Continuous synchronization of the Greenland ice-core and U–Th timescales using probabilistic inversion

IF 3.8 2区 地球科学 Q1 GEOSCIENCES, MULTIDISCIPLINARY Climate of The Past Pub Date : 2024-06-28 DOI:10.5194/cp-20-1415-2024
Francesco Muschitiello, Marco Antonio Aquino-Lopez
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Abstract

Abstract. This study presents the first continuously measured transfer functions that quantify the age difference between the Greenland ice-core chronology 2005 (GICC05) and the U–Th timescale during the last glacial period. The transfer functions were estimated using an automated algorithm for Bayesian inversion that allows inferring a continuous and objective synchronization between Greenland ice-core and East Asian summer monsoon speleothem data, and a total of three transfer functions were inferred using independent ice-core records. The algorithm is based on an alignment model that considers prior knowledge of the GICC05 counting error but also samples synchronization scenarios that exceed the differential dating uncertainty of the annual-layer count in ice cores, which are currently hard to detect using conventional alignment techniques. The transfer functions are on average 48 % more precise than previous estimates and significantly reduce the absolute dating uncertainty of the GICC05 back to 48 kyr ago. The results reveal that GICCC05 is, on average, systematically younger than the U–Th timescale by 0.86 %. However, they also highlight that the annual-layer counting error is not strictly correlated over extended periods of time and that within the coldest Greenland Stadials the differential dating uncertainty is likely underestimated by up to ∼13 %. Importantly, the analysis implies for the first time that during the Last Glacial Maximum GICC05 may overcount ice layers by ∼10 % – a bias possibly attributable to a higher frequency of sub-annual layers due to changes in the seasonal cycle of precipitation and mode of dust deposition to the Greenland Ice Sheet. The new timescale transfer functions provide important constraints on the uncertainty surrounding the stratigraphic dating of the Greenland age scale and enable an improved chronological integration of ice cores as well as U–Th-dated and radiocarbon-dated paleoclimate records on a common timeline. The transfer functions are available as a Supplement to this study.
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利用概率反演实现格陵兰冰芯和 U-Th 时间尺度的连续同步化
摘要本研究首次提出了连续测量的转移函数,用于量化格陵兰冰芯年代学 2005(GICC05)与上个冰川期 U-Th 时间尺度之间的年龄差异。转移函数是利用贝叶斯反演自动算法估算的,该算法可以推断格陵兰冰芯数据与东亚夏季季风湍流数据之间连续而客观的同步性,利用独立的冰芯记录共推断出三个转移函数。该算法基于一个配准模型,该模型考虑了 GICC05 计数误差的先验知识,但也对超过冰芯中年层计数的差分年代不确定性的同步情况进行了采样,而目前使用传统配准技术很难检测到这种情况。转移函数比以前的估计平均精确 48%,并大大降低了 GICC05 的绝对年代不确定性,使其可追溯到 48 千年前。结果显示,GICCC05 平均比 U-Th 时间尺度年轻 0.86%。不过,他们也强调,年层计数误差在较长时期内并不严格相关,在最冷的格陵兰晚期,差异年代测定的不确定性可能被低估了 13%。重要的是,该分析首次表明,在末次冰川极盛时期,GICC05 对冰层的计算可能高出 10%--这种偏差可能是由于格陵兰冰盖降水季节周期和尘埃沉积方式的变化导致次年冰层出现频率较高所致。新的时间尺度转换函数对格陵兰年龄尺度地层年代测定的不确定性提供了重要的约束,并使冰芯以及 U-Th 年代测定和放射性碳年代测定的古气候记录能够在一个共同的时间轴上进行更好的年代整合。转移函数可作为本研究的补充。
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来源期刊
Climate of The Past
Climate of The Past 地学-气象与大气科学
CiteScore
7.40
自引率
14.00%
发文量
120
审稿时长
4-8 weeks
期刊介绍: Climate of the Past (CP) is a not-for-profit international scientific journal dedicated to the publication and discussion of research articles, short communications, and review papers on the climate history of the Earth. CP covers all temporal scales of climate change and variability, from geological time through to multidecadal studies of the last century. Studies focusing mainly on present and future climate are not within scope. The main subject areas are the following: reconstructions of past climate based on instrumental and historical data as well as proxy data from marine and terrestrial (including ice) archives; development and validation of new proxies, improvements of the precision and accuracy of proxy data; theoretical and empirical studies of processes in and feedback mechanisms between all climate system components in relation to past climate change on all space scales and timescales; simulation of past climate and model-based interpretation of palaeoclimate data for a better understanding of present and future climate variability and climate change.
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