Uma aplicação do SPI (Standardized Precipitation Index) para dados de chuvas mensais em Pernambuco entre 1991-2019
Autor(a) principal: | |
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Data de Publicação: | 2023 |
Outros Autores: | , , , , |
Tipo de documento: | Artigo |
Idioma: | por |
Título da fonte: | Research, Society and Development |
Texto Completo: | https://rsdjournal.org/index.php/rsd/article/view/43217 |
Resumo: | The determination and classification of regions prone to critical weather events, both intense rainfall and drought periods, are of utmost importance in the context of climate variability. In the Brazilian Northeast, a semi-arid region, drought is a recurring problem, while intense weather events such as heavy rains and landslides affect metropolitan areas and cause disasters. The state of Pernambuco shows a trend of extreme weather events, with long periods of drought and intense rainfall, which is responsible for numerous natural disasters in the state. The objective of this study was to analyze and classify, in an objective manner, the climate variability between 1991 and 2019 in the five stations of Pernambuco represented by Recife, Palmares, Itaíba, Salgueiro, and Petrolina, based on different time scales (1, 3, 6, 9, 12, 24, and 36 months). For this purpose, the Standardized Precipitation Index (SPI) was used, developed to classify dry and wet conditions according to severity. Through the analysis, it was observed that the smaller scales SPI-1 and SPI-3 revealed the onset and trajectory of each event, while the other scales identified the most intense and prolonged events. The results obtained indicated that drought periods had longer duration and intensity, with the driest month in Itaíba being -4.416 (SPI-3) in August 2018. However, rainy periods occurred more frequently in the stations, with the wettest month being in Palmares with 2.928 (SPI-3) in September 2000. |
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Uma aplicação do SPI (Standardized Precipitation Index) para dados de chuvas mensais em Pernambuco entre 1991-2019An application of SPI (Standardized Precipitation Index) to monthly rainfall data in Pernambuco between 1991-2019Una aplicación del SPI (Standardized Precipitation Index) para datos de lluvas mensuales en Pernambuco entre 1991-2019Índice de Precipitación Estandarizado (SPI)Variabilidad climáticaEstacionesPernambuco.Índice de Precipitação Padronizado (SPI)Variabilidade climáticaEstaçõesPernambuco.Standardized Precipitation Index (SPI)Climate variabilityStationsPernambuco.The determination and classification of regions prone to critical weather events, both intense rainfall and drought periods, are of utmost importance in the context of climate variability. In the Brazilian Northeast, a semi-arid region, drought is a recurring problem, while intense weather events such as heavy rains and landslides affect metropolitan areas and cause disasters. The state of Pernambuco shows a trend of extreme weather events, with long periods of drought and intense rainfall, which is responsible for numerous natural disasters in the state. The objective of this study was to analyze and classify, in an objective manner, the climate variability between 1991 and 2019 in the five stations of Pernambuco represented by Recife, Palmares, Itaíba, Salgueiro, and Petrolina, based on different time scales (1, 3, 6, 9, 12, 24, and 36 months). For this purpose, the Standardized Precipitation Index (SPI) was used, developed to classify dry and wet conditions according to severity. Through the analysis, it was observed that the smaller scales SPI-1 and SPI-3 revealed the onset and trajectory of each event, while the other scales identified the most intense and prolonged events. The results obtained indicated that drought periods had longer duration and intensity, with the driest month in Itaíba being -4.416 (SPI-3) in August 2018. However, rainy periods occurred more frequently in the stations, with the wettest month being in Palmares with 2.928 (SPI-3) in September 2000.La determinación y clasificación de regiones propensas a eventos climáticos críticos, tanto de lluvias intensas como de períodos de sequía, es de suma importancia en el ámbito de la variabilidad climática. En el noreste de Brasil, una región semiárida, la sequía es un problema recurrente, mientras que eventos climáticos intensos, como fuertes lluvias y deslizamientos de tierra, afectan a las regiones metropolitanas y causan desastres. El estado de Pernambuco presenta una tendencia a eventos climáticos extremos, con largos períodos de sequía y lluvias intensas, lo que es responsable de numerosos desastres naturales en el estado. El objetivo del trabajo fue analizar y clasificar de manera objetiva la variabilidad climática entre 1991 y 2019 en las cinco estaciones de Pernambuco representadas por: Recife, Palmares, Itaíba, Salgueiro y Petrolina, basándose en diferentes escalas temporales (1, 3, 6, 9,12, 24 y 36 meses). Para ello, se utilizó el Índice de Precipitación Estandarizado (SPI) desarrollado para clasificar condiciones secas y húmedas según su severidad. A través del análisis, se observó que las escalas más pequeñas, SPI-1 y SPI-3, revelaron el inicio y la trayectoria de cada evento, mientras que las demás escalas identificaron los eventos más intensos y prolongados. Los resultados obtenidos indicaron que los períodos de sequía tuvieron una mayor duración e intensidad, siendo el mes más seco en Itaíba -4.416 (SPI-3) en agosto de 2018, pero los períodos de lluvias fueron más frecuentes en las estaciones, siendo el mes más húmedo en Palmares 2.928 (SPI-3) en septiembre de 2000.A determinação e classificação de regiões propensas a eventos climáticos críticos, tanto de chuvas intensas quanto de períodos de seca é de suma importância no âmbito da variabilidade climática. No Nordeste brasileiro, uma região semiárida, a seca é um problema recorrente, enquanto eventos climáticos intensos, como chuvas fortes e deslizamentos de terra, afetam regiões metropolitanas e causam desastres. O estado de Pernambuco apresenta tendência de eventos climáticos extremos, com longos períodos de seca e chuvas intensas, que é responsável por numerosos desastres naturais no estado. O objetivo do trabalho foi analisar e classificar, de forma objetiva, a variabilidade climática entre 1991 e 2019 em cinco estações de Pernambuco localizadas nas diferentes mesorregiões do Estado representadas por: Recife, Palmares, Itaíba, Salgueiro e Petrolina, com base em diferentes escalas temporais (1, 3, 6, 9, 12, 24 e 36 meses). Para isso, utilizou-se o Índice de Precipitação Padronizado (SPI) desenvolvido para classificar condições secas e úmidas de acordo com severidade. Através da análise observou-se que as escalas menores SPI-1 e SPI-3 revelaram o início e a trajetória de cada evento, enquanto as demais escalas identificaram os eventos mais intensos e prolongados. Os resultados obtidos indicaram que os períodos de secas apresentaram maior duração e intensidade, sendo o mês mais seco em Itaíba -4.416 (SPI-3) em agosto de 2018, porém os períodos de chuvas tiveram maior ocorrência nas estações, o mês mais úmido ocorreu em Palmares 2.928 (SPI-3) em setembro de 2000.Research, Society and Development2023-09-18info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfhttps://rsdjournal.org/index.php/rsd/article/view/4321710.33448/rsd-v12i9.43217Research, Society and Development; Vol. 12 No. 9; e8912943217Research, Society and Development; Vol. 12 Núm. 9; e8912943217Research, Society and Development; v. 12 n. 9; e89129432172525-3409reponame:Research, Society and Developmentinstname:Universidade Federal de Itajubá (UNIFEI)instacron:UNIFEIporhttps://rsdjournal.org/index.php/rsd/article/view/43217/34834Copyright (c) 2023 Viviane Farias Felipe; Jefferson Vieira dos Santos; Nyedja Fialho Morais Barbosa; Erika Fialho Morais Xavier; Sílvio Fernando Alves Xavier Júnior; Jader da Silva Jalehttps://creativecommons.org/licenses/by/4.0info:eu-repo/semantics/openAccessFelipe, Viviane Farias Santos, Jefferson Vieira dos Barbosa, Nyedja Fialho Morais Xavier, Erika Fialho Morais Xavier Júnior, Sílvio Fernando AlvesJale, Jader da Silva 2023-10-01T10:43:32Zoai:ojs.pkp.sfu.ca:article/43217Revistahttps://rsdjournal.org/index.php/rsd/indexPUBhttps://rsdjournal.org/index.php/rsd/oairsd.articles@gmail.com2525-34092525-3409opendoar:2023-10-01T10:43:32Research, Society and Development - Universidade Federal de Itajubá (UNIFEI)false |
dc.title.none.fl_str_mv |
Uma aplicação do SPI (Standardized Precipitation Index) para dados de chuvas mensais em Pernambuco entre 1991-2019 An application of SPI (Standardized Precipitation Index) to monthly rainfall data in Pernambuco between 1991-2019 Una aplicación del SPI (Standardized Precipitation Index) para datos de lluvas mensuales en Pernambuco entre 1991-2019 |
title |
Uma aplicação do SPI (Standardized Precipitation Index) para dados de chuvas mensais em Pernambuco entre 1991-2019 |
spellingShingle |
Uma aplicação do SPI (Standardized Precipitation Index) para dados de chuvas mensais em Pernambuco entre 1991-2019 Felipe, Viviane Farias Índice de Precipitación Estandarizado (SPI) Variabilidad climática Estaciones Pernambuco. Índice de Precipitação Padronizado (SPI) Variabilidade climática Estações Pernambuco. Standardized Precipitation Index (SPI) Climate variability Stations Pernambuco. |
title_short |
Uma aplicação do SPI (Standardized Precipitation Index) para dados de chuvas mensais em Pernambuco entre 1991-2019 |
title_full |
Uma aplicação do SPI (Standardized Precipitation Index) para dados de chuvas mensais em Pernambuco entre 1991-2019 |
title_fullStr |
Uma aplicação do SPI (Standardized Precipitation Index) para dados de chuvas mensais em Pernambuco entre 1991-2019 |
title_full_unstemmed |
Uma aplicação do SPI (Standardized Precipitation Index) para dados de chuvas mensais em Pernambuco entre 1991-2019 |
title_sort |
Uma aplicação do SPI (Standardized Precipitation Index) para dados de chuvas mensais em Pernambuco entre 1991-2019 |
author |
Felipe, Viviane Farias |
author_facet |
Felipe, Viviane Farias Santos, Jefferson Vieira dos Barbosa, Nyedja Fialho Morais Xavier, Erika Fialho Morais Xavier Júnior, Sílvio Fernando Alves Jale, Jader da Silva |
author_role |
author |
author2 |
Santos, Jefferson Vieira dos Barbosa, Nyedja Fialho Morais Xavier, Erika Fialho Morais Xavier Júnior, Sílvio Fernando Alves Jale, Jader da Silva |
author2_role |
author author author author author |
dc.contributor.author.fl_str_mv |
Felipe, Viviane Farias Santos, Jefferson Vieira dos Barbosa, Nyedja Fialho Morais Xavier, Erika Fialho Morais Xavier Júnior, Sílvio Fernando Alves Jale, Jader da Silva |
dc.subject.por.fl_str_mv |
Índice de Precipitación Estandarizado (SPI) Variabilidad climática Estaciones Pernambuco. Índice de Precipitação Padronizado (SPI) Variabilidade climática Estações Pernambuco. Standardized Precipitation Index (SPI) Climate variability Stations Pernambuco. |
topic |
Índice de Precipitación Estandarizado (SPI) Variabilidad climática Estaciones Pernambuco. Índice de Precipitação Padronizado (SPI) Variabilidade climática Estações Pernambuco. Standardized Precipitation Index (SPI) Climate variability Stations Pernambuco. |
description |
The determination and classification of regions prone to critical weather events, both intense rainfall and drought periods, are of utmost importance in the context of climate variability. In the Brazilian Northeast, a semi-arid region, drought is a recurring problem, while intense weather events such as heavy rains and landslides affect metropolitan areas and cause disasters. The state of Pernambuco shows a trend of extreme weather events, with long periods of drought and intense rainfall, which is responsible for numerous natural disasters in the state. The objective of this study was to analyze and classify, in an objective manner, the climate variability between 1991 and 2019 in the five stations of Pernambuco represented by Recife, Palmares, Itaíba, Salgueiro, and Petrolina, based on different time scales (1, 3, 6, 9, 12, 24, and 36 months). For this purpose, the Standardized Precipitation Index (SPI) was used, developed to classify dry and wet conditions according to severity. Through the analysis, it was observed that the smaller scales SPI-1 and SPI-3 revealed the onset and trajectory of each event, while the other scales identified the most intense and prolonged events. The results obtained indicated that drought periods had longer duration and intensity, with the driest month in Itaíba being -4.416 (SPI-3) in August 2018. However, rainy periods occurred more frequently in the stations, with the wettest month being in Palmares with 2.928 (SPI-3) in September 2000. |
publishDate |
2023 |
dc.date.none.fl_str_mv |
2023-09-18 |
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/43217 10.33448/rsd-v12i9.43217 |
url |
https://rsdjournal.org/index.php/rsd/article/view/43217 |
identifier_str_mv |
10.33448/rsd-v12i9.43217 |
dc.language.iso.fl_str_mv |
por |
language |
por |
dc.relation.none.fl_str_mv |
https://rsdjournal.org/index.php/rsd/article/view/43217/34834 |
dc.rights.driver.fl_str_mv |
https://creativecommons.org/licenses/by/4.0 info:eu-repo/semantics/openAccess |
rights_invalid_str_mv |
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. 12 No. 9; e8912943217 Research, Society and Development; Vol. 12 Núm. 9; e8912943217 Research, Society and Development; v. 12 n. 9; e8912943217 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 |
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1797052630767239168 |