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NASA NTRS2002

Insights into Corona Formation through Statistical Analyses

Statistical analysis of an expanded database of coronae on Venus indicates that the populations of Type 1 (with fracture annuli) and 2 (without fracture annuli) corona diameters are statistically indistinguishable, and therefore we have no basis for assuming different formation mechanisms. Analysis of the topography and diameters of coronae shows that coronae that are depressions, rimmed depressions, and domes tend to be significantly smaller than those that are plateaus, rimmed plateaus, or domes with surrounding rims. This is consistent with the model of Smrekar and Stofan and inconsistent with predictions of the spreading drop model of Koch and Manga. The diameter range for domes, the initial stage of corona formation, provides a broad constraint on the buoyancy of corona-forming plumes. Coronae are only slightly more likely to be topographically raised than depressions, with Type 1 coronae most frequently occurring as rimmed depressions and Type 2 coronae most frequently occuring with flat interiors and raised rims. Most Type 1 coronae are located along chasmata systems or fracture belts, while Type 2 coronas are found predominantly as isolated features in the plains. Coronae at hotspot rises tend to be significantly larger than coronae in other settings, consistent with a hotter upper mantle at hotspot rises and their active state.

Glaze, L. S.↗

NASA NTRS2002

Statistical Analysis of CFD Solutions from the Drag Prediction Workshop

A simple, graphical framework is presented for robust statistical evaluation of results obtained from N-Version testing of a series of RANS CFD codes. The solutions were obtained by a variety of code developers and users for the June 2001 Drag Prediction Workshop sponsored by the AIAA Applied Aerodynamics Technical Committee. The aerodynamic configuration used for the computational tests is the DLR-F4 wing-body combination previously tested in several European wind tunnels and for which a previous N-Version test had been conducted. The statistical framework is used to evaluate code results for (1) a single cruise design point, (2) drag polars and (3) drag rise. The paper concludes with a discussion of the meaning of the results, especially with respect to predictability, Validation, and reporting of solutions.

Hemsch, Michael J.↗

NASA NTRS2003

Statistical Distribution of Inflation on Lava Flows: Analysis of Flow Surfaces on Earth and Mars

The surface morphology of a lava flow results from processes that take place during the emplacement of the flow. Certain types of features, such as tumuli, lava rises and lava rise pits, are indicators of flow inflation or endogenous growth of a lava flow. Tumuli in particular have been identified as possible indicators of tube location, indicating that their distribution on the surface of a lava flow is a junction of the internal pathways of lava present during flow emplacement. However, the distribution of tumuli on lava flows has not been examined in a statistically thorough manner. In order to more rigorously examine the distribution of tumuli on a lava flow, we examined a discrete flow lobe with numerous lava rises and tumuli on the 1969 - 1974 Mauna Ulu flow at Kilauea, Hawaii. The lobe is located in the distal portion of the flow below Holei Pali, which is characterized by hummocky pahoehoe flows emplaced from tubes. We chose this flow due to its discrete nature allowing complete mapping of surface morphologies, well-defined boundaries, well-constrained emplacement parameters, and known flow thicknesses. In addition, tube locations for this Mauna Ulu flow were mapped by Holcomb (1976) during flow emplacement. We also examine the distribution of tumuli on the distal portion of the hummocky Thrainsskjoldur flow field provided by Rossi and Gudmundsson (1996). Analysis of the Mauna Ulu and Thrainsskjoldur flow lobes and the availability of high-resolution MOC images motivated us to look for possible tumuli-dominated flow lobes on the surface of Mars. We identified a MOC image of a lava flow south of Elysium Mons with features morphologically similar to tumuli. The flow is characterized by raised elliptical to circular mounds, some with axial cracks, that are similar in size to the tumuli measured on Earth. One potential avenue of determining whether they are tumuli is to look at the spatial distribution to see if any patterns similar to those of tumuli-dominated terrestrial flows can be identified. Since tumuli form by the injection of lava beneath a crust, the distribution of tumuli on a flow should represent the distribution of thermally preferred pathways beneath the surface of the crust. That distribution of thermally preferred pathways may be a function of the evolution of a basaltic lava flow. As a longer-lived flow evolves, initially broad thermally preferred pathways would evolve to narrower, more well-defined tube-like pathways. The final flow morphology clearly preserves the growth of the flow over time, with inflation features indicating pathways that were not necessarily contemporaneously active. Here, we test using statistical analysis whether this final flow morphology produces distinct distributions that can be used to readily determine the distribution of thermally preferred pathways beneath the surface of the crust.

Glazel, L. S.↗

NASA NTRS2002

Insights into Corona Formation Through Statistical Analyses

Statistical analysis of an expanded database of coronae on Venus indicates that the populations of Type 1 (with fracture annuli) and 2 (without fracture annuli) corona diameters are statistically indistinguishable, and therefore we have no basis for assuming different formation mechanisms. Analysis of the topography and diameters of coronae shows that coronae that are depressions, rimmed depressions, and domes tend to be significantly smaller than those that are plateaus, rimmed plateaus, or domes with surrounding rims. This is consistent with the model of Smrekar and Stofan and inconsistent with predictions of the spreading drop model of Koch and Munga. The diameter range for domes, the initial stage of corona formation, provides a broad constraint on the buoyancy of corona-forming plumes. Coronae are only slightly more likely to be topographically raised than depressions, with Type 1 coronae most frequently occurring as rimmed depressions and Type 2 coronae most frequently occurring with flat interiors and raised rims. Most Type 1 coronae are located along chasmata systems or fracture belts, while Type 2 coronae are found predominantly as isolated features in the plains. Coronae at hot spot rises tend to be significantly lager than coronae in other settings, consistent with a hotter upper mantle at hot spot rises and their active state.

Glaze, L. S.↗

NASA NTRS2002

The Statistics of Visual Representation

The experience of retinex image processing has prompted us to reconsider fundamental aspects of imaging and image processing. Foremost is the idea that a good visual representation requires a non-linear transformation of the recorded (approximately linear) image data. Further, this transformation appears to converge on a specific distribution. Here we investigate the connection between numerical and visual phenomena. Specifically the questions explored are: (1) Is there a well-defined consistent statistical character associated with good visual representations? (2) Does there exist an ideal visual image? And (3) what are its statistical properties?

Jobson, Daniel J.↗

NASA NTRS2002

Estimation of Mesoscale Atmospheric Latent Heating Profiles from TRMM Rain Statistics Utilizing a Simple One-Dimensional Model

In this study, a model is developed to estimate mesoscale-resolution atmospheric latent heating (ALH) profiles. It utilizes rain statistics deduced from Tropical Rainfall Measuring Mission (TRMM) data, and cloud vertical velocity profiles and regional surface thermodynamic climatologies derived from other available data sources. From several rain events observed over tropical ocean and land, ALH profiles retrieved by this model in convective rain regions reveal strong warming throughout most of the troposphere, while in stratiform rain regions they usually show slight cooling below the freezing level and significant warming above. The mesoscale-average, or total, ALH profiles reveal a dominant stratiform character, because stratiform rain areas are usually much larger than convective rain areas. Sensitivity tests of the model show that total ALH at a given tropospheric level varies by less than +/- 10 % when convective and stratiform rain rates and mesoscale fractional rain areas are perturbed individually by +/- 15 %. This is also found when the non-uniform convective vertical velocity profiles are replaced by one that is uniform. Larger variability of the total ALH profiles arises when climatological ocean- and land-surface temperatures (water vapor mixing ratios) are independently perturbed by +/- 1.0 K (+/- 5%) and +/- 5.0 K (+/- 15%), respectively. At a given tropospheric level, such perturbations can cause a +/- 25% variation of total ALH over ocean, and a factor-of-two sensitivity over land. This sensitivity is reduced substantially if perturbations of surface thermodynamic variables do not change surface relative humidity, or are not extended throughout the entire model evaporation layer. The ALH profiles retrieved in this study agree qualitatively with tropical total diabatic heating profiles deduced in earlier studies. Also, from January and July 1999 ALH-profile climatologies generated separately with TRMM Microwave Imager and Precipitation Radar rain statistics, it is shown that ALH profiles can be retrieved utilizing diverse satellite-derived rain products that offer convective and stratiform discrimination. Therefore, the ALH retrieval model developed in this study can be used to make regional estimates of total diabatic heating profiles in the future Global Precipitation Measurement mission, and to assimilate these profiles into numerical weather forecast and climate models.

Iacovazzi, Robert A., Jr.↗

NASA NTRS2002

A New Statistically based Autoconversion rate Parameterization for use in Large-Scale Models

The autoconversion rate is a key process for the formation of precipitation in warm clouds. In climate models, physical processes such as autoconversion rate, which are calculated from grid mean values, are biased, because they do not take subgrid variability into account. Recently, statistical cloud schemes have been introduced in large-scale models to account for partially cloud-covered grid boxes. However, these schemes do not include the in-cloud variability in their parameterizations. In this paper, a new statistically based autoconversion rate considering the in-cloud variability is introduced and tested in three cases using the Canadian Single Column Model (SCM) of the global climate model. The results show that the new autoconversion rate improves the model simulation, especially in terms of liquid water path in all three case studies.

Lin, Bing↗

NASA NTRS2004

A Numerical Simulation and Statistical Modeling of High Intensity Radiated Fields Experiment Data

Tests are conducted on a quad-redundant fault tolerant flight control computer to establish upset characteristics of an avionics system in an electromagnetic field. A numerical simulation and statistical model are described in this work to analyze the open loop experiment data collected in the reverberation chamber at NASA LaRC as a part of an effort to examine the effects of electromagnetic interference on fly-by-wire aircraft control systems. By comparing thousands of simulation and model outputs, the models that best describe the data are first identified and then a systematic statistical analysis is performed on the data. All of these efforts are combined which culminate in an extrapolation of values that are in turn used to support previous efforts used in evaluating the data.

Smith, Laura J.↗

NASA NTRS2002

Classification image analysis: estimation and statistical inference for two-alternative forced-choice experiments

We consider estimation and statistical hypothesis testing on classification images obtained from the two-alternative forced-choice experimental paradigm. We begin with a probabilistic model of task performance for simple forced-choice detection and discrimination tasks. Particular attention is paid to general linear filter models because these models lead to a direct interpretation of the classification image as an estimate of the filter weights. We then describe an estimation procedure for obtaining classification images from observer data. A number of statistical tests are presented for testing various hypotheses from classification images based on some more compact set of features derived from them. As an example of how the methods we describe can be used, we present a case study investigating detection of a Gaussian bump profile.

Non-NASA Center↗

NASA NTRS2004

The Impact of Subsampling on MODIS Level-3 Statistics of Cloud Optical Thickness and Effective Radius

The MODIS Level-3 optical thickness and effective radius cloud product is a gridded l deg. x 1 deg. dataset that is derived from aggregation and subsampling at 5 km of 1 km, resolution Level-2 orbital swath data (Level-2 granules). This study examines the impact of the 5 km subsampling on the mean, standard deviation and inhomogeneity parameter statistics of optical thickness and effective radius. The methodology is simple and consists of estimating mean errors for a large collection of Terra and Aqua Level-2 granules by taking the difference of the statistics at the original and subsampled resolutions. It is shown that the Level-3 sampling does not affect the various quantities investigated to the same degree, with second order moments suffering greater subsampling errors, as expected. Mean errors drop dramatically when averages over a sufficient number of regions (e.g., monthly and/or latitudinal averages) are taken, pointing to a dominance of errors that are of random nature. When histograms built from subsampled data with the same binning rules as in the Level-3 dataset are used to reconstruct the quantities of interest, the mean errors do not deteriorate significantly. The results in this paper provide guidance to users of MODIS Level-3 optical thickness and effective radius cloud products on the range of errors due to subsampling they should expect and perhaps account for, in scientific work with this dataset. In general, subsampling errors should not be a serious concern when moderate temporal and/or spatial averaging is performed.

Oreopoulos, Lazaros↗

NASA NTRS1992

The statistical analysis of circadian phase and amplitude in constant-routine core-temperature data

Accurate estimation of the phases and amplitude of the endogenous circadian pacemaker from constant-routine core-temperature series is crucial for making inferences about the properties of the human biological clock from data collected under this protocol. This paper presents a set of statistical methods based on a harmonic-regression-plus-correlated-noise model for estimating the phases and the amplitude of the endogenous circadian pacemaker from constant-routine core-temperature data. The methods include a Bayesian Monte Carlo procedure for computing the uncertainty in these circadian functions. We illustrate the techniques with a detailed study of a single subject's core-temperature series and describe their relationship to other statistical methods for circadian data analysis. In our laboratory, these methods have been successfully used to analyze more than 300 constant routines and provide a highly reliable means of extracting phase and amplitude information from core-temperature data.

NASA Discipline Regulatory Physiology↗

NASA NTRS2005

Information Theory - The Bridge Connecting Bounded Rational Game Theory and Statistical Physics

A long-running difficulty with conventional game theory has been how to modify it to accommodate the bounded rationality of all red-world players. A recurring issue in statistical physics is how best to approximate joint probability distributions with decoupled (and therefore far more tractable) distributions. This paper shows that the same information theoretic mathematical structure, known as Product Distribution (PD) theory, addresses both issues. In this, PD theory not only provides a principle formulation of bounded rationality and a set of new types of mean field theory in statistical physics; it also shows that those topics are fundamentally one and the same.

Wolpert, David H.↗

NASA NTRS2005

Comparison of Grammar-Based and Statistical Language Models Trained on the Same Data

This paper presents a methodologically sound comparison of the performance of grammar-based (GLM) and statistical-based (SLM) recognizer architectures using data from the Clarissa procedure navigator domain. The Regulus open source packages make this possible with a method for constructing a grammar-based language model by training on a corpus. We construct grammar-based and statistical language models from the same corpus for comparison, and find that the grammar-based language models provide better performance in this domain. The best SLM version has a semantic error rate of 9.6%, while the best GLM version has an error rate of 6.0%. Part of this advantage is accounted for by the superior WER and Sentence Error Rate (SER) of the GLM (WER 7.42% versus 6.27%, and SER 12.41% versus 9.79%). The rest is most likely accounted for by the fact that the GLM architecture is able to use logical-form-based features, which permit tighter integration of recognition and semantic interpretation.

Hockey, Beth Ann↗

NASA NTRS2005

Statistical Calibration and Validation of a Homogeneous Ventilated Wall-Interference Correction Method for the National Transonic Facility

Wind tunnel experiments will continue to be a primary source of validation data for many types of mathematical and computational models in the aerospace industry. The increased emphasis on accuracy of data acquired from these facilities requires understanding of the uncertainty of not only the measurement data but also any correction applied to the data. One of the largest and most critical corrections made to these data is due to wall interference. In an effort to understand the accuracy and suitability of these corrections, a statistical validation process for wall interference correction methods has been developed. This process is based on the use of independent cases which, after correction, are expected to produce the same result. Comparison of these independent cases with respect to the uncertainty in the correction process establishes a domain of applicability based on the capability of the method to provide reasonable corrections with respect to customer accuracy requirements. The statistical validation method was applied to the version of the Transonic Wall Interference Correction System (TWICS) recently implemented in the National Transonic Facility at NASA Langley Research Center. The TWICS code generates corrections for solid and slotted wall interference in the model pitch plane based on boundary pressure measurements. Before validation could be performed on this method, it was necessary to calibrate the ventilated wall boundary condition parameters. Discrimination comparisons are used to determine the most representative of three linear boundary condition models which have historically been used to represent longitudinally slotted test section walls. Of the three linear boundary condition models implemented for ventilated walls, the general slotted wall model was the most representative of the data. The TWICS code using the calibrated general slotted wall model was found to be valid to within the process uncertainty for test section Mach numbers less than or equal to 0.60. The scatter among the mean corrected results of the bodies of revolution validation cases was within one count of drag on a typical transport aircraft configuration for Mach numbers at or below 0.80 and two counts of drag for Mach numbers at or below 0.90.

Walker, Eric Lee↗

NASA NTRS2005

Statistical Considerations of Data Processing in Giovanni Online Tool

The GES DISC Interactive Online Visualization and Analysis Infrastructure (Giovanni) is a web-based interface for the rapid visualization and analysis of gridded data from a number of remote sensing instruments. The GES DISC currently employs several Giovanni instances to analyze various products, such as Ocean-Giovanni for ocean products from SeaWiFS and MODIS-Aqua; TOMS & OM1 Giovanni for atmospheric chemical trace gases from TOMS and OMI, and MOVAS for aerosols from MODIS, etc. (http://giovanni.gsfc.nasa.gov) Foremost among the Giovanni statistical functions is data averaging. Two aspects of this function are addressed here. The first deals with the accuracy of averaging gridded mapped products vs. averaging from the ungridded Level 2 data. Some mapped products contain mean values only; others contain additional statistics, such as number of pixels (NP) for each grid, standard deviation, etc. Since NP varies spatially and temporally, averaging with or without weighting by NP will be different. In this paper, we address differences of various weighting algorithms for some datasets utilized in Giovanni. The second aspect is related to different averaging methods affecting data quality and interpretation for data with non-normal distribution. The present study demonstrates results of different spatial averaging methods using gridded SeaWiFS Level 3 mapped monthly chlorophyll a data. Spatial averages were calculated using three different methods: arithmetic mean (AVG), geometric mean (GEO), and maximum likelihood estimator (MLE). Biogeochemical data, such as chlorophyll a, are usually considered to have a log-normal distribution. The study determined that differences between methods tend to increase with increasing size of a selected coastal area, with no significant differences in most open oceans. The GEO method consistently produces values lower than AVG and MLE. The AVG method produces values larger than MLE in some cases, but smaller in other cases. Further studies indicated that significant differences between AVG and MLE methods occurred in coastal areas where data have large spatial variations and a log-bimodal distribution instead of log-normal distribution.

Suhung, Shen↗

NASA NTRS2005

Statistical Calibration and Validation of a Homogeneous Ventilated Wall-Interference Correction Method for the National Transonic Facility

Walker, Eric L.↗

NASA NTRS2006

Statistical of a Characterization and the Simulation of a Reverberation Chamber Using Finite-Element Techniques

The statistical characterization of a simulation reverberation chamber is performed by considering a two-dimensional finite element model. This model includes a source to study the particular modal fields that couple into either a transverse electric or transverse magnetic configuration. The analysis includes a characterization of the basic field statistics, max-to-average ratio, normalized standard deviation, stirring ratio, and field uniformity. The shielding effectiveness of an aperture will be studied that will provide some insight into the nature of the fields coupled from a complex to a noncomplex environment.

Bunting, Charles F.↗

NASA NTRS2006

Field Penetration in a Rectangular Box Using Numerical Techniques: An Effort to Obtain Statistical Shielding Effectiveness

This paper emphasizes the application of numerical methods to explore the ideas related to shielding effectiveness from a statistical view. An empty rectangular box is examined using a hybrid modal/moment method. The basic computational method is presented followed by the results for single- and multiple observation points within the over-moded empty structure. The statistics of the field are obtained by using frequency stirring, borrowed from the ideas connected with reverberation chamber techniques, and extends the ideas of shielding effectiveness well into the multiple resonance regions. The study presented in this paper will address the average shielding effectiveness over a broad spatial sample within the enclosure as the frequency is varied.

Bunting, Charles F.↗