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Ionospheric and Birkeland current distributions inferred from the MAGSAT magnetometer data

Ionospheric and field-aligned sheet current density distributions are presently inferred by means of MAGSAT vector magnetometer data, together with an accurate magnetic field model. By comparing Hall current densities inferred from the MAGSAT data and those inferred from simultaneously recorded ground based data acquired by the Scandinavian magnetometer array, it is determined that the former have previously been underestimated due to high damping of magnetic variations with high spatial wave numbers between the ionosphere and the MAGSAT orbit. Among important results of this study is noted the fact that the Birkeland and electrojet current systems are colocated. The analyses have shown a tendency for triangular rather than constant electrojet current distributions as a function of latitude, consistent with the statistical, uniform regions 1 and 2 Birkeland current patterns.

Zanetti, L. J.↗

Surface Units on Venus Derived from Pioneer-venus Altimetry, Roughness, and Reflectivity Measurements

The nature of the Venusian surface was revealed by Pioneer-Venus (PV) observations to be diverse at scales from tens to hundreds of kilometers. Spatial correlations of elevation, surface roughness, and radar reflectivity were investigated as a means of assessing the degree of homogeneity of surface radar properties within topographic provinces and develop a map of possible geologic boundaries. Correlations were performed in a supervised fashion whereby unit boundaries were selected on the basis of statistical and empirical studies of the individual data sets. Interpretations of these units in terms of geologic characteristics are based on the determination of physical units which are model dependent.

Peterfreund, A. R.↗

Interpretation of F106B and CV580 in-flight lightning data and form factor determination

Two topics of in-flight aircraft/lightning interaction are addressed. The first is the analysis of measured data from the NASA F106B Thunderstorm Research Aircraft and the CV580 research program run by the FAA and Wright-Patterson Air Force Base. The CV580 data was investigated in a mostly qualitative sense, while the F106B data was subjected to both statistical and quantitative analysis using linear triggered lightning finite difference models. The second main topic is the analysis of field mill data and the calibration of the field mill systems. The calibration of the F106B field mill system was investigated using an improved finite difference model of the aircraft having a spatial resolution of one-quarter meter. The calibration was applied to measured field mill data acquired during the 1985 thunderstorm season. The experimental determination of form factors useful for field mill calibration was also investigated both experimentally and analytically. The experimental effort involved the use of conducting scale models and an electrolytic tank. An analytic technique was developed to aid in the understanding of the experimental results.

Rudolph, T.↗

Cross-Sensor Validation of the Optical Transient Detector (OTD)

Lightning data from the U.S. National Lightning Detection Network (NLDN) is used to perform preliminary validation of the satellite-based Optical Transient Detector (OTD). Sensor precision, accuracy, detection efficiency and biases of the deployed instrument are considered. We estimate the sensor to have, on average, better than 30 km spatial and 100 ms temporal accuracy. The detection efficiency for cloud-to-ground lightning is about 45-70%, slightly higher for intracloud lightning. There are only marginal day/night biases in the dataset, although 55 day averaging is required to remove sampling-based diurnal lightning cycle biases. The sensor detects statistically significant differences in the optical characteristics of intracloud, negative cloud-to-ground and positive cloud-to-ground lightning, although it cannot a priori determine flash types.

Boccippio, D. J.↗

Global Partitioning of NOx Sources Using Satellite Observations: Relative Roles of Fossil Fuel Combustion, Biomass Burning and Soil Emissions

This document contains the following abstract for the paper "Global partitioning of NOx sources using satellite observations: Relative roles of fossil fuel combustion, biomass burning and soil emissions." Satellite observations have been used to provide important new information about emissions of nitrogen oxides. Nitrogen oxides (NOx) are significant in atmospheric chemistry, having a role in ozone air pollution, acid deposition and climate change. We know that human activities have led to a three- to six-fold increase in NOx emissions since pre-industrial times, and that there are three main surface sources of NOx: fuel combustion, large-scale fires, and microbial soil processes. How each of these sources contributes to the total NOx emissions is subject to some doubt, however. The problem is that current NOx emission inventories rely on bottom-up approaches, compiling large quantities of statistical information from diverse sources such as fuel and land use, agricultural data, and estimates of burned areas. This results in inherently large uncertainties. To overcome this, Lyatt Jaegle and colleagues from the University of Washington, USA, used new satellite observations from the Global Ozone Monitoring Experiment (GOME) instrument. As the spatial and seasonal distribution of each of the sources of NOx can be clearly mapped from space, the team could provide independent topdown constraints on the individual strengths of NOx sources, and thus help resolve discrepancies in existing inventories. Jaegle's analysis of the satellite observations, presented at the recent Faraday Discussion on "Atmospheric Chemistry", shows that fuel combustion dominates emissions at northern mid-latitudes, while fires are a significant source in the Tropics. Additionally, she discovered a larger than expected role for soil emissions, especially over agricultural regions with heavy fertilizer use. Additional information is included in the original extended abstract.

Jaegle, Lyatt↗

Automated Identification and Differentiation of Spectrally Similar Hydrothermal Minerals on Mars

Early telescopic observations corroborated hydration related absorptions on Mars in the infrared. Images from the Viking missions led to speculation of hydrothermal alteration and were followed by two missions which mapped the spatial variability of the ~ 3 μm hydration feature. Since then, the Compact Reconnaissance Imager for Mars (CRISM) has provided high spatial resolution (up to 18m) spectral identification of a suite of hydrothermal and diagenetic minerals which have illuminated a range of formation mechanisms. Presence/absence and spatial segregation or mixing of minerals like prehnite, epidote, chlorite amphiboles, and mixed-layer Fe/Mg smectite-chlorite provide valuable evidence for the geologic setting of deposits on Earth, and these phases are often used as temperature and aqueous chemistry indicators in terrestrial systems. Mapping the distribution of these phases will help to answer whether Mars had widespread conditions favorable for low-grade metamorphism and diagenesis, or only focused hydrothermal systems in areas of high heat flow. Further characterizing the chemistry and structure of these phases will then help to answer how most of the widespread Fe/Mg phyllosilicates formed, further defining early geochemical cycling and climate. A fully automated approach for accurate mapping of important hydrothermal mineral phases on Mars has been a challenge. Due to overlapping features in the M-OH region (~2.2-2.4 μm), the strongest absorption features of chlorite, prehnite, and epidote in the short-wave infrared are difficult to distinguish from one another and from the most commonly occurring hydrated silicates on Mars, Fe/Mg smectites. Weaker absorptions are present in both prehnite and epidote which help to distinguish them from chlorite and smectites, but their relative strength in the presence of noise and spatial mixing is often too low to confidently identify them without the noise suppression and feature enhancement methods described here. The spectral signatures of mixed-layer Fe/Mg smectite-chlorite and partially chloritized Fe/Mg smectites have not yet been adequately assessed. Here we evaluate the effectiveness of two empirical and statistical methods for identifying and differentiating these phases using CRISM data.

Rasmussen, B. P.↗

A Hydrodynamic Theory for Spatially Inhomogeneous Semiconductor Lasers: Numerical Results - 2

We present numerical results of the diffusion coefficients (DCs) in the coupled diffusion model derived in the preceding paper for a semiconductor quantum well. These include self and mutual DCs in the general two-component case, as well as density- and temperature-related DCs under the single-component approximation. The results are analyzed from the viewpoint of free Fermi gas theory with many-body effects incorporated. We discuss in detail the dependence of these DCs on densities and temperatures in order to identify different roles played by the free carrier contributions including carrier statistics and carrier-LO phonon scattering, and many-body corrections including bandgap renormalization and electron-hole (e-h) scattering. In the general two-component case, it is found that the self- and mutual- diffusion coefficients are determined mainly by the free carrier contributions, but with significant many-body corrections near the critical density. Carrier-LO phonon scattering is dominant at low density, but e-h scattering becomes important in determining their density dependence above the critical electron density. In the single-component case, it is found that many-body effects suppress the density coefficients but enhance the temperature coefficients. The modification is of the order of 10% and reaches a maximum of over 20% for the density coefficients. Overall, temperature elevation enhances the diffusive capability or DCs of carriers linearly, and such an enhancement grows with density. Finally, the complete dataset of various DCs as functions of carrier densities and temperatures provides necessary ingredients for future applications of the model to various spatially inhomogeneous optoelectronic devices.

Li, Jianzhong↗

Understanding the Impacts of Soil Moisture Initial Conditions on NWP in the Context of Land-Atmosphere Coupling

The role of soil moisture in NWP has gained more attention in recent years, as studies have demonstrated impacts of land surface states on ambient weather from diurnal to seasonal scales. However, soil moisture initialization approaches in coupled models remain quite diverse in terms of their complexity and observational roots, while assessment using bulk forecast statistics can be simplistic and misleading. In this study, a suite of soil moisture initialization approaches is used to generate short-term coupled forecasts over the U.S. Southern Great Plains using NASA’s Land Information System (LIS) and NASA Unified WRF (NU-WRF) modeling systems. This includes a wide range of currently used initialization approaches, including soil moisture derived from ‘off-the-shelf’ products such as atmospheric models and land data assimilation systems, high-resolution land surface model spinups, and satellite-based soil moisture products from SMAP. Results indicate that the spread across initialization approaches can be quite large in terms of soil moisture conditions and spatial resolution, and that SMAP performs well in terms of heterogeneity and temporal dynamics when compared against high resolution land surface model and in-situ soil moisture estimates. Case studies are analyzed using the local land-atmosphere coupling (LoCo) framework that relies on integrated assessment of soil moisture, surface flux, boundary layer, and ambient weather, with results highlighting the critical role of inherent model background biases. In addition, simultaneous assessment of land vs. atmospheric initial conditions in an integrated, process-level fashion can help address the question of whether improvements in traditional NWP verification statistics are achieved for the right reasons.

Southern Great Plains↗

A New Lunar Globe as Seen by the Moon Mineralogy Mapper: Image Coverage Spectral Dimensionality and Statistical Anomalies

The Moon Mineralogy Mapper (M3), a NASA Discovery Mission of Opportunity, was launched October 22, 2008 from Shriharikota in India on board the Indian ISRO Chandrayaan- 1 spacecraft for a nominal two-year mission in a 100-km polar lunar orbit. M3 is a high-fidelity imaging spectrometer with 260 spectral bands in Target Mode and 85 spectral bands in a reduced-resolution Global Mode. Target Mode pixel sizes are nominally 70 meters and Global pixels (binned 2 by 2) are 140 meters, from the planned 100-km orbit. The mission was cut short, just before halfway, in August, 2009 when the spacecraft ceased operations. Despite the abbreviated mission and numerous technical and scientific challenges during the flight, M3 was able to cover more than 95% of the Moon in Global Mode. These data, presented and analyzed here as a global whole, are revolutionizing our understanding of the Moon. Already, numerous discoveries relating to volatiles and unexpected mineralogy have been published [1], [2], [3]. The rich spectral and spatial information content of the M3 data indicates that many more discoveries and an improved understanding of the mineralogy, geology, photometry, thermal regime and volatile status of our nearest neighbor are forthcoming from these data. Sadly, only minimal high-resolution Target Mode images were acquired, as these were to be the focus of the second half of the mission. This abstract gives the reader a global overview of all the M3 data that were collected and an introduction to their rich spectral character and complexity. We employ a Principal Components statistical method to assess the underlying dimensionality of the Moon as a whole, as seen by M3, and to identify numerous areas that are low-probability targets and thus of potential interest to selenologists.

Boardman, J. W.↗

Direct numerical simulation of hypersonic turbulent boundary layers: effect of spatial evolution and Reynolds number

Direct numerical simulations (DNS) are performed to investigate the spatial evolution of flat-plate zero-pressure-gradient turbulent boundary layers over long streamwise domains ( >300δ i , with δ i the inflow boundary-layer thickness) at three different Mach numbers, 2.5, 4.9 and 10.9, with the surface temperatures ranging from quasiadiabatic to highly cooled conditions. The settlement of turbulence statistics into a fully developed equilibrium state of the turbulent boundary layer has been carefully monitored, either based on the satisfaction of the von Kármán integral equation or by comparing runs with different inflow turbulence generation techniques. The generated DNS database is used to characterize the streamwise evolution of multiple important variables in the high-Mach-number, cold-wall regime, including the skin friction, the Reynolds analogy factor, the shape factor, the Reynolds stresses, and the fluctuating wall quantities. The data confirm the validity of many classic and newer compressibility transformations at moderately high Reynolds numbers (up to friction Reynolds number Re τ ≈1200 ) and show that, with proper scaling, the sizes of the near-wall streaks and superstructures are insensitive to the Mach number and wall cooling conditions. The strong wall cooling in the hypersonic cold-wall case is found to cause a significant increase in the size of the near-wall turbulence eddies (relative to the boundary-layer thickness), which leads to a reduced-scale separation between the large and small turbulence scales, and in turn to a lack of an outer peak in the spanwise spectra of the streamwise velocity in the logarithmic region.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Impact of Extreme Heat on Emergency Department Admissions for Childhood and Adult Asthma: An Evaluation of Earth Observations and Heat Wave Definitions

Extreme heat has been associated with adverse health outcomes, yet its impact on asthma exacerbations remains understudied. This is, in part, due to data limitations: research that relies on weather station records and aggregated health statistics cannot resolve fine-scale differences in heat impacts. This study investigates the association between heat wave definitions and summertime asthma-related emergency department visits in Baltimore, Maryland from 2016 to 2022, including 819 adult and 695 pediatric exacerbations. Using geocoded electronic health records and air temperature measurements at several spatial resolutions, we applied a case-crossover design with conditional logistic regressions at the census block group and tract levels. We found strong associations between asthma exacerbations and nighttime heat wave definitions based on relative thresholds of minimum temperatures when census block group or tract level temperature estimates were used. These relationships were significant for both age groups and showed elevated risks in socially vulnerable areas. In contrast, heat wave definitions derived from the city's primary National Weather Service synoptic weather station show associations between asthma and daytime heat extremes, suggesting that the character of the heat hazard depends on the scale at which it is defined. The extreme heat event definition used by Baltimore City's Code Red system showed no significant association with exacerbations. These findings highlight the importance of data resolution in shaping health inferences related to extreme heat in urban environments. Further, this study demonstrates that, regardless of spatial scale, extreme heat is associated with asthma exacerbations in both age groups.

Corpuz, B. [Johns Hopkins University, Baltimore, M↗

Stress and Strain Heterogeneity and Persistence in Uniaxially‐ and Triaxially‐Loaded Sandstone

Two critical questions in brittle rock mechanics are how rocks developed localized strains and to what extent internal stress heterogeneity controls this localization and subsequent macroscopic failure. Definitive answers have not yet been found, but would provide insight into rock fracture mechanics as relevant to hydrocarbon extraction and sequestration. Here, we use synchrotron X‐ray tomography (XRT) and 3D X‐ray diffraction (3DXRD) during uniaxial and triaxial tests on Nugget and Bentheimer sandstones to examine strain and stress localization prior to mechanical failure. 3DXRD was used to measure intra‐granular lattice strains which were used to compute elastic stress tensors of each grain. Digital volume correlation (DVC) was applied to XRT images to determine the strain field in the sample. Both samples featured marked spatial heterogeneity, localization, and temporal persistence of elevated stresses and strains during their mechanical deformation toward failure. Both samples featured a majority of grains with at least one principal stress component that was tensile, a signature of the influence of heterogeneity on stress transmission. Measurements further revealed that compressive stress orientations and statistics evolved in a similar manner to those of inter‐particle forces in loose granular materials, with triaxially‐compressed rock exhibiting enhanced grain stress heterogeneity compared to uniaxially‐compressed rock. Our results complement recent work by others who employed XRT and scanning 3DXRD to study triaxially‐compressed sandstone, but extend those results to uniaxial compression, sandstones of varied porosity, and grain stress measurements throughout the 3D full extent of the samples rather than in a single layer examined with scanning 3DXRD.

58 GEOSCIENCES↗

Intricate short-range order in GeSn alloys revealed by atomistic simulations with highly accurate and efficient machine-learning potentials

GeSn alloys hold promise for silicon-compatible integrated applications in electronics, photonics, and topological quantum devices. However, understanding their intricate structures using density functional theory (DFT) calculations is hindered by spatiotemporal constraints. To overcome this limitation, we develop highly accurate and efficient machine-learning interatomic potentials based on a neuroevolution potential approach with farthest point sampling on a comprehensive DFT data set. The application of the developed machine-learning potential in large-scale atomistic simulations bridges the spatiotemporal gap between modeling and advanced characterizations, and facilitates the discovery of structural intricacies in GeSn alloys. Through extensive statistical sampling, we identify a type of short-range order (SRO) that is distinguished by both its structural signature and electronic band gap from the SRO structure previously predicted. Modeling based on a large simulation cell reveals the coexistence of nano SRO domains with various degrees of ordering, demonstrating a complex spatial heterogeneity of SRO structure. Finally, our study not only reinforces the significance of fine-level structural information in alloys, but it also constitutes an effective framework for exploring SRO in a broad range of complex alloys based on highly accurate and effective machine-learning potentials.

36 MATERIALS SCIENCE↗

Fiber Uncertainty Visualization for Bivariate Data With Parametric and Nonparametric Noise Models

Visualization and analysis of multivariate data and their uncertainty are top research challenges in data visualization. Constructing fiber surfaces is a popular technique for multivariate data visualization that generalizes the idea of level-set visualization for univariate data to multivariate data. Here, in this paper, we present a statistical framework to quantify positional probabilities of fibers extracted from uncertain bivariate fields. Specifically, we extend the state-of-the-art Gaussian models of uncertainty for bivariate data to other parametric distributions (e.g., uniform and Epanechnikov) and more general nonparametric probability distributions (e.g., histograms and kernel density estimation) and derive corresponding spatial probabilities of fibers. In our proposed framework, we leverage Green's theorem for closed-form computation of fiber probabilities when bivariate data are assumed to have independent parametric and nonparametric noise. Additionally, we present a nonparametric approach combined with numerical integration to study the positional probability of fibers when bivariate data are assumed to have correlated noise. For uncertainty analysis, we visualize the derived probability volumes for fibers via volume rendering and extracting level sets based on probability thresholds. We present the utility of our proposed techniques via experiments on synthetic and simulation datasets.

97 MATHEMATICS AND COMPUTING↗

Steady-state mixing state of black carbon aerosols from a particle-resolved model

Abstract. Black carbon (BC) exerts a notable warming effect due to its strong light absorption, largely influenced by its “mixing state”. However, due to computational constraints, the mixing state is challenging to accurately represent in large-scale models. In this study, we employ a particle-resolved model to simulate the evolution of BC mixing state based on field observation. Our result shows that aerosol compositions, coating thickness (CT) distribution, and optical properties of BC aerosols all exhibit a tendency toward a steady state with a characteristic timescale of less than 1 d, considerably shorter than the BC atmospheric lifetime. The rapid attainment of a steady state suggests that it is reasonable to disregard this pre-steady-state period and instead concentrate on the average properties of BC across extensive spatial and temporal scales. The distribution of CT follows an exponential linear distribution and can be characterized by a single slope parameter k. This distribution is independent of the BC core's distribution. In the model simulation, the mean CT, equivalent to the 1/k, is 62 nm, which is consistent with the statistical results indicating a mean CT of 63 nm. Utilizing the slope parameter k, which effectively characterizes the CT distribution under the steady-state simplifying assumption, the BC absorption enhancement closely corresponds to the results obtained via the particle-resolved method. This study simplifies the BC mixing state description and yields a precise evaluation of the BC optical properties, which has the potential utility for modeling efforts in the refinement of the assessment of BC's radiative effects.

Zhang, Zhouyang↗

Comment on 'Distribution of whistler mode bursts at Venus' by F.L. Scarf, K.F. Jordan, and C.T. Russell

Consideration is given to the study of the 100-Hz electric field noise observed from the Pioneer Venus Orbiter (PVO) by Scarf et al. (1987). It is suggested that the study incorrectly interprets the results as evidence for lightning and volcanism at Venus. Statistical evidence is presented, suggesting that the distribution of the noise is essentially random, within the zone of occurrence of ion troughs, and decreases at the lowest PVO altitudes, closest to the neutral atmosphere. It is found that the topographic clustering reported by Scarf et al. is an artifact of the variable spatial distribution of troughs and associated noise.

Taylor, Harry A., Jr.↗

Backscatter characteristics of the winter ice cover in the Beaufort Sea

The microwave backscatter statistics of the sea ice cover in the winter Beaufort Sea are characterized using C band synthetic aperture radar (SAR) data collected by the European Earth Resources Satellite 1. Sea ice backscatter signatures were sampled from SAR image data collected during the winter of 1991-1992 and winter of 1992-1993. The spatial and temporal variabilities of the backscatter signatures of different ice types are discussed. The results show considerable seasonal stability of the backscatter signature of multiyear ice as well as of first-year ice. Small amplitude regional variations of the multiyear ice backscatter can be observed. Consistent contrast between multiyear ice and first-year ice is maintained throughout the season. The highest radiometric variability is observed in sea ice in leads. On the basis of these observations the backscatter from the principal ice types (multiyear and first-year) are consistent with scatterometer observations and can be easily identified under winter conditions. Correlations of the regional variations of multiyear ice signatures to physical processes are suggested.

Kwok, Ronald↗

Use of Satellite Data Assimilation to Infer Land Surface Thermal Inertia

There are two important but observationally uncertain parameters in the grid averaged surface energy budgets of mesoscale models - surface moisture availability and thermal heat capacity. A technique has been successfully developed for assimilating Geostationary Operational Environmental Satellite (GOES) skin temperature tendencies during the mid-morning time frame to improve specification of surface moisture. In a new application of the technique, the use of satellite skin temperature tendencies in early evening is explored to improve specification of the surface thermal heat capacity. Together, these two satellite assimilation constraints have been shown to significantly improve the characterization of the surface energy budget of a mesoscale model on fine spatial scales. The GOES assimilation without the adjusted heat capacity was run operationally during the International H2O Project on a 12-km grid. This paper presents the results obtained when using both the moisture availability and heat capacity retrievals in concert. Preliminary results indicate that retrieved moisture availability alone improved the verification statistics of 2-meter temperature and dew point forecasts. Results from the 1.5 month long study period using the bulk heat capacity will be presented at the meeting.

Lapenta, William↗