3~6 Months Variation of Sea Surface Height in the South China Sea and Its Adjacent Ocean

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1 Journal of Oceanography, Vol. 57, pp. 69 to 78, ~6 Months Variation of Sea Surface Height in the South China Sea and Its Adjacent Ocean JIANYU HU 1,2, HIROSHI KAWAMURA 2 *, HUASHENG HONG 1, FUMIAKI KOBASHI 2 and DONGXIAO WANG 3 1 College of Oceanography and Environmental Science, Marine Environmental Laboratory of Ministry of Education of China, Xiamen University, Fujian , China 2 Center for Atmospheric and Oceanic Studies, Faculty of Science, Tohoku University, Sendai , Japan 3 LED, South China Sea Institute of Oceanology, Chinese Academy of Sciences, 164 W. Xingang Rd., Guangzhou , China (Received 1 February 2000; in revised form 7 July 2000; accepted 20 September 2000) Sea surface height (SSH) variations with a period of 3~6 months (SSH36 variations) in the South China Sea (SCS) and its adjacent ocean are intensively investigated using six years of TOPEX/POSEIDON-derived SSH data. The results show that there appears higher energy of SSH36 variations in the east of the Luzon Strait and in some areas of the SCS, both of which are correlated with each other. The SSH36 variations usually propagate westward in the subtropical region of the northern Pacific Ocean and turn northward in the east of the Luzon Strait while they sometimes propagate into the SCS through the Luzon Strait with the phase speed of about cm/s, which may be considered as Rossby waves. It can be inferred that the SSH36 variations are strongly associated with current structures and eddies in the SCS because of their significant intensiveness. The SSH variations with the period of 6 months are more dominant than those with the other periods in the SCS. Keywords: Sea surface height, 3~6 months variations, TOPEX/ POSEIDON altimeter data, South China Sea. 1. Introduction The South China Sea (SCS) is the largest marginal sea in the Southeast Asia. A basin deeper than 4000 m in the central region is surrounded by some shallow water areas and coastal seas less than 200 m in the Gulf of Thailand and the Gulf of Tonkin. The SCS extends from the equator to 23 N and from 99 E to 121 E (Shaw and Chao, 1994) and connects to the North Pacific Ocean (NPO) through the Luzon Strait between the Taiwan Island and the Luzon Island (see Fig. 1(a)). Hu et al. (2000) reviewed the seasonal SCS circulation pattern described by many researches based on the current data: TS distributions, ship drift data, numerical computations under specific conditions and a few satellite data. They summarized the SCS circulation pattern as follows: (1) Since the SCS is situated in the monsoon regime, effects of the monsoon wind are dominant and the SCS current is the Ekman drift at the top layer (approximately 0~5 m), which is considered in accord with * Corresponding author. kamu@ocean.caos.tohoku. ac.jp Copyright The Oceanographic Society of Japan. the local wind direction. (2) As for the mean circulation in the upper layer (0~200 m), it is cyclonic in winter but anticyclonic in summer. There are two cyclonic eddies in winter, which are located in the west of the Luzon Island and in the southeast of the Zhongnan Peninsula, respectively. An anticyclonic eddy appears in the southeast of the Zhongnan Peninsula and another cyclonic eddy in the east of the Vietnam coast in summer. Recently, Morimoto et al. (2000) also described the similar patterns of the SCS sea surface circulation and its temporal and spatial variations with the use of TOPEX/POSEIDON (T/P) altimeter data from 1992 to The above mentioned circulation is related to the water exchange between the SCS and the Kuroshio through the Luzon Strait, which may induce some local current structures in the northern SCS (NSCS). Both hydrographic observations and numerical experiments suggest that a southwestward current, which is considered to originate from the Kuroshio, flows into the SCS through the Luzon Strait and reaches the sea area near the Dongsha Islands in winter. However, many researches point out that the Kuroshio does not enter into the SCS in summer, instead it may intrude into the SCS with a form of loop at the most. Hu et al. (2000) summarized and 69

2 Fig. 1. Map of the South China Sea and T/P tracks in the studied area. DS and HN indicate the Dongsha Islands and the Hainan Island. The lines specified by S-A and S-B are the selected sections for the diagrams shown in Fig. 7. (a) Map of the SCS and (b) T/P data points used in this study. demonstrated a schematic intrusion path of the Kuroshio in summer. They suggested that the Kuroshio intrudes into the NSCS with a loop form when it passes by the Luzon Strait while two unstable offshoots might extend towards the southeast of the Dongsha Islands and the southwest of the Taiwan Island, respectively. The variable intrusion path in summer may be caused by the inter-annual variation of the Kuroshio s path and the oceanographic conditions in the western NPO. It is well known that the Subtropical Countercurrent (SCC) accompanied by a subtropical front (STF) positioned at N (Uda and Hasunuma, 1969), flows eastward in the western NPO. Hasunuma and Yoshida (1978) indicated that the long-term mean dynamic topography is higher in the STF region than in its surroundings. White et al. (1978) pointed out that the SCC is strong in spring and weak in autumn. By using the SSH data derived from the Geosat altimeter and the Sea Surface Temperature (SST) data derived from the Advanced Very High Resolution Radiometer (AVHRR) on board the NOAA 11, Kawamura et al. (1995) investigated the STF and found a wavy undulation of the STF propagating westward at around 25 N. This westward propagation of the undulation has a wavelength of km and phase speed of 7 8 cm/s at 25 N, and the period is estimated as 3~6 months. Kobashi and Kawamura (2000) investigated this sea surface height (SSH) variation in the NPO using the T/P altimeter data of about 5 years and found that some meso-scale wave-like eddies propagating westward in the zonal band of about N east of the Hawaii Islands cause the 3~6 months SSH variations (SSH36 variations hereafter) in the STF region. These wave-like eddies coalesce into the Kuroshio. The bottom topography must influence on their generation, growth and disappearance. These researches suggest the existence of the SSH36 variations in the western NPO which propagate westward and are much related to the transport and path of the Kuroshio. However, Kobashi and Kawamura (2000) did not deal with interaction of this wave-like and westward propagating SSH36 variations and the SCS, though their energetic latitude band of N faces to the Luzon Strait. There is no report mentioning such interaction between the NPO and SCS through the wave-like eddies with the period of 3~6 months (Hu et al., 2000). Recently, Shaw et al. (1999) examined the SSH variations in the SCS with the use of the T/P altimeter data from 1992 to However, they only focused on the seasonal pattern of sea level field in the SCS and described the seasonal and inter-annual variations of the sea level and wind stress curl in terms of empirical orthogonal functions, suggesting that the wind stress is the main driving force of the circulation in the deep basin of the SCS. The purposes of the present study is to investigate the behaviour of the SSH36 variations around the Luzon Strait and in the SCS, and the interaction between the western NPO and SCS by using 6 years of the T/P altimeter data. The method used for data processing is briefly described in the next section. Section 3 indicates detection of the SSH36 variations by using spectrum analysis and wavelet analysis. Section 4 demonstrates some characteristics of the SSH36 variations in the NPO and the SCS. Discussion and summary are finally given in Section 5 and Section 6, respectively. 2. Altimeter Data and Data Processing TOPEX/POSEIDON (T/P) was launched on August 10, 1992 and has continued to obtain the altimeter data every days along the T/P tracks. The T/P altimeter data are provided as Merged Geophysical Data Record Generation B (MGDR-B) by the Physical Oceanography Distributed Active Archive Center (PO.DAAC) at the Jet Propulsion Laboratory (JPL). The satellite altimeter data is useful for the study of the geostrophic currents in the deep water ocean. The tide 70 J. Y. Hu et al.

3 models applied to the altimeter data can successfully eliminate the tidal signals from the SSH data with the accuracy enough for the ocean dynamics study, because the root mean square errors against the in situ SSH measurements are 2~3 cm in the deep ocean (Fu et al., 1994; Shum et al., 1997) even though the tide models may be bigger with the grid size of about 3~5 degrees. However, the satellite altimeter data, even after the tidal signals being removed by the selected ocean tide models, can not be directly used for studying the shallow water regions where the temporal and spatial gradients of tide are much greater than those in the deep water ocean and the tideinduced SSHs show complicated small-scale features. It is known that the above-stated ocean tide models are not applicable to the shallow water areas (Yanagi et al., 1997), and the T/P altimeter data have a strong high frequency aliasing in the shallow water areas such as in the continental shelves along the SCS (Li et al., 1999). Therefore, the tide model needs to be improved before applying to the T/P altimeter data to analyze the oceanographic conditions in the SCS. The algorithms provided by the PO.DAAC are firstly used to calculate the height of the sea surface above the reference ellipsoid, and the tide-included sea surface height is obtained for the harmonic analysis after removing the abnormal values. Some extreme values greater than 5 m are removed because the maximum spring tidal amplitude is reported about 2 m in the SCS (Huang et al., 1994). We spatially and temporally interpolate the processed SSH data on the reference ground track, and resample them at the fixed points with interval of about one second the same as the way of the NASA Pathfinder SLA data (Version 5.1, see the WWW site for the detailed features on this data set ( ocean.html)). Data at all points along the ground tracks are used except those without credible data among 4 successive cycles, and the altimeter data of both ascending and descending T/P tracks are also used. In order to estimate variations of the tide-induced SSHs in the SCS and its adjacent ocean, the harmonic analysis is applied on six years of the T/P altimeter data. Eight major tidal constituents (M 2, S 2, K 1, O 1, P 1, S a, N 2 and K 2 ) are analyzed using almost the same way as Yanagi et al. (1997). The outputs of the improved tide model agree well with these developed by Yanagi et al. (1997) though the analysis periods are different. For investigation of the SCS, six years of the T/P altimeter data from Cycle 11 (December 31, 1992) to Cycle 231 (December 31, 1998) are used. The 18 T/P tracks analyzed in the present study are shown in Fig. 1(b) (the studied area hereafter). Data points over the shallow water areas with the depth less than 200 m are not included, since the present study is focused on the wavelike eddies propagating in the deep water and the improved tide model still has some problems in the shallow and near-coast regions. 3. Detection of the SSH Variation with the Period of 3~6 Months 3.1 Spectrum analysis In this sub-section, investigation on dominant periods of the SSH variations in the studied area by means of spectrum analysis is described. The SSH anomaly referred to the whole-period mean at each T/P data point is calculated and the power spectrum density is thus computed by the Fast Fourier Transform method. In order to demonstrate the spatial distributions of the power spectrum density and to make the results more convictive, the ensemble average of power spectral density in the 2 2 area is calculated and plotted out in the diagrams. It can be seen from Fig. 2 that the power spectrum density has significant peaks around the periods of 3, 4 and 6 months, indicating that the SSH variations have dominant periods in the period band between 3 and 6 months. Figures 2(a) and (b) also show that there exists principal period of 3~6 months in the east of the Luzon Strait located near the STF region. Obviously, these results are in good accordance with those investigated by Kawamura et al. (1995) and Kobashi and Kawamura (2000). The period of about 180 days is the most dominant one in the SCS (Figs. 2(c) (f)) with compared to some other dominant ones. In the SCS, except for the existences of dominant period of 3~6 months, another dominant period of about 45 days can also be found as shown in Figs. 2(c) (f). However, since this frequency is much smaller than those focused on in the present study, we do not consider it furthermore until it becomes be important and needs to be studied. In some areas of the SCS, the appearance of the other peak at the period of about 70 days may be caused by the aliasing by the Q 1 tidal constituents (Li et al., 1999). 3.2 Wavelet analysis A wavelet analysis is employed to extract temporal variations of the important 3~6 months components from the SSH time series at each T/P data point along the T/P tracks in the studied area. The wavelet analysis, carried out by the wavelet transform, is a useful technique to obtain the spectral energy of the time series in a frequencytime domain. It decomposes a time series into the timefrequency space simultaneously so that one can get information on both the amplitude of any periodic signals within the series and how this amplitude varies with time. As the Mother wavelet, we selected the Morlet wavelet which was proposed by Morlet et al. (1982), and is known as easy handling and widely used. The Morlet 3~6 Months Variation of Sea Surface Height in the South China Sea and Its Adjacent Ocean 71

4 Fig. 2. Ensemble averaged power spectrum density (cm 2 /cpd) in some representative 2 2 areas, which are: (a) (22 24 N, E); (b) (18 20 N, E); (c) (20 22 N, E); (d) (16 18 N, E); (e) (12 14 N, E) and (f) (8 10 N, E). cpd means cycle per day. Confidence level of 95% is indicated in the upper-left corner of each figure. wavelet consists of a plane wave modulated by a Gaussian envelope and is defined as (Torrence and Compo, 1998): ( )=, () 1 14 ωη η η 2 Ψ 0 η π / i e e / where ω is nondimensional frequency and here taken to be 6 to satisfy the admissibility condition (Farge, 1992). The continuous wavelet transform of a discrete sequence x n is defined as the convolution of x n with a scaled and translated version of Ψ 0 (η): [( ) ] ( ) Wn ()= s xn Ψ n n δ t / s, 2 where the (*) indicates the complex conjugate and the elimination of the subscript 0 on Ψ indicates that the Ψ 0 has been normalized. Another selection is a set of scaling parameters s, such that we adequately sample all the frequencies present in the time series. That is: jdj ( ) () sj = s0 2 j = 0, 1, 2,..., J, 3 where s 0 is the smallest resolvable scale and J determines the largest scale. We set s 0 = 32, dj = 0.1 and J = 40, which means to divide the period between 32 and 512 days into 41 sub-scales. 72 J. Y. Hu et al.

5 The programs provided by Torrence and Compo (1998) are used to conduct the wavelet analysis and to plot out the wavelet power spectrum and global wavelet spectrum (GWS), which is the time-average of the wavelet power spectrum over all times. The wavelet power spectrum and the GWS at most T/P data points clearly show that a dominant peak of the wavelet power spectrum appears at the period of about 180 days while another at about 45 days (the latter is not discussed further in the present paper). The ensemble average of the GWS is computed in the 2 2 area as the same as that for spectrum analysis. It is indicated that there are some dominant peaks at the periods between 90 and 180 days. The most dominant peak is at around 180 days (about 6 months) in the SCS. The SSH variations are dominant with wider period band between 90 and 180 days in the east of the Luzon Strait while those in the other regions show the dominant period at the period of about 180 days. With corresponding to the results of the spectrum analysis, the GWS also shows another dominant peak at about 45 days in the SCS. Moreover, it is worth mentioning that the dominant peak with the period of 3-6 months is bigger in the east of the Luzon Strait than that in the interior of the SCS, suggesting a decreasing tendency from the NPO towards the SCS (the figures are not shown). 3.3 Energy distribution and global wavelet spectrum distribution of SSH36 variations In order to examine the SSH36 variations, a bandpass filter is employed to extract them from the time series of the SSH variations in the studied area. The temporal filter is a ten-pole, Butterworth recursive filter with a half-power cut-off periods of 80 and 190 days. The beginning and end of the filtered SSH time series are discarded. The energy distribution is calculated by integrating the SSH36 variations at each T/P data point, and is then interpolated onto grids by using a weighted average of the adjacent data points within the search radius r m around the grid point. A parameter y at grid point (m, n) is obtained by using the weighted average: r r 4 ( )= () () ymn, wyr w, where Y(r) is the value of the parameter y at the adjacent data points within a certain defined search radius r m around (m, n). The data weights w r are computed by: w exp d / L, r = 2 2 ( ) ( 5) where d is the spherical distance in degrees between data point r along the T/P track and grid point (m, n) and L is Fig. 3. Distributions of energy and ensemble averaged global wavelet spectrum for SSH36 variations. (a) Energy (unit in cm 2 ) and (b) global wavelet spectrum (unit in cm 2 ). an e-holding scale. We select L = 1.5 and r m = 1.5, which sufficiently smoothes the resulting energy distribution without noticeably distorting the original features. If there is no data point within the search radius, the weighted average is not carried out at that grid point. Figure 3(a) demonstrates the energy distribution in the studied area. It is indicated that there is a higher energy zone exceeding 60 cm 2 in the east of the Luzon Strait (around 17~25 N of the western NPO), corresponding to the higher energy zone described by Kobashi and Kawamura (2000). Figure 3(a) also shows that the higher energy zone extends westward to the Luzon Strait and there exists a relatively higher energy zone (greater than 40 cm 2 ) in the east of the Hainan Island, indicating the high energy of SSH36 variations may propagate toward the SCS. As mentioned above, the GWS is also ensemble averaged in the 2 2 area. Then the ensemble averaged GWS onto grids is interporated by the same weighted average method and construct the spatial distribution of the GWS as shown in Fig. 3(b). In corresponding with the energy distribution, the high GWS zone also exists in the east of the Luzon Strait, almost the same area as that appearing in the energy distribution, and the high GWS zone also extends westward to the Luzon Strait. 3~6 Months Variation of Sea Surface Height in the South China Sea and Its Adjacent Ocean 73

6 4. Examination of the Characteristics of 3~6 Months SSH Variation 4.1 Interaction between the SCS and the NPO for SSH36 variations Cross correlation analysis is made to investigate spatial structure of the SSH36 variations. Zonal and meridional lag correlation between two T/P data points within 500 km are calculated. Figures 4(a) and (b) show that the zonal and meridional spatial scales are broadly similar in the zone east of the Luzon Strait (20 25 N, E), indicating that there exits circular shape eddy with the wavelength of about km. These spatial structures are similar to these found in the N band of the NPO (from 130 E to 150 W) by Kobashi and Kawamura (2000). Since the zonal distance between the T/P tracks is about 290 km in the zone (20 25 N, E), the open circles concentrate at 290 km as shown in Fig. 4(a). In order to examine the relation of the SSH36 variations between the SCS and the NPO, correlation analysis is applied to the SSH36 time series. A 1 1 reference area is selected in the Luzon Strait (20~21 N, 121~122 E) and then the average lag correlation coefficients between each T/P data point along the T/P tracks and the reference area are calculated. Figure 5 shows that the SSH36 variations in the Luzon Strait have a high correlation with that in the east of the Luzon Strait (Fig. 5(c)). About 20 days (20 T/P cycles) later, the higher correlation coefficient zone appears in the west of the Luzon Strait (Fig. 5(d)), indicating that the SSH36 variations in the west of the Luzon Strait can be traced back in the reference area near the Luzon Strait 20 days before. The sea area in the east of the Hainan Island of the NSCS shows higher correlation coefficient 40 days later (Fig. 5(e)). Then the high correlation coefficient zone moves to the center of the SCS in another 20 days later. From Figs. 5(a) and (b), it can also be seen that the high correlation zone is near the Luzon Strait 10 days before but it is in the east of the Taiwan Island and in the east of the Luzon Island 20 days before. All these indicate that the SSH36 variations may propagate from the NPO into the interior of the SCS through the Luzon Strait. 4.2 Propagation characteristics of SSH36 variations In order to present a simultaneous picture of the SSH36 distribution, we temporally interpolate the SSH36 variation to the same observational time for every T/P cycle. Then, weighted average of the SSH36 variation at each T/P data point is made onto grid for every T/P cycle to investigate the spatial distribution of the SSH36 variations. Among them, six scenes representing the wave-like eddies and their propagation characteristics are selected and shown in Fig. 6. It is easily seen Fig. 4. Cross correlation coefficients with the zonal spatial lag (a) and meridional spatial lag (b). that the SSH36 variations propagate northward in the east of the Luzon Strait. Figure 6(a) shows that a higher energy area comes from the STF region and appears in the east of the Luzon Island at Cycle 073, then it moves northward (as indicated by an arrow in the figure) and becomes an eddy in the east of the Taiwan Island at Cycle 077, while it partially extends to the SCS through the southern Luzon Strait (see Fig. 6(b)). Afterwards, the eddy in the east of the Taiwan Island begins to disappear at Cycle 081. Figures 6(d) (f) specifically demonstrate another propagating pattern in the studied area during Cycle (March 25 June 12, 1996). At Cycle 130, a higher energy area is located in the east of the Luzon Strait and has a tendency to propagate into the SCS (see the arrow in Fig. 6(d)). Then an eddy is seen to be located in the northwest of the Luzon Island at Cycle 134. Figure 6(f) shows that the eddy propagates to the deep basin area of the SCS at Cycle 138. Furthermore, we select two sections (S-A and S-B shown in Fig. 1(a)) to plot the section-time diagram of the SSH36 variations. Figure 7 also indicates that the peak of the SSH36 variations usually propagates westwards in the east of the Luzon Strait, but it can sometimes propagate into the SCS through the Luzon Strait. It is estimated from the solid lines in Fig. 7 that the phase speed of propagation ranges from 7 cm/s to 15 cm/s in the east of the Luzon Strait, which is a little faster than that in the west- 74 J. Y. Hu et al.

7 Fig. 5. Spatial distribution of cross correlation coefficient between the reference area in the Luzon Strait and each T/P data point. The lag time is (a) 20 days, (b) 10 days, (c) zero, (d) 20 days, (e) 40 days and (f) 60 days. The lag time means SSHs at each T/P data point ahead. ern NPO calculated by Kobashi and Kawamura (2000). And the phase speed of propagation is about cm/s if the SSH36 variation propagates into the NSCS. 5. Discussion Many previous studies, such as Emery and Magaard (1976), White and Saur (1983), White (1985) and Kessler (1989), have reported first-mode baroclinic planetary wave signals in the Pacific Ocean using hydrographic data. Boulanger and Fu (1996) also used the T/P sea-level data to investigate the first-mode Rossby waves in the tropical Pacific Ocean. Both hydrographic and satellite observations showed that the westward wave-like propagation is evident in the Pacific Ocean. As for the SCS, some researches, such as by Xu et al. (1982), Qiu et al. (1984, 1985), Guo et al. (1985), Huang et al. (1992), Li et al. (1997, 1998) and Hu et al. (1999), indicated the existence of warm eddy and/or cold eddy in the seas around the Dongsha Islands by using hydrographic observational data. Some of them considered that the formation and variation of the eddies may be caused by the topographically influenced currents in the area. Yuan and Wang (1986) pointed out by using the potential vorticity conservation equation that the bottomtopography forcing effect may be the principal factor for the formation of a warm eddy in the northeast and a cold eddy in the southwest of the Dongsha Islands. However, Ma (1987) developed a numerical model for the NSCS and indicated that the reflection of the incident Rossby waves by the continental slope plays the significant role 3~6 Months Variation of Sea Surface Height in the South China Sea and Its Adjacent Ocean 75

8 Fig. 6. Distribution of SSH36 variations (unit in cm) at some specific cycles. (a) At Cycle 073 (September 9 16, 1994), (b) at Cycle 077 (October 16 26, 1994), (c) at Cycle 081 (November 25 December 5, 1994), (d) at Cycle 130 (March 25 April 4, 1996), (e) at Cycle 134 (May 3 13, 1996) and (f) at Cycle 138 (June 12 22, 1996). The arrow in (a), (d) and (e) shows the possible propagating direction of the eddy. in the intensification of the SCS Warm Current in the NSCS. Li et al. (1997, 1998) proposed that the warm eddy near the Dongsha Islands is a ring detached from the Kuroshio near the Luzon Strait. Obviously, the local current structures and eddies in the NSCS are not always induced by the local topography. Actually, it may be associated with the incident Rossby wave and oceanographic condition of the Kuroshio near the Luzon Strait. Kobashi and Kawamura (2000) indicated that the mesoscale eddies form a wave-like structure, exhibit remarkable westward propagation in the STF of the NPO, and have the zonal phase speed slightly faster than that of the baroclinic first-mode Rossby waves. As stated above, since the SSH36 variations in the SCS sometimes come through the Luzon Strait from the NPO, they can also be considered as the first-mode Rossby waves. Moreover, the propagation of the Rossby wave in the SCS may be affected by the bottom topography of the SCS, which induces the different propagation paths in the SCS. 6. Summary The SSH variations with the period of 3~6 months in the SCS and its adjacent ocean are intensively investigated by using six years of T/P-derived SSH data. It can be concluded that: (1) There appear greater energy of SSH variations with a period of 3~6 months (SSH36 variations) both in the east of the Luzon Strait and in the some areas of the SCS. The SSH36 variations are detected by both spectrum analysis and wavelet analysis. The SSH36 variations 76 J. Y. Hu et al.

9 Japan. Hu would like to express his sincere thanks to Professor G. H. Fang, Dr. A. Morimoto, Dr. O. Isoguchi and all the members in the laboratory who gave him various valuable comments and assisted in the data processing. Authors are much obliged to the editors and anonymous reviewers for their useful comments which enabled to improve the manuscript a great deal. It is also pleasure to acknowledge the efforts of the PO.DAAC at JPL and NASA/GSFC Ocean Altimeter Pathfinder Project. Wavelet software was provided by C. Torrence and G. Compo and is available at URL: research/wavelets. Fig. 7. Section-time diagram of the SSH36 variations (unit in cm) along two specific sections: (a) Section S-A and (b) Section S-B. The section locations are specified by S-A and S-B in Fig. 1(a). The solid lines in the figures indicate the propagation characteristics (see the text). in the SCS have a strong correlation with those in the NPO. (2) The SSH36 variations propagate westward from the western NPO and usually turn to propagate northward in the east of the Luzon Strait, but they sometimes enter into the SCS through the Luzon Strait. The phase speed is about 7 15 cm/s in the east of the Luzon Strait and about cm/s if it propagates into the NSCS. (3) The SSH variations with the period of 6 months are dominated than those with the other frequencies in the SCS. (4) The SSH36 variations in the SCS can be considered as Rossby waves, which may be strongly associated with current structures and eddies in the SCS. Acknowledgements This research is supported by the Key Project (No ) of the Natural Science Foundation of China, the Key Project (No. 98-Z-179) of Fujian Province of China, the State Key Basic Research Program of China (No. G ) and the LED of South China Sea Institute of Oceanology. The study is also supported by Research and Development Applying Advanced Computational Science and Technology, Japan Science and Technology Corporation. The research work is done while Hu s visiting to the Oceanic Variation Research Section, Center for Atmospheric and Oceanic Studies, Tohoku University, References Boulanger, J. P. and. L. L. Fu (1996): Evidence of boundary reflection of Kelvin and first-mode Rossby waves from TOPEX/POSEIDON sea level data. J. Geophys. Res., 101(C7), Emery, W. J. and L. Magaard (1976): Baroclinic Rossby waves as inferred from temperature fluctuations in the eastern Pacific. J. Mar. Res., 34, Farge, M. (1992): Wavelet transforms and their applications to turbulence. Annu. Rev. Fluid Mech., 24, Fu, L. L., E. J. Christensen, C. Yamarone, M. Lefebvre, Y. Menard, M. Dorrer and P. Escudier (1994): TOPEX/ POSEIDON mission overview. J. Geophys. Res., 99(C12), Guo, Z. X., T. H. Yang and D. Z. Qiu (1985): The South China Sea Warm Current and the SW-ward current on its right side in winter. Tropic Oceanology, 4(1), 1 9 (in Chinese with English abstract). Hasunuma, K. and K. Yoshida (1978): Splitting of the Subtropical Gyre in the western North Pacific. J. Phys. Oceanogr., 14, Hu, J. Y., H. X. Liang and X. B. Zhang (1999): Distributional features of temperature and salinity in the southern Taiwan Strait and its adjacent sea areas in late summer, Acta Oceanologica Sinica, 18(2), Hu, J. Y., H. Kawamura, H. S. Hong and Y. Qi (2000): A review on the currents in the South China Sea: Seasonal circulation, South China Sea Warm Current and Kuroshio intrusion. J. Oceanogr., 56, Huang, Q. Z., W. Z. Wang, Y. S. Li, C. W. Li and M. Mao (1992): General situations of the current and eddy in the South China Sea. Adv. Earth Sci., 7(5), 1 9 (in Chinese with English abstract). Huang, Q. Z., W. Z. Wang and J. C. Chen (1994): Tides, tidal currents and storm surge set-up of South China Sea. p In Oceanology of China Sea, Vol. 1, ed. by D. Zhou et al., Kluwer Academic Publishers. Kawamura, H., Y. Sawa and F. Sakaida (1995): Satellite observations of 3 6 months variation in the Kuroshio and the Subtropical front. Umi to Sora, 71, 9 15 (in Japanese with English abstract and legends). Kessler, W. S. (1989): Observations of long Rossby waves in the northern tropical Pacific. In NOAA Tech. Memo. ERL PMEL-86, 169 pp., Pac. Mar. Environ. Lab., Natl. Oceanic and Atmos. Amin., Seattle, Washington. 3~6 Months Variation of Sea Surface Height in the South China Sea and Its Adjacent Ocean 77

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