Validation of ECMWF climatic data, 1979–2017, and implications for modelling water balance for tropical climates
Autor(a) principal: | |
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Data de Publicação: | 2020 |
Outros Autores: | , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Institucional da UNESP |
Texto Completo: | http://dx.doi.org/10.1002/joc.6604 http://hdl.handle.net/11449/198787 |
Resumo: | Gridded meteorological systems greatly facilitate the analysis of the impacts of climate on crop development and productivity. Comparisons of these data with actual ground data validate this data source for various analyses in agricultural areas. The impact of the use of these grid data is an important evaluation for the temporal and spatial simulation of soil-water availability for crops. We seek to verify how meteorological (ECMWF) data represents the surface water balance for Minas Gerais state. Monthly data for air temperature (T) and precipitation (P) from ECMWF were compared with the data from 771 ground stations (National Meteorological Institute, INMET) in the state of Minas Gerais in southeastern Brazil for 1979–2017. Potential evapotranspiration was estimated by Thornthwaite method (1948), and water balance was estimated by the method proposed by Thornthwaite and Mather (1955), with an available water capacity of 100 mm. We temporally and spatially compared the two data sources, and the comparisons were evaluated for accuracy using mean absolute percentage error (MAPE) root mean square error (RMSE) and for precision using the adjusted coefficient of determination (R2adj). ECMWF T and P tended to be temporally and spatially similar to the INMET data. The largest deviation between INMET T and ECMWF T was 2.81°C, mainly in the southwest of the state (the Minas Gerais triangle) and part of the central region during winter and spring, and the smallest deviation was −0.19°C in the northeast. The largest deviation between INMET P and ECMWF P was 75 mm·mo−1 in the summer, mainly between January and February in the central region of Minas Gerais. ECMWF T and ECMWF P allowed an accurate estimation of the components of the water balance. For example, the lowest MAPEs were 1.21% for ECMWF water-storage capacity (southern Minas Gerais), 9.16% for ECMWF water deficiency (Vale do Jequitinhonha e Mucurí), and 8.69% for ECMWF excess water (Vale do Jequitinhonha e Mucurí). ECMWF can be used to estimate WB to represent surface stations, provided they are calibrated according to the region and seasons. |
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Validation of ECMWF climatic data, 1979–2017, and implications for modelling water balance for tropical climatesclimatic variablesclimatic zoningforecast verificationgeneral circulation modelwater deficiencyGridded meteorological systems greatly facilitate the analysis of the impacts of climate on crop development and productivity. Comparisons of these data with actual ground data validate this data source for various analyses in agricultural areas. The impact of the use of these grid data is an important evaluation for the temporal and spatial simulation of soil-water availability for crops. We seek to verify how meteorological (ECMWF) data represents the surface water balance for Minas Gerais state. Monthly data for air temperature (T) and precipitation (P) from ECMWF were compared with the data from 771 ground stations (National Meteorological Institute, INMET) in the state of Minas Gerais in southeastern Brazil for 1979–2017. Potential evapotranspiration was estimated by Thornthwaite method (1948), and water balance was estimated by the method proposed by Thornthwaite and Mather (1955), with an available water capacity of 100 mm. We temporally and spatially compared the two data sources, and the comparisons were evaluated for accuracy using mean absolute percentage error (MAPE) root mean square error (RMSE) and for precision using the adjusted coefficient of determination (R2adj). ECMWF T and P tended to be temporally and spatially similar to the INMET data. The largest deviation between INMET T and ECMWF T was 2.81°C, mainly in the southwest of the state (the Minas Gerais triangle) and part of the central region during winter and spring, and the smallest deviation was −0.19°C in the northeast. The largest deviation between INMET P and ECMWF P was 75 mm·mo−1 in the summer, mainly between January and February in the central region of Minas Gerais. ECMWF T and ECMWF P allowed an accurate estimation of the components of the water balance. For example, the lowest MAPEs were 1.21% for ECMWF water-storage capacity (southern Minas Gerais), 9.16% for ECMWF water deficiency (Vale do Jequitinhonha e Mucurí), and 8.69% for ECMWF excess water (Vale do Jequitinhonha e Mucurí). ECMWF can be used to estimate WB to represent surface stations, provided they are calibrated according to the region and seasons.Science and Technology of Mato Grosso do Sul - Campus of Naviraí IFMS - Federal Institute of EducationDepartment of Exact Sciences State University of São Paulo-UNESPDepartment of Exact Sciences State University of São Paulo-UNESPIFMS - Federal Institute of EducationUniversidade Estadual Paulista (Unesp)de Oliveira Aparecido, Lucas Eduardode Souza Rolim, Glauco [UNESP]da Silva Cabral de Moraes, Jose Reinaldo2020-12-12T01:21:58Z2020-12-12T01:21:58Z2020-01-01info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articlehttp://dx.doi.org/10.1002/joc.6604International Journal of Climatology.1097-00880899-8418http://hdl.handle.net/11449/19878710.1002/joc.66042-s2.0-85084133620Scopusreponame:Repositório Institucional da UNESPinstname:Universidade Estadual Paulista (UNESP)instacron:UNESPengInternational Journal of Climatologyinfo:eu-repo/semantics/openAccess2021-10-22T20:28:23Zoai:repositorio.unesp.br:11449/198787Repositório InstitucionalPUBhttp://repositorio.unesp.br/oai/requestopendoar:29462024-08-05T14:56:01.281846Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)false |
dc.title.none.fl_str_mv |
Validation of ECMWF climatic data, 1979–2017, and implications for modelling water balance for tropical climates |
title |
Validation of ECMWF climatic data, 1979–2017, and implications for modelling water balance for tropical climates |
spellingShingle |
Validation of ECMWF climatic data, 1979–2017, and implications for modelling water balance for tropical climates de Oliveira Aparecido, Lucas Eduardo climatic variables climatic zoning forecast verification general circulation model water deficiency |
title_short |
Validation of ECMWF climatic data, 1979–2017, and implications for modelling water balance for tropical climates |
title_full |
Validation of ECMWF climatic data, 1979–2017, and implications for modelling water balance for tropical climates |
title_fullStr |
Validation of ECMWF climatic data, 1979–2017, and implications for modelling water balance for tropical climates |
title_full_unstemmed |
Validation of ECMWF climatic data, 1979–2017, and implications for modelling water balance for tropical climates |
title_sort |
Validation of ECMWF climatic data, 1979–2017, and implications for modelling water balance for tropical climates |
author |
de Oliveira Aparecido, Lucas Eduardo |
author_facet |
de Oliveira Aparecido, Lucas Eduardo de Souza Rolim, Glauco [UNESP] da Silva Cabral de Moraes, Jose Reinaldo |
author_role |
author |
author2 |
de Souza Rolim, Glauco [UNESP] da Silva Cabral de Moraes, Jose Reinaldo |
author2_role |
author author |
dc.contributor.none.fl_str_mv |
IFMS - Federal Institute of Education Universidade Estadual Paulista (Unesp) |
dc.contributor.author.fl_str_mv |
de Oliveira Aparecido, Lucas Eduardo de Souza Rolim, Glauco [UNESP] da Silva Cabral de Moraes, Jose Reinaldo |
dc.subject.por.fl_str_mv |
climatic variables climatic zoning forecast verification general circulation model water deficiency |
topic |
climatic variables climatic zoning forecast verification general circulation model water deficiency |
description |
Gridded meteorological systems greatly facilitate the analysis of the impacts of climate on crop development and productivity. Comparisons of these data with actual ground data validate this data source for various analyses in agricultural areas. The impact of the use of these grid data is an important evaluation for the temporal and spatial simulation of soil-water availability for crops. We seek to verify how meteorological (ECMWF) data represents the surface water balance for Minas Gerais state. Monthly data for air temperature (T) and precipitation (P) from ECMWF were compared with the data from 771 ground stations (National Meteorological Institute, INMET) in the state of Minas Gerais in southeastern Brazil for 1979–2017. Potential evapotranspiration was estimated by Thornthwaite method (1948), and water balance was estimated by the method proposed by Thornthwaite and Mather (1955), with an available water capacity of 100 mm. We temporally and spatially compared the two data sources, and the comparisons were evaluated for accuracy using mean absolute percentage error (MAPE) root mean square error (RMSE) and for precision using the adjusted coefficient of determination (R2adj). ECMWF T and P tended to be temporally and spatially similar to the INMET data. The largest deviation between INMET T and ECMWF T was 2.81°C, mainly in the southwest of the state (the Minas Gerais triangle) and part of the central region during winter and spring, and the smallest deviation was −0.19°C in the northeast. The largest deviation between INMET P and ECMWF P was 75 mm·mo−1 in the summer, mainly between January and February in the central region of Minas Gerais. ECMWF T and ECMWF P allowed an accurate estimation of the components of the water balance. For example, the lowest MAPEs were 1.21% for ECMWF water-storage capacity (southern Minas Gerais), 9.16% for ECMWF water deficiency (Vale do Jequitinhonha e Mucurí), and 8.69% for ECMWF excess water (Vale do Jequitinhonha e Mucurí). ECMWF can be used to estimate WB to represent surface stations, provided they are calibrated according to the region and seasons. |
publishDate |
2020 |
dc.date.none.fl_str_mv |
2020-12-12T01:21:58Z 2020-12-12T01:21:58Z 2020-01-01 |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://dx.doi.org/10.1002/joc.6604 International Journal of Climatology. 1097-0088 0899-8418 http://hdl.handle.net/11449/198787 10.1002/joc.6604 2-s2.0-85084133620 |
url |
http://dx.doi.org/10.1002/joc.6604 http://hdl.handle.net/11449/198787 |
identifier_str_mv |
International Journal of Climatology. 1097-0088 0899-8418 10.1002/joc.6604 2-s2.0-85084133620 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
International Journal of Climatology |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.source.none.fl_str_mv |
Scopus reponame:Repositório Institucional da UNESP instname:Universidade Estadual Paulista (UNESP) instacron:UNESP |
instname_str |
Universidade Estadual Paulista (UNESP) |
instacron_str |
UNESP |
institution |
UNESP |
reponame_str |
Repositório Institucional da UNESP |
collection |
Repositório Institucional da UNESP |
repository.name.fl_str_mv |
Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP) |
repository.mail.fl_str_mv |
|
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1808128438096101376 |