Qiao Fangli

A Note on the South China Sea Shallow Interocean Circulation

The existing estimates of the volume transport from the Pacific Ocean to the South China Sea are summarized, showing an annual mean westward transport, with the Taiwan Strait outflow subtracted, of 3.5±2.0 Sv (1 Sv=106 m3 s−1). Results of a global ocean circulation model show an annual mean transport of 3.9 Sv from the Pacific to the Indian Ocean through the South China Sea. The boreal winter transport is larger and exhibits a South China Sea branch of the Pacific-to-Indian Ocean throughflow, which originates from the western Philippine Sea toward the Indonesian Seas through the South China Sea, as well as through the Karimata and Mindoro Straits. The southwestward current near the continental slope of the northern South China Sea is shown to be a combination of this branch and the interior circulation gyre. This winter branch can be confirmed by trajectories of satellite-tracked drifters, which clearly show a flow from the Luzón Strait to the Karimata Strait in winter. In summer, the flow in the Karimata Strait is reversed. Numerical model results indicate that the Pacific water can enter the South China Sea and exit toward the Sulu Sea, but no observational evidence is available. The roles of the throughflow branch in the circulation, water properties and air-sea exchange of the South China Sea, and in enhancing and regulating the volume transport and reducing the heat transport of the Indonesian Throughflow, are discussed.

Tidally induced upwelling off Yangtze River estuary and in Zhejiang coastal waters in summer

MASNUM wave-tide-circulation coupled numerical model (MASNUM coupled model, hereinafter) is developed based on the Princeton Ocean Model (POM). Both POM and MASNUM coupled model are applied in the numerical simulation of the upwelling off Yangtze River estuary and in Zhejiang coastal waters in summer. The upwelling mechanisms are analyzed from the viewpoint of tide, and a new mechanism is proposed. The study suggests that the tidally inducing mechanism of the upwelling includes two dynamic aspects: the barotropic and the baroclinic process. On the one hand, the residual currents induced by barotropic tides converge near the seabed, and upwelling is generated to maintain mass conservation. The climbing of the residual currents along the sea bottom slope also contributes to the upwelling. On the other hand, tidal mixing plays a very important role in inducing the upwelling in the baroclinic sea circumstances. Strong tidal mixing leads to conspicuous front in the coastal waters. The considerable horizontal density gradient across the front elicits a secondary circulation clinging to the tidal front, and the upwelling branch appears near the frontal zone. Numerical experiments are designed to determine the importance of tide in inducing the upwelling. The results indicate that tide is a key and dominant inducement of the upwelling. Experiments also show that coupling calculation of the four main tidal constituents (M2, S2, K1, and O1), rather than dealing with the single M2 constituent, improves the modeling precision of the barotropic tide-induced upwelling.

An improvement of the too cold tongue in the tropical Pacific with the development of an ocean-wave-atmosphere coupled numerical model

A common problem in the application of the coupled ocean-atmosphere general circulation models (CGCMs) without flux correction is that the simulated equatorial cold tongue in general tends to be too strong, narrow, and extending too far west. The causes are not well understood yet. One possible reason may be the simulated mixed layer depth (MLD) is too shallow in the tropical Pacific due to insufficient vertical mixing in the OGCM. It is believed that the wave-induced vertical mixing can greatly improve the simulation of the MLD and thermocline structure. In this study, the coupled ocean-atmosphere general circulation model (FGCM-0) incorporated with wave-induced mixing has been employed to simulate the tropical Pacific sea surface temperature (SST). Generally, the wave-induced mixing lowers the SST in the OGCM because the strengthened vertical mixing can bring more cold water upward. However, in the coupled model, the non-uniformity of the space distribution in SST drop generates a horizontal gradient of...

Simulation of double cold cores of the 35°N section in the Yellow Sea with a wave-tide-circulation coupled model

Based on the MASNUM wave-tide-circulation coupled numerical model, the temperature structure along 35°N in the Yellow Sea was simulated and compared with the observations. One of the notable features of the temperature structure along 35°N section is the double cold cores phenomena during spring and summer. The double cold cores refer to the two cold water centers located near 122°E and 125°E from the depth of 30m to bottom. The formation, maintenance and disappearance of the double cold cores are discussed. At least two reasons make the temperature in the center (near 123°E) of the section higher than that near the west and east shores in winter. One reason is that the water there is deeper than the west and east sides so its heat content is higher. The other is invasion of the warm water brought by the Yellow Sea Warm Current (YSWC) during winter. This temperature pattern of the lower layer (from 30m to bottom) is maintained through spring and summer when the upper layer (0 to 30m) is heated and strong thermocline is formed. Large zonal span of the 35°N section (about 600 km) makes the cold cores have more opportunity to survive. The double cold cores phenomena disappears in early autumn when the west cold core vanishes first with the dropping of the thermocline position.

Tidal effects on temperature front in the Yellow Sea

Temperature front (TF) is one of the important features in the Yellow Sea, which forms in spring, thrives in summer, and fades in autumn as thermocline declines. TF intensity ⋎ST⋎ is defined to describe the distribution of TF. Based on the MASNUM wave-tide-circulation coupled model, temperature distribution in the Yellow Sea was simulated with and without tidal effects. Along 36°N, distribution of TF from the simulated results are compared with the observations, and a quantitative analysis is introduced to evaluate the tidal effects on the forming and maintaining processes of the TF. Tidal mixing and the circulation structure adapting to it are the main causes of the TF.

High efficient parallel numerical surface wave model based on an irregular quasi-rectangular domain decomposition scheme

To achieve high parallel efficiency for the global MASNUM surface wave model, the algorithm of an irregular quasi-rectangular domain decomposition and related serializing of calculating points and data exchanging schemes are developed and conducted, based on the environment of Message Passing Interface (MPI). The new parallel version of the surface wave model is tested for parallel computing on the platform of the Sunway BlueLight supercomputer in the National Supercomputing Center in Jinan. The testing involves four horizontal resolutions, which are 1°×1°, (1/2)°×(1/2)°, (1/4)°×(1/4)°, and (1/8)°×(1/8)°. These tests are performed without data Input/Output (IO) and the maximum amount of processors used in these tests reaches to 131072. The testing results show that the computing speeds of the model with different resolutions are all increased with the increasing of numbers of processors. When the number of processors is four times that of the base processor number, the parallel efficiencies of all resolutions are greater than 80%. When the number of processors is eight times that of the base processor number, the parallel efficiency of tests with resolutions of 1°×1°, (1/2)°×(1/2)° and (1/4)°×(1/4)° is greater than 80%, and it is 62% for the test with a resolution of (1/8)°×(1/8)° using 131072 processors, which is the nearly all processors of Sunway BlueLight. When the processor’s number is 24 times that of the base processor number, the parallel efficiencies for tests with resolutions of 1°×1°, (1/2)°×(1/2)°, and (1/4)° ×(1/4)° are 72%, 62%, and 38%, respectively. The speedup and parallel efficiency indicate that the irregular quasi-rectangular domain decomposition and serialization schemes lead to high parallel efficiency and good scalability for a global numerical wave model.

Wave-induced mixing in the Yellow Sea

Vertical wave-induced mixing parameterBv expressed in wave number spectrum was estimated in the Yellow Sea. The spatial distributions ofBv averaged over upper 20 m in 4 seasons were analyzed. It is the strongest in winter because of winter monsoon, and the weakest in spring. Since in summer it plays an important role for circulation of upper layers, its vertical structure was also discussed. Two simulations with and without wave-induced mixing in this season were performed to evaluate its effect on temperature distribution. Numerical results indicate that wave-induced mixing could increase the mixed layer thickness greatly.

Simulation and analysis on seasonal variability of average salinity in the Yellow Sea

The CTD (conductivity, temperature and depth) data collected by six China-Korea joint cruises during 1996–1998 and the climatological data suggest that the seasonal variability of average salinity in the Yellow Sea (Sa) presents a general sinusoid pattern. To study the mechanism of the variability, annual cycles ofSa were simulated and a theoretical analysis based on the governing equations was reported.Three main factors are responsible for the variability: the Yellow Sea Warm Current (YSWC), the Changjiang (Yangtze) River diluted water (YRDW) and the evaporation minus precipitation (E-P). From December to the next May, the variability ofSa is mainly controlled by the salt transportation of the YSWC. But in early July, the YSWC is overtaken and replaced by the YRDW which then becomes the most important controller in summer. From late September to November, the E-P gradually took the lead. The mass exchange north of the 37°N line is not significant.

Seasonal variability of thermocline in the Yellow Sea

Based on the MASNUM wave-tide-circulation coupled numerical model, seasonal variability of thermocline in the Yellow Sea was simulated and compared with in-situ observations. Both simulated mixed layer depth (MLD) and thermocline intensity have similar spatial patterns to the observations. The simulated maximum MLD are 8 m and 22 m, while the corresponding observed values are 13 m and 27 m in July and October, respectively. The simulated thermocline intensity are 1.2°C/m and 0.5°C/m in July and October, respectively, which are 0.6°C/m less than those of the observations. It may be the main reason why the simulated thermocline is weaker than the observations that the model vertical resolution is less precise than that of the CTD data which is 1 m. Contours of both simulated and observed thermocline intensity present a circle in general. The wave-induced mixing plays a key role in the formation of the upper mixed layer in spring and summer. Tidal mixing enhances the thermocline intensity. Buoyancy-driven mixing destroys the thermocline in autumn and keeps the vertical temperature uniform in winter.

Wave assimilation and numerical prediction

An adjoint variational method for wave data assimilation in the LAGFD-WAM wave model is proposed. The adjoint equation of the wavenumber energy spectrum balance equation is derived. And fortunately, its characteristic equations are the same as those in the LAGFD-WAM wave model. Simple experiments on the functional optimization and assimilation effectiveness during the prediction period indicated that the adjoint variational method is effective for wave assimilation and that the initial optimization of the wave model is important for the short-range wave prediction. All of this is under the assumption that the wind field is accurate, the method is the important first step for combined wind and wave data assimilation systems.