Climate Prediction

Climate prediction aims to forecast future climate states, encompassing weather patterns and longer-term climate trends, to inform mitigation and adaptation strategies. Current research heavily utilizes machine learning, employing diverse architectures like neural networks (including convolutional and generative diffusion models), and normalizing flows to improve prediction accuracy and uncertainty quantification across various temporal and spatial scales. These advancements, including the development of faster and more efficient models, are enhancing the reliability and detail of climate predictions, impacting sectors such as agriculture and resource management.