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<article language="en">
	<journal>
		<journal_title>Ocean Science</journal_title>
		<journal_url>www.ocean-sci.net</journal_url>
		<issn>1812-0784</issn>
		<eissn>1812-0792</eissn>
		<volume_number>5</volume_number>
		<issue_number>4</issue_number>
		<publication_year>2009</publication_year>
	</journal>
	<doi>10.5194/os-5-495-2009</doi>
	<article_url>http://www.ocean-sci.net/5/495/2009/</article_url>
	<abstract_html>http://www.ocean-sci.net/5/495/2009/os-5-495-2009.html</abstract_html>
	<fulltext_pdf>http://www.ocean-sci.net/5/495/2009/os-5-495-2009.pdf</fulltext_pdf>
	<start_page>495</start_page>
	<end_page>510</end_page>
	<publication_date>2009-11-03</publication_date>
	<article_title content_type="html">Application of the Gaussian anamorphosis to assimilation in a 3-D coupled physical-ecosystem  model of the North Atlantic with the EnKF: a twin experiment</article_title>
	<authors>
		<author numeration="1" affiliations="1">
			<name>E. Simon</name>
			<email>ehouarn.simon@nersc.no</email>
		</author>
		<author numeration="2" affiliations="1">
			<name>L. Bertino</name>
		</author>
	</authors>
	<affiliations>
		<affiliation numeration="1" content_type="html">Nansen Environmental and Remote Sensing Center, Norway</affiliation>
	</affiliations>
	<abstract content_type="html">We consider the application of the Ensemble Kalman Filter (EnKF) to a coupled
ocean ecosystem model (HYCOM-NORWECOM). Such models, especially the ecosystem
models, are characterized by strongly non-linear interactions active in ocean
blooms and present important difficulties for the use of data assimilation
methods based on linear statistical analysis. Besides the non-linearity of
the model, one is confronted with the model constraints, the analysis state
having to be consistent with the model, especially with respect to the
constraints that some of the variables have to be positive. Furthermore the
non-Gaussian distributions of the biogeochemical variables break an important
assumption of the linear analysis, leading to a loss of optimality of the
filter. We present an extension of the EnKF dealing with these difficulties
by introducing a non-linear change of variables (anamorphosis function) in
order to execute the analysis step in a Gaussian space, namely a space where
the distributions of the transformed variables are Gaussian. We present also
the initial results of the application of this non-Gaussian extension of the
EnKF to the assimilation of simulated chlorophyll surface concentration data
in a North Atlantic configuration of the HYCOM-NORWECOM coupled model.</abstract>
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</article>
