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At least 145 records · Page 8
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

UAS remote sensing (Autel EVO II platform): Red-green-blue (RGB) imagery and derived products (Level 0-2 data), Seward Peninsula, Alaska, 2023

Airborne remote sensing data collected using a optical red-green-blue (RGB) sensor installed on an Autel EVO II unoccupied aerial system (UAS). This package includes data from 4 flights flown over the NGEE-Arctic Council Mile Marker (MM) 71 and Teller MM27 sites on the Seward Peninsula, Alaska USA, in July 2023. This package provides the Level 0 (raw, unprocessed) data collected by the platform and sensors, and Level 1-2 processed products including digital surface models (DSM), photo orthomosaics, canopy height models (CHM) and digital terrain models (DTM). Ancillary aircraft data, flight mission parameters, and general flight conditions provided by the onboard flight and data collection computers are also included. Data and metadata are provided as image (*.jpg, *.tif), point cloud (*.laz), tabular (*.csv) and *.pdf formats. Raw images are compressed as tar.gz. The metadata documents contain flight campaign, platform, sensor, flight and file metadata, along with a description of the data and file naming scheme.The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a 15-year research effort (2012-2027) 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

UAS remote sensing (Autel EVO II platform): Red-green-blue (RGB) imagery and derived products (Level 0-2 data), Seward Peninsula, Alaska, 2022

Airborne remote sensing data collected using a optical red-green-blue (RGB) sensor installed on an Autel EVO II unoccupied aerial system (UAS). This package includes data from 15 flights flown over the NGEE-Arctic Council Mile Marker (MM) 71, Kougarok MM64, and Teller MM27 sites on the Seward Peninsula, Alaska USA, in July 2022. This package provides the Level 0 (raw, unprocessed) data collected by the platform and sensors, and Level 1-2 processed products including digital surface models (DSM), photo orthomosaics, canopy height models (CHM) and digital terrain models (DTM). Ancillary aircraft data, flight mission parameters, and general flight conditions provided by the onboard flight and data collection computers are also included. Data and metadata are provided as image (*.jpg, *.tif), point cloud (*.laz), tabular (*.csv) and *.pdf formats. Raw images are compressed as tar.gz. The metadata documents contain flight campaign, platform, sensor, flight and file metadata, along with a description of the data and file naming scheme.The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a 15-year research effort (2012-2027) 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

Thaw depth, soil moisture, and vegetation height, Teller and Kougarok sites, Seward Peninsula, Alaska, 2022

Thaw depth, soil moisture, and vegetation height sampled from locations on the Teller MM27, Kougarok MM80, and Kougarok MM82 NGEE-Arctic sites, Seward Peninsula, Alaska. These data were collected in support of the ongoing NGEE-Arctic and NASA ABoVE data synthesis work. Samples were collected in July 2022, including 6 transects covering the entire Teller MM27 watershed and 4 transects covering 4 thaw ponds at Kougarok MM80 and MM82. This data package includes sample information and thaw depth, soil moisture, vegetation height data (.csv). Metadata files include data descriptions (_dd.csv) for tabular data and file level metadata (.csv). 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 OSTI2025

NEPATEC2.0: NEPA Text Corpus v2.0

The National Environmental Policy Act of 1969, as amended (NEPA), is a major environmental law in the United States, requiring Federal agencies to consider and document potential environmental impacts before deciding on a proposed action. Modernization of NEPA and permitting processes faces significant challenges due to the lack of standardized formats and interoperable systems for organizing and sharing NEPA-related information across agencies. Much of the information gathered during NEPA reviews is written into documents such as categorical exclusions, environmental assessments, and environmental impact statements, then filed in predominately independent agency file stores that may or may not be publicly accessible. The application of metadata and data standards, such as those recommended by the Council on Environmental Quality (CEQ), to NEPA documents offers a shared vocabulary and structure for key entities like projects, processes, and documents that can streamline information exchange and enhance collaboration across systems. In this work, we publicly release NEPATEC2.0, an expanded corpus of NEPA documents with associated metadata. NEPATEC2.0 encompasses approximately 120,000 documents from 60,000 projects prepared by more than 60 different agencies. Modeled to align with CEQ metadata standards, NEPATEC2.0 promotes consistency in environmental reviews and supports the ongoing effort to modernize permitting technologies by facilitating more transparent, efficient, and data-driven decision-making. Importantly, NEPATEC2.0 demonstrates the possibilities and limitations of large language model-based prompting to extract information from NEPA documents at scale.

environmental review↗
DOE OSTI2024

Active Layer and Moisture Measurements for Intensive Site 0 and 1, Utqiagvik (Barrow), Alaska

Thaw depth, relative dielectric permittivity, and soil temperature were collected along three transects within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) near Utqiagvik (Barrow), Alaska. Measurements were acquired along the transect at 3 m intervals on 2011-09-25, 2011-09-26, 2012-07-18, 2012-09-30, 2014-07-02, 2014-08-15, and 2014-09-14 for the L2 transect (intensive site 0), which is about 470 m long. Similarly, measurements were collected every 3 m on 2012-09-30, 2013-09-30, 2014-07-02, 2014-08-14, and 2014-09-23, and every 1 m on 2013-09-30 along the AB transect (intensive site 1) which is about 500 m long. File types in the package are all csv spreadsheets, following the ESS-DIVE csv guidelines (ESS-DIVE CSV v1), organized by transect name, with accompanying data dictionary files containing the filename suffix "_dd" (also csv format). Data collection details can be found in the Methods description of the metadata record. 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 OSTI2020

Extending the Publish/Subscribe Abstraction for High-Performance I/O and Data Management at Extreme Scale

The Adaptable I/O System (ADIOS) represents the culmination of substantial investment in Scientific Data Management, and it has demonstrated success for several important extreme-scale science cases. However, looking towards the exascale and beyond, we see the development of yet more stringent data management requirements that require new abstractions. Therefore, there is an opportunity to attempt to connect the traditional realms of HPC I/O optimization with the Database / Data Management community. As such, in this paper we offer some specific examples from our ongoing work in managing data structures, services, and performance at the extreme scale for scientific computing. Using the publish/subscribe model afforded by ADIOS, we demonstrate a set of services that connect data format, metadata, queries, data reduction, and high-performance delivery. The resulting publish/subscribe framework facilitates connection to on-line workflow systems to enable the dynamic capabilities that will be required for exascale science.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗
DOE OSTI2025

dCache project status and update

The dCache project delivers an open-source, massively scalable, distributed storage system deployed internationally to satisfy today’s scientists’ ever-demanding storage requirements. Its multifaceted approach supports different use cases with the same storage, from high throughput data ingest, data sharing over wide area networks, efficient access from HPC clusters, and longterm data persistence on tertiary storage. Even though dCache was initially developed for HEP experiments, today, it is used by various scientific communities, including astrophysics, biomed, and life science, each with their specific requirements. To match the needs of these new communities and keep up with the scaling demands of existing experiments, dCache is permanently evolving. With this contribution, we would like to highlight the recent developments in dCache regarding integration with CERN Tape Archive (CTA), advanced metadata handling, token-based authorization support, bulk API for QoS transitions, REST API to control interaction with the tape system, and future development directions.

Mkrtchyan, Tigran [DESY]↗
DOE OSTI2021

Enabling modern data discovery for atmospheric measurements

The Atmospheric Radiation Measurement (ARM) user facility is a US Department of Energy Office of Science user facility that is managed and operated through a collaborative effort led by nine US Department of Energy national laboratories. The ARM Data Center, located at Oak Ridge National Laboratory, is responsible for the timely collection, processing, and delivery of data products to the scientific community. The ARM Data Center holds more than 11,000 data products, including metadata collected from field campaigns, instruments, value-added products, and principal investigator–contributed data. These data sets are checked for successful transfer (for most data, this transfer is carried out automatically via the network; however, some of the largest data sets and some of the most remote sites require manual shipping of hard disks) and both the data and metadata are processed to a standard format, which is an ARM-standardized structure, via the Network Common Data Form. The Network Common Data Form is a self-describing binary format with many compatible software tools. Once processed, the data are cataloged, stored in the ARM Data Archive, and made discoverable through association with an array of metadata-characterizing information, such as location and measurement classification. These metadata enable powerful search capabilities through the ARM Data Center Data Discovery interface. This paper discusses the workflow of how the new discovery system has been redesigned from user requirements and how the data are distributed to the scientific community.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

SPRUCE Peat Core Sample Collection Metadata, Marcell Experimental Forest, Minnesota, August 2025

This data set contains metadata associated with peat core samples collected from the Spruce and Peatland Responses Under Changing Environments (SPRUCE) experiment in August 2025. This sample metadata contains no analytical results and is a reference for analytical datasets. To ensure accessibility and discoverability, each sample was assigned an International Generic Sample Number (IGSN), a persistent identifier, using System for Earth and Extraterrestrial Sample Registration (SESAR). These samples were used for downstream analysis by multiple teams of researchers the results of which will be reported separately. This dataset contains one data file in comma separate (.csv) format. Additional metadata are provided: one data dictionary and a file-level metadata file in comma separate (.csv) format and a user guide in PDF (*.pdf) format. An aliquot of most samples is stored in the SPRUCE archive and may be available for further analysis by request. Access this collection event on SESAR https://doi.org/10.58052/IEJ9B05LW. To inquire about obtaining archived samples for analysis, reach out using the Contact Sample Owner form located on the bottom of the landing page in SESAR.

EARTH SCIENCE > BIOSPHERE > ECOSYSTEMS > TERRESTRI↗
DOE OSTI2025

SPRUCE: Shrub-Layer Vegetation Biomass Collection Metadata, Marcell Experimental Forest, Minnesota, August 2025

This data set contains metadata associated with shrub-layer vegetation samples collected from the Spruce and Peatland Responses Under Changing Environments (SPRUCE) experiment in August 2025. This sample metadata contains no analytical results and is a reference for analytical datasets. To ensure accessibility and discoverability, each sample was assigned an International Generic Sample Number (IGSN), a persistent identifier, using System for Earth and Extraterrestrial Sample Registration (SESAR). These samples were used for downstream analysis by multiple teams of researchers the results of which will be reported separately. This dataset contains one data file in comma separate (.csv) format. Additional metadata are provided: one data dictionary and a file-level metadata file in comma separate (.csv) format and a user guide in PDF (*.pdf) format. An aliquot of most samples is stored in the SPRUCE archive and may be available for further analysis by request. See below under 7 Sample Access. Access this collection event on SESAR https://doi.org/10.58052/IEJ9B069L. To inquire about obtaining archived samples for analysis, reach out using the Contact Sample Owner form located on the bottom of the landing page in SESAR.

Birkebak, Joshua [ORNL] (ORCID:0009000955611494)↗
DOE OSTI2021

Data compression system using base values and methods thereof

In some embodiments, a memory controller in a processor includes a base value cache, a compressor, and a metadata cache. The compressor is coupled to the base value cache and the metadata cache. The compressor compresses a data block using at least a base value and delta values. The compressor determines whether the size of the data block exceeds a data block threshold value. Based on the determination of whether the size of the compressed data block generated by the compressor exceeds the data block threshold value, the memory controller transfers only a set of the compressed delta values to memory for storage. A decompressor located in the lower level cache of the processor decompresses the compressed data block using the base value stored in the base value cache, metadata stored in the metadata cache and the delta values stored in memory.

Seyedzadehdelcheh, SeyedMohammad↗
DOE OSTI2023

Data compression system using base values and methods thereof

In some embodiments, a memory controller in a processor includes a base value cache, a compressor, and a metadata cache. The compressor is coupled to the base value cache and the metadata cache. The compressor compresses a data block using at least a base value and delta values. The compressor determines whether the size of the data block exceeds a data block threshold value. Based on the determination of whether the size of the compressed data block generated by the compressor exceeds the data block threshold value, the memory controller transfers only a set of the compressed delta values to memory for storage. A decompressor located in the lower level cache of the processor decompresses the compressed data block using the base value stored in the base value cache, metadata stored in the metadata cache and the delta values stored in memory.

Seyedzadehdelcheh, Seyed Mohammad↗
DOE OSTI2023

Drone flight visible images, digital elevation maps, and geotiffs, Council, Seward Peninsula, Alaska, USA, July 2017

Remote sensing data collected from Lawrence Berkeley National Laboratory’s (LBNL) unmanned aerial system (UAS) quadcopter platform – Inspire-1 – operated by the Ameriflux Management Project (ameriflux.lbl.gov) Technical Team. The Insprire-1 is a visible imagery UAS platform that simultaneously measures very high spatial resolution optical red/green/blue (RGB) at regular intervals along each flight path. This package includes data from four flight paths over the NGEE Arctic Council Road Site near mile marker 71 in the Seward Peninsula, Alaska in July 2017. Derived image products for each flight include ortho-mosaiced RGB, an RGB-based digital surface model (DSM) using the structure from motion (SfM) technique, and a digital terrain model (DTM). Ancillary aircraft data, flight mission parameters, and general flight conditions are also included. Unprocessed and processed data products are included in this package (processing levels 0-2). This metadata document contains flight campaign, instrument and file metadata, along with a description of data processing levels, data products and file naming scheme.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

Drone flight visible images, digital elevation maps, and geotiffs, Teller, Seward Peninsula, Alaska, USA, July 2017

Remote sensing data collected from Lawrence Berkeley National Laboratory’s (LBNL) unmanned aerial system (UAS) quadcopter platform – Inspire-1 – operated by the Ameriflux Management Project (ameriflux.lbl.gov) Technical Team. The Insprire-1 is a visible imagery UAS platform that simultaneously measures very high spatial resolution optical red/green/blue (RGB) at regular intervals along the flight path. This package includes data from a flight path over the NGEE Arctic Teller Site, west of mile marker 27 Bob Blodgett Highway in the Seward Peninsula, Alaska in July 2017. Derived image products include ortho-mosaiced RGB, an RGB-based digital surface model (DSM) using the structure from motion (SfM) technique, and a digital terrain model (DTM). Ancillary aircraft data, flight mission parameters, and general flight conditions are also included. Unprocessed and processed data products are included in this package (processing levels 0-2). This metadata document contains flight campaign, instrument and file metadata, along with a description of data processing levels, data products and file naming scheme.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

Drone flight visible images, digital elevation maps, and geotiffs, Kougarok, Seward Peninsula, Alaska, USA, July 2017

Remote sensing data collected from Lawrence Berkeley National Laboratory’s (LBNL) unmanned aerial system (UAS) quadcopter platform – Inspire-1 – operated by the Ameriflux Management Project (ameriflux.lbl.gov) Technical Team. The Insprire-1 is a visible imagery UAS platform that simultaneously measures very high spatial resolution optical red/green/blue (RGB) at regular intervals along each flight path. This package includes data from four flight paths over the NGEE Arctic Kougarok Site, west of mile marker 64 on Kuzitrin Road in the Seward Peninsula, Alaska in July 2017. Derived image products include ortho-mosaiced RGB, an RGB-based digital surface model (DSM) using the structure from motion (SfM) technique, and a digital terrain model (DTM). Ancillary aircraft data, flight mission parameters, and general flight conditions are also included. Unprocessed and processed data products are included in this package (processing levels 0-2). This metadata document contains flight campaign, instrument and file metadata, along with a description of data processing levels, data products and file naming scheme.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

PDFDataExtractor: A Tool for Reading Scientific Text and Interpreting Metadata from the Typeset Literature in the Portable Document Format

The layout of portable document format (PDF) files is constant to any screen, and the metadata therein are latent, compared to mark-up languages such as HTML and XML. No semantic tags are usually provided, and a PDF file is not designed to be edited or its data interpreted by software. However, data held in PDF files need to be extracted in order to comply with opensource data requirements that are now government-regulated. In the chemical domain, related chemical and property data also need to be found, and their correlations need to be exploited to enable data science in areas such as data-driven materials discovery. Such relationships may be realized using text-mining software such as the “chemistry-aware” natural-language-processing tool, ChemDataExtractor; however, this tool has limited data-extraction capabilities from PDF files. This study presents the PDFDataExtractor tool, which can act as a plug-in to ChemDataExtractor. It outperforms other PDF-extraction tools for the chemical literature by coupling its functionalities to the chemical-named entityrecognition capabilities of ChemDataExtractor. The intrinsic PDF-reading abilities of ChemDataExtractor are much improved. The system features a template-based architecture. This enables semantic information to be extracted from the PDF files of scientific articles in order to reconstruct the logical structure of articles. While other existing PDF-extracting tools focus on quantity mining, this template-based system is more focused on quality mining on different layouts. PDFDataExtractor outputs information in JSON and plain text, including the metadata of a PDF file, such as paper title, authors, affiliation, email, abstract, keywords, journal, year, document object identifier (DOI), reference, and issue number. With a self-created evaluation article set, PDFDataExtractor achieved promising precision for all key assessed metadata areas of the document text.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

UAS remote sensing (AltaX platform): Red-green-blue (RGB) imagery, thermal infrared (TIR) imagery, and canopy reflectance (Level 0 data), Seward Peninsula, Alaska, 2023

Airborne remote sensing data collected using Brookhaven National Laboratory’s (BNL) heavy-lift unoccupied aerial system (UAS) AltaX platform on the Seward Peninsula, Alaska, USA. This package includes raw (L0) data from 11 flights flown over the NGEE-Arctic Kougarok mile marker 64 (MM64) and Teller MM 27 sites in July, 2023. The AltaX is a multi-sensor UAS platform that simultaneously measures very high spatial resolution optical red/green/blue (RGB) and thermal infrared (TIR) surface “skin” temperature imagery, as well as near-surface surface reflectance at 1 nm intervals in the visible to near-infrared spectral range from ~350 – 1000 nm. This package provides the Level 0 (raw, unprocessed) data collected by the platform and sensors. Ancillary aircraft data, flight mission parameters, and general flight conditions provided by the onboard flight and data collection computers are also included. Data and metadata are provided as text (*.txt, *.json), binary (*.dat, *.ulg), tabular (*.csv), geospatial (*.kml. *kmz), image (*.jpg, *.png, *.tif) and pdf formats. The metadata documents contain flight campaign, platform, sensor, flight and file metadata, along with a description of the L0 data and the file naming scheme.The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a 15-year research effort (2012-2027) 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↗