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Evolution of the Global Coupled Climate Response to Arctic Sea Ice
Loss during 1990–2090 and Its Contribution to Climate Change
LANTAO SUN
Cooperative Institute for Research in Environmental Sciences, University of Colorado Boulder, andPhysical Sciences Division, NOAA/Earth System Research Laboratory, Boulder, Colorado

MICHAEL ALEXANDER
Physical Sciences Division, NOAA/Earth System Research Laboratory, Boulder, Colorado

CLARA DESER
Climate and Global Dynamics, National Center for Atmospheric Research, Boulder, Colorado(Manuscript received 5 March 2018, in final form 22 June 2018)
ABSTRACTThe role of transient Arctic sea ice loss in the projected greenhouse gas–induced late-twentieth- to latetwenty-first-century climate change is investigated using the Geophysical Fluid Dynamics Laboratory’s
Coupled Model version 3. Two sets of simulations have been conducted, one with representative concentration pathway (RCP) 8.5 radiative forcing and the second with RCP forcing but with Arctic sea ice nudged
to its 1990 state. The difference between the two five-member sets indicates the influence of decreasing Arctic
sea ice on the climate system. Within the Arctic, sea ice loss is found to be a primary driver of the surface
temperature and precipitation changes. Arctic sea ice depletion also plays a dominant role in projected Atlantic meridional overturning circulation weakening and changes in North Atlantic extratropical sea surface
temperature and salinity, especially in the first half century. The effect of present-day Arctic sea ice loss on
Northern Hemisphere (NH) extratropical atmospheric circulation is small relative to internal variability andthe future sea ice loss effect on atmospheric circulation is distinct from the projected anthropogenic change.
Arctic sea ice loss warms NH extratropical continents and is an important contributor to global warming not
only over high latitudes but also in the eastern United States. Last, the Arctic sea ice loss displaces the Pacificintertropical convergence zone (ITCZ) equatorward and induces a ‘‘mini-global warming’’ in the tropicalupper troposphere.

1. Introduction
Arctic sea ice extent has declined rapidly over the past
three decades, likely resulting from increased poleward
heat transport and local radiative feedbacks associatedwith an increase in greenhouse gases (e.g., Park et al.
2015). Internal climate variability may also have contributed to sea ice loss (e.g., Mahajan et al. 2011; Dayet al. 2012; Yeager et al. 2015; Zhang 2015; Ding et al.
2017; Lee et al. 2017; Li et al. 2017, 2018). Climate
Supplemental information related to this paper is available atthe Journals Online website: https://doi.org/10.1175/JCLI-D-180134.s1.
Corresponding author: Dr. Lantao Sun, lantao.sun@noaa.gov

models forced by increasing greenhouse gas (GHG)
concentrations project an ice-free Arctic Ocean during
summer by the mid-to-late twenty-first century (e.g.,
Stroeve et al. 2012; Wang and Overland 2012). The
disappearing sea ice can affect the atmosphere andocean locally and remotely. Within the Arctic, nearsurface air temperature rises much faster than in the lower
latitudes (Screen and Simmonds 2010). Arctic precipitation also increases (Deser et al. 2010), dominated by rainnear the end of the twenty-first century, especially in thewarm seasons (Bintanja and Andry 2017). With fullocean–atmosphere coupling, the signals associated with
Arctic sea ice change can be seen in the tropics, and evenas far as Antarctica (e.g., Deser et al. 2015).
The remote effect of Arctic sea ice reduction on
Northern Hemisphere (NH) midlatitude weather and

DOI: 10.1175/JCLI-D-18-0134.1
Ó 2018 American Meteorological Society. For information regarding reuse of this content and general copyright information, consult the AMS Copyright
Policy (www.ametsoc.org/PUBSReuseLicenses).

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climate has been investigated for several decades. By
prescribing Arctic sea ice concentration changes in atmospheric general circulation models (AGCMs), many
previous studies have addressed the extent to which
Arctic sea ice loss influences the large-scale atmosphericcirculation and surface climate. For example, Deseret al. (2004) found that sea ice loss–induced circulation
changes are composed of a local baroclinic structurewith the surface trough and upper-level ridge and an
equivalent barotropic structure that resembles the negative phase of the North Atlantic Oscillation (NAO)/
northern annular mode (NAM). Also, several AGCM
experiments have suggested that most of the midlatitudecontinents warm in response to a reduction in sea ice
with the exception of central/eastern Asia, where weakcooling may appear in relation to an enhanced Siberianhigh (e.g., Peings and Magnusdottir 2014; Screen
et al. 2015a; Sun et al. 2015; Semmler et al. 2016).
These studies, however, cannot be used to address thequestions associated with the ocean change and ocean–
atmosphere coupling because the lower boundary conditions are specified.
More recently, some studies have utilized coupled atmosphere–ocean general circulation models(AOGCMs) to investigate the global climate response
to Arctic sea ice loss, either by altering the sea ice parameters such as albedo (e.g., Bitz et al. 2006; Winton
2008; Scinocca et al. 2009; Graversen and Wang 2009;Blackport and Kushner 2016, 2017; Cvijanovic et al.
2017) or by adding an additional heat flux to the sea ice
throughout the simulation (‘‘ghost forcing’’; Deser et al.
2015; Deser et al. 2016; Tomas et al. 2016; Oudar et al.
2017) or by sea ice nudging (McCusker et al. 2017; Smithet al. 2017). Arctic sea ice loss imposes surface heat andfreshwater into the ocean, and thus has the potential toinfluence ocean circulation, including the density-driven
Atlantic meridional overturning circulation (AMOC),
whose northern boundary interacts with Arctic sea ice(e.g., Li et al. 2017). The AMOC weakens in response to
an abrupt reduction in sea ice (Bitz et al. 2006; Winton
2008; Scinocca et al. 2009; Blackport and Kushner 2016;
Tomas et al. 2016; Oudar et al. 2017), in agreement withthe projected decline in simulations from phase 5 of the
Coupled Model Intercomparison Project (CMIP5)(Cheng et al. 2013; Collins et al. 2013). In addition,
Sévellec et al. (2017) examined the sensitivity of the
AMOC to the surface heat and freshwater fluxes andsuggested that 75% of the observed AMOC decline isdriven by Arctic sea ice changes. In these aforementioned sea ice experiments, the ‘‘North Atlantic
warming hole,’’ with little warming or even a decrease
in sea surface temperatures (SSTs) to the south ofGreenland, appears to be associated with the slowing of

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the AMOC (Cheng et al. 2013; Collins et al. 2013;
Tomas et al. 2016).
With ocean–atmosphere coupling, Arctic sea ice loss
can impact the tropical ocean and the location of theintertropical convergence zone (ITCZ), but the response varies depending on the type of ocean coupling.
Deser et al. (2015) conducted experiments with theCommunity Climate System Model version 4 (CCSM4),
which includes an ocean general circulation model(GCM). They found that the projected Arctic sea ice
loss caused the ITCZ to be displaced toward the equator. Moreover, as a result of enhanced equatorial convection and latent heat release, zonal-mean temperature
increases in the tropical upper troposphere, resemblinga ‘‘mini-global warming’’ due to increased GHG emissions. With ocean dynamics disabled by using a slab-ocean
model in place of the ocean GCM, the ITCZ is displaced
northward, toward the hemisphere in which sea ice declines(Deser et al. 2015; Tomas et al. 2016), which is consistent
with similar studies that use slab-ocean coupled models(e.g., Chiang and Bitz 2005; Broccoli et al. 2006; Frierson
and Hwang 2012; Cvijanovic et al. 2017) or fully coupledmodels that constrained ocean temperature and salinity
below 200 m (Smith et al. 2017). The sensitivity of the ITCZ
response to ocean coupling is closely connected to thecross-equatorial northward heat transport accomplished byboth the ocean and atmosphere (Deser et al. 2015; Tomas
et al. 2016; Kay et al. 2016). In the NH extratropics, theocean–atmosphere coupling can magnify the atmospheric
response to Arctic sea ice loss as compared to atmosphereonly simulations but does not change its overall structure, given that both dynamical and thermodynamical
processes have been included for a proper representation of oceanic feedbacks (Deser et al. 2016).
Most previous studies have focused on the equilibrium climate response to an abrupt Arctic sea ice loss
and only few looked at the transient evolutions. For
example, Blackport and Kushner (2016) compared theextratropical response in equilibrium with that averaged
over the first 50 years. Wang et al. (2018) exploredthe tropical response using full ocean coupled andslab-ocean coupled AOGCMs and found that ocean
dynamics become important within two decades of asudden loss of sea ice, considerably faster than often
assumed (Cvijanovic et al. 2017). Moreover, in theseexperiments the sea ice depletion occurs abruptly at the
beginning, and thus the transient response to sea ice loss
cannot be directly compared with the transient change
in fully forced climate projections, whose ice forcing
increases with time. And abrupt sea ice loss studies
cannot be used to tell how much the present-day sea ice
reduction may affect the NH jet stream either, a topic
still in debate [see two distinct perspectives in Barnes

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and Screen (2015) and Francis et al. (2017); see also
references therein].
The goal of this study is to comprehensively evaluate
the contributions of transient Arctic sea ice loss to theprojected global climate change over the twenty-first
century in a fully coupled climate model. While previous
studies investigated the equilibrium response to an
abrupt sea ice decline, we focus on the transient response to a gradually increasing projected Arctic sea ice
loss, which bridges the gap between present-day andfuture sea ice conditions and their potential impact on
the climate system. The rest of this paper is organized
into four sections. Section 2 contains a description of themodel used here, the Coupled Model version 3 (CM3)from the Geophysical Fluid Dynamics Laboratory(GFDL), and the experimental design. Section 3 presents the effects of transient Arctic sea ice loss on theocean and atmosphere and their contributions to the total
anthropogenic global climate change, including the responses in the Arctic, NH extratropics, and tropics.
Discussion and conclusions follow in section 4.

2. Model and experimental design
a. Model description
CM3 (version Ulm_201505) is composed of version 3of the atmospheric model (AM3), the Modular Ocean
Model version 5 (MOM5), a sea ice model, and landmodel components. AM3 uses a cubed-sphere implementation of a finite-volume dynamical core with thehorizontal resolution of approximately 200 km (Donneret al. 2011). The vertical resolution ranges approximately from 70 m near Earth’s surface to 1–1.5 km near
the tropopause and 3–4 km in much of the stratosphere,with the top model level at approximately 80 km(Donner et al. 2011). Compared to the previous versionof the atmosphere model (AM2), AM3 includes a morecomprehensive treatment of the indirect effect of aerosols and cloud drop number concentrations (Golaz et al.
2011). The horizontal resolution of MOM5 is 18 in latitude with enhanced meridional resolution equatorward
of 308N/S that reaches 1/38 at the equator (Griffies et al.
2011). The sea ice model, documented in Delworth et al.
(2006) and Winton (2000), uses the same horizontal gridarrangement as the ocean model. The Arctic sea ice
concentration and thickness in CM3 are in better agreement with observations than in the previous version of
the model (CM2; Griffies et al. 2011; Li et al. 2018).

b. Experimental design
We conducted two types of transient simulations.
First, a five-member ensemble of CM3 simulations were
performed over the period 1970–2090 by following theCMIP5 historical and representative concentration
pathway 8.5 (RCP8.5) protocol (denoted as RCP hereafter) to characterize the ‘‘full’’ global climate change.
This is a business-as-usual scenario in which the radiative forcing will reach 8.5 W m22 by 2100 (Riahi et al.
2011). This simulation allows us to calculate the climate
response to total anthropogenic forcing by calculating
the difference from 1971–90 climatology:
DRCP(year) 5 RCP(year)–RCP(1971 2 90) ,(1)

where ‘‘year’’ varies from 1990 to 2090. To isolate theArctic sea ice loss effect, five corresponding RCP simulations were conducted with the Arctic sea ice volume
artificially relaxed to a repeating seasonal cycle of 1990
sea ice conditions in each ensemble member (denoted as
RCP_ICE1990 hereafter). The initial condition of eachmember of RCP_ICE1990 also comes from 1 January
1990 of the corresponding RCP simulation to avoid any
discontinuity. This simulation can tell the climate response to anthropogenic forcing without Arctic sea icechanges, which is
DRCP_ICE1990(year)
5 RCP_ICE1990(year)–RCP(1971 2 90) .

(2)

The difference between DRCP and DRCP_ICE1990 canbe solely attributed to the effect of projected transient
Arctic sea ice loss, referred to as
DICE(year) 5 DRCP(year)–DRCP_ICE1990(year)
5 RCP(year)–RCP_ICE1990(year) ,(3)

where the same climatological reference is used to define the temporal difference in both experiments, so
DICE reduces to the difference between experiments forthe time period being examined. Note that in our experiments, DICE, the sea ice loss effect, is derived indirectly, different from some previous studies that keep
radiative forcing fixed with a change in sea ice being theonly forcing (e.g., Deser et al. 2015; Blackport andKushner 2016; Wang et al. 2018). However, it has beenshown that the effect of sea ice loss in the overall change
to increasing GHG is quite linear (McCusker et al.
2017), suggesting that our results may still be comparedwith those studies. While choosing the 1990 start timeinsures the simulations are identical at their start, there
is a small mismatch between the climate change effect(relative to 1971–90 climatology) and sea ice loss effect(relative to 1990 conditions) such that the fraction ofsea ice loss contribution (DICE/DRCP) may be slightly
underestimated, especially in the initial years. The
statistical significance is evaluated using two-sided

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Student’s t test based on the ensemble mean by treatingeach year to be an independent sample.
The sea ice volume nudging technique (Knutson 2003)
in RCP_ICE1990 is very similar to the method describedin McCusker et al. (2017) and works continuously to theice model over the course of the simulations. At eachtime step, the model calculates the enthalpy needed toconvert the Arctic sea ice volume to the target (i.e., theRCP 1990 value). This enthalpy is then applied to thebottom of the ice via a time-varying ‘‘ghost flux’’:
Qflux 5

Lice Dice (Cice hice 2 Cice_t hice_t ) dt
t ice

,

(4)

where Lice is the latent heat of fusion (3.34 3 105 J kg21),
Dice is the density of ice (905 kg m23), Cice is the sea ice
concentration (%), hice is the sea ice thickness (m), Cice_t
is the target sea ice concentration, hice_t is the target sea
ice thickness, dt is the time step (2 h), and tice is the relaxation time (5 days). We also account for the changes
in snow layer above the ice when calculating the Qflux.
When conducting the nudging, the Qflux is only applied
to the sea ice model and does not directly interact withthe ocean. Moreover, the ice bottom temperature isfixed at freezing in the model (Winton 2000), so thenudging does not artificially cool the underlying Arctic
Ocean (not shown). The nudging itself does not appear
to impact the AMOC, either. In the RCP simulation
when the sea ice is nudged to that in the RCP, theAMOC response also tends to follow that in RCP anddiverges from that in RCP_ICE1990 (not shown). Whileenergy is not conserved in the nudged RCP_ICE1990
simulations, effort has been made to conserve the water
flux across the atmosphere–ice–ocean interface so thatthe global water mass budget is always conserved. Additionally, there are some grid points around Greenland withunrealistically high ice thickness (more than 40 m, up to;600 m) in the RCP simulations. Conducting nudging inthese grid points caused the model to crash. To resolve thatissue, smaller values have been used in both initial condition and the ice volume target in RCP_ICE1990. Since sea
ice volume is always nudged to the 1990 condition, thisdid not affect the surface heat and freshwater budgets.

3. Resultsa. Arctic sea ice loss and surface energy flux response
Figure 1 shows the March and September Arctic sea
ice concentrations during 1971–90, 2011–50, 2051–90,
and the Arctic sea ice extent (SIE) evolution in RCP
simulations (black curves). The climatological sea ice
concentration and SIEs in March and September areboth in good agreement with observations (observed

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concentration not shown; green curves indicate observed SIEs from National Snow and Ice Data Center)(Fetterer et al. 2017). With increasing GHG concentrations, Arctic sea ice declines rapidly and the simulated SIE trend is slightly larger than in observations
during 1979–2017. The Arctic Ocean becomes ice-free(defined as the year of sea ice extent minimum less than
1 million km2) in the ensemble mean during summer by
2026 (;2040 if based on August SIE), a few decades
earlier than the ensemble mean of the models from
CMIP5 and the Community Earth System Model(CESM) Large Ensemble (Wang and Overland 2012;
Jahn et al. 2016). The faster sea ice decline in CM3 RCP
simulations might be partly related to the stronger atmospheric response to the reduction of future anthropogenic aerosol emissions through the indirect effects ofaerosols, increasing the climate sensitivity (Andrews
et al. 2012). The Arctic sea ice extent in RCP_ICE1990
is also shown in Figs. 1b and 1c (red curves). As a resultof sea ice nudging, Arctic sea ice extent, concentration,and thickness remain close to the corresponding RCP
1990 conditions even though the radiative forcing increases following the RCP8.5 protocol (Figs. 1b,c; seealso Fig. S1 in the online supplemental material).
Sea ice loss impacts the atmosphere and ocean locally
via surface energy fluxes (i.e., the latent heat flux, sensible heat flux, longwave radiative flux, and net solar
radiative flux). (Note that ocean can be heated by solar
radiation but the atmosphere is effectively transparent
to it.) The monthly change of SIE between 1971–90 and
2051–90 (bars) and the Arctic surface energy flux response in DICE (curves; obtained by differencing the
RCP and RCP_ICE1990 averaged over climatological
March SIE region and over 2051–90) are shown in Fig. 2.
During 2051–90, the maximum sea ice loss appears inJune–July and November–December; in contrast, themaximum loss occurs in September–October during
2011–50 (Fig. S2). In agreement with previous studies(e.g., Deser et al. 2010), Arctic sea ice loss induces more
upward heat flux into the atmosphere especially in
winter (Fig. 2a). Sea ice loss warms the Arctic Ocean
mostly in summer through downward solar radiation
as a result of surface albedo decrease and disappearing
ice barrier, which is partly offset by the upward heat flux
across the ocean–ice–atmosphere surface (Fig. 2b). In
winter, because of the lack of solar radiation, sea ice loss
is only responsible for strong fluxes from the ocean tothe atmosphere (bottom right panels of Figs. 2a and 2b).
The upward surface heat fluxes in the sea ice loss regions
are accompanied by downward fluxes farther south. Thisdipole pattern is a common feature in AGCM and
AOGCM sea ice experiments (e.g., Deser et al. 2010; Sunet al. 2015; Oudar et al. 2017) and can be explained as

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FIG. 1. (a) Arctic sea ice concentration (%) averaged over (left) 1971–90, (middle) 2011–50, and (right) 2051–90
in RCP experiments. (b) March Arctic sea ice extent (106 km2) from CM3 RCP and RCP_ICE1990 experiments.
(c) As in (b), but for sea ice extent in September. Thin gray (pink) curves denote the RCP (RCP_ICE1990) individual members and thick curve denotes the ensemble mean. Green curves show the observed values from
National Snow and Ice Data Center. Blue lines in (a) are due to polar projections on tripolar grids.

advection of anomalous warm air due to sea ice loss to thesurrounding region imposing downward heat fluxes. In the
North Atlantic, part of the downward heat flux is related
to the SST cooling as a result of ocean circulation changes,
as will be discussed in the next subsection. All these features are robust for both 2011–50 and 2051–90, withgreater magnitudes in the later period (Fig. 2 and Fig. S2).

b. Arctic climate change
Figures 3a and 3b show the seasonal cycles of Arctic
near-surface air temperature and SST responses in
DICE (RCP minus RCP_ICE1990; blue bars) and
DRCP [RCP minus RCP(1971–90); black bars] averaged
over 2011–50 (filled bars) and 2051–90 (empty bars),
while the sea ice contribution to the total change (DICE/
DRCP) is shown in Fig. 3d. Here, ‘‘Arctic’’ is defined as
the region encompassing the climatological March SIE;

similar results are obtained using the climatologicalmonthly SIE (not shown). Consistent with the surface
energy flux response, the maximum atmosphericwarming occurs in winter while the maximum oceanic
SST warming occurs in summer in DICE, with larger
magnitudes over 2051–90 compared to 2011–50. About
60%–80% of the projected SST warming in DRCP occurs in DICE over 2011–50 and the sea ice loss contribution increases to 80%–90% over 2051–90, indicatingthat the future Arctic Ocean SST change is primarily
due to sea ice loss. The contribution of sea ice loss to theprojected near-surface air temperature response issimilar between two periods and seasonally dependent,with the largest contribution (;80%) in winter andsmallest contribution (;40%–50%) in summer.
Figures 3c and 3d show the 2011–50 and 2051–90 averaged precipitation responses in DICE, DRCP, and7828

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FIG. 2. (a) (top) Monthly change of SIE between 1971–90 and 2051–90 (gray bars; 106 km2), and Arctic atmospheric surface energy flux (W m22; positive upward) response in DICE (obtained by differencing the RCP and
RCP_ICE1990 and averaged over the climatological March SIE region) during 2051–90. Atmospheric surface
energy flux includes longwave radiative flux (LWR), sensible heat (SH), and latent heat (LH) flux. Shortwave
radiative flux (SWR) is displayed separately. (bottom) Atmospheric surface energy flux response in (left) JJA and(right) DJF. (b) As in (a) but for the ocean surface energy flux response (positive downward). Ocean surface energy
flux includes SWR, LWR, SH, and LH. Contour interval is 20 W m22. Note that (a) is obtained from atmospheremodel output and (b) is obtained from ocean model output. White lines in the bottom panel of (b) are due to polar
projections on tripolar grids.

DICE/DRCP, indicating an even larger seasonal dependence than the temperature response. In particular,
sea ice loss induces ;0.2 mm day21 precipitation increases
in winter over 2011–50, accounting for about 80% of
projected precipitation change. In summer, by contrast,
Arctic precipitation increases by less than 0.05 mm day21
in response to disappearing sea ice, accounting for only
;10%–20% of the projected change. A similar fractionof the sea ice loss contribution also appears in 2051–90,
although the magnitudes in both DICE and DRCP arelarger. As a result of atmospheric warming, the Arctic
precipitation increase in the late twenty-first century isdominated by rain instead of snow, especially in April–
November (Fig. S3; Bintanja and Andry 2017). The
contribution from sea ice loss to the projected changes inrain and snow are similar to the total precipitation,
ranging from ;15% in summer to ;80% in winter.
One may wonder how different the Arctic climate
response will be once sea ice is completely gone in
September. Figure S4 shows the September near-surface
air temperature and SST response time series in DICE
and DRCP. The Arctic temperature appears to continue
warming in DICE after the ice-free period (;2026). One
possible explanation is that sea ice loss in other seasons
may still contribute a continuation of the warming in theatmosphere and ocean in September. This is further
explored by checking the evolution of September Arctic
surface energy flux response to sea ice loss (Fig. S5).
While the shortwave flux response appears to be nearlystable after the ice-free period, the longwave flux andlatent heat flux responses continue to increase. Thissuggests that sea ice loss effect continues to increase in
September even after September is ice-free.

c. North Atlantic Ocean response
The AMOC response time series in DICE and DRCP
are shown in Figs. 4a and 4d. Following previous studies(e.g., Cheng et al. 2013; Oudar et al. 2017) an AMOC
index is defined as the annual-mean maximum volumetransport streamfunction at 308N, although the index
trend was not sensitive to the selected latitude. For
model ensemble mean, AMOC declines by ;6 Sv(1 Sv [ 106 m3 s21) during 1990–2090 in response to
Arctic sea ice reduction and roughly two-thirds occur inthe first 20 years (estimated based on 20-yr runningmean; shown by dashed red curve). But there is a fair bitof variability among different ensemble members andthese differences in the trend may partly be caused by
the natural variability. The total AMOC decline during
1990–2090 (;6 Sv) is larger than in Tomas et al. (2016)

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FIG. 3. (a) Monthly change of Arctic near-surface air temperature (8C) responses in DICE (blue bars; RCP minus
RCP_ICE1990) and DRCP [black bars; RCP minus RCP(1971–90)] averaged over 2011–50 (filled bars) and 2051–
90 (empty bars). (b) As in (a), but for the Arctic sea surface temperature (8C) responses. (c) As in (a), but for theArctic precipitation (mm day21) responses. (d) Seasonal cycle of the fraction (%) of DICE/DRCP. In (a)–(c), theArctic is defined as the region of climatological Arctic sea ice extent in March.

and Blackport and Kushner (2016) (;2 Sv) but close tothat in Oudar et al. (2017). Moreover, the sea ice loss–
induced transient AMOC change is quite different fromthe change in RCP simulations, which shows a quasilinear decrease of ;1.2 Sv per decade and exhibits
much smaller natural variability. During 1990–2090, theAMOC decreases by ;12 Sv in RCP simulations androughly half of it (;6 Sv) is driven by the transient Arctic
sea ice loss. Figures 4b,e and 4c,f show the AMOC
streamfunction in DICE and DRCP during 2011–50 and
2051–90, respectively, as a function of latitude and depth.
In agreement with the time series in Figs. 4a and 4d, thesea ice loss–induced streamfunction can explain most of
the projected decline during 2011–50 and this fraction
becomes smaller during 2051–90 as AMOC largely stabilizes in response to projected sea ice loss but it continues to decline under anthropogenic climate change.
The ocean circulation change is accompanied bychanges in SSTs. The top panels of Fig. 5 show the annual North Atlantic SST response in DICE and DRCP
during four 20-yr periods after 2010. In response
to Arctic sea ice loss, SST increases mostly over marginal seas (e.g., Hudson Bay and areas surrounding
Greenland). Weak SST warming also appears in thelower-latitude Atlantic Ocean especially in 2071–90.
Near 508–608N, 278–378W (box), there is a small regionof SST cooling in DICE. Similar cooling also appears in
DRCP and other full climate change simulations (e.g.,

Collins et al. 2013) and is commonly referred to as theNorth Atlantic warming hole (NAWH). The NAWH
has been found to be closely related to the AMOC decline [see Fig. 6 in Cheng et al. (2013)], part of which canbe attributed to the Arctic sea ice depletion (e.g., Deseret al. 2016; Sévellec et al. 2017; Suo et al. 2017).
The NAWH in DICE and DRCP also evolves withtime (Fig. 5, top panels). During 2011–30, the SST
cooling region in DICE is well beyond the box, extending farther westward and southward. Over time, themagnitude of the cold SSTs gradually weakens and shifts
to the southeast corner of the region due to warming on
the west side of the NAWH and such warming appears
to come primarily from the sensible heat flux (notshown). The SST evolution in DRCP is similar to DICE,
but the NAWH simply weakens and shrinks inside thebox region. The bottom panel in Fig. 5 shows the timeseries of the NAWH SST response in DICE and DRCP.
In response to transient Arctic sea ice loss, annual SST
first decreases following the decline of AMOC, thentransitions back to warming by late twenty-first century
while AMOC weakening persists. Similar SST evolution
also appears in DRCP, but with smaller magnitude ofcooling likely due to the compensation of surface
warming by increased radiative forcing. Moreover, the
NAWH SST in DICE and DRCP both exhibit a welldefined seasonal change, with cooling to be stronger inwinter and weaker (or even warming) in summer (Fig. 5,

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FIG. 4. (a),(d) Time series of AMOC response (in Sv) in DICE and DRCP, respectively. Thin blue curves denotethe individual members and thick blue curve indicate ensemble mean. Dashed red curve indicates the smoothedblue curve using 20-yr running mean. (b),(e) Latitude–depth cross section of the AMOC streamfunction averaged over
2011–50 in DICE and DRCP, respectively. (c),(f) As in (b),(e), but averaged over 2051–90. Contour interval is 2 Sv.

bottom panel). This also occurs in observations of
AMOC (Caesar et al. 2018). It is likely related to theseasonal cycle in the ocean mixed-layer depth, which ismuch shallower in summer than in winter so that thegreenhouse gas–induced warming from the atmosphereis confined to a much thinner layer (Alexander et al. 2018)
and AMOC has a much smaller effect on SSTs in summer.
The corresponding annual North Atlantic sea surface
salinity (SSS) responses in DICE and DRCP are shownin Fig. 6. In response to continued sea ice loss, the salinity shows a freshening of the surface water at North
Atlantic subpolar gyre and an increase in salinity in thesubtropical gyre. The freshening near the Arctic is likely
related to the increased freshwater flux as a result of sea
ice melting and overall increased precipitation (Fig. S6).

In addition, the SSS response may be partly related tothe change in AMOC due to its similarity to the AMOC
regression pattern (Cheng et al. 2013). For example, thefreshening around the NAWH is largely explained by
the increase in precipitation minus evaporation (Fig. S7)
as a result of decrease in evaporation (not shown). Thereis a strong resemblance between sea ice loss–induced
salinity change and the projected RCP change. Arctic
sea ice loss can explain the majority of the salinity decrease in the mid-to-high latitudes of the North Atlantic,
especially prior to 2050, and part of the salinity increasein subtropics. In contrast, in the North Pacific, while thesurface salinity is projected to decrease in DRCP, there
is very little change in DICE (not shown), implying thedifferent influences of sea ice loss on the two oceans.

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FIG. 5. (top four rows) Annual North Atlantic SST responses in (left) DICE and (right) DRCP averaged over
2011–30, 2031–50, 2051–70, and 2071–90. Black boxes indicate the North Atlantic warming hole (NAWH; 508–608N,
278–378W). (bottom) Time series of the NAWH annual (thick curve) and JJA and DJF (thin curve) SST responses in(left) DICE and (right) DRCP. Stippling denotes the 95% statistical significance based on two-sided Student’s t test.

d. NH extratropical atmospheric circulation response
Figure 7a shows the monthly change of the 700-hPa
zonal-mean zonal wind response in DICE during 2051–
90. The NH atmospheric response peaks in winter(December–February), characterized by a meridional
dipole with zonal wind deceleration centered at 608N
and zonal wind acceleration between 358 and 458N.
There is also zonal wind deceleration at lower latitudes
signifying a narrowing of the jet. Figure 7b shows the7832

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FIG. 6. As in Fig. 5 (top four rows), but for the annual North Atlantic sea surface salinity (SSS; psu) responses in(left) DICE and (right) DRCP averaged over 2011–30, 2031–50, 2051–70, and 2071–90. Stippling denotes the 95%
statistical significance based on a two-sided Student’s t test.

winter 700-hPa zonal wind responses in DICE and
DRCP poleward of 238N. Sea ice loss–induced zonal
wind deceleration occurs mostly in northern Eurasia andthe North Atlantic over the latitude bands of 508–708N.
The overall pattern in DICE is similar to other studies(Deser et al. 2016; Oudar et al. 2017; McCusker et al.
2017). By contrast, the NH zonal wind response in
DRCP exhibits two well-defined meridional dipoles,
indicating poleward shift of the jets in the Atlantic andPacific, respectively. Figure 7c shows the time series of508–608N averaged zonal-mean zonal wind responses in
DICE and DRCP. Even for the five-member ensemble
mean, sea ice loss–induced zonal wind deceleration is
obscured by internal variability especially in the earlier
period. Likewise, the circulation change due to anthropogenic forcing strengthens relative to internal variability over the twenty-first century, and the sign is
opposite to the sea ice loss effect (Fig. 7c; black curve).
The 500-hPa geopotential height (Z500) and sea levelpressure (SLP) responses in DICE and DRCP during

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FIG. 7. (a) Monthly change of 700-hPa zonal-mean zonal wind response in DICE averaged over 2051–90. Contours denote the climatology with the interval of 2 m s21 and zero wind line thickened. (b) Winter (DJF) 700-hPa
zonal wind responses in (left) DICE and (right) DRCP. Contours denote the climatology with the interval of 5 m s21.
Stippling denotes the 95% statistical significance based on a two-sided Student’s t test. The shading rings indicate
the 508–608N latitude band. (c) Time evolution of winter 508–608N averaged 700-hPa zonal-mean zonal wind responses in DICE (blue curve) and DRCP (black curve).

1991–2020, 2021–50, and 2051–90 are shown in Fig. 8.
During 1991–2020, Z500 changes in DICE are mostly
less than 10 m and statistically insignificant. During
2021–50 and 2051–90, geopotential height increases overthe polar cap in association with the lower-troposphericwarming in the Arctic, with magnitudes of around 25
and 50 m, respectively. It is distinct from that in DRCP,
where the height increases everywhere but with smaller

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FIG. 8. (a) Winter (DJF) 500-hPa geopotential height (m) responses in DICE and DRCP for 1991–2020, 2021–50,
and 2051–90. (b) As in (a), but for the sea level pressure (hPa) responses. Stippling denotes the 95% statisticalsignificance based on a two-sided Student’s t test.

changes over the North Atlantic and North Pacific andgreater changes over portions of Eurasia midlatitudes.
The magnitude of the Z500 response in DRCP is always
larger than in DICE even in the Arctic.

The SLP response in DICE during 1991–2020 is weak
and there are negative values in the Sea of Okhotsk andHudson Bay as a result of sea ice loss–induced nearsurface warming (Deser et al. 2004). During 2021–50 and1 OCTOBER 2018

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2051–90, sea level pressure change exhibits a well-definedzonal wave-1 pattern with positive values in the Eurasiancontinent (strengthening of the Siberian high) and negative values in Canada and the North Pacific. This feature
has been found to be very robust in both coupled (Deseret al. 2016; Blackport and Kushner 2017; Oudar et al. 2017;
McCusker et al. 2017) and uncoupled modeling studies(e.g., Sun et al. 2015; Deser et al. 2016; Semmler et al.
2016). The Aleutian low strengthens in response to Arctic
sea ice loss but does not extend as far south in DICE as inother coupled model sea ice experiments (Deser et al.
2016; Oudar et al. 2017; McCusker et al. 2017). By contrast, during 2021–50 and 2051–90, sea level pressure in
DRCP is negative over the Arctic and positive over lower
latitudes, very different from the sea ice loss effect.

e. NH extratropical surface climate response
Figure 9 shows the winter near-surface air temperature and precipitation responses in DICE and DRCP
during 1991–2020, 2021–50, and 2051–90. In response tocontinued Arctic sea ice loss, there is increased warming
over high-latitude continents surrounding the ice loss
region (i.e., Alaska, northern Canada, Greenland, andnortheastern Siberia), and the warming gradually extends to lower latitudes especially in North America.
This warming is likely driven by horizontal diffusion(advection by climatological submonthly transient
eddies; Deser et al. 2010). There is generally lack ofwarming in the central/eastern Asia and weak coolingappears in Mongolia (below the smallest interval andstatistically insignificant), likely due to cold air advection induced by the enhanced Siberian high (Fig. 8). The
overall pattern is robust across models (Screen et al.
2015a; Sun et al. 2015; Deser et al. 2016; Semmler et al.
2016; Blackport and Kushner 2017; Oudar et al. 2017;
McCusker et al. 2017) except that the magnitudes varydepending on the interplay between thermodynamic
and dynamic effects. The temperature in DRCP always
shows warming with polar amplification.
In response to continued sea ice loss the Arctic precipitation increases likely due to enhanced evaporationfrom the underlying ocean (Fig. S8). The reduction inprecipitation over the NAWH is likely related to thenegative SSTs and thus less evaporation into the overlying atmosphere (Alexander et al. 2004). In North Pacific and west coast of North America, part of the
precipitation increase during 2051–90 may be driven by
the deepening Aleutian low (Fig. 8), as also shown inother models (Deser et al. 2016; Hay et al. 2018). The
precipitation patterns in DRCP and DICE are similar
over the Arctic and the NAWH. However, the midlatitude signal in DRCP is much larger and statisticallysignificant especially during 2051–90.

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Figure 10a shows DICE/DRCP (in percent) for winternear-surface air temperature response during 2051–90.
Over NH high-latitude continents, sea ice loss can explain up to ;80% of the projected temperature increase,
while its contribution is generally less than 10% in thesubtropics. Similar to Screen et al. (2015b), we select two
high-latitude and two midlatitude regions and present
the seasonal sea ice loss contributions to the projected
near-surface temperature change (Fig. 10b). These four
regions are high-latitude North America (508–858N, 108–
1688W), high-latitude Eurasia (508–858N and 108W–08,
08–1808, and 1808–1688W), western United States (WUS;
308–508N, 1028–1208W), and eastern United States(EUS; 308–508N; 608–1028W), respectively. In all four
regions the sea ice loss contribution is largest during
winter and smallest during summer, consistent with thesurface energy flux response (Fig. 2a). Over highlatitudes, a larger winter sea ice contribution occurs inNorth America (;55%) than in Eurasia (30%). In theeastern United States, the winter sea ice loss contribution reaches more than 30%, significantly larger thanover the western United States. This is likely because
Hudson Bay resides at a relatively low latitude (thesouth edge is at ;508N). Therefore, the local warming
associated with the sea ice loss can more effectively
warm the land farther south, especially during cold days
when the winds are blowing from the north (Screen2014). The role of the Arctic sea ice loss in causing
eastern North American warming and reducing cold
extremes can be seen in other studies (e.g., Screen et al.
2015a; Sun et al. 2015; Blackport and Kushner 2017;
Deser et al. 2016; Sun et al. 2016; McCusker et al. 2017).
The evolution of the fraction DICE/DRCP is shown in
Fig. 10c, with temporal smoothing to reduce the influenceof internal variability. While all of the NH extratropicalregions warm in both DICE and DRCP, the sea ice contribution to the warming remains nearly constant over time
except in the high-latitude North America where thefraction increases by ;10% during 2010–70 (and likely
related to the ice loss mismatch between DICE and DRCP).

f. Tropical climate response
Arctic sea ice loss can drive tropical SST and precipitation changes remotely through several processes
including a decline in AMOC (Zhang and Delworth 2005)
and atmosphere–ocean thermodynamical coupling(e.g., Chiang and Bitz 2005), or both (Tomas et al.
2016). Figure 11 shows annual SST and precipitation
responses in DICE and DRCP during 2051–90 (notethat difference color scales have been used because
the SST response in DICE is much smaller than in
DRCP). Although DICE only accounts for ;10% of the
SST responses in DRCP when zonally averaged, the7836

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FIG. 9. As in Fig. 8, but for (a) near-surface air temperature (8C) and (b) precipitation (mm day21) responses in
DICE and DRCP for 1991–2020, 2021–50, and 2051–90. Stippling denotes the 95% statistical significance based ona two-sided Student’s t test.

features are similar, with a pattern correlation of 0.76 in
the tropics. For example, SST responses in DICE and
DRCP both exhibit enhanced warming along the equator in the central and eastern Pacific.

In response to Arctic sea ice loss, the tropical Pacificprecipitation increases on the equatorward side of theclimatological ITCZ in both hemispheres. In the tropicalAtlantic, the ITCZ strengthens, while in the Indian1 OCTOBER 2018

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FIG. 10. (a) Fraction (%) of DICE/DRCP for winter near-surface air temperature response
in 2051–90. Green boxes denote various high-latitude and midlatitude continents, including
high-latitude North America, high-latitude Eurasia, western United States (WUS), andeastern United States (EUS). (b) As in (a), but averaged over four individual continents in
JJA (gray bars), SON (light blue bars), DJF (green bars), and MAM (red bars). (c) As in (b),but for the time evolution of winter temperature response fractions. To remove the internalvariability, 40-yr running mean is first performed before calculating the fraction.

Ocean precipitation increases on the north side of theequator, indicating a northward shift of the ITCZ. Thesefeatures in DICE are largely similar to DRCP (Fig. 11b),
despite the fact that it only accounts for ;16% of thetotal anthropogenic change over 158S–158N.
Figure 12 shows the evolution of the zonal-mean annual tropical SST and precipitation responses in DICE
and DRCP, after applying a 30-yr running mean to reduce the influence of internal variability. The tropicalresponse to transient Arctic sea ice loss is characterized
by SST warming from ;0.028C around 2020 to ;0.38C
by 2070. Associated with the SST change, precipitation
increases at 58S–108N with the peak at ;7oN, ranging
from ;0.015 mm day21 in 2010 to ;0.24 mm day21 in
2070. Precipitation initially decreases in the latitude
bands of 108–208N and 58–208S, but the NH drying zone
gradually decreases and disappears by ;2070. The
evolutions of SST and precipitation responses in DRCP
are similar to sea ice loss effect, but the magnitude ismuch larger. In DRCP, precipitation increases over 58S–
208N peaking at ;78N, but extending farther northward

than in DICE. Similar to DICE, there is also a drying
zone south of 58S in DRCP. Moreover, when averaged
over the tropics, the sea ice loss contribution to thetotal anthropogenic climate change appears to gradually increase with time for both SST and precipitation(Fig. S9), suggesting that the tropical response takes moretime to emerge than high-latitude response.
Figure 13 presents the zonal-mean annual temperature and zonal-wind responses as a function of pressure
and latitude in DICE and DRCP during 2051–90. In response to the sea ice loss, strong near-surface warming
occurs in the Arctic, accounting for most of the projected RCP change (also see Fig. 3a). A weak warmingof ;0.78C can also be observed in the tropical upper
troposphere, in association with enhanced equatorialconvection and latent heat release. While DICE only
explains ;8% of the tropical tropospheric temperature
signal in DRCP, it is statistically significant and robust
across all five members (not shown). This so-called‘‘mini-global warming’’ (Deser et al. 2015) has been foundto be robust among different coupled ocean–atmosphere

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FIG. 11. (a): Annual tropical SST (8C) response in DICE and DRCP averaged over 2051–90.
(b) As in (a), but for precipitation (mm day21) response, overlaid by its climatology. Stippling
denotes the 95% statistical significance based on a two-sided Student’s t test.

modeling studies (Screen et al. 2018). The zonal windresponse to Arctic sea ice loss is largely consistent withthe temperature response via the thermal wind relationship. The westerly winds weaken over NH high latitudes centered at 608N, in contrast to the meridional
dipole in DRCP, as already shown at 700 hPa (Fig. 7b).
The westerly winds are strengthened in the subtropicalupper troposphere and lower stratosphere in both hemispheres, in response to the tropical upper-troposphericwarming.

4. Summary and discussion
a. Summary
In this study, we use GFDL’s coupled ocean–
atmosphere model CM3 to evaluate the role of transient Arctic sea ice loss in the projected GHG-induced
global climate change from the late twentieth century to

the late twenty-first century. Our key findings are summarized as follows.
1) Within the Arctic, sea ice loss is the primary driver ofclimate change, especially for sea surface temperature and near-surface air temperature. The sea ice
contribution to total climate change is very similarfor 2011–50 and 2050–90. The increase in total precipitation is closely related to sea ice depletion in
winter but not in summer.
2) Arctic sea ice loss is one crucial factor for AMOC
weakening and the formation of the ‘‘North Atlantic
warming hole.’’ Roughly half of the projected
AMOC decline in twenty-first century due to anthropogenic forcing can be attributed to the loss of
sea ice, and its contribution is even larger for thepresent day and the near future, although part of therapid change may come from natural variability.
Associated with the AMOC change, the North

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FIG. 12. (top) Annual tropical zonal-mean SST (8C) response as a function of time and latitude in (left) DICE and(right) DRCP. (bottom) As in (top), but for annual tropical zonal-mean precipitation (mm day21) response. To
remove internal variability, SST and precipitation responses have been smoothed by 30-yr running mean. Note thatthe color scales are different between DICE and DRCP.

Atlantic warming hole appears with respect to theclimatology. The cooling is stronger in winter thanin summer. Moreover, the freshening of the North
Atlantic subpolar gyre caused by sea ice loss can
explain most of the projected salinity change, especially prior to 2050. Sea ice loss–induced surface
salinity also increases in North Atlantic subtropicalgyre, albeit with a smaller contribution than in the
subpolar gyre.
3) In contrast to the AMOC adjustment, the NH
atmospheric circulation response to present-day
Arctic sea ice loss is small relative to internalvariability. There is little signal in wind, sea levelpressure, and geopotential height prior to 2020 even

FIG. 13. (top) Annual zonal-mean temperature (8C) response in (left) DICE and (right) DRCP averaged over
2051–90, overlaid by the climatology (contours). The contour interval is 108C. (bottom) As in (top), but for zonalmean zonal wind (m s21) response. Contour interval is 5 m s21. Stippling denotes the 95% statistical significancebased on a two-sided Student’s t test.

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though the simulated sea ice reduction is slightly
larger than in observations. The sea ice loss effect on
the atmospheric circulation is distinct from the
projected anthropogenic change, suggesting thatthe circulation change initiated from the Arctic issmall relative to changes in other parts of the climate
system (e.g., tropical SSTs) due to an increase ingreenhouse gases.
4) Arctic sea ice loss warms the NH extratropicalcontinents over the course of the twenty-first century. It is an important contributor to greenhousegas–induced increases in surface air temperature not
only at high latitudes, but also over the eastern
United States. While temperatures continue to increase over the NH continents due to anthropogenic
forcing, the sea ice contribution remains nearly
constant with time.
5) Arctic sea ice loss can remotely influence the tropical
SST and precipitation, causing an equatorward displacement of the Pacific ITCZ. This effect is small
but robust, and is similar to the RCP change.
Associated with the precipitation increase in the
deep tropics, there is a ‘‘mini-global warming’’ response to continued Arctic sea ice loss.
The response at the end of the twenty-first century in
our transient sea ice loss experiments is in generalagreement with the equilibrium responses to an abrupt
loss of late-twenty-first-century Arctic sea ice (e.g.,
Deser et al. 2015, 2016; Blackport and Kushner 2016,2017; Oudar et al. 2017; McCusker et al. 2017). Thisimplies that these equilibrium responses provide a reasonable representation of end-of-century impacts of sea
ice loss. Moreover, our experimental design provides
additional information on the climatic impacts of atransitioning sea ice cover. We find that for many fields,
the response increases approximately linearly with timeover the course of the twenty-first century. A notable exception is the AMOC response, which exhibits
nonlinear behavior for reasons that remain to beunderstood.

b. Discussion
The results presented above highlight a numbers of
issues. The first issue concerns the evolution of the
AMOC response. In our experiments, we found that
Arctic sea ice loss induces significant weakening of
AMOC over the first two decades of the experiment,
consistent with other recent studies (Blackport andKushner 2016; Tomas et al. 2016; Oudar et al. 2017;
Sévellec et al. 2017). Thus, the recent loss of sea ice may
have already affected the ocean circulation. This is incontrast to the sea ice loss–induced atmospheric circulation

VOLUME 31

response, which still exhibits low detectability due tohigh internal variability (e.g., Screen et al. 2014; Smithet al. 2017). The processes responsible for the AMOC
response, in particular the role of surface heat versus
freshwater flux in causing AMOC to weaken, need further investigation.
While the AMOC slowdown is a common feature ofvarious sea ice experiments with fully coupled ocean–
atmosphere models, the changes of AMOC time series
and the contribution of sea ice loss differ across models.
For example, in Blackport and Kushner (2016) AMOC
declines in the first several decades but then recovers
over the following ;400 years, whereas in Deser et al.
(2015) and Oudar et al. (2017) AMOC is in quasiequilibrium after its initial slowdown without a clear
indication of recovery. The contribution of sea ice loss to
AMOC decline in full climate change simulations isfound also to differ; for example, the decline is ;30% inTomas et al. (2016), 75% in Sévellec et al. (2017), andmore than 100% in Oudar et al. (2017). Differences canarise due to many factors, such as the methodology usedin the sea ice experiments, abrupt versus transient sea
ice loss, and the magnitude of the sea ice change.
Moreover, the percentage of sea ice contribution varies
when looking at the early versus the late twenty-first
century; in our study, it is found to be much larger in theearlier period, which highlights the unique value of thetransient sea ice experiments.
The second issue concerns the atmospheric response
to Arctic sea ice loss over time. While the atmosphericcirculation response to late-twenty-first-century Arctic
sea ice loss has been found to be robust across models(Screen et al. 2018), the response to present-day sea ice
loss differs between modeling studies (e.g., Mori et al.
2014; Kim et al. 2014; Perlwitz et al. 2015; McCusker
et al. 2016; Sun et al. 2016). The transient experiments
performed here may help to explain this transition.
During 2051–90, the sea ice loss effect is qualitatively inagreement with previous studies (Deser et al. 2015;
Blackport and Kushner 2016, 2017; Oudar et al. 2017;
McCusker et al. 2017; Hay et al. 2018). During 1991–
2020, however, the atmospheric circulation response to
sea ice loss is very weak and statistically insignificant(Figs. 7 and 8), even though the sea ice reduction in CM3
is slightly larger than in observations (Fig. 1b). Thus, avery large number of samples are probably needed inorder to evaluate the effects of Arctic sea ice loss and it
might not be possible to disentangle the impact of sea ice
loss from other effects based on a short period of observations (Smith et al. 2017). In addition, the surface airtemperature response in our experiments is in agreement with other coupled and uncoupled model studies(Screen et al. 2015a; Sun et al. 2015; Deser et al. 2016;

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Semmler et al. 2016; Blackport and Kushner 2017;
Oudar et al. 2017; McCusker et al. 2017, Hay et al. 2018),
suggesting that sea ice loss makes a substantial contribution to warming in the eastern United States, rather
than cooling due to changes in atmospheric dynamics(e.g., Francis et al. 2017).
A related issue is that while the future sea ice loss
effect is generally found to be robust across models, theatmospheric circulation response to total anthropogenic
forcing is more model dependent. For example, somemodels exhibit a meridional dipole with zonal windstrengthening at the latitude band of 208–408N andweakening centered around 608N (Oudar et al. 2017;
McCusker et al. 2017), while others do not show a clear
zonal-mean jet change (Deser et al. 2015; Blackport andKushner 2017), both different from the poleward jet
shift found in our ice loss experiments. The diversity ofclimate change responses among models might reflect
different balances in the ‘‘tug of war’’ between tropicalwarming and Arctic warming (e.g., Barnes and Polvani
2015; Deser et al. 2015; Blackport and Kushner 2017;
McCusker et al. 2017; Oudar et al. 2017) or differencesin the circulation response to tropical forcing (Hayet al. 2018).
The last issue concerns the processes by which Arctic
sea ice influences the Pacific ITCZ, or more broadly,
how the high-latitude forcing impacts the tropical SST
and precipitation. Our results are largely in agreementwith those of Deser et al. (2015), who used CCSM4,
which includes a dynamical ocean model, and differsfrom studies using slab ocean models (e.g., Chiang andBitz 2005; Broccoli et al. 2006; Kang et al. 2008; Frierson
and Hwang 2012; Cvijanovic et al. 2017) or a fully coupled model but with constraining temperature and salinity below 200 m (Smith et al. 2017). Although we havenot examined the global energy balance in our experiments, we speculate that poleward oceanic heat transport is the key to understanding the difference between
our results and those of previous slab-ocean coupledmodeling studies, consistent with the findings of Tomas
et al. (2016). In particular, without ocean dynamics,
Arctic sea ice loss results in a reduction of atmospheric northward heat transport (NHT) across theequator and thus shifts the ITCZ northward; withocean dynamics, both oceanic and atmospheric NHT
diminish in response to Arctic sea ice loss (Deseret al. 2015; Tomas et al. 2016). As suggested by Cabréet al. (2017), the tropical ITCZ response to highlatitude forcing might depend on the partitioning
between atmospheric and oceanic components of thecross-equator energy transport. We note that thetropical upper-tropospheric warming associated with
future sea ice loss has also been found in other fully

coupled experiments (Screen et al. 2018), suggestingthat the so-called mini-global warming is a common
feature among models in response to Arctic sea iceloss.
To what extent our results are model dependent remains to be ascertained. The upcoming CMIP6 Polar
Amplification Model Intercomparison Project (PAMIP)
should be helpful in this regard, as all models will follow
the same experimental protocol (Smith et al. 2018). In
future work, we plan to investigate the mechanisms
underlying the nonlinear AMOC response to transient
Arctic sea ice loss, as well as the subseasonal atmospheric response including storm-track metrics andclimate extremes.
Acknowledgments. We thank Tom Knutson, Rong
Zhang, Michael Winton, and Fanrong Zeng at GFDL
for help in setting up the model experiments and valuable
discussions, and Martin Hoerling and Judith Perlwitz
at ESRL/PSD for their constructive suggestions. We
also thank the three anonymous reviewers and Editor
John Chiang for their helpful and constructive comments. This project was supported by the NOAA
Climate Program Office Earth System Modeling program. NCAR is sponsored by the National Science
Foundation.

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