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http://acervodigital.unesp.br/handle/11449/36961- Título:
- An intelligent system to real time rainfall prediction using radar data
- Universidade Estadual Paulista (UNESP)
- 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.
- 1-Jan-2001
- World Multiconference on Systemics, Cybernetics and Informatics, Vol 1, Proceedings. Orlando: Int Inst Informatics & Systemics, p. 30-34, 2001.
- 30-34
- Int Inst Informatics & Systemics
- rainfall
- radar
- Z-R relationships
- artificial neural network
- http://dl.acm.org/citation.cfm?id=704229
- Acesso restrito
- outro
- http://repositorio.unesp.br/handle/11449/36961
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