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At least 379 records · Page 21
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Exploring the origins of the indentation size effect at submicron scales

Significance Downscaling material structure into ever-decreasing levels for modern technological advancements demands small-scale mechanical characterizations of materials, such as nanoindentation. Thus, a comprehensive understanding of indentation size effect (ISE) has a far-reaching impact, but such understanding remains incomplete at the submicron scale despite a decades-long quest since the 1980s. Here, we explored the origins of this effect experimentally by linking dislocation behavior evolution with nanoindentation mechanical data at various depths. Importantly, the dislocation behavior is found to be strongly depth dependent and gives rise to subgrain formation progressively. Aided by subgrain boundaries, the ISE mechanism transitions from dislocation source starvation to dislocation interaction as indentation depth increases. The critical mechanism transition elucidates the distinctive ISE behavior at the submicron scale.

36 MATERIALS SCIENCE↗
DOE OSTI2024

California’s 2023 snow deluge: Contextualizing an extreme snow year against future climate change

The increasing prevalence of low snow conditions in a warming climate has attracted substantial attention in recent years, but a focus exclusively on low snow leaves high snow years relatively underexplored. However, these large snow years are hydrologically and economically important in regions where snow is critical for water resources. Here, we introduce the term “snow deluge” and use anomalously high snowpack in California’s Sierra Nevada during the 2023 water year as a case study. Snow monitoring sites across the state had a median 41 y return interval for April 1 snow water equivalent (SWE). Similarly, a process-based snow model showed a 54 y return interval for statewide April 1 SWE (90% CI: 38 to 109 y). While snow droughts can result from either warm or dry conditions, snow deluges require both cool and wet conditions. Relative to the last century, cool-season temperature and precipitation during California’s 2023 snow deluge were both moderately anomalous, while temperature was highly anomalous relative to recent climatology. Downscaled climate models in the Shared Socioeconomic Pathway-370 scenario indicate that California snow deluges—which we define as the 20 y April 1 SWE event—are projected to decline with climate change (58% decline by late century), although less so than median snow years (73% decline by late century). This pattern occurs across the western United States. Changes to snow deluge, and discrepancies between snow deluge and median snow year changes, could impact water resources and ecosystems. Understanding these changes is therefore critical to appropriate climate adaptation.

Marshall, Adrienne M.↗
DOE OSTI2025

Prioritizing urban heat adaptation infrastructure based on multiple outcomes: Comfort, health, and energy

Globally, cities face increasing extreme heat, impacting comfort, health, and energy consumption. Infrastructure-based heat adaptation strategies can improve these outcomes, but each strategy has a unique mix of benefits and drawbacks. Here, we apply an urbanized meteorological model (WRF) with the newly integrated multilayer BEP-Tree street tree model to dynamically downscale Earth System Model projections and a 3-D microclimate model (TUF-Pedestrian) to simulate the street-scale radiation environment impacting pedestrians. We evaluate the performance of five heat adaptation strategies (street trees, cool roofs, green roofs, rooftop photovoltaics (PV), and reflective pavements) during extreme heat events in three cities with contrasting background climates (Toronto, Phoenix, and Miami), under contemporary and end-of-century projected climates, based on three metrics: outdoor heat stress, air conditioning (AC) energy use, and ventilation of vehicular air pollution. No single adaptation strategy improves all three outcomes. While street trees inhibit ventilation, they reduce outdoor heat stress four times more effectively than the next best strategy via shade provision, fully offsetting heat stress increases under a high-emissions end-of-century climate scenario in all cities studied. Cool roofs and green roofs moderately reduce heat stress and energy use. Alternatively, rooftop PV with energy storage can generate sufficient power for space cooling but have marginal effects on heat stress. Reflective pavements are the least effective across metrics. Where the ventilation of street-level emissions is of less concern, our results clearly support the combination of street trees and rooftop PV as a highly complementary and effective means of adaptive mitigation across different climates and neighborhood densities.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2021

The implications of future climate change on the blue water footprint of hydropower in the contiguous US

As the largest renewable energy source, hydropower is essential to the sustainability of the global energy market. However, a considerable amount of water can be lost in the form of evaporation from the associated multipurpose reservoirs, and hence enlarge the blue water footprint (BWF) of hydropower in a warming climate. To facilitate the sustainable management of both water and energy resources under the impact of climate change in the contiguous United States (CONUS), the BWF values of 143 major multipurpose reservoirs were evaluated during the historical period (1985–2014) and two future periods (2020–2049 and 2070–2099). The historical reservoir evaporation loss was calculated using the Landsat-based reservoir surface area and a new evaporation rate algorithm that considers the heat storage effect. Future projections of runoff availability, hydropower generation, and reservoir evaporation were estimated based on the downscaled climate model ensemble from phase 5 of the Coupled Model Intercomparison Project (CMIP5). It was found that the BWF for the CONUS is highly spatially heterogeneous, with an average value of 26.2 m 3 /MWh in the historical period. In the future, the BWF values are projected to increase under both Representative Concentration Pathway (RCP) 4.5 and 8.5 scenarios. This is especially noticeable under RCP 8.5, which has an average BWF value of 30.2 m 3 /MWh for 2070–2099 (increasing by 15.3% from 26.2 m 3 /MWh). The uncertainty ranges increase even more, from 3.4 m 3 /MWh during 2020–2049 to 5.7 m 3 /MWh during 2070–2099. These findings can benefit water and energy resources management in identifying suitable environmental, economic, operational, and investment strategies for multipurpose reservoirs in a changing environment.

13 HYDRO ENERGY↗
DOE OSTI2022

Process-based climate change assessment for European winds using EURO-CORDEX and global models

Wind energy is an important pillar of decarbonization strategies and potentially vulnerable to climate change. Existing wind climate change assessments rely on climate models but a systematic investigation of the global-to-regional climate modeling chain is missing. In this study, I highlight key limitations, namely (a) the differing representation of land use change in global and regional climate models which compromises comparability, and (b) the consistency of large-scale features along the global-to-regional climate modeling chain. To this end, I analyze the large European Coordinated Downscaling Experiment (EURO-CORDEX) ensemble (rcp85: N = 49; rcp45: N= 18; rcp26: N = 22) along with the driving global models (rcp85: N = 7; rcp45: N = 5; rcp26: N = 7), finding evidence that climate change reduces mean wind speeds by up to -0.8 ms -1 (offshore) and -0.3 ms -1 (onshore). I provide physical explanations for these changes by identifying two key drivers. First, onshore wind speeds drop in the driving global models in regions and scenarios with strong land use change but show no drop in EURO-CORDEX where land use is held constant. Second, offshore wind reductions follow decreases in the equator-to-pole temperature gradient remarkably well with correlations reaching around 0.9 in resource-rich European countries like Ireland, the United Kingdom and Norway, implying that arctic amplification is a severe risk for European offshore wind energy. My results suggest that earlier conclusions of negligible climate change impacts on wind energy might be premature if either land use changes strongly or polar amplification is at or above the range sampled in global climate models.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Projected increases in tropical cyclone-induced U.S. electric power outage risk

Abstract While power outages caused by tropical cyclones (TCs) already pose a great threat to coastal communities, how—and why—these risks will change in a warming climate is poorly understood. To address this need, we develop a robust machine learning model to capture TC-induced power outage risk. When applied to 900 000 synthetic TCs downscaled from simulated historical and future climate conditions under a strong warming scenario, we find outage risk in the United States and Puerto Rico is expected to increase broadly by the end of the century, with some states seeing increases of 60% and higher. Further, we discover that rising rainfall rates will play an increasingly important role in TC-induced power outage risk as the climate changes, explaining more than 50% of the projected change in risk in some regions. These insights are important for guiding decision-makers in their future outage risk investment and mitigation plans.

Grid Resilience↗
DOE OSTI2026

High-resolution mountain topography can inform global snow vulnerability estimates

Snow is changing globally. Computationally intensive snow reanalysis products and downscaled climate model projections allow for the estimation of historical and projected changes in snow over ∼4–10 km resolutions, but these resolutions are coarse relative to the scales needed for water supply and flood planning. Fine-scale digital elevation models (DEMs) are widely available but are underutilized to make first-order assessments of snow vulnerability. Here, we leverage DEMs at a 7.5 arc s (∼250 m) resolution, combining these with historical freezing level height estimates from ERA-5 to derive estimates of changes in the snow-receiving area (SRA) and its variability across global mountain ranges. Results show estimated SRA declines in 29% (1.9 million km2) of the global mountain area from 1982–2020; 66% of the mountainous areas had no change over the historical period. At +1.5 °C of warming relative to the pre-industrial control, global mountain SRA would decline by 9.5% (1.0 million km2) relative to recent conditions. This loss would be approximately doubled with +2 °C of warming. In a +4 °C warming scenario, an additional 34% (3.6 million km2) of SRA would be lost beyond the +2 °C case. Across individual mountain ranges, SRA losses can occur nonlinearly with warming, with some locations that have historically had relatively minor SRA losses at risk of substantially larger losses in warmer climates. Analysis using coarser-resolution DEMs can underestimate or overestimate SRA and its rate of loss, with the largest impacts in relatively warm, low-elevation mountain ranges. Results of this work provide estimates of projected loss in SRA at policy-relevant warming levels; inform the resolutions needed for process-based snow modeling; identify snow vulnerability hotspots; and provide a new integrated approach to snow vulnerability assessment that is achievable at global scales and highlights potential nonlinearities from recent trends to a variety of future warming scenarios.

climate, mountains↗
DOE OSTI2021

Shifts in hydroclimatology of US megaregions in response to climate change

Most of the population and economic growth in the United States occurs in megaregions as the clustered metropolitan areas, whereas climate change may amplify negative impacts on water and natural resources. This study assesses shifts in regional hydroclimatology of fourteen US megaregions in response to climate change over the 21st century. Hydroclimatic projections were simulated using the Variable Infiltration Capacity (VIC) model driven by three downscaled climate models from the Multivariate Adaptive Constructed Analogs (MACA) dataset to cover driest to wettest future conditions in the conterminous United States (CONUS). Shifts in the regional hydroclimatolgy and basin characteristics of US megaregions were represented as a combination of changes in the aridity and evaporative indices using the Budyko framework and Fu's equation. Changes in the climate types of US megaregions were estimated using the Fine Gaussian Support Vector Machine (SVM) method. The results indicate that Los Angeles, San Diego, and San Francisco are more likely to experience less arid conditions with some shifts from Continental to Temperate climate type while the hydroclimatology of Houston may become drier with some shifts from Temperate to Continental climate type. Additionally, water yield is likely to decrease in Seattle. Change in the hydroclimatology of Denver and Phoenix highly depends on the selected climate model. However, the basin characteristics of Phoenix have the highest sensitivity to climate change. Overall, the hydroclimatic conditions of Los Angeles, San Diego, Phoenix, Denver, and Houston have the highest sensitivity to climate change. Understanding of future shifts in hydroclimatology of megaregions can help decision-makers to attenuate negative consequences by implementing appropriate adaptation strategies, particularly in the water-scare megaregions.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Exploring the role of clouds in offshore wind potential off the US West Coast in a changing climate

To meet US goals of deploying additional wind energy as part of the decarbonization strategy, wind plants are being planned for the deep water offshore the western US. The wind flow in that region is complex due to the proximity to the coast, cold water upwelling, and persistent stratiform clouds that interact with radiation in ways that have the potential to destabilize the atmosphere. That flow has the potential to change with a changing climate. To address these issues, we assess the flow and the clouds in that region using downscaled climate model data, under both historic climate (1975–2005) and projected future (2025–2055) conditions. We note that the climate simulations agree fairly well with the cloud patterns observed by satellite data in the nearshore and offshore regions. We then assess the projected changes in clouds, wind speed, and other important variables, noting that our simulations project that the predominant north/northwesterly low-level jet is expected to strengthen and clouds are likely to be commensurately enhanced, although projected changes are within about 10% of current conditions. Our examination of the dynamics associated with the changes in the climate simulations provides confidence in the dynamical consistency of these projected changes.

17 WIND ENERGY↗
DOE OSTI2023

Population Aging and Heat Exposure in the 21st Century: Which U.S. Regions Are at Greatest Risk and Why?

Abstract Background and Objectives The co-occurring trends of population aging and climate change mean that rising numbers of U.S. older adults are at risk of intensifying heat exposure. We estimate county-level variations in older populations’ heat exposure in the early (1995–2014) and mid (2050) 21st century. We identify the extent to which rising exposures are attributable to climate change versus population aging. Research Design and Methods We estimate older adults’ heat exposure in 3,109 counties in the 48 contiguous U.S. states. Analyses use NASA NEX Global Daily Downscaled Product (NEX-GDDP-CMIP6) climate data and county-level projections for the size and distribution of the U.S. age 69+ population. Results Population aging and rising temperatures are documented throughout the United States, with particular “hotspots” in the Deep South, Florida, and parts of the rural Midwest. Increases in heat exposure by 2050 will be especially steep in historically colder regions with large older populations in New England, the upper Midwest, and rural Mountain regions. Rising temperatures are driving exposure in historically colder regions, whereas population aging is driving exposure in historically warm southern regions. Discussion and Implications Interventions to address the impacts of temperature extremes on older adult well-being should consider the geographic distribution and drivers of this exposure. In historically cooler areas where climate change is driving exposures, investments in warning systems may be productive, whereas investments in health care and social services infrastructures are essential in historically hot regions where exposures are driven by population aging.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2024

Weather Sensitive High Spatio-Temporal Resolution Transportation Electric Load Profiles For Multiple Decarbonization Pathways

Electrification of transport compounded with climate change will transform hourly load profiles and their response to weather. We present a novel approach to generating hourly electric load profiles that considers charging strategies and evolving sensitivity to temperature. The approach consists of downscaling annual state-scale sectoral load projections from the multisectoral Global Change Analysis Model (GCAM) into hourly electric load profiles leveraging high resolution climate and population datasets. Profiles are developed and evaluated at the Balancing Authority scale, with a 5-year increment until 2050 over the Western U.S. Interconnect for multiple decarbonization pathways and climate scenarios. The datasets are readily available for production cost model analysis. Our open source approach is transferable to other regions.

Decarbonization, tranportation, Electric vehicle c↗
DOE OSTI2026

IAM-FIRE: a Climate Emulator–Based Framework to Project Wildfire Impacts and Risks for Integrated Assessment Models

Most Integrated Assessment Models (IAMs) underrepresent dynamic feedbacks from climate-driven disturbances such as wildfires, potentially overestimating the permanence of land-based carbon sinks. In particular, representing the impacts of forest fires is becoming increasingly important, as these are expected to intensify in the coming years. We introduce IAM-FIRE (Integrated Assessment Model – Fire Impacts & Risks Emulator), a novel framework that enables the projection of wildfire burned area (BA) and carbon emissions (CE) directly from IAM outputs. IAM-FIRE combines a spatial climate emulator, land-use downscaling, vegetation productivity modelling, and an empirical fire model to generate global annual wildfire impacts for arbitrary socioeconomic and emissions scenarios at 0.5° resolution for the period 2020–2100. Calibrated against GFEDv5 observations and using inputs from the Global Change Analysis Model (GCAM), we report projections BA and CE derived from IAM-FIRE for four scenarios: SSP1-2.6, SSP2-4.5, SSP3-6.6 and SSP5-7.6. The model reproduces historical global trends for total BA, including the observed global decline since the early 2000s, and for forest BA. Projected fire trajectories differ strongly among scenarios: total BA range from declines under SSP1-2.6 (-3.36 Mha yr-1) to increases under SSP3-6.6 (+1.6 Mha yr-1). Corresponding total CE show a similar divergence ranging from -15 to +10.6 TgC yr-1. Socioeconomic development exerts a dominant suppressing effect on wildfire impacts while climate change and CO2-driven increases in vegetation productivity amplify fire risk, particularly under high-emissions pathways. Compared with CMIP6 fire-enabled Earth System Models, IAM-FIRE exhibits greater sensitivity to radiative forcing and a stronger role for human-driven fire suppression, highlighting substantial structural uncertainties in future fire projections. By providing a computationally efficient and internally consistent approach to represent wildfire impacts within IAMs, IAM-FIRE enables systematic exploration of fire–climate–land feedbacks and supports improved assessments of mitigation permanence and climate risks in future integrated scenarios.

Rouhette, Theo↗
DOE OSTI2025

Integrated Modeling Driven Evaluation of Opportunities for Climate‐Resilient Perennial Biomass Crop Plantings in Flood‐Prone Agricultural Landscapes

Adapting to future climate change in flood-prone landscapes will require climate-resilient agricultural systems. Planting perennial crops, like switchgrass and willow, along river corridors can mitigate future flooding while supporting bioenergy markets. We developed an integrated assessment linking climate, hydrologic, and inundation model results to assess future flood risk to river-adjacent agricultural lands in the Mid-Atlantic Region (MAR) and explore this opportunity. We produced ensemble streamflow projections for every MAR stream using a hydrologic model driven by a suite of downscaled and bias-corrected Coupled Model Intercomparison Project Phase 6 climate projections. We then conducted high-resolution inundation mapping based on projected flood frequencies for baseline and future periods. Results show that in the near-term future, at least two-thirds of the streams will experience 100-year floods more severe than the baseline 200-year floods. Riparian zones are projected to face a median rise of inundation by 9.5%–24.1%. Results show that there is an opportunity to mitigate flooding in over half of MAR's counties with the quantities of switchgrass and willow plantings anticipated for mature bioenergy markets, even under the most extreme (200-year) flood events. Our integrated modeling framework can guide similar regions to evaluate opportunities for flood-resilient agricultural systems under climate change.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2023

Increased U.S. coastal hurricane risk under climate change

Several pathways for how climate change may influence the U.S. coastal hurricane risk have been proposed, but the physical mechanisms and possible connections between various pathways remain unclear. Here, future projections of hurricane activity (1980–2100), downscaled from multiple climate models using a synthetic hurricane model, show an enhanced hurricane frequency for the Gulf and lower East coast regions. The increase in coastal hurricane frequency is driven primarily by changes in steering flow, which can be attributed to the development of an upper-level cyclonic circulation over the western Atlantic. The latter is part of the baroclinic stationary Rossby waves forced mainly by increased diabatic heating in the eastern tropical Pacific, a robust signal across the multimodel ensemble. Last, these heating changes also play a key role in decreasing wind shear near the U.S. coast, further aggravating coastal hurricane risk enhanced by the physically connected steering flow changes.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Global cascade of kinetic energy in the ocean and the atmospheric imprint

Here, we present an estimate for the ocean's global scale transfer of kinetic energy (KE), across scales from 10 to 40,000 km. Oceanic KE transfer between gyre scales and mesoscales is induced by the atmosphere’s Hadley, Ferrel, and polar cells, and the intertropical convergence zone induces an intense downscale KE transfer. Upscale transfer peaks at 300 gigawatts across mesoscales of 120 km in size, roughly one-third the energy input by winds into the oceanic general circulation. Nearly three quarters of this “cascade” occurs south of 15°S and penetrates almost the entire water column. The mesoscale cascade has a self-similar seasonal cycle with characteristic lag time of ≈27 days per octave of length scales; transfer across 50 km peaks in spring, while transfer across 500 km peaks in summer. KE of those mesoscales follows the same cycle but peaks ≈40 days after the peak cascade, suggesting that energy transferred across a scale is primarily deposited at a scale four times larger.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Analysis of prescribed fire days in climate model output

This code analyzes openly available, downscaled climate model output and counts days in a year that are available to conduct prescribed fire based on meteorological prescription data obtained from US land management agencies.

Jonko, Alexandra↗
DOE OSTI2024

recon3d

SAND2025-00533O recon3d is a software tool that provides automated 3D reconstruction and meshing capabilities. It processes labeled 3D image data from various sources, starting from image stacks, and calculates 3D feature distributions like size, shape, and location. The software also has tools for downscaling rectilinear grid data and creating tetrahedral meshes directly from image data. recon3d can be used by novice users via the command line with a properly formatted configuration file. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525.

Emery, John↗