intermittent turbulence
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Abstract Intermittent transitions between turbulent and non-turbulent states are ubiquitous in the stable atmospheric surface layer (ASL). Data from two field experiments in Utqiagvik, Alaska, and from direct numerical simulations are used to probe these state transitions so as to (i) identify statistical metrics for the detection of intermittency, (ii) probe the physical origin of turbulent bursts, and (iii) quantify intermittency effects on overall fluxes and their representation in closure models. The analyses reveal three turbulence regimes, two of which correspond to weakly turbulent periods accompanied by intermittent behavior (regime 1: intermittent, regime 2: transitional), while the third is associated with a fully turbulent flow. Based on time series of the turbulence kinetic energy (TKE), two non-dimensional parameters are proposed to diagnostically categorize the ASL state into these regimes; the first characterizes the weakest turbulence state, while the second describes the range of turbulence variability. The origins of intermittent turbulence activity are then investigated based on the TKE budget over the identified bursts. While the quantitative results depend on the height, the analyses indicate that these bursts are predominantly advected by the mean flow, produced locally by mechanical shear, or lofted from lower levels by turbulent ejections. Finally, a new flux model is proposed using the vertical velocity variance in combination with different mixing length scales. The model provides improved representation (correlation coefficients with observations of 0.61 for momentum and 0.94 for sensible heat) compared to Monin–Obukhov similarity (correlation coefficients of 0.0047 for momentum and 0.49 for sensible heat), thus opening new pathways for improved parametrizations in coarse atmospheric models.


Atmosphere ◽  
2021 ◽  
Vol 12 (8) ◽  
pp. 1043
Author(s):  
Raoni A. S. Santana ◽  
Cléo Q. Dias-Júnior ◽  
Roseilson S. do Vale ◽  
Júlio Tóta ◽  
Rodrigo da da Silva ◽  
...  

The goal of this work is to compare the main air turbulence characteristics of two common areas in the Amazonian landscape: a dense forest (rough surface) and a water surface (smooth surface). Using wind components data collected at high frequency by sonic anemometers located just above these surfaces, turbulence intensity and power spectra, temporal and length scales of the eddies, as well as the main terms of the TKE budget (TKE = turbulent kinetic energy) were evaluated for each surface type. The results showed that in general, the air turbulence intensity above the forest was higher than above the lake during the daytime, due to the high efficiency of the forest in absorbing the momentum of the turbulent flow. During the nighttime, the situation was reversed, with greater air turbulence intensity above the lake, except in some periods in which intermittent turbulence bursts occured above the forest.


2021 ◽  
Author(s):  
Johannes Schwenkel ◽  
Björn Maronga

<p>Apart from hazards associated with deep fog, its presence significantly alters the properties of the nocturnal boundary layer (NBL). <br>The NBL is typically characterized by a stable stratification resulting in weak or sometimes intermittent turbulence. <br>In contrast, the NBL during deep fog is often convective, as for the longwave radiation optical thick fog layer, the net radiative loss takes place at the fog top, destabilizing the atmosphere from above.<br>Therefore, processes as modified longwave cooling, shortwave absorption, turbulent mixing, reduction of the total water content through droplet settling or modified dewfall, is able to induce differences between the stable NBL (SNBL) and foggy NBL. <br>Albeit after sunrise the SNBL is quickly transformed into a convective boundary layer (CBL), properties of the NBL are transferred into the day and affect the CBL. <br>Even though fundamental and applied research have significantly improved fog forecasts and contributed to a broader and deeper understanding at the process-level in the last decades, common numerical weather prediction (NWP) models still miss a significant amount of fog events.<br>A number of complex small-scale processes (such as turbulent mixing, land-atmosphere interactions, aerosol and cloud microphysics and radiation) interacting on different scales have to be correctly resolved or parameterized.<br>Likewise, the prerequisite formation conditions must be presented precisely as they are highly sensitive to slight changes in temperature, humidity or soil moisture, entailing that even small biases in the forcing data could lead to an incorrect representation of subtle supersaturations and might result in failing to predict fog.</p><p>Thus, we will present in this talk results of idealized large eddy simulations pairs (with and without the possibility to form fog) covering the diurnal cycle based on a typical fog event observed in Cabauw considering radiative conditions between February and April. <br>As we performed several parameter studies we will demonstrate, that the CBL in cases without fog is warmer and obtain higher inversion heights than in simulations with fog during night.<br>Further, we show that this temperature deviations are mainly driven by an stronger integrated  longwave cooling during night in the foggy cases.<br>Moreover, we identified the liquid water path as a crucial parameter determining the strength of the fog impact on CBL development. </p>


2021 ◽  
Author(s):  
Vyacheslav Boyko ◽  
Nikki Vercauteren

<p>We present results on the modeling of intermittent turbulence in the nocturnal boundary<br>layer using a data-driven approach. In high stratification and weak wind conditions, the<br>bulk shear can be too weak to sustain continuous turbulence and the sporadic submesoscale<br>motions trigger the turbulence production.<br>The main idea is to extend a TKE-based, 1.5 order turbulence closure model by in-<br>troducing a stochastic differential equation (SDE) for the nondimensional correction of the<br>mixing length. Such a nonstationary SDE model is built upon the traditional surface-layer<br>scaling functions, which model the effect of the static stability on the surface-layer profiles<br>using scaling with the Richardson (Ri) number . The nonstationary parameters of the SDE<br>equation are determined from data with a model-based clustering approach. Furthermore, it<br>is found that parameters scale with the local gradient Ri number, resulting in a closed-form<br>nonstationary stability correction depending only on this local gradient Ri number. Benefi-<br>cial is the interpretation of the noise term of the SDE. This term is interpreted as an effect<br>of the submesoscale motions on turbulent mixing. Furthermore, the SDE model provides<br>a conceptual view on intermittent turbulence, whereby in the noise-free limit, the steady-<br>state solution converges to the traditional functional scaling. Per construction, the SDE<br>is readily incorporated in a turbulence closure by modifying the definition of the stability<br>correction. Details will be provided.<br>We will present a numerical analysis of such a hybrid model for quasi-steady-state so-<br>lutions with different model settings. Furthermore, we investigate the regime transitions<br>between weakly and strongly stable flows under intermittent mixing based on the temper-<br>ature inversion characteristics.</p>


2021 ◽  
Vol 2 (1) ◽  
Author(s):  
Evgeny A. Podolskiy ◽  
Naoya Kanna ◽  
Shin Sugiyama

AbstractIn the Arctic, subglacial discharge plumes have been recently recognised as a key driver of fjord-scale circulation. However, owing to the danger that accompanies prolonged observations at plumes, no time-series data are available. Here, we present results showing the chaotic and irregular dynamics of a plume revealed by continuous subsurface monitoring directly on the calving front of a Greenlandic glacier. We found intense fluctuations in the current and scalars (temperature and salinity), recognised shallow and deep tidal modulation and anomalies due to co-seismic drainage of an ice-dammed lake via the plume, and observed rapid and marked changes in stratification. Our analysis uncovers energy cascade intermittency with coherent structures, corresponding to upwelling pulses of warm water. Prior to our research, in situ evidence of time-variable plume dynamics was absent and limited to snapshots, therefore, our study and approach will enable researchers to transition from an episodic view of a plume to a continuously updated image.


2021 ◽  
Author(s):  
Vyacheslav Boyko ◽  
Sebastian Krumscheid ◽  
Nikki Vercauteren

<p>We present results on the modelling of intermittent turbulence in the nocturnal boundary layer using a data-driven approach. In conditions of high stratification and weak wind, the bulk shear can be too weak to sustain continuous turbulence, and the sporadic submeso motions play an important role for the turbulence production. We show a way to stochastically parametrise the effect of the unresolved submeso scales and include it into a 1.5-order turbulence closure scheme. This is achieved by introducing a stochastic equation, which describes the evolution of the non-dimensional flux-gradient stability correction for momentum ($\phi_m$). The unperturbed equilibrium solution of the equation follows the functional form of the universal similarity function. The stochastic perturbations reflect the instantaneous excursions from its equilibrium state, and the distribution of values covers the scatter found in observations at high stability.</p><p>The non-stationary parameters of this equations are estimated from a time-series data of the FLOSS2 experiment using a model-based clustering approach. The clustering analysis of the parameters shows a scaling relationship with the local gradient Ri number, leading to a suggested closed-form model for the stochastic flux-gradient stability correction. The spatial correlation in height of the perturbations is included in the model as well. The resulting equation captures the transition of the stability correction across and beyond the critical Ri up to a value of 10. The out-of-sample prediction shows a valid transient dynamics into and within the regime of strongly-stable stratification.</p>


2021 ◽  
Author(s):  
Manuela Lehner ◽  
Mathias W. Rotach

<p>The stable boundary layer is typically characterized by weak and sometimes intermittent turbulence, particularly under very stable conditions. In mountain valleys, nocturnal temperature inversions and cold-air pools form frequently under synoptically undisturbed and clear-sky conditions, which will dampen turbulence. On the other hand, thermally driven slope and valley winds form under the same conditions, which interact with each other and are both characterized by jet-like wind profiles, thus resulting in both horizontal and vertical wind shear, which creates a persistent source for turbulence production. Data will be presented from six flux towers in the Austrian Inn Valley, which are part of the i-Box measurement platform, designed to study near-surface turbulence in complex, mountainous terrain. The six sites are located within an approximately 6.5-km long section of the 2-3-km wide valley approximately 20 km east of Innsbruck. The data are analyzed to characterize the strength and intermittency of turbulence kinetic energy and turbulent fluxes across the valley and to determine whether the persistent wind shear associated with thermally driven flows is sufficient to generate continuous turbulence.</p>


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