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774 results for “glacier”

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nasa28/100

Alaska Tidewater Glacier Terminus Positions, Version 1

This data set contains Alaska tidewater glacier terminus positions digitized from USGS topographic maps and Landsat images.

restrictednotspecifiedApr 2025View details →
nasa28/100

GLIMS Glacier Database, Version 1

Global Land Ice Measurements from Space (GLIMS) is an international initiative with the goal of repeatedly surveying the world's estimated 200,000 glaciers. GLIMS uses data collected by the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) instrument aboard the Terra satellite and the LANDSAT series of satellites, along with historical observations. The GLIMS initiative has created a unique glacier inventory, storing information about the extent and rates of change of all the world's mountain glaciers and ice caps. The GLIMS Glacier Database was built up from data contributions from many glaciological institutions, which are managed by Regional Coordinators, who coordinate the production of glacier mapping results for their particular region. The GLIMS Glacier Database provides students, educators, scientists, and the public with reliable glacier data from these analyses. New glacier data are continually being added to the database.The GLIMS Glacier Viewer was developed to provide the public with easy access to the GLIMS Glacier Database. This Web application allows users to view and query several thematic layers, including glacier outlines, Regional Coordinator institution locations, the World Glacier Inventory, and more. GLIMS data can be downloaded into a number of GIS-compatible formats, including ESRI Shapefiles, MapInfo tables, Geographic Mark-up Language (GML), and Keyhole Mark-up Language (KML) suitable for viewing in Google Earth.

restrictednotspecifiedApr 2025View details →
zenodo24/100

Supporting videos of (ice cliffs of) Lirung glacier

<p>Supplementary material for:&nbsp;<strong><em>Using 3D turbulence-resolving simulations to understand the impact of surface properties on the energy balance of a debris-covered glacier,&nbsp;</em></strong>PNJ Bonekamp, CC van Heerwaarden, JF Steiner&nbsp;and WW Immerzeel, submitted to The Cryosphere.</p> <p>List of movies:&nbsp;<br> Icecliff_movie_qt.gif: specific moisture at ice cliff<br> Icecliff_movie_th.gif : potential temperature at ice cliff<br> Icecliff_movie_UV.gif: wind speed at ice cliff<br> Movie_conductiveflux.gif: the conductive heat flux at the surface<br> vertical_cross_movie_q.gif:&nbsp;specific moisture along the xz cross section<br> vertical_cross_movie_thl.gif: potential temperature&nbsp;along the xz cross section<br> vertical_cross_movie_UV.gif: wind speed&nbsp;along the xz cross section</p>

opencc-by-4.0Aug 2019View details →
zenodo24/100

Measurements from the debris-covered Imja-Lhotse Shar Glacier (2013-2014)

<p>These data are from the debris-covered portion of Imja-Lhotse Shar Glacier (27.901N, 86.938E, ~5050 m a.s.l.)&nbsp;located in the Nepal Himalaya that were&nbsp;collected during three field expeditions&nbsp;between September 2013 and November&nbsp;2014.&nbsp; The data includes debris thickness measurements derived primarily by manual excavation,&nbsp;debris temperature measurements from thermistors located at the surface or within the debris, ablation stakes, and high-resolution digital elevation models used to estimate the surface roughness. Below is a brief description of the various datasets:</p> <p>- 15.03743_rounce2014-hd.csv: debris thickness measurements (m) from Rounce and McKinney (2014) and Rounce et al. (2015).</p> <p>- 15.03743_rounce2014-ts.csv: debris temperature measurements (K) where the depth is reported in cm from Rounce and McKinney (2014).</p> <p>- 15.03743_rounce2015-melt.csv: ablation stake measurements from the period May 18 - Nov 9 2014&nbsp;detailed in&nbsp;Rounce et al. (2015).</p> <p>- 15.03743_rounce2015-ts.csv: debris temperature measurements (K) where the depth is reported in cm from Rounce et al.&nbsp;(2015).</p> <p>- Site_XX_DEM_1cm.tif: digital elevation model used to estimate surface roughness from Rounce et al. (2015).</p> <p>&nbsp;</p> <p>----- Citing datasets -----</p> <p>If using the debris thickness measurements (15.03743_rounce2014-hd.csv) or temperature data from September 2013 (15.03743_rounce2014-ts.csv), please cite:</p> <p>Rounce, D.R. and McKinney, D.C. (2014). Debris thickness of glaciers in the Everest area (Nepal Himalaya) derived from satellite imagery using a nonlinear energy balance model,&nbsp;<em>Cryosphere</em>, 8:1317-1329, doi:10.5194/tc-8-1317-2014.</p> <p>For all other data please cite:</p> <p>Rounce, D.R., Quincey, D.J., and McKinney, D.C. (2015). Debris-covered glacier energy balance model for Imja-Lhotse Shar Glacier in the Everest region of Nepal,&nbsp;<em>Cryosphere</em>, 9:2295-2310, doi:10.5194/tc-9-2295-2015.</p>

opencc-by-4.0Jul 2014View details →
zenodo24/100

Supraglacial debris temperature measurements from Ngozumpa Glacier, Nepal (2014–2016)

<p>Supraglacial debris temperature measurements from a site 1.6&nbsp;km from the terminus of Ngozumpa Glacier, Nepal, collected between 06 December 2014&nbsp;and 03&nbsp;April 2016. Debris temperatures were measured every six hours at 11 thermistors within the debris layer at depths of 0.01 m, 0.2 m, 0.4 m, 0.6 m, 0.8 m, 1.0 m, 1.2 m, 1.4 m, 1.6 m, 1.8 m and&nbsp;2.0 m from the debris surface. The thickness of the debris layer at this site was 2.0 m, and the lowermost thermistor was installed at the debris-ice interface.</p> <p>Measurements were made using a Geoprecision thermistor array with a stated accuracy of &plusmn;0.25&deg;C.</p> <div class="wayback1996-RTmodal"> <div>&nbsp;</div> <div>&nbsp;</div> &times; <div>&nbsp;</div> <div>&nbsp;</div> <div>&nbsp;</div> </div>

opencc-by-4.0Jul 2020View details →
dryad24/100

High resolution lidar data of the Khumbu glacier

<p>This Dryad repository contains an airborne lidar dataset of the Khumbu Glacier from the base of the Lhotse Face in the Western Cwm to the trekking village of Dugla at the toe of the glacier. The data were collected by helicopter borne lidar on 27 May 2019 to 28 May 2019. The data were collected as part of the National Geographic and Rolex Perpetual Planet Everest Expedition.</p> <p>This research was conducted in partnership with National Geographic Society, Rolex, Tribhuvan University, and the Nepal Survey Department, with approval from all relevant agencies of the Government of Nepal.</p>

opencc-zeroOct 2020View details →
dryad24/100

Data from: Simple parameterization of aerodynamic roughness lengths and the turbulent heat fluxes at the top of midlatitude August‐one glacier, Qilian Mountains, China

The fluxes of sensible heat (H) and latent heat (LE), which are generally the important parts of the energy and mass balances over glacier surfaces, are widely quantified by the bulk method. However, due to the difficulty of determining the aerodynamic roughness length z0m in this method, H and LE values may still have large uncertainties with significant inaccuracy. To acquire reliable varying and intrinsic z0m values, new simpler parameterizations for z0m values at different ranges of the friction velocity u*b were fitted in this study. The method was implemented using the related meteorological data and glacial sublimation/condensation measured at the top of the August‐one glacier (4817 m a.s.l.) in the Qilian Mountains from 1 July 2016 to 15 August 2017. The parameterization shows that z0m increased sharply when u*b exceeded 0.43 m/s (the approximate threshold value) and that the effect of snowdrift was slight for the hourly z0m values in the range 0.15 ≤ u*b ≤ 0.43 m/s, which could thus be used to calculate the daily z0m. During the wet period (1 July to 24 September 2016 and 5 May to 15 August 2017), the turbulent fluxes calculated by the bulk method showed that net radiation Rnet was the primary source of surface energy (60.7 w/m2), whereas during the dry period (25 September 2016 to 4 May 2017), the main heat sink was the positive H (28.5 w/m2) rather than the negative Rnet (–10.0 w/m2).

opencc-zeroDec 2017View details →
zenodo24/100

Intra-annual dynamics of temperate glacier in the ablation season in the southeastern Tibetan Plateau

<p>Here, the data used in paper &ldquo;Intra-annual dynamics of temperate glacier in the ablation season in the southeastern Tibetan Plateau&rdquo; were given.</p> <p>In this database, "GlacierHeightChange_2023_0611" is the Yanong Glacier height changes that generated from six Digital Surface Models, "GlacierVelocity_2023_0644" is the Yanong Glacier surface veloicties that generated from six Digital Orthophoto Maps. The six DSMs and DOMs were derived &nbsp;from six UAV surveys from June to November in 2023.</p>

openJun 2024View details →
zenodo24/100

The role of snowmelt, glacier melt and rainfall in streamflow dynamics on James Ross Island, Antarctic Peninsula

<p>Description: The file in this record represents a supplementary data for the journal paper&nbsp;<br>Ondřej Nedělčev, Michael Matějka, Kamil L&aacute;ska, Zbyněk Engel, Jan Kavan, and Michal Jenicek (2024):<br>The role of snowmelt, glacier melt and rainfall in streamflow dynamics on James Ross Island, Antarctic Peninsula, DOY: 10.5281/zenodo.11001370&nbsp;</p> <p>The file contains simulations of the HBV-light rainfall-runoff model for Triangular catchment on James Ross Island.<br>The model simulated different water balance components, such as runoff, snow water equivalent, galcier water equivalent,&nbsp;<br>evapotranspiration and groundwater storage for the study period 2010/11&ndash;2020/21.</p>

opencc-by-4.0Apr 2024View details →
zenodo24/100

Variation of glaciers at Zangser Kangri on the Qiangtang Plateau during 1971 - 2015

<p>Manually digitized glaciers on Zangser Kangri, Central Tibetan Plateau.</p> <p>The data source of 1971 is&nbsp;topographic maps.&nbsp;</p> <p>Other results came from Landsat images on 1977-03-03, 1993-08-30, 2007-07-24 (1998-05-24 and 2000-10-28 as ancillaries),2006-09-19, and 2015-09-12.</p>

opencc-by-4.0Sep 2020View details →
zenodo24/100

Data from: A boulder beach formed by waves from a calving glacier revisited: multidecadal -tsunami- controlled coastal changes in front of Eqip Sermia

<div>This study is a contribution to the National Science Centre project &lsquo;GLAVE&rsquo; (Award No. UMO-2020/38/E/ST10/00042)</div> <div>&nbsp;</div>

opencc-by-4.0Dec 2023View details →
zenodo24/100

Glacio-hydrological changes along the Andes throughout the 21st Century: Data by glacier and catchment

<p>Results of the simulation analyzed in the article "Glacio-hydrological changes along the Andes throughout the 21st Century" submitted to review in the journal Scientific Reports. You can find other data such as the catchment outlines and their identifier (id) in https://doi.org/10.5281/zenodo.7890462, related to the article &ldquo;Hydrological response of Andean catchments to recent glacier mass loss&rdquo; https://doi.org/10.5194/tc-18-2487-2024.</p>

opencc-by-4.0Jul 2024View details →
zenodo24/100

Figure 7 from: Li W-C, Liu D (2015) A new species of Metaeuchromius (Lepidoptera, Crambidae) from the Tibetan glacier area. ZooKeys 475: 113-118. https://doi.org/10.3897/zookeys.475.8766

Figure 7 - Natural environment of collecting localitiy of Metaeuchromius glacialis Li, sp. n.

opencc-by-4.0Jan 2015View details →
zenodo24/100

Glacier surface elevation estimates for a glacier in the Poiqu river basin, Central Himalaya.

<p>This zip folder contains tif files representing glacier surface elevation estimates under two different scenarios of thinning towards the year 2100, informed by past (2000-2015) thinning rates which have been extrapolated into the future.&nbsp;</p> <p>These results are presented in the paper by Allen et al. 2022,&nbsp;<em>Glacial lake outburst flood hazard under current and future conditions: worst-case scenarios in a transboundary Himalayan basin,&nbsp;</em>Natural Hazards and Earth System Science,&nbsp;https://doi.org/10.5194/nhess-22-1-2022.</p>

opencc-by-4.0Dec 2021View details →
zenodo24/100

Nonlinear sensitivity of glacier-mass balance to climate attested by temperature-index models; synthetic data

<p>Synthetic data and results of the PDD model used in the paper&nbsp;<a href="https://doi.org/10.5194/tc-2022-210">https://doi.org/10.5194/tc-2022-210</a></p>

opencc-by-4.0Feb 2023View details →
zenodo24/100

Grounding line datasets of Totten and Moscow University Glaciers 2017-2021

<p>The grounding line (GL) datasets in 2017-2021 of Totten and Moscow University Glaciers located in Wilkes Land were mapped from different remote sensing methods, including ICESat and ICESat-2 satellite altimetry, and Sentinel-1a/b Differential Interferometry Synthetic Aperture Radar (DInSAR).</p>

opencc-by-4.0Dec 2022View details →
zenodo24/100

Data for "Cast shadows reveal changes in glacier surface elevation"

<p>This dataset contains the files that were calculated and used for the analysis described in the manuscript &quot;Cast shadows reveal changes in glacier surface elevation&quot; by Monika Pfau, Georg Veh, and Wolfgang Schwanghart submitted to journal The Cryosphere.</p>

openOct 2022View details →
zenodo24/100

Aletsch Glacier

*This Model was made with Blender and with the addon GIS you can download on Github* The Great Aletsch Glacier has shaped the landscape of the Aletsch Arena over thousands of years. During the last ice age (around 18,000 years ago), ice still covered the mountain ridges between the Bettmerhorn and the Riederhorn. The Aletsch Glacier is a vision of primaeval beauty. This huge river of ice that stretches over 20 km from its formation in the Jungfrau region (at 4000 m) down to the Massa Gorge, around 2500 m below, fascinates and inspires every visitor. **20 km length** This makes the Great Aletsch Glacier the longest ice stream in the Alps. **10 billion tonnes** is the weight of the Great Aletsch Glacier. **800 metres** is the thickest ice on the glacier. This is located at Konkordiaplatz. **79 square kilometres** is the surface of the Great Aletsch Glacier [https://www.aletscharena.ch/en/world-natural-heritage-site/great-aletsch-glacier](http://) Source: Objaverse 1.0 / Sketchfab

opencc-byAug 2022View details →
ClinicalTrials.gov24/100

Gedatolisib, Hydroxychloroquine or the Combination for Prevention of Recurrent Breast Cancer ("GLACIER")

ClinicalTrials.gov study NCT03400254. IPD Sharing: Not stated. Countries: 1. Publications: 0.

restrictedIPD-UNDECIDEDFeb 2026View details →
ClinicalTrials.gov24/100

A Study to Evaluate the Safety, Tolerability, and Activity of Intravenous MLDL1278A in Patients on Standard-of-Care Therapy for Stable Atherosclerotic Cardiovascular Disease (GLACIER)

ClinicalTrials.gov study NCT01258907. IPD Sharing: Not stated. Countries: 2. Publications: 0.

restrictedIPD-UNDECIDEDFeb 2026View details →

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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.

allen-brain-atlas
neuroscienceopenDocumentation, web resources, and API references are available online.
Last verified 2026-04-30Open record

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.

abode-home-cage
behavioral-neuroscienceopenThe DataShare record exposes download links for annotations, documentation, license text, and the zipped per-snippet data directory.
Last verified 2026-04-30Open record

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.

dandi-nwb
electrophysiologyopenPublished Dandiset metadata and archive endpoints are available through the production DANDI API.
Last verified 2026-04-30Open record

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.

ibl
behavioral-neuroscienceopenPublic sessions can be searched and loaded from the IBL public data server through ONE.
Last verified 2026-04-29Open record

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.

openneuro
neuroscienceopenPublished datasets are available on demand over the internet.
Last verified 2026-04-29Open record