This paper is based on data analysis by python programming language code provided by ChatGPT executed on google collaborator platform, model used as neural network, to understand the trend of special weather phenomena for the period March to May, to check the occurrence of special weather event like lightning, thunderstorm, rain, drizzle, squall, during this period, called as Nor ‘wester season and also as pre-monsoon period. Analysis has been done with data starting from the historical period since 1969, as recorded from observation for the station Alipore (42807) and thus with the help of this historical data, predicted the trend of the occurrence of special weather phenomena for the next five years. Analysis has been done with the help of ChatGPT, the chat-bot of artificial intelligence and machine learning. Also, the prediction by ARIMA, code provided by ChatGPT, has been done in addition to compare the result. The source of data is online data supply platform ‘INDIA METEOROLOGICAL DEPARTMENT, PUNE’ and the online site ‘OGIMET’ .The surface data for Alipore (42807) with all relevant weather parameters as available there has been collected in csv file format, since 1969 till 2025,for this season, as available,  then uploading the csv file in google collaborator platform ,executed analysis by python neural network model to find the trend of special weather events during the Nor ’wester season (March to May). During this period, the sudden, intense storm usually occur in the afternoon, or evening, which can bring gale-speed winds, localized torrential rains, occasionally accompanied by hailstorms, followed by uprooting trees and waterlogging roads and also brings cooling effect in atmosphere. This phenomenon is called in different name in different region of India, ‘Kal-baisakhi’ in Bengal. In this research, this was the aim, to determine, whether due to global warming, the frequency of this Nor ‘wester is changing or not. So, with the help of data analysis, analysis of big historical data by LSTM, neural network model, the future trend of this weather pattern has been tested to study the nature of change if there is any, and it has been observed as decreasing.