# AI Decodes Historical Chinese Archives to Reveal Lost Climate History

arXiv: https://arxiv.org/abs/2601.22458 · HTML: https://mlsanity.com/paper/2601.22458/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- First posted on arXiv 30 Jan 2026.

## Abstract (arXiv)

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~no 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.