应用灰色系统理论，对太平洋海域48个长期验潮站的月均海平面分别建立了GM（1，1）模型。GM（1，1）模型能较好地反映太平洋海域的悔平面变化的趋势，它除了能给出连续的海平面变化速率外，同时能方便地给出海平面变化的加速率。模拟结果表明，在太平洋地壳均衡假设下，太平洋海域的月均海平面以平均速率0.17cm/a上升。在太平洋海域所取的48个长期验潮站中，有40个站在加速上升，全部站的平均加速度为0.00029cm/a2。且加速率逐渐增大。当然这些加速率都很小，但作为一种普遗性的趋势，这已足以说明：太平洋海域的海平面在加速上升。

根据Munk等提出的响应法（Response Method）和Goves等（1975）的正交响应方法（Orthogonalized Convolution Method）的思想，利用正交潮响应对248个周期超过6年的南中国海的TOPEX/POSEIDON卫生高度计资料进行潮波分析。在分析中引入全日潮族和半日潮族，并利用正交潮函数（Orthotide function）分析出了3个主要的全日分潮（K1、O1、P1）和3个主要半日分潮（M2、S2、N2），并给出了K1、O1、M2、S2的等振幅线和同潮时图，结果与其他学者的主要结果符合得很好。通过与整个海区53个验潮站的主要全日分潮K1分潮和主要半日分潮的比较，K1分潮的振幅和迟角的平均绝对误差分别为4.73cm和11.6，而M2分潮的分别为11.91cm和28.4，优于Mazzega（1994）的结果。

旨在分析太平洋地区的月均海平面的变化，探讨其物理过程。文中共分析了54个长期站的海平面资料，对54个站分别建立了随机动态非线性模型，求得了太平洋地区的海平面平均上升速率为0.16cm/a。并对太平洋东西岸各站及海洋中观测站海平面资料相对于TA-LARA站海平面资料进行了交叉谱分析，结论是，太平洋月均海平面45个月的低额振动存在着以下的规律：由东太平洋（15°～25°N）开始，向西传播至太平洋西岸后，转向南，在5°N～25°S之间，转向东到达太平洋东岸后北上形成逆时针循环。在埃尔尼诺事件的低纬典型区，月平均海面振动中年周期振动的主导作用下降，甚至失去主导作用，而与埃尔尼诺事件的准周期相近的周期振动的作用增大。

本文将经验正交函数法与随机动态方法结合起来，分析了中国沿岸5个站的海平面变化。由于空间本征函数在短时间可认为不变，用随机动态方法分析各主要时间本征函数，最后采用非线性最小二乘法求出各主要时间本征函数的线性增长速率，分别乘上相应的空间本征函数便得到各站的相对海面线性增长速率，对未来的时间本征函数作出预报，从而得到未来的平均海面预报值。各站均衡基准下的海平面线变速率平均为0.24cm/a。

The upper mixed layer (UMI) depth obtained from temperature is very close to that from density: the maximum is about 15m. This indicdtes that temperature is a good indicator of mixed layer during measurements When the surface heat flux is balaceed by a cross-shore beat flux, the surface mixed layer depth obtained from the WM model (Weatherly and Martin, 1978), hPRT, is roughly the same as obscrred. The mixed layer depth calculated from the PWP model (Price, Weller and Pinkel, 1986) is close to the depth obtained from thermistor chain temperature data. The results show that both the WM model and PWP model can provide a good estimnate of stratification in the study area during the cruise. The value of log (h\u3) is about 9.5 in the study area, which shows that the study arca is strongly stratified in summer. Observtions on the northern Portugal shelf reveal high variability in stability, giving rise to semi-diurnal, scmi-nonthly and diurnal oscillations, and long term variations. The fortnightly oscillations are highlighted by post-springs and post-neaps. The stirring of spring tide is reinforced by strong wind mixing which brings about completc vertical homogencity everywhere. The semi diurnal periodic stratification is very pronounced because the major axis of the tidal cllipse is orientated acrossshore, even though the tidal current is wear in this area, the maximum stratification is obscrved around the middle of ebb, and, the water at this time is much warmer. The diurnal oscillation results from the upper ocean responsc to henting and wind mixing when solar heating warms and stabilizes the upper ocean There is a clcar relationship between upper mixed layer depth and wind stress magnitude at subtidal frequencies, Stronger winds result in a deeper surface mixed layer. Typically, the surface mixed layer depth lags the wind stress by h 12h.

A finite element model, QUODDY model, is used to study the tides in the East China Sea, the Yellow Sea and the Bohai Sea in this paper. The simulation results fit well with the observation data. The cotidal charts of M2, S2, K1, O1 and M4 are given out. The result of this paper supports that the phase-lag of M2 varies little at Laizhou Bay. The amphidromic point of M2 disappears in the Liaodong Bay when the bottom stress drag coefficient increases to 0.0028. There is a high amplitude (more than 0.06m) region of M4 around (32.8

Tidal waves in the Easl China Sea are simulated numetically with POM (Princeton Ocean Model) model for normal mcan sea level, 30cm higher, 60cm higher, and 100cm higher, respcctively, and the simulated rsult is compared with the harmonic analysis reult of hourly sea level data from 19 fide ganges for more than 19 years. It is indicated that the long-term mean sea level variation affects notably tidal waves in this region. Generally, the tidal amplitude increases when the mean sea level rises, but this relationship may be inverse for some sea areas. The maximal variation of tidal amplitude takes place in the zones near the Fujian coast and the Zhejiang coast, rather than the shallowest Bohai Sea. The maximum increase of M2 amplitude can excced about 15cm corressponding to the 60cm rise of the mean sea level along the Fujian coast. The other ragions with large variations of tidal amplitude are those along the Jiangsu coast, the south-east coast of Shandong, and the south-east coast of Dalian. The propagation of tidal waves is also related to mean sea level vatiation, and the tidal phase-lag decreases generally when the mean sea level rises. Almost all the ragions where the tidal phase-lag increases with rising mean sea level are close to amphidromic points, meanwhile the spatial area of such regions is very small. Because the influence of mean sea level variation upon tidal waves is spatially marked, such spatial effect should be considered in calculation of the tidal characteristic value and engineering water level. In the region where the amplitudes of the major tidal constituents increase, the probable maximum high water leval becomes higher, the probable maximum low water level becomes lower, and both design water level andcheck water level increase obviously. For example, the design water level at Xiamen increases by 13.5cm due to the variation of tidal waves when the mean sea level rises 60cm, the total increase of design water level being 73.5cm.

The long-term variation and seasonal variation of sea level have a notable effect on the calculation of engineering water level. Such an effect ts first analyzed in this paper. The maximal amplitude of inter-annual anomaly of monthly mean sea level along the China coast is larger than 60cm. Both the storm surge disaster and cold wave disaster are seasonal disasters in vario us regions, so the water level corresponding to the 1% of the cumulative frequency in the cumula tire frequency curve of hourly water level data for different seasons in various sea areas is different from design water level. for example, the difference between them reaches maximum in June. July and August for northern sea area, and maximum in September, October and November for Southern China Sea. The hourly water level data of 19 gauge stations along the China coast are analyzed. Firstly, the annual mean sea level for every station is obtained; secondly, linear chan ging rates of annual mean sea level are obtained with the stochastic dynamic method; thirdly, the astronomical tide and storm surge tide are obtained by subtracting the linear fitting part from the original hourly data. finally, two distributions corresponding to the astronomical tide and wind tide are obtained according tn whether the astronomical tide and storm tide are correlative or not. So the two check water levels are obtained with the joint probability method. The maximal difference between the two water levels of 100 years' recurrence is more than 30cm. Both of the two check wat er levels have disadvantages in the use of observation data, so the mean value is suggested to be taken as the final check water level. A comparison between the two check water levels indicates that the effect of sea level variation upon design water level and check water level is larger than 80 cm at some stations.

A coupled modeling system is developed to study the interactions between wave, current and tide in Bohai Sea during a winter storm. The coupled modeling system includes a wave model-WAVEWATCH III and a three-dimensional Ocean model-POM. Numerical results show that the interactions have a strong impact on all the elevation, current and wave fields. The sea surface elevation can increase 7cm in the Laizhou Bay, and decrease 7cm in the Liaodong Bay under the effect of the enhanced wind stress derived from the surface wave. The wavee influence on the wind stress also can increase the magnitude of surface current 8cm/s in the central Bohai Sea. The significant wave height waries as much as 40% under the effect of tides and surges in some coastal areas.