cometadata/datacite-titles-descriptions-related-identifiers huggingface dataset:
DOI: 10.18739/a2bc3sz08
title: Firth River Alaska 930 Year Maximum Latewood Density Temperature Reconstruction

description: Northwestern North America has one of the highest rates of recent temperature increase in the world, but the putative "divergence problem" in dendroclimatology potentially limits the ability of tree-ring proxy data at high latitudes to provide long-term context for current anthropogenic change. Here, summer temperatures are reconstructed from a Picea glauca maximum latewood density (MXD) chronology that shows a stable relationship to regional temperatures and spans most of the last millennium at the Firth River in northeastern Alaska. The warmest epoch in the last nine centuries is estimated to have occurred during the late twentieth century, with average temperatures over the last 30 yr of the reconstruction developed for this study [1973-2002 in the Common Era (CE)] approximately 1.3*deg* *plusmn* 0.4*deg*C warmer than the long-term preindustrial mean (1100-1850 CE), a change associated with rapid increases in greenhouse gases. Prior to the late twentieth century, multidecadal temperature fluctuations covary broadly with changes in natural radiative forcing. The findings presented here emphasize that tree-ring proxies can provide reliable indicators of temperature variability even in a rapidly warming climate.
DOI: 10.18739/a26m33469
title: NEEM_2011_S1 Ice Core

description: A continuous ice core analytical system was used to analyze the ~410 m NEEM-2011-S1 ice core collected in summer 2011 near the NEEM deep drilling site in NW Greenland. The core was analyzed for a broad range of elements and chemical species.
DOI: 10.6084/m9.figshare.27888879
title: Data for "Validity and reliability of the My Jump Lab app for the measurement of lower-limb force, power and velocity using artificial intelligence algorithms"

description: Data for the paper entitled "Validity and reliability of the My Jump Lab app for the measurement of lower-limb force, power and velocity using artificial intelligence algorithms" by Balsalobre-Fernández et al. 2024
DOI: 10.18739/a2z31np7g
title: O-Buoy15 Deployment

description: This data set contains O-Buoy Deployment data. Daily, hourly or continuous measurements over Arctic Ocean sea ice of ozone (O3), carbon dioxide (CO2), bromine monoxide (BrO), wind speed and direction, air temperature and relative humidity (RH), barometric pressure, latitude and longitude, Universal Coordinated Time (UTC), horizon pictures, heading, pitch and roll *** SEE INSTRUMENT README FILES IN DATASET *** These are level 1 data, unfiltered. *Data are current as of 2016-01-20.
DOI: 10.18739/a2hx15r7t
title: NEEM_2011_S1 Ice Core

description: A continuous ice core analytical system was used to analyze the ~410 m NEEM-2011-S1 ice core collected in summer 2011 near the NEEM deep drilling site in NW Greenland. The core was analyzed for a broad range of elements and chemical species.
DOI: 10.18739/a2np1wk2p
title: ACT11D Ice Core

description: A continuous ice core analytical system was used to analyze the ~300 m ACT11D ice core collected in summer 2011 near the Raven Training site(Dye 2) in SW Greenland. The core was analyzed for a broad range of elements and chemical species.
DOI: 10.18739/a28c9r493
title: Atmospheric d13C of CH4 covering the past 2,000 years, Greenland

description: Data on the d13C of atmospheric CH4 from NEEM ice core.
DOI: 10.18739/a24m91b5b
title: Collaborative Research: The NEEM Deep Ice Core

description: The North Eemian (NEEM) Deep Ice Core Project was designed to acquire a new ice core in northern Greenland. NEEM is an international effort, led by the glaciology group at the University of Copenhagen. More than a dozen countries have expressed a desire to participate. The US is a main partner in NEEM and is already providing about one-third of the logistics costs needed to collect the ice core. US scientists will take the lead on gas and gas isotope analyses and studies of the physics of gas incorporation into ice, they will place the modern climate in the context of the past two millennia, and they will help provide the basic temperature records in the ice needed to place all analyses in a climate context. A particular focus of the project will be on high temporal resolution to explore abrupt climate shifts. The most prominent analyses will focus on gas concentrations, in particular carbon monoxide, and stable isotopes of oxygen, hydrogen, argon, krypton, and carbon. A final subproject will focus on the firnification processes in order to understand the advection and diffusion of gases through the snow and ice and the development of ice bubbles that preserve the atmospheric gases. Funding Source: Arctic Natural Sciences (ANS) Sponsor: Dartmouth College - Thayer School of Engineering, 14 Engineering Dr. Hanover, NH 03755 USA
DOI: 10.15468/dl.ecvrtv
title: Occurrence Download

description: A dataset containing 739 species occurrences available in GBIF matching the query:
{
 "and" : [
 "HasGeospatialIssue is false",
 "HasCoordinate is true",
 "OccurrenceStatus is Present",
 {
 "not" : {
 "BasisOfRecord" : [
 "is one of (Fossil, Living Specimen)"
 ]
 }
 },
 "TaxonKey is one of (Nipponanthemum nipponicum (Franch. ex Maxim.) Kitam.)"
 ]
}

 The dataset includes 739 records from 19 constituent datasets; see https://api.gbif.org/v1/occurrence/download/0027803-241107131044228/datasets/export for details.
 
Data from some individual datasets included in this download may be licensed under less restrictive terms.
DOI: 10.18739/a2w66990b
title: Animation of time-dependent velocity magnitudes for Sermeq Kujalleq (Jakobshavn Isbræ) from 2009 - 2019.

description: This movie is an animation of reconstructed time-dependent flow speeds for Jakobshavn Isbrae. Flow speeds contain both short- and long-term variations. The colored circle in the bottom left indicates year and time-of-year of current frame where red and blue colors correspond to summer and winter months, respectively. The inset shows the location of Jakobshavn within Greenland. The movie is a supporting asset for the manuscript (abstract following):
 B. V. Riel, B. M. Minchew, and I. Joughin. Observing traveling waves in glaciers with remote sensing: New flexible time-series methods and application to Sermeq Kujalleq (Jakobshavn Isbræ), Greenland. submitted to The Cryosphere, 2020.
 The recent influx of remote sensing data provides new opportunities for quantifying spatiotemporal variations in glacier surface velocity and elevation fields. Here, we introduce a flexible time series reconstruction and decomposition technique for forming continuous, time-dependent surface velocity and elevation fields from discontinuous data and partitioning these time series into short- and long-term variations. The time series reconstruction consists of a sparsity-regularized least squares regression for modeling time series as a linear combination of generic basis functions of multiple temporal scales, allowing us to capture complex variations in the data using simple functions. We apply this method to the multitemporal evolution of Sermeq Kujalleq (Jakobshavn Isbræ), Greenland. Using 555 ice velocity maps generated by the Greenland Ice Mapping Project and covering the period 2009 -- 2019, we show that the amplification in seasonal velocity variations in 2012 -- 2016 was coincident with a longer-term speedup initiating in 2012. Similarly, the reduction in post-2017 seasonal velocity variations was coincident with a longer-term slowdown initiating around 2017. To understand how these perturbations propagate through the glacier, we introduce an approach for quantifying the spatially varying and frequency-dependent phase velocities and attenuation length scales of the resulting traveling waves. We hypothesize that these traveling waves are predominantly kinematic waves based on their long periods, coincident changes in surface velocity and elevation, and connection with variations in the terminus position. This ability to quantify wave propagation enables an entirely new framework for studying glacier dynamics using remote sensing data.
DOI: 10.18739/a20v89j16
title: Transient Electromagnetic (TEM) Soundings on Drained Permafrost Lake Basins, North Slope, Alaska, 2019

description: This dataset contains transient electromagnetic (TEM) geophysical soundings acquired on drained permafrost lake basins at the North Slope of Alaska during spring fieldwork in 2019. Measurements were made using an ABEM WalkTEM with a 1600 meter squared (m^2) transmitter loop, a 200 m^2 receiver loop, and a 5 m^2 receiver loop, all in a center-nested configuration. Raw data for 15 soundings are provided in the Universal Sounding Format (USF), and results after processing (smooth constraint) with SPIA (GuidelineGeo/ABEM/Aarhus Hydrogeopyhsics) inversion software are included as tabular geolocated values. A KML indicating point location of the center of each sounding is also provided.
DOI: 10.71687/00046750
title: KMD Institution (1992-2008)

description: Institutionssystemet har til formål at understøtte administrationen af børn som benytter daginstitution, skolefritidsordning, klub og lignende.

Indeholder:
Indeholder modulerne: Grunddel, venteliste, visitation og beregning.
DOI: 10.18739/a2rf5kg6k
title: Arctic sea ice seasonal transition metrics from coupled climate model simulations, 1979-2013

description: This dataset includes annual, gridded Arctic sea ice seasonal transition metrics (dates and periods) for fifteen Coupled Model Intercomparison Project version 6 (CMIP6) models and the Community Earth System Model version 1.1 (CESM1.1) Large Ensemble (CESM LE) (Kay, et al., 2015). Seasonal transition dates include melt onset, opening, break-up, freeze onset, freeze-up and closing. Seasonal transition periods include the melt period, the seasonal loss-of-ice period, the freeze period, the seasonal gain-of-ice period, the melt season, the open water period and the outer ice-free period. Data are provided for one ensemble member of the following models: Australian Community Climate and Earth System Simulator CM2 (ACCESS-CM2), Beijing Climate Center Climate System Model 2 MR (BCC-CSM2-MR), Beijing Climate Center Earth System Model 1 (BCC-ESM1), Community Earth System Model 2 (CESM2), Community Earth System Model 2 FV2 (CESM2-FV2), Community Earth System Model 2 Whole Atmosphere Community Climate Model (CESM2-WACCM), Community Earth System Model 2 Whole Atmosphere Community Climate Model FV2 (CESM2-WACCM-FV2), Centre National de Recherches Météorologiques ESM 2-1 (CNRM-ESM2-1), Centre National de Recherches Météorologiques CM 6-1 (CNRM-CM6-1), EC-Earth3, Meteorological Research Institute Earth System Model 2-0 (MRI-ESM2-0), Norwegian Earth System Model 2 LM (NorESM2-LM) and Norwegian Earth System Model 2 MM (NorESM2-MM). Data are provided for 40 members of the Community Earth System Model Large Ensemble (CESM LE), 35 members of Canadian Earth System Model 5 (CanESM5) and 30 members of Institut Pierre Simon Laplace CM6A LR (IPSL-CM6A-LR). The data is stored in netcdf format, and includes metadata in the netcdf files. The raw CMIP6 and CESM LE model output that these transition metrics are calculated from are publicly available at https://esgf-node.llnl.gov/projects/cmip6/ and https://www.earthsystemgrid.org/ respectively.
 This dataset was created to evaluate climate model projections of Arctic sea ice using seasonal transition metrics in the context of both observations and internal variability. It is used in the article Smith, Jahn, Wang (2020), Seasonal transition dates can reveal biases in Arctic sea ice simulations, The Cryosphere, in press. The discussion paper with a link to the final paper can be found at https://doi.org/10.5194/tc-2020-81. This work was conducted at the University of Colorado Boulder from 2019-2020.
DOI: 10.18739/a2mp4vp1z
title: Snow depth survey 2019 in North Slope, Alaska

description: This is the field measured snow depth data using an automatic snow depth probe (magnaprobe, Snow-Hydro LCC) in April 20-29, 2019 in North Slope, Alaska. The data are three different format: csv format (comma delimited text format), projected shape file (UTM zone 5), and unprojected shape file (geographical coordinate, WGS 84).
 The goal of this research project is to quantify the role of thermokarst lake drainage and drained thermokarst lake basin (DTLB) evolution in the arctic system. The joint research team (University of Alaska, Fairbanks and University of Wyoming) traveled over 19 days and approximately 1000 miles in Northern Alaska to make initial geophysical measurement on a range sites. Field work began in mid-April with several days based in Utqiagvik (Western Coastal Plain) in coordination with principle investigator Hinkel and his graduate student Ian Nichols. A group of six then departed for Teshekpuk Lake (Central Coastal Plain), followed by Inigok (Eastern Coastal Plain and Sand Sea), and Oumalik (Loess Belt and Sand Sea) before returning to Utqiagvik in early May. During the travel, manual snow survey was conducted using the mangaprobe to quantify the snowdrift around thermokarst lakes and other land features as complementary to the geophysical and remote sensed snowpack characterizations.
DOI: 10.18739/a2c53f235
title: Arctic sea ice seasonal transition metrics from coupled climate model simulations, 1979-2013

description: This dataset includes annual, gridded Arctic sea ice seasonal transition metrics (dates and periods) for fifteen Coupled Model Intercomparison Project version 6 (CMIP6) models and the Community Earth System Model version 1.1 (CESM1.1) Large Ensemble (CESM LE) (Kay, et al., 2015). Seasonal transition dates include melt onset, opening, break-up, freeze onset, freeze-up and closing. Seasonal transition periods include the melt period, the seasonal loss-of-ice period, the freeze period, the seasonal gain-of-ice period, the melt season, the open water period and the outer ice-free period. Data are provided for one ensemble member of the following models: Australian Community Climate and Earth System Simulator CM2 (ACCESS-CM2), Beijing Climate Center Climate System Model 2 MR (BCC-CSM2-MR), Beijing Climate Center Earth System Model 1 (BCC-ESM1), Community Earth System Model 2 (CESM2), Community Earth System Model 2 FV2 (CESM2-FV2), Community Earth System Model 2 Whole Atmosphere Community Climate Model (CESM2-WACCM), Community Earth System Model 2 Whole Atmosphere Community Climate Model FV2 (CESM2-WACCM-FV2), Centre National de Recherches Météorologiques ESM 2-1 (CNRM-ESM2-1), Centre National de Recherches Météorologiques CM 6-1 (CNRM-CM6-1), EC-Earth3, Meteorological Research Institute Earth System Model 2-0 (MRI-ESM2-0), Norwegian Earth System Model 2 LM (NorESM2-LM) and Norwegian Earth System Model 2 MM (NorESM2-MM). Data are provided for 40 members of the Community Earth System Model Large Ensemble (CESM LE), 35 members of Canadian Earth System Model 5 (CanESM5) and 30 members of Institut Pierre Simon Laplace CM6A LR (IPSL-CM6A-LR). The data is stored in netcdf format, and includes metadata in the netcdf files. The raw CMIP6 and CESM LE model output that these transition metrics are calculated from are publicly available at https://esgf-node.llnl.gov/projects/cmip6/ and https://www.earthsystemgrid.org/ respectively.
 This dataset was created to evaluate climate model projections of Arctic sea ice using seasonal transition metrics in the context of both observations and internal variability. It is used in the article Smith, Jahn, Wang (2020), Seasonal transition dates can reveal biases in Arctic sea ice simulations, The Cryosphere, in press. The discussion paper with a link to the final paper can be found at https://doi.org/10.5194/tc-2020-81. This work was conducted at the University of Colorado Boulder from 2019-2020.
DOI: 10.6084/m9.figshare.27888885
title: Supplementary Table 2

description: <b>Supplementary Table 2. Baseline characteristics of enrolled patients in vitamin D </b><b>insufficient and sufficient group split by 75nmol/L</b>
DOI: 10.6084/m9.figshare.27888885.v1
title: Supplementary Table 2

description: <b>Supplementary Table 2. Baseline characteristics of enrolled patients in vitamin D </b><b>insufficient and sufficient group split by 75nmol/L</b>
DOI: 10.18739/a27d2q80h
title: Hydrogeochemistry of Greenlandic proglacial and nonglacial streams, 2017-2018

description: This project assesses how weathering varies across deglaciated and proglacial watersheds in western and southern Greenland to evaluate the impact of ice sheet retreat on isotopic and nutrient fluxes to the ocean and atmospheric carbon dioxide (CO2) and methane (CH4) exchange. Deglaciated watersheds are separated from the ice sheet by hydrologic divides and drain precipitation and permafrost meltwater, while proglacial watersheds include also glacial meltwater. Previous studies of high latitude weathering focused almost exclusively on proglacial and subglacial systems; however, preliminary work suggests deglaciated watersheds in western Greenland have similar specific discharge (discharge normalized to drainage area) but solute concentrations distinct from proglacial system. Distinct solute concentrations results from increasing weathering extent from inland to the coast. Greenland Ice Sheet (GrIS) retreat will increase the areal extent of deglaciated watersheds, particularly those with coastal weathering characteristics, and thus should weathering fluxes. This project aims to test the hypothesis that differences in weathering reactions and extent within deglaciated watershed, and between deglaciated and proglacial environments, will produce predictable changes in isotopic, solute, and nutrient fluxes as the ice sheet retreats. We compare stream discharge and water chemistry between Greenlandic proglacial and nonglacial streams during the spring (2017), summer (2018) and fall (2017) melt seasons between two rivers draining the Greenland Ice Sheet (proglacial rivers) and six streams draining deglaciated watersheds (nonglacial streams). This dataset includes major cations and anions, biogeochemical solute concentrations, trace metals, radiogenic isotopes, Dissolved Organic Carbon (DOC) and Colored Dissolved Organic Matter (CDOM) characteristics analyzed with spectroscopic (UV (ultraviolet) absorbance and fluorescence) measurement, and stream discharge information.
DOI: 10.18739/a23n20f64
title: ArcSEES-LCLUC Prudhoe Bay Alaska Airport Site Road Effects, Summer 2015

description: This data report contains methods and data from transects, permanent vegetation plots, and permafrost boreholes sampled in summer-fall 2015 at the Airport Site at Prudhoe Bay, Alaska, for the National Science Foundation (NSF)-funded project, "Cumulative effects of Arctic oil development—planning and designing for sustainability," with additional funding from National Aeronautics and Space Administration (NASA)'s Land-Cover and Land-Use Change (LCLUC) Program. The study site consists of three transects located near the Deadhorse Airport. This builds on data collected in 2014 at a site near Lake Colleen. A forthcoming data report will contain additional data from both sites collected from fall 2015 to summer 2016. The main objectives of the 2014 field program were to document the extent and effects of road dust and road-related flooding to the topography, landforms, permafrost, soils and vegetation near the Spine Road—the oldest, most heavily traveled road in the Prudhoe Bay region. A full description of the project goals, methods, data and conclusions from the 2014 field season is in Alaska Geobotany Center Data Report AGC 15-01 (Walker et al., 2015). Objectives of the 2015 field program were similar to those in 2014, except the focus of the study was three new transects established near the Deadhorse Airport and the northern terminus of the Dalton Highway at Milepost 414. This site offers some contrasts to Colleen Site A, including extensive dry thermokarst terrain with well-developed high-centered polygons along Transect 3, located southeast of the Dalton High‐way between the road and the Sagavanirktok River, and terrain in a heavily disturbed area northwest of the road where Transect 4 was established, that is mostly continuously flooded due to drainage being blocked by the road berm. Transect 5 was established to provide better options for permafrost coring on the west side of the road, since deep flooding and gravel deposits from previous flood events prevented coring on Transect 4. Transect 5 also provides an approximate local analog of the conditions that existed prior to road construction. Data were collected on all three transects during 1-10 August and 16-23 September 2015. Another coring site, Sagavanirktok River Site 1 (SR-1), was established south of the Airport Site along the Sagavanirktok River, where local destruction of the highway caused by flooding from the Sagavanirktok River in spring 2015 created a major disturbance (Shur et al., 2016). More info: http://www.geobotany.uaf.edu/arcsees/
DOI: 10.18739/a2000014j
title: Arctic sea ice seasonal transition metrics from coupled climate model simulations, 1979-2013

description: This dataset includes annual, gridded Arctic sea ice seasonal transition metrics (dates and periods) for fifteen Coupled Model Intercomparison Project version 6 (CMIP6) models and the Community Earth System Model version 1.1 (CESM1.1) Large Ensemble (CESM LE) (Kay, et al., 2015). Seasonal transition dates include melt onset, opening, break-up, freeze onset, freeze-up and closing. Seasonal transition periods include the melt period, the seasonal loss-of-ice period, the freeze period, the seasonal gain-of-ice period, the melt season, the open water period and the outer ice-free period. Data are provided for one ensemble member of the following models: Australian Community Climate and Earth System Simulator CM2 (ACCESS-CM2), Beijing Climate Center Climate System Model 2 MR (BCC-CSM2-MR), Beijing Climate Center Earth System Model 1 (BCC-ESM1), Community Earth System Model 2 (CESM2), Community Earth System Model 2 FV2 (CESM2-FV2), Community Earth System Model 2 Whole Atmosphere Community Climate Model (CESM2-WACCM), Community Earth System Model 2 Whole Atmosphere Community Climate Model FV2 (CESM2-WACCM-FV2), Centre National de Recherches Météorologiques ESM 2-1 (CNRM-ESM2-1), Centre National de Recherches Météorologiques CM 6-1 (CNRM-CM6-1), EC-Earth3, Meteorological Research Institute Earth System Model 2-0 (MRI-ESM2-0), Norwegian Earth System Model 2 LM (NorESM2-LM) and Norwegian Earth System Model 2 MM (NorESM2-MM). Data are provided for 40 members of the Community Earth System Model Large Ensemble (CESM LE), 35 members of Canadian Earth System Model 5 (CanESM5) and 30 members of Institut Pierre Simon Laplace CM6A LR (IPSL-CM6A-LR). The data is stored in netcdf format, and includes metadata in the netcdf files. The raw CMIP6 and CESM LE model output that these transition metrics are calculated from are publicly available at https://esgf-node.llnl.gov/projects/cmip6/ and https://www.earthsystemgrid.org/ respectively.
 This dataset was created to evaluate climate model projections of Arctic sea ice using seasonal transition metrics in the context of both observations and internal variability. It is used in the article Smith, Jahn, Wang (2020), Seasonal transition dates can reveal biases in Arctic sea ice simulations, The Cryosphere, in press. The discussion paper with a link to the final paper can be found at https://doi.org/10.5194/tc-2020-81. This work was conducted at the University of Colorado Boulder from 2019-2020.