Latest

• Towards Accurate Extreme Event Likelihoods from Diffusion Model Climate Emulators
• Demystifying Data-Driven Probabilistic Medium-Range Weather Forecasting
• HealDA: Highlighting the Importance of Initial Errors in End-to-End AI Weather Forecasts
• Kilometer-Scale Convection-Allowing Model Emulation Using Generative Diffusion Modeling
• Learning Accurate Storm-Scale Evolution from Observations
• Long-Range Distillation: Distilling 10,000 Years of Simulated Climate into Long Timestep AI Weather Models
• Generative Data Assimilation of Sparse Weather Station Observations at Kilometer Scales
• Huge ensembles -- Part 1: Design of Ensemble Weather Forecasts Using Spherical Fourier Neural Operators
• Huge Ensembles Part 2: Properties of a Huge Ensemble of Hindcasts Generated with Spherical Fourier Neural Operators
• ClimSim-Online: A Large Multi-Scale Dataset and Framework for Hybrid Physics-ML Climate Emulation
• Adaptive Flow Matching for Resolving Small-Scale Physics
• Stable Machine-Learning Parameterization of Subgrid Processes in a Comprehensive Atmospheric Model Learned From Embedded Convection-Permitting Simulations
• Residual Corrective Diffusion Modeling for Km-Scale Atmospheric Downscaling
• Elucidated Rolling Diffusion Models for Probabilistic Weather Forecasting
• Coupled Ocean-Atmosphere Dynamics in a Machine Learning Earth System Model
• Generative Data Assimilation of Sparse Weather Station Observations at Kilometer Scales
• StormCast: Kilometer-Scale Convection Allowing Model Emulation Using Generative Diffusion Modeling