Multifractal analysis of standardize precipitation index

Detalhes bibliográficos
Autor(a) principal: Silva, Antonio Samuel Alves da
Data de Publicação: 2021
Outros Autores: Menezes, Rômulo Simões Cezar, Stosic, Tatijana
Tipo de documento: Artigo
Idioma: por
Título da fonte: Research, Society and Development
Texto Completo: https://rsdjournal.org/index.php/rsd/article/view/16535
Resumo: In many tropical countries including Brazil it has been observed that changes in rainfall patterns cause severe floods and with a tendency to continue to worsen during the 21st century. In order to reduce the consequences on human life and health, economic activities, ecosystems and infrastructure with efficient protection measures in mind, it is necessary to develop the most reliable forecasting models. The first step in this direction is a detailed analysis of the climatic variability in the region. In this work, we analyze the multifractal properties of the time series of Standardized Precipitation Index (SPI) developed to classify dry/wet conditions according to severity. This index was calculated for different time scales (1,3,6 and 12 months) and analyzed using the Multifractal detrended fluctuation analysis method. The multifractal spectrum complexity parameters (position of maximum, width and asymmetry) together with Hurst's exponent showed that the SPI series are generated by the multifractal process with stronger multifractality and stronger persistence for larger scales of rainfall accumulation.
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spelling Multifractal analysis of standardize precipitation indexAnálisis multifractal del índice de precipitación estandarizadoAnálise multifractal do índice de precipitação padronizadoMultrifactalPrecipitationSPIPernambuco.MultifractalPrecipitaciónSPIPernambuco.MultrifactalPrecipitaçãoSPIPernambuco.In many tropical countries including Brazil it has been observed that changes in rainfall patterns cause severe floods and with a tendency to continue to worsen during the 21st century. In order to reduce the consequences on human life and health, economic activities, ecosystems and infrastructure with efficient protection measures in mind, it is necessary to develop the most reliable forecasting models. The first step in this direction is a detailed analysis of the climatic variability in the region. In this work, we analyze the multifractal properties of the time series of Standardized Precipitation Index (SPI) developed to classify dry/wet conditions according to severity. This index was calculated for different time scales (1,3,6 and 12 months) and analyzed using the Multifractal detrended fluctuation analysis method. The multifractal spectrum complexity parameters (position of maximum, width and asymmetry) together with Hurst's exponent showed that the SPI series are generated by the multifractal process with stronger multifractality and stronger persistence for larger scales of rainfall accumulation.En muchos países tropicales, incluido Brasil, se ha observado que los cambios en los patrones de lluvia provocan graves inundaciones y sequías con una tendencia a seguir empeorando durante el siglo XXI. Para reducir las consecuencias sobre la vida y la salud humana, las actividades económicas, los ecosistemas y la infraestructura, teniendo en cuenta las medidas de protección eficientes, es necesario desarrollar los modelos de predicción más fiables. El primer paso en esta dirección es un análisis detallado de la variabilidad climática en la región estudiada. En este trabajo, analizamos las propiedades multifractivas de la serie temporal del índice de precipitación estándarizado - SPI desarrollado para clasificar las condiciones secas/húmedas según la severidad. Este índice se calculó para diferentes escalas de tiempo (1, 3, 6 y 12 meses) y se analizó mediante el método de Multifractal detrended fluctuation analysis.  Los parámetros de complejidad del espectro multifractal (posición de máxima, ancho y asimetría) junto con el exponente de Hurst mostraron que las series SPI son generadas por el proceso multifractal con multifractalidad y persistencia más fuerte para escalas más grandes de acumulación de lluvia.Em muitos países tropicais incluindo Brasil observou-se que as mudanças nos padrões de chuva causam inundações e secas com tendência a continuar se agravar durante século 21.  Para diminuir as consequências na vida e saúde humana, atividades econômicas, ecossistemas e infraestrutura é necessário desenvolver modelos de previsão mais confiáveis. O primeiro passo nesta direção é uma análise detalhada da variabilidade climática na região estudada. Neste trabalho analisou-se propriedades multifractais das séries temporais do Índice de Precipitação Padronizado (SPI), desenvolvido para classificar condições secas/úmidas de acordo com severidade. Este índice foi calculado para diferentes escalas de tempo (1, 3, 6 e 12 meses) e analisado utilizando o método Multifractal detrended fluctuation analysis. Os parâmetros de complexidade do espectro multifractal (posição de máximo, largura e assimetria) junto com o expoente de Hurst, mostraram que as séries de SPI são geradas pelo processo multifractal com multifractalidade e persistência mais forte para maiores escalas de acumulação da chuva.Research, Society and Development2021-06-20info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfhttps://rsdjournal.org/index.php/rsd/article/view/1653510.33448/rsd-v10i7.16535Research, Society and Development; Vol. 10 No. 7; e24710716535Research, Society and Development; Vol. 10 Núm. 7; e24710716535Research, Society and Development; v. 10 n. 7; e247107165352525-3409reponame:Research, Society and Developmentinstname:Universidade Federal de Itajubá (UNIFEI)instacron:UNIFEIporhttps://rsdjournal.org/index.php/rsd/article/view/16535/14752Copyright (c) 2021 Antonio Samuel Alves da Silva; Rômulo Simões Cezar Menezes; Tatijana Stosichttps://creativecommons.org/licenses/by/4.0info:eu-repo/semantics/openAccessSilva, Antonio Samuel Alves daMenezes, Rômulo Simões CezarStosic, Tatijana2021-07-18T21:07:03Zoai:ojs.pkp.sfu.ca:article/16535Revistahttps://rsdjournal.org/index.php/rsd/indexPUBhttps://rsdjournal.org/index.php/rsd/oairsd.articles@gmail.com2525-34092525-3409opendoar:2024-01-17T09:37:03.651714Research, Society and Development - Universidade Federal de Itajubá (UNIFEI)false
dc.title.none.fl_str_mv Multifractal analysis of standardize precipitation index
Análisis multifractal del índice de precipitación estandarizado
Análise multifractal do índice de precipitação padronizado
title Multifractal analysis of standardize precipitation index
spellingShingle Multifractal analysis of standardize precipitation index
Silva, Antonio Samuel Alves da
Multrifactal
Precipitation
SPI
Pernambuco.
Multifractal
Precipitación
SPI
Pernambuco.
Multrifactal
Precipitação
SPI
Pernambuco.
title_short Multifractal analysis of standardize precipitation index
title_full Multifractal analysis of standardize precipitation index
title_fullStr Multifractal analysis of standardize precipitation index
title_full_unstemmed Multifractal analysis of standardize precipitation index
title_sort Multifractal analysis of standardize precipitation index
author Silva, Antonio Samuel Alves da
author_facet Silva, Antonio Samuel Alves da
Menezes, Rômulo Simões Cezar
Stosic, Tatijana
author_role author
author2 Menezes, Rômulo Simões Cezar
Stosic, Tatijana
author2_role author
author
dc.contributor.author.fl_str_mv Silva, Antonio Samuel Alves da
Menezes, Rômulo Simões Cezar
Stosic, Tatijana
dc.subject.por.fl_str_mv Multrifactal
Precipitation
SPI
Pernambuco.
Multifractal
Precipitación
SPI
Pernambuco.
Multrifactal
Precipitação
SPI
Pernambuco.
topic Multrifactal
Precipitation
SPI
Pernambuco.
Multifractal
Precipitación
SPI
Pernambuco.
Multrifactal
Precipitação
SPI
Pernambuco.
description In many tropical countries including Brazil it has been observed that changes in rainfall patterns cause severe floods and with a tendency to continue to worsen during the 21st century. In order to reduce the consequences on human life and health, economic activities, ecosystems and infrastructure with efficient protection measures in mind, it is necessary to develop the most reliable forecasting models. The first step in this direction is a detailed analysis of the climatic variability in the region. In this work, we analyze the multifractal properties of the time series of Standardized Precipitation Index (SPI) developed to classify dry/wet conditions according to severity. This index was calculated for different time scales (1,3,6 and 12 months) and analyzed using the Multifractal detrended fluctuation analysis method. The multifractal spectrum complexity parameters (position of maximum, width and asymmetry) together with Hurst's exponent showed that the SPI series are generated by the multifractal process with stronger multifractality and stronger persistence for larger scales of rainfall accumulation.
publishDate 2021
dc.date.none.fl_str_mv 2021-06-20
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/16535
10.33448/rsd-v10i7.16535
url https://rsdjournal.org/index.php/rsd/article/view/16535
identifier_str_mv 10.33448/rsd-v10i7.16535
dc.language.iso.fl_str_mv por
language por
dc.relation.none.fl_str_mv https://rsdjournal.org/index.php/rsd/article/view/16535/14752
dc.rights.driver.fl_str_mv Copyright (c) 2021 Antonio Samuel Alves da Silva; Rômulo Simões Cezar Menezes; Tatijana Stosic
https://creativecommons.org/licenses/by/4.0
info:eu-repo/semantics/openAccess
rights_invalid_str_mv Copyright (c) 2021 Antonio Samuel Alves da Silva; Rômulo Simões Cezar Menezes; 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. 7; e24710716535
Research, Society and Development; Vol. 10 Núm. 7; e24710716535
Research, Society and Development; v. 10 n. 7; e24710716535
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_ 1797052680280997888

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