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@MastersThesis{Coelho:2019:SiNuPr,
               author = "Coelho, Sildiscley Assis",
                title = "Simula{\c{c}}{\~o}es num{\'e}ricas para previs{\~a}o de 
                         eventos de tempo severo sobre o Aeroporto Internacional de 
                         S{\~a}o Paulo",
               school = "Instituto Nacional de Pesquisas Espaciais (INPE)",
                 year = "2019",
              address = "S{\~a}o Jos{\'e} dos Campos",
                month = "2019-09-16",
             keywords = "alta resolu{\c{c}}{\~a}o, ensemble, WRF, high resolution.",
             abstract = "Eventos de tempo severo podem impactar as atividades 
                         aeroportu{\'a}rias e o gerenciamento do fluxo de tr{\'a}fego 
                         a{\'e}reo, al{\'e}m de levar a outros impactos 
                         socioecon{\^o}micos. Neste trabalho, para 3 casos de tempo severo 
                         ocorridos no Aeroporto Internacional de S{\~a}o Paulo Guarulhos 
                         entre 2016 e 2017, avaliou-se o desempenho de 
                         simula{\c{c}}{\~o}es em alta resolu{\c{c}}{\~a}o com o Weather 
                         Research and Forecasting Model (WRF) utilizando multiphysics 
                         ensemble. Nos 3 casos, a condi{\c{c}}{\~a}o sin{\'o}tica foi 
                         comum e consistiu na atua{\c{c}}{\~a}o de um sistema frontal 
                         sobre a regi{\~a}o. O n{\'u}mero de membros do ensemble foi 9. 
                         As simula{\c{c}}{\~o}es foram executadas em dois 
                         dom{\'{\i}}nios aninhados com espa{\c{c}}amento horizontal de 9 
                         e 3 km aproximadamente centrados no aeroporto. As 
                         condi{\c{c}}{\~o}es iniciais e de contorno foram provenientes de 
                         previs{\~o}es do Global Forecast System (GFS). O prazo {\'u}til 
                         de previs{\~a}o considerado foi de 24 h. A an{\'a}lise dos 
                         resultados enfocou duas vari{\'a}veis: precipita{\c{c}}{\~a}o e 
                         vento a 10 m. Para a compara{\c{c}}{\~a}o entre 
                         simula{\c{c}}{\~o}es e observa{\c{c}}{\~o}es, foram 
                         utilizadas, para a precipita{\c{c}}{\~a}o, estat{\'{\i}}sticas 
                         computadas com as informa{\c{c}}{\~o}es contidas em uma caixa de 
                         100 km x 100 km centrada no aeroporto; para o vento, valores no 
                         ponto de grade do aeroporto. As s{\'e}ries temporais observadas 
                         foram comparadas com as m{\'e}tricas do ensemble (mediana, 
                         dispers{\~a}o e outlier) representadas em boxplot. Os resultados 
                         mostraram que o instante de ocorr{\^e}ncia e a 
                         dura{\c{c}}{\~a}o de precipita{\c{c}}{\~a}o forte s{\~a}o 
                         previstos em ambos os dom{\'{\i}}nios pelos outliers. Para a 
                         intensidade de precipita{\c{c}}{\~a}o m{\'a}xima, o valor e o 
                         instante de ocorr{\^e}ncia podem ser previstos pelos outliers no 
                         dom{\'{\i}}nio de 9 km e pela mediana no dom{\'{\i}}nio de 3 
                         km. O instante de ocorr{\^e}ncia e a dura{\c{c}}{\~a}o das 
                         rajadas de vento podem ser previstos pela dispers{\~a}o dos 
                         membros em ambos os dom{\'{\i}}nios. Todos esses resultados, por 
                         terem sido v{\'a}lidos para os 3 casos, podem ser considerados 
                         robustos. A metodologia utilizada no trabalho, por ser simples, 
                         poder{\'a} ser adaptada e implementada em centros operacionais, 
                         como o Centro Integrado de Meteorologia Aeron{\'a}utica (CIMAER), 
                         para assistir a previs{\~a}o para o Aeroporto Internacional de 
                         S{\~a}o Paulo. ABSTRACT: Severe weather events can affect airport 
                         activities and air traffic management, as well as other 
                         socioeconomic activities. In this work, for 3 severe weather cases 
                         that occurred in the International Airport of S{\~a}o Paulo 
                         Guarulhos between 2016 and 2017, the performance of high 
                         resolution simulations with the Weather Research and Forecasting 
                         Model (WRF) using multiphysics ensemble was evaluated. In the 3 
                         cases, there was a common synoptic condition: the presence of a 
                         frontal system over the region. The number of members in the 
                         ensemble was 9. The simulations were performed in two nested 
                         domains with 9 km and 3 km horizontal spacing approximately 
                         centered at the airport. Initial and boundary conditions were 
                         provided by Global Forecast System (GFS) forecasts. The forecast 
                         range was 24 h. The analysis of results focused on two variables: 
                         precipitation and wind at 10 m. To compare simulations with 
                         observations, for precipitation, statistics computed from 
                         information contained in a 100 km x 100 km box centered at the 
                         airport were used; for wind, values at the grid point closest to 
                         the airport were used. The time series for observations were 
                         compared with that for simulations by using ensemble metrics 
                         (median, dispersion and outlier) represented in boxplot. The 
                         results showed that the time of occurrence and the duration of 
                         heavy precipitation can be predicted in both domains by outliers. 
                         For the maximum precipitation intensity, the value and the time of 
                         occurrence can be predicted by outliers in the 9 km domain and the 
                         median in the 3 km domain. The time of occurrence and duration of 
                         wind gusts can be predicted by the dispersion in both domains. All 
                         these results, being valid for all 3 cases, can be regarded as 
                         robust. The methodology used in the work, due to its simplicity, 
                         can be adapted and implemented in operational centers, such as the 
                         Centro Integrado de Meteorologia Aeron{\'a}utica (CIMAER), to 
                         assist the weather forecasting activities for the International 
                         Airport of S{\~a}o Paulo.",
            committee = "Fernandez, Julio Pablo Reyes (presidente) and Oyama, Marcos 
                         Daisuke (orientador) and Silva, Adaiana Francisca Gomes da",
         englishtitle = "Number simulations for forecasting several time events about 
                         S{\~a}o Paulo International Airport",
             language = "pt",
                pages = "149",
                  ibi = "8JMKD3MGP3W34R/3U9J6J8",
                  url = "http://urlib.net/rep/8JMKD3MGP3W34R/3U9J6J8",
           targetfile = "publicacao.pdf",
        urlaccessdate = "18 abr. 2021"
}


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