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<article language="en">
	<journal>
		<journal_title>Atmospheric Chemistry and Physics Discussions</journal_title>
		<journal_url>www.atmos-chem-phys-discuss.net</journal_url>
		<issn>1680-7367</issn>
		<eissn>1680-7375</eissn>
		<volume_number>7</volume_number>
		<issue_number>2</issue_number>
		<publication_year>2007</publication_year>
	</journal>
	<doi>10.5194/acpd-7-5701-2007</doi>
	<article_url>http://www.atmos-chem-phys-discuss.net/7/5701/2007/</article_url>
	<abstract_html>http://www.atmos-chem-phys-discuss.net/7/5701/2007/acpd-7-5701-2007.html</abstract_html>
	<fulltext_pdf>http://www.atmos-chem-phys-discuss.net/7/5701/2007/acpd-7-5701-2007.pdf</fulltext_pdf>
	<start_page>5701</start_page>
	<end_page>5737</end_page>
	<publication_date>2007-04-27</publication_date>
	<article_title content_type="html">Seeking for the rational basis of the median model: the optimal combination of multi-model ensemble results</article_title>
	<authors>
		<author numeration="1" affiliations="1">
			<name>A. Riccio</name>
		</author>
		<author numeration="2" affiliations="1">
			<name>G. Giunta</name>
		</author>
		<author numeration="3" affiliations="2">
			<name>S. Galmarini</name>
		</author>
	</authors>
	<affiliations>
		<affiliation numeration="1" content_type="html">Dept. of Applied Science, University of Naples &quot;Parthenope&quot;, Napoli, Italy</affiliation>
		<affiliation numeration="2" content_type="html">European Commission - DG Joint Research Centre, Institute for Environment and Sustainability, Ispra, Italy</affiliation>
	</affiliations>
	<abstract content_type="html">In this paper we present an approach for the statistical analysis of multi-model ensemble
results.
The models considered here are operational long-range transport and dispersion models, also
used for the real-time simulation of pollutant dispersion or the accidental release
of radioactive nuclides.
&lt;br&gt;&lt;br&gt;
We first introduce the theoretical basis (with its roots sinking into the Bayes theorem)
and then apply this approach to the analysis of model results obtained during the ETEX-1
exercise.
We recover some interesting results, supporting the heuristic approach
called &quot;median model&quot;, originally introduced in Galmarini et al. (2004a, b).
&lt;br&gt;&lt;br&gt;
This approach also provides a way to systematically reduce (and quantify)
model uncertainties, thus
supporting the decision-making process and/or regulatory-purpose activities
in a very effective manner.</abstract>
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</article>

