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23 results for “Ice cap”
Fifty years of firn evolution on Grigoriev ice cap, Tien Shan, Kyrgyzstan
<p><strong>README Grigoriev data</strong></p> <p><strong>Overview</strong></p> <p>The Grigoriev data collection consists of the following files, which are briefly explained further below.<br>From a relatively large number of files and for clarity, we provide mainly those files which have been directly<br>used in the generation of figures contained in Machguth et al. (2024). While the use in figure<br>creation was the main selection criteria, the files have not been truncated to data shown in the figures. <br>The files contain more information than shown in the figures. A few files have been added for completeness although<br>not used to create figures (see below).</p> <p>The data sets provided in this repository are listed in the following. Most of these tables contain relatively raw data. <br>The suggested citations are added in brackets. Please also check Table 1 in Machguth et al. (2024) for potential further references.</p> <p>- 1990_GRG_90_H1-BETA.xlsx (Arkhipov et al., 1996; Thompson et al., 1997)<br>- 1990_GRG_90_H1-CHM.xlsx (Arkhipov et al., 1996; Thompson et al., 1997)<br>- 1990_GRG_90_H1-STRAT.xlsx (Arkhipov et al., 1996; Thompson et al., 1997)<br>- 1990_GRG_90_H2-CHM.xlsx (Arkhipov et al., 1996; Thompson et al., 1997)<br>- 1990_GRG_90_H2-STRAT.xlsx (Arkhipov et al., 1996; Thompson et al., 1997)<br>- 1990_H1-H2_2018_Grigoriev_MI-decadal.xlsx (Arkhipov et al., 1996; Thompson et al., 1997; Machguth et al., 2024)<br>- 2001_GRG_01_S1-EE.xlsx (Arkhipov et al., 2004; Mikhalenko et al., 2005)<br>- 2001_metals.pdf (Usubaliev, 2003)<br>- 2003_GRG03-S1-EE_001.xlsx (Mikhalenko et al., 2005; Kutuzov, 2005)<br>- 2003_GRG03-S2-EE 001.xlsx (Mikhalenko et al., 2005; Kutuzov, 2005)<br>- 2003_pits.xlsx (Mikhalenko et al., 2005; Kutuzov, 2005)<br>- 2003_temperature_density.xlsx (Mikhalenko et al., 2005; Kutuzov, 2005)<br>- 2003_temperature_logger_data.xls (Mikhalenko et al., 2005; Kutuzov, 2005)<br>- 2018_density_stratigraphy_field_and_PSI_by_centimeter.xlsx (Machguth et al., 2024)<br>- 2018_PSI_dating_20230517.xlsx (Eichler et al., 2020; Machguth et al., 2024)</p> <p><br><strong>Detailed Information</strong></p> <p>1990_GRG_90_H1-BETA.xlsx: refers to Core 1 1990 (labelled H1 probably for "Hole 1"). Unknown to what the 1991 data refer, likely a repeat measurement.</p> <p>1990_GRG_90_H1-CHM.xlsx: Chemistry Core 1 1990.</p> <p>1990_GRG_90_H1-STRAT.xlsx: Stratigraphic information Core 1 1990</p> <p>1990_GRG_90_H2-CHM.xlsx: Chemistry Core 2 1990</p> <p>1990_GRG_90_H2-STRAT.xlsx: Stratigraphic information Core 2 1990</p> <p>1990_H1-H2_2018_Grigoriev_MI-decadal.xlsx: This table we calculated from the 1990 tables as well as the 2018 data for the purpose of visualizing<br> decadal means in MIs (Fig. 7). Decadal dating of the 1990 cores was done based on the bomb horizon of 1963 (Thompson et al., 1993, 1997), <br> decadal picks from Thompson et al. (1993) and personal communication by Lonnie Thompson (email 19 June 2023).</p> <p>2001_GRG_01_S1-EE.xlsx: 2001 core, stable water isotope ratios, firn temperatures, percentage of infiltration ice, stratigraphy</p> <p>2003_GRG03-S1-EE_001.xlsx: 2003 51m and 22.6m cores, 51m core was drilled thermally, 22.6m core mechanically. For the latter similar data as for 2001</p> <p>2003_GRG03-S2-EE 001.xlsx: 2003 21.3m core. Reduced amount of measured parameters compared to e.g. 2001 core. </p> <p>2003_pits.xlsx: Stratigraphy and density measured in a series of snow pits in 2003.</p> <p>2003_temperature_density.xlsx: Density and temperature measured in 2003 22.6m core. Comparison of T_ice at 4440 m a.s.l. to 1962 core (Dikikh, 1965)</p> <p>2003_temperature_logger_data.xls: Firn temperatures measured through a thermistor chain during 3 days in June 2003. Data from 14 June have been used for Fig. 5.</p> <p>2018_density_stratigraphy_field_and_PSI_by_centimeter.xlsx: 2018 core stratigraphy and density. This is a somwhat outdated file which shows the data per centimetre.<br> The file compares the two measurements of density (only the one from the laboratory was used in Machguth et al., 2024). <br> Also contains visually observed dust layers (not shown in Machguth et al., 2024)</p> <p>2018_PSI_dating_20230517.xlsx: Complete data from the analysis of the 2018 core.</p> <p><br><strong>Bibliography</strong></p> <p>Arkhipov, S. M., Mikhalenko, V. N., & Thompson, L. (1996). Struktura i stratigrafiya deyatel’nogo sloya lednika Grigor’eva na Tyan’-Shanye (Structure and stratigraphy of the active layer <br>of the Griroriev glacier in the Tjan-Shan). Materialy Glyatsiologicheskikh Issledovaniy (Data of Glaciological Studies), 80, 68–83.</p> <p>Arkhipov, S. M., Mikhalenko, V. N., Kunakhovich, M. G., Dikikh, A. N., and Nagornov, O. V.: Termicheskiy reshim, uslovija l’doobrazovanija i akkumulatsija na lednike Grigor’eva (Tyan’-<br>Shan), v 1962–2001 gg. (Thermal regime, types of ice formation and accumulation on the Grigoriev glacier (Tien Shan), 1962–2001), Materialy Glyatsiologicheskikh Issledovaniy (Data<br>of Glaciological Studies), 96, 77–83, 2004.</p> <p>Eichler, A., Kronenberg, M., Brütsch, S., Rüthi, M., Heule, M., Schwikowski, M., et al. (2020). Chernobyl horizon in a Central Asian ice core. <br>Annual Report 2019 - Laboratory of Environmental Chemistry - PSI, 31.</p> <p>Kutuzov, S. S.: Prostranstvennie izmenenija i stroenie lednikov vnutrennogo Tyan’-Shanya za poslednie 150 let (Spatial changes and structure of the glaciers of the inner Tien Shan over the last 150<br>years), Master’s thesis, Lomonossov State University, Moskva, 2005.</p> <p>Machguth, H., Eichler, A., Schwikowski, M., Brütsch, S., Mattea, E., Kutuzov, S., et al. (2024). Fifty years of firn evolution on Grigoriev ice cap, Tien Shan, Kyrgyzstan. <br>The Cryosphere, 18(4), 1633–1646. https://doi.org/10.5194/tc-18-1633-2024</p> <p>Mikhalenko, V. N., Kutuzov, S. S., Fayzrakhmanov, F. F., Nagornov, . B., Thompson, L. G., Kunakhovich, M. G., Arkhipov, S. M., Dikikh, A. N., and Usubaliev, R.: Sokrashhenie oledenenija<br>Tyan’-Shanja v XIX – nachale XXI vv.: rezul’taty kernovoro burenija i izmerenija temperatury v skvazhinakh (Glacier recession in the Tien Shan from the XIX to the beginning of the XXI century:<br>results from ice core drilling and borehole temperature measurements), Materialy Glyatsiologicheskikh Issledovaniy (Data of Glaciological Studies), 98, 175–182, 2005.</p> <p>Thompson, L. G., Mosley-Thompson, E., Davis, M., Lin, P. N., Yao, T., Dyurgerov, M., & Dal, J. (1993). “Recent warming” ice core evidence from tropical ice cores with emphasis <br>on Central Asia. Global Planet. Change, 7(1–3), 145–156. https://doi.org/10.1016/0921-8181(93)90046-Q</p> <p>Thompson, L. G., Mikhalenko, V., Mosley-Thompson, E., Durgerov, M., Lin, P. N., Moskalevsky, M., et al. (1997). Ice core records of recent climatic variability: Grigoriev and It-Tish ice caps <br>in Central Tien Shan, Central Asia. Materialy Glyatsiologicheskikh Issledovaniy (Data of Glaciological Studies), 81, 100–109.</p> <p>Usubaliev, R. A. (2003). Khimitcheskoe zagryaznenie lednikov Tyan’-Shanya (na primere lednika Grigor’eva) (Chemical pollution of Tien Shan glaciers (on the example of Grigoriev Glacier)). <br>Izvestija Natsional’noy Akademii Nauk Kirgizskoy Respubliki (News of the National Academy of Sciences of the Kyrgyz Republic), 4, 154–160.</p>
Ice thickness and bed topography of all Scandinavian glaciers and ice caps
<p>Files showing the ice thickness (m) and subglacial bed elevation (m) for all Scandinavian (i.e. Norwegian and Swedish) glaciers and ice caps. Coordinate system is epsg:25833</p> <p>Related publication which should be referenced when this data is used is </p> <div> <div> <div>Frank T, van Pelt W. Ice volume and thickness of all Scandinavian glaciers and ice caps. <em>Journal of Glaciology</em>. Published online 2024:1-34. doi:10.1017/jog.2024.25 <div> </div> </div> </div> </div>
El Niño Enhances Snowline Rise and Ice Loss on the Quelccaya Ice Cap, Peru
<p>El Niño Enhances Snowline Rise on the Quelccaya Ice Cap, Peru (in-review)</p> <p>Kara A. Lamantia, Laura J. Larocca, Lonnie G. Thompson, Bryan Mark</p> <p>Exported results from automated snow cover area detection on the Quelccaya Ice Cap (QIC). Further calculated results are detailed in the supplementary documentation in the draft manuscript. See READ ME.txt file for details</p> <p>Sample Code available for Landsat 8 imagery here at the following URL: https://code.<br>earthengine.google.com/cfcbd0780ff3f09b0698035cd6dd678a</p>
Supplemental data for "The possible transition from glacial surge to ice stream on Vavilov Ice Cap"
<p>Data presented in the paper "The possible transition from glacial surge to ice stream on Vavilov Ice Cap".</p>
Ice thicknesses of the Müller ice cap
<p>Modeled ice thicknesses of the Müller ice cap, Axel Heiberg Island. Five different models of the ice thickness has been made. All model results comes with individual GeoTIFFs of bedrock topography, ice thickness and surface elevation. The data is either on a 100 or 900 meters grid depending on the model.</p> <p>Citation:</p> <p>Ann-Sofie P. Zinck, Surface velocity and ice thickness of the Müller ice cap, Axel Heiberg Island, Master thesis, University of Copenhagen, Copenhagen, 2020</p>
Surface velocities of the Müller ice cap
<p>A median surface velocity map of the Müller ice cap on Axel Heiberg Island in the period of 2014 to 2019. The surface velocity maps are made using feature tracking of optical Landsat 8 images using the panchromatic band. The velocity map is on a 900 meters grid.<br> <br> ListOFLandsat8scenes.xlsx provides a list of all of the scenes used in the feature tracking process. The feature tracking is done using two scenes from the same row and path with approximately one year in between. The median of all velocity maps has been made and is presented here.</p> <p>Citation:</p> <p>Ann-Sofie P. Zinck, Surface velocity and ice thickness of the Müller ice cap, Axel Heiberg Island, Master thesis, University of Copenhagen, Copenhagen, 2020</p>
New insights into the decadal variability in glacier volume of a tropical ice-cap explained by the morpho-topographic and climatic context, Antisana, (0°29' S, 78°09' W)
<p>The dataset contains five periods of surface elevation change observed on the Antisana icecap in the inner tropical region. Data were obtained by geodetic observations of aerial photographs and high-resolution satellite images for the study periods: 1956-1965, 1965-1979, 1979-1997, 1997-2009, and 2009-2016.</p>
Mueller Ice Cap data
<p>Radar, surface elevation, velocity, meteorological, and ice-core data from Müller Ice Cap, Umingmat Nunaat, Nunavut, Canada.</p>
Area, volume and ELA changes of West Greenland local glaciers and ice caps over the last 35 years
<p>This dataset refers to:</p> <p><em>Area, volume and ELA changes of West Greenland local glaciers and ice caps over the last 35 years</em><br><em>Securo Andrea, Del Gobbo Costanza, Citterio Michele, Machguth Horst, Marcer Marco, Korsgaard Niels J., Colucci Renato R.</em></p> <p>This study analyses the cumulative area, ice mass and Equilibrium Line Altitude changes that occurred on more than 4000 glaciers and ice caps in West Greenland (outside of the Greenland Ice Sheet) from 1985 to 2020, using remotely sensed data and including glaciers smaller than 1 km2 in the calculations.</p> <p>This dataset contains:</p> <ol> <li><strong>1_Area_1985_2020.csv</strong> - Comma Separated Value file with the following data for all Glaciers and ice caps involved in the study:<br>Area Loss from 1985 to 2020 (km2), Total Area of 1985 (km2), Relative Area Loss from 1985 to 2020 (%), Longitude, Latitude</li> <li><strong>2_Area_Loss_1985_2020.gpkg</strong> - Geopackage file contanining the same information as (1.) but including the centroids positions. EPSG 4326 WGS84</li> <li><strong>3_Volume_and_ELA_1985_2020.csv</strong> - Comma Separated Value file with the following data for all Glaciers and ice caps involved in the study: GLIMS Glacier ID, minimum elevation (m a.s.l.), mean elevation (m a.s.l.), maximum elevation (m a.s.l.), Surface elevation change 1985-Present (m), Glacier Area from RGI (km2), Ice Mass Loss (Gt), 1985 mean ice thickness from Millan and others (m), Relative volume loss from 1985 to Present (%), Longitude, Latitude, Equilibrium Line Altitude* (m)</li> <li><strong>4_Volume_and_ELA_1985_2020.gpkg</strong> - Geopackage file contanining the same information as (3.) but including the centroids positions. EPSG 4326 WGS84</li> </ol> <p>* note that not all glaciers and ice caps have ELA value for present.</p>
Ground-penetrating radar and shallow firn cores from Devon Ice Cap, Canadian Arctic
<p>GPR data and firn cores were collected over Devon Ice Cap, Canadian Arctic in May 2015.</p> <p>-----------------------------------------------------------------</p> <p><strong>Firn cores</strong></p> <p>Six ~11 m long firn cores were drilled using a Kovacs drill (9 cm diameter) along the GPR profiles. Pictures were taken of the firn cores, which were subsequently used to log the firn facies. From each core, three sections at different depths that did not include ice layers were weighted with a digital scale and used to calculate the firn density. At each firn core location, the snow depth was recorded, as well as at an additional location where a snow pit was dug (SPB1).</p> <p><em>DIC_firn_cores_2015_density.xlsx</em>: Firn core density measurements. Three measurements were taken from each core, using ice-free sections. </p> <p><em>DIC_firn_cores_2015_stratigraphy.xlsx</em>: Firn stratigraphy for each core location, derived from the firn core pictures. F stands for firn, I for ice layer, and P for percolation pipe/feature (ice in the firn core that does not present as an ice layer throughout the core diameter).</p> <p><em>DIC_snowdepth_2015.xlsx</em>: Snow depth measurements at each core location.</p> <p><em>Firn_core_pictures.zip</em>: Pictures of the firn cores taken with infrared and visible light cameras.</p> <p>-----------------------------------------------------------------</p> <p><strong>GPR data</strong></p> <p>GPR data were collected with a PulseEKKO Noggin radar (Sensors & Software Inc.) with 500 MHz center frequency antennae (i.e., 0.6 m wavelength). The antennae were mounted on a plastic sled towed by snowmobile, generating a data set sampled every ~0.4 m along track. Positioning was obtained with a Leica Geosystems GPS system providing a 25 cm RMS accuracy.</p> <p>Processing of the GPR data was performed in Matlab and included dewow filtering, time-zero shift, background removal, Butterworth band-pass filtering and the application of a gain function.</p> <p><em>PulseEkko_RawData</em>: Folder containing the raw PulseEKKO GPR and GPS files.</p> <p><em>PulseEkko_ProcessedData</em>: Contains the processed GPR data as .mat files. Description of the data files can be found in <em>ProcessedData_readme.txt</em>.</p> <p> </p>
Austfonna ice cap: experiment 5 with γ = 0.2°C by Dunse et al. (2011)
<p>Surface-velocity and basal-temperature fields of Austfonna ice cap over 1000 years of present-day climate conditions (model year 29000-30000), simulated with the SICOPOLIS model: experiment 5 with sub-melt-sliding parameter γ = 0.2°C by <a href="https://doi.org/10.3189/002214311796405979">Dunse et al. (2011)</a>.</p>
dataset Spagnesi et al., 2023 "Preservation of chemical and isotopic signatures within the Weißseespitze millennial old ice cap (Eastern Alps), despite the ongoing ice loss"
<p>Dataset related to the paper "<strong>Preservation of chemical and isotopic signatures within the Weißseespitze millennial old ice cap (Eastern Alps), despite the ongoing ice loss</strong>" by Spagnesi et al. (2023). It contains the chemistry, microcharcoal and water stable isotopes measurements conducted on the Weißseespitze ice cores drilled in 2019 and 2021.</p>
Supporting Data: Exploring Canyons Beneath Devon Ice Cap
<p>These data are associated with the paper "<span>Exploring Canyons Beneath Devon Ice Cap for Sub-Glacial </span><span>Drainage Using Radar and Thermodynamic Modeling". This repository contains 3 data sets:</span></p> <ul> <li><span>RES simulations - returned power radargrams (Matlab .mat format) from 4 simulated scenarios over Canyon B at DEV3_PER0a_Y86a. These include 2 frozen bed scenarios (0.2m and 0.35m roughness) and 2 scenarios with a 10m canal (0.2m and 0.35m roughness).</span></li> <li><span>Temp simulations - the folder for each location simulated contains the following files:</span> <ul> <li><span>xx.csv - all x locations (in m) for the 2-D grid modeled</span></li> <li><span>zz.csv - all z locations (in m) for the 2-D grid modeled</span></li> <li><span>6 temperature grids (in degrees C) corresponding to the x and y positions in xx.csv and zz.csv. The filename indicates the basal boundary condition ("Lachenbruch" or "Constant") and accumulation rate ("b=<>") used. </span></li> </ul> </li> </ul>
Geodetic mass balance of Mýrdalsjökull ice cap, 1999−2021: DEM processing and climate analysis
<p>This repository gathers the data I used and produced during my master thesis at the University of Iceland from April to September 2022 with the financial support of the Landsvirkjun.</p> <p>The geodetic mass of Mýrdalsjökull, the fourth largest Icelandic ice cap, was investigated over the period 1999-2021. The untapped <strong>SPOT5 </strong>archive (2002−2015), the <strong>lidar </strong>data, the <strong>Pléiades </strong>imagery (2011−present), <strong>aerial photographs</strong> from 1999 [1] and the <strong>ArcticDEM </strong>dataset (2010−2019) [2] were used to create Digital Elevation Models (DEMs) of the ice cap. A pre-processing of the DEMs was first performed: co-registration, filtering and interpolation. Then, applying a <strong>Gaussian Process regression</strong> (GP) [3], a state-of-the-art method in DEM processing, a spatially and temporally continuous DEM dataset was created, in 15 x 15 m resolution and 1-month interval from 1999 to 2021. <strong>Volume and mass changes</strong> based on the synthetic GP-generated DEMs were computed and analyzed in 5-year and annual intervals between 1999 and 2019. A local analysis of three glacierized catchments of Mýrdalsjökull (southern catchment, northern catchment and Kötlujökull outlet) was also performed. Errors were estimated using the method from [4]. Tools from the following repositories were used:</p> <ul> <li> <p><em>demcoreg </em>(<a href="https://doi.org/10.5281/zenodo.5733347">https://doi.org/10.5281/zenodo.5733347</a>): DEM co-registration</p> </li> <li> <p><em>xdem </em>(<a href="https://doi.org/10.5281/zenodo.4809698">https://doi.org/10.5281/zenodo.4809698</a>): uncertainties computation and DEM manipulation </p> </li> <li> <p><em>pyddem </em>(<a href="https://pypi.org/project/pyddem/">https://pypi.org/project/pyddem/</a>): Gaussian Process regression</p> </li> </ul> <p>The complete master thesis can be accessed at :</p> <p> </p> <p>The repository contains the following data:</p> <p><strong>1</strong> – <strong>DEM_coregistered</strong></p> <p>All DEMs have been coregistered considering the Islandsdem v1.0 as a reference (atlas.lmi.is/dem)</p> <p>The DEM naming works as follow: </p> <p><em>Glaciername_DEM_date_sensor_resolution_zmae_projection_otherinformation.tif</em></p> <p>The files ending with <strong>*_filtered.tif</strong> (SPOT5, AerialPhotographs) have been filtered using the filtering combination described in 3.1.3.</p> <p>The files ending with<strong> *_mosaic.tif</strong> (SPOT5, Pléiades) are the result of the mosaicking of several DEMs.</p> <p> </p> <p><strong>2</strong> – <strong>Shapefiles</strong></p> <p>Outlines of Mýrdalsjökull in 1999 [1], 2003, 2010 and 2019 [6]</p> <p>Outlines of the three catchments (South, North and Kötlujökull) in 1999.</p> <p>Reference buffer around Mýrdalsjökull used to crop all DEMs to the same extent. </p> <p>Equilibrium Line Altitude (ELA) from 2004-10-05.</p> <p> </p> <p><strong>3</strong> – <strong>Gaussian_Process_regression</strong></p> <p>2 netcdf files: the stack of DEMs (<strong>*_DEMstack_*</strong>) and the result of the Gaussian Process regression (<strong>*_GPregression_*</strong>).</p> <p>Both files were obtained thanks to <em>pyddem </em>tools.</p> <p>The Gaussian Process regression was run at a spatial resolution of 15 x 15m and a temporal resolution of 1 month, starting in January 1999 and ending in December 2022.</p> <p> </p> <p><strong>4</strong> – <strong>Mass_balance_results</strong></p> <p>1 csv file containing mass balance results:</p> <ul> <li> <p>Annual mass balance for the ice cap & the 3 catchments</p> </li> <li> <p>4-year mass balance for the ice cap & the 3 catchments</p> </li> <li> <p>Results from the comparison with survey dates mass balance (Fig 11(a))</p> </li> <li> <p>Results from the comparison with [3] (Fig 11(b))</p> </li> <li> <p>Mass balance overview (Fig 11(c))</p> </li> </ul> <p> </p> <p><strong>References</strong></p> <p>[1] Belart, J., Magnússon, E., Berthier, E., Gunnlaugsson, Á. Þ., Pálsson, F., Aðalgeirsdóttir, G., Jóhannesson, T., Thorsteinsson, T., and Björnsson, H. (2020). Mass balance of 14 Icelandic glaciers, 19452017: spatial variations and links with climate. Frontiers in Earth Science, page 163.</p> <p>[2] Porter, C., Morin, P., Howat, I., Noh, M., Bates, B., Peterman, K., Keesey, S., Schlenk, M., Gardiner, J., et al. (2018). ArcticDEM. Harvard Dataverse, 1.</p> <p>[3] Hugonnet, R., McNabb, R., Berthier, E., Menounos, B., Nuth, C., Girod, L., Farinotti, D., Huss, M., Dussaillant, I., Brun, F., et al. (2021). Accelerated global glacier mass loss in the early twenty-first century. Nature, 592(7856):726731.</p> <p>[4] Hugonnet, R., Brun, F., Berthier, E., Dehecq, A., Mannerfelt, E. S., Eckert, N., and Farinotti, D. (2022). Uncertainty analysis of digital elevation models by spatial inference from stable terrain. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing.</p> <p>[5] Hannesdóttir, H., Sigurðsson, O., Þrastarson, R. H., Guðmundsson, S., Belart, J. M., Pálsson, F., Magnússon, E., Víkingsson, S., Kaldal, I., and Jóhannesson, T. (2020). A national glacier inventory and variations in glacier extent in Iceland from the Little Ice Age maximum to 2019. Jökull 2020: 1, 34.</p> <p> </p> <p><strong>Acknowledgements</strong></p> <p>Pléiades images were acquired at research price thanks to the CNES ISIS programme (http://www.isiscnes.fr). This study uses the lidar mapping of the glaciers in Iceland, funded by the Icelandic Research Fund, the Landsvirkjun research fund, the Icelandic Road Administration, the Reykjavík Energy Environmental and Energy Research Fund, the Klima- og Luftgruppen research fund of the Nordic Council of Ministers, the Vatnajökull National Park, the organization Friends of Vatnajökull, LMÍ, IMO, and the UI research fund.</p> <p> </p> <p><strong>Dataset Attribution</strong> </p> <p>This dataset is licensed under a <a href="https://creativecommons.org/licenses/by-nc/4.0/">Creative Commons CC BY-NC 4.0 International License</a> (Attribution-NonCommercial).</p>
Dataset for "The 21st-century fate of the Mocho-Choshuenco ice cap in southern Chile"
<p>Dataset for the paper "The 21st-century fate of the Mocho-Choshuenco ice cap in southern Chile", <a href="https://doi.org/10.5194/tc-15-3637-2021">published in The Cryosphere</a>. For more information, please refer to the readme file, the metadata of the nc-files, and the paper.</p>
Multi-technique surface geophysical surveys over Devon Ice Cap, Canadian Arctic
<p>This dataset was acquired during a multi-technique surface geophysical campaign in May 2022 over Devon Ice Cap, Canadian Arctic.</p> <p><strong>Description of data:</strong></p> <p><strong>Seismic</strong><br> 9 km of active source seismic reflection data<br> raw segy files for line A and line B<br> seismic observation log<br> matlab script for plotting a raw stack of line A and line B<br> coordinates of each seismic spread, with the ice surface elevation and estimated bed elevation</p> <p><strong>Transient electromagnetic (TEM) </strong><br> 7 large loop TEM soundings <br> with 500 x 500 m loop with receiver 250 m outside the loop (away from the transmitter)<br> USF files for each sounding<br> coordinates for each TEM sounding<br> TEM observation log </p> <p><strong>Magnetotelluric (MT)</strong><br> 17 MT stations<br> raw, unprocessed EDI files <br> coordinates for each MT station <br> MT observation log</p> <p>Time series data (~80GB) can be found at:<br> https://drive.google.com/drive/folders/1OyCIP_B3VUJ4-ULSp8YOAPuNEMHuNcN-?usp=share_link</p> <p><strong>Acknowledgments</strong></p> <p>We thanks the Polar Continental Shelf Program for logistical support throughout the field season; Rob Harris at Geonics for his support and help with the TEM method; Zoe Vestrum at the University of Alberta for her MT support during deployment to the field; </p> <p><strong>Funding</strong></p> <p>This work was funded by the Weston Family Foundation. The aircraft hours were funded by the Polar Continental Survey Program (PCSP) and ArcticNet. MT survey was supported by a NSERC Discovery Grant to Martyn Unsworth and the Future Energy Systems program at the University of Alberta. </p> <p><strong>Corresponding Author</strong></p> <p>Siobhan Killingbeck skillin1@ualberta.ca</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>
Data and derived products from airborne radar sounding survey over Devon Ice Cap, Canadian Arctic
<p>Data and derived products used in Rutishauser et al., “Radar sounding survey over Devon Ice Cap indicates the potential for a diverse hypersaline subglacial hydrological environment”, accepted for publication, The Cryosphere, <a href="https://doi.org/10.5194/tc-2021-220">https://doi.org/10.5194/tc-2021-220</a></p> <p>Corresponding author: <a href="mailto:rutishauser.anja@gmail.com">rutishauser.anja@gmail.com</a></p> <p> </p> <p><strong>Description of datasets:</strong></p> <p>------------------------------------------</p> <p><strong>2018_DIC_UTIG.IR2HI1B.kml</strong></p> <p>Geolocation of the SRH1 profile lines. Coordinates in EPSG: 4326 - WGS 84 (latitude, longitude)</p> <p>------------------------------------------</p> <p><strong>2018_DIC_UTIG.IR2HI1B.tgz</strong></p> <p>HiCARS 2 L1B echo strength profiles (radargrams) in NetCDF format. The naming of the files has the structure IR2HI1B_YYYYDOY_PST_x (e.g. IR2HI1B_2018153_DEV_JKB2t_Y87b_000.nc), where YYYY is the survey year (e.g. 2018), DOY is the survey day of the year (e.g. 153), PST is the profile name (e.g. DEV_JKB2t_Y87b), and x is the segment number if the profile was split in two (e.g. 000).</p> <p>For each profile, a PDF file showing the profile location and the radargram is included.</p> <p>------------------------------------------</p> <p><strong>2018_DIC_UTIG.Level2.tgz </strong></p> <p>Level 2 datasets for each profile, organized in the following folders:</p> <ul> <li><strong>2018_DIC_UTIG.ILUTP2:</strong> Laser altimeter geolocated surface elevation</li> <li><strong>2018_DIC_UTIG.IR2HI2:</strong> HiCARS 2 unfocused (pik1) geolocated ice thickness, ice surface elevation, bed elevation, surface- and bed reflection coefficients, and aircraft roll</li> <li><strong>2018_DIC_UTIG.IRHFOC2:</strong> HiCARS 2 focused (foc1) geolocated ice thickness, ice surface elevation, bed elevation, surface- and bed reflection coefficients, and aircraft roll</li> <li><strong>2018_DIC_UTIG.IRSPC2: </strong>HiCARS 2 derived basal interface specularity content</li> </ul> <p>------------------------------------------</p> <p><strong>Devon_basal_ice_temperature.tif: </strong>Modeled basal ice temperature [ºC] using a 1D advection diffusion model. 500 m grid cell size, coordinates in EPSG: 32617 - WGS 84 / UTM zone 17N.</p> <p>------------------------------------------</p> <p><strong>Devon_bedrockDEM.tif: </strong>Digital elevation model (DEM) of the bedrock topography beneath Devon Ice Cap [m asl.]. 500 m grid cell size, coordinates in EPSG: 32617 - WGS 84 / UTM zone 17N.</p> <p>------------------------------------------</p> <p><strong>Devon_gridded_RMSD_bedrock.tif</strong>: Root mean square deviation (RMDS) of the bedrock topography [m]. The RMSD was computed along each profile line, then interpolated on a 500x500m grid using the QGIS GDAL moving average grid interpolation. 500 m grid cell size, coordinates in EPSG: 32617 - WGS 84 / UTM zone 17N.</p> <p>------------------------------------------</p> <p><strong>Devon_gridded_specularity.tif</strong>: Specularity content from along the profile lines interpolated on a 500x500m grid using the QGIS GDAL moving average grid interpolation. 500 m grid cell size, coordinates in EPSG: 32617 - WGS 84 / UTM zone 17N.</p> <p>------------------------------------------</p> <p><strong>Devon_ice_thickness.tif</strong>: Gridded ice thickness [m] generated by subtracting the bedrock DEM from ice surface elevations derived from the ArcticDEM, Polar Geospatial Center from DigitalGlobe Inc. imagery. 500 m grid cell size, coordinates in EPSG: 32617 - WGS 84 / UTM zone 17N.</p> <p>------------------------------------------</p> <p><strong>Devon_modeled_Geology.zip</strong></p> <ul> <li><strong>Devon_modeled_subglacial_geology.tif</strong>: Map of the projected geological units beneath Devon Ice Cap. The assigned numbers correspond to the following geological units: 1: pPe, 2: Cm-cf, 3: Oe, 4: Ocb, 5: Oct. Details on the geological units can be found in (Harrison et al., 2016; Mayr, 1980; Thorsteinsson & Mayr, 1987). 500 m grid cell size, coordinates in EPSG: 32617 - WGS 84 / UTM zone 17N.</li> <li><strong>{pPe, Oe, Oct, Ocb,Cm_rb}_Model.stl</strong>: 3D geometry of the modeled geological units beneath Devon Ice Cap, originally published in (Rutishauser et al., 2018). Coordinates in EPSG: 32617 - WGS 84 / UTM zone 17N.</li> <li><strong>Devon_load_geology_stl_files.py</strong><em>: </em>Python script to load and plot the 3D geology layers in the .stl files.</li> </ul> <p>------------------------------------------</p> <p><strong>Devon_subgl_hydraulic_head.tif</strong>: Subglacial hydraulic head [m] beneath Devon Ice Cap. 500 m grid cell size, coordinates in EPSG: 32617 - WGS 84 / UTM zone 17N.</p> <p>------------------------------------------</p> <p><strong>Devon_subgl_hydraulic_slope.tif</strong></p> <p>Slope [º] of the subglacial hydraulic head beneath Devon Ice Cap. 500 m grid cell size, coordinates in EPSG: 32617 - WGS 84 / UTM zone 17N.</p> <p>------------------------------------------</p> <p><strong>Devon_subgl_lakes_brine_network.zip</strong></p> <ul> <li><strong>Devon_subgl_lake_outline.shp</strong>: Shoreline of the subglacial lakes beneath Devon Ice Cap (identified in this study). Coordinates in EPSG: 32617 - WGS 84 / UTM zone 17N.</li> <li><strong>Devon_brine_network_outline.shp</strong>: Outlines of the mapped subglacial brine network beneath Devon Ice Cap. Coordinates in EPSG: 32617 - WGS 84 / UTM zone 17N.</li> </ul> <p>------------------------------------------</p> <p><strong>Devon_subgl_water_routes.zip</strong></p> <ul> <li><strong>Devon_modeled_subgl_water_routes_{1, 2, 3}std.tif</strong>: Modeled subglacial water routes derived via application of a flow accumulation algorithm to the hydraulic head. The model is run 1000 times with normally distributed random errors of 1, 2 and 3 standard deviations of the hydraulic head uncertainty added to the hydraulic head (represented in the file name). Pixel values represent the model counts for which the cell has a minimum of 10 upstream cells draining into it. 500 m grid cell size, coordinates in EPSG: 32617 - WGS 84 / UTM zone 17N.</li> <li><strong>Devon_extracted_subgl_water_routes.shp</strong>: Modeled subglacial water routes derived via the application of a flow accumulation algorithm to the hydraulic head. Coordinates in EPSG: 32617 - WGS 84 / UTM zone 17N.</li> </ul> <p>------------------------------------------</p> <p><strong>SpecularityJustification.zip</strong></p> <p>Jupyter notebook and example datafile to show the justification for the chosen specularity threshold of 0.4 for declaring a detection of possible subglacial water.</p> <p>------------------------------------------</p> <p> </p> <p><strong>Acknowledgments</strong></p> <p>The aerogeophysical survey and subsequent standard data processing were funded by the Weston Family Foundation. We also thank the G. Unger Vetlesen Foundation and the UTIG Postdoctoral Fellowship program who provided further funding for data analysis. M.L.S. was partially supported by NASA NNX16AJ64G and NASA 80NSSC20K1134. We thank PCSP and Kenn Borek Air Ltd. for logistical support, and the Nunavut Research Institute and the peoples of Grise Fjord and Resolute Bay for permission to conduct airborne surveys over Devon Ice Cap. Finally, we thank Scott Kempf for assistance with data processing, and Sam Christian and Miguel Liu-Schiaffini for help with radar reflection picking.</p> <p><strong>References</strong></p> <p>Harrison, J. C., Lynds, T., Ford, A., & Rainbird, R. H. (2016). Geology, simplified tectonic assemblage map of the Canadian Arctic Islands, Northwest Territories - Nunavut. <em>Geological Survey of Canada, Canadian Geoscience</em>, <em>Map 80</em>. https://doi.org/10.4095/297416</p> <p>Mayr, U. (1980). Stratigraphy and correlation of lower Paleozoic formations, subsurface of Bathurst Island and adjacent smaller islands, Canadian Arctic Archipelago. <em>Geological Survey of Canada, Bulletin</em>, <em>306</em>. https://doi.org/10.4095/102157</p> <p>Rutishauser, A., Blankenship, D. D., Sharp, M., Skidmore, M. L., Greenbaum, J. S., Grima, C., Schroeder, D. M., Dowdeswell, J. A., & Young, D. A. (2018). Discovery of a hypersaline subglacial lake complex beneath Devon Ice Cap, Canadian Arctic. <em>Science Advances</em>, <em>4</em>(4), eaar4353. https://doi.org/10.1126/sciadv.aar4353</p> <p>Thorsteinsson, R., & Mayr, U. (1987). <em>The sedimentary rocks of Devon island, canadian arctic archipelago</em>. https://doi.org/10.4095/122451</p>
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<p>Scripts and data for Projections of Greenland periphery glaciers and ice caps’s change by using Open Global Glacier Model.</p>
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