Journal of the Meteorological Society of Japan, Vol. 90A, pp. 123--136, 2012.

123

DOI:10.2151/jmsj.2012-A06

Future Changes of Yamase Bringing Unusually Cold Summers
over Northeastern Japan in CMIP3 Multi-Models

Hirokazu ENDO
Meteorological Research Institute, Tsukuba, Japan(Manuscript received 26 April 2011, in ﬁnal form 31 August 2011)

Abstract
Northeasterly winds blowing from high latitudes of the North Paciﬁc in boreal summer, including the Sea of
Okhotsk and the Bering Sea, are called the ‘‘Yamase’’ in Japanese. The Yamase brings unusually cold and cloudy
summers over northeastern Japan, in contrast to climatological southeasterly winds, having great impact on agriculture and life in the region. Therefore, future changes of the Yamase, which may be caused by global warming,
are a major concern.
This study is the ﬁrst attempt to investigate future changes of Yamase frequency, which are deﬁned using 10day mean surface winds, by analyzing eighteen coupled atmosphere-ocean general circulation model (AOGCM)
experiments for May to August in the CMIP3 archives. We ﬁrst assess present-day climate experiments (1981–
2000, 20C3M) and then examine the changes in future climate (2081–2100, SRES A1B scenario). In the presentday climate, an eighteen multi-model ensemble (MME18) mean modestly reproduces seasonal variation of the
Yamase frequency, although each model generally underestimates the Yamase frequency compared to the reanalysis data and large di¤erences are seen among the models. In the future climate, most models project increases of
the Yamase frequency in August in contrast to decreases of the frequency in May, whereas projected frequencychanges in June, July and May to August (MJJA) are inconsistent among the MME18. Inter-model comparison
suggests that weakening of mean tropical circulation, including the Walker circulation, may contribute to theincreased Yamase frequency in August. A projection employing only nine of the models with higher skill(MME9hi), based on a deﬁned metric, is also tried. Negative anomalies in June over the Sea of Okhotsk and eastern Siberia in the mean sea level pressure ﬁeld are contrasted with positive anomalies in July, which are unclear in
the MME18 projections. In August, almost all the MME9hi project increase of the Yamase frequency, consistent
with the MME18 projections.

1. Introduction
Northeasterly winds blowing from high latitudesof the North Paciﬁc in boreal summer are called
the ‘‘Yamase’’ in Japanese. The Yamase brings unusually cold and cloudy summers to northeasternJapan, in contrast to climatological southeasterly
winds (Ninomiya and Mizuno 1985), having great
impact on agriculture and life in the region. Therefore, future changes of the Yamase, which may be
Corresponding author: Hirokazu Endo, Climate Research Depertment, Meteorological Research Institute,
1-1 Nagamine, Tsukuba, Ibaraki, 305-0052, Japan.
E-mail: hendo@mri-jma.go.jp
6 2012, Meteorological Society of Japancaused by global warming, are a major concern
across the region.
The origin of the Yamase is the cold polar maritime air mass formed over the high latitudes ofNorth Paciﬁc, including the Sea of Okhotsk andthe Bering Sea (Ninomiya and Mizuno 1985; Kodama 1997). In boreal summer, the Yamase sometimes blows toward northeastern Japan, typicallyunder a surface pressure pattern in which an anticyclone, called the Okhotsk high, stagnates aroundthe Sea of Okhotsk, and a front and/or a cyclone
stay over southern coast of Japan or the ocean eastof Japan (Ninomiya and Mizuno 1985; Kanno
1997), as shown in Fig. 1a. This anomalous pressure pattern is often accompanied by a blocking

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Fig. 1. A typical Yamase event on 22 June
2008. (a) The surface weather chart for
00UTC (09JST) on 22 June 2008 produced
by Japan Meteorological Agency. (b) The
MTSAT visible image at 03UTC (12JST)on 22 June 2008.

ﬂow in the upper troposphere and sometimes persists for a week or more (Nakamura and Fukamachi 2004). Air masses transported southward by the
Yamase become wet and are usually accompanied
by marine boundary layer clouds owing to anabundant supply of moisture from the ocean as the
air mass approaches Japan (Kodama 1997; Fig 1b).
Thus, continuous Yamase occurrences bring anomalously cold and cloudy summers over northeasternJapan. In interannual time scales, the anomalous
large-scale circulation providing background for
frequent Yamase occurrence is formed not only by
extra-tropical factors such as eastward propagationof a stationary Rossby wave along the polar frontaljet (Nakamura and Fukamachi 2004; Tachibana
et al. 2004; Wakabayashi and Kawamura 2004)
but also by tropical factors such as El Nino/
Southern oscillation (ENSO) with both simultane-

Vol. 90A

ous and lagged e¤ects (Wang et al. 2001; Kanno
2004; Tachibana et al. 2004; Yasunaka and Hanawa 2006).
For predicting climate changes caused by anthropogenic forcing, multi-model ensemble (MME)
methods utilizing coupled atmosphere-ocean general circulation model (AOGCM) outputs havebeen widely applied because the MME method ise¤ective for improving the projection due to reduction of biases and uncertainties of individual models (Giorgi and Mearns 2002; Min et al. 2004) andfor estimation of the robustness of the projectedchanges (Kitoh and Uchiyama 2006; Inoue andUeda 2011). For the East Asian summer, several
studies have projected future changes by theanthropogenic forcing based on the MME. Min
et al. (2004) applied weighted MME averages basedon each model’s skill to simulate present climate to
Phase 2 of the Coupled Model Intercomparison
Project (CMIP2) models, and obtained increased
precipitation and raised temperature over East
Asia in the future climate. Kimoto (2005) revealed
increased Meiyu-Changma-Baiu activity associatedwith the strengthening of anticyclonic cells to thesouth and north of East Asia, based on a simple
MME average of multiple AOGCM experimentsin the CMIP3 datasets. Kitoh and Uchiyama(2006) found a delay in the early summer rain withdrawal over the region extending from Taiwan to
the Ryukyu Islands to the south of Japan, throughthe weighted MME average of multiple AOGCM
simulations in the CMIP3 archives.
In addition to the AOGCMs, high-resolution atmospheric general circulation models (AGCM) andregional climate models (RCM) have been employed for use in the climate change study in orderto derive information about extreme phenomena
and regionally localized phenomena. Kusunoki
et al. (2006) and Kusunoki and Mizuta (2008) investigated future changes in the Baiu rain band
based on 20-km mesh AGCM experiments, and derived results consistent with the above ﬁndings.
Endo (2008) investigated a 20-km mesh RCM simulation for Japan (Kurihara et al. 2005), nested by
MRI-CGCM2 under the SRES A2 scenario, focusing on the Yamase phenomenon. He found thatYamase-type low temperature events, deﬁned byan east-west surface temperature di¤erence overthe northern Tohoku district, increase from late
July to early August in the future climate.
These previous studies hint that the Yamasemight be inﬂuenced by global warming, however,February 2012

H. ENDOthe Yamase has not yet been directly investigated in
the AOGCM simulations. Therefore, in this study,
we ﬁrst assess the Yamase in present-day climate
experiments, and then examine its changes in futureclimate experiments based on the MME in the
CMIP3 model outputs, and then discuss factors affecting the projected changes.
2. Data and deﬁnition of Yamase
We analyze daily outputs for the present-day(1981–2000) under the 20C3M simulation and forthe end of the twenty-ﬁrst century (2081–2100)
under the SRES A1B scenario simulation in the
CMIP3 dataset. We select the models that have
daily surface wind and sea level pressure dataarchives for those periods. The following eighteen AOGCMs are included in the analysis:
CGCM3.1(T47), CGCM3.1(T63), CNRM-CM3,
CSIRO-MK3.0, CSIRO-MK3.5, GFDL-CM2.0,
GFDL-CM2.1, GISS-AOM, GISS-ER, FGOALSg1.0, INM-CM3.0, MIROC3.2(hires), MIROC3.2(medres), ECHAM5/MPI-OM, MRI-CGCM2.3.2,
INGV-ECHAM4, IPSL-CM4 and ECHO-G. Only
one member (the ﬁrst member) of each model isused, even for models with multi-member data
available. The daily data are ﬁrst interpolated into
common 2.5 latitude by 2.5 longitude horizontal
grids, and then temporally averaged. Three models#16, #17 and #18 (ID numbers shown in Table 1)
use a 360 day annual calendar, and therefore we assume the three models have 30 days in each month.
For evaluation of the model outputs, JRA-25 reanalysis data (Onogi et al. 2007) is used. The analysis is carried out for May to August, which corresponds to typical Yamase season (Kanno 1993;
Takai et al. 2006).
In this study, the Yamase is deﬁned as a northeasterly wind blowing over the area east of northeastern Japan, based on surface wind data averaged
over 10-day or 11-day segments (i.e., averaged overthe 1st to 10th, 11th to 20th, and 21st to 30th (or31st) of each month). The daily data are ﬁrst temporally averaged over the 10-day or 11-day segments in the 20 years (1981–2000 and 2081–2100)
and then spatially averaged over 40 N–45 N and
142.5 E–155 E. Then, using the area-averaged
value, the frequency of northeasterly wind events(i.e. zonal wind component is easterly and meridional wind component is northerly) is counted.
The 10-day mean surface wind data are used inorder to exclude northeasterly wind events accompanying fast-passing synoptic disturbances and to125

focus on the Yamase events caused by the Okhotsk
high. The Okhotsk high has longer time scales
than the synoptic disturbances because it is developed by a quasi-stationary blocking ridge in theupper troposphere (Nakamura and Fukamachi
2004).
3. Present-day climate simulation
Before the Yamase simulated in the models is assessed, the model performances in reproducing theclimatological mean sea level pressure (MSLP) patterns of the present-day climate are ﬁrst evaluated.
Figure 2a shows MSLP for the JRA-25 and theeighteen multi-model ensemble (MME18) mean
and the bias of the MME18 mean over the northwestern Paciﬁc from May to August. The MME18
mean realistically simulates the Paciﬁc high and its
seasonal evolution on a broad scale: that is, a highpressure cell prevails over the Paciﬁc, and its ridge
axis gradually migrates northward from May toAugust. However, the MME18 mean shows a systematic bias toward a strong Paciﬁc high and aweak Okhotsk high, which cause a bias toward
southwesterly winds around Japan. It is also notedthat the MME18 mean does not show the relatively
low pressure zone over southern Japan seen in the
JRA-25 in June and July, which would indicate aweaker Baiu rain band.
In order to objectively quantify each model’s performance in reproducing the MSLP pattern, we introduced the skill score (SS) proposed by Taylor(2001), which has been widely employed to evaluate
the performance of climate model. The skill score
SS is deﬁned as follows:
SS ¼

4ð1 þ RÞðSDR þ 1=SDRÞ 2 ð1 þ R0 Þ:

ð1Þ

Where R is the spatial correlation coe‰cient between observation and simulation, SDR is the spatial standard deviation of the simulation divided bythat of the observation, and R0 is the maximum
correlation attainable. Here we assumed R0 ¼ 1.
SS evaluates both the spatial correlation coe‰cientand the spatial standard deviation. The SS approaches 1.0 in a perfect simulation. SSs of the
MSLP (SS_MSLP) over the northwestern Paciﬁc(120 E–170 E, 25 N–60 N) are calculated foreach model (Table 1).
Figure 2c shows the MSLP for JRA-25 andthe respective models in June, when the Yamaseblows the most frequently (as shown in the next
paragraph). The statistics used in the right side of126

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Vol. 90A

Fig. 2. (a) Climatological mean sea level pressure in JRA-25 (thin contours) and the MME18 mean (thickcontours) and bias of the MME18 (shading) from May to August in the present-day climate (1981–2000).
Negative biases are hatched. (b) same as (a) except for MME9hi. (c) Climatological mean sea level pressure
for JRA-25 and all models in June in the present climate. The contour interval is 2 hPa.

February 2012

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127

Table 1. Yamase frequency (per 20 years), skill scores for the spatial pattern of the mean sea level pressure(SS_MSLP) over the northwestern Paciﬁc (25 –60 N, 120 –170 E), deﬁned by Eq. (1), and the SS metric deﬁned
in this study for the 18 models. The Yamase frequency for JRA-25, MME18 average and MME9hi average areshown in the lower column. The SS_MSLP are validated against the JRA-25. Notice that the Yamase frequencies
are counted from 60 segments (3 segments  20 years) in each month in the present climate (1981–2000). See text for
deﬁnition of the Yamase frequency and the metric. Asterisks (*) and sharps (#) on the left side of the table indicate
the 9 higher skill models (MME9hi) and the 14 models (MME14) with a negative sign of DEQ-SOI, respectively.
Yamase frequency (per 20 years)

MSLP skill score

Metric

ID

Model

May

Jun

Jul

Aug

MJJA

May

Jun

Jul

Aug

JJ

1
#2
*#3
*#4
*#5
*#6
*#7
*#8
* 9
#10
11
#12
#13
#14
*#15
16
*#17
#18

CGCM3.1(T47)
CGCM3.1(T63)
CNRM-CM3CSIRO-MK3.0
CSIRO-MK3.5
GFDL-CM2.0
GFDL-CM2.1
GISS-AOM
GISS-ERFGOALS-g1.0
INM-CM3.0
MIROC3.2(hires)
MIROC3.2(medres)
ECHAM5/MPI-OM
MRI-CGCM2.3.2
INGV-ECHAM4
IPSL-CM4
ECHO-G

2
2
8
5
3
6
3
1
11
3
4
5
6
6
6
2
10
6

3
0
9
13
15
10
6
7
20
4
11
8
8
7
14
4
14
5

5
1
8
8
11
7
7
8
4
18
3
5
2
4
18
6
19
7

4
0
10
12
10
4
7
5
4
11
5
4
0
2
19
9
15
10

14
3
35
38
39
27
23
21
39
36
23
22
16
19
57
21
58
28

0.753
0.709
0.951
0.977
0.896
0.908
0.958
0.804
0.777
0.786
0.837
0.785
0.787
0.959
0.984
0.882
0.692
0.899

0.743
0.678
0.926
0.982
0.985
0.973
0.928
0.951
0.855
0.801
0.898
0.789
0.731
0.901
0.959
0.933
0.950
0.899

0.832
0.785
0.943
0.957
0.942
0.983
0.986
0.968
0.957
0.911
0.902
0.813
0.799
0.943
0.893
0.969
0.919
0.887

0.783
0.720
0.832
0.865
0.827
0.883
0.923
0.945
0.888
0.773
0.852
0.690
0.602
0.918
0.692
0.909
0.887
0.865

1.305
2.272
0.536
1.159
1.573
0.861
0.293
0.478
0.232
0.6720.020
0.691
1.209
0.0520.698
0.0310.635
0.253MME18
MME9hi
JRA-25

4.9
5.9
7

8.8
12.0
16

7.8
10.0
12

7.3
9.6
8

28.8
37.4
43

Eq. (1) are shown at the bottom of each panel inFig. 2c. In the JRA-25, the Paciﬁc high prevails
over the subtropical Paciﬁc and the high pressurearea extends into the Sea of Okhotsk, which corresponds to the Okhotsk high. In the model results,
on the other hand, the Okhotsk high tends to be
weak and the Paciﬁc high tends to be strong, as indicated by large spatial standard deviations of the
MSLP. In fact, 15 out of the 18 models show SDR
values lager than 1.0 in June. In particular, models#1, #2, #10, #12, and #13 have a large SDR
of more than 1.5 because they simulate a weak
Okhotsk high and a strong Paciﬁc high, resulting
in anomalous southwesterly winds around Japan.
These models with larger SDR also have lower
SSs (Table 1). Of the 18 models, 14 models inMay, 14 in July and 17 in August show a positive
bias in the SDR. In addition, it is noted that themodels tend to reproduce the Okhotsk high overthe northern part of the Sea of Okhotsk, whereas

the observation shows it over the central Sea of
Okhotsk.
We next assess the Yamase frequency reproducedby the models. Table 1 summarizes the frequency
in each model and in JRA-25 for May to August.
In JRA-25, the Yamase blows most frequently in
June. The winds occurred 16 times in the 20 years
for 1981 to 2000 in June, corresponding to a 27%
occurrence ratio (¼ 16 occurrences/(3 segments 
20 years)), 12 times in July, 8 times in August, and7 times in May. The MME18 mean reproduces thisseasonal variation, although its amplitude is lessthan that in the observed data. Comparing the frequencies between JRA-25 and each model, mostmodels underestimate the Yamase frequency, especially in June and July, and there are large di¤erences among the models. Only model #9 overestimates the frequency in June; models #10, #15
and #17 overestimate it in July; and models #15
and #17 overestimate the total frequency from

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128

Fig. 3. Seasonal variation of the climatological mean Yamase frequency (per 20 years)
for JRA-25 (gray), the MME18 mean
(black), and the MME9hi mean (dashedblack) by 10-day segments. The Yamasefrequency is obtained in the present climate(1981–2000). Key: I ¼ 1st to 10th, II ¼
11th to 20th, and III ¼ 21st to 30th (orMay to August (MJJA). Moderate inter-model correlations are seen between the error of the Yamasefrequency and the SS_MSLP over the northwestern
Paciﬁc, with correlation coe‰cients of 0.49,
0.65, 0.63 and 0.59 for May, June, July, andAugust, respectively.
Figure 3 shows the climatological seasonal variation in the Yamase frequency by 10- (or 11-) day
segments. Similar to the JRA-25, the MME18
mean frequency increases in June and July, peaking
in late June. According to Kanno (1993), who deﬁned ‘‘Yamase days’’ based on daily surface wind
and temperature observed at Hachinohe station,on the Paciﬁc side of northern Japan, the occurrence ratio of the Yamase is more than 30% fromlate June to mid July, and the Yamase is most frequent (37%) in late June. Compared to their result,the seasonal evolution in the Yamase occurrencedeﬁned in this study is similar to theirs, although
the occurrence is slightly less.
4. Future changes
4.1 Multi-model ensemble of eighteen models
Figure 4a shows future changes of the MSLP(DMSLP) in MME18 in the future climate (2081–
2100), compared with the present-day climate(1981–2000), for May to August. In order to dis-Vol. 90A

play the robustness of the projection, the numberof models showing a positive change is indicatedby the color scale, in which ‘18’ means that allmodels project a positive DMSLP, and ‘0’ meansthat all models project a negative DMSLP. In Fig.
4a, most models show negative anomalies overhigh latitudes in May and positive anomalies over
the tropical western Paciﬁc from July to August.
In addition, negative anomalies prevail over midlatitudes (30 N–40 N) of the Paciﬁc from June toAugust, and a north-south dipole pattern prevails
over the Paciﬁc in August; most of these anomalies, however, are not very consistent among themodels. Robust future change is not projectedaround the Sea of Okhotsk in June and July, whenthe quasi-stationary anticyclone (Okhotsk high)sometimes appears over that region, continuously
causing the Yamase over northeastern Japan in theobservation.
Figure 5 shows future changes in the Yamase frequency by comparing the future climate (2081–
2100) under the SRES A1B with the present-day
climate (1981–2000) under the 20C3M. Although
there are large di¤erences among the models, mostmodels project increased Yamase frequency in August in contrast to decreased Yamase frequency inMay. On the contrary, the projected changes in the
Yamase frequency in June, July and MJJA are inconsistent among the models. These future changesof the Yamase frequency are generally consistent
with wind changes inferred from the projected
MSLP changes shown in Fig. 4a.
We explore tropical factors a¤ecting the projected changes of the Yamase frequency by multimodel inter-comparison. According to IPCC
(2007), multi-AOGCM averages project a weakshift towards conditions which are described as ‘‘El
Nino-like’’, with sea surface temperatures in thecentral and eastern equatorial Paciﬁc warming
more than those in the western Paciﬁc, with an
eastward shift in the distribution of precipitation
and with weakened tropical circulation. This El
Nino-like mean state change is considered to be attributed to the general reduction in tropical circulations resulting from the increased dry static stability
in the tropics (Knutson and Manabe 1995). Kitoh
and Uchiyama (2006) and Kusunoki et al. (2006)
suggest that the El Nino-like change prolongs the
Baiu season due to increased moisture ﬂux from astrengthened subtropical high in the tropical western Paciﬁc. We investigate possible e¤ects of suchtropical change on the projected changes of theFebruary 2012

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129

Fig. 4. Future changes of the mean sea level pressure (hPa) in (a) MME18, (b) MME14 and (c) MME9hi for
May to August in the future climate (2081–2100) of the SRES A1B experiments compared with the present-day climate (1981–2000) of the 20C3M experiments. Contours show the changes in the MME mean;
the contour interval is 0.5 hPa. Shading shows the number of models with a positive change. Red (yellow)
shading indicates that the fraction of the models projecting a positive change is approximately 90% (80%)
or higher. Dense blue (light blue) shading indicates that fraction of the models projecting a negative change
is approximately 90% (80%) or higher.

Yamase occurrence, employing an equatorial SLP
index, as deﬁned by Vecchi et al. (2006), to roughly
assess change of the Walker circulation. This index
denoted as EQ-SOI is deﬁned as the di¤erence in
the MSLP between the eastern Paciﬁc (5 S–5 N,
160 W–80 W) and the Indo-West Paciﬁc (5 S–
5 N, 80 E–160 E). DEQ-SOI denotes futurechanges in the index. Figure 4b is the same as
Fig. 4a except it shows composite maps of only the
14 models (MME14) with a negative DEQ-SOI for
the June–August mean (JJA). In MME14, negative
anomalies are dominant over the mid-latitudes of
the Paciﬁc and positive anomalies are dominant
over the tropical western Paciﬁc from June to Au-

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Vol. 90A

Fig. 5. Future changes in the Yamase frequency per 20 years in the future climate (2081–2100) of the SRESA1B experiments compared with the present-day climate (1981–2000) of the 20C3M experiments for May
to August. The bars show the change in the frequency in each month. The black diamonds show the accumulated change from May to August. Numbers in the horizontal axis indicate model IDs shown in Table 1.
The numbers of the models belonging to the MME9hi are circled.

gust; these anomalies are clearer than those in
MME18. In addition, the north-south dipole anomaly over mid-latitudes of the Paciﬁc in August isclearer, and more than 90% of the models in
MME14 project negative anomalies over the oceaneast of Japan.
Models with a negative DEQ-SOI in JJA tend toproject increased Yamase frequency (Fig. 6a). Theinter-model correlation coe‰cient between DEQSOI and the projected change in the Yamase frequency is 0.58 for August, but it is low for othermonths (0.11 in May, 0.22 in June and 0.18 inJuly). The scatter plot of DEQ-SOI in JJA andDMSLP over the Sea of Okhotsk (140 E–170 E,
45 N–60 N; DMSLP_OH) in August (Fig. 6b) andthe DEQ-SOI and DMSLP over the area east ofJapan (140 E–170 E, 30 N–40 N; DMSLP_EJ) in
August (Fig. 6c) shows that models projecting increased Yamase (ﬁlled circles) tend to have a negative DMSLP_EJ and a positive DMSLP_OH. The
negative DMSLP_EJ is strongly related to a negative DEQ-SOI: the inter-model correlation coe‰cient between them is 0.74 (Fig. 6c). On the other
hand, positive DMSLP_OH cannot be explainedby this straightforward linear relationship with the
DEQ-SOI (Fig. 6b).
4.2 Multi-model ensemble of nine models
with higher skill
The CMIP3 models clearly underestimate the
Yamase frequency in June and July compared to
the reanalysis. Associated with this systematic bias,
the models tend to underestimate the Okhotsk highin the MSLP ﬁeld (Fig. 2a). These biases suggestthat current climate models do not have enoughskill to represent the Okhotsk high, which maylead to large uncertainty in the projected change in
the Yamase frequency in June and July.
We therefore attempt to select models based on
their skill in reproducing both the Yamase frequency and the MSLP pattern in the present climate. The deﬁned metric is the average of the skills
for the Yamase frequency and the MSLP patternin June and July. The skill for the Yamase is calculated as follows. First, the monthly errors of
the Yamase frequency, referenced to JRA-25, aresummed as the root-mean-square error (RMSE) in
June and July, and then the value is normalizedFebruary 2012

H. ENDO131

Fig. 6. Scatter plots of (a) future changes in
the Yamase frequency in August, (b) futurechanges in the mean sea level pressure(hPa) over the Sea of Okhotsk (140 –170 E, 45 –60 N; MSLP_OH) in Augustand (c) over the area east of Japan (140 –170 E, 30 –40 N; MSLP_EJ) in August
versus changes of the EQ-SOI in JJA
mean for the all 18 models. Data for models belonging to the MME9hi are shown by
as X marks. In (b) and (c), data of models
projecting an increased Yamase frequency
in August are plotted with ﬁlled circles.
EQ-SOI is deﬁned as the sea level pressuredi¤erence (hPa) between the eastern Paciﬁc(5 S–5 N, 160 –80 W) and the Indo-West
Paciﬁc (5 S–5 N, 80 –160 E).

and the sign is adjusted so as to have a positive
value for a better model. Skill scores of the MSLP
are calculated similarly; the monthly SS_MSLP,
listed in Table 1, are averaged in June and July,and then the value is normalized and the sign is adjusted. The calculated metrics are listed in the righthand column of Table 1. Using this metric, we select nine high-skill models (MME9hi), that is, halfof all of the models.
The MME9hi improves the weaker bias of the
Okhotsk high in the MME18 (Fig. 2b) and repro-

duces more frequent Yamase and a more realistic
seasonal variation of the Yamase frequency thanthe MME18, although the MME9hi mean slightly
overestimates the frequency in August (Table 1
and Fig. 3).
Although changes of the Yamase frequency areinconsistent even among the MME9hi in June andJuly (Fig. 5), negative anomalies in June over the
Sea of Okhotsk and eastern Siberia in the MSLP
are contrasted with positive anomalies in July(Fig. 4c), which are unclear in both the MME18

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Journal of the Meteorological Society of Japanand MME14 projections. In August, almost all the
MME9hi project weakening of the Paciﬁc high over
the ocean east of Japan and an increase of the
Yamase frequency (Figs. 4c, 5 and 6), consistent
with the MME18 projections. Positive MSLP
anomalies prevail over the tropical western Paciﬁcfrom May to August (Fig. 4c). These consistentchanges over the tropics and mid-latitudes among
the MME9hi may be partly due to consistent signsof the DEQ-SOI: namely, eight models out of
MME9hi project a negative DEQ-SOI (Table 1).
Kusunoki et al. (2006) showed future changes ofthe MSLP over the northwestern Paciﬁc as well as
the Baiu rainfall in June and July by performing experiments using a 20-km mesh AGCM that successfully reproduced the present climate. The futurechanges of the MSLP over the Sea of Okhotsk arepositive anomaly in July in contrast to negative
anomaly in June, although the changes are not statistically signiﬁcant, which is consistent with thisstudy’s MME9hi result.
5. Discussion
Weakening of the Walker circulation (i.e., negative DEQ-SOI) is closely related to the weakened
Paciﬁc high over the ocean east of Japan and the
Yamase increase in August (Fig. 6). Here we show
the observed inter-annual relationships between the
EQ-SOI and large-scale circulation anomalies inFig. 7, which are calculated from de-trended
monthly data for the period from 1958 to 2007 using NCEP/NCAR reanalysis (Kalnay et al. 1996).
For comparison with Fig. 4, the signs of the regression coe‰cient in Fig. 7 are reversed. In the observed inter-annual variability, negative EQ-SOI is
related to a weakened Paciﬁc high over the Paciﬁcand a strengthened and southward-shifted subtropical jet in late boreal summer. This MSLP anomaly
pattern is generally similar with the projectedchanges in late boreal summer (Fig. 4), that is, negative anomalies prevail over the mid-latitude of the
Paciﬁc in July and August, with positive anomalies
to the north in August. These similarities support a
possible connection between the weakening of theWalker circulation and the weakened Paciﬁc high.
Tanaka et al. (2005) and Ueda et al. (2006) revealed that many CMIP3 models project weakening of the Asian summer monsoon circulation, as
well as weakening of Walker and Hadley circulation. The weakening of the Asian monsoon circulation may also contribute to the robust weakening ofVol. 90A

the Paciﬁc high over the ocean just east of Japan inAugust (Fig. 4). Kosaka and Nakamura (2011) suggest that projected changes of large-scale circulations are similar to the Paciﬁc-Japan pattern (Nitta
1987) through investigation of the CMIP3 multimodels.
Even though many models project increase of
the Yamase in August, future strengthening of the
Okhotsk high in the MSLP in August seems not tobe signiﬁcant (Fig. 4). We think that the projected
weakened Paciﬁc high makes a certain contribution
to the increased Yamase in the model results.
Kanno (2004) and Yasunaka and Hanawa (2006)
showed a north-south surface pressure gradientover northeastern Japan is strongly related to the
Yamase and resultant Yamase-type anomaly distribution in terms of temperature and sunshine duration. Tachibana et al (2004) indicated that both thedevelopment of the ridge over eastern Siberia andthe weakness of the Paciﬁc high over the oceaneast of northern Japan inﬂuence the developmentof the Okhotsk high from investigation of the observed inter-annual variability. It is also anotherpossibility that the blocking activity over eastern
Siberia may increase in the future climate, as suggested by Arai and Kimoto (2008). If so, this leads
to enhancement of the Okhotsk high, increasing the
Yamase frequency even though the MSLP change
is unclear.
We should discuss not only tropical factors but
also extra-tropical factors on the projected changeof the Yamase frequency. In May, most models
project decrease of the Yamase frequency and negative anomalies over high latitudes in the MSLP.
Figure 8 shows the MSLP anomaly in January
through May. The negative anomalies over thehigh latitudes in May begin from the boreal winter,and this anomaly pattern is similar to the positive
phase of the Northern Annular Mode (NAM) or
the Arctic Oscillation (AO), which are known tobe response of the climate system to global warming (e.g., Miller et al. 2006). The negative anomalies persist until early boreal summer over the area
north of Japan, strengthening westerly winds andprobably attributing to the projected decrease of
the Yamase frequency in May.
Land surface warming has been considered to
be an important factor for enhancement of the
Okhotsk high in the climate change caused by
global warming as well as in the inter-annual variability (Kimoto 2005; Arai and Kimoto 2005,2008). Kimoto (2005) demonstrates that EurasianFebruary 2012

H. ENDO133

Fig. 7. Observed monthly (a) sea level pressure and (b) 200 hPa zonal wind regressed on the EQ-SOI, basedon NCEP/NCAR (1958–2007). For comparison with Fig. 4, the signs of the regression coe‰cient are reversed. Shading indicates that the correlation coe‰cient is signiﬁcant at the 5% level. The contour intervals
are (a) 0.5 hPa and (b) 2 m/s, respectively. The sea level pressure ﬁeld and the EQ-SOI are de-trended forthe analyzed period.

continental surface warming contributes to thestrengthening of an anticyclone over high latitudesof the Paciﬁc, through an AGCM experiment. We
brieﬂy examine inter-model relationships between
land surface warming over Siberia and enhancement of the Okhotsk high by a simple method,
based on MME18. Correlation coe‰cients between
surface air temperature changes over the land of
Siberia (60 –180 E, 40 –70 N; DSATMP_SB)
in JJA and DMSLP_OH in each month basedon MME18 are 0.15, 0.11, 0.44, 0.32, and 0.06
for May, June, July, August, JJA, respectively.
In the case of the lagged relationship between
DSTAMP_SB in March through May (MAM)

mean and DMSLP_OH in each month, the correlation coe‰cients are 0.06, 0.03, 0.35, 0.55, and0.19 for May, June, July, August, JJA, respectively.
Only the relationship between DSATMP_SB in
MAM and DMSLP_OH in August shows a statistically signiﬁcant at the 5% level. As for an investigation based on MME9hi, no coe‰cients reach to thesigniﬁcance level. Further elaborate investigation isneeded to clarify the continental warming on the
Okhotsk high and the Yamase.
The changes of the MSLP projected by theMME9hi show negative anomalies in June in contrast to positive anomalies in July over the Sea of
Okhotsk and eastern Siberia in the MSLP ﬁeld,

Journal of the Meteorological Society of Japan

134

Vol. 90A

Fig. 8. Same as Fig. 4a except for over high latitudes in the northern hemisphere in January, March andMay.

which are unclear for the MME18 and MME14(Fig. 4). These anomalies appearing near the Seaof Okhotsk only in the MME9hi are worth noting,because the metric to select the MME9hi reﬂects
model performance of reproducing the Okhotsk
high to some degree. Further studies are necessary
for understanding these interesting changes. It is
generally pointed out that the Okhotsk high develops associated with a blocking anticyclone in
the upper troposphere (Nakamura and Fukamachi
2004). Tachibana et al. (2004) discusses that thedevelopment of the Okhotsk high restricted in thelower troposphere may be inﬂuenced by air-sea
interaction through occurrence of low-level clouds
and marine fog. We should further assess the
Okhotsk high reproduced in the climate models
with focus on such phenomena.
6. Summary
This study investigates future changes in the frequency of the Yamase occurrences by analyzing 18
AOGCM experiments in CMIP3 archives for May
to August. In the present-day climate, the MME18
mean modestly reproduces seasonal variation of the
Yamase frequency, although each model generally
underestimates the Yamase frequency compared to
the reanalysis data and large di¤erences are seenamong the models. The models show a systematic
bias toward a strong Paciﬁc high and a weak
Okhotsk high.
In the future climate, most models project increases of the Yamase frequency in August in contrast to decreases of the frequency in May, whereas
projected frequency changes in June, July and

MJJA are inconsistent among the MME18. Intermodel comparison suggests that weakening of mean
tropical circulation, including the Walker circulation, may contribute to the increased Yamase frequency in August. A projection employing only
nine of the models with higher skill (MME9hi),
based on a deﬁned metric, is also tried. Althoughchanges of the Yamase frequency are inconsistenteven among the MME9hi in June and July, negative anomalies in June over the Sea of Okhotsk
and eastern Siberia in the MSLP are contrasted
with positive anomalies in July, which are unclear
in the MME18 projections. In August, almost all
the MME9hi project increase of the Yamase frequency, consistent with the MME18 projections.
Our study shows that the Yamase occurrences
will increase in August in the future climate. Thischange corresponds to a delay of the Yamase season, because in the present climate the Yamase
blow most frequently in June and July. Kitoh andUchiyama (2006) indicated a delay in the Baiu rain
withdrawal by an analysis using ﬁfteen CMIP3
model simulations (almost the same dataset analyzed in this study). Thus, the CMIP3 models project that not only the Baiu season observed oversouthern Japan but also the Yamase season observed over northeastern Japan will be delayed in
the future climate. Anomalous weather associatedwith the Yamase for late July to mid August, corresponding to the high summer season over northern
Japan, has particularly large impact on agriculture
and society, therefore the delay of the seasonal
march projected by the CMIP3 models is noteworthy.

February 2012

H. ENDOAcknowledgements
This work is supported by the Global Environment Research Fund (S-5-2). We acknowledge themodeling groups, the Program for Climate Model
Diagnosis and Intercomparison (PCMDI) and the
WCRP’s Working Group on Coupled Modeling(WGCM) for their roles in making available the
WCRP CMIP3 multi-model dataset. Support ofthis dataset is provided by the O‰ce of Science,
U.S. Department of Energy. We also express our
gratitude to the ‘‘Data Integration and Analysis
System’’ Fund for National Key Technology from
the Ministry of Education, Culture, Sports, Scienceand Technology, Japan, for providing us with aninvaluable environment for a mass data handling.
We appreciate various valuable comments fromDr. T. Ose of MRI, and technical support from
Kanako Aadachi in drawing Fig. 1. We also thankthe two anonymous reviewers and the editor for
useful comments.
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