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NASA NTRS1980

Statistical wind profile gust model

A statistical wind profile gust model for the Space Transportation Operations and Trade Studies is developed by using 1800 Jimsphere wind profile data collected at Cape Kennedy during 1965 to 1972. Wind profiles from the surface to 20 km in component form, i.e., zonal and meridional are processed through the digital filters of different wave length ranges bases on the Martin-Graham cosine rolloff model. The residuals obtained from the filtering processes for the data base for the statistical analysis. For each wind component the gust and gust length at a specified reference altitude in a residual profile are defined. A two parameter gamma probability marginal distribution seems to fit the component gust amplitude and the gust length when redefined. The problem of finding an appropriate bivariate joint distribution of the gust amplitude and length remains to be solved. The probability distribution of the modulus of the gust amplitudes was derived under the assumption that they are independently distributed as gamma variates.

Doss, D. C.↗

NASA NTRS1981

Climatological characteristics of high altitude wind shear and lapse rate layers

Indications of the climatological distribution of wind shear and temperature lapse and inversion rates as observed by rawinsonde measurements over the western United States are recorded. Frequencies of the strongest shear, lapse rates, and inversion layer strengths were observed for a 1 year period of record and were tabulated for the lower troposphere, the upper troposphere, and five altitude intervals in the lower stratosphere. Selected bivariate frequencies were also tabulated. Strong wind shears, lapse rates, and inversion are observed less frequently as altitude increases from 175 millibars to 20 millibars. On a seasonal basis the frequencies were higher in winter than in summer except for minor influences due to increased tropopause altitude in summer and the stratospheric wind reversal in the spring and fall.

Ehernberger, L. J.↗

NASA NTRS1981

A comprehensive model to determine the effects of temperature and species fluctuations on reactions in turbulent reacting flows

The joint probability distribution function (pdf), which is a modification of the bivariate Gaussian pdf, is discussed and results are presented for a global reaction model using the joint pdf. An alternative joint pdf is discussed. A criterion which permits the selection of temperature pdf's in different regions of turbulent, reacting flow fields is developed. Two principal approaches to the determination of reaction rates in computer programs containing detailed chemical kinetics are outlined. These models represent a practical solution to the modeling of species reaction rates in turbulent, reacting flows.

Antaki, P. J.↗

NASA NTRS1982

A comprehensive model to determine the effects of temperature and species fluctuations on reaction rates in turbulent reacting flows

A principal element to be derived from modeling turbulent reacting flows is an expression for the reaction rates of the various species involved in any particular combustion process under consideration. A temperature-derived most-likely probability density function (pdf) was used to describe the effects of temperature fluctuations on the Arrhenius reaction rate constant. A most-likely bivariate pdf described the effects of temperature and species concentrations fluctuations on the reaction rate. A criterion is developed for the use of an "appropriate" temperature pdf. The formulation of models to calculate the mean turbulent Arrhenius reaction rate constant and the mean turbulent reaction rate is considered and the results of calculations using these models are presented.

Foy, E.↗

NASA NTRS1981

The Use of Interactive Raster Graphics in the Display and Manipulation of Multidimensional Data

Techniques for the review, display, and manipulation of multidimensional data are developed and described. Multidimensional data is meant in this context to describe scalar data associated with a three dimensional geometry or otherwise too complex to be well represented by traditional graphs. Raster graphics techniques are used to display a shaded image of a three dimensional geometry. The use of color to represent scalar data associated with the geometries in shaded images is explored. Distinct hues are associated with discrete data ranges, thus emulating the traditional representation of data with isarithms, or lines of constant numerical value. Data ranges are alternatively associated with a continuous spectrum of hues to show subtler data trends. The application of raster graphics techniques to the display of bivariate functions is explored.

Anderson, D. C.↗

NASA NTRS1982

Correlation of hard X-ray and type 3 bursts in solar flares

Correlations between X-ray and type 3 radio emission of solar bursts are described through a bivariate distribution function. Procedures for determining the form of this distribution are described. A model is constructed to explain the correlation between the X-ray spectral index and the ratio of X-ray to radio intensities. Implications of the model are discussed.

Petrosian, V.↗

NASA NTRS1984

Generating Random Number Pairs

Algorithm generates pairs drawn from bivariate normal distribution with any desired values of two means, two standard deviations, and correlation coefficient.

Campbell, C. W.↗

NASA NTRS1982

BSPLASH: A three-stage surface interpolant to scattered data

Given N distinct points (X sub i, Y sub i) and N real numbers Z sub i, BSPLASH constructs a function G (x, y) that satisfies G (x sub i, y sub i) = Z sub i for i = 1,..., N. This C(2) interpolant consists of a bicubic spline approximation and Shepard's bivariate interpolant.

Foley, T. A.↗

NASA NTRS1982

Quantiles, parametric-select density estimation, and bi-information parameter estimators

A quantile-based approach to statistical analysis and probability modeling of data is presented which formulates statistical inference problems as functional inference problems in which the parameters to be estimated are density functions. Density estimators can be non-parametric (computed independently of model identified) or parametric-select (approximated by finite parametric models that can provide standard models whose fit can be tested). Exponential models and autoregressive models are approximating densities which can be justified as maximum entropy for respectively the entropy of a probability density and the entropy of a quantile density. Applications of these ideas are outlined to the problems of modeling: (1) univariate data; (2) bivariate data and tests for independence; and (3) two samples and likelihood ratios. It is proposed that bi-information estimation of a density function can be developed by analogy to the problem of identification of regression models.

Parzen, E.↗

NASA NTRS1983

FUNSTAT and statistical image representations

General ideas of functional statistical inference analysis of one sample and two samples, univariate and bivariate are outlined. ONESAM program is applied to analyze the univariate probability distributions of multi-spectral image data.

Parzen, E.↗

NASA NTRS1981

A life history method for estimating convective rainfall

The remote sensing of rain amounts is of great interest for a great variety of operational applications, including hydrology, hydroelectricity and agriculture is discussed. The microwave radiometer represents the most obvious technique, however, poor spatial and temporal resolution, together with the problems associated with the estimation of effective rain layer height make visible and IR techniques more promising at the present time. Based on bivariate frequency distribution of brightness versus temperature, brightness enhancing or infrared technique alone may be inadequate to deduce details of convective activity. It is implied that better estimates of rainfall will come from visible and IR observations combined than from either used alone. The technique identifies clouds with high probability of rain as those which have large optical and presumably physical thickness as measured by the visible albedo in comparison with their height, determined by the intensity of the IR emission.

Martin, D. W.↗

NASA NTRS1983

Information retrieval from wide-band meteorological data - An example

The methods proposed by Smith and Adelfang (1981) and Smith et al. (1982) are used to calculate probabilities over rectangles and sectors of the gust magnitude-gust length plane; probabilities over the same regions are also calculated from the observed distributions and a comparison is also presented to demonstrate the accuracy of the statistical model. These and other statistical results are calculated from samples of Jimsphere wind profiles at Cape Canaveral. The results are presented for a variety of wavelength bands, altitudes, and seasons. It is shown that wind perturbations observed in Jimsphere wind profiles in various wavelength bands can be analyzed by using digital filters. The relationship between gust magnitude and gust length is modeled with the bivariate gamma distribution. It is pointed out that application of the model to calculate probabilities over specific areas of the gust magnitude-gust length plane can be useful in aerospace design.

Adelfang, S. I.↗

NASA NTRS1983

Correlation of hard X-ray and type III bursts in solar flares

Petrosian, V.↗

NASA NTRS1983

Analysis of Wind Gust Data

Wind gust data were analyzed by statistical and mathematical procedures, developed for the bivariate gamma distribution. The results of the analysis are summarized.

Tubbs, J. D.↗

NASA NTRS1984

An operator calculus for surface and volume modeling

The mathematical techniques which form the foundation for most of the surface and volume modeling techniques used in practice are briefly described. An outline of what may be termed an operator calculus for the approximation and interpolation of functions of more than one independent variable is presented. By considering the linear operators associated with bivariate and multivariate interpolation/approximation schemes, it is shown how they can be compounded by operator multiplication and Boolean addition to obtain a distributive lattice of approximation operators. It is then demonstrated via specific examples how this operator calculus leads to practical techniques for sculptured surface and volume modeling.

Gordon, W. J.↗

NASA NTRS1984

Development of dynamic simulation of TF34-GE-100 turbofan engine with post-stall capability

This paper describes the development of a hybrid computer simulation of a TF34-GE-100 turbofan engine with post-stall capability. The simulation operates in real-time and will be used to test and evaluate stall recovery control modes for this engine. The simulation calculations are performed by an analog computer with a peripheral multivariable function generation unit used for computing bivariate functions. Tabular listings of a simulation variables are obtained by interfacing to a digital computer and using a custom software package for data collection and display.

Krosel, S. M.↗

NASA NTRS1983

Fitting of satellite and in-situ ocean surface temperatures Results for polymode during the winter of 1977-1978

For the period considered, December 1977 through February 1978, bivariate Gaussian discriminant function cloud identification revealed that more than 93 percent of the 8-km resolution GOES infrared pixels were cloud contaminated. Cloud-free in-situ calibration points were distributed in nonrandom groups; this resulted in systematic errors when using least squares techniques. Surfaces and regression lines were least squares fitted between satellite and in-situ data; use was also made of differences and ratios. The best results were achieved with a regression in the form of the infrared radiative transfer equation; but this was no better than + or - 0.9 K. Because of extensive cloudiness, the linear regressions were seldom useful, and temperature ratios with + or - 1.3 K experimental errors best represent the applicability of GEOS data to sea surface temperatures.

Maul, G. A.↗

NASA NTRS1984

A model function for ocean radar cross sections at 14.6 GHz

The relationship between the ocean's normalized radar cross section (NRCS) at 14.6 GHz and the surface wind vector is derived using the 3 months of Seasat microwave scatterometer (SASS) measurements. The derivation is based on the statistics of the SASS observations, and no in situ measurements are required, other than a mean global wind speed, which comes from climatology. The frequency distribution of the global wind vectors observed by SASS is assumed to be a bivariate normal probability function. A NRCS model function is found that maps the assumed wind vector statistics into the observed SASS NRCS statistics. This function is compared with a NRCS model coming from the Joint Air Sea Interaction Experiment (JASIN) and with aircraft scatterometer measurements. The results indicate that the statistically derived NRCS model is an improvement over the JASIN model, which was based on a limited number of in situ anemometer measurements.

Wentz, F. J.↗