Incoming Longwave Radiation Evaluation for the Legal Amazon Using HadRM3 and Geostatistic Theoretical Models

Detalhes bibliográficos
Autor(a) principal: Teodoro,Paulo Eduardo
Data de Publicação: 2018
Outros Autores: Delgado,Rafael Coll, Oliveira-Junior,Jose Francisco, Gois,Givanildo, Sohn,Fernanda Tayt
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Floresta e Ambiente
Texto Completo: http://old.scielo.br/scielo.php?script=sci_arttext&pid=S2179-80872018000200122
Resumo: ABSTRACT Incoming longwave radiation was estimated using air temperature data from the output of the regional HadRM3 model in the Intergovernmental Panel on Climate Change’s (IPCC) A2 scenario for projections up to 2070, 2080 and 2090 and using Swinbank’s equation. Spatial distribution was done by Ordinary Kriging through three theoretical mathematical models for the IPCC A2 scenario for the whole Legal Amazon. It was found that the highest averages and outliers occurred in 2090 compared to other years evaluated. The average incoming longwave radiation for 2070, 2080 and 2090 was 394.8, 403.9 and 413.0 Wm-2year-1 , respectively. The coefficients of variation (CV) were higher for 2080 (2.6%) and 2090 (2.8%), similar to the results found by standard deviation. 2070 obtained CV (2.2%) for estimated values of incoming longwave radiation with greater accuracy. Again, 2070 was the only year that could be interpolated because the average degree of spatial dependence found for all models was 12.23%. Lastly, 2080 could only be interpolated using the Gaussian model in the Legal Amazon.
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spelling Incoming Longwave Radiation Evaluation for the Legal Amazon Using HadRM3 and Geostatistic Theoretical Modelsclimate changegeostatisticsenergy balanceABSTRACT Incoming longwave radiation was estimated using air temperature data from the output of the regional HadRM3 model in the Intergovernmental Panel on Climate Change’s (IPCC) A2 scenario for projections up to 2070, 2080 and 2090 and using Swinbank’s equation. Spatial distribution was done by Ordinary Kriging through three theoretical mathematical models for the IPCC A2 scenario for the whole Legal Amazon. It was found that the highest averages and outliers occurred in 2090 compared to other years evaluated. The average incoming longwave radiation for 2070, 2080 and 2090 was 394.8, 403.9 and 413.0 Wm-2year-1 , respectively. The coefficients of variation (CV) were higher for 2080 (2.6%) and 2090 (2.8%), similar to the results found by standard deviation. 2070 obtained CV (2.2%) for estimated values of incoming longwave radiation with greater accuracy. Again, 2070 was the only year that could be interpolated because the average degree of spatial dependence found for all models was 12.23%. Lastly, 2080 could only be interpolated using the Gaussian model in the Legal Amazon.Instituto de Florestas da Universidade Federal Rural do Rio de Janeiro2018-01-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersiontext/htmlhttp://old.scielo.br/scielo.php?script=sci_arttext&pid=S2179-80872018000200122Floresta e Ambiente v.25 n.2 2018reponame:Floresta e Ambienteinstname:Universidade Federal do Rio de Janeiro (UFRJ)instacron:UFRJ10.1590/2179-8087.009416info:eu-repo/semantics/openAccessTeodoro,Paulo EduardoDelgado,Rafael CollOliveira-Junior,Jose FranciscoGois,GivanildoSohn,Fernanda Tayteng2018-05-15T00:00:00Zoai:scielo:S2179-80872018000200122Revistahttps://www.floram.org/PUBhttps://old.scielo.br/oai/scielo-oai.phpfloramjournal@gmail.com||floram@ufrrj.br||2179-80871415-0980opendoar:2018-05-15T00:00Floresta e Ambiente - Universidade Federal do Rio de Janeiro (UFRJ)false
dc.title.none.fl_str_mv Incoming Longwave Radiation Evaluation for the Legal Amazon Using HadRM3 and Geostatistic Theoretical Models
title Incoming Longwave Radiation Evaluation for the Legal Amazon Using HadRM3 and Geostatistic Theoretical Models
spellingShingle Incoming Longwave Radiation Evaluation for the Legal Amazon Using HadRM3 and Geostatistic Theoretical Models
Teodoro,Paulo Eduardo
climate change
geostatistics
energy balance
title_short Incoming Longwave Radiation Evaluation for the Legal Amazon Using HadRM3 and Geostatistic Theoretical Models
title_full Incoming Longwave Radiation Evaluation for the Legal Amazon Using HadRM3 and Geostatistic Theoretical Models
title_fullStr Incoming Longwave Radiation Evaluation for the Legal Amazon Using HadRM3 and Geostatistic Theoretical Models
title_full_unstemmed Incoming Longwave Radiation Evaluation for the Legal Amazon Using HadRM3 and Geostatistic Theoretical Models
title_sort Incoming Longwave Radiation Evaluation for the Legal Amazon Using HadRM3 and Geostatistic Theoretical Models
author Teodoro,Paulo Eduardo
author_facet Teodoro,Paulo Eduardo
Delgado,Rafael Coll
Oliveira-Junior,Jose Francisco
Gois,Givanildo
Sohn,Fernanda Tayt
author_role author
author2 Delgado,Rafael Coll
Oliveira-Junior,Jose Francisco
Gois,Givanildo
Sohn,Fernanda Tayt
author2_role author
author
author
author
dc.contributor.author.fl_str_mv Teodoro,Paulo Eduardo
Delgado,Rafael Coll
Oliveira-Junior,Jose Francisco
Gois,Givanildo
Sohn,Fernanda Tayt
dc.subject.por.fl_str_mv climate change
geostatistics
energy balance
topic climate change
geostatistics
energy balance
description ABSTRACT Incoming longwave radiation was estimated using air temperature data from the output of the regional HadRM3 model in the Intergovernmental Panel on Climate Change’s (IPCC) A2 scenario for projections up to 2070, 2080 and 2090 and using Swinbank’s equation. Spatial distribution was done by Ordinary Kriging through three theoretical mathematical models for the IPCC A2 scenario for the whole Legal Amazon. It was found that the highest averages and outliers occurred in 2090 compared to other years evaluated. The average incoming longwave radiation for 2070, 2080 and 2090 was 394.8, 403.9 and 413.0 Wm-2year-1 , respectively. The coefficients of variation (CV) were higher for 2080 (2.6%) and 2090 (2.8%), similar to the results found by standard deviation. 2070 obtained CV (2.2%) for estimated values of incoming longwave radiation with greater accuracy. Again, 2070 was the only year that could be interpolated because the average degree of spatial dependence found for all models was 12.23%. Lastly, 2080 could only be interpolated using the Gaussian model in the Legal Amazon.
publishDate 2018
dc.date.none.fl_str_mv 2018-01-01
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=S2179-80872018000200122
url http://old.scielo.br/scielo.php?script=sci_arttext&pid=S2179-80872018000200122
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 10.1590/2179-8087.009416
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 Instituto de Florestas da Universidade Federal Rural do Rio de Janeiro
publisher.none.fl_str_mv Instituto de Florestas da Universidade Federal Rural do Rio de Janeiro
dc.source.none.fl_str_mv Floresta e Ambiente v.25 n.2 2018
reponame:Floresta e Ambiente
instname:Universidade Federal do Rio de Janeiro (UFRJ)
instacron:UFRJ
instname_str Universidade Federal do Rio de Janeiro (UFRJ)
instacron_str UFRJ
institution UFRJ
reponame_str Floresta e Ambiente
collection Floresta e Ambiente
repository.name.fl_str_mv Floresta e Ambiente - Universidade Federal do Rio de Janeiro (UFRJ)
repository.mail.fl_str_mv floramjournal@gmail.com||floram@ufrrj.br||
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