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67 results for “ice core”
Ice core, auger hole, conductivity, and shapefile data to determine bottomfast sea ice extent from lagoon sites along the Beaufort Sea Coast, Alaska, 2017-2021
The shapefile represents bottomfast sea ice (BSI) extent in lagoons along the Alaska Beaufort Sea coast during winter and spring, 2017-2021. It was created by digitizing extents from interferograms from the Alaska Satellite Facility Vertex portal. The result is used to identify BSI lateral extent in Arctic lagoons during the growth cycle seasonally. Comparing to future interferograms will identify the trend of BSI within Arctic lagoons. Each feature is attributed with applicable date range and area. Accurate data for the initial growth and maximum extent of BSI could only be collected for the winter and spring months. After the last collection in the spring, there is likely still BSI; however, the surface processes that take place after this point prevent further readings. For early winter time periods, if there are interferograms available (2017 and 2018 data had gaps in interferogram collection as Sentinel-1 was still new), the first date collected can be considered the onset of BSI formation. Ice cores are collected using a Snow, Ice, and Permafrost Research Establishment (SIPRE) corer and measured for salinity. The data is logged in Excel format following Seasonal Ice Zone Observing Network (SIZONet) practices, making it compatible with the PySIC Python toolkit for analysis. The auger data identifies key measurements collected from in-situ observations. Data are collected along five surveys and saved as a single CSV file. The data represent a 1-D representation of each auger hole. The data are used to verify satellite interpretations of BSI extent. The apparent conductivity data includes values at three frequencies (1000 Hz, 4000 Hz, 16000 Hz) recorded during the spring of 2021 in Western Elson Lagoon. Data are saved as an EMI file, which is a CSV format with specific column names and header information. MATLAB scripts to read and interpret data are included in this data package. The apparent conductivity values are used to identify the boundary between floating
Ice, water, and sediment pigment concentrations from Beaufort Sea lagoons core program stations, 2023-24
Bottom ice (< 20 cm), water column, and undisturbed surface sediment samples from the Beaufort Lagoon Ecosystem Long Term Ecological Research programs were collected, in tandem, from core program sites in ice-cover (~April), ice break-up (~June), and open water (~August) seasons of 2023, and ice-cover 2024, to quantify algal pigment concentrations and variations in an annual cycle. We also ran historical samples from 2021 sampling seasons. This data can be used with analysis programs such as CHEMTAX or PhytoClass to elucidate microalgal community structure. Fourteen pigments were measured, including chlorophyll a, fucoxanthin, zeaxanthin, alloxanthin, peridinin, prasinoxanthin, lutein, chlorophyll c<sub>3</sub>, 19-hexanoyloxyfucoxanthin, and 19-butanoyloxyfucoxanthin. Phaeopigments (pheophytin, pheophorbide, and chlorophyllide a) were also included in these analyses. For sediment samples, the values of chlorophyll a, fucoxanthin, zeaxanthin, alloxanthin, peridinin, pheophytin, pheophorbide, and chlorophyllide a can be found in the core program pigment dataset, which is a continuously collected data set (<a href="https://doi.org/10.6073/pasta/5294f45c9c7287903078926a487f1fd7" style="text-decoration: underline;">Sediment pigment concentrations</a>). Pigment concentrations were measured using high-precision liquid chromatography (HPLC). Concentrations are represented as μg L<sup>-1</sup> for both ice and water column samples, and as μg g<sup>-1</sup> for sediment samples.
Supporting data for manuscript "Geochemical Characterization of Insoluble Particle Clusters in Ice Cores Using Two-dimensional Impurity Imaging"
<p>Laser ablation inductively coupled plasma mass spectrometry (LA-ICP-MS) offers micron-resolution 2D chemical imaging, which has been adapted recently to ice core analysis. The datasets are supporting information for the manuscript "Geochemical Characterization of Insoluble Particle Clusters in Ice Cores Using Two-dimensional Impurity Imaging" accepted for publication at Geochemistry, Geophysics, Geosystems (10.1029/2022GC010595). Measurements were performed at the Ca’Foscari University of Venice, considered as analytes are 23Na, 24Mg, 27Al, 29Si, 43Ca, 56Fe and 88Sr. Background and drift correction as well as image construction were performed using the software HDIP (Teledyne Photon Machines, Bozeman, MT, USA). Impurity maps are acquired as a pattern of lines, without overlap in the direction perpendicular to that of the scan, and without any further spatial interpolation. In a sample of the EGRIP Greenland ice core (from about 1256.95 m depth), maps were obtained over 3 adjacent areas. For each of the maps, for every chemical channel the intensities (in counts, after background and drift correction) are provided as a separate file, named as “ds01_Area1_Na.csv”, etc. These maps were obtained using a 20 µm square spot. This data can be used to obtain the images shown in the manuscript. For the additional map shown as Figure 9 in the manuscript, data were obtained using a LA-ICP-TOFMS for imaging a sample of the last glacial period in the EPICA Dome C (EDC) ice core, bag 1065. The maps were acquired using a 35 µm square spot, with 50% overlap between neighboring pixels to increase the spatial resolution horizontally.</p>
ICELEARNING - Detection of ice core particles via deep neural networks
<p>This dataset refers to the ICELEARNING project - Detection of ice core particles via deep neural networks, by Maffezzoli N. et al., <em>The Cryosphere</em>, 10.5194/tc-17-539-2023, 2023.</p> <p>The main folder contains all TRAINING data. </p> <p>The TEST data are contained in the folder /test. </p> <p>Please refer to the <a href="https://github.com/nmaffe/icelearning">icelearning GitHub</a> repository for instructions. </p>
Sulfate Isotope and geochemical ice core data from Dronning Maud Land over the penultimate glacial termination
<p>Sulfur isotope data over the penultimate termination from the EPICA Dronning Maud Land (EDML) ice core as published in Fischer et al., Nature Geosciences, 2024. The file contains:</p> <ul> <li>measured geochemical and sulfur isotope data from the EDML ice core over the time interval 112-153 kyr before present</li> <li>deconvolution of different sulfur sources for the EDML ice core over the time interval 112-153 kyr before present</li> <li>reconstruction of atmospheric sulfate aerosol concentrations from the EDML ice core over the time interval 112-153 kyr before present</li> <li>measured geochemical and sulfur isotope data data from the shallow coastal B38 ice core over the time interval 1964-1968</li> </ul>
Major ions in Trambau ice core, Nepal Himalaya
<p>An 81.2-m-long ice core was drilled in November 2019 at 5862m a.s.l. of Trambau Glacier, Rolwaling region, Nepal Himalaya (27.919° N, 86.545° E). This data set contains the concentrations of major ions and tritium concentrations in the ice core.</p> <p>The data set contains Depth in snow/ice (m), Depth in water equivalent (m w.e.), Date (digit year), Na (ppb), Cl (ppb), NH4 (ppb), K (ppb), Mg (ppb), Ca (ppb), NO3 (ppb), SO4 (ppb), T_rough (TU), T_fine (TU)</p>
Sea ice core temperature and salinity data collected during the 2019 SCALE Winter Cruise
<p>Temperature and salinity profiles of sea ice cores extracted from in situ sea ice floes and lifted pancakes were measured in the Atlantic sector of the Antarctic Marginal Ice Zone during the Southern oCean seAsonal Experiment (SCALE) winter cruise in 2019 (<a href="http://www.scale.org.za">www.scale.org.za</a>) aboard the SA Agulhas II.</p>
Sea ice core temperature and salinity data collected during the 2019 SCALE Spring Cruise
<p>Temperature and salinity profiles of sea ice cores extracted from in situ sea ice floes and lifted pancakes were measured in the Atlantic sector of the Antarctic Marginal Ice Zone during the Southern oCean seAsonal Experiment (SCALE) spring cruise in 2019 (<a href="http://www.scale.org.za">www.scale.org.za</a>) aboard the SA Agulhas II.</p>
Global ice drilling and archive location data for select ice cores
<p>This document includes ice drill site information and ice core repository information for select ice cores retrieved between 1958 and 2022. Included data are not representative of all ice cores drilled during this time period, nor are they representative of all ice core samples collected and maintained by all of the contributing programs and facilities. Data are presented as they were provided by contributing facilities in 2022, when they were used to generate a figure for an article in Past Global Changes Magazine (doi.org/10.22498/pages.30.2.98).</p> <p>The data describe ice core drilling sites (latitude, longitude, elevation, site name), ice core samples (bottom depth, bottom age, core diameter, core completion date, corresponding publications), and ice core storage facilities (latitude, longitude, name).</p> <p>Contributing facilities include the following: Alfred Wegener Institute (Germany), Australian Antarctic Division (Australia), Australian Antarctic Program Partnership (Australia), Byrd Polar Center - University of Ohio (United States of America), Canadian Ice Core Lab (Canada), Chiba University (Japan), Commonwealth Scientific and Industrial Research Organization (Australia), Institute of Environmental Geosciences - University of Grenoble (France), Institute of Low Temperature Science - University of Hokkaido (Japan), Institute of Polar Science and Engineering - Jilin University (China), Karakoram International University (Pakistan), Lanzhou Institute of Glaciology and Geocryology (China), Nagoya University (Japan), National Institute of Polar Research (Japan), National Science Foundation Ice Core Facility (United States of America), New Zealand National Ice Core Facility (New Zealand, Physics of Ice Climate and Earth - University of Copenhagen (Denmark), Polar Research Institute of China (China), Research Institute for Humanity and Nature (Japan), and Tibet University. </p> <p>We are grateful to each of these facilities for contributing details of their ice core collections for this work. </p> <p> </p> <p> </p> <p>Electronic data accessibility and sample request procedures for a few of these facilities of which the authors are aware are listed below.</p> <p>Australia: data can be obtained from the Australian Antarctic Data Centre (<a href="https://urldefense.com/v3/__https://data.aad.gov.au/__;!!K-Hz7m0Vt54!k4oxTmHZ_w1LKmpFwH8LzlfLDG73TEDLZwozl9Q6dL-wfS_EQG7S75R9T3faMQA7BHyK5mv3Br0-kyWRnumedvhR$">https://data.aad.gov.au</a>); access to ice from the Australian Antarctic Program is via application (see <a href="https://urldefense.com/v3/__https://www.antarctica.gov.au/science/information-for-scientists/__;!!K-Hz7m0Vt54!k4oxTmHZ_w1LKmpFwH8LzlfLDG73TEDLZwozl9Q6dL-wfS_EQG7S75R9T3faMQA7BHyK5mv3Br0-kyWRnosG8VPm$">https://www.antarctica.gov.au/science/information-for-scientists/)</a></p> <p>Denmark: data can be obtained from <a href="https://www.iceandclimate.nbi.ku.dk/data/">www.iceandclimate.nbi.ku.dk/data</a>; the ice sampling request procedure is listed here: <a href="https://www.iceandclimate.nbi.ku.dk/data/samplingprocedure/">https://www.iceandclimate.nbi.ku.dk/data/samplingprocedure/</a> </p> <p>United States: many ice core datasets can be found at the NOAA World Data Center (<a href="https://www.ncei.noaa.gov/products/paleoclimatology/ice-core">https://www.ncei.noaa.gov/products/paleoclimatology/ice-core</a>); the allocation policy for ice core samples can be found here: <a href="https://icecores.org/policy">https://icecores.org/policy</a>.</p>
Elbrus Ice Core, Caucasus record of ammonia (NH4+)
<p><span>A deep ice core was drilled to bedrock (182.6 m) in 2009 on the western plateau of <span>Mount Elbrus </span>(ELB, 43°N, 42°E; 5115 m above sea level, asl) in the Caucasus (Russia).</span><span> </span><span>The upper 168.6 m (131.5 meters</span><span> </span><span>water equivalent, mwe) depth of the ice core were first dated by annual layer counting using pronounced seasonal variations in ammonium and succinate concentrations, both exhibiting well-marked winter minima (Mikhalenko et al., 2015; Preunkert et al., 2019). <span>Chemical measurements were done with a Dionex ICS-1000 chromatograph equipped with a CS12 separator column for cations </span>(Na<sup>+</sup>, K<sup>+</sup>, Mg<sup>2+</sup>, Ca<sup>2+</sup>, and NH<sub>4</sub><sup>+</sup>), a Dionex 600 equipped with an AS11 separator column for anions (Cl<sup>-</sup>, NO<sub>3</sub><sup>-</sup>, and SO<sub>4</sub><sup>2-</sup>) and light carboxylates. Detailed working conditions are given in Legrand et al. (2013). <span>Using the winter ammonium/succinate minima we determined half-year summer and winter means of of ammonia (NH4+) from 1748 to 2009.</span></span></p>
Model Output and Figure Scripts for: "Uncertainty in reconstructing paleo-elevation of the Antarctic Ice Sheet from temperature-sensitive ice core records"
<p>New climate model output and figure scripts for the paper "Uncertainty in reconstructing paleo-elevation of the Antarctic Ice Sheet from temperature-sensitive ice core records".</p>
Sea ice core biogeochemical data collected during the 2019 SCALE Winter Cruise
<p><strong>Title: </strong>Biogeochemical profiles of sea ice cores sampled during the Southern oCean seAsonal Experiment (SCALE) winter cruise in 2019.</p> <p> </p> <p><strong>Authors:</strong> Riesna R. Audh, Siobhan Johnson, Mark Hambrock, Hazel Little, Joshua Mirkin, Emmanuel Omatuku, Benjamin Hall, Tokoloho Rampai, Keith MacHutchon, Sebastian Skatulla, Sarah E. Fawcett, Marcello Vichi</p> <p> </p> <p><strong>Data Description:</strong></p> <p> </p> <p><strong>Abstract</strong></p> <p>Biogeochemical profiles of sea ice cores extracted from in situ sea ice floes and lifted pancakes were measured in the Atlantic sector of the Antarctic Marginal Ice Zone during the Southern oCean seAsonal Experiment (SCALE) winter cruise in 2019 (<a href="http://www.scale.org.za">www.scale.org.za</a>) aboard the SA Agulhas II.</p> <p> </p> <p>A total of four sea ice cores (cores) were sampled during the cruise. Two cores were collected overboard on a consolidated floe that was accessed via a personnel carrier suspended by the ship’s forward crane. Two cores were collected from a pancake that was lifted aboard the ship via a net that was attached to the ship’s aft crane and placed on the helideck for sampling. Profiles were obtained by cutting the cores using a bandsaw in a cold laboratory at -10 °C. The cores were cut into approximately 0.05 m segments, starting from the bottom of the core. These segments were allowed to melt in the dark in an insulated box. The meltwater was filtered for chlorophyll measurements (Welschmeyer, 1994) and the filtrate was analysed for oxygen isotopes (Walker and others, 2015), ammonium (Holmes et al., 1999), phosphate, nitrate, nitrite and silicate (using a SEAL AA500 segmented flow autoanalyser). These values are reported at the depth of the top of the segment in the core in μM. In order to facilitate comparison with the seawater concentrations below the ice, the in-ice nutrients (including NH4+) were salinity normalised using the equation of Fripiat and others (2017):</p> <p> </p> <p><em>C</em><em>norm</em><em> = C</em>SwS<em> </em><em> </em></p> <p> </p> <p>Where C is the measured bulk concentration, Sw is the salinity of the seawater, and S is the corresponding measured bulk salinity of the ice segment.</p> <p> </p> <p>Although sampling of the core occurred from the bottom of the core to the top of the core, the data are reported as the top of the core (snow/ice interface) being 0 m (depth=0 m). </p> <p> </p> <p><strong>This research has been funded by the National Research Foundation of South Africa (NRF)</strong></p> <p><br> </p> <p><strong>Cruise:</strong> VOY-038 (SCALE2019-WINTER) (URL: https://scale.org.za/)</p> <p><strong>Station(s):</strong> VOY-038-MIZ3A</p> <p>VOY-038-MIZ1D</p> <p><strong>Position(s):</strong> -58.13783 S; 0.00442 W</p> <p>-56.8017 S; 0.30262 E</p> <p><strong>Date/Time:</strong> 2019-07-27/10:38:00</p> <p>2019-07-28/09:15:00</p> <p><strong>Method(s):</strong> Overboard coring</p> <p>Pancake lifting via aft crane, on deck coring</p> <p><strong>Parameters:</strong><strong> </strong>Station Number (Station)</p> <p>Date/Time of station (Date/Time)</p> <p>Latitude of station (Latitude)</p> <p>Longitude of station (Longitude)</p> <p>Ice type (Ice Type)</p> <p>Core ID(Core), Pancake identifier A/B/C/D</p> <p>Oxygen isotopes (d18O)</p> <p>Chlorophyll (Chl-a)</p> <p>Ammonium (NH4)</p> <p>Nitrate + Nitrite (NO3+NO2)</p> <p>Nitrite (NO2)</p> <p>Phosphate (PO4)</p> <p>Silicate (Si)</p> <p>Nitrate (NO3)</p> <p>Salinity of the ice segment from physical cores (IceSalinity)</p> <p>Standard deviation of the salinity average from physical cores (IceSalinityStdev)</p> <p>Seawater salinity from CTD (SeawaterSalinity)</p> <p>Salinity normalised nitrate+nitrite (N03+N02_Avg_SalinityNormalised)</p> <p>Salinity normalised ammonium (NH4_SalinityNormalised)</p> <p>Salinity normalised nitrite (NO2_SalinityNormalised)</p> <p>Salinity normalised phosphate (PO4_SalinityNormalised)</p> <p>Salinity normalised silicate (Si_SalinityNormalised)</p> <p>Salinity normalised nitrate (NO3_SalinityNormalised)</p> <p><br> </p> <p> </p> <p><strong>Keywords: </strong>sea ice cores, Antarctica, pancake ice, sea ice, biogeochemistry, winter</p> <p> </p> <p><strong>References</strong><strong>:</strong></p> <p> </p> <p>Fripiat, F., Meiners, K.M., Vancoppenolle, M., Papadimitriou, S., Thomas, D.N., Ackley, S.F., Arrigo, K.R., Carnat, G., Cozzi, S., Delille, B. and Dieckmann, G.S., 2017. Macro-nutrient concentrations in Antarctic pack ice: Overall patterns and overlooked processes. Elementa: Science of the Anthropocene, 5. </p> <p> </p> <p>Holmes, R.M., Aminot, A., Kérouel, R., Hooker, B.A. and Peterson, B.J., 1999. A simple and precise method for measuring ammonium in marine and freshwater ecosystems. Canadian Journal of Fisheries and Aquatic Sciences, 56(10), pp.1801-1808. </p> <p> </p> <p>Walker, S.A., Azetsu‐Scott, K., Normandeau, C., Kelley, D.E., Friedrich, R., Newton, R., Schlosser, P., McKay, J.L., Abdi, W., Kerrigan, E. and Craig, S.E., 2016. Oxygen isotope measurements of seawater (18O/16O): A comparison of cavity ring‐down spectroscopy (CRDS) and isotope ratio mass spectrometry (IRMS). Limnology and Oceanography: Methods, 14(1), pp.31-38. </p> <p> </p> <p>Welschmeyer, N., 1994. A method for the determination of chlorophyll a in the presence of chlorophyll b and pheopigments. Limnology and Oceanography, 39, pp.1985-1992. </p> <p> </p>
Three reconstructions of the formation of large open ocean polynyas in the Southern Ocean using ice core records
<p>The dataset contains the indices for three reconstructions of open ocean polynya formation in the Southern Ocean over the period 1250-1990 and their uncertainties. See the associated publication</p> <p>Goosse H., Dalaiden Q., Cavitte M.G.P., Zhang L. Can we reconstruct the formation of large open ocean polynyas in the Southern Ocean using ice core records? Climate of the past 2020. <a href="https://doi.org/10.5194/cp-2020-91">https://doi.org/10.5194/cp-2020-91</a></p> <p>The data are included in a text file. The first column is the time (in years). The next six columns are the three reconstructions using data assimilation with SPEAR_AM2 (DA AM2), using data assimilation with SPEAR_LO (DA LO) and a simple average of standardized time series (Stat), each of them directly followed by their uncertainties. The uncertainties are estimated from the standard deviation of the seven reconstructions using different combinations of the available ice core records.</p> <p>Please contact <a href="mailto:hugues.goosse@uclouvain.be">Hugues Goosse</a>(hugues.goosse@uclouvain.be) for more information.</p>
RESICE - Reusability-targeted Enriched Sea Ice Core Database - Part A
<div> <div>RESICE is described in detail in the article <em>Reusability-targeted enrichment of sea ice core data</em> published on 2025-03-20 in Scientific Data (DOI: <a href="https://doi.org/10.1038/s41597-025-04665-x" target="_blank" rel="noopener">10.1038/s41597-025-04665-x</a>). This is Part A of RESICE. RESICE_PartA.csv contains all data including profile data (several rows per core), RESICE_PartA_cores.csv provides all data excuding profile data (one row per core) and sources_PartA.csv provides a list of all sources. The database including its <a title="RE-SICE Part B" href="https://www.doi.org/10.5281/zenodo.14744942" target="_blank" rel="noopener">Part B</a> is described in the <a title="RE-SICE General Information" href="https://www.doi.org/10.5281/zenodo.14744912" target="_blank" rel="noopener">general information. </a>Part A and Part B had to be separated due to different licenses of the orginal data sources.</div> </div>
RESICE - Reusability-targeted Enriched Sea Ice Core Database - General Information
<div> <div>RESICE is described in detail in the article <em>Reusability-targeted enrichment of sea ice core data</em> published on 2025-03-20 in Scientific Data (DOI: <a href="https://doi.org/10.1038/s41597-025-04665-x" target="_blank" rel="noopener">10.1038/s41597-025-04665-x</a>).</div> <div> </div> <div>A large number of sea ice core data sets are available that have been acquired by research groups around the world and published in different data repositories. The structure of sea ice core data differs substantially across repositories and entries regarding combinations of content, level and quality of description, label names, formats, units, etc. Here, we have compiled sea ice core data and metadata available in data sets (DS) into a tabular database. Additionally, we have added data and metadata from articles (A) and expedition reports (ER). We have enriched the database with metadata from instrument manuals (IM) and controlled terminologies (CT) such as the <a title="SIN" href="https://library.wmo.int/idurl/4/41953" target="_blank" rel="noopener"><em>Sea Ice Nomenclature</em></a> (SIN) from the World Meteorological Organization (WMO) and the <a title="SeaVoX Polygons" href="https://doi.org/10.14284/590" target="_blank" rel="noopener"><em>Polygon data set of water body extent from the SeaVoX Salt and Fresh Water Body Gazetteer</em></a> by the British Oceanographic Data Centre (BODC). We grouped the type of sources into primary sources (DS), secondary sources (A, ER), and tertiary sources (IM, CT). RESICE enhances reusability of the included sea ice core data through enrichment. RESICE provides a comprehensive resource for sea ice modeling applications that aim at using information from compiled sea ice core data. Some examples are calibration and validation of physics-based process models addressing the generation and evolution of sea ice or the training of data-driven models that rely on harmonized training data. As data and metadata are combined from many sources, each entry in the data set needs to be traceable to the original source and its corresponding DOI or URL. Where appropriate, we refer to the original excerpt, figure or table of the original source or comment on inconsistencies or required changes to transparently communicate the entries origin. This is the general information on the database. Please find <a title="RESICE Part A" href="https://www.doi.org/10.5281/zenodo.14745035" target="_blank" rel="noopener">Part A</a> of the database that can be reused under license CC-BY, and <a href="https://www.doi.org/10.5281/zenodo.14744942">Part B</a> of the database that can be reused under license CC-BY-SA. RESICE can be interactively viewed, analyzed and plotted in the <a title="MOSAiC webODV" href="https://mvre.webodv.cloud.awi.de/DataExploration/id/DVevtE7c">MOSAiC webODV</a> instance. RESICE can be reproduced and extended with the <a title="pyresice Python package" href="https://doi.org/10.5281/zenodo.11198658" target="_blank" rel="noopener">pyresice</a> Python package available on <a title="pyresice gitLab" href="https://git.rwth-aachen.de/mbd/pyresice/" target="_blank" rel="noopener">gitLab</a>.</div> </div>
Predictive simulations of core electron binding energies of halogenated species adsorbed on ice surfaces from relativistic quantum embedding calculations
<p>This dataset collects the unprocessed (= outputs from calculations) and processed (= plots, average values for orbital and ionization energies) results discussed in the paper titled "Predictive simulations of core electron binding energies of halogenated species adsorbed on ice surfaces from relativistic quantum embedding calculations" by Richard Asamoah Opoku, Céline Toubin, and André Severo Pereira Gomes.</p>
Ice core and model data for Moseid et al. 2022
<p>These datasets are used in the publication "Using ice cores to evaluate CMIP6 aerosol concentrations over the historical era" with the authors Kine Onsum Moseid, Michael Schulz, Anja Eichler, Margit<br> Schwikowski, Joseph R. McConnell, Dirk Olivi ́e, Alison S. Criscitiello, Karl J. Kreutz, and Michel Legrand.</p> <p>The paper is currently in review when this data is published.</p> <p>The excel sheet dataset contains sulfate and black carbon records from 15 ice cores as presented in the paper. </p> <p>One zip file contain the part of the data from NorESM2-LM experiments as described in the paper. Another dataset will be published to compliment this dataset. </p>
Ice Core Measurements - Northern Norwegian Fjord Ice - Winter 2018/2019
<p>Dataset from the 2018-2019 field season in six northern Norwegian fjords including ice bulk salinity and d18O, seawater salinity and d18O, and river water d18O. The fjords included are Beisfjord (Nordland), Lavangen (Nordland), Nordkjosbotn (Tromsø), Storfjord (Tromsø), Storfjord (Tromsø), Ramfjord (Tromsø), and Kattfjord (Tromsø).</p>
Results of ultrasound measurements of sea-ice cores sampled during the Southern oCean seAsonal Experiment (SCALE) winter cruise in 2019
<p>This dataset details the results of testing sea ice cores collected during the SCALE 2019 Winter Cruise using ultrasound techniques. </p>
Water isotopic composition (Oxygen-18 and Deuterium) from the EPICA Dome C ice core at 11 cm resolution
<p>This manuscript presents a compilation of high resolution (11 cm) water isotopic records including published and new measurements over the last 800 000 years on the EPICA Dome C ice core, Antarctica. Using this new water isotopes (δ18O and δD) combined dataset, we study the variability and possible influence of diffusion at multi-decadal to multi-centennial scale. We observe a stronger variability on the onset of the interglacial interval corresponding to a warm period.</p>
ScienceDex guides
Understand access before you commit
These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.