Introduction
Surface temperature changes in response to radiative forcings are far from
spatially uniform due to local radiative feedbacks and atmosphere and
ocean dynamics. While anthropogenic greenhouse gases exert the largest
radiative forcing at low and midlatitudes, the largest surface temperature
increase is observed in the Arctic region. Currently, the Arctic surface
temperature is increasing at more than twice the rate of lower latitudes
, and global climate models suggest that by the end of the
century the Arctic will have warmed substantially not only in absolute terms,
but also compared to the rest of the globe . Polar amplification
of surface temperature change has also been detected based on Arctic proxies
for past glacial and warm periods , and it is not limited to the
Arctic. In CO2 perturbation experiments for the early Eocene,
found that several models consistently simulate the greatest warming in the
Antarctic region due to the lower topography via the lapse rate (LR) effect and
the change in albedo.
However, the Arctic has recently been warming faster than Antarctica,
and based on climate model projections, it is also expected that Arctic
amplification will still be notably stronger than Antarctic amplification by
the end of this century. According to the fifth assessment report (AR5) by
the Intergovernmental Panel on Climate Change (IPCC), coupled climate models
from the Coupled Model Intercomparison Project phase 5 (CMIP5) yielded an
Arctic warming of 4.2 ± 1.6 K compared to an Antarctic warming of only
1.5 ± 0.7 K for the years 2081–2100 relative to a 1986–2005
reference period in the RCP4.5 radiative forcing stabilization scenario
. The corresponding tropical warming under this scenario was
1.6 ± 0.4 K.
The focus in explaining Arctic amplification has long been on the surface
albedo (ALB) feedback and lack of vertical mixing e.g.,. However, several studies have found that Arctic amplification was
simulated even in models in which the ice albedo feedback is suppressed
. While the surface albedo feedback is still
considered to be an important contribution to Arctic amplification, more
recently, other processes have also been identified as being important. In
particular, atmospheric feedbacks e.g.,
and changes in heat transport from lower
latitudes to the Arctic (cooling lower latitudes and warming the Arctic)
e.g., have both been suggested to be important
contributors to Arctic amplification.
Since the average Antarctic surface height exceeds 2 km, mainly due to the
presence of thick ice sheets and a compensation of above-sea-level (positive)
and below-sea-level (negative) bed rock elevation , the ice is
thick enough and the surface temperature is low enough that in many areas
melting from above is expected to play a minor role, unless temperatures
increase dramatically. Even for a fairly substantial CO2 increase,
simulated Arctic amplification was found to be larger than Antarctic
amplification due to a weaker Antarctic surface albedo feedback already in
the early climate model study by .
Melting from below associated with increased sea surface temperature is, however, a major concern, in part because of the sea level rise
associated with pieces breaking off the Antarctic ice shield and sliding into
the sea , although regions that are located far inland and in
which the bedrock remains above sea level are not immediately affected. Furthermore, the
sea ice in the Southern Ocean induces a surface albedo
feedback in climate change simulations, and in association with the
transition from glacials to interglacials, it has long been proposed that
melting at the edges of ice sheets and glacier flow can successively lower
the altitude of the Antarctic ice to where it becomes more prone to melting
. The corresponding processes are difficult to represent in
climate models, and at present, not all climate models include them.
In addition to the surface albedo feedback , the Antarctic
surface height is expected to influence the response of the atmospheric heat
transport (AHT) to a CO2 increase. Atmospheric feedbacks such as the water
vapor (WV) feedback are also expected to differ between the Arctic and
Antarctic due to the differences in surface elevation. Furthermore, the
asymmetric land–sea distribution, with more land in the Northern Hemisphere,
could potentially play a role in the polar amplification asymmetry.
Another reason for the polar amplification asymmetry that has recently been
investigated by is an asymmetric response of the ocean heat
transport (OHT) to ozone and greenhouse gas forcing. also
indicated that asymmetric warming between the Arctic and Southern Ocean in
climate models might be linked to asymmetries in ocean heat uptake and ozone
depletion over Antarctica.
Here, the role of the Antarctic surface height in the temperature response to
an abrupt carbon dioxide doubling is investigated based on idealized
sensitivity simulations with a low-resolution three-dimensional coupled
global climate model in which the surface height was artificially set to 1 m
above mean sea level for the entire Antarctic continent. Recently, have found that lowering the Antarctic surface height in a coupled global climate model leads to increased outgoing longwave radiation over Antarctica, which drives anomalous southward energy transport toward the continent. They did not, however, study the effect of increasing CO2 concentrations on Antarctic polar amplification.
The model, the partial radiative perturbation (PRP) computations, and the analysis methods used in the present study are described in
the next section. In Sect. , the zonal mean radiation
budget is investigated. The surface temperature response to doubling CO2
is discussed in Sect. . Changes in meridional heat transport
are analyzed in Sect. and local radiative feedbacks are
analyzed in Sect. and . In Sect.
an attempt is made to compare contributions from local feedbacks, heat
transport, and heat storage. The temporal evolution of the coupled runs and
potential improvements to the model setup used in the present study are
discussed in Sect. .
Methods
The Community Earth System Model (CESM) version 1.0.6 was used
in the Community Climate System Model Version 4 (CCSM4) configuration
to perform a set of idealized 600-year coupled model
sensitivity runs. The atmospheric component (using the Community Atmosphere
Model (CAM4) physics package) was run at spectral truncation T31
(approximately 3.75∘ horizontal resolution) with 26 vertical layers
(due to computational constraints). The ocean component based on the
Parallel Ocean Program version 2 (POP2); was run in the so-called
gx3v7 setup with 3∘ horizontal resolution and 60 vertical layers.
Land, ice, and snow were simulated by the land surface model Community
Land Model version 4;, which includes glacier as a land cover type.
Sea ice was simulated using a modified version of the Los Alamos Sea Ice
Model version 4 CICE4; . The coupled model was run in a
standard configuration without a dynamic ice sheet model.
In the base control run, the atmospheric carbon dioxide concentration was
kept fixed at 284.7 ppmv (for the year 1850). In the base 2 × CO2 run,
the CO2 concentration was doubled. In addition, two coupled sensitivity
runs were performed, for which Antarctica was assumed to be flat. These runs
are usually referred to as flat AA control run and flat AA 2 × CO2 run.
Table provides an overview of these coupled runs.
Coupled runs.
Run
Description
Base control
Control run for constant year-1850 conditions
Base 2 × CO2
Same as base control, but doubled CO2
concentration
Flat Antarctica control
Control run for flat Antarctica (flat AA)
Flat Antarctica 2 × CO2
Flat AA CO2-doubling run
The analysis focuses on the transient response to CO2 doubling during the
years 76 to 125 and especially during the years 80 to 109, for which the model
was rerun and PRP calculations were performed. While most of the temperature
response in the upper ocean to the CO2 perturbation takes place during the
initial decades of a 2 × CO2 perturbation experiment, the deep ocean has
not yet reached equilibrium during this period, which is similar to the
situation in present-day climate and transient future climate change. In the
base 2 × CO2 run, Antarctic warming (see Sect. ) became
stronger than Arctic warming around year 200 (and around year 120 for the
flat AA 2 × CO2 run). This differs from present-day observations of a
stronger polar amplification in the Arctic compared to the Antarctic region
and from the results of shorter CMIP5 simulations, which the present study
aims to help explain.
In the standard model setup, the radiation computations were performed every other
time step. In order to increase the accuracy of the PRP computations
(described below), the coupled model was rerun for the years 76 to 125,
with radiation performed every (half hour) time step instead of every other time
step. This ensured that the net top of the atmosphere radiation in the
offline PRP and the coupled runs was consistent, although closing the
budgets, including atmospheric and oceanic transport and heat storage, remained
challenging (this point is discussed further below). The results from these
radiation (RAD) reruns are not identical to the original coupled runs
because the more frequent radiation computations trigger a new realization.
Many of the main findings of this study are, however, independent of this
choice and rerunning the entire period would have been computationally
expensive. The reruns differ mainly in their temporal evolution, but the PRP
analysis based on these runs yields qualitatively similar results, except
that the sum of all feedbacks (which is a small term compared to the
individual feedbacks) is closer to the top of the atmosphere (TOA) net radiation change in the coupled
run and except that the contributions of the individual feedbacks and transport
terms to the decreasing polar amplification asymmetry differ. The advantage
of the RAD reruns is that the PRP analysis is more exact, which makes them
more suitable for the budget analysis. The advantage of the base model setup
is that it is computationally cheaper to run and is thus better suited for
longer integrations.
In addition to these coupled simulations, the radiation code was run in an
offline setup to perform a set of standard two-sided PRP computations as well
as several sensitivity computations in order to investigate contributions of
local radiative feedbacks. The offline version of the radiative code that is
included in the CESM v1.0.6 distribution was described by .
In the original PRP method , radiative feedbacks are estimated
by substituting individual fields (such as atmospheric water vapor) from the
perturbed (2 × CO2) simulation into an offline radiation calculation that
takes all other fields from the unperturbed (control) run. In addition, in the two-sided
PRP method , individual fields from the unperturbed
control run are substituted into the offline radiation calculation for the
perturbed run. The resulting radiation perturbations are then combined
according to
δ2-1(R)x-δ1-2(R)x2,
where R is the net radiation flux at the TOA, i.e.,
the difference between incoming solar and outgoing solar and terrestrial
radiation, δ2-1, is the radiation perturbation from the first
substitution
(2 × CO2 into control) and δ1-2 is from the second substitution (control into
2 × CO2) for variable x (or variables x for feedbacks in
which contributions from several model variables such as cloud liquid and
cloud ice concentration are combined into a single feedback).
Here, the ALB, WV, cloud (CL), and
LR feedbacks were computed. Furthermore, the CO2 radiative
forcing and the Planck (PL) feedback were computed using the two-sided PRP
method. The PL feedback was computed by substituting the surface temperature
and adding the surface air temperature difference ΔTs(λ,ϕ) to the atmospheric temperatures
Ts(λ,ϕ,z) at each model layer (where ΔTs depends on longitude λ and latitude ϕ). The LR
feedback was defined as LR = TA - PL, where TA is the
perturbation that is obtained by substituting the surface as well as the
atmospheric temperatures.
The radiation code was run offline based on three-hourly instantaneous model
output for years 80 to 109 of the coupled simulations. This fairly high
temporal sampling frequency in combination with a fairly long period of
30 years led to a rather smooth and less noisy geographical distribution of
cloud feedbacks compared to lower sampling rates, and it also ensured that the
TOA energy budget in the PRP runs was consistent with the
corresponding coupled runs.
In order to study differences of the LR feedback between the base and the
flat AA model setup, a set of additional 30-year PRP sensitivity computations
was performed (in addition to the standard PRP computations) based on
73-hourly instantaneous model output. In these sensitivity computations,
individual variables from the flat AA setup were substituted in PRP
computations for the base setup. For example, a PRP calculation was performed
in the base model setup using Ts from the flat AA control and the
flat AA 2 × CO2 run instead of from the base control and the base
2 × CO2 run. An overview of the additional sensitivity computations is
given in Table . The lower output frequency in the additional
sensitivity computations was used since it significantly reduces storage
requirements and run time, although the PRP computations become less accurate.
Additional PRP sensitivity computations.
Label
Variable(s) from flat AA model setup
in base model setup
LRPLSens
Surface air (Ts) and atmospheric (Ta) temperature
LRsens
Atmospheric temperature Ta
PLSens
Ts and control Ta with added ΔTs as in PL
Strictly speaking, the cloud radiative response to CO2 doubling and
surface warming that is computed using the PRP method is not a pure
feedback since it is not only modulated by surface temperature changes.
Instead, the cloud radiative response also contains contributions from fast
cloud responses to the CO2 increase, which are independent from surface
temperature changes. Since the focus here is not on clouds, the historical
term feedback is nevertheless used for convenience, even though
response would be more correct. Furthermore, the feedbacks were not
normalized by the surface temperature change, which facilitates a straight
forward comparison of the actual TOA energy flux differences associated with
each of the feedbacks between the base and the flat AA model setup.
Normalization by the surface temperature change without taking into account
heat storage is only appropriate when two equilibrium states are compared.
In analyzing the model output, meridional AHT at
latitude ϕ was computed by meridionally integrating the difference
between the net radiative flux at the TOA (R) and the net energy flux at
the surface (Fs, here also defined as positive downward) from the
South Pole to latitude ϕ:
AHTϕ=∫-π2ϕ∫02πRλ,ϕ′-Fsλ,ϕ′a2cos(ϕ′)dλdϕ′,
where the net downward surface flux
Fs= Rs - SHF - LHF - SN is the sum of the
net downward surface radiation flux (Rs) and the sensible and
latent heat fluxes, and SN is a contribution from snowfall; a is the
Earth's
radius. OHT is available as a standard diagnostic in
the CESM. When computing AHT to the polar regions, the integral in
Eq. () was evaluated individually for each pole, integrating from
the pole across all latitudes inside the respective polar circle. The
corresponding grid cell edges of the atmosphere grid are located at
66.8∘ N and Southern Ocean heat transport is diagnosed at 66.6∘ N
and S.
The Arctic and Antarctic region averages were defined as averages over model
grid points that are centered poleward of the respective polar circle. In
order to roughly compare local radiative feedbacks and changes of heat
transport convergence, the meridional heat transport at the edge of the polar
region was simply divided by the area of the polar region.
In the flat Antarctica runs, the land height over Antarctica was set to 1 m
for the entire continent.
Heat storage terms (here mainly due to changing ocean heat content and a
smaller contribution from sea ice and also a minor contribution from snow)
were estimated based on the difference in model state during the first month and
the last month of the period under investigation. The regional heat storage
term should be balanced by changes of net meridional heat transport
convergence and TOA net radiation flux. However, after taking into account
heat storage, atmospheric and oceanic transport, and TOA radiation fluxes,
the energy budgets were still not balanced, especially in the Arctic, and it
appears that this difficulty is only in part caused by different atmospheric
and oceanic grids. Instead, it could in principle either have been caused by
an energy conservation issue in the model (which cannot easily be confirmed
based on the present analysis) or else by inaccuracies in the analysis
methods used here. However, the (mainly Arctic) imbalance was found to be of
similar magnitude in the base and the flat AA run, so that the residual terms
in the differences between the base and the flat AA model setup were small.
Therefore, the energy budget analysis was still considered useful. The
imbalance between the net radiation deficit and the sum of the other budget
terms (dominated by poleward heat transports) varied between 2 and 5 % of
the net radiation deficit in the polar regions.
For model evaluation purposes, solar and terrestrial radiation fluxes derived
from satellite observations for years 2001 to 2014 were taken from the NASA
CERES Clouds and the Earth's Radiant Energy System; SYN1deg
Edition 3A. The orbit covers latitudes up to about 80∘ north and 80∘ south.
Results
Zonal mean radiation budget
In the polar regions, more energy is emitted to space via longwave
(terrestrial) radiation than is supplied by the absorption of solar radiation.
This energy deficit is balanced by a radiation energy surplus at the Equator
and poleward heat transport by the ocean and the atmosphere. The radiation
energy deficit is smaller in the Antarctic region than in the Arctic region.
The base model setup (Fig. a) and observations
(Fig. b) show a pronounced Arctic–Antarctic asymmetry in the
magnitude of the outgoing terrestrial radiation flux, which is in line with
the higher average surface temperature (and lower average surface elevation)
in the Arctic and also with a larger meridional heat flux from lower
latitudes toward the Arctic.
(a) Zonal mean radiation budget at the top of the
atmosphere (TOA) for years 80 to 109 of the base and flat AA control run: net
downward solar (= absorbed shortwave, red lines) and upward terrestrial
(= outgoing longwave, blue lines) radiation fluxes. The shaded areas are
based on the base control run. Red shading indicates a net radiation surplus
(i.e., on the net, more solar radiation is being absorbed than terrestrial
radiation emitted) and blue shading a net radiation deficit. Since the focus
is on the polar regions, the x axis has not been scaled by the cosine of
the latitude. (b) Zonal mean radiation budget at the top of the
atmosphere (TOA) for years 2001 to 2014 based on the CERES SYN1deg Edition 3A
satellite data product.
Conversely, when Antarctica was assumed to be flat, the asymmetry in
the simulated radiation budget decreased markedly (Fig. a). In
the flat AA run, Antarctica was similar to the Arctic in terms of the zonal
mean radiation budget, which implies that the overall poleward heat transport
was also more symmetric in the flat AA run. Atmospheric and oceanic
meridional heat transport will be further analyzed in Sect. .
The slight increase in absorbed shortwave radiation over the Antarctic
continent in the flat AA run (Fig. a) is consistent with
increased atmospheric absorption and also includes a minor contribution from
an increase in snow albedo as the melting temperature is occasionally
approached in the flat AA base run. The latter contribution is non-zero in
spite of the fact that the entire Antarctic continent remains covered by snow
year round (not shown). This is because the snow albedo in the CESM
decreases with temperature whenever the melting temperature is approached.
Surface temperature response to doubling CO2
Doubling CO2 in the base model setup led to the well-known pattern of a
strong polar amplification in the Arctic region and a weaker polar
amplification in the Antarctic region (Fig. , based on the RAD
reruns) that is also found in certain transient climate change experiments.
Conversely, in the flat AA run, the polar amplification was increased
in the Antarctic region, while it decreased over time in the Arctic region
(the temporal evolution in the original coupled runs will be discussed in
Sect. ).
Surface air temperature increase for a CO2 doubling in the base
and the flat AA model setup for years 80–109 (from the RAD
reruns).
This decrease in asymmetry is also reflected in Table (based
on the original coupled runs), in which the polar warming due to doubling
CO2 was analyzed for three consecutive 25-year time slices starting in
year 51 and ending in year 126. In the base run, the Arctic region warmed on
average 1.40 ± 0.29 K (mean of three time slices ± 1
standard deviation) more than the Antarctic region. Conversely, in the flat AA run, the difference between the Arctic and the Antarctic warming
was reduced to 0.59 ± 0.32 K. Thus, on average, about
56 ± 30 % of the difference in warming between the Arctic and the
Antarctic region (i.e., 0.81 ± 0.46 of 1.40 ± 0.29 K) was
explained by the Antarctic surface height for the three time slices. However,
as evidenced by the large standard deviation, this ratio was not constant in
time.
Mean Arctic and Antarctic warming (2 × CO2 minus
control) ± 1 standard deviation for three consecutive 25-year time
slices starting at year 51 for the base and flat AA model
setups.
Arctic warming
Antarctic warming
Difference
(K)
(K)
Base
3.95 ± 0.48
2.55 ± 0.22
1.40 ± 0.29
Flat AA
3.76 ± 0.31
3.17 ± 0.01
0.59 ± 0.32
In the first time slice, only 24 % of the difference was explained by
Antarctic surface height, while 64 % was explained in the second, and
80 % was explained in the third time slice. When only Antarctic temperature change was
taken into account (i.e., the Arctic temperature increase was taken from the
base setup, while the Antarctic temperature increase was taken from the flat
AA setup), 73, 26, and 42 % was explained by Antarctic surface height.
The differences are explained by a pronounced Arctic warming toward the
beginning of the flat AA 2 × CO2 run compared to the flat AA control run
and a weaker subsequent Arctic warming (i.e., a cooling relative to the
initial warming). This result is based on the original coupled runs and
differs from the corresponding result of the RAD reruns since the temporal
evolution of the surface temperature differs, although the finding that polar
amplification asymmetry decreases markedly in the flat AA model setup holds
in the RAD reruns as well. Because the original coupled runs reflect the
standard configuration of the model, and also because the RAD reruns are
only available for the years 76 to 125, the original coupled runs were chosen
for this analysis.
(a) Northward atmospheric heat transport (AHT) in petawatts
in the base and flat AA model setups for years 80–109.
(b) Differences (2 × CO2 minus control) for doubling
CO2 (from the RAD reruns).
Before discussing the underlying temporal evolution of the zonal mean
temperature in the original coupled runs in detail in Sect. ,
the reasons for the decreased polar amplification asymmetry in the flat AA
model setup (Fig. ) will be analyzed in some detail based on
the RAD reruns, which generally yield sufficiently similar results to the
original runs for this analysis to be useful.
Atmospheric and oceanic heat transport
In this section, the zonal mean AHT (Fig. ) and OHT
(Fig. ) for the years 80–109 are compared between the base and
the flat AA model setup, and their changes in the corresponding CO2-doubling runs are analyzed based on the RAD reruns. As expected, based on
Fig. a, AHT and OHT were more symmetric in the flat AA model
setup than in the base setup (although they cannot be expected to become
completely symmetric because the overall land mass distribution differs
between the Northern and Southern hemispheres). In the control runs, the
poleward AHT increased in the flat AA model setup compared to the base setup
mainly in the Southern Hemisphere. Poleward OHT across the polar circles
increased in the Southern Hemisphere and also slightly increased in the
Northern Hemisphere. Conversely, in the original coupled runs,
poleward OHT across the polar circle in the Northern Hemisphere slightly
decreased during this period (Fig. ). Other findings in this
section were not affected by this difference.
Same as Fig. but for oceanic heat transport
(OHT).
Same as Fig. but from the original runs instead of the
RAD reruns.
CO2 radiative forcing (CO2) as well as Planck (PL), lapse rate
(LR), water vapor (WV), albedo (ALB), and cloud (CL) radiative feedbacks based
on two-sided PRP calculations for years 80–109. FSU = LR + WV + ALB + CL is the sum
of the feedbacks, except for PL. The residual (RES) is the difference between the
radiative perturbation from replacing all variables simultaneously and the
sum (SUM = CO2 + LR + WV + ALB + CL + PL) of the
individual contributions, including CO2 and PL.
Differences between Fig. (a) and
(b).
Doubling CO2 led to an increased poleward AHT in the base and flat AA
model setups. The increase in the southward AHT across the polar circle in the
2 × CO2 runs was larger in the flat AA model setup than in the base model
setup, but poleward of 60∘ S ΔAHT changed sign. At the same
time, the increase in southward OHT reached a maximum around this latitude. This
indicates that AHT and OHT are closely linked and that they should not be
considered in isolation. Both AHT and OHT contributed to decreasing the
asymmetry in the flat AA run compared to the base run, and changes of OHT are
not confined to the Southern Hemisphere, especially in the tropics. In
summary, for the CO2-doubling experiments, AHT and OHT both contributed to
an increased southward heat transport in the flat AA model setup, with OHT
changes being more important in the Southern Ocean and AHT taking over above the continent.
Radiative forcing and feedback maps for the base model setup for the
years 80–109. Labels as in Fig. .
Local radiative feedbacks
In addition to AHT and OHT, local radiative feedbacks and increased CO2
forcing over Antarctica contributed to the decreased polar amplification
asymmetry in the flat AA run. Figure shows the CO2
radiative forcing as well as various radiative feedbacks for the base and
flat AA model setups for years 80–109 from the PRP computations. The residual
(RES) represents the difference between the radiative perturbation from runs
in which all variables, including the CO2 concentration, are replaced
simultaneously and the sum of the individual contributions from the
feedbacks,
including the PL feedback and the CO2 forcing. For an identical 3 h
sampling interval, replacing all variables yielded the same radiative
perturbation as the corresponding 2 × CO2 coupled RAD rerun. The SUM and
the RES terms in Fig. are expected to balance the
contributions from changes in AHT convergence, OHT convergence, and heat
storage. The corresponding individual contributions were diagnosed separately
as explained in Sect. 2 and they were found to be of the same order of
magnitude as the SUM term, which is much smaller than the individual
contributions of the major feedbacks, except for CL (not shown). Unfortunately,
however, as explained in Sect. 2, the diagnosed contributions do not add up
to the SUM + RES term as expected.
The difference between Fig. a and b is shown in
Fig. . Maps of the feedbacks in the base model run are
provided in Fig. . Figure shows maps of
the differences between the feedbacks in the flat AA and the base model
setup.
Red bars that are shorter than blue bars in Fig. indicate that the
difference of the local radiative feedbacks between the Arctic and
Antarctic regions has decreased in the flat AA run. The polar asymmetry for
FSU (that is, the sum of all feedbacks except for PL) has roughly halved. The main
contribution was the LR feedback, which will be further analyzed in
Sect. . In addition, the WV feedback increased in the
Antarctic region, as expected for a deeper atmospheric column. The ALB feedback changed only slightly and the overall contribution of the
CL feedback was small, in general agreement with results from other coupled
models .
The most pronounced ALB feedback in the Southern Ocean was found
north of the Antarctic Circle (Fig. ). The more positive
feedback in this region in the flat AA run (Fig. )
contributed to the overall decreased polar amplification asymmetry. The
Antarctic region as defined here was not directly affected by the sea ice
changes north of the Antarctic Circle (since it was defined as the region
south of the Antarctic Circle), but rather indirectly via meridional heat
transports. This indicates that the values in the bar charts should not be
overinterpreted. Furthermore, the small tropical LR feedback in
Fig. is noteworthy, which together with the large positive
high-latitude LR feedback, led to a positive global LR feedback during years
80–109 of this particular run. The (model-dependent) net cloud feedback over
the Pacific warm pool was dominated by a negative shortwave feedback rather
than the predominantly positive longwave feedback.
In the next section, the large contribution from the LR feedback to the
decrease in polar amplification asymmetry is analyzed in some detail. Then
the results are combined with the results from the previous sections.
Differences between the flat AA and base setups (comparable to
Fig. ).
Contribution of surface temperature change to lapse rate feedback
The LR feedback was defined as LR = TA - PL, where PL
depends only on the change in surface temperature (which is applied at each
height level throughout the atmospheric column), while for TA changes in
surface as well as the atmospheric temperatures were taken into account. In
the tropics, the atmospheric lapse rate is coupled to the surface temperature
via deep convection and via the dependence of the slope of the moist adiabat
on surface temperature. In the polar regions, where subsidence takes place
and deep convection is absent, atmospheric temperatures are less strongly
coupled to surface temperatures, and the LR feedback is less well understood.
Figure shows that the actual mid- and upper-tropospheric
temperature change in response to doubling CO2 in the Antarctic region was
similar in the base and flat AA model setups, even though assuming a flat
Antarctica affected atmospheric dynamics in various ways. This indicates that
the large difference in the LR feedback between the flat AA and the base
model setup might not only depend on changes in the mid- and upper-tropospheric temperature profile. Instead, they could have been influenced by
different surface temperatures in the base and flat AA control runs. The
apparent mismatch between the dots and crosses and the profiles at the lowest
atmospheric levels in Fig. b and d is explained by the
condition that all pressure levels where more than 20 % of the grid
points are above ground are shown in the profiles. Consequently, only a
limited number of grid points entered the average temperature for the lowest
atmospheric levels, while the average surface temperature was computed as an
average over all grid points.
In order to find out whether the difference of the LR feedback between the
flat AA and the base run can be attributed to differences in atmospheric
temperatures or in surface temperatures, a number of PRP sensitivity
computations were conducted in which variables from flat AA model runs were
substituted into results of runs from the base setup (see
Sect. and Table for details). The results
from these runs are shown in Fig. .
In the first sensitivity experiment (LRPLsens) surface air and atmospheric
temperature were taken from the flat AA setup to perform the PRP
computations. The LR feedback in this sensitivity computation is similar to
the LR feedback in the flat AA standard PRP computation. This indicates that
the depth of the atmospheric column was not the main reason for the
difference in the LR feedback between the flat AA and base model setups.
In the second sensitivity computation (LRSens), only the atmospheric
temperatures were taken from the flat AA setup, and in the third computation
(PLSens) only the surface temperatures were taken from the flat AA setup.
When only atmospheric temperatures were replaced, the LR feedback was
similarly strong to the one in the base setup. Applying only the surface
temperatures from the flat AA model setup in the base model setup, however, explained the stronger Antarctic LR feedback in the flat AA model
setup, even though the actual atmospheric lapse rate above the lowest
atmospheric model layer did not change in the PRP computations.
In other words, the difference of LR = TA - PL between the flat AA
and base runs appeared to be dominated by a change of PL and not by a
change of TA, and it is therefore difficult to interpret the changes in the LR
feedback in terms of atmospheric lapse rate changes
Consequently, the LR and PL feedbacks will be
considered together in the next section. The rationale for this is that in the present study
setup the sum LR + PL in the Antarctic region is mainly sensitive to
changes in surface temperature and not to changes in the atmospheric lapse
rate above the surface layer. Note that by definition, LR + PL
corresponds to total temperature feedback TA, i.e., the perturbation that is
obtained by substituting the surface as well as the atmospheric temperatures.
The definition of the TA feedback is identical to the definition of the
longwave feedback in a study by and to the definition
of the temperature feedback in a study by .
The usual decomposition of the total temperature feedback into PL and LR
feedbacks is nevertheless useful for understanding polar climate change. As
explained above, the PL feedback is defined as the hypothetical feedback that
would be expected if the atmosphere would warm at the same rate as the
surface. However, the polar atmosphere generally warms less than the surface
due to a lack of vertical mixing (e.g., Manabe and Wetherald, 1975). Conversely, the
tropical atmosphere warms more than the surface.
Therefore, in order to radiate away a given amount of energy, a larger surface
warming is required in the polar regions compared to the tropics (Pithan and
Mauritsen, 2014). The lack of atmospheric warming in the polar atmosphere
relative to the surface is reflected in the large positive polar LR
feedback.
Local radiative forcing, feedbacks, and heat transport
In Sect. it was argued that the partitioning between the
atmospheric and oceanic heat transport toward Antarctica strongly depends on
the exact latitude that is used to define the Antarctic region. Furthermore,
in Sect. it was argued that the ALB feedback
outside the Antarctic region as defined by the grid points poleward of the
Antarctic Circle almost certainly acts to decrease the polar amplification
asymmetry in contrast to the ALB feedback inside the region.
Furthermore, in Sect. it was explained that closing the
energy budgets turned out to be more problematic than anticipated, especially
for the Arctic. In spite of these caveats, a comparison between local
forcings, feedbacks, changes of heat transport convergence, and heat storage
terms is attempted here.
Average air temperature profiles for the Antarctic and Arctic
regions from the coupled runs and differences (2 × CO2 minus control) for
the base and flat AA model setups for years 80–109. Dots and crosses
denote average surface air temperature at the region average surface
pressure. Dots correspond to solid lines and crosses to dashed lines. Only pressure
levels where more than 20 % of the grid points are above the ground are
shown in the profiles.
Arctic minus Antarctic difference of the lapse rate (LR) and Planck
(PL) feedbacks in the base and flat AA model setups and for the sensitivity
calculations described in Table . All computations are based on
PRP calculations using 73-hourly instantaneous model output, and the original
base and flat AA runs are analyzed.
Figure essentially shows the difference between the blue and
red bars in Fig. , where PL and LR have been combined into
a single temperature feedback based on the arguments in Sect. ,
and FSUP is defined as the sum of all feedbacks, including the Planck
feedback. In addition, the heat transport convergence differences and the
heat storage terms are shown. On the whole, it appears as if the changes in
local feedbacks have increased the asymmetry, although this finding depends
on whether or not one chooses to follow the arguments in the previous section
and to include the Planck feedback here. Apart from the LR feedback (see
Sect. ), which was here combined with the Planck feedback into
a single temperature feedback, only the CO2 forcing and the WV feedback
acted to decrease the polar amplification asymmetry.
Changes in AHT and also changes in
heat content (heat storage terms) appear to have contributed to the decreased
asymmetry found in the previous sections. Part of the reason for the change
in heat content being fairly important is that the ocean heat content south
of the Antarctic Circle decreases in the flat AA base run and increases in
the flat AA 2 × CO2 run.
This result should, however, not be over-interpreted since for example the
albedo feedback would most likely contribute to the overall decrease in
asymmetry if contributions from outside the region were also taken into
account. Furthermore, in Sect. , it was argued that OHT also contributed to an overall decrease in asymmetry since it
transports heat to the Southern Ocean, where the atmospheric heat transport
then becomes more dominant. Finally, in Sect. it was shown that small OHT
changes in response to doubling CO2 across the Arctic Circle that
contribute to the OHT difference in Fig. depend on whether
the original runs or the RAD reruns are analyzed.
In a more qualitative sense, Fig. suggests that contributions
from changes of heat transport convergence and from heat storage (which would
be zero in equilibrium) were of roughly the same magnitude as contributions
from local feedbacks, indicating that local feedbacks and changes in heat
transport convergence both played a role.
Difference flat AA minus base setup of
FAR-FAA, where
FAR-FAA is the difference between the
Arctic and Antarctic regions shown in Fig. . For the
forcing and the feedbacks, this corresponds to the difference between the red
and the blue bars in Fig. .
FSUP = PL + LR + WV + ALB + CL is the sum of all
feedbacks, including the Planck feedback. It is compared to contributions from
atmospheric and oceanic heat transport (AHT, OHT) and heat storage (HS). The
residual (RES) is defined as the difference between HS and the sum of
forcing, feedbacks, and heat transport convergence
(CO2 +FSUP + AHT + OHT).
Evolution of surface temperature in the coupled runs
Figure shows the temporal evolution of the zonal mean surface
temperature in the control runs and the 2 × CO2 runs for the original
coupled runs. As expected, the largest surface temperature response to
the assumption that Antarctica is flat occurred during the first decades of the flat
AA control run (Fig. c). These decades were not taken onto
account in the preceding analysis. After this, the surface temperatures
remained fairly stable in the flat AA control run, although the deep ocean
was still adjusting. Taking the difference between the flat AA 2 × CO2 run
and the flat AA control run (as was done in the preceding sections) is
expected to remove most of the latter effect.
Figure b and d show that Antarctic surface temperatures increased
faster in the flat AA 2 × CO2 run than in the base 2 × CO2 run, as
expected based on the previous sections. The Arctic temperatures varied
strongly due to internal variability, which helps to explain the differences
between the original coupled run and the coupled reruns with half-hourly
radiation calls, which have been pointed out in the discussion of the ocean
heat transport in Sect. .
The weaker Arctic warming in the middle of the 2 × CO2 base run
(Fig. b) is an indication of a slowing of the ocean's
meridional overturning circulation (MOC). Such a slowdown has often been
found in CO2 perturbation experiments, and it tended to be stronger in
low-resolution, low-complexity models compared to state-of-the-art
high-resolution models. Since the CESM was run at a low resolution in this
study, this finding should also not be overinterpreted. In the 2 × CO2
flat AA run, the MOC started to slow down earlier than in the 2 × CO2 base
run (Fig. d), which might indicate that assuming a flat
Antarctica did not only influence the Antarctic region but also the Arctic
region. For a more reliable estimate of this effect, coupled runs at a higher
resolution and an ensemble of model runs with slightly perturbed initial
conditions would be required.
Difference between the zonal mean surface air temperature and the
time-averaged zonal mean surface air temperature from the corresponding
control run (Tav) in the control and the 2 × CO2 run for the
base and flat AA model setups.
(a) Shows the 25-year running mean of the temperature difference
between the 2 × CO2 and control runs for the Arctic and Antarctic
regions in the base and flat AA model setups and (b) ratio of
Arctic to Antarctic amplification based on 25-year running mean time
series.
Figure a shows the evolution of the Arctic and Antarctic
surface temperature for the base and flat AA model setups, and
Fig. b shows ratios of the Arctic to the Antarctic
amplification, which are computed as
f=AArAAA=T^Ar,2xCO2-T^Ar,ControlT^AA,2xCO2-T^AA,Control,
where T^ is a regional average 25-year running mean temperature.
It should be noted that Antarctic warming relative to the respective control
run (Fig. a) was stronger in the flat AA than in the base
model setup throughout almost the entire 600-year period. However, even
though the temperature in the flat AA control run stabilized after a moderate
initial warming and even though the temperature evolution from the control
run was subtracted in this analysis, it cannot be completely ruled out that
this moderate initial warming could have also played a role in the later
development in the 2 × CO2 flat AA run. Therefore, in retrospect, starting
the flat AA 2 × CO2 run from a separate long flat AA spinup run and
prescribing a more realistic gradual increase of the CO2 concentration,
which would allow the inspection of the first decades of the CO2 perturbation
experiments, would have been better.
After 250 years, f was lower than unity in the base and the flat AA model
setup, which indicates that the Antarctic temperature increase was stronger
than the Arctic temperature increase in both model setups. This finding is
related to a slowdown of the north Atlantic MOC in both of the 2 × CO2
runs, which could in part be a transient feature as the MOC recovery times are
known to be extremely long. Again, in order to gain confidence in this
result, additional ensemble model runs at higher resolution and ideally also
a comparison with results from a multi-model ensemble would be necessary.
Since the aim of the various model sensitivity runs has been to investigate
the sensitivity of the polar amplification asymmetry to Antarctic surface
height (and not to provide a future projection of Antarctic climate change
under global warming), the runs were performed without an ice sheet model. In
order to arrive at a more credible projection of Antarctic climate change,
state-of-the-art high-resolution models that include state-of-the-art ice
sheet dynamics models should be used.
Conclusions
Idealized CO2-doubling experiments in a low-resolution coupled climate
model were performed in order to investigate the effects of Antarctic surface
height on the polar amplification asymmetry. It was found that Antarctic
surface height indeed played an important role in the slower Antarctic
warming, as expected based on the early climate model study by .
Furthermore, it was found that assuming Antarctica to be flat strongly
reduced the hemispheric asymmetry of the zonal mean top of the atmosphere
radiation budget, which already by itself indicates that meridional heat
transport was also more symmetric in the flat AA model setup.
The polar amplification in the 2 × CO2 runs also became notably more
symmetric when Antarctica was assumed to be flat. In addition to meridional
heat transport, the stronger CO2 radiative forcing and the stronger
WV feedback over Antarctica in the flat AA runs also contributed to the
decrease in asymmetry. All of these changes were expected in the deeper
atmospheric column that resulted from assuming Antarctica to be flat. For
OHT and the albedo feedback it was argued that changes
north of the Antarctic Circle also had to be taken into account when assessing
their contribution to the decreased polar amplification asymmetry in the flat
AA runs. Both decreased rather than increased the polar amplification
asymmetry in the flat AA 2 × CO2 run.
Among the local radiative feedbacks, the biggest contributor to the decreased
polar amplification asymmetry was the LR feedback, in agreement with
. However, based on results from additional experiments, it was
argued that in this particular model setup, the change of the LR
feedback was mainly linked to the change in surface temperature and was much less
dependent on changes in the atmosphere above the surface. Therefore, it was
argued that one might combine the LR and PL feedbacks into a
single temperature feedback. The disadvantage of this approach is that it
blurs the distinction between the PL and LR feedbacks.
Although the rationale for decomposing the total temperature feedback into
the PL and LR feedbacks is less clear in the polar regions
than in the tropics, such a decomposition is nevertheless useful for
understanding polar climate change see e.g.,. A more
detailed discussion of this issue was given at the end of Sect. .
Other important factors such as stratospheric ozone depletion ,
which were found to contribute to the polar amplification asymmetry in
previous studies, were not investigated in this study.
Given the important role of increased atmospheric heat transport in the flat
AA runs in the present study, one could argue that a decrease in land height
due to Antarctic melting would be favorable for increased AHT from midlatitudes. Consequently, once the Antarctic surface height
is lowered due to melting, it would be more difficult to restore the
Antarctic ice sheet due to increased AHT.
Finally, it was found that assuming a flat Antarctica may not only influence
the Antarctic but also the Arctic region. However, in order to arrive at more
reliable results regarding this point, one would have to perform an ensemble
of higher-resolution model runs because it has long been understood that the
MOC can be overly sensitive to perturbations in low-resolution coupled
models. Potential future studies based on coupled climate model runs that aim
to study the influence of surface elevation on the polar amplification
asymmetry, which is found in present-day observations and also in future
climate projections (which often span only 1 or 1.5 centuries),
would benefit from a separate long, flat AA spinup run and from prescribing a
more realistic gradual increase in the CO2 concentration.