activity
20242026
most citedFengWu-GHR: Learning the Kilometer-scale Medium-range Global Weather Forecasting

7 citations · 8 across the 8 of their papers we have counts for

collaborators

9 papers

cs.LG2026

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…

cs.CV2026

Generative 3D Gaussian Splatting for Arbitrary-ResolutionAtmospheric Downscaling and Forecasting

Tao Han, Zhibin Wen, Zhenghao Chen +4

While AI-based numerical weather prediction (NWP) enables rapid forecasting, generating high-resolution outputs remains computationally demanding due to limited multi-scale adaptab…

cs.CV2026

EMFormer: Efficient Multi-Scale Transformer for Accumulative Context Weather Forecasting

Hao Chen, Tao Han, Jie Zhang +3

Long-term weather forecasting is critical for socioeconomic planning and disaster preparedness. While recent approaches employ finetuning to extend prediction horizons, they remain…

cs.CV2025

InfGen: A Resolution-Agnostic Paradigm for Scalable Image Synthesis

Tao Han, Wanghan Xu, Junchao Gong +4

Arbitrary resolution image generation provides a consistent visual experience across devices, having extensive applications for producers and consumers. Current diffusion models in…

cs.LG2025

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…

cs.LG2024

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…

cs.LG2024

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…

cs.LG2024★ 1 cited

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,…

cs.LG2024★ 7 cited

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…