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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 109 records · Page 6
All sourcesNASA NTRSDOE OSTI
DOE OSTI2017

Simulations of CO 2 injection into fractures and faults for improving their geophysical characterization at EGS sites

Here, we propose the use of CO 2 in push-pull well tests to improve geophysical identification and characterization of fractures and faults at enhanced geothermal system (EGS) sites. Using TOUGH2/ECO2N, we carried out numerical experiments of push-pull injection-production cycling of CO 2 into idealized vertical fractures and faults to produce pressure-saturation-temperature conditions that can be analyzed for their geophysical response. Our results show that there is a strong difference between injection and production mainly because of CO 2 buoyancy. While the CO 2 -plume grows laterally and upward during injection, not all CO 2 is recovered during the subsequent production phase. Even under the best conditions for recovery, at least 10% of the volume of the pores still remains filled with CO 2 . To improve EGS characterization, comparisons can be made of active seismic methods carried out before and after (time lapse mode) CO 2 injection into the fracture or fault. Here we find that across the CO 2 saturation range, C11 (the normal stiffness in the horizontal direction perpendicular to the fracture plane) varies between maximum and minimum values by about 15%. It reaches a maximum at around 6% gas saturation, decreasing exponentially to a minimum at higher saturations. Finally, our results suggest that CO 2 injection can be effectively used to infiltrate fault and fracture zones reaching about optimal saturation values in order to enhance seismic imaging at EGS sites.

58 GEOSCIENCES↗
DOE OSTI2026

Rapid Coal-Ash Characterization using Geophysical Methods & Machine Learning

Coal combustion products (CCP) are challenging to delineate in heterogeneous field settings. Conventional methods (test pits, coring, and laboratory analyses) are labor-intensive, slow, invasive, and provide sparse spatial coverage. This study evaluates whether rapid non-invasive geophysical screening methods—induced polarization (IP), magnetic susceptibility, and nuclear magnetic resonance (NMR) —combined with surface colorimetry (RGB_24), can discriminate CCP-soil mixtures and provide reliable estimates of CCP content. Laboratory measurements were collected on five CCP-soil mixtures (series) and modeled using (i) a linear baseline, (ii) a calibrated non-linear (power-mean) model, and (iii) a machine-learning (ML) Random Forest approach, with validation via leave-one-series-out and site-specific tests. Across the five series, individual signals—particularly IP and magnetic susceptibility—were strongly predictive of ash content but were consistently outperformed by combined models. The pooled calibrated non-linear and ML models captured the observed non-linearity and achieved high accuracy and precision, improving on linear fits. Colorimetry showed the weakest direct relationship with ash content for the tested samples but improved performance when included in multi-signal models. At pre-selected 3.5% decision threshold, calibrated and ML approaches yielded near-perfect classification (Matthews correlation coefficient ˜ 1), suggesting strong practical operability for field screening. Additionally, field-analog tests highlighted the role of endmembers—accuracy declined without access to end-member measurements but was largely recovered by collecting a minimal labeled pair for local recalibration. With end members, accuracy remained high. Globally trained models performed well on three operational unknowns; however, series-specific refits provided the most accurate predictions. Overall, these results highlight the potential of combining rapid geophysics and minimal local calibration for improved coal-ash delineation.

Peshtani, Klaudio↗
DOE OSTI2023

Geophysical signatures of soil AFFF contamination from spectral induced polarization and low field nuclear magnetic resonance methods

Few field methods are available for characterizing source zones contaminated with aqueous film forming foam (AFFF). Non-invasive geophysical characterization of AFFF source zone contamination in situ could assist with the delineation and characterization of these sites, allowing for more informed sampling regimes aimed at quantifying subsurface poly- and perfluoroalkyl substances (PFAS) contamination. In this study, we present initial results from the investigation of the sensitivity of two existing surface and borehole-deployable geophysical technologies, spectral induced polarization (SIP), and low field nuclear magnetic resonance (NMR), to soils impacted with AFFF. To investigate the sensitivity of these methods to AFFF-impacted soil, bench-scale column experiments were conducted on samples consisting of natural and synthetic soils and groundwater. While our findings do not show strong evidence of NMR sensitivity to soil PFAS contamination, we do find evidence that SIP has sufficient sensitivity to detect PFAS sorption to soils. This finding is based on evidence that AFFF constituents associated with the pore surface produce a measurable polarization response in both freshly contaminated synthetic soils and in soils historically impacted with AFFF.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2014

New perspectives on superparameterization for geophysical turbulence

This is a research expository paper regarding superparameterization, a class of multi-scale numerical methods designed to cope with the intermittent multi-scale effects of inhomogeneous geophysical turbulence where energy often inverse-cascades from the unresolved scales to the large scales through the effects of waves, jets, vortices, and latent heat release from moist processes. Original as well as sparse space–time superparameterization algorithms are discussed for the important case of moist atmospheric convection including the role of multi-scale asymptotic methods in providing self-consistent constraints on superparameterization algorithms and related deterministic and stochastic multi-cloud parameterizations. Test models for the statistical numerical analysis of superparameterization algorithms are discussed both to elucidate the performance of the basic algorithms and to test their potential role in efficient multi-scale data assimilation. The very recent development of grid-free seamless stochastic superparameterization methods for geophysical turbulence appropriate for “eddy-permitting” mesoscale ocean turbulence is presented here including a general formulation and illustrative applications to two-layer quasigeostrophic turbulence, and another difficult test case involving one-dimensional models of dispersive wave turbulence. This last test case has randomly generated solitons as coherent structures which collapse and radiate wave energy back to the larger scales, resulting in strong direct and inverse turbulent energy cascades.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2018

Experimental Measurement of the Solid Particle Concentration in Geophysical Turbulent Gas-Particle Mixtures

Dilute gas-particle mixtures in which the particles are carried by the turbulent fluid are found in various geophysical contexts, from cold snow avalanches to hot pyroclastic density currents. Though previous studies suggest that such mixtures have maximum particle concentrations of a few volume percent, the dependence of this maximum concentration on the Reynolds number is unclear. We addressed this issue through laboratory experiments in a vertical pipe, where dilute gas-particle mixtures were created by injecting a turbulent air flow from below. Nearly monodisperse mixtures of glass beads of different grain sizes (77 to 1,550 μm) were used with varying bulk concentrations from 0.025 to 8 vol. %. To create quasi-static mixtures, the mean air velocity matched the terminal settling velocity for the grain sizes investigated. The maximum Reynolds numbers of the mixtures were ~104–106. The air pressure indicated full support of the particle weight at concentrations down to 0.025 vol. %. Above a critical particle concentration, at which all the particles were suspended, subsequent additional particles were not maintained in the mixture and led to the formation of clusters that settled downward in the pipe to form a dense fluidized bed. Maximum mean particle concentrations of the dilute mixtures increased from ~1 to ~2.8 vol. % and reached a plateau at increasing mixture Reynolds number. These results give insights into the maximum particle concentrations of geophysical turbulent gas-particle mixtures and may serve to constrain observations as well as the input and output data of models.

58 GEOSCIENCES↗
DOE OSTI2022

Achievements and Prospects of Global Broadband Seismographic Networks After 30 Years of Continuous Geophysical Observations

Global seismographic networks (GSNs) emerged during the late nineteenth and early twentieth centuries, facilitated by seminal international developments in theory, technology, instrumentation, and data exchange. The mid- to late-twentieth century saw the creation of the World-Wide Standardized Seismographic Network (1961) and International Deployment of Accelerometers (1976), which advanced global geographic coverage as seismometer bandwidth increased greatly allowing for the recording of the Earth's principal seismic spectrum. The modern era of global observations and rapid data access began during the 1980s, and notably included the inception of the GEOSCOPE initiative (1982) and GSN (1988). Through continual improvements, GEOSCOPE and the GSN have realized near-real time recording of ground motion with state-of-art data quality, dynamic range, and timing precision to encompass 180 seismic stations, many in very remote locations. Data from GSNs are increasingly integrated with other geophysical data (e.g., space geodesy, infrasound and Interferometric Synthetic Aperture Radar). Globally distributed seismic data are critical to resolving crust, mantle, and core structure; illuminating features of the plate tectonic and mantle convection system; rapid characterization of earthquakes; identification of potential tsunamis; global nuclear test verification; and provide sensitive proxies for environmental changes. As the global geosciences community continues to advance our understanding of Earth structure and processes controlling elastic wave propagation, GSN infrastructure offers a springboard to realize increasingly multi-instrument geophysical observatories. Here, we review the historical, scientific, and monitoring heritage of GSNs, summarize key discoveries, and discuss future associated opportunities for Earth Science.

58 GEOSCIENCES↗
DOE OSTI2018

Integrating geophysical monitoring data into multiphase fluid flow reservoir simulation

Simulation of multiphase flow systems are of critical importance in managing hydrological systems. Flow simulations are affected by a number of factors including structure and flow properties including porosity and permeability as well as the anisotropy and heterogeneity of these properties. In many cases traditional hydrological and reservoir data are highly affected by these parameters, but are not directly sensitive to them. As such modellers often adjust these parameters in an ad hoc manner until solutions numerically converge. Simulation models are generally based on structural data from reflection seismics whose physical flow properties are then populated using geostatistical extrapolation techniques utilizing a sparse number of borehole logs and core analysis. In multiphase systems including enhanced oil recovery and carbon capture and sequestration uncertainties regarding phase-dependent physical properties confounds this challenge further. Geophysical methods provide a means by which to gain an improved understanding of phase distributions in the subsurface. In this paper we will look at applications from active carbon capture and sequestration and enhanced oil recovery applications, as well as synthetic examples. Geophysical data including electromagnetic and gravity are inverted using structural constraints from the reservoir model. Inversions are then mapped into flow properties using calibrated relations such as Archie’s Equation. The coupled models can then be used to both verify and improve on the reservoir flow model which improves it’s predictive power and utility as a management tool.

02 PETROLEUM↗
DOE OSTI2014

A NEW UNDERSTANDING OF THE EUROPA ATMOSPHERE AND LIMITS ON GEOPHYSICAL ACTIVITY

Deep extreme ultraviolet spectrograph exposures of the plasma sheet at the orbit of Europa, obtained in 2001 using the Cassini Ultraviolet Imaging Spectrograph experiment, have been analyzed to determine the state of the gas. The results are in basic agreement with earlier results, in particular with Voyager encounter measurements of electron density and temperature. Mass loading rates and lack of detectable neutrals in the plasma sheet, however, are in conflict with earlier determinations of atmospheric composition and density at Europa. A substantial fraction of the plasma species at the Europa orbit are long-lived sulfur ions originating at Io, with ∼25% derived from Europa. During the outward radial diffusion process to the Europa orbit, heat deposition forces a significant rise in plasma electron temperature and latitudinal size accompanied with conversion to higher order ions, a clear indication that mass loading from Europa is very low. Analysis of far ultraviolet spectra from exposures on Europa leads to the conclusion that earlier reported atmospheric measurements have been misinterpreted. The results in the present work are also in conflict with a report that energetic neutral particles imaged by the Cassini ion and neutral camera experiment originate at the Europa orbit. An interpretation of persistent energetic proton pitch angle distributions near the Europa orbit as an effect of a significant population of neutral gas is also in conflict with the results of the present work. The general conclusion drawn here is that Europa is geophysically far less active than inferred in previous research, with mass loading of the plasma sheet ≤4.5 × 10{sup 25} atoms s{sup –1} two orders of magnitude below earlier published calculations. Temporal variability in the region joining the Io and Europa orbits, based on the accumulated evidence, is forced by the response of the system to geophysical activity at Io. No evidence for the direct injection of H{sub 2}O into the Europa atmosphere or from Europa into the magnetosphere system, as has been observed at Enceladus in the Saturn system, is obtained in the present investigation.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Surface parameters and bedrock properties covary across a mountainous watershed: Insights from machine learning and geophysics

Bedrock property quantification is critical for predicting the hydrological response of watersheds to climate disturbances. Estimating bedrock hydraulic properties over watershed scales is inherently difficult, particularly in fracture-dominated regions. Our analysis tests the covariability of above- and belowground features on a watershed scale, by linking borehole geophysical data, near-surface geophysics, and remote sensing data. We use machine learning to quantify the relationships between bedrock geophysical/hydrological properties and geomorphological/vegetation indices and show that machine learning relationships can estimate most of their covariability. Although we can predict the electrical resistivity variation across the watershed, regions of lower variability in the input parameters are shown to provide better estimates, indicating a limitation of commonly applied geomorphological models. Our results emphasize that such an integrated approach can be used to derive detailed bedrock characteristics, allowing for identification of small-scale variations across an entire watershed that may be critical to assess the impact of disturbances on hydrological systems.

58 GEOSCIENCES↗
DOE OSTI2017

Introduction to this special section: Geophysical applications of fiber-optic distributed sensing

Here, this special section is dedicated to geophysical distributed acoustic sensing (DAS) and distributed temperature sensing (DTS) applications. Since the introduction of commercial DTS units in the 1980s and more recent deployment of DAS in this decade, distributed sensing is quietly revolutionizing sectors of geophysics, particularly those requiring permanent downhole measurements. The common component of distributed sensing technologies is the use of laser scattering measurements on fiber-optic cables (tens of kilometers long) to estimate the physical state of each fiber segment with measurands including temperature (DTS), static strain (DSS), and, most recently, dynamic strain and seismic waves (DAS) recorded either continuously or on an as-needed basis. The high spatial coverage, accuracy, and resolution of this technology make it a truly groundbreaking addition to our subsurface sensing toolbox.

47 OTHER INSTRUMENTATION↗
DOE OSTI2012

The Institute of Geophysics and Planetary Physics adds Science of Signatures and a new Deputy to its portfolio

The Institute of Geophysics and Planetary Physics (IGPP) is adding the Science of Signatures to it’s portfolio. It’s new title, the Institute of Geophysics, Planetary Physics and Signatures (IGPPS) is in recognition that Science of Signatures is a LANL strategic science pillar, and is a natural fit with the IGPPS goal of promoting and supporting high quality, cutting-edge science in the areas of astrophysics, space physics, solid planetary geoscience, and climate science. IGPPS Director Dogliani states that, “One cannot fully understand natural phenomena without conducting field measurements of key events.” Beginning in FY13, IGPPS will consider proposals that investigate and develop signature and sensor science for potential use in understanding our evolving climate, geoscience, planetary space and cosmology phenomena.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2015

Final Scientific/Technical Report – DE-EE0002960 Recovery Act. Detachment faulting and Geothermal Resources - An Innovative Integrated Geological and Geophysical Investigation of Pearl Hot Spring, Nevada

The Pearl Host Spring Geothermal Project funded by the DoE Geothermal Program was a joint academic (KU/UT & OU) and industry collaboration (Sierra and Ram Power) to investigate structural controls and the importance of low-angle normal faults on geothermal fluid flow through a multifaceted geological, geophysical, and geochemical investigation in west-central Nevada. The study clearly showed that the geothermal resources in Clayton Valley are controlled by the interplay between low-angle normal faults and active deformation related to the Walker Lane. The study not only identified potentially feasible blind geothermal resource plays in eastern Clayton Valley, but also provide a transportable template for exploration in the area of west-central Nevada and other regional and actively-deforming releasing fault bends. The study showed that deep-seated low-angle normal faults likely act as crustal scale permeability boundaries and could play an important role in geothermal circulation and funneling geothermal fluid into active fault zones. Not unique to this study, active deformation is viewed as an important gradient to rejuvenated fracture permeability aiding the long-term viability of blind geothermal resources. The technical approach for Phase I included the following components, (1) Structural and geological analysis of Pearl Hot Spring Resource, (2) (U-Th)/He thermochronometry and geothermometry, (3) detailed gravity data and modeling (plus some magnetic and resistivity), (4) Reflection and Refraction Seismic (Active Source), (5) Integration with existing and new geological/geophysical data, and (6) 3-D Earth Model, combining all data in an innovative approach combining classic work with new geochemical and geophysical methodology to detect blind geothermal resources in a cost-effective fashion.

15 GEOTHERMAL ENERGY↗
DOE OSTI2015

Blind Geothermal System Exploration in Active Volcanic Environments; Multi-phase Geophysical and Geochemical Surveys in Overt and Subtle Volcanic Systems, Hawai’i and Maui

Suites of new geophysical and geochemical exploration surveys were conducted to provide evidence for geothermal resource at the Haleakala Southwest Rift Zone (HSWRZ) on Maui Island, Hawai’i. Ground-based gravity (~400 stations) coupled with heli-bourne magnetics (~1500 line kilometers) define both deep and shallow fractures/faults, while also delineating potentially widespread subsurface hydrothermal alteration on the lower flanks (below approximately 1800 feet a.s.l.). Multi-level, upward continuation calculations and 2-D gravity and magnetic modeling provide information on source depths, but lack of lithologic information leaves ambiguity in the estimates. Additionally, several well-defined gravity lows (possibly vent zones) lie coincident with magnetic highs suggesting the presence of dike intrusions at depth which may represent a potentially young source of heat. Soil CO2 fluxes were measured along transects across geophysically-defined faults and fractures as well as young cinder cones along the HSWRZ. This survey generally did not detect CO2 levels above background, with the exception of a weak anomalous flux signal over one young cinder cone. The general lack of observed CO2 flux signals on the HSWRZ is likely due to a combination of lower magmatic CO2 fluxes and relatively high biogenic surface CO2 fluxes which mix with the magmatic signal. Similar surveys at the Puna geothermal field on the Kilauea Lower East Rift Zone (KLERZ) also showed a lack of surface CO2 flux signals, however aqueous geochemistry indicated contribution of magmatic CO2 and He to shallow groundwater here. As magma has been intercepted in geothermal drilling at the Puna field, the lack of measured surface CO2 flux indicative of upflow of magmatic fluids here is likely due to effective “scrubbing” by high groundwater and a mature hydrothermal system. Dissolved inorganic carbon (DIC) concentrations, δ13C compositions and 3He/4He values were sampled at Maui from several shallow groundwater samples indicating only minor additions of magmatic CO2 and He to the groundwater system, although much less than observed near Puna. The much reduced DIC and He abundances at Maui, along with a lack of hotsprings and hydrothermal alteration, as observed near Puna, does not strongly support a deeper hydrothermal system within the HSWRZ.

15 GEOTHERMAL ENERGY↗
DOE OSTI2018

Effectiveness of Geophysical Monitoring Methods in Detecting Brine and CO 2 Leakage in Underground Sources of Drinking Water

The US DOE National Risk Assessment Partnership (NRAP), funded through the Office of Fossil Energy and the National Energy Technology Laboratory (NETL), is developing methods to evaluate the effectiveness of monitoring techniques to detect brine and CO 2 leakage from legacy wells into underground sources of drinking water (USDW) overlying a CO 2 storage reservoir. As part of the NRAP Strategic Monitoring task group, we have generated Kimberlina Rev. 1.1 of the simulated aquifer impact data (140 simulations) from a model framework based on a hypothetical, compartmentalized, CO 2 storage reservoir near Kimberlina in the southern San Joaquin Basin, California. Brine and CO 2 leakage along damaged wellbores results in subsurface changes in pressure, CO 2 saturation and total dissolved solids (TDS). CO 2 buoyancy allows a significant fraction of leaked CO 2 to reach shallow permeable zones, which is more detectable by surface geophysical sensors. We generated synthetic geophysical data from the simulated aquifer impact data to assess electrical resistivity tomography (ERT), magnetotellurics (MT), gravity and seismic methods for remote and indirect detection of brine and CO 2 leakage.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2022

Deep Learning At Depth: Estimating subsurface parameters from geophysical monitoring data

Geophysical imaging techniques are a non-invasive way to image the subsurface and understand both subsurface solid (rock/soil) and fluid property distributions and their evolution in time. Inversions of the geophysical data, such as Electrical Resistance Tomography (ERT) data, are solved to estimate the subsurface property distributions, such as conductivity, and many inversion techniques smooth out sharp gradients in rock or fluid property distributions. Sharp gradients in subsurface properties tend to be present in situations with complex subsurface structures, which are common in many subsurface applications. We have successfully demonstrated that it is possible to inform, or constrain, inversions with neural networks trained on synthetic data with complex subsurface structures. Initial results suggest this process may be optimizable to yield property distributions that better represent the true property distributions than the same inversion process without the neural network constraint. Future work would optimize the neural network performance for this application and then apply the synthetic-data trained neural network to real data to understand the utility and performance of this technique for real data sets.

47 OTHER INSTRUMENTATION↗
DOE OSTI2019

Remote sensing and geophysical characterization of a floodplain-hillslope system in the East River watershed, Colorado

This package is part of the Watershed Function SFA Data Collection and contains remote sensing data and geophysical measurements acquired at the Pumphouse hillslope-floodplain site, in the East River, Colorado. The remote sensing dataset includes: a) a WorldView-2 (WV-2) pan-sharpened multi-spectral remote sensing image, and b) LiDAR derived products. The WV-2 image was acquired on September 24th, 2015, and it is composed of eight spectral bands (coastal, blue, green, yellow, red, red edge, NIR1, and NIR2) with a spatial resolution of 0.5 m, covering an area of 750x750 m. The LiDAR products are a digital surface model (DSM), representing the top-of-canopy elevation, and a digital terrain model (DTM), representing the bare-ground elevation, at the spatial resolution of 0.5 m. Such data are extracted from the LiDAR point-cloud dataset acquired over the entire watershed on August 2015 (http://dx.doi.org/10.21952/WTR/1412542). The geophysical dataset is composed of the electrical resistivity tomography (ERT) data acquired along a 158.75 m long transect, spanning the hillslope topographical gradient with 1.25 m electrode spacing. The dataset also includes soil water content measured with a TDR system. The package provides also polygons of different vegetation communities, which were used as reference data for mapping plant community distributions. The spatial polygons are based on plant locations acquired during the field campaign of June-July 2017 using an RTK DGPS system. The reference dataset is composed by 11 vegetation classes, namely, deciduous forest, evergreen forest, riparian shrubland, sagebrush, shrubland, potentilla, frasera, lupine meadow, veratrum, bunchgrass meadow, and forb, as well as four non-vegetation classes, such as water-river, water-lake, man-made, bare area, and shadow. The vegetation classes are determined based on distinct spectral and/or structural signatures of dominant species. The package includes products derived by these datasets, such as: a) a plant height map, computed by subtracting the DTM from the DSM, and b) a plant community distribution map, obtained by using a data-fusion machine-learning-based framework that exploit the WV-2 image and plant height information.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Geophysical Observations of the 2023 September 24 OSIRIS-REx Sample Return Capsule Reentry

Sample return capsules (SRCs) entering Earth's atmosphere at hypervelocity from interplanetary space are a valuable resource for studying meteor phenomena. The 2023 September 24 arrival of the Origins, Spectral Interpretation, Resource Identification, and Security-Regolith Explorer SRC provided an unprecedented chance for geophysical observations of a well-characterized source with known parameters, including timing and trajectory. A collaborative effort involving researchers from 16 institutions executed a carefully planned geophysical observational campaign at strategically chosen locations, deploying over 400 ground-based sensors encompassing infrasound, seismic, distributed acoustic sensing, and Global Positioning System technologies. Additionally, balloons equipped with infrasound sensors were launched to capture signals at higher altitudes. This campaign (the largest of its kind so far) yielded a wealth of invaluable data anticipated to fuel scientific inquiry for years to come. The success of the observational campaign is evidenced by the near-universal detection of signals across instruments, both proximal and distal. This paper presents a comprehensive overview of the collective scientific effort, field deployment, and preliminary findings. The early findings have the potential to inform future space missions and terrestrial campaigns, contributing to our understanding of meteoroid interactions with planetary atmospheres. Furthermore, the data set collected during this campaign will improve entry and propagation models and augment the study of atmospheric dynamics and shock phenomena generated by meteoroids and similar sources.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2021

Geophysical and Environmental Monitoring Data, Lower Watershed, Teller Road Mile Marker 27, Seward Peninsula, Alaska, 2017-2019

This data set contains geophysical and environmental monitoring data acquired between September 2017 and 2019 at the lower Teller watershed, Seward Peninsula, Alaska. Geophysical data comprises processed resistivity data, acquired daily between Spring and Fall of 2018 and 2019, and a baseline measurement of Fall 2017. The environmental monitoring data comprises depth resolved, distributed soil moisture and soil temperature data. These measurements were obtained used Decagon 5TE sensors placed at 0.1 m, 0.2 m , 0.3 m, and 0.4 m depth. In addition, temperature data at 0.5 m, 1.0 m, and 1.5 m were acquired using Hobo temperature sensors. Data were collected to improve our understanding of the hydrological response of discontinuous permafrost systems, in particular focusing on multi-annual dynamics and short term disturbances, such as snowmelt or precipitation events. The electrical resistivity tomography (ERT) monitoring data are included as processed resistivity models, with model cells x dimension equal to the distance along the profile, and model z dimension being elevation. The start and end point of the transect are (UTM Zone 3N): E 454881.66 m, N 7178949.45 m, and E 454772.60, N 7178885.81. Locations of the soil moisture and temperature sensors are provided in the data package. This dataset is discussed in detail in the Uhlemann, S. et al 2021 paper listed in the references. This dataset includes one *.pdf user guide and 315 *.csv data files included within four zipped files.The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a research effort to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research.The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska.Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

54 ENVIRONMENTAL SCIENCES↗