Spatial and seasonal dynamics of rainfall in subtropical Brazil



Título del documento: Spatial and seasonal dynamics of rainfall in subtropical Brazil
Revista: Boletim de ciencias geodesicas
Base de datos: PERIÓDICA
Número de sistema: 000456635
ISSN: 1413-4853
Autors: 1
2
3
Institucions: 1Universidade Federal de Santa Maria, Programa de Pos-Graduacao en Ciencias Ambientais, Santa Maria, Rio Grande do Sul. Brasil
2Universidade de Sao Paulo, Escola Superior de Agricultura "Luiz de Queiroz", Piracicaba, Sao Paulo. Brasil
3Universidade Federal de Santa Maria, Departamento de Estatistica, Santa Maria, Rio Grande do Sul. Brasil
Any:
Volum: 29
Número: 2
País: Brasil
Idioma: Inglés
Tipo de documento: Artículo
Enfoque: Analítico, descriptivo
Resumen en inglés The mapping of rainfall is fundamental in the hydrological modeling process. In this sense, the importance of knowing the geographic and seasonal dynamics of average estimates of rainfall and associated uncertainties is evident. Thus, the present study aimed to predict the spatial and seasonal distribution of rainfall, with the estimation of related uncertainties, in the state of Rio Grande do Sul (RS). Average rainfall varies over the months of the year. In January, February, June, July, August, and September it rains more north and northeast. In March, April, May, October, November, and December it rains more northwest and north. In general, it rains a lot in October and little rain in August. From a geographical point of view, it is possible to highlight that greater volumes of rain occur in the northern part of the state of RS. The uncertainties associated with rainfall estimates show divergent temporal dynamics, with the greatest uncertainties tending to occur in January, February, September, and October and that the smallest uncertainties are observed in June, July, and August
Disciplines Geociencias
Paraules clau: Ciencias de la atmósfera,
Lluvia,
Geoestadística,
Krigeaje,
Dinámica espacial,
Brasil
Keyword: Atmospheric sciences,
Rainfall,
Geostatistics,
Kriging,
Spatial dynamics,
Brazil
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