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  • The survey collected a total of 11,500 km of data along 22 lines, spaced 12 km apart and oriented perpendicular to the strike of both the Bouguer anomaly field, as derived from land data (McGibbon and Smith, 1991), and the major sub-ice topographical features (Doake et al., 1983). The speed of the aircraft was set to produce a sample spacing of about 60 m and the data were collected at heights between 1600 and 2000 m above sea level. The gravity signal was recorded using a LaCoste and Romberg air/sea gravimeter, S-83, which has been kindly loaned to BAS by the Hydrographic Office of the Royal Navy. The meter was modified by the ZLS company for use in an aircraft. The equipment was deployed in a BAS De-Havilland Twin Otter aircraft. Differential, dual frequency, carrier phase, GPS measurements of the aircraft''s motion were made using Trimble and Ashtech geodetic receivers and antennas. Ice thickness data were obtained using a BAS-built, radio echo sounding system (Corr and Popple, 1994). Ice-bottom returns over most of the survey area were obtained at a sample spacing of approximately 28 m. GPS measurements were tied into base stations in International Terrain Reference Frame network (Dietrich et al., 1998) and gravity measurements to base stations in the IGSN71 net (Jones and Ferris, 1999). We present here the processed bed elevation picks from airborne radar depth sounding collected using the BAS PASIN radar system. Data are provided as XYZ ASCII line data.

  • This is a collection of all vintage BAS radar data that went into BEDMAP 1 (Lythe and Vaughan, 2001) that have not been released so far as line data. BEDMAP data descries the thickness of the Antarctic ice sheet. They have been collected on surveys undertaken over the past 50 years and brought together into a single database. These data have allowed the compilation of a suite of seamless digital topographic models for the Antarctic continent and surrounding ocean. Data are provided as XYZ ASCII line data.

  • In 2011, aerogeophysics data were acquired over Pine Island Glacier, West Antarctica on a grid comprising 30 transverse lines across the glacier, each around 20 km long, and with a spacing of roughly 500 m between the lines. The orientation of the lines was selected to be perpendicular to the surface features visible in satellite images in the central part of the ice shelf. Elevation of the ice-surface directly beneath the aircraft was simultaneously measured using a nadir-pointing laser altimeter. We present here the processed bed elevation picks from airborne radar depth sounding collected using the BAS PASIN radar system. Data are provided as XYZ ASCII line data.

  • An airborne radar survey was flown as part of the GRADES-IMAGE project funded by BAS over the Evans Ice stream/Carson Inlet region mainly to image englacial layers and bedrock topography during the 2006/07 field season. Aeromagnetic data were also opportunistically collected. We present here the bed elevation picks from airborne radar depth sounding collected using the BAS PASIN radar depth sounding system. Data are provided as XYZ ASCII line data.

  • This dataset contains the position and depth (ice thickness) of three spatially-extensive Internal Reflecting Horizons (IRHs) mapped from ice-penetrating radar data acquired with the British Antarctic Survey''s PASIN and PASIN2 ice radar systems across central East Antarctica. The dataset extends geographically from Dome A to South Pole. Using previous dated IRHs from Winter et al (2019), an independent validation of IRH ages from the South Pole ice-core chronology and a 1-D steady-state model, we assigned ages to our three IRHs: (H1) 38.5 +/- 2.2 ka, (H2) 90.4 +/- 3.57, and (H3) 161.9 +/- 6.76 ka. This study was motivated by the AntArchitecture Action Group of the Scientific Committee for Antarctic Research (SCAR). The project was supported by the National Environmental Research Council (NERC)-funded ONE Planet Doctoral Training Partnership (NE/S007512/1), hosted jointly by Newcastle and Northumbria Universities. The authors thank the BAS science and logistics teams for acquiring both the AGAP PASIN and PolarGAP PASIN2 data which is fully available on the Polar Airborne Geophysics Data Portal of the UK Polar Data Center (https://www.bas.ac.uk/project/nagdp/). BedMachine (version 2) data are available at https://doi.org/10.5067/E1QL9HFQ7A8M.

  • This dataset includes ~3,000 line km of radio-echo sounding data along the English Coast of western Palmer Land in the Antarctic Peninsula. Data was acquired by the British Antarctic Survey Polarimetric-radar Airborne Science Instrument (PASIN2) ice sounding radar system in the austral summer of 2016/2017. Radar lines collected at ~3-5 km line spacing transect a number of outlet glacier flows, close to the grounding line, where continental ice begins to float. Data were funded by a BAS National Capability grant.

  • This data set provides processed Ku- and Ka-band fully-polarimetric backscatter and derived polarimetric parameters from hourly scans, acquired using the KuKa radar, during Legs 1, 2, 4 and 5 of the 2019-2020 MOSAiC International Arctic Drift Expedition. Scans were acquired during winter (Legs 1 and 2), advanced melt (Leg 4) and freeze-up (Leg 5) seasons, from various Remote Sensing (RS) sites, located in the MOSAiC ice floe. The first deployment of the KuKa radar was on 18 October 2019 at RS1 site and the radar was retreated (due to ice break up) on 18th November. The radar was redeployed on 29th November at RS2 site until 13th December when cracks were observed at the site and the instrument was turned off and moved to a safe location. The radar was redeployed at RS3 site and started measuring again on 21st December 2019 until 31st January 2020, after which the radar was taken off the RS site to conduct maintenance. The radar was not operational during Leg 3. During Leg 4, the radar was operational between 25th June and 19th July 2020, and later retreated back to the ship, for deployment in Leg 5. The radar was deployed on 24th August 2020 and operational until the end of the MOSAiC expedition. The dataset was collected by MOSAiC Team ICE participants and processed by Vishnu Nandan at the University of Manitoba, Canada. This work was funded in part through NERC grant NE/S002510/1, the Canada 150 Chair Program and the European Space Agency PO 5001027396. The authors thank Marine Environmental Observation, Prediction and Response Network (MEOPAR) Postdoctoral Fellowship grant to Vishnu Nandan. The authors also thank the crew of R/V Polarstern and all scientific members of the MOSAiC expedition for their support in field logistics and field data collection.

  • This data set provides processed Ku- and Ka-band fully-polarimetric backscatter and derived polarimetric parameters from hourly scans, acquired using the KuKa radar, during Legs 1, 2, 4 and 5 of the 2019-2020 MOSAiC International Arctic Drift Expedition. Scans were acquired during winter (Legs 1 and 2), advanced melt (leg 4) and freeze-up (Leg 5) seasons, from various Remote Sensing (RS) sites, located in the MOSAiC ice floe. The first deployment of the KuKa radar was on 18 October 2019 at RS1 site and the radar was retreated (due to ice break up) on 18th November. The radar was redeployed on 29th November at RS2 site until 13th December when cracks were observed at the site and the instrument was turned off and moved to a safe location. The radar was redeployed at RS3 site and started measuring again on 21st December 2019 until 31st January 2020, after which the radar was taken off the RS site to conduct maintenance. The radar was not operational during Leg 3. During Leg 4, the radar was operational between 25th June and 19th July 2020, and later retreated back to the ship, for deployment in Leg 5. The radar was deployed on 24th August 2020 and operational until the end of the MOSAiC expedition. The dataset was collected by MOSAiC Team ICE participants and processed by Vishnu Nandan at the University of Manitoba, Canada. This work was funded in part through NERC grant NE/S002510/1, the Canada 150 Chair Program and the European Space Agency PO 5001027396. The authors thank Marine Environmental Observation, Prediction and Response Network (MEOPAR) Postdoctoral Fellowship grant to Vishnu Nandan. The authors also thank the crew of R/V Polarstern and all scientific members of the MOSAiC expedition for their support in field logistics and field data collection. ***** 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 that was found in the original KuKa radar processing chain.

  • This dataset presents monthly gridded sea ice and ocean parameters for the Arctic derived from the European Space Agency''s satellite CryoSat-2. Parameters include sea ice freeboard, sea ice thickness, sea ice surface roughness, mean sea surface height, sea level anomaly, and geostrophic circulation. Data are provided as monthly grids with a resolution of 25 km, mapped onto the NSIDC EASE2-Grid, covering the Arctic region north of 50 degrees latitude, for all winter months (Oct-Apr) between 2010 and 2018. CryoSat-2 Level 1b Baseline C observed waveforms have been retracked using a numerical model for the SAR altimeter backscattered echo from snow-covered sea ice presented in Landy et al. (2019), which offers a sophisticated physically-based treatment of the effect of ice surface roughness on retracked ice and ocean elevations. Methods for optimizing echo model fits to observed CryoSat-2 waveforms, retracking waveforms, classifying returns, deriving sea ice freeboard, and converting to thickness are detailed in Landy et al. (In Review). This dataset contains derived sea ice thicknesses from two processing chains, the first using the conventional snow depth and density climatology from Warren et al. (1999) and the second using reanalysis and model-based snow data from SnowModel (Stroeve et al., In Review). Sea surface height and ocean topography grids were derived from only those CryoSat-2 samples classified as leads. Both the random and systematic uncertainties relevant for each parameter have been carefully estimated and are provided in the data files. NetCDF files contain detailed descriptions of each derived parameter. Funding was provided by ESA Living Planet Fellowship Arctic-SummIT grant ESA/4000125582/18/I-NS and NERC Project PRE-MELT grant NE/T000546/1.

  • This dataset presents biweekly gridded sea ice thickness and uncertainty for the Arctic derived from the European Space Agency''s satellite CryoSat-2. An associated ''developer''s product'' also includes intermediate parameters used or output in the sea ice thickness processing chain. Data are provided as biweekly grids with a resolution of 80 km, mapped onto a Northern Polar Stereographic Grid, covering the Arctic region north of 50 degrees latitude, for all months of the year between October 2010 and July 2020. CryoSat-2 Level 1b Baseline-D observed radar waveforms have been retracked using two different approaches, one for the ''cold season'' months of October-April and the second for ''melting season'' months of May-September. The cold season retracking algorithm uses a numerical model for the SAR altimeter backscattered echo from snow-covered sea ice presented in Landy et al. (2019), which offers a physical treatment of the effect of ice surface roughness on retracked ice and ocean elevations. The method for optimizing echo model fits to observed CryoSat-2 waveforms, retracking waveforms, classifying returns, and deriving sea ice radar freeboard are detailed in Landy et al. (2020). The melting season retracking algorithm uses the SAMOSA+ analytical echo model with optimization to observed CryoSat-2 waveforms through the SARvatore (SAR Versatile Altimetric Toolkit for Ocean Research and Exploitation) service available through ESA Grid Processing on Demand (GPOD). The method for classifying radar returns and deriving sea ice radar freeboard in the melting season are detailed in Dawson et al. (2022). The melting season sea ice radar freeboards require a correction for an electromagnetic range bias, as described in Landy et al. (2022). After applying the correction, year-round freeboards are converted to sea ice thickness using auxiliary satellite observations of the sea ice concentration and type, as well as snow depth and density estimates from a Lagrangian snow evolution scheme: SnowModel-LG (Stroeve et al., 2020; Liston et al., 2020). The sea ice thickness uncertainties have been estimated based on methods described in Landy et al. (2022). NetCDF files contain detailed descriptions of each parameter. Funding was provided by the NERC PRE-MELT grant NE/T000546/1 and the ESA Living Planet Fellowship Arctic-SummIT grant ESA/4000125582/18/I-NS.