Análise climática pontual de eventos extremos de precipitação no Rio Grande do Sul.

Abstract

This study presents a quantitative analysis of extreme precipitation events that can cause flood in the following cities of Rio Grande do Sul State: Bagé, Encruzilhada do Sul, Iraí, Passo Fundo, Pelotas, Porto Alegre, Santa Maria, Santa Vitória do Palmar, São Luiz Gonzaga, Torres and Uruguaiana. Here, we considers event that can cause flood every time the precipitation rate (threshold) is greater than or equal to the average precipitation rate based on the flood history of each city. The thresholds were obtained following the flood cases collected from some sources, as Defesa Civil Estadual, whereas daily precipitation data were provided by INMET (Instituto Nacional de Meteorologia) e ANA (Agência Nacional de Águas) from 1961 to 2010. The daily data were analyzed until 30 days before the flood day in order to obtaining the daily accumulated mean and, hence, the thresholds (for a given lag of days) that might indicate a possible flood in the city. Subsequently, there was obtained the quantification of these extreme precipitation events, as well as its time variation. In general, it was observed the number of occurrences have positive linear trend in most cities, although not significant due the great interannual variability. According to scientific literature, rainfall in southern Brazil may be influenced by Sea Surface Temperature (SST) of Atlantic e Pacific. Here, such influence was found by means of linear correlation between climate indices - Multivariate Enso Index (MEI), Oceanic Nino Index (ONI), Southern Oscillation Index (SOI), Pacific Decadal Oscillation (PDO), Índice do Atlântico Sul (IAS), Índice do Atlântico Tropical (IAT) and Índice do Atlântico Sul e Tropical (IAST) - and the number of possible flood cases in the selected cities. The results show a significant correlation, significance level above 95%, between the indices MEI, SOI, ONI, PDO, IAS and IAST and the flood cases in such regions of State. Only the IAT index do not showed significant correlation with any region of Rio Grande do Sul (RS), that is, SST variations in the tropical region of Atlantic ocean have no influences in flood cases of RS.