48 citations · 54 across the 4 of their papers we have counts for
4 papers
Phys-Diff: A Physics-Inspired Latent Diffusion Model for Tropical Cyclone Forecasting
Lei Liu, Xiaoning Yu, Kang Chen +4
Tropical cyclone (TC) forecasting is critical for disaster warning and emergency response. Deep learning methods address computational challenges but often neglect physical relatio…
VQLTI: Long-Term Tropical Cyclone Intensity Forecasting with Physical Constraints
Xinyu Wang, Lei Liu, Kang Chen +3
Tropical cyclone (TC) intensity forecasting is crucial for early disaster warning and emergency decision-making. Numerous researchers have explored deep-learning methods to address…
Global Tropical Cyclone Intensity Forecasting with Multi-modal Multi-scale Causal Autoregressive Model
Xinyu Wang, Kang Chen, Lei Liu +3
Accurate forecasting of Tropical cyclone (TC) intensity is crucial for formulating disaster risk reduction strategies. Current methods predominantly rely on limited spatiotemporal…
FengWu: Pushing the Skillful Global Medium-range Weather Forecast beyond 10 Days Lead
Kang Chen, Tao Han, Junchao Gong +11
We present FengWu, an advanced data-driven global medium-range weather forecast system based on Artificial Intelligence (AI). Different from existing data-driven weather forecast m…