<?xml version="1.0" encoding="utf-8" standalone="no"?>
<!DOCTYPE article SYSTEM "http://www.atmos-chem-phys-discuss.net/inc/acpd/copernicus.dtd">
<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>3</volume_number>
		<issue_number>1</issue_number>
		<publication_year>2003</publication_year>
	</journal>
	<doi>10.5194/acpd-3-655-2003</doi>
	<article_url>http://www.atmos-chem-phys-discuss.net/3/655/2003/</article_url>
	<abstract_html>http://www.atmos-chem-phys-discuss.net/3/655/2003/acpd-3-655-2003.html</abstract_html>
	<fulltext_pdf>http://www.atmos-chem-phys-discuss.net/3/655/2003/acpd-3-655-2003.pdf</fulltext_pdf>
	<start_page>655</start_page>
	<end_page>676</end_page>
	<publication_date>2003-02-10</publication_date>
	<article_title content_type="html">Accounting for local meteorological effects in the ozone time-series of Lovozero (Kola Peninsula)</article_title>
	<authors>
		<author numeration="1" affiliations="1">
			<name>O. A. Tarasova</name>
		</author>
		<author numeration="2" affiliations="2">
			<name>A. Y. Karpetchko</name>
		</author>
	</authors>
	<affiliations>
		<affiliation numeration="1" content_type="html">Atmosphere Physics Department, Faculty of Physics, Moscow State University, Moscow, Russia</affiliation>
		<affiliation numeration="2" content_type="html">Polar Geophysical Institute, Apatity, Russia (present address: Finnish Meteorological Institute, Sodankyla, Finland)</affiliation>
	</affiliations>
	<abstract content_type="html">The impact of local meteorological conditions on surface ozone was studied by means of
      regression models creation. Ozone and meteorological parameters measured at Lovozero site
      (250 m a.s.l., 68.5&amp;deg; N, 35.0&amp;deg; E, Kola Peninsula) for the period of
      1999&amp;ndash;2000 were used.  The regression model of daily mean ozone concentrations on the meteorological parameters like
      temperature, relative humidity, and wind speed can explain up to 70% of the ozone
      variability, if the seasonal cycle is also considered. A regression model was created for
      separated time scales of the variables. The separation of short-term, synoptical and seasonal
      components was done by means of Kolmogorov-Zurbenko filtering. The synoptical scale
      variations were chosen as the most informative from the point of their relation with
      meteorological parameters. About 40% of synoptical scale variations of surface ozone can be
      explained by regression model on separated meteo parameters that is 30% more efficient than
      ozone residuals usage.</abstract>
	<references>
	</references>
</article>

