25

Journal of Oceanography, Vol. 62, pp. 25 to 35, 2006

Keywords:⋅⋅⋅⋅⋅ Kuroshio volumetransport,

⋅⋅⋅⋅⋅ interannualvariability,

⋅⋅⋅⋅⋅ quasi-geostrophicvorticity equation,

⋅⋅⋅⋅⋅ Rossby wave.

* Corresponding author. E-mail: wakata@riam.kyushu-u.ac.jp

Copyright © The Oceanographic Society of Japan.

Interannual Variability of the Kuroshio Transport Pass-ing through the 137°E Meridian in an OGCM Related tothe North Pacific Windstress

YOSHINOBU WAKATA1*, TAKASHI SETOU2, IKUO KANEKO3, HIROSHI UCHIDA3 and SHIRO IMAWAKI1

1Research Institute for Applied Mechanics, Kyushu University, Kasuga-kohen, Kasuga-shi, Fukuoka 816-8580, Japan2Mitsubishi Research Institute, Otemachi, Chiyoda-ku, Tokyo 100-8141, Japan3Japan Agency for Marine-Earth Science and Technology, Natsushima-cho, Yokosuka-shi, Kanagawa 237-0061, Japan

(Received 29 January 2004; in revised form 28 April 2005; accepted 9 May 2005)

The interannual variability of the Kuroshio volume transport passing through the137°E meridian south of Japan was simulated with an ocean general circulation model(OGCM). The time series of the Kuroshio volume transport over the 1000 m depth inthe OGCM is well reproduced by the one-dimensional quasi-geostrophic (QG) vorticityequation with a windstress forcing. In our analysis of the OGCM and QG results, wefound that peaks and troughs of the time series of the Kuroshio volume transportwith 2–3 yr time-scale were induced by windstress curl, both local and immediatelyeastward, whereas longer time-scale variability was also induced by windstress curlnear the dateline.

transport west of Ryukyu Islands (Nansei Shoto)), and itwas found that the interannual variability is not very high.This calmness is caused by the effect of the blocking ofthe Rossby waves by the Ryukyu Islands. As Kawabe(2001) noted, there is a possibility that a current east ofthe Ryukyu Islands may be responsible for large amountof the volume transport. Yuan et al. (1994, 1995) andIchikawa et al. (2004) actually observed this current. Thevolume transport related to the PN-line is thus a realmonitor of the Kuroshio Current, but it may be not suffi-cient to evaluate the interannual variability as the west-ern boundary current transport reflected in the variabilityof the subtropical gyre.

To evaluate the interannual variability of theKuroshio transport, we consider the transport south ofJapan. Here we investigate the volume transport of theKuroshio south of Japan passing through the 137°E me-ridian, since the Japan Meteorological Agency (JMA)conducted a repeat survey along the 137°E meridian from1967, to reveal general oceanographic structure and vari-ability in the western North Pacific. This survey provideshydrographic observation data over more than 30 years.Volume transport, estimated from this hydrographic databy use of the geostrophic relation, may support an evalu-ation of the present results as reference data.

The steady western boundary current can be esti-mated from the windstress over the open ocean by use of

1. IntroductionThe Kuroshio Current transports a large amount of

heat northward in the western North Pacific and its vari-ability is thus thought to cause a climate change over awide-area. The interannual variability has year-to-yearand decadal components. It is important to consider thereason for this. It is well known that the time-mean trans-port can be explained in terms of the Sverdrup relation(1947) as a response to open ocean windstress, but thetime-dependent variability has not yet been thoroughlyinvestigated due to a lack of long-term observations. Thisstudy addresses the interannual variability of the Kuroshiosouth of Japan through numerical simulation of an oceangeneral circulation model (OGCM). We investigate howadequately a simple quasi-geostrophic (QG) vorticityequation can explain the variability and identify the ef-fective wind-forcing area. The Sverdrup relation is thendeduced from a kind of steady solution of the QG equa-tion.

The relative scarcity of long-term monitoring datais due to the difficulty of ocean observation. One long-term observation was carried on in the East China Sea(PN-line; a representative observation line of the Kuroshio

26 Y. Wakata et al.

the Sverdrup theory (1947), which is based on the con-cept of mass balance between the western boundary trans-port and the open-ocean transport through the latitude lineestimated from the Sverdrup balanced flow with thesteady-state assumption, i.e. the sum of both transports isalways zero. However, as in the case of the present time-dependent upper layer transport, the presumption of massbalance is not applicable since the water mass can be tem-porarily one-sided in part, and hence the method used inthe Sverdrup theory cannot be used. To evaluate the time-dependent problem, QG dynamics is often applicable in-stead.

The Kuroshio mainly flows through the upper oceanover about 1000 m depth (Book et al., 2002). We treatthe transport based on the currents relative to the refer-ence 1000 m depth currents, because our aim is not toevaluate the mass balance due to each current system butto explain its variability. The abyssal flow along the areawith the large bottom-slope gradient may contribute tothe total transport, but these flows are sometimes in a dif-ferent position from the main axis of the Kuroshio Cur-rent and vary with a different timescale from the core ofthe Kuroshio Current. The upper level flow is influencedby the baroclinic Rossby wave, while the abyssal flowmay be influenced by the bottom trapped wave propagat-ing along the f/h isoline (f is the Colioris parameter and his the ocean depth). The definition of variable transportdue to the Kuroshio, i.e. transport over 1000 m or totaldepth, is a matter of debate. We adopt the former stance,and thus do not aim to explain the dynamics of abyssalflow.

The interannual variability of the upper level trans-port is influenced by the baroclinic Rossby wave. We at-tempted to evaluate the western boundary current fromthe QG equation assuming a long wave based on the 1.5layer model with reduced gravity. The Kuroshio volumetransport can be fundamentally evaluated by the dynamicheight difference between the Japan coast and the southborder of the Kuroshio through the geostrophic flow re-lation. If the dynamic height variability near the Japancoast is relatively small and if the southern border of theKuroshio is determined by the QG vorticity equation, theKuroshio volume transport will be estimated by a simpleeast-west, one-dimensional QG vorticity equation.

We have evaluated how adequately the simple sce-nario, in which the volume transport is estimated by theQG vorticity equation, can explain the interannual vari-ability of the Kuroshio volume transport. This can allowa discussion of which area of windstress gives rise to theinterannual variability of the Kuroshio, and may allow aprediction of the Kuroshio transport on an interannualtime scale. The best way to evaluate the result of QGmodel is to compare it with observed data, but the timecoverage of the data is too sparse for this purpose. Hence,

we mainly discuss the results of QG model and OGCM.Yasuda and Kitamura (2003) also investigated the

interannual variability of the Kuroshio transport associ-ated with the decadal variability based on OGCM outputdata. They compared the time series of the Kuroshio trans-port with that of the windstress curl averaged over 170°E–170°W, 25°–35°N with a 5 yr running mean, and found alinkage between the interannual variability of theKuroshio transport and the wind stress near the dateline3 yr previously. We also treated OGCM data, but we alsopaid attention to year-to-year variability with a time scaleshorter than their results, focusing on the QG dynamics.

Akitomo et al. (1996) treated the same subject usingthe 1.5 layer reduced gravity model. They indicated thatthe baroclinic Rossby wave at the beginning of theKuroshio (south of 21°N) causes variability of the down-stream Kuroshio transport in the East China Sea (28°N)and south of Japan. They inferred that fluctuation in theinitial area affected the downstream Kuroshio volumetransport due to the nonlinear (advection) effect of theKuroshio itself.

Kawabe (2000) developed a simple model, based onQG dynamics, to explain the interannual variability ofthe sea surface height. Kawabe (2001) solved the linearQG equations of a barotropic mode and two baroclinicmodes to investigate variability of the Kuroshio volumetransport in the East China Sea (PN-line; a representativeobservation line of the Kuroshio transport west of theRyukyu Islands). This study allowed for mode transferbetween the baroclinic and barotropic modes resultingfrom the bottom topography effect, which is based on theidea that the upper part of the node of the first baroclinicmode can pass over the Izu-Ogasawara Ridge. Thebaroclinic mode can change the transport only through

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grid number

sigm

a va

lue

Fig. 1. Distribution of vertical sigma coordinates for each grid.

Interannual Variability of the Kuroshio Transport Passing 27

this process. Kawabe concluded that the volume trans-port in the East China Sea could be explained mainly bythe barotropic mode.

Akitomo et al. (1996) and Kawabe (2001) focusedon the interannual variability of the Kuroshio volumetransport passing through the PN-line in the East ChinaSea because it was considered that their variability maybe related to the large meander of the Kuroshio south ofJapan. However, variability of the volume transportthrough the PN-line is quite small, as mentioned above.Here, we consider the Kuroshio volume transport southof Japan passing through the 137°E meridian. Qiu andJoyce (1992) calculated geostrophic flow through the137°E meridian using the JMA hydrographic observationdata. We have recalculated it until recent times, and there-after compared it with OGCM results.

Comparison of the results of the QG model with theOGCM shows that QG dynamics is mainly acceptable inthe area without the area of intensive eddy activity. Thetemporal Kuroshio transport can be estimated from thewindstress over the open ocean, which must extend ourknowledge of how the interannual variability of Kuroshiotransport links to the windstress over the wide PacificOcean.

2. Model DescriptionThe Princeton ocean general circulation model

(POM) was used. The topography estimated from NationalGeophysical Data Center ETOPO5 data is set at the bot-tom of the model, but the ocean floor deeper than 6000 m

is smoothly shallowed as transferred h(x, y) = –6000 –500 × (1 – exp((etopo5(x, y) + 6000)/2000)), whereh(x, y) is the model ocean depth and etopo5(x, y) is thedepth data of ETOPO5; the depth (in meters) is then de-fined as negative. The sigma coordinate, in which thevertical coordinate is scaled on the water column depth,is used in the POM and the total number of vertical lev-els is 30. The level interval is narrowed near the surfaceand bottom (Fig. 1). This model adopts the level 2.5 tur-bulent closure scheme to estimate the vertical eddy vis-cosity and diffusivity (Mellor and Yamada, 1982). Thehorizontal grid size is 0.25° × 0.25° in longitude and lati-tude, respectively. The horizontal eddy viscosity and dif-fusivity are assumed to be the Smagorinsky type, depend-ing on the grid spacing and the velocity gradient(Smagorinsky, 1963; Mellor and Blumberg, 1985). Themodel domain is from 30°S to 65°N latitude and from110°E to 70°W longitude (Fig. 2). The radiation bound-ary condition is adopted at the southern boundary.

The monthly means of surface fluxes of short waveradiation, long wave radiation, latent heat and sensibleheat and the daily means of windstress are obtained fromthe reanalysis data of the National Centers for Environ-mental Prediction and the National Center for Atmos-pheric Research (NCEP/NCAR, Kalnay et al., 1996) asthe driving forcing of the model. The salinity flux is esti-mated from the precipitation rate and the evaporation rate,but the evaporation rate was estimated from the latentheat flux. These fluxes further include additional Haneytype correction terms such as α(Tobs – T) or α(Sobs – S),

0 5 10 15 20 25 30 35 40 45 50 55 60

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15S

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30N

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Fig. 2. Computational area and bottom depth (m) of the ocean model. Sea levels at the marked locations are examined in Fig. 5.

28 Y. Wakata et al.

120oE 130oE 140oE 150oE 160oE 170oE

24oN

30oN

36oN

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48oN

-1.0 -0. 8 -0.6 -0.4 -0.2 0 0.2 0.4 0.6 0.8 1.0

Fig. 3. Sea surface height (m) of the OGCM. This is a time mean for the period 1965–2000.

where α is an adjusting coefficient and T and S are sur-face temperature and salinity of the model and Tobs andSobs are the value of climatology taken from Levitus andBoyer (1994) and Levitus et al. (1994). These adjust thesea surface temperature and the sea surface salinity tothe climatological monthly surface data, which can pre-vent the model results from deviating widely from theclimatological value (Haney, 1971). The flux correctionof surface salinity (temperature) can relax the anomalyin a 50 m column, assuming uniform salinity (tempera-ture), to the climatological value with 100 days for α =5.8 × 10–6 m/s. The temperature and salinity is also ad-justed to the climate values in the deep ocean below 2000m. The relaxation time is 730days/(1 – exp(1 + d/2000)),where d is the water depth in meters (negative). Theboundary layer is assumed at the ocean bottom. Theroughness parameter is set to 0.003, which is applied todetermine the drag coefficient (Mellor, 2004).

To obtain the initial field the model was driven bythe climatological monthly mean fluxes for 20 years fromthe climatological temperature and salinity fields withmotionless states obtained from the World Ocean AtlasData (Levitus and Boyer, 1994; Levitus et al., 1994). Themodel was driven from this initial field using the monthlymean fluxes from January 1st 1958 to December 31st2002.

The time mean sea surface height of the model isshown in Fig. 3. The Kuroshio takes the non-large mean-

der path and the Kuroshio separation around 34°N is alittle south but is by and large well reproduced. TheKuroshio extension area shows a very wavy pattern. Fig-ure 4 shows the root mean square of the sea surface height.The Kuroshio extension area is strongly fluctuated andthe detached cold water mass sometimes migrates west-ward south of Japan. The passage of this detached eddygives rise to an artificial high rms area around the area of(31°N, 139°E). The zonally extended high rms area isshown around 20°N, which relates to the activity of thewave along the Hawaiian Lee Countercurrent (Kobashiand Kawamura, 2002). We compared the model sea levelanomaly with the tidegauge data at some Island stationsdistributed in mid latitude shown in Fig. 2. The anomalyindicates the difference from the time mean value here-after. Figure 5 shows the simulated and observed sea lev-els at some observation stations aligned in the middle lati-tude east of the Kuroshio, which may influence the vari-ability of the Kuroshio transport. The observed data atChichi-jima shows an increasing trend but this is not cap-tured in the model. However, on the whole, it shows atendency of agreement about the peaks and troughs.

3. Results

3.1 Interannual variability of Kuroshio volume transportThe volume transport of the Kuroshio south of Ja-

pan passing through the 137°E meridian is investigated

Interannual Variability of the Kuroshio Transport Passing 29

RMS of model sea surface height (m)

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)

Fig. 4. Root mean square of the OGCM sea surface height (m).

Fig. 5. Sea surface height (cm) of the general circulation model (heavy line) and tidegauge data (thin line) at several stationsmarked in Fig. 2.

30 Y. Wakata et al.

here. We hereafter treat the data with a 1-yr running meanto remove the seasonal variability. We calculate the vol-ume transports passing the 137°E meridian from the southcoast of Japan to some southern latitudes in the openocean. To allow comparison of the model transport withthat based on the observed geostrophic flow, and to in-vestigate the effect of baroclinic Rossby waves, we usethe relative current to the 1000 m-depth reference cur-rent in this calculation. To eliminate the eddy effect atthe south boundary, which produces an artificial variabil-ity of Kuroshio transport due to the attachiment (or not)of vigorous eddy to the border, some transports relevantto the different southern borders are averaged. The cor-ner of the integration area, which is a kind of windowtaking the area mean in data analysis, is then somewhatrounded. The southern borders are taken as 26–28°N with0.25 degree interval.

Figure 6 shows the model transport; the mean valueis 37.2 SV. The figure shows minima in 1968, 1973 and1976 with some peaks, and large maxima in 1982 andminima in 1985. In succeeding years the volume trans-port oscillates with a 2–3 yr period. This does not includethe Kuroshio transport due to the recirculation becausewe integrated up to around 27°N and then the eastwardand westward transports due to the recirculation must becanceled out. Hence, the interannual variability of therecirculation is not included.

3.2 Relation between Kuroshio volume transport andwindstress curlWe take the lag correlation between the Kuroshio

volume transport passing through the 137°E meridian(Fig. 6) and the dynamic height in the North Pacific Oceanto evaluate the effect of the wave propagation in Fig. 7(a).The dynamic height was calculated from the referencelevel 1000 m depth to 200 m depth to extract wave sig-nals; the section shallower than 200 m was excluded toavoid mixture with the steric effect resulting from thesurface heat and salt flux. A high correlation appears near

the dateline (180°E) 3–4 yr previously. This high areagradually shifts westward. At lag 0 yr, the high correla-tion area extends eastward from the 137°E meridian. Itshould be noted that the correlation was calculated up to10 yr lag (not shown here) and no high correlation wasfound east of 160°W. Figure 7(b) depicts the correlationwith the windstress curl. A high correlation area appearsnear the dateline 3–4 yr previously; this corresponds tothat of the dynamic height 3–4 yr previously. This strongwindstress curl induces this dynamic height anomaly. Thisis consistent with the finding of Yasuda and Kitamura(2003), who calculated a similar lag correlation and founda large lag correlation 3 yr previously near the dateline.The present research gives a more detailed treatment ofshorter time-scale phenomena, such as year-to-year vari-ation. The Kuroshio volume transport found in the presentresearch shows peaks and troughs with a 2–3 yr time scale,as shown in Fig. 6. Yasuda and Kitamura (2003) showedonly the correlation map with a 3 yr lag for annual meandata and compared the time-series of the windstress andthe Kuroshio transport with a 5 yr running mean becausetheir aim was to study decadal phenomena; however, asshown in Fig. 7(b), a large correlation with windstresscurl also appears around 150°E at 0–1 yr previously. Inorder to discover which area of the windstress is crucial,research is needed that adopts a dynamical approach ratherthan a statistical one.

Propagation of the wave can be readily detected bydepicting the Hovmöller diagram of the dynamic heightanomaly. Figure 8(b) shows the dynamic height anomaly,which is the meridional mean between 26°N and 28°N.The appearance of a high dynamic height around 137°Ecoincides with the peak of the Kuroshio volume trans-port in Fig. 8(a). The Kuroshio transport minima in 1968,1973 and 1985 correspond to a negative dynamic heightat 137°E. The maximum in 1982 originates in the posi-tive dynamic height anomaly. These dynamic heightanomalies seem to come from the east. These wavepropagations have been evaluated by QG dynamics.

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30

35

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50

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SV

model volume transport

Fig. 6. Model volume transports (SV) based on the relative current to the reference current at 1000 m depth. This is a mean of thevolume transports calculated from the several southern borders (26–28°N) to the south coast of Japan.

Interannual Variability of the Kuroshio Transport Passing 31

Fig. 7. (a) Year lag correlation between the volume transport passing through the 137°E meridian in Fig. 6 and the dynamicheight anomaly. (b) Year lag correlation between the volume transport and the windstress curl. Note that the scale of (b) isreversed.

32 Y. Wakata et al.

3.3 Understanding with the quasi-geostrophic modelIf this wave signal results from the first baroclinic

Rossby wave, it can be well explained by QG dynamics.The baroclinic Rossby wave formed by the windstresscurl can be investigated using a simple QG equation witha long-wave assumption (Meyers, 1979; Wakata andKitaya, 2002). The QG equation is derived from the re-duced gravity system that deals with the upper layer mo-tion over the motionless, infinitely deep ocean. The gov-erning equation of the upper layer thickness (ULT)anomaly h, i.e. the main thermocline depth anomaly, is

∂∂

∂θ∂λ

τ αρh

tc

h

a

curl

fh− = − − ( )

cos,

0

1

where θ and λ are latitude and longitude, respectively, cis the velocity of the first baroclinic Rossby wave (c canbe expressed by βg*H/f2; g* is a reduced gravity param-eter and H is a mean upper layer depth and β is a meridi-onal derivative of the Coriolis parameter), τ is the

windstress, α is the Rayleigh type damping, and a is theearth’s radius, ρ0 is the density of water and f is theCoriolis parameter at 27°N. We adopted c = 5 cm/s andα = 1/(2 yr). Kawabe (2000, 2001) used c = 5.88 cm/sand damping rate 1/(532 d). It should be noted that thehomogeneous solution of the present QG model can ex-press a baroclinic Rossby wave which has a verticallyintegrated non-zero flow, in contrast to the free baroclinicRossby mode defined by the usual vertical mode expan-sion (Kawabe, 2000, 2001).

The solution of QG is

ha

c f

a

c

a

ccurl d

E

=

⋅ − ′

′ ( )∫

cosexp

cos

expcos

,

θρ

α θ λ

α θ λ τ λλ

λ

0

2

where integration is performed along a characteristic lineon which λ – ct is constant. Figure 8(c) shows the solu-

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-20 20-0.05 0.05-7

Fig. 8. (a) Kuroshio volume transport (SV) passing through the 137°E meridian (Fig. 6). (b) Time-longitude sections of dynamicheight anomaly (m) of OGCM, (c) upper layer thickness anomaly (m) of QG model, and (d) windstress curl anomaly (N/m3),which are meridional mean from 26°N to 28°N. Note that the scale of (d) is reversed.

Interannual Variability of the Kuroshio Transport Passing 33

tion. A great deal of variability near the western bound-ary in the OGCM in Fig. 8(b) can be well reproduced bythis simple QG equation. The windstress curl anomaly,used to calculate Eq. (2), was taken as the meridional meanfrom 26°N to 28°N, as shown in Fig. 8(d). The wind forc-ing corresponding to each Rossby wave activity in Figs.8(b) and (c) can be distinguished. The positive signalsaround 137°E in 1981–83, 86, 91, 94 in Figs. 8(b) and (c)are emitted by the negative windstress curl anomaly, lo-cal and immediately eastward, shown in Fig. 8(d). Thelarge negative windstress curl anomaly around 170°W in1983 induced a large positive ULT anomaly. This posi-tive signal propagates westward, but seems to be feebleon arrived at the 137°E area, and its influence on the trans-port is limited. The large dynamic height and ULT anoma-lies around 137°E in Figs. 8(b) and (c), which are relatedto the variability of the volume transport, are excited bythe wind forcing around 150°E, as shown in Fig. 8(d).This was confirmed by solving the QG model separatelyfor the east part forcing and the west part forcing.

Volume transports at the western boundary may beestimated by the geostrophic balance using the solutionof Eq. (2), if the nonlinear and viscosity effects are small.The value of –(hN – hS)g*H/f, where hN is the Japan coastand hS is the south border, gives the eastward geostrophictransport between the Japan coast and the southern bound-ary. Furthermore, if the anomaly hN near the coast is small,this becomes simply U = hSg*H/f, which can also be ex-pressed as U = hScf/β using the phase velocity c. TheKuroshio transport at 137°E estimated by this method isshown in Fig. 9 (heavy line), where the windstress usedin this calculation is the meridional mean from 26°N to

28°N. It should be noted that this is not based on the con-cept of mass balance along the latitude line in the NorthPacific as adopted in the derivation of the Sverdrup flowbecause this is not applicable to the baroclinic compo-nent. It is surprising that the tendency is quite similar tothat of the OGCM. Each peak and trough in the time se-ries of the volume transport in the QG model shows quitegood agreement with those of OGCM (Fig. 6). The time-mean value difference of the volume transport betweenOGCM and QG may come from the barotropic compo-nents, since the signal of the QG model, describingbaroclinic components with slow phase velocity, is welldamped by the dissipation. However, the barotropic com-ponent can propagate quickly and hence all effects ofwindstress can be reflected in the western boundary cur-rent.

We considered the forcing origin of each peak andtrough of the volume transport. To evaluate the locationwhere windstress is important, the transport is calculatedseparately in the west of 170°E (line with stars) and inthe east of 170°E (line with circles) in Fig. 9. The respec-tive peaks and troughs can be explained by windstresswest of 170°E, whereas the increase of the volume trans-port after 1980, which seems to have a longer time scale,such as decadal variability, could be influenced bywindstress curl east of 170°E, as discussed by Yasuda andKitamura (2003). The complementary calculations of theremote forcing show that the variability of transport dueto the windstress east of 170°E is mainly explained interms of the windstress near the dateline and the meanvalue is augmented by the windstress further east.

The applicability of QG has been investigated at otherlatitudes. Figure 10 shows the correlation between thetransports deduced from QG and OGCM at each south-

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Fig. 9. Kuroshio volume transport (SV) estimated by integrat-ing QG equation from 137°E to American west coast (heavyline), from 137°E to 170°E (line with stars), and from 170°Eto American west coast (line with circles). Thin line is thetransport from the OGCM, which is 25 SV removed fromFig. 6.

Fig. 10. Correlations between the Kuroshio volume transportof OGCM and QG at each latitude.

34 Y. Wakata et al.

ern border. For example, the southern border 30°N indi-cates the mean transport from 29°N to 31°N as in the pre-vious study. The correlation is very high: around 26°N itis over 0.7. It becomes small around 29°N, owing to theeffect of the westward passage of the cold eddy detachedfrom the Kuroshio extension area, which seems to be tooactive in this model (Fig. 4), and the correlation aroundthere is unreliable. The low correlation around 22°N mayresult from the wave activity along the Hawaiian LeeCountercurrent.

4. Discussion and ConclusionsWe have investigated the interannual variability of

the Kuroshio volume transport, explained in terms of sim-ple one-dimensional QG dynamics. Peaks and troughswith a 2–3 yr time scale can be explained by the localand immediate east windstress curl west of 170°E. Thevariability on a longer time-scale, which may be relatedto decadal variability, is also affected by windstress nearthe dateline, as discussed by Yasuda and Kitamura (2003).The dynamical discussion based on QG was studied, andwe have confirmed that the decadal variability of theKuroshio transport is linked to the windstress near thedateline.

Akitomo et al. (1996) also discussed a similar sce-nario, but they calculated the transport at the beginningregion (17–21°N) of the Kuroshio by integrating the QGequation along the same latitude as this beginning region.They considered that variability of this transport influ-ences the downstream Kuroshio in the East China Seaowing to the advective (nonlinear) effect of the Kuroshioitself. However, the present result does not always sup-port their scenario because the linkage between theKuroshio transport at 137°E and the beginning region isnot clear, as seen in the correlation map in Fig. 7. Theimportant forcing was rather the wind at the same lati-tude as the Kuroshio.

Kawabe (2001) noted the importance of barotropicRossby waves for interannual variability of the Kuroshiovolume transport. However, the present results empha-size the role of the baroclinic Rossby waves. This dis-crepancy may arise from the definition of the intendedKuroshio because their subject of the Kuroshio is in theEast China Sea (PN-line) while the present research ad-dresses an area south of Japan. There are sharp continen-tal slopes under the East China Sea; in addition, the bot-tom topography may induce the barotropic componentthere.

We compared the QG with OGCM, but made no com-parison with the observational record. The Japan Mete-orological Agency (JMA) conducted a repeat survey alongthe 137°E meridian from 1967, revealing general ocea-nographic structure and variability in the western NorthPacific. This survey provides hydrographic observation

data over more than 30 years. Volume transport can beestimated from hydrographic data by use of thegeostrophic relation. Qiu and Joyce (1992) calculated thevolume transport of the eastward flow from this data set.We extended this calculation for a longer period to thepresent and calculated the transport from the Japan coastto 27°N (26°–27°N mean the same as OGCM analysis),and compared it with the model results. The observedtransport based on the geostrophic flow, the referencelevel of which is 1250 dbar, shows peaks in 1982 and1990 and troughs in 1970, 1975, 1985 and 1995 (Fig. 11).Some peaks and troughs show agreements with theOGCM, such as 1982, 1985, 1995, but the others are notclear. It is interesting that the period of good agreementcomes after the climate shift of late the 1970’s. The agree-ment with observation was worse than we had expected.Many reasons for this discrepancy may be come up with.There are few observations; the observational transportis highly variable, depending on the choice of southernborder of integration; it is impossible to simulate the phe-nomena related to the intrinsic instability without theproper initial condition in a model; etc. However, eventhough the representation of phase is not complete, thestatistical relation and the dynamical linkage between thetransport and windstress might be correct and the resultsderived from the present study may aid our understand-ing of the real ocean dynamics.

It should be noted that the transport treated here doesnot simply indicate the eastward Kuroshio Current. Theeastward and westward transports relating to therecirculation must be canceled out, and the interannualvariability of the recirculation is not included in thepresent meridionally integrated transport. Here we haveonly treated the vertically integrated transport in the up-per layer, based on the reference flow at 1000 m depth,while the total transport is not treated, because theinterannual variability is dominant in the upper layer and

Fig. 11. Annual mean observed Kuroshio transport (SV) fromthe south coast of Japan to 27°N (a mean 26–28°N calcu-lated in the same way as Fig. 6) obtained from thegeostrophic flow to the reference depth 1250 db.

1965 1970 1975 1980 1985 1990 1995 200020

30

40

50

60

YEAR

SV

observation volume transport

Interannual Variability of the Kuroshio Transport Passing 35

the deep ocean transport does not convey much heat rela-tive to the upper ocean, owing to the weak meridionaltemperature gradient. QG dynamics are sometimes usedto consider the interannual variability of ocean for sim-plicity, but the applicability of this treatment has not beenconfirmed, since it may be due to lack of long-term ob-servations. It has been confirmed, though, using theOGCM, that the western boundary transport can easilybe estimated by a simple QG equation, which allows theuse of QG for investigating the time-dependent westernboundary current.

AcknowledgementsThe authors wish to acknowledge the support of Ja-

pan Science and Technology Corporation. They are greatlyappreciative of Drs. M. Ikeda and K. Tanaka for theirhelpful discussion and also wish to express their thanksto two reviewers whose comments were very helpful inimproving this article.

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