IGGCAS OpenIR  > 新生代地质与环境院重点实验室
Quantitative climatic reconstruction of the Last Glacial Maximum in China
Wu, Haibin1,2,3; Li, Qin1,4; Yu, Yanyan1; Sun, Aizhi3; Lin, Yating1,3; Jiang, Wenqi1,3; Luo, Yunli5
2019-08-01
Source PublicationSCIENCE CHINA-EARTH SCIENCES
ISSN1674-7313
Volume62Issue:8Pages:1269-1278
AbstractQuantitative paleoclimatic reconstruction is crucial for understanding the operation and evolution of the global climate system. For example, a quantitative paleoclimatic reconstruction for the Last Glacial Maximum (18 +/- 2 ka C-14, LGM) is fundamental to understanding the evolution of Earth's climate during the last glacial-interglacial cycle. Previous quantitative palaeoclimate reconstructions in China are generally based on statistical comparison of modern pollen assemblages and modern climate data. These methods are based on the premise that vegetation-climate interactions remain the same through time, and implicitly assume that the interactions are independent of changes in seasonality and atmospheric CO2 concentration. However, these assumptions may not always be valid, which may affect the reconstructions. Here, we present the results of a quantitative study of the LGM climate of China based on an improved inverse vegetation model which incorporates physiological processes combined with a new China Quaternary Pollen Database. The results indicate that during the LGM, mean annual temperature (ANNT), mean temperature of the coldest month (MTCO) and mean temperature of the warmest month in China were lower by similar to 5.6 +/- 0.8, similar to 11.0 +/- 1.6 and similar to 2.6 +/- 0.9 degrees C, respectively, compared to today, and that the changes in ANNT were mainly due to the decrease of MTCO. The ANNT decrease in southern China was similar to 5.5 +/- 0.5 degrees C. Mean annual precipitation was lower by similar to 46.3 +/- 17.8 mm compared to today and was especially low in northern China (similar to 51.2 +/- 21.4 mm) due to the decrease in summer rainfall. Comparison of our results with recent outputs from paleoclimatic modelling reveals that while the latter are broadly consistent with our estimated changes in mean annual climatic parameters, there are substantial differences in the seasonal climatic parameters. Our results highlight the crucial importance of developing seasonal simulation on paleoclimatic models, as well as the need to improve the quality of paleoclimatic reconstructions based on proxy records from geological archives.
KeywordQuantitative paleoclimatic reconstruction Inverse vegetation model Biome Seasonal climate changes Atmospheric CO2 concentration
DOI10.1007/s11430-018-9338-3
Funding OrganizationStrategic Priority Research Program of the Chinese Academy of Sciences ; Strategic Priority Research Program of the Chinese Academy of Sciences ; National Key Research and Development Program of China ; National Key Research and Development Program of China ; National Natural Science Foundation of China ; National Natural Science Foundation of China ; Strategic Priority Research Program of the Chinese Academy of Sciences ; Strategic Priority Research Program of the Chinese Academy of Sciences ; National Key Research and Development Program of China ; National Key Research and Development Program of China ; National Natural Science Foundation of China ; National Natural Science Foundation of China ; Strategic Priority Research Program of the Chinese Academy of Sciences ; Strategic Priority Research Program of the Chinese Academy of Sciences ; National Key Research and Development Program of China ; National Key Research and Development Program of China ; National Natural Science Foundation of China ; National Natural Science Foundation of China ; Strategic Priority Research Program of the Chinese Academy of Sciences ; Strategic Priority Research Program of the Chinese Academy of Sciences ; National Key Research and Development Program of China ; National Key Research and Development Program of China ; National Natural Science Foundation of China ; National Natural Science Foundation of China
WOS KeywordPOLLEN DATA ; VEGETATION ; MODEL ; MONSOON ; SIMULATIONS ; MIDHOLOCENE ; VARIABILITY
Language英语
Funding ProjectStrategic Priority Research Program of the Chinese Academy of Sciences[XDA05120700] ; Strategic Priority Research Program of the Chinese Academy of Sciences[XDA13010106] ; National Key Research and Development Program of China[2016YFA0600504] ; National Natural Science Foundation of China[41572165] ; National Natural Science Foundation of China[41430531] ; National Natural Science Foundation of China[41125011] ; National Natural Science Foundation of China[41472319]
Funding OrganizationStrategic Priority Research Program of the Chinese Academy of Sciences ; Strategic Priority Research Program of the Chinese Academy of Sciences ; National Key Research and Development Program of China ; National Key Research and Development Program of China ; National Natural Science Foundation of China ; National Natural Science Foundation of China ; Strategic Priority Research Program of the Chinese Academy of Sciences ; Strategic Priority Research Program of the Chinese Academy of Sciences ; National Key Research and Development Program of China ; National Key Research and Development Program of China ; National Natural Science Foundation of China ; National Natural Science Foundation of China ; Strategic Priority Research Program of the Chinese Academy of Sciences ; Strategic Priority Research Program of the Chinese Academy of Sciences ; National Key Research and Development Program of China ; National Key Research and Development Program of China ; National Natural Science Foundation of China ; National Natural Science Foundation of China ; Strategic Priority Research Program of the Chinese Academy of Sciences ; Strategic Priority Research Program of the Chinese Academy of Sciences ; National Key Research and Development Program of China ; National Key Research and Development Program of China ; National Natural Science Foundation of China ; National Natural Science Foundation of China
WOS Research AreaGeology
WOS SubjectGeosciences, Multidisciplinary
WOS IDWOS:000472529900006
PublisherSCIENCE PRESS
Citation statistics
Document Type期刊论文
Identifierhttp://ir.iggcas.ac.cn/handle/132A11/92481
Collection新生代地质与环境院重点实验室
Corresponding AuthorWu, Haibin
Affiliation1.Chinese Acad Sci, Inst Geol & Geophys, Key Lab Cenozo Geol & Environm, Beijing 100029, Peoples R China
2.CAS Ctr Excellence Life & Paleoenvironm, Beijing 100044, Peoples R China
3.Univ Chinese Acad Sci, Beijing 100049, Peoples R China
4.CAS Ctr Excellence Tibetan Plateau Earth Sci, Beijing 100101, Peoples R China
5.Chinese Acad Sci, Inst Bot, Beijing 100093, Peoples R China
Recommended Citation
GB/T 7714
Wu, Haibin,Li, Qin,Yu, Yanyan,et al. Quantitative climatic reconstruction of the Last Glacial Maximum in China[J]. SCIENCE CHINA-EARTH SCIENCES,2019,62(8):1269-1278.
APA Wu, Haibin.,Li, Qin.,Yu, Yanyan.,Sun, Aizhi.,Lin, Yating.,...&Luo, Yunli.(2019).Quantitative climatic reconstruction of the Last Glacial Maximum in China.SCIENCE CHINA-EARTH SCIENCES,62(8),1269-1278.
MLA Wu, Haibin,et al."Quantitative climatic reconstruction of the Last Glacial Maximum in China".SCIENCE CHINA-EARTH SCIENCES 62.8(2019):1269-1278.
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