Observations of Flow and Turbulence in the Nocturnal Boundary Layer over a Slope

Monti, Paolo; Fernando, Harindra J. S.; Princevac, Marko; Chan, Wang; Kowalewski, T. A.; Pardyjak, Eric R.

doi:10.1175/1520-0469(2002)059<2513:oofati>2.0.co;2

Cited by 202 publications

(185 citation statements)

References 56 publications

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“…This formula corresponds that flux Richardson number approaches 0.2 at the Ri → ∞ limit. Strang and Fernando (2001) and Monti et al (2002) reported that Rf(Ri) does not monotonically increase but has a peak, whose value is Rf ≈ 0.4 at Ri ≈ 1. A common feature seen in the previous studies is that flux Richardson number in stable stratification has an upper limit less than unity, though its value still remains uncertain.…”

Section: Introductionmentioning

confidence: 99%

Flux Richardson Number and Turbulent Prandtl Number in a Developing Stable Boundary Layer

Kitamura

Hori²,

Yagi³

2013

Journal of the Meteorological Society of Japan

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Wind tunnel experiments and large-eddy simulations for stable stratification are performed to specify flux Richardson number Rf and turbulent Prandtl number Pr as a function of gradient Richardson number Ri. We attempted to avoid self-correlation by using independent samples for the variables commonly contained in these nondimensional numbers and confirmed the dependence of Rf and Pr on Ri for 10 −3 < Ri < 5. We found that Rf could exceed unity in a stable boundary layer under a developing stage, while the assumption of local energy balance violates for Rf > 1, which corresponds to negative production of turbulent kinetic energy. Nevertheless, the analysis of the TKE budget shows that the third-order term in the prognostic equation of TKE, which plays a role in the TKE transfer, can contribute to increase TKE despite negative TKE production. Therefore, TKE cannot be determined locally and the effects of TKE transfer must be taken into account in the region satisfying Rf > 1.

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Section: Introductionmentioning

confidence: 99%

Flux Richardson Number and Turbulent Prandtl Number in a Developing Stable Boundary Layer

Kitamura

Hori²,

Yagi³

2013

Journal of the Meteorological Society of Japan

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“…Based on numerical studies, laboratory experiments and theoretical considerations, the submeso modes in stratified flow are viewed as a combination of gravity waves and horizontal modes, sometimes referred to as pancake vortices (see, for example, Riley and Lelong 2000;Waite and Bartello 2004;Meunier et al 2005, and references therein). Interaction between the gravity waves and two-dimensional modes are explored by Godoy-Diana et al (2006), and interaction between turbulence, submeso motions and drainage flows was demonstrated by Monti et al (2002). Horizontal modes have been difficult to identify from atmospheric data, perhaps due to inadequacy of the datasets.…”

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confidence: 99%

Characteristics of Submeso Winds in the Stable Boundary Layer

Mahrt

2008

Boundary-Layer Meteorol

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The characteristics of submeso motions in the stable boundary layer are examined using observations from networks of sonic anemometers with network sizes ranging from a few hundred metres to 100 km. This study examines variations on time scales between 1 min and 1 h. The analysis focuses on the behaviour of the spectra of the horizontal kinetic energy, the ratios of the three velocity variances, their kurtosis, the dependence of horizontal variability on time scale, and the inter-relationship between vertical vorticity, horizontal divergence and deformation. Motions on larger time and space scales in the stable boundary layer are found to be nearly two-dimensional horizontal modes although the ratio of the vorticity to the divergence is generally on the order of one and independent of scale. One exception is a small network where stronger horizontal divergence is forced by a decrease in surface roughness. The horizontal variability, averaged over 1 h, appears to be strongly influenced by surface heterogeneity and increases with wind speed. In contrast, the time dependence of the horizontal structure on time scales less than one hour tends to be independent of wind speed for the present datasets. The spectra of the horizontal kinetic energy and the ratio of the crosswind velocity variance to the along-wind variance vary substantially between networks. This study was unable to isolate the cause of such differences. As a result, the basic behaviour of the submeso motions in the stable boundary layer cannot be generalized into a universal theory, at least not from existing data.

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“…On the other hand, drainage flows are thermal circulations generated by the differential cooling between surface air masses in sloped or complex terrain under low synoptic forcing, when local conditions gain importance (Whiteman, 2000;Monti et al, 2002;Soler et al, 2002Soler et al, , 2014Adachi et al, 2004). They are also typical SBL motions and manifest as sudden changes in wind direction, a temperature drop (due to the cooler current) or increasing winds at certain heights, among other effects (Yagüe et al, 2006;Viana et al, 2010;Udina et al, 2013).…”

Section: Introductionmentioning

confidence: 99%

“…Mountain breezes or katabatic winds (Whiteman, 2000) have been studied in many zones of the world (e.g. the Alps, Rotach et al, 2004;Nadeau et al, 2013, or Salt Lake Valley, Doran et al, 2002Monti et al, 2002). However, shallow drainage flows (SDFs) or density currents have been less studied (Mahrt et al, 2001;Soler et al, 2002;Udina et al, 2013;Oldroyd et al, 2014;Lehner et al, 2015a), in part because of their smaller scale, that often makes them more difficult to detect.…”

Section: Introductionmentioning

confidence: 99%

Interactions among drainage flows, gravity waves and turbulence: a BLLAST case study

et al. 2015

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Abstract. The interactions among several stable-boundarylayer (SBL) processes occurring just after the evening transition of 2 July 2011 have been analysed using data from instruments deployed over the area of Lannemezan (France) during the Boundary Layer Late Afternoon and Sunset Turbulence (BLLAST) field campaign. The near-calm situation of the afternoon was followed by the formation of local shallow drainage flows (SDFs) of less than 10 m depth at different locations. The SDF stage ended with the arrival of a stronger wind over a deeper layer more associated with the mountain-plain circulation, which caused mixing and destruction of the SDFs. Several gravity-wave-related oscillations were also observed on different time series. Wavelet analyses and wave parameters were calculated from high resolution and accurate surface pressure data of an array of microbarometers. These waves propagated relatively long distances within the SBL. The effects of these phenomena on turbulent parameters (friction velocity and kinematic heat flux) have been studied through multi-resolution flux decomposition methods performed on high frequency data from sonic anemometers deployed at different heights and locations. With this method, we were able to detect the different time-scales involved in each turbulent parameter and separate them from wave contributions, which becomes very important when choosing averaging-windows for surface flux computations using eddy covariance methods. The extensive instrumentation allowed us to highlight in detail the peculiarities of the surface turbulent parameters in the SBL, where several of the noted processes were interacting and producing important variations in turbulence with height and between sites along the sloping terrain.

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Observations of Flow and Turbulence in the Nocturnal Boundary Layer over a Slope

Cited by 202 publications

References 56 publications

Flux Richardson Number and Turbulent Prandtl Number in a Developing Stable Boundary Layer

Flux Richardson Number and Turbulent Prandtl Number in a Developing Stable Boundary Layer

Characteristics of Submeso Winds in the Stable Boundary Layer

Interactions among drainage flows, gravity waves and turbulence: a BLLAST case study

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