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Dominant Interannual and Decadal Variability of Winter Surface Air Temperature
over Asia and the Surrounding Oceans
CHIHIRO MIYAZAKI
National Institute for Environmental Studies, Tsukuba, JapanTETSUZO YASUNARI
Hydrospheric Atmospheric Research Center, Nagoya University, Nagoya, Japan(Manuscript received 9 January 2007, in final form 9 July 2007)
ABSTRACTTo clarify the interannual variability of winter surface air temperature (SAT) over Asia and the surrounding oceans, the authors applied principal component analysis to normalized monthly SATs. The firstmode represents the Asian north–south dipole pattern with a node over the Tibetan Plateau. This component has close relationships to the Arctic Oscillation and cold surge variability around Southeast Asia,
showing decadal oscillation with signal changes in 1988 and 1997. The second mode is the inner-Asian modewith a center to the north of the Tibetan Plateau. This component connects to fluctuations of not only thewestern Siberian high but also the Icelandic low, which is associated with the pattern of the polar vortex
over Eurasia. A recent warming trend and possible relationship to solar activity are also shown. The modesof Asian SAT variability associated with ENSO are extracted as the north–south dipole mode over thetropical western Pacific and Japan (the third mode) and Silk Road mode (the fourth mode). The two
independent modes appear to be caused by different sea surface temperature (SST) anomalies over thewestern Pacific and Indian Ocean and their associated atmospheric Rossby wave responses: the atmosphericwave trains over both the north and south of the Tibetan Plateau in the third mode, and the atmosphericwave train that propagates toward the Silk Road via Greenland in the fourth mode.

1. Introduction
The global mean of surface air temperature (SAT)
has increased by approximately 0.6°C since the latenineteenth century (Houghton et al. 2001). During thisperiod, the largest warming (0.17°C decade⫺1) has occurred since the late 1970s (Karl et al. 2000). Mid- andhigh-latitude regions of continental Asia have shown
the strongest warming of the world, exceeding 0.6°C
decade⫺1 (Wang and Gong 2000). The warming trend
in mid- and high-latitude areas of Asia has occurred
mainly in winter (Houghton et al. 2001; Yasunari et al.
1998).
However, few studies have examined the trend andinterannual variability of the winter SAT in mid- andlow-latitude areas of Asia. Gong and Ho (2004) inves-

Corresponding author address: Tetsuzo Yasunari, Hydrospheric
Atmospheric Research Center, Nagoya University, Nagoya Furocho, Chikusa-ku, Nagoya 464-8601, Japan.
E-mail: yasunari@hyarc.nagoya-u.ac.jp
DOI: 10.1175/2007JCLI1845.1© 2008 American Meteorological Society

tigated the temperature trend using station data for
China and Korea from 1954 to 2000; their results indicated significant warming in northern China, whilemost stations south of 30°N experienced weaker warming trends. Yatagai and Yasunari (1994) also noted a
warming trend in northern China north of 35°N, as well
as a conspicuous cooling trend over Sichuan and Yunnan provinces from 1951 through 1994. By contrast,
according to Houghton et al. (2001), based on datafrom 1976 to 2000, a warming trend exceeding 0.6°C
decade⫺1 spreads over the South China Sea.
Warming trends are also found in the annual mean
SAT in tropical Asia. Harger (1995) demonstrated a
warming of 0.134°C decade⫺1 in Jakarta from 1866 to
1993. Malhi and Wright (2004) estimated the trend inSoutheast Asia as 0.2°–0.3°C decade⫺1. Given the small
amplitude of temperature variations in the tropics,
these values are noteworthy. In contrast, Kubota andTerao (2004) described a cooling trend since the last
half of the 1970s in the interannual variation of theannual mean tropical tropospheric temperature.

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Some of these temperature trends have been explained by associated climate periodic variabilities, inaddition to the anthropogenic climate change. Many
studies (e.g., Hurrell and van Loon 1997; Thompson
and Wallace 1998) reported that the wintertime temperature variability in recent decades, especially thewarming tendency in mid- and high-latitude Eurasia, isinfluenced by positive phase of the North Atlantic Oscillation (NAO)–Arctic Oscillation (AO). According to
the analysis on the zonal-averaged atmospheric condition by Thompson and Lorenz (2004), this atmosphericfluctuation in middle and high latitude exerts the influence on the tropics.
Moreover, ENSO has undergone successive warm
phase since about 1976 (Houghton et al. 2001). In general, the climate over Southeast Asia is warm and dry inthe case of El Niño (e.g., Harger 1995; Malhi andWright 2004). Hurrell (1996) showed that the warm
phase of El Niño contributes to the warming over partsof Siberia and cooling over the North Pacific Ocean.
Many studies agree that the warm phase of El Niño
results in weak Asian winter monsoon (Horel and Wallace 1981; Tomita and Yasunari 1996).
Influence of solar cycle (especially 11-yr cycle) to theearth’s climate has also been studied in various studies.
Lassen and Friis-Christensen (1995) shows the strong
correlation between the solar cycle length and the annual average temperature in Northern Hemisphere
during the recent 120 yr. The solar effect on the lower
and middle atmosphere in the objective analysis data
(Gleisner and Thejll 2003) and global SST (Lohmann etal. 2004) are also reported.
In this paper, we extract the dominant spatiotemporal pattern of SAT variabilities during winter in thehigh latitudes through the tropics over the whole of
Asia, and examine the associations of these patterns
with atmospheric circulation, the winter monsoon, andother climate variables. The dominant spatial patternsof the SAT anomalies were obtained by empirical orthogonal function (EOF) analysis that is introduced in
section 2. Section 3 describes the spatial and temporalcharacteristics of the dominant SAT modes. Section 4
presents the composite chart analysis of atmosphericcirculation for each dominant mode, which was conducted to reveal the relationships between each modeand climate variables. The correlations of each modewith several relevant climate indices are also examined.
We will draw the summary and some discussions in
section 5.

2. Data and method of analysis
We have used monthly datasets of National Centers
for Environmental Prediction–National Center for At-

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mospheric Research (NCEP–NCAR) reanalysis (version 1) data (Kalnay et al. 1996). Our period of interestis 1979/80–2002/03. We defined November–March (i.e.,
120 months for the 24 yr) as winter season and employed near-surface air temperature at the 0.995 sigma
level as SAT. The Asian region was defined as the rectangular area extended from 40° to 160°E and from 10°S
to 70°N, which covers the entire area of the Siberianhigh, the area from northwestern India (Rao 1981) toEast Asia influenced by the winter monsoon, and thearea of cold surges from the western Pacific to Indian
Ocean (Meehl et al. 1996). To estimate SAT variationin Asia from the low through high latitudes, normalized
SAT anomaly data for each calendar month were produced using the average and standard deviation of 24 yr
for each grid (2.5° ⫻ 2.5°).
We then applied EOF analysis to all the normalized
monthly SAT data for Asia. Prior to this analysis, eachgrid value was weighted by the square root of the cosineof latitude to reflect the actual area of the individual
grid. In our study, to extract dominant modes in thenormalized SAT variation influencing over the wholeof Asia and surrounding oceans covering high latitudes
through low latitudes, we adopted the ordinary EOF
analysis to them, and the results of first four components realistically showed regionalities for our analyzed
area in winter. Thus, we did not think that we needed toadopt another analysis, such as rotated EOF analysis.
Alternatively, to improve the robustness of this EOF
analysis, we showed the original SAT variations at ornear the positive and negative centers of action for each
EOF mode.
We also compared the time coefficients for each principal component mode with several climatic indices: theArctic Oscillation index (AOI), the Southern Oscillation index (SOI), and solar flux data (10.7 cm; F10.7)
provided by the National Oceanic and Atmospheric
Administration/Climate Prediction Center (NOAA/
CPC); University of East Anglia/Climate Research
Unit (UEA/CRU); and National Research Council,
Canada, respectively. We have also employed the Siberian high index (SHI), as a measure of the Asian wintermonsoon intensity that is presumed to be closely related to the winter SAT in Asia (e.g., Gong and Ho
2002; Panagiotopoulos et al. 2005). Following themethod of Panagiotopoulos et al. (2005), we defined
SHI to represent the average value of sea level pressure(SLP) averaged over the region extended from 40° to
60°N and 80° to 120°E. Additionally, Northern Hemisphere average temperature by the UEA/CRU (Jonesand Moberg 2003) is referred to in the summary anddiscussion.
Composite charts for mode 1 of the SAT variability

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MIYAZAKI AND YASUNARITABLE 1. Percentages of variances and cumulative variances forthe principal component mode of this study.

EOF1
EOF2
EOF3
EOF4
EOF5
EOF6
EOF7
EOF8
EOF9
EOF10

Variance(%)

Cumulative
variance (%)

22.5
15.3
11.2
9.1
5.6
5.3
4.4
3.3
3.2
2.6

22.5
37.8
49.0
58.1
63.7
68.9
73.3
76.6
79.8
82.3

were constructed by selecting months in which the timescore of mode 1 ⬎1 and those in which the score ⬍⫺1.
We repeated this procedure for the remaining modes.
Climate variables considered for the composite chart
analysis were SLP, surface wind, geopotential height,
and wind at 200 hPa from NCEP–NCAR reanalysis
data. In addition, NOAA Extended Reconstructed Sea
Surface Temperature (SST) and Global Precipitation
Climatology Project (GPCP) data were also used. To
check if these composite fields are statistically significant, a t test is made by comparing with the averageover all of the data period.

3. Principal modes of winter SAT anomalies over
Asia and the western PacificIn this section, we briefly describe the spatial–
temporal characteristics of the major principal component modes.
Our analysis revealed that the four leading modes
explain 22.5%, 15.3%, 11.2%, and 9.1%, respectively,of the variance and are well separated from the higher
modes (Table 1), for which the criteria of North et al.
(1982) were applied. For convenience, we will define 1)
north–south dipole mode over Asia, 2) inner-Asianmode, 3) north–south dipole mode over the tropicalwestern Pacific and Japan, and 4) Silk Road mode, torepresent the four leading modes.

a. North–south dipole mode over Asia
Figure 1a shows the eigenvector spatial pattern of thefirst mode. The pattern represents a dipole SAT
anomaly between Siberia and the South China Sea,
with a node region near the Tibetan Plateau. Time series of this mode (Fig. 1b, top) primarily represented
the interannual variation in SAT, because intraseasonalvariability of this component within the 5-month scoresof one winter was much smaller than that of othermodes described later. In this figure, negative or
slightly positive (less than ⫹1) scores tended to appear1373

from 1988/89 through 1996/97, implying dominant cold
anomalies over the South China Sea and warm anomalies in Siberia. From 1997/98 through 2002/03, the timescores changed to positive or slightly negative values(more than ⫺1), corresponding to warm anomalies
over the South China Sea and cold anomalies over Siberia; that is, decadal-scale variation also dominated inthis mode. These tendencies can be confirmed in thetime series of normalized SAT at and near the centersof action of this mode (i.e., around the negative andpositive extreme values of the eigenvectors over central
Siberia and northern Philippines, respectively) as
shown in Fig. 1b (bottom).

b. Inner-Asian mode
The spatial structure of the second mode exhibits asignificant positive SAT anomaly north of the Tibetan
Plateau (Fig. 2a). The core of the anomaly occurs along
the arid/semiarid region of China, Mongolia, and central Asia; hence, we call this the inner-Asian mode. An
anomaly that is less organized but of the same sign as in
the inner-Asian region is present over the equatorial
Indian Ocean and the Maritime Continent. In the corresponding time series (Fig. 2b, top), two successive
negative phases appeared for 1979/80–1986/87 and1991/92–1996/97, which reflected cold phases. By contrast, positive phases were also observed in the periodsof 1987/88–1990/91 and 1997/98–2002/03, corresponding
to warm phases. These temporal characteristics indicated that this mode had a decadal variation differingfrom that of the first mode. The score of this mode
represents the SAT variation over the northern Tibet
well, meanwhile the SAT fluctuation over equatorial
Indian Ocean shows the decadal variation more clearly,
especially from the late 1980s to the late 1990s (Fig. 2b,bottom). The second mode is also characterized by aremarkably positive linear trend (⫹0.047 yr⫺1 of wintermean) which is significant at the 95% level; the othermodes showed no significance. Considering the prominent positive tendency of the score since 1997/98, therecent warm anomaly was particularly prominent in thismode.

c. North–south dipole mode over the tropicalwestern Pacific and JapanThe spatial pattern of the third mode is characterized
by the largest positive and negative anomalies over thetropical western Pacific and southwestern Japan, respectively (Fig. 3a). Significant negative SAT anomaly
is also found in the Arabian Sea. The time series of thescore (Fig. 3b, top) are highly variable on interannual
time scales. The extreme score values above ⫹1 (e.g.,
1983/84, 1985/86, and 1999/2000) and below ⫺1 (e.g.,

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FIG. 1. The first component of normalized surface temperature anomalies in winters from1979/80 to 2002/03. (a) Eigenvector patterns. Contour intervals (CIs) of 0.2. Solid (dashed)lines correspond to positive (negative) contours. The shaded area indicates coefficients ⬎ (⬍)
0.4 (⫺0.4); 1000 and 3000 m altitudes are also shown. (b, top) Time series of the score (thickline); Y-axis is in the left side. Five scores of November through March are shown successively,
as one winter. The AOI multiplied by ⫺1 (thin line) is superimposed. See the main text
(section 4a). (b, bottom) Time series of normalized SAT around the extreme value of theeigenvector. Solid (dashed) line is the average of four grids located in the positive (negative)
area over northern Philippines (central Siberia), shown as closed (open) circles in (a); the yaxis is on the right side.

1992/93, 1997/98) correspond to cold (warm) SAT oversouthern Japan and warm (cold) SAT over the western
Pacific, respectively (Fig. 3b, bottom). In addition, SAT
variation over the eastern Arabian Sea also shows in(out of) phase with that over southern Japan (the tropical western Pacific), which suggest that this mode isrelated to the ENSO over the tropical Pacific and Indian Ocean basins (as will be discussed in section 4c).

d. Silk Road modeThis mode exhibits a SAT anomaly along the northern periphery of the Tibetan Plateau (Fig. 4a). The

negative anomaly has a center over the eastern plainarea of the plateau, and extends over the northern
through the western edges of the plateau, which corresponds to the ancient “Silk Road.” The positive anomalies were located both in northern Eurasia (northwardof 55°N) and the tropical oceans (Indian Ocean and thesouthern South China Sea). The time series (Fig. 4b,top) revealed the presence of extreme events: There
are two extreme positive phases in 1982/83 and 1997/98;
by contrast, extreme negative value is shown in 1998/99.
These extreme positive (negative) values of the scoreare coincident with extremely warm (cold) SAT winters

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FIG. 2. Same as in Fig. 1, but for the second component. In the top of (b), F10.7 (thin line)
is superimposed. In the bottom of (b), solid (dashed) line is the average of four grids locatedin the positive area over northern Tibet (equatorial Indian Ocean), shown as closed (open)
circles in (a).

over the southern Indian Ocean and extremely cold
(warm) SAT over eastern Tibet (Fig. 4b, bottom).

4. Atmospheric circulation patterns related to thefour principal modes of SAT
In this section, we performed the composite charts
analysis of climate variables to examine the anomalous
circulation patterns associated with each mode. These
charts (Figs. 5–8) show the synoptic pattern for the
positive phase of each component time series. The climate variables used here are 1) SLP and surface wind,2) geopotential height and wind at 200 hPa, 3) SST,and 4) precipitation. The analysis of the correlation between the four modes and three major climate variations (AOI, F10.7, and SOI) will be summarized inTable 2.

a. North–south dipole mode over Asia
A prominent, positive SLP anomaly is located overnorthern Eurasia and the Arctic, whereas the negative
SLP anomaly is visible south of the Tibetan Plateau(Fig. 5a). Surface wind anomalies over and around
Southeast Asia (i.e., southerly wind around the Philippines, cross-equatorial flow, anticyclonic circulation
over the Philippine Sea, and easterly wind over the
Malay Peninsula) indicates that the Asia north–south
dipole mode, although extracted from monthly data, islikely connected with the weakening of cold surges inthis area. At 200 hPa (Fig. 5b), the wind direction
around the Philippine Islands is nearly opposite that at
the surface, which is indicative of the local weakeningof the Hadley cell, accompanied by cold surges.
In the positive (negative) composite chart of SST

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FIG. 3. Same as in Fig. 1, but for the third component. In the top of (b), the SOI (thin line)
is superimposed. In the bottom of (b), solid (dashed) line is the average of four grids locatedin the positive (negative) area over the western Pacific (southern Japan), shown as closed(open) circles in (a).

anomalies on the first component (Fig. 5c), warm (cold)
SST anomalies are located over the northwestern Pacific to the south of Japan, East China Sea, and South
China Sea, where weaker (stronger) northeasterlies atthe surface prevail, which are associated with theanomalous winter monsoon condition over East Asia
(Fig. 5a). This spatial pattern of SST anomalies corresponds well with the anomalous sea surface conditionof the winter monsoon over East and Southeast Asia
through the control of the latent heat flux, as discussed
by some previous papers (e.g., Tomita and Yasunari
1996; Zhang et al. 1997). The diabatic heating process
over the winter monsoon surge in East Asia (Yanai andTomita 1998) also showed that a cold surge anomaly infact induced changes in the sensible and latent heating
anomaly, which in turn changed SST anomalies of thisparticular ocean. We thus have concluded that SST

anomalies in the East and South China Seas area may
principally be the result of a cold surge anomaly fromthe continent.
Over the North Atlantic–European sector and theNorth Pacific, north–south dipole SLP anomalies arealso prominent, but the polarity differs between the twobasins. They appear to be associated with the strengthened/weakened storm track of the Aleutian/Icelandic
lows, and vice versa. The dipole SLP anomaly in North
Atlantic appears to be related to the North Atlantic
Oscillation.
The atmospheric circulation at 200 hPa in this modeindicated the annular seesaw pattern of height between
the Arctic and midlatitudes (Fig. 5b), which corresponded
to the AO pattern reported by Thompson and Wallace(1998). In fact, the correlation coefficient between thefirst mode and the AOI was ⫺0.47 (Table 2)—the high-15 MARCH 2008

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FIG. 4. Same as in Fig. 1, but for the fourth component. In the top of (b), the SOI multipliedby ⫺1 (thin line) is superimposed. In the bottom of (b), solid (dashed) line is the average offour grids located in the positive (negative) area over the southern Indian Ocean (eastern
Tibet), shown as closed (open) circles in (a).

est correlation among the four modes in this study. The
AO appears to modulate the distribution of precipitation over the North Atlantic to central Siberia (Fig. 5d).
Therefore, we suggest that, to some extent, the Asian
north–south dipole mode of the SAT anomaly is closely
associated with the Arctic Oscillation that modulates
fluctuation between the Icelandic low and the Aleutian
low. It also modulates cold surge variability over Southeast Asia and the local Hadley circulation.

b. Inner-Asian mode
The second mode, inner-Asian mode, displays a huge
cyclonic anomaly over western Eurasia in the composite chart of SLP and surface wind anomalies (Fig. 6a).
The center of the anomaly is west of the Ural Mountains. As this mode is well correlated with SHI (⫺0.63,
p ⬍ 0.05), it is a good proxy for the state of the cold

wave north of 30°N in Asia. However, this cyclonicanomaly is indicative of not only weak westward expansion of the Siberian high, but also the strong Icelandic low in the case of a positive score. The positive
precipitation anomaly over northwestern Eurasia (Fig.
6d) seems to be broadly consistent with this cyclonicanomaly.
Geopotential anomalies at 200 hPa (Fig. 6b) confirm
not only the huge cyclonic anomaly over western Eurasia, but also the emergence of an anticyclonic anomaly
to the north of the Tibetan Plateau. This pair of (north)west–(south) east anomalies over Eurasia indicated thepattern of the northern polar vortex that is characterized by the mean chart of upper geopotential height(not shown): tripole and dipole for positive and negative phases of the mode, respectively. Moreover, a pairof north–south height anomalies over East Asia links

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FIG. 5. Composite anomaly charts of the first component. Positive and negative anomalies
are contoured by solid and dashed lines, respectively. (a) SLP and surface wind vector anomalies; CI is 0.5 hPa between ⫺0.5 and 0.5 hPa, and otherwise is 1 hPa. (b) Geopotential height
and wind vector anomalies at 200 hPa; CI is 15 m. (c) SST anomalies; CI is 0.2°C. (d)Precipitation anomaly; CI is 0.5 mm day⫺1. The zero contour is omitted for SST and precipitation. Areas exceeding 5% significant t value are hatched. Wind vectors are only plotted(every 5°) where either the zonal or meridional component exceeds 5% significant t value.

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FIG. 6. Same as in Fig. 5, but for the second component.

the tropical zonal wind anomalies over the Maritime
Continent.
Positive SST anomalies around Japan (Fig. 6c) may
be induced by the weakening of surface westerly and
SLP anomaly patterns over the latitudes (Fig. 6a), probably through a reduction in the surface latent heat
fluxes to the atmosphere.

Therefore, this inner-Asian mode relates to the wax
and wane of the western Siberian high and the shape of
the polar vortex over northern Eurasia, which may be
associated with the wave train pattern from northeast
Europe toward Southeast Asia and the Maritime Continent.
Interestingly, this mode exhibits a linear warming

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FIG. 7. Same as in Fig. 5, but for the third component.

trend, and also appears to be connected with the decadal-scale (approximately 11-yr cycle) solar activity. In
fact, the SST anomaly of this mode was moderately correlated with the pattern influenced by the solar cycle (periodicity of 9–15 yr; see Lohmann et al. 2004). The correlation coefficient between this inner-Asian mode andF10.7 series was marginally significant (0.23; Table 2).

Further discussion on the relation between this modeand the solar activity is attempted in section 5.

c. North–south dipole mode over the tropicalwestern Pacific and Japan
This mode is characterized by a west–east contrast of
the SLP anomaly over East Asia (Fig. 7a). This

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FIG. 8. Same as in Fig. 5, but for the fourth component.

anomaly appears to induce large temperature variations over Japan that are well correlated with the SST
anomalies (Fig. 7c).
The composite map of circulation at 200 hPa (Fig. 7b)
showed wave trains over much of Eurasia, through boththe north and south of the Tibetan Plateau. The northern wave train contains the Eurasian (EU) and western

Pacific (WP) patterns (Wallace and Gutzler 1981) overnorthern Eurasia. On the southern wave train, heightanomalies over the Middle East and the southeasternedge of the Tibetan Plateau could modulate thestrength of the subtropical jet. These two wave trains
pass over Europe, and their origin could be tracked
back westward to the tropical eastern Pacific. This tele-

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JOURNAL OF CLIMATETABLE 2. Correlation coefficients between the four principal
component time series and some major climate indices. Boldface
denotes that the probability values ( p value) of the correlation
coefficients are significant with the value below 0.05.

AO
F10.7
SOI

EOF1

EOF2

EOF3

EOF4

ⴑ0.47
⫺0.10
0.04

0.25
0.23
⫺0.11

⫺0.15
⫺0.04
0.44

0.22
0.04
ⴑ0.48

connection pattern seems to be a standing Rossby wave
train influenced by El Niño–Southern Oscillation(ENSO) as shown in Horel and Wallace (1981). It could
be reasonable that the wave train splits into a highzonal wavenumber component that is deflected equatorward via the Middle East and a low zonal wavenumber component that propagates toward the higher latitudes over Siberia and then East Asia (Hoskins andAmbrizzi 1993). In fact, this mode is correlated with
SOI (0.44; Table 2). However, some years with the significant score value of this third mode do not exactly
coincide with those of SOI (Fig. 3b), presumably because this mode is more directly related to the SST
anomaly over the western Pacific rather than the SST
anomaly over central and eastern Pacific (i.e., principal
ENSO domain), as described below.
In the tropics, remarkable Walker circulation and associated precipitation anomalies are shown (Figs.
7a,b,d). The SST composite chart for this component(Fig. 7c) denotes the anomaly located over the central–eastern equatorial Pacific, indicative of the connection
with ENSO. An extreme value over the central equatorial Pacific is detached from the anomaly over theeastern area. Over the equatorial western Pacific, theopposite SST anomaly is also very significant, although
the anomalous value is less than in the central–eastern
Pacific. The extending of the Walker circulation to theequatorial Indian Ocean (Fig. 7b) appears to be induced by SST anomaly in the Arabian Sea (Fig. 7c) andthe upper wave train south of the Tibetan Plateau.
Apart from the deep tropics, the anomalous precipitation patterns are also evident in southern China andthe Middle East. These are attributed to ENSO (Zhang
and Sumi 2002; Barlow et al. 2002).
We therefore suggest that the third mode is largely
linked to ENSO. Over the entire Eurasian region, atmospheric wave trains over both the north and south of
the Tibetan Plateau emerged through the stationary
Rossby wave response to the SST anomaly over thetropical Pacific. The linkage of tropical SST and atmospheric circulation over the Indian Ocean and the western Pacific could contribute the maintenance of thesewave trains over the entire Eurasian region.

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d. Silk Road mode
Over the Silk Road, the SAT variation appears to be
associated with the SLP anomaly and the opposite
height anomaly at 200 hPa (Figs. 8a,b). This baroclinic
structure seemed to represent local fluctuations in thesouthern edge of the Siberian high and upper trough/ridge north of Tibetan Plateau. However, the correlation coefficient between SHI and time series of the
fourth mode are 0.20 ( p ⬍ 0.05), which is the leastsignificant of the four components in this study.
In the equatorial central–eastern Pacific, a prominent
Matsuno–Gill-type circulation pattern (Matsuno 1966;
Gill 1980) is seen at 200 hPa (Fig. 8b), suggesting astationary response to the localized heating anomalies
in this region. Its heating origin is the SST anomaly overthe central–eastern Pacific (Fig. 8c), accompanied by
ENSO. Walker-type anomalous zonal circulation was
limited in the Pacific and Maritime Continent (Fig. 8b),differing from the third mode, which circulation extend
to Indian Ocean. A pair of precipitation anomalies islocated between the western Pacific and central–eastern Pacific (Fig. 8d), caused by ENSO and associatedWalker circulation.
The other prominent atmospheric anomaly of thismode is located over Greenland (Figs. 8a,b), which appears to be linked to the Northern Atlantic Oscillation.
We suggest that a Rossby wave train response to SST
anomaly over the central–eastern equatorial Pacificpropagates toward the Silk Road via Greenland.
Compared to the third mode, SST anomalies of thismode are characterized as follows: 1) The center of theanomaly is located over the central through eastern Pacific, 2) the anomaly over the western Pacific is lesssignificant, and 3) significant SST anomalies of the Pacific and Indian Ocean are mainly located in the South
Hemisphere. Particularly, the latter two characteristicsof SST in this mode appear to cause the absence of the
wave train south of the Tibetan Plateau, in contrast to
the third mode. Moreover, these SST characteristics induce the features of precipitation in the Silk Road
mode: 1) an anomaly over southern China, which is notaccompanied with an anomaly over the Middle East;and 2) significant precipitation anomalies of the Pacificand Indian Oceans are mainly located in the Southern
Hemisphere.
The correlation coefficients between SOI and thismode are significant (⫺0.48; Table 2). Differing fromthe third mode, the year with extreme values of thisfourth mode tended to coincide with the year showing
extreme values of SOI (Fig. 3b), because of its larger
SST anomaly over the equatorial central–eastern Pacific.

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Therefore, the Silk Road mode has a very clear dynamic link to ENSO. This mode corresponds to one
component of Rossby wave train response by extremely
large ENSO, which propagates toward the Silk Road
via Greenland, rather than a local fluctuation of thesouthern Siberian high over the Silk Road.

5. Summary and discussion
We have examined the interannual and interdecadal
variability of winter SAT over Asia and the surrounding oceans. Using principal component analysis of thenormalized SAT for 24 winters, we have identified thefour leading modes, namely: 1) north–south dipole
mode over Asia, 2) inner-Asian mode, 3) north–south
dipole mode over the tropical western Pacific and Japan, and 4) Silk Road mode. We have also constructed
global composite maps of various climate variables foreach mode.
Note that the first mode and the second mode are notso sensitive to the extent of EOF domain; an EOF
analysis of interannual temperature anomalies over
50°–80°N, 80°–120°E (central Siberia) reveals the twoleading modes comparable with those in this study(I. C. Handoh 2006, personal communication).
The north–south dipole mode over Asia is extracted
as the first mode in Asia, which is associated with theatmospheric circulations of the Arctic Oscillation andcold surges in Southeast Asia.
The first mode shows some characteristics describedin the previous studies on decadal oscillations: theNorth Atlantic Oscillation, the Arctic Oscillation, decadal climate shift, and so on. The northern center ofaction in the eigenvector pattern of the first mode extends to northern Japan (Fig. 1a), which is an important
aspect of the North Atlantic Oscillation as pointed out
by Xie et al. (1999). A composite map of SAT in the
Northern Hemisphere (not shown) expresses theanomaly from northern Europe to Siberia and opposite
anomalies over eastern Canada and northern Africa,
which is an important feature of NAO. The SLP
anomaly on the first mode also shows the anomalies ofNAO (Fig. 5a). The correlation coefficient of this modewith the NAO index is quite significant (⫺0.25). On theother hand, the SAT over Japan except in northern
Japan is more correlated with ENSO, as shown in thethird mode (Fig. 3a), which is also described in Xie et al.
(1999).
The temperature shift in 1988/89 northern wintershown in the score of the first mode is reported in theprevious studies. Watanabe and Nitta (1999) concluded
that the climatic shift is characterized as a dipole pattern of height anomalies between midlatitudes and polar regions with an equivalent barotropic structure.

1383

However, in their figure of SLP (their Fig. 1d), anomaly
in the south of Tibetan Plateau (30°N, 90°E) is shownwith the opposite sign to the higher latitude, which corresponds to the major surface anomaly associated witha cold surge in our first mode (Fig. 5a). In turn, ourstudy has clarified that the dominant mode studied by
Watanabe and Nitta (1999) for the high and midlatitudes is connected to lower latitudes in association with
the Asian cold surges.
The linkage between the Arctic Oscillation and thetropical troposphere is consistent with previous studies.
Over the northern and equatorial Atlantic, this regional
linkage between the Arctic Oscillation and the tropics
has been reported (e.g., Meehl and Van Loon 1979;
McHugh and Rogers 2001). The dynamic mechanism of
the zonal-mean tropical atmospheric circulation associated with Arctic Oscillation was demonstrated byThompson and Lorenz (2004): forcing by waves originating at extratropical latitudes and the eddy momentum flux convergence at the tropics. Their paper
showed a formation of the subtropical Hadley cell anda north–south temperature contrast near the surface,associated with the Arctic Oscillation (see their Fig. 1,
top). These characteristics are consistent with the features in the composite charts of the first mode in thepresent study. In the case of Asia and the surrounding
oceans, the variability of this regional Hadley cell links
directly to the appearance/absence of cold surges inSoutheast Asia. Therefore, the wax and wane of the
Arctic Oscillation is most likely associated with themodulation of cold surges in Southeast Asia, throughits regional Hadley cell over the eastern half of Eurasia.
Chang et al. (2004) indicated that only winter precipitation in the vicinity of Sumatra and the Malay Peninsula showed a weak relationship to ENSO; they concluded that the effect of ENSO was shut out by highmountains and variation of the cross-equatorial flow. In
our study, the first mode showed close association withanomalous precipitation over the Malay Peninsula.
Only this mode demonstrated the fluctuation of crossequatorial wind accompanied with cold surges in Southeast Asia. Because this first mode showed close association with the Arctic Oscillation on decadal scales,
the long-term variation of cold surges and precipitation
in Southeast Asia should be studied in conjunction with
the SAT and circulation changes of the higher latitudes,
as well as the atmosphere–ocean system in the tropics.
Furthermore, atmospheric circulation of the firstmode showed not only the direct relevance to North
Atlantic Oscillation, but also the seesaw-like fluctuation between the Icelandic low and the Aleutian low.
Honda and Nakamura (2001) investigated the processof late-winter formation of an interannual seesaw be-

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JOURNAL OF CLIMATEVOLUME 21

FIG. 9. Eigenvector patterns of the EOF analysis for normalized surface temperature
anomalies in the Northern Hemisphere in winters from 1979/80 to 2002/03. (a) The first mode,(b) the second mode, and (c) the third mode are shown. Details for drawing are same as
Fig. 1a.

tween the surface Aleutian and Icelandic lows, interpreting the Arctic Oscillation as the North Atlantic Oscillation in early winter and as the Aleutian–Iceland
seesaw in late winter. The first mode of this study
seemed to contain their circulation characteristics fromearly winter through late winter.
Inner-Asian mode, with a unique warming trend in
Asia, is extracted as the second mode. This component
indicated a significant correlation with Jones andMoberg’s (2003) Northern Hemisphere average temperature (0.74, p ⬍ 0.05). This is likely to reflect thatinner Asia is the region that shows one of the strongest
global warming signals. Moreover, this inner-Asianmode showed the some relation with the solar cycle.
Kodera (2002, 2003) pointed out that atmospheric feature of NAO was modulated by the solar cycle and theinfluence was shown in the anomaly of SLP and SAT
over Eurasia. Furthermore, these studies showed thatthe feature over Eurasia connected to zonal wind in the
troposphere through stratosphere. Hence, it should beclarified whether this significant correlation between
the inner-Asian mode and solar activity is due to thefact that the huge mass of the Eurasian continent, which
occupies a major terrestrial part in the Northern Hemisphere, may take a direct or indirect connection withthe solar activity. For this issue, we thought that the15 MARCH 2008

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MIYAZAKI AND YASUNARI

result of EOF analysis for normalized SAT in the
Northern Hemisphere may prove the hemispheric extent of inner-Asian mode and its temporal tendency of
appearance. As a result (Fig. 9), the synchronizing continental SAT mode over midlatitude Eurasia andAmerica was extracted as the third mode (9.4%), following the synchronizing maritime mode in the Atlantic, western Pacific, and Arctic Oceans (EOF1: 15.0%)
and NAO mode (EOF2: 12.4%). Temporal variation ofthis EOF3 in the Northern Hemisphere is almost thesame as that of the second mode in Asia (correlation
coefficient: 0.71), and shows better correlation with
F10.7 (0.27). Therefore, this inner-Asian mode takes
one part as hemispheric warming and as the huge massof the Northern Hemisphere for a direct or indirect
heating/cooling in conjunction with the solar activity.
Further evidence and the mechanism of the connection
between the second component and the solar cycle will
be examined separately, with reference to the theory on
the indirect connection of solar activity with the earth’s
atmosphere through stratospheric (ozone) circulation,
as shown in Kodera and Kuroda (2002).
The modes of Asian SAT variability associated with
ENSO are extracted as the north–south dipole modeover the tropical western Pacific and Japan (the thirdmode) and Silk Road mode (the fourth mode). The two
independent modes were caused by respective remoteRossby wave responses to different sea temperature
anomalies over the Pacific and Indian Oceans (in sections 4c and 4d). The two kinds of the Rossby wave
response may cause the difference of precipitation variability in midlatitude Asia. The variation of precipitation in southern China was seen both in the third andthe fourth modes, whereas the precipitation anomaly
over the Middle East appeared only in the third mode.
Zhang and Sumi (2002) concluded that precipitation
variability in southern China was caused by a low-level
circulation anomaly to the north of the Maritime Continent, which was forced through a Rossby wave train
by the western tropical Pacific SST associated with
ENSO. Since these characteristics are prominent overthe Pacific in the case of typical ENSO, both the thirdand fourth modes contain this variability in southern
China. On the anomalous precipitation in the Middle
East, Barlow et al. (2002) pointed out the following
three synoptic characteristics: the out-of-phase relationship of precipitation is prominent between the eastern Indian Ocean and the Middle East, this relationshipis due to ENSO with a strong SST signal over the western Pacific, and anticyclonic circulations over the southeastern edge of the Tibetan Plateau and the Middle
East are induced by strong convection over the eastern
Indian Ocean and the western Pacific through a station-

ary Rossby wave response. A strong SST signal over
the western Pacific and a remarkable anomaly of precipitation over the Indian Ocean correspond well to thefeatures of the third mode. The precipitation variability
in the Middle East can prove the robustness of the
Rossby wave response to the western Pacific and Indian
Ocean in the third mode.
To better understand and quantify the nature of
Asian climate variability, further investigations into the
dynamic and thermodynamic feedbacks operating ineach climate mode are merited.
Acknowledgments. The NCEP–NCAR reanalysis
datasets and NOAA extended reconstructed sea surface temperature were obtained from the Climate Diagnostics Center. Precipitation data of the Global Precipitation Climatology Project were obtained from the
National Climatic Data Center. We thank Dr. Shinjiro
Kanae (University of Tokyo), Dr. Akiyo Yatagai [Research Institute for Humanity and Nature (RIHN)],
and Dr. Itsuki C. Handoh (Ehime University) for constructive comments and encouragement, which helped
us to improve the manuscript. Chihiro Miyazaki wasfinancially supported by a RIHN Project 5-1, Global
Water Cycle Variation and the Current World Water
Resources Issues and Their Perspectives.
REFERENCES
Barlow, M., H. Cullen, and B. Lyon, 2002: Drought in Central andSoutheast Asia: La Niña, the warm pool, and Indian Ocean
precipitation. J. Climate, 15, 697–700.
Chang, C. P., Z. Wang, J. Ju, and T. Li, 2004: On the relationshipbetween western maritime continent monsoon rainfall and
ENSO during northern winter. J. Climate, 17, 665–672.
Gill, A. E., 1980: Some simple solutions for heat-induced tropicalcirculation. Quart. J. Roy. Meteor. Soc., 106, 447–462.
Gleisner, H., and P. Thejll, 2003: Patterns of tropospheric response to solar variability. Geophys. Res. Lett., 30, 1711,
doi:10.1029/2003GL017129.
Gong, D. Y., and C. H. Ho, 2002: The Siberian High and climatechange over middle to high latitude Asia. Theor. Appl. Climatol., 72, 1–9.
——, and ——, 2004: Intra-seasonal variability of wintertime temperature over East Asia. Int. J. Climatol., 24, 131–144.
Harger, J. R. E., 1995: Air-temperature variations and ENSO
effects in Indonesia, the Philippines and El Salvador. ENSO
patterns and changes from 1866–1993. Atmos. Environ., 29,
1919–1942.
Honda, M., and H. Nakamura, 2001: Interannual seesaw between
the Aleutian and Icelandic lows. Part II: Its significance in theinterannual variability over the wintertime Northern Hemisphere. J. Climate, 14, 4512–4529.
Horel, J. D., and J. M. Wallace, 1981: Planetary-scale atmosphericphenomena associated with the Southern Oscillation. Mon.
Wea. Rev., 109, 813–829.
Hoskins, B. J., and T. Ambrizzi, 1993: Rossby wave propagation

1386

JOURNAL OF CLIMATEon a realistic longitudinally varying flow. J. Atmos. Sci., 50,
1661–1671.
Hurrell, J. W., 1996: Influence of variations in extratropical wintertime teleconnections on Northern Hemisphere temperature. Geophys. Res. Lett., 23, 665–668.
——, and H. van Loon, 1997: Decadal variations in climate associated with the North Atlantic Oscillation. Climatic Change,
36, 301–326.
Houghton, J. T., Y. Ding, D. J. Griggs, M. Noguer, P. J. van der
Linden, X. Dai, K. Maskell, and C. A. Johnson, Eds., 2001:
Climate Change 2001: The Scientific Basis. Cambridge University Press, 881 pp.
Jones, P. D., and A. Moberg, 2003: Hemispheric and large-scalesurface air temperature variations: An extensive revision andan update to 2001. J. Climate, 16, 206–223.
Kalnay, E., and Coauthors, 1996: The NCEP/NCAR 40-Year Reanalysis Project. Bull. Amer. Meteor. Soc., 77, 437–471.
Karl, T. R., R. W. Knight, and B. Baker, 2000: The record breaking global temperatures of 1997 and 1998: Evidence for an
increase in the rate of global warming. Geophys. Res. Lett.,
27, 719–722.
Kodera, K., 2002: Solar cycle modulation of the North Atlantic
Oscillation: Implication in the spatial structure of the NAO.
Geophys. Res. Lett., 29, 1281, doi:10.1029/2001GL014557.
——, 2003: Solar influence on the spatial structure of the NAO
during the winter 1900–1999. Geophys. Res. Lett., 30, 1175,
doi:10.1029/2002GL016584.
——, and Y. Kuroda, 2002: Dynamical response to the solar cycle.
J. Geophys. Res., 107, 4749, doi:10.1029/2002JD002224.
Kubota, T., and T. Terao, 2004: Interdecadal variability of theseasonal-scale persistence in the tropical mean tropospherictemperature. J. Meteor. Soc. Japan, 82, 1213–1221.
Lassen, K., and E. Friis-Christensen, 1995: Variability of the solar
cycle length during the past five centuries and the apparent
association with terrestrial climate. J. Atmos. Solar-Terr.
Phys., 57, 835–845.
Lohmann, G., N. Rimbu, and M. Dima, 2004: Climate signature ofsolar irradiance variations: Analysis of long-term instrumental, historical, and proxy data. Int. J. Climatol., 24, 1045–1056.
Malhi, Y., and J. Wright, 2004: Spatial patterns and recent trends
in the climate of tropical rainforest regions. Philos. Trans.
Roy. Soc. London, 359, 311–329.
Matsuno, T., 1966: Quasi-geostrophic motions in the equatorial
area. J. Meteor. Soc. Japan, 44, 25–43.
McHugh, M. J., and J. C. Rogers, 2001: North Atlantic Oscillationinfluence on precipitation variability around the Southeast
African convergence zone. J. Climate, 14, 3631–3642.
Meehl, G. A., and H. Van Loon, 1979: The seesaw in winter temperatures between Greenland and Northern Europe. Part III:
Teleconnections with lower latitudes. Mon. Wea. Rev., 107,1095–1106.
——, G. N. Kiladis, K. M. Weickmann, M. Wheeler, D. S. Gutzler, and G. P. Compo, 1996: Modulation of equatorial sub-VOLUME 21

seasonal convective episodes by tropical–extratropical interaction in the Indian and Pacific Ocean regions. J. Geophys.
Res., 101, 15 033–15 049.
North, G. R., T. L. Bell, R. F. Cahalan, and F. J. Moeng, 1982:
Sampling errors in the estimation of empirical orthogonal
functions. Mon. Wea. Rev., 110, 699–706.
Panagiotopoulos, F., M. Shahgedanova, A. Hannachi, and D. B.
Stephenson, 2005: Observed trends and teleconnections of
the Siberian High: A recently declining center of action. J.
Climate, 18, 1411–1422.
Rao, Y. P., 1981: The climate of the Indian subcontinent. World
Survey of Climatology, K. Takahashi and H. Arakawa, Eds.,
Vol. 9, Climates of Southern and Western Asia, Elsevier Scientific Publishing Company, 67–182.
Thompson, D. W. J., and J. M. Wallace, 1998: The Arctic Oscillation signature in the wintertime geopotential height andtemperature fields. Geophys. Res. Lett., 25, 1297–1300.
——, and D. J. Lorenz, 2004: The signature and the annual modesin the tropical troposphere. J. Climate, 17, 4330–4342.
Tomita, T., and T. Yasunari, 1996: Role of the northeast wintermonsoon on the biennial oscillation of the ENSO/Monsoon
system. J. Meteor. Soc. Japan, 74, 399–413.
Wallace, J. M., and D. S. Gutzler, 1981: Teleconnections in thegeopotential height field during the Northern Hemisphere
winter. Mon. Wea. Rev., 109, 784–812.
Wang, S., and D. Gong, 2000: Enhancement of the warming trend
in China. Geophys. Res. Lett., 27, 2581–2584.
Watanabe, M., and T. Nitta, 1999: Decadal changes in the atmospheric circulation and associated surface climate variationsin the Northern Hemisphere winter. J. Climate, 12, 494–510.
Xie, S. P., H. Noguchi, and S. Matsumura, 1999: A hemisphericscale quasi-decadal oscillation and its signature in Northern
Japan. J. Meteor. Soc. Japan, 77, 573–582.
Yanai, M., and T. Tomita, 1998: Seasonal and interannual variability of atmospheric heat sources and moisture sinks asdetermined from NCEP–NCAR reanalysis. J. Climate, 11,463–482.
Yasunari, T., M. Nishimori, and T. Mito, 1998: Trends and interdecadal variations of the surface and lower-tropospheric temperature in the Northern Hemisphere from 1964 to 93. J.
Meteor. Soc. Japan, 76, 517–531.
Yatagai, A., and T. Yasunari, 1994: Trends and decadal-scale fluctuation of surface air temperature and precipitation over
China and Mongolia during the recent 40 year period (1951–90). J. Meteor. Soc. Japan, 72, 937–957.
Zhang, R., and A. Sumi, 2002: Moisture circulation over East Asia
during El Niño episode in northern winter, spring and autumn. J. Meteor. Soc. Japan, 80, 213–227.
Zhang, Y., K. R. Sperber, and J. S. Boyle, 1997: Climatology andinterannual variation of the East Asian Winter Monsoon:
Results from the 1979–95 NCEP/NCAR reanalysis. Mon.
Wea. Rev., 125, 2605–2619.