Interannual-to-decadal variability in the Oyashio Current

Interannual-to-decadal variability in the Oyashio Current and its influence on
temperature in the subarctic frontal zone: An eddy-resolving OGCM simulation
Masami Nonaka,
Frontier Research Center for Global Change, JAMSTEC, Yokohama, JAPAN
Hisashi Nakamura
Frontier Research Center for Global Change, JAMSTEC, Yokohama, JAPAN
also Graduate school of Science, the University of Tokyo, Tokyo, JAPAN
Youichi Tanimoto
Frontier Research Center for Global Change, JAMSTEC, Yokohama, JAPAN
also Faculty of Environmental Earth Science, Hokkaido University, Sapporo, JAPAN
Takashi Kagimoto
Frontier Research Center for Global Change, JAMSTEC, Yokohama, JAPAN
Hideharu Sasaki
Earth Simulator Center, JAMSTEC, Yokohama, JAPAN
submitted to the Journal of Climate
October 18, 2007
Corresponding author address:
Masami Nonaka
Frontier Research Center for Global Change,
Japan Agency for Marine-Earth Science and Technology (JAMSTEC),
3173-25 Showa-machi, Kanazawa-ku, Yokohama, 236-0001 Japan
[email protected]
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ABSTRACT
Output of an eddy-resolving OGCM simulation is used to investigate mechanisms for
interannual-to-decadal variability in the Oyashio Current and its influence on the subarctic
frontal zone in the western North Pacific. Lag correlation analysis reveals that positive
anomalies both in basin-scale wind-stress curl and in local Ekman pumping can intensify
the southward Oyashio Current almost simultaneously via barotropic and baroclinic Rossby
wave propagations, respectively. The Oyashio Current strength can also be influenced by
anomalous Ekman pumping exerted in the western portion of the basin with the lag of three
years through the baroclinic wave propagation. The intensification of the Oyashio Current
is accompanied by negative anomalies both in the sea surface temperature and height off
the Hokkaido Island of Japan and followed by their eastward propagation/extent along the
subarctic frontal zone in association with a southward displacement of the frontal axis.
These changes are associated with low potential-vorticity anomalies at the thermocline
level, induced probably by the intensified Oyashio Current off the Hokkaido Island and
then advected by the mean eastward current along the frontal zone. The surface cooling
thus induced in the frontal zone by those oceanic processes accompanies anomalous
downward surface heat fluxes, indicative of ocean-to-atmosphere feedback forcing
associated with the Oyashio Current variations.
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1. Introduction
For the North Pacific decadal variability, the importance of remote influence from the
tropics (Nitta and Yamada 1989; Trenberth and Hurrell 1994; Newman et al. 2003; Deser et
al. 2004, among others) and that of the midlatitude atmospheric stochastic forcing
(Hasselman 1976; Frankignoul 1985) have been stressed. A semi-empirical reconstruction
of the North Pacific sea surface temperature anomalies (SSTAs) by Schneider and
Cornuelle (2005), however, demonstrates that an ocean-to-atmosphere feedback in the
Kuroshio Oyashio Extension (KOE) region can be as equally important as the two
aforementioned two factors, as has been suggested by some previous studies (Latif and
Barnett 1994; Barnett et al. 1999; Pierce et al. 2001; Schneider et al. 2002, among others).
In fact, Nakamura et al. (1997) and Nakamura and Yamagata (1999) pointed out that the
KOE region is the primary center of action of North Pacific decadal variability, and SST
anomalies, especially in the northern portion of the region, exhibits no significant
simultaneous correlation with the tropical decadal SST variability. Indeed, it has been
shown that oceanic processes can induce interannual-to-decadal SSTAs in the KOE region
on the basis of ocean general circulation model (OGCM) experiments (Xie et al. 2000;
Seager et al. 2001; Yasuda and Kitamura 2003; Nonaka et al. 2006), a linear model
experiment (Schneider and Miller 2001), and observational data analyses (Qiu 2000, 2002,
2003; Tomita et al. 2002; Kelly and Dong 2004), implying a possibility of an
ocean-to-atmosphere feedback in the region as mentioned below.
In most of those previous studies, the KOE region has been treated as a single frontal
zone owing to rather coarse horizontal resolutions of their models or datasets.
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High-resolution observational data, however, apparently shows that there are at least two
prominent oceanic frontal zones in the KOE region: the Kuroshio Extension (KE) frontal
zone (KEFZ) along the KE Current (e.g., Mizuno and White 1983) and the subarctic frontal
zone (SAFZ; or polar frontal zone, (Belkin et al. 2002)) associated with the Oyashio
Extension and the North Pacific Current (e.g., Yuan and Talley 1996). These two frontal
zones have distinct vertical structures (Nonaka et al. 2006): SSTAs in SAFZ tend to be
substantially stronger than in KEFZ (Nakamura and Kazmin 2003; Nonaka et al. 2006).
Tanimoto et al. (2003) showed that warm (cold) SSTAs in SAFZ locally induce anomalous
upward (downward) surface heat flux. Given SSTAs are induced by oceanic processes, this
suggests the existence of an ocean-to-atmosphere feedback in the region. In spite of their
potential importance as thermal forcing onto the overlying atmosphere, how SSTAs in the
SAF region are generated has not been clarified yet. The aforementioned previous studies
have suggested that incoming baroclinic Rossby waves are particularly important for the
formation of SSTAs in the KOE region. Nonaka et al. (2006) have shown, however, that
decadal variations of the SAFZ and KEFZ reproduced in an eddy-resolving OGCM are not
necessarily coherent temporally. Their results suggest potential importance of processes
other than the Rossby waves, especially for the SAFZ variability, including variability of
the Oyashio Current, as has been suggested by Sekine (1988a).
The Oyashio Current is a western boundary current of the western subarctic gyre in the
North Pacific, transporting cold water from that gyre and the Sea of Okhotsk into SAFZ
(Yasuda 2003, for a recent review) with its vertical extent more than 1000 m (Uehara et al.
2004). The Oyashio Current, especially its along-shore branch, is known to exhibit large
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interannual variability (Sekine 1988a). Owing to the limited availability of direct
measurements of the current velocity, interannual and decadal variations in the current has
been detected mainly by examining the corresponding changes in the southern-most
latitude of the Oyashio near-shore branch defined from 100-m depth temperature
distributions off northern Japan (Ogawa 1988; Yasuda 2003, and references therein). While
the importance of barotropic Rossby wave propagation has been pointed out for seasonal
and interannual variations in the Oyashio Current (Sekine 1988b; Hanawa 1995; Isoguchi et
al. 1997; Kono and Kawasaki 1997), it has been recently shown that baroclinic Rossby
wave propagation is also important for interannual and longer timescale variability (Qiu
2002; Tatebe and Yasuda 2005). Recently, Ito et al. (2004) examined interannual variations
in the Oyashio Current after 1993 by combining in situ measurements and satellite altimeter
measurements. More recently, Isoguchi and Kawamura (2006) attempted to estimate
interannual variability in the Oyashio Current based on tide gauge data, although it tends to
emphasize the barotropic component of the current variations.
As mentioned above, the limited availability of observational data limits our
understanding of the mechanisms for interannual and decadal variability in the Oyashio
Current and the associated variability in SAFZ. Nevertheless, recent development of an
eddy-resolving OGCM that can realistically represent the frontal structures in the KOE
region (Nonaka et al. 2006) has enabled us to investigate their long-term variability in
detail. In this study we investigate how long-term variability of the Oyashio Current is
induced by wind-stress anomalies and how the current variations induce SSTAs in SAFZ,
taking advantage of an output of the eddy-resolving OGCM hindcast simulation for
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1950-2003.
This paper is organized as follows. Section 2 introduces the OGCM and datasets.
Section 3 describes the mean state of the Oyashio Current and its variability represented in
the OGCM. Influence of wind stress variability on the Oyashio Current is investigated in
Section 4. Section 5 shows influences of the Oyashio Current variations on SAFZ. Section
6 provides a summary and discussions.
2. Model and datasets
The OGCM we use in this study is based on the Modular Ocean Model (MOM3)
(Pacanowski and Griffies 2000), developed at the Geophysical Fluid Dynamics
Laboratory/National Ocean and Atmospheric Administration (GFDL/NOAA), but the code
has been substantially modified for attaining its efficient performance on the vector-parallel
hardware system of the Japan’s Earth Simulator (Ohfuchi et al. 2007). Our ocean model for
the Earth Simulator (OFES; Masumoto et al. 2004) covers a near-global domain extending
from 75°S to 75°N, except for the Arctic Ocean, with horizontal resolution of 0.1°. The
model has 54 vertical levels, with resolutions from 5 m at the surface to 330 m near the
bottom. The model topography is based on the 1/30° bathymetry dataset (kindly provided
by GFDL/NOAA) with the maximum depth of 6,065 m. Although the lack of sea-ice
processes leads to somewhat unrealistic features in the stratification within the North
Pacific subpolar gyre, the overall circulation system is realistically reproduced in OFES.
The model solves the primitive equation system in spherical coordinates under the
Boussinesq and hydrostatic approximations. The KPP boundary layer mixing scheme
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(Large et al. 1994) is adopted for vertical mixing. For horizontal mixing of momentum and
tracers, we adopt a scale-selective damping with a bi-harmonic operator, to suppress
grid-scale computational noises (Smith et al. 2000). The background horizontal
bi-harmonic viscosity and diffusivity are -27x109 m4s-1 and -9x109 m4s-1, respectively.
These values are the same as those used in Maltrud and McClean (2005) and Smith et al.
(2000) for 0.1°-resolution global and Atlantic OGCMs, respectively.
In the model, the surface heat flux and evaporation rate are calculated with the bulk
formula developed by Rosati and Miyakoda (1988), based on the model-simulated SST and
atmospheric variables from the National Centers for Environmental Prediction/National
Center for Atmospheric Research (NCEP/NCAR) reanalysis (Kalnay et al. 1996). The fresh
water flux is evaluated from the evaporation rate and daily precipitation rate taken from the
reanalysis data, under the constraint for sea surface salinity to be restored to its monthly
climatology with timescale of 6 days, to include the contribution from river run-off. The
climatology is based on World Ocean Atlas 1998 (WOA98; Boyer et al. 1998a, 1998b,
1998c). Within 3° from the model’s artificial boundaries placed at 75°N and 75°S,
temperature and salinity are restored to their local monthly climatologies (WOA98) with
time scale that is 1 day at the boundaries and increasing to infinity into the interior region.
See Masumoto et al. (2004) and Sasaki et al. (2007) for details of the model setup.
The model was first integrated for 50 years from the climatological annual-mean fields
of temperature and salinity (WOA98) without motion by applying the climatological
monthly-mean atmospheric forcing. Following this 50-year spin-up, we then conducted a
54-year hindcast integration with daily mean atmospheric fields of the NCEP/NCAR
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reanalysis data from 1950 to 2003. This hindcast simulation successfully captures
variability with intraseasonal-to-decadal time scales (Sasaki et al. 2007), and it has been
used for an investigation of decadal variability in SAFZ and KEFZ (Nonaka et al. 2006). In
the following analyses, model monthly climatology and anomalies are defined as the mean
for this 54-year period and deviations from it, respectively.
For our analytical convenience, the full (0.1°) resolution for the model output has been
reduced to 0.5° resolution by picking up the data at every five grid-points both in the zonal
and meridional directions, except in our evaluation of the potential vorticity (PV) field.
Though reduced, the resolution is still adequate for resolving the Oyashio Current and fine
structures in SAFZ as shown below. The simulated variability in frontal structures at least
in the SST and sea surface height (SSH) fields discussed below is confirmed to have the
same characteristics between the reduced and full resolution datasets.
In addition to the output of the hindcast integration of OFES, we also use the Japan
Meteorological Agency (JMA) SST data set. The data have been compiled for the western
North Pacific (100°-180°E, 0°-60°N) with 1° horizontal resolutions with subjective analysis
of in situ and satellite observations for every 10-day period from 1950 to 19991.
3. Simulated fields in the Oyashio and SAF regions
a. Annual mean fields
Before describing the simulated variability in the Oyashio Current region, we plot
annual mean fields of sea surface current, height and temperature to see general structures
1
The JMA-SST data include satellite data since 1998, yielding a discontinuity in the data
quality in that year. It has, however, little influence on our analyses because we focus
primarily on earlier years in this study.
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of the North Pacific subarctic gyre in OFES (Fig. 1). The annual mean sea surface current
field (Fig. 1a) shows that OFES well reproduces the major components of the subarctic
gyre: the Alaskan Stream, the East Kamchatka Current, the Oyashio Current, the North
Pacific Current. The Alaskan gyre is found in the surface current field, though not apparent
in the mean SSH field (Fig. 1b). In contrast, the western subarctic gyre is more apparent in
the mean SSH field, and the cyclonic gyre in the Bering Sea is found in both of the fields. It
should be noted here that in OFES, the Kuroshio Current tends to overshoot as far north as
~40°N along the east coast of Japan, while its large part returns to about 36°N before
merging itself into the KE Current. In association with an overshoot of the Kuroshio
Current, SSTs along the east coast of Japan tend to be warmer than the counterpart in the
observed data as shown below. Except these discrepancies around Japan, however, annual
mean SSTs are well represented in OFES.
b. Seasonal variability
In the JMA data (Fig. 2b), strong SST gradient associated with SAFZ extends eastward
around 40°N, in which the Oyashio front with the particularly tight SST gradient is
embedded off Japan with its axis tilted northeastward. In OFES (Fig. 2a), the overshoot
Kuroshio warms off the east coast of Japan, leading to slight relaxation of SST gradient in
the Oyashio and SAFZ, especially in their southern portions. Nevertheless, the simulated
SST field represents fairly strong horizontal SST gradient in the regions of the Oyashio
front and SAFZ, especially in their northern portions, and the overall SST distribution over
the western North Pacific is well reproduced in OFES. Compared to JMA-SST (Fig. 3b),
the seasonal SST variability in the Oyashio frontal region is well captured in OFES, despite
some warm bias maximized in winter. In contrast to the seasonal variations in SST, 100-m
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depth temperature in the same area (Fig. 3b, thin curve) is minimizes in March and
maximizes in November. The virtually same seasonal march are found in the southernmost
latitude of the Oyashio coastal intrusion (Yasuda 2003, his Fig. 2b), with the lowest latitude
in March and highest latitude in November.
The seasonal variability in surface currents is characterized by the strongest southward
Oyashio Current off the Kuril Islands and Hokkaido Island in winter and its weakest
southward penetration in summer (Fig. 4), consistent with previous observational studies
(e.g., Ito et al. 2004, Yasuda 2003 and references therein). Seasonal surface current
variability is also apparent within the Sea of Okhotsk. The southward East Sakhalin Current
strengthens in winter, while an anti-cyclonic gyre in the Kuril basin (around 44°-47°N,
144°-150°E) develops in summer to autumn, both consistent with observational studies
(Mizuta et al. 2003, Wakatsuchi and Martin 1991). In contrast, seasonal variations in the
Kuroshio and its extension currents are substantially weaker.
For the following analyses of the variability in the Oyashio Current and its influence on
temperature field, we define an index of the strength of the Oyashio Current (the Oyashio
Current index) as the southward velocity for a given level averaged over a rectangular
domain off Hokkaido Island (40.1°-45.1°N, 143.1°-151.1°E) as indicated in the upper-left
panel of Fig. 42. The area mean was taken in order to exclude the influence of meso-scale
eddies that are ubiquitous in the Oyashio Current region. Additionally, in the following
analyses, we regard the vertical average of the index values as a measure of the barotropic
component of the current, whereas the difference of the index value at the 100-m depth
2
Although the rectangular domain includes the southern edge of the Sea of Okhotsk, this
part is excluded in our estimation of the area-mean value.
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from the vertical mean is regarded as a measure of its baroclinic component. In this study
we focus on the Oyashio Current at the 100-m depth, because temperatures at that depth
have been used to define the southernmost latitude of the Oyashio near-shore branch.
In their climatological mean seasonal march (Fig. 5, bottom panel), the wintertime
intensification of the Oyashio Current at the 100-m depth is largely contributed to by the
barotropic component, while the baroclinic component shows relatively small seasonal
variability. Owing to the wintertime intensification of the Aleutian Low and associated
positive wind-stress curl over the North Pacific Ocean, this wintertime intensification in the
barotropic component is consistent with the Sverdrup balance. The same mechanism is also
operative in interannual variations of the current, as shown in the following analyses
(section 4.a).
c. Interannual variability
The simulated interannual variability in winter (January-March) SST within the
Oyashio frontal region is compared to its counterpart in the JMA-SST data in Fig. 3a. The
simulated area-mean SST anomaly shows its negative peaks in the middle of the 1960s,
1970s, and 1980s, and its positive peaks in the early 1960s and 1970s and in the late of
1970s and 1980s. Though somewhat weaker, these peaks are also found in the JMA-SST
with their correlation coefficient of r=0.66. In the same figure, time series of the simulated
area-mean 100-m depth temperature is found to be highly correlated with those in the
surface index.
In the top panel of Fig. 5, interannual variations in the Oyashio Current intensity are
found both in its baroclinic and barotropic components, but they are not well correlated
(r=0.26). Although no observational data are available for a direct comparison with the
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simulated time series of the Oyashio Current, a comparison with the temperature anomalies
(Fig. 3a) suggests that SAFZ tends to be cooler when the Oyashio Current is intensified
(r=0.36, r=0.47 for winter SSTAs), as will be further discussed in section 5. A good
correspondence between the observed and simulated SSTA time series in Fig. 3a indicates
that the Oyashio Current variations are well captured in OFES.
d. Decadal variability
On decadal timescales, the observed and simulated SSTAs and simulated 100-m depth
temperature in SAFZ were all relatively high around 1970 and in the 1990s, whereas a
pronounced cool period was found in between in the mid-1980s (Fig. 3a). These
temperature variations are concurrent with long-term variations in the southward Oyashio
intrusion, as have been already detected in the 100-m depth temperature measurements
along the east coast of Japan (Ogawa 1988; Sekine 1988b; Hanawa 1995; Yasuda 2003, his
Fig. 2a). In good agreement with its enhanced southward penetration and the northward
retreat, the simulated Oyashio Current strengthened in the mid-1980s and weakened around
1970, respectively (Fig. 5, top panel). In fact, five-year mean surface current fields in Fig. 6
show that the southward Oyashio Current and its eastward extension along SAFZ are
stronger in the cool period (1984-88) than in the warm period (1968-72). The
aforementioned relationship between the Oyashio Current and SSTAs in SAFZ on
interannual and decadal time scales suggests significant influence of the former on the latter,
calling for the investigation of the mechanisms for changes in the Oyashio Current.
4. Influence of wind variability on the Oyashio Current
To investigate how the changes in the Oyashio Current are induced, in this section we
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examine lead-lag correlations of the Oyashio Current strength with wind-stress curl and
Ekman pumping fields. Our investigation is carried out separately for the barotropic and
baroclinic components of the Oyashio Current, as we expect that different mechanisms may
be operative in their variability. In the following correlation analysis, we estimate the
number of degree of freedom (DOF) for the barotropic component (100-m depth) Oyashio
Current index to be 50 (25), based on its auto-correlation with one-year (two-year) lag of
only 0.135 (0.194)3 . With the number of DOF of 50 (25), the 95%, 90% and 80%
confidence levels for correlation are 0.27 (0.38), 0.23 (0.32) and 0.18 (0.26), respectively.
a. Barotropic component
Figure 7 indicates that the barotropic component has significant simultaneous
correlation (panel b) with the wind-stress curl almost over the whole North Pacific basin
(shaded in the left column), whereas the correlation almost diminishes in either the previous
or the following year (panels a and c). The simultaneous correlation between the barotropic
component of the Oyashio Current and sea level pressure (SLP) show the tendency that the
basin-wide cyclonic wind-stress curl anomalies are associated with the enhancement and
southward expansion of the Aleutian Low (Fig. 8, top and bottom panels). The
corresponding correlation map for 500-hPa height indicates that the SLP anomaly pattern is
associated with a PNA-like pattern aloft (not shown). The regression maps of surface
current vectors onto the barotropic component of the Oyashio Current index (Fig. 7, right
panels) also indicate that the southwestward surface Oyashio Current tends to enhance
along the Kuril Islands and Hokkaido Island only simultaneously with the intensified
barotropic component, consistent with very fast propagation of barotropic Rossby waves.
3
The auto-correlation with one-year lag for the 100-m depth Oyashio Current is 0.368.
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Driven by wind-stress curl anomalies, barotropic Rossby waves induce the changes in the
Oyashio Current, consistent with the linear vorticity balance as suggested by previous
studies (Sekine 1988b; Hanawa 1995; Isoguchi et al. 1997).
b. Comparison with Sverdrup transport
The above results suggest that the vertically integrated southward transport by the
Oyashio Current and its interannual variability can be explained by the Sverdrup transport
and its variability, respectively, estimated from the wind-stress curl fields imposed on
OFES as forcing. In Fig. 9, we plot time series of the meridional transport integrated
vertically from the bottom to the sea surface and zonally from the western boundary to
151°E (solid line) and the Sverdrup transport based on wind-stress curl over the whole
width of the basin (dashed line). Consistent with the above results, their simultaneous
correlation (r=0.76) is high and significant, but the estimated Sverdrup transport and its
variations are substantially larger than those of the meridional transport of the Oyashio
Current in OFES. Specifically, the mean transport is approximately six times larger (24.4
Sv vs. 4.3 Sv), and the standard deviation is approximately three times larger (26.2 Sv vs.
8.5 Sv). We have also estimated the Sverdrup transport based on the same wind-stress curl
field as above but from the western boundary to 170°E (dotted line in Fig. 9). The
corresponding mean (10.1 Sv) and its standard deviation (8.8 Sv) are better correspondent
to the simulated meridional transport of the Oyashio Current with respective to their
magnitudes, although their correlation (r=0.67) is slightly lower. Kono and Kawasaki
(1997), who made qualitatively the same comparison as above based on their observations
for several years, speculated that the Emperor Seamounts located around 170°E obstructs
propagation of barotropic Rossby waves from their east, and therefore wind-stress curl only
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to their west can effectively force the Oyashio Current and its variability (see also Sekine
1989; Ito et al. 2004). Indeed, a longitude-time section of simulated daily SSH anomalies
that can depict the propagation of barotropic waves (not shown) reveals that westward
propagating signals are sometimes halted or weakened around 170°E, in a manner
consistent with the above speculation. Though beyond the scope of this study, however,
more detailed investigations are necessary to understand specifically how the Emperor
Seamounts influence the propagation of barotropic Rossby waves and thereby the
meridional transport of the Oyashio Current.
c. 100-m depth Oyashio Current including baroclinic component
Unlike to its vertically averaged strength, the Oyashio Current in the surface layer can
be influenced also by propagation of baroclinic Rossby waves (Qiu 2002; Tatebe and
Yasuda 2005). Indeed, as exemplified at the 100-m depth (Fig. 5, top panel), the Oyashio
Current strength in the surface layer varies interannually in a manner different from that of
the vertical mean current intensity. A map of simultaneous correlation between the 100-m
depth Oyashio Current index and the local Ekman pumping (Fig. 10d) indicates that
anomalous upward Ekman pumping in the region around [45°N, 160°E] tends to occur
concomitantly with the enhancement of the southward Oyashio Current at the 100-m depth.
Consistent with the linear theory, this relationship strongly suggests that the southward
Oyashio Current off Japan is driven by wind-induced upwelling just to the east.
Though slightly weaker than the simultaneous correlations, the 100-m depth Oyashio
Current index is also correlated significantly with the Ekman pumping associated with
northeasterly wind anomalies within the region [42°-45°N, 160°-170°E], if the pumping
leads the Current index by three years (Fig. 10a). That is almost the same region in which
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the simultaneous correlation is significant. With their slow propagation speed, it takes
nearly three years for baroclinic Rossby waves to propagate from 170°E to the western
boundary at these latitudes until they influence the Oyashio Current. Correlation maps
between the Ekman pumping and the baroclinic component of the 100-m depth Oyashio
Current (dashed line in the top panel of Fig. 5) show the similar results with slightly weaker
correlations (not shown). Figure 8b indicates that the strengthening of the 100-m depth
Oyashio Current tends to accompany anomalous near-local Ekman pumping associated
with the intensification of the Aleutian Low on its western flank, but no significant
correlation is found over the North Pacific Ocean in the three-year-lead SLP field (not
shown).
A map of simultaneous correlation between the 100-m depth Oyashio Current index
and surface layer current (Fig. 10h) indicates that the meridional extent of the anomalous
Oyashio Current is limited in comparison with that of the barotropic component (Fig. 7e)
reflecting the meridionally confined forcing (Fig. 10d). No significant correlation is found,
however, along the eastward extension of the Oyashio Current in SAFZ, where meso-scale
eddy activity is particularly high. Nevertheless, negative correlation is significant between
the 100-m depth Oyashio Current index and the axial latitude of the eastward Oyashio
Extension Current averaged for 150-160°E (r=-0.46, Fig. 11a). In other words, the stronger
(weaker) southward Oyashio Current tends to be associated with a southward (northward)
displacement of the eastward current. Additionally, the maximum eastward velocity along
the axis and its latitude are negatively correlated (r=-0.46, Fig. 11b). The eastward current
tends to be enhanced when its axis is displaced southward, in a manner consistent with the
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decadal differences in the currents as shown in Fig. 6.
5. Influence of Oyashio Current variability on SAFZ
In the preceding sections, we have investigated how variations in the Oyashio Current
are caused by wind forcing. In this section how those variations induce changes in SAFZ is
examined for spring (March-May) with lag correlation analysis. Qualitatively the same
results are obtained for winter (not shown), but the correlation coefficients are slightly
lower probably due to the stronger influences of atmospheric noise.
Lag correlation maps of SST with the 100-m depth Oyashio Current index (Fig. 12)
clearly indicate that the intensification of the southward Oyashio Current tends to
accompany surface cooling off northern Japan and in SAFZ, as discussed in the previous
studies (Sekine 1988a, Hanawa 1995). A close inspection reveals that the cool SST
anomalies in SAFZ tend to maximize two or three years after the peak intensification of the
Oyashio Current, but the cooling signal starts emerging even one-year earlier than the peak.
The maturing of the cool anomalies occurs first just off the Hokkaido Island and later to the
east along the Oyashio front/SAFZ. This eastward development of the cool SST anomalies
along SAFZ following the enhancement of the Oyashio Current is evident in the mid- to
late 1980s in the OFES simulation, and it is also hinted in the JMA-SST data (not shown).
Though somewhat less clear, similar downstream development of negative SSH anomalies
tends to occur along SAFZ following the intensification of the Oyashio Current (Fig. 13,
right panels). This suggests that the evolution of the temperature anomalies along the
frontal region is not limited to the surface layer but coherent with subsurface temperature
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changes.
Indeed, there are anomalies in a subsurface potential vorticity (PV) field developing
along SAFZ following the intensification of the Oyashio Current (Fig. 14). The left-top
panel of Fig. 14 shows the climatological-mean PV field on an isopycnal surface of σθ=27.0
kg m-3 in the lower part of the thermocline. Low-PV water is spilling out of its pool in the
Sea of Okhotsk southward along the Kuril Islands and east coast of Hokkaido as observed
(Yasuda 1997, and references therein), forming fairly tight meridional PV gradient across
SAFZ with higher PV to the south. A lag correlation analysis reveals that one year before
the peak of the Oyashio intensification, low-PV anomalies start emerging in the western
portion of SAFZ off the Hokkaido Island, followed by their downstream development
along SAFZ (right panels). The whole sequence suggests that the PV anomalies are
probably caused by the intensified advection of low-PV water southward along the coast
and then develop eastward along SAFZ by the eastward extension of the Oyashio Current.
The low-PV anomalies in SAFZ correspond to its southward displacement (c.f., left-top
panel of Fig. 14), indicating that both the cool SST anomalies (Fig. 12) and negative SSH
anomalies (Fig. 13) can be interpreted as being associated with the southward displacement
of SAFZ following the intensification of the Oyashio Current. The zonal velocity averaged
over [40°-42°N, 150°-170°E] on the σθ=27.0 kg m-3 isopycnal surface is 2.8 cm s-1 or
approximately 10° in longitude a year. Though somewhat slower, the eastward
propagation/extension speed of the anomalies along SAFZ is thus comparable to the mean
current speed.
If the oceanic processes as discussed above give rise to the SST anomalies in SAFZ,
- 18 -
the anomalies may exert some feedback forcing onto the overlying atmosphere via
anomalous surface heat fluxes. To examine this we conduct another lag correlation analysis
between the 100-m depth Oyashio Current index and upward surface heat flux (sensible
and latent heat fluxes combined, Fig. 15). The intensification of the Oyashio Current tends
to yield negative (downward) heat flux anomalies off the Hokkaido Island and later along
SAFZ, collocated with cool SST anomalies. The collocation means that the anomalous flux
acts to damp the SST anomalies, exerting thermal forcing on the overlying atmosphere, as
observed by Tanimoto et al. (2003).
6. Summary and discussions
In the present study, mechanisms for the low-frequency variability in the Oyashio
Current and its influence on SAFZ have been investigated, by using an eddy-resolving
numerical ocean hindcast integration that can reproduce SAFZ and the Oyashio Current in
the western North Pacific reasonably well with respect to their seasonal and interannual
variations. Our lag correlation analysis indicates that basin-scale wind forcing induces
variations in the barotropic component of the Oyashio Current almost instantaneously. In
addition, wind forcing in the western portion of the basin can impact the Oyashio Current
strength through baroclinic Rossby wave propagations within three years. The strong
correlation between the basin-scale wind-stress curl and the vertically-integrated Oyashio
transport suggests that temporal variability of the transport can be understood by the
time-varying Sverdrup transport, although the Sverdrup transport for the whole zonal width
of the basin is found to overestimate the simulated Oyashio transport, as has been pointed
by observational studies (Kono and Kawasaki 1997; Ito et al. 2004). This discrepancy may
- 19 -
be caused by the disturbing effect of the Emperor Seamounts on barotropic Rossby wave
propagation. Note that the OFES integration cannot resolve the 18.6-year variations in tidal
mixing around the Kuril Islands (Yasuda et al. 2006), which may also contribute to changes
in the Oyashio Current.
Our lag correlation analysis has revealed that the intensification of the southward
Oyashio Current is accompanied by negative SST and SSH anomalies off the Hokkaido
Island and their subsequent downstream development into SAFZ, suggesting that the
frontal cooling is not limited to the surface. Indeed, it appears on an isopycnal surface in the
lower part of the thermocline (σθ=27.0 kg m-3) that the intensified Oyashio Current
enhances its southward transport of low-PV water originated from the Sea of Okhotsk,
leaving low-PV anomalies off the Hokkaido Island. The anomalies then develop eastward
probably by the mean Oyashio Extension Current along SAFZ, yielding a southward
displacement of SAFZ and the associated cool SSTAs. It is those oceanic processes that
induce the cool SST anomalies in SAFZ following the intensification of the Oyashio
Current. Consistently, surface heat flux anomalies in SAFZ are distinctively downward,
acting to damp the cool SST anomalies. In other words, the SSTAs in SAFZ associated with
the anomalous Oyashio Current can exert thermal feedback forcing onto the atmosphere.
Longitude-time sections of OFES-simulated SSH anomalies for the North Pacific basin
(Fig. 16) reveal latitudinal dependence of wave propagation characteristics. At 38°N to the
south of the mean axial position of SAFZ, coherent westward propagating signals are
evident over the whole width of the basin. Likewise, basin-wide signature of westward
propagation is also evident at the mean latitude of KEFZ (36°N, not shown). Their
- 20 -
propagation is fairly consistent with the theoretical values of baroclinic Rossby wave
propagation speeds for the respective latitudes (Nonaka et al. 2006, their Fig. 12). At 40°N,
the corresponding westward propagating signals are still apparent, but they become less
coherent as they approach to the western boundary (west of ~150°E). At 42°N, within
SAFZ, coherent westward propagating signals are apparent only in the eastern through
central portions of the basin. In the western portion of the basin (west of ~170°E), however,
they tend to be disturbed, and even some eastward propagating signals are hinted, for
example, around the beginning of the 1970s and the end of the 1980s, as suggested by
Nonaka et al. (2006). This same feature is also noticeable at 44°N, on the northern flank of
SAFZ. These eastward propagating signals, which cannot be regarded as Rossby waves
excited in the central or eastern portion of the basin, seem to be consistent with the
eastward developing signals found in SAFZ following the enhancement or weakening of
the Oyashio Current (Figs. 13 and 14). It is noteworthy that dominant time scales of the
SSH fluctuations plotted in Fig. 16 also exhibit substantial latitudinal dependence, with
longer time scales at higher latitudes in both the westward and eastward propagating signals.
The longer time scales of the fluctuations and the stronger influence of the Oyashio Current
in SAFZ than in KEFZ can be two of the factors that give rise to unsynchronized decadal
variations between the two adjacent frontal zones, as pointed out by Nonaka et al. (2006).
If baroclinic Rossby waves could reach the western boundary at the latitude of SAFZ
without suffering from any significant damping or dissipation, wind variations over the
central portion of the basin would effectively change the Oyashio Current with lags of
several years. However, the tendency for the westward propagating signals to be disturbed
- 21 -
or dissipated in SAFZ until they reach the western boundary acts to prevent the wind
forcing to the east from effectively influencing the Oyashio Current. In fact, virtually no
significant correlation is found in our analysis between the Oyashio Current intensity and
Ekman pumping in the central and eastern portions of the basin with leading time longer
than three years (not shown). Unlike in KEFZ, where westward propagating Rossby waves
reach the western boundary several years after their excitation, predictability of oceanic
variations in SAFZ is thus likely to be limited.
Very recently, air-sea interactions associated with oceanic frontal zones are gaining
increasing attention (Nakamura et al. 2004; Xie 2004). It has been confirmed with archived
shipboard (Tanimoto et al. 2003; Tokinaga et al. 2005), satellite (Nonaka and Xie 2003; Xie
2004; Chelton et al. 2004, among others), and in situ (Tokinaga et al. 2006) observational
data that SSTAs in midlatitude oceanic frontal zones can influence the overlying
atmospheric boundary layer by modulating surface heat fluxes. It is also suggested that
oceanic fronts act to anchor the atmospheric storm tracks (Nakamura and Sampe 2002;
Nakamura and Shimpo 2004; Inatsu and Hoskins 2004; Sampe 2006) by maintaining the
atmospheric surface baroclinicity through restoring the tight cross-frontal gradient of
surface air temperature (Sampe 2006). The present study suggests the potential for the
Oyashio Current variations to induce SSTAs in SAFZ. Similarly, it is suggested that
variations in KEFZ are governed by oceanic processes, including unknown nonlinear
dynamics, under the influence of westward propagating Rossby waves (e.g., Taguchi et al.
2005; 2007). How these anomalies in the frontal zones can exert feedback forcing to
large-scale atmospheric circulation is under investigation with very-high resolution
- 22 -
atmospheric GCM (AFES, Ohfuchi et al. 2004; 2007) and ocean-atmosphere coupled GCM
(CFES, Komori et al. 2007).
Acknowledgments. We thank members of the OFES group, including Drs. Y. Masumoto, H.
Sakuma and T. Yamagata, for their efforts and support in the model development. The
OFES simulations were conducted on the Earth Simulator under the support of JAMSTEC.
- 23 -
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- 29 -
Figure 1. Annual-mean (a) surface current vectors and speeds (shaded as indicated to the
right), (b) sea surface height, and (c) sea surface temperature simulated in the OFES
hindcast integration. Climatological (1950-2003) mean fields are shown. The scaling for the
vectors is indicated at the upper-right corner with unit of cm s-1. Thick vectors show
currents with mean speeds greater than 30 cm s-1. Contour intervals for sea surface height
and temperature are 5 cm and 1°C, respectively. In (a) some currents and geographies are
labeled (AS is the Alaskan Stream, EKC the East Kamchatska Current, OC the Oyashio
Current, NPC the North Pacific Current, KP Kamchatska Peninsula, HI Hokkaido Island,
and KIs Kuril Islands).
Figure 2. Climatological (1950-1999) mean wintertime (January-March) SST based on (a)
the OFES hindcast integration and (b) JMA-SST. Contour intervals are 1°C. Black
rectangular indicates the region used to make regional mean temperature fields shown in
Fig. 3.
Figure 3. Time series of regional mean temperature in the region indicated by the
rectangular shown in Fig. 2 (40°-42°N, 147.5°-152.5°E). (a) Annual mean SST (thick lines)
based on the OFES simulation (solid) and the JMA-SST (dashed), and 100-m depth
temperature based on the OFES simulation (thin line; right axis). (b) Climatological
(1950-1999) mean seasonal variability in SST (thick lines with closed circles; left axis)
based on the OFES simulation (solid) and the JMA-SST (dashed), and in 100-m depth
temperature based on the OFES simulation (thin line with open circles; right axis).
Figure 4. Climatological (1950-2003) mean seasonal mean current vectors in the surface
layer and meridional velocity (shading; as indicated below the lower-left panel), based on
the OFES simulation in (top-left) January-March, (top-right) April-June, (lower-left)
July-September, and (lower-right) October-December. The scaling for the vectors (unit of
cm s-1) are indicated below the lower-right panel. Thick vectors show currents with mean
speeds greater than 50 cm s-1. Black rectangular indicated the region used to make regional
mean meridional velocity fields shown in Fig. 5.
- 30 -
Figure 5. Time series of regional mean meridional velocity in the region indicated by the
rectangular shown in Fig. 4 (40.1°N-45.1°N, 143.1°E-151.1°E) based on the OFES
simulation. (Top) Wintertime (January-March) mean 100-m depth (solid) and vertically
averaged (dotted) meridional velocities, and their difference (dashed). (Bottom)
Climatological (1950-2003) mean seasonal variability in 100-m depth (solid) and vertically
averaged (dotted) meridional velocities, and their difference (dashed). Unit is cm s-1.
Figure 6. Current vectors in the surface layer and their magnitudes (shading; as indicated to
the right of the top panel), based on the OFES simulation averaged over the five winters
(January-March) separately for (top) 1984-88 and (bottom) 1968-72. The scaling for the
vectors (unit: cm s-1) is indicated below lower-right corner of the top panel.
Figure 7. (a, d) One-year lead, (b, e) simultaneous, and (c, f) one-year lagged wintertime
(January-March) (d, e, f) surface layer current vector and (a, b, c) wind-stress regressions,
and correlation coefficients of wind-stress curl (shading in the left panels as indicated
below panel c) to the standardized wintertime vertical mean Oyashio Current index in the
OFES simulation. The scaling vectors for the wind-stress (unit: dyn cm-2) and currents
(unit: cm s-1) are indicated at the upper-right corner of panels a and d, respectively.
Regression vectors for surface layer current are plotted only for |r|>0.27 (the 95%
confidence level) for both zonal and meridional components. For wind stress, black vectors
show that |r|>0.27 for zonal or meridional component.
Figure 8. Simultaneous correlation (shading as indicated to the right of each panel) and
regression fields between the SLP field and the (top) barotropic component and (middle)
100-m depth standardized wintertime Oyashio Current index in the OFES. The SLP field is
based on the NCEP reanalysis and its wintertime climatological (1950-2003) mean field is
shown in the bottom panel. Contour intervals are 1.0 and 4.0 hPa for the regression and
mean fields, respectively.
- 31 -
Figure 9. Time series of wintertime (January-March) mean meridional transport integrated
from the western boundary and 151°E (solid line; northward is positive; left axis) based on
the OFES simulation, and Sverdrup transport (southward is positive) integrated from 145°E
to the eastern boundary (dashed line; right axis) and to 170°E (dotted line; left axis). All
values are meridionally averaged between 40°N to 45°N. Unit for transport is Sv
(=1.0x106m3s-1).
Figure 10. Regression fields of wintertime (January-March) (e-h) surface layer current and
(a-d) wind stress, and correlation coefficients of Ekman pumping velocity (shading in the
left panels as indicated below panel d) on the standardized wintertime 100-m depth
Oyashio Current index. From the top to the bottom panel, surface current and wind fields
lead the index three- to zero-year. The scaling vectors for the wind stress (unit: dyn cm-2)
and currents (unit: cm s-1) are indicated at the upper-right corner of the top panels of the
corresponding column. Regression vectors for surface current are plotted only for |r|>0.32
(the 90% confidence level) for both zonal and meridional components. For wind stress,
black vectors show that |r|>0.32 for zonal or meridional component.
Figure 11. Scatter plots for latitude of axis of the eastward extension of the Oyashio Current
versus (a) the 100-m depth Oyashio Current index, and (b) the maximum zonal current
velocity at the axis. The axis is defined as the latitude of the maximum of the surface
eastward current zonally averaged between 150-160°E with SST colder than 10°C averaged
in the same zonal extent to exclude the zonal jet of the KE.
Figure 12. Springtime (March-May) SST regression (shading as indicated below the bottom
panel; unit: °C) and correlation coefficient (dashed contours; ±0.32, the 90% confidence
level, only) on the wintertime 100-m depth Oyashio Current index in the OFES simulation.
In the left column, SST leads the index three to one year, and right column shows the
simultaneous and one-, two-, and three-year lagged correlation and regression fields from
the top to the bottom panels. Solid contours are climatological (1950-2003) springtime
mean SST with contour intervals of 1°C.
- 32 -
Figure 13. Springtime (March-May) SSH regression (shading as indicated below the
bottom panel; unit: cm) and correlation coefficient (dashed contours; ±0.32, the 90%
confidence level, only) on the wintertime 100-m depth Oyashio Current index in the OFES
simulation. In the left column, SST leads the index three to one year, and right column
shows the simultaneous and one-, two-, and three-year lagged correlation and regression
fields from the top to the bottom panels. Solid contours are climatological (1950-2003)
springtime mean SSH with contour intervals of 5 cm.
Figure 14. Regression (shading as indicated below the bottom panels) and correlation
coefficient (contours) of springtime (March-May) absolute PV on σθ=27.0 kg m-3 isopycnal
surface to the wintertime 100-m depth Oyashio Current index in the OFES simulation. In
the left column, PV leads the index three to one year, and right column shows the
simultaneous and one-, two-, and three-year lagged correlation and regression fields from
the top to the bottom panels. In the top-left panel climatological (1950-2003) springtime
mean field of absolute PV on σθ=27.0 kg m-3 isopycnal surface is shown. Unit for potential
vorticity is 10-12 cm-1 s-1. Correlation coefficients are plotted only for ±0.32 (the 90%
confidence level) with solid (dashed) contours for positive (negative) values.
Figure 15. Springtime (March-May) upward sea surface heat flux regression (shading as
indicated below the bottom panel; unit: W m-2) and correlation coefficient (contours) to the
wintertime 100-m depth Oyashio Current index in the OFES simulation. In the left column,
heat flux leads the index three to one year, and right column shows the simultaneous and
one-, two-, and three-year lagged correlation and regression fields from the top to the
bottom panels. Correlation coefficients are plotted only for ±0.26 (thin, the 80% confidence
level) and ±0.32 (thick, the 90% confidence level) with solid (dashed) contours for positive
(negative) values.
Figure 16. Longitude-time sections of detrended SSH anomalies (cm; color shading as
indicated below the lower panels) at (upper-left) 38°N, (upper-right) 40°N, (lower-left)
42°N, and (lower-right) 44°N.
- 33 -
Figure 1. Annual-mean (a) surface current vectors and speeds (shaded as indicated to
the right), (b) sea surface height, and (c) sea surface temperature simulated in the
OFES hindcast integration. Climatological (1950-2003) mean fields are shown. The
scaling for the vectors is indicated at the upper-right corner with unit of cm s-1. Thick
vectors show currents with mean speeds greater than 30 cm s-1. Contour intervals for
sea surface height and temperature are 5 cm and 1°C, respectively. In (a) some currents
and geographies are labeled (AS is the Alaskan Stream, EKC the East Kamchatska
Current, OC the Oyashio Current, NPC the North Pacific Current, KP Kamchatska
Peninsula, HI Hokkaido Island, and KIs Kuril Islands).
- 34 -
Figure 2. Climatological (1950-1999) mean wintertime (January-March) SST based on
(a) the OFES hindcast integration and (b) JMA-SST. Contour intervals are 1°C. Black
rectangular indicates the region used to make regional mean temperature fields shown
in Fig. 3.
- 35 -
Figure 3. Time series of regional mean temperature in the region indicated by the
rectangular shown in Fig. 2 (40°-42°N, 147.5°-152.5°E). (a) Annual mean SST (thick
lines) based on the OFES simulation (solid) and the JMA-SST (dashed), and 100-m
depth temperature based on the OFES simulation (thin line; right axis). (b)
Climatological (1950-1999) mean seasonal variability in SST (thick lines with closed
circles; left axis) based on the OFES simulation (solid) and the JMA-SST (dashed), and
in 100-m depth temperature based on the OFES simulation (thin line with open circles;
right axis).
- 36 -
Figure 4. Climatological (1950-2003) mean seasonal mean current vectors in the surface
layer and meridional velocity (shading; as indicated below the lower-left panel), based
on the OFES simulation in (top-left) January-March, (top-right) April-June, (lower-left)
July-September, and (lower-right) October-December. The scaling for the vectors (unit
of cm s-1) are indicated below the lower-right panel. Thick vectors show currents with
mean speeds greater than 50 cm s-1. Black rectangular indicated the region used to
make regional mean meridional velocity fields shown in Fig. 5.
- 37 -
Figure 5. Time series of regional mean meridional velocity in the region indicated by the
rectangular shown in Fig. 4 (40.1°N-45.1°N, 143.1°E-151.1°E) based on the OFES
simulation. (Top) Wintertime (January-March) mean 100-m depth (solid) and vertically
averaged (dotted) meridional velocities, and their difference (dashed). (Bottom)
Climatological (1950-2003) mean seasonal variability in 100-m depth (solid) and
vertically averaged (dotted) meridional velocities, and their difference (dashed). Unit is
cm s-1.
- 38 -
Figure 6. Current vectors in the surface layer and their magnitudes (shading; as
indicated to the right of the top panel), based on the OFES simulation averaged over the
five winters (January-March) separately for (top) 1984-88 and (bottom) 1968-72. The
scaling for the vectors (unit: cm s-1) is indicated below lower-right corner of the top
panel.
- 39 -
Figure 7. (a, d) One-year lead, (b, e) simultaneous, and (c, f) one-year lagged wintertime
(January-March) (d, e, f) surface layer current vector and (a, b, c) wind-stress
regressions, and correlation coefficients of wind-stress curl (shading in the left panels as
indicated below panel c) to the standardized wintertime vertical mean Oyashio Current
index in the OFES simulation. The scaling vectors for the wind-stress (unit: dyn cm-2)
and currents (unit: cm s-1) are indicated at the upper-right corner of panels a and d,
respectively. Regression vectors for surface layer current are plotted only for |r|>0.27
(the 95% confidence level) for both zonal and meridional components. For wind stress,
black vectors show that |r|>0.27 for zonal or meridional component.
- 40 -
Figure 8. Simultaneous correlation (shading as indicated to the right of each panel) and
regression fields between the SLP field and the (top) barotropic component and (middle)
100-m depth standardized wintertime Oyashio Current index in the OFES. The SLP
field is based on the NCEP reanalysis and its wintertime climatological (1950-2003)
mean field is shown in the bottom panel. Contour intervals are 1.0 and 4.0 hPa for the
regression and mean fields, respectively.
- 41 -
Figure 9. Time series of wintertime (January-March) mean meridional transport
integrated from the western boundary and 151°E (solid line; northward is positive; left
axis) based on the OFES simulation, and Sverdrup transport (southward is positive)
integrated from 145°E to the eastern boundary (dashed line; right axis) and to 170°E
(dotted line; left axis). All values are meridionally averaged between 40°N to 45°N. Unit
for transport is Sv (=1.0x106m3s-1).
- 42 -
Figure 10. Regression fields of wintertime (January-March) (e-h) surface layer current
and (a-d) wind stress, and correlation coefficients of Ekman pumping velocity (shading
in the left panels as indicated below panel d) on the standardized wintertime 100-m
depth Oyashio Current index. From the top to the bottom panel, surface current and
wind fields lead the index three- to zero-year. The scaling vectors for the wind stress
(unit: dyn cm-2) and currents (unit: cm s-1) are indicated at the upper-right corner of the
top panels of the corresponding column. Regression vectors for surface current are
plotted only for |r|>0.32 (the 90% confidence level) for both zonal and meridional
components. For wind stress, black vectors show that |r|>0.32 for zonal or meridional
component.
- 43 -
Figure 11. Scatter plots for latitude of axis of the eastward extension of the Oyashio
Current versus (a) the 100-m depth Oyashio Current index, and (b) the maximum zonal
current velocity at the axis. The axis is defined as the latitude of the maximum of the
surface eastward current zonally averaged between 150-160°E with SST colder than
10°C averaged in the same zonal extent to exclude the zonal jet of the KE.
- 44 -
Figure 12. Springtime (March-May) SST regression (shading as indicated below the
bottom panel; unit: °C) and correlation coefficient (dashed contours; ±0.32, the 90%
confidence level, only) on the wintertime 100-m depth Oyashio Current index in the
OFES simulation. In the left column, SST leads the index three to one year, and right
column shows the simultaneous and one-, two-, and three-year lagged correlation and
regression fields from the top to the bottom panels. Solid contours are climatological
(1950-2003) springtime mean SST with contour intervals of 1°C.
- 45 -
Figure 13. Springtime (March-May) SSH regression (shading as indicated below the
bottom panel; unit: cm) and correlation coefficient (dashed contours; ±0.32, the 90%
confidence level, only) on the wintertime 100-m depth Oyashio Current index in the
OFES simulation. In the left column, SST leads the index three to one year, and right
column shows the simultaneous and one-, two-, and three-year lagged correlation and
regression fields from the top to the bottom panels. Solid contours are climatological
(1950-2003) springtime mean SSH with contour intervals of 5 cm.
- 46 -
Figure 14. Regression (shading as indicated below the bottom panels) and correlation
coefficient (contours) of springtime (March-May) absolute PV on σθ=27.0 kg m-3
isopycnal surface to the wintertime 100-m depth Oyashio Current index in the OFES
simulation. In the left column, PV leads the index three to one year, and right column
shows the simultaneous and one-, two-, and three-year lagged correlation and
regression fields from the top to the bottom panels. In the top-left panel climatological
(1950-2003) springtime mean field of absolute PV on σθ=27.0 kg m-3 isopycnal surface is
shown. Unit for potential vorticity is 10-12 cm-1 s-1. Correlation coefficients are plotted
only for ±0.32 (the 90% confidence level) with solid (dashed) contours for positive
(negative) values.
- 47 -
Figure 15. Springtime (March-May) upward sea surface heat flux regression (shading
as indicated below the bottom panel; unit: W m-2) and correlation coefficient (contours)
to the wintertime 100-m depth Oyashio Current index in the OFES simulation. In the
left column, heat flux leads the index three to one year, and right column shows the
simultaneous and one-, two-, and three-year lagged correlation and regression fields
from the top to the bottom panels. Correlation coefficients are plotted only for ±0.26
(thin, the 80% confidence level) and ±0.32 (thick, the 90% confidence level) with solid
(dashed) contours for positive (negative) values.
- 48 -
Figure 16. Longitude-time sections of detrended SSH anomalies (cm; color shading as
indicated below the lower panels) at (upper-left) 38°N, (upper-right) 40°N, (lower-left)
42°N, and (lower-right) 44°N.
- 49 -