Climatology for Precipitation in Brazil by the BAM Model

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 São 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.