Project staff and support

Joseph Daron (Intern, London School of Economics)
Doug McNeall (Company Supervisor, Met Office)
David Stainforth (Academic Mentor, London School of Economics)
Lorcan Mac Manus (Technology Translator, Industrial Mathematics KTN)

This Internship project was carried out at the Met Office, in conjunction with the London School of Economics. It was part of the KTN's Industrial Mathematics Internships Programme, co-funded by EPSRC and NERC. The project was also part of the Environmental Risk Management Special Interest Group funded by NERC. Start date: September 2009; duration: 6 months.

Outcomes

The project helped to further understanding of the role that Bayesian Networks can have within climate impacts research. The results of the case study suggest that the tool can be used as an instrument for consultation, highlighting system sensitivities and providing a conceptual framework for considering the many factors that impact climate adaptation decisions.

Benefits

The project allowed the student to gain an improved understanding of the decision-making process in a climate change context. The student developed skills in building Bayesian Networks using Netica and gained experience in structuring interviews and communicating with stakeholders. Working with members of the Climate Impacts Team and other members of the Met Office enabled the student to appreciate the range of issues being addressed and gain insight into the way that the Met Office and the Hadley Centre conducts research and interacts with businesses and the wider research community.

"Working on the internship at the Met Office allowed me to engage directly with decision-makers who are faced with decisions that are sensitive to climate model information. The experience has given me valuable insights that I can apply in my PhD research," said Joseph Daron, Intern (London School of Economics and Political Science).

"The work that Joe has done has been very valuable at a time when increasing attention is being paid to the value of climate information to decision makers. The case study helped to identify the circumstances under which the Bayesian network is a useful tool, and allowed us to engage with decision makers in a new way. The lessons learned from the case study will inform the way that the climate impacts team engage with decision makers in the future. We hope to continue collaborating with Joe, including on a paper for which Joe has already provided a well developed draft. We also hope to continue working with the hospital trusts, using contacts that Joe formed in his time at the Hadley Centre," said Doug McNeall, Industrial supervisor (Met Office Hadley Centre).

"Joe has gained valuable experience and expertise regarding the relative roles of different information sources when making practical decisions influenced by climate change. This will be of benefit in his PhD research and beyond," said David Stainforth, Academic supervisor (London School of Economics and Political Science).

related resources:

»	Probabilistic networks for climate risk
	Technical summary and references
	Download Case Study as PDF

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