Novel approach to estimate the water isotope diffusion length in deep ice cores with an application to Marine Isotope Stage 19 in the Dome C ice core

• Published in: The Cryosphere
• Main Authors: F. Shaw, A. M. Dolman, T. Kunz, V. Gkinis, T. Laepple
• Format: Article in Journal/Newspaper
• Language: English
• Published: Copernicus Publications 2024
• Subjects: Environmental sciences; GE1-350; Geology; QE1-996.5; EPICA; ice core; The Cryosphere
• Online Access: https://doi.org/10.5194/tc-18-3685-2024; https://doaj.org/article/a27156f447ea485c96183d9305cb1b88

Accurate estimates of water isotope diffusion lengths are crucial when reconstructing and interpreting water isotope records from ice cores. This is especially true in the deepest, oldest sections of deep ice cores, where thermally enhanced diffusive processes have acted over millennia on extremely thinned ice. Previous statistical estimation methods, used with great success in shallower, younger ice cores, falter when applied to these deep sections, as they fail to account for the statistics of the climate on millennial timescales. Here, we present a new method to estimate the diffusion length from water isotope data and apply it to the Marine Isotope Stage 19 (MIS 19) interglacial at the bottom of the EPICA Dome C (EDC, Dome Concordia) ice core. In contrast to the conventional estimator, our method uses other interglacial periods taken from further up in the ice core to estimate the structure of the variability before diffusion. Through use of a Bayesian framework, we are able to constrain our fit while propagating the uncertainty in our assumptions. We estimate a diffusion length of 31±5 cm for the MIS 19 period, which is significantly smaller than previously estimated (40–60 cm). Similar results were obtained for each interglacial used to represent the undiffused climate signal, demonstrating the robustness of our estimate. Our result suggests better preservation of the climate signal at the bottom of EDC and likely other deep ice cores, offering greater potentially recoverable temporal resolution and improved reconstructions through deconvolution.