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At least 1,099 records · Page 61

A parametric multiclass Bayes error estimator for the multispectral scanner spatial model performance evaluation

The author has identified the following significant results. The probability of correct classification of various populations in data was defined as the primary performance index. The multispectral data being of multiclass nature as well, required a Bayes error estimation procedure that was dependent on a set of class statistics alone. The classification error was expressed in terms of an N dimensional integral, where N was the dimensionality of the feature space. The multispectral scanner spatial model was represented by a linear shift, invariant multiple, port system where the N spectral bands comprised the input processes. The scanner characteristic function, the relationship governing the transformation of the input spatial, and hence, spectral correlation matrices through the systems, was developed.

Mobasseri, B. G.↗

Optical processing for landmark identification

A study of optical pattern recognition techniques, available components and airborne optical systems for use in landmark identification was conducted. A data base of imagery exhibiting multisensor, seasonal, snow and fog cover, exposure, and other differences was assembled. These were successfully processed in a scaling optical correlator using weighted matched spatial filter synthesis. Distinctive data classes were defined and a description of the data (with considerable input information and content information) emerged from this study. It has considerable merit with regard to the preprocessing needed and the image difference categories advanced. A optical pattern recognition airborne applications was developed, assembled and demontrated. It employed a laser diode light source and holographic optical elements in a new lensless matched spatial filter architecture with greatly reduced size and weight, as well as component positioning toleranced.

Casasent, D.↗

A case study of gravity waves-convective storms interaction 9 May 1979

An analysis is presented of a series of severe storms which occurred in the north central United States on 9 May 1979 and whose spatial distribution and movement correlate well with observed gravity waves. Two gravity wave trains of 2.1-3 mb amplitude, 2.5-3.3 h period and 240-265 km horizontal wavelength were isolated through power spectra analysis and cross-correlation techniques applied to National Weather Service barograph traces. The wave trains propagated in the 200 deg direction, which coincided with the jet axis, with a phase velocity of 20-30 m/s and within a 300 km wide band. The storms were identified on enhanced infrared GOES satellite pictures with the help of radar summaries. These convective systems initially developed in Nebraska and propagated north-northeast at 25 m/s, revealing wave-like characteristics with a separation of 300-400 km. The convective systems were closely linked to the observed wave trains with cell intensity, height and associated rainfall maximized at the wave ridge. One of the two wave trains developed in regions of weak or no convection and appeared to initiate more intense convective clusters downstream from the point of origin. It is shown that the characteristics of the wave trains are consistent with those of gravity waves generated in a region of strong vertical shear associated with the jet. It is suggested that the wave trains continue to extract energy from the basic state all along their track through critical level interaction.

Stobie, J. G.↗

On the causes of temperature change in inhomogeneous low-density astrophysical plasmas

The temperature changes that are possible in inhomogeneous low-density astrophysical plasmas were investigated for a variety of boundary distribution functions that occur in astrophysics, with emphasis placed on the spatial changes in temperature and their correlations with those of the density caused by time-independent, but spatially varying, conservative potentials. It is proven that decelerating forces produce equilibrium temperatures that are anticorrelated with densities, provided that the boundary condition is non-Maxwellian, and the proof is extended analytically for a generalized Lorentzian distribution, showing that they obey a polytrope relation with the value of gamma between 0 and l.

Scudder, Jack D.↗

Coarsening following a morphological instability in the one-sided model

We study the coarsening of the interfacial pattern separating two coexisting phases after the pattern becomes morphologically unstable. Shortly after the instability, the scale of the structure is given by the most unstable wave number in the linear regime. At later times, nonlinear interactions cause the structure to coarsen. Coarsening is studied by monitoring the time dependence of the two-dimensional power spectrum of the pattern, especially for wave vectors transverse to the direction of growth. Characteristic length scales of the pattern obtained from moments of the power spectrum are asymptotically linear in time. Furthermore, the power spectrum is seen to satisfy a scaling relation, in agreement with previous studies. A normal-velocity autocorrelation function is calculated and found to decay substantially over length scales that are of the order of the scale of the pattern. The issue of spatial anisotropy in the correlation functions is also discussed.

Vinals, Jorge↗

Automatic target recognition using a feature-based optical neural network

An optical neural network based upon the Neocognitron paradigm (K. Fukushima et al. 1983) is introduced. A novel aspect of the architectural design is shift-invariant multichannel Fourier optical correlation within each processing layer. Multilayer processing is achieved by iteratively feeding back the output of the feature correlator to the input spatial light modulator and updating the Fourier filters. By training the neural net with characteristic features extracted from the target images, successful pattern recognition with intra-class fault tolerance and inter-class discrimination is achieved. A detailed system description is provided. Experimental demonstration of a two-layer neural network for space objects discrimination is also presented.

Chao, Tien-Hsin↗

Optical implementation of neocognitron and its applications to radar signature discrimination

A feature-extraction-based optoelectronic neural network is introduced. The system implementation approach applies the principle of the neocognitron paradigm first introduced by Fukushima et al. (1983). A multichannel correlator is used as a building block of a generic single layer of the neocognitron for shift-invariant feature correlation. Multilayer processing is achieved by iteratively feeding back the output of the feature correlator to the input spatial light modulator. Successful pattern recognition with intraclass fault tolerance and interclass discrimination is achieved using this optoelectronic neocognitron. Detailed system analysis is described. Experimental demonstration of radar signature processing is also provided.

Chao, Tien-Hsin↗

Canopy reflectance modelling of semiarid vegetation

Three different types of remote sensing algorithms for estimating vegetation amount and other land surface biophysical parameters were tested for semiarid environments. These included statistical linear models, the Li-Strahler geometric-optical canopy model, and linear spectral mixture analysis. The two study areas were the National Science Foundation's Jornada Long Term Ecological Research site near Las Cruces, NM, in the northern Chihuahuan desert, and the HAPEX-Sahel site near Niamey, Niger, in West Africa, comprising semiarid rangeland and subtropical crop land. The statistical approach (simple and multiple regression) resulted in high correlations between SPOT satellite spectral reflectance and shrub and grass cover, although these correlations varied with the spatial scale of aggregation of the measurements. The Li-Strahler model produced estimated of shrub size and density for both study sites with large standard errors. In the Jornada, the estimates were accurate enough to be useful for characterizing structural differences among three shrub strata. In Niger, the range of shrub cover and size in short-fallow shrublands is so low that the necessity of spatially distributed estimation of shrub size and density is questionable. Spectral mixture analysis of multiscale, multitemporal, multispectral radiometer data and imagery for Niger showed a positive relationship between fractions of spectral endmembers and surface parameters of interest including soil cover, vegetation cover, and leaf area index.

Franklin, Janet↗

Test-particle simulations in increasingly strong turbulence

Quasi-linear theory supposes that the energy in resonant fluctuations is small compared to that in the mean magnetic field. This is evident in the fact that the zeroth-order particle trajectories are helices about a mean field B(sub o) that is spatially uniform over many correlation lengths. However, in the solar wind it is often the case that the fluctuating part of the field is comparable in magnitude to the mean part. It is generally expected that quasi-linear theory remains viable for particles that are in resonance with a region of the fluctuation spectrum having only small energy density, but even so, care must be taken when comparing simulations to theoretical predictions. We have performed a series of test-particle simulations to explore the evolution of ion distributions in turbulent situations with varying levels of magnetic fluctuations. As delta-B/B(sub o) is increased the distinctions among absolute pitch angle (defined relative to B(sub o)), local pitch angle (defined relative to B(x)), and magnetic moment become important, some of them exhibiting periodic sloshing unrelated to the nonadiabatic processes of interest. Comparing and contrasting the various runs illustrates the phenomena that must be considered when the premise underlying quasi-linear theory are relaxed.

Pontius, D. H., Jr.↗

Super Smooth Optics for Extra-Solar Planet Detection

The goal of imaging planets around the nearby stars has important scientific significance but requires the use of advanced methods of controlling diffracted and scattered light. Over the last three years we have undertaken a study of coronagraphic methods of controlling diffracted light and of figuring hyper-contrast optics. Progress in these two general areas have led to a proposed space-based, 1.9 meter diameter coronagraphic telescope designed specifically for very high performance in the imaging of faint objects near bright sources. This instrument, called the Circumstellar Imaging Telescope (CIT), relies on a new high efficiency coronagraph design and the careful control of scattered light by extremely smooth optics. The high efficiency coronagraph uses focal plane apodization in order to concentrate diffracted light more efficiently in the pupil. This allows convenient removal of the diffracted light by masking off parts of the telescope pupil while not sacrificing the center of the field. Reductions of diffracted light by factors exceeding 1000 are not only possible but are required in order to detect extra-solar planets. Laboratory experiments with this new design have confirmed the theoretical diffraction reductions to the limits of the optics used (factors of about 300) . The extremely high efficiency of this coronagraph puts strong constraints on the narrow angle scattered light due to figure errors in the telescope mirror. Since planets orbiting nearby stars are expected at angular distances of about 1 arcsecond, it is in this small angular range in which scattering must be controlled. The figure errors responsible for scattering in this range come from mid-spatial frequencies corresponding to correlation lengths of about 10 cm on the primary mirror. A primary mirror about 15 times smoother than the Hubble Space Telescope mirror is required for the CIT. Laboratory experiments indicate that small test mirrors can be fabricated with existing technology which come within a factor of two of this requirement.

Terrile, Richard J.↗

Spatial evolution of 26-day recurrent galactic cosmic ray decreases: Correlated Ulysses COSPIN/KET and SOHO COSTEP observations

A Lomb (spectral) analysis was performed on the galactic comsic ray flux from February 1996 to June 1996. The most probable frequency is approximately 28 days and not 26 or 27 days, corresponding to one solar rotation. The amplitude of the recurrent cosmic ray decreases (RCRDs) is approximately 2.3 percent on both spacecraft. The variation in the solar wind speed shows the same periodicites and is anticorrelated to the variation in the cosmic ray flux. In contrast to the RCRDs, the amplitude found in the solar wind speed is four times larger at WIND (120 km/s) than at Ulysses (32 km/s). The solar wind proton density and magnetic field strength yielded no significant periodicities, neither at Ulysses nor at WIND. Comparing the RCRDs with coronal hole structures observed in the FE XIV line, it was found that a single coronal hole close to the heliographic equator can account for the RCRDs observed 'simultaneously' at Ulysses and SOHO. The coronal hole boundaries changed towards lower Carrington longitudes and vanished slowly. The changes of the boundaries during the investigated period could explain a 28-day periodicity.

Heber, B.↗

Vibration Response Predictions for Heavy Panel Mounted Components from Panel Acreage Environment Specifications

The development of new launch vehicles in the Aerospace industry often relies on response measurements taken from previously developed vehicles during various stages of liftoff and ascent, and from wind tunnel models. These measurements include sound pressure levels, dynamic pressures in turbulent boundary layers and accelerations. Rigorous statistical scaling methods are applied to the data to derive new environments and estimate the performance of new skin panel structures. Scaling methods have proven to be reliable, particularly for designs similar to the vehicles used as the basis for scaling, and especially in regions of smooth acreage without exterior protuberances or heavy components mounted to the panel. To account for response attenuation of a panel-mounted component due to its apparent mass at higher frequencies, the vibroacoustics engineer often reduces the acreage vibration according to a weight ratio first suggested by Barrett. The accuracy of the reduction is reduced with increased weight of the panel-mounted component, and does not account for low-frequency amplification of the component/panel response as a system. A method is proposed that combines acreage vibration from scaling methods with finite element analysis to account for the frequency-dependent dynamics of heavy panel-mounted components. Since the acreage and mass-loaded skins respond to the same dynamic input pressure, such pressure may be eliminated in favor of a frequency-dependent scaling function applied to the acreage vibration to predict the mass-loaded panel response. The scaling function replaces the Barrett weight ratio, and contains all of the dynamic character of the loaded and unloaded skin panels. The solution simplifies for spatially uncorrelated and fully correlated input pressures. Since the prediction uses finite element models of the loaded and unloaded skins, a rich suite of response data are available to the design engineer, including interface forces, stress and strain, as well as acceleration and displacement. An extension of the method is also developed to incorporate the effect of a local protuberance near a heavy component. Acreage environments from traditional scaling methods with and without protuberance effects serve as the basis for the extension. Authors:

Harrison, Phillip↗

Generating Vegetation Leaf Area Index Earth System Data Record from Multiple Sensors: Implementation, Analysis and Validation - Part 2

The evaluation of a new global monthly leaf area index (LAI) data set for the period July 1981 to December 2006 derived from AVHRR Normalized Difference Vegetation Index (NDVI) data is described. The physically based algorithm is detailed in the first of the two part series. Here, the implementation, production and evaluation of the data set are described. The data set is evaluated both by direct comparisons to ground data and indirectly through inter-comparisons with similar data sets. This indirect validation showed satisfactory agreement with existing LAI products, importantly MODIS, at a range of spatial scales, and significant correlations with key climate variables in areas where temperature and precipitation limit plant growth. The data set successfully reproduced well-documented spatio-temporal trends and inter-annual variations in vegetation activity in the northern latitudes and semi-arid tropics. Comparison with plot scale field measurements over homogeneous vegetation patches indicated a 7% underestimation when all major vegetation types are taken into account. The error in mean values obtained from distributions of AVHRR LAI and high-resolution field LAI maps for different biomes is within 0.5 LAI for six out of the ten selected sites. These validation exercises though limited by the amount of field data, and thus less than comprehensive, indicated satisfactory agreement between the LAI product and field measurements. Overall, the intercomparison with short-term LAI data sets, evaluation of long term trends with known variations in climate variables, and validation with field measurements together build confidence in the utility of this new 26 year LAI record for long term vegetation monitoring and modeling studies.

Ganguly, Sangram↗

A Regional CO2 Observing System Simulation Experiment Using ASCENDS Observations and WRF-STILT Footprints

Knowledge of the spatiotemporal variations in emissions and uptake of CO2 is hampered by sparse measurements. The recent advent of satellite measurements of CO2 concentrations is increasing the density of measurements, and the future mission ASCENDS (Active Sensing of CO2 Emissions over Nights, Days and Seasons) will provide even greater coverage and precision. Lagrangian atmospheric transport models run backward in time can quantify surface influences ("footprints") of diverse measurement platforms and are particularly well suited for inverse estimation of regional surface CO2 fluxes at high resolution based on satellite observations. We utilize the STILT Lagrangian particle dispersion model, driven by WRF meteorological fields at 40-km resolution, in a Bayesian synthesis inversion approach to quantify the ability of ASCENDS column CO2 observations to constrain fluxes at high resolution. This study focuses on land-based biospheric fluxes, whose uncertainties are especially large, in a domain encompassing North America. We present results based on realistic input fields for 2007. Pseudo-observation random errors are estimated from backscatter and optical depth measured by the CALIPSO satellite. We estimate a priori flux uncertainties based on output from the CASA-GFED (v.3) biosphere model and make simple assumptions about spatial and temporal error correlations. WRF-STILT footprints are convolved with candidate vertical weighting functions for ASCENDS. We find that at a horizontal flux resolution of 1 degree x 1 degree, ASCENDS observations are potentially able to reduce average weekly flux uncertainties by 0-8% in July, and 0-0.5% in January (assuming an error of 0.5 ppm at the Railroad Valley reference site). Aggregated to coarser resolutions, e.g. 5 degrees x 5 degrees, the uncertainty reductions are larger and more similar to those estimated in previous satellite data observing system simulation experiments.

Wang, James S.↗

Regional Warming from Aerosol Removal over the United States: Results from a Transient 2010-2050 Climate Simulation

We use a general circulation model (NASA Goddard Institute for Space Studies GCM 3) to investigate the regional climate response to removal of aerosols over the United States. We perform a pair of transient 2010e2050 climate simulations following a scenario of increasing greenhouse gas concentrations, with and without aerosols over the United States and with present-day aerosols elsewhere. We find that removing U.S. aerosol significantly enhances the warming from greenhouse gases in a spatial pattern that strongly correlates with that of the aerosol. Warming is nearly negligible outside the United States, but annual mean surface temperatures increase by 0.4e0.6 K in the eastern United States. Temperatures during summer heat waves in the Northeast rise by as much as 1e2 K due to aerosol removal, driven in part by positive feedbacks involving soil moisture and low cloud cover. Reducing U.S. aerosol sources to achieve air quality objectives could thus have significant unintended regional warming consequences.

Mickley, L. J.↗

Global Distribution and Variability of Surface Skin and Surface Air Temperatures as Depicted in the AIRS Version-6 Data Set

In this presentation, we will briefly describe the significant improvements made in the AIRS Version-6 retrieval algorithm, especially as to how they affect retrieved surface skin and surface air temperatures. The global distribution of seasonal 1:30 AM and 1:30 PM local time 12 year climatologies of Ts,a will be presented for the first time. We will also present the spatial distribution of short term 12 year anomaly trends of Ts,a at 1:30 AM and 1:30 PM, as well as the spatial distribution of temporal correlations of Ts,a with the El Nino Index. It will be shown that there are significant differences between the behavior of 1:30 AM and 1:30 PM Ts,a anomalies in some arid land areas.

Retrieval algorithm↗

Future Atmospheric Rivers and Impacts on Precipitation: Overview of the ARTMIP Tier2 High-Resolution Global Warming Experiment

Atmospheric rivers (ARs) are long, narrow synoptic scale weather features important for Earth’s hydrological cycle typically transporting water vapor poleward, delivering precipitation important for local climates. Understanding ARs in a warming climate is problematic because the AR response to climate change is tied to how the feature is defined. The Atmospheric River Tracking Method Intercomparison Project (ARTMIP) provides insights into this problem by comparing 16 atmospheric river detection tools (ARDTs) to a common dataset consisting of high resolution climate change simulations from a global atmospheric general circulation model. ARDTs mostly show increases in frequency and intensity, but the scale of the response is largely dependent on algorithmic criteria. Across ARDTs, bulk characteristics suggest intensity and spatial footprint are inversely correlated, and most focus regions experience increases in precipitation volume coming from extreme ARs. The spread of the AR precipitation response under climate change is large and dependent on ARDT selection.

Atmospheric Rivers↗

Assessment of Wind Parameter Sensitivity on Ultimate and Fatigue Wind Turbine Loads: Preprint

Wind turbines are designed using a set of simulations to ascertain the structural loads that the turbine could encounter. While mean hub-height wind speed is considered to vary, other wind parameters such as turbulence spectra, sheer, veer, spatial coherence, and component correlation are fixed or conditional values that, in reality, could have different characteristics at different sites and have a significant effect on the resulting loads. This paper therefore seeks to assess the sensitivity of different wind parameters on the resulting ultimate and fatigue loads on the turbine during normal operational conditions. Eighteen different wind parameters are screened using an Elementary Effects approach with radial points. As expected, the results show a high sensitivity of the loads to the turbulence standard deviation in the primary wind direction, but the sensitivity to wind shear is often much greater. To a lesser extent, other wind parameters that drive loads include the coherence in the primary wind direction and veer.

17 WIND ENERGY↗