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<front>
<journal-meta>
<journal-id journal-id-type="publisher">GMD</journal-id>
<journal-title-group>
<journal-title>Geoscientific Model Development</journal-title>
<abbrev-journal-title abbrev-type="publisher">GMD</abbrev-journal-title>
<abbrev-journal-title abbrev-type="nlm-ta">Geosci. Model Dev.</abbrev-journal-title>
</journal-title-group>
<issn pub-type="epub">1991-9603</issn>
<publisher><publisher-name>Copernicus Publications</publisher-name>
<publisher-loc>Göttingen, Germany</publisher-loc>
</publisher>
</journal-meta>
<article-meta>
<article-id pub-id-type="doi">10.5194/gmd-7-2223-2014</article-id>
<title-group>
<article-title>FLEXINVERT: an atmospheric Bayesian inversion framework for determining surface fluxes of trace species using an optimized grid</article-title>
</title-group>
<contrib-group><contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Thompson</surname>
<given-names>R. L.</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
</contrib>
<contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Stohl</surname>
<given-names>A.</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
</contrib>
</contrib-group><aff id="aff1">
<label>1</label>
<addr-line>Norwegian Institute for Air Research, Kjeller, Norway</addr-line>
</aff>
<pub-date pub-type="epub">
<day>30</day>
<month>09</month>
<year>2014</year>
</pub-date>
<volume>7</volume>
<issue>5</issue>
<fpage>2223</fpage>
<lpage>2242</lpage>
<permissions>
<copyright-statement>Copyright: &#x000a9; 2014 R. L. Thompson</copyright-statement>
<copyright-year>2014</copyright-year>
<license license-type="open-access">
<license-p>This work is licensed under the Creative Commons Attribution 3.0 Unported License. To view a copy of this licence, visit <ext-link ext-link-type="uri"  xlink:href="https://creativecommons.org/licenses/by/3.0/">https://creativecommons.org/licenses/by/3.0/</ext-link></license-p>
</license>
</permissions>
<self-uri xlink:href="https://gmd.copernicus.org/articles/7/2223/2014/gmd-7-2223-2014.html">This article is available from https://gmd.copernicus.org/articles/7/2223/2014/gmd-7-2223-2014.html</self-uri>
<self-uri xlink:href="https://gmd.copernicus.org/articles/7/2223/2014/gmd-7-2223-2014.pdf">The full text article is available as a PDF file from https://gmd.copernicus.org/articles/7/2223/2014/gmd-7-2223-2014.pdf</self-uri>
<abstract>
<p>We present a new modular Bayesian inversion framework, called FLEXINVERT,
for estimating the surface fluxes of atmospheric trace species. FLEXINVERT
can be applied to determine the spatio-temporal flux distribution of any
species for which the atmospheric loss (if any) can be described as a linear
process and can be used on continental to regional and even local scales
with little or no modification. The relationship between changes in
atmospheric mixing ratios and fluxes (the so-called source–receptor
relationship) is described by a Lagrangian Particle Dispersion Model (LPDM)
run in a backwards-in-time mode. In this study, we use FLEXPART but any LPDM
could be used. The framework determines the fluxes on a nested grid of
variable resolution, which is optimized based on the source–receptor
relationships for the given observation network. Background mixing ratios
are determined by coupling FLEXPART to the output of a global Eulerian model
(or alternatively, from the observations themselves) and are also optionally
optimized in the inversion. Spatial and temporal error correlations in the
fluxes are taken into account using a simple model of exponential decay with
space and time and, additionally, the aggregation error from the variable
grid is accounted for. To demonstrate the use of FLEXINVERT, we present one
case study in which methane fluxes are estimated in Europe in 2011 and
compare the results to those of an independent inversion ensemble.</p>
</abstract>
<counts><page-count count="20"/></counts>
</article-meta>
</front>
<body/>
<back>
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