5 papers
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…
XiChen: A global weather observation-to-forecast machine learning system via four-dimensional variational gradient-guided flexible assimilation
Wuxin Wang, Weicheng Ni, Lilan Huang +13
Machine Learning (ML) has shown great promise in revolutionizing weather forecasting, yet most ML systems still rely on initial conditions generated by Numerical Weather Prediction…
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…
ReconMOST: Multi-Layer Sea Temperature Reconstruction with Observations-Guided Diffusion
Yuanyi Song, Pumeng Lyu, Ben Fei +3
Accurate reconstruction of ocean is essential for reflecting global climate dynamics and supporting marine meteorological research. Conventional methods face challenges due to spar…
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…