Variabilidade da precipitação pluviométrica da microrregião de Campo Mourão e sua associação com anomalias de temperatura da superfície do mar

• Ano de defesa: 2019
• Autor(a) principal: Marins , Jeremias Alécio Leperes de
• Orientador(a): Limberger, Leila
• Banca de defesa: Limberger, Leila , Massoquim, Nair Glória , Calegari, Márcia Regina
• Tipo de documento: Dissertação
• Tipo de acesso: Acesso aberto
• Idioma: por
• Instituição de defesa: Universidade Estadual do Oeste do Paraná; Marechal Cândido Rondon
• Programa de Pós-Graduação: Programa de Pós-Graduação em Geografia
• Departamento: Centro de Ciências Humanas, Educação e Letras
• País: Brasil
• Palavras-chave em Português: Caracterização climática da MRCM; Variabilidade climática da MRCM; Mapa de correlação linear; Regressão linear; Modelo estocástico para simulação de chuva
• Área do conhecimento CNPq: CIÊNCIAS HUMANAS:GEOGRAFIA
• Link de acesso: http://tede.unioeste.br/handle/tede/4363

Climate is an important input of the socioeconomic activities, mainly in what concern its variability, because are the anomalies that achieve the society the most. One of the originator of climate variability are the Sea Surface Temperature (SST), considering ocean and atmosphere are coupled. This research aims to understand the climate variability of the Campo Mourão Microregion Geographical (MRCM) and its association with SST anomalies. In the climatic characterization it was identified a spatial variability of the rainfall, with higher values registered in the South area. Regarding temporal variability it was identified that, mainly about positive rainy anomalies, they are associated with El Niño. However, several events of anomalies, positive and negative, were not associated with ENOS events. To identify other SST areas that may be associated with rainy variability in the MRCM it was elaborated a correlation map. In this, it was identified 6 areas best correlated with the rainfall in the MRCM, being West Indic, Central Pacific, Antarctic, PDO, North Atlantic and South Tropical Atlantic. The linear regression model shows that the most important area that contributes in rainfall modulation in the MRCM is Equatorial Pacific, associated to ENOS events, followed by Antarctic and PDO.