[2603.27738] TianJi:An autonomous AI meteorologist for discovering physical mechanisms in atmospheric science

Computer Science > Artificial Intelligence arXiv:2603.27738 (cs) [Submitted on 29 Mar 2026] Title:TianJi:An autonomous AI meteorologist for discovering physical mechanisms in atmospheric science Authors:Kaikai Zhang, Xiang Wang, Haoluo Zhao, Nan Chen, Mengyang Yu Jing-Jia Luo, Tao Song, Fan Meng View a PDF of the paper titled TianJi:An autonomous AI meteorologist for discovering physical mechanisms in atmospheric science, by Kaikai Zhang and 6 other authors View PDF HTML (experimental) Abstract:Artificial intelligence (AI) has achieved breakthroughs comparable to traditional numerical models in data-driven weather forecasting, yet it remains essentially statistical fitting and struggles to uncover the physical causal mechanisms of the atmosphere. Physics-oriented mechanism research still heavily relies on domain knowledge and cumbersome engineering operations of human scientists, becoming a bottleneck restricting the efficiency of Earth system science exploration. Here, we propose TianJi - the first "AI meteorologist" system capable of autonomously driving complex numerical models to verify physical mechanisms. Powered by a large language model-driven multi-agent architecture, TianJi can autonomously conduct literature research and generate scientific hypotheses. We further decouple scientific research into cognitive planning and engineering execution: the meta-planner interprets hypotheses and devises experimental roadmaps, while a cohort of specialized worker agents coll...