Turbulence in convective boundary layers: a statistical investigation

by Venecia Chávez Medina
Doctoral thesis
Date of Examination:2023-12-15
Date of issue:2024-12-12
Advisor:Prof. Dr. Michael Wilczek
Referee:Prof. Dr. Michael Wilczek
Referee:Prof. Dr. Eberhard Bodenschatz
Persistent Address: http://dx.doi.org/10.53846/goediss-10957

 

 

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Abstract

English

A combination of vertical turbulent convection and shear-driven turbulence governs the convective boundary layers (CBLs), and the role of turbulence in CBL dynamics has yet to be fully understood. In this thesis, we aim to comprehensively understand the underlying dynamics of turbulence in convective boundary layers through a multifaceted approach consisting of a combination of statistical analysis, direct numerical simulations and in-situ measurements. In the first part, we investigate turbulence in convective boundary layers for varying atmospheric conditions by combining probability-density-function methods and direct numerical simulations. The evolution equations for the probability density functions of vertical velocity and buoyancy contain unclosed terms in the form of conditional averages. We estimate these terms from our direct-numerical-simulation data and discuss their physical interpretation. Furthermore, using the method of characteristics, we investigate how these unclosed terms jointly determine the average evolution of a fluid parcel in a convective boundary layer and how it relates to the evolution of the probability density functions of vertical velocity and buoyancy as a function of height. Our work establishes a connection between the turbulent dynamics of convective boundary layers and the resulting statistics. The second part of the thesis explores the relationship between wind velocity and virtual potential temperature in the atmospheric boundary layer during midday. We investigate this relationship using data from in-situ measurements recorded during the PaCE campaign. In this part, too, we complement our analysis with data from direct numerical simulations. We provide an overview of the campaign and the extensive data set collected by the CloudKite team with the Max Planck WinDarts, two airborne scientific instruments designed to measure atmospheric turbulence. Finally, we characterise the stability of the atmospheric boundary layer, detect traces of the diurnal cycle in the time series, and identify signatures of large-scale convective processes encoded in the wind velocity and virtual potential temperature cross-correlations.
Keywords: turbulencence
 
Statistik