Keyword

glacier

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  • This dataset has been produced as part of the Theme 5 (Cryosphere and Polar Oceans) in the National Centre for Earth Observation which aims to use new EO data to quantify changes in the mass balance of the cryosphere and to develop new models to represent the relevant processes in coupled climate prediction models. This dataset holds timeseries of Greenland glacier calving front fluctuations as maps and backscatter intensity images for the period March-July 2011. The dataset consists of 38 SAR backscatter images acquired every 3 days between the 12th March and 1st July 2011 during the ERS-2 3-day campaign. The backscatter data were transformed to map coordinates using the GLAS/ICESat 1 km Laser Altimetry Digital Elevation Model of Greenland which is provided at Polar Stereographic grids (DiMarzio, J., Brenner, A., Schutz, R., Schuman, A. & Zwally, H.J. (2007): GLAS/ICESat 1 km laser altimetri digital elevation model of Greenland. Boulder, Colorado USA: National Snow and Ice Data Centre. Digital media).

  • This dataset has been produced as part of the Theme 5 (Cryosphere and Polar Oceans) in the National Centre for Earth Observation which aims to use new EO data to quantify changes in the mass balance of the cryosphere and to develop new models to represent the relevant processes in coupled climate prediction models. This dataset holds timeseries of Greenland glacier velocity fluctuations as maps for the period March-July 2011. The 37 velocity maps were derived from SAR data acquired during the 2011 ERS-2 3-day campaign. The velocity maps are 3-day velocity averages and are given in meters per year (m/y) (magnitude values). The name of the velocity files provides the start and end date of each 3-day period. The velocity fields were transformed to map coordinates using the GLAS/ICESat 1 km Laser Altimetry Digital Elevation Model of Greenland which is provided at Polar Stereographic grids (DiMarzio, J., Brenner, A., Schutz, R., Schuman, A. & Zwally, H.J. (2007)): GLAS/ICESat 1 km laser altimetri digital elevation model of Greenland. Boulder, Colorado USA: National Snow and Ice Data Centre. Digital media).

  • Meteorological variables (wind speed, air temperature and wind direction) were collected using two wind towers. Photogrammetric data were collected using a pole-mounted digital camera and DJI Phantom 3 UAV. LiDAR data collected via terrestrial and airborne laser scanning. Fieldwork carried out at Hintereisferner glacier, in the Oetztal Alps region, Tyrol, Austria, from 1-15 August 2018 by Joshua Chambers, Thomas Smith and Mark Smith. Terrestrial laser scan (TLS) data collected by Rudolf Sailer. Airborne laser scan (ALS) data originally from Open Data Austria, see Sailer et al. (2012). One wind tower recorded for the entire study duration, the second was moved to different plots every ~4 days. Photogrammetric data were collected on 8, 10, 11, 12 and 13 August. TLS scans were split into upper- and lower-glacier, and completed on 3, 7, 12 and 16 August. Data were used to examine the relations between glacier aerodynamic roughness and sampling resolution, and to develop a correction factor for roughness derived from coarser resolution data. Fieldwork was funded by an INTERACT Transnational Access grant awarded to Mark Smith under the European Union H2020 Grant Agreement No. 730938. Joshua Chambers is supported by a NERC PhD studentship (NE/L002574/1). Ivana Stiperski was funded by Austrian Science Fund (FWF) grant T781-N32. ***** PLEASE BE ADVISED TO USE VERSION 2.0 DATA ***** The VERSION 2.0 data set (see ''Related Data Set Metadata'' link below) provides corrected glacier aerodynamic roughness calculated using the new model outlined in Chambers et al.

  • This dataset contains the annual ice front position shapefiles of the Thwaites Glacier Ice Tongue between 2000 and 2018 as shown in the Miles et al. (2020) paper. Each shapefile was mapped manually from MODIS imagery in the March of each year. The dataset details the retreat of the ice tongue and transition from a tabular calving regime to a disintegration type calving. This work was funded by NERC grant NE/R000824/1.

  • This dataset comprises four distinct shapefiles, which were used to demonstrate how glacier ELA is affected by volcanic thermal conditions, in the Andes, South America. With the exception of ''139_Remapped_Glaciers.shp'', the shapefiles are obtained from existing, open access data from the Randolph Glacier Inventory (RGI 6.0) and the Global Volcanism Program 2013, but with the addition of information, in the shapefile''s attribute table, relevant to the study of the interaction between glaciers and volcanoes, as obtained via the GIS analysis of these datasets. The ''600_RGI_Glaciers.shp'' shapefile comprises 600 (land-terminating, no debris-covered, > 0.1 km2) glacier polygons, which are located within 15 km from a Holocene (erupted in the past 10,000 years) volcano in South America. Crucially, the equilibrium line altitude (i.e., the elevation on the glacier where the surface mass balance, measured over 1 yr, is zero) and distance to the nearest volcano for each glacier is reported in the attribute table. The ''37_GVP_Volacanoes.shp'' shapefile contains points for 37 South America Holocene volcanoes which have glaciers both within 1 km (volcanic-glaciers), and between 1 and 15 km (proximal glaciers). For each volcano, the difference in ELA between volcanic (<1km from volcano) and proximal (1-15 km) glaciers is reported in the attribute table, along with mean temperature and precipitation. The ''139_Remapped_Glaciers.shp'' shapefile provides detailed and updated (relative to RGI) mapping of glaciers (as polygons) that are located within 15 km from 13 South America Holocene volcanoes for which thermal anomaly is known. The ELA of these glaciers is calculated and reported in the attribute table. The ''13_AVTOD_Volacanoes.shp'' shapefile comprises the points for 13 Holocene volcanoes that have glaciers both within 1 km (volcanic-glaciers), and between 1 and 15 km (proximal glaciers) from their centre, as well as recorded thermal anomaly. The glacier ELA and volcano thermal data provided in the attribute table allows us to establish the quantitative relationship between volcanoes and glaciers. A detailed description of the study based on this dataset is provided in Howcutt et al. (2023). This project and data were supported by the NERC Global Partnerships Seedcorn fund (NE/W003724/1).

  • This dataset represents model output from 4 simulations of Store Glacier produced using the Elmer/Ice glacier model equipped with novel 3D calving subroutines. As described in the paper associated with this dataset (Todd et al., JGR, 2018), the model is initialised with velocity observations and then forced with present day environmental forcing. The simulation covers a 5 year time period with no fixed dates. Funding was provided by the NERC grant NE/K500884/1.

  • Meteorological variables (wind speed, air temperature and wind direction) were collected using two wind towers. Photogrammetric data were collected using a pole-mounted digital camera and DJI Phantom 3 UAV. LiDAR data collected via terrestrial and airborne laser scanning. Fieldwork carried out at Hintereisferner glacier, in the Oetztal Alps region, Tyrol, Austria, from 1-15 August 2018 by Joshua Chambers, Thomas Smith and Mark Smith. Terrestrial laser scan (TLS) data collected by Rudolf Sailer. Airborne laser scan (ALS) data originally from Open Data Austria, see Sailer et al. (2012). One wind tower recorded for the entire study duration, the second was moved to different plots every ~4 days. Photogrammetric data were collected on 8, 10, 11, 12 and 13 August. TLS scans were split into upper- and lower-glacier, and completed on 3, 7, 12 and 16 August. Data were used to examine the relations between glacier aerodynamic roughness and sampling resolution, and to develop a correction factor for roughness derived from coarser resolution data. Fieldwork was funded by an INTERACT Transnational Access grant awarded to Mark Smith under the European Union H2020 Grant Agreement No. 730938. Joshua Chambers is supported by a NERC PhD studentship (NE/L002574/1). Ivana Stiperski was funded by Austrian Science Fund (FWF) grant T781-N32.

  • This dataset consists of a bed DEM and four velocity maps of Kongsvegen, a surge-type glacier in Svalbard. The bed DEM was generated from ground-penetrating radar surveys in spring 2016 and 2018, and the velocity maps span the period Dec 2017 to Feb 2019. The velocity maps show the initial speed-up of the glacier as it transitions from quiescence to surge. Data acquisition was funded by NERC Urgency Grant NE/R018243/1 REBUS (Resolving Enthalpy Budget to Understand Surges).

  • Meteorological variables (wind speed, air temperature and wind direction) were collected using two wind towers. Photogrammetric data were collected using a pole-mounted digital camera and DJI Phantom 3 UAV. Sites were Storglaciaren and Sydostra Kaskasatjakkaglaciaren, both in the Tarfala Valley in Arctic Sweden. Fieldwork was carried out between the 8th and 20th of July 2017, by Mark Smith, Duncan Quincey and Jonathan Carrivick. Wind towers recorded data continuously for the study period, and photogrammetric data were collected from each site on alternate days. Data from both sources were used to estimate glacier aerodynamic roughness (z0) for a method comparison. Funding was provided by NERC DTP grant NE/L002574/1