Influence of Obstacles on the Aerodynamic Roughness of the Netherlands

Jong, J.J.M. de; Vries, A.C de; Klaassen, Wim

doi:10.1023/a:1001888629613

Cited by 8 publications

(4 citation statements)

References 22 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…[, Figures 20 and A1] on the basis of large‐eddy simulations (LES). From all this, it would appear that while the measurements at 32 m provide a better estimate of regional conditions than those at 12 m and definitely than those at 2 m, the blending height of the measurements at the Changwu station is likely higher than 32 m. Note that some studies, albeit in flat terrain, have indicated that the effect of the choice of the blending height in roughness estimations is relatively small [e.g., Bottema et al ., ; De Jong et al ., ], and thus perhaps negligible for practical purposes. This would suggest that the estimate of

z_{0} = 0.5 m

by Li et al .…”

Section: Resultsmentioning

confidence: 99%

Nonlinear advection‐aridity method for landscape evaporation and its application during the growing season in the southern Loess Plateau of the Yellow River basin

Brutsaert

Takahashi

et al. 2017

Water Resources Research

View full text Add to dashboard Cite

The advection‐aridity approach to estimate actual evaporation from natural land surfaces is one of the better known implementations of Bouchet's complementary principle. Detailed measurements at 2, 12, and 32 m above the ground surface during the growing seasons of 2004–2007 allowed validation of a generalized nonlinear form of this approach above the highly variable terrain in Changwu County in the southern Loess Plateau of the Yellow River basin in China. The obtained values of the parameters were found to lie well within the ranges to be expected on physical grounds or from previous measurements by different experimental means; calibration on the basis of any one year of data allowed predictions within roughly 5% on average. Relative to the corresponding observed turbulent vapor fluxes, the evaporation rates calculated with measurements at the highest level of 32 m displayed the least scatter but only slightly less than those calculated with measurements at the lower level of 12 m; however, those based on measurements at the lowest level of 2 m displayed considerably more scatter than those derived at the two higher levels. This is consistent with the existence of a blending height at higher elevations above the ground, where the effects of surface variability tend to fade away.

show abstract

z_{0} = 0.5 m

by Li et al .…”

Section: Resultsmentioning

confidence: 99%

Nonlinear advection‐aridity method for landscape evaporation and its application during the growing season in the southern Loess Plateau of the Yellow River basin

Brutsaert

Takahashi

et al. 2017

Water Resources Research

View full text Add to dashboard Cite

show abstract

“…yielding a roughness length of z 0 ≈ 0.55 m, which is representative of the site [20]. Furthermore, a spectral tensor Φ(κ; L, α 2/3 , Γ) according to [21], was set up with L ≈ 25 m, α 2/3 ≈ 0.16 m 4/3 /s 2 , and Γ ≈ 3.…”

Section: Resultsmentioning

confidence: 99%

Assessing the Severity of Wind Gusts with Lidar

2016

View full text Add to dashboard Cite

Abstract:Lidars have gained a lot of popularity in the field of wind energy, partly because of their potential to be used for wind turbine control. By scanning the oncoming wind field, any threats such as gusts can be detected early and high loads can be avoided by taking preventive actions. Unfortunately, lidars suffer from some inherent weaknesses that hinder measuring gusts; e.g., the averaging of high-frequency fluctuations and only measuring along the line of sight). This paper proposes a method to construct a useful signal from a lidar by fitting a homogeneous Gaussian velocity field to a set of scattered measurements. The output signal, an along-wind force, acts as a measure for the damaging potential of an oncoming gust and is shown to agree with the rotor-effective wind speed (a similar control input, but derived directly from the wind turbine's shaft torque). Low data availability and the disadvantage of not knowing the velocity between the lidar beams is translated into uncertainty and integrated in the output signal. This allows a designer to establish a control strategy based on risk, with the ultimate goal to reduce the extreme loads during operation.

show abstract

“…For instance, the roughness of a patchy landscape is not always a weighed average of the elements, but might even exceed the roughness of the roughest element (Bottema et al, 1998). The large roughness is attributed to additional momentum absorption at changes in vegetation height, in particular forest edges and tree lines (De Jong et al, 1999).…”

Section: Introductionmentioning

confidence: 99%

Increased heat fluxes near a forest edge

Klaassen

Breugel²,

Moors

et al. 2002

Theoretical and Applied Climatology

View full text Add to dashboard Cite

Observations of sensible and latent heat¯ux above forest downwind of a forest edge show these¯uxes to be larger than the available energy over the forest. The enhancement averages to 56 W m À 2 , or 16% of the net radiation, at fetches less than 400 m, equivalent to fetch to height ratios less than 15. The enhancement of turbulent energy¯uxes is explained by advection and increases with the difference in temperature and humidity of the air over the upwind area as compared to the forest. The relatively high temperature and humidity of the upwind air are not caused by high surface heat¯uxes, but are explained by the relatively low aerodynamic roughness of the upwind surface. Although the heat uxes over forest are enhanced, the momentum¯uxes are almost adjusted to the underlying forest. The different behaviour of heat and momentum¯uxes is explained by absorption of momentum by pressure gradients near the forest edge. It is concluded that fetch requirements to obtain accurate surface¯uxes from atmospheric observations need to be more stringent for scalar¯uxes as compared to momen-tum¯uxes. 232W. Klaassen et al.Increased heat¯uxes near a forest edge 241

show abstract

Influence of Obstacles on the Aerodynamic Roughness of the Netherlands

Cited by 8 publications

References 22 publications

Nonlinear advection‐aridity method for landscape evaporation and its application during the growing season in the southern Loess Plateau of the Yellow River basin

Nonlinear advection‐aridity method for landscape evaporation and its application during the growing season in the southern Loess Plateau of the Yellow River basin

Assessing the Severity of Wind Gusts with Lidar

Increased heat fluxes near a forest edge

Contact Info

Product

Resources

About