Weather prediction using random forest machine learning model

The complex numerical climate models pose a big challenge for scientists in weather predictions, especially tropical system. This paper is focused on presenting the importance of prediction using machine learning (ML) technique. Recently many researchers recommended that can produce sensible predictions spite having no precise knowledge atmospheric physics. In this work, global solar radiation (GSR) MJ/m2/day and wind speed m/s predicted Tamil Nadu, India random forest ML model. model validated with measured data collected from IMD, Pune. results based are compared statistical regression SVM Overall, has minimum error values 0.750 MSE R2 score 0.97. Compared to model, more accurate. Thus, study neglects need an expensive measuring instrument all potential locations acquire data.