EGU21-822, updated on 08 Oct 2023
EGU General Assembly 2021
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.

The Paleochrono probabilistic model to derive a consistent chronology for several paleoclimatic sites

Frédéric Parrenin1, Lucie Bazin2, Christo Buizert3, Emilie Capron1, Jai Chowdry Beeman1, Ellen Corrick4,5, Russell Drysdale4,5, Kenji Kawamura6, Amaëlle Landais2, Robert Mulvaney7, Ikumi Oyabu6, and Sune Rasmussen8
Frédéric Parrenin et al.
  • 1Université Grenoble Alpes, CNRS, IRD, IGE, 38000 Grenoble, France (
  • 2Laboratoire des Sciences du Climat et de l’Environnement (LSCE/IPSL/CEA/CNRS/UVSQ/UPS), Gif-sur-Yvette, France
  • 3College of Earth, Ocean and Atmospheric Sciences, Oregon State University (OSU), Corvallis, OR, USA
  • 4School of Geography, The University of Melbourne, Melbourne,Victoria, Australia
  • 5EDYTEM, CNRS, Université Savoie Mont Blanc, Université Grenoble Alpes, Chambéry, France
  • 6National Institute of Polar Research, Research Organizations of Information and Systems, 10-3 Midori-cho, Tachikawa, Tokyo 190-8518, Japan
  • 7British Antarctic Survey, Madingley Road, High Cross, Cambridge, CB3 0ET, UK
  • 8Physics of Ice, Climate and Earth, Niels Bohr Institute, University of Copenhagen, Copenhagen, Denmark

Past climatic and environmental changes can be reconstructed thanks to paleoclimatic archives such as ice cores, marine sediment cores, lake sediment cores, speleothems, tree rings, corals, etc. The dating of these natural archives is crucial for deciphering the temporal sequence of events during past climate changes. It is also essential to estimate the absolute and relative errors of such estimated chronologies. This task is, however, complex since it involves the combination of different dating approaches on different paleoclimatic sites and often different types of archives. Here we present Paleochrono, a new probabilistic model to derive a common and probalistically optimal chronology for several paleoclimatic sites with potentially different types of archives. Paleochrono is based on the inversion of an archiving model: a varying deposition rate (also named sedimentation or accumulation rate) and also, for ice cores, a lock-in-depth of air bubbles (since air is not trapped at surface) and a thinning function (since ice undergoes flow). The model integrates several types of chronological information: prior knowledge of the archiving process, independently dated horizons, depth intervals of known duration, undated stratigraphic links between records, and, for ice cores, Δdepth observations (depth differences between synchronous events recorded in the bubbles and ice, respectively). The optimization is formulated as a least-squares problem, assuming that all densities of probabilities are near-Gaussian and that the model is almost linear in the vicinity of the best solution. Paleochrono is the successor of IceChrono, which was dealing only with ice-core records. Paleochrono performs better than IceChrono in terms of computational efficiency, ease of use, and accuracy. We demonstrate the ability of Paleochrono in a new AICC2012-Hulu dating experiment, which combines the AICC2012 dating experiment, based on records from five polar ice cores, with data from two U/Th-dated speleothems from Hulu Cave (China). We analyse the performance of Paleochrono in terms of computing time and memory usage in various dating experiments. Paleochrono is freely available under the MIT open source license.

How to cite: Parrenin, F., Bazin, L., Buizert, C., Capron, E., Chowdry Beeman, J., Corrick, E., Drysdale, R., Kawamura, K., Landais, A., Mulvaney, R., Oyabu, I., and Rasmussen, S.: The Paleochrono probabilistic model to derive a consistent chronology for several paleoclimatic sites, EGU General Assembly 2021, online, 19–30 Apr 2021, EGU21-822,, 2021.