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At least 505 records · Page 28

An extended polynomial chaos expansion for PDF characterization and variation with aleatory and epistemic uncertainties

This paper presents an extended polynomial chaos formalism for epistemic uncertainties and a new framework for evaluating sensitivities and variations of output probability density functions (PDF) to uncertainty in probabilistic models of input variables. An ”extended” polynomial chaos expansion (PCE) approach is developed that accounts for both aleatory and epistemic uncertainties, modeled as random variables, thus allowing a unified treatment of both types of uncertainty. We explore in particular epistemic uncertainty associated with the choice of prior probabilistic models for input parameters. A PCE-based Kernel Density (KDE) construction provides a composite map from the PCE coefficients and germ to the PDF of quantities of interest (QoI). Here, the sensitivities of these PDF with respect to the input parameters are then evaluated. Input parameters of the probabilistic models are considered. By sampling over the epistemic random variable, a family of PDFs is generated and the failure probability is itself estimated as a random variable with its own PCE. Integrating epistemic uncertainties within the PCE framework results in a computationally efficient paradigm for propagation and sensitivity evaluation. Two typical illustrative examples are used to demonstrate the proposed approach.

Aleatory uncertainty↗

Data for Yield from Iowa’s first commercial miscanthus fields: implications of spatial variability for productivity and sustainability beyond research plots

This dataset contains biomass yield measurements and associated vegetation index data collected from commercial Miscanthus × giganteus fields in eastern Iowa during the 2022–2023 growing seasons. The data support the analyses presented in the article: “Yield From Iowa's First Commercial Miscanthus Fields: Implications of Spatial Variability for Productivity and Sustainability Beyond Research Plots.” We collected 105 ground-truth biomass samples from four mature commercial fields (>4 years old) covering 92.81 ha. Samples were taken from 3 m² quadrats that were hand-harvested in alignment with commercial harvest timing. Stem biomass (excluding leaves) was weighed, moisture-corrected, and converted to dry-matter yield expressed in Mg DM ha⁻¹. Sampling locations were selected to capture spatial variability visible in aerial imagery and were recorded using RTK GPS. Each biomass observation was paired with vegetation indices derived from high-resolution PlanetScope satellite imagery (3 m resolution). Images were acquired throughout the growing season, and indices were calculated to evaluate their ability to predict end-of-season biomass yield. Statistical and machine learning approaches were used to identify key predictors, and a linear regression model based on end-of-July Green Normalized Difference Vegetation Index (GNDVI) was developed and evaluated. This repository includes the data used in that modeling workflow. Management practices, economic data, full imagery time series, and additional methodological details are described in the associated publication and are not included here. The dataset consists of three comma-separated value (CSV) files: 1. Combine_Groundtruth_Yield_VI_22_23.csv This file contains ground-truth biomass yield measurements and associated key vegetation index values collected during the 2022 and 2023 growing seasons. Rows: 105 observations Columns: Year — Year of observation (2022 or 2023) Field — Field location identifier Sample_number — Unique sample identifier GNDVI_End_Jul — Green Normalized Difference Vegetation Index calculated at end of July GNDVI_End_Aug — Green Normalized Difference Vegetation Index calculated at end of August NDRE_End_Aug — Normalized Difference Red Edge index calculated at end of August Biomass_Stem_Yield_MgDM/ha — Measured stem biomass yield (megagrams dry matter per hectare) 2. trainData_GNDVI.csv This file contains the subset of observations used to train the predictive relationship between July GNDVI and biomass yield. Rows: 76 observations Columns: Unnamed: 0 — Row index retained from the original data processing workflow GNDVI_End_Jul — GNDVI at end of July Stem_Yield_MgDM/ha — Observed stem biomass yield (Mg DM ha⁻¹) 3. testData_GNDVI.csv This file contains the test dataset used to evaluate model performance. Rows: 29 observations Columns: Unnamed: 0 — Row index retained from the original data processing workflow GNDVI_End_Jul — GNDVI at end of July Predicted_Yield_MgDM/ha — Model-predicted stem biomass yield (Mg DM ha⁻¹) Observed_Yield_MgDM/ha — Measured stem biomass yield (Mg DM ha⁻¹)

Potential yield, yield gap, in-field management, y↗

X-Ray Emission of Ultraviolet Variable Active Galactic Nucleus Candidates

We analyze the X-ray properties of a sample of 23 high-probability active galactic nucleus (AGN) candidates with ultraviolet variability identified in Wasleske et al. Using data from the Chandra X-ray Observatory and XMM-Newton Observatory, we that find 11/23 nuclei are X-ray detected. We use spectral energy distribution modeling to compute star formation rates and show that the X-ray luminosities are typically in excess of the X-ray emission expected from star formation by at least an order of magnitude. Interestingly, this sample shows a diversity of optical spectroscopic properties. We explore possible reasons for why some objects lack optical spectroscopic signatures of black hole activity while still being UV-variable and X-ray bright. We find that host galaxy stellar emission and obscuration from gas and dust are potential factors. We study where this sample falls on relationships such as α OX - L 2500 and L X - L IR and find that some of the sample falls outside the typical scatter for these relations, indicating that they differ from the standard quasar population. With the diversity of optical spectroscopic signatures and varying impacts of dust and stellar emissions on our sample, these results emphasize the strength of variability in selecting the most complete set of AGN, regardless of other host galaxy properties.

79 ASTRONOMY AND ASTROPHYSICS↗

An omnipresent diversity and variability in the chemical composition of atmospheric functionalized organic aerosol

Abstract The atmospheric evolution of organic compounds encompasses many thousands of compounds with varying volatility, polarity, and water solubility. The molecular-level chemical composition of this mixture plays a major, yet uncertain, role in its transformations and impacts. Here we perform a non-targeted molecular-level intercomparison of functionalized organic aerosol from three diverse field sites and a chamber. Despite similar bulk composition, we report large molecular-level variability between multi-hour organic aerosol samples at each site, with 66 ± 13% of functionalized compounds differing between consecutive samples. Single precursor environmental laboratory chamber experiments and fully chemically-explicit modeling confirm this variability is due to changes in emitted precursors, chemical age, and/or oxidation conditions. These molecular-level results demonstrate greater compositional variability than is typically observed in less-speciated measurements, such as bulk elemental composition, which tend to show less daily variability. These observations should inform future field and laboratory studies, including assessments of the effects of variability on aerosol properties and ultimately the development of strategic organic aerosol parameterizations for air quality and climate models.

Ditto, Jenna C.↗

An Examination of the Space Weathering Patina of Lunar Rock 76015

Space weathering discussions have generally centered around soils but exposed rocks will also incur the effects of weathering. Rocks have much longer surface lifetimes than an individual soil grain and thus record a longer history of exposure. By studying the weathering products which have built up on a rock surface, we can gain a deeper perspective on the weathering process and better assess the relative importance of various weathering components. The weathered coating, or patina, of the lunar rock 76015 has been previously studied under SEM and also by TEM using ultramicrotome sample preparation methods. However, to really understand the products involved in creating these coatings, it is helpful to examine the patina in cross section, something which is now possible though the use of Focused Ion Beam (FIB) sample prep techniques, which allows us to preserve intact the delicate stratigraphy of the patina coating and provides a unique cross-sectional view of the space weathering process. Several samples have been prepared from the rock and the coatings are found to be quite variable in thickness and composition from one sample to the next.

Noble, S.↗

Homogenization of Satellite Based Hyperspectral Infrared Sounder Data To Build Long Term Climate Record

Building long term climate record using data from multiple hyperspectral Infrared (IR)sounders requires the homogenization of different data record to ensure the consistency andcontinuity. Such a requirement comes from two perspectives: 1) the need to adjust theoverlapping measurements of different sounders to ensure the radiometric consistency in thespectral radiance domain; 2) the need for a rigorously defined scheme to ensure the radiometricconsistency being transferred to the essential climate variables derived from the radiance record.We develop a solution that uses a spectral fingerprinting scheme to derive anomalies of keyclimate variables from long term spectral radiance data record constructed using both AIRS andCrIS observations aboard AQUA, SNPP and JPSS satellites. The fingerprinting scheme usescommon radiative kernels for all sounder measurements and therefore effectively avoids thealgorithm introduced inconsistency in retrieved geophysical variables. Our approach uses aunified sampling scheme to match AIRS and CrIS observations in both spectral and spatial-temporal domain, facilitating the intercomparison of spectral radiances from different sensors(platforms). The optimized liner inversion scheme allows the direct quantification and thereforethe adjustment for the impact on the derived climate anomalies imposed by potential radiometricinconsistency between the overlapping measurements. Such a scheme also enables the low-latency data processing of long term hyperspectral sounder data records. This paper provides a detailed introduction of the spectral fingerprinting methodology.Also introduced here is the climate fingerprinting Sounder Product (ClimFiSP) developed basedon the fingerprinting methodology. ClimFiSP products include the space-time averagedproperties of key climate variables that are derived from the long-term, space-time averagedradiances from AQUA-AIRS, SNPP-CrIS, and JPSS1-CrIS. ClimFiSP will be available to usersthrough NASA'sGoddard Earth Sciences Data and Information Services Center (GES DISC).

Wan Wu↗

Efficiently sampling conformations and pathways using the concurrent adaptive sampling (CAS) algorithm

Molecular dynamics (MD) simulations are useful in obtaining thermodynamic and kinetic properties of bio-molecules but are limited by the timescale barrier, i.e., we may be unable to efficiently obtain properties because we need to run microseconds or longer simulations using femtoseconds time steps. While there are several existing methods to overcome this timescale barrier and efficiently sample thermodynamic and/or kinetic properties, problems remain in regard to being able to sample un- known systems, deal with high-dimensional space of collective variables, and focus the computational effort on slow timescales. Hence, in this work, a new sampling method, called the “Concurrent Adaptive Sampling (CAS) algorithm,” has been developed to tackle these three issues and efficiently obtain conformations and pathways. The method is not constrained to use only one or two collective variables, unlike most reaction coordinate-dependent methods. Instead, it can use a large number of collective vari- ables and uses macrostates (a partition of the collective variable space) to enhance the sampling. The exploration is done by running a large number of short simula- tions, and a clustering technique is used to accelerate the sampling. In this paper, we introduce the new methodology and show results from two-dimensional models and bio-molecules, such as penta-alanine and triazine polymer

59 BASIC BIOLOGICAL SCIENCES↗

Whole genome sequencing of Mycobacterium bovis directly from clinical tissue samples without culture

Advancement in next generation sequencing offers the possibility of routine use of whole genome sequencing (WGS) for Mycobacterium bovis (M. bovis) genomes in clinical reference laboratories. To date, the M. bovis genome could only be sequenced if the mycobacteria were cultured from tissue. This requirement for culture has been due to the overwhelmingly large amount of host DNA present when DNA is prepared directly from a granuloma. To overcome this formidable hurdle, we evaluated the usefulness of an RNA-based targeted enrichment method to sequence M. bovis DNA directly from tissue samples without culture. Initial spiking experiments for method development were established by spiking DNA extracted from tissue samples with serially diluted M. bovis BCG DNA at the following concentration range: 0.1 ng/μl to 0.1 pg/μl (10 –1 to 10 –4 ). Library preparation, hybridization and enrichment was performed using SureSelect custom capture library RNA baits and the SureSelect XT HS2 target enrichment system for Illumina paired-end sequencing. The method validation was then assessed using direct WGS of M. bovis DNA extracted from tissue samples from naturally (n = 6) and experimentally (n = 6) infected animals with variable Ct values. Direct WGS of spiked DNA samples achieved 99.1% mean genome coverage (mean depth of coverage: 108×) and 98.8% mean genome coverage (mean depth of coverage: 26.4×) for tissue samples spiked with BCG DNA at 10 –1 (mean Ct value: 20.3) and 10 –2 (mean Ct value: 23.4), respectively. The M. bovis genome from the experimentally and naturally infected tissue samples was successfully sequenced with a mean genome coverage of 99.56% and depth of genome coverage ranging from 9.2× to 72.1×. The spoligoyping and M. bovis group assignment derived from sequencing DNA directly from the infected tissue samples matched that of the cultured isolates from the same sample. Our results show that direct sequencing of M. bovis DNA from tissue samples has the potential to provide accurate sequencing of M. bovis genomes significantly faster than WGS from cultures in research and diagnostic settings.

59 BASIC BIOLOGICAL SCIENCES↗

Using low volume eDNA methods to sample pelagic marine animal assemblages

Environmental DNA (eDNA) is an increasingly useful method for detecting pelagic animals in the ocean but typically requires large water volumes to sample diverse assemblages. Ship-based pelagic sampling programs that could implement eDNA methods generally have restrictive water budgets. Studies that quantify how eDNA methods perform on low water volumes in the ocean are limited, especially in deep-sea habitats with low animal biomass and poorly described species assemblages. Using 12S rRNA and COI gene primers, we quantified assemblages comprised of micronekton, coastal forage fishes, and zooplankton from low volume eDNA seawater samples (n = 436, 380–1800 mL) collected at depths of 0–2200 m in the southern California Current. We compared diversity in eDNA samples to concurrently collected pelagic trawl samples (n = 27), detecting a higher diversity of vertebrate and invertebrate groups in the eDNA samples. Differences in assemblage composition could be explained by variability in size-selectivity among methods and DNA primer suitability across taxonomic groups. The number of reads and amplicon sequences variants (ASVs) did not vary substantially among shallow (<200 m) and deep samples (>600 m), but the proportion of invertebrate ASVs that could be assigned a species-level identification decreased with sampling depth. Using hierarchical clustering, we resolved horizontal and vertical variability in marine animal assemblages from samples characterized by a relatively low diversity of ecologically important species. Low volume eDNA samples will quantify greater taxonomic diversity as reference libraries, especially for deep-dwelling invertebrate species, continue to expand.

59 BASIC BIOLOGICAL SCIENCES↗

Cloud, Aerosol and Boundary Layer Structure across the Northeast Pacific Stratocumulus-Cumulus Transition as observed during CSET

During the Cloud System Evolution in the Trades (CSET) field study, 14 research flights of the National Science Foundation G-V sampled the stratocumulus-cumulus transition between Northern California and Hawaii and its synoptic variability. The G-V made vertically resolved measurements of turbulence, cloud microphysics, aerosol characteristics, and trace gases. It also carried dropsondes and a vertically pointing W-band radar and lidar. This paper summarizes these observations with the goals of fostering novel comparisons with theory, models and reanalyses, and satellite-derived products. A longitude-height binning and compositing strategy mitigates limitations of sparse sampling and spatiotemporal variability. Typically, a 1-km-deep decoupled stratocumulus-capped boundary layer near California evolved into 2-km-deep precipitating cumulus clusters surrounded by patches of thin stratus that dissipated toward Hawaii. Low cloud cover was correlated with estimated inversion strength more than with cloud droplet number, even though the thickest clouds were generally precipitating and ultraclean layers indicative of aerosol-cloud-precipitation interaction were common west of 140 degrees W. Accumulation-mode aerosol concentration correlated well with collocated cloud droplet number concentration and was typically largest near the surface. Aitken mode aerosol concentration was typically larger in the free troposphere. Wildfire smoke produced spikes of aerosol and trace gases on some flights. CSET data are compared with space-time collocated output from MERRA-2 reanalysis and from the CAM6 climate model run with winds and temperature nudged toward this reanalysis. The reanalysis compares better with the observed relative humidity than does nudged CAM6. Both vertically diffuse the stratocumulus cloud layer versus observations. MERRA-2 slightly underestimates in situ carbon monoxide measurements and underestimates ozone depletion within the boundary layer.

Bretherton, Christopher S.↗

The x ray variability of NGC6814: Power spectra

Simulation techniques are used to obtain the X-ray variability power spectrum of unevenly sampled GINGA data from NGC6814. A simple power law is not an adequate description of the power spectrum, with the residuals showing excess power on timescales consistent with the periodicity seen in EXOSAT observations of this object. However the shape of the folded lightcurve is very different, with 3 main peaks, two of which are separated by an extremely sharp dip instead of the single peak and small harmonic structure observed by EXOSAT. Using the dip as a fiducial mark, a second GINGA observation of this source taken one year later is found to be consistent with being completely periodic and phase coherent with this first GINGA observation. Thus the period is consistent with being constant over a period of 6 years, but phase coherence is only maintained on timescales of approximately 1 year. Over 75 percent of the total source variability is due to the periodic component (r.m.s. amplitude of 36 percent). The residual variability can be described as the more usual 'flicker noise' f(exp -1.1) powerlaw. This shows no apparent high frequency break on timescales greater than 300 seconds. Subtle differences in the shape of the folded light curve with energy, and the very large amount of power in the periodic component suggest occultation as its origin, though amplification of variability from an X-ray emitting 'hot spot' at the disk inner radius through gravitational lensing is also possible. The former suffers from the very arbitrary nature of the periodic timescale, while the latter is unattractive as it cannot simply explain the lack of high frequency break in the residual power. That these models probably fail to provide an adequate explanation may be due to the added complexity of anisotropy of the X-ray emission, suggested by the discrepancy between the lack of soft photons implied by the flat spectrum and the copious source of soft photons available from reprocessing in the iron line producing material.

Done, C.↗

The Effects of High-Temperature Fractional Crystallization on Calcium Isotopic Composition

We report Ca isotope fractionation among a co-genetic suite of samples from the Mauritanian Guelb el Azib ultramafic-mafic-anorthosite complex (GAC), which represents the fractional crystallization sequence of an igneous magma chamber. We investigate how the composition of an evolving crystallizing liquid and the resultant mineralogy of co-crystallizing assemblages affects inter-phase Ca isotope fractionation. Because the GAC is an Archean metamorphosed complex, we first investigate the resistance of the Ca isotope signature to secondary hydrothermal alteration and to metamorphism. While we cannot conclude here that Ca isotopes are undisturbed at the mineral scale, we show that they are preserved at the bulk rock scale. This is adequate for our study where several samples are almost monomineralic at the bulk scale level. The δ(exp 44/40)Ca (relative to NIST standard SRM 915a) of GAC layers range from −1.53 to 1.61‰, with the earliest-formed ultramafic cumulate layer being isotopically heaviest and the later, more felsic layers being isotopically lighter. For the first time, we show that plagioclase is much more enriched in light Ca isotopes compared to olivine and (Ca-) pyroxene. Monte Carlo simulations suggest that Ca isotopes are fractionated among co-existing silicate minerals during fractional crystallization, possibly in relation with the residual liquid composition. In qualitative agreement with computational models based on first principles lattice dynamics, we observe that Ca isotope fractionation is mineralogically controlled and importantly, that the degree of fractionation can vary according to the CaO composition of the residual liquid. While previous studies have aimed to understand partial melting as a source of Ca isotope fractionation, our results suggest that fractional crystallization is also a source of Ca isotope variability among co-genetic samples.

Maria C. Valdes↗

The optical polarization properties of X-ray-selected BL Lacertae objects

We discuss the optical polarization properties of X-ray-selected BL Lacertae objects (XSBLs) as determined from 3 yr of monitoring the polarization of 37 BL Lac objects and candidates. The observed objects include a complete X-ray flux limited sample drawn from the Einstein Extended Medium Sensitivity Survey (EMSS). We find that the majority of the XSBLs classified solely on the appearance of their optical spectra are true members of the class of BL Lacertae objects since they possess intrinsically polarized and variable continua. The duty cycle of polarized emission (fraction of time spent with the degree of polarization greater than 4%) from XSBLs is 44%. The maximum observed percent polarizations are of order 10%, considerably below the maximum values observed for radio-selected BL Lacertae objects and blazars (30%-40%). While XSBLs have variable polarized emission, the majority (approximately equal to 85%) have preferred polarization position angles on timescales at least as long as 3 yr. This reflects stability in the geometry of the region emitting the linearly polarized optical emission. We describe the spectral dependence of the degree of polarization and discuss some of the possible mechanisms producing the observed characteristics. While dilution of the polarized emission by the host galaxy starlight is certainly present in some objects, we demonstrate that the average polarization properties of XSBLs derived from our observations are not drastically affected by this effect. While the confirmed BL Lac objects are shown to be photometric variables, the objects in our monitored sample did not display the larger than 1 mag variations generally used to characterize the optical variability of radio-selected BL Lacertae objects or blazars in general.

Jannuzi, Buell T.↗

Climate monitoring from space - Asynoptic sampling considerations

Asynoptic sampling for orbits and viewing geometries for climate monitoring from space is discussed. The basic physical processes pertinent to climate are reviewed. Two classes of variability are identified which challenge the information content of asynoptic sampling: irregular and diurnal variability. The limitations of nadir- and limb-viewing instruments, scanning radiometers, and wide FOV radiometers are discussed. The implications of variability for single and multiple orbital platforms are considered.

Salby, Murry L.↗

On representation of temporal variability in electricity capacity planning models

This study systematically investigates how to represent intra-annual temporal variability in models of optimum electricity capacity investment. Inappropriate aggregation of temporal resolution can introduce substantial error into model outputs and associated economic insight. The mechanisms underlying the introduction of this error are shown. How many representative periods are needed to fully capture the variability is then investigated. For a sample dataset, a scenario-robust aggregation of hourly (8760) resolution is possible in the order of 10 representative hours when electricity demand is the only source of variability. The inclusion of wind and solar supply variability increases the resolution of the robust aggregation to the order of 1000. A similar scale of expansion is shown for representative days and weeks. These concepts can be applied to any such temporal dataset, providing, at the least, a benchmark that any other aggregation method can aim to emulate. Finally, how prior information about peak pricing hours can potentially reduce resolution further is also discussed.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Ellipsometric Analysis of Contaminant Layer on Optical Witness Samples from MISSE

Several optical witness samples included in the Materials for International Space Station Experiment (MISSE) trays have been analyzed with a variable angle spectroscopic ellipsometer or VASE. Witness samples of gold or platinum mirrors are extremely useful as collectors of space-borne contamination, due to the relative inertness of these noble metals in the atomic oxygen-rich environment of LEO. Highly accurate thickness measurements, typically at the sub-nanometer scale, may be achieved with this method, which uses polarized light in a spectral range of 300 to 1300 nanometers at several angles of incidence to the sample surface.

Norwood, Joseph K.↗

An independent analysis of bias sources and variability in wind plant pre-construction energy yield estimation methods

The wind resource assessment community has long had the goal of reducing the bias between wind plant pre-construction energy yield assessment (EYA) and the observed annual energy production (AEP). This comparison is typically made between the 50% probability of exceedance (P50) value of the EYA and the long-term corrected operational AEP (hereafter OA P50), and is known as the P50 bias. The industry has critically lacked an independent analysis of bias reduction investigated across multiple consultants to identify the greatest sources of uncertainty and variance in the EYA process and the best opportunities for uncertainty reduction. The present study addresses this gap by benchmarking consultant methodologies against each other and against operational data at a scale not seen before in industry collaborations. We consider data from 10 wind plants and evaluate discrepancies between eight consultancies in the steps taken from estimates of gross to net energy. Consultants tend to overestimate the gross energy produced at the turbines and then compensate by further overestimating downstream losses, leading to a mean P50 bias near zero, still with significant variability among the individual wind plants. Within our data sample, we find that consultant estimates of all loss categories, except environmental losses, tend to reduce the project-to-project variability of the P50 bias. The disagreement between consultants, however, remains flat throughout the addition of losses. Finally, we find that differences in consultants’ estimates of project performance can lead to differences up to $10/MWh in the levelized cost of energy for a wind plant.

Todd, Austin C.↗