NJUHML is affiliated with the School of Atmospheric Sciences, Nanjing University,
under the leadership of Professor Huiling Yuan.
Physical Sciences • AI for Meteo • Applications
NJUHML focuses on AI-driven weather and climate modeling, including global and regional prediction systems, nowcasting, data assimilation, and interdisciplinary applications.
For more information, please visit our 🌐 official website.
- NJU-Earth — Global AI model (0.25°)
- Baguan HR — Global high-resolution AI model (0.1°)
- RegionalCast — Regional surface variable forecasts (0.05°)
- RainCast — Regional high-resolution precipitation forecasts (0.05°)
- NJU-Mars — Global AI model for Mars (5°)
- GAP — Generative assimilation and prediction for weather and climate (0.25°)
- CM4Nowcast — A customized multi-scale deep learning framework
- WADEPre — Wavelet-based decomposition model
- Downscaling — High-resolution weather and climate products
- PrecipFusionNet / pyCBC — Precipitation post-processing
- SMMerge — China’s 1 km daily surface soil moisture fusion dataset
- MeteorIR — Weather dataset based on multimodal large language models (MLLMs)
- BaguanCyclone — Tropical cyclone track correction
- 🌐 Website: NJUHML Official Website
- 🏫 Affiliation: School of Atmospheric Sciences, Nanjing University
- 👩🏫 PI: Professor Huiling Yuan
Welcome to explore our repositories and research projects.
