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.
102
datasets available to search
ShareScore release 0.9.0
Dataset results
102 results for “water ice”
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.
High Frequency Under-Ice Water Temperature Buoy Data - Crystal Bog, Trout Bog, and Lake Mendota, Wisconsin, USA 2016-2020
Water temperature measurements from three Wisonsin lakes. Two bog lakes are in Northern Wisconsin, Lake Mendota is in Southern Wisconsin. Thermistor chains span the full depth of each lake. See freeze dates for periods of open or frozen lake (NTL 32, DOI 10.6073/pasta/1c1acdb5489a0355f6f8bb5c496fdf8b and NTL 33, DOI 10.6073/pasta/22a5b5f8bce193353e559918b0024f9d)
Lake Mendota water temperature secchi depth snow depth ice thickness and meterological conditions 1894 - 2007
Data for water temperature at different depth and different frequencies assembled from various sources by Dale Roberson. A table with additional parameters collected at the same time is also provided for dates when available. These parameters are weather observations, secchi depth, snow and ice depths.
Seasonal sea ice indices including the timing of ice-edge advance and ice-edge retreat (in year day), the ice season duration (in days) and number of actual ice days (versus open water days) within the ice season, extracted for various PAL LTER sub-regions West of the Antarctic Peninsula and derived from passive microwave satellite data for 1979/80 to 2023/24 ice seasons.
Seasonal sea ice indices including the timing of ice-edge advance and ice-edge retreat (in year day), the ice season duration (in days) and number of actual ice days (versus open water days) within the ice season, extracted for various PAL LTER sub-regions West of the Antarctic Peninsula and derived from passive microwave satellite data for 1979/80 to 2023/24 ice seasons. The ice season duration is defined as the time elapsed between day of ice-edge advance and day of ice-edge retreat within a given sea ice year, which begins mid-February (mean minimum of summer sea ice extent for the Southern Ocean) and ends the following mid-February. See Stammerjohn et al (2008, JGR) for further details.
Snow depth, snow water equivalent, ice thickness in Fuglebekken and Revdalen catchments collected in the SnowPilot campaign in Spring 2022
<p>File SnowPilot_snowdepth_along_the_GPR_profile_2022 contains snow depth measurements taken along the GPR profile performed during the SIOS SnowPilot campaign in Spring 2022. File SnowPilot_snowdepth_swe_2022 contains depth, snow water equivalent and basal ice thickness. Snowpits were dug on GPR profile crossings in the Fuglebekken and Revdalen catchments in the Hornsund fiord, Spitsbergen catchment. Snow density was measured with an IG PAS snow tube, and snow depth and basal ice (ice forming on the ground surface) thickness were measured with an avalanche probe. Point locations measured. with handheld GPR reciever.</p>
GFN2-xTB structures of iCOM adsorbed on a cluster model of water molecules derived from a periodic model of crystalline ice
<p>This dataset contains the atomic coordinates in the <a href="http://www.moldraw.unito.it/">.</a>xyz format of the GFN2-xTB optimized structures of 20 iCOMs adsorbed at the surface of a cluster of 84 water molecules mimicking the periodic model of crystalline water icy grain as described by Ferrero, S.; Zamirri, L., Ceccarelli, C.; Witzel, A.; Rimola, A.; Ugliengo, P. ApJ, (2020) 904:11. For all considered structures we also provided a specific file in the Gaussian format with the computed harmonic frequencies. Each file can be easily converted in input for the variety of quantum mechanical programs, like VASP, QE, Gaussian 16 etc.</p> <p> </p> <p> </p>
Water stable isotope, temperature and electrical conductivity dataset (snow, ice, rain, surface water, groundwater) from a high alpine catchment (2019-2021).
<p>Data collected in the Otemma forefield in Switzerland (45°56’03”N,7°24’42”) from July 2019 to October 2021.<br> Data were collected by the research teams of Bettina Schaefli<sup>2</sup> and Stuart N. Lane<sup>1</sup>.</p> <p><sup>1</sup> Institute of Earth Surface Dynamics (IDYST), University of Lausanne, 1015 Lausanne, Switzerland</p> <p><sup>2</sup> Institute of Geography (GIUB), University of Bern, 3012 Bern, Switzerland</p> <p>For further information, please contact:</p> <ul> <li>tom.muller.1@unil.ch</li> </ul> <p><strong>Description of the dataset</strong></p> <p>This dataset contains water stable isotope (δ<sup>2</sup>H, δ<sup>17</sup>O, δ<sup>18</sup>O), water temperature and water electrical conductivity (EC) measurements collected from the Otemma glacier catchment.</p> <p>All water isotope samples were collected directly from the source and stored in 12 mL amber glass vials with an air-tight caps. River samples were first collected with an automatic ISCO 6712 portable water sampler with 1L open plastic bottles and transferred in 12 mL vials every one to two weeks. All isotope analysis were performed using a Wavelength-Scanned Cavity Ring Down Spectrometer (Picarro 2140-I, Santa Clara, California, USA) and expressed relative to the international Vienna Standard Mean Ocean Water (VSMOW) standards.</p> <p>All EC and water temperature measurements were performed with a WTW Multi 3510 IDS logger with a IDS TetraCon® 925 probe.</p> <p>The dataset contains measurements performed at various locations within the catchment. A total of approximately 1500 measurements are provided. In the dataset each point correspond to a measurement station (column "<strong>Station</strong>") which we classified in specific class of water (column "<strong>Type</strong>") as follows :</p> <ul> <li><strong>Stream </strong>: samples collected at three locations, from the glacier snout, after a small outwash plain and 2km downstream.</li> <li><strong>Tributary </strong>: 5 hillslopes tributaries originating from small seasonal overland flow or small springs at the base of the morainic hillslope. Those tributaries were monitored weekly. In addition, a few other seasonal lateral streams were sampled in various locations (Type: Other tributaries).</li> <li><strong>Bedrock </strong>: A few exfiltrations directly leaking out of the bedrock outcrop were sampled.</li> <li><strong>Ice </strong>: Ice was sampled either as surface ice (small cores 5 cm deep), as deeper cores (5 to 8m deep) or as meltwater from supraglacial gullies. All solid ice samples were melted at ambiant air temperature in air-tight plastic bags before being transferred into 12 mL vials.</li> <li><strong>Snow </strong>: The snowpack was sampled either at the surface (0 to 5cm) or at about 20 cm depth. Where possible, meltwater leaking from the snowpack was sampled. At 3 locations in 2021, we dug snowpits from which we sampled snow at different layers with depth. All solid snow samples were melted at ambiant air temperature in air-tight plastic bags before being transferred into 12 mL vials</li> <li><strong>Rain </strong>: Rainwater was mostly sampled at our camp site at 2450 m. asl. Rainwater samples represent single rain events which are identified by dry periods of at least one day long.</li> <li><strong>Groundwater </strong>: shallow (2 to 3 meters) fully-screened groundwater wells were installed in the outwash plain and water sampled monthly in the snow-free season.</li> </ul> <p>- GPS coordinates are provided with each point (Swiss coordinate system CH1903+ / LV95<strong> (EPSG: 2056)).</strong></p> <p>- Dates are provided in local timezone (GMT+1 with daylight saving time) and in UTC date format.</p> <p>- Analyitcal error from the Picarro spectrometer is reported as 1 standard deviation.</p> <p>More information can be accessed in the corresponding publication by Müller et al. (to be published in 2023).</p> <p><strong>Data files</strong></p> <ul> <li><em>Otemma_isotope_EC_T_2019_2021.csv</em> : file containing all data with GPS coordinates</li> <li> <p><em>isotope_locations_Otemma.jpg</em> : an overview of the locations of each measurement point</p> </li> <li> <p><em>Otemma_Isotopes_2019-2020.html </em>: interactive plots of all datasets (δ<sup>2</sup>H, EC, temperature), classified by Type.</p> </li> </ul>
Characterization of Water Quality, Nutrients, and Algae Under Ice in the St. Louis River Estuary 2013 - 2018
This data package includes physical, chemical, and biological measurements characterizing under-ice and early open-water conditions in the St. Louis River Estuary—a freshwater estuary located at the western tip of Lake Superior. Data were collected annually during February and March from 2013 to 2018, with additional sampling in May and June 2018. Sampling sites were distributed across the estuary to assess spatial variability and investigate potential hypoxia. Field data include in situ water quality measurements (e.g., temperature, dissolved oxygen, conductivity, pH), light penetration, and snow and ice thickness. Laboratory analyses were conducted on collected samples to quantify nutrients, suspended sediment, and chlorophyll-a concentrations. Phytoplankton samples were collected using plankton nets and preserved in Lugol’s solution for taxonomic identification. Sampling and analysis followed EPA and USGS Standard Methods where applicable to ensure compatibility with other environmental datasets. This dataset fills a critical gap in winter limnology by providing rare observations of under-ice estuarine conditions. It supports ecological research, environmental monitoring, and comparative studies of seasonal dynamics, nutrient cycling, and primary producer communities in Great Lakes coastal wetlands and other northern freshwater systems. The dataset is complete and not ongoing, although data acquired through the System-wide Monitoring Program at the Lake Superior National Estuarine Research Reserve is complementary and ongoing.
University of Kansas Field Station: Water level and ice cover at Frank B. Cross Reservoir (Kansas, USA) 1993 - 2016
This database is from regular monitoring of water level and surface ice cover at Frank B. Cross Reservoir, a small freshwater impoundment in northeastern Kansas (USA). Cross Reservoir, located at the University of Kansas Field Station near Lawrence (KS), has a 3-ha surface area and a maximum depth of 12 m. Measurements of water elevation and estimates of ice cover were made at semi-monthly intervals (i.e., roughly every two weeks). The first data were taken in December 1993, shortly after the reservoir was constructed and first filled to capacity. Water levels were measured relative to a permanent water control structure. Ice cover observations were visual estimates of the percent (%) surface of the reservoir covered with ice. Water level measurements and ice cover estimates are made at the same time. This database is updated periodically and maintenance is ongoing.
Greenhouse gas and water chemistry data from urban ponds in Madison, Wisconsin during the summer and under-ice period of 2021-2022
Stormwater ponds are common features in urbanized landscapes and can suffer from rapid oxygen depletion when thermally stratified or ice-covered. To investigate under-ice oxygen dynamics and drivers of bottom water oxygen saturation, we sampled 20 stormwater ponds in Madison, Wisconsin, USA during the summer of 2021 and winter 2022. The urban ponds ranged in age, shape, size, and depth. We repeatedly took YSI profiles of water temperature, oxygen, and specific conductance 7 times in the summer and 3 times in the winter. Water chemistry variables were collected in the surface waters, habitat surveys were conducted in the summer, and ice/snow thickness was recorded in the winter. We also measured the concentration of greenhouse gases in the surface waters as a consequence to oxygen depletion using the headspace equilibrium method.
Water column changes under ice during diferent winters in a mid-latitude Mediterranean high mountain lake - Dataset
<p>Dataset of the research article <em>Water column changes under ice during diferent winters in a mid-latitude Mediterranean high mountain lake.</em></p> <p>Granados, I., Toro, M., Giralt, S., Camacho, A., Montes, C., 2020. Water column changes under ice during different winters in a mid-latitude Mediterranean high mountain lake. Aquatic Sciences 82, 30. <a href="https://doi.org/10/ggmkhv">https://doi.org/10/ggmkhv</a></p> <p> </p>
ICESat-2 Water Depth Retrieval Comparisons for Four Supraglacial on Amery Ice Shelf, East Antarctica
<p>This archive contains the code used for analysis and producing figures for the following paper:</p> <p>Fricker, H.A., Arndt, P.S., Brunt, K.M., Datta, R.T., Fair, Z., Jasinski, M.F., Kingslake, J., Magruder, L.A., Moussavi, M., Pope, A. and Spergel, J.J., 2021. “ICESat-2 meltwater depth estimates: application to surface melt on Amery Ice Shelf, East Antarctica.” Geophysical Research Letters, 48(8), DOI: 10.1029/2020GL090550. URL: <a href="https://doi.org/10.1029/2020GL090550">https://doi.org/10.1029/2020GL090550</a><br><br>These materials are also on GitHub:<br><a href="github.com/fliphilipp/ameryMeltLakesICESat2">https://github.com/fliphilipp/ameryMeltLakesICESat2</a> </p> <p> </p> <p>The code for generating manually annotated baseline depth estimates from ICESat-2 ATL03 photon data is available here:<br><a href="https://github.com/fliphilipp/pondpicking">https://github.com/fliphilipp/pondpicking</a></p>
FESOM2.1 model data used in the paper "Atlantic Water warming increases melt below Northeast Greenland's last floating ice tongue"
<p><span>This data set includes the minimal data necessary to reproduce the findings of Wekerle et al., in revision. Output of model simulations with the global ocean sea ice model FESOM2.1 is provided. In particular, the data set includes:</span></p> <p><span>a) long term means of potential temperature, salinity, velocity and basal melt of the 79N Glacier averaged over 1970-2021 (</span>Wekerle2024_FESOM2_ltm_REF.nc<span>)</span></p> <p><span>b) annual means of maximum potential temperature and basal melt rate of the 79N Glacier from the reference experiment REF for the years 1970-2021 (</span>Wekerle2024_FESOM2_annual_avg_REF.nc<span>)</span></p> <p><span>c) annual means of maximum potential temperature and basal melt rate of the 79N Glacier from experiment CLIM for the years 2000-2021 (</span>Wekerle2024_FESOM2_annual_avg_CLIM.nc<span>)</span></p> <p><span>d) daily mean basal melt rates of experiments with varying subglacial discharge averaged over the years 2010-2014 (</span>Wekerle2024_FESOM2_daily_avg_EXP_subglacial_discharge.nc<span>)</span></p> <p><span>e) daily mean basal melt rates of experiments with varying drag coefficients for the year 2000 (</span>Wekerle2024_FESOM2_daily_EXP_basal_drag.nc<span>)</span></p> <p><span>Each netcdf file includes information on the model grid (longitude and latitude of nodes, depths of the vertical layers, elements, nodal areas).</span></p>
The Water-ice Feature in Near-infrared Disk-scattered Light around HD 142527: Micron-sized Icy Grains Lifted up to the Disk Surface?
<p>This is a reproduction package for the paper "The Water-ice Feature in Near-infrared Disk-scattered Light around HD 142527: Micron-sized Icy Grains Lifted up to the Disk Surface?" by Tazaki et al. (2021). In this repository, you will find the data files used to make figures in the paper. Source codes and scripts are included as well.</p>
Icing Wind Tunnel Measurements of Supercooled Large Droplets Using the 12 mm Total Water Content Cone of the Nevzorov Probe: Measurement Data
<p>This repository contains the measurement data that was used for the publication "Icing Wind Tunnel Measurements of Supercooled Large Droplets Using the 12 mm Total Water Content Cone of the Nevzorov Probe".</p>
Simulated water models with Apoferritin for use in cryo-EM image simulations with amorphous ice
<p>This dataset contains the atomic coordinates of several water models produced using the NAMD molecular dynamics software. The contents of each file is listed below.</p> <ul> <li><strong><em>water_81_coords.pdb</em></strong> - water only in a cubic box with side length 81A</li> <li><strong><em>water_243_coords.pdb</em></strong> - water only in a cubic box with side length 243A</li> <li><strong><em>water_486_coords.pdb</em></strong> - water only in a cubic box with side length 486A</li> <li><strong>water_567_coords.pdb</strong> - water only in a cubic box with side length 567A</li> <li><strong><em>water_645_coords.pdb</em></strong> - water only in a cubic box with side length 645A</li> <li><strong><em>water_735_coords.pdb</em></strong> - water only in a cubic box with side length 735A</li> <li><strong><em>apo_water_723_coords.pdb</em></strong> - water and apoferritin in a cubic box with side length 723A where apoferritin atoms are constrained</li> </ul>
Data and Software for "Gullies on Mars could have formed by melting of water ice during periods of high obliquity"
<p>Code, movies and climate model outputs for "Gullies on Mars could have formed by melting of water ice during periods of high obliquity" by Dickson et al. Science, 2023.</p>
Seasonality of in-lake and meteorological data from seven lakes, including daily measurements of water temperature, chlorophyll-a, dissolved oxygen, ice cover, air temperature, and solar radiation
This data product supports the manuscript "Seasons and seasonality in lakes: a synthesis amid global change" (Lewis et al. 2026; in review). Data were analyzed to understand how seasonality varies among diverse lakes and variables. Specifically, this data publication includes daily mean water temperature, chlorophyll-a, and dissolved oxygen at multiple depths, ice cover (binary), air temperature and solar radiation. Data availability and collection methods differ among lakes, as described in the Methods.
Methane ebullition and diffusion rates, turbulence, water temperature, and water depth data from Falling Creek Reservoir (Virginia, USA) in the ice-free period during 2016-2019
This dataset includes weekly and subweekly methane ebullition and diffusion rates collected from March through November in 2016, 2017, 2018, and 2019 in Falling Creek Reservoir (FCR), a drinking water reservoir owned and managed by the Western Virginia Water Authority and located in Vinton, Virginia, USA. In 2016, ebullition rates were measured at four near-shore sites along a longitudinal gradient in FCR that included four replicate locations within each site, for a total of 16 sites in the reservoir. In 2017, methane emission rates and five different potential environmental driver variables (water temperature, wind speed, pressure, turbulence, primary production) were measured at five longitudinal transects that included four replicate sites per transect, for a total of 20 sites in the reservoir. In 2018, ebullition was measured at the same five longitudinal transects but with two replicate sites per transect, for a total of 10 sites. In 2019, ebullition was only measured at the furthest upstream transect monitored in 2017-2018, with four replicate sites within that transect. The dataset consists of four tables: 1) weekly methane ebullition and diffusion rates and the water depths at each of the 24 unique monitoring sites; 2) 10-minute resolution sediment-water interface and surface water temperatures from 16 sites in 2017; 3) weekly sediment-water interface and surface turbulence at the four transects in 2017; and 4) geographical coordinates of each of the 24 sites in the reservoir.
Data release accompanying JGR publication "Electron-induced radiolysis of water ice and the buildup of oxygen" by Tinner et al.
Open the record for dataset details and reuse information.
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.