Ice speed & Artificial Intelligence (AI): Using satellite data and advanced computer techniques to detect ice sheet change

Supervisors: Dr Anna Hogg (Uni Leeds); Dr Isabel Nias (Uni Liverpool); Dr He Wang (Uni Leeds)

Global sea level rise and the associated flood and coastal realignment that accompanies it, is recognized as posing the greatest climate change risk to the UK. Over the past century, global sea levels have risen by 1.7 ± 0.3 mm per year on average, increasing to 3.2 ± 0.4 mm per year during the last 30-years. Climate models predict that this acceleration is only set to continue in the future. While thermal expansion of the ocean is currently the largest component of the sea level budget, our knowledge of the size and timing of the future contribution from the Antarctic and Greenland Ice Sheets is much less certain.

Satellite Earth observation has revolutionised our understanding of the remote and inaccessible Polar Regions. Without this critical resource we would have a far less complete understanding of which regions are changing & how fast, and what the physical mechanisms are responsible for driving the associated change. In Antarctica, satellite data has been vital for revealing the continent-wide spatial pattern of ice flow. Since 1992 ice velocity in West Antarctica has sped up markedly, with individual ice streams such as Pine Island Glacier nearly doubling in speed over the 22-year period. Despite a clear long-term trend for increasing ice velocity, speed up has not been constant through time, with neighbouring glaciers speeding up and slowing down in response to different forcing mechanisms.

This project offers an exciting opportunity to work at the interface of climate and space science, making an important contribution to international efforts to study the effects and impact of climate change. In this PhD, you will work closely with world-leading experts in satellite observations, ice flow modelling, and advanced computer techniques, to better understand the Antarctic and Greenland Ice Sheets. Through supervision by Dr Hogg, you will use satellite observations to measure ice speed and then the mass balance of the Antarctic and Greenland Ice sheets, quantifying the ice sheet sea level contribution over the last 30-years. Synthetic Aperture Radar (SAR) data, from Earth observation satellites including ERS-1/2, TerraSAR-X and Sentinel-1, will be used to track changes in ice speed In Antarctica and Greenland, using intensity feature tracking and interferometry. Ice velocity measurements will be combined with surface and bed topography measurements to determine ice flux, and then this will be converted to mass balance using the Input-output-method (IOM). Through co-supervision by Dr Nias at the University of Liverpool, your satellite observations will be combined with the BISICLES ice flow model in an ice flow optimisation procedure to fill gaps in the satellite data, providing a continuous record of change. Through co-supervision by Dr Wang, you will pioneer the use of advanced computer techniques, such as Artificial Intelligence, to determine the significance of observed change, and to correlate changes in ice flow with ocean temperature measurements.

During your PhD you will lead at least three journal papers on these important science topics, and you may have the option to undertake a Polar field campaign. The PhD will be based in the School of Earth and Environment at the University of Leeds, and you will therefore have valuable opportunities to work closely with both the European and German Space Agencies (ESA & DLR), and European collaborators through the projects affiliation with the ESA Polar+ Ice Shelves research project that is already funded. The successful applicant will have access to a broad spectrum of specialist training in Earth Observation and glaciology, in addition to the extensive University of Leeds workshops on a range of topics, including satellite remote sensing, scientific programming through to managing your degree. Applicants will hold good first degree (first or high 2.1) or Masters degree in physics, maths, Earth science, climate science, computer science, Earth observation or a related discipline. We welcome applications from a wide range of backgrounds, including those with non-traditional qualifications or from industry – please contact us to have a chat about your suitability for the programme.