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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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At least 109 records · Page 6
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Projecting Changes in the Frequency and Magnitude of Ozone Pollution Events Under Uncertain Climate Sensitivity

Abstract Climate change is projected to worsen ozone pollution over many populated regions, with larger impacts at higher concentrations. More intense and frequent ozone episodes risk setbacks to human health and environmental policy achievements. However, assessing these changes is complicated by uncertain climate sensitivity, closely related to climate model response, and internal variability in simulations projecting climate's influence on air quality. Here, leveraging a global modeling framework that one‐way couples a human activity model, an Earth system model of intermediate complexity, and an atmospheric chemistry model, we investigate the role of climate sensitivity in climate‐induced changes to high ozone pollution episodes in the United States using multiple greenhouse gas emissions scenarios, representations of climate sensitivity, and initial condition members. We bias correct and evaluate historical model simulations, identifying modeled and observed O 3 episodes using extreme value theory, and extend the approach to projections of mid‐ and end‐century climate impacts. Results show that the influence of climate sensitivity can be as significant as that of greenhouse gas emissions scenario absent precursor emissions changes. Climate change is projected to increase the magnitude of the highest annually occurring O 3 concentrations by over 2.3 ppb on average across the U.S. at mid‐century under a high climate sensitivity and moderate emissions scenario, but the increase is limited to less than 0.3 ppb under lower climate sensitivity. Further, we show that areas in the U.S. currently meeting air quality standards risk being pushed into non‐compliance due to a climate‐induced increase in frequency of high ozone days.

Environmental Sciences & Ecology↗
DOE OSTI2025

The Observed and Projected Changes of Global Monsoons: Current Status and Future Perspectives

The global monsoon system, encompassing the Asian-Australian, African, and American monsoons, sustains two-thirds of the world’s population by regulating water resources and agriculture. Monsoon anomalies pose severe risks, including floods and droughts. Recent research associated with the implementation of the Global Monsoons Model Intercomparison Project under the umbrella of CMIP6 has advanced our understanding of its historical variability and driving mechanisms. Observational data reveal a 20th-century shift: increased rainfall pre-1950s, followed by aridification and partial recovery post-1980s, driven by both internal variability (e.g., Atlantic Multidecadal Oscillation) and external forcings (greenhouse gases, aerosols), while ENSO drives interannual variability through ocean-atmosphere interactions. Future projections under greenhouse forcing suggest long-term monsoon intensification, though regional disparities and model uncertainties persist. Models indicate robust trends but struggle to quantify extremes, where thermodynamic effects (warming-induced moisture rise) uniformly boost heavy rainfall, while dynamical shifts (circulation changes) create spatial heterogeneity. Volcanic eruptions and proposed solar radiation modification (SRM) further complicate predictions: tropical eruptions suppress monsoons, whereas high-latitude events alter cross-equatorial flows, highlighting unresolved feedbacks. The emergent constraint approach is booming in terms of correcting future projections and reducing uncertainty with respect to the global monsoons. Critical challenges remain. Model biases and sparse 20th-century observational data hinder accurate attribution. The interplay between natural variability and anthropogenic forcings, along with nonlinear extreme precipitation risks under warming, demands deeper mechanistic insights. Additionally, SRM’s regional impacts and hemispheric monsoon interactions require systematic evaluation. Addressing these gaps necessitates enhanced observational networks, refined climate models, and interdisciplinary efforts to disentangle multiscale drivers, ultimately improving resilience strategies for monsoon-dependent regions.

climate extreme events↗
DOE OSTI2025

Lack of clear standards and usable comparisons of downscaled climate projections pose a roadblock for US climate discovery and adaptation

Abstract The release of global climate projections coupled with the demand for local-resolution climate-forced meteorology has prompted many research groups to downscale these projections using various statistical, dynamical, and current machine learning techniques. Such downscaled datasets are being used to plan infrastructure and other community needs over the coming decades. Faced with roughly a dozen available US downscaled datasets, many practitioners ask, ‘What are the relevant differences between datasets?’ This work highlights the difficulty of comparing downscaled datasets and illustrates ways in which datasets differ even when using identical climate model input data. We show that substantial variability in precipitation projections arises from downscaling alone and that the downscaled dataset agreement varies depending on global climate projection. This analysis emphasizes the need for greater coordination and movement toward rigorous benchmarking of downscaling strategies within the downscaling research community, à la the land-modeling community, to better quantify downscaling dataset differences, strengths, and weaknesses for practitioners.

Hartke, Samantha H. (ORCID:0000000202394723)↗
DOE OSTI2024

Future Climate Projections for South Florida: Improving the Accuracy of Air Temperature and Precipitation Extremes With a Hybrid Statistical Bias Correction Technique

Projecting future climate variables is essential for comprehending the potential impacts on hydroclimatic hazards like floods and droughts. Evaluating these impacts is challenging due to the coarse spatial resolution of global climate models (GCMs); therefore, bias correction is widely used. Here, we applied two statistical methods—standard empirical quantile mapping (EQM) and a hybrid approach, EQM with linear correction (EQM-LIN)—to bias correct precipitation and air temperature simulated by nine GCMs. We used historical observations from 20 weather stations across South Florida to project future climate under three shared socioeconomic pathways (SSPs). Compared to the EQM, the hybrid EQM-LIN method improved R 2 of daily quantiles by up to 30% over the historical period and improved MAE up to 70% in months that contain most extreme values. Projected extreme precipitation at the weather stations showed that, compared to the EQM-LIN, the EQM method underestimates the high quantiles by up to 26% in SSP585. The projected changes in annual maximum precipitation from historical period (1985–2014) to near future (2040–2069) and far future (2070–2100) were between 2% and 16% across the study area. Projected future precipitation suggested a slight decrease during summer but an increase in fall. This, along with rising summer temperatures, suggested that South Florida can experience rapid oscillations from warmer summers and increased flooding in fall under future climate. Additionally, our comparative analyses with globally and nationally downscaled studies showed that such coarse scale studies do not represent the climatic extremes well, particularly for high quantile precipitation.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2017

Assessing Inter-Sectoral Climate Change Risks: The Role of ISIMIP

The aims of the Inter-Sectoral Impact Model Intercomparison Project (ISIMIP) are to provide a framework for the intercomparison of global and regional-scale risk models within and across multiple sectors and to enable coordinated multi-sectoral assessments of different risks and their aggregated effects. The overarching goal is to use the knowledge gained to support adaptation and mitigation decisions that require regional or global perspectives within the context of facilitating transformations to enable sustainable development, despite inevitable climate shifts and disruptions. ISIMIP uses community-agreed sets of scenarios with standardized climate variables and socioeconomic projections as inputs for projecting future risks and associated uncertainties, within and across sectors. The results are consistent multi-model assessments of sectoral risks and opportunities that enable studies that integrate across sectors, providing support for implementation of the Paris Agreement under the United Nations Framework Convention on Climate Change.

Regional-scale risk models↗
DOE OSTI2024

High-Resolution Meteorology with Climate Change Impacts from Global Climate Model Data Using Generative Machine Learning

As renewable energy generation increases, the impacts of weather and climate on energy generation and demand become critical to the reliability of the energy system. However, these impacts are often overlooked. Global climate models (GCMs) can be used to understand possible changes to our climate, but their coarse resolution makes them difficult to use in energy system modelling. Here we present open-source generative machine learning methods that produce meteorological data at a nominal spatial resolution of 4 km at an hourly frequency based on inputs from 100 km daily-average GCM data. These methods run 40 times faster than traditional downscaling methods and produce data that have high-resolution spatial and temporal attributes similar to historical datasets. We demonstrate that these methods can be used to downscale projected changes in wind, solar and temperature variables across multiple GCMs including projections for more frequent low-wind and high-temperature events in the Eastern United States.

climate change↗
DOE OSTI2020

Simple Algorithms for a Physics Code Base

Project 1: Developing a container for state variables in a physics code. Project 2: Setting up near-continuous performance and usage metrics monitoring of a physics code.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2025

Implications of Aerosol Physicochemical Properties Including Ice Nucleation at ARM Mega Sites for Improved Understanding of Microphysical Atmospheric Cloud Processes (Final Technical Report)

Continuous, long-term measurements of atmospheric ice-nucleating particles (INPs) that influence clouds and precipitation were conducted to investigate the abundance and variability of ground-level INPs across the world. Three field campaigns were organized by the DOE Atmospheric Radiation Measurement (ARM) program, including Examining INP from Southern Great Plains (ExINP-SGP, 2019), Examining INP from Eastern North Atlantic (ExINP-ENA, 2020 – 2021), and Examining INP from North Slope of Alaska (ExINP-NSA, 2021 – 2024). Additional small-scale supporting field experiments were performed in 2019 and 2021 to collect airborne particulate matter at SGP for complementary laboratory characterization of the particles’ physical and chemical properties [Aerosol-Ice Formation Closure Pilot Study (AEROICESTUDY), 2019; ExINP-SGP II, 2021]. In these studies, the PI’s team measured INP concentration with both real-time and laboratory measurements in a wide range of freezing temperatures ($T$ from 0 °C to about –30 °C). This project elucidated spatial variability and seasonality in the abundance of immersion mode active INPs across three ARM sites using a single instrument, a Portable Ice Nucleation Experiment (PINE) chamber version 03 (PINE-03 hereafter). Collocated aerosol and meteorological data were analyzed to assess the correlation between ambient INP abundance, air mass origin region, and meteorological variability. Our findings suggest very high freezing efficiency of INPs at the NSA site across the measured temperatures (ice nucleation active surface site density, $n_s(T)$, $\approx 2 \times 10^{8} - 10^{10}$ m -2 for from –16 to –31 °C), which is a factor of 10 – 1000 times greater efficiency as compared to that found in the previous mid-latitude INP measurements in autumn using the same instrument; surprisingly high INP abundance ($\ge 1 \text{ L}^{-1}$ at –25 °C) for the examined temperatures throughout the year that PINE-03 did not measure at other sites; and high INP concentration in spring, possibly related to arctic haze episodes.

58 GEOSCIENCES↗
DOE OSTI2021

SB10 Frit Recommendation, and Evaluations of the Glass Variability Study and Cs-137 Concentrations in Strip Effluent Based on May 2021 Projections

The Defense Waste Processing Facility (DWPF) is currently preparing to initiate processing of Sludge Batch 10 (SB10), which is comprised of material from Tanks 11H, 13H, 15H, and 26F, Alternate Feed Stock-2 (AFS-2) and Sodium Reactor Experiment (SRE) material from H-Canyon. In support of SB10 qualification, frit development using 2020 Tank 40 blend projections and experimental work for the glass variability study were previously conducted. Frit 473 and Frit 209 were identified as candidate frits and both were included in the development of the variability study test matrix; however, a final frit recommendation was postponed until more information could be determined about the composition of SB10 after washing. In May 2021, Savannah River Remediation (SRR) reprojected SB10 based on the analytical results from the Tank 51 qualification sample that was washed in the Savannah River National Laboratory (SRNL) Shielded Cells Facility.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2020

MACHO 311.37557.169: A VY Scl star

Abstract Optical surveys, such as the MACHO project, often uncover variable stars whose classification requires follow‐up observations by other instruments. We performed X‐ray spectroscopy and photometry of the unusual variable star MACHO 311.37557.169 with XMM‐Newton in April 2018, supplemented by archival X‐ray and optical spectrographic data. The star has a bolometric X‐ray luminosity of about 1 × 10 32 erg s −1 cm −2 and a heavily absorbed two‐temperature plasma spectrum. The shape of its light curve, its overall brightness, its X‐ray spectrum, and the emission lines in its optical spectrum suggest that it is most likely a VY Scl cataclysmic variable.

Wörpel, Hauke↗
DOE OSTI2021

EPIsembleVis: A geo-visual analysis and comparison of the prediction ensembles of multiple COVID-19 models

In this work, we present EPIsembleVis, a web-based comparative visual analysis tool for evaluating the consistency of multiple COVID-19 prediction models. Our approach analyzes a collection of COVID-19 predictions from different epidemiological models as an ensemble and utilizes two metrics to quantify model performance. These metrics include (a) prediction uncertainty (represented as the dispersion of predictions in each ensemble) and (b) prediction error (calculated by comparing individual model predictions with the recorded data). Through an interactive visual interface, our approach provides a data-driven workflow for (a) selecting and constructing the COVID-19 model prediction ensemble based on the spatiotemporal overlap of available predictions of multiple epidemiological models, (b) quantifying the model performance using both the uncertainty of each model prediction ensemble, and the error of each ensemble member that represents individual model predictions, and (c) visualizing the spatiotemporal variability in the projection performance of individual models using a suite of novel ensemble visualization techniques, such as the data availability map, a spatiotemporal textured-tile calendar, multivariate rose chart, and time-series leaflet glyph. We demonstrate the capability of our ensemble visual interface through a case study that investigates the performance of weekly COVID-19 predictions, which are provided through the COVID-19 Forecast Hub UMass-Amherst Influenza Forecasting Center of Excellence [47] for the United States and United States Territories. The EPIsembleVis tool is implemented using open-source web technologies and adaptive system design, rendering it interoperable with Elasticsearch and Kibana for automatically ingesting COVID-19 predictions from online repositories, and it is generalizable for analyzing worldwide projections from more epidemiological models.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2024

Stress Testing California's Hydroclimatic Whiplash: Potential Challenges, Trade‐Offs and Adaptations in Water Management and Hydropower Generation

Abstract Inter‐annual precipitation in California is highly variable, and future projections indicate an increase in the intensity and frequency of hydroclimatic “whiplash.” Understanding the implications of these shocks on California's water system and its degree of resiliency is critical from a planning perspective. Therefore, we quantify the resilience of reservoir services provided by water and hydropower systems in four basins in the western Sierra Nevada. Using downscaled runoff from 10 climate model outputs, we generated 200 synthetic hydrologic whiplash sequences of alternating dry and wet years to represent a wide range of extremes and transitional conditions used as inputs to a water system simulation model. Sequences were derived from upper (wet) and lower (dry) quintiles of future streamflow projections (2030–2060). Results show that carryover storage was negatively affected in all basins, particularly in those with lower storage capacity. All basins experienced negative impacts on hydropower generation, with losses ranging from 5% to nearly 90%. Reservoir sizes and inflexible operating rules are a particular challenge for flood control, as in extremely wet years spillage averaged nearly the annual basins' total discharge. The reliability of environmental flows and agricultural deliveries varied depending on the basin, intensity, and duration of whiplash sequences. Overall, wet years temporarily rebound negative drought effects, and greater storage capacity results in higher reliability and resiliency, and lesser volatility in services. We highlight potential policy changes to improve flexibility, increase resilience, and better equip managers to face challenges posed by whiplash while meeting human and environmental needs.

Environmental Sciences & Ecology↗
DOE OSTI2025

Response of Atmospheric River Width and Intensity to Aquaplanet Warming: A Detection Algorithm‐ and Background Moisture‐Independent Approach

The width of an atmospheric river (AR) is an important parameter when evaluating its impact. Although previous research suggests ARs will widen with global warming, a precise response has been muddled by the large sensitivity of width to a diverse set of AR detection techniques (ARDTs). Here, we propose a methodology that removes the influence of the ARDT by modeling AR‐integrated vapor transport (IVT) profiles as idealized exponential curves with free parameters given by background IVT, intensity above background IVT, and profile width. Notably, our definition for AR profile width does not include any explicit numerical thresholds, relative or absolute, for IVT. We apply our approach to a series of idealized aquaplanet experiments, first with a baseline sea surface temperature (SST) distribution, and then with +2K, +4K, and +6K uniform warming, so as to determine the contributions of each free parameter to AR width. We also apply our approach to high‐resolution atmosphere‐only models forced with SSTs modified to preserve historical variability but following projected warming over 2016–2050. Our results show that contributions to impacts‐relevant AR widening comes primarily from enhancements in background IVT and AR intensity, as opposed to from dynamic width changes.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Precipitation regime changes in High Mountain Asia driven by cleaner air

High Mountain Asia (HMA) has experienced a spatial imbalance in water resources in recent decades, partly due to a dipolar pattern of precipitation changes known as South Drying-North Wetting. These changes can be influenced by both human activities and internal climate variability. While climate projections indicate a future widespread wetting trend over HMA, the timing and mechanism of the transition from a dipolar to a monopolar pattern remain unknown. Here, we demonstrate that the observed dipolar precipitation change in HMA during summer is primarily driven by westerly- and monsoon-associated precipitation patterns. The weakening of the Asian westerly jet, caused by uneven emission of anthropogenic aerosols, favors the dipolar precipitation trend during 1951-2020. Additionally, the phase transition of the interdecadal Pacific oscillation induces an out-of-phase precipitation change between the core region of the South Asian monsoon and southeastern HMA. Under medium or high emission scenarios, corresponding to a global warming of 0.6-1.1 °C compared to the present, the dipolar pattern is projected to shift into a monopolar wetting trend in the 2040s. This shift of precipitation patterns is mainly attributed to the intensified jet stream resulting from reduced emissions of anthropogenic aerosols. In conclusion, these findings underscore the importance of considering the impact of aerosol emission reduction in future social planning by policymakers.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Variable Precision Computing (VPC) (Final Report)

The overall goal of the Variable Precision Computing project is exploring and identifying ways to reduce internodal communication cost in production physics simulation experiments running on a distributed-memory systems by compressing data, either in a lossy or lossless way, thus resulting in a significant computational performance increase. Among the several approaches proposed, the one discussed here has been proposed, designed and implemented by me. It concerns the application of information theory-derived metrics to classical molecular dynamics and computational fluid dynamics simulation experiments.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Multiscale Electricity Modeling for Evaluating Carbon Capture and Sequestration Technologies (Final Report)

Carbon capture and sequestration (CCS) technologies that can operate with a high degree of operating flexibility could provide necessary electric grid flexibility in a system with high shares of variable renewables. This project examines the deployment and dispatch potential of twelve unique flexible CCS (FLECCS) technologies that encompass post-combustion carbon dioxide (CO 2 ) capture designs, concepts using a storage media to enable energy arbitrage, and hybrid processes that integrate CCS with direct air capture (DAC) for flexibility with net zero or negative CO 2 emissions. FLECCS technology potential is explored with a multi-model, multi-scale framework including the Regional Energy Deployment System (ReEDS) electric sector capacity expansion model (CEM) and the PLEXOS production cost model (PCM). Innovative methods were developed to represent FLECCS technology operating modes, performance, and cost in the two models. ReEDS was then used to simulate nine scenarios for each FLECCS technology, three CO 2 emissions price futures reaching $\$$150, $\$$225, and $\$$300/tCO 2 in 2050; and three scenarios for FLECCS technology deployment favorability relative to competing technologies. For each CO 2 price and reference FLECCS favorability, the 2050 infrastructures from ReEDS model are downscaled and implemented in PLEXOS to examine hourly dispatch under detailed operational constraints that are not included in ReEDS. FLECCS technologies exhibited a wide range of deployment potential ranging from none to several hundred gigawatts of capacity, with outcomes highly sensitive to input cost and performance parameters that are inherently highly uncertain. When deployed, FLECCS tended to displace a combination of wind, solar, and natural gas-based technologies rather than supporting increased renewable deployment. As a result, CO 2 emissions reductions facilitated by FLECCS deployment tended to come with higher overall system costs and electricity prices. When economically competitive, FLECCS technologies can contribute significant flexible generation and firm capacity to the grid, but continued technology development and an expanded analytical scope are necessary to fully understand FLECCS deployment potential its impact on the electric power sector. Follow-on analysis incorporating captured CO 2 tax credit value from the Inflation Reduction Act (IRA) and other potential policy scenarios could be particularly valuable, as this policy can substantially change the relative competitiveness of FLECCS technologies.

03 NATURAL GAS↗
DOE OSTI2023

A Persistence Meter for Nimble Alarming Using Ambient Synchrophasor Data

Persistent oscillations in the power grid are often indicative of fragility, and may be harbingers of systemic or cascading failures. Modernization of the grid, including increased penetration of intermittent renewables and integration of new power electronics, is making the oscillatory swing dynamics of the network both more complex and variable. In this project researchers from the University of Wisconsin-Madison (Bernard Lesieutre, lead), Washington State University (Sandip Roy, lead), and the Electric Power Group (Neeraj Nayak, lead) have developed technologies that monitor persistent oscillations in the grid and provide operators with alarms and analytics when concerning oscillations are detected. Some of the algorithms have already been implemented in EPG’s PGDA software and integrated into their RTDMS system for use in control rooms.

24 POWER TRANSMISSION AND DISTRIBUTION↗
NASA NTRS1981

VTOL as it applies to resource development in the Canadian north

It is pointed out that, for many of the natural resource development projects planned in Canada between now and the end of the century, it may be necessary for the work force to commute to the site by air. Examples of successful operations, including those involving VTOL, are given. A computer program developed for determining the least expensive type of aircraft for commuting to remote projects is described. It is noted that the program can select both fixed-wing and helicopter aircraft types for a specific project, employing such variables as the size and shift schedules of the work force and the commuting distance. Capital and operating costs of existing and proposed aircraft types, as well as groundside infrastructure operations and maintenance costs, are compared for competing aircraft.

Lightfoot, R. N.↗