ClimateGuard: A Forecasting Application for Extreme Weather Event Preparedness

Abstract

In today's data-driven world, weather forecasting is an essential undertaking that affects transportation, agriculture, disaster relief, and everyday human activities. This study examines the most recent developments in weather prediction technology, encompassing both contemporary AI-based methods and conventional numerical models. We address the shift from statistical to data-driven models and the benefits of using machine learning approaches by examining many review studies. Along with offering a generalized algorithmic technique appropriate for intelligent weather systems, the paper also provides an outline of the difficulties in forecasting accuracy [1], [2], and [4]