Incoming Longwave Radiation Evaluation for the Legal Amazon Using HadRM3 and Geostatistic Theoretical Models
Autor(a) principal: | |
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Data de Publicação: | 2018 |
Outros Autores: | , , , |
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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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|| |
_version_ |
1750128142069006336 |