Climate trends in the municipality of Pelotas, state of Rio Grande do Sul, Brazil

Detalhes bibliográficos
Autor(a) principal: Kruel,Izabele B.
Data de Publicação: 2015
Outros Autores: Meschiatti,Monica C., Blain,Gabriel C., Ávila,Ana M. H. de
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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spelling 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
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dc.identifier.uri.fl_str_mv http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0100-69162015000400769
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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
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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)
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