Talk by Mai Winstrup, University of Copenhagen.
Abstract:
In this talk, I will present a Hidden Markov Model-based algorithm for constructing timescales for paleoclimate records by annual layer counting. This objective, statistics-based approach has a number of major advantages over the current manual approach, beginning with speed. Additionally, the algorithm gives rigorous uncertainty estimates for the resulting timescale, which are far smaller than those produced manually. I will demonstrate the utility of StratiCounter by applying it to ice-core data from Greenland and Antarctica, and compare the resulting timescales to those obtained manually. For ice cores with reasonably well-defined annual layers, false-discovery rates and miss rates are ~1%, which are similar to disagreements among human experts in the field, thus suggesting that the performance of the algorithm is comparable to a manual approach.