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All sourcesNASA NTRSDOE OSTI
NASA NTRS1995

Soot Aerosol In The Atmosphere: Pole-to-Pole Distribution And Contributions by Aircraft

Interest in the distribution of black carbon (soot) aerosol (BCA) in the atmosphere is warranted for the following reasons: (1) BCA has the highest absorption cross section of any compound known, thus it can absorb solar radiation to cause atmospheric warming; (2) BCA is a strong adsorber of gases, thus it can catalyze heterogeneous chemical reactions to modify the chemical composition of the atmosphere; (3) If aircraft emission is the major source of atmospheric BCA, it can serve as an atmospheric tracer of aircraft exhaust. We collect BCA particles greater than or equal to 0.02 micrometer diameter by wires mounted on both the DC-8 and ER-2 aircraft. After return to the laboratory, the wires are examined with a field emission scanning electron microscope to identify BCA particles by their characteristic morphology. Typically, BCA exists in the atmosphere as small particles of complex morphology. The particle sizes at the source are measured in tens of Angstrom units; after a short residence time in the atmosphere, individual particles coalesce to loosely packed agglomerates of typical dimensions 0.01 to 0.1 micrometer. We approximate the size of each BCA aggregate by that of a sphere of equivalent volume. This is done by computing the volume of a sphere whose diameter is the mean between averaged minimum and maximum dimensions of the BCA particle. While this procedure probably underestimates the actual surface area, it permits us to compare BCA size distributions among themselves and with other types of aerosols. When statistically justified, we fit lognormal distributions to the data points to determine number concentrations, geometric mean radii, standard deviations, BCA surface areas and volumes. Results to date permit the following conclusions: (1) BCA concentration in the northern stratosphere averages 0.6 ng per cubic meters. This amount is one part in 10(exp 4) after a volcanic eruption (e.g., Pinatubo) increasing to about one percent during volcanic quiescence. In the northern troposphere, BCA concentration averages 3.2 ng per cubic meters, or 0.3 percent of the background aerosol. (2) Applying an BCA emission index EI(BCA)=5 x 10(exp -5), measured in the exhaust wake of a Concorde supersonic jet aircraft, to realistic estimates of fuel burnt by the current and projected fleets permits us to conclude that: (i) Most BCA in the northern stratosphere results from aircraft emissions; (ii) Most BCA in the northern troposphere results from other sources than aircraft; (iii) A projected supersonic fleet will increase the northern stratospheric BCA concentration by one order of magnitude, unless the emission index is substantially reduced. (3) A strong gradient between the northern and southern hemispheres indicates that mixing across the equator is greatly inhibited in relation to atmospheric residence times of BCA. (4) The single scatter albedo of BCA/"background" aerosol mixtures suggests a cooling effect for most of the globe; an exemption is the Arctic because of the high surface albedo of the snow/ice covered earth's surface.

Pueschel, R. F.↗
NASA NTRS2003

Vector Radiative Transfer Equation for Arbitrarily Shaped and Arbitrarily Oriented Particles: A Microphysical Derivation from Statistical Electromagnetics

We use the concepts of statistical electromagnetics to derive the general radiative transfer equation (RTE) describing multiple scattering of polarized light by sparse discrete random media consisting of arbitrarily shaped and arbitrarily oriented particles. The derivation starts from the volume integral and Lippmann-Schwinger equations for the electric field scattered by a fixed N-particle system and proceeds to the vector form of the Foldy-Lax equations and their approximate far-field version. We then assume that particle positions are completely random and derive the vector RTE by applying the Twersky approximation to the coherent electric field and the Twersky and ladder approximations to the coherency dyad of the diffuse field in the limit N -> infinity. The concluding section discusses the physical meaning of the quantities entering the general vector RTE and the assumptions made in its derivation.

Mishchenko, Michael I.↗
NASA NTRS1981

Fluctuations and turbulence in an electric field Bumpy Torus plasma

Fluctuation characteristics of plasma number density and electrostatic potential below the ion plasma and ion cyclotron frequencies in an electric field Bumpy Torus plasma were investigated experimentally, using digitally implemented spectral analysis techniques. The toroidal plasma was biased to high potentials by applying positive or negative voltage to electrodes located in the midplanes of two sectors of the toroidal array. The plasma was observed to be biased to 80 or 90% of the potential on the midplane electrodes, regardless of polarity. The radial electric field exceeded 1 kV/cm at the plasma boundary and penetrated inward to at least one-half of the plasma radius. When the imposed radial electric fields reached values characteristic of the experiment, the E/B drift velocities were comparable to the particle thermal velocities. The amplitude statistics of both the density and the potential fluctuations were found to be Gaussian for the most part, with near-zero skewness and a kurtosis of about 3.0. The spectral index of the density and potential fluctuations ranged from 2 to 6. The higher frequency components were found to propagate faster than the E/B drift velocity, which is the characteristic speed of the lower-frequency components.

Roth, J. R.↗
NASA NTRS1985

Asymmetric electroosmotic flow and mobility measurements at nonstationary positions in the rectangular chamber

The electrophoretic mobility of a cell in solution is defined by its velocity divided by the electric field strength it experiences. An obvious way to measure the mobility of cells is to apply a constant electric field to a suspension of cells in a glass chamber and clock the velocities of individual cells through a microscope. This microscope method is the classic technique in cell electrophoresis and it has been used for the bulk of research in this field. Two aspects of the microscope method can critically affect the accuracy and consistency of its cell mobility measurements: (1) the electroosmotic fluctuations in the chamber from measurement to measurement; and (2) the number of cells which can be practically measured for statistically meaningful results. A new method of analyzing microelectrophoretic data using a computer program has been developed which addresses both of these aspects. It makes possible the mobility measurements of individual cells as positions throughout the rectangular chamber depth during asymmetric electroosmotic flow.

Source record↗
NASA NTRS1986

Utilizing remote sensing of Thematic Mapper data to improve our understanding of estuarine processes and their influence on the productivity of estuarine-dependent fisheries

LANDSAT thematic mapper (TM) data are being used to refine and validate a stochastic spatial computer model to be applied to coastal resource management problems in Louisiana. Two major aspects of the research are: (1) the measurement of area of land (or emergent vegetation) and water and the length of the interface between land and water in TM imagery of selected coastal wetlands (sample marshes); and (2) the comparison of spatial patterns of land and water in the sample marshes of the imagery to that in marshes simulated by a computer model. In addition to activities in these two areas, the potential use of a published autocorrelation statistic is analyzed.

Browder, J. A.↗
NASA NTRS1986

Development of algorithms for understanding the temporal and spatial variability of the earth's radiation balance

A brief description is given of how temporal and spatial variability in the earth's radiative behavior influences the goals of satellite radiation monitoring systems and how some previous systems have addressed the existing problems. Then, results of some simulations of radiation budget monitoring missions are presented. These studies led to the design of the Earth Radiation Budget Experiment (ERBE). A description is given of the temporal and spatial averaging algorithms developed for the ERBE data analysis. These algorithms are intended primarily to produce monthly averages of the net radiant exitance on regional, zonal, and global scales and to provide insight into the regional diurnal variability of radiative parameters such as albedo and long-wave radiant exitance. The algorithms are applied to scanner and nonscanner data for up to three satellites. Modeling of dialy shortwave albedo and radiant exitance with satellite samling that is insufficient to fully account for changing meteorology is discussed in detail. Studies performed during the ERBE mission and software design are reviewed. These studies provide quantitative estimates of the effects of temporally sparse and biased sampling on inferred diurnal and regional radiative parameters. Other topics covered include long-wave diurnal modeling, extraction of a regional monthly net clear-sky radiation budget, the statistical significance of observed diurnal variability, quality control of the analysis, and proposals for validating the results of ERBE time and space averaging.

Brooks, D. R.↗
NASA NTRS2001

A Study of the Response of Deep Tropical Clouds to Mesoscale Processes: Modeling Strategies and Simulations of TOGA-COARE Convective Systems - Part 1

Interactions between deep tropical clouds over the western Pacific warm pool and the larger-scale environment are key to understanding climate change. Cloud models are an extremely useful tool in simulating and providing statistical information on heat and moisture transfer processes between cloud systems and the environment, and can therefore be utilized to substantially improve cloud parameterizations in climate models. In this paper, the Goddard Cumulus Ensemble (GCE) cloud-resolving model is used in multi-day simulations of deep tropical convective activity over the Tropical Ocean-Global Atmosphere Coupled Ocean-Atmosphere Response Experiment (TOGA COARE). Large-scale temperature and moisture advective tendencies, and horizontal momentum from the TOGA-COARE Intensive Flux Array (IFA) region, are applied to the GCE version which incorporates cyclical boundary conditions. Sensitivity experiments show that grid domain size produces the largest response to domain-mean temperature and moisture deviations, as well as cloudiness, when compared to grid horizontal or vertical resolution, and advection scheme. It is found that a minimum grid-domain size of 500 km is needed to adequately resolve the convective cloud features. The control experiment shows that the atmospheric heating and moistening is primarily a response to cloud latent processes of condensation/evaporation, and deposition/sublimation, and to a lesser extent, melting of ice particles. Air-sea exchange of heat and moisture is found to be significant, but of secondary importance, while the radiational response is small. The simulated rainfall and atmospheric heating and moistening, agrees well with observations, and performs favorably to other models simulating this case.

Johnson, Daniel E.↗
NASA NTRS2011

Monitoring Crop Yield in USA Using a Satellite-Based Climate-Variability Impact Index

A quantitative index is applied to monitor crop growth and predict agricultural yield in continental USA. The Climate-Variability Impact Index (CVII), defined as the monthly contribution to overall anomalies in growth during a given year, is derived from 1-km MODIS Leaf Area Index. The growing-season integrated CVII can provide an estimate of the fractional change in overall growth during a given year. In turn these estimates can provide fine-scale and aggregated information on yield for various crops. Trained from historical records of crop production, a statistical model is used to produce crop yield during the growing season based upon the strong positive relationship between crop yield and the CVII. By examining the model prediction as a function of time, it is possible to determine when the in-season predictive capability plateaus and which months provide the greatest predictive capacity.

Zhang, Ping↗
NASA NTRS2018

Estimating Software Reliability for Space Launch Vehicles in Probabilistic Risk Assessment (PRA)

It is acutely recognized in the Probabilistic Risk assessment (PRA) field that software plays a defining role in overall system reliability for all modern systems across a wide variety of industries. Regardless if the software is embedded firmware for working components or elements, part of a Human-Machine-Interface, or automated command and control logic, the success of the software to fulfill its function under nominal and off-nominal environments will be a dominant contributor to system reliability. It is also recognized that software reliability prediction and estimation is one of the more challenging and questionable aspects of any PRA or system analyses due to the nature of software and its integration with physics based systems. Irrespective of this dichotomy, any incorporation of software reliability methods requires that the contributions are accountable, quantitative, and tractable. This paper provides a brief overview of software reliability methods, establishes some minimum requirements that the methods should incorporate for completeness, and provides a logic structure for applying software reliability. Model resolution will be discussed that supports current testing plans and trade studies. We will provide initial recommendations for use in the NASA PRA and present a future dynamic option for software and PRA. Space Launch Vehicle Software is recognized to be reliable in static conditions, yet relatively vulnerable to a set of failure modes in changing environments/flight phases. Two quantitative methods were chosen to incorporate software reliability into a Space Launch Vehicle PRA accounting for phase adjustments. One method predicts latent software failure using statistical methods, and the second provides estimates of coding errors and software operating system failures based on test and historical data, respectively. Software uncertainty will also be discussed. We determined that recommendations for PRA software reliability should be modeled at the software module level where multiple software components compose a module and combinations of the software architecture can lead to a functional failure.

Novack, Steven↗
NASA NTRS2019

Application of High-Dimensional Fuzzy K-Means Cluster Analysis to CALIOP/CALIPSO Version 4.1 Cloud-Aerosol Discrimination

This study applies fuzzy k-means (FKM) cluster analyses to a subset of the parameters reported in the CALIPSO lidar level 2 data products in order to classify the layers detected as either clouds or aerosols. The results obtained are used to assess the reliability of the cloud–aerosol discrimination (CAD) scores reported in the version 4.1 release of the CALIPSO data products. FKM is an unsupervised learning algorithm, whereas the CALIPSO operational CAD algorithm (COCA) takes a highly supervised approach. Despite these substantial computational and architectural differences, our statistical analyses show that the FKM classifications agree with the COCA classifications for more than 94 % of the cases in the troposphere. This high degree of similarity is achieved because the lidar-measured signatures of the majority of the clouds and the aerosols are naturally distinct, and hence objective methods can independently and effectively separate the two classes in most cases. Classification differences most often occur in complex scenes (e.g., evaporating water cloud filaments embedded in dense aerosol) or when observing diffuse features that occur only intermittently (e.g., volcanic ash in the tropical tropopause layer). The two methods examined in this study establish overall classification correctness boundaries due to their differing algorithm uncertainties. In addition to comparing the outputs from the two algorithms, analysis of sampling, data training, performance measurements, fuzzy linear discriminants, defuzzification, error propagation, and key parameters in feature type discrimination with the FKM method are further discussed in order to better understand the utility and limits of the application of clustering algorithms to space lidar measurements. In general, we find that both FKM and COCA classification uncertainties are only minimally affected by noise in the CALIPSO measurements, though both algorithms can be challenged by especially complex scenes containing mixtures of discrete layer types. Our analysis results show that attenuated backscatter and color ratio are the driving factors that separate water clouds from aerosols; backscatter intensity, depolarization, and mid-layer altitude are most useful in discriminating between aerosols and ice clouds; and the joint distribution of backscatter intensity and depolarization ratio is critically important for distinguishing ice clouds from water clouds.

Zeng, Shan↗
NASA NTRS1986

Dynamics, statistics and predictability of planetary flow regimes

Consideration is given to regimes of low-frequency variability in large-scale atmospheric dynamics. The model utilized is the fully-nonlinear, equivalent-baratropic vorticity equation on the sphere, with simplified forcing, dissipation and topography. It is found that certain limited regions in the system's phase space are visited repeatedly and for extended periods by model solutions. Flow patterns coupled with these regions correspond to synoptically-defined zonal and blocked Northern Hemisphere midlatitude flows. It is shown that the system's macrodynamics can be depicted by two or more planetary flow regimes, the expected residence time in each regime, and the transition properties from one regime to another. These model-derived ideas are also applied to a time series of atmospheric data from the Southern Hemisphere.

Ghil, Michael↗
NASA NTRS1983

Redshift modifications to HEAO A-1 cluster X-ray luminosities

New redshift measurements for the 24 Abell galactic clusters are presented. The optical observations are described and applied to the cluster X-ray luminosity function, and the results are used to delimit the cluster contribution to the diffuse X-ray background (DXRB). The evolution of the X-ray luminosity function is then investigated. It is found that while simple two-parameter analytic forms do not fit this function very well, three-parameter forms such as the exponential times power law do fit it very well. Future redshift observations will probably not change the volume emissivity significantly, but they may in a statistically significant way affect the parameters of analytic fits which define the shape of the luminosity function. The contribution of rich clusters to the DXRB in the 2-6 keV range is 5.2 percent. Future redshift observations will modify this result by no more than a factor of about 1.1.

Cruddace, R. G.↗
NASA NTRS1994

Is a data set distributed as a power law? A test, with application to gamma-ray burst brightnesses

We present a method to determine whether an observed sample of data is drawn from a parent distribution that is pure power law. The method starts from a class of statistics which have zero expectation value under the null hypothesis, H(sub 0), that the distribution is a pure power law: F(x) varies as x(exp -alpha). We study one simple member of the class, named the `bending statistic' B, in detail. It is most effective for detection a type of deviation from a power law where the power-law slope varies slowly and monotonically as a function of x. Our estimator of B has a distribution under H(sub 0) that depends only on the size of the sample, not on the parameters of the parent population, and is approximated well by a normal distribution even for modest sample sizes. The bending statistic can therefore be used to test a set of numbers is drawn from any power-law parent population. Since many measurable quantities in astrophysics have distriibutions that are approximately power laws, and since deviations from the ideal power law often provide interesting information about the object of study (e.g., a `bend' or `break' in a luminosity function, a line in an X- or gamma-ray spectrum), we believe that a test of this type will be useful in many different contexts. In the present paper, we apply our test to various subsamples of gamma-ray burst brightness from the first-year Burst and Transient Source Experiment (BATSE) catalog and show that we can only marginally detect the expected steepening of the log (N (greater than C(sub max))) - log (C(sub max)) distribution.

Wijers, Ralph A. M. J.↗
NASA NTRS2002

Number Partitioning via Quantum Adiabatic Computation

We study both analytically and numerically the complexity of the adiabatic quantum evolution algorithm applied to random instances of combinatorial optimization problems. We use as an example the NP-complete set partition problem and obtain an asymptotic expression for the minimal gap separating the ground and exited states of a system during the execution of the algorithm. We show that for computationally hard problem instances the size of the minimal gap scales exponentially with the problem size. This result is in qualitative agreement with the direct numerical simulation of the algorithm for small instances of the set partition problem. We describe the statistical properties of the optimization problem that are responsible for the exponential behavior of the algorithm.

Smelyanskiy, Vadim N.↗
NASA NTRS2006

Evaluation of Mesoscale Model Phenomenological Verification Techniques

Forecasters at the Spaceflight Meteorology Group, 45th Weather Squadron, and National Weather Service in Melbourne, FL use mesoscale numerical weather prediction model output in creating their operational forecasts. These models aid in forecasting weather phenomena that could compromise the safety of launch, landing, and daily ground operations and must produce reasonable weather forecasts in order for their output to be useful in operations. Considering the importance of model forecasts to operations, their accuracy in forecasting critical weather phenomena must be verified to determine their usefulness. The currently-used traditional verification techniques involve an objective point-by-point comparison of model output and observations valid at the same time and location. The resulting statistics can unfairly penalize high-resolution models that make realistic forecasts of a certain phenomena, but are offset from the observations in small time and/or space increments. Manual subjective verification can provide a more valid representation of model performance, but is time-consuming and prone to personal biases. An objective technique that verifies specific meteorological phenomena, much in the way a human would in a subjective evaluation, would likely produce a more realistic assessment of model performance. Such techniques are being developed in the research community. The Applied Meteorology Unit (AMU) was tasked to conduct a literature search to identify phenomenological verification techniques being developed, determine if any are ready to use operationally, and outline the steps needed to implement any operationally-ready techniques into the Advanced Weather Information Processing System (AWIPS). The AMU conducted a search of all literature on the topic of phenomenological-based mesoscale model verification techniques and found 10 different techniques in various stages of development. Six of the techniques were developed to verify precipitation forecasts, one to verify sea breeze forecasts, and three were capable of verifying several phenomena. The AMU also determined the feasibility of transitioning each technique into operations and rated the operational capability of each technique on a subjective 1-10 scale: (1) 1 indicates that the technique is only in the initial stages of development, (2) 2-5 indicates that the technique is still undergoing modifications and is not ready for operations, (3) 6-8 indicates a higher probability of integrating the technique into AWIPS with code modifications, and (4) 9-10 indicates that the technique was created for AWIPS and is ready for implementation. Eight of the techniques were assigned a rating of 5 or below. The other two received ratings of 6 and 7, and none of the techniques a rating of 9-10. At the current time, there are no phenomenological model verification techniques ready for operational use. However, several of the techniques described in this report may become viable techniques in the future and should be monitored for updates in the literature. The desire to use a phenomenological verification technique is widespread in the modeling community, and it is likely that other techniques besides those described herein are being developed, but the work has not yet been published. Therefore, the AMIU recommends that the literature continue to be monitored for updates to the techniques described in this report and for new techniques being developed whose results have not yet been published. 111

Lambert, Winifred↗
NASA NTRS1986

Statistical methods for astronomical data with upper limits. II - Correlation and regression

Statistical methods for calculating correlations and regressions in bivariate censored data where the dependent variable can have upper or lower limits are presented. Cox's regression and the generalization of Kendall's rank correlation coefficient provide significant levels of correlations, and the EM algorithm, under the assumption of normally distributed errors, and its nonparametric analog using the Kaplan-Meier estimator, give estimates for the slope of a regression line. Monte Carlo simulations demonstrate that survival analysis is reliable in determining correlations between luminosities at different bands. Survival analysis is applied to CO emission in infrared galaxies, X-ray emission in radio galaxies, H-alpha emission in cooling cluster cores, and radio emission in Seyfert galaxies.

Isobe, T.↗
NASA NTRS2011

Estuarine Sediment Deposition during Wetland Restoration: A GIS and Remote Sensing Modeling Approach

Restoration of the industrial salt flats in the San Francisco Bay, California is an ongoing wetland rehabilitation project. Remote sensing maps of suspended sediment concentration, and other GIS predictor variables were used to model sediment deposition within these recently restored ponds. Suspended sediment concentrations were calibrated to reflectance values from Landsat TM 5 and ASTER using three statistical techniques -- linear regression, multivariate regression, and an Artificial Neural Network (ANN), to map suspended sediment concentrations. Multivariate and ANN regressions using ASTER proved to be the most accurate methods, yielding r2 values of 0.88 and 0.87, respectively. Predictor variables such as sediment grain size and tidal frequency were used in the Marsh Sedimentation (MARSED) model for predicting deposition rates for three years. MARSED results for a fully restored pond show a root mean square deviation (RMSD) of 66.8 mm (<1) between modeled and field observations. This model was further applied to a pond breached in November 2010 and indicated that the recently breached pond will reach equilibrium levels after 60 months of tidal inundation.

Newcomer, Michelle↗
NASA NTRS1990

Clustered or regular cumulus cloud fields - The statistical character of observed and simulated cloud fields

The spatial distribution of cumulus clouds is assumed to be the result of the effects of convective activity on the thermodynamic environment. The effects can be parameterized in terms of a stabilization function representing the time rate of change of convective available potential energy. Using these results, a new inhibition hypothesis explaining the expected characteristics of the spatial distribution of cumulus clouds is postulated. This paper performs a verification of the inhibition hypothesis on real and simulated cloud fields. In order to do so, an objective measure of the spatial characteristics of cumulus clouds is introduced. Multiple cloud experiments are performed with a three-dimensional numerical cloud model. Skylab pictures of real cumuli are also used in the verification. Results of applying this measure to simulated and observed cumulus cloud fields confirm the inhibition hypothesis.

Ramirez, Jorge A.↗