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October 16, 20253 citationsOpen Access

EarthLink: A Self-Evolving AI Agent for Climate Science

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ZGZijie GuoJWJiong WangXYXiaoyu Yue

Key Points

  • EarthLink improves analytical efficiency in climate science by automating the entire research workflow.
  • In evaluations, EarthLink's analyses were rated comparable to a human junior researcher's performance.
  • This AI agent integrates a feedback loop, allowing it to learn from interactions and refine its outputs continuously.
  • Accessible online, EarthLink promotes strategic oversight over manual tasks, fostering innovative hypothesis generation.

Abstract

Modern Earth science is at an inflection point. The vast, fragmented, and complex nature of Earth system data, coupled with increasingly sophisticated analytical demands, creates a significant bottleneck for rapid scientific discovery. Here we introduce EarthLink, the first AI agent designed as an interactive copilot for Earth scientists. It automates the end-to-end research workflow, from planning and code generation to multi-scenario analysis. Unlike static diagnostic tools, EarthLink can learn from user interaction, continuously refining its capabilities through a dynamic feedback loop. We validated its performance on a number of core scientific tasks of climate change, ranging from model-observation comparisons to the diagnosis of complex phenomena. In a multi-expert evaluation, EarthLink produced scientifically sound analyses and demonstrated an analytical competency that was rated as comparable to specific aspects of a human junior researcher's workflow. Additionally, its transparent, auditable workflows and natural language interface empower scientists to shift from laborious manual execution to strategic oversight and hypothesis generation. EarthLink marks a pivotal step towards an efficient, trustworthy, and collaborative paradigm for Earth system research in an era of accelerating global change. The system is accessible at our website https://earthlink.intern-ai.org.cn.

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Cite This Study

Guo et al. (2025) studied this question.

synapsesocial.com/papers/68f163c79903599108abcdc1https://doi.org/10.48550/arxiv.2507.17311
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