BiXiao：一种使用非连续网格的基于AI的大气环境预报模型
BiXiao: An AI-Based Atmospheric Environment Forecasting Model Using Discontinuous Grids
AI总结：
本文提出了一种新型非连续网格AI大气环境预报模型BiXiao，通过耦合气象与环境子模型利用站点数据生成预报，在京津冀地区实现了高效高精度的72小时六种主要污染物预报，为业务化应用提供了创新技术支撑。
AI中文摘要：
目前，基于数值模型的大气环境预报技术已趋于成熟，但传统数值预报方法难以平衡计算成本与预报精度，面临发展瓶颈。人工智能（AI）的最新进展为天气预报提供了新方案。然而，现有大多数AI模型不具备大气环境预报能力，而具备相关功能的模型仍受限于依赖网格的数据需求，从而无法提供具备业务可行性的城市尺度大气环境预报。在此，我们介绍“BiXiao”，一种用于大气环境预报的新型非连续网格AI模型。“BiXiao”耦合了气象与环境子模型，利用特定站点的观测数据生成预报，在30秒内完成了京津冀地区所有重点城市六种主要污染物的72小时预报。在对比实验中，“BiXiao”模型在计算效率和预报精度上均优于主流数值模型。它在业务化72小时预报方面超越了CAMS，并在重污染个例预报中超过了WRF-Chem的性能。“BiXiao”展现出全国范围应用的潜力，为中国大气环境预报业务提供了创新的技术支撑和新视角。
英文摘要：
Currently, the technique of numerical model-based atmospheric environment forecasting has becoming mature, yet traditional numerical prediction methods struggle to balance computational costs and forecast accuracy, facing developmental bottlenecks. Recent advancements in artificial intelligence (AI) offer new solutions for weather prediction. However, most existing AI models do not have atmospheric environmental forecasting capabilities, while those with related functionalities remain constrained by grid-dependent data requirements, thus unable to deliver operationally feasible city-scale atmospheric environment forecasts. Here we introduce 'BiXiao', a novel discontinuous-grid AI model for atmospheric environment forecasting. 'BiXiao' couples meteorological and environmental sub-models to generate predictions using site-specific observational data, completing 72-hour forecasts for six major pollutants across all key cities in the Beijing-Tianjin-Hebei region within 30 seconds. In the comparative experiments, the 'BiXiao' model outperforms mainstream numerical models in both computational efficiency and forecast accuracy. It surpasses CAMS with respect of operational 72-hour forecasting and exceeds WRF-Chem's performance in heavy pollution case predictions. The 'BiXiao' shows potential for nationwide application, providing innovative technical support and new perspectives for China's atmospheric environment forecasting operations.
