Combined effect of El Nino-Southern Oscillation and PacificDecadal Oscillation on the East Asian winter monsoon

Ji-Won Kim • Sang-Wook Yeh • Eun-Chul Chang

Received: 24 September 2012 / Accepted: 7 March 2013 / Published online: 24 March 2013

� Springer-Verlag Berlin Heidelberg 2013

Abstract Using long-term observational data and

numerical model experiments, the combined effect of the

El Nino-Southern Oscillation (ENSO) and Pacific Decadal

Oscillation (PDO) on the variability of the East Asian

winter monsoon is examined. In the observations, it is

found that when the ENSO and PDO are in-phase combi-

nations (i.e., El Nino/positive PDO phase and La Nina/

negative PDO phase), a negative relationship between

ENSO and East Asian winter monsoon is significantly

intensified. In other words, when El Nino (La Nina) occurs

with positive (negative) PDO phase, anomalous warm

(cold) temperatures are dominant over the East Asian

winter continent. On the other hand, there are no significant

temperature anomalies when the ENSO and PDO are out-

of-phase combinations (i.e., El Nino/negative PDO phase

and La Nina/positive PDO phase). Further analyses indi-

cate that the anticyclone over the western North Pacific

including the East Asian marginal seas plays an essential

role in modulating the intensity of the East Asian winter

monsoon under the changes of ENSO–PDO phase rela-

tionship. Long-lasting high pressure and warm sea surface

temperature anomalies during the late fall/winter and fol-

lowing spring over the western North Pacific, which appear

as the El Nino occurs with positive PDO phase, can lead to

a weakened East Asian winter monsoon by transporting

warm and wet conditions into the East Asian continent

through the southerly wind anomalies along the western

flank of the anomalous high pressure, and vice versa as the

La Nina occurs with negative PDO phase. In contrast, the

anomalous high pressure over the western North Pacific

does not show a prominent change under the out-of-phase

combinations of ENSO and PDO. Numerical model

experiments confirm the observational results, accompa-

nying dominant warm temperature anomalies over East

Asia via strong anticyclonic circulation anomalies near the

Philippine Sea as the El Nino occurs with positive PDO

phase, whereas such warming is weakened as the El Nino

occurs with negative PDO phase. This result supports the

argument that the changes in the East Asian winter mon-

soon intensity with ENSO are largely affected by the

strength of the anticyclone over the western North Pacific,

which significantly changes according to the ENSO–PDO

phase relationship.

1 Introduction

The East Asian winter monsoon (EAWM) that brings

severe cold surges and heavy snowfall can cause serious

damage to crops, daily life, and economic activities over

East Asia. The EAWM is not only an important factor that

influences the local weather but it is also one of the most

active components in the global climate system during the

boreal winter season. This is because the EAWM is

J.-W. Kim

Climate Change Research Team, APEC Climate Center,

Busan, Korea

Present Address:

J.-W. Kim

Department of Atmospheric Sciences,

Yonsei University, Seoul, Korea

S.-W. Yeh (&)

Department of Environmental Marine Sciences and Convergent

Technology, ERICA, Hanyang University, Ansan, Korea

e-mail: swyeh@hanyang.ac.kr

E.-C. Chang

Atmosphere and Ocean Research Institute,

University of Tokyo, Kashiwa, Japan

123

Clim Dyn (2014) 42:957–971

DOI 10.1007/s00382-013-1730-z

associated with a powerful atmospheric circulation system

named Siberian-Mongolian High, which is generated by

the large thermal contrast between the world’s largest

landmass, Eurasia, and the Indo-Pacific Ocean (Li 1955;

Tao 1957). Hence, there have been many efforts to

understand the variability of the EAWM (Chang et al.

1979, 2006; Chang and Lau 1982; Lau and Li 1984; Ding

1994; Huang et al. 2003, 2007; Chan and Li 2004; Wang

et al. 2010).

According to previous studies, it has been known that

the variability of the EAWM is closely linked to the tropics

(Lau and Chang 1987; Zhang et al. 1997b) as well as some

other forcings such as the Arctic Oscillation (AO), the

North Atlantic Oscillation (NAO), the Southern Hemi-

sphere annular mode (SAM), and the anthropogenic global

warming (Gong et al. 2001; Jhun and Lee 2004; Wu et al.

2006, 2009; Li and Bates 2007). In particular, the El Nino-

Southern Oscillation (ENSO) exerts the greatest influence

on the EAWM on interannual timescales (Zhang et al.

1996; Tomita and Yasunari 1996; Ji et al. 1997; Wang et al.

2000; Hamada et al. 2002; Chang et al. 2004). Wang et al.

(2000), one of the pioneering works, reported that a key

system that bridges El Nino (La Nina) events in the eastern

tropical Pacific and the weak (strong) EAWM is an

anomalous lower-tropospheric anticyclone (cyclone) loca-

ted near the Philippine Sea. These anticyclonic (cyclonic)

wind anomalies cause anomalously warm (cold) and wet

(dry) conditions over East Asia. In other words, the mature

phase of El Nino (La Nina) is normally accompanied by a

weaker (stronger) than normal EAWM. The so-called

Pacific-East Asian teleconnection pattern can explain the

aforementioned relationship between the ENSO and East

Asian winter climate on interannual timescales.

However, it has been recognized that the Pacific-East

Asian teleconnection pattern is not stationary, a fact that may

be due to decadal-to-multidecadal variations in the sea sur-

face temperature (SST) in the Pacific Ocean. Therefore, such

variations should be considered as an additional element that

modifies the ENSO–EAWM relationship (Tsonis et al. 2007;

Swanson and Tsonis 2009). In particular, the Pacific Decadal

Oscillation (PDO; Mantua et al. 1997), which is the most

dominant mode of SST oscillation in the North Pacific on

interdecadal timescale, has been proposed as an important

modulation factor on ENSO-related teleconnections from

the tropics to the mid-latitudes (Gershunov and Barnett

1998; Pavia et al. 2006; Yoon and Yeh 2010). Although the

PDO fluctuates on the low-frequency timescales that are

quite different from those of the ENSO, the PDO has been

described by some as a long-lived ENSO-like pattern of

Pacific climate variability because climate anomalies asso-

ciated with the PDO are somewhat similar to those connected

to the ENSO (Latif and Barnett 1996; Zhang et al. 1997a).

In fact, extensive researches have been conducted in an

effort to understand the interdecadal modulation effect of

the PDO on the impact of the ENSO on extratropical cli-

mate (Kung and Chern 1995; Paegle and Mo 2002; Kayano

and Andreoli 2007; Lupo et al. 2007; Wang et al. 2008; Hu

and Huang 2009; McCabe et al. 2011). Among them, Hu

and Huang (2009) examined the influence of PDO and

ENSO on the climate variability over the Great Plains with

considering the short timescale variations of PDO. Wang

et al. (2008) insisted that when the PDO is in its high phase,

there is no robust relationship between the ENSO and

EAWM on interannual timescale. In contrast, when the

PDO is in its low phase, the ENSO exerts a strong impact

on the EAWM with robust and significant low-level tem-

perature changes occurring over East Asia. However, the

PDO modulation effect on the ENSO–EAWM relationship

on the low-frequency timescales has not been sufficiently

elucidated in the aforementioned studies because focus was

mostly placed on the two phases of the PDO without

considering the combined effect of the ENSO on interan-

nual timescales and PDO phases on the low-frequency

timescales. Moreover, details regarding the physical

mechanisms for the modulation of the PDO are still

unknown.

The main purpose of the present study is therefore to

investigate the influence of phase combinations of the

ENSO and PDO on the EAWM using long-term observa-

tional datasets. As in the study of Wang et al. (2010), we

chose surface air temperature (SAT) as the key variable to

examine the EAWM variability unlike most other previous

studies which have taken circulation variables as measures

of its strength (e.g., Guo 1982; Ji et al. 1997; Lu and Chan

1999; Cui and Sun 1999; Chen et al. 2000; Li and Zeng

2002; Jhun and Lee 2004; Wu et al. 2006). Furthermore, an

attempt will be made to understand the physical mecha-

nism of the interdecadal PDO modulation effect on the

EAWM variability as shown in Sect. 3.

This paper is organized as follows: The datasets and the

methodologies utilized in this study are introduced briefly

in Sect. 2. In Sect. 3, we investigate the individual effect of

the ENSO and PDO on the diverse background fields to

quantify how much they are related to the EAWM vari-

ability and compare their combined effect on the EAWM

using the conditional composite analysis method. Possible

interpretations, including the physical mechanism for

modifying the EAWM and the role of atmospheric circu-

lation patterns in accordance with the conventional Pacific-

East Asian teleconnection concept, are explained in Sect.

3.3. In addition, the findings in this study are assessed by

means of numerical model experiments. Finally, a sum-

mary and discussion of the results and avenues for further

study are presented in Sect. 4.

958 J.-W. Kim et al.

123

2 Data and methodology

2.1 Observational datasets

Four types of observed monthly mean datasets and two cli-

mate indices are used in this study; detailed descriptions of

each are given in Table 1. Global land surface air tempera-

ture data developed at the University of Delaware, which

covers the period from January 1900 to December 2008, was

utilized (http://jisao.washington.edu/data_sets/ud). These

data are provided in native 0.5 degree latitude-longitude

resolution and a variety of analysis techniques were applied

for spatial interpolation and cross-validation. Several upda-

ted sources for the data include a recent version of the Global

Historical Climatology Network version 2 (GHCN2; Peter-

son and Vose 1997), the Atmospheric Environment Service/

Environment Canada, the State Hydrometeorological Insti-

tute, St. Petersburg, Russia, Greenland-from the GC-Net

(Steffen et al. 1996), the Automatic Weather Station Project,

the Global Synoptic Climatology Network, and the Global

Surface Summary of the day.

Monthly-mean meteorological datasets obtained from

the 40-years European Centre for Medium-Range Weather

Forecasts (ECMWF) Re-Analysis (ERA-40) (Uppala

et al. 2005; http://data-portal.ecmwf.int/data/d/era40_moda/)

were also employed. The datasets cover the period from

September 1957 to August 2002 with a horizontal resolu-

tion of approximately 2.5� 9 2.5� in both latitude and

longitude. This resolution extends from 1,000- to 1-hPa

with 23 vertical pressure levels. In addition, the monthly

means of daily means ERA-Interim datasets, also produced

by the ECMWF, were used (Simmons et al. 2006; http://

data-portal.ecmwf.int/data/d/interim_moda/). The ERA-

Interim data have a 1.5� 9 1.5� average horizontal reso-

lution and a hybrid vertical coordinate system with 60

levels and covers the period from January 1979 to

December 2010.

In this study, the atmospheric variables used as back-

grounds were created by two different datasets: ERA-40

and ERA-Interim. As noted above, the period of the ERA-

40 data has a limitation from September 1957 to August

2002. To extend the analysis period, we therefore con-

nected ERA-Interim data by using a bilinear interpolation

method, beginning from January 2002 to December 2010.

To maintain spatial homogeneity, the rectilinear grid of the

ERA-Interim data was interpolated into that of the ERA-40

data. Hereafter, the unified data will be referred to as the

combined-ERA data. The monthly-mean SST values were

obtained from the National Oceanic and Atmospheric

Administration (NOAA) Extended Reconstructed SST

version 3b data (ERSSTv3b) on a 2.0� 9 2.0� horizontal

grid globally, which spans from January 1854 to December

2010 (Smith et al. 2008; http://www.esrl.noaa.gov/psd/

data/gridded/).

2.2 Climatic index and methodology

Two essential climatic oscillation indices were utilized.

One is the ENSO index, which covers January 1868–

December 2010 and follows the definition provided by the

Japan Meteorological Agency (http://coaps.fsu.edu/jma.

shtml). This index is a widely accepted definition of the

ENSO that has been used in many climatic studies (e.g.,

Birk et al. 2010 and references therein). Based on the index

derived from observed SST anomalies, the ENSO is cate-

gorized into three phases: El Nino, La Nina, and neutral

phases. A particular phase of the ENSO is determined by a

5-month running mean of spatially averaged SST anoma-

lies over the eastern tropical Pacific (4�S–4�N, 150–90�W).

In order for a particular year to be classified as an El Nino

(La Nina) year, the SST anomalies must be 0.5 �C

(-0.5 �C) or greater (less) for 6 consecutive months

including October, November, and December. Alterna-

tively, neutral years are determined when the SST anom-

alies are between 0.5 and -0.5 �C. The other is the PDO

index, which spans from January 1900 to December

2010 (http://jisao.washington.edu/data_sets/pdo/). The PDO

index is defined as the leading Empirical Orthogonal

Function (EOF) PC time series of mean November through

March de-trended SST anomalies for the Pacific Ocean to

the north of 20�N using Met Office Historical SST data

(Parker et al. 1995) for 1900–1981 and the Optimum

Table 1 Datasets utilized in

this studyHorizontal

resolution

Range of

years

Source

Surface air

temperature

(Univ. of Delaware)

0.5� 9 0.5� 1900–2008 http://jisao.washington.edu/data_sets/ud

ERA-40 2.5� 9 2.5� 1957–2002 Uppala et al. (2005)

ERA-Interim 1.5� 9 1.5� 1979–2010 Simmons et al. (2006)

ERSSTv3b 2.0� 9 2.0� 1854–2010 Smith et al. (2008)

ENSO index 1868–2010 http://coaps.fsu.edu/jma.shtml

PDO index 1900–2010 http://jisao.washington.edu/data_sets/pdo/

Combined effect of El Nino-Southern Oscillation 959

123

Interpolation SST (OISST) version 2 (Reynolds et al. 2002)

for 1982–2010. Because the PDO is a largely interdecadal

oscillation, an 11-year running average was performed

utilizing reflective conditions to extract a decadal vari-

ability of the PDO. Positive (negative) PDO phases cor-

respond to a case in which the 11-year running mean PDO

index is above (below) zero.

The classification of years according to the phases of the

ENSO and PDO for the period of 1900–2010 is shown in

Table 2. Over this time period, 28 El Nino, 31 La Nina, and

52 neutral years occurred along with 59 positive and 52

negative PDO years. For convenience, El Nino, La Nina,

and neutral years will be denoted as EN, LN, and Neu,

respectively. Further, El Nino combined with a positive

(negative) PDO phase will be referred to as

EN ? Pos_PDO (EN ? Neg_PDO). Similarly, La Nina

and neutral combined with a positive (negative) PDO phase

will be referred to as LN ? Pos_PDO (LN ? Neg_PDO)

and Neu ? Pos_PDO (Neu ? Neg_PDO), respectively.

Note that the winter used in this study is designated as the

time during the months of December, January, and Feb-

ruary (DJF) and the year of 1901, for example, refers to the

boreal 1900/1901 winter. Anomalies are presented as val-

ues after removing the monthly-mean climatology data for

the whole period. The regression and composite analyses

are mainly carried out and a statistical significance is

assessed using a two-tailed student’s t test at different

confidence levels (Wilks 2006). To obtain the effective

number of degrees of freedom (EDOF), in addition, we use

the methodology following Davis (1976). Note that the

EDOF is also calculated by the way suggested by Krish-

namurthy and Kirtman (2009) and it reaches the similar

results in comparison with those based on Davis (1976).

3 Results

3.1 Individual effect of ENSO and PDO

The aforementioned ENSO and PDO indices averaged for

the winter from 1900 to 2010 are shown in Fig. 1. The thin

lines indicate unfiltered values and the thick lines represent

the decadal components, which are obtained by an 11-years

running mean method. As stated, the ENSO index is the

most dominant on interannual timescales around a peak

period of 3–7 years, thereby there are little variations on

decadal timescales owing to the strong interannual vari-

ability. Meanwhile, the PDO index has a significant peak

over a broad range from the interannual to multidecadal

timescales as confirmed by the thin line of Fig. 1b. It has

been known that the interannual variations of the PDO are

likely to be associated with the ENSO variability (e.g., Lau

and Nath 1994). In fact, the temporal correlation coefficient

(r) between unfiltered ENSO and PDO indices for the

110 years is 0.43, exceeding a 99 % confidence level. On

the other hand, the 11-years running mean PDO index (i.e.,

decadal component of the PDO) is scarcely related to the

unfiltered ENSO index (r = 0.17). Therefore, the decadal-

varying PDO index could be considered as an independent

variability differently from the ENSO variability. As pre-

viously noted, the purpose of this study is to investigate the

interdecadal PDO modulation effect on the ENSO–EAWM

relationship, therefore, using the 11-years running mean

PDO index is reasonable to represent the interdecadal PDO

modulation. Thus, the PDO index hereafter indicates the

11-years running mean PDO index, whereas the ENSO

index indicates the unfiltered ENSO index [cf. interannual

ENSO index, which is calculated by 10-years high pass

filtering method, is mostly the same with the unfiltered

ENSO index (r = 0.94)].

Regression maps with respect to the ENSO index using

the sea level pressure (SLP), the geopotential height at

500-hPa (Z500), and the zonal wind component at 200-hPa

(U200) during the winter are depicted in Fig. 2a, c and e,

while the regression maps with respect to the PDO index

using the same parameters are displayed in Fig. 2b, d and f.

A typical Pacific-North American (PNA; Wallace and

Gutzler 1981; Horel and Wallace 1981) pattern is evident

in the form of a linear-stationary Rossby wave train asso-

ciated with the ENSO (Fig. 2a, c). On the other hand, the

regressed SLP and Z500 against the PDO index are likely

to be more associated with the variability of Aleutian Low

Table 2 Classification of years based on the phases of the ENSO and PDO for the period of 1900–2010

Positive PDO Negative PDO

El Nino 1900, 1903, 1905, 1906, 1926, 1930, 1931, 1941, 1983, 1987, 1988,

1992, 1998, 2003

1912, 1914, 1919, 1920, 1952, 1958, 1966, 1969, 1970, 1973,

1977, 1995, 2007, 2010

Neutral 1901, 1902, 1908, 1922, 1924, 1925, 1927, 1928, 1929, 1932, 1933,

1934, 1935, 1936, 1937, 1940, 1942, 1944, 1979, 1980, 1981,

1982, 1984, 1986, 1990, 1991, 1993, 1997, 2001, 2002, 2005

1913, 1915, 1947, 1948, 1949, 1951, 1953, 1954, 1957, 1959,

1960, 1961, 1962, 1963, 1964, 1967, 1972, 1978, 1994, 2004,

2009

La Nina 1904, 1907, 1909, 1910, 1911, 1923, 1938, 1939, 1943, 1985, 1989,

1999, 2000, 2006

1916, 1917, 1918, 1921, 1945, 1946, 1950, 1955, 1956, 1965,

1968, 1971, 1974, 1975, 1976, 1996, 2008

The year of 1901, for example, refers to the boreal 1900/1901 winter

960 J.-W. Kim et al.

123

over the central North Pacific (Fig. 2b, d). In addition, the

ENSO is not closely related to the variability of the Asian

jet stream, at least in a linear sense, when compared to that

of the PDO (Fig. 2e, f). In spite of such differences, it is

suggested that the atmospheric circulation patterns are

broadly analogous in response to the both ENSO and PDO

indices, indicating that a combined effect of the ENSO and

PDO has a potential to significantly modify the winter

climate variability on the globe through its teleconnections.

To clarify the influence of the ENSO and PDO on the

East Asian winter climate, we use long-term monthly mean

SAT data obtained from the University of Delaware

(hereafter, UD_SAT data) during the period from 1900 to

2008 (cf. Table 1). The spatial structure of the regressed

SAT against the ENSO index indicates the influence of El

Nino (La Nina), which induces anomalously warmer

(colder) winter climate in East Asia as shown in Fig. 3a. In

other words, a mature phase of El Nino (La Nina) leads to a

relatively weaker (stronger) than normal EAWM; this

result is consistent with the findings of many previous

studies (Zhang et al. 1996; Kang and Jeong 1996; Ji et al.

1997; Tao and Zhang 1998). More specifically, regions

showing significant positive values are broadly separated

into two areas: the Southeast Asia around 20�N and the far

eastern countries including Korea, Japan, and some areas in

northern China. Central and eastern China near 30�N

exhibit weak positive values, but these are statistically

insignificant at a 95 % confidence level. Figure 3b is the

same as Fig. 3a, except that the regressed SAT is shown

with respect to the PDO index. One can find that significant

positive values are largely displayed almost all over the

East Asian countries except Korea and Japan where they

show significant negative values, presumably affected by

the thermal advection from the PDO-related cold SST

anomalies in their adjacent seas.

Collectively, the effect of the PDO is also influential in

the mid-latitude on the low-frequency and the East Asian

winter climate could be significantly affected by the

combination of the ENSO and PDO phase. For consistency,

we compute the same regression maps using the combined-

ERA data; the results are almost the same as the UD_SAT

data despite the different time period used for the analysis

(not shown).

3.2 Combined effect of ENSO and PDO

A conditional composite analysis for the six categories (i.e.,

Neu ? Pos_PDO, Neu ? Neg_PDO, EN ? Pos_PDO,

EN ? Neg_PDO, LN ? Pos_PDO, and LN ? Neg_PDO,

see Sect. 2.2 for a more detailed explanation), which is

based on the phase relationship of ENSO–PDO, is con-

ducted to identify the combined effect of the ENSO and

PDO over East Asia (Fig. 4a–f). It should be noted that the

analysis period starts in January 1958 in order to coincide

with the period of the combined-ERA data. Figure 4a, b

show the composites of anomalous winter SAT in positive

and negative PDO phases excluding ENSO years (see

neutral years in Table 2), respectively, which are regarded

as a pure PDO effect. One can find that the anomalous SAT

over East Asia, which is influenced by the PDO only, is

negligible except in the northwestern part of China where it

shows significant warm and cold anomalies in statistics. On

one hand, the combined effects of the ENSO and PDO are

shown in Fig. 4c–f. It is evident that the anomalous SAT is

more significant under in-phase combinations of the ENSO

and PDO (Fig. 4c, f; i.e., El Nino/positive PDO phase and

La Nina/negative PDO phase) when compared to out-of-

phase combinations (Fig. 4d, e; i.e., El Nino/negative PDO

phase and La Nina/positive PDO phase). In other words, the

EN ? Pos_PDO (LN ? Neg_PDO) composite leads to an

obvious warmer (colder) than normal winter condition in

East Asia, while the EN ? Neg_PDO and LN ? Pos_PDO

composites do not show any prominent anomalous SAT.

Therefore, it is clear that the intensity of the EAWM is

significantly weakened (strengthened) when El Nino (La

Nina) occurs with a positive (negative) PDO phase in terms

of temperature. However, a combined effect of the ENSO

and PDO under out-of-phase conditions does not exert a

strong influence on the EAWM. Likewise, these combined

effects on East Asia are almost identical even if the analysis

period is extended to the period of 1900–2008 (not shown).

Fig. 1 a The ENSO index provided by the Japan Meteorological

Agency averaged for December–February (DJF) during the period of

1900–2010. b Same as a, but for the PDO index provided by the

University of Washington. The thin lines indicate unfiltered indices of

them and the thick lines represent the decadal components, which

describe an 11-years running average. A detailed description of each

index is given in Sect. 2.2

Combined effect of El Nino-Southern Oscillation 961

123

Furthermore, we conduct the same conditional composite

using a long-term high resolution (0.5� 9 0.5�) global pre-

cipitation data, which is also provided by University of Del-

aware as in the UD_SAT data (not shown). It is found that

there exist the significant changes in the amount of rainfall

over the southern China under in-phase relationship of

ENSO–PDO. On the contrary, such contrast of rainfall amount

is very weak under out-of-phase relationship of ENSO–PDO.

These results are largely consistent with the results in Fig. 4.

3.3 Possible interpretations

To uncover a physical mechanism for the combined effect

of the ENSO and PDO, we compute the differences

between the in- and out-of-phase ENSO and PDO com-

posites using the winter SST, SLP, and the horizontal wind

at 850-hPa (UV850), respectively. In other words, Fig. 5a,

c and e indicate the difference between El Nino with a

positive PDO phase and La Nina with a negative PDO

Fig. 2 Regression maps of the DJF (a) sea level pressure (SLP, in

hPa), c geopotential height at 500-hPa (Z500, in m), and e zonal wind

component at 200-hPa (U200, in m/s) with respect to the ENSO

index. b, d and f are the same as a, c and e, but with respect to the

11-years running mean PDO index. Areas with black dots indicate a

95 % confidence level according to a two-tailed student’s t test. For

the persistent nature of the low-frequency PDO index, the effective

number of degrees of freedom (EDOF) proposed by Davis (1976) is

used

962 J.-W. Kim et al.

123

phase (i.e., EN ? Pos_PDO minus LN ? Neg_PDO). In

contrast, the difference between El Nino with a negative

PDO phase and La Nina with a positive PDO phase (i.e.,

EN ? Neg_PDO minus LN ? Pos_PDO) is illustrated in

Fig. 5b, d and f. Note that the significance test for the

UV850 is assessed using a 90 % confidence level as dif-

ferent as other variables.

In the extratropics, both the in- and out-of-phase dif-

ference composites of SST (Fig. 5a, b) are characterized by

cold SST anomalies centered at 155�W and 30�N and

warm SST anomalies around the west coast of North

America. Meanwhile, strong warm SST anomalies extend

from the eastern tropical Pacific to the central tropical

Pacific, indicating that it represents a typical structure of El

Nino event. The western North Pacific (WNP) region

(5–35�N, 120–170�E; black rectangle in Fig. 5a) exerts a

dipole-like structure of warm and cold SST anomalies in

the in-phase difference composite. In contrast, there is no

significant anomalous warm SST in the WNP region in the

out-of-phase difference composite (Fig. 5b), which is dif-

ferent in comparison with the in-phase difference com-

posite. This result suggests a possibility that the WNP is a

notable region in modulating the EAWM regarding the

combined effect of the ENSO and PDO.

As expected, the spatial structures of atmospheric cir-

culations are also quite different in the in- and out-of-phase

differences (Fig. 5c–f). Massive anticyclonic circulation

anomalies (i.e., high pressure anomalies) cover both the

tropics and mid-latitudes from the western to central North

Pacific, almost expanding to 50�N and 150�W in the in-

phase difference SLP composite (Fig. 5c). Indeed, the

extent of the anticyclonic anomalies is much larger and

expands northward compared to that of the out-of-phase

difference composite (Fig. 5d). These well-developed

anomalous anticyclones effectively induce southerly wind

anomalies at the lower-tropospheric level, which can in

turn transport warm and moist air toward the East Asian

winter continent. Consistently, in-phase difference com-

posite of UV850 demonstrates the enhanced low-level

southerly wind anomalies initiating around 15�N and

110�E that follow the contour lines in the western flank of

the anomalous anticyclonic circulations over the western

Pacific (Fig. 5e). Because of these structures, the winter

climate in East Asia is most likely to be warmer and wetter

than normal, resulting in a weakening of the EAWM. On

the other hand, the anticyclonic anomalies in the out-of-

phase difference of UV850 are drastically confined to the

tropics so that southerly wind anomalies turn eastward

towards the subtropical western and central North Pacific

(Fig. 5f). As such, there is little impact on the EAWM

when the ENSO and PDO are combined with the out-of-

phase, regardless of the El Nino and/or La Nina events

which would induce the Pacific-East Asian teleconnection

pattern. Therefore, these results indicate that the PDO

contributes to the strength of the WNP anticyclone by

overlapping its effects on ENSO on the low-frequency

timescales.

To understand the role of the PDO in the development

and maintenance of the WNP anticyclone, we calculate the

regressed SST anomalies against with the PDO index for

the period of 1900–2010 (Fig. 6a). The spatial manifesta-

tions of the positive PDO phase are characterized by cold

SST in the western and central North Pacific with an

elliptical shape and are accompanied by warm SST in the

Fig. 3 a Regression map of the DJF surface air temperature (SAT, in

�C) provided by the University of Delaware with respect to the ENSO

index. b Same as a, but with respect to the 11-year running mean

PDO index. Areas with black dots indicate a 95 % confidence level

according to a two-tailed student’s t test

Combined effect of El Nino-Southern Oscillation 963

123

Fig. 4 Conditional composite maps of the DJF surface air temper-

ature (SAT, in �C) anomalies in the East Asian continent for the case

of a Neu ? Pos_PDO, b Neu ? Neg_PDO, c EN ? Pos_PDO,

d EN ? Neg_PDO, e LN ? Pos_PDO, and f LN ? Neg_PDO. Areas

with black dots indicate a 90 % confidence level according to a two-

tailed student’s t test

964 J.-W. Kim et al.

123

tropical and subtropical Pacific. In particular, there exists a

dipole-like pattern of anomalous warm and cold SSTs in

the WNP, which is associated with the anomalous high

pressure over the same region as shown in Fig. 2b. The

anomalous high pressure over the WNP reflects the

enhanced (reduced) total wind speed in its east (west) side,

resulting in the cold (warm) SST through the evaporation

and entrainment processes. Furthermore, the anomalous

cold SST is able to favor the amplification of anomalous

anticyclone by exciting Rossby waves (Wang et al. 2000).

Thus, the positive feedback between the anomalous anti-

cyclonic circulation and SST associated with the positive

phase of PDO over the WNP may play a role in the

development and maintenance of the surface wind and SST

anomalies. It is noteworthy that the physical processes on

the strengthening of anticyclone over the WNP under the

positive PDO phase are similar to the physical mechanism

of the Pacific-East Asian teleconnection under El Nino

Fig. 5 Difference composite maps of the DJF (a) sea surface

temperature (SST, in �C), c sea level pressure (SLP, in hPa), and

e 850-hPa wind (UV850, in m/s) between the cases of

EN ? Pos_PDO and LN ? Neg_PDO (i.e., in-phase difference). b,

d and f are the same as a, c and e, respectively, but for the

EN ? Neg_PDO and LN ? Pos_PDO (i.e., out-of-phase difference).

Areas with black dots indicate a 95 % confidence level and thick

vectors are significant at a 90 % confidence level according to a two-

tailed student’s t test

Combined effect of El Nino-Southern Oscillation 965

123

condition suggested by Wang et al. (2000) except but the

temporal scale. This might be from that the PDO has

similar signature of ENSO, in particular, over the WNP

(Figs. 2a, b, 6b). Therefore, the differences of the spatial

structures of atmospheric circulations in the difference

composite maps of ENSO–PDO combinations (see

Fig. 5c–f) are mainly due to the overlapping of PDO’s

effect on ENSO on the low-frequency timescales.

We further examine the detailed evolution of SLP

anomalies in conjunction with the underlying SST anomalies

in the different phase combinations of ENSO and PDO.

Figure 7 describes longitude-time diagrams for the monthly

variations of SST and SLP anomalies averaged over

25–35�N in the composites of El Nino with positive and

negative PDO phases (i.e., EN ? Pos_PDO and

EN ? Neg_PDO). Note that the same analysis in different

latitudinal bands over the WNP results in a similar feature

(not shown). One of the salient features of the

EN ? Pos_PDO composite is that the cold SST anomalies

during summer to early fall (JASO(0)) in the El Nino-

developing period may induce the anomalous high pressure

during late fall/early winter (OND(0)) and then such anom-

alous high pressure is associated with the anomalous warm

SST during the following winter (D(0)JF(?1)) and spring

(MAM(?1)) (Fig. 7a), which is indicative of the positive

feedback processes as discussed above. However, in the

EN ? Neg_PDO composite (Fig. 7b), the monthly varia-

tions of the SST and SLP anomalies are commonly sup-

pressed compared to those in the EN ? Pos_PDO

composite. The high SLP anomalies are not well-established

during early winter and coarsely located in the east of 140�E

with changing time, meaning that the anomalous anticyclone

is not effective in modulating the intensity of the EAWM.

Thus, the anomalous warm SST during the following winter

and spring also weakens and disappears early. Similarly, the

composites of La Nina with two different PDO phases

exhibit the same result except for the reserved signs (not

shown). Consequently, we assert that a well-developed

anomalous anticyclonic (cyclonic) circulation over the WNP

as El Nino (La Nina) occurs with positive (negative) PDO

phase leads to a weakened (strengthened) EAWM. Chen

et al. (2013) also argued that when the EAWM is related to

the ENSO during the positive PDO phase, the anomalous

WNP anticyclone is strong with a large domain including not

only western Pacific but also the northern Pacific. However,

when the EAWM is related to the ENSO during the negative

PDO phase, the anomalous WNP anticyclone is relatively

weaker showing a weakened Aleutian low. It reaffirms that

the different PDO phases have an influence on the develop-

ment and maintenance of the WNP anticyclone in connection

with the ENSO and EAWM.

To corroborate the assertion more practically, we

quantitatively measure the extent of the WNP anticyclone

by using the winter Z500 distribution because the anticy-

clone contains a considerable barotropic component.

Indeed, Fig. 8 reveals the extents of the WNP anticyclones

as delineated by the 5,860-gpm contour lines for the in- and

out-of-phase relationships of the ENSO and PDO. Note

that the thin solid lines in Fig. 8 represent climatological

5,860-gpm contour lines for the winter period of

1958–2010. In the in-phase composites (Fig. 8a), it is

apparent that the assumed size of the WNP anticyclone in

the EN ? Pos_PDO (thick solid) is much larger when

compared to that in the LN ? Neg_PDO (thick dashed).

Specifically, the 5,860-gpm line of the EN ? Pos_PDO

covers most of the subtropical WNP region including the

South China Sea and the Philippine Sea, while that of the

LN ? Neg_PDO is only in an isolated area near 15�N and

155�E. In other words, the WNP anticyclone largely

expands in the EN ? Pos_PDO but visibly shrinks in the

LN ? Neg_PDO in comparison with the climatological

WNP anticyclone. Such a huge difference can give rise to

an intensification of the negative relationship between

ENSO and EAWM. On the other hand, in the out-of-phase

composites (Fig. 8b), there is no large difference in the

sizes of the WNP anticyclones in comparison with the

climatological 5,860-gpm contour line, which is associated

with a weakening of the ENSO–EAWM relationship.

Fig. 6 Regression map of the DJF sea surface temperature (SST, in

�C) against the PDO index for the period of 1900–2010. b Same as a,

but with respect to the ENSO index. Areas with black dots indicate a

95 % confidence level according to a two-tailed student’s t test

966 J.-W. Kim et al.

123

Finally, we conduct four numerical experiments to

examine the influence of SST forcings due to the combined

effect of the ENSO and PDO. Those are EN ? Pos_PDO

run, EN ? Neg_PDO run, LN ? Pos_PDO run, and LN ?

Neg_PDO run. In each experiment, the ERSSTv3b is car-

ried out as prescribed SST boundary over the entire Pacific

Ocean (20�S–70�N, 100�E–70�W) based on the SST

composite in case of EN ? Pos_PDO, EN ? Neg_PDO,

LN ? Pos_PDO, and LN ? Neg_PDO, respectively. The

areas outside of the Pacific Ocean are prescribed with the

climatological SST. Each experiment is integrated for

10 years with four ensemble members and the last 5 years

of simulation result is analyzed. Atmospheric general cir-

culation model (AGCM) in the Global/Regional Integrated

Model system (GRIMs; Hong et al. 2013), whose hori-

zontal resolution is T62 (approximately 200 km) and ver-

tically 28 layers, is used for the experiments. The physics

of the model include long- and short- wave radiations,

cloud-radiation interactions, planetary boundary layer

(PBL) processes, shallow convection, gravity wave drag,

simple hydrology, land surface processes, and vertical and

horizontal diffusions.

We display the winter SAT, SLP, and SST anomalies for

the experiments of EN ? Pos_PDO run and EN ?

Neg_PDO run, respectively, in Fig. 9a–f. It is found that

the anomalous SAT over East Asia has a difference

between the EN ? Pos_PDO run and EN ? Neg_PDO

run, which is similar to the observations. In the

EN ? Pos_PDO run, for example, anomalous warm SAT

is dominant over East Asia, including its marginal seas and

the western Pacific. In contrast, such warming is weakened

in the EN ? Neg_PDO run except the inland areas of

China. This result indicates that the intensity of the EAWM

is largely modulated by the SST forcing in relation to the

ENSO–PDO phase relationship. In particular, there exist

strong anticyclonic circulation anomalies near the Philip-

pine Sea which can bring warmer and moist air into the

East Asian winter continent via southerly wind anomalies

along the western flank of the anticyclone in the

EN ? Pos_PDO run (Fig. 9c). However, the anticyclone is

fairly weakened in the EN ? Neg_PDO run (Fig. 9d),

decreased by about 30 % of the maximum SLPs. Given the

AMIP-type experiments, such differences in both experi-

ments are essentially due to the underlying SST boundary

forcings as shown in Fig. 9e, f. That is, a dipole-like

structure of warm and cold SST anomalies in the western

Pacific is obvious in the EN ? Pos_PDO run, while it is

weak in the EN ? Neg_PDO run. As discussed above, the

dipole-like pattern of anomalous SST is associated with the

positive feedback for development and maintenance of the

Fig. 7 Longitude-time diagrams of sea surface temperature (SST,

shadings at 0.1�C interval) and sea level pressure (SLP, contours at

0.5 hPa interval) averaged over 25–35�N for the composites of

a EN ? Pos_PDO, and b EN ? Neg_PDO. The vertical axis is the

lagged time (month) starting from May of the El Nino development

year (Year 0) to September of the following year (Year ? 1). The

negative contours are dashed and the zero contours are suppressed in

all plots

Combined effect of El Nino-Southern Oscillation 967

123

surface wind and SSTs over the WNP region so that the

difference of the spatial structures of SST anomalies due to

the PDO phase difference plays an important role in

modulating the intensity of the EAWM through the chan-

ges of atmospheric circulation. In comparison with the

EN ? Pos_PDO run and EN ? Neg_PDO run, significant

differences are not found in case of LN ? Pos_PDO run

and LN ? Neg_PDO run, however, there still exists a

difference of atmospheric circulation over the WNP due to

the underlying SST boundary forcing (not shown).

4 Summary and discussion

This study explored the combined effect of the ENSO and

PDO on the variability of the EAWM and its associated

mechanism by analyzing long-term observational data and

numerical model experiments. For this purpose, we firstly

clarified the individual influences of the ENSO and PDO

on the East Asian winter climate using the regression

analysis. It was found that the atmospheric regressed pat-

terns are broadly analogous in response to the ENSO and

PDO indices over the East Asian region, indicating that a

combined effect of the ENSO and PDO has a potential to

modify the East Asian winter climate variability.

In order to identify the combined effect of the ENSO

and PDO on the EAWM, we conducted a conditional

composite analysis of SAT over East Asia by means of the

six group categories for the ENSO and PDO phase:

Neu ? Pos_PDO, Neu ? Neg_PDO, EN ? Pos_PDO,

EN ? Neg_PDO, LN ? Pos_PDO, and LN ? Neg_PDO

(cf. Table 2). As a result, it was found that when the ENSO

and PDO are combined with the in-phase relationship (i.e.,

El Nino/positive PDO phase and La Nina/negative PDO

phase), a negative relationship between ENSO and EAWM

is significantly intensified. In other words, when El Nino

(La Nina) occurs with positive (negative) PDO phase

during the boreal winter, anomalous warm (cold) temper-

atures over the East Asian continent are dominant. How-

ever, there were no significant temperature anomalies over

East Asia when the ENSO and PDO are combined with the

out-of-phase relationship (i.e., El Nino/negative PDO

phase and La Nina/positive PDO phase). Therefore, it is

recognized that the decadal-varying low-frequency PDO

variability can constructively or destructively contribute to

the ENSO–EAWM relationship.

Further analyses indicated that the anticyclone over the

WNP including the East Asian marginal seas plays an

essential role in modulating the intensity of the EAWM

under the changes of ENSO–PDO phase relationship. The

positive feedback between anomalous high SLP and warm

SST over the WNP during late fall/winter and following

spring, which occurred during the El Nino with positive

PDO phase, can lead to a weakened EAWM by trans-

porting anomalous warm and wet conditions into the East

Asian continent along with the southerly wind anomalies,

and vice versa during the La Nina with negative PDO

phase. In contrast, there were little visible anomalous high

SLP and warm SST structures when the ENSO and PDO

are under the out-of-phase, indicating that the intensity of

the EAWM is likely to be invariant. That is, the intensity of

the EAWM is largely affected by the changes in the

strength of the anticyclone over the WNP, which is asso-

ciated with the underlying SST in relation to the ENSO–

PDO phase relationship. In fact, the extent of the WNP

anticyclone depicted by the 5,860-gpm contour line

showed an obvious difference under the in-phase combi-

nations of the ENSO and PDO. In the case of the

EN ? Pos_PDO, the WNP anticyclone was remarkably

enhanced, covering most of the subtropical WNP region

including the South China Sea and the Philippine Sea.

However, the WNP anticyclone was prominently

Fig. 8 The DJF 500-hPa

geopotential height (Z500, in m)

composite, indicated by a 5,860-

gpm contour line, for a the in-

phase cases: EN ? Pos_PDO

(thick solid) and

LN ? Neg_PDO (thick

dashed); and b the out-of-phase

cases: EN ? Neg_PDO (thick

solid) and LN ? Pos_PDO

(thick dashed). The thin solid

lines represent DJF

climatological 5,860-gpm

contour line for the period of

1958–2010

968 J.-W. Kim et al.

123

weakened in the case of the LN ? Neg_PDO. On the other

hand, there was little difference for the strength of the

WNP anticyclone between the out-of-phase ENSO and

PDO combinations, resulting in there is no significant

changes in the intensity of the EAWM according to the

ENSO events (i.e., El Nino and La Nina). In addition, the

numerical experiments using the AGCM also supported our

findings. The prescribed SST forcing over the Pacific

Ocean generated by the EN ? Pos_PDO run induced a

strong anticyclonic circulation near the Philippine Sea and

then leads to warm SAT anomalies over East Asia followed

as the physical mechanism we proposed. However, in the

EN ? Neg_PDO run, the strength of the WNP anticyclone

was weaker and the warm SAT anomalies over East Asia

also diminished.

Despite the distinct combined effect of the ENSO and

PDO on the EAWM variability, there still have been

questions about how robust the effect is because the

EAWM can be influenced by many factors other than the

strength of the WNP anticyclone. In particular, the secular

warming in the northern Indian Ocean has recently been

discovered to have a much larger impact on East Asian

Fig. 9 The DJF a surface air temperature (SAT, in �C), c sea level

pressure (SLP in hPa), and e sea surface temperature (SST in �C)

anomalies for the EN ? Pos_PDO run simulated by the prescribed

SST forcing over the entire Pacific Ocean from AGCM. b, d and f are

the same as a, c, and e but for the EN ? Neg_PDO run. Positive

(negative) values are denoted as solid (dashed) lines with suppressed

zero values. Contour intervals are 0.2 �C in SAT and SST and 0.4 hPa

in SLP, respectively

Combined effect of El Nino-Southern Oscillation 969

123

climate variability, including the EAWM (Watanabe and

Jin 2002; Watanabe and Jin 2003; Annamalai et al. 2005;

Yang et al. 2007). The persistence of El Nino-induced

warm SST anomalies in the northern Indian Ocean could

be another important factor to form the WNP anticyclone

with emanating a Kelvin wave propagating into the WNP

(cf. the Indian Ocean capacitor mechanism; Xie et al.

2009). Furthermore, the WNP anticyclone can persist until

summer through the Kelvin wave-induced Ekman diver-

gence mechanism, thereby influencing on the variability of

the East Asian summer monsoon. This long-term persis-

tence of the WNP anticyclone is quite similar to our results

as shown in Fig. 7. Thus, the influence of the northern

Indian Ocean warming in conjunction with the combined

effect of the ENSO and PDO should be investigated in a

future study.

Acknowledgments This work was supported by the National

Research Foundation of Korea Grant funded by the Korean Govern-

ment (MEST) (NRF-2009-C1AAA001-2009-0093042). S.-W. Yeh

was funded by the Korea Meteorological Administration Research

and Development Program under Grant CATER 2012–3041.

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