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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 181 records · Page 10
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Leaf structural and chemical traits, and vegetation temperature and height, Seward Peninsula, Alaska, 2019.

Leaf nitrogen and carbon content, leaf water content (LWC) and leaf mass per area (LMA) of leaves, and vegetation height and temperatures sampled from locations on the Teller MM 27, Kougarok MM 64 and Kougarok MM 80 NGEE Arctic sites, Seward Peninsula, Alaska. These data were collected in support of ongoing NASA ABoVE AVIRIS data synthesis work. Samples were collected in July 2019 from 24 species. This data package includes leaf sample information and vegetation trait data (*.csv). Metadata files include data descriptions (_dd.csv) for tabular data and a key to species symbols used in data files. All included files are listed and described in NGA210_flmd.csv. See data package NGA212 "Full spectrum 350-2500 nm leaf and canopy spectral reflectance, Seward Peninsula, Alaska, 2019" for linked spectral reflectance data. 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 OSTI2022

UAS remote sensing (DJI Phantom 4 RTK platform): RGB orthomosaic, digital surface and canopy height models, plant functional type map, Seward Peninsula, Alaska, 2019

Airborne remote sensing data collected using a DJI Phantom 4 RTK unoccupied aerial system (UAS) ? operated by the University of Maine Wheatland Geospatial Lab (https://wheatlandlab.org/). This package includes data from 17 flights flown over the NGEE-Arctic Council, Kougarok, Kougarok Mile80, Teller, and Teller Mile32 sites in July 2019. The Phantom 4 RTK is a drone platform that collects very high spatial resolution optical red/green/blue (RGB) imagery. Derived image products include point cloud, ortho-mosaiced RGB, a digital surface model (DSM) using the structure from motion (SfM) technique, and a canopy height model (CHM). Unprocessed and processed data products (1,000+ files) are included in this package (processing levels 0-3). Data and metadata are provided as text (*.txt, *.json, *hdr,), ENVI image file (*.dat), point cloud (*.laz) and image (*.jpg, *.tif, *png) 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↗
DOE OSTI2023

UAS remote sensing (3DR SOLO platform): multispectral reflectance, canopy height model, normalized difference vegetation index, Seward Peninsula, Alaska, 2021

Airborne remote sensing data collected using a Parrot Sequoia+ multispectral sensor installed on a 3DR SOLO unoccupied aerial system (UAS) - operated by the Terrestrial Ecosystem Science Technology group at Brookhaven National Laboratory. This package includes data from 10 flights flown over the NGEE-Arctic Council Mile Marker (MM) 71, Kougarok MM64, and Teller MM27 sites on the Seward Peninsula, Alaska, in August 2021. Derived image products include point cloud, ortho-mosaiced multispectral image, ortho-mosaiced RGB image, a digital surface model (DSM) using the structure from motion (SfM) technique, a canopy height model (CHM), and a normalized difference vegetation index (NDVI) map. Unprocessed and processed data products are included in this package (processing levels 0-2). Data and metadata are provided as text (*.txt, *.json, *hdr,), tabular (*.dat, *.csv), point cloud (*.laz), Cloud Optimized GeoTIFF (COG, *.tif), and image (*.jpg, *.tif, *png) 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↗
DOE OSTI2022

Modeled Hourly Tidal Current Velocities, Directions, and Heights from May 1 - September 1, 2005 at Two Points Near East Forelands and Tyonek in Cook Inlet, Alaska

This dataset includes modeled tidal current velocities, direction and depth at two locations in East and North Forelands (60.716, -151.434 and 61.024, -151.157) near Nikiski and Tyonek, respectively, in Cook Inlet, Alaska. Data from two grid cells were provided by the Pacific Northwest National Laboratory based on a tidal hydrodynamic model that characterized the tidal stream resources in Cook Inlet for a period from May 1 to September 1, 2005 (Wang and Yang 2020). The model grid size had a horizontal spatial resolution of 100 m at East Forelands and 200 m at Tyonek; mean sea level (MSL) depth was 47.9 m and 23.7 m at each respective site, and there were 10 depth bins that ranged in size with the tide from 4.3-5.2 m and 1.9-2.8 m, respectively (Wang and Yang 2020).

16 TIDAL AND WAVE POWER↗
DOE OSTI2023

Planetary Boundary Layer Height (PBLH) over SGP from 1998 to 2023

PBLH is a critical parameter influencing weather phenomena, air quality, and various meteorological processes. However, accurately retrieving PBLH has been a challenging task due to limitations such as coarse temporal resolution and measurement drift in traditional radiosonde observations. To address these limitations, we have devised a lidar-based methodology that capitalizes on a newly developed algorithm for PBLH retrieval. This algorithm demonstrates enhanced capabilities in capturing diurnal fluctuations in PBLH compared to existing lidar-based methods (Su et al. 2020). In addition, we have refined this algorithm specifically for PBLH retrieval under cloudy conditions through a novel scheme (Su et al. 2022). To ensure data reliability, a quality-control process has been implemented to filter out questionable data points. Accompanying the data set is a quality-control flag for ease of reference. It should be noted that we have assimilated all available radiosonde observations to provide a more robust estimate of PBLH, making the data set valuable for a variety of related studies.

54 ENVIRONMENTAL SCIENCES↗