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The Seasonal Atmospheric Response to Projected Arctic Sea Ice Loss in the
Late Twenty-First Century
CLARA DESER AND ROBERT TOMASNational Center for Atmospheric Research,* Boulder, Colorado

MICHAEL ALEXANDERNOAA/Earth System Research Laboratory, Boulder, Colorado

DAVID LAWRENCE
National Center for Atmospheric Research,* Boulder, Colorado(Manuscript received 26 January 2009, in final form 9 July 2009)
ABSTRACTThe authors investigate the atmospheric response to projected Arctic sea ice loss at the end of the twentyfirst century using an atmospheric general circulation model (GCM) coupled to a land surface model. The
response was obtained from two 60-yr integrations: one with a repeating seasonal cycle of specified sea ice
conditions for the late twentieth century (1980–99) and one with that of sea ice conditions for the late twentyfirst century (2080–99). In both integrations, a repeating seasonal cycle of SSTs for 1980–99 was prescribed toisolate the impact of projected future sea ice loss. Note that greenhouse gas concentrations remained fixed at
1980–99 levels in both sets of experiments. The twentieth- and twenty-first-century sea ice (and SST) conditions were obtained from ensemble mean integrations of a coupled GCM under historical forcing andSpecial Report on Emissions Scenarios (SRES) A1B scenario forcing, respectively.
The loss of Arctic sea ice is greatest in summer and fall, yet the response of the net surface energy budget
over the Arctic Ocean is largest in winter. Air temperature and precipitation responses also maximize in
winter, both over the Arctic Ocean and over the adjacent high-latitude continents. Snow depths increase over
Siberia and northern Canada because of the enhanced winter precipitation. Atmospheric warming over thehigh-latitude continents is mainly confined to the boundary layer (below ;850 hPa) and to regions witha strong low-level temperature inversion. Enhanced warm air advection by submonthly transient motions
is the primary mechanism for the terrestrial warming. A significant large-scale atmospheric circulation response is found during winter, with a baroclinic (equivalent barotropic) vertical structure over the Arctic in
November–December (January–March). This response resembles the negative phase of the North Atlantic
Oscillation in February only. Comparison with the fully coupled model reveals that Arctic sea ice loss accounts for most of the seasonal, spatial, and vertical structure of the high-latitude warming response to
greenhouse gas forcing at the end of the twenty-first century.

1. Introduction
Arctic sea ice extent has declined over the past several decades, with the largest rate of retreat (;210%* The National Center for Atmospheric Research is sponsoredby the National Science Foundation.

Corresponding author address: Dr. Clara Deser, Climate andGlobal Dynamics Division, NCAR, P.O. Box 3000, Boulder CO
80307.
E-mail: cdeser@ucar.edu
DOI: 10.1175/2009JCLI3053.1
Ó 2010 American Meteorological Society

decade21) in late summer (Serreze et al. 2007; Comiso
et al. 2008; Deser and Teng 2008; among others). The
rate of decline has accelerated substantially in the past
decade and now outpaces that simulated by most climate models in response to increasing greenhouse gas(GHG) concentrations (Stroeve et al. 2007). The record
losses of perennial Arctic sea ice in both 2007 and 2008highlight the ongoing trajectory toward ice-free summers, a state that climate models project may be realized
within 15–50 yr (Holland et al. 2006).
A seasonally ice-free Arctic Ocean is expected tohave widespread socioeconomic, ecological, and climatic

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consequences. For example, commercial shipping routes
and energy resource development in the Arctic are likely
to change, impacting native populations and habitat.
Warming associated with Arctic sea ice loss may hasten permafrost degradation (Lawrence et al. 2008) andlead to trophic mismatch (Post and Forchhammer 2008).
Atmospheric circulation patterns and accompanying
precipitation and storm-track distributions over midand high latitudes may also be affected (Sewall 2005;
Singarayer et al. 2006; Gerdes 2006; Seierstad and Bader2009).
Identification of the climatic impacts of a seasonallyice-free Arctic Ocean from observational data alone isdifficult because of a variety of factors, including 1) thatthe loss of perennial Arctic sea ice is not yet complete, 2)
the confounding presence of climate variability due tointernal atmospheric processes and/or forced by factors
other than Arctic sea ice loss, and 3) that observational
data contain a mixture of forcing and response. To circumvent these difficulties, we use an atmospheric modeling approach to address the atmospheric response toprojected future Arctic sea ice loss. The model results
may be useful for informing observational attribution
studies of the climatic effects of Arctic sea ice retreat.
For example, is the enhanced Arctic warming in autumn
over the past few years an early signal of the emerging
climate response to Arctic sea ice loss as proposed bySerreze et al. (2008)?
Many studies have used atmospheric general circulation models to investigate the effects of prescribedchanges in Arctic sea ice cover upon the atmosphere.
The specified sea ice extent or concentration conditions
range from realistic values for winter (Alexander et al.
2004; Singarayer et al. 2006) and summer (Bhatt et al.
2008) to more idealized configurations (realistic spatial
patterns with exaggerated amplitudes) within the Atlantic (Magnusdottir et al. 2004; Deser et al. 2004;
Kvamstø et al. 2004) and Pacific (Honda et al. 1999)
sectors in winter. Focusing on dynamical aspects, thesestudies reported a range of atmospheric circulation responses depending on the location and polarity of the sea
ice changes as well as time of year. For the Atlantic sea
ice cases, the winter circulation response was found toresemble the North Atlantic Oscillation (NAO; Hurrell1995) or northern annular mode (NAM; Wallace 2000),
the leading structure of internal atmospheric variability
over the extratropical Northern Hemisphere. For the
Pacific sea ice case, the winter circulation response
consisted of a stationary Rossby wave train downstreamof the Sea of Okhotsk and extending across the Pacificinto North America. The summer circulation response
to sea ice changes within the Arctic Ocean displayeda significant remote effect over the North Pacific.

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In addition to present-day sea ice conditions, projected future changes in Arctic sea ice concentrations at
the end of the twenty-first century have been prescribedas boundary conditions to atmospheric general circulation models. Singarayer et al. (2006) employed idealized
scenarios of future Arctic sea ice loss, while Seierstad
and Bader (2009) used Arctic sea ice loss projections
taken from coupled model simulations driven by increasing GHG concentrations. The former study focusedupon the wintertime (December–February average) responses in circulation, precipitation, and surface air temperature, while the latter was concerned mainly with thecirculation response, contrasting December–February
and March. Singarayer et al. (2006) reported reductions in sea level pressure over the Arctic, northeastern
Canada, and the Bering Sea, accompanied by local increases in precipitation and air temperature. Seierstad
and Bader (2009) showed a positive 500-hPa geopotential height response over the Atlantic sector of the
Arctic in December–February and an amplified circulation response in March that resembles the negative
polarity of the NAO/NAM. Because of a lack of information on the vertical structure of the circulation responses in the two studies, it is difficult to make a directcomparison between them.
The present study aims to provide a more comprehensive assessment of the atmospheric response toprojected Arctic sea ice loss at the end of the twenty-first
century than earlier studies, including aspects not previously addressed in detail such as seasonal dependence
and vertical structure. For example, we document thefull seasonal cycle of the three-dimensional circulation
response to future Arctic sea ice loss. Another focus of
our study is the terrestrial climate response to future
Arctic sea ice loss, including effects on air temperature,
precipitation, and snow depth. We also investigate therole of atmospheric boundary layer stability in determining the geographical distribution and verticalstructure of the terrestrial climate response. In addition
to terrestrial impacts, the seasonal cycle of the responseof the Arctic Ocean surface energy balance is investigated. Finally, we compare the atmospheric response to future Arctic sea ice loss with the atmospheric
response to GHG forcing in a fully coupled climate
model in order to assess the relative role of Arctic sea ice
loss in future climate change. Early results on the terrestrial air temperature response were presented in
Lawrence et al. (2008).
We note that our atmospheric modeling approachis designed to isolate the direct impact of future sea ice
loss upon the atmosphere without accounting for feedbacks from the oceans or other components of the climate system. As such, it may be used as a baseline for15 JANUARY 2010

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evaluating the impact of Arctic sea ice loss upon theatmosphere.
The paper is organized as follows. The model andexperimental design are described in section 2. Results
are presented in section 3. Summary and discussion are
given in sections 4 and 5, respectively.

2. Model experiments
To address the impacts of projected future changes in
Arctic sea ice cover upon the global atmospheric circulation and climate, we have conducted two experimentswith the National Center for Atmospheric Research(NCAR) Community Atmospheric Model Version 3(CAM3), an atmospheric general circulation model witha horizontal resolution of ;1.48 latitude and 1.48 longitude (85-wave triangular spectral truncation; T85) and26 vertical levels, coupled to the Community Land
Model (CLM). CAM3 is the atmospheric component of
one of the principal climate models used in the Fourth
Assessment Report (AR4) of the Intergovernmental
Panel on Climate Change (Solomon et al. 2007). The
physical and numerical methods used in CAM3 are
documented in Collins et al. (2006a) and references
therein. The most important differences from the previous version of the NCAR atmospheric model are associated with changes to the parameterized physics
package, notably the representation of cloud and precipitation processes (Boville et al. 2006) and the treatment of aerosols and radiative processes (Collins et al.
2006b).
The CAM3 ‘‘control’’ experiment consists of a 60-yr
integration with a specified repeating seasonal cycle of
SSTs and sea ice (concentration and thickness) for theperiod 1980–99, obtained from the 7-member ensemble
mean of twentieth-century Community Climate System
Model, version 3 (CCSM3) simulations at T85 resolution. CCSM3 is a fully coupled climate model comprisedof CAM3, CLM, the Parallel Ocean Program model,
and the Community Sea Ice Model version 4. The
CCSM3 twentieth-century simulations are forced withobserved estimates of time-varying atmospheric chemical composition (greenhouse gases, tropospheric andstratospheric ozone, and sulfate and volcanic aerosols)and solar output as described in Meehl et al. (2006), andare conducted without flux adjustments.
The CAM3 ‘‘perturbation’’ experiment consists of a
60-yr integration with a repeating seasonal cycle of Arctic sea ice (concentration and thickness) for the period
2080–99, taken from the 8-member ensemble mean oftwenty-first-century CCSM3 simulations at T85 resolution under the Special Report on Emissions Scenarios(SRES) A1B greenhouse gas forcing scenario. For the335

CAM3 experiments with prescribed sea ice conditions
for the late twenty-first century, SSTs are set to those in
the control experiment so as to isolate the impact of thesea ice changes. At grid boxes where fractional sea ice
cover in the late twentieth century is replaced by open
water in the late twenty-first century, SSTs are set to thefreezing point of seawater (;21.88C). A two-sided
Student’s t test is used to evaluate the statistical significance of the atmospheric changes between the 60-yr
averages of the control and perturbation experiments.
Our experimental design is similar to the studies ofSingarayer et al. (2006) and Seierstad and Bader (2009)
except 1) we do not include any changes in SSTs, 2) we
include changes in sea ice thickness (in addition toconcentration), 3) our ensemble size is considerablylarger, and 4) the horizontal resolution of our atmospheric GCM is approximately double.
As with all climate model experiments, model biases
must be kept in mind when evaluating the results.
CAM3 has been extensively compared against observations (see the special issue of the Journal of Climate,
2006, Vol. 19, No. 11). In particular, the dynamical andhydrological aspects have been evaluated in Hurrell
et al. (2006) and Hack et al. (2006). These studies showthat the model reproduces well the main features of theseasonal cycle of the extratropical atmospheric circulation, although the simulated sea level pressures are toohigh over midlatitudes and too low over high latitudes.
In particular, the Icelandic low is too deep and extends
too far over Eurasia and the Arctic Basin comparedto observations. In addition, CAM3 overestimates theamount of low stratus clouds and precipitation over theArctic Ocean in winter, a common bias among currentgeneration climate models (Vavrus and Waliser 2008).
The strength of the mean low-level temperature inversion in winter over the Arctic and adjacent high-latitudecontinents is also overestimated in CAM3 as in manyother models (Boé et al. 2009).

3. Resultsa. Arctic sea ice concentration and thickness
The prescribed sea ice concentration (SIC) and sea
ice thickness (SIT) distributions for the late-twentiethcentury (1980–99) and late-twenty-first-century (2080–
99) CAM3 experiments, taken from CCSM3, are shownin Fig. 1 as bimonthly averages (January–February,
March–April, May–June, July–August, September–
October, and November–December). The most dramatic loss of Arctic sea ice between the late twentiethand twenty-first centuries occurs during summer, witha nearly ice-free Arctic Ocean projected during August–October. Although largest in summer, the loss of sea ice

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FIG. 1. Bimonthly distributions of Arctic (a) sea ice concentration (%) and (b) sea ice thickness (m) during 1980–99 and
2080–99 from CCSM3.

occurs year-round as the ice edge retreats from the peripheral Arctic seas. The areal reduction in Arctic
sea ice is accompanied by a thinning of the ice pack. SIT
in the central Arctic Ocean decreases from 3–4 m to
0.5–1 m in winter and from 2.5–3.5 m to ,0.5 m insummer. The late-twentieth-century SIC and SIT distributions are generally realistic compared to the available observations (Holland et al. 2006).
The bimonthly changes in SIT and SIC between thelate twentieth and twenty-first centuries are shown in the
top two rows of Fig. 2. The magnitude and pattern of sea

ice thinning is relatively uniform throughout the year,with maximum values ;2.5–3.5 m in the central Arctic
Ocean. In contrast, the reductions in SIC are seasonallydependent, with the largest decreases (;80%–90%)
within the central Arctic Ocean in summer (September–
October) and smaller decreases (;50%–60%) within
the marginal seas in winter.

b. Surface energy flux response
The changes in Arctic sea ice are communicated to theatmosphere via changes in the net surface energy fluxes.

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FIG. 2. Bimonthly Arctic (top row) sea ice thickness (DSIT; m) and (second row) concentration (DSIC; %) differences (2080–99 minus
1980–99) from CCSM3. Bimonthly (third row) turbulent energy flux (DSH 1 LH), (fourth row) longwave radiative flux (DLW), and(bottom row) shortwave radiative flux (DSW) responses to sea ice cover changes. Fluxes (W m22) are positive upward.

Figure 2 shows bimonthly differences between the latetwentieth and twenty-first centuries in the surface turbulent energy fluxes (sensible plus latent) and the longwave
and shortwave radiative fluxes. The turbulent energy
flux response is considerably greater than, and exhibits
a different seasonal dependence from, the radiative flux
response. The former is largest (maximum amplitudes;60–90 W m22) in winter whereas the latter is largest (maximum amplitudes ;10–20 W m22) in summer(shortwave) and late fall (longwave). The winter maximum of the turbulent energy flux response is due to thefact that this is the time of year when the air temperatures
are coolest relative to the underlying surface (ice or open
water).
The radiative flux responses (upward for longwave
and downward for shortwave) are localized to the SIC
changes, whereas the turbulent flux response exhibits
a dipole structure with upward anomalies over the SIC
losses and downward anomalies directly to the south(Fig. 2). The downward turbulent heat flux response
directly to the south of the SIC changes may be understood as a result of the retreat of the ice edge and the338

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FIG. 3. Seasonal cycle of the turbulent energy flux (W m22; DSH 1
LH; thin solid curve), longwave radiative flux (DLW; dotted curve),and shortwave radiative flux (DSW; dashed curve) responses area
averaged over the Arctic Ocean. The net surface energy flux response is given by the thick solid curve, and the SIC changes (%) areindicated by the gray bars (note the inverted scale). Fluxes are
positive upward.

accompanying region of maximum turbulent energy flux
loss from the ocean to the atmosphere (Deser et al. 2000;
Magnusdottir et al. 2004; Alexander et al. 2004). Although the magnitude of the downward turbulent heat
flux response directly to the south of the SIC changes isoverestimated in CAM3 because of the lack of an interactive ocean, the dipole-like structure remains evident even in the fully coupled CCSM3 model (notshown) and in observations (Deser et al. 2000).
A more detailed view of the seasonal cycle of the SIC
changes and the surface energy flux response over theArctic Ocean is given in Fig. 3. For each month, the data
were area averaged over all grid points for which SIC
during 1980–99 exceeds 50%. This criterion encompasses the full region of SIC losses while excluding mostof the negative turbulent energy flux response along theequatorward margins of the ice edge. Consistent with
Fig. 2, the largest SIC loss occurs in July–November(peaking in October), while the greatest net surface energy flux response occurs in October–February (peaking
in November). The delay in the surface energy flux response relative to the maximum SIC loss has important
implications for the timing of the atmospheric circulation and climate response.
Indeed, the seasonal cycles of the surface air temperature and precipitation responses over the Arctic
Ocean and over the high-latitude continents (658–808N)
are in phase with the seasonal cycle of the net surface
energy flux response, not SIC (Figs. 4a,b). (Note that inFigs. 4a,b the shortwave radiative component is omitted
from the net surface energy flux response in view of thefact that the enhanced downward shortwave radiation
resulting from the reduced albedo associated with an
ice-free Arctic Ocean does not warm the atmospheredirectly but instead warms the ocean, an effect that has
been suppressed in our experiments.) Over the Arctic

FIG. 4. Seasonal cycles of air temperature (8C; dotted curve) and
precipitation (mm day21; dashed curve) responses area averaged
over (a) the Arctic Ocean and (b) the high-latitude continents (658–808N; 608–3008E). The solid curve in both (a) and (b) shows the sumof the turbulent and longwave fluxes area averaged over the Arctic
Ocean (W m22). SIC changes are indicated by the gray bars (scale
as in Fig. 3, not shown).

Ocean, the maximum responses occur in November,with values of 178C, 0.4 mm day21, and 67 W m22 fortemperature, precipitation, and net surface energy flux,
respectively (Fig. 4a). Over land, the maximum temperature and precipitation responses occur in November–
December, with values of 78C and 0.16 mm day21,
respectively (Fig. 4b). The close agreement among theseasonal cycles of the temperature, precipitation, andnet surface energy flux responses indicate that the Arctic
Ocean net surface energy flux response to sea ice loss
exerts a strong local control on climate within the Arctic
Ocean (Fig. 4a) and even an important remote control
on climate over the adjacent continents (Fig. 4b).

c. Atmospheric temperature response
The bimonthly net surface energy flux (turbulent plus
longwave radiation) response and the terrestrial air
temperature, snow depth, and precipitation responses
are shown in Fig. 5. Air temperature responses thatexceed ;0.58C (first level of shading) and snow depth
responses that exceed ;0.75 cm liquid water equivalent
in absolute value (second level of shading) are statistically significant at the 5% confidence level based on a
two-sided Student’s t test. Precipitation responses significant at the 5% confidence level are outlined withthick black contours in the figure.

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FIG. 5. Bimonthly responses of net surface energy flux (DQnet; W m22), terrestrial air temperature (DAir T; 8C), terrestrial snow depth(DSnow; cm liquid water equivalent), and terrestrial precipitation (DPrecip; mm day21). Color scales are given at the bottom of the figure.
Thick black contours on the air temperature panels outline regions with a low-level temperature inversion (T850hPa 2 T1000hPa . 08C)
during 1980–99. Precipitation responses significant at the 5% confidence level are outlined with black contours.

Consistent with Fig. 4b, the seasonal cycle of the terrestrial air temperature response follows that of the net
surface energy flux response, with maximum warming in
winter (November–December and January–February)
and weaker warming in autumn (September–October)and spring (March–April). The terrestrial warming islargest in coastal regions adjacent to the Arctic Ocean,with the maximum temperature response over Siberia
and northern Canada and Alaska, and penetrates approximately 1500 km inland.
The terrestrial surface air temperature responses
in early (November–December) and mid-(January–
February) winter are largely confined to regions witha mean boundary layer temperature inversion in the latetwentieth century (marked by thick black contours on
the bimonthly air temperature responses in Fig. 5; notethat there is no inversion in the warm season May–Junethrough September–October). Indeed, the vertical structures of the December atmospheric temperature re-sponses over the Arctic Ocean and high-latitude (658–808N) continents are confined to below ;800 hPa, withthe warming amplifying toward the surface (maximum
values of 6.58C over land and 168C over the ocean; Fig. 6).
As a consequence of the vertical structure of the warming,
the static stability of the boundary layer decreases fromthe late twentieth century to the late twenty-first century.
Over the ocean, the 108C inversion between 1000 and
900 hPa in the late twentieth century is completely
eroded in the late twenty-first century. Over land, thecapping inversion, while not completely gone in thetwenty-first century, is only approximately 50% of thatin the twentieth century (Fig. 6).
The geographical distributions of the strength of the
December low-level inversion in the late twentieth andtwenty-first centuries are shown in Fig. 7. The marine
inversion, which exceeds 128C over the central Arctic
Ocean in the late twentieth century, disappears entirelyin the late twenty-first century. The terrestrial inversion

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FIG. 6. Vertical profiles of atmospheric temperature during 1980–99 (dashed curves) and
2080–99 (solid curves) over (left) the Arctic Ocean and (center) the high-latitude (658–808N)
continents in December. (right) The 2080–99 minus 1980–99 differences over the Arctic Ocean(thick curve) and high-latitude continents (thin curve).

weakens and retreats from far eastern Siberia and thenorth slope of Alaska in the late twenty-first century
compared to the late twentieth century. The inversion
strength over the Canadian Archipelago decreases from
;148C in the late twentieth century to ;68C in the latetwenty-first century.
The seasonal cycles of the strength of the boundary
layer temperature inversion over the Arctic Ocean andhigh-latitude continents during the late twentieth andtwenty-first centuries are shown in Fig. 8. As before, theArctic Ocean region is defined on a monthly basis as thearea with SIC .50% during 1980–99, and the terrestrial
region is defined as 658–808N, 608–3008E. In the latetwentieth century, the Arctic marine (terrestrial) inversion exists from October through April (November
through March), with maximum values ;98C in January.
The wintertime Arctic marine inversion almost disappears entirely in the late twenty-first century, with only
a weak vestige left in February–March (18–28C). The
wintertime terrestrial inversion also diminishes in strength

FIG. 7. Geographical distributions of the strength of the December low-level inversion(T850hPa 2 T1000hPa . 08C) during (left) 1980–99 and (right) 2080–99. Values ,1.58C notshown.

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FIG. 8. Seasonal cycles of T850hPa 2 T1000hPa during 1980–99(dark colors) and 2080–99 (light colors) over the (top) Arctic
Ocean (blue) and (middle) high-latitude continents (red). (bottom)
The 2080–99 minus 1980–99 differences for the Arctic Ocean(blue) and high-latitude continents (red).

(maximum values ;58C) in the late twenty-first century,
but not as dramatically as the marine inversion, and its
onset is delayed to December. The largest changes ininversion strength between the twentieth and twenty-first
centuries occur in November–December, with maximum
values of ;58C over land and ;158C over the Arctic
Ocean (Fig. 8, lower panel).

d. Terrestrial snow cover and precipitation responses
Despite the warming of the atmospheric boundary
layer, winter snow depth increases over Siberia, northern Canada, and the northern slope of Alaska (Fig. 5).

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At the end of winter (March–April), snow depth has
increased by ;1.5–3 cm liquid water equivalent over
Siberia and ;1.0–1.5 cm liquid water equivalent overnorthern Canada and Alaska. Smaller decreases in snow
depth occur to the south, primarily over western Russia
and the Canadian Rockies. The patterns of snow depthchange persist throughout the winter season, emerging
in November–December and reaching their maximum
amplitude in March–April.
Given the widespread terrestrial warming during thewinter season, the increases in snow depth must be a resultof enhanced precipitation. Indeed, precipitation increases
in early winter (November–December) over Siberia,
eastern Alaska, and northern Canada, and through midwinter (January–February) over Siberia (Fig. 5). Several
factors may contribute to the precipitation increases, including enhanced water vapor content in the terrestrial
boundary layer (due to increased moisture transport outof the Arctic by the submonthly transients; not shown),
destabilization of the terrestrial boundary layer due tosurface-intensified warming (recall Figs. 6–8), and enhanced low-level convergence associated with decreases
in sea level pressure (discussed in section 3f).
The role of precipitation in the snow depth response isfurther assessed by comparing the accumulated precipitation during the cold season (October–March) with
March snow depth (Fig. 9). The spatial patterns of thetwo fields are similar, with areas of positive (negative)
accumulated precipitation changes generally corresponding to regions of positive (negative) snow depthchanges. There is also quantitative agreement between
the magnitudes of the positive accumulated precipitation and snow depth responses. Note that the region of
positive accumulated precipitation values over western
Europe (excluding Scandinavia) does not correspond toincreased snow depth because the air temperature is
above 08C (thick gray curve in Fig. 9, right).
More detail on the seasonal timing of the precipitation, accumulated precipitation, and snow depth responses over Siberia and northern Canada is provided inFig. 10. The regions are defined using those grid boxes
for which the snow depth response in March exceeds
2.5 cm liquid water equivalent. Over northern Canada(Fig. 10a), positive precipitation anomalies occur from
October through February, with the largest increases in
November–December. The resulting accumulated precipitation response tracks the snow depth response, witha gradual increase throughout the winter to maximum
values in February. Similar results are found for Siberia,
although there the maximum precipitation response increases occur in December–January and the maximum
accumulated precipitation and snow depth responses
occur in March (Fig. 10b).

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FIG. 9. Accumulated cold season (October–March) precipitation and March snow depth
responses (cm). The thick black and gray contours on the snow panel denote the 2108 and 08C
air temperature isotherms, respectively, during 2080–99.

e. Heat budget
What processes account for the winter (October–
April) air temperature increases over the Arctic Ocean
and adjacent continents? We evaluated the terms in
the thermodynamic energy equation (e.g., Holton 2004)
using daily model output. The resulting area-averaged
heat budget response for the Arctic Ocean (defined as
the region with SIC .50% during 1980–99) is shown in
Fig. 11 (left panel). The near-surface warming (1000–
950 hPa) is primarily due to vertical diffusion (acting totransmit the upward sensible and latent surface heat flux
anomalies; green curve) while the warming in the upper
part of the boundary layer (900–850 hPa) is attributable
to condensational heating (dashed purple curve; Fig. 11,left). Horizontal temperature advection by both themonthly mean and submonthly transient circulation(dashed black and solid black curves) and longwave
radiation (solid purple curve) act to cool the boundary
layer (Fig. 11, left). Contributions to the heat budget byshortwave radiation and monthly mean temperaturetendency are negligible (not shown). The residual term(e.g., the sum of all the terms in the heat budget, including shortwave radiation and temperature tendency)
is small compared to the dominant terms in the balance(orange curve in Fig. 11, left).
A different balance of terms obtains for the adjacentcontinents (Fig. 11, right). The high-latitude (polewardof 658N) terrestrial boundary layer is warmed by meansof horizontal temperature advection by submonthlytransient atmospheric motions (primarily their meridi-

onal component), condensational heating (except at1000 hPa), and subgrid-scale horizontal and vertical diffusion. Of these, submonthly transient advection is thedominant mechanism for warming the lower portion of
the boundary layer (below 900 hPa; maximum value;0.808C day21) while condensational heating makes

FIG. 10. Seasonal cycles of precipitation (mm day21; dashedcurve), accumulated precipitation (cm; dotted curve), and snow
depth (cm liquid water equivalent; solid curve) responses for (a)northern Canada and (b) Siberia.

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FIG. 11. Heat budget response (8C day21) for the (left) Arctic Ocean and (right) high-latitude (658–808N) continents. Submonthly transient temperature advection (solid black curve); monthly mean temperature advection(dashed black curve); condensational heating (dashed purple curve); vertical and horizontal diffusion (green curve);
longwave radiation (solid purple curve). The time-tendency and shortwave radiation terms are negligible (notshown). The sum of all the terms (e.g., the heat budget residual) is given by the orange curve.

a substantial contribution in the upper portion of theboundary layer (but cools the surface). The other terms
in the heat budget act to cool the boundary layer: primarily horizontal temperature advection by the monthly
mean atmospheric circulation and longwave radiation(shortwave radiation and the monthly mean temperature tendency terms are near zero; not shown). There isalso a substantial residual in the heat budget that acts tocool the air at 950 and 1000 hPa; the origin of this residual is not known.
In summary, heat released from the Arctic Ocean
under reduced sea ice conditions (primarily via turbulent sensible and latent heat fluxes) is communicated to

the Arctic atmospheric boundary layer by vertical diffusion and to a lesser extent condensational heating.
The resulting temperature increase is mixed out over
the adjacent continents by submonthly transient atmospheric motions, causing a warming of the terrestrial
atmospheric boundary layer. A similar picture holds forthe moisture budget (not shown).

f. Atmospheric circulation response
Unlike the thermodynamic responses discussed above,the dynamical atmospheric response varies greatly frommonth to month (not shown). The bimonthly atmospheric circulation responses, depicted by geopotential

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FIG. 12. Bimonthly geopotential height responses at 1000 and 500 hPa. The contour interval is 10 m, with positive (negative) values
in red (blue) and the zero contours omitted. Shading indicates values that exceed the 5% confidence level based on a two-sided
Student’s t test.

height responses at 1000 and 500 hPa, are shown in
Fig. 12. The circulation responses are weak (generally,10 m and not statistically significant) during the warm
season (June–September), in accord with the small response of the net surface energy fluxes. Although thecirculation responses are larger and statistically significant during the cold season (October–May), they exhibit
considerable variation in pattern and amplitude. The
response in November–December (and in each monthindividually; not shown) exhibits a baroclinic verticalstructure over the Arctic consisting of negative values(220 to 230 m) at 1000 hPa and positive (10–20 m)
values at 500 hPa, and an equivalent barotropic (e.g.,
amplifying with height) ridge over central and eastern
Russia and trough over the Bering Sea. Similar features are found in March–April with weaker amplitudes.
A different circulation response is seen in midwinter(January–February), which resembles the negative polarity of the NAO (although this occurs mainly in
February; not shown). In this season, the Arctic is dominated by an upper-level ridge response (maximum amplitude ;50 m at 500 hPa) and negligible response at thesurface accompanied by equivalent barotropic troughs
over the Atlantic and northeast Pacific.
More detail on the vertical structure of the circulation
responses is given in Fig. 13, which shows transects ofthe temperature and geopotential height changes along
908E in early (November–December) and mid-(January–
February) winter. In early winter, a shallow baroclinic
geopotential height response with a nodal point near
925 hPa develops over the Arctic in association with theice-induced near-surface warming. Farther south, theresponse consists of an equivalent barotropic ridge withmaximum values ;40 m at 250 hPa near 658N. The

Arctic baroclinic response is also evident in midwinter,but it competes with the equivalent barotropic ridge
aloft that weakens the surface trough compared to thatin early winter.
The shallow baroclinic atmospheric circulation response over the Arctic in early (and late) winter may beunderstood as a linear dynamical response to enhanced
boundary layer heating induced by the underlying loss of
sea ice (Hoskins and Karoly 1981). On the other hand,the equivalent barotropic component of the circulation
response in midwinter (e.g., the NAO) and the ridge
response over Eurasia in early and late winter represent
a nonlinear dynamical response to enhanced boundary
layer heating in which transient eddy momentum flux
feedbacks associated with perturbations in the storm
track play a dominant role (Lau and Holopainen 1984;
Peng et al. 1997; Deser et al. 2007; among others). We
conjecture that the lack of a surface circulation responseover the Arctic in midwinter is due to the near cancellation
between the competing effects of the linear and nonlinear
dynamical components of the response. A quantitative
analysis of the momentum balances of the circulation responses in CAM3 is beyond the scope of this paper.
Internal modes of atmospheric circulation variability
have been shown to play a role in shaping the structureof the atmospheric response to different types of external forcing, for example SST changes, sea ice anomalies,or orbital variations (Peng et al. 1997; Deser et al. 2004;
Hall et al. 2001; among others). In the case of our CAM3
experiments, however, there is little correspondence
between the dominant patterns of internal circulation
variability and the patterns of geopotential height response to Arctic sea ice loss, with the notable exceptionof the month of February (not shown).

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345

FIG. 13. Vertical structures of the geopotential height (m; contours) and temperature (8C; color
shading) responses along 908E in (left) November–December and (right) January–February.

g. Comparison with CCSM3
How much of the projected Northern Hemisphereclimate response in the fully coupled climate model
CCSM3 at the end of the twenty-first century is due toArctic sea ice loss? To address this question, we compare the climate response to Arctic sea ice loss in the
CAM3 experiments with the climate response to GHG
forcing under the SRES A1B scenario in CCSM3.
Figure 14a (top row) shows the CCSM3 bimonthly terrestrial air temperature response, formed by subtracting
the period 1980–99 taken from the twentieth-century
ensemble mean from the period 2080–99 taken from thetwenty-first-century ensemble mean. The CCSM3 terrestrial air temperature response exhibits the expected
poleward amplification in winter, with maximum values
exceeding 108C over Siberia and northern Canada in
November–December. Weaker and more spatially uniform warming occurs in summer, with values ;28–58C.
Removing the sea ice–induced component from the
CCSM3 response (e.g., subtracting the CAM3 response
from the full CCSM3 response) eliminates most of thepoleward amplification, resulting in a more spatiallyhomogeneous pattern of winter warming over the continents. The main structure in the pattern of residual
winter air temperature response is zonal rather than
meridional, with ;28–48C (18C) less warming on thewestern side of Eurasia (North America) relative to theeastern side. This effect, which is most pronounced inearly winter (November–December), may be due toadvection of maritime air over Europe and western
North America.
In addition to reducing the spatial inhomogeneity,
removing the effect of Arctic sea ice loss also reduces theamplitude of the seasonal cycle of the terrestrial air
temperature response in CCSM3. This aspect is documented further in Fig. 14b, which shows the seasonal
cycles of the CCSM3, CAM3, and sea ice residual
CCSM3 terrestrial air temperature responses averaged
over the region 608–3008E poleward of 658N. The seasonal marches of the temperature responses are remarkably similar in CCSM3 and CAM3, with maximum
warming in November–December (108C in CCSM3 and78C in CAM3) and minimum warming in May–August(38–48C in CCSM3 and 08–0.58C in CAM3). The similarity of the amplitude and timing of the seasonal cycles in
CCSM3 and CAM3 results in a relatively constant offset(28–48C) between the two. That is, the sea ice–residualcomponent of the high-latitude terrestrial warming in
CCSM3 is much less seasonally dependent than the full
response, with maximum values ;38–48C during July–
February and minimum values ;28C in April–May.
Finally, the vertical structures of the high-latitude
terrestrial air temperature responses in December for
CCSM3 and CAM3 are compared in Fig. 14c. The
CCSM3 profile is very similar to CAM3 except for346

JOURNAL OF CLIMATEVOLUME 23

FIG. 14. (a) Bimonthly terrestrial air temperature responses (8C) for (top) CCSM3 and (bottom) CCSM3 minus CAM3. (b) Seasonal
cycle of the high-latitude (658–808N) terrestrial air temperature response in CCSM3 (dashed), CAM3 (solid), and their difference(dotted). (c) Vertical profiles of the December high-latitude (658–808N) terrestrial air temperature response in CCSM3 (dashed), CAM3
(solid), and their difference (dotted).

a nearly constant offset of approximately 38C. Thus,
most of the enhanced warming within the boundary
layer (;68C temperature increases at 1000 hPa relative
to that at 800 hPa) results directly from Arctic sea ice
loss. The height-invariant sea ice residual warming in
CCSM3 is presumably due mainly to enhanced longwave radiation from increased GHG and water vapor
concentrations; advection from lower latitudes may also
play a role.

Figure 15 shows the accumulated cold season (October–March) precipitation and March snow depth responses in
CCSM3. These may be compared with the CAM3 responses to Arctic sea ice loss shown in Fig. 9 (note thedoubled range of the color bar scale in Fig. 15 compared
to Fig. 9). The patterns of snow depth response in CCSM3
and CAM3 are similar, but the amplitudes are considerably greater in the coupled model compared to the atmospheric model. In particular, the negative (positive)15 JANUARY 2010

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347

FIG. 15. Accumulated cold season (October–March) precipitation and March snow depth
responses (cm) in CCSM3. The thick black and gray contours on the snow panel denote the2108 and 08C air temperature isotherms, respectively, during 2080–99.

snow depth response values are 4–5 (1.5–2) times larger in
CCSM3 than in CAM3. Warmer air temperatures in
CCSM3 relative to CAM3 account for the larger snow
reductions, while higher accumulated winter precipitation amounts (associated with the warmer air temperatures) account for the greater snow increases. BothCCSM3 and CAM3 exhibit positive snow depth responses over eastern Russia and northern Canada where
the accumulated precipitation responses are positive andsurface air temperatures during 2080–99 are ,2108C(thick black contour on snow cover panel in Fig. 15).
However, the conditions leading to the negative snow
depth responses over western Eurasia and North America
differ between the two models: in the case of CCSM3
warmer air temperatures control the decreases in snow
depth despite the enhanced winter precipitation, whereas
in CAM3 warmer temperatures and decreased precipitation lead to diminished snow cover.
The monthly SLP responses for CCSM3 and CAM3
are shown in Fig. 16. Perhaps the most striking aspectof this comparison is that CCSM3 exhibits a substantial SLP response in summer (May/June–September/
October) that is almost entirely absent from CAM3.
This summer response is quasi-annular in its spatial
pattern, with a trough over the Arctic and a ridge over
the North Pacific and Atlantic, and exhibits an equivalent barotropic vertical structure (not shown). This
comparison indicates that Arctic sea ice loss does notdirectly drive the high-latitude Northern Hemispherecirculation response in the fully coupled model in summer. There is some similarity between the CAM3 andCCSM3 SLP responses in November–December over theArctic and North Atlantic as well as in January and May(not shown).

4. Summary
We have documented the response of CAM3/CLM3,
an atmospheric general circulation model coupled toa land surface model, to projected Arctic sea ice loss at
the end of the twenty-first century. The response wasobtained from two 60-yr integrations of the model: one
with a repeating seasonal cycle of specified sea ice concentration and thickness conditions for the late twentieth century (1980–99) and one with sea ice conditions
for the late twenty-first century (2080–99). In both integrations, the same repeating seasonal cycle of SSTs forthe late twentieth century (1980–99) was specified inorder to isolate the direct impact of projected future sea
ice loss. Note that greenhouse gas concentrations remained fixed at 1980–99 levels in both sets of experiments. The twentieth- and twenty-first-century sea ice(and SST) conditions were obtained from ensemble
mean integrations of the fully coupled climate model
CCSM3 under historical forcing and SRES A1B scenario forcing, respectively.
An important finding of this study is the delayed response of the net surface energy budget over the Arctic
Ocean to sea ice loss. Specifically, the loss of Arctic sea
ice is greatest in summer and autumn (July–November,peaking in October) yet the response of the net surface energy flux is largest in winter (October–February,

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FIG. 16. Bimonthly SLP responses for CAM3 and CCSM3. The contour interval is 1 hPa, with positive (negative) values in red (blue) andthe zero contours omitted. Shading indicates values that exceed the 5% confidence level based on a two-sided Student’s t test.

peaking in November). This is because the turbulent(sensible and latent) energy loss, the dominant term in
the net surface energy budget, is greatest when the airtemperatures are coolest relative to the underlying
surface (ice or open water). The delay in the surface
energy flux response relative to the maximum sea ice
loss has important implications for the timing of theatmospheric response since the energy fluxes communicate the sea ice change to the atmosphere. Indeed, theseasonal cycle of the climate response to future Arctic
sea ice loss was shown to follow that of the net surface
energy flux rather than that of the sea ice (e.g., the response is greatest in October–February).
Another important finding is the impact of future
Arctic sea ice loss on high-latitude terrestrial air temperatures, precipitation, and snow cover. The air temperature and precipitation responses are greatest in
November–December over Siberia and northern Canada, with values ;78C and ;0.16 mm day21, respectively. As a result of enhanced winter precipitation (anddespite the warmer air temperatures), snow depths over
Siberia and northern Canada increase by ;1 cm liquidwater equivalent in late winter (February–April). The
climatological air temperature inversion over the highlatitude continents in winter plays an important rolein determining the geographical distribution and vertical structure of the air temperature response to Arctic
sea ice loss. Specifically, the spatial extent of the winterair temperature response is confined to the region
with a present-day inversion, and the vertical extent of
the temperature response is confined to the boundary
layer (e.g., below ;850 hPa and amplifying toward thesurface). As a consequence of the vertical structureof the terrestrial air temperature response, the static
stability of the boundary layer decreases by ;50%

from the late twentieth century to the late twenty-first
century.
The dominant process warming the atmosphericboundary layer over the high-latitude continents is horizontal heat advection by submonthly transient atmospheric motions. In other words, high-frequency windfluctuations mix the air warmed over the Arctic Ocean
because of enhanced sensible heat loss associated with
reduced sea ice cover out over the high-latitude continents. Temperature advection by the monthly mean
atmospheric circulation acts as a negative feedback, as
do all of the other terms in the heat budget except for
latent heat release during condensation (e.g., enhanced
cloud formation). Similar results are found for the highlatitude terrestrial moisture budget.
The seasonal response of the atmospheric circulation
to Arctic sea ice loss is also approximately in phase withthe timing of the net surface energy flux response. In
particular, significant circulation responses are foundonly during the cold season (October–April) with insignificant responses during summer. Within the coldseason, the spatial and vertical structures of the response
differ from month to month. In early winter (November–
December), the response is baroclinic over the Arctic,
with low pressure anomalies near the surface (maximum
values ;3–5 hPa) and high pressure anomalies aloft.
The baroclinic response over the Arctic is also evident
in midwinter (January–March), but it competes with anequivalent barotropic ridge aloft, resulting in near-zerosurface pressure anomalies. In February, the response
resembles the negative phase of the North Atlantic
Oscillation, the dominant internal mode of winter circulation variability. In April, the surface trough over
the Arctic is accompanied by low pressure anomalies
aloft.

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Comparison of the CAM3 results with the coupledmodel response to GHG forcing reveals that Arctic sea
ice loss accounts for most of the seasonal, spatial, andvertical structure of the late-twenty-first-century highlatitude terrestrial air temperature change in CCSM3.
The terrestrial warming associated with Arctic sea ice
loss has implications for Arctic ecosystems and permafrost degradation (Lawrence et al. 2008). Arctic sea ice
loss also accounts for much of CCSM3’s high-latitude
SLP response during November–January but plays anegligible role in the atmospheric circulation response inother months. Finally, Arctic sea ice loss is not thedominant factor in the coupled model’s terrestrial snow
cover and winter precipitation responses to GHG increases.

5. Discussion
A common criticism of AGCM experiments is that the
specified boundary conditions are themselves a response
to atmospheric conditions rather than a cause (e.g.,
Bretherton and Battisti 2000), rendering the experimental design inappropriate. This is not the case, however, for future Arctic sea ice loss. Indeed, the net
surface turbulent energy flux response over the Arctic
Ocean, the dominant mechanism whereby the ice loss isthermally communicated to the atmosphere, is similar
between the fully coupled CCSM3 and the CAM3 experiments (Fig. 17). In both models, the maximum
upward surface turbulent energy flux response occurs
during November–January, with slightly weaker amplitude in CCSM3 (;40 W m22) than CAM3 (;50 W m22)
due to the additional atmospheric warming from thedirect radiative effect of increased GHG concentrationsin the coupled model simulation (not shown). The spatial pattern of the net surface turbulent energy flux response is also very similar in CCSM3 and CAM3 (notshown). As expected, the surface longwave radiativeflux response is opposite in sign between CCSM3 andCAM3 because of the lack of GHG concentration
changes in the CAM3 experiments. The downward surface longwave radiative flux response in CCSM3, associated with the direct radiative effect of increased GHGs,
is approximately constant over the course of the year at;15 W m22 (Fig. 17).
Our experiments address only the direct impact ofArctic sea ice loss on the atmospheric circulation andclimate and neglect the potential role of oceanic feedbacks. In particular, warming of the Arctic Ocean due toenhanced solar heating associated with sea ice loss may
provide additional forcing to the overlying atmosphere,
although Singarayer et al. (2006) has shown this effect tobe small. In addition, warming of the high-latitude North

349

FIG. 17. As in Fig. 3 but for CCSM3. The net surface energy flux
response curve is omitted.

Pacific and Atlantic Oceans due to enhanced downward
turbulent energy fluxes as a result of anomalous warm air
advection out of the Arctic may also alter the atmosphericcirculation response through feedbacks with the midlatitude storm tracks (e.g., Peng et al. 1997; Deser et al.
2007). A follow-up study with an interactive ocean model
will be conducted to address the role of oceanic feedbacks.
Magnusdottir et al. (2004) found a consistent negative
NAO–NAM-like circulation response (e.g., an equivalent barotropic vertical structure with positive SLP
anomalies over the Arctic and negative SLP anomalies
in midlatitudes) to an idealized pattern of Arctic sea ice
loss in the Atlantic sector in each of the winter months
examined (December–March), with the strongest response in March. Their findings are generally consistent
with those reported in Seierstad and Bader (2009) for an
Arcticwide pattern of future Arctic sea ice loss. In thisstudy, we find different circulation responses in early(November–December) and mid- (January–March) winter. The early winter responses are not NAO-like, andexhibit negative SLP values over the Arctic, the Bering
Sea, and northeastern Canada, with a baroclinic structure in the vertical. This early winter response closely
resembles that found by Singarayer et al. (2006) for the
December–February average. The midwinter response
exhibits negligible SLP change over the Arctic, with astrong negative NAO pattern in February only. Further
research is needed to understand the reasons for the
disparity in the winter circulation responses among different studies.
The lack of a pronounced summertime circulation
response found in this study, although consistent withthe small net surface energy flux response to the imposed sea ice loss, is at odds with the results of Bhattet al. (2008). In that study, a statistically significant
equivalent barotropic high pressure anomaly over the
North Pacific (maximum SLP amplitude ;2 hPa) was
found in response to specified sea ice extent anomalies
taken from observations in August 1995. Such a response is opposite to the 1-hPa low pressure anomaly

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obtained in this study. The sea ice extent anomaly imposed in the study of Bhatt et al. (2008) is confined to thecoastal Arctic seas (Laptev, Kara, East Siberian, andBeaufort), and thus differs from the Arcticwide decreasein summer sea ice concentration used in our experiments. Also, sea ice thickness was kept constant at 2 m
in Bhatt et al. (2008), which is different from the treatment of sea ice thickness in our study. In summary, it
appears prudent to acknowledge that large uncertainties
remain in quantifying the dynamical atmospheric response to future Arctic sea ice loss.
The low-level temperature inversion was shown toplay a role in the surface thermal response over theArctic Ocean and adjacent continental regions. Given
that the strength of the present-day (late twentieth century) wintertime inversion is considerably overestimatedin CAM3 compared to both the National Centers forEnvironmental Prediction (NCEP)–NCAR and European Centre for Medium-Range Weather Forecasts(ECMWF) reanalysis products (not shown but see Boéet al. 2009), this may inflate the magnitude of the wintertime surface temperature response to Arctic sea ice loss.
However, the geographical distribution of the presentday inversion is well simulated in CAM3 compared to thereanalysis products (not shown), implying that the spatial
extent of the surface thermal response to future Arctic
sea ice loss may be realistic.
With the caveats noted above, the results shown here
may serve as a guide to the direct impact of projected
future Arctic sea ice loss upon climate and atmosphericcirculation. Indeed, the emerging signal of enhanced
autumn warming over the Arctic in the past ;5 yr(Serreze et al. 2008) exhibits many similarities with thesimulated response to Arctic sea ice loss documented inthis study. It remains to be seen whether other aspects ofthe simulated response become detectable in the near
future as Arctic sea ice continues to decline.
Acknowledgments. We thank the two anonymous reviewers for helpful comments and suggestions. We gratefully acknowledge support from the National Science
Foundation’s Arctic System Science Program.
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