An intelligent system to real time rainfall prediction using radar data
Contribuinte(s) |
Universidade Estadual Paulista (UNESP) |
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Data(s) |
20/05/2014
20/05/2014
01/01/2001
|
Resumo |
This work presents a new approach for rainfall measurements making use of weather radar data for real time application to the radar systems operated by institute of Meteorological Research (IPMET) - UNESP - Bauru - SP-Brazil. Several real time adjustment techniques has been presented being most of them based on surface rain-gauge network. However, some of these methods do not regard the effect of the integration area, time integration and distance rainfall-radar. In this paper, artificial neural networks have been applied for generate a radar reflectivity-rain relationships which regard all effects described above. To evaluate prediction procedure, cross validation was performed using data from IPMET weather Doppler radar and rain-gauge network under the radar umbrella. The preliminary results were acceptable for rainfalls prediction. The small errors observed result from the spatial density and the time resolution of the rain-gauges networks used to calibrate the radar. |
Formato |
30-34 |
Identificador |
http://dl.acm.org/citation.cfm?id=704229 World Multiconference on Systemics, Cybernetics and Informatics, Vol 1, Proceedings. Orlando: Int Inst Informatics & Systemics, p. 30-34, 2001. http://hdl.handle.net/11449/36961 WOS:000175785900006 |
Idioma(s) |
eng |
Publicador |
Int Inst Informatics & Systemics |
Relação |
World Multiconference on Systemics, Cybernetics and Informatics, Vol 1, Proceedings |
Direitos |
closedAccess |
Palavras-Chave | #rainfall #radar #Z-R relationships #artificial neural network |
Tipo |
info:eu-repo/semantics/conferencePaper |