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An exploration of the utility of speleothem age distributions for palaeoclimate assessment
Quaternary Geochronology ( IF 2.7 ) Pub Date : 2020-08-01 , DOI: 10.1016/j.quageo.2020.101112
Rieneke Weij , Jon Woodhead , John Hellstrom , Kale Sniderman

Age distributions of speleothem growth frequency are often employed as proxies for past climate variation. However, their interpretation can be influenced by many variables such as the type of probability density estimator used, the number of samples studied, and indeed the nature of the sampling itself. In order to explore the utility of speleothem age distributions in this context, we constructed a synthetic speleothem growth dataset by randomly generating U-Th ages, based on a known climatic forcing to evaluate whether the most basic climatic information could be recovered by subsequent sampling of this dataset under differing conditions. This modelling approach allows us to separately examine the influences of sample size, the type of probability density estimator, and its parameterisation on the shape of the resulting age distribution. Our model demonstrates that periodic Quaternary climate fluctuations can be recovered from growth frequency distributions derived from as few as 120–150 radiometric ages. To construct such distributions, a kernel density estimator may more accurately represent speleothem growth frequency than the commonly employed probability density plot, because peaks in the latter often reflect data precision rather than data density. For U-Th ages, randomizations of the activity ratios can be used to reintroduce chronometric or analytical uncertainty into the Kernel Density Estimator in a Monte-Carlo simulation.



中文翻译:

脾骨年龄分布在古气候评估中的应用探索

鞘翅目生长频率的年龄分布通常被用作过去气候变化的代表。但是,它们的解释可能会受到许多变量的影响,例如所使用的概率密度估计器的类型,研究的样本数以及抽样本身的性质。为了在这种情况下探索针叶类年龄分布的效用,我们基于已知的气候强迫,通过评估随后的采样是否可以恢复最基本的气候信息,通过随机生成U-Th年龄来构建合成的针叶类生长数据集。该数据集在不同条件下。这种建模方法使我们能够分别检查样本大小,概率密度估计器的类型及其参数化对最终年龄分布形状的影响。我们的模型表明,可以从低至120-150辐射年龄的生长频率分布中恢复周期性的第四纪气候波动。为了构建这样的分布,内核密度估计器可能比常用的概率密度图更准确地表示脾疫增长频率,因为后者中的峰值通常反映数据精度而不是数据密度。对于U-Th年龄,可以在蒙特卡罗模拟中使用活动比的随机化将计时或分析不确定性重新引入内核密度估计器中。内核密度估计器可能比常用的概率密度图更准确地表示脾疫增长频率,因为后者中的峰值通常反映数据精度而不是数据密度。对于U-Th年龄,可以在蒙特卡罗模拟中使用活动比的随机化将计时或分析不确定性重新引入内核密度估计器中。内核密度估计器可能比常用的概率密度图更准确地表示脾疫增长频率,因为后者中的峰值通常反映数据精度而不是数据密度。对于U-Th年龄,可以在蒙特卡罗模拟中使用活动比的随机化将计时或分析不确定性重新引入内核密度估计器中。

更新日期:2020-08-01
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