Climatic Change

, Volume 131, Issue 4, pp 663–676 | Cite as

A multi-proxy reconstruction of spatial and temporal variations in Asian summer temperatures over the last millennium

  • Feng Shi
  • Quansheng GeEmail author
  • Bao Yang
  • Jianping Li
  • Fengmei Yang
  • Fredrik Charpentier Ljungqvist
  • Olga Solomina
  • Takeshi Nakatsuka
  • Ninglian Wang
  • Sen Zhao
  • Chenxi Xu
  • Keyan Fang
  • Masaki Sano
  • Guoqiang Chu
  • Zexin Fan
  • Narayan P. Gaire
  • Muhammad Usama Zafar


To investigate climate variability in Asia during the last millennium, the spatial and temporal evolution of summer (June–July–August; JJA) temperature in eastern and south-central Asia is reconstructed using multi-proxy records and the regularized expectation maximization (RegEM) algorithm with truncated total least squares (TTLS), under a point-by-point regression (PPR) framework. The temperature index reconstructions show that the late 20th century was the warmest period in Asia over the past millennium. The temperature field reconstructions illustrate that temperatures in central, eastern, and southern China during the 11th and 13th centuries, and in western Asia during the 12th century, were significantly higher than those in other regions, and comparable to levels in the 20th century. Except for the most recent warming, all identified warm events showed distinct regional expressions and none were uniform over the entire reconstruction area. The main finding of the study is that spatial temperature patterns have, on centennial time-scales, varied greatly over the last millennium. Moreover, seven climate model simulations, from the Coupled Model Intercomparison Project Phase 5 (CMIP5), over the same region of Asia, are all consistent with the temperature index reconstruction at the 99 % confidence level. Only spatial temperature patterns extracted as the first empirical orthogonal function (EOF) from the GISS-E2-R and MPI-ESM-P model simulations are significant and consistent with the temperature field reconstruction over the past millennium in Asia at the 90 % confidence level. This indicates that both the reconstruction and the simulations depict the temporal climate variability well over the past millennium. However, the spatial simulation or reconstruction capability of climate variability over the past millennium could be still limited. For reconstruction, some grid points do not pass validation tests and reveal the need for more proxies with high temporal resolution, accurate dating, and sensitive temperature signals, especially in central Asia and before AD 1400.


Empirical Orthogonal Function Warm Period Temperature Reconstruction Instrumental Data Proxy Record 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.



Version B of the reconstruction is a contribution to the PAGES Asia2k working group. We are indebted to Lucien von Gunten for helpful comments and assistance, and thank Edward R. Cook, Brendan Buckley, Kevin Anchukaitis, Paul J. Krusic, Chun Qin, Xuemei Shao, Jingyun Zheng, Hemant Borgaonkar, Katsuhiko Kimura, Masumi Zaiki, Koh Yasue, Achim Bräuning, Jiangfeng Li, Yujiang Yuan, Hongbing Liu, Yu Liu, Qibing Zhang, Jinbao Li, Jianfeng Peng, Xiaohua Gou, Haifeng Zhu, Shaowu Wang, Deer Zhang, Jonathan Palmer, Paul Sheppard, Margit Schwikowski, Tatyana Papina and other scientists who have contributed their proxy data for the study region to the publicly available database. The study was jointly funded by the CAS Strategic Priority Research Program Grant (XDA05080800; XDB03020500), and the National Natural Science Foundation of China (41301220). Feng Shi was supported by China Meteorological Administration Drought Research (IAM201213) and West Light Program for Talent Cultivation of Chinese Academy of Sciences.

Supplementary material

10584_2015_1413_MOESM1_ESM.doc (2.9 mb)
ESM 1 (DOC 2.93 mb)


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Copyright information

© Springer Science+Business Media Dordrecht 2015

Authors and Affiliations

  • Feng Shi
    • 1
  • Quansheng Ge
    • 2
    Email author
  • Bao Yang
    • 3
  • Jianping Li
    • 4
    • 5
  • Fengmei Yang
    • 6
  • Fredrik Charpentier Ljungqvist
    • 7
    • 8
  • Olga Solomina
    • 9
    • 10
  • Takeshi Nakatsuka
    • 11
  • Ninglian Wang
    • 3
  • Sen Zhao
    • 12
  • Chenxi Xu
    • 11
  • Keyan Fang
    • 13
  • Masaki Sano
    • 11
  • Guoqiang Chu
    • 1
  • Zexin Fan
    • 14
  • Narayan P. Gaire
    • 15
    • 16
  • Muhammad Usama Zafar
    • 17
  1. 1.Key Laboratory of Cenozoic Geology and Environment, Institute of Geology and GeophysicsChinese Academy of SciencesBeijingChina
  2. 2.Institute of Geographic Sciences and Natural Resources ResearchChinese Academy of SciencesBeijingChina
  3. 3.Cold and Arid Regions Environmental and Engineering Research InstituteChinese Academy of SciencesLanzhouChina
  4. 4.College of Global Change and Earth System ScienceBeijing Normal UniversityBeijingChina
  5. 5.Joint Center for Global Change StudiesBeijingChina
  6. 6.China Meteorological Administration Training CentreBeijingChina
  7. 7.Department of HistoryStockholm UniversityStockholmSweden
  8. 8.Bolin Centre for Climate ResearchStockholm UniversityStockholmSweden
  9. 9.Institute of GeographyRussian Academy of SciencesMoscowRussia
  10. 10.Tomsk State UniversityTomskRussia
  11. 11.Research Institute for Humanity and NatureKyotoJapan
  12. 12.State Key Laboratory of Numerical Modeling for Atmospheric Sciences and Geophysical Fluid Dynamics, Institute of Atmospheric PhysicsChinese Academy of SciencesBeijingChina
  13. 13.Key Laboratory of Humid Subtropical Eco-Geographical Process (Ministry of Education)Fujian Normal UniversityFuzhouChina
  14. 14.Xishuangbanna Tropical Botanical GardenChinese Academy of SciencesYunnanChina
  15. 15.Faculty of ScienceNepal Academy of Science and TechnologyLalitpurNepal
  16. 16.Central Department of Environmental ScienceTribhuvan UniversityKathmanduNepal
  17. 17.Laboratory of Dendrochronology and Plant EcologyFederal Urdu UniversityKarachiPakistan

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