Probability and Uncertainty in Climate Modelling Workshop
24th-28th September 2007
St Aidan's College
When we attempt to learn about complex processes through the development of mathematical models, then it is necessary for us to assess the uncertainty in our model based statements about the underlying phenomena. Such uncertainty derives from many sources, including uncertainty as to the initial conditions and to appropriate choices of model parameters, imperfect science, approximate solutions for the the model equations and observational errors in data used to calibrate the model. Further, computer implementations of the models may be very time consuming to evaluate, even for a single choice of model input values, so that, in practice, we are uncertain about the functional form of the model itself.
There is a growing interface between statistics and mathematical modelling, based around Bayesian analysis, which is aimed at developing and implementing an efficient technology that is capable of addressing all sources of uncertainty in model calibration, prediction, optimisation and validation, even for complex high dimensional models. This technology is of interest and importance for all modelling problems, and is a focus for much research in the Statistics group within Mathematical Sciences.
The activities in this strand will concern helping modellers within a range of disciplines to understand more deeply the key methodological issues regarding uncertainty analysis arising from their models and therefore to develop appropriate uncertainty assessments in corresponding areas of application.
The first of these events is this five-day workshop on Probability, Uncertainty and Climate Modelling. This will bring together experts from the climate modelling (both present day and palaeo) and statistics communities to discuss in an informal setting issues of interest to both. These will include probabilistic climate prediction, the calibration of climate models and how models relate to reality. The theme of this year's meeting is on 'models and data' but the workshop will cover the full range of subjects.
If you would like to attend, please let the organiser Peter Challenor know by 14th September 2007