Extreme Weather

Extreme weather prediction is a critical area of research aiming to improve forecasting accuracy and reliability, particularly for high-impact events like floods, wildfires, and heatwaves. Current research heavily utilizes machine learning, employing diverse models such as recurrent neural networks (RNNs, including LSTMs and GRUs), support vector machines (SVMs), and convolutional neural networks (CNNs), often combined with novel loss functions designed to better capture extreme value distributions. These advancements are crucial for enhancing disaster preparedness, risk assessment, and mitigation strategies, improving the safety and efficiency of sectors like aviation and impacting climate change adaptation efforts.