Forecasting the Future with Future Technologies: Advancements in Large Meteorological Models

arXiv:2404.06668v1 Announce Type: new
Abstract: The field of meteorological forecasting has undergone a significant transformation with the integration of large models, especially those employing deep learning techniques. This paper reviews the advancements and applications of these models in weather prediction, emphasizing their role in transforming traditional forecasting methods. Models like FourCastNet, Pangu-Weather, GraphCast, ClimaX, and FengWu have made notable contributions by providing accurate, high-resolution forecasts, surpassing the capabilities of traditional Numerical Weather Prediction (NWP) models. These models utilize advanced neural …

abstract applications arxiv cs.ai cs.lg deep learning deep learning techniques forecasting future future technologies integration large models paper physics.ao-ph prediction reviews role technologies transformation type weather weather prediction