Assessing the performance of the south american land data assimilation system version 2 (SALDAS-2) energy balance across diverse biomes
Autor(a) principal: | |
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Data de Publicação: | 2023 |
Outros Autores: | , , , , , , , , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Institucional da UFRGS |
Texto Completo: | http://hdl.handle.net/10183/262810 |
Resumo: | Understanding the exchange of energy between the surface and the atmosphere is important in view of the climate scenario. However, it becomes a challenging task due to a sparse network of observations. This study aims to improve the energy balance estimates for the Amazon, Cerrado, and Pampa biomes located in South America using the radiation and precipitation forcing obtained from the Clouds and the Earth’s Radiant Energy System (CERES) and the precipitation CPTEC/MERGE datasets. We employed three surface models—Noah-MP, Community Land Model (CLSM), and Integrated Biosphere Simulator (IBIS)—and conducted modeling experiments, termed South America Land Data Assimilation System (SALDAS-2). The results showed that SALDAS-2 radiation estimates had the smallest errors. Moreover, SALDAS-2 precipitation estimates were better than the Global Land Data Assimilation System (GLDAS) in the Cerrado (MBE = −0.16) and Pampa (MBE = −0.19). Noah-MP presented improvements compared with CLSM and IBIS in 100% of towers located in the Amazon. CLSM tends to overestimate the latent heat flux and underestimate the sensible heat flux in the Amazon. Noah-MP and Ensemble outperformed GLDAS in terms latent and sensible heat fluxes. The potential of SALDAS-2 should be emphasized to provide more accurate estimates of surface energy balance. |
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Ávila, Álvaro Vasconcellos Araujo deGonçalves, Luis Gustavo Gonçalves deSouza, Vanessa de ArrudaAlves, Laurizio Emanuel RibeiroGaletti, Giovanna DeponteMaske, Bianca MussGetirana, AugustoRuhoff, Anderson LuisBiudes, Marcelo SacardiMachado, Nadja GomesRoberti, Débora Regina2023-07-29T03:35:06Z20232073-4433http://hdl.handle.net/10183/262810001171248Understanding the exchange of energy between the surface and the atmosphere is important in view of the climate scenario. However, it becomes a challenging task due to a sparse network of observations. This study aims to improve the energy balance estimates for the Amazon, Cerrado, and Pampa biomes located in South America using the radiation and precipitation forcing obtained from the Clouds and the Earth’s Radiant Energy System (CERES) and the precipitation CPTEC/MERGE datasets. We employed three surface models—Noah-MP, Community Land Model (CLSM), and Integrated Biosphere Simulator (IBIS)—and conducted modeling experiments, termed South America Land Data Assimilation System (SALDAS-2). The results showed that SALDAS-2 radiation estimates had the smallest errors. Moreover, SALDAS-2 precipitation estimates were better than the Global Land Data Assimilation System (GLDAS) in the Cerrado (MBE = −0.16) and Pampa (MBE = −0.19). Noah-MP presented improvements compared with CLSM and IBIS in 100% of towers located in the Amazon. CLSM tends to overestimate the latent heat flux and underestimate the sensible heat flux in the Amazon. Noah-MP and Ensemble outperformed GLDAS in terms latent and sensible heat fluxes. The potential of SALDAS-2 should be emphasized to provide more accurate estimates of surface energy balance.application/pdfengAtmosphere. Basel. Vol. 14, no. 6 (June 2023), [article] 959, 24 p.BiomasBalanco energeticoSensoriamento remotoModelos físicosPrecipitaçãoAmérica do SulModelingSurfaceEnergyBalancePrecipitationAssessing the performance of the south american land data assimilation system version 2 (SALDAS-2) energy balance across diverse biomesEstrangeiroinfo:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/openAccessreponame:Repositório Institucional da UFRGSinstname:Universidade Federal do Rio Grande do Sul (UFRGS)instacron:UFRGSTEXT001171248.pdf.txt001171248.pdf.txtExtracted Texttext/plain100184http://www.lume.ufrgs.br/bitstream/10183/262810/2/001171248.pdf.txt7ef8a11cdb96f39e146616b3cef33ec2MD52ORIGINAL001171248.pdfTexto completo (inglês)application/pdf3064840http://www.lume.ufrgs.br/bitstream/10183/262810/1/001171248.pdfc5cf92e7a911bf4f1f879d890b49b74dMD5110183/2628102023-07-30 03:46:08.863339oai:www.lume.ufrgs.br:10183/262810Repositório de PublicaçõesPUBhttps://lume.ufrgs.br/oai/requestopendoar:2023-07-30T06:46:08Repositório Institucional da UFRGS - Universidade Federal do Rio Grande do Sul (UFRGS)false |
dc.title.pt_BR.fl_str_mv |
Assessing the performance of the south american land data assimilation system version 2 (SALDAS-2) energy balance across diverse biomes |
title |
Assessing the performance of the south american land data assimilation system version 2 (SALDAS-2) energy balance across diverse biomes |
spellingShingle |
Assessing the performance of the south american land data assimilation system version 2 (SALDAS-2) energy balance across diverse biomes Ávila, Álvaro Vasconcellos Araujo de Biomas Balanco energetico Sensoriamento remoto Modelos físicos Precipitação América do Sul Modeling Surface Energy Balance Precipitation |
title_short |
Assessing the performance of the south american land data assimilation system version 2 (SALDAS-2) energy balance across diverse biomes |
title_full |
Assessing the performance of the south american land data assimilation system version 2 (SALDAS-2) energy balance across diverse biomes |
title_fullStr |
Assessing the performance of the south american land data assimilation system version 2 (SALDAS-2) energy balance across diverse biomes |
title_full_unstemmed |
Assessing the performance of the south american land data assimilation system version 2 (SALDAS-2) energy balance across diverse biomes |
title_sort |
Assessing the performance of the south american land data assimilation system version 2 (SALDAS-2) energy balance across diverse biomes |
author |
Ávila, Álvaro Vasconcellos Araujo de |
author_facet |
Ávila, Álvaro Vasconcellos Araujo de Gonçalves, Luis Gustavo Gonçalves de Souza, Vanessa de Arruda Alves, Laurizio Emanuel Ribeiro Galetti, Giovanna Deponte Maske, Bianca Muss Getirana, Augusto Ruhoff, Anderson Luis Biudes, Marcelo Sacardi Machado, Nadja Gomes Roberti, Débora Regina |
author_role |
author |
author2 |
Gonçalves, Luis Gustavo Gonçalves de Souza, Vanessa de Arruda Alves, Laurizio Emanuel Ribeiro Galetti, Giovanna Deponte Maske, Bianca Muss Getirana, Augusto Ruhoff, Anderson Luis Biudes, Marcelo Sacardi Machado, Nadja Gomes Roberti, Débora Regina |
author2_role |
author author author author author author author author author author |
dc.contributor.author.fl_str_mv |
Ávila, Álvaro Vasconcellos Araujo de Gonçalves, Luis Gustavo Gonçalves de Souza, Vanessa de Arruda Alves, Laurizio Emanuel Ribeiro Galetti, Giovanna Deponte Maske, Bianca Muss Getirana, Augusto Ruhoff, Anderson Luis Biudes, Marcelo Sacardi Machado, Nadja Gomes Roberti, Débora Regina |
dc.subject.por.fl_str_mv |
Biomas Balanco energetico Sensoriamento remoto Modelos físicos Precipitação América do Sul |
topic |
Biomas Balanco energetico Sensoriamento remoto Modelos físicos Precipitação América do Sul Modeling Surface Energy Balance Precipitation |
dc.subject.eng.fl_str_mv |
Modeling Surface Energy Balance Precipitation |
description |
Understanding the exchange of energy between the surface and the atmosphere is important in view of the climate scenario. However, it becomes a challenging task due to a sparse network of observations. This study aims to improve the energy balance estimates for the Amazon, Cerrado, and Pampa biomes located in South America using the radiation and precipitation forcing obtained from the Clouds and the Earth’s Radiant Energy System (CERES) and the precipitation CPTEC/MERGE datasets. We employed three surface models—Noah-MP, Community Land Model (CLSM), and Integrated Biosphere Simulator (IBIS)—and conducted modeling experiments, termed South America Land Data Assimilation System (SALDAS-2). The results showed that SALDAS-2 radiation estimates had the smallest errors. Moreover, SALDAS-2 precipitation estimates were better than the Global Land Data Assimilation System (GLDAS) in the Cerrado (MBE = −0.16) and Pampa (MBE = −0.19). Noah-MP presented improvements compared with CLSM and IBIS in 100% of towers located in the Amazon. CLSM tends to overestimate the latent heat flux and underestimate the sensible heat flux in the Amazon. Noah-MP and Ensemble outperformed GLDAS in terms latent and sensible heat fluxes. The potential of SALDAS-2 should be emphasized to provide more accurate estimates of surface energy balance. |
publishDate |
2023 |
dc.date.accessioned.fl_str_mv |
2023-07-29T03:35:06Z |
dc.date.issued.fl_str_mv |
2023 |
dc.type.driver.fl_str_mv |
Estrangeiro 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://hdl.handle.net/10183/262810 |
dc.identifier.issn.pt_BR.fl_str_mv |
2073-4433 |
dc.identifier.nrb.pt_BR.fl_str_mv |
001171248 |
identifier_str_mv |
2073-4433 001171248 |
url |
http://hdl.handle.net/10183/262810 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.ispartof.pt_BR.fl_str_mv |
Atmosphere. Basel. Vol. 14, no. 6 (June 2023), [article] 959, 24 p. |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
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