@Article{FerreiraAlVeArNoBi:2020:ImPaMi,
               author = "Ferreira, Rute Costa and Alves J{\'u}nior, Mario Paulo and 
                         Vendrasco, {\'E}der Paulo and Arav{\'e}quia, Jos{\'e} 
                         Ant{\^o}nio and Nolasco J{\'u}nior, Luciano Ritter and Biscaro, 
                         Thiago Souza",
          affiliation = "{Instituto Nacional de Pesquisas Espaciais (INPE)} and {Instituto 
                         de Controle do Espa{\c{c}}o A{\'e}reo} and {Instituto Nacional 
                         de Pesquisas Espaciais (INPE)} and {Instituto Nacional de 
                         Pesquisas Espaciais (INPE)} and {Instituto Nacional de Pesquisas 
                         Espaciais (INPE)} and {Instituto Nacional de Pesquisas Espaciais 
                         (INPE)}",
                title = "Impacto das parametriza{\c{c}}{\~o}es de microf{\'{\i}}sica na 
                         previs{\~a}o de precipita{\c{c}}{\~a}o utilizando 
                         assimila{\c{c}}{\~a}o de dados de radar",
              journal = "Revista Brasileira de Meteorologia",
                 year = "2020",
               volume = "35",
               number = "1",
                pages = "123--134",
             keywords = "parametriza{\c{c}}{\~a}o de microf{\'{\i}}sica, 
                         assimila{\c{c}}{\~a}o de dados de radar, WRF e Wmicrophysics 
                         parameterization, radar data assimilation, WRF and WRFDA.RFDA.",
             abstract = "Trabalhos recentes mostram que a assimila{\c{c}}{\~a}o de dados 
                         melhora a efic{\'a}cia dos modelos de previs{\~a}o de tempo, 
                         contudo o impacto da assimila{\c{c}}{\~a}o dos dados de radar 
                         {\'e} pouco quantificado com rela{\c{c}}{\~a}o {\`a}s 
                         parametriza{\c{c}}{\~o}es f{\'{\i}}sicas do modelo, 
                         especialmente de microf{\'{\i}}sica. O objetivo deste trabalho 
                         {\'e} estudar o impacto do uso de dados de radar com diferentes 
                         parametriza{\c{c}}{\~o}es de microf{\'{\i}}sica do modelo 
                         Weather Research and Forecasting (WRF) com seu sistema de 
                         assimila{\c{c}}{\~a}o de dados (WRFDA-3DVAR) para casos de 
                         precipita{\c{c}}{\~a}o intensa. Foram selecionados tr{\^e}s 
                         eventos de precipita{\c{c}}{\~a}o em 2014, com {\'a}rea de 
                         estudo abrangendo o oeste da regi{\~a}o sul do Brasil e sudeste 
                         do Paraguai. Desta forma, s{\~a}o avaliados nove esquemas de 
                         parametriza{\c{c}}{\~o}es de microf{\'{\i}}sica com 
                         assimila{\c{c}}{\~a}o de dados convencionais e de radar, para 
                         determinar qual representa de forma mais adequada a 
                         precipita{\c{c}}{\~a}o e refletividade nas previs{\~o}es de 
                         curto prazo, al{\'e}m de determinar o impacto relativo entre as 
                         mudan{\c{c}}as de microf{\'{\i}}sica e a 
                         assimila{\c{c}}{\~a}o de dados convencionais e de radar. A 
                         compara{\c{c}}{\~a}o realizada atrav{\'e}s da m{\'e}trica 
                         estat{\'{\i}}stica Fractional Skill Score (FSS) mostra o impacto 
                         positivo da assimila{\c{c}}{\~a}o de dados do radar foi na 
                         m{\'e}dia de at{\'e} 20% no FSS, enquanto que o impacto positivo 
                         entre as op{\c{c}}{\~o}es de microf{\'{\i}}sica atingiu 70%. 
                         ABSTRACT: Recent studies show that data assimilation improves the 
                         efficiency of weather forecast models, however, it is not properly 
                         quantified the impacts of radar data assimilation related to the 
                         physical model parameterizations, especially the microphysics. The 
                         goal of this study was to study the impact of the use of radar 
                         data with different microphysics parameterizations of the Weather 
                         Research and Forecasting (WRF) model with its data assimilation 
                         system (WRFDA3DVAR) for cases of intense precipitation. The study 
                         area covers the South-western Brazil and Southeastern Paraguay. 
                         The simulations were done for three cases in 2014. The comparison 
                         is performed through the statistical metrics Fractional Skill 
                         Score (FSS) and Local Root Mean Square Error (LRMSE). Different 
                         microphysics parameterizations were tested when assimilating 
                         conventional and radar data for three events. Thus, we evaluated 
                         nine microphysical parameterizations in order to determine which 
                         one provides the most realistic short-term forecasts of 
                         meteorological fields over the radar coverage, as well as the 
                         relative impact of different microphysical parameterization and 
                         the assimilation of conventional and radar data. The positive 
                         impact of the radar data assimilation was in the average up to 20% 
                         in the FSS, while the positive impact among the microphysics 
                         options reached 70% in the FSS.",
                  doi = "10.1590/0102-778635100",
                  url = "http://dx.doi.org/10.1590/0102-778635100",
                 issn = "0102-7786",
             language = "pt",
           targetfile = "ferreira_impacto.pdf",
        urlaccessdate = "28 abr. 2024"
}