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NASA NTRS2000

Troposphere-Stratosphere Connections in Recent Northern Winters in NASA GEOS Assimilated Datasets

The northern winter stratosphere displays a wide range of interannual variability, much of which is believed to result from the response to the damping of upward-propagating waves. However, there is considerable (growing) evidence that the stratospheric state can also impact the tropospheric circulation. This issue will be examined using datasets generated in the Data Assimilation Office (DAO) at NASA's Goddard Space Flight Center. Just as the tropospheric circulation in each of these years was dominated by differing synoptic-scale structures, the stratospheric polar vortex also displayed different evolutions. The two extremes are the winter 1998/1999, when the stratosphere underwent a series of warming events (including two major warmings), and the winter 1999/2000, which was dominated by a persistent, cold polar vortex, often distorted by a dominant blocking pattern in the troposphere. This study will examine several operational and research-level versions of the DAO's systems. The 70-level-TRMM-system with a resolution of 2-by-2.5 degrees and the 48-level, 1-by-l-degree resolution ''Terra'' system were operational in 1998/1999 and 1999/2000, respectively. Research versions of the system used a 48-level, 2-by-2.5-degree configuration, which facilitates studies of the impact of vertical resolution. The study includes checks against independent datasets and error analyses, as well as the main issue of troposphere-stratosphere interactions.

Pawson, Steven↗

NASA NTRS2000

Phase-Shifting Liquid Crystal Point-Diffraction Interferometry

Microgravity fluid physics experiments frequently measure concentration and temperature. Interferometers such as the Twyman Green illustrated have performed full-field measurement of these quantities. As with most such devices, this interferometer uses a reference path that is not common with the path through the test section. Recombination of the test and reference wavefronts produces interference fringes. Unfortunately, in order to obtain stable fringes, the alignment of both the test and reference paths must be maintained to within a fraction of the wavelength of the light being used for the measurement. Otherwise, the fringes will shift and may disappear. Because these interferometers are extremely sensitive to bumping, jarring and transmitted vibration, they are typically mounted on optical isolation tables. Schlieren deflectometers or the more recent Shack-Hartmann wavefront sensors also measure concentration and temperature in laboratory fluid flows. Ray optics describe the operation of both devices. In a schlieren system, an expanded, collimated beam passes through a test section where refractive index gradients deflect rays. A lens focuses the beam to a filter placed in the rear focal plane of the decollimating lens. In a quantitative color schlieren system, gradients in the index of refraction appear as colors in the field of view due to the action of the color filter. Since sensitivity is a function of the focal length of the decollimating lens, these systems are rather long and filter fabrication and calibration is rather difficult. A Shack-Hartmann wavefront sensor is an array of small lenslets. Typical diameters are on the order of a few hundred microns. Since these lenslets divide the test section into resolution elements, the spatial resolution can be no smaller than an individual lenslet. Such a device was recently used to perform high-speed tomography of heated air exiting a 1.27 cm diameter nozzle. While these wavefront sensors are very compact, the limited spatial resolution and the methods required for data reduction suggest that a more useful instrument needs to be developed. The category of interferometers known as common path interferometers can eliminate much of the vibration sensitivity associated with traditional interferometry as described above. In these devices, division of the amplitude of the wavefront following the test section produces the reference beam. Examples of these instruments include shearing and point diffraction interferometers. In the latter case, shown schematically, a lens focuses light passing through the test section onto a small diffracting object. Such objects are typically either a circle of material on a high quality glass plate or a small sphere in a glass cell. The size of the focused spot is several times larger than the object so that the light not intercepted by the diffracting object forms the test beam while the diffracted light generates a spherical reference beam. While this configuration is mechanically stable, phase shifting one beam with respect to the other is difficult due to the common path. Phase shifting enables extremely accurate measurements of the phase of the interferogram using only gray scale intensity measurements and is the de facto standard of industry. Mercer and Creath 2 demonstrated phase shifting in a point diffraction interferometer using a spherical spacer in a liquid crystal cell as the diffracting object. By changing the voltage across the cell, they were able to shift the phase of the undiffracted beam relative to the reference beam generated by diffraction from the sphere. While they applied this technology to fluid measurements, the device shifted phase so slowly that it was not useful for studying transient phenomena. We have identified several technical problems that precluded operation of the device at video frame rates and intend to solve them to produce a phase-shifting liquid crystal point-diffraction interferometer operating at video frame rates. The first task is to produce high contrast fringes. Since the diffracted beam is much weaker than the transmitted beam, interferograms have poor contrast unless a dye is added to the liquid crystal to reduce the intensity of the undiffracted light. Dyes previously used were not rigorously characterized and suffered from hysteresis in both the initial alignment state of the device and the electro-optic switching characteristics. Hence, our initial effort will identify and characterize dyes that do not suffer from these difficulties and are readily soluble in the liquid crystal host. Since the ultimate goal of this research is to produce interferometers capable of phase shifting at video frame rates, we will quantify the difference in switching times between ferroelectric and nematic liquid crystals. While we have more experience with nematic crystals, they typically switch more slowly than ferroelectric cells. As part of that effort, we will investigate the difference in the modulation of the interferograms as a function of the type of liquid crystal in the cell. Because the temporal switching response of a liquid crystal cell is directly related its thickness, we intend to explore techniques required to produce cells that are as thin as possible. However, the cells must still produce a total phase shift of two pi radians.

Griffin, DeVon W.↗

NASA NTRS2006

Flood and Landslide Applications of High Time Resolution Satellite Rain Products

Experimental, potentially real-time systems to detect floods and landslides related to heavy rain events are described. A key basis for these applications is high time resolution satellite rainfall analyses. Rainfall is the primary cause for devastating floods across the world. However, in many countries, satellite-based precipitation estimation may be the best source of rainfall data due to insufficient ground networks and absence of data sharing along many trans-boundary river basins. Remotely sensed precipitation from the NASA's TRMM Multi-satellite Precipitation Analysis (TMPA) operational system (near real-time precipitation at a spatial-temporal resolution of 3 hours and 0.25deg x 0.25deg) is used to monitor extreme precipitation events. Then these data are ingested into a macro-scale hydrological model which is parameterized using spatially distributed elevation, soil and land cover datasets available globally from satellite remote sensing. Preliminary flood results appear reasonable in terms of location and frequency of events, with implementation on a quasi-global basis underway. With the availability of satellite rainfall analyses at fine time resolution, it has also become possible to assess landslide risk on a near-global basis. Early results show that landslide occurrence is closely associated with the spatial patterns and temporal distribution of TRMM rainfall characteristics. Particularly, the number of landslides triggered by rainfall is related to rainfall climatology, antecedent rainfall accumulation, and intensity-duration of rainstorms. For the purpose of prediction, an empirical TMPA-based rainfall intensity-duration threshold is developed and shown to have skill in determining potential areas of landslides. These experimental findings, in combination with landslide surface susceptibility information based on satellite-based land surface information, form a starting point towards a potential operational landslide monitoring/warning system around the globe.

Adler, Robert F.↗

DOE OSTI2020

Project 8: Measuring the tritium beta-decay spectrum using Cyclotron Radiation Emission Spectroscopy

Abstract. The goal of the Project 8 experiment is to measure the absolute neutrino mass using tritium beta decays and a new spectroscopic technique, Cyclotron Radiation Emission Spectroscopy (CRES). The first phase of Project 8 demonstrated that CRES could be used to detect single-electron cyclotron radiation and perform precision electron spectroscopy. We are in Phase II of the experiment, performing a 100-day measurement of the endpoint of the tritium spectrum. We will demonstrate the ability to measure the last ~2 keV of the beta-decay spectrum and explore the background rate at energies just above the endpoint; CRES has the potential for extremely low backgrounds. In Phase III we will demonstrate the ability to scale up the volume of the experiment. In Phase IV we will switch the source from molecular tritium to atomic tritium, which will avoid systematic uncertainties from the final states of the molecule. I will present the current status of Project 8 Phase II and the plans for Phases III and IV.

Oblath, Noah↗

DOE OSTI2022

Silicon nitride stress-optic microresonator modulator for optical control applications

Modulation-based control and locking of lasers, filters and other photonic components is a ubiquitous function across many applications that span the visible to infrared (IR), including atomic, molecular and optical (AMO), quantum sciences, fiber communications, metrology, and microwave photonics. Today, modulators used to realize these control functions consist of high-power bulk-optic components for tuning, sideband modulation, and phase and frequency shifting, while providing low optical insertion loss and operation from DC to 10s of MHz. In order to reduce the size, weight and cost of these applications and improve their scalability and reliability, modulation control functions need to be implemented in a low loss, wafer-scale CMOS-compatible photonic integration platform. The silicon nitride integration platform has been successful at realizing extremely low waveguide losses across the visible to infrared and components including high performance lasers, filters, resonators, stabilization cavities, and optical frequency combs. Yet, progress towards implementing low loss, low power modulators in the silicon nitride platform, while maintaining wafer-scale process compatibility has been limited. Here we report a significant advance in integration of a piezo-electric (PZT, lead zirconate titanate) actuated micro-ring modulation in a fully-planar, wafer-scale silicon nitride platform, that maintains low optical loss (0.03 dB/cm in a 625 µm resonator) at 1550 nm, with an order of magnitude increase in bandwidth (DC - 15 MHz 3-dB and DC - 25 MHz 6-dB) and order of magnitude lower power consumption of 20 nW improvement over prior PZT modulators. The modulator provides a >14 dB extinction ratio (ER) and 7.1 million quality-factor (Q) over the entire 4 GHz tuning range, a tuning efficiency of 162 MHz/V, and delivers the linearity required for control applications with 65.1 dB·Hz 2/3 and 73.8 dB·Hz 2/3 third-order intermodulation distortion (IMD3) spurious free dynamic range (SFDR) at 1 MHz and 10 MHz respectively. We demonstrate two control applications, laser stabilization in a Pound-Drever Hall (PDH) lock loop, reducing laser frequency noise by 40 dB, and as a laser carrier tracking filter. This PZT modulator design can be extended to the visible in the ultra-low loss silicon nitride platform with minor waveguide design changes. This integration of PZT modulation in the ultra-low loss silicon nitride waveguide platform enables modulator control functions in a wide range of visible to IR applications such as atomic and molecular transition locking for cooling, trapping and probing, controllable optical frequency combs, low-power external cavity tunable lasers, quantum computers, sensors and communications, atomic clocks, and tunable ultra-low linewidth lasers and ultra-low phase noise microwave synthesizers.

Wang, Jiawei (ORCID:0000000257965220)↗

NASA NTRS2015

A Framework for the Cross-Sectoral Integration of Multi-Model Impact Projections: Land Use Decisions Under Climate Impacts Uncertainties

Climate change and its impacts already pose considerable challenges for societies that will further increase with global warming (IPCC, 2014a, b). Uncertainties of the climatic response to greenhouse gas emissions include the potential passing of large-scale tipping points (e.g. Lenton et al., 2008; Levermann et al., 2012; Schellnhuber, 2010) and changes in extreme meteorological events (Field et al., 2012) with complex impacts on societies (Hallegatte et al., 2013). Thus climate change mitigation is considered a necessary societal response for avoiding uncontrollable impacts (Conference of the Parties, 2010). On the other hand, large-scale climate change mitigation itself implies fundamental changes in, for example, the global energy system. The associated challenges come on top of others that derive from equally important ethical imperatives like the fulfilment of increasing food demand that may draw on the same resources. For example, ensuring food security for a growing population may require an expansion of cropland, thereby reducing natural carbon sinks or the area available for bio-energy production. So far, available studies addressing this problem have relied on individual impact models, ignoring uncertainty in crop model and biome model projections. Here, we propose a probabilistic decision framework that allows for an evaluation of agricultural management and mitigation options in a multi-impactmodel setting. Based on simulations generated within the Inter-Sectoral Impact Model Intercomparison Project (ISI-MIP), we outline how cross-sectorally consistent multi-model impact simulations could be used to generate the information required for robust decision making. Using an illustrative future land use pattern, we discuss the trade-off between potential gains in crop production and associated losses in natural carbon sinks in the new multiple crop- and biome-model setting. In addition, crop and water model simulations are combined to explore irrigation increases as one possible measure of agricultural intensification that could limit the expansion of cropland required in response to climate change and growing food demand. This example shows that current impact model uncertainties pose an important challenge to long-term mitigation planning and must not be ignored in long-term strategic decision making

farmlands↗

DOE OSTI2023

Materials in Extremes [Slides]

Goals: Realization of advanced predictive models that capture aspects of processing structure-properties-performance (PSPP) in ways that build on scale bridging, data science, and transformational physics insights from experiments; Based on a robust and seamless integration of sample manufacturing, characterization (pre- and post-mortem), theory and simulation, and novel experiments; Ultimately we want to be able to reliably predict performance, and control the functionality of materials in extreme environments.

36 MATERIALS SCIENCE↗

DOE OSTI2022

Quantum vacuum processes in the extremely intense light of relativistic plasma mirror sources

Abstract The advent of petawatt-class laser systems allows generating electromagnetic fields of unprecedented strength in a controlled environment, driving increasingly more efforts to probe yet unobserved processes through their interaction with the quantum vacuum. Still, the lowest intensity scale governing these effects lies orders of magnitude beyond foreseen capabilities, so that such endeavor is expected to remain extremely challenging. In recent years, however, plasma mirrors have emerged as a promising bridge across this gap, by enabling the conversion of intense infrared laser pulses into coherently focused Doppler harmonic beams lying in the X-UV range. In this work, we present predictions on the quantum vacuum signatures produced when such beams are focused to intensities between 10 24 and 10 28 W cm −2 , specifically photon–photon scattering and electron–positron pair creation. These signatures are computed via the stimulated vacuum formalism, combined with a model of perfectly focused beam built from PIC-generated harmonics spectra, and implemented on state-of-the-art massively parallel numerical tools. In view of identifying experimentally favorable configurations, we also consider the coupling of the focused harmonic beam with an auxiliary optical beam, and provide comparison with other established schemes. Our results show that a single coherently focused harmonic beam can produce as much scattered photons as two infrared pulses in head-on collision, and confirm that the coupling of the harmonic beam to an auxiliary beam gives rise to significant levels of inelastic scattering, and hence holds the potential to strongly improve the attainable signal to noise ratios in experiments.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2023

Seeing through noise in power laws

Despite widespread claims of power laws across the natural and social sciences, evidence in data is often equivocal. Modern data and statistical methods reject even classic power laws such as Pareto’s law of wealth and the Gutenberg–Richter law for earthquake magnitudes. We show that the maximum-likelihood estimators and Kolmogorov–Smirnov (K-S) statistics in widespread use are unexpectedly sensitive to ubiquitous errors in data such as measurement noise, quantization noise, heaping and censorship of small values. This sensitivity causes spurious rejection of power laws and biases parameter estimates even in arbitrarily large samples, which explains inconsistencies between theory and data. We show that logarithmic binning by powers of λ > 1 attenuates these errors in a manner analogous to noise averaging in normal statistics and that λ thereby tunes a trade-off between accuracy and precision in estimation. Binning also removes potentially misleading within-scale information while preserving information about the shape of a distribution over powers of λ, and we show that some amount of binning can improve sensitivity and specificity of K-S tests without any cost, while more extreme binning tunes a trade-off between sensitivity and specificity. We therefore advocate logarithmic binning as a simple essential step in power-law inference.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2023

Architecture for Co-Simulation of Transportation and Distribution Systems with Electric Vehicle Charging at Scale in the San Francisco Bay Area

This work describes the Grid-Enhanced, Mobility-Integrated Network Infrastructures for Extreme Fast Charging (GEMINI) architecture for the co-simulation of distribution and transportation systems to evaluate EV charging impacts on electric distribution systems of a large metropolitan area and the surrounding rural regions with high fidelity. The current co-simulation is applied to Oakland and Alameda, California, and in future work will be extended to the full San Francisco Bay Area. It uses the HELICS co-simulation framework to enable parallel instances of vetted grid and transportation software programs to interact at every model timestep, allowing high-fidelity simulations at a large scale. This enables not only the impacts of electrified transportation systems across a larger interconnected collection of distribution feeders to be evaluated, but also the feedbacks between the two systems, such as through control systems, to be captured and compared. The findings are that with moderate passenger EV adoption rates, inverter controls combined with some distribution system hardware upgrades can maintain grid voltages within ANSI C.84 range A limits of 0.95 to 1.05 p.u. without smart charging. However, EV charging control may be required for higher levels of charging or to reduce grid upgrades, and this will be explored in future work.

24 POWER TRANSMISSION AND DISTRIBUTION↗

NASA NTRS2011

High Resolution Global Climate Modeling with GEOS-5: Intense Precipitation, Convection and Tropical Cyclones on Seasonal Time-Scales.

In 2008 the World Modeling Summit for Climate Prediction concluded that "climate modeling will need-and is ready-to move to fundamentally new high-resolution approaches to capitalize on the seamlessness of the weather-climate continuum." Following from this, experimentation with very high-resolution global climate modeling has gained enhanced priority within many modeling groups and agencies. The NASA Goddard Earth Observing System model (GEOS-5) has been enhanced to provide a capability for the execution at the finest horizontal resolutions POS,SIOle with a global climate model today. Using this high-resolution, non-hydrostatic version of GEOS-5, we have developed a unique capability to explore the intersection of weather and climate within a seamless prediction system. Week-long weather experiments, to mUltiyear climate simulations at global resolutions ranging from 3.5- to 14-km have demonstrated the predictability of extreme events including severe storms along frontal systems, extra-tropical storms, and tropical cyclones. The primary benefits of high resolution global models will likely be in the tropics, with better predictions of the genesis stages of tropical cyclones and of the internal structure of their mature stages. Using satellite data we assess the accuracy of GEOS-5 in representing extreme weather phenomena, and their interaction within the global climate on seasonal time-scales. The impacts of convective parameterization and the frequency of coupling between the moist physics and dynamics are explored in terms of precipitation intensity and the representation of deep convection. We will also describe the seasonal variability of global tropical cyclone activity within a global climate model capable of representing the most intense category 5 hurricanes.

Putnam, WilliamM.↗

DOE OSTI2021

Role of locally polar regions in the superconductivity of SrTiO 3

Understanding the interaction between polar and superconducting order parameters may hold the key to several classes of superconductors that remain poorly understood, including SrTiO 3 and several tellurides. Here we show that doped, strained SrTiO 3 films can exhibit both global or local polar order, respectively, depending on the amount of epitaxial mismatch strain, thereby providing a platform to understand how inversion symmetry breaking affects superconductivity. We find that the superconducting critical temperature correlates with the length scale of polar order. In particular, the transition temperature is enhanced when polar nanodomains are sufficiently large or, in the extreme limit, films are globally ferroelectric. In these cases, the Cooper pairs reside in a noncentrosymmetric environment. Conversely, low transition temperatures are found when the nanodomains are small. The findings point to the length scale of polar nanodomains and spin-orbit coupling as important parameters controlling the superconductivity of SrTiO 3 . Furthermore, the ability to control the size of the polar domains opens up new opportunities to design and control the nature of superconductivity in a wide range of materials.

36 MATERIALS SCIENCE↗

DOE OSTI2021

Genome-Scale Metabolic Model of Caldicellulosiruptor bescii Reveals Optimal Metabolic Engineering Strategies for Bio-based Chemical Production

The extremely thermophilic cellulolytic bacterium, Caldicellulosiruptor bescii , degrades plant biomass at high temperatures without any pretreatments and can serve as a strategic platform for industrial applications. The metabolic engineering of C. bescii , however, faces potential bottlenecks in bio-based chemical productions.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2022

Scientific machine learning benchmarks

Deep learning has transformed the use of machine learning technologies for the analysis of large experimental datasets. In science, such datasets are typically generated by large-scale experimental facilities, and machine learning focuses on the identification of patterns, trends and anomalies to extract meaningful scientific insights from the data. In upcoming experimental facilities, such as the Extreme Photonics Application Centre (EPAC) in the UK or the international Square Kilometre Array (SKA), the rate of data generation and the scale of data volumes will increasingly require the use of more automated data analysis. Furthermore, at present, identifying the most appropriate machine learning algorithm for the analysis of any given scientific dataset is a challenge due to the potential applicability of many different machine learning frameworks, computer architectures and machine learning models. Historically, for modelling and simulation on high-performance computing systems, these issues have been addressed through benchmarking computer applications, algorithms and architectures. Extending such a benchmarking approach and identifying metrics for the application of machine learning methods to open, curated scientific datasets is a new challenge for both scientists and computer scientists. Here, we introduce the concept of machine learning benchmarks for science and review existing approaches. As an example, we describe the SciMLBench suite of scientific machine learning benchmarks.

42 ENGINEERING↗

DOE OSTI2021

Knowledge-Guided Machine Learning (KGML) Platform to Predict Integrated Water Cycle and Associated extremes

Focal Area(s): Predictive modeling through the use of AI techniques and insight gleaned from complex data (both observed and simulated). Science Challenge: Although advanced predictive capabilities of the water cycle are critical to address environmental needs and develop sustainable solutions for energy demands, there is no robust framework, to say the least, that seamlessly integrates local to intermediate to global scales and a gamut of biogeophysical information to enhance understanding of the integrated water cycle and its associated extremes.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2022

Changing Trends in Drought Patterns over the Northeastern United States Using Multiple Large Ensemble Datasets

Since the infamous extreme drought of the 1960s, the climate of the northeastern United States (NEUS) has generally trended toward warmer and wetter conditions. Nonetheless, there is mounting evidence that short-term droughts will continue to pose a significant risk for this region. To better explore the processes governing events such as these, climate models have adopted more complex representations of the fully coupled atmosphere–land–ocean–sea ice system; however, large uncertainties in future projections still persist, with internal variability necessitating large ensembles to understand trends in both rare and high-impact extreme events such as rapidly developing droughts (a term here that includes flash droughts developing on monthly scales). In this study, seven large ensemble (LE) models are employed to answer the outstanding question: How are the frequency and character of drought in the NEUS changing under a warming climate? We find that most LE models indicate the NEUS will experience a long-term wetting trend with more “extremely wet” months, but also more frequent short-term extreme droughts. These changes are associated with increasing precipitation, atmospheric water demand, and climate variability. We also conclude that discrepant trends in precipitation and evapotranspiration variability will lead to increasing anticorrelation of these variables, which is relevant to the intensification of rapidly developing drought, particularly in the spring season. These changes are associated with an increase in evapotranspiration from plants, brought by an earlier emergence of the growing season and denser vegetation.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2022

PIONEER: Studies of Rare Pion Decays

A next-generation rare pion decay experiment, PIONEER, is strongly motivated by several inconsistencies between Standard Model (SM) predictions and data pointing towards the potential violation of lepton flavor universality. It will probe non-SM explanations of these anomalies through sensitivity to quantum effects of new particles even if their masses are at very high scales. Measurement of the charged-pion branching ratio to electrons vs. muons $R_{e/\mu}$ is extremely sensitive to new physics effects. At present, the SM prediction for $R_{e/\mu}$ is known to 1 part in $10^4$, which is 15 times more precise than the current experimental result. An experiment reaching the theoretical accuracy will test lepton flavor universality at an unprecedented level, probing mass scales up to the PeV range. Measurement of pion beta decay, $\pi^+\to \pi^0 e^+ \nu (\gamma)$, with 3 to 10-fold improvement in sensitivity, will determine $V_{ud}$ in a theoretically pristine manner and test CKM unitarity, which is very important in light of the recently emerged tensions. In addition, various exotic rare decays involving sterile neutrinos and axions will be searched for with unprecedented sensitivity. The experiment design benefits from experience with the recent PIENU and PEN experiments at TRIUMF and the Paul Scherrer Institut (PSI). Excellent energy and time resolutions, greatly increased calorimeter depth, high-speed detector and electronics response, large solid angle coverage, and complete event reconstruction are all critical aspects of the approach. The PIONEER experiment design includes a 3$\pi$ sr 25 radiation length calorimeter, a segmented low gain avalanche detector stopping target, a positron tracker, and other detectors. Using intense pion beams, and state-of-the-art instrumentation and computational resources, the experiments can be performed at the PSI ring cyclotron.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2024

Sensitivity and vulnerability to summer heat extremes in major cities of the United States

Many cities are experiencing increases in extreme heat because of global temperature rise combined with the urban heat island effect. The heterogeneity of urban morphology also leads to fine-scale variability in potential for heat exposure. Yet, how this rise in temperature and local variability together impacts urban residents differently at exposure-relevant scales is still not clear. Here we map the Universal Thermal Climate Index, a more complete indicator of human heat stress at an unprecedentedly fine spatial resolution (1 m), for 14 major cities in the United States using urban microclimate modeling. We examined the different heat exposure levels across different socioeconomic and racial/ethnic groups in these cities, finding that income level is most consistently associated with heat stress. We further conducted scenario simulations for a hypothetical 1 °C increase of air temperature in all cities. Results show that a 1 °C increase would have a substantial impact on human heat stress, with impacts that differ across cities. The results of this study can help us better evaluate the impact of extreme heat on urban residents at decision-relevant scales.

54 ENVIRONMENTAL SCIENCES↗