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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>10</volume_number>
		<issue_number>1</issue_number>
		<publication_year>2010</publication_year>
	</journal>
	<doi>10.5194/acpd-10-1559-2010</doi>
	<article_url>http://www.atmos-chem-phys-discuss.net/10/1559/2010/</article_url>
	<abstract_html>http://www.atmos-chem-phys-discuss.net/10/1559/2010/acpd-10-1559-2010.html</abstract_html>
	<fulltext_pdf>http://www.atmos-chem-phys-discuss.net/10/1559/2010/acpd-10-1559-2010.pdf</fulltext_pdf>
	<start_page>1559</start_page>
	<end_page>1593</end_page>
	<publication_date>2010-01-20</publication_date>
	<article_title content_type="html">Cluster analysis of midlatitude oceanic cloud regimes – Part 1: Mean  cloud and meteorological properties</article_title>
	<authors>
		<author numeration="1" affiliations="1,2">
			<name>N. D. Gordon</name>
			<email>n.gordon@leeds.ac.uk</email>
		</author>
		<author numeration="2" affiliations="1">
			<name>J. R. Norris</name>
		</author>
	</authors>
	<affiliations>
		<affiliation numeration="1" content_type="html">Scripps Institution of Oceanography, University of California, San Diego, La Jolla, CA, USA</affiliation>
		<affiliation numeration="2" content_type="html">now at: School of Earth and Environment, University of Leeds, Leeds, UK</affiliation>
	</affiliations>
	<abstract content_type="html">Clouds play an important role in the climate system by
      reducing the amount of shortwave radiation reaching the
      surface and the amount of longwave radiation escaping to
      space. Although dependent on type and location, clouds produce
      more cooling than warming in the global average. Accurate
      simulation of clouds in computer models remains elusive,
      however, pointing to a lack of understanding of the connection
      between large-scale dynamics and cloud properties. This study
      uses a &lt;i&gt;k&lt;/i&gt;-means clustering algorithm to group 21-years of
      satellite cloud data over midlatitude oceans into seven
      clusters and demonstrates that the cloud clusters are
      associated with distinct large-scale dynamical
      conditions. Three clusters correspond to low-level cloud
      regimes with different cloud fraction and cumuliform or
      stratiform characteristics, but all occur under large-scale
      descent and a relatively dry free troposphere. The &quot;small
      cumulus&quot; regime is most prevalent equatorward of 40&amp;deg;
      in all seasons; the &quot;large cumulus&quot; regime is associated
      with a relatively cold troposphere and primarily occurs during
      winter; and the &quot;stratocumulus/stratus&quot; regime occurs
      under a temperature inversion and relatively warm free
      troposphere and predominates during summer. Three clusters
      correspond to vertically extensive cloud regimes with tops in
      the middle or upper troposphere. They differ according to the
      strength of large-scale ascent and enhancement of tropospheric
      temperature and humidity: &quot;deep altostratus&quot; has the
      smallest forcing, &quot;weak frontal&quot; is in the middle, and
      &quot;strong frontal&quot; has the largest forcing. The frontal
      cloud regimes occur most frequently in storm track
      regions. The final cluster, &quot;cirrus&quot; is associated with
      a lower troposphere that is dry and an upper troposphere that
      is moist and experiencing weak ascent and horizontal moist
      advection. This information builds a foundation for producing
      an observational estimate of the midlatitude ocean cloud
      response to warming that is independent of confounding
      meteorological influences.</abstract>
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</article>

