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NASA NTRS1990

Spatial variability of rain rate and slant path attenuation distributions at 28 GHz in the mid-Atlantic coast region of the United States

Rain rate and corresponding estimated slant-path attenuation distributions derived from two years of measurements are presented for a network of nine rain-gage sites located in a region with extent 70 km N-S and 47 km E-W in the mid-Atlantic coast of the U.S. near the NASA Wallops Flight Facility, VA. The network average rain-rate distribution was compared with a previously measured 6-year average at one of the site locations. Agreement in rain rates was found to be within approximately 1 mm/h over the percentage range of 1-0.01 percent of the year, signifying the constancy of the rain-rate climatology for the region, and implying an ergodic rainfall process. Slant-path attenuation statistics were estimated at 28.56 GHz by interfacing the measured rain-rate distributions at each of nine site locations with Crane's (1980) global model.

Goldhirsh, Julius↗

NASA NTRS2013

10 Yr Spatial and Temporal Trends of PM2.5 Concentrations in the Southeastern US Estimated Using High-resolution Satellite Data

Long-term PM2.5 exposure has been reported to be associated with various adverse health outcomes. However, most ground monitors are located in urban areas, leading to a potentially biased representation of the true regional PM2.5 levels. To facilitate epidemiological studies, accurate estimates of spatiotemporally continuous distribution of PM2.5 concentrations are essential. Satellite-retrieved aerosol optical depth (AOD) has been widely used for PM2.5 concentration estimation due to its comprehensive spatial coverage. Nevertheless, an inherent disadvantage of current AOD products is their coarse spatial resolutions. For instance, the spatial resolutions of the Moderate Resolution Imaging Spectroradiometer (MODIS) and the Multiangle Imaging SpectroRadiometer (MISR) are 10 km and 17.6 km, respectively. In this paper, a new AOD product with 1 km spatial resolution retrieved by the multi-angle implementation of atmospheric correction (MAIAC) algorithm was used. A two-stage model was developed to account for both spatial and temporal variability in the PM2.5-AOD relationship by incorporating the MAIAC AOD, meteorological fields, and land use variables as predictors. Our study area is in the southeastern US, centered at the Atlanta Metro area, and data from 2001 to 2010 were collected from various sources. The model was fitted for each year individually, and we obtained model fitting R2 ranging from 0.71 to 0.85, MPE from 1.73 to 2.50 g m3, and RMSPE from 2.75 to 4.10 g m3. In addition, we found cross validation R2 ranging from 0.62 to 0.78, MPE from 2.00 to 3.01 g m3, and RMSPE from 3.12 to 5.00 g m3, indicating a good agreement between the estimated and observed values. Spatial trends show that high PM2.5 levels occurred in urban areas and along major highways, while low concentrations appeared in rural or mountainous areas. A time series analysis was conducted to examine temporal trends of PM2.5 concentrations in the study area from 2001 to 2010. The results showed that the PM2.5 levels in the study area followed a generally declining trend from 2001 to 2010 and decreased about 20 during the period. However, there was an exception of an increase in year 2005, which is attributed to elevated sulfate concentrations in the study area in warm months of 2005. An investigation of the impact of wild and prescribed fires on PM2.5 levels in 2007 suggests a positive relationship between them.

particulate matter (PM2.5)↗

NASA NTRS1991

The distribution of particulate material on Mars

The surface materials on Mars were extensively studied using a variety of spacecraft and Earth-based remote sensing observations. These measurements include: (1) diurnal thermal measurements, used to determine average particle size, rock abundance, and the presence of crusts; (2) radar observations, used to estimate the surface slope distributions, wavelength scale roughness, and density; (3) radio emission observations, used to estimate subsurface density; (4) broadband albedo measurements, used to study the time variation of surface brightness and dust deposition and removal; and (5) color observations, used to infer composition, mixing, and the presence of crusts. Remote sensing observations generally require some degree of modeling to interpret, making them more difficult to interpret than direct observations from the surface. They do, however, provide a means for examining the surface properties over the entire planet and a means of sampling varying depths within the regolith. Albedo and color observations only indicate the properties of the upper-most few microns, but are very sensitive to thin, sometimes emphemeral dust coatings. Thermal observations sample the upper skin depth, generally 2 to 10 cm. Rock abundance measurements give an indirect indication of surface mantling, where the absence of rocks suggests mantles of several meters. Finally, radar and radio emission data can penetrate several meters into the surface, providing an estimate of subsurface density and roughness.

Christensen, Philip R.↗

NASA NTRS1985

Gamma-ray line emission from Al-26 produced by Wolf-Rayet stars

The recent satellite observations of the 1.8 MeV line from the decay of Al-26 has given a new impetus to the study of the nucleosynthesis of Al-26. The production and ejection of Al-26 by massive mass-losing stars (Of and WR stars) is discussed in the light of recent stellar models. The longitude distribution of the Al-26 gamma ray line emission produced by the galactic collection of WR stars is derived based on various estimates of their radial distribution. This longitude profile provides: (1) a specific signature of massive stars on the background of other potential Al-26 sources, as novae, supernovae, certain red giants and possibly AGB stars; and (2) a possible tool to improve the data analysis of the HEAO 3 and SMM experiments.

Prantzos, N.↗

NASA NTRS1983

Micromechanically Based Constitutive Relations for Polycrystalline Solids

A basic method to estimate the overall mechanical response of solids which contain periodically distributed defects is presented. The method estimates the shape and growth pattern of voids periodically distributed over the grain boundaries in a viscous matrix. The relaxed moduli are obtained for a polycrytalline solid that undergoes relaxation by grain boundary sliding which accounts for the interaction effects. The overall inelastic nonlinear response at elevated temperatures in terms of a model which considers nonlinear power law creep within the grains, and linear viscous flow in the grain boundaries is discussed.

Nemat-Nasser, S.↗

NASA NTRS2018

A Singular Value Decomposition Framework for Retrievals with Vertical Distribution Information from Greenhouse Gas Column Absorption Spectroscopy Measurements

We describe a variation of the Optimal Estimation (OE) method for greenhouse gas remote sensing retrievals using a singular value decomposition (SVD) and an uninformative prior. The SVD method is capable of discerning vertical information in column integrated absorption measurements. While traditional Bayesian optimal estimation (OE) assumes a prior distribution in order to regularize the inversion problem, the SVD approach identifies principal components that can be retrieved from the measurement without explicitly specifying a prior mean and prior covariance matrix. We discuss the method, illustrate its use on an integrated path differential absorption CO2 lidar measurement model, and compare it to traditional optimal estimation using numerical simulations. In the absence of forward model error, the mathematics behind the SVD method guarantee it to be bias-free, which is confirmed by the numerical simulations. In contrast, traditional OE retrievals exhibit bias when the prior mean used in the retrieval differs from the true mean. While the SVD approach can be used for most trace gas retrievals, it is particularly useful for situations where prior knowledge of the trace gas profile is poor. The SVD analysis is also useful in illustrating how vertical information is treated by the traditional OE approach.

Ramanathan, Anand K.↗

NASA NTRS1973

The Mean Ozone Distribution from Several Series of Rocket Sounding to 52 Km at Latitudes from 58 Deg S to 64 Deg N

The results of 21 rocket flights of Arcas optical ozonesondes were combined to produce estimates of the mean ozone distribution and its variability; these estimates apply to a broad range of latitudes. The flights were launched from sites near the equator to 58 S and to 64 N, in the years from 1965 to 1971. The local-noon mean ozone densities in molecules/cubic centimeter are 7.0 to the 10th power at 50 km, 6.7 x 10 to the 11th power at 40 km, 3.1 x 10 to the 12th power at 30 km, and 3.1 x 10 to the 12th power at 20 km. The range of observed densities is about + or - 30 percent of the mean value at 50 km; + or 40 percent at 40 km; + or - 40 percent at 30 km; and +200 percent, -66 percent at 20 km. The variabilities in this set of observations are much smaller than those indicated by previous measurements.

Krueger, A. J.↗

NASA NTRS1977

A model for dispersion from area sources in convective turbulence

Four independent estimates of the vertical distribution of the eddy coefficient for dispersion of a passive contaminant from an extensive area source in a convective layer have been presented. The estimates were based on the following methods: (1) a second-order closure prediction, (2) field data of pollutant concentrations over Los Angeles, (3) lab measurements of particle dispersion, and (4) assumption of equality between momentum and mass transfer coefficients in the free convective limit. It is suggested that K-values estimated both from second-order closure theory and from Los Angeles measurements are systematically underestimated.

Crane, G.↗

NASA NTRS1991

Space station internal propagation

The Space Station Freedom (SSF) is planned with a wireless communication system in place for the transmission of information between crew members on board. The clarity of transmission is paramount to an effective system of communication. A short overview is presented of the system including the requirements of interest, and a statement of the problem. The theory used to solve the problem is explored. The results given are for the experiments performed on a mockup of the proposed structure at NASA-Marshall. The requirements on the signal level are that there is a 45 dB signal to noise ratio from end to end, and that coverage over 99 pct. of the volume be maintained. The Rice probability distribution function, a simple extension of the Rayleigh distribution, is used to estimate the field strength inside a volume, where a significant line of sight from the transmitter to the receiver exists. For the SSF, this distribution will correspond to the summation of a coherent line of sight path between the transmitter and the receiver and an incoherent portion. The incoherent portion is the sum of reflections from the walls and the equipment inside the SSF. The Rice distribution was found to be the optimal distribution from the results.

Richie, J. E.↗

NASA NTRS1996

Estimation of Snow Parameters Based on Passive Microwave Remote Sensing and Meteorological Information

A method to incorporate passive microwave remote sensing measurements within a spatially distributed snow hydrology model to provide estimates of the spatial distribution of Snow Water Equivalent (SWE) as a function of time is implemented. The passive microwave remote sensing measurements are at 25 km resolution. However, in mountain regions the spatial variability of SWE over a 25 km footprint is large due to topographic influences. On the other hand, the snow hydrology model has built-in topographic information and the capability to estimate SWE at a 1 km resolution. In our work, the snow hydrology SWE estimates are updated and corrected using SSM/I passive microwave remote sensing measurements. The method is applied to the Upper Rio Grande River Basin in the mountains of Colorado. The change in prediction of SWE from hydrology modeling with and without updating is compared with measurements from two SNOTEL sites in and near the basin. The results indicate that the method incorporating the remote sensing measurements into the hydrology model is able to more closely estimate the temporal evolution of the measured values of SWE as a function of time.

Tsang, Leung↗

NASA NTRS1972

Dynamic mass modeling and geophysical analysis of lunar maria based on Apollo tracking data

A series of lunar gravity analyses were carried out using unified S-band tracking network data obtained from Apollos 8, 10, 11, 12, 14, and 15. The progress obtained to date is summarized as it relates to the estimation of lunar mass distributions and their geologic interpretation. The analyses reported are of two distinct types. The first type consists of data obtained at two ranges of altitude to estimate the total mass associated with various lunar features employing a point mass assumption. The second type consists of detailed analyses of Apollo 14 tracking data.

Strange, W. E.↗

NASA NTRS1994

Independent pixel and Monte Carlo estimates of stratocumulus albedo

Monte Carlo radiative transfer methods are employed here to estimate the plane-parallel albedo bias for marine stratocumulus clouds. This is the bias in estimates of the mesoscale-average albedo, which arises from the assumption that cloud liquid water is uniformly distributed. The authors compare such estimates with those based on a more realistic distribution generated from a fractal model of marine stratocumulus clouds belonging to the class of 'bounded cascade' models. In this model the cloud top and base are fixed, so that all variations in cloud shape are ignored. The model generates random variations in liquid water along a single horizontal direction, forming fractal cloud streets while conserving the total liquid water in the cloud field. The model reproduces the mean, variance, and skewness of the vertically integrated cloud liquid water, as well as its observed wavenumber spectrum, which is approximately a power law. The Monte Carlo method keeps track of the three-dimensional paths solar photons take through the cloud field, using a vectorized implementation of a direct technique. The simplifications in the cloud field studied here allow the computations to be accelerated. The Monte Carlo results are compared to those of the independent pixel approximation, which neglects net horizontal photon transport. Differences between the Monte Carlo and independent pixel estimates of the mesoscale-average albedo are on the order of 1% for conservative scattering, while the plane-parallel bias itself is an order of magnitude larger. As cloud absorption increases, the independent pixel approximation agrees even more closely with the Monte Carlo estimates. This result holds for a wide range of sun angles and aspect ratios. Thus, horizontal photon transport can be safely neglected in estimates of the area-average flux for such cloud models. This result relies on the rapid falloff of the wavenumber spectrum of stratocumulus, which ensures that the smaller-scale variability, where the radiative transfer is more three-dimensional, contributes less to the plane-parallel albedo bias than the larger scales, which are more variable. The lack of significant three-dimensional effects also relies on the assumption of a relatively simple geometry. Even with these assumptions, the independent pixel approximation is accurate only for fluxes averaged over large horizontal areas, many photon mean free paths in diameter, and not for local radiance values, which depend strongly on the interaction between neighboring cloud elements.

Cahalan, Robert F.↗

NASA NTRS2006

An Ensemble-Based Smoother with Retrospectively Updated Weights for Highly Nonlinear Systems

Monte Carlo computational methods have been introduced into data assimilation for nonlinear systems in order to alleviate the computational burden of updating and propagating the full probability distribution. By propagating an ensemble of representative states, algorithms like the ensemble Kalman filter (EnKF) and the resampled particle filter (RPF) rely on the existing modeling infrastructure to approximate the distribution based on the evolution of this ensemble. This work presents an ensemble-based smoother that is applicable to the Monte Carlo filtering schemes like EnKF and RPF. At the minor cost of retrospectively updating a set of weights for ensemble members, this smoother has demonstrated superior capabilities in state tracking for two highly nonlinear problems: the double-well potential and trivariate Lorenz systems. The algorithm does not require retrospective adaptation of the ensemble members themselves, and it is thus suited to a streaming operational mode. The accuracy of the proposed backward-update scheme in estimating non-Gaussian distributions is evaluated by comparison to the more accurate estimates provided by a Markov chain Monte Carlo algorithm.

Monte Carlo↗

NASA NTRS1974

The definition and specification of the near earth environmental criteria for spacecraft thermal design

The variation of the earth's thermal and albedo radiation received by a near-earth orbiting space vehicle or space payload as a result of temporal variation of the earth atmosphere is discussed. A statistical study of current satellite data for determining probability distributions is proposed. With these distributions the thermal designer can define confidence levels on predicted temperature ranges which are compatible with engineering models for use in design, failure probabilities, and spacecraft cost estimates. Use of the distributions in environmental criteria guidelines is also considered.

Gary, G. A.↗

NASA NTRS1981

The effects of missing data on global ozone estimates

The effects of missing data and model truncation on estimates of the global mean, zonal distribution, and global distribution of ozone are considered. It is shown that missing data can introduce biased estimates with errors that are not accounted for in the accuracy calculations of empirical modeling techniques. Data-fill techniques are introduced and used for evaluating error bounds and constraining the estimate in areas of sparse and missing data. It is found that the accuracy of the global mean estimate is more dependent on data distribution than model size. Zonal features can be accurately described by 7th order models over regions of adequate data distribution. Data variance accounted for by higher order models appears to represent climatological features of columnar ozone rather than pure error. Data-fill techniques can prevent artificial feature generation in regions of sparse or missing data without degrading high order estimates over dense data regions.

Drewry, J. W.↗

NASA NTRS1987

UV flux distributions of novalike variables

Previous estimates of distance, reddening, orbital inclination, and white dwarf mass for a sample of nine nova-like cataclysmic variables are presented, along with their representative IUE fluxes. Blackbody and Kurucz (1979) model atmosphere fluxes are used to construct sequences of model accretion disk spectra. It is found that the Kurucz-type accretion disk models do not reproduce simultaneously the UV flux level and color.

Wade, Richard A.↗

NASA NTRS1983

The spatial distribution of fixed mutations within genes coding for proteins

An examination has been conducted of the extensive amino acid sequence data now available for five protein families - the alpha crystallin A chain, myoglobin, alpha and beta hemoglobin, and the cytochromes c - with the goal of estimating the true spatial distribution of base substitutions within genes that code for proteins. In every case the commonly used Poisson density failed to even approximate the experimental pattern of base substitution. For the 87 species of beta hemoglobin examined, for example, the probability that the observed results were from a Poisson process was the minuscule 10 to the -44th. Analogous results were obtained for the other functional families. All the data were reasonably, but not perfectly, described by the negative binomial density. In particular, most of the data were described by one of the very simple limiting forms of this density, the geometric density. The implications of this for evolutionary inference are discussed. It is evident that most estimates of total base substitutions between genes are badly in need of revision.

Holmquist, R.↗

NASA NTRS1989

Stress distribution and topography of Tellus Regio, Venus

The Tellus Regio area of Venus represents a subset of a narrow latitude band where Pioneer Venus Orbiter (PVO) altimetry data, line-of-sight (LOS) gravity data, and Venera 15/16 radar images have all been obtained with good resolution. Tellus Regio also has a wide variety of surface morphologic features, elevations ranging up to 2.5 km, and a relatively low LOS gravity anomaly. This area was therefore chosen in order to examine the theoretical stress distributions resulting from various models of compensation of the observed topography. These surface stress distributions are then compared with the surface morphology revealed in the Venera 15/16 radar images. Conclusions drawn from these comparisons will enable constraints to be put on various tectonic parameters relevant to Tellus Regio. The stress distribution is calculated as a function of the topography, the equipotential anomaly, and the assumed model parameters. The topography data is obtained from the PVO altimetry. The equipotential anomaly is estimated from the PVO LOS gravity data. The PVO LOS gravity represents the spacecraft accelerations due to mass anomalies within the planet. These accelerations are measured at various altitudes and angles to the local vertical and therefore do not lend themselves to a straightforward conversion. A minimum variance estimator of the LOS gravity data is calculated, taking into account the various spacecraft altitudes and LOS angles and using the measured PVO topography as an a priori constraint. This results in an estimated equivalent surface mass distribution, from which the equipotential anomaly is determined.

Williams, David R.↗