Statistical downscaling in the TRMM satellite rainfall estimates for the Goiás state and the Federal District, Brazil
Autor(a) principal: | |
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Data de Publicação: | 2023 |
Outros Autores: | , , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Pesquisa Agropecuária Tropical (Online) |
Texto Completo: | https://revistas.ufg.br/pat/article/view/75552 |
Resumo: | Rainfall is a fundamental component of agricultural production, and knowing its potential and variability can ensure the success of this activity. However, the number of meteorological stations is still small, even in states with agricultural aptitude, such as Goiás. Geoprocessing techniques can be used to overcome this problem. Thus, this study aimed to evaluate the products of the Tropical Rainfall Measuring Mission (TRMM) satellite to describe the annual and monthly rainfall variability in the Goiás state and the Federal District (Brazil). Interpolations were carried out to increase the spatial resolution by means of ordinary kriging and cluster analysis for spatial and temporal distribution. It was observed that the evaluated territory can be classified into three regions with differentiated water regimes up to 500 mm annually, with seasonality of accumulated precipitation from November to March. Even though the regression evaluation showed limitations for a monthly precipitation above 200 mm, the analysis of the TRMM satellite products demonstrated that this tool allows forecasts of provisional normals with a higher spatial resolution than the Brazilian National Institute of Meteorology (INMET) stations network, with known measurement errors for each evaluation period, allowing the data application in forecast models for agricultural planning involving water management. KEYWORDS: Brazilian Midwest rainfall, Tropical Rainfall Measuring Mission satellite, spatial and temporal variability. |
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Statistical downscaling in the TRMM satellite rainfall estimates for the Goiás state and the Federal District, BrazilEstatística para redução de escala nas estimativas de chuva pelo satélite TRMM para o estado de Goiás e Distrito Federal, BrasilRainfall is a fundamental component of agricultural production, and knowing its potential and variability can ensure the success of this activity. However, the number of meteorological stations is still small, even in states with agricultural aptitude, such as Goiás. Geoprocessing techniques can be used to overcome this problem. Thus, this study aimed to evaluate the products of the Tropical Rainfall Measuring Mission (TRMM) satellite to describe the annual and monthly rainfall variability in the Goiás state and the Federal District (Brazil). Interpolations were carried out to increase the spatial resolution by means of ordinary kriging and cluster analysis for spatial and temporal distribution. It was observed that the evaluated territory can be classified into three regions with differentiated water regimes up to 500 mm annually, with seasonality of accumulated precipitation from November to March. Even though the regression evaluation showed limitations for a monthly precipitation above 200 mm, the analysis of the TRMM satellite products demonstrated that this tool allows forecasts of provisional normals with a higher spatial resolution than the Brazilian National Institute of Meteorology (INMET) stations network, with known measurement errors for each evaluation period, allowing the data application in forecast models for agricultural planning involving water management. KEYWORDS: Brazilian Midwest rainfall, Tropical Rainfall Measuring Mission satellite, spatial and temporal variability.A chuva é um componente fundamental para a produção agrícola, e conhecer seu potencial e variabilidade pode garantir o sucesso dessa atividade. Entretanto, o número de estações meteorológicas ainda é pequeno, mesmo em estados com aptidão agrícola, como Goiás. Para contornar esse problema, técnicas de geoprocessamento podem ser utilizadas. Objetivou-se avaliar os produtos do satélite Tropical Rainfall Measuring Mission (TRMM) para a descrição da variabilidade anual e mensal da precipitação pluvial no estado de Goiás e no Distrito Federal. Interpolações foram realizadas para aumentar a resolução espacial por meio de krigagem ordinária e análise de cluster para distribuição espacial e temporal. Verificou-se que o território avaliado pode ser classificado em três regiões com regimes hídricos diferenciados em até 500 mm anuais, com sazonalidade de precipitação acumulada de novembro a março. Embora a avaliação de regressão tenha mostrado limitações para precipitação mensal acima de 200 mm, a análise dos produtos do satélite TRMM demonstrou que esta ferramenta permite previsões de normais provisórias com maior resolução espacial que a rede de estações do Instituto Nacional de Meteorologia (INMET), com erros de medição conhecidos para cada período de avaliação, permitindo a aplicação dos dados em modelos de previsão para planejamento agrícola envolvendo manejo hídrico. PALAVRAS-CHAVE: Chuvas no Centro-Oeste brasileiro, satélite Tropical Rainfall Measuring Mission, variabilidade espacial e temporal.Escola de Agronomia - Universidade Federal de Goiás2023-07-03info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionAvaliado por paresapplication/pdfhttps://revistas.ufg.br/pat/article/view/75552Pesquisa Agropecuária Tropical [Agricultural Research in the Tropics]; Vol. 53 (2023); e75552Pesquisa Agropecuária Tropical (Agricultural Research in the Tropics); Vol. 53 (2023); e75552Pesquisa Agropecuária Tropical; v. 53 (2023); e755521983-4063reponame:Pesquisa Agropecuária Tropical (Online)instname:Universidade Federal de Goiás (UFG)instacron:UFGenghttps://revistas.ufg.br/pat/article/view/75552/39993Copyright (c) 2023 Pesquisa Agropecuária Tropicalinfo:eu-repo/semantics/openAccessJardim , Carlos Cesar SilvaCasaroli, DerblaiAlves Júnior, JoséEvangelista, Adão Wagner PêgoBattisti, Rafael2023-07-03T18:47:55Zoai:ojs.revistas.ufg.br:article/75552Revistahttps://revistas.ufg.br/patPUBhttps://revistas.ufg.br/pat/oaiaseleguini.pat@gmail.com||mgoes@agro.ufg.br1983-40631517-6398opendoar:2024-05-21T19:56:38.928367Pesquisa Agropecuária Tropical (Online) - Universidade Federal de Goiás (UFG)true |
dc.title.none.fl_str_mv |
Statistical downscaling in the TRMM satellite rainfall estimates for the Goiás state and the Federal District, Brazil Estatística para redução de escala nas estimativas de chuva pelo satélite TRMM para o estado de Goiás e Distrito Federal, Brasil |
title |
Statistical downscaling in the TRMM satellite rainfall estimates for the Goiás state and the Federal District, Brazil |
spellingShingle |
Statistical downscaling in the TRMM satellite rainfall estimates for the Goiás state and the Federal District, Brazil Jardim , Carlos Cesar Silva |
title_short |
Statistical downscaling in the TRMM satellite rainfall estimates for the Goiás state and the Federal District, Brazil |
title_full |
Statistical downscaling in the TRMM satellite rainfall estimates for the Goiás state and the Federal District, Brazil |
title_fullStr |
Statistical downscaling in the TRMM satellite rainfall estimates for the Goiás state and the Federal District, Brazil |
title_full_unstemmed |
Statistical downscaling in the TRMM satellite rainfall estimates for the Goiás state and the Federal District, Brazil |
title_sort |
Statistical downscaling in the TRMM satellite rainfall estimates for the Goiás state and the Federal District, Brazil |
author |
Jardim , Carlos Cesar Silva |
author_facet |
Jardim , Carlos Cesar Silva Casaroli, Derblai Alves Júnior, José Evangelista, Adão Wagner Pêgo Battisti, Rafael |
author_role |
author |
author2 |
Casaroli, Derblai Alves Júnior, José Evangelista, Adão Wagner Pêgo Battisti, Rafael |
author2_role |
author author author author |
dc.contributor.author.fl_str_mv |
Jardim , Carlos Cesar Silva Casaroli, Derblai Alves Júnior, José Evangelista, Adão Wagner Pêgo Battisti, Rafael |
description |
Rainfall is a fundamental component of agricultural production, and knowing its potential and variability can ensure the success of this activity. However, the number of meteorological stations is still small, even in states with agricultural aptitude, such as Goiás. Geoprocessing techniques can be used to overcome this problem. Thus, this study aimed to evaluate the products of the Tropical Rainfall Measuring Mission (TRMM) satellite to describe the annual and monthly rainfall variability in the Goiás state and the Federal District (Brazil). Interpolations were carried out to increase the spatial resolution by means of ordinary kriging and cluster analysis for spatial and temporal distribution. It was observed that the evaluated territory can be classified into three regions with differentiated water regimes up to 500 mm annually, with seasonality of accumulated precipitation from November to March. Even though the regression evaluation showed limitations for a monthly precipitation above 200 mm, the analysis of the TRMM satellite products demonstrated that this tool allows forecasts of provisional normals with a higher spatial resolution than the Brazilian National Institute of Meteorology (INMET) stations network, with known measurement errors for each evaluation period, allowing the data application in forecast models for agricultural planning involving water management. KEYWORDS: Brazilian Midwest rainfall, Tropical Rainfall Measuring Mission satellite, spatial and temporal variability. |
publishDate |
2023 |
dc.date.none.fl_str_mv |
2023-07-03 |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Avaliado por pares |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
https://revistas.ufg.br/pat/article/view/75552 |
url |
https://revistas.ufg.br/pat/article/view/75552 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
https://revistas.ufg.br/pat/article/view/75552/39993 |
dc.rights.driver.fl_str_mv |
Copyright (c) 2023 Pesquisa Agropecuária Tropical info:eu-repo/semantics/openAccess |
rights_invalid_str_mv |
Copyright (c) 2023 Pesquisa Agropecuária Tropical |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
application/pdf |
dc.publisher.none.fl_str_mv |
Escola de Agronomia - Universidade Federal de Goiás |
publisher.none.fl_str_mv |
Escola de Agronomia - Universidade Federal de Goiás |
dc.source.none.fl_str_mv |
Pesquisa Agropecuária Tropical [Agricultural Research in the Tropics]; Vol. 53 (2023); e75552 Pesquisa Agropecuária Tropical (Agricultural Research in the Tropics); Vol. 53 (2023); e75552 Pesquisa Agropecuária Tropical; v. 53 (2023); e75552 1983-4063 reponame:Pesquisa Agropecuária Tropical (Online) instname:Universidade Federal de Goiás (UFG) instacron:UFG |
instname_str |
Universidade Federal de Goiás (UFG) |
instacron_str |
UFG |
institution |
UFG |
reponame_str |
Pesquisa Agropecuária Tropical (Online) |
collection |
Pesquisa Agropecuária Tropical (Online) |
repository.name.fl_str_mv |
Pesquisa Agropecuária Tropical (Online) - Universidade Federal de Goiás (UFG) |
repository.mail.fl_str_mv |
aseleguini.pat@gmail.com||mgoes@agro.ufg.br |
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1799874821579866112 |