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Glaciology

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    This is a collection of iceberg surface areas digitized by hand from a range of satellite images. The data may be useful for classifying ice shelf behaviour.

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    Perpendicular seismic refraction profiles collected at 11 sites along and across the ice flow unit boundary between ice units coming from the Lambert Glacier and the Mawson Escarpment Ice Stream. Survey sites are located upstream of Gillock Island.

  • We utilize the sea level fingerprint module - ISSM’s Solid Earth and Sea level Adjustment Workbench (ISSM-SESAW), developed by NASA/Jet Propulsion Laboratory (JPL), to provide high-resolution sea level fingerprints in response to future polar ice sheet mass changes in the 21st century under the Representative Concentration Pathway (RCP) 4.5 and 8.5 scenarios. We also explore the sensitivity of sea level fingerprints to different 1-D elastic Earth models and the spatial resolution at which mass change of polar ice sheets is resolved. Furthermore, sea level contributions by individual polar ice sheet basins in the 21st century are also estimated for some coastal cities of interest (e.g., Perth) in this research.

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    A numerical ocean model based on the Regional Ocean Modelling System (ROMS) framework was run for the Sorsdal ice shelf region and included modifications for ice/ocean thermodynamics and mechanical pressure, following (Dinniman et al., 2007). The model domain was discretised on a polar stereographic grid with a uniform 2 km horizontal resolution. The vertical terrain-following coordinate had 31 vertical layers with a sigmoidal layer distribution to provide higher vertical resolution at the surface and bottom regions.

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    The East Antarctic Ice Sheet (EAIS) is the largest source of potential sea-level rise, containing some 19 m of sea-level equivalent. One of the well-investigated regions in East Antarctica is Law Dome, which is a small independent ice cap situated to the west of Totten Ice Shelf. The ice cap is slow-moving, has a low melt-rate at the surface and moderate wind speeds, making it a useful study site for our investigations. Radar data from Investigating the Cryospheric Evolution of the Central Antarctic Plate (ICECAP) project has good coverage over this area. A new method is proposed for the estimation of attenuation rate from radar data which is mathematically modeled as a constrained regularised l2 minimization problem. In the proposed method, only radar data is required and the englacial reflectors are automatically detected from the radar data itself. A final product of 3D attenuation rates and 3D samples count is provided for the research community in this data set.

  • Antarctic Landfast sea ice (fast ice) is important climatologically, biologically and for logistics for short time-scale anomalies. Until recently, there hasn’t been an accurate, high-resolution fast ice extent dataset which can support an analysis on drivers of fast ice and most studies only investigate fast ice on limited regions of Antarctica in a limited time scale. There is a need to extend the spatial and temporal studying coverage to provide detailed information on the Antarctic coast over a longer period. This is the first detailed analysis to identify and quantify correlation between the environmental anomaly and fast ice anomaly mainly in the east Antarctic coast. By examining regional/local fast ice extent in in east Antarctic coast in the context of the broader and/or remote-teleconnected atmospheric circulation/properties using spatial correlation techniques, a strong correlation between NINO3 region and Lützow-Holm Bay fast ice and similar and significant correlation of regional scale factors from Lützow-Holm Bay to Mawson Coast mainly are found. The results of this thesis suggest that the pack ice, atmospheric factors and oceanic factors are important for interpreting fast ice anomalies. To identify and quantify correlation between the pack ice, temperature at 2m, wind at 10m, snow fall anomaly, sea surface temperature anomaly, ocean heat content anomaly and fast ice anomaly, backward multiple linear regression is conducted to demonstrate some predictive fast ice driver information by quantifying the correlation between different drivers and fast ice anomaly. The multiple linear regression also suggests that oceanic influences including pack ice are generally more important than atmospheric influences. Future experiments could be conducted to interpret fast ice anomalies in the context of the ocean mainly.