Lightning Prediction using Radiosonde Data

L.Y. Weng, J. Bin Omar, Y.K. Siah, I. Bin Zainal Abidin, and S.K. Ahmad (Malaysia)


Lightning prediction, Lightning forecasting, Neural networks, Artificial intelligence


This paper presents a concept of predicting lightning with the data from radiosonde using only a simple back propagation neural network model written in C code. The location of interest in this research is Kuala Lumpur International Airport (KLIA). In this model, the parameters related to wind were disregarded. Preliminary results indicate that this method shows some positive results. Future work should include wind parameters to fully capture all properties for lightning formation, subsequently its prediction.

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