3 citations · 3 across the 3 of their papers we have counts for
5 papers
Transforming Weather Data from Pixel to Latent Space
Sijie Zhao, Feng Liu, Xueliang Zhang +7
The increasing impact of climate change and extreme weather events has spurred growing interest in deep learning for weather research. However, existing studies often rely on weath…
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…
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…
FengWu-W2S: A deep learning model for seamless weather-to-subseasonal forecast of global atmosphere
Fenghua Ling, Kang Chen, Jiye Wu +4
Seamless forecasting that produces warning information at continuum timescales based on only one system is a long-standing pursuit for weather-climate service. While the rapid adva…
WeatherFormer: Empowering Global Numerical Weather Forecasting with Space-Time Transformer
Junchao Gong, Tao Han, Kang Chen +1
Numerical Weather Prediction (NWP) system is an infrastructure that exerts considerable impacts on modern society.Traditional NWP system, however, resolves it by solving complex pa…