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At least 667 records · Page 37
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Atmospheric Radiation Measurement (ARM) airborne field campaign data products between 2013 and 2018

Airborne measurements are pivotal for providing detailed, spatiotemporally resolved information about atmospheric parameters and aerosol and cloud properties, thereby enhancing our understanding of dynamic atmospheric processes. For 30 years, the US Department of Energy (DOE) Office of Science supported an instrumented Gulfstream 1 (G-1) aircraft for atmospheric field campaigns. Data from the final decade of G-1 operations were archived by the Atmospheric Radiation Measurement (ARM) Data Center and made publicly available at no cost to all registered users. To ensure a consistent data format and to improve the accessibility of the ARM airborne data, an integrated dataset was recently developed covering the final 6 years of G-1 operations (2013 to 2018, https://doi.org/10.5439/1999133; Mei and Gaustad, 2024). The integrated dataset includes data collected from 236 flights (766.4 h), which covered the Arctic, the US Southern Great Plains (SGP), the US West Coast, the eastern North Atlantic (ENA), the Amazon Basin in Brazil, and the Sierras de Córdoba range in Argentina. These comprehensive data streams provide much-needed insight into spatiotemporal variability in the thermodynamic quantities and aerosol and cloud properties for addressing essential science questions in Earth system process studies. This paper describes the DOE ARM merged G-1 datasets, including information on the acquisition, data collection challenges and future potentials, and quality control processes. It further illustrates the usage of this merged dataset to evaluate the Energy Exascale Earth System Model (E3SM) with the Earth System Model Aerosol–Cloud Diagnostics (ESMAC Diags) package.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

The Beneficial Effect of Iron in Aluminum-Cerium-Based Cast Alloys

Iron (Fe) has been considered a major impurity since it is detrimental to the mechanical properties of many cast aluminum alloys due to the formation of Fe-containing brittle intermetallic phases. Fe is found naturally as an impurity in bauxite ore, resulting in Fe contamination of aluminum alloys with increasing contamination from current recycling practices. The Al–Ce–Fe system was investigated using CALPHAD (CALculation of PHAse Diagrams) modeling and experimental casting techniques. It was found that additions of Fe to the Al–Ce system are beneficial to the strength (slightly) and ductility (significantly) of the ternary alloys, which is attributed to the formation of fine metastable Al 8 CeFe 2 phase with aggregate morphology and equilibrium Al 10 CeFe 2 phase, suppressing coarse proeutectic Al 11 Ce 3 phase in near-eutectic Al–Ce alloys. Heat treatment study showed that the metastable Al 8 CeFe 2 phase transforms to predicted equilibrium Al 10 CeFe 2 phase at 500 °C, with essentially no intermetallic or grain coarsening; thus, the alloy displayed excellent property retention. The Al–Ce–Fe alloy system offers opportunities for sustainable, recyclable alloy development using low-cost Fe and low-cost cerium (a byproduct of rare-earth extraction).

42 ENGINEERING↗
DOE OSTI2026

Terrestrial Gamma‐Ray Flash Following Intense Negative Return Stroke Observed With BIMAP‐3D

We report ground-based observations of a terrestrial gamma-ray flash (TGF) associated with a strong negative cloud-to-ground lightning strike (-CG) which occurred near Los Alamos National Laboratory (LANL) in New Mexico, USA. Gamma photons were detected by the Terrestrial High-energy Observations of Radiation (THOR) instrument, developed at the University of California, Santa Cruz, which has been hosted at LANL since 2022. Simultaneous measurements were also made with the 3-Dimensional Broadband Interferometric Mapping and Polarization (BIMAP-3D) system, which includes 3D lightning mapping, two fast antennas, and an additional plastic scintillator. Additional field change waveforms were obtained from the Earth Networks Total Lightning Network (ENTLN). The lightning initiated about 1 km above the ground, leading to a powerful -CG with an ENTLN peak current of −237 kA and bipolar field change matching the recently described “energetic compact stroke” (ECS) shape. The TGF was then observed ∼35 µs after the start of the return stroke. We also observe an electric field pulse likely produced by the TGF either in isolation or by coupling to the lightning channel. Based on modeling of the radiated electric field and photon propagation through the atmosphere we infer that the TGF source was on the order of 1⁢0 17 photons. This TGF and associated lightning are extremely similar to some recently reported ECS TGFs in coastal Japan in winter, but we report the first observation of this phenomenon outside of Japan in a different climate, terrain, and season.

58 GEOSCIENCES↗
DOE OSTI2023

Global monthly sectoral water use for 2010–2100 at 0.5° resolution across alternative futures

Water usage is closely linked with societal goals that are both local and global in scale, such as sustainable development and economic growth. It is therefore of value, particularly for long-term planning, to understand how future sectoral water usage could evolve on a global scale at fine resolution. Additionally, future water usage could be strongly shaped by global forces, such as socioeconomic and climate change, and the multi-sector dynamic interactions those forces create. We generate a novel global gridded monthly sectoral water withdrawal and consumption dataset at 0.5° resolution for 2010–2100 for a diverse range of 75 scenarios. The scenarios are harmonized with the five Shared Socioeconomic Pathways (SSPs) and four Representative Concentration Pathways (RCPs) scenarios to support its usage in studies evaluating the implications of uncertain human and earth system change for future global and regional dynamics. To generate the data, we couple the Global Change Analysis Model (GCAM) with a land use spatial downscaling model (Demeter), a global hydrologic framework (Xanthos), and a water withdrawal downscaling model (Tethys).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Ensuring statistical reproducibility of ocean model simulations in the age of hybrid computing

Novel high performance computing systems that feature hybrid architectures require large scale code refactoring to unravel underlying exploitable parallelism. Such redesign can often be accompanied with machine-precision changes as the order of computation cannot always be maintained. For chaotic systems like climate models, these round-off level differences can grow rapidly. Systematic errors may also manifest initially as machine-precision differences. Isolating genuine round off level differences from such errors remains a challenge. Here, we apply two-sample equality of distribution tests to evaluate statistical reproducibility of the ocean model component of US Department of Energy's Energy Exascale Earth System Model (E3SM). A 2-year control simulation ensemble is compared to a modified ensemble as a test case - after a known non-bit-for-bit change in a model component is introduced - to evaluate the null hypothesis that the two ensembles are statistically indistinguishable. To quantify the false negative rates of these tests, we conduct a formal power analysis using a targeted suite of short simulation ensembles. The ensemble suite contains several perturbed ensembles, each with a progressively different climate than the baseline ensemble - obtained by perturbing the magnitude of a single model tuning parameter, the Gent and McWilliams κ, in a controlled manner. The null hypothesis is evaluated for each of perturbed ensembles using these tests. The power analysis informs on the detection limits of the tests for given ensemble size allowing model developers to evaluate the impact of an introduced non-bit-for-bit change to the model.

Mahajan, Salil↗
DOE OSTI2026

Research Development and Partnership Pilot (RDPP): Developing plans and partnerships for incorporating tree reproduction to understand Earth system change

The goals for this Research Development and Partnership Pilot (RDPP) proposal were to i) learn about Department of Energy (DOE) research and use the PI’s expertise on patterns and environmental drivers of tree reproduction as a basis to make connections with individuals and research groups at DOE National Laboratories, and ii) to develop plans and form partnerships that will both enhance the PI’s research. The objectives of the proj ect were for the PI to i) participate in the Department of Energy's Office of Science program in Biological and Environmental Research training and outreach activities, ii) conduct directed fact-finding on Earth and Environmental Systems Sciences Division (EESSD) research projects and new partnerships with individuals and groups at National Laboratories, ii) conduct meetings with potential collaborators at National Laboratories to discuss EESSD-relevant research ideas, and iv) to develop a plan for future research efforts. During the period of the award, the objectives of the proposal were met, as the PI attended Environmental System Sciences meetings, American Geophysical Union meetings, SPRUCE experiment meetings, and visited the Oak Ridge National Lab. These activities led to increased understanding of the research being conducted by DOE scientists and the PI had meetings with potential collaborators to develop future research plans that leverage expertise at DOE and the research interests of the PI to increase understanding of the role of tree reproduction in future carbon allocation and in tree regeneration models in boreal ecosystems.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Seasonal forecasting skill for the High Mountain Asia region in the Goddard Earth Observing System

Seasonal variability of the global hydrologic cycle directly impacts human activities, including hazard assessment and mitigation, agricultural decisions, and water resources management. This is particularly true across the High Mountain Asia (HMA) region, where availability of water resources can change depending on local seasonality of the hydrologic cycle. Forecasting the atmospheric states and surface conditions, including hydrometeorologically relevant variables, at subseasonal-to-seasonal (S2S) lead times of weeks to months is an area of active research and development. NASA's Goddard Earth Observing System (GEOS) S2S prediction system has been developed with this research goal in mind. Here, we benchmark the forecast skill of GEOS-S2S (version 2) hydrometeorological forecasts at 1–3-month lead times in the HMA region, including a portion of the Indian subcontinent, during the retrospective forecast period, 1981–2016. To assess forecast skill, we evaluate 2 m air temperature, total precipitation, fractional snow cover, snow water equivalent, surface soil moisture, and terrestrial water storage forecasts against the Modern-Era Retrospective analysis for Research and Applications, Version 2 (MERRA-2) and independent reanalysis data, satellite observations, and data fusion products. Anomaly correlation is highest when the forecasts are evaluated against MERRA-2 and particularly in variables with long memory in the climate system, likely due to the similar initial conditions and model architecture used in GEOS-S2S and MERRA-2. When compared to MERRA-2, results for the 1-month forecast skill range from an anomaly correlation of R anom =0.18 for precipitation to R anom =0.62 for soil moisture. Anomaly correlations are consistently lower when forecasts are evaluated against independent observations; results for the 1-month forecast skill range from R anom =0.13 for snow water equivalent to R anom =0.24 for fractional snow cover. We find that, generally, hydrometeorological forecast skill is dependent on the forecast lead time, the memory of the variable within the physical system, and the validation dataset used. Overall, these results benchmark the GEOS-S2S system's ability to forecast HMA hydrometeorology.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) (Field Campaign Report)

The Arctic is rapidly changing, and these changes have substantial societal relevance. First, arctic change is a leading sign of global change, as the warming observed in the Arctic is 2-3 times faster than observed across the rest of the globe. This so-called arctic amplification is due to numerous feedbacks, including those linked to the declining sea ice. Broad arctic changes are also hypothesized to be related to shifts in large-scale circulation patterns that may have implications for mid-latitude weather and ocean circulation. Arctic change is further affecting the oceans through acidification that threatens food supplies. Declining sea ice also opens the Arctic for new resource development, shipping routes, tourism, and other commercial activities. Lastly, the changing Arctic is a hotbed for geopolitical challenges as nations vie for influence and control of this resource-rich and newly accessible region. Clearly the Arctic and its changes are playing a huge role in our Earth both from a geophysical and socio-political standpoint. To navigate, manage, and respond to the challenges associated with arctic change requires a vastly improved understanding of the coupled arctic system, and the drivers and implications of these changes. It is essential to better understand the physical basis for why the arctic sea ice is declining, the associated feedbacks that work to amplify or modulate this decline, and the myriad ways that the Earth system is responding. As a result of these changes and uncertainties, there are increasing societal needs for improved model predictive skill in the Arctic, to address pressing gaps in global climate prediction, to advance forecast skills for regional and hemispheric weather and sea ice, and to ensure robust ecosystem models that realistically link physical and biological systems. To fulfill these core needs requires new, sophisticated, and cross-cutting observations within the rapidly changing arctic ice pack.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

EQSIM—A multidisciplinary framework for fault-to-structure earthquake simulations on exascale computers part I: Computational models and workflow

Computational simulations have become central to the seismic analysis and design of major infrastructure over the past several decades. Most major structures are now “proof tested” virtually through representative simulations of earthquake-induced response. More recently, with the advancement of high-performance computing (HPC) platforms and the associated massively parallel computational ecosystems, simulation is beginning to play a role in increased understanding and prediction of ground motions for earthquake hazard assessments. However, the computational requirements for regional-scale geophysics-based ground motion simulations are extreme, which has restricted the frequency resolution of direct simulations and limited the ability to perform the large number of simulations required to numerically explore the problem parametric space. In this article, recent developments toward an integrated, multidisciplinary earth science-engineering computational framework for the regional-scale simulation of both ground motions and resulting structural response are described with a particular emphasis on advancing simulations to frequencies relevant to engineered systems. This multidisciplinary computational development is being carried out as part of the US Department of Energy (DOE) Exascale Computing Project with the goal of achieving a computational framework poised to exploit emerging DOE exaflop computer platforms scheduled for the 2022–2023 timeframe.

58 GEOSCIENCES↗
DOE OSTI2025

Direct measurement of reduced exchange stiffness and its impact on magnetic vortex behavior in PyGd alloys

Thin films composed of sputtered transition metal/rare earth (TM/RE) ferrimagnets have emerged as promising building blocks for future spintronic devices, offering tunable magnetic properties critical for data storage, memory, and logic applications. However, understanding how the combination of TM and RE elements influences effective magnetic properties, such as exchange stiffness (Aex), remains challenging. Magnetic vortices provide a versatile tool for probing these properties in thin film systems. By combining magnetic imaging via soft x-ray microscopy and micromagnetic modeling, we quantify the effective exchange stiffness in PyGd ferrimagnetic disks with varying Gd concentrations. Our results indicate a reduction in Aex to below 3 pJ/m for a 20% Gd concentration when compared to reference Py, and values below 2 pJ/m for 30% Gd, reflecting weak Ni–Gd exchange coupling. These findings highlight the critical role of rare earth content in tuning the exchange stiffness. The reduced exchange stiffness facilitates a linear field response of the magnetization up to the edge of the disk, as well as significant deformations in the vortex core itself when compared to films with larger Aex. Our results are in line with, albeit lower than, recent measurements of the exchange stiffness in intermixed PyGd. This reduced exchange stiffness has implications for the development of spintronic devices based on ferrimagnetic skyrmions.

Jacob, Liyan↗
DOE OSTI2022

Mitigating the Impacts of Uncertain Geomagnetic Disturbances on Electric Grids: A Distributionally Robust Optimization Approach

Severe geomagnetic disturbances (GMDs) increase the magnitude of the electric field on the Earth’s surface (E-field) and drive geomagnetically-induced currents (GICs) along the transmission lines in electric grids. These additional currents can pose severe risks, such as current distortions, transformer saturation and increased reactive power losses, each of which can lead to system unreliability. Today several mitigation actions (e.g., changing grid topology) exist that can reduce the harmful GIC effects on the grids. Making such decisions can be challenging, however, because the magnitude and direction of the E-field are uncertain and non-stationary. In this paper, we model uncertain E-fields using the distributionally robust optimization (DRO) approach that determines optimal transmission grid operations such that the worst-case expectation of the system cost is minimized. We also capture the effect of GICs on the nonlinear AC power flow equations. For solution approaches, we develop an accelerated column-and-constraint generation (CCG) algorithm by exploiting a special structure of the support set of uncertain parameters representing the E-field. Extensive numerical experiments based on “epri-21” and “uiuc-150” systems, designed for GMD studies, demonstrate (i) the computational performance of the accelerated CCG algorithm, (ii) the superior performance of distributionally robust grid operations that satisfy nonlinear, nonconvex AC power flow equations and GIC constraints, in comparison with standard stochastic programming-based methods during the out-of-sample testing.

42 ENGINEERING↗
DOE OSTI2022

Satellite Enveloped with STITCHED Engineering Sensors for Detection of Approaching Objects

Today as well as tomorrows spaceborne assets impact almost all areas of national and nuclear security. Spaceborne assets can not only collect and disseminate valuable data, well beyond just the visual, but also track terrestrial-based mobile assets in real-time, and active spaceborne platforms potentially pose serious risk to vulnerable earth-based systems and infrastructures. The capability to defend national spaceborne assets from attack/interference is critical for security interests. This effort supports this mission through the cost-effective preeminent detection of approaching threats to our nation’s vital resources, in order to help secure and trust these high-value assets against the threats of tomorrow. This project develops novel fabrication techniques for conformal, low-profile and lightweight leakywave antenna (LWA) detection/imaging systems, which fuses technical embroidery (TE) and laser ablation (LA) processes with LWA design. Technical embroidery is an emerging field in additive textile manufacturing where flexible materials and functionalized fabrics are created for a wide variety of uses and purposes, while laser ablation is the process of removing material from a solid surface by irradiating it with a laser beam. Here, thin, conformal antenna designs are designed, modeled and fabricated using both TE and LA, to create lightweight, flexible and conformal object detection and imaging radars. This novel development ensures our nation’s ability to field advanced lightweight and conformal technologies to protect spaceborne assets.

42 ENGINEERING↗
DOE OSTI2025

Demography, dynamics and data: building confidence for simulating changes in the world's forests

Vegetation demographic models (VDMs) are advanced tools for simulating forest responses to climate and land-use changes, and are essential for projecting carbon cycling and large-scale forest management strategies. Despite their increasing incorporation into Earth System Models, VDMs differ in their demographic assumptions, with no prior quantitative comparison of their performance. We benchmarked nine VDMs against observational data from boreal, temperate and tropical sites, assessing their accuracy in predicting tree growth, carbon turnover, biomass stocks and size distributions. Models were simulated under consistent climate conditions with postdisturbance recovery monitored for at least 420 yr. Postdisturbance carbon recovery trajectories showed significant variability while remaining within observational ranges. Initial regrowth rates varied substantially (0.03-0.60, 0.18-0.70 and 0.35-1.10 kgCm-2 yr-1 for boreal, temperate and tropical sites, respectively), influenced by each model's initial forest state. Models captured mature forest carbon content but showed compensating effects between overestimated growth and underestimated mortality rates. This first multi-model benchmarking identifies growth and mortality rates as critical calibration targets and highlights the need to refine postdisturbance establishment conditions for model development. We outline specific benchmarking variables needed to improve predictions of forest responses to environmental change.

demographic vegetation model benchmarking↗
DOE OSTI2022

Spatial patterns of snow distribution in the sub-Arctic

Abstract. The spatial distribution of snow plays a vital role in sub-Arctic and Arctic climate, hydrology, and ecology due to its fundamental influence on the water balance, thermal regimes, vegetation, and carbon flux. However, the spatial distribution of snow is not well understood, and therefore, it is not well modeled, which can lead to substantial uncertainties in snow cover representations. To capture key hydro-ecological controls on snow spatial distribution, we carried out intensive field studies over multiple years for two small (2017–2019; ∼ 2.5 km2) sub-Arctic study sites located on the Seward Peninsula of Alaska. Using an intensive suite of field observations (> 22 000 data points), we developed simple models of the spatial distribution of snow water equivalent (SWE) using factors such as topographic characteristics, vegetation characteristics based on greenness (normalized different vegetation index, NDVI), and a simple metric for approximating winds. The most successful model was random forest, using both study sites and all years, which was able to accurately capture the complexity and variability of snow characteristics across the sites. Approximately 86 % of the SWE distribution could be accounted for, on average, by the random forest model at the study sites. Factors that impacted year-to-year snow distribution included NDVI, elevation, and a metric to represent coarse microtopography (topographic position index, TPI), while slope, wind, and fine microtopography factors were less important. The characterization of the SWE spatial distribution patterns will be used to validate and improve snow distribution modeling in the Department of Energy's Earth system model and for improved understanding of hydrology, topography, and vegetation dynamics in the sub-Arctic and Arctic regions of the globe.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

X-ray absorption spectroscopy of lanmodulin-derived peptides bound to rare earth elements

A sustainable and robust supply chain of rare earth elements (REEs) is necessary to meet our consumer, national security and clean energy goals. However, current intra-REE separation technologies (e.g. solvent extraction) are costly and carry a heavy environmental burden. Therefore, the development of new aqueous based ligands that are selective for individual REEs will be integral in future REE production systems. To develop these ligands, an understanding of how ligand coordination structure relates to selectivity is imperative. We used X-ray absorption spectroscopy (XAS) to observe the local structure around four lanthanide (Ln) ions (La, Ce, Pr and Nd) complexed by water and several relevant chelating ligands [lanmodulin EF-hand 1 peptides (LanM1), ethyl­enedi­amine­tetra­acetic acid (EDTA), amino­tris­(methyl­ene­phospho­nic acid) (ATMP) and citric acid]. To collect these liquid-phase XAS spectra, we developed a new flow cell that prevents bubble interference and beam damage to the samples. In the X-ray absorption near-edge structure (XANES), we observed energy shifts in the white line, white line broadening and differences in the white line intensity of different Ln–ligand complexes between ligands. In the extended X-ray absorption fine structure (EXAFS), we distinguished differences in peak intensity and distance between coordinating ligands. Differences in the local coordination structure between Ln–LanM1 peptide complexes were more subtle compared with the other ligands (La–water, La–EDTA, La–ATMP and La–citric acid complexes). Further XANES and EXAFS studies, in combination with modelling and other techniques, could greatly improve our structural knowledge of how these aqueous ligands bind Ln ions and how they can be used to design more selective ligands for more efficient and sustainable REE separations.

EDTA↗
DOE OSTI2025

A unified ensemble soil moisture dataset across the continental United States

Abstract A unified ensemble soil moisture (SM) package has been developed over the Continental United States (CONUS). The data package includes 19 products from land surface models, remote sensing, reanalysis, and machine learning models. All datasets are unified to a 0.25-degree and monthly spatiotemporal resolution, providing a comprehensive view of surface SM dynamics. The statistical analysis of the datasets leverages the Koppen-Geiger Climate Classification to explore surface SM’s spatiotemporal variabilities. The extracted SM characteristics highlight distinct patterns, with the western CONUS showing larger coefficient of variation values and the eastern CONUS exhibiting higher SM values. Remote sensing datasets tend to be drier, while reanalysis products present wetter conditions. In-situ SM observations serve as the basis for wavelet power spectrum analyses to explain discrepancies in temporal scales across datasets facilitating daily SM records. This study provides a comprehensive soil moisture data package and an analysis framework that can be used for Earth system model evaluations and uncertainty quantification, quantifying drought impacts and land–atmosphere interactions and making recommendations for drought response planning.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Reservoir Sediment Management and Monitoring Database

Overview This dataset compiles dam sediment management and monitoring information from surveys, case studies, and journal articles. Additionally, features described by the National Inventory of Dams (i.e., presence of sluice gates) are included to indicate known infrastructure features that may address sediment releases. The location and description of records from downstream monitoring gages are catalogued in order to help with tracking conditions over time (e.g., before and after management actions, as operations change, etc.). The data help address national scale understanding of challenges and solutions related to the accumulation of sediment behind a dam as well as downstream passage. Sediment trapping causes problems as it reduces storage capacity, disrupts dam and reservoir function, impedes access for recreation, alters water quality/habitat conditions, and contributes to riverbank and coastal erosion within the reservoir. Data compilation from a variety of sources is a first step towards assessing system-wide efficacy of management solutions. This dataset was developed under the Water Power Technologies Office funded effort which began as a Seedling on Reservoir Sedimentation Data, and was supported by the Reservoir Sedimentation Modeling Framework and Data Analysis project. These projects have addressed challenges in describing sediment transport, trapping, and management at dams throughout the US. Methodology An outer join on dams/reservoirs with surveys and survey reports (documented in the RESSED database, USBR or USACE databases, project websites, etc.) with the National Inventory of Dams, based on the NIDID to determine dams with documented management and/or sluice gates. Additional dams with documented management activity were identified through review of technical articles from the past 25 years in Journal of Hydrology, Journal of Water Resources Planning and Management, Geomorphology, Journal of Hydraulic Engineering, Water, Journal of Cleaner Production, International Journal of Sediment Research, Nature Scientific Reports, Earth Surface Processes and Landforms, and Environmental Science and Pollution Research. Individual records were created for each survey or management activity documented. To evaluate downstream sediment monitoring records, the nhdPlusTools and dataRetrieval packages in R were used to find gages within 10km of each dam in the management database. Length of record and location of matched gages were retrieved for those parameters relevant to sediment concentration or total sediment discharge.

Hansen, Carly [ORNL] (ORCID:0000000193280838)↗