A Comparison of Ensemble Kalman Filters for Storm Surge Assimilation

Handle URI:
http://hdl.handle.net/10754/346986
Title:
A Comparison of Ensemble Kalman Filters for Storm Surge Assimilation
Authors:
Altaf, M. U.; Butler, T.; Mayo, T.; Luo, X.; Dawson, C.; Heemink, A. W.; Hoteit, Ibrahim ( 0000-0002-3751-4393 )
Abstract:
This study evaluates and compares the performances of several variants of the popular ensembleKalman filter for the assimilation of storm surge data with the advanced circulation (ADCIRC) model. Using meteorological data from Hurricane Ike to force the ADCIRC model on a domain including the Gulf ofMexico coastline, the authors implement and compare the standard stochastic ensembleKalman filter (EnKF) and three deterministic square root EnKFs: the singular evolutive interpolated Kalman (SEIK) filter, the ensemble transform Kalman filter (ETKF), and the ensemble adjustment Kalman filter (EAKF). Covariance inflation and localization are implemented in all of these filters. The results from twin experiments suggest that the square root ensemble filters could lead to very comparable performances with appropriate tuning of inflation and localization, suggesting that practical implementation details are at least as important as the choice of the square root ensemble filter itself. These filters also perform reasonably well with a relatively small ensemble size, whereas the stochastic EnKF requires larger ensemble sizes to provide similar accuracy for forecasts of storm surge.
KAUST Department:
Water Desalination and Reuse Research Center (WDRC); Physical Sciences and Engineering (PSE) Division
Citation:
A Comparison of Ensemble Kalman Filters for Storm Surge Assimilation 2014, 142 (8):2899 Monthly Weather Review
Publisher:
American Meteorological Society
Journal:
Monthly Weather Review
Issue Date:
Aug-2014
DOI:
10.1175/MWR-D-13-00266.1
Type:
Article
ISSN:
0027-0644; 1520-0493
Additional Links:
http://journals.ametsoc.org/doi/abs/10.1175/MWR-D-13-00266.1
Appears in Collections:
Articles; Physical Sciences and Engineering (PSE) Division; Water Desalination and Reuse Research Center (WDRC)

Full metadata record

DC FieldValue Language
dc.contributor.authorAltaf, M. U.en
dc.contributor.authorButler, T.en
dc.contributor.authorMayo, T.en
dc.contributor.authorLuo, X.en
dc.contributor.authorDawson, C.en
dc.contributor.authorHeemink, A. W.en
dc.contributor.authorHoteit, Ibrahimen
dc.date.accessioned2015-03-23T11:28:52Zen
dc.date.available2015-03-23T11:28:52Zen
dc.date.issued2014-08en
dc.identifier.citationA Comparison of Ensemble Kalman Filters for Storm Surge Assimilation 2014, 142 (8):2899 Monthly Weather Reviewen
dc.identifier.issn0027-0644en
dc.identifier.issn1520-0493en
dc.identifier.doi10.1175/MWR-D-13-00266.1en
dc.identifier.urihttp://hdl.handle.net/10754/346986en
dc.description.abstractThis study evaluates and compares the performances of several variants of the popular ensembleKalman filter for the assimilation of storm surge data with the advanced circulation (ADCIRC) model. Using meteorological data from Hurricane Ike to force the ADCIRC model on a domain including the Gulf ofMexico coastline, the authors implement and compare the standard stochastic ensembleKalman filter (EnKF) and three deterministic square root EnKFs: the singular evolutive interpolated Kalman (SEIK) filter, the ensemble transform Kalman filter (ETKF), and the ensemble adjustment Kalman filter (EAKF). Covariance inflation and localization are implemented in all of these filters. The results from twin experiments suggest that the square root ensemble filters could lead to very comparable performances with appropriate tuning of inflation and localization, suggesting that practical implementation details are at least as important as the choice of the square root ensemble filter itself. These filters also perform reasonably well with a relatively small ensemble size, whereas the stochastic EnKF requires larger ensemble sizes to provide similar accuracy for forecasts of storm surge.en
dc.publisherAmerican Meteorological Societyen
dc.relation.urlhttp://journals.ametsoc.org/doi/abs/10.1175/MWR-D-13-00266.1en
dc.rights© 2015 American Meteorological Society Privacy Policy and Disclaimer Headquarters: 45 Beacon Street Boston, MA 02108-3693 DC Office: 1120 G Street, NW, Suite 800 Washington DC, 20005-3826 amsinfo@ametsoc.org Phone: 617-227-2425 Fax: 617-742-8718 Allen Press, Inc. assists in the online publication of AMS journalsen
dc.titleA Comparison of Ensemble Kalman Filters for Storm Surge Assimilationen
dc.typeArticleen
dc.contributor.departmentWater Desalination and Reuse Research Center (WDRC)en
dc.contributor.departmentPhysical Sciences and Engineering (PSE) Divisionen
dc.identifier.journalMonthly Weather Reviewen
dc.eprint.versionPublisher's Version/PDFen
dc.contributor.institutionDelft University of Technology, Delft, Netherlandsen
dc.contributor.institutionDepartment of Mathematical and Statistical Sciences, University of Colorado Denver, Denver, Coloradoen
dc.contributor.institutionInstitute for Computational Engineering and Sciences, The University of Texas at Austin, Austin, Texasen
dc.contributor.institutionInternational Research Institute of Stavanger, Bergen, Norwayen
dc.contributor.affiliationKing Abdullah University of Science and Technology (KAUST)en
kaust.authorAltaf, Muhammaden
kaust.authorHoteit, Ibrahimen
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