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All sourcesNASA NTRSDOE OSTI
NASA NTRS1987

Comparison of remote measurements of infrared surface temperatures and microwave soil moisture

Scatterometric measurements of active microwave soil water content and radiometric measurements of thermal IR surface temperatures were made simultaneously fron an aircraft flying 400 m over an agricultural region of France after harvesting. The surface temperatures were used to deterine soil moisture availability estimates according to the Carlson (1986) model. Surface temperature or soil moisture availability and microwave soil moisture were correlated. The standard error in the IR temperature and soil moisture availability due to influences other than soil moisture is found to be + or - 2 C. The standard deviation of the temperature/moisture availability is greater than this standard error. It is shown that correlations between soil water content and moisture availability improve with increasing spatial or temporal variance in the measure surface temperatures.

Perry, Eileen M.↗
DOE OSTI2016

Impact of hydrogen bonding on dynamics of hydroxyl-terminated polydimethylsiloxane

Dielectric spectroscopy, rheology, and differential scanning calorimetry were employed to study the effect of chain-end hydrogen bonding on the dynamics of hydroxylterminated polydimethylsiloxane. We demonstrate that hydrogen bonding has a strong influence on both segmental and slower dynamics in the systems with low molecular weights. In particular, the decrease in the chain length leads to an increase of the glass transition temperature, viscosity, and fragility index, at variance with the usual behavior of nonassociating polymers. The supramolecular association of hydroxylterminated chains leads to the emergence in dielectric and mechanical relaxation spectra of the so-called Debye process traditionally observed in monohydroxy alcohols. Our analysis suggests that the hydroxyl-terminated PDMS oligomers may associate in brush-like or chain-like structures, depending on the size of their covalent chains. Finally, the effective length of the linear-associated chains was estimated from the rheological measurements.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Analyzing Wildland Fire Smoke Emissions Data Using Compositional Data Techniques

By conservation of mass, the mass of wildland fuel that is pyrolyzed and combusted must equal the mass of smoke emissions, residual char and ash. For a given set of conditions, these amounts are fixed. This places a constraint on smoke emissions data which violates statistical assumptions for many of the methods currently used to analyze these data such as linear regression, analysis of variance, and t-tests. These data are inherently multivariate and non-negative parts of a whole. This paper introduces the field of compositional data analysis to the emissions community and provides examples of appropriate statistical treatment of emissions data. It is shown that modified combustion efficiency should not be used as a predictor variable for other smoke emissions because it is not an independent variable. An alternative method based on compositional linear trends to estimate trace gas composition using CO and CO2 is presented. The data used in this paper resulted from projects the DOD/DOE/EPA Strategic 586 Environmental Research and Development Program projects RC-1648 and 1649. The senior 587 author appreciates the guidance and R scripts provided by Prof. Girty at San Diego State 588 University to estimate linear trends by perturbation. J. P.-A. was supported by the Spanish 589 Ministry of Science, Innovation and Universities under the project CODAMET (RTI2018-590 095518-B-C21, 2019-2021). The data used in this study have been previously published and are 591 available in the original publications. DRW conceived the initial manuscript (70 percent) and 592 performed the bulk of the data analysis. JPA provided statistical guidance and compositional data 593 expertise and contributed 20 percent of the manuscript. TJJ and HJ were extensively involved in 594 the study that provided the data. TJJ provide smoke emissions expertise and HJ provided 595 combustion expertise. The authors declare that they have no conflict of interest. The use of trade 596 or firm names in this publication is for reader information and does not imply endorsement by 597 the U.S. Department of Agriculture of any product or service.

simplex, compositional data analysis, balance, log↗
DOE OSTI2023

(U) A General-Purpose Code for Correlated Sampling Using Batch Statistics with MCNP6 for Fixed-Source Problems

Correlated sampling can be used to reduce the uncertainty of a difference of tallies by taking advantage of the negative covariance term in the sandwich formula. Booth first showed how correlated sampling can be applied with batch statistics using MCNP’s tally fluctuation chart (TFC) to reduce the uncertainty of a difference of tallies in fixed-source problems. Booth presented a problem in which a 1273% uncertainty in a difference was reduced to 8% by accounting for correlations. Researchers He and Su recently studied correlated sampling using the TFC in MCNP version 5. They determined that the code did not print enough digits in the TFC tally means for accurate batch statistics in some cases. After modifying the source code, they concluded that “correlated sampling can yield a standard deviation of about one magnitude smaller than that predicted by the direct, un-correlated simulation when the changes in system response are small (say about 1%), which is equivalent to saving in CPU time by a factor of 100. Such saving [sic] becomes less significant as the change in system response becomes larger.” He and Su provided the formulas needed to apply batch statistics to compute the correlated uncertainty of a difference of tallies. In this report, we follow up on their work by providing the formulas needed to apply batch statistics to compute the correlated uncertainty of a ratio of tallies and of a difference of two tallies divided by a third tally. We extend these formulas to differences and ratios of ratios. These formulas are applied to reduce the uncertainty associated with calculating a relative sensitivity. He and Su did not investigate the accuracy of their correlated sampling uncertainty estimates. We use their test problems and evaluate the accuracy of the uncertainty estimates by comparing with results obtained from random sampling, and, in simple cases, with theoretical values of the “exact” uncertainties. We find that the uncertainties obtained from batch statistics are accurate as long as at least 100 batches are used. We present a new computer code, COSUBS (COrrelated Sampling Using Batch Statistics), that reads MCNP6 TFCs and applies correlated sampling using batch statistics for the tally combinations that the user specifies. COSUBS is a very general tool that compares all TFCs for a base case and one or two perturbed cases. It computes uncertainties for ratios if given only a base case. This report is organized as follows. The equations to apply batch statistics to the difference of random tallies are reviewed in Sec. II. Section III presents the equations for applying batch statistics to a ratio of random tallies; this is useful for computing relative sensitivities using a one-sided finite difference and the relative sensitivity using the differential operator method. Section IV presents the equations for applying batch statistics to a difference of two random tallies divided by a third; this is useful for computing a relative sensitivities using a central difference. Section V presents the equations for applying batch statistics to a difference of two ratios with four random tallies. Section VI presents the equations for applying batch statistics to a one-sided finite difference estimate of the relative sensitivity of a ratio (this uses four random tallies). Section VII presents the equations for applying batch statistics to a central difference estimate of the relative sensitivity of a ratio (this uses six random tallies). Section VIII presents the equations for applying batch statistics to a sum of random tallies. Section IX discusses how to apply batch statistics using MCNP6. Section X presents COSUBS, describing its command-line options and logic. Sections XI through XVI present numerical results for various test problems. Section XVII is a summary and conclusions. Appendix A derives the theoretical Monte Carlo tally variance given certain assumptions; these variances are used to verify the batch statistics for some of the problems. Appendix B lists the MCNP6 input for the unperturbed example problem. Appendix C presents modifications made to MCNP6.3 to support this work.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2015

Source mechanism analysis of central Aceh earthquake July 2, 2013 Mw 6.2 using moment tensor inversion with BMKG waveform data

The source mechanism of earthquake on July 2, 2013 was investigated by using moment tensor inversion. The result also compared by the field observation. Five waveform data of BMKG’s seismic network used to estimate the mechanism of earthquake, namely ; KCSI, MLSI, LASI, TPTI and SNSI. Main shock data taken during 200 seconds and filtered by using Butterworth band pass method from 0.03 to 0.05 Hz of frequency. Moment tensor inversion method is applied based on the point source assumption. Furthermore, the Green function calculated using the extended reflectivity method which modified by Kohketsu. The inversion result showed a strike-slip faulting, where the nodal plane strike/dip/rake (124/80.6/152.8) and minimum variance value 0.3285 at a depth of 6 km (centroid). It categorized as a shallow earthquake. Field observation indicated that the building orientated to the east. It can be related to the southwest of dip direction which has 152 degrees of slip. As conclusion, the Pressure (P) and Tension (T) axis described dominant compression is happen from the south which is caused by pressure of the Indo-Australian plate.

58 GEOSCIENCES↗
NASA NTRS2004

Employing Sensitivity Derivatives to Estimate Uncertainty Propagation in CFD

Two methods that exploit the availability of sensitivity derivatives are successfully employed to predict uncertainty propagation through Computational Fluid Dynamics (CFD) code for an inviscid airfoil problem. An approximate statistical second-moment method and a Sensitivity Derivative Enhanced Monte Carlo (SDEMC) method are successfully demonstrated on a two-dimensional problem. First- and second-order sensitivity derivatives of code output with respect to code input are obtained through an efficient incremental iterative approach. Given uncertainties in statistically independent, random, normally distributed flow parameters (input variables); these sensitivity derivatives enable one to formulate first- and second-order Taylor Series approximations for the mean and variance of CFD output quantities. Additionally, incorporation of the first-order sensitivity derivatives into the data reduction phase of a conventional Monte Carlo (MC) simulation allows for improved accuracy in determining the first moment of the CFD output. Both methods are compared to results generated using a conventional MC method. The methods that exploit the availability of sensitivity derivatives are found to be valid when considering small deviations from input mean values.

Putko, Michele M.↗
DOE OSTI2013

Sources of Technical Variability in Quantitative LC-MS Proteomics: Human Brain Tissue Sample Analysis.

To design a robust quantitative proteomics study, an understanding of both the inherent heterogeneity of the biological samples being studied as well as the technical variability of the proteomics methods and platform is needed. Additionally, accurately identifying the technical steps associated with the largest variability would provide valuable information for the improvement and design of future processing pipelines. We present an experimental strategy that allows for a detailed examination of the variability of the quantitative LC-MS proteomics measurements. By replicating analyses at different stages of processing, various technical components can be estimated and their individual contribution to technical variability can be dissected. This design can be easily adapted to other quantitative proteomics pipelines. Herein, we applied this methodology to our label-free workflow for the processing of human brain tissue. For this application, the pipeline was divided into four critical components: Tissue dissection and homogenization (extraction), protein denaturation followed by trypsin digestion and SPE clean-up (digestion), short-term run-to-run instrumental response fluctuation (instrumental variance), and long-term drift of the quantitative response of the LC-MS/MS platform over the 2 week period of continuous analysis (instrumental stability). From this analysis, we found the following contributions to variability: extraction (72%) >> instrumental variance (16%) > instrumental stability (8.4%) > digestion (3.1%). Furthermore, the stability of the platform and its’ suitability for discovery proteomics studies is demonstrated.

Environmental Molecular Sciences Laboratory↗
DOE OSTI2014

Sensitivity Analysis and Data Assimilation in a Subcritical Plutonium Metal Benchmark

Here, this work presents the application of first-order adjoint sensitivity analysis, uncertainty quantification, and data assimilation to a subcritical plutonium benchmark experiment using a modified version of the discrete ordinates radiation transport code Denovo. Previous Monte Carlo simulations of this benchmark saw a consistent overprediction of the mean and variance of the measured neutron multiplicity distribution. It was observed that a small scalar reduction in the value of the 239 Pu-induced fission neutron multiplicity was capable of significantly reducing the discrepancies. This work extends those results by computing first-order sensitivities to each nuclide, reaction type, energy, and material region in the benchmark. The sensitivities are then used in a data assimilationmethodology to simultaneously calibrate all responses and multigroup nuclear data. The resulting best-estimate values for the energy group differential multiplicity $\bar{v}$(E g ) are 1σ to 2σ less than the nominal values found in ENDF/B-VII for energies less than 1.5 MeV.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2025

Air temperature and precipitation constraining the modelled wetland methane emissions in a boreal region in northern Europe

Wetland methane responses to temperature and precipitation are studied in a boreal wetland-rich region in northern Europe using ecosystem process models. Six ecosystem models (JSBACH-HIMMELI, LPX-Bern, LPJ-GUESS, JULES, CLM4.5, and CLM5) are compared to multi-model means of ecosystem models and atmospheric inversions from the Global Carbon Project and upscaled eddy covariance flux results for their temperature and precipitation responses and seasonal cycles of the regional fluxes. Two models with contrasting response patterns, LPX-Bern and JSBACH-HIMMELI, are used as priors in atmospheric inversions with Carbon Tracker Europe–CH4 (CTE-CH4) in order to find out how the assimilation of atmospheric concentration data changes the flux estimates and how this alters the interpretation of the flux responses to temperature and precipitation. Inversion moves wetland emissions of both models towards co-limitation by temperature and precipitation. Between 2000 and 2018, periods of high temperature and/or high precipitation often resulted in increased emissions. However, the dry summer of 2018 did not result in increased emissions despite the high temperatures. The process models show strong temperature and strong precipitation responses for the region (51 %–91 % of the variance explained by both). The month with the highest emissions varies from May to September among the models. However, multi-model means, inversions, and upscaled eddy covariance flux observations agree on the month of maximum emissions and are co-limited by temperature and precipitation. The setup of different emission components (peatland emissions, mineral land fluxes) has an important role in building up the response patterns. Considering the significant differences among the models, it is essential to pay more attention to the regional representation of wet and dry mineral soils and periodic flooding which contribute to the seasonality and magnitude of methane fluxes. The realistic representation of temperature dependence of the peat soil fluxes is also important. Furthermore, it is important to use process-based descriptions for both mineral and peat soil fluxes to simulate the flux responses to climate drivers.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2015

Scaling impacts on environmental controls and spatial heterogeneity of soil organic carbon stocks

The spatial heterogeneity of land surfaces affects energy, moisture, and greenhouse gas exchanges with the atmosphere. However, representing the heterogeneity of terrestrial hydrological and biogeochemical processes in Earth system models (ESMs) remains a critical scientific challenge. We report the impact of spatial scaling on environmental controls, spatial structure, and statistical properties of soil organic carbon (SOC) stocks across the US state of Alaska. We used soil profile observations and environmental factors such as topography, climate, land cover types, and surficial geology to predict the SOC stocks at a 50 m spatial scale. These spatially heterogeneous estimates provide a data set with reasonable fidelity to the observations at a sufficiently high resolution to examine the environmental controls on the spatial structure of SOC stocks. We upscaled both the predicted SOC stocks and environmental variables from finer to coarser spatial scales ( s = 100, 200, and 500 m and 1, 2, 5, and 10 km) and generated various statistical properties of SOC stock estimates. We found different environmental factors to be statistically significant predictors at different spatial scales. Only elevation, temperature, potential evapotranspiration, and scrub land cover types were significant predictors at all scales. The strengths of control (the median value of geographically weighted regression coefficients) of these four environmental variables on SOC stocks decreased with increasing scale and were accurately represented using mathematical functions ( R 2 = 0.83–0.97). The spatial structure of SOC stocks across Alaska changed with spatial scale. Although the variance (sill) and unstructured variability (nugget) of the calculated variograms of SOC stocks decreased exponentially with scale, the correlation length (range) remained relatively constant across scale. The variance of predicted SOC stocks decreased with spatial scale over the range of 50 m to ~ 500 m, and remained constant beyond this scale. The fitted exponential function accounted for 98 % of variability in the variance of SOC stocks. We found moderately accurate linear relationships between mean and higher-order moments of predicted SOC stocks ( R 2 ∼ 0.55–0.63). Current ESMs operate at coarse spatial scales (50–100 km), and are therefore unable to represent environmental controllers and spatial heterogeneity of high-latitude SOC stocks consistent with observations. We conclude that improved understanding of the scaling behavior of environmental controls and statistical properties of SOC stocks could improve ESM land model benchmarking and perhaps allow representation of spatial heterogeneity of biogeochemistry at scales finer than those currently resolved by ESMs.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2015

Scaling impacts on environmental controls and spatial heterogeneity of soil organic carbon stocks

The spatial heterogeneity of land surfaces affects energy, moisture, and greenhouse gas exchanges with the atmosphere. However, representing heterogeneity of terrestrial hydrological and biogeochemical processes in earth system models (ESMs) remains a critical scientific challenge. We report the impact of spatial scaling on environmental controls, spatial structure, and statistical properties of soil organic carbon (SOC) stocks across the US state of Alaska. We used soil profile observations and environmental factors such as topography, climate, land cover types, and surficial geology to predict the SOC stocks at a 50 m spatial scale. These spatially heterogeneous estimates provide a dataset with reasonable fidelity to the observations at a sufficiently high resolution to examine the environmental controls on the spatial structure of SOC stocks. We upscaled both the predicted SOC stocks and environmental variables from finer to coarser spatial scales ( s = 100, 200, 500 m, 1, 2, 5, 10 km) and generated various statistical properties of SOC stock estimates. We found different environmental factors to be statistically significant predictors at different spatial scales. Only elevation, temperature, potential evapotranspiration, and scrub land cover types were significant predictors at all scales. The strengths of control (the median value of geographically weighted regression coefficients) of these four environmental variables on SOC stocks decreased with increasing scale and were accurately represented using mathematical functions ( R 2 = 0.83–0.97). The spatial structure of SOC stocks across Alaska changed with spatial scale. Although the variance (sill) and unstructured variability (nugget) of the calculated variograms of SOC stocks decreased exponentially with scale, the correlation length (range) remained relatively constant across scale. The variance of predicted SOC stocks decreased with spatial scale over the range of 50 to ~ 500 m, and remained constant beyond this scale. The fitted exponential function accounted for 98% of variability in the variance of SOC stocks. We found moderately-accurate linear relationships between mean and higher-order moments of predicted SOC stocks ( R 2 ~ 0.55–0.63). Current ESMs operate at coarse spatial scales (50–100 km), and are therefore unable to represent environmental controllers and spatial heterogeneity of high-latitude SOC stocks consistent with observations. We conclude that improved understanding of the scaling behavior of environmental controls and statistical properties of SOC stocks can improve ESM land model benchmarking and perhaps allow representation of spatial heterogeneity of biogeochemistry at scales finer than those currently resolved by ESMs.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2019

Cs-137 Body-burdens in Wild Pigs on the Department of Energy's Savannah River Site: Determination of an Appropriate Framework for Spatiotemporal Analysis of Hunter Dose Tracking System Data

The Savannah River Site (SRS) is a U.S. Department of Energy facility with an area of 310 square miles. Since its opening in 1951, SRS has produced and processed nuclear materials for national defense and industrial purposes. These activities have resulted in the release of radiocesium (Cs-137) which has led to contamination of associated streams, floodplains, man-made reservoirs, soil and vegetation. Contamination is spread to wild pigs as they move about SRS, consume vegetation, drink water and wallow in soil. SRS provides annual deer hunts open to the public in which wild pigs may be taken as well. The Cs-137 concentration of each animal is determined before it is released to the hunter for consumption and a cumulative dose is retained for each individual hunter. These tasks are accomplished using the Hunter Dose Tracking System (HDTS). The data collected on SRS by the HDTS for White-Tailed deer has been extensively analyzed. A repeatable method for calculating the background radiocesium body burden for the SRS deer population was established by Gaines and Novak (2009,2016). This model was framed using Cs-137 contamination obtained via gamma over-flight data, the decay rate of radiocesium and the historical behavior observed in the SRS deer population. These parameters were used in a spatiotemporal analysis to estimate background Cs-137 body burdens (from global fallout, etc.), as well as the effect SRS activities may have. The purpose of this project is to modify the framework to represent the behavior of the wild pig population on SRS such that HDTS data collected may be analyzed similarly. The 2018 data were collected via the HDTS in the field to screen wild pigs dispatched by Forest Service - Savannah River. These data will provide insight for an analysis of seasonal variance in the body burdens of the SRS wild pig population. The HDTS quickly provided Cs-137 concentrations in the field, as well as automatically updated the electronic database. Space: Historically, the average home range of wild pigs on the Savannah River Site has been reported at approximately six square miles. This range was confirmed accurate as of July 2018, with the observed minimum and maximum at one and ten square miles respectively. This range was geoprocessed using ArcMap to project buffers based on 1991 gamma over-flight data. The buffers were constructed to originate at all Cs-137 contamination point coordinates and protrude outward in all directions for 1.5, 2.45 and 6 square miles. While the 2.45 mile buffer is theoretically representative of potential hog exposure based on the average home range, it does not consider the possibility of home ranges not uniform in shape. Therefore, the 1.5 and 6 mile buffers were also constructed as visual aids for determining the appropriate hunt compartments for background level considerations. The SRS is divided into numbered hunt compartments of varying size and shape. These compartment numbers are used during sponsored hunts to record the location in which a wild pig was dispatched. Time: The Gaines report determined deer analysis should be carried out at the half-decade level for the best representation of true body burdens. This is due to the impact natural factors, such as drought or flood, can have on the bioaccumulation of Cs-137. To determine the appropriate time scale for hog analysis, all available data was totaled and averaged at 1, 2, 3 and 7 year increments. The annual averages and running average are provided. The appropriate compartments for the determination of the SRS hog population background level should be: 2, 3, 4, 9, 10, 14 and 15. Hogs dispatched within other compartments are most likely exposed to Cs-137 contamination and should not be included in the background level. The current dataset is small, but was still able to demonstrate the relationship between where hogs on SRS and the Cs-137 body burdens they incur. Geoprocessing the data using the average home range of wild pigs highlighted the importance of collecting additional samples from areas surrounding SRS if an accurate background is to be determined. When the average concentration of Cs-137 in pigs from background compartments is compared against that of pigs from contaminated compartments, a significant difference can be seen. A Table provides a summary of the analyzed data from the 15 years processed thus far.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2012

Disaggregating measurement uncertainty from population variability and Bayesian treatment of uncensored results

In making low-level radioactivity measurements of populations, it is commonly observed that a substantial portion of net results are negative. Furthermore, the observed variance of the measurement results arises from a combination of measurement uncertainty and population variability. This paper presents a method for disaggregating measurement uncertainty from population variability to produce a probability density function (PDF) of possibly true results. To do this, simple, justifiable, and reasonable assumptions are made about the relationship of the measurements to the measurands (the 'true values'). The measurements are assumed to be unbiased, that is, that their average value is the average of the measurands. Using traditional estimates of each measurement's uncertainty to disaggregate population variability from measurement uncertainty, a PDF of measurands for the population is produced. Then, using Bayes's theorem, the same assumptions, and all the data from the population of individuals, a prior PDF is computed for each individual's measurand. These PDFs are non-negative, and their average is equal to the average of the measurement results for the population. The uncertainty in these Bayesian posterior PDFs is all Berkson with no remaining classical component. The methods are applied to baseline bioassay data from the Hanford site. The data include 90Sr urinalysis measurements on 128 people, 137Cs in vivo measurements on 5,337 people, and 239Pu urinalysis measurements on 3,270 people. The method produces excellent results for the 90Sr and 137Cs measurements, since there are nonzero concentrations of these global fallout radionuclides in people who have not been occupationally exposed. The method does not work for the 239Pu measurements in non-occupationally exposed people because the population average is essentially zero.

61 RADIATION PROTECTION AND DOSIMETRY↗
DOE OSTI2022

Understanding the Drivers of Atlantic Multidecadal Variability using a Stochastic Model Hierarchy

The relative importance of ocean and atmospheric dynamics in generating Atlantic Multidecadal Variability (AMV) remains an open question. Comparisons between climate models with SLAB and fully-dynamic (FULL) ocean components are often used to explore this question, but cannot reveal how individual ocean processes generate these differences. We build a hierarchy of physically interpretable stochastic models to investigate the contribution of two upper-ocean processes to AMV: the role of seasonal variation and mixed-layer entrainment. This interpretability arises from the stochastic model’s simplified representation of sea surface temperature (SST), considering only the local upper ocean response to white-noise atmospheric forcing and its impact on surface heat exchange. We focus on understanding differences between SLAB and FULL non-eddy resolving pre-industrial control simulations of the Community Earth System Model 1 (CESM), and estimate the stochastic model parameters from each respective simulation. Despite its simplicity, the stochastic model reproduces temporal characteristics of SST variability in the SPG, including reemergence, seasonal-to-interannual persistence and power spectra. Furthermore, unrealistically persistent SST of the CESM-SLAB ocean simulation is reproduced in the equivalent stochastic model configuration where the mixed-layer depth (MLD) is constant. The stochastic model also reveals that vertical entrainment primarily damps SST variability, thus explaining why SLAB exhibits larger SST variance than FULL. Here, the stochastic model driven by temporally stochastic, spatially coherent forcing patterns reproduces the canonical AMV pattern. However, the amplitude of low-frequency variability remains underestimated, suggesting a role for ocean dynamics beyond entrainment.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1976

Some new results on the statistics of radio wave scintillation. I - Empirical evidence for Gaussian statistics

This paper presents an analysis of ionospheric scintillation data which shows that the underlying statistical structure of the signal can be accurately modeled by the additive complex Gaussian perturbation predicted by the Born approximation in conjunction with an application of the central limit theorem. By making use of this fact, it is possible to estimate the in-phase, phase quadrature, and cophased scattered power by curve fitting to measured intensity histograms. By using this procedure, it is found that typically more than 80% of the scattered power is in phase quadrature with the undeviated signal component. Thus, the signal is modeled by a Gaussian, but highly non-Rician process. From simultaneous UHF and VHF data, only a weak dependence of this statistical structure on changes in the Fresnel radius is deduced. The signal variance is found to have a nonquadratic wavelength dependence. It is hypothesized that this latter effect is a subtle manifestation of locally homogeneous irregularity structures, a mathematical model proposed by Kolmogorov (1941) in his early studies of incompressible fluid turbulence.

Rino, C. L.↗
NASA NTRS2001

Continued Investigations of the Accretion History of Extraterrestrial Matter over Geologic Time

This grant supported our ongoing project to characterize the accretion rate of interplanetary dust particles (IDPs) to Earth over geologic time using He-3 as a tracer. IDPs are derived from collisions in the asteroid belt and from disaggregation of active comets. Owing to their small size (few to few hundred micrometers diameter) these particles spiral into the sun under Poynting-Robertson drag typically in less than a few tens of kyrs. Thus IDPs must be continually resupplied to the zodiacal cloud, and because the processes of IDP production are likely to be sporadic, time variation in the IDP accretion rate to Earth is likely to be time-varying. For example, major asteroidal collisions and comet showers should greatly enhance the IDP accretion rate. Our ultimate objective (still ongoing) is to document this time variance so as to better understand the history of the solar system, the source of IDPs accreting to Earth, and the details of the mechanism by which particles are captured by Earth. To document variations in IDP accretion rate through time we use He-3 as a tracer. This isotope is in extremely low abundance in terrestrial matter, but IDPs have very high concentrations of He-3 from implantation of solar wind ions. By measuring He-3 in seafloor sediments, we can estimate the IDP accretion rate for at least the last few hundred Myrs. Under an earlier NASA grant we identified the existence of a large increase in He-3 flux in the Late Eocene (35 Myr ago), coincident with the two largest impact craters of the Cenozoic Era. The simplest interpretation of this observation is the occurrence of a shower of long period comets at that time, simultaneously increasing the impact cratering probability and accretion rate of IDPs to Earth (Farley et al., 1998). Comet showers produced by stellar perturbation of the Oort cloud should be fairly common in the geologic record, so this is not an unreasonable interpretation of our observations.

Farley, Kenneth↗
NASA NTRS2005

Ross sea ice motion, area flux, and deformation

The sea ice motion, area export, and deformation of the Ross Sea ice cover are examined with satellite passive microwave and RADARSAT observations. The record of high-resolution synthetic aperture radar (SAR) data, from 1998 and 2000, allows the estimation of the variability of ice deformation at the small scale (10 km) and to assess the quality of the longer record of passive microwave ice motion. Daily and subdaily deformation fields and RADARSAT imagery highlight the variability of motion and deformation in the Ross Sea. With the passive microwave ice motion, the area export at a flux gate positioned between Cape Adare and Land Bay is estimated. Between 1992 and 2003, a positive trend can be seen in the winter (March-November) ice area flux that has a mean of 990 x 103 km2 and ranges from a low of 600 x 103 km2 in 1992 to a peak of 1600 x 103 km2 in 2001. In the mean, the southern Ross Sea produces almost twice its own area of sea ice during the winter. Cross-gate sea level pressure (SLP) gradients explain 60% of the variance in the ice area flux. A positive trend in this gradient, from reanalysis products, suggests a 'spinup' of the Ross Sea Gyre over the past 12 yr. In both the NCEP-NCAR and ERA-40 surface pressure fields, longer-term trends in this gradient and mean SLP between 1979 and 2002 are explored along with positive anomalies in the monthly cross-gate SLP gradient associated with the positive phase of the Southern Hemisphere annular mode and the extrapolar Southern Oscillation.

Ross Sea↗
NASA NTRS2009

A Method for Retrieving Ground Flash Fraction from Satellite Lightning Imager Data

A general theory for retrieving the fraction of ground flashes in N lightning observed by a satellite-based lightning imager is provided. An "exponential model" is applied as a physically reasonable constraint to describe the measured optical parameter distributions, and population statistics (i.e., mean, variance) are invoked to add additional constraints to the retrieval process. The retrieval itself is expressed in terms of a Bayesian inference, and the Maximum A Posteriori (MAP) solution is obtained. The approach is tested by performing simulated retrievals, and retrieval error statistics are provided. The ability to retrieve ground flash fraction has important benefits to the atmospheric chemistry community. For example, using the method to partition the existing satellite global lightning climatology into separate ground and cloud flash climatologies will improve estimates of lightning nitrogen oxides (NOx) production; this in turn will improve both regional air quality and global chemistry/climate model predictions.

Koshak, William J.↗