD) normalization method that relates DSD moments to one another via generalized power series, generalized multivariate power expressions are derived for the microphysical process rates as functions of a set of prognostic DSD moments. The scheme is flexible and can utilize any number and combination of prognostic moments and any number of terms in the process rate formulations. This means that both uncertainty in parameter values and structural uncertainty associated with the process rate formulations can be investigated systematically, which is not possible using traditional schemes. In this paper, BOSS is compared to two- and three-moment versions of a traditional bulk rain microphysics scheme (denoted as MORR). It is demonstrated that some process formulations in MORR are analytically equivalent to the generalized power expressions in BOSS using one or two terms, while others are not. BOSS is able to replicate the behavior of MORR in idealized one-dimensional rainshaft tests, but with a much more flexible and systematic design. Part II of this study describes the application of BOSS to derive rain microphysical process rates and posterior parameter distributions in Bayesian experiments using Markov chain Monte Carlo sampling constrained by synthetic observations.

58 GEOSCIENCES↗
NASA NTRS1986

Design and performance of the halogen occultation experiment (HALOE) remote sensor

HALOE is an optical remote sensor that measures extinction of solar radiation caused by the earth's atmosphere in eight channels, ranging in wavelength from 2.5 to 10.1 microns. These measurements, which occur twice each satellite orbit during solar occultation, are inverted to yield vertical distributions of middle atmosphere ozone (O3), water vapor, nitrogen dioxide, nitric oxide, hydrogen fluoride, hydrogen chloride, and methane. A channel located in the 2.7 region is used to infer the tangent point pressure by measuring carbon dioxide absorption. The HALOE instrument consists of a two-axis gimbal system, telescope, spectral discrimination optics and a 12-bit data system. The gimbal system tracks the solar radiometric centroid in the azimuthal plane and tracks the solar limb in the elevation plane, placing the instrument's instantaneous field-of-view 4 arcmin down from the solar top edge. The instrument gathers data for tangent altitudes ranging from 150 km to the earth's horizon. Prior to an orbital sunset and after an orbital sunrise, HALOE automatically performs calibration sequences to enhance data interpretation. The instrument is presently being tested at the NASA Langley Research Center in preparation for launch on the Upper Atmosphere Research Satellite near the end of this decade. This paper describes the instrumenmt design, operation, and functional performance.

Baker, R. L.↗
NASA NTRS1996

Evaluation of IGS Orbits with Satellite Laser Ranging

The accuracy with which orbits for the Global Positioning System (GPS) spacecraft, can be computed directly affects the accuracy of the resulting site coordinates and polar motion. Several groups routinely analyze GPS ground tracking data to compute precise orbits and terrestrial reference frame solutions. In this paper, we infer the accuracy of the orbits of two of the GPS satellites by comparing to independent laser ranges of subcentimeter accuracy obtained by a small but reasonably well distributed network of tracking sites. We find that all seven International GPS Service for Geodynamics (IGS) analysis centers achieve range residual root mean square (rms) errors at or below the 100 mm level. The best orbit solutions, from JPL, CODE, and the IGS combined product, yield a residual rms of about 50 mm. These residuals are consistent with three dimensional orbit errors of less than 150 mm. Estimating yaw rates for the spacecraft during shadow events, and using these estimates to compute the laser residual, significantly improves the fit. A small mean residual value of -15 to -30 mm seems to exist for most centers and laser sites which is not fully explained at present, but may be due to uncertainties in the corrections to the laser data, such as the reflector to spacecraft center of mass vector or small reference frame differences between the SLR sites and the GPS orbits.

Watkins, M. M.↗