Multilevel ensemble Kalman filtering
Abstract
This study embeds a multilevel Monte Carlo sampling strategy into the Monte Carlo step of the ensemble Kalman filter (EnKF) in the setting of finite dimensional signal evolution and noisy discretetime observations. The signal dynamics is assumed to be governed by a stochastic differential equation (SDE), and a hierarchy of time grids is introduced for multilevel numerical integration of that SDE. Finally, the resulting multilevel EnKF is proved to asymptotically outperform EnKF in terms of computational cost versus approximation accuracy. The theoretical results are illustrated numerically.
 Authors:

 Univ. of Oslo (Norway)
 Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)
 King Abdullah University of Science and Technology (KAUST), Thuwal (Saudi Arabia)
 Publication Date:
 Research Org.:
 Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)
 Sponsoring Org.:
 USDOE Laboratory Directed Research and Development (LDRD) Program
 OSTI Identifier:
 1302921
 Grant/Contract Number:
 AC0500OR22725
 Resource Type:
 Accepted Manuscript
 Journal Name:
 SIAM Journal on Numerical Analysis
 Additional Journal Information:
 Journal Volume: 54; Journal Issue: 3; Journal ID: ISSN 00361429
 Publisher:
 Society for Industrial and Applied Mathematics
 Country of Publication:
 United States
 Language:
 English
 Subject:
 97 MATHEMATICS AND COMPUTING; 71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSICS; Monte Carlo; multilevel; ltering; Kalman lter; ensemble Kalman lter
Citation Formats
Hoel, Hakon, Law, Kody J. H., and Tempone, Raul. Multilevel ensemble Kalman filtering. United States: N. p., 2016.
Web. doi:10.1137/15M100955X.
Hoel, Hakon, Law, Kody J. H., & Tempone, Raul. Multilevel ensemble Kalman filtering. United States. doi:10.1137/15M100955X.
Hoel, Hakon, Law, Kody J. H., and Tempone, Raul. Tue .
"Multilevel ensemble Kalman filtering". United States. doi:10.1137/15M100955X. https://www.osti.gov/servlets/purl/1302921.
@article{osti_1302921,
title = {Multilevel ensemble Kalman filtering},
author = {Hoel, Hakon and Law, Kody J. H. and Tempone, Raul},
abstractNote = {This study embeds a multilevel Monte Carlo sampling strategy into the Monte Carlo step of the ensemble Kalman filter (EnKF) in the setting of finite dimensional signal evolution and noisy discretetime observations. The signal dynamics is assumed to be governed by a stochastic differential equation (SDE), and a hierarchy of time grids is introduced for multilevel numerical integration of that SDE. Finally, the resulting multilevel EnKF is proved to asymptotically outperform EnKF in terms of computational cost versus approximation accuracy. The theoretical results are illustrated numerically.},
doi = {10.1137/15M100955X},
journal = {SIAM Journal on Numerical Analysis},
number = 3,
volume = 54,
place = {United States},
year = {2016},
month = {6}
}
Other availability
Cited by: 7 works
Citation information provided by
Web of Science
Web of Science
Save to My Library
You must Sign In or Create an Account in order to save documents to your library.