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  • 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.

  • 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.

  • The datasets are temperature time series from thermistor strings installed into two boreholes drilled to a depth of ~7 m in the northern sector of Larsen C Ice Shelf, Antarctica. Supporting borehole information is presented by Ashmore and others (2017). 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. Associated (longer) borehole temperature records, OPTV logs and density records are also available, as are other MIDAS datasets.

  • The data consists of 30 minute observations recorded by an automatic weather station (iWS 18) in Cabinet Inlet on Larsen C Ice Shelf on the Antarctic Peninsula. The iWS consists of a custom-built weather station unit, assembled at the Institute of Marine and Atmospheric research Utrecht (IMAU). There are sensors for air temperature, surface air pressure, relative humidity, as well as a gps, an acoustic snow height sensor, an ARGOS communication antenna, and three Lithium batteries that fuel the unit when solar radiation is absent. The unit is complemented by a propeller-vane Young anemometer measuring wind direction and speed. Additionally, all radiation fluxes are measured with a Kipp and Zonen CNR4 radiometer. This dataset runs from November 2014 to January 2017. Funded was provided by the NERC grant NE/L005409/1. ***** PLEASE BE ADVISED TO USE VERSION 2.0 DATA ***** The VERSION 2.0 data set (see ''Related Data Set Metadata'' link below) has an additional 10 months of measurements.

  • This dataset contains bed, surface elevation and ice thickness measurements from the Recovery/Slessor/Bailey Region, East Antarctica. Radar data was collected using the 150MHz PASIN radar echo sounding system (Corr et al., 2007) deployed on a British Antarctic Survey (BAS) Twin Otter during the ICEGRAV-2013 airborne geophysics campaign (Forsberg et al., 2018). Data is identified by flight and are available in both Geosoft database (.gdb) and ASCII file formats (.xyz).

  • 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.

  • 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.

  • This data are derived from single point seismic data collected across the Filchner-Ronne Ice Shelf. The seismic data were collected over the course of three seasons by a number of field parties, consisting of two main surveys between the 15/16 and 16/17 austral summers and several smaller surveys, as part of a joint initiative between the British Antarctic Survey (BAS) and the Alfred-Wegener-Institute (AWI) in the framework of the "Filchner Ice Shelf System" (FISS) and the "Filchner Ice Shelf Project" (FISP). A total of 256 point seismic measurements were made, of which 248 had clearly visible reflectors and were deemed usable. Each data point consists of a location, together with measurements of ice thickness and water column thickness. These data were collected as part of the FISS NERC large grant, project number NE/L013770/1.