The Cryosphere, 9, 821–835, 2015
www.the-cryosphere.net/9/821/2015/
doi:10.5194/tc-9-821-2015
© Author(s) 2015. CC Attribution 3.0 License.
How do icebergs affect the Greenland ice sheet under pre-industrial
conditions? – a model study with a fully coupled ice-sheet–climate
model
M. Bügelmayer1, D. M. Roche1,2, and H. Renssen2
1Vrije Universiteit Amsterdam, Amsterdam, the Netherlands
2Laboratoire des Sciences du Climat et de l’Environnement (LSCE), CEA/CNRS-INSU/UVSQ,
Gif-sur-Yvette CEDEX, France
Correspondence to: M. Bügelmayer (m.bugelmayer@vu.nl)
Received: 19 November 2013 – Published in The Cryosphere Discuss.: 7 January 2014
Revised: 13 January 2015 – Accepted: 9 April 2015 – Published: 4 May 2015
Abstract. Icebergs have a potential impact on climate since
they release freshwater over a widespread area and cool the
ocean due to the take-up of latent heat. Yet, so far, icebergs
have never been modelled using an ice-sheet model
coupled to a global climate model. Thus, in climate models
their impact on climate has been restricted to the ocean.
In this study, we investigate the effect of icebergs on the
climate of the mid- to high latitudes and the Greenland
ice sheet itself within a fully coupled ice-sheet (GRenoble
model for Ice Shelves and Land Ice, or GRISLI)–earthsystem
(iLOVECLIM) model set-up under pre-industrial climate
conditions. This set-up enables us to dynamically compute
the calving sites as well as the ice discharge and to
close the water cycle between the climate and the cryosphere
model components. Further, we analyse the different impact
of moving icebergs compared to releasing the ice discharge at
the calving sites directly. We performed a suite of sensitivity
experiments to investigate the individual role of the different
factors that influence the impact of the ice release on the
ocean: release of ice discharge as icebergs versus as freshwater
fluxes, and freshening and latent heat effects. We find that
icebergs enhance the sea-ice thickness around Greenland,
thereby cooling the atmosphere and increasing the Greenland
ice sheet’s height. Melting the ice discharge directly at the
calving sites, thereby cooling and freshening the ocean locally,
results in a similar ice-sheet configuration and climate
as the simulation where icebergs are explicitly modelled. Yet,
the simulation where the ice discharge is released into the
ocean at the calving sites while taking up the latent heat homogeneously
underestimates the cooling effect close to the
ice-sheet margin and overestimates it further away, thereby
causing a reduced ice-sheet thickness in southern Greenland.
We conclude that in our fully coupled atmosphere–ocean–
cryosphere model set-up the spatial distribution of the takeup
of latent heat related to iceberg melting has a bigger impact
on the climate than the input of the iceberg’s meltwater.
Moreover, we find that icebergs affect the ice sheet’s geometry
even under pre-industrial equilibrium conditions due to
their enhancing effect on sea ice, which causes a colder prevailing
climate.
1 Introduction
During the last decade satellite observations have shown
a reduction of the Greenland ice sheet’s height, by up to
1.5 m yr−1 over the past 3 years (Helm et al., 2014). This
reflects an accelerated mass loss of the Greenland ice sheet
(GrIS), which has been associated with a continuous rise
in the annual surface temperature observed over Greenland
since 1994. Compared to the average over 1951–1980, temperatures
increased by about 1.5 ◦C (Hanna et al., 2011; Box,
2013). Even though this mass loss was partly counteracted
by higher accumulation rates, the net GrIS mass balance (accumulation
minus ablation) decreased during the past two
decades by about 20 Gt yr−1, caused by increased ice discharge
(Rignot and Kanagaratnam, 2006; Van den Broeke et
al., 2009). Although we have clear evidence of major changes
of the GrIS in the past and present, our understanding of the
Published by Copernicus Publications on behalf of the European Geosciences Union.
822 M. Bügelmayer et al.: How do icebergs affect the Greenland ice sheet
potential impact of the GrIS mass loss due to interactions
with the ocean and the atmosphere is still limited and has
never been investigated in a fully coupled global climate–icesheet–iceberg
modelling framework. In this paper, we therefore
analyse these interactions using an earth system model
including fully dynamic components for land ice, ice shelves
and icebergs. We focus on the question of how icebergs affect
the GrIS and the regional climate under pre-industrial
conditions.
There are numerous feedback mechanisms related to the
growing and shrinking of ice sheets (Clark, 1999). First,
changes in topography can lead to altered atmospheric circulation
patterns (Ridley, 2005). Second, when an ice sheet
is shrinking, there are fewer ice-covered areas and the resulting
decrease in surface albedo enhances the uptake of heat by
newly exposed land surfaces. Vizcaíno et al. (2008) showed
that under future warming the decrease in both topography
and albedo of the GrIS strongly enhances its decay. A further
effect of the ice sheet’s shrinking is enhanced runoff into the
ocean and, as a consequence, a reduced sea surface salinity
that increases the stability of the water column. This process,
depending on the position and strength of the freshwater flux,
might lead to a reduction or even collapse of the Atlantic
Meridional Overturning Circulation (AMOC; e.g. Roche et
al., 2010; Swingedouw et al., 2009). Besides runoff, iceberg
calving is one of the main mechanisms of mass loss of ice
sheets, and in a warming climate it is expected to increase.
Recently, an increase in ice speed of the Greenland glaciers
of up to 200 % and Arctic ice shelf break-ups led to enhanced
ice discharge (e.g. Mueller et al., 2003; Rignot and
Kanagaratnam, 2006; Nick et al., 2009). Since icebergs act
as a mobile freshwater source and a sink of latent heat, they
freshen and cool the ocean, thereby facilitating the stratification
of the ocean as well as the formation of sea ice (Jongma
et al., 2009).
Numerical ice-sheet models are valuable tools with which
to study the evolution of the ice sheet during different climate
states and its impact on climate. Therefore, they are
used to better understand and investigate the aforementioned
interactions between the GrIS and the other climate components.
Most ice-sheet models currently used for performing
longer time simulations are three-dimensional thermomechanical
models, based on the shallow-ice approximation
(Hutter, 1983; Morland, 1984). The ice sheet’s thickness and
extension are calculated at every time step. Some models also
differentiate between fast- and slow-flowing ice, such as ice
shelves and grounded ice, respectively, to allow for a dynamic
computation of the grounding line (e.g. Huybrechts,
1990; Huybrechts and de Wolde, 1999; Greve, 1995, 1997;
Ritz et al., 2001; Pollard and DeConto, 2007). These models
are used, on the one hand, to predict the future development
of the ice sheets and, on the other hand, to model their evolution
during the past millennia and even millions of years.
The simplest approach to investigate the ice sheet’s development
over the past is by evaluating the impact of the
forcing fields on it. This can be done either by using reconstructed
air temperature and precipitation fields as input data
(e.g. Ritz et al., 2001) or by using climate model output of
specific time periods to drive the evolution of the ice sheet
(e.g. Huybrechts et al., 2004; Charbit et al., 2007), or a combination
of both (e.g. Gates, 1976; Pollard and Thompson,
1997; Broccoli, 2000). Using this set-up, the interactions are
only one-sided as the climate is applied to the ice sheet but
not altered by it.
A further and more complex approach is to couple icesheet
models to earth system models of intermediate complexity
(EMICs; Claussen et al., 2002) or to general circulation
models (GCMs). In this case, the climate model (EMIC
or GCM) and the ice-sheet model exchange input (temperature
and precipitation) and output (albedo, topography, melting
and calving of the ice sheet) fields (e.g. Wang and Mysak,
2002; Kageyama et al., 2004; Gregory et al., 2012). Therefore,
the interactions are two-sided as the ice sheet’s geometry
and its freshwater fluxes are used as input for the climate
model, where the runoff (surface and basal melt) as well as
the ice discharge are considered as freshwater fluxes that are
released into the ocean directly at the coastline (e.g. Bonelli
et al., 2009; Vizcaíno et al., 2008; Goelzer et al., 2010) or
over a pre-defined area (Ridley, 2005). Therefore, the meltwater
released due to iceberg calving and the related takeup
of latent heat by them is considered in the same way as
the runoff and consequently spatially restricted to the coastline
or homogenously distributed over a fixed region. A more
complete description of coupled ice-sheet–climate modelling
can be found in Pollard (2010).
The importance of icebergs has been shown in different
studies where an iceberg module was coupled to climate
models and forced with climatological data (e.g. Bigg et
al., 1996, 1997; Gladstone et al., 2001; Death et al., 2006;
Levine and Bigg, 2008; Green et al., 2011; Jongma et al.,
2009, 2013). Jongma et al. (2009) highlighted the effect of
icebergs under pre-industrial conditions using an EMIC that
included an interactively coupled iceberg module based on
Bigg et al. (1996). Focusing on the Southern Ocean, Jongma
et al. (2009) revealed that icebergs significantly facilitate the
formation of sea ice. Moreover, Levine and Bigg (2008),
Green et al. (2011) and Jongma et al. (2013) highlighted
the importance of including icebergs in model simulations of
past ice shelf break-ups since the ocean, and consequently the
AMOC, respond differently to them than to directly applied
freshwater fluxes. A shortcoming of the studies done so far
is that the locations and the amount of water used to generate
icebergs have been prescribed according to observations and
reconstructions. Recently, Martin and Adcroft (2010) coupled
an iceberg module to a GCM. The climate model was
used to generate icebergs at the coastal sites defined by the
river routing system. This approach allows the background
climate to define the number of icebergs generated under the
assumption of an equilibrated ice sheet. Yet, none of these
studies focusing on icebergs incorporated an ice-sheet model.
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M. Bügelmayer et al.: How do icebergs affect the Greenland ice sheet 823
Consequently, the interactions between the ice sheet and the
icebergs were not taken into account.
Our aim is to include all the previously mentioned feedbacks
(albedo, topography, runoff and icebergs) in a fully
coupled climate system. Therefore, we use the iLOVECLIM
climate model of intermediate complexity (Roche et al.,
2014), with a dynamic-thermodynamic iceberg module
(Jongma et al., 2009, 2013; Wiersma and Jongma, 2010) and
an ice-sheet/ice-shelves module (Ritz et al., 1997, 2001) included
and actively coupled. The cryosphere part is coupled
to the climate part on a yearly basis, and the changes in icesheet
geometry depend on the climate background that is defined
by the atmosphere–ocean–vegetation component that
itself is modified by alterations of the ice-sheet topography,
albedo and freshwater fluxes.
To achieve a fully coupled climate system, we further developed
the model compared to previous studies (Jongma et
al., 2009, 2013; Roche et al., 2014) by including the following
two extensions. First, instead of prescribing the locations
and the amount of icebergs being calved, they are now generated
according to the ice lost by the dynamical ice-sheet
model at the corresponding positions. Second, the water cycle
is now closed between all the climate components. Therefore,
the precipitation coming from the atmospheric model is
used to build the ice sheet, its runoff is given to the river
routing system and finally put into the ocean, and the calved
mass is used to create icebergs that then release meltwater
to the ocean. This fully coupled model set-up allows us to
analyse the following questions. (1) How well are we able
to reproduce the dynamics and main features of Greenland
iceberg calving and ice-sheet development in a coupled climate
model under pre-industrial conditions? (2) What is the
influence of icebergs on the mid- to high-latitudinal climate
and the modelled Greenland ice sheet itself? (3) How well
can the effect of icebergs on climate be reproduced by freshwater
fluxes that are applied at the same calving sites and
with the same seasonal cycle, but lack the dynamic characteristics
of icebergs? The difference between direct freshwater
fluxes and icebergs has already been investigated by
Jongma et al. (2009, 2013), but in their work the freshwater
fluxes used to parameterise icebergs were distributed
homogeneously around the Antarctic ice sheet (Jongma et
al., 2009) or at a certain latitude belt in the North Atlantic
(Jongma et al., 2013). In the present study, however, we introduce
the freshwater fluxes into the ocean at the actual calving
sites, a set-up that is closer to what has been done in other
coupled climate models (e.g. Vizcaíno et al., 2008; Bonelli et
al., 2009; Goelzer et al., 2010).
The questions stated here are addressed by performing
and comparing four different model experiments that were
all done under pre-industrial conditions and were performed
until the ice sheet was equilibrated. The experiments differ
in the way in which the freshwater fluxes (runoff and calving)
of the ice sheet and the related uptake of latent heat are
included in the climate model.
The paper is structured as follows: first the global climate
model iLOVECLIM, as well as the included iceberg and icesheet
module, is described. Second, the different set-ups of
the runs are explained. Third, we present the results of our
simulations and finally proceed to discussions and conclu-
sions.
2 Methods
The earth system model of intermediate complexity used in
this study is the so-called iLOVECLIM model (version 1.0),
which is a code fork of the LOVECLIM climate model version
1.2 (Goosse et al., 2010). The physical climate components
(atmosphere (ECBilt), ocean (CLIO) and vegetation
(VECODE)) are the same, yet iLOVECLIM differs in the
iceberg and the ice-sheet (GRISLI) module included.
2.1 Atmosphere–ocean–vegetation model
The atmospheric model ECBilt (Opsteegh et al., 1998) is a
quasi-geostrophic, spectral model calculated on a horizontal
T21 truncation (5.6◦ in latitude/longitude) and three vertical
pressure levels (800, 500, 200 hPa) with a time step of
4 h. The precipitation is computed in the lowermost layer
according to the available humidity. The sea-ice and ocean
component CLIO consists of a dynamic-thermodynamic seaice
model (Fichefet and Morales Maqueda, 1997, 1999) coupled
to a 3-D ocean general circulation model (Deleersnijder
and Campin, 1995; Deleersnijder et al., 1997; Campin
and Goosse, 1999). The formulation of the surface albedo
of the sea ice takes into account its state (frozen or melting)
and the thickness of the snow and ice covers (Goosse
et al., 2010). The ocean model has a free surface, allowing
the use of real freshwater fluxes and a realistic bathymetry. It
has a horizontal resolution of approximately 3◦ × 3◦ in longitude
and latitude and 20 unevenly spaced vertical levels. In
the default model set-up, the iceberg module is not coupled.
Therefore, the presence of icebergs is parameterised as homogeneous
uptake of latent heat around Greenland (Fig. 1a)
according to the amount of excess snow calculated in ECBilt.
CLIO has a daily time step. The vegetation model used
is VECODE (Brovkin et al., 1997), which accounts for two
plant functional types (trees and grass) and bare soil. It has
the same resolution as the atmospheric model but allows fractional
use of one grid cell to consider small spatial changes
in vegetation. It depends on the temperature and precipitation
provided by ECBilt and accounts for long-term (decadal
to centennial) changes of the climate.
2.2 GRISLI ice-sheet model
The GRenoble model for Ice Shelves and Land Ice (GRISLI)
is a three-dimensional thermomechanical model which was
first developed for the Antarctic (Ritz et al., 1997, 2001) and
then further expanded for the Northern Hemisphere (Peyaud
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824 M. Bügelmayer et al.: How do icebergs affect the Greenland ice sheet
Figure 1. (a) Mask used in CLIO where the latent heat needed to
melt the excess snow is homogeneously taken up to parameterise
icebergs; (b) take-up of latent heat from the ocean surface due to
iceberg melting in CALV; (c) take-up of latent heat from the ocean
surface due to local release of ice discharge (FWFc) (non-linear
colour scheme); (d) 1000-year averaged iceberg meltwater fluxes
(m3 s−1) of the CALV experiment; (e) 1000-year averaged meltwater
flux due to calving put into the ocean directly at the ice-sheet
margin (same for both FWF experiments); (f) difference between
iceberg melt flux and direct freshwater flux (CALV–FWF) (nonlinear
colour scheme).
et al., 2007). In the present study only the Northern Hemisphere
grid is used with a horizontal resolution of 40 × 40 km
on a Lambert azimuthal grid. It predicts the evolution of the
geometry (thickness and extension) of the ice-sheet according
to the surface mass balance, ice flow and basal melting.
GRISLI takes into account three different types of ice flow,
namely inland ice, ice streams and ice shelves. The ice flow
of the grounded parts of the ice sheet is based on the 0-order
shallow-ice approximation (Hutter, 1983; Morland, 1984).
The fast-flowing ice, corresponding to ice streams, is calculated
using the shallow-shelf approximation (MacAyeal,
1989), as are the ice shelves. The impact of the ice load on
the bedrock is determined by the flow of the asthenosphere
with a characteristic time constant of 3000 yr, as well as by
the rigidity of the lithosphere. Calving occurs whenever the
ice thickness at the border of the ice sheet reaching the ocean
is below 150 m and the ice provided by the upstream grid
points is not enough to maintain the height above this threshold.
In the iceberg module this mass is used to generate icebergs
of different size classes at the calving site, as described
in detail in Sect. 2.3. In this simplified calving scheme the
width of the calving front is indirectly taken into account by
the amount of calved mass, which depends on the number of
grid cells that meet the calving criteria, as stated above. The
minimum width corresponds to the grid resolution of 40 km.
The ice sheet’s runoff (basal and surface melt) is computed
at the end of the coupling time step, in our case 1 year, by
calculating the difference in ice-sheet thickness between the
beginning and the end of the year and taking into account
the mass that is lost due to calving. This method has been
chosen because of the initial design of GRISLI that does not
explicitly include the output of liquid runoff.
As explained in detail in Sect. 2.4 and in Roche et
al. (2014), the yearly runoff is added to the atmospheric
model ECBilt and recomputed to fit its time step of 4 h.
2.3 The iceberg module
We use the optional dynamic-thermodynamic iceberg module
(Jongma et al., 2009, 2013; Wiersma and Jongma, 2010)
with the same parameter set as in Jongma et al. (2009).
It is based on the iceberg-drift model published by Smith
and coworkers (Smith and Banke, 1983; Smith, 1993; Loset,
1993) and was further developed by Bigg et al. (1996, 1997)
and Gladstone et al. (2001). It was implemented in CLIO
by Jongma et al. (2009) and Wiersma and Jongma (2010).
The icebergs are calculated on the CLIO grid and moved according
to the Coriolis force; the air, water and sea-ice drag;
the horizontal pressure gradient force; and the wave radiation
force. These forces depend on the wind and the ocean
currents calculated in ECBilt and CLIO, which are then interpolated
linearly from the surrounding grid corners to fit the
icebergs location. Melting of the bergs occurs due to basal
melt, lateral melt and wave erosion. As the icebergs melt,
their length-to-height ratio changes and they are allowed to
roll over. Yet, break-up of icebergs is not considered. The
meltwater fluxes are added to the ocean’s surface layer of the
current grid cell, and the latent heat fluxes needed to melt
the icebergs are taken from the ocean layer according to the
depth of the iceberg.
In contrast to Jongma et al. (2009, 2013), who prescribed
the release position and amount of icebergs, we have coupled
the iceberg module to GRISLI. Thus, we generate icebergs
according to the mass loss that is calculated by GRISLI
over 1 year and then given to the iceberg module. Therefore,
we divide the yearly amount of mass at the calving sites into
monthly values considering the seasonality of calving. We
follow the results of Martin and Adcroft (2010), with the
maximum occurring in spring and the minimum in late summer
(Fig. 2a). The monthly mass is then transformed into a
daily available mass as follows in Eqs. (1) and (2):
MAM(i,j) = TYM(i,j) · percentage_month, (1)
DAM(i,j) = MAM(i,j)/30, (2)
with MAM defining the monthly available mass at the grid
point i,j; TYM the total yearly mass at the grid point i,j;
percentage_month the percentage that is used of the TYM
per month; and DAM being the daily available mass at the
grid point i,j. The grid point i,j is always referring to the
CLIO grid.
Furthermore, 10 size classes of bergs have been computed
as defined by Bigg et al. (1997) and used and stated by e.g.
Gladstone et al. (2001), Death et al. (2006) and Jongma et
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M. Bügelmayer et al.: How do icebergs affect the Greenland ice sheet 825
Figure 2. (a) Seasonal calving distribution in percent of yearly mass per month as calculated by Martin and Adcroft (2010); (b) sites and
tracks as stated in the AMAP Assessment Report (2007), reproduced with permission.
al. (2013). These size classes are based on present-day observations
in the Arctic done by Dowdeswell et al. (1992).
Each class corresponds to a defined percentage of the daily
available amount. Thus, every day we produce icebergs of
the 10 different size classes as
NBS(i,j,k) = DAM(i,j) · percentage_sizeclass(k)/
mass_sizeclass(k), (3)
with NBS being the number of bergs of size class k at the grid
cell i,j; DAM the daily available mass at the grid cell i,j;
the percentage_sizeclass(k) corresponding to the percentage
of DAM used for bergs of size class k; and mass_sizeclass(k)
corresponding to its mass. Following Eq. (3), we get a number
of bergs per different size class at each calving site.
Yet, as icebergs of the different classes can only be generated
if there is enough ice available, their size distribution
and amount strongly depend on the ice mass as computed
by GRISLI at the different locations. Using this method, the
size of the calving front affects the calving mass and thus
indirectly the amount of icebergs calved. But local characteristics,
such as small glaciers producing more small bergs,
are not considered since the percentage of the different size
classes is the same for all calving sites. The part of the daily
available mass that has not been used is saved and added to
the available amount of the following day.
2.4 The coupling method and experimental set-up
We have performed four different experiments (Table 1) that
vary in the implementation of the freshwater fluxes (runoff
Table 1. Summary of treatment of freshwater fluxes coming from
the ice sheet and of latent heat fluxes related to iceberg melting.
Runoff: basal and surface melting of the ice sheet; iceberg FWF:
melt flux related to iceberg calving; direct FWF: input of calving
mass as freshwater flux into the first ocean cell next to the ice-sheet
margin instead of forming icebergs; local LHF: take-up of latent
heat at the position where the freshwater related to iceberg melting
is put into the ocean; homogeneous LHF: parameterisation of
freshwater fluxes related to iceberg calving as take-up of latent heat
homogenously around Greenland.
Iceberg Direct Local Homogeneous
Runoff FWF FWF LHF LHF
CTRL (1) – – – – X
CALV (2) X X – X –
FWFf (3) X – X – X
FWFc (4) X – X X –
and calving) calculated in GRISLI and the uptake of latent
heat needed to melt the calving flux. All experiments have
in common that GRISLI is coupled to iLOVECLIM applying
a yearly time step (Roche et al., 2014). After 1 year the
monthly surface temperatures and the total amount of snowfall
are downscaled from the ECBilt to the GRISLI grid.
Further, the temperature fields are vertically downscaled to
overcome the large height differences between the modelled
ECBilt and GRISLI surfaces. Therefore, the temperature at
the highest and the lowest GRISLI point, within one ECBilt
grid cell, is taken to compute a vertical lapse rate that is then
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826 M. Bügelmayer et al.: How do icebergs affect the Greenland ice sheet
used to compute the altitude-dependent temperature at the
GRISLI surface (Roche et al., 2014). The accumulation and
temperature fields are needed as input fields to calculate the
surface mass balance (SMB) that is defined by the accumulation
minus ablation. To obtain the ablation rates, the positive
degree-day (PDD) method of Fausto et al. (2009) is used,
which takes into account the dependence of the ice and snow
melt rate parameters on temperature as well as the dependence
of the refreezing parameter on the altitude. After one
model year, GRISLI provides the updated topography and
ice mask to ECBilt to calculate the surface albedo. A more
detailed description of the coupling between ECBilt, CLIO
and GRISLI is given in Roche et al. (2014).
In the control (CTRL) experiment, the freshwater cycle
is closed between the atmospheric model ECBilt and the
oceanic model component CLIO. In ECBilt, the precipitation
(solid and liquid) is computed every 4 h and the solid precipitation
is added to the snow layer. To prevent the model from
piling up too much snow in areas with a positive snow mass
balance, the height of the snow layer is not allowed to exceed
a pre-defined threshold (10 m). If the snow layer exceeds this
threshold, the amount of snow above it (the so-called excess
snow) is melted, and it is added to the soil moisture (in a
bucket model) and routed into the ocean when the maximum,
pre-set soil water holding capacity is exceeded. In the CTRL
experiment where icebergs are not explicitly modelled, their
cooling effect is parameterised using the excess snow. Therefore,
the heat needed to melt the excess snow is taken up homogenously
around Greenland from the ocean surface layer
in the ocean model CLIO (Fig. 1a). The solid precipitation
that is falling on the ice sheet is given to GRISLI, where it
is used to calculate the surface mass balance. However, it is
not removed from ECBilt because in CTRL the water cycle
between ECBilt-CLIO and GRISLI is uncoupled, implying
that GRISLI is not incorporated into the freshwater cycle of
ECBilt–CLIO.
In the calving (CALV), the “fresh” freshwater (FWFf) and
the “cold” freshwater (FWFc) experiments, the freshwater
cycle is closed between ECBilt, CLIO and GRISLI. Therefore,
the precipitation given from ECBilt to GRISLI is removed
from ECBilt. GRISLI uses the precipitation to calculate
the surface mass balance. At the end of one model year
it provides ECBilt with the amount of the computed runoff
(surface and basal melt) and CLIO with the ice discharge. In
ECBilt the runoff is incorporated into the land routing system
and distributed to the ocean. The ice discharge in CLIO is either
used to generate icebergs (CALV experiment) or melted
instantaneously at the ice-sheet border (FWFf and FWFc experiments).
The ice discharge has to be melted before being
supplied to the ocean as a freshwater flux, and the treatment
of the heat needed to do this differs between the CALV,
FWFc and FWFf experiments. In CALV and FWFc, this heat
is taken up from the ocean cell corresponding to the position
where the ice discharge is added to the ocean either in
the form of an iceberg melt flux (CALV) or in the form of a
Figure 3. Schematic representation of the water cycle between the
atmospheric component ECBilt, the ice-sheet module GRISLI, the
iceberg module and the oceanic component CLIO; numbers correspond
to experiments (1: CTRL; 2: CALV; 3: FWFf; 4: FWFc).
freshwater flux at the ice-sheet margin (FWFc). In FWFf the
ice discharge is melted at the ice-sheet border without taking
up heat; instead the latent heat related to the excess snow is
taken up homogenously around Greenland, identical to the
CTRL experiment. This allows us to separate the freshening
and the cooling effect of icebergs.
A schematic representation of the water cycle between the
atmosphere (ECBilt), ocean (CLIO), ice sheet (GRISLI) and
iceberg model is displayed in Fig. 3. Volume changes of the
ice sheet are reflected in the resulting calving flux and runoff.
The latter is given to the land routing system of ECBilt and
transported into the ocean. Runoff is included in all the experiments
except the CTRL run.
When we compare these four experiments (Table 2), we
can analyse the impact of the icebergs on the climate of the
mid- to high latitudes caused by the distribution of their meltwater
and the related cooling and freshening of the ocean
(CALV–CTRL). Moreover, we can separately analyse the impact
of freshening (FWFf–CTRL) and of cooling the ocean
(FWFc–FWFf) as the freshwater experiments only differ in
the treatment of latent heat. Further, the differences between
simulated icebergs and directly applied freshwater fluxes
(CALV–FWF), which ignore the spatial distribution of the
meltwater, are investigated.
All runs were done under pre-industrial conditions (orbital
parameters and greenhouse gas concentrations corresponding
to the year 1850), and the ice sheet was initialised from
present-day observations (Bamber et al., 2001). The experiments
were continued until the ice sheet was equilibrated,
which took about 11 000 model years. In total the experiments
were performed for 12 000 model years, and the results
of the last 1000 model years are presented in the following
section. The climate is equilibrated, with no detectable drift
in the deep-ocean temperature.
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M. Bügelmayer et al.: How do icebergs affect the Greenland ice sheet 827
Table 2. Summary of anomalies analysed.
Anomaly Interpretation
CALV–CTRL Effect of non-parameterised take-up of latent
heat as well as slow and spatially spread melting
due to moving icebergs (i.e. cooling, freshening
and distribution effect)
FWFf–CTRL Effect of freshwater (i.e. freshening)
FWFc–CTRL Effect of freshwater and non-parameterised
take-up of latent heat (i.e. freshening and cooling
effect)
FWFc–FWFf Effect of non-parameterised take-up of latent
heat (i.e. cooling effect)
CALV–FWFc Effect of slower and spatially spread melting
due to moving icebergs (i.e. distribution ef-
fect)
CALV–FWFf Effect of non-parameterised take-up of latent
heat as well as slower and spatially spread
melting due to moving icebergs (i.e. cooling
and distribution effect)
Figure 4. First row: ice-sheet thickness (m): (a) observed (Bamber
et al., 2001), (b) CTRL run and (c) difference CTRL–observed;
second row displays the differences (d) CALV–CTRL, (e) CALV–
FWFf and (f) FWFf–CTRL (non-linear colour scheme).
3 Results
Before analysing our results, we briefly summarise the main
properties of the CTRL ice sheet. In CTRL, the resulting
modelled ice-sheet volume (3.8 × 1015 m3) is overestimated
with an excess volume of about 0.95 × 1015 m3 compared to
observations (2.85 × 1015 m3; Bamber et al., 2001). Comparing
the CTRL volume to the computed volume using presentday
observations as input fields to force GRISLI displays that
dynamically coupling GRISLI to ECBilt results in an excess
ice-sheet volume of 4.4 × 1014 m3 (Roche et al., 2014). The
ice sheet (Fig. 4b) extends almost everywhere down to the
Greenland coast, even in regions that are currently ice-free
Figure 5. 1000-year averages. First row: mass balance (m):
(a) CTRL, (b) CALV and (c) FWFf; 2nd row: accumulation (m):
(d) CTRL, (e) CALV and (f) FWFf (non-linear colour scheme).
according to observations (Fig. 4a). Further, the CTRL ice
sheet is too thin (by up to 500 m) in northwest Greenland
but too thick in central and northeast Greenland (by up to
1000 m) and over Devon Island. This can be explained by the
overestimation of the positive SMB by GRISLI compared to
the SMB modelled by a regional climate model MAR (not
shown; Fettweis et al., 2013). The computed SMB (Fig. 5a)
captures the overall pattern of positive SMB in the south and
less in the north of Greenland, and negative SMB along the
coast. Yet, GRISLI overestimates the positive SMB resulting
in the excessive extension and ice-sheet thickness. The computed
SMB (Fig. 5a) captures the overall pattern of positive
SMB in the south and less in the north of Greenland, and
negative SMB along the coast. Yet, GRISLI overestimates
the positive SMB resulting in the excessive extension and
ice-sheet thickness. This is also seen in the computed surface
mass balance of the CTRL ice sheet (648 Gt yr−1, Table
3), which is about one-third higher than computed with a
regional climate model (469 Gt yr−1; Ettema et al., 2009) in
accordance with the overestimated volume.
3.1 Representation of icebergs compared to
observations
The results of the CALV experiment reveal that the modelled
calving sites and iceberg tracks fit the observations reasonably
well. As is shown in the Arctic Monitoring and Assessment
Programme (AMAP) plot (Fig. 2b), calving occurs
along almost the entire coast of Greenland, with major
calving sites in Baffin Bay and along the southeast coast of
Greenland. Despite the coarse resolution of GRISLI and the
simplified calving scheme used, these calving sites are generally
well captured (Fig. 6a). The sites in the northeast of
Greenland are overestimated, which is probably caused by
overestimated ice-sheet thickness there compared to observations
(Fig. 4b compared to a). The modelled calving flux
(2.0 × 10−2 Sv, Table 3) is almost twice as large as indicated
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828 M. Bügelmayer et al.: How do icebergs affect the Greenland ice sheet
Table 3. Summary of computed ice discharge (Calvflux) as calculated in GRISLI, surface mass balance (SMB) of the Greenland ice sheet,
runoff as calculated in GRISLI, and sea-ice volume and area as computed in CLIO.
Surface
Calvflux mass balance Runoff Sea-ice Sea-ice
(GRISLI) (GRISLI) (GRISLI) volume area
(Gt yr−1) (Gt yr−1) (Gt yr−1) (103 km3) (1012 km2)
CTRL – 648 – 13,01 10,43
CALV 481 697 65 16,17 10,92
FWFf 453 808 45 15,89 10,91
FWFc 679 791 48 16,14 11,0
Figure 6. (a) Number of icebergs being generated per year; (b)
number of icebergs moving within a grid cell per year. Icebergs
moving within one grid cell for a longer period are counted more
than once (non-linear colour scheme).
by present-day observations that range from 0.8 × 10−2 Sv
(Church et al., 2001) to 1.0 × 10−2 Sv (Hooke, 2005), which
is due to the simplified calving method that assumes calving
as soon as the ice sheet’s thickness is below 150 m, and partly
due to the applied pre-industrial forcing, producing a colder
climate than observed today (Kobashi et al., 2011).
The mean yearly distribution of icebergs (Fig. 6b) illustrates
that the majority of bergs travels along the east and
west coast of Greenland reaching as far south as about 50 ◦N
with a few bergs moving further south and even travelling up
to Europe. The transportation of the icebergs depends on both
the winds and ocean currents. But it can be seen that most
bergs calved east of Greenland are transported southward due
to the northerly winds and the East Greenland Current and
the ones calved west of the GrIS are first moved northward
by the West Greenland Current and then southward again by
the Baffin Island and Labrador Currents (Fig. 6b). Further,
the icebergs calved along the north coast of the GrIS are distributed
in the Arctic Ocean by the Beaufort Gyre and the
prevailing winds. These modelled patterns fit well with observations
(Fig. 2b) and are also found in the model study of
Bigg et al. (1996).
3.2 Impact of icebergs on the pre-industrial climate
and the Greenland ice sheet
(cooling–freshening–distribution effect)
We find that including icebergs in the model set-up (CALV
experiment) causes a cooler ocean state than the CTRL run
around Greenland (Fig. 7a). This is due to the transportation
of the icebergs by winds and ocean currents, leading to a
more extensive distribution of the meltwater, reaching up to
Svalbard and Iceland (Fig. 1d). In accordance with the icebergs’
melt flux, the sea surface temperatures (SSTs, Fig. 7a)
decrease around the GrIS as a result of the take-up of latent
heat needed to melt the icebergs as well as the incoming
cold meltwater (Fig. 1b, d). Strong differences are found
in Baffin Bay due to the large number of icebergs in this
region. The increased melt flux enhances the sea-ice thickness
(SIT) up to 0.7 m (Fig. 7b). In Baffin Bay the response
in sea surface salinity (SSS, Fig. 7d) is two-sided. North of
65◦ N there are lower values due to the icebergs’ freshening
effect, but south of 65◦ N we find higher SSS in CALV than
in CTRL due to enhanced brine rejection by the thickened
sea ice (Fig. 7b). In Hudson Bay the lower SSTs due to the
parameterisation used in CTRL (Fig. 1a) causes less evaporation
and thus lower SSS than in CALV (Fig. 7d). Also in the
Labrador Sea including icebergs causes a decrease of SST by
up to −0.5 ◦C (Fig. 7a) because their meltwater enhances the
ocean’s stratification, thereby weakening the deep convection
and the mixing of the upper water columns with the underlying
warmer and saltier waters (Fig. 7c, d). In the Greenland,
Iceland and Norwegian (GIN) seas, however, the icebergs
freshen the ocean surface and cause a shift of the centre of
the deep convection site southward without a change in the
convective activity (Fig. 7c). The shifted centre is also seen
in the SST and SSS patterns, with locally higher values being
found north of Iceland in CALV than in CTRL.
A thicker sea-ice cover in combination with a higher
albedo and generally lower SSTs cause a cooler atmospheric
state (Fig. 7e, f) in CALV compared to CTRL, since less heat
is exchanged between the ocean and the atmosphere. Thus,
the air temperatures over the whole region decrease by up to
−2 ◦C (Fig. 7e). This changed temperature field is linked to
an altered atmospheric circulation pattern with high-pressure
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M. Bügelmayer et al.: How do icebergs affect the Greenland ice sheet 829
Figure 7. CALV–CTRL differences of 1000-year averages: (a) sea surface temperature, SST (◦C, non-linear colour scheme); (b) sea-ice
thickness (m, non-linear colour scheme); (c) convection layer depth, CLD (m); (d) sea surface salinity, SSS (psu); (e) air temperature,
TAIR (◦C); (f) surface albedo, ALB (%, non-linear colour scheme); (g) total snowfall, SNOW (cm yr−1, non-linear colour scheme); (h)
geopotential (m, non-linear colour scheme).
anomalies over central Greenland (Fig. 7h). This is linked to
less snowfall at the centre of the ice sheet and more along the
ice-sheet border (Fig. 7g), which is also partly seen in the resulting
accumulation patterns of CALV and CTRL (Fig. 5d,
e). In southeastern Greenland the altered snowfall pattern results
in a thinner ice sheet than in CALV (Fig. 4c, 7g). Moreover,
the colder surface temperatures over the ice sheet and
especially western Greenland decrease the ablation zone in
CALV (Fig. 6a, b). This causes an increase in thickness of
the western ice sheet’s margin by up to 300 m in CALV. This
fits better to the observed GrIS height than the CTRL experiment,
where we find an underestimation of the ice sheet’s
thickness in western and an overestimation in eastern Greenland
compared to observations (Fig.4c).
From the comparison of CALV with CTRL we conclude
that icebergs cause an overall colder climate in the mid- to
high latitudes. This pattern is not captured by the homogeneous
uptake of latent heat in the CTRL run because the parameterisation
of icebergs used underestimates the freshening
and cooling (Fig. 1a, b). Overall, the CALV ice sheet is
too extensive and thick compared to observations, as is the
CTRL one. But explicitly modelling icebergs increases (decreases)
the ice-sheet thickness along the western (eastern)
Greenland margin (Fig. 4c), which fits better to observations
(not shown). This is caused by the local effect of the icebergs
on the sea-ice thickness and the atmospheric temperatures.
3.3 Parameterising icebergs using freshwater fluxes –
how well does it work?
3.3.1 The freshening effect (FWFf–CTRL)
In the FWFf experiment the calving flux (1.9 × 10−2 Sv,
Table 3) is released instantaneously at the calving sites
(Fig. 1e), consequently introducing meltwater at 0 ◦C to the
upper ocean layer that freshens and cools it and causes a
cooler mid- to high-latitude climate compared to CTRL. But
the heat needed to melt the ice discharge is not taken up
from the ocean; instead the FWFf and CTRL set-up share
the same parameterisation of homogeneous take-up of latent
heat (Fig. 1a). The FWFf experiment results in up to
0.5 ◦C colder SST (Fig. 8a) than CTRL, particularly around
the GrIS, with the strongest differences in the calving regions,
such as Baffin Bay, or in regions of deep-ocean convection.
We find increased sea-ice thickness in FWFf because
of the colder ocean state, especially north of 65◦ N where it
grows up to 0.6 m thicker compared to CTRL (Fig. 8b). The
deep-ocean convection site in the Labrador Sea is close to the
GrIS margin and thus especially sensitive to the ice sheet’s
ice discharge that weakens the convection and stabilises the
water column, as can be seen in the colder and fresher surface
ocean layer (Fig. 8a, c, d). The opposite is seen in the
GIN seas, where the ocean convection is enhanced and the
centre shifted westwards in FWFf. The colder SSTs close to
the Greenland margin promote deep mixing, which causes
higher SST and higher SSS values north of Iceland. Due to
the shift of convection centre, there is less upwelling of warm
and salty water in the Norwegian Sea, as can be directly seen
in the SST and SSS (Fig. 8a, d).
The altered ocean conditions in FWFf compared to CTRL
are evident in the increased surface albedo due to the thickened
sea ice. Its shielding effect causes lower air temperatures
of up to −1.5 ◦C (Fig. 8b, e). In FWFf there is less
snowfall in the centre of Greenland up to the Denmark Strait
and more along the margins than in CTRL (Fig. 8g). Due
to the colder conditions in Baffin Bay, the ablation zone is
smaller in FWFf than in CTRL (Fig. 5c). This is also rewww.the-cryosphere.net/9/821/2015/
The Cryosphere, 9, 821–835, 2015
830 M. Bügelmayer et al.: How do icebergs affect the Greenland ice sheet
Figure 8. FWFf–CTRL differences of 1000-year averages: (a) sea surface temperature, SST (◦C, non-linear colour scheme); (b) sea-ice
thickness (m, non-linear colour scheme); (c) convection layer depth, CLD (m); (d) sea surface salinity, SSS (psu); (e) air temperature,
TAIR (◦C); (f) surface albedo, ALB (%, non-linear colour scheme); (g) total snowfall, SNOW (cm yr−1, non-linear colour scheme); (h)
geopotential (m, non-linear colour scheme).
flected in the ice-sheet height of FWFf along the western
margin (Fig. 5e). This is in contrast to the thinner eastern
margin (up to 500 m) than CTRL that results from less accumulation
and an enhanced negative surface mass balance
(Fig. 6c, f).
3.3.2 The distribution effect (CALV–FWFc)
Applying the calving fluxes in the form of instantaneous
freshwater fluxes (2.0 × 10−2 Sv, Table 3) that do take-up the
latent heat needed to melt them at the calving sites (FWFc)
both freshens and cools the ocean close to the GrIS margin
(Fig. 1c, e). At the end of the FWFc experiment, the simulated
climate and ice-sheet configuration are similar to CALV
(not shown). Even though the take-up of latent heat, due to
the melt of icebergs, is spatially more restricted in FWFc
than in CALV (Fig. 1b, c), the effect on the ocean (Table 3),
the atmosphere and the GrIS is comparable to CALV (not
shown). Therefore, the spatial pattern of the uptake of latent
heat and released freshwater (distribution effect, Fig. 1) related
to the movement of the icebergs is relatively small under
pre-industrial conditions.
3.3.3 The cooling and distribution effect
(CALV–FWFf)
Using the calving mass calculated by GRISLI to generate
icebergs (as in CALV) that freshen and cool the ocean unevenly
instead of applying this mass in the form of local
freshwater fluxes and homogenous take-up of latent heat (as
in FWFf) results in different ice-sheet topographies at the
end of the experiments. Explicitly modelling icebergs has a
stronger cooling effect close to the Greenland ice sheet than
FWFf, since most of the iceberg melt flux (IMF) is released
close to the ice sheet. The melting of icebergs extracts heat
from the upper layers of the ocean, depending on the size
and the number of bergs (Fig. 1b, d). In FWFf, however, this
spatial pattern of take-up of latent heat is ignored. Therefore,
CALV results in lower SST values (−0.2 ◦C) around the GrIS
and in higher values (+0.2 ◦C) further away. Moreover, the
stronger cooling in CALV allows for a thicker SIT than in
FWFf (Fig. 9b), especially in Baffin Bay where a lot of icebergs
are generated as well as transported to.
In the Labrador and GIN seas the explicit modelling of icebergs
causes a weakened convection compared to FWFf because
the icebergs withdraw the latent heat they need to melt
from the respective ocean layer, thereby stabilising the water
column. Due to the distribution of icebergs, less melt flux
is released in the Greenland Sea than in FWFf because the
calved bergs are moved southward (Fig. 1f). This is displayed
in the higher SSS (0.2 psu) compared to FWFf (Fig. 9d).
The small differences in the resulting ocean state are also
reflected in the atmosphere, which displays lower temperatures
(−0.5 ◦C) over Greenland and North America but
higher temperatures over the North Atlantic and Iceland and
Norwegian seas (Fig. 9e) as well as a slightly changed snowfall
pattern (Fig. 9g). Nevertheless, these relatively small differences
cause thinner ice-sheet thicknesses up to 150 m in
southern Greenland because in FWFf there is less accumulation
and the warmer surface temperatures cause more ablation
than in CALV (Fig. 5b, c, e, f).
From our studies we conclude that the experiments with
the freshwater fluxes from the ice sheet (runoff and calving)
implemented (CALV, FWFf, FWFc) result in a colder
climate than CTRL and an up to 300 m altered ice-sheet
thickness. Even though the resulting ocean and atmospheric
state is comparable in all the freshwater experiments, the icesheet
topographies vary up to 150 m. The differences in iceThe
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M. Bügelmayer et al.: How do icebergs affect the Greenland ice sheet 831
Figure 9. CALV–FWFf differences of 1000-year averages: (a) sea surface temperature, SST (◦C, non-linear colour scheme); (b) sea-ice
thickness (m, non-linear colour scheme); (c) convection layer depth (CLD) (m); (d) sea surface salinity, SSS (psu); (e) air temperature,
TAIR (◦C); (f) surface albedo, ALB (%, non-linear colour scheme); (g) total snowfall, SNOW (cm yr−1, non-linear colour scheme); (h)
geopotential (m, non-linear colour scheme).
sheet thickness arise due to the different spatial pattern of the
added calving flux, either directly at the calving site (FWFf,
FWFc) or distributed by the icebergs (CALV), and especially
due to the spatial pattern of the take-up of latent heat needed
to melt it. Using local freshwater and latent heat fluxes to
parameterise icebergs (FWFc) results in a similar ice sheet
and climate as the explicit modelling of icebergs (CALV),
whereas the differences are stronger if the take-up of latent
heat is computed homogenously (FWFf).
4 Discussion
In the presented study the coupling between the ice-sheet
model GRISLI and the earth system model of intermediate
complexity iLOVECLIM and the dynamical iceberg module
was further developed. This set-up was used to investigate
the impact of icebergs on climate and the ice sheet itself in a
fully coupled low-resolution model. Modelling iceberg calving
is a complex task as small-scale processes are involved
which we cannot expect to represent with the 40 × 40 km
resolution of GRISLI. Still, the calculated calving sites fit
reasonably to observations, as do the modelled iceberg trajectories.
Moreover, as we are particularly interested in the
mechanisms behind the impact of icebergs on both the climate
and the ice sheet, we would argue that these are relatively
insensitive to the ice-sheet model resolution. Nevertheless,
the modelled calving sites and iceberg trajectories
fit reasonably to the observations. This is the calving flux
is twice as large as currently observed, due to the ice sheet’s
model resolution, which might result in an overestimated impact
of the icebergs. Another potential limitation is that the
refreezing of the meltwater, as well as splitting-up of bergs,
is not accounted for. Excluding this latter process probably
leads to an underestimation of the spread of the freshwater
anomaly, but an overestimation of the near-shore freshwater
input, as has been reported by Martin and Adcroft (2010).
This could explain the less extensive spread of the iceberg
melt flux in our simulations compared to theirs. Despite the
aforementioned shortcomings, this model set-up is a valuable
tool with which to investigate the effect of icebergs on the
climate of the mid- to high latitudes and the Greenland ice
sheet, especially as the EMIC is coupled to a dynamically
computed ice-sheet model and therefore changes in calving
rates and positions are taken into account. This is of particular
interest for the study of past climate changes at relatively
long timescales (centennial to multi-millennia), when large
changes in the ice-sheet geometry can also be expected.
So far, icebergs have mostly been parameterised using
freshwater fluxes to save computation time. To study the impact
of such parameterisations, we compared dynamically
included icebergs to freshwater fluxes released at the same
locations and according to the same seasonal cycle as the
icebergs and found noticeable differences. Icebergs cause
thicker sea ice all around Greenland and especially in Baffin
Bay and the Arctic Ocean compared to the freshwater
fluxes being applied at the calving locations together with
homogeneous take-up of latent heat around Greenland. This
is comparable to the findings of Jongma et al. (2009), who
performed sensitivity studies under pre-industrial conditions,
where they investigated the different impact of icebergs compared
to homogeneously distributed freshwater fluxes south
of 55◦ in the Southern Ocean. They found that the effect
of icebergs is restricted closer to shore than the freshwater
fluxes and that the sea-ice formation is facilitated by icebergs.
Yet, when we apply local freshwater fluxes that cool
the ocean locally due to the take-up of latent heat, these differences
decrease, and in regions where more freshwater is
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832 M. Bügelmayer et al.: How do icebergs affect the Greenland ice sheet
released directly than in the form of icebergs these fluxes are
generally more efficient in producing thicker sea ice. This
is in agreement with Martin and Adcroft (2010), who investigated
the impact of interactively coupled icebergs in an
atmosphere–ocean GCM and also compared it to directly applied
freshwater fluxes. They find a decrease in sea-ice thickness
almost everywhere around Antarctica besides a few regions
when generating icebergs. Hunke and Comeau (2011)
also investigated the interactions between sea ice and both
giant and small icebergs in the Southern Ocean using a standalone
ocean model with explicitly included icebergs that are
moved according to the ocean currents and the atmospheric
forcing applied. They revealed that the bergs locally affect
the sea-ice thickness and area but conclude that on a global
scale these dynamically induced differences are negligible.
In our study the effects on sea ice are over a bigger spatial
scale and have an extensive impact via feedback mechanisms
on the atmosphere and consequently the development of the
ice sheet. In most regions, the experiment with the explicitly
modelled icebergs enhances the sea-ice thickness stronger
than the other freshwater experiments because of both the
freshening and the cooling effect as the bergs take up the latent
heat from the ocean. These findings coincide with the
results of Jongma et al. (2013), who investigated the impact
of icebergs on climate during Heinrich events. They show
that including icebergs as meltwater fluxes and take-up of latent
heat has a stronger impact on climate than just meltwater
fluxes.
The presented coupled model set-up offers a great approach
to conduct long-term experiments to better understand
the role of icebergs and the interactions between the
different climate components during abrupt climate changes.
This is feasible with the presented model since the computation
time for 1000 model years is about 2 days in the fully
coupled set-up. A useful next step could be to use this model
set-up to study Heinrich events in detail, as the crucial question
as to how the icebergs’ feedback was on climate under
colder and more instable times has not yet been fully ad-
dressed.
5 Conclusions
We have coupled the ice-sheet model GRISLI to the
earth system model iLOVECLIM to study the impact of
dynamical-thermodynamical icebergs on climate and the
Greenland ice sheet under pre-industrial conditions. We find
that the modelled calving sites correspond well with presentday
observations with a slight underestimation of the calving
along the southeastern margin of Greenland. The amount of
ice being calved is almost 2 times the value observed for the
present-day climate, which can be explained by the colder
pre-industrial than present-day climate conditions and the
simple calving method used. Further, the main iceberg routes
are reproduced using the modelled winds and ocean currents.
According to our study, implementing the freshwater
fluxes (calving and runoff) from the Greenland ice sheet
causes a colder climate at mid- to high latitudes. Explicitly
including icebergs results in an increased sea-ice thickness
all around the Greenland ice sheet, especially north of
65◦ N. Consequently, we find higher surface albedo values
and a weakened sensible heat flux, due to its shielding effect.
Therefore, icebergs cause cooler air temperatures above
Greenland and a shift in the atmospheric pattern, which
is linked to decreased snowfall over central and southern
Greenland and an increased one at the ice-sheet border. The
colder prevailing temperatures and the changed accumulation
pattern lead to a thicker western ice-sheet height and a
thinner eastern ice sheet (up to 300 m), which fit better to
observations.
From the presented analysis we conclude that the strongest
impact of calving on the climate is due to the spatial distribution
of the take-up of latent heat needed to melt the ice
mass and that the freshening due to the released meltwater
has a smaller impact. Applying direct freshwater fluxes that
absorb the latent heat locally at the calving sites results in a
similar climate and ice-sheet geometry as in the CALV experiment.
However, directly applied freshwater fluxes together
with homogenous take-up of latent heat lead to an underestimated
cooling at the ice-sheet border and an overestimated
one temperatures further away. The warmer surface temperatures
over southern Greenland cause higher ablation rates and
result in a 150 m reduction in ice-sheet thickness compared
to the iceberg experiment.
In the present study the resulting climate conditions and
ice-sheet geometries differ between the experiments even
though they were done under pre-industrial conditions where
the calving rates are relatively constant and small. The impact
of icebergs on the ice sheet’s development is thought
to be stronger during colder climate conditions with higher
calving rates.
Acknowledgements. M. Bügelmayer is supported by NWO through
the VIDI/AC2ME project no. 864.09.013. D. M. Roche is supported
by NWO through the VIDI/AC2ME project no. 864.09.013 and by
CNRS-INSU. The authors wish to thank Christophe Dumas for his
advice and help in the coupling of the ice-sheet model to the iceberg
module and Catherine Ritz for the use of the GRISLI ice-sheet
model. Further, the authors wish to thank the reviewers for providing
constructive comments on how to improve the quality of this
paper. The authors also gratefully acknowledge the Institute Pierre
Simon Laplace for hosting the iLOVECLIM model code under
the LUDUS framework project (https://forge.ipsl.jussieu.fr/ludus).
This is NWO/AC2ME contribution number 06.
Edited by: E. Larour
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M. Bügelmayer et al.: How do icebergs affect the Greenland ice sheet 833
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