6456

JOURNAL OF CLIMATEVOLUME 24

Future Change in Extratropical Cyclones Associated with Change in theUpper Troposphere
RYO MIZUTA
Meteorological Research Institute, Tsukuba, JapanMIO MATSUEDA
Japan Agency for Marine-Earth Science and Technology, Tsukuba, JapanHIROKAZU ENDO AND SEIJI YUKIMOTO
Meteorological Research Institute, Tsukuba, Japan(Manuscript received 2 August 2010, in final form 31 March 2011)
ABSTRACT
Future changes in Northern Hemisphere wintertime storm activity as a consequence of global warming areinvestigated using the AGCM of Meteorological Research Institute (MRI-AGCM) with horizontal grid sizesof 60 and 20 km. A future (2075–99) climate experiment, in which the change in sea surface temperature(SST) derived from the Coupled Model Intercomparison Project phase 3 (CMIP3) multimodel ensemble
mean is added to observed SST, is compared with a present-day (1979–2003) climate experiment. Results ofthree-member simulations using the 60-km model are presented. A single simulation using the 20-km model isalso presented, showing that similar results are obtained.
In the future climate experiment, the number of intense cyclones (sea level pressure below 980 hPa) showsa significant increase whereas the number of total cyclones shows a significant decrease, similar to the results
obtained from the CMIP3 models themselves. The increase in intense cyclones is seen on the polar side anddownstream side of Atlantic and Pacific storm tracks. At the same time, the growth rate of the cyclones
increases in areas upstream of these regions.
For the regions with the increasing growth rate, a high correlation is seen between the growth rate of thesurface cyclones and upper-tropospheric zonal wind at a monthly-mean time scale. Months of high cyclone
growth rate with strong zonal wind in these regions become more frequent, and months of low cyclone growthrate with weak zonal wind become less frequent. One of the possibilities that can explain this relationship ischanges in the wave-breaking pattern, that is, a decrease in wave breakings in areas of cyclonic shear and anincrease in wave breakings in areas of anticyclonic shear. Associated with these changes, rapid cyclone developments are more commonly seen, and weak, long-lived cyclones become less frequent.

1. Introduction
The activity of extratropical cyclones is a dominant
weather feature in the midlatitudes during the period
from autumn to spring. Any change in this activity due toglobal warming would have a marked influence on thedaily lives of many people. In particular, a change in theoccurrence of intense cyclones could influence the scale
and frequency of disasters resulting from extreme wind

Corresponding author address: Ryo Mizuta, MeteorologicalResearch Institute, 1-1 Nagamine, Tsukuba 305-0052, Japan.
E-mail: rmizuta@mri-jma.go.jp
DOI: 10.1175/2011JCLI3969.1
Ó 2011 American Meteorological Society

or precipitation events. The changes in cyclone activity
likely to occur with a warmer climate remain insufficiently
understood, especially with regard to extreme cyclones(Solomon et al. 2007).
According to the results of climate models that contributed to the Coupled Model Intercomparison Project
phase 3 (CMIP3; Meehl et al. 2007), synoptic-scale activity (so-called storm-track activity) increases in the
middle–upper troposphere in future climate experiments compared with present-day experiments. Yin(2005) reported that the zonal-mean eddy kinetic energy
at a synoptic time scale shows an increase in future climate experiments, and that its peak shifts poleward and15 DECEMBER 2011

MIZUTA ET AL.

slightly to the higher level. This change is consistent withthe temperature change expected in the middle–upper
troposphere around 200–500 hPa. Whereas greater warming occurs in the tropics because of increased verticalwater vapor flux and latent heat release, relatively little
warming occurs at high latitudes. This occurs because
the tropopause is located lower at high latitudes than in
the tropics, so high-latitude regions at these levels are
more affected by the air of the stratosphere, where thetemperature is decreasing because of increased radiative
cooling by CO2. Therefore, the meridional temperature
gradient at these levels is intensified in the future, resulting in stronger synoptic-scale activity in response to
the meridional temperature gradient. While the increasein synoptic-scale activity is larger in the upper levels, theincrease is also seen in the middle troposphere (Pinto
et al. 2007) and near the surface (Ulbrich et al. 2008),
although the signal near the surface is relatively weak
and limited to specific regions that depend on the model.
According to the same set of results of climate models,
the total number of surface cyclone tracks decreases in
the future experiments (Lambert and Fyfe 2006). Sucha decrease has been reported in many studies (Geng andSugi 2003; Bengtsson et al. 2006), as reviewed by Ulbrichet al. (2009). This change is consistent with the temperature change expected in the lower troposphere thatwarming is greater at high latitudes than in the tropics.
The most well-known explanation of larger warming athigh latitudes is that the melting of snow cover and sea
ice induces a change in surface albedo, leading in turn tomore warming (e.g., Hall 2004), although Winton (2006)
argues that other radiative feedbacks also contribute toit. Consequently, the meridional temperature gradientnear the surface becomes weaker than the present gradient, resulting in weaker baroclinicity in the lower
troposphere. The reduced baroclinicity is often explained as the cause of decrease in cyclone number.
Apparently, the decrease in the number of cyclones
and the increase in the synoptic-scale activity do notseem to be consistent with each other. Another changethat many of the models predict is an increasing numberof intense cyclones. Lambert and Fyfe (2006) showedthat the frequency of extreme cyclones (sea level pressure below 970 hPa) in winter is expected to increase in
the future experiments in a large part of the CMIP3
models. The increase in intense cyclones is limited tosome areas, depending on models and experiments.
Regions near the British Isles and Aleutian Islands show
an increase in some models (Geng and Sugi 2003; Pinto
et al. 2007). These regions are corresponding to those ofincreasing storm-track activity near the surface in theensemble mean of CMIP3 experiments (Ulbrich et al.
2008). While the increase in the number of intense

6457

cyclones could explain the increase in the synoptic-scale
activity, the reason for this increase in intense cyclones
remains unclear, although some studies suggested theincrease is related to the enhanced latent heat release(e.g., Geng and Sugi 2003).
Extratropical cyclones are categorized into the following two types based on their life cycles (LCs) of LC1 andLC2 (Thorncroft et al. 1993; Shapiro et al. 1999). The
former corresponds to cyclones that develop within anticyclonic shear, accompanied by anticyclonic Rossby wave
breakings, whereas the latter corresponds to cyclonicshear and cyclonic breakings. Idealized numerical experiments show that these two types of extratropical cyclones
have different developments (Wernli et al. 1998). Averaged cyclone developments are more rapid under anticyclonic wave breakings, and lifetimes of the cyclones
become longer under cyclonic wave breakings due tosuppressed energy conversion (Thorncroft et al. 1993;
Watanabe 2009). In the real atmosphere, rapid cyclone
development is triggered by upper-tropospheric Rossby
waves (Yoshiike and Kawamura 2009). The results of theabove studies suggest that future change in the upper
troposphere associated with global warming may influence the development of extratropical cyclones.
The present study investigates how the global warming–
related changes in the middle–upper troposphere andthose near the surface are explained consistently; that is,
the relationships between enhanced storm-track activity,
reduced number of total cyclones, and increased numberof intense cyclones under the opposed change in meridional temperature gradient between the upper troposphereand near the surface. We focus on regional changes inupper-tropospheric background flows and in growth rates
of surface cyclones. Roles of cyclonic/anticyclonic patterns of wave breakings are also considered.
Changes during the Northern Hemisphere winter are
studied by comparing the present-day climate and thefuture climate in a high-resolution atmospheric generalcirculation model (AGCM) that can simulate the structures of intense cyclones. By using the change in sea surface temperature (SST) and sea ice concentration fromthe CMIP3 multimodel ensemble as the lower-boundary
conditions in the model, we obtained high-resolution
data on atmospheric change similar to that predicted bya multimodel ensemble. Because the climate of extratropical winter shows large interannual variability, threemembers of 25-yr simulations with initial-value ensemble approach are analyzed to extract statistically significant changes.
The remainder of this paper is organized as follows.
The model and the method of cyclone detection are
described in section 2. Section 3 presents the results regarding future changes in cyclone behavior, background6458

JOURNAL OF CLIMATE

flows, and the relations between these factors. Finally,
section 4 contains the discussion and conclusions.

2. Model and methodology
a. Model outline
This study uses Meteorological Research InstituteAtmospheric General Circulation Model version 3.1,
(MRI-AGCM3.1), a global atmospheric general circulation model jointly developed by the Japan Meteorological
Agency and the MRI. Details of the model can be foundin Mizuta et al. (2006), who showed that the global distributions of the seasonal-mean atmospheric fields, precipitation, and surface air temperature simulated by the
20-km-mesh version of the model agree well with observations. Moreover, the model yields improved representation of regional-scale phenomena and local climate asa result of increased horizontal resolution, thereby yielding an improved expression of topographical effects andphysical processes without degrading the representationof global climate.
Here, we use the results of present-day and future climate experiments performed using the above model(Kitoh et al. 2009). For the present-day climate experiment, from 1979 to 2003, monthly-mean observed SST
and sea ice concentration by the Hadley Center (Rayner
et al. 2003) are given as the lower-boundary conditions.
For the future climate experiment, from 2075 to 2099, theSST is prepared by superposing (i) the detrended observed SST, including year-to-year variability; (ii) futurechange in the multimodel ensemble mean (MMEM) of
SST; and (iii) the linear trend in the MMEM of SST
projected by CMIP3 models. Future change in the
MMEM of SST was evaluated by the difference between
twentieth-century simulations and future simulations
conducted under the Special Report on Emission Scenario (SRES) A1B emission scenario. The design retains
observed year-to-year variability, such as El Niño–Southern Oscillation (ENSO) events, in the future climate. Future sea ice distribution is obtained in a similar
fashion. Details of the method can be found in Mizuta
et al. (2008). The concentrations of greenhouse gases arealso changed following the A1B emission scenario.
We use the simulations performed with horizontal
resolutions of 60 and 20 km. The 60-km model has 640 3
320 grid cells, corresponding to a triangular truncationof 319 with a linear Gaussian grid (TL319) in the horizontal. The 20-km model has 1920 3 960 grid cells with
TL959. Both models have 60 layers in the vertical, withthe model top at 0.1 hPa. In addition, for comparison
with the Japanese 25-year Reanalysis (JRA-25; Onogi
et al. 2007), the results of a 120-km model (TL159, 40
layers) are presented because the reanalysis was made

VOLUME 24

using a horizontal resolution of 120 km. The model settings are the same among the three resolutions, except forseveral tuning parameters that are altered to reduce theresolution dependence of the results.
Although the higher-resolution model is more realistic
in representing phenomena such as blockings (Matsueda
et al. 2009), the length of the simulation is limited bycomputational resources. We performed three pairs of
the present and future experiments with the 60-km
model, which use the same boundary conditions but startfrom different initial values, while only a single pair of theexperiments is obtained with the 20-km model. Consequently, we focus on the results of the 60-km simulations
to obtain the nature of changes between the present andfuture climates. The 20-km results are also presented toshow the robustness of this approach, in that similar results are obtained for a higher-resolution model.

b. Method of cyclone tracking
The method of cyclone detecting and tracking
employed in the present study is a modified version ofthat described by Geng and Sugi (2003). The method
uses 6-hourly sea level pressure (SLP) interpolated toa 1.258 grid. As the detecting step, points with SLP lower
than the surrounding 8 points and with SLP more than
0.3 hPa lower than the average of the surrounding 8
points are identified as cyclones. Points at elevations
higher than 1500 m above sea level are excluded fromanalysis. Next, as the tracking step, each point is advected by the background flow (15-day running mean of
700-hPa wind), and search the nearest point within
300 km at the next time step. We use 700-hPa wind as
a representation of the lower troposphere from surface
to about 500 hPa, and use a 15-day running mean toremove the fluctuation by the cyclone itself. If the point
is found, the two related points are regarded as one sequence of a cyclone. This method is relatively simple
compared with those proposed in recent studies [see thereview by Ulbrich et al. (2009)] and has arbitrary parameters, especially in the tracking step. However, theresults shown here are largely independent of the detailsof the method, as we focus on the difference between thetwo experiments and on the pressure change between
successive steps during the developing stage of cyclones.
Figures 1a–d show cyclone tracks from December to
February (DJF) for two winters (2000/01 and 2001/02),
as derived from JRA-25 and the 120-, 60-, and 20-km
models. Cyclones that persist for longer than 24 h andexperience below 1010 hPa are shown. Cyclone tracks in
the Pacific (from Korea and Japan to Alaska and the west
coast of North America) and in the Atlantic (from central
North America to the Norwegian Sea and northern coastof Russia) are well simulated at all resolutions. Cyclone

15 DECEMBER 2011

MIZUTA ET AL.

6459

FIG. 1. (a)–(d) Cyclone tracks from DJF for two winters (2000/01 and 2001/02), and (e)–(h) the cyclone density within 2.58 grid boxes (1per month per box) for DJF over a 25-yr period. Cyclones that persist for longer than 24 h and experience below 1010 hPa are shown, for(a),(e) JRA-25, (b),(f) the 120-km model, (c),(g) the 60-km model, and (d),(h) the 20-km model.

tracks are also seen in the Mediterranean Sea. Difference between the reanalysis data and models is found at
low latitudes, around India and the tropical eastern
Pacific.
Figures 1e–h show the cyclone density for the 25-yr
period (1979 to 2003). The density is defined as thefrequency of existence of cyclones that persist for longer
than 24 h and experience below 1010 hPa. The density
for each 2.58 grid box is shown. The horizontal resolutionof the reanalysis is the same as that in the 120-km model,
and these two have similar results. The 60- and 20-km
models show slightly more tracks than in the 120-km
model and reanalysis data. Weak disturbances are captured more frequently in higher-resolution models whenusing this type of method (Jung et al. 2006), even if all
the results are interpolated to a 1.258 grid. However, thespatial distribution of densities during the Northern
winter is well simulated at all resolutions. Althoughtropical cyclones are also captured using this method, as
seen in the tracks at low latitudes, we treat all cyclones in
the region 208–908N as extratropical cyclones because
tropical cyclones are rare in this region during winter.

3. Resultsa. Change in cyclone frequency
Here, we examine the change in cyclone tracks fromthe present-day experiments to the future experiments.

Figure 2 shows the total cyclone track number in theregion 208–908N during winter as a function of threshold
minimum SLP. Cyclones that persist for longer than 24 h
and whose minimum SLP during the lifetime is lower
than each threshold value are counted. The rates ofchange from the present-day experiments to the future
experiments are plotted in the lower panel, showing thestatistical significance of the change (Student’s t test).
When a higher SLP threshold is used to capture almost all
the cyclones, the number of cyclones decreases in the
future experiments. The decrease is 10%–20% and is
statistically significant in both the 60- and 20-km models.
However, for an SLP threshold of below 980 hPa, inwhich case only intense cyclones are detected, the number of cyclones increases by 10%–20%. This change isconsistent with the results obtained using CMIP3 models(Lambert and Fyfe 2006) and the results presented by
Bengtsson et al. (2009). The increase is statistically significant only in the 60-km model. It is noted that thesignificance is obtained from averaging of the three experiments, not from the difference in horizontal resolution. If we compare a single member of the present-day
experiments with a single member of the future experiments, the increase is not statistically significant.
Figure 3 shows whether the results of Fig. 2 depend on
the lifetime threshold of the cyclones. Cyclones thatpersist for longer than 48, 72, and 96 h in the 60-km
model are counted, respectively, while the value of 24 h
is used in Fig. 2. The decrease in the number of all

6460

JOURNAL OF CLIMATEVOLUME 24

FIG. 2. Number of cyclones in the region 208–908N in DJF as a function of the threshold minimum sea level pressurefor (a) the 20-km model and (b) the three-member mean of the 60-km models. Units are 1 yr21. Thin lines indicate
the present-day experiments, and thick lines indicate the future experiments. (bottom) The rate of change from thepresent-day to future experiments is shown. Dots indicate that the change is significant at the 99% level (Student’s ttest).

cyclones is more remarkable when the longer lifetime
threshold is taken. For an SLP threshold of 1000 hPa, forinstance, a decrease of over 30% is seen in the cyclones
longer than 96 h, while there is about 10% decrease in
those longer than 24 h. The increase in intense cyclones
does not depend much on the lifetime. About 20% increase for an SLP threshold of 960 hPa, and about 50%
increase for 940 hPa in any lifetime thresholds, althoughstatistical significance is smaller in the region of long
lifetime thresholds and lower SLP thresholds due to thesmaller sample number.
Figures 4a and 4b show the horizontal distribution of
cyclone density for all cyclones (#1010 hPa) and its
future change for the 60-km model. A future decrease incyclone density is seen in large parts of regions where
cyclones are frequently seen, including the Pacific and
the Atlantic storm tracks. A relatively large decrease isseen in the Mediterranean Sea. An increase is seen onlyin the northern part of the Sea of Okhotsk, Baffin Bay,and in parts of the Arctic sea. These areas correspond toregions of sea ice retreat and large changes in surface
temperature. The cyclone density and its change in intense cyclones (#980 hPa) are shown in Figs. 4c and 4d.

In the areas east of Japan and east of Canada, which arein the first half of storm tracks, intense cyclones decrease
as well as weak cyclones. In contrast, an increase in intense cyclones is seen in the latter half of storm tracks,
from the east coast of Russia to the west coast of Alaska
and Canada and from Scotland to the north coast of
Russia. In these areas, an increase is also seen in seasonal precipitation amount and frequency of strong
wind (e.g., exceeding 25 m s21) (not shown).
It is speculated from the above changes that the development of individual cyclones in storm-track regions
could change under the future climate. Then we calculated the growth rate of storms, defined as temporal SLPchange along each cyclone track. These values wereaveraged for the cyclones that pass through each of the
2.58 grid boxes. Figure 5 shows the distribution of theaverage growth rate and its future change. The average
growth rate in the present-day experiments (Fig. 5a) islargest at about 408N in the Pacific and 458N in the Atlantic. The growth rate increases on the polar side of thepeak latitudes but decreases on the equatorial side (Fig.
5b). The contrast between increasing and decreasing
trends is more pronounced in the Pacific region than in15 DECEMBER 2011

MIZUTA ET AL.

6461

FIG. 3. As in Fig. 2, but for cyclones with lifetimes longer than (a) 24, (b) 48, and (c) 96 h for the three-member mean of the 60-km models.

the Atlantic. In the Atlantic, a large increase in growthrate is seen upstream of the British Isles. The increase in
the density of intense cyclones (Fig. 4d) is seen downstream of regions with an increase in growth rate.
Therefore, combined with the fact that the increase inintense cyclones does not depend much on the lifetime(Fig. 3), the increased density of intense cyclones can be
explained by the increase in growth rate.

b. Future changes in background fields
To investigate what part of the changes in the background fields are related to changes in cyclone behavior,
we examined changes in the three-dimensional seasonalmean fields. Figures 6a and 6b show the zonal mean
temperature in the present-day experiments and thedifference between the present-day and future experiments. The contours show values of the present-day experiments, and shading indicates the difference between
the present-day and future experiments. The future change
below 850 hPa corresponds to the surface temperaturechange, which shows a larger increase at high latitudes
than at low latitudes. The meridional temperature gradient becomes smaller at these altitudes. In the upper
troposphere (150–400 hPa), the temperature increase islarge in the tropics but small at high latitudes. Figures 6c
and 6d show the future change in the zonal mean eddy
kinetic energy at the synoptic time scale (2.5–8.0 days).
The region of high activity shifts to higher latitudes andactivity increases. The increase is more pronounced in theupper levels, although a small increase is still seen at lower
levels. These results are common to the 20-km model andthe 60-km model and similar to those obtained from themultimodel ensemble mean (Yin 2005).
Here, changes in the upper troposphere are comparedwith those in the lower troposphere. Figure 7 shows thehorizontal distribution of future change in zonal wind,
eddy kinetic energy, and the maximum Eady growthrate (Lindzen and Farrell 1980) at the upper level(300 hPa) and the lower level (850 hPa). The maximum
Eady growth rate s is as an index of baroclinicity, calculated as s 5 0.31 gN21T 21$T, where T is temperature
and N is the Brunt–Väisälä frequency. Daily values of s
are calculated, and they are averaged over DJF. The
data are from the 60-km experiments, although similar
results were obtained in the 20-km experiments.
Figure 7a shows the horizontal distribution of futurechange in the zonal wind at 300 hPa. The subtropical jet
becomes weaker around northern Africa and south ofJapan. The jet extends to downstream areas, showing an
increase around the eastern Pacific and from the eastern
Atlantic to Europe. The wind is enhanced also from
northeastern Asia to north of Japan, indicating that thepolar jet becomes stronger. The patterns of change inthe western Pacific and eastern Atlantic are similar to
those of the cyclone growth rate (Fig. 5b). The extensionof the jet indicates the eastward extension of momentum
flux convergence in the latter part of the jet. Open andclosed circles indicate the locations of maximum windfor each longitude, for the present-day and future experiments, respectively. The shift of the locations of the
maximum wind is very small. Thus, in this model, it ismore appropriate to say that the jet is broadened with

6462

JOURNAL OF CLIMATEVOLUME 24

FIG. 4. Horizontal distributions of cyclone density in DJF of (a),(c) the present-day experiments and (b),(d) thechange from the present-day to future experiments for (a),(b) all cyclones (#1010 hPa) and (c),(d) intense cyclones(#980 hPa) for the three-member mean of the 60-km models. The density of cyclones that persist for longer than 24 h
is calculated for each 2.58 grid box. Units are 1 per month per box.

the enhanced polar jet and the reduced subtropical jet,rather than that the subtropical jet is shifted poleward.
Figure 7b shows the future change in the eddy kinetic
energy at a synoptic time scale at 300 hPa. An increase isseen at almost all longitudes of 408–508N, corresponding to
the zonal-mean increase in Fig. 6d. Stronger increase is seenfrom the eastern Atlantic to Europe and from northeastern
Asia to north of Japan. These regions are also similar to theregions of an increase in the polar jet (Fig. 7a).
The future change in s at 300 hPa is shown in Fig.
7c. An increase in s is seen across large areas of theextratropics at 300 hPa. The increase is mainly fromstrengthening of the meridional temperature gradientin midlatitudes, and from the decrease in static stability due to the change in the vertical (potential) temperature gradient. This is speculated from Figs. 6a and6b, and can be seen by dividing the change in s into
Ds ; [D($T/T)/($T/T)]s 1 [D(1/N)/(1/N)]s and calculating each component (not shown). Overall, the situationin the upper troposphere is promoting more activity ofthe synoptic-scale waves, although the change in s is not
so similar to the cyclone growth rate (Fig. 5b) in the15 DECEMBER 2011

MIZUTA ET AL.

6463

FIG. 5. Horizontal distributions of the mean growth rate of cyclones (hPa day21) in DJF of (a) the present-day
experiments and (b) the change from the present-day to future experiments for the three-member mean of the 60-km
models. The areas outlined by green lines are referred to in Fig. 8.

horizontal pattern and does not seem to be contributing
directly to the change in cyclone developments.
The future change in zonal wind at 850 hPa shown in
Fig. 7d is much smaller than that at 300 hPa (Fig. 7a),while the pattern of the change is similar around Europe
and East Asia, occurring via vertical momentum transport from upper levels or via meridional heat transport byeddies. In the eddy kinetic energy at 850 hPa (Fig. 7e),the decreasing signals are stronger than the increasing
signals, when compared with 300 hPa (Fig. 7b). The
decreasing signal is especially pronounced in the area
south of Japan, while the increasing signal is seen in theeastern Atlantic and near Alaska. A similar pattern isseen in the future change in meridional heat transport byeddies (not shown) and has been also seen in the futurechange in variability of SLP at a synoptic time scale obtained from the ensemble mean of the CMIP3 models
themselves (Ulbrich et al. 2008). Figure 7f is the change
in s at 850 hPa. The values show a decrease over the
middle–high latitudes, especially in the Pacific, and only
a very small area shows an increase. This decrease isthought to be related to a decrease in the total number ofcyclones (Geng and Sugi 2003; Yin 2005) and has a similar
pattern to that also in our experiments (Fig. 4b). It isdifficult to explain the increase in cyclonedevelopment(Fig. 5) in terms of these lower-level situations.

c. Cyclone intensification and the upper troposphereA correspondence is seen between regions of jet intensification in the upper troposphere (Fig. 7a) and regionsof intensified surface cyclone development (Fig. 5b) at a
climatological time scale. To assess the correspondence
at a monthly-mean time scale, scatter diagrams of uppertropospheric zonal wind (average of 300–500 hPa) andcyclone growth rate for each month are shown in Fig. 8.
Those for each month of DJF for 25 yr of the JRA-25,
the three present-day experiments, and the three future
experiments in the 60-km model averaged over thenorthwest Pacific (1208E–1808, 408–558N; region P) andthe North Atlantic (408W–08, 458–608N; region A), where
growth rate shows a marked increase (Fig. 5b), are plotted in Figs. 8a and 8b. In addition, those averaged over
two regions (1208E–1808, 258–408N: region P9; 408W–08,
308–458N; region A9), where the growth rate decreases on
the equatorial side of the region P and A, are also plottedin Figs. 8c and 8d.
Strong, positive correlations are seen in regions P and
A in the JRA-25 reanalysis in the present-day experiments and in the future experiments (Figs. 8a,b),
whereas weaker correlations are seen in regions P9 andA9 (Figs. 8c,d). Note that in region P, the growth rate
shows a correlation with the meridional temperature
gradient at lower levels (;0.53) but not as high as theupper-tropospheric zonal wind. Unlike the case oftropical cyclone development, neither humidity nor latent heat flux is correlated with cyclone growth rate (notshown), while tropical cyclones are likely to intensify inthe future climate in response to an increase in water
vapor via enhanced latent heat release (Oouchi et al.
2006; Bengtsson et al. 2007). In regions P and A, months

6464

JOURNAL OF CLIMATEVOLUME 24

FIG. 6. Latitude–height sections of (a),(b) zonal mean temperature in units of K and (c),(d) zonal mean eddy
kinetic energy at a synoptic time scale (2.5–8.0 days) in units of m2 s22 for (a),(c) the 20-km model and (b),(d) the
three-member mean of the 60-km model. The contours show values of the present-day experiments (contour interval
is 40 m2 s22); shading indicates the difference between the present-day and future experiments.

with weak zonal wind (5–10 m s21) become less frequent in the future climate, and months with strong
zonal wind (25–30 m s21) become more frequent. Consequently, months of high cyclone growth rate become
more frequent, and months of low cyclone growth rate
become less frequent.
To know what process could relate the uppertropospheric wind speed to the surface cyclone growthrate in the region P and A, time evolutions in a shortertime scale are shown here for two extreme cases. Figure
9a shows a latitude–time cross section of 300-hPa zonal
wind averaged over 1208E–1808 during the winter of
2090/91 of a member of the future experiments, when theJanuary-mean growth rate in the region P is the highest
among the months of January in the present-day andfuture experiments. Closed and open circles denote thelatitudes and times of rapid surface cyclone development

in excess of 30 and 25 hPa day21, respectively. Most of
the rapid developments are confined to 358–558N. The
rapid developments commonly correspond to the enhancements of the wind at these latitudes at a time scaleof several days. At the same time, the jet is weakened
around the core latitudes (308–408N). Figure 9c shows
300-hPa zonal wind and rapid surface cyclone development during the winter of 1996/97 of a member of thepresent-day experiments, when the January-mean growthrate in the region P is the lowest. The zonal wind is steadythroughout winter and is stronger (weaker) at lower(higher) latitudes. The rapid cyclone developments aresparse and limited to periods of minor displacement of
the jet at around 3 and 15 January.
Snapshots of the Ertel’s potential vorticity (PV) andwind vector at 300 hPa for a typical day during theJanuary of Fig. 9a and one during the January of Fig. 9c

15 DECEMBER 2011

MIZUTA ET AL.

6465

FIG. 7. Horizontal distributions of (a),(d) zonal wind in units of m s21 and (b),(e) eddy kinetic energy at a synoptic time scale (2.5–
8.0 days) in units of m2 s22 and (c),(f) the maximum Eady growth rate in units of day21, at (a)–(c) 300 hPa and (d)–(f) 850 hPa. The contours
show values of the present-day experiments; shading indicates the difference between the present-day and future experiments. Open andclosed circles in (a),(d) indicate the locations of maximum wind for each longitude for the present-day and future experiments, respectively.

are shown in Figs. 9b and 9d. On the month with thehighest growth rate, anticyclonic wave-breaking patterns like Fig. 9b are frequently seen. This reflects anticyclonic shear is frequently dominant around thebreaking region (408–508N). The jet is often fluctuatedand displaced poleward, associated with the enhanced
polar jet and the future increase in eddy kinetic energy
in the upper troposphere (Fig. 7b). Closed and open
circles denote the positions of rapid surface cyclone
development in excess of 30 and 25 hPa day21, respectively, between 0000 UTC of the previous day and1800 UTC of that day. The rapid development of surface
cyclones is seen near regions with strong southwesterly
wind (Fig. 9b), where a strong horizontal PV gradientexists as a result of the displacement of high-PV air. In
this case, the breaking pattern is found in the upstreamof the rapid development. On the month with the lowest
growth rate, the wave-breaking pattern is cyclonic likeFig. 9d throughout most of the month, reflecting thecyclonic shear around the region. This is associated withthe strong subtropical jet and a reduced frequency ofmeandering of the jet.
To assess the difference in the wave-breaking patternin the upper troposphere between the months with thehigh growth rate and those with low growth rate, thewave-breaking pattern is categorized into LC1 type(anticyclonic shear) and LC2 type (cyclonic shear) andtheir frequencies are examined. One of the various
categorizing methods proposed by Gabriel and Peters(2008) is used. If PV at a grid point satisfies ›PV/›y ,0 and ›PV/›x . 0, the point is classified as LC1. If PV ata grid point satisfies ›PV/›y , 0 and ›PV/›x , 0, thepoint is classified as LC2.
Three months with the highest growth rate in the region P are picked up for each of the three future experiments (a total of nine months, referred to as HG) andthree months with the lowest growth rate in the region P
are picked up for each of the three present experiments (atotal of nine months, referred to as LG). Figure 10 compares the frequency of LC1 and LC2 at 300 hPa, for the6466

JOURNAL OF CLIMATEVOLUME 24

FIG. 8. Scatter diagrams of upper-tropospheric zonal wind averaged from 300 to 500 hPa and surface cyclone
growth rate for each month, for the regions of (a) the northwest Pacific (1208E–1808, 408–558N; region P) and (b) the
North Atlantic (408W–08, 458–608N; region A), (c) the equatorial side of region P (1208E–1808, 258–408N; region P9)and (d) the equatorial side of region A (408W–08, 308–458N; region A9). Green, blue, and red points indicate JRA-25,
the present-day experiments, and the future experiments, respectively, with their correlation coefficients.

average over HG and over LG. Because the height of
the isentropic surface shows a marked change with global
warming, the change is shown on the pressure surface.
In LG, occurrence of LC2 is more frequent (Fig. 10d)than that of LC1 (Fig. 10c) in most of the region P.
Meanwhile, occurrence of LC1 (Fig. 10a) and LC2 (Fig.
10b) is more comparable in HG. Compared with LG,
occurrence of LC1 in HG is more frequent over thewestern half of the region P (Fig. 10e), and occurrence of
LC2 in HG is much less frequent not only within theregion P but also in its upstream and downstream. Notethat comparing months with the highest and lowest
growth rate within the three present experiments also
gives similar results, with less pronounced difference(not shown).
Figure 11 is the result of the same calculation as Fig. 10
but for region A. A similar result to Fig. 10 is obtained
also in region A. Occurrence of LC2 in HG is much lessfrequent than in LG not only within the region A but
also in its upstream and downstream. Although occurrence15 DECEMBER 2011

MIZUTA ET AL.

6467

FIG. 9. (a),(c) Latitude–time cross section of 300-hPa zonal wind averaged over 1208E–1808 from the previous DJF of (a) 2091 ofa member of the future experiments, and (c) 1997 of a member of the present-day experiments. Closed and open circles denote the latitudes
and times of rapid surface cyclone development in 1208E–1808 in excess of 30 and 25 hPa day21, respectively. (b),(d) Snapshots of theErtel’s potential vorticity at 300 hPa (shading) and horizontal wind at 300 hPa (arrows) for (b) a typical day during (a), and for (d) a typical
day during (c). The units of potential vorticity are PVU (1 PVU 5 1026 K m2 s21 kg21). Closed and open circles denote the positions ofrapid surface cyclone development in excess of 30 and 25 hPa day21, respectively, between 0000 UTC of the previous day and 1800 UTC of
the present day.

of LC1 does not show a marked difference within the region A, it is more frequent in the upstream, equatorial
side around 608–208W, 208–458N. Under idealized simulations, averaged cyclone developments are more rapid
under anticyclonic wave breakings, and lifetimes of thecyclones become longer under cyclonic wave breakings(Thorncroft et al. 1993; Watanabe 2009). Although therelationships have not been statistically presented in thereal atmosphere, the increase in occurrence of LC1 isconsistent with the enhancement of cyclone development

FIG. 10. Frequency distributions of (a),(c),(e) LC1-type and (b),(d),(f) LC2-type breakings at 300 hPa, in (a),(b)averaged over nine months with high growth rate in the region P, in (c),(d) averaged over nine months with low
growth rate in the region P, and in (e),(f) the difference between the two. See text for details. The frequencies arecalculated for each 2.58 grid box. Units are 1 per month per box.

6468

JOURNAL OF CLIMATEVOLUME 24

FIG. 11. As in Fig. 10, but for the region A.

in our model. Moreover, the decrease in occurrence of
LC2 is also consistent with the decrease in long-lived
cyclones (Fig. 3), especially for weak cyclones. Note thatthe regions of increase in occurrence of LC1 are not thesame as regions P and A themselves. These shifts could
exist because the wave breaking and rapid cyclone development are occurring at different locations.
Therefore, one of the possibilities that can explain theincreasing growth rate in the future experiments ischanges in wave-breaking pattern, that is, a decrease inwave breakings in areas of cyclonic shear and an increase in wave breakings in areas of anticyclonic shear.
Associated with these changes, rapid cyclone developments can be more commonly seen, and weak,long-lived cyclones become less frequent.

4. Summary and discussion
Future changes in wintertime cyclone behavior were
investigated using a high-resolution AGCM forced by
the SST change estimated by the CMIP3 multimodel
ensemble mean. The total number of cyclones showsa decrease in future experiments. It is associated witha decrease in baroclinicity near the surface, resulting
from a large temperature increase in the polar region. In
contrast, the number of intense cyclones shows a future
increase. The increase is seen on the polar side, downstream of the storm track. The increase in the synopticscale activity can be explained by the increase in intense
cyclones in spite of the decrease in total cyclone numberof cyclones. Cyclone development is enhanced in theareas upstream of regions with intense cyclones.

The regions with enhanced cyclone development
correspond to regions with increasing zonal wind in theupper troposphere. In these regions, a strong correlationis seen between the upper-tropospheric zonal windspeed and the average surface cyclone growth rate ata monthly time scale. Months of high cyclone growthrate with strong zonal wind in these regions become
more frequent, and months of low cyclone growth ratewith weak zonal wind become less frequent. As a consequence of an enhanced upper-tropospheric polar jet,wave breaking in areas of cyclonic shear (LC2) is reduced and that in areas of anticyclonic shear (LC1) isincreased. This could explain the enhancement of thesurface cyclone developments. However, more studies
are needed on the relationships between the breaking
pattern and the cyclone development, which have notbeen statistically presented in the realistic atmosphere.
The zonal mean of zonal wind change (Figs. 7a,d)shows a decrease around 308N and an increase around508N. This has an equivalent barotropic structure, associated with a positive change in the Arctic Oscillationindex (Shindell et al. 1999; Yukimoto and Kodera 2005).
Around the middle–upper troposphere at midlatitudes,
an increase in the meridional temperature gradient leads
to an increase in eddy kinetic energy at a synoptic timescale (Fig. 7b), and an increase in equatorward Eliassen–
Palm (EP) flux, or poleward momentum flux, as a resultof changes in the refractive index. These changes correspond to weakening of the jet at around 308N andenhancement at around 508N (Rind et al. 2005).
In contrast, the location of the baroclinic zone near thesurface, where energy is supplied to the upper-tropospheric15 DECEMBER 20116469

MIZUTA ET AL.

Rossby wave, is influenced mainly by the meridional
gradient of SST. In our experimental setting, the change
in location of the strong SST gradient is not large.
Therefore, the relative positions of the baroclinic zone
and the jet are changed. Because the breaking pattern isdetermined largely by the relative position of the lowertropospheric baroclinic zone and the upper-troposphericjet (Thorncroft et al. 1993), wave breaking in areas of
cyclonic shear (LC2) shows a decrease and that in areas of
anticyclonic shear (LC1) shows an increase in the regions
shown in Fig. 8.
Especially in the Pacific, development is suppressedin midwinter, known as the midwinter suppression(Nakamura 1992). Nakamura and Sampe (2002) showedthat the suppression is due to the separation of the baroclinic zone and the subtropical jet. The reduced size of theseparation in the future may affect the change in cyclone
development via more frequent couplings (Inatsu andKimoto 2005). Note that the small change in the locationof the strong SST gradient may reflect the experimental
setup, in which the change in SST gradient in the CMIP3
models is smoothed by taking the ensemble mean.
Much of the change at lower altitudes tends to result in
weaker cyclone activity (Fig. 7e), except for changes inwind and water vapor. The future change in wind at lower
levels (Fig. 7d) is derived mainly from the upper level(Fig. 7a) via vertical momentum transport by baroclinic
eddies. The change in water vapor can result in enhanced
cyclone development. In fact, tropical cyclones are likely
to intensify in the future climate experiments, although
the number of storms is likely to be reduced; their intensification is related to an increase in water vapor(Oouchi et al. 2006; Bengtsson et al. 2007). Although latent heat flux from the surface shows an increase also in
the winter extratropics, the correlation between the flux
and the cyclone growth rate is weaker than that between
the flux and the jet. Furthermore, the increase in the latent heat flux cannot explain the decrease in cyclone
growth at around 308N (Fig. 5b), indicating that it is nota crucial factor, although it may play supplementary roleon the change in cyclone development.
Because higher-resolution models have an advantage
in representing the locations of storm tracks and blockings, especially in the Atlantic (Matsueda et al. 2009),
such models are suitable for investigating future changes
in storm behavior. In the same experiments as those analyzed in the present study, Matsueda et al. (2009) showed
the frequency of blocking events are reduced in the future
experiments, especially on the western side of the present
peaks. Moreover, using long-term ensemble simulations
are needed to obtain more statistically significant change
because phenomena in the wintertime extratropics havelarge internal, interannual variability. The detection ofsuch changes from observational data is currently a difficult task. Using long-term and high-resolution simulations, it would be possible to examine, as a topic for a
future study, the nature of the relationships between thechange in cyclones shown in the present study and otherchanges such as blockings, heat transport by transient or
stationary waves, and the Arctic Oscillation. However,even in the case that SST change is given by the ensemble
mean of the CMIP3 models, the present results arefrom a single atmospheric model. Once long-term, highresolution simulations have been performed using manyother models, many more things would be clarified
through a comparison of the simulation results.
Acknowledgments. This work was supported by the‘‘Projection of the Change in Future Weather Extremes
using Super-High-Resolution Atmospheric Models’’project as part of the KAKUSHIN Program by the
Ministry of Education, Culture, Sports, Science andTechnology of Japan. The model calculations weremade on the Earth Simulator. The GFD-DENNOU
Library was used for making the figures. We thank two
anonymous reviewers for constructive comments.
REFERENCES
Bengtsson, L., K. I. Hodges, and E. Roeckner, 2006: Storm tracks
and climate change. J. Climate, 19, 3518–3543.
——, ——, M. Esch, N. Keenlyside, L. Kornblueh, J.-J. Luo, andT. Yamagata, 2007: How May tropical cyclones change ina warmer climate? Tellus, 59A, 539–561.
——, ——, and N. Keenlyside, 2009: Will extratropical storms intensify in a warmer climate? J. Climate, 22, 2276–2301.
Gabriel, A., and D. Peters, 2008: A diagnostic study of different
types of Rossby wave breaking events in the Northern extratropics. J. Meteor. Soc. Japan, 86, 613–631.
Geng, Q. Z., and M. Sugi, 2003: Possible change of extratropical
cyclone activity due to enhanced greenhouse gases and sulfate
aerosols—Study with a high-resolution AGCM. J. Climate, 16,
2262–2274.
Hall, A., 2004: The role of surface albedo feedback in climate.
J. Climate, 17, 1550–1568.
Inatsu, M., and M. Kimoto, 2005: Two types of interannual variability of the mid-winter storm tracks and their relationship to
global warming. SOLA, 1, 61–64.
Jung, T., S. K. Gulev, I. Rudeva, and V. Soloviov, 2006: Sensitivityof extratropical cyclone characteristics to horizontal resolution in the ECMWF model. Quart. J. Roy. Meteor. Soc., 132,
1839–1857.
Kitoh, A., and Coauthors, 2009: Projection of changes in future
weather extremes using super-high-resolution global andregional atmospheric models in the KAKUSHIN Program:
Results of preliminary experiments. Hydro. Res. Lett., 3,
49–53.
Lambert, S. J., and J. C. Fyfe, 2006: Changes in winter cyclone
frequencies and strengths simulated in enhanced greenhousewarming experiments: Results from the models participatingin the IPCC diagnostic exercise. Climate Dyn., 26, 713–728.

6470

JOURNAL OF CLIMATE

Lindzen, R. S., and B. F. Farrell, 1980: A simple approximate result
for maximum growth rate of baroclinic instabilities. J. Atmos.
Sci., 37, 1648–1654.
Matsueda, M., R. Mizuta, and S. Kusunoki, 2009: Future change inwintertime atmospheric blocking simulated using a 20-kmmesh atmospheric global circulation model. J. Geophys. Res.,
114, D12114, doi:10.1029/2009JD011919.
Meehl, G., C. Covey, T. Delworth, M. Latif, B. McAvaney,
J. Mitchell, R. Stouffer, and K. Taylor, 2007: The WCRP
CMIP3 multimodel dataset: A new era in climate change research. Bull. Amer. Meteor. Soc., 88, 1383–1394.
Mizuta, R., and Coauthors, 2006: 20-km-mesh global climate
simulations using JMA-GSM model: Mean climate states.
J. Meteor. Soc. Japan, 84, 165–185.
——, Y. Adachi, S. Yukimoto, and K. Kusunoki, 2008: Estimationof future distribution of sea surface temperature and sea ice
using CMIP3 multi-model ensemble mean. MeteorologicalResearch Institute Tech. Rep. 56, 28 pp.
Nakamura, H., 1992: Midwinter suppression of baroclinic wave
activity in the Pacific. J. Atmos. Sci., 49, 1629–1641.
——, and T. Sampe, 2002: Trapping of synoptic-scale disturbances
into the North-Pacific subtropical jet core in midwinter. Geophys. Res. Lett., 29, 1761, doi:10.1029/2002GL015535.
Onogi, K., and Coauthors, 2007: The JRA-25 Reanalysis. J. Meteor.
Soc. Japan, 85, 369–432.
Oouchi, K, J. Yoshimura, H. Yoshimura, R. Mizuta, S. Kusunoki,
and A. Noda, 2006: Tropical cyclone climatology in a globalwarming climate as simulated in a 20 km-mesh global atmospheric model: Frequency and wind intensity analyses. J.
Meteor. Soc. Japan, 84, 259–276.
Pinto, J. G., U. Ulbrich, G. C. Leckebusch, T. Spangehl, M. Reyers,
and S. Zacharias, 2007: Changes in storm track and cyclone
activity in three SRES ensemble experiments with the
ECHAM5/MPIOM1 GCM. Climate Dyn., 29, 195–210.
Rayner, N. A., D. E. Parker, E. B. Horton, C. K. Folland, L. V.
Alexander, D. P. Rowell, E. C. Kent, and A. Kaplan, 2003:
Global analyses of sea surface temperature, sea ice, and nightmarine air temperature since the late nineteenth century.
J. Geophys. Res., 108, 4407, doi:10.1029/2002JD002670.
Rind, D., J. Perlwitz, and P. Lonergan, 2005: AO/NAO response to
climate change: 1. Respective influences of stratospheric andtropospheric climate changes. J. Geophys. Res., 110, D12107,
doi:10.1029/2004JD005103.

VOLUME 24

Shapiro, M. A., and Coauthors, 1999: A planetary-scale to mesoscale perspective of the life cycles of extratropical cyclones:
The bridge between theory and observations. The Life Cycles
of Extratropical Cyclones, M. A. Shapiro and S. Grønås, Eds.,
Amer. Meteor. Soc., 139–185.
Shindell, D., R. Miller, G. Schmidt, and L. Pandolfo, 1999: Simulation of recent northern winter climate trends by greenhousegas forcing. Nature, 399, 452–455.
Solomon, S., D. Qin, M. Manning, M. Marquis, K. Averyt, M. M. B.
Tignor, H. L. Miller Jr., and Z. Chen, Eds., 2007: Climate
Change 2007: The Physical Science Basis. Cambridge University Press, 996 pp.
Thorncroft, C. D., B. J. Hoskins, and M. McIntyre, 1993: Twoparadigms of baroclinic-wave life-cycle behavior. Quart.
J. Roy. Meteor. Soc., 119, 17–55.
Ulbrich, U., J. G. Pinto, H. Kupfer, G. C. Leckebusch, T. Spangehl,
and M. Reyers, 2008: Changing Northern Hemisphere storm
tracks in an ensemble of IPCC climate change simulations.
J. Climate, 21, 1669–1679.
——, G. C. Leckebusch, and J. G. Pinto, 2009: Extra-tropical cyclones in the present and future climate: A review. Theor.
Appl. Climatol., 96, 117–131.
Watanabe, M., 2009: Self-limiting feedback between baroclinic
waves and a NAO-like sheared zonal flow. Geophys. Res.
Lett., 36, L08803, doi:10.1029/2009GL037176.
Wernli, H., R. Fehlmann, and D. Lüthi, 1998: The effect of barotropic shear on upper-level induced cyclogenesis: Semigeostrophic and primitive equation numerical simulations.
J. Atmos. Sci., 55, 2080–2094.
Winton, M., 2006: Amplified Arctic climate change: What does
surface albedo feedback have to do with it? Geophys. Res.
Lett., 33, L03701, doi:10.1029/2005GL025244.
Yin, J. H., 2005: A consistent poleward shift of the storm tracks
insimulations of 21st century climate. Geophys. Res. Lett., 32,
L18701, doi:10.1029/2005GL023684.
Yoshiike, S., and R. Kawamura, 2009: Influence of wintertime
large-scale circulation on the explosively developing cyclones
over the western North Pacific and their downstream effects.
J. Geophys. Res., 114, D13110, doi:10.1029/2009JD011820.
Yukimoto, S., and K. Kodera, 2005: Interdecadal Arctic Oscillationin twentieth century climate simulations viewed as internalvariability and response to external forcing. Geophys. Res.
Lett., 32, L03707, doi:10.1029/2004GL021870.