Revision of TR-09-25: A Hybrid Variational/Ensemble Filter Approach to Data Assimilation

Simple item page
dc.contributor.authorSandu, Adrianen
dc.contributor.authorCheng, Haiyanen
dc.contributor.departmentComputer Scienceen
dc.date.accessioned2013-06-19T14:36:38Zen
dc.date.available2013-06-19T14:36:38Zen
dc.date.issued2010-03-01en
dc.description.abstractTwo families of methods are widely used in data assimilation: the four dimensional variational (4D-Var) approach, and the ensemble Kalman filter (EnKF) approach. The two families have been developed largely through parallel research efforts. Each method has its advantages and disadvantages. It is of interest to develop hybrid data assimilation algorithms that can combine the relative strengths of the two approaches. This paper proposes a subspace approach to investigate the theoretical equivalence between the suboptimal 4D-Var method (where only a small number of optimization iterations are performed) and the practical EnKF method (where only a small number of ensemble members are used) in a linear Gaussian setting. The analysis motivates a new hybrid algorithm: the optimization directions obtained from a short window 4D-Var run are used to construct the EnKF initial ensemble. The proposed hybrid method is computationally less expensive than a full 4D-Var, as only short assimilation windows are considered. The hybrid method has the potential to perform better than the regular EnKF due to its look-ahead property. Numerical results show that the proposed hybrid ensemble filter method performs better than the regular EnKF method for both linear and nonlinear test problems.en
dc.format.mimetypeapplication/pdfen
dc.identifierhttp://eprints.cs.vt.edu/archive/00001109/en
dc.identifier.sourceurlhttp://eprints.cs.vt.edu/archive/00001109/01/hybrid_filter.pdfen
dc.identifier.trnumberTR-10-19en
dc.identifier.urihttp://hdl.handle.net/10919/20339en
dc.language.isoenen
dc.publisherDepartment of Computer Science, Virginia Polytechnic Institute & State Universityen
dc.relation.ispartofComputer Science Technical Reportsen
dc.rightsIn Copyrighten
dc.rights.urihttp://rightsstatements.org/vocab/InC/1.0/en
dc.subjectNumerical analysisen
dc.titleRevision of TR-09-25: A Hybrid Variational/Ensemble Filter Approach to Data Assimilationen
dc.typeTechnical reporten
dc.type.dcmitypeTexten

Files

Original bundle
Now showing 1 - 1 of 1
Thumbnail Image
Name:
hybrid_filter.pdf
Size:
277.34 KB
Format:
Adobe Portable Document Format
Download

Collections

Computer Science Technical Reports
Scholarly Works, Computational Science Laboratory