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@PhDThesis{Guimarães:2021:CoAvIn,
               author = "Guimar{\~a}es, Bruno dos Santos",
                title = "Previs{\~a}o sub-sazonal com o modelo global atmosf{\'e}rico do 
                         CPTEC/INPE: configura{\c{c}}{\~a}o, avalia{\c{c}}{\~a}o e 
                         investiga{\c{c}}{\~a}o das fontes de previsibilidade para a 
                         Am{\'e}rica do Sul",
               school = "Instituto Nacional de Pesquisas Espaciais (INPE)",
                 year = "2021",
              address = "S{\~a}o Jos{\'e} dos Campos",
                month = "2020-12-14",
             keywords = "oscila{\c{c}}{\~a}o de Madden-Julian, BAM-1.2, fontes de 
                         previsibilidade, Madden-Julian oscillation, source of 
                         predictability.",
             abstract = "Este estudo teve como objetivo determinar a habilidade preditiva 
                         do modelo atmosf{\'e}rico global do CPTEC (BAM-1.2) na escala 
                         sub-sazonal e investigar as principais fontes de previsibilidade 
                         associadas sobre a Am{\'e}rica do Sul, durante 12 ver{\~o}es 
                         estendidos (novembro mar{\c{c}}o, 1999/2000 2010/2011). Sete 
                         configura{\c{c}}{\~o}es do BAM-1.2 foram avaliadas em termos de 
                         resolu{\c{c}}{\~a}o vertical, parametriza{\c{c}}{\~o}es de 
                         convec{\c{c}}{\~a}o profunda e camada limite planet{\'a}ria, e 
                         inicializa{\c{c}}{\~o}es da componente atmosf{\'e}rica 
                         (condi{\c{c}}{\~a}o inicial) e umidade do solo. Atrav{\'e}s da 
                         avalia{\c{c}}{\~a}o dessas sete configura{\c{c}}{\~o}es foi 
                         poss{\'{\i}}vel determinar a configura{\c{c}}{\~a}o mais 
                         adequada do BAM-1.2 para as previs{\~o}es das anomalias semanais 
                         de precipita{\c{c}}{\~a}o e temperatura do ar a 2 metros de 
                         altura (T2M) e evolu{\c{c}}{\~a}o di{\'a}ria da 
                         Oscila{\c{c}}{\~a}o de Madden e Julian (OMJ). Com a 
                         configura{\c{c}}{\~a}o do BAM-1.2 determinada, a habilidade 
                         preditiva do modelo do CPTEC, a partir de um conjunto de 
                         previs{\~o}es retrospectivas, composto por 11 membros, foi 
                         avaliada e comparada com a habilidade preditiva dos modelos do 
                         Japan Meteorological Agency (JMA), Environmental and Climate 
                         Change Canada (ECCC), European Centre for Medium-range Weather 
                         Forecasts (ECMWF) e Australian Bureau of Meteorology (BoM), os 
                         quais participam do projeto internacional Sub-seasoanl-to-Seasonal 
                         (S2S) do programa mundial de pesquisa em tempo e clima da 
                         Organiza{\c{c}}{\~a}o Meteorol{\'o}gica Mundial (OMM). Por 
                         {\'u}ltimo, os modos de variabilidade espa{\c{c}}o-temporal das 
                         anomalias semanais de precipita{\c{c}}{\~a}o foram determinados. 
                         Tais modos foram associados a fen{\^o}menos 
                         atmosf{\'e}ricos/oce{\^a}nicos para definir as principais fontes 
                         de previsibilidade na escala sub-sazonal sobre a Am{\'e}rica do 
                         Sul durante o ver{\~a}o estendido. Os resultados mostraram que o 
                         BAM-1.2 se mostrou competitivo em rela{\c{c}}{\~a}o aos modelos 
                         do projeto S2S avaliados. Entretanto, os superiores 
                         {\'{\i}}ndices de destreza alcan{\c{c}}ados pelo modelo do 
                         ECMWF indicam que a habilidade preditiva das previs{\~o}es 
                         sub-sazonais do CPTEC pode ser aprimoradas possivelmente com o 
                         incremento na resolu{\c{c}}{\~a}o espacial do BAM- 1.2, 
                         acoplamento com o componente oce{\^a}nico e melhorias nos 
                         esquemas de parametriza{\c{c}}{\~o}es f{\'{\i}}sicas e de 
                         gera{\c{c}}{\~a}o dos membros para inicializa{\c{c}}{\~a}o do 
                         modelo. Com rela{\c{c}}{\~a}o {\`a}s principais fontes de 
                         previsibilidade sobre a Am{\'e}rica do Sul, o padr{\~a}o de 
                         dipolo meridional sobre o leste da Am{\'e}rica do Sul foi 
                         encontrado como sendo o modo de variabilidade 
                         espa{\c{c}}o-temporal dominante. Foi identificado que esse 
                         padr{\~a}o {\'e} fortemente influenciado por 
                         oscila{\c{c}}{\~o}es dentro das escalas de variabilidade 
                         intrassazonal e interanual. Esta constata{\c{c}}{\~a}o indica 
                         que v{\'a}rios fen{\^o}menos influenciam a forma{\c{c}}{\~a}o 
                         do padr{\~a}o de dipolo e, dessa forma, atuam como fontes de 
                         previsibilidade sobre a Am{\'e}rica do Sul [e.g., 
                         teleconex{\~o}es tr{\'o}pico-extratr{\'o}pico, El-Niņo 
                         Oscila{\c{c}}{\~a}o Sul (ENOS) e OMJ]. Al{\'e}m disso, o 
                         segundo modo de variabilidade espa{\c{c}}o-temporal tamb{\'e}m 
                         mostrou relevante contribui{\c{c}}{\~a}o para a habilidade 
                         preditiva sobre a regi{\~a}o equatorial da Am{\'e}rica do Sul. 
                         Esse padr{\~a}o apresenta uma forte rela{\c{c}}{\~a}o com a 
                         atividade convectiva sobre a regi{\~a}o equatorial do Oceano 
                         Pac{\'{\i}}fico Oeste, influenciado principalmente pelo ENOS. 
                         ABSTRACT: The aim of this work was to study the predictive ability 
                         of the Brazilian Global Atmospheric Model version 1.2 (BAM-1.2) at 
                         sub-seasonal time-scale and the associated sources of 
                         predictability over South America during the 12 extended austral 
                         summers (November March, 1999/2000 2010/2011). Seven BAM-1.2 
                         configurations were tested in terms of vertical resolution, deep 
                         convection and boundary layer parameterizations, as well as 
                         atmospheric component and soil moisture initializations, in order 
                         to identify the configuration with best performance when 
                         predicting weekly precipitation anomalies, weekly mean 2-meter 
                         temperature (T2M) and the Madden and Julian Oscillation (MJO) 
                         daily evolution. With BAM-1.2 configuration determined, an 
                         inter-comparison performance assessment of 11 member ensemble 
                         hindcasts produced with BAM-1.2 against four Sub-seasonal to 
                         Seasonal (S2S) prediction project models from Japan Meteorological 
                         Agency (JMA), Environmental and Climate Change Canada (ECCC), 
                         European Centre for Mediumrange Weather Forecasts (ECMWF) and 
                         Australian Bureau of Meteorology (BoM) was performed. Lastly, the 
                         main spatio-temporal variability modes of weekly precipitation 
                         anomalies were determined. These modes were associated with 
                         atmospheric/oceanic phenomena to define the main sources of 
                         predictability at subseasonal time-scale over South America during 
                         the extended summer. The performed inter comparison revealed that 
                         for prediction of precipitation anomalies and MJO BAM-1.2 showed 
                         competitive performance compared to the investigated S2S models, 
                         but with respect to ECMWF there is scope for improvements, 
                         possibly by a combination of including coupling to an interactive 
                         ocean and improving resolution, physical parameterization schemes 
                         and the ensemble generation approach for initialization. Regarding 
                         the main sources of predictability over South America, the South 
                         American seesaw pattern has been found to be the dominant mode of 
                         variability. This pattern is strongly influenced by oscillations 
                         within the intraseasonal and interannual variability time scales. 
                         This suggests that several phenomena can influence the formation 
                         of this pattern, acting as sources of predictability [e.g., 
                         tropical-extratropical interaction, El-Niņo South Oscillation 
                         (ENSO), and MJO]. Besides, the second mode of variability 
                         contributes to the predictive ability over the equatorial South 
                         American region. This mode has a strong relationship with the 
                         convective activity over the Equatorial West Pacific Ocean, 
                         influenced mainly by ENSO.",
            committee = "Bonatti, Jos{\'e} Paulo (presidente) and Coelho, Caio Augusto dos 
                         Santos (orientador) and Ferreira, Nelson Jesuz and Dias, Pedro 
                         Leite da Silva and Andrade, Felipe Marques de",
         englishtitle = "Sub-seasonal prediction with the global atmospheric model of 
                         CPTEC/INPE: configuration, evaluation and investigation of sources 
                         of predictability for South America",
             language = "pt",
                pages = "175",
                  ibi = "8JMKD3MGP3W34R/43KQ468",
                  url = "http://urlib.net/ibi/8JMKD3MGP3W34R/43KQ468",
           targetfile = "publicacao.pdf",
        urlaccessdate = "28 abr. 2024"
}


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