Data Assimilation Meetings at Reading
If you would like to be informed about future meetings please email and ask to be added to the mailing list.
Meetings
These are usually held in the Department of Meteorology in room 1L43 from 11.00 to 12.00, but please email to confirm time and venue.
| Date | Meeting type | Speakers |
| 19 April 2012 | DARC seminar |
Neil Bowler (Met Office) Developing 4D-En-Var as a potential replacement to 4D-Var and the ETKF |
| 3 May 2012 | DARC seminar |
Jean-Francois Caron (Met Office at Reading) Mismatching perturbations at the lateral boundaries in limited-area ensemble forecasting |
| 9 May 2012 | DARC seminar |
Robin Hogan (Radar and clouds group, UoR) Fast reverse-mode automatic differentiation using expression templates in C++ |
| 16 May 2012 | Informal DARC meeting |
David Livings (UoR) How to Turn an Ensemble Kalman Filter into a Particle Filter |
| 30 May 2012 | Special double DARC seminar |
11-11.50: Alberto Carrassi (IC3 Barcelona) Accounting for model error in data assimilation We present the progress and outcomes achieved in the framework of the Belgian Science Policy Project "A new approach to data assimilation accounting for the dynamics and statistics of the model error". A new approach to deal with model error due to uncertain parameters and to the presence of unresolved scales is discussed. An alternative formulation of the extended Kalman filter, referred to as Short-Time Augmented Extended Kalman Filter (ST-AEKF), for state and parameter estimation is presented first. In this algorithm, the evolution of the model error generated by the uncertain parameters is described using a truncated short-time Taylor expansion within the assimilation interval. This allows for a simplification of the forward propagation of the augmented error covariance matrix with respect to the classical state augmented approach. The model error due to unresolved scales is then considered. By treating it as a deterministic fully correlated process an equation for the model error covariance required in the Kalman filter update is derived along with an approximation suitable for application with large scale dynamical systems typical in environmental modeling. A similar approach is then implemented in the context of variational data assimilation procedure and a new formulation of the weak-constraint 4D-Var is discussed. 11.50-12: BREAK 12-12.50: Vanja Blazica (Uni. of Ljubljana) Analysis of divergent energy spectra in a limited area model |
| 6th June 2012 | DARC seminar |
Prof. Arnaud Doucet (Oxford University) Particle Markov chain Monte Carlo methods Markov chain Monte Carlo and sequential Monte Carlo methods have emerged as the two main tools to sample from high dimensional probability distributions.Although asymptotic convergence of Markov chain Monte Carlo algorithms is ensured under weak assumptions, the performance of these algorithms is unreliable when the proposal distributions that are used to explore the space are poorly chosen and/or if highly correlated variables are updated independently. We show here how it is possible to build efficient high dimensional proposal distributions by using sequential Monte Carlo methods. This allows us not only to improve over standard Markov chain Monte Carlo schemes but also to make Bayesian inference feasible for a large class of statistical models where this was not previously so.We demonstrate these algorithms on a non-linear state space model and a Lévy-driven stochastic volatility model. |
| 13 June 2012 | DARC seminar |
David Fairbairn (Uni. of Surrey) and Stephen Pring (Met Office) Comparing 4D-Var with 4D-En-Var using a toy model. |
| 20 June 2012 | RMets meeting | Challenges for data assimiation: from convective-scale to climate. Madjeski Lecture Theatre, University of Reading, 14:00-17:45. |
| 27 June 2012 | DARC seminar |
Jean-Francois Caron (Met Office at Reading) TBA |
| 18 July 2012 | DARC seminar |
John Hemmings (NOC, Southampton) TBA |
Other confirmed speakers:
none