A Novel Approach for Thunderstorm and Lightning Detection System

Thunderstorm and lightning is a sudden electrical expulsion manifested by a blaze of lightening with a muffled sound. It is one of the most spectacular mesoscale weather phenomena in the atmosphere which occurs seasonally. Every thunderstorm produce lightening, this kills more people every year than tornadoes, and prediction of thunderstorms is said to be the most complicated task in weather forecasting, due to its limited spatial and temporal extension either dynamically or physically. Various researches are been carried on for forecasting of this severe to reduce damage. Many of the researchers proposed various methodologies like STP model, MOM model, CG model, LM model, QKP model, DBD model and so on for the detection, but neither of them could provide an accurate prediction. The proposed system is to gather the satellite images obtained from dataset in order to predict whether the cloud images produces thunderstorms or not. The proposed system adopted clustering and wavelet transform techniques for thunderstorms and lightning detection using image processing and data mining. The proposed system improves the prediction rate to a greater extent, on the basis of some statistical analysis.