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@MastersThesis{AlvesJr:2017:ImPaMi,
               author = "Alves Junior, Mario Paulo",
                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",
               school = "Instituto Nacional de Pesquisas Espaciais (INPE)",
                 year = "2017",
              address = "S{\~a}o Jos{\'e} dos Campos",
                month = "2017-08-15",
             keywords = "parametriza{\c{c}}{\~a}o de microf{\'{\i}}sica, 
                         assimila{\c{c}}{\~a}o de dados de radar, WRF e WRFDA, 
                         microphysics parameterization, radar data assimilation, WRF and 
                         WRFDA.",
             abstract = "Na avia{\c{c}}{\~a}o, a previs{\~a}o do tempo de curto prazo 
                         {\'e} muito importante para o planejamento da 
                         navega{\c{c}}{\~a}o a{\'e}rea. Trabalhos recentes mostram que a 
                         assimila{\c{c}}{\~a}o de dados melhora a efic{\'a}cia dos 
                         modelos num{\'e}ricos de previs{\~a}o de tempo, contudo {\'e} 
                         pouco quantificado o impacto da assimila{\c{c}}{\~a}o dos dados 
                         de radar 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 
                         foi testar 9 diferentes parametriza{\c{c}}{\~o}es de 
                         microf{\'{\i}}sica do modelo Weather Research and Forcasting 
                         (WRF) com seu sistema de assimila{\c{c}}{\~a}o de dados 
                         (WRFDA-3DVAR), em uma grade com resolu{\c{c}}{\~a}o horizontal 
                         de 2 km. A {\'a}rea de estudo escolhida abrange o oeste da 
                         regi{\~a}o sul do Brasil e sudeste do Paraguai. Os casos 
                         escolhidos de precipita{\c{c}}{\~a}o foram os dias 30 de 
                         outubro, 07 de novembro e 13 de dezembro de 2014, devido {\`a} 
                         intensidade da precipita{\c{c}}{\~a}o, al{\'e}m da qualidade e 
                         disponibilidade dos dados observacionais em superf{\'{\i}}cie, 
                         das radiossondagens e dos dados de radar. A compara{\c{c}}{\~a}o 
                         foi realizada atrav{\'e}s das m{\'e}tricas estat{\'{\i}}sticas 
                         Fractional Skill Score (FSS) e Local Root Mean Square Error 
                         (LRMSE). Foram testadas diferentes parametriza{\c{c}}{\~o}es de 
                         microf{\'{\i}}sica com assimila{\c{c}}{\~a}o de dados 
                         convencionais e de radar nos tr{\^e}s eventos, totalizando 81 
                         rodadas do modelo. Desta forma, procurou-se determinar qual a 
                         parametriza{\c{c}}{\~a}o de microf{\'{\i}}sica melhor 
                         representou os campos meteorol{\'o}gicos nas previs{\~o}es de 
                         curto prazo para a regi{\~a}o de estudo, assim como 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. 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 o impacto 
                         positivo entre as op{\c{c}}{\~o}es de microf{\'{\i}}sica 
                         atingiu 70\% no FSS. ABSTRACT: In aviation, short-term weather 
                         forecast is very important for the planning of air navigation. 
                         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 is to perform experiments using 9 different 
                         parameterization of microphysics using the Weather Research and 
                         Forcasting (WRF) model and its data assimilation system 
                         (WRFDA-3DVAR) in a grid with 2 km horizontal resolution. The study 
                         area covers the South-western Brazil and Southeastern Paraguay. 
                         The simulations were done for October 30th, November 7th and 
                         December 13th of 2014, due to the intensity of precipitation, as 
                         well as the quality and availability of observational data, i.e., 
                         surface, radiosonde and radar data. The comparison is performed 
                         through the statistical metrics Fractional Skill Score (FSS) and 
                         Local Root Mean Square Error (LRMSE). Different microphysics 
                         parametrizations were tested when assimilating conventional and 
                         radar data for three events, totalling 81 run of the model. Thus, 
                         it is expected to determine the best microphysical 
                         parameterization that provides the more realistic short-term 
                         forecasts of meteorological fields over the radars area, 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 FSS.",
            committee = "Herdies, Dirceu Luis (presidente) and Vendrasco, Eder Paulo 
                         (orientador) and Arav{\'e}quia, Jos{\'e} Antonio (orientador) 
                         and Corr{\^e}a, Cleber Souza",
         englishtitle = "The impact of microphysics parametrization on precipitation 
                         forecast using radar data assimilation",
             language = "pt",
                pages = "146",
                  ibi = "8JMKD3MGP3W34P/3PB9P3L",
                  url = "http://urlib.net/rep/8JMKD3MGP3W34P/3PB9P3L",
           targetfile = "publicacao.pdf",
        urlaccessdate = "26 nov. 2020"
}


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