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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 OSTI2025

Long-term hydro-economic analysis tool for evaluating global groundwater cost and supply: Superwell v1.1

Abstract. Groundwater plays a key role in meeting water demands, supplying over 40 % of irrigation water globally, with this role likely to grow as water demands and surface water variability increase. A better understanding of the future role of groundwater in meeting sectoral demands requires an integrated hydro-economic evaluation of its cost and availability. Yet substantial gaps remain in our knowledge and modeling capabilities related to groundwater availability, recharge, feasible locations for extraction, extractable volumes, and associated extraction costs, which are essential for large-scale analyses of integrated human–water system scenarios, particularly at the global scale. To address these needs, we developed Superwell, a physics-based groundwater extraction and cost accounting model that operates at sub-annual temporal and at the coarsest 0.5° (≈50 km × 50 km) gridded spatial resolution with global coverage. The model produces location-specific groundwater supply–cost curves that provide the levelized cost to access different quantities of available groundwater. The inputs to Superwell include recent high-resolution hydrogeologic datasets of permeability, porosity, aquifer thickness, depth to water table, recharge, and hydrogeological complexity zones. It also accounts for well capital and maintenance costs, as well as the energy costs required to lift water to the surface. The model employs a Theis-based scheme coupled with an amortization-based cost accounting formulation to simulate groundwater extraction and quantify the cost of groundwater pumping. The result is a spatiotemporally flexible, physically realistic, economics-based model that produces groundwater supply–cost curves. We show examples of these supply–cost curves and the insights that can be derived from them across a set of scenarios designed to explore model outcomes. The supply–cost curves produced by the model show that most (90 %) nonrenewable groundwater in storage globally is extractable at costs lower than USD 0.57 m−3, while half of the volume remains extractable at under USD 0.108 m−3. The global unit cost is estimated to range from a minimum of USD 0.004 m−3 to a maximum of USD 3.971 m−3. We also demonstrate and discuss examples of how these cost curves could be used by linking Superwell's outputs with other models to explore coupled human–environmental system challenges, such as water resources planning and management, or broader analyses of multisectoral feedbacks.

Global Change Analysis Model (GCAM)↗
DOE OSTI2026

Historical and Future Global Irrigation Energy Consumption by Fuel and Region

Irrigation energy use is a significant component of agricultural production costs, contributing directly to the energy and emissions intensity of crop production and ultimately to food prices. Understanding the existing structure of irrigation energy consumption help achieve food-energy-water security and environmental goals. We present a comprehensive global data set detailing country-level irrigation energy consumption, emphasizing the comparative use of electric, diesel, and emerging solar pumps. To our knowledge, no such data set exists. We draw from a literature review to develop a logistic transformed regression model to estimate the shares of fuel sources for irrigation across countries over historical years to construct a global data set of country-level irrigation energy consumption by multiple fuel sources. Additionally, we compare our estimates of irrigation energy use with agricultural energy use as reported by the International Energy Agency and other external sources. We then use this data to project future irrigation energy use with the Global Change Analysis Model, which is a multisector dynamics model, to showcase the usage of this data set. Projections under the reference scenario show a global shift in fuel types for irrigation pumping, while patterns vary across regions, with India and Pakistan leading in solar-powered irrigation growth and countries like the USA and China continuing to rely primarily on grid electricity. This data set provides a resource to understand the role of irrigation fuel choices within the broader energy sector, as well as the connected agricultural, land use, and water sectors under alternative future scenarios, enabling informed decision making toward efficient agricultural practices.

Global Change Analysis Model (GCAM)↗
DOE OSTI2024

Global spatially explicit carbon emissions from land-use change over the past six decades (1961–2020)

Land-use change (LUC) is a major source of global anthropogenic carbon emissions that contribute to climate change. However, current estimates of LUC-induced emissions vary widely with differences in data and models, making it challenging to identify and manage emissions hotspots by location and LUC activity. Here, we estimated spatially explicit carbon fluxes associated with global major gross land-use transitions based on a new bookkeeping model (i.e., LUCE). Between 1961 and 2020, LUC induced 215 and 142 Pg C of global carbon emissions and removals, respectively, resulting in average net emissions (E LUC ) of 1.21 Pg C year −1 . Latin America, Southeast Asia, and Sub-Saharan Africa dominated global E LUC with 69% of 60-year cumulative emissions, or about 86% between 2001 and 2020. Forest-related LUC activities (e.g., deforestation, reforestation) contributed largely to both regional and global carbon fluxes. Our findings shed new light on identifying LUC-induced emissions hotspots and managing land for climate mitigation and conservation.

bookkeeping model↗
NASA NTRS2013

Global and Regional Temperature-change Potentials for Near-term Climate Forcers

The emissions of reactive gases and aerosols can affect climate through the burdens of ozone, methane and aerosols, having both cooling and warming effects. These species are generally referred to near-term climate forcers (NTCFs) or short-lived climate pollutants (SLCPs), because of their short atmospheric residence time. The mitigation of these would be attractive for both air quality and climate on a 30-year timescale, provided it is not at the expense of CO2 mitigation. In this study we examine the climate effects of the emissions of NTCFs from 4 continental regions (East Asia, Europe, North America and South Asia) using results from the Task Force on Hemispheric Transport of Air Pollution Source-Receptor global chemical transport model simulations. We address 3 aerosol species (sulphate, particulate organic matter and black carbon - BC) and 4 ozone precursors (methane, reactive nitrogen oxides - NOx, volatile organic compounds VOC, and carbon monoxide - CO). For the aerosols the global warming potentials (GWPs) and global temperature change potentials (GTPs) are simply time-dependent scaling of the equilibrium radiative forcing, with the GTPs decreasing more rapidly with time than the GWPs. While the aerosol climate metrics have only a modest dependence on emission region, emissions of NOx and VOCs from South Asia have GWPs and GTPs of higher magnitude than from the other northern hemisphere regions. On regional basis, the northern mid-latitude temperature response to northern mid-latitude emissions is approximately twice as large as the global average response for aerosol emission, and about 20-30% larger than the global average for methane, VOC and CO emissions. We also found that temperatures in the Arctic latitudes appear to be particularly sensitive to black carbon emissions from South Asia.

climate forcer↗
NASA NTRS2014

Changes in Global Tropospheric OH Expected as a Result of Climate Change Over the Last Several Decades

The oxidizing capacity of the troposphere is controlled primarily by the abundance of hydroxyl radical (OH). The global mean concentration of OH, [OH]_GLOBAL, inferred from measurements of methyl chloroform, has remained relatively constant during the past several decades, despite rising levels of CH4 that should have led to a steady decline. Here we examine other factors that may have affected [OH]_GLOBAL, such as the changing overhead burden of stratospheric O3 using observations from OMI, TOMS and SBUV; rising tropospheric H2O using observations from AIRS and reanalysis fields from MERRA; and widening of the climatological tropics using widening rate estimates from the literature and global OH fields from the GEOS Chemistry-Climate Model. Our analysis suggests these factors may have contributed a positive trend to [OH]_GLOBAL large enough to counter the decrease due to CH4.

Climate Change↗
NASA NTRS2014

Thermal Tides During the 2001 Martian Global-Scale Dust Storm

The 2001 (Mars Year 25) global dust storm radically altered the dynamics of the Martian atmosphere. Using observations from the Thermal Emission Spectrometer onboard the Mars Global Surveyor spacecraft and Mars WRF general circulation model simulations, we examine the changes to thermal tides and planetary waves caused by the storm. We find that the extratropical diurnal migrating tide is dramatically enhanced during the storm, particularly in the southern hemisphere, reaching amplitudes of more than 20 K. The tropical diurnal migrating tide is weakened to almost undetectable levels. The diurnal Kelvin waves are also significantly weakened, particularly during the period of global expansion at Ls=200deg-210deg. In contrast, the westward propagating diurnal wavenumber 2 tide strengthens to 4-8 K at altitudes above 30km. The wavenumber 1 stationary wave reaches amplitudes of 10-12 K at 50deg-70degN, far larger than is typically seen during this time of year. The phase of this stationary wave and the enhancement of the diurnal wavenumber 2 tide appear to be responses to the high-altitude westward propagating equatorial wavenumber 1 structure in dust mixing ratio observed during the storm in previous works. This work provides a global picture of dust storm wave dynamics that reveals the coupling between the tropics and high-latitude wave responses. We conclude that the zonal distribution of thermotidal forcing from atmospheric aerosol concentration is as important to understanding the atmospheric wave response as the total global mean aerosol optical depth.

Thermal tides↗
NASA NTRS2015

Spatial and Temporal Analysis of a Global Landslide Catalog

Landslide inventories are critical to support investigations ofwhere andwhen landslides have happened andmay occur in the future; however, there is surprisingly little information on the historical occurrence of landslides at the global scale. This paper presents a new publicly available global landslide catalog (GLC), which is based on media reports, online databases, and other sources. This database is currently available at http://ojo-streamer. herokuapp.com/. The 5741 points in the GLC provide a foundation for evaluating spatial and temporal trends in landslide activity from 2007 to 2013. Globally, landslideswere reportedmost frequently from July to September. Most events occurred in Asia, North America and Southeast Asia. In contrast, fewer than 5% of the fatalities were reported in North America, suggesting a significant amount of under-reporting in other regions as well as potential discrepancies between developing and developed regions. Reported landslide events were also compared to satellite-based precipitation estimates fromthe Tropical RainfallMeasuring Mission (TRMM) to evaluate the co-occurrence of extreme precipitation and landslide activity. Of the 3550 points considered in a subset of the GLC, approximately 60% of the reported landslides have daily precipitation exceeding the 95th percentile of precipitation calculated over a 14-year TRMMrecord for the same location. This study also investigated how the recurrence interval of extreme precipitation corresponded to some of the most catastrophic landslide events. In spite of several reporting and cataloging biases, spatial and temporal analysis of the GLC suggests that it is a valuable database for characterizing global patterns of landslide occurrence and evaluating relationships with extreme precipitation at regional and global scales.

Analysis↗
NASA NTRS2016

Detecting Climate Signals in Precipitation Extremes from TRMM (1998-2013) - Increasing Contrast Between Wet and Dry Extremes During the "Global Warming Hiatus"

We investigate changes in daily precipitation extremes using Tropical Rainfall Measuring Mission (TRMM) data (1998-2013), which coincides with the "global warming hiatus." Results show a change in probability distribution functions of local precipitation events (LPEs) during this period consistent with previous global warming studies, indicating increasing contrast between wet and dry extremes, with more intense LPE, less moderate LPE, and more dry (no rain) days globally. Analyses for land and ocean separately reveal more complex and nuanced changes over land, characterized by a strong positive trend (+12.0% per decade, 99% confidence level (c.l.)) in frequency of extreme LPEs over the Northern Hemisphere extratropics during the wet season but a negative global trend (−6.6% per decade, 95% c.l.) during the dry season. A significant global drying trend (3.2% per decade, 99% c.l.) over land is also found during the dry season. Regions of pronounced increased dry events include western and central U.S., northeastern Asia, and Southern Europe/Mediterranean.

Precipitation↗
NASA NTRS2016

Global Simulation of Aviation Operations

The simulation and analysis of global air traffic is limited due to a lack of simulation tools and the difficulty in accessing data sources. This paper provides a global simulation of aviation operations combining flight plans and real air traffic data with historical commercial city-pair aircraft type and schedule data and global atmospheric data. The resulting capability extends the simulation and optimization functions of NASA's Future Air Traffic Management Concept Evaluation Tool (FACET) to global scale. This new capability is used to present results on the evolution of global air traffic patterns from a concentration of traffic inside US, Europe and across the Atlantic Ocean to a more diverse traffic pattern across the globe with accelerated growth in Asia, Australia, Africa and South America. The simulation analyzes seasonal variation in the long-haul wind-optimal traffic patterns in six major regions of the world and provides potential time-savings of wind-optimal routes compared with either great circle routes or current flight-plans if available.

simulation↗
NASA NTRS2018

Are Water Markets Globally Applicable?

Water scarcity is a global concern that necessitates a global perspective, but it is also the product of multiple regional issues that require regional solutions. Water markets constitute a regionally applicable non-structural measure to counter water scarcity that has received the attention of academics and policy-makers, but there is no global view on their applicability. We present the global distribution of potential nations and states where water markets could be instituted in a legal sense, by investigating 296 water laws internationally, with special reference to a minimum set of key rules: legalization of water reallocation, the separation of water rights and landownership, and the modification of the cancellation rule for non-use. We also suggest two additional globally distributed prerequisites and policy implications: the predictability of the available water before irrigation periods and public control of groundwater pumping throughout its jurisdiction.

global water scarcity↗
NASA NTRS2020

Uncertainty Quantification of Global Net Methane Emissions From Terrestrial Ecosystems Using a Mechanistically Based Biogeochemistry Model

Quantification of methane (CH4) emissions from wetlands and its sinks from uplands is still fraught with large uncertainties. Here, a methane biogeochemistry model was revised, parameterized, and verified for various wetland ecosystems across the globe. The model was then extrapolated to the global scale to quantify the uncertainty induced from four different types of uncertainty sources including parameterization, wetland type distribution, wetland area distribution, and meteorological input. We found that global wetland emissions are 212 ± 62 and 212 ± 32 Tg CH4 year−1 (1Tg = 1012 g) due to uncertain parameters and wetland type distribution, respectively, during 2000–2012. Using two wetland distribution data sets and three sets of climate data, the model simulations indicated that the global wetland emissions range from 186 to 212 CH4 year−1 for the same period. The parameters were the most significant uncertainty source. After combining the global methane consumption in the range of −34 to −46 Tg CH4 year−1, we estimated that the global net land methane emissions are 149–176 Tg CH4 year−1 due to uncertain wetland distribution and meteorological input. Spatially, the northeast United States and Amazon were two hotspots of methane emission, while consumption hotspots were in the Eastern United States and eastern China. During 1950–2016, both wetland emissions and upland consumption increased during El Niño events and decreased during La Niña events. This study highlights the need for more in situ methane flux data, more accurate wetland type, and area distribution information to better constrain the model uncertainty.

wetland methane emission↗
NASA NTRS2022

Impacts of Climate Change on Global Food Trade Networks

Countries' reliance on global food trade networks implies that regionally different climate change impacts on crop yields will be transmitted across borders. This redistribution constitutes a significant challenge for climate adaptation planning and may affect how countries engage in cooperative action. This paper investigates the long-term (2070–2099) potential impacts of climate change on global food trade networks of three key crops: wheat, rice and maize. We propose a simple network model to project how climate change impacts on crop yields may be translated into changes in trade. Combining trade and climate impact data, our analysis proceeds in three steps. First, we use network community detection to analyse how the concentration of global production in present-day trade communities may become disrupted with climate change impacts. Second, we study how countries may change their network position following climate change impacts. Third, we study the total climate-induced change in production plus import within trade communities. Results indicate that the stability of food trade network structures compared to today differs between crops, and that countries' maize trade is least stable under climate change impacts. Results also project that threats to global food security may depend on production change in a few major global producers, and whether trade communities can balance production and import loss in some vulnerable countries. Overall, our model contributes a baseline analysis of cross-border climate impacts on food trade networks.

climate change↗
NASA NTRS2023

Convective Impact on the Global Lower Stratospheric Water Vapor Budget

Water vapor in the stratosphere is primarily controlled by temperatures in the tropical upper troposphere and lower stratosphere. However, the direct impact of deep convection on the global lower stratospheric water vapor budget is still an actively debated issue. Two complementary modeling approaches are used to investigate the convective impact in boreal winter and summer. Convective influence is diagnosed by tracing trajectories through convective cloud top altitude fields derived from global rainfall and brightness temperature data. Backward trajectory model simulations coupled with a detailed treatment of cloud microphysical processes indicate that convection moistens the global lower stratosphere by approximately 0.3 ppmv in boreal winter and summer 2010. The diurnal peak in convection is responsible for about half of the total convective moistening during winter and nearly all of the convective moistening during summer. Deep convective clouds overshooting the tropopause have relatively minor effect on global lower stratospheric water vapor. A forward trajectory model coupled with a simplified cloud module is used to estimate the relative magnitude of the interannual variability of the convective impact. Combining the results from the two models, we find that the convective impact on the global lower stratospheric water vapor during 2006-2016 is approximately 0.3 ppmv with year-to-year variations of up to 0.1 ppmv. An important mechanism of convective hydration of the lower stratosphere is via the detrainment of saturated air and ice into the tropical uppermost troposphere and the subsequent upward transport of some of these moist air parcels across relatively warm and subsaturated tropopause.

CONVECTION↗
NASA NTRSDate not supplied

Efficient Global Optimization with Gradient Finish for Design Under Uncertainty

The Efficient Global Optimization (EGO) algorithm is extended to include a gradient-descent-based finish upon reaching a threshold value of the expected improvement function. Emphasis is placed on efficient evaluation of local gradients using Kriging models during the gradient-based finish to enable application to design under uncertainty (DUU) problems. The modified algorithm is applied to both the well-known Rosenbrock function and a more challenging hypersonic inlet design under uncertainty problem. Results demonstrate improvement in locating the global optimum compared to the classical implementation of EGO, as well as a reduced number of true function evaluations compared to pure gradient-based algorithms. For the Rosenbrock function, a global optimum is returned using an average of 12% fewer function calls than a gradient-based optimizer with comparable tolerances. For the design under uncertainty problem, a global optimum is found using an average of 75% fewer function calls than a gradient-based optimizer. Global Pareto fronts of multiobjective DUU problems are obtained at little additional cost after a single optimization is complete.

Optimization↗
DOE OSTI2024

Global brain activity and its coupling with cerebrospinal fluid flow is related to tau pathology

Abstract INTRODUCTION Factors responsible for the deposition of pathological tau in the brain are incompletely understood. This study links macroscale tau deposition in the human brain to cerebrospinal fluid (CSF) flow dynamics using resting‐state functional magnetic resonance imaging (rsfMRI). METHODS Low‐frequency (< 0.1 Hz) resting‐state global brain activity is coupled with CSF flow and potentially reflects CSF dynamics‐related clearance. We examined the correlation between rsfMRI measures of CSF inflow and global activity (gBOLD–CSF coupling) as a predictor, interacting with amyloid beta (Aβ), of tau and cortical thickness (dependent variables) across Alzheimer's Disease Neuroimaging Initiative (ADNI) participants from cognitively unimpaired through mild cognitive impairment (MCI) and Alzheimer's disease (AD). RESULTS Tau deposition in Aβ+ participants, accompanied by cortical thinning and cognitive decline, is associated with decreased gBOLD–CSF coupling. Tau mediates the relationship between coupling and thickness. DISCUSSION Findings suggest that resting‐state global brain activity and CSF movements comodulate Alzheimer's tau deposition, presumably related to CSF clearance. Highlights A non‐invasive functional magnetic resonance imaging (fMRI) assessment of a CSF clearance‐related process is carried out. Global brain activity is coupled with CSF inflow in human fMRI during resting state. Global fMRI–CSF coupling is correlated with tau in Alzheimer's disease (AD). This coupling measure is also associated with cortical thickness, mediated by tau.

Neurosciences & Neurology↗
DOE OSTI2026

Do we have globally representative data to understand soil processes?

Understanding and modeling soils and soil organic matter (SOM) are central to a variety of human needs, from food production to ecosystem management. Soil data have been collected for over a century, but the global spatial and process representativeness of soil data remains unclear. We assessed the representativeness of currently available soil data that could be used to understand a variety of SOM processes. We used 16 open-source soil databases and data from over 281,000 unique locations globally, categorizing the databases into three main data types necessary to understand SOM processes: soil carbon stocks and fluxes, mechanistic drivers of these stocks and fluxes, and soil carbon gain or loss potential. We found that stock and driver data have extensive global coverage. However, data on soil carbon gain or loss potential, particularly data describing change in soils over time such as time series data, are severely limited in their global coverage. We conclude that while significant strides have been made in measuring soil carbon stocks and fluxes, and their drivers, we are limited in global data related to changes in soils over time. Our recommendations for soil data generators are to ensure precise metadata reporting and prioritizing sampling in underrepresented areas like tropical, arctic, mountainous, wetland and arid regions. We also encourage designing revisit schemes that explicitly support change detection and reporting multi-modal datasets that can aid in model development. Targeted measurement of low coverage soil data types and regions is necessary for a range of applications including current and future biogeochemical predictions, and their management and policy implications.

carbon fluxes↗
DOE OSTI2024

A global urban heat island intensity dataset: Generation, comparison, and analysis

The urban heat island (UHI) effect, a phenomenon of local warming over urban areas, is the most well-known impact of urbanization on climate. Globally consistent estimates of the UHI intensity (UHII) are crucial for examining this phenomenon across time and space. However, publicly available UHII datasets are limited and have several constraints: (1) they are for clear-sky surface UHII, not all-sky surface UHII and canopy (air temperature) UHII; (2) the estimation methods often neglect anthropogenic disturbance, introducing uncertainties in the estimated UHII. To address these issues, this study proposes a new dynamic equal-area (DEA) method that can minimize the influence of various confounding factors on UHII estimates through a dynamic cyclic process. Utilizing the DEA method and leveraging various gridded temperature data, we develop a global-scale (>10,000 cities), long-term (over 20 years by month), and multi-faceted (clear-sky surface, all-sky surface, and canopy) UHII dataset. Further, based on these estimates, we provide a comprehensive analysis of the UHII and its trends in global cities. The UHII is found to be greater than zero in >80% of cities, with global annual average magnitudes around 1.0 °C (day) and 0.8 °C (night) for surface UHII, and close to 0.5 °C for canopy UHII. Furthermore, an interannual upward trend in UHII is observed in >60% of cities, with global annual average trends exceeding 0.1 °C/decade (day) and over 0.06 °C/decade (night) for surface UHII, and slightly surpassing 0.03 °C/decade for canopy UHII. Notably, there exists a positive correlation between the magnitude and trend of UHII, suggesting that cities with stronger UHII tend to experience faster growth in UHII. Additionally, discrepancies in UHII are found between different temperature data, stemming not only from distinctions in data types (surface or air temperature) but also from differences in data acquisition times (Terra or Aqua), weather conditions (clear-sky or all-sky), and processing methodologies (with or without gap filling). Overall, our proposed method, dataset, and analysis results have the potential to provide valuable insights for future urban climate studies. The UHII dataset is publicly available at https://doi.org/10.6084/m9.figshare.24821538.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Large Ensemble Exploration of Global Energy Transitions Under National Emissions Pledges

Global climate goals require a transition to a deeply decarbonized energy system. Meeting the objectives of the Paris Agreement through countries' nationally determined contributions and long-term strategies represents a complex problem with consequences across multiple systems shrouded by deep uncertainty. Robust, large-ensemble methods and analyses mapping a wide range of possible future states of the world are needed to help policymakers design effective strategies to meet emissions reduction goals. This study contributes a scenario discovery analysis applied to a large ensemble of 5,760 model realizations generated using the Global Change Analysis Model. Eleven energy-related uncertainties are systematically varied, representing national mitigation pledges, institutional factors, and techno-economic parameters, among others. The resulting ensemble maps how uncertainties impact common energy system metrics used to characterize national and global pathways toward deep decarbonization. Results show globally consistent but regionally variable energy transitions as measured by multiple metrics, including electricity costs and stranded assets. Larger economies and developing regions experience more severe economic outcomes across a broad sampling of uncertainty. The scale of CO 2 removal globally determines how much the energy system can continue to emit, but the relative role of different CO 2 removal options in meeting decarbonization goals varies across regions. Previous studies characterizing uncertainty have typically focused on a few scenarios, and other large-ensemble work has not (to our knowledge) combined this framework with national emissions pledges or institutional factors. Our results underscore the value of large-ensemble scenario discovery for decision support as countries begin to design strategies to meet their goals.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗