@InProceedings{InouyeVeHeCaBePa:2022:UsRaDa,
               author = "Inouye, Rafael Toshio and Vendrasco, Eder Paulo and Herdies, 
                         Dirceu Lu{\'{\i}}s and Calvetti, Leonardo and Beneti, Cesar and 
                         Paz, Sheila",
          affiliation = "SIMEPAR and {Instituto Nacional de Pesquisas Espaciais (INPE)} and 
                         {Instituto Nacional de Pesquisas Espaciais (INPE)} and 
                         {Universidade Federal de Pelotas (UFPel)} and SIMEPAR and 
                         SIMEPAR",
                title = "The Use of the Radar Data Assimilation to Improve Short-Range 
                         Forecasts of Precipitation",
                 year = "2022",
         organization = "American Meteorological Society Annual Meeting, 102.",
            publisher = "AMS",
             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 Paran{\'a} 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.",
  conference-location = "Houston, Texas",
      conference-year = "23-27 jan. 2022",
             language = "en",
        urlaccessdate = "27 abr. 2024"
}