Bayesian Glaciological Modelling to quantify uncertainties in ice core chronologies

Klauenberg, Katy; Blackwell, Paul G.; Buck, Caitlin E.; Mulvaney, Robert; Röthlisberger, Regine; Wolff, Eric W.

doi:10.1016/j.quascirev.2011.03.008

“…this relation was also used by Klauenberg et al (2011). We assume that w z obeys the normal distribution N (0, σ 2 w ).…”

Section: State Space Modelmentioning

confidence: 99%

“…They then estimated the parameters for that model using the Bayesian approach and the Markov chain Monte Carlo (MCMC) method, although they did not consider the errors in the glaciological process model in the estimation of the parameters. Klauenberg et al (2011) took a Bayesian approach to estimate the age-depth relationship and to improve some parameters in their dating model by using δ 18 O data. The uncertainty of the estimate was also evaluated in a Bayesian manner.…”

Section: Introductionmentioning

confidence: 99%

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

Nakano¹,

Suzuki²,

Kawamura³

et al. 2016

Nonlin. Processes Geophys.

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Abstract.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 linearity or Gaussianity. The performance of the proposed technique is demonstrated by applying it to ice core data from Dome Fuji in Antarctica.

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“…Still, many questions remain open on the mechanisms and feedbacks within the climate system that were behind the generation and propagation of these events. Such understanding would be greatly facilitated if the regional synchronicity of change and timing of events (Blaauw et al, 2010;Braun et al, 2011;Klauenberg et al, 2011) could be tested with respect to the contrasting thermo-climatic relationship between the polar regions as predicted by the bipolar seesaw hypothesis (Stocker and Johnsen, 2003;Steig et al, 1998;Pedro et al, 2011;Barker et al, 2011;Stenni et al, 2011;Buiron et al, 2012). Advancements in the absolute dating and relative synchronization of records are thus of primary importance for paleoclimatic archives (Blockley et al, 2012 and references therein), including ice cores (Parrenin et al, 2004(Parrenin et al, , 2012aKawamura et al, 2007;Svensson et al, 2008;Lemieux-Dudon et al, 2010).…”

Section: Introductionmentioning

confidence: 99%

The Antarctic ice core chronology (AICC2012): an optimized multi-parameter and multi-site dating approach for the last 120 thousand years

Vereș

¹

,

Bazin

²

,

Landais

³

et al. 2013

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The deep polar ice cores provide reference records commonly employed in global correlation of past climate events. However, temporal divergences reaching up to several thousand years (ka) exist between ice cores over the last climatic cycle. In this context, we are hereby introducing the Antarctic Ice Core Chronology 2012 (AICC2012), a new and coherent timescale developed for four Antarctic ice cores, namely Vostok, EPICA Dome C (EDC), EPICA Dronning Maud Land (EDML) and Talos Dome (TALDICE), alongside the Greenlandic NGRIP record. The AICC2012 timescale has been constructed using the Bayesian tool Datice (Lemieux-Dudon et al., 2010) that combines glaciological inputs and data constraints, including a wide range of relative and absolute gas and ice stratigraphic markers. We focus here on the last 120 ka, whereas the companion paper by Bazin et al. (2013) focuses on the interval 120–800 ka.

Compared to previous timescales, AICC2012 presents an improved timing for the last glacial inception, respecting the glaciological constraints of all analyzed records. Moreover, with the addition of numerous new stratigraphic markers and improved calculation of the lock-in depth (LID) based on δ¹⁵N data employed as the Datice background scenario, the AICC2012 presents a slightly improved timing for the bipolar sequence of events over Marine Isotope Stage 3 associated with the seesaw mechanism, with maximum differences of about 600 yr with respect to the previous Datice-derived chronology of Lemieux-Dudon et al. (2010), hereafter denoted LD2010. Our improved scenario confirms the regional differences for the millennial scale variability over the last glacial period: while the EDC isotopic record (events of triangular shape) displays peaks roughly at the same time as the NGRIP abrupt isotopic increases, the EDML isotopic record (events characterized by broader peaks or even extended periods of high isotope values) reached the isotopic maximum several centuries before.

It is expected that the future contribution of both other long ice core records and other types of chronological constraints to the Datice tool will lead to further refinements in the ice core chronologies beyond the AICC2012 chronology. For the time being however, we recommend that AICC2012 be used as the preferred chronology for the Vostok, EDC, EDML and TALDICE ice core records, both over the last glacial cycle (this study), and beyond (following Bazin et al., 2013). The ages for NGRIP in AICC2012 are virtually identical to those of GICC05 for the last 60.2 ka, whereas the ages beyond are independent of those in GICC05modelext (as in the construction of AICC2012, the GICC05modelext was included only via the background scenarios and not as age markers). As such, where issues of phasing between Antarctic records included in AICC2012 and NGRIP are involved, the NGRIP ages in AICC2012 should therefore be taken to avoid introducing false offsets. However for issues involving only Greenland ice cores, there is not yet a strong basis t...

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“…Still, many questions remain open on the mechanisms and feedbacks within the climate system that were behind the generation and propagation of these events. Such understanding would be greatly facilitated if the regional synchronicity of change and timing of events (Blaauw et al, 2010;Braun et al, 2011;Klauenberg et al, 2011) could be tested with respect to the contrasting thermo-climatic relationship between the polar regions as predicted by the bipolar seesaw hypothesis (Stocker and Johnsen, 2003;Steig et al, 1998;Pedro et al, 2011;Barker et al, 2011;Stenni et al, 2011;Buiron et al, 2012). Advancements in the absolute dating and relative synchronization of records are thus of primary importance for paleoclimatic archives (Blockley et al, 2012 and references therein), including ice cores (Parrenin et al, 2004(Parrenin et al, , 2007(Parrenin et al, , 2012a(Parrenin et al, , 2013Kawamura et al, 2007;Svensson et al, 2008;Lemieux-Dudon et al, 2010).…”

Section: Introductionmentioning

confidence: 99%

The Antarctic ice core chronology (AICC2012): an optimized multi-parameter and multi-site dating approach for the last 120 thousand years

Vereș¹,

Bazin²,

Landais³

et al. 2012

Preprint

View full text Add to dashboard Cite

The deep polar ice cores provide reference records commonly employed in global correlation of past climate events. However, temporal divergences reaching up to several thousand years (ka) exist between ice cores over the last climatic cycle. In this context, we are hereby introducing the Antarctic Ice Core Chronology 2012 (AICC2012), a new and coherent timescale developed for four Antarctic ice cores, namely Vostok, EPICA Dome C (EDC), EPICA Dronning Maud Land (EDML) and Talos Dome (TALDICE), alongside the Greenlandic NGRIP record. The AICC2012 time scale has been constructed using the Bayesian tool Datice (Lemieux-Dudon et al., 2010) that combines glaciological inputs and data constraints, including a wide range of relative and absolute gas and ice stratigraphic markers. We focus here on the last 120 ka, whereas the companion paper by Bazin et al., (2012) focuses on the interval 120–800 ka. <br><br> Compared to previous timescales, AICC2012 presents an improved timing for the last glacial inception respecting the glaciological constraints of all analyzed records. Moreover, with the addition of numerous new stratigraphic markers and improved calculation of the lock-in depth (LID) based on δ<sup>15</sup>N data employed as the Datice background scenario, the AICC2012 presents a new timing for the bipolar sequence of events over Marine Isotope Stage 3 associated with the see-saw mechanism, with maximum differences of about 500 yr with respect to the previous Datice-derived chronology of Lemieux-Dudon et al. (2010), hereafter denoted LD2010. Our improved scenario confirms the regional differences for the millennial scale variability over the last glacial period: while the EDC isotopic record (events of triangular shape) displays peaks roughly at the same time as the NGRIP abrupt isotopic increases, the EDML isotopic record (events characterized by broader peaks or even extended periods of high isotope values) reached the isotopic maximum several centuries before

show abstract

Bayesian Glaciological Modelling to quantify uncertainties in ice core chronologies

Cited by 17 publications

References 25 publications

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

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

The Antarctic ice core chronology (AICC2012): an optimized multi-parameter and multi-site dating approach for the last 120 thousand years

The Antarctic ice core chronology (AICC2012): an optimized multi-parameter and multi-site dating approach for the last 120 thousand years

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