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		<citationkey>InouyeVeHeCaBePa:2022:UsRaDa</citationkey>
		<title>The Use of the Radar Data Assimilation to Improve Short-Range Forecasts of Precipitation</title>
		<year>2022</year>
		<secondarytype>PRE CI</secondarytype>
		<author>Inouye, Rafael Toshio,</author>
		<author>Vendrasco, Eder Paulo,</author>
		<author>Herdies, Dirceu Luís,</author>
		<author>Calvetti, Leonardo,</author>
		<author>Beneti, Cesar,</author>
		<author>Paz, Sheila,</author>
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		<group></group>
		<group>DIMNT-CGCT-INPE-MCTI-GOV-BR</group>
		<group>DIMNT-CGCT-INPE-MCTI-GOV-BR</group>
		<affiliation>SIMEPAR</affiliation>
		<affiliation>Instituto Nacional de Pesquisas Espaciais (INPE)</affiliation>
		<affiliation>Instituto Nacional de Pesquisas Espaciais (INPE)</affiliation>
		<affiliation>Universidade Federal de Pelotas (UFPel)</affiliation>
		<affiliation>SIMEPAR</affiliation>
		<affiliation>SIMEPAR</affiliation>
		<electronicmailaddress></electronicmailaddress>
		<electronicmailaddress>edervendrasco@gmail.com</electronicmailaddress>
		<electronicmailaddress>dirceu.herdies@inpe.br</electronicmailaddress>
		<conferencename>American Meteorological Society Annual Meeting, 102</conferencename>
		<conferencelocation>Houston, Texas</conferencelocation>
		<date>23-27 jan. 2022</date>
		<publisher>AMS</publisher>
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		<abstract>Regions such as South America and especially the southern region of Brazil are at the center of extreme events, with the occurrence of several phenomena of extreme impact, with large volumes of precipitation and intense winds, including the occurrence of tornadoes, which have become more frequent and affected the lives of thousands of people, causing material damage and loss of human life. In this sense, several works have been developed to improve the quality of the analyzes and mainly the short-term forecast. The use of radar data has been shown to be fundamental for forecasting up to 6 h. Using the WRF model and its data assimilation component, several experiments were carried out. The reflectivity and radial wind data from the Paraná state radar data mosaic were prepared for its use in assimilation. In this work, the results of these experiments will be presented, as well as the use of the reflectivity null echo assimilation procedure, in order to suppress the spurious precipitation effects of the model. Besides, data from local surface station network were also assimilated and compared to the experiments assimilating radar data over Parana State in Brazil. All the experiments performed better than the control run, with no data assimilation, at least in the first few hours of simulation. The main impact observed was the simulation of convective areas when radar data assimilation was used and, of course, the convection was detected in the radar coverage area. These results indicated that the mixing ratio distribution could be better solved when factor reflectivity from weather radar is used in the simulations for severe weather.</abstract>
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		<language>en</language>
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