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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

The National Climate Data Base (NCDB): A Bias-Corrected High-Resolution Climate Dataset

Assessing renewable energy resources under future climate scenarios has been highlighted in recent years to analyze and understand potential impacts of future change in renewable generation on the power sector. Solar energy is well-known as the most plentiful among various renewable resources and usually converted to electricity using photovoltaics (PV) technologies, and the global deployment of PV technology has increased rapidly in recent decades. In this study, we develop a statistical technique to downscale the future projection of solar irradiance for PV energy-related applications. A set of Regional Climate Model (RCM)-based projections obtained from the North American Coordinated Regional Climate Downscaling Experiment (NA-CORDEX) are used as inputs to statistical methods to generate high-resolution global horizontal irradiance (GHI) over the contiguous United States (CONUS). The main steps of the statistical downscaling method include (1) regridding RCM output (0.22 degree and daily resolutions) to handle the modeled-observed data sets on a common grid, (2) correcting bias of RCM GHI using satellite-derived observation, and (3) implementing temporal and spatial downscaling to generate GHI at 8-km and hourly resolution. Basically, complex physical processes and interactions between solar radiation and various atmospheric constituents lead solar irradiance to be highly variable and uncertain. Underrepresentation of clouds from the RCM parameterizations is the main source of error and uncertainty in modeling solar irradiance. Thus, we adapt and use the high-quality satellite-derived data from the National Solar Radiation Database (NSRDB) to analyze the bias and error of RCM GHI as well as estimate the statistical parameters for spatial and temporal downscaling. This presentation will summarize the comprehensive analysis conducted to produce and assess the results under two climate scenarios (RCP4.5 and RCP8.5). We will also present a detailed validation demonstrating the strengths of the proposed downscaling method and future extension of this research.

climate data↗
DOE OSTI2025

Drivers of Historical and Future Coastal Runoff Across the Arctic and Sub‐Arctic Subregions of Alaska, USA

This study investigates historical and future coastal runoff across the Arctic and sub-Arctic subregions of Alaska, USA, emphasising changes in terrestrial hydrology and their implications for coastal discharge. Using the physically based SnowModel-HydroFlow framework, historical (1991–2020) and future (2071–2100) coastal discharge climatologies were simulated, incorporating meteorological, topographic, and land cover inputs. Results reveal distinct seasonal and spatial patterns in temperature, precipitation, and snow dynamics across the Beaufort, Chukchi, Yukon, and Bristol subregions. Future projections suggest significant warming and shifts in hydrological regimes, such as increased annual precipitation and coastal discharge totals. Following a high emissions, business as usual pathway (SSP5-8.5), coastal discharge hydrographs in the Beaufort and Yukon subregions remain snow dominated with increases in discharge in nearly all months, while Chukchi and Bristol subregions shift from snow dominated to rain dominated. These changes are linked to rising temperatures, decreasing snow precipitation fractions, and altered freezing levels, with implications for water storage, timing, and availability. This research provides insights into the drivers and consequences of hydrological changes in a rapidly warming Arctic, supporting efforts to predict and mitigate the impacts on coastal and marine ecosystems.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

The productivity of perennial crops miscanthus and switchgrass is more resistant to vapor pressure deficit stress than maize

Rising atmospheric vapor pressure deficit (D) with warming is an increasingly important driver of crop productivity loss, yet the relative sensitivity of conventional seed crops and alternative perennial crops remains poorly resolved. In this study, we combined a 9-year eddy covariance carbon flux record (2008 – 2016) with 600+ midday leaf water potential (ψ L ) measurements (2024 – 2025) from adjacent maize (Zea mays), miscanthus (Miscanthus x giganteus), and switchgrass (Panicum virgatum) plots to: (1) quantify the limitations of elevated D on crop-specific productivity and (2) evaluate how these responses vary as a function of soil moisture (Θ) status. We found that maize strictly regulated ψ L and its gross primary productivity (GPP) was strongly reduced by increasing D. In contrast, miscanthus and switchgrass allowed larger ψ L declines and sustained higher GPP under similar moisture constraints. D exerted a larger limitation on maize GPP than Θ, but D-driven declines were less severe when accompanied by high Θ. GPP sensitivity to D was also influenced by Θ for miscanthus and switchgrass, but the buffering effect was stronger compared to maize. Specifically, high D paired with high Θ were the most productive conditions for the perennials, reflecting temperature-driven gains in photosynthetic efficiency when evaporative stress was mitigated by sufficient soil water supply. Overall, miscanthus and switchgrass displayed greater resistance to atmospheric drought and more stable GPP across hydroclimate variability than maize. These findings highlight that maize is more vulnerable to future projections of rising D than miscanthus or switchgrass.

drought↗
DOE OSTI2024

Machine Learning Driven Sensitivity Analysis of E3SM Land Model Parameters for Wetland Methane Emissions

Methane (CH 4 ) is globally the second most critical greenhouse gas after carbon dioxide, contributing to 16%–25% of the observed atmospheric warming. Wetlands are the primary natural source of methane emissions globally. However, wetland methane emission estimates from biogeochemistry models contain considerable uncertainty. One of the main sources of this uncertainty arises from the numerous uncertain model parameters within various physical, biological, and chemical processes that influence methane production, oxidation, and transport. Sensitivity Analysis (SA) can help identify critical parameters for methane emission and achieve reduced biases and uncertainties in future projections. This study performs SA for 19 selected parameters responsible for critical biogeochemical processes in the methane module of the Energy Exascale Earth System Model (E3SM) land model (ELM). The impact of these parameters on various CH 4 fluxes is examined at 14 FLUXNET- CH 4 sites with diverse vegetation types. Given the extensive number of model simulations needed for global variance-based SA, we employ a machine learning (ML) algorithm to emulate the complex behavior of ELM methane biogeochemistry. We found that parameters linked to CH 4 production and diffusion generally present the highest sensitivities despite apparent seasonal variation. Comparing simulated emissions from perturbed parameter sets against FLUXNET-CH 4 observations revealed that better performances can be achieved at each site compared to the default parameter values. This presents a scope for further improving simulated emissions using parameter calibration with advanced optimization techniques.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Soil moisture gradients strengthen mesoscale convective systems by increasing wind shear

Mesoscale convective systems are a class of storm linked to extensive flooding and other destructive hazards in many regions globally. In West Africa, soil moisture impacts provide a valuable source of predictability for mature storm hazards, but little is known about mature storm sensitivity to soil moisture in other climatic regions. Here we use a storm track dataset, satellite observations and reanalysis fields to investigate the response of mature storms to soil moisture in seven global storm hotspots—West Africa, India, South America, South Africa, Australia and the United States Great Plains. We demonstrate that mesoscale soil moisture gradients (~500 km) can enhance storms by driving increased vertical wind shear conditions, a crucial ingredient for storm organization, through the strengthening of atmospheric temperature gradients. This is evidenced by a 10–30% increase in precipitation feature size and rainfall for the largest storms on days with favourable soil moisture gradients compared with unfavourable gradients. Global simulations confirm that soil moisture gradients influence wind shear. The results demonstrate the importance of soil moisture feedbacks for accurate forecasting of mesoscale convective systems and future projections of extreme events under climate change.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

United States multi-sector land use and land cover base maps to support human and Earth system models

Abstract Earth System Models (ESMs) require current and future projections of land use and landcover change (LULC) to simulate land-atmospheric interactions and global biogeochemical cycles. Among the most utilized land systems in ESMs are the Community Land Model (CLM) and the Land-Use Harmonization 2 (LUH2) products. Regional studies also use these products by extending coarse projections to finer resolutions via downscaling or by using multisector dynamic (MSD) models. One such MSD model is the Global Change Analysis Model (GCAM), which has its own independent land module, but often relies on CLM or LUH2 as spatial inputs for its base years. However, this requires harmonization of thematically incongruent land systems at multiple spatial resolutions, leading to uncertainty and error propagation. To resolve these issues, we develop a thematically consistent LULC system for the conterminous United States adaptable to multiple MSD frameworks to support research at a regional level. Using empirically derived spatial products, we developed a series of base maps for multiple contemporary years of observation at a 30-m resolution that support flexibility and interchangeability amongst LUH2, CLM, and GCAM classification systems.

Oliver, Jay↗
DOE OSTI2025

Dynamically downscaled seasonal heat wave projections in the CONUS

Heat waves are a well-documented hazard that are projected to increase in intensity, duration, and frequency with climate change. Regions of the US experience widely varying temperatures; for example, 35 °C is extremely hot for spring in the Northeast but not for summer in the Southeast. It is important to evaluate projections within a regional context and at a high enough resolution to understand the risks to populations. We identify heat waves across the Conterminous US (CONUS) under SSP5–8.5 from 2020 to 2059 with an ensemble of dynamically downscaled Coupled Model Intercomparison Project Phase 6 (CMIP6) model outputs. We demonstrate that there are regional differences caused by seasonal and local drivers of persistent hot temperatures. Summer heat waves are increasing in intensity and duration faster than winter heat waves because of the atmospheric conditions that promote these events. Our analysis emphasizes the value of fine-resolution modeling for projecting future climate risks.

Rubin, Hannah [University of Tennessee, Knoxville ↗
DOE OSTI2024

Plant, insect, and fungi fossils under the center of Greenland’s ice sheet are evidence of ice-free times

The persistence and size of the Greenland Ice Sheet (GrIS) through the Pleistocene is uncertain. This is important because reconstructing changes in the GrIS determines its contribution to sea level rise during prior warm climate periods and informs future projections. To understand better the history of Greenland’s ice, we analyzed glacial till collected in 1993 from below 3 km of ice at Summit, Greenland. The till contains plant fragments, wood, insect parts, fungi, and cosmogenic nuclides showing that the bed of the GrIS at Summit is a long-lived, stable land surface preserving a record of deposition, exposure, and interglacial ecosystems. Knowing that central Greenland was tundra-covered during the Pleistocene informs the understanding of Arctic biosphere response to deglaciation.

58 GEOSCIENCES↗
DOE OSTI2024

Soil management practices can contribute to net carbon neutrality in California

Stabilizing climate requires reducing greenhouse gas (GHG) emissions and storing atmospheric carbon dioxide (CO 2 ) in land or ocean systems. Soil management practices can reduce GHG emissions or sequester atmospheric CO 2 into inorganic and organic forms. However, whether soil carbon strategies represent a viable and impactful climate mitigation pathway is uncertain. A specific question concerns the role that land-management practices and soil amendments can play in realizing California's ambition for carbon neutrality by 2045. Here we examine the carbon flux impacts of soil conservation (i.e., compost, reduced tillage, cover crop) and enhanced silicate rock weathering (EW) practices at different areal extents of implementation in cropland, grassland, and savanna in California under two climate change cases. We show that with implementation areas of 15% or 50% of private cultivated land, grassland, and savanna in California, soil conservation practices alone can contribute $1.4^{2.1}_{0.7}$% ($-1.8^{-2.7}_{ -0.9}$ Mt CO 2 eq y -1 ) and $4.6^{6.9}_{2.3}$% ($-6.0^{-8.9}_{-3.0}$ Mt CO 2 eq y -1 ) of the additional emissions reduction needed (beyond previous targets) to meet the 2045 net neutrality goal (-129.3 Mt CO 2 eq y -1 ), respectively, on an average annual basis, including climate uncertainty. Including EW in these scenarios increases the total contributions of management practices to $4.1^{5.6}_{2.5}$% ($-5.2^{-7.3}_{-3.2}$ Mt CO 2 eq y -1 ) and $13.5^{18.6}_{8.2}$% ($-17.5^{-24.2}_{-10.7}$ Mt CO 2 eq y -1 ), respectively, of this reduction. This highlights that the extent of implementation area is a major factor in determining benefits and that EW has the potential to make a real contribution to net reduction targets. Results are similar across climate cases, indicating that contemporary field data can be used to make future projections. With EW there remains mechanistic uncertainties, however, such as rock dissolution rate and environmental controls on weathering products, which require additional field research to improve understanding of the technological efficacy of this approach for California's 2045 carbon neutrality goal.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

A framework for testing soil carbon dynamics post land-use transition in a multisector dynamics model

Soil carbon plays a crucial role in the global carbon cycle. Changes in land use can determine whether carbon is stored or is emitted into the atmosphere as carbon dioxide, which has broad implications for the human and Earth systems. These feedbacks to the carbon cycle and their socio-economic drivers are modelled by many global multisector dynamics models to project future possibilities for the human-Earth system. One notable model of this class is the Global Change Analysis Model (GCAM), which uses a simplified process to model soil organic carbon (SOC) content after land-use transition across 384 land units. While the current GCAM soil carbon framework is based on scientific principles, it has not been tested against experimental data. This work examines rates of SOC change from GCAM input data. Specifically, first order rate constants derived from model inputs were compared to values from two syntheses to assess GCAM’s accuracy. Welch’s t-tests and linear models were used to determine if rate constants were consistent across all tested geographical areas and land-use transition types. While we found that there was general agreement on the direction and magnitude (i.e., rate) of SOC change, the rate constant derived from GCAM and empirical values differed strongly in a subset of specific instances. These results indicate that GCAM’s current SOC dynamics during land use transition successfully capture broad patterns of change in this critical carbon pool, but should be interpreted with caution at finer spatial scales. One potential cause of these discrepancies is our highly aggregated variable, soil timescale, which could be made more granular to improve accuracy. When using economically rooted multisector dynamics models, such as GCAM, it is critical to understand such model limitations for representing specific Earth system processes.

carbon↗
DOE OSTI2026

New bounds on heavy QCD axions from big bang nucleosynthesis

We study big bang nucleosynthesis (BBN) constraints on heavy QCD axions. BBN offers a powerful probe of new physics that modifies the neutron-to-proton ratio during the process, thanks to the precisely measured primordial Helium-4 abundance. A heavy QCD axion provides an attractive target for this probe, because not only is it a well-motivated hypothetical particle by the strong 𝐶⁢𝑃 problem, but also it dominantly decays to hadrons if kinematically allowed. A range of its lifetime is thus excluded where the hadronic decays would significantly alter the neutron-to-proton ratio. We compute axion-induced modification of the neutron-to-proton ratio, and obtain robust upper bounds on the axion lifetimes, as low as 0.017 s for the axion mass higher than 300 MeV. Remarkably, this is stronger than projected future cosmic microwave background bounds via 𝑁 eff . Our bounds are largely insensitive to uncertainties in hadronic cross sections and the axion’s branching fractions into various hadrons, as well as to the precise value of the initial axion abundance. We also incorporate, for the first time, several key improvements, such as scattering processes by energetic 𝐾 𝐿 and secondary hadrons, that can also be important for studying general hadronic injections during BBN, not limited to those from axion decays.

Axions↗
DOE OSTI2024

Finite Bubble Statistics Constrain Late Cosmological Phase Transitions

We consider first order cosmological phase transitions (PTs) happening at late times below standard model temperatures T PT ≲ GeV. The inherently stochastic nature of bubble nucleation and the finite number of bubbles associated with a late-time PT lead to superhorizon fluctuations in the PT completion time. We compute how such fluctuations eventually source curvature fluctuations with universal properties, independent of the microphysics of the PT dynamics. Using cosmic microwave background (CMB) and large scale structure measurements, we constrain the energy released in a dark-sector PT. For 0.1 eV ≲ T PT ≲ keV this constraint is stronger than both the current bound from additional neutrino species Δ⁢N eff , and in some cases, even CMB-S4 projections. Future measurements of CMB spectral distortions and pulsar timing arrays will also provide competitive sensitivity for keV ≲ T PT ≲ GeV.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2026

FLOW BATTERY COST AND COMMERCIALIZATION TOOL (FlowBaCC) v.1.0

The Flow Battery Cost and Commercialization Tool (FlowBaCC) is a python-based framework used to project the costs and commercialization timelines for redox flow batteries. FlowBaCC combines learning curves for component costs and performance with adoption curves for market diffusion to project future system costs. The tool uses the bottom-up, spreadsheet-based Battery Performance and Cost Model for Flow Batteries (BatPaC-Flow) as the engine to translate learning curve inputs into full system costs. FlowBaCC provides capital costs and levelized costs of energy storage. The tool enables scenario analysis, sensitivity analysis, and uncertainty quantification (via grid and Monte Carlo methods).

Fu, Xiaoxu [Argonne National Laboratory (ANL), Arg↗
DOE OSTI2026

How Well Can CMIP6 Models Represent the Observed Influence of the Pacific and Indian Oceans on the Indian Summer Monsoon Rainfall?

This study evaluates the ability of CMIP6 climate models to simulate the observed effects of tropical Pacific and Indian Ocean sea surface temperature anomalies (SSTAs) on Indian summer monsoon rainfall (ISMR) variability. Using observational data and the large ensemble historical simulations of seven CMIP6 models from 1950 to 2014, we applied a cyclostationary linear inverse model (CS-LIM) to isolate the impacts of tropical Pacific SSTAs, Indian Ocean SSTAs and their interaction on the interannual variability of ISMR. Overall, CMIP6 models well reproduced the observed enhanced (reduced) ISMR variability from Pacific SSTAs (Indian Ocean SSTAs and the Indo-Pacific interaction), but with varying spatial patterns and magnitudes. While CESM2 and E3SM-2-0 showed the best agreement with observations for the effects of Pacific SSTAs and the Indo-Pacific interaction, respectively, CMIP6 models showed mixed results for the impacts from Indian Ocean SSTAs. Composite analysis of ISMR anomalies during the developing phases of pure and co-occurring El Niño-Southern Oscillation (ENSO) and Indian Ocean dipole (IOD) events revealed that the impacts from Pacific SSTAs were captured reasonably well by E3SM-2-0, CESM2, MIROC6, and MPI-ESM1-2-LR, while E3SM-2-0 also showed the best agreement with observations for the effects from the Indo-Pacific interaction. However, all models showed substantial biases in simulating the Indian Ocean SSTA impacts on ISMR, especially for pure El Niño events. Overall, this study provides new insights into how individual CMIP6 models simulate the isolated impacts from the tropical Pacific and Indian Oceans, which has important applications for improving ISMR predictions and interpreting ISMR future projections.

monsoon↗
DOE OSTI2026

1994 SEMCOG Household-Based Person Trip Survey

The Southeast Michigan Council of Governments contracted with the Applied Management & Planning Group to conduct a travel behavior survey of 7,361 households from March 28, 1994, to June 10, 1994. The primary purpose of this study was to provide the council with a new database of travel behavior to assist in updating the region's transportation models. This data collection includes demographic, socioeconomic, travel, and mobile source emissions models for projecting future patterns of development, travel, congestion, and air pollution. Information about household characteristics and travel was collected using a one-day, activity-focused diary and a separate household survey. In an activity diary, respondents recorded 65,535 trips during the assigned the day.

1Hz data↗
DOE OSTI2024

Gender in Mineral Names

Minerals are the fundamental constituents of Earth, and mineral names appear in scientific literature for disciplines including geology, chemistry, materials science, biology, and medicine, among others. Choosing a name is the full responsibility of the authors of new mineral proposals submitted to the International Mineralogical Association (IMA). Scientific nomenclature and its traditions have evolved over time and, consequently, mineral names track changes in the landscape of mineralogy with respect to language, technology, and culture. To evaluate these changes, the namesake information for all 5896 minerals approved by the IMA or ‘grandfathered’ into use as of December 2022 was recorded and categorized within a workable database. The compiled information yields diverse insights into the intersection of science and culture and could also be used to project future trends. In this study, we used the name database to investigate gender diversity among mineral eponyms. More than half (c. 54%) of all mineral species are named after people, the identities of whom are largely a reflection of the people that have historically been involved, in one way or another, in the geosciences and in the mining industry. Of the 2738 people with minerals named for them, approximately 6.1% are (interpreted to be) women. Nearly all minerals named for women were named during the last sixty years, although the rate of growth in the year-on-year percentage of women among new mineral namesakes has slowed since about 1985. If current and historical trends hold, our model predicts that women will not comprise more than about 10.35% of newly established mineral namesakes in future years. The representation of women among mineral namesakes also differs starkly among countries. For example, Russians comprise 43.11% of women with minerals named for them, but account for only 15.12% of all eponyms. However, there are additional disparities beyond the proportions of namesakes. For scientists who were alive when a mineral was named for them, women were an average of 3.74 years older than men when evaluated over the same timespan (1954–2022). These results demonstrate that gender-based disparities are imprinted into current mineral nomenclature and indicate that gender parity among new mineral namesakes is impossible without unprecedented changes in the upstream demographics that are most likely to affect naming trends.

58 GEOSCIENCES↗
DOE OSTI2024

SRNL High and Low Activity Residue Characterization System Phase II [Poster]

The characterization system contains data sampled from 1996 to 2024 and can display any desired combination of 45 different isotopes. This system is intended to be used to quickly access historical data, generate trends for accurate future projections, and evaluate relevant unit conversion calculations.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2024

Powered by dsgrid [Slides]

NREL's demand-side grid (dsgrid) toolkit harnesses decades of sector-specific energy modeling expertise to understand current and future U.S. electricity load for power systems analyses. The primary purpose of dsgrid is to create comprehensive electricity load data sets at high temporal, geographic, sectoral, and end-use resolution. These data sets enable detailed analyses of current patterns and future projections of end-use loads. This presentation will include NREL power grid researcher Elaine Hale.

24 POWER TRANSMISSION AND DISTRIBUTION↗