Dataset for AI Based Framework for Short Term Weather Forecasting and Extreme Event Detection

This dataset contains processed meteorological data used for training and evaluating deep learning models for short-term weather forecasting and extreme event detection. The dataset includes variables such as temperature, precipitation, humidity, and wind speed, collected and preprocessed from publicly available sources including NASA POWER and Open-Meteo. The data has been structured into multivariate time series format and prepared using preprocessing techniques such as normalization, interpolation, and sliding window generation for supervised learning. This dataset supports the development and evaluation of models such as MLP, LSTM, GRU, CNN, CNN-LSTM, and Transformer architectures for real-time weather prediction and extreme event classification.