title: The temperature distribution and geothermal heat flux at Law Dome, East Antarctica
Creators: name: Abdul Salam, S
Publisher: name: University of Tasmania
Year: 2020

description: The East Antarctic Ice Sheet (EAIS) is the world’s largest potential source of sealevel rise, with the marine-based component (i.e. where the ice sheet is grounded below sea level) containing enough ice to raise sea levels by 52 m. Ice dynamics are strongly influenced by the internal temperature distribution within the ice sheet, with warmer, more deformable ice leading to potential increases in iceflow velocities, discharge of ice into the ocean and global sea-level fluctuations. Therefore, accurately quantifying englacial ice temperature has the potential to help refine projections of the Antarctic ice-sheet contribution to global sea-level change. Direct temperature measurements through borehole drilling within the ice sheet are reliable but are very sparse over Antarctica. This is because it is very expensive, slow to acquire, and logistically challenging to obtain direct measurements of ice temperature. To mitigate this, one approach is radar-echo sounding, which is a powerful and widely used method to constrain temperatures on basin to continental-scales. Law Dome is a small independent ice cap (approximately 200 km diameter) situated to the west of Totten Ice Shelf in East Antarctica. The region of Law Dome is an appropriate target for investigating englacial temperatures because of the good coverage of airborne radar data from the Investigating the Cryospheric Evolution of the Central Antarctic Plate (ICECAP) project and a temperature profile to bedrock from within an ice borehole at Dome Summit South (DSS). Also, this ice cap is slow-moving and stable with a low melt-rate (2.9 m/yr) at the surface due to the moderate wind speed (mean wind speed 8.3 m/sec), which makes it a good case study region. Here, we use radar data to detect the englacial reflectors in the ice, followed by the estimation of the radar attenuation rate. Previous methods used either estimates of the depth averaged value of the attenuation rate or required additional information regarding the englacial reflectors (stratigraphy), which is not the case here. The extraction of the attenuation rate from radar data is mathematically modelled as a constraint regularised l2 minimisation. Once the attenuation rate is estimated, these attenuations are mapped to temperature profiles. The attenuation is greatly affected by ice temperature and ice chemistry. It is assumed that the ice chemistry will remain the same over Law Dome and the ice borehole temperature profile at DSS is used for calibrating the attenuation-temperature mapping function. The gradient of these temperature profiles is used to obtain geothermal heat flux (GHF) using Fourier’s heat flow equation. To validate our methodology, attenuation differences at flight crossover points are calculated and statistical analyses performed to assess the accuracy of the results. Both spatial and depth analysis are performed over these crossovers. In spatial analysis the differences are averaged over the depth and in depth analysis it is averaged over the spatial dimension. For spatial analysis, the differences are of the order 22.6%, 15.2%, and 32.8% for mean absolute deviation, median absolute deviation, and root mean square error respectively. Also, for the depth analyses, up to the depth of 800 m, the errors are under 29.8%, 24.2%, and 38.8% for mean absolute deviation, median absolute deviation, and root mean square error respectively. The products obtained are 3-D radar attenuation rate of the region, temperature profiles along the ice-column, basal temperature, and GHF across Law Dome. The resulted GHF values are in the range 65-80 mWm−2 . All data sets have high spatial resolution (1km x 1km grid) and are compared with the previously available GHF for the region. A novel method is developed which shows how raw radar sounding data can be used to estimate the attenuation rates, temperatures, and GHF. This method utilises a special case of Ridge regression for estimation of high resolution data sets. In comparison to the existing GHF maps, this method has high resolution and it only requires raw radar data and a single temperature profile over several hundred kilometres.