Show simple item record

dc.contributor.authorAltaf, Muhammad
dc.contributor.authorButler, T.
dc.contributor.authorMayo, T.
dc.contributor.authorLuo, X.
dc.contributor.authorDawson, C.
dc.contributor.authorHeemink, A. W.
dc.contributor.authorHoteit, Ibrahim
dc.date.accessioned2015-03-23T11:28:52Z
dc.date.available2015-03-23T11:28:52Z
dc.date.issued2014-08
dc.identifier.citationA Comparison of Ensemble Kalman Filters for Storm Surge Assimilation 2014, 142 (8):2899 Monthly Weather Review
dc.identifier.issn0027-0644
dc.identifier.issn1520-0493
dc.identifier.doi10.1175/MWR-D-13-00266.1
dc.identifier.urihttp://hdl.handle.net/10754/346986
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.
dc.publisherAmerican Meteorological Society
dc.relation.urlhttp://journals.ametsoc.org/doi/abs/10.1175/MWR-D-13-00266.1
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 journals
dc.titleA Comparison of Ensemble Kalman Filters for Storm Surge Assimilation
dc.typeArticle
dc.contributor.departmentEarth Fluid Modeling and Prediction Group
dc.contributor.departmentEarth Science and Engineering Program
dc.contributor.departmentPhysical Science and Engineering (PSE) Division
dc.contributor.departmentWater Desalination and Reuse Research Center (WDRC)
dc.identifier.journalMonthly Weather Review
dc.eprint.versionPublisher's Version/PDF
dc.contributor.institutionDelft University of Technology, Delft, Netherlands
dc.contributor.institutionDepartment of Mathematical and Statistical Sciences, University of Colorado Denver, Denver, Colorado
dc.contributor.institutionInstitute for Computational Engineering and Sciences, The University of Texas at Austin, Austin, Texas
dc.contributor.institutionInternational Research Institute of Stavanger, Bergen, Norway
dc.contributor.affiliationKing Abdullah University of Science and Technology (KAUST)
kaust.personAltaf, Muhammad
kaust.personHoteit, Ibrahim
refterms.dateFOA2018-06-13T10:52:30Z


Files in this item

Thumbnail
Name:
mwr-d-13-002661.pdf
Size:
1.503Mb
Format:
PDF
Description:
Main article

This item appears in the following Collection(s)

Show simple item record