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774 results for “glacier”
GNSS data at the Astrolabe Glacier
<p>This dataset contains GNSS measurements collected at the Astrolabe Glacier (Terre Adélie, East Antarctica) from January 17, 2023, to February 2, 2023 and presented in:</p> <p>Le Bris et al. (2024), <span>Spatial and Temporal Variability in Tide-induced Icequake Activity at the Astrolabe Coastal Glacier, East Antarctica. <em>Submitted in JGR.</em><br></span></p> <p>Data from each GNSS station (7 stations in total) are saved in individual files. The processed data (*pos files) are organized by columns as follows: Time, North, East, Up, and Up Detrended. Additionally, raw GNSS data files used to generate the processed outputs are included. Details on data processing steps are provided in the supporting materials of the above reference.</p>
Terminus data for: Multi-decadal retreat of Greenland's marine-terminating glaciers
<p>Many marine-terminating glaciers draining the Greenland ice sheet have retreated over the past decade, yet the extent and magnitude of retreat relative to past variability is unknown. We measure changes in front positions of 210 marine-terminating glaciers using Landsat imagery spanning nearly four decades and compare decadal-scale rates of change with earlier observations. We find that 90% of the observed glaciers retreated between 2000 and 2010, approaching 100% in the northwest, with rapid retreat observed in all sectors of the ice sheet. The current retreat is accelerating and likely began between 1992 and 2000, coincident with the onset of warming, following glacier stability and minor advance during a mid-century cooling period. While it is clear an extensive retreat occurred in the early 20th century, a period of increasing air temperatures, a comparison of our results with historical observations provides evidence that the current retreat is more widespread. The onset of rapid retreat with warming relative to the slow and lagged advance with cooling suggests an asymmetry in the response of marine fronts to external forcing.</p> <p> </p>
Early 21st century accelerated glacier shrinkage and associated climatic drivers in Bhaga basin, north-western Himalaya
<p>This study investigates the glacier changes in the Bhaga basin, western Himalaya during the last five decades based on various satellite imagery: Corona KH4 (1971), Landsat 7 Enhanced Thematic Mapper Plus (ETM+; 2000), Linear Imaging Self-Scanning Sensor (LISS IV; 2013), Sentinel 2 (2016 and 2018). We compare glacier changes on spatial and temporal scales and their dependency on local topographic settings (elevation, slope, aspect, debris cover, presence of glacial lakes) and climatic fluctuations. Long-term (1900-present) reanalysis climatic datasets were evaluated to monitor the temperature and precipitation trend of the region. Glacier mapping from 2013 (LISS IV) images yielded 306 glaciers (>0.2 km²) with a total area of 360.3 ± 4.0 km², of which 55.7 ± 0.6 km² was covered by debris. Glaciers in the Bhaga basin lost -7.9 ± 1.5% (-0.17% yr¯¹) of ice during 1971-2018 with a significant heterogeneous rate within tributary watersheds. The number of analyzed glaciers increased by nine due to fragmentations. In recent decades (2000-18), the deglaciation rate has increased significantly (-0.25% yr¯¹) compared to previous decades (1971-2000; -0.12% yr¯¹). The retreat rate has been observed to be much lower than previously reported. Heterogeneous ice loss was mostly controlled by the size, altitudinal range, orientation, and debris cover. Analysis and inter-comparison of multiple gridded climatic data during the last century shows a drastic change in climatic trends around 2000 in western Himalaya. Asian Precipitation-Highly Resolved Observational Data Integration Towards Evaluation (APHRODITE) data reveals an increasing trend in temperature (0.019° C yr¯¹) and a significant decreasing trend in precipitation (-1.969 mm yr¯¹) after 1990. The observed glacier change in the Bhaga basin is in similarity to the observed climatic trend for the western Himalaya.</p>
Large-Scale Atmospheric Drivers of Snowfall over Thwaites Glacier, Antarctica
<p>Monthly RACMO2 snowfall rates (1979-2015, in mm w.e. per month), as described in Lenaerts et al., 2018 (https://www.cambridge.org/core/journals/annals-of-glaciology/article/climate-and-surface-mass-balance-of-coastal-west-antarctica-resolved-by-regional-climate-modelling/E3DD6D0DA914C6031F96A548AF53603A), and used in this paper. </p>
Glacier inventory for the Greater Caucasus (2000-2020)
<p>Data from the new glacier inventory at two time periods (2000, 2020) covering the entire Greater Caucasus (Georgia, Russia, and Azerbaijan) is presented here. This work was conducted based on satellite imagery (Landsat, Sentinel, SPOT) and 30 m resolution Advanced Spaceborne Thermal Emission and Reflection Radiometer Global Digital Elevation Model (ASTER GDEM).</p> <p>How to cite. Tielidze, L. G., Nosenko, G. A., Khromova, T. E., and Paul, F.: Strong acceleration of glacier area loss in the Greater Caucasus over the past two decades, The Cryosphere Discuss. [preprint], https://doi.org/10.5194/tc-2021-312, in review, 2021.</p>
High spatial resolution thickness changes of Pyrenean glaciers from 2011 to 2020
<p>Pyrenean glaciers are the largest in southern Europe. Because their very survival is threatened by climate change in the coming decades, it is urgently necessary to monitor their evolution. This dataset presents high spatial resolution observation of Pyrenean glaciers during the period 2011–2020. In 2011, the glacier surface was retrieved with an airborne lidar and in 2020 data were obtained with three different UAVs (fixed-wing or quad copters). Comparing these observations, glacier surface changes were computed for 17 out of the 24 remaining glaciers. Using high-resolution optical satellite imagery and field observations, glacier outline changes between 2011 and 2020 were also obtained. On average the glacierized area has shrunk by 23.2% and thickness has decreased on average by 6.3 m.</p>
Database for Towards ice thickness inversion: an evaluation of global DEMs in the glacierized Tibetan Plateau
<p>x, latitude of ICESat-2 point</p> <p>y, longitute of ICESat-2 point</p> <p>icesat-2, elevation from icesat-2</p> <p>sigma-icesat-2, error of elevation from icesat-2</p> <p>date-icesat2, acquiring date of icesat-2 point</p> <p>dhdx, along track slope of icesat-2 data</p> <p>dhdx_sigma, error of along track slope of icesat-2 data</p> <p>elevation range min, the minimum elevation of glaciers where icesat-2 data is located</p> <p>elevation range med, the median elevation of glaciers where icesat-2 data is located</p> <p>elevation range max, the maximum elevation of glaciers where icesat-2 data is located</p> <p>dh, glacier surface elevation change from Shean et al. (2020)</p> <p>aw3d30, elevation from aw3d30 in EGM96 geoid</p> <p>srtmgl1, elevation from srtmgl1 in EGM96 geoid</p> <p>tandem, elevation from TanDEM-X in WGS84 ellipsoid</p> <p>srtmv41, elevation from srtmv41 in EGM96 geoid</p> <p>nasadem, elevation from NASADEM in WGS84 ellipsoid</p> <p>merit, elevation from merit in EGM96 geoid</p> <p>aw3d30slp, slope from aw3d30</p> <p>srtmgl1slp, slope from srtmgl1</p> <p>tandemslp, slope from tandem</p> <p>srtmv41slp, slope from srtmv41</p> <p>nasademslp, slope from nasadem</p> <p>meritslp, slope from merit</p> <p>aw3d30asp, aspect from aw3d30</p> <p>srtmgl1asp, aspect from srtmgl1</p> <p>tandemasp, aspect from tandem</p> <p>srtmv41asp, aspect from srtmv41</p> <p>nasademasp, aspect from nasadem</p> <p>meritasp, aspect from merit</p> <p>The elevation should be <strong>converted</strong> using geoidheight function in MATLAB</p> <p> </p> <p> </p> <p> </p>
Ice Velocity of Icelandic Glaciers
<p>Ice velocity map of Icelandic glaciers derived from Sentinel-1 SAR data acquired from 2014-10-01 to 2020-12-31. The surface velocity is derived applying feature tracking techniques. The ice velocity map is provided at 100m grid spacing in North Polar Stereographic projection (EPSG: 3413). The horizontal velocity is provided in true meters per day, towards EASTING(vx) and NORTHING(vy) direction of the grid, and the vertical displacement (vz), is derived from a digital elevation model. Provided is a NetCDF file with the velocity components: vx, vy, vz and vv (magnitude of the horizontal components), along with maps of valid pixel count and uncertainty (stdx, stdy). The product was generated by ENVEO.<br> </p>
A regionally resolved inventory of High Mountain Asia surge-type glaciers, derived from a multi-factor remote sensing approach
<p>This file is the .csv database compiling surge-type glaciers automatically identified in Guillet et al (2022).</p> <p>File format is compliant with the Randolph Glacier Inventory (RGI) V6.0.</p> <p>If you have questions about the dataset - please refer to the following reference or contact Dr. Guillet.</p> <table> <tbody> <tr> <td>Guillet, G., King, O., Lv, M., Ghuffar, S., Benn, D., Quincey, D., & Bolch, T. (2022). A regionally resolved inventory of High Mountain Asia surge-type glaciers, derived from a multi-factor remote sensing approach. <em>The Cryosphere</em>, <em>16</em>(2), 603-623.</td> </tr> <tr> <td> </td> </tr> </tbody> </table> <p> </p>
BISICLES Pine Island Glacier simulations with linear friction
<p>Model simulations of the ice sheet model BISICLES for 100 years on a set of topographies, sampled form a GP (plus BM2 and BedMachine) with linear Weertman friction law.</p> <p>See chapter 5 of <a href="https://doi.org/10.21954/ou.ro.0001223d">https://doi.org/10.21954/ou.ro.0001223d</a> for more information</p>
BISICLES Pine Island Glacier simulations with nonlinear friction
<p>Model simulations of the ice sheet model BISICLES for 100 years on a set of topographies, sampled form a GP (plus BM2 and BedMachine) with m=1/3 Weertman friction law exponent.</p> <p>See chapter 5 of DOI: <a href="https://doi.org/10.21954/ou.ro.0001223d">https://doi.org/10.21954/ou.ro.0001223d</a> for more information</p>
The UAV-derived orthomosaics and DEMs of 23K Glacier and 24K Glacier in southeastern Tibetan Plateau (2019-2020)
<p>The UAV-derived orthomosaics and DEMs of 23K Glacier and 24K Glacier in southeastern Tibetan Plateau (Agu. 2019, Oct. 2019, Agu. 2020, Oct. 2020). </p>
Typology of glaciers and perennial ice bodies for the Mont Blanc massif
<p>The inventory presents different glacier classes and other perennial ice bodies like ice aprons, glacierets, ice caps and snow ice covers for the Mont Blanc massif. </p>
Major element chemistry from supraglacial debris at Khumbu Glacier
<p>An Excel spreadsheet containing raw XRF measurements of 34 major elements in sand samples from source tributaries and the compound tongue of Khumbu Glacier. Samples collected in the field between 1-15 May 2018 and measured in laboratory conditions.</p>
Hydrochemistry of the Leverett Glacier proglacial river, Southwest Greenland (2009-2012)
<p>This dataset describes the dissolved major ion (Ca2+, Mg2+, K+, Na+, Cl-, SO4 2-), nutrient (NO3-, NH4+, PO4 3-, DSi, TDN) and organic carbon (DOC) concentrations in the proglacial rivers of the Leverett Glacier (LG) in Southwest Greenland for the 2009, 2010 and 2012 melt seasons. The data have already been part of 3 different publications (Lawson et al. 2014, Hawkings et al. 2015, Wadham et al. 2016) but are archived here for the first time.</p> <p>For similar data at LG and/or Kiattut Sermia (South Greenland) for the 2015 and 2013 melt seasons, respectively, see Hatton et al. 2018 (see 'related identifiers').</p>
Similar vegetation-geomorphic disturbance feedbacks shape unstable glacier forelands across mountain regions
<p>Glacier forelands are among the most rapidly changing landscapes on Earth. Stable ground is rare as geomorphic processes move sediments across large areas of glacier forelands for decades to centuries following glacier retreat. Yet, most ecological studies sample exclusively on stable terrain to fulfil chronosequence criteria, thus missing potential feedbacks between geomorphic disturbances and vegetation colonization. By influencing vegetation and soil development, such vegetation-geomorphic disturbance feedbacks could be crucial to understand glacier foreland ecosystem development in a changing climate. We surveyed vegetation and environmental properties, including geomorphic disturbance intensities, in 105 plots located on both stable and unstable moraine terrain in two geomorphologically active glacier forelands in New Zealand and Switzerland. Our plot data showed that geomorphic disturbance intensities changed permanently from high/moderate to low/stable when vegetation reached cover values around 40%. Around this cover value, species with response and effect traits adapted to geomorphic disturbances dominated. This suggests that such species can act as 'biogeomorphic' ecosystem engineers that stabilize ground through positive feedback loops. Across floristic regions, biogeomorphic ecosystem engineer traits creating ground stabilization, such as mat growth and association with mycorrhiza, are remarkably similar. Non-metric multidimensional scaling revealed a linked sequence of decreasing geomorphic disturbance intensities and changing species composition from pioneer to late successional species. We interpret this linked geomorphic disturbance-vegetation succession sequence as 'biogeomorphic succession', a common successional pathway in unstable river and coastal ecosystems across the world. Soil and vegetation development were related to this sequence, and only advanced once biogeomorphic ecosystem engineer species covered 40–45% of a plot, indicating a crucial role of biogeomorphic ecosystem engineer stabilization. Different topoclimatic conditions could explain variance in biogeomorphic succession timescales and ecosystem engineer root traits between the glacier forelands. As glacier foreland ground is widely unstable, we propose to consider glacier forelands as 'biogeomorphic ecosystems' in which ecosystem structure and function are shaped by geomorphic disturbances and their feedbacks with adapted plant species, similar to rivers and coasts.</p>
Reconstructed Aneto glacier surfaces from historic aerial image photogrammetry (1981) and remote sensing techniques (2020, 2021, 2022)
<p>The Aneto Glacier, is the largest glacier in the Pyrenees. Its shrinkage and wastage have been continuous in recent decades, and there are signs of accelerated melting in recent years. In this study, changes in the surface and ice thickness of the Aneto Glacier from 1981 to 2022 are investigated using historical aerial imagery, airborne LiDAR point clouds, and UAV imagery. A GPR survey conducted in 2020, combined with data from photogrammetric analyses, allowed us to reconstruct the current ice thickness and also the existing ice distribution in 1981 and 2011. Over the last 41 years, the total glaciated area has shrunk by 64.7% and the ice thickness has decreased, on average, by 30.5 m. The mean remaining ice thickness in autumn 2022 was 11.9 m, as against the mean thicknesses of 32.9 m, 19.2 m reconstructed for 1981 and 2011 and 15.0 m observed in 2020 respectively. The results demonstrate the critical situation of the glacier, with an imminent segmentation into two smaller ice bodies and no evidence of an accumulation zone. We also found that the occurrence of an extremely hot and dry year, as observed in the 2021–2022 season, leads to a drastic degradation of the glacier, posing a high risk to the persistence of the Aneto Glacier, a situation that could extend to the rest of the Pyrenean glaciers in a relatively short time. </p>
Surge-induced Crevasse dynamics of Monacobreen Glacier, Svalbard, through SAR observations and subglacial flow estimations
<p>This repository contains the datasets of glacial surface velocity, subsurface velocities, and the basal shear stress published in the paper 'Surge-induced Crevasse dynamics of Monacobreen Glacier, Svalbard, through SAR observations and subglacial flow estimations' in AGU Earth and Space Sciences. The detailed methodological description along with the computational methods have been discussed in detail in the article.</p>
Dataset associated with article: Self-sufficient seismic boxes for monitoring glacier seismology in Greenland
<p>Dataset associated with article: Self-sufficient seismic boxes for monitoring glacier3 seismology in Greenland</p> <p>Contains:<br> - Seismic data of both SG-boxes and regular geophones from Gornergletscher fieldtest, 2021( Seismic_Data_Gorner_Fieldtest.zip) <br> --> SG-box data naming: GO"station_number"SG <br> --> Geophone data naming: GO"station_number"GP<br> <br> - Weather data Gornergletscher fieldtest from Monte Rosa, Meteo Swiss Weather station ( Weather_data_Gorner_Fieldtest_2021.zip) <br> --> 1hr wind averages <br> --> 1hr temperature averages<br> <br> - MSR logger data from SG-boxes from Gornergletscher fieldtest, 2021. Every 5 min these log battery power, tilt (along three axes, temperature and humidity inside the box and light strength on two sides of the SG-box. ( MSR_logger_data_SGboxes_Gorner_Fieldtest.zip )<br> <br> - Seismic data of SG box (Sensor code BSM) next to weather station first acquisition Greenland 2021 ( Seismic_Data_SG_Box_first_acquisition_Greenland_2021.zip) <br> --> .pri0 is East component, .pri1 is North component, .pri2 is Vertical component.<br> <br> - Weather data from weather station next to SG-box (sensor code BSM) during first acquisition Greenland 2021 ( Weather_station_data_Greenland_2021.zip) <br> --> The weather station logs a value every two hours.</p> <p> </p>
Modelled runoff for 14 glaciers in NW Greenland, 2015-2020
<p>Modelled catchment runoff timeseries for 14 glaciers in NW Greenland between 2015-2020.</p> <p>This data set has been archived to comply with open data access requirements during manuscript submission.</p> <p> </p>
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International Brain Laboratory public data
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OpenNeuro
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