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The global distributions of eight principal tidal constituents, M2, S2, K1, O1, N2, K2, P1, and Q1, are derived using TOPEX/Poseidon and JASON-1(T/P-J) satellite altimeter data for 16 a. The intercomparison of the derived harmonics at 7000 subsatellite track crossover points shows that the root mean square (RMS) values of the tidal height differences of the above eight constituents range from 1.19 cm to 2.67 cm, with an average of about 2 cm. The RMS values of the tidal height differences between T/P-J solutions and the harmonics from ground measurements at 152 tidal gauge stations for the above constituents range from 0.34 cm to 1.08 cm, and the relative deviations range from 0.031 to 0.211. The root sum square of the RMS differences of these eight constituents is 2.12 cm, showing the improvement of the present model over the existing global ocean tidal models. Based on the obtained tidal model the global ocean tidal energetics is studied and the global distribution of the tidal power input density by tide-generating force of each constituent is calculated, showing that the power input source regions of semidiurnal tides are mainly concentrated in the tropical belt between 30°S and 30°N, while the power input source regions of diurnal tides are mainly concentrated off the tropic oceans. The global energy dissipation rates of the M2, S2, K1, O1, N2, P1, K2 and Q1 tides are 2.424, 0.401, 0.334, 0.160, 0.113, 0.035, 0.030 and 0.006 TW, respectively. The total global tidal dissipation rate of these eight constituents amounts to 3.5 TW.

Based on an empirical orthogonal function (EOF) analysis of the monthly NCEP Optimum Interpolation Sea Surface Temperature (OISST) data in the South China Sea (SCS) after removing the climatological mean and trends of SST, over the period of January 1982 to October 2003, the corresponding TCF correlates best with the Dipole Mode Index (DMI), Nino1+2, Nino3.4, Nino3, and Nino4 indices with time lags of 10, 3, 6, 5, and 6 months, respectively. Thus, a statistical hindcasts in the prediction model are based on a canonical correlation analysis (CCA) model using the above indices as predictors spanning from 1993/1994 to 2003/2004 with a 1–12 month lead time after the canonical variants are calculated, using data from the training periods from January 1982 to December1992. The forecast model is successful and steady when the lead times are 1–12 months. The SCS warm event in 1998 was successfully predicted with lead times from 1–12 months irrespective of the strength or time extent. The prediction ability for SSTA is lower during weak ENSO years, in which other local factors should be also considered as local effects play a relatively important role in these years. We designed the two forecast models: one using both DMI and Nino indices and the other using only Nino indices without DMI, and compared the forecast accuracies of the two cases. The spatial distributions of forecast accuracies show different confidence areas. By turning off the DMI, the forecast accuracy is lower in the coastal areas off the Philippines in the SCS, suggesting some teleconnection may occur with the Indian Ocean in this area. The highest forecast accuracies occur when the forecast interval is five months long without using the DMI, while using both of Nino indices and DMI, the highest accuracies occur when the forecast interval time is eight months, suggesting that the Nino indices dominate the interannual variability of SST anomalies in the SCS. Meanwhile the forecast accuracy is evaluated over an independent test period of more than 11 years (1993/94 to October 2004) by comparing the model performance with a simple prediction strategy involving the persistence of sea surface temperature anomalies over a 1–12 month lead time (the persisted prediction). Predictions based on the CCA model show a significant improvement over the persisted prediction, especially with an increased lead time (longer than 3 months). The forecast model performs steadily and the forecast accuracy, i.e., the correlation coefficients between the observed and predicted SSTA in the SCS are about 0.5 in most middle and southern SCS areas, when the thresholds are greater than the 95% confidence level. For all 1 to 12 month lead time forecasts, the root mean square errors have a standard deviation of about 0.2. The seasonal differences in the prediction performance for the 1–12 month lead time are also examined.

The South China Sea (SCS) interocean circulation and its associated heat and freshwater budgets are examined using the results of a variable-grid global ocean model. The ocean model has a 1/6° resolution in the SCS and its adjacent oceans. The model results from 1982 to 2003 show that the western Pacific waters enter the SCS through the Luzon Strait with an annual mean volume transport of 4.80 Sv, of which 1.71 Sv returns to the western Pacific through the Taiwan Strait and East China Sea and 3.09 Sv flows toward the Indian Ocean. The heat in the western Pacific is transported to the SCS with a rate of 0.373 PW (relative to a reference temperature 3.72 °C), while the total heat transport through the outflow straits is 0.432 PW. The net heat transport out of the SCS is thus 0.059 PW, which is balanced by a mean net downward heat flux of 17 W/m 2 across the SCS air–sea interface. Therefore, the interocean circulation acts as an “air conditioner”, cooling the SCS and its overlaying atmosphere. The SCS contributes a heat transport of 0.279 PW to the Indian Ocean, of which 0.240 PW is from the Pacific Ocean through the Luzon Strait and 0.039 PW is from the SCS interior gained from the air–sea exchange. The Luzon Strait salt transport is greater than the total salt transport leaving the SCS by 3.97 Gg/s, implying a mean freshwater flux of 0.112 Sv (or 3.54 × 10 12 m 3 /year) from the land discharge and P − E (precipitation minus evaporation). The total annual land discharge to the SCS is estimated to be 1.60 × 10 12 m 3 /year, the total annual P − E over the SCS is thus 1.94 × 10 12 m 3 /year, equivalent to a mean P − E of 0.55 m/year. The SCS freshwater contribution to the Indian Ocean is 0.096 Sv. The pattern of the SCS interocean circulation in winter differs greatly from that in summer. The SCS branch of the Pacific-to-Indian Ocean throughflow exists in winter, but not in summer. In winter this branching flow starts at the Luzon Strait and extends to the Karimata Strait. In summer the interocean circulation is featured by a north-northeastward current starting at the Karimata Strait and extending to the Taiwan and Luzon Straits, and a subsurface inflow from the Luzon Strait that upwells into the surface layer in the SCS interior to supply the outward transports.

Global ocean circulation is a primary mechanism for transporting energy and nutrients around the planet. At its most basic level, this circulation transports water from the Pacific Ocean through the Indonesian archipelago into the Indian Ocean; these waters join the Agulhas Current, which loops around Africa and in turn joins the Gulf Stream in the Atlantic Ocean. Upon reaching the North Atlantic, waters sink, creep south along the ocean floor as deep water, trace around Antarctica as bottom water, and move to the Pacific Ocean where they upwell, only to seep back into the Indian Ocean through the straits and channels surrounding Indonesia. The seepage of warm equatorial waters from the western Pacific Ocean into the Indian Ocean is called the Indonesian Throughflow (ITF). Long recognized as a key component of global ocean circulation, the ITF's magnitude and variability play an important role in determining heat and nutrient exchange to other ocean basins. Scientists' ability to estimate ITF behavior is therefore essential for understanding the global climate system.

The two-dimensional data assimilation model of the tides in the Bohai Sea was established using the ajoint method to study the tides of the Bohai Sea. The adjoint equations were derived from the two-dimensional tidal equations by Lagrange multiplier method. The observation data were from the tidal gauge stations and the satellite altimetry data. To evaluate the role of the altimetry data and the tidal gauge data in the data assimilation of the tides in the Bohai Sea, three numerical experiments were carried out. Experiment 1 only assimilates the tidal gauge data, Experiment 2 only assimilates the altimetry data, and Experiment 3 assimilates the combined data of the tidal gauge stations and the satellite altimetry. The tidal constituents M 2 , S 2 , K 1 and O 1 of the Bohai Sea were simulated. The results show that it is better when assimilating the tidal gauge data and the altimetry data simultaneously than assimilating any one separately. The mean absolute differences of the amplitude and phase-lag are 1.52 cm and 2.22° for M 2 , 1.26 cm and 3.30° for S 2 , 1.19 cm and 2.72° for K 1 , 0.55 cm and 1.93° for O 1 , respectively. The results reflect the tidal system of the Bohai Sea well, especially for the outer sea area since the altimetry data were assimilated.

The relative admittances of S 2 versus M 2 , N 2 versus M 2 , K 2 versus S 2 , O 1 versus K 1 , P 1 versus K 1 and Q 1 versus O 1 in the Bohai, Yellow and East China Seas are interpolated from harmonics at 113 long-term coastal and island tidal gauge stations. The empirical cotidal charts of N 2 , K 2 , P 1 and Q 1 are derived from the obtained relative admittance distribution and the cotidal charts of M 2 , S 2 , K 1 and O 1 obtained from satellite altimetry. Comparison with observed harmonics at 5 long-term tidal stations shows that the amplitude differences of these 4 constituents range from 0.3 to 1.9 cm, and the phase-lag differences range from 4 to 7°, except that the phase-lag differences become larger in the regions close to amphidromic points.

A fine-grid model (1/6°) covering the South China Sea (SCS), East China Sea and Japan/East Sea, which is embedded into a coarse-grid (2°) global model, was established to study the sea surface height of the China adjacent seas. In the present paper, we report the model-produced monthly and annual mean sea surface heights(SSH) and their anomalies of the China adjacent seas. Comparison to the TOPEX/Poseidon data shows that the model-produced monthly sea surface height anomalies (SSHA) are in good agreement with altimeter measurements. Based on the results, the distribution of the China adjacent seas SSH and its seasonal variation are discussed. In the East China Sea, the seasonal variation of SSH is not as remarkable as that in the South China Sea. There is an area whose SSH is high near the northern continental slope of the SCS all the year round. On the contrary, there is a low-SSH region in the south of SCS in summer and high-SSH in winter. It could be diagnosed from the distribution of SSH that the western Philippine Sea water intrudes into the SCS through the Luzon Strait in the surface layer, especially in autumn, winter and spring. The SE Vietnam Off-Shore Current in summertime and the Yellow Sea Warm Current in the wintertime are reproduced reasonably. The changing characteristics of SSH in the China adjacent seas indicate the significant effect of the external forcing and open seas on the distribution of SSH in the China adjacent seas.

[1] Acoustic Doppler current profiler observations were carried out at two stations along a transect northwest of the Karimata Strait from December 2007 to November 2008. One month and 10 months of full-depth current data were obtained at the western and eastern stations, respectively. The observations show that the South China Sea (SCS) water flows persistently to the Indonesian seas (ISs) in boreal winter. On the basis of current, temperature, and salinity observations by conductivity-temperature-depth casts and bottom-mounted sensors, the volume, heat, and freshwater transport from the SCS to ISs in the month from 13 January to 12 February 2008 are estimated to be 3.6 ± 0.8 Sv (Sv = 106 m3/s), 0.36 ± 0.08 PW, and 0.14 ± 0.04 Sv, respectively. The corresponding transport-weighted temperature is 27.99°C. A downward sea surface slope from north to south at the study area in boreal winter is also found. The observations confirm the existence of the SCS branch of the Pacific-to-Indian-Ocean throughflow in boreal winter and the reversal of the Karimata Strait transport in boreal summer. The seasonal variability in the Karimata Strait transport can exceed 5 Sv. It is proposed that the Karimata Strait throughflow plays a double role in the total Indonesian Throughflow transport, which is especially evident in boreal winter. The negative effect of the double role is reducing the Makassar Strait volume and heat transports; the positive effect is that the Karimata Strait throughflow itself can contribute volume and heat transports to the total Indonesian Throughflow.

[1] Interannual variation of the South China Sea (SCS) circulation is investigated using variable grid global ocean circulation model results from December 1981 to October 2004 forced by the NCEP Reanalysis wind stress. The upper (0–58 m) Luzon Strait transport (LST) correlates with the local wind stress very well, while the lower (58 m to seabed) LST shows a statistically significant correlation with the integral of wind stress over the tropical Pacific according to Godfrey's “island rule,” with a delay of about 5 months. The Empirical Orthogonal Function (EOF) analysis shows significant correlation between the first wind stress curl EOF mode and El Nino, with a lag of 3 months. The interannual variation of upper layer currents closely correlates with El Nino, with a maximum correlation coefficient of 0.7, lagging by 5 months. The first EOF spatial pattern shows a basin-scale cyclonic gyre. The interannual variation of subsurface currents marginally correlates with Nino3.4. The model results show that in the winter of 1997/1998, the cyclonic circulation weakens and the associated southward cool water advection is thus reduced. In the summer of 1998, the normal double gyre structure (cyclonic in the south and anticyclonic in the north) of the upper layer currents is replaced by a basin scale anticyclonic gyre, and the offshore current southeast of Vietnam and its associated upwelling vanish. The reduced southward advection in the winter and the disappearance of upwelling in the summer are considered as contributions of the anomalous ocean circulation to the 1998 warm event.

[1] Trends and interannual variability of the surface winds (SW), sea surface height (SSH), and sea surface temperature (SST) of the South China Sea (SCS) in 1993–2003 are analyzed using monthly products from satellite observations. Time series are smoothed with a 12-month running mean filter. The east and north components of the SW, SSH, and SST have linear trends of 0.53 ± 0.35 ms−1 decade−1, −0.04 ± 0.17 ms−1 decade−1, 6.7 ± 2.7 cm decade−1, and 0.50 ± 0.26 K decade−1, respectively. The sea level rising rate and sea surface warming rate are significantly higher than the corresponding global rates. An Empirical Orthogonal Function (EOF) analysis is performed to evaluate the interannual variability. Results show that the first EOF of the SW is characterized by a basin-wide anticyclonic pattern. The corresponding time coefficient function (TCF) correlates with the Nino3.4 index at the 99% confidence level, with a lag of 3 months. The first EOF of the SSH is characterized by a low sea level along the eastern boundary. The corresponding TCF correlates with the Nino3.4 at the 99% level, with a lag of 2 months. The first EOF of the SST is characterized by a basin-wide warming with the highest anomalies in the north deep basin. The corresponding TCF correlates with the Nino3.4 index at the 95% level, with a lag of 8 months. Based on the EOF analysis, the ENSO-associated correlation patterns of the SW, SSH, and SST are presented.

[1] Fine structures of surface fronts during winter-spring in the Taiwan Strait and their evolution over time are studied using satellite and in situ data. At times, different water masses are interleaved into each other. The northward intruding warm water bifurcates into several branches, causing complicated multiple cross strait fronts with maximum surface temperature gradients at the fronts to be greater than 2°C/km. The mean surface velocity of the fronts estimated from a sequence of satellite images is between 0.15 and 0.3 m/s during the February–March 2001 frontal event. The speed appears to have accelerated during the latter stages from 0.2 m/s during March 2–4 to 0.3 m/s during March 4–6. The total northward transport associated with the passage of the fronts is estimated to be 0.6–1 Sv between February 16 and March 6, 2001. The timescale of the passage of the fronts through the entire Taiwan Strait is therefore at least four weeks. Hydrographic observations in February–March of 1998 and 2000 also demonstrate similar frontal events with strong vertical gradients of water temperature and salinity on the western side of the strait. The 1998 data also show clearly that the low temperature and low salinity Zhemin Coastal Current separates from the coast and enters into the middle of the strait, a feature consistent with the satellite observations.

[1] Harmonic analysis of 10 years of TOPEX/Poseidon (TP) along-track altimetry is performed to derive the semidiurnal, diurnal, long-period, and quarter-diurnal tides in the Bohai, Yellow, and East China Seas. The TP solutions are evaluated through intercomparison for crossover points and comparison with the ground truth, showing that the accuracy of TP solutions in the study area has achieved levels of 2 - 4 cm in amplitudes and 5degrees in phase lags for principal constituents (M-2, S-2, K-1, O-1, and S-a). The TP-derived S-a amplitudes have a systematic bias of about - 10% as compared with the ground truth, indicating the possible importance of loading effect of this constituent in the study area, which is generally not considered in geodetic surveys. The tidal harmonics from TP altimetry and at coastal and island stations are used to give a new set of empirical cotidal charts for principal constituents (M-2, S-2, K-1, O-1, and S-a). The accuracy of these new charts is believed to be significantly higher than the previous charts for the offshore area.

The mean sea surface heights (sea surface topography) of the South China, East China, Yellow and Bohai Seas are derived from an ocean general circulation model and surface air pressure. The circulation model covers the global oceans, with fine grid (1/6°) covering the East Asian marginal seas and coarse grid (3°) covering the rest part of the global oceans. The result shows that the China 1985 National Altitude Datum is 24.7 cm above the mean sea surface height of the world oceans. The mean sea surface in the coastal ocean adjacent to China is higher in the south than in the north. Intercomparison of the model results with the geodetic leveling measurements at 28 coastal tidal stations shows a standard deviation of 4.8 cm and a fitting coefficient of 95.3%. After correction through linear regression, the standard deviation is reduced to 4.5 cm. This indicates that the accuracy of model results is sufficient for practical application. Based on the model results, the mean sea surface heights for the study area with a resolution of 1/6 degree are given. This result also links the mean sea levels at islands with those on the mainland coast and gives the mean sea surface heights at tidal stations in the Taiwan Island, the Dongsha Islands, the Xisha Islands and the Nansha Islands relative to the China 1985 National Altitude Datum.