Multifractal analysis of rainfall in coastal area in Pernambuco, Brazil

Detalhes bibliográficos
Autor(a) principal: Barreto, Ikaro Daniel de Carvalho
Data de Publicação: 2021
Outros Autores: Stosic, Tatijana
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Research, Society and Development
Texto Completo: https://rsdjournal.org/index.php/rsd/article/view/12424
Resumo: Global warming and climate change are the mayor concerns of scientists, engineers and policy makers because they affect every aspect of nature and human life. Rainfall and air temperature are the most important variables used to detect climate change, through the statistical analysis of set of indices that describe temperature and rainfall extremes. Over the last decades concepts and methods from complex system science were applied in analysis of hydrological data to describe variability of hydrological processes on multiple temporal and spatial scales. In this work we analyzed daily rainfall temporal series in Recife, Brazil (during the period from 1962 to 2019) using Multifractal Detrended Fluctuation analysis (MFDFA) in order to study long term correlations in subsets of small and large rainfall fluctuations. We calculated multifractal parameters (that quantify position of maximum, width and asymmetry of multifractal spectrum) which are related to different properties of rainfall fluctuations. By comparing the values of these parameters for two subperiods of 29 years, we found that after 1990, rainfall dynamics changed towards stronger persistency, weaker multifractality and decreased dominance of small fluctuations.
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spelling Multifractal analysis of rainfall in coastal area in Pernambuco, BrazilAnálisis multifractal de precipitación en la zona costera de Pernambuco, BrasilAnálise multifractal da precipitação na área costeira de Pernambuco, BrasilRainfallClimate changeMultifractal.PrecipitaciónCambio climáticoMultifractal.PrecipitaçãoMudança climáticaMultifractal.Global warming and climate change are the mayor concerns of scientists, engineers and policy makers because they affect every aspect of nature and human life. Rainfall and air temperature are the most important variables used to detect climate change, through the statistical analysis of set of indices that describe temperature and rainfall extremes. Over the last decades concepts and methods from complex system science were applied in analysis of hydrological data to describe variability of hydrological processes on multiple temporal and spatial scales. In this work we analyzed daily rainfall temporal series in Recife, Brazil (during the period from 1962 to 2019) using Multifractal Detrended Fluctuation analysis (MFDFA) in order to study long term correlations in subsets of small and large rainfall fluctuations. We calculated multifractal parameters (that quantify position of maximum, width and asymmetry of multifractal spectrum) which are related to different properties of rainfall fluctuations. By comparing the values of these parameters for two subperiods of 29 years, we found that after 1990, rainfall dynamics changed towards stronger persistency, weaker multifractality and decreased dominance of small fluctuations.El calentamiento global y el cambio climático son las principales preocupaciones de los científicos, ingenieros y políticos porque afectan todos los aspectos de la naturaleza y la vida humana. Las precipitaciones y la temperatura del aire son las variables más importantes que se utilizan para detectar el cambio climático, mediante el análisis estadístico de un conjunto de índices que describen los extremos de temperatura y precipitación. Durante las últimas décadas, se aplicaron conceptos y métodos de la ciencia de sistemas complejos en el análisis de datos hidrológicos para describir la variabilidad de los procesos hidrológicos en múltiples escalas temporales y espaciales. En este trabajo analizamos series temporales de lluvia diaria en Recife, Brasil (durante el período de 1962 a 2019) utilizando el Multifractal Detrended Fluctuation Analysis (MFDFA) para estudiar las correlaciones a largo plazo en subconjuntos de fluctuaciones de lluvia pequeñas y grandes. Calculamos parámetros multifractales (que cuantifican la posición de máximo, ancho y asimetría del espectro multifractal) que se relacionan con diferentes propiedades de las fluctuaciones de las precipitaciones. Al comparar los valores de estos parámetros para dos subperíodos de 29 años, encontramos que después de 1990, la dinámica de la lluvia cambió hacia una persistencia más fuerte, una multifractalidad más débil y una dominancia disminuida de pequeñas fluctuaciones.O aquecimento global e as mudanças climáticas são as principais preocupações dos cientistas, engenheiros e legisladores, porque afetam todos os aspectos da natureza e da vida humana. A precipitação e a temperatura do ar são as variáveis mais importantes para detectar as alterações climáticas, através da análise estatística de um conjunto de índices que descrevem os extremos de temperatura e precipitação. Nas últimas décadas, conceitos e métodos da ciência de sistemas complexos foram aplicados na análise de dados hidrológicos para descrever a variabilidade dos processos hidrológicos em múltiplas escalas temporais e espaciais. Neste trabalho, analisamos séries temporais de precipitação diária em Recife, Brasil (durante o período de 1962 a 2019) usando a análise Multifractal Detrended Fluctuation Analysis (MFDFA) a fim de estudar correlações de longo prazo em subconjuntos de pequenas e grandes flutuações de chuva. Calculamos parâmetros multifractais (que quantificam a posição de máximo, largura e assimetria do espectro multifractal) que estão relacionados a diferentes propriedades das flutuações da precipitação. Ao comparar os valores desses parâmetros para dois subperíodos de 29 anos, descobrimos que, após 1990, a dinâmica da chuva mudou para uma persistência mais forte, multifractalidade mais fraca e diminuição da dominância de pequenas flutuações.Research, Society and Development2021-02-08info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfhttps://rsdjournal.org/index.php/rsd/article/view/1242410.33448/rsd-v10i2.12424Research, Society and Development; Vol. 10 No. 2; e15410212424Research, Society and Development; Vol. 10 Núm. 2; e15410212424Research, Society and Development; v. 10 n. 2; e154102124242525-3409reponame:Research, Society and Developmentinstname:Universidade Federal de Itajubá (UNIFEI)instacron:UNIFEIenghttps://rsdjournal.org/index.php/rsd/article/view/12424/11086Copyright (c) 2021 Ikaro Daniel de Carvalho Barreto; Tatijana Stosichttps://creativecommons.org/licenses/by/4.0info:eu-repo/semantics/openAccessBarreto, Ikaro Daniel de CarvalhoStosic, Tatijana 2021-03-02T09:32:39Zoai:ojs.pkp.sfu.ca:article/12424Revistahttps://rsdjournal.org/index.php/rsd/indexPUBhttps://rsdjournal.org/index.php/rsd/oairsd.articles@gmail.com2525-34092525-3409opendoar:2024-01-17T09:34:00.212816Research, Society and Development - Universidade Federal de Itajubá (UNIFEI)false
dc.title.none.fl_str_mv Multifractal analysis of rainfall in coastal area in Pernambuco, Brazil
Análisis multifractal de precipitación en la zona costera de Pernambuco, Brasil
Análise multifractal da precipitação na área costeira de Pernambuco, Brasil
title Multifractal analysis of rainfall in coastal area in Pernambuco, Brazil
spellingShingle Multifractal analysis of rainfall in coastal area in Pernambuco, Brazil
Barreto, Ikaro Daniel de Carvalho
Rainfall
Climate change
Multifractal.
Precipitación
Cambio climático
Multifractal.
Precipitação
Mudança climática
Multifractal.
title_short Multifractal analysis of rainfall in coastal area in Pernambuco, Brazil
title_full Multifractal analysis of rainfall in coastal area in Pernambuco, Brazil
title_fullStr Multifractal analysis of rainfall in coastal area in Pernambuco, Brazil
title_full_unstemmed Multifractal analysis of rainfall in coastal area in Pernambuco, Brazil
title_sort Multifractal analysis of rainfall in coastal area in Pernambuco, Brazil
author Barreto, Ikaro Daniel de Carvalho
author_facet Barreto, Ikaro Daniel de Carvalho
Stosic, Tatijana
author_role author
author2 Stosic, Tatijana
author2_role author
dc.contributor.author.fl_str_mv Barreto, Ikaro Daniel de Carvalho
Stosic, Tatijana
dc.subject.por.fl_str_mv Rainfall
Climate change
Multifractal.
Precipitación
Cambio climático
Multifractal.
Precipitação
Mudança climática
Multifractal.
topic Rainfall
Climate change
Multifractal.
Precipitación
Cambio climático
Multifractal.
Precipitação
Mudança climática
Multifractal.
description Global warming and climate change are the mayor concerns of scientists, engineers and policy makers because they affect every aspect of nature and human life. Rainfall and air temperature are the most important variables used to detect climate change, through the statistical analysis of set of indices that describe temperature and rainfall extremes. Over the last decades concepts and methods from complex system science were applied in analysis of hydrological data to describe variability of hydrological processes on multiple temporal and spatial scales. In this work we analyzed daily rainfall temporal series in Recife, Brazil (during the period from 1962 to 2019) using Multifractal Detrended Fluctuation analysis (MFDFA) in order to study long term correlations in subsets of small and large rainfall fluctuations. We calculated multifractal parameters (that quantify position of maximum, width and asymmetry of multifractal spectrum) which are related to different properties of rainfall fluctuations. By comparing the values of these parameters for two subperiods of 29 years, we found that after 1990, rainfall dynamics changed towards stronger persistency, weaker multifractality and decreased dominance of small fluctuations.
publishDate 2021
dc.date.none.fl_str_mv 2021-02-08
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv https://rsdjournal.org/index.php/rsd/article/view/12424
10.33448/rsd-v10i2.12424
url https://rsdjournal.org/index.php/rsd/article/view/12424
identifier_str_mv 10.33448/rsd-v10i2.12424
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv https://rsdjournal.org/index.php/rsd/article/view/12424/11086
dc.rights.driver.fl_str_mv Copyright (c) 2021 Ikaro Daniel de Carvalho Barreto; Tatijana Stosic
https://creativecommons.org/licenses/by/4.0
info:eu-repo/semantics/openAccess
rights_invalid_str_mv Copyright (c) 2021 Ikaro Daniel de Carvalho Barreto; Tatijana Stosic
https://creativecommons.org/licenses/by/4.0
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Research, Society and Development
publisher.none.fl_str_mv Research, Society and Development
dc.source.none.fl_str_mv Research, Society and Development; Vol. 10 No. 2; e15410212424
Research, Society and Development; Vol. 10 Núm. 2; e15410212424
Research, Society and Development; v. 10 n. 2; e15410212424
2525-3409
reponame:Research, Society and Development
instname:Universidade Federal de Itajubá (UNIFEI)
instacron:UNIFEI
instname_str Universidade Federal de Itajubá (UNIFEI)
instacron_str UNIFEI
institution UNIFEI
reponame_str Research, Society and Development
collection Research, Society and Development
repository.name.fl_str_mv Research, Society and Development - Universidade Federal de Itajubá (UNIFEI)
repository.mail.fl_str_mv rsd.articles@gmail.com
_version_ 1797052670094082048

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