A computer model integrating conventional weather-forecasting technology with machine learning outperforms other AI-based tools, offering accurate ensemble weather forecasts, faster and less energy-intensive than traditional models, detailed climate trend predictions.
Machine learning leverages historical weather data to create more reliable models, contrasting with the computing power-demanding General Circulation Models (GCMs). Models like Pangu-Weather and GraphCast provide accurate deterministic forecasting but fall short in ensemble forecasts and long-term climate predictions.
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