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Explore how artificial intelligence revolutionizes weather prediction across multiple spatial and temporal scales in this 54-minute conference talk. Learn about the integration of machine learning techniques with traditional meteorological models to enhance forecasting accuracy from local to global scales. Discover the latest developments in AI-driven weather prediction systems, including deep learning approaches, neural network architectures, and data-driven models that are transforming operational meteorology. Examine the challenges and opportunities in applying artificial intelligence to complex atmospheric processes, from short-term local weather events to long-term climate patterns. Understand how AI methods can improve parameterization of physical processes, reduce computational costs, and provide more accurate predictions across different scales of weather phenomena. Gain insights into the current state of AI weather prediction systems being adopted by national meteorological agencies and their potential for future operational use.
Syllabus
AI Weather Prediction Across Scales by Sue Ellen Haupt
Taught by
International Centre for Theoretical Sciences