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At least 163 records · Page 9

Spinning dust emission from ultra-small silicates: emissivity and polarization spectrum

Anomalous microwave emission (AME) is an important Galactic foreground of cosmic microwave background radiation. It is believed that AME arises from rotational emission by spinning polycyclic aromatic hydrocarbons in the interstellar medium (ISM). In this paper, we suppose that a new population of ultra-small silicate grains perhaps exists in the ISM, and quantify the rotational emissivity from these tiny particles and its polarization spectrum. We find that spinning silicate nanoparticles can produce strong rotational emission when the tiny grains follow a log-normal size distribution. The polarization fraction of spinning dust emission from tiny silicates increases with decreasing dipole moment per atom (β) and can reach P∼20% for β∼0.1 D at a grain temperature of 60 K. We identify a parameter space (β,Y{sub Si}), with Y{sub Si} being the fraction of Si abundance in nanoparticles, in which its rotational emission can adequately reproduce both the observed AME and the polarization of the AME, without violating the observational constraints of ultraviolet extinction and polarization of starlight. Our results reveal that rotational emission from spinning silicate may be an important source of AME.

79 ASTRONOMY AND ASTROPHYSICS↗

A size-frequency study of large Martian craters

The log normal frequency distribution law was used to analyze the crater population on the surface of Mars. Resulting data show possible evidence for the size frequency evolution of crater producing bodies. Some regions on Mars display excessive depletion of either large or small craters; the most likely causes of the depletion are considered. Apparently, eolian sedimentation has markedly altered the population of the small craters south of -30 deg latitude. The general effects of crater obliteration in the Southern Hemisphere appear to be confined to diameters of less than 20 km. A strong depletion of large craters in a large region just south of Deuteronilus Mensae, and in a small region centered at 35 deg latitude and 10 deg west longitude, may indicate locations of subsurface ice.

Woronow, A.↗

Aerosol sensing from balloons using photopolarimetry

A photopolarimeter designed to measure the radiance and the polarization ratio at lambda equals 0.85 microns and lambda equals 1.65 microns is set up on a gondola of a stratospheric balloon. By rotating the gondola, measurements of the diffuse solar light are obtained for a wide range of the scattering angles. An inversion scheme, based on the assumption of a log-normal size distribution, provides the relevant size parameters, the refractive index, and the slant optical thicknesses of the aerosols. Since 1983, this experiment was launched twice a year from Aire Sur Adour (S-E of France). The post-El Chichon atmospheric stratospheric aerosol proved to be quite stable in size and nature (hydratid sulfuric acid), but the abundance decreased by a factor of 10 between 1983 and 1987. The experiment was also launched to observe the stratosphere during the Arctic winter. Two flights, on January 28, 1988 and January 18, 1990, corresponded to an unperturbed atmosphere. But during a third flight, on April, 2, 1990, the temperatures were low enough for PCS formulations. A multilayer situation was observed with the standard H2SOH aerosols below 20 km; a dense layer was observed, peaked at around 23 km, with scattering coefficients about 50 times layer than in background conditions; and an upper layer was observed, rather sharp (approximately equal to 1 km), with micron sized particles.

Santer, R.↗

Optical properties of aerosol emissions from biomass burning in the tropics, BASE-A

Ground-based and airborne measurements of biomass-burning smoke particle optical properties, obtained with a view to aerosol-absorption properties, are presented as a function of time and atmospheric height. The wavelength dependence of the optical thickness can be explained by a log-normal size distribution, with particles' effective radius varying between 0.1 and 0.2 microns. The strong correlation noted between aerosol particle profile and CO profile indicates that smoke particulates constitute a good tracer for emission trace gases from tropical biomass burning.

Holben, Brent N.↗

A satellite-borne radar wind sensor (RAWS)

Modeling global atmospheric circulations and forecasting the weather would improve if worldwide information on winds aloft were available. Accurate prediction of weather is important to agriculture, shipping, air traffic, and many other fields. Global system models of climate are of great importance. Current global atmospheric models use pressure measurements and thermodynamic properties to calculate the effects of wind for use in Numerical Weather Prediction (NWP) models. Inputs to the NWP models are temperature, pressure and wind velocities at different heights. Clearly direct wind measurements could significantly improve the NWP model performance. The RAdar Wind Sounder (RAWS) program at the University of Kansas is a study of the feasibility and the trade-offs in the design of a space-based radar system to measure wind vectors. This can be done by measuring the Doppler shift of cloud and rain returns from three or more points and calculating the components of the wind vector. The RAWS study to date uses the candidate system selected after preliminary study of frequencies and sensitivities. Two frequencies chosen, 10 and 35 GHz, allow higher sensitivity for clouds and more penetration for rain. The past year was devoted to modeling the signal-to-noise ratio (SNR) achievable for the two frequencies. The determination of SNR versus cloud penetration depth used a cloud backscattering and attenuation model in the appropriate radar equation. Calculations assumed reasonable losses in reception and transmission, in addition to the atmospheric attenuation. We discovered that ice clouds provide a higher SNR than previously calculated, but some water clouds give lower SNRs than we calculated before. One of the primary issues in the SNR calculation was the choice of the drop size distribution. Although Xin used several distributions (e.g., log normal, Khrigian and Mazin), this year we used the Deirmendjian cloud model. SNR versus cloud penetration plots were generated to validate the candidate system. Rain, which appears in the cloud models at the lower altitudes, provides ample SNR, as do the higher clouds composed of ice particles. However, in some cloud situations we found the sensitivity for the clouds was marginal or inadequate. At 35 GHz, two of the cloud models characterized by 1 to 2 g/cu m of water content at altitudes extending from 150 to 1500 meters, produced a sufficient SNR. Other models, however, with water contents ranging from 0.5 to 4 g/cu m and altitudes up to 4000 meters, exhibit SNR of -3 to -23 dB, largely because of attenuation in the upper cloud layers. These results coupled with the lower SNR at 10 GHz, led to an investigation of alternate frequencies. The rain present beneath these clouds provides adequate SNR at 10 GHz, and in most cases, at GHz.

Moore, Richard K.↗

Radiative Closure Experiments at a Cloud-Free Desert Site, Nevada, as Part of MISR Algorithm Validation

Radiative closure experiments involving a comparison between surface-measured spectral irradiance and the surface irradiance calculated according to a radiative transfer code at a desert site in Nevada under clear skies, yield the result that agreement between the two requires presence of an absorbing aerosol component with an imaginary refractive index equal to 0.03 and a 50:50 mix by optical depth of small and large particles with log-normal size distributions.

MISR experiment field observations calibration dat↗

Aircraft Particle Emissions eXperiment (APEX)

APEX systematically investigated the gas-phase and particle emissions from a CFM56-2C1 engine on NASA's DC-8 aircraft as functions of engine power, fuel composition, and exhaust plumage. Emissions parameters were measured at 11 engine power, settings, ranging from idle to maximum thrust, in samples collected at 1, 10, and 30 m downstream of the exhaust plane as the aircraft burned three fuels to stress relevant chemistry. Gas-phase emission indices measured at 1 m were in good agreement with the ICAO data and predictions provided by GEAE empirical modeling tools. Soot particles emitted by the engine exhibited a log-normal size distribution peaked between 15 and 40 nm, depending on engine power. Samples collected 30 m downstream of the engine exhaust plane exhibited a prominent nucleation mode.

Wey, C. C.↗

A comparative review of radiation aerosol models

Aerosol characteristics to be introduced into a set of models within a framework of a Standard Radiation Atmosphere (SRA) are reviewed, and a reconciliation of the Toon and Pollack (TP) global model with the SRA models is attempted. Among the topics discussed are physical and radiative characteristics, radiation aerosol models, albedo for single scattering, and phase function and spectral variation of extinction. Size distribution models are also covered, inclusive the Junge power law, and the modified gamma-, log normal-, and zold-distribution. Recommendations include modifying the SRA profile VI to resemble the Elterman profile modified in the TP model, improving discontinuity at the tropopause level for all SRA models, and retaining the same log-normal size distribution for all SRA components.

Lenoble, J.↗

A NEW STATISTICAL PERSPECTIVE TO THE COSMIC VOID DISTRIBUTION

In this study, we obtain the size distribution of voids as a three-parameter redshift-independent log-normal void probability function (VPF) directly from the Cosmic Void Catalog (CVC). Although many statistical models of void distributions are based on the counts in randomly placed cells, the log-normal VPF that we obtain here is independent of the shape of the voids due to the parameter-free void finder of the CVC. We use three void populations drawn from the CVC generated by the Halo Occupation Distribution (HOD) Mocks, which are tuned to three mock SDSS samples to investigate the void distribution statistically and to investigate the effects of the environments on the size distribution. As a result, it is shown that void size distributions obtained from the HOD Mock samples are satisfied by the three-parameter log-normal distribution. In addition, we find that there may be a relation between the hierarchical formation, skewness, and kurtosis of the log-normal distribution for each catalog. We also show that the shape of the three-parameter distribution from the samples is strikingly similar to the galaxy log-normal mass distribution obtained from numerical studies. This similarity between void size and galaxy mass distributions may possibly indicate evidence of nonlinear mechanisms affecting both voids and galaxies, such as large-scale accretion and tidal effects. Considering the fact that in this study, all voids are generated by galaxy mocks and show hierarchical structures in different levels, it may be possible that the same nonlinear mechanisms of mass distribution affect the void size distribution.

79 ASTRONOMY AND ASTROPHYSICS↗

A size-frequency study of large Martian craters

Martian craters in the size range 10-250 km follow a log-normal size-frequency distribution law. Analysis techniques based on the log-normal model yield possible evidence for the size-frequency evolution of crater-producing bodies. Some regions on Mars display excessive depletions of either large or small craters; the most likely causes of the depletions are considered. Apparently, eolian sedimentation has markedly altered the population of small craters south of -30 deg latitude. The general effects of crater obliteration in the Southern Hemisphere appear to be confined to diameters of less than 20 km. A strong depletion of large craters in a large region centered at 35 deg latitude and 10 deg W longitude may indicate locations of subsurface ice.

Woronow, A.↗

Distributions of the Mean for Lognormally Distributed Data - 19427

In environmental sciences, a distribution of the mean is often needed for right-skewed data. For example, risk assessments are often based on distributions of the mean to obtain upper confidence limits (UCLs) for analyte concentrations, and, in probabilistic performance assessment (PPA) models, parameters are given distributions rather than deterministic values, and they are usually given distributions of their mean rather than the population distributions to account for the large spatial and temporal domains to which they are applied. How this distribution of the mean is developed depends on the characteristics of the parameter's full distribution and how the parameter relates to its use. In this presentation, I will discuss the implications of a right skew in distribution development. Parameters may vary over orders of magnitude and/or may be right-skewed. The material property of saturated hydraulic conductivity, Ks, is a prime example of such a parameter. Right-skewed parameters are often assumed to follow lognormal distributions. If X follows a lognormal distribution, then log(X) follows a normal distribution. For some right-skewed parameters, practitioners go back and forth between the two forms of the data depending on their needs. For example, it may be preferred to use the untransformed version of X in a model or equation, but it is easier to visualize the parameter values on a logarithmic scale. However, distribution development for the average value of the parameter will differ depending on whether X or log(X) is modeled. This difference is due to Jensen's Inequality, a theorem which states that the expected value of a concave function of a variable is less than or equal to the same function of the expected value of the variable; a logarithm is a concave function. In other words, the mean of log(X) is always less than or equal to the log of the mean of X and therefore the mean estimated from a distribution based on log(X) is less than or equal to the mean estimated from a distribution based on X. If a parameter is naturally considered on a log scale by subject matter experts, then distributions developed for the mean of log(X) may be more consistent with the use of the parameters in the literature than distributions developed for X. The statistical decisions of distribution development will be discussed within the context of right-skewed, lognormal data. These issues include method-of-moments versus maximum likelihood estimation of the distribution parameters and the use of bootstrapping to aid in the visualization of a distribution of the mean. The details surrounding Jensen's Inequality will be explained and visualized within the context of distribution development of a right-skewed parameter such as saturated hydraulic conductivity. (authors)

54 ENVIRONMENTAL SCIENCES↗

Improving multiwell petrophysical interpretation from well logs via machine learning and statistical models

Well-log interpretation estimates in situ rock properties along well trajectory, such as porosity, water saturation, and permeability, to support reserve-volume estimation, production forecasts, and decision making in reservoir development. However, due to measurement errors, variability of well logs caused by multiple measurement vendors, different borehole tools, and nonuniform drilling/borehole conditions, estimations of rock properties with original well logs without proper preprocessing may not be accurate, especially in the context of multiwell estimation. Well-log normalization techniques such as two-point scaling and mean-variance normalization are commonly used to improve the robustness of multiwell rock-property estimation. However, these techniques do not consider the correlation between well logs and require subjective knowledge for their effective implementation. To reduce uncertainties and processing time associated with multiwell rock-property estimation from well logs, we develop discriminative adversarial (DA) and linear constraint models for well-log normalization and rock-property estimation. The DA neural network model developed for well-log normalization and interpretation can perform linear and nonlinear well-log normalization while considering the joint distribution of each well log and rock properties. However, the linear constraint model uses an ensemble of predictions from linear models to constrain well-log normalization and rock-property estimation. We also develop a divergence-based type well identification method to select type (training) wells for a test well based on the statistical similarity of associated well-log distributions instead of the interwell distance. We apply the DA model to perform well-log normalization and prediction of permeability for the Seminole San Andres Unit carbonate reservoir. Compared with the permeability predicted with the classical machine learning model without well-log normalization and models with two-point scaling normalization, the DA model yields the most accurate permeability prediction by decreasing the mean-squared error of permeability prediction by 20%–50%.

Geochemistry & Geophysics↗

Higher-order skewness and excess coefficients of some probability distributions applicable to optical propagation phenomena

Expressions are derived for higher-order skewness and excess coefficients using central moments and cumulants up to 8th order. These coefficients are then calculated for three probability distributions: (1) Log-normal, (2) Rice-Nakagami, and (3) Gamma distributions. Curves are given to shown the variation of skewness with excess coefficients for these distributions. These curves are independent of the particular distribution parameters. This method is useful for studying fluctuating phenomena, which obey non-Gaussian statistics.

Majumdar, A. K.↗

Quantifying the evidence for dark matter in CoGeNT data

We perform an independent analysis of data from the CoGeNT direct detection experiment to quantify the evidence for dark matter recoils. We critically re-examine the assumptions that enter the analysis, focusing specifically on the separation of bulk and surface events, the latter of which constitute a large background. This separation is performed using the event rise-time, with the surface events being slower on average. We fit the rise-time distributions for the bulk and surface events with a log-normal and Pareto distribution (which gives a better fit to the tail in the bulk population at high rise-times) and account for the energy-dependence of the bulk fraction using a cubic spline. Using Bayesian and frequentist techniques and additionally investigating the effect of varying the rise-time cut, the bulk background spectrum and bin-sizes, we conclude that the CoGeNT data show a preference for light dark matter recoils at less than 1σ.

79 ASTRONOMY AND ASTROPHYSICS↗

Property Improvement in CZT via Modeling and Processing Innovations . Te-particles in vertical gradient freeze CZT: Size and Spatial Distributions and Constitutional Supercooling

A section of a vertical gradient freeze CZT boule approximately 2100-mm 3 with a planar area of 300-mm 2 was prepared and examined using transmitted IR microscopy at various magnifications to determine the three-dimensional spatial and size distributions of Te-particles over large longitudinal and radial length scales. The boule section was approximately 50-mm wide by 60-mm in length by 7-mm thick and was doubly polished for TIR work. Te-particles were imaged through the thickness using extended focal imaging to locate the particles in thickness planes spaced 15-µm apart and then in plane of the image using xy-coordinates of the particle center of mass so that a true three dimensional particle map was assembled for a 1-mm by 45-mm longitudinal strip and for a 1-mm by 50-mm radial strip. Te-particle density distributions were determined as a function of longitudinal and radial positions in these strips, and treating the particles as vertices of a network created a 3D image of the particle spatial distribution. Te-particles exhibited a multi-modal log-normal size density distribution that indicated a slight preference for increasing size with longitudinal growth time, while showing a pronounced cellular network structure throughout the boule that can be correlated to dislocation network sizes in CZT. Higher magnification images revealed a typical Rayleigh-instability pearl string morphology with large and small satellite droplets. This study includes solidification experiments in small crucibles of 30:70 mixtures of Cd:Te to reduce the melting point below 1273 K (1000°C). These solidification experiments were performed over a wide range of cooling rates and clearly demonstrated a growth instability with Te-particle capture that is suggested to be responsible for one of the peaks in the size distribution using size discrimination visualization. The results are discussed with regard to a manifold Te-particle genesis history as 1) Te-particle direct capture from melt-solid growth instabilities, 2) Te-particle formation from dislocation core diffusion and the formation and breakup of Te-tubes, and 3) Te-particle formation due to classical nucleation and growth as precipitates.

36 MATERIALS SCIENCE↗

The effects of burial diagenesis on multiscale porosity in the St. Peter Sandstone: An imaging, small-angle, and ultra-small-angle neutron scattering analysis

To examine the effects of burial diagenesis on heirarchical pore structures in sandstone and compare those with the effects of overgrowth formation, we obtained samples of St. Peter Sandstone from drill cores obtained in the Illinois and Michigan Basins. The multiscale pore structure of rocks in sedimentary reservoirs and the mineralogy associated with those pores are critical factors for estimating reservoir properties, including fluid mass in place, permeability, and capillary pressures, as well as geochemical interactions between the rock and the fluid. The combination of small- and ultra-small-angle neutron scattering with backscattered electron or X ray-computed tomographic imaging, or both, provided a means by which pore structures were quantified at scales ranging from aproximately 1 nm to 1 cm—seven orders of magnitude. Larger scale (>10 µm) porosity showed the expected logarithmic decrease in porosity with depth, although there was significant variation in each sample group. However, small- and ultra-small-angle neutron scattering data showed that the proportion of small-scale porosity increased with depth. Porosity distributions were not continuous, but consisted of a series of log normal-like distributions at several distinct scales within these rocks. Fractal dimensions at larger scales decreased (surfaces smoothed) with increasing depth, and those at smaller scales increased (surfaces roughened) and pores become more isolated (higher lacunarity). Furthermore, data suggest that changes in pore-size distributions are controlled by both physical (compaction) and chemical effects (precipitation, cementation, dissolution).

58 GEOSCIENCES↗

Improved Algorithm to Estimate Convective and Stratiform Rain from TRMM Microwave Radiometer Data

The rain rates associated with Mesoscale Convective Systems (MCSS) deduced from the Tropical Rainfall Measuring Mission (TRMM) Precipitation Radar (PR) follow the well known log-normal type frequency distribution characteristic of conventional radars and rain gauges. On the other hand, the current microwave radiometer rain retrieval algorithms cannot give good representations of convective and stratiform precipitation. Thus they capture poorly this log-normal character. In particular, this is noticed clearly over land areas. The objective of the present study is to improve TRMM Microwave Imager (TMI) retrievals of convective and stratiform rain to a level comparable to the PR. For this purpose, we have developed a TMI rain retrieval algorithm that depends primarily on the 85 GHz brightness temperatures (Tbs) and their spatial distribution. We emphasize the 85 GHz channel because of its fine footprint size (about 5.5 km) and strong extinction property. The other spectral channels, because they are poorer in these respects, are given less importance. The brightness temperatures and spatial distribution information in the 85 GHz allows us to detect thunderstorms, or cumulonimbus clouds (Cbs), that are in different stages of development, as well as stratiform rain outside of these Cbs. Utilizing our retrieval technique, we have produced maps of convective and stratiform rain for several MCS events over land and ocean that agree well with those given by the PR. On average, the convective and stratiform rain rates given by our technique have an accuracy of about 15 % with respect to those given by the PR.

Prabhakara, C.↗

Probabilistic structural analysis of a truss typical for space station

A three-bay, space, cantilever truss is probabilistically evaluated using the computer code NESSUS (Numerical Evaluation of Stochastic Structures Under Stress) to identify and quantify the uncertainties and respective sensitivities associated with corresponding uncertainties in the primitive variables (structural, material, and loads parameters) that defines the truss. The distribution of each of these primitive variables is described in terms of one of several available distributions such as the Weibull, exponential, normal, log-normal, etc. The cumulative distribution function (CDF's) for the response functions considered and sensitivities associated with the primitive variables for given response are investigated. These sensitivities help in determining the dominating primitive variables for that response.

Pai, Shantaram S.↗