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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 145 records · Page 8
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

CASSCF with Extremely Large Active Spaces Using the Adaptive Sampling Configuration Interaction Method

The complete active space self-consistent field (CASSCF) method is the principal approach employed for studying strongly correlated systems. However, exact CASSCF can only be performed on small active spaces of ~20 electrons in ~20 orbitals due to exponential growth in the computational cost. Here, we show that employing the Adaptive Sampling Configuration Interaction (ASCI) method as an approximate Full CI solver in the active space allows CASSCF-like calculations within chemical accuracy (<1 kcal/mol for relative energies) in active spaces with more than ~50 active electrons in ~50 active orbitals, significantly increasing the sizes of systems amenable to accurate multiconfigurational treatment. The main challenge with using any selected CI-based approximate CASSCF is the orbital optimization problem; they tend to exhibit large numbers of local minima in orbital space due to their lack of invariance to active–active rotations (in addition to the local minima that exist in exact CASSCF). We highlight methods that can avoid spurious local extrema as a practical solution to the orbital optimization problem. We employ ASCI-SCF to demonstrate a lack of polyradical character in moderately sized periacenes with up to 52 correlated electrons and compare against heat-bath CI on an iron porphyrin system with more than 40 correlated electrons.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Amphiphile Organization in Organic Solutions: An Alternative Explanation for Small-Angle X-ray Scattering Features in Malonamide/Alkane Mixtures

In this work, the role of different intermolecular interactions in the aggregation of amphiphiles in an organic solvent is studied for systems of relevance to liquid-liquid extraction (LLE), a chemical process used to selectively recover metals from complex mixtures. Of specific interest is the role, or lack thereof, of hydrogen bonding, which is often assumed to be a main driver of the organic phase structural organization that has been linked to separation efficacy. Toward that end, a series of malonamide extractants in n-dodecane have been studied in the absence of any extracted aqueous solutes, including water. The series of extractants includes N,N'-dimethyl-N,N'-dibutyltetradecylmalonamide (DMDBTDMA), two of its homologs, and N,N'-dimethyl-N,N'-dioctylhexylethoxymalonamide (DMDOHEMA). This simplified model LLE system enables systematic investigation of the role of dipole-dipole and alkyl tail steric interactions in amphiphile aggregation. Small-angle X-ray scattering (SAXS) profiles computed from molecular dynamics trajectories are in good agreement with experimental SAXS data. Molecular dynamics simulations show that malonamide aggregation results from dipole-driven self-association and lacks characteristic aggregate sizes. Mid-q correlation peaks in the SAXS profiles emerge at high concentration for each malonamide. In those densely packed solutions, the correlation peaks are observed to result from alkyl tail-induced spacing between electron-rich polar head groups, with peak positions determined by the different alkyl tail lengths present in the malonamide molecule. This explanation of the SAXS correlation peaks contrasts with the prevailing literature, which attributes mesoscale features observed in small-angle scattering to the formation of microemulsions. Instead, this work finds that these features are present in the absence of water or any reverse micellar organization of the malonamides. As such, molecular-scale malonamide self-association and packing, rather than microemulsion-based colloidal-scale descriptions, is a more appropriate framework for these LLE systems.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

New Insights into Secondary Organic Aerosol Formation at the Air–Liquid Interface

Air-liquid interfacial processing of volatile organic compound oxidation has been suggested as an important source of secondary organic aerosols. However, owing to the lack of techniques for in situ air-liquid interface analysis, the detailed interfacial mechanism remains speculative. To obviate this, the analysis of air-liquid interfacial reactions and the dynamics of glyoxal oxidation as a model volatile organic compound using in situ liquid synchrotron-based vacuum ultraviolet single photon ionization mass spectrometry enabled by the system for analysis at the liquid vacuum interface microreactor is reported. This approach allows for determination of reaction intermediates and oxidation products including polymers and oligomers at the air-liquid interface by mass spectral analysis and appearance energy measurements. Furthermore, an expanded reaction mechanism of photooxidation free radical induced reactions as a source of aqueous secondary organic aerosol formation is proposed based on these new results, suggesting that single photon ionization could be applied to provide unique insights into interfacial chemistry changing the earth atmospheric composition.

aqueous secondary organic aerosol, glyoxal, photoo↗
DOE OSTI2021

In Situ Probing Potassium-ion Intercalation-induced Amorphization in Crystalline Iron Phosphate Cathode Materials

Na-ion and K-ion batteries are promising alternatives for large-scale energy storage applications due to their abundance and low cost. Intercalation of these large ions could cause irreversible structural deformation and partial to complete amorphization in the crystalline electrodes. The designing of new amorphous electrodes is another route to develop electrodes to store these ions reversibly. Lack of understanding of dynamic changes in the amorphous nanostructures during battery operation is the bottleneck for further developments. Here, we report the utilization of in situ digital image correlation and in-operando X-ray diffraction (XRD) techniques to probe dynamic changes in the amorphous phase of iron phosphate during potassium intercalation. In-operando XRD demonstrates amorphization in the electrode’s nanostructure during the first charge/discharge cycle. Additionally, the ex-situ high-resolution transmission electron microscopy further confirms the amorphization after potassium insertion. In situ strain analysis detects the reversible deformation associated with redox reactions in the amorphous phases. Our approach offers new insights on the mechanisms of ion intercalation in the amorphous nanostructures which are highly potent for development of next-generation batteries.

Ozdogru, Bertan↗
DOE OSTI2023

Metal–Carbodithioate-Based 3D Semiconducting Metal–Organic Framework: Porous Optoelectronic Material for Energy Conversion

Solar energy conversion requires the working compositions to generate photoinduced charges with high potential and the ability to deliver charges to the catalytic sites and/or external electrode. These two properties are typically at odds with each other and call for new molecular materials with sufficient conjugation to improve charge conductivity but not as much conjugation as to overly compromise the optical band gap. In this work, we developed a semiconducting metal-organic framework (MOF) prepared explicitly through metal-carbodithioate"(-CS 2 ) n M" linkage chemistry, entailing augmented metal-linker electronic communication. The stronger ligand field and higher covalent character of metal-carbodithioate linkages-when combined with spirofluorene-derived organic struts and nickel-(II) ion-based nodes-provided a stable, semiconducting 3D-porous MOF, Spiro-CS 2 Ni. This MOF lacks long-range ordering and is defined by a flexible structure with non-aggregated building units, as suggested by reverse Monte Carlo simulations of the pair distribution function obtained from total scattering experiments. The solvent-removed "closed pore"material recorded a Brunauer-Emmett-Teller area of similar to 400m 2 /g, where the "open pore" form possesses90 wt % solvent-accessible porosity. Electrochemical measurements suggest that Spiro-CS 2 Ni possesses a band gap of 1.57 eV(sigma = 10 -7 S/cm at -1.3 V bias potential),which can be further improved by manipulating the d-electron configuration through an axial coordination (ligand/substrate), the latter of which indicates usefulness as an electrocatalyst and/or a photoelectrocatalyst(upon substrate binding). Transient-absorption spectroscopy reveals a long-lived photo-generated charge-transfer state (τ CR = 6.5 mu s) capable of chemical transformation under a biased voltage. Spiro-CS 2 Ni can endure a compelling range of pH(1-12 for weeks) and hours of electrochemical and photoelectrochemical conditions in the presence of water and organic acids. We believe this work provides crucial design principles for low-density, porous,light-energy-conversion materials.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Phosphonium-Based Metal Halide Semiconductors: When a Single Atom Dictates Water and Thermal Stability

Phosphonium-based (R-P(R’) 3 + ) metal halide semiconductors (MHS) emerged recently as a promising family of materials offering enhanced water and thermal stability over conventional ammonium-based (R-NH 3 + ) MHS. Despite this performance, there is a lack of systematic studies that elucidate the origin of these features as well as the underlying optoelectronic properties. Here, we report here the synthesis of nine new 1D materials (L)PbX 3 (L= C4-P, C6-P, C6-N, P3-P, P4-P, X= I, Br), using custom made organic ligands, namely butyl(triethyl)phosphonium bromide (C4-P), hexyl(triethyl)phosphonium bromide (C6-P), benzyl(triethyl)phosphonium bromide (P3-P), benzyl(trimethyl)phosphonium bromide (P4-P), and hexyl(triethyl)ammonium bromide (C6-N). Most of the materials are water stable for over 21 months, while the assembly of the isostructural (C6-N)PbBr 3 and (C6-P)PbBr 3 allowed us to directly identify the impact of a single atom (phosphorus versus nitrogen), on water stability. Notably, the C6-P analog remains water stable for 21 months, whereas the C6-N analog dissolves in water. It was found that neither crystal packing nor the lack of hydrogen bond interactions with water is responsible for this record stability performance, challenging currently established claims on the 1 origin of water stability in MHS. All materials feature broad light emission at RT, with (P3-P)PbBr 3 exhibiting a PLQY of 22.0% ascribed to permanent traps, while electrochemical studies uncovered for the first time the redox properties and their strong potential for the sensing of per- and polyfluoroalkyl substances (PFAS) in water samples. Our work showcases the potential of these compounds for applications where thermal and water stability are interwoven, potentially rendering their (R-NH 3 + ) based counterparts obsolete.

PFAS sensing↗
DOE OSTI2021

U.S. Manufacturing Water Use Data and Estimates: Current State, Limitations, and Future Needs for Supporting Manufacturing Research and Development

Water is essential to manufacturing operations; without it, many facilities could not operate or meet production demands. Physical, reputational, and regulatory risks to water supplies compounded by climate change-induced impacts on hydrological conditions threaten the adequacy of water supplies for manufacturing. Manufacturing water use has not been a major focus of either water or manufacturing-related research. Research and development (R&D) aimed at helping manufacturers use water more sustainably and adapt to changing water conditions is needed to ensure a thriving sector and economy. However, the ability to identify R&D needs is severely limited due to a lack of current, statistically representative data on manufacturing water use and its environmental implications. In this Perspective, we outline four key questions to inform R&D on manufacturing use and highlight how the current state of water data in the United States does not support the adequate investigation of these questions. We make recommendations for the water data characteristics needed to explore the research questions and knowledgeably inform R&D on manufacturing water use.

McCall, James↗
DOE OSTI2021

Mechanistic Duality of Bacterial Efflux Substrates and Inhibitors: Example of Simple Substituted Cinnamoyl and Naphthyl Amides

Antibiotic resistance poses an immediate and growing threat to human health. Multidrug efflux pumps are promising targets for overcoming antibiotic resistance with small-molecule therapeutics. Previously, we identified a diaminoquinoline acrylamide, NSC-33353, as a potent inhibitor of the AcrAB–TolC efflux pump in Escherichia coli. This inhibitor potentiates the antibacterial activities of novobiocin and erythromycin upon binding to the membrane fusion protein AcrA. It is also a substrate for efflux and lacks appreciable intrinsic antibacterial activity of its own in wild-type cells. Here, we have modified the substituents of the cinnamoyl group of NSC-33353, giving rise to analogs that retain the ability to inhibit efflux, lost the features of the efflux substrates, and gained antibacterial activity in wild-type cells. The replacement of the cinnamoyl group with naphthyl isosteres generated compounds that lack antibacterial activity but are both excellent efflux pump inhibitors and substrates. Surprisingly, these inhibitors potentiate the antibacterial activity of novobiocin but not erythromycin. Surface plasmon resonance experiments and molecular docking suggest that the replacement of the cinnamoyl group with naphthyl shifts the affinity of the compounds away from AcrA to the AcrB transporter, making them better efflux substrates and changing their mechanism of inhibition. These results provide new insights into the duality of efflux substrate/inhibitor features in chemical scaffolds that will facilitate the development of new efflux pump inhibitors.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

A Machine Learning Model for Predicting Composition of Catalytic Coprocessing Products from Molecular Beam Mass Spectra

Demand for the development of an automated and integrated refining process for biofuels has increased in recent years due to the lack of generalized process inspection tools. In bio-oil upgrading processes, all process variables are maintained based on the offline specification of intermediates and products. A lack of real-time product specifications in batch-wise monitoring can cause process failure and wasted resources. Therefore, there is a need for a fast and accurate intermediates/product specification tool that can be used for real-time specification to reduce waste and mitigate the risk of process failure. Here, to address this gap, we developed a machine learning (ML) model for predicting speciated bio-oil composition, including paraffin, iso-paraffins, olefins, naphthene, and aromatics. The model is trained using the mass spectra from upgraded products collected in the vapor phase before condensation and predicts the composition of the condensed product. Training ML models using raw mass spectra is challenging due to numerous overlapped peaks originating from different parent compounds. With this in mind, we propose a protocol that (i) transforms raw mass spectra to chemistry-inspired predefined features and (ii) trains decision tree-based models using these features. Our results show that the random forest model was robust against overfitting and had the highest accuracy compared to other models. Moreover, a stochastic ablation method determined the eight most significant features while maximizing the accuracy. Our protocol facilitates real-time compositional analysis of upgraded bio-oils and thus real-time process monitoring. Additionally, this protocol enables the rational design of efficient catalysts and the determination of optimal process conditions.

09 BIOMASS FUELS↗
DOE OSTI2020

LixNiO/Ni Heterostructure with Strong Basic Lattice Oxygen Enables Electrocatalytic Hydrogen Evolution with Pt-like Activity

The low-cost hydrogen production from water electrolysis is crucial for practical deployment of sustainable hydrogen economy, but is often constrained by the lack of active and robust electrocatalysts from Earth-abundant materials. We describe here an unconventional heterostructure composed of strongly coupled Ni-deficient LixNiO nanoclusters and polycrystalline Ni nanocrystals, and its exceptional activities toward hydrogen evolution reaction (HER) in aqueous electrolytes. The presence of unique lattice oxygen species with strong Brønsted basicity is a significant feature, which spontaneously split water molecules and effectively accelerate the sluggish Volmer H-OH dissociation step in neutral and alkaline HER. In combination with the unpreceded level of intimate LixNiO and Ni interfacial junctions that produces abundant “hotspots” for promoted hydride coupling, the catalyst exhibited kinetic activities almost identical as Pt/C and decent long term stability in universal pH.

Lu, Ke↗
DOE OSTI2025

Telecom-Luminescent and Room Temperature Coherent Tetrathiafulvalene-Based Qubits in Spin-Rich Solids

One of the main challenges facing quantum information science (QIS) is the development of robust qubits that can be op-erated under ambient conditions. Current state-of-the-art anionic nitrogen vacancy center (NV–) defect qubits are robust enough to be operated at room temperature but lack scalability and tunability. These are areas where molecular qubits excel, although they typically suffer from poor air stability and fast decoherence at elevated temperatures and in magneti-cally noisy environments. Organic-based systems offer advantages to this end, although examples retaining room tem-perature coherence are still rare. Furthermore, most organic-based systems lack optical transitions similar to NV– centers that could allow for optical initialization and readout. Here we report two new organic-based qubit candidates that demonstrate room temperature coherence in nuclear and electron spin-rich environments. These qubits luminesce far into the near-infrared (NIR, 700-1700 nm) and telecom (~1260-1625 nm) regions, ideal for biological sensing and com-munications applications, respectively.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

The [4Fe-4S] Cluster of HydF Is Essential for [FeFe]-Hydrogenase Maturation

The organometallic H-cluster of the [FeFe]-hydrogenase is assembled in vivo through a complex process requiring the action of three dedicated maturation enzymes, HydG, HydE, and HydF, as well as the aminomethyl-lipoyl-H-protein (H met ) of the glycine cleavage system (GCS). Here we probe the role of HydF and its [4Fe-4S] cluster in [FeFe]-hydrogenase maturation by using a defined semisynthetic approach in which [Fe I 2 (μ-SH) 2 (CO) 4 (CN) 2 ] 2– ([2Fe] E ) is used to bypass HydE and HydG, and GCS components are used in place of cell lysate. We show that inclusion of the iron–sulfur carrier protein NfuA and the high-CO-affinity myoglobin variant Mb H64L provides dramatically improved hydrogenase activities up to 828 μmol/min/mg, equivalent to the best reported activities for Chlamydomonas reinhardtii [FeFe]-hydrogenase isolated from the native organism. Apo-HydF lacking a [4Fe-4S] cluster provides very little hydrogenase activity; however, full maturation is restored with the addition of NfuA, which we demonstrate reconstitutes the [4Fe-4S] cluster of HydF. In addition, a HydF variant lacking a [4Fe-4S] cluster by changing two cysteine ligands to alanine is completely unable to support either semisynthetic maturation using [2Fe] E , or full maturation using HydG and HydE, even in the presence of NfuA, demonstrating that the HydF [4Fe-4S] cluster is absolutely essential for [FeFe]-hydrogenase maturation. The possibility that the HydF [4Fe-4S] cluster plays a role in direct binding of [2Fe] E is negated by our results with the HydF D311C variant, which demonstrate that the labile Asp311 cluster ligand is not essential for [2Fe] E binding and HydA maturation. We therefore conclude that [2Fe]E binds HydF adjacent to, but not directly coordinated to, the [4Fe-4S] cluster. The HydF [4Fe-4S] cluster is proposed to be essential due to its impact on the [2Fe] E binding orientation and the ability of the HydF/[2Fe] E complex to form productive interactions with H met or the H met /T-protein complex during DTMA ligand biosynthesis.

cluster chemistry↗
DOE OSTI2021

Testing the Recycled Gabbro Hypothesis for the Origin of “Ghost Plagioclase” Melt Signatures Using 87 Sr/ 86 Sr of Individual Olivine-Hosted Melt Inclusions From Hawai'i

Melt inclusions with large, positive Sr anomalies have been described in multiple tectonic settings, and the origins of this unusual geochemical feature are debated. Three origins have been proposed, all involving plagioclase as the source of the elevated Sr: (i) direct assimilation of plagioclase-rich lithologies, (ii) recycled lower oceanic gabbro in the mantle source, and (iii) shallow-level diffusive interaction between present day lower oceanic crust (i.e., plagioclase-bearing lithologies) and the percolating melt. A “ghost plagioclase” signature (i.e., a large, positive Sr anomaly without associated high Al 2 O 3 ) is present in melt inclusions from Mauna Loa. Here, we present new 87 Sr/ 86 Sr measurements of individual olivine-hosted melt inclusions from three Hawaiian volcanoes, Mauna Loa, Loihi, and Koolau. The data set includes a Mauna Loa melt inclusion with the highest reported Sr anomaly (or highest (Sr/Ce) N , which is 7.2) for Hawai'i. All melt inclusions have 87 Sr/ 86 Sr values within the range reported previously for the lavas from each volcano. Critically, the 87 Sr/ 86 Sr of the high (Sr/Ce) N melt inclusion lies within the narrow range of 87 Sr/ 86 Sr for Mauna Loa melts that lack high (Sr/Ce) N signatures. Therefore, to explain the high (Sr/Ce) N ratio of the ghost plagioclase signature using an ancient recycled gabbro, the gabbro-infused mantle source would have had to evolve, by chance, to have the same 87 Sr/ 86 Sr as the source of the Mauna Loa melts that lack a recycled gabbro (ghost plagioclase) signature. Alternatively, shallow-level diffusive interactions between Mauna Loa plagioclase-rich cumulates and a percolating mantle-derived melt provides a simpler explanation for the presence of the high (Sr/Ce) N Mauna Loa melts.

58 GEOSCIENCES↗
DOE OSTI2021

Examination of Radiation Belt Dynamics During Substorm Clusters: Activity Drivers and Dependencies of Trapped Flux Enhancements

Here, dynamical variations of radiation belt trapped electron fluxes are examined to better understand the variability of enhancements linked to substorm clusters. Analysis is undertaken using the Substorm Onsets and Phases from Indices of the Electrojet substorm cluster algorithm for event detection. Observations from low earth orbit are complemented by additional measurements from medium earth orbit to allow a major expansion in the energy range considered, from medium energy energetic electrons up to ultra-relativistic electrons. The number of substorms identified inside a cluster does not depend strongly on solar wind drivers or geomagnetic indices either before, during, or after the cluster start time. Clusters of substorms linked to moderate (100 nT < AE ≤ 300 nT) or strong AE (AE ≥ 300 nT) disturbances are associated with radiation belt flux enhancements, including up to ultra-relativistic energies by the strongest substorms (as measured by strong southward Bz and high AE). These clusters reliably occur during times of high speed solar winds streams with associated increased magnetospheric convection. However, substorm clusters associated with quiet AE disturbances (AE ≤ 100 nT) lead to no significant chorus whistler mode intensity enhancements, or increases in energetic, relativistic, or ultra-relativistic electron flux in the outer radiation belts. In these cases the solar wind speed is low, and the geomagnetic Kp index indicates a lack of magnetospheric convection. Our study clearly indicates that clusters of substorms occurring outside of high speed wind streams are not by themselves sufficient to drive acceleration, which may be due to the lack of pre-cluster convection.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Detecting Large Explosions With Machine Learning Models Trained on Synthetic Infrasound Data

Explosions produce low-frequency acoustic (infrasound) waves capable of propagating globally, but the spatio-temporal variability of the atmosphere makes detecting events difficult. Machine learning (ML) is well-suited to identify the subtle and nonlinear patterns in explosion infrasound signals, but a previous lack of ground-truth data inhibited training of generalized models. We introduce a physics-based method that propagates infrasound sources through realistic atmospheres to create 28,000 synthetic events, which are used to train ML classifiers. A simple artificial neural network and modern temporal convolutional network discriminate synthetic events from background noise with >90% accuracy and, more importantly, successfully identify the majority of real-world explosion signals recorded during the Humming Road Runner experiment. ML models trained entirely on physics-based synthetics advance explosion detection capabilities and make ML more viable to related fields lacking training data.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗
DOE OSTI2023

Future Projections of the El Niño—Southern Oscillation and Tropical Pacific Mean State in CMIP6

Abstract The El Niño—Southern Oscillation (ENSO) is an important mode of tropical Pacific atmosphere‐ocean variability that drives teleconnections with weather and climate globally. However, prior studies using state‐of‐the‐art climate models lack consensus regarding future ENSO projections and are often impacted by tropical Pacific sea‐surface temperature (SST) biases. We used 173 simulations from 29 climate models participating in the Coupled Model Intercomparison Project, version 6 (CMIP6) to analyze model biases and future ENSO projections. We analyzed two ENSO indices, namely the ENSO Longitude Index (ELI), which measures zonal shifts in tropical Pacific deep convection and accounts for changes in background SST, and the Niño 3.4 index, which measures SST anomalies in the central‐eastern equatorial Pacific. We found that the warm eastern tropical‐subtropical Pacific SST bias typical of previous generations of climate models persists into many of the CMIP6 models. Future projections of ENSO shift toward more El Niño‐like conditions based on ELI in 48% of simulations and 55% of models, in association with a future weakening of the zonal equatorial Pacific SST gradient. On the other hand, none of the models project a significant shift toward La Niña‐like conditions. The standard deviation of the Niño 3.4 index indicates a lack of consensus on whether an increase or decrease in ENSO variability is expected in the future. Finally, we found a possible relationship between historical SST and low‐level cloud cover biases in the ENSO region and future changes in ELI; however, this result may be impacted by limitations in data availability.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Assessing the Atmospheric Response to Subgrid Surface Heterogeneity in the Single-Column Community Earth System Model, Version 2 (CESM2)

Land-atmosphere interactions are central to the evolution of the atmospheric boundary layer and the subsequent formation of clouds and precipitation. Existing global climate models represent these connections with bulk approximations on coarse spatial scales, but observations suggest that small-scale variations in surface characteristics and co-located turbulent and momentum fluxes can significantly impact the atmosphere. Recent model development efforts have attempted to capture this phenomenon by coupling existing representations of subgrid-scale (SGS) heterogeneity between land and atmosphere models. Such approaches are in their infancy and it is not yet clear if they can produce a realistic atmospheric response to surface heterogeneity. Here, we implement a parameterization to capture the effects of SGS heterogeneity in the Community Earth System Model (CESM2), and compare single-column simulations against high-resolution Weather Research and Forecasting (WRF) large-eddy simulations (LESs), which we use as a proxy for observations. The CESM2 experiments increase the temperature and humidity variances in the lowest atmospheric levels, but the response is weaker than in WRF-LES. In part, this is attributed to an underestimate of surface heterogeneity in the land model due to a lack of SGS meteorology, a separation between deep and shallow convection schemes in the atmosphere, and a lack of explicitly represented mesoscale secondary circulations. These results highlight the complex processes involved in capturing the effects of SGS heterogeneity and suggest the need for parameterizations that communicate their influence not only at the surface but also vertically.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Regional and Temporal Variability of Atmospheric River Seasonality: Influences of Detection Algorithms and Moisture Transport Dynamics

Abstract Understanding the regional and temporal variability of atmospheric river (AR) seasonality is crucial for preparedness and mitigation of extreme events. While ARs were thought to peak in winter, recent research shows they exhibit region‐specific seasonality and are heavily influenced by the chosen detection algorithm. This study examines the link between the year‐to‐year consistency of peak‐AR activity to the presence of a dominant seasonal pattern, considering both location and algorithm choice. Regions are categorized by their temporal characteristics: consistent patterns (e.g., East Asia), patterns with occasional outliers (e.g., British Columbia coast), and regions lacking a clear dominant peak season (e.g., South Atlantic, parts of Australia). Hence, not all regions display a consistent seasonal cycle of AR activity. This study quantifies the extent to which a region experiences a dominant peak season of AR activity (or lacks one) and offers insights to enhance decision‐making in water management, natural hazard preparedness, and forecasting. Furthermore, given our finding that detection algorithms influence the peak season of AR activity, we also examine two diagnostic variables representative of moisture transport to corroborate our results. Integrated vapor transport, which captures meridional and zonal moisture transport, and Moist Wave Activity, representing moisture intrusions from lower to higher latitudes, are examined. Our analysis indicates that inconsistencies in the seasonal cycle of AR activity are not solely due to discrepancies in detection algorithms but also arise from changes in moisture transport. Plain Language Summary Atmospheric rivers (ARs) are critical weather phenomena that can cause extreme events like heavy rainfall and flooding. Understanding when and where ARs are most likely to occur throughout the year is essential for preparing and responding to these events. Traditionally, ARs were thought to peak in winter, but recent studies show this varies by region. Our study helps address the challenge decision‐makers face in anticipating and preparing for AR events by providing insights into the consistency of peak seasonal patterns across different areas. Some regions, like East Asia, and the British Columbia coast, show a consistent peak season, while others, like the South Atlantic and parts of Australia, have significant year‐to‐year variations, making it hard to identify a dominant season. To better understand these changes over time, the study also examines how moisture moves in the atmosphere, using Integrated Vapor Transport (which looks at moisture movement in various directions) and Moist Wave Activity (which tracks moisture shifts from lower to higher latitudes). The findings suggest that inconsistencies in AR patterns are due not only to detection methods but also due to changes in moisture transport. Key Points The peak season of atmospheric river activity can change depending on the year in some areas Interannual variations in the peak season can make identifying a dominant season challenging for some regions Frequent shifts in peak season across years reflect inconsistencies tied to detection algorithms and to underlying dynamics

Kamnani, Diya↗