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

Costa, Marcelo Viana da; Oliveira‐Júnior, José Francisco de; Santos, Paulo José dos; Filho, Washington Luiz Félix Correia; Góis, Givanildo de; Blanco, Cláudio José Cavalcante; Teodoro, Paulo Eduardo; Silva, Carlos Antônio da; Santiago, Dimas de Barros; Souza, Edson de Oliveira; Jardim, Alexandre Maniçoba da Rosa Ferraz

doi:10.1002/joc.6835

Cited by 60 publications

(70 citation statements)

References 74 publications

(168 reference statements)

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“…Na avaliação do desempenho dos dados do CHELSA foram usados os seguintes parâmetros estatísticos: os coeficientes de determinação (R 2 ) e correlação linear de Pearson (r), Erro Padrão da Estimativa (EPE, mm) e Raiz Quadrada do Erro Quadrático Médio (RMSE, mm), conforme as equações a seguir. (Lyra et al, 2017;Costa et al, 2020).…”

Section: Estatística Aplicada E As Fases Do Enosunclassified

“…O munícipio de Maceió, entre 1960 a 1989 (período 1 -P1), houve diversos anos chuvosos, sendo superiores a média histórica do período (1838 mm), com destaque para os anos de 1964 (2455,70 mm), 1969 (2680,90 mm), 1977 (2664,80 mm) e 1989 (2985,65 mm). Ambos os anos citados correspondem aos eventos de ENOS (El Niño e La Niña), comuns no Estado de Alagoas, particularmente na mesorregião do Leste Alagoano (Lyra et al, 2017;Costa et al, 2020), e no NEB (Marengo et al, 2018;Correia Filho et al, 2019). Situação contrária, entre 1990 a 2016 (período 2 -P2), onde houve uma diminuição significava de anos chuvosos em relação à média, as exceções foram 2000 (2617,96 mm), 2009 (2674,30 mm) e 2011 (2372,70 mm) -(Figura 3a).…”

Section: Variabilidade Anual E Decadal Da Chuvaunclassified

“…Situação contrária, entre 1990 a 2016 (período 2 -P2), onde houve uma diminuição significava de anos chuvosos em relação à média, as exceções foram 2000 (2617,96 mm), 2009 (2674,30 mm) e 2011 (2372,70 mm) -(Figura 3a). As exceções mencionadas anteriormente correspondem aos episódios de La Niña, que por sua vez são responsáveis pelo aumento considerável de chuva no NEB, principalmente na costa (Correia Filho et al, 2019;Da Silva et al, 2020;Costa et al, 2020).…”

Section: Variabilidade Anual E Decadal Da Chuvaunclassified

“…Em geral, o período P1 foi período de ocorrências de chuvas superiores à média histórica, enquanto no período P2 houve redução significativa da chuva no munícipio de Maceió. As fases do ENOS são responsáveis diretas pela variabilidade da chuva interanual em Maceió, porém não se descarta a influência do modo de variabilidade climática Oscilação Decadal do Pacífico (ODP), identificado anteriormente por Lyra et al (2017), visto que a variabilidade decadal está diretamente ligada à mudança de fase da ODP, que por sua vez intensifica as fases do ENOS (Lyra et al, 2017;Costa et al, 2020).…”

Section: Variabilidade Anual E Decadal Da Chuvaunclassified

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Climatologia da Chuva em Maceió: Aspectos Climáticos e Ambientais

Júnior

Souza

et al. 2021

Rev. Bras. Geog. Fis.

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The objectives of the study are: i) to evaluate the climatology of rain in Maceió based on observed data, with emphasis on climatic and environmental aspects and ii) to validate the precipitation product for the municipality. Data from 1979 to 2013 of the precipitation product CHELSA (Climatologies at High Resolution for the Earth's Land Surface Areas) were validated by rainfall data from the National Water Agency (NWA) from 1960 to 2016. Statistical indicators showed a high coefficient of determination and linear correlation between CHELSA and observed data (R2 = 0.80; r = 0.89) and the smallest errors (SEE = 6.58 mm and RMSE = 18.76 mm), therefore the CHELSA product can be applied in the region. The time series presented a period 1 (P1) - (1960 to 1989) with rainfall above the historical average and a period 2 (P2) - (1990 to 2016) with a significant reduction in rainfall. Observed data versus climatological normals showed a significant decrease in normal 1 (1961-1990) in the rainy season, while in relation to normal 2 (1981-2010) there was an increase in the months of February, March and April (between 10 to 20%) and October and December (between 5 to 15%). The spatial distribution of monthly rainfall via the CHELSA product showed the formation of a pluviometric gradient between the coast and the upper part of Maceió. The topography influences the rainfall regime in neighborhoods belonging to the administrative regions (AR) - (R4, R5 and R6) with the highest rainfall records. The ENOS phases are directly responsible for the variability of interannual rain, while the decadal variability corresponded to the PDO phase change and changes in land use and occupation in Maceió.

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Section: Estatística Aplicada E As Fases Do Enosunclassified

Section: Variabilidade Anual E Decadal Da Chuvaunclassified

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Climatologia da Chuva em Maceió: Aspectos Climáticos e Ambientais

Júnior

Souza

et al. 2021

Rev. Bras. Geog. Fis.

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“…In addition, there was a time lag between dry-hot conditions and ENSO [19]. In the arid and semi-arid regions in Northeast Brazil and East Africa and arid to semi-arid subtropical regions, ENSO and drought were closely correlated in different periods with a certain degree of time lag [20][21][22]. In view of the MJO, most researchers have analyzed the influence of MJO on drought mainly by studying the correlation between it and rainfall.…”

Section: Introductionmentioning

confidence: 99%

The Influence of ENSO and MJO on Drought in Different Ecological Geographic Regions in China

Zhou

Wang

et al. 2021

Remote Sensing

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Mastering the spatial and temporal differences of ENSO (EI Niño-Southern Oscillation) and MJO (Madden–Julian Oscillation) and their influence on drought is very important for accurately monitoring and forecasting drought. In this study, spatiotemporal characteristics and variability of the impact of ENSO and MJO on drought were analyzed from the perspectives of meteorological drought and agricultural drought through temporal and spatial correlation analyses of China’s 48 eco-geographical regions. The results show a strong correlation between drought and ENSO and MJO in general. The spatial correlation coefficients are different, and the response of extreme events varies in different regions. The influence of ENSO and MJO on agricultural drought is higher than that on meteorological drought. ENSO and MJO have a considerable influence on agricultural drought in regions such as the Qinghai-Tibet Plateau and Xinjiang, with the highest correlation coefficient of 0.72. A significant influence of ENSO and MJO on meteorological drought was found in the Jiangnan region with the highest correlation coefficient of 0.40. In addition, agricultural drought shows a significant time lag in response to ENSO events. When the lag time is six months, the time series presents the highest correlation coefficient with the mean value of the correlation coefficient reaching 0.38 and the maximum value reaching 0.75. This research is of great significance for understanding the spatiotemporal correlation between climate patterns and drought on a large regional scale and it provides further insights into the teleconnection mechanisms of drought.

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Historical contamination with a current problem: Can mining tailings enhance coastal arsenic pollution?

Nascimento

Longhini

Cagnin

et al. 2023

Integr Envir Assess & Manag

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The coast of Espírito Santo state (Southeast Brazil) is recognized for its environmental arsenic (As) enrichment and, over the years, mining operations have potentialized it. We aimed to evaluate the effect of Rio Doce discharge on As inputs and the role of iron ore tailings from the Fundão dam disaster in enhancing As contamination in the marine sediment. Two scenarios were evaluated: Predisaster and Postdisaster; dry and wet conditions were considered in each period. High As concentrations were found in the Predisaster (28.44 ± 13.53 µg g−1), but a significant increase in As was remarkable during the Postdisaster in the wet season, one year after the disaster (maximum of 58.39 µg g−1; geoaccumulation index (Igeo) Class 3, moderately severe pollution). On that occasion, iron (Fe) oxy‐hydroxides from tailings were remobilized from the Rio Doce channel and deposited on the continental shelf bottom. Therefore, chemical interactions among Fe, As, and carbonates were enhanced, resulting in As and Fe coprecipitation and the trapping by carbonate adsorption. Rio Doce discharge seems to be the main factor in As inputs to the inner continental shelf when flooding do not occur previously in samplings, which allows further dispersion of contaminants, although this hypothesis should be tested further. Integr Environ Assess Manag 2023;00:1–10. © 2023 SETAC

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

Cited by 60 publications

References 74 publications

Climatologia da Chuva em Maceió: Aspectos Climáticos e Ambientais

Climatologia da Chuva em Maceió: Aspectos Climáticos e Ambientais

The Influence of ENSO and MJO on Drought in Different Ecological Geographic Regions in China

Historical contamination with a current problem: Can mining tailings enhance coastal arsenic pollution?

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