From 1 - 10 / 24
  • 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.

  • This archive is a suite of ground penetrating radar (GPR) data acquired by Project MIDAS during field campaigns on Larsen C, in 2014 and 2015. All data were acquired with a Sensors&Software pulsEKKO PRO GPR system, fitted with antennas of 200 MHz centre-frequency. The system was towed behind a snowmobile, with distances recorded with GPS. These data are part of the NERC-funded MIDAS (''Impact of surface melt and ponding on ice shelf dynamics and stability'') research project, with grant references NE/L006707/1 and NE/L005409/1. Other MIDAS data are available.

  • This data set contains the ULF wave model output data required to produce the figures in the article: A. W. Degeling, I. J. Rae, C. E. J. Watt, Q. Q. Shi, R. Rankin and Q. G. Zong, "Control of ULF Wave Accessibility to the Inner Magnetosphere by the Convection of Plasma Density", J. Geophys. Res. (accepted Dec. 2017) doi:10.1002/2017JA024874 The dataset has a Matlab binary file format. It consists of a structure array "d" (with 325 elements). These elements correspond to the 2D parameter scan in driver frequency and elapsed time during plume development performed for this study. The elapsed time parameter has 25 elements, ranging 0 to 24 hours (i.e. 1 hour spacing), and the driver frequency parameter has 13 elements ranging from 1 to 7 mHz (with 0.5 mHz spacing). e.g. use "d = reshape(d,25,13);" to reshape the structure array into 2D with columns for the frequency scan and rows for the elapsed time scan. The Matlab function "make_PDP_figs.m" is used to read the data, perform the necessary post-processing operations and output the article figures. To produce all six figures, simply run the file without any input arguments.

  • This data set contains aeromagnetic data collected opportunistically during an airborne radar survey of the Brunt Ice Shelf as part of the NERC/BAS Life Time of Halley project. The survey was flown draped with an average height above the ice surface of 420m, and includes 4716 km of new data. The aircraft used was the BAS aerogeophysically equipped twin otter VP-FBL. Data are available include all data streams from raw to fully processed, following the ADMAP 2 naming convention, and are provided in both Geosoft database (.gdb) and ASCII file formats (.xyz). Base station data is also provided.

  • This dataset documents the trends and variability in the latitude and strength of the belt of lower-atmosphere westerly winds over the Southern Ocean, referred to as the ''westerly jet''. Time series of annual mean and seasonal diagnostics are available for the period 1979-present, specifically time series of seasonal and annual mean jet latitude and strength. The diagnostics are derived from the European Centre for Medium Range Weather Forecasts (ECMWF) ERA-Interim reanalysis (for more information see www.ecmwf.int and Dee et al. (2011)), which is an observationally-constrained reconstruction of atmospheric conditions. The broad characterisation of the westerly winds into these simple diagnostics has been found to be useful for understanding long-term climate change due to contrasting drivers of change and impacts on other aspects of the climate system. This is an index of winds around the full circumference of all longitudes at Southern Hemisphere middle latitudes. The exact latitude depends on the position of the jet at any given time, but on average the jet (the core of the westerlies) is located at approximately 52 deg S.

  • Meteorological data collected on Larsen Ice Shelf including pressure, temperature, wind speed and direction.

  • These two files (.csv) provide independent methods of quantifying subglacial roughness in Greenland, both calculated from radio-echo sounding (or ice penetrating radar) data collected by the Operation Ice Bridge programme using CReSIS instrumentation. They are an output of the Basal Properties of Greenland (BPOG) project (http://bpog.blogs.ilrt.org/), with funding from NERC grant NE/M000869/1. Roughness here, and in the wider literature, is defined as the variation in bed elevation (in the vertical) at the ice-bed interface, over a given length-scale. These two metrics calculate/quantify this variation in different ways: one shows topographic-scale roughness, calculated from the variation in along-track topography (bed elevation measurements derived from the radar pulse); and the other shows scattering-derived roughness, calculated from quantifying characteristics of each bed-echo (the return from the radar pulse at the ice-bed interface).

  • Seventy-nine Antarctic ice core snow accumulation records were gathered as part of a community led project coordinated by the PAGES Antarctica 2k working group. Individual ice core records (kg m2 yr-1) were normalised relative to a reference period (1960-1990). The normalised records were separated into seven geographical regions and averaged together to form the regional composites. The seven geographical regions are: East Antarctica; Wilkes Land Coast; Weddell Sea Coast; Antarctic Peninsula; West Antarctic Ice Sheet; Victoria Land; and Dronning Maud Land. Full data description and methods can be found in Thomas et al., 2017. This record also includes the original data, from which the composite records were produced. This dataset represents an updated version of another published dataset. The update was necessary due to erroneous data contained in the files. Please use this corrected dataset in preference to the other one.

  • High-resolution simulation of summer climate over West Antarctica using the Polar-optimised version of the Weather Research and Forecasting (WRF) model conducted at British Antarctic Survey, Cambridge, UK. Runs are conducted for summer (January-centred) 1980-2015, i.e. from December 1979 to February 2015, for December, January and February (DJF). Experiments were carried out for the NERC West Antarctic Grant (NE/K00445X/1) during 2014-2017. The project is aimed at understanding the variability and climatology over the West Antarctic ice sheet and ice shelves as well as to project the future change over the twenty-first century. The model outer domain encompasses the West Antarctic ice sheet and a large part of the surrounding ocean at 45 km horizontal grid spacing, and the nested (one-way) inner domain covers the Amundsen Sea Embayment at 15 km grid spacing. The model uses vertical eta coordinates with both domains have a model top of 50 hPa, and 30 vertical levels.

  • Monthly averaged total ozone values measured at Halley station, Antarctica. All measurements are in Dobson Units. These monthly averages are a flat average of any daily average values that exist for each given month; the daily averages are a flat average of the measurements obtained during a particular 24-hour period (UTC). The number of observations may vary from day to day. The Dobson ozone observing season at Halley begins at the end of August and ends in mid April; however, very early and late season observations are made with the Sun at low elevation, and are less accurate than those made during the main observing period of September 6 to April 6. The values for 1956/57 (MacDowall, J., 1962) and 1957-1973 (Farman, J. C. and Hamilton, R. A., 1975) have been approximately corrected from the original using the WMO recommended guidance (Komhyr, W. D., Mateer C. L. and Hudson, R. D., 1993) for the Bass-Paur ozone absorption coefficients. Ozone values from 1973 onwards have been calculated using the Bass-Paur coefficients. The approximation of a US standard atmosphere, which will differ from the Antarctic atmosphere, has been used and the assumed temperature used for the absorption coefficients may be inaccurate.