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10 results for “Debris-covered glaciers”
Automatic weather station data from the debris-covered Kennicott Glacier, Alaska (May-Aug 2019)
<p>Data from an automatic weather station installed on the debris-covered<strong> Kennicott Glacier</strong> in the Wrangell St. Elias National Park, Alaska, USA, spanning most of the 2019 ablation season (28 May - 22 August 2019).</p> <p>Brief description of the uploaded datasets:</p> <ul> <li><em><strong>KEN_2019_60.csv</strong></em>: Hourly aggregated measurements of air temperature, relative humidity, wind speed and direction, atmospheric pressure, incoming and reflected shortwave radiation, incoming and outgoing longwave radiation and precipitation</li> <li><em><strong>KEN_2019_AWS_Metadata.pdf</strong></em>: Metedata file describing the station location, sensor setup and measurements</li> <li><em><strong>KEN_2019_debris.csv</strong></em>: Debris properties assumed to be potentially applicable for this site (not measured but taken from literature)</li> <li><strong><em>KEN_2019_VAL_debristemperature.csv</em></strong>: Hourly time series of temperature measurements at known depths within the debris cover close to the station location</li> <li><strong><em>KEN_2019_VAL_subdebrismelt.csv</em></strong>: Monthly stake measurements of surface height change (sub-debris ice melt) close to the station location spanning the ablation season</li> </ul> <p>We recorded additional meteorological data at the weather station (e.g. vertical profiles of wind speed/direction, relative humidity and temperature; 3D ultrasonic anemometer) as well as subdebris melt, dGPS-surface change and temperature profiles at additional transects for the same period. Please contact the authors in case of interest in any additional data.</p>
Debris temperature and ablation measurements from the Lirung Debris-Covered Glacier (2013-2014), Nepal
<p>These data are from the debris-covered portion of Lirung Glacier, Langtang Valley located in the Langtang National Park of the Nepal Himalaya that were collected during three field expeditions between September 2013 and April 2014. The data includes debris temperature measurements at two different sites of the glacier in three different seasons of the year 2013 (Monsoon and Winter) and 2014 (Pre-Monsoon). Debris temperature measurements from thermistors located at the surface (Black-colored dirty ice) to up to 40 cm from the surface. Dataset also included the ablation measurement in three seasons at different debris-thicknesses. Below is a brief description of the two different datasets:</p> <p>- Ablation_stake_data_Lirung_glacier_CHAND.csv: ablation stake measurement in the Monsoon and Winter season of 2013 and pre-monsoon season of 2014 from Chand and Kayastha (2018) and Chand et al. (2015).</p> <p>- Debris_temperature_profile_Lirung_Glacier_CHAND.csv: debris temperature measurements (Degree Celcius) where the depth is reported in cm from Chand and Kayastha (2018).</p> <p>----- Citing datasets -----</p> <p>Chand, M. B., and Kayastha, R. B. (2018). Study of thermal properties of supraglacial debris and degree-day factors on Lirung Glacier, Nepal. Sciences in Cold and Arid Regions, 10(5): 357-368 doi:10.3724/SP.J.1226.2018.00357</p> <p>Chand, M. B., Kayastha, R. B., Parajuli, A., and Mool, P. K. (2015). Seasonal variation of ice melting on varying layers of the debris of Lirung Glacier, Langtang Valley, Nepal, Proc. IAHS, 368, 21–26, https://doi.org/10.5194/piahs-368-21-2015</p> <p> </p>
On-Glacier Air Temperatures for Miage Debris-Covered Glacier, 2014
<p>Miage_Glacier_Air_Temperature_Data_2014.xlsx<br> %------------------------------------------%<br> Data Generated on 13th May 2022</p> <p>Data Curator: Dr. Thomas Shaw (Swiss Federal Institute, WSL, Switzerland)</p> <p>Data Provider(s): Dr. Thomas Shaw (Swiss Federal Institute, WSL, Switzerland) thomas.shaw@wsl.ch<br> Prof. Benjamin Brock (Northumbria University, Newcastle, UK) benjamin.brock@northumbria.ac.uk</p> <p>Data period: 1st July - 27th September, 2014</p> <p><br> Details:<br> Hourly data are generated for air temperature stations ('T-Loggers') distributed across the debris-covered Miage Glacier, Italy (45.8129°N, 6.8458°E).<br> Air temperatures (°C) were measured using Tinytag thermistors (accuracy +/- 0.2-0.35°C) housed in naturally ventilated Campbell MET20 / MET21 radiation shields.</p> <p>Off-Glacier air temperatures (measured as above) are provided for comparison with on-glacier air temperatures. </p> <p>For additional details can be found in the article: <br> Shaw, T. E., Brock, B. W., Fyffe, C. L., Pellicciotti, F., Rutter, N., & Diotri, F. (2016).<br> Air temperature distribution and energy-balance modelling of a debris-covered glacier. Journal of Glaciology, 62(231), 1–14. <br> https://doi.org/10.1017//jog.2016.31</p> <p>Please cite the above article for any usage of the dataset.</p> <p>Data are shared and compiled as part of a wider project to estimate on-glacier air temperatures from off-glacier data<br> For more details on the 'TEMPEST' project, visit: https://tempestglacier.com/</p>
Datasets associated with "Quantifying debris thickness of debris-covered glaciers in the Everest region of Nepal through inversion of a sub-debris melt model"
<p>Datasets that accompany "Quantifying debris thickness of debris-covered glaciers in the Everest region of Nepal through inversion of a sub-debris melt model". These datasets include the debris thickness estimates derived including and excluding ponds (denoted as wponds and noponds, respectively), flux divergences, the shapefile of the 600 m boxes, the master 10 m DEM, the median x and y velocities, and the change in elevation for each pair of DEMs used in the study for Ngozumpa, Khumbu, and Imja-Lhotse Shar Glaciers. Debris thickness is in units of meters. Flux divergence is in units of meters per year. A negative flux divergence means the box is gaining mass and is called the emergence velocity; while positive flux divergence means the box is losing mass and is called the submergence velocity.</p>
Data used in meta-analysis of debris-covered glacier melt
<p>The data used in the study Accuracy of Empirical Models of Debris-Covered Glaciers, A Winter-Billington, RD Moore and R Dadic, in prep. for submission to the Journal of Glaciology.</p>
Data for 'Controls on Ice Cliff Distribution and Characteristics on Debris-Covered Glaciers'
<p>This dataset contains ice cliff, pond, debris, glacier and crevasse zone outlines (as shapefiles) derived for the study 'Controls on Ice Cliff Distribution and Characteristics on Debris-Covered Glaciers'.</p> <p>They were outlined from 14 Pléiades multi-spectral images (see Methods and tables in corresponding manuscript and SI) acquired at the dates indicated in the corresponding folder names.</p> <p>The majority of the Pléiades stereo-pairs used were provided by Etienne Berthier via the Pléiades Glacier Observatory (PGO) initiative of the French Space Agency (CNES). The remaining images were acquired through the CNES ISIS Programme. </p>
Data products associated with "Multi-year glaciological and meteorological observations on debris-covered Kennicott Glacier, Alaska, 2016 - 2023"
<p>Data for Petersen, E., R. Hock, M. Loso, W. Guo, C. Markovsky, R. Yang, H. Han, D. Shangguan, and S. Kang, “Multi-year glaciological and meteorological observations on debris-covered Kennicott Glacier, Alaska, 2016-2023,” Geoscience Data Journal, Submitted January 2025.</p>
Data Products associated with "Stream hydrology controls on ice cliff evolution and survival on debris-covered glaciers"
<p>Data products from the study "Stream hydrology controls on ice cliff evolution and survival on debris-covered glaciers," by Petersen et al, submitted September 2023 to Earth Surface Dynamics.</p>
Comparison of turbulent structures and energy fluxes over exposed and debris-covered glacier ice: Datasets
<p>This repository contains data of near surface data of turbulence conditions measured simultaneously over exposed ice and a 0.08 m thick supraglacial debris cover on Suldenferner, a small glacier in the Italian Alps. It is related to the following publication:</p> <p>Nicholson, L. and Stiperski, I. (2020) Comparison of turbulent structures and energy fluxes over exposed and debris-covered glacier ice. Journal of Glaciology.</p> <p><strong>The repository contains the following files</strong></p> <p>(1) Overview figure of the locations of the installed weather stations collecting data used in the analysis, and images of the eddy covariance installations </p> <ul> <li><strong>Filename:</strong> overview.tif</li> </ul> <p>(2) 30 minute average meteorological data from the automatic weather station (AWS) on the debris-covered glacier surface with ca. 0.09 m thick debris cover.</p> <ul> <li><strong>Filename:</strong> aws.csv</li> <li><strong>Location:</strong> 46.496 °N / 10.569 °E / ~2625 m</li> <li><strong>Time period:</strong> 11.08.2015 13:30 – 14.08.2015 21:00</li> <li><strong>Variables - unit:</strong> listed in variables&units.pdf</li> </ul> <p>(3) 5 minute data from the eddy covariance station on the clean ice glacier surface.</p> <ul> <li><strong>Filename:</strong> ecci.csv</li> <li><strong>Location:</strong> 46.498°N /10.560°E / ~ 2780 m</li> <li><strong>Time period:</strong> 11.08.2015 13:42 – 14.08.2015 20:57</li> <li><strong>Variables - unit:</strong> listed in variables&units.pdf</li> </ul> <p>(4) 5 minute data from the eddy covariance station on the debris-covered glacier surface with ca. 0.08 m thick debris cover.</p> <ul> <li><strong>Variables - unit:</strong> listed in variables&units.pdf</li> <li><strong>Location:</strong> 46.495 °N / 10.572 °E / ~ 2600 m</li> <li><strong>Time period:</strong> 11.08.2015 13:42 – 14.08.2015 20:57</li> <li><strong>Variables - unit:</strong> listed in variables&units.pdf</li> </ul> <p>(5) A list of the variables and units used in the datafiles.</p> <ul> <li><strong>Filename:</strong> variables&units.pdf</li> </ul> <p> </p> <p>The<strong> instrumentation locations</strong> can be seen in the overview figure. </p> <p>The <strong>automatic weather station </strong>consists of a Kipp and Zonen CNR1 4-way radiation sensor, a shielded Vaisala HMP45c temperature and relative humidity sensor, and a Young 05103 anemometer. 30-minute averages and standard deviations of variables were recorded by a Campbell C3000 datalogger. Temperature and relative humidity are also sampled at 30-minute intervals allowing the vapor pressure to be calculated at this interval. </p> <p>The <strong>eddy covariance</strong><strong> instrumentation</strong> was identical at both stations (ecci and ecdc) and consisted of two segmented masts drilled into the ice with sensors mounted at a height of 1.6 m on a cross arm spanning the vertical masts. A CSAT 3D sonic anemometer and KH20 hygrometer sampling data at a frequency of 20Hz were mounted parallel to the surface and facing obliquely across-glacier at a bearing of 255° so as to capture both up and downglacier winds. A shielded Vaisala HMP45 was installed on the EC mast to record 1-minute averages of air temperature, relative humidity and vapor pressure. Data were recorded using Campbell Scientific CR1000 data loggers with compact flash card storage modules. Power was provided by 60Ah deep cycle batteries connected to 20 W solar panels. </p> <p>The <strong>data provided</strong> here is gap-filled data. The eddy covariance station over debris-covered ice was installed on 10 August 2015, and the one over clean ice was installed on 11 August 2015. At ecdc, a faulty solar panel regulator resulted in this station losing power on 15 August. At ecci two instrument failures occurred; the Vaisala instrument on the afternoon of 12 August and the KH20 at the end of 14 August. Air pressure was not recorded at any of the three stations. Missing data was filled on the basis of multiple regression transformation of data measured at nearby stations, as described fully in the publication. Pressure data were filled in with data from the nearby Madritsch weather station, operated by the Autonomous Province of Bozen. Missing temperature and vapor pressure data spanning 12-14 August at the eddy station over clean ice was filled in with data from the glacier automatic weather station.</p> <p><strong>Thanks</strong> are due to the Gutgsell family at the Hintergrathütte for continued support of our research activities and (in alphabetical order) Michael Adamer, Federico Covi, Costanza del Gobbo, Lukas Hammerer, Irmgard Juen, Marius Massimo, Kristin Richter, Reto Stauffer and Anna Wirbel for assistance in the field. Permission to work on Suldenferner is granted by Stelvio National Park. This research was funded by the Austrian Science Fund Grant numbers V309, P28521 and T781-N32.</p> <p> </p>
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.) located in the Nepal Himalaya that were collected during three field expeditions between September 2013 and November 2014. The data includes debris thickness measurements derived primarily by manual excavation, 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 detailed in 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. (2015).</p> <p>- Site_XX_DEM_1cm.tif: digital elevation model used to estimate surface roughness from Rounce et al. (2015).</p> <p> </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, <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, <em>Cryosphere</em>, 9:2295-2310, doi:10.5194/tc-9-2295-2015.</p>
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