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At least 109 records · Page 6

New low-resolution spectrometer spectra for IRAS sources

Low-resolution spectra of 486 IRAS point sources with F sub nu(12 microns) in the range 20-40 Jy are presented. This is part of an effort to extract and classify spectra that were not included in the Atlas of Low-Resolution Spectra and represents an extension of the earlier work by Volk and Cohen which covers sources with F sub nu(12 microns) greater than 40 Jy. The spectra have been examined by eye and classified into nine groups based on the spectral morphology. This new classification scheme is compared with the mechanical classification of the Atlas, and the differences are noted. Oxygen-rich stars of the asymptotic giant branch make up 33 percent of the sample. Solid state features dominate the spectra of most sources. It is found that the nature of the sources as implied by the present spectral classification is consistent with the classifications based on broad-band colors of the sources.

Volk, Kevin↗

High-Order Finite-Difference Nonlinear Filter Methods for Subsonic Turbulence Simulation with Stochastic Forcing

Numerical stability of high-order filter schemes developed by Yee & Sjogreen is tested on three-dimensional turbulence simulations with stochastic forcing and their performance is compared with that of TVD and WENO schemes. The best­ performing filter method employs an eighth-order central base scheme with the Kennedy & Gruber skew-symmetric splitting of the inviscid flux derivative, a wavelet-based local flow sensor, a nonlinear filter utilizing the dissipative portion of seventh-order \VENO scheme, and an explicit third - or fourth-order Runge­-Kutta time integration. We show that the filter scheme is more computational]y efficient and provides a wider spectral bandwidth compared to the seventh-order WENO scheme. The method also demonstrates robust long-time integration for moderately compressible turbulence. In contrast, the fifth- and seventh­ order WENO schemes show non-trivial evolution of the velocity and density power spectra. over a. few dozen dynamical times, where both TVD and filter schemes recover a so lid statistically stationary turbulent state

Kritsuk, Alexei G.↗

Mapping unstructured grid computations to massively parallel computers

Investigated here is this mapping problem: assign the tasks of a parallel program to the processors of a parallel computer such that the execution time is minimized. First, a taxonomy of objective functions and heuristics used to solve the mapping problem is presented. Next, we develop a highly parallel heuristic mapping algorithm, called Cyclic Pairwise Exchange (CPE), and discuss its place in the taxonomy. CPE uses local pairwise exchanges of processor assignments to iteratively improve an initial mapping. A variety of initial mapping schemes are tested and recursive spectral bipartitioning (RSB) followed by CPE is shown to result in the best mappings. For the test cases studied here, problems arising in computational fluid dynamics and structural mechanics on unstructured triangular and tetrahedral meshes, RSB and CPE outperform methods based on simulated annealing. Much less time is required to do the mapping and the results obtained are better. Compared with random and naive mappings, RSB and CPE reduce the communication time two fold for the test problems used. Finally, we use CPE in two applications on a CM-2. The first application is a data parallel mesh-vertex upwind finite volume scheme for solving the Euler equations on 2-D triangular unstructured meshes. CPE is used to map grid points to processors. The performance of this code is compared with a similar code on a Cray-YMP and an Intel iPSC/860. The second application is parallel sparse matrix-vector multiplication used in the iterative solution of large sparse linear systems of equations. We map rows of the matrix to processors and use an inner-product based matrix-vector multiplication. We demonstrate that this method is an order of magnitude faster than methods based on scan operations for our test cases.

Hammond, Steven Warren↗

Coccolithophorid blooms in the global ocean

The global distribution pattern of coccolithophrid blooms was mapped in order to ascertain the prevalence of these blooms in the world's oceans and to estimate their worldwide production of CaCO3 and dimethyl sulfide (DMS). Mapping was accomplished by classifying pixels of 5-day global composites of coastal zone color scanner imagery into bloom and nonbloom classes using a supervised, multispectral classification scheme. Surface waters with the spectral signature of coccolithophorid blooms annually covered an average of 1.4 x 10(exp 6) sq km in the world oceans from 1979 to 1985, with the subpolar latitudes accounting for 71% of this surface area. Classified blooms were most extensive in the Subartic North Atlantic. Large expanses of the bloom signal were also detected in the North Pacific, on the Argentine shelf and slope, and in numerous lower latitude marginal seas and shelf regions. The greatest spatial extent of classified blooms in subpolar oceanic regions occurred in the months from summer to early autumn, while those in lower latitude marginal seas occurred in midwinter to early spring. Though the classification scheme was effcient in separating bloom and nonbloom classes during test simulations, and biogeographical literature generally confirms the resulting distribution pattern of blooms in the subpolar regions, the cause of the bloom signal is equivocal in some geographic areas, particularly on shelf regions at lower latitudes. Standing stock estimates suggest that the presumed Emiliania huxleyi blooms act as a significant source of calcite carbon and DMS sulfur on a regional scale. On a global scale, however, the satellite-detected coccolithophorid blooms are estimated to play only a minor role in the annual production of these two compounds and their flux from the surface mixed layer.

Brown, Christopher W.↗

Error Estimation of An Ensemble Statistical Seasonal Precipitation Prediction Model

This NASA Technical Memorandum describes an optimal ensemble canonical correlation forecasting model for seasonal precipitation. Each individual forecast is based on the canonical correlation analysis (CCA) in the spectral spaces whose bases are empirical orthogonal functions (EOF). The optimal weights in the ensemble forecasting crucially depend on the mean square error of each individual forecast. An estimate of the mean square error of a CCA prediction is made also using the spectral method. The error is decomposed onto EOFs of the predictand and decreases linearly according to the correlation between the predictor and predictand. Since new CCA scheme is derived for continuous fields of predictor and predictand, an area-factor is automatically included. Thus our model is an improvement of the spectral CCA scheme of Barnett and Preisendorfer. The improvements include (1) the use of area-factor, (2) the estimation of prediction error, and (3) the optimal ensemble of multiple forecasts. The new CCA model is applied to the seasonal forecasting of the United States (US) precipitation field. The predictor is the sea surface temperature (SST). The US Climate Prediction Center's reconstructed SST is used as the predictor's historical data. The US National Center for Environmental Prediction's optimally interpolated precipitation (1951-2000) is used as the predictand's historical data. Our forecast experiments show that the new ensemble canonical correlation scheme renders a reasonable forecasting skill. For example, when using September-October-November SST to predict the next season December-January-February precipitation, the spatial pattern correlation between the observed and predicted are positive in 46 years among the 50 years of experiments. The positive correlations are close to or greater than 0.4 in 29 years, which indicates excellent performance of the forecasting model. The forecasting skill can be further enhanced when several predictors are used.

Shen, Samuel S. P.↗

On the dynamics of approximating schemes for dissipative nonlinear equations

Since one can rarely write down the analytical solutions to nonlinear dissipative partial differential equations (PDE's), it is important to understand whether, and in what sense, the behavior of approximating schemes to these equations reflects the true dynamics of the original equations. Further, because standard error estimates between approximations of the true solutions coming from spectral methods - finite difference or finite element schemes, for example - and the exact solutions grow exponentially in time, this analysis provides little value in understanding the infinite time behavior of a given approximating scheme. The notion of the global attractor has been useful in quantifying the infinite time behavior of dissipative PDEs, such as the Navier-Stokes equations. Loosely speaking, the global attractor is all that remains of a sufficiently large bounded set in phase space mapped infinitely forward in time under the evolution of the PDE. Though the attractor has been shown to have some nice properties - it is compact, connected, and finite dimensional, for example - it is in general quite complicated. Nevertheless, the global attractor gives a way to understand how the infinite time behavior of approximating schemes such as the ones coming from a finite difference, finite element, or spectral method relates to that of the original PDE. Indeed, one can often show that such approximations also have a global attractor. We therefore only need to understand how the structure of the attractor for the PDE behaves under approximation. This is by no means a trivial task. Several interesting results have been obtained in this direction. However, we will not go into the details. We mention here that approximations generally lose information about the system no matter how accurate they are. There are examples that show certain parts of the attractor may be lost by arbitrary small perturbations of the original equations.

Jones, Donald A.↗

A data base and analysis program for shuttle main engine dynamic pressure measurements. Appendix C: Data base plots for SSME tests 902-214 through 902-314

A dynamic pressure data base and data base management system developed to characterize the Space Shuttle Main Engine (SSME) dynamic pressure environment is reported. The data base represents dynamic pressure measurements obtained during single engine hot firing tests of the SSME. Software is provided to permit statistical evaluation of selected measurements under specified operating conditions. An interpolation scheme is included to estimate spectral trends with SSME power level. Flow Dynamic Environments in High Performance Rocket Engines are described.

Coffin, T.↗

Methods for estimating the optical constants of atmospheric hazes based on complex optical measurements

The methods of multifrequency laser sounding (MLS) are the most effective remote methods for investigating the atmospheric aerosols, since it is possible to obtain complete information on aerosol microstructure and the effective methods for estimating the aerosol optical constants can be developed. The MLS data interpretation consists in the solution of the set of equations containing those of laser sounding and equations for polydispersed optical characteristics. As a rule, the laser sounding equation is written in the approximation of single scattering and the equations for optical characteristics are written assuming that the atmospheric aerosol is formed by spherical and homogeneous particles. To remove the indeterminacy of equations, the method of optical sounding of atmospheric aerosol, consisting in a joint use of a mutifrequency lidar and a spectral photometer in common geometrical scheme of the optical experiment was suggested. The method is used for investigating aerosols in the cases when absorption by particles is small and indicates the minimum necessary for interpretation of a series of measurements.

Zuev, V. E.↗

Relationship between the longwave cloud radiative forcing at the surface and the top of the atmosphere

In order to achieve global coverage, any surface radiation climatology has to be based on satellite observations. In the last decade several schemes have been devised to obtain the surface solar insolation from top of the atmosphere reflected solar radiation. More recently, attempts have been made to infer the components of longwave radiation at the surface from satellite sounder data using a radiative transfer model. In addition to the radiative transfer scheme, these methods require assumptions about the effective emitting temperature of cloud tops and bases. Modeling studies have shown that although there are strong correlations between the solar upwelling radiative flux and surface flux, this is not true of the longwave. However, if the clear sky component is considered separately such that the cloud longwave forcing at the top and at the surface are compared, a slightly different picture emerges. During the FIRE Cirrus IFO, surface radiation measurements were made at several sites and coincident satellite overpass data was also collected. It may be possible to extract the longwave cloud radiative forcing at the top and surface from these data. If relationships are verifiable by observations, this information can be useful for the extraction of the surface longwave radiation from satellite data. The radiative transfer schemes used to convert upwelling spectral radiances into a downwelling longwave radiation can provide the clear sky component. The cloud radiative forcing at the top of the atmosphere can then modify the surface fluxes according to relationships shown. It should be noted that this procedure may be considered only for temporal averages and not for instantaneous deductions of surface fluxes. This would be most useful in compiling monthly mean regional climatologies of the surface longwave fluxes.

HARSHVARDHAN↗

Development of a recursion RNG-based turbulence model

Reynolds stress closure models based on the recursion renormalization group theory are developed for the prediction of turbulent separated flows. The proposed model uses a finite wavenumber truncation scheme to account for the spectral distribution of energy. In particular, the model incorporates effects of both local and nonlocal interactions. The nonlocal interactions are shown to yield a contribution identical to that from the epsilon-renormalization group (RNG), while the local interactions introduce higher order dispersive effects. A formal analysis of the model is presented and its ability to accurately predict separated flows is analyzed from a combined theoretical and computational stand point. Turbulent flow past a backward facing step is chosen as a test case and the results obtained based on detailed computations demonstrate that the proposed recursion -RNG model with finite cut-off wavenumber can yield very good predictions for the backstep problem.

Zhou, YE↗

Ka-Band Link Study and Analysis for a Mars Hybrid RF/Optical Software Defined Radio

The integrated radio and optical communications (iROC) project at the NASA Glenn Research Center (GRC) is investigating the feasibility of a hybrid RF and optical communication subsystem for future deep space missions. The hybrid communications subsystem enables the advancement of optical communications while simultaneously mitigating the risk of infusion by combining an experimental optical transmitter and telescope with a reliable Ka-band RF transmitter and antenna. The iROC communications subsystem seeks to maximize the total data return over the course of a potential 2-year mission in Mars orbit beginning in 2021. Although optical communication by itself offers potential for greater data return over RF, the reliable Ka-band link is also being designed for high data return capability in this hybrid system. A daily analysis of the RF link budget over the 2-year span is performed to optimize and provide detailed estimates of the RF data return. In particular, the bandwidth dependence of these data return estimates is analyzed for candidate waveforms. In this effort, a data return modeling tool was created to analyze candidate RF modulation and coding schemes with respect to their spectral efficiency, amplifier output power back-off, required digital to analog conversion (DAC) sampling rates, and support by ground receivers. A set of RF waveforms is recommended for use on the iROC platform.

communication↗

GEONEX: Land Monitoring From a New Generation of Geostationary Satellite Sensors

The latest generation of geostationary satellites carry sensors such as ABI (Advanced Baseline Imager on GOES-16) and the AHI (Advanced Himawari Imager on Himawari) that closely mimic the spatial and spectral characteristics of Earth Observing System flagship MODIS for monitoring land surface conditions. More importantly they provide observations at 5-15 minute intervals. Such high frequency data offer exciting possibilities for producing robust estimates of land surface conditions by overcoming cloud cover, enabling studies of diurnally varying local-to-regional biosphere-atmosphere interactions, and operational decision-making in agriculture, forestry and disaster management. But the data come with challenges that need special attention. For instance, geostationary data feature changing sun angle at constant view for each pixel, which is reciprocal to sun-synchronous observations, and thus require careful adaptation of EOS algorithms. Our goal is to produce a set of land surface products from geostationary sensors by leveraging NASA's investments in EOS algorithms and in the data/compute facility NEX. The land surface variables of interest include atmospherically corrected surface reflectances, snow cover, vegetation indices and leaf area index (LAI)/fraction of photosynthetically absorbed radiation (FPAR), as well as land surface temperature and fires. In order to get ready to produce operational products over the US from GOES-16 starting 2018, we have utilized 18 months of data from Himawari AHI over Australia to test the production pipeline and the performance of various algorithms for our initial tests. The end-to-end processing pipeline consists of a suite of modules to (a) perform calibration and automatic georeference correction of the AHI L1b data, (b) adopt the Multi-Angle Implementation of Atmospheric Correction (MAIAC) algorithm to produce surface spectral reflectances along with compositing schemes and QA, and (c) modify relevant EOS retrieval algorithms (e.g., LAI and FPAR, GPP, etc.) for subsequent science product generation. Initial evaluation of Himawari AHI products against standard MODIS products indicate general agreement, suggesting that data from geostationary sensors can augment low earth orbit (LEO) satellite observations.

geostationary↗

Remotely sensed image compression based on wavelet transform

In this paper, we present an image compression algorithm that is capable of significantly reducing the vast amount of information contained in multispectral images. The developed algorithm exploits the spectral and spatial correlations found in multispectral images. The scheme encodes the difference between images after contrast/brightness equalization to remove the spectral redundancy, and utilizes a two-dimensional wavelet transform to remove the spatial redundancy. the transformed images are then encoded by Hilbert-curve scanning and run-length-encoding, followed by Huffman coding. We also present the performance of the proposed algorithm with the LANDSAT MultiSpectral Scanner data. The loss of information is evaluated by PSNR (peak signal to noise ratio) and classification capability.

Kim, Seong W.↗

Atmospheric Energy Spectra in Global Kilometre-Scale Models

Eleven 40-day long integrations of five different global models with horizontal resolutions of less than 9 km are compared in terms of their global energy spectra. The method of normal-mode function decomposition is used to distinguish between balanced (Rossby wave; RW) and unbalanced (inertia-gravity wave; IGW) circulation. The simulations produce the expected canonical shape of the spectra, but their spectral slopes at mesoscales, and the zonal scale at which RW and IGW spectra intersect differ significantly. The partitioning of total wave energies into RWs an IGWs is most sensitive to the turbulence closure scheme and this partitioning is what determines the spectral crossing scale in the simulations, which differs by a factor of up to two. It implies that care must be taken when using simple spatial filtering to compare gravity wave phenomena in storm-resolving simulations, even when the model horizontal resolutions are similar. In contrast to the energy partitioning between the RWs and IGWs, changes in turbulence closure schemes do not seem to strongly affect spectral slopes, which only exhibit major differences at mesoscales. Despite their minor contribution to the global (horizontal kinetic plus potential available) energy, small scales are important for driving the global mean circulation. Our results support the conclusions of previous studies that the strength of convection is a relevant factor for explaining discrepancies in the energies at small scales. The models studied here produce the major large-scale features of tropical precipitation patterns. However, particularly at large horizontal wavenumbers, the spectra of upper tropospheric vertical velocity, which is a good indicator for the strength of deep convection, differ by factors of three or more in energy. High vertical kinetic energies at small scales are mostly found in those models that do not use any convective parameterisation.

DYAMOND↗

Signal processing of aircraft flyover noise

A detailed analysis of signal processing concerns for measuring aircraft flyover noise is presented. Development of a de-Dopplerization scheme for both corrected time history and spectral data is discussed along with an analysis of motion effects on measured spectra. A computer code was written to implement the de-Dopplerization scheme. Input to the code is the aircraft position data and the pressure time histories. To facilitate ensemble averaging, a uniform level flyover is considered but the code can accept more general flight profiles. The effects of spectral smearing and its removal is discussed. Using data acquired from XV-15 tilt rotor flyover test comparisons are made showing the measured and corrected spectra. Frequency shifts are accurately accounted for by the method. It is shown that correcting for spherical spreading, Doppler amplitude, and frequency can give some idea about source directivity. The analysis indicated that smearing increases with frequency and is more severe on approach than recession.

Kelly, Jeffrey J.↗

Signal processing of aircraft flyover noise

A detailed analysis of signal processing concerns for measuring aircraft flyover noise is presented. Development of a de-Dopplerization scheme for both corrected time history and spectral data is discussed along with an analysis of motion effects on measured spectra. A computer code was written to implement the de-Dopplerization scheme. Input to the code is the aircraft position data and the pressure time histories. To facilitate ensemble averaging, a level uniform flyover is considered in the study, but the code can accept more general flight profiles. The effects of spectral smearing and its removal are discussed. Using test data acquired from an XV-15 tilt-rotor flyover, comparisons are made between the measured and corrected spectra. Frequency shifts are accurately accounted for by the de-Dopplerization procedure. It is shown that by correcting for spherical spreading and Doppler amplitude, along with frequency, can give some idea about noise source directivity. The analysis indicated that smearing increases with frequency and is more severe on approach than recession.

Kelly, J. J.↗

An isoparametric spectral element method for solution of the Navier-Stokes equations in complex geometry

High-order (p-type) finite element methods combine the geometric flexibility of standard low-order finite element (or finite volume) techniques with the rapid convergence properties of spectral methods. Various p-type schemes have been proposed for elliptic problems. However, an application of p-type methods to more complex equations, in particular the passive scalar or Navier-Stokes equations, is complicated by the nature of the equations and by efficiency considerations as regards the solution procedure. Patera (1984) has proposed a p-type method for the Navier-Stokes equations, taking into account the arising additional complications. The present study is concerned with an isoparametric spectral element discretization for the solution of flow problems in fully general, curvy geometries. Attention is given to the isoparametric formulation for elliptic equations and a time-splitting scheme for the Navier-Stokes equations.

Korczak, K. Z.↗