Open AccessSampling Errors in Ensemble Kalman Filtering. Part II: Application to a Barotropic Model
Author(s) -
William Sacher,
Peter Bartello
Publication year - 2009
Publication title -
monthly weather review
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.862
H-Index - 179
eISSN - 1520-0493
pISSN - 0027-0644
DOI - 10.1175/2008mwr2685.1
Subject(s) - ensemble kalman filter , kalman filter , covariance , barotropic fluid , extended kalman filter , divergence (linguistics) , data assimilation , invariant extended kalman filter , inflation (cosmology) , fast kalman filter , computer science , covariance intersection , alpha beta filter , mathematics , algorithm , statistics , physics , meteorology , moving horizon estimation , linguistics , philosophy , theoretical physics , mechanics
In the current study, the authors are concerned with the comparison of the average performance of stochastic versions of the ensemble Kalman filter with and without covariance inflation, as well as the double ensemble Kalman filter. The theoretical results obtained in Part I of this study are confronted with idealized simulations performed with a perfect barotropic quasigeostrophic model. Results obtained are very consistent with the analytic expressions found in Part I. It is also shown that both the double ensemble Kalman filter and covariance inflation techniques can avoid filter divergence. Nevertheless, covariance inflation gives efficient results in terms of accuracy and reliability for a much lower computational cost than the double ensemble Kalman filter and for smaller ensemble sizes.