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At least 1,657 records · Page 92

Understanding aerosol properties in convective outflows during TRACER

Convective outflow boundaries commonly form across the southeastern U.S., often originating from storms initiated along sea-breeze fronts. As outflows spread, merge, and collide, they frequently trigger secondary convection in air masses already modified by primary storm outflow. This resulting air mass carries a distinctive aerosol population, which can influence the development of secondary convective cells. During the U.S. DOE TRACER field campaign in summer 2022, we investigated how outflows affect aerosol size, composition, and hygroscopicity across Greater Houston, Texas. Using a novel detection algorithm, we identified and verified 72 outflow boundaries from surface meteorological observations. In the relatively simple continental environment northwest of Houston, a common relationship emerged between CCN-inferred hygroscopicity (κ) and size-resolved aerosol concentrations. The κ of aerosols typically decreased in size ranges where aerosol concentrations increased following outflow passage and increased where concentrations decreased. In contrast, at the Atmospheric Radiation Measurement’s (ARM) fixed site in La Porte, Texas, the aerosol response depended on outflow direction, shaped by concentrated industrial and shipping activity to the north and south/southeast along the Houston Ship Channel. Concurrent size distribution and composition changes suggested case-specific variability in κ, with either reinforcing or offsetting effects. Outflows passing over industrial/shipping sectors often promoted less hygroscopic aerosol populations while cleaner residential outflows often favored more hygroscopic aerosol populations. These results highlight key aerosol changes following outflow passage, providing a foundation for improved understanding of aerosol-cloud interactions related to secondary convection initiation along or in the wake of outflow boundaries.

Thompson, Seth A. [Texas A & M Univ., College Stat↗

CoreCruncher : Fast and Robust Construction of Core Genomes in Large Prokaryotic Data Sets

The core genome represents the set of genes shared by all, or nearly all, strains of a given population or species of prokaryotes. Inferring the core genome is integral to many genomic analyses, however, most methods rely on the comparison of all the pairs of genomes; a step that is becoming increasingly difficult given the massive accumulation of genomic data. Here, we present CoreCruncher; a program that robustly and rapidly constructs core genomes across hundreds or thousands of genomes. CoreCruncher does not compute all pairwise genome comparisons and uses a heuristic based on the distributions of identity scores to classify sequences as orthologs or paralogs/xenologs. Although it is much faster than current methods, our results indicate that our approach is more conservative than other tools and less sensitive to the presence of paralogs and xenologs. CoreCruncher is freely available from: https://github.com/lbobay/CoreCruncher. CoreCruncher is written in Python 3.7 and can also run on Python 2.7 without modification. It requires the python library Numpy and either Usearch or Blast. Certain options require the programs muscle or mafft.

59 BASIC BIOLOGICAL SCIENCES↗

The violent side of mare volcanism

In the past 15 years it has become increasingly evident that lunar pyroclastic volcanism played an important role in the formation and resurfacing of portions of the Moon. Located on mare/highland boundaries, many of these deposits formed in association with mare volcanism. Based on recently acquired geologic and remote sensing data, two generally distinct types of pyroclastic mantling deposits have been identified: regional and localized. Both the regional dark mantling deposits (RDMD) and localized dark mantling deposits (LDMD) are widely distributed across the lunar nearside. The larger RDMD are typically located in lunar highland areas adjacent to many of the major lunar maria, while the smaller LDMD are found on the floors of pre-Imbrian and Inbrian craters. Both deposits are basaltic in composition and are presumed to have originated at great depth (approx. 300 km). The composition, geometry, and vent morphology of the pyroclastic deposits have been used to infer the eruption mechanisms and emplacement styles for both types of deposits.

Coombs, Cassandra R.↗

Evidence for a high temperature differentiation in a molten earth: A preliminary appraisal

If the earth were molten during its later stages of accretion as indicated by the present understanding of planetary accretion process, the differentiation that led to the formation of the core and mantle must have occurred at high temperatures in the range of 3000-5000 K because of the effect of pressure on the temperature of melting in the interior of the earth. This calls into question the use of low-temperature laboratory measurements of partition coefficients of trace elements to make inferences about earth accretion and differentiation. The low temperature partition coefficients cannot be directly applied to high temperature fractionations because partition coefficients refer to an equilibrium specific to a temperature for a given reaction, and must change in some proportion to exp 1/RT. There are no laboratory data on partition coefficients at the high temperatures relevant to differentiation in the interior of the earth, and an attempt to estimate high temperature distribution coefficients of siderophile elements was made by considering the chemical potential of a given element at equilibrium and how this potential changes with temperature, under some specific assumptions.

Murthy, V. Rama↗

Rare earth element transport in the western North Atlantic inferred from Nd isotopic observations

The relationship between the Nd isotopic composition in the Atlantic waters and the origin and circulation of the water masses was investigated. Samples were collected in the western North Atlantic between 7 and 54 deg N. The isotopic composition (Nd-143/Nd-144 ratios) showed extensive vertical structure at all locations. In regions where a thermocline was well-developed, large isotopic shifts were observed across the base of the thermocline, while regions without a thermocline were characterized by much more gradual shifts in isotopic composition with depth. The data reveal an excellent correlation between the Nd isotopic distribution in the western North Atlantic water column and the distribution of water masses identified from temperature and salinity measurements.

Piepgras, D. J.↗

On the quantification and efficient propagation of imprecise probabilities with copula dependence

This paper addresses the problem of quantification and propagation of uncertainties associated with dependence modeling when data for characterizing probability models are limited. Practically, the system inputs are often assumed to be mutually independent or correlated by a multivariate Gaussian distribution. However, this subjective assumption may introduce bias in the response estimate if the real dependence structure deviates from this assumption. In this work, we overcome this limitation by introducing a flexible copula dependence model to capture complex dependencies. Here, a hierarchical Bayesian multimodel approach is proposed to quantify uncertainty in dependence model-form and model parameters that result from small data sets. This approach begins by identifying, through Bayesian multimodel inference, a set of candidate marginal models and their corresponding model probabilities, and then estimating the uncertainty in the copula-based dependence structure, which is conditional on the marginals and their parameters. The overall uncertainties integrating marginals and copulas are probabilistically represented by an ensemble of multivariate candidate densities. A novel importance sampling reweighting approach is proposed to efficiently propagate the overall uncertainties through a computational model. Through an example studying the influence of constituent properties on the out-of-plane properties of transversely isotropic E-glass fiber composites, we show that the composite property with copula-based dependence model converges to the true estimate as data set size increases, while an independence or arbitrary Gaussian correlation assumption leads to a biased estimate.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Adaptive stabilization of quantum circuits executed on unstable devices

Conventional computers have evolved to device components that demonstrate failure rates of 10 −17 or less, while current quantum computing devices typically exhibit error rates of 10 −2 or greater. This raises concerns about the reliability and reproducibility of the results obtained from quantum computers. The problem is highlighted by experimental observation that today’s NISQ devices are inherently unstable. Remote quantum cloud servers typically do not provide users with an ability to calibrate the device themselves. Using inaccurate characterization data for error mitigation can have devastating impact on reproducibility. In this study, we investigate if one can infer the critical channel parameters dynamically from the noisy binary output of the executed quantum circuit and use it to improve program stability. An open question however is how well does this methodology scale. We discuss the efficacy and efficiency of our adaptive algorithm using canonical quantum circuits such as the uniform superposition circuit. Our metric of performance is the Hellinger distance between the post-stabilization observations and the reference (ideal) distribution.

Dasgupta, Samudra↗

A New Field Instrument for Leaf Volatiles Reveals an Unexpected Vertical Profile of Isoprenoid Emission Capacities in a Tropical Forest

Both plant physiology and atmospheric chemistry are substantially altered by the emission of volatile isoprenoids (VI), such as isoprene and monoterpenes, from plant leaves. Yet, since gaining scientific attention in the 1950’s, empirical research on leaf VI has been largely confined to laboratory experiments and atmospheric observations. Here, we introduce a new field instrument designed to bridge the scales from leaf to atmosphere, by enabling precision VI detection in real time from plants in their natural ecological setting. With a field campaign in the Brazilian Amazon, we reveal an unexpected distribution of leaf emission capacities (EC) across the vertical axis of the forest canopy, with EC peaking in the mid-canopy instead of the sun-exposed canopy surface, and moderately high emissions occurring in understory specialist species. Compared to the simple interpretation that VI protect leaves from heat stress at the hot canopy surface, our results encourage a more nuanced view of the adaptive role of VI in plants. We infer that forest emissions to the atmosphere depend on the dynamic microenvironments imposed by canopy structure, and not simply on canopy surface conditions. We provide a new emissions inventory from 52 tropical tree species, revealing moderate consistency in EC within taxonomic groups. We highlight priorities in leaf volatiles research that require field-portable detection systems. Our self-contained, portable instrument provides real-time detection and live measurement feedback with precision and detection limits better than 0.5 nmol VI m -2 leaf s -1 . We call the instrument ‘PORCO’ based on the gas detection method: photoionization of organic compounds. We provide a thorough validation of PORCO and demonstrate its capacity to detect ecologically driven variation in leaf emission rates and thus accelerate a nascent field of science: the ecology and ecophysiology of plant volatiles.

54 ENVIRONMENTAL SCIENCES↗

Pioneer-Venus radio occultation (ORO) data reduction: Profiles of 13 cm absorptivity

In order to characterize possible variations in the abundance and distribution of subcloud sulfuric acid vapor, 13 cm radio occultation signals from 23 orbits that occurred in late 1986 and 1987 (Season 10) and 7 orbits that occurred in 1979 (Season 1) were processed. The data were inverted via inverse Abel transform to produce 13 cm absorptivity profiles. Pressure and temperature profiles obtained with the Pioneer-Venus night probe and the northern probe were used along with the absorptivity profiles to infer upper limits for vertical profiles of the abundance of gaseous H2SO4. In addition to inverting the data, error bars were placed on the absorptivity profiles and H2SO4 abundance profiles using the standard propagation of errors. These error bars were developed by considering the effects of statistical errors only. The profiles show a distinct pattern with regard to latitude which is consistent with latitude variations observed in data obtained during the occultation seasons nos. 1 and 2. However, when compared with the earlier data, the recent occultation studies suggest that the amount of sulfuric acid vapor occurring at and below the main cloud layer may have decreased between early 1979 and late 1986.

Steffes, Paul G.↗

The atmospheric CH4 increase since the Last Glacial Maximum. I - Source estimates

An estimate of the distribution of wetland area and associated CH4 emission is presented for the Last Glacial Maximum (LGM, 18 kyr BP, kiloyear Before Present) and the Pre-Industrial Holocene (PIH, 9000-200 years BP). The wetland source, combined with estimates of the other biogenic sources and sink, yields total source strengths of 120 and 180 Tg CH4/yr for LGM and PIH respectively. These source strengths are shown to be consistent with source estimates inferred from a photochemical model, and point to changes in wetland CH4 source as a major factor driving the atmospheric CH4 increase from LGM to PIH.

Chappellaz, Jerome A.↗

Probabilistic inference in very large universes

Our current favored cosmological theories allow for the striking and controversial possibility that the observable universe is just a small part of a much larger universe in which parameters that describe the effective, low-energy laws of physics vary from one region to another. The controversy is largely driven by the fact that such a “very large universe” is mostly observationally inaccessible to us, so the issue arises of how we can reasonably assess a theory that describes such a universe. In this paper, we propose a Bayesian method for theory assessment based on theory-generated probability distributions for our observations. We focus on the principles that define this method, leaving aside concerns about how, in practice, one would carry out the required calculations. (One important issue that we set aside is the measure problem.) We argue that cosmological theories can be tested by the standard method of Bayesian updating, but we need to use theoretical predictions for “first-person” probabilities—that is, probabilities that we should use for our observations, taking into account all relevant selection effects. These selection effects can vary from one observer to another and can vary with time, so, in principle, first-person probabilities are defined for each observer instant—an observer at a specific instant of time. Calculations of first-person probabilities should take into account everything that the observer believes about herself and her surroundings, which we refer to as her subjective state. If the universe is very large, a theory might predict that there are many observer instants in the same subjective state; we argue that first-person probabilities should be calculated using a principle of self-locating indifference (PSLI), the assumption that any real observer should make predictions for her future as if she were chosen randomly and uniformly from the theoretically predicted observer instants that share her subjective state. We believe the PSLI is intuitively very reasonable, but we also argue that, if the theory is correct, the use of this principle maximizes the expected fraction of observers who will make correct predictions. A further complication is that cosmological theories are not expected to fully predict the detailed properties of the universe, but rather will predict a set of possible universes, each with a probability. Different possible universes will generically have different numbers of observers. We argue that, in the calculation of first-person probabilities, the probability for each possible universe should be weighted by the number of observer instants in the specified subjective state that it contains. These issues have been controversial in the literature, so we also provide a rebuttal to the claim that principles like the PSLI involve a “selection fallacy”; a rebuttal to what we dub the principle of required certainty; an argument rejecting theories that predict a preponderance of Boltzmann brains; a rebuttal to a parable about humans and Jovians used by Hartle and Srednicki to argue that assumptions of typicality can lead to absurd consequences; and, finally, a discussion about how the use of “old evidence” can be fit into a Bayesian mold.

Azhar, Feraz [University of Notre Dame, IN (United↗

The vertical distribution of Mars water vapor

Analysis of observations made from the Viking 1 Orbiter indicates that the water vapor over the Viking 1 landing site is uniformly mixed with the atmosphere and not concentrated near the surface. The analysis incorporates the effects of atmospheric scattering and explains why previous earth-based observations showed a strong diurnal variation in water content. It also explains the lack of an early morning fog and removes the necessity of daily exchange of large amounts of water between the surface and the atmosphere. A water vapor volume mixing ratio of 1.5 x 10 to the -4th is inferred for the Viking 1 site in late summer.

Davies, D. W.↗

Tectonic motions in California inferred from very long baseline interferometry observations, 1980-1984

Using VLBI, three baselines of 150-300 km length within California, and three baselines of 1500 km length between California and Texas, measured between 1980 and 1984, have been fitted to a steady plane/strain rotation model. The observed rate of displacement across the southern San Andreas fault is in agreement with other contemporary rate estimates near 3 cm/yr. Discrepancies between these rates and indicators of relative plate motion near 6 cm/yr seem to be related to local departures of the San Andreas system from the expected strike of the plate boundary. Results support a regional distribution of elastic strain that is offset in about the same sense and amount as the Big Bend of the San Andreas fault, and finite element simulations suggest that tractions on the base of the crust that accompany mantle downswelling beneath the Transverse Ranges could contribute to these strain inhomogeneities.

Lyzenga, Gregory A.↗

Mitigation of spatial nonstationarity with vision transformers

Spatial nonstationarity, the location variance of features’ statistical distributions, is ubiquitous in many natural settings. For example, in geological reservoirs rock matrix porosity varies vertically due to geomechanical compaction trends, in mineral deposits grades vary due to sedimentation and concentration processes, in hydrology rainfall varies due to the atmosphere and topography interactions, and in metallurgy crystalline structures vary due to differential cooling. Conventional geostatistical modeling workflows rely on the assumption of stationarity to be able to model spatial features for geostatistical inference. Nevertheless, this is often not a realistic assumption when dealing with nonstationary spatial data and this has motivated a variety of nonstationary spatial modeling workflows such as trend and residual decomposition, cosimulation with secondary features, and spatial segmentation and independent modeling over stationary subdomains. The advent of deep learning technologies has enabled new workflows for modeling spatial relationships. However, there is a paucity of demonstrated best practice and general guidance on mitigation of spatial nonstationarity with deep learning in the geospatial context. We demonstrate the impact of two common types of geostatistical spatial nonstationarity on deep learning model prediction performance and propose the mitigation of such impacts using self-attention (vision transformer) models. We demonstrate the utility of vision transformers for the mitigation of nonstationarity with relative errors as low as 10%, exceeding the performance of alternative deep learning methods such as convolutional neural networks. We establish best practice by demonstrating the ability of self-attention networks for modeling large-scale spatial relationships in the presence of commonly observed geospatial nonstationarity.

58 GEOSCIENCES↗

Informed total-error-minimizing priors: Interpretable cosmological parameter constraints despite complex nuisance effects

While Bayesian inference techniques are standard in cosmological analyses, it is common to interpret resulting parameter constraints with a frequentist intuition. This intuition can fail, for example, when marginalizing high-dimensional parameter spaces onto subsets of parameters, because of what has come to be known as projection effects or prior volume effects. We present the method of informed total-error-minimizing (ITEM) priors to address this problem. An ITEM prior is a prior distribution on a set of nuisance parameters, such as those describing astrophysical or calibration systematics, intended to enforce the validity of a frequentist interpretation of the posterior constraints derived for a set of target parameters (e.g., cosmological parameters). Our method works as follows. For a set of plausible nuisance realizations, we generate target parameter posteriors using several different candidate priors for the nuisance parameters. We reject candidate priors that do not accomplish the minimum requirements of bias (of point estimates) and coverage (of confidence regions among a set of noisy realizations of the data) for the target parameters on one or more of the plausible nuisance realizations. Of the priors that survive this cut, we select the ITEM prior as the one that minimizes the total error of the marginalized posteriors of the target parameters. As a proof of concept, we applied our method to the density split statistics measured in Dark Energy Survey Year 1 data. We demonstrate that the ITEM priors substantially reduce prior volume effects that otherwise arise and that they allow for sharpened yet robust constraints on the parameters of interest.

79 ASTRONOMY AND ASTROPHYSICS↗

Projecting Future Energy Production from Operating Wind Farms in North America. Part I: Dynamical Downscaling

Abstract New simulations at 12-km grid spacing with the Weather and Research Forecasting (WRF) Model nested in the MPI Earth System Model (ESM) are used to quantify possible changes in wind power generation potential as a result of global warming. Annual capacity factors (CF; measures of electrical power production) computed by applying a power curve to hourly wind speeds at wind turbine hub height from this simulation are also used to illustrate the pitfalls in seeking to infer changes in wind power generation directly from low-spatial-resolution and time-averaged ESM output. WRF-derived CF are evaluated using observed daily CF from operating wind farms. The spatial correlation coefficient between modeled and observed mean CF is 0.65, and the root-mean-square error is 5.4 percentage points. Output from the MPI-WRF Model chain also captures some of the seasonal variability and the probability distribution of daily CF at operating wind farms. Projections of mean annual CF (CF A ) indicate no change to 2050 in the southern Great Plains and Northeast. Interannual variability of CF A increases in the Midwest, and CF A declines by up to 2 percentage points in the northern Great Plains. The probability of wind droughts (extended periods with anomalously low production) and wind bonus periods (high production) remains unchanged over most of the eastern United States. The probability of wind bonus periods exhibits some evidence of higher values over the Midwest in the 2040s, whereas the converse is true over the northern Great Plains. Significance Statement Wind energy is playing an increasingly important role in low-carbon-emission electricity generation. It is a “weather dependent” renewable energy source, and thus changes in the global atmosphere may cause changes in regional wind power production (PP) potential. We use PP data from operating wind farms to demonstrate that regional simulations exhibit skill in capturing actual power production. Projections to the middle of this century indicate that over most of North America east of the Rocky Mountains annual expected PP is largely unchanged, as is the probability of extended periods of anomalously high or low production. Any small declines in annual PP are of much smaller magnitude than changes due to technological innovation over the last two decades.

Meteorology & Atmospheric Sciences↗

Hyperdimensional Imaging Contrast Using an Optical Fiber

Fluorescence properties of a molecule can be used to study the structural and functional nature of biological processes. Physical properties, including fluorescence lifetime, emission spectrum, emission polarization, and others, help researchers probe a molecule, produce desired effects, and infer causes and consequences. Correlative imaging techniques such as hyperdimensional imaging microscopy (HDIM) combine the physical properties and biochemical states of a fluorophore. Here we present a fiber-based imaging system that can generate hyper-dimensional contrast by combining multiple fluorescence properties into a single fluorescence lifetime decay curve. Fluorescence lifetime imaging microscopy (FLIM) with controlled excitation polarization and temporally dispersed emission can generate a spectrally coded, polarization-filtered lifetime distribution for a pixel. This HDIM scheme generates a better contrast between different molecules than that from individual techniques. This setup uses only a single detector and is simpler to implement, modular, cost-efficient, and adaptable to any existing FLIM microscope. We present higher contrast data from Arabidopsis thaliana epidermal cells based on intrinsic anthocyanin emission properties under multiphoton excitation. This work lays the foundation for an alternative hyperdimensional imaging system and demonstrates that contrast-based imaging is useful to study cellular heterogeneity in biological samples.

47 OTHER INSTRUMENTATION↗

An Estimate of the Likelihood for a Climatically Significant Volcanic Eruption Within the Present Decade (2000-2009)

Since 1750, the number of cataclysmic volcanic eruptions (i.e., those having a volcanic explosivity index, or VEI, equal to 4 or larger) per decade is found to span 2-11, with 96% located in the tropics and extra-tropical Northern Hemisphere, A two-point moving average of the time series has higher values since the 1860s than before, measuring 8.00 in the 1910s (the highest value) and measuring 6.50 in the 1980s, the highest since the 18 1 0s' peak. On the basis of the usual behavior of the first difference of the two-point moving averages, one infers that the two-point moving average for the 1990s will measure about 6.50 +/- 1.00, implying that about 7 +/- 4 cataclysmic volcanic eruptions should be expected during the present decade (2000-2009). Because cataclysmic volcanic eruptions (especially, those having VEI equal to 5 or larger) nearly always have been associated with episodes of short-term global cooling, the occurrence of even one could ameliorate the effects of global warming. Poisson probability distributions reveal that the probability of one or more VEI equal to 4 or larger events occurring within the next ten years is >99%, while it is about 49% for VEI equal to 5 or larger events and 18% for VEI equal to 6 or larger events. Hence, the likelihood that a, climatically significant volcanic eruption will occur within the next 10 years appears reasonably high.

Wilson, Robert M.↗