吕宋海峡水体通量时空变化特征的数值模拟研究-海洋预报

吕宋海峡水体通量时空变化特征的数值模拟研究

单位：1. 国家海洋环境预报中心, 北京 100081;
2. 自然资源部海洋灾害预报技术重点实验室, 北京 100081

分类号：P731.2

出版年·卷·期（页码）：2020·37·第四期（1-14）

摘要：

利用区域海洋数值模式（ROMS）建立了南中国海三维海洋环流数值模型。基于2006—2018年逐日平均的数值模拟结果，分析了吕宋海峡断面（120.75°E）的纬向流及通过断面的水体通量的时空变化规律，并采用集合经验模态分解法（EEMD）分别探讨了整层和表、中、底层水体通量的时间变化特征。结果表明：断面处纬向流呈现明显的多核结构，流态分布随季节变化较小，而流速变化受季节影响较大；断面水体通量存在明显的季节、月际变化；其垂向变化在年平均、春季、秋季和冬季时都呈现“三明治”结构，分界点分别在540 m和1 720 m左右，受黑潮分支强度的影响，在夏半年（5—9月）呈现“四层”结构，上表层厚度为45~80 m且存在月变化，5月为发展期，6—8月为成熟期，9月为消亡期；表层水体通量的时间变化对整层的变化影响最大，黑潮入侵的强度是导致整层及表层水体通量变化的主要因素。

A three-dimensional numerical ocean circulation model for the South China Sea is established using the Regional Ocean Modelling System (ROMS). Based on daily-mean model output from 2006 to 2018, we analyze the temporal and spatial variation of the zonal flow and the sea water volume transport (SWVT) through the section of Luzon Strait (120.75°E). Meanwhile, the temporal variation characteristics of SWVT in the whole layer, surface layer, middle layer and bottom layer are studied using the ensemble empirical mode decomposition (EEMD). The results show that the zonal flow through the Luzon Strait shows a multi-core structure with minor seasonal variation. However, the speed of the zonal flow is significantly affected by the seasonal cycle, and the SWVT reveals significant seasonal and monthly variation. The vertical distribution of SWVT shows a sandwich structure in its annual mean as well as in the spring, autumn and winter season with the separation lines at depths of about 540 m and 1720 m. Nevertheless, it shows a four-layer structure in the summer time (May to September) influenced by the intensity of the Kuroshio branch. The depth of the upper layer is about 45~80 m with monthly variation, and May, June to August and September are the development, mature and decay phase of the four-layer structure, respectively. The temporal variation of the SWVT in the surface layer has the greatest influence on the variation of the whole layer. The intensity of the Kuroshio intrusion is the main factor that causes the variation of the SWVT of the whole layer and surface layer.

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