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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>7</volume_number>
		<issue_number>3</issue_number>
		<publication_year>2007</publication_year>
	</journal>
	<doi>10.5194/acpd-7-8455-2007</doi>
	<article_url>http://www.atmos-chem-phys-discuss.net/7/8455/2007/</article_url>
	<abstract_html>http://www.atmos-chem-phys-discuss.net/7/8455/2007/acpd-7-8455-2007.html</abstract_html>
	<fulltext_pdf>http://www.atmos-chem-phys-discuss.net/7/8455/2007/acpd-7-8455-2007.pdf</fulltext_pdf>
	<start_page>8455</start_page>
	<end_page>8524</end_page>
	<publication_date>2007-06-20</publication_date>
	<article_title content_type="html">Quality assessment of water cycle parameters in REMO by Radar-Lidar  synergy</article_title>
	<authors>
		<author numeration="1" affiliations="1,4">
			<name>B. Hennemuth</name>
			<email>hennemuth@dkrz.de</email>
		</author>
		<author numeration="2" affiliations="2">
			<name>A. Weiss</name>
		</author>
		<author numeration="3" affiliations="1">
			<name>J. BÃ¶senberg</name>
		</author>
		<author numeration="4" affiliations="1">
			<name>D. Jacob</name>
		</author>
		<author numeration="5" affiliations="1">
			<name>H. LinnÃ©</name>
		</author>
		<author numeration="6" affiliations="3">
			<name>G. Peters</name>
		</author>
		<author numeration="7" affiliations="1">
			<name>S. Pfeifer</name>
		</author>
	</authors>
	<affiliations>
		<affiliation numeration="1" content_type="html">Max-Planck-Institute for Meteorology, Hamburg, Germany</affiliation>
		<affiliation numeration="2" content_type="html">British Antarctic Survey, High Cross, Madingley Road,  Cambridge CB3 0ET, UK</affiliation>
		<affiliation numeration="3" content_type="html">Meteorological Institute, University of Hamburg,  Hamburg, Germany</affiliation>
		<affiliation numeration="4" content_type="html">now: Consulting Meteorologist, Hamburg, Germany</affiliation>
	</affiliations>
	<abstract content_type="html">A comparison study of water cycle parameters derived from ground-based
remote-sensing instruments and from the regional model REMO is presented.
Observational data sets were collected during three measuring campaigns in
summer/autumn 2003 and 2004 at Richard AÃŸmann Observatory, Lindenberg,
Germany. The remote sensing instruments which were used are differential
absorption lidar, Doppler lidar,
ceilometer, cloud radar, and micro rain radar for the derivation of humidity
profiles, ABL height, water vapour flux profiles, cloud parameters, and rain
rate.
Additionally, surface latent and sensible heat flux and soil moisture were
measured. Error ranges  and
representativity of the data are discussed.
For comparisons the regional model REMO was run for all measuring periods with a
horizontal resolution of 18 km and 33 vertical levels. Parameter output was
every hour.
The measured data were transformed to the vertical model grid and averaged in
time in order to better fit with gridbox model values. The comparisons show
that the atmospheric boundary layer is not adequately simulated, on most days
it is too shallow and too moist. This is found to be caused by a wrong
partitioning of energy at the surface, particularly a too large latent heat
flux. The reason is obviously an overestimation of soil moisture during drying
periods by the one-layer scheme in the model. The profiles of water vapour
transport within the ABL appear to be realistically simulated. The comparison
of cloud cover reveals an underestimation of low-level and mid-level clouds by
the model, whereas the comparison of high-level clouds is hampered by the
inability of the cloud radar to see cirrus clouds above 10 km. Simulated ABL
clouds apparently have a too low cloud base, and the vertical extent is
underestimated. The ice water content of clouds agree in model and observation
whereas the liquid water content is unsufficiently derived from cloud radar
reflectivity in the present study. Rain rates are similar, but the
representativeness of both observations and grid box values is low.</abstract>
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</article>

