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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 343 records · Page 19
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Fractured Earth Laboratory

Researchers at Los Alamos apply extensive knowledge and expertise through the Los Alamos Fractured Earth Laboratory to measure elusive rock fracture, chemical, cementing, and flow properties with purposebuilt systems that apply new and emerging measurement approaches. Unlike traditional rock mechanics laboratories, this unique laboratory capability allows researchers to accurately measure and observe fracture growth and transient flow in rock samples with microtomography at subsurface conditions. This provides critical information to solve complex and challenging subsurface fracture and flow process problems. Los Alamos is seeking to offer the Fractured Earth Laboratory’s measurement capabilities and expertise to researchers and developers in the oil and gas; geothermal; and the carbon capture, sequestration, and utilization industries. By utilizing the Fractured Earth Laboratory’s capabilities, researchers in these industries will have access to tools diagnose problems and develop solutions to subsurface issues.

58 GEOSCIENCES↗
DOE OSTI2021

Hidden Processes During Seasonal Isolation of a High-Altitude Watershed

Biogeochemical processes capable of altering global carbon systems occur frequently in Earth’s Critical Zone–the area spanning from vegetation canopy to saturated bedrock–yet many of these phenomena are difficult to detect. Observation of these processes is limited by the seasonal inaccessibility of remote ecosystems, such as those in mountainous, snow- and ice-dominated areas. This isolation leads to a distinct gap in biogeochemical knowledge that ultimately affects the accuracy and confidence with which these ecosystems can be computationally modeled for the purpose of projecting change under different climate scenarios. To examine a high-altitude, headwater ecosystem’s role in methanogenesis, sulfate reduction, and groundwater-surface water exchange, water samples were continuously collected from the river and hyporheic zones (HZ) during winter isolation in the East River (ER), CO watershed. Measurements of continuously collected ER surface water revealed up to 50 μM levels of dissolved methane in July through September, while samples from 12 cm deep in the hyporheic zone at the same location showed a spring to early summer peak in methane with a strong biogenic signature (<65 μM, δ13C-CH4, -60.76‰) before declining. Continuously collected δ 18 O-H 2 O and δ 2 H-H 2 O isotopes from the water column exhibited similar patterns to discrete measurements, while samples 12 cm deep in the hyporheic zone experienced distinct fluctuations in δ 18 O-H 2 O, alluding to significant groundwater interactions. Continuously collected microbial communities in the river in the late fall and early winter revealed diverse populations that reflect the taxonomic composition of ecologically similar river systems, including taxa indicative of methane cycling in this system. These measurements captured several biogeochemical components of the high-altitude watershed in response to seasonality, strengthening our understanding of these systems during the winter months.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Vertically Resolved Analysis of the Madden-Julian Oscillation Highlights the Role of Convective Transport of Moist Static Energy

We simulate the Madden-Julian oscillation (MJO) over an aquaplanet with uniform surface temperature using the multiscale modeling framework (MMF) configuration of the Energy Exascale Earth System Model (E3SM-MMF). The model produces MJO-like features that have a similar spatial structure and propagation behavior to the observed MJO. To explore the processes involved in the propagation and maintenance of these MJO-like features, we perform a vertically resolved moist static energy (MSE) analysis for the MJO (Yao et al., 2022, https://doi.org/10.1175/jas-d-20-0254.1). Unlike the column-integrated MSE analysis, our method emphasizes the local production of MSE variance and quantifies how individual physical processes amplify and propagate the MJO's characteristic vertical structure. We find that radiation, convection, and boundary layer (BL) processes all contribute to maintaining the MJO, balanced by the large-scale MSE transport. Furthermore, large-scale dynamics, convection, and BL processes all contribute to the propagation of the MJO, while radiation slows the propagation. Additionally, we perform mechanism-denial experiments to examine the role of radiation and associated feedbacks in simulating the MJO. We find that the MJO can still self-emerge and maintain its characteristic structures without radiative feedbacks. This study highlights the role of convective MSE transport in the MJO dynamics, which was overlooked in the column-integrated MSE analysis.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Climate Intervention Assessment and Attribution

Focal Area(s): To ensure the US is positioned to scientifically attribute noncooperative climate interventions, we propose developing a foundational analytical framework for increased confidence in the assessment and attribution of observed changes in the climate. This framework will enable probabilistic attribution of prospective climate interventions. The target is to glean insight from complex Earth system data (Focal Area 3) by using AI to develop a prediction system comprised of a hierarchy of models (Focal Area 2).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Machine-Learning-Assisted Hybrid Earth System Modelling

We propose a novel hybrid modeling approach that combines a physics-based, numerical model of the Earth system with a machine learning model. We also envision to integrate the hybrid model training with a data assimilation cycle, so that new observations update both the state estimate used as initial conditions and the machine learning model parameters.

58 GEOSCIENCES↗
DOE OSTI2021

Southern Ocean latitudinal gradients of cloud condensation nuclei

Abstract. The Southern Ocean region is one of the most pristine in the world and serves as an important proxy for the pre-industrial atmosphere. Improving our understanding of the natural processes in this region is likely to result in the largest reductions in the uncertainty of climate and earth system models. While remoteness from anthropogenic and continental sources is responsible for its clean atmosphere, this also results in the dearth of atmospheric observations in the region. Here we present a statistical summary of the latitudinal gradient of aerosol (condensation nuclei larger than 10 nm, CN10) and cloud condensation nuclei (CCN at various supersaturations) concentrations obtained from five voyages spanning the Southern Ocean between Australia and Antarctica from late spring to early autumn (October to March) of the 2017/18 austral seasons. Three main regions of influence were identified: the northern sector (40–45∘ S), where continental and anthropogenic sources coexisted with background marine aerosol populations; the mid-latitude sector (45–65∘ S), where the aerosol populations reflected a mixture of biogenic and sea-salt aerosol; and the southern sector (65–70∘ S), south of the atmospheric polar front, where sea-salt aerosol concentrations were greatly reduced and aerosol populations were primarily biologically derived sulfur species with a significant history in the Antarctic free troposphere. The northern sector showed the highest number concentrations with median (25th to 75th percentiles) CN10 and CCN0.5 concentrations of 681 (388–839) cm−3 and 322 (105–443) cm−3, respectively. Concentrations in the mid-latitudes were typically around 350 cm−3 and 160 cm−3 for CN10 and CCN0.5, respectively. In the southern sector, concentrations rose markedly, reaching 447 (298–446) cm−3 and 232 (186–271) cm−3 for CN10 and CCN0.5, respectively. The aerosol composition in this sector was marked by a distinct drop in sea salt and increase in both sulfate fraction and absolute concentrations, resulting in a substantially higher CCN0.5/CN10 activation ratio of 0.8 compared to around 0.4 for mid-latitudes. Long-term measurements at land-based research stations surrounding the Southern Ocean were found to be good representations at their respective latitudes; however this study highlighted the need for more long-term measurements in the region. CCN observations at Cape Grim (40∘39′ S) corresponded with CCN measurements from northern and mid-latitude sectors, while CN10 observations only corresponded with observations from the northern sector. Measurements from a simultaneous 2-year campaign at Macquarie Island (54∘30′ S) were found to represent all aerosol species well. The southernmost latitudes differed significantly from both of these stations, and previous work suggests that Antarctic stations on the East Antarctic coastline do not represent the East Antarctic sea-ice latitudes well. Further measurements are needed to capture the long-term, seasonal and longitudinal variability in aerosol processes across the Southern Ocean.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

DisasterAWARE – A Global Alerting Platform for Flood Events

The rising number of flooding events combined with increased urbanization is contributing to significant economic losses due to damages to structures and infrastructures. From a risk reduction and resilience perspective, it is not only essential to forecast flood risk and potential impacts, but also to disseminate the information to stakeholders on the ground for rapid implementation of mitigation and response measures. This paper provides (i) an introduction to DisasterAWARE®, a global alerting system, that is used to disseminate flood risk information to stakeholders across the globe, and (ii) a discussion of the models implemented using earth observation data (Synthetic Aperture Radar and optical imagery) for near real-time assessment of flood severity and potential flood impacts to infrastructures. While the models are still in their nascent stage, a case study implementation of the models for the 2020 flooding event in Africa is presented to showcase the model integration with DisasterAWARE®.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

A Planetary Defense System For Responsive Space Missions

As King et al succinctly write, “Collision between the Earth and small objects in the solar system are known to occur regularly, and can result in extinction-level events at their most energetic or more commonly widespread loss of life or economic destruction even for relatively low-energy impacts.” Currently, the JPL Sentry System and the NASA NEO Surveyor mission track, identify, and monitor potential asteroid threats. The JPL Sentry System4 is an automated collision monitoring system which scans the current asteroid catalog for potential impact trajectories with Earth. A 2017 study led by P. Tricarico titled “The near-Earth asteroid population from two decades of observations” analyzes the combined observations of nine leading asteroid surveys. The NASA NEO Surveyor mission seeks to identify 90% of near-Earth objects (NEO) with diameters greater than 140 meters (460 feet) within 10 years. The NEO Surveyor combines data from two infrared imaging detectors to measure NEO size, composition, shape, rotational state, and orbits. Recently, the NASA Double Asteroid Redirection Test (DART) mission successfully altered the orbit of asteroid moon Dimorphos in 2022. This demonstrated that orbit alteration is possible. Thus, collisions between the Earth and asteroids are both likely and demonstrate potential for great harm. There is ongoing work to identify, catalog, and track potential threats. However, when a threat is identified there is not yet a system in place to target the threatening asteroid and defend the planet from potentially existential threats. Building on the DART Mission, we explore a planetary defense system to mitigate asteroid threats.

42 ENGINEERING↗
DOE OSTI2022

Large–scale asymmetry in galaxy spin directions: Analysis of galaxies with spectra in DES, SDSS, and DESI Legacy Survey

Multiple previous studies using several different probes have shown considerable evidence for the existence of cosmological–scale anisotropy and a Hubble–scale axis. One of the probes that show such evidence is the distribution of the directions toward which galaxies spin. The advantage of the analysis of the distribution of galaxy spin directions compared to the cosmic microwave background anisotropy is that the ratio of galaxy spin directions is a relative measurement, and therefore less sensitive to background contamination such as Milky Way obstruction. Another advantage is that many spiral galaxies have spectra, and therefore allow to analyze the location of such axis relative to Earth. This paper shows an analysis of the distribution of the spin directions of over 90K galaxies with spectra. That analysis is also compared to previous analyses using the Earth–based Sloan Digital Sky Survey, Panoramic Survey Telescope and Rapid Response System, and Dark Energy Spectroscopic Instrument Legacy Survey, as well as space–based data collected by Hubble Space Telescope. Finally, the results show very good agreement between the distribution patterns observed with the different telescopes. The dipole or quadrupole axes formed by the spin directions of the galaxies with spectra do not necessarily go directly through Earth.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Correction and calibration of atmospheric impact observations in GOES GLM data

The Earth's atmosphere is impacted daily by both meteoroids and artificial objects. Calibrated observations of the emitted light at sufficiently high sampling rates can enable or improve the estimation of impactor attributes such as size, cohesion, trajectory, and composition, but are difficult to obtain owing to the unpredictability, brevity, and high dynamic (brightness) range of impacts. Ground-based camera systems have successfully monitored small regions of the atmosphere at video frame rates and with limited radiometric capabilities, but most impacts occur over the 70% of the Earth's surface covered by water and are therefore missed by these networks. The Geostationary Lightning Mapper (GLM) instruments aboard Geostationary Operational Environmental Satellites 16 and 17 provide near-hemispherical coverage at 500 frames per second. These data have been shown to contain the signatures of many independently confirmed impacts, often from both viewing angles simultaneously, and constitute an observational resource that is currently unparalleled in the public domain. NASA's Asteroid Threat Assessment Project has implemented an automated impact detection pipeline that processes data from GLM daily. Given a detected impact, the GLM data contain a wealth of information for use in quantitative follow-up analyses. However, impact events differ from lightning in ways that violate key assumptions built into GLM's design. The result is that GLM's onboard processing introduces errors into pixel observations of impact events and the calibrated energies near the periphery of the detector may be substantially overestimated. We present methods for mitigating these and other issues to produce a data product more suitable for impact analyses than the existing GLM lightning product.

58 GEOSCIENCES↗
DOE OSTI2021

Evaluation of precipitation indices in suites of dynamically and statistically downscaled regional climate models over Florida

Abstract The present work evaluates historical precipitation and its indices defined by the Expert Team on Climate Change Detection and Indices (ETCCDI) in suites of dynamically and statistically downscaled regional climate models (RCMs) against NOAA’s Global Historical Climatology Network Daily (GHCN-Daily) dataset over Florida. The models examined here are: (1) nested RCMs involved in the North American CORDEX (NA-CORDEX) program, (2) variable resolution Community Earth System Models (VR-CESM), (3) Coupled Model Intercomparison Project phase 5 (CMIP5) models statistically downscaled using localized constructed analogs (LOCA) technique. To quantify observational uncertainty, three in situ-based (PRISM, Livneh, CPC) and three reanalysis (ERA5, MERRA2, NARR) datasets are also evaluated against the station data. The reanalyses and dynamically downscaled RCMs generally underestimate the magnitude of the monthly precipitation and the frequency of the extreme rainfall in summer. The models forced with CanESM2 miss the phase of the seasonality of extreme precipitation. All models and reanalyses severely underestimate both the mean and interannual variability of mean wet-day precipitation (SDII), consecutive dry days (CDD), and overestimate consecutive wet days (CWD). Metric analysis suggests large uncertainty across NA-CORDEX models. Both the LOCA and VR-CESM models perform better than the majority of models. Overall, RegCM4 and WRF models perform poorer than the median model performance. The performance uncertainty across models is comparable to that in the reanalyses. Specifically, NARR performs poorer than the median model performance in simulating the mean indices and MERRA2 performs worse than the majority of models in capturing the interannual variability of the indices.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Ecological Insights from Transferable Plant Biomass Mapping across the Arctic using High-resolution Structure-from-Motion and LiDAR Data

Warmer temperatures, permafrost thaw, and increased wildfire activity are driving rapid ecological change across the Arctic, significantly altering plant productivity and aboveground biomass (AGB). These rapid changes highlight the urgent need to improve monitoring of vegetation dynamics in the Earth’s northern ecosystems, where high spatiotemporal heterogeneity occurs at scales finer than those captured by traditional satellite observations. The growing use of Unoccupied Aerial Systems (UASs) presents an opportunity to overcome this limitation. Yet, the diversity of UAS platforms, sensors, and data collection and processing workflows presents challenges for developing standardized, generalizable approaches. To address this challenge, we compiled 672 AGB plots co-located with 183 UAS-based Structure-from-Motion (SfM) or Light Detection and Ranging (LiDAR) surveys collected across the Arctic. Here, we: (1) evaluated the generalizability of UAS-derived canopy structure derived from high-resolution SfM and LiDAR for estimating AGB, (2) assessed scaling errors and their sources in two recent satellite-based AGB products derived from Landsat and MODIS, and (3) demonstrated the use of high-resolution AGB maps to quantify biomass variation across tundra plant functional types (PFTs) and to monitor post-fire recovery. Our results show that both SfM and LiDAR accurately captured AGB and its variability across tundra PFTs using a Random Forest (RF) model (overall RMSE: 0.336 kg/m2), with mapping performance varying slightly by region and data source. Using UAS-derived AGB maps as a benchmark, we identified systematic biases in satellite-derived AGB products, largely attributable to the magnitude of AGB and structural heterogeneity within coarse-resolution pixels. Applying our model to repeat UAS surveys following a tundra fire on Seward Peninsula, we observed rapid AGB recovery in non-shrub patches, with biomass recovering to pre-fire levels within 2 years. In contrast, shrub patches recovered more slowly, with AGB gains continuing over 2–4 years through both in-patch growth and lateral expansion (via dispersal) into remaining burned areas. Overall, these findings demonstrate the generalizability of UAS-based SfM and LiDAR data for estimating tundra AGB and highlight the potential of our approach to be broadly applied to generate high-quality AGB data for ecological monitoring and model benchmarking across the Arctic.

Yang, Daryl [ORNL] (ORCID:0000000317057823)↗
DOE OSTI2022

Magnetic interactions of 4 f electrons in the topological insulator chalcogenide Bi 2 Se 3

Here, the gap opening mechanism of a topological insulator, the quantum anomalous Hall effect and the axion physics are still pressing open questions and a microscopic viewpoint to further understand the role of magnetism in topology is highly desirable. In this work we have performed a micro scopic investigation, by means of electron spin resonance (ESR) along with complementary bulk measurements, on the chalcogenide (Bi 1-x Gd x ) 2 Se 3 (x = 0, 0.001, 0.002 and 0.006). Our analysis of the Gd 3+ spin dynamics reveal no significant change of the Fermi surface as a function of Gd 3+ concentration, which indicates that the 4f magnetism is different from the non-local effects induced by transition metals (d electrons) substitutions. Additionally, we observe an unusual evolution of the Gd 3+ ESR spectra as a function of the applied magnetic field, which we discuss considering the magnetic interaction between Gd 3+ 4f electrons and impurity centers such as Se vacancies. This interaction would give rise to a local weak antilocalization effect surrounding the Gd 3+ ions. Such mechanism is observable due to particular details of the Gd 3+ 4f electrons magnetism in this system compared to d electrons. Our work points out that rare earth substitutions in this model topological insulator is a promising path to explore the axion insulating systems.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2021

Combining artificial intelligence, Earth observations, and climate models to improve predictability of ice-biogeochemistry interactions

Focal Area: Predictive Modeling. We describe how artificial intelligence (AI) can be combined with state-of-the-science Earth system models to better predict future regional climate responses. To demonstrate, we describe a case study in biogeochemical interactions with sea ice. Science Challenge: Biogeochemical models are poorly constrained for high latitude systems. Machine learning methods and edge computing can be combined with Earth system models, such as the Energy Exascale Earth System Model (E3SM), to gain insight into ice-biogeochemical interactions and improve sea ice extent prediction.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

First Analysis of Earth's Stratospheric γ ‐Ray Emission in Geographical Coordinates With Fermi LAT

Abstract From low‐Earth orbit, the Earth is an extremely bright γ ‐ray source compared to distant astrophysical objects. The high‐energy γ ‐ray emission, from the Earth's upper atmosphere, is produced by the interactions between cosmic rays (CRs) and air molecules. As CRs are predominantly charged particles, the geomagnetic field acts as a spectrometer, forbidding CRs below a certain energy to arrive and interact with the atmosphere at a given geomagnetic location from a given direction. We use photon data between 0.2 and 20 GeV as observed by the Fermi Large Area Telescope (LAT) to create, for the first time, stratospheric γ ‐ray emission maps of the Earth in the geographical coordinate system, for different viewing directions from LAT altitude. These maps confirm a strong association between measured γ ‐ray fluxes and geomagnetic cutoffs for CRs. We also report the spectrum of the Earth's stratospheric γ ‐ray emission in cardinal directions and use the geomagnetic spectrometer effect to infer the atmosphere's yield function of γ rays per incoming CR proton as a function of CR rigidity at the altitude of the Fermi spacecraft. This work is relevant to the study of near‐Earth radiation exposure for astronauts and spacecraft, modeling the geomagnetic field, and CR‐air interactions.

Madlee, S.↗
DOE OSTI2021

Gridded daily weather data for North America with comprehensive uncertainty quantification

Abstract Access to daily high-resolution gridded surface weather data based on direct observations and over long time periods is essential for many studies and applications including vegetation, wildlife, soil health, hydrological modelling, and as driver data in Earth system models. We present Daymet V4, a 40-year daily meteorological dataset on a 1 km grid for North America, Hawaii, and Puerto Rico, providing temperature, precipitation, shortwave radiation, vapor pressure, snow water equivalent, and day length. The dataset includes an objective quantification of uncertainty based on strict cross-validation analysis for temperature and precipitation results. The dataset represents several improvements from a previous version, and this data descriptor provides complete documentation for updated methods. Improvements include: reductions in the timing bias of input reporting weather station measurements; improvement to the three-dimensional regression model techniques in the core algorithm; and a novel approach to handling high elevation temperature measurement biases. We show cross-validation analyses with the underlying weather station data to demonstrate the technical validity of new dataset generation methods, and to quantify improved accuracy.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

UFNet: Joint U-Net and Fully Connected Neural Network to Bias Correct Precipitation Predictions from

Paper information. Shuang Yu, Indrasis Chakraborty, Gemma J. Anderson, Donald D. Lucas, Yannic Lops, and Daniel Galea. UFNet: Joint U-Net and fully connected neural network to bias correct precipitation predictions from climate models. Artificial Intelligence for the Earth Systems, 2024. Overview. This work develops the UFNet methodology to correct E3SM historical precipitation projection bias. The UFNet deep learning framework consists of a two-part architecture: a U-Net convolutional network to capture the spatiotemporal distribution of precipitation and a fully connected network to capture the distribution of higher-order statistics. The joint network, termed UFNet, can simultaneously improve the spatial structure of the modeled precipitation and capture the distribution of extreme precipitation values. Below we provide guidance for applying UFNet to correct the Energy Exascale Earth System Model (E3SM; Golaz et al. 2019) daily precipitation projection over the contiguous United States (CONUS). Getting started 1. Obtain the historical climate simulation and observation data. The E3SM historical simulation data are available through https://aims2.llnl.gov/search/cmip6/. The CPC unified gauge-based analysis of daily precipitation can be found through https://psl.noaa.gov/data/gridded/data.cpc.globalprecip.html. The ECMWF atmospheric reanalysis of the 20th century (ERA-20C) data are available through https://www.ecmwf.int/en/forecasts/datasets/reanalysis-datasets/era-20c. The spatial resolution of E3SM and observed datasets are both regridded to a common 1° resolution grid using conservative interpolation. The regridded E3SM, CPC and ERA-20C with 1° resolution can be found throught ./data/. 2. Train the fully connected network (DNN) Python train_dnn.py 3. Train the UFNet Python train_ufnet.py 4. Evaluation and compared with the baseline Python evaluation.py

Lucas, DonaldD↗