About the Project
Introduction:
The calving of icebergs represent a varied range of processes that are currently too complex to be fully integrated into large scale ice sheet models (Benn et al., 2007; 2017). This creates the need to derive simpler relationships (i.e. calving laws) that capture time averaged calving behaviour. However, universally applicable laws are currently lacking and there are many uncertainties about the dynamic feedbacks that regulate calving behaviour.
This project will seek to collect an unprecedented dataset of observations of glacier calving and dynamic behaviour, utilising (and expanding on) cutting edge rapid remote sensing techniques that have been developed by the supervisory team (Lea, 2018; www.liverpoolGEE.wordpress.com).
The evolution of glacier margins and ice flow will be investigated with respect to both climate and ideas that iceberg calving may exhibit self-organised criticality-type behaviour (Åström et al., 2014; Leonardi & Fagherazzi, 2014). This aspect of the project would explore the potential that calving might exhibit systematic structures and patterns of behaviour, and that overall stability can be influenced by incremental, localised changes at the ice margin (e.g. Bak, 2013; Åström et al., 2014).
Results from these analyses will then be compared to widespread observations of glacier (in-)stability to determine whether they can be a predictor of rapid retreat. The project will therefore seek to advance our knowledge of calving and glacier stability in Greenland, which has significant implications for both future sea level change projections and iceberg hazards to shipping and infrastructure under a changing climate.
We encourage applications from those with backgrounds in Geography, Earth Sciences/Geology, Environmental Science, Mathematics, Engineering, Physics and/or Computing with an enthusiasm for studying glacial environments.
While experience in coding is useful, it is not compulsory - for those with no/little experience, training in Javascript, Python (Google Earth Engine), and MATLAB (data analysis) will be provided by the supervisory team. Similarly, for those with experience in coding, but not in glacial environments, training will be provided in the first year of study.
Funding Notes
Full funding (fees, stipend, research support budget) is provided by the University of Liverpool. Formal training is offered through partnership between the Universities of Liverpool and Manchester in both subject specific and transferable skills to the entire PhD cohort and at each University through local Faculty training programmes.
References
Åström, J.A., Vallot, D., Schäfer, M., Welty, E.Z., O’Neel, S., Bartholomaus, T.C., Liu, Y., Riikilä, T.I., Zwinger, T., Timonen, J. and Moore, J.C., 2014. Termini of calving glaciers as self-organized critical systems. Nature Geoscience, 7(12), p.874.
Bak, P., 2013. How nature works: the science of self-organized criticality. Springer Science & Business Media.
Benn, D.I., Warren, C.R. and Mottram, R.H., 2007. Calving processes and the dynamics of calving glaciers. Earth-Science Reviews, 82(3-4), pp.143-179.
Benn, D.I., Åström, J., Zwinger, T., Todd, J., Nick, F.M., Cook, S., Hulton, N.R. and Luckman, A., 2017. Melt-under-cutting and buoyancy-driven calving from tidewater glaciers: new insights from discrete element and continuum model simulations. Journal of Glaciology, 63(240), pp.691-702.
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