SOM

SOM
Supplementary material to AICC2012
Common for Bazin et al. (2013) and Veres et al. (2013)
The method for the building of AICC2012 is an improved version of Datice presented in LemieuxDudon et al. (2010), hereafter LD2010, for 4 ice cores (Vostok, EPICA Dome C, EPICA Dronning
Maud Land, NorthGRIP) and modified for TALDICE by Buiron et al. (2011). The aim is to combine chronological information from data and model to build coherent and precise timescales with
5
associated estimates of uncertainty range. For this, the Datice tool needs several inputs. First, independent background scenarios for thinning, accumulation rate and lock-in depth in ice equivalent
(LIDIE) have to be implemented for each of the 5 ice cores. Then, Datice builds a correction function associated with each scenario (thinning, accumulation rate, LIDIE). The correction function is
more or less allowed to modify the initial scenario depending on the variance associated with each
10
scenario for each ice core. The variance scenarios need to be prescribed by the user. Then, Datice
incorporates markers from ice core records such as absolute or orbital age markers on each ice core,
gas and ice stratigraphic links between the ice cores and constraints for ∆depth (depth difference
between the signatures of the same event in the ice and gas phases). The error statistics of the background and observations must be decorrelated for a proper application of the Datice inverse method.
15
An important aspect of the Datice initialisation that was not modified in this study from LD2010
is the correlation length that imposes the depth range of the ice core on which a marker influences
the correction function. If the correlation length is large, a marker has the effect of modifying on
a large depth range the correction function. Finally, Datice calculates a cost function that measures
the distance between background scenarios and new scenarios as well as between new scenarios and
20
data constraints. A too high cost function obviously means that there are incoherencies between the
inputs proposed by the user.
In the previous studies, the dating method was optimized for the last 50 ka and here we have extended
it over the past 800 ka. Several improvements have been made compared to the study of LemieuxDudon et al. (2010), both in some background scenarios and in the parameterization of the variance
25
associated with these scenarios. In addition, our new chronology also incorporates numerous new
stratigraphic, absolute and orbital markers that strongly reduce the dating uncertainty especially for
the last glacial cycle. We provide below all the necessary information and input parameters to run
1
the open source Datice tool and obtain the AICC2012 chronology for NorthGRIP, Vostok, EDC,
EDML and TALDICE. When nothing is specified (i.e. correlation length), then the original LD2010
30
parameterization is still used.
1
Background parameters
For each ice core, 3 background parameters are needed: accumulation rate, thinning, LIDIE.
1.1
Accumulation rate
For all Antarctic ice cores, we have followed the classical estimate of accumulation rate based on an
35
exponential relationship between accumulation rate and water isotopes (as temperature proxies). For
the 4 Antarctic cores, we have thus used exactly the same accumulation rate scenarios as those prescribed in Lemieux-Dudon et al. (2010) and Buiron et al. (2011) (for TALDICE). Note that for Vostok and TALDICE, changes in elevation are taken into account to correct the temperature estimate
from the water isotopic profiles. With regard to GICC05, in order to constrain AICC2012 to match
40
GICC05 for the past 60 ka, we have deduced the accumulation rate from the annual layer thickness
given by the GICC05modelext (Vinther et al., 2006; Rasmussen et al., 2006; Andersen et al., 2006;
Svensson et al., 2008; Wolff et al., 2010) and the strain rate given by the Dansgaard-Johnsen model
tuned for NorthGRIP (NorthGRIP Community Members, 2004; Andersen et al., 2006).
1.2
45
Thinning
For Vostok and EDC, we used the same thinning function as in LD2010. For Vostok, the thinning
function is deduced from the accumulation and FGT1 age scale. For EDC, it is deduced from the
accumulation and the EDC3 model age scale. Concerning EDML, the thinning function is obtained
from the flow model of Huybrechts et al. (2007). Such a background thinning function is different
from the one implemented in Lemieux-Dudon et al. (2010) and especially avoids spurious peaks
50
around 500 m depth. We used the same thinning function as Buiron et al. (2011) for TALDICE,
obtained from a 1D flow model. For NGRIP, the strain rate is given by the Dansgaard-Johnsen model
tuned for NorthGRIP (NorthGRIP Community Members, 2004; Andersen et al., 2006) and used here
as thinning background scenario. Note that the background thinning function for NorthGRIP used in
Lemieux-Dudon et al. (2010) was not fully consistent with GICC05. As a consequence, there was a
55
slight disagreement between the LD2010 NorthGRIP timescale and GICC05 at the rapid warmings
associated with Dansgaard-Oeschger events with differences of ±30 a. These differences do not
exist anymore for AICC2012 (Fig. 5).
We performed a test of the influence of different thinning functions as input for Vostok (the one
used to build AICC2012 and a ”test thinning function”). The test thinning function is very simplified
60
and obtained using IceChronoModel (F. Parrenin Pers. comm.). We can see that the thinning outputs
2
with Datice tend to the same behaviour. The resulting chronology is not significantly changed with
the test thinning function as input (Fig. 1).
Fig. 1. Thinning function tests on Vostok. Grey curves are background and blue curves are Datice results. a:
thinning function as in AICC2012. b: test thinning function. c: comparison of Datice outputs (AICC2012 in
dark blue, test thinning function in light blue). d: comparison of the resulting chronologies.
1.3
LIDIE
Initially, the background LIDIE for each site came from the Goujon et al. (2003) firnification model
(Lemieux-Dudon et al., 2010). The model has been validated over NorthGRIP (Landais et al., 2004;
Huber et al., 2006; Guillevic et al., 2013) but seems to overestimate LIDIE for glacial conditions
in Antarctic sites except for TALDICE (Landais et al., 2006; Parrenin et al., 2012a; Capron et al.,
2013). Parrenin et al. (2012a) have suggested that δ 15 N may provide more realistic constraints on
past LID even in low accumulation rate sites. We have thus performed tests with Datice comparing
the output LIDIE when using as input the firnification model (background scenario LIDIE 1) and a
LIDIE inspired by the δ 15 N profile on each site except NorthGRIP (background scenario LIDIE 2).
For this scenario 2, we have assumed that the convective zone did not change over time and took a 0
m convective zone for EDML, TALDICE and EDC and 13 m for Vostok as observed on present firn
(Landais et al., 2006). The LIDIE can then be calculated from the δ 15 N variations in the absence of
any rapid temperature variation (2◦ C in 100 a) at the surface. This condition is valid in Antarctica
over the considered period.
LIDIE = 0.7 · δ 15 N · R · T /g
where T is the mean firn temperature, R the ideal gas constant and g the standard gravity. The factor
65
0.7 stands for the mean density of the firn. A small correction for temperature gradient in the firn
affects the glacial LIDIE in low accumulation rate sites like Vostok and Dome C by 3 m at maximum. This correction has been taken into account using the firn gradient calculated by the Goujon
3
et al. (2003) model. For building scenario 2, we have used δ 15 N profiles when they were available
(Dreyfus et al. (2010) for EDC, Sowers et al. (1992) for Vostok, Capron et al. (2013) for TALDICE
70
and EDML). None of these profiles cover the whole depth of the 4 Antarctic ice cores. We then take
advantage of the strong link between δ 15 N and δD evolution on an age scale (Dreyfus et al., 2010).
As a consequence, we could build the missing part of the δ 15 N profiles from the δD−δ 15 N regression over Terminations using the official ice and gas timescales for each core. Such method has been
applied to fill the gaps of the δ 15 N profiles for EDC over the last 300 ka (except for Terminations
75
where δ 15 N profiles are available, Dreyfus et al. (2010)). For TALDICE, the firnification model has
been shown to be in good agreement with δ 15 N data over the last deglaciation (Capron et al., 2013)
so that we have used the Goujon et al. (2003) LIDIE output to fill the gap over the last interglacial
and last glacial periods.
80
The different background scenarios for LIDIE have a small impact on the final chronology because
the variance associated with the LIDIE background scenario is quite large. As a consequence, the
Antarctic output LIDIE are mostly constrained by the ice and gas stratigraphic points, especially
over the last glacial period where many stratigraphic tie-points are available (see corresponding section below). During the last glacial period at EDC, the agreement is better between output and
85
background LIDIE when scenario LIDIE 2 is used (Fig. 2) especially over Termination I. There are
several reasons why we do not end with the same LIDIE after analyses at Dome C in LD2010 and in
AICC2012. The first reason, which is probably not the main one, is that we have much more stratigraphic points in AICC2012 than in LD2010. The second reason is linked to the background LIDIE
scenarios. In AICC2012, the LIDIE background scenario of NorthGRIP is significantly lower than
90
the one in LD2010 (Figure 5 of Veres et al. (2013)). This is due to a better constrained temperature
input scenario for the firn densification model used to obtain the background LIDIE of NorthGRIP,
in agreement with the full δ 15 N record at NorthGRIP (Landais et al., 2004, 2005; Huber et al., 2006,
P. Kindler, pers. comm.) which could not be used in LD2010. For this, we had to use a temporal
relationship, alpha ∼ 0.38, to link the temperature variations to the ice δ 18 O variations. Similarly,
95
the EDML LIDIE background scenario is reduced in AICC2012 (scenario LIDIE 2) compared to the
one of LD2010 as it is based on δ 15 N rather than on firnification model. Finally, AICC2012 also incorporates TALDICE background LIDIE scenario given by the firnification model in agreement with
the δ 15 N estimate. Then, the numerous gas and/or ice stratigraphic markers, the NorthGRIP, EDML
and TALDICE LIDIE are reflected also in the analysed LIDIE for Dome C. As a consequence, if
100
the LIDIE scenarios are smaller at EDML and NorthGRIP in AICC2012 than in LD2010, this will
automatically lead to a smaller LIDIE at EDC.
Finally, it should be noted that the Datice model can be run with several interpolations from the
background scenario, i.e. a fast mode with an interpolation of the background scenario every 2 or 3
4
Fig. 2. Different tests on the EDC chronology for the choice of the best LIDIE scenario. Black line: LIDIE
background scenario from the firnification model of Goujon et al. (2003). Red line: LIDIE output scenario
when Datice is run with background LIDIE from the firnification model. Green line: LIDIE background scenario calculated from δ 15 N values (Dreyfus et al. (2010) over TII; unpublished values for MIS 5). A linear
interpolation has been applied between δ 15 N based LIDIE at the beginning and at the end of the the last glacial
period to cover the period where no δ 15 N measurements on EDC are available. Pink line: LIDIE output scenario when Datice is run with background LIDIE from δ 15 N data. Purple line: LIDIE background scenario
calculated from δ 15 N−δD scenario. It has been observed that for different Antarctic sites, δ 15 N and δD are
well correlated on an age scale (Dreyfus et al., 2010; Capron et al., 2013). We use here the correlation between
δD and δ 15 N over the last Termination to obtain a synthetic δ 15 N curve when δ 15 N data are missing. Yellow
line: LIDIE output scenario when Datice is run with background LIDIE from δ 15 N−δD scenario.
Table 1. Origin of the background parameter profiles
Accu.
Thinning
LIDIE
15
Vostok
From isotope
Accu. - FGT1
δ N − δD
EDC
From isotope
Accu. - EDC3 model
δ 15 N − δD
EDML
From isotope
Huybrechts et al. (2007)
δ 15 N − δD
TALDICE
From isotope
1D-flow model (Buiron et al., 2011)
δ 15 N − firn model
NGRIP
From GICC05
From GICC05
Firn model
5
105
points or a slow mode with use of the background scenario with its prescribed resolution (1 m for
NorthGRIP, 0.55 m for EDC, 1 m from the surface down to 125 m and then 0.5 m below for EDML,
1 m for Vostok and 1 m for TALDICE). Since the initial resolution of the background scenario and
the interpolation step may have an influence on the final chronology, we have performed tests with
several resolutions. It appears that this effect is negligible compared to the effect of uncertainties
110
associated with the tie-points or the variances associated with the background scenarios which are
thus the important parameters to be imposed (see next section).
2
Variances profiles
Each background scenario is associated with a variance. If the variance is high, Datice is allowed to
make a strong correction to the background scenario in the final chronology. On the opposite, if the
115
variance is small, the final scenarios should be very close to the background ones.
We implemented variance profiles for accumulation rate, thinning function and LIDIE that have
been slightly modified from their initial formulation in Lemieux-Dudon et al. (2010). They take into
account the depth (variance increases with depth for some sites) as well as the deviation from the
present-day conditions based on the accumulation rate values.
120
2.1
Thinning function
The variance on the thinning function is expressed as:
Z z
σA,loc
D(z)
σT (z) = cT1 + cT2 ·
dz + cT3 · max
T (z)
σA,loc
where cT1 , cT2 and cT3 are user defined constant parameters (cT2 equal c · 0.1/H where H is the
maximum depth of the input and c a user defined constant), T(z) is the thinning function, D(z)
max
the relative density, σA,loc the local standard deviation of accumulation and σA,loc
the maximum
standard deviation of accumulation. The last term was implemented in order to increase the thinning
125
variances during transitions since it has been suggested that the mechanical properties of ice can
be modified in these periods. The parameterization of this effect could be improved by modifying
also the correlation length during these periods but would require additionnal tests for a correct
parameterization. This last term is however of second order relatively to the depth dependence (Fig.
4b).
130
2.2
Accumulation rate
The variance is formulated as follows:
z
| A0 − A |
· 1 + cA1
σA (z) = σb,A ·
| A0 − A |max
zmax
with σb,A being a reference standard deviation, A0 is the mean Holocene accumulation rate, cA1 is
a constant parameter. The variance associated with the accumulation rate scenario thus increases
6
when the background accumulation rate strongly deviates from the Holocene value. The reason for
such a parameterization is that the reconstruction of accumulation rate from water isotopes through
the exponential law is semi-empirical and its extrapolation far from the present-day conditions may
be problematic.
In order to avoid too small variances, a threshold value, σm , is implemented for each ice core.
When σA is smaller than σm , then σA is recalculated as:
z
σA = σm · 1 + cA1
zmax
where σm represents the minimum values, defined by user.
A dependence from upstream origin of the ice should be considered in the future.
2.3
LIDIE
The LIDIE variance is parameterized as:
σL (z) =
σb,L
σA (z)
·
A,loc
σb,A 1 + m
mmax
A,loc
135
with mA,loc being the local mean accumulation rate and mmax
A,loc its maximum value over the length
of the core, σb,L is a reference standard deviation. In this case, the variance on the LIDIE increases
with the variance on the accumulation rate, i.e. with the deviation from present-day conditions. This
is justified by the fact that we do not have a standardized way to link LIDIE to accumulation rate or
temperature (firnification model or δ 15 N based estimate, see above).
140
An example of the resulting variances for the EDC core is presented on Fig. 3. The different coefficient values are given for each core in Table 2. The choice of variance remains necessary subjective
but the following approach has been done:
– The depth dependence of the variances associated with accumulation rate and LIDIE has only
145
been considered for sites located on a slope and not on a dome. Hence, cA1 has been assigned
a value of 1 for Vostok and EDML.
– A larger variance for LIDIE has been applied for sites where the firnification model and δ 15 N
approaches clearly disagree, i.e. for Vostok, EDML and EDC.
– A larger variance has been prescribed for EDML and Vostok thinning compared to EDC and
150
NorthGRIP because their location on a slope make the estimate of the background thinning
function from the glaciological model less certain.
– The thinning variance has been adjusted for TALDICE compared to EDC in order to avoid dating inconsistencies produced by the glaciological background scenario of TALDICE thinning.
7
Indeed, the background scenarios obtained from glaciological model for TALDICE gives an
age model that is much too young with the δD optimum of MIS 5 occurring around 110 ka
155
(Fig. 4a). This is in contradiction with available data suggesting that this optimum should
occur around 130 ka (Waelbroeck et al., 2008), with an uncertainty of several ka. It is impossible that Termination II was only 110 ka old. Using the initial variance for the thinning
and accumulation rate of TALDICE produced a quite young Termination II because of the
influence of the TALDICE background scenario on the final chronology. We therefore had to
160
increase the variance associated with thinning at TALDICE (Fig. 4b).
– The variance on EDC and NorthGRIP thinning has been adjusted so that the new chronology
of MIS 5 and MIS 4 lies between the EDC3 and NorthGRIPmodelext chronologies. These two
initial chronologies where mostly derived from different glaciological constraints over this
particular period and there is no reason why one chronology should be preferred compared to
165
the other.
Table 2. Coefficient values of the variance profiles for the different ice cores. With respect to LD2010, cT1 has
been lowered, cT2 has been adjusted for each ice core and the term cT3 added. The values of σb for accumulation
rate and LIDIE have been kept from LD2010 except the value of σb,A which has been increased for EDML.
Thinning
Accu. rate
LIDIE
cT1
cT2
cT3
σb,A
cA1
σb,C
Vostok
0.01
0.000084
0.15
0.6
1
0.7
EDC
0.01
0.000030
0.15
0.7
0
0.7
EDML
0.01
0.000078
0.15
0.5
1
0.6
TALDICE
0.01
0.000268
0.15
0.6
0
0.6
NGRIP
0.01
0.000016
0.05
0.6
0
0.6
Many test of the variances assigned to the input scenarios were performed to evaluate the sensitivity of the final solution to initial model conditions but cannot be detailed here.
3
170
Observations
The different markers included in Datice are common for Veres et al. (2013) and Bazin et al. (2013).
The database combines absolute ages, orbital markers, delta-depth markers and stratigraphic links
in gas and ice phases to synchronize our five ice cores.
The AICC2012 chronology is also constrained back to 800 ka with the use of orbital markers when
absolute markers are missing (Bazin et al., 2013).
175
Compared to the first Datice application used to produce the chronology delivered by LemieuxDudon et al. (2010), we wanted to suppress the climatic synchronization assumptions and avoid
8
Fig. 3. Variances profiles of accumulation rate (red), LIDIE (black) and thinning function (blue) as function of
age for EDC
circular synchronisation markers. We have thus removed or modified the following absolute markers:
– Climatic orbital markers derived from δD insolation matching at Vostok (Parrenin et al.,
2001).
– Speleothem point at 130.1 ka - see main text of Bazin et al. (2013)
180
– Air content orbital markers at Vostok and EDC - they have been replaced by the new table of
orbital markers as explained in Bazin et al. (2013).
– All points derived by successive transfer between the cores (Parrenin et al., 2007)
3.1
185
Absolute age markers
The absolute ages described here are obtained from independent dating of events recorded in the
cores. All absolute ages have been determined by argon dating with the standard of Kuiper et al.
(2008) (Fish Canyon sanidine at 28.201 ± 0.046 Ma). Ages of the Laschamp event, Mount Moulton
eruption and Brunhes-Matuyama reversal have in some cases slightly changed from the published
ages due to the re-calculation on the same standard.
9
Fig. 4a. Upper panel: background chronologies from glaciological models for EDC (black) and TALDICE
(green) Lower panel: output AICC2012 chronologies for EDC (black) and TALDICE (green)
Fig. 4b. Thinning variances used for AICC2012 for EDC (black) and TALDICE (green). The red points
correspond to the depth location of Termination II in the EDC and TALDICE ice cores.
190
3.1.1
Vostok
The absolute age markers for Vostok are deduced from 10 Be data. An age of 7.18±0.10 ka at 178 m
depth was assigned by comparison of the cosmogenic production of 10 Be and 14 C (Parrenin et al.,
10
Fig. 5. NGRIP. Upper panel: difference between the LD2010 and GICC05 chronologies (grey); difference
between the AICC2012 and GICC05 chronologies (black). Bottom panel: δ 18 O records on the LD2010 and
GICC05 chronologies.
2001; Raisbeck et al., 1998).
The second age marker corresponds to the Laschamp event recorded at 601 m, associated with a
195
revised age of 40.65 ± 0.95 ka (Raisbeck et al., 1987; Yiou et al., 1997; Singer et al., 2009).
3.1.2
EDC
EDC absolute ages are derived from 10 Be data and a tephra layer. The Laschamp event is recorded
at 740 m and associated with an age of 40.65 ± 0.95 ka (Raisbeck et al., 2006; Singer et al., 2009).
The Mount Moulton eruption tephra layer is observed at 1265.1 m (Narcisi et al., 2006). Its age
200
was first dated by Dunbar et al. (2008) on the Fish Canyon Tuff standard of Renne et al. (1998), and
when converted to the Fish Canyon sanidine standard of Kuiper et al. (2008) we finally obtain an
absolute age of 93.2 ± 4.4 ka. The last two ages are associated with the Brunhes-Matuyama (B-M)
reversal and its precursor, observed at 3165.5 m and 3183.5 m, and dated at 780.3 ka and 798.3
ka respectively (Raisbeck et al., 2006; Dreyfus et al., 2008). We decided to enlarge the uncertainty
205
associated with these ages (from 3.5 to 10 ka) because many different ages of the B-M reversal are
found in the literature spanning over ±10 ka. These different ages can be explained by spatially
11
asynchronous changes in the field direction and smoothing effect of the signal due to lock-in depth
uncertainties in marine sediments (Channell et al., 2010; Camps et al., 2011; Mochizuki et al., 2011;
Dreyfus et al., 2008).
210
3.1.3
EDML
No absolute ages for the EDML ice core.
3.1.4
TALDICE
No absolute ages for the TALDICE ice core.
3.1.5
215
NGRIP
As in Lemieux-Dudon et al. (2010), we used absolute ages from GICC05 to force the model to respect the GICC05 chronology. Points were selected every 60 years over the last 60 ka (not listed,
leading to 990 points). We associated an uncertainty of maximum 50 years with the purpose of
constraining AICC2012 tightly to GICC05, but in return did not use the absolute gas age markers of
table 6 of (Lemieux-Dudon et al., 2010). Note that the background parameters of NGRIP (deduced
220
from GICC05) and these markers are correlated, and this does not satify the hypothesis of independence between background and data. However, this is the only practical way to constrain the final
timescale tightly to GICC05 for the last 60 ka (Fig. 5).
3.2
Orbital age markers
The choice of the orbital markers and associated uncertainties is fully explained in Bazin et al.
225
(2013). We will here only justify the keeping or removing of some orbital age markers presented in
Bazin et al. (2013).
In the final version of AICC2012, we decided to remove three δ 18 Oatm gas age markers around
MIS 12 on the EDC ice core. Figure 6 shows a comparison of the background LIDIE (constructed
from δ 15 N measurements on EDC over this depth interval) and output LIDIE using δ 18 Oatm and
230
δO2 /N2 constraints. Clearly, the implementation of some δ 18 Oatm markers creates spurious 10 m
variations of the LIDIE during a period of 12 ka within MIS 12 and MIS 14. The background scenario for EDC LIDIE over these interglacial periods is based on δ 15 N measurements. Because no
convective zone is observed today at Dome C, we suppose that no convective zone should affect the
relationship between δ 15 N and LIDIE at this site over the past, so that the LIDIE estimate based on
235
δ 15 N measurements is robust. These are the two reasons why we raised doubts on the coherency of
these age markers. Still, removing these age markers had no significant impact on the final chronology within the uncertainty range (Fig. 6 bottom).
12
Fig. 6. Top: influence of δ 18 Oatm markers on the LIDIE parameter at EDC around MIS 12. Red crosses mark
position of the δ 18 Oatm age markers that are included (left) or not (right) in our sensitivity tests. Bottom: EDC
δD record on the resulting ice chronologies: with δ 18 Oatm age markers (blue) and without these age markers
(orange).
240
The comparison of the EDC thinning function derived from the EDC3 and AICC2012 age scales
shows variations of the same amplitude and at the same depths for the bottom part of the core (Fig.
7; Parrenin et al., 2007; Dreyfus et al., 2007). These variations also appear when only the δO2 /N2
age markers are considered. This result is then common for the two types of orbital markers, giving
us a good argument to assume that this behaviour is robust.
245
3.3
∆depth markers
∆depth markers are only given for NorthGRIP over the last glacial period. They have been obtained by a depth comparison of the δ 18 Oice and air δ 15 N profiles over the succession of DansgaardOeschger events. Because of thermal isotopic fractionation, each step in δ 18 Oice corresponding to
a rapid warming is recorded as a peak in δ 15 N in the gas phase. The ∆depth markers have been
250
measured as either the depth difference between the mid-slopes of δ 18 Oice and of δ 15 N or as the
depth difference between the peaks of δ 18 Oice and of δ 15 N. The uncertainty estimate is 2 m from
the resolution of the measurements and the difference of ∆depth estimates (mid-slopes of peaks)
(Table 3).
13
Fig. 7. Thinning function at EDC between 540-600 ka. Blue crosses mark the position of δO2 /N2 age markers
when accounted for (AICC2012, red curve) and without them (blue curve) cases.
3.4
255
Gas stratigraphic links
The gas stratigraphic links come from matching of CH4 and δ 18 Oatm variations between ice cores
following the published tie-points (references are provided in Table 4 of gas stratigraphic tie-points).
δ 15 N data are used as markers of rapid warming in the NorthGRIP ice core when CH4 data were
not available (tie-points from Capron et al. (2010)). In some cases, the associated uncertainties had
to be increased for obtaining the final chronology because of incoherencies in the final thinning,
260
accumulation rate or LIDIE scenarios. A few tie-points had also to be removed because of similar
incoherencies.
3.5
4
Ice stratigraphic links
Application
Using all the previously cited inputs, the Datice tool is capable of calculating the best compromise
265
between the background ages and the observations, using an inverse method (Lemieux-Dudon et al.,
2010). On Fig. 8 we can visualize the improvement of the EDC chronology in the 1200 to 1340 m
depth range. The background chronologies are represented by the dashed-black curve for the gas age
and dashed-grey curve for the ice age. Different observations are represented with their uncertainties:
14
Table 3. List of ∆depth markers for NGRIP included in Datice
Depth(m)
∆depth
Uncertainty (m)
2099.9
16.29
2
2123.6
15.8
2
2157.1
15.56
2
2218.2
15.7
2
2255.6
12.85
2
2345.2
11.74
2
2364.5
12.36
2
2419.31
11.6
2
2465.1
8.85
2
2506.9
8.16
1.5
2577.8
7.66
1.5
2685.1
7.15
2
2890.2
5.54
2
2895.8
4.44
1.5
2936.5
7.8
1.5
Table 4. Gas stratigraphic links between ice cores
Pairs
Nb. of points
Sources
Lemieux-Dudon et al. (2010)
Vostok-EDC
67
Loulergue (2007)
This study
Vostok-TALDICE
8
This study
Vostok-NGRIP
5
Landais et al. (2006)
Schilt et al. (2010)
EDC-EDML
64
Loulergue et al. (2007)
Loulergue (2007)
This study
Buiron et al. (2011)
EDC-TALDICE
22
EDC-NGRIP
6
Schilt et al. (2010)
EDML-TALDICE
13
Schüpbach et al. (2011)
Schüpbach et al. (2011)
Lemieux-Dudon et al. (2010)
EDML-NGRIP
45
Schilt et al. (2010)
Capron et al. (2010)
NGRIP-TALDICE
25
Buiron et al. (2011) (revised NGRIP depth)
15
Table 5. Ice stratigraphic links between ice cores
Pairs
Nb. of points
Vostok-EDC
104
Sources
Udisti et al. (2004)
Parrenin et al. (2012b)
Ruth et al. (2007)
EDC-EDML
240
Severi et al. (2007)
This study
EDC-TALDICE
102
EDC-NGRIP
2
EDML-NGRIP
86
Severi et al. (2012)
Loulergue et al. (2007)
Vinther et al. (2013)
Svensson et al. (2013)
some gas stratigraphic links (blue squares), some ice stratigraphic links (red squares) and absolute
270
ice ages (yellow triangles). After applying the inverse method, we finally obtain the blue and red
curves corresponding to the best compromise between the background and observations for the gas
(blue) and ice (red) chronologies. For example, we can see that at 1200 m depth the previous gas age
was 80.5 ka (83.5 ka for the ice phase), now the new gas age is 81.5 ka (84.5 ka for the ice). Note that
the blue and red curves necessarily fit perfectly the ice and gas stratigraphic markers (red and blue
275
squares) because these stratigraphic markers are initially only given as depth constraints on each ice
core, their respective ages are then calculated on the new chronology. On Fig. 8, the stratigraphic
points have thus been placed corresponding to their calculated age on the new chronology. The error
bars stand for the initial age uncertainties associated with these stratigraphic links.
5
280
Uncertainty attached to the AICC2012 chronology
The calculation of the age uncertainty is done exactly the same way as in Lemieux-Dudon et al.
(2010) and presented in the main text of Bazin et al. (2013).
The error on the gas age is currently defined as the error on the ice age plus an error on the depth.
This overestimates the error when the stratigraphic links are provided on the gas phase (in this case,
the gas age uncertainty should be smaller than the ice age uncertainty). The two uncertainties are
285
close, with differences of only a few centuries. As a result, we have expressed the uncertainty for
each depth as the maximum between gas and ice uncertainty on the final AICC2012 chronology. An
exception was made for EDC over the last 60 ka because of the presence of many ice stratigraphic
markers between EDML and EDC. In this case, the ice age uncertainty should be much smaller than
the gas age uncertainty, mainly governed by uncertainty on the LIDIE determination. The high den-
290
sity of ice stratigraphic links with very small associated uncertainty (cf Table 5) means that the EDC
and EDML ice age uncertainties should be similar and equal to the EDML ice age uncertainty. We
16
EDC Chronology
98000
96000
AICC2012 age (a B1950)
94000
bkg ice age
new ice age
bkg gas age
new gas age
age marker
ice tie-point
gas tie-point
92000
90000
88000
86000
84000
82000
80000
1200
1220
1240
1260
1280
1300
1320
1340
Depth (m)
Fig. 8. Visualization of the Datice tool mechanism on the period 80 ka to 98 ka of the EDC ice core.
have thus assigned the values of EDML gas age uncertainty for the EDC ice age one over the last
60 ka. Moreover, the NGRIP uncertainty calculated by Datice for the last 60 ka has no meaning (not
shown on Figure 10) as we have artificially constrained AICC2012 on GICC05 with age markers
295
associated with small uncertainties (less than 50 years). As a result, the uncertainty of AICC2012
for NGRIP should be taken as the one of GICC05 (1 sigma = 1/2 MCE) over the last 60 ka.
Figure 9 shows the calculated error by DATICE (1 sigma) for the 5 ice cores on the AICC2012
chronology. As expected, the error increases with depth because of : (1) the increase of variance
300
associated with background scenario, (2) less numerous absolute, orbital or stratigraphic constraints
with depth, (3) the increase of uncertainties attached to data constraints with depth, and (4) the fact
that error propagation applied to the ice age equation as a function of accumulation, and thinning
cumulates the errors at each depth level. This is particularly visible for the NorthGRIP chronology
where the numerous absolute tie-points over the last 60 ka are associated with an uncertainty of
305
1-50 years and much less data constraints prior to 60 ka. In presence of numerous age markers, the
uncertainty of the chronology decreases as sigma/sqrt(N), when N is the number of markers. For
example, this explains why we observe an error of ∼4 ka over a period constrained with several age
markers of 6 ka uncertainty.
310
Focussing now on the last 60 ka, it is possible to explain the influence of the different inputs on
the uncertainty of the final chronology (Fig. 10). In the absence of any absolute or stratigraphic tie-
17
18
δ Oice (‰)
8000
-36
6000
-40
4000
2000
-44
6000
-38
4000
-40
2000
-42
0
-42
-44
-46
-48
-50
-52
18
δ Oice (‰)
ECIDLAT
8000
-36
δ Oice (‰)
0
-34
18
LMDE
kotsoV
δD (‰)
8000
6000
4000
2000
0
8000
-420
6000
-440
4000
-460
2000
-480
0
)sraey( ega eci eht no noitaived dradnats
PIRGN
-32
CDE
δD (‰)
8000
-380
6000
-400
4000
-420
2000
-440
0
0
200000
400000
600000
800000
Ice Age (a B1950)
Fig. 9. δ 18 Oice records for the 5 ice cores on the AICC2012 chronology (blue) and standard deviation on ice
ages for each ice core chronology (red).
points, the uncertainty will only be given by the variance associated with background scenario, hence
much larger in the case of TALDICE than for EDC given our parameterization of variance (Table
2). Then, in the vicinity of stratigraphic or absolute tie-points, the uncertainty will be decreased
315
according to (1) the uncertainty of the tie-point itself and (2) the age uncertainty of the second ice
core used in the case of stratigraphic tie-point. In Figure 10, we can separate different phases:
– From 0 to 11 ka, the main tie-points are volcanic ice stratigraphic tie-points. The uncertainty
associated with these tie-points is small, as well as the uncertainty associated with thinning
function and accumulation rate (close to present-day conditions and small depth). The smallest
320
uncertainty for Antarctic ice cores is observed for EDML due to its stratigraphic links with
NorthGRIP, whose chronology is given with a very small uncertainty (tuned to GICC05).
– Between 11–16 ka, we still have a few volcanic links but the chronology is mostly driven by
methane links to the NorthGRIP ice core. Methane links are associated with larger uncertainties and with a more sparse resolution than volcanic tie-points. This leads to a general increase
325
of the uncertainties of the Antarctic chronologies.
– The period 16–26 ka, roughly corresponding to MIS2, has the particularity of not being constrained with any marker for TALDICE. As a consequence, the final error is only function
of the background variances, leading to an important increase of the chronology uncertainty
especially for the TALDICE chronology that has the largest background variance for the thin-
330
ning.
– Between 26 and 40 ka, the presence of (few) volcanic and (several) methane links, reduces the
chronology uncertainty to the same level as during the last deglaciation.
18
– The Laschamp event is recorded as an absolute age marker on EDC and Vostok, and is reflected in the other ice cores through the volcanic and methane links. After the Laschamp
event, we observe an increased uncertainty for all Antarctic ice core due to the loosening of
335
constraints.
TALDICE
1000
500
1000
volcanic tie-points
500
no tie-points
3000
)sraey(
)sraey(
methane tie-points
methane tie-points
Laschamp
ytniatrecnu ega
ytniatrecnu ega
1500
EDML
)sraey(
0
ytniatrecnu ega
)sraey(
ytniatrecnu ega
1500
0
Vostok
2000
1000
0
1500
EDC
1000
500
0
0
10000
20000
30000
40000
50000
60000
AICC2012 age (a B1950)
Fig. 10. AICC2012 uncertainty for TALDICE, EDML, Vostok and EDC over the last 60 ka.
6
Comparison with other chronologies
The comparison between EDC3 vs AICC2012 is discussed in the main text. Here we compare
AICC2012 with other chronologies.
340
6.1
AICC2012 vs Suwa and Bender (2008)
Suwa and Bender (2008) have built a chronology for the Vostok ice core over the last 400 ka using
δO2 /N2 and δ 18 Oatm orbital markers. Because the same markers are used in AICC2012, we expect
some similarities between both chronologies. They are indeed very close: 3.5 ka max difference
within the last glacial period due to the numerous stratigraphic links with other cores, otherwise less
345
than 2 ka difference over the last 400 ka (Fig. 11).
6.2
AICC2012 vs Kawamura et al. (2007)
Kawamura et al. (2007) have constructed the Dome F chronology back to 360 ka using δO2 /N2
constraints (DFO-2006). AICC2012 appears consistent with the Dome F orbital chronology, within
2 ka, except for the last glacial inception (up to 5-6 ka difference with Dome F, and only 1.5 ka
19
350
difference with Suwa and Bender (2008), Fig. 11). This results from different relationships between
δO2 /N2 and δD records that are not really identical during MIS 5 at Dome F and Vostok. The
time difference between the AICC2012 timescale and Dome F DFO-2006 timescale is of the same
amplitude as the difference between DFO-2006 with the EDC3. To enhance the comparison, it
would be very interesting to compare also the AICC2012 gas chronology with Dome F gas age scale
355
using methane records when it will be published for Dome F.
Fig. 11. Water isotopes of Dome F (green) and Vostok with different chronologies: Suwa et Bender 2008
(orange) and AICC2012 (black).
6.3
AICC2012 vs Parrenin et al. (2013) over the last deglaciation
Parrenin et al. (2013) have recently derived a new chronology for the EDC gas and ice records over
the last deglaciation using δ 15 N constraints for LIDIE determination at Dome C. We do not compare
AICC2012 to Parrenin et al. (2013) in terms of absolute ages since this age scale was built only for
360
inferring the CO2 / Antarctic temperature phasing. In term of relative phasing, AICC2012 confirms
the findings of Parrenin et al. (2013), with no significant phase shift between CO2 and Antarctic
temperature at the onset of Termination I and Younger-Dryas and a small lag of CO2 (slightly larger
by 100-400 years in AICC2012) at the onset of Bølling-Allerød and Holocene.
6.4
365
AICC2012 vs speleothems
Following Fleitmann et al. (2009) who suggested that CH4 abrupt variations over DO events and
changes in speleothem δ 18 O of calcite are in phase, we have compared some CH4 abrupt transitions
in AICC2012 with changes in Chinese speleothem records of calcite δ 18 O. This exercise has already
been proposed to validate the Dome F chronology based on δO2 /N2 measurements. The comparison
is showed on Table 6. The AICC2012 chronology is in very good agreement with the speleothem
20
370
ages (within the uncertainty of the AICC2012 chronology; Cheng et al., 2009, 2012; Wang et al.,
2001, 2008), which give us confidence in the methodology used to construct this timescale.
Table 6. Comparison of AICC2012 with speleothems.
Events
AICC2012 age (ka)
DO-8
38.29
DO-11
43.43
DO-19
72.57
DO-22
90.52
Speleothem age (ka)
MCL-Hulu
38.32
MSD-Hulu
38.23
MCL-Hulu
43.81
MSD-Hulu
44.08
MCL-Hulu
72.17
SB-22-Sanbao
71.7
SB25-1-Sanbao
91.52
SB22-Sanbao
90.8
SB25
129.04
SB11
129.08
B61
243.1
LZ15
243.6
B61
336.4
LZ15
337.6
onset MIS5
128.88
onset MIS7
243.41
onset MIS9
337.2
onset MIS11
426.2
Kesang
426.6
Onset MIS13
492.5
Kesang
492.1
21
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