Latest

• DLESyM-Ocean: A Deep Learning Probabilistic Global Model for Simulating Present-Day Upper Ocean and Sea Ice
• Anomalous Diffusion of Tropical Cyclones Observed in Huge Ensembles of Hindcasts
• Scaling Storm-Resolving Atmospheric AI Simulation to the Entire Planet
• Crowdsourcing the Frontier: Advancing Hybrid Physics-ML Climate Simulation via a $50,000 Kaggle Competition
• ShardTensor: Domain Parallelism for Scientific Machine Learning
• Towards Accurate Extreme Event Likelihoods from Diffusion Model Climate Emulators
• Surface Temperature Extremes Produced by Huge Machine Learning Hindcasts of Summer 2023
• Data-Driven Integration Kernels for Interpretable Nonlocal Operator Learning
• Examining Fast Radiatively Driven Responses Using Machine-Learning Weather Emulators
• NVIDIA Launches Earth-2 Family of Open Models — the World's First Fully Open, Accelerated Set of Models and Tools for AI Weather
• 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
• Subseasonal forecasting and MJO teleconnections in machine learning weather prediction models
• 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
• Predict Extreme Weather Events in Minutes Without a Supercomputer
• ClimSim-Online: A Large Multi-Scale Dataset and Framework for Hybrid Physics-ML Climate Emulation
• Adaptive Flow Matching for Resolving Small-Scale Physics
• Climate In A Bottle: Towards a Generative Foundation Model for the Kilometer-Scale Global Atmosphere
• FourCastNet 3: A Geometric Approach to Probabilistic Machine-Learning Weather Forecasting at Scale
• Stable Machine-Learning Parameterization of Subgrid Processes in a Comprehensive Atmospheric Model Learned From Embedded Convection-Permitting Simulations
• A Practical Probabilistic Benchmark for AI Weather Models
• Heavy-Tailed Diffusion Models
• Navigating the Noise: Bringing Clarity to ML Parameterization Design with O(100) Ensembles
• Simulating Atmospheric Processes in Earth System Models and Quantifying Uncertainties With Deep Learning Multi-Member and Stochastic Parameterizations
• Application of the AI2 Climate Emulator to E3SMv2's Global Atmosphere Model, With a Focus on Precipitation Fidelity
• AI Chases the Storm: New NVIDIA Research Boosts Weather Prediction, Climate Simulation
• Pushing the Frontiers in Climate Modelling and Analysis with Machine Learning
• Coupled Ocean-Atmosphere Dynamics in a Machine Learning Earth System Model
• ClimSim: A large multi-scale dataset for hybrid physics-ML climate emulation