Examination of the empirical flux-profile models in the atmospheric surface boundary layer

Viswanadham, Y.

doi:10.1007/bf00128056

Cited by 8 publications

(4 citation statements)

References 31 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…3, conspicuous differences among the functions are implied in the curves. When Ri is less than 0.1, D M seems to linearly decrease with Ri, similar with the linear decline found with linear Kansas type functions [35,36]. Interestingly, the curves deviate from the linearity even before ζ reaches 1.…”

Section: Critical Comments For Future Improvementsupporting

confidence: 72%

“…An attempt is made to check the Ri-D M curves with measurements in the Huaihe River Basin Experiment (HUBEX) in 1999. Earlier works, such as Viswanadham [35,36], adopted the formulae to estimate D M , as proposed by Lettau [40]. Realizing that they are unsuitable for our data, Appendix 2 explains our application of the Deacon number technique.…”

Section: Critical Comments For Future Improvementmentioning

confidence: 97%

“…Pr approaches the molecular Prandtl number in laminar flow limit, ∼ 0.71. Another feasible method to examine the stability functions is known as the Deacon number technique [34][35][36]. In simple terms, the relationship between Ri and D M or D H is first derived with theoretical analysis.…”

Section: Profile Metrics and Deacon Number Techniquementioning

confidence: 99%

See 2 more Smart Citations

A performance comparison between nonlinear similarity functions in bulk parameterization for very stable conditions

Guo

Zhang

2007

Environ Fluid Mech

View full text Add to dashboard Cite

Three sets of nonlinear similarity functions for strong stability are selected to compare their performance in bulk parameterization. To uncover their advantages and disadvantages, theoretical and measurement analyses are made with four profile metrics and the Deacon number technique. Main disadvantages include the negligence of the different transfer efficiency between momentum and heat, the flux cutoff due to the upper limit in gradient Richardson number (Ri) and the ignorance of limited stability range where the dimensionless gradient functions (ϕ M and ϕ H ) approach constants. Accordingly, three suggestions are made for future improvement. First, the functions for wind velocity and potential temperature should have the same function form, but with different coefficients. Second, ϕ M and ϕ H should approach constants only within a certain stability range. Third, the limit value in Ri should be avoided to widen their applicability in flux modeling. Furthermore, quantitative comparisons in transfer coefficients for moment and sensible heat (C D and C H ) are made among the similarity functions in the bulk Richardson number (Ri B ) range 0 < Ri B < 1. Generally, significant discrepancy is found, which may approach a factor of two and three at large Ri B in C D and C H , respectively. Finally, a new recommendation is made to one of the three sets, mainly because of its ability to predict C D and C H that decrease rather slowly in very stable conditions.

show abstract

Section: Critical Comments For Future Improvementsupporting

confidence: 72%

Section: Critical Comments For Future Improvementmentioning

confidence: 97%

See 1 more Smart Citation

A performance comparison between nonlinear similarity functions in bulk parameterization for very stable conditions

Guo

Zhang

2007

Environ Fluid Mech

View full text Add to dashboard Cite

show abstract

“…For discussions of the values of the coefficients used, see Businger et al (1971), Yaglom (1977), Viswanadham (1982), and Wier and Riimer (1987). In a preliminary version of this paper, we had used the earlier proposals by Businger ef al.…”

Section: Appendix: Monin-obukhov Relationshipsmentioning

confidence: 99%

Minimum friction velocity and heat transfer in the rough surface layer of a convective boundary layer

Schumann¹

1988

Boundary-Layer Meteorol

View full text Add to dashboard Cite

A simple model is deduced for the surface layer of a convective boundary layer for zero mean wind velocity over homogeneous rough ground. The model assumes large-scale convective circulation driven by surface heat flux with a flow pattern as it would be obtained by conditional ensemble averages. The surface layer is defined here such that in this layer horizontal motions dominate relative to vertical components. The model is derived from momentum and heat balances for the surface layer together with closures based on the Monin-Obukhov theory. The motion in the surface layer is driven by horizontal gradients of hydrostatic pressure. The balances account for turbulent fluxes at the surface and fluxes by convective motions to the mixed layer. The latter are the dominant ones. The model contains effectively two empirical coefficients which are determined such that the model's predictions agree with previous experimental results for the horizontal turbulent velocity fluctuations and the temperature fluctuations. The model quantitatively predicts the decrease of the minimum friction velocity and the increase of the temperature difference between the mixed layer and the ground with increasing values of the boundary layer/roughness height ratio. The heat transfer relationship can be expressed in terms of the common Nusselt and Rayleigh numbers, Nu and Ra, as Nu -Ra'/*. Previous results of the form Nu -Ra'j3 are shown to be restricted to Rayleighnumbers less than a certain value which depends on the boundary layer/roughness height ratio.

show abstract

16.4 The surface layer

Etling¹

Climatology. Part 1

View full text Add to dashboard Cite

Examination of the empirical flux-profile models in the atmospheric surface boundary layer

Cited by 8 publications

References 31 publications

A performance comparison between nonlinear similarity functions in bulk parameterization for very stable conditions

A performance comparison between nonlinear similarity functions in bulk parameterization for very stable conditions

Minimum friction velocity and heat transfer in the rough surface layer of a convective boundary layer

16.4 The surface layer

Contact Info

Product

Resources

About