Rainfall extremes and drought in Northeast Brazil and its relationship with El Niño–Southern Oscillation

• Published in: International journal of climatology 2021-01, Vol.41 (S1), p.E2111-E2135
• Main Authors: Costa, Micejane da Silva, Oliveira‐Júnior, José Francisco de, Santos, Paulo José dos, Correia Filho, Washington Luiz Félix, Gois, Givanildo de, Blanco, Cláudio José Cavalcante, Teodoro, Paulo Eduardo, Silva Junior, Carlos Antonio da, Santiago, Dimas de Barros, Souza, Edson de Oliveira, Jardim, Alexandre Maniçoba da Rosa Ferraz
• Format: Article
• Language: English
• Subjects: Agriculture; Annual precipitation; Civil defense; climate extremes; Climatic extremes; Cluster analysis; Drought; drought index; Drought periods; El Nino; El Nino phenomena; El Nino-Southern Oscillation event; El Nino-Southern Oscillation event-rainfall relationships; ENSO; Extreme drought; Extreme weather; La Nina; Monthly rainfall; Monthly rainfall data; Multivariate analysis; multivariate statistics; Principal components analysis; Rain; Rainfall; Rainfall data; Southern Oscillation; SPI; Standardized precipitation index; Variance analysis; Vulnerability
• ISSN: 0899-8418; 1097-0088
• DOI: 10.1002/joc.6835

The objective of this study was to evaluate the annual standardized precipitation index (SPI) obtained from the DrinC software based on multivariate analysis in the identification of rainfall and drought extremes in the State of Alagoas and its relationship with El Niño–Southern Oscillation. Monthly rainfall data from 1960 to 2016 from National Water Agency were analysed. Annual SPI (SPI‐12) has been designed for comparison with ENSO phases via Oceanic Niño Index for 3.4 region and in identifying climate extremes in the State of Alagoas. The principal component analysis and cluster analysis techniques were applied to the rainfall series of SPI‐12. Extreme events were identified in both rainy and drought periods according to SPI‐12, and were associated with the ENSO phases (El Niño, La Niña, and Neutral). The first four principal components explained 46.68% of the variance. Our findings are crucial for agriculture and civil defence since northeastern Brazil has several areas of risk and social vulnerability. Monthly rainfall data from 1960 to 2016 from National Water Agency. The time series was treated for failures using data imputing technique and then used by DrinC to obtain the SPI‐12. The principal component analysis and cluster analysis techniques were applied to the rainfall series of SPI‐12. Extreme events were identified in both rainy and drought periods according to SPI‐12, and were associated with the ENSO phases (El Niño, La Niña, and Neutral).