Interactions between mesoscale eddy variability and IndianOcean dipole events in the Southeastern tropicalIndian Ocean—case studies for 1994 and 1997/1998

Tomomichi Ogata & Yukio Masumoto

Received: 29 May 2009 /Accepted: 17 May 2010 /Published online: 6 June 2010# Springer-Verlag 2010

Abstract Interannual modulation of mesoscale eddy activ-ity at the intraseasonal timescale in the southeastern tropicalIndian Ocean and its relation to the Indian Ocean dipolemode (IOD) events are investigated using results from ahigh-resolution ocean general circulation model. The modelreproduces observed characteristics of the intraseasonalvariability and its interannual modulation fairly well, withlarge variances of the intraseasonal variability during the1994 and 1997/1998 IOD events. Large negative temper-ature anomaly off the coasts of Java and the Lesser SundaIslands in boreal summer, due to seasonal variation andinterannual anomaly, extended further to the east in 1994,and the associated strong Indonesian throughflow enhancedthe baroclinic instability in the upper layer, generatinganomalously large mesoscale eddy activity. The eddy heattransport, in turn, significantly affected decaying phase ofthe 1994 IOD event. On the other hand, the development ofthe cold region off the Java Island associated with the 1997/1998 IOD event occurred in boreal winter, causing weakerbaroclinic instability and hence weaker eddy activity offJava. This led to little influence on the heat budget in thesoutheastern tropical Indian Ocean for the 1997/1998 IODevent.

Keywords Indian Ocean . Interannual variability .

Intraseasonal variability . Mesoscale eddy

1 Introduction

A far southeastern basin in the tropical Indian Ocean,hereafter referred to as SETIO, between the Lesser SundaIslands and northwestern Australia east of approximately100° E is known as a region of strong mesoscale eddyactivity (e.g., Quadfasel and Cresswell 1992; Feng andWijffels 2002; Yu and Potemra 2006). Feng and Wijffels(2002) showed strong intraseasonal variability (ISV) in theobserved sea surface height (SSH) anomaly, with distinctseasonal variation in the ISV amplitude, with largeamplitude appearing from July to September. They con-cluded that the ISV is associated with eddy activity causedby baroclinic instability in the South Equatorial Current(SEC)/Indonesian Throughflow (ITF) system in the SETIO,partly because they did not have adequate data to studybarotropic instability. Yu and Potemra (2006) investigatedthe ISV in the same region using a 4.5-layer model forcedby climatological monthly-mean wind forcing. They suc-ceeded in reproducing the ISV with larger variability duringJuly to September and attributed it to mixed instability,which was sensitive to transports through three mainpassages to the Indian Ocean, namely the Lombok, Ombaiand Timor passages, in particular the Lombok Strait. Inaddition to such internal instability within the ocean, theISV can be directly forced by local wind variability alongthe southern coast of the Lesser Sunda Islands andgenerated by eastward propagation of the intraseasonalcoastal Kelvin waves, which are remotely forced by thezonal wind variability in the equatorial Indian Ocean(Iskandar et al. 2005; Iskandar 2007).

Responsible Editor: Hideharu Sasaki

T. Ogata (*)International Pacific Research Center,University of Hawaii at Manoa,POST Bldg, Room 412F1680 East-West Road,Honolulu, HI 96822, USAe-mail: ogatat@hawaii.edu

Y. MasumotoResearch Institute for Global Change,Japan Agency for Marine-Earth Science and Technology,Yokohama, Japan

Ocean Dynamics (2010) 60:717–730DOI 10.1007/s10236-010-0304-4

The SETIO is also known as one of the action centers forthe Indian Ocean dipole mode (IOD), which is an air–seacoupled climate mode at the interannual timescale inherentin the tropical Indian Ocean (Saji et al. 1999; Webster et al.1999; Murtugudde et al. 2000). Positive IOD is character-ized by negative temperature and lower SSH anomalies onthe Indonesian side of the SETIO, creating meridionaltemperature gradient and associated vertical shear in theSEC that are stronger than those under climatologicalconditions. Thus, together with the El Nino/SouthernOscillation phenomenon in the Pacific Ocean, the IOD inthe Indian Ocean is one of the dominant phenomenaaffecting magnitude of the ITF at the interannual timescale(Meyers 1996; Masumoto 2002; Sprintall et al. 2009).Although such interannual variations in the current systemof the SETIO are expected to appear in the interannualmodulation of the ISV activity through local instabilities, sofar, there is no study on this important link between the twosignals in the SETIO.

In general, the ISV associated with the instabilitiesgenerates net heat transport across the mean current toreduce the temperature gradient. Therefore, the interannualmodulation of the ISV activity may affect heat budget inthis region at the interannual timescale, hence affectingevolution of interannual climate variability modes in theSETIO. In this study, the ISV and its interannual modula-tion within the SETIO and their influence on the IODevolution are investigated using results from a high-resolution ocean general circulation model (OGCM).

A brief description of the OGCM and dataset used in thefollowing analyses is presented in Section 2. The simulatedISV and the interannual variations of the ISV activity areillustrated and compared to the observed characteristics ofthe ISV in Section 3. Details of the relation between theISV activity and the IOD events in 1994/1995 and 1997/1998 are shown in Section 4. Conclusions and discussionabout the Pacific influence on the ISV activity in the SETIOare given in Section 5.

2 Data and model descriptions

In the present study, we mainly utilize results from a high-resolution OGCM, called OFES (OGCM for the EarthSimulator). OFES is a three-dimensional, finite differenceprimitive equation model based on the Modular OceanModel version 3 (MOM3), developed at Geophysical FluidDynamics Laboratory/National Oceanic and AtmosphericAdministration (Pacanowski and Griffies 2000). It is tunedand improved to obtain the best performance on the EarthSimulator at Japan Agency for Marine-Earth Science andTechnology. The model covers near-global areas from 75° Sto 75° N, with a horizontal grid spacing of 0.1° in both

longitude and latitude. There are 54 levels in the vertical, ofwhich 20 levels are located in the upper 200-m depth toreproduce the variations within and shallower than thethermocline as realistically as possible. The horizontalmixing process is parameterized by the bi-harmonicscheme, and the K-Profile Parameterization scheme isadopted for the vertical mixing (Large et al. 1994). Ahigh-resolution bottom topography data provided by theOCCAM project is used, with the Partial Cell schemeembedded in MOM3, to represent the coastline and bottomtopography as realistically as possible. Note that the majorfeatures such as the Maldives island chain and the NinetyEast Ridge are well represented in OFES.

The model is, at first, forced by climatological monthly-mean wind stresses calculated from the NCEP/NCARreanalysis (Kalnay et al. 1996) for 50 years and then drivenby the daily-mean wind stresses of the reanalysis data from1950 to 2004. The surface heat flux is calculated using abulk formula similar to Rosati and Miyakoda (1988), withnecessary data from the NCEP/NCAR reanalysis. Forfreshwater flux, we utilize a scheme based on precipitationminus evaporation, with the NCEP/NCAR reanalysisprecipitation data and the evaporation calculated using thebulk formula. In order to include influences of the riverrunoff, a term with a timescale of 6 days is added to relaxsurface salinity to the climatological monthly-mean valuesof World Ocean Atlas 98 (WOA98; Boyer et al. 1998).Similar relaxations to the climatological monthly-meantemperature and salinity fields are adopted near theboundaries at 75° S and 75° N. For more details of themodel description, readers are referred to Masumoto et al.(2004) and Sasaki et al. (2006).

In this study, we analyze the results of OFES forced byNCEP/NCAR daily reanalysis data for the period from1990 to 2003, during which several satellite observationsare available for comparison. Note that two positive IODevents, in 1994 and 1997/1998, occurred in this period.

The Ocean Topography Experiment/Poseidon (T/P) andEuropean Remote Sensing Satellite-1 and-2 (ERS-1/2)blended dataset (Ducet et al. 2000) is used to evaluate themodel results. The combined T/P and ERS-1/2 altimeterdata provides global SSH variability with high temporal(7-day interval) and spatial (0.25° in longitude and 0.33° inlatitude) resolutions from October 1992 to the present.

In order to focus on the ISV and its relation to theinterannual variations in the SETIO, the total variability ofeach variable is separated into intraseasonal, seasonal, andinterannual timescales; so for any variable of interest, V,

V ¼ VISV þ Vclim þ Vanom: ð1Þ

To separate the variability, climatological seasonalvariation (Vclim) is calculated at first and subtracted from

718 Ocean Dynamics (2010) 60:717–730

the total variations. Then, the 18–96 and 14–98 days band-pass filters are applied to the OFES results and the observedSSH variability, respectively, to extract the ISV or VISV.Since the variability shorter than about 2 weeks is relativelysmall in OFES, most of the remaining variability (Vanom)consists of only the interannual variations. In the followinganalyses, therefore, we call these separated variabilities asthe ISV, seasonal variation, and interannual anomaly,respectively.

3 Model validations

3.1 Simulated seasonal to interannual variabilityin the tropical Indian Ocean

Figure 1 compares climatological mean temperature andzonal currents along 120° E in March and September from

OFES and WOA98. The 20°C isotherm, which correspondsto the middle of the thermocline, is highlighted by red.OFES resembles well the observed features, includingshoaling of the 20°C isotherm toward the Java coast (northof 14° S) and strengthening of the westward current in theupper ocean in boreal summer. However, observed thermo-cline slope is significantly weaker than that in OFES, duelikely to strong smoothing applied to the WOA98 dataset.

Figure 2 shows the comparison of the Dipole ModeIndex (DMI; Saji et al. 1999) obtained from OFES andExtended Reconstruction sea surface temperature (ERSST;Smith et al. 2008). The DMI is defined as the difference ofarea-averaged SST anomaly between the western box (50–70° E, 10° S–10° N) and the eastern box (90–110° E,10° S–0° N). OFES captures positive (negative) IOD eventsduring 1994 and 1997 (1996 and 1998), with a correlationcoefficient of 0.66, which is significant at the 95%confidence level.

(a)

(b)

(cm/s)

Fig. 1 Latitude-depth section of the seasonal climatology for zonalcurrent (shade) and temperature (contour) along 120° E. Left (right)panels show results of OFES (WOA98) in March (a) and September

(b). Note that current fields in WOA98 are derived by means of thegeostrophic calculation that assumes 1,000 m as the depth of nomotion

Ocean Dynamics (2010) 60:717–730 719

3.2 Intraseasonal variability in the SETIOand its interannual modulation

Figure 3 compares horizontal distribution of the observedand simulated variances of the intraseasonal SSH variabilityin the SETIO for the period from January 1993 to December2003. Both results exhibit large amplitude variability in aregion south of the Java Island (100° E–115° E, 9° S–15° S).The simulated amplitude, however, is slightly larger andshifted southward compared with the observed one, dueperhaps to slight difference in location and structure of theSEC between the two results. Intraseasonal SSH variance isalso large along the coast of the Sumatra and Java islands,showing a manifestation of intraseasonal coastal Kelvinwaves generated by zonal wind variability in the equatorial

Indian Ocean as well as by the local alongshore winds(Iskandar et al. 2005). However, this coastal area of the largeamplitude is separated from the offshore maximum variancesin both OFES and observations.

Figure 4 illustrates the observed and simulated variationsof the total SSH along 12° S from January 1994 toDecember 1995 to show distinct characteristics of thevariations. Significant variability at the intraseasonal time-scale is clearly seen in both observations and OFESsimulation, showing clear westward propagation with aspeed of 0.19 m/s and a typical period of 20–60 days. Theamplitude of the variability tends to be large from July toDecember and to be small from February to June, which isconsistent with Feng and Wijffels (2002). In addition,distinct seasonal variation can be observed in both OFESand observations: The SSH becomes larger during Augustto December and smaller during February to June near90° E. This annual signal also propagates westward with aspeed of 0.15 m/s, suggesting an association with annualforced Rossby waves in the southern tropical Indian Ocean(Masumoto and Meyers 1998). Note that the abovecharacteristics of the intraseasonal and seasonal timescalesare basically the same in other years, even though theinterannual variability is superposed on the seasonal andintraseasonal variations.

As another measure for the ISV activity and itsinterannual modulation, an eddy kinetic energy (EKE)associated with the 18- to 96-day variability is definedas Ke = ρ(uISV

2 + vISV2). Then, its monthly value with

3-month sliding window is calculated and separated into theseasonal climatology (Keclim) and remaining interannualvariation (Keanom) similar to the derivation of Eq. 1.

The SSH variation contains both large-scale variationsassociated with atmospheric intraseasonal disturbances andthe mesoscale eddy variability due to internal oceanicprocesses. On the other hand, the EKE tends to capturemesoscale eddy variability and does not represent the large-scale forced variations. In this regard, the EKE anomalytime series is more appropriate for exploring the role ofintraseasonal eddy activities associated with oceanic pro-

Fig. 2 Dipole Mode Index(DMI) from January 1990 toDecember 2003. Black line(red line) indicates the DMIderived from OFES (ERSST)

(a)

(b)

(cm

(cm

Fig. 3 Horizontal distributions of the intraseasonal variance of theSSH variability from satellite altimetry observation (14- to 98-dayband-passed variability) (a) and OFES (18- to 96-day band-passedvariability) (b) for a period from January 1993 to December 2003

720 Ocean Dynamics (2010) 60:717–730

cesses. Figure 5a displays time series of variance of theintraseasonal EKE variability averaged over 95° E–115° Ealong 12° S. The variance is calculated each month for3-month time window, and the time series is normalized bythe standard deviation of the variance. The observed valueof the EKE is calculated from the geostrophic velocityestimated from the T/P and ERS-1/2 SSH variability. Thestandard deviation of the OFES simulated and observedEKE anomalies are 31.8 and 23.9 g/cm/s2, respectively.Both the simulated ISV and observed ISV demonstratesignificant interannual modulations. The ISV variances arelarger (weaker) in 1994 and 1997/1998 (1993 and 1998/1999) in both OFES and observations. The correlationcoefficient between simulated and observed EKE anomalyis 0.56, which is above the 90% confidence level.

There are some differences between the simulated andobserved EKE anomalies in 1995/1996 and 1996/1997. Thediscrepancy in 1995/1996 may be due to the simulatednegative heat content anomaly in the SETIO during borealsummer of 1995, while the difference in 1996/1997 areassociated with warm anomaly around 14° S, which ispropagated from the western tropical Pacific. Detailedanalysis on the influence of the Pacific Ocean on the eddyactivity in the SETIO is ongoing and will be reported in aseparate paper.

In order to investigate the relationship between the eddyactivities in the SETIO and basin-scale subsurface phe-nomena in the Indian Ocean, Fig. 5b shows horizontal

(a) (b)

(cm)

Fig. 4 Longitude-time sectionsof the SSH variability fromJanuary 1994 to December 1995at 12°S for satellite observation(a) and OFES (b)

(a)

(b)

norm

aliz

ed b

y S

td.

( )

Fig. 5 a Time series of anomaly of the intraseasonal EKE variabilityaveraged over 95° E–115° E along 12° S for satellite observation(black line) and for OFES (green line). DMI derived from ERSST isalso superposed (red line). b Regression of the EKE anomaly timeseries in Fig. 5a onto heat content anomaly in the upper 250-m depthfor the Indian Ocean basin. Note that EKE for satellite observation ina is calculated using the geostrophic relation

Ocean Dynamics (2010) 60:717–730 721

distribution of the heat content anomaly in the upper 250-mdepth regressed to the EKE anomaly time series shown inFig. 5a, with the heat content anomaly leading to the EKEanomaly by 3 months. While negative heat content anomalyoccupies in the eastern tropical Indian Ocean with largesignal occurring along the coast of Sumatra and JavaIslands, positive anomaly appears in the southwesterntropical Indian Ocean. The maximum anomaly exceeds200°Cm in both positive and negative regions. Thisstructure is generally similar to the spatial distribution ofthe upper layer heat content anomaly during the positiveIOD event (Rao et al. 2002).

The time series of the DMI is also plotted in Fig. 5a. Thesignificant positive DMI appeared during 1994 and 1997/1998, which corresponds to the positive IOD years. Thetwo time series of the DMI and the OFES simulated EKEanomaly indicate in-phase relation with a correlationcoefficient of 0.59, which is above the 90% significantlevel. The DMI leads the eddy activity by 3 months.

The above results suggest that the EKE anomaly, whichalso corresponds to the ISV anomaly, in the SETIO hasstrong correlation with the IOD event in the tropical IndianOcean. In general, the cold temperature anomaly off theSumatra and Java islands associated with the IOD eventsenhances the meridional temperature gradient in the fareastern region around 12° S, a situation favorable forincreasing the eddy activity through the enhanced baro-clinic instability. In the following section, we will explorethe eddy development and background conditions duringthe 1994 and 1997/1998 IOD events.

4 Eddy activity during the 1994 IOD event

4.1 Seasonal anomaly and eddy activity in the SETIO

Figure 6 shows interannual anomaly of the heat content inthe upper 250-m depth averaged in the SETIO (95–125° E,12° S–3° N) during January 1994–December 1995. Thenegative temperature anomaly in the SETIO associated withthe 1994 IOD matured in boreal summer (August), with thelargest decreasing of over 2°C. This temperature anomalyextended along the coast of Sumatra, Java and the LesserSunda Islands, with upwelling favorable southeasterly windfield over the SETIO (Fig. 6b). The cold anomaly furtherpenetrates eastward into a region around the Timor Island,suggesting coastal Kelvin wave propagation in response tothe upwelling favorable wind anomaly along the coasts.Note that the seasonal variation of the upper layertemperature also indicates its minimum in boreal summerdue to enhanced seasonal upwelling along the Sumatra andJava coasts (e.g., Qu and Meyers 2005). The seasonalvariation together with the interannual anomaly associated

with the IOD event generated significantly cold conditionin the northern part of the SETIO during boreal summer in1994. In this particular case, a ratio of the interannualanomaly to the seasonal variation is about 1.8.

Upper layer currents in the SETIO also went throughsignificant changes associated with the aforementionedtemperature anomalies. Figure 7b demonstrates a latitude-depth section of zonal current and the temperature across120° E where the ITF through the Timor Passage connectsto the SEC. This area also corresponds to an upstreamregion of the active intraseasonal eddy activities (seeFig. 3). The thermocline was located around 150-m depthsouth of 13° S, and it became shallower to the north toabout 70 m around 11° S. Strong westward zonal current inthe upper layer was observed between 13° S and 11° S,with significant vertical shear near the thermocline depth.

The upper layer current structure in the SETIO isaffected by transports through several passages connectingthe Indonesian Seas and the SETIO. Interannual anomaliesof the transport through the Lombok, Ombai and Timorpassages and the averaged current shallower than the depthof 100 m are shown in Fig. 7. The averaged upper oceancurrent into the SETIO through the Timor passage was

(a)

(b)

Fig. 6 a Time series of the heat content anomaly in the upper 250-mdepth averaged in the SETIO (95–125° E, 12° S–3° N) during January1994–December 1995. b Heat content anomaly in the upper 250-mdepth (shade) and the surface wind stress anomaly (vectors) averagedfrom June to August 1994

722 Ocean Dynamics (2010) 60:717–730

increased about 10 cm/s (corresponding transport of 1 Sv)during boreal summer, while there was no significantincrease in the Lombok and Ombai throughflows duringthe 1994 IOD event, which is consistent with the subsurfacetemperature field shown in Fig. 6. It is also noted that therewere a weak negative subsurface temperature anomalyassociated with an increase in the transport across the Timorpassage during boreal summer in 1995 when the eddyactivity was increased in OFES.

Mechanisms responsible for the strong eddy activity inthe SETIO can be clarified by considering the EKEequation. Following Masina et al. (1999), the equation iswritten as:

@Ke

@tþ~u�rKe ¼ �r� ~u0p0

� �� gr0w0 � r0~u0

� ~u0 � r~u� �

þ res:; ð2Þ

where Ke is the EKE, ~u is the horizontal velocity, w is thevertical current, p is the pressure, ρ′ is the densityperturbation, ρ0 is the mean density, and ∇ is the horizontalgradient operator. The residual term, indicated by res.corresponds to the diffusion terms. The overbar indicateslow-frequency variation longer than the 96-day period,while the primed variables represent the intraseasonalvariations. The second (third) term on the right-hand siderepresents baroclinic (barotropic) energy conversion. Thehorizontal distributions of the meridional temperaturegradient, as an index of the baroclinicity for the backgroundcondition to the perturbation, the baroclinic and barotropicenergy conversion terms averaged over upper 250-m depthin the SETIO during 3 months from June to August 1994are shown in Fig. 8. Superposed on these variables are thedistribution of the simulated surface EKE.

The strong meridional temperature gradient existedalong 12° S, spanning from 110° E to 125° E, with arelatively weaker gradient extending to the west near 95° E.This strong baroclinicity is associated with the anomalouscooling along the coast of the Lesser Sunda Islands andrelatively strong Timor throughflow during the second halfof 1994. This, in turn, enhances the EKE through thebaroclinic energy conversion term. The baroclinic energyconversion appeared to be large in a region centered at112° E, 12° S, with a zonally elongated shape along theSEC, and the region corresponded to the area of the largestEKE. Westward shift of large baroclinic energy conversionto the strong meridional temperature gradient suggests theimportance of downstream advection due to the SEC.

The barotropic conversion term, on the other hand, wasrelatively small over the entire region of the SETIO duringthe 1994 IOD period, suggesting the baroclinic instabilityin the SEC as a dominant mechanism for the eddygeneration. This result is consistent with Feng and Wijffels(2002), but different from Yu and Potemra (2006) in whichthe barotropic instability near the Lombok Strait wasanother dominant energy source for the eddy activity.

In addition, a canonical linear stability analysis, using asimple continuously stratified model with the mean con-ditions derived from the OFES results, demonstratesreasonable values of growth rate and period (Table 1; seeAppendix 1 for details). The largest growth rate occurred ataround 116° E, 12° S during the 1994 IOD, although the

(a)

(b)

(c)

(d)

(cm/s)

(cm/s)

(cm/s)

(cm/s)

Fig. 7 a Time series of the spatially averaged current in the upper100-m depth through the Lombok Strait (a), Ombai Passage (b), andTimor Passage (c) during January 1994–December 1995. Thick (thin)line shows monthly averaged (monthly climatological) transport in a–c. d Latitude-depth section of zonal current (shade) and temperature(contour) along 120° E averaged from June to August 1994. Note thatthe positive value in a–c means the current is toward the Indian Ocean

Ocean Dynamics (2010) 60:717–730 723

growth rate of about 77 days is somewhat longer than thevalue given by Feng and Wijffels (2002).

4.2 Heat budget analysis and heat content variationin the SETIO

Large eddy activities generate net meridional heat transportand, therefore, should contribute to heat budget in theSETIO, especially in the region of the negative temperature

anomaly associated with the IOD event. To explore thispoint during the 1994 IOD event, a heat budget analysis isconducted using the following thermodynamic equation:

@T

@t¼ Q

rcpH� @

@xuTð Þ � @

@yvTð Þ � @

@zwTð Þ þ diff ; ð3Þ

where T is temperature, Q is the heat flux at sea surface, (u,v, w) are the three components of velocity, ρ is the density,Cp is the heat capacity under constant pressure, and H is theupper layer thickness, which is assumed to be constant at250-m depth in the present study. The last term on the right-hand side indicates the diffusion term. In this equation, eachvariable (T, u, v, w, or Q) is separated into threecomponents: the ISV, the climatological seasonal cycle,and the interannual anomaly, as in Eq. 1. Temperature fluxcan be expressed as:

vT ¼ ðvISV þ vclim þ vanomÞðTISV þ Tclim þ TanomÞ¼ vISVTISV þ . . .þ vanomTanom

:ð4Þ

The first term on the right-hand side, vISVTISV, is definedas eddy heat transport in the following analysis. Thehorizontal distribution of the eddy heat transport in theSETIO is shown in Fig. 8d, indicating almost the samedistribution with that for the baroclinic conversion term.

Time series of each term in the thermodynamic Eq. 3,integrated over the upper layer (0- to 250-m depth) in theSETIO (95–125° E, 12° S–3° N), for the 1994 IOD event isshown in Fig. 9a. During the cooling phase (Feb. to Jun.1994) prior to the IOD event, the heat divergenceassociated with seasonal temperature variability and inter-annual current anomaly was dominant. The IOD in 1994evolved from August to October and the cold temperaturecondition continued until December. However, in thisdeveloping phase (Jul. to Nov. 1994), strong meridionaleddy heat transport overwhelmed heat divergence term andcontributed to the heat content increase in the SETIO,which prevented the development of the IOD event.

There was another positive peak in the rate of timechange of the averaged upper layer temperature fromDecember 1994 to February 1995, corresponding to thedecay period of the 1994 IOD event. In this period, the

Table 1 Maximum growth rate (e-folding time) and period for themost unstable wave derived from a linear stability analysis for the1994 and 1997/1998 IOD cases

Jun–Aug1994 Sep–Nov1997

e-folding time (days) 76.9 124.0

Period (days) 94.9 131.1

The values are averaged over the region from 10° S to 14° S and from115° E to 120° E

(C/deg)

(g*cm

(g*cm

(a)

(b)

(c)

(d)

( *cm/s)˚C

Fig. 8 Horizontal distributions of meridional temperature gradient (a),magnitude of the barotropic energy conversion term (b), magnitude ofthe baroclinic energy conversion term (c), and meridional eddy heattransport (d) averaged over the upper 250-m depth for a period fromJune to August 1994. The EKE averaged over the upper 250-m depthfor a period from August to November 1994 is superposed on eachpanel using solid contours

724 Ocean Dynamics (2010) 60:717–730

product of the seasonal temperature variation and theinterannual current anomaly played a key role, and theeddy heat transport had a weak negative contribution tothe warming. The heat budget result reveals that the heatinput through the western side (across 95° E) was dominantfor the latter warming peak, and especially the eastwardcurrent anomalies centered at 5° S, 80-m depth and at 12° Scontributed to the heat transport in the SETIO during thisperiod (not shown).

Significant influence of the eddy heat transport duringthe developing phase of the IOD is also demonstrated bytwo calculations of the heat content variability in theSETIO. Figure 9b exhibits time series of the heat contentanomaly in the upper 250-m depth for two cases: oneestimated from the full contribution of all the terms in the

thermodynamic equation and the other without the eddyheat transport contribution. In boreal summer to fall 1994,the eddy heat transport term significantly reduced thenegative heat content anomaly in the SETIO. On the otherhand, the estimated heat content anomaly without the eddyheat transport continued to cool until November, and theheat content did not return to its normal condition even atthe end of 1995.

5 Eddy activity during the 1997/98 IOD event

Another large positive IOD event occurred in late 1997, inconjunction with the El Nino phenomenon in the PacificOcean. It is interesting to investigate in detail the relationbetween the ISV and the interannual variation in the SETIOfor this particular event since there are significant differ-ences between the two conditions in 1994 and 1997.

The time series of the interannual heat content anomalyin the upper 250-m depth averaged over the SETIO regionis shown in Fig. 10a. The temperature anomaly decreasedfrom early 1997 and reached its minimum in Novemberwith a negative anomaly of about 2°C. Since the seasonaltemperature variation takes its coldest phase in August, thetotal negative temperature anomaly, which created thefavorable condition for the generation of unstable distur-

-3e+06

-2e+06

-1e+06

0

1e+06

Feb94 Jul94 Dec94 May95 Oct95

’hc_SEIO’hc_SEIO@without_eddy

vanom*Tanom

vanom*Tclim

vclim*Tanom

veddy*Teddy

dT/dt

Feb94 Jul94 Dec94 May95 Oct95

0.4

0.1

0.2

0.3

-0.1

-0.2

-0.3

0

(a)

(b)

heat

tran

spor

t (P

W)

Fig. 9 a Time series of each term in the thermodynamic Eq. 3,integrated over the upper layer (0- to 250-m depth) in the SETIO (95–125° E, 12° S–3° N) during December 1993–December 1995. b Timeseries of the heat content anomaly in the upper 250-m depth. The redsolid line indicates the estimate from the full contribution of all theterms in the thermodynamic equation, while the blue dashed lineshows the estimate without the eddy heat transport contribution. In a,vanomTanom (red), vanomTclim (green), vclimTanom (blue), vISVTISV(purple), @T=@t (black), and Q=r0cpH (aqua) are shown

(a)

(b)

( )

(

Fig. 10 Same as in Fig. 6, except for the 1997/1998 IOD event

Ocean Dynamics (2010) 60:717–730 725

bances in 1997, was weaker than that in 1994. Thehorizontal distribution of the interannual heat contentanomaly in the upper 250-m depth (Fig. 10b) shows thecold region along the southern coasts of Java and LesserSunda Islands. However, in 1997, the anomalous temper-ature extended only to the Lombok Strait, and there was nosignificant temperature anomaly east of it.

The differences between the 1997 case and the 1994 caseare also captured by the velocity fields and the transports inthe ITF. The time series of the upper ocean averagedcurrent through the Lombok Strait and Timor Sea during1997/1998 and the latitude-depth section of the zonalcurrent along 120° E averaged from September to December1997 are also shown in Fig. 11. The Timor transport didnot indicate any significant positive anomaly during the

1997 event, while the upper ocean current increased about10 cm/s (corresponding to transport of 1 Sv) after the event.The upper ocean current through the Lombok Strait, on theother hand, strengthened by 40 cm/s (corresponding totransport of 0.5 Sv) during the period from September toDecember 1997. Note that the easterly wind anomaly in theregion south of the Java and the Lesser Sunda Islands wasalso weaker than that during the 1994 IOD event.

The above differences in the background conditionsbetween the two IOD events result in a quite differentbehavior of the eddy activity in the SETIO. Figure 12shows horizontal distributions of meridional temperaturegradient, baroclinic energy conversion rate, and meridional

(a)

(b)

(c)

(d)

(cm/s)

(cm/s)

(cm/s)

(cm/s)

Fig. 11 Same as in Fig. 7, except for the 1997/1998 IOD case

(a)

(b)

(c)

(d)

(̊ C/deg)

(g*cm

(g*cm

(˚C*cm/s)

/s )2 3

/s )2 3

Fig. 12 Same as in Fig. 8, except for the 1997/1998 IOD case. TheEKE is averaged from November 1997 to February 1998

726 Ocean Dynamics (2010) 60:717–730

eddy heat transport in the SETIO during fall and winter1997 when the meridional eddy kinetic energy anomaly hadits largest value (see Fig. 5a). Because of the mismatch inthe phase between the seasonal and interannual temperatureevolutions, the degree of the baroclinicity was weaker in1997 compared to that during the 1994 IOD event, whichwas reflected by a weaker shoaling of the thermoclinetoward the Indonesian coast and the associated weakervertical shear of the zonal current east of the Lombok Strait

in 1997. This caused a reduction of baroclinic energyconversion rate, eddy kinetic energy, and, hence, themeridional eddy heat transport in 1997. It should be notedthat although the merdional temperature gradient largerthan 1°C/deg occupied almost the same area as that for the1994 case, the region of strong meridional temperaturegradient was significantly small in 1997. In addition, thelinear stability analysis reveals that the largest growth rateduring the 1997/1998 IOD event is about half of the oneduring the 1994 IOD event (Table 1), which is consistentwith the disappearance of the region of strong baroclinicityin the SEC.

The area-averaged heat content anomaly in the regionsouth of the Java Island during 1997/1998 IOD event isshown in Fig. 13. As expected from the above results, thetime series of the heat content anomaly with and withoutthe eddy heat transport term indicates very similarbehaviors, suggesting no significant influence of the eddyterm on the evolution of the 1997/1998 IOD event.

6 Summary and discussion

In this study, relations between mesoscale eddy activity atthe intraseasonal timescale and the interannual IOD eventsin the SETIO are investigated using the results from the

-4e+06

-2e+06

0

2e+06

Jan97 Jun97 Dec97 Apr98 Sep98

’hc_SEIO’hc_SEIO@without_eddy

Fig. 13 Same as in Fig. 9b, except for a period from December 1996to December 1998, covering the 1997/1998 IOD event

-0.5

-0.4

-0.3

-0.2

-0.1

0

0.1

0.2

0.3

0.4

0.5

corr@EKE_SEIO-Timorcorr@EKE_SEIO-ULT_Timor

corr@EKE_SEIO-enso

corr@EKE_SEIO-iod90% significant (0.36)

-15 -10 -5 0 5 10 15lag (month)

Fig. 14 Lagged correlation of the EKE anomaly in the upper 250-mdepth averaged over 10–16° S and 95–115° E, with Timor through-flow anomaly in the layer from the sea surface down to 1,000-m depth(red solid line), with Timor transport in the upper 100-m depth (greendotted line), with the zonal wind anomaly averaged over the centralequatorial Pacific (5° S–5° N, 170° E–170° W) as an index for the

ENSO (blue dotted line), and with the zonal wind anomaly averagedover the central equatorial Indian Ocean (5° S–5° N, 70–90° E) as anindex for the IOD (purple dotted line). Negative value indicates thateach variable leads to the EKE variability. The black dash-dotted linesindicate 90% significant level

Ocean Dynamics (2010) 60:717–730 727

high-resolution OGCM, OFES. OFES reproduces well theobserved ISV in the SETIO and its interannual modulation,with large variances of the ISV during the 1994 and 1997/1998 IOD events. During the 1994 IOD event, the largenegative temperature anomaly off the south coasts of Javaand the Lesser Sunda Islands developed in boreal summerdue to phase matching between the seasonal variation andthe interannual anomaly. The eastward extension of the coldregion and the associated strong Timor throughflowenhanced the baroclinic instability in the upper layer,generating the anomalous mesoscale eddy activity there.The eddy heat transport, in turn, significantly affected thedecay of the 1994 IOD event. On the other hand, thedevelopment of the cold region off the Java Islandassociated with the 1997/1998 IOD event occurred inboreal winter, and the weaker Timor throughflow alsoprevented large eddy activity off Java. This resulted in littleinfluence of the eddy heat transport on the heat budget inthe SETIO for the 1997/1998 IOD event.

In Section 3, we show that the interannual modulation ofthe eddy activity in the SETIO has large correlation with theIOD events and also with the upper layer Timor throughflow.Potemra and Schneider (2007), however, demonstrated thatthe interannual variability of the ITF transport anomaly inthe thermocline layer (between 100 and 500 m) is controlledby divergent winds over the equatorial Pacific and IndianOcean, suggesting the importance of the variability not onlyin the Indian Ocean but also in the Pacific Ocean. To explorethe possibility of such influence from the Pacific side on theISV in the SETIO, we calculated lagged correlation betweenthe EKE in the SETIO and indices for the IOD, ENSO, andITF anomalies (Fig. 14). As expected from the above results,correlation coefficients with the upper layer Timor through-flow anomaly and with the IOD index show its largestminimum correlation with a negative lag of a few months.On the other hand, the correlation coefficient with the ENSOindex is almost zero for any of the negative lags, suggestingno direct influence of the ENSO events on the ISV in theSETIO. However, the depth-integrated net transport throughthe Timor Passage indicates relatively large negativecorrelation with the eddy activities at a −6-month lag,suggesting that signals in the Pacific Ocean may affect theconditions in the SETIO through changes in the net ITFtransport.

Acknowledgments We thank two anonymous reviewers for thehelpful comments, which greatly improved our original manuscript.We also would like to appreciate suggestions and English editing byDr. Zuojun Yu, which were very important for the completion of thispaper. Dr. Hideharu Sasaki (JAMSTEC/ESC) provided us outputs ofOFES runs, and this thesis could not be accomplished without hishelp. Comments and encouragements by Prof. Kelvin Richards, Prof.Shang-Ping Xie, Prof. Kirk Bryan, Prof. Yukari Takayabu, andDr. Susan Wijffels were essential to improve this study.

Appendix 1: Linear stability analysis

Governing equations for the linear stability analysis in aquasi-geostrophic potential vorticity framework is asfollows:

@

@tþ U

@

@x

� �@2y@x2

þ @2y@y2

þ f 2

N 2

@2y@z2

� �

þ b � @2U

@y2� f 2

N2

@2U

@z2

� �@y@x

¼ 0;

ð5Þ

@

@tþ U

@

@x

� �@y@z

� @U

@z

@y@x

¼ 0; ð6Þ

where U is the mean zonal velocity, f is the Coriolisparameter, N2 is the Blant–Visala frequency, β is theplanetary beta term, and y is the stream function. Withy ¼ fðzÞ cos py=2Lð Þ exp ik x� ctð Þ½ �, Eqs. 5 and 6 arereplaced by the equations of fðzÞ,

U � cð Þ �k2 � p2

4L2þ f 2

N 2

@2

@z2

� �fðzÞ

þ b � @2U

@y2� f 2

N 2

@2U

@z2

� �fðzÞ ¼ 0;

ð7Þ

U � cð Þ @

@zfðzÞ � @U

@zfðzÞ ¼ 0: ð8Þ

For the stability analysis, U(z) and N2(z) are derivedfrom the OFES output averaged from 10° S to 14° S, f =3×10−5 s−1, β=2.3×10−11 m−1 s−1, and meridional scale ofeddy L = 500 km is assumed. The lower boundary is set atthe 750-m depth. Eigenvalues (phase velocity) c arenumerically solved for each zonal wavenumber k using anexact diagonalization method by the Linear AlgebraPACKage (LAPACK).

Appendix 2: Sensitivity of heat budget analysisto the reference depth

In Sections 4.2 and 5, the heat budget analyses in theSETIO are conducted with a bottom of the reference box at250-m depth. Here, we show influence of this referencedepth on the heat budget analysis.

728 Ocean Dynamics (2010) 60:717–730

Time series of the 20°C isotherm depth, the mixed-layerdepth, and vertical profiles of the temperature anomalyaveraged in the SETIO (95–115° E, 12° S–3° N) are shownin Fig. 15. Large temperature anomaly variation is locatedbetween 50- and 150-m depths, and the 20°C isotherm islocated around 100-m depth. Furthermore, the mixed-layerthickness is located near 20–30 m, which is much shallowerthan the depth of 20°C isotherm. Significantly coldtemperature anomalies correspond to the positive IODevents which appeared in 1994 and 1997. The 20°Cisotherm was shoaling in these periods. All these varia-bilities occurred in the upper layer shallower than the depthof 200 m.

Ratio of time change of the heat content in the upper 50,100, 150, 200, and 250 m from 1994 to 1998 are shown inFig. 16. While the time series for the boxes shallower than50 and 100 m underestimated the tendency term, the onesfor the boxes deeper than 150 m showed almost the sameamplitude. A much deeper reference depth would providethe same result with the one with using the 250-m referencedepth since all the major variability is already included.

This result justifies the selection of the bottom of the box atany depth deeper than 150 m in the OFES results.

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