@Article{MendesMareRodrOliv:2014:DoStMo,
               author = "Mendes, David and Marengo, Jos{\'e} Antonio and Rodrigues, Sidney 
                         and Oliveira, Magaly",
          affiliation = "Climate Science Program, Federal University of Rio Grande do Norte 
                         and {Instituto Nacional de Pesquisas Espaciais (INPE)} and 
                         {WorldWild Life Fund Brazil (WWF)} and {WorldWild Life Fund Brazil 
                         (WWF)}",
                title = "Downscaling Statistical Model Techniques for Climate Change 
                         Analysis Applied to the Amazon Region",
              journal = "Advances in Artificial Neural Systems",
                 year = "2014",
               volume = "2014",
                pages = "1--10",
             abstract = "The Amazon is an area covered predominantly by dense tropical 
                         rainforest with relatively small inclusions of several other types 
                         of vegetation. In the last decades, scientific research has 
                         suggested a strong link between the health of the Amazon and the 
                         integrity of the global climate: tropical forests and woodlands 
                         (e.g., savannas) exchange vast amounts of water and energy with 
                         the atmosphere and are thought to be important in controlling 
                         local and regional climates. Consider the importance of the Amazon 
                         biome to the global climate changes impacts and the role of the 
                         protected area in the conservation of biodiversity and 
                         state-of-art of downscaling model techniques based on ANN 
                         Calibrate and run a downscaling model technique based on the 
                         Artificial Neural Network (ANN) that is applied to the Amazon 
                         region in order to obtain regional and local climate predicted 
                         data (e.g., precipitation). Considering the importance of the 
                         Amazon biome to the global climate changes impacts and the 
                         state-of-art of downscaling techniques for climate models, the 
                         shower of this work is presented as follows: the use of ANNs good 
                         similarity with the observation in the cities of BelŽem and 
                         Manaus, with correlations of approximately 88.9% and 91.3%, 
                         respectively, and spatial distribution, especially in the 
                         correction process, representing a good fit.",
                  doi = "10.1155/2014/595462",
                  url = "http://dx.doi.org/10.1155/2014/595462",
                 issn = "1687-7594",
                label = "lattes: 5719239270509869 2 MendesMareRodrOliv:2014:DoStMo",
             language = "en",
           targetfile = "595462.pdf",
        urlaccessdate = "28 abr. 2024"
}