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Bayesian updating of atmospheric dispersion after a nuclear accident
SMHI, Forskningsavdelningen, Luftmiljö.ORCID-id: 0000-0003-2738-5556
2004 (engelsk)Inngår i: Journal of the Royal Statistic Society, Series C: Applied Statistics, ISSN 0035-9254, E-ISSN 1467-9876, Vol. 53, s. 583-600Artikkel i tidsskrift (Fagfellevurdert) Published
Abstract [en]

We consider a Bayesian forecasting. system to predict the dispersal of contamination on a large scale grid in the event of an accidental release of radioactivity. The statistical model is built on a physical model for atmospheric dispersion and transport called MATCH. Our spatiotemporal model is a dynamic linear model where the state parameters are the (essentially, deterministic) predictions of MATCH; the distributions of these are updated sequentially in the light of monitoring data. One of the distinguishing features of the model is that the number of these parameters is very large (typically several hundreds of thousands) and we discuss practical issues arising in its implementation as a realtime model. Our procedures have been checked against a variational approach which is used widely in the atmospheric sciences. The results of the model are applied to test data from a tracer experiment.

sted, utgiver, år, opplag, sider
2004. Vol. 53, s. 583-600
Emneord [en]
adjoint equations, atmospheric dispersion, data assimilation, dynamic linear models
HSV kategori
Forskningsprogram
Miljö
Identifikatorer
URN: urn:nbn:se:smhi:diva-1331DOI: 10.1111/j.1467-9876.2004.04837.xISI: 000224094900004OAI: oai:DiVA.org:smhi-1331DiVA, id: diva2:814115
Tilgjengelig fra: 2015-05-26 Laget: 2015-05-26 Sist oppdatert: 2017-12-04bibliografisk kontrollert

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