Decadal Predictions of the Dynamic State of
the Kuroshio Extension System
B. Qiu 1 , S. Chen 1 , N. Schneider 1 , and B. Taguchi 2
1Dept
of Oceanography, University of Hawaii at Manoa, Hawaii, USA
2Earth
Simulator Center, JAMSTEC, Yokohama, Japan
An important feature emerging from the high-quality satellite altimeter measurements of the past
18 years, is that the Kuroshio Extension (KE) current system undergoes clearly-defined decadal
oscillations between two dynamic states. When the KE jet is in an elongated state, its transport and
latitudinal position tend to be greater and more northerly, the southern recirculation gyre tends to
strengthen, and the eddy kinetic energy level in the upstream KE region tends to drop. The reverse
is true when the KE jet changes to a contracted state. Since October 1992 after the satellite
altimeter measurements became available, the contracted state of the KE jet appeared in 1995-2001
and in 2006-09 and the elongated state was detected in the remaining intervening years (Fig.1). The
cause responsible for the transitions between the elongated and contracted states of the KE jet has
been explored extensively both observationally and based on the eddy-resolving OFES simulations.
It is by now relatively well established that the observed transitions were initiated by the decadallyfluctuating wind stress curl forcing over the central midlatitude North Pacific Ocean. Specifically,
when the central North Pacific wind stress curl anomalies are positive, enhanced Ekman flux
divergence generates negative local sea surface height (SSH) anomalies. As these wind-induced
negative SSH anomalies propagate westward into the KE region after a delay of 3~4 years, they
weaken the zonal KE jet, leading to a contracted state of the KE system with a reduced recirculation
gyre and an active eddy kinetic energy field. The negative wind stress curl anomaly forcing in the
central North Pacific, on the other hand, generates positive SSH anomalies that lead to the
elongated state of the KE jet.
Notice that the decadal modulations of the KE system can be adequately represented by a
dynamic state index (referred to as the KE index below) defined as the average of the 4 dynamic
quantities presented in Fig.1. As shown in Fig.2a, the low-pass filtered KE index time series can be
very well represented by the SSH anomaly signals in the region of 31°-36°N and 140°-165°E
encompassing the KE jet and its southern recirculation gyre. It is important to emphasize that the
decadal modulations as represented by the KE index have taken place after the 1976/77 shift of the
North Pacific climate system (Fig.2b). The objective of this study is to explore the extent to which the
KE index can be predicted with a multi-year lead. To achieve this, we adopt a dynamic-statistical
model, in which the SSH variability associated with the KE index is determined by the linear
vorticity dynamics (i.e., the Rossby wave model) driven by the surface wind stress curl forcing and
the low-frequency KE variability can feedback to the overlying wind field through a laggedcorrelation statistical model. By applying this dynamic-statistical model to the results of the OFES
hindcast run and by determining the feedback wind forcing signals with the use of NCEP-NCAR
reanalysis data, we find a positive KE index induces overlying negative and downstream positive
surface wind stress curl anomaly. This feedback favors a coupled mode with a ~10 year timescale in
the North Pacific Ocean.
Following the establishment of the dynamic-statistical model, we explore the predictability
of the OFES SSH anomaly time series shown in Fig.2b as a proxy for the KE index time series.
Specifically, we compare the KE index anomaly mean square skill scores under the persistence, the
forced (the dynamic model only), and the coupled (the dynamic-statistical model) scenarios.
Consistent with previous analyses, predictive skill of the Rossby wave dynamics greatly exceeds that
over the persistence (Fig.3). At the lead of 5 years, the Rossby wave dynamics explains ~20% of the
KE index variance. Inclusion of the feedback wind forcing further improves the predictive skill: at
the 5-year lead, it explains an additional 10% of the variance and it doubles the predictive skill over
that of the Rossby wave dynamics at the 6-year lead.
1
Fig.1: (a) Upstream KE path length integrated from 141°E to 153°E. (b) SSH difference across the
KE jet averaged from 140°E to165°E. (c) Strength of the KE recirculation gyre. (d) Latitudinal
position of the KE averaged from 140°E to 153°E. Dark underlying lines indicate the periods when
the KE system is in the unstable state.
Fig.2: (a) Time series of the altimeter-measured SSH anomalies averaged in 31°-36°N and 140°165°E. Thick dark line indicates the KE index based on the dynamic properties of the observed KE
system shown in Fig.1. (b) Same as (a) except for the SSH anomalies from the OFES hindcast run.
Fig.3: Predicative skill of the KE index (with the OFES SSH anomalies shown in Fig.2b as its proxy)
from the persistence (black line), the Rossby wave dynamics (blue line), and the dynamic-statistical
model of the present study (red line).
2