南海东北部深层次的细结构观测与湍流混合研究*

doi:10.11978/2024201

热带海洋学报 ›› 2025, Vol. 44 ›› Issue (5): 22-30.doi: 10.11978/2024201CSTR: 32234.14.2024201

南海东北部深层次的细结构观测与湍流混合研究^*

朱小宇(), 杨华(), 毛蓓蓓, 郑雨轩

中国海洋大学电子工程系, 山东青岛 266000

收稿日期:2024-10-23 修回日期:2025-02-10 出版日期:2025-09-10 发布日期:2025-10-14
通讯作者: 杨华
作者简介:
朱小宇(2000—), 女, 山东省烟台市人, 硕士研究生, 从事湍流理论研究。email: zxy3319@stu.ouc.edu.cn
*本研究的数据及样品采集得到国家自然科学基金委员会共享航次计划项目(42149905)的资助, 该航次(NORC2022-05)由“东方红3”号科考船实施, 在此一并致谢
基金资助:
国家自然科学基金项目(61871354); 国家自然科学基金项目(6172780176)

Observations of fine-scale structure and study of turbulent mixing in the deep northeastern South China Sea^*

ZHU Xiaoyu(), YANG Hua(), MAO Beibei, ZHENG Yuxuan

Department of Electronic Engineering, Ocean University of China, Qingdao 266000, China

Received:2024-10-23 Revised:2025-02-10 Online:2025-09-10 Published:2025-10-14
Contact: YANG Hua
Supported by:
National Natural Science Foundation of China(61871354); National Natural Science Foundation of China(6172780176)

摘要/Abstract

摘要：

基于2022年南海H2站位(17°N, 116°E)直接观测的4000m湍流数据, 对南海东北部的湍流混合参数(包括湍动能耗散率、混合率、Thorpe尺度等)的垂向分布进行综合化研究。混合率与Thorpe尺度分别从湍流耗散和水体翻转角度表征湍流混合强度, 二者在1500~4000m深度每500m的平均参数波动一致, 呈现大-小-大-小的4层分布(反z形), 具有高相关性。文章采用MacKinnon-Gregg参数化模型对此站位进行了良好估算, 发现估算的混合率和Thorpe尺度间整体相关系数也高于0.7。基于二者的相关系数分布, 分别挑选混合率和Thorpe尺度强相关(1755m)和弱相关(3785m)区域进行小波分析, 发现强相关区域的能量多尺度级串更加剧烈, 证明参数间的相关系数确可用于识别真实的湍流混合, 有效去除仪器和海洋环境造成的虚假误差。

关键词: 南海湍流混合, 细结构观测, Thorpe尺度, 湍耗散率, 混合率, MG模型

Abstract:

Based on direct turbulence measurements at 4000 m depth from Station H2 (17°N, 116°E) in the South China Sea in 2022, this study comprehensively investigates the vertical distribution and correlation of turbulent mixing parameters — including turbulent kinetic energy dissipation rate, mixing rate, Thorpe scale — in the northeastern South China Sea. The mixing rate and Thorpe scale characterize the turbulent mixing intensity from the perspectives of turbulent dissipation and water mass overturning, respectively. Both parameters exhibit consistent average fluctuations every 500 m in the 1500~4000 m depth range, diaplaying a four-layer “big-small-big-small” distribution (inverse z-shaped) with high correlation. The MacKinnon-Gregg parameterization model was applied to this station, yielding reliable estimates, with an overall correlation coefficient exceeding 0.7 between the estimated mixing rate and Thorpe scale. Based on their correlation coefficient distribution, we select depths with strong (1755 m) and weak (3785 m) correlations between the mixing rate and Thorpe scale for wavelet analysis. The results reveal more intense multi-scale energy cascade in regions of strong correlation, demonstrating that the correlation coefficient between parameters can effectively identify genuine turbulent mixing and filter out false errors caused by instrument noise or environmental factors. By combining fine-structure direct observations with parameterization methods, this study provides valuable insights into turbulence observation, the vertical distribution of mixing parameters and the evolution mechanisms of turbulent mixing in the middle and deep layers of the South China Sea.

Key words: turbulence mixing in the South China Sea, fine-scale observations, Thorpe scale, turbulent dissipation rate, mixing rate, MacKinnon-Gregg model

中图分类号:

P731.26

朱小宇, 杨华, 毛蓓蓓, 郑雨轩. 南海东北部深层次的细结构观测与湍流混合研究^*[J]. 热带海洋学报, 2025, 44(5): 22-30.

ZHU Xiaoyu, YANG Hua, MAO Beibei, ZHENG Yuxuan. Observations of fine-scale structure and study of turbulent mixing in the deep northeastern South China Sea^*[J]. Journal of Tropical Oceanography, 2025, 44(5): 22-30.

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名称	性能参数
采样频率/Hz	1000
响应时间/ms	1
空间分辨率/mm	0.35
剪切流灵敏度/(V·m·s²·kg^-1)	2.68×10^-2
耗散率测量范围/(W·kg^-1)	1×10^-11~1×10^-4

南海东北部深层次的细结构观测与湍流混合研究^*

Observations of fine-scale structure and study of turbulent mixing in the deep northeastern South China Sea^*

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南海东北部深层次的细结构观测与湍流混合研究*

Observations of fine-scale structure and study of turbulent mixing in the deep northeastern South China Sea*

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南海东北部深层次的细结构观测与湍流混合研究^*

Observations of fine-scale structure and study of turbulent mixing in the deep northeastern South China Sea^*