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At least 973 records · Page 54

SCExAO CHARIS Direct Imaging Discovery of a 20 au Separation, Low-mass Ratio Brown Dwarf Companion to an Accelerating Sun-like Star

We present the direct imaging discovery of a substellar companion to the nearby Sun-like star, HD 33632 Aa, at a projected separation of ∼20 au, obtained with SCExAO/CHARIS integral field spectroscopy complemented by Keck/NIRC2 thermal infrared imaging. The companion, HD 33632 Ab, induces a 10.5σ astrometric acceleration on the star as detected with the Gaia and Hipparcos satellites. SCExAO/CHARIS JHK (1.1–2.4 μm) spectra and Keck/NIRC2 L(sub p) (3.78 μm) photometry are best matched by a field L/T transition object: an older, higher-gravity, and less dusty counterpart to HR 8799 cde. Combining our astrometry with Gaia/Hipparcos data and archival Lick Observatory radial velocities, we measure a dynamical mass of 46.4 ± 8 MJ and an eccentricity of e < 0.46 at 95% confidence. HD 33632 Ab’s mass and mass ratio (4.0% ± 0.7%) are comparable to the low-mass brown dwarf GJ 758 B and intermediate between the more massive brown dwarf HD 19467 B and the (near-)planet-mass companions to HR 2562 and GJ 504. Using Gaia to select for direct imaging observations with the newest extreme adaptive optics systems can reveal substellar or even planet-mass companions on solar system–like scales at an increased frequency compared to blind surveys

exoplanets↗

The Importance of Being Adaptable: An Exploration of the Power and Limitations of Domain Adaptation for Simulation-Based Inference with Galaxy Clusters

The application of deep machine learning methods in astronomy has exploded in the last decade, with new models showing remarkably improved performance on benchmark tasks. Not nearly enough attention is given to understanding the models' robustness, especially when the test data are systematically different from the training data, or "out of domain." Domain shift poses a significant challenge for simulation-based inference, where models are trained on simulated data but applied to real observational data. In this paper, we explore domain shift and test domain adaptation methods for a specific scientific case: simulation-based inference for estimating galaxy cluster masses from X-ray profiles. We build datasets to mimic simulation-based inference: a training set from the Magneticum simulation, a scatter-augmented training set to capture uncertainties in scaling relations, and a test set derived from the IllustrisTNG simulation. We demonstrate that the Test Set is out of domain in subtle ways that would be difficult to detect without careful analysis. We apply three deep learning methods: a standard neural network (NN), a neural network trained on the scatter-augmented input catalogs, and a Deep Reconstruction-Regression Network (DRRN), a semi-supervised deep model engineered to address domain shift. Although the NN improves results by 17% in the Training Data, it performs 40% worse on the out-of-domain Test Set. Surprisingly, the Scatter-Augmented Neural Network (SANN) performs similarly. While the DRRN is successful in mapping the training and Test Data onto the same latent space, it consistently underperforms compared to a straightforward Yx scaling relation. These results serve as a warning that simulation-based inference must be handled with extreme care, as subtle differences between training simulations and observational data can lead to unforeseen biases creeping into the results.

Ntampaka, Michelle [Baltimore, Space Telescope Sci↗

Climatological analysis of tropical cyclone impacts on hydrological extremes in the Mid-Atlantic region of the United States

Abstract Research efforts related to landfalling tropical cyclones (TCs) and their hydrological impacts have focused mostly on the continental or regional scales, whereas many coastal management and infrastructure decisions are made at much finer spatial scales. In this context, this study aims to provide local-scale understandings of the climatological characteristics and hydrological impacts of TCs (from 1950 to 2019) over the Mid-Atlantic region defined as the Delaware River Basin (DRB) and Susquehanna River Basin (SRB). The climatological analysis is based on analyzing long-term, spatially distributed observational datasets of hurricane tracks, precipitation, and streamflows. Results suggest that, despite limited contribution of TCs to regional precipitation (<9%), TC is the dominant driver for extreme floods in the southern part of DRB (e.g. tributaries of the Christina River and lower Schuylkill River) and the southwestern portions of SRB (e.g. tributaries of the Lower Susquehanna and Junita River), where TC’s effect on drought alleviation is also comparatively higher. At the basin level, SRB is more susceptible to flooding associated with TCs and prone to drought relative to DRB; however, strong spatial variability of TC’s impact on hydrological extremes is observed within and across the basins. While the TC effect on flood/drought is negligible for the high-elevation, northern part of the region, TC increases the magnitude of the 100 year flood by up to 19.6% in DRB and 53.0% in SRB; the duration of short-term extreme hydrological drought is reduced by TC by up to 25.0% in SRB and 24.7% in DRB, respectively.

54 ENVIRONMENTAL SCIENCES↗

Scaling Laws of Ejecta Streaks in Lunar Landings

From the crewed Apollo missions of the 1960s to the recent Chang’e uncrewed lunar missions, the interaction between the supersonic exhaust and the lunar surface generates a striking ray system of ejecta particles that travel radially outward at high speeds. While this intriguing pattern has been observed in experiments and simulations, the underlying mechanism remains unclear. These radial ejecta streaks were also observed during an experimental campaign using a Mach 5.3 jet impinging on a granular bed within a large-scale vacuum chamber. Our findings reveal that the radial ejecta streaks are caused by the Gortler instability, which, due to the curvature of the extremely underexpanded jet, induces counter-rotating streamwise vortices within the jet shear layer. These vortices impact the ground and entrain particles in their upwash regions. Experimental measurements from both ground tests and the literature show that the number of streaks strongly depends on the jet diameter at impact and the shear layer thickness, further revealing a power-law scaling with the jet pressure ratio. These insights highlight the pivotal role of fluid dynamics in extraterrestrial landings and provide a foundation for mitigating risks in future planetary missions.

Lunar Landing↗

Durability of YSZ Coated Ti2AlC in 1300 °C Mach 0.3 Burner Rig Tests

A thermal barrier coating system survived burner rig testing at 1300 °C for 500 h. A 160 µm thick yttria stabilized zirconia (YSZ) coating was applied to a Ti2AlC MAX phase bar sample by plasma spray physical vapor deposition (PS-PVD) and tested face-on in an atmospheric Mach 0.3 jet fuel burner, using 5-h thermal cycles. No thermal barrier coating (TBC) spallation or recession was observed, only a 2.4 mg/cm2 mass gain. The modest weight gain precluded severe volatility losses under high velocity burner conditions. The coating surface exhibited colonies of (111)flourite fiber-textured columns separated by craze patterns, with no visible moisture attack. The metastable tetragonal t' YSZ phase was obtained initially, transitioning to equilibrium teq and cubic YSZ, but with little detrimental monoclinic. The thickness of the alumina TGO was ~21 to 23 μm under the heated YSZ face and ~13 to 15 μm on the uncoated, cooler backside. The backside exhibited removal of initial transient TiO2 nodules and partial etching of the underlying Al2O3 scale by volatile hydroxides formed in high temperature, high velocity water vapor. Aerodynamic forces produced some bending of the cantilevered sample via creep. The test indicated exceptional stability of YSZ coatings on Ti2AlC under turbine conditions, with thermal expansion matching playing a key role. The purpose of this study was to demonstrate long term durability of YSZ/MAX phase system in aggressive high temperature burner rig testing. MAX phases have been keenly studied because of their unique crystal structure and intriguing properties (Refs. 1 and 2). Having Mn+1(Al,Si)(C,N)n general composition, they are defined as ceramics, but possess unusual desirable attributes such as high conductivity, thermal shock resistance, easy machinability, and deformation tolerance. The mechanical properties derive from weak M-(Al,Si) bonding in the basal plane that leads to sliding and kinking in preference to catastrophic crack growth. Like most ceramics they are phase stable at high temperatures, generally up to 1500 °C. High temperature oxidation resistance is excellent for alumina-forming Ti3AlC2, Ti2AlC, and Cr2AlC, as reviewed by Tallman, et al. (Ref. 3). Compatibility with α-Al2O3 scales is further enhanced in cyclic exposures by a close matching of thermal expansion coefficients, (Ref. 4) i.e., (~9.3, 10.2, 11.3×10–6/K for Al2O3, Ti2AlC, and YSZ, to be discussed). Turbine environments generally contain 10 percent water vapor in the combustion gases, therefore moisture effects can be a concern for some materials (Ref. 5). Furnace tests of MAX phases in high temperature steam generally showed little effect on Al2O3 scale growth (Ref. 6). However, high velocity and high pressure gas can influence scale losses by the formation of volatile reaction products, such as TiO(OH)2 and Al(OH)3 (Refs. 7 to 10). This phenomenon had been discussed for 1100 to 1300 °C high pressure burner rig tests of Ti2AlC (Ref. 11). A single cubic growth rate parameter kcubic was measurably lower than comparable furnace TGA data, but it could be matched reasonably well if corrected for a slight volatility term. In general, a two-parameter cubic-linear growth-volatility law was believed to apply. Corresponding scale volatility loss rates, directly measured at 1300 °C on a pre-oxidized sample, were moderate (0.012 mg/cm2/h) and largely attributed to removal of the initial TiO2 transient scale. A related CH4 burner study of high purity Cr2AlC MAX phase demonstrated 1200 °C durability after 500 rapid (5 min. heat and 2 min. cool) thermal shock cycling (29 h hot time) (Ref. 12). Heating and cooling rates were ~1000 and 500 °C per minute, with a gas velocity of 5 m/s, producing a 75 °C/mm gradient. A 7 μm Al2O3 surface scale and a 13 μm Cr7C3 depletion zone formed with no signs of failure. No evidence of scale volatility was evident, although weight change was not provided, the velocity was moderate, and the total hot time was not extensive. The same high gradient BRT was used to produce 1400 °C surface temperatures for a YSZ/Cr2AlC/IN738 system in the first study of MAX phases used as bond coats for thermal barrier coatings (TBC) (Ref. 25). Here TBC failure was reported after 745 cycles, with only a 1.5 μm Al2O3 scale entrained within a porous, Cr7C3 bondcoat depletion phase. YSZ thermal barrier coatings have been considered to be a compatible complement to Al-MAX phases because of thermal expansion matching and extremely low volatility in water vapor. Initial studies showed superior oxidative stability up to 1300 °C, for long times (at least 500 h) for Ti2AlC substrates and less (268 h) for Cr2AlC, while withstanding large alumina TGO scale thickness (~35 to 40 μm) (Refs. 13 and 14). By comparison, typical superalloy systems can only survive 1150 °C maximum interface temperatures for extended periods, with a maximum sustained TGO below 10 μm (Ref. 15). High temperature SiC based systems are known to form slow-growing SiO2 scales. But these are subject to rate enhancement and volatile Si(OH)4 products in the presence of water vapor, as described comprehensively by Opila, et al. (Refs. 5, 16 to 19). Net weight losses are generally observed in high velocity, high pressure burner rig studies (e.g., 0.084 mg/cm2/h at 1300 °C) (Ref. 20). Furthermore, the loss rates have been shown from chemical physics to scale with v1/2 and pH2O 2 (Ref. 16). Low activity, moisture-resistant environmental barrier coatings (EBC), such as rare earth silicates, are needed to prevent substrate recession under turbine conditions (Refs. 21 to 23).

Smialek, James L.↗

The hidden structure of hydrodynamic transport in random fracture networks

We study the large-scale dynamics and prediction of hydrodynamic transport in random fracture networks. The flow and transport behaviour is characterized by first passage times and displacement statistics, which show heavy tails and anomalous dispersion with a strong dependence on the injection condition. The origin of these behaviours is investigated in terms of Lagrangian velocities sampled equidistantly along particle trajectories, unlike classical sampling strategies at a constant rate. The velocity series are analysed by their copula density, the joint distribution of the velocity unit scores, which reveals a simple, albeit hidden, correlation structure that can be described by a Gaussian copula. Based on this insight, we derive a Langevin equation for the evolution of equidistant particle speeds. In this framework, particle motion is quantified by a stochastic time-domain random walk, the joint density of particle position, and speed satisfies a Klein–Kramers equation. The upscaled theory quantifies particle motion in terms of the characteristic fracture length scale and the distribution of Eulerian flow velocities. That is, it is predictive in the sense that it does not require the a priori knowledge of transport attributes. The upscaled model captures non-Fickian transport features, and their dependence on the injection conditions in terms of the velocity point statistics and average fracture length. It shows that the first passage times and displacement moments are dominated by extremes occurring at the first step. The presented approach integrates the interaction of flow and structure into a predictive model for large-scale transport in random fracture networks.

42 ENGINEERING↗

Generation of Continental Scale Percent Tree Cover Product Using Deep-learning and Multi-scale Remote Sensing Data

Spatially explicit percent tree cover (TC) estimation is critical for mapping forest aboveground biomass and its dynamics. While various TC products have been developed, there has not been a generalized framework that can be applied to diverse terrestrial ecosystems due to underlain extreme complexities. Deep learning algorithms can learn a spatial pattern and radiometric characteristics of tree canopy as a robust approximation of physical or empirical models, and thus have emerged as promising and efficient tools for large-scale TC mapping. In this study, we synergistically use very high-resolution aerial imageries (National Agriculture Imagery Program, NAIP) and medium resolution Landsat data to map continental-scale TC (CONUS and Mexico) through a hierarchical deep learning approach (Convolutional Neural Network), i.e., NAIP TC generated from a NAIP model is utilized to train a Landsat model. The produced TC product (hereafter, NEX-TC) is able to capture the spatial pattern of TC distribution and its changes driven by natural disturbance and human land management. We further explore and analyze the reliability and potential uncertainty of the NEX-TC by comparing it to lidar- (lidar-TC), National Land Cover Database (NLCD-TC), and MODIS Vegetation Continuous Field (MODIS-TC). This evaluation practice reveals that TC products based on passive optical sensors tend to underestimate TC across all land cover types while Landsat-based TCs (i.e., NEX-TC & NLCD-TC) perform better than the coarser MODIS TC estimate. Our results show that the NEX-TC is generally comparable to NLCD-TC but it particularly outperforms NLCD-TC and MODIS-TC over the dense forests where lidar-TC indicates >80% TC. These results indicate that our hierarchical deep learning approach and TC product will be effective and useful for characterizing large-scale tree cover and possibly associated carbon dynamics.

Landsat↗

Concurrent Changes in Extreme Hydroclimate Events in the Colorado River Basin

Extreme events resulting in catastrophic damage have more than doubled in the last five years, costing hundreds of lives and thousands of homes, and heavily undermining regional economic stability. At present, most of these hydroclimatic extreme events are documented by the media as individual events; however, in scientific terms, many are better understood as concurrent events—concurrent extremes of both temperature and precipitation (e.g., drought, floods). This paper considers concurrent changes in hydroclimate extremes, including heatwaves, drought, flooding, and low flows, in six historical-to-future (1970–1999, 2070–2099) Earth System Model (ESM) climate scenarios for the Colorado River basin. Results indicate that temperature-driven Impacts (heatwaves, drought) have the strongest responses while precipitation-driven Impacts have weaker responses. All Impacts exhibit an increase in magnitude from synoptic to annual time scales, with heatwaves increasing in strength about three times at the annual time scale versus the synoptic, while low flows only increase slightly. Critical watersheds in the Colorado were identified, highlighting the Blue River basin, Uncompahgre, East Taylor, Salt/Verde watersheds, locations of important water infrastructures, water resources, and hydrological research. Our results indicate that concurrent extreme hydroclimate events are projected to increase in the future and intensify within critical regions of the Colorado River basin. Considering extreme hydroclimate events concurrently is an important step towards linking economic and social effects of these events and their associated instabilities on a regional scale.

54 ENVIRONMENTAL SCIENCES↗

Rapid charging made practical in graphite-based lithium batteries: surface-acoustic wave turbulent electrolyte mixing to overcome diffusion limited charging rates [Final Report]

One of the key limits in rapidly recharging a lithium-ion battery is the depletion of lithium ions within the electrolyte adjacent the anode during charging and long diffusion time to overcome this depletion. It also causes dendrite formation, inefficient use of the lithium, and battery degradation over many charge-discharge cycles. Because the liquid electrolyte remains quiescent and unmixed, this depletion layer’s depth rapidly grows to match the anode-cathode separation distance at even modest charge rates. The solution proposed by PI Prof. James Friend and Co-PI Prof. Ping Liu, both from the University of California, San Diego, is to mix the electrolyte and minimize the Li+ ion concentration gradient during charging. Even in the presence of the separator, the charging rate could then be significantly increased. They propose to accomplish this using surface acoustic wave (SAW)-driven acoustic streaming, a technique employing 10-mW fingernail-sized solid-state devices from the telecommunications industry to drive turbulent mixing to submicron length scales in a manner completely compatible with the typical 20700 and 18650 cells used in electric vehicles. 0.1. Turbulent acoustic streaming mixes the electrolyte during charging—even with separator Our proposed 100-MHz SAW device used to recirculate the electrolyte is compatible with lithium- ion battery electrochemistry, as it is made in our lab of single-crystal lithium niobate. Their solution is straightforward to drive from a DC power source alongside the signal provided during battery charging. The device is only needed during charging and does not consume power dur- ing battery discharge. Uniquely, SAW generates extreme accelerations of over 1 billion meters per second squared in the fluid, driving turbulent mixing from centimeter to submicron length scales, even through the porous separator materials that tend to be used in batteries, all while avoiding interfering with the anode’s solid electrolyte interphase layer that forms during use. By employing novel fluid mechanics, the investigators are proposing a new direction for battery research away from direct use of materials science and electrochemistry. The chemistry agnostic solution may be employed in any battery chemistry that makes use of liquid electrolytes, providing a broader transformative benefit to the battery research community. They are to produce a series of prismatic and 20700-cell sized 2 Ah batteries capable of being charged and discharged at least 500 times without more than 20% loss in battery capacity, and to provide analysis tools useful to the battery research and development community for adopting this approach for other battery chemistries and configurations.

25 ENERGY STORAGE↗

A review of challenges, barriers, and opportunities for large-scale deployment of cool surfaces

Major urban centers are warming due to a combination of global and local phenomena. City governments are increasingly adopting strategies to mitigate the causes and impacts of extreme heat on their populations. Among these strategies are high solar-reflectance (cool) surfaces installed on building roofs and walls. Use of cool surfaces is a cost-effective and simple strategy that replaces conventional darker surfaces with surfaces that have a high reflectance to shortwave (solar) energy. This report reviews the recent history of cool-surface deployment efforts. This includes peer-reviewed literature, conference proceedings, and grey literature to identify challenges and barriers to wide-scale deployment of cool surfaces. We have also researched heat action plans and programs from cities and different codes and standards, as well as available incentive and rebate programs. The review identifies challenges, barriers, and opportunities associated with large-scale deployment of cool surfaces and categorize them broadly as being related to product development & performance or policies & mandates. It provides a foundation upon which we intend to build a roadmap for rapidly accelerating future deployments of cool surfaces. Finally, this roadmap will address identified challenges and incorporate lessons learned from historical efforts to generate a practical and actionable plan.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Small Scale Melter Testing of HLW Algorithm Glasses: Matrix 1 Tests

The principal objectives of the DM100 tests were to determine the effects of glass property extremes (glass viscosity, electrical conductivity, and T1%), minimum and maximum concentrations of several major and minor glass components, +/-15% batching errors in the addition of Glass Forming Chemicals (GFCs) to the feed, and variation in the sources of boron and sodium used in the GFCs on processing rates and melter conditions (off-gas characteristics, glass processing, foaming, cold cap, etc.) at constant bubbling rate.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Large Scale Bilevel Optimization for N-K SCOPF Using Adversarial Robustness

Ensuring a secure dispatch against multiple simultaneous outages has long been desired to maintain grid security in the presence of severe events, such as extreme weather phenomena. Traditionally denoted as N-k security constrained optimal power flow (N-k SCOPF), this problem is intractable to solve due to its size being combinatorial in the number of simultaneous outages and due to the non-convex nature of the AC network constraints. This hinders the use of N-k SCOPF for operating realistic-scale systems. In this paper, we introduce a methodology to scalably solve an AC-feasible dispatch that improves security over k simultaneous outages. Our methodology poses N-k SCOPF as a bilevel optimization problem and solves it using an adversarial robustness approach. We develop new efficient methods to solve each level of the bilevel optimization by employing knowledge of the physics of the underlying system. This yields significant improvements in speed and convergence that enable us to address the N-k SCOPF problem at scale. We demonstrate the effectiveness of our method by conducting a comprehensive analysis of an N-3 SCOPF for a 500-bus network. Furthermore, we emphasize the ability of our physics-driven techniques to handle larger systems by successfully scaling up to 12,000 buses.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Application of High Speed Digital Image Correlation in Rocket Engine Hot Fire Testing

Hot fire testing of rocket engine components and rocket engine systems is a critical aspect of the development process to understand performance, reliability and system interactions. Ground testing provides the opportunity for highly instrumented development testing to validate analytical model predictions and determine necessary design changes and process improvements. To properly obtain discrete measurements for model validation, instrumentation must survive in the highly dynamic and extreme temperature application of hot fire testing. Digital Image Correlation has been investigated and being evaluated as a technique to augment traditional instrumentation during component and engine testing providing further data for additional performance improvements and cost savings. The feasibility of digital image correlation techniques were demonstrated in subscale and full scale hotfire testing. This incorporated a pair of high speed cameras to measure three-dimensional, real-time displacements and strains installed and operated under the extreme environments present on the test stand. The development process, setup and calibrations, data collection, hotfire test data collection and post-test analysis and results are presented in this paper.

Gradl, Paul R.↗

Logarithmic Corrections to Kerr Thermodynamics

Recent work has shown that loop corrections from massless particles generate $\frac{3}{2}$ ⁢log⁡𝑇 Hawking corrections to black hole entropy which dominate the thermodynamics of cold near-extreme charged black holes. Here we adapt this analysis to near-extreme Kerr black holes. Like AdS 2 ×𝑆 2 , the near-horizon extreme Kerr (NHEK) metric has a family of normalizable zero modes corresponding to reparametrizations of boundary time. The path integral over these zero modes leads to an infrared divergence in the one-loop approximation to the Euclidean NHEK partition function. We regulate this divergence by retaining the leading finite temperature correction in the NHEK scaling limit. This “not-NHEK” geometry lifts the eigenvalues of the zero modes, rendering the path integral infrared finite. The quantum-corrected near-extremal entropy exhibits $\frac{3}{2}$ ⁢log⁡𝑇 Hawking behavior characteristic of the Schwarzian model and predicts a lifting of the ground state degeneracy for the extremal Kerr black hole.

General relativity↗

Pursuing Dark Energy with Large Galaxy Redshift Surveys: Baryon Acoustic Oscillations and Beyond (Final Technical Report)

We have developed and applied methods of large-scale structure from galaxy redshift surveys to the study of dark energy. This program supported my group's development of the baryon acoustic method and our participation in the Dark Energy Spectroscopic Instrument (DESI) survey. In addition to my leadership role in the DESI collaboration, my group at Harvard focused on several topics addressing key needs of the DESI science program. 1) We continued our design, validation, and documentation of DESI target selection of the luminous red galaxy and emission-line galaxy samples. 2) We applied simulations from our novel and extremely fast N-body code to make DESI catalogs. With these, we will search for possible systematic shifts in the acoustic scale due to clustering bias with an unprecedented volume of simulations. 3) We extended our method for the fast construction of covariance matrices for correlation functions. 4) We developed new large-scale structure methods, including density-field reconstruction and three-point function analysis.

79 ASTRONOMY AND ASTROPHYSICS↗

Crater Morphometry and Scaling in Coarse, Rubble-Like Targets: Insights from Impact Experiments

Spacecraft images reveal that the asteroids Itokawa, Ryugu, and Bennu are covered with coarse, boulder-rich material [1–3]. Impactors that collide with these bodies encounter a target with extreme physical heterogeneity. Other bodies can also possess significant physical heterogeneity (e.g., megaregolith, layering, etc.). Such heterogeneities establish free surfaces and impedance contrasts that can affect shock propagation and attenuation. Therefore, such heterogeneities may also affect crater formation and excavation [4], melt generation [5–7] and crater scaling [4]. As described by [8,9], the extent to which target heterogeneity affects crater formation likely depends on how the length scale, d, of the heterogeneity (e.g., boulder size on a rubble-pile asteroid) compares to the width of the shock, w, generated by impact. Here we further test this hypothesis using impact experiments across a broad range of impact velocities and target grain sizes to systematically vary the ratio between the width of the shock and the diameter of target grains.

Daly, R. T.↗

Magnetic activity in pre-main-sequence stars

The extensive new evidence for extremely high levels of magnetic activity on the surface of premain-sequence stars is reviewed and analyzed in the context of solar evolution. Most of these observations concern 'weak' T Tauri stars, in which the surface properties of the young stars are not dominated by circumstellar matter as in 'classical' T Tauri stars. Optical photometry shows that weak T Tauria stars are moderately rapid rotaters with cool starspots covering 5 to 40 percent of the surface. Optical and ultraviolet spectroscopy indicates that their chromospheres are enhanced about 50 times over contemporary solar levels. X-ray and radio intensities are of order 1000 to 100,000 times greater than peak solar levels, and they vary on time scales of days and (in a few cases) hours or minutes. The variability can only be explained in terms of some extremely powerful magnetic-flare model. The large numbers of weak T Tauri stars, probably larger than the population of classical T Tauri stars, strongly suggests that the sun was a weak T Tauri star for at least part of its premain-sequence evolutionary phase. These findings are summarized in a suggested portrait of the sun as a 1 Myr old weak T Tauri star.

Feigelson, Eric D.↗

Historical and Future Windstorms in the Northeastern United States

Large-scale windstorms represent an important atmospheric hazard in the Northeastern US (NE) and are associated with substantial socioeconomic losses. Regional simulations performed with the Weather Research and Forecasting (WRF) model using lateral boundary conditions from three Earth System Models (ESMs: Geophysical Fluid Dynamics Laboratory (GFDL), Hadley Centre Global Environment Model (HadGEM) and Max Planck Institute (MPI)) are used to quantify possible future changes in windstorm characteristics and/or changes in the parent cyclone types responsible for windstorms. WRF nested within MPI ESM best represents important aspects of historical windstorms and the cyclone types responsible for generating windstorms compared with a reference simulation performed with the ERA-Interim reanalysis for the historical climate. The spatial scale and frequency of the largest windstorms in each simulation defined using the greatest extent of exceedance of local 99.9th percentile wind speeds (U > U999) plus 50-year return period wind speeds (U50,RP) do not exhibit secular trends. Projections of extreme wind speeds and windstorm intensity/frequency/geolocation and dominant parent cyclone type associated with windstorms vary markedly across the simulations. Only the MPI nested simulations indicate statistically significant differences in windstorm spatial scale, frequency and intensity over the NE in the future and historical periods. This model chain, which also exhibits the highest fidelity in the historical climate, yields evidence of future increases in 99.9th percentile 10 m height wind speeds, the frequency of simultaneous U > U999 over a substantial fraction (5–25%) of the NE and the frequency of maximum wind speeds above 22.5 ms−1. These geophysical changes, coupled with a projected doubling of population, leads to a projected tripling of a socioeconomic loss index, and hence risk to human systems, from future windstorms.

Pryor, Sara C. (ORCID:0000000348473440)↗