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Please use this identifier to cite or link to this item: http://acervodigital.unesp.br/handle/11449/36961
Title: 
An intelligent system to real time rainfall prediction using radar data
Author(s): 
Institution: 
Universidade Estadual Paulista (UNESP)
Abstract: 
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.
Issue Date: 
1-Jan-2001
Citation: 
World Multiconference on Systemics, Cybernetics and Informatics, Vol 1, Proceedings. Orlando: Int Inst Informatics & Systemics, p. 30-34, 2001.
Time Duration: 
30-34
Publisher: 
Int Inst Informatics & Systemics
Keywords: 
  • rainfall
  • radar
  • Z-R relationships
  • artificial neural network
Source: 
http://dl.acm.org/citation.cfm?id=704229
URI: 
Access Rights: 
Acesso restrito
Type: 
outro
Source:
http://repositorio.unesp.br/handle/11449/36961
Appears in Collections:Artigos, TCCs, Teses e Dissertações da Unesp

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