Sa分潮与月平均海面

根据临时验潮站观测到的一个月潮位资料通常能够分析得到11个分潮的调和常数。如果用所分析得到的调和常数与邻近站的Sa和Ssa的调和常数以及年平均海面做出潮汐预报,则在这一个月当中的平均海面的日变化将会反映出来,因而,潮位预报精度应该比仅由11个分潮和月平均海面所预报的潮位要高。本文对上述的问题进行论述。     

用TOPEX/Poseidon资料研究南海潮汐和海面高度季节变化

采用引入差比关系法对南海TOPEX/Poseidon卫星高度计算资料进行了潮汐分析；根据所得潮汐调和常数对卫星高度计测得的海面高度进行潮汐订证，进而得到南海各季节的海面高度距平。结果表明，南海冬、夏季季风强盛期海面高度距平位相相反，南海中部夏季为正距平，且有2个正距平中心；冬季为负距平，且有2个负距平中心。春、秋季是不同的季风过渡期，海面高度距平分布也明显不同：南海中部春季为正距平，且只有1个正距平中心；秋季为负距平，且只有1个负距平中心。研究表明，长周期分潮Sa和Saa的叠加值可以很好地逼近南海海面高度距平。根据平均海面和海面高度距平得到了合成的海面高度和地转流场，发现南海表层地转流总体上是气旋式的；秋、冬季表层环流的西向强化十分明显，春、夏季较弱；冬季黑潮通过吕宋海峡进入南海北部，夏季基本上没有进入南海。     

渤黄海潮汐潮流精细化数值模拟及可视化预报系统

利用有限元海洋模式ADCIRC (Advanced Circulation Model),建立了高分辨率的渤黄海二维潮汐潮流数值模型,该模型以M2,S2,K1,O1等8个分潮的水位作为驱动,模拟出了该8个分潮的潮汐潮流调和常数;利用该调和常数预报的潮位和二维平均潮流与实测资料相比,符合较好;利用模拟得到的潮汐潮流调和常...     

利用T/P 卫星高度计资料调和分析南海潮汐信息

利用j,v模型调和分析1992～2002年共10 a的TOPEX/Poseidon(T/P)海面高度距平资料,提取了南海K1,O1,P1,Q1,M2,S2,N2和K2等8个主要分潮的潮汐调和常数。分析比较了卫星上下行轨道的19个交叉点的振幅和迟角,其中M2,S2,K1和O1的平均向量均方根偏差分别是1.5,1.1,2.5和1.4 cm;将交叉点的调和常数与TPXO7.2模式的结果进行了比较,结果表明M2,S2,K1和O1分潮振幅的绝对平均误差均小于3 cm,迟角的最大绝对平均误差为7.8°。选取了与卫星轨道较近的8个验潮站,对验潮站的实测数据调和常数和本文所得调和常数进行了比较,结果显示K1分潮的向量均方根偏差为4.7 cm,M2分潮的向量均方根偏差为3.7 cm。论文结果表明利用j,v模型调和分析方法对南海海域卫星高度计资料进行潮汐信息提取是可靠的,并可为局部重力场的研究提供海洋潮汐改正数据,有一定的参考价值。     

基于T/P和Jason-1/2卫星高度计海面高度数据获取南海同潮图的研究

随着卫星高度计资料的不断丰富,通过对卫星高度计所得潮汐调和常数进行插值或拟合得到潮汐同潮图成为可能。本文拟对T/P(TOPEX/POSEIDON)、Jason-1和Jason-2卫星高度计数据进行分析,得到南海区域星下观测点处四个主要分潮(M2、S2、K1和O1分潮)的调和常数,进而利用双调和样条插值方法对其进行插值,获取南海同潮图。首先,以1992～2016年T/P和Jason卫星高度计所得海面高度数据为基础,利用调和分析方法计算了南海星下观测点处M2、S2、K1和O1四个主要分潮的调和常数,并与40个验潮站数据进行了对比,最大矢量均差为4.99cm,说明分析所得调和常数与利用验潮站资料提取的调和常数的误差较小。进而采用双调和样条插值方法对星下点调和常数进行插值,得到了南海四个主要分潮的同潮图,所得结果与全球潮汐模型TPXO7.2模式结果的矢量均差分别为4.69、2.46、3.13和2.42 cm,与141个验潮站处观测结果的矢量均差分别为22.59、10.26、10.24和8.51 cm。此外,插值所得四个主要分潮的无潮点位置与前人研究结果相近。上述实验结果表明:利用双调和样条插值方法对卫星高度计所得调和常数进行插值能够获取较为准确的同潮图。     

高、低潮数据的调和分析

本文给出了由高、低潮数据计算潮汐调和常数和由最大流速及转流数据计算潮流调和常数的方法。文章还讨论了不同频率分潮间的混淆效应,指出本方法用于混合型和全日型潮汐可获得比半日型潮汐好的效果。对两个港口实测高、低潮数据分析表明,所得调和常数与由逐时潮高分析所得的数值一般较接近,但对长周期分潮较差。本方法所得调和常数用于预报高、低潮或最大流速和转流时可得到很好的结果。     

潮汐调和常数的变化趋势研究

潮汐调和常数具有随时间变化的特性,以某一长期验潮站44年的观测数据为样本,研究分析了在短期、中期和长期观测时段下潮汐调和常数的变化规律,计算出各分潮调和常数的平均值、最大互差及中误差的变化量级。研究表明,较短时间的观测资料得出的各分潮调和常数存在着较大的变动误差,但随着观测时间的增长,其误差量级呈逐渐减小并且逐步稳定的变化趋势。建议采用调和常数计算理论最低潮面时,宜选定19年作为观测周期,以消除分潮调和常数的误差影响,满足高精度海洋测深基准面的稳定和统一。     

潮汐非调和常数的计算方法——Ⅱ.人工计算过程

在本文第Ⅰ部分,我们导出了日潮和半日潮平均振幅的计算式,其中包括半日潮振幅和位相的浅水校正。这些计算式经简化后已经只包含M_2,S_2,K_l,O_l,M_4,M_6这六个分潮的调和常数。第Ⅱ部分主要讨论利用日潮和半日潮平均振幅计算潮汐非调和常数的具体过     

中国沿岸验潮站潮汐调和常数的精度评估

论证了验潮站潮汐调和常数的精度指标与精度评估方法,对中国沿岸有代表性的长期验潮站分别按年、月调和分析结果序列进行了调和常数的精度统计计算。结果表明,对于面向开阔海域的验潮站,由年观测资料分析的主要分潮振幅具有毫米级精度,月分析结果具有厘米级精度。而分布于黄海、东海沿岸和北部湾的验潮站,由年、月观测序列求得的调和常数均存在较大量级的趋势性或周期性变化成分。为海图深度基准面计算和潮汐模型精度评价的需要,对调和常数实施修正和规定参考历元是必要的。     

全球大洋潮汐模式在北印度洋潮汐预报准确性的评估

为评估DTU10、TPXO8、GOT00.2和NAO.99b 4个全球大洋潮汐模式对北印度洋潮汐的预报能力,采用英国海洋资料中心提供的海区中部和沿岸站潮汐调和常数资料,检验了这些模式4个主要分潮(M_2、S_2、K_1、O_1)的准确度。它们的各分潮调和常数资料准确度都比较高,振幅绝均差的最大值仅5.61 cm,迟角绝均差的最大值仅9.13°。这些模式的调和常数给出潮波传播特征差别不大。基于这些模式提供的调和常数,分别建立了北印度洋4、8和16分潮潮汐预报模型,将预报结果与中国海事服务网提供的沿岸24个站潮汐表资料进行对比。各模式的8分潮(M_2、S_2、N_2、K_2、K_1、O_1、P_1、Q_1)潮汐预报模型均优于4分潮(M_2、S_2、K_1、O_1)潮汐预报模型,NAO.99b模式可以提供16分潮(M_2、S_2、N_2、K_2、K_1、O_1、P_1、Q_1、MU_2、NU_2、T_2、L_2、2N_2、J_1、M1、OO_1)潮汐预报模型,但是对预报结果改善不明显;在各模式中,GOT00.2模式的8分潮潮汐预报模型对北印度洋沿岸的预报效果最好,平均绝均差为14.97 cm。     

厦门地区软相潮间带多毛类的生态

根据厦门地区１９９０年２月至１９９２年１月调查软相潮间带所获资料，研究了该区多毛类的种类组成，数量与分布，结果表明，该区多毛类种类丰富，共鉴定出１１８种，隶属于３７科８３属。其中，高潮区４０种，中潮区９０种，低潮区８３种。多毛类平均栖息密度８７个／ｍ＾３，平均生物量３．３３ｇ／ｍ＾２。     

Improving the Coastal Mean Dynamic Topography by Geodetic Combination of Tide Gauge and Satellite Altimetry

Abstract

The ocean mean dynamic topography (MDT) is the surface representation of the ocean circulation. The MDT may be determined by the ocean approach, which involves temporal averaging of numerical ocean circulation model information, or by the geodetic approach, wherein the MDT is derived using the ellipsoidal height of the mean sea surface (MSS), or mean sea level (MSL) minus the geoid as the geoid. The ellipsoidal height of the MSS might be estimated either by satellite or coastal tide gauges by connecting the tide gauge datum to the Earth-centred reference frame. In this article we present a novel approach to improve the coastal MDT, where the solution is based on both satellite altimetry and tide gauge data using new set of 302 tide gauges with ellipsoidal heights through the SONEL network. The approach was evaluated for the Northeast Atlantic coast where a dense network of GNSS-surveyed tide gauges is available. The typical misfit between tide gauge and satellite or oceanographic MDT was found to be around 9?cm. This misfit was found to be mainly due to small scale geoid errors. Similarly, we found, that a single tide gauge places only weak constraints on the coastal dynamic topography.     

大鹏湾岬湾型海滩季节性变化特征及原因分析——以官湖海滩为例

随着全球海平面的上升及极端气象的频发,全球海滩总体呈现出一定的退化现象,海滩保护成为海岸带生态修复的焦点问题之一。我国华南地区岬湾型海滩分布广泛,以深圳市大鹏湾官湖海滩为代表,基于2020—2021年实测海滩剖面高程数据,分析岬湾型海滩季节性变化特征。研究表明,官湖海滩剖面坡度夏秋缓冬春陡,夏秋侵蚀冬春淤积;海滩沉积物粒径季节性变化不明显。海滩剖面形态受风浪、平均潮位的季节性变化控制,以夏秋季为例,平均潮位逐渐升高,南向波浪强度较大,在二者的共同作用下,海滩后滨侵蚀明显,泥沙离岸输运,并在前滨淤积。补沙方案宜在夏秋季进行,且重点区域为官湖海滩东侧与观海湾海滩,防御方案应主要削弱南向波浪。     

Inferring the global mean sea level from a global tide gauge network

An attempt is made to infer the global mean sea level(GMSL) from a global tide gauge network and frame the problem in terms of the limitations of the network. The network,owing to its limited number of gauges and poor geographical distribution complicated further by unknown vertical land movements,is ill suited for measuring the GMSL. Yet it remains the only available source for deciphering the sea level rise over the last 100 a. The poor sampling characteristics of the tide gauge network have necessitated the usage of statistical inference. A linear optimal estimator based on the Gauss-Markov theorem seems well suited for the job. This still leaves a great deal of freedom in choosing the estimator. GMSL is poorly correlated with tide gauge measurements because the small uniform rise and fall of sea level are masked by the far larger regional signals. On the other hand,a regional mean sea level(RMSL) is much better correlated with the corresponding regional tide gauge measurements. Since the GMSL is simply the sum of RMSLs,the problem is transformed to one of estimating the RMSLs from regional tide gauge measurements. Specifically for the annual heating and cooling cycle,we separate the global ocean into 10-latitude bands and compute for each 10-latitude band the estimator that predicts its RMSL from tide gauges within. In the future,the statistical correlations are to be computed using satellite altimetry. However,as a first attempt,we have used numerical model outputs instead to isolate the problem so as not to get distracted by altimetry or tide gauge errors. That is,model outputs for sea level at tide gauge locations of the GLOSS network are taken as tide gauge measurements,and the RMSLs are computed from the model outputs. The results show an estimation error of approximately 2 mm versus an error of 2.7 cm if we simply average the tide gauge measurements to estimate the GMSL,caused by the much larger regional seasonal cycle and mesoscale variation plaguing the individual tide gauges. The numerical model,Los Alamos POP model Run 11 lasting 3 1/4 a,is one of the best eddy-resolving models and does a good job simulating the annual heating and cooling cycle,but it has no global or regional trend. Thus it has basically succeeded in estimating the seasonal cycle of the GMSL. This is still going to be the case even if we use the altimetry data because the RMSLs are dominated by the seasonal cycle in relatively short periods. For estimating the GMSL trend,longer records and low-pass filtering to isolate the statistical relations that are of interest. Here we have managed to avoid the much larger regional seasonal cycle plaguing individual tide gauges to get a fairly accurate estimate of the much smaller seasonal cycle in the GMSL so as to enhance the prospect of an accurate estimate of GMSL trend in short periods. One should reasonably expect to be able to do the same for longer periods during which tide gauges are plagued by much larger regional interannual(e. g.,ENSO events) and decadal sea level variations. In the future,with the availability of the satellite altimeter data,we could use the same approach adopted here to estimate the seasonal variations of GMSL and RMSL accurately and remove these seasonal variations accordingly so as to get a more accurate statistical inference between the tide gauge data and the RMSLs(therefore the GMSL) at periods longer than 1 a,i. e.,the long-term trend.     

渤海海峡断面温度结构及流量的季节变化

作者采用 POM模式 ,利用从卫星遥感资料反演的风和海表温度 (SST)数据并考虑 M2分潮作用 ,对渤海海域的温度、流场的三维结构进行数值计算。根据数值模式的计算结果 ,重点分析渤海海峡温度结构和水交换的季节变化特征。结果表明风应力和 SST的季节性变化导致渤海海峡的水交换流型、温度结构和流量有明显的季节性变化。     

渤、黄、东海海流和潮汐共同作用下的悬浮物输运、沉积及其季节变化

渤、黄、东海是一个水动力状况相当复杂的半封闭宽陆架海，本海区悬浮颗粒物含量高，季节变化明显，影响范围广，是世界上悬浮物含量最高的海域之一。对于该海域悬浮物的输运沉积过程、分布规律以及底质分布等中外学者均进行过比较深入的研究(秦蕴珊，1963； Honjo et al.，1974；Milliman et al.，1985，1986；秦蕴珊等，1987，1989；杨作升等，1992；Li et al.，1997；孙效功等，2000；雷坤等，2001)。然而，以往的研究大都基于实际海洋调查资料，由于受实测资料在时间和空间覆盖范围上的限制，很难从整体上把握渤、黄、东海陆架区悬浮物输运的时间和空间变化规律。数值模拟的方法能很好地克服上述局限，已有学者从不同角度对渤、黄、东海的某些海域的悬浮物进行了模拟研究。 董礼先等(1989)首先模拟了在二维潮流场作用下，黄、渤海推移质和悬移质的输运状况，得出潮流作用下海底的冲淤状况。Graber等(1989)利用有限水深的风浪模型、模拟了风浪对悬浮物输运、沉积的作用。Yanagi等(1995)用拉格朗日粒子追踪方法对整个东中国海冬季悬浮物的输运、沉积过程进行了计算。江文胜等(2000，2001)考虑了风等气象要素、外海传入的潮波的作用、悬浮物的沉降及再悬浮机制，对渤海中悬浮物的浓度进行了数值模拟。 海洋环流、潮汐、潮流和波浪均对悬浮物的输运与沉积产生影响，尤其在中陆架和外陆架地区，环流对悬浮物的长期输运起决定性作用，因此以往仅针对潮流、风浪作用的模拟很不完整，其结果与实际情况的差别也会较大。其次，海水的流动处在不断变化之中，小到日变化、月变化，大到季节变化、年际变化，因此定常风场、定常温盐场的环流模拟，即诊断流场并不符合实际情形。本文将首先对渤、黄、东海月平均风场、温盐场作用下的环流场进行模拟，进而探讨环流以及潮汐、潮流共同作用下的悬浮物输运过程及其季节变化规律。     

Comparative simulation study of effects of eddy-topography interaction in the East/Japan Sea deep circulation

In this study the structure and seasonal variations of deep mean circulation in the East/Japan Sea (EJS) were numerically simulated using a mid-resolution ocean general circulation model with two diffe...     

Mechanism of currents through the straits of the Japan Sea: Mean state and seasonal variation

The mechanism governing the mean state and the seasonal variation of the transports through the straits of the Japan Sea is studied using a newly presented, simple analytical model and a basin scale general circulation model (GCM). The GCM reproduces the transports through the straits of the Japan Sea realistically owing to its fine horizontal resolution of about 20 km and realistic topography. A series of experiments conducted by changing surface forcing shows that the annual mean wind-driven circulation in the North Pacific Ocean is most responsible for the formation of the mean transports. It is also found that the seasonal variation of the alongshore component of monsoonal wind stress over the North Pacific basin, especially that over the Okhotsk Sea, is responsible for the seasonal variation of the transports. The simple analytical model can explain these simulated features very well. The physical concept of this model is based on the formation of the around-island circulation through the adjustment of coastally trapped waves and Rossby waves and geostrophic control at the narrow straits. It solves the sea surface heights (SSHs) at the edge of each strait and the transport through it. The value of the line integral of the SSH along the island is determined by the baroclinic Rossby waves approaching the island from the east and the alongshore wind stress around the island. The basin scale seasonal variation of SSH along the coast induced by the variation of the alongshore monsoonal wind stress can also be incorporated into this model by giving the SSH anomaly at the northeastern point of the Soya Strait. Thus, it is suggested that both the mean state and the seasonal variation are caused mainly by wind stress forcing. Minor modification by the seasonal heat flux forcing brings the amplitude and the phase of the seasonal variation closer to the observed values.     

Effect of Sea Level Variation on Calculation of Design Water Level

The long-term variation and seasonal variation of sea level have a notable effect on the calculation of engineering water level. Such an effect is first analyzed in this paper. The maximal amplitude of inter-annual anomaly of monthly mean sea level along the China coast is larger than 60 cm. Both the storm surge disaster and cold wave disaster are seasonal disasters in various regions, so the water level corresponding to the 1% of the cumulative frequency in the cumulative 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 stochasti     

渤、黄海风生流场季节循环时空模态与变异

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.