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At least 271 records · Page 15

Sequential spectral line analysis for accurate density and temperature diagnosis of laboratory opacity measurements

The accuracy of iron opacity calculated in stellar interiors has been questioned since the discovery of the “solar problem” and the discrepancies between the measured and modeled iron opacity reported in 2015. Experimental opacity benchmarks require accurate temperature and density measurements, which were inferred by analyzing tracer magnesium spectra in those experiments. Could the observed discrepancy be explained by insufficient accuracy in the inferred temperature, density, and their uncertainties? Previous analyses may have yielded biased results due to three limitations: (1) simultaneous multi-line fitting, (2) approximations in line-shape models, and (3) exclusion of certain spectral lines due to insufficient background characterization. Notably, the first issue is a common concern for many inversion methods, including Bayesian inferences. We present a refined analysis method that overcomes these limitations, applied to three categories of iron opacity experiments (Anchor 1, 2, and 3). In particular, the sequential fitting method yields unbiased results with more realistic uncertainties by accounting for line inconsistencies in the parameter uncertainties. The average electron temperature and density values are 162 ± 6 eV and (7.0 ± 1.9) × 10 21 cm −3 for six Anchor 1 experiments, 189 ± 7 eV and (3.4 ± 0.3) × 10 22 cm −3 for 21 Anchor 2 experiments, and 201 ± 6 eV and (4.8 ± 1.1) × 10 22 cm −3 for nine Anchor 3 experiments. These results show ∼4% temperature and ∼20% density reproducibility over a decade, which also aligns with the inferred parameter uncertainties. In conclusion, the resulting temperature and density uncertainties lead to a quasi-continuum iron opacity variation of ±4%–7% for wavelengths below 9.5 Å, which is insufficient to explain the significant model-data discrepancies reported in 2015.

Absorption spectroscopy↗

Solar Models in Light of New High Metallicity Measurements from Solar Wind Data

We study the impact of new metallicity measurements, from solar wind data, on the solar model. The “solar modeling problem” refers to the persisting discrepancy between helioseismological observations and predictions of solar models computed implementing state-of-the-art photospheric abundances. We critically reassess the problem, in particular considering the new set of abundances of von Steiger and Zurbuchen, determined through the in situ collection of solar wind samples from polar coronal holes. This new set of abundances indicates a solar metallicity Z{sub ⊙}⩾0.0196±0.0014, significantly higher than the currently established value. The new values hint at an abundance of volatile elements (i.e., C, N, O, Ne) close to previous results of Grevesse and Sauval, whereas the abundance of refractory elements (i.e., Mg, Si, S, Fe) is considerably increased. Using the Linear Solar Model formalism, we determine the variation of helioseismological observables in response to the changes in elemental abundances, in order to explore the consistency of these new measurements with constraints from helioseismology. We find that for observables that are particularly sensitive to the abundance of volatile elements, in particular the radius of the convective zone boundary (CZB) and the sound speed around the radius of CZB, improved agreement over previous models is obtained. Conversely, the high abundance of refractories correlates with a higher core temperature, resulting in an overproduction of neutrinos and a huge increase in the surface helium abundance. We conclude that the “solar modeling problem” remains unsolved.

79 ASTRONOMY AND ASTROPHYSICS↗

STEM HAADF Image Simulation of the Orthorhombic M1 Phase in the Mo-V-Nb-Te-O Propane Oxidation Catalyst

A full frozen phonon multislice simulation of high angle annular dark field scanning transmission electron microscopy (HAADF STEM) images from the M1 phase of the Mo-V-Nb-Te-O propane oxidation catalyst has been performed by using the latest structural model obtained using the Rietveld method. Simulated contrast results are compared with experimental HAADF images. Good agreement is observed at ring sites, however significant thickness dependence is noticed at the linking sites. The remaining discrepancies between the model based on Rietveld refinement and image simulations indicate that the sampling of a small volume element in HAADF STEM and averaging elemental contributions of a disordered site in a crystal slab by using the virtual crystal approximation might be problematic, especially if there is preferential Mo/V ordering near the (001) surface.

36 MATERIALS SCIENCE↗

Physics-Informed Machine Learning with Application to Solid Oxide Fuel Cell System Modeling and Optimization

Traditional data-driven machine learning (ML) techniques were combined with the physics-based SOFC-MP model toward improving SOFC system-level performance prediction. Four different physics-informed ML methods were proposed to demonstrate better prediction accuracy compared with traditional ML methods. First, it was preferred that the existing Kriging-based surrogate model not be entirely abandoned, so errors between Kriging regression prediction and true solution are learned using ML. The goal was to find the pattern of the error distribution as a function of model input so discrepancies between the Kriging prediction and true solution could be reduced by adding the additional ML-trained error term to the existing prediction. Second, deep neural networks (DNN) coupled with the mass balance model (MBM) have been developed to significantly decrease the reduced order model (ROM) prediction error with fewer training data compared to the traditional Kriging-based ROM and traditional DNN regression approaches. Third, DNN regression coupled with a neural networks (NN) classifier and MBM was developed. It provides superior performance on classifying the physically operational conditions for natural gas fuel cell (NGFC) than traditional classification approaches. Finally, two kinds of DNN transferring were studied and tested. One was transferring DNN for low-fidelity model data to a high-fidelity model. The second one was transferring DNN from state-of-the-art NGFC to advanced NGFC. These physic-informed ML frameworks can serve as a solid foundation for estimating U.S. Department of Energy-targeted fuel cell performance and exhibit great potential to be employed to other engineering applications.

30 DIRECT ENERGY CONVERSION↗

Exclusive η Electro-Production Beam Spin Asymmetry Measurements using CLAS12 at Jefferson Lab

The exploration of nucleon structure and electromagnetic transitions from ground-state to excited-state is a cornerstone of nuclear physics research. Meson electro-production experiments have opened new avenues for investigating these phenomena, particularly in the 12 GeV era at Jefferson Lab with the CLAS12 spectrometer. The ?N final states, accessible only through isospin resonances I = 1/2, provide a unique tool for studying nucleon excitations. By simplifying the analysis and enabling a cleaner extraction of resonance properties compared to the extensively studied ?N final states, ? electroproduction offers a complementary approach to unraveling the structure of excited nucleons. This work presents the first-ever measurement of the beam spin asymmetry (BSA) in exclusive ? electroproduction, covering a previously unexplored kinematic region with 1.6 ? W ? 2.2 GeV. The BSA is extracted from the CLAS12 data using a comprehensive analysis framework that carefully considers the statistical limitations of the data set. The results are compared to predictions from theoretical models, such as the Jülich-Bonn-Washington (JBW) and MAID, as well as compared to previously published cross-section and spin observable results from CLAS and SLAC. Notably, the extracted BSA exhibits discrepancies with the model predictions, highlighting the potential for refining theoretical descriptions of nucleon resonances and their electromagnetic couplings through the incorporation of these new data. The high precision data obtained in this previously unmeasured kinematic region now serve as valuable input for theorists to refine their models.

Illari, Isabella↗

Northern Hemisphere Blocking in ~25-km-Resolution E3SM v0.3 Atmosphere-Land Simulations

The fidelity of a prerelease Energy Exascale Earth System Model (E3SM) in reproducing atmospheric blocking is evaluated with ~100- and ~25-km horizontal resolution within ensembles of simulations with Atmospheric Modeling Intercomparison Protocol-type active atmosphere and land surface configurations. Here this evaluation is conducted via a hybrid bidimensional blocking index based on geopotential height. The lower-resolution model correctly reproduces the spatial distribution of blocking frequency maxima over the Northern Hemisphere. However, it overestimates the blocking frequency over western North America, the Pacific Northeast, and Eastern Europe regions and largely underestimates blocking frequency over the North Atlantic. The high-resolution model significantly reduces the bias over the North Pacific region, particularly over western North America, but the biases over the North Atlantic blocking sector mostly persist. A diagnosis of the mean flow reveals that the subtropical jet is displaced poleward in the high-resolution model with a jet core speed that is generally more realistic. A time scale analysis of eddies suggests that synoptic eddies associated with the blocking events are increased in the high-resolution configuration. The discrepancy between the models implies that both synoptic and low-frequency eddies play significant roles in determining North Pacific blocking, whereas North Atlantic blocking is mainly driven by low-frequency eddies. The characteristic time scale associated with blocking events is also investigated, and it shows that both model resolutions produce events that are overly persistent. However, the bias in the high-resolution model is reduced, which reflects more efficient energy dispersion with higher resolution.

54 ENVIRONMENTAL SCIENCES↗

Observations and modeling of the companions of short period binary millisecond pulsars: evidence for high-mass neutron stars

We present observations of fields containing eight recently discovered binary millisecond pulsars using the telescopes at MDM Observatory. Optical counterparts to four of these systems are detected, one of which, PSR J2214+3000, is a novel detection. Additionally, we present the fully phase-resolved B, V, and R light curves of the optical counterparts to two objects, PSR J1810+1744 and PSR J2215+5135 for which we employ model fitting using the eclipsing light curve (ELC) model of Orosz and Hauschildt to measure the unknown system parameters. For PSR J1810+1744, we find that the system parameters cannot be fit even assuming that 100% of the spin-down luminosity of the pulsar is irradiating the secondary, and so radial velocity measurements of this object will be required for the complete solution. However, PSR J2215+5135 exhibits light curves that are extremely well constrained using the ELC model and we find that the mass of the neutron star is constrained by these and the radio observations to be M {sub NS} > 1.75 M {sub ☉} at the 3σ level. We also find a discrepancy between the model temperature and the measured colors of this object, which we interpret as possible evidence for an additional high-temperature source such as a quiescent disk. Given this and the fact that PSR J2215+5135 contains a relatively high mass companion (M {sub c} > 0.1 M {sub ☉}), we propose that similar to the binary pulsar systems PSR J1023+0038 and IGR J18245–2452, the pulsar may transition between accretion- and rotation-powered modes.

79 ASTRONOMY AND ASTROPHYSICS↗

Measurement of Inclusive Charged-Current $\barν_μ$ Scattering on C, CH, Fe, and Pb at $\langle E_{\barν}\rangle \sim$ 6 GeV with MINERvA

We report MINERvA's first measurement of inclusive charged-current $\barν_μ$ cross sections on carbon, hydrocarbon, iron, and lead, and their ratios to the cross section on hydrocarbon, as functions of the antimuon transverse momentum, $p_{\mathrm{T}}$. Using a wide-band $\barν_μ$ beam with mean energy $\sim 6~\text{GeV}$, these measurements probe all interaction modes, including the transition from resonance production to deep-inelastic scattering. The total uncertainties are typically $5-10\%$ for the absolute cross sections and $2-5\%$ for the ratios. Comparisons with multiple neutrino interaction models reveal significant discrepancies in the $p_{\mathrm{T}}$ dependence, particularly for heavier nuclei. The disagreements are most pronounced at low $p_{\mathrm{T}}$ but extend across the full $p_{\mathrm{T}}$ range, indicating missing or mis-modelled nuclear effects.

Klustová, A. [Imperial Coll., London] (ORCID:00000↗

Uncertainty quantification of a physics-informed model based on sparse identification of a Thermal Energy Distribution System

Integrated energy systems (IES)s are crucial for enhancing the economy and efficiency of power generation sources (e.g., nuclear energy) necessary to unleash American energy dominance. These systems can be integrated with thermal energy storage (TES) and intermittent renewable energies to optimize overall energy use, peak-load regulation, and demand-side responses. However, the stabilization of energy generation, transport, and utilization introduces operational complexities that exceed the challenges of managing each sub-component individually. Currently, though IESs rely on human operators for efficiency and stability, reducing human error risk and enhancing performance through automation is highly desirable. Recent advances at Idaho National Laboratory have demonstrated successful control of the Thermal Energy Distributed System (TEDS). However, the automatic control system depends on a deterministic Sparse Identification of Nonlinear Dynamics with Control (SINDyC) model, which are trained based on simulation data from physics-based simulations. Because of uncertainties in physics-based simulation, SINDyC model results in large discrepancies against experimental data and cannot be reliably used in automatic control. In this paper, we present an innovative approach to address these discrepancies by quantifying uncertainties and developing a more robust model. We first generated trajectories by using first-principles physics codes to encapsulate the experiment. Next, we trained thousands of models by randomly sampling these trajectories. We then collapsed all those models into one probabilistic SINDyC by fitting a multivariate Gaussian distribution onto the resulting coefficient’s distribution. Despite its simplicity, our approach successfully produced 95% confidence intervals that captured the experimental trajectories. It even did so with a higher probability and better U-pooling score across six of the seven relevant quantities of interest (QoIs), as compared to other classical approaches. In conclusion, ongoing research is focusing on generating new experimental trajectories to validate this approach, and on employing Bayesian calibration to refine parametric uncertainties and guide future model development efforts.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗

In situ measurement of three-dimensional intergranular stress localizations and grain yielding under elastoplastic axial-torsional loading

The three-dimensional grain-averaged response of solid bar samples under non-proportional (NP) elastoplastic axial-torsional loading was investigated using in situ high energy diffraction microscopy (HEDM) and companion crystal plasticity finite element (CPFE) modeling. Important stress metrics including applied shear (σ θZ ) and axial (σ ZZ ) stress tensor components, stress and stress deviator tensor invariants (I 1 , J 2 , and J 3 ), von Mises equivalent stress (σ$^{grain}_{VM}$), maximum resolved shear stress (mRSS), stress triaxiality (η), and lode angle parameter ($\barθ$) values were tracked for ~300 grains under two different loading conditions: (1) Torsion-dominated loading (low NP) and (2) Tension-torsion loading (high NP) in equiatomic NiCoCr, a representative multicomponent face-centered cubic (FCC) superalloy. Overall, significant stress localizations existed within both samples as evidenced by the radial dependence of grain-resolved σ θZ , σ$^{grain}_{VM}$, and J 2 ; by comparison, I 1 , J 3 , η, and $\barθ$ metrics did not show discernible trends within the volume. These stress localizations reveal a complex interplay between axial and shear stress components (e.g., stress coupling) resulting in grain yielding near the sample surface largely driven by shear stress, whereas internal grain yielding was largely accommodated by axial stress. Grain-resolved stress localization trends were described well by the CPFE model, although some discrepancies in magnitude occurred, particularly for volumetric stress metrics (I 1 and η) due to initial type II residual stress distributions. The superposition of initial residual stress states onto CPFE grain-resolved data significantly improved model accuracy for η. This suggests that residual stresses more strongly influence the simulation of volumetric rather than deviatoric (yield) stress metrics.

36 MATERIALS SCIENCE↗

Transport and Loss of Ring Current Electrons Inside Geosynchronous Orbit During the 17 March 2013 Storm

Ring current electrons (1–100 keV) have received significant attention in recent decades, but many questions regarding their major transport and loss mechanisms remain open. In this study, we use the four-dimensional Versatile Electron Radiation Belt code to model the enhancement of phase space density that occurred during the 17 March 2013 storm. Our model includes global convection, radial diffusion, and scattering into the Earth's atmosphere driven by whistler-mode hiss and chorus waves. We study the sensitivity of the model to the boundary conditions, global electric field, the electric field associated with subauroral polarization streams, electron loss rates, and radial diffusion coefficients. The results of the code are almost insensitive to the model parameters above 4.5 R E R E , which indicates that the general dynamics of the electrons between 4.5 R E and the geostationary orbit can be explained by global convection. We found that the major discrepancies between the model and data can stem from the inaccurate electric field model and uncertainties in lifetimes. We show that additional mechanisms that are responsible for radial transport are required to explain the dynamics of ≥40-keV electrons, and the inclusion of the radial diffusion rates that are typically assumed in radiation belt studies leads to a better agreement with the data. The overall effect of subauroral polarization streams on the electron phase space density profiles seems to be smaller than the uncertainties in other input parameters. This study is an initial step toward understanding the dynamics of these particles inside the geostationary orbit.

79 ASTRONOMY AND ASTROPHYSICS↗

Southern Ocean Sulfate Aerosol Sources Quantified From Sulfur Isotopes in Antarctic Ice Cores

The Southern Ocean has emerged as a key region for constraining aerosol-climate interactions due to its relatively low anthropogenic influence. Sulfate is an important aerosol over the Southern Ocean, and models suggest dimethyl sulfide (DMS) is the largest source of sulfate during summer. However, sulfur isotopes of sulfate (δ 34 S(SO 4 2− )) in Antarctic ice cores suggest a significant contribution from a previously unexplained non-DMS source. Here we show that the fractional contribution from passive volcanic degassing (f volc ) explains observed δ 34 S(SO 4 2− ), and that a global chemical transport model underestimates f volc across Antarctica. Underestimated f volc implies that the model mischaracterizes sulfate sources in this important region. The discrepancy between observed and modeled sulfate sources can be reconciled by increasing passive volcanic sulfur degassing emissions and decreasing DMS emissions. Our results imply that current biases in emissions inventories could bias assessments of aerosol-cloud interactions in the Southern Ocean region and globally.

Jongebloed, Ursula A. [Univ. of Washington, Seattl↗

High temperature inelastic constitutive models for the ASME Section III, Division 5 Class A materials

This report describes the exploration of a universal high temperature inelastic constitutive model for use with the ASME Boiler & Pressure Vessel Code Section III, Division 5, Class A design rules. The idea, developed based on feedback from reactor vendors, is to simplify the current bespoke material models for Grade 91, 316H, and Alloy 617 and the new model for Alloy 800H into a simple, single model form. The report describes a new parallel time integration technique implemented in the pyoptmat package which allowed us to explore a wide variety of model forms, searching for a suitable common model. The report then describes preliminary work on models for monontonic deformation and then the development of a set of models suitable for capturing high temperature cyclic deformation. These models are suitable for use with the ASME design rules, except potentially for a narrow, material-specific band of temperatures at the edge of the creep regime. An incremental improvement the current models could overcome this discrepancy and provide a new, simpler set of constitutive model for all four materials.

36 MATERIALS SCIENCE↗

Intermittency and lifetime of the 625 Hz quasi-periodic oscillation in the 2004 hyperflare from the magnetar SGR 1806-20 as evidence for magnetic coupling between the crust and the core

Quasi-periodic oscillations (QPOs) detected in the 2004 giant flare from SGR 1806-20 are often interpreted as global magneto-elastic oscillations of the neutron star. There is, however, a large discrepancy between theoretical models, which predict that the highest frequency oscillations should die out rapidly, and the observations, which suggested that the highest-frequency signals persisted for ∼100 s in X-ray data from two different spacecraft. This discrepancy is particularly important for the high-frequency QPO at ∼625 Hz. However, previous analyses did not systematically test whether the signal could also be present in much shorter data segments, more consistent with the theoretical predictions. Here, we test for the presence of the high-frequency QPO at 625 Hz in data from both the Rossi X-ray Timing Explorer (RXTE) and the Ramaty High Energy Solar Spectroscopic Imager (RHESSI) systematically both in individual rotational cycles of the neutron star, as well as averaged over multiple successive rotational cycles at the same phase. We find that the QPO in the RXTE data is consistent with being only present in a single cycle, for a short duration of ∼0.5 s, whereas the RHESSI data are as consistent with a short-lived signal that appears and disappears as with a long-lived QPO. Taken together, this data provides evidence for strong magnetic interaction between the crust and the core.

79 ASTRONOMY AND ASTROPHYSICS↗

FIRE SPECTROSCOPY OF THE ULTRA-COOL BROWN DWARF, UGPS J072227.51-054031.2: KINEMATICS, ROTATION AND ATMOSPHERIC PARAMETERS

We present {lambda}/{Delta}{lambda} {approx} 6000 near-infrared spectroscopy of the nearby T9 dwarf, UGPS J072227.51-054031.2, obtained during the commissioning of the Folded-Port Infrared Echellette Spectrograph on the Baade Magellan telescope at Las Campanas Observatory. The spectrum is marked by significant absorption from H{sub 2}O, CH{sub 4}, and H{sub 2}. We also identify NH{sub 3} absorption features by comparing the spectrum to recently published line lists. The spectrum is fit with BT-Settl models, indicating T{sub eff} {approx}500-600 K and log g {approx}4.3-5.0. This corresponds to a mass of {approx}10-30 M{sub Jup} and an age of 1-5 Gyr, however, there are large discrepancies between the model and observed spectrum. The radial and rotational velocities of the brown dwarf are measured as 46.9 {+-} 2.5 and 40 {+-} 10 km s{sup -1}, respectively, reflecting a thin disk Galactic orbit and fast rotation similar to other T dwarfs, suggesting a young, possibly planetary-mass brown dwarf.

79 ASTRONOMY AND ASTROPHYSICS↗

The mass–radius relation of young stars. I. USCO 5, an M4.5 eclipsing binary in upper Scorpius observed by K2

We present the discovery that UScoCTIO 5, a known spectroscopic binary in the Upper Scorpius star-forming region (P = 34 days, M{sub tot}sin(i)=0.64 M{sub ⊙}), is an eclipsing system with both primary and secondary eclipses apparent in K2 light curves obtained during Campaign 2. We have simultaneously fit the eclipse profiles from the K2 light curves and the existing RV data to demonstrate that UScoCTIO 5 consists of a pair of nearly identical M4.5 stars with M{sub A}=0.329±0.002 M{sub ⊙}, R{sub A}=0.834±0.006 R{sub ⊙}, M{sub B}=0.317±0.002 M{sub ⊙}, and R{sub B}=0.810±0.006 R{sub ⊙}. The radii are broadly consistent with pre-main-sequence ages predicted by stellar evolutionary models, but none agree to within the uncertainties. All models predict systematically incorrect masses at the 25%–50% level for the HR diagram position of these mid-M dwarfs, suggesting significant modifications to mass-dependent outcomes of star and planet formation. The form of the discrepancy for most model sets is not that they predict luminosities that are too low, but rather that they predict temperatures that are too high, suggesting that the models do not fully encompass the physics of energy transport (via convection and/or missing opacities) and/or a miscalibration of the SpT–T{sub eff} scale. The simplest modification to the models (changing T{sub eff} to match observations) would yield an older age for this system, in line with the recently proposed older age of Upper Scorpius (τ ∼ 11 Myr).

79 ASTRONOMY AND ASTROPHYSICS↗

In-depth analysis of solar models with high-metallicity abundances and updated opacity tables

Context. As a result of the high-quality constraints available for the Sun, we are able to carry out detailed combined analyses using neutrino, spectroscopic, and helioseismic observations. These studies lay the ground for future improvements of the key physical components of solar and stellar models because ingredients such as the equation of state, the radiative opacities, or the prescriptions for macroscopic transport processes of chemicals are then used to study other stars in the Universe. Aims. We study the existing degeneracies in solar models using the recent high-metallicity spectroscopic abundances by comparing them to helioseismic and neutrino data and discuss the effect on their properties of changes in the micro and macro physical ingredients. Methods. We carried out a detailed study of solar models computed with a high-metallicity composition from the literature based on averaged 3D models that were claimed to resolve the solar modelling problem. We compared these models to helioseismic and neutrino constraints. Results. The properties of the solar models are significantly affected by the use of the recent OPLIB opacity tables and the inclusion of macroscopic transport. The properties of the standard solar models computed using the OPAL opacities are similar to those for which the OP opacities were used. We show that a modification of the temperature gradient just below the base of the convective zone is required to remove the discrepancies in solar models, particularly in the presence of macroscopic mixing. This can be simulated by a localised increase in the opacity of a few percent. Conclusions. We conclude that the existing degeneracies and issues in solar modelling are not removed by using an increase in the solar metallicity, in contradiction to what has been suggested in the recent literature. Therefore, standard solar models cannot be used as an argument for a high-metallicity composition. While further work is required to improve solar models, we note that direct helioseismic inversions indicate a low metallicity in the convective envelope, in agreement with spectroscopic analyses based on full 3D models.

74 ATOMIC AND MOLECULAR PHYSICS↗

Regional climate change: consensus, discrepancies, and ways forward

Climate change has emerged across many regions. Some observed regional climate changes, such as amplified Arctic warming and land-sea warming contrasts have been predicted by climate models. However, many other observed regional changes, such as changes in tropical sea surface temperature and monsoon rainfall are not well simulated by climate model ensembles even when taking into account natural internal variability and structural uncertainties in the response of models to anthropogenic radiative forcing. This suggests climate model predictions may not fully reflect what our future will look like. The discrepancies between models and observations are not well understood due to several real and apparent puzzles and limitations such as the “signal-to-noise paradox” and real-world record-shattering extremes falling outside of the possible range predicted by models. Addressing these discrepancies, puzzles and limitations is essential, because understanding and reliably predicting regional climate change is necessary in order to communicate effectively about the underlying drivers of change, provide reliable information to stakeholders, enable societies to adapt, and increase resilience and reduce vulnerability. The challenges of achieving this are greater in the Global South, especially because of the lack of observational data over long time periods and a lack of scientific focus on Global South climate change. To address discrepancies between observations and models, it is important to prioritize resources for understanding regional climate predictions and analyzing where and why models and observations disagree via testing hypotheses of drivers of biases using observations and models. Gaps in understanding can be discovered and filled by exploiting new tools, such as artificial intelligence/machine learning, high-resolution models, new modeling experiments in the model hierarchy, better quantification of forcing, and new observations. Conscious efforts are needed toward creating opportunities that allow regional experts, particularly those from the Global South, to take the lead in regional climate research. This includes co-learning in technical aspects of analyzing simulations and in the physics and dynamics of regional climate change. Finally, improved methods of regional climate communication are needed, which account for the underlying uncertainties, in order to provide reliable and actionable information to stakeholders and the media.

54 ENVIRONMENTAL SCIENCES↗