STATISTICS Seminars Series: Chuang Zhang

Topic The Trends of AI for Meteorology

Abstract The application of AI in meteorology has become a crucial development trend. AI technologies, such as deep learning and large-scale foundation models, are rebuilding the value chain of meteorological data, covering aspects from data acquisition, cleaning, and fusion to modeling and result expression. For example, Google's AI-powered weather forecasting model simplifies meteorological forecasts, improving its efficiency and accuracy. In China, the meteorological department has developed a series of AI-based meteorological application models, significantly enhancing the level of accurate forecasting and business efficiency. However, current AI models in meteorology also have limitations. They rely heavily on historical data, and there are concerns about their effectiveness in predicting future weather patterns that may differ significantly from past patterns. Additionally, the interpretability of AI models is limited, and they struggle to identify causal relationships. The report will focus on introducing the trends in AI-empowered meteorological forecasting and the challenges associated with them. It will integrate the trend of fusion between traditional numerical models and AI, with an emphasis on describing the key technological innovations that need to be breakthroughs in the future.