THUNDERSTORM TRACKING SYSTEM USING NEURAL NETWORKS AND MEASURED ELECTRIC FIELDS FROM A FEW FIELD MILLS

Jigme Singye - Katsumi Masugata - Tadakuni Murai - Iwao Kitamura - Honda Kontani

   This paper presents a novel system to quickly asses the direction of thunderstorm by using a few field mills on the ground. As opposed to the traditional methods of using expensive radar systems to detect the thundercloud movement, the method presented in this paper simply uses the electric waveforms detected by the field mills and using a neural network of suitable complexity and can determine the thunderclouds direction with reasonable accuracy. The neural system is trained with data from the simulation of thundercloud movement using parameters obtained through experiments. Through extensive testing, it is found that the system presented in this paper can track the direction of the thunderstorm as it randomly propagates while dynamically changing its parameters, and thus, offers the possibility of using the system for practical purposes. In this paper, two types of neural networks are developed and their efficiencies are compared.

Keywords: thundercloud, lightning, dipole, electric charge in cloud, electric charge on ground, field mill, neural network

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