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On the Reset of the Wind-Forced Decadal Kuroshio Extension Variability in Late 2017
BO QIU,a SHUIMING CHEN,a NIKLAS SCHNEIDER,a EITAROU OKA,b AND SHUSAKU SUGIMOTOca

Department of Oceanography, University of Hawai‘i at Manoa, Honolulu, Hawaii
Atmosphere and Ocean Research Institute, The University of Tokyo, Kashiwa, Japanc
Department of Geophysics, Graduate School of Science, Tohoku University, Sendai, Japanb

ABSTRACT: Decadal modulations of the Kuroshio Extension (KE) system between a stable and an unstable dynamic
state in the western North Pacific have prevailed in the past three decades. This dominance of decadal variations is controlled by the negative feedback loop involving the wind-forced KE variability and its feedback onto the overlying extratropical storm tracks and the basin-scale surface wind field. The wind-forced decadal KE modulations were disrupted inAugust 2017 due to the development of the Kuroshio large meander south of Japan. By forcing the inflow KE paths
northward and by avoiding overriding the shallow Izu Ridge, the Kuroshio large meander was able to compel the KE tochange rapidly from the wind-forced, pre-existing, unstable state to a stable state. Following the large meander occurrencein late 2017, the stabilized KE change is found to affect the overlying storm tracks and the basin-scale wind field the same
way as those generated by the wind-forced KE change prior to 2017. Given the consistent atmospheric response to both thelarge-meander-induced and wind-forced KE variability, we expect that the KE dynamic state will resume its decadal
modulation after the phase reset relating to the 2017 large meander event.
KEYWORDS: Atmosphere-ocean interaction; Boundary currents; Climate prediction; Decadal variability; Mesoscale
processes; Oceanic variability

1. Introduction
The Kuroshio has its origin in the northern branch of theNorth Equatorial Current (NEC) that flows westward and bifurcates off the Philippine coast near 128N (Fig. 1). As it flows
poleward, the Kuroshio gains progressively its volume transport and becomes a well-defined western boundary current(WBC) with a transport of ;15 Sv (1 Sv [ 106 m3 s21) whenreaching the Luzon Strait (Lien et al. 2014). After passing by
Taiwan, the Kuroshio enters the semi-enclosed East China Sea
wherein its path is dynamically constrained by the steep continental slope. The Kuroshio enters the deep Shikoku basinthrough the Tokara Strait near 1308E and, due to the development of an offshore recirculation gyre, its eastward volumetransport can reach up to 60 Sv (e.g., Imawaki et al. 2013). The
Kuroshio exits the Shikoku basin by overriding the shallow Izu
Ridge along 1408E and it is renamed the Kuroshio Extension(KE) after it enters the open North Pacific. With the enhancement from both the southern and northern recirculation
gyres, the volume transport of the eastward-flowing KE has
been observed to exceed 100 Sv (Wijffels et al. 1998; Qiu et al.
2008; Jayne et al. 2009).
Large-amplitude variability in the Kuroshio/KE system canbe separated into three segments, each with distinct regional
characteristics. The first segment lies in the latitudinal bandeast of Luzon and Taiwan between 188 and 258N. As indicatedin Fig. 1, this band has a high mesoscale eddy variability that
extends eastward to the Hawaiian Islands across the western
North Pacific Ocean. Mesoscale eddies along the 188–258N
band have been observed to propagate westward with a typicalCorresponding author: Bo Qiu, bo@soest.hawaii.edu

period of O(100) days and a phase speed of about 0.1 m s21,
and they are generated by baroclinic instability induced by thezonal velocity shear between the eastward-flowing SubtropicalCountercurrent (STCC) in the surface layer and the westwardflowing NEC in the subsurface layer in the western North
Pacific (Qiu 1999; Kobashi and Kawamura 2002; Cheng et al.
2017). After impinging upon the western boundary, the STCC
mesoscale eddies have been detected to exert significant
changes in the Kuroshio path and transport inside the East
China Sea, as well as the Ryukyu Current that flows northward
to the east of the Ryukyu Islands (e.g., Zhang et al. 2001; Gilson
and Roemmich 2002; Ichikawa et al. 2004; Andres et al. 2008).
The second segment of enhanced Kuroshio variability appears in the deep Shikoku basin south of Japan. Constrained by
the inflow via the narrow Tokara Strait and the need to override the meridionally oriented Izu Ridge along 1408E, theKuroshio in the Shikoku basin is known for its bimodal pathfluctuations between a nearshore straight path and an offshore
meandering path (Kawabe 1995). During both of these twopaths (commonly known as the ‘‘straight path’’ and ‘‘large
meander path’’), the Kuroshio exits the Shikoku basin via a
relatively deep channel centered around 348N along the
shoaling Izu Ridge. In addition to these two preferred paths,
the Kuroshio south of Japan can also exhibit a third path thatloops southward over the shoaling Izu Ridge. The Kuroshio
path fluctuations south of Japan are highly irregular and chaotic; the occurrence of the Kuroshio large meander (LM)shows no dominant periodicities, nor a preferred duration [forrecent reviews, see Qiu and Miao (2000) and Usui et al. (2013)].
As will be explored in section 3 of this study, the dynamicalcauses underlying the bimodal Kuroshio path fluctuations in
the Shikoku basin continues to be a topic of active research.

DOI: 10.1175/JCLI-D-20-0237.1
Ó 2020 American Meteorological Society. For information regarding reuse of this content and general copyright information, consult the AMS Copyright
Policy (www.ametsoc.org/PUBSReuseLicenses).

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(Manuscript received 4 April 2020, in final form 18 September 2020)

10814JOURNAL OF CLIMATEFree from the constraint of coastal boundaries, the KE eastof Japan constitutes the third high eddy variability segment.
With the enhancement of its volume transport and horizontal
shear, the KE has long been observed to be an eastwardflowing inertial jet accompanied by large-amplitude meanders
and energetic pinched-off eddies (e.g., Mizuno and White 1983;
Yasuda et al. 1992). One salient feature emerging from recent
satellite and eddy-resolving ocean general circulation model
simulations is that the KE exhibits well-defined decadal modulations between a stable and an unstable dynamic state (Qiu
and Chen 2005, 2010; Taguchi et al. 2007; Ceballos et al. 2009;
Sugimoto and Hanawa 2009; Sasaki et al. 2013; Pierini 2014;
Bishop et al. 2015). For example, Fig. 2 shows that the KE
paths were relatively stable in 1993–94, 2002–05, 2010–15, and2018–19, based on merged satellite altimeter observations. In
contrast, spatially convoluted paths prevailed during 1995–
2001, 2006–09, and 2016–17. This decadal modulation of theKE system has persisted after the 1976–77 ‘‘climate shift’’ in
the North Pacific (Qiu et al. 2014) and the basinwide windstress curl variability associated with the Pacific decadal oscillations (PDOs; Mantua et al. 1997), or the North Pacific gyre
oscillations (NPGOs; Di Lorenzo et al. 2008), has been identified as the external forcing that controls the phase change
between the stable/unstable dynamic states.
Given their distinct characteristics, the oceanic circulation
variability in these three segments of the North Pacific winddriven WBC system has largely been explored separately in thepast studies. The objective of our present study is to use theoccurrence of the Kuroshio large meander in late 2017 todemonstrate that the variability in the aforementioned threesegments are dynamically interconnected. To better understand the roles of the KE variability upon the overlying atmosphere, we argue that it is, in fact, critical to clarify theinteractions among the mesoscale eddies from the STCC band,

the Kuroshio path fluctuations south of Japan, and the downstream KE variability in the open Pacific Ocean.
This paper is organized as follows. After describing the observational datasets in section 2, we examine in section 3 theKE dynamic state variability and its influence upon the overlying atmosphere. The negative feedback loop that enhances
the decadal fluctuations in the extratropical ocean–atmospheresystem of the North Pacific is reviewed. In section 4, the bimodal Kuroshio path fluctuations in the Shikoku basin are
examined with a focus on the ongoing Kuroshio LM event thatstarted in August 2017. In section 5, we address how the LMinduced KE dynamic state change affects the oceanic andoverlying atmospheric circulation, and point to the reset of thenegative feedback loop in the extratropical North Pacific ocean–
atmosphere system by the 2017 LM occurrence. Discussion isprovided in section 6 and section 7 summarizes the findings fromthe present study.

2. Observational datasets
To examine the surface oceanic circulation changes, we use
the global sea surface height (SSH) dataset processed by
Ssalto/Duacs and distributed by the Copernicus Marine andEnvironment Monitoring Service (CMEMS) (https://marine.
copernicus.eu/). This dataset merges along-track SSH measurements from all satellite altimeter missions after October
1992 and has a 7-day temporal resolution and a 1/48 spatial
resolution. The data period analyzed in this study extends fromJanuary 1993 to December 2019.
To explore the subsurface circulation changes surrounding
the KE jet, we utilize the conductivity–temperature–depth(CTD) surveys conducted by Japan Meteorological Agency(JMA) southeast of Japan on 28 February–11 March 2017versus 2–12 March 2018. The CTD data have a vertical resolution of 1 dbar in the 2000-m upper ocean and can be accessedfrom https://www.data.jma.go.jp/gmd/kaiyou/db/vessel_obs/datareport/html/ship/ship.php.
To relate the oceanic variability to those at the air–sea interface and in the overlying atmosphere, we adopt the daily
data from the European Centre for Medium–Range Weather
Forecasts (ECMWF) ERA5 reanalysis product (https://cds.
climate.copernicus.eu/). The ECMWF ERA-5 data have aspatial resolution of 0.258 and are available from January 1979
to present. To infer the location/baroclinicity of extratropicalstorm tracks, we follow Hoskins and Valdes (1990) and calculate the maximum Eady growth rate, sBI 5 0.31fN21›U/›z,
in the lower troposphere. Specifically, the vertical zonal wind
shear ›U/›z and the static stability parameter N are evaluatedusing the ERA5 data between 700- and 850-hPa levels. To
quantify the amplitude of extratropical storm-track activities, wefollow Nakamura et al. (2002) and calculate the synoptic-scale(2–8 days) meridional transient eddy temperature fluxes hy0 T0 i
from the hourly 850-hPa level ERA5 data.

3. KE dynamic state and its prediction/verification
There are several metrics to quantify the decadal variabilityof the KE system depicted visually in Fig. 2. Figure 3a, for

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FIG. 1. Root-mean-square sea surface height variability in thewestern North Pacific based on high-pass filtered satellite altimeterdata from January 1992 to February 2020. The high-pass filter has a
half-power at 180 days. Regions where the rms variability exceeds
12 cm are indicated by black contours with an interval of 2 cm.
White contours denote the mean SSH field by Rio et al. (2011).

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example, shows the KE path length integrated from 1418 to1538E. A short (long) path length here corresponds to a stable(unstable) KE dynamic state. Similarly, Figs. 3b and 3c show
the surface eastward transport and latitudinal position of
the KE averaged from 1418 to 1658E, and Fig. 3d shows thestrength of the KE’s southern recirculation gyre based on thesatellite altimeter SSH data of the past 27 years. In its stable
dynamic state, the KE jet tends to have an intensified eastward
transport, a northward latitudinal position, and an enhanced

southern recirculation gyre. The reverse is true when the KE
jet switches to an unstable dynamic state. Given the close
connections among the dynamic properties shown in Fig. 3,
Qiu et al. (2014) combined these four time series (by reversing
the sign of KE path length and averaging the four time series
normalized by their respective standard deviations) and introduced the ‘‘KE index’’ to concisely represent the lowfrequency changes of the KE system. As shown in Fig. 4a, a
positive (negative) KE index is defined to represent a stable

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FIG. 2. Yearly paths of the Kuroshio and KE plotted every 14 days since 1993 based on satellite altimetry observations [for detailed pathderivation, see Qiu and Chen (2005)]. Red (blue) labels denote years in which the KE is largely in a stable (unstable) dynamic state.

10816JOURNAL OF CLIMATE(unstable) KE dynamic state. Statistically, the KE index iscorrelated favorably with the SSH anomaly signals averaged in
the southern recirculation gyre region of 318–368N, 1408–1658E(Fig. 4b). This favorable correlation makes dynamical sense
because a stable KE state is accompanied by an intensified
southern recirculation gyre, hence a positive regional SSH
anomaly.
Like all other extratropical WBCs, the Kuroshio/KE
transport a significant amount of warmer tropical water poleward, providing a source of heat and moisture for the midlatitude atmosphere (Kelly et al. 2010). This source of oceanic
heat/moisture has been demonstrated by many recent studies
to help maintain the lower tropospheric baroclinicity and anchor the extratropical storm tracks (Nakamura et al. 2004;
Minobe et al. 2008; Kwon et al. 2010; Booth et al. 2012; Small
et al. 2014; Masunaga et al. 2016; Ma et al. 2016; Bishop et al.
2017; Parfitt and Seo 2018). Many data analysis studies in thepast decades have examined the impact of the SST changes in
the KE region on the atmospheric circulation across the midlatitude North Pacific basin (Frankignoul and Sennechael 2007;
Qiu et al. 2007, 2017; Frankignoul et al. 2011; Taguchi et al.
2012; Smirnov et al. 2015; Ma et al. 2015; O’Reilly and Czaja
2014; Révelard et al. 2016). A consistent feature resulting fromthese analyses is that when the KE dynamic state is stable,
increased surface turbulent (i.e., sensible 1 latent) heat fluxes

FIG. 4. (a) Time series of the KE index synthesized from the KE
dynamical properties shown in Figs. 3a–d. (b) Time series of SSH
anomalies averaged in the KE southern recirculation region of 318–
368N, 1408–1658E. (c) As in (b), but for the SSH anomalies of 2013–19 (the green line) predicted based on the observed SSH data of
2012. See Qiu et al. (2014) for derivations of the SSH anomaly timeseries and its prediction. (d) Time series of the negative PDO index(available from http://research.jisao.washington.edu/data_sets/pdo).
Anomalies in (b)–(d) are relative to their respective 1989–2019means and thick black lines in (a), (b), and (d) denote the time series
after a low-pass filter that has a half-power at 6 months.

tend to emit from ocean to atmosphere along the polewardshifted KE path (Fig. 5a; defined positive from ocean to atmosphere). This enhanced turbulent heat flux forcing results innorthward migration/amplification of the extratropical storm
tracks as can be inferred from the lower-tropospheric Eadygrowth rate and transient eddy hy0 T0 i distributions shown in
Figs. 5b and 5c. In connection with the meridional migration ofstorm tracks, the Ekman pumping velocity (wEk) field tends tosimilarly shift northward across the North Pacific basin (Fig. 5d).
Notice that the time-mean storm tracks follow roughly thewEk 5 0 line denoted by the thick black contour in Fig. 5. Thisline is tilted southwest–northeast across the North Pacific basin
due to the combined orographic constraint and diabatic oceanic forcing (Wilson et al. 2009). When the storm tracks migrate northward during the KE’s stable state, a negative wEk
anomaly band appears that straddles the time-mean wEk 5 0line (Fig. 5d). South of this band, the wEk anomalies turn
positive because the northward migration of the wind systembrings in weaker, subtropical-origin, negative wEk signals fromthe south. As a consequence, the anomalous wEk in the 318–
368N band of the eastern North Pacific becomes positive. For
the lower atmosphere, this positive wEk anomaly brings aboutenhanced regional rainfall over the eastern North Pacific (Maet al. 2015). For the upper ocean, this leads to regional Ekman
flux divergence and negative SSH anomalies in the eastern
North Pacific Ocean. When these wind-forced negative SSH
signals propagate westward into the KE region with a delay of

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FIG. 3. Time series of (a) upstream KE path length integrated
from 1418 to 1538E, (b) SSH difference across the KE jet averaged
from 1418 to 1658E, (c) latitudinal position of the KE averaged from1418 to 1658E, and (d) intensity of the KE recirculation gyre. Thickblack lines denote the periods when the KE is in an unstable dynamic state. For more details about the time series, see Qiu andChen (2005).

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3–4 years, they work to weaken the southern recirculation gyre,
shifting the KE jet southward to override the shallow Izu
Ridge, and transforming the KE system to an unstable dynamic
state (e.g., Qiu and Chen 2005; Taguchi et al. 2007). Once theKE system switches to its unstable state, the reverse of theatmospheric responses depicted in Fig. 5 takes place and a
dynamic state transition to a stable state occurs following adelayed oceanic adjustment. Although the KE-induced basinscale atmosphere response is weak in comparison with the internal atmospheric fluctuations (typically at 10%–15% level
for the interannual and decadal signals), this ocean-toatmosphere feedback loop provides a negative feedback
mechanism that was argued by many recent studies to explain
the enhanced decadal variability observed in the extratropical North Pacific ocean and atmosphere (Qiu et al. 2014;
Smirnov et al. 2015; Na et al. 2018).

It is relevant to mention that many of the studies cited above
have related the KE’s dynamic state variability to the basinwide wind forcing associated with the PDOs. As shown in
Fig. 4d, there is a good correspondence between the negative
PDO index and the KE index, or the recirculation gyre SSH
signals, with the former leading the latter by 3 years and acorrelation coefficient r 5 0.52. A similar good correspondence
also exists between the KE index and the NPGO index put
forth by Di Lorenzo et al. (2008). Physically, this is not surprising because the KE dynamic state change is caused by the
low-frequency surface wind stress fluctuations in the North
Pacific basin that are encapsulated by leading climate indices,such as the PDO and the NPGO.
The aforementioned negative feedback loop provides not
only a mechanism for explaining the enhanced decadal variability, but also a framework for predicting the KE dynamic state.

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FIG. 5. (a) Regression coefficient between the surface turbulent heat flux anomaly field and the KE index of Jan
1979–Jul 2017 with the former lagging the latter by 2 months. (b) As in (a), but for the maximum Eady growth rateanomaly field at the 700–850-hPa level. (c) As in (a), but for the 2–8-day band-passed meridional transient eddy
temperature flux anomaly field at the 850-hPa level. (d) As in (a), but for the wEk anomaly field. In all figures, thethick black contour denotes the time-mean wEk 5 0 line and stippled areas indicate where the statistical significanceexceeds the 90% confidence level based on Monte Carlo simulations [for detailed methodology, see Qiu et al.
(2007)]. Dashed box in (d) indicates the 318–368N band where the Ekman pumping forcing impacts the KE dynamic state.

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Relying on the slow oceanic baroclinic adjustment that carries
the wind-forced SSH signals into the KE region and the basinscale storm tracks and Ekman pumping field response to thechanging KE dynamic state, we have attempted to forecast the
SSH signals in the KE’s recirculation region or, equivalently,
the KE index for the 2013–22 period based on the observed
SSH field of 2012 [see green line in Fig. 4c; replotted from Fig. 8
in Qiu et al. (2014)]. Compared to the observed SSH time series shown in Fig. 4b, it is interesting to note that the prediction
did a good job in forecasting the positive-to-negative SSH
change of the KE dynamic state in early 2017. The prediction,
however, failed to forecast the abrupt reversal of the SSH
signals to positive (i.e., stabilizing of the KE dynamic state) inlate 2017.

4. The 2017 Kuroshio large meander event
What caused the ‘‘failure’’ of the predicted KE dynamic
state in late 2017 based on the negative feedback loop between the KE and atmosphere storm track interactions? The
answer is the occurrence of the Kuroshio LM that started inAugust 2017 in the upstream Shikoku basin. Figure 6a shows
the monthly time series of the southernmost latitude of theKuroshio south of Japan compiled by Japan Meteorological Agency based on combined 200-m water temperature measurements and satellite observations (https://www.

data.jma.go.jp/gmd/kaiyou/data/shindan/b_2/kuroshio_stream/kuroshio_stream.html). Shaded periods with latitude , 31.88N
denote the LM state of the Kuroshio designated by JMA. As wenoted in introduction, the LM occurrences and durations arehighly irregular. During the satellite altimeter era after 1992,
one LM event took place in mid-2004 and lasted for 14 months.
Following this short-lived event and a dormant period of 12
years, an intense and more persistent LM event initiated inAugust 2017 (Qiu 2019; Sugimoto et al. 2020) and the event isstill ongoing at the writing of this article.
Due to the lack of persistent LM occurrence in the past three
decades, the KE dynamic state, as shown in Fig. 4, has been
dominated by the decadal variability whose time scale is dictated by the negative feedback loop between the KE andoverlying atmospheric storm track interactions. Indeed, thiswind-forced KE variability was operative in the beginning of2017 when the KE switched from a stable dynamic state to anegative one following the PDO phase change in early 2014
(Fig. 4d). After its dynamic state entered the unstable phase,
Fig. 6b reveals that the Kuroshio path along 1408E shifted
southward over the shoaling Izu Ridge, resulting in fluctuating
KE paths southeast of Japan (Qiu and Chen 2005, their section 5). Subsequent to the LM occurrence in August 2017,
however, the offshore detouring Kuroshio becomes confined to
the west of the Izu Ridge and its outflow is restricted to enter
the open Pacific through a narrow but deep (depth . 1100 m)

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FIG. 6. (a) Time series of the monthly southernmost latitude of the Kuroshio south of Japan compiled by theJapan Meteorological Agency. Solid thick line shows the low-pass filtered time series after a 13-month runningmean average. Shaded periods with latitude , 31.88N denote the large meander state of the Kuroshio. (b) Weekly
Kuroshio/KE paths off Japan during January–July 2017. Black dots denote CTD stations by JMA cruise KS1702.
(c) As in (b), but during September 2017–March 2018 and JMA cruise RF1802. Green (gray) shade denotes areas
shallower than 500 (1500) m.

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channel between the mainland Japan and offshore Izu Ridge(see Fig. 6c; Kawabe 1985). Forced by these changes in the
upstream Kuroshio, the KE jet in the 1408–1538E segment
becomes stabilized, leading to the reversal of the KE index in
2018–19 as indicated in Figs. 4a and 4b.
Given the capability of the Kuroshio path south of Japan inreversing the KE dynamic state, a question arising naturally iswhat led to the occurrence of the 2017 LM event. To address
this question, it is instructive to examine the evolution of the
SSH anomaly field prior to the occurrence of the LM event. As
depicted in Fig. 7, the LM is well developed by September 2017and its presence corresponds geostrophically to the negative
SSH anomaly (indicated by dashed line in the figure) located tothe south of Japan. Tracing it backward in time, it is discernible
that this negative SSH anomaly initiated in the upstream
Kuroshio southeast of Kyushu during April–May 2017 and it
can be further traced back to around 1458–1508E in the 288–
308N band as a sequence of cyclonic mesoscale eddies in
October 2016. These cyclonic eddies propagated westward at a
speed of 0.11 m s21 during November 2016–March 2017 andconsolidated into a single negative SSH anomaly off Kyushu in
April 2017.
The negative SSH anomaly appearing in the upstream
Kuroshio southeast of Kyushu in April–May 2017 is known as
the ‘‘trigger’’ meander in existing literature and its importanceas a precursor to the LM occurrence has been recognized in

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FIG. 7. Monthly maps of SSH anomalies from October 2016 to September 2017 in the western North Pacific Ocean. To avoid large-scalesteric height changes due to seasonal heating/cooling, the area mean SSH anomaly value of each month is removed. Dashed lines denotethe evolution of the trigger meander that appeared southeast of Kyushu in April 2017 and solid lines, the positive SSH anomalies that
replaced the trigger meander off Kyushu in August 2017. The green box in the first (last) panel denotes the area used to construct the SSH
anomaly time series shown in Figs. 8b and 8a.

10820JOURNAL OF CLIMATEVOLUME 33

many previous studies (e.g., Solomon 1978; Mitsudera et al.
2001; Ebuchi and Hanawa 2003; Miyazawa et al. 2004; Usuiet al. 2008). In Fig. 8a, we plot the time series of the negative
SSH anomalies averaged southeast of Kyushu within a 48 widthfrom 298 to 328N (the green box in last panel of Fig. 7) based on
the altimeter SSH data. The negative SSH anomaly triggering the2017 LM event corresponds to that appearing in early 2017. From
this time series negative SSH anomalies, or trigger meanders, haveappeared quite frequently off Kyushu during the past three decades. While a necessary condition, the trigger meander is clearly
not a sufficient condition that will lead to a LM occurrence.
A careful inspection of the sequential SSH anomaly maps ofFig. 7 reveals another factor that has contributed to the 2017

LM event. Following the trigger meander in May 2017, Fig. 7
reveals that the area off Kyushu is replaced by an intense
positive SSH anomaly in July and August. This positive SSH
anomaly appears to have two sources: one originated from the
STCC band of 248–278N in October 2016 and moved subsequently northward to the east of the Ryukyu Islands, and theother started around 1538E in the 278–308N band in October
2016 and moved westward to merge with the STCC-originatedanomaly off Kyushu in August 2017 (see the solid lines inFig. 7). An important role played by this intense positive SSH
anomaly is that it is able to thrust the preceding negative SSH
anomaly, or the trigger meander, eastward, leading it to develop into a LM south of Japan.

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FIG. 8. (a) Time series of SSH anomalies averaged at southeast of Kyushu within a 48 widthfrom 298 to 328N. Only negative anomalies denoting the Kuroshio trigger meanders areshown. (b) Time series of SSH anomalies averaged in the 48 band east of the Ryukyu Islands
from 248 to 298N. (c) Product of the SSH anomalies shown in (a) and (b) with a lag of 4months. Only negative anomalies denoting trigger meanders followed by positive SSH
anomalies east the Ryukyu Islands are shown. The black line denotes the Kuroshio’s
southernmost latitude south of Japan.

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5. Impact on oceanic and atmospheric conditions
In the preceding section, we have quantified the impact ofthe 2017 LM event on the KE dynamic state based on
altimeter-measured SSH information. To assess further the KEchange below the sea surface, we examine the in situ CTD datacollected by JMA in the upstream KE region before and after
the 2017 LM occurrence. Figure 9 compares the temperature, salinity, and cross-track geostrophic velocity profiles from the JMA’s
KS1702 cruise of March 2017 versus those from the RF1802 cruiseof March 2018 (see Figs. 6b,c for locations of the CTD stations).
From the T/S profiles, it is discernible that the KE front withthe sharp T/S gradients in the 1000-m upper ocean shifted from33.58N in March 2017 to 34.58N in March 2018. Accompaniedby this northward shift is an increase in the KE’s transport andintensity: the maximum eastward geostrophic velocity andtransport of the KE jet referenced to 2000 dbar were 0.70 m s21
and 70.2 Sv, respectively, from the 2017 cruise (Fig. 9c) andthese values increased to 0.88 m s21 and 76.3 Sv during the 2018
cruise (Fig. 9f).
Another noticeable difference between the two cruises isthat the condition surrounding the KE jet was more variable in2017 than in 2018. For example, Fig. 9a indicates the presenceof an intense cold-core eddy centered around 30.58N in 2017.
This cold-core eddy has a geostrophic transport of 50 Sv, close
to 70% of the KE’s eastward transport value. Next to the coast ofJapan, there appears a shallow branch of warmer/saltier subtropicalorigin water in Figs. 9a and 9b. A look at the sequential SSH maps
(not shown) indicates that it was a remnant of the KE jet before its
main body shifted southward in early 2017. Accompanying thissouthward shift of the KE jet, a fresh, subarctic-origin watermass with salinity , 34.0 psu is seen to intrude to the north of the
KE jet near 348N (Fig. 9b). In contrast to the 2017 result, oceanic
condition surrounding the KE jet was devoid of mesoscale
perturbations in 2018. The above results from the subsurface
CTD measurements regarding the LM-induced changes in the
KE’s position, intensity, and surrounding conditions, are allconsistent with those of the preceding sections based on the altimeter SSH measurements.
To evaluate if the 2017 LM-induced KE change exerted asimilar impact upon the overlying atmosphere as that of thewind-forced dynamic state change in the past three decades, weplot in Fig. 10a the surface turbulent heat flux anomaly fieldaveraged in the two years of September 2017–August 2019
after the 2017 LM occurrence (this 2-yr window is selected
because it is sufficiently long and contains two full seasonal
cycles after the 2017 LM that are currently available to us). In
conjunction with the northward shift and intensification of the
KE jet, the surface turbulent heat fluxes exhibit positive
anomalies (i.e., more heat supply from ocean to atmosphere) inthe broad region east of Japan. This surface turbulent heat flux
anomaly pattern is similar to that in Fig. 5a, showing the surface turbulent heat flux anomalies regressed to the KE index inJanuary 1979–July 2017 before the 2017 LM. In Figs. 10b and10c, we plot the storm track anomalies inferred from the lower
tropospheric Eady growth rate and 850-hPa synoptic-scaletransient eddy hy 0 T0 i anomalies, in the two years after the2017 LM occurrence. Consistent with the turbulent heat flux
anomaly pattern shown in Fig. 10a, there exist an enhancement
and a northward migration of the storm track activities in the
recent two years. A comparison with Figs. 5b and 5c indicatesthat a very similar storm track response to the KE change was
detected in the 1979–2017 period prior to the 2017 LM event.

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To examine if such positive SSH anomalies have succeeded
other trigger meanders that appeared off Kyushu in the past,
we construct in Fig. 8b the time series of the SSH anomalies
averaged in the 48-width band east of the Ryukyu Islands from
248 to 298N (the green box in first panel of Fig. 7). As shown in
Fig. 1, this band has an elevated SSH variance that connects the
eddy-rich STCC to the Kuroshio southeast of Kyushu. The
eddy variability in this band has positive and negative SSH
anomalies with a time scale of typical oceanic mesoscales. To
identify the events where a trigger meander southeast of Kyushu
is followed by a positive SSH anomaly from east of the Ryukyu
Islands, we multiply the SSH anomalies shown Fig. 8a to those of
Fig. 8b with a lag of 4 months. Thus constructed, a negative
product indicates an event in which a pre-existing trigger meander
off Kyushu is succeeded by a positive SSH anomaly, with themagnitude of the product indicating their combined intensities.
Figure 8c shows the time series of the above-mentioned negative
product. Large negative products are now infrequent, and they
appeared in late 1998, late 2002, late 2003–early 2004, late 2006,
late 2007, and early 2017, respectively. When compared to thetime series of the Kuroshio’s southernmost latitude south of Japan(black curve in Fig. 8c), it is of interest to note that the large
negative products of late 2002 and late 2003–early 2004 precededthe 2004–05 LM event, and the early 2017 large negative productpreceded the 2017–present LM event. Although not categorized
by JMA as LM events, the late 1998 large negative product preceded the offshore meandering of the Kuroshio in 1999–2000, andthe large negative products of late 2006 and late 2007 preceded theoffshore meandering of the Kuroshio in 2008–09.
We have from the above analyses identified the combined
emergence of trigger meander and subsequent positive SSH
anomalies southeast of Kyushu as a prerequisite for the LM
development south of Japan. It is worth emphasizing that theimportance of anticyclonic perturbations in facilitating trigger
meanders off Kyushu to develop into a LM has been emphasized by a number of previous studies (Akitomo and Kurogi
2001; Kobashi and Hanawa 2004; Miyazawa et al. 2008; Usuiet al. 2013; Tsujino et al. 2013). The origins of the anticyclonicperturbations proposed by these studies are, however, different from those identified in our analyses. All these previous
studies have considered the anticyclonic perturbations of positive
SSH anomalies to originate along the STCC band and be carriednorthward by the Kuroshio along the steep continental slope in the
East China Sea. In light of the SSH anomaly maps shown in Fig. 7,
we contend that the anticyclonic/positive SSH anomalies from the
STCC band have more capacity and a direct route east of the
Ryukyu Islands, rather than by deforming the slope-constrained
Kuroshio in the East China Sea, to affect the trigger meander thatdevelops off Kyushu. This contention of ours is also supported by
the satellite altimeter data (Fig. 1) revealing that an elevated SSH
anomaly band exists to the east of the Ryukyu Islands that connects
the eddy-rich STCC to the time-varying Kuroshio south of Japan.

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Given the good agreement between the surface turbulent heat
flux and storm track activity anomalies, it is of no surprise to findthat a favorable correspondence also exists between the KEinduced wEk anomalies before and after the 2017 LM occurrence(cf. Figs. 10d and 5d). In short, the above comparisons indicatethat the LM-induced KE variability after 2017 has exerted an
impact upon the overlying atmospheric circulation similar tothat by the wind-forced KE variability of the past three decades.

6. Discussion
Although the focus of our present study is on the recent
interruption of the wind-forced decadal KE variability by the2017 LM event, it is helpful to relate the KE dynamic state, theKuroshio LM, and the basin-scale atmospheric variability
from a longer time scale perspectives.

a. Oceanic reach of the decadal KE variability
In section 3, we combined four properties of the KE anddefined the KE index to concisely describe the variations of theKE dynamic state. Although all these four properties are basedon characteristics of the observed KE jet/recirculation gyrewest of 1658E, it does not imply that the oceanic influence ofthe decadal KE variability is confined regionally to the west of
1658E. Figure 11a shows the altimeter-measured SSH anomaly
distribution regressed to the KE index during the 1993–2019
period. With the anomalous SSH signals being a good proxy forthe upper heat content anomalies (Kelly et al. 2010), it is clear
from Fig. 11a that the positive heat content anomalies during
the stable state of KE extend both eastward beyond 1658E
and northeastward into the Oyashio Extension and subarctic
frontal regions. This is so because as the KE flows eastward, it
sheds mesoscale eddies and broadens its entity via northwardbifurcations (Kida et al. 2015). In fact, our recent study reveals
that the decadal Oyashio Extension variability along ;408N
and 1538–1738E is by and large dictated by the KE variability
through northward shed eddies and bifurcated branches (Qiu
et al. 2017; their Fig. 3). It is of interest to note that the spatial
pattern of the turbulent heat flux anomalies regressed to the
KE index (Fig. 5a) bears a close resemblance to that of Fig. 11a,

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FIG. 9. Cross section profiles of (a) temperature, (b) salinity, and (c) geostrophic flows (referenced to 2000 dbar) from the JMA cruise
KS1702 of 28 Feb–11 Mar 2017. (d)–(f) As in (a)–(c), but from the JMA cruise RF1802 of 2–12 Mar 2018.

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lending credence to the idea that it is the KE-originated variability that is responsible for the diabatic heating anomalies
presented in Fig. 5a.

b. Kuroshio LM and the PDO forcing
That the Kuroshio LM paths are able to steer the low-level
cyclone tracks away from the southern coast of Japan has beenpreviously observed by Nakamura et al. (2012). To clarify if theKuroshio LMs affect the atmospheric circulation across thebroader Pacific basin, we define the Kuroshio path index asanomalies of the Kuroshio southernmost latitude away fromthe coast of Japan (Fig. 12a). Thus defined, a positive anomaly
indicates a LM state of the Kuroshio south of Japan. Figure 11b
shows the turbulent heat flux anomalies regressed to the
Kuroshio path index with a 2-month lag during the 1979–2019
period. Consistent with the findings by Nakamura et al. (2012),
the diabatic heating effects of the LM events are confined to
the regions surrounding Japan and there appears to be no

systematic influence on the extratropical storm tracks acrossthe North Pacific basin (figures not shown). This result indicates that although a LM event can alter the extratropicalstorm tracks by modifying the KE dynamic state as we found insection 5, changes by the Kuroshio paths alone may not be
sufficient to induce the storm track variability across the North
Pacific basin.
We have emphasized in section 4 the roles played by mesoscale eddies along the 188–258N STCC band for the LM development. Previous studies have shown that the eddy activity
level in the STCC band is modulated by the PDO-related wind
forcing (Yoshida et al. 2011; Qiu and Chen 2013). Specifically,
when the PDO is in positive phase, enhanced westerlies andtrade winds over the western North Pacific generate a greater
Ekman temperature flux convergence along the STCC band,
causing a stronger upper ocean meridional temperature gradient and strengthening the vertically sheared STCC/NEC
system. This enhanced current shear results in a stronger

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FIG. 10. Distributions of anomalous (a) surface turbulent heat flux, (b) maximum Eady growth rate at the 700–
850-hPa level, (c) 2–8-day band-passed meridional transient eddy temperature heat flux at the 850-hPa level, and(d) Ekman pumping velocity fields averaged in the recent Kuroshio large meander period of September 2017–
August 2019. With the mean SSH anomalies during this period equal to 0.05 m (see Fig. 4b), the color scale for eachquantity can be converted to that shown in Fig. 5 by multiplying by 20. For example, a 10 W m22 anomaly in(a) corresponds to a 200 W m22 m21 regression anomaly depicted in Fig. 5a.

10824JOURNAL OF CLIMATE

baroclinic instability and elevates the level of regional eddy
activities. A comparison between the Kuroshio path index and
the PDO time series in Figs. 12a and 12b reveals that with the
exception of the 1975 LM event, all other Kuroshio LM eventswere preceded by positive PDO phases. A lagged correlation
analysis reveals that the Kuroshio path anomalies have amaximum correlation, r 5 0.27, with the PDO index at a 32month lag. Although not a high coefficient, this positive correlation is consistent with the notion that a positively phased
PDO forcing is able to enhance the mesoscale eddy activities in
the STCC band, conducive for the formation of the Kuroshio
LMs. The 32-month lag likely reflects the time required for 1)
the baroclinic instability along the STCC to fully grow, 2) the
instability-generated eddies to propagate westward across the
STCC and poleward along the Ryukyu Island, and 3) the development from a trigger meander off Kyushu to the LM southof Japan.

c. Imprint on PDO versus PMM by the KE variability
Throughout this study, we have emphasized the negative
feedback mechanism that involves the KE dynamic state, themeridional migration of extratropical storm tracks/gyre-scale

Ekman pumping field, and the excitation of upper ocean baroclinic Rossby waves whose westward propagation alters thepre-existing KE dynamic state. Instead of invoking the storm
track migration, Joh and Di Lorenzo (2019) have found recently that the decadally varying KE can induce an eastern
Pacific wind stress curl response that projects on atmosphericforcing of the Pacific meridional mode (PMM; Chiang andVimont 2004). Specifically, when it is in a stable state, the KEinduced positive wEk anomaly shown in Fig. 5d in the 258–358N
band of the eastern North Pacific projects to the positive
PMM forcing pattern (Fig. 13a). This PMM forcing can activate the central tropical Pacific El Niño–Southern Oscillation(CP-ENSO), which in turn can strengthen a positive PDO (ornegative NPGO) forcing, generating the negative SSH anomalies in the eastern North Pacific and altering the KE to an
unstable state after these wind-forced SSH anomalies reach the
KE region.
It is important to note that both our study and that of Joh and
Di Lorenzo (2019) advocate the negative feedback mechanismthat favors the decadal climate variability involving the KE
system. The difference lies in whether the KE-induced positivewEk anomalies in the eastern North Pacific are a response
confined to the midlatitude atmosphere via migration of storm
tracks, or a response involving the tropical PMM/CP-ENSO
variability. Figure 13b shows the spatial pattern of the wEk
anomaly regressed to the PDO index. Similar to the PMMregressed pattern shown in Fig. 13a, the PDO-regressed pattern shows a positive wEk anomaly in the eastern North Pacificthat coincides with the positive wEk anomaly identified inFig. 5d. In other words, like their projection on PMM, the KEinduced wEk anomalies project similarly on the PDO wind
forcing pattern. The reason behind this similarity is because the
PDO and PMM indices, as shown in Figs. 12b and 12c, sharesimilar time-varying signals especially on the decadal timescale of our interest (see also Stuecker 2018). Given these results, we believe it will be challenging to differentiate the negative feedback mechanism described in this study and that
proposed by Joh and Di Lorenzo (2019) from the statisticalanalyses alone. It will be crucial for future studies to clarify theatmospheric responses to the KE variability based on processoriented, coupled ocean–atmosphere general circulation model
simulations.

7. Summary
Low-frequency Kuroshio Extension variability is composedof concurrent changes in its latitudinal position, eastward
transport, eddy kinetic energy level, and southern recirculation
gyre strength. In its stable dynamic state, the KE has a northward position, an increased transport, a reduced eddy kinetic
energy level, and an intensified recirculation gyre, and the
opposite is true during its unstable dynamic state. In the past
three decades, the KE has been observed to oscillate between
these two dynamic states with a well-defined 10-yr period. The
dominance of this decadal oscillation is caused by the delayed
negative feedback mechanism, in which the KE variability isdriven by the basin-scale wind forcing with its center over theeastern North Pacific and the forced KE, in turn, modifies the

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FIG. 11. (a) Regression map between the KE index and the North
Pacific SSH anomaly field in 1993–2019. The dashed box denotes
the region where the SSH anomalies are used to define the KE
index shown in Fig. 4b. (b) Regression coefficient between thesurface turbulent heat flux anomaly field and the Kuroshio pathindex of Fig. 12a with the former lagging the latter by 2 months.
Thick black contour denotes the time-mean wEk 5 0 line.

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overlying storm tracks and the large-scale wind pattern
through anomalous turbulent heat fluxes from the ocean toatmosphere.
The long-term, wind-forced KE variability was disrupted inAugust 2017 due to the occurrence of the Kuroshio large meander south of Japan. Instead of remaining in the unstable
dynamic state that started in early 2017 in response to the 2014
phase change of the PDO wind forcing, the KE transitioned
abruptly to a stable state in late 2017. The occurrence of LM isfound from satellite altimeter measurements and available
in situ hydrographic surveys to impact the KE in two importantways. First, it forced the Kuroshio to enter the open North
Pacific through a northerly deep channel close to Japan,
causing the downstream KE path to shift northward. Second,by entering through the northerly deep channel, the Kuroshio
avoided overriding the shoaling Izu Ridge and minimized theKE path fluctuations in the east of the Izu Ridge. Both of theseeffects worked to stabilize the KE dynamic state following the2017 LM occurrence.
Over the past three decades when the wind-forced KE variability prevails, the Kuroshio LM occurrence has been rare.
The LM event preceding 2017 took place from July 2004 to
August 2005 and this LM event exerted little impact upon thewind-forced KE variability because it occurred when the KE
was already in a stable dynamic state. In agreement with theprevious studies, we found that the LM occurrences in 2004–05
and 2017–present were preceded by trigger meanders (represented by negative SSH anomalies) in the upstream Kuroshio

southeast of Kyushu. For trigger meanders off Kyushu to develop fully into a LM state, we found it is necessary that they besucceeded by intense anticyclonic, or positive, SSH anomalies
that work to thrust the trigger meander eastward and stationary south of Japan. Most of these anticyclonic/positive SSH
anomalies have their origins in the STCC band of 188–258N
and, rather than being advected by the Kuroshio through theEast China Sea, they are observed to propagate northward to
the east along the Ryukyu Islands.
The LM-induced KE dynamic state change after late 2017 isfound to affect the overlying storm tracks and the large-scalewind pattern the same way as those generated by the windforced KE change prior to the 2017 LM occurrence. Thisconsistent atmospheric response implies that although disrupted temporally, the negative feedback loop and the decadally modulating KE variability will likely resume once thecurrent LM event terminates. It will be interesting to find out
how long the current LM event will last and how the KE dynamic state will respond in the coming years to the LMinduced positive Ekman pumping anomalies in the 328–368N
band over the eastern North Pacific Ocean.
Acknowledgments. This study was conducted while EO and
SS were on their sabbatical visit to the University of Hawaii.
Constructive comments made by four anonymous reviewers havesignificantly improved an early version of the manuscript. The
ECMWF ERA-5 reanalysis data used in this study were accessedfrom https://cds.climate.copernicus.eu/, the JMA hydrographic

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FIG. 12. (a) Time series of Kuroshio path anomalies measured from the southern coast ofJapan. (b) Time series of the PDO index provided by http://research.jisao.washington.edu/
data_sets/pdo. (c) Time series of the PMM index provided by http://www.aos.wisc.edu/;
dvimont/MModes/Data.html. In all figures, thick black lines denote the time series after alow-pass filter that has a half-power at 6 months.

10826JOURNAL OF CLIMATE

cruise data and analysis information from http://www.jma.go.jp/
jma/indexe.html, and the merged satellite altimeter data from
Ssalto/Duacs and the Copernicus Marine and Environment
Monitoring Service (https://marine.copernicus.eu/). We acknowledge the support of NSF Grant 2019312 and NASA Grant
NNX17AH33G to BQ and SC, MEXT Grant 19H05700 and
JSPS Grant 17K05652 to EO, and MEXT Grant 19H05704 andJSPS Grant 18K03737 to SS. This is SOEST Contribution
Number 11158 and IPRC Contribution Number 1479.
REFERENCES
Akitomo, K., and M. Kurogi, 2001: Path transition of the Kuroshio
due to mesoscale eddies: A two-layer, wind-driven experiment. J. Oceanogr., 57, 735–741, https://doi.org/10.1023/A:
1021292627245.
Andres, M., J. H. Park, M. Wimbush, X. H. Zhu, K. I. Chang, andH. Ichikawa, 2008: Study of the Kuroshio/Ryukyu Current system
based on satellite-altimeter and in situ measurements. J. Oceanogr.,64, 937–950, https://doi.org/10.1007/s10872-008-0077-2.
Bishop, S. P., F. O. Bryan, and R. J. Small, 2015: Bjerknes-likecompensation in the wintertime North Pacific. J. Phys.
Oceanogr., 45, 1339–1355, https://doi.org/10.1175/JPO-D-140157.1.
——, R. J. Small, F. O. Bryan, and R. A. Tomas, 2017: Scale dependence of midlatitude air–sea interaction. J. Climate, 30,
8207–8221, https://doi.org/10.1175/JCLI-D-17-0159.1.

Booth, J. F., L. Thompson, J. Patoux, and K. A. Kelly, 2012:
Sensitivity of midlatitude storm intensification to perturbations in the sea surface temperature near the Gulf Stream.
Mon. Wea. Rev., 140, 1241–1256, https://doi.org/10.1175/
MWR-D-11-00195.1.
Ceballos, L. I., E. Di Lorenzo, C. D. Hoyos, N. Schneider, and
B. Taguchi, 2009: North Pacific Gyre Oscillation synchronizes climate fluctuations in the eastern and westernboundary systems. J. Climate, 22, 5163–5174, https://doi.org/
10.1175/2009JCLI2848.1.
Cheng, Y.-H., C.-R. Ho, Q. Zheng, B. Qiu, J. Hu, and N.-J. Kuo,
2017: Statistical features of eddies approaching the Kuroshio
east of Taiwan Island and Luzon Island. J. Oceanogr., 73, 427–
438, https://doi.org/10.1007/s10872-017-0411-7.
Chiang, J. C. H., and D. J. Vimont, 2004: Analogous Pacific andAtlantic meridional modes of tropical atmosphere–ocean
variability. J. Climate, 17, 4143–4158, https://doi.org/10.1175/
JCLI4953.1.
Di Lorenzo, E., and Coauthors, 2008: North Pacific Gyre Oscillation
links ocean climate and ecosystem change. Geophys. Res. Lett.,
35, L08607, https://doi.org/10.1029/2007GL032838.
Ebuchi, N., and K. Hanawa, 2003: Influence of mesoscale eddies onvariations of the Kuroshio paths south of Japan. J. Oceanogr.,59, 25–36, https://doi.org/10.1023/A:1022856122033.
Frankignoul, C., and N. Sennechael, 2007: Observed influence ofNorth Pacific SST anomalies on the atmospheric circulation.
J. Climate, 20, 592–606, https://doi.org/10.1175/JCLI4021.1.
——, ——, Y.-O. Kwon, and M. A. Alexander, 2011: Influence ofthe meridional shifts of the Kuroshio and the Oyashio
Extensions on the atmospheric circulation. J. Climate, 24, 762–
777, https://doi.org/10.1175/2010JCLI3731.1.
Gilson, J., and D. Roemmich, 2002: Mean and temporal variability
in Kuroshio geostrophic transport south of Taiwan (1993–
2001). J. Oceanogr., 58, 183–195, https://doi.org/10.1023/A:
1015841120927.
Hoskins, B. J., and P. J. Valdes, 1990: On the existence of stormtracks. J. Atmos. Sci., 47, 1854–1864, https://doi.org/10.1175/
1520-0469(1990)047,1854:OTEOST.2.0.CO;2.
Ichikawa, H., H. Nakamura, A. Nishina, and M. Higashi, 2004:
Variability of northeastward current southeast of northern
Ryukyu Islands. J. Oceanogr., 60, 351–363, https://doi.org/
10.1023/B:JOCE.0000038341.27622.73.
Imawaki, S., A. S. Bower, L. Beal, and B. Qiu, 2013: Westernboundary currents. Ocean Circulation and Climate—A 21stCentury Perspective, 2nd ed. G. Siedler et al., Eds., Academic
Press, 305–338.
Jayne, S., and Coauthors, 2009: The Kuroshio Extension and its
recirculation gyres. Deep-Sea Res. I, 56, 2088–2099, https://doi.org/10.1016/j.dsr.2009.08.006.
Joh, Y., and E. Di Lorenzo, 2019: Interactions between Kuroshio
Extension and central tropical Pacific lead to preferred decadal timescale oscillations in Pacific climate. Sci. Rep., 9,13558, https://doi.org/10.1038/s41598-019-49927-y.
Kawabe, M., 1985: Sea level variations at the Izu Islands and typicalstable paths of the Kuroshio. J. Oceanogr. Soc. Japan, 41, 307–
326, https://doi.org/10.1007/BF02109238.
——, 1995: Variations of current path, velocity, and volumetransport of the Kuroshio in relation with the large meander.
J. Phys. Oceanogr., 25, 3103–3117, https://doi.org/10.1175/
1520-0485(1995)025,3103:VOCPVA.2.0.CO;2.
Kelly, K. A., R. J. Small, R. M. Samelson, B. Qiu, T. M. Joyce,
Y.-O. Kwon, and M. F. Cronin, 2010: Western boundary
currents and frontal air–sea interaction: Gulf Stream and

Downloaded from http://journals.ametsoc.org/jcli/article-pdf/33/24/10813/5019114/jclid200237.pdf by University of Hawaii at Manoa, Library user on 30 November 2020

FIG. 13. Distributions of the wEk anomalies regressed to (a) the
PMM index of Fig. 12c and (b) the PDO index of Fig. 12b for theperiod of January 1979–July 2017. The thick black contour in both
figures denotes the time-mean wEk 5 0 line.

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track activity and East Asian winter monsoon. J. Climate, 15,
1855–1874, https://doi.org/10.1175/1520-0442(2002)015,1855:
IADMRO.2.0.CO;2.
——, T. Sampe, Y. Tanimoto, and A. Shimpo, 2004: Observed associations among storm tracks, jet streams and midlatitude oceanic
fronts. Earth’s Climate: The Ocean–Atmosphere Interaction,
Geophys. Monogr., Vol. 147, Amer. Geophys. Union, 329–346.
——, A. Nishina, and S. Minobe, 2012: Response of storm tracks tobimodal Kuroshio path states south of Japan. J. Climate, 25,
7772–7779, https://doi.org/10.1175/JCLI-D-12-00326.1.
O’Reilly, C. H., and A. Czaja, 2014: The response of the Pacific storm
track and atmospheric circulation to Kuroshio Extension variability. Quart. J. Roy. Meteor. Soc., 141, 52–66, https://doi.org/
10.1002/qj.2334.
Parfitt, R., and H. Seo, 2018: A new framework for near-surface windconvergence over the Kuroshio Extension and Gulf Stream in
wintertime: The role of atmospheric fronts. Geophys. Res. Lett.,
45, 9909–9918, https://doi.org/10.1029/2018GL080135.
Pierini, S., 2014: Kuroshio Extension bimodality and the North
Pacific oscillation: A case of intrinsic variability paced by external forcing. J. Climate, 27, 448–454, https://doi.org/10.1175/
JCLI-D-13-00306.1.
Qiu, B., 1999: Seasonal eddy field modulation of the North Pacific
Subtropical Countercurrent: TOPEX/POSEIDON observations
and theory. J. Phys. Oceanogr., 29, 2471–2486, https://doi.org/
10.1175/1520-0485(1999)029,2471:SEFMOT.2.0.CO;2.
——, 2019: Kuroshio and Oyashio currents. Encyclopedia of Ocean
Sciences, 3rd ed. J. K. Cochran, H. Bokuniewicz, and P. Yager,
Eds., Academic Press, 384–394.
——, and W. Miao, 2000: Kuroshio path variations south of Japan:
Bimodality as a self-sustained internal oscillation. J. Phys.
Oceanogr., 30, 2124–2137, https://doi.org/10.1175/1520-0485(2000)
030,2124:KPVSOJ.2.0.CO;2.
——, and S. Chen, 2005: Variability of the Kuroshio Extension jet,recirculation gyre, and mesoscale eddies on decadal timescales. J. Phys. Oceanogr., 35, 2090–2103, https://doi.org/
10.1175/JPO2807.1.
——, and ——, 2010: Eddy–mean flow interaction in the decadallymodulating Kuroshio Extension system. Deep-Sea Res. II, 57,
1098–1110, https://doi.org/10.1016/j.dsr2.2008.11.036.
——, and ——, 2013: Concurrent decadal mesoscale eddy modulationsin the western North Pacific subtropical gyre. J. Phys. Oceanogr.,
43, 344–358, https://doi.org/10.1175/JPO-D-12-0133.1.
——, N. Schneider, and S. Chen, 2007: Coupled decadal variability
in the North Pacific: An observationally constrained idealized
model. J. Climate, 20, 3602–3620, https://doi.org/10.1175/
JCLI4190.1.
——, S. Chen, P. Hacker, N. Hogg, S. Jayne, and H. Sasaki, 2008: The
Kuroshio Extension northern recirculation gyre: Profiling float
measurements and forcing mechanism. J. Phys. Oceanogr., 38,
1764–1779, https://doi.org/10.1175/2008JPO3921.1.
——, ——, N. Schneider, and B. Taguchi, 2014: A coupled decadal
prediction of the dynamic state of the Kuroshio Extension
system. J. Climate, 27, 1751–1764, https://doi.org/10.1175/
JCLI-D-13-00318.1.
——, ——, and ——, 2017: Dynamical links between the decadal
variability of the Oyashio and Kuroshio Extensions. J. Climate,30, 9591–9605, https://doi.org/10.1175/JCLI-D-17-0397.1.
Révelard, A., C. Frankignoul, N. Sennechael, Y.-O. Kwon, andB. Qiu, 2016: Influence of the decadal variability of theKuroshio Extension on the atmospheric circulation in the coldseason. J. Climate, 29, 2123–2144, https://doi.org/10.1175/
JCLI-D-15-0511.1.

Downloaded from http://journals.ametsoc.org/jcli/article-pdf/33/24/10813/5019114/jclid200237.pdf by University of Hawaii at Manoa, Library user on 30 November 2020

Kuroshio Extension. J. Climate, 23, 5644–5667, https://doi.org/
10.1175/2010JCLI3346.1.
Kida, S., and Coauthors, 2015: Oceanic fronts and jets around
Japan: A review. J. Oceanogr., 71, 469–497, https://doi.org/
10.1007/s10872-015-0283-7.
Kobashi, F., and H. Kawamura, 2002: Seasonal variation and instability nature of the North Pacific Subtropical Countercurrent
and the Hawaiian Lee Countercurrent. J. Geophys. Res., 107,3185, https://doi.org/10.1029/2001JC001225.
——, and K. Hanawa, 2004: Hydrographic features off the southeast coast of Kyushu during the Kuroshio small meanders: A
case study for small meanders that occurred in 1994 and 1995.
J. Oceanogr., 60, 645–661, https://doi.org/10.1007/s10872-0045758-x.
Kwon, Y.-O., M. A. Alenxader, N. A. Bond, C. Frankignoul,
H. Nakamura, B. Qiu, and L. Thompson, 2010: Role of the
Gulf Stream and Kuroshio–Oyashio systems in large-scaleatmosphere–ocean interaction: A review. J. Climate, 23, 3249–
3281, https://doi.org/10.1175/2010JCLI3343.1.
Lien, R.-C., B. Ma, Y.-H. Cheng, C.-R. Ho, B. Qiu, C. M. Lee, and
M.-H. Chang, 2014: Modulation of Kuroshio transport by mesoscale eddies at the Luzon Strait entrance. J. Geophys. Res.
Oceans, 119, 2129–2142, https://doi.org/10.1002/2013JC009548.
Ma, J., and Coauthors, 2016: Western boundary currents regulated
by interaction between ocean eddies and the atmosphere.
Nature, 535, 533–537, https://doi.org/10.1038/nature18640.
Ma, X., and Coauthors, 2015: Distant influence of Kuroshio eddies
on North Pacific weather patterns. Sci. Rep., 5, 17785, https://doi.org/10.1038/srep17785.
Mantua, N. J., S. R. Hare, Y. Zhang, J. M. Wallace, and R. C.
Francis, 1997: A Pacific interdecadal climate oscillation with
impacts on salmon production. Bull. Amer. Meteor. Soc., 78,
1069–1079, https://doi.org/10.1175/1520-0477(1997)078,1069:
APICOW.2.0.CO;2.
Masunaga, R., H. Nakamura, T. Miyasaka, K. Nishii, and B. Qiu,
2016: Interannual modulations of oceanic imprints on thewintertime atmospheric boundary layer under the changing
dynamical regimes of the Kuroshio Extension. J. Climate, 29,3273–3296, https://doi.org/10.1175/JCLI-D-15-0545.1.
Minobe, S., A. Kuwano-Yoshida, N. Komori, S.-P. Xie, and R. J.
Small, 2008: Influence of the Gulf Stream on the troposphere.
Nature, 452, 206–209, https://doi.org/10.1038/nature06690.
Mitsudera, H., T. Waseda, T. Yoshikawa, and B. Taguchi, 2001:
Anticyclonic eddies and Kuroshio Meander formation. Geophys.
Res. Lett., 28, 2025–2028, https://doi.org/10.1029/2000GL012668.
Miyazawa, Y., X. Guo, and T. Yamagata, 2004: Roles of mesoscale eddies
in the Kuroshio paths. J. Phys. Oceanogr., 34, 2203–2222, https://doi.org/10.1175/1520-0485(2004)034,2203:ROMEIT.2.0.CO;2.
——, T. Kagimoto, X. Guo, and H. Sakuma, 2008: The Kuroshio
large meander formation in 2004 analyzed by an eddyresolving ocean forecast system. J. Geophys. Res., 113, C10015,
https://doi.org/10.1029/2007JC004226.
Mizuno, K., and W. B. White, 1983: Annual and interannual variability in the Kuroshio Current system. J. Phys. Oceanogr., 13,
1847–1867, https://doi.org/10.1175/1520-0485(1983)013,1847:
AAIVIT.2.0.CO;2.
Na, H., K.-Y. Kim, S. Minobe, and Y. N. Sasaki, 2018: Interannual
to decadal variability of the upper-ocean heat content in thewestern North Pacific and its relationship to oceanic and atmospheric variability. J. Climate, 31, 5107–5125, https://doi.org/
10.1175/JCLI-D-17-0506.1.
Nakamura, H., T. Izumi, and T. Sampe, 2002: Interannual anddecadal modulations recently observed in the Pacific storm

10827

10828JOURNAL OF CLIMATE

Pacific subarctic frontal zone: Observations and a coupledmodel simulation. J. Climate, 25, 111–139, https://doi.org/
10.1175/JCLI-D-11-00046.1.
Tsujino, H., S. Nishikawa, K. Sakamoto, N. Usui, H. Nakano, andG. Yamanaka, 2013: Effects of large-scale wind on the
Kuroshio path south of Japan in a 60-year historical OGCM
simulation. Climate Dyn., 41, 2287–2318, https://doi.org/
10.1007/s00382-012-1641-4.
Usui, N., H. Tsujino, H. Nakano, and Y. Fujii, 2008: Formation
process of the Kuroshio large meander in 2004. J. Geophys.
Res., 113, C08047, https://doi.org/10.1029/2007JC004675.
——, ——, ——, and S. Matsumoto, 2013: Long-term variability of
the Kuroshio path south of Japan. J. Oceanogr., 69, 647–670,
https://doi.org/10.1007/s10872-013-0197-1.
Wijffels, S. E., M. M. Hall, T. Joyce, D. J. Torres, P. Hacker, and
E. Firing, 1998: Multiple deep gyres of the western North
Pacific: A WOCE section along 1498E. J. Geophys. Res., 103,
12 985–13 009, https://doi.org/10.1029/98JC01016.
Wilson, C., B. Sinha, and R. G. Williams, 2009: The effect ofocean dynamics and orography on atmospheric storm
tracks. J. Climate, 22, 3689–3702, https://doi.org/10.1175/
2009JCLI2651.1.
Yasuda, I., K. Okuda, and M. Hirai, 1992: Evolution of a Kuroshio
warm-core ring—Variability of the hydrographic structure.
Deep-Sea Res., 39A, S131–S161, https://doi.org/10.1016/S01980149(11)80009-9.
Yoshida, S., B. Qiu, and P. Hacker, 2011: Low-frequency
eddy modulations in the Hawaiian Lee Countercurrent:
Observations and connection to the Pacific decadal oscillation. J. Geophys. Res., 116, C12009, https://doi.org/10.1029/
2011JC007286.
Zhang, D., T. N. Lee, W. E. Johns, C.-T. Liu, and R. Zantopp, 2001:
The Kuroshio east of Taiwan: Modes of variability and relationship to interior ocean mesoscale eddies. J. Phys. Oceanogr.,
31, 1054–1074, https://doi.org/10.1175/1520-0485(2001)031,1054:
TKEOTM.2.0.CO;2.

Downloaded from http://journals.ametsoc.org/jcli/article-pdf/33/24/10813/5019114/jclid200237.pdf by University of Hawaii at Manoa, Library user on 30 November 2020

Rio, M.-H., S. Guinehut, and G. Larnico, 2011: New CNES-CLS09
global mean dynamic topography computed from the combinationof GRACE data, altimetry, and in situ measurements. J. Geophys.
Res., 116, C07018, https://doi.org/10.1029/2010JC006505.
Sasaki, Y. N., S. Minobe, and N. Schneider, 2013: Decadal responseof the Kuroshio Extension jet to Rossby waves: Observationand thin-jet theory. J. Phys. Oceanogr., 43, 442–456, https://doi.org/10.1175/JPO-D-12-096.1.
Small, R. J., R. A. Tomas, and F. O. Bryan, 2014: Storm track response to ocean fronts in a global high-resolution climate
model. Climate Dyn., 43, 805–828, https://doi.org/10.1007/
s00382-013-1980-9.
Smirnov, D., M. Newman, M. A. Alexander, Y.-O. Kwon, and
C. Frankignoul, 2015: Investigating the local atmospheric response to a realistic shift in the Oyashio sea surface temperature front. J. Climate, 28, 1126–1147, https://doi.org/10.1175/
JCLI-D-14-00285.1.
Solomon, H., 1978: Occurrence of small ‘‘trigger’’ meanders in the
Kuroshio off southern Kyushu. J. Oneanogr. Soc. Japan, 34,
81–84, https://doi.org/10.1007/BF02109256.
Stuecker, M. F., 2018: Revisiting the Pacific meridional mode. Sci.
Rep., 8, 3216, https://doi.org/10.1038/s41598-018-21537-0.
Sugimoto, S., and K. Hanawa, 2009: Decadal and interdecadal
variations of the Aleutian Low activity and their relation toupper oceanic variations over the North Pacific. J. Meteor. Soc.
Japan, 87, 601–614, https://doi.org/10.2151/jmsj.87.601.
——, B. Qiu, and A. Kojima, 2020: Marked coastal warming off
Tokai attributable to Kuroshio large meander. J. Oceanogr.,76, 141–154, https://doi.org/10.1007/s10872-019-00531-8.
Taguchi, B., S.-P. Xie, N. Schneider, M. Nonaka, H. Sasaki, and
Y. Sasai, 2007: Decadal variability of the Kuroshio Extension:
Observations and an eddy-resolving model hindcast. J. Climate,20, 2357–2377, https://doi.org/10.1175/JCLI4142.1.
——, H. Nakamura, M. Nonaka, N. Komori, A. Kuwano-Yoshida,
K. Takaya, and A. Goto, 2012: Seasonal evolutions of atmospheric response to decadal SST anomalies in the North

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