The Role of Barents Sea Ice in the Wintertime Cyclone Track andEmergence of a Warm-Arctic Cold-Siberian Anomaly

JUN INOUE AND MASATAKE E. HORI

Research Institute for Global Change, JAMSTEC, Yokosuka, Japan

KOUTAROU TAKAYA

Research Institute for Global Change, JAMSTEC, Yokohama, Japan

(Manuscript received 14 August 2011, in final form 9 November 2011)

ABSTRACT

Sea ice variability over the Barents Sea with its resultant atmospheric response has been considered one of

the triggers of unexpected downstream climate change. For example, East Asia has experienced several major

cold events while the underlying temperature over the Arctic has risen steadily. To understand the influence

of sea ice in the Barents Sea on atmospheric circulation during winter from a synoptic perspective, this study

evaluated the downstream response in cyclone activities with respect to the underlying sea ice variability. The

composite analysis, including all cyclone events over the Nordic seas, revealed that an anticyclonic anomaly

prevailed along the Siberian coast during light ice years over the Barents Sea. This likely caused anomalous

warm advection over the Barents Sea and cold advection over eastern Siberia. The difference in cyclone paths

between heavy and light ice years was expressed as a warm-Arctic cold-Siberian (WACS) anomaly. The lower

baroclinicity over the Barents Sea during the light ice years, which resulted from a weak gradient in sea

surface temperature, prevented cyclones from traveling eastward. This could lead to fewer cyclones and hence

to an anticyclonic anomaly over the Siberian coast.

1. Introduction

The decline in Arctic sea ice during summer has had

a leading role in temperature amplification during au-

tumn and winter, partly through air–sea heat transfer

(Graversen et al. 2008; Screen and Simmonds 2010). One

of the important heat transfer processes is the release of

ocean heat associated with autumn cyclone activity along

the marginal ice zone (Inoue and Hori 2011). Frequent

meridional heat transport, as well as air–sea heat ex-

change during autumn, is vital to the freezing of the

Arctic Ocean until early winter. Winter temperature

anomalies are especially large over the Barents Sea

(Serreze et al. 2011). In this region, warm advection by

anomalous winds helps to keep the ocean ice free and the

overlying atmosphere warm.

Remote responses to the warm Arctic at midlatitudes

have been found in recent years and are receiving

increased research attention (Overland et al. 2010).

Francis et al. (2009) showed that low values of summer ice

extent are related to higher winter temperatures not only

over the Arctic but also throughout the Northern Hemi-

sphere. One exceptional area is northern Siberia, which

exhibits a cooling anomaly when the ice extent is low. Re-

cent radical shifts of atmospheric circulations were respon-

sible for the cold winter anomaly over the Eurasian

continent during the winters of 2001/02 to 2005/06 (Zhang

et al. 2008). The impacts of Siberian coldness during

winter 2005/06 were widespread from Europe to East

Asia. Using numerical experiments, Honda et al. (2009,

hereafter H09) concluded that the reduced ice cover in

the Barents and Kara Seas in summer 2005 accounted for

the cold anomalies in East Asia the following winter. This

was due to a stationary Rossby wave induced by anom-

alous turbulent heat fluxes, which in turn amplified the

Siberian high. Petoukhov and Semenov (2010) found the

same response in a limited situation with 80%–40% ice

reduction over the Barents and Kara Seas. The sea ice

anomaly in 2007 also intensified surface anticyclones over

the Eurasian and American continents in association with

Corresponding author address: Jun Inoue, Research Institute

for Global Change, JAMSTEC, 2-15 Natsushima-cho, Yokosuka

237-0061, Japan.

E-mail: jun.inoue@jamstec.go.jp

1 APRIL 2012 I N O U E E T A L . 2561

DOI: 10.1175/JCLI-D-11-00449.1

� 2012 American Meteorological Society

anomalous advection of cold polar air on their eastern

sides, bringing colder temperatures along the Pacific

coast of Asia and northeastern North America (Orsolini

et al. 2012). The effects of record persistence of the

negative phase of the North Atlantic Oscillation (NAO)

and the Arctic Oscillation (AO) in winter 2009/10 on the

United States, Europe, and East Asia were investigated

(Jung et al. 2011; Cattiaux et al. 2010; Cohen et al. 2010).

While the NAO/AO was helpful for determining the

hemispheric tendency of cold air flowing in and out of the

Arctic region and into the midlatitudes, the downstream

effect of a blocking high over the Nordic seas gave a more

deterministic and predictable view of the cold-air ad-

vection from the Arctic (Hori et al. 2011). Croci-Maspoli

and Davies (2009) also found that the anomalous cold

European winter in 2005/06 was not related to a negative

phase of the NAO but to a pattern with a blocking high

located over the North Atlantic Ocean.

A strong blocking high over the North Atlantic is

closely related to the generation of polar lows over the

Barents Sea during winter (Blechschmidt et al. 2009). In

addition, a cyclonic anomaly over northern Norway is

known to be associated with an anticyclonic anomaly

along the west coast of Greenland, as much as 3 days prior

to the outbreak of polar lows (Businger 1985). Although

not detailed in the literature, a response downstream of

an anticyclonic anomaly is also visible following the

mature stage of cyclones (Fig. 7 of Businger 1985). This

anticyclonic anomaly should induce cold advection over

the Eurasian continent. Although the temporal and spatial

scales differ between polar lows and synoptic cyclones,

baroclinic instability seems to be a common mechanism

for the generation of both types of cyclones. In addition,

analyses of synoptic activity (e.g., cyclone tracking) some-

times provide good explanations of the physical mecha-

nisms behind statistically observed relationships (Zhang

et al. 2004; Finnis et al. 2007; Stroeve et al. 2011). There-

fore, the cyclone activity over the Barents Sea during

winter might be a good indicator for the interpretation

and prediction of cold events over the downstream region.

The climatology of Arctic cyclone activity shows a

high cyclone count over the North Atlantic sector and

from the Iceland/Greenland Sea to the Barents Sea

(Zhang et al. 2004). The position of a sea ice edge likely

affects cyclones, particularly their development and

track. The sea ice distribution over the Barents Sea has

a large year-to-year variability with a strong air–ice–sea

coupled system. Although sea ice retreat over the Barents

Sea was hypothesized to enhance the westerly wind-

driven oceanic inflow via frequent local cyclogenesis

(Ikeda 1990; Bengtsson et al. 2004), the cyclone density

over the Nordic seas was found to be only weakly cor-

related with the Barents Sea ice extent during winter

(Sorteberg and Kvingedal 2006). Therefore, the depen-

dence of cyclone behavior over the Barents Sea on the

variability of sea ice cover and cyclone impact on the

downstream climate system has not been fully clarified.

Here, we focus on how each cyclone generated over

the Nordic seas is influenced by the ice edge over the

Barents Sea during winter and impacts the warm-Arctic

and cold-continental pattern. By comparing the cyclone

tracks between light and heavy ice years over the Barents

Sea, we assess the linkage between cyclone characteristics

and downstream impact.

2. Data and methods

a. Reanalysis

We obtained atmospheric data from the National

Centers for Environmental Prediction–National Center

for Atmospheric Research (NCEP–NCAR) reanalysis

(Kalnay et al. 1996) for mean sea level pressure (SLP),

surface air temperature (SAT), geopotential height,

and wind fields. The data have a spatial resolution of

2.58 3 2.58 on a regular latitude–longitude grid. Six-hourly

data from December 1979 to March 2011 were used.

The Met Office Hadley Centre Sea Ice and Sea Surface

Temperature (SST) dataset version 1 (HadISST1) (Rayner

et al. 2003) was also used in this study. These data consist

of monthly globally complete fields on a 1.08 3 1.08 reg-

ular latitude–longitude grid.

b. Cyclone identification and tracking

An algorithm for cyclone identification and tracking,

developed by the University of Melbourne (for details,

see Simmonds and Murray 1999), was applied to the

NCEP–NCAR reanalysis. To find possible cyclones, the

Laplacian of pressure (=2p) at each grid point was

compared with values at neighboring grid points for the

whole Northern Hemisphere during winter [December–

February (DJF)] during the period 1979–2011. When a

potential cyclone was identified, the position of the as-

sociated pressure minimum was determined by iteration

to the center of the ellipsoid best fit to the pressure surface.

Identified cyclones were tested by a concavity criterion,

which required that the average value of the Laplacian

exceed 0.2 hPa (8lat)22 over a radius of 28 latitude. After

identifying potential cyclones with this algorithm for each

time step, a tracking algorithm estimated each cyclone

track by scanning the connection from a point detected in

the previous time step based on cyclone characteristics

(e.g., cyclone steering velocity). Matching between each

old and new cyclone was evaluated as possible combina-

tions. The greatest probability gave the matching for the

cyclone track. To remove noise, we only included cyclones

that lasted more than 1 day. We focused on cyclones

2562 J O U R N A L O F C L I M A T E VOLUME 25

generated over the Nordic seas, including the Barents Sea

(658–858N, 308W–608E), to reveal the atmospheric re-

sponse to the variability in sea ice distribution.

3. Warm-Arctic cold-Siberian (WACS) anomaly

To understand the effect of sea ice variability on the

cyclones and their synoptic environment, we selected

typical cases, defined as heavy and light ice cover years

over the Barents Sea. Figure 1a shows the standard de-

viation of ice concentration in December from 1979 to

2010. The northern Barents Sea had the maximum var-

iability (box area in Fig. 1a). Using the time series of the

anomaly field over this area, we selected heavy and light

ice cover years (Fig. 1b). We confirmed that the anomaly

of ice concentration in December statistically persists

during the whole winter. As heavy ice years, 1980, 1981,

1988, 1997, and 2003 were selected for analysis, while as

light ice years 2004–07 and 2009 were used.

For the heavy and light ice cases, 205 and 207 cyclones

were detected, respectively, in winter (including the

following January and February). Although the num-

bers are nearly equal between the cases, the mean

central minimum SLP of cyclones in the heavy ice case

(982.9 hPa) was lower than that in the light ice case

(986.9 hPa). Furthermore, the average position shif-

ted northward by about 28 in the light ice case (dots in

Fig. 1a). This suggested that the sea ice retreat might

have affected the cyclone tracks. Figure 2 shows all

the cyclone tracks generated over the Nordic seas. In

the heavy ice case (Fig. 2a), the tracks and the positions

where the SLP reached a minimum (green crosses in

Fig. 2) were concentrated over the Norwegian coast and

Barents Sea, whereas in the light ice years (Fig. 2b), the

tracks tended to be spread out, with some heading di-

rectly toward the North Pole.

To show the atmospheric environment in the heavy

and light ice cases, the composite SLP fields during DJF

when each cyclone reached the minimum SLP are also

shown in Fig. 2 (shading). The SLP was 5 hPa deeper

over the Norwegian Sea in the heavy ice case (Fig. 2a)

than in the light ice case (Fig. 2b), supporting the cyclone

statistics mentioned before. In the light ice case, the

Siberian high expanded northward up to 708N. To high-

light the atmospheric responses to the sea ice anomalies,

we created a difference field by subtracting the heavy

ice SLP from the light ice SLP (Fig. 3a). An anticyclonic

anomaly was visible along the coastal area of Siberia

near the Taymyr Peninsula (758N, 908E) as well as in

Scandinavian regions. This anticyclonic anomaly seemed

FIG. 1. (a) Standard deviation of ice cover (contour: %) during December from 1979 to 2010.

Mean positions of cyclone centers for heavy and light ice years are depicted by blue and red

dots, respectively. (b) Ice cover anomaly during December from climatology over the northern

Barents Sea [enclosed area in (a)]. Heavy and light ice years used in the analysis are indicated

by blue and red dots, respectively.

Fig(s). 1 live 4/C

1 APRIL 2012 I N O U E E T A L . 2563

to bring anomalous warm air from the North Atlantic

sector and cold air from northeastern Siberia (Fig. 3b),

creating the WACS anomaly, which is likely a precursor

to severe weather in the downstream East Asian region.

Serreze et al. (2011) showed that the recent enhanced

warm anomaly over the Barents Sea is influenced by the

enhanced warm advection under declining sea ice. The

anomalous warm advection might lead to reduced sur-

face heat fluxes because of the low air–sea temperature

difference, preventing the air mass from cooling. The

warm southwesterly wind anomaly likely prevents the

sea ice from forming and advecting southward. This

would help explain why the warm anomaly over the

northern Barents Sea extended to 858N (Fig. 3b). To

confirm this notion from an atmospheric point of view,

we calculated the baroclinicity, which we defined as the

FIG. 2. Composite SLP (hPa) for (a) heavy ice and (b) light ice

years. Cyclone tracks and minimum SLP points are denoted by

magenta lines and green crosses, respectively.

FIG. 3. Difference maps of (a) SLP (hPa) and (b) SAT (K) be-

tween light and heavy ice years. These values were obtained by

subtracting the composite response for averaged heavy ice case

events from those for averaged light ice case events. Gray shading

indicates areas with less than a 99% confidence level based on

Student’s t test.

Fig(s). 2,3 live 4/C

2564 J O U R N A L O F C L I M A T E VOLUME 25

vertical zonal wind shear between 500 and 925 hPa

during cyclogenesis (i.e., the time when each cyclone

was initially detected). Figure 4a shows the anomaly

field of baroclinicity between heavy and light cases. A

remarkable weakening zone was observed from the east

Greenland coast to the Kara Sea. Over the Barents–Kara

Seas, the reduced baroclinic zone was limited to a narrow

region. Therefore, the zonal wind at the steering level of

cyclones (e.g., 500 hPa) became weaker in the light ice

years, hindering the eastward propagation of cyclones

from this region. As expected, the system density (i.e.,

number and strength of cyclones) along the Barents–

Kara Seas also decreased (Fig. 4b) because of its north-

ward shift (Fig. 2b), hinting that the sea ice edge and SST

distribution play important roles in synoptic development

(Adakudlu and Barstad 2011).

To better understand the role of SST in the WACS

anomaly, we focused on the SST field over the Barents Sea.

Figures 5a,b show the horizontal distributions of SST in

December 2003 (heavy ice year) and December 2005 (light

ice year). In the light ice year, the area of open water in

the northern Barents Sea expanded northward with a SST

below 18C (Fig. 5b). Compositing 5 yr for both cases, we

found a robust difference in the SST gradient over the

area (Fig. 5c). Because SSTs in the coastal region did not

vary greatly from 28C, the meridional gradient basically

depended on the southernmost ice edge in the Barents

Sea. The distance from the coastline at which the SST be-

came lower than 218C differed by as much as 300 km,

signifying a large difference in baroclinicity (Fig. 4a).

FIG. 4. (a) Baroclinicity anomaly (m s21 km21), defined as the

difference in zonal wind speed between 500 and 925 hPa (light

minus heavy ice cases) at cyclogenesis. Contour indicates the

baroclinicity in heavy ice years. (b) System density anomaly

[1023 (8lat)22].

FIG. 5. SST (8C) distributions in December in (a) 2003 and (b)

2005. (c) SST as a function of latitude averaged over 308–608E for

heavy ice (blue) and light ice (red) cases. Five members for each

case selected in Fig. 1b are also depicted by thin lines.

Fig(s). 4,5 live 4/C

1 APRIL 2012 I N O U E E T A L . 2565

4. Summary and discussion

To elucidate the mechanisms of the recent severe

cold winters in East Asia, the effect of the upstream

atmospheric circulation triggered by sea ice variability

over the Barents Sea was investigated. The synoptic char-

acteristics of cyclones generated near the Nordic seas

showed that the sea ice variability over the Barents Sea

very likely controls the cyclone tracks through changes in

baroclinicity. The relationship between the warm anomaly

over the northern Barents Sea and the positive system

density around Svalbard under a light ice situation is linked

to anomalous warm horizontal advection by northward-

moving cyclones. The northward shift of cyclone tracks

creates an anomalous anticyclonic circulation over the

Siberian coast, triggering a distinct advection of cold air

over the northern Siberia sector. Therefore, our findings

support the idea that cyclone paths under a light ice sit-

uation over the Barents Sea are the driving mechanism

for generating the WACS anomaly.

To date, the large-scale response to reduced ice extent

over the Barents Sea sector has been discussed using

general circulation models. Alexander et al. (2004) showed

a significant anticyclonic SLP anomaly over eastern

Siberia under a case of reduced ice concentration (winter

1995/96). The horizontal distribution is partly the same as

in the WACS anomaly (Fig. 3a), although the amplitude

is significantly stronger in our case. This suggests that

each synoptic event is important for generating the

WACS anomaly. Magnusdottir et al. (2004) confirmed

the remote response to SST and sea ice anomalies over

the North Atlantic sector. Although each anomaly is

responsible for weakening storm activity over the North

Atlantic basin, a cold anomaly over eastern Siberia was

only found in the reduced-ice case. This result also sup-

ports the idea that the difference in local baroclinicity

over the Barents Sea influences the continental cold

anomaly. A significant large-scale atmospheric circula-

tion response was also found in projected Arctic sea ice

loss at the end of the twenty-first century (Deser et al.

2010). The WACS-like and baroclinic vertical structure

anomaly was seen in early winter; however, this response

was modified to the equivalent barotropic pattern in late

winter, suggesting a difference in cyclone activity in as-

sociation with projected sea ice anomalies between early

and late winter. Regarding cyclone intensity and fre-

quency, Finnis et al. (2007) found that the cyclone in-

tensity over the Barents Sea and northern Siberian sector

was slightly weakened during winter under a reduced-ice

situation (i.e., twenty-first-century run), although the

frequency did not change between the twentieth and

twenty-first centuries; this tendency is very similar to our

result. They speculated that the loss of autumn ice cover

greatly reduces meridional temperature gradients in the

lower troposphere.

The WACS anomaly is also very similar to those

found by H09 and Petoukhov and Semenov (2010), who

concluded that the cold anomaly over east Siberia is

triggered by a stationary Rossby wave emanating from

anomalous turbulent heat fluxes as a result of anomalous

ice cover over the Barents–Kara Seas. The study of H09

was based on a seasonal time scale, at which the effect of

the ice anomaly during October persists into late winter.

While the results of H09 were statistically significant, the

source of this persistence was not well discussed. Our

analysis offers a more detailed view of the sea ice in-

fluence on the downstream anticyclonic anomaly on in-

traseasonal time scales as manifested in the changing

cyclone tracks.

To further elucidate this point, we also analyzed the

250-hPa geopotential height (Z250) response described

by H09 between light and heavy ice years (Fig. 6). No-

tably, the upper-tropospheric pattern shifted upstream

by about a quarter wavelength relative to the SLP pat-

tern (Fig. 3a), reflecting the baroclinic nature of the re-

sponse found by H09. Significant wavelike anomalies

occur across Eurasia, which are associated with the pro-

pagation of wave activity flux (WAF), as indicated by

arrows (Takaya and Nakamura 2001) in Fig. 6. This sug-

gests that this wave train was probably associated with

a stationary Rossby wave excited by anomalous turbulent

heat fluxes around the Barents Sea as described by H09.

Therefore, the dynamical remote response from the

anomalous ice cover over the Barents Sea toward the

FIG. 6. As in Fig. 3, but for the geopotential height (m) at 250 hPa.

Vectors show the WAF (m2 s22).

Fig(s). 6 live 4/C

2566 J O U R N A L O F C L I M A T E VOLUME 25

upper atmosphere in east Siberia reported by H09 also

exists on intraseasonal time scales. Because the remote

response proposed by H09 is triggered by the turbulent

heat flux over the ice-free ocean, it strongly corresponds

to the case in which cold-air advection is present. In our

study, the mean position of the cyclone center is located

over the Barents Sea opening regardless of whether it is

a heavy or light ice year (dots in Fig. 1a), which creates

warm advection over the Barents Sea. Thus, both the cold

advection near the ice margin and the warm advection

brought by the cyclone systems are responsible for the

creation of the WACS anomaly.

To demonstrate that the existence of fewer cyclones

over northern Siberia enhances the anticyclonic anom-

aly (i.e., northward expansion of the Siberian high), we

created composite anomaly maps by simply averaging

SLP and SAT anomaly fields during five winters between

cases of heavy ice and light ice years (Fig. 7). Compared

to the cyclone composite field (Fig. 3), the anticyclonic

anomaly is weakened by 2 hPa along the Siberian coast

(Fig. 7a); accordingly, the cold anomaly is also reduced

over central Siberia (Fig. 7b). This fact suggests that cy-

clones developing over the Barents Sea have a leading

role in the emergence of the WACS anomaly. From the

viewpoint of larger atmospheric circulation change, how-

ever, the northward shift of cyclone centers and tracks

might also be related to the northeastward shift of the

NAO/AO center of action over the past decade (Zhang

et al. 2008).

Although the midlatitude climate is also influenced

by other teleconnections, for example, the El Nino–

Southern Oscillation (Sakai and Kawamura 2009), each

cyclone path over the Arctic should be worth monitoring

for cold-air accumulation over Siberia in short-term

forecasts (weekly or less). Furthermore, the variability

in Barents ice cover has the potential predictability for

long-term forecasts (seasonal and monthly scales). How-

ever, the atmospheric circulation leading up to the WACS

anomaly might change in the near future as sea ice is

significantly diminished (e.g., Petoukhov and Semenov

2010). Therefore, we must pay careful attention to the

transitional phase of the Arctic system and its changing

impact on the midlatitude climate system.

Acknowledgments. We thank Prof. I. Simmonds at

the University of Melbourne for providing the cyclone

tracking algorithm. JI is partly supported by the Japan–

Norway Researcher mobility programme (Norwegian

Research Council Project 211932/F11). The authors also

thank three anonymous reviewers for their helpful

comments.

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