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At least 433 records · Page 24

Polarimetric Properties of Event Horizon Telescope Targets from ALMA

We present the results from a full polarization study carried out with the Atacama Large Millimeter/submillimeter Array (ALMA) during the first Very Long Baseline Interferometry (VLBI) campaign, which was conducted in 2017 April in the λ3 mm and λ1.3 mm bands, in concert with the Global mm-VLBI Array (GMVA) and the Event Horizon Telescope (EHT), respectively. We determine the polarization and Faraday properties of all VLBI targets, including Sgr A*, M87, and a dozen radio-loud active galactic nuclei (AGNs), in the two bands at several epochs in a time window of 10 days. We detect high linear polarization fractions (2%–15%) and large rotation measures (RM > 10 3.3 –10 5.5 rad m -2 ), confirming the trends of previous AGN studies at millimeter wavelengths. We find that blazars are more strongly polarized than other AGNs in the sample, while exhibiting (on average) order-of-magnitude lower RM values, consistent with the AGN viewing angle unification scheme. For Sgr A* we report a mean RM of (-4.2 ± 0.3) × 10 5 rad m -2 at 1.3 mm, consistent with measurements over the past decade and, for the first time, an RM of (–2.1 ± 0.1) × 10 5 rad m -2 at 3 mm, suggesting that about half of the Faraday rotation at 1.3 mm may occur between the 3 mm photosphere and the 1.3 mm source. We also report the first unambiguous measurement of RM toward the M87 nucleus at millimeter wavelengths, which undergoes significant changes in magnitude and sign reversals on a one year timescale, spanning the range from -1.2 to 0.3 × 10 5 rad m -2 at 3 mm and -4.1 to 1.5 × 10 5 rad m -2 at 1.3 mm. Given this time variability, we argue that, unlike the case of Sgr A*, the RM in M87 does not provide an accurate estimate of the mass accretion rate onto the black hole. We put forward a two-component model, comprised of a variable compact region and a static extended region, that can simultaneously explain the polarimetric properties observed by both the EHT (on horizon scales) and ALMA (which observes the combined emission from both components). These measurements provide critical constraints for the calibration, analysis, and interpretation of simultaneously obtained VLBI data with the EHT and GMVA.

79 ASTRONOMY AND ASTROPHYSICS↗

Changes in Precipitation and Air Temperature Contribute Comparably to Permafrost Degradation in a Warmer Climate: Modeling Archive

The dataset contains "ecosys" model outputs reported in Mekonnen et al. (2021) to examine the importance of heat transfer from precipitation on permafrost degradation. The study highlighted the importance of mechanistically representing this process in earth system models (ESMs) and demonstrated that precipitation is as important an environmental control on permafrost degradation as surface air temperature. Included are (1) the modeled spatially averaged annual active layer depth (ALD) and daily maximum soil temperature across the North Slope of Alaska from 1980 to 2100, and (2) 25 km resolution modeled ALD for averaged for two time intervals, 2006 - 2010 and 2096 - 2100. The results are provided for two "ecosys" simulations: S1 with precipitation heat transfer and S2 without precipitation heat transfer across the North Slope of Alaska. These data are available in a NetCDF and csv data formats. 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↗

National Center for Airborne Laser Mapping (NCALM) LiDAR, Imagery, and DEM data from five NGEE Arctic Sites, Seward Peninsula, Alaska, August 2021

From August 8 through August 16 of 2021, airborne remote sensing data was collected by the National Center for Airborne Laser Mapping (NCALM) in collaboration with NGEE Arctic scientists. Data was collected around five NGEE Arctic study sites on the Seward Peninsula of Alaska: Teller mm 27, Teller mm 47, Kougarok mm 64, Kougarok mm 86, and Council mm 71. A Robinson R44 II helicopter with a RIEGL VQ-580 II airborne laser scanner was used to collect the LiDAR point cloud data for each study site. A Phase One iXM-RS100F camera was integrated with the Riegl sensor to collect RGB imagery. This data package contains LiDAR point clouds (.las), RGB imagery (tif), 1 m or 50 cm Digital Elevation Models (.tif) generated from the LiDAR data, and shapefiles of the .las tiling system for each site (.shp). Two supplemental documents are also included in the package: 1) a report describing data collection details, GNSS corrections, and processing steps and 2) a document describing the LiDAR Classification used (.pdf). This survey was conducted towards the end of the summer on the Seward Peninsula, and can be paired with data collected in April of 2022 during the snow-on campaign "National Center for Airborne Laser Mapping (NCALM) LiDAR and DEM data from two NGEE Arctic Sites, Seward Peninsula, Alaska, Winter 2022" (Singhania et.al, 2023) (NGA314). 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↗

Hot hydrogen in the exosphere of Venus

Lyman-alpha measurements of the hydrogen corona of Venus by Mariners 5 and 10 have been shown to be consistent with a two-temperature component model. Bertaux et al. (1978) have successfully fitted the Venera 9 exospheric Lyman-alpha data to an elevated (500 K) single temperature. Various source mechanisms have been proposed to explain the 'hot' (1000 K) energetic component of the hydrogen corona. In the present paper recent results from the Pioneer Venus Orbiter are used to establish the major sources of this hot hydrogen population.

Cravens, T. E.↗

Ground effects on the low-speed aerodynamics of a powered, generic hypersonic configuration

A study was undertaken in the NASA Langley 14- by 22-foot subsonic tunnel to determine the low-speed aerodynamic characteristics of a powered, generic, hypersonic configuration in ground effect. The model was a simplified configuration consisting of a triangular wedge forebody, a rectangular mid-section which housed the flow through, an ejector type propulsion simulation system, and a rectangular wedge afterbody. Additional model components included a delta wing, a rectangular wedge forebody, inlet fences, exhaust flow deflectors, and afterbody fences. Aerodynamic force and moment data were obtaind over an angle of attack range from -4 to 18 degrees while model height above the tunnel floor was varied from 1/4 inch to 6 feet. Variations in freestream dynamic pressure, from 10 psf to 80 psf, and engine ejector pressure yielded a range of thrust coefficients from 0 to 0.8.

Gatlin, Gregory M.↗

Implementation of the University of Miami Wave Model (UMWM) into the NASA/GMAO Goddard Earth Observing System Model (GEOS)

Wind generated waves are integral element in air-sea interactions and affect exchange of momentum, heat, water, gases and production of marine aerosol. Motivated by the need to resolve the air-sea interface we have implemented the University of Miami Wave model (UMWM) into the NASA/GMAO Goddard Earth Observing System Model (GEOS). The implementation of the wave model in GEOS aimed to facilitate coupling with the atmosphere and ocean model components with minimal changes to the existing system, while at the same time ensure correctness of the predicted wave energy spectrum and wave diagnostics. Here we describe the implementation of the GEOS/UMWM system and show results from model experiments and verifications. This work is a step toward development of a coupled atmosphere-wave-ocean GEOS system.

Darmenov, Anton↗

Topographical Controls on Hillslope-Scale Hydrology Drive Shrub Distributions on the Seward Peninsula, Alaska: Modeling Archive

The dataset is a model output used in a study that examined the role topography plays in determining shrub expansion by applying a coupled transect version of a mechanistic ecosystem model (ecosys) in a tundra hillslope site in the Seward Peninsula, Alaska. The study highlights the importance of mechanistically representing hillslope-scale coupled surface and sub-surface hydrology to accurately predict current plant distributions and future trajectories in Arctic ecosystems. The dataset contain ecosys model outputs used in a study: Article Title - Topographical Controls on Hillslope-Scale Hydrology Drive Shrub Distributions on the Seward Peninsula, Alaska. It includes the data files (ten *.csv files) used in creating figures in the publication and three *.pdf files (user guide and two Supplementary Information documents).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↗

Observing Human-induced Linkages between Urbanization and Earth's Climate System

Urbanization is one of the extreme cases of land use change. Most of world s population has moved to urban areas. Although currently only 1.2% of the land is considered urban, the spatial coverage and density of cities are expected to rapidly increase in the near future. It is estimated that by the year 2025, 60% of the world s population will live in cities. Human activity in urban environments also alters atmospheric composition; impacts components of the water cycle; and modifies the carbon cycle and ecosystems. However, our understanding of urbanization on the total Earth-climate system is incomplete. Better understanding of how the Earth s atmosphere-ocean-land-biosphere components interact as a coupled system and the influence of the urban environment on this climate system is critical. The goal of the 2003 AGU Union session Human-induced climate variations on urban areas: From observations to modeling was to bring together scientists from interdisciplinary backgrounds to discuss the data, scientific approaches and recent results on observing and modeling components of the urban environment with the intent of sampling our current stand and discussing future direction on this topic. Herein, a summary and discussion of the observations component of the session are presented.

Shepherd, J. Marshall↗

An Empirical Correction Method for Improving off-Axes Response Prediction in Component Type Flight Mechanics Helicopter Models

Historically, component-type flight mechanics simulation models of helicopters have been unable to satisfactorily predict the roll response to pitch stick input and the pitch response to roll stick input off-axes responses. In the study presented here, simple first-order low-pass filtering of the elemental lift and drag forces was considered as a means of improving the correlation. The method was applied to a blade-element model of the AH-64 APache, and responses of the modified model were compared with flight data in hover and forward flight. Results indicate that significant improvement in the off-axes responses can be achieved in hover. In forward flight, however, the best correlation in the longitudinal and lateral off-axes responses required different values of the filter time constant for each axis. A compromise value was selected and was shown to result in good overall improvement in the off-axes responses. The paper describes both the method and the model used for its implementation, and presents results obtained at hover and in forward flight.

Mansur, M. Hossein↗

Neural simulation-based inference approach for characterizing the Galactic Center γ-ray excess

The nature of the Fermi γ-ray Galactic Center Excess (GCE) has remained a persistent mystery for over a decade. Although the excess is broadly compatible with emission expected due to dark matter annihilation, an explanation in terms of a population of unresolved astrophysical point sources e.g., millisecond pulsars, remains viable. The effort to uncover the origin of the GCE is hampered in particular by an incomplete understanding of diffuse emission of Galactic origin. This can lead to spurious features that make it difficult to robustly differentiate smooth emission, as expected for a dark matter origin, from more “clumpy” emission expected from a population of relatively bright, unresolved point sources. Here, we use recent advancements in the field of simulation-based inference, in particular density estimation techniques using normalizing flows, in order to characterize the contribution of modeled components, including unresolved point source populations, to the GCE. Compared to traditional techniques based on the statistical distribution of photon counts, our machine learning-based method is able to utilize more of the information contained in a given model of the Galactic Center emission, and in particular can perform posterior parameter estimation while accounting for pixel-to-pixel spatial correlations in the γ-ray map. This makes the method demonstrably more resilient to certain forms of model misspecification. On application to Fermi data, the method generically attributes a smaller fraction of the GCE flux to unresolved point sources when compared to traditional approaches. We nevertheless infer such a contribution to make up a non-negligible fraction of the GCE across all analysis variations considered, with at least $38^{+9}_{-19}$% of the excess attributed to unresolved point sources in our baseline analysis.

79 ASTRONOMY AND ASTROPHYSICS↗

Snow distribution patterns revisited: A physics-based and machine learning hybrid approach to snow distribution mapping in the sub-Arctic Supporting Data

Snow in the Arctic and sub-Arctic is highly variable at fine scales, with deep drifts and shallow scoured areas creating a complex pattern of snow on the landscape. This fine-scale variation in snow is driven primarily by landscape and vegetation properties. Some landscape features, such as river beds, will rapidly fill in with snow during the wintertime due to high winds, while shrubs will trap blowing snow, resulting in drifts. Meanwhile, snow will blow off of exposed areas, resulting in abnormally shallow snow. These complex interactions between wind, vegetation, and terrain are difficult to represent well with physically-based models, but machine learning techniques have shown promise in the past. Here, we propose a hybrid modeling approach, where we use machine learning derived snow pattern maps to inform SnowModel, a physically-based snow process model. We develop and test this technique at the Teller 27 Seward Peninsula NGEE-Arctic study site. This dataset includes 5 *.nc files of model inputs and outputs plus one user guide (*.pdf). We present the data we use to drive SnowModel (vegetation type, digital elevation model), the snow pattern maps used to inform SnowModel (Standardized Depth Values maps, Machine Learning Snow Distribution Pattern), and our machine learning, SnowModel, and Hybrid snow depth and snow water equivalent results. The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), 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↗

Analysis of the solar magnesium lines

The observed quiet-sun profiles for a number of Mg I and II lines are compared with theoretical spectra computed for two upper-photosphere lower-chromosphere models published by Ayres and Linsky (1976). Both the Mg I and the Mg II resonance line wings, observed with the University of Hawaii Echelle Rocket Spectrographs, favor a model with a higher temperature in the upper photosphere than required to match the visible region lines 4571 and 5172. Neither model atmosphere reproduces the observed shapes in the cores of the strong lines or the limb darkening of the 4571 A intercombination line. The wings of the ultraviolet lines in plages can be reproduced either with a mean one-component atmosphere or by a two-component model with an ad hoc filling factor.

Heasley, J. N.↗

Stationary electrostatic solitary waves in the auroral plasma

Time-stationary fluid equations are used to describe electrostatic solitons in an auroral plasma of cold ionospheric and hot plasma sheet particles. A one-dimensional fluid analysis of the four component model auroral plasma indicates that at least two different, weakly damped, small amplitude electrostatic solitons can propagate along the geomagnetic field. The slower of the two is a generalization of an ion-acoustic solitary wave in a multi-component plasma, and ion inertia is negligible for the faster mode which is supported by the two electron components and resembles a clump of shielded negative space charge convected by the drifting plasma sheet electrons. Some expected features of the large amplitude properties are indicated qualitatively, and an analogy is considered between the theory of ion-acoustic shocks and a theory of double layers.

Lotko, W.↗

Far-ultraviolet fluorescence of carbon monoxide in the red giant Arcturus. II - Analysis of high-dispersion IUE spectra

Faint, diffuse emissions near 1380 A in deeply exposed IUE spectrograms of the red giant Arcturus very likely are associated with bands of the A-X fourth-positive system of carbon monoxide, fluoresced by multiplet UV2 of neutral oxygen near 1305 A. Numerical simulations indicate that the strength of the CO bands is exceedingly sensitive, in the best available one-dimensional model of the chromosphere of Arcturus, to a delicate balance between the rapid inward attenuation of the oxygen radiation field and the rapid outward decline of the molecular absorptivity. The fortuitous character of the overlap region in the single-component model argues that one should also consider the possibility that the pumping occurs in a highly inhomogeneous chromosphere, of the type proposed in previous studies of Arcturus based on observations of the infrared absorption bands of CO.

Ayres, T. R.↗

Carbon storage cost modeling for the offshore Gulf of Mexico

Groundbreaking for geologic carbon storage (GCS) projects in the offshore Gulf of Mexico is imminent, and there is great interest in utilizing this region for GCS projects. Offshore saline reservoirs provide a significant and accessible resource for GCS. However, conducting GCS in the offshore environment will pose distinct challenges pertaining to site selection, operations, infrastructure use, and monitoring compared to operating onshore that ultimately affect technoeconomic assessment of offshore GCS projects. Carbon storage and transport costs are critical to project developers looking to deploy carbon storage in the offshore environment. We present CO2_S_COM_Offshore, a model developed by the National Energy Technology Laboratory (NETL) as a screening-level offshore saline GCS cost modeling tool. Based on NETL’s widely used CO2_S_COM cost model for onshore saline CS, CO2_S_COM_Offshore enables technoeconomic analysis of GCS in offshore areas. This model comprehensively incorporates multiple facets of offshore GCS projects, from regional evaluation and site selection to permitting, transport, operations, monitoring, site closure, and decommissioning. In general, the model can explore the cost implications for potential offshore GCS project(s) by enabling the user to change several project operational and financial attribute configurations. Key inputs include offshore storage formation options, CO2 injection rate and duration, infrastructure types, monitoring intensity, project financing, and post-injection site care duration. Supporting cost algorithms within CO2_S_COM_Offshore were compiled utilizing S&P Global’ s QUE$TORTM cost estimation software alongside a variety of open-source scientific literature. In addition to reviewing key model components, we discuss several sensitivity analyses, input variabilities, and results on analysis of break-even CO2 price required by a project based on different regulation/policy and operational scenarios for the offshore Gulf of Mexico. These results indicate the value of modeling offshore GCS specifically, and the potential of offshore GCS within a decarbonization value chain. Presented at the 41st USAEE/IAEE North American Conference, 3-6 November 2024, Baton Rouge, LA, United States.

Mark-Moser, Mackenzie K.↗

Modeling and Validation of a Residential Multi-Functional Variable Refrigerant Flow Heat Pump System with Heat Recovery

To bridge the existing gap in modeling the variable refrigerant flow heat pump systems with heat recovery (VRFHR), we developed a suite of dynamic VRFHR system models in Modelica. These models are specifically tailored for residential multi-functional VRFHR (MF-VRFHR) applications, including space conditioning and domestic hot water (DHW) heating, utilizing both the TIL library for HVAC equipment and the Buildings library for thermal load calculations. The development comprises essential component models, including the newly developed heat recovery unit (HRU), along with system models that integrate the heat pump system and building envelope. These system models accommodate various operational modes such as heating-only, cooling-only, and heating-recovery (including heating-dominant and cooling-dominant) modes. Furthermore, we propose an efficient optimization-based model calibration method that identifies critical model parameters while utilizing a small amount of data obtained from either real systems or manufacturer's specifications. We demonstrate the effectiveness of these models and the proposed calibration method for a MF-VRFHR system installed in Richland, WA. The developed models are calibrated and validated using data collected under different operational modes during both heating and cooling seasons. The results show that the models capture the system dynamics and achieve high accuracy, with the coefficient of the variation of the root-mean-square-error less than 15% for variables such as outdoor unit power consumption, compressor speed, space temperature and DHW temperature. The validated models serve as a reliable representation of the MF-VRFHR system, facilitating the development and validation of optimized controls needed to realize the full benefits of integrated heat pump systems. Future research will utilize these models to develop advanced controls and optimize system performance for improved energy efficiency and demand flexibility.

Modeling, Variable refrigerant flow (VRF) systems,↗

Expansion of high-latitude deciduous forests driven by interactions between climate warming and fire: Modeling Archive

This Modeling Archive is in support of an NGEE Arctic publication. More information in the related references. The dataset is a model (ecosys) output used in a study that examined the potential future shifts in high-latitude vegetation types (PFTs) driven by changes in 21st century climate and fire. The study highlights the importance of mechanistically representing differences in plant functional traits on current and possible 21st century trajectories of Alaskan PFTs. This dataset package includes 13 files in pdf, csv, and nc formats.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↗

Rapidly changing high-latitude seasonality: Implications for the 21st century carbon cycle in Alaska: Modeling Archive

This Modeling Archive is in support of an NGEE Arctic publication "Rapidly changing high-latitude seasonality: Implications for the 21st century carbon cycle in Alaska" DOI: 10.1088/1748-9326/ac4362.The dataset contains "ecosys" model outputs reported in Shirley et al. (2022) that explored how climate warming will shift carbon cycle seasonality in Alaska. The study used analysis of seasonal dynamics to support the prediction that high-latitude ecosystems are carbon sinks and will continue to accumulate carbon throughout the century. The study predicts surprisingly large increases in spring net carbon uptake that result in larger net carbon uptake in spring than in summer by year 2100. Included as *.nc files are modeled daily net ecosystem exchange (NEE), net primary productivity (NPP), heterotrophic respiration (Rh), autotrophic respiration (Ra), gross primary productivity (GPP), and plant nitrogen uptake. The output is provided (1) at 25 km resolution across Alaska; (2) for years 2010 through 2100. Scripts to generate publication figures included as text files (*.m) from MATLAB. A user guide included as *.pdf.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↗