About the Project
Are we at risk of omitting vitally important processes in our assessments? How can very rare but potentially catastrophic events be factored into models? Policy makers, industry and society must work with these deep uncertainties. What can we learn from other areas of policy that also necessarily deal with deep uncertainty? And, how can society effectively respond to challenges that are inherently probabilistic?
Project Aims and Methods:
This interdisciplinary project has two main aims. First, it will assess how deep uncertainties involved in the simulation of complex physical and social systems are addressed within existing and proposed future General Circulation Models and Integrated Assessment Models on which national and international climate policy is based. In doing so, it will ask are there effective limits of model complexity when it comes to producing outputs that have relevance to policy and wider society ? Second, it will investigate how uncertainty and confidence in climate science is communicated between scientists, decision-makers, and the public . It will explore different methods currently in use, and also alternative methods used in other fields of science. The supervisory team has a unique skill set to support the student through the project. Their expertise spans the academic fields of sustainability science, complex systems simulation, climate science and science communication. All supervisors also have significant experience across the policy, practitioner and media realms.
The student will work closely with the Met Office Hadley Centre staff involved in UKCP18. This is a state-of-the-art, highly complex climate analysis tool which accounts for uncertainties in (1) future emissions, (2) the translation of emissions into concentration pathways, (3) climate sensitivity, and (4) regional climate responses. These uncertainties are potentially of crucial importance to the effectiveness of decisions in climate policy, especially for adaptation where quantitative information is required to inform long-term planning and implementation of adaptation measures. An initial aim of the project will be to find communication methods which are most effective for enabling decision-makers to act appropriately in the face of the often very large uncertainty in climate projections. This will be important new knowledge for the Met Office Hadley Centre, the wider climate modelling community and have a beneficial impact on collaborations between science and decision-makers and help further develop the effectiveness of climate modelling in informing societal and policy responses.
The student will work with the users of climate projections to investigate how they interpret the outputs of climate models and how their understanding of confidence and uncertainty affects their decisions. This will involve working with policy makers, journalists, activists and the public There is significant scope for the student to shape the aims and objective of the project.
Candidates must either possess a good first degree in a quantitative subject (such as natural and social science or mathematics), or demonstrate an ability to increase their skills in probability and statistics.
The student will spend time working within the Met Office Hadley Centre alongside climate scientists who are developing climate projections, and with those involved in science communicating with policy making.
Training will include specialist science communication, and working at the science-policy interface. This will be delivered via the GW4+ DTP and MSc Global Sustainability Solutions programme.
NERC GW4+ DTP studentships are open to UK and Irish nationals who, if successful in their applications, will receive a full studentship including payment of university tuition fees at the home fees rate.
A limited number of full studentships are also available to international students which are defined as EU (excluding Irish nationals), EEA, Swiss and all other non-UK nationals.
 Pidgeon, N. and Fischhoff, B., 2011. The role of social and decision sciences in communicating uncertain climate risks. Nature climate change, 1(1), pp.35-41
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