7 papers
Earth-o1: A Grid-free Observation-native Atmospheric World Model
Junchao Gong, Kaiyi Xu, Wangxu Wei +22
Despite the unprecedented volume of multimodal data provided by modern Earth observation systems, our ability to model atmospheric dynamics remains constrained. Traditional modelin…
IceBench-S2S: A Benchmark of Deep Learning for Challenging Subseasonal-to-Seasonal Daily Arctic Sea Ice Forecasting in Deep Latent Space
Jingyi Xu, Shengnan Wang, Weidong Yang +3
Arctic sea ice plays a critical role in regulating Earth's climate system, significantly influencing polar ecological stability and human activities in coastal regions. Recent adva…
MODS: Multi-source Observations Conditional Diffusion Model for Meteorological State Downscaling
Siwei Tu, Jingyi Xu, Weidong Yang +2
Accurate acquisition of high-resolution surface meteorological conditions is critical for forecasting and simulating meteorological variables. Directly applying spatial interpolati…
Satellite Observations Guided Diffusion Model for Accurate Meteorological States at Arbitrary Resolution
Siwei Tu, Ben Fei, Weidong Yang +7
Accurate acquisition of surface meteorological conditions at arbitrary locations holds significant importance for weather forecasting and climate simulation. Due to the fact that m…
Taming Generative Diffusion Prior for Universal Blind Image Restoration
Siwei Tu, Weidong Yang, Ben Fei
Diffusion models have been widely utilized for image restoration. However, previous blind image restoration methods still need to assume the type of degradation model while leaving…
IceDiff: High Resolution and High-Quality Sea Ice Forecasting with Generative Diffusion Prior
Jingyi Xu, Siwei Tu, Weidong Yang +6
Variation of Arctic sea ice has significant impacts on polar ecosystems, transporting routes, coastal communities, and global climate. Tracing the change of sea ice at a finer scal…