Forecasting thunderstorm is one of the most difficult tasks in weather prediction, due to their rather small spatial and temporal extension and the inherent nonlinearity of their dynamics and physics. Accurate forecasting of severe thunderstorms is critical for a large range of users in the community. In this paper, experiments are conducted with artificial neural network model to predict severe thunderstorms that occurred over Kolkata during May 3, 11, and 15, 2009, using thunderstorm affected meteorological parameters. The capabilities of six learning algorithms, namely, Step, Momentum, Conjugate Gradient, Quick Propagation, Levenberg-Marquardt, and Delta-Bar-Delta, in predicting thunderstorms and the usefulness for the advanced prediction were studied and their performances were evaluated by a number of statistical measures. The results indicate that Levenberg-Marquardt algorithm well predicted thunderstorm affected surface parameters and 1, 3, and 24？h advanced prediction models are able to predict hourly temperature and relative humidity adequately with sudden fall and rise during thunderstorm hour. This demonstrates its distinct capability and advantages in identifying meteorological time series comprising nonlinear characteristics. The developed model can be useful in decision making for meteorologists and others who work with real-time thunderstorm forecast. 1. Introduction Thunderstorm, resulting from vigorous convective activity, is one of the most spectacular weather phenomena in the atmosphere. It is one of the global phenomena that can occur anywhere in the world at any time. It is also known as lightning storm or hailstorm. This storm is a form of weather characteristic containing strong wind, lightning, heavy rain, and sometimes snow or hail. Although thunderstorm is generally very short-lived phenomena, it has great potential to produce serious damage to human life and property such as lightning, damaging straight-line wind, large sized hail, heavy precipitation, and flooding. Many parts over the Indian region experience thunderstorms at higher frequency during premonsoon months (March–May), when the atmosphere is highly unstable because of high temperatures prevailing at lower levels. Severe thunderstorms form and move generally from northwest to southeast over the eastern and northeastern states of India during the premonsoon season. These severe thunderstorms associated with thunder, squall lines, lightning, torrential rain, and hail cause extensive loss in agriculture, damage to property, and also loss of life. The casualties
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