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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

Multi-scale simulation of high burnup UO2 nuclear fuel during loss-of-coolant accident conditions

To improve the economics of commercial nuclear energy generation, U.S. utilities are currently seeking licensing approval to operate UO2 fuel to higher burnups. One significant safety issue that must be addressed to obtain approval is the potential for fine fragmentation/pulverization of the fuel during a loss-of-coolant accident (LOCA). It has been hypothesized that pulverization is caused by the rapid increase of pressure in fission gas bubbles in the high burnup region of the fuel during a LOCA. To better understand this phenomenon, a novel phase-field model of the fission gas bubble microstructure in UO2 has been developed and implemented in Idaho National Laboratory (INL)'s Marmot application for phase-field simulation of nuclear materials. Simulations of the bubble response to steady-state and transient conditions were conducted, and the results were used to inform a mechanistic model of pulverization in BISON, INL’s fuel performance simulation code.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Development of a Translational Model to Assess the Impact of Opioid Overdose and Naloxone Dosing on Respiratory Depression and Cardiac Arrest

In response to a surge of deaths from synthetic opioid overdoses, there have been increased efforts to distribute naloxone products in community settings. Prior research has assessed the effectiveness of naloxone in the hospital setting; however, it is challenging to assess naloxone dosing regimens in the community/first‐responder setting, including reversal of respiratory depression effects of fentanyl and its derivatives (fentanyls). Here, we describe the development and validation of a mechanistic model that combines opioid mu receptor binding kinetics, opioid agonist and antagonist pharmacokinetics, and human respiratory and circulatory physiology, to evaluate naloxone dosing to reverse respiratory depression. Validation supports our model, which can quantitatively predict displacement of opioids by naloxone from opioid mu receptors in vitro , hypoxia‐induced cardiac arrest in vivo , and opioid‐induced respiratory depression in humans from different fentanyls. After validation, overdose simulations were performed with fentanyl and carfentanil followed by administration of different intramuscular naloxone products. Carfentanil induced more cardiac arrest events and was more difficult to reverse than fentanyl. Opioid receptor binding data indicated that carfentanil has substantially slower dissociation kinetics from the opioid receptor compared with nine other fentanyls tested, which likely contributes to the difficulty in reversing carfentanil. Administration of the same dose of naloxone intramuscularly from two different naloxone products with different formulations resulted in differences in the number of virtual patients experiencing cardiac arrest. This work provides a robust framework to evaluate dosing regimens of opioid receptor antagonists to reverse opioid‐induced respiratory depression, including those caused by newly emerging synthetic opioids.

Pharmacology & Pharmacy↗

Short-Wave Infrared Upconverting Nanoparticles

Optical technologies enable real-time, noninvasive analysis of complex systems but are limited to discrete regions of the optical spectrum. While wavelengths in the short-wave infrared (SWIR) window (typically, 1700-3000 nm) should enable deep subsurface penetration and reduced photodamage, there are few luminescent probes that can be excited in this region. Here, we report the discovery of lanthanide-based upconverting nanoparticles (UCNPs) that efficiently convert 1740 or 1950 nm excitation to wavelengths compatible with conventional silicon detectors. Screening of Ln3+ ion combinations by differential rate equation modeling identifies Ho3+/Tm3+ or Tm3+ dopants with strong visible or NIR-I emission following SWIR excitation. Experimental upconverted photoluminescence excitation (U-PLE) spectra find that 10% Tm3+-doped NaYF4 core/shell UCNPs have the strongest 800 nm emission from SWIR wavelengths, while UCNPs with an added 2% or 10% Ho3+ show the strongest red emission when excited at 1740 or 1950 nm. Mechanistic modeling shows that addition of a low percentage of Ho3+ to Tm3+-doped UCNPs shifts their emission from 800 to 652 nm by acting as a hub of efficient SWIR energy acceptance and redistribution up to visible emission manifolds. Parallel experimental and computational analysis shows rate equation models are able to predict compositions for specific wavelengths of both excitation and emission. These SWIR-responsive probes open a new IR bioimaging window, and are responsive at wavelengths important for vision technologies.

Qi, Xiao↗

Lower length scale model for palladium attack of silicon carbide in TRISO fuel

TRistructural ISOtropic (TRISO) particle fuels rely on silicon carbide (SiC) as the primary barrier for metallic fission product (FP) release. Palladium (Pd) generated by fission degrades the SiC layer, resulting in the formation of lamellar layers of palladium silicides (PdxSi) and carbon (C) perpendicular to the direction of attack. The Pd attack has been hypothesized to be responsible for failure of the SiC layer and enhance FP release. To better understand and quantify Pd attack of SiC in TRISO particles, a multiscale, mechanistic model of Pd transport is being developed by the NEAMS program. Previous work provided an initial hypothesis for modeling lamellar microstructure formation in SiC due to Pd attack using a phase-field model. The work described in this report builds on the previous model by using molecular dynamics (MD) simulations to parameterize the phase-field model kinetics, and build a reduced order model in BISON using the improved mesoscale Pd penetration model.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Using metacommunity ecology to understand environmental metabolomes

Abstract Environmental metabolomes are fundamentally coupled to microbially-linked biogeochemical processes within ecosystems. However, significant gaps exist in our understanding of their spatiotemporal organization, limiting our ability to uncover transferrable principles and predict ecosystem function. We propose that a theoretical paradigm, which integrates concepts from metacommunity ecology, is necessary to reveal underlying mechanisms governing metabolomes. We call this synthesis between ecology and metabolomics ‘meta-metabolome ecology’ and demonstrate its utility using a mass spectrometry dataset. We developed three relational metabolite dendrograms using molecular properties and putative biochemical transformations and performed ecological null modeling. Based upon null modeling results, we show that stochastic processes drove molecular properties while biochemical transformations were structured deterministically. We further suggest that potentially biochemically active metabolites were more deterministically assembled than less active metabolites. Understanding variation in the influences of stochasticity and determinism provides a way to focus attention on which meta-metabolomes and which parts of meta-metabolomes are most likely to be important to consider in mechanistic models. We propose that this paradigm will allow researchers to study the connections between ecological systems and their molecular processes in previously inaccessible detail.

54 ENVIRONMENTAL SCIENCES↗

Initial Assessment of CTF for Time-at-Temperature Applications

The US nuclear industry is interested in improving the economics of their fleet of light-water reactors (LWRs) by uprating US plants. One option being considered is to regain lost margin from overly conservative fuel safety limits. The current limit requires avoidance of critical heat flux (CHF) and prevents further operation of fuel that experiences a dry-out in boiling water reactors (BWRs) or departure from nucleate boiling (DNB) in pressurized water reactors (PWRs); however, it has been shown that temporary, mild dry-out of the fuel does not necessarily increase the risk of fuel failure during its normal anticipated operating life. Such mild dry-out or DNB events may occur during a plant anticipated operational occurrence (AOO), such as a locked rotor in a PWR or a pump trip in a BWR. The time-at-temperature (TAT) approach to regulating fuel operation aims to demonstrate that the fuel rod’s integrity is not challenged during such a mild transient that leads to CHF in which the fuel operates at an elevated temperature for a brief period of time. However, implementing this approach will require extensive fuel material experimental data, as well as supporting modeling and simulation (M&S) predictions, to ensure that the predicted fuel response during AOOs, with all applicable uncertainty considered, will not threaten the safety of the fuel during the transient or the remainder of its anticipated lifecycle. To address this need, a comprehensive effort is being proposed that includes generating cladding material data under TAT conditions, assessment of available code capabilities for TAT conditions, development of new mechanistic models, and demonstration of the M&S capabilities for AOOs of interest. This will require a joint effort between the Nuclear Energy Advanced Modeling and Simulation (NEAMS) and Advanced Fuels Campaign (AFC) programs, as well as close collaboration with nuclear industry stakeholders. The outcome of this collaboration will result in development and assessment of capabilities that can be used by the nuclear industry to support qualification of a TAT-based fuel failure criteria safety limit. This report focuses on the thermal hydraulics (T/H) modeling capabilities and summarizes currently available data for validating the T/H subchannel code CTF for TAT conditions, as well as preliminary assessment results of the code. The initial assessment also resulted in implementation of an alternative post-CHF heat transfer package, which has been shown to significantly improve accuracy. This report is not a final assessment and does not consider all available validation data; it is intended that a future assessment will more fully validate the code for this application.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Rhizosphere Soil Biogeochemical Data and Photosynthetic Data of Vicia Faba in a Rhizobox

Here we share the data in column format via csv files for pH, redox, and dissolved oxygen collected at hourly resolution from microelectrodes. Dissolved organic carbon concentrations collected from TOC are also provided in a similar format but are composited samples from hourly microdialysis collection. This provided resolution of diel rhizosphere dynamics belowground. Plant physiological data was also collected at every 5 min for 24 hr cycles in order to capture diel dynamics aboveground. This data was used to parameterize the reaction transport model eSTOMP-ROOTS, which examines the rhizosphere biogeochemistry of a growing Vicia faba plant. The aim was to investigate plant activity and belowground biogeochemical processes, particularly their impact on mineral-organic associations in the rhizosphere. We combined in-situ rhizosphere microsensor and plant physiological measurements with a 3-D plant-soil reactive transport model to explore the behavior of dissolved organic carbon (DOC) in the rhizosphere. Over several days, microdialysis probes placed at the root-soil interface in live soil showed distinct daily patterns of DOC concentration in the pore water. Spikes in DOC concentrations during the day aligned with peaks in leaf-level photosynthesis, accompanied by decreasing redox potential and dissolved oxygen levels, and increasing pH in the rhizosphere. This new mechanistic modeling framework, which integrates aboveground plant physiological data with non-destructive, high-resolution monitoring of rhizosphere processes, offers significant potential for studying the factors that control carbon storage in soils.

54 ENVIRONMENTAL SCIENCES↗

Thioester synthesis by a designed nickel enzyme models prebiotic energy conversion

The formation of carbon–carbon bonds from prebiotic precursors such as carbon dioxide represents the foundation of all primordial life processes. In extant organisms, this reaction is carried out by the carbon monoxide dehydrogenase (CODH)/acetyl coenzyme A synthase (ACS) enzyme, which performs the cornerstone reaction in the ancient Wood–Ljungdahl metabolic pathway to synthesize the key biological metabolite, acetyl-CoA. Despite its significance, a fundamental understanding of this transformation is lacking, hampering efforts to harness analogous chemistry. To address these knowledge gaps, we have designed an artificial metalloenzyme within the azurin protein scaffold as a structural, functional, and mechanistic model of ACS. We demonstrate the intermediacy of the Ni I species and requirement for ordered substrate binding in the bioorganometallic carbon–carbon bond-forming reaction from the one-carbon ACS substrates. The electronic and geometric structures of the nickel-acetyl intermediate have been characterized using time-resolved optical, electron paramagnetic resonance, and X-ray absorption spectroscopy in conjunction with quantum chemical calculations. Moreover, we demonstrate that the nickel-acetyl species is chemically competent for selective acyl transfer upon thiol addition to biosynthesize an activated thioester. Drawing an analogy to the native enzyme, a mechanism for thioester generation by this ACS model has been proposed. The fundamental insight into the enzymatic process provided by this rudimentary ACS model has implications for the evolution of primitive ACS-like proteins. Ultimately, these findings offer strategies for development of highly active catalysts for sustainable generation of liquid fuels from one-carbon substrates, with potential for broad applications across diverse fields ranging from energy storage to environmental remediation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

BISON analyses of TRISO fuel performance, its dependence on time-at-temperature, and possible implications for fuel design and qualification

The Advanced Gas Reactor Fuel Development and Qualification (AGR) program has established a substantial technical foundation to support private entry into the U.S. high-temperature gas-cooled reactor market. However, emerging tristructural isotropic (TRISO)-fueled reactor applications include small modular reactors and microreactors with longer fuel residence times, which may expose fuels to higher time-at-temperature (TAT) values than were explored by the AGR program. Increased TAT could affect diffusive and thermomechanical behaviors such as Pd penetration, fission gas release, creep, and fission product transport. In this work, we applied multiscale best-estimate BISON fuel performance modeling to assess these effects within a representative design space based on the AGR-5/6/7 experiment and analyzed trends in predicted particle and compact fuel performance metrics with possible implications for near-term fuel design and qualification. BISON unambiguously predicted that TRISO fuel performance is sensitive to TAT. Increasing TAT was not predicted to increase the magnitude of failure-inducing tangential stresses in particle coating layers. Predictions obtained using a mechanistic model for Pd penetration indicated that penetration depth does not depend strongly on TAT. While these observations suggest that AGR testing provides a conservative upper bound for the steady-state operation of TRISO particles at lower powers and higher residence times, BISON also predicted that the release of poorly retained Ag would increase with TAT. Because these analyses applied models to extrapolate beyond the available experimental data, the authors recommend performing targeted experiments to confirm these predictions. Nevertheless, these predictions may provide reactor developers with enough confidence to make near-term design decisions associated with the potential fuel performance trade-offs of increasing TAT.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Benefits and Cautions in Data Assimilation Strategies: An Example of Modeling Groundwater Recharge

Assimilating recent observations improves model outcomes for real-time assessments of groundwater processes. This is demonstrated in estimating time-varying recharge to a shallow fractured-rock aquifer in response to precipitation. Results from estimating the time-varying water-table altitude (h) and recharge, and their error covariances, are compared for forecasting, filtering, and fixed-lag smoothing (FLS), which are implemented using the Kalman Filter as applied to a data-driven, mechanistic model of recharge. Forecasting uses past observations to predict future states and is the current paradigm in most groundwater modeling investigations; filtering assimilates observations up to the current time to estimate current states; and FLS estimates states following a time lag over which additional observations are collected. Results for forecasting yield a large error covariance relative to the magnitude of the expected recharge. With assimilating recent observations of h, filtering and FLS produce estimates of recharge that better represent time-varying observations of h and reduce uncertainty in comparison to forecasting. Although model outcomes from applying data assimilation through filtering or FLS reduce model uncertainty, they are not necessarily mass conservative, whereas forecasting outcomes are mass conservative. Mass conservative outcomes from forecasting are not necessarily more accurate, because process errors are inherent in any model. Improvements in estimating real-time groundwater conditions that better represent observations need to be weighed for the model application against outcomes with inherent process deficiencies. In conclusion, results from data assimilation strategies discussed in this investigation are anticipated to be relevant to other groundwater processes models where system states are sensitive to system inputs.

aquifer recharge↗

Estimating reaction parameters in mechanism-enabled population balance models of nanoparticle size distributions: A Bayesian inverse problem approach

In order to quantitatively predict nano- as well as other particle-size distributions, one needs to have both a mathematical model and estimates of the parameters that appear in these models. Here, we show how one can use Bayesian inversion to obtain statistical estimates for the parameters that appear in recently derived mechanism-enabled population balance models (ME-PBM) of nanoparticle growth. The Bayesian approach addresses the question of “how well do we know our parameters, along with their uncertainties?.” The results reveal that Bayesian inversion statistical analysis on an example, prototype $\mathrm{lr(0)_n}$ nanoparticle formation system allows one to estimate not just the most likely rate constants and other parameter values, but also their SDs, confidence intervals, and other statistical information. Moreover, knowing the reliability of the mechanistic model's parameters in turn helps inform one about the reliability of the proposed mechanism, as well as the reliability of its predictions. Importantly, the paper can also be seen as a tutorial with the additional goal of achieving a “Gold Standard” Bayesian inversion ME-PBM benchmark that others can use as a control to check their own use of this methodology for other systems of interest throughout nature. Overall, the results provide strong support for the hypothesis that there is substantial value in using a Bayesian inversion methodology for parameter estimation in particle formation systems.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Dry Season Transpiration and Soil Water Dynamics in the Central Amazon

With current observations and future projections of more intense and frequent droughts in the tropics, understanding the impact that extensive dry periods may have on tree and ecosystem-level transpiration and concurrent carbon uptake has become increasingly important. Here, we investigate paired soil and tree water extraction dynamics in an old-growth upland forest in central Amazonia during the 2018 dry season. Tree water use was assessed via radial patterns of sap flow in eight dominant canopy trees, each a different species with a range in diameter, height, and wood density. Paired multi-sensor soil moisture probes used to quantify volumetric water content dynamics and soil water extraction within the upper 100 cm were installed adjacent to six of those trees. To link depth-specific water extraction patterns to root distribution, fine root biomass was assessed through the soil profile to 235 cm. To scale tree water use to the plot level (stand transpiration), basal area was measured for all trees within a 5 m radius around each soil moisture probe. The sensitivity of tree transpiration to reduced precipitation varied by tree, with some increasing and some decreasing in water use during the dry period. Tree-level water use scaled with sapwood area, from 11 to 190 L per day. Stand level water use, based on multiple plots encompassing sap flow and adjacent trees, varied from ∼1.7 to 3.3 mm per day, increasing linearly with plot basal area. Soil water extraction was dependent on root biomass, which was dense at the surface (i.e., 45% in the upper 5 cm) and declined dramatically with depth. As the dry season progressed and the upper soil dried, soil water extraction shifted to deeper levels and model projections suggest that much of the water used during the month-long dry-down could be extracted from the upper 2–3 m. Results indicate variation in rates of soil water extraction across the research area and, temporally, through the soil profile. These results provide key information on whole-tree contributions to transpiration by canopy trees as water availability changes. In addition, information on simultaneous stand level dynamics of soil water extraction that can inform mechanistic models that project tropical forest response to drought.

54 ENVIRONMENTAL SCIENCES↗

Predicting ecosystem metaphenome from community metagenome: A grand challenge for environmental biology

Abstract Elucidating how an organism's characteristics emerge from its DNA sequence has been one of the great triumphs of biology. This triumph has cumulated in sophisticated computational models that successfully predict how an organism's detailed phenotype emerges from its specific genotype. Inspired by that effort's vision and empowered by its methodologies, a grand challenge is described here that aims to predict the biotic characteristics of an ecosystem, its metaphenome, from nucleic acid sequences of all the species in its community, its metagenome. Meeting this challenge would integrate rapidly advancing abilities of environmental nucleic acids (eDNA and eRNA) to identify organisms, their ecological interactions, and their evolutionary relationships with advances in mechanistic models of complex ecosystems. Addressing the challenge would help integrate ecology and evolutionary biology into a more unified and successfully predictive science that can better help describe and manage ecosystems and the services they provide to humanity.

59 BASIC BIOLOGICAL SCIENCES↗

Assessment of CTF for Steady-state and Transient Post-CHF Conditions in Support of Time-at-Temperature Modeling Applications

The US nuclear industry is exploring options to improve operational economics and uprate the current fleet of light-water reactors by investigating transitioning to cladding performance–based safety criteria as opposed to the current limit, which requires complete avoidance of critical heat flux (CHF)/dryout. Past experience has shown that not all events leading to a dryout are severe enough to cause fuel performance degradation. Allowing temporary dryout of the fuel—that is, using a time-at-temperature (TaT) strategy—could allow for economic improvements via large power uprates and enhanced operational flexibility for current plants without compromising fuel integrity. To support this effort, the US Department of Energy is executing a comprehensive program that includes generating cladding material data under TaT conditions, developing new mechanistic models, and demonstrating modeling and simulation capabilities for transients of interest. This paper presents work performed to assess the CTF thermal-hydraulics subchannel code. CTF is a package used in the VERA core simulator, which will ultimately be used for TaT analysis. CTF will provide the thermal-hydraulic boundary conditions that will be needed for fuel performance analysis in the BISON code. Quantifying both the accuracy and uncertainty of post-CHF models will therefore be necessary. This paper outlines the strategy for the assessment of TaT and presents the results of using the steady-state and transient dryout experiments of the Boiling Fine-mesh Bundle Tests for CTF validation. The results show that the current model tends to overpredict steady-state critical power. This behavior translates to the transient tests, in which CTF is unable to capture transient dryout behavior. Some discussion of sensitivity analysis work being performed is provided to indicate which models must be further analyzed to properly model transient dryout and its uncertainty.

Salko Jr, Robert [ORNL] (ORCID:0000000253566679)↗

Operational and geological controls of coupled poroelastic stressing and pore-pressure accumulation along faults: Induced earthquakes in Pohang, South Korea

Coupled poroelastic stressing and pore-pressure accumulation along pre-existing faults in deep basement contribute to recent occurrence of seismic events at subsurface energy exploration sites. Our coupled fluid-flow and geomechanical model describes the physical processes inducing seismicity corresponding to the sequential stimulation operations in Pohang, South Korea. Simulation results show that prolonged accumulation of poroelastic energy and pore pressure along a fault can nucleate seismic events larger than M w 3 even after terminating well operations. In particular the possibility of large seismic events can be increased by multiple-well operations with alternate injection and extraction that can enhance the degree of pore-pressure diffusion and subsequent stress transfer through a rigid and low-permeability rock to the fault. This study demonstrates that the proper mechanistic model and optimal well operations need to be accounted for to mitigate unexpected seismic hazards in the presence of the site-specific uncertainty such as hidden/undetected faults and stress regime.

58 GEOSCIENCES↗

A Pd III Sulfate Dimer Initiates Rapid Methane Monofunctionalization by H Atom Abstraction

An electrogenerated Pd III 2 species in fuming sulfuric acid is competent for rapid and concurrent methane monohydroxylation to methyl bisulfate (CH 3 OSO 3 H) and methane sulfonation to methanesulfonic acid (CH 3 SO 3 H). In situ NMR at 50 °C is used to track methane transformation exclusively to CH 3 OSO 3 H and CH 3 SO 3 H at high conversions. Integrating a set of kinetic and computational studies, the mechanism of methane monofunctionalization by Pd III 2 is examined. Here, experimental rate laws and common kinetic isotope effects for CH 3 OSO 3 H and CH 3 SO 3 H formation suggest that both transformations proceed via a common rate-limiting C-H activation step. Introduction of O 2 or Pd II,III 2 suppresses CH 3 SO 3 H generation, indicating a radical chain sequence. Although the metal-metal bonded Pd III 2 complex is a net two-electron oxidant, our aggregate kinetic data point to a mechanistic model that features rate-limiting H atom abstraction by the Pd III 2 complex to generate a methyl radical intermediate. The CH 3 • intermediate then recombines with Pd II,III 2 to furnish a CH 3 Pd III 2 intermediate that reductively eliminates CH 3 OSO 3 H. Alternatively, the CH 3 intermediate can enter a chain reaction with SO 3 to generate CH 3 SO 3 H. DFT computations support the radical-based C-H activation by Pd III 2 and delineate H atom abstraction pathways with computed reaction barriers and kinetic isotope effects (KIEs) that are consistent with experimental data. These mechanistic investigations challenge the paradigm of electrophilic C-H activation and highlight H atom abstraction as a potent pathway for selective methane C-H oxidative functionalization at high reaction rates.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Enhance BISON Metal Fuel Transient Models and Enable Assessment Based on Out-of-Pile Transient Experiments

In this report, the activities and achievements made by Argonne National Laboratory for the Nuclear Energy Advanced Modeling and Simulation (NEAMS) BISON code metallic fuel validation and verification (V&V) project in FY2023, with a focus on the capability development and assessment case development for the out-of-pile transient experiments, are summarized. The liquid cladding penetration model was improved based on a comprehensive set of fuel behavior test apparatus (FBTA) test results. The new model was implemented into BISON along with a simple model to account for fuel melting effects. The metallic fuel meshing capability was also upgraded to allow local refinement using unstructured triangular mesh. Based on the previous success in developing the BISON-FIPD integration powered BISON assessment case, this database enabled BISON evaluation and V&V capability was expanded to the out-of-pile transient experiments by introducing BISON-OPTD integration. A series of initial out-of-pile transient assessment cases were implemented into BISON to provide powerful platforms to evaluate current BISON’s capabilities in simulating metallic fuel performance during out-of-pile transients. The established capabilities will also benefit the calibration and V&V of future advanced mechanistic models.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Warming Pattern over the Northern Hemisphere Midlatitudes in Boreal Summer 1979–2020

Abstract Significant surface air temperature warming during summer 1979–2020 is not uniformly distributed in the northern midlatitudes over land but rather is confined to several longitudinal sectors including Europe, central Siberia and Mongolia, and both coasts of North America. These hot spots are accompanied by a chain of high pressure ridges from an anomalous, circumglobal Rossby wave train in the upper troposphere. From reanalysis data and several baseline experiments from phase 6 of the Coupled Model Intercomparison Project (CMIP6), we find that the circulation trend pattern is associated with fluctuations of the Atlantic multidecadal variability (AMV) and the interdecadal Pacific oscillation. The phase shift of AMV in the 1990s is particularly noteworthy for accelerating warming averaged over the northern midlatitude land. The amplitude of the observed trend in both surface air temperature and the upper-level geopotential height generally falls beyond the range of multidecadal trends simulated by the CMIP6 preindustrial control runs, supporting the likelihood that anthropogenic forcing played a critical role in the observed trend. On the other hand, the fidelity of the simulated low-frequency modes of variability and their teleconnections, especially on multidecadal time scales, is difficult to assess because of the relatively short observational records. Our mechanistic modeling results indicate that synoptic eddy–mean flow interaction is a key to the formation of the anomalous wave train but how the multidecadal modes can modulate the synoptic eddies through atmosphere–ocean and atmosphere–land interactions remains poorly understood. This gap in our knowledge makes it challenging to quantify the roles of the low-frequency modes and external forcings in causing the observed multidecadal trends.

54 ENVIRONMENTAL SCIENCES↗