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At least 577 records · Page 32

Comparison of shipboard acoustic Doppler current profiler and moored current measurements in the Equatorial Pacific

Depth-averaged current shears computed from shipboard acoustic Doppler current profiler (ADCP) and moored Savonius rotor and vane vector-averaging current meter (VACM) measurements are compared at 35, 62.5, 100 and 140 m depths within 7 km of each other near 0 deg, 140 deg W during a 12-day interval in November 1984. The agreement between the VACM and ADCP shears was excellent. The average root-mean-square difference of hourly shear values was small, approximately 0.0021/s, and the average correlation coefficient was 0.90. Spectral estimates were equivalent to within a 95 percent significance level and the VACM and ADCP shears were 95 percent statistically coherent with zero phase difference for frequencies below 0.2 cycles per hour.

Chereskin, T. K.↗

Autocorrelation and regularization in digital images. I - Basic theory

Spatial structure occurs in remotely sensed images when the imaged scenes contain discrete objects that are identifiable in that their spectral properties are more homogeneous within than between them and other scene elements. The spatial structure introduced is manifest in statistical measures such as the autocovariance function and variogram associated with the scene, and it is possible to formulate these measures explicitly for scenes composed of simple objects of regular shapes. Digital images result from sensing scenes by an instrument with an associated point spread function (PSF). Since there is averaging over the PSF, the effect, termed regularization, induced in the image data by the instrument will influence the observable autocovariance and variogram functions of the image data. It is shown how the autocovariance or variogram of an image is a composition of the underlying scene covariance convolved with an overlap function, which is itself a convolution of the PSF. The functional form of this relationship provides an analytic basis for scene inference and eventual inversion of scene model parameters from image data.

Jupp, David L. B.↗

Stratospheric H2(O-18) distribution from far infrared observations

The stratospheric distribution of H2(O-18) in the 22 to 37 km altitude range has been obtained from balloon-based measurement of far infrared thermal emission spectra with an unapodized spectral resolution of 0.0033/cm. The analysis is based on the observed spectra of 9 isolated spectral lines in the 46 to 72/cm region obtained from four complete limb sequences. Comparison of the results with the statistically expected values indicates enhancement in the H2(O-18) concentrations increasing from 27 + or - 14 percent at 29 km to 40 + or - 23 percent at 37 km. No significant enhancement at lower altitudes was observed.

Guo, J.↗

Effects of rotating frame turbulence and dynamic stall on gust response of helicopter blades

The instantaneous or frequency-time spectrum of rotating frame turbulence (RFT) is presented. This spectrum makes it possible to predict the transfer of energy with respect to frequencies and the periodically varying nonstationarity with respect to time. Attention is also given to the RFT effects on the response statistics of an isolated rotor blade for low-advance-ratio and low-altitude conditions. It is noted that spectral density, rms values, and threshold-crossing expectation rates are significantly influenced by RFT.

Madhavan, R.↗

Simulations of sonic boom ray tube area fluctuations for propagation through atmospheric turbulence including caustics via a Monte Carlo method

A theory which gives statistical predictions for how often sonic booms propagating through the earth's turbulent boundary layer will encounter caustics, given the spectral properties of the atmospheric turbulence, is outlined. The theory is simple but approximately accounts for the variation of ray tube areas along ray paths. This theory predicts that the variation of ray tube areas is determined by the product of two similar area factors, psi (x) and phi (x), each satisfying a generic harmonic oscillator equation. If an area factor increases the peak acoustic pressure decreases, and if the factor decreases the peak acoustic pressure increases. Additionally, if an area factor decreases to zero and becomes negative, the ray has propagated through a caustic, which contributes a phase change of 90 degrees to the wave. Thus, it is clear that the number of times that a sonic boom wave passes through a caustic should be related to the distorted boom waveform received on the ground. Examples are given based on a characterization of atmospheric turbulence due to the structure function of Tatarski as modified by Crow.

Sparrow, Victor W.↗

Advanced Water Vapor Lidar Detection System

In the present water vapor lidar system, the detected signal is sent over long cables to a waveform digitizer in a CAMAC crate. This has the disadvantage of transmitting analog signals for a relatively long distance, which is subjected to pickup noise, leading to a decrease in the signal to noise ratio. Generally, errors in the measurement of water vapor with the DIAL method arise from both random and systematic sources. Systematic errors in DIAL measurements are caused by both atmospheric and instrumentation effects. The selection of the on-line alexandrite laser with a narrow linewidth, suitable intensity and high spectral purity, and its operation at the center of the water vapor lines, ensures minimum influence in the DIAL measurement that are caused by the laser spectral distribution and avoid system overloads. Random errors are caused by noise in the detected signal. Variability of the photon statistics in the lidar return signal, noise resulting from detector dark current, and noise in the background signal are the main sources of random error. This type of error can be minimized by maximizing the signal to noise ratio. The increase in the signal to noise ratio can be achieved by several ways. One way is to increase the laser pulse energy, by increasing its amplitude or the pulse repetition rate. Another way, is to use a detector system with higher quantum efficiency and lower noise, on the other hand, the selection of a narrow band optical filter that rejects most of the day background light and retains high optical efficiency is an important issue. Following acquisition of the lidar data, we minimize random errors in the DIAL measurement by averaging the data, but this will result in the reduction of the vertical and horizontal resolutions. Thus, a trade off is necessary to achieve a balance between the spatial resolution and the measurement precision. Therefore, the main goal of this research effort is to increase the signal to noise ratio by a factor of 10 over the current system, using a newly evaluated, very low noise avalanche photo diode detector and constructing a 10 MHz waveform digitizer which will replace the current CAMAC system.

Elsayed-Ali, Hani↗

A New Ensemble Canonical Correlation Prediction Scheme for Seasonal Precipitation

Department of Mathematical Sciences, University of Alberta, Edmonton, Canada This paper describes the fundamental theory of the ensemble canonical correlation (ECC) algorithm for the seasonal climate forecasting. The algorithm is a statistical regression sch eme based on maximal correlation between the predictor and predictand. The prediction error is estimated by a spectral method using the basis of empirical orthogonal functions. The ECC algorithm treats the predictors and predictands as continuous fields and is an improvement from the traditional canonical correlation prediction. The improvements include the use of area-factor, estimation of prediction error, and the optimal ensemble of multiple forecasts. The ECC is applied to the seasonal forecasting over various parts of the world. The example presented here is for the North America precipitation. The predictor is the sea surface temperature (SST) from different ocean basins. The Climate Prediction Center's reconstructed SST (1951-1999) is used as the predictor's historical data. The optimally interpolated global monthly precipitation is used as the predictand?s historical data. Our forecast experiments show that the ECC algorithm renders very high skill and the optimal ensemble is very important to the high value.

Kim, Kyu-Myong↗

Crop Acreage Estimation: Landsat TM and Resourcesat-1 AWiFS Sensor Assessment of the Mississippi River Delta, 2005

AWiFs data are appropriate for crop acreage estimation over large, spectrally homogenous, crop areas such as the Mid-West, the Delta and the Northern Great Plains. Regression and Kappa statistics for soybean, corn, cotton, rice and sorghum produced using both the Landsat TM and AWiFS data are very similar. AWiFS data appear to be a suitable alternative or supplement to Landsat TM data for production of NASS'Cropland Data Layer product.

Boryan, Claire↗

The Herschel* PEP-HERMES Luminosity Function- I. Probing the Evolution of PACS Selected Galaxies to z approx. equal to 4

We exploit the deep and extended far-IR data sets (at 70, 100 and 160 μm) of the Herschel Guaranteed Time Observation (GTO) PACS Evolutionary Probe (PEP) Survey, in combination with the Herschel Multi-tiered Extragalactic Survey data at 250, 350 and 500 μm, to derive the evolution of the rest-frame 35-, 60-, 90- and total infrared (IR) luminosity functions (LFs) up to z ∼ 4.We detect very strong luminosity evolution for the total IR LF (LIR ∝ (1 + z)(sup 3.55 +/- 0.10) up to z ∼ 2, and ∝ (1 + z)(sup 1.62 +/- 0.51) at 2 less than z less than approximately 4) combined with a density evolution (∝ (1 + z)(sup −0.57 +/- 0.22) up to z ∼ 1 and ∝ (1 + z)(sup −3.92 +/- 0.34) at 1 less than z less than approximately 4). In agreement with previous findings, the IR luminosity density (ρIR) increases steeply to z ∼ 1, then flattens between z ∼ 1 and z ∼ 3 to decrease at z greater than approximately 3. Galaxies with different spectral energy distributions, masses and specific star formation rates (SFRs) evolve in very different ways and this large and deep statistical sample is the first one allowing us to separately study the different evolutionary behaviours of the individual IR populations contributing to ρIR. Galaxies occupying the well-established SFR-stellar mass main sequence (MS) are found to dominate both the total IR LF and ρIR at all redshifts, with the contribution from off-MS sources (≥0.6 dex above MS) being nearly constant (∼20 per cent of the total ρIR) and showing no significant signs of increase with increasing z over the whole 0.8 < z <2.2 range. Sources with mass in the range 10 ≤ log(M/solar mass) ≤ 11 are found to dominate the total IR LF, with more massive galaxies prevailing at the bright end of the high-z (greater than approximately 2) LF. A two-fold evolutionary scheme for IR galaxies is envisaged: on the one hand, a starburst-dominated phase in which the Super Massive Black Holes (SMBH) grows and is obscured by dust (possibly triggered by a major merging event), is followed by an AGN-dominated phase, then evolving towards a local elliptical. On the other hand, moderately star-forming galaxies containing a low-luminosity AGN have various properties suggesting they are good candidates for systems in a transition phase preceding the formation of steady spiral galaxies.

Herschel↗

Identification of the Hard X-Ray Source Dominating the E > 25 keV Emission of the Nearby Galaxy M31

We report the identification of a bright hard X-ray source dominating the M31 bulge above 25 kiloelectronvolts from a simultaneous NuSTAR-Swift observation. We find that this source is the counterpart to Swift J0042.6+4112, which was previously detected in the Swift BAT All-Sky Hard X-Ray Survey. This Swift BAT source had been suggested to be the combined emission from a number of point sources; our new observations have identified a single X-ray source from 0.5 to 50 kiloelectronvolts as the counterpart for the first time. In the 0.5-10 kiloelectronvolt band, the source had been classified as an X-ray Binary candidate in various Chandra and XMM-Newton studies; however, since it was not clearly associated with Swift J0042.6+4112, the previous E is less than 10 kiloelectronvolts observations did not generate much attention. This source has a spectrum with a soft X-ray excess (kT approximately equal to 0.2 kiloelectronvolts) plus a hard spectrum with a power law of gamma approximately equal to 1 and a cutoff around 15-20 kiloelectronvolts, typical of the spectral characteristics of accreting pulsars. Unfortunately, any potential pulsation was undetected in the NuSTAR data, possibly due to insufficient photon statistics. The existing deep HST (Hubble Space Telescope) images exclude high-mass (greater than 3 times the radius of the moon) donors at the location of this source. The best interpretation for the nature of this source is an X-ray pulsar with an intermediate-mass (less than 3 times the radius of the moon M) companion or a symbiotic X-ray binary. We discuss other possibilities in more detail.

galaxies: bulges – galaxies: individual (M31)↗

Identification of the Hard X-Ray Source Dominating the E>25 keV Emission of the Nearby Galaxy M31

We report the identification of a bright hard X-ray source dominating the M31 bulge above 25 keV from a simultaneous NuSTAR-Swift observation. We find that this source is the counterpart to Swift J0042.6+4112, which was previously detected in the Swift BAT All-sky Hard X-ray Survey. This Swift BAT source had been suggested to be the combined emission from a number of point sources; our new observations have identified a single X-ray source from 0.5 to 50 keV as the counterpart for the first time. In the 0.5-10 keV band, the source had been classified as an X-ray Binary candidate in various Chandra and XMM-Newton studies; however, since it was not clearly associated with Swift J0042.6+4112, the previous E<10 keV observations did not generate much attention. This source has a spectrum with a soft X-ray excess (kT ∼ 0.2 keV) plus a hard spectrum with a power law of G ~ 1 and a cutoff around 15-20 keV, typical of the spectral characteristics of accreting pulsars. Unfortunately, any potential pulsation was undetected in the NuSTAR data, possibly due to insufficient photon statistics. The existing deep HST images exclude high-mass (>3 solar mass) donors at the location of this source. The best interpretation for the nature of this source is an X-ray pulsar with an intermediate-mass (<3 solar mass) companion or a symbiotic X-ray binary. We discuss other possibilities in more detail.

Yukita, M.↗

Recent Developments in Tolerancing Methods for Imaging Spectrometers

We discuss detailed tolerancing methods developed for imaging spectrometers at NASA Jet Propulsion Laboratory, California Institute of Technology using the Earth Surface Mineral Dust Source Investigation (EMIT) imaging spectrometer as an illustrative example. We tolerance five metrics simultaneously: along-track response function, cross-track response function, spectral response function, spectral centroid uniformity, and spatial centroid uniformity. A method to calculate tolerancing sensitivities for each metric directly, a method to statistically combine Monte Carlo files from multiple tolerancing runs, and an example summary error budgets that communicate the key and driving tolerances for each metric are discussed. These methods facilitate rapid and semi-automated assessment of the predicted performance of imaging spectrometer systems from design through to assembly and launch life cycle, using metrics that are directly relevant to the extraction of accurate spectroscopic data from these instruments.

Mouroulis, Pantazis↗

Atomistic simulations and machine learning of solute grain boundary segregation in Mg alloys at finite temperatures

Understanding solute segregation thermodynamics is the first step in investigating grain boundary (GB) properties, such as strong yttrium (Y) effects on grain growth and texture evolution in micro-scale polycrystalline magnesium (Mg) alloys. To estimate the average GB segregation behavior in low-solute-concentration Mg alloys (e.g., 2 at.% Y), a state-of-the-art spectral approach is applied based on a per-site segregation energy spectrum for Y solute atoms at zero K obtained from molecular statistics (MS) simulations of ~10 4 GB sites in Mg symmetric tilt GBs (STGBs). Although selected MS simulation results are consistent with verification by density functional theory (DFT) calculations, estimates of average segregation tendency based on the zero-K energy spectrum deviate from experimental observations. To resolve this problem, thermodynamic integration (TI) methods based on molecular dynamics (MD) simulations are used to determine the per-site segregation free energies of Y at representative GB sites, which show contributions beyond harmonic approximations can be important for certain GB sites at high temperatures. A surrogate model of per-site segregation free energy is constructed from a small set of TI data points using stacking cross-validation regressors and physics-informed descriptors. This model is applied to predict the Y segregation free energy spectra for thousands of GB sites in Mg STGBs with uncertainty quantification. Finally, the average segregation tendency predicted by the spectral approach based on the free energy spectra agrees well (within the uncertainty range) with experimental observations for micro-scale polycrystalline Mg alloys at typical thermomechanical processing temperatures (500 ~ 800 K), where thermodynamic equilibrium states are likely to be achieved due to fast diffusion.

Atomistic simulations↗

A procedure for combining acoustically induced and mechanically induced loads (first passage failure design criterion)

The combined load statistics are developed by taking the acoustically induced load to be a random population, assumed to be stationary. Each element of this ensemble of acoustically induced loads is assumed to have the same power spectral density (PSD), obtained previously from a random response analysis employing the given acoustic field in the STS cargo bay as a stationary random excitation. The mechanically induced load is treated as either (1) a known deterministic transient, or (2) a nonstationary random variable of known first and second statistical moments which vary with time. A method is then shown for determining the probability that the combined load would, at any time, have a value equal to or less than a certain level. Having obtained a statistical representation of how the acoustic and mechanical loads are expected to combine, an analytical approximation for defining design levels for these loads is presented using the First Passage failure criterion.

Crowe, D. R.↗

LANDSAT-4 MSS and TM Spectral Class Comparison and Coherent Noise Analysis

A detailed spectral analysis is conducted of thematic mapper and MSS data for an area near Des Moines, Iowa. Data are utilized from 7 blocks distributed throughout the area which included agricultural, forest, suburan, urban, and water scene types. The blocks are processed using a clustering algorithm to produce up to 18 cluster groupings for each block. Each cluster class is then identified with a ground-cover class using aerial photography and maps of the area. The clusters from each of the 7 blocks are inspected with regard to separability, mean, and variances. The separability measure used in the transformed divergence function or processor measures the statistical distance between classes based on class means and covariance matrices. The measure has a maximum value of 2,000 and the minimum of 0. Spectrally, very close classes will typically have values as low as 50 to 500.

Anuta, P. E.↗

Determination of Non-Thermal Velocity Distributions from SERTS Linewidth Observations

Non-thermal velocities obtained from the measurement of coronal Extreme Ultraviolet (EUV) linewidths have been consistently observed in solar EUV spectral observations and have been theorized to result fro m many plausible scenarios including wave motions, turbulence, or magnetic reconnection. Constraining these velocities can provide a physical limit for the available energy resulting from unresolved motions in the corona. We statistically determine a series of non-thermal velocity distributions from linewidth measurements of 390 emission lines from a wide array of elements and ionization states observed during the Solar Extreme Ultraviolet Research Telescope and Spectrograph 1991-1997 flights covering the spectral range 174-418 A and a temperature range from 80,000 K to 12.6 MK. This sample includes 248 lines from active regions, 101 lines from quiet-Sun regions, and 41 lines were observed from plasma off the solar limb. We find a strongly peaked distribution corresponding to a non-thermal velocity of 19-22 km/s in all three of the quiet-Sun, active region, and off-limb distributions. For the possibility of Alfven wave resonance heating, we find thai velocities in the core of these distributions do not provide sufficient energy, given typical densities and magnetic field strengths for the coronal plasma, to overcome the estimated coronal energy losses required to maintain the corona at the typical temperatures working as the sole mechanism. We find that at perfect efficiency 50%-60% of the needed energy flux can be produced from the non-thermal velocities measured.

Coyner, Aaron J.↗

Application of Multilayer Feedforward Neural Networks to Precipitation Cell-Top Altitude Estimation

The use of passive 118-GHz O2 observations of rain cells for precipitation cell-top altitude estimation is demonstrated by using a multilayer feed forward neural network retrieval system. Rain cell observations at 118 GHz were compared with estimates of the cell-top altitude obtained by optical stereoscopy. The observations were made with 2 4 km horizontal spatial resolution by using the Millimeter-wave Temperature Sounder (MTS) scanning spectrometer aboard the NASA ER-2 research aircraft during the Genesis of Atlantic Lows Experiment (GALE) and the COoperative Huntsville Meteorological EXperiment (COHMEX) in 1986. The neural network estimator applied to MTS spectral differences between clouds, and nearby clear air yielded an rms discrepancy of 1.76 km for a combined cumulus, mature, and dissipating cell set and 1.44 km for the cumulus-only set. An improvement in rms discrepancy to 1.36 km was achieved by including additional MTS information on the absolute atmospheric temperature profile. An incremental method for training neural networks was developed that yielded robust results, despite the use of as few as 56 training spectra. Comparison of these results with a nonlinear statistical estimator shows that superior results can be obtained with a neural network retrieval system. Imagery of estimated cell-top altitudes was created from 118-GHz spectral imagery gathered from CAMEX, September through October 1993, and from cyclone Oliver, February 7, 1993.

Spina, Michelle S.↗

Spectral distortions to momentum and scalar exchanges by non-turbulent motion and patchy landscape variability

Modifications to the spectra of turbulent velocity and scalars and co-spectra of vertical fluxes of momentum and scalars due to patchy landscape heterogeneity and non-stationarity are explored for a Mediterranean ecosystem. About 9 months of high frequency measurements of the three velocity components, water vapor concentration, carbon dioxide concentration, and air temperature were analyzed for different seasons (spring/summer) and prevalent wind directions (southeast/northwest). The two wind directions sampled a contrast of clumped and patchy landscape comprised of olive trees (southeast) and wall bounded flow disturbed by the presence of few upwind trees (northwest). The measured spectra and co-spectra were also compared to theoretical scaling forms from stationary, planar homogeneous flow, in the absence of subsidence as derived from the Kansas experiment. To assess the role of low frequency non-turbulent motion on the spectral and co-spectral content, a 5-min Fourier cutoff was introduced and the analysis was limited to near-neutral conditions where the boundary layer depth is shallow compared to its unstable counterpart. It was shown that the velocity statistics were not appreciably impacted by the low-frequency motion causing non-stationarity. Moreover, the turbulent scalar fluxes were also shown not to be significantly impacted by such low frequency motion. The scalar variances were impacted, especially the water vapor variance and its concomitant spectral shape. When the non-turbulent motion was filtered, the scalar spectra at low wavenumbers followed expectations from the so-called attached eddy hypothesis (i.e. exhibited a $k^{-1}_x$ scaling with $k_x$ defining the longitudinal wavenumber) applicable for near-neutral conditions. For momentum co-spectra, the canonical shapes from the Kansas experiment appear to describe well the measurements here and in both dominant directions and seasons with some adjustment to the integral time scales based on wind direction. For the scalar co-spectra, deviations from the Kansas experiment were prevalent. The most noticeable and surprising deviations were their slow decay with increased sampling frequency at inertial subrange scales. This slow decay was shown not to contribute appreciably to the overall scalar fluxes. At those fine scales, predictions from local isotropy were expected to hold. The scalar co-spectral deviations from local isotropy were then discussed using a simplified co-spectral budget model where scalar–scalar co-spectra naturally emerged and the interplay between landscape heterogeneity and a scale-dependent pressure-scalar de-correlation time was postulated. It is also envisaged that the findings here offer a preliminary template for analyzing eddy-covariance data in situations that deviate from ideal conditions, especially regarding low-frequency modulations of scalar spectra and vertical scalar flux co-spectra.

Canopy turbulence↗