Análise do Índice de Precipitação Padronizada (SPI) para o Estado de São Paulo Através de Técnicas Estatísticas Multivariadas e sua Relação com o Oceano Atlântico Sul

• Main Author: Almeida, Letícia Punski de
• Other Authors: Universidade Estadual Paulista (UNESP)
• Format: Bachelor Thesis
• Language: Portuguese
• Published: Universidade Estadual Paulista (Unesp) 2022
• Subjects: Extreme events; Precipitation; SPI; São Paulo; Ocean indices; Eventos extremos; Precipitação; Índices oceânicos; South Atlantic Ocean
• Online Access: http://hdl.handle.net/11449/217047

Não recebi financiamento Extreme climate events can be responsible for natural disasters with great impact on the population and the environment. In this work, the behavior of the Standardized Precipitation Index (SPI), calculated from monthly precipitation data, between 1981-2020, in the state of São Paulo, was evaluated, looking for extreme periods and homogeneous regions, using statistical methods Principal Components (PCA), Factor (FA) and Clustering (CA). In addition, the relationship between the climate variability of precipitation in these homogeneous regions and teleconnection patterns in the South Atlantic Ocean (SAO) was investigated through correlations with six indexes (Tropical Southern Atlantic Index - TSA, South Atlantic Subtropical Anticyclone Index). - IASAS, South Atlantic Ocean dipole Index - SAODI, South Atlantic Subtropical Dipole index - SASDI, TSM Index in RG2 - ITSMRG2 and SST Index in regions RG2 and RG3 - ITSMRG2+RG3). With the PCA applied to the SPI-1, the first five PCs were selected for rotation, which together explained 97.96% of the variability of the original data. After the rotation of the axes, the PCA indicated anomalous conditions throughout the state, more intense to the east in 42.05% (PC1) of the data, and to the west in 38.31% (PC2). The CA (Ward and K-means) pointed out two homogeneous groups with spatial behaviors in agreement with the first two modes of the rotated PCA. The correlation between the SPI-1 and the SAO indices presented three values of significant correlations (95%) negative in PC1, indicating that when positive anomalies of SST occur (ITSMRG2+RG3 in February and May and TSA in October) there are dry conditions in the east of the state, and showed two in CP2, one negative, indicating that positive SST anomalies (ITSMRG2 in April) occur with dry conditions in the west, and one positive, in which the negative phase of SASDI (in November) occurs in dry conditions in the west of the state of São Paulo. Os eventos extremos climáticos podem ser responsáveis ...