The Error-Subspace Transform Kalman Filter


Contact
Lars.Nerger [ at ] awi.de

Abstract

Ensemble square-root Kalman filters are currently the computationally most efficient ensemble-based Kalman filter methods. In particular, the Ensemble Transform Kalman Filter (ETKF) is known to provide a minimum ensemble transformation in a very efficient way. In order to further improve the computational efficiency, the Error-Subspace Transform Kalman Filter (ESTKF) was developed. The ESTKF solves the optimization problem of the Kalman filter in the error-subspace that is represented by the ensemble. As the ETKF, the ESTKF provides the minimum ensemble transformation, but at a slightly lower cost. We discuss the ESTKF and its localized counter part the LESTKF using numerical experiments with the parallel data assimilation framework PDAF and models of different complexity.



Item Type
Conference (Poster)
Authors
Divisions
Programs
Publication Status
Published
Event Details
Ocean Sciences Meeting, Salt Lake City, UT, USA, February 20-24, 2012.
Eprint ID
25886
Cite as
Nerger, L. , Hiller, W. and Schröter, J. (2012): The Error-Subspace Transform Kalman Filter , Ocean Sciences Meeting, Salt Lake City, UT, USA, February 20-24, 2012 .


Download
[thumbnail of poster.pdf]
Preview
PDF
poster.pdf

Download (72kB) | Preview
Cite this document as:

Share
Add to AnyAdd to TwitterAdd to FacebookAdd to LinkedinAdd to PinterestAdd to Email

Research Platforms
N/A

Campaigns
N/A


Actions
Edit Item Edit Item