The school will provide advanced training in risk and uncertainty in natural hazards from the Cabot Institute's leading academics plus some special guest lecturers.  Afternoons will include hands-on exercises.

The school is open to postgraduates, early career researchers and scientists from industry and government agencies.

Confirmed lecturers and subjects

 Introduction to uncertainty - Professor Keith Beven

An introduction to the issues underlying uncertainty estimation. An R practical on generation of random variables and joint variables using copulas. Finishing with an example GLUE application.

Sensitivity analysis - Professor Thorsten Wagener

Sensitivity analysis investigates how the uncertainty in the model output can be apportioned to the uncertainty in the model input (including its parameters). We will introduce the most widely used approaches to sensitivity analysis and provide hands-on applications of these methods to natural hazard models of varying complexity. 

Expert elicitation - Professor Willy Aspinall

This session covers background to the use of scientific experts' opinions in decision support; concept of Cooke's Classical Model for determining performance-based weights and differential pooling of opinions from a group of experts, with strong emphasis on the expression of uncertainty estimates; principles for obtaining a "rational consensus".  Also described will be a complementary approach for eliciting qualitative rankings and preferences by a paired comparison approach coupled with probabilistic inversion to produce ranking metrics and consistency checks.

Calibrate your model - Dr Jonty Rougier

In this session we explore the principles of model calibration, and simple tools for the same: space-filling designs (eg latin hypercubes), visualisation with parallel coordinate plots, dealing with multivariate outputs (principal variables analysis), ruling out regions of parameter space (history matching), proceeding sequentially.  

Bayesian belief networks - Dr Thea Hincks

A practical introduction to Bayesian Belief Networks for hazard assessment and decision making.  Bayesian Networks are probabilistic graphical models, in which a system is represented by a set of nodes corresponding to different variables or states of the system, and a set of arcs which represent conditional dependencies between the nodes. The network structure and parameters can be determined by expert judgement and/or observational evidence. Observable or known states can then be used to provide a probabilistic estimate or forecast for unknown or future states. Case studies include a retrospective assessment of volcanic hazard for Guadeloupe based on the 1976 volcanic crisis (using expert judgement), and a data driven lahar forecasting model. We will briefly cover alternative tools for BBN development, with demonstration exercises using freely available software (GUI will require windows or Wine on Mac/Linux).

Decision Analysis - Dr Theo Economou

When trying to fit statistical models for inferential purposes, we may conclude that there is not enough data to actually implement a model. In decision making however, decisions have to be made regardless of the amount or quality of the available information. This session introduces Bayesian decision analysis which offers a coherent framework for making decisions under uncertainty. The framework is illustrated using the example of issuing hazard warnings, followed by an R practical session.

Venue

The summer school will be held at Engineers House, a Grade II listed building in Clifton Down, a prestigious suburb of Bristol.

Directions, travel and parking.

Fees

Postgraduate students: £300

Non-students: £500

The cost includes all course materials & lunch and your place on the course for the week.

Accommodation is not provided but we have a Summer School accommodation (PDF, 200kB) [PDF, 195.9 KB].  Please note the University does not endorse these venues. 

Registration

You can register for this summer school by filling in the online application form.  You will be notified by email if you have been successful, at which point we will send you the details to pay for your place. 

This is always a popular summer school so we advise booking early to avoid disappointment as spaces are limited. 

Deadline for applications is Monday 6 July 2015.

Other information

Please contact cabot-enquiries@bristol.ac.uk if you have any queries about the school.

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Eyjafjallajokull Susanna Jenkins