Machine learning (ML) provides novel and powerful ways of accurately and efficiently
recognizing complex patterns, emulating nonlinear dynamics, and predicting the spatio …

The recent hype about artificial intelligence has sparked renewed interest in applying the
successful deep learning (DL) methods for image recognition, speech recognition, robotics …

Weather forecasting is important for science and society. At present, the most accurate
forecast system is the numerical weather prediction (NWP) method, which represents …

Global medium-range weather forecasting is critical to decision-making across many social
and economic domains. Traditional numerical weather prediction uses increased compute …

FourCastNet, short for Fourier Forecasting Neural Network, is a global data-driven weather
forecasting model that provides accurate short to medium-range global predictions at …

Global medium-range weather forecasting is critical to decision-making across many social
and economic domains. Traditional numerical weather prediction uses increased compute …

Most state-of-the-art approaches for weather and climate modeling are based on physics-
informed numerical models of the atmosphere. These approaches aim to model the non …

Abstract Fourier Neural Operators (FNOs) have proven to be an efficient and effective
method for resolution-independent operator learning in a broad variety of application areas …

We present FengWu, an advanced data-driven global medium-range weather forecast
system based on Artificial Intelligence (AI). Different from existing data-driven weather …

Earth system models (ESMs) are our main tools for quantifying the physical state of the Earth
and predicting how it might change in the future under ongoing anthropogenic forcing. In …