RESEARCH ARTICLE
10.1029/2018JC014771
Key Points:• Tempo‐spatial variations of theKuroshio in the Tokara Strait were
examined using nearly nine‐year
ferryboat ADCP data with two‐day
intervals• The Kuroshio baroclinic(barotropic) transport via the Tokara
Strait occurs on biannual (annual)seasonal cycles• In addition to the meander andtransport variations, the Kuroshio
exhibits a band‐like structure, whichis related to island wakes
Supporting Information:• Supporting Information S1

Correspondence to:
X.‐H. Zhu,
xhzhu@sio.org.cn

Citation:
Liu, Z.‐J., Nakamura, H., Zhu, X.‐H.,
Nishina, A., Guo, X., & Dong, M. (2019).
Tempo‐spatial variations of theKuroshio current in the Tokara Strait
based on long‐term ferryboat ADCP
data. Journal of Geophysical Research:
Oceans, 124. https://doi.org/10.1029/
2018JC014771
Received 17 NOV 2018
Accepted 30 JUL 2019
Accepted article online 5 AUG 2019

Tempo‐Spatial Variations of the Kuroshio Current
in the Tokara Strait Based on Long‐Term
Ferryboat ADCP Data
Zhao‐Jun Liu1 , Hirohiko Nakamura2
Xinyu Guo4,5 , and Menghong Dong1, Xiao‐Hua Zhu1,3, Ayako Nishina2,

1State Key Laboratory of Satellite Ocean Environment Dynamics, Second Institute of Oceanography, Ministry of Natural
Resources, Hangzhou, China, 2Faculty of Fisheries, Kagoshima University, Kagoshima, Japan, 3Southern Marine Scienceand Engineering Guangdong Laboratory (Zhuhai), Zhuhai, China, 4Center for Marine Environment Studies, Ehime
University, Matsuyama, Japan, 5Application Laboratory, Japan Agency for Marine‐Earth Science and Technology,
Yokohama, Japan

Abstract Transverse‐vertical structure and temporal variability of the Kuroshio current across theTokara Strait during 2003–2012 measured by a ferryboat acoustic Doppler current proﬁler with a 2‐km
horizontal resolution and a two‐day interval are presented. The Kuroshio passing through the Tokara Strait
exhibits a multicore velocity structure. Its seasonal volume transport variation is biannual for baroclinic
components relative to 700 m, peaking in July and December–January. However, the barotropic transportcomponent exhibits an annual cycle with a maximum in December. Empirical orthogonal function analysisof the cross‐sectional velocity is performed. The ﬁrst two empirical orthogonal function modes reveal thenorth‐south shift of the Kuroshio current axis and the change in Kuroshio volume transport, respectively.
Temporal variabilities of the leading two modes correspond to those of the Kuroshio Position Index and thesea level difference across the strait, respectively. The third empirical orthogonal function mode, with arelatively smaller horizontal scale, was examined in terms of turbulent mixing. The banded structure
captured by this mode is likely induced by ﬂow‐topography interaction because islands in the Kuroshio
route could cause horizontal and vertical ﬂow separation. Additional analysis based on high‐resolution
reanalysis data suggested that (1) inertial instability, which is expected in the areas with negative Ertel's
potential vorticity, arises to enhance vertical mixing around the islands in the Tokara Strait, and (2) when
the Kuroshio directly impinges the islands, ﬂow divergence in the lee of the islands drives upwelling andleads to uplift of isotherms.
Plain Language Summary The Kuroshio is a western boundary current in the North Paciﬁc
which enters the East China Sea and leaves through the Tokara Strait. It is located between
Amamioshima and Yakushima Islands to the south of Kyushu, Japan. The variations in the Kuroshio path
position and transport across the Tokara Strait are crucial in monitoring the variability of the Kuroshio
downstream. This study presents the ﬁrst long‐term continuous transverse‐vertical structure and temporalvariability of the Kuroshio across the Tokara Strait, with unprecedented resolution based on observational
data. The Kuroshio passing through the Tokara Strait exhibits multiple‐core velocity structure, with amaximum transport in July and a secondary transport in December–January. The path ﬂuctuation andtransport variation explain 41% and 27%, respectively, of the total current variance in the Kuroshio in the
Tokara Strait. Moreover, because the Kuroshio current interacts strongly with the topography around theTokara Strait, many vortices are generated in this region. The lee of Tokara Islands is characterized by the
return current against the incoming current, and the wake water is 0.3–0.5 °C colder than the surrounding
waters. Additionally, the intensity of island‐induced wakes depends strongly on the shape of the Kuroshio
path around the Tokara Strait.
1. Introduction©2019. American Geophysical Union.
All Rights Reserved.

LIU ET AL.

The Tokara Strait is located between Amamioshima and Yakushima Islands to the south of Kyushu, Japan,
connecting the East China Sea and the North Paciﬁc (Figure 1). Through this strait, the Kuroshio carries signiﬁcant heat, salt, nutrients, and organic matter from the East China Sea into the North Paciﬁc (Andres
et al., 2009; Guo et al., 2012; Guo et al., 2013; Nitani, 1972; Oka & Kawabe, 1998). A number of studies

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Figure 1. (a) Bottom topography in the western North Paciﬁc and the typical Kuroshio path (thick cyan curve). (b) Close‐
up of the Tokara Strait area, indicated by the square box in Figure 1a. Bathymetry data are from JTOPO30v2 developed by
the Marine Information Research Center (MIRC), Japan. OhS indicates the Ohsumi Strait. The green and gray contour
lines refer to the 100‐ and 200‐m isobaths. Black bars indicate the vertically averaged ﬂow vectors during January
2003–March 2012 (unit vector of 0.4 m/s shown inside the ﬁgure), and principle axis variance ellipses of the ﬂows are
2 2shown in red (unit vector of 0.04 m /s shown inside the ﬁgure). Red triangles mark the locations of the tide gauge stations
at Naze, Nakanoshima, and Nishinoomote. All sections lacking spatial coverage of data are not used in the calculation of
the vertically averaged ﬂow vectors.

have suggested that the Kuroshio current shifts position in the north‐south direction, along with the volumetransport change in the Tokara Strait prior to the Kuroshio meander variations south of Japan (Kawabe,
1995; Zhu et al., 2001; Miyazawa et al., 2008; Usui et al., 2008). On the other hand, recent studies (Nagai
et al., 2017; Tsutsumi et al., 2017) have revealed that the vertical structure and water properties of theKuroshio are signiﬁcantly modiﬁed by vertical mixing around the shallow seamounts and small islands
existing within the route of the Kuroshio in the Tokara Strait. The Tokara Strait is a choke point for monitoring the variability of the Kuroshio. Therefore, it is important to obtain a full and complete understandingof the tempo‐spatial Kuroshio variation across the Tokara Strait, not only in terms of the physical processes
in the local area but also regarding the properties of the Kuroshio downstream.
Thus far, considerable efforts have been made to elucidate the tempo‐spatial velocity variations of theKuroshio, especially the current axis position and volume transport through the Tokara Strait, throughdirect current observation (e.g., Bingham & Talley, 1991; Feng et al., 2000; Kawabe, 1995; Nagata &Takeshita, 1985), geostrophic calculation (Andres et al., 2008; Ichikawa, 2001; Nakamura et al., 2006; Weiet al., 2013; Zhu et al., 2006), and product reanalysis (Soeyanto et al., 2014).
Four years of intensive moored observations (Feng et al., 2000) and inverse calculations (Nakano et al., 1994;
Wei et al., 2013) reveal a multicore velocity structure in the mean Kuroshio current in the Tokara Strait. This
multicore structure is likely due to the topographic blockage of the Tokara Islands in the upstream region(Bingham & Talley, 1991; Feng et al., 2000). The Kuroshio transport through the Tokara Strait varies fromapproximately 18 to 32 Sv (1 Sv ≡ 106 m3/s) and exhibits seasonal variation, with a maximum in summer
and minimum in fall (Blaha & Reed, 1982; Kawabe, 1988; Kubota et al., 1995).

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The Kuroshio current exhibits meandering motions in the Tokara Strait. Kawabe (1995) quantiﬁed thenorth‐south shift of the Kuroshio path in the Tokara Strait using the Kuroshio Position Index (KPI).
Yamashiro and Kawabe (1996) revealed that, according to the KPI, energetic Kuroshio‐path shifting in
the Tokara Strait has periods of approximately 30, 60, 120, and 180 days. Using KPI in addition to sea surface
dynamic topography from altimetry data, Ichikawa (2001) suggested that the above‐mentioned long‐term
Kuroshio path variations near periods of 120 and 180 days are associated with westward propagating mesoscale eddies from the North Paciﬁc interior region, while the short‐term Kuroshio path variation, with a period of 30–60 days, is locally generated immediately upstream of the Kuroshio, ﬂowing through the Tokara
Strait. Based on the KPI, Nakamura et al. (2006) found that the meander of the Kuroshio path is dominatedby a 30–90‐day peak in the Tokara Strait and is also characterized by a ﬁxed seasonal nature, with high activity in December–July.
Feng et al. (2000) performed mooring array measurements across the Tokara Strait from March 1992 toMarch 1996, providing valuable insights into the vertical and temporal variability of the Kuroshio current.
Their measurements spanned 143 km of the Tokara Strait, with a horizontal resolution of 11–28 km, eventhough were mostly deeper than 200 m. These measurements revealed that the variations of Kuroshio acrossthe Tokara Strait are dominated by long‐term (an approximately 100‐day period) and short‐term (10–30
days) ﬂuctuations.
However, the above‐mentioned direct current measurements may overlook some small‐scale temporal andspatial variations of the Kuroshio in the Tokara Strait due to the coarse tempo‐spatial resolution. For example, the moored observations conducted by Feng et al. (2000) were limited to currents deeper than 200 m.
The quarterly hydrographic observations conducted by the Japan Meteorological Agency were infrequent,
making the analysis of short‐term variability in the Kuroshio very difﬁcult. On the other hand, the inverse
method commonly used in previous studies assumes that the deep layer has an estimated reference velocity,
resulting in a barotropic component that is not available in the calculation (Imawaki et al., 2001; Wunsch,1978). Therefore, more intensive measurements are required to assess the tempo‐spatial variability inKuroshio through the Tokara Strait.
From January 2003 to March 2012, Kagoshima University conducted full‐depth acoustic Doppler current
proﬁler (ADCP) measurements across the Tokara Strait, using the round‐trip ferryboat Naminoue
between Kagoshima and Okinawa (Liu et al., 2017; Zhu et al., 2017). The repeated full‐depth ferryboat
ADCP surveys provide unprecedented temporal and spatial resolution to resolve the variation in the
Kuroshio across the Tokara Strait. Utilizing this data set, Zhu et al. (2017) successfully removed the inﬂuence of tidal currents and provided more accurate absolute Kuroshio transport across the Tokara Strait
than previous estimates.
The purpose of this study is to describe the mean transverse‐vertical structure, variability, andbarotropic/baroclinic components of the Kuroshio across the Tokara Strait. This paper is structured as follows. In section 2, we describe the data used in this study. The mean vertical structure and temporal variations are ﬁrst shown in section 3. Then, we show the three leading empirical orthogonal function (EOF)
modes of the cross‐sectional velocity of the Kuroshio on the transection across the Tokara Strait insection 4. The features of island‐induced wakes are discussed along with JCOPE‐T reanalysis data in
section 5. A discussion followed by concluding remarks is provided in section 6.

2. Data and Method
2.1. Ferryboat ADCP Observation Data
The current velocity data used in this study were taken from an ADCP (38.4 kHz, Ocean Surveyor ADCP,
Teledyne RD Instruments) mounted on the ferryboat Naminoue during January 2003–March 2012. The
ADCP was installed on the hull bottom of the ferryboat at a depth of approximately 6 m in bottom‐tracking
mode. The ferry Naminoue made round trips between the Kagoshima and Naze ports once every four days.
The data have a nearly two‐year gap during March 2008–April 2010 due to technical reasons including issues
with the GPS operation and uninterruptible power supply. The data sampling rate was set to one ping per 6 s,
and the bin length was 24 m with a total of 50 bins. The accuracy of the ADCP was ±0.5 cm/s (Teledyne RD
Instruments, 2013). The velocity proﬁles used in this study were averaged over 2 km in the horizontal, and a
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Table 1
Summary of the Information Regarding the Ferryboat and ADCP

Ferryboat

ADCP

Parameter

Description

Name
Ferryboat
Ship speed
ADCP installed depth
Data‐sampling rate
Bin length
Bin number
Removed tidal
constituents

Naminoue
6500 t, 145.6 m long, 22.0 m wide
10 m/s
6 m below the sea surface
One ping per 6 s
24 m
50
M2, S2, N2, K2, K1, O1, P1, and Q1

10.1029/2018JC014771

total of 146 mean proﬁles spanned the Tokara Strait. Consequently, a totalof 1,234 data tracks were collected, including 364 sections with data missing. The main information regarding the ferryboat and ADCP is listed inTable 1. Eight tidal constituents (M2, S2, N2, K2, K1, O1, P1, and Q1) havebeen removed from the ferryboat ADCP data utilizing tidal harmonic analysis methods. A detailed description of the data return and processing canbe found in Zhu et al. (2017).
2.2. Kuroshio Position Index
This study also used KPI as an indicator of the Kuroshio path position in
the Tokara Strait (Kawabe, 1995), which is deﬁned as
KPI ¼

X þ 83 cm;
Y þ 100 cm(1)

where X is the anomaly of the daily sea level difference between Nakanoshima and Nishinoomote from theaverage value of January 2003–March 2012. Y is the same as X but for Naze minus Nishinoomote. The sea
level difference was derived from daily sea levels recorded by tide gauges at Naze, Nakanoshima, andNishinoomote (as shown in Figure 1b) during the study period, corrected for the inverse barometer effect.
According to Yamashiro and Kawabe (1996), the linear regression relationship between the KPI and the latitude (°N) of the Kuroshio axis in the Tokara Strait can be expressed as follows:
LAT ð°NÞ ¼ 1:817×KPI þ 28:389(2)

In the following, we will use the term KPI to refer to the latitude of the Kuroshio axis in the Tokara Strait.
2.3. Ocean Reanalysis Data
To explore island‐induced wakes in more detail, especially the spatial distribution of island wakes aroundthe Tokara Strait, ocean reanalysis data (current velocity, temperature) calculated by JCOPE‐T were usedin this study. JCOPE‐T is a tide‐resolving real‐time general circulation modeling system with a horizontal
resolution of 1/36° and 47 sigma levels in the vertical direction (Varlamov et al., 2015). JCOPE‐T was developed based on the Princeton Ocean Model with a general coordinate of sigma (Mellor et al., 2002), covering
part of the western North Paciﬁc over 28°–44°N, 125°–148°E. JCOPE‐T was nested in an outer model with
no‐tide (JCOPE2; Miyazawa et al., 2009), with the use of a one‐way nesting technique (Guo et al., 2003).
JCOPE‐T is driven by the surface momentum, heat, and freshwater ﬂuxes calculated by an algorithm given
by Li et al. (2010), which uses modeled sea surface temperatures and hourly atmospheric data obtained fromthe Japan Meteorological Agency nonhydrostatic Mesoscale Model with a horizontal 5‐km grid (Saito et al.,2007). The JCOPE‐T data have been used to describe the general circulation and tidal current in the western
North Paciﬁc and around Japan (Miyazawa et al., 2012).

3. Mean Flow and Seasonal Variability
3.1. Mean Structure of the Kuroshio Current
The directly measured vertically averaged ﬂow and principle axis variance ellipses of the Kuroshio across theTokara Strait are shown in Figure 1b. The Kuroshio ﬂowing southeastward into the North Paciﬁc presents
two current maxima of 0.35 and 0.36 m/s in the northern and southern Tokara Strait, respectively. The
double‐core structure is consistent with the result obtained by Feng et al. (2000) at the observation line
located approximately 50 km east of the ferry track. Feng et al. (2000) suggested that the double‐core
structure may be caused by obstruction of the seamount south of Yakushima Island. As seen in Figure 1b,
a relatively weak northwestward countercurrent between these two current maxima (downstream of
Nakanoshima Island) was observed. Yet another important feature is that the vertically averaged ﬂow displays a sawtooth‐like structure in the southern channel. This phenomenon is likely due to the ﬂow‐
topography interaction around the Tokara Islands located in the upstream region of the ferry track(Bingham & Talley, 1991; Feng et al., 2000). The current cores also represent a distinct increase in variance.
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Figure 2. Mean vertical sections of (a) cross‐sectional and (b) along‐sectional velocities (unit: m/s) during January
2003–March 2012. Positive values in (a) and (b) denote southeastward and southwestward ﬂow, respectively. Blackand pink contours indicate standard deviations of 0.20 and 0.15 m/s, respectively. Bottom topography along the ferryboat
track is schematically denoted by the gray shade. (c) Mean (dots) and standard deviation (shaded area) of the layertransport (per unit meter; unit: Sv) over the period from January 2003 to March 2012. Black, red, blue, and green lines
indicate the net volume transport, eastward volume transport, volume transport in the northern part of the Tokara Strait,and volume transport in the southern part of the Tokara Strait, respectively. Here the northern and southern parts are
divided by the black triangle (29.96°N), shown at the top of Figure 2a.

Meanwhile, the coastal current through the Ohsumi Strait located north of Yakushima Island, ranging from
0.10 to 0.20 m/s with a large variance of up to 0.04 m2/s2, ﬂows along isobaths.
By averaging 1,234 sections from January 2003 to March 2012, Figure 2a provides a sectional view of themean cross‐sectional velocity of the Kuroshio through the Tokara Strait (positive is southeastward). The
Tokara Strait is characterized by two gaps divided by a seamount south of Yakushima Island: the northern
channel is shallower with a water depth of about 600 m and the southern channel has a maximum depth ofapproximately 1,050 m. Overall, the Kuroshio clearly shows a double‐core structure in the Tokara Strait. The
current cores are gradually strengthened from south to north; the maximum velocity in the southern channel is 0.54 m/s at 119 m deep and the maximum velocity in the northern channel is 0.64 m/s near the sea
surface. Additionally, the southern core is further divided into two smaller current cores. Therefore, asawtooth‐like structure is presented in the vertically averaged ﬂow vectors (Figure 1b). The net volumetransport distributed in the upper 200 m is 13.32 Sv, which is approximately 50% of the total net transport
through the Tokara Strait (Figure 2c). Therefore, to estimate the time‐varying Kuroshio volume transport,
retrieving the current above 200 m is important. The northern core is narrow and shallow, while the southern core is relatively broad with a width that is roughly twice that of the northern core. In addition, the total
width of the Kuroshio is approximately 200 km in the Tokara Strait, and the Kuroshio can penetrate todepths greater than 800 m in the southern strait.
The along‐sectional velocity (positive is southwestward) is similar to the cross‐sectional velocity in structure,but its magnitude is weaker than that of the cross‐sectional velocity, with maximum magnitudes of approximately 0.50 and 0.44 m/s at the northern and southern velocity cores, respectively (Figure 2b). Most of thelarge variances are concentrated in the current cores, and they are consistent with the principle axis varianceellipses of the ﬂows shown in Figure 1b. A subsurface countercurrent ﬂows northwestward between thenorthern and southern cores, with a maximum velocity of 0.18 m/s near the seaﬂoor (Figures 2a and 2b).
This countercurrent may result from the topographic effect of the island and seamount around the ferry
track, as mentioned above.
3.2. Seasonal Variability of the Kuroshio
The monthly mean cross‐sectional velocity over the period January 2003–March 2012 is presented in
Figure 3. The monthly mean Kuroshio current within the Tokara Strait exhibits a nearly permanent
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Figure 3. Monthly mean cross‐sectional velocity (unit: m/s). Gray shading indicates the topography. The monthly mean
volume transport is shown in the bottom left of each panel. The section numbers used for calculation are shown inbrackets.

multicore structure, which is consistent with that described by Feng et al. (2000). In addition, acountercurrent exists between the northern and southern cores for all months. The Kuroshio current isstrongest in July and weakest in October. The core velocity within the northern channel ranges from 0.60m/s in June and October to 0.71 m/s in July. Conversely, the core velocity in the southern channel varies
from 0.51 m/s in March and October to 0.60 m/s in July and December. The Kuroshio current cores tend
to be intensiﬁed in summer and winter and weakened in spring and fall. In the monthly mean
computation, we used all available data at each point on the transverse, so that all observation data are
fully utilized.

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Figure 4. (a–l) Monthly mean cross‐sectional velocity anomaly (unit: m/s). Each panel is accompanied by (right panel)a vertical proﬁle (24–600 m) of the horizontally averaged cross‐sectional velocity anomaly between two black triangles(unit: m/s), showing both edges of the main Kuroshio stream, and (top panel) a horizontal proﬁle of the verticallyaveraged cross‐sectional velocity anomaly between 24 and 600 m (unit: m/s). The monthly mean anomaly of the transport
is shown in the bottom left corner. Red (blue) dots in each top and right panel denote the positive (negative) velocity
anomalies.

Both the north‐south shift of the current axis and the change in volume transport for the Kuroshio can inﬂuence the cross‐sectional velocity structure shown in Figure 3. Therefore, it is considerably important to knowwhat roles they play in the vertical structure. To accomplish this, we ﬁrst analyze the anomaly of themonthly mean cross‐sectional velocity relative to the annual mean (shaded in Figure 4). Figure 4 clearlyshows that the Kuroshio exhibits a distinct positive anomaly in January, February, and July. Meanwhile,the current shows a seesaw‐like pattern, consisting of positive and negative anomalies in April, June,
August, September, and December. These seesaw patterns are suggested to be the result of the shift in the
Kuroshio axis. Therefore, it is difﬁcult to address the question proposed at the beginning: what is the effectof the Kuroshio axis shifting and transport change on the vertical structure of the cross‐sectional velocity?
We horizontally averaged the anomaly (proﬁles at the right of the shaded area) to remove the effect of axis
shifting and then found that the horizontally averaged anomaly is nearly zero from the surface to 600 m inJune and September (Figures 4f and 4i), indicating that the Kuroshio axis shifting is dominant in June and
September. In January and February, the horizontally averaged positive anomaly revealed that the Kuroshio

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tends to be intensiﬁed in the upper layer; meanwhile, the vertically averaged anomaly showed that theKuroshio slightly shifts northward (Figures 4a and 4b). In December, the Kuroshio shifts southward, andthe surface current is intensiﬁed (Figure 4l). In July, the vertically averaged anomaly is almost positive,
and such an anomaly in the northern part is much larger than that in the southern part, indicating that
the Kuroshio axis shifts northward and the Kuroshio velocity signiﬁcantly increases (Figure 4g).
The total water column of the Kuroshio on a transect across the Tokara Strait observed by the ferryboat
ADCP provides an excellent opportunity to separate the barotropic and baroclinic components, which is
absolutely crucial in understanding the mechanisms underlying the seasonal variability of the Kuroshio
in the Tokara Strait. In this study, the barotropic component was deﬁned as the near‐bottom velocity justabove the Ekman layer (Donohue et al., 2016; Fofonoff, 1962). Here it should be noted that in the southern
Tokara Strait, the water is much deeper, and a countercurrent is always present below 700 m (Figure 3). To
remove the effect of this countercurrent on the baroclinic component and maintain consistency with previous estimates from hydrography (e.g., Wei et al., 2013), the velocity of the barotropic component at which
point the water is deeper than 700 m was deﬁned as the observed velocity at 700‐m depth. The baroclinic
component was then the difference between the actual velocity and the barotropic velocity. Figure 5 shows
the monthly mean baroclinic cross‐sectional velocities. In general, the baroclinic velocity ﬁeld is similar to
the undecomposed current ﬁeld, with a maximum in July and minimum in October. In the following subsection, we will examine the variability in the Kuroshio transport, particularly separating its baroclinicand barotropic components.
Following the deﬁnition of the barotropic component mentioned above, barotropic volume transport(BTVT) through the Tokara Strait is deﬁned byA

BTVT ¼ ∫0 700×v700 m ðlÞdl for H≥700 m

(3)

and
A

BTVT ¼ ∫0 H ðlÞ×vbotm ðlÞdl for H<700 m(4)

where A is the width of the Tokara Strait, l is the distance from the northern end of the ferry track, H is thewater depth, and v700 m and vbotm are the observed velocities at 700‐m depth and near the bottom, respectively. Baroclinic volume transport (BCVT) is deﬁned by
700 m A
∫0 ½vðl; zÞ−v700 m ðlÞdl dz

BCVT ¼ ∫0

for H≥700 m

(5)

and
H A

BCVT ¼ ∫0 ∫0 ½vðl; zÞ−vbotm ðlÞdl dz for H<700 m(6)where v(l,z) is the observed velocity at distance l and depth z. Furthermore, positive volume transport(PVT) is deﬁned as the eastward Kuroshio transport through the Tokara Strait into the North Paciﬁc.
Figure 6a shows the temporal variations of the PVT, BCVT, and BTVT from January 2003 to March 2012.
The mean and standard deviation of the PVT for the observation period is 25.84 ± 3.13 Sv. The BCVT is comparable to PVT and is equal to 19.57 Sv with a standard deviation ±3.85 Sv, indicating that the Kuroshio
through the Tokara Strait is approximately 76% baroclinic. The BTVT through the Tokara Strait is muchsmaller than BCVT, equaling a value of 4.70 ± 2.25 Sv. The annual mean BTVT for each year, 4.55, 4.42,
4.57, 4.44, 4.39, and 4.36 Sv (years 2003, 2004, 2006, 2007, 2010, and 2011, respectively), is remarkably steady
except for year 2005 (6.01 Sv).
As shown in Figure 6b, the seasonal variation of the PVT exhibits a biannual signal, peaking in July
(27.17 ± 3.32 Sv), January (26.49 ± 2.72 Sv), and December (26.73 ± 2.77 Sv). The PVT has a minimumin May (24.63 ± 2.79 Sv) and a second minimum in October (24.83 ± 4.35 Sv). The BCVT (red line in
Figure 6b) displays a similar biannual variation as PVT, with a maximum in July (22.02 ± 3.16 Sv).

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Figure 5. Monthly mean cross‐sectional baroclinic velocity (unit: m/s). The monthly mean baroclinic volume transport
for the Kuroshio (positive velocity) is shown in the bottom left of each panel.

However, the seasonal variation of the BTVT (blue line in Figure 6c) is clearly different from that of the
BCVT, which exhibits an annual signal with its maximum in December (5.32 ± 3.32 Sv).
The seasonal signals for BCVT and BTVT shown in this study are consistent with recent results obtained byZ. Zhang, H. Nakamura, and X.‐H. Zhu, using satellite and reanalysis data (article not published, 2018; see
supporting information): over the entire Kuroshio path from east of Luzon Island to south of Japan, seasonal
velocity variations in the upper layer (from 0 to approximately 500 m) reach a maximum in July and a minimum in autumn (October to November) or winter (December to February) with different tendencies in eachregion. However, the lower layer velocity (>~500‐m depth) shows a reversed seasonal variation, reaching amaximum in winter, especially in the continental slope area from Luzon Island to the Ryukyu Island chain.
According to their consideration based on numerical experiments, the seasonal velocity variations in theupper layer are primarily forced by local wind stress upon the Kuroshio, which is related to the East Asia
monsoon, and secondarily inﬂuenced by downstream anomaly advection along the current. However, theseasonal velocity variations in the lower layer are the nontopographic Sverdrup response to seasonal windstress curl in the interior region west of the Izu‐Ogasawara Ridge. In this situation, if we consider the seasonal Kuroshio transport variations estimated for the water column from the sea surface to depths over 700 m,
we can detect a semiannual cycle with maxima in winter and summer for a combined feature of the two

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Figure 6. (a) Monthly averaged PVT (black), BCVT (red), and BTVT (blue) through the Tokara Strait from January 2003
to March 2012 (unit: Sv). Green and pink lines indicate the PVT for the southern strait (PVTS) and that for the northernstrait (PVTN), respectively. Dashed line with a number indicates the mean value for each volume transport. (b and c)
Seasonal variations in PVT (black), BCVT (red), and BTVT (blue) with error bars (unit: Sv). Error bar indicatesstandard error for the mean transport in each month. Positive transports correspond to southeastward ﬂow.

responses for the BCVT. However, the BTVT, estimated to be 700‐m depth, has a characteristic
corresponding to only lower layer velocity. This study supports their result with the ﬁrst observational
evidence from the vertical section of velocity.
Figure 6 yields additional information about partial volume transports in the southern and northern channels. A positive transport of 20.32 ± 3.47 Sv exists due to southeastward ﬂow (green line) through the southern channel (south of 29.96°N), indicating that approximately 79% of the total Kuroshio transport occurs
through the southern channel. Meanwhile, the positive transport (pink line) through the northern channel(north of 29.96°N) contributes 5.50 ± 1.41 Sv.

4. Three Leading EOF Modes of the Kuroshio Variability
To examine the temporal and spatial variability of the Kuroshio through the Tokara Strait, we performed
EOF analysis for the cross‐sectional velocity during January 2003–March 2012. Because the data have a
gap for the period 7 August 2008 to 12 March 2010, we ﬁlled the data gap with the mean value for the same
day and month in normal years. For example, the data gap on 7 August 2008 was ﬁlled using the mean value
for 7 August of years 2003, 2004, 2005, 2006, 2007, 2010, and 2011.
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Figure 7. Spatial patterns of the ﬁrst three EOF modes of the cross‐sectional velocity (unit: m/s): (a) EOF1, (b) EOF2,
and (c) EOF3. The percentage of explained variance is indicated in the bracket for each pattern. Gray contours indicate
zero. (d–f) Associated normalized principal components (PCs) for the ﬁrst three EOF modes (blue lines). The KPI,
SSH difference between Naze and Nishinoomote (unit: cm), and integration of the absolute value of the horizontal
cross‐sectional velocity gradient (μ, unit: 1/s) are superimposed on (d)–(f), respectively (black lines), along with thecorrelation coefﬁcient between the two time series given at the top right corner. The horizontal gradient is calculated
over the region between the two black triangles shown in Figure 7c.

Figure 7 shows the ﬁrst three EOF spatial patterns and normalized principal components (PC) of the cross‐sectional velocity. The ﬁrst three EOF modes explain 41.1%, 26.3%, and 19.2% of the total variance,
respectively. The spatial structure of EOF1 is characterized by a dipole‐like pattern, indicating that thecross‐sectional velocity variations on the northern and southern sides of the Kuroshio mean current axis
are out of phase; that is, there is a north‐south Kuroshio axis shift (Figure 7a). The normalized PC1 is reasonably well correlated with the KPI time series (r = 0.77, signiﬁcant at the 95% conﬁdence level; Figure 7d). A
positive PC1 value indicates a southward Kuroshio axis shift, while a negative PC1 value indicates a northward Kuroshio axis shift. The EOF1 of the current captures the dominant variability in the Kuroshio paththrough the Tokara Strait, consistent with Wei et al. (2013).
The EOF2 spatial structure exhibits a monopole pattern, which is characterized by in‐phase velocity variation over the cross section with a core of the largest amplitude near the mean Kuroshio core (Figure 7b).
This mode can be interpreted as the variation of the Kuroshio transport. The normalized PC2 can be tracked
down in the time series of the SSH difference between Nishinoomote and Naze; the correlation coefﬁcient of
the two time series is equal to 0.65 (signiﬁcant at the 95% conﬁdence level; Figure 7e). The latter time series isoften referred to as the temporal variations of the Kuroshio transport through the Tokara Strait, based ongeostrophic calculations (e.g., Ichikawa, 2001; Kawabe, 1988).

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Figure 8. Power spectrum density (unit: m ·s ·day ) for the ﬁrst three EOF principal components: (a) PC1, (b) PC2,and (c) PC3. Broken lines denote 90% conﬁdence curves for the periodgrams smoothed with a seven‐point runningmean. The data gaps during January 2003–March 2012 are ﬁlled with zeros.

Different from the ﬁrst two EOF modes, the EOF3 spatial pattern exhibits a banded structure with a characteristic scale smaller than that of the ﬁrst two EOF modes, as revealed in Figure 7c. Previous studies suggestthat the islands and seamounts in the Kuroshio route could cause a ﬂow divergence and convergence in thewake, inducing energy conversion from large‐scale to small‐scale motion, and then drive the upwelling andvertical mixing in the wake. For example, previous studies about island wakes have been performed aroundthe Green Island east of Taiwan (Chang et al., 2013), the Tokara Islands in the Tokara Strait (Hasegawa et al.,2008; Nagai et al., 2017; Tsutsumi et al., 2017), and Aoga‐Shima near the Izu‐Ogasawara Ridge (Hasegawa
et al., 2004). Therefore, we attributed the EOF3 to the island‐induced wakes in the lee of the Tokara
Islands, located approximately 20 km upstream of the ferryboat ADCP section. To further identify these
topography‐induced Kuroshio variations captured by the EOF3, we vertically and horizontally integrated
absolute values of the horizontal gradient of the cross‐sectional velocity (μ), and we found that it is correlatedwith the PC3 (r = 0.56, signiﬁcant at the 95% conﬁdence level), as shown in Figure 7f.
Next, we examined the dominant frequencies for the temporal variation of each principle component.
Figure 8 shows the power spectrum densities for the ﬁrst three PCs. Both PC1 (meander mode) and PC2(transport mode) show statistically signiﬁcant (90%) spectral peaks for the periods of 10–20 and 35–50 days.
This tendency of PC1 and PC2 exhibiting the same spectral peaks suggests that meandering motions (PC1)
are associated with transport variations (PC2), with a phase difference of approximately 1/4 period (seeFigure S5 in the supporting information). By examining the current pattern during the phase propagationof PC1 and PC2, we found that a frontal meander exists when the Kuroshio separates the continental slope.
Additionally, the Kuroshio axis clearly shifts northward and the southern part gradually penetrates deeper
in the Tokara Strait (ﬁgures are not shown). Therefore, the phase difference between PC1 and PC2 may haveoriginated from the frontal meander generated by barotropic and baroclinic instability in the Kuroshio front
on the continental slope area. According to previous observational studies (e.g., Ichikawa & Beardsley, 1993;
James et al., 1999; Nakamura et al., 2003), this instability could propagate downstream to the Tokara Strait.
Horizontal and vertical phase shifts during the propagation may induce the phase difference between the
Kuroshio meander and the transport variation in the Tokara Strait. Future studies are needed to identify
the concrete mechanism behind the phase difference in the propagation. On the other hand, only PC2(transport mode) shows a weak peak at 146 days, although this peak is not distinguishable from backgroundnoise at the 90% conﬁdence interval. This peak is likely related to mesoscale eddies propagated from theNorth Paciﬁc interior (Ichikawa, 2001; Yan et al., 2016).
The spectrum of PC3 has several distinct peaks around 10, 20, 40, and 100 days (Figure 8c). It seems to benatural to ask why the spectra of PC3 exhibit similar frequency ﬂuctuations as those of PC1 and PC2. Weshould note that, although EOF modes are orthogonal and, therefore, are not correlated in the time domain,
EOF modes are not necessarily uncorrelated in every given frequency band, as suggested by Zhang et al.
(2001). In fact, as we will show in section 5.2, PC3 (island‐induced wakes) is closely related to the
Kuroshio state (connected with meander and/or transport) in the upstream of the ferry track. In summary,
the Kuroshio state could modify island‐induced wakes in the following three cases: (1) the shifting Kuroshio
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Figure 9. Mean absolute velocity (unit: m/s) on the transection for (a) JCOPE‐T reanalysis data and (b) ADCP
observation. The time frame spans the observational period during January 2003–March 2012. (c) Comparison oftransport (unit: Sv) time series from the JCOPE‐T reanalysis (black) with ADCP observation (blue). Correlation coefﬁcient
between two time series is given at the top right corner.

current path with uniform transport causes the main Kuroshio stream to directly impinge the Tokara
Islands, (2) the increased Kuroshio transport with a steady Kuroshio current path induces the passing ofadditional Kuroshio water through the Tokara Islands, and (3) coexistence of the above two cases. This is
why the spectra of PC3 (island‐induced wakes) are close to those of PC1 (meander mode) and PC2(transport mode).

5. Island Wakes in Ocean Reanalysis Data
For better understanding of the character of island wakes behind the Tokara Islands captured by the EOF3,
we used the JCOPE‐T ocean reanalysis data to examine the plain and vertical structure of the island wakes inthis section.
5.1. Validation of Ocean Reanalysis Data
In this subsection, we ﬁrst compare the JCOPE‐T reanalysis and ferryboat ADCP data for the time‐averaged
velocity structure of the Kuroshio on a transection through the Tokara Strait, and then, we examine theirtemporal agreement by the correlation analysis.
First, to be consistent with observations, the JCOPE‐T data were linearly interpolated to the ferry track.
Next, the time frame of the JCOPE‐T data was set to strictly coincide with the observational time; in thissense, the reanalysis data in the period when the observational data are missing were not used in the analysis. Considering that the direction of the current across the ferry track may differ from the JCOPE‐T and
ADCP data, we compared the absolute velocities on the transection but not cross‐sectional velocities. In
the time‐mean vertical structure of the absolute velocity on the transection (Figure 9), both the observation
and reanalysis demonstrate a multicore feature of the Kuroshio, including the countercurrent beneath the
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Figure 10. Same as in Figure 7 but for the result obtained from the JCOPE‐T data. Spatial patterns of the ﬁrst three EOF
modes of the cross‐sectional velocity (unit: m/s): (a) EOF1, (b) EOF2, and (c) EOF3. The percentage of explained varianceis indicated in the bracket for each pattern. Gray contours indicate zero. (d–f) Associated normalized principal
components (PCs) for the ﬁrst three EOF modes (blue lines). The SSH difference between Naze and Nishinoomote(unit: cm), KPI (°N), and integration of the absolute value of the horizontal gradient of cross‐sectional velocity (μ, unit: 1/s)
are superimposed on (d)–(f), respectively (black lines), along with the correlation coefﬁcient (r) between the two timeseries given at the top right corner. The horizontal gradient is calculated over the region between the two black triangles
shown in Figure 7c.

Kuroshio, although the current in the northern channel is excessive for the JCOPE‐T data. The cause of theexcessive northern Kuroshio core may be related to the overshooting of the Kuroshio, separating from thecontinental slope.
The JCOPE‐T time series of volume transport through the Tokara Strait during 2003–2012 is shown in
Figure 9c. The JCOPE‐T reanalysis agrees well with observations but has a slightly smaller mean and variability. The JCOPE‐T mean net volume transport through the Tokara Strait (excluding the Ohsumi Strait) is
20.41 ± 3.01 Sv, while the observed net volume transport by ferryboat ADCP is 23.03 ± 3.31 Sv. During theobservational period, the JCOPE‐T reanalysis captures the temporal transport variability well. The correlation coefﬁcient between the observed and reanalyzed volume transports through the Tokara Strait is 0.68
(signiﬁcant at the 95% conﬁdence level).

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We also computed the EOFs for the modeled cross‐sectional velocity during January 2003–March 2012. To
maintain consistency with the observational data (data gap during 7 August 2008–12 March 2010), theJCOPE‐T data during the gap years were padded with the mean value for the same day and month innormal years.
Figure 10 shows the ﬁrst three EOF spatial patterns and normalized principal components of the cross‐sectional velocity based on JCOPE‐T data. In the modeled EOFs, the meander and transport variations
are two dominant modes of the Kuroshio structure, consistent with the observation. However, the explained
variances in these two leading modes are different from those in observation. The meander mode is the mostdominant in observation (41.1%), but this mode loses 14.1% of its explained variance in JCOPE‐T data
(27.0%). The transport mode shows a signiﬁcant increase of 19.4% in explained variance from observation(26.3%) to JCOPE‐T data (45.7%). This difference may be attributed to the fact that the modeled Kuroshio
path is more stable than the real Kuroshio path.
To conﬁrm this hypothesis, we further compared the Kuroshio axis position (in latitude) at 129°E observedby the Japan Coast Guard (https://www1.kaiho.mlit.go.jp/KANKYO/KAIYO/qboc/kurosio‐num.html)
with that in JCOPE‐T model. Observational data are available from August 2006. The mean ± standard
deviation values for the observed and simulated Kuroshio axis latitudes at 129°E during August 2006–
March 2012 are 30.01 ± 0.22° and 30.29 ± 0.13°, respectively (see Figure S6 in the supporting information).
This means that the Kuroshio always overshoots as compared with the observed Kuroshio near 129°E whenthe modeled Kuroshio separates from the continental slope and ﬂows toward the Tokara Strait. This bias,
therefore, causes a weaker Kuroshio path variation (smaller standard deviation) in the Tokara Strait thanin the realistic ocean.
The model bias is essentially associated with the open boundary conditions at its lateral boundary (125°E)
that is located upstream of the Tokara Strait. The open boundary conditions there were obtained fromJCOPE2, whose resolution is not fully sufﬁcient to resolve the Kuroshio front meander, and its associatedfrontal eddy. Because of insufﬁcient input of perturbations from the upstream area, the Kuroshio in the
Tokara Strait for JCOPE‐T is, therefore, more stable as compared to the observation.
Nevertheless, the EOF3 in the JCOPE‐T and observation are indeed very similar. Not only are the patterns
quite similar but the explained variances are not signiﬁcantly different. Both the observational and modeled
EOF3 show a banded structure with a characteristic scale smaller than that of the ﬁrst two EOF modes.
Therefore, it is appropriate to deeply examine the island wakes in the Tokara Strait based on JCOPE‐T data.

5.2. Surface Pattern and Vertical View of Island Wakes
The JCOPE‐T reanalysis data with a horizontal resolution of 1/36° have indeed simulated the island‐induced
wakes in the Tokara Strait. Recent studies (e.g., Gula et al., 2016; Thomas et al., 2013) suggest that inertial(or centrifugal) instability, in the context of the Gulf Stream, can be triggered in the area where ζ/f(relative vorticity ζ normalized by Coriolis parameter f) becomes smaller than −1 (namely, Ertel's potential
vorticity is negative), and such an instability extracts kinetic energy mostly from the horizontal shear so thatenhanced local dissipation and mixing are expected to occur. As for the Kuroshio, Liu and Chang (2018)
have examined the effect of inertial instability for Kuroshio‐induced island wakes at Green Island off theeastern coast of Taiwan, based on numerical experiment. Their study showed that the inertial instability
tends to slightly destabilize the anticyclonic recirculation on the leeside of the island with negative Ertel's
potential vorticity. This situation is examined using the JCOPE‐T reanalysis.
Figure 11a shows the time series of the sum of absolute normalized relative vorticity along the ferryboat
track (red lines; hereafter sum|ζ/f|). This time series reveals that strong wakes with large amplitudes (>mean+ standard deviation) tend to develop in the summer (e.g., June–July). In contrast, weak wakes with small
amplitudes (<mean − standard deviation) tend to occur in the winter. Such a seasonal variation of island‐
induced wake intensity is closely associated with the location in the latitude for the Kuroshio at 129°E, asrevealed in Figure 11a. The correlation between the sum|ζ/f| (red line) and the latitude of Kuroshio at
129°E (green line) is 0.68. In the following section, we will show the surface patterns and vertical views of
the strongest wake (on 20 June 2006) and the weakest wake (19 October 2011), respectively, in the entire
observation period.
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Figure 11. (a) Comparison of the sum of the absolute normalized surface relative vorticity (∣ζ/f∣; red line) with the
Kuroshio axis latitude at 129°E (blue line) based on JCOPE‐T data (correlation coefﬁcient r = 0.61 for the period
January 2003–March 2012). (b)–(d) Instantaneous ζ/f, sea surface temperature anomaly (unit: °C), and sea surface current
velocity (unit: m/s) for 20 June 2006, when the island wakes are strongest. (e–g) Same as in (b)–(d) but for instantaneous
distribution on 19 October 2011 when the island wakes are weakest.

Figure 11b shows the instantaneous ζ/f (surface relative vorticity normalized by f) on 20 June 2006, and it
reveals that the anticyclonic and cyclonic vorticities are on the left and right sides of the wake, respectively.
As shown in Figure 11b, the area where ζ/f less than −1 (equivalent to negative Ertel's potential vorticity) ispresent in the Tokara Strait where the Kuroshio current strongly interacts with the topography. Cold, thinstreaks with lengths of approximately 50 km appear behind the islands on 20 June 2006 (Figure 11c). The
water within the wakes is 0.3–0.5 °C colder than the surrounding waters. The lee of the islands is characterized by the return current against the incoming current (Figure 11d). Figures 12a–12c show the vertical

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Figure 12. Vertical sections of (a) normalized relative vorticity ζ/f, (b) temperature (°C), and (c) cross‐sectional velocity(m/s) on 20 June 2006 when the island wakes are strongest. (d–f) Same as in (a)–(c) but for vertical sections on 19
October 2011 when the island wakes are weakest. The white curves for temperature (b and e) and velocity (c and f) indicate
isotherms from 21.6 °C to 27.6 °C with an interval of 2 °C, and zero velocity.

views of relative vorticity, temperature, and velocity over the section, respectively. Behind the island, themulticore velocity structure of Kuroshio is more enhanced on 20 June 2006 than the mean state shown in
Figure 9. Isotherms in the upper 100 m are domed behind the islands, indicating that upwelling andvertical mixing occur there.
Contrary to the situation shown in Figure 11b (20 June 2018), Figure 11e shows that when the island‐
induced wakes become relatively weaker (19 October 2011), the Kuroshio path clearly shifts northward.
In this case, the concurrent distributions of relative vorticity and sea surface temperature do not change
as much in the lee of the islands (Figures 11e–11g). Additionally, the vertical sections of the relative vorticity,temperature, and velocity (Figures 12e–12f) are comparable to the mean state displayed in Figure 9.

6. Summary
We examined the transverse‐vertical structure and temporal variability of the Kuroshio on a transect acrossthe Tokara Strait based on nearly nine years of ADCP data obtained by the ferry Naminoue (Figure 1). Flowis divided into cross‐ and along‐sectional components (Figure 2). A multicore structure of the Kuroshio isobserved in the northern and southern parts of the Tokara Strait (Figure 2a).
The monthly averaged cross‐sectional velocity revealed that the Kuroshio tends to shift northward, accompanied by intensiﬁed surface current in January, February, and July (Figures 3 and 4). In contrast, theKuroshio tends to shift southward, and the surface current also intensiﬁes in December.

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The mean PVT and standard deviation for the observation period is 25.84 ± 3.13 Sv (Figure 6). The meantransports through the northern and southern channels are 5.50 and 20.32 Sv, respectively. Baroclinic transport relative to the bottom is 21.93 Sv and ﬂuctuates by 2.68 Sv, indicating that the Kuroshio in the Tokara
Strait is approximately 80% baroclinic.
The seasonal variation of PVT represents a biannual signal with three peaks in July (27.17 ± 3.32 Sv),
January (26.49 ± 2.72 Sv), and December (26.73 ± 2.77 Sv). The seasonal variation of BCVT exhibits a similar
biannual cycle with a maximum in July (22.02 ± 3.16 Sv). However, the BTVT shows different seasonalvariations from the PVT and BCVT, portraying an annual variation with a maximum in December(5.32 ± 3.32 Sv). As explained in section 3.2, the different seasonal variations between BCVT and BTVT
may be related to the hypothesis that the seasonal velocity variations in the upper layer are primarily forced
by local wind stress upon the Kuroshio due to the East Asia monsoon, while those variations in the lower
layer are the nontopographic Sverdrup response to seasonal wind stress curl in the interior region west of
the Izu‐Ogasawara Ridge.

Acknowledgments
The authors would like to thank thecaptain and crew of the Ferry
Naminoue, Hiroshi Ichikawa for
conducting the current monitoring
program in the early stages, andTakeyoshi Nagai for the valuablecomments to inertial instability. We
appreciate the helpful suggestions fromthe editor and two anonymous
reviewers. The SIO group was mainly
supported by the National Natural
Science Foundation of China(41920104006, 41576001, 41906023,
41776107, and 41621064), the Project ofState Key Laboratory of Satellite Ocean
Environment Dynamics, Second
Institute of Oceanography(SOEDZZ1901, SOEDZZ1804, and
SOEDZZ1806), the Scientiﬁc Research
Fund of SIO under grants JT1604 andJT1801, and the National Program on
Global Change and Air‐Sea Interaction(GASI‐IPOVAI‐01‐02). The KU groupwas supported by the Japan Society for
the Promotion of Science (JSPS)
KAKENHI (JP15H05821, JP15H03725).
The EU group was also supported by
JSPS KAKENHI (JP15H05821) and by
the Ministry of Education, Culture,
Sports, Science and Technology, Japan(MEXT) to a project on Joint
Usage/Research Center–Leading
Academia in Marine and Environment
Pollution Research (LaMer). Data usedin this study are available under thefollowing link: https://pan.baidu.com/
s/18uwsDLFGQgfF_DhyHE_I0g.

LIU ET AL.

EOF analysis of the cross‐sectional velocity suggests that the major variations of Kuroshio (nearly 67%) in
the Tokara Strait result from a combination of meandering (EOF1, 41.1%) and transport (EOF2, 26.3%)
modes (Figure 7). The PC1 is reasonably well correlated with the KPI time series (r = 0.77; Figure 7d),and the PC2 is correlated with the sea level difference between Naze and Nishinoomote (r = 0.65;
Figure 7e). Although the ﬁrst two EOF modes have been reported by previous studies based on quarterlyhydrographic data from the Japan Meteorological Agency, these studies depicted only the interannual anddecadal variability of these two modes due to limited temporal resolution. The full‐depth ferryboat ADCP
data set with 2‐km horizontal resolution and two‐day interval enables us to capture the short‐term temporalvariation of the Kuroshio Current across the Tokara Strait. Both meandering and transport mode PCs havesigniﬁcant energy peaks at 10, 20, and 35–75 days (Figures 8a and 8b). The third spatial mode shows a band‐
like structure with a horizontal scale smaller than those of the ﬁrst two EOF modes (Figure 7c); the band‐likestructure is related to the Kuroshio‐induced wake in the lee of Tokara Islands, located approximately 20 km
upstream of the ferryboat ADCP section.
The high‐resolution (1/36°) JCOPE‐T reanalysis data revealed that many vortexes were generated aroundthe Tokara Strait by ﬂow‐topographic interaction. The anticyclonic and cyclonic vorticities were in the left
and right halves of the island wake, respectively (Figure 11b). In the areas where the relative vorticity issmaller than −f (namely, the areas with negative Ertel's potential vorticity), the inertial instability is
expected to develop and enhance the energy dissipation in this region. This reanalysis data suggest thatthe amplitude of relative vorticity underlying the precondition of inertial instability strongly depends on
the shape of the Kuroshio path around the Tokara Strait. According to the JCOPE‐T reanalysis data, whenstrong island‐induced wakes occurred, the water within the wakes could be 0.3–0.5 °C colder than the surrounding waters, with isotherms in the upper 100 m domed behind the islands (Figure 12). Concurrently,
they can be carried downstream by the Kuroshio current. In future studies, it will be important to identify
the impact of island wake variations associated with the Kuroshio shape around the Tokara Strait on thesurrounding ecosystem.
In this study, we revealed full‐depth characteristics of seasonal and intraseasonal variations for the Kuroshio
current in the Tokara Strait for the ﬁrst time, based on a long‐term record of directly measured velocity
sections with high spatial and temporal resolutions. We believe that the results of this study signiﬁcantly
contribute to understanding the dynamics of the Kuroshio for seasonal and intraseasonal variations.
Furthermore, studies of the ﬂow‐topography interaction associated with the EOF3 are helpful for understanding the ecosystem within the Kuroshio in which nutrient supply from deep water by upwelling andvertical mixing is necessary to sustain primary production.

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