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@Article{FigueroaBKGMBFRSCSSPCAEDSCNBMP:2016:PeTrRa,
               author = "Figueroa, Silvio Nilo and Bonatti, Jos{\'e} Paulo and Kubota, 
                         Paulo Yoshi and Grell, Georg A. and Morrison, Hugh and Barros, 
                         Saulo R. M. and Fernandez, Julio Pablo Reyes and Ramirez 
                         Gutierrez, Enver Manuel Amador and Siqueira, Leo and Costa, 
                         Graziela Luzia da and Silva, Josiane da and Silva, Juliana Resende 
                         da and Pendharkara, Jayant and Capistrano, Vinicius Buscioli and 
                         Alvim, D{\'e}bora Souza and Enor{\'e}, Diego Pereira and Diniz, 
                         F{\'a}bio Luiz Rodrigues and Satyamurty, Prakki and Cavalcanti, 
                         Iracema Fonseca de Albuquerque and Nobre, Paulo and Barbosa, 
                         Henrique M. J. and Mendes, Celso Luiz and Panetta, Jairo",
          affiliation = "{Instituto Nacional de Pesquisas Espaciais (INPE)} and {Instituto 
                         Nacional de Pesquisas Espaciais (INPE)} and {Instituto Nacional de 
                         Pesquisas Espaciais (INPE)} and {National Oceanic and Atmospheric 
                         Administration (NOAA)} and {National Center for Atmospheric 
                         Research} and {Universidade de S{\~a}o Paulo (USP)} and 
                         {Instituto Nacional de Pesquisas Espaciais (INPE)} and {Instituto 
                         Nacional de Pesquisas Espaciais (INPE)} and {University of Miami} 
                         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)} 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)} and {Instituto 
                         Nacional de Pesquisas Espaciais (INPE)} and {Instituto Nacional de 
                         Pesquisas Espaciais (INPE)} and {Instituto Nacional de Pesquisas 
                         Espaciais (INPE)} and {Universidade de S{\~a}o Paulo (USP)} and 
                         {Instituto Nacional de Pesquisas Espaciais (INPE)} and {Instituto 
                         Tecnol{\'o}gico de Aeron{\'a}utica}",
                title = "The Brazilian Global Atmospheric Model (BAM): Performance for 
                         tropical rainfall forecasting and sensitivity to convective scheme 
                         and horizontal resolution",
              journal = "Weather and Forecasting",
                 year = "2016",
               volume = "31",
               number = "5",
                pages = "1547--1572",
             keywords = "Convective parameterization, Forecast verification/skill, 
                         Forecasting, General circulation models, Model 
                         evaluation/performance, Models and modeling, Numerical weather 
                         prediction/forecasting, Operational forecasting.",
             abstract = "This article describes the main features of the Brazilian Global 
                         Atmospheric Model (BAM), analyses of its performance for tropical 
                         rainfall forecasting, and its sensitivity to convective scheme and 
                         horizontal resolution. BAM is the new global atmospheric model of 
                         the Center for Weather Forecasting and Climate Research [Centro de 
                         Previs{\~a}o de Tempo e Estudos Clim{\'a}ticos (CPTEC)], which 
                         includes a new dynamical core and state-of-the-art 
                         parameterization schemes. BAM's dynamical core incorporates a 
                         monotonic two-time-level semi-Lagrangian scheme, which is carried 
                         out completely on the model grid for the tridimensional transport 
                         of moisture, microphysical prognostic variables, and tracers. The 
                         performance of the quantitative precipitation forecasts (QPFs) 
                         from two convective schemes, the Grell-D{\'e}v{\'e}nyi (GD) 
                         scheme and its modified version (GDM), and two different 
                         horizontal resolutions are evaluated against the daily TRMM 
                         Multisatellite Precipitation Analysis over different tropical 
                         regions. Three main results are 1) the QPF skill was improved 
                         substantially with GDM in comparison to GD; 2) the increase in the 
                         horizontal resolution without any ad hoc tuning improves the 
                         variance of precipitation over continents with complex orography, 
                         such as Africa and South America, whereas over oceans there are no 
                         significant differences; and 3) the systematic errors (dry or wet 
                         biases) remain virtually unchanged for 5-day forecasts. Despite 
                         improvements in the tropical precipitation forecasts, especially 
                         over southeastern Brazil, dry biases over the Amazon and La Plata 
                         remain in BAM. Improving the precipitation forecasts over these 
                         regions remains a challenge for the future development of the 
                         model to be used not only for numerical weather prediction over 
                         South America but also for global climate simulations.",
                  doi = "10.1175/WAF-D-16-0062.1",
                  url = "http://dx.doi.org/10.1175/WAF-D-16-0062.1",
                 issn = "0882-8156",
             language = "en",
        urlaccessdate = "27 nov. 2020"
}


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