EA模型在海洋的速度横向时空互相关函数中的应用

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中文摘要：椭圆近似(EA)模型是从单个点的时间波动数据中推断空间波动数据的重要方法，它已在室内实验剪切场的纵向时空互相关函数C(r，τ)得到验证并被广泛应用。在这里，我们研究了EA模型在海洋流场中的有效性，并介绍了其在横向时空互相关函数G(r，τ)中的应用。结果表明，EA模型在海洋的速度场中是有效的，即G(r，τ)具有G(rE，0)的尺度形式，其中rE=[(r-Uτ)2+(Vτ)2]1/2，U和V是与内波垂直相速度相关的两个特征速度。基于EA模型，我们可以获得海洋的垂直波数能谱，并估计海洋的泰勒微尺度和雷诺数。

外文标题：Application of the EA model to the velocity transversal space-time cross-correlation functions measured in the ocean

外文摘要：The elliptical approximation(EA)model is an important method for deducing spatial fluctuations from the temporal fluc-tuations at a single point.It has been extensively examined and used in shear fields of desktop experiments for the longitudinal space-time cross-correlation functions C(r,τ).Here we examine the EA model in the flow field of the ocean and present its application to the transversal space-time cross-correlation functions G(r,τ).The result shows that EA model is valid for the velocity field of the ocean,that is,G(r,τ)has the scaling form of G(rE,0)with rE=[(r-Uτ)2+(Vτ)2]1/2,where U and V are the velocities associated with the vertical phase velocities of the internal waves.Based on the EA model,we can obtain the vertical wavenumber energy spectrum of the ocean and estimate the transversal Taylor micro-scale and Reynolds number.

外文关键词：

Elliptical approximation modelSpatial fluctuationsTemporal fluctuationsSpace-time cross-correlation functionsTaylor micro-scale

作者：

梁长荣、尚晓东、陈桂英、何晓舟、童彭尔

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作者单位：

State Key Laboratory of Tropical Oceanography,South China Sea Institute of Oceanology,Chinese Academy of Sciences,Guangzhou 510301,China

School of Mechanical Engineering and Automation,Harbin Institute of Technology(Shenzhen),Shenzhen 518055,China

Department of Physics,Hong Kong University of Science and Technology Hong Kong,China

关键词：

Elliptical approximation model Spatial fluctuations Temporal fluctuations Space-time cross-correlation functions Taylor micro-scale

基金：

National Key Research and Development Program of Chinainnovation project of Innovative Academy of Marine Information Technology,Chinese Academy of SciencesNational Natural Science Foundation of ChinaNational Natural Science Foundation of ChinaNational Natural Science Foundation of ChinaNational Natural Science Foundation of ChinaScience.Technology and Innovation Commission of Shenzhen MunicipalityScience and Technology Program of Guangzhou

项目编号：

2021YFC3101300CXBS20210141876022123722164163097041806033GXWD20220818113020001202102020707

出版年：

2024

DOI：

10.1007/s10409-023-23381-x

力学学报(英文版)

CSTPCD

影响因子：0.363

ISSN：0567-7718

年,卷(期)：2024.40(3)