北京大学学报（自然科学版）2025，Vol.61Issue(3)：465-477,13.DOI:10.13209/j.0479-8023.2025.014
基于无量纲化湍流方程组的风速-气压关联与湍流动能变化关系研究
Characterization of Wind-Pressure Coupling and Turbulent Kinetic Energy Change Based on Nondimentionalization of Turbulence Equations
摘要
Abstract
Observational data from the Atmospheric Boundary Layer and Atmospheric Environment Compre-hensive Experimental Station in Naiman,Inner Mongolia,from June to August 2019 were utilized.The turbulent statistical characteristics of pressure and wind speed were analyzed,and the variation relationship between wind-pressure coupling and turbulent kinetic energy was quantified.The results indicate that the pressure variance spectrum follows the overall-5/3 scaling law in the inertial subrange,exhibiting clear non-stationarity and dependence on stratification conditions.The relationship between normalized standard deviation of pressure and stability parameter exhibits a linear pattern based on the turbulent kinetic energy budget equation,while demonstrating an exponential pattern derived from the wind speed budget equation.The temporal derivative of the normalized standard deviation of pressure fluctuation and the wind-pressure covariance spectrum jointly reveal the relationship between wind-pressure coupling and turbulent kinetic energy changes.At sunrise,the wind-pressure coupling is strong,making a positive contribution to turbulent kinetic energy,which gradually weakens with the development of unstable atmospheric layers.After sunset,the wind-pressure coupling is reconstructed and gradually consumes turbulent kinetic energy.The analysis above underscores the significant role of pressure in turbulence kinetic energy,closely tied to atmospheric stratification conditions and essential for understanding atmospheric turbulence.关键词
气压脉动/风速-气压关联/归一化标准差/湍流动能Key words
pressure fluctuation/wind-pressure coupling/normalized standard deviation/turbulent kinetic energy引用本文复制引用
刘子涵,曹竹音,张宏昇,宋宇,康凌..基于无量纲化湍流方程组的风速-气压关联与湍流动能变化关系研究[J].北京大学学报（自然科学版）,2025,61(3):465-477,13.基金项目
北京市科技计划项目(Z241100009124014)、国家重点研发计划(2023YFC3706301)和国家自然科学基金(42175092)资助 （Z241100009124014）
