Dependence of near‐surface similarity scaling on the anisotropy of atmospheric turbulence

Abstract

Turbulence data from the CASES‐99 field experiment, over comparatively horizontally homogeneous and flat terrain, are separated based on the anisotropy of the Reynolds stress tensor (into isotropic, two‐component axisymmetric and one‐component turbulence) and flux‐variance similarity scaling relations are tested. Results illustrate that different states of anisotropy correspond to different similarity relations, especially under unstable stratification. Experimental data with close to isotropic turbulence match similarity relationships well. On the other hand, very anisotropic turbulence deviates significantly from the traditional scaling relations. We examine in detail the characteristics of these states of anisotropy, identify conditions in which they occur and connect them with different governing parameters. The governing parameters of turbulence anisotropy are shown to be different for stable and unstable stratification, but are able to delineate clearly the conditions in which each of the anisotropy states occurs.

Scaling, Anisotropy, and Complexity in Near‐Surface Atmospheric Turbulence

“…This scatter also persists despite the advanced postprocessing techniques and progressively more restrictive quality criteria imposed on the data. In an effort to overcome these challenges, Stiperski and Calaf () employed a novel approach by examining traditional similarity scaling relations over flat and horizontally homogeneous terrain based on clustering the data according to anisotropy. Results of this work illustrated a strong dependence between the quality of the scaling fit and the characteristic topology of the turbulent flow, showing that the similarity scaling significantly improves when the turbulent flow is a priori classified according to the anisotropy type.…”

“…The data set that conforms to the flat and horizontally homogeneous terrain the best is CASES‐99. Already studied in Stiperski and Calaf (), it forms the basis of the current analysis. The data consist of a month of measurements from a 60‐m tower with 7 levels of sonic anemometers.…”

“…On the other hand, one‐component turbulence strongly departs from common scaling curves. These results, together with the possibility of predicting the anisotropy type based on larger‐scale variables as shown in Stiperski and Calaf (), promised to be a powerful tool to improve similarity scaling relations.…”

“…In this work, and based on the earlier approach first introduced in Stiperski and Calaf (), we present a new interpretation of the a priori mismatch of near‐surface data in complex terrain and traditional scaling relations based on the anisotropy of the turbulence stress tensor. The results show that similar to flat and horizontally homogeneous terrain, separating the complex terrain data according to anisotropy significantly improves scaling, offering a pathway toward a unified theory of turbulence.…”

Exchange Processes in the Atmospheric Boundary Layer Over Mountainous Terrain

“…While methods to deal with non-stationarity have been in use for some time now [77], turbulence anisotropy over mountainous terrain is a scarcely explored issue that deserves further investigation [78,79]. A new metric to characterize turbulence anisotropy [80] has recently been used to demonstrate that different states of anisotropy correspond to different similarity relations, especially for horizontal variances, and to confirm that separating the experimental data according to anisotropy significantly improves the match to MOST scaling laws. Since anisotropy in complex terrain may be related to terrain features [81], systematic anisotropy analysis could help identify turbulence properties that hold generally for any complex terrain site and that can be used to generalize scaling laws.…”