NeuralGCM: Physics-ML Hybrid Climate Model for Long-Range Global Precipitation Simulation
Автор: CosmoX
Загружено: 2026-01-21
Просмотров: 1
Описание:
🌍 In this video, we break down Google Research’s NeuralGCM and how it improves
long-range global precipitation simulation by combining physics-based modeling with AI.
📌 What you’ll learn
🧠 What NeuralGCM is: a hybrid ML + physics general circulation model (GCM)
🌧️ Why precipitation is one of the hardest variables to model in climate systems
🛰️ How training on NASA satellite precipitation observations changes the game
📈 Key improvements in extremes, distribution bias, and the diurnal precipitation cycle
⚡ Efficiency vs traditional climate models and numerical weather prediction (NWP)
🔍 Real-world impacts: flood risk modeling, climate adaptation, and sustainability applications
🎯 Recommended for
🌦️ Anyone tracking the latest Weather AI / Climate AI progress
🧪 Researchers interested in physics-informed ML and differentiable climate modeling
📊 Engineers working on precipitation forecasting, extreme event simulation, or climate risk
#AI #NeuralGCM #ClimateAI #WeatherForecasting #Precipitation #PhysicsBasedModeling #MachineLearning #GoogleResearch #ClimateTech
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