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Investigating the influence of meltwater runoff and near-terminus subglacial hydrology on the dynamics of Greenland’s marine-terminating glacier margins

Project summary

This project will investigate the influence of meltwater runoff and near-terminus subglacial hydrology on the dynamic stability of marine-terminating glaciers draining the Greenland Ice Sheet.


The greatest store of fresh water in the northern hemisphere is held within the Greenland Ice Sheet (GrIS). Over recent decades, the ice sheet’s rate of mass loss has accelerated driven by a warming climate and substantial increases both in: 1) the speed of large marine terminating glaciers (MTGs) draining the ice sheet; and 2) surface melt rates and melt extent. However, while there is clear evidence intimating a role between meltwater and subglacial hydrology and MTG dynamics1 , the precise nature of these interactions, particularly over long (>5 yr) timescales remains very poorly understood. On shorter[1]time scales, in-situ2 and satellite3 based studies have revealed links between the seasonal evolution in both meltwater-runoff and subglacial hydrology and the dynamics of tidewater glacier termini. However, the extent to which any sustained changes in dynamics are driven by subglacial processes, as opposed to fjord processes operating at the ice-ocean interface and in particular submarine melting, remain unclear. Nevertheless, improved satellite data availability in conjunction with exciting developments in EO techniques to infer both glacier adjacent fjord-water properties (temperature, salinity and turbidity)4,5 and ice motion6 offers the exciting potential to investigate how both evolving subglacial hydrology and submarine melt processes impact longer term MTG dynamics with clear implications for GrIS mass loss.

Aim and research questions

This project will use a range of earth observation data to investigate the influence of ice-sheet runoff, subglacial hydrology and near-terminus fjord processes on the long-term dynamic stability of MTGs draining the GrIS. More specifically, the project will quantify how ice-motion at Greenland’s MTGs has responded spatially and temporally to changes in subglacial discharge, near-terminus subglacial hydraulic efficiency and variations in calving and frontal (submarine) ablation. The project will be delivered via the following objectives:

O1) Determine, at high spatial and temporal resolution, how MTG velocity, terminus position and surface elevation have changed in recent decades at a suite of (~10) fast-flowing glaciers.

O2) Determine seasonal/inter-annual evolution in meltwater-runoff and subglacial hydraulic efficiency.

O3) Determine the distribution of fjordwater temperatures and associated submarine melt-rates.

O4) Determine how MTGs will respond dynamically to increased meltwater-runoff associated with projected climate warming.

Methodology and timetable

To address these objectives, the project will: O1) Analyse a wealth of available satellite data to derive ice-motion3,6 (Sentinel; Landsat) and surface elevation (CryoSat-2; IceSat) change over recent decades. O2) Determine meltwater runoff using the MAR climate model and subglacial hydraulic efficiency from sediment rich plume extent/visibility as detected using surface reflectance (LandSat-8 5 and MODIS7 ). O3) Derive ice-proximal fjord surface water temperatures and salinity4 from TOA reflectance (Sentinel-2) to better constrain plume extent and submarine melt-distribution; novel machine learning will be used to delineate the temperature/salinity fields and thus plume extent. O4) Estimate future MTG retreat using a parameterisation8 based on surface melt, subglacial hydraulic efficiency and fjord water temperatures.

Training provision and required skills

You will be supervised by a team of leading glaciologists and remote-sensing scientists, gaining expertise in advanced techniques in remote sensing, data manipulation, machine learning and modelling while being an integral part of the >20 strong world class cryosphere research group at Edinburgh. We seek an enthusiastic candidate equipped with advanced quantitative skills and a suitable degree including physics, mathematics, computer science, engineering, earth sciences or physical geography.

References and further reading

1 – Nienow et al, 2017, Curr. Clim. Change Rep. 3; 2 – Bunce et al, 2021, J. Glac., 262; 3 – Davison et al, 2020, J. Geophys. Res. 125; 4 – Medina-Lopez and Urena Fuentes, 2019, Rem. Sensing, 11; 5 – Schild et al, 2017, Int. J. Rem. Sens. 38; 6 – Hogg A. et al, 2017, Geophys. Res. Lett., 44; 7 – Hudson et al, 2014, Cryosphere, 8; 8 – Cowton et al, 2018, PNAS, 115