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<front>
<journal-meta>
<journal-id journal-id-type="publisher">ACP</journal-id>
<journal-title-group>
<journal-title>Atmospheric Chemistry and Physics</journal-title>
<abbrev-journal-title abbrev-type="publisher">ACP</abbrev-journal-title>
</journal-title-group>
<issn pub-type="epub">1680-7324</issn>
<publisher><publisher-name>Copernicus GmbH</publisher-name>
<publisher-loc>Göttingen, Germany</publisher-loc>
</publisher>
</journal-meta>
<article-meta>
<article-id pub-id-type="doi">10.5194/acp-11-3731-2011</article-id>
<title-group>
<article-title>Toward unification of the multiscale modeling of the atmosphere</article-title>
</title-group>
<contrib-group><contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Arakawa</surname>
<given-names>A.</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
<xref ref-type="aff" rid="aff3">
<sup>3</sup>
</xref>
</contrib>
<contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Jung</surname>
<given-names>J.-H.</given-names>
</name>
<xref ref-type="aff" rid="aff2">
<sup>2</sup>
</xref>
</contrib>
<contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Wu</surname>
<given-names>C.-M.</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
</contrib>
</contrib-group><aff id="aff1">
<label>1</label>
<addr-line>University of California, Los Angeles, California, USA</addr-line>
</aff>
<aff id="aff2">
<label>2</label>
<addr-line>Colorado State University, Fort Collins, Colorado, USA</addr-line>
</aff>
<aff id="aff3">
<label>3</label>
<addr-line>Invited contribution by A. Arakawa, recipient of the EGU Vilhelm Bjerknes Medal 2010.</addr-line>
</aff>
<pub-date pub-type="epub">
<day>21</day>
<month>04</month>
<year>2011</year>
</pub-date>
<volume>11</volume>
<issue>8</issue>
<fpage>3731</fpage>
<lpage>3742</lpage>
<permissions>
<license xlink:type="simple">
<license-p>This is an open-access article ditributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.</license-p>
</license>
</permissions>
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<self-uri xlink:href="http://www.atmos-chem-phys.net/11/3731/2011/acp-11-3731-2011.pdf">The full text article is available as a PDF file from http://www.atmos-chem-phys.net/11/3731/2011/acp-11-3731-2011.pdf</self-uri>
<abstract>
<p>As far as the representation of deep moist convection is
concerned, only two kinds of model physics are used at present: highly
parameterized as in the conventional general circulation models (GCMs) and
explicitly simulated as in the cloud-resolving models (CRMs). Ideally, these
two kinds of model physics should be unified so that a continuous transition
of model physics from one kind to the other takes place as the resolution
changes. With such unification, the GCM can converge to a global CRM (GCRM)
as the grid size is refined. This paper suggests two possible routes to
achieve the unification. ROUTE I continues to follow the parameterization
approach, but uses a unified parameterization that is applicable to any
horizontal resolutions between those typically used by GCMs and CRMs. It is
shown that a key to construct such a unified parameterization is to
eliminate the assumption of small fractional area covered by convective
clouds, which is commonly used in the conventional cumulus parameterizations
either explicitly or implicitly. A preliminary design of the unified
parameterization is presented, which demonstrates that such an assumption
can be eliminated through a relatively minor modification of the existing
mass-flux based parameterizations. Partial evaluations of the unified
parameterization are also presented. ROUTE II follows the &quot;multi-scale
modeling framework (MMF)&quot; approach, which takes advantage of explicit
representation of deep moist convection and associated cloud-scale processes
by CRMs. The Quasi-3-D (Q3-D) MMF is an attempt to broaden the applicability
of MMF without necessarily using a fully three-dimensional CRM. This is
accomplished using a network of cloud-resolving grids with large gaps. An
outline of the Q3-D algorithm and highlights of preliminary results are
reviewed.</p>
</abstract>
<counts><page-count count="12"/></counts>
</article-meta>
</front>
<body/>
<back>
<ref-list>
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</back>
</article>