Neuro-computing based short range prediction of some meteorological parameters during the pre-monsoon season
A Feed forward multi-layered artificial neural network model is designed in this paper to estimate the maximum surface temperature and relative humidity needed for the genesis of severe thunderstorms over Calcutta (22 degrees 32 degrees, 88 degrees 20 degrees). The performance of the model is found to be adroit. It has, thus, been discerned that the neural network technique is of great use in forecasting the occurrence of high frequency small-scale weather systems like Severe Local Storms. Filing up the missing values and extension of time series is observed to be possible with this model. Prediction error is computed and compared for single layer network and one hidden layer neural nets. Result reveals the efficiency of the one hidden layer neural net.
surface temperature relative humidity severe thunderstorm single layer network one hidden layer neural net