The first continuously measured transfer functions that quantify the age difference between the Greenland ice-core chronology 2005 (GICC05) and the U–Th timescale are presented. The transfer functions were generated using a novel probabilistic algorithm for the synchronization of proxy signals. The results greatly improve the accuracy and precision of previous synchronization estimates and reveal that the annual-layer counting error of GICC05 is less systematic than previously assumed.

In general, the variance and short-lag autocorrelations of the fluctuations increase in a system approaching a critical transition. Using these indicators, we identify statistical precursor signals for the Dansgaard–Oeschger cooling events recorded in two climatic proxies of three Greenland ice core records. We then provide a dynamical systems theory that bridges the gap between observing statistical precursor signals and the physical precursor signs empirically known in paleoclimate research.

Dansgaard–Oeschger events are a series of past abrupt climate change events, during which the atmosphere, sea ice, and ocean in the North Atlantic underwent rapid changes. One current topic of interest is the order in which these different changes occurred, which remains unknown. In this work, we find that the current best method used to investigate this topic is subject to substantial bias. This implies that it is not possible to reliably determine the order of the different changes.

The record of past climate is preserved by several archives from different regions, such as ice cores from Greenland or Antarctica or speleothems from caves such as the Hulu Cave in China. In this study, these archives are aligned by taking advantage of the globally synchronous production of cosmogenic radionuclides. This produces a new perspective on the global climate in the period between 20 000 and 25 000 years ago.

This paper analyzes the uniqueness of a paleoclimate event entitled the Bølling–Allerød Younger Dryas (BA/YD) through a statistical lens in order to better understand its relation to other events similar to it. Furthermore, we implement a novel statistical method entitled PCOut in order to measure the BA/YD's various elements of uniqueness in existing paleoclimate records. We suggest future use of this method for paleoclimate research that aims to assess uniqueness across multiple criteria.