Ocean Dynamics (2012) 62:633–644
DOI 10.1007/s10236-011-0519-z

Ensemble numerical forecasts of the sporadic Kuroshio water
intrusion (kyucho) into shelf and coastal waters
Atsuhiko Isobe & Shin’ichiro Kako & Xinyu Guo &Hidetaka Takeoka

Received: 31 August 2011 / Accepted: 27 December 2011 / Published online: 17 January 2012
# The Author(s) 2012. This article is published with open access at Springerlink.com

Abstract The finite volume coastal ocean model downscaling ocean reanalysis and forecast data provided by the Japan
Coastal Ocean Predictability Experiment (JCOPE2) are used
to forecast sudden Kuroshio water intrusion events (kyucho)
induced by frontal waves amplified south of the Bungo
Channel in 2010. Two-month hindcast computations giveinitial conditions of the following 3-month forecasts computations which consist of ten ensemble members. The
temperature time series computed by these ten members
are averaged to compare with that actually observed in the
Bungo Channel, where sudden temperature rises related tokyucho events are remarkable in February, August, andSeptember. Overall, the intense kyucho events actuallyobserved in these months are predicted successfully. However, intense kyucho events are forecasted frequently during
the period of May through June even though intense kyucho
events are absent during this period in the actual ocean. It issuggested that the present downscaling forecast model
requires reliable lateral boundary conditions provided by
JCOPE2 data to which numerous Argo data are assimilated
to enhance the accuracy. In addition, it seems likely that themodel accuracy is reduced by small eddies moving along
the shelf break.
Keywords JCOPE2 . FVCOM . Ensemble forecast .
Kyucho . Argo
Responsible Editor: Tal Ezer
This article is part of the Topical Collection on the 3rd International
Workshop on Modelling the Ocean 2011
A. Isobe (*) : S. Kako : X. Guo : H. Takeoka
Center for Marine Environmental Studies, Ehime University,
2-5 Bunkyo-cho,
Matsuyama 790-8577, Japane-mail: aisobe@ehime-u.ac.jp

1 Introduction
Western boundary currents such as the Kuroshio in the
North Pacific are always accompanied by frontal waves on
the onshore side. Unlike the Gulf Stream in the North
Atlantic, the Kuroshio path is located very close to thewestern boundary (the southern coast of Japan in this case),so the frontal waves excited along the ocean currents frequently extend onto the shallow shelf and coastal waters(Akiyama and Saitoh 1993; Arai 2005) and rapidly alter themarine environment in these areas (Koizumi and Kohno
1994; Katano et al. 2007; Hirose et al. 2008). In fact, it
has been reported that these frontal waves amplified at theshelf break cause sporadic Kuroshio water intrusion into
various coastal waters south of Japan, where cultured fishes
and fixed nets have been frequently damaged by sudden
increases in both temperature and current speed associatedwith this warm water intrusion (Takeoka and Yoshimura
1988 and references therein). The Japanese term “kyucho”(meaning sudden stormy currents) has been used by theoceanographic community of Japan as well as fishermen torefer to these intrusion events, which have heretofore
received attention from oceanographers (e.g., Uda 1953).
Besides the disadvantages to inshore fisheries as mentioned
above, kyucho events have an advantage in that catches ofcommercially high-valued fishes increase suddenly incoastal waters during these events, presumably because fisharound shelf breaks avoid rapid temperature changes (Hashida2011, personal communication). Thus, a research project inhigh demand is to establish kyucho forecasting similar to
weather forecasting.
To date, it has been difficult to forecast ocean currents
and hydrographic properties in shelf and coastal waters
despite the development of high-performance computerssuch as the Earth Simulator (Masumoto et al. 2004) along

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It is difficult to detect kyucho events directly in JCOPE2
data because their horizontal resolution of 1/12 of a degree
is unlikely to resolve Kuroshio frontal waves accurately(Isobe et al. 2004). Probably the simplest way to simulate
kyucho events is to downscale JCOPE2 data using a numerical model suitable for reproducing small-scale features in
shelf and coastal waters. The present study employs thefinite volume coastal ocean model (FVCOM; Chen et al.
2003) for resolving complex topography in shallow waters
using triangular cell grids. In fact, a hindcast computation
using JCOPE2 data as boundary conditions of the FVCOM
well reproduces the kyucho events in 2003 (Isobe et al.
2010) because mesoscale warm eddies impinging on the
Kuroshio south of Japan trigger the kyucho occurrence
and these eddies are well reproduced in the JCOPE2 analysis.
In addition, the JCOPE2 model successfully forecasts
Kuroshio meanders after removing the assimilation schemes
incorporated into the model (Miyazawa et al. 2005), and
FVCOM computations using JCOPE2 forecast data as lateralboundary conditions are therefore expected to forecast kyucho
events as they occur in the actual ocean.
The objective of the present study is to examine thecapability of ensemble kyucho forecasts by downscaling
either physical processes or resolution in JCOPE2 analysis
into a smaller FVCOM domain (i.e., one-way nested model)
around the Bungo Chanel. In the present application, 3-monthforecast computations follow 2-month hindcast computations,
during which observation data are not assimilated into the
FVCOM domain. This is because, as mentioned above, thefine structure of Kuroshio frontal waves is likely to be
destroyed by assimilating sporadic observations insufficientwith sophisticated numerical model codes. The developmentof numerical forecasting in these shallow waters seems tohave been prevented by two obstacles. One is that thedensity of observation stations is too sparse to constructobjectively analyzed datasets suitable for providing reliable
initial conditions for models. For instance, one of the mostpowerful tools to obtain spatiotemporally dense oceanographic data is satellite altimetry, which provides sea surface
height (SSH) data approximately once every 10 days withspatial resolution of 100 km, while both temporal and spatial
scales required for resolving Kuroshio frontal waves are oneorder of magnitude smaller (see Table 1 in James et al.
1999). The other obstacle is uncertain in lateral boundary
conditions. Even if a forecast model does a reasonable job ofsimulating ocean currents within the model domain, a wrong
condition at lateral boundaries may reduce model accuracy.
In the present study, special attention is given to kyucho
events in the Bungo Channel (Fig. 1), the width and axis
length of which are both approximately 50 km. In spite of
the above two limitations, the present attempt to forecast
kyucho events may succeed because more oceanic data haverecently become available to the oceanographic community.
Apparently, it is not yet possible to overcome the former
obstacle because we have no way of providing gridded
oceanic data (e.g., SSH) operationally once a day with theseveral kilometers resolution required for kyucho forecasts
in the relatively narrow Bungo Channel. However, daily
ocean reanalysis and forecast data provided by the Japan
Coastal Ocean Predictability Experiment (JCOPE2; Miyazawa
et al. 2008, 2009) allow us to impose reliable lateral boundary
conditions on numerical coastal models.

130˚

131.5

132

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136˚

132.5E
33˚

50
200

50

00

31˚

10

Fig. 1 Study area. The area
within the shaded square in
the upper right inset map isenlarged in the lower left panel.
The Kuroshio path is shown
schematically on the inset map.
Also shown are isobaths inmeters. Temperature at 5-m
depth below the sea surface isobserved at two stations(Shitaba and Hiburi) denotedby open circles. The forecast
temperature at the open squareis compared with the temperature averaged between thetwo stations

29˚

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Ocean Dynamics (2012) 62:633–644

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for coastal waters. The insufficient accuracy that may appear
in the present forecast computations is caused by the uncertainty of small-scale processes generated in the FVCOM
domain as well as that included within JCOPE2 data.
It is worthwhile to specify causes reducing the capability of the forecasts to improve this “first generation” ofkyucho forecast models.

2 Data and methods
2.1 Kyucho events in the Bungo Channel
Experiments are conducted to forecast the kyucho events
observed in 2010 in the Bungo Channel. Before describing
the experimental details, we next present a temperaturerecord in which several kyucho events are observed(Fig. 2). This time series is the average of those observed
5 m below the sea surface at Hiburi and Shitaba stations(Fig. 1) because each single temperature record was occasionally interrupted by mechanical errors. The temperaturerecord band-passed between 5 days and 1 year indicates that
intense kyucho events occur during two periods as shownby the shading in Fig. 2. First, there are temperature
increases of more than 3°C even in the midwinter, althoughin general, warm water is prevented from intruding onto

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J
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A

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D

Fig. 2 Observed temperature record. The dotted curve indicates temperature averaged between two observation stations (Fig. 1). The
observed temperature anomaly from the annual average is low-passed
using a 5-day box-car filter, and the annual variation is removed byfitting a sinusoidal curve with a least square method (solid curve). See
the right ordinate for the raw temperature record and left ordinate for theprocessed record. The bars show the periods of forecast runs. Two shaded
bands emphasize the intense kyucho occurrences during February,
August, and September. SSH maps derived from JCOPE2 reanalysis dataat the points labeled a, b, and c are depicted in Fig. 3. The closed and open
circles indicate new and full moons, respectively

shallow shelves because the intense winter cooling makes
shallow waters vertically well-mixed. It is therefore suggested that highly suitable conditions for triggering the
kyucho occurrence are established during this period. Frequent relatively weak temperature rises are revealed during
the period May through June. However, it should be notedthat kyucho events comparable to those in the first period
occur in the midsummer and that the temperature rises by
about 3°C twice during the period July through September.
Isobe et al. (2010) point out that the kyucho events in
midsummer 2003 in the Bungo Channel were triggered bymesoscale warm eddies impinging on the Kuroshio south ofthe channel. Indeed, the SSH maps on days a, b, and c(Fig. 2) demonstrate that the sharpness of the Kuroshio front
increases gradually (lower three panels in Fig. 3) as the areas
with high SSH anomalies extend westward (upper threepanels in Fig. 3). It is anticipated that kyucho events (i.e.,development of Kuroshio frontal waves) are likely to occur
on day c because the frontal sharpness is a condition favorable for the enhancement of baroclinic instability.
2.2 Model setup and nests
We next describe details of the numerical model used forhindcast computations. The behavior of mesoscale warm
eddies is well reproduced in JCOPE2 reanalysis in whichdatasets derived from both satellites and the Global Temperature Salinity Profile Program (GTSPP) including Argo
data are assimilated (Miyazawa et al. 2008, 2009). Hence, it
is anticipated that downscaling these reanalysis data to data
for shelf and coastal waters will allow us to reproduce thecondition favoring kyucho events. The SSH, temperature,salinity, and horizontal components of currents in the
JCOPE2 reanalysis data are given to the lateral boundariesof the FVCOM domain (Fig. 4), where the length of celledges is the same as that of JCOPE2 data (1/12°) at open
boundaries so that the FVCOM is connected to JCOPE2
data without spatial interpolations of variables. Thereby, thisone-way nested model is likely to conserve volume transport between two different models. This is a clear advantage
of unstructured grid models like the FVCOM over models
with a uniform grid in constructing nested models. The
length in the channel reduces to less than 1 km, which is
sufficiently small to reproduce both frontal waves and complex topography (see the enlarged panel of Fig. 4). Sidewallboundaries are imposed at Hayasui Strait and Awaji Island
because the throughflow that may alter circulation in themodel domain is unclear around these narrow straits(~10 km width) (Chang et al. 2009) and because there is
no way of knowing current and hydrographic conditions inthese straits during the course of the hindcast/forecast computations; note that the JCOPE2 analysis does not provide us
with oceanic conditions within the shallow Seto Inland Sea.

636
Fig. 3 SSH anomalies (upper
panels) and SSH (lower) at a, b,
and c in Fig. 2. The anomalies
are computed by removing the
SSH averaged over the period athrough c. The contour interval
is 5 (10)cm in the upper(lower) panels

Ocean Dynamics (2012) 62:633–644
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0
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Fig. 4 Area modeled using the
FVCOM. The bold lines in theupper right panel denote thelateral boundaries of the
FVCOM domain. Shading in
the upper right panel indicates“sponge layers” in which
FVCOM results are restored to
JCOPE2 data to remove
artificial disturbances caused by
the connection between two
different model results. Argo
data within the box outlined by
the bold broken line are used forthe computation in Table 1. Also
shown are 200- and 1,000-m
isobaths. The area within thesmall rectangle in the upper
right panel is enlarged in thelower left panel to illustrate unstructured triangular cell grids
and depths represented by thinwhite lines and shading, respectively. Light shading is used forareas shallower than 50 m, whileareas deeper than 100 m are
represented by dark shading(c)sponge regions is doubled along the eastern boundary tocarefully retain the shape of warm eddies propagating westward as baroclinic Rossby waves and/or advection due to the
Kuroshio Countercurrent. The FVCOM domain is divided into
23 layers vertically, and 23-layer JCOPE2 data are interpolated
linearly to each FVCOM layer in the sponge regions.

130˚

132˚

134˚

136˚

33˚

200

Perturbations generated by connecting two different
models are removed in sponge regions (shading in Fig. 4),
where all modeled variables are restored to JCOPE2 reanalysis
data. The coefficient (a reciprocal of time) of restoring terms
diminishes linearly from 1/6 h−1 at the lateral boundaries tozero at the inner edge of the sponge regions. The width of the

28˚

(b)

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10
00

(a)

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Ocean Dynamics (2012) 62:633–644

637

Two datasets are combined to give depth data to eachtriangular cell grid of the FVCOM. The topographic datasetwith 1/12° resolution (ETOPO5) provided by the US National Geophysical Data Center is used for the area south of
31.5° N, while the 500-m gridded topographic dataset provided by the Marine Information Research Center, Japan isused for the area north of 31° N. The above two topographic
datasets are blended using a coefficient varying linearly inspace between 31° N and 31.5° N latitudes. The depth in eachtriangular cell grid is determined by interpolating the nearest
16 topographic data weighted by the inverse distance.
The procedures for hindcast computations are shown in
Fig. 5. Daily JCOPE2 reanalysis data are imposed at thelateral boundaries through linear interpolation at each time
step. To date, no research project has pointed out thatkyucho occurrences in the Bungo Channel are triggered bymomentum and heat fluxes through the sea surface. Nevertheless, winter northerly monsoon winds (hence, intense
cooling) are likely to prevent warm Kuroshio water from
intruding northward on the shelf. Thus, in the present application, monthly averaged wind stresses and sea surface
temperature (SST) are imposed over the FVCOM domain.
In addition, daily wind stresses are imposed over the model
domain for comparison. In lieu of adopting the Quick Scatterometer (QSCAT) winds unavailable at this time, we employ
the monthly averaged wind vectors observed by the Advanced
Scatterometer (ASCAT) after gridding with an optimal interpolation method (Kako et al. 2011). The drag coefficient ofLarge and Pond (1981) is adopted to convert wind speeds into
stresses. SST over the FVCOM domain is restored to SST
provided by climatologically averaged monthly JCOPE2 dataon a time scale of 5 days. It is reported that kyucho events in the
Bungo Channel tend to generate at neap tides because of weakvertical mixing (Takeoka et al. 1993). It is, however, ambiguous that the kyucho occurrences in 2010 are synchronized withfortnightly neaps–springs cycles (Fig. 2) and so tidal forcing is
not applied to the present model. Hindcast computations arestarted with initial conditions produced using JCOPE2 data andare thereafter continued over the course of 2 months, which is
sufficient for initial disturbances to spin-down over the modelFig. 5 Flowchart describing
the relationship between
hindcast/forecast computations
and dataset input to the models

domain and for small-scale features (say, frontal waves) not
resolved in the JCOPE2 reanalysis to be generated in the
FVCOM.
2.3 Procedures of forecast computations
Three-month forecasts follow the above hindcasts, with theresults at the end of the computations used as initial conditions (Fig. 5). Three-month period is chosen as the forecast duration because JCOPE2 provides us with 3-month
daily forecast data, which are set to lateral boundaries in thesame manner as in the hindcast computations. In addition,modeled SST is restored to monthly averaged JCOPE2
forecast data on a timescale of 5 days so that small-scalefeatures revealed in the SST field of the original JCOPE2
analysis do not destroy those in the FVCOM domain. Forecast winds such as those of the Numerical Analysis andPrediction System of the Japan Meteorological Agency are
not used to drive the present forecast model because, as
mentioned above, short-term wind fluctuations are not critical to kyucho occurrences and because the use of forecast
winds complicates interpretations of the forecast accuracy.
Monthly averaged wind stresses computed using QSCAT
data in the period 2002 through 2008 drive the model
domain during the course of the forecast computations.
Tidal forcing is not included in the forecast computations
as in the hindcast computations.
The forecast computations are conducted six times for2010 (bars in Fig. 2) as follows: Each forecast run consistsof ten ensemble members; ten temperature records at the
midpoint between Shitaba and Hiburi (box in Fig. 1) areaveraged to compare with the observed time series in Fig. 2.
The computations of ten ensemble members are started fromdifferent perturbed initial states generated by the breeding
method (Toth and Kalnay 1993) as schematically shown in
Fig. 6. In the first run (referred to as run 1), random temperature perturbations with a standard deviation of 0.1°C are
added to the temperature field in the 2-month hindcast
computation on 21 January. Ten perturbation patterns provide us with ten different forecast members (solid circles in

ASCAT windstressmonthly-averaged SST

boundary conditions
at the sea surface

FVCOM

initial condition

QSCAT windstressboundary conditions
at the sea surface

FVCOM

initial & lateral boundary conditions

lateral boundary conditions

JCOPE2 reanalysis data

JCOPE2 forecast data

2-month hindcast

3-month forecast

satellite data
GTSPP
including
ARGO

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Ocean Dynamics (2012) 62:633–644

2010/04/21

year / month / day

2010/05/18
2010/02/18
2009/11/21

2010/01/21
2010/06/30
2010/03/31
2009/12/18

2010/02/18

2010/01/31

2010/03/31

Fig. 6 Schematic view of the breeding method. See text for details

Fig. 6) in the following 3 months. Simultaneously, a single“unperturbed” ensemble member without the addition of
initial perturbations is computed until the beginning of run
2 (open circle with the broken line at run 1). The temperature differences between perturbed and unperturbed ensemble members on 18 February are normalized so that theirstandard deviations are adjusted to 0.1°C in each combination and are added as the initial perturbations to the next ten
ensemble members of run 2. In the same manner as for run
2, four sets of hindcast and forecast runs (runs 3–6) are
thereafter repeated as shown by the bars in Fig. 2. Overall,the coefficients of correlation among normalized standard
deviations of each ensemble member are very small (~0.2).

Both satellite-observed and forecast SST maps demonstrate that the kyucho event occurs in mid-February when
the Kuroshio front approaches the Bungo Channel (Fig. 8).
A cloud-free image taken on 20 February 2010 (images
before and after the 20th were unavailable owing to cloud)and downloaded from the website of the North PacificRegion Environmental Cooperation Center (http://www.
npec.or.jp/) shows that the Kuroshio front with temperature
between 16.5°C and 18.5°C is embedded on the shelf of the
Bungo Chanel mouth and that warm water originating fromthe Kuroshio extends further to the north in the channel. The
SST maps forecasted every 5 days also represent both the
Kuroshio front located close to the channel and northward
extension of warm water in mid-February. However, SST ishigher than that observed by the satellite partly because
the sea surface cooling within the narrow channel isincorporated by restoring SST computed using the relatively
coarse JCOPE2 model.
The present downscaling model was capable of forecasting kyucho events if the accuracy in Fig. 7 was maintained
throughout all forecast runs. It should, however, be notedthat the accuracy considerably differs for each forecast run(Fig. 9). For instance, intense kyucho events rarely occur inthe period April through June in the actual ocean (Fig. 2),
although remarkable kyucho events frequently appear in

o
C
3

2
1

3 Results
We first show the results for run 1 which give us confidence
in forecasting kyucho events in the Bungo Channel. To
emphasize the timing of the kyucho occurrence, Fig. 7graphs de-trended time series of temperature anomalies atthe box position in Fig. 1. Thin curves indicating ten
ensemble members show that temperature rises suddenly
in mid-February in spite of stochastic fluctuations considerably differing for each member; see the solid curve at thebase of the figure for the standard deviation of ensemble
members from the averaged curve. The temperature rise in
the actual ocean is observed over the course of February (seethe broken curve in Fig. 7), while the average (bold curve)of ten members shows that the onset of the temperaturerise seems to be delayed by about a week. Nevertheless,we emphasize that the kyucho occurrence in February2010 is forecasted successfully in run 1 conducted about
20 days previously.

0-1

Run 1-1

-2
-3
20
31
Jan.

10 20 28 10 20
Mar.
Feb.
2010

31

10 20
Apr.

Fig. 7 Time series of temperature anomalies in the period of run 1.
The observed series (broken curve) is the same as the solid curve in
Fig. 2 except for de-trending in lieu of removing the annual variation
because of the 3-month computation. The temperature records forecast
by ten ensemble members are denoted by thin solid curves; the curve of
the first member is indicated by the arrow. The bold solid curve shows
the time series averaged for the ten ensemble members. The
standard deviation of ensemble members (thin solid curves) fromthe averaged value (bold curve) is indicated by the solid curve atthe bottom of the figureOcean Dynamics (2012) 62:633–644

639
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MODIS_SST

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20 Feb., 201018

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Run 1-1
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[oC]

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22

Fig. 8 SST maps during the period of run 1. The satellite-derived SST is shown in the upper panel. Shading indicates areas covered by clouds. The
lower three panels show SST maps computed for the first member of run 1. The contour interval is 0.5°C in both upper and lower panels

runs 3 and 4 (Fig. 9). Sudden temperature rises in run 5 (seethe arrow with the letter a) and run 6 (arrows with the lettersb and d) are well forecasted in the present model, while a
Fig. 9 Comparison between
observed (broken curves)and forecast (solid curves)
temperature records. The
forecast records are the averagefor ten ensemble members.
Both time series are low-passed
by a 5-day box-car filter and arede-trended during the forecast
period of each run. The curvesindicate anomalies from thetemporally averaged value
during the forecast period. The
solid circles with numerals areplotted at the beginning of each
forecast run. Each curve isshifted downward by 2.5°C forease of presentation. See thetext for the meaning of theletters a to d. The numerals
for each graph indicate themaximum values of thelag-correlation coefficient
within ±5 days. The coefficientsare all insignificant over thecourse of 10 days in run 3,
according to a t test with
a 95% confidence level

temperature rise in run 6 (the arrow with the letter c) does
not occur in the actual ocean. The numerals in each graph
are the maximum values of the lag-correlation coefficient1

R± 5 = 0.83

R± 5 = 0.41
[oC]

2

5

3

R± 5 = insignificant

R± 5 = 0.63

0a4

R± 5 = 0.50

5

d

-5

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c

6

R± 5 = 0.27

Jan. Feb.

Mar.

Apr.

May

2010

Jun.

Jul.

Aug.

Sep.

640

within ±5 days to roughly show the similarity between theforecast and observed time series.

4 Discussion

Ocean Dynamics (2012) 62:633–644

N

34˚

32˚

4.1 Reliability of the lateral boundary conditions
30˚

As mentioned above, the kyucho events actually observed
during the two shaded periods in Fig. 2 are all forecasted(mid-February and a (b) and d in Fig. 9) in the present
experiment, while the kyucho events revealed in the forecast
computations are not always observed in the actual ocean(run 3, run 4, and c). In general, the accuracy of downscaling
computations depends strongly on the reliability of lateralboundary conditions, and it is thus worth investigating to what
extent the boundary conditions provided by JCOPE2 data arereliable. The number of Argo floats south of Japan is likely tobe crucial to enhancing the reliability of JCOPE2 data becausehydrographic data assimilated to the reanalysis model arederived from numerous Argo floats and because the numberof Argo floats carried passively by ocean currents is unlikely
to be stable south of Japan.
We first seek areas correlated significantly with the lateralboundaries of the forecast computations and thereafter investigate the number of Argo floats passing these areas in
the past. The lag-correlation maps of SSH at the lateral open
boundaries are depicted using JCOPE2 reanalysis data inwhich the satellite-derived SSH is assimilated (Fig. 10).
Two representative locations at the mid-points of theeastern and southern boundaries are chosen for the computation because these boundaries are located “upstream” ofwestward-propagating mesoscale eddies that trigger the
kyucho occurrence in the Bungo Channel. The significant
correlation areas are traceable roughly in the past 5 months(bold curves in Fig. 10), suggesting that the reliability of thelateral boundary conditions depends on whether or not eddies
moving around these areas are reproduced appropriately in
JCOPE2 data.
The number of Argo floats within the shaded areas ofFig. 10 during the past 5 months is next counted in thecourse of each 3-month forecast run (Fig. 11). We here use
the Argo dataset arranged by Oka et al. (2007; http://ocg.
aori.u-tokyo.ac.jp/member/eoka/data/NPargodata/). Notethat the float number should decrease monotonically in the
figure because the period during which Argo data are notassimilated increases gradually as the 3-month forecast
computations proceed. For instance, open boundary conditions (i.e., JCOPE2 analysis) on day 0 of each forecast run
undergo the assimilation of Argo data over the course of thepast 5 months, while the conditions on day 90 undergo theassimilation only in 2 months of the past 5 months. It should

60

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E
Fig. 10 Lag-correlation maps of SSH at locations denoted by open
circles. The areas with statistically significant correlation coefficients
according to a t test with a 99% confidence level are outlined by bold
curves. The numerals superimposed on the curves denote the lag indays toward the past. The broken curves are used every 60 days forease of reference. Shading indicates the area in which numbers of Argo
floats are counted in Fig. 11

be noted that Argo float numbers drastically change witheach forecast run. In fact, numbers in the former three
forecast computations (runs 1, 2, and 3) are smaller thanthose in the latter three computations (runs 4, 5, and 6). In
particular, numbers in both runs 5 and 6 are nearly double
those in the former three runs.
It is anticipated that eddies that might trigger kyucho
events in 2010 appear reliably in the FVCOM domain
during the latter three forecast runs because of reliableOcean Dynamics (2012) 62:633–644

641

ARGOs
200

Table 1 Comparison of potential density anomalies in the forecast
runs and those observed by Argo floats: the number of Argo floats (n)during each forecast run within the box outlined by the broken line in
Fig. 4, correlation coefficient (r), and skill (s)

Run 6

Run

Run 5

150

Run 4

100
Run 3

n

r

s
−1.26

1

47

0.24

2

42

0.53

0.20

3
4

49
51

0.38
0.71

−0.42
0.46

5

55

0.51

0.13

6

73

0.51

0.10

Run 2

50
Run 1

0
0

10

20

30

40

50

60

70

80 90
days

Fig. 11 Number of Argo floats within the shaded area in Fig. 10 in thepast 5 months during the 3-month forecast computations. The abscissa
indicates elapsed days from the beginning of each forecast run, while
the ordinate shows the float number during the past 5 months counted
from each day given on the abscissa. The line type and thickness differ
among runs1, 2, and 3 for ease of reference

lateral boundary conditions corrected by numerous Argo
data and that the actual kyucho events are therefore wellforecast because of these eddies impinging on the Kuroshio
front. We next compare forecast density profiles with density profiles observed by Argo floats south of Japan to
examine whether or not the anomalous density field in
the forecast computations is consistent with that in theactual ocean. The Argo data during each forecast run
are chosen in the area outlined by the broken line in
Fig. 4 and are used to compute the anomaly of verticalpotential density profile from the profile averaged over
the area. Table 1 lists correlation coefficients and skills
2 PPdefined as 1 
σa  σf = ðσa  σa Þ2 , where σ isthe potential density anomaly above 1,000 m, the overbar
indicates the average of all values (i.e., zero in this case),and the subscripts a and f denote densities observed by Argo
floats and those computed at the same locations in the forecast
runs, respectively. As expected, both correlation coefficientsand skills in the latter three forecast runs remain high, whilethe values fluctuate largely in the former three computations.
In fact, in runs 5 and 6 when the number of Argo floats southof Japan in the past 5 months is the largest among all forecast
runs (Fig. 11), the sudden temperature rises marked by a, b,
and d in Fig. 9 are all forecasted successfully.

However, Fig. 9 apparently shows that the number ofArgo floats is not a unique factor in determining the forecast
accuracy. For instance, the sudden temperature rise c in run
6 is not present in the actual time series despite the forecast
computation using the lateral boundary conditions corrected by numerous Argo data. Furthermore, the forecast
computation goes well in run 1 (Figs. 7 and 9) in spiteof there being the least Argo floats among all forecast
runs. Hence, factors unrelated to the number of Argo
floats south of Japan should be specified to improve
this forecast model developed for coastal waters.
4.2 Modeled processes reducing the forecast accuracy
The behavior of relatively small eddies (~100 km) in the
FVCOM domain explains why the sudden temperature risec in run 6 does not exist in the actual time series. In addition
to mesoscale eddies impinging on the Kuroshio south of the
Bungo Channel, eddies passing through the Tokara Strait(Fig. 1) affect the Kuroshio volume transport south of Japan(Ichikawa 2001). In fact, the SSH anomaly provided by
JCOPE2 reanalysis data during run 6 shows that a cold eddy
shed from the Tokara Strait moves to the area south of the
Bungo Chanel; see the arrow in the upper panels in Fig. 12.
The cold eddy is located north of the Kuroshio on 10 August2010 and seems to prevent Kuroshio water from intruding
onto the shallow shelf; see the white arrow in the lower left
panel of Fig. 12. However, the cold eddy forecast in run 6 ismuch smaller than that in JCOPE2 reanalysis data (lower
right panel). Therefore, the forecast Kuroshio axis is locatedcloser to the channel than that in the reanalysis data, and thisis the reason for the kyucho event (c in Fig. 9) that did notoccur in the actual ocean appearing in run 6.
In the case of run 1, a kyucho-favoring condition is
maintained by a warm eddy (the solid circle in the lower
panels of Fig. 13) located stably south of Japan during midFebruary; see SSH anomaly maps in Fig. 13. In fact, the642
Fig. 12 SSH maps in August.
The anomalies from the SSH
averaged over the computation
period of run 6 are depicted in
the upper panels every 5 days
using JCOPE2 reanalysis data.
Areas with the negative SSH
anomalies are indicated byshading. The cold eddy shedfrom the Tokara Strait isindicated by the arrow. The
SSH map using JCOPE2
reanalysis data on 10 August is
shown in the lower left panel,
while that computed for the first
ensemble member of run 6 is
depicted in the right panel. In
the lower panels, cold eddies
located on the onshore side of
the Kuroshio are indicated bywhite arrows. The contour
interval in the upper (lower)
panel is 5 (10)cm

Ocean Dynamics (2012) 62:633–644
130˚
34˚

132˚

134˚

136˚

Aug., 5

Aug., 7JCOPE2

Aug., 10JCOPE2JCOPE2

32˚

30˚

28˚
34˚

Aug., 10

Aug., 10JCOPE2FVCOM

32˚

Run 6-1

0

0

30˚

28˚
130˚

132˚

134˚

Kuroshio paths in both JCOPE2 reanalysis data (lower left
panel of Fig. 13) and the forecast computation (lower rightpanel) are located close to the Bungo Channel. Thereby,
frontal waves excited along the Kuroshio front extend easily
Fig. 13 Same as Fig. 12 but for
February maps. Unlike Fig. 12,
shading in the upper panels
represents positive anomalies.
The closed circles are plotted in
the lower panels for ease offinding the warm eddy southof Japan

130˚
34˚

132˚

134˚

136˚

onto the shelf of the Bungo Channel in both actual andforecast oceans, irrespective of whether or not the SSH
distribution except this warm eddy appears reliably in theforecast computation.
136˚Feb.,10

Feb.,15JCOPE2Feb.,20JCOPE2JCOPE2

32˚

30˚

28˚
34˚

Feb.,20

Feb.,20JCOPE2

FVCOM

0
32˚

Run 1-1

0
30˚
0
28˚
130˚

132˚

134˚

136˚

Ocean Dynamics (2012) 62:633–644

643

shortcomings that we should overcome to establish operationally practical kyucho forecast models. In particular, kyucho
events that did not occur in the actual ocean often appear in themodel (Fig. 9). For instance, the forecast kyucho event in midAugust (c in Fig. 9) is prevented from forming in the actual
ocean by the cold eddy moving along the shelf break (Fig. 12).
Apparently, this cold eddy is advected by the Kuroshio along
the shelf break south of the Bungo Channel, and it is thus
considered that short-term fluctuations in the current speed
cause the detachment of the eddy in mid-August. If this is thecase, the suggestion is that the daily wind forcing and/or tidal
currents at the shelf break, which are omitted in the present
model, are required to enhance the forecast accuracy.
The above arguments are also supported by extra experiments carried out to examine the dependency of the forecast
accuracy on the model design. Figure 14 shows the same timeseries of temperature at 5-m depth as those in run 6 in Fig. 9,
except for the first ensemble member (i.e., runs 6–1). Run 6 ischosen for the experiments because the number of Argo floats
was the largest among all forecast runs (Fig. 11) and because
the model accuracy is insensitive to the lateral boundary conditions. Also shown by the bold lines in Fig. 14 are (a) the timeseries obtained at the same location in the JCOPE2 analysis,(b) the time series obtained by the computation using daily
wind stresses instead of monthly wind stresses, (c) time series

5 Conclusion possible improvementof the kyucho forecast model
The present study investigated whether numerical models
downscaling JCOPE2 reanalysis and forecast data are capableof forecasting ocean circulation in coastal waters. The target
oceanic phenomenon in the present study is the kyucho events
generated in the Bungo Channel in 2010, when sudden temperature increases caused by Kuroshio water intrusion are
observed in February, August, and September. In particular,
the Kuroshio front south of the Bungo Channel is favorable forthe kyucho occurrence in February because it is located close
to the channel owing to the existence of a stable warm eddy
south of Japan. This stable eddy is also revealed in the forecast
computation (run 1), and the kyucho event thus occurs in theforecast model as in the actual ocean (Figs. 7 and 9). In
addition, the kyucho events in August and September (a (b)and d in Fig. 9) are successfully forecasted in the present
model, where mesoscale eddies south of Japan appear consistently with those observed as shown by relatively high correlation coefficients and skills during both runs 5 and 6 (Table 1).
The establishment of assimilation methods applicable tocoastal waters will enhance the accuracy of hindcast computations (and hence, the initial condition of forecasts). Besides
the assimilation methods, the present forecast model has
Fig. 14 Temperature timeseries in extra experiments.
The thin and broken curves
represent the same quantities as
those of run 6 in Fig. 9, but for
the first ensemble member (i.e.,runs 6–1). The bold curves in ato d represent the time series inextra experiments; see the text
for details

o

o

C
3

C
3

2

2

1

1

0

0

-1

-1

-2

-2
a

-3
30

10

20

Jul.
o

31

10

20

31

Aug.
2010

10

-3
30

20

3

2

2

1

1

0

0

-1

-1

-2

-2
b
20

Jul.

31

10

20

Aug.
2010

31

10

31

10

20

31

Aug.
2010

10

d

-3
20

Sept.

20

Sept.

C

3

-3

20

Jul.
o

10

10

Sept.

C

30

c

30

10

20

Jul.

31

10

20

Aug.
2010

31

10

20

Sept.

644

obtained by the computation in which the time scale taken to
restore SST in the FVCOM domain to the monthly average isdoubled (i.e., 10 days), and (d) the time series obtained by thecomputation in which the standard deviation of initial perturbations added to each forecast run is doubled (i.e., 0.2°C). The
forecast daily winds are not used in computing wind stresses
with the drag coefficients of Large and Pond (1981), but thoseobserved by ASCAT (Kako et al. 2011) are used in thisexperiment. That is to say, the present application provides us
with results using the wind stresses that are forecasted “perfectly”. Figure 14a indicates that the downscaling to the
FVCOM domain is effective in reproducing kyucho events
because the temperature fluctuations with periods shorter than
1 month are not revealed in the relatively coarse JCOPE2
analysis. It is noted that these short-term fluctuations are sensitive to the daily wind stresses (b) in comparison with both therestoring time of SST (c) and magnitude of initial perturbations(d). It is likely that accurately forecasted wind stresses with fineresolution are required to forecast kyucho events in coastal
waters under the complex orographic conditions and that thesewinds (and/or tidal currents) might be required to forecast the
behavior of small-scale eddies like those in Fig. 12.
Kyucho events accompanied by large temperature rises
are frequently forecasted during the period May throughJune when intense kyucho events are absent in the actual
ocean (Fig. 9). The forecast computations during this period
are conducted using lateral boundary conditions that passthrough areas with less Argo data. In fact, runs 5 and 6 using
lateral boundary conditions, which undergo assimilating
numerous Argo data, result in relatively high and stablecorrelation coefficients and skills between forecast and reanalysis density profiles and successfully forecast the kyucho
events actually observed in August and September. The suggestion is that one of the most efficient improvements inforecasting coastal waters is to deploy numerous Argo floats
offshore, but this improvement is beyond a scientific issue.
Acknowledgments Professor Lie-Yauw Oey and all other membersof the scientific committee provided the authors with the opportunity topresent this topic at the 3rd International Workshop of Modeling the
Ocean (IWMO-2011), which we greatly appreciated. Comments of two
anonymous reviewers are very helpful in improving the manuscript
and are appreciated. This work is supported by the Japan Society for
the Promotion of Science KAKENHI (21244073).
Open Access This article is distributed under the terms of the Creative Commons Attribution Noncommercial License which permits any
noncommercial use, distribution, and reproduction in any medium,provided the original author(s) and source are credited.

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