Next-generation radiocarbon calibration: Incorporating information on calibration curve covariance

一个为期6个月的项目，旨在调查IntCal20放射性碳校准曲线中协方差信息对放射性碳校准的影响。放射性碳(14C)提供了过去55,000年来最常见的测年方法，并支撑了环境和考古科学的广度。由于过去14C水平的波动，放射性碳测年需要对照国际商定的IntCal校准曲线进行校准。传统上，这些IntCal校准曲线提供过去14C水平的逐点估计，这些估计从一年到下一年被视为独立的。这种独立性表明，真正的14C水平可能会在一年内从不确定性包络的底部变化到下一年区间的顶部，然后再回到底部。这种极端的变异性是不切实际的。在现实中，曲线估计是有协方差的--我们预计在其不确定性范围内，随着时间的推移，它的变化会更慢。在校准多个14C测定时，这种协方差很重要，这对许多环境建模至关重要。为最近的IntCal20曲线实施的新的曲线构造方法使得能够存储单独的校准曲线实现(对于已出版的逐点IntCal20估计进行了总结)。每一次实现都代表了55,000-0卡年BP的整个可信的14C历史，并对曲线协方差进行了编码。这个项目的目的是探索使用这些实现(因此协方差信息)而不是逐点校准的效果。我们的发现有可能改写我们校准的方式。

A 6-month project to investigate the effect on radiocarbon calibration of covariance information within the IntCal20 radiocarbon calibration curve. Radiocarbon (14C) provides the most common method for dating the last 55,000 years and underpins the breadth of the environmental and archaeological sciences. Due to fluctuations in past levels of 14C, radiocarbon dating requires calibration against the internationally-agreed IntCal calibration curves. Traditionally, these IntCal calibration curves provide pointwise estimates of past 14C levels that are treated as independent from one year to the next. This independence suggests the true 14C level could change from the bottom of the uncertainty envelope in one year, to the top of the interval in the next, and then back to the bottom again. This extreme variability is unrealistic. In reality, the curve estimate has covariance - we expect it to vary more slowly over time within its uncertainty envelope. When calibrating multiple 14C determinations, essential for much environmental modelling, this covariance matters. The novel approach to curve construction implemented for the recent IntCal20 curves enabled storage of individual calibration curve realisations (which were summarised for the published pointwise IntCal20 estimates). Each realisation represents an entire plausible 14C history from 55,000 - 0 cal yr BP and encodes the curve covariance. This project aims to explore the effect of using these realisations (and hence covariance information) rather than pointwise calibration. Our findings have the potential to rewrite the way we calibrate.