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All sources NASA NTRS DOE OSTI

DOE OSTI2022

L0 Data from the 2018 NGEE Arctic LiDAR and Imagery Unoccupied Aerial System Campaign at the Teller 47 Field Site, Seward Peninsula, Alaska

Airborne remote sensing data collected from Los Alamos National Laboratory's (LANL) heavy-lift unoccupied aerial system (UAS) hexacopter platform operated by NGEE Arctic scientists from EES-14 (Earth System Observations group) at Los Alamos National Laboratory. These data were collected in July 2018 at a field site near mile marker 47 along the Teller road between Nome, Alaska and Teller, Alaska. A DJI Matrice 600 Pro Airframe and Routescene UAV LiDARSystem was used to collect LiDAR data, and DJI Phantom 4 Advanced was used to collect optical red/green/blue (RGB) imagery at regular intervals along 11 flight paths. This data package contains unprocessed data products (processing level 0) including flight paths, raw photos, and raw lidar data files (*.kml, *.jpg, and *.lpd formats). Ancillary aircraft data, flight mission parameters, and general flight conditions are also included (see Supplemental Files, *.rinex, and *.rtcm3 files). 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↗

DOE OSTI2025

Electrical Resistivity Tomography data from 2016 to 2018 at the Lower Montane site in the East River Watershed, Colorado

This dataset contains time-lapse Electrical Resistivity Tomography (ERT) data along a transect located on the northeast-facing hillslope at the lower montane site (Pumphouse site) in the upper East River Watershed. The monitoring dataset covers the period from November 2, 2016, to August 6, 2018. In addition, the archive also contains a baseline dataset from October 9, 2016. The ERT transect consisted of 128 electrodes with an electrode spacing of 1.25 m. The acquisition system was located in the middle of the transect, about 50 m on one side, and included an MPT (Multi-Phase Technologies) ERT system, a mini computer, and batteries with solar panels. Acquisition occurred daily under normal circumstances. The first 16 electrodes (from the upper end of the transect) could not be used after the cable was damaged during the 2017–2018 winter. Also, due to multiple failures in the power system, the temporal resolution of the data is much lower in 2018 compared to 2016 and 2017. The data have been processed and used in Dafflon et al., 2023, and the baseline dataset was used in Falco et al., 2019 (see reference list). This archive contains the measurements (ER.zip containing csv files) for each of the 326 acquisition times and a filtered version where only electrodes 17 to 128 are included (ERT_sm.zip containing csv files). The archive also contains the baseline dataset and two acquisitions with full reciprocals (ERT_RB.zip containing csv files), as well as all the raw MPT files (ERT_raw_MTP.zip). The geometry (electrode position and elevation) is provided in Universal Transverse Mercator (UTM) 13N Geoid2012AB in the file named ERT_Location.csv. The archive contains 1 *.csv data files, four *.zip files, and three metadata *.csv files. This work was supported by the Watershed Function Science Focus Area at Lawrence Berkeley National Laboratory funded by the US Department of Energy, Office of Science, Biological and Environmental Research under Contract No. DE-AC02-05CH11231.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS2000

Autonomous, Full-Time Cloud Profiling at Arm Sites with Micro Pulse Lidar

Since the early 1990's technology advances permit ground based lidar to operate full time and profile all significant aerosol and cloud structure of the atmosphere up to the limit of signal attenuation. These systems are known as Micro Pulse Lidars (MPL), as referenced by Spinhirne (1993), and were first in operation at DOE Atmospheric Radiation Measurement (ARM) sites. The objective of the ARM program is to improve the predictability of climate change, particularly as it relates to cloud-climate feedback. The fundamental application of the MPL systems is towards the detection of all significant hydrometeor layers, to the limit of signal attenuation. The heating and cooling of the atmosphere are effected by the distribution and characteristics of clouds and aerosol concentration. Aerosol and cloud retrievals in several important areas can only be adequately obtained with active remote sensing by lidar. For cloud cover, the height and related emissivity of thin clouds and the distribution of base height for all clouds are basic parameters for the surface radiation budget, and lidar is essetial for accurate measurements. The ARM MPL observing network represents the first long-term, global lidar study known within the community. MPL systems are now operational at four ARM sites. A six year data set has been obtained at the original Oklahoma site, and there are several years of observations at tropical and artic sites. Observational results include cloud base height distributions and aerosol profiles. These expanding data sets offer a significant new resource for cloud, aerosol and atmospheric radiation analysis. The nature of the data sets, data processing algorithms, derived parameters and application results are presented.

Spinhirne, James D.↗

NASA NTRS2002

Site distribution and aliasing effects in the inversion for load coefficients and geocenter motion from GPS data

Precise GPS measurements of elastic relative site displacements due to surface mass loading offer important constraints on global surface mass transport. We investigate effects of site distribution and aliasing by higher- degree (n ≥ 2) loading terms on inversion of GPS data for n = 1 load coefficients and geocenter motion. Covariance and simulation analyses are conducted to assess the sensitivity of the inversion to aliasing and mismodeling errors and possible uncertainties in the n = 1 load coefficient determination. We found that the use of center-of-figure approximation in the inverse formulation could cause 10– 15% errors in the inverted load coefficients. n = 1 load estimates may be contaminated significantly by unknown higher-degree terms, depending on the load scenario and the GPS site distribution. The uncertainty in n = 1 zonal load estimate is at the level of 80–95% for two load scenarios.

Webb, Frank H.↗

DOE OSTI2024

Continuous snow depth, ground interface temperature and shallow soil temperature measurements from 2021-10-1 to 2022-6-14, Seward Peninsula, Alaska

The dataset contains co-located snow depth, ground interface temperature, and shallow soil temperature measured at 98 discrete locations in a watershed located along the Nome-Teller road at mile marker 27 (referred to as T27), and at 53 discrete locations on a hillslope located along the Kougarok road at mile marker 64 (referred to as K64), in Seward Peninsula, Alaska. The dataset aims to understand the local heterogeneity of snow depth, snow temperature, and soil temperature dynamics and their interactions in a discontinuous permafrost region. The dataset is also valuable to train and evaluate machine learning and physical models to predict snow depth or the impact of snow depth on ground surface temperature. At each location, temperatures above and below the ground surface were measured by a pair of vertically deployed distributed temperature profiling probes designed based on Dafflon et al (2022). The probes have high precision temperature sensors spaced at 5 or 10 cm. The mean daily snow depth was estimated by identifying the pair of consecutive sensors with maximum drop of daily temperature high-frequency fluctuations. The ground interface temperature was measured by the sensor located 1-5 cm above the ground surface at 15-minute intervals. The shallow soil temperature was measured by the sensor located 1-5 cm below the ground surface at 15-minute intervals. The dataset includes a description of the probe locations in the "Probe_locations_*.csv" file and the 3 data files (Snow_depths_*.csv, Ground_interface_temperatures_*.csv, Shallow_soil_temperatures_*.csv). * is either T27 or K64, which are the two study sites. In each data file, each column corresponds to a measurement location. Metadata files include data descriptions (_dd.csv) for tabular data. All included files are listed and described in xxxx_flmd.csv. A more detailed description of data processing, along with an updated dataset incorporating multiple seasons and improved snow depth estimation is available at https://doi.org/10.15485/2480365 (Wang et al., 2025a, Wang et al., 2025b).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↗

DOE OSTI2024

AWAKEN Site A1 HALO XR Lidar (Cornell University) / Raw Data

These data are scanning Doppler lidar measurements from the deployment of a HALO XR at AWAKEN site A1. The measurements include calibrated beam azimuth angles, radial velocity, backscatter, signal to noise ratio per each line of sight, and range-gate.

17 WIND ENERGY↗

DOE OSTI2024

AWAKEN Site H HALO XR Lidar (Cornell University) / Raw Data

These data are scanning Doppler lidar measurements from the deployment of a HALO XR at AWAKEN site H. The measurements include calibrated beam azimuth angles, radial velocity, backscatter, signal to noise ratio per each line of sight, and range-gate.

17 WIND ENERGY↗

NASA NTRS1988

Requirements for ongoing development of the Pilot Land Data System (PLDS)

The Pilot Land Data System being developed to address the information processing needs of the NASA land sciences research community is presented. The objective of the pilot program is to establish a limited-scale, distributed information system for the archival, location, transfer, integration, and manipulation of data across multiple sites connected by a high-speed communications network. Functional capabilities required for users to create, access, and maintain local and distributed data bases containing various types of data in support of land sciences research are summarized.

Wharton, S. W.↗

NASA NTRS2002

Use of GPR Surveys in Historical Archaeology Studies at Gainesville Mississippi

Ground Penetrating Radar (GPR) was used in recent surveys to acquire subsurface geophysical data for historic sites at Gainesville, Mississippi, a town abandoned in 1962 with the building of the John C. Stennis Space Center. Prior to GPR data collection, a 20- by 20-meter grid was established using UTM map projection and GPS for locating cell corners. Lines of GPR data were then collected every 25 centimeters. The images were then processed, and coregistered to georeferenced aerial and satellite imagery. This procedure is enabling analysts to assess the GPR imagery more effectively in a geospatial context. Field validation of anomalies created by known subsurface features from both recent and historic sources is allowing soil attributes, such as variations in Relative Dielectric Permittivity, to be tested more accurately. Additional work is assessing how GPR data can be effectively combined with other forms of remote sensing to direct archaeological surveys and excavations.

Goodwin, Ben↗

DOE OSTI2026

SULI End of Summer Presentation

This presentation made on Power Point is a brief summary of my work enhancing the Supervisory Control and Data Acquisition (SCADA) architecture for Idaho National Lab’s Critical Infrastructure Test Range Complex (CITRC). This work was part of an on-going project to create a digital twin of CITRC that will be implemented for resiliency research. Resiliency is growing more important as extreme weather, aging infrastructure, and increasing load all exert stress on the United States power grid. This presentation highlights how I documented the existing devices and data flow on site and then updated specific device settings to better support the needs of the project. It also examines future use of this data in the digital twin data warehouse (DeepLynx), and future Artificial Intelligence and Advanced Distribution Management System applications. It will be presented to the B751 Water and Energy Systems Analysis group at INL during my last week.

24 - POWER TRANSMISSION AND DISTRIBUTION↗

NASA NTRS2009

Aerosol-Cloud Interaction Determined by Both in Situ and Satellite Data Over a Northern High-Latitude Site

The first aerosol indirect effect over a clean, northern high-latitude site was investigated by determining the aerosol cloud interaction (ACI) using three different approaches; ground-based in situ measurements, combined ground-based in situ measurements 5 and satellite retrievals and using only satellite retrievals. The obtained values of ACI were highest for in situ ground-based data, clearly lower for combined ground-based and satellite data, and lowest for data relying solely on satellite retrievals. One of the key findings of this study was the high sensitivity of ACI to the definition of the aerosol burden. We showed that at least a part of the variability in ACI can be explained by 10 how different investigators have related dierent cloud properties to "aerosol burden".

Lihavainen, H.↗

DOE OSTI2020

Trace Metal Content and Speciation, Water and Soil Chemistry, and Methane Production for a Wetland in Missouri (September 2015) and in Florida (January 2016)

Data is associated with a manuscript in preparation for submission to explore whether low trace metal availability inhibits methane production in freshwater wetland soils. Reported data are from two field sites, one in Missouri and the second in Florida (see location data). At each site, surface water compositions and properties and soil compositions are reported. Trace metal availability is assessed via sequential chemical extractions, Ni K-edge X-ray absorption near edge structure (XANES) spectroscopy, and X-ray microfluorescence imaging. Soil mineralogy is determined via powder X-ray diffraction. Multi-energy X-ray microfluorescence imaging as well as bulk and microscale S K-edge XANES spectra assess sulfur speciation in the soils. This package also reports data from trace metal amendment experiments, specifically methane (CH4) production versus time in soil incubations, the dissolved trace metal concentrations in these incubations, and the Ni K-edge XANES and extended X-ray absorption fine structure (EXAFS) spectra of soils to which increasing concentrations of Ni were added. A final version of this package will be published upon acceptance of the associated manuscript.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2020

Opportunities for an Integrated Web-Based Workbench for Data Access and Analysis - 20244

Management of environmental issues can require integration of multiple types of data and information, conducting data analysis and interpretation, and providing data visualization for effective communications. These data elements are important for site management to support regulator interactions and provide defensibility for remedial decisions. Databases and information repositories are core elements of managing data; however, efficient data access and analysis also enable effective site management. The U.S. Department of Energy (DOE) Hanford Site is an example of a complex site with a voluminous quantity of environmental data and a need for efficient site management. Different tiers of data and information tools have been developed and deployed to address site needs. These tools are configured for ready access via the web site interfaces and meet the rigorous quality requirements for environmental site management. Evolving efforts are focused on an integrated platform to meet site environmental management needs. In this platform, users can access site information at multiple levels of detail based on their need and permissions, so that data and associated analyses are presented within the context of the site mission and the user's management or technical needs. This concept is not only applicable at individual sites like Hanford but also applicable at other sites within the DOE complex. An integrated web-based architecture that links data visualization, data analytics, and management tools can provide holistic access to large data sets, minimize complexity, and maximize interactivity and technical communication. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

NASA NTRS2002

Site Distribution and Aliasing Effects in the Inversion for Load Coefficients and Geocenter Motion from GPS Data

Precise GPS measurements of elastic relative site displacements due to surface mass loading offer important constraints on global surface mass transport. We investigate effects of site distribution and aliasing by higher-degree (n greater than or equal 2) loading terms on inversion of GPS data for n = 1 load coefficients and geocenter motion. Covariance and simulation analyses are conducted to assess the sensitivity of the inversion to aliasing and mismodeling errors and possible uncertainties in the n = 1 load coefficient determination. We found that the use of center-of-figure approximation in the inverse formulation could cause 10- 15% errors in the inverted load coefficients. n = 1 load estimates may be contaminated significantly by unknown higher-degree terms, depending on the load scenario and the GPS site distribution. The uncertainty in n = 1 zonal load estimate is at the level of 80 - 95% for two load scenarios.

global positioning system↗

DOE OSTI2023

Standardized Data to Improve Understanding and Modeling of Soil Nitrogen at Continental Scale

Abstract Nitrogen (N) is a key limiting nutrient in terrestrial ecosystems, but there remain critical gaps in our ability to predict and model controls on soil N cycling. This may be in part due to lack of standardized sampling across broad spatial–temporal scales. Here, we introduce a continentally distributed, publicly available data set collected by the National Ecological Observatory Network (NEON) that can help fill these gaps. First, we detail the sampling design and methods used to collect and analyze soil inorganic N pool and net flux rate data from 47 terrestrial sites. We address methodological challenges in generating a standardized data set, even for a network using uniform protocols. Then, we evaluate sources of variation within the sampling design and compare measured net N mineralization to simulated fluxes from the Community Earth System Model 2 (CESM2). We observed wide spatiotemporal variation in inorganic N pool sizes and net transformation rates. Site explained the most variation in NEON’s stratified sampling design, followed by plots within sites. Organic horizons had larger pools and net N transformation rates than mineral horizons on a sample weight basis. The majority of sites showed some degree of seasonality in N dynamics, but overall these temporal patterns were not matched by CESM2, leading to poor correspondence between observed and modeled data. Looking forward, these data can reveal new insights into controls on soil N cycling, especially in the context of other environmental data sets provided by NEON, and should be leveraged to improve predictive modeling of the soil N cycle.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2023

WHONDRS Surface Water Dissolved Organic Carbon and FTICR-MS across Glacial Features in Svalbard 2022

This dataset supports a broader study examining climatic forcing of terrestrial greenhouse gas emission through permafrost and glaciers in Svalbard. The dataset provides geochemistry and organic matter characterization data generated from surface water collected from 11 sites across central Svalbard. Data were also collected in 2021 and can be found at https://data.ess-dive.lbl.gov/view/doi:10.15485/1888571. Additional related data were collected and will be published separately in collaboration with Yde and Kleber.This dataset is comprised of one main data folder containing (1) file-level metadata; (2) data dictionary; (3) field metadata; (4) dissolved organic carbon (DOC; measured as non-purgeable organic carbon; NPOC); (5) surface water sampling protocol; (6) readme; (7) methods codes; (8) international geo-sample number (IGSN) mapping file; (9) a folder of field photos; and (10) folder of high resolution characterization of organic matter via 7 Tesla Fourier transform ion cyclotron resonance mass spectrometry (FTICR-MS) generated through the Environmental Molecular Sciences Laboratory (EMSL; https://www.pnnl.gov/environmental-molecular-sciences-laboratory). The FTICR folder contains two subfolders, one containing the .xml data files and the other containing instructions for using Formularity (https://omics.pnl.gov/software/formularity) and an R script to process the data based on the user's specific needs. All files are .csv, .pdf, .R, .ref, or .xml.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2021

Discovering Hidden Geothermal Signatures using Unsupervised Machine Learning

Discovering hidden geothermal resources is a very challenging task. It requires the mining of large datasets, including various diverse data attributes representing subsurface hydrogeological and geothermal conditions. The commonly used Play Fairway Analysis (PFA) typically relies on subject-matter expertise to analyze site or regional data to estimate geothermal conditions and prospectivity. Here, we demonstrate an alternative approach based on machine learning (ML) to process a geothermal dataset of Southwest New Mexico (SWNM). The study region includes low- and medium-temperature hydrothermal systems. However, most of these systems are poorly characterized because of insufficient existing data and limited past explorative studies. This study aims to discover hidden patterns and relationships in the SWNM geothermal dataset to better understand regional hydrothermal conditions. This is achieved by applying an unsupervised machine learning algorithm based on non-negative matrix factorization coupled with customized k-means clustering (NMFk). NMFk can automatically identify (1) hidden (latent) signatures characterizing datasets, (2) the optimal number of these signatures, (3) dominant data attributes associated with each signature, and (4) spatial distribution of the extracted signatures. Here, NMFk is applied to analyze 18 geological, geophysical, hydrogeological, geothermal attributes at 44 locations in SWNM. NMFk successfully finds data patterns and identifies the spatial associations of hydrothermal signatures with the four physiographic provinces in SWNM (Colorado Plateau, Volcanic Field, Basin and Range, and the Rio Grande rift). The algorithm identified up to 5 hydrothermal signatures in the SWNM datasets that differentiate between low- and medium-temperature hydrothermal systems in different provinces. Also, the algorithm identifies two medium-temperature hydrothermal systems in SWNM that require further exploration for geothermal resource development. Based on our analyses, 12 of the attributes are important to identify medium-temperature hydrothermal systems, and the remaining six attributes are critical to characterize low-temperature hydrothermal systems. Based on the obtained results, we identify potential physiographic provinces for further exploration to characterize them as geothermal resources. The resulting NMFk model can be applied to predict geothermal conditions and their uncertainties at new SWNM locations based on limited data from unexplored areas.

58 GEOSCIENCES↗

NASA NTRS1983

Mobile radio alternative systems study. Volume 1: Traffic model

The markets for mobile radio services in non-urban areas of the United States are examined for the years 1985-2000. Three market categories are identified. New Services are defined as those for which there are different expressed ideas but which are not now met by any application of available technology. The complete fulfillment of the needs requires nationwide radio access to vehicles without knowledge of vehicle location, wideband data transmission from remote sites, one- and two way exchange of short data and control messages between vehicles and dispatch or control centers, and automatic vehicle location (surveillance). The commercial and public services market of interest to the study is drawn from existing users of mobile radio in non-urban areas who are dissatisfied with the geographical range or coverage of their systems. The mobile radio telephone market comprises potential users who require access to the public switched telephone network in areas that are not likely to be served by the traditional growth patterns of terrestrial mobile telephone services. Conservative, likely, and optimistic estimates of the markets are presented in terms of numbers of vehicles that will be served and the radio traffic they will generate.

Tucker, W. T.↗