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At least 253 records · Page 14

A search for variability in exoplanet analogues and low-gravity brown dwarfs

We report the results of a J-band survey for photometric variability in a sample of young, low-gravity objects using the New Technology Telescope (NTT) and the United Kingdom Infrared Telescope (UKIRT). Surface gravity is a key parameter in the atmospheric properties of brown dwarfs and this is the first large survey that aims to test the gravity dependence of variability properties. We do a full analysis of the spectral signatures of youth and assess the group membership probability of each target using membership tools from the literature. This results in a 30 object sample of young low-gravity brown dwarfs. Since we are lacking in objects with spectral types later than L9, we focus our statistical analysis on the L0–L8.5 objects. We find that the variability occurrence rate of L0–L8.5 low-gravity brown dwarfs in this survey is 30(+16,−8) per cent⁠. We reanalyse the results of Radigan (2014) and find that the field dwarfs with spectral types L0–L8.5 have a variability occurrence rate of 11(+13,−4) per cent⁠. We determine a probability of 98 per cent that the samples are drawn from different distributions. This is the first quantitative indication that the low-gravity objects are more likely to be variable than the field dwarf population. Furthermore, we present follow-up J(S) and K(S) observations of the young, planetary-mass variable object PSO 318.5–22 over three consecutive nights. We find no evidence of phase shifts between the J(S) and K(S) bands and find higher J(S) amplitudes. We use the J(S) light curves to measure a rotational period of 8.45 ± 0.05 h for PSO 318.5–22.

Johanna M. Vos↗

Broadband Spectral Investigations of SGR J1550-5418 Bursts

We present the results of our broadband spectral analysis of 42 SGR J1550−5418 bursts simultaneously detected with the Swift/X-ray Telescope (XRT) and the Fermi/Gamma-ray Burst Monitor (GBM), during the 2009 January active episode of the source. The unique spectral and temporal capabilities of the XRT windowed timing mode have allowed us to extend the GBM spectral coverage for these events down to the X-ray domain (0.5-10 keV). Our earlier analysis of the GBM data found that the SGR J1550−5418 burst spectra were described equally well with either a Comptonized model or with two blackbody functions; the two models were statistically indistinguishable. Our new broadband (0.5-200 keV) spectral fits show that, on average, the burst spectra are better described with two blackbody functions than with the Comptonized model. Thus, our joint XRT-GBM analysis clearly shows for the first time that the SGR J1550−5418 burst spectra might naturally be expected to exhibit a more truly thermalized character, such as a two-blackbody or even a multi-blackbody signal. Using the Swift and RXTE timing ephemeris for SGR J1550−5418 we construct the distribution of the XRT burst counts with spin phase and find that it is not correlated with the persistent X-ray emission pulse phase from SGR J1550−5418. These results indicate that the burst emitting sites on the neutron star need not to be co-located with hot spots emitting the bulk of the persistent X-ray emission. Finally, we show that there is a significant pulse phase dependence of the XRT burst counts, likely demonstrating that the surface magnetic field of SGR J1550−5418 is not uniform over the emission zones, since it is anticipated that regions with stronger surface magnetic field could trigger bursts more efficiently.

bursts↗

Isotopic gamma lines for identification of shielding materials

Identifying the constituting materials of concealed objects is crucial in a wide range of sectors, such as medical imaging, geophysics, nonproliferation, national security investigations, and so on. Existing methods face limitations, particularly when multiple materials are involved or when there are challenges posed by scattered radiation and large areal mass. Here we introduce a novel brute-force statistical approach for material identification using high spectral resolution detectors, such as HPGe. The method relies upon updated semianalytic formulae for computing uncollided flux from source of gamma radiation, shielded by a sequence of nested spherical or cylindrical materials. These semianalytical formulae make possible rapid flux estimation for material characterization via combinatorial search through all possible combinations of materials, using a high-resolution HPGe counting detector. An important prerequisite for the method is that the geometry of the objects is known (for example, from X-ray radiography). We demonstrate the viability of this material characterization technique in several use cases with both simulated and experimental data in spherical geometry.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗

Stationary conditions for stochastic differential equations

This is a preliminary study of possible necessary and sufficient conditions to insure stationarity in the solution process for a stochastic differential equation. It indirectly sheds some light on ergodicity properties and shows that the spectral density is generally inadequate as a statistical measure of the solution. Further work is proceeding on a more general theory which gives necessary and sufficient conditions in a form useful for applications.

Adomian, G.↗

Nonlinear panel response by a Monte Carlo approach

The vibration of clamped and simply supported elastic panels due to subsonic and supersonic turbulent boundary-layer flows is investigated by a Monte Carlo technique. The resulting generalized random forces are simulated numerically from boundary-layer turbulence spectra, and the response analysis is performed in the time domain. The mutual interaction between panel motion and external and/or internal airflow is included. Response studies are performed with respect to rms response, probability structure, peak distribution, threshold crossing and spectral density. The effect on the response statistics of in-plane loading, static pressure differential, and cavity pressure is investigated.

Vaicaitis, R.↗

Wheat signature modeling and analysis for improved training statistics

The author has identified the following significant results. The spectral, spatial, and temporal characteristics of wheat and other signatures in LANDSAT multispectral scanner data were examined through empirical analysis and simulation. Irrigation patterns varied widely within Kansas; 88 percent of wheat acreage in Finney was irrigated and 24 percent in Morton, as opposed to less than 3 percent for western 2/3's of the State. The irrigation practice was definitely correlated with the observed spectral response; wheat variety differences produced observable spectral differences due to leaf coloration and different dates of maturation. Between-field differences were generally greater than within-field differences, and boundary pixels produced spectral features distinct from those within field centers. Multiclass boundary pixels contributed much of the observed bias in proportion estimates. The variability between signatures obtained by different draws of training data decreased as the sample size became larger; also, the resulting signatures became more robust and the particular decision threshold value became less important.

Nalepka, R. F.↗

Analysis of Martian terrains using optical power spectra

Planetary geological studies are almost entirely based on the analysis of orbital imagery. In the case of Mars, optical power spectra are providing the photogeologist with an additional aid in his task of classification and characterization of diverse terrains. Statistical pattern recognition techniques using optical power spectral data may be especially valuable in subdividing terrain units with characteristics that are only subtly different and in correlation of isolated patches of similar materials that are widely separated on the planet's surface.

Wolfe, R. W.↗

Current NASA studies for a Far Ultraviolent Spectrographic Explorer (FUSE)

The NASA plans for FUSE, a satellite which obtains spectra with resolutions between 100,000 and 100 in the spectral regions from 912 to 1216A and 100 to 912A, are outlined. Scientific problems which can be tackled by FUSE, but not by IUE or the Space Telescope, are discussed. A grazing incidence echelle and a hybrid echelle design are presented. They have high throughput, large simultaneous spectral range, and low background photon counting statistics. The satellite operational organization is similar to that of IUE.

Linsky, J.↗

Contextual classification on the massively parallel processor

Classifiers are often used to produce land cover maps from multispectral Earth observation imagery. Conventionally, these classifiers have been designed to exploit the spectral information contained in the imagery. Very few classifiers exploit the spatial information content of the imagery, and the few that do rarely exploit spatial information content in conjunction with spectral and/or temporal information. A contextual classifier that exploits spatial and spectral information in combination through a general statistical approach was studied. Early test results obtained from an implementation of the classifier on a VAX-11/780 minicomputer were encouraging, but they are of limited meaning because they were produced from small data sets. An implementation of the contextual classifier is presented on the Massively Parallel Processor (MPP) at Goddard that for the first time makes feasible the testing of the classifier on large data sets.

Tilton, James C.↗

The Astrometric Imaging Telescope: Detection of planetary systems with imaging and astrometry

The Astrometric Imaging Telescope (AIT) is a proposed spaceborne observatory whose primary goal is the detecton and study of extra-solar planetary systems. It contains two instruments that use complementary techniques to address the goal. The first instrument, the Coronagraphic Imager, takes direct images of nearby stars and Jupiter-size planets. It uses a telescope with scattering-compensated optics and a high-efficiency coronagraph to separate reflected planet light from the central star light. Planet detections take hours; confirmations occur in months. With a program duration of about 2 years, about 50 stars are observed. The second instrument, the Astrometric Photometer, shares the same telescope and focal plane. It uses a Ronchi ruling that is translated across the focal plane to simultaneously measure the positions of each target star and about 25 reference stars with sufficient accuracy to detect Uranus-mass planets around hundreds of stars. Enough stars of several spectral types are observed to obtain a statistically significant measurement of the prevalence of planetary systems. This observing program takes about 10 years to complete. The combination of both instruments in a single telescope system results from a number of innovative solutions that are described in this paper.

Pravdo, Steven H.↗

Remote Sensing of Aerosol and Non-Aerosol Absorption

Remote sensing of aerosol from the new satellite instruments (e.g. MODIS from Terra) and ground based radiometers (e.g. the AERONET) provides the opportunity to measure the absorption characteristics of the ambient undisturbed aerosol in the entire atmospheric column. For example Landsat and AERONET data are used to measure spectral absorption of sunlight by dust from West Africa. Both Application of the Landsat and AERONET data demonstrate that Saharan dust absorption of solar radiation is several times smaller than the current international standards. This is due to difficulties of measuring dust absorption in situ, and due to the often contamination of dust properties by the presence of air pollution or smoke. We use the remotely sensed aerosol absorption properties described by the spectral sin le scattering albedo, together with statistics of the monthly optical thickness for the fine and coarse aerosol derived from the MODIS data. The result is an estimate of the flux of solar radiation absorbed by the aerosol layer in different regions around the globe where aerosol is prevalent. If this aerosol forcing through absorption is not included in global circulation models, it may be interpreted as anomalous absorption in these regions. In a preliminary exercise we also use the absorption measurements by AERONET, to derive the non-aerosol absorption of the atmosphere in cloud free conditions. The results are obtained for the atmospheric windows: 0.44 microns, 0.66 microns, 0.86 microns and 1.05 microns. In all the locations over the land and ocean that were tested no anomalous absorption in these wavelengths, was found within absorption optical thickness of +/- 0.005.

Kaufman, Y. J.↗

On the Feasibility of Satellite Altimeter Tomography

The time-varying field of sea surface height (SSH) reflects a large number of dynamical processes including a broad range of baroclinic waves. Inertia-gravity (IG) and Rossby waves (RW) are readily detected in power spectra F(k) of SSH spatial variations, as well as in wavenumber-frequency spectral, ,k), and autocorrelation functions W(). these statistical characteristics contain information on dynamical processes in the upper thermocline. We show that the well-known 3-segment shape of 1-d spectra (based on SSH variations along satellite tracks) is determined by the Internal Rossby radius of deformation and by the degree of nonlinearity of baroclinic IG waves. Analyzing altimeter-based spectra of SSH variations in the light of a recently proposed theory for IG wave turbulence, we demonstrate that baroclinic IG waves are typically highly nonlinear. For a number of mid- and high-latitude regions, the internal Rossby radius and the wave nonlinearity are estimated from T/P data and shown to agree with expected values. The degree of the wave nonlinearity is of great practical interest. In particular, it tells us about the intensity of internal wave breaking. Furthermore, estimating the velocity of baroclinic RW we derive additional information on the upper layer stratification. These experiments point to the feasibility of using observed SSH field statistics (such F(k) and W()) to monitor properties of and dynamical processes in the upper mixed layer of the ocean.

Satellite Altimeter↗

Assessment of Global Cloud Datasets from Satellites: Project and Database Initiated by the GEWEX Radiation Panel

Clouds cover about 70% of the Earth's surface and play a dominant role in the energy and water cycle of our planet. Only satellite observations provide a continuous survey of the state of the atmosphere over the whole globe and across the wide range of spatial and temporal scales that comprise weather and climate variability. Satellite cloud data records now exceed more than 25 years in length. However, climatologies compiled from different satellite datasets can exhibit systematic biases. Questions therefore arise as to the accuracy and limitations of the various sensors. The Global Energy and Water cycle Experiment (GEWEX) Cloud Assessment, initiated in 2005 by the GEWEX Radiation Panel, provided the first coordinated intercomparison of publically available, standard global cloud products (gridded, monthly statistics) retrieved from measurements of multi-spectral imagers (some with multiangle view and polarization capabilities), IR sounders and lidar. Cloud properties under study include cloud amount, cloud height (in terms of pressure, temperature or altitude), cloud radiative properties (optical depth or emissivity), cloud thermodynamic phase and bulk microphysical properties (effective particle size and water path). Differences in average cloud properties, especially in the amount of high-level clouds, are mostly explained by the inherent instrument measurement capability for detecting and/or identifying optically thin cirrus, especially when overlying low-level clouds. The study of long-term variations with these datasets requires consideration of many factors. A monthly, gridded database, in common format, facilitates further assessments, climate studies and the evaluation of climate models.

Stubenrauch, C. J.↗

Evaluating Approaches Relating Ecosystem Productivity with Desis Spectral Information

Data from the DLR Earth Sensing Imaging Spectrometer (DESIS), mounted on the International Space Station (ISS), were used to develop and test algorithms for remotely retrieving ecosystem productivity. Twenty DESIS images were used from three widely separated forested study sites representing deciduous and conifer forests. Gross primary production (GPP) values from eddy covariance flux towers at the sites were matched with DESIS spectral reflectances collected on the same days. Multiple algorithms were successful relating spectral reflectance with GPP, including: spectral vegetation indices (SVI) sensitive to chlorophyll content, SVI used in a photosynthetic light-use efficiency model framework, spectral shape characteristics through spectral derivatives and absorption feature analysis, and statistical models leading to multiband hyperspectral indices from partial least squares regression. Successful algorithms were able to achieve R2 better than 0.7 using a diverse set of observations combining data from different sites from multiple years and at multiple times during the year. The demonstrated robustness of the algorithms provides some confidence in using DESIS imagery to map spatial patterns of GPP.

K F Huemmrich↗

Periodic Solar Wind Structures Observed in Measurements of Elemental and Ionic Composition in situ at L1

Mesoscale periodic structures observed in solar wind plasma serve as an important diagnostic tool for constraining the processes that govern the formation of the solar wind. These structures have been observed in situ and in remote data as fluctuations in proton and electron density. However, only two events of this type have been reported regarding the elemental and ionic composition. Composition measurements are especially important in gaining an understanding of the origin of the solar wind as the composition is frozen into the plasma at the Sun and does not evolve as it advects through the heliosphere. Here, we present the analysis of four events containing mesoscale periodic solar wind structure during which the Iron and Magnesium number density data, measured by the Solar Wind Ion Composition Spectrometer (SWICS)on board the Advanced Composition Explorer spacecraft, are validated at statistically significant count levels. We use a spectral analysis method specifically designed to extract periodic signals from astrophysical time series and apply it to the SWICS 12-minute native resolution dataset. We find variations in the relative abundance of elements with low first ionization potential, mass dependencies, and charge state during time intervals in which mesoscale periodic structures are observed. These variations are linked to temporal or spatial variations in solar source regions and put constraints on the solar wind formation mechanisms that produce them. Techniques presented here are relevant for future, higher-resolution studies of data from new instruments such as Solar Orbiter’s Heavy Ion Sensor.

Irena Gershkovich↗

Metabolome patterns identify active dechlorination in bioaugmentation consortium SDC-9™

Ultra-high performance liquid chromatography–high-resolution mass spectrometry (UPHLC–HRMS) is used to discover and monitor single or sets of biomarkers informing about metabolic processes of interest. The technique can detect 1000’s of molecules (i.e., metabolites) in a single instrument run and provide a measurement of the global metabolome, which could be a fingerprint of activity. Despite the power of this approach, technical challenges have hindered the effective use of metabolomics to interrogate microbial communities implicated in the removal of priority contaminants. Herein, our efforts to circumvent these challenges and apply this emerging systems biology technique to microbiomes relevant for contaminant biodegradation will be discussed. Chlorinated ethenes impact many contaminated sites, and detoxification can be achieved by organohalide-respiring bacteria, a process currently assessed by quantitative gene-centric tools (e.g., quantitative PCR). This laboratory study monitored the metabolome of the SDC-9™ bioaugmentation consortium during cis-1,2-dichloroethene (cDCE) conversion to vinyl chloride (VC) and nontoxic ethene. Untargeted metabolomics using an UHPLC-Orbitrap mass spectrometer and performed on SDC-9™ cultures at different stages of the reductive dechlorination process detected ~10,000 spectral features per sample arising from water-soluble molecules with both known and unknown structures. Multivariate statistical techniques including partial least squares-discriminate analysis (PLSDA) identified patterns of measurable spectral features (peak patterns) that correlated with dechlorination (in)activity, and ANOVA analyses identified 18 potential biomarkers for this process. Statistical clustering of samples with these 18 features identified dechlorination activity more reliably than clustering of samples based only on chlorinated ethene concentration and Dhc 16S rRNA gene abundance data, highlighting the potential value of metabolomic workflows as an innovative site assessment and bioremediation monitoring tool.

environmental monitoring↗

Characterizing Hyperspectral Imagery (AVIRIS) Using Fractal Technique

With the rapid increase in hyperspectral data acquired by various experimental hyperspectral imaging sensors, it is necessary to develop efficient and innovative tools to handle and analyze these data. The objective of this study is to seek effective spatial analytical tools for summarizing the spatial patterns of hyperspectral imaging data. In this paper, we (1) examine how fractal dimension D changes across spectral bands of hyperspectral imaging data and (2) determine the relationships between fractal dimension and image content. It has been documented that fractal dimension changes across spectral bands for the Landsat-TM data and its value [(D)] is largely a function of the complexity of the landscape under study. The newly available hyperspectral imaging data such as that from the Airborne Visible Infrared Imaging Spectrometer (AVIRIS) which has 224 bands, covers a wider spectral range with a much finer spectral resolution. Our preliminary result shows that fractal dimension values of AVIRIS scenes from the Santa Monica Mountains in California vary between 2.25 and 2.99. However, high fractal dimension values (D > 2.8) are found only from spectral bands with high noise level and bands with good image quality have a fairly stable dimension value (D = 2.5 - 2.6). This suggests that D can also be used as a summary statistics to represent the image quality or content of spectral bands.

Qiu, Hong-Lie↗

Data Processing for the Near Earth Asteroid Rendezvous (NEAR), X-ray and Gamma-ray Spectrometer (XGRS) Ground System

An X-ray and Gamma-ray spectrometer (XGRS) is onboard the Near Earth Asteroid Rendezvous (NEAR) spacecraft to determine the elemental composition of the surface of the asteroid 433Eros. The Eros asteroid is highly non-spherical in physical shape and the development of data management and analysis methodologies are in several areas a divergence from traditional remotely sensed geographical information systems techniques. Field of view and asteroid surface geometry must be derived virtually and then combined with real measurements of solar, spectral and instrument calibration information to derive meaningful scientific results. Spatial resolution of planned geochemical maps will be improved from the initial conditions of low statistical significance per integration by repeated surface flyovers and regional spectral accumulation. This paper describes the results of a collaborative effort of design and development of the NEAR XGRS instrument ground system undertaken by participants at the Goddard Space Flight Center, University of Arizona, Cornell University, Applied Physics Laboratory, and Max Plank institute.

McClanahan, Timothy P.↗