Data assimilation (DA) is a technique for combining mathematical models of physical systems with measurements of those systems in order to estimate either the state of the systems or the parameters in the models. Such techniques have been used extensively in weather and climate prediction, and are now being used in a wide variety of applications, including geological exploration (especially oil reservoir modelling), river/tide flow modelling, traffic flow modelling and monitoring air quality. The mathematics underpinning these techniques includes nonlinear partial differential equations, stochastic processes, statistical mechanics, control theory, statistical estimation theory, optimization, and numerical analysis. Nearly 50 years ago Kalman published his seminal work on linear filtering and such techniques have played a major role in environmental modelling. However, the need to represent nonlinear, non-Gaussian processes in high-resolution models presents major challenges, and under Topics we highlight the key issues that will form the basis of the Symposium.

List of Participants