Modelling air temperature in Brazilian northeast to evaluate change patterns from 2000 to 2017

Detalhes bibliográficos
Autor(a) principal: Moraes, Daniel
Data de Publicação: 2019
Outros Autores: Ribeiro, Sara, Costa, Ana Cristina
Idioma: eng
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: https://doi.org/10.5593/sgem2019/2.2/S11.113
Resumo: Moraes, D., Ribeiro, S., & Costa, A. C. (2019). Modelling air temperature in Brazilian northeast to evaluate change patterns from 2000 to 2017. In 19th International Multidisciplinary Scientific Geoconference, SGEM 2019: Conference Proceedings. (2.2 ed., Vol. 19, pp. 915-922). (International Multidisciplinary Scientific GeoConference Surveying Geology and Mining Ecology Management, SGEM). https://doi.org/10.5593/sgem2019/2.2/S11.113
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spelling Modelling air temperature in Brazilian northeast to evaluate change patterns from 2000 to 2017BrazilClimate variabilityInterpolationOrdinary krigingGeotechnical Engineering and Engineering GeologyGeologySDG 13 - Climate ActionMoraes, D., Ribeiro, S., & Costa, A. C. (2019). Modelling air temperature in Brazilian northeast to evaluate change patterns from 2000 to 2017. In 19th International Multidisciplinary Scientific Geoconference, SGEM 2019: Conference Proceedings. (2.2 ed., Vol. 19, pp. 915-922). (International Multidisciplinary Scientific GeoConference Surveying Geology and Mining Ecology Management, SGEM). https://doi.org/10.5593/sgem2019/2.2/S11.113Air temperature influences a variety of environmental processes, having a significant impact on the conditions of living of humans and other life forms. The Brazilian Northeast is a region that comprises a diversity of ecosystems, but it is most known as a semi-arid area characterized by severe environmental conditions. This work proposes to model air temperature in Brazilian Northeast to evaluate changing patterns between 2000 and 2017 using two interpolation techniques and comparing them. Monthly average temperature data from meteorological stations were gathered and used to compute the average annual temperature. Then, the timeframe was divided into 2 periods: 2000 to 2008 (1) and 2009 to 2017 (2), and the average temperature of each period was computed based on the annual average. Descriptive statistics analysis and exploratory spatial data analysis were performed, providing insights on the temperature patterns and distribution. In addition, interpolated surfaces were generated using the Inverse Distance Weighting and Ordinary Kriging methods for each period, and results were compared using error statistics derived with cross-validation. The results revealed that for both periods the highest temperatures are exhibited in the northern and central regions, whereas the lowest values occur in the south and east. In terms of change, an overall increase in the average temperature was noticed from period 1 to 2, although in some areas the increase was greater than in others. There was an increase of 0,37ºC in the mean, 1,37ºC in the maximum and 0,18ºC in the minimum temperature over the study region. Furthermore, Ordinary Kriging produced better results in terms of the bias of the predictions. The interpolated surfaces allow to visually notice the change in the average temperature between the periods. This study contributes to a better understanding of the temperature variability in the Brazilian Northeast in the 21st century.NOVA Information Management School (NOVA IMS)Information Management Research Center (MagIC) - NOVA Information Management SchoolRUNMoraes, DanielRibeiro, SaraCosta, Ana Cristina2019-10-23T03:53:32Z2019-01-012019-01-01T00:00:00Zconference objectinfo:eu-repo/semantics/publishedVersion8application/octet-streamhttps://doi.org/10.5593/sgem2019/2.2/S11.113eng978-619-7408-80-51314-2704PURE: 15112517http://www.scopus.com/inward/record.url?scp=85073394689&partnerID=8YFLogxKhttps://doi.org/10.5593/sgem2019/2.2/S11.113info:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2024-05-22T17:41:50Zoai:run.unl.pt:10362/85166Portal AgregadorONGhttps://www.rcaap.pt/oai/openairemluisa.alvim@gmail.comopendoar:71602024-05-22T17:41:50Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse
dc.title.none.fl_str_mv Modelling air temperature in Brazilian northeast to evaluate change patterns from 2000 to 2017
title Modelling air temperature in Brazilian northeast to evaluate change patterns from 2000 to 2017
spellingShingle Modelling air temperature in Brazilian northeast to evaluate change patterns from 2000 to 2017
Moraes, Daniel
Brazil
Climate variability
Interpolation
Ordinary kriging
Geotechnical Engineering and Engineering Geology
Geology
SDG 13 - Climate Action
title_short Modelling air temperature in Brazilian northeast to evaluate change patterns from 2000 to 2017
title_full Modelling air temperature in Brazilian northeast to evaluate change patterns from 2000 to 2017
title_fullStr Modelling air temperature in Brazilian northeast to evaluate change patterns from 2000 to 2017
title_full_unstemmed Modelling air temperature in Brazilian northeast to evaluate change patterns from 2000 to 2017
title_sort Modelling air temperature in Brazilian northeast to evaluate change patterns from 2000 to 2017
author Moraes, Daniel
author_facet Moraes, Daniel
Ribeiro, Sara
Costa, Ana Cristina
author_role author
author2 Ribeiro, Sara
Costa, Ana Cristina
author2_role author
author
dc.contributor.none.fl_str_mv NOVA Information Management School (NOVA IMS)
Information Management Research Center (MagIC) - NOVA Information Management School
RUN
dc.contributor.author.fl_str_mv Moraes, Daniel
Ribeiro, Sara
Costa, Ana Cristina
dc.subject.por.fl_str_mv Brazil
Climate variability
Interpolation
Ordinary kriging
Geotechnical Engineering and Engineering Geology
Geology
SDG 13 - Climate Action
topic Brazil
Climate variability
Interpolation
Ordinary kriging
Geotechnical Engineering and Engineering Geology
Geology
SDG 13 - Climate Action
description Moraes, D., Ribeiro, S., & Costa, A. C. (2019). Modelling air temperature in Brazilian northeast to evaluate change patterns from 2000 to 2017. In 19th International Multidisciplinary Scientific Geoconference, SGEM 2019: Conference Proceedings. (2.2 ed., Vol. 19, pp. 915-922). (International Multidisciplinary Scientific GeoConference Surveying Geology and Mining Ecology Management, SGEM). https://doi.org/10.5593/sgem2019/2.2/S11.113
publishDate 2019
dc.date.none.fl_str_mv 2019-10-23T03:53:32Z
2019-01-01
2019-01-01T00:00:00Z
dc.type.driver.fl_str_mv conference object
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
status_str publishedVersion
dc.identifier.uri.fl_str_mv https://doi.org/10.5593/sgem2019/2.2/S11.113
url https://doi.org/10.5593/sgem2019/2.2/S11.113
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 978-619-7408-80-5
1314-2704
PURE: 15112517
http://www.scopus.com/inward/record.url?scp=85073394689&partnerID=8YFLogxK
https://doi.org/10.5593/sgem2019/2.2/S11.113
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv 8
application/octet-stream
dc.source.none.fl_str_mv reponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
instacron:RCAAP
instname_str Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
instacron_str RCAAP
institution RCAAP
reponame_str Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
collection Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
repository.name.fl_str_mv Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
repository.mail.fl_str_mv mluisa.alvim@gmail.com
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