@Article{SantosEichMatoHerd:2020:AnSiWe,
               author = "Santos, Aline Luara dos and Eichholz, Cristiano Wickboldt and 
                         Matos, Enrique Vieira and Herdies, Dirceu Lu{\'{\i}}s",
          affiliation = "{Universidade Federal de Itajub{\'a} (UNIFEI)} and {Instituto 
                         Nacional de Pesquisas Espaciais (INPE)} and {Universidade Federal 
                         de Itajub{\'a} (UNIFEI)} and {Instituto Nacional de Pesquisas 
                         Espaciais (INPE)}",
                title = "Analysis of significant weather events during 
                         chuva-goamazon2014/15 experiments / Article)(Open Access) 
                         [An{\'a}lise de eventos de tempo significativo atuantes durante 
                         os experimentos chuva-goamazon2014/15",
              journal = "Anu{\'a}rio do Instituto de Geoci{\^e}ncias",
                 year = "2020",
               volume = "43",
               number = "2",
                pages = "33--43",
             keywords = "Convec{\c{c}}{\~a}o, Precipita{\c{c}}{\~a}o, Eventos Extremos, 
                         Convection, Precipitation, Extreme Events.",
             abstract = "Este trabalho avaliou as diferen{\c{c}}as f{\'{\i}}sicas e 
                         termodin{\^a}micas entre os sistemas precipitantes das 
                         esta{\c{c}}{\~o}es seca, chuvosa e de transi{\c{c}}{\~a}o que 
                         atuaram na regi{\~a}o de Manaus/AM durante os experimentos 
                         CHUVA-GOAmazon2014/15. Foram empregados dados de refletividade do 
                         radar Banda-S de Manaus e {\'{\i}}ndices meteorol{\'o}gicos 
                         calculados a partir de radiossondagens. Ao todo 4961 sistemas 
                         precipitantes foram identificados e rastreados atrav{\'e}s do 
                         algoritmo Forecasting and Tracking the Evolution of Cloud Clusters 
                         (ForTraCC), para os quais foram calculados a taxa de 
                         precipita{\c{c}}{\~a}o, tamanho e tempo de vida. Atrav{\'e}s da 
                         metodologia baseada em percentis foram definidos os Eventos de 
                         Tempo Significativo (ETS). Esses eventos s{\~a}o aqueles que 
                         apresentaram, estatisticamente os maiores valores (> percentil de 
                         90 %) de taxa de precipita{\c{c}}{\~a}o, tamanho e tempo de vida 
                         dos sistemas precipitantes. Os resultados mostraram que, embora a 
                         esta{\c{c}}{\~a}o chuvosa apresente maior conte{\'u}do de 
                         {\'a}gua precipit{\'a}vel e acumulados de chuva, os sistemas 
                         precipitantes da esta{\c{c}}{\~a}o seca foram os que 
                         apresentaram maiores taxas de precipita{\c{c}}{\~a}o e, por 
                         isso, maior potencial para o desenvolvimento de eventos severos. 
                         De forma geral, uma maior quantidade de ETS ocorreram durante as 
                         esta{\c{c}}{\~o}es de transi{\c{c}}{\~a}o e seca, 
                         per{\'{\i}}odo com menor umidade atmosf{\'e}rica, mas grandes 
                         valores de energia potencial dispon{\'{\i}}vel para 
                         convec{\c{c}}{\~a}o, energia de inibi{\c{c}}{\~a}o convectiva 
                         e cisalhamento vertical do vento, o que contribuiu para processos 
                         convectivos mais intensos e duradouros. ABSTRACT: This work 
                         evaluated the physical and thermodynamic differences between the 
                         precipitating systems of the dry, rainy and transition seasons in 
                         the Manaus/AM region during the CHUVA-GOAmazon2014/15 experiments. 
                         Reflectivity data from Manaus Banda-S radar and meteorological 
                         indexes calculated from the radiosonde were used. Approximately 
                         4961 precipitating systems were identified and tracked using the 
                         Forecasting and Tracking the Evolution of Cloud Clusters 
                         (ForTraCC) algorithm and the precipitation rate, size and life 
                         span were calculated. Through the percentile methodology (> 90 %), 
                         Significant Weather Events (SWE) were defined. These events are 
                         those that presented, statistically, the highest values of 
                         precipitation rate, size and lifetime of the precipitating 
                         systems. The results showed that, although the rainy season has a 
                         higher content of precipitable water and accumulated rain, the dry 
                         season precipitating systems were the ones with the highest 
                         precipitation rates and, therefore, the greatest potential for the 
                         development of severe events. In general, a greater number of 
                         cases of SWE occurred during the transition and dry seasons, a 
                         period with less atmospheric humidity, but high values of 
                         potential energy available for convection, convective inhibition 
                         energy and vertical wind shear, which contributed to more intense 
                         and lasting convective processes.",
                  doi = "10.11137/2020_2_33_43",
                  url = "http://dx.doi.org/10.11137/2020_2_33_43",
                 issn = "0101-9759",
             language = "pt",
           targetfile = "santos_analise.pdf",
        urlaccessdate = "25 abr. 2024"
}