5 papers
OmniPMNet: Bridging discrete and gridded PM10 forecasts via omni-query neural processes
Shuangshuang He, Shuo Wang
Forecasting particulate matter (PM10) requires both station-scale accuracy and continuous spatial fields, especially during severe dust storms. Chemical transport models (CTMs) pro…
Physics-Guided Inductive Spatiotemporal Kriging for PM2.5 with Satellite Gradient Constraints
Shuo Wang, Mengfan Teng, Yun Cheng +8
High-resolution mapping of fine particulate matter (PM2.5) is a cornerstone of sustainable urbanism but remains critically hindered by the spatial sparsity of ground monitoring net…
FlowCast-ODE: Continuous Hourly Weather Forecasting with Dynamic Flow Matching and ODE Solver
Shuangshuang He, Yuanting Zhang, Hongli Liang +3
Data-driven hourly weather forecasting models often face the challenge of error accumulation in long-term predictions. The problem is exacerbated by non-physical temporal discontin…
CNCast: Leveraging 3D Swin Transformer and DiT for Enhanced Regional Weather Forecasting
Hongli Liang, Yuanting Zhang, Qingye Meng +2
This study introduces a cutting-edge regional weather forecasting model based on the SwinTransformer 3D architecture. This model is specifically designed to deliver precise hourly…
Skillful High-Resolution Ensemble Precipitation Forecasting with an Integrated Deep Learning Framework
Shuangshuang He, Hongli Liang, Yuanting Zhang +1
High-resolution precipitation forecasts are crucial for providing accurate weather prediction and supporting effective responses to extreme weather events. Traditional numerical mo…