Characteristics of Sea Surface Circulation and Eddy Field in the South China Sea Revealed by Satellite Altimetric Data

Journal of Oceanography, Vol. 56, pp. 331 to 344, 2000 Characteristics of Sea Surface Circulation and Eddy Field in the South China Sea Revealed by Satellite Altimetric Data AKIHIKO MORIMOTO 1 *, KOICHI YOSHIMOTO 1 and TETSUO YANAGI 2 1 Department of Civil and Environmental Engineering, Ehime University, Matsuyama 790-8577, Japan 2 Research Institute for Applied Mechanics, Kyushu University, Kasuga 816-8580, Japan (Received 20 May 1999; in revised form 14 September 1999; accepted 21 October 1999) Temporal and spatial variations of sea surface circulation in the South China Sea were revealed with use of altimetric data provided by TOPEX/POSEIDON from December 1992 to October 1997. The estimated distribution of sea surface dynamic heights from altimetric data coincide well with the results of observation by Soong et al. (1995) and Chu et al. (1998). The RMS variability of sea surface dynamic height, which is obtained after tidal correction based on Yanagi et al. (1997), is high in the central part of the South China Sea, the Gulf of Tongking, the Sunda Shelf and the Gulf of Thailand. The high RMS variability in the Gulf of Tongking, the Sunda Shelf and the Gulf of Thailand is due to set up and set down of sea water by the East Asian monsoon, which is northeasterly during winter and southwesterly during summer. Also, the high RMS variability in the central part of the South China Sea is due to the variations of basin-wide circulation. The circulations are dominant in the central part of the South China Sea during summer and winter, an anticyclonic circulation during summer and a cyclonic circulation during winter. It is suggested that these circulations are controlled by the East Asian monsoon. Hence, there is an interannual variability of the basin-wide circulation associated with the variation of the East Asian monsoon. Keywords: Sea surface circulation, South China Sea, altimetric data. 1. Introduction The South China Sea, surrounded by the Asian continent, Borneo, Palawan, Luzon and Taiwan, is one of the largest marginal seas in the world. The maximum water depth is more than 5000 m in the central part of the South China Sea (Fig. 1). The deep basin is bordered by two continental shelves shallower than 200 m. One is located in the northern part of the South China Sea, the Gulf of Tongking and south of China. The other is located in the southern part of the South China Sea, the Gulf of Thailand and the Sunda Shelf. Water exchange between the South China Sea and the Pacific Ocean has mainly taken place through the Luzon Strait, where a sill develops and the water depth is about 2000 m. The seasonal variation of the wind stress field obtained by Hellerman and Rosenstein (1983) is shown in Fig. 2. The northeastward wind stress dominates off * Corresponding author. E-mail: amorimo@dpc.ehime-u.ac.jp Copyright The Oceanographic Society of Japan. Vietnam and the southwestward wind stress dominates in the vicinity of Taiwan in September. The large southwestward wind stress appears in the northern part of the South China Sea in October. In December, the maximum southwestward wind stress appears in the whole area. There is no dominant wind stress in May and the northeastward monsoon dominates in the central part of the South China Sea in August. The circulation in the South China Sea is mainly driven by such wind field (Wyrtki, 1961). It is suggested that an anticyclonic circulation has existed in summer and a cyclonic one in winter, which are generated by the monsoon, from the results of a numerical model (Shaw and Chao, 1994). As for the eddy field in the South China Sea, Soong et al. (1995) has revealed that a cyclonic eddy existed in the west of the Luzon Island from January 1 until January 15 from a result of the trajectory of a drifting buoy and sea surface dynamic height estimated from altimetric data of TOPEX/POSEIDON. Also, Chu et al. (1998) suggested that warm and cold eddies exist in the central part of the South China Sea from the results of observation 331

Fig. 1. The South China Sea. Numbers show the depth in meters. using AXBT data (Airborne Expendable Bathythermograph). However, these studies only revealed the snap shot of the eddy field in the South China Sea so that we do not understand the temporal and spatial variations of eddy field. Recently, Shaw et al. (1999) examined the sea surface elevation in the South China Sea with use of the TOPEX/POSEIDON altimetric data from 1992 to 1995, which used almost the same data set as the present study. They showed several snapshots of the sea level field to characterize the seasonal patterns and their variations in different years. Also, seasonal and inter-annual variations of sea level and the wind stress curl were described in terms of empirical orthogonal modes. Their results suggested that the wind stress curl is the main driving force of the circulation in the deep basin of the South China Sea except near the Luzon Strait. This means that the variation of circulation in the central part of the basin is associated with strong (weak) wind stress curl in normal (weak) years related to the period of La Niña (El Niño). However, in order to carry out the tidal correction of altimetric data, which is most difficult in respect of the corrections of altimetric data in the marginal seas, the altimetric data in their study were spatially and temporally smoothed using weighting functions. Signals shorter than about a month were removed due to this processing. Furthermore, the processing could not correctly eliminate the tidal signals of K 1 and P 1 constituents in the central basin. Yanagi et al. (1997) has developed a method of tidal correction using the harmonic analysis. In this study, tidal signals are eliminated from the altimetric data on the basis of the results of Yanagi et al. (1997). We try to determine the average sea surface circulation every season, and the temporal and spatial variations of the eddy field in the South China Sea with use of altimetric data of TOPEX/POSEIDON during about five years. 2. Altimetric Data Processing We use altimetric data from TOPEX/POSEIDON in order to reveal the sea surface circulation every season and the characteristics of the eddy field in the South China Sea. The satellite TOPEX/POSEIDON was launched in August 1992 and has continued to obtain altimetric data every 10 days along 17 subsatellite tracks in the South China Sea, as shown in Fig. 3. The data have been pro- 332 A. Morimoto et al.

Fig. 2. Wind stress distribution derived from Hellerman and Rosenstein (1983). Fig. 3. The observation lines of TOPEX/POSEIDON. vided as Generation B Merged Geophysical Data Records (MGDR-B) by the Physical Oceanography Distributed Active Archive Center at Jet Propulsion Laboratory, USA. We only use the data from the TOPEX altimeter from Cycle 11 (December 1992) until Cycle 185 (October 1997) in this analysis. Standard data correction, including electromagnetic bias correction, ionospheric correction, dry and wet tropospheric correction, solid earth tide correction and loading tide correction were made using the values provided in the MGDR-B. The altimetric data are originally obtained about every 1 second (corresponding to about every 6.2 km along the subsatellite track, which is the projection of the satellite track on the sea surface) but the data points differ every cycle. Therefore, we linearly interpolated every data value in a cycle at the fixed points within a 6.2 km interval along the subsatellite track. Tidal signals of M 2, S 2, O 1, K 1 and P 1 constituents, which have an amplitude Characteristics of Sea Surface Circulation and Eddy Field in the South China Sea 333

of more than 7 cm in the South China Sea, are eliminated on the basis of the results of Yanagi et al. (1997). After these processing steps, seven data points are further averaged in order to reduce small-scale phenomena observed along subsatellite tracks. The estimated sea surface height of TOPEX/ POSEIDON altimetric data after several corrections at the point r at time t, S(r, t), is expressed by the following formula: S(r, t) = ζ(r, t) + {N(r) + ε n (r)} + {ε s (r) + ε r (t)} + ε m (t), (1) where ζ(r, t) denotes the sea surface dynamic height, N(r) the geoid, ε n (r) the error of geoid, ε s (r) + ε r (t) the spatial and temporal components of orbit error and ε m (t) the measurement error. The sea surface dynamic height ζ(r, t) is divided into the temporal average height ζ m (r) and the anomaly ζ (r, t): ζ(r, t) = ζ m (r) + ζ (r, t). (2) Altimetric data S(r, t) have to be divided into the temporal average value S m (r) and the anomaly S (r, t) due to the fact that the accuracy of geoid data is not adequate: S(r, t) = S m (r) + S (r, t). (3) From Eqs. (1) to (3), we get S (r, t) = ζ (r, t) + ε r (t) + ε m (t). (4) We ignore the temporal averages of ε r (t) and ε m (t) because they are small. ζ (r, t) is divided into the temporal mean during the period of q, ζ mq (r), and the anomaly ζ (r, t): ζ (r, t) = ζ mq (r) + ζ (r, t). (5) Substituting Eq. (5) into Eq. (4), we get S (r, t) = ζ mq (r) + ζ (r, t) + ε r (t) + ε m (t) = H q (r) + E (r, t q ), (6) where t q denotes an arbitrary time during the period of q and H q (r) = ζ mq (r) (7) E (r, t q ) = ζ (r, t) + ε r (t) + ε m (t). (8) We estimate H q (r) with the error of E (r, t q ) by the optimal interpolation method (Imawaki et al., 1991) using observed S (r, t): S (r, t q ) = H q (r) + E (r, t q ) (9) Fig. 4. The distribution of the data that are applied for the optimal interpolation method (a) and the estimated error (b). Numbers show the estimated error in centimeters. 334 A. Morimoto et al.

N ()= ( ) ( 10) H q r α rxs x, tq. x = 1 expressed as φ( t) = σ 0 2 δ( t). (15) Here, α rx denotes the matrix which we want to obtain: N 1 α rx C rx A sx s= 1 =, ( 11) C rs = W(r r s ). (12) Where r denotes the point where we want to estimate H q (r), and r s the points with the number s where the observed data exist. W(r r s ) denotes the covariance function of signal and it is expressed as W( R ) = w 0 2 exp{ ( R /L) 2 }, (13) where R denotes the distance between two points, L the decorrelation scale and w 0 the magnitude of the signal (=7.2 cm in this case). We adopted the decorrelation scale L as 270 km in terms of the cross-separation of subsatellite tracks (=about 300 km). A sx = W(r s r x ) + φ( t), (14) where A sx denotes the covariance function of obtained data at r s and r x, φ( t) the covariance function of noise and is Here, σ 0 denotes the magnitude of noise (=5.8 cm in this study). δ( t) is 1.0 at t = 0 and 0.0 in the other cases. The magnitudes of w 0 and σ 0 are decided on the autocorrelation function. The reason why σ 0 is greater than the measurement error (about 3 cm) is that σ 0 includes the temporal variation of the sea surface dynamic height during 10 days. An example of distribution of the data that are applied for the optimal interpolation method is shown in Fig. 4(a) and the estimated error is shown in Fig. 4(b). It can be seen that the data distribute in the whole area of the South China Sea and the estimated error is relatively small there, being less than 3 cm. 3. Results In order to verify estimated sea surface dynamic height derived from altimetric data, the results obtained are compared with the results of Soong et al. (1995) and Chu et al. (1998). The averaged sea surface dynamic height from January 2 in 1994 until January 12 in 1994 is shown in Fig. 5(a) and the result of the drifting buoy trajectory by Soong et al. (1995) at nearly the same time are shown in Fig. 5(b). Comparing both figures, a cold eddy at 17 N, 117 E shown in Fig. 5(a) agrees well with a cold eddy shown in Fig. 5(b). According to the result of Soong et al. (1995), the speed of the drifting buoy was between Fig. 5. The average sea surface dynamic height calculated from altimetric data from January 2 in 1994 until January 12 in 1994 (a) and the result of drifting buoy trajectory (b) (after Soong et al., 1995). Characteristics of Sea Surface Circulation and Eddy Field in the South China Sea 335

Fig. 6. Average sea surface dynamic height calculated from altimetric data from May 12 in 1995 until May 21 in 1995 (a) and water temperature at the sea surface derived from AXBT data (b) (after Chu et al., 1998). 30 cm/s and 50 cm/s but the speed of geostrophic current estimated from our result is about 20 cm/s. The reason why our result is smaller than that of Soong et al. (1995) is that altimetric data are smoothed by the decorrelation scale L in the optimal interpolation method, as in Eq. (13). The average sea surface dynamic height from May 12 in 1995 until May 21 in 1995 is shown in Fig. 6(a) and water temperature at the sea surface derived from AXBT data by Chu et al. (1998) is shown in Fig. 6(b). A low sea surface height region off Vietnam, which is shown as A in Fig. 6(a), coincides with a low water temperature region shown in Fig. 6(b). A high sea surface height region, which is shown as B in Fig. 6(a), coincides with a high water temperature region shown in Fig. 6(b). A cold eddy in the vicinity of the Luzon Strait, which is shown as C, coincides with a low water temperature region shown in Fig. 6(b). A warm eddy in the central part of the South China Sea, which is shown as D in Fig. 6(a), coincides with a high water temperature region shown in Fig. 6(b). From these comparisons, it can be seen that the average sea surface dynamic height derived from TOPEX/ POSEIDON altimetric data can well reproduce the eddy field in the South China Sea. The temporal fluctuations of sea surface dynamic height in the South China Sea from June 7 until July 16 in 1993 are shown in Fig. 7. A warm eddy, which is shown as W1, tends to propagate westward with a speed of about 10 cm/s from the vicinity of the Luzon Strait to the Gulf of Tongking. Assuming as H = 300 m, β = 2.3 10 11 m 1 s 1, g* = 2.0 10 2 ms 2 and f = 4.2 10 5 s 1, the phase speed of the first baroclinic mode Rossby Wave in this region is about 8 cm/s. Here H is the vertical eddy scale, β the planetary beta, g* the reduced gravity and f the Coriolis parameter at 17 N. Although the propagation speed of the warm eddy is a little greater than the theoretical one, this result suggests that the eddy propagates westward as the first baroclinic mode Rossby Wave. A warm eddy, which is shown as W2, is stationary off Vietnam. In the other period, the warm and cold eddies which are generated near the Luzon Strait tend to propagate westward. On the other hand, the warm and cold eddies which are generated off Vietnam tend to be stationary there. We have calculated seasonally averaged sea surface dynamic height during about five years. Here, we define each season as spring being from March to May, summer from June to August, autumn from September to November, and winter from December to February, in terms of variations of the monsoon. Wu et al. (1998) and Shaw et al. (1999) have showed the snapshots of the distribution of sea surface height, which are calculated from TOPEX/ POSEIDON altimetric data and a numerical model. However, no one has ever showed the seasonally averaged sea surface height in the South China Sea. Seasonally averaged sea surface dynamic heights are shown in Fig. 8. In spring, an anticyclonic circulation 336 A. Morimoto et al.

Fig. 7. The temporal fluctuation of sea surface dynamic height from June 7 in 1993 until July 16 in 1993. Numbers show the sea surface dynamic height in centimeters. exists off Vietnam and a cyclonic circulation exists in the northern part of the South China Sea, as shown in Fig. 8(a). In summer, an anticyclonic basin-wide circulation develops in the central part of the South China Sea and an anticyclonic circulation exists in the southeast of Vietnam, as shown in Fig. 8(b). The low sea surface height regions exist in the Sunda Shelf and the Gulf of Tailand. In autumn, a cyclonic circulation develops off Vietnam, which is opposite to the spring circulation, and an anticyclonic circulation exists in the east of the Luzon Strait, as shown in Fig. 8(c). In winter, a cyclonic basin-wide circulation develops in the central part of the South China Sea and a cyclonic circulation exists in the southeast of Vietnam, as shown in Fig. 8(d). The high sea surface height regions exist in the Sunda Shelf and the Gulf of Tailand. There are some disparities between the seasonal averaged sea surface height and the snapshots derived from Shaw et al. (1999). This means that circulation in each season has a large month-to-month variability. Characteristics of Sea Surface Circulation and Eddy Field in the South China Sea 337

Fig. 8. Seasonally averaged sea surface dynamic height in spring (a), summer (b), autumn (c) and winter (d). 4. Discussion Assuming the geostrophic balance, we calculate the sea surface current velocity for every season and the results are shown in Fig. 9. In these figures, the geostrophic currents are calculated in the areas north of 5 N, because the geostrophic balance cannot be correctly assumed in the low latitude. In spring, an anticyclonic circulation with speeds of about 10 cm/s exists off Vietnam and a cyclonic circulation with speeds of a few cm/s obtains in the northern part of the South China Sea, as shown in Fig. 9(a). In summer, there is a northeastward current along the coast of Vietnam and the continental shelf south of China. The speed of this current is about 20 cm/s in the southern part of the South China Sea and about 5 cm/s in the northern part as shown in Fig. 9(b). An anticyclonic basin-wide circulation with speeds of 5 10 cm/s develops in the central part of the South China Sea and an anticyclonic circulation with speeds of about 10 cm/s exists in the southeast of Vietnam in summer. The sea surface current fields in August, which were obtained by Levitus (1982) and Shaw and Chao (1994), are shown in Figs. 10(a) and (a ), respectively. Both figures represent almost the same feature in the whole area of the South China Sea. Comparison of these figures with our result, shown in Fig. 9(b), shows some discrepancies between them in 338 A. Morimoto et al.

Fig. 9. Seasonally averaged sea surface current velocity in spring (a), summer (b), autumn (c) and winter (d). the central part of the basin and near the Luzon Strait. Levitus (1982) and Shaw and Chao (1994) show strong eastward currents leaving the Vietnam coast in the central part and northward currents near the Luzon Strait, while our result shows the westward current along 15 N and the southward current in the vicinity of the Luzon Strait. We will discuss these discrepancies between our result and Figs. 10(a) and (a ) later. The current patterns coincide with each other, except in the central part of the basin and near the Luzon Strait, but the current velocity of our result is smaller than Levitus (1982) and Shaw and Chao (1994). We think that since our results are smoothed by the decorrelation scale L (=270 km) in the optimal interpolation method and averaged over 3 months, the current velocity, which is estimated from the altimetric data, is underestimated. In autumn, there are five circulations in the South China Sea as shown in Fig. 9(c). The largest cyclonic circulation with a speed of about 10 cm/s is located east of Vietnam. In winter, there is a southwestward current along the continental shelf south of China and the coast of Vietnam. The speed of this current is 5 cm/s in the northern part of the South China Sea and 15 20 cm/s in the south- Characteristics of Sea Surface Circulation and Eddy Field in the South China Sea 339

Fig. 10. Sea surface current velocities in August and December, estimated from ship drifts (a) and (b) (after Levitus, 1982), and from the numerical experiment (a ) and (b ) (after Shaw and Chao, 1994). ern part as shown in Fig. 9(d). Comparing the winter current field with the results of Levitus (1982) and Shaw and Chao (1994) in December shown in Figs. 10(b) and (b ), respectively, the current pattern of our result coincides well with their results, except in the central part of the basin. Levitus (1982) shows a westward current in the central part of the basin but our result shows an eastward current along 15 N. There are large discrepancies in the current velocities between them. Because our results are smoothed by the decorrelation scale L in the optimal interpolation method and are averaged over 3 months, the current velocity, which is estimated from altimetric data, is underestimated. And also it is possible that current velocity of Levitus (1982) does not have sufficient accuracy, because these current velocities were estimated from ship drifts. In this study, the seasonally averaged sea surface current velocity is calculated by using only temporal fluctuation component of sea surface dynamic height obtained from the altimetric data. In order to estimate the absolute sea surface current velocity, we have to combine the temporal mean component of sea surface current velocity and temporal fluctuation component as Eq. (2). Therefore, the discrepancies between our result and the previous studies in summer and winter current fields may be happened. Indeed, Shaw et al. (1999) suggested that there is a disparity between the summer anticyclonic gyre and the winter cyclonic gyre associated with asymmetric variation of summer and winter monsoon. Also Metzger and Hurlburt (1996) have suggested that there is an eastward current throughout the year along 15 N with a speed of about 10 cm/s from the result of the numerical experi- 340 A. Morimoto et al.

ments. These discrepancies between summer and winter current fields shown in Fig. 9 and those shown in Fig. 10 seem to imply that an eastward current exists throughout the year in the central part of the basin. However, if there is an eastward current along 15 N throughout a year as Metzger and Hurlburt (1996) suggested, the current directions along 15 N both in summer and winter shown in Fig. 9 would not show the opposite current directions. Because if there is an eastward current along 15 N with the speed of about 10 cm/s (Metzger and Hurlburt, 1996), the current field in winter in Fig. 9(d) must show a strong eastward current along 15 N with a speed of about 20 cm/s. However, Figs. 10(b) and (b ) do not show a stronger eastward current. Hence we have to examine the mean sea surface height with use of a numerical model or climatological data set of water temperature and salinity in the near future. But it is supposed that we can to some degree describe the average sea surface current field in the South China Sea using only the temporal fluctuation component of sea surface dynamic height at the moment. In order to examine the characteristic of spatial variation of sea surface dynamic height, we calculate RMS (Root Mean Square) variability of the temporal fluctuation of sea surface dynamic height in the South China Sea derived from altimetric data during five years. The distribution of the RMS variability is shown in Fig. 11. There is high RMS variability in areas in the central part of the basin, off Vietnam, the Gulf of Tongking, the Sunda Shelf and the Gulf of Tailand. The high RMS variability in the Gulf of Tongking, the Sunda Shelf and the Gulf of Tailand is due to the set up and set down of sea water by the monsoon wind because of the shallow water depth. On the other hand, although the water depth is about 5000 m in the central part of the South China Sea, a high RMS variability appears there. It is supposed that the high RMS variability area in the central part of the basin is due to the variation of basin-wide circulation. This is because this area corresponds to the region where basin-wide circulation develops during winter and summer, as shown in Figs. 8(b) and (d). We are going to investigate in detail the mechanism of high RMS variability area in the central part of the South China Sea in our next paper. Here, we focus on the temporal variation of basinwide circulation in the central part of the South China Sea. A time-space plot of the sea surface dynamic height along the solid line shown in Fig. 11 is depicted in Fig. 12. The positive or negative sea surface dynamic height changes seasonally. The positive value appears off Vietnam in March or April and it gradually expands to the northeastward. In June or July, the sea surface dynamic heights become positive in the whole area. In August, the negative value appears off Vietnam and it gradually expands to the northeastward. In December, the sea surface dynamic height assumes a negative value in the whole Fig. 11. Distribution of RMS variability of temporal fluctuation of sea surface dynamic height. area. It is supposed that these variations denote the development process of basin-wide circulation. The phase of these phenomena seems to correspond to the variation of the wind field. In others words, the basin-wide circulation is generated by the wind stress or wind stress curl. We also examine inter-annual variability in Fig. 12. The negative values appear off Vietnam in July or August 1993, 1994, 1996 and 1997 and they expand to the northeastward. However, the negative value does not appear by October in 1995 and it rapidly expands to the whole area in the central part of the South China Sea. The inter-annual variability is expected to be associated with the variation of monsoon wind. According to Wu et al. (1998), the monsoon in the South China Sea is weak at the period of El Niño while it is strong during the period of La Niña. The time series of monthly mean SST anomalies at Nino-3, which is located in the eastern part of the equatorial Pacific Ocean, is shown in Fig. 13 (Japan Meteorological Agency, 1999). In this figure, a positive anomaly denotes an El Niño period and a negative anomaly a La Niña period. From this figure, 1995 and 1996 are La Niña. It is thus suggested that the basin-wide circulation in 1995 is changed by the strong monsoon related to La Niña. However, we do not investigate the detailed correlation between the circulation and wind field in the present study; we expect to reveal the relationship between the circulation and the wind field in the near future. Characteristics of Sea Surface Circulation and Eddy Field in the South China Sea 341

Fig. 12. Time-space plot of sea surface dynamic height along the line shown in Fig. 9. Numbers show the sea surface dynamic height in centimeters. Dark tones denote negative values. 342 A. Morimoto et al.

Fig. 13. Time series of monthly mean sea surface temperature anomalies at Nino-3, which is located in the eastern part of the equatorial Pacific Ocean. 5. Conclusions We can exactly obtain the eddies and seasonally averaged circulation patterns in the South China Sea by using TOPEX/POSEIDON altimetric data. The sea surface dynamic heights estimated from altimetric data coincide well with the earlier studies by Soong et al. (1995) and Chu et al. (1998). There are a lot of warm and cold eddies in the South China Sea. These eddies are generated in the vicinity of Luzon Strait and tend to propagate westward to the Gulf of Tongking as the first baroclinic mode Rossby Wave. As for the seasonally averaged circulation, an anticyclonic circulation exists off Vietnam and a cyclonic one in the northern part of the South China Sea in spring, and an anticyclonic basin-wide circulation develops in the central part of the South China Sea and a cyclonic circulation in the southwest of Vietnam in summer. The circulation pattern in autumn is opposite to that in spring, and the in winter pattern is opposite to that in summer. These circulations are considered to be controlled by the East Asian monsoon because these phenomena have a seasonal period with a phase that seems to agree with that of the monsoon. There are high RMS variability areas in the central part of the basin, off Vietnam, the Gulf of Tongking, the Sunda Shelf and the Gulf of Tailand. The high RMS variability in the central part of the basin is due to the variation of basin-wide circulation and those in other areas are due to the pile up and pile down by the monsoon wind. We still have to investigate the detailed process of development of the basin-wide circulation and the relationship between the wind field and the circulation. Also characteristics of the propagation and generation of warm and cold eddies have to be studied in the near future. Acknowledgements The authors express their sincere thanks to Prof. H. Takeoka, Mr. A. Kaneda and Mr. D. V. Manh of Ehime University for their fruitful discussion. We are grateful to two anonymous reviewers for their critical reading and useful comments. The TOPEX/POSEIDON altimetric data were provided by the Physical Oceanography Distributed Active Archive Center at Jet Propulsion Laboratory. References Chu, C. P., C. Fan, C. J. Lozano and J. L. Kerling (1998): An airborne expendable bathythermography survey of the South China Sea, May 1995. J. Geophys. Res., 103, C10, 21637 21652. Hellerman, S. and M. Rosenstein (1983): Normal monthly wind stress over the world ocean with error estimates. J. Phys. Oceanogr., 13, 1093 1104. Imawaki, S., K. Ichikawa and H. Nishigaki (1991): Mapping the mean sea surface elevation field from satellite altimetry data using optimal interpolation. Marine Geodesy, 15, 31 46. Japan Meteorological Agency (1999): Monthly Ocean Report. January 1999, 34 pp. Levitus, S. (1982): Climatological atlas of the World Ocean. NOAA Professional Paper No. 13, U.S. Government Printing Office, Washington, D.C., 173 pp. Metzger, E. J. and H. E. Hurlburt (1996): Coupled dynamics of the South China Sea, the Sulu Sea, and the Pacific Ocean. J. Geophys. Res., 101, C5, 12331 12352. Shaw, P. T. and S. Y. Chao (1994): Surface circulation in the South China Sea. Deep-Sea Res., 41, 1663 1683. Characteristics of Sea Surface Circulation and Eddy Field in the South China Sea 343

Shaw, P. T., S. Y. Chao and L. L. Fu (1999): Sea surface height variations in the South China Sea from satellite altimetry. Oceanologica Acta, 22, 1 17. Soong, Y. S., J. H. Hu, C. R. Ho and P. P. Niiler (1995): Coldcore eddy detected in South China Sea. EOS Trans. AGU, 76, 345 347. Wu, C. R., P. T. Shaw and S. Y. Chao (1998): Seasonal and interannual variations in the velocity field of the South China Sea. J. Oceanogr., 54, 361 372. Wyrtki, K. (1961): Physical oceanography of the Southeast Asian waters. NAGA Report Vol. 2, Scientific Results of Marine Investigation of the South China Sea and the Gulf of Thailand, Scripps Institution of Oceanography, La Jolla, California, 195 pp. Yanagi, T., T. Takao and A. Morimoto (1997): Co-tidal and corange charts in the South China Sea derived from satellite altimetry data. La mer, 35, 85 93. 344 A. Morimoto et al.