济州岛南部海区的双跃层现象

本文分析了济州岛南部区域温度双跃层现象的类型及其成因。特别阐明了双跃层的波状现象,指出:强流锋区的侧向效应,黑潮次—中层混合水的爬升,黄海冷水团边缘密度环流引起的侧向流动,以及上、下层流速、流向不一致引起的剪切作用,是导致双跃层波状现象的主要原因。发现上、下跃层之间存在着“跃层间环流”,这是一个有趣的海洋学现象,它将导致双扩散的发生和有利于双跃层的维持。     

聚类分析法在浅海水团分析中的应用及黄、东海变性水团的分析

本文引入变性水团概念,用聚类分析确定黄、东海浅海海域变性水团的边界及其变化。根据给定的标准进行聚类,确定了水团的个数、边界及混合区。 由聚类方法所得结果看出,在该海区中有八个变性水团。根据温、盐相对指标,将这些水团分为九种不同的特征。也可以把这些水团划分为三种盐度类型。在温—盐点聚图上,不同变性水团的温盐点,分布于一条曲线附近,它体现出逐级变性的特点。各变性水团的变化范围都很大,这说明该海区中水团变性强烈。在暖季中的增温降盐和冷季中的降温增盐,可认为是整个黄海和东海水体变性的特征。所有季节性水团都经历一个形成与消亡的过程。 文中讨论了变性水团和海洋环境的相互关系。水团变性是热力因素和动力因素共同作用而产生的。通过变性水团的分析,作者认为,在该海区水团的变性中,热力因素起着主要作用。变性水团界线的舌状分布与流向之间的关系是很明显的,可作为分析环流的旁证。最后描述了变性水团和底层中心渔场之间的关系。     

长江口及济州岛附近海域变性水团的初步分析

基于变性水团的概念,本文把聚类分析用于确定长江口及济州岛附近海域变性水团的边界。由聚类分析得到的结果表明,在该海区有十个水团。对它们的特征、分布与变化进行了初步分析。作者得出的结论是:1、在十个水团中,有四个大洋性水团,六个变性水团。2、该海域水团变性的特点为暧季增温、降盐、降氧,而冷季则相反。3、水团变性是由海区内、外因素综合作用而发生的,而后者在浅水区域起主要作用。4、水团边界的舌状分布与流向之间有明显关系。因之,海流的方向及强度,大致可依水团舌状分布而判断。5、底层中心渔场基本上位于各变性水团之间的混合区或其附近。     

南海北部海区水团的判别分析

将判别分析应用于南海北部海区的水团分析。划分为八个水团:沿岸冲淡水团(F),近岸混合水团(M),暖表层水团(WS),表层水团(S),表—次层混合水团(SU),次层水团(U),次—中层混合水团(UI)和中层水团(I)。给出了各水团在四季代表月的Bayes多组判别的系数和参数。用资料检验判别的成效.冬季和春季可达95.90％以上,夏季为94.80％,秋季是全年最低值,为92.72％。讨论了造成错判的原因,并与Fisher判别作了比较。当测值维数较低时,建议选用Bayes判别。对八个水团以及各水团两两之间差异的显著性进行了检验,证实在每个季节中各水团之间的差异,都在高度置信水平(α=0.01)上具有显著性。因而,划分为八个水团是有实际意义的,其判别式的系数和参数,可用于实际的判别和预报。     

用模糊集合观点讨论水团的有关概念

本文将划分水团的基本原则,概括为水团内部特征的相对均一性及其与外部海水的明显差异性。用模糊集合讨论了水型、水团和水系等有关概念。提出了用模糊集合观点定义水团及其核心、本体、边界与混合区的建议,并以1979年8月黄海和东海表层为例,给出了各水团的隶属函数。计算了其核心、本体、边界、混合区及贴近度,按其模糊性排出了顺序。     

Baroclinic Buoyancy-Inertia Joint Stability Parameter

At present, the barotropic buoyant stability parameter has been derived from a vertical virtual displacement of a water parcel. The barotropic inertial stability parameter in the eccentrically cyclogeostrophic, basic current field was derived in 2003 from a horizontal cross-stream virtual displacement of a parcel. By expressing acceleration of a parcel due to a virtual displacement, which is arbitrarily sloping within a vertical section across the basic current, in terms of natural coordinates, we derived the vertical component of baroclinic buoyant stability parameter B ₂ ², the horizontal component of baroclinic inertial stability parameter I ₂ ², the baroclinic joint stability parameter J ², its buoyant component B ² and its inertial component I ². B ² is far greater than I ₂ ², and when neglecting relative vorticity except for vertical shear, a downward convex curve of J ² plotted against the slope of a virtual displacement follows a trend of B ² curve. If a parcel displaces along a horizontal surface or an isopycnal surface, however, B ² vanishes, and J ² becomes equal to I ². Actual parcel is apt to displace not only along the bottom slope, but also along the sea surface and an isopycnal interfacial surface, which is approximately equivalent to an isentropic surface, preferred by lateral mixing and exchange of momentum. Such actual displacement makes B ² vanishing, and grants I ² an important role. The present analysis of I ² examining effects due to curvature and horizontal and vertical shear vorticities are useful in deepening our understanding of baroclinic instability in actual oceanic streams.     

Simulations of Annual Cycle of Phytoplankton Production and the Utilization of Nitrogen in the Yellow Sea

A nutrient dynamic model coupled with a 3D physical model has been developed to study the annual cycle of phytoplankton production in the Yellow Sea. The biological model involves interactions between inorganic nitrogen (nitrate and ammonium), phosphate and phytoplankton biomass. The model successfully reproduces the main features of phytoplankton-nutrient variation and dynamics of production. 1. The well-mixed coastal water is characterized by high primary production, as well as high new production. 2. In summer, the convergence of tidal front is an important hydrodynamic process, which contributes to high biomass at frontal areas. 3. The evolution of phytoplankton blooms and thermocline in the central region demonstrate that mixing is a dominant factor to the production in the Yellow Sea. In this simulation, nitrate- and ammonium-based productions are estimated regionally and temporally. The northern Yellow Sea is one of the highly ranked regions in the Yellow Sea for the capability of fixing carbon and nitrogen. The annual averaged f-ratio of 0.37 indicates that regenerated production prevails over the Yellow Sea. The result also shows that phosphate is the major nutrient, limiting phytoplankton growth throughout the year and it can be an indicator to predict the bloom magnitude. Finally, the relative roles of external nutrient sources have been evaluated, and benthic fluxes might play a significant role in compensating 54.6% of new nitrogen for new production consumption.     

Preconditioned Optimizing Utility for Large-dimensional analyses (POpULar)

I present the derivation of the Preconditioned Optimizing Utility for Large-dimensional analyses (POpULar), which is developed for adopting a non-diagonal background error covariance matrix in nonlinear variational analyses (i.e., analyses employing a non-quadratic cost function). POpULar is based on the idea of a linear preconditioned conjugate gradient method widely adopted in ocean data assimilation systems. POpULar uses the background error covariance matrix as a preconditioner without any decomposition of the matrix. This preconditioning accelerates the convergence. Moreover, the inverse of the matrix is not required. POpULar therefore allows us easily to handle the correlations among deviations of control variables (i.e., the variables which will be analyzed) from their background in nonlinear problems. In order to demonstrate the usefulness of POpULar, we illustrate two effects which are often neglected in studies of ocean data assimilation before. One is the effect of correlations among the deviations of control variables in an adjoint analysis. The other is the nonlinear effect of sea surface dynamic height calculation required when sea surface height observation is employed in a three-dimensional ocean analysis. As the results, these effects are not so small to neglect.     

Spatial and Temporal Variations of Sound Speed at the PN Section

Gridded sound speed data were calculated using Del Grosso's formulation from the temperature and salinity data at the PN section in the East China Sea covering 92 cruises between February 1978 and October 2000. The vertical gradients of sound speed are mainly related to the seasonal variations, and the strong horizontal gradients are mainly related to the Kuroshio and the upwelling. The standard deviations show that great variations of sound speed exist in the upper layer and in the slope zone. Empirical orthogonal function analysis shows that contributions of surface heating and the Kuroshio to sound speed variance are almost equivalent. This revised version was published online in July 2006 with corrections to the Cover Date.     

水下拖曳系统运动姿态仿真研究

采用凝集参数法建立了水下拖曳系统的三维离散模型,该模型由一系列的质量点和不计重量的弹簧组成.采用数学模型编程对NCEL浮球实验和四个典型拖曳系统进行了仿真计算.计算结果表明此数学模型具有一定的理论意义和工程实用价值.