Data/hora: 22/06/2024 03:34:16

Biblioteca(s): 	Embrapa Agrossilvipastoril.	
Data corrente: 	23/02/2022	
Data da última atualização: 	23/02/2022	
Autoria: 	GRIS, D. J.; VENDRUSCULO, L. G.; ZOLIN, C. A.	
Afiliação: 	DIEGO JOSÉ GRIS, UFSM, Santa-Maria-RS; LAURIMAR GONCALVES VENDRUSCULO, CNPTIA; CORNELIO ALBERTO ZOLIN, CPAMT.	
Título: 	Evaluation of chirps satellite rainfall data at Mato Grosso, Brazil.	
Ano de publicação: 	2018	
Fonte/Imprenta: 	In: ENCONTRO DE CIÊNCIA E TECNOLOGIAS AGROSSUSTENTÁVEIS, 2.; JORNADA CIENTÍFICA DA EMBRAPA AGROSSILVIPASTORIL, 7., 2018. Sinop, MT. Resumos... Sinop, MT: Embrapa Agrossilpastoril, 2018. p. 161-164.	
Idioma: 	Inglês	
Conteúdo: 	Water is a basic resource for human life and understanding how it cycles in the environment is important for its management. Nevertheless, hydrological models require high quality data in order to accurately reproduce the natural water cycle. Precipitation is one of the most important data required for these models, and it is usually provided by weather stations located across the territory. However, stations tend to be sparsely distributed in developing countries, especially in low populated areas, which is the case of the state of Mato Grosso, Brazil. Mato Grosso has only 36 official weather stations (INMET, 2018) in an area of 903,357 km², resulting in approximately one station for each 25,000 km². Considering this context, satellite-based precipitation products become a useful resource to overcome the lack of a dense weather station network. One of these products is the Climate Hazards Group InfraRed Precipitation with Station (CHIRPS). However, the main issue associated with remote sensed rainfall data is that they are only estimates based on algorithms that compute rainfall amount from satellite measurements, such as cloud temperature (Arkin; Meisner, 1987). Consequently, it is crucial to evaluate the accuracy of these precipitation products before using them in further applications. Therefore, the objective of this study was to compare CHIRPS rainfall data to ground rain gauges in Mato Grosso State, Brazil, and evaluate the satellite estimate accuracy.	
Palavras-Chave: 	Mato Grosso.	
Thesagro: 	Análise de Dados; Chuva; Satélite.	
Thesaurus Nal: 	Accuracy; Data analysis; Rain; Rainfall duration; Satellites.	
Categoria do assunto: 	X Pesquisa, Tecnologia e Engenharia	
URL: 	http://ainfo.cnptia.embrapa.br/digital/bitstream/item/231808/1/2018-cpamt-caz-evaluation-chirps-satellite-rainfall-data-mato-grosso-p-161-164.pdf	
Registro original: 	Embrapa Agrossilvipastoril (CPAMT)	
Exemplares: 	CPAMT - (1809-1) - UPC - AA - DD -  -  -  - DIS