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Enhanced warming of the Arctic region relative to the rest of the globe, known as Arctic amplification, is caused by a variety of diverse factors, many of which are influenced by the Atlantic meridional overturning circulation (AMOC). Here, we quantify the role of AMOC changes in Arctic amplification throughout the twenty-first century by comparing two suites of climate model simulations under the same climate change scenario but with two different AMOC states: one with a weakened AMOC and another with a steady AMOC. We find that a weakened AMOC can reduce annual mean Arctic warming by 2 °C by the end of the century. A primary contributor to this reduction in warming is surface albedo feedback, related to a smaller sea ice loss due to AMOC slowdown. Another major contributor is the changes in ocean heat uptake. The weakened AMOC and its associated anomalous ocean heat transport divergence lead to increased ocean heat uptake and surface cooling. These two factors are inextricably linked on seasonal timescales, and their relative importance for Arctic amplification can vary by season. The weakened AMOC can also abate Arctic warming via lapse rate feedback, creating marked cooling from the surface to lower-to-mid troposphere while resulting in relatively weaker cooling in the upper troposphere. Additionally, the weakened AMOC increases the low-level cloud fraction over the North Atlantic warming hole, causing significant cooling there via shortwave (sw) cloud feedback despite the overall effect of sw cloud feedback being a slight warming of the average temperature over the Arctic. 

(Bi,Sb)2(Te,Se)3 tetradymite materials are among the most efficient for thermoelectric energy conversion, and most robust for topological insulator spintronic technologies, but should possess rather disparate doping properties to be useful for either technology. In this work, we report results on the molecular beam epitaxy growth of p-type (Bi0.43Sb0.57)2Te3 and n-type Bi2(Te0.95Se0.05)3 that can contribute to both technology bases, but are especially useful for topological insulators where low bulk doping is critical for devices to leverage the Dirac-like topological surface states. Comprehensive temperature, field and angular dependent magnetotransport measurements have attested to the superior quality of these ternary tetradymite films, displaying low carrier density on the order of 1018 cm–3 and a record high mobility exceeding 104 cm2 V–1 s–1 at 2 K. The remarkable manifestation of strong Shubnikov–de Haas (SdH) quantum oscillation under 9 T at liquid helium temperatures, as well as the analyses therein, has allowed direct experimental investigation of the tetradymite electronic structure with optimized ternary alloying ratio. Our effort substantiates tetradymites as a critical platform for miniaturized thermoelectric cooling and power generation in wearable consumer electronics, as well as for futuristic topological spintronics with unprecedented magnetoelectric functionalities. 

Polar metals are challenging to identify spectroscopically because the fingerprints of electric polarization are often obscured by the presence of screening charges. Here, we unravel unambiguous signatures of a distortive polar order buried in the Fermi sea by probing the nonlinear optical response of materials driven by tailored terahertz fields. We apply this strategy to investigate the topological crystalline insulator Pb_1−xSn_xTe, tracking its soft phonon mode in the time domain and observing the occurrence of inversion symmetry breaking as a function of temperature. By combining measurements across the material’s phase diagram with ab initio calculations, we demonstrate the generality of our approach. These results highlight the potential of terahertz driving fields to reveal polar orders coexisting with itinerant electrons, thus opening additional avenues for material discovery. 

Abstract Magnetic transition metal chalcogenides form an emerging platform for exploring spin-orbit driven Berry phase phenomena owing to the nontrivial interplay between topology and magnetism. Here we show that the anomalous Hall effect in pristine Cr 2 Te 3 thin films manifests a unique temperature-dependent sign reversal at nonzero magnetization, resulting from the momentum-space Berry curvature as established by first-principles simulations. The sign change is strain tunable, enabled by the sharp and well-defined substrate/film interface in the quasi-two-dimensional Cr 2 Te 3 epitaxial films, revealed by scanning transmission electron microscopy and depth-sensitive polarized neutron reflectometry. This Berry phase effect further introduces hump-shaped Hall peaks in pristine Cr 2 Te 3 near the coercive field during the magnetization switching process, owing to the presence of strain-modulated magnetic layers/domains. The versatile interface tunability of Berry curvature in Cr 2 Te 3 thin films offers new opportunities for topological electronics. 

Abstract Near-Earth asteroids (NEAs) are a key test bed for investigations into planet formation, asteroid dynamics, and planetary defense initiatives. These studies rely on understanding NEA sizes, albedo distributions, and regolith properties. Simple thermal models are a commonly used method for determining these properties; however, they have inherent limitations owing to the simplifying assumptions they make about asteroid shapes and properties. With the recent collapse of the Arecibo Telescope and a decrease of direct size measurements, as well as future facilities such as LSST and NEO Surveyor coming online soon, these models will play an increasingly important role in our knowledge of the NEA population. Therefore, it is key to understand the limits of these models. In this work we constrain the limitations of simple thermal models by comparing model results to more complex thermophysical models, radar data, and other existing analyses. Furthermore, we present a method for placing tighter constraints on inferred NEA properties using simple thermal models. These comparisons and constraints are explored using the NEA (285263) 1998 QE2 as a case study. We analyze QE2 with a simple thermal model and data from both the NASA IRTF SpeX instrument and NEOWISE mission. We determine an albedo between 0.05 and 0.10 and thermal inertia between 0 and 425J m⁻²s^−1/2K⁻¹. We find that overall the simple thermal model is able to well constrain the properties of QE2; however, we find that model uncertainties can be influenced by topography, viewing geometry, and the wavelength range of data used. 

Accurate multidecadal radiative flux records are vital to understand Arctic amplification and constrain climate model uncertainties. Uncertainty in the NASA Clouds and the Earth’s Radiant Energy System (CERES)-derived irradiances is larger over sea ice than any other surface type and comes from several sources. The year-long Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition in the central Arctic provides a rare opportunity to explore uncertainty in CERES-derived radiative fluxes. First, a systematic and statistically robust assessment of surface shortwave and longwave fluxes was conducted using in situ measurements from MOSAiC flux stations. The CERES Synoptic 1degree (SYN1deg) product overestimates the downwelling shortwave flux by +11.40 Wm–2 and underestimates the upwelling shortwave flux by –15.70 Wm–2 and downwelling longwave fluxes by –12.58 Wm–2 at the surface during summer. In addition, large differences are found in the upwelling longwave flux when the surface approaches the melting point (approximately 0°C). The biases in downwelling shortwave and longwave fluxes suggest that the atmosphere represented in CERES is too optically thin. The large negative bias in upwelling shortwave flux can be attributed in large part to lower surface albedo (–0.15) in satellite footprint relative to surface sensors. Additionally, the results show that the spectral surface albedo used in SYN1deg overestimates albedo in visible and mid-infrared bands. A series of radiative transfer model perturbation experiments are performed to quantify the factors contributing to the differences. The CERES-MOSAiC broadband albedo differences (approximately 20 Wm–2) explain a larger portion of the upwelling shortwave flux difference than the spectral albedo shape differences (approximately 3 Wm–2). In addition, the differences between perturbation experiments using hourly and monthly MOSAiC surface albedo suggest that approximately 25% of the sea ice surface albedo variability is explained by factors not correlated with daily sea ice concentration variability. Biases in net shortwave and longwave flux can be reduced to less than half by adjusting both albedo and cloud inputs toward observed values. The results indicate that improvements in the surface albedo and cloud data would substantially reduce the uncertainty in the Arctic surface radiation budget derived from CERES data products. 

Abstract Brains demonstrate varying spatial scales of nested hierarchical clustering. Identifying the brain’s neuronal cluster size to be presented as nodes in a network computation is critical to both neuroscience and artificial intelligence, as these define the cognitive blocks capable of building intelligent computation. Experiments support various forms and sizes of neural clustering, from handfuls of dendrites to thousands of neurons, and hint at their behavior. Here, we use computational simulations with a brain-derived fMRI network to show that not only do brain networks remain structurally self-similar across scales but also neuron-like signal integration functionality (“integrate and fire”) is preserved at particular clustering scales. As such, we propose a coarse-graining of neuronal networks to ensemble-nodes, with multiple spikes making up its ensemble-spike and time re-scaling factor defining its ensemble-time step. This fractal-like spatiotemporal property, observed in both structure and function, permits strategic choice in bridging across experimental scales for computational modeling while also suggesting regulatory constraints on developmental and evolutionary “growth spurts” in brain size, as per punctuated equilibrium theories in evolutionary biology. 

Arctic amplification (AA) is a coupled atmosphere-sea ice-ocean process. This understanding has evolved from the early concept of AA, as a consequence of snow-ice line progressions, through more than a century of research that has clarified the relevant processes and driving mechanisms of AA. The predictions made by early modeling studies, namely the fall/winter maximum, bottom-heavy structure, the prominence of surface albedo feedback, and the importance of stable stratification have withstood the scrutiny of multi-decadal observations and more complex models. Yet, the uncertainty in Arctic climate projections is larger than in any other region of the planet, making the assessment of high-impact, near-term regional changes difficult or impossible. Reducing this large spread in Arctic climate projections requires a quantitative process understanding. This manuscript aims to build such an understanding by synthesizing current knowledge of AA and to produce a set of recommendations to guide future research. It briefly reviews the history of AA science, summarizes observed Arctic changes, discusses modeling approaches and feedback diagnostics, and assesses the current understanding of the most relevant feedbacks to AA. These sections culminate in a conceptual model of the fundamental physical mechanisms causing AA and a collection of recommendations to accelerate progress towards reduced uncertainty in Arctic climate projections. Our conceptual model highlights the need to account for local feedback and remote process interactions within the context of the annual cycle to constrain projected AA. We recommend raising the priority of Arctic climate sensitivity research, improving the accuracy of Arctic surface energy budget observations, rethinking climate feedback definitions, coordinating new model experiments and intercomparisons, and further investigating the role of episodic variability in AA.