cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.18739/a2r49gb1j
title: Trace gas and wind velocities at 10 hertz from the 10 meter MetCity tower during the MOSAiC Arctic drift campaign, 2019-2020

description: Data are available for download at http://arcticdata.io/data/10.18739/A2R49GB1J These files are merged, 10 Hertz (Hz) measurements of 3 dimensional wind components (u,v,w) and dry air mole fractions of carbon dioxide (ppm) and methane (ppm). These are intended as raw files for computation of turbulent flux. The time lag between wind and gas measurements due to the long gas inlet has been corrected in this dataset (i.e. the gas concentration time series is time-shifted to synchronize the trace gas and vertical wind speed measurements). Files are provided in netCDF format with the standard CDF epoch timestamp (milliseconds since 01-Jan-1970 00:00Z) and year/month/day/hour/minute/second time vectors, to simplify date-time calculations. The wind coordinate system is right-handed and earth-relative, where u is northward velocity, v is westward velocity and w is upward velocity. Wind data is from the 10-meter ultrasonic anemometer on the MetCity tower. These data are available in original form from our collaborators (doi:10.18739/A2VM42Z5F) and are provided here in merged format with the gas data as a convenience to facilitate flux calculations.
DOI: 10.18739/a2rf5kh1m
title: Arctic aquatic graminoid tundra: soil, water, leaf, root chemistry and spectral data (2013)

description: This datasets represent an interdisciplinary sampling effort to better understand Arctic aquatic graminoid tundra. In particular, we assessed how environmental nutrient availability influences production of biomass and greenness in the 2 dominant aquatic tundra species: Arctophila fulva and Carex aquatilis.We sampled a total of 17 sites distributed across the Barrow Peninsula and Atqasuk, Alaska, following a nutrient gradient that ranged from sites with thermokarst slumping or urban runoff to sites with relatively low nutrient inputs. Additional information about methods, sites and other considerations on the dataset please refer to: Andresen CG, and Lougheed VL. Arctic aquatic graminoid tundra responses to nutrient availability. Biogeosciences, 18, 1–14, 2021
DOI: 10.18739/a2rn3087n
title: Digital elevation models (DEMs) and ortho-mosaic imagery derived from uncrewed aerial vehicle (UAV) images over Point 660 in Southwest Greenland (67.16 N, 49.99 W)

description: This dataset is associated with the article "Supraglacial Stream Sediment Variability on the Greenland Ice Sheet Over the 2019 Melt Season" submitted to the journal Remote Sensing of the Environment. The dataset includes digital elevation models (DEMs) and orthomosaic images of the Greenland Ice Sheet (spatial extent: 67.155 - 67.165 N, 49.986-50.000 W). DEMs and Orthomosaic images were produced from image collected with an 18-megapixel FC3610 camera mounted on a DJI Phantom 3 quadcopter UAV (July 22-August 11, 2019) or a 17-megapixel L1D-20c camera mounted on a Mavic 2 Pro quadcopter UAV (August 14-15, 2019). Images from the UAV were analyzed in Agisoft Metashape Pro v1.6.5, a Structure-from-Motion software program. High quality dense point clouds were georeferenced to the UTM (Universal Transverse Mercator) 22N projection using markers placed around the study site including orange plastic trays (0.35 x 0.25 meter (m)), orange panted rocks (~0.1 m diameter), and red tarps with black X's to demark the center point (1.5 x 1.5 m). Ground control point markers were geolocated using a UNAVCO Trimble R7 GNSS running in PPK (Post-Processed Kinematic) and corrected using a base station located ~2 kilometers (km) away on bedrock on the ice edge. DEMs and Orthomosaics were exported using the maximum resolution (0.003 - 0.013 m resolution). All images were collected within 2 hours of solar noon. Images were used to digitize the location of supraglacial stream shorelines within the catchment area and to analyze the distribution of sediment throughout the melt season to determine if changes in supraglacial streamflow effected sediment deposition and the absorption of solar radiation.
DOI: 10.18739/a2rr1pn93
title: Stable water isotopes measured from the deep ice core of the East GReenland Ice-core Project (EGRIP), spanning depths of 21.5m (meters) to 2120.7m with 10cm (centimeter) data resolution, obtained using averaged high-resolution continuous flow analysis measurements.

description: This data set is part of a joint international effort for the East GReenland Ice-core Project (EGRIP), which has retrieved an ice core by drilling through the Northeast Greenland Ice Stream (NEGIS, 75.63°N (North), 35.98°W (West)). Ice streams are responsible for draining a significant fraction of the ice from the Greenland Ice Sheet (GIS), and the project was developed to gain new and fundamental information on ice stream dynamics, thereby improving the understanding of how ice streams will contribute to future sea-level change. The drilled core also provides a new record of past climatic conditions from the northeastern part of the GIS. The project has many international partners and is managed by the Centre for Ice and Climate, Denmark with air support carried out by US ski-equipped Hercules aircraft managed through the US (United States) Office of Polar Programs, National Science Foundation. As of May 2022, approximately 2099.2 m (meters) of ice core have been recovered from the combined efforts of drilling operations in 2017, 2018, and 2019. Here we present records of stable isotopes of oxygen and hydrogen from 21.5 meters to 2120.7 m depth. Bedrock is estimated to be at a depth of approximately 2550 m; the remaining ice is expected to be recovered in the 2022 and 2023 field seasons. The data product presented here is supported by the National Science Foundation project: Collaborative Research: The fingerprint of abrupt temperature events throughout Greenland during the last glacial period. Award # 1804098.
DOI: 10.18739/a2sn0156d
title: Camera Trap Photogrammetry Dataset, Fairbanks, Alaska, USA, Sept. 2021

description: The dataset and images provided here were used to evaluate a method of using pixel measurements in an image to estimate animal size or distance from the camera using a conceptual model in photogrammetry known as the “pinhole camera model". Our objectives were to 1) determine whether the pinhole camera model can produce reliable estimates of animal size or distance using different camera traps, models, and image settings under ideal conditions using stationary life-like animal targets and 2) evaluate performance of the pinhole camera model in a practical field setting using live captive reindeer. Images of captive reindeer were collected at the Large Animal Research Station at the University of Alaska Fairbanks in Alaska, United States of America, in 2021. We found this approach addressed limitations of current methods while remaining conceptually simple, easy to implement, and generalizable to different camera trap models and installations.
DOI: 10.18739/a2sn0157w
title: Future of Greenland Ice Sheet Science (FOGSS) Workshop 2022: Summary report

description: Future of Greenland Ice Sheet Science (FOGSS) represents a refocus on the collaborative, community-driven spirit of early National Aeronautics and Space Administration (NASA) Program for Arctic Regional Climate Assessment (PARCA) and NSF Greenland Environmental Observatory (GEOSummit) workshops. The workshop’s mission is to identify and advise on medium-to-long-term priorities for U.S. research on the Greenland Ice Sheet. Over three hours on each of three days, April 6-8, 2022, we hosted a virtual (Zoom) workshop. Approximately 100 national and international researchers from career stages ranging from beginning graduate students to senior scientists attended FOGSS 2022. Participants accomplished the workshop goal through two primary activities: thematic goal setting within breakout groups for the future of science on and around the Greenland Ice Sheet, and geographically-focused discussion to identify opportunities for collaboration and research synergies. Additional presentations added context to the discussion, including from NSF and NASA program officers, the head of Department of Environment and Minerals within the Greenland Institute of Natural Resources, and representatives of several large research projects. Workshop participants worked within breakout groups, each focused on different research themes, and prepared a set of slides focused on charting the future of each theme. The organizing committee identified five cross-cutting challenges, distilling the feedback from the major thematic groups: a. Decolonizing U.S. research in Greenland; b. Better integration of observation &amp;amp; models; c. Water remains a unifying unknown; d. Sustained, open polar-observations; e. Projecting Greenland’s contribution to sea-level rise. Following these five challenges, this report presents distilled feedback gained from the post-workshop survey, the workshop agenda, and statistics regarding workshop participants. Complete slide decks produced by eight different thematic breakout groups, complete responses to the post-workshop survey, and instructions for participants are available at the workshop website (fogss-workshop.org).
DOI: 10.18739/a2sq8qj9s
title: North Pacific and Arctic Marine Vessel Traffic Dataset (2015-2020); 1 Kilometer Resolution Coastal.

description: These data are a spatially explicit representation of monthly shipping intensity in the Pacific Arctic region from January 1, 2015 to December 31, 2020. We calculated shipping intensity based on Automatic Identification System (AIS) data, a type of Global Positioning System (GPS) transmitter required by the International Maritime Organization on all ships over 300 gross tonnes on an international voyage, all cargo ships over 500 gross tonnes, and all passenger ships. We used AIS data received by the exactEarth satellite constellation (64 satellites as of 2020), ensuring spatial coverage regardless of national jurisdiction or remoteness. Our analytical approach converted raw AIS input into monthly raster datasets. We first filtered raw AIS messages to remove spurious records and GPS errors, then joined remaining vessel positional records with static messages including descriptive attributes. To develop the raster dataset, we created a series of spatially explicit daily vessel tracks according to unique voyages and aggregated tracks by month. We then created a raster grid and calculated the total length, in meters, of all vessel tracks within each raster cell. To capture a high resolution look at vessel traffic in coastal areas, this data set aggregates vessel track lines into 1-km resolution raster cells located within a 10-km buffer of the coastline of the study area. These monthly datasets provide a critical snapshot of dynamic commercial and natural systems in the Pacific Arctic region. Recent declines in sea ice have lengthened the duration of the shipping season and have expanded the spatial coverage of large vessel routes, from the Aleutian Islands through the Bering Strait and into the southern Chukchi Sea. As vessel traffic has increased, so has exposure to the myriad environmental risks posed by large ships, including oil spills, underwater noise pollution, large cetacean ship-strikes, and discharges of pollutants. This dataset provides scientific researchers, local community members, mariners, and decision-makers with a quantitative means to evaluate the distribution and intensity of shipping across space and through time. In addition to this coastal data subset, we also produced data products in 25- and 10-km raster format for the entire study area as well as a hex data set which contains additional attributes (e.g., number of ships, ship speed). To find these products, search for “North Pacific and Arctic Marine Vessel Traffic Dataset” in the Arctic Data Center’s data repository.
DOI: 10.18739/a2sx64b5f
title: Arctic Ocean 3.5 kilometer model monthly mean outputs for 2014 and configuration for rerunning model with and without tides

description: Data are available at: https://arcticdata.io/data/10.18739/A2SX64B5F/. This data set is part of an NSF project to understand the role of tides and high frequency winds in influencing the Arctic ocean stratification and sea ice. A high resolution model was configured, with horizontal resolution of 3.5km and 90 vertical levels varying from 1m at the surface to 200m at the ocean floor. Three runs were set up, (1) with JRA55 full atmospheric forcing and with tides, (2) same as (1) but without tides, (3) same as (2) but with 48-hour running mean winds. The runs were spun up from WOA13 version 1 and zero velocity for 12 years, then run for 2014 with outputs of basic model variables for diagnostics. As such, all three runs were not constrained to observations and had biases in watermass, circulations, and sea ice representations. In the data set, monthly mean hydrography (T,S,U,V) and 2D ocean-seaice and atmospheric forcings are provided for 3 runs to see how the mean ocean-sea ice states are different for the year 2014. In addition, the data set provides instruction for how to set up the runs and all input binary fields, model code, input parameters required to generate high resolution model outputs for runs with tidal forcings and/or low frequency winds for the year 2014. The model outputs are in subdirectories called nc_tiles_monthly_[tides,notides,notides_LFwinds]. Model grid is provided in nctiles_grid. A figure tile_Arctic.png provides geographic map of where the tiles are located, and the "available_diagnostics.log" file provides detailed description and units of the output variables. For re-running the model, three subfolders are provided as follows: code_c67 and NAMELISTS_c67 are the model code and input parameters that is tied to the open-sourced MITgcm checkpoint 67 (https://github.com/MITgcm/MITgcm/archive/checkpoint67.zip). input_binaries: inputs in raw binary format (float32) required for the runs, including the model grid (tile00*.mitgrid), bathymetry, pick-up and associated meta files, lateral open boundary T,S,U,V extracted from ASTE Release 1 (https://arcticdata.io/catalog/portals/ASTE), surface forcings from the Japanese Reanalysis JRA55 product, and tidal potential field generated from open-source code distributed at https://github.com/joernc/tidal-potential. Finally, a README.txt file provides the brief overview of the data set, and a PDF file Highres_runs_outputs_guide.pdf provides more in-depth details and structures of the outputs.
DOI: 10.18739/a2sx64b6x
title: Alaska Lake Buoy Thermister String & Estimated Ice Thickness, 2019-2022

description: This dataset contains thermistor string observations from autonomous buoys and estimated ice thicknesses with the purpose of remote ice thickness monitoring in locations around the state of Alaska. Some buoys are co-located within or nearby partner observation communities for calibration purposes while others are more remote. These buoys were installed fall of 2019 and fall of 2020.
DOI: 10.18739/a2t43j430
title: Arctic Great Rivers Observatory III Biogeochemistry and Discharge Data, 2017-2019

description: The PARTNERS (Pan-Arctic River Transport of Nutrients, Organic Matter, and Suspended Sediments) and Arctic-GRO (Great Rivers Observatory) projects sample the biogeochemistry of the six largest rivers draining to the Arctic Ocean: the Yenisey, Ob', Lena, and Kolyma Rivers in Siberia and the Yukon and Mackenzie Rivers in North America. To the greatest extent possible, sample collection techniques are identical across rivers. Once collected, samples are returned to Woods Hole, Massachusetts, from where they are shipped to expert laboratories for analyses. The Arctic Great Rivers Observatory III (Arctic-GRO III; NSF-OPP-1602615 (National Science Foundation, Office of Polar Programs)) Project spans the years between 2017 and 2019, and continues a sample collection effort that has been ongoing since 2004. On each river, samples are collected bi-monthly (six times per year), with target sampling months alternating between years. Full field and laboratory details for Arctic GRO III can be found in the "Sample Collection and Analyses" document on this page. For real-time updates of the Arctic GRO dataset, please visit www.arcticgreatrivers.org/data.
DOI: 10.18739/a2tb0xw8r
title: Terrestrial carbon, water and energy fluxes measured by eddy covariance, and associated biomet variables, at three adjacent tundra ecosystems at Imnavait Creek, Alaska, 2021

description: This Arctic Observing Network (AON) project focuses on maintaining and expanding our long-term network of measurements of carbon, water, and energy exchange in terrestrial systems in Alaska. These exchanges help regulate the Arctic System and its feedbacks to global climate. Thus, extending long-term observations is a key science priority for the observing-change component of the Study of Environmental Arctic Change (SEARCH). Detecting and interpreting change in arctic C, water, and energy fluxes requires a continuous year-round record over multiple years. Recent data syntheses and modeling studies of Arctic Carbon balance suggest that tundra is either a carbon dioxide (CO2) sink, a source, or neutral (e.g., McGuire et al., 2009, McGuire et al., 2012) . This uncertainty arises mainly from a lack of data on winter CO2 flux and how tundra responds to recent warming. Because of harsh, remote environments and the lack of line power, long-term measurements of arctic CO2 fluxes over the full year are rare. We have been measuring year-round C, water, and energy fluxes for eleven years in two broadly representative flagship observatories with long-term histories of research, at Imnavait Creek near Toolik Lake, Alaska, and near Cherskiy, Siberia. Similar versions of these eddy covariance and biomet data are available from Ameriflux as sites US-ICx. https://ameriflux.lbl.gov/data/download-data/ Our three Imnavait Creek Alaska sites retained multiple names over the years. The following clarification is needed. The 'official' site name is followed by the technical station name (IC_xxxx), the positional name (Ridge), and the Ameriflux site name (US-ICx), and finally the site coordinates. Wet Sedge tundra (IC_1523, Fen, US-ICs) 68.6058 -149.3110 Tussock tundra (IC_1993, Tussock, US-ICt) 68.6063 -149.3041 Dry Heath tundra (IC_1991, Ridge, US-ICh) 68.6068 -149.2958
DOI: 10.18739/a2td9n921
title: Benthic macroinfaunal samples collected from the Canadian Coast Guard Ship (CCGS) Sir Wilfrid Laurier, Northern Bering Sea to Chukchi Sea, 2018

description: The Pacific sector of the Arctic Ocean is experiencing major reductions in seasonal sea ice extent and increases in sea surface temperatures. One of the key uncertainties in this region is how the marine ecosystem will respond to seasonal shifts in the timing of spring sea ice retreat and/or delays in fall sea ice formation. Variations in upper ocean water hydrography, planktonic production, pelagic-benthic coupling and sediment carbon cycling are all influenced by sea ice and temperature change. To more systematically track the broad biological response to sea ice retreat and associated environmental change, an international consortium of scientists have developed a coordinated “Distributed Biological Observatory” (DBO) that includes selected biological measurements at multiple trophic levels, along with satellite and mooring measurements. The DBO currently focuses on five regional biological “hotspot” locations along a latitudinal gradient that allows for consistent sampling and monitoring at five biologically productive locations across a latitudinal gradient: DBO 1 (SLIP)-south of St. Lawrence Island (SLI), DBO2 (Chirikov)-north of SLI, DBO3 (southern Chukchi Sea), DBO4-NE Chukchi Sea,and DBO5-Barrow Canyon. This dataset contains benthic macroinfaunal population level from sediment samples collected at each station for the United States Coast Guard Cutter (USCGC) Healy cruise-Leg 1 in 2017, identified by station number (#), Station name (Stn. Name), Date (mm/dd/yy), latitude (°N), longitude (°W), and station depth (m). The following macroinfaunal parameters were determined: abundance, wet weight biomass (grams of wet weight per meters squared), dry weight biomass (grams of Carbon per meters squared), and taxon type.
DOI: 10.18739/a2th8bp4v
title: Toolik Lake and Imnaviat Creek plot-level Normalized Difference Vegetation Index, Plant Functional Type Cover, and CO2 flux, 2010-2011

description: The Normalized Difference Vegetation Index (NDVI), derived from reflected visible and infrared radiation, has been critical to understanding change across the Arctic, but relatively few ground truthing efforts have directly linked NDVI to structural and functional properties of Arctic tundra ecosystems. To improve the interpretation of changing NDVI within moist acidic tundra (MAT), a common Arctic ecosystem, we coupled measurements of NDVI, vegetation structure, and CO2 flux in seventy MAT plots, chosen to represent the full range of typical MAT vegetation conditions, over two growing seasons.
DOI: 10.18739/a2tm72263
title: Metadata for zooplankton gut DNA 18S ribosomal DNA sequences taken during the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition in the central Arctic and Fram Straight from November 2019 to September 2020

description: These files contain metadata describing the samples used in 18S ribosomal DNA sequencing of gut contents from zooplankton collected during the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition. Raw sequence data along with these files are deposited in the Sequence Read Archive (SRA), and will be accessible through National Center for Biotechnology Information (NCBI), BioProject Identification (ID) PRJNA789896 upon manuscript publication (expected December 2022). The study looks at the Eukaryotic organisms in the guts of Arctic zooplankton collected through the year-long drift survey. The majority of the samples used were female copepods (Calanus glacialis, Calanus hyperboreus, and Metridia longa), with a few other organisms and life stages included.
DOI: 10.18739/a2tt4fv4x
title: Beaver pond bathymetry rasters and point depths 2021-2022

description: The Arctic Beaver Observation Network is a 5-year project (2021-2026) funded by the National Science Foundation. The natural science part of the project uses remote sensing to observe the progress and impacts of beaver engineering in the Arctic, starting in Alaska and extending into Canada and Eurasia. The project also establishes field sites at tundra beaver ponds to study the implications of beaver engineering on hydrology and permafrost, as well as pond evolution documented using Unmanned Aerial Systems (UAS). Remote sensing work will map beaver ponds over time. Field measurements at tundra beaver ponds are made in August and late March. Data generated by field measurements include water level and temperature from pressure-transducers, subsurface imaging from ground-penetrating radar, sonar measurements for beaver pond bathymetry, tabular data associated with water quality measurements, and ice thickness and water depth (in winter). Data is also posted from UAS surveys: annual visible and multi-spectral surveys, as well as snow depth.