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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>4</issue_number>
		<publication_year>2007</publication_year>
	</journal>
	<doi>10.5194/acpd-7-12541-2007</doi>
	<article_url>http://www.atmos-chem-phys-discuss.net/7/12541/2007/</article_url>
	<abstract_html>http://www.atmos-chem-phys-discuss.net/7/12541/2007/acpd-7-12541-2007.html</abstract_html>
	<fulltext_pdf>http://www.atmos-chem-phys-discuss.net/7/12541/2007/acpd-7-12541-2007.pdf</fulltext_pdf>
	<start_page>12541</start_page>
	<end_page>12572</end_page>
	<publication_date>2007-08-23</publication_date>
	<article_title content_type="html">A climatology of surface ozone in the extra tropics: cluster analysis of observations and model results</article_title>
	<authors>
		<author numeration="1" affiliations="1,2">
			<name>O. A. Tarasova</name>
			<email>tarasova@mpch-mainz.mpg.de</email>
		</author>
		<author numeration="2" affiliations="1">
			<name>C. A. M. Brenninkmeijer</name>
		</author>
		<author numeration="3" affiliations="1">
			<name>P. Jöckel</name>
		</author>
		<author numeration="4" affiliations="3">
			<name>A. M. Zvyagintsev</name>
		</author>
		<author numeration="5" affiliations="2">
			<name>G. I. Kuznetsov</name>
		</author>
	</authors>
	<affiliations>
		<affiliation numeration="1" content_type="html">Max Planck Institute for Chemistry, Mainz, Germany</affiliation>
		<affiliation numeration="2" content_type="html">Lomonosov Moscow State University, Faculty of Physics, Moscow, Russia</affiliation>
		<affiliation numeration="3" content_type="html">Central Aerological Observatory, Dolgoprudny, Russia</affiliation>
	</affiliations>
	<abstract content_type="html">Important aspects of the seasonal variations of surface ozone are discussed.
The underlying analysis is based on the long-term (1990&amp;ndash;2004) ozone records
of Co-operative Programme for Monitoring and Evaluation of the Long-range
Transmission of Air Pollutants in Europe (EMEP) and the World Data Center of
Greenhouse Gases which do have a strong Northern Hemisphere bias. Seasonal
variations are pronounced at most of the 114 locations for any time of the
day. Seasonal-diurnal variability classification using hierarchical
agglomeration clustering reveals 5 distinct clusters: clean/rural,
semi-polluted non-elevated, semi-polluted semi-elevated, elevated and
polar/remote marine types. For the cluster &quot;clean/rural&quot; the seasonal
maximum is observed in April, both for night and day. For those sites with a
double maximum or a wide spring-summer maximum, the one in spring appears
both for day and night, while the one in summer is more pronounced for
daytime and hence can be attributed to photochemical processes. For the
spring maximum photochemistry is a less plausible explanation as no
dependence of the maximum timing is observed. More probably the spring
maximum is caused by dynamical/transport processes. Using data from the 3-D
atmospheric chemistry general circulation model ECHAM5/MESSy1 covering the
period of 1998&amp;ndash;2005 a comparison has been performed for the identified
clusters. For the model data four distinct classes of variability are
detected. The majority of cases are covered by the regimes with a spring
seasonal maximum or with a broad spring-summer maximum (with prevailing
summer). The regime with winter&amp;ndash;early spring maximum is reproduced by the
model for southern hemispheric locations. Background and semi-polluted sites
appear in the model in the same cluster. The seasonality in this model
cluster is characterized by a pronounced spring (May) maximum. For the model
cluster that covers partly semi-elevated semi-polluted sites the role of the
photochemical production/destruction seems to be overestimated. Taking into
consideration the differences in the data sampling procedure the carried out
comparison demonstrates the ability of the model to reproduce the main
regimes of surface ozone variability quite well.</abstract>
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</article>

