Submitted by Automa??o e Estat?stica (sst@bczm.ufrn.br) on 2016-01-15T14:36:00Z No. of bitstreams: 1 WashingtonLuizFelixCorreiaFilho_TESE.pdf: 1284178 bytes, checksum: 828e65ac066df616cd79dbeb9443edfe (MD5) / Approved for entry into archive by Elisangela Moura (lilaalves@gmail.com) on 2016-01-25T13:43:02Z (GMT) No. of bitstreams: 1 WashingtonLuizFelixCorreiaFilho_TESE.pdf: 1284178 bytes, checksum: 828e65ac066df616cd79dbeb9443edfe (MD5) / Made available in DSpace on 2016-01-25T13:43:02Z (GMT). No. of bitstreams: 1 WashingtonLuizFelixCorreiaFilho_TESE.pdf: 1284178 bytes, checksum: 828e65ac066df616cd79dbeb9443edfe (MD5) Previous issue date: 2014-03-27 / Nesta tese foram utilizados tr?s diferentes modelos de regress?o, os Modelos Lineares Generalizados via regress?o log?stica e de Poisson e os Modelos Vetoriais Lineares Generalizados via distribui??o generalizada de valores extremos (MVLG-GEV) com o objetivo de detectar os extremos de precipita??o no Nordeste do Brasil. Inicialmente aplicaram-se os modelos de regress?o log?stica e de Poisson para identificar as intera??es entre os extremos de precipita??o e as demais vari?veis a partir das raz?es de chances e de riscos relativos. Constatou-se que a vari?vel indicadora da ocorr?ncia de extremos de precipita??o ? a radia??o de onda longa, verificada nas regi?es leste, norte e semi?rido do NEB, e a umidade relativa foi verificada no sul do NEB, em ambos os modelos. Os resultados apresentados pelos modelos de regress?o log?stica e de Poisson mostram evid?ncias de que estes extremos de precipita??o s?o impulsionados pela Oscila??o Madden-Julian, que ao interagir com os outros sistemas meteorol?gicos locais, regionais e grande escala podem ocasionar a ocorr?ncia destes extremos. O terceiro modelo, MVLG-GEV, avaliou os extremos a partir dos m?ximos anuais de precipita??o de forma m?ltipla (a partir de um conjunto de vari?veis) e constatou-se que as vari?veis que subsidiaram a ocorr?ncia dos extremos de precipita??o foram: as componentes zonal e meridional do vento, evapora??o e TSM (Atl?ntico e Pac?fico). Este artigo mostra evid?ncias de que a variabilidade da TSM vistas no Atl?ntico como no Pac?fico (El Ni?o-Oscila??o Sul) interfera na variabilidade interanual da precipita??o, modificando o padr?o de circula??o atmosf?rica na regi?o, resultando na intensifica??o ou inibi??o da ocorr?ncia dos extremos de precipita??o. Os coeficientes de regress?o log?stica, de Poisson e de MVLG-GEV demonstraram signific?ncia estat?stica, inferiores a 5%. Em rela??o aos n?veis de retorno para os pr?ximos 30 anos pelos MVLG-GEV, o menor n?vel foi de 91,62mm no sul da Bahia, enquanto o maior foi de 185,72mm no norte do Cear?. / In this thesis used four different methods in order to diagnose the precipitation extremes on Northeastern Brazil (NEB): Generalized Linear Model s via logistic regression and Poisson, extreme value theory analysis via generalized extre me value (GEV) and generalized Pareto (GPD) distributions and Vectorial Generalized Linea r Models via GEV (MVLG GEV). The logistic regression and Poisson models were used to identify the interactions between the precipitation extremes and other variables based on the odds ratios and relative risks. It was found that the outgoing longwave radiation was the indicator variable for the occurrence of extreme precipitation on eastern, northern and semi arid NEB, and the relative humidity was verified on southern NEB. The GEV and GPD distribut ions (based on the 95th percentile) showed that the location and scale parameters were presented the maximum on the eastern and northern coast NEB, the GEV verified a maximum core on western of Pernambuco influenced by weather systems and topography. The GEV and GPD shape parameter, for most regions the data fitted by Weibull negative an d Beta distributions (? < 0) , respectively. The levels and return periods of GEV (GPD) on north ern Maranh?o (centerrn of Bahia) may occur at least an extreme precipitation event excee ding over of 160.9 mm /day (192.3 mm / day) on next 30 years. The MVLG GEV model found tha t the zonal and meridional wind components, evaporation and Atlantic and Pacific se a surface temperature boost the precipitation extremes. The GEV parameters show the following results: a) location ( ), the highest value was 88.26 ? 6.42 mm on northern Maran h?o; b) scale ( ? ), most regions showed positive values, except on southern of Maranh?o; an d c) shape ( ? ), most of the selected regions were adjusted by the Weibull negative distr ibution ( ? < 0 ). The southern Maranh?o and southern Bahia have greater accuracy. The level period, it was estimated that the centern of Bahia may occur at least an extreme precipitatio n event equal to or exceeding over 571.2 mm/day on next 30 years.