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1.
通过对比2017年9月和2019年9月的温盐大面观测数据,发现东海陆架上黑潮近岸分支流的路径在两次观测中存在显著差异。2019年9月黑潮近岸分支流中上游的路径相较2017年9月明显的东向偏移,造成黑潮次表层水入侵东海近岸海域的强度较弱。为了探究黑潮近岸分支流的上述显著年际差异的原因,利用卫星高度计数据和再分析风场数据,通过分析大面观测同期的绝对海表动力高度、地转流场以及海表风场的差异,阐述了黑潮近岸分支流路径产生显著年际差异的动力机制。2019年8—9月东海海表较2017年8—9月盛行更强的西南向沿岸季风,强的西南向沿岸风通过埃克曼输运促使水体向岸堆积并在近岸区域沿岸西南向堆积。因此, 2019年8—9月东海近岸海域的跨岸方向压力梯度与2017年8—9月相比较小而沿岸压力梯度则较大。2019年8—9月,受压力梯度分布的影响,东海近岸海域产生西南向的沿岸地转流和离岸地转流。其中西南向的沿岸地转流会在底部生成离岸的底埃克曼流,离岸底埃克曼流和离岸地转流共同抑制了黑潮近岸分支流的向岸入侵。这导致2019年9月黑潮近岸分支流的路径向东偏移,黑潮次表层水入侵浙江近海及长江口区域的强度随之减弱。通过分析研究实际观测案例,阐述了风影响黑潮近岸分支流入侵东海近岸海域的动力机制,同时明确指出海表风场会从黑潮近岸分支流的中上游区域改变其路径,进而对黑潮入侵东海近岸海域产生重要影响。 相似文献
2.
渤黄海海平面的变化及其与ENSO的关系 总被引：3，自引：0，他引：3
利用1992年12月至2007年5月的高度计资料,研究了渤黄海海平面的变化特征。统计分析表明,近14a间渤海及北黄海、中央黄海海平面的平均上升高度分别为45.9mm和34.7mm,各海域的海平面上升速度不完全相同。研究发现,南方涛动指数(SOI)、纬向风应力距平都与渤海及北黄海、中央黄海的SLA呈负相关性,渤黄海海平面显著受SOI、纬向风应力调制,并且,SOI与渤黄海海域的风场之间有良好相关。将坐标系进行旋转后,获得与当地海平面异常相关最大的风应力方向。对SLA与新坐标系下风应力距平u的低频分量分析发现,渤海及北黄海海区、中央黄海对海平面影响最大的风应力距平u方向分别为东偏南20°方向、东偏南8°方向,风应力距平u分量与SLA、SOI的低频分量呈现更好的相关性。ENSO通过大气环流过程对渤黄海海域的风场产生影响,当地风场通过纬向风应力对渤黄海海平面的年际变化产生调制作用。因此,ENSO可以通过风应力对渤黄海海平面产生影响。 相似文献
3.
渤黄海海域悬浮体季节性分布及主要运移路径 总被引：1，自引：0，他引：1
依据国家自然科学基金委公共航次2010年和2012年4个航次在渤黄海海域获得的现场悬浮体浓度数据及CTD海洋水文观测数据,结合MODIS L1B数据第4波段反射率值,建立了悬浮体浓度(SSC)与反射率强度的反演模型,反演了渤黄海海域表层悬浮体的月均分布。综合现场实测数据和遥感反演结果,研究渤黄海海域悬浮体的季节性变化特征。利用HYCOM数值模拟得到的各个层位流速数据,分析渤黄海海域主要断面的悬浮体扩散通量。结果表明,渤黄海海域表层悬浮体浓度高值区主要分布在黄河口莱州湾及渤海湾附近沿岸海域、山东半岛沿岸、苏北浅滩至长江口一带、罗洲群岛附近海域以及沿岸其他小河流入海口。渤黄海海域水体结构具有季节性变化特征。夏季,水体上下温差大、层化较强、水动力条件较弱,海域悬浮体浓度相对较低。而在冬季,海域气温较低,水体上下温差小,同时,渤黄海海域强劲的东北风盛行,水体混合强烈,海域悬浮体浓度较高。同时,黄海暖流和山东半岛沿岸流等流系加强,携带悬浮体的能力和效率均大大提高,冬季成为海域悬浮体输运的主要季节。在冬季,黄河三角洲沿岸、山东半岛沿岸以及苏北海岸等区域在强动力作用下的再悬浮成为海域的悬浮体主要来源。黄河三角洲沿岸再悬浮的沉积物通过渤海海峡的南端输入北黄海,在沿岸流的作用下悬浮体输送通量沿程增大,经过成山头海域后转向南输送,输送通量沿程减少,沉积物在黄海中部泥质沉积区汇聚。沉积动力的分析结果显示,冬春季节在山东半岛区域形成的混合锋面对悬浮体的输运路径有重要的影响。 相似文献
4.
《中国海洋大学学报(自然科学版)》2010,(Z1)
本文基于有限体积方法的海洋数值模式FVCOM,对渤、黄海M2分潮潮汐、潮流进行数值模拟。模式水平采用不规则三角形网格,较好地拟合曲折岸线并提高近岸海域的网格分辨率;底摩擦采用数值模式同化结果,较真实的反应了海底实际底摩擦状况;采用干/湿处理模块,可以较好模拟近岸的潮汐潮流。通过沿岸19个验潮站M2分潮潮汐调和常数的实测值与计算值的对比,振幅平均误差为5.6 cm,位相平均误差为6.1(°),模拟值与实测值较为接近。表层潮流椭圆的分布,基本反映了渤海及黄海北部的潮流特征。 相似文献
5.
根据1978—2015年渤、黄海沿岸观测风应力场与二维非线性垂直平均风生流模式，以及旋转经验正交函数（REOF）、调和分析等方法，研究了渤、黄海月平均风生流速度势、流函数场季节循环时空模态与年际变异.渤、黄海月平均风生流速度势、流函数场主要有两种时空模态，季节周期分量是时空模态的主要分量.由于风应力场季节循环变异，渤海流函数场季节时空循环变异程度大于速度势场，速度势、流函数场第二模态是季节变异的主要分量，黄海速度势场季节时空循环变异程度大于流函数场，速度势场第二模态是季节变异的主要分量.由于月平均风应力场强度年际变化显著线性减弱，渤、黄海季节平均风生流场强度年际变化也显著减弱.渤、黄海暖流与冷水团季节生消是风生流水平环流与垂直对流对冷 暖水体输送与汇集共同作用的结果，渤、黄海春、夏季辐合上升环流延缓及减弱了浅层暖水向深层传播，是春、夏季冷水团与温跃层形成的重要动力因素，因此，速度势是研究渤、黄海风生流场十分重要的因素.冬季渤海中部、黄海东部反气旋型及辐散下沉环流与黄海中部气旋型环流、辐合上升环流是黄海暖流季节转换与强度的主要动力控制因素，夏季黄海东部气旋型环流、辐合上升环流与黄海中部反气旋型环流、辐散下沉环流是黄海冷水团季节转换与强度的主要动力控制因素. 相似文献
6.
东中国海环流及其季节变化的数值模拟 总被引：1，自引：0，他引：1
关于东中国海环流的研究，国内外学者已做了大量的工作。早期科学家们主要依赖于对温盐资料和少数测流资料的分析研究对渤、黄、东海的环流结构有了较系统和深入的认识。东中国海环流是由一个气旋式的“流涡”组成，东侧主要是北上的黑潮-对马暖流-黄海暖流及其延伸部分；西侧为南下的沿岸流系。黑潮对东中国海环流的影响是如此之大，以致于除了某些局部区域外，上述海域主要流系的冬、夏季分布形式比较相似而无本质上的差异(胡敦欣等，1993)。但本文所研究海域正处于世界上最显著的季风区，冬、夏季盛行风向基本相反，过渡季节(春、秋季)风向多变，风力减弱；海洋热盐结构季节变化明显(如冬季混合强，而夏季层化明显等)，这些因素都使得东中国海环流存在着较明显的季节变化。
自20世纪80年代以来，东中国海环流的数值模拟工作逐步展开，并已成为研究环流结构及其形成机制的强有力工具。但由于数值模式本身以及计算方案的缺陷(如有些学者用固定的风场、温盐场对东中国海环流进行诊断模拟等)和观测资料的不足，数值模拟的结果难以得到验证，渤、黄、东海的环流研究中仍有大量的问题存在争议，以待澄清。例如，台湾暖流的来源、流径;对马暖流的来源;夏季黄海暖流的流径以及黄海冷水团环流等均有不同的论述。对黄、东海环流季节变化的数值模拟工作也较少，多用冬、夏典型月份的风场强迫积分至稳定态，给出冬、夏季环流，这种做法值得商榷。三维环流模式很难在1个月内达到稳定态，尤其是夏季层化明显、风力减弱的情况下，非常定风场的影响更应引起人们的重视。
本文采用比较符合实际的计算方案，用年循环风场和海面热通量场为外强迫，对渤、黄、东海的环流及其季节变化进行了模拟，并对一些争议问题进行了探讨。 相似文献
7.
黑潮延伸体海域海平面年际变化及其与海流的关系 总被引：1，自引：0，他引：1
利用黑潮延伸体海域海平面异常(SLA)数据和SODA海流资料,分析海平面和海流的年际变化特征,以及两者之间的关系。分析发现黑潮延伸体SLA的第二模态是黑潮大弯曲模态,存在29个月的准两年显著振荡。该海域海平面具有显著的年际变化,且与ENSO和PDO密切相关,2002-2004年的黑潮大弯曲期间,海平面与Nino3指数的相关系数为0.74。海平面年际变化和海流关系密切,黑潮延伸体主轴两侧海平面具有显著的季节和年际变化,急流呈大弯曲路径(1993-1996、2002-2004)时,流轴稳定流速大,流轴影响深,急流主轴南侧海平面较高,达到年际变化的最大值,主轴两侧海面高度梯度大。非弯曲期间,急流主轴南压,海流强度减弱,此期间海平面低,主轴两侧海面高度梯度较小。黑潮延伸体上游区海平面变化受黑潮大弯曲影响更为显著。上下游区的海平面和比容海平面的年际变化较为相似,黑潮延伸体海域海流和比容效应共同调控该区域海平面变化。 相似文献
8.
日本南部黑潮路径变异对北太平洋地区的气候和环境具有显著的影响,对黑潮路径变异的研究具有重要的意义。本文利用POM(Princeton Ocean Model)数值模式模拟了日本南部黑潮的路径变异情况,分析了黑潮大弯曲路径形成的可能机制。研究结果表明,当黑潮处于非大弯曲路径时,相对位势涡度的平均值呈现递减趋势,说明日本南部低位势涡度水在不断积累,这样会使得四国再循环流的强度增强,迫使黑潮保持平直路径,同时,近岸黑潮垂直流速剪切增大,斜压不稳定性的作用也逐渐增大;当黑潮从非大弯曲路径向大弯曲路径过渡时,再循环流强度的减弱会导致黑潮的流速剪切减小。根据海表高度异常场以及海洋上层流场信息发现,近岸黑潮附近的气旋涡会随着再循环流区域反气旋涡的东侧向南运动,最终导致黑潮大弯曲的发生。分析涡流的能量,结果显示,黑潮大弯曲路径的形成与斜压不稳定性密切相关。 相似文献
9.
使用卫星测高、海表温度以及中国沿海台站水位等数据，分析研究了ENSO对中国近海海平面影响的区域特征。结果表明:（1）赤道东太平洋海表温度与我国近海海平面存在显著的遥相关关系。相关系数自北至南呈梯度递增，分为3个影响明显的区域，分别是渤、黄海、东海和南海海域。南海海平面异常与赤道东太平洋区域的海表温度异常相关性最强，大部分区域的相关系数超过了0.6；东海海域海平面异常与赤道东太平洋海表温度的遥相关系数弱于南海，强于渤、黄海，大部分海域的遥相关系数超过了0.4；渤、黄海海域海平面异常与赤道东太平洋海表温度的遥相关系数最弱，但是大部分海域的遥相关系数超过了0.3，通过了显著性检验。（2）中国沿海海平面的季节变化与ENSO有明显的相关关系，且影响范围具有明显的区域特征，以长江口和台湾海峡为分界线分为长江口以北、长江口到台湾海峡以及台湾海峡以南3个区域。海平面的年振幅在厄尔尼诺年均出现偏低的现象，并且年振幅的极小值均出现在厄尔尼诺年。另外，海平面的年振幅对厄尔尼诺事件的响应与其强弱有关，在强厄尔尼诺事件中，响应区域和幅度较大，弱事件中，响应区域和幅度偏小。（3）南海、东海和渤、黄海这3个区域沿海的海平面变化均存在4~7 a的显著振荡周期，说明这3个区域的海平面均受ENSO的影响。其中，南海7 a周期的振荡幅度最大，约为1.5 cm；东海7 a周期的振荡幅度次之，约为1.3 cm；渤、黄海6 a周期的振荡幅度最小，不到1 cm。 相似文献
10.
利用"908"专项所获取的CTD观测资料,系统地阐述了渤、黄、东海温度的分布特征及季节变化。结果显示,冬季,水平方向上,水温分布呈现多舌状:外海温度多暖舌结构,近岸等温线基本平行于岸线,并出现多个指向南方的冷水舌,且暖流区与近岸冷水区间形成了较强的温度峰。夏季,三大海域底层均出现了各具特色的冷水团和冷水块,最为典型的有"渤中冷水"、"辽东湾冷水"、黄海冷水团、青岛冷水团和东海北部底层冷水。春、秋季水温分布呈现过渡季节的特征。春季,跃层开始出现,"渤中冷水"及黄海冷水团等冷水现象开始形成。进入秋季,跃层明显下沉,直至消失,水温分布逐渐呈现垂向均匀状况。同时,分析还表明,三大海域的水温分布存在明显的区域性差异。水温分布的年变幅从北向南、从近岸向外海递减。 相似文献
11.
东海沿海季节性海平面异常成因 总被引：1，自引：0，他引：1
Based on the analysis of sea level, air temperature, sea surface temperature(SST), air pressure and wind data during 1980–2013, the causes of seasonal sea level anomalies in the coastal region of the East China Sea(ECS) are investigated. The research results show:(1) sea level along the coastal region of the ECS takes on strong seasonal variation. The annual range is 30–45 cm, larger in the north than in the south. From north to south, the phase of sea level changes from 140° to 231°, with a difference of nearly 3 months.(2) Monthly mean sea level(MSL)anomalies often occur from August to next February along the coast region of the ECS. The number of sea level anomalies is at most from January to February and from August to October, showing a growing trend in recent years.(3) Anomalous wind field is an important factor to affect the sea level variation in the coastal region of the ECS. Monthly MSL anomaly is closely related to wind field anomaly and air pressure field anomaly. Wind-driven current is essentially consistent with sea surface height. In August 2012, the sea surface heights at the coastal stations driven by wind field have contributed 50%–80% of MSL anomalies.(4) The annual variations for sea level,SST and air temperature along the coastal region of the ECS are mainly caused by solar radiation with a period of12 months. But the correlation coefficients of sea level anomalies with SST anomalies and air temperature anomalies are all less than 0.1.(5) Seasonal sea level variations contain the long-term trends and all kinds of periodic changes. Sea level oscillations vary in different seasons in the coastal region of the ECS. In winter and spring, the oscillation of 4–7 a related to El Ni?o is stronger and its amplitude exceeds 2 cm. In summer and autumn, the oscillations of 2–3 a and quasi 9 a are most significant, and their amplitudes also exceed 2 cm. The height of sea level is lifted up when the different oscillations superposed. On the other hand, the height of sea level is fallen down. 相似文献
12.
Subinertial and seasonal variations in the Soya Warm Current revealed by HF ocean radars,coastal tide gauges,and bottom-mounted ADCP 总被引：2，自引：2，他引：0
Naoto Ebuchi Yasushi Fukamachi Kay I. Ohshima Masaaki Wakatsuchi 《Journal of Oceanography》2009,65(1):31-43
Subinertial and seasonal variations in the Soya Warm Current (SWC) are investigated using data obtained by high frequency
(HF) ocean radars, coastal tide gauges, and a bottom-mounted acoustic Doppler current profiler (ADCP). The HF radars clearly
captured the seasonal variations in the surface current fields of the SWC. Almost the same seasonal cycle was repeated in
the period from August 2003 to March 2007, although interannual variations were also discernible. In addition to the annual
and interannual variations, the SWC exhibited subinertial variations with a period of 5–20 days. The surface transport by
the SWC was significantly correlated with the sea level difference between the Sea of Japan and Sea of Okhotsk for both the
seasonal and subinertial variations, indicating that the SWC is driven by the sea level difference between the two seas. The
generation mechanism of the subinertial variation is discussed using wind data from the European Centre for Medium-range Weather
Forecasts (ECMWF) analyses. The subinertial variations in the SWC were significantly correlated with the meridional wind stress
component over the region. The subinertial variations in the sea level difference and surface current delay from the meridional
wind stress variations by one or two days. Sea level difference through the strait caused by wind-generated coastally trapped
waves (CTWs) along the east coast of Sakhalin and west coast of Hokkaido is considered to be a possible mechanism causing
the subinertial variations in the SWC. 相似文献
13.
本文通过对中国沿海25个观测站水位资料的分析,初步探讨了中国沿海1980-2012年增减水的变化特征及与海平面变化的关系。结果表明:（1）中国沿海增减水的季节变化特征明显,相邻站由于受到的气象状况相同,其沿海增减水变化的过程相近,但是变化幅度存在较大差异。从空间分布看,沿海增减水的变化幅度呈现中间大南北小的区域特征,自长江口至广东沿海,增减水的年变化幅度最大,年变幅平均为5.0~7.5 cm;南海周边及北部湾沿海,增减水的年变化幅度次之,年变幅平均为4.0~5.5 cm;自渤海至黄海沿海,增减水的年变化幅度较小,年变幅平均为3.3~3.5 cm。（2）从时间变化看,1980-2012年中国沿海年平均增减水长期基本没有趋势性变化,但明显存在2至5年的周期性变化信号,该信号的震荡幅度为0.1 cm。经过高频滤波后,对沿海月平均增减水序列与Niño3.4指数进行相关性分析,相关系数为-0.5,该相关系数通过了显著性检验,说明中国沿海的增减水变化与ENSO事件呈现负相关关系。（3）中国沿海增减水的长期变化及空间分布特征均与海平面变化不同。1980-2012年,中国沿海海平面的上升速率为2.9 mm/a,而增减水长期基本无趋势性变化;另外,其季节变化与海平面的季节变化从时间和区域上均不存在一致性。（4）但是,短期海平面的变化与增减水有关,并且增减水对短期海平面的贡献根据其具体情况而定,增水幅度大且持续时间长的过程对短期海平面有抬升作用,其贡献率最大可达65%;反之,减水幅度大且持续时间长的过程则对短期海平面有降低的作用。 相似文献
14.
The Chukchi and Beaufort Seas include several important hydrological features： inflow of the Pacific water, Alaska coast current （ ACC ）, the seasonal to perennial sea ice cover, and landfast ice ＇along the Alaskan coast. The dynamics of this coupled ice-ocean system is important for both regional scale oceanography and large-scale global climate change research. A mumber of moorings were deployed in the area by JAMSTEC since 1992, and the data revealed highly variable characteristics of the hydrological environment. A regional high-resolution coupled ice-ocean model of the Chukchi and Beaufort Seas was established to simulate the ice-ocean environment and unique seasonal landfast ice in the coastal Beaufort Sea. The model results reproduced the Beaufort gyre and the ACC. The depthaveraged annual mean ocean currents along the Beaufort Sea coast and shelf hreak compared well with data from four moored ADCPs, but the simulated velocity had smaller standard deviations, which indicate small-scale eddies were frequent in the region. The model resuits captured the sea,real variations of sea ice area as compared with remote sensing data, and the simulated sea ice velocity showed an ahnost stationary area along the Beaufort Sea coast that was similar to the observed landfast ice extent. It is the combined effects of the weak oceanic current near the coast, a prevailing wind with an onshore component, the opposite direction of the ocean current, and the blocking hy the coastline that make the Beaufort Sea coastal areas prone to the formation of landfast ice. 相似文献
15.
东海海平面变化的综合分析 总被引：3，自引：2，他引：1
利用1993年1月至2011年12月的卫星高度计数据,研究了东海海平面变化的季节信号、线性趋势和低频信号,并结合风应力资料、Ishii温盐数据和海表面温度数据分析了季节信号和低频信号的驱动机制。东海季节性海平面变化主要由年信号组成,其占海平面变化的大部分;年信号振幅和相位的分布具有明显的区域差异;东海季节性海平面变化主要受海面风和海水热膨胀驱动,而且在不同季节、不同区域,两种驱动机制的作用存在明显差异,主导地位也不断变化;季节信号还受到黑潮的一定影响。1993-2011年间东海海平面线性上升速率为3.28mm/a,各海域海平面上升速率不同。东海海平面变化低频信号与比容海平面变化低频信号具有显著相关性,最大相关系数为0.55;东海比容海平面变化低频信号与SOI低频信号同样具有一定的相关性,最大相关系数为0.3。ENSO通过大气环流和黑潮洋流等对东海海域的比容海平面变化产生影响,比容海平面变化进而对东海年际间海平面变化产生调制作用,因此ENSO可以通过东海年际间比容海平面变化对东海年际间海平面变化产生影响。 相似文献
16.
南海沿海季节性海平面异常变化特征及成因分析 总被引：1，自引：1，他引：0
Based on sea level, air temperature, sea surface temperature(SST), air pressure and wind data during 1980–2014,this paper uses Morlet wavelet transform, Estuarine Coastal Ocean Model(ECOM) and so on to investigate the characteristics and possible causes of seasonal sea level anomalies along the South China Sea(SCS) coast. The research results show that:(1) Seasonal sea level anomalies often occur from January to February and from June to October. The frequency of sea level anomalies is the most in August, showing a growing trend in recent years. In addition, the occurring frequency of negative sea level anomaly accounts for 50% of the total abnormal number.(2) The seasonal sea level anomalies are closely related to ENSO events. The negative anomalies always occurred during the El Ni?o events, while the positive anomalies occurred during the La Ni?a(late El Ni?o) events. In addition, the seasonal sea level oscillation periods of 4–7 a associated with ENSO are the strongest in winter, with the amplitude over 2 cm.(3) Abnormal wind is an important factor to affect the seasonal sea level anomalies in the coastal region of the SCS. Wind-driven sea level height(SSH) is basically consistent with the seasonal sea level anomalies. Moreover, the influence of the tropical cyclone in the coastal region of the SCS is concentrated in summer and autumn, contributing to the seasonal sea level anomalies.(4) Seasonal variations of sea level, SST and air temperature are basically consistent along the coast of the SCS, but the seasonal sea level anomalies have no much correlation with the SST and air temperature. 相似文献
17.
Response of the low-frequency fluctuations of sea level to atmospheric forcing along the coasts of the Huanghai Sea and the East China Sea 总被引：1，自引：0，他引：1
In this paper, the low-frequency fluctuations of sea level and their relationship to atmospheric forcing along the coasts of the Huanghai Sea and the East China Sea are studied. Spectrum analyses are made for the time series of daily mean sea level, atmospheric pressure and wind stress at seven coastal stations. It is found that at all the stations, the main part of the energy of the sea level fluctuations, within the (2-60)-day period, is concentrated on the (12-60)-day period band and that an obvious spectral peak appears at the 3-day period. Along the coast of the Huanghai Sea, variations in the sea level are greater in winter than in summer. In winter, along the coasts of the Huanghai Sea and the East China Sea there is a kind of sea level fluctuations propagating southwards. Among the many factors causing sea level variation, the most obvious one is atmospheric pressure, followed next by the alongshore wind stress. 相似文献
18.
Spatio-temporal variability in sea surface wind stress near and off the east coast of Korea 总被引：1，自引：1，他引：0
Sea surface wind stress variabilities near and off the east coast of Korea, are examined using 7 kinds of wind datasets from measurements at 2 coastal (land) stations and 2 ocean buoys,satellite scatterometer (QuikSCAT), and global reanalyzed products (ECMWF,NOGAPS,and NCEP/NCAR). Temporal variabilities are analyzed at 3 frequency bands; synoptic (2-20 d), intra-seasonal (20-90 d),and seasonal (>90 d).Synoptic and intra-seasonal 相似文献
19.
基于ROMS模式利用集合最优插值同化沿轨海表面高度异常数据的研究 总被引：2，自引：1，他引：1
The ensemble optimal interpolation （EnOI） is applied to the regional ocean modeling system （ROMS） with the ability to assimilate the along-track sea level anomaly （TSLA）. This system is tested with an eddy-resolving system of the South China Sea （SCS）. Background errors are derived from a running seasonal ensemble to account for the seasonal variability within the SCS. A fifth-order localization function with a 250 km localization radius is chosen to reduce the negative effects of sampling errors. The data assimilation system is tested from January 2004 to December 2006. The results show that the root mean square deviation （RMSD） of the sea level anomaly decreased from 10.57 to 6.70 cm, which represents a 36.6% reduction of error. The data assimilation reduces error for temperature within the upper 800 m and for salinity within the upper 200 m, although error degrades slightly at deeper depths. Surface currents are in better agreement with trajectories of surface drifters after data assimilation. The variance of sea level improves significantly in terms of both the amplitude and position of the strong and weak variance regions after assimilating TSLA. Results with AGE error （AGE） perform better than no AGE error （NoAGE） when considering the improvements of the temperature and the salinity. Furthermore, reasons for the extremely strong variability in the northern SCS in high resolution models are investigated. The results demonstrate that the strong variability of sea level in the high resolution model is caused by an extremely strong Kuroshio intrusion. Therefore, it is demonstrated that it is necessary to assimilate the TSLA in order to better simulate the SCS with high resolution models. 相似文献