Intraseasonal Variability in the Indo–Paciﬁc Throughﬂow …Murray and Arief 1988; Meyers et al. 1995; Molcard et al. 1996). Several studies have attributedthistransport cycle

JULY 1999 1599Q I U E T A L .

q 1999 American Meteorological Society

Intraseasonal Variability in the Indo–Pacific Throughflow and the Regions Surroundingthe Indonesian Seas

BO QIU, MING MAO, AND YUJI KASHINO*

Department of Oceanography, University of Hawaii at Manoa, Honolulu, Hawaii

(Manuscript received 27 March 1998, in final form 15 September 1998)

ABSTRACT

Intraseasonal oscillations in sea level, sea surface temperature, and upper ocean flow field have recently beenobserved in various locations surrounding the Indonesian seas. While the observed oscillations at these locationshave similar wave periods ranging from 30 to 85 days, their forcing mechanisms can involve different dynamicprocesses. In order to clarify the dynamic processes essential for the observed intraseasonal signals, the authorsadopted in this study a fine-resolution 1½-layer reduced-gravity model and carried out a series of model ex-periments by varying coastline geometry and surface wind forcing. From these carefully designed experiments,they show that the intense 50-day oscillations observed at the entrance of Celebes Sea are a result of Rossbywave resonance in which the frequency of cyclonic eddy shedding by the retroflecting Mindanao Current matchesthat of the gravest Rossby mode of the semi-enclosed Celebes Sea basin. These 50-day oscillations of the CelebesSea have a large impact on the throughflow in the Makassar Strait and Banda Sea, but do not contributesignificantly to the throughflow changes in the Lombok, Ombai, and Timor Straits.

The observed intraseasonal signals along the Sumatra/Java coasts in the eastern Indian Ocean are dominatedby oscillations with wave periods of 50 and 85 days. The origin of these wave signals can be traced back tothe central equatorial Indian Ocean where the surface zonal wind fluctuates intraseasonally with the same waveperiods. The remotely induced coastal Kelvin waves along the Sumatra/Java coasts strongly influence the LombokStrait, but exert no direct influence upon the Ombai and Timor Straits farther to the east; the gap of the LombokStrait is found to conduit the Kelvin wave signals effectively into the Makassar Strait and the Banda Sea. Theintraseasonal signals observed in the Timor Passage have a dominant wave period of 30–35 days. The modelsimulation further suggests the presence of a second spectral peak around 85 days. Both of these intraseasonalsignals are attributable to the local, along-archipelago wind near the Timor Passage.

1. Introduction

Our understanding of the ocean circulation in the In-donesian archipelago region has improved considerablyover the past decade. Recognition that the IndonesianThroughflow (ITF) is not only crucial to the heat andfreshwater balance in the Indian Ocean but also playsan important role in the global circulation of thermoclinewater (Godfrey and Golding 1981; Piola and Gordon1984; Gordon 1986; Broecker 1991) has led to increasedinterest in this region of the World Ocean (Fig. 1). Mostof the past observational, numerical, and theoreticalstudies have focused on the transport value of the ITF,as well as its seasonal-to-interannual fluctuations. As

* Current affiliation: Japan Marine Science and Technology Center,Yokosuka, Japan.

Corresponding author address: Dr. Bo Qiu, Department of Ocean-ography, University of Hawaii at Manoa, 1000 Pope Road, Honolulu,HI 96822.E-mail: [email protected]

presented in a recent comprehensive review by Godfrey(1996), estimates for the throughflow transport rangedfrom nil to 20 Sv (Sv [ 106 m3 s21), depending on thedata and methodology used. A recent estimate based onlong-term expandable bathythermograph (XBT) obser-vations by Meyers et al. (1995) placed the meanthroughflow transport at 7 Sv for the upper 400 m ofthe water column.

The annual cycle of the ITF, with a maximum trans-port in boreal summer and a minimum in boreal winter,is well established from observations (Wyrtki 1987;Murray and Arief 1988; Meyers et al. 1995; Molcardet al. 1996). Several studies have attributed this transportcycle to the seasonal fluctuations of the Asian–Austra-lian monsoonal wind; namely, the ITF is strongest dur-ing the southeast monsoon from May to September andit is weaker during the northwest monsoon from No-vember to March (e.g., Kindle et al. 1989; Inoue andWelsh 1993; Masumoto and Yamagata 1993; Clarke andLiu 1993; Miyama et al. 1995; Yamagata et al. 1996).Interannually, the ITF transport is found to be closelyconnected to Pacific ENSO events, and the correlationis such that a smaller than normal ITF transport is found

1600 VOLUME 29J O U R N A L O F P H Y S I C A L O C E A N O G R A P H Y

FIG. 1. Topography map in the region surrounding the Indonesian archipelago (based on NOAA’sETOP05 dataset). Solid contours denote the 3000-m isobaths.

FIG. 2. Time series of velocity vectors from moored current metersdeployed at the entrance of the Celebes Sea (4.08N, 127.58E). (a)Observed velocity vectors at the 350-m and 550-m depths. (b) Ve-locity vectors after 30-to-120 day bandpass filtering. Adapted fromWatanabe et al. (1997).

in El Nino years and a larger transport in La Nina years(e.g., Kindle et al. 1989; Clarke and Liu 1994; Waj-sowicz 1994; Verschell et al. 1995; Meyers 1996; Po-temra et al. 1997). The peak-to-trough amplitude of theENSO-related transport changes is estimated to be about5 Sv (Meyers 1996).

Compared to the seasonal-to-interannual signals,throughflow variability with the intraseasonal timescalehas heretofore received less attention. Given the shallowwater depth and the complex coastline geometry of thearchipelago, short-term current fluctuations are likely tobe important for the regional mixing and water masstransformation of the ITF. This study focusing on theITF’s intraseasonal variability is motivated by severalrecent observational studies. From current meter moor-ings at the Pacific entrance of the Celebes Sea around4.08N, 127.58E, Watanabe et al. (1997) and Kashino etal. (1999) recently observed strong 50- to 60-day os-cillations in the Mindanao Current just before it entersthe Celebes Sea and forms the ‘‘western route’’ of theITF (Ffield and Gordon 1992). The observed intrasea-sonal oscillation is clearest at the 350-m depth, but alsodetectable deeper at 550 m, and persisted throughoutthe 14-month period of the mooring measurements (Fig.2). It is interesting to note that the observed intrasea-sonal fluctuations have opposite phases between thesetwo depths, indicating a baroclinic nature of the intra-seasonal signals.

Within the Indonesian seas, Ffield and Gordon (1996)analyzed the weekly SST data compiled by the Climate

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FIG. 3. (a) Time series of the first EOF mode for the alongchannelflow at 11.38S, 122.98E in the Timor Passage (from Fig. 9a of Molcardet al. 1996). (b) Power spectra of the time series shown in variancepreserving format.

Analysis Center and found the dominant SST changesin the intraseasonal frequency band there are around 60days. These 60-day signals can be detected in almostall subregions of the Indonesian seas; Ffield and Gordonsuggested that the 60-day periodicity might be a har-monic of the monthly tidal signal or reflect the atmo-spheric Madden–Julian oscillation (MJO).

Intraseasonal fluctuations have been detected at theexit side of the ITF in the Indian Ocean as well. Fromcurrent meter moorings deployed across the Timor Pas-sage, Molcard et al. (1996) observed successions of cur-rent oscillations with wave periods ranging from 20 to60 days. Their empirical orthogonal function (EOF)analysis on the alongchannel flow revealed that most ofthe 20 to 60 day variability is contained in the upper500 m of the ocean. Figure 3a shows the time series ofthe first EOF mode obtained by Molcard et al. from themooring data at 11.38S, 122.98E. The EOF mode con-tains 37% of the signal variance and has a surface-intensified, first baroclinic mode structure (for details,see Fig. 8 of Molcard et al. 1996). The power spectraof this time series show that the dominant intraseasonalsignals have energy peaks around 35 and 17 days (Fig.3b). Similar spectral peaks have also been detected byMolcard et al. (1994) in their earlier mooring obser-vations in the Timor Passage from August 1989 to July1990.

Along the Java coast, intraseasonal signals in the 40–60-day band were noted by Arief and Murray (1996) intheir analysis of tide gauge sea level data. From laggedregression analysis, Arief and Murray showed that theseobserved oscillations exhibited characteristics of baro-clinic coastal Kelvin waves originating from the equa-

torial Indian Ocean and that they had a direct impacton the observed ITF outflow in Lombok Strait. Morerecently, Bray et al. (1997) have detected energetic ed-dies and meanders in the current system south of Javawith 60-day intraseasonal changes in the surface dy-namic height field. The observed intraseasonal signalswere comparable in magnitude to the seasonal and in-terannual signals and they accounted for much of thevariation in water mass properties between hydrographiccruises.

It is worth noting that intraseasonal signals of 40–60days are also present in some of the simulation modelsfocusing on either the global ocean circulation or theregional circulation in the tropical Pacific westernboundary and the Indonesian archipelago. For example,Ponte and Gutzler (1992) analyzed the Semtner andChervin (1992) eddy-resolving general circulation mod-el output and found the presence of energetic 40–60day oscillations in both the western equatorial Pacificand the eastern equatorial Indian Oceans. Similarly, in-traseasonal variability in the Mindanao Current alongthe Philippine coast has been identified in regional mod-eling studies by Inoue and Welsh (1993, see their Fig.10) and by Qiu and Lukas (1996, their Fig. 12b). Asthese modeling studies were mainly concerned with thelower-frequency (annual to interannual) changes of theocean circulation, a thorough investigation focusing onthe dynamic processes underlying the intraseasonal var-iability is lacking.

Understanding the intraseasonal variability in the re-gion surrounding the Indonesian archipelago is complexfor several reasons. First, this region is where the MJOhas its strongest surface wind signals (for a recent re-view of the observational aspects of the MJOs, see Mad-den and Julian 1994). A question arising immediatelyis to what extent the observed intraseasonal signals inthe ocean are a consequence of direct atmospheric forc-ing. Second, the Indonesian archipelago is located inpathways of equatorial and coastal waveguides; as aresult, ocean circulation is subject to regional surfacewind forcing as well as remote surface wind forcing.Third, the complicated coastline geometry in the region,when interacting with the seasonally varying through-flow, can both regulate and enhance current fluctuationsin the intraseasonal frequency band.

The objective of this study is to use a fine-resolution,1½-layer reduced-gravity model forced by the observedwind to clarify the nature and causes of the intraseasonalsignals found in the aforementioned observational stud-ies. Though simple in its formulation, the 1½-layer re-duced-gravity model has been used successfully in thepast to simulate the tropical and subtropical circulationsin the Pacific and Indian Oceans (e.g., Kindle et al. 1989;Woodberry et al. 1989; Hurlburt et al. 1989; Inoue andWelsh 1993; Verschell et al. 1995; among others). It isworth emphasizing that the reduced-gravity modeladopted in this study contains the essential physics forreproducing the intraseasonal signals similar to the ob-


servations. Through a series of model experiments withdifferent surface wind forcing and coastal geometries,we will address the three issues listed above that arerelevant to the intraseasonal signals in the Indonesianarchipelago regions.

The presentation of this paper is organized as follows.In section 2, we start with a brief description of thenumerical model. Section 3 focuses on the simulatedITF’s variability: its seasonal and intraseasonal signalsand its comparison with available observations. In sec-tion 4, we will explore the physics underlying the ob-served and modeled intraseasonal variability with anemphasis on the Pacific entrance region of the ITF. In-traseasonal variability of the throughflow in the IndianOcean outflow region is investigated in section 5. Sec-tion 6 summarizes the results from the present study.

2. The model

The numerical model used in this study is a 1½-layerreduced-gravity model that incorporates the mixed layerphysics of Kraus and Turner (1967). As the model’sdynamics and thermodynamics closely follow those de-scribed by McCreary and Kundu (1989), only a concisedescription is included below. Dynamically, the modelconsists of an active upper layer and an underlying in-finitely deep abyssal layer. Equations governing the mo-tion in the upper layer are

]u t21 u · =u 1 f k 3 u 5 2=p 1 1 A ¹ u, (1)h]t r ho

]h21 = · (hu) 5 K ¹ h 1 w , (2)h e]t

where u is the velocity vector in the upper layer, h isthe upper-layer thickness, k is a unit vector in the ver-tical direction, Ah (Kh) is the coefficient of the horizontaleddy viscosity (diffusivity), f is the Coriolis parameter,t is the surface wind stress vector, and ro is the referencewater density. The entrainment velocity we in Eq. (2)is given by

w , h . hs mw 5 (3)e 5w 1 w , h 5 h ,s K m

where hm is the thickness of the surface mixed layer andws denotes the shear entrainment and is operative if hbecomes less than a prescribed ‘‘entrainment depth’’ He:

2(H 2 h) /t H , h # He e e ew 5s 50, h . H ,e

where te is a specified relaxation time. In Eq. (3), wK

denotes the Kraus and Turner entrainment due to windstirring and surface cooling (for details, see McCrearyand Kundu 1989).

Within the dynamic upper layer, a surface mixed layerof thickness hm and temperature Tm exists above a fossil

sublayer of thickness hf ([h 2 hm) and temperature Tf .By requiring the horizontal pressure gradient to vanishin the abyssal layer, we can express the =p term in Eq.(1) associated with the horizontal temperature changesin the upper layer as follows:

1=p 5 ag=(T 2 T )h 2 agh=T,d 2

where a is the thermal expansion coefficient, g is thegravity constant, T 5 (hmTm 1 hf Tf )/h is the verticallyaveraged temperature in the upper layer, and Td is thetemperature of the abyssal ocean.

Equations governing the temporal evolution of themixed layer depth and the mixed layer and fossil layertemperatures are

]hm 21 = · (h u) 5 K ¹ h 1 w , (4)m h m K]t

]T Qm 21 u · =T 5 K ¹ T 1m h m]t r c ho p m

1 entrainment, (5)

]Tf 21 u · =T 5 K ¹ T 1 entrainment, (6)f h f]t

where Q is surface heat flux and cp is the specific heatof seawater. The detailed expressions for the entrain-ment terms in Eqs. (5) and (6) involve wk, ws, and thetemperature differences across the layers. For the nu-merical implementation of these terms, readers are re-ferred to McCreary and Kundu (1989).

The model domain includes all longitudes and ex-tends latitudinally from 658S to 358N. The model hasrealistic coastline geometry that is determined by the200-m depth contour. To adequately resolve the detailedcoastline features surrounding the Indonesian archipel-ago, the model grid has the finest resolution of 1⁄68 inlatitude and 1⁄68 in longitude in the region from 88S to88N, 1188 to 1308E. The grid size increases graduallyaway from this focus region to 18 in latitude and 18 inlongitude.

Equations (1)–(6) are solved in finite difference formusing the energy-conserving scheme proposed by Sa-dourney (1975). The Arakawa C-grid is used in definingthe staggered positions for the dependent variables u,y , and h (Arakawa and Lamb 1977). Temperatures aredefined at the point of h. Along the model’s open oceanboundaries (in the North Pacific and North Atlanticalong 358N), no-normal flow and free-slip conditionsare used. No-normal-flow and non-slip conditions areused along the coast and marginal seas (depth ,200m). The horizontal eddy viscosity/diffusivity coefficientis 400 m2 s21 in the model’s tropical region. The Ah

(Kh) value increases gradually to 2500 m2 s21 at higherlatitudes where the model grid size is coarse. Values forthe other parameters used in the model simulation arelisted in Table 1.

JULY 1999 1603Q I U E T A L .

TABLE 1. Parameter values for the base model run.

Parameter Value

Initial upper-layer thicknessMinimum upper-layer thicknessInitial mixed layer depthMinimum mixed layer depthGravity constant, gThermal expansion coefficient aInitial mixed layer temperatureInitial fossil layer temperatureAbyssal layer temperature Td

Relaxation timescale for Tm, RT

Entrainment depth He

Entrainment timescale te

Horizontal eddy viscocity Ah

Horizontal eddy diffusivity Kh

300 m80 m75 m30 m9.8 m s22

0.000258C21

258C158C

28C40 days80 m1 day

400 m2 s21

400 m2 s21

The model ocean, which is initially at rest, is spunup by the monthly, climatological wind of Hellermanand Rosenstein (1983). For the surface thermal forcing,we followed the formulation proposed by Barnier et al.(1995):

climQ Q 1clim5 1 (T 2 T ); (7)mr c h r c h Ro p m o p m T

namely, it contains a climatological heat flux (Qclim) termand a correction term proportional to the difference be-tween the climatological SST (T clim) and the model pre-dicted mixed layer temperature. In Eq. (7), RT is therelaxation timescale with a value of 40 days. For theQclim and T clim fields used in the model simulation, weadopted the COADS monthly climatological dataset ofDaSilva et al. (1994).

In addition to the base model case described above,we carried out other model experiments in which weeither changed the model’s coastline configuration orforced the model ocean using the daily ECMWF surfacewind data. These additional experiments are conductedin order to test hypotheses on the generation mecha-nisms of the 40–60 day signals found around the In-donesian archipelago. The details of these experimentswill be described in sections 4 and 5. For all the modelcases, we integrated the governing equations till thetemperature and flow fields reached statistical equilib-rium. Thereafter, an additional 4-yr integration was car-ried out and the results from these 4 years are used inthe following analyses.

3. Results of the base model case

In this section, we examine the results of the basemodel case forced by the monthly climatological surfacewind and heat flux data. The focus will be on bothseasonal and intraseasonal signals in regions surround-ing the Indonesian archipelago. A discussion of the sea-sonal variability helps validate model results throughcomparison with existing studies; it also provides a con-text for our following investigation of the intraseasonalsignals.

a. Mean state and seasonal variability

Figure 4 shows the annually averaged upper-layerflow field derived from the base model case in the regionsurrounding the Indonesian archipelago. The flow pat-tern agrees well with that derived from observations(e.g., Lukas et al. 1991) and it is also similar to themean flow patterns obtained in past modeling studies(e.g., Kindle et al. 1989; Inoue and Welsh 1993; Mas-umoto and Yamagata 1993; Miyama et al. 1995). Brief-ly, the Pacific-origin waters move to the Indian Oceanfollowing two major routes. The ‘‘western route’’ beginsas a southwestward branch of the Mindanao Current,which bifurcates at the entrance of the Celebes Sea andpasses through the Makassar Strait. One part enters theIndian Ocean through the Lombok Strait; the other partveers eastward through the Flores Sea to reach the Ban-da Sea. In the Banda Sea, part of this flow recirculatesback northward to merge with the North EquatorialCountercurrent (NECC) east of the Celebes Sea. Theremaining part of the ‘‘western route’’ flow continueseastward in the Banda Sea and is joined by the weak‘‘eastern route’’ flow coming directly from the norththrough the Halmahera Sea. Together, they enter theIndian Ocean through the Ombai Strait and the TimorPassage (see Fig. 1).

Figure 5 shows the time series of the modeled trans-port through the Lombok Strait, the Ombai Strait, andthe Timor Passage. The total ITF transport through thesethree straits is given in Fig. 5d. The mean ITF transportfrom our model is 6.9 Sv, which is in the mid range ofthe previous indirect estimates (see Table 1 of Godfrey1996). This value for the mean ITF is close to the recentestimate of 7 Sv by Meyers et al. (1995) based on thelong-term XBT measurements between Java and Aus-tralia. The annual cycle of the modeled ITF has a min-imum transport in January/February and a broad max-imum transport from June to November. The phase ofthis annual cycle agrees well with the annual cycle ofthe ITF transport inferred from the sea level differencebetween Davao and Darwin by Wyrtki (1987).

Among the three straits contributing to the ITF, Fig.5a shows that Lombok Strait carries a mean transportof 3.0 Sv, which is 43% of the mean total ITF. Thistransport value is somewhat larger than 1.7 Sv estimatedby Murray and Arief (1988) based on in situ currentmeter measurements. Their measured ITF transportthrough Lombok Strait fluctuated from near zero in Feb-ruary to about 5 Sv in August, a seasonal signal alsoevident in the model result of Fig. 5a. The Ombai Straitcarries a mean transport of 1.1 Sv (16% of the meantotal ITF) and its annual cycle is similar in phase withthat in Lombok Strait. The Timor Passage in our modelcarries a mean transport of 2.8 Sv; this value is closeto 3.5 Sv derived by Cresswell et al. (1993) for theupper 350 m layer transport in the Timor Passage basedon Pegasus and ADCP measurements.

In the India Ocean south of the Indonesian archipel-


FIG. 4. Upper-layer mean flow pattern in the vicinity of the Indonesian archipelago. The flow pattern is derived froma global 1½-layer reduced-gravity model (638S–358N) forced by the monthly climatological wind (Hellerman and Ro-senstein 1983) and surface heat flux (da Silva et al. 1994). Areas shallower than 200 m are considered land in the model.

ago, the combined ITF outflows from the three straitsare incorporated into the South Equatorial Current(SEC), which flows westward in the zonal band between98 and 148S (see Fig. 4). The annual cycle of the mod-eled SEC has a maximum transport in August/Septem-ber and a minimum in April (Fig. 6a); it agrees favorablywith the SEC’s annual cycle observed by Meyers et al.(1995) from the repeat XBT measurements betweenJava and Australia. Notice that a weak eastward flowingSouth Java Current exists along the southern coast ofJava in the mean flow field of Fig. 4. The modeled SouthJava Current, defined here as a zonal flow between 98Sand the Java coast, has a clear semiannual variation withmaximum eastward flow appearing in spring and fall(Fig. 6b). This semiannual signal of the South Java Cur-rent is consistent with the observations reported byClarke and Liu (1993) and Meyers et al. (1995).

Finally, the mean flow pattern in the low-latitudewestern Pacific is well established from observations(e.g., Lukas et al. 1991; Tsuchiya et al. 1990). The modelresult shown in Fig. 4 is again in good agreement withthese studies. Major circulation features here includebifurcation of the North Equatorial Current (NEC) at148N along the Mindanao coast to form the Kuroshioand the Mindanao Current, confluence of the Mindanao

Current and the South Equatorial Current to form theeastward flowing North Equatorial Countercurrent(NECC), and the presence of the quasi-permanent Min-danao and Halmahera eddies (centered at 78N, 1308Eand 38N, 130.58E, respectively). As it is not the focusof this study, the detailed seasonal variability of thesecirculation features will not be presented here.

b. Intraseasonal variability

Given the newly available current meter data shownin Fig. 2, it is interesting to first look into the modeledvelocity field at the same geographical location (4.08N,127.58E). Figure 7a shows the time series of the me-ridional velocity obtained in the base model case. Here,the y component of the velocity is selected because itshowed the clearest intraseasonal signal in the obser-vations (Watanabe et al. 1997). Figure 7b compares thepower spectrum from the modeled time series (Fig. 7a)with that from the observations. While the rms ampli-tude of the observed y velocity is about one order ofmagnitude smaller than the model’s (recall that the ob-servation was made at the 350-m depth, whereas Fig.7a represents the averaged y velocity in the upper 270-mlayer), the dominance of the intraseasonal signals with

JULY 1999 1605Q I U E T A L .

FIG. 5. Time series of model transport (dashed lines) through (a)the Lombok Strait, (b) the Ombai Strait, and (c) the Timor Passageover a 2-yr period. (d) The time series of the total throughflow trans-port. Base model result driven by climatological wind and heat fluxdata. Solid lines are the results after applying a 120-day low-passfilter.

FIG. 6. Time series of transport of (a) the South Equatorial Currentand (b) the South Java Current along 1048E in the eastern IndianOcean. Here, SEC is defined as the zonal flow between 158 and 98Sand SJC is defined as the zonal flow between 98S and the Java coast.

FIG. 7. (a) Time series of modeled meridional velocity at the en-trance of the Celebes Sea (4.08N, 127.58E) over a 3-yr period. (b)Power spectra of the meridional velocity time series from the basemodel (solid line) and from the current meter measurement at a 350-mdepth (dashed line; cf. Fig. 2). Spectra are plotted in variance pre-serving format.

periods around 50 days is obvious in both model andobservations.

Since the climatological monthly wind data are usedto force the base model, the direct model response tothe wind forcing is limited to timescales of 2 monthsand longer. The result of Fig. 7, thus, suggests that theinternal dynamics of the ocean alone can possibly ex-plain the intraseasonal signals observed at the Pacificentrance of the Indonesian seas (Fig. 2). This result perse, however, cannot be used to dismiss the possible rolesplayed by the external high-frequency wind forcing. Todo so requires a comparison with a model run that isforced by surface wind including high frequency sig-nals. Another question related to Fig. 7 is what oceandynamics is responsible for determining the predomi-nant timescale of the intraseasonal signals. In otherwords, why is the 50-day oscillation being preferentially


FIG. 8. Ratio of the eddy kinetic energy in the 30–60 day frequency band versus the total eddy kineticenergy from the base model run. Light-shaded areas denote the ratio greater than 5% and dark-shaded areasdenote the ratio greater than 25%.

selected near the entrance of the Celebes Sea? Thesetwo questions will be addressed in section 4.

Notice that areas with significant intraseasonal signalsare not only confined to the Celebes Sea. As presentedin Fig. 8, intraseasonal variability with the eddy kineticenergy ratio greater than 5% can be found in most ofthe low-latitude western Pacific Ocean and the Indo-nesian seas. Here, the energy ratio is defined as the eddykinetic energy in the 30–60 day frequency band versusthat over the whole frequency band (i.e., the total eddykinetic energy). Particularly large intraseasonal signals,with the eddy kinetic energy ratio greater than 25%, arepresent in three areas: the Celebes Sea, the Banda Sea,and the area of the Mindanao eddy. One interestingaspect revealed by Fig. 8 is that a part of the intrasea-sonal signals in the Indonesian seas is able to ‘‘leak’’southward along the northeast coast of Australia viabaroclinic coastal Kelvin waves. A manifestation of thisleakage can be also seen in Fig. 5 in which high-fre-quency signals are apparent in the time series of thetransport through Timor Passage. Details of the intra-seasonal signals in Timor Passage will be discussed insection 5b.

In the eastern Indian Ocean away from the Australiacoast, Fig. 8 shows that the intraseasonal signals arealmost nonexistent. This base model result is quite dif-ferent from available observations. For example, Figs.9a and 9b show the sea level time series measured atthe tide gauge stations at Benoa (8.78S, 115.28E) nearthe Lombok Strait and at Christmas Island (10.48S,105.78E). As indicated in Fig. 9c, intraseasonal signalswith a dominant spectral peak around 50–60 days and

a secondary peak around 85 days are present at both ofthese locations. Clearly, these intraseasonal signals andthose described recently by Bray et al. (1997) are in-duced by mechanisms that are missing from our basemodel case. An in-depth examination into the intrasea-sonal variability in the outflow region of the ITF willbe conducted in section 5.

4. Intraseasonal variability in the low-latitudewestern Pacific

The base model result of section 3 revealed that theinternal dynamics of the ocean alone can generate sig-nificant intraseasonal variability in the low-latitudewestern Pacific Ocean and within the Indonesian seas.A question arising naturally is to what extent the high-frequency wind forcing, which is absent in the Heller-man and Rosenstein (1983) climatological wind data,can modify the intraseasonal signals modeled in theseregions. To address this question, we carried out anadditional model experiment in which we forced themodel ocean by daily averaged, 1000-mb wind data ofthe European Centre for Medium-Range Weather Fore-casts (ECMWF). For this ‘‘daily model case,’’ we usedthe base model result as initial condition and extendedthe model integration over a 10-yr period using theavailable wind data from 1980 to 1989. The ensuingdiscussions are based on the model output from 1985to 1989.

Figure 10 shows the time series and power spectrumof the meridional velocity at the mooring site of theCelebes Sea from the daily model case. Not surprisingly,

JULY 1999 1607Q I U E T A L .

FIG. 9. Time series of the sea level anomalies observed at (a) Benoaand (b) Christmas tide gauge stations in the eastern Indian Ocean.(c) Power spectra of the Benoa and Christmas sea level time seriesin variance preserving format.

the energy level in the frequency band from 30 to 100days is generally higher in the daily model case than inthe base case (cf. Fig. 7). Like in the base model case,however, the dominance of the near-50-day oscillationis again obvious. It is interesting to note that a secondaryenergy peak exists with a wave period of about 100days in the power spectrum of the daily model result.A similar energy peak is discernible in the power spec-trum of the observed velocity time series (Fig. 2), al-though the observed 100-day signals appear to havemuch less energy compared to the 50-day signals thanthose in the daily model result. As far as the dominant50-day signals are concerned, the comparison betweenthe base and daily model results clearly suggests thatthe high-frequency surface wind forcing is not essential.In other words, the intraseasonal signals presented inFig. 2 are determined by internal ocean dynamics.

a. Dynamic role of the Celebes Sea basin

To explore the ocean dynamics important for the ob-served intraseasonal signals, it is helpful to first examinethe detailed circulation patterns in the Celebes Sea. Fig-ure 11 shows a sequence of snapshots of the upper-layerthickness field from the base model output at 10-dayintervals. Figure 11a shows a fully developed cycloniceddy close to break off from the Mindanao Current. InFig. 11b, this cyclonic eddy breaks off from the Min-danao Current and has a diameter of d 5 450 km. Basedon conservation of potential vorticity, Hurlburt andThompson (1980) showed that the size of a cutoff eddyfrom a boundary current is given by d 5 2(Vc/b)1/2,where Vc is the core speed of the boundary current andb is the y derivative of the Coriolis parameter. With Vc

5 1.2 m s21 estimated from the modeled MindanaoCurrent and b 5 2.3 3 10211 s21 m21, the theory predictsd 5 457 km, a value matching well with the size of themodeled cutoff eddy shown in Fig. 11b. In Fig. 11c,this cutoff eddy drifts westward and subsequently dis-appears from the Celebes Sea after it reaches the westernboundary (Fig. 11d). Meanwhile a new cyclonic eddybegins to form in the Mindanao Current. This new eddyreaches a breaking-off state similar to the previous eddyshown in Fig. 11a with a time separation of 50 days(Fig. 11f).

Figure 12 shows the x–t diagram of the modeled up-per-layer thickness anomalies along the center latitude(48N) of the Celebes Sea. It indicates that the eddy shed-ding event depicted in Fig. 11 takes place regularlyabout every 50 days. The westward propagating speedof the cutoff eddies based on the anomaly slopes shownin Fig. 12 is about 0.21 m s21. This propagating speedcan be compared with the phase speed of dispersivebaroclinic Rossby waves:

bc 5 2 , (8)px 2 2 2k 1 l 1 f /g9h

with k 5 l 5 p/d. Using d 5 450 km, g9h 5 9.1 m2

s22, and f 5 1.02 3 1025 s21, we have cpx 5 20.21 ms21, suggesting the westward propagation of the cutoffeddies is constrained by the baroclinic Rossby wavedynamics. That the cutoff eddies tend to propagate west-ward at the phase speed of dispersive baroclinic Rossbywaves is also true for the Loop Current eddies in theGulf of Mexico (see Hurlburt and Thompson 1980).Notice that the presence of the cyclonic eddies cut offfrom the Mindanao Current can be seen in some of thesurface drifter trajectories observed in the Celebes Sea.As depicted in Fig. 2 of Lukas et al. (1991), of the fourdrifters that entered the Celebes Sea, two looped cy-clonically before entering Makassar Strait, one showedsign of cyclonic looping (but demised prematurely), andone passed through the Celebes Sea without looping.

While the eddy shedding events are clearly respon-sible for the near-50-day signals in the Celebes Sea, weemphasize that the basin size of the Celebes Sea is an-other critical parameter for the intraseasonal signals in


FIG. 10. (a) Time series of the meridional velocity at the entranceof the Celebes Sea (408N, 127.58E). Daily model result. (b) Powerspectra of the meridional velocity time series from the daily model(solid line) and from the current meter measurement at a 350-m depth(dashed line; cf. Fig. 2). Spectra are plotted in variance preservingformat.

the low-latitude Pacific Ocean and the Indonesian seas.For a rectangular basin with a zonal length of Lx and ameridional length of Ly, the intrinsic frequency for thebasin Rossby modes is given by

21/22 2 2 2 2b n p m p fv 5 1 1 , (9)

2 21 22 L L g9hx y

where n and m are mode numbers in the x and y direc-tions (see LeBlond and Mysak 1978, 299–302). Forvalues appropriate for the Celebes Sea, Lx 5 720 km,Ly 5 500 km, g9h 5 9.1 m2 s22, f 5 1.02 3 1025 s21,and b 5 2.3 3 10211 s21 m21, the gravest basin Rossbymode (n 5 m 5 1) has an intrinsic wave period of 52.8days. This close match between the period of the eddyshedding from the Mindanao Current and the intrinsicwave period of the Celebes Sea basin suggests that res-onance could have played an important role in the resultspresented above. To test this hypothesis, we conductedtwo model experiments in which we artificially alteredthe basin size of the Celebes Sea, while keeping all otherconditions the same as the base model case. In the ‘‘largeCS case,’’ we enlarged the basin size by shifting Min-ahassa Peninsula southward by 2.08 latitude (see thecheckered block in Fig. 13b), whereas in the ‘‘small CS

case,’’ we reduced the basin size of the Celebes Sea byshifting Minahassa Peninsula northward by 1.58 latitude(see the checkered block in Fig. 13c). This effectivelyshifts the intrinsic wave period of the Celebes Sea to43.7 days in the large SC case and to 68.6 days in thesmall CS case, respectively.

Figure 13b and 13c show the 30–60 day bandpassededdy kinetic energy distributions from the large andsmall CS cases. Their difference from the base modelcase shown in Fig. 13a is striking. In the large CS case,not only is the intraseasonal eddy kinetic energy peakin the Celebes Sea no longer present, but also the off-shore intraseasonal energy peak associated with theMindanao eddy and the NECC is greatly reduced. Thisdrastic reduction in intraseasonal eddy kinetic energyin the large CS case is due to the fact that the MindanaoCurrent in this case intrudes into the Celebes Sea andforms a relatively stable cyclonic circulation that oc-cupies the entire enlarged Celebes Sea (not shown). Inthe small CS case, on the other hand, the intrusion ofthe Mindanao Current into the Celebes Sea is dynam-ically prohibited, as the Celebes Sea width in this case(335 km) is narrower than the cutoff eddy diameter (450km). The intraseasonal eddy kinetic energy associatedwith the Mindanao eddy and the NECC is slightly higherin the small CS case than in the base model case. Inshort, the model result of Fig. 13 demonstrates that theintense 50-day oscillation observed at the entrance ofthe Celebes Sea (Fig. 2) is a result of Rossby waveresonance, in which the frequency of cyclonic eddyshedding by the retroflecting Mindanao Current matchesthat of the gravest Rossby mode in the Celebes Seabasin.

b. Impact of Celebes Sea–originated 50-dayoscillations

One consequence of the Rossby wave resonance inthe Celebes Sea is that the western route ITF is beingperiodically ‘‘perturbed’’ at the 50-day timescale. Thisis obvious in Fig. 14, which shows the throughflowtransport through the Makassar Strait from the basemodel run. It is interesting to note that the influence ofthis 50-day oscillation reaches the Banda Sea (a regionwhere the modeled intraseasonal eddy kinetic energyratio is relatively high; see Fig. 8) and the Timor Pas-sage, but does not impact the Lombok and Ombai Straitssignificantly (see Figs. 5a–c). This may appear para-doxical as both the Lombok and Ombai Straits are lo-cated geographically closer to the Makassar Strait thanare the Banda Sea and the Timor Passage. To clarifythis point, we conducted a simple model experiment, inwhich we locally excited 50-day oscillations in the Cel-ebes Sea by imposing an oscillatory surface wind in theCelebes Sea basin. Figure 15a shows the distribution ofthe upper-layer thickness variance derived from this ide-alized model run. Following the sequence of the modeloutput reveals that the Celebes Sea–originated 50-day

JULY 1999 1609Q I U E T A L .

FIG. 11. Snapshots of the upper-layer thickness field from the base model output. Unit in meters. Each snapshot is separated by 10 days.


FIG. 12. Time–longitude diagram of the upper-layer thicknessanomalies from the base model run along the center latitude (48N)of the Celebes Sea. Unit in meters.

FIG. 13. Distributions of the eddy kinetic energy in the intraseasonal(30–60 day) frequency band from (a) the base model case, (b) thelarge Celebes Sea (CS) case, and (c) the small CS case. Unit in m2

s22. The checkered blocks in (b) and (c) denote the Minahassa Pen-insula shifted meridionally to test the Rossby wave resonance theory.

oscillation affects the surrounding waters by way ofcoastal Kelvin waves. After passing through the Ma-kassar Strait, the intraseasonal Kelvin wave signal fol-lows the coast of Sulawesi, loops around the Banda Sea,and part of it leaks into the Indian Ocean through theTimor Passage along the shallow continental slope westof Australia.

Examining the flow transport through the variousstraits in the Indonesian seas (Fig. 15b) shows that thetransport peak in the Timor Passage lags about 12 daysbehind that in the Makassar Strait, the time it takes forthe coastal Kelvin waves to travel from the MakassarStrait to the Timor Passage. The amplitude of the flowthrough the Timor Passage is about 30% of that throughthe Makassar Strait. As the coastal Kelvin waves loop

JULY 1999 1611Q I U E T A L .

FIG. 14. Time series of transport (dashed line) through the MakassarStrait from the base model output. Solid line shows the result afterapplying a 120-day low-pass filter.

FIG. 15. (a) Distribution of the upper-layer thickness variance froma model driven by localized surface wind forcing. The model oceanhas an initial constant depth of 300 m and is forced by an oscillatoryzonal wind stress patch centered in the Celebes Sea: t x 5 to cos[p (x2 xc)/Lx] exp[2y2/ sin(vt), 2Lx/2 # x # Lx/2; t x 5 0 otherwise,22L ]y

where xc 5 122.58E, Lx 5 88 long, yc 5 3.08N, Ly 5 48 lat, v 5 2p/50 days, and t o 5 0.2 N m22. Shaded areas denote variance values.2 m2. (b) Time series of flow transport through the four straits inthis idealized model run.

around the Banda Sea, a small portion of the 50-daysignal also reaches the Ombai Strait. The wave ampli-tude there, however, is further attenuated as comparedto the amplitude in the Timor Passage. Little wave en-ergy appears to reach the Lombok Strait, which is lo-cated farther to the west.

In concluding this section, we note that the intrasea-sonal signals originating in the low-latitude western Pa-cific boundary affect the ITF preferentially through theTimor Passage. For the observed throughflow fluctua-tions in the Timor Passage, however, it will become clearin section 5b that the intraseasonal along-archipelagowind in the eastern Indian Ocean plays a more importantrole than do the remote wave signals from the CelebesSea.

5. Intraseasonal variability in the eastern IndianOcean and the Indonesian seas

On the Indian Ocean side of the Indonesian seas, awayfrom the Australia coast, the base model result of Fig.8 shows that the intraseasonal signals are essentiallynonexistent. This suggests that the intraseasonal signalsobserved in this region, such as those presented in Fig.9, must be induced by high-frequency winds missing inthe climatological wind dataset. Indeed, forcing themodel ocean using the daily ECMWF wind data (thedaily model case) reveals that the eddy kinetic energyratio in the intraseasonal frequency band increases sig-nificantly in the eastern Indian Ocean (Fig. 16). Theeddy kinetic energy ratio along the Java coast, for ex-ample, increased from ,0.5% in the base model caseof Fig. 8 to 15%–20% in Fig. 16.

a. Local versus remote wind forcing

A detailed comparison can be made at Benoa whereobserved sea level data are available (see Fig. 9). Figure17a shows a 3-yr time series of the upper-layer thicknessanomalies at Benoa from the daily model run. In theintraseasonal frequency band, the modeled time seriesis dominated by oscillations with periods around 50 and85 days (the solid line in Fig. 17c), resembling the char-acteristics of the observed sea level signals. Note thatthe modeled energy peak around 85 days is comparable

in magnitude with the 50-day peak, whereas it is weakerthan the 50-day peak in the observations. While theyare clearly wind-forced, these intraseasonal signals candynamically be driven either by local winds along theJava coast or by the remote wind along the equatorialIndian Ocean. Indeed, several investigators in the pasthave suggested the remote equatorial wind forcing isresponsible for exciting the intraseasonal oscillations inthe ITF outflow regions (e.g., Arief and Murray 1996;Molcard et al. 1996).

To evaluate the relative importance of the local windversus the remote wind in forcing the intraseasonal sig-nals along the Java coast, we carried out an additionalmodel experiment in which we forced the model in theeastern Indian Ocean (east of 1008E) and the Indonesianseas by the daily ECMWF wind data and the rest of theworld ocean by the climatological Hellerman and Ro-


FIG. 16. Ratio of the eddy kinetic energy in the 30–60 day frequency band versus the total eddy kineticenergy from the daily model run. Light-shaded areas denote the ratio greater than 5% and dark-shaded areasdenote the ratio greater than 25%.

senstein (1983) wind data. This model experiment ef-fectively removes all influences of the intraseasonalwind forcing along the equatorial Indian Ocean and isreferred to as the ‘‘local model case’’ below. The solidline in Fig. 17b shows the time series of the upper-layerthickness anomalies at Benoa obtained from this localmodel run. Compared to Fig. 17a, the amplitude of theintraseasonal signals in this time series is greatly re-duced. Also, the 50-day spectral peak computed fromthis time series is no longer as distinctive as that fromthe daily model result (see Fig. 17c). While the com-parison between the local model time series and the basemodel time series (the dashed line in Fig. 17b) doesindicate that the local wind along the Java coast inducesthe intraseasonal signals to some extent, our above mod-el results indicate that it is the remote wind forcing alongthe equatorial Indian Ocean that determines the energylevel of the intraseasonal signals along the Java coast.

Given the importance of the remote equatorial windin exciting the intraseasonal signals along the Java coast,we next examined the characteristics of the surface windalong the equatorial Indian Ocean. Figure 18 shows thepower spectra of the zonal wind stress along the equatorof the Indian Ocean in the intraseasonal frequency band.Not surprisingly, spectral peaks indeed exist around 50and 85 days in the zonal wind data, which correspondto the intraseasonal spectral peaks of the oceanic re-sponse at Benoa (see Fig. 9c). Notice that the largestintraseasonal wind signals are located in the central In-dian Ocean from 708 to 908E and that the 50- and 85-day signals are more energetic in the zonal componentof the wind stress data than in the meridional component

(not shown). In the segments of 508–608E and 908–1008E near the equatorial land boundaries, the windstress data show no clear spectral peaks in bands withwave periods longer than 40 days.

b. Intraseasonal signals in through-strait flows

As the surface wind in the central equatorial IndianOcean fluctuates intraseasonally, it generates eastwardpropagating equatorial Kelvin waves. Upon reaching thecoast of Sumatra, these equatorial waves continue tomove poleward in the form of coastal Kelvin waves.The intraseasonal signals at Benoa as shown in Fig. 17aare largely due to the passage of these coastal Kelvinwaves. Notice that the Lombok Strait exists next toBenoa and is the first deep strait a poleward-movingcoastal Kelvin wave would encounter along the Indo-nesian archipelago. Does this coastline gap of the Lom-bok Strait interrupt the poleward movement of the re-motely forced coastal Kelvin waves? Interestingly, un-like the intraseasonal signals at Benoa, the moored cur-rent meter data obtained at the Timor Passage byMolcard et al. (see Fig. 3) revealed no clear spectralpeaks around the 50- and 85-day periods. This suggeststhat the Lombok Strait may play an important role inpreventing the remotely forced coastal Kelvin wavesfrom effectively influencing the downstream polewardregions.

To quantitatively access the influence of the remotelyforced coastal Kelvin waves upon the variability in thedownstream Ombai and Timor Straits, we carried out amodel experiment similar to that presented in Fig. 15

JULY 1999 1613Q I U E T A L .

FIG. 17. Time series of modeled sea level anomalies at Benoa: (a)the daily model result and (b) the local (solid line) and base model(dashed line) results. Panel (c) shows the power spectra of the twotime series in variance preserving format. Model day 0 here corre-sponds to 1 January 1985.

FIG. 18. Power spectra of the zonal wind stress in the intraseasonalfrequency band (10–150 days) along the equator from 508 to 1008E.The power spectra are based on the daily 1000-mbar ECMWF winddata and are averaged in five 108-wide segments. The power spectrafor each segment are shown with an offset of 0.3 3 1024 N2 m24.

except, in this case, we imposed the oscillatory windforcing in a localized area centered on the equator and908E. Figure 19a shows the distribution of the upper-layer thickness variance derived from this model ex-periment; the time series of the transport through thefour straits of our interest are presented in Fig. 19b. Aclose look at the paths of the Kelvin wave signals (notshown here) reveals that as the poleward propagatingcoastal Kelvin waves reach the gap of the LombokStrait,1 the majority of the wave signals turn northwardentering the Makassar Strait. As these waves moveequatorward, their horizontal scale increases due to de-creasing f. In the narrow Makassar Strait, the coastalKelvin waves become wide enough to reach the westcoast of Sulawesi and a portion of the wave signals isable to propagate cyclonically around the coast of Su-

1 The width of the Lombok Strait is 40 km, which is about one-third of the size of the local, first-mode baroclinic Rossby radius.

lawesi, circulate the Banda Sea, and eventually reachthe Timor Strait. Because of this indirect route, the Om-bai Strait is now on the downstream side of the TimorPassage, and this is why the wave amplitude detectedin the Ombai Strait in Fig. 19b is smaller than that inthe Timor Passage. For both of these two straits, Fig.19b demonstrates that the influence from the coastalKelvin waves remotely forced in the equatorial IndianOcean is small.

The result from this idealized model experiment alsoprovides a base for understanding the intraseasonal ITFvariability obtained in the daily model case. Figure 20shows the transport time series through the Lombok,Ombai, Timor, and Makassar Straits from the daily mod-el run. As indicated in Fig. 21a, the characteristics ofthe intraseasonal signals in the Lombok and MakassarStraits are similar, both having dominant spectral peaksaround 50 and 85 days. In light of the above discussion,this is understandable because the 50- and 85-day sig-nals are remotely excited in the central equatorial IndianOcean and they can intrude largely unobstructedly intothe Lombok Strait and reach the Makassar Strait. Thatthe energy levels of the 50- and 85-day signals in Fig.21a are higher in the Makassar Strait than in the LombokStrait is due to the additional, intraseasonal signal inputfrom the Celebes Sea (see the detailed discussion insection 4). Recall that the Celebes Sea–originated in-


FIG. 19. Same as Fig. 15 except for the oscillatory zonal windstress patch in this case is centered in the equatorial eastern IndianOcean, namely, xc 5 90.08E, and yc 5 08.

FIG. 20. Time series of the transport through (a) the Lombok Strait,(b) the Ombai Strait, (c) the Timor Passage, and (c) the MakassarStrait from the daily model run over a 3-yr period. Model day 0 herecorresponds to 1 January 1985.

traseasonal signals have little impact upon the transportin the Lombok Strait.

The characteristics of the intraseasonal signals in theTimor Passage (Fig. 21b) are quite different from thosein the Lombok and Makassar Straits.2 In the Timor Pas-sage, the 50-day oscillations are no longer the dominantintraseasonal signals. Instead, a broad 30–35-day spec-tral peak becomes apparent. Note that this spectral peakaround 30–35 days also exists in the in situ current meterdata from the Timor Passage (see Fig. 3 and Molcardet al. 1994). Like in the Lombok and Makassar Straits,an 85-day spectral peak appears in Fig. 21b. The originfor the 85-day signals in the Timor Passage, however,is different from that in the Lombok Strait. The latter,

2 The intraseasonal signals in the Ombai Strait bear similar char-acteristics to those in the Timor Passage, but with a much lowerenergy level. Our discussion below will focus on the Timor Passageonly.

as we discussed in section 5a, comes from the surfacezonal wind fluctuations in the central equatorial IndianOcean. For the Timor Passage, both of the 85-day sig-nals and the shorter-period, 30–35-day signals are in-duced by local wind. This is evident if we look into thezonal wind stress data along the Indonesian coast from1008 to 1258E (Fig. 22). Along the Sumatra coast of1008–1058E and the Java coast of 1058–1108E, the windstress data exhibits a spectral peak around 50 days. Eastof 1108E the 50-day spectral peak weakens and is re-placed by the dual spectral peaks centered on 85 and35 days. As one moves eastward toward the Timor Pas-sage at 1258E, these two spectral peaks become moreprominent. Notice that the 85-day spectral peak is absentin the observed alongchannel flow in the Timor Passage(see Fig. 3b). This could be due to the short length ofthe mooring record (about 330 days) or to the inter-annual changes in the surface wind’s intraseasonal char-acteristics.

One available mooring record that overlaps with the

JULY 1999 1615Q I U E T A L .

FIG. 21. Power spectra of the transport time series shown in Fig.20: (a) Lombok Strait vs Makassar Strait and (b) Timor Passage vsOmbai Strait.

simulation period of the daily model case (1980–89) isthat of Murray and Arief (1988) from the Lombok Strait.The solid line in Fig. 23 shows the time series of themeridional flow observed by Murray and Arief at a 35-mdepth of the Lombok Strait. The dashed line in Fig. 23shows the flow transport through the Lombok Straitfrom the daily model case. The agreement between thetwo time series is favorable with the modeled through-channel flow capturing most of the observed intrasea-sonal signals. The cross-correlation coefficient betweenthe two time series is 0.70; it is significant at the 99%confidence level with the degrees of freedom for thetime series estimated at 20. This favorable comparisonbetween the model and the observation is encouragingas it lends credibility to the physical explanations pro-vided in this study for the observed intraseasonal sig-nals.

c. Intraseasonal signals in the Indonesian–Australianbasin

In the Indonesian–Australian basin away from theJava coast, Bray et al. (1997) observed strong 60-daysea surface height fluctuations associated with the eddiesand meanders of the South Equatorial Current. Asshown by Bray et al., these fluctuations are well capturedby the sea level measurement at Christmas Island(10.48S, 105.78E), which is located near the northernedge of the SEC. The intraseasonal signals in the SECof our daily model simulation are relatively weak. Alook at the modeled sea level time series at ChristmasIsland (Fig. 24) reveals that while the 60- and 90-dayspectral peaks are discernible due to the intraseasonalwind forcing, their amplitudes are an order of magnitudesmaller than those from the tide gauge measurement (cf.Fig. 9c). We speculate that this discrepancy is attrib-utable to the deficiency of our present 1½-layer modelthat disallows baroclinic instability to develop in theSEC. Questions such as what determines the timescaleof the intraseasonal changes of the SEC and whetherthe regional intraseasonal wind forcing contributes tothe selection of this timescale need to be addressed infuture studies.

6. Summary

Recent long-term current meter observations from thelow-latitude Pacific western boundary and from aroundthe Indonesian archipelago regions revealed the ubiq-uitous presence of flow fluctuations with intraseasonaltimescales. Theoretically, intraseasonal fluctuations inthe upper-ocean circulation can be excited through sev-eral dynamic processes: direct wind forcing, wind forc-ing in remote areas via waveguide, mean flow instabil-ity, and resonance due to coastline geometry. The ob-jective of this study is to clarify the dynamic processesunderlying the observed intraseasonal signals at differ-ent locations around the Indonesian seas.

To achieve this, we used a fine-resolution, 1½-layerreduced-gravity model with the Kraus and Turner mixedlayer dynamics embedded. The model simulated wellboth the mean circulation and the seasonal/intraseasonalsignals observed around the Indonesian seas. Our modelexperiments ranged from simple cases, where either cli-matological or idealized surface wind forcing wasadopted, to a more realistic case in which we used thedaily ECMWF surface wind data. Given the complexcoastline geometry in the Indonesian seas and the rich-ness in the surface wind variability, these model ex-periments with various levels of complexity helped testhypotheses and shed light on the physics essential forthe observed intraseasonal signals.

At the Pacific entrance of the Celebes Sea, our studyshowed that the energetic 50-day oscillations detectedby a recent current meter mooring observation were aresult of Rossby wave resonance in the Celebes Seabasin. As the Mindanao Current retroflects eastward off-shore of Mindanao, it sheds cyclonic eddies into the


FIG. 22. Power spectra of the zonal wind stress in the intraseasonalfrequency band (10–150 days) along the Indonesian coast from 1008to 1258E. The power spectra are based on the daily 1000-mbarECMWF wind data and are averaged in five 58-wide segments. Thepower spectra for each segment are shown with an offset of 0.7 31024 N2 m24.

FIG. 23. Time series of the observed meridional flow (solid line)versus the modeled meridional transport (dashed line) through theLombok Strait. The observed time series is based on Fig. 3 of Murrayand Arief (1988) and the modeled time series is from the daily modelcase. The unit for y axis is Sv for the model transport and 0.1 m s21

for the observed meridional flow.

FIG. 24. (a) Time series of modeled sea level anomalies at Christ-mas Island. (b) Power spectra of the time series in variance preservingformat. Model day 0 here corresponds to 1 January 1985.

semi-enclosed Celebes Sea. The eddy shedding period,which is determined by the length scale and the west-ward translating speed of the cutoff eddies, is about 50days and matches closely the gravest Rossby mode ofthe Celebes Sea basin. This match amplifies the 50-daysignals in the Celebes Sea and its effect further influ-ences the ITF in the Makassar Strait.

Intraseasonal signals along the Sumatra/Java coastsin the eastern Indian Ocean are dominated by oscilla-tions with wave periods of 50 days and 85 days. Thesesignals have been observed both by tide gauges alongthe Sumatra/Java coasts and by current meter mooringsin the Lombok Strait. The origin of these wave signalscan be traced back to the central equatorial Indian Oceanwhere the surface zonal wind fluctuates intraseasonallywith the same wave periods of 50 and 85 days. Whenthe coastal Kelvin waves that are remotely excited asequatorial Kelvin waves in the central Indian Oceanreach the Lombok Strait, most of the wave signals donot continue poleward along the archipelago coast.Rather, these waves enter the Makassar Strait and affectareas in the Banda Sea and around the coast of Sulawesi.Because of this in-land route, the 50- and 85-day signalsof the equatorial Indian Ocean–origin do not have asignificant effect on the throughflow fluctuations in theTimor and Ombai Straits.

Intraseasonal signals observed in the surface layer ofthe Timor Passage are dominated by oscillations withwave periods of 30–35 days. Our model result suggestedthat a second spectral peak with an 85-day wave periodexisted for the time period from 1985 to 1989 as well.Along the Indonesian archipelago coast between 1158and 1258E, the surface zonal winds have dominant spec-tral peaks around 35 and 85 days. It is these regionalwind forcings that are responsible for the observed andmodeled transport fluctuations in the Timor Passage.Notice that although the Timor Passage is in the pathwayof the coastal Kelvin waves originating in the upstreamCelebes Sea or along the Sumatra/Java coasts, the in-fluence from these waves appears to be small in com-

JULY 1999 1617Q I U E T A L .

parison with the local-wind-induced intraseasonal sig-nals.

Finally, this study has been motivated by several re-cent observational studies around the Indonesian archi-pelago regions. While the in situ data are still limitedfrom these regions, observational efforts are presentlybeing made by scientists from various countries. Webelieve that future modeling studies, when combinedwith new observational results, will be useful in im-proving our understanding of the intraseasonal vari-ability in this important part of the World Ocean.

Acknowledgments. We thank Akio Ishida, Roger Lu-kas, Toru Miyama, and Jim Potemra for their interestand discussions during the course of this study. JacksonChong, Stuart Godfrey, Steve Murray, Susan Wijffels,and an anonymous reviewer carefully read an earlierversion of the manuscript and provided many helpfulcomments. The in situ velocity time series presented inFig. 3a was provided to us by Robert Molcard, theECMWF daily wind data by NCAR, and the in situ sealevel data by the Sea Level Center at University ofHawaii. We are grateful to the Maui High PerformanceComputer Center for contributing the computer timeused in our modeling work. B.Q. and M.M. were sup-ported by NOAA through the Wyrtki Climate ResearchCenter at the University of Hawaii (Cooperative Agree-ment NA67RJ0154).

REFERENCES

Arakawa, A., and V. R. Lamb, 1977: Computational design of thebasic dynamical processes of the UCLA General CirculationModel. Method Comput. Phys., 17, 173–265.

Arief, D., and S. P. Murray, 1996: Low-frequency fluctuations in theIndonesian throughflow through Lombok Strait. J. Geophys.Res., 101, 12 455–12 464.

Barnier, B., L. Siefridt, and P. Marchesiello, 1995: Thermal forcingfor a global ocean circulation model using a three-year climo-tology of ECMWF analyses. J. Mar. Sys., 6, 363–380.

Bray, N. A., S. E. Wijffels, J. C. Chong, M. Fieux, S. Hautala, G.Meyers, and W. M. L. Morawitz, 1997: Characteristics of theIndo-Pacific throughflow in the eastern Indian Ocean. Geophys.Res. Lett., 24, 2569–2572.

Broecker, W. S., 1991: The great ocean conveyor. Oceanography, 4,79–89.

Clarke, A. J., and X. Liu, 1993: Observations and dynamics of semi-annual and annual sea levels near the eastern equatorial IndianOcean boundary. J. Phys. Oceanogr., 23, 386–399., and , 1994: Interannual sea level in the northern and easternIndian Ocean. J. Phys. Oceanogr., 24, 1224–1235.

Cresswell, G., A. Frische, J. Peterson, and D. Quadfasel, 1993: Cir-culation in the Timor Sea. J. Geophys. Res., 98, 14 379–14 389.

Da Silva, A. M., C. C. Young, and S. Levitus, 1994: Atlas of SurfaceMarine Data 1994, Vol. 1: Algorithms and Procedures, NOAAAtlas NESDIS 6. NOAA, U.S. Dept. of Commerce, Washington,D.C., 83 pp.

Ffield, A., and A. L. Gordon, 1992: Vertical mixing in the Indonesianthermocline. J. Phys. Oceanogr., 22, 184–195., and , 1996: Tidal mixing signitures in the Indonesian seas.J. Phys. Oceanogr., 26, 1924–1937.

Godfrey, J. S., 1996: The effect of the Indonesian throughflow onocean circulation and heat exchange with the atmosphere: Areview. J. Geophys. Res., 101, 12 217–12 237.

, and T. J. Golding, 1981: The Sverdrup relation in the IndianOcean, and the effect of Pacific–Indian Ocean throughflow onIndian Ocean circulation and on the East Australian Current. J.Phys. Oceanogr., 11, 771–779.

Gordon, A. L., 1986: Inter-ocean exchange of thermocline water. J.Geophys. Res., 91, 5037–5046.

Hellerman, S., and M. Rosenstein, 1983: Normal monthly wind stressover the world ocean with error estimates. J. Phys. Oceanogr.,13, 1093–1104.

Hurlburt, H. E., and J. D. Thompson, 1980: A numerical study ofloop current intrusions and eddy shedding. J. Phys. Oceanogr.,10, 1611–1651., J. C. Kindle, E. J. Metzger, and A. J. Wallcraft, 1989: Resultsfrom a global model in the western tropical Pacific. Proc. West-ern Pacific Int. Meeting and Workshop on TOGA COARE, Nou-mea, New Caledonia, Centre ORSTOM de Noumea, 343–354.

Inoue, M., and S. E. Welsh, 1993: Modeling seasonal variability inthe wind-driven upper-layer circulation in the Indo–Pacific re-gion. J. Phys. Oceanogr., 23, 1411–1436.

Kashino, Y., H. Watanabe, B. Herunadi, M. Aoyama, and D. Hartoyo,1999: Current variability at the Pacific entrance of the IndonesianThroughflow J. Geophys. Res., in press.

Kindle, J. C., H. E. Hurlburt, and E. J. Metzger, 1989: On the seasonaland interannual variability of the Pacific to Indian Oceanthroughflow. Proc. Western Pacific Int. Meeting and Workshopon TOGA COARE, Noumea, New Caledonia, Centre ORSTOMde Noumea, 355–365.

Kraus, E. B., and J. S. Turner, 1967: A one-dimensional model ofthe seasonal thermocline. II: The general theory and its conse-quences. Tellus, 19, 98–106.

LeBlond, P. H., and L. A. Mysak, 1978: Waves in the Ocean. ElsevierOceanography Series, Vol. 20, Elsevier, 602 pp.

Lukas, R., E. Firing, P. Hacker, P. L. Richardson, C. A. Collins, R.Fine, and R. Gammon, 1991: Observations of the MindanaoCurrent during the Western Equatorial Pacific Ocean CirculationStudy. J. Geophys. Res., 96, 7089–7104.

Madden, R. A., and P. R. Julian, 1994: Observations of the 40–50day tropical oscillation—A review. Mon. Wea. Rev., 122, 814–837.

Masumoto, Y., and T. Yamagata, 1993: Simulated seasonal circulationin the Indonesian seas. J. Geophys. Res., 98, 12 501–12 509.

McCreary, J. P., and P. K. Kundu, 1989: A numerical investigationof sea surface temperature variability in the Arabian Sea. J.Geophys. Res., 94, 16 097–16 114.

Meyers, G., 1996: Variation of Indonesian throughflow and the ElNino–Southern Oscillation. J. Geophys. Res., 101, 12 255–12 263., R. J. Bailey, and A. P. Worby, 1995: Geostrophic transport ofIndonesian throughflow. Deep-Sea Res., 42, 1163–1174.

Miyama, T., T. Awaji, K. Akitomo, and N. Imasato, 1995: Study ofseasonal transport variations in the Indonesian seas. J. Geophys.Res., 100, 20 517–20 541.

Molcard, R., M. Fieux, J. C. Swallow, A. G. Ilahude, and J. Ban-jarnahor, 1994: Low frequency variability of the currents in In-donesian Channels (Savu-Roti and Roti-Ashmore Reef ). Deep-Sea Res., 41, 1643–1662., , and A. G. Ilahude, 1996: The Indo–Pacific throughflowin the Timor Passage. J. Geophys. Res., 101, 12 411–12 420.

Murray, S. P., and D. Arief, 1988: Throughflow into the Indian Oceanthrough the Lombok Strait, January 1985–January 1986. Nature,333, 444–447.

Piola, A. R., and A. L. Gordon, 1984: Pacific and Indian Ocean upper-layer salinity budget. J. Phys. Oceanogr., 14, 747–753.

Ponte, R. M., and D. S. Gutzler, 1992: 40–60 day oscillations in thewestern tropical Pacific: Results from an eddy-resolving globalocean model. Geophys. Res. Lett., 19, 1475–1478.

Potemra, J. T., R. Lukas, and G. T. Mitchum, 1997: Large-scale es-timation of transport from the Pacific to the Indian Ocean. J.Geophys. Res., 102, 27 795–27 812.

Qiu, B., and R. Lukas, 1996: Seasonal and interannual variability of


the North Equatorial Current, the Mindanao Current and theKuroshio along the Pacific western boundary. J. Geophys. Res.,101, 12 315–12 330.

Sadourny, R., 1975: The dynamics of finite-difference models of theshallow-water equations. J. Atmos. Sci., 32, 680–689.

Semtner, A. J., and R. M. Chervin, 1992: Ocean general circulationfrom a global eddy-resolving model. J. Geophys. Res., 97, 5493–5550.

Tsuchiya, M., R. Lukas, R. A. Fine, E. Firing, and E. Lindstrom,1990: Source waters of the Pacific Equatorial Undercurrent. Pro-gress in Oceanography, Vol. 23, Pergamon, 101–147.

Verschell, M. A., J. C. Kindle, and J. J. O’Brien, 1995: Effects ofIndo–Pacific throughflow on the upper tropical Pacific and IndianOceans. J. Geophys. Res., 100, 18 409–18 420.

Wajsowicz, R. C., 1994: A relationship between interannual variationsin the South Pacific wind stress curl, the Indonesian Through-flow, and the west Pacific warm water pool. J. Phys. Oceanogr.,24, 2180–2187.

Watanabe, H., and Coauthors, 1997: Moored measurement of theIndonesian throughflow at the southwestern edge of the Phil-ippine Sea. Int. WOCE Newslett., 27, 26–30.

Woodberry, K. E., M. E. Luther, and J. J. O’Brien, 1989: The wind-driven seasonal circulation in the southern tropical Indian Ocean.J. Geophys. Res., 94, 17 985–18 002.

Wyrtki, K., 1987: Indonesian throughflow and the associated pressuregradient. J. Geophys. Res., 92, 12 941–12 946.

Yamagata, T., K. Mizuno, and Y. Masumoto, 1996: Seasonal varia-tions in the equatorial Indian Ocean and their impact on theLombok throughflow. J. Geophys. Res., 101, 12 465–12 473.

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Intraseasonal Variability in the Indo–Paciﬁc Throughﬂow …Murray and Arief 1988; Meyers et al. 1995; Molcard et al. 1996). Several studies have attributedthistransport cycle