ClimSight: Leveraging LLMs for Revolutionizing Climate Services

ClimSight is an innovative open-source climate information system that integrates large language models (LLMs) with geographical and climate data to provide climate information to everyone, everywhere. This description builds upon the original paper [1] by presenting the system’s recent developments and updated methodologies. By leveraging high-resolution data, including local conditions and climate projections, combined with retrieval-augmented generation systems (based on climate reports, scientific literature, and other sources), and an agent-based architecture, ClimSight addresses the limitations of general-purpose LLMs in climate data analysis, ensuring accurate, reliable, and reproducible outputs. This presentation details the enhanced methodologies employed in ClimSight to deliver climate assessments for specific locations and activities. The system utilizes the LangGraph and LangChain packages to manage agents and LLM calls, providing flexibility in selecting different LLM models, with current implementations relying on OpenAI’s models. The effectiveness of ClimSight is demonstrated through selected examples and evaluations, highlighting its potential to democratize access to localized climate information.

[1] Koldunov, N., Jung, T. Local climate services for all, courtesy of large language models. Commun Earth Environ 5, 13 (2024). https://doi.org/10.1038/s43247-023-01199-1