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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>6</volume_number>
		<issue_number>3</issue_number>
		<publication_year>2006</publication_year>
	</journal>
	<doi>10.5194/acpd-6-3709-2006</doi>
	<article_url>http://www.atmos-chem-phys-discuss.net/6/3709/2006/</article_url>
	<abstract_html>http://www.atmos-chem-phys-discuss.net/6/3709/2006/acpd-6-3709-2006.html</abstract_html>
	<fulltext_pdf>http://www.atmos-chem-phys-discuss.net/6/3709/2006/acpd-6-3709-2006.pdf</fulltext_pdf>
	<start_page>3709</start_page>
	<end_page>3756</end_page>
	<publication_date>2006-05-11</publication_date>
	<article_title content_type="html">Comparing atmospheric transport models for future regional inversions over Europe. Part&amp;nbsp;1: Mapping the CO&lt;sub&gt;2&lt;/sub&gt; atmospheric signals</article_title>
	<authors>
		<author numeration="1" affiliations="1">
			<name>C. Geels</name>
		</author>
		<author numeration="2" affiliations="2">
			<name>M. Gloor</name>
		</author>
		<author numeration="3" affiliations="3">
			<name>P. Ciais</name>
		</author>
		<author numeration="4" affiliations="3">
			<name>P. Bousquet</name>
		</author>
		<author numeration="5" affiliations="3">
			<name>P. Peylin</name>
		</author>
		<author numeration="6" affiliations="4">
			<name>A. T. Vermeulen</name>
		</author>
		<author numeration="7" affiliations="3">
			<name>R. Dargaville</name>
		</author>
		<author numeration="8" affiliations="5">
			<name>T. Aalto</name>
		</author>
		<author numeration="9" affiliations="1">
			<name>J. Brandt</name>
		</author>
		<author numeration="10" affiliations="1">
			<name>J. H. Christensen</name>
		</author>
		<author numeration="11" affiliations="1">
			<name>L. M. Frohn</name>
		</author>
		<author numeration="12" affiliations="6">
			<name>L. Haszpra</name>
		</author>
		<author numeration="13" affiliations="7">
			<name>U. Karstens</name>
		</author>
		<author numeration="14" affiliations="7">
			<name>C. Rödenbeck</name>
		</author>
		<author numeration="15" affiliations="3">
			<name>M. Ramonet</name>
		</author>
		<author numeration="16" affiliations="8">
			<name>G. Carboni</name>
		</author>
		<author numeration="17" affiliations="9">
			<name>R. Santaguida</name>
		</author>
	</authors>
	<affiliations>
		<affiliation numeration="1" content_type="html">National Environmental Research Institute, Department of Atmospheric Environment, 4000 Roskilde, Denmark</affiliation>
		<affiliation numeration="2" content_type="html">University of Leeds, Leeds, UK</affiliation>
		<affiliation numeration="3" content_type="html">Laboratoire des Sciences du Climat et de l-Environnement, UMR CEA-CNRS 1572, 91191 Gif-sur-Yvette, France</affiliation>
		<affiliation numeration="4" content_type="html">Energieonderzoek Centrum Nederland (ECN), 1755 ZG Petten, The Netherlands</affiliation>
		<affiliation numeration="5" content_type="html">Finnish Meteorological Institute Air Quality Research, Sahaajankatu 20E 00810 Helsinki, Finland</affiliation>
		<affiliation numeration="6" content_type="html">Hungarian Meteorological Service P.O. Box 39, 1675 Budapest, Hungary</affiliation>
		<affiliation numeration="7" content_type="html">Max-Planck-Institut f&amp;uuml;r Biogeochemie, 07701 Jena, Germany</affiliation>
		<affiliation numeration="8" content_type="html">CESI ApA, Via r. Rubattino 54, 20134 Milano, Italy</affiliation>
		<affiliation numeration="9" content_type="html">Italian Air Force Meteorological Service, Via delle Ville, 40, 41029 Sestola (MO), Italy</affiliation>
	</affiliations>
	<abstract content_type="html">The CO&lt;sub&gt;2&lt;/sub&gt; source and sink distribution across Europe can be
estimated in principle through inverse methods by combining CO&lt;sub&gt;2&lt;/sub&gt; observations and atmospheric transport models. Uncertainties of such
estimates are mainly due to insufficient spatiotemporal coverage of
CO&lt;sub&gt;2&lt;/sub&gt; observations and biases of the models. In order to assess the
biases related to the use of different models the CO&lt;sub&gt;2&lt;/sub&gt;
concentration field over Europe has been simulated with five
different Eulerian atmospheric transport models as part of the
EU-funded AEROCARB project, which has the main goal to estimate the
carbon balance of Europe. In contrast to previous comparisons, here
both global coarse-resolution and regional higher-resolution models
are included. Continuous CO&lt;sub&gt;2&lt;/sub&gt; observations from continental,
coastal and mountain in-situ atmospheric stations as well as flask
samples sampled on aircrafts are used to evaluate the models&apos;
ability to capture the spatiotemporal variability and distribution
of lower troposphere CO&lt;sub&gt;2&lt;/sub&gt; across Europe. &lt;sup&gt;14&lt;/sup&gt;CO&lt;sub&gt;2&lt;/sub&gt; is used
in addition to evaluate separately fossil fuel signal predictions.
The simulated concentrations show a large range of variation, with
up to ~10 ppm higher surface concentrations over Western and
Central Europe in the regional models with highest (mesoscale)
spatial resolution.
&lt;br&gt;&lt;br&gt;
The simulation &amp;ndash; data comparison reveals that generally
high-resolution models are more successful than coarse models in
capturing the amplitude and phasing of the observed short-term
variability. At high-altitude stations the magnitude of the
differences between observations and models and in between models is
less pronounced, but the timing of the diurnal cycle is not well
captured by the models.
&lt;br&gt;&lt;br&gt;
The data comparisons show also that the timing of the observed
variability on hourly to daily time scales at low-altitude stations
is generally well captured by all models. However, the amplitude of
the variability tends to be underestimated. While daytime values are
quite well predicted, nighttime values are generally underpredicted.
This is a reflection of the different mixing regimes during day and
night combined with different vertical resolution between models. In
line with this finding, the agreement among models is increased when
sampling in the afternoon hours only and when sampling the mixed
portion of the PBL, which amounts to sampling at a few hundred
meters above ground. Main recommendations resulting from the study
for constraining land carbon sources and sinks using high-resolution
concentration data and state-of-the art transport models are
therefore: 1) low altitude stations are preferable over high
altitude stations as these locations are difficult to represent in
state-of-the art models, 2) at low altitude stations only afternoon
values can be represented sufficiently well to be used to constrain
large-scale sources and sinks in combination with transport models,
3) even when using only afternoon values it is clear that data
sampled several hundred meters above ground can be represented
substantially more robust in models than surface station records,
and finally 4) traditional large scale transport models seem not
sufficient to resolve CO&lt;sub&gt;2&lt;/sub&gt; distributions over regions of the size
of for example Spain and thus seem too coarse for interpretation of
continental data.</abstract>
	<references>
	</references>
</article>

