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arXiv · 2601.22458

AI Decodes Historical Chinese Archives to Reveal Lost Climate History

Sida He·Lingxi Xie·Xiaopeng Zhang·Qi Tian
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Abstract

Historical archives contain qualitative descriptions of climate events, yet converting these into quantitative records has remained a fundamental challenge. Here we introduce a paradigm shift: a generative AI framework that inverts the logic of historical chroniclers by inferring the quantitative climate patterns associated with documented events. Applied to historical Chinese archives, it produces the sub-annual precipitation reconstruction for southeastern China over the period 1368-1911 AD. Our reconstruction not only quantifies iconic extremes like the Ming Dynasty's Great Drought but also, crucially, maps the full spatial and seasonal structure of El Ni$ñ$o influence on precipitation in this region over five centuries, revealing dynamics inaccessible in shorter modern records. Our methodology and high-resolution climate dataset are directly applicable to climate science and have broader implications for the historical and social sciences.

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Sida He, Lingxi Xie, Xiaopeng Zhang, Qi Tian. 2026-01-30. AI Decodes Historical Chinese Archives to Reveal Lost Climate History. https://arxiv.org/abs/2601.22458

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