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At least 757 records · Page 42

Effects of High-frequency Wind Sampling on Simulated Mixed Layer Depth and Upper Ocean Temperature

Effects of high-frequency wind sampling on a near-global ocean model are studied by forcing the model with a 12 hourly averaged wind product and its 24 hourly subsamples in separate experiments. The differences in mixed layer depth and sea surface temperature resulting from these experiments are examined, and the underlying physical processes are investigated. The 24 hourly subsampling not only reduces the high-frequency variability of the wind but also affects the annual mean wind because of aliasing. While the former effect largely impacts mid- to high-latitude oceans, the latter primarily affects tropical and coastal oceans. At mid- to high-latitude regions the subsampled wind results in a shallower mixed layer and higher sea surface temperature because of reduced vertical mixing associated with weaker high-frequency wind. In tropical and coastal regions, however, the change in upper ocean structure due to the wind subsampling is primarily caused by the difference in advection resulting from aliased annual mean wind, which varies with the subsampling time. The results of the study indicate a need for more frequent sampling of satellite wind measurement and have implications for data assimilation in terms of identifying the nature of model errors.

mixed layered depth↗

Hierarchical Inference of the Lensing Convergence from Photometric Catalogs with Bayesian Graph Neural Networks

Abstract We present a Bayesian graph neural network (BGNN) that can estimate the weak lensing convergence ( κ ) from photometric measurements of galaxies along a given line of sight (LOS). The method is of particular interest in strong gravitational time-delay cosmography (TDC), where characterizing the “external convergence” ( κ ext ) from the lens environment and LOS is necessary for precise Hubble constant ( H 0 ) inference. Starting from a large-scale simulation with a κ resolution of ∼1′, we introduce fluctuations on galaxy–galaxy lensing scales of ∼1″ and extract random sight lines to train our BGNN. We then evaluate the model on test sets with varying degrees of overlap with the training distribution. For each test set of 1000 sight lines, the BGNN infers the individual κ posteriors, which we combine in a hierarchical Bayesian model to yield constraints on the hyperparameters governing the population. For a test field well sampled by the training set, the BGNN recovers the population mean of κ precisely and without bias (within the 2 σ credible interval), resulting in a contribution to the H 0 error budget well under 1%. In the tails of the training set with sparse samples, the BGNN, which can ingest all available information about each sight line, extracts a stronger κ signal compared to a simplified version of the traditional method based on matching galaxy number counts, which is limited by sample variance. Our hierarchical inference pipeline using BGNNs promises to improve the κ ext characterization for precision TDC. The code is available as a public Python package, Node to Joy ⏬ .

79 ASTRONOMY AND ASTROPHYSICS↗

Spectral emissivity measurements of land-surface materials and related radiative transfer simulations

Spectral radiance measurements have been made in the laboratory and in the field for deriving spectral emissivities of some land cover samples with a spectroradiometer and an auxiliary radiation source in the wavelength range 2.5-14.5 micrometers. A easy and quick four-step method (four steps to measure the sample and a diffuse reflecting plate surface under sunshine and shadowing conditions, respectively) has been used for simultaneous determination of surface temperature and emissivity. We emphasized in-situ measurements in combination with radiative transfer simulations, and an error analysis for basic assumptions in deriving spectral emissivity of land-surface samples from thermal infrared measurements.

Wan, Z.↗

Enabling probabilistic learning on manifolds through double diffusion maps

Here, we present a generative learning framework for probabilistic sampling that extends Probabilistic Learning on Manifolds (PLoM), which is designed to generate statistically consistent realizations of a random vector in a finite-dimensional Euclidean space, informed by a (representative) set of observations. In its original form, PLoM constructs a reduced-order probabilistic model by combining three main components: (a) kernel density estimation to approximate the underlying probability measure, (b) Diffusion Maps to characterize the manifold of the data, and (c) a reduced-order Itô Stochastic Differential Equation (ISDE) to sample from the learned distribution. However, its sampling dynamics are posed in the ambient space and the retained number of reduced coordinates is chosen by projection-reconstruction error. In practice, this often (i) requires more coordinates than the data’s intrinsic dimension to achieve stable sampling and (ii) lacks a smooth, basis-independent lifting back to the data domain; moreover, standard Diffusion Maps emphasize harmonic eigenfunctions and can miss non-harmonic latent structure. We address these limitations by decoupling geometry learning from sampling: a first Diffusion Maps pass identifies non-harmonic coordinates on which we formulate a full-order ISDE directly in the latent space, while Double Diffusion Maps captures multiscale geometric features and Geometric Harmonics (GH) learns a smooth lifting map to the ambient variables that is independent of the particular diffusion basis. This hybrid design preserves the system’s dynamical richness with a compact geometric representation and enables principled out-of-sample inference. The effectiveness and robustness of the proposed method are illustrated through two numerical studies: one based on data generated from two-dimensional Hermite polynomial functions and another based on high-fidelity simulations of a detonation wave in a reactive flow.

Double diffusion maps↗

Joint Polar Satellite System (JPSS)-3 VIIRS Prelaunch Geometric Calibration and Characterization Status

The NASA/NOAA Visible Infrared Imaging Radiometer Suite (VIIRS) is a key instrument in the JPSS missions (SNPP, JPSS-1-4). Being part of the calibration and validation process, JPSS-3 VIIRS prelaunch geometric performance assessment focuses on the sensor’s spatial response, band-to-band co-registration (BBR), and pointing knowledge. In general, JPSS-3 VIIRS’ prelaunch geometric performance is very good, and consistent with SNPP and JPSS-1-2 VIIRS sensors. This paper highlights some specific key findings from the JPSS-3 VIIRS’ prelaunch tests. We first show that with timing adjustments, JPSS-3 VIIRS scan BBR error between VisNIR and S/M/LWIR bands has been reduced from 0.12/0.03 M sampling intervals to 0.005/0.002 M sampling intervals, respectively. Focal Plane Assembly (FPA) rotations have been changed from 0.1 degree to 0.04 degree in VisVIR, from 0.18 degree to 0.09 degree in S/MWIR, and 0.16 degree to 0.08 degree in LWIR. Another finding from the prelaunch test is that JPSS-3 VIIRS has relatively large band-to-band co-registration errors between VisNIR and S/M/LWIR bands in the track direction. This BBR mis-registration increases when aft‐optics assembly (AOA) temperature decreases. The BBR mis-registration is about 0.10 M sampling intervals between VisNIR and S/MWIR bands, and 0.08 M sampling intervals between VisNIR and LWIR bands. By comparison, the track BBR offset in JPSS-2 is less than 0.02 M sampling intervals between VisNIR and S/M/LWIR bands. We also notice that the unsymmetrical Day Night Band (DNB) scan-direction Line Spread Function (LSF) of JPSS-2 VIIRS at different gain stages and aggregation modes have been corrected in J3 VIIRS.

VIIRS↗

Decision Making In A High-Tech World: Automation Bias and Countermeasures

Automated decision aids and decision support systems have become essential tools in many high-tech environments. In aviation, for example, flight management systems computers not only fly the aircraft, but also calculate fuel efficient paths, detect and diagnose system malfunctions and abnormalities, and recommend or carry out decisions. Air Traffic Controllers will soon be utilizing decision support tools to help them predict and detect potential conflicts and to generate clearances. Other fields as disparate as nuclear power plants and medical diagnostics are similarly becoming more and more automated. Ideally, the combination of human decision maker and automated decision aid should result in a high-performing team, maximizing the advantages of additional cognitive and observational power in the decision-making process. In reality, however, the presence of these aids often short-circuits the way that even very experienced decision makers have traditionally handled tasks and made decisions, and introduces opportunities for new decision heuristics and biases. Results of recent research investigating the use of automated aids have indicated the presence of automation bias, that is, errors made when decision makers rely on automated cues as a heuristic replacement for vigilant information seeking and processing. Automation commission errors, i.e., errors made when decision makers inappropriately follow an automated directive, or automation omission errors, i.e., errors made when humans fail to take action or notice a problem because an automated aid fails to inform them, can result from this tendency. Evidence of the tendency to make automation-related omission and commission errors has been found in pilot self reports, in studies using pilots in flight simulations, and in non-flight decision making contexts with student samples. Considerable research has found that increasing social accountability can successfully ameliorate a broad array of cognitive biases and resultant errors. To what extent these effects generalize to performance situations is not yet empirically established. The two studies to be presented represent concurrent efforts, with student and professional pilot samples, to determine the effects of accountability pressures on automation bias and on the verification of the accurate functioning of automated aids. Students (Experiment 1) and commercial pilots (Experiment 2) performed simulated flight tasks using automated aids. In both studies, participants who perceived themselves as accountable for their strategies of interaction with the automation were significantly more likely to verify its correctness, and committed significantly fewer automation-related errors than those who did not report this perception.

Mosier, Kathleen L.↗

Transient desorption of water vapor - A potential source of error in upper atmosphere rocket experiments

Results of measurements of the outgassing rates of samples of materials and surface finishes used on the outer skins of rocket-borne experiment packages in simulated rocket ascents. The results showed outgassing rates for anodized aluminum in the second minute of flight which are two to three orders of magnitude higher than those given in typical tables of outgassing rates. The measured rates for aluminum with chromate conversion surface coatings were also abnormally high. These abnormally high initial rates fell quickly after about five to ten minutes to values comparable with those in the published literature. It is concluded that anodized and chromate conversion coatings on the aluminum outer surfaces of a sounding rocket experiment package will cause gross distortion of the true water vapor environment.

Kendall, B. R. F.↗

Computer Simulations to Study Diffraction Effects of Stacking Faults in Beta-SiC: II. Experimental Verification: Experimental Verification - 2

Earlier results from computer simulation studies suggest a correlation between the spatial distribution of stacking errors in the Beta-SiC structure and features observed in X-ray diffraction patterns of the material. Reported here are experimental results obtained from two types of nominally Beta-SiC specimens, which yield distinct XRD data. These samples were analyzed using high resolution transmission electron microscopy (HRTEM) and the stacking error distribution was directly determined. The HRTEM results compare well to those deduced by matching the XRD data with simulated spectra, confirming the hypothesis that the XRD data is indicative not only of the presence and density of stacking errors, but also that it can yield information regarding their distribution. In addition, the stacking error population in both specimens is related to their synthesis conditions and it appears that it is similar to the relation developed by others to explain the formation of the corresponding polytypes.

Pujar, Vijay V.↗

Elevated initial Sr-87/Sr-86 in ordinary chondrite metal

The metal phase of ordinary chondrites has been found to contain a complex assemblage of non-metal phases, evidently formed when elements such as Si, Cr and P, originally dissolved in the metal, were subsequently oxidized and exsolved. We have investigated the Rb-Sr isotopic system in samples of H-chondrite metal, finding small but nontrivial amounts of Sr, apparently concentrated toward the surface of metal grains, and characterized by pronounced excesses of Sr-87/Sr-86 in chondritic metal can plausibly account for the characteristically elevated initial Sr-87/Sr-86 found in ordinary chondrite phosphates, but it remains unclear when and where the metal experienced the high Rb/Sr environment needed to account for such high Sr-87/Sr-86. We have previously reported Rb-Sr data for separated metal from Dhajala (H3), Forest Vale (H4) and Estacado (H6). Here we report data for two size fractions (80-160 and 280-450 microns) of separated metal from the H4 chondrite Ste. Marguerite. These samples were etched twice (.5N HCl for one hour) before dissolution (6N HCl). Aliquots of the solutions were spiked for Fe, Ca and Rb + Sr. The results for Ste. Marguerite metal are presented; errors are two-sigma and elemental concentrations are stated in terms of total sample weight.

Podosek, F. A.↗

Human Performance Contributions to Safety in Commercial Aviation

In the commercial aviation domain, large volumes of data are collected and analyzed on the failures and errors that result in infrequent incidents and accidents, but in the absence of data on behaviors that contribute to routine successful outcomes, safety management and system design decisions are based on a small sample of non- representative safety data. Analysis of aviation accident data suggests that human error is implicated in up to 80% of accidents, which has been used to justify future visions for aviation in which the roles of human operators are greatly diminished or eliminated in the interest of creating a safer aviation system. However, failure to fully consider the human contributions to successful system performance in civil aviation represents a significant and largely unrecognized risk when making policy decisions about human roles and responsibilities. Opportunities exist to leverage the vast amount of data that has already been collected, or could be easily obtained, to increase our understanding of human contributions to “things going right” in commercial aviation. The principal focus of this assessment was to identify current gaps and explore methods for identifying human “success” data generated by the aviation system, from personnel and within the supporting infrastructure.

Holbrook, Jon B.↗

14C and U-series disequilibria age constraints from recent eruptions at Sete Cidades volcano, Azores

Accurate dating of young (<10 ka) volcanic rocks poses numerous challenges, yet determining eruption ages is critical to understanding magmatic evolution and hazards associated with active volcanic centers. 14C dating is the preferred technique for dating young geologic materials, but a few studies have suggested that volcanic degassing can result in erroneously old 14C dates (e.g. Pasquier-Cardin et al., 1999). Finding an isotopic system with which to accurately constrain eruptive recurrence intervals at recently active volcanic centers is critical to assessing future volcanic hazards. In this study, we have obtained 14C data from modern terrestrial gastropods on Sa~o Miguel island, Azores to assess the current impact of volcanic degassing on 14C ages near active and extinct volcanic centers, and for one active volcanic center, we have compared 14C of paleosols with 226Ra-230Th maximum eruptive ages for pumices immediately overlying the respective paleosols. 14C ages of the modern terrestrial gastropod Cornu aspersum demonstrate the effects of dilution from a range of current outgassing levels at three active trachytic stratovolcanoes on Sa~o Miguel island: Sete Cidades, Fogo, Furnas, as well as the extinct Povoac¸a~o volcano. A modern gastropod sampled at Furnas, where there is evidence of extensive present-day degassing, has a 14C age of 394 ±97 y cal BP. At Fogo volcano, also a location with active degassing, the 14C age of a modern gastropod is 1324 ±60 y cal BP. Both of these ages clearly show effects of dilution of atmospheric 14C due to volcanic degassing. In contrast, there is currently no apparent outgassing occurring at Sete Cidades or Povoac¸a~o, and modern gastropod ages from these volcanoes are post-bomb. We also obtained 14C data from paleosols and 226Ra-230Th ages associated pumices from the youngest eruptive sequence of Sete Cidades volcano, the Pepom P1-P17 deposits, the ages of which are poorly constrained but thought to be <5,000 y (Queiroz, 1997). 226Ra-230Th disequilibrium in a P1 glass separate indicates a maximum eruptive age of 4440 ±195 y. 14C ages of paleosols below P1 and P3 are older than those derived from 226Ra-230Th dating, at 7293 ±141 y cal BP and 7698 ± 172 y cal BP, respectively. We interpret the 14C ages as being erroneously old due to abundant volcanic degassing at the time of eruption. Similarly, but to a lesser extent, the 226Ra-230Th maximum eruptive age of glass separated from the P8 eruption is 2659 ±55 y, whereas the age of the paleosol sampled directly beneathP8 is older (3054 ±194 y BP). In contrast, paleosols sampled at multiple field localities from below the most recent eruptive deposit (P17) are within error of each other (476 ±56 cal y BP and 585 ±68 cal y BP), while 226Ra-230Th maximum eruptive ages in glass separates from two different P17 sampling sites are 762 ±14 y and 730 y ±15 y. This is consistent with the observation that Sete Cidades volcano is experiencing limited hydrothermal activity at the present time and likely had similar low levels of degassing just prior to the last eruption. The average eruptive recurrence interval for the P1-P17 deposits, based on 226Ra-230Th maximum eruptive ages from P1 and P8 and 14C ages from P17, is ~220 years. This recurrence interval is similar to the ~200 y eruptive recurrence interval at Furnas volcano and much shorter than the ~1200 y eruptive interval at Fogo volcano. This has important implications with respect to volcanic hazards and should be considered in any future volcanic hazard planning.

U-series disequilibria, Carbon-14, Cornu aspersum,↗

Performance Metrics for the Assessment of Satellite Data Products: An Ocean Color Case Study

Performance assessment of ocean color satellite data has generally relied on statistical metrics chosen for their common usage and the rationale for selecting certain metrics is infrequently explained. Commonly reported statistics based on mean squared errors, such as the coefficient of determination (r2), root mean square error, and regression slopes, are most appropriate for Gaussian distributions without outliers and, therefore, are often not ideal for ocean color algorithm performance assessment, which is often limited by sample availability. In contrast, metrics based on simple deviations, such as bias and mean absolute error, as well as pair-wise comparisons, often provide more robust and straightforward quantities for evaluating ocean color algorithms with non-Gaussian distributions and outliers. This study uses a SeaWiFS chlorophyll-a validation data set to demonstrate a framework for satellite data product assessment and recommends a multimetric and user-dependent approach that can be applied within science, modeling, and resource management communities.

remote sensing↗

A theoretical basis for the analysis of redundant software subject to coincident errors

Fundamental to the development of redundant software techniques fault-tolerant software, is an understanding of the impact of multiple-joint occurrences of coincident errors. A theoretical basis for the study of redundant software is developed which provides a probabilistic framework for empirically evaluating the effectiveness of the general (N-Version) strategy when component versions are subject to coincident errors, and permits an analytical study of the effects of these errors. The basic assumptions of the model are: (1) independently designed software components are chosen in a random sample; and (2) in the user environment, the system is required to execute on a stationary input series. The intensity of coincident errors, has a central role in the model. This function describes the propensity to introduce design faults in such a way that software components fail together when executing in the user environment. The model is used to give conditions under which an N-Version system is a better strategy for reducing system failure probability than relying on a single version of software. A condition which limits the effectiveness of a fault-tolerant strategy is studied, and it is posted whether system failure probability varies monotonically with increasing N or whether an optimal choice of N exists.

Eckhardt, D. E., Jr.↗

Performance of the all-digital data-transition tracking loop in the advanced receiver

The performance of the all-digital data-transition tracking loop (DTTL) with coherent or noncoherent sampling is described. The effects of few samples per symbol and of noncommensurate sampling rates and symbol rates are addressed and analyzed. Their impacts on the loop phase-error variance and the mean time to lose lock (MTLL) are quantified through computer simulations. The analysis and preliminary simulations indicate that with three to four samples per symbol, the DTTL can track with negligible jitter because of the presence of earth Doppler rate. Furthermore, the MTLL is also expected to be large engough to maintain lock over a Deep Space Network track.

Cheng, U.↗

The ensemble variability properties of faint QSOs

A refined sample of 64 variable objects with stellar image structure has been identified in SA 57 to B approximately = 22.5, over a time baseline of 15 yr, sampled at 11 distinct epochs. The photometric data typically have a root-mean-square (rms) error at B = 22 of only 0.05 mag. Thirty-five quasars in this field have already been spectroscopically confirmed, 34 of which are among the sample of variables. Of the other variables, six are known spectroscopically to be stars, 10 additional objects are stars based on reliable detection of proper motion, and one is spectroscopically a narrow emission line galaxy. Of the 13 remaining variables, it is argued that they are a mixture of distant halo subdwarfs and quasars with starlike colors. We compute the ensemble average structure function and autocorrelation function from the light curves in the respective quasar rest frames, which are used to investigate the general dependences on apparent magnitude, absolute magnitude, and redshift.

Trevese, Dario↗

Recommendations for Using Noise Monitors to Estimate Noise Exposure During X-59 Community Tests

A low fidelity simulation approach is used to explore how to place and use noise monitors during X-59 QueSST community tests, where people’s annoyance to the noise produced by the X-59 aircraft will be gathered. Several recommendations are provided including: 1) the desired number of sparsely spaced noise monitor sites within the survey area, 2) whether to group and average measurements across multiple noise monitors located at a site, 3) what spacing should be used if grouped noise monitors are used, 4) an approach to mitigate ambient noise contamination at the measurement sites, 5) a method to combine empirical and predicted dose estimates to provide a single dose estimate for respondents, and 6) assessing how changes in turbulence intensity and array configuration affect dose uncertainty. To make these recommendations, the error that is expected when fitting contrived, smoothly varying sonic boom “reference exposure surfaces” is studied when a spatially sparse and scattered set of samples is used as responses for the fit. The reference exposure surfaces mimic the sonic boom exposure at ground level that might be expected in the X-59 survey area in the absence of atmospheric turbulence, ambient noise, and other localized effects. The spatial extent of these surfaces varies and is representative of the different survey area sizes that might be expected during future X-59 community overflight tests. These contrived reference surfaces are sampled, and those reference samples are then perturbed to mimic atmospheric turbulence, ambient noise and other localized effects that might affect noise monitor measurements within overflown communities. Two different surface fitting methods are investigated when fitting these perturbed samples to approximate the reference surface. The first method uses interpolation between the perturbed data at the scattered sites to compute the fit. The second method fits a polynomial surface model to the perturbed data using ordinary least squares regression analysis. For both fitting methods, the root mean square fit error is computed from the pointwise difference between the fit surface and the reference surface as the count and configuration of the sites is varied while also averaging the error across many different realizations of both the smooth variation of the reference exposure surface and the random, localized perturbations at the sample sites. Different site configurations are compared using this error statistic to make the recommendations noted above. Additionally, the two fitting approaches (interpolation vs linear regression) are compared based on the fit error observed in these simulations. These analyses, comparisons, and recommendations should inform future decisions on the noise monitor placement and the methods used to analyze the noise monitor data that is collected during X-59 community overflights.

sonic boom↗

Comparing Designed Training Sets to Optimize Multivariate Regression Models for Pr, Nd, and Nitric Acid Using Spectrophotometry

Chemometric regression models were developed for the quantification of praseodymium (Pr, 0–1000 µg/mL), neodymium (Nd, 0–1000 µg/mL), and nitric acid (HNO 3 , 0.1–5 M) using spectrophotometry. Designed calibration sets were composed of 20 samples each: 10 model points and 10 lack-of-fit (LOF) points. The D-optimal designs effectively minimized the number of samples required to build models, and each design resulted in similar prediction performance, suggesting that statistical design of experiments can provide a reliable framework for selecting training set samples in three-variable systems. Partial least squares regression (PLSR) models were validated against a one-factor-at-a-time validation set composed of 125 samples (three variables, five levels). The top PLS-1 models resulted in average percent root mean square error of prediction error values of 3.5%, 1.7%, and 1.2% for Pr(III), Nd(III), and HNO 3 , respectively. Power set augmentations of the model and LOF samples were investigated to optimize the number of training set samples. PLSR models built using just required model points (10) had similar predictive capabilities as models including the LOF points (20) but with fewer samples. The number of validation samples was also varied systematically to learn how many samples are needed to validate regression models. This work addresses long-standing questions in the field of chemometrics to help make this approach amenable to the near-real-time quantification of hazardous species in remote settings.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Development and cross‐validation of a circumference‐based predictive equation to estimate body fat in an active population

Abstract Objective The U.S. Army uses sex‐specific circumference‐based prediction equations to estimate percent body fat (%BF) to evaluate adherence to body composition standards. The equations are periodically evaluated to ensure that they continue to accurately assess %BF in a diverse population. The objective of this study was to develop and validate alternative field expedient equations that may improve upon the current Army Regulation (AR) body fat (%BF) equations. Methods Body size and composition were evaluated in a representatively sampled cohort of 1904 active‐duty Soldiers (1261 Males, 643 Females), using dual‐energy X‐ray absorptiometry (%BF DXA ), and circumferences obtained with 3D imaging and manual measurements. Sex stratified linear prediction equations for %BF were constructed using internal cross validation with %BF DXA as the criterion measure. Prediction equations were evaluated for accuracy and precision using root mean squared error, bias, and intraclass correlations. Equations were externally validated in a convenient sample of 1073 Soldiers. Results Three new equations were developed using one to three circumference sites. The predictive values of waist, abdomen, hip circumference, weight and height were evaluated. Changing from a 3‐site model to a 1‐site model had minimal impact on measurements of model accuracy and performance. Male‐specific equations demonstrated larger gains in accuracy, whereas female‐specific equations resulted in minor improvements in accuracy compared to existing AR equations. Equations performed similarly in the second external validation cohort. Conclusions The equations developed improved upon the current AR equation while demonstrating robust and consistent results within an external population. The 1‐site waist circumference‐based equation utilized the abdominal measurement, which aligns with associated obesity related health outcomes. This could be used to identify individuals at risk for negative health outcomes for earlier intervention.

Taylor, Kathryn M.↗