The Greenland ice sheet contains enough water to raise global sea level by 7 m, and submerge low-lying cities such as Venice, Amsterdam, Manhattan and Shanghai. Although it is unlikely that the ice sheet will melt away completely during our lifetime, Greenland has already contributed 10% to global sea level rise over the last 20 years. It is extremely important that we accurately estimate how much Greenland is likely to contribute to future sea level so that we can adapt and plan accordingly; 21 million people worldwide currently experience flooding and this figure is expected to double for every additional 10 cm of sea level rise. Regional climate models are currently used to predict ice sheet melting and, although they are excellent at forecasting long-term trends and average states, we do not know how well they capture extreme events (e.g. high temperatures) that happen in a small area and/or for a very short amount of time. If such events are poorly captured, it is likely that we underestimate the total amount of melt the ice sheet will undergo in future.
This project, supervised by Dr Amber Leeson and Dr Emma Eastoe (two leading researchers with complimentary expertise), will develop the first historical inventory of extreme melt events on Greenland using a combination of ice core records, climate data and satellite images. Using these data, together with state-of-the-science statistical techniques drawn from Extreme Value Analysis, which has previously been used to model both extreme river flow events and extreme sea states, we will develop a model of extreme melting on Greenland. Using this model, we will predict the frequency, intensity and duration of such events in a future (warmer) world, estimate their contribution to global sea level, and determine if (and by how much) our current estimates of Greenland’s contribution to future sea level are underestimated. As climate models become larger and more complex, there is an increasing need for methodological innovation drawn from the fields of mathematics and computer science in order to understand their strengths and limitations. By exploiting advanced mathematics in order to answer an important data-driven research question, this project will transform our understanding of cryospheric change and improve our capability to make reliable predictions of future global sea level.
Further Information: http://www.lancaster.ac.uk/sci-tech/downloads/phd_259.pdf
Academic Requirements: First-class or 2.1 (Hons) degree, or Masters degree (or equivalent) in an appropriate subject.
Deadline for applications: 14 February 2016
Provisional Interview Date: [tbc] Week Beginning 29 February 2016
Start Date: October 2016
Application process: Please upload a completed application form (download from http://www.lancaster.ac.uk/media/lancaster-university/content-assets/documents/lec/pg/LEC_Funded_PhD_Application_Form.docx) outlining your background and suitability for this project and a CV at LEC Postgraduate Research Applications, http://www.lec.lancs.ac.uk/postgraduate/pgresearch/apply-online.
You also require two references, please send the reference form (download from http://www.lancaster.ac.uk/media/lancaster-university/content-assets/documents/lec/pg/LEC_Funded_PhD_Reference_Form.docx) to your two referees and ask them to email it to Andy Harrod ([email protected]
), Postgraduate Research (PGR) Co-ordinator, Lancaster Environment Centre by the deadline.
Due to the limited time between the closing date and the interview date, it is essential that you ensure references are submitted by the closing date or as soon as possible.
Nghiem, S. V. et al. (2012), The extreme melt across the Greenland ice sheet in 2012, Geophys. Res. Lett., 39, L20502, doi:10.1029/2012GL053611.
Keef, C. et al. (2013), Estimating the probability of widespread flood events, Environmetrics. 24, 1, p. 13-21 9 p.
Fettweis, X. et al. (2013), Estimating the Greenland ice sheet surface mass balance contribution to future sea level rise using the regional atmospheric climate model MAR, The Cryosphere, 7, 469-489, doi:10.5194/tc-7-469-2013.