A netcdf-formatted file containing the original binned data (described in Shore et al ), in their state before they were subjected to EOF analysis. These have had additional processing applied to the SuperMAG data (publically available at http://supermag.jhuapl.edu/) in the form of sampling them to the centroid of the bins, thus they are worth providing here despite the large file size (approximately 12GB). To conserve file space, we have removed empty bins, thus the temporal and spatial basis for these data are provided for each filled bin element. Please note that the binned data had not had the temporal mean values (described in Shore et al , and available in the Supporting Information) removed when they were stored in this netcdf file. The file contains 144 (monthly) sets of 8 variables. These variables are named: 1: filled_bin_data_YYYYMM_r 2: filled_bin_data_YYYYMM_theta 3: filled_bin_data_YYYYMM_phi Variables 1 to 3 contain the nanoTesla vales of the binned data for each of the three magnetic field components in the Quasi-Dipole frame. 4: filled_bin_contrib_stations_YYYYMM The three-letter SuperMAG acronym of the station which contributed to each 5-minute mean data point. 5: filled_bin_colats_YYYYMM 6: filled_bin_longs_YYYYMM Variables 5 and 6 are the co-latitude and longitude coordinates of each filled bin element. 7: filled_bin_times_YYYYMM The 5-minute-mean epoch of each filled bin element, with columns in the order: year, month, day, hour, minute, second). 8: filled_bin_indices_YYYYMM A set of fiducial values describing how the sparse elements of the 1D vector of filled bin values relate to the fiducials of the (transposed!) EOF prediction a 2D matrix product of the spatial and temporal eigenvectors with values in every bin. An example of the usage of these data is given in the MATLAB program Shore-ms01.m, provided in the Supporting Information of Shore et al . ***** PLEASE BE ADVISED TO USE VERSION 2.0 DATA ***** The VERSION 2.0 data set (see ''Related Data Set Metadata'' link below) has been corrected for a bug which led to the bins which span the local midnight meridian having fewer samples than they should. The data density in these bins is now in-line with the rest of the polar coverage. Apart from that change, the original and updated data sets are the same.
Microwave radiometer data at Halley Station, Antarctica, 2013-present
Adelie and Chinstrap penguins were fitted with a combined GPS and time-depth recorder (TDR) tags for between two and fourteen days in order to log their three-dimensional foraging trips. Tags were deployed between December and February of 2008 with a total of 19 Adelie penguin tracks and 35 Chinstrap penguin tracks.
Version 2.0 This data set contains mesospheric carbon monoxide (CO) data acquired by the ground-based microwave radiometer of the British Antarctic Survey (BAS radiometer) stationed at Troll station in Antarctica (72 deg S, 2.5 deg E, 1270 amsl). The BAS radiometer has been designed in order to study the effects of energetic particle precipitation on the middle and upper atmosphere, using nitric oxide and ozone measurements. This data set contains the CO measurements carried out in order to study the dynamical context. The data set covers the period from February 2008 to January 2010, however, due to very low CO concentrations below approximately 80 km altitude in summer, profiles can only be retrieved during Antarctic winter. CO is measured for approximately 2 hours each day (80 percent of the profiles are within +-2 hours around local noon) and profiles are retrieved approximately every half hour. The retrieved profiles, cover two independent layers in the pressure range from 1 to 0.01 hPa (approximately 48 to 80 km, altitude resolution of approximately 16 km). In this version of the data; an additional column of "apriori vmr" has been included in the data files.
A digital elevation model of the bed of Rutford Ice Stream, Antarctica, derived from radio-echo sounding data. The data cover an 18 x 40 km area immediately upstream of the grounding line of the ice stream. This area is of particular interest because repeated seismic surveys have shown that rapid erosion and deposition of subglacial sediments has taken place. The bed topography shows a range of different subglacial landforms including mega-scale glacial lineations, drumlins and hummocks. This dataset will form a baseline survey which, when compared to future surveys, should reveal how active subglacial landscapes change over time. The dataset comprises observed ice thickness data, an interpolated bed elevation grid, observed surface elevation data and a surface elevation grid.
The data set contains values of basal slipperiness (C) and the rate factor (A) for the whole of the Antarctic Ice Sheet. The slipperiness was estimated through model inversion from measurements of surface velocities (1) and ice thickness (2) using the ice-flow model Ua (3). The ice was assumed to deform according to Glen''s flow law with a stress exponent n=3. Basal sliding was assumed to follow Weertman sliding law with m=3, with u_b = C tau^m, where u_b is the basal sliding velocity and tau the (tangential) basal traction.
Due to the constant thermal environment and lower carbonate saturation state of the Southern Ocean, Antarctic marine ectotherms are expected to be amongst the most sensitive to the combined stressors of warming and ocean acidification (OA).To investigate their long term acclimation capacity, adult Antarctic sea urchins, Sterechinus neumayeri, were incubated for 40 months under four treatments: 1) T cur - 0.3 deg C (present day) and pH 7.8 (moderate acidification) 2) pH cur 1.7 deg C (predicted temperature) and pH 8.1 (current pH) 3) pH-0.3 1.9 deg C and pH 7.8 4) pH-0.5 2.2 deg C and pH7.5 (high acidification) The energy budget (energy absorbed, energy lost through respiration and as nitrogenous waste) and growth parameters (scope for growth, mass of somatic and gonad tissues and the CHN content of gonad) were measured through the duration of two 21 day feeding and food processing cycles.Energy budgets were fully acclimated to OA treatments but there was only partial acclimation to temperature. Although metabolic rate was lower in the ambient temperature treatment (-0.3 compared to 2 deg C) and more energy was absorbed from food, there was no significant difference in the scope for growth between treatments. S. neumayeri can acclimate to predicted near future OA and is resilient to predicted temperature conditions.
KRILLBASE is a data rescue and compilation project which aims to improve the availability of information on two of the Southern Ocean''s most important zooplankton taxa: Antarctic krill (Euphausia superba) and salps (Family Salpidae). In 2016, the project released a database of information from 15,194 scientific net hauls, collected between 1926 and 2016 by scientists from ten countries. These data, on the density of Antarctic krill and salps, provide a resource for analysing the distribution and abundance of these taxa throughout the Southern Ocean, to support ecological and biogeochemical research as well as fisheries management and conservation. The data are available as a downloadable csv files and via a seachable web interface. Each row of the main data table represents either a net haul or a composite of several net hauls. The columns describe searchable and filterable sampling and environmental information as well as the krill and salp density. The krill data are presented as both the observed density (NUMBER_OF_KRILL_UNDER_1M2, no.m-2) and the density standardised to a single, relatively efficient sampling method (STANDARDISED_KRILL_UNDER_1M2, no.m-2). The salp data are presented as observed density for all species combined, where an individual can be either a solitary oozoid or a member of an aggregate chain (NUMBER_OF_SALPS_UNDER_1M2, no.m-2). 12,758 of the net hauls in the database include krill data, 9,726 include salp data. 7,295 of the net hauls include both krill and salp data. For hauls where data for either salps or krill were not available the relevant field is blank. The RECORD_TYPE column distinguishes between four types of record and we emphasise that every analysis of the data should first screen on this field to avoid using the same data twice. Most records are labelled "haul", and these result from a single net sampling the water column at a specific station. Others, labelled "stratified pooled haul", are the combined result of several (typically three) stratified hauls (labelled "stratified haul") sampling different parts of the water column. A small number of records, labelled "survey mean" represent the arithmetic mean densities from multiple stations as this was the only recoverable information from the relevant surveys, which were mainly conducted in the 1980s. The dataset is fully described in the following publication which should be cited in published analyses of these data: Atkinson A, Hill SL, Pakhomov E, Siegel V, Anadon R, Chiba S, Daly KL, Downie R, Fielding S, Fretwell P, Gerrish L, Hosie GW, Jessopp MJ, Kawaguchi S, Krafft BA, Loeb V, Nishikawa J, Peat HJ, Reiss CS, Ross RM, Langdon B Quetin, Schmidt K, Steinberg DK, Subramaniam RC, Tarling GA, Ward P (2017) KRILLBASE: a circumpolar database of Antarctic krill and salp numerical densities, 1926-2016. Earth Syst. Sci. Data, 9: 193-210 (doi:10.5194/essd-9-193-2017)
Signy Island camera image files of sea-ice coverage for 2004; played as a movie.
Two netcdf files are provided that contain daily precipitation amounts for January 1979 - July 2017 from the RACMO version 3p2 limited area, atmosphere-only model. The model is described in van Wessem, J. M., C. H. Reijmer, M. Morlighem, J. Mouginot, E. Rignot, B. Medley, and E. van Meijgaard, (2014) Improved representation of East Antarctic surface mass balance in a regional atmospheric climate model, Journal of Glaciology, 60, 761-770. The model was run over a 262 by 240 grid point domain covering Antarctica and parts of the Southern Ocean. The model was forced at the lateral boundaries by data from the European Centre for Medium-range Weather Forecasting (ECMWF) Interim reanalysis (ERA-Interim). Flags are provided for extreme precipitation events. A precipitation day was taken as a daily total of precipitation of greater than 0.02 mm. Extreme precipitation events were then taken as days when daily precipitation amount was greater than the 90th percentile of the daily precipitation values over the period 1979 - 2016.