Quantitative Reconstruction of Beijing’s Climate over 380 Years Ago

To address the scarcity of natural archives in historical climate reconstruction, this study utilized the late Ming Dynasty text Jiu Jing Yi Shi (Reminiscences of the Old Capital) as a primary data source to extract botanical and phenological information, aiming to quantitatively reconstruct climate parameters for the Beijing region circa 1644 CE. Using botanical textual research, 11 out of 20 recorded plant names were identified to the species level, 2 to the genus level, and 7 were classified as non-native species. Breaking from the traditional reliance solely on woody plants, we innovatively incorporated three herbaceous species into the coexistence analysis framework to enhance the accuracy of climate reconstruction. By comprehensively comparing four climate indicators—mean annual temperature (MAT), mean temperature of the coldest month (MTCM), mean temperature of the warmest month (MTWM), and annual precipitation (AP)—across three critical nodes (1368 CE, 1644 CE, and the present), this research revealed a “decline-then-rise” trajectory in Beijing’s temperature over the past 600 years, alongside corresponding variations in precipitation patterns. Results indicated that the cooling event in the Beijing region between 1368 CE and 1644 CE was synchronous with global cooling trends during the same period and demonstrated a climatic transition from maritime to continental characteristics in the region. This work not only expands the application of historical literature in paleoclimatology but also provides critical scientific evidence for understanding centennial-scale climate evolution in the East Asian monsoon region and predicting future climate trends.

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Publication Details

Journal
Atmosphere
Published
2026-06-30
DOI
https://doi.org/10.3390/atmos17070656
Primary Topic
Tree-ring climate responses
Type
article
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article

Quantitative Reconstruction of Beijing’s Climate over 380 Years Ago

Haiyan Bi, Haiming Liu
Atmosphere
Tree-ring climate responses
article

Quantitative Reconstruction of Beijing’s Climate over 380 Years Ago

Haiyan Bi, Haiming Liu
article en

Abstract

To address the scarcity of natural archives in historical climate reconstruction, this study utilized the late Ming Dynasty text Jiu Jing Yi Shi (Reminiscences of the Old Capital) as a primary data source to extract botanical and phenological information, aiming to quantitatively reconstruct climate parameters for the Beijing region circa 1644 CE. Using botanical textual research, 11 out of 20 recorded plant names were identified to the species level, 2 to the genus level, and 7 were classified as non-native species. Breaking from the traditional reliance solely on woody plants, we innovatively incorporated three herbaceous species into the coexistence analysis framework to enhance the accuracy of climate reconstruction. By comprehensively comparing four climate indicators—mean annual temperature (MAT), mean temperature of the coldest month (MTCM), mean temperature of the warmest month (MTWM), and annual precipitation (AP)—across three critical nodes (1368 CE, 1644 CE, and the present), this research revealed a “decline-then-rise” trajectory in Beijing’s temperature over the past 600 years, alongside corresponding variations in precipitation patterns. Results indicated that the cooling event in the Beijing region between 1368 CE and 1644 CE was synchronous with global cooling trends during the same period and demonstrated a climatic transition from maritime to continental characteristics in the region. This work not only expands the application of historical literature in paleoclimatology but also provides critical scientific evidence for understanding centennial-scale climate evolution in the East Asian monsoon region and predicting future climate trends.

AtmosphereVol. 17(7)
Beijing Museum of Natural History (CN)
Climate action
Openalex Percentile: Top 8%
Tree-ring climate responses
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Quantitative Reconstruction of Beijing’s Climate over 380 Years Ago — Haiyan Bi, Haiming Liu · Atmosphere (2026) | TGRS Research Map | TGRS