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At least 181 records · Page 10

Statistical Aspects of the North Atlantic Basin Tropical Cyclones: Trends, Natural Variability, and Global Warming

Statistical aspects of the North Atlantic basin tropical cyclones for the interval 1945- 2005 are examined, including the variation of the yearly frequency of occurrence for various subgroups of storms (all tropical cyclones, hurricanes, major hurricanes, U.S. landfalling hurricanes, and category 4/5 hurricanes); the yearly variation of the mean latitude and longitude (genesis location) of all tropical cyclones and hurricanes; and the yearly variation of the mean peak wind speeds, lowest pressures, and durations for all tropical cyclones, hurricanes, and major hurricanes. Also examined is the relationship between inferred trends found in the North Atlantic basin tropical cyclonic activity and natural variability and global warming, the latter described using surface air temperatures from the Armagh Observatory Armagh, Northern Ireland. Lastly, a simple statistical technique is employed to ascertain the expected level of North Atlantic basin tropical cyclonic activity for the upcoming 2007 season.

Wilson, Robert M.↗

Confidence set inference with a prior quadratic bound

In the uniqueness part of a geophysical inverse problem, the observer wants to predict all likely values of P unknown numerical properties z=(z sub 1,...,z sub p) of the earth from measurement of D other numerical properties y (sup 0) = (y (sub 1) (sup 0), ..., y (sub D (sup 0)), using full or partial knowledge of the statistical distribution of the random errors in y (sup 0). The data space Y containing y(sup 0) is D-dimensional, so when the model space X is infinite-dimensional the linear uniqueness problem usually is insoluble without prior information about the correct earth model x. If that information is a quadratic bound on x, Bayesian inference (BI) and stochastic inversion (SI) inject spurious structure into x, implied by neither the data nor the quadratic bound. Confidence set inference (CSI) provides an alternative inversion technique free of this objection. Confidence set inference is illustrated in the problem of estimating the geomagnetic field B at the core-mantle boundary (CMB) from components of B measured on or above the earth's surface.

Backus, George E.↗

Inferring Small Scale Dynamics from Aircraft Measurements of Tracers

The millions of ER-2 and DC-8 aircraft measurements of long-lived tracers in the Upper Troposphere/Lower Stratosphere (UT/LS) hold enormous potential as a source of statistical information about subgrid scale dynamics. Extracting this information however can be extremely difficult because the measurements are made along a 1-D transect through fields that are highly anisotropic in all three dimensions. Some of the challenges and limitations posed by both the instrumentation and platform are illustrated within the context of the problem of using the data to obtain an estimate of the dissipation scale. This presentation will also include some tutorial remarks about the conditional and two-point statistics used in the analysis.

Sparling, L. C.↗

Measurements of the cosmic background radiation

Maps of the large scale structure (theta is greater than 6 deg) of the cosmic background radiation covering 90 percent of the sky are now available. The data show a very strong 50-100 sigma (statistical error) dipole component, interpreted as being due to our motion, with a direction of alpha = 11.5 + or - 0.15 hours, sigma = -5.6 + or - 2.0 deg. The inferred direction of the velocity of our galaxy relative to the cosmic background radiation is alpha = 10.6 + or - 0.3 hours, sigma = -2.3 + or - 5 deg. This is 44 deg from the center of the Virgo cluster. After removing the dipole component, the data show a galactic signature but no apparent residual structure. An autocorrelation of the residual data, after substraction of the galactic component from a combined Berkeley (3 mm) and Princeton (12 mm) data sets, show no apparent structure from 10 to 180 deg with a rms of 0.01 mK(sup 2). At 90 percent confidence level limit of .00007 is placed on a quadrupole component.

Lubin, P.↗

Autoclass: An automatic classification system

The task of inferring a set of classes and class descriptions most likely to explain a given data set can be placed on a firm theoretical foundation using Bayesian statistics. Within this framework, and using various mathematical and algorithmic approximations, the AutoClass System searches for the most probable classifications, automatically choosing the number of classes and complexity of class descriptions. A simpler version of AutoClass has been applied to many large real data sets, has discovered new independently-verified phenomena, and has been released as a robust software package. Recent extensions allow attributes to be selectively correlated within particular classes, and allow classes to inherit, or share, model parameters through a class hierarchy. The mathematical foundations of AutoClass are summarized.

Stutz, John↗

Bayesian classification theory

The task of inferring a set of classes and class descriptions most likely to explain a given data set can be placed on a firm theoretical foundation using Bayesian statistics. Within this framework and using various mathematical and algorithmic approximations, the AutoClass system searches for the most probable classifications, automatically choosing the number of classes and complexity of class descriptions. A simpler version of AutoClass has been applied to many large real data sets, has discovered new independently-verified phenomena, and has been released as a robust software package. Recent extensions allow attributes to be selectively correlated within particular classes, and allow classes to inherit or share model parameters though a class hierarchy. We summarize the mathematical foundations of AutoClass.

Hanson, Robin↗

Radar-Based Bayesian Estimation of Ice Crystal Growth Parameters within a Microphysical Model

The potential for polarimetric Doppler radar measurements to improve predictions of ice microphysical processes within an idealized model–observational framework is examined. In an effort to more rigorously constrain ice growth processes (e.g., vapor deposition) with observations of natural clouds, a novel framework is developed to compare simulated and observed radar measurements, coupling a bulk adaptive-habit model of vapor growth to a polarimetric radar forward model. Bayesian inference on key microphysical model parameters is then used, via a Markov chain Monte Carlo sampler, to estimate the probability distribution of the model parameters. The statistical formalism of this method allows for robust estimates of the optimal parameter values, along with (non-Gaussian) estimates of their uncertainty. To demonstrate this framework, observations from Department of Energy radars in the Arctic during a case of pristine ice precipitation are used to constrain vapor deposition parameters in the adaptive habit model. The resulting parameter probability distributions provide physically plausible changes in ice particle density and aspect ratio during growth. A lack of direct constraint on the number concentration produces a range of possible mean particle sizes, with the mean size inversely correlated to number concentration. Consistency is found between the estimated inherent growth ratio and independent laboratory measurements, increasing confidence in the parameter PDFs and demonstrating the effectiveness of the radar measurements in constraining the parameters. The combined Doppler and polarimetric observations produce the highest-confidence estimates of the parameter PDFs, with the Doppler measurements providing a stronger constraint for this case.

Robert S. Schrom↗

Using Federated Learning to Overcome Data Gravity in Space

Humans intend to take longer missions to outer space. Understanding the impact that space has on human health is paramount to the success of these missions. Controlled experiments with model organisms are run to infer the impact of space conditions on human health, but the data these experiments generate are too large to transfer to Earth for building models. The same is true for space-relevant data generated on Earth. Ideally, these datasets should be combined to improve statistical power and model accuracy without having to transfer data. Federated learning is such a method which trains an algorithm across decentralized computing systems, each of which has their own local copy of training and testing data. In this research, made possible by NASA@Work, the AI for Life in Space group at NASA demonstrates the use of federated learning to train an ensemble of causality inference models on a combination of data residing on the International Space Station (ISS) and in the cloud. Our work leverages CRISP, a causal inference platform developed during the 2020 Frontier Development Lab’s “Astronaut Health Challenge.” We also leverage the OpenFL federated learning library which was collaboratively developed at Intel and UPenn. We used publicly available data from the NASA Ames Life Sciences Data Archive to identify features in ionizing radiation experiments as causal of changes in cardiac blood velocity. This research demonstrates, for the first time, the possibility of running machine learning algorithms on datasets separated by astronomical distances. In this experiment, all the data were generated in terra, half of which were transferred to the ISS and analyzed on the Spaceborne Computer. In the future, our research will leverage federated learning on data generated in situ on the ISS with data generated terrestrially to predict the impact of spaceflight on mammalian female reproductive capacity.

James Casaletto↗

Evaluation of a fault tolerant system for an integrated avionics sensor configuration with TSRV flight data

The performance analysis results of a fault inferring nonlinear detection system (FINDS) using sensor flight data for the NASA ATOPS B-737 aircraft in a Microwave Landing System (MLS) environment is presented. First, a statistical analysis of the flight recorded sensor data was made in order to determine the characteristics of sensor inaccuracies. Next, modifications were made to the detection and decision functions in the FINDS algorithm in order to improve false alarm and failure detection performance under real modelling errors present in the flight data. Finally, the failure detection and false alarm performance of the FINDS algorithm were analyzed by injecting bias failures into fourteen sensor outputs over six repetitive runs of the five minute flight data. In general, the detection speed, failure level estimation, and false alarm performance showed a marked improvement over the previously reported simulation runs. In agreement with earlier results, detection speed was faster for filter measurement sensors soon as MLS than for filter input sensors such as flight control accelerometers.

Caglayan, A. K.↗

Development of algorithms for understanding the temporal and spatial variability of the earth's radiation balance

A brief description is given of how temporal and spatial variability in the earth's radiative behavior influences the goals of satellite radiation monitoring systems and how some previous systems have addressed the existing problems. Then, results of some simulations of radiation budget monitoring missions are presented. These studies led to the design of the Earth Radiation Budget Experiment (ERBE). A description is given of the temporal and spatial averaging algorithms developed for the ERBE data analysis. These algorithms are intended primarily to produce monthly averages of the net radiant exitance on regional, zonal, and global scales and to provide insight into the regional diurnal variability of radiative parameters such as albedo and long-wave radiant exitance. The algorithms are applied to scanner and nonscanner data for up to three satellites. Modeling of dialy shortwave albedo and radiant exitance with satellite samling that is insufficient to fully account for changing meteorology is discussed in detail. Studies performed during the ERBE mission and software design are reviewed. These studies provide quantitative estimates of the effects of temporally sparse and biased sampling on inferred diurnal and regional radiative parameters. Other topics covered include long-wave diurnal modeling, extraction of a regional monthly net clear-sky radiation budget, the statistical significance of observed diurnal variability, quality control of the analysis, and proposals for validating the results of ERBE time and space averaging.

Brooks, D. R.↗

Decorrelation in interferometric radar echoes

A radar interferometric technique for topographic mapping of surfaces promises a high resolution, globally consistent approach to generation of digital elevation models. One implementation approach, that of utilizing a single SAR system in a nearly repeating orbit, is attractive not only for cost and complexity reasons but also in that it permits inference of changes in the surface over the orbit repeat cycle from the correlation properties of the radar echoes. The various sources contributing to the echo correlation statistics are characterized, and the term which most closely describes surficial change is isolated. There is decorrelation increasing with time, but digital terrain model generation remains feasible.

Zebker, Howard A.↗

Theoretical and experimental models of the diffuse radar backscatter from Mars

The general objective for this work was to develop a theoretically and experimentally consistent explanation for the diffuse component of radar backscatter from Mars. The strength, variability, and wavelength independence of Mars' diffuse backscatter are unique among our Moon and the terrestrial planets. This diffuse backscatter is generally attributed to wavelength-scale surface roughness and to rock clasts within the Martian regolith. Through the combination of theory and experiment, the authors attempted to bound the range of surface characteristics that could produce the observed diffuse backscatter. Through these bounds they gained a limited capability for data inversion. Within this umbrella, specific objectives were: (1) To better define the statistical roughness parameters of Mars' surface so that they are consistent with observed radar backscatter data, and with the physical and chemical characteristics of Mars' surface as inferred from Mariner 9, the Viking probes, and Earth-based spectroscopy; (2) To better understand the partitioning between surface and volume scattering in the Mars regolith; (3) To develop computational models of Mars' radio emission that incorporate frequency dependent, surface and volume scattering.

England, A. W.↗

Degradation of small mare surface features

Ring-moat structures are interpreted as remnants of flow topography associated with mare emplacement. Measurements of narrow moats characterizing these small mare features reveal a contradiction between their inferred preservation and the degree of surface degradation predicted by theoretical erosional models. Moat widths smaller than 50 m are recorded in areas where erosional models predict that walls of craters three to four times as large should be degraded to slopes of 1 deg. Crater statistics in such regions provide estimates of equilibrium conditions for impact crater formation that are consistent with the degree of preservation of the narrow moats. Although relative ages determined by observation of crater wall slopes near 20 deg, may be appropriate, it is concluded that current erosional models are not valid down to impact-degraded slopes of 1 deg. Relative age estimates based on the inferred degraded state of highly subdued craters are believed to be invalid, particularly for late Eratosthenian-age and Copernican-age mare units. In regions displaying ring-moat structures, highly subdued craters larger than the average moat widths are intepreted as either endogenic features associated with the emplacement of mare flow units or degraded secondary craters, which are typically subdued at the outset.

Schultz, P. H.↗

Rate of reaction between molecular hydrogen and molecular oxygen

The shock tube data of Jachimowski and Houghton were rigorously analyzed to obtain rate constants for the candidate initiation reactions H2 + O2 yields H + HO2, H2 + O2 yields H2O + O, and H2 + O2 yields OH + OH. Reaction (01) is probably not the initiation process because the activation energy obtained is less than the endothermicity and because the derived rates greatly exceed values inferred in the literature from the reverse of reaction (01). Reactions (02) and (03) remain as possibilities, with reaction (02) slightly favored on the basis of steric and statistical considerations. The solution of the differential equations is presented in detail to show how the kinetics of other ignition systems may be solved.

Brokaw, R. S.↗

Dynamics of the 4-day wave in the Southern Hemisphere polar stratosphere

Horizontal wind and temperature data are employed to investigate the dynamics of the 4-day wave in the Southern Hemisphere polar stratosphere. They were derived from synoptic maps of satellite-measured brightness temperatures, which were generated using the fast Fourier synoptic mapping technique of Salby (1982). Circulation statistics from these data are compared to those from the NMC operational stratospheric analyses, demonstrating improvements afforded by detailed treatment of asynoptic sampling effects. The 40-day wave is isolated using temporally filtered data. Several events of wave growth and decay are observed in the upper stratosphere during August 1980. Derived zonal-mean and eddy statistics suggest that the 4-day wave results from an instability of the zonal-mean flow near 55-60S, at and above 1 mb. It is inferred from climatological data that the source of the instability is the 'double-jet' structure in the upper stratosphere and mesosphere.

Randel, William J.↗

Effect of surface conductivity on the peak magnetic field radiated by first return strokes in cloud-to-ground lightning

The effect of surface conductivity on the peak magnetic field radiated by the first return stroke in cloud-to-ground lightning was investigated by comparing the peak magnetic fields from return strokes that struck water with those that struck land. The data were obtained from a network of three gated, wideband magnetic direction finders (DFs) at the NASA Kennedy Space Center during the summer of 1985. Two geographical areas that were equidistant from two of the direction finders were compared where the flash distances ranged from approximately 40 to 60 km. An unbiased data set was obtained by correcting site errors, equalizing differences in sensor gain, eliminating directional biases in DF triggering, and keeping differences in signal attenuation over the two surfaces to a minimum. When a statistical analysis was performed on the frequency distributions of the signal amplitudes, there was no statistically significant difference in the peak amplitudes of first return strokes over land (lambda = 8.2 x 10(exp -3) mho/m) and over water (lambda = 4 mho/m). Therefore we infer that the conductivity of the underlying surface does not significantly affect the magnitude of the peak magnetic field, and hence the peak current, in the first return stroke of a cloud-to-ground lightning flash.

Tyahla, Lori J.↗

Anticipating Cycle 24 Minimum and its Consequences: An Update

This Technical Publication updates estimates for cycle 24 minimum and discusses consequences associated with cycle 23 being a longer than average period cycle and cycle 24 having parametric minimum values smaller (or larger for the case of spotless days) than long term medians. Through December 2007, cycle 23 has persisted 140 mo from its 12-mo moving average (12-mma) minimum monthly mean sunspot number occurrence date (May 1996). Longer than average period cycles of the modern era (since cycle 12) have minimum-to-minimum periods of about 139.0+/-6.3 mo (the 90-percent prediction interval), inferring that cycle 24 s minimum monthly mean sunspot number should be expected before July 2008. The major consequence of this is that, unless cycle 24 is a statistical outlier (like cycle 21), its maximum amplitude (RM) likely will be smaller than previously forecast. If, however, in the course of its rise cycle 24 s 12-mma of the weighted mean latitude (L) of spot groups exceeds 24 deg, then one expects RM >131, and if its 12-mma of highest latitude (H) spot groups exceeds 38 deg, then one expects RM >127. High-latitude new cycle spot groups, while first reported in January 2008, have not, as yet, become the dominant form of spot groups. Minimum values in L and H were observed in mid 2007 and values are now slowly increasing, a precondition for the imminent onset of the new sunspot cycle.

Wilson, Robert M.↗

From Surface Chlorophyll a to Phytoplankton Community Composition in Oceanic Waters

The objective of the present study is to examine the potential of using the near-surface total chlorophyll a concentration (C(sub surf)), as it can be derived from ocean color observation, to infer the column-integrated and the vertical distribution of the phytoplanktonic biomass, both in a quantitative way and in a qualitative way (z.e., in terms of community structure). Within this context, a large HPLC (High Performance Liquid Chromatography) pigment database has been analyzed. It includes 2419 vertical pigment profiles, all sampled in Case-1 waters with various trophic states. The relationshps between C(sub surf) and the total chlorophyll alpha vertical distribution, as previously derived by Morel and Berthon, are fully confirmed, as the present results coincide with the previous ones. This agreement allows to go further, namely to examine the possibility of extracting relationships between C(sub surf) and the vertical composition of the algal assemblages. Thanks to the detailed pigment composition available from HPLC measurements, the contribution of three size classes (micro-, nano-, and pico-phytoplankton) to the local total chlorophyll a concentration can be assessed. Corroborating previous findings (e.g., large species dominate in eutrophc environments, whereas tiny phytoplankton prevail in oligotrophic zones), the results lead to a statistically based parameterization. The predictive skill of this parameterization is successfully tested on a separate data set. With such a tool, the vertical total chlorophyll a profiles associated with each size class can be inferred from the sole knowledge of C(sub surf). By combining this tool with satellite ocean color data, it becomes conceivable to quantify on a global scale the phytoplankton biomass associated with each of the three size classes.

Uitz, Julia↗