Weather Forecasting, Reanalysis, Downscaling

under construction

• Andrea Asperti, Ali Aydogdu, Angelo Greco, Fabio Merizzi, Pietro Miraglio, Beniamino Tartufoli, Alessandro Testa, Nadia Pinardi, Paolo Oddo. Deep Learning for Sea Surface Temperature Reconstruction under Cloud Occlusion

Generative models represent the state-of-the-art approach for addressing problems characterized by a substantial degree of stochasticity in the predicted outcomes. In essence, the focus lies in modeling the probability distribution of the results, wherein the expected value signifies the most probable prediction. The precise goal of generative models is to accurately capture this distribution.

This approach finds applications across a wide array of disciplines, encompassing domains such as weather forecasting, financial analysis and prediction, epidemiology and disease spread, traffic flow and transportation modeling, as well as social dynamics and opinion propagation.

• Asperti, A., Merizzi, F., Paparella, A. et al. Precipitation nowcasting with generative diffusion models. Appl Intell 55, 187 (2025). https://doi.org/10.1007/s10489-024-06048-y