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JOURNAL OF CLIMATE
VOLUME 25
Changes in the Extratropical Storm Tracks in Response
to Changes in SST in an AGCM
LISE SELAND GRAFF AND J. H. LACASCE
Meteorology and Oceanography Section, Department of Geosciences, University of Oslo, Oslo, Norway
(Manuscript received 29 March 2011, in final form 12 August 2011)
ABSTRACT
A poleward shift in the extratropical storm tracks has been identified in observational and climate simulations. The authors examine the role of altered sea surface temperatures (SSTs) on the storm-track position
and intensity in an atmospheric general circulation model (AGCM) using realistic lower boundary conditions.
A set of experiments was conducted in which the SSTs where changed by 2 K in specified latitude bands.
The primary profile was inspired by the observed trend in ocean temperatures, with the largest warming
occurring at low latitudes. The response to several other heating patterns was also investigated, to examine the
effect of imposed gradients and low- versus high-latitude heating. The focus is on the Northern Hemisphere
(NH) winter, averaged over a 20-yr period.
Results show that the storm tracks respond to changes in both the mean SST and SST gradients, consistent
with previous studies employing aquaplanet (water only) boundary conditions. Increasing the mean SST
strengthens the Hadley circulation and the subtropical jets, causing the storm tracks to intensify and shift
poleward. Increasing the SST gradient at midlatitudes similarly causes an intensification and a poleward shift
of the storm tracks. Increasing the gradient in the tropics, on the other hand, causes the Hadley cells to
contract and the storm tracks to shift equatorward. Consistent shifts are seen in the mean zonal velocity, the
atmospheric baroclinicity, the eddy heat and momentum fluxes, and the atmospheric meridional overturning
circulation. The results support the idea that oceanic heating could be a contributing factor to the observed
shift in the storm tracks.
1. Introduction
Extratropical cyclones form preferentially in the storm
tracks (e.g., Blackmon et al. 1977; Hoskins and Valdes
1990; Chang et al. 2002). These lie at midlatitudes and are
intensified over the oceans. In the Northern Hemisphere
(NH), where the oceans occupy only a fraction of the
surface area, there are two distinct tracks: over the North
Atlantic and the North Pacific. In the Southern Hemisphere (SH), where the oceans cover a greater area, a single storm track is found, and this is more zonal. The storm
tracks are dynamically important in both hemispheres, at
both short and longer time scales. The regions are associated with increased precipitation and winds and are subject
to extreme weather events. The storm tracks are instrumental for meridional heat transport and thus the reduction of the equator-to-pole temperature gradient.
Corresponding author address: Lise Seland Graff, Meteorology
and Oceanography Section, University of Oslo, P.O. Box 1022,
Blindern, N-0315 Oslo, Norway.
E-mail: l.s.graff@geo.uio.no
DOI: 10.1175/JCLI-D-11-00174.1
Ó 2012 American Meteorological Society
There is growing evidence that the storm tracks are
systematically changing in the warming climate, shifting
poleward in both hemispheres. Observational studies
suggest that the number of cyclones has decreased at
midlatitudes in the NH during the last half of the twentieth century, whereas the number at high latitudes has
increased (e.g., McCabe et al. 2001; Wang et al. 2006).
The cyclone count between 408 and 608S has decreased
during the same period (Simmonds and Keay 2000; Fyfe
2003), whereas it has slightly increased poleward of 608S
(Fyfe 2003). The shift in the SH storm track is occurring
simultaneously with a poleward migration of the westerly jet (e.g., Chen and Held 2007) and of the atmospheric baroclinicity (e.g., Fyfe 2003).
Similar changes have been seen in models forced
according to specific climate warming scenarios (e.g.,
Nakicenovic and Swart 2000), as documented by the
Intergovernmental Panel of Climate Change (IPCC)
(Meehl et al. 2007). In a study of an ensemble of 15 coupled general circulation models (GCMs), Yin (2005) found
that the storm tracks intensified in the warmer climate and
shifted poleward and upward along with the baroclinicity.
15 MARCH 2012
GRAFF AND LACASCE
Fischer-Bruns et al. (2005), Bengtsson et al. (2006),
Ulbrich et al. (2008), and Wu et al. (2011) observed similar
changes in simulations with the same and other warming
scenarios.
The storm tracks are clearly influenced by the ocean
surface. Cyclones generated over open water preferentially do so close to oceanic frontal zones, in regions
with strong sea surface temperatures (SST) gradients
(Sinclair 1995). The track position and intensity are
heavily influenced by low-level baroclinicity associated
with such frontal zones (e.g., Nakamura and Shimpo
2004; Nakamura et al. 2008; Sampe et al. 2010). Sampe
et al. (2010) found that, when removing such a frontal
zone (based on southwestern Indian Ocean climatology) in an aquaplanet simulation, the storm tracks
weaken and shift equatorward. Similarly, there is evidence that the ocean shifts the NH storm tracks poleward by transporting heat and thereby intensifying the
SST gradients along the western boundaries of the
ocean basins (Wilson et al. 2009). In addition, the storm
tracks shift in response to other SST changes, such as
those associated with El Niño–Southern Oscillation
(ENSO) (e.g., Chang and Fu 2002; Chang et al. 2002;
Orlanski 2005). Therefore, it is reasonable to ask whether
the poleward shift observed over the previous decades
and that seen in climate simulations is also related to
systematic changes in SST.
Several studies have addressed such issues, using
aquaplanet simulations. Caballero and Langen (2005)
found an increase in poleward heat transport and a poleward shift in the storm tracks in response to an increase
in the global-mean SST. Kodama and Iwasaki (2009) and
Lu et al. (2010) found similar changes. Brayshaw et al.
(2008) observed similar shifts but suggested they derived
from changes in the SST gradient. In their simulations,
the direction of shift was dictated not only by the sign of
the change in SST gradient but also by where the gradient
was altered. Increasing the gradient at midlatitudes produced a poleward shift in the tracks while increasing it in
the tropics yielded an equatorward shift. However, the
relative importance of the mean surface temperature
and the gradients remains unclear. Caballero and Langen
(2005), Lu et al. (2010), and Kodama and Iwasaki (2009)
found little change in storm-track position when altering
only the SST gradient.
Observations suggest the oceans are indeed warming.
The warming moreover is intensified at the ocean surface
and at low latitudes (Levitus et al. 2005). SST has increased up to 18C over the past 50 yr in the tropics, with
smaller changes at higher latitudes (bottom right panel
of Fig. 5.3 in Bindoff et al. 2007; P. Durack et al. 2011,
personal communication). Such changes would imply an
increase in the temperature gradients at midlatitudes.
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The goal of the present study is to see how the storm
tracks respond to such changes in SST in a realistic atmospheric model. The model, the atmospheric component of the National Center of Atmospheric Research
(NCAR) Community Climate System Model (CCSM),
has a more realistic lower boundary than in the aquaplanet simulations, including continents and orography.
The latter significantly affect the circulation, particularly
in the NH. We imposed various changes to SST and then
observed the changes in the storm tracks. The primary
focus is on warming at low latitudes, but we also consider
scenarios where the warming or cooling is confined to
high latitudes and to the tropics and where the warming
is uniform with latitude.
The results in many ways resemble those found in the
aforementioned aquaplanet simulations, suggesting that
the oceans exert a similar influence even when land is
present. This is true in both hemispheres, even though
the oceans occupy a different fraction of the total surface area. The results then support the notion that SST is
central to storm-track dynamics (with implications not
only for climate change but also for weather forecasting,
particularly on seasonal time scales).
The model and the SST modifications are described in
section 2 and the analysis methods are described in
section 3. The results are presented in section 4, a 20-yr
control run first and then the experiments with altered
SST. The results are discussed in section 5.
2. Model and data
For the simulations, we used the NCAR Community
Atmosphere Model version 3 (CAM3), the atmospheric
component of the NCAR CCSM version 3 (Collins et al.
2004). CAM3 has been used previously to study the
storm track (e.g., Hurrell et al. 2006; Alexander et al.
2006; Donohoe and Battisti 2009). In terms of bandpassfiltered eddy kinetic energy, the majority of structures
and interseasonal changes are well simulated in CAM3
(Hurrell et al. 2006).
We ran the model in its stand-alone version, with the
Community Land Model (version 3.0) and a thermodynamic sea ice model. We used T42 resolution in the
horizontal and 26 vertical hybrid levels. The SST was
specified using a climatological dataset, with 12 monthly
samples (i.e., the SST changes from month to month but
not daily). For additional information on the model, see
Collins et al. (2006) and Hurrell et al. (2006).
We will focus on six experiments, one control and five
sensitivity runs. All span the 20-yr period from 1 December
1980 to 28 February 2000. The control run employs
standard surface forcing over the 20-yr period, including
climatological SSTs. In the sensitivity runs, the SSTs were
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JOURNAL OF CLIMATE
VOLUME 25
FIG. 1. The SST modification (i.e., difference from the control run) in (a) the 2-K lowlat run, (b) the 2-K run, (c) 2-K
highlat run, and (d) the 2-K tropics run. Contour interval (CI) is 0.5 K, as indicated in the gray-shade bar. Note that
the SST change in the 22-K highlat run (not shown) is the same as in the 2-K highlat run, only negative.
increased or decreased by 2 K in different domains, as
shown in Figs. 1 and 2. The initial surface temperature
over land was left unaltered in all runs and SSTs were
not changed where there is sea ice (e.g., in the Arctic and
Antarctic). In the ‘‘2 K’’ run, SSTs were increased over
the entire ocean. In the ‘‘2-K lowlat’’ and ‘‘2-K tropics’’
runs, the SSTs were increased equatorward of 458 and 158,
respectively. In the ‘‘2-K highlat’’ and ‘‘22-K highlat’’
runs, the SSTs were increased and decreased by 2 K
poleward of 458. When a domain boundary was located
within the ocean basin, the SST increment was linearly
relaxed to climatology over a latitude band of 88 along
that boundary. Thus, in these cases, the SST gradient
was altered as well. In the 22-K highlat and 2-K lowlat
runs, the gradient was increased at midlatitudes around
458, whereas in the 2-K highlat run it was decreased.
In the 2-K tropics run, the gradient was increased at
158.
Unlike the aquaplanet simulations, the oceans cover
only a fraction of the earth’s surface, to a degree that
varies with latitude. As a result, warming the ocean uniformly, as in the 2-K run, also changes the zonally averaged SST gradients (Fig. 2). Moreover, the change is
greater in the NH, where the land fraction is greater.
Furthermore, because the temperatures were not altered
over ice, the gradients are affected where the sea meets
ice (e.g., at Antarctica).
We focus on the NH winter season [December–
February (DJF)] for both hemispheres. An alternative is
to use the SH winter season for that hemisphere and then
to merge the figures (e.g., Sampe et al. 2010). However,
the winter response in the SH is qualitatively similar to
the summer response (section 4), so we will employ the
DJF period for both. All data were interpolated to constant pressure surfaces, with a 50-hPa interval, from 850
to 50 hPa.
For validation, we used the geopotential height field
at the 500-hPa surface (Z500 hPa) from the National
Center of Environmental Prediction (NCEP)–NCAR
Global Reanalysis 1 (NCEP-1) [Kalnay et al. 1996;
NCEP-1 data are provided by the National Oceanic and
Atmospheric Administration (NOAA); see http://www.
cdc.noaa.gov/]. The NCEP-1 data were taken from the
same time period and season as the CAM3 data.
3. Analysis method
Three methods of identifying the storm tracks are commonly used. One is ‘‘feature point identification’’ (e.g.,
Klein 1957; Reitan 1974; Serreze et al. 1997; McCabe
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GRAFF AND LACASCE
FIG. 2. The initial zonally averaged DJF SST field from the
control run (dashed line) and the corresponding difference field
from the 2-K run (solid line). Vertical lines indicate the latitudes
where SST modifications starts/stops in the other modified runs:
namely, 158N/S (the 2-K tropics run) and 458N/S (the 2-K lowlat
run and the 2-K highlat run). So, for example, the SST field from
the 2-K tropics run is indicated by the part of the solid curve between the vertical lines 158S and 158N. Temperature is given in
kelvins.
et al. 2001; Paciorek et al. 2002; Hoskins and Hodges
2002; Fyfe 2003; Benestad and Chen 2006), which identifies low pressure centers (commonly using surface pressure) in space and time. Then the storm tracks are evident
as regions with high cyclone count densities. The second
involves tracking cyclones, identified typically by surface
pressure or vorticity (e.g., Hinman 1888; Klein 1957;
Murray and Simmonds 1991; Sinclair 1994, 1995; Blender
et al. 1997; Serreze et al. 1997; Simmonds and Keay 2000;
Hoskins and Hodges 2002, 2005; Bengtsson et al. 2006;
Wang et al. 2006). The storm tracks can then be identified
as regions of high track density. An advantage with this
method is that it allows studying changes in the storms
during their life cycles. Using surface pressure, the approach captures the large-scale structure of the tracks
but can also be affected by biased extrapolation over
high topography or large-scale flows (e.g., the Icelandic
low–fast jets) (e.g., Hoskins and Hodges 2002; Ulbrich
et al. 2009). Using vorticity, the results preferentially
capture the small scales, but the results also depend
strongly on model resolution (e.g., Hoskins and Hodges
2002).
The third method involves bandpass-filtered fields,
where fluctuations with time scales between roughly
1 and 8 days are retained (e.g., Blackmon 1976; Blackmon
et al. 1977; Hartmann 1974; Randel and Stanford 1985;
Trenberth 1991; Branstator 1992; Chang and Fu 2002;
Nakamura and Shimpo 2004; Yin 2005; Brayshaw et al.
2008; Ulbrich et al. 2008; Sampe et al. 2010; Wu et al.
2011). The storm tracks are evident as maxima in the
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variability of these bandpassed fields (e.g., Blackmon
et al. 1977). The bandpass method is less selective than
cyclone tracking, capturing both cyclones and anticyclones as well as other disturbances with the chosen time
scales. However, the method is straightforward to apply,
is easily reproducible, and can be carried out at any altitude, allowing for 3D reconstructions (e.g., Blackmon
et al. 1977; Chang et al. 2002). The method has been used,
among other things, to demonstrate the relation between
the storm tracks and the variability of the large-scale flow
(e.g., Branstator 1992, 1995).
In the present study, we will use the bandpass method.
In terms of bandpassed statistics, the storm tracks can
be represented using a variety of fields including geopotential height Z, pressure, temperature, and velocity
(e.g., Blackmon et al. 1977; Chang et al. 2002; Hoskins
and Hodges 2002). Our focus will be on the standard deviation of the bandpassed Z field. Following Blackmon
(1976) and Blackmon et al. (1977), we retain fluctuations
with time periods between 2.5 and 6 days.
We will also focus primarily on zonal averages, although horizontal (2D) fields are used to compare the
control run with reanalysis fields and to identify zonal
asymmetries. Then we use the zonally averaged fields to
compare the control run with the various modified runs.
4. Results
a. The control run
We first consider the fields from the control run, comparing them to those from the NCEP-1 reanalysis and
pointing out differences between the NH and SH. Similar
fields have been described previously, so the presentation
will be brief. However, the measures used in the subsequent sections are also introduced. Note that, in what
follows, the fields are generally temporally averaged with
the exception of the bandpassed Z fields for which we
show the standard deviation, which is denoted with an SD
subscript (ZSD).
1) HORIZONTAL FIELDS
The bandpassed ZSD field on the 500-hPa surface
Z500hPa,SD from the control run for the NH winter
(DJF) is shown in Fig. 3a. The storm tracks appear as
bands of increased variability in both hemispheres, situated between approximately 408 and 608. In the NH,
the tracks are intensified over the Atlantic and Pacific
and tilt to the northeast. The variability intensifies near
the east coasts of North America and Asia, in the socalled entrance regions (e.g., Hoskins and Valdes 1990;
Chang et al. 2002; Hoskins and Hodges 2002). In the SH,
the variability increases east of the Andes, peaks in the
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FIG. 3. The (a) DJF and (b) JJA bandpass ZSD standard deviation fields from the control run. (c) The DJF bandpass
ZSD standard deviation field from the NCEP-1. (d) The mean bandpass y9T9 field from the control run. All fields are
taken at the 500-hPa surface. CI is 5 m in (a)–(c) and 1 K m s21 in (d).
southern Indian Ocean, and then decreases over the
South Pacific. The SH storm track is considerably more
zonal than that in the NH (e.g., Trenberth 1991).
The storm tracks from the NH summer [July–August
(JJA)] are shown in Fig. 3b. The NH tracks are considerably weaker and shifted poleward compared to DJF.
They are also more zonal, displaying less tilt. The SH storm
track on the other hand has intensified and tilts somewhat
to the southeast, particularly south of Australia. The result
is a spiral structure (Trenberth 1991; Inatsu and Hoskins
2004; Hoskins and Hodges 2005). Nevertheless, the SH
storm track has largely the same structure in both seasons;
as such, we will focus exclusively on the DJF response in
both hemispheres.
The NH winter bandpassed Z500hPa,SD field from the
NCEP-1 is shown in Fig. 3c. The structure closely resembles that in the CAM3 field, both in location and
amplitude. However, the NH storm tracks in CAM3
are slightly stronger in the entrance regions and weaker
in the exit regions. In addition, the simulated tracks are
somewhat too zonal, as noted by Hurrell et al. (2006).
In the SH, the two fields are very similar, except for
small differences in amplitude. Thus, the CAM3 fields
are realistic enough to warrant the sensitivity studies
that follow.
The temporally averaged bandpassed eddy heat fluxes
y9T9 from the 500-hPa surface are shown in Fig. 3d. The
fluxes are calculated as follows:
y9BP T9BP 5 y BP TBP 2 y BP T BP .
(1)
The subscript BP indicates bandpass filtered (dropped
hereafter), and the bar indicates a temporal average; the
remaining notation is standard. The heat transport is
strongest in the storm tracks, particularly in the entrance
regions (e.g., Blackmon et al. 1977; Hoskins and Valdes
1990; Chang et al. 2002). However, the fluxes are positive
over much of the NH (and negative in the SH), indicating
poleward transport of warm air and equatorward transport of cold air over the entire region. The largest maximum in the NH is in the Atlantic track, whereas the largest
maximum in the SH is in the southern Indian Ocean.
2) ZONALLY AVERAGED FIELDS
Hereafter, we focus on the zonally averaged fields,
which are a convenient means for comparing the runs.
However, it should be noted that such fields are perhaps
more appropriate for the SH, where the (summer) storm
track is more zonal. Because the fields are tilted in the
NH, they are somewhat spread out in zonal average.
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GRAFF AND LACASCE
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FIG. 4. Zonally averaged DJF fields from the control run. (a) The bandpass [ZSD] standard deviation field; CI
is 5 m. (b) The [sB1 ] field; CI is 1 3 1021 day21. (c) The [u] field; CI is 5 m s21. (d) The [sB1,dT /dy ] field; CI is
1 3 1021 day21. (e) The [CM ] field; CI is 1 3 1010 kg s21. (f) The [sB1,N ] field; CI is 1 3 1021 day21.
Despite this, the changes are usually clear in both
hemispheres. Zonal averages will be denoted by square
brackets.
The bandpassed [ZSD] field from the control run is
shown in Fig. 4a. One maximum is seen in the extratropics of each hemisphere, between 408 and 608. The
NH maximum is wider, which is consistent with the
aforementioned spreading.
The temporally and zonally averaged zonal wind [u] is
shown in Fig. 4c. Each hemisphere has a westerly jet,
which lies equatorward and above the bandpassed [ZSD]
maxima. As is well known, the jets represent a merger of
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FIG. 5. Zonally averaged DJF fields from the control run. (a) The mean bandpass [y9T9] field, with CI of 1 K m s21.
(b) The mean bandpass [u9y9] field, with CI of 4 m2 s22.
two structures, a baroclinic subtropical jet on the equatorward side and a more barotropic eddy-driven jet on
the poleward side.
It is also useful to consider the meridional overturning
circulation streamfunction CM, which is defined as (e.g.,
Hartmann 1994)
CM
ð
2pa cos(f) p
5
[y] dp.
g
0
(2)
Here, a is the mean radius of the earth and f is the
latitude. The [CM ] field (Fig. 4e) conveniently captures
the secondary circulation over the range of latitudes. It is
useful in the present context, because it shows how the
Hadley and Ferrel cells shift with the other fields. As is
typical during the NH winter, the NH Hadley cell is
displaced southward across the equator and the Hadley
cell in the SH is weaker. The eddy-driven Ferrel cells are
evident in both hemispheres, with similar magnitudes.
Thus, in the SH, the eddy-driven overturning accounts
for a greater portion of the total.
The storm tracks derive from the baroclinic instability
of the westerly jets, and a frequently used measure of the
latter is the Eady parameter of maximum baroclinic
growth sB1 (Lindzen and Farrell 1980; Hoskins and
Valdes 1990; Chang et al. 2002; Yin 2005). Here, sB1 is
defined as
sB1
g ›T 5 0:31
,
N[T] ›y (3)
where N is the Brunt–Väisälä frequency. Thus, sB1 is
proportional to the meridional temperature gradient and
inversely proportional to the Brunt–Väisälä frequency, so
that increasing the temperature gradient increases baroclinicity whereas increasing static stability decreases it.
The value of [sB1 ] is plotted in Fig. 4b. In each
hemisphere, there is a maximum near 400 hPa. There is
also a secondary maximum higher up, between 100 and
50 hPa. The maxima occur in regions of strong vertical
shear in u. They lie below the corresponding maxima in
bandpassed [ZSD] and, in the NH, equatorward.
Of the Brunt–Väisälä frequency and the meridional
temperature gradient, it is the latter that dominates the
structure seen here. To show this, we decompose sB1
into two parts, one that varies only with the temperature gradient sB1,dT/dy and another that varies with the
Brunt–Väisälä frequency sB1,N (Yin 2005). They are
defined as
sB1,dT /dy
sB1,N
›T g
,
5 0:31
Nref [T]ref ›y g ›T 5 0:31
,
N[T]ref ›y ref
(4)
where Nref, [T]ref, and j›T/›yjref are reference values
derived from the spatially and temporally averaged
control run fields.
The terms [sB1,dT /dy ] and [sB1,N ] are shown in Figs. 4d,f.
We see that [sB1,dT /dy ] captures the main features of [sB1 ],
whereas [sB1,N ] is weaker and different in structure. Thus,
[sB1 ] is dominated by the meridional temperature gradient, as in Yin (2005). The same result obtains in the sensitivity runs; as such, we only show [sB1 ] hereafter.
As noted, the storm bands are regions of intensified
eddy fluxes of heat and also momentum. The temporally
and zonally averaged bandpassed eddy fluxes of heat and
momentum [y9T9] and [u9y9] are shown in Figs. 5a,b. As
expected, the fluxes are poleward and intensified in the
storm tracks. The [y9T9] field displays largest values near
the bottom boundary but also intensified at the jet level.
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GRAFF AND LACASCE
In the [u9y9] field, one large maximum is evident in each
hemisphere, slightly below the jet cores. Such fluxes yield
a poleward intensification of the zonal flow, as (e.g.,
Holton 2004)
›[u]
›[u9y9]
}2
.
›t
›y
(5)
The gradient of [u9y9] is positive on the equatorward side
of the maximum and negative on the poleward side,
forcing a poleward shift of the mean flow.
b. Sensitivity runs
Hereafter, we consider the sensitivity runs. We examine the same fields as in the control run (bandpassed
[ZSD ], [u], [CM ], [sB1 ], [y9T9], and [u9y9]). Differences
from the control run are plotted rather than the full fields,
to accentuate the response to the imposed changes in SST.
1) THE 2-K LOWLAT RUN
SSTs were increased by 2 K equatorward of 458 in the
2-K lowlat run, as illustrated in Fig. 1a. Thus, both the
low-latitude heating and the midlatitude SST gradients
were increased in this case. The difference plots are
shown in Fig. 6.
The difference in the bandpassed [ZSD] field is shown
in Fig. 6a. The storm tracks have intensified: the maxima
are approximately 20% stronger, with the deviations at
the lowest level larger by 10%–15%. In addition, the
maxima have shifted poleward by roughly 78–88. In the
NH, the track has also shifted slightly upward.
The changes in [u] are shown in Fig. 6c. In the SH, both
the subtropical and eddy-driven jets have intensified, illustrating the double-jet structure clearly. Note that the
center of the eddy-driven jet is slightly equatorward of
the bandpassed [ZSD] maximum. Similar changes are
seen in the NH, although the separation between subtropical and eddy-driven jets is less clear. The impression
is rather of a poleward shift and a strengthening of the
barotropic flow.
The change in [CM ] (Fig. 6e) is likewise clearest in the
SH. The Ferrel cell has shifted poleward, in line with the
bandpassed [ZSD] variability. The Hadley cell (which
has a negative sense) has also shifted poleward, because
the change is negative on the poleward side and positive
on the equatorward side. In the NH, the Ferrel cell has
also shifted poleward. The changes in the Hadley cell on
the other hand are more skewed: the cell has intensified
on the poleward side, near 308N, but has also weakened
somewhat at height along its southern edge. It has also
intensified near the upper boundary, at tropopause
height.
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The change in [sB1 ] is shown in Fig. 6b. The strengthening of the two jets in the SH increases the shear and this
is mirrored in [sB1 ], which displays a two-maximum
structure. As noted, the latter is dominated by changes in
the meridional temperature gradient and hence the shear.
In the NH, where the two jets are merged, there is only
a single maximum in the [sB1 ] difference.
The eddy fluxes [y9T9] and [u9y9] (Figs. 6d,f) have
intensified and shifted poleward, in both hemispheres.
Interestingly, the [y9T9] difference has a nearly barotropic
structure over much of the troposphere. The [u9y9] difference on the other hand is more localized at the jet level.
As noted, we increased both the mean temperature
and the temperature gradient at midlatitudes in the 2-K
lowlat run. The subsequent runs are meant to distinguish
these forcings.
2) THE 2-K RUN
In the 2-K run, the surface ocean is warmed uniformly
by 2 K, as shown in Fig. 1b. As noted though, such a
change also affects the zonally averaged surface temperature gradients, because the oceans cover a varying
fraction of the surface area.
The difference fields are shown in Fig. 7. These resemble
those in the previous run, but with weaker amplitudes. The
bandpassed [ZSD] difference field suggest the storm tracks
have intensified and shifted poleward, in both hemispheres, but the changes are less than before. Likewise, the
[u] difference field shows an intensification and poleward
shift in the jets, with the greatest changes occurring near the
subtropical jets. The [sB1 ] difference field also resembles
the previous one, and the changes in the vicinity of the
subtropical jet are comparable. Likewise, the [CM ] difference field suggests the Hadley and Ferrel cells have
shifted poleward and intensified, but to a lesser extent than
in the previous run. The same comments apply to [y9T9]
and [u9y9], whose maxima have shifted poleward.
Thus, the mean SST also appears to be important for
the strength and position of the storm tracks. Primarily, the
increased diabatic heating at low latitudes strengthens
the Hadley circulation, yielding stronger subtropical jets.
Note that the changes in the [ZSD] field in the SH occur
near 608S, where the ocean meets the Antarctic continent. This suggests that the changes in the SH may be due
to an altered surface temperature gradient there. However, the NH bandpassed [ZSD] field changes comparably, and the storm track lies well south of the ocean–ice
boundary. The changes in any case are weaker in this
example than in the 2-K lowlat run.
3) THE 62-K HIGHLAT RUNS
In the two 2-K highlat runs, the SSTs were increased
and decreased by 2 K poleward of 458. The increase in
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VOLUME 25
FIG. 6. Zonally averaged DJF difference plots from the 2-K lowlat run. The thick solid (stippled) contours are
positive (negative) control run contours (CRCs) for reference. The thin filled contours are difference field
contours. (a) The bandpass [ZSD] standard deviation difference field; CI is 2 m, and CRCs are 20, 30, 40, 50, 60,
and 70 m. (b) The [sB1 ] difference field; CI is 2 3 1022 day21, and CRCs are 5, 6, 7, and 8 day21. (c) The [u]
difference field; CI is 1 m s21, and CRCs are 10, 20, 30, and 40 m s21. (d) The [y9T9] field; CI is 2 3 1021 K m s21,
and CRCs are 26, 24, 22, 2 and 4 K m s21. (e) The [CM ] difference field; CI is 2 3 109 kg s21, and CRCs are
24, 23, 22, 21, 1, 2, 3, and 4 3 1010 kg s21. (f) The [u9y9] field; CI is 1 m2 s22, and CRCs are 216, 212, 28, 24, 0,
4, 8, and 12 m2 s22.
15 MARCH 2012
GRAFF AND LACASCE
1863
FIG. 7. As in Fig. 6, but for the 2-K run.
the 2-K highlat run is shown in Fig. 1c. The SST difference
in the 22-K highlat run is the same, with the opposite
sign. Thus, the midlatitude SST gradient was weakened
and strengthened in these runs, respectively, without
changing the low-latitude temperatures.
Consider the 22-K highlat run first (difference fields
are shown in Fig. 8). In this, the temperature gradient at
458 has increased as much as in the 2-K lowlat run (Fig. 6).
The bandpassed [ZSD] difference field indicates the storm
band has intensified and shifted poleward. The changes
are less than in the 2-K lowlat run but are quite comparable to those in the 2-K run. However, unlike in that
run, the largest changes in [u] occur near the eddy-driven
jets, with little change in the subtropical jets. The [sB1 ]
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VOLUME 25
FIG. 8. As in Fig. 6, but for the 22-K highlat run.
difference field reflects this, with the largest changes
occurring at midlatitudes. The Ferrel cells have also
shifted poleward, as might be expected, but the Hadley
cells have widened as well. The change in the midlatitude gradient has also produced an intensification of
the eddy fluxes. In fact, the changes are greater than in
the 2-K run and comparable to those seen in the 2-K
lowlat run.
Now, consider the 2-K highlat run (Fig. 9). As noted, the
midlatitude SST gradient is weakened here. The result is
that the storm track weakens and shifts equatorward.
Consistently, the eddy fluxes shift equatorward and the
overturning cells have contracted. However, as in the 22-K
highlat run, the subtropical jets are left largely unchanged.
Thus, the two 2-K highlat runs are consistent with the
midlatitude SST gradient influencing the position of the
15 MARCH 2012
GRAFF AND LACASCE
1865
FIG. 9. As in Fig. 6, but for the 2-K highlat run.
storm tracks. However, the subtropical jets are largely
unaltered in these runs, unlike in the 2-K run. The
changes in [ZSD] are comparable to those seen in the 2-K
run but weaker than in the 2-K lowlat run. This suggests
that the storm-track variability in that run stems from
both the increase in tropical heating and the change in
the midlatitude SST gradient.
4) THE 2-K TROPICS RUN
The 2-K tropics run resembles the 2-K lowlat run in
that both the low-latitude SSTs and the SST gradients
have been increased. However, the heating is restricted
to the tropics and the gradient is increased at 158 inside
the NH Hadley cell and at the equatorward edge of the
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VOLUME 25
FIG. 10. As in Fig. 6, but for the 2-K tropics run.
SH Hadley cell (Fig. 1). The resulting difference fields
are shown in Fig. 10.
There is a pronounced intensification in the subtropical
jets, in both hemispheres, on the equatorward sides.
Consistently, the Hadley cells have contracted and the
baroclinicity reflected in [sB1 ] has increased. The
bandpassed [ZSD] difference field also suggests an equatorward shift. However, interestingly, the magnitude of
the change is much less than in the 2-K lowlat run. Likewise, the eddy fluxes, though shifted equatorward, have
changed less than in that run.
Thus, the primary changes here occur in the subtropical
jets, which have intensified and shifted equatorward. The
storm tracks have also shifted equatorward. However, the
changes are less than in the 2-K lowlat run, where the SST
gradients were changed at midlatitudes.
15 MARCH 2012
GRAFF AND LACASCE
1867
FIG. 11. Horizontal projections of the bandpassed ZSD standard deviation field at the 300-hPa surface: (a) the 2-K lowlat plot, (b) the
2-K plot, (c) the 3-K highlat plot, and (d) the 2-K tropics plot. The thick solid lines are CRCs of 40 and 50 m, and the thin filled contours are
the difference field contours with a CI of 3 m.
5) 2D DEVIATIONS
In the preceding examples, the changes in the NH are
frequently less clear than in the SH. This is because in
the NH the storm tracks tilt and because the oceans
cover less surface area. Here we return to 2D fields, to
see aspects that may have been obscured by zonal averaging. Figure 11 shows the bandpassed ZSD difference
fields from the 2-K lowlat, 2-K, 2-K highlat, and 2-K
tropics runs. Note that these fields are taken at 300 hPa,
closer to the jet level.
The 2-K lowlat run is shown in Fig. 11a. The poleward
shift in the SH is mostly zonal, but there is a marked
increase in the Drake Passage (and this is seen in many
of the other runs as well). The deviations in the NH are
more tilted. The largest alteration in the North Atlantic
storm track is actually in the exit region, over northern
Europe and extending to central Asia. There are additional maxima in the entrance region of the North Pacific
track and over northern Canada. The structure suggests
complex changes in the storm band, possibly reflecting
the activity of mature cyclones.
The 2-K run exhibits similar but weaker changes (Fig.
11b). The North Atlantic storm track has shifted to the
northeast, the North Pacific track has shifted eastward,
and the SH track has shifted poleward. However, there
are also noticeable differences with the 2-K lowlat run.
The changes seen previously over Asia are largely absent
and those over the North Atlantic are more complex,
indicating even a weakening in variability over the Nordic
Seas. Note that significant changes occur near 608S, where
the oceans meet the Antarctic ice sheet. These are conceivably the result of the forcing, because we have only
warmed the oceans. However, we note that the changes in
the 2-K lowlat run occur over the same latitudes, despite
the SSTs being changed farther north in the 2-K run.
In the 2-K highlat run (Fig. 11c), the storm tracks
weaken on the poleward flanks in both hemispheres.
The changes resemble those in the previous runs, being
largely zonal in the SH and undulating in the NH. In
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JOURNAL OF CLIMATE
both NH storm tracks, the variability is altered primarily
in the exit regions and most noticeably in the North Atlantic track. The 22-K highlat run response (not shown)
is similar to the 2-K highlat run, but with opposite signs.
The 2-K tropics run (Fig. 11d) presents an interesting
contrast to the previous examples. The SH storm track
has intensified on the equatorward flank, with large
changes over the South Atlantic and southern Indian
Oceans and south of Australia. In the NH, the field again
has an undulating appearance, with a small decrease in
variability along an arc extending from New England to
England. In the Pacific, there is a decrease on the poleward
side and increase on the equatorward side, most noticeably
on the eastern side of the basin.
Thus, the 2D plots largely confirm the previous conclusions. However, they also show that the changes in
the NH are spatially variable, with the most pronounced
changes occurring in the exit regions.
5. Summary and discussion
We investigated changes in the storm tracks in both
hemispheres induced by altering the SSTs in an atmospheric GCM (AGCM). We warmed/cooled the surface
oceans by 2 K in various latitude bands and examined
the changes when averaged over a 20-yr period. The
storm tracks were shown in terms of the bandpass-filtered
Z standard deviation field, retaining fluctuations with a
time-scale range of 2.5–6 days.
The results suggest the intensity and position of the
storm tracks change in a consistent way in response to
the forcing. Increasing the SST gradient at midlatitudes
increases the baroclinicity and the eddy fluxes at midlatitudes, leading to an intensification of the storm
tracks and a shift poleward. Increasing the gradient in
the tropics also increases the variability but produces
an equatorward shift in the storm band. Increasing the
SSTs uniformly by 2 K strengthens Hadley circulation
and the subtropical jets and produces a poleward shift
in the storm track.
Similar effects have been seen previously in simulations
with aquaplanet boundary conditions. The dependence
on SST gradient seen here is consistent with that described by Brayshaw et al. (2008), who found a poleward
shift following an increase in the midlatitude gradient and
an equatorward shift in response to an increased gradient
in the tropics. Caballero and Langen (2005), Kodama and
Iwasaki (2009), and Lu et al. (2010) found that increasing
the mean temperature produced a poleward shift in the
tracks, as in the 2-K run. Also, El Niño, which is a
warming of the ocean surface in the equatorial Pacific,
causes the Pacific storm track to shift equatorward (e.g.,
Chang et al. 2002; Lu et al. 2008), as in the 2-K tropics run.
VOLUME 25
The present results suggest that changes both in the
mean SST and in the gradients are important for the
position and intensity of the tracks. Increasing the mean
temperature affects the subtropical jets, and changing
the midlatitude gradients alters the eddy-driven jets.
Both changes affect the baroclinicity, as seen with the sB1
parameter. The latter is primarily affected by changes in
the mean temperature gradient, rather than the stratification [as noted previously by Yin (2005)]. This would
seem to imply that altering the surface temperature gradient will have a greater effect than simply increasing
diabatic heating. However, the latter, which is greater in
the runs where SSTs were increased in the tropics, also
affects baroclinicity by altering the subtropical jets.
It is perhaps unsurprising that our results are similar to
the aquaplanet simulations in the SH, where the oceans
cover a large fraction of the surface area. However,
consistent changes are seen in the NH. Here, though, the
greatest changes occur in the exit regions of the storm
tracks. This is suggestive on a nonlinear interaction between the mature cyclones and the surface temperature
gradient.
The shifts in the storm tracks in the present runs were
accompanied by an expansion or contraction of the
Hadley cells. It is well known that the latter are currently
expanding. This has been seen in observations (Fu et al.
2006; Hudson et al. 2006; Hu and Fu 2007; Seidel and
Randel 2007; Seidel et al. 2008) and in models (Kushner
et al. 2001; Previdi and Liepert 2007; Lu et al. 2007;
Frierson et al. 2007; Johanson and Fu 2009). Indeed, it is
difficult to separate the response in the tropics with that
occurring on the flanks of Hadley cells and in the Ferrel
cells. This suggests an important role for eddies in the
Hadley circulation, as stressed by Schneider (2006).
Recently, Polvani et al. (2011) suggested that similar
effects to those seen here (e.g., a poleward shift of the
midlatitude jet and a widening of the Hadley cell) could
be induced in the SH as a result of stratospheric ozone
depletion. In their simulations (also with CAM3), they
fixed the SSTs to observed values. Given our results, it
may then be difficult to distinguish which forcing is more
important, particularly if changes in ozone also induce
surface temperature changes (Sigmond et al. 2011).
However, it should be noted that similar changes are
found in the NH, where ozone-related forcing is weaker.
As noted, the primary motivation of this study was
testing the idea that the observed changes in the storm
track could be triggered by oceanic warming. The pattern of warming found in observations is similar to that
in the present 2-K lowlat run, in that the low latitudes
experience the greatest warming and the temperature
gradients at midlatitudes are increased. We found a
poleward shift in the storm tracks, accompanied by an
15 MARCH 2012
GRAFF AND LACASCE
upward shift in the NH (although the latter was not as
apparent in the SH). Moreover, the changes in both sB1
and the storm tracks in the 2-K lowlat run resemble
those found by Yin (2005) (cf. our Fig. 6 with his Figs. 1,
2, left). Thus, the present results are consistent with the
idea that oceanic warming is an important contributor to
the observed changes in the storm tracks.
It remains to be explained exactly why the storm tracks
shift in the way they do. Increasing the SST gradients
should intensify the heat fluxes, which are strongest near
the surface. This in turn will strengthen the Eliassen–
Palm fluxes acting on the mean circulation, particularly in
relation to the eddy-driven jet. The latter could shift
north or south in response. However, the present results
and those of Brayshaw et al. (2008) indicate that the eddy
fluxes themselves shift poleward. Therefore, there is evidently a feedback between the fluxes, the eddy-driven
jet, and storm track. We are currently exploring how to
capture this feedback in simplified models.
Acknowledgments. The CAM3 simulations were performed on the Titan cluster at the University of Oslo. We
would like to acknowledge three anonymous reviewers
whose comments helped improve the paper.
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