Efeitos do El Niño-Oscilação Sul nos eventos extremos de chuva em Alagoas

Abstract

Extreme weather events can cause major disruptions in various areas of society. Intense rains and droughts can promote the collapse of infrastructure services, deaths and impacts on production in the hydroelectric and agricultural sectors. Northeast Brazil (NEB) has great rainfall variability and is influenced by several meteorological systems, such as the El Niño-Southern Oscillation (ENSO). The cold (La Niña) and warm (El Niño) phases are commonly associated with increased and decreased rainfall in the state of Alagoas. The study of the extreme phases of ENSO is important to understand its impacts. Therefore, this work identified the years of occurrence of extremes in Alagoas, mapped the distribution of rainfall in years of extreme ENSO and evaluated the effects of extreme phases of ENSO on extreme rainfall events in Alagoas. The rainfall data used belong to the hydrometeorological network of the National Water Agency (ANA). In addition to statistical analyses, maps were generated, whose interpolation (Inverse Distance Weighting – IDW) was performed using Quantum GIS software (QGIS). Criteria for highlighting and analyzing extreme ENSO years were based on the Oceanic Niño Index (ONI) for region 3.4. The results obtained show the great interannual variability due to the influences of ENSO. In more than 70% of extreme ENSO years, rainfall was below or above average and coincided with the El Niño and La Niña phases, respectively. Some cities had higher precipitation values than the others even in an El Niño year, which can be explained by the physiographic characteristics of the place. From the analysis of the spatial distribution it was possible to observe that the climatic mesoregion closer to the coast (Leste) presented higher precipitation rates than the more continental regions (Agreste and Sertão). Wetter regions also had greater dispersion of rainfall data. It is worth mentioning that the ONI anomaly managed to represent negative anomalies in a large part of the State, however in some years it underestimated or overestimated. The results make it possible to understand how extreme rainfall events in Alagoas behave in relation to ENSO episodes.