CoDiCast: Conditional Diffusion Model for Global Weather Prediction with Uncertainty Quantification

Understand

Accurate weather forecasting is critical for science and society.

• Yet, existing methods have not managed to simultaneously have the properties of high accuracy, low uncertainty, and high computational efficiency.
• On one hand, to quantify the uncertainty in weather predictions, the strategy of ensemble forecast (i.e., generating a set of diverse predictions) is often employed.
• However, traditional ensemble numerical weather prediction (NWP) is computationally intensive.