Effects of extreme phases of El Niño–Southern Oscillation on rainfall extremes in Alagoas, Brazil

Author:

de Sousa Santos Juliana1ORCID,de Oliveira‐Júnior José Francisco12ORCID,da Silva Costa Micejane1ORCID,Cardoso Kelvy Rosalvo Alencar13ORCID,Shah Munawar45ORCID,Shahzad Rasim45ORCID,da Silva Luis Felipe Francisco Ferreira12ORCID,de Oliveira Romão William Max1ORCID,Singh Sudhir Kumar6ORCID,Mendes David7ORCID,da Silva Santos Iwldson Guilherme8ORCID,da Silva Júnior Rosiberto Salustiano3ORCID

Affiliation:

1. Laboratório de Meteorologia Aplicada e Meio Ambiente (LAMMA), Instituto de Ciências Atmosféricas (ICAT) e Programa de Pós‐Graduação em Arquitetura e Urbanismo (PPGAU) Universidade Federal de Alagoas (UFAL) Maceió Brazil

2. Pós‐Graduação em Engenharia de Biossistemas (PGEB) Universidade Federal Fluminense (UFF) Niterói Brazil

3. Laboratório de Modelagem Atmosférica (LABMODEL), Instituto de Ciências Atmosféricas (ICAT) Universidade Federal de Alagoas (UFAL) Maceió Brazil

4. Institute of Space Technology Islamabad Pakistan

5. College of Surveying and Geoinformatics Tongji University Shanghai China

6. K. Banerjee Centre of Atmospheric and Ocean Studies University of Allahabad Prayagraj India

7. Department of Atmospheric and Climate Sciences (DCAC), Centre for Exact and Earth Sciences (CCET) Federal University of Rio Grande do Norte (UFRN) Natal Brazil

8. Unidade Acadêmica de Ciências Atmosféricas (UACA) e Centro de Tecnologia e Recursos Naturais (CTRN) da Universidade Federal de Campina Grande (UFCG) Campina Grande Brazil

Abstract

AbstractThe Northeast of Brazil (NEB) is influenced by the phases of El Niño–Southern Oscillation (ENSO), which are associated with increased or decreased rainfall in the East NEB (ENEB). The study evaluated the effects of extreme ENSO phases on rainfall extremes in ENEB. Rainfall data from 54 stations in Alagoas were obtained from the National Water and Basic Sanitation Agency (ANA) and subjected to statistical analysis, with a data imputation method used to fill in gaps in the time series. The Inverse Distance Weighting (IDW) method was consistent and suitable for spatially representing rainfall data in the state of Alagoas, according to the adopted statistical indicators. Extreme, decadal and anomaly maps were interpolated using IDW method in Quantum GIS (QGIS), due to the positioning of the stations. The criteria for analysing extreme ENSO years were based on the Oceanic Niño Index (ONI) for region 3.4, between 1960 and 2016. The results show high interannual variability due to ENSO phases in the climatic mesoregions of Alagoas. In over 70% of extreme ENSO years, rainfall was below average (during strong and very strong El Niño) or above average (during strong La Niña). Some cities in the mesoregions of Alagoas experienced higher rainfall than others, even in extreme ENSO situations, suggesting the influence of physiography and multiscale meteorological systems. On a decadal scale, the East region recorded the highest rainfall accumulations, primarily due to decadal variability of two rainfall cores, corresponding to the Metropolitan Region of Maceió (MRM) and the northern part of the state. An exception is the Upper São Francisco region, which experiences dry decades. The East mesoregion (coast) had higher rainfall records compared to the more continental mesoregions (Hinterland and Arid), regardless of ENSO phases and interannual and decadal scales.

Funder

Conselho Nacional de Desenvolvimento Científico e Tecnológico

Publisher

Wiley

Subject

Atmospheric Science

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