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<!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>6</volume_number>
		<issue_number>3</issue_number>
		<publication_year>2006</publication_year>
	</journal>
	<doi>10.5194/acpd-6-4341-2006</doi>
	<article_url>http://www.atmos-chem-phys-discuss.net/6/4341/2006/</article_url>
	<abstract_html>http://www.atmos-chem-phys-discuss.net/6/4341/2006/acpd-6-4341-2006.html</abstract_html>
	<fulltext_pdf>http://www.atmos-chem-phys-discuss.net/6/4341/2006/acpd-6-4341-2006.pdf</fulltext_pdf>
	<start_page>4341</start_page>
	<end_page>4373</end_page>
	<publication_date>2006-05-31</publication_date>
	<article_title content_type="html">Impact of cloud-borne aerosol representation on aerosol direct and indirect effects</article_title>
	<authors>
		<author numeration="1" affiliations="1">
			<name>S. J. Ghan</name>
		</author>
		<author numeration="2" affiliations="1">
			<name>R. C. Easter</name>
		</author>
	</authors>
	<affiliations>
		<affiliation numeration="1" content_type="html">Atmospheric Science and Global Change Division, Pacific Northwest National Laboratory, Richland, Washington, USA</affiliation>
	</affiliations>
	<abstract content_type="html">Aerosol particles attached to cloud droplets are much more likely to be
removed from the atmosphere and are much less efficient at scattering
sunlight than if unattached. Models used to estimate direct and indirect
effects of aerosols employ a variety of representations of such cloud-borne
particles. Here we use a global aerosol model with a relatively complete
treatment of cloud-borne particles to estimate the sensitivity of simulated
aerosol, cloud and radiation fields to various approximations to the
representation of cloud-borne particles. We find that neglecting transport
of cloud-borne particles introduces little error, but that diagnosing
cloud-borne particles produces global mean biases of 20% and local errors
of up to 40% for many variables of interest. A treatment that predicts
the total mass concentration of cloud-borne particles for each mode yields
smaller errors and runs 20% faster than the complete treatment.</abstract>
	<references>
	</references>
</article>

