Project Description
In this project you will analyse large ensembles of climate and ice-sheet simulations to quantify uncertainty in model projections of past and future sea level changes.
Changes in past ice-sheets in response to differing climate conditions provides valuable information in the study of future ice-sheets evolution, and in turn, aids the constraint of future sea level predictions. Complex computer models are a vital tool used extensively in climate science to improve our understanding of the underlying physical processes, enable future predictions, quantify uncertainties, assess the effects of human actions, and thus guide policy decisions. Within the Climate-Ice research group we are interested in the study of climate and ice-sheet interactions and utilise coupled climate and ice-sheet computer models such as FAMOUS-Ice. Over time we have run numerous ensembles (collections) of simulations (using FAMOUS-Ice) for the Last Glacial Maximum (LGM, circa 21,000 years ago). However, even though the same model is used, not all elements of the setup (initial and boundary conditions such as orbital configuration, prescribed sea surface temperatures, and greenhouse gas concentrations) are the same across the ensembles. Consequently, the comparison of different simulation ensembles is challenging and may have important ramifications when running simulations for future climate projections.
The objective of this project is to investigate the relationship between the different ensembles and assess the effects of changing the model setup on the various outputs. The project entails learning about the FAMOUS-Ice model, as well as the different ensembles and their outputs, before conducting an exploratory graphical and quantitative analysis by writing and adapting existing R code. There is also scope to perform an uncertainty quantification which uses statistical methods to link the different ensembles and learn about the importance and effect of the different model setup configurations.
This project would be suitable for anyone with an interest in how computer models are used in the study of climate and ice, how climate projections such as the IPCC reports are formulated, and the impact and assessment of various types of uncertainty on climate projections.
During this 6-week research project you will:
• Be part of the collegiate and inclusive interdisciplinary Climate-Ice research group which currently comprises two academics, three postgraduate researchers, and three postdoctoral researchers working across climate science, glaciology and statistics,
• Attend fortnightly Climate-Ice research group meetings, meet with your supervisory team each week, and present your work at the Climate-Ice group meeting at the end of your placement,
• Work with talented researchers to contribute to new and impactful research in past and future sea level change,
• Write your own and adapt existing R code to analyse simulation outputs, identify optimal model input parameter values, and quantify uncertainty in sea level change,
• Shadow researchers working on quantifying uncertainty and running climate simulations on high performance computers, and experience the day-to-day life of PhD students, postdoctoral researchers, and academics within the group.
Prerequisites:
A-level Mathematics, and programming experience in R.
Supervisory Team:
Dr Jonathan Owen, Statistician;
Dr Lauren J Gregoire, Earth System Modeller;
Violet Patterson, Earth System Modeller.
Contact
Jonathan Owen, j.owen1@leeds.ac.uk
How to Apply
- Complete the online REP application form, one for each project of interest, including a copy of your CV.
- Complete the EDI form (only one is needed, you do not need to submit more than one if you apply for multiple projects). Although this is optional, if places are over-subscribed, preference will be given to under-represented groups.