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All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Photometric redshift-aided classification using ensemble learning

We present SHEEP, a new machine learning approach to the classic problem of astronomical source classification, which combines the outputs from the XGBoost, LightGBM, and CatBoost learning algorithms to create stronger classifiers. A novel step in our pipeline is that prior to performing the classification, SHEEP first estimates photometric redshifts, which are then placed into the data set as an additional feature for classification model training; this results in significant improvements in the subsequent classification performance. SHEEP contains two distinct classification methodologies: (i) Multi-class and (ii) one versus all with correction by a meta-learner. We demonstrate the performance of SHEEP for the classification of stars, galaxies, and quasars using a data set composed of SDSS and WISE photometry of 3.5 million astronomical sources. The resulting F1 -scores are as follows: 0.992 for galaxies; 0.967 for quasars; and 0.985 for stars. In terms of the F1-scores for the three classes, SHEEP is found to outperform a recent RandomForest-based classification approach using an essentially identical data set. Our methodology also facilitates model and data set explainability via feature importances; it also allows the selection of sources whose uncertain classifications may make them interesting sources for follow-up observations.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

Multiple emission components in the Cygnus cocoon detected from Fermi -LAT observations

Star-forming regions may play an important role in the life cycle of Galactic cosmic rays (CRs), notably as home to specific acceleration mechanisms and transport conditions. Gamma-ray observations of Cygnus X have revealed the presence of an excess of hard-spectrum gamma-ray emission, possibly related to a cocoon of freshly accelerated particles. We seek an improved description of the gamma-ray emission from the cocoon using ~13 yr of observations with the Fermi-Large Area Telescope (LAT) and use it to further constrain the processes and objects responsible for the young CR population. We developed an emission model for a large region of interest, including a description of interstellar emission from the background population of CRs and recent models for other gamma-ray sources in the field. Thus, we performed an improved spectro-morphological characterisation of the residual emission including the cocoon. The best-fit model for the cocoon includes two main emission components: an extended component FCES G78.74+1.56, described by a 2D Gaussian of extension r 68 = 4.4° ± 0.1° -0.1° +0.1° and a smooth broken power law spectrum with spectral indices 1.67 ± 0.05 -0.01 +0.02 and 2.12 ± 0.02 -0.01 +0.00 below and above 3.0 ± 0.6 -0.2 +0.0 GeV, respectively; and a central component FCES G80.00+0.50, traced by the distribution of ionised gas within the borders of the photo-dissociation regions and with a power law spectrum of index 2.19 ± 0.03 -0.01 +0.00 that is significantly different from the spectrum of FCES G78.74+1.56. An additional extended emission component FCES G78.83+3.57, located on the edge of the central cavities in Cygnus X and with a spectrum compatible with that of FCES G80.00+0.50, is likely related to the cocoon. For the two brightest components FCES G80.00+0.50 and FCES G78.74+1.56, spectra and radial-azimuthal profiles of the emission can be accounted for in a diffusion-loss framework involving one single population of non-thermal particles with a flat injection spectrum. Particles span the full extent of FCES G78.74+1.56 as a result of diffusion from a central source, and give rise to source FCES G80.00+0.50 by interacting with ionised gas in the innermost region. For this simple diffusion-loss model, viable setups can be very different in terms of energetics, transport conditions, and timescales involved, and both hadronic and leptonic scenarios are possible. The solutions range from long-lasting particle acceleration, possibly in prominent star clusters such as Cyg OB2 and NGC 6910, to a more recent and short-lived release of particles within the last 10–100 kyr, likely from a supernova remnant. The observables extracted from our analysis can be used to perform detailed comparisons with advanced models of particle acceleration and transport in star-forming regions.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Opportunities for Renewable Energy, Storage, Vehicle Electrification, and Demand Response in Rajasthan's Power Sector

To support the government of Rajasthan and inform state policy makers, regulators, planners, and system operators on power system trends, NREL undertook a long-term capacity expansion planning study. We used NREL's flagship capacity expansion planning tool for the power sector called the Regional Energy Deployment System India (ReEDS-India) to understand the generation and transmission needs of Rajasthan through 2050. NREL's modeling framework includes co-optimized decisions about generation, energy storage, transmission, and reserves investments needed to meet future demand while maintaining reliable electricity supply. Scenario analysis was conducted to assess a range of potential future scenarios, providing insight for planning agencies, utilities, and local stakeholders about key trends and sources of uncertainty.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
NASA NTRS2010

Proposed Use of the NASA Ames Nebula Cloud Computing Platform for Numerical Weather Prediction and the Distribution of High Resolution Satellite Imagery

The development of the Nebula Cloud Computing Platform at NASA Ames Research Center provides an open-source solution for the deployment of scalable computing and storage capabilities relevant to the execution of real-time weather forecasts and the distribution of high resolution satellite data to the operational weather community. Two projects at Marshall Space Flight Center may benefit from use of the Nebula system. The NASA Short-term Prediction Research and Transition (SPoRT) Center facilitates the use of unique NASA satellite data and research capabilities in the operational weather community by providing datasets relevant to numerical weather prediction, and satellite data sets useful in weather analysis. SERVIR provides satellite data products for decision support, emphasizing environmental threats such as wildfires, floods, landslides, and other hazards, with interests in numerical weather prediction in support of disaster response. The Weather Research and Forecast (WRF) model Environmental Modeling System (WRF-EMS) has been configured for Nebula cloud computing use via the creation of a disk image and deployment of repeated instances. Given the available infrastructure within Nebula and the "infrastructure as a service" concept, the system appears well-suited for the rapid deployment of additional forecast models over different domains, in response to real-time research applications or disaster response. Future investigations into Nebula capabilities will focus on the development of a web mapping server and load balancing configuration to support the distribution of high resolution satellite data sets to users within the National Weather Service and international partners of SERVIR.

Limaye, Ashutosh S.↗
DOE OSTI2020

Application of Gaussian Bayes classifier to differentiate chlorine-based chemical agents

The Portable Isotopic Neutron Spectroscopy (PINS) is a commercialized system developed by Idaho National Laboratory (INL) to examine chemical warfare agents (CWA) non-destructively, utilizing Prompt Gamma Neutron Activation Analysis (PGNAA) techniques. The PINS system takes advantage of a high-resolution gamma-ray spectrum from a mechanically-cooled high-purity germanium (HPGe) detector. One of the difficult technical challenges is to discriminate the chlorine-based chemical agents. Especially, CN, CNB, CNS and CG have similar chemical compositions to make it hard to discriminate them with a higher confidence. Current identification algorithms for PINS systems with 252-Cf sources have been improved and updated continuously as more field data became available, and new algorithms was studied to complement the current algorithms by adopting the Gaussian Bayes classifier. These new algorithms were intended to be applied to a subset of chlorine-based chemical agents, and their main goal is discriminate CN, CNB, CNS and CG with their ratios of the chlorine neutron inelastic 1763keV peak to the chlorine thermal neutron capture 1959keV peak, which is referred to as the “Cl i/c” or “clic” ratio in this study. The Cl i/c ratios were assumed to follow Gaussian distributions with the means and the standard deviations unique to their corresponding chemical agents. The prior probabilities of these four chemical agents were optimized with a collection of field data to achieve the best performance in terms of precision or positive predictive value (PPV). Finally, their posterior probabilities as functions of the Cl i/c ratio were implemented in the current version of PINS analysis software in order to be tested with more field data.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗
DOE OSTI2025

Imprint of Anthropogenic Sources and Soil Removal on the Surface Concentration of H2 in the Contiguous US

Hydrogen (H2) is experiencing renewed interest throughout the world as a low carbon fuel alternative or complement to fossil fuels. Significant uncertainties remain regarding the environmental impact of increasing H2 usage, in part due to gaps in our understanding of the H2 atmospheric budget, including the H2 release from industrial activities and the H2 soil removal, the most important sink of H2. This study focuses on H2 dry air mole fractions measured by the NOAA Global Monitoring Laboratory in discrete ambient air samples collected every few days at sites located in the contiguous United States between 2010 and 2022. We take advantage of the long-term observations from this network to study the regional distribution of H2 sources using the potential source contribution function (PSCF). We find that H2 PSCF is consistent with a large anthropogenic source of atmospheric H2 from the incomplete combustion of fossil fuel. However, episodic air masses with high H2 dry air mole fractions (>700 ppb) recorded at some sampling locations in the Western and Southeastern US are not associated with elevated CO, suggesting significant noncombustion anthropogenic or geological sources of H2. Air masses depleted in H2 are recorded in rural or remote continental sites. Our analysis of observations from a tall tower in NE Colorado suggests that the degree of H2 depletion not only reflects differences in soil exposure but also the regional inhibition of the soil sink under arid conditions.

Paulot, Fabien↗
DOE OSTI2021

Model fusion with physics-guided machine learning: Projection-based reduced-order modeling

The unprecedented amount of data generated from experiments, field observations, and large-scale numerical simulations at a wide range of spatiotemporal scales has enabled the rapid advancement of data-driven and especially deep learning models in the field of fluid mechanics. Although these methods are proven successful for many applications, there is a grand challenge of improving their generalizability. This is particularly essential when data-driven models are employed within outer-loop applications like optimization. In this work, we put forth a physics-guided machine learning (PGML) framework that leverages the interpretable physics-based model with a deep learning model. Leveraging a concatenated neural network design from multi-modal data sources, the PGML framework is capable of enhancing the generalizability of data-driven models and effectively protects against or inform about the inaccurate predictions resulting from extrapolation. We apply the PGML framework as a novel model fusion approach combining the physics-based Galerkin projection model and long- to short-term memory (LSTM) network for parametric model order reduction of fluid flows. We demonstrate the improved generalizability of the PGML framework against a purely data-driven approach through the injection of physics features into intermediate LSTM layers. Our quantitative analysis shows that the overall model uncertainty can be reduced through the PGML approach, especially for test data coming from a distribution different than the training data. Moreover, we demonstrate that our approach can be used as an inverse diagnostic tool providing a confidence score associated with models and observations. The proposed framework also allows for multi-fidelity computing by making use of low-fidelity models in the online deployment of quantified data-driven models.

42 ENGINEERING↗
NASA NTRS1973

First look analyses of five cycles of ERTS-1 imagery over County of Los Angeles: Assessment of data utility for urban development and regional planning

Significant results have been obtained from the analyses of ERTS-1 imagery from five cycles over Test Site SR 124 by classical photointerpretation and by an interactive hybrid multispectral information extraction system (GEMS). The synopticity, periodicity and multispectrality of ERTS coverage, available for the first time to LA County planners, have opened up both a new dimensionality in data and offer new capability in preparation of planning inputs. Photointerpretation of ERTS images has produced over 25 overlays at 1:1,000,000 scale depicting regional relations and urban structure in terms of several hundred linear and areal features. To mention only one such result, a possible new fault lineament has been discovered on the northern slope of the Santa Monica mountains in the scene 1144-18015, composited of MSS bands 4, 5, 6,. GEMS analysis of the ERTS products has provided new or improved information in the following planning data categories: urban vegetation; land cover segregation; man-made and natural impact monitoring; urban design; and suitability. ERTS data analysis has allowed planners to establish trends that directly impact planning policies. This new source of information will not only assist current methods to be more efficient, but permits entirely new planning methodologies to be employed.

Raje, S.↗
NASA NTRS1998

The Outbursts and Orbit of the Accreting Pulsar GS 1843-02=2S 1845-024

We present observations of a series of 10 transient outbursts of pulsed hard x-ray flux from the 10.6 mHz accreting pulsar GS 1843-02 using the Burst and Transient Source Experiment (BATSE) on the Compton Observatory. These outbursts occurred regularly every 242 days, coincident with the ephemeris of the periodic transient GRO J1849-03 (Zhang et al. 1996)), which has recently been identified with the the SAS 3 source 2S 1845-024 (Soffitta et al. 1998). Our pulsed detection provides the first clear identification of GS 1843-02 with 2S 1845-024. We present a pulse timing analysis which shows that the 2S 1845-024 outbursts occur near the periastron passage of a highly eccentric (e = 0.88 q 0.01) 242.18 +/- 0.01 day period binary orbit about a high mass (M(sub opt) > 7 solar mass companion. The orbit and transient outburst pattern suggest a Be star/X-ray pulsar system, however the optical companion is unknown. Our observations show a long-term spin-up trend, with most of the spin-up occurring during the outbursts. From the measured spin-up rates and inferred mass accretion rates we conclude that an accretion disk is present during the outbursts.

Finger, Mark H.↗
DOE OSTI2026

Risk-Aware Measurement Synchronization and Recovery for DSSE With Heterogeneous Data Sources

Power distribution systems are increasingly integrating heterogeneous sensors with varying data reporting rates and types, which pose challenges to achieving observability at the desired temporal resolution of distribution system state estimation (DSSE). Multisensor failures caused by extreme events exacerbate these issues, introducing substantial uncertainties into DSSE. This article proposes a novel solution to these challenges by ensuring high-resolution system observability despite heterogeneous data sources and multisensor failures. First, a deep learning architecture combining long short-term memory (LSTM) and graph convolutional network (GCN) is employed to synchronize meters with different reporting rates, aiming to achieve system observability. A random-walk-model-based approach is introduced to generate pseudo-measurements while properly characterizing their uncertainties under multisensor failures. Finally, a disaster-risk-informed observability metric (RiOM) is defined to quantify the uncertainty associated with state estimation results. The proposed framework offers deeper insights into the system observability on the fly compared with conventional analysis. The effectiveness of the framework is demonstrated on an IEEE standard test case and a large-scale real-world distribution feeder in mid-Minnesota in the U.S.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1984

Structural characterizaiton and gas reactions of small metal particles by high-resolution, in-situ TEM and TED

The existing in-situ transmission electron microscopy (TEM) facility was improved by adding a separately pumped mini-specimen chamber. The chamber contains wire-evaporation sources for three metals and a specimen heater for moderate substrate temperatures. A sample introduction device was constructed, installed, and tested, facilitating rapid introduction of a specimen into the mini-chamber while maintaining the background pressure in that chamber in the 10(-9) millibar range. Small particles and clusters of Pd, grown by deposition from the vapor phase in an in-situ TEM facility on amorphous and crystalline support films of alumina and on ultra-thin carbon films, were analyzed by conventional high-resolution TEM and image analysis in terms of detectability, number density, and size distribution. The smallest particles that could be detected and counted contained no more than 6 atoms; size determinations could be made for particles 1 nm in diameter. The influence of various oxygen plasma treatments, annealing treatments, and of increasing the substrate temperature during deposition was investigated. The TEM technique was employed to demonstrate that under otherwise identica l conditions the lattice parameter of Pd particles in the 1 to 2 nm size range and supported in random orientation on ex-situ prepared mica films is expanded by some 3% when compared to 5 nm size particles. It is believed that this expansion is neither a small-particle diffraction effect nor due to pseudomorphism, but that it is due to a annealing-induced transformation of the small as-deposited particles with predominantly composite crystal structures into larger particles with true f.c.c. structure and thus inherently smaller lattice parameter.

Source record↗
NASA NTRS1987

Presentations by participants (edited and condensed)

The utility of Geomagnetic Automonous Shuttle-Launched Probe (GASP) for studying the earth's crust can be characterized in terms of lithospheric contributions by past satellite programs. In contrast to the POGO and MAGSAT satellites, GASP will orbit at a lower elevation to provide better resolved lithospheric magnetic anomalies for more detailed and improved geologic analysis. In the geological representation of satellite magnetic anomaly data, two current approaches can serve the analysis of GASP observations. When global scale coverage is available, spherical harmonic expansions of the observations may be utilized. When satellite elevation data is used, a useful and efficient approach is to determine the physical properties of an array of point equivalent sources by least squares matrix inversion of the observations, which will closely duplicate the observed field. An important preliminary step in the representation of satellite magnetic observations by either approach, is to register the data at constant elevation over uniform intervals of latitude and longitude. Further applications of GASP are discussed.

Vonfrese, R. R. B.↗
NASA NTRS1992

Inputs from regularly and irregularly discharging vestibular nerve afferents to secondary neurons in squirrel monkey vestibular nuclei. III. Correlation with vestibulospinal and vestibuloocular output pathways

1. A previous study measured the relative contributions made by regularly and irregularly discharging afferents to the monosynaptic vestibular nerve (Vi) input of individual secondary neurons located in and around the superior vestibular nucleus of barbiturate-anesthetized squirrel monkeys. Here, the analysis is extended to more caudal regions of the vestibular nuclei, which are a major source of both vestibuloocular and vestibulospinal pathways. As in the previous study, antidromic stimulation techniques are used to classify secondary neurons as oculomotor or spinal projecting. In addition, spinal-projecting neurons are distinguished by their descending pathways, their termination levels in the spinal cord, and their collateral projections to the IIIrd nucleus. 2. Monosynaptic excitatory postsynaptic potentials (EPSPs) were recorded intracellularly from secondary neurons as shocks of increasing strength were applied to Vi. Shocks were normalized in terms of the threshold (T) required to evoke field potentials in the vestibular nuclei. As shown previously, the relative contribution of irregular afferents to the total monosynaptic Vi input of each secondary neuron can be expressed as a %I index, the ratio (x100) of the relative sizes of the EPSPs evoked by shocks of 4 x T and 16 x T. 3. Antidromic stimulation was used to type secondary neurons as 1) medial vestibulospinal tract (MVST) cells projecting to spinal segments C1 or C6; 2) lateral vestibulospinal tract (LVST) cells projecting to C1, C6; or L1; 3) vestibulooculo-collic (VOC) cells projecting both to the IIIrd nucleus and by way of the MVST to C1 or C6; and 4) vestibuloocular (VOR) neurons projecting to the IIIrd nucleus but not to the spinal cord. Most of the neurons were located in the lateral vestibular nucleus (LV), including its dorsal (dLV) and ventral (vLV) divisions, and adjacent parts of the medial (MV) and descending nuclei (DV). Cells receiving quite different proportions of their direct inputs from regular and irregular afferents were intermingled in all regions explored. 4. LVST neurons are restricted to LV and DV and show a somatotopic organization. Those destined for the cervical and thoracic cord come from vLV, from a transition zone between vLV and DV, and to a lesser extent from dLV. Lumbar-projecting neurons are located more dorsally in dLV and more caudally in DV. MVST neurons reside in MV and in the vLV-DV transition zone.(ABSTRACT TRUNCATED AT 400 WORDS).

NASA Discipline Neuroscience↗
DOE OSTI2024

Systems Analysis and Engineering of Biofuel Production in Chromochloris zofingiensis , an Emerging Model Green Alga

As a core component of a sustainable bioeconomy, microalgae have the potential to become a major source of biofuels and bioproducts. These photosynthetic microbes utilize solar energy, grow quickly, consume CO 2 , and can be cultivated on non-arable land. However, there are presently considerable practical limitations in the photosynthetic production of biofuels from microalgae, resulting in low productivity and high costs. Algae are a strikingly diverse group and understudied algae can reveal new opportunities for biofuels. Integrative systems biology and engineering of emerging model systems are needed to expand the possibilities of microbial production of biofuels and bioproducts. Our long-term goal is to design and engineer high-level production of biofuel precursors in microalgae.

09 BIOMASS FUELS↗
DOE OSTI2024

Water foraging with dynamic roots in E3SM; The role of roots in terrestrial ecosystem memory on intermediate timescales (Final Technical Report)

Terrestrial ecosystems can show sustained responses to stress events that may last for years after the initial perturbation. This phenomenon is referred to as legacy or memory and it emerges from a set of ecosystem processes that are poorly captured by Earth System and Land Surface Models. Consequently, these models struggle to predict the impact that extreme climate events have on surface energy, carbon and hydrological exchange once a stressor such as drought has relaxed or in response to repeated exposure to stress. In this project, we set out to test how the addition of dynamic root profiles in land surface models impact the capacity for Earth System Models, such as the Department of Energy’s E3SM, to capture realistic legacy effects. Observations have shown that vegetation shifts their root profiles during stress events to forage for water and these altered root profiles may take years to relax back to the initial state. We hypothesized that the alteration of the belowground root structures may be a source of terrestrial ecosystem legacy that is missing from models. To test this idea we undertook three core activities. (1) We developed a global-scale analysis of the impact of dynamic roots on ecosystem legacy building from a recently developed dynamic root module. (2) We developed new root dynamics in the DOE’s Energy Land Model (ELM) that allowed not only root profiles to shift their profile but also simultaneously alter carbon allocation to fine root pools. We then tested the impact of these new dynamics with intensive sensitivity analysis at four long-term AmeriFlux sites. (3) We undertook detailed isotopic analysis of tree rings from these AmeriFlux sites to assess ecophysiological and ecohydrological legacy to stress events that can be used to benchmark the sensitivity experiments with ELM. From these core activities, we report the following key findings. Firstly, on a global scale, the addition of dynamic roots led to chronically water-stressed ecosystems recovering faster to climate stress while wetter ecosystem showed enhanced legacy. This is because across ecosystems, stress events were almost universally associated with water shortages that led to the development of deeper root profiles. These deeper root profiles proved beneficial for recovery from drought stress. While the root dynamics did not universally improve the modeled representation of legacy it showed complex transient dynamics that emerge from the addition of dynamic roots. Secondly, the sensitivity analysis illustrated long term shifts in rooting depths away from the prescribed default profile suggesting that initializing of root profiles could benefit from spin-up simulations that converge on locally optimized root profiles. In addition, by enabling dynamic allocation some of the sites predicted unrealistically low allocation to roots (and high allocation to leaves). While these changes did not dramatically alter modeled gross primary productivity, they illustrated that without more sophisticated root processes in models, there is little penalty to dramatically disinvest in roots. Thirdly, the isotopic analysis of tree rings showed highly distinct legacy responses across species and sites. For example, T. canadensis showed reduced transpiration the year after stress events illustrated by sustained elevated $\delta^{18}$O. In contrast, A saccharum displayed elevated $\delta^{13}$C associated with reduced stomatal conductance in response to the previous years’ stress event. These geochemical signatures of legacy were present despite tree growth returning to normal the year after the stress. The results show the importance of species-level dynamics in legacy that are absent in modeling that assumes common traits within plant functional types. In summary, the work here established new avenues to explore root dynamics in models while illustrating how additional root processes are needed before dynamic carbon allocation can be implemented. Lastly, this project provided mentorship to a postdoctoral fellow, training for an early career scientist and multiple undergraduate students recruited from a minority serving institution.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1987

Voyager 2 plasma ion observations in the magnetosphere of Uranus

Positive ion measurements in the magnetosphere of Uranus have been made by the Voyager 2 plasma science experiment. The paper presents an overview of the entire data set and a detailed analysis of the observations from the inner magnetosphere which complements and extends results reported elsewhere. Densities and temperatures are obtained from an analysis which incorporates details of the instrumental response. These results are then used to calculate flux tube particle and energy content to support the hypothesis that the plasma transport is controlled by a solar wind-driven magnetospheric convection system. Variations in the flux tube content suggest both a local source of plasma, produced from the neutral hydrogen corona of Uranus, and a nonlocal source, convected inwared and heated by adiabatic compression. In each case a proton composition is inferred. Sharp boundaries in the high-energy (approximately 1 keV) plasma population are interpreted in terms of the spatial extent of the magnetospheric convection, with significant shielding of the convection electric field. The convection theory is also used in a simulation of the low-energy (approximately 10 eV) ion component using the neutral hydrogen source, resulting in distribution functions which qualitatively agree with the observations.

Selesnick, Richard S.↗
NASA NTRS1991

A search for periodicity in the x ray spectrum of black hole candidate A0620-00

The archived data from the SAS-3 observations of the X-ray nova A0620-00, the best of the stellar blackhole candidates, were exhaustively examined for evidence of variable phenomena correlated with the orbital motion of the binary system of which it is a member. The original analysis of these data was completed before discovery of the binary companion and determination of the orbital period of the system. New interest was drawn to the task of a reexamination of the archive data by the recent discovery of the massive nature of the X-ray source through analysis of the Doppler variations and ellipsoidal light variations of the faint K-star companion by McClintock and Remillard. The archive research, carried out under the supervision of the principal investigator, was the topic of the thesis submitted to the MIT Department of Physics by Kenneth Plaks in partial fulfillment of the requirements for the degree of Master of Science. Plaks' effort was focused on the elimination of fluctuations in the data due to errors in attitude solutions and other extraneous causes. The first products of his work were long-term light curves of the X-ray intensities in the various energy channels as functions of time during the time from outbursts in August 1975 to quiescence approximately 6 months later. These curves, are refined versions of the preliminary results published in 1976 (Matilsky et al. 1976). Smooth exponentials were fitted to these long term light curves to provide the basis for detrending the data, thereby permitting a calculation of residuals derived by subtracting the fitted curve from the data. The residuals were then analyzed by Fourier analysis to search for variations with the period of the binary orbit, namely 7.75 hours. No evidence of an orbital periodicity was found. However, the refined light curve provides a much clearer picture of the outburst and subsequent decay of the X-ray luminosity. In fact, there were two outbursts, each followed by an exponential decay with similar time constants of about 25 days. Previous evidence of a three-oscillation variation with a 7.8 day period were confirmed. Substantial theoretical effort has been devoted to attempts to account for the decay characteristics as the result of the gradual eating up of an accretion disk by a stellar-mass blackhole (e.g., Huang and Wheeler 1989). The improved decay curves will provide significant new constraints on the theoretical analyses.

Clark, George W.↗
NASA NTRS1999

Interrelationships Between Aerosol Characteristics and Light Scattering During Late-winter in a Eastern Mediterranean Arid Environment

An intensive field campaign involving measurement of various aerosol physical, chemical, and radiative properties was conducted at Sde Boker in the Negev Desert of Israel, from 18 February to 15 March 1997. Nephelometer measurements gave average background scattering coefficient values of about 25 M/m at 550 nm wavelength, but strong dust events caused the value of this parameter to rise up to about 800 M/m Backscattering fractions did not depend on aerosol loading, and generally fell in the range of 0.1 to 0.25, comparable to values reported for marine and Arctic environments. Chemical analysis of the aerosol revealed that, in the coarse size range (2 - 10 micrometer equivalent aerodynamic diameter (EAD)), calcium (Ca) was by far the most abundant element followed by silicon (Si), both of which are indicators for mineral dust. In the fine size fraction (< 2 micrometers EAD), sulfur (S) generally was the dominant element, except during high dust episodes when Ca and Si were again the most abundant. Furthermore, fine black carbon (BC) correlates with S, suggesting that they may have originated from the same sources or source regions. An indication of the short-term effect of aerosol loading on radiative forcing was provided by measurements of global and diffuse solar radiation, which showed that during high turbidity periods (strong dust events) almost all of the solar radiation reaching the area is scattered or absorbed.

Ichoku, C.↗