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At least 451 records · Page 25
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

As above, not so below: Ion fractionation in planetary analog ices

The geophysical evolution and astrobiological potential of ocean worlds are indelibly linked to the chemical compositions of their oceans and ice shells. In the absence of direct measurements, empirical estimates of subsurface ocean compositions have relied on the assumption that the ionic compositions of ice shell surfaces are representative of their underlying ocean compositions. Here, we present experimental results demonstrating that ion fractionation—the differential entrainment of ion species in forming ices—is likely a prevalent process on ocean worlds, suggesting that planetary ice shell compositions do not directly reflect their underlying ocean compositions. We measure in-ice depletions and amplifications of relative ion concentrations ranging between −40 and +77%, compared to the parent fluid composition. Although this may complicate the interpretation of spacecraft data, ion fractionation provides a mechanism for generating compositionally diverse ices that could help explain the geological complexity of planetary ice shells.

58 GEOSCIENCES↗
DOE OSTI2022

Magmatic water content controls the pre-eruptive depth of arc magmas

We report that vanguard efforts in forecasting volcanic eruptions are turning to physics-based models, which require quantitative estimates of magma conditions during pre-eruptive storage. Below active arc volcanoes, observed magma storage depths vary widely (~0 to 20 kilometers) and are commonly assumed to represent levels of neutral buoyancy. Here we show that geophysically observed magma depths (6 ± 3 kilometers) are greater than depths of neutral buoyancy, ruling out this commonly assumed control. Observed depths are instead consistent with predicted depths of water degassing. Intrinsically wetter magmas degas water and crystallize deeper than dry magmas, resulting in viscosity increases that lead to deeper stalling of ascending magma. The water–depth relationship provides a critical constraint for forecasting models by connecting depth of eruption initiation to its volatile fuel.

58 GEOSCIENCES↗
DOE OSTI2022

Atmospheric waves and global seismoacoustic observations of the January 2022 Hunga eruption, Tonga

The 15 January 2022 climactic eruption of Hunga volcano, Tonga, produced an explosion in the atmosphere of a size that has not been documented in the modern geophysical record. The event generated a broad range of atmospheric waves observed globally by various ground-based and spaceborne instrumentation networks. Most prominent was the surface-guided Lamb wave (≲0.01 hertz), which we observed propagating for four (plus three antipodal) passages around Earth over 6 days. As measured by the Lamb wave amplitudes, the climactic Hunga explosion was comparable in size to that of the 1883 Krakatau eruption. The Hunga eruption produced remarkable globally detected infrasound (0.01 to 20 hertz), long-range (~10,000 kilometers) audible sound, and ionospheric perturbations. Seismometers worldwide recorded pure seismic and air-to-ground coupled waves. Air-to-sea coupling likely contributed to fast-arriving tsunamis. In this article, we highlight exceptional observations of the atmospheric waves.

58 GEOSCIENCES↗
DOE OSTI2025

Elasticity of davemaoite as a primary contributor to lower-mantle heterogeneities

Geophysical detection of subducted mid–ocean ridge basalt (MORB) in the lower mantle is hindered by uncertainties in the elasticity of Fe,Al,Mg,Ti–bearing davemaoite, a key MORB component. Using Brillouin spectroscopy and x-ray diffraction, we determined the elasticity of a Ca 0.906(1) Fe 2+ 0.027(1) Fe 3+ 0.042(1) Mg 0.033(1) Al 0.072(1) Ti 0.020(1) Si 0.912(1) O 3 davemaoite up to 113 gigapascals and 2294 K. Here, we found that it exhibited a shear wave velocity 10 to 20% slower than end-member davemaoite, making it the slowest phase among major lower-mantle minerals. Our models show that MORB, containing 20 to 25 volume percent davemaoite, potentially contributes to large low-shear-velocity provinces (LLSVPs), whereas a cumulate layer enriched in davemaoite crystallized from basal magma ocean may comprise ultralow-velocity zones (ULVZs). Davemaoite’s ability to host incompatible and heat-producing elements possibly links LLSVPs and ULVZs to mantle plume initiation and geochemical signatures of ocean island basalts.

Zhou, Wen-Yi [Texas A & M Univ., College Station, ↗
DOE OSTI2023

Improved scientific knowledge of methanogenesis and methanotrophy needed to slow climate change during the next 30 years

Owing to the high radiative forcing and short atmospheric residence time of methane, abatement of methane emissions offers a crucial opportunity for effective, rapid slowing of climate change. Here, we report on a colloquium jointly sponsored by the American Society for Microbiology and the American Geophysical Union, where 35 national and international experts from academia, the private sector, and government met to review understanding of the microbial processes of methanogenesis and methanotrophy. The colloquium addressed how advanced knowledge of the microbiology of methane production and consumption could inform waste management, including landfills and composts, and three areas of agricultural management: enteric emissions from ruminant livestock, manure management, and rice cultivation. Support for both basic and applied research in microbiology and its applications is urgently needed to accelerate the realization of the large potential for these near-term solutions to counteract climate change.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Timescales of mafic magmatic fractionation documented by paleosecular variation in basaltic drill core, Snake River Plain volcanic province, Idaho, USA

Abstract The timescales over which fractional crystallization and recharge work in mafic volcano-plutonic provinces is subject to great uncertainty. Currently modeled processes are subject to the scale of measurement: monogenetic basaltic fields accumulate over hundreds of thousands of years, consistent with U-Th-Ra isotopic variations that imply 50% crystallization of basic magmas on timescales of 100,000 years or more, whereas crystal diffusion modeling implies phenocryst residence times of ~1–1000 years. Monogenetic basalts of the Snake River Plain in southern Idaho, USA, are up to 2 km thick and postdate passage over the Yellowstone–Snake River Plain hotspot. Detailed lithologic and geophysical logging of core from deep drill holes, along with chemical stratigraphy and high-resolution paleomagnetic inclination measurements, document individual eruptive units, compound lava flows, and basaltic flow groups that accumulated over 1–6 m.y. Hiatuses are commonly marked by loess or fluvial interbeds that vary from ~0.1 m thick to 20 m thick. Radiometric (40Ar-39Ar, detrital zircon U-Pb) and paleomagnetic timescale ages show that the deepest hole (Kimama drill hole, 1912 m total depth) accumulated over ~6 m.y. Cycles of fractional crystallization and recharge are recognized in the chemical stratigraphy as up-section shifts in major and trace elements; these fractionation cycles commonly represent 40%–50% fractionation. Individual fractionation cycles may comprise 20–40 eruptive units (8–17 lava flows) with little to no change in paleomagnetic inclination (0°–1°), whereas adjacent cycles may differ by several degrees from one another or reflect changes in polarity. Rates of paleosecular variation in Holocene lavas and sediments dated using 14C document significant shifts in magnetic inclination over short timescales, ranging from ~0.05° to 2°/decade, with an average of ~0.5°/decade and a minimum rate of 0.05°/decade. This implies that fractionation cycles with ≤1° variation in magnetic inclination formed on timescales of a few decades up to a few centuries (20–200 years). Thus, the lavas collectively represent only a few thousand years of eruptive activity, with major flow groups separated in time by tens to hundreds of thousands of years. We suggest that the rates defined by paleosecular variation capture the timescales of magmatic chamber evolution (fractionation/recharge) in the seismically imaged mid-crustal sill complex; in contrast, we suggest that crystal diffusion modeling captures the residence times in shallow subvolcanic magmatic chambers that underlie individual monogenetic volcanoes.

Geology↗
DOE OSTI2022

Cretaceous sequence stratigraphy of the northern Baltimore Canyon Trough: Implications for basin evolution and carbon storage

We evaluate the Cretaceous stratigraphy and carbon sequestration potential of the northern Baltimore Canyon Trough (NBCT) using >10,000 km of multi-channel seismic profiles integrated with geophysical logs, biostratigraphy, and lithology from 29 offshore wells. We identify and map six sequences resolved primarily at the stage level. Accommodation was dominated by thermal and non-thermal subsidence, though sequence boundaries correlate with regional and global sea-level changes, and the record is modified by igneous intrusion, active faulting, and changes in sediment supply and sources. Our stratigraphic maps illustrate a primary southern (central Appalachian) Early Cretaceous source that migrated northward during the Aptian and Albian. During the Cenomanian, sedimentation rates in the NBCT increased and depocenters shifted northward and landward. We show that deposition occurred in three phases: (1) earlier Cretaceous paleoenvironments were primarily terrestrial indicated by variable amplitude, chaotic seismic facies, serrated gamma logs, and heterolithic sandstones and mudstones with terrestrial microfossils; (2) the Albian to Cenomanian was dominated by deltaic paleoenvironments indicated by blocky, funnel-shaped, gamma-ray logs and clinoforms characterized by continuous high-amplitude seismic reflections with well-defined terminations; and (3) the Cenomanian and younger was marine shelf, inferred from mudstoneprone lithologies, peak gamma-ray values in well logs, and foraminiferal evidence. Long-term transgression and maximum water depths at the Cenomanian/Turonian boundary correlative with Ocean Anoxic Event 2 were followed by a regression and relative sea-level fall. We show that porous and permeable sandstones of three Aptian to Cenomanian highstand systems tracts are high-volume reservoirs for supercritical CO 2 storage that are confined by overlying deep water mudstones.

58 GEOSCIENCES↗
DOE OSTI2021

A Fast Solver for the Fractional Helmholtz Equation

The purpose of this paper is to study a Helmholtz problem with a spectral fractional Laplacian, instead of the standard Laplacian. Recently, it has been established that such a fractional Helmholtz problem better captures the underlying behavior in Geophysical Electromagnetics. In this work, we establish the well-posedness and regularity of this problem. We introduce a hybrid spectral-finite element approach to discretize it and show well-posedness of the discrete system. In addition, we derive a priori discretization error estimates. Finally, we introduce an efficient solver that scales aswell as the best possible solver for the classical integer-order Helmholtz equation. We conclude withseveral illustrative examples that confirm our theoretical findings.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Estella Atekwana: Autobiographical Notes

I describe my career journey from a young girl in Cameroon, West Africa, to a trailblazing geophysicist to my current role as dean. I chronicle my time as a student, the transition to being an early career faculty, launching my research career, and ultimately finding my way to administration. Along the way I helped pioneer biogeophysics as a subdiscipline in geophysics while simultaneously maintaining an international research program in continental rift tectonics. I also describe the many intersectionalities in my life including being the first Black woman in many spaces, being a champion for student success, developing a diverse talent pipeline by enhancing diversity in the geosciences, and navigating academic job searches as part of a dual-career couple. Finally, I acknowledge all those who helped shape my career including the many students I had the opportunity to mentor. • Many underrepresented minority geoscientists lack the social capital and professional networks critical for their success. • Geoscience departments must be intentional and deliberate in promoting and ensuring more inclusive workplace environments. • Dual-career couples remain a major challenge, impacting retention and recruitment of top talent; universities should provide resources to alleviate this challenge. • Biogeophysics has untapped potential for advancing understanding of subsurface biogeochemical processes and the search for life in extreme environments. • To date, considerable speculation remains regarding the fundamental geodynamic processes that initiate and sustain the evolution of magma-deficient rifts.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2021

Mechanical Response of Castlegate Sandstone under Hydrostatic Cyclic Loading

The stress history of rocks in the subsurface affects their mechanical and petrophysical properties. Rocks can often experience repeated cycles of loading and unloading due to fluid pressure fluctuations, which will lead to different mechanical behavior from static conditions. This is of importance for several geophysical and industrial applications, for example, wastewater injection and reservoir storage wells, which generate repeated stress perturbations. Laboratory experiments were conducted with Castlegate sandstone to observe the effects of different cyclic pressure loading conditions on a common reservoir analogue. Each sample was hydrostatically loaded in a triaxial cell to a low effective confining pressure, and either pore pressure or confining pressure was cycled at different rates over the course of a few weeks. Fluid permeability was measured during initial loading and periodically between stress cycles. Samples that undergo cyclic loading experience significantly more inelastic (nonrecoverable) strain compared to samples tested without cyclic hydrostatic loading. Permeability decreases rapidly for all tests during the first few days of testing, but the decrease and variability of permeability after this depend upon the loading conditions of each test. Cycling conditions do affect the mechanical behavior; the elastic moduli decrease with the increasing loading rate and stress cycling. The degree of volumetric strain induced by stress cycles is the major control on permeability change in the sandstones, with less compaction leading to more variation from measurement to measurement. The data indicate that cyclic loading degrades permeability and porosity more than static conditions over a similar period, but the petrophysical properties are dictated more by the hydrostatic loading rate rather than the total length of time stress cycling is imposed.

58 GEOSCIENCES↗
DOE OSTI2021

AGU/AMS Abstract Search and Display Software

The AGU/AMS Abstract Search and Display Software is a standalone web application which enables the searching, storing, and displaying of abstracts featured at the annual American Geophysical Union (AGU) and American Meteorological Society (AMS) meetings. This application is designed for those who wish to host a standalone web application and feature a select subset of posters and talks scheduled for the AGU/AMS meetings. Please read the entirety of this README.md file before attempting to download and use the application. There are three views available via the UI: Lookup - enables searching and submitting posters for displaying on the summary view Manual Submission - allows individual manual submission of posters given a poster ID Summary - displays all posters submitted by users from the lookup view

Darnell, Wade↗
DOE OSTI2022

labquake_future_prediction

The labquake_future_prediction code is a collection of python modules and scripts that serves as supporting information for the article “Predicting future laboratory fault friction through deep learning” for publication in the journal of “Geophysical Research Letters”. It is designed to predict laboratory fault slips in the immediate future by scanning continuous acoustic emission (AE) waveforms recorded in laboratory biaxial shear experiments. The predictions are made with a deep learning model based on convolutional encoder-decoder (CED) models and the Transformer model primarily developed for Natural Language Processing (NLP). The deep learning model is trained with the tensorflow package using publicly available laboratory data sets in standard binary file format in numpy. The utility functions for reading data files, configuring model hyperparameters, constructing the CED and Transformer models, training and testing of the models are defined in python module files. The workflow of training the models for labquake future predictions and the multiple GPU’s rapid model hyperparameter optimization as described in the journal article, are demonstrated in accompanying python script files and Jupyter notebooks.

Wang, Kun↗
DOE OSTI2024

Codes for "Shallow Soil Response to a Buried Chemical Explosion with Geophones and Distributed Acoustic Sensing" DAG - 01101646

The codes reproduce the figures of the manuscript entitled "Shallow Soil Response to a Buried Chemical Explosion with Geophones and Distributed Acoustic Sensing" submitted to Journal of Geophysical Research - Solid Earth. Geophone data and Distributed acoustic sensing (DAS) data recorded during the Phase II of the The Source Physics Experiment (SPE) along a fiber-optic cable offshore were processed to understand the response of the shallow subsurface to an explosion. This Ground-based Nuclear Detonation Detection (GNDD), Low Yield Nuclear Monitoring (LYNM), and Source Physics Experiment (SPE) research was funded by the National Nuclear Security Administration, Defense Nuclear Nonproliferation Research and Development (NNSA DNN R&D).

Viens, Loic↗
DOE OSTI2021

pnnl/fieryfuture

Deep learning approaches which incorporate geophysical data and readings from multiple remote sensing platforms for predictive mapping of vegetation over very large, ecologically diverse regions.

Larson, Kyle↗
DOE OSTI2024

cjohnson-LANL/GRL_Kilauea

The python routines are outlined in detail to perform the methods and results in the manuscript under review in the journal Geophysical Research Letters titled “Seismic features predict ground motions during repeating caldera collapse sequence” with LA-UR-23-33345. All routines are written in open source python and were applied to publicly available data sets. The codes formats the data into the appropriate structure required to train a boosted tree regression model. Other codes produce figure results.

Johnson, Christopher W↗
DOE OSTI2024

Deep Learning-based Non-Stationary Bias Correction (NSBC)

This work develops the NSBC (non-stationary bias correction) methodology to correct temperature projection bias from E3SM. The NSBC deep learning framework consists of a three-part architecture: an auto-encoder for compressing the spatial information, an LSTM for predicting annual temperature mean, and a U-Net for capturing the residual bias in temperature. The non-stationary bias correction (NSBC) framework can correct the non-stationarity of the biases of the climate models, which significantly improves the accuracy of future temperature prediction and improves the overestimation of extreme high temperatures that many existing bias correction methods suffer from. Getting started 1. Obtain the historical climate simulation and observation data. The E3SM simulation data are available through https://aims2.llnl.gov/search/cmip6/. The pseudo observations, the Geophysical Fluid Dynamics Laboratory (GFDL)-ESM4 model (Krasting et al., 2018) are available through https://aims2.llnl.gov/search/cmip6/. The spatial resolution of E3SM and pseudo observation datasets are both regridded to a common 1° resolution grid using conservative interpolation. The regridded E3SM and pseudo observation with 1° resolution can be found throught ./data/. 2. Train the Auto-encoder model. Python 0-autoencoder.py 3. Train the LSTM Python 1-LSTM.py 4. Generate the annual mean temperature based on trained LSTM Python 2-generate_annual_mean_LSTM.py 5. Train the U-Net. Python 3-unet.py 6. Evaluation and compared with the baseline Python 4_evaluation.py Is there a deadline approaching that requires the release of yo

Lucas, Donald↗