Introduction
Our knowledge of changes in the atmospheric mixing ratios of the important
greenhouse gases (GHGs) CO2, CH4, and N2O beyond the instrumental
record is mainly based on discrete data points derived from gas extractions
in polar ice cores. While there are recent developments towards continuous
CH4 records using gas extraction and measurement systems coupled to
continuous-flow analysis systems
, this
approach has not yet been developed for the other two important GHGs, CO2
and N2O. To obtain the continuous GHG records, necessary for transient
climate simulations, these discrete data have to be processed in order to
extract those variabilities that have climatological significance and to
account for measurement uncertainties.
All three GHG records have special features which need some attention during data compilation:
For some of the CO2 records obtained from different ice cores, there exist significant and as yet unexplained offsets .
These offsets need to be addressed in our data compilation.
Due to the dominance of CH4 sources in the Northern Hemisphere, the CH4 concentrations are higher in records from Greenland than from Antarctica
referred to as interpolar difference; e.g..
In situ production of N2O connected to high mineral dust values leads to unreliable N2O concentrations e.g., particularly
during glacial peak times and in records from Greenland, for which special care has to be taken during data selection.
Rapid changes are most pronounced in CH4 and N2O (and to some extent
also in CO2) during millennial-scale climate variability, or the so-called
Dansgaard–Oeschger (D/O) events. Therefore, only well synchronised ice cores
from Greenland and Antarctica can be used if records from the Northern and
the Southern Hemisphere are to be merged into one global record. However,
even with the recent efforts on ice core age scale development, there remain
issues with this north–south synchronisation. For example, inconsistencies
in the timing of abrupt changes in CH4 concentration in the North
Greenland Ice Core Project (NGRIP), EPICA Dronning Maud Land (EDML), and
Talos Dome (TALDICE) ice cores have been identified for several D/O event
transitions if based on AICC2012, the Antarctic Ice
Core Chronology of four major Antarctic ice cores .
Furthermore, when comparing data from the West Antarctic Ice Sheet Divide ice
core (WDC) on its most recent age scale, WD2014, with data from Greenlandic
ice cores, the chronology of the latter (GICC05) has been stretched by
0.63 % in order to find the best match to the absolute U/Th-dated paleo
record of Hulu Cave .
In order for these issues to be overcome, careful data selection and
processing are required. Here, we document our assumptions during data
compilation and calculate continuous time series of CO2, CH4, and
N2O via spline-smoothing with a
nominal temporal resolution Δt of 1 year from the penultimate glacial
maximum until present, the time window of interest for PALMOD, the German
Paleo Modelling Project (www.palmod.de). Note, however, that this
Δt represents not the true resolution but only the typical spline
average for each year and that the ice core information represents a low-pass
filtered signal of atmospheric variability concentrations by the slow bubble
enclosure process. Furthermore, the resulting spline is of restricted use for
in-depth analysis with a focus on the rates of changes in the three GHGs,
since the spline smoothing suppresses the most abrupt changes in the GHGs.
Here, we extend the ice-core-based paleo records using instrumental data up
until the beginning of the year 2016 CE, including several decades of
overlap between the ice core and instrumental data. The resulting continuous
GHG records might also be of interest and may be used in the Last
Deglaciation experiment within PMIP4 (Paleoclimate Modelling Intercomparison
Project phase 4) . Note that different GHG data sets
have so far been chosen to force transient simulations for the last 21 kyr
in , but well-motivated different set-ups (e.g. using
the GHG splines compiled here) are possible within PMIP4.
Previous splines (similar to our approach here but not identical in detail)
have also been proposed to be used in interglacial experiments of the
Holocene within PMIP4 . Within the most recent
model intercomparison project, the Coupled Model Intercomparison Project
Phase 6 (CMIP6), a slightly different compilation of GHGs for historical
times, or the Common Era, has been presented .
While this alternative approach has its focus on the time since 1850 CE, its
data compilation nevertheless extends back until the year 0 CE, based solely
on the Law Dome ice core in non-instrumental times
. We will finally
compare our splines with these forcing data sets proposed by
to be used within CMIP6.
As will be seen in detail in the next section, the mathematical formulation of
the spline smoothing method needs information on the uncertainties or errors in the data points supporting the spline. These data uncertainties represent
the precisions of individual measurements (1σ errors) and are of the
order of a few parts per million for CO2 or a few parts per billion for CH4 and N2O. The
uncertainty in the final spline, however, is larger, since the applied
smoothing, which depends on the chosen cutoff periods, adds some additional
uncertainty. Furthermore, the estimates of the radiative forcing based on
these three GHGs given here are even more uncertain, since the calculations
of the radiative forcing themselves are based on models
with an embedded intrinsic uncertainty of
about ∼ 10 % . Note that the
calculations of the GHG radiative forcing provided here are just a first-order approximation, since we use the simplified expressions of
, while full climate models calculate radiative
forcing internally, when forced with variable GHG concentrations.
In the following, ages are either given in years CE (Common Era) or in years
BP (before present), where present is defined as 1950 CE. We define the
onset of anthropogenic activities at 1750 CE (or 200 BP), based on the
timing of the increase in CO2 and CH4 in our final splines, although we
acknowledge that the onset of the Anthropocene is still debated
e.g..
Details on the spline smoothing method
The numerical code for spline smoothing is based on ,
but see also and for further
details, discussions, and applications. It offers the possibility to select
different cutoff periods for different time intervals or parts of the input data
set, which is needed when data spacing is variable throughout the data set.
In a smoothing spline a cost function is minimised. This cost function
includes two terms: (i) the error-weighted deviation between the spline value
and the actual data value and (ii) the curvature of the spline, represented
by its second derivative. A parameter λ defines how much weight is
given to the curvature. For a large λ, the optimisation results in
low curvature, i.e. a very smooth spline and relatively large deviations
from the original data. Similarly, increasing errors in the data results in a
smoother spline for a given λ. In other words, the smoothing of the
spline depends on both the assumed errors in the data and the parameter
λ.
According to Fourier, each time series can be represented by a sum of sine
functions. Since a smoothing spline acts as a low-pass filter, high
frequencies are dampened in the spline. The period at which the amplitude is
attenuated to 50 % is defined as the cutoff period Pc
e.g.. The parameter λ is linked to
Pc as described in detail in Eq. () below.
Let us assume input data are tj, yj, and vj corresponding to time,
value, and error (1σ). For a given interval of the input data, an
average error, v, and an average data spacing, Δt, can be computed.
The link between the cutoff period (Pc), the data spacing
(Δt), and the 1σ error in the input data (v) is
Pc=2π⋅λ⋅Δt⋅v20.25.
In the following, we prescribe Pc and can calculate λ
following the given relationship in Eq. (). We choose a
Pc value such that it is much larger than the temporal resolution
of the data, Δt, to avoid overfitting. However, since the choice of
Pc is also partially subjective, we investigate its influence on
the final spline by sensitivity studies, in which Pc is varied by
±50 %. One aspect of Eq. () is that Pc depends
only weakly on Δt.
Locations of the different data sources, ordered north to south.
Individual sites of the NOAA observational network are not explicitly
mentioned here, when they only contribute to global mean calculations. SH
CH4: Southern Hemisphere CH4.
Site
Latitude
Longitude
Data used here
NGRIP
75.10∘ N
42.32∘ W
N2O
GRIP
72.583∘ N
37.633∘ W
comparing to SH CH4
Barrow
71.3230∘ N
156.6114∘ W
comparing to SH CH4
Mauna Loa
19.5362∘ N
155.5763∘ W
CO2
Law Dome1
∼ 66.73∘ S
∼ 112.83∘ E
CO2, SH CH4, N2O
Talos Dome (TALDICE)
72.817∘ S
159.183∘ E
CO2, N2O
EPICA Dronning Maud Land (EDML)
75.0∘ S
0.067∘ E
CO2
EPICA Dome C (EDC)
75.1∘ S
123.35∘ E
CO2, SH CH4, N2O
Taylor Glacier2
∼ 77.77∘ S
∼ 161.7∘ E
N2O
WAIS Divide Ice Core (WDC)
79.468∘ S
112.086∘ W
CO2, SH CH4
Siple Dome
81.66∘ S
148.82∘ W
CO2
South Pole1
90∘ S
59∘ E
CO2, SH CH4
Notes: 1 The data compilation of
and on
CO2, SH CH4, and N2O uses
data from the Law Dome deep ice core and from various shallow ice and firn cores in its vicinity but also from atmospheric data
from Cape Grim and firn core data from the South Pole. While we here state all the relevant positions, the original source of the
individual data points is not marked in Tables , , and
or in the data files uploaded to PANGAEA, where data are only labelled with “Law Dome” as their source. Please see the original references for further details.
2 Data taken from Taylor Glacier are based on a “horizontal ice core”,
which does not have a point location like all other sites do.
Let us now assume we have a data set with variable data spacing, for which we
would like to apply different smoothing depending on Δt. We proceed
by modifying λ to follow the predefined individual Pc for
each interval of the input data set as follows.
Reference interval:
We take the most recent time window, consisting of instrumental measurements,
as reference interval. λ is computed using Eq. () for the
given cutoff period, average data spacing, and average error for this first
interval.
Other intervals:
A modified λ′=λ⋅s2, with λ taken from the reference interval, is used for other intervals, implying that for the reference interval s=1 and λ′=λ.
The scaling factor s is chosen to gain the desired Pc′ after
s=(Pc′2π)2(λ⋅Δt′)⋅v′,
where Pc′, Δt′, and v′ are the cutoff period, the mean
data spacing, and the mean error for the interval under consideration.
An intermediate product with tj,yj, and vj′ is calculated, in which
the revised uncertainty vj′ is defined by Eq. () using the
cutoff-related scaling factor s. From this intermediate product, the final
spline with time-dependent Pc is calculated. In doing so, the
approach abstains from any further merging of partial time series to a final
spline. The resulting spline follows the prescribed cutoff periods throughout
the whole time series. However, for every change in cutoff period from
Pc1 to Pc2 a transition window around the time of
change, tchange, exists (defined as tchange±Pct, with Pct being the smaller of Pc1 and
Pc2), in which the variability of the spline transits from one
cutoff period to the other and does not follow the prescribed
Pc exactly. The summaries of the spline calculation contained in
Tables , , and show
the effect of this transition in a column of averaged realised cutoff
periods, which are always slightly lower than the prescribed cutoff periods.
Data used to construct the CO2 spline.
Time (in BP)
Time (in CE)
Source
Age scale
Citation
-66 to -8
2016 to 1958
Mauna Loa1 (monthly)
–
-10 to 1949
1960 to 1
Law Dome2
as in references.
200 to 1210
1750 to 740
WDC3
WD2014
1902 to 10 954
48 to before CE
EDC4
AICC2012
8807 to 22 909
–
WDC6
WD2014
21 926 to 48 720
–
Siple Dome
GICC05
38 127 to 69 672
–
Talos Dome5
AICC2012
43 205 to 113 429
–
EDML
AICC2012
104 331 to 156 306
–
EDC
AICC2012
124 859 to 153 135
–
EDC
AICC2012
Notes: 1 Data taken from
ftp://aftp.cmdl.noaa.gov/products/trends/co2/co2_mm_mlo.txt. 2 Law
Dome data are taken from various sources; see references for details. They
are available from 2001 CE to 1 CE; only data before 1960 CE are taken for
the spline. 3 WDC data are available from 10 BP to 1217 BP, but not all were
used here. Published WDC data have been shifted by -3.13 ppm (see Fig. A1).
4 EDC data are available from 350 BP to 22 236 BP, but not all were used here.
5 Talos Dome data exist from 34 360 BP but contain some outliers before
38 kyr BP. 6 Published WDC data have been shifted by -6.06 ppm (see
Fig. A2).
The uncertainties of the final splines are calculated from the square root of
the sum of squares of three individual errors (σ=σ12+σ22+σ32). Pc error (σ1): Mean difference from the standard
spline by smoothing with cutoff periods Pc which are varied by
±50 %.
Data resolution error
(σ2): The importance of uncertainty of the individual data points
vi for the spline smoothing by setting all vi to 0.01.
Monte Carlo error (σ3): Repeated
(n=500) realisation of the data sets yi by randomly choosing data points
out of the normally distributed data using the given uncertainty ranges
vi.
Greenhouse gas data compilations and final splines
Our GHG data compilations are based on various data sets from 13 global
distributed locations. An overview of the locations, including latitude and
longitude, is provided in Table . Please note that CH4
data are only included from Southern Hemisphere records. These pointwise data
sets are supplemented for the instrumental period by some global mean data
from the National Oceanic and Atmospheric Administration (NOAA) observational
network, including Radiatively Important Trace Species (RITS) nitrous oxide
data from the Earth System Research Laboratory (NOAA/ESRL) halocarbons
program and nitrous oxide data from the NOAA/ESRL halocarbons in situ
program, which consists of globally distributed measurements. Individual data
uploaded to the database PANGAEA, based on
and are
all labelled as “Law Dome” data for simplicity, although these two studies
contain data from the Law Dome deep ice core, data from various shallow cores, and
atmospheric data from Cape Grim and the South Pole. Please refer to the original publications for a precise
characterisation of the sample origins.
CO2 spline covering all data: 2016 CE–156 307 BP.
Error bars around the ice core data points are ±2σ. WDC data have
been adjusted to reduce offsets; see text for details. In (a) the
right axis contains the resulting radiative forcing ΔR[CO2]=5.35⋅ln(CO2/(278ppm)) W m-2
calculated after . (b) Total
uncertainty of the spline based on three individual error sources; see text
for details. (c) Temporal resolution (Δt) of the CO2 data
points underlying the spline on a log scale. Additionally, the prescribed
time-dependent cutoff period Pc is plotted, including its
variation by ±50 %, which has been used to determine σ1.
Statistics of the CO2 spline. Interval: iCO2; s:
scaling factor to fulfil the constraints given by the prescribed cutoff
period Pc; Pc‾: average realised cutoff
period; Δt: mean data spacing; v: mean 1σ error – exact
time framing is given by the age of the first (tstart) and last
(tstop) data point of the interval (in years BP); N: number of
data points within interval. In the last column the underlying data source is
briefly mentioned; see Table for details and citations.
iCO2
s
Pc
Pc‾
Δt
v
tstart
tstop
N
Data source
–
yr
yr
yr
ppm
yr BP
yr BP
–
1
1.00
4.0
4.0
0.1
0.3
-66.0
-8.1
699
Mauna Loa, Law Dome
2
2.65
20.0
18.5
0.4
1.3
-8.0
19.2
69
Law Dome
3
7.49
40.0
37.5
1.0
1.2
20.6
117.1
96
Law Dome
4
79.91
160.0
151.0
4.3
0.9
123.1
997.8
206
Law Dome, WDC
5
388.87
500.0
468.8
13.0
1.0
1006.0
1796.5
62
Law Dome, WDC
6
5377.63
3000.0
2883.1
93.3
1.0
1814.0
8994.9
78
Law Dome, WDC, EDC
7
1532.28
1600.0
1519.4
48.8
1.3
9060.2
10 962.5
40
WDC, EDC
8
357.66
600.0
567.4
28.1
1.0
11 060.3
18 463.6
264
WDC
9
1563.85
2000.0
1806.4
176.2
1.1
18 559.8
109 840.0
519
WDC, Siple D, Talos Dome, EDML, EDC
10
1690.90
3000.0
2593.3
383.9
1.5
110 555.4
127 829.0
46
EDML, EDC
11
225.60
1000.0
921.5
257.3
1.5
128 024.5
134 970.7
28
EDC
12
530.27
2000.0
1853.3
871.7
1.4
135 387.0
156 306.8
25
EDC
Atmospheric CO2
There are small offsets of a few parts per million in measured CO2
concentration between records obtained from different ice cores
e.g..
These offsets may be related to inter-laboratory differences in the
calibration or potentially due to in situ artefact production of CO2 in
the ice archive. For a detailed discussion, see and the
supplement to . In addition to these offsets, the
amplitudes of GHG variations can differ from one core to the next due to the
site-dependent bubble enclosure characteristics, which act as low-pass
filtering. Offsets require the adjustment of individual records to avoid
spurious CO2 changes when linking different records from different
laboratory and ice cores. Ice core data are considered here on the best (most
recent) age model available, whose details are contained in
Table . AICC2012 refers to the most recent Antarctic Ice
Cores Chronology, providing age models for EPICA Dome C (EDC), EDML, Talos
Dome, Vostok, and the NGRIP record . The
CO2 record from WDC is used here on its more recent age scale WD2014 to
have the timing of CO2 and the other two GHGs consistently on the same
chronology. Using WD2014 instead of the original chronology WDC06A-7 shifts
the WDC CO2 time series towards younger ages: by about 100 years during
Termination I and by about 10 years during the last 1.2 kyr.
Our CO2 data compilation extends to ∼ 156 kyr BP, at which point in
time well-resolved CO2 records stop. The full CO2 spline covering the
whole time window from 2016 CE to 156 kyr BP is plotted in
Fig. , including its uncertainty estimate (b) and the
temporal resolution, Δt, of the compilation of data points (c). The
11-point running mean of Δt is around 100 years in the Holocene,
between 20 and 50 years during Termination I, varies between 40 and 200 years
between 20 and 70 kyr BP, and rises to 1000 years prior to 70 kyr BP.
Across Termination II, Δt decreases to an average of 200 years.
The CO2 data contributing to this spline are described below (further
details in Table ):
Comparison of our final spline data with values used for PMIP4
experiments for 21 kyr and 1850 CE, 6 kyr, and 127 kyr . Please note that the PMIP4 values
should be millennial-scale mean numbers to serve as forcing values for time
slice experiments, while the values given from our study are snapshots of
the given points in time. Furthermore, we calculate SH CH4 values, while
in PMIP4 the global CH4 is given.
GHG
Unit
1850 CE
6 kyr
21 kyr
127 kyr
Our study:
CO2
ppm
286.1
264.4
187
274
SH CH4
ppb
795
553
382
660
N2O
ppb
271
261
206
257
PMIP4:
CO2
ppm
284.6
264.4
190
275
global CH4
ppb
808
597
375
685
N2O
ppb
273
262
200
255
Details of the CO2 spline.
Light and dark grey bands around the spline represent ±1σ and
±2σ, respectively; error bars around the ice core data points are
±2σ. (a) Instrumental times (1950–2016 CE);
(b) 0–2000 BP; (c) Termination I;
(d) 0–40 kyr BP without the Law Dome data showing the
anthropogenic rise; (e) 40–90 kyr BP;
(f) 90–160 kyr BP. WDC data have been adjusted to reduce offsets; see text for details. Dashed line labelled CMIP6 in panels (a) and (b) is the
compiled CO2 record to be used in CMIP6 experiments for the last 2 kyr
.
Our CO2 data compilation uses instrumental monthly CO2 data taken from the NOAA network up to the beginning
of the year 2016 CE, or -66.0 BP .
We here choose to take only the data of the original so-called
“Keeling curve” started by C.D. Keeling at NOAA's Mauna Loa Observatory in
1958 CE, and since 1974 CE independently measured by both the Scripps
Institution of Oceanography (scrippsco2.ucsd.edu) and NOAA
(www.esrl.noaa.gov/gmd/ccgg/trends/) (Fig. a).
There is a small interpolar difference in CO2 concentrations, with higher
concentrations in the north than in the south; e.g. the 10-year averages
from 2006 CE to 2015 CE were 3.5 ppm lower at the South Pole than at Mauna
Loa and 1.4 ppm higher at Barrow (Alaska) than at Mauna Loa
. We therefore assume that CO2 data from
Mauna Loa are a good approximation of the global average concentration.
However, in practice this interpolar difference cannot be determined prior to
the instrumental records since CO2 is only measured on ice cores from
Antarctica, as the higher impurity content gives rise to artefacts in any
CO2 measurement based on Greenlandic ice cores e.g..
The firn and ice data compilation of Law Dome, which also contains some
contributions from Cape Grim and the South Pole – available for the time from
1996 CE to 1 CE (-46 BP to 1949 BP)
and 2001 CE to 154 CE
(-51 BP to 1796 BP) – overlap consistently with
direct atmospheric measurements. We therefore take these data as our
reference time series for the Common Era (Fig. b) but
include only the data from year 1960 CE and older in our spline compilation.
In doing so, we use the more precise and temporally more highly resolved
instrumental data for later times.
Data from the WDC ice core exist for the times of 11–1210 BP, or 1939–740 CE and for Termination I (see point no. 5
below). These WDC data overlap with the Law Dome data
; however, the
available high-resolution CO2 records from different ice cores (Law Dome,
WDC, EDML) show some apparent offsets . Whilst the CO2
data in all three ice cores converge on similar concentrations during the
anthropogenic rise in CO2 after 1750 CE, the WDC CO2 concentrations
are slightly higher than CO2 in the other two ice cores prior to 1750 CE.
In pre-anthropogenic times, EDC data not contained in the comparison of also agree more with the Law Dome data than with those of
WDC. We therefore choose to take WDC data only prior to the anthropogenic
rise (200–1210 BP or 1750–740 CE). Furthermore, WDC data are adjusted by
-3.13 ppm to bring them into agreement with the Law Dome CO2 record. The data from Law Dome and
the adjusted data from WDC contribute to our data compilation between
200–1210 BP. The mean temporal resolutions of both ice core CO2 records
within this time interval are 8 and 13 years for WDC and Law Dome,
respectively. The amplitude of the CO2 minima around 300–400 BP is
controversial . In our final spline, little
of the large negative anomaly in CO2 contained in the Law Dome data is
preserved, since we smoothed the ice data in this time window with a cutoff
period of 160 years (Fig. b). The time between the start
of the anthropogenic rise (1750 CE) and the start of the instrumental record
(1958 CE) is only supported by the Law Dome data in our compilation
(Fig. b). Further details on this adjustment of the WDC
data are covered in Fig. A1 in the Appendix.
EDC data exist between 350 BP and the Last Glacial Maximum (LGM)
and
further back in time (see point no. 7 below). They overlap with the Law Dome
data between 350 and 1950 BP (Fig. b) without any apparent
offset, and therefore no adjustment is applied to the EDC data. However, EDC
data are only included in our compilation for the interval 1.9–11 kyr BP because Law Dome and WDC data provide a better resolution for the interval
younger than 1.9 kyr BP, whilst the WDC data are the more highly resolved record
for the interval older than 11 kyr BP (Fig. c).
Termination I is best covered by data from WDC . WDC data
are available for 8.8–22.9 kyr BP and are adjusted by -6.06 ppm
(Fig. c). This difference corresponds to the
duration-weighted mean offset between the WDC and EDC records during three
intervals of relatively constant CO2 (22.3–18.5 kyr BP: WDC (n=29)
194.75±2.44 ppm; EDC (n=21) 188.22±2.32 ppm; 14.5–13.0 kyr BP:
WDC (n=45) 243.02±2.44 ppm; EDC (n=9) 237.57±1.42 ppm;
11.5–9.0 kyr BP: WDC (n=36) 269.97±3.67 ppm; EDC (n=27)
264.24±1.88 ppm). The intervals have been selected to minimise the
influence of potential age scale differences between the two records. Only
those EDC studies focusing on CO2 measurements
have
been considered here, rather than those with a main focus on δ13C
, which have a lower precision in CO2
concentrations. More details on this adjustment of the WDC data during
Termination I are found in Fig. A2. Our offset corrections imply an
absolute CO2 concentration uncertainty of about 5 ppm (accuracy). The
corresponding uncertainty in the radiative forcing ΔR[CO2]
following a simplified expression of ,
ΔR[CO2]=5.35⋅ln(CO2/(278ppm))Wm-2,
is 0.15 or 0.09 W m-2 for a reference concentration of 180 or
280 ppm, respectively. This uncertainty is larger than the measurement
uncertainty (precision) of the order of 1 ppm attached to individual data
points which is used to determine the smoothing spline through the data.
Further back in time all ice core records used have some data overlap with their successive records.
There are some small offsets between the different records for
details, see. We treat them all alike, so the spline averages over
all cores, and we select a large cutoff period of 2000 years for the interval
18.5–110 kyr BP to account for those uncertainties. Rapid variations in
CO2 during glacial times (Fig. d–f) are best recorded
in the Siple Dome record between 21.9 and 48.7 kyr BP ,
the Talos Dome record between 34.4 and 69.7 kyr BP ,
and the EDML record between 43.2 and 113.4 kyr BP
. Talos Dome CO2 data include some
outliers in the interval 34–38 kyr BP that disagree with CO2 records
from other ice cores by more than 10 ppm. Therefore, Talos Dome data are
only considered for the times older than 38.0 kyr BP.
From 104.3 to 156.3 kyr BP – the interval spanning the last glacial
inception, the last interglacial, Termination II, and the penultimate glacial
maximum (Fig. f) – the EDC CO2 record is used in the
compilation .
For every supporting data point j a 1σ uncertainty or error vj
has to be assigned in order to be able to calculate the smoothing spline (see
Sect. for details). A nominal uncertainty of 0.3 ppm is
assigned to the Mauna Loa data, which is for conservative reasons slightly
higher than the generally stated measurement uncertainty of 0.2 ppm
(https://www.esrl.noaa.gov/gmd/ccgg/about/co2_measurements.html).
Uncertainties for the ice and firn data are taken either as reported or set
to 0.5 ppm if the reported standard deviation is missing or less than
0.5 ppm. For Law Dome data published in
, we take the reported uniform
uncertainty of 1.1 ppm. Note that the adjusted ice core offset between WDC
and the other ice cores is not considered in our uncertainty calculation as
this represents a systematic error.
The data selection as described above then leads to n=2152 data points
including 20 ages with duplicate entries. These duplicates are averaged
(reducing n to 2132) and the assigned uncertainties based on this
averaging.
To account for the variable temporal resolution of the data points
(Fig. c) whilst preserving as much of the abrupt changes in
CO2 during Termination I as possible e.g., the
spline is divided into 12 intervals with different nominal cutoff periods that vary between 4 years (for instrumental times) and 3000 years (for the
Holocene). A low Pc of 600 years was assigned to the
high-resolution interval of Termination I (11–18.5 kyr BP). For the
glacial interval between 18.5 and 110 kyr BP, Pc of 2000 years was
chosen. For the warm interglacial between 110 and 128 kyr BP, we assign a
cutoff period of 3000 years similar to the Holocene. Across Termination II
(128–135 kyr BP), we use a 1000-year cutoff period, whilst for the
penultimate glacial maximum a cutoff period of 2000 years was used. A summary
of all details on the calculated spline is found in
Table .
The total 1σ uncertainty of the spline is < 2 ppm on average
(Fig. b). Across some short time windows, it rises up to
6 ppm, and around 108 kyr BP, it reaches a maximum of 11 ppm. The three
different error sources contribute equally to the total uncertainty; however, time windows with large uncertainties are often dominated by one error
source.
The CO2 record of the last 2 kyr to be used within CMIP6
is nearly indistinguishable from our spline
across the instrumental period (Fig. a); however, CO2
concentrations during the pre-anthropogenic interval of the last 2 kyr are
partly larger by a few parts per million than our spline (Fig. b).
This difference is readily explained by the underlying data and the different
filtering. We use a combination of Law Dome and WDC data between 200 and
1210 BP, whilst only Law Dome data are considered for CMIP6.
The CO2 values chosen as boundary conditions for several time slice
experiments within PMIP4 can be
compared with snapshots from our splines (Table ). However,
one needs to be aware that some short-term fluctuations in our spline might
offset the values from long-term averages and lead to differences between our
final splines and the PMIP4 forcing data. For the mid-Holocene (6 kyr
experiment), both our spline and data used in PMIP4 are based on the same EDC
data and processed with the identical spline routines and cutoff frequencies,
leading to identical values. Values differ by a few parts per million for the
experiments 1850 CE, 21 kyr, and 127 kyr.
Since spline smoothing is a low-pass filter, abrupt changes in CO2 are
always smaller in the spline than in the original data sets. Therefore, if
one wants to investigate the impact of abrupt increases in CO2
concentration on the climate system that have been identified during three
intervals (around 11.6, 14.7 or 16.2 kyr BP) across Termination I
, an alternative
continuous CO2 record needs to be constructed. One approach might be to
reduce the cutoff period so that the spline would include these pronounced
jumps. For example, one might want to capture the rise in CO2 of 12 and
13 ppm across a single century at 16.2 and 11.6 kyr BP,
respectively, as identified in the WDC record . For the
abrupt rise in CO2 around 14.7 kyr BP, even an increase of 15 ppm in 200
years, slightly larger than the 12 ppm of the WDC record, has been suggested
to represent atmospheric changes in CO2 potentially caused by permafrost
thawing during the northern hemispheric warming into the
Bølling–Allerød interstadial . Transient
simulations investigating these abrupt jumps in CO2 concentration should
use a CO2 times series that contains greater details than our
low-frequency spline.
Data used to construct (or compare to) the Southern Hemisphere
CH4 spline.
Time (in BP)
Time (in CE)
Source
Age scale
Spline5
Citation
-66 to -34
2016 to 1984
NOAA network1 (annual)
–
no
-66 to -33
2016 to 1983
South Pole2 (monthly)
–
yes
-66 to -33
2016 to 1983
Barrow3 (monthly)
–
no
-32 to 168
1982 to 1782
Law Dome4
as in references
yes
169 to 4669
1781 to before CE
WDC discrete, OSU6
WD2014
yes
4689 to 9798
–
WDC discrete, PSU7
WD2014
yes
9821 to 67 233
–
WDC continuous
WD2014
yes
192 to 100 469
–
GRIP
GICC05ext
no
67 401 to 15 6211
–
EDC
AICC2012
yes
Notes: 1 Global annual mean of the NOAA network. Data taken
from ftp://aftp.cmdl.noaa.gov/products/trends/ch4/ch4_annmean_gl.txt.
2 Data taken from
ftp://aftp.cmdl.noaa.gov/data/trace_gases/ch4/flask/surface/ch4_spo_surface-flask_1_ccgg_month.txt.
3 Data taken from
ftp://aftp.cmdl.noaa.gov/data/trace_gases/ch4/flask/surface/ch4_brw_surface-flask_1_ccgg_month.txt.
4 Law Dome data are taken from various sources; see references for details. They exist for 2005 CE to 14 CE (or -55 BP to 1936 BP),
but only the part bridging the gap between instrumental data and WDC is taken for the calculation of the spline (1982 CE to 1782 CE or -32 BP to 168 BP).
5 Indicates if the data are used to construct the spline. 6 Measured in
laboratory at Oregon State University (OSU). 7 Measured in laboratory at Penn State
University (PSU); measured data shifted by +9.9 ppb to account for
unexplained OSU and PSU laboratory offset .
Atmospheric CH4
Our data compilation of CH4 data and the consistently calculated CH4
spline is restricted to the Southern Hemisphere (SH). Northern hemispheric
(NH) data are shown for comparison but are not included in the spline, since
for such efforts chronologies of ice cores from both hemispheres have to
match perfectly during abrupt climate changes of the D/O events. However, as
has been shown , there remains some mismatch in the
timing of the NH and the SH CH4 records in the most recent chronology
AICC2012. NH CH4, and consequently global CH4 concentrations, should, according to the estimates of the interpolar difference, be larger than our SH
CH4 values. Therefore, our SH CH4 spline represents the lower bound of
global CH4 concentration. found that NH CH4
was up to +4 % (+14 ppb) and up to +10 % (+60 ppb) larger than
the SH CH4 during glacial times and the Holocene, respectively. However,
new and as yet unpublished results point to in situ CH4 production in
Greenland ice cores during times of high dust fluxes, calling for a revision
of the interpolar difference in CH4 during glacial times. For this reason,
we refrain from calculating an NH or global CH4 spline. As CH4 is only
of secondary importance for the total greenhouse gas radiative forcing, this
systematic error is of little relevance for climate simulation
studies. Studies are under way to improve our knowledge of the NH CH4
value for glacial times, too. Using an approximation of the radiative forcing
ΔR[CH4]∼1.4⋅0.036⋅(CH4/ppb-742)Wm-2,
which neglects the interacting effects of CH4 and N2O
but which considers the approximate increase in ΔR[CH4] by 40 % through indirect effects
of CH4 on stratospheric H2O and tropospheric O3
, we estimate that our restriction
of CH4 to the SH only would underestimate the radiative forcing of CH4
by less than 0.05 W m-2.
Our data compilation starts with the beginning of the year 2016 CE (-66.0 BP)
and stops around 156 kyr BP to cover the same time interval as for CO2
(Fig. a). The 11-point running mean temporal resolution
between neighbouring data points, Δt, is less than 100 years for most
of the last 67 kyr, increasing to ∼ 700 years between 67 and 156 kyr BP
(Fig. c). Our strategy here is to select one data set for
each point in time and use overlapping intervals only for confirmation of
data consistency. The following data sets are considered here.
CH4 spline covering all data: 2016 CE–156 211 BP. Details on plotted
data are explained in the text. The maximum ice core data uncertainty
(±2σ) is given in the lower left corner. In (a) the right
axis contains the resulting radiative forcing approximated with ΔR[CH4]∼1.4⋅0.036⋅(CH4/ppb-742) W m-2 based on , but
neglecting interacting effects of CH4 and N2O and considering indirect
effects of CH4 on stratospheric H2O and tropospheric O3
. The latitudinal origin of data
is indicated by NH and SH, indicating Northern and Southern Hemisphere,
respectively. (b) Total uncertainty of the spline based on three
individual error sources; see text for details. (c) Temporal
resolution (Δt) of the CH4 data points underlying the spline on a
log scale. Additionally, the prescribed time-dependent cutoff period
Pc is plotted, including its variation by ±50 %, which has
been used to determine σ1.
Details of the southern hemispheric CH4 spline. Light and dark grey bands
around the spline represents ±1σ and ±2σ, respectively.
(a) Instrumental times (1950–2016 CE); (b) 0–2000 BP;
(c) Termination I; (d) 0–40 kyr BP without the Law Dome
data showing the anthropogenic rise; (e) 40–90 kyr BP;
(f) 90–160 kyr BP. Hemispheric origin of data is indicated by NH
(north) and SH (south). WDC PSU data are adjusted by +9.9 ppb. GRIP+:
Greenland composite; GICC05+: GICC05 model extended. See text for details.
Dashed line labelled CMIP6 in panels (a) and (b) is the
compiled CH4 record to be used in CMIP6 experiments for the last 2 kyr
.
Statistics of the CH4 spline. Interval: iCH4; s:
scaling factor to fulfil the constraints given by the prescribed cutoff
period Pc; Pc‾: average realised cutoff
period; Δt: mean data spacing; v: mean 1σ error – exact
scaling factor to fulfil the constraints given by the prescribed cutoff
period Pc; Pc‾: average realised cutoff
period. Δt: mean data spacing; v: mean 1σ error; exact
time framing is given by the age of the first (tstart) and last
(tstop) data point of the interval (in years BP); N: number of
data points within interval. In the last column the underlying data source is
briefly mentioned; see Table for details and citations.
iCH4
s
Pc
Pc‾
Δt
v
tstart
tstop
N
Data source
–
yr
yr
yr
ppb
yr BP
yr BP
–
1
1.00
4.0
4.0
0.1
2.0
-66.0
-33.1
396
South Pole
2
0.68
10.0
9.5
1.7
4.0
-31.8
165.1
114
Law Dome
3
13.12
50.0
49.7
8.2
2.4
169.0
2591.0
296
WDC discrete
4
33.63
100.0
98.8
20.0
2.4
2602.0
9798.0
361
WDC discrete
5
3.09
20.0
20.0
2.0
3.3
9821.0
67 233.0
28 707
WDC continuous
6
56.26
500.0
497.0
257.1
10.0
67 401.0
127 831.0
236
EDC
7
171.96
1000.0
982.0
440.4
10.0
128 026.0
156 211.0
65
EDC
From the NOAA network, the annual global mean concentration of CH4 from 2016 CE to 1984 CE is available
(www.esrl.noaa.gov/gmd/ccgg/trends/). These global mean concentrations
lie in between the seasonally resolved CH4 concentration measured at
Barrow, Alaska (NH), and at the South Pole (SH), both reaching back in time until
1983 CE (Fig. a). The
interpolar difference between the NH (Barrow) and the SH (South Pole) was +161 ppb
or +9 % at the beginning of 2016 CE. In absolute CH4 concentration, this most recent interpolar
difference is ∼ 100 ppb larger than the interpolar difference in the Holocene, while the relative interpolar
difference during both time intervals is comparable
. An estimation of the radiative forcing of this
interpolar difference reveals that, for the time covered by the NOAA network,
the ΔR[CH4] for the NH was <0.1 W m-2 larger
than for the SH. This estimate of the radiative forcing of the interpolar
difference is obtained from Eq. (), based on Barrow and the South Pole CH4 data. For our SH compilation we used the South Pole data.
Ice core and firn air data from Law Dome and Cape Grim (SH) exist from
2005 CE back to 14 CE (= 1936 BP)
with an overlap
of more than 2 decades with the instrumental measurements
(Fig. a, b). The CH4 data from Law Dome and Cape Grim
used in our compilation span the period from 1982 CE to 1782 CE (= 168 BP),
bridging the gap between instrumental data and CH4 from WDC. Where the Law
Dome data overlap with the data from either the South Pole or WDC, no apparent
systematic offsets between the different data sets have been identified. WDC
and Law Dome data differ slightly across short intervals between 1000 and
2000 BP (Fig. b). However, since WDC is the more highly
resolved record, it alone is included in the spline; no data adjustment is
necessary here.
The discrete CH4 data from WDC (SH) span the interval 169 BP to
67 kyr BP
.
Starting with the year 9821 BP, continuous CH4 data from WDC with higher
temporal resolution are now available and are used to support our spline
. These continuous CH4 data have already been
post-processed, including the support from some discrete WDC data points to
improve the data set, whenever larger gaps in the continuous record appeared.
The data product of the continuous CH4 WDC data obtained at NOAA is
splined to a constant temporal resolution of 2 years. For the missing part of
the Holocene not contained in the continuous WDC data, discrete WDC CH4
data are used. They have been measured in two different laboratories: at Oregon State University (OSU; 169–4669 BP) and at Pennsylvania State
University (PSU; 4689–9798 BP). An unexplained inter-laboratory offset between the
discrete CH4 WDC data from OSU and PSU has been identified. To account for
this offset the PSU CH4 data have been adjusted by +9.9 ppb Supplementary Information to.
To date WDC CH4 are the temporally most highly resolved data of the last
glacial, and therefore they are our reference record (Fig. b–e).
The data not only contain the well-known abrupt CH4 changes at the
onset and end of the millennial-scale D/O events in high resolution and
accuracy but also centennial-scale features that are understood to be of
climatic origin e.g..
We extend our SH CH4 data compilation beyond WDC with data from EDC,
spanning the period from 67 to 156 kyr BP
(Fig. e–f). These EDC data actually extend back to
800 kyr BP, but since our focus here is on the time since the penultimate
glacial maximum (i.e. the last 156 kyr), the CH4 record older than
156 kyr is not considered here. CH4 data from EDML might be in part
more highly resolved than in EDC because of a higher annual layer thickness
between 67 kyr BP (the end of WDC) and 80 kyr BP
. However, a well-documented EDML CH4 record is
not available to date, and therefore none of the published EDML CH4 data
for this interval are considered here.
The NH Greenland composite of CH4
is only plotted for comparison to the SH data
(Fig. b–f).
Data used to construct the N2O spline.
Time (in BP)
Time (in CE)
Source
Age scale
Citation
-66 to -49
2016 to 1999
NOAA network (monthly)
–
nitrous oxide data from the NOAA/ESRL halocarbons in situ program1
-50 to -38
2000 to 1988
NOAA network (monthly)
–
RITS nitrous oxide data from the NOAA/ESRL halocarbons program2
-33 to 1937
1983 to 13
Law Dome3
as in references
1975 to 11 502
–
EDC4
AICC2012
29 065 to 134 519
–
EDC
AICC2012
9858 to 15 843
–
Taylor Glacier
WD20145
15 000 to 118 602
–
NGRIP6
AICC2012
15 000 to 134 418
–
Talos Dome7
AICC2012
Notes:
1 ftp://ftp.cmdl.noaa.gov/hats/n2o/insituGCs/CATS/global/insitu_global_N2O.txt.
2 ftp://ftp.cmdl.noaa.gov/hats/n2o/insituGCs/RITS/global/RITS_global_N2O.txt.
3 Law Dome data are taken from various sources; see references for
details. They exist from 2004 CE to 13 CE (or -54 BP to 1937 BP), but
only those older than the instrumental record (1986 CE and older) are taken
here. 4 Data exist from 334 BP (or 1616 CE) until 11 502 BP, but only
data not yet covered by the Law Dome records (13 CE or 1937 BP and older)
are considered here. 5 WD2014 age model for Taylor Glacier, published in
. 6 Data exist for 11 068 BP–119 555 BP, but
only those older than 15 kyr BP are considered here. Five data points in
the oldest part considerably disagree with SH records and are therefore
rejected. 7 Data exist for 217 BP–134 418 BP, but only those older
than 15 kyr BP are considered here.
The assigned data uncertainty (1σ error) is 2.0, 4.0, 2.4, 3.3, and
10 ppb for instrumental data, Law Dome, discrete WDC, continuous WDC, and
EDC, respectively
.
Using the approximation of ΔR[CH4], given the above
1σ errors the uncertainty in the radiative forcing is
<0.01 W m-2.
Compiled data contain 30 214 data points, among which duplicate entries
exist for 39 ages. These duplicates are averaged giving n=30175.
The whole data set is divided into seven intervals with different assigned
cutoff periods. Pc ranges from 4 years (for the interval covered
by instrumental data) to 20 years (for the interval covered by the continuous
WDC record). Due to lower data coverage during the Holocene and further back
in time, Pc is increased to 100 years (0.2–9.8 kyr BP),
500 years (60–128 kyr BP), and 1000 years (128–156 kyr BP)
(Fig. c). More details are shown in
Table .
The total 1σ uncertainty of our final CH4 spline is around
3–10 ppb in the Holocene, ∼ 2 ppb in the time window supported by
the continuous WDC CH4 data (9.8–67 kyr BP), and around 10 ppb in
earlier parts. During some short time windows, σCH4 reaches a
maximum of 20 ppb (Fig. b). The uncertainty is dominated by
the Monte Carlo error before 9.8 kyr BP and by the error in the cutoff
period in the Holocene and during those short events in which
σCH4 reached its local maxima. An abrupt jump in
σCH4 appears at 67 kyr BP (transition from continuous WDC
to discrete EDC data), when individual data point uncertainty rose from 3.3
to 10 ppb (changing σ3) at the same time as Δt, and
therefore Pc, increased by 2 orders of magnitude (changing
σ1).
N2O spline covering all data: 2016 CE–134 519 BP. Details on plotted data are explained in the text.
The maximum ice core data uncertainty (±2σ) is sketched in the lower
left corner. In (a) the right axis contains the resulting radiative
forcing approximated with ΔR[N2O]∼0.12⋅(N2O/ppb-272) W m-2 after
, neglecting interacting effects of CH4 and
N2O. Filled symbols: data taken for spline; open symbols: data not taken
for spline. (b) Total uncertainty of the spline based on three
individual error sources; see text for details. (c) Temporal
resolution (Δt) of the N2O data points underlying the spline on a
log scale. Additionally, the prescribed time-dependent cutoff period
Pc is plotted, including its variation by ±50 %, which has
been used to determine σ1.
Details of the N2O spline. Light and dark grey bands around the spline
represent ±1σ and ±2σ, respectively.
(a) Instrumental times (1950–2016 CE); (b) 0–2000 BP;
(c) Termination I; (d) 0–40 kyr BP without the Law Dome
data showing the anthropogenic rise; (e) 40–90 kyr BP;
(f) 90–140 kyr BP. Filled symbols: data taken for spline; open
symbols: data not taken for spline. See text for further details. Dashed line
labelled CMIP6 in panels (a) and (b) is the compiled N2O
record to be used in CMIP6 experiments for the last 2 kyr
.
Statistics of N2O spline. Interval: iN2O; s: scaling
factor to fulfil the constraints given by the prescribed cutoff period
Pc; Pc‾: average realised cutoff period;
Δt: mean data spacing; v: mean 1σ error – exact time
framing is given by the age of the first (tstart) and last
(tstop) data point of the interval (in years BP); N: number of
data points within interval. In the last column the underlying data source is
briefly mentioned; see Table for details and citations.
iN2O
s
Pc
Pc‾
Δt
v
tstart
tstop
N
Data source
–
yr
yr
yr
ppb
yr BP
yr BP
–
1
1.00
4.0
3.4
0.1
0.8
-66.0
-38.3
334
NOAA network
2
3.01
50.0
48.7
2.5
7.2
-33.7
95.0
53
Law Dome
3
19.08
200.0
190.2
16.8
7.0
104.0
389.6
18
Law Dome
4
321.85
1000.0
952.4
85.1
4.6
400.3
9425.6
107
Law Dome, EDC
5
77.33
500.0
469.0
58.2
5.8
9517.2
15 974.7
112
EDC, Taylor Glacier, NGRIP, Talos Dome
6
1443.10
2000.0
1915.3
60.4
4.9
16 003.0
116 900.0
1672
EDC, NGRIP, Talos Dome
7
4236.11
5000.0
4792.5
370.0
4.2
117 130.0
134 519.0
48
EDC, NGRIP, Talos Dome
The SH CH4 record to be used within CMIP6
largely agrees with our SH CH4 spline (Fig. a, b).
However, during instrumental times the CMIP6 SH CH4 record is consistently
larger than our SH CH4 spline by about 10–15 ppb, probably caused by the
inclusion of different stations in the calculation of the SH CH4 record
within CMIP6, while we rely on South Pole data. Prior to the instrumental
CH4 data around 1980 CE, the maximum difference between both approaches
is 30 ppb. This difference might be caused by the statistical routines
within CMIP6 to account for missing stations. Further back in time (around
1150 BP, 1300 BP, and 1900 BP), higher-frequency variation contained in
the WDC CH4 record (used here but ignored within CMIP6) leads to some
CH4 variations within our SH CH4 spline on the order 10–25 ppb that
are not captured by the CMIP6 SH CH4 record.
A comparison of our final spline with the GHG values chosen for the PMIP4
time slice experiments is not
straightforward, since we only compile SH CH4 data, while the PMIP4
experiments use global values. Taking the two records at face value, one
finds that our SH CH4 is 13, 44, and 25 ppb smaller than the global mean
value used in PMIP4 for 1850 CE, 6 kyr, and 127 kyr, respectively. In
particular, the large SH-global difference of 44 ppb around 6 kyr seems to
be rather large but is readily explained by the centennial variability
contained in the WDC CH4, which leads to a local minimum in SH CH4
around 6 ka. Similarly, our SH CH4 spline is 7 ppb higher than the
global CH4 value chosen within PMIP4 for the 21 kyr experiment. This
difference can again be explained by the centennial-scale variability
contained in the WDC CH4 record, which shows a local maximum at
21 kyr BP. A hundred years later, our SH CH4 spline has a local minimum
which is 11 ppb smaller than the global CH4 values taken for PMIP4
(Table ).
Atmospheric N2O
For the data compilation of the third GHG, N2O, one has to be aware that
during times of high dust input, in situ production of N2O occurs,
leading to artefacts in the paleo record . Furthermore,
the precise synchronisation of Northern and Southern Hemisphere records, as
already explained for CH4, is crucial to accurately obtain the changes in
N2O during millennial-scale D/O events.
The compiled record starts at the beginning of the year 2016 CE
(-66.0 BP) but extends back in time only until ∼134.5 kyr BP
(Fig. a) because the ice cores on which the N2O
compilation is based in the older parts, Talos Dome, EDC, and NGRIP, have
either no data points between 134.5 and 156 kyr BP or unreliable N2O
data containing artefacts across the penultimate glacial maximum
. The latter is also the case for EDML, whose data have
not been taken to support the spline because despite the agreement of the
N2O of EDML and EDC, the data from EDML have a lower temporal resolution
than those of EDC .
The data sets contributing to the N2O stack are listed below.
There are two contributions of N2O data based on instrumental measurements
to the NOAA network or ESRL halocarbon program: (a) in situ N2O data are
available from 2016 CE back until 1999 CE, and (b) the RITS N2O data
from 2000 CE go back until 1988 CE. Both represent global mean monthly
values (Fig. a). Note that due to the long atmospheric
lifetime of N2O, any interpolar difference can be safely neglected.
Law Dome and Cape Grim N2O data exist from 2004 CE back until 13 CE
(1937 BP) and correlate well
with the instrumental data in overlapping intervals
(Fig. a,b). Here, the Law Dome data contribute to the
spline only for those years not covered by the instrumental record, i.e. 1983 CE and earlier.
In the Holocene, N2O was measured at EDC
from 334 BP until 11.5 kyr BP. For
the last two millennia, the EDC N2O data points are sparser than the Law
Dome data; therefore, the EDC N2O data are only considered for times older
than what is covered in the Law Dome N2O record, i.e. before 1975 BP
(Fig. b, d).
The most highly resolved N2O record across large parts of Termination I is
provided by the horizontal ice core from Taylor Glacier
which has been linked to the chronology of the WDC ice core (WD2014) via
CH4 . The Taylor Glacier N2O record used in
our spline covers the interval 9.6 to 15.8 kyr BP
(Fig. c).
The last glacial interval is well resolved by N2O data from the NGRIP
record .
While the NGRIP N2O data cover the times between 11 kyr BP and
119.6 kyr BP, we only take those data older than 15 kyr BP due to the
more highly resolved Taylor Glacier N2O data during Termination I
(Fig. c–f). Five data points near the bedrock in the
bottom part of the NGRIP records apparently have higher N2O values than
found in ice cores from the Southern Hemisphere. These data points are
rejected here, leading to the oldest NGRIP N2O data point at
118.6 kyr BP. We are aware that due to the imperfect north–south
synchronisation of gas records in AICC2012 (see Sect. for
details), the usage of N2O data from NGRIP might introduce erroneous
phasing between our global N2O record and the purely SH-based CH4
spline, particularly during abrupt change connected to D/O events. However,
N2O data coverage in the SH is very sparse and a spline only based on SH
data would be even less reliable. This potential synchronisation problem is
also addressed by large cutoff periods of the spline of 2000 to 5000 years
beyond 16 kyr BP.
Additional N2O data going back to 134.4 kyr BP are obtained from the
Talos Dome ice core and from further data of the EDC
ice core (compilation found in ; data source between
29.0–134.5 kyr BP: ).
Since – besides EDML, which correlates well with EDC
– these are the only N2O records with reliable data going back to the
penultimate glacial maximum, we consider all data points from the Talos Dome
and EDC ice cores here before 15 kyr BP. The data points of Talos Dome and
EDC in general agree with the NGRIP data over the last glacial cycle, but
NGRIP diverges from the SH records towards higher (probably biased) values in
the warm previous interglacial around 115 kyr BP. As already explained
above, these five NGRIP data points are rejected. However, across Termination
I, Talos Dome N2O data seems to be systematically lower than NGRIP N2O
data, with Taylor Glacier data in between both (Fig. c).
We therefore believe that a mixture of all three records (N2O from NGRIP,
EDC, and Talos Dome) most likely represents a reasonable mean global N2O
value (Fig. c–f). The relatively large difference in
N2O from different ice cores during the last glacial times indicates that
the uncertainty (accuracy) in N2O is probably higher than the reported
measurement errors (precision) of up to 7 ppb.
Calculated radiative forcing of CO2, CH4, N2O, and their sum (ΔR[GHG]),
including 1σ-uncertainty bands. In addition to the uncertainty of the spline,
further uncertainties need to be considered: 10 % relative uncertainty contained
in the simplified Eqs. ()–(); 0.2 W m-2 uncertainty in
ΔR[CH4] and ΔR[N2O] due to the omission of interaction effects;
5 % uncertainty in efficiency of CH4 for more details, see. The total
uncertainty of the ΔR[GHG] is calculated as the square root of the sum of squares of the uncertainties of the individual GHGs.
The calculations are based on Eqs. ()–() given
in the text following. Sub-figures focus on
specific time windows: (a) anthropogenic rise since 1750 CE;
(b) Termination I; (c) 20–90 kyr BP, including the
abrupt changes during D/O event; (d) full record from 2016 CE to
156 kyr BP – here N2O was kept constant beyond 134 kyr BP.
The generally assigned 1σ uncertainty of each data point is 7 ppb for
the Law Dome ice core . The
uncertainty of individual data points in other ice cores was in general less
than 7 ppb . For the
instrumental measurements, we take the reported uncertainties of around
1 ppb. For 58 times, more than one data point for the same age exists. These
duplicates are averaged reducing the number of N2O data to n=2344. Using
an estimate of the radiative forcing of N2O, which neglects the
interacting effects of CH4 and N2O,
ΔR[N2O]∼0.12⋅(N2O/ppb-272)Wm-2,
, we estimate that the 1σ error in
N2O is related to an uncertainty in the radiative forcing of about
0.04 W m-2, slightly larger than the uncertainty in ΔR related
to the CH4 data. Comparing the different values of N2O in Talos Dome
and NGRIP for same intervals reveals differences on the order of about
10 ppb (e.g. Fig. c–f), suggesting that the
ice-core-specific values of N2O contain an intrinsic uncertainty which is
comparable to the measurement error.
The mean temporal resolution (11-point running mean) of the underlying N2O
data is around 50 years across large parts of the last glacial cycle
(15–60 kyr BP), with slightly lower resolution of 100 years in the
Holocene and between 60 and 115 kyr BP. In MIS5.5, Termination II, and the
penultimate glacial maximum, the mean temporal resolution rises to
∼ 500 years (Fig. c). Based on this distribution of
Δt the prescribed cutoff periods for the spline vary for seven
different intervals between 4 (for the instrumental period) and 5000 years
(for data older than 117 kyr BP). For the majority of the data (400 yr BP
to 117 kyr BP), a Pc between 500 and 2000 years is prescribed.
More details on the spline are found in Table .
The total 1σ uncertainty of the spline varies between 1 and 6 ppb
(Fig. b). This uncertainty is mainly based on σ3
(the error related to the Monte Carlo statistics) for periods younger than
the LGM. For intervals older than the LGM, the main uncertainty is
σ1, the error related to the cutoff period.
If compared with the N2O compilation used within CMIP6
both approaches largely agree for instrumental
times (Fig. a). Further back in time during the last
2 kyr, both approaches rely on the same data: the published Law Dome/Cape
Grim N2O data .
Interestingly, both time series differ by up to 6 ppb between 0.7 and
2.0 kyr BP (Fig. b). This difference is in the range
of the ice core data uncertainty, and therefore still small, but we have no
ready explanation. The records used in CMIP6 have a higher N2O
concentration than all data from Law Dome or other SH ice cores
(Fig. b), for some unknown reason.
The N2O data used as starting values in the PMIP4 experiments 1850 CE,
6 kyr, 21 kyr, and 127 kyr
agree within 1 or 2 ppb with values based on our calculated spline; only for
21 kyr is the offset with 6 ppb greater (Table ).