基于观测的南海越南沿岸次表层涡旋

In this study, subsurface eddies near the Vietnam coast of the South China Sea were observed with in situ observations, including Argo, CTD, XBT and some processed and quality controlled data. Based on temperature profiles from four Argo floats near the coast of Vietnam, a subsurface warm eddy was identified in spring and summer. The multi-year Argo and Global Temperature and Salinity Profile Programme(GTSPP) data were merged on a seasonal basis based on the data interpolating variational analysis(DIVA) method to reconstruct the three-dimensional temperature structure. There is a warm eddy in the central subsurface at 12.5°N, 111°E below300 m depth in spring, which does not exist in autumn and is weak in winter and summer. From CSIRO Atlas of Regional Seas(CARS) and Generalized Digital Environment Model(GDEM) reanalysis data, this subsurface warm eddy is also verified in spring.     

基于领海基线外推领海、毗连区和专属经济区的2种算法及其比较

由于领海基线一般由折线组成且地球表面为球面,基于领海基线外推领海、毗连区和专属经济区的实际计算存在困难。文章基于交圆法设计最短距离法和椭圆法2种算法并对其优劣性进行比较,研究表明:外推12nmile领海和24nmile毗连区的界线基本与外推的领海基线平行,外推200nmile专属经济区的界线形状变化较大;最短距离法精度高但计算量较大,椭圆法所需计算时间短但精度较低且没有消除误差。     

Dominant modes of winter SST variability in the Japan Sea and their influences on atmosphere

Journal of Oceanography - The high-resolution spatial and long-term temporal variabilities of winter sea surface temperature (SST) in the Japan Sea and their influences on the atmosphere...     

基于遗传聚类算法的印度洋环境特征区划

利用全球海洋 Agro 观测计划提供的温、盐浮标资料,开展了印度洋海域水下环境特征提取与区划分析.在垂直方向运用Akima 方法对浮标剖面进行插值,提取一组表征跃层、声速场的特征指标,并针对常规模糊 C 均值聚类算法中初始聚类数难以客观选取和聚类结果易陷入局部最优等问题,利用遗传算法的全局搜索能力对聚类算法作了改进.通过在遗传进化过程中引入动态变化的聚类中心解决了聚类数难以客观确定的问题,并在该算法的生存策略中引入 Boltzmann 选择机制,提高算法的收敛速度.在对印度洋海域温、盐跃层、声速分布及层结稳定度分析的基础上,利用改进的遗传聚类方法对印度洋海域水下环境特征进行聚类区划,得到一个基本的特征分类构型,结合各类构型的典型特征,分析了对水下潜器活动、声纳探测和水声通信等的影响.