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At least 811 records · Page 45

Sensitivities of Large Eddy Simulations of Aerosol Plume Transport and Cloud Response

Abstract Cloud responses to surface‐based sources of aerosol perturbation partially depend on how turbulent transport of the aerosol to cloud base affects the spatial and temporal distribution of aerosol. Here, scenarios of plume injection below a marine stratocumulus cloud are modeled using large eddy simulations coupled to a prognostic bulk aerosol and cloud microphysics scheme. Both passive plumes, consisting of an inert tracer, and active plumes are investigated, where the latter are representative of saltwater droplet plumes such as have been proposed for marine cloud brightening. Passive plume scenarios show higher in‐plume cloud brightness (relative to out‐of‐plume) due to the predominant transport of the passive plume tracer from the near‐surface to the cloud layer within updrafts. These updrafts rise into brighter areas within the cloud deck, even in the absence of an aerosol perturbation associated with an active plume. Comparing albedo at in‐plume to out‐of‐plume locations associates the inert plume with the brightest cloud locations, without any causal effect of the plume on the cloud. Numerical sensitivities are first assessed to establish a suitable model configuration. Then sensitivity to particle injection rate is investigated. Trade‐offs are identified between the number of injected particles and the suppressive effect of droplet evaporation on plume loft and spread. Furthermore, as the near‐field in‐plume brightening effect does not depend significantly on injection rate given a suitable definition of perturbed versus unperturbed regions of the flow, plume area is a key controlling factor on the overall cloud brightening effect of an aerosol perturbation.

54 ENVIRONMENTAL SCIENCES↗

Navigating the Noise: Bringing Clarity to ML Parameterization Design With O $\boldsymbol{\mathcal{O}}$(100) Ensembles

Abstract Machine‐learning (ML) parameterizations of subgrid processes (here of turbulence, convection, and radiation) may one day replace conventional parameterizations by emulating high‐resolution physics without the cost of explicit simulation. However, uncertainty about the relationship between offline and online performance (i.e., when integrated with a large‐scale general circulation model) hinders their development. Much of this uncertainty stems from limited sampling of the noisy, emergent effects of upstream ML design decisions on downstream online hybrid simulation. Our work rectifies the sampling issue via the construction of a semi‐automated, end‐to‐end pipeline for size ensembles of hybrid simulations, revealing important nuances in how systematic reductions in offline error manifest in changes to online error and online stability. For example, removing dropout and switching from a Mean Squared Error to a Mean Absolute Error loss both reduce offline error, but they have opposite effects on online error and online stability. Other design decisions, like incorporating memory, converting moisture input from specific humidity to relative humidity, using batch normalization, and training on multiple climates do not come with any such compromises. Finally, we show that ensemble sizes of may be necessary to reliably detect causally relevant differences online. By enabling rapid online experimentation at scale, we can empirically settle debates regarding subgrid ML parameterization design that would have otherwise remained unresolved in the noise.

Lin, Jerry [Department of Earth System Sciences Un↗

Overview of the Nephele Perturbed Parameter Ensemble for Aerosol‐Cloud Interactions in E3SMv3

Aerosol-cloud interactions (aci) are the leading source of uncertainty in inferring climate sensitivity from the historical record. Earth system models (ESMs) struggle to represent aci because the processes responsible for these phenomena occur at much finer time and space scales than can be resolved by any ESM. Observational constraints provide key benchmarks to test ESMs, but cannot be used alone to fully understand aci processes except in very specific cases where causality is controlled; some degree of modeling is required to infer aci and estimate radiative forcing. Here, we generate and characterize a perturbed parameter ensemble (PPE) in version 3 of the Energy Exascale ESM (E3SMv3). We perturb 25 parameters that govern aci processes over 250 members and integrate the model over present-day and preindustrial aerosol emissions. We find that the process representation in E3SMv3 is flexible and can generate global-mean effective radiative forcings due to aci (ERFaci) ranging from −3.0 to +0.9 W m −2 . The positive ERFaci values simulated by a portion of the PPE are implausible and result from parameter combinations that produce unrealistic top-of-atmosphere energy fluxes. While global-mean cloud droplet number concentration always increases in response to anthropogenic aerosol, cloud liquid water path can both increase and decrease, suggesting that precipitation suppression is not the only aerosol-cloud adjustment represented by E3SMv3. Analysis of which processes control liquid cloud adjustment in the PPE points toward stratiform precipitation processes and aerosol activation, which is consistent with many previous ESMs, as well as the new two-moment convective cloud microphysics in E3SMv3.

Nugent, Jacqueline M. [Univ. of Wyoming, Laramie, ↗

Computational evaluation of exome sequence data using human and model organism phenotypes improves diagnostic efficiency

Purpose: Medical diagnosis and molecular or biochemical confirmation typically rely on the knowledge of the clinician. Although this is very difficult in extremely rare diseases, we hypothesized that the recording of patient phenotypes in Human Phenotype Ontology (HPO) terms and computationally ranking putative disease-associated sequence variants improves diagnosis, particularly for patients with atypical clinical profiles. Methods: Using simulated exomes and the National Institutes of Health Undiagnosed Diseases Program (UDP) patient cohort and associated exome sequence, we tested our hypothesis using Exomiser. Exomiser ranks candidate variants based on patient phenotype similarity to (i) known disease–gene phenotypes, (ii) model organism phenotypes of candidate orthologs, and (iii) phenotypes of protein– protein association neighbors. Results: Benchmarking showed Exomiser ranked the causal variant as the top hit in 97% of known disease–gene associations and ranked the correct seeded variant in up to 87% when detectable disease–gene associations were unavailable. Using UDP data, Exomiser ranked the causative variant(s) within the top 10 variants for 11 previously diagnosed variants and achieved a diagnosis for 4 of 23 cases undiagnosed by clinical evaluation. Conclusion: Structured phenotyping of patients and computational analysis are effective adjuncts for diagnosing patients with genetic disorders.

semantic comparison↗

Reconciling justice and attribution research to advance climate policy

The Paris Climate Agreement is an important step for international climate policy, but the compensation for negative effects of climate change based on clear assignment of responsibilities remains highly debated. From both a policy and a science perspective, it is unclear how responsibilities should be defined and on what evidence base. We explore different normative principles of justice relevant to climate change impacts, and ask how different forms of causal evidence of impacts drawn from detection and attribution research could inform policy approaches in accordance with justice considerations. Here, we reveal a procedural injustice based on the imbalance of observations and knowledge of impacts between developed and developing countries. This type of injustice needs to be considered in policy negotiations and decisions, and efforts strengthened to reduce it.

54 ENVIRONMENTAL SCIENCES↗

Avalanching strain dynamics during the hydriding phase transformation in individual palladium nanoparticles

Phase transitions in reactive environments are crucially important in energy and information storage, catalysis and sensors. Nanostructuring active particles can yield faster charging/ discharging kinetics, increased lifespan and record catalytic activities. However, establishing the causal link between structure and function is challenging for nanoparticles, as ensemble measurements convolve intrinsic single-particle properties with sample diversity. Here we study the hydriding phase transformation in individual palladium nanocubes in situ using coherent X-ray diffractive imaging. The phase transformation dynamics, which involve the nucleation and propagation of a hydrogen-rich region, are dependent on absolute time (aging) and involve intermittent dynamics (avalanching). A hydrogen-rich surface layer dominates the crystal strain in the hydrogen-poor phase, while strain inversion occurs at the cube corners in the hydrogen-rich phase. A three-dimensional phase-field model is used to interpret the experimental results. In conclusion, our experimental and theoretical approach provides a general framework for designing and optimizing phase transformations for single nanocrystals in reactive environments.

36 MATERIALS SCIENCE↗

Fluorescence intermittency originates from reclustering in two-dimensional organic semiconductors

Fluorescence intermittency or blinking is observed in nearly all nanoscale fluorophores. It is characterized by universal power-law distributions in on- and off-times as well as 1/f behaviour in corresponding emission power spectral densities. Blinking, previously seen in confined zero- and one-dimensional systems has recently been documented in two-dimensional reduced graphene oxide. Here we show that unexpected blinking during graphene oxide-to-reduced graphene oxide photoreduction is attributed, in large part, to the redistribution of carbon sp 2 domains. This reclustering generates fluctuations in the number/size of emissive graphenic nanoclusters wherein multiscale modelling captures essential experimental aspects of reduced graphene oxide’s absorption/emission trajectories, while simultaneously connecting them to the underlying photochemistry responsible for graphene oxide’s reduction. These simulations thus establish causality between currently unexplained, long timescale emission intermittency in a quantum mechanical fluorophore and identifiable chemical reactions that ultimately lead to switching between on and off states.

36 MATERIALS SCIENCE↗

The selective pressures on the microbial community in a metal-contaminated aquifer

Abstract In many environments, toxic compounds restrict which microorganisms persist. However, in complex mixtures of inhibitory compounds, it is challenging to determine which specific compounds cause changes in abundance and prevent some microorganisms from growing. We focused on a contaminated aquifer in Oak Ridge, Tennessee, USA that has large gradients of pH and widely varying concentrations of uranium, nitrate, and many other inorganic ions. In the most contaminated wells, the microbial community is enriched in the Rhodanobacter genus. Rhodanobacter abundance is positively correlated with low pH and high concentrations of uranium and 13 other ions and we sought to determine which of these ions are selective pressures that favor the growth of Rhodanobacter over other taxa. Of these ions, low pH and high UO22+, Mn2+, Al3+, Cd2+, Zn2+, Co2+, and Ni2+ are both (a) selectively inhibitory of a Pseudomonas isolate from an uncontaminated well vs. a Rhodanobacter isolate from a contaminated well, and (b) reach toxic concentrations (for the Pseudomonas isolate) in the Rhodanobacter-dominated wells. We used mixtures of ions to simulate the groundwater conditions in the most contaminated wells and verified that few isolates aside from Rhodanobacter can tolerate these eight ions. These results clarify which ions are likely causal factors that impact the microbial community at this field site and are not merely correlated with taxonomic shifts. Furthermore, our general high-throughput approach can be applied to other environments, isolates, and conditions to systematically help identify selective pressures on microbial communities.

59 BASIC BIOLOGICAL SCIENCES↗

Forest tree growth is linked to mycorrhizal fungal composition and function across Europe

Most trees form symbioses with ectomycorrhizal fungi (EMF) which influence access to growth-limiting soil resources. Mesocosm experiments repeatedly show that EMF species differentially affect plant development, yet whether these effects ripple up to influence the growth of entire forests remains unknown. Here we tested the effects of EMF composition and functional genes relative to variation in well-known drivers of tree growth by combining paired molecular EMF surveys with high-resolution forest inventory data across 15 European countries. We show that EMF composition was linked to a three-fold difference in tree growth rate even when controlling for the primary abiotic drivers of tree growth. Fast tree growth was associated with EMF communities harboring high inorganic but low organic nitrogen acquisition gene proportions and EMF which form contact versus medium-distance fringe exploration types. These findings suggest that EMF composition is a strong bio-indicator of underlying drivers of tree growth and/or that variation of forest EMF communities causes differences in tree growth. While it may be too early to assign causality or directionality, our study is one of the first to link fine-scale variation within a key component of the forest microbiome to ecosystem functioning at a continental scale.

54 ENVIRONMENTAL SCIENCES↗

Structure-guided design of pure orthosteric inhibitors of αIIbβ3 that prevent thrombosis but preserve hemostasis

A prevailing dogma is that inhibition of vascular thrombosis by antagonizing platelet integrin αIIbβ3 cannot be achieved without compromising hemostasis, thus causing serious bleeding and increased morbidity and mortality. It is speculated that these adverse outcomes result from drug-induced activating conformational changes in αIIbβ3 but direct proof is lacking. Here, we report the structure-guided design of peptide Hr10 and a modified form of the partial agonist drug tirofiban that act as “pure” antagonists of αIIbβ3, i.e., they no longer induce the conformational changes in αIIbβ3. Both agents inhibit human platelet aggregation but preserve clot retraction. Hr10 and modified tirofiban are as effective as partial agonist drugs in inhibiting vascular thrombosis in humanized mice, but neither causes serious bleeding, establishing a causal link between partial agonism and impaired hemostasis. Pure orthosteric inhibitors of αIIbβ3 may thus provide safer alternatives for human therapy, and valuable tools to probe structure–activity relationships in integrins.

60 APPLIED LIFE SCIENCES↗

Laboratory measurements of the physics of auroral electron acceleration by Alfvén waves

While the aurora has attracted attention for millennia, important questions remain unanswered. Foremost is how auroral electrons are accelerated before colliding with the ionosphere and producing auroral light. Powerful Alfvén waves are often found traveling Earthward above auroras with sufficient energy to generate auroras, but there has been no direct measurement of the processes by which Alfvén waves transfer their energy to auroral electrons. Here, we show laboratory measurements of the resonant transfer of energy from Alfvén waves to electrons under conditions relevant to the auroral zone. Experiments are performed by launching Alfvén waves and simultaneously recording the electron velocity distribution. Numerical simulations and analytical theory support that the measured energy transfer process produces accelerated electrons capable of reaching auroral energies. The experiments, theory, and simulations demonstrate a clear causal relationship between Alfvén waves and accelerated electrons that directly cause auroras.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Effect of specific non-pharmaceutical intervention policies on SARS-CoV-2 transmission in the counties of the United States

Non-pharmaceutical interventions (NPIs) remain the only widely available tool for controlling the ongoing SARS-CoV-2 pandemic. We estimated weekly values of the effective basic reproductive number (R eff ) using a mechanistic metapopulation model and associated these with county-level characteristics and NPIs in the United States (US). Interventions that included school and leisure activities closure and nursing home visiting bans were all associated with a median R eff below 1 when combined with either stay at home orders (median R eff 0.97, 95% confidence interval (CI) 0.58–1.39) or face masks (median R eff 0.97, 95% CI 0.58–1.39). While direct causal effects of interventions remain unclear, our results suggest that relaxation of some NPIs will need to be counterbalanced by continuation and/or implementation of others.

60 APPLIED LIFE SCIENCES↗

Major proliferation of transposable elements shaped the genome of the soybean rust pathogen Phakopsora pachyrhizi

With >7000 species the order of rust fungi has a disproportionately large impact on agriculture, horticulture, forestry and foreign ecosystems. The infectious spores are typically dikaryotic, a feature unique to fungi in which two haploid nuclei reside in the same cell. A key example is Phakopsora pachyrhizi, the causal agent of Asian soybean rust disease, one of the world’s most economically damaging agricultural diseases. Despite P. pachyrhizi’s impact, the exceptional size and complexity of its genome prevented generation of an accurate genome assembly. Here, we sequence three independent P. pachyrhizi genomes and uncover a genome up to 1.25 Gb comprising two haplotypes with a transposable element (TE) content of ~93%. We study the incursion and dominant impact of these TEs on the genome and show how they have a key impact on various processes such as host range adaptation, stress responses and genetic plasticity.

59 BASIC BIOLOGICAL SCIENCES↗

Electronic signatures of Lorentzian dynamics and charge fluctuations in lithiated graphite structures

Lithium graphite intercalation compounds (Li-GICs) are essential materials for modern day portable electronics and obtaining insights into their atomic structure and thermodynamics is of fundamental interest. Here we explore the electronic and atomic states of Li-GICs at varying degrees of Lithium loading (i.e., “staging”) by means of ab-initio molecular dynamics simulations and simulated X-ray adsorption spectroscopy (XAS). We analyze the atomic correlation functions and shows that the enhancements of the Li-ion entropy with increased staging result from Lorentzian lithium-ion dynamics and charge fluctuations, which activate low-energy phonon modes. The associated electronic signatures are modulations of the unoccupied π*/σ* orbital energy levels and unambiguous fingerprints in Carbon K-edge XAS spectra. Thus, we extend the canonical view of XAS, establishing that these “static” measurements in fact encode the signature of the thermodynamic response and relaxation dynamics of the system. This causal link between atomic structure, spectroscopy, thermodynamics, and information theory can be generally exploited to better understand stability in solid-state electrochemical systems.

25 ENERGY STORAGE↗

Resolving electron and hole transport properties in semiconductor materials by constant light-induced magneto transport

The knowledge of minority and majority charge carrier properties enables controlling the performance of solar cells, transistors, detectors, sensors, and LEDs. Here, we developed the constant light induced magneto transport method which resolves electron and hole mobility, lifetime, diffusion coefficient and length, and quasi-Fermi level splitting. We demonstrate the implication of the constant light induced magneto transport for silicon and metal halide perovskite films. We resolve the transport properties of electrons and holes predicting the material’s effectiveness for solar cell application without making the full device. The accessibility of fourteen material parameters paves the way for in-depth exploration of causal mechanisms limiting the efficiency and functionality of material structures. To demonstrate broad applicability, we further characterized twelve materials with drift mobilities spanning from 10 –3 to 10 3 cm 2 V –1 s –1 and lifetimes varying between 10 –9 and 10 –3 seconds. The universality of our method its potential to advance optoelectronic devices in various technological fields.

14 SOLAR ENERGY↗

Water flipping and the oxygen evolution reaction on Fe 2 O 3 nanolayers

Hematite photoanodes are promising for the oxygen evolution reaction, however, their high overpotential (0.5-0.6 V) for water oxidation and limited photocurrent make them economically unviable at present. The work needed to orient dipoles at an electrode surface may be an overlooked contribution to the overpotential, especially regarding dipoles of water, the electron source in the oxygen evolution reaction (OER). Here, we employ second harmonic amplitude and phase measurements to quantify the number of net-aligned Stern layer water molecules and the work associated with water flipping, on hematite, an earth abundant OER semiconductor associated with a high overpotential. At zero applied bias, the pH-dependent potentials for Stern layer water molecule flipping exhibit Nernstian behavior. At positive applied potentials and pH 13, approximately one to two monolayers of water molecules points the oxygen atoms towards the electrode, favorable for the OER. The work associated with water flipping matches the cohesive energy of liquid water (44 kJ mol -1 ) and the OER current density is highest. This current is negligible at pH 5, where the work approaches 100 kJ mol -1 . Our findings suggest a causal relationship between the need for Stern layer water flipping and the OER overpotential, which may lead to developing strategies for decreasing the latter.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

High-frequency heating of the solar wind triggered by low-frequency turbulence

The fast solar wind’s high speeds and non-thermal features require that considerable heating occurs well above the Sun’s surface. Two leading theories seem incompatible: low-frequency ‘Alfvénic’ turbulence, which transports energy outwards and is observed ubiquitously by spacecraft but seems insufficient to explain the observed dominance of ion over electron heating; and high-frequency ion-cyclotron waves, which explain the non-thermal heating of ions but lack an obvious source. Here we argue that the recently proposed ‘helicity barrier’ effect, which limits electron heating by inhibiting the turbulent cascade of energy to the smallest scales, can unify these two paradigms. Our six-dimensional simulations show how the helicity barrier causes the large-scale energy to grow through time, generating small parallel scales and high-frequency ion-cyclotron-wave heating from low-frequency turbulence, while simultaneously explaining various other long-standing observational puzzles. Furthermore, the predicted causal link between plasma expansion and the ion-to-electron heating ratio suggests that the helicity barrier could contribute to key observed differences between fast and slow wind streams.

79 ASTRONOMY AND ASTROPHYSICS↗

Understanding how microbiomes influence the systems they inhabit

Translating the ever-increasing wealth of information on microbiomes (environment, host, or built environment) to advance the understanding of system-level processes is proving to be an exceptional research challenge. One reason for this challenge is that relationships between characteristics of microbiomes and the system-level processes they influence are often evaluated in the absence of a robust conceptual framework and reported without elucidating the underlying causal mechanisms. The reliance on correlative approaches limits the potential to expand the inference of a single relationship to additional systems and advance the field. We propose that research focused on how microbiomes influence the systems they inhabit should work within a common framework and target known microbial processes that contribute to the system-level processes of interest. Here we identify three distinct categories of microbiome characteristics (microbial processes, microbial community properties, and microbial membership) and propose a framework to empirically link each of these categories to each other and the broader system level processes they affect. We posit that it is particularly important to distinguish microbial community properties that can be predicted from constituent taxa (community aggregated traits) from and those properties that are currently unable to be predicted from constituent taxa (emergent properties). Existing methods in microbial ecology can be applied to more explicitly elucidate properties within each of these categories and connect these three categories of microbial characteristics with each other. We view this proposed framework, gleaned from a breadth of research on environmental microbiomes and ecosystem processes, as a promising pathway with the potential to advance discovery and understanding across a broad range of microbiome science.

Hall, Ed K.↗