Influence of stability on the flux-profile relationships for wind speed, &amp;lt;i&amp;gt;Φ&amp;lt;/i&amp;gt;&amp;lt;sub&amp;gt;m&amp;lt;/sub&amp;gt;, and temperature, &amp;lt;i&amp;gt;Φ&amp;lt;/i&amp;gt;&amp;lt;sub&amp;gt;h&amp;lt;/sub&amp;gt;, for the stable atmospheric boundary layer

Yagüe, Carlos; Viana, Samuel; Maqueda, Gregorio; Redondo, J. M.

doi:10.5194/npg-13-185-2006

Cited by 68 publications

(66 citation statements)

References 63 publications

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“…However, with strongly stratified flow, the vertical mixing of scalars by the turbulence may become extremely weak e.g., [25] while the horizontal transport by submeso motions can be rather large, as found in this study. The vertical flux by the submeso motions is difficult to estimate due to large sampling errors and difficulties measuring very weak vertical motions, and is outside the scope of this study.…”

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confidence: 60%

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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confidence: 60%

Horizontal diffusion by submeso motions in the stable boundary layer

Mahrt

Mills

2009

Environ Fluid Mech

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“…Wyngaard and Coté (1971) named this detached turbulence as z-less stratification. Previous studies reported that turbulence structure showed the properties of z-less stratification up to z/L ∼ 1 in general (e.g., Basu et al, 2006;Yagüe et al, 2006;Mahrt, 2008). That is, as z/L increases, σ u /u * , σ w /u * , σ T /T * are nearly constant if z-less turbulence is valid (Nieuwstadt, 1984;Dias et al, 1995;Grachev et al, 2005;Basu et al, 2006;Hong , 2010).…”

Section: Resultsmentioning

confidence: 97%

Surface layer similarity in the nocturnal boundary layer: the application of Hilbert-Huang transform

et al. 2010

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Abstract. Turbulence statistics such as flux-variance relationship are critical information in measuring and modeling ecosystem exchanges of carbon, water, energy, and momentum at the biosphere-atmosphere interface. Using a recently proposed mathematical technique, the Hilbert-Huang transform (HHT), this study highlights its possibility to quantify impacts of non-turbulent flows on turbulence statistics in the stable surface layer. The HHT is suitable for the analysis of non-stationary and intermittent data and thus very useful for better understanding the interplay of the surface layer similarity with complex nocturnal environment. Our analysis showed that the HHT can successfully sift non-turbulent components and be used as a tool to estimate the relationships between turbulence statistics and atmospheric stability in complex environments such as nocturnal stable boundary layer.

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“…This Fig. 7 shows that there are certain atmospheric situations (coinciding with those more stably-stratified) in which the model is unable to represent their corresponding scaling exponents (for example those situations present in the 14-15 night, where very strong stable stratification was observed - Yagüe et al, 2006 -), due to the fact that the scaling exponents are too high (for orders higher than 3) or too low (for orders lower than 3) for the model. Moreover, the minimum values (for orders lower than 3) or maximum values (for orders higher than 3) of the scaling exponents that the model is able to reproduce are very similar for different q values (see Fig.…”

Section: Data and Empirical Resultsmentioning

confidence: 99%

Application of a GOY model to atmospheric boundary layer data

Vindel

Yagüe

2009

Nonlin. Processes Geophys.

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Abstract. This article analyzes the possibility of applying a GOY theoretical model to atmospheric boundary layer data. Bearing this in mind, relative scaling exponents of velocity structure functions are used to compare the model with the data under study. In the model, these exponents are set based on two parameters (q and δ), which are appropriate to define the model that better features a certain atmospheric state.From these scaling exponents, the gap between 2-D and 3-D turbulence is observed in the model, depending on the fact that δ is higher or lower than unity, respectively. Atmospheric data corresponding to very different states of stratification stability have been analyzed. For convective or near-neutral situations (usually associated to 3-D turbulence), it is possible to find parameters q and δ to define a model that fits the measured data. More stable situations can be featured by GOY models with higher values of δ. However, it is clear that it is impossible to represent nocturnal situations of strong stable stratification (with a more similar behaviour to 2-D) with this type of model.

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Influence of stability on the flux-profile relationships for wind speed, <i>Φ</i><sub>m</sub>, and temperature, <i>Φ</i><sub>h</sub>, for the stable atmospheric boundary layer

Cited by 68 publications

References 63 publications

Horizontal diffusion by submeso motions in the stable boundary layer

Horizontal diffusion by submeso motions in the stable boundary layer

Surface layer similarity in the nocturnal boundary layer: the application of Hilbert-Huang transform

Application of a GOY model to atmospheric boundary layer data

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