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.
79
datasets available to search
ShareScore release 0.9.0
Dataset results
79 results for “ice thickness”
Ice thickness and bed elevation of the Northern and Southern Patagonian Icefields
Open the record for dataset details and reuse information.
ICECAP-2 consortium processed airborne ice thickness data from the Princess Elizabeth Land, East Antarctica
<p>Airborne ice thickness data from the Princess Elizabeth Land (PEL), East Antarctica was collected in four separate seasons. During the first ICECAP2 season (2015/16), a survey acquiring exploratory ‘fan-shaped’ radial profiles to maximize range and data return on each flight was completed across the broadly unknown region of PEL. These flight lines extend from the coastal Progress Station to the interior ice-sheet divide at Ridge B. In the second and third seasons (2016/17 and 2017/18), a survey ‘grid’ was completed, targeting enhanced resolution over a proposed subglacial lake and a series of basal canyons (Jamieson et al., 2016). In the fourth season (2018/19), a few additional transects were completed to fill the largest data gaps within aircraft range. Field data acquisition was achieved using the “Snow Eagle 601” aero geophysical platform; a BT-67 airplane operated by the Polar Research Institute of China for the Chinese National Antarctic Research Expedition (CHINARE) program. The suite of instruments configured on the airplane include a phase-coherent radio-echo sounder system, operating at a central frequency of 60 MHz and a peak power of 8 kW, making it capable of penetrating deep (>3 km) ice in Antarctica. After applying coherent integration and pulse compression at a bandwidth of 15 MHz, which gave an along-track spatial sampling rate and a vertical resolution of ~10 m and ~5.6 m, respectively.</p>
Small Variations in Ice Composition and Layer Thickness Explain Bright Reflections Below Martian Polar Cap Without Liquid Water
<p>These files include the model results used in Lalich et al. 2024 as well as the code necessary to analyze and reprooduce those results. See README for more detail. </p>
ECCO Sea-Ice and Snow Concentration and Thickness - Daily Mean 0.5 Degree (Version 4 Release 4)
This dataset contains daily-averaged sea-ice and snow concentration and thickness interpolated to a regular 0.5-degree grid from the ECCO Version 4 revision 4 (V4r4) ocean and sea-ice state estimate. Estimating the Circulation and Climate of the Ocean (ECCO) ocean and sea-ice state estimates are dynamically and kinematically-consistent reconstructions of the three-dimensional, time-evolving ocean, sea-ice, and surface atmospheric states. ECCO V4r4 is a free-running solution of the 1-degree global configuration of the MIT general circulation model (MITgcm) that has been fit to observations in a least-squares sense. Observational data constraints used in V4r4 include sea surface height (SSH) from satellite altimeters [ERS-1/2, TOPEX/Poseidon, GFO, ENVISAT, Jason-1,2,3, CryoSat-2, and SARAL/AltiKa]; sea surface temperature (SST) from satellite radiometers [AVHRR], sea surface salinity (SSS) from the Aquarius satellite radiometer/scatterometer, ocean bottom pressure (OBP) from the GRACE satellite gravimeter; sea ice concentration from satellite radiometers [SSM/I and SSMIS], and in-situ ocean temperature and salinity measured with conductivity-temperature-depth (CTD) sensors and expendable bathythermographs (XBTs) from several programs [e.g., WOCE, GO-SHIP, Argo, and others] and platforms [e.g.,research vessels, gliders, moorings, ice-tethered profilers, and instrumented pinnipeds]. V4r4 covers the period 1992-01-01T12:00:00 to 2018-01-01T00:00:00.
ECCO Sea-Ice and Snow Concentration and Thickness - Daily Mean llc90 Grid (Version 4 Release 4)
This dataset provides daily-averaged sea-ice and snow concentration, thickness, and pressure loading on the native Lat-Lon-Cap 90 (LLC90) model grid from the ECCO Version 4 Release 4 (V4r4) ocean and sea-ice state estimate. Estimating the Circulation and Climate of the Ocean (ECCO) ocean and sea-ice state estimates are dynamically and kinematically-consistent reconstructions of the three-dimensional time-evolving ocean, sea-ice, and surface atmospheric states. ECCO V4r4 is a free-running solution of the 1-degree global configuration of the MIT general circulation model (MITgcm) that has been fit to observations in a least-squares sense. Observational data constraints used in V4r4 include sea surface height (SSH) from satellite altimeters [ERS-1/2, TOPEX/Poseidon, GFO, ENVISAT, Jason-1,2,3, CryoSat-2, and SARAL/AltiKa]; sea surface temperature (SST) from satellite radiometers [AVHRR], sea surface salinity (SSS) from the Aquarius satellite radiometer/scatterometer, ocean bottom pressure (OBP) from the GRACE satellite gravimeter; sea ice concentration from satellite radiometers [SSM/I and SSMIS], and in-situ ocean temperature and salinity measured with conductivity-temperature-depth (CTD) sensors and expendable bathythermographs (XBTs) from several programs [e.g., WOCE, GO-SHIP, Argo, and others] and platforms [e.g., research vessels, gliders, moorings, ice-tethered profilers, and instrumented pinnipeds]. V4r4 covers the period 1992-01-01T12:00:00 to 2018-01-01T00:00:00.
ECCO Sea-Ice and Snow Concentration and Thickness - Monthly Mean llc90 Grid (Version 4 Release 4)
This dataset provides monthly-averaged sea-ice and snow concentration, thickness, and pressure loading on the native Lat-Lon-Cap 90 (LLC90) model grid from the ECCO Version 4 Release 4 (V4r4) ocean and sea-ice state estimate. Estimating the Circulation and Climate of the Ocean (ECCO) ocean and sea-ice state estimates are dynamically and kinematically-consistent reconstructions of the three-dimensional time-evolving ocean, sea-ice, and surface atmospheric states. ECCO V4r4 is a free-running solution of the 1-degree global configuration of the MIT general circulation model (MITgcm) that has been fit to observations in a least-squares sense. Observational data constraints used in V4r4 include sea surface height (SSH) from satellite altimeters [ERS-1/2, TOPEX/Poseidon, GFO, ENVISAT, Jason-1,2,3, CryoSat-2, and SARAL/AltiKa]; sea surface temperature (SST) from satellite radiometers [AVHRR], sea surface salinity (SSS) from the Aquarius satellite radiometer/scatterometer, ocean bottom pressure (OBP) from the GRACE satellite gravimeter; sea ice concentration from satellite radiometers [SSM/I and SSMIS], and in-situ ocean temperature and salinity measured with conductivity-temperature-depth (CTD) sensors and expendable bathythermographs (XBTs) from several programs [e.g., WOCE, GO-SHIP, Argo, and others] and platforms [e.g., research vessels, gliders, moorings, ice-tethered profilers, and instrumented pinnipeds]. V4r4 covers the period 1992-01-01T12:00:00 to 2018-01-01T00:00:00.
ECCO Sea-Ice and Snow Concentration and Thickness - Snapshot llc90 Grid (Version 4 Release 4)
This dataset provides instantaneous sea-ice and snow concentration, thickness, and pressure loading on the native Lat-Lon-Cap 90 (LLC90) model grid from the ECCO Version 4 Release 4 (V4r4) ocean and sea-ice state estimate. Estimating the Circulation and Climate of the Ocean (ECCO) ocean and sea-ice state estimates are dynamically and kinematically-consistent reconstructions of the three-dimensional time-evolving ocean, sea-ice, and surface atmospheric states. ECCO V4r4 is a free-running solution of the 1-degree global configuration of the MIT general circulation model (MITgcm) that has been fit to observations in a least-squares sense. Observational data constraints used in V4r4 include sea surface height (SSH) from satellite altimeters [ERS-1/2, TOPEX/Poseidon, GFO, ENVISAT, Jason-1,2,3, CryoSat-2, and SARAL/AltiKa]; sea surface temperature (SST) from satellite radiometers [AVHRR], sea surface salinity (SSS) from the Aquarius satellite radiometer/scatterometer, ocean bottom pressure (OBP) from the GRACE satellite gravimeter; sea ice concentration from satellite radiometers [SSM/I and SSMIS], and in-situ ocean temperature and salinity measured with conductivity-temperature-depth (CTD) sensors and expendable bathythermographs (XBTs) from several programs [e.g., WOCE, GO-SHIP, Argo, and others] and platforms [e.g., research vessels, gliders, moorings, ice-tethered profilers, and instrumented pinnipeds]. V4r4 covers the period 1992-01-01T12:00:00 to 2018-01-01T00:00:00.
ECCO Sea-Ice and Snow Concentration and Thickness - Monthly Mean 0.5 Degree (Version 4 Release 4)
This dataset contains monthly-averaged sea-ice and snow concentration and thickness interpolated to a regular 0.5-degree grid from the ECCO Version 4 revision 4 (V4r4) ocean and sea-ice state estimate. Estimating the Circulation and Climate of the Ocean (ECCO) ocean and sea-ice state estimates are dynamically and kinematically-consistent reconstructions of the three-dimensional, time-evolving ocean, sea-ice, and surface atmospheric states. ECCO V4r4 is a free-running solution of the 1-degree global configuration of the MIT general circulation model (MITgcm) that has been fit to observations in a least-squares sense. Observational data constraints used in V4r4 include sea surface height (SSH) from satellite altimeters [ERS-1/2, TOPEX/Poseidon, GFO, ENVISAT, Jason-1,2,3, CryoSat-2, and SARAL/AltiKa]; sea surface temperature (SST) from satellite radiometers [AVHRR], sea surface salinity (SSS) from the Aquarius satellite radiometer/scatterometer, ocean bottom pressure (OBP) from the GRACE satellite gravimeter; sea ice concentration from satellite radiometers [SSM/I and SSMIS], and in-situ ocean temperature and salinity measured with conductivity-temperature-depth (CTD) sensors and expendable bathythermographs (XBTs) from several programs [e.g., WOCE, GO-SHIP, Argo, and others] and platforms [e.g.,research vessels, gliders, moorings, ice-tethered profilers, and instrumented pinnipeds]. V4r4 covers the period 1992-01-01T12:00:00 to 2018-01-01T00:00:00.
Updated sea ice thickness
Open the record for dataset details and reuse information.
Updated sea ice thickness from CryoSat-2 (2013-2018)
Open the record for dataset details and reuse information.
Arctic and Antarctic sea ice thickness climate data record from ERS-1, ERS-2, Envisat and CryoSat-2
Open the record for dataset details and reuse information.
Glacier thickness and ice volume of the inner tropical Andes
<p>Glacier thickness and ice volume of the inner tropical Andes <br> ------------------------------------------------------------</p> <p>Data folder</p> <p>This folder contains all of the velocity, thickness and basin-divided water volume described in our Scientific Data data decriptor, along with the code we used to generate the dataset.</p> <p>File structure:<br> ./Ice_velocities_individual_maps -> Contains individual ice velocity maps for each glacier in our study area (glacier velocity in metres per year)</p> <p><br> ./Ice_thicknesses_individual_maps -> Contains individual ice thickness maps for each glacier in our study area (ice thickness in m)</p> <p><br> ./Ice_thickness_stdev_individual_maps -> Contains ice thickness standard deviation maps for each glacier in our study area (standard deviation in metres)</p> <p><br> ./Basin_divided_water_eq_volumes -> Contains a map of ice equivalent water volume for each glacier basin. Three maps are provided for each glacier, for buffer distances of 1km, 5km and 20 km. Values represent cubic metres of water equivalent ice volume in a given catchment area.</p> <p><br> ./Code -> The code used to generate our results. See a separate README in that folder. Our study also used the GIV toolbox (10.5281/zenodo.4904544). All code is commented for easy re-use.</p> <p><br> Please contact Max Van Wyk de Vries (vanwy048@umn.edu) with any queries.</p>
Greenland 5 km DEM, Ice Thickness, and Bedrock Elevation Grids, Version 1
A Digital Elevation Model (DEM), ice thickness grid, and bedrock elevation grid of Greenland, acquired as part of the PARCA program. DEM data are a combination of ERS-1 and Geosat satellite radar altimetry data, Airborne Topographic Mapper (ATM) data, and photogrammetric digital height data. Ice thickness data are based on approximately 700,000 data points collected in the 1990s from a University of Kansas airborne Ice Penetrating Radar (IPR). Nearly 30,000 data points were collected in the 1970s from a Technical University of Denmark (TUD) airborne echo sounder.The ice thickness grid was subtracted from the DEM to produce a grid of bedrock elevation values. Data set applications include studies of gravitational driving stress and ice volume (mass balance) of the Greenland Ice Sheet.
Arctic Sea Ice Freeboard and Thickness, Version 1
This data set provides measurements of sea ice freeboard and sea ice thickness for the Arctic region. The data were derived from measurements made by from the Ice, Cloud, and land Elevation Satellite (ICESat) Geoscience Laser Altimeter System (GLAS) instrument, the Special Sensor Microwave/Imager (SSM/I), and climatologies of snow and drift of ice.
Simulated Sea Ice (weighted by the Sea ice concentration) and Snow Thickness along the MOSAiC drift trajectory, from AWI-CM-1 and AWI-CM-3 nudged simulations.
<p>Sea ice thickness (weighted by the Sea ice concentration<i>)</i> and snow (on sea ice) thickness from nudged simulations performed using the coupled climate models AWI-CM-1 (zonal wavenumber truncated at 20) and AWI-CM-3 (T20 truncation; Pithan et al., 2023) with a 1h relaxation time. The model data is collocated to the drift trajectory of the Multidisciplinary Drifting Observatory for the Study of the Arctic Climate (MOSAIC) across the Arctic Ocean, from 01 September 2019 until 31 August 2020. The collocation is done daily, by finding all model grid cells within the area covered by the distributed network of snow and sea ice measuring instruments deployed and maintained during MOSAIC. The sea ice and snow thickness is then spatially averaged for each day. </p><p>Data is provided in three .nc files for each model and variable (wm_ice for sea ice thickness, m_snow for snow thickness) representing ensemble members 1 to 3.</p>
Radar Attenuation in Enceladus' Ice Shell: Obstacles and Opportunities for Constraining Shell Thickness, Chemistry, and Thermal Structure
<p>Figures data for submission of paper ``Radar Attenuation in Enceladus' Ice Shell: Obstacles and Opportunities for Constraining Shell Thickness, Chemistry, and Thermal Structure'' by Ondrej Soucek, Marie Behounkova, Dustin M. Schroeder, Natalie S. Wolfenbarger, Klara Kalousova, Gregor Steinbruegge and Krista M. Soderlund.</p>
On-Ice Arctic Sea Ice Thickness Measurements by Auger, Core, and Electromagnetic Induction, from the Late 1800s Onward, Version 2
This data set consists of on-ice sea ice thickness measurements derived from drill holes, gauges, thermistor strings, and surface electromagnetic induction. From journal articles, reports, on-line databases, and direct contact with sea ice investigators, measurements have been assembled from many types of expeditions with the earliest data extending back to 1879 and the most recent data going to 2016. The on-ice thickness archive currently holds data from 50 expeditions.
CryoSat-2 Sea Ice Freeboard, Thickness, and Snow Depth Quick Look, Version 1
This data set contains sea ice thickness and other derived geophysical parameters measured over the Arctic sea ice cover. The data are primarily based on ESA's CryoSat-2 Level-1B SAR/SarIn Baseline B data products for March 2014 and March 2015. Ancillary data include snow depth, snow density, sea ice concentration, sea ice freeboard, and sea ice roughness. This quick look product is experimental and designed to aid in seasonal sea ice forecasting and other time-sensitive projects. The data were collected as part of Operation IceBridge funded campaigns.Note: This data set is the Quick Look counterpart to the <a href="https://nsidc.org/data/RDEFT4">CryoSat-2 Level-4 Sea Ice Elevation, Freeboard, and Thickness</a> data set.
Russian River Ice Thickness and Duration, 1917 - 1992, Version 1
This data set consists of river ice thickness measurements, and beginning and ending dates for river freeze-up events from fifty stations in northern Russia. The data set includes values from 1917 through 1992, however the record length varies for each station. The longest station record covers the period 1917 through 1988 (the station table shows the beginning and end years for measurements at each station). Data were obtained through the U.S.-Russia Working Group VIII of the U.S.-Russia Bilateral Agreement on the Protection of Environmental and Natural Resources.
Unified Sea Ice Thickness Climate Data Record, 1947 Onward, Version 1
The Unified Sea Ice Thickness Climate Data Record, 1947 Onward is the result of a concerted effort to collect as many observations as possible of Arctic and Antarctic sea ice draft, freeboard, and thickness and to format them consistently with clear documentation, allowing the scientific community to better utilize what is now a considerable body of observations.
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.