DiffDA: Diffusion Model for High-Resolution Data Assimilation in Weather Forecasting

DiffDA proposes a denoising diffusion model for assimilating atmospheric variables, achieving high resolution and accuracy. The approach leverages GraphCast neural network as the backbone, setting a new standard in ML-based data assimilation models.