Nocturnal Low-Level Jet Characteristics Over Kansas During Cases-99

Banta, Robert M.; Newsom, Rob; Lundquist, Julie K.; Pichugina, Yelena L.; Coulter, R. L.; Mahrt, L.

doi:10.1023/a:1019992330866

Cited by 341 publications

(293 citation statements)

References 30 publications

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“…Blackadar, 1957;Hoecker, 1963;Bonner, 1968;Parish et al, 1988;Mitchell et al, 1995;Stensrud, 1996;Zhong et al, 1996;Whiteman et al, 1997;Banta et al, 2002;Song et al, 2005;Banta, 2008;Walters et al, 2008) but also observed at many other locations worldwide (see references in Sládkovič and Kanter, 1977;Stensrud, 1996;Beyrich et al, 1997). The jet typically begins to develop around sunset, under dry cloud-free conditions conducive to strong radiational cooling, reaches a peak intensity in the early morning hours, and then decays shortly after dawn, with the onset of daytime convective mixing.…”

Section: Introductionmentioning

confidence: 85%

“…7 and 8 of Banta, 2008). An analysis of high-resolution Doppler lidar data from the CASES-99 field campaign in Kansas revealed large variability in the temporal behaviour of the height of the wind maximum (Banta et al, 2002). Since a descending wind maximum was a more robust feature of the numerical simulations over flat terrain without an imposed thermal wind than of the observations (which were frequently over gentle, but generally non-zero, terrain slopes, and subject to synoptic influences), we speculate that the tendency of the height of some observed wind maxima to increase with time may be a consequence of synoptic-or terrain-associated baroclinicity.…”

Section: Analytical Solutionmentioning

confidence: 99%

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Analytical description of a nocturnal low‐level jet

Shapiro

Fedorovich

2010

Quart J Royal Meteoro Soc

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Section: Introductionmentioning

confidence: 85%

Section: Analytical Solutionmentioning

confidence: 99%

Analytical description of a nocturnal low‐level jet

Shapiro

Fedorovich

2010

Quart J Royal Meteoro Soc

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“…This is mentioned here because references to experiments in such sites are made later in the thesis. Banta et al (2002) studied the characteristics of LLJs over Kansas. Most of the jet maxima they measured occurred below 140m which is within the height range swept by the rotor of a modern multi-MW wind turbine.…”

Section: Low Level Jetmentioning

confidence: 99%

Accounting for the speed shear in wind turbine power performance measurement

Wagner¹,

Courtney²,

Gottschall³

et al. 2011

Wind Energy

147

109

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Abstract:The power curve of a wind turbine is the primary characteristic of the machine as it is the basis of the warranty for it power production. The current IEC standard for power performance measurement only requires the measurement of the wind speed at hub height and the air density to characterise the wind field in front of the turbine. However, with the growing size of the turbine rotors during the last years, the effect of the variations of the wind speed within the swept rotor area, and therefore of the power output, cannot be ignored any longer. Primary effects on the power performance are from the vertical wind shear and the turbulence intensity. The work presented in this thesis consists of the description and the investigation of a simple method to account for the wind speed shear in the power performance measurement. Ignoring this effect was shown to result in a power curve dependant on the shear condition, therefore on the season and the site. It was then proposed to use an equivalent wind speed accounting for the whole speed profile in front of the turbine. The method was first tested with aerodynamic simulations of a multi-megawatt wind turbine which demonstrated the decrease of the scatter in the power curve. A power curve defined in terms of this equivalent wind speed would be less dependant on the shear than the standard power curve. The equivalent wind speed method was then experimentally validated with lidar measurements. Two equivalent wind speed definitions were considered both resulting in the reduction of the scatter in the power curve. As a lidar wind profiler can measure the wind speed at several heights within the rotor span, the wind speed profile is described with more accuracy than with the power law model. The equivalent wind speed derived from measurements, including at least one measurement above hub height, resulted in a smaller scatter in the power curve than the equivalent wind speed derived from profiles extrapolated from measurements at hub height and below only. It is well established that the turbulence intensity also influences the power performance of a wind turbine. Two ways of accounting for the turbulence were tested with the experimental data: an adaptation of the equivalent wind speed so that it also accounts for the turbulence intensity and the combination of the equivalent wind speed accounting for the wind shear only with the turbulence normalising method for turbulence intensity suggested by Albers. The second method was found to be more suitable for normalising the power curve for the turbulence intensity. Using the equivalent wind speed accounting for the wind shear in the power performance measurement was shown to result in a more repeatable power curve than the standard power curve and hence, in a better annual energy production estimation. Furthermore, the decrease of the scatter in the power curve corresponds to a decrease of the category A uncertainty in power, resulting in a smaller uncertainty in estimated AEP.The thesis is submitted to the Danish Tec...

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“…Bonner 1968;Garratt 1982;Brook 1985;Kraus et al 1985;Parish et al 1988;Lettau 1990;Sjostedt et al 1990;Beyrich 1994;Mitchell et al 1995;Whiteman et al 1997;Banta et al 2002;Song et al 2005;Baas et al 2009;Karipot et al 2009), however, up to now there is no commonly accepted criterion for identifying the LLJ, since such flows can be of different origins (such as breezes, mountain-valley circulation, synoptic baroclinity, atmospheric fronts etc.) and behave differently.…”

mentioning

confidence: 99%

“…The LLJs were studied remotely with Doppler sodars (Coulter 1981;Beyrich 1994;Emeis et al 2007;Kallistratova et al 2009), radars (Zhong et al 1996;Song et al 2005), and lidars (Banta et al 2002;Wang et al 2007;Banta 2008).…”

mentioning

confidence: 99%

Low-Level Jets in the Moscow Region in Summer and Winter Observed with a Sodar Network

Kallistratova

Kouznetsov

2011

Boundary-Layer Meteorol

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We evaluate the statistical properties of low-level jets (LLJs) observed by means of a network of Doppler sodars in the Moscow region, Russia. Continuous long-term measurements of the echo-signal intensity and wind-velocity profiles were carried out in July 2005 and in 2008-2010 synchronously in the centre of Moscow and at a rural site. The summertime nocturnal LLJs have a very clear diurnal cycle and exhibit features predicted by the Blackadar mechanism. In contrast, the long-lasting wintertime jets do not have any clear diurnal variability. The urban environment strongly influences LLJs in both seasons: above the city LLJs are higher, weaker and observed more rarely than at the rural site. In very cold periods (air temperature below −8 • C) no LLJs were observed over the city, instead convection emerged in the urban boundary layer. The results are based on observations made in

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Nocturnal Low-Level Jet Characteristics Over Kansas During Cases-99

Cited by 341 publications

References 30 publications

Analytical description of a nocturnal low‐level jet

Analytical description of a nocturnal low‐level jet

Accounting for the speed shear in wind turbine power performance measurement

Low-Level Jets in the Moscow Region in Summer and Winter Observed with a Sodar Network

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