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PhD Projects

Evolution of sub-surface damage and snow properties on Antarctic ice shelves

Project Summary:

Antarctic snow layers contain information about past ice dynamics, accumulation rate, temperature and the timing of melt events.  They can also hide buried features such as crevasses (Marsh et al., 2021).  To observe sub-surface layering, we have historically relied on ground-based measurements (snowpits, ice cores) or radio-echo sounding from aircraft (Bingham et al., 2015), requiring extensive field campaigns and providing limited spatial and temporal coverage.

Recent improvement in satellite-borne radar resolution and the timing of orbital crossovers allows coincident measurements over ice sheets at multiple frequencies, enabling the mapping of near-surface snow properties through penetration differences (Michel et al., 2014; Rott et al., 2021) and advanced waveform analysis (Fons et al.,  2021).  This new satellite capability, alongside machine learning assisted processing, provides a pathway to mapping Antarctic-wide accumulation rates and physical properties that control crack growth, which remain two of the most uncertain components of mass balance of the ice sheet (Palerme et al., 2017).  This PhD project ties in with a NERC-funded research project on the Brunt Ice Shelf (RIFT-TIP) and field validation work may be possible through the Collaborative Antarctic Science Scheme.

Objectives and Methods:

The project has two aims:

1/ To investigate temporal change in satellite radar backscatter and penetration at X-, C- and L- band (including at different polarisations) over a well-studied control site in Antarctica (Fig 1):  Images will first be radiometrically calibrated and adjusted for ice flow.  A supervised or semi-supervised change detection approach will be developed, (e.g., a convolutional neural network), using differences of multi-look backscatter images and interferometric coherence as input. Initially, the seasonal evolution of a 4+ year sequence of TerraSAR-X and Sentinel-1 synthetic aperture radar (SAR) backscatter imagery will be correlated with local meteorological observations and ground-based (400 MHz) radar (GPR) measurements.  Coincident field validation work may be possible on the Brunt Ice Shelf through the Collaborative Antarctic Science Scheme.

Figure 1: The evolution of backscatter in a sequence of TerraSAR-X multi-look images for the Brunt Ice Shelf, showing a) high backscatter from a buried crack and a buried, compacted ice road, b) spatial variations associated with thickness of isochronous layers, c) localised reduction in backscatter associated with high water content, d) and overall reduction in penetration depth after surface re-freezing.

2/ To investigate the extent and depth at which subsurface features (crevasses, firn aquifers, etc.) are visible and represented at X-, C- and L- band (TerraSAR-X, Sentinel-1, Palsar-2) relative to depths and surface heights obtained from GPR and altimetry (Envisat, Cryosat-2, ICESat-2):  A classifier will be developed to match unlabelled regions of SAR images against subsurface information available from layer tracking of GPR (e.g. Ibikunle et al., 2020) to form a spatially continuous layer depth map.  Data from the P-band BIOMASS sensor may be included after its launch (in 2024) with the potential to map and interpret more deeply buried features.

Figure 2: Internal layering from GPR showing spatial variability in accumulation rate in the upper 10 m of an ice shelf

Figure 2: Internal layering from GPR showing spatial variability in accumulation rate in the upper 10 m of an ice shelf


Bingham, R.G., et al., (2015), Ice-flow structure and ice dynamic changes in the Weddell Sea sector of West Antarctica from radar-imaged internal layering, J. Geophysical Research – Earth Surface, doi:10.1002/2014JF003291

Fons, S.W., et al., (2021), Assessing CryoSat-2 Antarctic Snow Freeboard Retrievals Using Data From ICESat-2, Earth and Space Science, doi:10.1029/2021EA001728

Ibikunle, O., et al., (2020), Snow Radar Layer Tracking Using Iterative Neural Network Approach, IGARSS 2020, doi: 10.1109/IGARSS39084.2020.9323957

Michel, A., Flament, T., and Remy, F. (2014) Study of the Penetration Bias of ENVISAT Altimeter Observations over Antarctica in Comparison to ICESat Observations, Remote Sensing, doi:10.3390/rs6109412

Marsh, O.J., Price, D., Courville, Z.R., and Floricioiu, D., (2021), Crevasse and rift detection in Antarctica from TerraSAR-X satellite imagery, Cold Regions Science and Technology, doi:10.1016/j.coldregions.2021.103284

Palerme, C., Genthon, C., Claud, C. et al. (2017), Evaluation of current and projected Antarctic precipitation in CMIP5 models, Climate Dynamics, doi:10.1007/s00382-016-3071-1

Rott, H., Scheiblauer, S., Wuite, J., Krieger, L., Floricioiu, D., et al., (2021), Penetration of interferometric radar signals in Antarctic snow, The Cryosphere, doi:10.5194/tc-15-4399-2021

Please be aware that due to immigration requirements this project is only available to applicants from the UK or who have settled or pre-settled status in the UK  (i.e. a home fees student) 

The student for this project will be registered at the University of Edinburgh and based at British Antarctic Survey in Cambridge along with several other SENSE students