From 1 - 10 / 13
  • Polarimetric phase-sensitive radar measurements were collected at the Western Antarctic Ice Sheet (WAIS) Divide on the 25th and 26th December 2019. The measurements were conducted at 10 sites along a 6 km-long transect ~5-10 km northeast of the location of the WAIS Divide Deep Ice Core. At each site, a suite of four quadrature (quad-) polarimetric measurements were collected using an autonomous phase-sensitive radio echo sounder (ApRES) in a single-input single-output (SISO) configuration. The study is part of the Thwaites Interdisciplinary Margin Evolution (TIME) project of the International Thwaites Glacier Collaboration (ITGC), and is a collaboration between the United States National Science Foundation (NSF) and the United Kingdom Natural Environment Research Council (NERC). It was funded by UK Natural Environment Research Council (NERC) research grant NE/S006788/1 and USA National Science Foundation (NSF) research grant 1739027.

  • The dataset encompasses the processed point clouds (.pts format), a panoramic tour, and a video flythrough of registered point clouds capturing a 273 m long reach of the englacial portal channel in the glacier, Austre Broggerbreen, Svalbard, in March 2017. Point clouds were derived from 27 Terrestrial Laser Scanning (TLS) surveys, to characterise the morphology of the channel in three-dimensions and enable extraction of features reflective of hydrological flow conditions. The panoramic tour shows a greyscale image of the scan reflectivity values at each survey location, whereby the lighter the pixel colour, the greater the intensity of the laser beam return. This panoramic tour enables the viewer to self-navigate through the channel to see the morphological features within it. The video flythrough of the point cloud provides a visualisation of the point cloud data, travelling from the portal exit to the extent of the scanned reach. The point cloud has been coloured to reflect differences in height above the portal exit. Funding source Knowledge Economy Skills Scholarship (KESS II) under Project AU10003, a pan-Wales higher-level skills initiative led by Bangor University of behalf of the HE sector in Wales. It is part funded by the Welsh Government''s European Social Fund (ESF) convergence programme for West Wales and the Valleys. Funding was awarded to TDLI-F and JEK, with support from Deri Jones & Associates Ltd. Additional support is acknowledged from Aberystwyth University (Department of Geography and Earth Sciences).

  • The dataset encompasses the processed point clouds (.pts format), a panoramic tour, and a video flythrough of registered point clouds capturing a 122 m long reach of an englacial cut-and-closure channel in the glacier, Austre Broggerbreen, Svalbard, in March 2016. Point clouds were derived from 28 Terrestrial Laser Scanning (TLS) surveys, to characterise the morphology of the channel in three-dimensions and enable extraction of features reflective of hydrological flow conditions. The panoramic tour shows a greyscale image of the scan reflectivity values at each survey location, whereby the lighter the pixel colour, the greater the intensity of the laser beam return. This panoramic tour enables the viewer to self-navigate through the channel to see the morphological features within it. The video flythrough of the point cloud provides a visualisation of the point cloud data, travelling from the glacier surface, down the moulin and along the extent of the scanned reach. The point cloud has been coloured to reflect differences in height. Funding source Knowledge Economy Skills Scholarship (KESS II) under Project AU10003, a pan-Wales higher-level skills initiative led by Bangor University of behalf of the HE sector in Wales. It is part funded by the Welsh Government''s European Social Fund (ESF) convergence programme for West Wales and the Valleys. Funding was awarded to TDLI-F and JEK, with support from Deri Jones & Associates Ltd. Additional support is acknowledged from Aberystwyth University (Department of Geography and Earth Sciences).

  • This dataset provides the data produced as part of the work published in: Leeson, A. A., Foster, E., Rice, A., Gourmelen, N. and van Wessem, J. M.. 2019. ''Evolution of supraglacial lakes on the Larsen B ice shelf in the decades before it collapsed'' Geophysical Research Letters. It includes 1) shapefiles of supraglacial lakes mapped in both optical (Landsat) and SAR (ERS) satellite imagery, 2) rasters of lake depth, derived from Landsat TM and ETM+ images acquired in 1988 and 2000 and 3) shapefiles of the study area considered in the paper. Funding was provided by ERPSRC grant EP/R01860X/1.

  • This dataset provides supraglacial lake extents as published in the paper by Arthur et al. (2020) entitled "Distribution and seasonal evolution of supraglacial lakes on Shackleton Ice Shelf, East Antarctica". Please cite this paper if using this data. This dataset consists of (1) shapefiles of supraglacial lake extents on Shackleton Ice Shelf, in Queen Mary Land, East Antarctica (65 degS; 100 degE) derived from optical satellite imagery (Landsat-1, -4, -5, -7, -8, Sentinel 2) acquired between 1974 and 2020 and (2) rasters of supraglacial lake depths derived from optical satellite imagery (Landsat-1, -4, -5, -7, -8, Sentinel 2) acquired between 2000 and 2020. The datasets presented here were used to analyse the spatial distribution of lakes, lake densities, elevation, slope and ice surface velocity distributions, proximity to exposed bedrock, blue ice and the grounding line, and time series of lake area, depth and volume. Funding was provided by NERC DTP grant NE/L002590/1 and NERC grant NE/R000824/1.

  • Uncertainties in future sea level projections are dominated by our limited understanding of the dynamical processes that control instabilities of marine ice sheets. A valuable case to examine these processes is the last deglaciation of the British-Irish Ice Sheet. The Minch Ice Stream, which drained a large proportion of ice from the northwest sector of the British-Irish Ice Sheet during the last deglaciation, is well constrained, with abundant empirical data which could be used to inform, validate and analyse numerical ice sheet simulations. We use BISICLES, a higher-order ice sheet model, to examine the dynamical processes that controlled the retreat of the Minch Ice Stream. We simulate retreat from the shelf edge under constant "warm" surface mass balance and subshelf melt, to isolate the role of internal ice dynamics from external forcings. The model simulates a slowdown of retreat as the ice stream becomes laterally confined at a "pinning-point" between mainland Scotland and the Isle of Lewis. At this stage, the presence of ice shelves became a major control on deglaciation, providing buttressing to upstream ice. Subsequently, the presence of a reverse slope inside the Minch Strait produces an acceleration in retreat, leading to a "collapsed" state, even when the climate returns to the initial "cold" conditions. Our simulations demonstrate the importance of the Marine Ice Sheet Instability and ice shelf buttressing during the deglaciation of parts of the British-Irish Ice Sheet. Thus, geological data could be used to constrain these processes in ice sheet models used for projecting the future of our contemporary ice sheets. Funding was provided by the Natural Environment Research Council (NERC) SPHERES Doctoral Training Partnership (NE/L002574/1) with CASE support from the British Geological Survey.

  • This dataset provides supraglacial lake extents and depths as included in the paper by Arthur et al. (in review, Nature Comms.) entitled " Large interannual variability in supraglacial lakes around East Antarctica". Please cite this paper if using this data. This dataset consists of (1) shapefiles of supraglacial lake extents around the East Antarctic Ice Sheet derived from Landsat-8 imagery acquired between January 2014 and 2020 and (2) rasters of supraglacial lake depths derived from Landast-8 imagery acquired over the same period. The datasets presented here were used to analyse the spatial distribution and interannual variability in lake distributions and volume. Funding was provided by NERC DTP grant NE/L002590/1 and NERC grant NE/R000824/1.

  • 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. 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

  • Datasets from the Resolving subglacial properties, hydrological networks and dynamic evolution of ice flow on the Greenland Ice Sheet (RESPONDER) project as published in the paper by Chudley et al. entitled "Controls on water storage and drainage in crevasses on the Greenland Ice Sheet". This dataset consists of remotely sensed observations of water-filled crevasses across a marine-terminating sector of the west Greenland Ice Sheet between 2017 and 2019.The dataset presented here includes all data necessary to replicate the findings presented in the main paper, including UAV photogrammetry-derived raster data (producing a series of orthophotos and digital elevation models) and observations from satellite-derived data (Sentinel-2, ArcticDEM, and MEaSUREs Greenland velocity data) of crevasse presence, water presence, and estimates of surface stress. This research was funded by the European Research Council as part of the RESPONDER project under the European Union''s Horizon 2020 research and innovation program (Grant 683043). Tom Chudley was supported by a Natural Environment Research Council Doctoral Training Partnership Studentship (Grant NE/L002507/1).

  • We can learn about the flow of ice in Antarctica by evaluating the key parameters that control the flow speed. These parameters include the basal drag coefficient and the ice viscosity. They can be estimated by adjusting their values so that model velocities at the upper surface agree with satellite observations. This dataset was produced using inverse methods to obtain the parameter values. In this approach a cost function that describes the mismatch between model and satellite data is minimised iteratively by making small adjustments to the parameters at each iteration to improve the fit. The result is better information about the flow field in the Antarctic ice sheet. Once the flow field is available it can be used as an initial state from which begin temporally evolving simulations using the model. A number of different examples are included to show how varying different parameters alters the temporally evolving simulations. The contributing datasets used to constrain the model are listed by Arthern et al (2015) and Arthern and Williams (2017). Multidecadal model simulations span up to 100 years of simulation time. This work was funded by NERC standard grant NE/L005212/1.