Evidence from the Lacustrine Sediments of Lop-Nur Lake, Northwest China for the Younger Dryas Event
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摘要: 通过对罗布泊CK-2钻孔湖相沉积物磁化率、粒度、碳酸盐和有机质含量的测定以及地球化学元素的多元统计分析, 探讨了我国西北极端干旱区域的环境对全球气候变化的响应.结果显示各代用指标均一致揭示了发生在12.8~11.6kaBP间非常明显的低温期, 且降温幅度大, 变化迅速.这次冷事件在时间坐标以及发生特点上都与格陵兰冰心记录的末次冰消期中的新仙女木事件相对应, 为新仙女木事件的全球性特征提供了新的证据.这说明在我国新疆的极端干旱区, 其气候与环境的变化也与北半球高纬度地区有着密切的联系; 由主成分分析结果, 揭示了我国西北地区的西风气候区有别于东南季风气候区的水热配置特点, 即冷期湿润, 暖期干旱, 并提出了该事件信号从北大西洋传送到罗布泊地区的潜在机制.Abstract: The environmental proxies of the susceptibility, particle size, and the contents of carbonate and organic carbon in the lacustrine sediments of the CK-2 core from Lop-Nur Lake, Xinjiang, Northwest China are determined in this study.The core section corresponds to the 0.94-5.50 m and 9-14 kaBP.The reconstructed records in Xinjiang, NW China fully demonstrate that the Younger Dryas event occurred within 12.8-11.6 ka BP synchronously with that record in Greenland ice core, and its climate appeared to be cool and humid.These results suggest the rapid response of westerly climate system in the NW China to the climate variability in northern high latitudes in short time.A mechanism involving immigration of westerly winds and the intensity change of the westerly is tentatively proposed to account for this synchronicity.
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图 1 罗布泊地理位置及周边地区地质简图
1.前寒武纪地层; 2.古生代地层; 3.新生代盆地; 4.河流; 5.湖泊; 6.古湖岸线; 7.钻孔位置
Fig. 1. The location of Lop-Nur Lake, Xinjiang, Northwest China and the circumjacent regions
图 2 CK-2孔沉积剖面(部分) 及深度-年龄对应关系示意图
1.粉砂含粗粒石盐; 2.粉砂含中粒石盐; 3.粉砂隔水层; 4.黑色粉砂含石膏; 5.粉砂含细粒石膏; 6.粉砂含中粒石膏; 7.粉砂含粒石膏; 8.U-Th年龄
Fig. 2. Detailed stratigraphic column and age/depth correlation of CK-2 core. Triangle represents the result of U/Th dating
图 3 K-2孔磁化率、粒度、碳酸盐和有机质含量的变化序列
Fig. 3. The susceptibility/granularity/content of organic matter and carbonate sequences of CK-2 core
图 4 罗布泊地区14~9 kaBP古温度指数序列与Greenland冰心(B) 氧同位素记录的对比
Fig. 4. Comparison of the paleo-temperature index sequence of Lop-Nur region and isotope record of Greenland ice core during 14-9 ka
表 1 统计分析结果中主成分1和2与各金属元素之间的相关系数
Table 1. The correlation coefficients between the first and second principal components of multivariate statistical analysis and the geochemistry elements
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