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		<citationkey>FerreiraArav:2006:SeStIn</citationkey>
		<title>A sensibility study of the inclusion of the cloud drift wind data in the CPTEC global data assimilation system</title>
		<format>CD-ROM; On-line.</format>
		<year>2006</year>
		<secondarytype>PRE CI</secondarytype>
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		<author>Ferreira, Sérgio Henrique Soares,</author>
		<author>Aravéquia, José Antonio,</author>
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		<group>DMD-INPE-MCT-BR</group>
		<group>DMD-INPE-MCT-BR</group>
		<affiliation>Instituto Nacional de Pesquisas Espaciais (INPE)</affiliation>
		<affiliation>Instituto Nacional de Pesquisas Espaciais (INPE)</affiliation>
		<electronicmailaddress>henrique@cptec.inpe.br</electronicmailaddress>
		<electronicmailaddress>Araveq@cptec.inpe.br</electronicmailaddress>
		<editor>Vera, Carolina,</editor>
		<editor>Nobre, Carlos,</editor>
		<e-mailaddress>henrique@cptec.inpe.br</e-mailaddress>
		<conferencename>International Conference on Southern Hemisphere Meteorology and Oceanography, 8 (ICSHMO).</conferencename>
		<conferencelocation>Foz do Iguaçu</conferencelocation>
		<date>24-28 Apr. 2006</date>
		<publisher>American Meteorological Society (AMS)</publisher>
		<publisheraddress>45 Beacon Hill Road, Boston, MA, USA</publisheraddress>
		<pages>1769-1771</pages>
		<booktitle>Proceedings</booktitle>
		<tertiarytype>Poster</tertiarytype>
		<organization>American Meteorological Society (AMS)</organization>
		<transferableflag>1</transferableflag>
		<keywords>data assimilation, cloud track wind, PSAS, numeric weather prediction, analysis system.</keywords>
		<abstract>Since 2004, the Physical-Space Statistical Analysis System (PSAS) developed by Global Modeling and Assimilation Office (GMAO of NASA) have been operationally tested at Centro de Previsão do Tempo e Estudos Climáticos (CPTEC) integrated with the operational Global Model of this center. In this integrated system, designated GPSAS, were firstly used a database composed by conventional meteorological data and Advanced TOVS data. However, these data were not sufficient to produced analysis and forecasts with desired quality. In this work, Cloud Track Winds data (CTW) were added to initial databases to improve the quality of Analysis and Forecast. The results with and without CTW data are compared in term of skill index and field of pressure, winds and humidity, and is showed that the CTW data improve the characterization of the eddies in the analysis.  Other important aspect showed is the computational cost associated with quantity of data used in this system.</abstract>
		<area>MET</area>
		<type>Weather analysis and forecasting</type>
		<language>en</language>
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