Find research datasets worth reusing
Search datasets from major research repositories and use ShareScore to quickly assess how well each record supports discovery, access, and reuse.
186
datasets available to search
ShareScore release 0.9.0
Dataset results
186 results for “Ice Sheet”
Annual Ice Velocity of the Greenland Ice Sheet (1972-1990)
Open the record for dataset details and reuse information.
Ice sheet effects to the Asian winter monsoon since the Last Glacial Maximum
<p><strong><em>Modern climate data, surface sediment dataset, <em><strong> Simu</strong></em>lations of TRACE and PMIP3.</em></strong></p>
Alpine ice sheet glacial cycle simulations animation frames
<p>These data contain a visualization achieved by spatial interpolation of time-dependent glacier model output variables onto higher-resolution topography data than the one used in the model. The animation resulting of all frames combined (English version) can be visualized at <a href="https://vimeo.com/322189870">https://vimeo.com/322189870</a>.</p> <p><strong>References:</strong></p> <ul> <li>Seguinot, J., Ivy-Ochs, S., Jouvet, G., Huss, M., Funk, M., and Preusser, F.: Modelling last glacial cycle ice dynamics in the Alps, <em>The Cryosphere</em>, 12, 3265-3285, doi:<a href="https://doi.org/10.5194/tc-12-3265-2018">10.5194/tc-12-3265-2018</a>, 2018.</li> <li>Seguinot., J. (2020). Alpine ice sheet glacial cycle simulations continuous variables, <em>Zenodo</em>, doi:<a href="http://doi.org/10.5281/zenodo.3604142">10.5281/zenodo.3604142</a>, 2020.</li> </ul> <p><strong>File names:</strong></p> <pre><code>anim_alps_4k_*.zip</code></pre> <ul> <li>Main animation layer <ul> <li><em>main_al_co_1ka</em>: color frames every 1 ka</li> <li><em>main_al_co_200a</em>: every 200 a except every 1 ka</li> <li><em>main_al_co_1ka</em>: every 40 a except every 200 a</li> </ul> </li> <li>Animation overlays <ul> <li><em>city_al</em>: fixed-frame city overlays in multiple languages</li> <li><em>tbar_??_1200</em>: time bar overlay in multiple languages</li> </ul> </li> </ul>
Inland limits to diffusion of thinning along Greenland Ice Sheet outlet glaciers
<p>This dataset contains limits to the inland diffusion of terminus-initiated thinning along 141 Greenland Ice Sheet outlet glaciers. The data is separated in 187 files and each file contains data for an individual outlet glacier or a branch of an outlet glacier. Shapefiles and NetCDF files are provided with data for 6 primary flowlines, and up to 18 iterated flowlines, spanning the width of each glacier. The iterated flowlines are used to find the furthest inland thinning limits (see the associated publication for more details). Files are named <em>glacierXXXX </em>where <em>XXXX </em>is the identifier for an individual glacier or branch. Identifiers that begin with a letter ('a', 'b', 'c', or 'd') represent a separate branch of an outlet glacier. Shapefiles filenames have an additional <em>_iterNN </em>suffix, where <em>NN</em> identifies the iteration number of that set of flowlines.</p> <p>The shapefiles contain multiple features, each of which is one flowline. Each flowline has a "flowline" attribute, a two-digit identifier that corresponds to the same identifier in the NetCDF files. The NetCDF files contains glacier geometry, dynamic thinning, Peclet number, and identified knickpoints, extracted and calculated along the primary and iterated flowlines. The flowlines in the NetCDF files have a regular 50-meter spacing between nodes, whereas the flowlines in the shapefiles have a coarser and irregular spacing.</p> <p>More information on how the flowlines were derived and how data was extracted and calculated is in the associated publication (Felikson et al., 2020), with a DOI to be provided. Example code that can be used to read and plot the data can be obtained at http://doi.org/10.5281/zenodo.4284715.</p>
Marine Ice Sheet Experiments CISM 2021
This work aims at investigating the numerical properties of the Community Ice Sheet Model (CISM) using idealized marine ice sheet set up from the MISMIP3d and MISMIP+ experiments. These experiments have the goal in testing CISM to infer model configuration for real Antarctic simulations. In these experiments we investigate several parameters such as stress balance approximation, basal friction law, grounding line parameterization, basal melt parameterization, and resolution. These simulations combine steady state and transient simulations.
Chapter 3 - A highly-dynamic East Antarctic Ice Sheet during the Miocene: A multi-proxy sedimentary provenance approach using in-situ 87Rb/87Sr dating of detrital K-feldspar in ODP Site 1165, Prydz Bay
Open the record for dataset details and reuse information.
Data for "Antarctic ice-sheet meltwater reduces transient warming and climate sensitivity through the sea-surface temperature pattern effect"
<p>Data of the Historical Hosing simulations presented in "Antarctic ice-sheet meltwater reduces transient warming and climate sensitivity through the sea-surface temperature pattern effect" submitted to Geophysical Research Letters</p> <p>Authors: Yue Dong, Andrew G. Pauling, Shaina Sadai, Kyle C. Armour </p> <p>Abstract:</p> <p>Coupled global climate models (GCMs) generally fail to reproduce the observed sea-surface temperature (SST) trend pattern since the 1980s. The model-observation discrepancies may arise in part from the lack of realistic Antarctic ice-sheet meltwater imbalance in GCMs. Here we employ two sets of CESM1-CAM5 simulations forced by anomalous Antarctic meltwater fluxes over 1980--2013 and into the 21st century. Both show a reduced global warming rate and an SST trend pattern that better resembles observations. The meltwater drives surface cooling in the Southern Ocean and the tropical southeast Pacific, in turn increasing low-cloud cover and driving radiative feedbacks to become more stabilizing (corresponding to a lower effective climate sensitivity). These feedback changes contribute more than ocean heat uptake efficiency changes in reducing the global warming rate. Accurately projecting historical and future warming thus requires improved representation of Antarctic meltwater and its impacts in models. </p>
Chapter 4 – Characterising the Gamburtsev Subglacial Mountains by detrital apatite, rutile, and titanite U-Pb dating and trace element analysis: How passive tectonics led to inception of the Antarctic Ice Sheet
Open the record for dataset details and reuse information.
Chapter 2 - Dynamic collapse and regrowth of the Antarctic Ice Sheet in the Weddell Sea Sector during the Middle Miocene: A novel multi-proxy sedimentary provenance approach using in-situ 87Rb/87Sr dating of detrital K-feldspar - Supplementary Materials
Open the record for dataset details and reuse information.
Mass Balance and Velocity Data for Greenland Ice Sheet at High Elevations
<p>This is an estimation of mass balance of the Greenland Ice Sheet at higher elevations, computed as the difference between the estimated annual total snow accumulation and ice discharge. Measurements are taken at 161 stations located 30 km apart, at 2000 m elevation that circumnavigates Greenland. Ice velocities are determined from GPS data, and ice thickness from ice-penetrating radar. Results are presented for single gates between adjacent stations, and gate combinations representing larger areas.</p> <p><strong>Interactive Map</strong><br><a href="http://rsl.geology.buffalo.edu/data/Pages/Greenland_MB_AllGates.html" target="_blank" rel="nofollow noreferrer noopener noreferrer noopener noreferrer">http://rsl.geology.buffalo.edu/data/Pages/Greenland_MB_AllGates.html</a></p> <p><strong>NSIDC page</strong><br><a href="https://nsidc.org/data/NSIDC-0618" target="_blank" rel="nofollow noreferrer noopener noreferrer noopener noreferrer">https://nsidc.org/data/NSIDC-0618</a></p> <p><strong>References</strong></p> <ul> <li>Thomas, R., T. Akins, B. Csatho, M. Fahnestock, P. Gogineni, C. Kim, and J. Sonntag. 2000. Mass balance of the Greenland Ice Sheet at high elevations. Science 289: 426-427.</li> <li>Thomas, R., B. Csatho, C. Davis, C. Kim, W. Krabill, S. Manizade, J. McConnell and J. Sonntag. 2001. Mass balance of higher-elevation parts of the Greenland Ice Sheet. Journal of Geophysical Research - Atmosphere 106 (D24) (December): 33707-33716.</li> <li>Thomas, R., B. Csatho, S. Gogineni, K. Jezek, and K. Kuivinen. 1998. Thickening of the western part of the Greenland Ice Sheet. Journal of Glaciology 44: 653-658.</li> </ul>
Retreat of the Greenland Ice Sheet leads to divergent patterns of reconfiguration at its freshwater and tidewater margins
<p>Datasets to accomany paper.</p>
Supporting data and files for PNAS paper entitled Ice sheet contributions to future sea level rise from structured expert judgement.
<p>This repository contains supporting documentation with background information about the structured expert judgement described in the paper entitled: Ice sheet contributions to future sea level rise from structured expert judgement.. It also includes the files containing the anonymous expert judgements for the target questions elicited.</p>
Data files used in the paper "First Radar Evidence of Large-Scale Englacial Folding in the South Polar Layered Deposits (Ultimi Scopuli, Mars) and Possible Ice Sheet Flow Unveiled by MARSIS" By Guallini et al.
<p>This archive contains radargrams, geometric information and visualizations of a subset of MARSIS radar observations over Planum Australe, Mars. This archive contains everything needed to reproduce the results presented in the paper "Large-scale folds detected by MARSIS in the Southern ice sheet of Ultimi Scopuli (Mars)" by Guallini et al.</p> <p>Three types of MARSIS data files are contained in this archive:</p> <p>* orbit_XXXXX_frequency_Y_MHz_radargram.csv, where XXXXX is the orbit number, and Y the frequency at which the radar was operating, in MHz. The file contains an ASCII table of real numbers separated by commas. The table has as many columns as the number of radar echoes acquired during the orbit (usually 3200), and 980 lines, one for each echo sample. Values are samples of the uncalibrated echo voltage, without phase information (i.e. positive real numbers instead of complex echo samples). Echo samples are acquired every 0.3571 microseconds (2.8 MHz sampling rate). The first sample of an echo is located at a round-trip time corresponding to an altitude of 25 km above the Martian IAU ellipsoid.</p> <p>* orbit_XXXXX_frequency_Y_MHz_geometry.csv, where XXXXX is the orbit number, and Y the frequency at which the radar was operating, in MHz. The file contains an ASCII table of real numbers separated by commas. The table has as many rows as the number of radar echoes acquired during the orbit (usually 3200), and contains the following auxiliary parameters:</p> <p> - EPHEMERIS TIME - Number of seconds elapsed since Jan 1, 2000, 12:00 UTC corresponding to the time at which data collection for the current echo started.</p> <p> - MARS SOLAR LONGITUDE - Angle between the Mars-Sun line at the time corresponding to EPHEMERIS TIME and the Mars-Sun line at the vernal equinox, in degrees.</p> <p> - MARS SUN DISTANCE - Distance from the centre of Mars to centre of the Sun at the time corresponding to EPHEMERIS TIME, in Km.</p> <p> - SPACECRAFT ALTITUDE - Distance from the Mars Express spacecraft to the reference surface of the target body measured normal to the surface at the time corresponding to EPHEMERIS TIME, expressed in Km.</p> <p> - SUB-SPACECRAFT LONGITUDE - East longitude of the point on the target body that lies closest to the Mars Express spacecraft at the time corresponding to EPHEMERIS TIME, expressed in degrees and in the [ 0 -360 ] range.</p> <p> - SUB-SPACECRAFT LATITUDE - Planetocentric latitude of the point on the target body that lies directly beneath the Mars Express spacecraft at the time corresponding to EPHEMERIS TIME, expressed in degrees.</p> <p> - RADIAL VELOCITY - Radial component of the Mars Express spacecraft velocity vector in the reference frame of the target body at the time corresponding to EPHEMERIS TIME, expressed in Km/s.</p> <p> - TANGENTIAL VELOCITY - Tangential component of the Mars Express spacecraft velocity vector in the reference frame of the target body at the time corresponding to EPHEMERIS TIME, expressed in Km/s.</p> <p> - LOCAL TRUE SOLAR TIME - Angle between the extension of the vector from the Sun to Mars and the projection on Mars' ecliptic plane of a vector from the center of the target body and the point on the target body surface that lies directly beneath the Mars Express spacecraft at the time corresponding to EPHEMERIS TIME, expressed on a 24-hour clock with decimal fractions of the hour.</p> <p>* orbit_XXXXX_frequency_Y_MHz.png, where XXXXX is the orbit number, and Y the frequency at which the radar was operating, in MHz. The file is a visualization of the corresponding radargram, of the spacecraft ground track during the observation, and of surface and subsurface echo power.</p>
Annual Ice Velocity of the Greenland Ice Sheet (2010-2017)
Open the record for dataset details and reuse information.
MEaSUREs Greenland Ice Sheet Mosaics from SAR Data, Version 1
This data set, part of the NASA Making Earth System Data Records for Use in Research Environments (MEaSUREs) program, contains high resolution mosaics of radar backscatter for the Greenland Ice Sheet derived from synthetic aperture radar (SAR) data. Both calibrated and uncalibrated mosaics are available for: the winters of 2000-2001, 2005-2006 through 2008-2009, and 2012-2013; and a multiyear composite. Uncalibrated mosaics are available for the winter of 2009-2010. All mosaics are provided at both 100 m and 20 m resolutions.See <a href="http://nsidc.org/data/measures/gimp">Greenland Ice Mapping Project (GIMP)</a> for related data.
Greenland Ice Sheet Melt Characteristics Derived from Passive Microwave Data, Version 1
The Greenland ice sheet melt extent data, acquired as part of the NASA Program for Arctic Regional Climate Assessment (PARCA), is a daily (or every other day, prior to August 1987) estimate of the spatial extent of wet snow on the Greenland ice sheet since 1979. It is derived from passive microwave satellite brightness temperature characteristics using the Cross-Polarized Gradient Ratio (XPGR) of Abdalati and Steffen (1997). It is physically based on the changes in microwave emission characteristics observable in data from the Scanning Multi-channel Microwave Radiometer (SMMR) and the Special Sensor Microwave/Imager (SSM/I) instruments when surface snow melts. It is not a direct measure of the snow wetness but rather is a binary indicator of the state of melt of each SMMR and SSM/I pixel on the ice sheet for each day of observation. It is, however, a useful proxy for the amount of melt that occurs on the Greenland ice sheet. The data are provided in a variety of formats including raw data in ASCII format, gridded daily data in binary format, and annual and complete time series climatologies in gridded binary and GeoTIFF format. All data are in a 60 x 109 pixel subset of the standard Northern Hemisphere polar stereographic grid with a 25 km resolution and are available via FTP.
Digital SAR Mosaic and Elevation Map of the Greenland Ice Sheet, Version 1
The Digital SAR Mosaic and Elevation Map of the Greenland Ice Sheet combines the most detailed synthetic aperture radar (SAR) image mosaic available with the best current digital elevation model. The mosaic image shows both the location of the ice edge and the distribution of melt-related 'scatterers' on the surface. These scatterers include ice lenses and complex layered structure in the percolation zone and bare ice of the ablation zone. Other melt-related features that can be seen include lake and surface meltwater stream channels at lower elevations, as well as ice-marginal lakes.This characterization of the ice sheet provides a reference against which future change can be measured. Changing conditions resulting from climatic variation should show up as changes in the ice margin and shifts in the hydrologic zones. It is hoped that the standard reference provided by this data set can facilitate activities aimed at change detection and promote other work aimed at understanding the processes operating on the ice sheet.The image data are derived from SAR image swaths acquired by the ERS-1 satellite during August of 1992. The mosaic was assembled at the Jet Propulsion Laboratory (JPL) and Goddard Space Flight Center (GSFC). Its component images are a copyrighted product of the European Space Agency. The mosaic, a value-added derived product, is available to individuals and non-profit organizations for research oriented purposes only. The Danish geodetic and cadastral agency Kort-og Matrikelstyrelsen (KMS) compiled the elevation data provided with the product from a number of sources, including field surveys, aerial photographs, and the ERS-1 radar altimeter.
Elevation Change of the Southern Greenland Ice Sheet from 1978-88, Version 1
Southern Greenland ice sheet elevation change estimates are derived from SEASAT and GEOSAT radar altimetry data from 1978 to 1988. Data are confined to 61-72 deg N, 30-50 deg W, above 1700 m elevation. The addition of GEOSAT Geodetic Mission (GM) data results in twice as many crossover points and 50% greater coverage than previous studies. Coverage above 2000 m elevation is improved to 90%, and about 75% of the area between 1700 m and 2000 m is now covered. Data are in ASCII text format, available via FTP, and consist of elevation change rate (dH/dt, cm/year) and corresponding error estimates in 50 km grid cells.
Seasat and GEOSAT Altimetry for the Antarctic and Greenland Ice Sheets, Version 1
<p><font color="#FF0000">Note: This data set is now on HTTPS so references to CD-ROM are historic and no longer applicable.</font></p>The Ice Altimetry System (IAS) data seet contains surface elevations of the Antarctic and Greenland ice sheets derived from Seasat and GEOSAT radar altimetry data. The Seasat data were collected for a continuous 90 days in 1978, at latitudes between 72 degrees South and 72 degrees North. GEOSAT was launched in 1985 and placed in a nearly identical orbit to Seasat, also at latitudes of between 72 degrees South and 72 degrees North. The orbit was designed to provide high-density measurements over the Earth's surface, at a maximum grid spacing of 2.7 kilometers at the equator and much denser spacing over polar ice sheets. Data were acquired between April 1985 and September 1986.Initially acquired by the Johns Hopkins APL (Applied Physics Lab) satellite tracking facility, the raw altimetry satellite data from Seasat and GEOSAT were passed on to NASA, via the US Navy. NASA developed slope correction routines for the higher slopes over the ice sheets, relative to ocean surfaces. The data are height profile Level 3 data and gridded height Level 4 data provided by the Oceans and Ice branch of the Laboratory for Hydrospheric Physics of Goddard Space Flight Center. Elevations from the full data rate (i.e., one measurement every 662.5 m) are provided in georeferenced databases. These elevations are relative to the WGS-84 ellipsoid. Gridded elevations at 10-kilometer and 20-kilometer spacing are provided in the gridded data sets created from the GEOSAT and Seasat data, respectively. Software to extract and browse subsets of these data is included. The IAS software also allows the user to view contours created from the gridded data and groundtracks of the full-rate data.
Output of CAM simulations performed for study "Impact of cloud physics on the Greenland Ice Sheet near-surface climate: a study with the Community Atmosphere Model"
<p>Output of CAM simulations performed for study "Impact of cloud physics on the Greenland Ice Sheet near-surface climate: a study with the Community Atmosphere Model" in JGR-Atmospheres (2020). </p> <p>Output are NetCDF files containing annual means (named 'yearmean', 2007-2013), or multi-annual monthly means ('ymonmean', 2007-2012) of various variables that are of interest and/or used for analysis in this study. The file name starts with the variable name. Fields are global, at a resolution of 0.9 x 1.25 degrees latitude/longitude.</p> <p>The test simulations are named (as discussed in the paper):</p> <p>cam4_clm5<br> cam5_clm5<br> cam6_noicenucl_clm5<br> cam6_noclubb_clm5<br> cam6_mg1_clm5<br> cam6</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.