Agentic Systems for Earth Science: From Tool-Augmented Assistants to Self-Evolving Scientific Agents

PhD Qualifying Examination


Title: "Agentic Systems for Earth Science: From Tool-Augmented Assistants to 
Self-Evolving Scientific Agents"

by

Mr. Chenyue LI


Abstract:

Earth science is entering a transition from model-centric AI to 
capability-centric agent systems. Earlier waves of AI improved local 
components of the scientific pipeline—forecasting, retrieval, language 
interaction, and multimodal understanding—but they rarely closed the 
end-to-end loop of scientific work. This paper reframes current progress 
through a four-level capability ladder: Level 1 tool-augmented assistants, 
Level 2 autonomous workflow agents, Level 3 research agents, and Level 4 
self-evolving scientific agents. We argue that this taxonomy should organize 
the field from the outset rather than appear only as a concluding outlook. We 
then reconstruct the co-evolution of AI and Earth-science technology, from 
physics-first numerical modeling and observation-constrained reanalysis to 
deep representation learning, Earth foundation models, reasoning-oriented 
LLMs, and emerging agentic systems. A central conceptual distinction is that 
Earth foundation models act as world models for spatiotemporal state 
evolution, whereas climate or geo LLMs act as language interfaces for 
knowledge, synthesis, and planning. Agent systems are the orchestration layer 
that connects these components to tools, data, and executable environments. 
Reviewing current systems shows that Earth science already has credible Level 
1 and early Level 2 examples, while Level 3 and Level 4 remain open 
frontiers. The key barriers are physical-model integration, domain skill 
infrastructure, memory and tacit knowledge accumulation, and evaluation 
frameworks that measure scientific usefulness rather than isolated model 
performance. We conclude that reasoning LLMs can serve as the thinking layer, 
Earth foundation models and physical simulators can serve as the world-model 
layer, and agent systems can provide the control loop for scientific action, 
validation, and long-horizon discovery.


Date:                   Monday, 21 April 2026

Time:                   2:00pm - 4:00pm

Venue:                  Room 2131B
                        Lift 22

Committee Members:      Dr. Binhang Yuan (Supervisor)
                        Dr. Ling Pan (Chairperson)
                        Dr. Mengqian Lu (CIVL)