7 citations · 8 across the 8 of their papers we have counts for
6 papers · 1 filter
RealBench: Benchmarking Data-Driven Numerical Weather Forecasting Under Operational Conditions and Extreme Event Challenges
Ruize Li, Zhibin Wen, Tao Han +5
Accurate evaluation of weather forecasting models is critical for their reliable deployment in real-world applications. However, existing benchmarks predominantly rely on reanalysi…
STCast: Adaptive Boundary Alignment for Global and Regional Weather Forecasting
Hao Chen, Tao Han, Jie Zhang +2
To gain finer regional forecasts, many works have explored the regional integration from the global atmosphere, e.g., by solving boundary equations in physics-based methods or crop…
VA-MoE: Variables-Adaptive Mixture of Experts for Incremental Weather Forecasting
Hao Chen, Han Tao, Guo Song +4
This paper presents Variables Adaptive Mixture of Experts (VAMoE), a novel framework for incremental weather forecasting that dynamically adapts to evolving spatiotemporal patterns…
Benchmarking Physics-Informed Time-Series Models for Operational Global Station Weather Forecasting
Tao Han, Zhibin Wen, Zhenghao Chen +3
The development of Time-Series Forecasting (TSF) models is often constrained by the lack of comprehensive datasets, especially in Global Station Weather Forecasting (GSWF), where e…
CRA5: Extreme Compression of ERA5 for Portable Global Climate and Weather Research via an Efficient Variational Transformer
Tao Han, Zhenghao Chen, Song Guo +2
The advent of data-driven weather forecasting models, which learn from hundreds of terabytes (TB) of reanalysis data, has significantly advanced forecasting capabilities. However,…
FengWu-GHR: Learning the Kilometer-scale Medium-range Global Weather Forecasting
Tao Han, Song Guo, Fenghua Ling +7
Kilometer-scale modeling of global atmosphere dynamics enables fine-grained weather forecasting and decreases the risk of disastrous weather and climate activity. Therefore, buildi…