An Analysis Of Sonic Anemometer Observations In Low Wind Speed Conditions

Anfossi, D.; Oettl, Dietmar; Degrazia, Gervásio Annes; Goulart, A.

doi:10.1007/s10546-004-1984-4

Cited by 169 publications

(213 citation statements)

References 42 publications

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“…In general, the horizontal kinetic energy for submeso flow is poorly related to other local parameters such as wind speed and stability, as also found by Anfossi et al (2005) and Vickers and Mahrt (2007). While the kinetic energy may depend on wind speed for a specific scale range and network, no general behaviour could be found.…”

Section: Dependence On Time Scalementioning

confidence: 82%

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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Section: Dependence On Time Scalementioning

confidence: 82%

Characteristics of Submeso Winds in the Stable Boundary Layer

Mahrt

2008

Boundary-Layer Meteorol

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“…not only in urban conditions. We recall that Anfossi et al (2005) observed that there is not a general consensus in the literature on how to define low wind speeds. This definition is based on a limiting wind speed that ranges from 0.5 to 2.0 m s −1 and they suggested 1.5 m s…”

Section: Eulerian Autocorrelation Functionsmentioning

confidence: 97%

Low‐frequency processes and turbulence structure in a perturbed boundary layer

Mortarini

Ferrero

Falabino

et al. 2012

Quart J Royal Meteoro Soc

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An analysis of the turbulence structure in a perturbed boundary layer and in low-wind regimes is presented. The study is based on 15 months of continuous wind and turbulence measurements gathered, within the framework of the Urban Turbulence Project, at three levels (5, 9 and 25 m) on a mast located in the outskirts of the city of Turin (Italy). The aim of the work is to investigate low-frequency processes in a perturbed boundary-layer. In fact, the urban canopy and the heat island, together with frequent low-wind conditions, interact with and modify the turbulence structure. In order to investigate this modification, the velocity Eulerian autocorrelation functions together with both the Eulerian and Lagrangian timescales are shown and compared with the classical theory. The comparisons show that in low-wind cases the velocity autocorrelation functions are not simply exponential but present an oscillating behaviour. A method of normalization is proposed together with an analysis on the applicability of this function. The estimated Lagrangian timescales are compared with two widely used parametrizations. It is found that the presence of the urban fabric influences the turbulence time-scales and suggests the development of new parametrizations. Finally, higher-order statistics are evaluated and the relationship between higher-order and lower-order moments are analysed, pointing out the effects due to the urban environment.

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“…Anfossi et al [1] and Vickers and Mahrt [21] found that the kinetic energy of the mesoscale motions based on time variation did not depend significantly on wind speed or stability. However, information on time variation cannot be used to infer spatial variation.…”

Section: Dependence On Scale and Ambient Conditionsmentioning

confidence: 98%

Horizontal diffusion by submeso motions in the stable boundary layer

Mahrt

Mills

2009

Environ Fluid Mech

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Four networks of wind data are used to construct the first systematic estimates of the horizontal diffusivity from observations of submeso motions on scales often unresolved in numerical models. Currently, the horizontal diffusivity in numerical models is specified mainly for numerical reasons without observational support. The data analysis in this study emphasizes the stable boundary layer although results are briefly presented for the unstable boundary layer. The horizontal diffusivity is estimated from the horizontal gradient and the observed flux. Horizontal gradients of scalars are generally difficult to directly estimate from observations with sufficient accuracy for much of the data. As an alternative, simulated particles with conservative properties are introduced into the observed wind field in order to estimate the horizontal diffusivity for submeso motions. The sensitivity of the horizontal diffusivity to details of the method is examined. The horizontal diffusivity increases with the range of time and space scales that are included in the evaluation. The horizontal diffusivity is much larger with significant topography and may increase with wind speed, depending on the site location. The coarse station spacing or the small domain size is found to be a major limitation to the analysis.

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An Analysis Of Sonic Anemometer Observations In Low Wind Speed Conditions

Cited by 169 publications

References 42 publications

Characteristics of Submeso Winds in the Stable Boundary Layer

Characteristics of Submeso Winds in the Stable Boundary Layer

Low‐frequency processes and turbulence structure in a perturbed boundary layer

Horizontal diffusion by submeso motions in the stable boundary layer

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