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Article: Data assimilation in the atmospheric dispersion model for nuclear accident assessments

TitleData assimilation in the atmospheric dispersion model for nuclear accident assessments
Authors
KeywordsData assimilation
Dispersion model
Ensemble Kalman filter
Nuclear accident
Issue Date2007
PublisherPergamon. The Journal's web site is located at http://www.elsevier.com/locate/atmosenv
Citation
Atmospheric Environment, 2007, v. 41 n. 11, p. 2438-2446 How to Cite?
AbstractUncertainty factors in atmospheric dispersion models may influence the reliability of model prediction. The ability of a model in assimilating measurement data will be helpful to improve model prediction. In this paper, data assimilation based on ensemble Kalman filter (EnKF) is introduced to a Monte Carlo atmospheric dispersion model (MCADM) designed for assessment of consequences after an accident release of radionuclides. Twin experiment has been performed in which simulated ground-level dose rates have been assimilated. Uncertainties in the source term and turbulence intensity of wind field are considered, respectively. Methodologies and preliminary results of the application are described. It is shown that it is possible to reduce the discrepancy between the model forecast and the true situation by data assimilation. About 80% of error caused by the uncertainty in the source term is reduced, and the value for that caused by uncertainty in the turbulence intensity is about 50%. © 2006 Elsevier Ltd. All rights reserved.
Persistent Identifierhttp://hdl.handle.net/10722/80411
ISSN
2015 Impact Factor: 3.459
2015 SCImago Journal Rankings: 1.999
ISI Accession Number ID
References

 

DC FieldValueLanguage
dc.contributor.authorZheng, DQen_HK
dc.contributor.authorLeung, JKCen_HK
dc.contributor.authorLee, BYen_HK
dc.contributor.authorLam, HYen_HK
dc.date.accessioned2010-09-06T08:06:10Z-
dc.date.available2010-09-06T08:06:10Z-
dc.date.issued2007en_HK
dc.identifier.citationAtmospheric Environment, 2007, v. 41 n. 11, p. 2438-2446en_HK
dc.identifier.issn1352-2310en_HK
dc.identifier.urihttp://hdl.handle.net/10722/80411-
dc.description.abstractUncertainty factors in atmospheric dispersion models may influence the reliability of model prediction. The ability of a model in assimilating measurement data will be helpful to improve model prediction. In this paper, data assimilation based on ensemble Kalman filter (EnKF) is introduced to a Monte Carlo atmospheric dispersion model (MCADM) designed for assessment of consequences after an accident release of radionuclides. Twin experiment has been performed in which simulated ground-level dose rates have been assimilated. Uncertainties in the source term and turbulence intensity of wind field are considered, respectively. Methodologies and preliminary results of the application are described. It is shown that it is possible to reduce the discrepancy between the model forecast and the true situation by data assimilation. About 80% of error caused by the uncertainty in the source term is reduced, and the value for that caused by uncertainty in the turbulence intensity is about 50%. © 2006 Elsevier Ltd. All rights reserved.en_HK
dc.languageengen_HK
dc.publisherPergamon. The Journal's web site is located at http://www.elsevier.com/locate/atmosenven_HK
dc.relation.ispartofAtmospheric Environmenten_HK
dc.subjectData assimilationen_HK
dc.subjectDispersion modelen_HK
dc.subjectEnsemble Kalman filteren_HK
dc.subjectNuclear accidenten_HK
dc.titleData assimilation in the atmospheric dispersion model for nuclear accident assessmentsen_HK
dc.typeArticleen_HK
dc.identifier.openurlhttp://library.hku.hk:4550/resserv?sid=HKU:IR&issn=1352-2310&volume=41&spage=2438&epage=2446&date=2007&atitle=Data+assimilation+in+the+atmospheric+dispersion+model+for+nuclear+accident+assessmentsen_HK
dc.identifier.emailLeung, JKC: jkcleung@hku.hken_HK
dc.identifier.authorityLeung, JKC=rp00732en_HK
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.doi10.1016/j.atmosenv.2006.05.076en_HK
dc.identifier.scopuseid_2-s2.0-33847034344en_HK
dc.identifier.hkuros128321en_HK
dc.relation.referenceshttp://www.scopus.com/mlt/select.url?eid=2-s2.0-33847034344&selection=ref&src=s&origin=recordpageen_HK
dc.identifier.volume41en_HK
dc.identifier.issue11en_HK
dc.identifier.spage2438en_HK
dc.identifier.epage2446en_HK
dc.identifier.isiWOS:000245157700016-
dc.publisher.placeUnited Kingdomen_HK
dc.identifier.scopusauthoridZheng, DQ=15849854400en_HK
dc.identifier.scopusauthoridLeung, JKC=24080627200en_HK
dc.identifier.scopusauthoridLee, BY=15848940000en_HK
dc.identifier.scopusauthoridLam, HY=36986584100en_HK

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