Real-Time Long Horizon Air Quality Forecasting via Group-Relative Policy Optimization

ArXi:2511.22169v2 Announce Type: replace-cross Accurate long horizon forecasting of particulate matter (PM) concentration fields is essential for operational public health decisions. However, achieving reliable forecasts remains challenging in regions with complex terrain and strong atmospheric dynamics such as East Asia. While foundation models such as Aurora offer global generality, they often miss region-specific dynamics and rely on non-real-time inputs, limiting their practical utility for localized warning systems.