An intelligent system to real time rainfall prediction using radar data


Autoria(s): Ulson, Jose Alfredo Covolan; Antonio, MDA; Da Silva, I. N.; De Souza, A. N.; Callaos, N.; DaSilva, I. N.; Molero, J.
Contribuinte(s)

Universidade Estadual Paulista (UNESP)

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