Advancing Weather Prediction and Forecasting: A Comparative Study of AI and Deep Learning Techniques

Predicting the weather is one of the most important factor that helps to manage natural disasters, helps in agricultural field, and provide public safety. Using Traditional methods can be an outdated option as they are limited by complex calculations, inconsistent data, and unpredictable results. While using Artificial Intelligence and Deep Learning methods can be a smart way as they have improved the accuracy of weather prediction and forecasting. Some challenges are still present like integrating data, predicting extreme weather scenario. This Study majorly focus how these advance algorithms can be used to predict weather like rainfall, floods, hurricanes and cyclones by analysing how different machine learning and deep learning algorithms are applied, also comparing various models based on their accuracy, precision, recall and F1 Score. The paper has also discussed the major challenges and future directions for improving weather prediction and Forecasting.