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dc.contributor.authorSicardi, Valentina
dc.contributor.authorOrtiz, Joana
dc.contributor.authorRincón, Ángel
dc.contributor.authorJorba Casellas, Oriol
dc.contributor.authorPay Pérez, M. Teresa
dc.contributor.authorGassó Domingo, Santiago
dc.contributor.authorBaldasano Recio, José María
dc.contributor.otherUniversitat Politècnica de Catalunya. Departament de Projectes d'Enginyeria
dc.date.accessioned2011-04-08T09:08:31Z
dc.date.available2011-04-08T09:08:31Z
dc.date.created2011-02-15
dc.date.issued2011-02-15
dc.identifier.citationSicardi, V. [et al.]. Ground-level ozone concentration over Spain: an application of Kalman Filter post-processing to reduce model uncertainties. "Geoscientific model development discussions", 15 Febrer 2011, vol. 4, p. 343-384.
dc.identifier.issn1991-9611
dc.identifier.urihttp://hdl.handle.net/2117/12315
dc.description.abstractThe CALIOPE air quality modelling system, namely WRF-ARW/HERMESEMEP/ CMAQ/BSC-DREAM8b, has been used to perform the simulation of ground level O3 concentration for the year 2004, over the Iberian Peninsula. We use this system to study 5 the daily ground-level O3 maximum. We investigate the use of a post-processing such as the Kalman Filter bias-adjustment technique to improve the simulated O3 maximum. The Kalman Filter bias-adjustment technique is a recursive algorithm to optimally estimate bias-adjustment terms from previous measurements and model results. The bias-adjustment technique is found to improve the simulated O3 maximum for the en10 tire year and the whole domain. The corrected simulation presents improvements in statistical indicators such as correlation, root mean square error, mean bias, standard deviation, and gross error. After the post-processing the exceedances of O3 concentration limits, as established by the European Directive 2008/50/CE, are better reproduced and the uncertainty of the modelling system is reduced from 20% to 7.5%. Such un15 certainty in the model results is under the established EU limit of the 50%. Significant improvements in the O3 average daily cycle and in its amplitude are also observed after the post-processing. The systematic improvements in the O3 maximum simulations suggest that the Kalman Filter post-processing method is a suitable technique to reproduce accurate estimate of ground-level O3 concentration.
dc.format.extent42 p.
dc.language.isoeng
dc.rightsAttribution-NonCommercial-NoDerivs 3.0 Spain
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/3.0/es/
dc.subjectÀrees temàtiques de la UPC::Enginyeria química::Química del medi ambient::Química atmosfèrica
dc.subject.lcshAir quality
dc.subject.lcshOzone
dc.titleGround-level ozone concentration over Spain: an application of Kalman Filter post-processing to reduce model uncertainties
dc.typeArticle
dc.subject.lemacAire -- Qualitat
dc.subject.lemacOzó atmosfèric
dc.contributor.groupUniversitat Politècnica de Catalunya. MTA - Modelització i Tecnologia Ambiental
dc.identifier.doi10.5194/gmdd-4-343-2011
dc.description.peerreviewedPeer Reviewed
dc.rights.accessOpen Access
drac.iddocument5456043
dc.description.versionPostprint (published version)
upcommons.citation.authorSicardi, V.; Ortiz, J.; Rincón, Á.; Jorba i Casellas, O.; Pay, M.; Gassó, S.; Baldasano, J.
upcommons.citation.publishedtrue
upcommons.citation.publicationNameGeoscientific model development discussions
upcommons.citation.volume4
upcommons.citation.startingPage343
upcommons.citation.endingPage384


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Except where otherwise noted, content on this work is licensed under a Creative Commons license: Attribution-NonCommercial-NoDerivs 3.0 Spain