GMDGeoscientific Model DevelopmentGMDGeosci. Model Dev.1991-9603Copernicus GmbHGöttingen, Germany10.5194/gmd-8-3621-2015Ice-sheet configuration in the CMIP5/PMIP3 Last Glacial Maximum experimentsAbe-OuchiA.abeouchi@aori.u-tokyo.ac.jphttps://orcid.org/0000-0003-1745-5952SaitoF.https://orcid.org/0000-0001-5935-9614KageyamaM.BraconnotP.HarrisonS. P.LambeckK.Otto-BliesnerB. L.https://orcid.org/0000-0003-1911-1598PeltierW. R.https://orcid.org/0000-0002-5555-7661TarasovL.PeterschmittJ.-Y.https://orcid.org/0000-0003-3486-3157TakahashiK.Atmosphere Ocean Research Institute, University of Tokyo, 5-1-5, Kashiwanoha, Kashiwa-shi, Chiba 277-8564, JapanJapan Agency for Marine-Earth Science and Technology, 3173-25 Showamachi, Kanazawa, Yokohama, Kanagawa, 236-0001, JapanLaboratoire des Sciences du Climat et de l'Environnement/Institut Pierre Simon Laplace unité mixte de recherches CEA-CNRS-UVSQ,
Orme des Merisiers, point courrier 129, 91191 Gif sur Yvette Cedex, FranceCentre for Past Climate Change and School of Archaeology, Geography and Environmental Sciences, University of Reading, Whiteknights, Reading, RG6 6AH, UKResearch School of Earth Sciences, The Australian National University, Canberra, ACT 0200, AustraliaClimate and Global Dynamics Division, National Center for Atmospheric Research, Boulder, CO 80305, USADepartment of Physics, University of Toronto, 60 George Street, Toronto, Ontario, M5S 1A7, CanadaDepartment of Physics and Physical Oceanography, Memorial University of Newfoundland, St. John's, NL A1B 3X7, CanadaA. Abe-Ouchi (abeouchi@aori.u-tokyo.ac.jp)6November20158113621363728April20153June201525September20158October2015This work is licensed under a Creative Commons Attribution 3.0 Unported License. To view a copy of this license, visit http://creativecommons.org/licenses/by/3.0/This article is available from https://gmd.copernicus.org/articles/8/3621/2015/gmd-8-3621-2015.htmlThe full text article is available as a PDF file from https://gmd.copernicus.org/articles/8/3621/2015/gmd-8-3621-2015.pdf
We describe the creation of a data set describing changes related to the
presence
of ice sheets, including ice-sheet extent and height, ice-shelf extent,
and the distribution and elevation of ice-free land at the Last Glacial
Maximum (LGM), which were used in LGM experiments conducted as part of the fifth
phase of the Coupled Modelling Intercomparison Project (CMIP5) and the
third phase of the Palaeoclimate Modelling Intercomparison Project
(PMIP3).
The CMIP5/PMIP3 data sets were created from reconstructions
made by three different groups, which were all obtained using
a model-inversion approach but differ in the assumptions used in the
modelling and in the type of data used as constraints.
The ice-sheet
extent in the Northern Hemisphere (NH) does
not vary substantially between the three individual data sources.
The difference in the topography of the NH ice sheets is also moderate, and
smaller than the differences between these reconstructions (and the
resultant composite reconstruction) and ice-sheet reconstructions used
in previous generations of PMIP.
Only two of the individual
reconstructions provide information for Antarctica.
The discrepancy
between these two reconstructions is larger than the difference for the
NH ice sheets, although still less than the difference between the
composite reconstruction and previous PMIP ice-sheet
reconstructions.
Although largely confined to the ice-covered regions, differences between the
climate response to the individual LGM reconstructions extend over the North
Atlantic Ocean and Northern Hemisphere continents, partly through atmospheric
stationary waves. Differences between the climate response to the
CMIP5/PMIP3 composite and any individual ice-sheet reconstruction are
smaller than those between the CMIP5/PMIP3 composite and the ice sheet
used in the last phase of PMIP (PMIP2).
Introduction
There are large differences in the modelled response to scenarios of future
climate forcing . Modelling of past climate
states, and evaluation of the simulations using paleoclimate reconstructions,
provide unique opportunities to assess the performance of models used for
future climate projections when subjected to large changes in forcing
.
Palaeo-evaluations are also useful in identifying the causes of inter-model
differences in simulated climate responses
. Thus, the simulation of past climates
provides an opportunity to identify and quantify systematic biases that are
likely to be present in future climate projections and to explore the
potential causes of inter-model spread in these projections. The Last Glacial
Maximum (LGM, ca. 21 000 yr BP) is an exemplary period for such an exercise
because the change in global forcing (relative to the present) was large and,
although the forcing was different in nature, similar in magnitude to that
expected by the end of the 21st century . The LGM has
been a major focus for simulations since the early days of numerical
modelling
e.g..
It was chosen as a focus for model experiments in both Phase 1 and Phase 2 of
the Palaeoclimate Modelling Intercomparison Project (PMIP:
) because of the availability of
syntheses of palaeoclimatic reconstructions
(e.g.)
for model evaluation. It is perhaps not surprising then that the LGM was one
of the simulations chosen when palaeoclimate experiments were first included
in the fifth phase of the Coupled Modelling Intercomparison Project (CMIP5:
). The LGM simulations are further
examined to constrain the climate sensitivity, which is an important metrics
for the future climate projection
.
Factors affecting climate that are not simulated explicitly, usually
designated boundary conditions, need to be specified in both control and
palaeoclimate model simulations. The boundary conditions that must be
specified for the LGM experiment are a (relatively small) change in orbital
forcing, reduced atmospheric concentrations of greenhouse gases, and the
presence of large ice sheets. Land-surface conditions, in particular the
distribution of vegetation , were also
different at the LGM. On the other hand, the spatial coverage of information
on LGM vegetation is currently insufficient to provide a gridded global data
set to use as a model input. LGM vegetation was therefore either computed by
the model or prescribed to be the same as the pre-industrial control
simulation. However, the changes in orbital forcing and greenhouse gas
concentrations are well known. The expansion of the ice sheets at the LGM
resulted in a sea-level lowering of ca. 130 m and changed
palaeogeography. The marginal limits of the North American (Laurentide),
Greenland and European ice sheets are increasingly well constrained by
radiocarbon-dated moraines and other glacial deposits
(e.g.).
However, there is little direct evidence for the distribution of ice mass,
and this must therefore be inferred through a combination of physical
modelling and the use of indirect observational constraints (such as
information on relative sea-level changes). Thus, the specification of
ice-sheet topography has been a major source of uncertainty in defining
boundary conditions for LGM experiments.
The earliest LGM simulations made use of a reconstruction of ice-sheet extent
and height made by the CLIMAP project .
Subsequently, the PMIP project made use of reconstructions based on two
different generations of an isostatic rebound model: ICE-4G
in the first phase of the project (PMIP1) and
ICE-5G v1.1 in PMIP2 . The inferred ice volume was
ca. 35 % lower in ICE-4G than in the earlier CLIMAP
reconstructions, resulting in considerably lower maximum elevations for the
Laurentide and European ice sheets. The Laurentide has a greater volume in
ICE-5G than ICE-4G, and the Keewatin Dome is 2–3 km
higher over much of central Canada, but the European ice sheet is less
extensive in ICE-5G than ICE-4G.
The lowering of CO2 makes a large contribution to the cooling at the
LGM
,
but the ice sheets (and the changes in albedo caused by the change in
land–sea geography associated with the growth of these ice sheets and
lowering of sea level) also have an important impact on both regional and
global climates, particularly in the NH. Furthermore, the change in ice
sheets affects the carbon cycle and atmospheric CO2 concentrations in
glacial cycles . Ice-sheet
height has major impacts on surface temperature via lapse rate,
planetary-scale atmospheric circulation and the location of storm tracks, and
hence precipitation patterns, and even on ocean circulation. Simulations
using different ice-sheet configurations have demonstrated these large
differences both in global mean temperature and in NH circulation patterns
and regional temperatures
().
At the time of the definition of the PMIP3 boundary conditions, there were
several candidate ice-sheet reconstructions that could have been used as
a boundary condition for the CMIP5/PMIP3 LGM simulations (ICE-6G v2.0:
; GLAC-1a: ; ANU:
), which differ in the assumptions used in the
modelling and in the type of data used as constraints on these models. The
purpose of this paper is to explain the ice-sheet configuration that was used
in the CMIP5/PMIP3 simulations, which was created by blending the three
individual realisations, and to explore the consequences of this choice. This
paper provides the information on the difference between the individual ice
sheets and the blended ice sheet as well as ice-sheet configuration of
previous phases of PMIP. The individual ice-sheet reconstructions are
described in Sect. , and the procedure for creating
the blended ice sheet is described in Sect. .
The differences between this blended ice sheet, the individual ice-sheet
reconstructions, and previous ice-sheet configurations used by PMIP, and
their impact on forcing and climate, are discussed in
Sect. . The final section of the paper
highlights the uncertainties associated with the specification of the
CMIP5/PMIP3 ice sheet. It makes recommendations for further work to
investigate the impact of ice-sheet configuration on climate change as well
as to minimise these uncertainties.
Documentation of the original ice-sheet reconstructionsICE-6G v2.0 ice reconstruction
ICE-6G is the latest of a series of inversions of a glacial isostatic
adjustment (GIA) model based on the solution for the impulse response of
a viscoelastic Earth to surface loading described by , in
which global ice history and radial Earth viscosity profiles are repeatedly
tuned to improve model predictions of relative sea-level (RSL) histories and
present-day deformation rates compared to observations
.
The model is based upon detailed and continuously updated analyses of the
data of each of the previously glaciated regions (North America:
; Fennoscandia:
; Greenland:
; the British Isles:
; Patagonia: ; and
Antarctica: ), where each regional analysis is
performed in a global context to yield a globally consistent response. In the
most recent versions of the model, including the one used as an input to the
CMIP5/PMIP3 composite ice sheet, satellite geodetic data (e.g. GPS, GRACE)
are used to provide additional constraints .
ICE-4G was used to define the land–sea mask, the
ice-sheet extent and elevation, and land-surface topography and palaeo-ocean
bathymetry in the first phase of PMIP (PMIP1) and
ICE-5G in the second phase of PMIP (PMIP2).
ICE-5G was improved relative to ICE-4G largely through the
incorporation of revised information about the extent of the Eurasian ice
sheets at the LGM from the QUEEN project
and the use
of gravity changes across North America from the GRACE satellite as an
additional constraint.
ICE-6G (or more precisely ICE-6G version 2.0 VM5a T60 Rot)
differs from previous inversions through more extensive use of geodetic data
as a constraint, including e.g. the Global Positioning Satellite (GPS),
satellite laser ranging (SLR), very long baseline interferometry (VLBI), and
Doppler Orbitography and Radiopositioning Integrated by Satellite (DORIS).
The model uses the VM5a mantle viscosity profile with an elastic lithosphere
thickness of 60 km (T60). VM5a is a three-layer approximation of the
VM2 T90 profile described by , in which the lithosphere
consists of a 60 km thick elastic layer above a 40 km thick
layer that is higher viscous. This modification was made to improve the fit
of the model to observations of horizontal displacement rates in North
America. ICE-6G also takes account of the Earth's rotational effect
(Rot) on the geoid. The sea-level predictions from ICE-6G have been
shown to provide a good fit to several hundred Holocene RSL curves
, including Holocene RSL observations for the Caribbean Sea
and the Atlantic coast of North America .
showed that a further improvement to the match between
observations and predictions for the southern part of the Atlantic coast
could be obtained by reducing the viscosity on the upper mantle (above
660 km) from 0.5×1021 Pa s (VM5a) to 0.25×1021 Pa s (VM5b). However, subsequent work has shown
that an even better match is obtained by reducing the viscosity of the upper
part of the lower mantle.
GLAC-1a ice reconstruction
The GLAC-1a reconstruction is based on a set of glaciological models that are
derived from a plausible climate forcing based on PMIP1 and PMIP2 results for
LGM and that fit independently derived ice margin chronologies, within
explicit uncertainties. The climate forcing involves an interpolation between
present-day observed climatologies and the set of highest-resolution LGM
fields from PMIP1 and PMIP2 data sets. The interpolation is weighted
according to a glaciological inversion of the GRIP record
for regional temperatures over the last glacial cycle.
The North American and Eurasian reconstructions are derived from separate
Bayesian calibrations of the Glacial Systems Model (GSM). The GSM
incorporates a 3-D thermo-mechanically coupled ice-sheet model based on the
shallow ice approximation, a permafrost resolving bed thermal model, an
asynchronously coupled down-slope surface drainage/lake depth solver, and
also includes thermodynamic lake ice, sub-glacial till deformation, buoyancy
and temperature-dependent ice calving, and an ice-shelf representation
. The
visco-elastic bedrock response uses either the VM2 (as used in ICE-5G)
or VM5a (used in ICE-6G) earth rheologies. RSL is computed using
a gravitationally self-consistent formalism similar to that of
, except that it includes an eustatic approximation for
dealing with changing ocean masks and does not take account of Earth
rotational effects .
Separate calibrations are made for North America and Eurasia. The calibration
involves 36 ensemble parameters for North America and 29 ensemble parameters
for Eurasia, to capture uncertainties in deglacial climate and ice dynamics.
The majority of these parameters are used for the climate forcing, including
weighting the empirical orthogonal functions (EOFs) between PMIP models for
LGM monthly precipitation and temperature, regional desert elevation effects,
and LGM atmospheric lapse rate. Other ensemble parameters adjust the calving
response, the effective viscosity of subglacial till, the strength of the
ice-marginal constraint, and flow parameters for ice shelves. Model runs are
forced to stay within uncertainties of independently derived ice margin
chronologies for North America and Eurasia
. Calibration targets include RSL observations from 512
sites , geologically inferred deglacial ice-margin
chronologies, and geodetic constraints from . In the case
of North America, the calibrated ensemble is further scored with respect to
strand lines (paleo lake-level indicators) and observations of the maximum
level of marine inundation. Model runs are penalised in proportion to the
amount of margin correction (or “margin forcing”; see Sect. 2.4 of
) required, so the calibration is directed towards
a climate forcing that is consistent with the margin chronology.
The model was originally calibrated using the ICE-4G ice load
reconstruction for Antarctica and the VM2 Earth rheology. However, the
subsequent use of an expanded geodetic data set for North America coupled
with the significant reduction in LGM Antarctic ice volume in
ICE-6G v.2 compared to ICE-4G led to a significant misfit with
the far-field Barbados RSL record. A random 2000 member ensemble was
generated along with a rerun of the best 300 previously calibrated parameter
sets and some 200 attempts at hand-tuning. There is a significant tradeoff
between fitting the Barbados constraint and fitting the constraints from
other locations. In order to satisfy the Barbados constraint, the 1.5 sigma
upper limit of the previously calibrated ensemble for North America (which
almost reaches the inferred Barbados record for 26 to 21 ka) was
used. A weighted ensemble mean of the model runs that passed hard threshold
constraints in the previous calibration was used for North America. The
Eurasian calibration converged and was successful, except for minor issues
with the Norwegian fjords. A single run with the largest 26 ka RSL
contribution to the Barbados record was therefore used. A single run was
chosen to ensure consistency between drainage fields and the surface
topography. The Greenland model is from ,
a glaciological model with hand-tuned climate adjustments to enforce fit to
RSL records and the GRIP borehole temperature record.
ANU ice reconstruction
The ANU reconstruction has also evolved over a period of years in an
iterative fashion . The first
iterations were based on the analysis of far-field sea-level data, where the
sea-level signal is predominantly a measure of the changes in total ice
volume (the ice-volume equivalent sea level or ESL). The principle isostatic
contribution to these sea levels is from the change in water load, a function
of the rate at which water is added into or removed from the oceans and how
it is distributed within ocean basins. Simple models were initially used for
the ice sheets. The separation of mantle rheology from the ESL function was
achieved by using the spatial variability of the far-field sea-level signals
. The resulting ice volume was then redistributed between
the ice sheets using scaling relations initially and iterating between
far-field and near-field solutions to ensure convergence
.
Inversions were also made for individual NH ice sheets using new compilations
of field data from within and close to the ice margins, which are sensitive
to the ice model and mantle rheology. Separate reconstructions have been made
for Scandinavia , the Barents–Kara region
, Greenland , the
British Isles , and North America
(Lambeck, Purcell and Zhao, unpublished). These separate solutions allow
lateral variability in mantle viscosity beneath the individual ice sheets to
be detected, as well as differences between oceanic and continental mantles
. Some interactions occur between the separate ice-sheet
solutions, requiring further iterations as each ice-sheet model is modified.
The field data from Antarctica are insufficient to use a similar approach to
reconstruct ice-volume changes. Volume changes for the Antarctic ESL were
obtained as the difference between the global ESL and
the NH ESL, the latter being the sum of the individual ice-sheet
contributions, and including mountain deglaciation in both hemispheres
. The ice in Antarctica was then distributed using the
LGM ice margins proposed by , and assuming the ice
profiles followed the quasi-parabolic function proposed by . The
retreat history is determined by the difference between the global ESL
function and the combined Northern Hemisphere mountain-glacier contributions.
This reconstruction is not meant to be an accurate reflection of Antarctic
ice history. Rather it is a convenient way of disposing of ice volume that
cannot be attributed to the NH ice sheets in a way that does not impact in
a major way on the far-field and NH analyses.
Several iterations have been performed to combine the far-field and
individual ice-sheet reconstructions. The results used to create the
CMIP5/PMIP3 composite are based on solutions current in 2009. The inversions
yield changes in ice thickness compared to the present-day volume of each ice
sheet. Thus, the LGM ice thickness is obtained by adding the present-day ice
thickness. The LGM ice elevation with respect to sea level at the LGM is
obtained by subtracting the sea-level change (geoid change beneath the ice
sheet) from the LGM ice thickness. The ESL function used in these solutions
is defined as all land ice and grounded ice on the shelves. The LGM ocean
margin is defined by the ice-grounding line .
Construction of the composite CMIP5/PMIP3 ice sheetsTerminology
We use the term “topography” to refer to the elevation of the upper ice
surface if the land is covered by ice, including floating ice, or the
elevation of the land surface or ocean floor in areas not covered by ice or
floating ice. Topography can be expressed either relative to modern sea level
or relative to the sea level at a specific time t. We use
Topo(t) for topography relative to the sea level at time t, and
topo(t) for topography expressed relative to the modern sea level
(i.e. when t is 0).
Surface elevation (Surf) is the elevation of the bottom of the
atmosphere. Surf(t) is defined as
Surf(t)=max0,Topo(t),
which is 0 for ocean grid points and topography otherwise. Bathymetry
(Bath) is the elevation of the ocean floor under ice shelves or
topography otherwise.
There are four components that need to be provided to define
ice-sheet-related boundary conditions at the LGM: the difference in surface
elevation (ΔSurf), an ice mask (Mask1), an
ice-shelf mask (Mask2) and a land–sea mask
(Mask3). The first term (ΔSurf) is the
difference in the surface elevation between LGM and the present day. The
three masks define the conditions at individual grid points. In the ice mask
(Mask1), 0 indicates ice-free and 1 indicates ice-covered
grid points, including floating ice points. In the ice-shelf mask
(Mask2), 0 indicates ice-free points, 1 indicates
grounded ice, and 2 indicates floating-ice grid points. In the land–sea
mask (Mask3), 0 indicates land and 1 indicates ocean grid
points. This information is provided for the domain from -180 to
179∘ in longitude and -89.5 to 89.5∘ in latitude, at
a spatial resolution of 1∘× 1∘.
The spatial domain and output variables provided by each of
the individual ice-sheet reconstructions, ICE-6G v.2, GLAC-1a and ANU.
Latitude and longitude ranges are expressed in decimal degrees, where
positive indicates north and east respectively and negative indicates
south and west.
The difference in the surface elevation at the LGM can be computed as
ΔSurf(21ka)=Surf(21ka)-Surf(0ka).
However, each of the individual ice-sheet reconstructions provides different
outputs corresponding to the terms on the right-hand side of this equation
(Table ). ANU provides estimates of the change in
thickness between the LGM and the present day (ΔThick) and
relative sea level (RSL), GLAC-1a provides Thick and
topo(21ka), while ICE-6G provides
Topo(21ka) and bathymetry Bath(21ka)
as well as providing explicit masks for 21 and 0 ka. In order to
produce the composite CMIP5/PMIP3 data set, it was therefore necessary to
transform the original outputs before interpolating these data onto a common
grid.
The domain of ICE-6G v2.0 is the same as that used in the composite
CMIP5/PMIP3 reconstructions, so no spatial transformation was needed. The
difference in the surface elevation at the LGM compared to the present day
was computed from the original variables as
ΔSurf(21ka)=max0,Topo(21ka)-max0,Topo(0ka).
The ice mask, Mask1(21ka), was extracted directly from
the original reconstruction. The ice-shelf mask, Mask2(21ka), was computed from Topo and Bath as
Mask2(21ka)=2ifTopo≠Bath,Mask1otherwise.
The ANU reconstruction provides RSL and (ΔThick) for
four separate regions (Table ). RSL over the British Isles
was computed under the assumption that the present day is in equilibrium,
with a mantle density of 4500 kgm-3. These terms were first
interpolated to the PMIP3 spatial grid, but no attempt was made to attribute
values to grid points beyond those covered by the original data set.
The LGM topography was computed as
Topo(21ka)=Topo(0ka)+ΔThick-RSL,
where Topo(0ka) was derived from the ETOPO1 data set
. Ice-covered grid points that were still under
0 m (i.e. sea-level elevation) after this procedure were corrected
using an ice-floating adjustment, using ice and water densities of 910 and
1028 kgm-3 respectively. Topography was then converted to
ΔSurf using Eq. (). There are several grid
cells (e.g. near ice divides) where ice is present but ΔThick=0. A modern reference ice mask is therefore required to
compute the LGM ice mask for the ANU reconstruction. The LGM ice mask
was therefore computed as
Mask1(21ka)=0if Topo≠Bath,1else if ICE-6GMask1=1,1else if ΔThick(21ka)>0,0otherwise.
The ice-shelf mask was computed as
Mask2=2if Topo(21ka)<0,1if Mask1=1,0otherwise.
The GLAC-1a reconstruction provides Thick(21ka)
and topo(21ka) for North America and Eurasia, and
specifies the global sea-level change of 116m. The topography
relative to the LGM sea level is computed as
Topo(21ka)=topo(21ka)+116m.
The resulting values were then interpolated to the PMIP3 grid, although no
attempt was made to attribute values to grid points beyond those covered by
the original data set (i.e. Antarctica). Grid points that were ice-covered
but below sea level were corrected using the same floating-ice adjustment as
used for the ANU reconstruction. ΔSurf was then
computed using Eq. (). The ice mask was computed from
Thick(21ka) as
Mask1=0if Thick(21ka)=0,1otherwise.
The ice-shelf mask was computed using Eq. ().
Integration of the three reconstructions
The CMIP5/PMIP3 composite ice-sheet reconstruction was created from the three
transformed individual reconstructions. The LGM ice mask was taken as the
maximum possible coverage:
Mask1,ave=1if at least one of thethreeMask1is 1,0otherwise.
The surface elevation for ice-free grid cells was taken from
ICE-6G v.2, while the difference in the surface elevation for
ice-covered grid cells was computed by averaging the three reconstructions:
ΔSurf=(ΔSurf′(ANU)+ΔSurf′(ICE-6G)+ΔSurf′(GLAC-1))/Ndwhere Mask1,ave=1,ΔSurf(ICE-6G)otherwise,
where Nd is the number of individual data sets (i.e. between 1
and 3) which provide a value for ΔSurf for a given grid
point, and ΔSurf′ is the surface elevation field extended
over undefined grid points such that
ΔSurf′=ΔSurfif defined,0if undefined (no quantity).
The ice-shelf mask is computed as the minimum possible shelf coverage.
Mask2,ave=1if at least one of the three Mask2 is 1,0if all of the three Mask2 are 0,2otherwise.
The resulting mask had five glaciated grid points where ΔSurf was anomalously much lower than the surrounding points. We
took the average value of the surrounding grid points, in order to avoid
unrealistic spatial variability in ice-sheet topography. The present-day area
of the Caspian Sea was included in the LGM land–sea mask, and a small number
of land grid cells spuriously assigned to the ocean were also corrected.
Implied changes (Last Glacial Maximum–present) in ice volume for the Laurentide, Eurasian and Antarctic
ice sheets, expressed in terms of impact on eustatic sea level (in m). The
impact of eustatic sea level is inferred by assuming no change in ocean area
compared to today (assumed ocean area: 360 768 576 km2),
and using densities for ice and water of 910
and 1028 kgm-3
respectively. Results are shown for the three individual reconstructions
(ICE-6G v.2, GLAC-1a, ANU) and for the composite
CMIP5/PMIP3 ice sheets, and compared to the implied changes for the ice
sheets used in the Last Glacial Maximum simulations run in the first and
second phases of the Palaeoclimate Modelling Intercomparison Project (PMIP1,
PMIP2).
North AmericaEurasiaAntarcticaTotalICE-6Gv.276.817.515.6113.0GLAC-1a76.614.0Not reconstructedNot availableANU82.518.229.0130.0CMIP5/PMIP3 composite78.616.622.3121.5PMIP1(ICE-4G)60.529.121.7117.8PMIP2(ICE-5Gv1.1)74.620.317.3112.2Comparison of the ice-sheet reconstructionsComparison of the individual ice-sheet reconstructions
The ANU reconstruction shows larger changes in all of the individual
ice sheets than shown by either the GLAC-1a or the ICE-6G v.2
reconstruction, while the GLAC-1a reconstruction shows smaller changes
in NH ice-sheet volume than the other two reconstructions
(Table ). The estimates for the Laurentide Ice Sheet, when
expressed in terms of eustatic sea level, vary from 83 to 77 m, and
the estimates for the Eurasian ice sheet from 18 to 14 m. The
GLAC-1a reconstruction shows the Laurentide Ice Sheet as a single
broad dome, with maximum elevations (< 3000 m) in the west
(Fig. ). ICE-6G v.2 also shows maximum elevations in the
western part of the ice sheet, but has a smaller secondary maximum over the
James Bay area (Fig. ). A larger part of the Laurentide Ice
Sheet has elevations > 3000 m in the ANU reconstruction
(Fig. ). The GLAC-1a and ICE-6G v.2
reconstructions for Greenland are similar (because they are essentially
derived from the same model: see ) and
show a flatter ice sheet with increased elevations around the margin and
somewhat lower elevations than today in the centre (Fig. ).
The ANU reconstruction does not show lower central elevations, but
does have an increase in marginal elevations. All three reconstructions show
the Eurasian ice sheet with two major domes, one centred upon the Gulf of
Bothnia and the other over the Barents Sea. The ANU reconstruction has
elevations > 3000 m for the western dome, whereas both domes are
of similar and lower (2000–3000m) elevation in the
ICE-6G v.2 and GLAC-1a reconstructions
(Figs. , ).
Surface elevation (m) at the Last Glacial Maximum (LGM) Northern
Hemisphere ice sheets from the (a) ICE-6G v.2,
(b) GLAC-1a and (c) ANU reconstructions, and
for the (d) CMIP5/PMIP3 composite compared to the ice sheets used in
(e) PMIP1 and (f) PMIP2.
Difference in surface elevation (m) of the Northern Hemisphere ice
sheets at the LGM compared to the present day from the
(a) ICE-6Gv.2, (b) GLAC-1a and
(c) ANU reconstructions, and for the (d) CMIP5/PMIP3
composite compared to the ice sheets used in (e) PMIP1 and
(f) PMIP2. The region shown is between 40 and
90∘N.
Only ICE-6G v.2 and ANU provide independent reconstructions of
Antarctica. The volumetric change, when expressed in terms of eustatic sea
level, is nearly twice as large in the ANU reconstruction
(29 m) than in the ICE-6G v.2 reconstruction (15.6 m)
(Table ). More of the eastern part of the ice sheet lies at
elevations > 3000 m in the ANU reconstruction
(Fig. ), whereas the ICE-6G v.2 reconstruction has
a secondary dome at elevations > 3000 m over the Marie Byrd
region, which is not present in the ANU reconstructions. In both
reconstructions, the major differences in elevation between the LGM and
present are in western Antarctica, where elevation is higher by ca.
900 m at the LGM than today (Fig. ). The area of
increased elevation is larger in the ANU reconstruction than in the
ICE-6G v.2 reconstruction.
Surface elevation (m) of Antarctica at the LGM from the
(a) ICE-6G v.2, (b) ANU reconstructions, and
for (c) the CMIP5/PMIP3 composite compared to the ice sheets used in
(d) PMIP1 and (e) PMIP2. The GLAC-1a reconstruction
for Antarctica is identical to that of ICE-6G, and is therefore not
shown.
Difference in surface elevation (m) of Antarctica at the LGM
compared to the present day from the (a) ICE-6Gv.2,
(b) ANU reconstructions, and for (c) the CMIP5/PMIP3
composite compared to the ice sheets used in (d) PMIP1 and
(e) PMIP2. The GLAC-1a reconstruction for Antarctica is
identical to that of ICE-6G, and is therefore not shown.
Although all of the individual reconstructions are constructed using
information on the location of the margins of each ice sheet, nevertheless
the final reconstructed extent of the ice sheets is derived from the inverse
model. Thus, there may be discrepancies between the reconstructions and the
actual, observed location of the LGM margins of each ice sheet. There are
indeed differences between the ice and ice-shelf and land–sea masks obtained
from each of the individual reconstructions. The implied change in eustatic
sea level (Table ) is larger in the ANU reconstruction
than in the ICE-6G v.2 reconstruction. Similarly, the extent of ice
shelves is consistently smaller in the ICE-6G v.2 reconstruction than
in the ANU reconstruction, both for the NH and around Antarctica
(Fig. ).
Ice-shelf extent at the LGM from the ice-shelf masks for the
Northern Hemisphere derived
from ICE-6G v.2 for (a) the Northern Hemisphere and (b) Antarctica,
from GLAC-1a (c) for the Northern Hemisphere,
and from ANU for (d) the Northern Hemisphere and (e) Antarctica.
The GLAC-1a reconstruction for Antarctica is identical to that of
ICE-6Gv.2,
and is therefore not shown.
These reconstructed masks can be compared with the CMIP5/PMIP3 mask
for (f) the Northern Hemisphere and (g) Antarctica.
Cyan, blue and white areas indicate the grounded-ice, floating-ice and ice-free regions, respectively.
Comparison of the CMIP5/PMIP3 composite reconstruction with earlier PMIP ice sheets
Ice-sheet reconstructions used in the first two phases of PMIP were based on
earlier versions of the ICE-6G inversion approach: ICE-4G
for the first phase of PMIP (PMIP1) and ICE-5G
for the second phase of PMIP (PMIP2). ICE-5G was
improved relative to ICE-4G through the incorporation of revised
information about the extent of the Eurasian ice sheets at the LGM from the
QUEEN project
.
ICE-6G differs from ICE-5G because of the inclusion of
constraints based on satellite geodetic data as well as a more extensive data
set of relative sea-level changes. The differences between the three
reconstructions are substantial. The PMIP2 NH ice sheets are considerably
higher than the CMIP5/PMIP3 composite ice sheet, while the PMIP1 NH ice
sheets are lower than the CMIP5/PMIP3 composite and do not show the
pronounced dome in the western part of the Laurentide
(Figs. , ). The Eurasian ice sheet is less
extensive in the CMIP5/PMIP3 composite reconstruction than in the earlier
reconstructions and maximum elevations are lower than in the earlier PMIP
reconstructions. In contrast, the region of western Antarctica characterised
by large changes (< 900 m) is more extensive in the CMIP5/PMIP3
composite reconstruction than in the earlier reconstructions, though this is
partly due to the higher spatial resolution of the composite ice sheet
compared to the earlier reconstructions.
Changes in radiative forcing (Wm-2) associated with
changes in the ice
sheet and implied changes in land–sea geography, calculated for the
CMIP5/PMIP3 composite and the PMIP2 ice sheets respectively. The
resulting change in global annual mean surface air temperature
(∘C) is
shown in the last column. The error is calculated as the difference
between the estimates obtained while using the present-day climate as a
reference or the glacial climate as a reference in the
partial-radiative perturbation calculation. Note that the values given
for the PMIP2 ice sheet are slightly different from those given in
because of corrections made subsequent to the
publication of that paper. Values given here may also differ slightly
from published results of individual models where either a different
method or a different time window was used for the calculation.
The implied forcing resulting from the change in ice sheets and land–sea
geography given by the CMIP5/PMIP3 composite is estimated using the
approximate partial-radiative perturbation method. The
method is based on a simplified shortwave radiative model of the atmosphere.
Surface absorption, atmospheric scattering and absorption are represented by
means of three parameters that are diagnosed at each grid cell from surface
and top-of-the-atmosphere fluxes and albedo. These parameters are different
in each model and simulation, and reflect the properties of the radiative
code in the individual models and the differences of these terms in the
different time periods. To quantify the effect of the change of each of these
parameters, the parameters in the simple model are perturbed individually by
the amount that they change in the climate response in order to compute the
corresponding radiative change. We adopted a two-sided approach, in which two
estimates of the radiative change are made considering the control simulation
and the palaeo-simulation in turn as a reference. According to these
calculations, the forcing resulting from the change in the ice sheet alone is
between -1.85 and -3.49 Wm-2, depending on the climate model
(Table ), while the total change in forcing resulting from the
imposition of LGM boundary conditions varies between -3.62 and
-5.20 Wm-2. The difference in forcing in simulations using the
CMIP/PMIP composite (Fig. ) and the PMIP2 ice sheet is
ca. 1.0 Wm-2. Technically, the estimated difference in forcing
between the PMIP2 and CMIP5/PMIP3 simulations obtained through these analyses
reflects both differences in the ice-sheet reconstruction (other boundary
conditions are the same in the two sets of experiments) and differences in
the version of the model used for the PMIP2 and CMIP5/PMIP3 experiments. Only
three modelling groups (CCSM, IPSL, MIROC) have made LGM simulations in using
both the PMIP2 and CMIP5/PMIP3 ice sheets. They show an average change in
total forcing of 1.34 Wm-2, with the change in radiative forcing
caused by the ice sheet being ca. 1 Wm-2, i.e. of comparable
magnitude to the estimate obtained from the ensemble mean. The impact of
changes in individual model configuration would be unlikely to yield the
systematic increase in forcing between PMIP2 and CMIP5/PMIP3 shown by these
three models. Thus, it seems plausible that the estimate of the effect of
using the CMIP5/PMIP3 ice sheet obtained by comparing the PMIP2 and
CMIP5/PMIP3 ensemble of simulations is realistic.
Estimation of the difference in radiative forcing
(Wm-2)
at the LGM compared with pre-industrial conditions caused by imposition
of the CMIP5/PMIP3 ice sheet and the change in the land–sea mask. The
map is a composite of the results from five ocean–atmosphere models
showing the spatial patterns of the change in total forcing associated
with the expanded Northern Hemisphere ice sheets at the LGM and with
the increase in land area due to a lowered sea level.
Impact of differences between the ice-sheet reconstructions on climate
To evaluate the impact of elevation differences between the individual ice
sheets and the CMIP5/PMIP3 composite ice sheet on surface climate, we have
run simulations with the atmosphere–slab ocean version of the MIROC3 model
assuming no change in ocean heat transport from the control run and no change
in the ocean mask. Using different ice-sheet reconstructions has an impact on
surface temperature over the ice sheets themselves, and in adjacent regions
of the ocean (Arctic, North Atlantic and Southern oceans), and a smaller
impact over the Northern Hemisphere, partly through the influence on
atmospheric stationary waves (Fig. ). The largest
differences from the CMIP5/PMIP composite occur where the reconstructions
differ in terms of the ice extent (e.g. between North America and Greenland)
or elevation (e.g. western Antarctica, Scandinavian ice sheet). The
ANU reconstruction produces slightly colder temperatures in the Arctic
than either ICE-6G v.2 or GLAC-1a. The largest discrepancy
occurs over Antarctica, where regional differences in temperature can be
> 6 ∘C between the simulations using the ICE-6G v.2
and ANU reconstructions (Fig. ).
According to the MIROC simulations (Fig. ), the overall
impact of using the CMIP5/PMIP3 composite ice sheet in preference to any
individual reconstruction is smaller than the difference between the
CMIP5/PMIP3 composite and the ICE-5G ice sheet used in the PMIP2
simulations. Comparison of the multi-model ensemble from PMIP2 and
CMIP5/PMIP3 (Fig. ) shows that the decision to move to
a new generation of ice-sheet reconstructions has a large impact on simulated
LGM climate, not only in regions adjacent to the ice sheets, but also over
the ocean and in the tropics. Based on these ensemble results, the use of the
CMIP5/PMIP3 composite ice sheet together with the development of climate
models produces an additional reduction of ca. 0.5 ∘C in global mean
annual temperature compared to the PMIP2 experiments.
Discussion and conclusions
There is currently no consensus about the form of the LGM ice sheets.
Differences between existing reconstructions reflect the fact that new
information is still emerging about the details of ice-sheet margins at the
LGM and their retreat history, and the lithologic and geomorphic parameters
that are used as constraints for ice-sheet modelling. While it is useful to
explore the consequences of differences between reconstructions through
sensitivity experiments, the use of a unified data set facilitates
model–model intercomparison focusing on the role of structural differences
between models. This was the motivation for the construction of a composite
set of ice-sheet-related boundary conditions for the CMIP5/PMIP3 LGM
experiment. It is heartening that the differences between the individual
reconstructions contributing to the composite are relatively small and have
only a minor impact on simulated NH radiative forcing and temperature.
The differences between the CMIP5/PMIP3 composite ice sheet and the ice
sheets used in LGM simulations made during earlier phases of PMIP are not
negligible. estimated that the difference between the
prescribed land–sea mask from the PMIP2 and CMIP5/PMIP3 ice sheets would
result in an additional 0.6 Wm-2 forcing in the CMIP5/PMIP3
simulations, while the difference in ice-sheet height would result in
temperatures ca. 0.6 ∘C warmer than in the PMIP2 experiments. We
estimate that, in fact, the difference in forcing in simulations using the
CMIP/PMIP composite and the PMIP2 ice sheet is ca. 1.0 Wm-2, and
the average (ensemble) difference in the global mean annual temperature
anomaly is ca. 0.5 ∘C. These estimates are derived from the ensemble
of simulations made for each set of experiments, and thus we cannot exclude a
contribution from changes in model configuration to the apparent difference
in forcing and temperature response between the PMIP2 and CMIP5/PMIP3
results. However, the three models from the ensemble which performed both
sets of experiments all show an estimate of a difference in forcing due to an
ice-sheet configuration of ca. 1.0 Wm-2, which suggests that
this is a result of a systematic difference in the simulation protocol rather
than the non-systematic changes that might be expected to result from changes
in model configuration. While it would clearly be useful for a larger number
of modelling groups to test the impact of an ice-sheet configuration, it
seems plausible that the use of the CMIP5/PMIP3 ice sheet results in an
increase in radiative forcing of ca. 1.0 Wm-2 compared to the
previous generation of PMIP simulations. The climate difference is
non-negligible over the North Atlantic and over the continents of the
Northern Hemisphere due to both radiative forcing and the atmospheric
circulation change in multi-models, as well as the MIROC model sensitivity
test.
Differences in mean annual temperature (∘C) caused by
using different ice-sheet configurations from the CMIP5/PMIP3 composite ice
sheet in simulations made with the MIROC slab ocean model. The individual
ice-sheet configurations are the (a) PMIP2,
(b) ICE-6G v.2, (c) GLAC-1a, and
(d) ANU ice sheets, where each is referenced to the
CMIP5/PMIP3 composite
ice sheet. The land mask (> 50 % land) is shown in grey; the ice margin
(> 50 % ice) is shown in black in all four plots.
Sensitivity experiments using the MIROC model show that the decision to use
a composite ice sheet, rather than any of the existing ice-sheet
realisations, does have an impact on simulated climate. The differences,
however, are largely confined to the ice sheets themselves and adjacent
oceans, and basically reflect disagreements between the independent
reconstructions about ice extent and/or elevation. The choice makes little
difference to simulated temperatures beyond the ice-sheet margins.
Nevertheless, over the ice sheets, the differences in surface temperature can
be large (> 5 ∘C), and this could have a non-negligible impact on
other aspects of the surface climate (see e.g. ) and
ocean circulation. Testing the response of a fully coupled atmosphere–ocean
model to these three reconstructions is beyond the scope of the present
paper, but we would anticipate larger changes than in the atmosphere–slab
ocean experiments, notably through the impact of the different
reconstructions on westerly winds over the North Atlantic, which can, in
turn, have an impact on the Atlantic Meridional Overturning Circulation
. Thus, it is important that the differences
between the reconstructions are examined carefully so that better-constrained
reconstructions are available for future PMIP analyses. However, simulations
made with the composite CMIP5/PMIP3 ice sheet have more realistic
temperatures over Antarctica, falling within or very close to the uncertainty
range of estimates of the LGM cooling derived from ice core data than the
majority of PMIP2 simulations . While this may
reflect model improvements to some extent, it would be unlikely to occur if
the ice-sheet configuration of CMIP5/PMIP3 were substantially wrong.
Change in mean annual temperature (∘C) in
the (a) PMIP2 and
(b) CMIP5/PMIP3 coupled ocean–atmosphere simulations.
Each of these
plots is an ensemble average of all the LGM simulations in PMIP2 and
CMIP5/PMIP3 respectively. The difference between the ensemble mean
results for the two generations of experiments is shown in plot (c).
The land mask (> 50 % land) is shown in grey, and the ice margin
(> 50 % ice) is shown in black in all plots. Contour lines in
(a) and (b) are at 1 ∘C intervals to
-9 ∘C;
temperature differences
>-9 ∘C are not differentiated.
Implementation of the CMIP5/PMIP3 composite ice sheet in individual
models. The plots show the surface elevation (m) as implemented in each
model, and thus reveal that there are small differences in the prescribed
ice sheet between models because of differences in e.g. model type and
resolution.
There are differences between the actual, observed margin of each ice sheet
at the LGM and the margins reconstructed by inverse modelling. Furthermore,
the way in which ice-sheet topography and extent are implemented varies
between different climate models. Thus, there may be differences between the
CMIP5/PMIP3 ice-sheet mask and the mask used by an individual model (see e.g.
, Fig. ). Both of these issues
could be important in the processing of model outputs for model–model or
data–model comparison. This is clearly an issue that needs to be addressed
more fully in the design of palaeo-simulations for the next phase of CMIP
(CMIP6). Changes in palaeo-bathymetry, which is one output that can be
obtained from the ice-sheet models (e.g. ICE-6G v.2), have rarely
been implemented in a coupled ocean–atmosphere model context. The
implications of palaeo-bathymetry changes for ocean circulation could be
important, and again this is an issue that could be addressed in the future
design of palaeo-experiments.
Our knowledge of the LGM ice-sheet/ice-shelf reconstruction is continually
improving, as are the models that are used to reconstruct the most likely
distribution of ice mass
.
Indeed, there have been updated reconstructions of the LGM ice-sheet
configuration since the CMIP5/PMIP3 ice sheet was constructed. For example,
the ICE-6G_C (VM5a) reconstruction is an updated version of the
ICE-6G (VM5a) v2.0 model discussed here, and is informed by a much
richer database of space geodetic information
. It is inevitable that there will be further
changes in the future, although less clear when there will be a consensus
about their form.
It is imperative, then, that a wider range of models conduct sensitivity
tests of the impact of ice-sheet configurations, focusing on both
near-field and remote impacts on climate.
This would make it possible to draw on the wealth of
palaeoclimate data from beyond the ice sheets to evaluate, and perhaps
even constrain, ice-sheet reconstructions.
The Supplement related to this article is available online at doi:10.5194/gmd-8-3621-2015-supplement.
Acknowledgements
We thank Rosemarie Drummond and Rumi Ohgaito for technical assistance. We
thank Catherine Ritz, Peter Clark, Anders Carlson, Jun'ichi Okuno,
Heinz Blatter, all of those who contributed to the PMIP Wiki, and the
participants in the PMIP and PALSEA workshops for scientific discussion. We
acknowledge the World Climate Research Programme's Working Group on Coupled
Modelling, which is responsible for CMIP, and we thank the climate modelling
groups (listed in Table 3 of this paper) for producing and making available
their model output. For CMIP the US Department of Energy's Program for
Climate Model Diagnosis and Intercomparison provides coordinating support and
led development of software infrastructure in partnership with the Global
Organization for Earth System Science Portals. The numerical experiments by
the MIROC model were carried out on the JAMSTEC Earth Simulator. The research
was supported by JSPS KAKENHI grant 25241005. This paper is a contribution to
the ongoing work on the Palaeoclimate Modelling Intercomparison
Project. Edited by: D. Roche
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