ESR 12 – Estimating and accounting for diffusion in deep ice using advanced statistical methods

Early stage researcher: Fyntan Shaw (AWI, DE)

Supervisors: T. Laepple (AWI, D), V. Gkinis (Univ. of Copenhagen, DK)

Academic secondment: Univ. of Copenhagen (DK) ; Non-academic secondment: Risk Management Solutions (UK)


The isotope record in the deep part of the oldest ice core is expected to be strongly affected by diffusion. Therefore, the isotopic record of millennial climate variations and potentially even glacial-interglacial changes is expected to be heavily smoothed.

Accounting for the diffusion and mixing processes will thus be necessary to recover the amplitude of the climate variations (back-diffusion) as well as to provide information which climate variations were consistent to the measured isotopic variations (probabilistic reconstruction).

The proposed PhD project will work on this challenge by using and developing advanced statistical techniques for the estimation of the diffusion length, the statistical characterization of the measurement process and deconvolution of the deep ice-core signal. It will complement the other PhD projects proposed in the ITN working on this question from a measurement or firn/ice- modeling perspective.

Key words: climate reconstruction, signal recovery, statistics, firn and ice diffusion, water isotopes

Scientific results


Presentation by Fyntan Shaw at EGU 2022:

CL1.2.5 – The state-of-the-art in ice coring sciences, Room 0.14 on Thursday 26th of May 2022, 14:12 CEST – EGU22-5519

Estimating the diffusion in the deepest section of the Dome-C ice core using a new statistical method

by Fyntan Shaw, Thomas Laepple, Torben Kunz, Vasileios Gkinis, and Dorthe Dahl-Jensen