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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 127 records · Page 7
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Monitoring of ground water table depth and soil moisture at the Point Reyes field site

Ground water table (GWT) depth and soil moisture (SM) have been monitored at several locations at the Point Reyes field site (Californian coastal grassland) from 2021 to 2024. Monitoring is still on-going and data may be added to this archive at later time. The SM data have been acquired using Teros 12 Meter soil moisture sensors placed at 10, 30, 60 and 90 cm depth at 5 locations along a small hillslope. These sensors also collect soil temperature and bulk conductance. In addition, some collocated sensors provide pore pressure and Photochemical Reflectance Index (PRI). The GWT depth has been inferred from various type of Onset pressure transducers. The pressure measurements have been corrected for atmospheric pressure variations and sensor position relative to the ground surface to infer GWT depth, as well as with RTK GPS data to infer GWT elevation. The GWT data have been acquired at 5 distinct locations from 2020 to 2024 with the sensors placed at about 4 m depth. In addition, GWT data has been acquired for the 2023-2024 period with sensors located in 1 m deep shallow wells installed near each deeper well. This data is intended to evaluate possibly different dynamic in shallow (perched) and deep aquifer. The datasets are all provided in csv format. Please note that the interpretation of the GWT data needs to be done with consideration of environmental and well characteristics at the site and uncertainty in various variables. For more information on GWT and SM data, please contact the author.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Shear–Mediated Stabilization of Spin Spiral Order in Multiferroic NiI 2

Type-II multiferroicity from non-collinear spin order is recently explored in the van der Waals material NiI 2 . Despite the importance for improper ferroelectricity, the microscopic mechanism of the helimagnetic order remains poorly understood. Here, the magneto-structural phases of NiI 2 are investigated using resonant magnetic X-ray scattering (RXS) and X-ray diffraction. Two competing magnetic phases are identified. Below 60 K, an incommensurate magnetic reflection (q ≈ [0.143,0,1.49] reciprocal lattice units) is observed which exhibits finite circular dichroism in RXS, signaling the inversion symmetry-breaking helimagnetic ground state. At elevated temperature, in the non-polar phase (60 K < T < 75 K), a distinct q ≈ [0.087,0.087,1.5] magnetic order is observed, attributed to a collinear incommensurate (CI) state. The first-order CI-helix transition is concomitant with a structural transition characterized by a significant interlayer shear, which drives the helimagnetic ground state as evidenced by a mean-field Heisenberg model including interlayer exchange and its coupling to the structural distortion. Furthermore, these findings identify interlayer magneto-structural coupling as the key driver behind multiferroicity in NiI 2 .

36 MATERIALS SCIENCE↗
DOE OSTI2021

Dairy Methane Emissions in California's San Joaquin Valley Inferred With Ground‐Based Remote Sensing Observations in the Summer and Winter

Abstract The dairy industry in the San Joaquin Valley (SJV) is one of California’s largest methane (CH 4 ) sources. Reducing dairy emissions is a priority for the state’s climate change plans. Observations of current dairy CH 4 emissions are key to monitoring actions taken toward this goal. To help support this, we present new ground‐based measurements of atmospheric column‐averaged CH 4 mixing ratio (XCH 4 ) gradients across a group of 600 dairies in the central SJV using EM27/SUN solar spectrometers. We used measurements from the 2019 summer and 2020 winter seasons for a top‐down emission inversion based on the WRF‐STILT model. Our top‐down estimates of the region’s dairy emissions range from 90% to 183% of the current CALGEM inventory’s emissions of 277 Gg/yr. In contrast to the strong temperature dependence found by earlier dairy CH 4 emission studies, we also find that our top‐down emissions during the winter measurement days are comparable to the summer measurement days, possibly due to seasonal changes in dairy management practices and meteorological conditions. Furthermore, we find significant interday variability in our measurements and find that our emission estimates overlap with earlier top‐down studies and bottom‐up inventories in this region. Our study demonstrates how analysis of ground‐based remotely sensed CH 4 gradient observations can help improve our understanding of CH 4 sources at scales relevant to mitigation policy. It also reflects the need for long‐term monitoring of CH 4 emissions in the region and at individual facilities to better understand their emissions.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

An Automatic Processing Framework for In Situ Determination of Ecohydrological Root Water Content by Ground-Penetrating Radar

This report concerns Root water content (RWC) as a vital component in water flux in soil-plant-atmosphere continuum. Knowledge of RWC helps to better understand the root function and the soil-root interaction and improves water cycle modeling. However, due to the lack of appropriate methods, field monitoring of RWC is seriously constrained. In this study, we used ground-penetrating radar (GPR), a common geophysical technique, to characterize RWC of coarse roots noninvasively. An automatic GPR data processing framework was proposed to (1) identify hyperbolic root reflections and locate roots in GPR images and (2) extract waveform parameters from the reflected wave of identified roots. These waveform parameters were then used to establish an empirical model and a semiempirical model to determine RWC. We validated the developed models using GPR root data at three antenna center frequencies (500 MHz, 900 MHz, and 2 GHz) that were produced from simulation experiments (with RWC ranging from 70% to 150%) and field experiments in sandy soils (with RWC ranging from 66% to 144%). Our results show that both the empirical and the semiempirical models achieved a good performance in estimating RWC with similar accuracy, i.e., the prediction error [root-mean-square error (RMSE)] was less than 8% for the simulation data and 12% for the field data. For both models, the accuracy of RWC estimation was the highest when applied to 2-GHz data. This study renders a new opportunity to determine RWC under field conditions that enhances the application of GPR for root study and the understanding and modeling of ecohydrology in the rhizosphere.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

The geometry of signal space: a case study of direct mapping between seismic signals and event distribution

SUMMARY Under favourable circumstances, seismic waveforms corresponding to an ensemble of events related by a common, spatially distributed process collectively exhibit a regular, signal-space geometry. When events in the ensemble have a common, or nearly common, source mechanism, this geometry is a distorted image of the distribution of events in the source region. The signal-space image can be visualized using a relatively simple waveform alignment and projection operation. Ensemble waveform correlation measurements can be inverted to estimate the distribution of the events in the source region, up to an arbitrary rotation, reflection and scaling, with residual distortion. We demonstrate these concepts with synthetic waveforms and with observations of long-wall mining induced seismicity for which substantial ground truth information is available. Our experience with these data has implications for location, correlation detection and machine learning and possible application to studies of repeating events in induced, volcanic and glacial seismicity. Our results place limits on the widely held assumption that waveform correlation is a useful measure of event separation. We suggest that the constraints on event separation need to be evaluated in the context of a population of related events, whose waveforms sample the signal space image of the source region. A better indicator of event separation is the length of the shortest path in signal space along the image.

58 GEOSCIENCES↗
DOE OSTI2021

LL18-Signal Analysis-NDD2Ad (Final Report)

Under favorable circumstances, seismic waveforms corresponding to an ensemble of events related by a common, spatially-distributed process collectively exhibit a regular, signal-space geometry. When events in the ensemble have a common, or nearly common, source mechanism, this geometry is a distorted image of the distribution of events in the source region. The signal space image can be visualized using a relatively simple waveform alignment and projection operation. Ensemble waveform correlation measurements can be inverted to estimate the distribution of the events in the source region, up to an arbitrary rotation, reflection, and scaling with residual distortion. We demonstrate these concepts with synthetic waveforms and with observations of long-wall mining induced seismicity for which substantial ground truth information is available. Our experience with these data has implications for location, correlation detection and machine learning, and possible application to studies of repeating events in induced, volcanic, and glacial seismicity. Our results place limits on the widely-held assumption that waveform correlation is a useful measure of event separation. We suggest that the constraints on event separation need to be evaluated in the context of a population of related events, whose waveforms sample the signal space image of the source region. A better indicator of event separation is the length of the shortest path in signal space along the image.

58 GEOSCIENCES↗
DOE OSTI2020

Estimating total attenuation using Rayleigh targets at cloud top: applications in multilayer and mixed-phase clouds observed by ground-based multifrequency radars

At millimeter wavelengths, attenuation by hydrometeors, such as liquid droplets or large snowflakes, is generally not negligible. When using multifrequency ground-based radar measurements, it is common practice to use the Rayleigh targets at cloud top as a reference in order to derive attenuation-corrected reflectivities and meaningful dual-frequency ratios (DFRs). By capitalizing on this idea, this study describes a new quality-controlled approach that aims at identifying regions of cloud where particle growth is negligible. The core of the method is the identification of a “Rayleigh plateau”, i.e., a large enough region near cloud top where the vertical gradient of DFR remains small. By analyzing co-located Ka–W band radar and microwave radiometer (MWR) observations taken at two European sites under various meteorological conditions, it is shown how the resulting estimates of differential path-integrated attenuation (ΔPIA) can be used to characterize hydrometeor properties. When the ΔPIA is predominantly produced by cloud liquid droplets, this technique alone can provide accurate estimates of the liquid water path. When combined with MWR observations, this methodology paves the way towards profiling the cloud liquid water, quality-flagging the MWR retrieval for rain and drizzle contamination, and/or estimating the snow differential attenuation.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Variable Daily Autocorrelation Functions of High-Frequency Seismic Data on Mars

Abstract High-frequency seismic data on Mars are dominated by wind-generated lander vibrations, which are radiated partially to the subsurface. Autocorrelation functions (ACFs) of seismic data on Mars filtered between 1 and 5 Hz show clear phases at ∼1.3, ∼2.6, and ∼3.9 s. Daily temporal changes of their arrival times (dt/t) correlate well with the daily changes of ground temperature, with ∼5% daily variation and ∼50 min apparent phase delay. The following two mechanisms could explain the observations: (1) the interference of two predominant spectral peaks at ∼3.3 and ∼4.1 Hz, assumed to be both lander resonance modes, generate the apparent arrivals in the ACFs; (2) the interference of the lander vibration and its reflection from an interface ∼200 m below the lander generate the 3.3 Hz spectral peak and ∼1.3 s arrival in the ACFs. The driving mechanism of the resolved dt/t that most likely explains the ∼50 min delay is thermoelastic strain at a near-surface layer, affecting the lander–ground coupling and subsurface structures. The two outlined mechanisms suggest, respectively, up to ∼10% changes in ground stiffness at 1–5 Hz and ∼15% velocity changes in the top ∼20 m layer. These are upper bound values considering also other possible contributions. The presented methodology and results contribute to analysis of ACFs with limited data and the understanding of subsurface materials on Mars.

Geochemistry & Geophysics↗
DOE OSTI2021

Rashba exciton in a 2D perovskite quantum dot

The Rashba effect has been proposed to give rise to a bright exciton ground state in halide perovskite nanocrystals (NCs), resulting in very fast radiative recombination at room temperature and extremely fast radiative recombination at low temperature. In this paper we find the dispersion of the “Rashba exciton”, i.e., the exciton whose bulk dispersion reflects large spin–orbit Rashba terms in the conduction and valence bands and thus has minima at non-zero quasi-momenta. Placing Rashba excitonsin quasi-2D cylindrical quantum dots, we calculate size-dependent levels of confined excitons and their oscillator transition strengths. Here, we consider the implications of this model for two-dimensional hybrid organic–inorganic perovskites, discuss generalizations of this model to 3D NCs, and establish criteria under which a bright ground exciton state could be realized.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Impact of aqueous solution pH on network structure of corrosion–induced surface layers of boroaluminosilicate glass

Understanding of the long-term stability of vitrified nuclear waste glass is critical to its safe storage, but knowledge gaps remain regarding the corrosion mechanism, especially with respect to surface alteration layers whose presence changes the observed corrosion rates. Here, we report the aqueous corrosion of a model boroaluminosilicate glass at ground water relevant pHs as investigated by vibrational spectroscopy to understand the network structure of the alteration layer that we hypothesize controls the corrosion rates. Both specular reflection infrared spectroscopy and infrared variable angle spectroscopic ellipsometry were used to elucidate details of the structure of the alteration layers formed at pH 7 and pH 9. After 2312 days, the thickness of the alteration layer is found to be ~2000 nm for corrosion at pH 7 and ~300 nm for corrosion at pH 9. Here, the interpretation of the vibrational spectra suggests that alteration layers formed at pH 7 and pH 9 both exhibit a porous network with "silica-like" structures, but with differences in the bond lengths and bond angles in the glass network. Moreover, the relative abundance of the hydrous species within the porous network appears to be dependent on pH. Additionally, the spectroscopic data suggest that the B and Ca trapped in the alteration layer during the secondary corrosion of the pH 9 pre-corroded sample in pH 3 solution are hydrated within the nano-porous layer and not bound to the silicate network. However, the precise chemical form remains to be determined. Based on these findings, we propose that the combination of the network structure of the alteration layer and the relative abundance of hydrous species within the alteration layer act to control the transport of ionic species dissolved from the reaction front to the aqueous solution outside the glass.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Coexistence Praxis: The Role of Resource Managers in Wolf-Livestock Interactions on Federal Lands

In resource management, new terms are frequently introduced, reflecting ongoing evolution in the theory and practice of ecology and governance. Yet understandings of what new concepts mean, for whom, and what they imply for management on the ground can vary widely. Coexistence—a prominent concept within the literature and practices around human-wildlife conflict and predator management—is one such term: widely invoked and yet poorly defined. While for some coexistence is the latest paradigm in improving human-wildlife relations, the concept remains debated and indeed even hotly contested by others—particularly on the multiple-use public lands of the American West, where gray wolf conservation, livestock production, and the claims of diverse stakeholders share space. The multiple meanings of coexistence present serious challenges for conservation practice, as what the concept implies or requires can be contested by those most central to its implementation. In this study we examine wolf-livestock management—a classic case of human-wildlife conflict—by focusing on the experiences and perspectives of U.S. Forest Service (USFS) managers. We reviewed coexistence's multivalence in the literature, complementing semi-structured interviews conducted with USFS employees on case study forests from across the western states. Through this, we highlight the complexity and multi-dimensionality of the concept, and the unique yet under-explored perspective that resource managers bring to these debates. This work draws on insights from political ecology to emphasize the situatedness of manager practice—taking place within a broader set of relations and contextual pressures—while extending political ecologists' traditional focus on the resource user to a concern with the resource manager as a key actor in environmental conflicts. Through our engagement with the experiences and perceptions of USFS managers, who must balance conservation aims with long-established land uses like livestock grazing, we hope to clarify the various dimensions of coexistence. Our hope is that this work thus increases the possibility for empathy and collaboration among managers and stakeholders engaged in this complex socio-ecological challenge.

Martin, Jeff Vance↗
DOE OSTI2025

Groundwater table elevation and temperature from 2015 to 2024 at the Lower Montane site in the East River Watershed, Colorado.

This groundwater level elevation and temperature data package is aimed at improving the predictive understanding of hydro-biogeochemical processes at the lower montane site in the East River Watershed, Colorado. The dataset is obtained using pressure transducers placed in shallow wells in the floodplain. This dataset contains data from wells with Location ID's ER-DOW (alias DO1West), ER-DOE (alias DO2East), ER-MBA1 (alias M1Bend1), ER-MBA2 (alias M1Bend2), ER-UPW (alias UP1West), ER-UPM (alias UP2), ER-UPE (alias UP3East). Another dataset contains the data from wells with Location ID's ER-CPA1 to ER-CPA6. Each file contains the water level elevation and the water temperature. Water level elevation has been obtained using the barometric pressure from the pressure transducer (Hobos sensor) in the well, barometric pressure from a sensor in air located at the same site (lower montane), depth from top-of-casing (TOC) to sensor measurement point, and TOC elevation. Data have been checked with a few measurements of water table depths. A real-time kinematic (RTK) global positioning system (GPS) has been used to survey the TOC (data in file Well_Location.csv). The water level elevation is given in UTM13N Geoid2012AB. While depth to water level is not present in the data files, it can be easily calculated with the TOC and distance to ground provided in the GPS coordinate file. The dataset quality is discussed in Collection/Analysis section of the methods. Time-series of measurements were initially added to the archive for the period 2015 to 2019, and later updated with time-series until 2024 (end of data collection). The dataset contains 8 *.csv data files, and 3 *.csv metadata files. Feel free to contact the author with any questions or collaboration interests. The publication year was updated from "2020" to "2025" to reflect the revised version of this dataset.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Arctic Cloud‐Base Ice Precipitation Properties Retrieved Using Bayesian Inference

Abstract Cloud‐climate feedbacks are still the greatest source of uncertainty in current climate projections. Arctic clouds, which are predominantly stratiform and supercooled, often long‐lived, and nearly continuously precipitate ice particles, contribute roughly 10% of the uncertainty attributed to the global cloud feedback. This Arctic cloud uncertainty is driven by incomplete observational and theoretical knowledge required to estimate and explain the state and active processes occurring in those clouds. A focus on ice precipitation properties at Arctic cloud base rather than the surface deconfounds the product of cloud condensate sink processes from the influence of the atmospheric thermodynamic state below cloud base, rendering cloud‐base properties a more appealing target for inference and evaluation of model simulations. Here I describe an inverse model for the estimation of cloud base ice precipitation properties over Utqiagvik, North Slope of Alaska, using the synthesis of ground‐based radar and lidar measurements. By leveraging a Markov Chain Monte Carlo algorithm as the core of the inverse model, a wide range of particle size distributions are sampled, and different combinations of ice habit models are examined, both of which are typically fixed in other retrieval methods. Results show intriguing links between different cloud base thermodynamic and ice precipitation properties. Apparent ice number concentration enhancements at temperatures of −5 and −15°C suggest possible secondary ice production (SIP). The analysis alludes to an overestimation of SIP occurrence and intensity, especially in studies relying only on radar or lidar measurements. Finally, reflectivity‐dependent ice precipitation rate and ice water content parameterizations are presented.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

PSF–NET: A Nonparametric Point-spread Function Model for Ground-based Optical Telescopes

Ground-based optical telescopes are seriously affected by atmospheric turbulence induced aberrations. Understanding properties of these aberrations is important both for instrument design and image restoration method development. Because the point-spread function can reflect performance of the whole optic system, it is appropriate to use the point-spread function to describe atmospheric turbulence induced aberrations. Assuming point-spread functions induced by the atmospheric turbulence with the same profile belong to the same manifold space, we propose a nonparametric point-spread function—PSF–NET. The PSF–NET has a cycle convolutional neural network structure and is a statistical representation of the manifold space of PSFs induced by the atmospheric turbulence with the same profile. Testing the PSF–NET with simulated and real observation data, we find that a well trained PSF–NET can restore any short exposure images blurred by atmospheric turbulence with the same profile. Besides, we further use the impulse response of the PSF–NET, which can be viewed as the statistical mean PSF, to analyze interpretation properties of the PSF–NET. We find that variations of statistical mean PSFs are caused by variations of the atmospheric turbulence profile: as the difference of the atmospheric turbulence profile increases, the difference between statistical mean PSFs also increases. The PSF–NET proposed in this paper provides a new way to analyze atmospheric turbulence induced aberrations, which would benefit the development of new observation methods for ground-based optical telescopes.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

Radio-echo sounding of Crary Ice Rise reveals abundant marine ice in former ice shelf rifts and basal crevasses

Crary Ice Rise formed after the Ross Ice Shelf re-grounded ~1 kyr BP. We present new ice-penetrating radar data from two systems operating at center frequencies of 7 and 750 MHz that confirm the ice rise is composed of a former ice shelf buried by subsequent accumulation. Stacks of englacial diffraction hyperbolas are present almost everywhere across the central ice rise and extend up to ~350 m above the bed. In many cases, bed reflections beneath the diffraction hyperbolas are obscured for distances up to 1 km. Waveform modeling indicates that the diffraction hyperbolas are likely caused by marine ice deposits in former basal crevasses and rifts. The in-filling of rifts and basal crevasses may have strengthened the connection between the ice rise and the surrounding ice shelf, which could have influenced local and regional ice dynamics. Three internal reflection horizons mark the upper limit of disturbed ice and diffraction hyperbolas in different sections of the ice rise, indicating at least three stages of flow stabilization across the ice rise. A surface lineation visible in MODIS imagery corresponds spatially to deepening and strong deformation of these layers, consistent with the characteristics of former grounding lines observed elsewhere in Antarctica.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Distant Observer™ [SWR-12-09]

Distant Observer™ (DO) is an optical measurement tool, designed for parabolic trough solar collectors, that determines reflector slope error, absorber position error, and the combined errors based on images of the receiver-tube reflection taken from different angles. We have demonstrated that DO can provide a measurement accuracy of 0.25 mrad for the slope and receiver position errors. DO has two implementation versions: ground-based and drone-driven. As we pursue efforts to lower the capital and installation costs of parabolic trough solar collectors, it is essential to maintain high optical performance. The Distant Observer™ (DO) tool, developed by engineers at NREL, is a fast and highly accurate tool that provides complete characterization of the performance of the optical components which include the mirror panels and thermal receiver. This tool is very useful for testing both prototype and operational modules. The Distant Observer™ is an optical measurement tool for parabolic solar collectors that measures reflector slope error, absorber position error and the combined errors. Reflector slope errors occur for many reasons including imperfection in structural frame design, manufacturing and assembly. Absorber position error can be caused by poor structural design, poor installation, sag from the absorber weight, or change in the structure over time.

Ihas, Benjamin↗
DOE OSTI2025

Groundwater table elevation and temperature from 2015 to 2024 across Meander C at the Lower Montane site in the East River Watershed, Colorado.

This groundwater level elevation and temperature data package is aimed at improving the predictive understanding of hydro-biogeochemical processes at the lower montane site in the East River Watershed, Colorado. The dataset is obtained using pressure transducers placed in shallow wells in the floodplain. This dataset contains data from wells ER-CPA1 to ER-CPA6. Another dataset contains the data from wells at nearby Locations. Each file contains the water level elevation and the water temperature. Water level elevation has been obtained using the barometric pressure from the pressure transducer (Hobos sensor) in the well, barometric pressure from a sensor in air located at the same site (lower montane), depth from top-of-casing (TOC) to sensor measurement point, and TOC elevation. Data have been checked with a few measurements of water table depths. A real-time kinematic (RTK) global positioning system (GPS) has been used to survey the TOC (data in file Well_Location.csv). The water level elevation is given in UTM13N Geoid2012AB. While depth to water level is not present in the data files, it can be easily calculated with the TOC and distance to ground provided in the GPS coordinate file. The dataset quality is discussed in Collection/Analysis section of the methods. Time-series of measurements were initially added to the archive for the period 2015 to 2019, and later updated with time-series until 2024 (end of data collection). The dataset contains 7 *.csv data files, and 3 *.csv metadata files. Feel free to contact the author with any questions or collaboration interests. The publication year was updated from "2020" to "2025" to reflect the revised version of this dataset.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Soil Temperature and Moisture, Teller Road Mile Marker 27, Seward Peninsula, Alaska, 2016-2023

Daily averages of soil temperature and moisture measured once every hour at different heights located at Intensive Monitoring Stations at Teller Road Mile Marker 27 site. Data are retrieved annually from 2016-2023. This is the final update to this dataset: no changes to previous data files with the addition of 2022-2023 data files. Data files have header rows, NaN fields indicate invalid or missing data, and negative vertical offsets are above ground. UPDATED 2025-07: Seven new data files collected in 2022-2023 were added and no previously archived data were changed. This represents the final collection of data and text in the title was changed to reflect the defined timespan. Other files that were added: file-level metadata, a data dictionary, a site location map, and a data file inventory by year. 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↗