In ice cores which are drilled through ice sheets in polar regions, valuable information about past environment and climate are preserved. A pivotal part of interpreting the information held within the cores is to build ice core chronologies i.e. to relate time to depth. Existing dating methods can be categorised as follows: (1) layer counting using the seasonality in signals, (2) glaciological modelling describing processes such as snow accumulation and plastic deformation of ice, (3) comparison with other dated records, or (4) any combination of these. Conventionally, implementation of these approaches does not use statistical methods.
We combine glaciological models with a Bayesian framework. For this purpose, the sources of uncertainty in the glaciological model and the knowledge about these are formalised. Additionally, we include information from layer counting and other dated records (i.e. traces from volcanic eruptions) to constrain the resulting dating. During the talk the setup of this statistical model will be described, the effect of uncertainty in the glaciological model will be demonstrated and the interplay with information from other dating methods will be illustrated.
This combined statistical dating approach is applied to date Antarctic ice cores. For the first time the effects of uncertainty implied by the dating method are investigated for ice core chronologies, which provides valuable insights for the applied community.