Eventos climáticos extremos no ABC Paulista: identificação via Índice Padronizado de Precipitação, condições oceânicas associadas e impactos no nível do reservatório Rio Grande
Data
2021-08-12
Autores
Oliveira, Marina de 
Orientadores
Drumond, Anita Rodrigues de Moraes
Tipo
Trabalho de conclusão de curso
Título da Revista
ISSN da Revista
Título de Volume
Resumo
As alterações no clima têm contribuído com o aumento da ocorrência e intensidade de eventos climáticos extremos. A precipitação é uma das variáveis que permite caracterizar a variabilidade do clima. O Índice Padronizado de Precipitação (SPI) é um indicador que permite detectar eventos climáticos secos e úmidos através de dados de precipitação acumulada em diferentes escalas. Além disso, estudos têm explorado as interações oceano-atmosfera e a influência dos seus modos de variabilidade na climatologia da América do Sul. Entre eles destacam-se o ENOS (El Niño-Oscilação Sul) e o DSAS (Dipolo Subtropical do Atlântico Sul) associados a anomalias de Temperatura da Superfície do Mar (TSM) nos oceanos Pacifico e Atlântico Sul, respectivamente. Os eventos climáticos, tanto os secos como os úmidos, podem gerar impactos negativos ambientais e socioeconômicos, incluindo o desabastecimento hídrico. Regiões mais vulneráveis tendem a ser mais impactadas por eventos extremos. O ABC Paulista, localizado a sudeste da Região Metropolitana de São Paulo (RMSP), é considerado uma região vulnerável diante de extremos climáticos. Compreende sete municípios e abrange a Represa Billings, que possui um dos importantes sistemas de abastecimento hídrico para a RMSP, o reservatório Rio Grande. Os objetivos deste trabalho foram (i) identificar e caracterizar os eventos climáticos secos e úmidos que ocorreram no ABC Paulista no período de 2000-2020 por meio do SPI, (ii) analisar possíveis relações entre os modos de variabilidade climática ENOS e DSAS e a ocorrência desses eventos e, (iii) a partir de um estudo de caso, avaliar a aplicabilidade do SPI no monitoramento e a análise da variação do nível do reservatório Rio Grande. Dados de precipitação do produto de satélite GPM/IMERG foram utilizados no cálculo do SPI para as escalas de acumulação de 1, 3, 6 e 12 meses visando a identificação dos eventos climáticos. As condições climáticas anômalas foram classificadas em leve, moderada, severa ou extrema, e os eventos úmidos e secos identificados segundo os parâmetros de duração, severidade, intensidade e pico. Os índices oceânicos EN3.4 (ENOS), SASDI e SAODI (DSAS) foram extraídos do CPC/NOAA e da página de Teleconexões da UNIFEI. Foram feitas correlações de Pearson entre o SPI e os índices oceânicos para avaliar a variabilidade linear conjunta. Já os dados do nível (m) do reservatório Rio Grande foram obtidos da Companhia de Saneamento Básico do Estado de São Paulo (Sabesp). As análises dos eventos climáticos utilizando o SPI mostraram que as condições úmidas predominaram na primeira década (2000-2010) e as secas na segunda (2010-2020). Foram encontrados 27 eventos úmidos e 25 secos (SPI-1), 15 úmidos e 13 secos (SPI-3), 6 úmidos e 6 secos (SPI-6) e 2 úmidos e 1 seco (SPI-12). O SPI se mostrou eficaz na identificação desses eventos. A correlação entre o SPI e o EN3.4 apresentou valores positivos ao longo do ano (com valor significativo de 0,50 a 95% em novembro), exceto em abril, outubro e dezembro. A correlação entre o SPI e o SASDI não apresentou nenhum mês com significância estatística, enquanto que, para o SAODI, foi encontrada correlação negativa (-0,40) com significância estatística em setembro. Os resultados confirmam a complexidade dos processos que controlam a precipitação no sudeste brasileiro, e particularmente a variabilidade associada ao DSAS precisa ser melhor explorada. Na análise com o nível, utilizou-se a escala SPI-12 e foram identificados dois eventos úmidos, o primeiro atingindo a categoria extremo (Jul/2009-Jan/2012) e o segundo na categoria moderado (Mar/2012-Nov/2013); e um seco na categoria severo (Dez/2013-Jun/2019). Anomalias positivas do SPI-12 coincidiram com anomalias positivas do nível do reservatório, assim como anomalias negativas em ambas as séries. Esse resultado mostra que o SPI, como indicador das condições climáticas, pode ser útil para o planejamento hídrico e alertas no contexto do reservatório Rio Grande.
Climate change has contributed to increase the occurrence and intensity of climate extreme events. Precipitation is one of the variables that allow the characterization of climate variability. The Standardized Precipitation Index (SPI) is an index that allows the identification of dry and wet climate events through precipitation accumulated at different time scales. In addition, studies have explored the ocean-atmosphere interactions and their influence on the South America climate. Two important modes of climate variability are the ENSO (El Niño-Southern Oscillation) and the DSAS (South Atlantic Subtropical Dipole) associated with Sea Surface Temperature (SST) anomalies in the Pacific and the South Atlantic oceans, respectively. Climate extreme events can generate negative environmental and socio-economic impacts, including water shortages. The most vulnerable regions tend to be more impacted by extreme events. The ABC Paulista, located in southeast of the Metropolitan Area of São Paulo (MASP), can be considered a vulnerable region in terms of climatic extremes. It comprises seven municipalities and includes the Billings reservoir, which has one of the important water supply systems for MASP, the Rio Grande reservoir. The objectives of this work were (i) to identify and characterize the dry and wet climate events that occurred in the ABC Paulista in the period 2000-2020 by means of SPI, (ii) to analyze possible relationships between ENSO and DSAS modes of climate variability and the occurrence of these events and, (iii) based on a case study, to evaluate the applicability of SPI in the monitoring and analysis of the variation in the level of the Rio Grande reservoir. Precipitation data from the GPM/IMERG satellite product has been applied to calculate the SPI for the accumulation scales of 1, 3, 6 and 12 months in order to identify the climatic events. The anomalous climate conditions were classified into mild, moderate, severe or extreme, and the anomalous climate events characterized according to the parameters of duration, severity, intensity and peak. The oceanic indices EN3.4 (ENOS), SASDI and SAODI (DSAS) were extracted from CPC/NOAA and UNIFEI's Teleconnections page. Pearson correlations between SPI and ocean indices were calculated to assess joint linear variability. The level data (m) of the Rio Grande reservoir were obtained by the Companhia de Saneamento Básico do Estado de São Paulo (Sabesp). The analysis of climatic events using SPI showed that wet conditions predominated in the first decade (2000-2010) and dry conditions in the second (2010-2020). There were 27 wet and 25 dry events (SPI-1), 15 wet and 13 dry (SPI-3), 6 wet and 6 dry (SPI-6), and 2 wet and 1 dry (SPI-12). The SPI was effective in identifying these events. The correlation between SPI and EN3.4 showed positive values throughout the year (reaching a significant value of 0.5 at 95% in November), except in April, October and December. The correlation between SPI and SASDI did not show any month with statistical significance. However, a negative correlation of (-0.40) between SPI and SAODI with statistical significance was found in september. The results confirm the complexity of the processes that control precipitation in southeastern Brazil, and particularly the variability associated with the DSAS needs to be better explored. For Rio Grande level analysis, using SPI-12, two wet events were identified , the first one reaching the extreme category (Jul/2009-Jan/2012) and the second in the moderate category (Mar/2012-Nov/2013); and one severe dry (Dec/2013-Jun/2019). Positive values of SPI-12 coincided with reservoir level positive anomalies, as well as negative anomalies in both series. This result shows that SPI, as an indicator of climatic conditions, can be useful for water planning and warnings in the context of the Rio Grande reservoir.
Climate change has contributed to increase the occurrence and intensity of climate extreme events. Precipitation is one of the variables that allow the characterization of climate variability. The Standardized Precipitation Index (SPI) is an index that allows the identification of dry and wet climate events through precipitation accumulated at different time scales. In addition, studies have explored the ocean-atmosphere interactions and their influence on the South America climate. Two important modes of climate variability are the ENSO (El Niño-Southern Oscillation) and the DSAS (South Atlantic Subtropical Dipole) associated with Sea Surface Temperature (SST) anomalies in the Pacific and the South Atlantic oceans, respectively. Climate extreme events can generate negative environmental and socio-economic impacts, including water shortages. The most vulnerable regions tend to be more impacted by extreme events. The ABC Paulista, located in southeast of the Metropolitan Area of São Paulo (MASP), can be considered a vulnerable region in terms of climatic extremes. It comprises seven municipalities and includes the Billings reservoir, which has one of the important water supply systems for MASP, the Rio Grande reservoir. The objectives of this work were (i) to identify and characterize the dry and wet climate events that occurred in the ABC Paulista in the period 2000-2020 by means of SPI, (ii) to analyze possible relationships between ENSO and DSAS modes of climate variability and the occurrence of these events and, (iii) based on a case study, to evaluate the applicability of SPI in the monitoring and analysis of the variation in the level of the Rio Grande reservoir. Precipitation data from the GPM/IMERG satellite product has been applied to calculate the SPI for the accumulation scales of 1, 3, 6 and 12 months in order to identify the climatic events. The anomalous climate conditions were classified into mild, moderate, severe or extreme, and the anomalous climate events characterized according to the parameters of duration, severity, intensity and peak. The oceanic indices EN3.4 (ENOS), SASDI and SAODI (DSAS) were extracted from CPC/NOAA and UNIFEI's Teleconnections page. Pearson correlations between SPI and ocean indices were calculated to assess joint linear variability. The level data (m) of the Rio Grande reservoir were obtained by the Companhia de Saneamento Básico do Estado de São Paulo (Sabesp). The analysis of climatic events using SPI showed that wet conditions predominated in the first decade (2000-2010) and dry conditions in the second (2010-2020). There were 27 wet and 25 dry events (SPI-1), 15 wet and 13 dry (SPI-3), 6 wet and 6 dry (SPI-6), and 2 wet and 1 dry (SPI-12). The SPI was effective in identifying these events. The correlation between SPI and EN3.4 showed positive values throughout the year (reaching a significant value of 0.5 at 95% in November), except in April, October and December. The correlation between SPI and SASDI did not show any month with statistical significance. However, a negative correlation of (-0.40) between SPI and SAODI with statistical significance was found in september. The results confirm the complexity of the processes that control precipitation in southeastern Brazil, and particularly the variability associated with the DSAS needs to be better explored. For Rio Grande level analysis, using SPI-12, two wet events were identified , the first one reaching the extreme category (Jul/2009-Jan/2012) and the second in the moderate category (Mar/2012-Nov/2013); and one severe dry (Dec/2013-Jun/2019). Positive values of SPI-12 coincided with reservoir level positive anomalies, as well as negative anomalies in both series. This result shows that SPI, as an indicator of climatic conditions, can be useful for water planning and warnings in the context of the Rio Grande reservoir.
Descrição
Citação
OLIVEIRA, M. Eventos climáticos extremos no ABC Paulista: identificação via Índice Padronizado de Precipitação, condições oceânicas associadas e impactos no nível do reservatório Rio Grande. 2021. 118 f. Trabalho de conclusão de curso (Graduação em Ciências Ambientais) - Instituto de Ciências Ambientais, Químicas e Farmacêuticas, Universidade Federal de São Paulo, Diadema, 2021.