SPEI and Hurst Analysis of Precipitation in the Amazonian Area of Brazil

Detalhes bibliográficos
Autor(a) principal: Vega,Humberto Millán
Data de Publicação: 2019
Outros Autores: Lima,Jakeline Rabelo, Cerniak,Samuel Nogueira
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Revista Brasileira de Meteorologia (Online)
Texto Completo: http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0102-77862019000200325
Resumo: Abstract Amazon rainforest controls, to some extent, the global hydrological cycle. The objectives of the present work were (i) to investigate hydrologicalpatterns in a larger regionof the Brazilian rainforestthrough 9-month SPEI series and (ii) to search for long or short-term correlation within the number of days with precipitation by monthand accumulated monthly rainfall. Data sets were collected from 15 meteorological stations spanning a large area of the Amazonian rainforest in Brazil. We computed SPEI values from monthly precipitation and monthly meantemperature time series and determined Hurst exponents from detrendedtime series of days with precipitationand accumulated monthly rainfall. In the first case SPEI was determined on a 9-month timescale while Hurst exponents were calculated from rescaled range analysis. Percentage of SPEI values in the near normal class (-1 ≤SPEI ≤ 1) ranged from 59.8% (Peixe, TO) to 69.7% (Tarauaca, AC). The Hurst exponent varied from 0.382 (Diamantino, MT) to 0.636 (Tefé, AM) and correlated positively with the monthly meanrainfall. This indicates a persistenttrend of wet patterns in the futurein some areas. Hurst analysis of days with precipitation and monthly rainfallcould be an additional tool for interpreting rainfall data.
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spelling SPEI and Hurst Analysis of Precipitation in the Amazonian Area of BrazilprecipitationspeiHurst analysisAmazonian rainforestAbstract Amazon rainforest controls, to some extent, the global hydrological cycle. The objectives of the present work were (i) to investigate hydrologicalpatterns in a larger regionof the Brazilian rainforestthrough 9-month SPEI series and (ii) to search for long or short-term correlation within the number of days with precipitation by monthand accumulated monthly rainfall. Data sets were collected from 15 meteorological stations spanning a large area of the Amazonian rainforest in Brazil. We computed SPEI values from monthly precipitation and monthly meantemperature time series and determined Hurst exponents from detrendedtime series of days with precipitationand accumulated monthly rainfall. In the first case SPEI was determined on a 9-month timescale while Hurst exponents were calculated from rescaled range analysis. Percentage of SPEI values in the near normal class (-1 ≤SPEI ≤ 1) ranged from 59.8% (Peixe, TO) to 69.7% (Tarauaca, AC). The Hurst exponent varied from 0.382 (Diamantino, MT) to 0.636 (Tefé, AM) and correlated positively with the monthly meanrainfall. This indicates a persistenttrend of wet patterns in the futurein some areas. Hurst analysis of days with precipitation and monthly rainfallcould be an additional tool for interpreting rainfall data.Sociedade Brasileira de Meteorologia2019-06-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersiontext/htmlhttp://old.scielo.br/scielo.php?script=sci_arttext&pid=S0102-77862019000200325Revista Brasileira de Meteorologia v.34 n.2 2019reponame:Revista Brasileira de Meteorologia (Online)instname:Sociedade Brasileira de Meteorologia (SBMET)instacron:SBMET10.1590/0102-77863340027info:eu-repo/semantics/openAccessVega,Humberto MillánLima,Jakeline RabeloCerniak,Samuel Nogueiraeng2019-08-22T00:00:00Zoai:scielo:S0102-77862019000200325Revistahttp://www.rbmet.org.br/port/index.phpONGhttps://old.scielo.br/oai/scielo-oai.php||rbmet@rbmet.org.br1982-43510102-7786opendoar:2019-08-22T00:00Revista Brasileira de Meteorologia (Online) - Sociedade Brasileira de Meteorologia (SBMET)false
dc.title.none.fl_str_mv SPEI and Hurst Analysis of Precipitation in the Amazonian Area of Brazil
title SPEI and Hurst Analysis of Precipitation in the Amazonian Area of Brazil
spellingShingle SPEI and Hurst Analysis of Precipitation in the Amazonian Area of Brazil
Vega,Humberto Millán
precipitation
spei
Hurst analysis
Amazonian rainforest
title_short SPEI and Hurst Analysis of Precipitation in the Amazonian Area of Brazil
title_full SPEI and Hurst Analysis of Precipitation in the Amazonian Area of Brazil
title_fullStr SPEI and Hurst Analysis of Precipitation in the Amazonian Area of Brazil
title_full_unstemmed SPEI and Hurst Analysis of Precipitation in the Amazonian Area of Brazil
title_sort SPEI and Hurst Analysis of Precipitation in the Amazonian Area of Brazil
author Vega,Humberto Millán
author_facet Vega,Humberto Millán
Lima,Jakeline Rabelo
Cerniak,Samuel Nogueira
author_role author
author2 Lima,Jakeline Rabelo
Cerniak,Samuel Nogueira
author2_role author
author
dc.contributor.author.fl_str_mv Vega,Humberto Millán
Lima,Jakeline Rabelo
Cerniak,Samuel Nogueira
dc.subject.por.fl_str_mv precipitation
spei
Hurst analysis
Amazonian rainforest
topic precipitation
spei
Hurst analysis
Amazonian rainforest
description Abstract Amazon rainforest controls, to some extent, the global hydrological cycle. The objectives of the present work were (i) to investigate hydrologicalpatterns in a larger regionof the Brazilian rainforestthrough 9-month SPEI series and (ii) to search for long or short-term correlation within the number of days with precipitation by monthand accumulated monthly rainfall. Data sets were collected from 15 meteorological stations spanning a large area of the Amazonian rainforest in Brazil. We computed SPEI values from monthly precipitation and monthly meantemperature time series and determined Hurst exponents from detrendedtime series of days with precipitationand accumulated monthly rainfall. In the first case SPEI was determined on a 9-month timescale while Hurst exponents were calculated from rescaled range analysis. Percentage of SPEI values in the near normal class (-1 ≤SPEI ≤ 1) ranged from 59.8% (Peixe, TO) to 69.7% (Tarauaca, AC). The Hurst exponent varied from 0.382 (Diamantino, MT) to 0.636 (Tefé, AM) and correlated positively with the monthly meanrainfall. This indicates a persistenttrend of wet patterns in the futurein some areas. Hurst analysis of days with precipitation and monthly rainfallcould be an additional tool for interpreting rainfall data.
publishDate 2019
dc.date.none.fl_str_mv 2019-06-01
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
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status_str publishedVersion
dc.identifier.uri.fl_str_mv http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0102-77862019000200325
url http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0102-77862019000200325
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 10.1590/0102-77863340027
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv text/html
dc.publisher.none.fl_str_mv Sociedade Brasileira de Meteorologia
publisher.none.fl_str_mv Sociedade Brasileira de Meteorologia
dc.source.none.fl_str_mv Revista Brasileira de Meteorologia v.34 n.2 2019
reponame:Revista Brasileira de Meteorologia (Online)
instname:Sociedade Brasileira de Meteorologia (SBMET)
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repository.name.fl_str_mv Revista Brasileira de Meteorologia (Online) - Sociedade Brasileira de Meteorologia (SBMET)
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