Ice cores record crucial information about past climate. However, before ice core data can have scientific value, the chronology must be inferred by estimating the age as a function of depth. Under certain conditions, chemicals locked in the ice display quasi-periodic cycles that delineate annual layers. Manually counting these noisy seasonal patterns to infer the chronology can be an imperfect and time-consuming process, and does not capture uncertainty in a principled fashion. In addition, several ice cores may be collected from a region, introducing an aspect of spatial correlation between them. We present an exploration of the use of probabilistic models for automatic dating of ice cores, using probabilistic programming to showcase its use for prototyping, automatic inference and maintainability, and demonstrate common failure modes of these tools.

翻译：冰芯记录了有关过去气候的重要信息。然而,在冰芯数据具有科学价值之前,必须用估计年限作为深度函数来推断时间顺序。在某些情况下,冰层中锁定的化学品显示的半周期周期性周期性分布为每年的层次。人工计算这些吵闹的季节性模式来推断时间顺序,可能是一个不完善和耗时的过程,不能以有原则的方式捕捉不确定性。此外,可以从一个区域收集一些冰芯,引入它们之间空间相关性的一个方面。我们探讨了使用概率模型来自动确定冰芯的日期,利用概率性编程来展示其用于原型、自动推论和可维持性,并展示这些工具的常见失败模式。