author = "Bresciani, Caroline and Ferraz, Simone Erotildes Teleginski and 
                         Boiaski, Nathalie Tissot and Herdies, Dirceu Lu{\'{\i}}s",
          affiliation = "{Universidade Federal de Santa Maria (UFSM)} and {Universidade 
                         Federal de Santa Maria (UFSM)} and {Universidade Federal de Santa 
                         Maria (UFSM)} and {Instituto Nacional de Pesquisas Espaciais 
                title = "Climatology for precipitation in Brazil by the BAM model",
            booktitle = "Proceedings...",
                 year = "2020",
         organization = "American Meteorological Society Annual Meeting, 100.",
             abstract = "Precipitation is one of the main meteorological variables that 
                         define the climate of each region. The annual distribution of the 
                         precipitation, as well as the amount and duration, are key factors 
                         in the maintenance of various sectors that depend on water 
                         availability, such as the energy sector, agricultural crops, 
                         industries, human consumption, etc. Due to the vast territory and 
                         different geography, in Brazil different atmospheric systems 
                         operate and develop in each region, which results in an 
                         inhomogeneity in the spatial and temporal distribution of 
                         precipitation. Some Brazilian regions have a well-defined annual 
                         precipitation distribution, characterizing a dry season (winter) 
                         and a wet season (summer), such as the Southeast, Midwest and part 
                         of the North. The southern region of Brazil has a uniform 
                         distribution of precipitation showing high values due to the 
                         action of medium latitude atmospheric systems, mainly cold fronts 
                         and mesoscale convective systems. The Northeast region presents a 
                         seasonal variation influenced by the displacement of the 
                         Intertropical Convergence Zone (ITCZ), which shifts according to 
                         the season established in the South, during the summer and in the 
                         North during the winter of the Southern Hemisphere. The same 
                         influence is observed in the far north of the country. Therefore, 
                         the representation of precipitation is very complex and the need 
                         for numerical models calibrated according to the atmospheric 
                         conditions of the region to be analyzed is increasing. In view of 
                         this need, researchers from the National Institute for Space 
                         Research (INPE) in conjunction with several Universities have been 
                         developing the Brazilian Global Atmospheric Model (BAM). BAM is an 
                         evolving model in Brazil, based on the CPTEC/INPE global 
                         atmospheric model called AGCM3 and seeks the best representation 
                         of Brazilian conditions. With this in mind, this paper aims to 
                         evaluate the performance of the BAM model in the representation of 
                         precipitation in Brazil from the comparison with observed data. In 
                         this study, we used precipitation data from the global BAM model, 
                         with a resolution of approximately 1, generated by the National 
                         Institute for Space Research (INPE), from September, 1990 to 
                         December, 2013. In addition to the model, we used daily observed 
                         precipitation data of Brazil from the National Institute of 
                         Meteorology (INMET), the National Water Agency (ANA) and the 
                         Department of Water and Electric Energy of S{\~a}o Paulo (DAEE), 
                         from 1990 to 2013, interpolated in high spatial resolution (0.25 
                         x 0.25), for the comparison of the results obtained from the two 
                         sets. Both sets of data underwent an interpolation process for a 
                         spatial resolution network of approximately 1  for data 
                         comparison. The analyzes were obtained from statistical methods, 
                         with the mean and monthly standard deviation of the accumulated 
                         precipitation, applied to both data sets, the difference between 
                         the two data sets and the Pearson correlation coefficient 
                         analysis. Overall, the initial results showed a good deal of 
                         agreement between the two sets.",
  conference-location = "Boston, USA",
      conference-year = "12-16 jan.",
             language = "en",
        urlaccessdate = "12 abr. 2021"