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Mike Pritchard

Mike Pritchard

Director of Climate Simulation Research

NVIDIA Research

Interests
  • Accelerating cloud resolving climate simulations with physics-informed machine learning
  • Reinforcement learning for climate model calibration
  • Limitations of autoregressive weather simulations trained on observational data
  • AI-assisted analysis of large high-resolution climate datasets

Latest

  • 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
  • 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
  • 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
  • Heavy-Tailed Diffusion Models
  • AI Chases the Storm: New NVIDIA Research Boosts Weather Prediction, Climate Simulation
  • ClimSim: A large multi-scale dataset for hybrid physics-ML climate emulation

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