Global Intermittency and Collapsing Turbulence in the Stratified Planetary Boundary Layer

Direct numerical simulation of the turbulent Ekman layer over a smooth wall is used to investigate bulk properties of a planetary boundary layer under stable stratification. Our simplified configuration depends on two non-dimensional parameters: a Richardson number characterizing the stratification and a Reynolds number characterizing the turbulence scale separation. This simplified configuration is sufficient to reproduce global intermittency, a turbulence collapse, and the decoupling of the surface from the outer region of the boundary layer. Global intermittency appears even in the absence of local perturbations at the surface; the only requirement is that large-scale structures several times wider than the boundary-layer height have enough space to develop. Analysis of the mean velocity, turbulence kinetic energy, and external intermittency is used to investigate the large-scale structures and corresponding differences between stably stratified Ekman flow and channel flow. Both configurations show a similar transition to the turbulence collapse, overshoot of turbulence kinetic energy, and spectral properties. Differences in the outer region resulting from the rotation of the system lead, however, to the generation of enstrophy in the non-turbulent patches of the Ekman flow. The coefficient of the stability correction function from Monin-Obukhov similarity theory is estimated as (Formula presented.) in agreement with atmospheric observations, theoretical considerations, and results from stably stratified channel flows. Our results demonstrate the applicability of this set-up to atmospheric problems despite the intermediate Reynolds number achieved in our simulations. © 2014 The Author(s)

Scale Dependence of Atmosphere–Surface Coupling Through Similarity Theory

Monin-Obukhov similarity theory (MOST) applies for homogeneous and stationary conditions but is used in ever more complex and heterogeneous configurations. Here, it is used to estimate the surface friction velocity u from the wind speed and temperature in the atmospheric surface layer (ASL). Filters of varying scale and direction are applied to wind speed and temperature in the ASL before MOST is used to estimate u. This procedure unveils the scale dependence of coupling between the ASL and the surface. Direct numerical simulation of turbulent Ekman flow above a smooth surface is used to explicitly resolve the near-wall dynamics. It is found that the viscous sub-layer may cease to exist, even in continuously turbulent neutral conditions, while the ASL covers more than one decade of variation in height. An underestimation in the variance of u estimated through MOST versus its actual variance is quantified as a function of height, averaging time, and length scale. For large filter scales, the variance exhibits a purely statistical convergencethere is no signature of long-term memory beyond the scale of coherent turbulent motion. Joint convergence of u estimated by MOST and the actual u is obtained for filter scales beyond several thousand wall units, and only for data filtered along both horizontal dimensions; the three-dimensional structure of the turbulence elements limits the convergence of data filtered along any of the single dimensions: time, the streamwise or spanwise direction. In stably stratified conditions, MOST is found to have no or negative skill in locally estimating ASL properties from u and should therefore only be applied to filtered quantities

LES of Arctic mixed-phase Stratocumulus (ACLOUD RF13)

This data was created via three horizontally different resolved large-eddy simulations (35.0m, 10.0m, 3.5m) where the vertical resolution is below 5.0m within the atmospheric boundary layer and gradually increases to 20.0m at model top of about 850.0m. A modified version of WRF-LES 4.0.3 was applied to an atmospheric case based on observations of ACLOUD RF13 on June 5th, 2017. The simulations cover the period between 11 UTC and 17 UTC and are located at 81.93 °N, 10.95 °E

Analyses of external and global intermittency in the logarithmic layer of Ekman flow

Existence of non-turbulent flow patches in the vicinity of the wall of a turbulent flow is known as global intermittency. Global intermittency challenges the conventional statistics approach when describing turbulence in the inner layer and calls for the use of conditional statistics. We extend the vorticity-based conditioning of a flow to turbulent and non-turbulent sub-volumes by a high-pass filter operation. This modified method consistently detects non-turbulent flow patches in the outer and inner layers for stratifications ranging from the neutral limit to extreme stability, where the flow is close to a complete laminarization. When applying this conditioning method to direct numerical simulation data of stably stratified Ekman flow, we find the following. First, external intermittency has a strong effect on the logarithmic law for the mean velocity in Ekman flow under neutral stratification. If instead of the full field, only turbulent sub-volumes are considered, the data fit an idealized logarithmic velocity profile much better; in particular, a problematic dip in the von Kármán measure K in the surface layer is decreased by approximately 50 and our data only support the reduced range 0.41 ≤ K ≤ 0.43. Second, order-one changes in turbulent quantities under strong stratification can be explained by a modulation of the turbulent volume fraction rather than by a structural change of individual turbulence events; within the turbulent fraction of the flow, the character of individual turbulence events measured in terms of turbulence dissipation rate or variance of velocity fluctuations is similar to that under neutral stratification. © © 2016 Cambridge University Press

The role of noise in self-organized decision making by the true slime mold Physarum polycephalum

Self-organized mechanisms are frequently encountered in nature and known to achieve flexible, adaptive control and decision-making. Noise plays a crucial role in such systems: It can enable a self-organized system to reliably adapt to short-term changes in the environment while maintaining a generally stable behavior. This is fundamental in biological systems because they must strike a delicate balance between stable and flexible behavior. In the present paper we analyse the role of noise in the decision-making of the true slime mold Physarum polycephalum, an important model species for the investigation of computational abilities in simple organisms. We propose a simple biological experiment to investigate the reaction of P. polycephalum to time-variant risk factors and present a stochastic extension of an established mathematical model for P. polycephalum to analyze this experiment. It predicts that-due to the mechanism of stochastic resonance D noise can enable P. polycephalum to correctly assess time-variant risk factors, while the corresponding noise-free system fails to do so. Beyond the study of P. polycephalum we demonstrate that the influence of noise on self-organized decision-making is not tied to a specific organism. Rather it is a general property of the underlying process dynamics, which appears to be universal across a wide range of systems. Our study thus provides further evidence that stochastic resonance is a fundamental component of the decision-making in self-organized macroscopic and microscopic groups and organisms

Overlapping of Communication and Computation in nb3dfft for 3D Fast Fourier Transformations

For efficiency and accuracy of Direct Numerical Simulations(DNS) of turbulent flows pseudo-spectral methods can be employed,where the governing equations are solved partly in Fourier space. Theinhouse-developed 3d-FFT library nb3dfft is optimized to the specialneeds of pseudo-spectral DNS, particularly for the scientific code psOpen,used by the Institute for Combustion Technology at RWTH Aachen Uni-versity. In this paper we discuss the method of overlapping communica-tion and computation of multiple FFTs at the same time