地球科学进展 ›› 2023, Vol. 38 ›› Issue (6): 619 -630. doi: 10.11867/j.issn.1001-8166.2023.031

研究论文 上一篇    下一篇

张宇翱 1 , 2( ), 张旭 1( ), 昝金波 1, 方小敏 1   
  1. 1.中国科学院青藏高原研究所,北京 100101
    2.中国科学院大学,北京 101408
  • 收稿日期:2023-04-04 修回日期:2023-05-04 出版日期:2023-06-10
  • 通讯作者: 张旭 E-mail:zhangyuao20@itpcas.ac.cn;xu.zhang@itpcas.ac.cn
  • 基金资助:

Investigating Uncertainty of Simulating Northern Hemisphere Ice Sheet Evolution by Glacial Index Method

Yuao ZHANG 1 , 2( ), Xu ZHANG 1( ), Jinbo ZAN 1, Xiaomin FANG 1   

  1. 1.Institute of Tibetan Plateau Research, Chinese Academy of Sciences, Beijing 100101, China
    2.University of Chinese Academy of Science, Beijing 101408, China
  • Received:2023-04-04 Revised:2023-05-04 Online:2023-06-10 Published:2023-06-07
  • Contact: Xu ZHANG E-mail:zhangyuao20@itpcas.ac.cn;xu.zhang@itpcas.ac.cn
  • About author:ZHANG Yuao (1997-), male, Suzhou City, Jiangsu Province, Master student. Research area includes ice sheet dynamics and simulation. E-mail: zhangyuao20@itpcas.ac.cn
  • Supported by:
    the Outstanding Member Projects of the Chinese Academy of Sciences for Youth Promotion(Y202023);The Basic Science Center for Tibetan Plateau Earth System(Grant 41988101);The Second Tibetan Plateau Scientific Expedition and Research, Ministry of Science and Technology of China "Weathering and erosion history of Plateau and its climatic and environmental effects” Sub-Project of Project 7 “Plateau Growth and Evolution”(2019QZKK0707)

IPCC第六次评估报告(AR6)显示,自20世纪起极地冰盖持续消融,全球海平面不断上升。目前对于地球冰盖未来的预测以及过去的演变历史尚不明确,而数值模拟能够提供一种有效的解决方案。在冰盖模拟研究中,冰期指数法可依据古气候代用指标将离散的气候强迫转化为连续的气候强迫,用于冰盖演变的瞬态模拟。基于该方法,利用2组(共6条)分别代表全球海平面和温度变化的代用指标,开展末次冰期旋回北半球冰盖的时空演变模拟研究,结果表明: 模拟的冰量演变特征受指数的变化趋势控制; 在指数变化特征(轨迹和变幅)相似时,千年尺度气候突变事件的存在会导致模拟的总冰量偏少; 在同一气候强迫下,不同指数模拟的最大冰盖范围受夏季0 ℃等温线的约束,同时指数的演变轨迹与变幅也会影响末次冰期盛冰期冰盖模拟的空间分布。因此,在利用冰期指数法开展冰盖瞬态模拟研究时,需根据关注的研究区域选取有代表性的指数并考虑古气候代用指标(即冰期指数)的不确定性对模拟结果的影响。

The Intergovernmental Panel on Climate Change Sixth Assessment Report (AR6) stresses threat of the continuous melting of polar ice sheets and hence rising global sea levels on our socioeconomic and living environment. However, large uncertainty remains in future projections of Earth’s ice sheet, which might be reduced by improving our understanding of its evolution history and associated dynamics by ice-sheet modeling. Glacial index method is an effective approach to investigate transient ice sheet change by interpolating discrete climate forcing into continuous climate forcing based on paleoclimate proxies. This indicates the choice of paleoclimate proxy might be of crucial impact on simulated transient ice sheet change. Here we investigate this issue with a focus on the tempo-spatial evolution of the Northern Hemisphere ice sheet during the last glacial cycle using two sets (six in total) of proxies representing global sea level and temperature changes, respectively. Three key conclusions are summarized in the following. First, the characteristics of proxy trajectory have a significant influence on the simulated ice volume’s evolutionary characteristics. Second, the presence of millennial-scale abrupt climate change events in proxies lowers the simulated overall ice volume when tendency and amplitude of proxies are similar. Third, ice sheet extent is constrained by the summer 0 °C isotherm which is modulated by the tendency and amplitude of different proxies, even when subjected to the same Last Glacial Maximum climate forcing. Therefore, our results emphasize the need to carefully consider the characteristics of paleoclimate proxies when using the glacial index method for studying global ice sheet changes over time. Understanding the limitations and potential biases associated with the chosen proxies is crucial to avoid misinterpretation and overstatement of modeling results.


表1 三维热动力冰盖模式选用的物理参数
Table 1 The physical parameters selected in the 3-D dynamic-thermodynamic ice-sheet model
图1 冰盖模式输入的现代与末次冰盛期夏季2 m高度气温[(a)和(b)]与降水[(c)和(d)]
Fig. 1 Summer temperature at 2 m height [(aandb)] and precipitation [(candd)] during modern and Last Glacial MaximumLGMperiods for the ice-sheet model input
JJA: June, July and August (summer)
图2 模式选用的6条地质记录及其对应的冰期指数
NGRIP:格陵兰冰芯δ 18O记录指数;IPSST:伊比利亚半岛海表温度指数;GSST:全球平均海表温度指数;LR04:全球平均底栖有孔虫δ 18O记录指数;RSRSL:红海相对海平面指数;GRSL:全球平均相对海平面指数
Fig. 2 Six geological records selected by the model and their corresponding ice age indices
NGRIP: North Greenland Ice Core Project; IPSST: Iberian Peninsula Sea Surface Temperature; GSST: Global mean Sea Surface Temperature; RSRSL: Red Sea Relative Sea Level; GRSL: Global mean Relative Sea Level
表2 试验中采用的 6组地质记录
Table 2 Six sets of geological records were used in the experiment
图3 冰期指数及其模拟所得冰量
(a)第一组中3条指数的对比;(b)第一组试验结果中的冰量演变过程;(c)第二组中3条指数的对比;(d)第二组试验结果中的冰量演变过程;NGRIP:格陵兰冰芯δ 18O记录指数;IPSST:伊比利亚半岛海表温度指数;GSST:全球平均海表温度指数;LR04:全球平均底栖有孔虫δ 18O记录指数;RSRSL:红海相对海平面指数;GRSL:全球平均相对海平面指数
Fig. 3 Glacial indices and the simulated ice volume
(a) Comparison of the three indicators in the first group; (b) Evolution of ice volume in the first set of test results; (c) Comparison of the three indices in the second group; (d) Evolution of ice volume in the second group of test results; NGRIP: North Greenland Ice Core Project; IPSST: Iberian Peninsula Sea Surface Temperature; GSST: Global mean Sea Surface Temperature; RSRSL: Red Sea Relative Sea Level; GRSL: Global mean Relative Sea Level
图4 海平面当量变化速率
(a)~(b)80~58 ka时期第一(二)组试验结果;(c)~(d)30~0 ka时期第一(二)组试验结果;蓝色阴影标注了地质记录指示的3次融水脉冲事件;NGRIP:格陵兰冰芯δ 18O记录指数;IPSST:伊比利亚半岛海表温度指数;GSST:全球平均海表温度指数;LR04:全球平均底栖有孔虫δ 18O记录指数;RSRSL:红海相对海平面指数;GRSL:全球平均相对海平面指数
Fig. 4 Sea Level EquivalentSLEchange rate
(a)~(b) 80~58 ka period group I(II) test results; (c)~(d) 30~0 ka period group I(II) test results, where blue shading marks the three meltwater pulse events indicated by the geological record; NGRIP: North Greenland Ice Core Project; IPSST: Iberian Peninsula Sea Surface Temperature; GSST: Global mean Sea Surface Temperature; RSRSL: Red Sea Relative Sea Level; GRSL: Global mean Relative Sea Level
图5 末次冰盛期的冰盖地理分布及其冰量对应的等效海平面高度
红线表示该时期夏季0 ℃等温线位置;NGRIP:格陵兰冰芯δ 18O记录指数;IPSST:伊比利亚半岛海表温度指数;GSST:全球平均海表温度指数;LR04:全球平均底栖有孔虫δ 18O记录指数;RSRSL:红海相对海平面指数;GRSL:全球平均相对海平面指数
Fig. 5 The geographical distribution of the ice sheet and the equivalent sea level corresponding to the amount of ice in the last glacial maximum
The red line indicates the position of 0 ℃ isotherm in summer during this period; NGRIP: North Greenland Ice Core Project; IPSST: Iberian Peninsula Sea Surface Temperature; GSST: Global mean Sea Surface Temperature; RSRSL: Red Sea Relative Sea Level; GRSL: Global mean Relative Sea Level
图6 MIS 4阶段的冰盖地理分布及其冰量对应的等效海平面高度
红线表示末次冰盛期夏季0 ℃等温线位置;NGRIP:格陵兰冰芯δ 18O记录指数;IPSST:伊比利亚半岛海表温度指数;GSST:全球平均海表温度指数;LR04:全球平均底栖有孔虫δ 18O记录指数;RSRSL:红海相对海平面指数;GRSL:全球平均相对海平面指数
Fig. 6 The geographical distribution of ice sheet and the equivalent sea level corresponding to the amount of ice in MIS 4
The red line represents the position of 0 ℃ isotherm in summer during the last glacial maximum; NGRIP: North Greenland Ice Core Project; IPSST: Iberian Peninsula Sea Surface Temperature; GSST: Global mean Sea Surface Temperature; RSRSL: Red Sea Relative Sea Level; GRSL: Global mean Relative Sea Level
图7 6条指数在MIS 4时期和末次冰盛期对应的海平面当量标准差
Fig. 7 The standard deviation of Sea Level EquivalentSLEcorresponding to six indices in MIS 4 and Last Glacial MaximumLGMperiods
图8 4条末次冰盛期冰量相近的指数模拟结果在末次冰盛时期与MIS 4时期的冰盖厚度差异
(a)~(c) GSST-IPSST、GSST-LR04和GSST-RSRSL在LGM时期的差异;(d)~(f) MIS 4时期的差异
Fig. 8 The difference of ice sheet thickness between the Last Glacial MaximumLGMperiod and MIS 4 period was obtained by four index simulations with similar ice volume in LGM period
(a)~(c) The difference of GSST-IPSST, GSST-LR04 and GSST-RSRSL in LGM period; (d)~(f) The difference during MIS 4
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