Urban rainfall in the Capitals of Brazil: Variability, trend, and wavelet analysis

Oliveira‐Júnior, José Francisco de; Filho, Washington Luiz Félix Correia; Monteiro, Lua da Silva; Shah, Munawar; Hafeez, Amna; Góis, Givanildo de; Lyra, Gustavo Bastos; Carvalho, Marcel Abreu de; Santiago, Dimas de Barros; Souza, Amaury de; Mendes, David; Costa, Carlos Eduardo Aguiar de Souza; Blanco, Cláudio José Cavalcante; Zeri, Marcelo; Pimentel, Leonardo Duarte; Jamjareegulgarn, Punyawi; Silva, Elania Barros da

doi:10.1016/j.atmosres.2021.105984

Cited by 18 publications

(9 citation statements)

References 76 publications

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“…The percentages identified show rainfall variability as a function of ENSO phases. However, the human influence on rainfall dynamics cannot be ruled out, particularly the urbanization process which has altered rainfall patterns in Brazil and the NEB [19,50]. During the evaluated period (1960 to 2020), there were several occurrences of ENSO in the Neutral phase.…”

Section: C) South Of the Neb (Sneb)mentioning

confidence: 99%

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Rainfall in the Urban Area and Its Impact on Climatology and Population Growth

et al. 2022

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Due to the scarcity of studies linking the variability of rainfall and population growth in the capital cities of Northeastern Brazil (NEB), the purpose of this study is to evaluate the variability and multiscale interaction (annual and seasonal), and in addition, to detect their trends and the impact of urban growth. For this, monthly rainfall data between 1960 and 2020 were used. In addition, the detection of rainfall trends on annual and seasonal scales was performed using the Mann–Kendall (MK) test and compared with the phases of El Niño-Southern Oscillation (ENSO) and Pacific Decadal Oscillation (PDO). The relationship between population growth data and rainfall data for different decades was established. Results indicate that the variability of multiscale urban rainfall is directly associated with the ENSO and PDO phases, followed by the performance of rain-producing meteorological systems in the NEB. In addition, the anthropic influence is shown in the relational pattern between population growth and the variability of decennial rainfall in the capitals of the NEB. However, no capital showed a significant trend of increasing annual rainfall (as in the case of Aracaju, Maceió, and Salvador). The observed population increase in the last decades in the capitals of the NEB and the notable decreasing trend of rainfall could compromise the region’s water security. Moreover, if there is no strategic planning about water bodies, these changes in the rainfall pattern could be compromising.

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Section: C) South Of the Neb (Sneb)mentioning

confidence: 99%

“…In addition, extreme coastal rainfall events are common in the NEB capital cities [19]. When associated with cities with precarious infrastructure and unplanned growth, these events result in floods, flash flood overflows, and an increase in waterborne diseases (dengue, zika, chikungunya, and leptospirosis) [20,21].…”

Section: Introductionmentioning

confidence: 99%

Rainfall in the Urban Area and Its Impact on Climatology and Population Growth

et al. 2022

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“…The major advantage of wavelet analysis is that it helps in analysing the temporal variations of teleconnection by the decomposition of a signal at various timescales. The study done by Torrence and Compo (1998) and updated by Grinsted et al (2004) increased the popularity of the wavelet tool in geophysical studies (Athira et al, 2022; Das et al, 2020; de Oliveira‐Júnior et al, 2022; Hu & Si, 2016; Keitt & Urban, 2005; Kumar & Foufoula‐Georgiou, 1997; Mitra et al, 2014; Rigozo et al, 2002; Zeri et al, 2019). Özger et al (2009) used cross wavelet transform to examine the teleconnections between ENSO and PDO on droughts in Texas.…”

Section: Introductionmentioning

confidence: 99%

Multiscale association between large‐scale climate variability modes and drought in India via wavelet analysis

Sidhan,

Singh

2024

Intl Journal of Climatology

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Extreme events, such as droughts, are influenced by climate variability modes such as El Niño–Southern Oscillation (ENSO), Pacific Decadal Oscillation (PDO), Atlantic Multi‐decadal oscillation (AMO) and Equatorial Indian Ocean Oscillation (EQUINOO). Due to the significant interdependency among the climatic indices at various frequencies, a time‐frequency framework is necessary to better understand the teleconnection. The present study evaluates the association between climate variability modes and drought index in India using different variants of wavelet analysis such as wavelet coherence analysis (WCA), partial wavelet coherence analysis (PWCA), multiple wavelet coherence analysis (MWCA) and wavelet reconstruction methods. In this study, four major climatic indices (ENSO, PDO, AMO, EQUINOO) and the drought index, standard precipitation index (SPI), at four different monthly time periods (1, 3, 6 and 12) are considered. The results from the WCA analysis highlight significant teleconnection spectra for ENSO, PDO and EQUINOO at 2–8, 8–16 and 16–32 year time‐frequency bands. Further, PWCA results reveal significant interdependency in the teleconnection of ENSO and PDO at all the scales, while ENSO and EQUINOO are found to be independent modes of interannual drought variability in India. Finally, MWCA results show that the combination of EQUINOO and ENSO better explains the interannual variability of droughts in Northwest and Central northeast India. The results of this study will help improve drought prediction and early warning systems in India, by selection of appropriate climatic oscillations for different regions in India.

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“…Regions classified as arid, semi‐arid, dry subhumid and mountainous are extremely susceptible to changes in climate patterns, especially changes in rainfall spatial and temporal variability (Carvalho et al, 2020; Shrestha et al, 2018; Thornthwaite, 1948). In this context, studies on rainfall are essential for Brazil, which is a country of great territorial extension, with biological diversity distributed in six different biomes (Amazon, Atlantic Forest, Caatinga, Cerrado, Pantanal and Pampa), followed by variations in relief and great climatic diversity (Alvares et al, 2013; Oliveira‐Júnior et al, 2022; Santos et al, 2020; Silva Junior et al, 2020). It is worth mentioning that rainfall influences the main economic activities of Brazil, such as agricultural production (Santos et al, 2020; Souza et al, 2020a), tourism and manufacturing industry and, therefore, both activities are extremely dependent on climatic conditions (Bouklikha et al, 2021; Carvalho et al, 2020).…”

Section: Introductionmentioning

confidence: 99%

Long‐term trend analysis in annual, seasonal and monthly rainfall in East Northeast of Brazil and the influence of modes of climate variability

Abreu,

de Souza Fraga,

Lyra

et al. 2023

Intl Journal of Climatology

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The study of rainfall trends is crucial for food security and water availability in Alagoas state, Northeast of Brazil. In this work, monthly, seasonal and annual rainfall trends have been studied (1960–2016) for homogeneous rainfall regions over the eastern part of the Northeast Brazil (ENEB) and later related to climate variability. Cluster analysis was applied to identify homogeneous rainfall regions while the Mann–Kendall (MK), modified Mann–Kendall (MMK) and Pettitt tests were used in the analysis and identification of trends on a spatial and temporal scale. To relate rainfall and climate variability modes, Spearman's correlation was used in each homogeneous region. The rainfall series provided evidence of a general decrease in rainfall in the rainy period and an increase in the dry period, mainly over the driest region. The break points of time series occurred mostly in periods of great variations in values of modes of climate variability, especially the Monthly Niño3.4 Index and the Southern Oscillation Index (SOI), both having a robust influence across the region. Moreover, the probable rainfall in the time series with trends was different in most months before and after the breakpoint. After the breakpoint, probable rainfall was lower, influenced by the breakpoint year (size of the series before and after the breakpoint), which mainly occurred in the 1980s and 1990s and presented a warm phase and a greater number of El Niño events. The MK and MMK trend tests showed the ability to detect trends, although there is no established standard on which test or version to use due to self‐correlated, nonhomogeneous series with nonrandom or nonindependent data. Rainfall is an important variable for water and food security and in the monitoring of natural disasters. The changes detected in this study can be used as reference information for public policies on water resources and future studies for Alagoas and similar regions.

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Urban rainfall in the Capitals of Brazil: Variability, trend, and wavelet analysis

Cited by 18 publications

References 76 publications

Rainfall in the Urban Area and Its Impact on Climatology and Population Growth

Rainfall in the Urban Area and Its Impact on Climatology and Population Growth

Multiscale association between large‐scale climate variability modes and drought in India via wavelet analysis

Long‐term trend analysis in annual, seasonal and monthly rainfall in East Northeast of Brazil and the influence of modes of climate variability

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