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<article language="en">
	<journal>
		<journal_title>Advances in Geosciences</journal_title>
		<journal_url>www.adv-geosci.net</journal_url>
		<issn>1680-7340</issn>
		<eissn>1680-7359</eissn>
		<volume_number>16</volume_number>
		<volume_title>Observation, Prediction and Verification of Precipitation (EGU Session 2007)</volume_title>
		<publication_year>2008</publication_year>
	</journal>
	<doi>10.5194/adgeo-16-109-2008</doi>
	<article_url>http://www.adv-geosci.net/16/109/2008/</article_url>
	<abstract_html>http://www.adv-geosci.net/16/109/2008/adgeo-16-109-2008.html</abstract_html>
	<fulltext_pdf>http://www.adv-geosci.net/16/109/2008/adgeo-16-109-2008.pdf</fulltext_pdf>
	<start_page>109</start_page>
	<end_page>116</end_page>
	<publication_date>2008-04-09</publication_date>
	<article_title content_type="html">Intercomparison of simulations using 5 WRF microphysical schemes with dual-Polarization data for a German squall line</article_title>
	<authors>
		<author numeration="1" affiliations="1">
			<name>W. A. Gallus Jr.</name>
			<email>wgallus@iastate.edu</email>
		</author>
		<author numeration="2" affiliations="2">
			<name>M. Pfeifer</name>
		</author>
	</authors>
	<affiliations>
		<affiliation numeration="1" content_type="html">Iowa State University, Ames, IA, USA</affiliation>
		<affiliation numeration="2" content_type="html">DLR Institute of Atmospheric Physics, Oberpfaffenhofen, Germany</affiliation>
	</affiliations>
	<abstract content_type="html">Simulations of a squall line system which occurred on 12 August 2004 near
Munich, Germany are performed using a fine grid version of the Weather
Research and Forecasting (WRF) model with five different microphysical
schemes. Synthetic dual polarization observations are created from the model
output and compared with detailed observations gathered by the DLR
polarimetric radar POLDIRAD located near Munich. Synthetic polarimetric
radar scans are derived from the model forecasts employing the polarimetric
radar forward operator SynPolRad. Evaluations of the microphysical
parameterization schemes are carried out comparing Plan Position Indicator
(PPI) and Range Height Indicator (RHI) scans of reflectivity and the spatial
distribution of hydrometeor types. The hydrometeor types are derived
applying a hydrometeor classification scheme to the observed and simulated
polarimetric radar quantities. Furthermore, the Ebert-McBride contiguous
rain area method of verification is tested in a variety of ways on the
reflectivity output from the simulations. It is found that all five schemes
overestimate reflectivity in the domain, particularly in the stratiform
region of the convective system. All four schemes including graupel as a
hydrometeor type produce too much of it. Differences are seen among the
schemes in their depiction of reflectivity in the convective line and their
representation of radar bright bands.</abstract>
	<references>
		<reference numeration="1" content_type="text">Bringi, V. N., Rasmussen, R. M., and Vivekanandan, J.: Multiparameter Radar measurements in Colorado convective Storms, Part I: Graupel Melting Studies, J. Atmos. Sci., 43, 2545&amp;ndash;2563, 1986 </reference>
		<reference numeration="2" content_type="text">Chen, S.-H. and Sun, W.-Y.: A one dimensional, time dependent cloud model, J. Meteor. Soc. Japan, 60, 99&amp;ndash;118, 2002. </reference>
		<reference numeration="3" content_type="text">Colle, B. A., Garvert, M. F. Wolfe, J. B., Mass, C. F., and Woods, C. P.: The 13&amp;ndash;14~December~2001 IMPROVE-2 event, Part III: Simulated microphysical budgets and sensitivity studies, J. Atmos. Sci., 62, 3535&amp;ndash;3558, 2005 </reference>
		<reference numeration="4" content_type="text">Dudhia, J.: Numerical study of convection observed during the winter monsoon experiment using a mesoscale two-dimensional model, J. Atmos. Sci., 46, 3077&amp;ndash;3107, 1989. </reference>
		<reference numeration="5" content_type="text">Ebert, E. E. and McBride, J. L.: Verification of precipitation in weather systems: Determination of systematic errors, J. Hydrology, 239, 179&amp;ndash;202, 2000 </reference>
		<reference numeration="6" content_type="text">Ferrier, B. S., Tao, W. K., and Simpson, J.: A double-moment multiple-phase four-class bulk ice scheme, Part II: Simulations of convective storms in different large-scale environments and comparisons with other bulk parameterizations, J. Atmos. Sci., 52, 1001&amp;ndash;1033, 1995. </reference>
		<reference numeration="7" content_type="text">Garvert, M. F., Woods, C. P., Colle, B. A., Mass, C. F., Hobbs, P. V., Stoelinga, M. T., and Wolfe, J. B.: The 13&amp;ndash;14~December~2001 IMPROVE-2 event, Part II: Comparison of MM5 Model simulations of clouds and precipitation with observations, J. Atmos. Sci., 62, 3520&amp;ndash;3534, 2005. </reference>
		<reference numeration="8" content_type="text">Gilmore, M. S., Straka, J. M., and Rasmussen, E. N.: Precipitation and evolution sensitivity in simulated deep convective storms: Comparisons between liquid-only and simple ice &amp; liquid phase microphysics, Mon. Weather Rev., 132, 1897&amp;ndash;1916, 2004. </reference>
		<reference numeration="9" content_type="text">Grams, J. S., Gallus, Jr., W. A., Wharton, L. S., Koch, S. E., Loughe, A., and Ebert, E. E.: The use of a modified Ebert-McBride technique to evaluate mesoscale model QPF as a function of convective system morphology during IHOP 2002, Wea. Forecasting, 21, 288&amp;ndash;306, 2006. </reference>
		<reference numeration="10" content_type="text">Hoeller, H., Bringi, V., Hubbert, J., Hagen, M., and Meischner, P. F.: Life cycle and precipitation formation in a hybrid-type hailstorm revealed by polarimetric and Doppler radar measurements, J. Atmos. Sci., 51, 2500&amp;ndash;2522 1994. </reference>
		<reference numeration="11" content_type="text">Hong, S.-Y., Dudhia, J., and Chen, S.-H.: A revised approach to ice microphysical processes for the bulk parameterization of cloud and precipitation, Mon. Weather Rev., 132, 103&amp;ndash;120, 2004 </reference>
		<reference numeration="12" content_type="text">Jankov, I., Gallus, Jr., W. A., Shaw, B., and Koch, S. E.: On the impacts of different WRF physical parameterizations and their interactions on warm season MCS rainfall, Wea. Forecasting, 20, 1048&amp;ndash;1060, 2005. </reference>
		<reference numeration="13" content_type="text">Lin, Y.-L., Farley, R. D., and Orville, H. D.: Bulk parameterization of the snow field in a cloud model, J. Appl. Meteor., 22, 1065&amp;ndash;1092, 1983. </reference>
		<reference numeration="14" content_type="text">Mishchenko, M. I. and Travis, L. D.: Capabilities and limitations of a current Fortran implementation of the T-Matrix Method for randomly oriented, rotationally symmetric scatterers, J. Quant. Spectros. Radiat. Transfer, 60, 309&amp;ndash;324, 1998. </reference>
		<reference numeration="15" content_type="text">Murphy, A. H.: The coefficients of correlation and determination as measures of performance in forecast verification, Wea. Forecasting, 10, 681&amp;ndash;688, 1995. </reference>
		<reference numeration="16" content_type="text">Pfeifer, M., Craig, G., Hagen, M., and Keil, C.: A polarimetric radar forward operator, Proceedings of ERAD, 2, 494&amp;ndash;498, 2004. </reference>
		<reference numeration="17" content_type="text">Pfeifer, M.: Evaluation of precipitation forecasts by polarimetric radar, Dissertation, 134 pages, LMU München, (ttp://edoc.ub.uni-muenchen.de/7253/), 2007. </reference>
		<reference numeration="18" content_type="text">Schroth, A. C., Chandra, M. S., and Meischner, P. F.: A C-band coherent polarimetric radar for propagation and cloud physics research, J. Atmos. Oceanic Technol., 5, 804&amp;ndash;822, 1988. </reference>
		<reference numeration="19" content_type="text">Thompson, G., Rasmussen, R. M., and Manning, K.: Explicit forecasts of winter precipitation using an improved bulk microphysics scheme, Part I: Description and sensitivity analysis, Mon. Weather Rev., 132, 519&amp;ndash;542, 2004. </reference>
		<reference numeration="20" content_type="text">Vivekanandan, J., Bringi, V. N., and Raghavan, R.: Multiparameter radar modeling and observation of melting ice, J. Atmos. Sci., 47, 549&amp;ndash;564, 1990. </reference>
		<reference numeration="21" content_type="text">Vivekanandan, J., Raghavan, R., and Bringi, V. N.: Polarimetric radar modeling of mixtures of precipitation particles, IEEE Trans. Geos., 31, 1017&amp;ndash;1030, 1993. </reference>
		<reference numeration="22" content_type="text">Wang, Y.: An explicit simulation of tropical cyclones with a triply nested movable nest primitive equation model: TCM3, Part II: Model refinements and sensitivity to cloud microphysics parameterization, Mon. Wea. Rev., 130, 3022&amp;ndash;3036, 2002. </reference>
		<reference numeration="23" content_type="text">Waterman, P. C.: Scattering by dielectric obstacles, Alta Frequenza (Speciale), 348&amp;ndash;352, 1969. </reference>
		<reference numeration="24" content_type="text">Zrnic, D. S., Keenan, T. D., Carey, L. D., and May, P.: Sensitivity analysis of polarimetric variables at a 5-cm wavelength in rain, J. Appl. Meteor., 39, 1514&amp;ndash;1526, 2000. </reference>
	</references>
</article>

