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At least 307 records · Page 17
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Quantifying CanESM5 and EAMv1 sensitivities to Mt. Pinatubo volcanic forcing for the CMIP6 historical experiment

Large volcanic eruptions reaching the stratosphere have caused marked perturbations to the global climate including cooling at the Earth's surface, changes in large-scale circulation and precipitation patterns and marked temporary reductions in global ocean heat content. Many studies have investigated these effects using climate models; however, uncertainties remain in the modelled response to these eruptions. This is due in part to the diversity of forcing datasets that are used to prescribe the distribution of stratospheric aerosols resulting from these volcanic eruptions, as well as uncertainties in optical property derivations from these datasets. To improve this situation for the sixth phase of the Coupled Model Intercomparison Project (CMIP6), a two-step process was undertaken. First, a combined stratospheric aerosol dataset, the Global Space-based Stratospheric Aerosol Climatology (GloSSAC; 1979–2016), was constructed. Next, GloSSAC, along with information from ice cores and Sun photometers, was used to generate aerosol distributions, characteristics and optical properties to construct a more consistent stratospheric aerosol forcing dataset for models participating in CMIP6. This “version 3” of the stratospheric aerosol forcing has been endorsed for use in all contributing CMIP6 simulations. Recent updates to the underlying GloSSAC from version 1 to version 1.1 affected the 1991–1994 period and necessitated an update to the stratospheric aerosol forcing from version 3 to version 4. As version 3 remains the official CMIP6 input, quantification of the impact on radiative forcing and climate is both relevant and timely for interpreting results from experiments such as the CMIP6 historical simulations. This study uses two models, the Canadian Earth System Model version 5 (CanESM5) and the Energy Exascale Earth System Model (E3SM) Atmosphere Model version 1 (EAMv1), to estimate the difference in instantaneous radiative forcing in simulated post-Pinatubo climate response when using version 4 instead of version 3. Differences in temperature, precipitation and radiative forcings are generally found to be small compared to internal variability. An exception to this is differences in monthly temperature anomalies near 24 km altitude in the tropics, which can be as large as 3 °C following the eruption of Mt. Pinatubo.

58 GEOSCIENCES↗
DOE OSTI2020

Hydrous olivine alteration on Mars and Earth

In this report hydrous alteration of olivine macrocrysts in a Martian olivine phyric basalt, NWA 10416, and a terrestrial basalt from southern Colorado are examined using SEM, EPMA, TEM, and µXRD techniques. The olivines in the meteorite contain linear nanotubes of hydrous material, amorphous areas, and fluid dissolution textures quite distinct from alteration identified in other Martian meteorites. Instead, they bear resemblance to terrestrial deuteric alteration features. The presence of the hydrous alteration phase Mg‐laihunite within the olivines has been confirmed by µXRD analysis. The cores of the olivines in both Martian and terrestrial samples are overgrown by unaltered rims whose compositions match those of a separate population of groundmass olivines, suggesting that the core olivines are xenocrysts whose alteration preceded crystallization of the groundmass. The terrestrial sample is linked to deep crustal metasomatism and the “ignimbrite flare‐up” of the Oligocene epoch. The comparison of the two samples suggests the existence of an analogous relatively water‐rich magmatic reservoir on Mars.

58 GEOSCIENCES↗
DOE OSTI2021

Improved Time-Stepping Methods in Global to Regional Ocean Modeling (Annual Status Report 2020)

Time stepping algorithms are an important part of ocean models, and strongly influence both the accuracy of solution and performance. There have been a number of projects investigating various improvements for ocean time-stepping schemes in the Model for Prediction Across Scales-Ocean (MPAS-Ocean), a component of the DOE Energy Exascale Earth System Model. Ocean dynamics include fast surface gravity waves, which are two-dimensional, and slower internal waves, which are three-dimensional, so ocean models use a split time-stepping scheme that separates these barotropic and baroclinic modes for efficiency. MPAS-Ocean runs on variable-resolution horizontal meshes, and must scale to tens of thousands of cores and millions of horizontal gridcells. Ocean models require time stepping algorithms that are customized to these needs, and which are tuned for performance on various resolutions and architectures.

58 GEOSCIENCES↗
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 OSTI2024

Predicting Fracture Porosity Evolution in Sandstone (Final Report)

To better understand porosity, strength, chemical reactivity, and patterns of fractures, we developed methods using mineral deposits to unravel how fracture growth and diagenesis interact to create and destroy fracture porosity. Quartz and dolomite cement textures and associated fluid inclusion assemblage sequences and thermal histories provided data to infer the duration and rates at which fractures open. We developed and tested a model that accounts for how fracture porosity and rock properties change as a function of thermal exposure and how fracture size and arrangement evolve. Effects of cement deposits on growth were investigated with new geomechanical models and new methods to quantify fracture spatial arrangement. We tested these concepts in a wide range of rock types using outcrop and core-based datasets. We documented opening histories of fractures and fracture arrays in contrasting tectonic and thermal regimes. Our methods set a new standard for fracture characterization and our diagenetic-geomechanical model accurately predicts fluid flow characteristics of fractured rocks based on coupled effects of diagenesis and deformation. Results represent a significant advance in fundamental understanding of fractures in the Earth and have application to improving subsurface engineering operations in a wide range of contexts including geothermal and sequestration applications. The breakthrough of successfully reconstructing the timing and opening rates of parts of single fractures and portions of fracture arrays to document the growth and linkage of fracture arrays was an accomplishment of this grant that is being followed up in our current BES grant DE-SC0022968, ‘Reconstructing and Predicting Fracture Pattern Evolution‘

58 GEOSCIENCES↗
DOE OSTI2026

CHESS 2025: Discrete-return LiDAR point clouds from NEON AOP surveys

This dataset provides Level 1 (L1) discrete-return light detection and ranging (LiDAR) point cloud data collected for the 2025 Colorado Headwaters Ecological Spectroscopy Study (CHESS). These data were acquired to enable characterization of vegetation structure and other three-dimensional features of the land surface, and to evaluate structural changes that may have occurred between a prior LiDAR acquisition in 2018 and the 2025 overflight. The data were acquired over three study domains in the Upper Gunnison river basin: the upper East River watershed (CRBU); Almont Triangle and Taylor Canyon (ALMO); and Upper Taylor River watershed (UPTA) between 2025-06-13 and 2025-07-15. LiDAR data were acquired using the Optech Galaxy Prime Airborne LiDAR Terrain Mapper onboard the National Ecological Observatory Network (NEON) Airborne Observation Platform (AOP). These are the primary unclassified discrete-return LiDAR data delivered by NEON and are provided per flightline as LASzip (LAZ) 1.4 Format 6 files. Data were processed following the workflow described in the NEON L0-to-L1 Discrete Return LiDAR Algorithm Theoretical Basis Document (Krause and Goulden 2022). Each record in the unclassified point clouds represents a geolocated laser target/return recorded by the LiDAR system, with values for X, Y, Z position and return intensity. All point coordinates are provided in meters. Horizontal coordinates are referenced in Universal Transverse Mercator (UTM) zone 13N and the World Geodetic System (WGS) 1984 ensemble datum. Elevations are referenced to Geoid12A. Flight metadata describing flightline boundaries and positional uncertainty by point are also included. CHESS Project Description: The Colorado Headwaters Ecological Spectroscopy Study (CHESS) comprised a multi-week airborne remote sensing and field observation campaign in the Upper Gunnison Basin, Colorado, conducted in June and July of 2025. Airborne remote sensing was conducted by the National Ecological Observatory Network Airborne Observation Platform (NEON AOP), concurrent with a field campaign run by the Rocky Mountain Biological Laboratory (RMBL), the Lawrence Berkeley National Laboratory (LBNL) and SLAC National Accelerator Laboratory Watershed Function Science Focus Area (SFA), and NASA-JPL (Jet Propulsion Laboratory) Earth Surface Mineral Dust Source Investigation (EMIT) program. Between June 10 and July 18, 2025, the NEON AOP flight team collected high-resolution aerial imaging spectroscopy and Light Detection and Ranging (LiDAR) data over three domains: the Upper East River (CRBU), Almont Triangle (ALMO), and the Upper Taylor Basin (UPTA). In coordination with the flights, a field campaign acquired ground-truth observations, including observations of vegetation composition, foliar traits, forest demography, and subsurface properties in 18 core sampling areas within the domains. Additional surface water observations were taken at over 380 point locations. All CHESS campaign datasets can be found within the CHESS ESS-DIVE data portal: https://data.ess-dive.lbl.gov/portals/chess. Funding Acknowledgement: Field and remote-sensing data acquisition was performed under a grant from the National Aeronautics and Space Administration (80NSSC24K1005). This work was also supported by the Watershed Function Science Focus Area at Lawrence Berkeley National Laboratory funded by the US Department of Energy, Office of Science, Biological and Environmental Research under Contract No. DE-AC02-05CH11231.

2018 NEON and 2025 CHESS Campaigns↗
DOE OSTI2023

Development of Laboratory Testbeds Simulating Real-World Greenhouse Gas Emissions [Slides]

In this presentation, I discussed the development of laboratory test beds that simulate field greenhouse gas emissions. Field experiments are used to test new landscape management practices that could reduce greenhouse gas emissions. However, field experiments are very expensive and time consuming. Laboratory experiments are generally more cost efficient and timesaving. There are methods that can be used to make these laboratory tests more closely replicate natural systems for the improvement of agricultural lands used in biofuel and food production. The goal of this project is to develop a laboratory testbed that will mimic field greenhouse gas emissions. To achieve this goal, we used soil cores taken from agricultural and marginal lands, then attached fiberglass wicks to improve the drainage system in the core to simulate a more natural hydraulic system. The combination of using native soils and fiberglass wicks should demonstrate similar greenhouse gas emissions between the lab and the field. Our preliminary results suggest that the carbon dioxide and nitrous oxide flux from the agricultural land site were comparable to the greenhouse soil cores equipped with the drainage wicks. The data suggests that laboratory testbeds can be used to mimic field greenhouse gas emissions if parameters, such as soil water content are in a set range.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

CHESS 2025: Spectrometer orthorectified at-sensor radiance from NEON AOP imaging spectroscopy surveys

This dataset provides Level 1 (L1) orthorectified at-sensor radiance derived from measurements collected by the Imaging Spectrometer-1 (NIS-1) onboard the NEON (National Ecological Observatory Network) Airborne Observation Platform (AOP) for the 2025 Colorado Headwaters Ecological Spectroscopy Study (CHESS). NIS-1 captures light reflected from the Earth’s surface in 426 discrete wavelength bands as raw digital numbers (DNs; Level 0). These data are then calibrated to physical units (uW/cm²·sr·nm) following the processing steps described in the NEON Imaging Spectrometer Level 1B Calibrated Radiance Algorithm Theoretical Basis Document (ATBD; Gallery 2022). The data delivered here are the primary inputs for the surface reflectance product in “Custom surface reflectance, shade masks, and equivalent water thickness maps for the Colorado Headwaters Ecological Spectroscopy Study” (Carroll et al. 2026). For intertemporal comparison, the radiance data here are most directly relatable to the v2 radiance data in “NEON AOP Imaging Spectroscopy Survey of Upper East River Colorado Watersheds: Raw-Space Radiance and Observational Variable Dataset” (Goulden et al. 2018), to which the same processing methodology was applied. Together, the radiance and reflectance data enable users to exploit the unique reflection signatures of different surface objects for land cover classification, foliar trait mapping, plant vigor assessment, water content estimation, trace-element identification, and other scientific applications. The data were acquired over three study domains in the Upper Gunnison river basin: the upper East River watershed (CRBU); Almont Triangle and Taylor Canyon (ALMO); and Upper Taylor River watershed (UPTA) between 2025-06-13 and 2025-07-15. Within each domain, data are delivered by flightline as orthorectified and calibrated hyperspectral rasters in Hierarchical Data Format version 5 (HDF5) format, with radiance values provided in uW/cm²·sr·nm on a fixed, uniform Universal Transverse Mercator (UTM) grid at 1 meter spatial resolution. The radiance rasters include all 426 NIS-1 spectral bands, along with associated quality-assurance (QA) and diagnostic and ancillary layers needed for atmospheric correction workflows. Orthorectified radiance is produced from pushbroom spectrometer observations by applying NEON’s radiometric calibration (including bad pixel masking, dark subtract, dark pedestal shift correction, electronic panel ghost correction, grating ghost correction, deblur correction and flat-fielding) and spectral calibration (using spectral response function band centers and full-width at half-maximum intensity), followed by geolocation and regridding to the fixed grid. CHESS Project Description: The Colorado Headwaters Ecological Spectroscopy Study (CHESS) comprised a multi-week airborne remote sensing and field observation campaign in the Upper Gunnison Basin, Colorado, conducted in June and July of 2025. Airborne remote sensing was conducted by the National Ecological Observatory Network Airborne Observation Platform (NEON AOP), concurrent with a field campaign run by the Rocky Mountain Biological Laboratory (RMBL), the Lawrence Berkeley National Laboratory (LBNL) and SLAC National Accelerator Laboratory Watershed Function Science Focus Area (SFA), and NASA-JPL (Jet Propulsion Laboratory) Earth Surface Mineral Dust Source Investigation (EMIT) program. Between June 10 and July 18, 2025, the NEON AOP flight team collected high-resolution aerial imaging spectroscopy and Light Detection and Ranging (LiDAR) data over three domains: the Upper East River (CRBU), Almont Triangle (ALMO), and the Upper Taylor Basin (UPTA). In coordination with the flights, a field campaign acquired ground-truth observations, including observations of vegetation composition, foliar traits, forest demography, and subsurface properties in 18 core sampling areas within the domains. Additional surface water observations were taken at over 380 point locations. All CHESS campaign datasets can be found within the CHESS ESS-DIVE data portal: https://data.ess-dive.lbl.gov/portals/chess. Funding Acknowledgement: Field and remote-sensing data acquisition was performed under a grant from the National Aeronautics and Space Administration (80NSSC24K1005). This work was also supported by the Watershed Function Science Focus Area at Lawrence Berkeley National Laboratory funded by the US Department of Energy, Office of Science, Biological and Environmental Research under Contract No. DE-AC02-05CH11231.

2018 NEON and 2025 CHESS Campaigns↗
DOE OSTI2021

Modeling 233 Pa Generation in Thorium-fueled Reactors for Safeguards

Thorium has been considered as a possible alternative to uranium for nuclear fuel for many decades. It is three to four times more abundant in the earth than uranium and produces significantly less long-lived transuranic nuclear waste. Some claim thorium poses fewer proliferation concerns than other fuel types largely due to 232 U buildup (and associated high energy gamma-emitting decay products) in the irradiated thorium fuel. However, to fully explore potential proliferation concerns, generation and subsequent decay of 233 Pa produced in the reactor core still must be studied. With its half-life of 27 days, 233 Pa decays to 233 U, which is an International Atomic Energy Agency (IAEA) defined special fissionable material that can be used for nuclear weapons production. With more research being dedicated to thorium-fueled reactors, and several of these reactor designs possessing online fuel processing (allowing for on-site protactinium separation), it is important to understand this potential proliferation pathway. In particular, it is theoretically possible to extract protactinium from the irradiated fuel salt before it decays into 233 U. This hypothetical potential diversion can become an even greater proliferation concern if the extracted protactinium is purified through a second separation of protactinium approximately ten days later to remove the short half-life decay products of 232 Pa and 234 Pa, thus resulting in a higher concentration of the 233 Pa isotope, which decays into weapons usable 233 U with hardly any 232 U or 234 U in it. To estimate the concern of this potential proliferation challenge of thorium, different nuclear material accountancy techniques were reviewed for their viability to quantify 233 Pa if extracted from used thorium fuel. Characteristics of interest included technology maturity, cost, precision, and time taken to acquire results. Some technologies, like hybrid K-edge densitometry and passive gamma spectroscopy, appear to be viable techniques based on current literature. Due to the limited scope of this project, only passive gamma spectroscopy was further investigated. Three different reactor types (PWR, CANDU, MSR) were modeled with mixed thorium-uranium oxide fuels that were burned until the fuel was spent. The protactinium in the used fuel was extracted at the time of shutdown and the change in isotopic content of the protactinium quantified. Gamma spectroscopy simulations were performed for the protactinium isotopes and their decay products at various decay times. Given the simplicity of the models and large assumptions made (e.g. no background, no shielding, no self-attenuation), the initial results indicate that though 233 Pa is detectible for all the reactor types modeled at all decay times (0 to 300 days), more work should be done with higher fidelity models.

07 ISOTOPE AND RADIATION SOURCES↗
DOE OSTI2023

CRITICAL MINERAL PARTITIONING IN COAL-HOSTED CLAYS OF THE POWDER RIVER BASIN, WY DETERMINED BY SEQUENTIAL EXTRACTION

Increasing demand for a more robust domestic supply of rare earth elements (REE) and critical minerals (CM) has led to significant investigation into unconventional sources. Coal and coal byproducts from the Powder River Basin (PRB) of Wyoming are potential sources of REE and CM. The association between strategic metals and their mineral hosts has important implications for extractability. Samples of overburden, underclays, and clay-rich partings were selected for analysis from core and bucket samples from three PRB coal mines. Quartz, illite, and kaolinite-group minerals are abundant in clay-rich portions of the PRB coal strata. We performed a five-step sequential extraction to constrain critical metal partitioning in samples of overburden and underclays (n=10). Unlike the occurrences of REE in other clay deposits, insignificant amounts of total REE + Y (TREY) were recovered in the ion-exchangeable fraction (< 0.5 ppm). A significant amount of TREY was leached from the acid-soluble fraction by 0.1M HCl, suggesting REE may be tied up within crystal lattices rather than sorbed to clay surfaces. The acid-soluble fraction contained between 3 and 250 ppm TREY, with an average TREY concentration of 60 ppm. Relative standard deviations for each extraction step were generally < ±10%. Whole-rock samples (n=72) contained greater TREY enrichment in overburden than in underclays and partings, however, the opposite is true for other CM, such as Ti and V. Other locations in the PRB show different enrichment trends. Our findings supplement a broader effort to couple REE and CM extraction with existing domestic coal production and contribute to the fundamental understanding of how these metals concentrate in low-temperature basin environments.

Stuart, Sophia↗
DOE OSTI2026

CHESS 2025: Field-collected vegetation attributes and site photos

This dataset represents field observations of vegetation samples collected as part of the Colorado Headwaters Ecological Spectroscopy Study (CHESS) during June and July of 2025. Samples were collected in the field using tablet computers and digital forms, with target data differing by sample type (individual trees, individual shrubs, or 1-meter square plots of meadow and subshrub vegetation). Field samples were collected within 72 hours of airborne data collection using the National Ecological Observatory Network’s Aerial Observation Platform (NEON AOP). The NEON AOP collected waveform LiDAR (Light Detection and Ranging) and imaging spectrometer data in 426 spectral bands from the visible to shortwave infrared. Remote sensing data for the project is available on ESS-DIVE (DOI and citation to be added upon publication). Field data collected included canopy height and per-species horizontal proportional cover for meadow plots, species identity and height information for shrubs, as well as species identity, height, diameter at breast height, and health assessment information for trees. Photos of the focal site and surrounding landscape were taken for all sampling sites and are included in this archive. Green leaves or needles were collected for plant trait and foliar chemistry analysis. This data is archived separately (DOI and citation to be added upon publication). High-precision geospatial data for each sample (crown perimeter polygons for trees and shrubs, plot boundaries for meadow plots) is available here (Henderson et al., 2026). Field and remote sensing protocols largely followed those of a previous field and airborne imaging campaign performed in 2018 (described in Chadwick et al. 2020). Field data from the 2018 campaign can be found here (Chadwick et al., 2020 doi:10.15485/1618130). Because different field measurements were taken for meadow, shrub, and tree sites, data from these three sample types are archived as separate tables (chess_meadow_site_cleaned.csv, chess_shrub_site_cleaned.csv, chess_tree_site_cleaned.csv). Meadow proportional cover data is stored in a separate table (chess_meadow_cover_cleaned.csv). Taxonomy was treated identically between sample types, and the dataset shares a common set of voucher specimens (chess_voucher_IDs_cleaned.csv), as well as a single species list (chess_species_list_cleaned.csv). All taxonomic determinations were performed to the species level, and adhere to the Global Biodiversity Information Facility (GBIF) backbone taxonomy as of January 10th, 2026 (GBIF Secretariat 2023). CHESS Project Description: The Colorado Headwaters Ecological Spectroscopy Study (CHESS) comprised a multi-week airborne remote sensing and field observation campaign in the Upper Gunnison Basin, Colorado, conducted in June and July of 2025. Airborne remote sensing was conducted by the National Ecological Observatory Network Airborne Observation Platform (NEON AOP), concurrent with a field campaign run by the Rocky Mountain Biological Laboratory (RMBL), the Lawrence Berkeley National Laboratory (LBNL) and SLAC National Accelerator Laboratory Watershed Function Science Focus Area (SFA), and NASA-JPL (Jet Propulsion Laboratory) Earth Surface Mineral Dust Source Investigation (EMIT) program. Between June 10 and July 18, 2025, the NEON AOP flight team collected high-resolution aerial imaging spectroscopy and Light Detection and Ranging (LiDAR) data over three domains: the Upper East River (CRBU), Almont Triangle (ALMO), and the Upper Taylor Basin (UPTA). In coordination with the flights, a field campaign acquired ground-truth observations, including observations of vegetation composition, foliar traits, forest demography, and subsurface properties in 18 core sampling areas within the domains. Additional surface water observations were taken at over 380 point locations. All CHESS campaign datasets can be found within the CHESS ESS-DIVE data portal: https://data.ess-dive.lbl.gov/portals/chess. Funding Acknowledgment: Field and remote-sensing data acquisition was performed under a grant from the National Aeronautics and Space Administration (80NSSC24K1005). This work was also supported by the Watershed Function Science Focus Area at Lawrence Berkeley National Laboratory funded by the US Department of Energy, Office of Science, Biological and Environmental Research under Contract No. DE-AC02-05CH11231.

2018 NEON and 2025 CHESS Campaigns↗
DOE OSTI2026

CHESS 2025: Leaf Area Index (LAI) for meadow, shrub, tree, and understory vegetation

This dataset contains Leaf Area Index (LAI) measurements made as part of the Colorado Headwaters Ecological Spectroscopy Study (CHESS) during June and July of 2025. Data were collected in the Upper Gunnison Basin, Colorado, across three study domains: the Upper East River (CRBU), Almont Triangle (ALMO), and the Upper Taylor Basin (UPTA). Field observations of LAI were collected within 72 hours of airborne data collection by the National Ecological Observatory Network’s Aerial Observation Platform (NEON AOP). The NEON AOP collected waveform LiDAR (Light Detection and Ranging) and imaging spectrometer data in 426 spectral bands from the visible to shortwave infrared. LAI measurements were collected using the LICOR LAI-2200C Plant Canopy Analyzer following protocols outlined in the instrument manual (LI-COR 2019). Sampling targeted four distinct vegetation types: meadows, shrubs, trees, and aspen forest understory. We have archived data separately by site type because different field methods were used for each. At meadow sites, measurements were made at the four corners of 1m x 1m plots, with the instrument moving inward toward the center of the plot. At shrub sites, we measured the canopies of individual shrubs. At tree sites, we made measurements within a 10m x 10m subplot centered around a focal tree, with 30 observations taken on a regular grid. At aspen understory sites, we measured overstory trees following the tree protocol and understory herbaceous vegetation following the meadow protocol. All measurements included above-canopy (A) and below-canopy (B) readings, with specific protocols for scattering correction measurements in direct-sun conditions. Data were processed using the R package `rlai` (Worsham 2025). This package includes functions to calculate LAI, gap fraction, apparent clumping factor (Ω), scattering correction, and other canopy metrics. Package contents: Full file descriptions appear in ‘flmd.csv’. Files named according to the convention ‘lai_*_summary_data_cleaned.csv’ contain summary values of LAI, apparent clumping factor (Ωapp), and scattering correction factors for each site. These are the analysis-ready products that most data users will work with. Files named ‘lai_*_metadata_cleaned.csv’ contain additional site-level observations made during field collection. We have also archived intermediate and supplementary data for users who wish to check our processing approach or apply alternative methods. ‘raw_lai_2200C.zip’ contains the raw files as read from the LI-COR instrument, with no processing applied, in TXT format. The zip archive contains subdirectories by site type, which are further subdivided by sampling area. Filenames correspond to the sampling site number. ‘intermediate_results.zip’ contains detailed output from the processing routines, in JSON format. The zip archive contains subdirectories by site type; filenames correspond to the sampling site number. ‘scattering_correction_logs.zip’ contains logfiles from the implementation of Kobayashi et al.'s (2013) scattering correction algorithm. The logfiles report values of several parameters at each iteration of the algorithm, as the model converges toward a stable solution. They are intended for users who want to verify scattering correction performance. The zip archive contains subdirectories by site type; filenames correspond to the sampling site number. ‘spot_checks.csv’ reports LAI and other values for a small number of files processed with LI-COR FV2200 software (LI-COR 2013) using the same control parameters as in our R-based approach. Additional metadata are provided in a data dictionary describing column names and definitions (dd.csv), and in a file-level metadata file (flmd.csv). All zip files can be expanded with common archive utilities. TXT, CSV, and JSON files can be ingested into R or Python computing environments or read in common text editor utilities. Geospatial information: Geospatial data for mapping measurement site locations are in the files CHESS_polygons_lai_UTM.geojson, CHESS_polygons_shrub_UTM.geojson, and CHESS_polygons_meadow_UTM.geojson in the companion geospatial package for the 2025 CHESS campaign, ‘CHESS 2025: Location data for field observations and sampling’ (Henderson et al., 2026). CHESS Project Description: The Colorado Headwaters Ecological Spectroscopy Study (CHESS) comprised a multi-week airborne remote sensing and field observation campaign in the Upper Gunnison Basin, Colorado, conducted in June and July of 2025. Airborne remote sensing was conducted by the National Ecological Observatory Network Airborne Observation Platform (NEON AOP), concurrent with a field campaign run by the Rocky Mountain Biological Laboratory (RMBL), the Lawrence Berkeley National Laboratory (LBNL) and SLAC National Accelerator Laboratory Watershed Function Science Focus Area (SFA), and NASA-JPL (Jet Propulsion Laboratory) Earth Surface Mineral Dust Source Investigation (EMIT) program. Between June 10 and July 18, 2025, the NEON AOP flight team collected high-resolution aerial imaging spectroscopy and Light Detection and Ranging (LiDAR) data over three domains: the Upper East River (CRBU), Almont Triangle (ALMO), and the Upper Taylor Basin (UPTA). In coordination with the flights, a field campaign acquired ground-truth observations, including observations of vegetation composition, foliar traits, forest demography, and subsurface properties in 18 core sampling areas within the domains. Additional surface water observations were taken at over 380 point locations. All CHESS campaign datasets can be found within the CHESS ESS-DIVE data portal: https://data.ess-dive.lbl.gov/portals/chess. Funding Acknowledgement: Field and remote-sensing data acquisition was performed under a grant from the National Aeronautics and Space Administration (80NSSC24K1005). This work was also supported by the Watershed Function Science Focus Area at Lawrence Berkeley National Laboratory funded by the US Department of Energy, Office of Science, Biological and Environmental Research under Contract No. DE-AC02-05CH11231. * Todorov and Worsham are co–first authors.

2018 NEON and 2025 CHESS Campaigns↗
DOE OSTI2023

Equation of State and Spin Crossover of (Al, Fe)–Phase H

The transport of hydrogen into Earth's deep interior may have an impact on lower mantle dynamics as well as on the seismic signature of subducted material. Due to the stability of the hydrous phases δ-AlOOH (delta phase), MgSiO 2 (OH) 2 (phase H), and ε-FeOOH at high temperatures and pressures, their solid solutions may transport significant amounts of hydrogen as deep as the core-mantle boundary. Here we have constrained the equation of state, including the effects of a spin crossover in the Fe 3+ atoms, of (Al, Fe)-phase H: Al 0.84 Fe 3+ 0.07 Mg 0.02 Si 0.06 OOH, using powder X-ray diffraction measurements to 125 GPa, supported by synchrotron Mössbauer spectroscopy measurements on (Al, Fe)-phase H and δ-(Al, Fe)OOH. The changes in spin state of Fe 3+ in (Al, Fe)-phase H results in a significant decrease in bulk sound velocity and occurs over a different pressure range (48–62 GPa) compared with δ-(Al, Fe)OOH (32–40 GPa). Changes in axial compressibilities indicate a decrease in the compressibility of hydrogen bonds in (Al, Fe)-phase H near 30 GPa, which may be associated with hydrogen bond symmetrization. The formation of (Al, Fe)-phase H in subducted oceanic crust may contribute to scattering of seismic waves in the mid-lower mantle (~1,100–1,550 km). Accumulation of 1–4 wt.% (Al, Fe)-phase H could reproduce some of the seismic signatures of large, low seismic-velocity provinces. Our results suggest that changes in the electronic structure of phases in the (δ-AlOOH)-(MgSiO 2 (OH) 2 )-(ε-FeOOH) solid solution are sensitive to composition and that the presence of these phases in subducted oceanic crust could be seismically detectable throughout the lower mantle.

58 GEOSCIENCES↗
DOE OSTI2023

Hydrostatic and Non‐Hydrostatic Baroclinic Instability in the Dynamical Core of the DOE Global Climate Model

Abstract The dynamical core of the Department of Energy global climate model is used to understand the role of non‐hydrostatic dynamics in the simulation of dry and moist baroclinic waves. To reduce computational cost, the Diabatic Acceleration and REscaling approach is adopted. Scale analysis and numerical simulations suggest that the model solution is not distorted by the change of spherical metric terms due to the change of Earth radius, neither are the inter‐scale interactions strongly altered as indicated by the analysis of spectral flux. Compared with hydrostatic simulations, the onset of baroclinic instability is delayed under non‐hydrostatic dynamics as the associated weaker vertical motions tend to increase the critical wavelength and narrow the range of waves that can be baroclinically unstable. During the development of baroclinic waves, non‐hydrostatic dynamics tends to induce vertical motions in the upper troposphere, accelerating the eastward propagation of upper‐level ridges through their impact on local vorticity tendency. These processes reduce the westward tilt of the vertical ridge axes and suppress the conversion of mean flow available potential energy to eddy kinetic energy, leading to weaker baroclinic eddies than in hydrostatic simulations. The contrasts between hydrostatic and non‐hydrostatic settings hold in supplemental experiments that vary the background flow Rossby number, the amount of water vapor content and vertical resolution. We also find that mesoscale and smaller‐scale activities can be considerably under‐represented when the vertical resolution is limited to that typically used in global climate models.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Project Task Statement 2 to Umbrella Cooperative Research and Development Agreement between National Energy Technology Laboratory and Ramaco Carbon [Abstract]

NETL and Ramaco will collaborate to characterize domestic coal, beneficiated coal, and coal byproducts to evaluate these materials for rare earth element (REE) content and ease of extraction. Ramaco will provide samples of coal, beneficiated coal, and coal byproducts to NETL, as well as provide research expertise on coal extraction and processing. NETL will characterize these feedstocks using the chemical/physical methods being utilized in its research laboratories. The objectives of this project are: identify promising coal-related REE reserves by testing and analysis of core samples from coal bearing formations; provide insights and expertise into opportunities for the extraction of REEs and other value-added products from domestic coal; and collect data that will be used to create quantitative modeling tools for predicting the likelihood of successful prospecting for REEs in coal, beneficiated and processed coal, and related geologic formation.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2023

Improving Subsurface Stress Characterization for Carbon Dioxide Storage Projects by Incorporating Machine Learning Techniques

The overall objective of this project is to develop a framework for reliable characterization and prediction of the state of stress in the overburden and underburden (including the basement) in CO 2 storage reservoirs using machine learning and integrated geomechanics and geophysical methods. Specifically, we propose to develop workflow encompassing of technologies and/or methods to predict stress and pressure changes due to CO 2 injection in an active tertiary recovery site and their impacts on subtle fault activation, fractures and occurrence of microseismic events and compare responses to field observations. In this project, we anticipate using dataset from the Farnsworth field Unit (FWU) which is operated by Purdure Petroleum. A novel elastic-waveform VSP inversion technique will be used to estimate high-resolution spatial and temporal changes of elastic moduli in CO 2 storage reservoirs, which will be combined with velocity-stress relationship derived from laboratory tests to obtain subsurface pressure and stress. Clustered microseismic data will be jointly inverted for improved focal mechanisms. Least-squares reverse-time migration of microseismic waveform data will be performed to directly image fracture/fault zones. Additionally, a deep neural network machine learning technique with convolutional and recurrent layers will be used for learning the spectro-temporal structures in microseismic waveforms. The results of this geotechnical data analysis will be integrated to develop a high-resolution 3D mechanical earth model extending from the overburden sealing formations to the underburden including the basement. Mechanical properties will be derived through integration of mechanical logs, tests, available results from chemo-mechanical laboratory tests, and elastic inversion of seismic data using a combination of Bayesian and stochastic methods as well as machine learning technique. Failure features (faults/fractures) will be represented and/or modeled based on seismic and core data analysis. A transient hydrodynamic-geomechanical model will be developed through coupling with the calibrated FWU reservoir simulation model. The full physics coupled model will be used to train a reduced order proxy model using machine learning algorithm for estimating stress which will then be used with appropriate constitutive relationships and forward seismological models to simulate pressure changes and induced microseismicity. An advanced optimization framework will be developed to perform a history match to minimize error between field observations and simulated. The history matched proxy model will be verified against the full-physics equivalent. The field observations that will be used in the coupled model calibration process include pressure/stress inverted from VSP, moment magnitude from microseismic analysis, real time downhole pressure measurements, production and injection data. Parameter sensitivity and uncertainty analysis will be performed to characterize the impact of model parameter uncertainty on stress estimates. The proposed project will have significant impact on future field implementation of the proposed technology. Because the project field site is an ongoing CO 2 EOR development, the value of the new technology will be demonstrated in an operational context and evaluated as a viable risk mitigation strategy. Cost/benefit will be evaluated together with the various commercial incentives for CO 2 sequestration available to oil and gas operators. The extensive available dataset and ongoing data acquisition under the SWP Phase III work plan provides flexibility for investigation of multiple approaches and reduces technical risk.

58 GEOSCIENCES↗
DOE OSTI2024

Deformation and Transformation Textures in the NaMgF3 Neighborite—Post-Perovskite System

The D″ region of the lower mantle, which lies just above the core–mantle boundary, is distinct from the bulk of the lower mantle in that it exhibits complex seismic heterogeneity and seismic anisotropy. Seismic anisotropy in this region is likely to be largely due to the deformation-induced texture (crystallographic preferred orientation) development of the constituent mineral phases. Thus, seismic anisotropy can provide a marker for deformation processes occurring in this dynamic region of the Earth. Post-perovskite-structured (Mg,Fe)SiO3 is believed to be the dominant mineral phase in many regions of the D”. As such, understanding deformation mechanisms and texture development in post-perovskite is important for the interpretation of observed seismic anisotropy. Here, we report on high-pressure diamond anvil cell deformation experiments on NaMgF3 neighborite (perovskite structure) and post-perovskite. During deformation, neighborite develops a 100 texture, as has been previously observed, both in NaMgF3 and MgSiO3 perovskite. Upon transformation to the post-perovskite phase, an initial texture of {130} at high angles to compression is observed, indicating that the {100} planes of perovskite become the ~{130} planes of post-perovskite. Further compression results in the development of a shoulder towards (001) in the inverse pole figure. Plasticity modeling using the elasto-viscoplastic self-consistent code shows this texture evolution to be most consistent with deformation on (001)[100] with some contribution of glide on (100)[010] and (001)<110> in NaMgF3 post-perovskite. The transformation and deformation mechanisms observed in this study in the NaMgF3 system are consistent with the behavior generally observed in other perovskite–post-perovskite systems, including the MgSiO3 system. This shows that NaMgF3 is a good analog for the mantle bridgmanite and MgSiO3 post-perovskite.

Geochemistry & Geophysics↗
DOE OSTI2022

Mixing of Condensable Constituents with H–He during the Formation and Evolution of Jupiter

Simulations of Jupiter's formation are presented that incorporate mixing of H–He with denser material entering the planet as solids. Heavy compounds and gas mix substantially when the planet becomes roughly as massive as Earth, because incoming planetesimals can fully vaporize. Supersaturation of vaporized silicates causes the excess to sink as droplets, but water remains at higher altitudes. Because the mean molecular weight decreases rapidly outward, some of the compositional inhomogeneities produced during formation can survive for billions of years. After 4.57 Gyr, our Jupiter model retains compositional gradients; proceeding outward, one finds (i) an inner heavy-element core, the outer part derived from hot supersaturated rain-out; (ii) a composition-gradient region, containing most of the heavy elements, where H–He abundance increases outward, reaching about 0.9 mass fraction at 0.3 of the radius, with silicates enhanced relative to water in the lower parts and depleted in the upper parts; (iii) a uniform-composition region (neglecting He immiscibility) that is enriched over protosolar and contains most of the planet’s mass; and (iv) an outer region where cloud formation (condensation) of heavy constituents occurs. This radial compositional profile has heavy elements more broadly distributed than predicted by classical formation models but less diluted than suggested by Juno-constrained gravity models. The compositional gradients in the region containing the bulk of the heavy elements prevent convection, in both our models and those fitting current gravity, resulting in a hot interior where much of the accretion energy remains trapped.

79 ASTRONOMY AND ASTROPHYSICS↗