A sequential Bayesian approach for the estimation of the age-depth relationship of the Dome Fuji ice core

• Published in: Nonlinear Processes in Geophysics
• Main Authors: Nakano, Shin'Ya, Suzuki, Kazue, Kawamura, Kenji, Parrenin, Frédéric, Higuchi, Tomoyuki
• Other Authors: Graduate University for Advanced Studies Hayama (SOKENDAI), The Institute of Statistical Mathematics (Tokyo ), National Institute of Polar Research Tokyo (NiPR), Laboratoire de glaciologie et géophysique de l'environnement (LGGE), Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS)-Observatoire des Sciences de l'Univers de Grenoble (OSUG ), Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut national des sciences de l'Univers (INSU - CNRS)-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Université Savoie Mont Blanc (USMB Université de Savoie Université de Chambéry )-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes 2016-2019 (UGA 2016-2019 )-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP )-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Université Savoie Mont Blanc (USMB Université de Savoie Université de Chambéry )-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes 2016-2019 (UGA 2016-2019 ), Université Grenoble Alpes 2016-2019 (UGA 2016-2019 )
• Format: Article in Journal/Newspaper
• Language: English
• Published: HAL CCSD 2016
• Subjects: [SDE]Environmental Sciences; Antarc*; Antarctica; ice core
• Online Access: https://insu.hal.science/insu-01387825; https://insu.hal.science/insu-01387825/document; https://insu.hal.science/insu-01387825/file/NONLINEAR%20PROCESSES%20IN%20GEOPHYSICS%20-%20A%20sequential%20Bayesian%20approach%20for%20the%20estimation%20of%20the%20age-depth%20relationship%20of%20the%20Dome%20Fuji%20ice%20c.pdf; https://doi.org/10.5194/npg-23-31-2016

International audience A technique for estimating the age–depth relationship in an ice core and evaluating its uncertainty is presented. The age–depth relationship is determined by the accumulation of snow at the site of the ice core and the thinning process as a result of the deformation of ice layers. However, since neither the accumulation rate nor the thinning process is fully known, it is essential to incorporate observational information into a model that describes the accumulation and thinning processes. In the proposed technique, the age as a function of depth is estimated by making use of age markers and δ 18 O data. The age markers provide reliable age information at several depths. The data of δ 18 O are used as a proxy of the temperature for estimating the accumulation rate. The estimation is achieved using the particle Markov chain Monte Carlo (PMCMC) method, which is a combination of the sequential Monte Carlo (SMC) method and the Markov chain Monte Carlo method. In this hybrid method, the posterior distributions for the parameters in the models for the accumulation and thinning process are computed using the Metropolis method, in which the likelihood is obtained with the SMC method, and the posterior distribution for the age as a function of depth is obtained by collecting the samples generated by the SMC method with Metropolis iterations. The use of this PMCMC method enables us to estimate the age–depth relationship without assuming either lin-earity or Gaussianity. The performance of the proposed technique is demonstrated by applying it to ice core data from Dome Fuji in Antarctica.