Data Assimilation Meetings at Reading
| Date | Meeting type | Speakers |
| 19 November 2014 Maths 314 | Invited speaker |
Naratip Santitissadeekorn (University of Surrey)
Joint state-parameter data assimilation by a two-stage filtering technique (pdf) This presentation is about an approach for a joint state-parameter estimation in a sequential data assimilation framework. The state augmentation technique, in which the state vector is augmented by the model parameters, has been investigated in many previous studies and some success with this technique has been reported. However, many geophysical or climate models contains stochastic parameters such as background and observation error variances or those arising from physical parametrization of sub-grid scale processes, in which case the state augmentation technique may become ineffective. In this talk, we study a two-stage filtering technique that runs particle filtering (PF) to estimate parameters while updating the state estimate using Ensemble Kalman filter (EnKF); these two sub-filters interact. |