Extreme value theory applied to the standardized precipitation index - doi: 10.4025/actascitechnol.v36i1.17475
Autor(a) principal: | |
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Data de Publicação: | 2014 |
Tipo de documento: | Artigo |
Idioma: | por eng |
Título da fonte: | Acta scientiarum. Technology (Online) |
Texto Completo: | http://www.periodicos.uem.br/ojs/index.php/ActaSciTechnol/article/view/17475 |
Resumo: | The Standardized Precipitation Index (SPI) is a mathematical algorithm developed for detecting and characterizing precipitation departures with regard to an expected regional climate condition. Thus, this study aimed to verify the possibility of using the time-independent general extreme value distribution (GEV) for modeling the probability of occurrence of both SPI annual maxima (the maximum monthly SPI value; SPImax) and SPI annual minima (the minimum monthly SPI value; SPImim) obtained from the weather station of Campinas, State of São Paulo, Brazil (1891-2011) and to evaluate the presence of trends, temporal persistence and periodical components in these two datasets. The goodness-of-fit tests used in this study quantify the agreement between the empirical cumulative distribution and the GEV cumulative function. Our results have indicated that such parametric function can be used to assess the probability of occurrence of SPImin and SPImax values. No significant serial correlation and no trend were detected in both series. For the SPImim, the wavelet analysis has detected a dominant mode in the 4-8 year band. Future studies should focus on the development of a GEV model capable of accounting for such feature. No dominant mode was found for the annual monthly SPI maximums. |
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Extreme value theory applied to the standardized precipitation index - doi: 10.4025/actascitechnol.v36i1.17475wavelet analysisMann-Kendall testSPIThe Standardized Precipitation Index (SPI) is a mathematical algorithm developed for detecting and characterizing precipitation departures with regard to an expected regional climate condition. Thus, this study aimed to verify the possibility of using the time-independent general extreme value distribution (GEV) for modeling the probability of occurrence of both SPI annual maxima (the maximum monthly SPI value; SPImax) and SPI annual minima (the minimum monthly SPI value; SPImim) obtained from the weather station of Campinas, State of São Paulo, Brazil (1891-2011) and to evaluate the presence of trends, temporal persistence and periodical components in these two datasets. The goodness-of-fit tests used in this study quantify the agreement between the empirical cumulative distribution and the GEV cumulative function. Our results have indicated that such parametric function can be used to assess the probability of occurrence of SPImin and SPImax values. No significant serial correlation and no trend were detected in both series. For the SPImim, the wavelet analysis has detected a dominant mode in the 4-8 year band. Future studies should focus on the development of a GEV model capable of accounting for such feature. No dominant mode was found for the annual monthly SPI maximums. Universidade Estadual De Maringá2014-01-07info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfapplication/pdfhttp://www.periodicos.uem.br/ojs/index.php/ActaSciTechnol/article/view/1747510.4025/actascitechnol.v36i1.17475Acta Scientiarum. Technology; Vol 36 No 1 (2014); 147-155Acta Scientiarum. Technology; v. 36 n. 1 (2014); 147-1551806-25631807-8664reponame:Acta scientiarum. Technology (Online)instname:Universidade Estadual de Maringá (UEM)instacron:UEMporenghttp://www.periodicos.uem.br/ojs/index.php/ActaSciTechnol/article/view/17475/pdfhttp://www.periodicos.uem.br/ojs/index.php/ActaSciTechnol/article/view/17475/pdf_1Blain, Gabriel Constantinoinfo:eu-repo/semantics/openAccess2014-04-10T08:01:20Zoai:periodicos.uem.br/ojs:article/17475Revistahttps://www.periodicos.uem.br/ojs/index.php/ActaSciTechnol/indexPUBhttps://www.periodicos.uem.br/ojs/index.php/ActaSciTechnol/oai||actatech@uem.br1807-86641806-2563opendoar:2014-04-10T08:01:20Acta scientiarum. Technology (Online) - Universidade Estadual de Maringá (UEM)false |
dc.title.none.fl_str_mv |
Extreme value theory applied to the standardized precipitation index - doi: 10.4025/actascitechnol.v36i1.17475 |
title |
Extreme value theory applied to the standardized precipitation index - doi: 10.4025/actascitechnol.v36i1.17475 |
spellingShingle |
Extreme value theory applied to the standardized precipitation index - doi: 10.4025/actascitechnol.v36i1.17475 Blain, Gabriel Constantino wavelet analysis Mann-Kendall test SPI |
title_short |
Extreme value theory applied to the standardized precipitation index - doi: 10.4025/actascitechnol.v36i1.17475 |
title_full |
Extreme value theory applied to the standardized precipitation index - doi: 10.4025/actascitechnol.v36i1.17475 |
title_fullStr |
Extreme value theory applied to the standardized precipitation index - doi: 10.4025/actascitechnol.v36i1.17475 |
title_full_unstemmed |
Extreme value theory applied to the standardized precipitation index - doi: 10.4025/actascitechnol.v36i1.17475 |
title_sort |
Extreme value theory applied to the standardized precipitation index - doi: 10.4025/actascitechnol.v36i1.17475 |
author |
Blain, Gabriel Constantino |
author_facet |
Blain, Gabriel Constantino |
author_role |
author |
dc.contributor.author.fl_str_mv |
Blain, Gabriel Constantino |
dc.subject.por.fl_str_mv |
wavelet analysis Mann-Kendall test SPI |
topic |
wavelet analysis Mann-Kendall test SPI |
description |
The Standardized Precipitation Index (SPI) is a mathematical algorithm developed for detecting and characterizing precipitation departures with regard to an expected regional climate condition. Thus, this study aimed to verify the possibility of using the time-independent general extreme value distribution (GEV) for modeling the probability of occurrence of both SPI annual maxima (the maximum monthly SPI value; SPImax) and SPI annual minima (the minimum monthly SPI value; SPImim) obtained from the weather station of Campinas, State of São Paulo, Brazil (1891-2011) and to evaluate the presence of trends, temporal persistence and periodical components in these two datasets. The goodness-of-fit tests used in this study quantify the agreement between the empirical cumulative distribution and the GEV cumulative function. Our results have indicated that such parametric function can be used to assess the probability of occurrence of SPImin and SPImax values. No significant serial correlation and no trend were detected in both series. For the SPImim, the wavelet analysis has detected a dominant mode in the 4-8 year band. Future studies should focus on the development of a GEV model capable of accounting for such feature. No dominant mode was found for the annual monthly SPI maximums. |
publishDate |
2014 |
dc.date.none.fl_str_mv |
2014-01-07 |
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 |
http://www.periodicos.uem.br/ojs/index.php/ActaSciTechnol/article/view/17475 10.4025/actascitechnol.v36i1.17475 |
url |
http://www.periodicos.uem.br/ojs/index.php/ActaSciTechnol/article/view/17475 |
identifier_str_mv |
10.4025/actascitechnol.v36i1.17475 |
dc.language.iso.fl_str_mv |
por eng |
language |
por eng |
dc.relation.none.fl_str_mv |
http://www.periodicos.uem.br/ojs/index.php/ActaSciTechnol/article/view/17475/pdf http://www.periodicos.uem.br/ojs/index.php/ActaSciTechnol/article/view/17475/pdf_1 |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
application/pdf application/pdf |
dc.publisher.none.fl_str_mv |
Universidade Estadual De Maringá |
publisher.none.fl_str_mv |
Universidade Estadual De Maringá |
dc.source.none.fl_str_mv |
Acta Scientiarum. Technology; Vol 36 No 1 (2014); 147-155 Acta Scientiarum. Technology; v. 36 n. 1 (2014); 147-155 1806-2563 1807-8664 reponame:Acta scientiarum. Technology (Online) instname:Universidade Estadual de Maringá (UEM) instacron:UEM |
instname_str |
Universidade Estadual de Maringá (UEM) |
instacron_str |
UEM |
institution |
UEM |
reponame_str |
Acta scientiarum. Technology (Online) |
collection |
Acta scientiarum. Technology (Online) |
repository.name.fl_str_mv |
Acta scientiarum. Technology (Online) - Universidade Estadual de Maringá (UEM) |
repository.mail.fl_str_mv |
||actatech@uem.br |
_version_ |
1799315334976503808 |