河南空管分局组织开展数值预报AI气象大模型专题培训

Core Insights - The training organized by the Henan Air Traffic Control Bureau focuses on the development and application of AI meteorological models to enhance forecasting capabilities [1][2] - AI meteorological models offer advantages over traditional models, including high computational efficiency, minimal resource consumption, and strong nonlinear simulation capabilities [1] - The training also highlighted the limitations of current AI models in weather forecasting, such as weak interpretability and insufficient generalization ability [1] Group 1 - The training aims to help forecasters understand AI meteorological models better and provide stronger technical support for future forecasting work [1] - AI models can quickly generate high-precision weather forecast products, improving forecasting accuracy [1][2] - The integration of "numerical forecasting + AI" is expected to enhance the precision and reliability of numerical models in simulating atmospheric phenomena [1] Group 2 - Forecasters are required to acquire new technical knowledge and learn to collaborate with AI to maximize the advantages of AI models [2] - The training opens new technological avenues for forecasters at the Henan Air Traffic Control Bureau, providing them with a clearer understanding of future meteorological forecasting [2] - The bureau plans to continue monitoring developments in meteorological technology and conduct related training to promote the widespread application of new technologies in operations [2]