Climate trends in the municipality of Pelotas, state of Rio Grande do Sul, Brazil
Autor(a) principal: | |
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Data de Publicação: | 2015 |
Outros Autores: | , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Engenharia Agrícola |
Texto Completo: | http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0100-69162015000400769 |
Resumo: | ABSTRACT Changes in the frequency of occurrence of extreme weather events have been pointed out as a likely impact of global warming. In this context, this study aimed to detect climate change in series of extreme minimum and maximum air temperature of Pelotas, State of Rio Grande do Sul, (1896 - 2011) and its influence on the probability of occurrence of these variables. We used the general extreme value distribution (GEV) in its stationary and non-stationary forms. In the latter case, GEV parameters are variable over time. On the basis of goodness-of-fit tests and of the maximum likelihood method, the GEV model in which the location parameter increases over time presents the best fit of the daily minimum air temperature series. Such result describes a significant increase in the mean values of this variable, which indicates a potential reduction in the frequency of frosts. The daily maximum air temperature series is also described by a non-stationary model, whose location parameter decreases over time, and the scale parameter related to sample variance rises between the beginning and end of the series. This result indicates a drop in the mean of daily maximum air temperature values and increased dispersion of the sample data. |
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Climate trends in the municipality of Pelotas, state of Rio Grande do Sul, Brazilgeneral extreme value distributiontime dependent modelextreme weather eventsABSTRACT Changes in the frequency of occurrence of extreme weather events have been pointed out as a likely impact of global warming. In this context, this study aimed to detect climate change in series of extreme minimum and maximum air temperature of Pelotas, State of Rio Grande do Sul, (1896 - 2011) and its influence on the probability of occurrence of these variables. We used the general extreme value distribution (GEV) in its stationary and non-stationary forms. In the latter case, GEV parameters are variable over time. On the basis of goodness-of-fit tests and of the maximum likelihood method, the GEV model in which the location parameter increases over time presents the best fit of the daily minimum air temperature series. Such result describes a significant increase in the mean values of this variable, which indicates a potential reduction in the frequency of frosts. The daily maximum air temperature series is also described by a non-stationary model, whose location parameter decreases over time, and the scale parameter related to sample variance rises between the beginning and end of the series. This result indicates a drop in the mean of daily maximum air temperature values and increased dispersion of the sample data.Associação Brasileira de Engenharia Agrícola2015-08-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersiontext/htmlhttp://old.scielo.br/scielo.php?script=sci_arttext&pid=S0100-69162015000400769Engenharia Agrícola v.35 n.4 2015reponame:Engenharia Agrícolainstname:Associação Brasileira de Engenharia Agrícola (SBEA)instacron:SBEA10.1590/1809-4430-Eng.Agric.v35n4p769-777/2015info:eu-repo/semantics/openAccessKruel,Izabele B.Meschiatti,Monica C.Blain,Gabriel C.Ávila,Ana M. H. deeng2016-07-20T00:00:00Zoai:scielo:S0100-69162015000400769Revistahttp://www.engenhariaagricola.org.br/ORGhttps://old.scielo.br/oai/scielo-oai.phprevistasbea@sbea.org.br||sbea@sbea.org.br1809-44300100-6916opendoar:2016-07-20T00:00Engenharia Agrícola - Associação Brasileira de Engenharia Agrícola (SBEA)false |
dc.title.none.fl_str_mv |
Climate trends in the municipality of Pelotas, state of Rio Grande do Sul, Brazil |
title |
Climate trends in the municipality of Pelotas, state of Rio Grande do Sul, Brazil |
spellingShingle |
Climate trends in the municipality of Pelotas, state of Rio Grande do Sul, Brazil Kruel,Izabele B. general extreme value distribution time dependent model extreme weather events |
title_short |
Climate trends in the municipality of Pelotas, state of Rio Grande do Sul, Brazil |
title_full |
Climate trends in the municipality of Pelotas, state of Rio Grande do Sul, Brazil |
title_fullStr |
Climate trends in the municipality of Pelotas, state of Rio Grande do Sul, Brazil |
title_full_unstemmed |
Climate trends in the municipality of Pelotas, state of Rio Grande do Sul, Brazil |
title_sort |
Climate trends in the municipality of Pelotas, state of Rio Grande do Sul, Brazil |
author |
Kruel,Izabele B. |
author_facet |
Kruel,Izabele B. Meschiatti,Monica C. Blain,Gabriel C. Ávila,Ana M. H. de |
author_role |
author |
author2 |
Meschiatti,Monica C. Blain,Gabriel C. Ávila,Ana M. H. de |
author2_role |
author author author |
dc.contributor.author.fl_str_mv |
Kruel,Izabele B. Meschiatti,Monica C. Blain,Gabriel C. Ávila,Ana M. H. de |
dc.subject.por.fl_str_mv |
general extreme value distribution time dependent model extreme weather events |
topic |
general extreme value distribution time dependent model extreme weather events |
description |
ABSTRACT Changes in the frequency of occurrence of extreme weather events have been pointed out as a likely impact of global warming. In this context, this study aimed to detect climate change in series of extreme minimum and maximum air temperature of Pelotas, State of Rio Grande do Sul, (1896 - 2011) and its influence on the probability of occurrence of these variables. We used the general extreme value distribution (GEV) in its stationary and non-stationary forms. In the latter case, GEV parameters are variable over time. On the basis of goodness-of-fit tests and of the maximum likelihood method, the GEV model in which the location parameter increases over time presents the best fit of the daily minimum air temperature series. Such result describes a significant increase in the mean values of this variable, which indicates a potential reduction in the frequency of frosts. The daily maximum air temperature series is also described by a non-stationary model, whose location parameter decreases over time, and the scale parameter related to sample variance rises between the beginning and end of the series. This result indicates a drop in the mean of daily maximum air temperature values and increased dispersion of the sample data. |
publishDate |
2015 |
dc.date.none.fl_str_mv |
2015-08-01 |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0100-69162015000400769 |
url |
http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0100-69162015000400769 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
10.1590/1809-4430-Eng.Agric.v35n4p769-777/2015 |
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 |
Associação Brasileira de Engenharia Agrícola |
publisher.none.fl_str_mv |
Associação Brasileira de Engenharia Agrícola |
dc.source.none.fl_str_mv |
Engenharia Agrícola v.35 n.4 2015 reponame:Engenharia Agrícola instname:Associação Brasileira de Engenharia Agrícola (SBEA) instacron:SBEA |
instname_str |
Associação Brasileira de Engenharia Agrícola (SBEA) |
instacron_str |
SBEA |
institution |
SBEA |
reponame_str |
Engenharia Agrícola |
collection |
Engenharia Agrícola |
repository.name.fl_str_mv |
Engenharia Agrícola - Associação Brasileira de Engenharia Agrícola (SBEA) |
repository.mail.fl_str_mv |
revistasbea@sbea.org.br||sbea@sbea.org.br |
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1752126272388988928 |