Data Assimilation Meetings at Reading
| Date | Meeting type | Speakers |
| 28 May 2014 | Internal speaker |
Noeleene Mallia (University of Reading)
Assessing the Performance of Data Assimilation Algorithms with Linear Error Feedback A problem of many real world data assimilation experiments is that they cannot be replicated. An evaluation of model performance against the available observations will yield optimistic results since the observations have been used to find the solution. A possible solution to this problem is to estimate the optimism using the in-sample error. This talk will consider estimating the optimism for data assimilation algorithms that employ linear error feedback. This type of feedback is found frequently in data assimilation; examples include 3D-Var and the Kalman Filter. Numerical experiments implementing this approach are presented. Specifically, this talk considers an algorithm where we employ linear error feedback using a constant gain matrix. We use results from control theory along with our estimate of the out of sample error to select a gain matrix which yields minimum out-of-sample error. |