Turbulent Structure and Local Similarity in the Tower Layer Over the Nanjing Area

Yumao, Xu; Zhou, Chaofu; Li, Zhongkai; Zhang, Wei

doi:10.1023/a:1000111431036

Cited by 25 publications

(6 citation statements)

References 18 publications

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“…The influence of z / h or σ h / h (wakes) in different sectors does not seem to affect the scatter of data, which is consistent with what has been concluded by Rotach () and Roth () ( C 1 = − 3) and Yumao et al () ( C 1 = − 1.86). Hanna et al () found that the range − 2 to − 5 is common for street canyons in near‐neutral conditions, this study addresses moderately to very unstable conditions.…”

Section: Resultssupporting

confidence: 90%

“…Interestingly, lower C 1 values are usually obtained when the stability range measured falls within this category. This trend is also evident in the studies by Yumao et al (1997) and Al-Jiboori et al (2002), albeit a slightly higher value of −2.23, although Quan and Hu (2009) obtained a value of −1.5 despite both experimental setups being the same.…”

Section: Spectral Analysis Of Wsupporting

confidence: 63%

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Turbulence variances in the convective urban roughness sublayer: an application of similarity theory using local scales

Yusup¹,

Lim²

2012

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Similarity theory using local scales was applied to the normalized standard deviation of the vertical wind component, w, and potential temperature, θ , σ w /u * loc and σ θ /θ * loc , where u * loc and θ * loc are the friction velocity and temperature and 'loc' refers to variables that are locally measured. These data were obtained in a tropical city under convective atmospheric conditions within the roughness sublayer. The following parameters were assessed based on the upwind characteristics of the site, denoted as 'sectors': the non-dimensional height, z/ h (1.16 and 1.20), and the non-dimensional vertical heterogeneity, σ h /h (0.56 and 0.32). The results obey a semi-empirical relation of the formwhere z is the effective measurement height, L loc is the local Obukhov length). The resultant extrapolated near-neutral constants depend on σ h /h: (σ w /u * loc ) neutral = 1.04 and 1.27 for σ h /h = 0.56 and 0.32, in the range −0.01 > ζ loc > −20. Spectral analysis of w reveals a separation of the spectral power at low nondimensional frequencies (f < 0.03) with increasing deviation as the atmosphere approaches neutral conditions, ζ loc > −0.6 for σ h /h = 0.32. The term σ θ /u * loc follows the form (−ζ loc )− 1/3 with constants of (σ θ /θ * loc ) neutral = −1.31 and −1.34 for the two sectors, thus being independent of both σ h /h and z/ h. These findings show that similarity theory using local scales is applicable for determining σ w and σ θ in the convective roughness sublayer but depends on the vertical heterogeneity of the upwind sectors for σ w , which only affects the near-neutral σ w /u * loc constants.

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Section: Resultssupporting

confidence: 90%

Section: Spectral Analysis Of Wsupporting

confidence: 63%

Turbulence variances in the convective urban roughness sublayer: an application of similarity theory using local scales

Yusup¹,

Lim²

2012

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“…Local scaling has been more successful in these cases (Holtslag and Nieuwstadt 1986, Holtslag and De Bruin 1988, Beljaars and Holtslag 1991, Vickers and Mahrt 1999. Local scaling can also be applied to φ m in unstable conditions at homogeneous sites (Sorbjan 1986, Yumao et al 1997. Figures 5b and 5d, however, show that local scaling of φ m also applies above the surface layer, in the disturbed ABL at Cabauw.…”

Section: Flux-profile Relationshipsmentioning

confidence: 99%

“…Sorbjan (1986) tested local scaling for the dimensionless wind speed (φ m ) and temperature gradient (φ h ) using a small dataset from Minnesota. Yumao et al (1997) tested local scaling for φ m and φ h for an urban and a rural site near Nanjing. Recently, Steeneveld et al (2005) tested local scaling at Cabauw for temperature and humidity profiles.…”

Section: Introductionmentioning

confidence: 99%

Wind profiles, momentum fluxes and roughness lengths at Cabauw revisited

Verkaik

Holtslag

2006

Boundary-Layer Meteorol

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We describe the results of an experiment focusing on wind speed and momentum fluxes in the atmospheric boundary layer up to 200 m. The measurements were conducted in 1996 at the Cabauw site in the Netherlands. Momentum fluxes are measured using the K-Gill Propeller Vane. Estimates of the roughness length are derived using various techniques from the wind speed and flux measurements, and the observed differences are explained by considering the source area of the meteorological parameters. A clear rough-to-smooth transition is found in the wind speed profiles at Cabauw. The internal boundary layer reaches the lowest k-vane (20 m) only in the south-west direction where the obstacle-free fetch is about 2 km. The internal boundary layer is also reflected in the roughness lengths derived from the wind speed profiles. The lower part of the profile (<40 m) is not in equilibrium and no reliable roughness analysis can be given. The upper part of the profile can be linked to a large-scale roughness length. Roughness lengths derived from the horizontal wind speed variance and gustiness have large footprints and therefore represent a large-scale average roughness. The drag coefficient is more locally determined but still represents a large-scale roughness length when it is measured above the local internal boundary layer. The roughness length at inhomogeneous sites can therefore be determined best from drag coefficient measurements just above the local internal boundary layers directly, or indirectly from horizontal wind speed variance or gustiness. In addition, the momentum and heat fluxes along the tower are analysed and these show significant variation with height related to stability and possibly surface heterogeneity. It appears that the dimensionless wind speed gradients scale well with local fluxes for the variety of conditions considered, including the unstable cases.

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“…Equation (9) became a commonly accepted expression for the non-dimensional standard deviation σ w /u * for negative values of ζ = (z m − d) /L, and is tested in the present work also for the horizontal components (cf. Yumao et al, 1997;Zhang et al, 2001;Al-Jiboori et al, 2002), and extended to cover positive values of ζ . Under non-neutral conditions, various expressions have been proposed to represent the dependence of σ i on stability; an overview is provided in Table II.…”

Section: Similarity Functionsmentioning

confidence: 99%

Analysis of second‐order moments in surface layer turbulence in an Alpine valley

Franceschi

Zardi

Tagliazucca

et al. 2009

Quart J Royal Meteoro Soc

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ABSTRACT:The paper presents the analysis of field measurements in the atmospheric surface layer over the floor of the Adige Valley, near the city of Bolzano in the Alps. Turbulence quantities, such as drag coefficient, displacement height and roughness length, appear similar to those reported in the literature concerning surface-layer turbulence over flat uniform terrain. The analysis of the non-dimensional standard deviations (σ u , σ v , σ w ) legitimates the adoption, for all the wind components, of the same Monin-Obukhov similarity relationship in the form σ i /u * = α i (1 + β i |ζ |) 1/3 , originally proposed only for flat uniform terrain under steady state conditions, and the extension of this expression to the case of winds over a valley floor in slowly varying situations. The coefficients α i are very similar for along-valley and cross-valley winds, as are the β i ones. Moreover the α u values are only slightly larger than the α v , contrary to what is reported in the literature. Conversely, σ θ /θ * shows distinctly different behaviour in the stable and unstable regimes. In particular, in the latter case a large scatter in the data is observed. However, since the most scattered data turn out to occur in transition periods (i.e. sunrise and sunset), after a specific data selection the best-fit parameters are more accurately estimated. In addition, emphasis is laid on the relevance of an appropriate formulation and use of a suitable recursive filter to separate the low-frequency unsteadiness of the mean flow from the turbulence signal.

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Turbulent Structure and Local Similarity in the Tower Layer Over the Nanjing Area

Cited by 25 publications

References 18 publications

Turbulence variances in the convective urban roughness sublayer: an application of similarity theory using local scales

Turbulence variances in the convective urban roughness sublayer: an application of similarity theory using local scales

Wind profiles, momentum fluxes and roughness lengths at Cabauw revisited

Analysis of second‐order moments in surface layer turbulence in an Alpine valley

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