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At least 541 records · Page 30

The NASA Subsonic Jet Particle Image Velocimetry (PIV) Dataset

Many tasks in fluids engineering require prediction of turbulence of jet flows. The present document documents the single-point statistics of velocity, mean and variance, of cold and hot jet flows. The jet velocities ranged from 0.5 to 1.4 times the ambient speed of sound, and temperatures ranged from unheated to static temperature ratio 2.7. Further, the report assesses the accuracies of the data, e.g., establish uncertainties for the data. This paper covers the following five tasks: (1) Document acquisition and processing procedures used to create the particle image velocimetry (PIV) datasets. (2) Compare PIV data with hotwire and laser Doppler velocimetry (LDV) data published in the open literature. (3) Compare different datasets acquired at the same flow conditions in multiple tests to establish uncertainties. (4) Create a consensus dataset for a range of hot jet flows, including uncertainty bands. (5) Analyze this consensus dataset for self-consistency and compare jet characteristics to those of the open literature. The final objective was fulfilled by using the potential core length and the spread rate of the half-velocity radius to collapse of the mean and turbulent velocity fields over the first 20 jet diameters.

Bridges, James↗

Estimating Terrestrial Carbon Exchange from Space: How Often and How Well?

Data from a new space mission measuring integrated light-use efficiency could provide a breakthrough in understanding of global carbon, water, and energy dynamics, and greatly improve the accuracy of model predictions for terrestrial carbon cycles and climate. Over the past decade, Gamon and others have shown that changes in photo-protective pigments are sensitive indicators of declines in light-use efficiency of plants and plant canopies. The requirements for integrated diurnal measurements from space need to be defined, before a space mission can be formulated successfully using this concept. We used towerbased CO 2 flux data as idealized proxies for remote measurements, examining their sampling properties. Thousands of half-hourly CO 2 flux measurements are needed before their average begins to converge on an average annual net CO 2 exchange. Estimates of daily integrated fluxes (i.e., diurnal curves) are more statistically efficient, especially if the spacing between measured days is quasiregular, rather than random. Using a few measurements per day one can distinguish among days with different net CO 2 exchanges. Fluxes sampled between mid-morning to mid-afternoon are more diagnostic than early morning or late afternoon measurements. Similar results (correlation >0.935) were obtained using 2 measurements per day with high accuracy ([:plusmn:]5%), 3 measurements per day with medium accuracy ([:plusmn:] 10%), or 5 measurements per day at lower accuracy ([:plusmn:]20%). An observatory in a geosynchronous or near-geosynchronous orbit could provide appropriate observations, as could a multi-satellite constellation in polar orbits, but there is a potential trade-off between the required number of observations per day and quality of each observation.

Knox, Robert G.↗

A stochastic atmospheric model for remote sensing applications

There are many factors which reduce the accuracy of classification of objects in the satellite remote sensing of Earth's surface. One important factor is the variability in the scattering and absorptive properties of the atmospheric components such as particulates and the variable gases. For multispectral remote sensing of the Earth's surface in the visible and infrared parts of the spectrum the atmospheric particulates are a major source of variability in the received signal. It is difficult to design a sensor which will determine the unknown atmospheric components by remote sensing methods, at least to the accuracy needed for multispectral classification. The problem of spatial and temporal variations in the atmospheric quantities which can affect the measured radiances are examined. A method based upon the stochastic nature of the atmospheric components was developed, and, using actual data the statistical parameters needed for inclusion into a radiometric model was generated. Methods are then described for an improved correction of radiances. These algorithms will then result in a more accurate and consistent classification procedure.

Turner, R. E.↗

Search for gamma rays of energy 10(15) eV from Cygnus X-3

Finite flux of excess radiation of energy 10 to the 15th power has been reported by two groups from the direction of Cygnus X-3, with the characteristic periodicity of 4.8 hrs. Samorski and Stamm find that the muon content of the showers generated by this excess radiation is about 77% of that in normal cosmic ray showers, whereas the expectation for gamma ray showers is less than 10%. It is thus difficult to understand the nature of the radiation arriving from the direction of Cygnus X-3. Samorski and Stamm measured the muon densities close to the core (approx. 10 m), where contamination due to other components is severe. Even though this does not explain the high ratio of muon densities, measurements should be carried out away from the core to establish the nature of the radiation. In order to establish the signal from Cygnus X-3 and its muon content with better statistical significance, an extensive air shower array, specifically designed for this purpose was operated at Kolar Gold Fields (longitude: 78 deg .3 E; latitude: + 12 deg .95; atmospheric depth: 920 q/square centimeters) since September, 1984. The details of the array and the accuracy of arrival direction measurements are discussed.

Bhat, P. N.↗

Metric analysis and data validation across FORTRAN projects

The desire to predict the effort in developing or explaining the quality of software has led to the proposal of several metrics. As a step toward validating these metrics, the Software Engineering Laboratory (SEL) has analyzed the software science metrics, cyclomatic complexity, and various standard program measures for their relation to effort (including design through acceptance testing), development errors (both discrete and weighted according to the amount of time to locate and fix), and one another. The data investigated are collected from a project FORTRAN environment and examined across several projects at once, within individual projects and by reporting accuracy checks demonstrating the need to validate a database. When the data comes from individual programmers or certain validated projects, the metrics' correlations with actual effort seem to be strongest. For modules developed entirely by individual programmers, the validity ratios induce a statistically significant ordering of several of the metrics' correlations. When comparing the strongest correlations, neither software science's E metric cyclomatic complexity not source lines of code appears to relate convincingly better with effort than the others.

Basili, Victor R.↗

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↗

Delta Method Application for the Correlation of IR Detector Thermal Parasitic Loads with Statistically Accurate Results

The Linear Etalon Imaging Spectral Array (LEISA) is a cryogenic IR detector that is passively cooled below 110K. LEISA is part of the L’Ralph instrument, which is going on the Lucy mission, with planned flyby’s of the Trojan asteroids around 5.5 AU. One of the primary thermal challenges is to successfully quantify each significant parasitic heat flow value with statistical certainty.Simulation of flight-like thermal environments and correlation of thermal models is an important part of this challenge, which can be critical for thermally sensitive systems such as cryogenic detectors that are passively cooled. It is common practice during TVAC to achieve several thermal balance points and then to correlate several design variables in order to achieve the closest match to all balance points tested. This approach lends itself to high levels of uncertainty in the correlated values due to the cumulative effect of absolute temperature uncertainty and differences between the sensors used for the measurement. Accuracy can be improved with the use of more accurate sensors, by calibrating all sensors with respect to each other, and by using Zero-Q methodologies, all of which add cost and complexity to the test.The Delta Method uses the difference in temperature caused by the changes in the boundary conditions to calculate heat flows and/or thermal resistances across temperature differentials. This eliminates the problem of high uncertainties with absolute temperature measurements, and yields statistically accurate results down to the sensor resolution of 1mK at < 100K, by taking the sensor’s calibration errors out of the equation. During testing, this method relies on parametric variations around an initial balance point, by varying the boundary conditions of the different parasitic heat sources. The Delta Method, as well as its application on the LEISA thermal test, will be discussed in detail.

Daniel G. Bae↗

Influence of fabrication tolerances on the surface accuracy of large antenna structures

One of the sources of error in radio frequency antennas is the lack of dimensional precision of the surface. This paper presents an approach for estimating the amount of error caused by random dimensional imperfections of the many structural elements which make up a truss-type antenna. A principle of equivalence between the analyses of statistical errors and of the natural vibration frequencies of the structure is developed. Examples are presented to show the application of this equivalence principle to the determination of average surface errors of several types and proportions of antenna structures.

Hedgepeth, J. M.↗

Solar activity prediction

A statistical study of formulas for predicting the sunspot number several years in advance is reported. By using a data lineup with cycle maxima coinciding, and by using multiple and nonlinear predictors, a new formula which gives better error estimates than former formulas derived from the work of McNish and Lincoln is obtained. A statistical analysis is conducted to determine which of several mathematical expressions best describes the relationship between 10.7 cm solar flux and Zurich sunspot numbers. Attention is given to the autocorrelation of the observations, and confidence intervals for the derived relationships are presented. The accuracy of predicting a value of 10.7 cm solar flux from a predicted sunspot number is dicussed.

Slutz, R. J.↗

Advances in gamma-ray burst astronomy

The paper reviews the current status of observational research into the highly puzzling problem of cosmic gamma-ray bursts. Up to now there is no convincing temporal or spatial correlation with any known celestial processes or objects. The typical burst source strength is somewhere between 10 to the 26th power ergs and 10 to the 52nd power ergs. A list of 39 confirmed and 9 unconfirmed cosmic gamma-ray bursts observed by satellite is given, showing times of occurrence and in some cases, the size in erg per square centimeter. Several approaches to the problem of source object identification are discussed: (1) accumulation of observation statistics with their present poor resolution and research for correlative phenomena, (2) mapping out celestial source distributions with moderate resolution in order to search for galactic or other anisotropies in direction or to look for repeating source regions, and (3) very high-accuracy localization of the source directions of one or several bursts in order to pinpoint a tiny fraction of the celestial sphere for correlative radio, optical and X-ray studies. Planned future instrumentation for deep space probes and multiple-balloon studies is described.

Cline, T. L.↗

A probabilistic approach to radiative energy loss calculations for optically thick atmospheres - Hydrogen lines and continua

An approximate probabilistic radiative transfer equation and the statistical equilibrium equations are simultaneously solved for a model hydrogen atom consisting of three bound levels and ionization continuum. The transfer equation for L-alpha, L-beta, H-alpha, and the Lyman continuum is explicitly solved assuming complete redistribution. The accuracy of this approach is tested by comparing source functions and radiative loss rates to values obtained with a method that solves the exact transfer equation. Two recent model solar-flare chromospheres are used for this test. It is shown that for the test atmospheres the probabilistic method gives values of the radiative loss rate that are characteristically good to a factor of 2. The advantage of this probabilistic approach is that it retains a description of the dominant physical processes of radiative transfer in the complete redistribution case, yet it achieves a major reduction in computational requirements.

Canfield, R. C.↗

Radar estimation of slant path rain attenuation at frequencies above 10 GHz and comparisons with measured multi-season results

Techniques and results pertaining to estimating Earth satellite path rain attenuation events and statistics using radar at nonattenuating wavelengths are presented. The radar formulation and beam scanning methods are described and the procedure for relating the radar measured Rayleigh reflectivity to the high frequency Mie attenuation coefficient are given. Examples of radar derived single terminal statistics and estimation criteria as they relate to path angle and frequency are reviewed. Radar derived space diversity statistics and their dependence on terminal spacing and frequency are described. Site diversity performance curves obtained by radar and radiometry are compared with each other demonstrating the utility of radar methods. Results of a multi-year experiment to test, refine, and establish accuracies of radar methods for arriving at estimates of rain attenuation along an Earth-satellite path are discussed. Comparisons of measured and radar estimated fade events are presented and found to be good. Comparisons of cumulative fade distributions show agreement to be excellent giving an rms deviation of 1 dB.

Goldhirsh, J.↗

Uncertainty in cloud optical depth estimates made from satellite radiance measurements

The uncertainty in optical depths retrieved from satellite measurements of visible wavelength radiance at the top of the atmosphere is quantified. Techniques are briefly reviewed for the estimation of optical depth from measurements of radiance, and it is noted that these estimates are always more uncertain at greater optical depths and larger solar zenith angles. The lack of radiometric calibration for visible wavelength imagers on operational satellites dominates the uncertainty retrievals of optical depth. This is true for both single-pixel retrievals and for statistics calculated from a population of individual retrievals. For individual estimates or small samples, sensor discretization can also be significant, but the sensitivity of the retrieval to the specification of the model atmosphere is less important. The relative uncertainty in calibration affects the accuracy with which optical depth distributions measured by different sensors may be quantitatively compared, while the absolute calibration uncertainty, acting through the nonlinear mapping of radiance to optical depth, limits the degree to which distributions measured by the same sensor may be distinguished.

Pincus, Robert↗

Best Merge Region Growing with Integrated Probabilistic Classification for Hyperspectral Imagery

A new method for spectral-spatial classification of hyperspectral images is proposed. The method is based on the integration of probabilistic classification within the hierarchical best merge region growing algorithm. For this purpose, preliminary probabilistic support vector machines classification is performed. Then, hierarchical step-wise optimization algorithm is applied, by iteratively merging regions with the smallest Dissimilarity Criterion (DC). The main novelty of this method consists in defining a DC between regions as a function of region statistical and geometrical features along with classification probabilities. Experimental results are presented on a 200-band AVIRIS image of the Northwestern Indiana s vegetation area and compared with those obtained by recently proposed spectral-spatial classification techniques. The proposed method improves classification accuracies when compared to other classification approaches.

Tarabalka, Yuliya↗

Bayes Error Rate Estimation Using Classifier Ensembles

The Bayes error rate gives a statistical lower bound on the error achievable for a given classification problem and the associated choice of features. By reliably estimating th is rate, one can assess the usefulness of the feature set that is being used for classification. Moreover, by comparing the accuracy achieved by a given classifier with the Bayes rate, one can quantify how effective that classifier is. Classical approaches for estimating or finding bounds for the Bayes error, in general, yield rather weak results for small sample sizes; unless the problem has some simple characteristics, such as Gaussian class-conditional likelihoods. This article shows how the outputs of a classifier ensemble can be used to provide reliable and easily obtainable estimates of the Bayes error with negligible extra computation. Three methods of varying sophistication are described. First, we present a framework that estimates the Bayes error when multiple classifiers, each providing an estimate of the a posteriori class probabilities, a recombined through averaging. Second, we bolster this approach by adding an information theoretic measure of output correlation to the estimate. Finally, we discuss a more general method that just looks at the class labels indicated by ensem ble members and provides error estimates based on the disagreements among classifiers. The methods are illustrated for artificial data, a difficult four-class problem involving underwater acoustic data, and two problems from the Problem benchmarks. For data sets with known Bayes error, the combiner-based methods introduced in this article outperform existing methods. The estimates obtained by the proposed methods also seem quite reliable for the real-life data sets for which the true Bayes rates are unknown.

Tumer, Kagan↗

Statistical Performance of TOPEX/POSEIDON Prime Mission Ground and On-Board Ephemerides and Consequences for the Extended Mission

TOPEX/POSEIDON is a joint American/French ocean topography experiment currently in the last year of its nominal mission and soon to enter a three year extended mission. To meet science requirements, the satellite must point the altimeter antenna at the ocean local nadir with good accuracy. This paper discusses the pointing accuracy of the Operational Orbit Ephemeris and its Fourier power series representation in the On-Board Computer. The consequences for the extended mission due to this performance are also discussed.

TOPEX/POSEIDON↗

Verify MesoNAM Performance

The AMU conducted an objective analysis of the MesoNAM forecasts compared to observed values from sensors at specified KSC/CCAFS wind towers by calculating the following statistics to verify the performance of the model: 1) Bias (mean difference), 2) Standard deviation of Bias, 3) Root Mean Square Error (RMSE), and 4) Hypothesis test for Bias = O. The 45 WS LWOs use the MesoNAM to support launch weather operations. However, the actual performance of the model at KSC and CCAFS had not been measured objectively. The analysis compared the MesoNAM forecast winds, temperature and dew point to the observed values from the sensors on wind towers. The data were stratified by tower sensor, month and onshore/offshore wind direction based on the orientation of the coastline to each tower's location. The model's performance statistics were then calculated for each wind tower based on sensor height and model initialization time. The period of record for the data used in this task was based on the operational start of the current MesoNAM in mid-August 2006 and so the task began with the first full month of data, September 2006, through May 2010. The analysis of model performance indicated: a) The accuracy decreased as the forecast valid time from the model initialization increased, b) There was a diurnal signal in T with a cool bias during the late night and a warm bias during the afternoon, c) There was a diurnal signal in Td with a low bias during the afternoon and a high bias during the late night, and d) The model parameters at each vertical level most closely matched the observed parameters at heights closest to those vertical levels. The AMU developed a GUI that consists of a multi-level drop-down menu written in JavaScript embedded within the HTML code. This tool allows the LWO to easily and efficiently navigate among the charts and spreadsheet files containing the model performance statistics. The objective statistics give the LWOs knowledge of the model's strengths and weaknesses and the GUI allows quick access to the data which will result in improved forecasts for operations.

Bauman, William H., III↗

Lightning NOx Statistics Derived by NASA Lightning Nitrogen Oxides Model (LNOM) Data Analyses

What is the LNOM? The NASA Marshall Space Flight Center (MSFC) Lightning Nitrogen Oxides Model (LNOM) [Koshak et al., 2009, 2010, 2011; Koshak and Peterson 2011, 2013] analyzes VHF Lightning Mapping Array (LMA) and National Lightning Detection Network(TradeMark) (NLDN) data to estimate the lightning nitrogen oxides (LNOx) produced by individual flashes. Figure 1 provides an overview of LNOM functionality. Benefits of LNOM: (1) Does away with unrealistic "vertical stick" lightning channel models for estimating LNOx; (2) Uses ground-based VHF data that maps out the true channel in space and time to < 100 m accuracy; (3) Therefore, true channel segment height (ambient air density) is used to compute LNOx; (4) True channel length is used! (typically tens of kilometers since channel has many branches and "wiggles"); (5) Distinction between ground and cloud flashes are made; (6) For ground flashes, actual peak current from NLDN used to compute NOx from lightning return stroke; (7) NOx computed for several other lightning discharge processes (based on Cooray et al., 2009 theory): (a) Hot core of stepped leaders and dart leaders, (b) Corona sheath of stepped leader, (c) K-change, (d) Continuing Currents, and (e) M-components; and (8) LNOM statistics (see later) can be used to parameterize LNOx production for regional air quality models (like CMAQ), and for global chemical transport models (like GEOS-Chem).

Koshak, William↗